source stringlengths 3 92 | c stringlengths 26 2.25M |
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GB_unop__isfinite_bool_fp32.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_atomics.h"
#include "GB_unop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB (_unop_apply__isfinite_bool_fp32)
// op(A') function: GB (_unop_tran__isfinite_bool_fp32)
// C type: bool
// A type: float
// cast: float cij = (aij)
// unaryop: cij = isfinite (aij)
#define GB_ATYPE \
float
#define GB_CTYPE \
bool
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
float aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = isfinite (x) ;
// casting
#define GB_CAST(z, aij) \
float z = (aij) ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
float aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
float z = (aij) ; \
Cx [pC] = isfinite (z) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_ISFINITE || GxB_NO_BOOL || GxB_NO_FP32)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_apply__isfinite_bool_fp32)
(
bool *Cx, // Cx and Ax may be aliased
const float *Ax,
const int8_t *restrict Ab, // A->b if A is bitmap
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
if (Ab == NULL)
{
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
float aij = Ax [p] ;
float z = (aij) ;
Cx [p] = isfinite (z) ;
}
}
else
{
// bitmap case, no transpose; A->b already memcpy'd into C->b
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!Ab [p]) continue ;
float aij = Ax [p] ;
float z = (aij) ;
Cx [p] = isfinite (z) ;
}
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_tran__isfinite_bool_fp32)
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
fox_floats_timer_caching_omp_fileIO_benchmark.c | /* fox_floats_timer_caching_omp_fileIO_benchmark.c -- uses Fox's algorithm to multiply two square matrices
*
* Implementation of parallel matrix multiplication:
* LaTeX: $C_{i,j} = \sum_{k} A_{i,k}B_{k,j}$
*
* Input:
* Input Matrix file name: A.dat, B.dat
*
* Output:
* Output Matrix file name: C.dat
* Output Sub-matrices file name: SubMatrices.dat
*
* Notes:
* 1. Assumes the number of processes is a perfect square
* 2. The array member of the matrices is statically allocated
*
* See Chap 7, pp. 113 & ff and pp. 125 & ff in PPMPI
*/
/* Compiler command:
* mpiicc -O3 -qopenmp -qopt-report-phase=vec -qopt-report=3 fox_floats_timer_caching_omp_fileIO_benchmark.c
* -o fox_floats_timer_caching_omp_fileIO_benchmark
*
* Run command:
* mpirun -n -4 ./fox_floats_timer_caching_omp
*/
/* Head files */
#include <stdio.h>
#include <math.h>
#include <stdlib.h>
#include <mpi.h>
#include <omp.h>
// define problem scale, matrix row/col size
#define PROBLEM_SCALE 128
// define whether or not Print Matices in the Command Line
#define PRINT_A 0
#define PRINT_B 0
#define PRINT_C 0
#define PRINT_LOCAL_A 0
#define PRINT_LOCAL_B 0
#define PRINT_LOCAL_C 0
// define float precision, 4 byte single-precision float or 8 byte double-precision float
#define FLOAT double
#define FLOAT_MPI MPI_DOUBLE
// Define threads speed-up affnity in the computing
#define NUM_THREADS 16
// Define threads affinity "scatter" or "compact"
#define AFFINITY "KMP_AFFINITY = compact"
/* Type define structure of process grid */
typedef struct {
int p; /* Total number of processes */
MPI_Comm comm; /* Communicator for entire grid */
MPI_Comm row_comm; /* Communicator for my row */
MPI_Comm col_comm; /* Communicator for my col */
int q; /* Order of grid */
int my_row; /* My row number */
int my_col; /* My column number */
int my_rank; /* My rank in the grid comm */
} GRID_INFO_T;
/* Type define structure of local matrix */
#define MAX 2097152 // Maximum number of elements in the array that store the local matrix (2^21)
typedef struct {
int n_bar;
#define Order(A) ((A)->n_bar) // defination with parameters
FLOAT entries[MAX];
#define Entry(A,i,j) (*(((A)->entries) + ((A)->n_bar)*(i) + (j))) // defination with parameters, Array dereference
} LOCAL_MATRIX_T;
/* Function Declarations */
LOCAL_MATRIX_T* Local_matrix_allocate(int n_bar);
void Free_local_matrix(LOCAL_MATRIX_T** local_A);
void Read_matrix_A(char* prompt, LOCAL_MATRIX_T* local_A,
GRID_INFO_T* grid, int n); // Read matrix A from a file
void Read_matrix_B(char* prompt, LOCAL_MATRIX_T* local_B, // for continuous memory access, local A(i,k)*B(k,j) = A(i,k)*B^{T}(j,k)
GRID_INFO_T* grid, int n); // Read matrix B from a file
void Print_matrix_A(char* title, LOCAL_MATRIX_T* local_A,
GRID_INFO_T* grid, int n); // Print matrix A in the command line
void Print_matrix_B(char* title, LOCAL_MATRIX_T* local_B, // Speical print function for local matrix B^{T}(j,k)
GRID_INFO_T* grid, int n); // Print matrix B in the command line
void Print_matrix_C(char* title, LOCAL_MATRIX_T* local_C,
GRID_INFO_T* grid, int n); // Print matrix C in the command line
void Set_to_zero(LOCAL_MATRIX_T* local_A);
void Local_matrix_multiply(LOCAL_MATRIX_T* local_A,
LOCAL_MATRIX_T* local_B, LOCAL_MATRIX_T* local_C);
void Build_matrix_type(LOCAL_MATRIX_T* local_A);
MPI_Datatype local_matrix_mpi_t;
LOCAL_MATRIX_T* temp_mat; // global LOCAL_MATRIX_T* type pointer
void Print_local_matrices_A(char* title, LOCAL_MATRIX_T* local_A,
GRID_INFO_T* grid);
void Print_local_matrices_B(char* title, LOCAL_MATRIX_T* local_B, // Speical print function for local matrix B^{T}(j,k)
GRID_INFO_T* grid);
void Print_local_matrices_C(char* title, LOCAL_MATRIX_T* local_B,
GRID_INFO_T* grid);
void Write_matrix_C(char* title, LOCAL_MATRIX_T* local_C,
GRID_INFO_T* grid, int n); // Write matrix multiplication to a file
void Write_local_matrices_A(char* title, LOCAL_MATRIX_T* local_A,
GRID_INFO_T* grid); // Write local matrix A to a file
void Write_local_matrices_B(char* title, LOCAL_MATRIX_T* local_B, // Speical print function for local matrix B^{T}(j,k)
GRID_INFO_T* grid); // Write local matrix B to a file
void Write_local_matrices_C(char* title, LOCAL_MATRIX_T* local_A,
GRID_INFO_T* grid); // Write local matrix C to a file
/*********************************************************/
main(int argc, char* argv[]) {
FILE *fp;
int p;
int my_rank;
GRID_INFO_T grid;
LOCAL_MATRIX_T* local_A;
LOCAL_MATRIX_T* local_B;
LOCAL_MATRIX_T* local_C;
int n;
int n_bar;
double timer_start;
double timer_end;
int content;
int i;
int j;
void Setup_grid(GRID_INFO_T* grid);
void Fox(int n, GRID_INFO_T* grid, LOCAL_MATRIX_T* local_A,
LOCAL_MATRIX_T* local_B, LOCAL_MATRIX_T* local_C);
// Matrix Generator
fp = fopen("A.dat", "w"); // Generate and print matrix A into a file
for (i = 0; i < PROBLEM_SCALE; i++) {
for (j = 0; j < PROBLEM_SCALE; j++)
if(i == j){
fprintf(fp,"%d ", 1);
}
else {
fprintf(fp,"%d ", 0);
}
fprintf(fp,"\n");
}
fclose(fp);
fp = fopen("B.dat", "w"); // Generate and print matrix B into a file
for (i = 0; i < PROBLEM_SCALE; i++){
for (j = 0; j < PROBLEM_SCALE; j++)
fprintf(fp,"%d ", (i*PROBLEM_SCALE)+j);
fprintf(fp, "\n");
}
fclose(fp);
// SPMD Mode start from here (Processess fork from here)
MPI_Init(&argc, &argv); // MPI initializing
MPI_Comm_rank(MPI_COMM_WORLD, &my_rank); // Get my process id in the MPI communicator
// Initial OpenMP Environment
omp_set_num_threads(NUM_THREADS);
kmp_set_defaults(AFFINITY);
Setup_grid(&grid); // Set up Processess grid
if (my_rank == 0) {
fp = fopen("A.dat","r");
n = 0;
while((content = fgetc(fp)) != EOF)
{
//printf("fgetc = %d\n", content);
if(content != 0x20 && content != 0x0A) n++;
}
fclose(fp);
n = (int) sqrt((double) n);
printf("We read the order of the matrices from A.dat is\n %d\n", n);
// while(fgetc(fp) != EOF) n++;
// printf("What's the order of the matrices?\n");
// scanf("%d", &n); // Overall Matrix's Order
}
MPI_Bcast(&n, 1, MPI_INT, 0, MPI_COMM_WORLD); // MPI broadcast the overall matrix's order
n_bar = n/grid.q; // \bar n is the local matrix's order
local_A = Local_matrix_allocate(n_bar); // Allocate local matrix A
Order(local_A) = n_bar; // Local matrix A's order
Read_matrix_A("Read A from A.dat", local_A, &grid, n); // Read local matrices A from process 0 by using stdin, and send them to each process (Procedure)
if (PRINT_A == 1)
Print_matrix_A("We read A =", local_A, &grid, n);// Print local matrices A from process 0 by using stdout, and send them to each process (Procedure)
local_B = Local_matrix_allocate(n_bar); // Allocate local matrix
Order(local_B) = n_bar; // Local matrix B's order
Read_matrix_B("Read B from B.dat", local_B, &grid, n); // Read local matrix B as it's local transpose from process 0 by using stdin, and send them to each process (Procedure)
if (PRINT_B == 1)
Print_matrix_B("We read B =", local_B, &grid, n);// Print local matrix B as it's local transpose from process 0 by using stdout, and send them to each process (Procedure)
Build_matrix_type(local_A); // Buid local_A's MPI matrix data type
temp_mat = Local_matrix_allocate(n_bar); // Allocate temporary matrix of order n $\time$ n
local_C = Local_matrix_allocate(n_bar); // Allocate matrix local_C
Order(local_C) = n_bar; // Set matrix local_C's order
MPI_Barrier(MPI_COMM_WORLD); // Set the MPI process barrier
timer_start = MPI_Wtime(); // Get the MPI wall time
Fox(n, &grid, local_A, local_B, local_C); // FOX parallel matrix multiplication Algorithm implement function
timer_end = MPI_Wtime(); // Get the MPI wall time
MPI_Barrier(MPI_COMM_WORLD); // Set the MPI process barrier
Write_matrix_C("Write C into the C.dat", local_C, &grid, n); // Print matrix local_C (parallel matrix multiplication result)
if (PRINT_C == 1)
Print_matrix_C("The product is", local_C, &grid, n); // Print matrix local_C (parallel matrix multiplication result)
Write_local_matrices_A("Write split of local matrix A into local_A.dat",
local_A, &grid); // Write local matrix A into file
if (PRINT_LOCAL_A == 1)
Print_local_matrices_A("Split of local matrix A",
local_A, &grid); // Print matrix A split in processess
Write_local_matrices_B("Write split of local matrix B into local_B.dat",
local_B, &grid); // Write local matrix B into file, special for row-major storage
if (PRINT_LOCAL_B == 1)
Print_local_matrices_B("Split of local matrix B",
local_B, &grid); // Print matrix B split in processess, special for row-major storage
Write_local_matrices_C("Write split of local matrix C into local_C.dat",
local_C, &grid); // Print matrix C split in processess
if (PRINT_LOCAL_C == 1)
Print_local_matrices_C("Split of local matrix C",
local_C, &grid); // Print matrix C split in processess
Free_local_matrix(&local_A); // Free local matrix local_A
Free_local_matrix(&local_B); // Free local matrix local_B
Free_local_matrix(&local_C); // Free local matrix local_C
if(my_rank == 0)
printf("Parallel Fox Matrix Multiplication Elapsed time:\n %30.20E seconds\n", timer_end-timer_start);
MPI_Finalize(); // MPI finalize, processes join and resource recycle
} /* main */
/*********************************************************/
void Setup_grid(
GRID_INFO_T* grid /* out */) {
int old_rank;
int dimensions[2];
int wrap_around[2];
int coordinates[2];
int free_coords[2];
/* Set up Global Grid Information */
MPI_Comm_size(MPI_COMM_WORLD, &(grid->p));
MPI_Comm_rank(MPI_COMM_WORLD, &old_rank);
/* We assume p is a perfect square */ // but what if it's not a perfect square
grid->q = (int) sqrt((double) grid->p);
dimensions[0] = dimensions[1] = grid->q;
/* We want a circular shift in second dimension. */
/* Don't care about first */
wrap_around[0] = wrap_around[1] = 1;
MPI_Cart_create(MPI_COMM_WORLD, 2, dimensions,
wrap_around, 1, &(grid->comm));
MPI_Comm_rank(grid->comm, &(grid->my_rank));
MPI_Cart_coords(grid->comm, grid->my_rank, 2,
coordinates);
grid->my_row = coordinates[0];
grid->my_col = coordinates[1];
/* Set up row communicators */
free_coords[0] = 0;
free_coords[1] = 1;
MPI_Cart_sub(grid->comm, free_coords,
&(grid->row_comm));
/* Set up column communicators */
free_coords[0] = 1;
free_coords[1] = 0;
MPI_Cart_sub(grid->comm, free_coords,
&(grid->col_comm));
} /* Setup_grid */
/*********************************************************/
void Fox(
int n /* in */,
GRID_INFO_T* grid /* in */,
LOCAL_MATRIX_T* local_A /* in */,
LOCAL_MATRIX_T* local_B /* in */,
LOCAL_MATRIX_T* local_C /* out */) {
LOCAL_MATRIX_T* temp_A; /* Storage for the sub- */
/* matrix of A used during */
/* the current stage */
int stage;
int bcast_root;
int n_bar; /* n/sqrt(p) */
int source;
int dest;
MPI_Status status;
n_bar = n/grid->q;
Set_to_zero(local_C);
/* Calculate addresses for row circular shift of B */
source = (grid->my_row + 1) % grid->q;
dest = (grid->my_row + grid->q - 1) % grid->q;
/* Set aside storage for the broadcast block of A */
temp_A = Local_matrix_allocate(n_bar);
for (stage = 0; stage < grid->q; stage++) {
bcast_root = (grid->my_row + stage) % grid->q;
if (bcast_root == grid->my_col) { // Process P_{ii} broadcast A_{ii} in process gird's row commnunicator
MPI_Bcast(local_A, 1, local_matrix_mpi_t,
bcast_root, grid->row_comm);
Local_matrix_multiply(local_A, local_B,
local_C);
} else { // temp_A is a buffer for process P_{ij} to store A_{ij}
MPI_Bcast(temp_A, 1, local_matrix_mpi_t,
bcast_root, grid->row_comm);
Local_matrix_multiply(temp_A, local_B,
local_C);
}
MPI_Sendrecv_replace(local_B, 1, local_matrix_mpi_t, // MPI send and receive with single buffer
dest, 0, source, 0, grid->col_comm, &status); // Circular shift of process grid B's row, after local multiplication operation
} /* for */
} /* Fox */
/*********************************************************/
LOCAL_MATRIX_T* Local_matrix_allocate(int local_order) {
LOCAL_MATRIX_T* temp;
temp = (LOCAL_MATRIX_T*) malloc(sizeof(LOCAL_MATRIX_T));
return temp;
} /* Local_matrix_allocate */
/*********************************************************/
void Free_local_matrix(
LOCAL_MATRIX_T** local_A_ptr /* in/out */) {
free(*local_A_ptr);
} /* Free_local_matrix */
/*********************************************************/
/* Read and distribute matrix for matrix A:
* foreach global row of the matrix,
* foreach grid column
* read a block of n_bar floats on process 0
* and send them to the appropriate process.
*/
void Read_matrix_A(
char* prompt /* in */,
LOCAL_MATRIX_T* local_A /* out */,
GRID_INFO_T* grid /* in */,
int n /* in */) {
FILE *fp;
int mat_row, mat_col;
int grid_row, grid_col;
int dest;
int coords[2];
FLOAT* temp;
MPI_Status status;
if (grid->my_rank == 0) { // Process 0 read matrix input from stdin and send them to other processess
fp = fopen("A.dat","r");
temp = (FLOAT*) malloc(Order(local_A)*sizeof(FLOAT));
printf("%s\n", prompt);
fflush(stdout);
for (mat_row = 0; mat_row < n; mat_row++) {
grid_row = mat_row/Order(local_A);
coords[0] = grid_row;
for (grid_col = 0; grid_col < grid->q; grid_col++) {
coords[1] = grid_col;
MPI_Cart_rank(grid->comm, coords, &dest);
if (dest == 0) {
for (mat_col = 0; mat_col < Order(local_A); mat_col++)
fscanf(fp, "%lf",
(local_A->entries)+mat_row*Order(local_A)+mat_col);
/* scanf("%lf",
(local_A->entries)+mat_row*Order(local_A)+mat_col);
*/
} else {
for(mat_col = 0; mat_col < Order(local_A); mat_col++)
fscanf(fp,"%lf", temp + mat_col);
// scanf("%lf", temp + mat_col);
MPI_Send(temp, Order(local_A), FLOAT_MPI, dest, 0,
grid->comm);
}
}
}
free(temp);
fclose(fp);
} else { // Other processess receive matrix from process 0
for (mat_row = 0; mat_row < Order(local_A); mat_row++)
MPI_Recv(&Entry(local_A, mat_row, 0), Order(local_A),
FLOAT_MPI, 0, 0, grid->comm, &status);
}
} /* Read_matrix */
/*********************************************************/
/* Read and distribute matrix for local matrix B's transpose:
* foreach global row of the matrix,
* foreach grid column
* read a block of n_bar floats on process 0
* and send them to the appropriate process.
*/
void Read_matrix_B(
char* prompt /* in */,
LOCAL_MATRIX_T* local_B /* out */,
GRID_INFO_T* grid /* in */,
int n /* in */) {
FILE *fp;
int mat_row, mat_col;
int grid_row, grid_col;
int dest;
int coords[2];
FLOAT *temp;
MPI_Status status;
if (grid->my_rank == 0) { // Process 0 read matrix input from stdin and send them to other processess
fp = fopen("B.dat","r");
temp = (FLOAT*) malloc(Order(local_B)*sizeof(FLOAT));
printf("%s\n", prompt);
fflush(stdout);
for (mat_row = 0; mat_row < n; mat_row++) {
grid_row = mat_row/Order(local_B);
coords[0] = grid_row;
for (grid_col = 0; grid_col < grid->q; grid_col++) {
coords[1] = grid_col;
MPI_Cart_rank(grid->comm, coords, &dest);
if (dest == 0) { // process 0 (local)
for (mat_col = 0; mat_col < Order(local_B); mat_col++)
fscanf(fp, "%lf",
(local_B->entries)+mat_col*Order(local_B)+mat_row); // switch rows and colums in local_B, for column major storage
/* scanf("%lf",
(local_B->entries)+mat_col*Order(local_B)+mat_row); // switch rows and colums in local_B, for column major storage
*/
/* scanf("%lf",
(local_A->entries)+mat_row*Order(local_A)+mat_col); */
} else {
for(mat_col = 0; mat_col < Order(local_B); mat_col++)
fscanf(fp, "%lf", temp + mat_col);
// scanf("%lf", temp + mat_col);
MPI_Send(temp, Order(local_B), FLOAT_MPI, dest, 0,
grid->comm);
}
}
}
free(temp);
fclose(fp);
} else { // Other processess receive matrix from process 0
temp = (FLOAT*) malloc(Order(local_B)*sizeof(FLOAT)); // switch rows and colums in local_B, for column major storage
for (mat_col = 0; mat_col < Order(local_B); mat_col++) {
MPI_Recv(temp, Order(local_B),
FLOAT_MPI, 0, 0, grid->comm, &status); // switch rows and colums in local_B, for column major storage
for(mat_row = 0; mat_row < Order(local_B); mat_row++)
Entry(local_B, mat_row, mat_col) = *(temp + mat_row); // switch rows and colums in local_B, for column major storage
/* MPI_Recv(&Entry(local_A, mat_row, 0), Order(local_A),
FLOAT_MPI, 0, 0, grid->comm, &status); */
}
free(temp);
}
} /* Read_matrix_B */
/*********************************************************/
/* Recive and Print Matrix A:
* foreach global row of the matrix,
* foreach grid column
* send n_bar floats to process 0 from each other process
* receive a block of n_bar floats on process 0 from other processes and print them
*/
void Print_matrix_A(
char* title /* in */,
LOCAL_MATRIX_T* local_A /* out */,
GRID_INFO_T* grid /* in */,
int n /* in */) {
int mat_row, mat_col;
int grid_row, grid_col;
int source;
int coords[2];
FLOAT* temp;
MPI_Status status;
if (grid->my_rank == 0) {
temp = (FLOAT*) malloc(Order(local_A)*sizeof(FLOAT));
printf("%s\n", title);
for (mat_row = 0; mat_row < n; mat_row++) {
grid_row = mat_row/Order(local_A);
coords[0] = grid_row;
for (grid_col = 0; grid_col < grid->q; grid_col++) {
coords[1] = grid_col;
MPI_Cart_rank(grid->comm, coords, &source);
if (source == 0) {
for(mat_col = 0; mat_col < Order(local_A); mat_col++)
printf("%20.15E ", Entry(local_A, mat_row, mat_col));
} else {
MPI_Recv(temp, Order(local_A), FLOAT_MPI, source, 0,
grid->comm, &status);
for(mat_col = 0; mat_col < Order(local_A); mat_col++)
printf("%20.15E ", temp[mat_col]);
}
}
printf("\n");
}
free(temp);
} else {
for (mat_row = 0; mat_row < Order(local_A); mat_row++)
MPI_Send(&Entry(local_A, mat_row, 0), Order(local_A),
FLOAT_MPI, 0, 0, grid->comm);
}
} /* Print_matrix_A */
/*********************************************************/
/* Recive and Print Matrix for local matrix B's transpose:
* foreach global row of the matrix,
* foreach grid column
* send n_bar floats to process 0 from each other process
* receive a block of n_bar floats on process 0 from other processes and print them
*/
void Print_matrix_B(
char* title /* in */,
LOCAL_MATRIX_T* local_B /* out */,
GRID_INFO_T* grid /* in */,
int n /* in */) {
int mat_row, mat_col;
int grid_row, grid_col;
int source;
int coords[2];
FLOAT* temp;
MPI_Status status;
if (grid->my_rank == 0) {
temp = (FLOAT*) malloc(Order(local_B)*sizeof(FLOAT));
printf("%s\n", title);
for (mat_row = 0; mat_row < n; mat_row++) {
grid_row = mat_row/Order(local_B);
coords[0] = grid_row;
for (grid_col = 0; grid_col < grid->q; grid_col++) {
coords[1] = grid_col;
MPI_Cart_rank(grid->comm, coords, &source);
if (source == 0) {
for(mat_col = 0; mat_col < Order(local_B); mat_col++)
printf("%20.15E ", Entry(local_B, mat_col, mat_row)); // switch rows and colums in local_B, for column major storage
// printf("%20.15E ", Entry(local_A, mat_row, mat_col));
} else {
MPI_Recv(temp, Order(local_B), FLOAT_MPI, source, 0,
grid->comm, &status);
for(mat_col = 0; mat_col < Order(local_B); mat_col++)
printf("%20.15E ", temp[mat_col]);
}
}
printf("\n");
}
free(temp);
} else {
temp = (FLOAT*) malloc(Order(local_B)*sizeof(FLOAT));
for (mat_col = 0; mat_col < Order(local_B); mat_col++) {
for(mat_row = 0; mat_row < Order(local_B); mat_row++)
*(temp+mat_row) = Entry(local_B, mat_row, mat_col); // switch rows and colums in local_B, for column major storage
MPI_Send(temp, Order(local_B), FLOAT_MPI, 0, 0, grid->comm);
}
free(temp);
}
} /* Print_matrix_B */
/*********************************************************/
/* Recive and Print Matrix A:
* foreach global row of the matrix,
* foreach grid column
* send n_bar floats to process 0 from each other process
* receive a block of n_bar floats on process 0 from other processes and print them
*/
void Print_matrix_C(
char* title /* in */,
LOCAL_MATRIX_T* local_C /* out */,
GRID_INFO_T* grid /* in */,
int n /* in */) {
int mat_row, mat_col;
int grid_row, grid_col;
int source;
int coords[2];
FLOAT* temp;
MPI_Status status;
if (grid->my_rank == 0) {
temp = (FLOAT*) malloc(Order(local_C)*sizeof(FLOAT));
printf("%s\n", title);
for (mat_row = 0; mat_row < n; mat_row++) {
grid_row = mat_row/Order(local_C);
coords[0] = grid_row;
for (grid_col = 0; grid_col < grid->q; grid_col++) {
coords[1] = grid_col;
MPI_Cart_rank(grid->comm, coords, &source);
if (source == 0) {
for(mat_col = 0; mat_col < Order(local_C); mat_col++)
printf("%20.15E ", Entry(local_C, mat_row, mat_col));
} else {
MPI_Recv(temp, Order(local_C), FLOAT_MPI, source, 0,
grid->comm, &status);
for(mat_col = 0; mat_col < Order(local_C); mat_col++)
printf("%20.15E ", temp[mat_col]);
}
}
printf("\n");
}
free(temp);
} else {
for (mat_row = 0; mat_row < Order(local_C); mat_row++)
MPI_Send(&Entry(local_C, mat_row, 0), Order(local_C),
FLOAT_MPI, 0, 0, grid->comm);
}
} /* Print_matrix_C */
/*********************************************************/
/* Recive and Write Matrix C into a file:
* foreach global row of the matrix,
* foreach grid column
* send n_bar floats to process 0 from each other process
* receive a block of n_bar floats on process 0 from other processes and print them
*/
void Write_matrix_C(
char* title /* in */,
LOCAL_MATRIX_T* local_C /* out */,
GRID_INFO_T* grid /* in */,
int n /* in */) {
FILE *fp;
int mat_row, mat_col;
int grid_row, grid_col;
int source;
int coords[2];
FLOAT* temp;
MPI_Status status;
if (grid->my_rank == 0) {
fp = fopen("C.dat", "w+");
temp = (FLOAT*) malloc(Order(local_C)*sizeof(FLOAT));
printf("%s\n", title);
for (mat_row = 0; mat_row < n; mat_row++) {
grid_row = mat_row/Order(local_C);
coords[0] = grid_row;
for (grid_col = 0; grid_col < grid->q; grid_col++) {
coords[1] = grid_col;
MPI_Cart_rank(grid->comm, coords, &source);
if (source == 0) {
for(mat_col = 0; mat_col < Order(local_C); mat_col++)
fprintf(fp, "%20.15E ", Entry(local_C, mat_row, mat_col));
// printf("%20.15E ", Entry(local_A, mat_row, mat_col));
} else {
MPI_Recv(temp, Order(local_C), FLOAT_MPI, source, 0,
grid->comm, &status);
for(mat_col = 0; mat_col < Order(local_C); mat_col++)
fprintf(fp, "%20.15E ", temp[mat_col]);
// printf("%20.15E ", temp[mat_col]);
}
}
fprintf(fp,"\n");
}
free(temp);
fclose(fp);
} else {
for (mat_row = 0; mat_row < Order(local_C); mat_row++)
MPI_Send(&Entry(local_C, mat_row, 0), Order(local_C),
FLOAT_MPI, 0, 0, grid->comm);
}
} /* Write_matrix_C */
/*********************************************************/
/*
* Set local matrix's element to zero
*/
void Set_to_zero(
LOCAL_MATRIX_T* local_A /* out */) {
int i, j;
for (i = 0; i < Order(local_A); i++)
for (j = 0; j < Order(local_A); j++)
Entry(local_A,i,j) = 0.0E0;
} /* Set_to_zero */
/*********************************************************/
void Build_matrix_type(
LOCAL_MATRIX_T* local_A /* in */) {
MPI_Datatype temp_mpi_t;
int block_lengths[2];
MPI_Aint displacements[2];
MPI_Datatype typelist[2];
MPI_Aint start_address;
MPI_Aint address;
MPI_Type_contiguous(Order(local_A)*Order(local_A),
FLOAT_MPI, &temp_mpi_t); // Creates a contiguous datatype
/*
Synopsis
int MPI_Type_contiguous(int count,
MPI_Datatype oldtype,
MPI_Datatype *newtype)
Input Parameters
count
replication count (nonnegative integer)
oldtype
old datatype (handle)
*/
block_lengths[0] = block_lengths[1] = 1;
typelist[0] = MPI_INT;
typelist[1] = temp_mpi_t;
MPI_Address(local_A, &start_address); // Gets the address of a location in caller's memory
MPI_Address(&(local_A->n_bar), &address);
/*
Synopsis
int MPI_Address(const void *location, MPI_Aint *address)
Input Parameters
location
location in caller memory (choice)
Output Parameters
address
address of location (address integer)
*/
displacements[0] = address - start_address;
MPI_Address(local_A->entries, &address);
displacements[1] = address - start_address;
MPI_Type_struct(2, block_lengths, displacements,
typelist, &local_matrix_mpi_t); // Creates a struct datatype
/*
Synopsis
int MPI_Type_struct(int count,
const int *array_of_blocklengths,
const MPI_Aint *array_of_displacements,
const MPI_Datatype *array_of_types,
MPI_Datatype *newtype)
Input Parameters
count
number of blocks (integer) -- also number of entries in arrays array_of_types , array_of_displacements and array_of_blocklengths
array_of_blocklengths
number of elements in each block (array)
array_of_displacements
byte displacement of each block (array)
array_of_types
type of elements in each block (array of handles to datatype objects)
Output Parameters
newtype
new datatype (handle)
*/
MPI_Type_commit(&local_matrix_mpi_t); // Commits the datatype
/*
Synopsis
int MPI_Type_commit(MPI_Datatype *datatype)
Input Parameters
datatype
datatype (handle)
*/
} /* Build_matrix_type */
/*********************************************************/
/* local matrix multiplication function
* withing OpenMP Thread Acceleration
*/
void Local_matrix_multiply(
LOCAL_MATRIX_T* local_A /* in */,
LOCAL_MATRIX_T* local_B /* in */,
LOCAL_MATRIX_T* local_C /* out */) {
int i, j, k;
// int my_rank;
// MPI_Comm_rank(MPI_COMM_WORLD, &my_rank); // Get my process id in the MPI communicator
#pragma omp parallel for private(i, j, k) shared(local_A, local_B, local_C) num_threads(NUM_THREADS) // Threads acceleration upgrade, parallel task split
for (i = 0; i < Order(local_A); i++) {
// printf("Current in the Fox Kernel:\n my process id is %d, my thread id is %d\n",my_rank,omp_get_thread_num());
for (j = 0; j < Order(local_A); j++)
for (k = 0; k < Order(local_B); k++)
Entry(local_C,i,j) = Entry(local_C,i,j) // switch rows and colums in local_B, for column major storage
+ Entry(local_A,i,k)*Entry(local_B,j,k); // continuous memory access, local matrix multiplication A(i,k)*B^T(j,k)
/* Entry(local_C,i,j) = Entry(local_C,i,j)
+ Entry(local_A,i,k)*Entry(local_B,k,j); // non-continuous memory access, A(i,k)*B^T(j,k) is more proper
*/
}
} /* Local_matrix_multiply */
/*********************************************************/
/* Recive and Print Local Matrix A:
* Process 0 print local matrix local_A
* Other Processess send local matrix local_A to process 0
* And process 0 receive local matrix local_A from other processess
*/
void Print_local_matrices_A(
char* title /* in */,
LOCAL_MATRIX_T* local_A /* in */,
GRID_INFO_T* grid /* in */) {
int coords[2];
int i, j;
int source;
MPI_Status status;
// print by process No.0 in process mesh
if (grid->my_rank == 0) {
printf("%s\n", title);
printf("Process %d > grid_row = %d, grid_col = %d\n",
grid->my_rank, grid->my_row, grid->my_col);
for (i = 0; i < Order(local_A); i++) {
for (j = 0; j < Order(local_A); j++)
printf("%20.15E ", Entry(local_A,i,j));
printf("\n");
}
for (source = 1; source < grid->p; source++) {
MPI_Recv(temp_mat, 1, local_matrix_mpi_t, source, 0,
grid->comm, &status);
MPI_Cart_coords(grid->comm, source, 2, coords);
printf("Process %d > grid_row = %d, grid_col = %d\n",
source, coords[0], coords[1]);
for (i = 0; i < Order(temp_mat); i++) {
for (j = 0; j < Order(temp_mat); j++)
printf("%20.15E ", Entry(temp_mat,i,j));
printf("\n");
}
}
fflush(stdout);
} else {
MPI_Send(local_A, 1, local_matrix_mpi_t, 0, 0, grid->comm);
}
} /* Print_local_matrices_A */
/*********************************************************/
/* Recive and Print Local Matrix for local matrix B's transpose:
* Process 0 print local matrix local_A
* Other Processess send local matrix local_A to process 0
* And process 0 receive local matrix local_A from other processess
*/
void Print_local_matrices_B(
char* title /* in */,
LOCAL_MATRIX_T* local_B /* in */,
GRID_INFO_T* grid /* in */) {
int coords[2];
int i, j;
int source;
MPI_Status status;
// print by process No.0 in process mesh
if (grid->my_rank == 0) {
printf("%s\n", title);
printf("Process %d > grid_row = %d, grid_col = %d\n",
grid->my_rank, grid->my_row, grid->my_col);
for (i = 0; i < Order(local_B); i++) {
for (j = 0; j < Order(local_B); j++)
printf("%20.15E ", Entry(local_B,j,i)); // switch rows and colums in local_B, for column major storage
printf("\n");
}
for (source = 1; source < grid->p; source++) {
MPI_Recv(temp_mat, 1, local_matrix_mpi_t, source, 0,
grid->comm, &status);
MPI_Cart_coords(grid->comm, source, 2, coords);
printf("Process %d > grid_row = %d, grid_col = %d\n",
source, coords[0], coords[1]);
for (i = 0; i < Order(temp_mat); i++) {
for (j = 0; j < Order(temp_mat); j++)
printf("%20.15E ", Entry(temp_mat,j,i)); // switch rows and colums in local_B, for column major storage
printf("\n");
}
}
fflush(stdout);
} else {
MPI_Send(local_B, 1, local_matrix_mpi_t, 0, 0, grid->comm);
}
} /* Print_local_matrices_B */
/*********************************************************/
/* Recive and Print Local Matrix A:
* Process 0 print local matrix local_A
* Other Processess send local matrix local_A to process 0
* And process 0 receive local matrix local_A from other processess
*/
void Print_local_matrices_C(
char* title /* in */,
LOCAL_MATRIX_T* local_C /* in */,
GRID_INFO_T* grid /* in */) {
int coords[2];
int i, j;
int source;
MPI_Status status;
// print by process No.0 in process mesh
if (grid->my_rank == 0) {
printf("%s\n", title);
printf("Process %d > grid_row = %d, grid_col = %d\n",
grid->my_rank, grid->my_row, grid->my_col);
for (i = 0; i < Order(local_C); i++) {
for (j = 0; j < Order(local_C); j++)
printf("%20.15E ", Entry(local_C,i,j));
printf("\n");
}
for (source = 1; source < grid->p; source++) {
MPI_Recv(temp_mat, 1, local_matrix_mpi_t, source, 0,
grid->comm, &status);
MPI_Cart_coords(grid->comm, source, 2, coords);
printf("Process %d > grid_row = %d, grid_col = %d\n",
source, coords[0], coords[1]);
for (i = 0; i < Order(temp_mat); i++) {
for (j = 0; j < Order(temp_mat); j++)
printf("%20.15E ", Entry(temp_mat,i,j));
printf("\n");
}
}
fflush(stdout);
} else {
MPI_Send(local_C, 1, local_matrix_mpi_t, 0, 0, grid->comm);
}
} /* Print_local_matrices_C */
/*********************************************************/
/* Recive and Write Local Matrix A:
* Process 0 print local matrix local_A
* Other Processess send local matrix local_A to process 0
* And process 0 receive local matrix local_A from other processess
*/
void Write_local_matrices_A(
char* title /* in */,
LOCAL_MATRIX_T* local_A /* in */,
GRID_INFO_T* grid /* in */) {
FILE *fp;
int coords[2];
int i, j;
int source;
MPI_Status status;
// print by process No.0 in process mesh
if (grid->my_rank == 0) {
fp = fopen("local_A.dat","w+");
printf("%s\n", title);
fprintf(fp,"Process %d > grid_row = %d, grid_col = %d\n",
grid->my_rank, grid->my_row, grid->my_col);
for (i = 0; i < Order(local_A); i++) {
for (j = 0; j < Order(local_A); j++)
fprintf(fp,"%20.15E ", Entry(local_A,i,j));
fprintf(fp, "\n");
}
for (source = 1; source < grid->p; source++) {
MPI_Recv(temp_mat, 1, local_matrix_mpi_t, source, 0,
grid->comm, &status);
MPI_Cart_coords(grid->comm, source, 2, coords);
fprintf(fp, "Process %d > grid_row = %d, grid_col = %d\n",
source, coords[0], coords[1]);
for (i = 0; i < Order(temp_mat); i++) {
for (j = 0; j < Order(temp_mat); j++)
fprintf(fp, "%20.15E ", Entry(temp_mat,i,j));
fprintf(fp, "\n");
}
}
fflush(stdout);
fclose(fp);
} else {
MPI_Send(local_A, 1, local_matrix_mpi_t, 0, 0, grid->comm);
}
} /* Write_local_matrices_A */
/*********************************************************/
/* Recive and Write Local Matrix for local matrix B's transpose:
* Process 0 print local matrix local_A
* Other Processess send local matrix local_A to process 0
* And process 0 receive local matrix local_A from other processess
*/
void Write_local_matrices_B(
char* title /* in */,
LOCAL_MATRIX_T* local_B /* in */,
GRID_INFO_T* grid /* in */) {
FILE *fp;
int coords[2];
int i, j;
int source;
MPI_Status status;
// print by process No.0 in process mesh
if (grid->my_rank == 0) {
fp = fopen("local_B.dat","w+");
printf("%s\n", title);
fprintf(fp, "Process %d > grid_row = %d, grid_col = %d\n",
grid->my_rank, grid->my_row, grid->my_col);
for (i = 0; i < Order(local_B); i++) {
for (j = 0; j < Order(local_B); j++)
fprintf(fp, "%20.15E ", Entry(local_B,j,i)); // switch rows and colums in local_B, for column major storage
fprintf(fp, "\n");
}
for (source = 1; source < grid->p; source++) {
MPI_Recv(temp_mat, 1, local_matrix_mpi_t, source, 0,
grid->comm, &status);
MPI_Cart_coords(grid->comm, source, 2, coords);
fprintf(fp, "Process %d > grid_row = %d, grid_col = %d\n",
source, coords[0], coords[1]);
for (i = 0; i < Order(temp_mat); i++) {
for (j = 0; j < Order(temp_mat); j++)
fprintf(fp, "%20.15E ", Entry(temp_mat,j,i)); // switch rows and colums in local_B, for column major storage
fprintf(fp, "\n");
}
}
fflush(stdout);
fclose(fp);
} else {
MPI_Send(local_B, 1, local_matrix_mpi_t, 0, 0, grid->comm);
}
} /* Write_local_matrices_B */
/*********************************************************/
/* Recive and Write Local Matrix C:
* Process 0 print local matrix local_C
* Other Processess send local matrix local_C to process 0
* And process 0 receive local matrix local_C from other processess
*/
void Write_local_matrices_C(
char* title /* in */,
LOCAL_MATRIX_T* local_C /* in */,
GRID_INFO_T* grid /* in */) {
FILE *fp;
int coords[2];
int i, j;
int source;
MPI_Status status;
// print by process No.0 in process mesh
if (grid->my_rank == 0) {
fp = fopen("local_C.dat","w+");
printf("%s\n", title);
fprintf(fp, "Process %d > grid_row = %d, grid_col = %d\n",
grid->my_rank, grid->my_row, grid->my_col);
for (i = 0; i < Order(local_C); i++) {
for (j = 0; j < Order(local_C); j++)
fprintf(fp, "%20.15E ", Entry(local_C,i,j));
fprintf(fp, "\n");
}
for (source = 1; source < grid->p; source++) {
MPI_Recv(temp_mat, 1, local_matrix_mpi_t, source, 0,
grid->comm, &status);
MPI_Cart_coords(grid->comm, source, 2, coords);
fprintf(fp, "Process %d > grid_row = %d, grid_col = %d\n",
source, coords[0], coords[1]);
for (i = 0; i < Order(temp_mat); i++) {
for (j = 0; j < Order(temp_mat); j++)
fprintf(fp, "%20.15E ", Entry(temp_mat,i,j));
fprintf(fp, "\n");
}
}
fflush(stdout);
fclose(fp);
} else {
MPI_Send(local_C, 1, local_matrix_mpi_t, 0, 0, grid->comm);
}
} /* Write_local_matrices_C */
|
GB_binop__lor_uint32.c |
//------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2022, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_emult.h"
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB (_AaddB__lor_uint32)
// A.*B function (eWiseMult): GB (_AemultB_08__lor_uint32)
// A.*B function (eWiseMult): GB (_AemultB_02__lor_uint32)
// A.*B function (eWiseMult): GB (_AemultB_04__lor_uint32)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__lor_uint32)
// A*D function (colscale): GB (_AxD__lor_uint32)
// D*A function (rowscale): GB (_DxB__lor_uint32)
// C+=B function (dense accum): GB (_Cdense_accumB__lor_uint32)
// C+=b function (dense accum): GB (_Cdense_accumb__lor_uint32)
// C+=A+B function (dense ewise3): GB ((none))
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__lor_uint32)
// C=scalar+B GB (_bind1st__lor_uint32)
// C=scalar+B' GB (_bind1st_tran__lor_uint32)
// C=A+scalar GB (_bind2nd__lor_uint32)
// C=A'+scalar GB (_bind2nd_tran__lor_uint32)
// C type: uint32_t
// A type: uint32_t
// A pattern? 0
// B type: uint32_t
// B pattern? 0
// BinaryOp: cij = ((aij != 0) || (bij != 0))
#define GB_ATYPE \
uint32_t
#define GB_BTYPE \
uint32_t
#define GB_CTYPE \
uint32_t
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
1
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
1
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA,A_iso) \
uint32_t aij = GBX (Ax, pA, A_iso)
// true if values of A are not used
#define GB_A_IS_PATTERN \
0 \
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB,B_iso) \
uint32_t bij = GBX (Bx, pB, B_iso)
// true if values of B are not used
#define GB_B_IS_PATTERN \
0 \
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
uint32_t t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA,A_iso) \
cij = GBX (Ax, pA, A_iso)
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB,B_iso) \
cij = GBX (Bx, pB, B_iso)
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z,x,y,i,j) \
z = ((x != 0) || (y != 0)) ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
0
// op is second
#define GB_OP_IS_SECOND \
0
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_LOR || GxB_NO_UINT32 || GxB_NO_LOR_UINT32)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
#if 0
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
#endif
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
void GB (_Cdense_ewise3_noaccum__lor_uint32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_noaccum_template.c"
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumB__lor_uint32)
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *B_ek_slicing, const int B_ntasks, const int B_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
#include "GB_dense_subassign_23_template.c"
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumb__lor_uint32)
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
// get the scalar b for C += b, of type uint32_t
uint32_t bwork = (*((uint32_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_AxD__lor_uint32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix D,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint32_t *restrict Cx = (uint32_t *) C->x ;
#include "GB_AxB_colscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_DxB__lor_uint32)
(
GrB_Matrix C,
const GrB_Matrix D,
const GrB_Matrix B,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint32_t *restrict Cx = (uint32_t *) C->x ;
#include "GB_AxB_rowscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C=A+B, C<M>=A+B, C<!M>=A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__lor_uint32)
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool is_eWiseUnion,
const GB_void *alpha_scalar_in,
const GB_void *beta_scalar_in,
const bool Ch_is_Mh,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GB_WERK_DECLARE (M_ek_slicing, int64_t) ;
GB_WERK_DECLARE (A_ek_slicing, int64_t) ;
GB_WERK_DECLARE (B_ek_slicing, int64_t) ;
uint32_t alpha_scalar ;
uint32_t beta_scalar ;
if (is_eWiseUnion)
{
alpha_scalar = (*((uint32_t *) alpha_scalar_in)) ;
beta_scalar = (*((uint32_t *) beta_scalar_in )) ;
}
#include "GB_add_template.c"
GB_FREE_WORKSPACE ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, or C<M!>=A.*B where C is sparse/hyper
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_08__lor_uint32)
(
GrB_Matrix C,
const int C_sparsity,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_08_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<#> = A.*B when A is sparse/hyper and B is bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_02__lor_uint32)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool flipxy,
const int64_t *restrict Cp_kfirst,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if GB_BINOP_FLIP
// The operator is not commutative, and does not have a flipped
// variant. For example z=atan2(y,x).
if (flipxy)
{
// use fmult(y,x)
#undef GB_FLIPPED
#define GB_FLIPPED 1
#include "GB_emult_02_template.c"
}
else
{
// use fmult(x,y)
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
}
#else
// No need to handle the flip: the operator is either commutative, or
// has been handled by changing z=div(y,x) to z=rdiv(x,y) for example.
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<M> = A.*B, M sparse/hyper, A and B bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_04__lor_uint32)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict Cp_kfirst,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_04_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, C<!M>=A.*B where C is bitmap
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_bitmap__lor_uint32)
(
GrB_Matrix C,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_bitmap_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB (_bind1st__lor_uint32)
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *restrict Bb,
int64_t bnz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint32_t *Cx = (uint32_t *) Cx_output ;
uint32_t x = (*((uint32_t *) x_input)) ;
uint32_t *Bx = (uint32_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < bnz ; p++)
{
if (!GBB (Bb, p)) continue ;
uint32_t bij = GBX (Bx, p, false) ;
Cx [p] = ((x != 0) || (bij != 0)) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__lor_uint32)
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *restrict Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
uint32_t *Cx = (uint32_t *) Cx_output ;
uint32_t *Ax = (uint32_t *) Ax_input ;
uint32_t y = (*((uint32_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
uint32_t aij = GBX (Ax, p, false) ;
Cx [p] = ((aij != 0) || (y != 0)) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
uint32_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = ((x != 0) || (aij != 0)) ; \
}
GrB_Info GB (_bind1st_tran__lor_uint32)
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
uint32_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint32_t x = (*((const uint32_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
uint32_t
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
uint32_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = ((aij != 0) || (y != 0)) ; \
}
GrB_Info GB (_bind2nd_tran__lor_uint32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint32_t y = (*((const uint32_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
GB_binop__bor_uint16.c |
//------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2022, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_emult.h"
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB (_AaddB__bor_uint16)
// A.*B function (eWiseMult): GB (_AemultB_08__bor_uint16)
// A.*B function (eWiseMult): GB (_AemultB_02__bor_uint16)
// A.*B function (eWiseMult): GB (_AemultB_04__bor_uint16)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__bor_uint16)
// A*D function (colscale): GB (_AxD__bor_uint16)
// D*A function (rowscale): GB (_DxB__bor_uint16)
// C+=B function (dense accum): GB (_Cdense_accumB__bor_uint16)
// C+=b function (dense accum): GB (_Cdense_accumb__bor_uint16)
// C+=A+B function (dense ewise3): GB ((none))
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__bor_uint16)
// C=scalar+B GB (_bind1st__bor_uint16)
// C=scalar+B' GB (_bind1st_tran__bor_uint16)
// C=A+scalar GB (_bind2nd__bor_uint16)
// C=A'+scalar GB (_bind2nd_tran__bor_uint16)
// C type: uint16_t
// A type: uint16_t
// A pattern? 0
// B type: uint16_t
// B pattern? 0
// BinaryOp: cij = (aij) | (bij)
#define GB_ATYPE \
uint16_t
#define GB_BTYPE \
uint16_t
#define GB_CTYPE \
uint16_t
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
1
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
1
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA,A_iso) \
uint16_t aij = GBX (Ax, pA, A_iso)
// true if values of A are not used
#define GB_A_IS_PATTERN \
0 \
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB,B_iso) \
uint16_t bij = GBX (Bx, pB, B_iso)
// true if values of B are not used
#define GB_B_IS_PATTERN \
0 \
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
uint16_t t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA,A_iso) \
cij = GBX (Ax, pA, A_iso)
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB,B_iso) \
cij = GBX (Bx, pB, B_iso)
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z,x,y,i,j) \
z = (x) | (y) ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
0
// op is second
#define GB_OP_IS_SECOND \
0
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_BOR || GxB_NO_UINT16 || GxB_NO_BOR_UINT16)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
#if 0
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
#endif
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
void GB (_Cdense_ewise3_noaccum__bor_uint16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_noaccum_template.c"
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumB__bor_uint16)
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *B_ek_slicing, const int B_ntasks, const int B_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
#include "GB_dense_subassign_23_template.c"
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumb__bor_uint16)
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
// get the scalar b for C += b, of type uint16_t
uint16_t bwork = (*((uint16_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_AxD__bor_uint16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix D,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint16_t *restrict Cx = (uint16_t *) C->x ;
#include "GB_AxB_colscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_DxB__bor_uint16)
(
GrB_Matrix C,
const GrB_Matrix D,
const GrB_Matrix B,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint16_t *restrict Cx = (uint16_t *) C->x ;
#include "GB_AxB_rowscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C=A+B, C<M>=A+B, C<!M>=A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__bor_uint16)
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool is_eWiseUnion,
const GB_void *alpha_scalar_in,
const GB_void *beta_scalar_in,
const bool Ch_is_Mh,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GB_WERK_DECLARE (M_ek_slicing, int64_t) ;
GB_WERK_DECLARE (A_ek_slicing, int64_t) ;
GB_WERK_DECLARE (B_ek_slicing, int64_t) ;
uint16_t alpha_scalar ;
uint16_t beta_scalar ;
if (is_eWiseUnion)
{
alpha_scalar = (*((uint16_t *) alpha_scalar_in)) ;
beta_scalar = (*((uint16_t *) beta_scalar_in )) ;
}
#include "GB_add_template.c"
GB_FREE_WORKSPACE ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, or C<M!>=A.*B where C is sparse/hyper
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_08__bor_uint16)
(
GrB_Matrix C,
const int C_sparsity,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_08_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<#> = A.*B when A is sparse/hyper and B is bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_02__bor_uint16)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool flipxy,
const int64_t *restrict Cp_kfirst,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if GB_BINOP_FLIP
// The operator is not commutative, and does not have a flipped
// variant. For example z=atan2(y,x).
if (flipxy)
{
// use fmult(y,x)
#undef GB_FLIPPED
#define GB_FLIPPED 1
#include "GB_emult_02_template.c"
}
else
{
// use fmult(x,y)
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
}
#else
// No need to handle the flip: the operator is either commutative, or
// has been handled by changing z=div(y,x) to z=rdiv(x,y) for example.
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<M> = A.*B, M sparse/hyper, A and B bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_04__bor_uint16)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict Cp_kfirst,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_04_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, C<!M>=A.*B where C is bitmap
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_bitmap__bor_uint16)
(
GrB_Matrix C,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_bitmap_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB (_bind1st__bor_uint16)
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *restrict Bb,
int64_t bnz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint16_t *Cx = (uint16_t *) Cx_output ;
uint16_t x = (*((uint16_t *) x_input)) ;
uint16_t *Bx = (uint16_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < bnz ; p++)
{
if (!GBB (Bb, p)) continue ;
uint16_t bij = GBX (Bx, p, false) ;
Cx [p] = (x) | (bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__bor_uint16)
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *restrict Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
uint16_t *Cx = (uint16_t *) Cx_output ;
uint16_t *Ax = (uint16_t *) Ax_input ;
uint16_t y = (*((uint16_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
uint16_t aij = GBX (Ax, p, false) ;
Cx [p] = (aij) | (y) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
uint16_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = (x) | (aij) ; \
}
GrB_Info GB (_bind1st_tran__bor_uint16)
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
uint16_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint16_t x = (*((const uint16_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
uint16_t
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
uint16_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = (aij) | (y) ; \
}
GrB_Info GB (_bind2nd_tran__bor_uint16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint16_t y = (*((const uint16_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
convolution_sgemm_pack8to4_int8.h | // Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.
//
// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
// in compliance with the License. You may obtain a copy of the License at
//
// https://opensource.org/licenses/BSD-3-Clause
//
// Unless required by applicable law or agreed to in writing, software distributed
// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
// CONDITIONS OF ANY KIND, either express or implied. See the License for the
// specific language governing permissions and limitations under the License.
#if !(__AVX512VNNI__ || __AVXVNNI__ || __AVX2__ || __XOP__)
#if NCNN_RUNTIME_CPU && NCNN_AVX512VNNI && __AVX512F__ && !__AVX512VNNI__
void im2col_sgemm_pack8to4_int8_sse_avx512vnni(const Mat& bottom_im2col, Mat& top_blob, const Mat& kernel, const Option& opt);
#endif
#if NCNN_RUNTIME_CPU && NCNN_AVXVNNI && __AVX2__ && !__AVXVNNI__
void im2col_sgemm_pack8to4_int8_sse_avxvnni(const Mat& bottom_im2col, Mat& top_blob, const Mat& kernel, const Option& opt);
#endif
#if NCNN_RUNTIME_CPU && NCNN_AVX2 && __AVX__ && !__AVX2__
void im2col_sgemm_pack8to4_int8_sse_avx2(const Mat& bottom_im2col, Mat& top_blob, const Mat& kernel, const Option& opt);
#endif
#if NCNN_RUNTIME_CPU && NCNN_XOP && __SSE2__ && !__XOP__
void im2col_sgemm_pack8to4_int8_sse_xop(const Mat& bottom_im2col, Mat& top_blob, const Mat& kernel, const Option& opt);
#endif
#endif
static void im2col_sgemm_pack8to4_int8_sse(const Mat& bottom_im2col, Mat& top_blob, const Mat& kernel, const Option& opt)
{
#if !(__AVX512VNNI__ || __AVXVNNI__ || __AVX2__ || __XOP__)
#if NCNN_RUNTIME_CPU && NCNN_AVX512VNNI && __AVX512F__ && !__AVX512VNNI__
if (ncnn::cpu_support_x86_avx512_vnni())
{
im2col_sgemm_pack8to4_int8_sse_avx512vnni(bottom_im2col, top_blob, kernel, opt);
return;
}
#endif
#if NCNN_RUNTIME_CPU && NCNN_AVXVNNI && __AVX2__ && !__AVXVNNI__
if (ncnn::cpu_support_x86_avx_vnni())
{
im2col_sgemm_pack8to4_int8_sse_avxvnni(bottom_im2col, top_blob, kernel, opt);
return;
}
#endif
#if NCNN_RUNTIME_CPU && NCNN_AVX2 && __AVX__ && !__AVX2__
if (ncnn::cpu_support_x86_avx2())
{
im2col_sgemm_pack8to4_int8_sse_avx2(bottom_im2col, top_blob, kernel, opt);
return;
}
#endif
#if NCNN_RUNTIME_CPU && NCNN_XOP && __SSE2__ && !__XOP__
if (ncnn::cpu_support_x86_xop())
{
im2col_sgemm_pack8to4_int8_sse_xop(bottom_im2col, top_blob, kernel, opt);
return;
}
#endif
#endif
// Mat bottom_im2col(size, maxk, inch, 8u, 8, opt.workspace_allocator);
const int size = bottom_im2col.w;
const int maxk = bottom_im2col.h;
const int inch = bottom_im2col.c;
const int outch = top_blob.c;
// permute
Mat tmp;
#if __AVX2__
if (size >= 4)
tmp.create(4 * maxk, inch, size / 4 + (size % 4) / 2 + size % 2, 8u, 8, opt.workspace_allocator);
else if (size >= 2)
tmp.create(2 * maxk, inch, size / 2 + size % 2, 8u, 8, opt.workspace_allocator);
else
tmp.create(maxk, inch, size, 8u, 8, opt.workspace_allocator);
#else
if (size >= 2)
tmp.create(2 * maxk, inch, size / 2 + size % 2, 8u, 8, opt.workspace_allocator);
else
tmp.create(maxk, inch, size, 8u, 8, opt.workspace_allocator);
#endif
{
#if __AVX2__
int remain_size_start = 0;
int nn_size = size >> 2;
#pragma omp parallel for num_threads(opt.num_threads)
for (int ii = 0; ii < nn_size; ii++)
{
int i = remain_size_start + ii * 4;
int64_t* tmpptr = tmp.channel(i / 4);
for (int q = 0; q < inch; q++)
{
const int64_t* img0 = (const int64_t*)bottom_im2col.channel(q) + i;
for (int k = 0; k < maxk; k++)
{
__m256i _v = _mm256_loadu_si256((const __m256i*)img0);
_mm256_storeu_si256((__m256i*)tmpptr, _v);
tmpptr += 4;
img0 += size;
}
}
}
remain_size_start += nn_size << 2;
nn_size = (size - remain_size_start) >> 1;
#else
int remain_size_start = 0;
int nn_size = size >> 1;
#endif
#pragma omp parallel for num_threads(opt.num_threads)
for (int ii = 0; ii < nn_size; ii++)
{
int i = remain_size_start + ii * 2;
#if __AVX2__
int64_t* tmpptr = tmp.channel(i / 4 + (i % 4) / 2);
#else
int64_t* tmpptr = tmp.channel(i / 2);
#endif
for (int q = 0; q < inch; q++)
{
const int64_t* img0 = (const int64_t*)bottom_im2col.channel(q) + i;
for (int k = 0; k < maxk; k++)
{
__m128i _v = _mm_loadu_si128((const __m128i*)img0);
_mm_storeu_si128((__m128i*)tmpptr, _v);
tmpptr += 2;
img0 += size;
}
}
}
remain_size_start += nn_size << 1;
#pragma omp parallel for num_threads(opt.num_threads)
for (int i = remain_size_start; i < size; i++)
{
#if __AVX2__
int64_t* tmpptr = tmp.channel(i / 4 + (i % 4) / 2 + i % 2);
#else
int64_t* tmpptr = tmp.channel(i / 2 + i % 2);
#endif
for (int q = 0; q < inch; q++)
{
const int64_t* img0 = (const int64_t*)bottom_im2col.channel(q) + i;
for (int k = 0; k < maxk; k++)
{
tmpptr[0] = img0[0];
tmpptr += 1;
img0 += size;
}
}
}
}
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < outch; p++)
{
int* outptr0 = top_blob.channel(p);
int i = 0;
#if __AVX2__
for (; i + 3 < size; i += 4)
{
const signed char* tmpptr = tmp.channel(i / 4);
const signed char* kptr0 = kernel.channel(p);
int nn = inch * maxk; // inch always > 0
__m256i _sum00_11 = _mm256_setzero_si256();
__m256i _sum10_01 = _mm256_setzero_si256();
__m256i _sum02_13 = _mm256_setzero_si256();
__m256i _sum12_03 = _mm256_setzero_si256();
__m256i _sum04_15 = _mm256_setzero_si256();
__m256i _sum14_05 = _mm256_setzero_si256();
__m256i _sum06_17 = _mm256_setzero_si256();
__m256i _sum16_07 = _mm256_setzero_si256();
int j = 0;
for (; j < nn; j++)
{
__m128i _val01 = _mm_loadu_si128((const __m128i*)tmpptr);
__m256i _val01_16 = _mm256_cvtepi8_epi16(_val01);
__m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
__m128i _w23 = _mm_loadu_si128((const __m128i*)(kptr0 + 16));
__m256i _w01_16 = _mm256_cvtepi8_epi16(_w01);
__m256i _w23_16 = _mm256_cvtepi8_epi16(_w23);
__m256i _val10_16 = _mm256_permute4x64_epi64(_val01_16, 78);
#if __AVXVNNI__ || __AVX512VNNI__
_sum00_11 = _mm256_dpwssd_epi32(_sum00_11, _val01_16, _w01_16);
_sum10_01 = _mm256_dpwssd_epi32(_sum10_01, _val10_16, _w01_16);
_sum02_13 = _mm256_dpwssd_epi32(_sum02_13, _val01_16, _w23_16);
_sum12_03 = _mm256_dpwssd_epi32(_sum12_03, _val10_16, _w23_16);
#else
__m256i _sl00_11 = _mm256_mullo_epi16(_val01_16, _w01_16);
__m256i _sh00_11 = _mm256_mulhi_epi16(_val01_16, _w01_16);
__m256i _sl10_01 = _mm256_mullo_epi16(_val10_16, _w01_16);
__m256i _sh10_01 = _mm256_mulhi_epi16(_val10_16, _w01_16);
__m256i _sl02_13 = _mm256_mullo_epi16(_val01_16, _w23_16);
__m256i _sh02_13 = _mm256_mulhi_epi16(_val01_16, _w23_16);
__m256i _sl12_03 = _mm256_mullo_epi16(_val10_16, _w23_16);
__m256i _sh12_03 = _mm256_mulhi_epi16(_val10_16, _w23_16);
_sum00_11 = _mm256_add_epi32(_sum00_11, _mm256_unpacklo_epi16(_sl00_11, _sh00_11));
_sum10_01 = _mm256_add_epi32(_sum10_01, _mm256_unpacklo_epi16(_sl10_01, _sh10_01));
_sum02_13 = _mm256_add_epi32(_sum02_13, _mm256_unpacklo_epi16(_sl02_13, _sh02_13));
_sum12_03 = _mm256_add_epi32(_sum12_03, _mm256_unpacklo_epi16(_sl12_03, _sh12_03));
_sum00_11 = _mm256_add_epi32(_sum00_11, _mm256_unpackhi_epi16(_sl00_11, _sh00_11));
_sum10_01 = _mm256_add_epi32(_sum10_01, _mm256_unpackhi_epi16(_sl10_01, _sh10_01));
_sum02_13 = _mm256_add_epi32(_sum02_13, _mm256_unpackhi_epi16(_sl02_13, _sh02_13));
_sum12_03 = _mm256_add_epi32(_sum12_03, _mm256_unpackhi_epi16(_sl12_03, _sh12_03));
#endif
__m128i _val23 = _mm_loadu_si128((const __m128i*)(tmpptr + 16));
__m256i _val23_16 = _mm256_cvtepi8_epi16(_val23);
__m256i _val32_16 = _mm256_permute4x64_epi64(_val23_16, 78);
#if __AVXVNNI__ || __AVX512VNNI__
_sum04_15 = _mm256_dpwssd_epi32(_sum04_15, _val23_16, _w01_16);
_sum14_05 = _mm256_dpwssd_epi32(_sum14_05, _val32_16, _w01_16);
_sum06_17 = _mm256_dpwssd_epi32(_sum06_17, _val23_16, _w23_16);
_sum16_07 = _mm256_dpwssd_epi32(_sum16_07, _val32_16, _w23_16);
#else
__m256i _sl04_15 = _mm256_mullo_epi16(_val23_16, _w01_16);
__m256i _sh04_15 = _mm256_mulhi_epi16(_val23_16, _w01_16);
__m256i _sl14_05 = _mm256_mullo_epi16(_val32_16, _w01_16);
__m256i _sh14_05 = _mm256_mulhi_epi16(_val32_16, _w01_16);
__m256i _sl06_17 = _mm256_mullo_epi16(_val23_16, _w23_16);
__m256i _sh06_17 = _mm256_mulhi_epi16(_val23_16, _w23_16);
__m256i _sl16_07 = _mm256_mullo_epi16(_val32_16, _w23_16);
__m256i _sh16_07 = _mm256_mulhi_epi16(_val32_16, _w23_16);
_sum04_15 = _mm256_add_epi32(_sum04_15, _mm256_unpacklo_epi16(_sl04_15, _sh04_15));
_sum14_05 = _mm256_add_epi32(_sum14_05, _mm256_unpacklo_epi16(_sl14_05, _sh14_05));
_sum06_17 = _mm256_add_epi32(_sum06_17, _mm256_unpacklo_epi16(_sl06_17, _sh06_17));
_sum16_07 = _mm256_add_epi32(_sum16_07, _mm256_unpacklo_epi16(_sl16_07, _sh16_07));
_sum04_15 = _mm256_add_epi32(_sum04_15, _mm256_unpackhi_epi16(_sl04_15, _sh04_15));
_sum14_05 = _mm256_add_epi32(_sum14_05, _mm256_unpackhi_epi16(_sl14_05, _sh14_05));
_sum06_17 = _mm256_add_epi32(_sum06_17, _mm256_unpackhi_epi16(_sl06_17, _sh06_17));
_sum16_07 = _mm256_add_epi32(_sum16_07, _mm256_unpackhi_epi16(_sl16_07, _sh16_07));
#endif
tmpptr += 32;
kptr0 += 32;
}
// transpose 4x8
{
__m256i _tmp0, _tmp1, _tmp2, _tmp3;
_tmp0 = _mm256_unpacklo_epi32(_sum00_11, _sum10_01);
_tmp1 = _mm256_unpacklo_epi32(_sum02_13, _sum12_03);
_tmp2 = _mm256_unpackhi_epi32(_sum00_11, _sum10_01);
_tmp3 = _mm256_unpackhi_epi32(_sum02_13, _sum12_03);
_sum00_11 = _mm256_unpacklo_epi64(_tmp0, _tmp1);
_sum10_01 = _mm256_unpackhi_epi64(_tmp0, _tmp1);
_sum02_13 = _mm256_unpacklo_epi64(_tmp2, _tmp3);
_sum12_03 = _mm256_unpackhi_epi64(_tmp2, _tmp3);
}
{
__m256i _tmp0, _tmp1, _tmp2, _tmp3;
_tmp0 = _mm256_unpacklo_epi32(_sum04_15, _sum14_05);
_tmp1 = _mm256_unpacklo_epi32(_sum06_17, _sum16_07);
_tmp2 = _mm256_unpackhi_epi32(_sum04_15, _sum14_05);
_tmp3 = _mm256_unpackhi_epi32(_sum06_17, _sum16_07);
_sum04_15 = _mm256_unpacklo_epi64(_tmp0, _tmp1);
_sum14_05 = _mm256_unpackhi_epi64(_tmp0, _tmp1);
_sum06_17 = _mm256_unpacklo_epi64(_tmp2, _tmp3);
_sum16_07 = _mm256_unpackhi_epi64(_tmp2, _tmp3);
}
_sum00_11 = _mm256_add_epi32(_sum00_11, _sum10_01);
_sum02_13 = _mm256_add_epi32(_sum02_13, _sum12_03);
_sum00_11 = _mm256_add_epi32(_sum00_11, _sum02_13);
_sum04_15 = _mm256_add_epi32(_sum04_15, _sum14_05);
_sum06_17 = _mm256_add_epi32(_sum06_17, _sum16_07);
_sum04_15 = _mm256_add_epi32(_sum04_15, _sum06_17);
__m256i _perm_mask = _mm256_set_epi32(6, 3, 4, 1, 7, 2, 5, 0);
_sum00_11 = _mm256_permutevar8x32_epi32(_sum00_11, _perm_mask);
_sum04_15 = _mm256_permutevar8x32_epi32(_sum04_15, _perm_mask);
_mm256_storeu_si256((__m256i*)outptr0, _sum00_11);
_mm256_storeu_si256((__m256i*)(outptr0 + 8), _sum04_15);
outptr0 += 16;
}
#endif
for (; i + 1 < size; i += 2)
{
#if __AVX2__
const signed char* tmpptr = tmp.channel(i / 4 + (i % 4) / 2);
#else
const signed char* tmpptr = tmp.channel(i / 2);
#endif
const signed char* kptr0 = kernel.channel(p);
int nn = inch * maxk; // inch always > 0
#if __AVX2__
__m256i _sum00_11 = _mm256_setzero_si256();
__m256i _sum10_01 = _mm256_setzero_si256();
__m256i _sum02_13 = _mm256_setzero_si256();
__m256i _sum12_03 = _mm256_setzero_si256();
#else
__m128i _sum00 = _mm_setzero_si128();
__m128i _sum01 = _mm_setzero_si128();
__m128i _sum02 = _mm_setzero_si128();
__m128i _sum03 = _mm_setzero_si128();
__m128i _sum10 = _mm_setzero_si128();
__m128i _sum11 = _mm_setzero_si128();
__m128i _sum12 = _mm_setzero_si128();
__m128i _sum13 = _mm_setzero_si128();
#endif
int j = 0;
for (; j < nn; j++)
{
#if __AVX2__
__m128i _val01 = _mm_loadu_si128((const __m128i*)tmpptr);
__m256i _val01_16 = _mm256_cvtepi8_epi16(_val01);
__m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
__m128i _w23 = _mm_loadu_si128((const __m128i*)(kptr0 + 16));
__m256i _w01_16 = _mm256_cvtepi8_epi16(_w01);
__m256i _w23_16 = _mm256_cvtepi8_epi16(_w23);
__m256i _val10_16 = _mm256_permute4x64_epi64(_val01_16, 78);
#if __AVXVNNI__ || __AVX512VNNI__
_sum00_11 = _mm256_dpwssd_epi32(_sum00_11, _val01_16, _w01_16);
_sum10_01 = _mm256_dpwssd_epi32(_sum10_01, _val10_16, _w01_16);
_sum02_13 = _mm256_dpwssd_epi32(_sum02_13, _val01_16, _w23_16);
_sum12_03 = _mm256_dpwssd_epi32(_sum12_03, _val10_16, _w23_16);
#else
__m256i _sl00_11 = _mm256_mullo_epi16(_val01_16, _w01_16);
__m256i _sh00_11 = _mm256_mulhi_epi16(_val01_16, _w01_16);
__m256i _sl10_01 = _mm256_mullo_epi16(_val10_16, _w01_16);
__m256i _sh10_01 = _mm256_mulhi_epi16(_val10_16, _w01_16);
__m256i _sl02_13 = _mm256_mullo_epi16(_val01_16, _w23_16);
__m256i _sh02_13 = _mm256_mulhi_epi16(_val01_16, _w23_16);
__m256i _sl12_03 = _mm256_mullo_epi16(_val10_16, _w23_16);
__m256i _sh12_03 = _mm256_mulhi_epi16(_val10_16, _w23_16);
_sum00_11 = _mm256_add_epi32(_sum00_11, _mm256_unpacklo_epi16(_sl00_11, _sh00_11));
_sum10_01 = _mm256_add_epi32(_sum10_01, _mm256_unpacklo_epi16(_sl10_01, _sh10_01));
_sum02_13 = _mm256_add_epi32(_sum02_13, _mm256_unpacklo_epi16(_sl02_13, _sh02_13));
_sum12_03 = _mm256_add_epi32(_sum12_03, _mm256_unpacklo_epi16(_sl12_03, _sh12_03));
_sum00_11 = _mm256_add_epi32(_sum00_11, _mm256_unpackhi_epi16(_sl00_11, _sh00_11));
_sum10_01 = _mm256_add_epi32(_sum10_01, _mm256_unpackhi_epi16(_sl10_01, _sh10_01));
_sum02_13 = _mm256_add_epi32(_sum02_13, _mm256_unpackhi_epi16(_sl02_13, _sh02_13));
_sum12_03 = _mm256_add_epi32(_sum12_03, _mm256_unpackhi_epi16(_sl12_03, _sh12_03));
#endif
#else
__m128i _val01 = _mm_loadu_si128((const __m128i*)tmpptr);
__m128i _extval01 = _mm_cmpgt_epi8(_mm_setzero_si128(), _val01);
__m128i _val0 = _mm_unpacklo_epi8(_val01, _extval01);
__m128i _val1 = _mm_unpackhi_epi8(_val01, _extval01);
__m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
__m128i _w23 = _mm_loadu_si128((const __m128i*)(kptr0 + 16));
__m128i _extw01 = _mm_cmpgt_epi8(_mm_setzero_si128(), _w01);
__m128i _extw23 = _mm_cmpgt_epi8(_mm_setzero_si128(), _w23);
__m128i _w0 = _mm_unpacklo_epi8(_w01, _extw01);
__m128i _w1 = _mm_unpackhi_epi8(_w01, _extw01);
__m128i _w2 = _mm_unpacklo_epi8(_w23, _extw23);
__m128i _w3 = _mm_unpackhi_epi8(_w23, _extw23);
#if __XOP__
_sum00 = _mm_maddd_epi16(_val0, _w0, _sum00);
_sum01 = _mm_maddd_epi16(_val0, _w1, _sum01);
_sum02 = _mm_maddd_epi16(_val0, _w2, _sum02);
_sum03 = _mm_maddd_epi16(_val0, _w3, _sum03);
_sum10 = _mm_maddd_epi16(_val1, _w0, _sum10);
_sum11 = _mm_maddd_epi16(_val1, _w1, _sum11);
_sum12 = _mm_maddd_epi16(_val1, _w2, _sum12);
_sum13 = _mm_maddd_epi16(_val1, _w3, _sum13);
#else
__m128i _sl00 = _mm_mullo_epi16(_val0, _w0);
__m128i _sh00 = _mm_mulhi_epi16(_val0, _w0);
__m128i _sl01 = _mm_mullo_epi16(_val0, _w1);
__m128i _sh01 = _mm_mulhi_epi16(_val0, _w1);
__m128i _sl02 = _mm_mullo_epi16(_val0, _w2);
__m128i _sh02 = _mm_mulhi_epi16(_val0, _w2);
__m128i _sl03 = _mm_mullo_epi16(_val0, _w3);
__m128i _sh03 = _mm_mulhi_epi16(_val0, _w3);
__m128i _sl10 = _mm_mullo_epi16(_val1, _w0);
__m128i _sh10 = _mm_mulhi_epi16(_val1, _w0);
__m128i _sl11 = _mm_mullo_epi16(_val1, _w1);
__m128i _sh11 = _mm_mulhi_epi16(_val1, _w1);
__m128i _sl12 = _mm_mullo_epi16(_val1, _w2);
__m128i _sh12 = _mm_mulhi_epi16(_val1, _w2);
__m128i _sl13 = _mm_mullo_epi16(_val1, _w3);
__m128i _sh13 = _mm_mulhi_epi16(_val1, _w3);
_sum00 = _mm_add_epi32(_sum00, _mm_unpacklo_epi16(_sl00, _sh00));
_sum01 = _mm_add_epi32(_sum01, _mm_unpacklo_epi16(_sl01, _sh01));
_sum02 = _mm_add_epi32(_sum02, _mm_unpacklo_epi16(_sl02, _sh02));
_sum03 = _mm_add_epi32(_sum03, _mm_unpacklo_epi16(_sl03, _sh03));
_sum00 = _mm_add_epi32(_sum00, _mm_unpackhi_epi16(_sl00, _sh00));
_sum01 = _mm_add_epi32(_sum01, _mm_unpackhi_epi16(_sl01, _sh01));
_sum02 = _mm_add_epi32(_sum02, _mm_unpackhi_epi16(_sl02, _sh02));
_sum03 = _mm_add_epi32(_sum03, _mm_unpackhi_epi16(_sl03, _sh03));
_sum10 = _mm_add_epi32(_sum10, _mm_unpacklo_epi16(_sl10, _sh10));
_sum11 = _mm_add_epi32(_sum11, _mm_unpacklo_epi16(_sl11, _sh11));
_sum12 = _mm_add_epi32(_sum12, _mm_unpacklo_epi16(_sl12, _sh12));
_sum13 = _mm_add_epi32(_sum13, _mm_unpacklo_epi16(_sl13, _sh13));
_sum10 = _mm_add_epi32(_sum10, _mm_unpackhi_epi16(_sl10, _sh10));
_sum11 = _mm_add_epi32(_sum11, _mm_unpackhi_epi16(_sl11, _sh11));
_sum12 = _mm_add_epi32(_sum12, _mm_unpackhi_epi16(_sl12, _sh12));
_sum13 = _mm_add_epi32(_sum13, _mm_unpackhi_epi16(_sl13, _sh13));
#endif
#endif
tmpptr += 16;
kptr0 += 32;
}
#if __AVX2__
// transpose 4x8
{
__m256i _tmp0, _tmp1, _tmp2, _tmp3;
_tmp0 = _mm256_unpacklo_epi32(_sum00_11, _sum10_01);
_tmp1 = _mm256_unpacklo_epi32(_sum02_13, _sum12_03);
_tmp2 = _mm256_unpackhi_epi32(_sum00_11, _sum10_01);
_tmp3 = _mm256_unpackhi_epi32(_sum02_13, _sum12_03);
_sum00_11 = _mm256_unpacklo_epi64(_tmp0, _tmp1);
_sum10_01 = _mm256_unpackhi_epi64(_tmp0, _tmp1);
_sum02_13 = _mm256_unpacklo_epi64(_tmp2, _tmp3);
_sum12_03 = _mm256_unpackhi_epi64(_tmp2, _tmp3);
}
_sum00_11 = _mm256_add_epi32(_sum00_11, _sum10_01);
_sum02_13 = _mm256_add_epi32(_sum02_13, _sum12_03);
_sum00_11 = _mm256_add_epi32(_sum00_11, _sum02_13);
__m256i _perm_mask = _mm256_set_epi32(6, 3, 4, 1, 7, 2, 5, 0);
_sum00_11 = _mm256_permutevar8x32_epi32(_sum00_11, _perm_mask);
_mm256_storeu_si256((__m256i*)outptr0, _sum00_11);
#else
// transpose 4x4
{
__m128i _tmp0, _tmp1, _tmp2, _tmp3;
_tmp0 = _mm_unpacklo_epi32(_sum00, _sum01);
_tmp1 = _mm_unpacklo_epi32(_sum02, _sum03);
_tmp2 = _mm_unpackhi_epi32(_sum00, _sum01);
_tmp3 = _mm_unpackhi_epi32(_sum02, _sum03);
_sum00 = _mm_unpacklo_epi64(_tmp0, _tmp1);
_sum01 = _mm_unpackhi_epi64(_tmp0, _tmp1);
_sum02 = _mm_unpacklo_epi64(_tmp2, _tmp3);
_sum03 = _mm_unpackhi_epi64(_tmp2, _tmp3);
}
{
__m128i _tmp0, _tmp1, _tmp2, _tmp3;
_tmp0 = _mm_unpacklo_epi32(_sum10, _sum11);
_tmp1 = _mm_unpacklo_epi32(_sum12, _sum13);
_tmp2 = _mm_unpackhi_epi32(_sum10, _sum11);
_tmp3 = _mm_unpackhi_epi32(_sum12, _sum13);
_sum10 = _mm_unpacklo_epi64(_tmp0, _tmp1);
_sum11 = _mm_unpackhi_epi64(_tmp0, _tmp1);
_sum12 = _mm_unpacklo_epi64(_tmp2, _tmp3);
_sum13 = _mm_unpackhi_epi64(_tmp2, _tmp3);
}
_sum00 = _mm_add_epi32(_sum00, _sum01);
_sum02 = _mm_add_epi32(_sum02, _sum03);
_sum10 = _mm_add_epi32(_sum10, _sum11);
_sum12 = _mm_add_epi32(_sum12, _sum13);
_sum00 = _mm_add_epi32(_sum00, _sum02);
_sum10 = _mm_add_epi32(_sum10, _sum12);
_mm_storeu_si128((__m128i*)outptr0, _sum00);
_mm_storeu_si128((__m128i*)(outptr0 + 4), _sum10);
#endif
outptr0 += 8;
}
for (; i < size; i++)
{
#if __AVX2__
const signed char* tmpptr = tmp.channel(i / 4 + (i % 4) / 2 + i % 2);
#else
const signed char* tmpptr = tmp.channel(i / 2 + i % 2);
#endif
const signed char* kptr0 = kernel.channel(p);
int nn = inch * maxk; // inch always > 0
#if __AVX2__
__m256i _sum0_1 = _mm256_setzero_si256();
__m256i _sum2_3 = _mm256_setzero_si256();
#else
__m128i _sum0 = _mm_setzero_si128();
__m128i _sum1 = _mm_setzero_si128();
__m128i _sum2 = _mm_setzero_si128();
__m128i _sum3 = _mm_setzero_si128();
#endif
int j = 0;
for (; j < nn; j++)
{
#if __AVX2__
__m128i _val = _mm_loadl_epi64((const __m128i*)tmpptr);
_val = _mm_cvtepi8_epi16(_val);
__m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
__m128i _w23 = _mm_loadu_si128((const __m128i*)(kptr0 + 16));
__m256i _w01_16 = _mm256_cvtepi8_epi16(_w01);
__m256i _w23_16 = _mm256_cvtepi8_epi16(_w23);
__m256i _valval = _mm256_inserti128_si256(_mm256_castsi128_si256(_val), _val, 1);
#if __AVXVNNI__ || __AVX512VNNI__
_sum0_1 = _mm256_dpwssd_epi32(_sum0_1, _valval, _w01_16);
_sum2_3 = _mm256_dpwssd_epi32(_sum2_3, _valval, _w23_16);
#else
__m256i _sl0_1 = _mm256_mullo_epi16(_valval, _w01_16);
__m256i _sh0_1 = _mm256_mulhi_epi16(_valval, _w01_16);
__m256i _sl2_3 = _mm256_mullo_epi16(_valval, _w23_16);
__m256i _sh2_3 = _mm256_mulhi_epi16(_valval, _w23_16);
_sum0_1 = _mm256_add_epi32(_sum0_1, _mm256_unpacklo_epi16(_sl0_1, _sh0_1));
_sum2_3 = _mm256_add_epi32(_sum2_3, _mm256_unpacklo_epi16(_sl2_3, _sh2_3));
_sum0_1 = _mm256_add_epi32(_sum0_1, _mm256_unpackhi_epi16(_sl0_1, _sh0_1));
_sum2_3 = _mm256_add_epi32(_sum2_3, _mm256_unpackhi_epi16(_sl2_3, _sh2_3));
#endif
#else
__m128i _val = _mm_loadl_epi64((const __m128i*)tmpptr);
#if __SSE4_1__
_val = _mm_cvtepi8_epi16(_val);
#else
_val = _mm_unpacklo_epi8(_val, _mm_cmpgt_epi8(_mm_setzero_si128(), _val));
#endif
__m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
__m128i _w23 = _mm_loadu_si128((const __m128i*)(kptr0 + 16));
__m128i _extw01 = _mm_cmpgt_epi8(_mm_setzero_si128(), _w01);
__m128i _extw23 = _mm_cmpgt_epi8(_mm_setzero_si128(), _w23);
__m128i _w0 = _mm_unpacklo_epi8(_w01, _extw01);
__m128i _w1 = _mm_unpackhi_epi8(_w01, _extw01);
__m128i _w2 = _mm_unpacklo_epi8(_w23, _extw23);
__m128i _w3 = _mm_unpackhi_epi8(_w23, _extw23);
#if __XOP__
_sum0 = _mm_maddd_epi16(_val, _w0, _sum0);
_sum1 = _mm_maddd_epi16(_val, _w1, _sum1);
_sum2 = _mm_maddd_epi16(_val, _w2, _sum2);
_sum3 = _mm_maddd_epi16(_val, _w3, _sum3);
#else
__m128i _sl0 = _mm_mullo_epi16(_val, _w0);
__m128i _sh0 = _mm_mulhi_epi16(_val, _w0);
__m128i _sl1 = _mm_mullo_epi16(_val, _w1);
__m128i _sh1 = _mm_mulhi_epi16(_val, _w1);
__m128i _sl2 = _mm_mullo_epi16(_val, _w2);
__m128i _sh2 = _mm_mulhi_epi16(_val, _w2);
__m128i _sl3 = _mm_mullo_epi16(_val, _w3);
__m128i _sh3 = _mm_mulhi_epi16(_val, _w3);
_sum0 = _mm_add_epi32(_sum0, _mm_unpacklo_epi16(_sl0, _sh0));
_sum1 = _mm_add_epi32(_sum1, _mm_unpacklo_epi16(_sl1, _sh1));
_sum2 = _mm_add_epi32(_sum2, _mm_unpacklo_epi16(_sl2, _sh2));
_sum3 = _mm_add_epi32(_sum3, _mm_unpacklo_epi16(_sl3, _sh3));
_sum0 = _mm_add_epi32(_sum0, _mm_unpackhi_epi16(_sl0, _sh0));
_sum1 = _mm_add_epi32(_sum1, _mm_unpackhi_epi16(_sl1, _sh1));
_sum2 = _mm_add_epi32(_sum2, _mm_unpackhi_epi16(_sl2, _sh2));
_sum3 = _mm_add_epi32(_sum3, _mm_unpackhi_epi16(_sl3, _sh3));
#endif
#endif
tmpptr += 8;
kptr0 += 32;
}
#if __AVX2__
__m128i _sum0 = _mm256_extracti128_si256(_sum0_1, 0);
__m128i _sum1 = _mm256_extracti128_si256(_sum0_1, 1);
__m128i _sum2 = _mm256_extracti128_si256(_sum2_3, 0);
__m128i _sum3 = _mm256_extracti128_si256(_sum2_3, 1);
#endif
// transpose 4x4
{
__m128i _tmp0, _tmp1, _tmp2, _tmp3;
_tmp0 = _mm_unpacklo_epi32(_sum0, _sum1);
_tmp1 = _mm_unpacklo_epi32(_sum2, _sum3);
_tmp2 = _mm_unpackhi_epi32(_sum0, _sum1);
_tmp3 = _mm_unpackhi_epi32(_sum2, _sum3);
_sum0 = _mm_unpacklo_epi64(_tmp0, _tmp1);
_sum1 = _mm_unpackhi_epi64(_tmp0, _tmp1);
_sum2 = _mm_unpacklo_epi64(_tmp2, _tmp3);
_sum3 = _mm_unpackhi_epi64(_tmp2, _tmp3);
}
_sum0 = _mm_add_epi32(_sum0, _sum1);
_sum2 = _mm_add_epi32(_sum2, _sum3);
_sum0 = _mm_add_epi32(_sum0, _sum2);
_mm_storeu_si128((__m128i*)outptr0, _sum0);
outptr0 += 4;
}
}
}
static void convolution_im2col_sgemm_transform_kernel_pack8to4_int8_sse(const Mat& _kernel, Mat& kernel_tm, int inch, int outch, int kernel_w, int kernel_h)
{
const int maxk = kernel_w * kernel_h;
// interleave
// src = maxk-inch-outch
// dst = 8a-4b-maxk-inch/8a-outch/4b
Mat kernel = _kernel.reshape(maxk, inch, outch);
kernel_tm.create(32 * maxk, inch / 8, outch / 4, (size_t)1u);
for (int q = 0; q + 3 < outch; q += 4)
{
signed char* g00 = kernel_tm.channel(q / 4);
for (int p = 0; p + 7 < inch; p += 8)
{
for (int k = 0; k < maxk; k++)
{
for (int i = 0; i < 4; i++)
{
for (int j = 0; j < 8; j++)
{
const signed char* k00 = kernel.channel(q + i).row<const signed char>(p + j);
g00[0] = k00[k];
g00++;
}
}
}
}
}
}
static void convolution_im2col_sgemm_pack8to4_int8_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, int kernel_w, int kernel_h, int dilation_w, int dilation_h, int stride_w, int stride_h, const Option& opt)
{
int w = bottom_blob.w;
int inch = bottom_blob.c;
int outw = top_blob.w;
int outh = top_blob.h;
const int size = outw * outh;
const int maxk = kernel_w * kernel_h;
// im2col
Mat bottom_im2col(size, maxk, inch, 8u, 8, opt.workspace_allocator);
{
const int gap = w * stride_h - outw * stride_w;
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < inch; p++)
{
const Mat img = bottom_blob.channel(p);
int64_t* ptr = bottom_im2col.channel(p);
for (int u = 0; u < kernel_h; u++)
{
for (int v = 0; v < kernel_w; v++)
{
const int64_t* sptr = img.row<const int64_t>(dilation_h * u) + dilation_w * v;
for (int i = 0; i < outh; i++)
{
int j = 0;
for (; j < outw; j++)
{
ptr[0] = sptr[0];
sptr += stride_w;
ptr += 1;
}
sptr += gap;
}
}
}
}
}
im2col_sgemm_pack8to4_int8_sse(bottom_im2col, top_blob, kernel, opt);
}
|
Fig_8.2_race.c | #include <omp.h>
#include <assert.h>
#include <stdlib.h>
int main()
{
int x = 0, y = 0, r = 0;
omp_set_num_threads(2); // request two threads
#pragma omp parallel
{
int id = omp_get_thread_num();
#pragma omp single
{
int nthrds = omp_get_num_threads();
// verify that we have at least two threads
if (nthrds < 2) exit(1);
} // end of single region
if (id == 0) {
x = 1;
r = x;
}
else if (id == 1) {
if (r == 1) {
y = x;
assert (y == 1); // Assertion will occasionally fail;
// i.e., r == 1 while x == 0
}
}
} // end of parallel region
}
|
md-core.c | /******************************************************************************/
/* */
/* Molecular dynamics */
/* ================== */
/* */
/* Copyright (c) 2017 Ruben Felgenhauer, Leonhard Reichenbach */
/* */
/* This file is released under the MIT license. */
/* */
/******************************************************************************/
#include "md-core.h"
void seed() {
struct timeval time;
gettimeofday(&time, NULL);
srand48(((unsigned long long)time.tv_sec * 1000000) + time.tv_usec);
}
/**
* The Lennard Jones potential between two molecules
* @param r the distance between the two molecules
* @return the resulting potential
*/
static double lennjo_potential(double r) {
return 4 * (1/pow(r,12) - 1/pow(r,6));
}
/**
* The force that gets induced by the Lennard jones potential
* @param r the distance between the two molecules
* @return The resulting force
*/
static double lennjo_force(double r) {
return 24 * (2/pow(r,13) - 1/pow(r,7));
}
/**
* Returns a vector from the given coordinates (that also contains the length
* of the vector).
* @param x the x coordinate
* @param y the y coordinate
* @return the resulting vector
*/
static Vector build_vector(double x, double y) {
Vector result;
result.coordinates.x = x;
result.coordinates.y = y;
result.length = sqrt(x*x + y*y);
return result;
}
/**
* Determines the distance between two molecules.
* @param first the first position
* @param second the second position
* @param L the length of the square distance
* @param periodic_boundaries whether to use periodic boundaries
* @return the distance vector
*/
static Vector distance(const Coordinates *first, const Coordinates *second,
SimParams *params) {
double dx = second->x - first->x;
double dy = second->y - first->y;
if (params->periodic_boundaries) {
double L = params->L;
if (fabs(dx) > L / 2) {
dx = dx - copysign(1.0, dx) * L;
}
if (fabs(dy) > L / 2) {
dy = dy - copysign(1.0, dy) * L;
}
}
return build_vector(dx, dy);
}
/**
* Gathers the kinetic energy, potential energy, total energy and temperature
* of the system and writes that data back into their corresponding members
* of data.
* @param data The simulation data
* @param params The simulation parameters
*/
void get_statistics(SimData *data, SimParams *params) {
double Epot = 0.0;
double Ekin = 0.0;
for (uint64_t i=0; i < params->N; i++) {
for (uint64_t j=i+1; j < params->N; j++) {
Vector dist = distance(&(data->molecules[i].curr_pos),
&(data->molecules[j].curr_pos), params);
if(params->dist_threshold == 0.0 || dist.length <= params->dist_threshold){
Epot += lennjo_potential(dist.length);
}
}
Ekin += (data->molecules[i].vel.x * data->molecules[i].vel.x
+ data->molecules[i].vel.y * data->molecules[i].vel.y) / 2;
}
data->kinetic_energy = Ekin;
data->potential_energy = Epot;
data->energy = Ekin + Epot;
data->temperature = Ekin / params->N;
}
/**
* Initializes the molecules array
* @param params the simulation parameters to use
* @return the molecules
*/
static Molecule *init_molecules(SimParams *params) {
Molecule *molecules = malloc(params->N * sizeof(Molecule));
ASSERT(molecules, "Could not initialize molecules");
uint64_t grid_size = ceil(sqrt(params->N));
double grid_dist = params->L / ((double)grid_size);
for (uint64_t i = 0; i < params->N; i++) {
double x_curr = ((((double)(i % grid_size)) + 0.5)
+ params->max_deviation * (drand48() - 0.5) * sqrt(2)) * grid_dist;
double y_curr = ((((double)(i / grid_size)) + 0.5)
+ params->max_deviation * (drand48() - 0.5) * sqrt(2)) * grid_dist;
double v_x = params->max_v0 * (drand48() - 0.5) * sqrt(2);
double v_y = params->max_v0 * (drand48() - 0.5) * sqrt(2);
double x_prev = x_curr - v_x * params->timestep;
double y_prev = y_curr - v_y * params->timestep;
Molecule molecule;
molecule.curr_pos.x = x_curr;
molecule.curr_pos.y = y_curr;
molecule.prev_pos.x = x_prev;
molecule.prev_pos.y = y_prev;
molecule.vel.x = v_x;
molecule.vel.y = v_y;
molecules[i] = molecule;
}
return molecules;
}
void calculate_forces(SimData *data, SimParams *params){
#pragma omp for simd
for (uint64_t i = 0; i < params->N-1; i++) {
for (uint64_t j = i + 1; j < params->N; j++) {
Vector dist = distance(&(data->molecules[i].curr_pos),
&(data->molecules[j].curr_pos),
params);
Coordinates *force_ij = &(data->forces_buffer[i][j]);
Coordinates *force_ji = &(data->forces_buffer[j][i]);
if(dist.length > 0.0 && (params->dist_threshold == 0.0
|| dist.length <= params->dist_threshold)){
double force = lennjo_force(dist.length);
double force_x = force * dist.coordinates.x / dist.length;
double force_y = force * dist.coordinates.y / dist.length;
force_ij->x = force_x;
force_ij->y = force_y;
force_ji->x = -force_x;
force_ji->y = -force_y;
} else {
force_ij->x = 0.0;
force_ij->y = 0.0;
force_ji->x = 0.0;
force_ji->y = 0.0;
}
}
}
}
/**
* Calculates the total force F_i that affects a particle i. This is just the sum
* of all forces F_j,i that act on a particle.
* @param data the simulation data
* @param params the simulation params
* @param i The index of the particle to get the force for.
* @return the resulting force.
*/
static Coordinates get_total_force(SimData *data, SimParams *params, uint64_t i) {
Coordinates result = {.x = 0.0, .y = 0.0};
for (uint64_t j = 0; j < params->N; j++) {
result.x += data->forces_buffer[j][i].x;
result.y += data->forces_buffer[j][i].y;
}
return result;
}
/**
* Corrects a position so that 0 <= position <= L.
* @param curr the current position that is going to be positioned the same way
* relatively to next that it was before the correction was applies. This
* might include putting curr on the other side of next with the same
* distance if the movement of direction is being flipped during
* elastic reflection (if periodic_boundaries == false).
* @param next the next position (the one to correct). If periodic_boundaries,
* next will be teleported to the other side of the lattice. Otherwise,
* it will be reflected elastically.
* @param params the simulation params, including L and periodic_boundaries.
*/
static void fix_boundaries(double *curr, double *next, SimParams *params) {
double L = params->L;
if (*next > L || *next < 0) {
// We'll need this to correct the current position later
double curr_to_next = *next - *curr;
if (params->periodic_boundaries) {
if (*next > L) {
// fmod should return a value between 0.0 and L here.
*next = fmod(*next, L);
} else {
// fmod should return a value between -L and 0.0 here, so position should
// mathematically be between 0.0 and and L, but numerical errors do happen.
*next = L + fmod(*next, L);
// The >= is there to catch numerical errors. The distance to L should be
// at the order of magnitude of machine accuracy. Position can not be greater
// than L mathematically at this point.
if (*next >= L) {
*next = 0.0;
}
}
} else { /* Reflective walls */
double dist_to_border = *next > L ? L - *curr : *curr;
// The distance that remains after the first collision
double rem_initial = fabs(curr_to_next) - dist_to_border;
// The distance that remains after the last collision, if there is going
// to be more than one, according to the velocity.
double rem_final = fmod(rem_initial, L);
// We'll need to turn the direction of movement around, if the particle
// reflects an odd amount of times with any walls.
bool keep_direction = (bool)((int)((rem_initial - rem_final) / L) % 2);
// Determine at which border the particle is going to be placed
if (keep_direction == (*next > L)) {
*next = rem_final;
} else {
*next = L - rem_final;
}
// Determine on which side curr is going to be placed
if (!keep_direction) {
curr_to_next *= -1;
}
}
// Correct curr.
*curr = *next - curr_to_next;
}
}
void apply_forces(SimData *data, SimParams *params){
double squared_timestep = params->timestep * params->timestep;
#pragma omp for simd
for(uint64_t i = 0; i < params->N; i++) {
Coordinates force = get_total_force(data, params, i);
Coordinates *prev_pos = &(data->molecules[i].prev_pos);
Coordinates *curr_pos = &(data->molecules[i].curr_pos);
Coordinates next_pos = {.x = 2 * curr_pos->x - prev_pos->x
+ force.x * squared_timestep,
.y = 2 * curr_pos->y - prev_pos->y
+ force.y * squared_timestep};
data->molecules[i].vel.x = (next_pos.x - prev_pos->x)
/ (2 * params->timestep);
data->molecules[i].vel.y = (next_pos.y - prev_pos->y)
/ (2 * params->timestep);
fix_boundaries(&(curr_pos->x), &(next_pos.x), params);
fix_boundaries(&(curr_pos->y), &(next_pos.y), params);
*prev_pos = *curr_pos;
*curr_pos = next_pos;
}
}
void enable_heat_bath(SimData *data, double target_temperature, uint64_t steps) {
ASSERT(steps, "Steps must be greater than 0");
double alpha_tilde = 3.0;
HeatBath heat_bath;
heat_bath.alpha_tilde = alpha_tilde;
heat_bath.steps_to_the_alpha_tilde = pow(steps, alpha_tilde);
heat_bath.steps = steps;
heat_bath.current_step = 1;
heat_bath.target_temperature = target_temperature;
data->heat_bath = heat_bath;
data->heat_bath_enabled = true;
}
void multiply_velocity(double *curr_pos, double *prev_pos, double *vel, double factor) {
*prev_pos = *curr_pos - (*curr_pos - *prev_pos) * factor;
*vel *= factor;
}
void apply_heat_bath(SimData *data, SimParams *params) {
HeatBath *heat_bath = &(data->heat_bath);
double foo1 = pow(heat_bath->current_step, heat_bath->alpha_tilde);
double foo2 = foo1 / heat_bath->steps_to_the_alpha_tilde;
double foo3 = heat_bath->target_temperature / data->temperature;
double foo4 = pow(foo3, foo2);
for (uint64_t i = 0; i < params->N; i++) {
Coordinates *prev_pos = &(data->molecules[i].prev_pos);
Coordinates *curr_pos = &(data->molecules[i].curr_pos);
Coordinates *vel = &(data->molecules[i].vel);
multiply_velocity(&(curr_pos->x), &(prev_pos->x), &(vel->x), foo4);
multiply_velocity(&(curr_pos->y), &(prev_pos->y), &(vel->y), foo4);
}
if (++(heat_bath->current_step) > heat_bath->steps) {
data->heat_bath_enabled = false;
}
}
void step(SimData *data, SimParams *params) {
#pragma omp parallel
calculate_forces(data, params);
apply_forces(data, params);
get_statistics(data, params);
if (data->heat_bath_enabled) {
apply_heat_bath(data, params);
}
}
SimData init_data(SimParams *params) {
SimData result;
result.molecules = init_molecules(params);
result.forces_buffer = malloc(sizeof(Coordinates*) * params->N);
ASSERT(result.forces_buffer, "Could not allocate memory for forces buffer");
for (uint64_t i = 0; i < params->N; i++) {
result.forces_buffer[i] = malloc(sizeof(Coordinates) * params->N);
ASSERT(result.forces_buffer[i], "Could not allocate memory for forces buffer");
result.forces_buffer[i][i].x = 0.0;
result.forces_buffer[i][i].y = 0.0;
}
result.heat_bath_enabled = false;
return result;
}
SimParams init_params(uint64_t number_of_threads, uint64_t N,
double L, double timestep, double max_deviation,
double max_v0, bool periodic_boundaries, double dist_threshold,
uint64_t iterations) {
SimParams result;
result.number_of_threads = number_of_threads;
result.N = N;
result.L = L;
result.timestep = timestep;
result.max_deviation = max_deviation;
result.max_v0 = max_v0;
result.periodic_boundaries = periodic_boundaries;
result.dist_threshold = dist_threshold;
result.iterations = iterations;
omp_set_num_threads(number_of_threads);
return result;
}
void finalize(SimData *data, SimParams *params) {
free(data->molecules);
for (uint64_t i = 0; i < params->N; i++) {
free(data->forces_buffer[i]);
}
free(data->forces_buffer);
}
|
5341.c | /* POLYBENCH/GPU-OPENMP
*
* This file is a part of the Polybench/GPU-OpenMP suite
*
* Contact:
* William Killian <killian@udel.edu>
*
* Copyright 2013, The University of Delaware
*/
#include <stdio.h>
#include <unistd.h>
#include <string.h>
#include <math.h>
/* Include polybench common header. */
#include <polybench.h>
/* Include benchmark-specific header. */
/* Default data type is double, default size is 4000. */
#include "atax.h"
/* Array initialization. */
static
void init_array (int nx, int ny,
DATA_TYPE POLYBENCH_2D(A,NX,NY,nx,ny),
DATA_TYPE POLYBENCH_1D(x,NY,ny))
{
int i, j;
for (i = 0; i < ny; i++)
x[i] = i * M_PI;
for (i = 0; i < nx; i++)
for (j = 0; j < ny; j++)
A[i][j] = ((DATA_TYPE) i*(j+1)) / nx;
}
/* DCE code. Must scan the entire live-out data.
Can be used also to check the correctness of the output. */
static
void print_array(int nx,
DATA_TYPE POLYBENCH_1D(y,NX,nx))
{
int i;
for (i = 0; i < nx; i++) {
fprintf (stderr, DATA_PRINTF_MODIFIER, y[i]);
if (i % 20 == 0) fprintf (stderr, "\n");
}
fprintf (stderr, "\n");
}
/* Main computational kernel. The whole function will be timed,
including the call and return. */
static
void kernel_atax(int nx, int ny,
DATA_TYPE POLYBENCH_2D(A,NX,NY,nx,ny),
DATA_TYPE POLYBENCH_1D(x,NY,ny),
DATA_TYPE POLYBENCH_1D(y,NY,ny),
DATA_TYPE POLYBENCH_1D(tmp,NX,nx))
{
int i, j;
#pragma scop
#pragma omp parallel
{
#pragma omp parallel for schedule(static, 16) num_threads(4)
for (i = 0; i < _PB_NY; i++)
y[i] = 0;
#pragma omp parallel for private (j) schedule(static, 16) num_threads(4)
for (i = 0; i < _PB_NX; i++)
{
tmp[i] = 0;
for (j = 0; j < _PB_NY; j++)
tmp[i] = tmp[i] + A[i][j] * x[j];
for (j = 0; j < _PB_NY; j++)
y[j] = y[j] + A[i][j] * tmp[i];
}
}
#pragma endscop
}
int main(int argc, char** argv)
{
/* Retrieve problem size. */
int nx = NX;
int ny = NY;
/* Variable declaration/allocation. */
POLYBENCH_2D_ARRAY_DECL(A, DATA_TYPE, NX, NY, nx, ny);
POLYBENCH_1D_ARRAY_DECL(x, DATA_TYPE, NY, ny);
POLYBENCH_1D_ARRAY_DECL(y, DATA_TYPE, NY, ny);
POLYBENCH_1D_ARRAY_DECL(tmp, DATA_TYPE, NX, nx);
/* Initialize array(s). */
init_array (nx, ny, POLYBENCH_ARRAY(A), POLYBENCH_ARRAY(x));
/* Start timer. */
polybench_start_instruments;
/* Run kernel. */
kernel_atax (nx, ny,
POLYBENCH_ARRAY(A),
POLYBENCH_ARRAY(x),
POLYBENCH_ARRAY(y),
POLYBENCH_ARRAY(tmp));
/* Stop and print timer. */
polybench_stop_instruments;
polybench_print_instruments;
/* Prevent dead-code elimination. All live-out data must be printed
by the function call in argument. */
polybench_prevent_dce(print_array(nx, POLYBENCH_ARRAY(y)));
/* Be clean. */
POLYBENCH_FREE_ARRAY(A);
POLYBENCH_FREE_ARRAY(x);
POLYBENCH_FREE_ARRAY(y);
POLYBENCH_FREE_ARRAY(tmp);
return 0;
}
|
SoftmaxLoss.h | #ifndef SOFTMAXLOSS_H
#define SOFTMAXLOSS_H
#include <Eigen/Dense>
#include "multinomial.h"
#include "util.h"
namespace nplm
{
// is this cheating?
using Eigen::Matrix;
using Eigen::MatrixBase;
using Eigen::Dynamic;
///// Softmax layer plus log-loss function.
enum loss_function_type { LogLoss, NCELoss, InvalidLoss };
inline loss_function_type string_to_loss_function (const std::string &s)
{
if (s == "log")
return LogLoss;
else if (s == "nce")
return NCELoss;
else
return InvalidLoss;
}
inline std::string loss_function_to_string (loss_function_type f)
{
if (f == LogLoss)
return "log";
else if (f == NCELoss)
return "nce";
}
/// Note: Outputs log-probabilities.
struct SoftmaxLogLoss
{
template <typename DerivedI, typename DerivedW, typename DerivedO>
void fProp(const MatrixBase<DerivedI> &input, const MatrixBase<DerivedW> &output_words, const MatrixBase<DerivedO> &output_const, user_data_t &loss)
{
UNCONST(DerivedO, output_const, output);
user_data_t log_likelihood = 0.0;
#pragma omp parallel for reduction(+:log_likelihood)
for (int train_id = 0; train_id < input.cols(); train_id++)
{
user_data_t normalization = logsum(input.col(train_id));
output.col(train_id).array() = input.col(train_id).array() - normalization;
log_likelihood += output(output_words(train_id), train_id);
}
loss = log_likelihood;
}
template <typename DerivedW, typename DerivedO, typename DerivedI>
void bProp(const MatrixBase<DerivedW> &output_words, const MatrixBase<DerivedO> &output, const MatrixBase<DerivedI> &grad_input_const)
{
UNCONST(DerivedI, grad_input_const, grad_input);
grad_input.setZero();
#pragma omp parallel for
for (int train_id = 0; train_id < output.cols(); train_id++)
{
grad_input(output_words(train_id), train_id) += 1.;
grad_input.col(train_id) -= output.col(train_id).array().exp().matrix();
}
}
};
///// Softmax layer plus NCE loss function.
///// Note: Outputs probabilities.
///// Note: Unlike SoftmaxLogLoss, does not compute *or* apply precomputed
///// normalizations. Currently the caller is expected to do normalization.
template <typename Multinomial>
class SoftmaxNCELoss
{
const Multinomial &unigram;
public:
SoftmaxNCELoss(const Multinomial &unigram)
: unigram(unigram)
{
}
template <typename DerivedI, typename DerivedW, typename DerivedO>
void fProp(const MatrixBase<DerivedI> &scores,
const MatrixBase<DerivedW> &minibatch_samples,
const MatrixBase<DerivedO> &output_const, user_data_t &loss)
{
UNCONST(DerivedO, output_const, output);
user_data_t log_likelihood = 0.0;
int num_noise_samples = minibatch_samples.rows()-1;
user_data_t log_num_noise_samples = std::log(num_noise_samples);
#pragma omp parallel for reduction(+:log_likelihood) schedule(static)
for (int train_id = 0; train_id < scores.cols(); train_id++)
{
for (int sample_id = 0;sample_id < minibatch_samples.rows(); sample_id++)
{
int sample = minibatch_samples(sample_id, train_id);
// To avoid zero or infinite probabilities,
// never take exp of score without normalizing first,
// even if it's a little slower...
user_data_t score = scores(sample_id, train_id);
user_data_t score_noise = log_num_noise_samples + unigram.logprob(sample);
user_data_t z = logadd(score, score_noise);
user_data_t logprob = score - z;
user_data_t logprob_noise = score_noise - z;
output(sample_id, train_id) = std::exp(logprob);
log_likelihood += sample_id == 0 ? logprob : logprob_noise;
}
}
loss = log_likelihood;
}
template <typename DerivedO, typename DerivedI>
void bProp(const MatrixBase<DerivedO> &probs, const MatrixBase<DerivedI> &output_const)
{
UNCONST(DerivedI, output_const, output);
#pragma omp parallel for schedule(static)
for (int train_id = 0; train_id < probs.cols(); train_id++)
{
output.col(train_id) = -probs.col(train_id);
output(0, train_id) += 1.0;
}
}
};
} // namespace nplm
#endif
|
critical.c | /*
* critical.c -- Archer testcase
*/
//===----------------------------------------------------------------------===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
//
// See tools/archer/LICENSE.txt for details.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
// RUN: %libarcher-compile-and-run | FileCheck %s
#include <omp.h>
#include <stdio.h>
int main(int argc, char *argv[]) {
int var = 0;
#pragma omp parallel num_threads(8) shared(var)
{
#pragma omp critical
{ var++; }
}
fprintf(stderr, "DONE\n");
int error = (var != 8);
return error;
}
// CHECK-NOT: ThreadSanitizer: data race
// CHECK-NOT: ThreadSanitizer: reported
// CHECK: DONE
|
main.c | #include <omp.h>
#define MAX_NUMBER_OF_ELEMENTS 10
int main ()
{
int i;
int threadID, totalNumberThreads;
float vectorA[MAX_NUMBER_OF_ELEMENTS], vectorB[MAX_NUMBER_OF_ELEMENTS],
vectorC[MAX_NUMBER_OF_ELEMENTS], vectorD[MAX_NUMBER_OF_ELEMENTS];
// data initialization
for (i=0; i < MAX_NUMBER_OF_ELEMENTS; i++)
{
vectorA[i] = i * 1.5;
vectorB[i] = i + 22.35;
}
omp_set_num_threads(16);
#pragma omp parallel shared(vectorA,vectorB,vectorC,vectorD)\
private(i, threadID, totalNumberThreads)
{
threadID = omp_get_thread_num();
totalNumberThreads = omp_get_num_threads();
#pragma omp sections nowait
{
#pragma omp section
for (i=0; i < MAX_NUMBER_OF_ELEMENTS; i++)
{
vectorC[i] = vectorA[i] + vectorB[i];
printf("Thread %d of %d calculates i = %d (section 1)\n", threadID, totalNumberThreads, i);
}
#pragma omp section
for (i=0; i < MAX_NUMBER_OF_ELEMENTS; i++)
{
vectorD[i] = vectorA[i] * vectorB[i];
printf("Thread %d of %d calculates i = %d (section 2)\n", threadID, totalNumberThreads, i);
}
} /* end of sections */
} /* end of parallel section */
return 0;
}
|
minmax.h | #ifndef MINMAX_H
#define MINMAX_H
#include <limits.h>
#include <sys/time.h>
#include "matrix.h"
ull minmax(ull r, // Matrix rows
ull c, // Matrix cols
ul threads)
{
timeval start, end;
matrix* A = alloc(r, c);
T maximum = MINIMUM;
fill(A);
gettimeofday(&start, NULL);
/**
* Find maximum value of all rows' minimums
*/
{
ull i = 0, j = 0;
#pragma omp parallel for reduction(max: maximum) private(i, j) shared(A) num_threads(threads)
iterate(, i, A->rows) {
T minimum = A(i, 0);
#pragma omp parallel for reduction(min: minimum) private(j) shared(A) num_threads(threads)
iterate(, j, A->cols) {
if (A(i, j) < minimum) { minimum = A(i, j); }
}
if (minimum > maximum) { maximum = minimum; }
}
}
gettimeofday(&end, NULL);
printf("\tResult: ");
printf(TOKEN, maximum);
#ifdef WRITE
write(A, "minmax.txt");
printf("\tMatrix is written to `minmax.txt`\n");
#endif
dealloc(A);
return ELAPSED;
}
#endif // MINMAX_H
|
conv_dw_kernel_mips.c | /*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* License); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* AS IS BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
/*
* Copyright (c) 2021, OPEN AI LAB
* Author: qtang@openailab.com
*/
#include "conv_dw_kernel_mips.h"
#include <stdint.h>
#include <stdlib.h>
#include <math.h>
#define max(a, b) ((a) > (b) ? (a) : (b))
#define min(a, b) ((a) < (b) ? (a) : (b))
void relu(float* data, int size, int activation)
{
for(int i = 0; i < size; i++)
{
data[i] = max(data[i], ( float )0);
if(activation > 0)
{
data[i] = min(data[i], ( float )activation);
}
}
}
void convdw3x3s1(float* output, float* input, float* _kernel, float* _bias, int channel, int in_h, int in_w, int out_h, int out_w, int num_thread)
{
int w = in_w;
int h = in_h;
int c_step_in = w * h;
int outw = out_w;
int outh = out_h;
int c_step_out = outw * outh;
const int group = channel;
const float* kernel = _kernel;
#pragma omp parallel for num_threads(num_thread)
for (int g=0; g<group; g++)
{
float* out = output + g * c_step_out;
float* outptr = out;
float* outptr2 = outptr + outw;
const float bias0 = _bias ? _bias[g] : 0.f;
const float* kernel0 = kernel + g*9;
const float* img0 = input + g * c_step_in;
const float* r0 = img0;
const float* r1 = img0 + w;
const float* r2 = img0 + w*2;
const float* r3 = img0 + w*3;
const float* k0 = kernel0;
const float* k1 = kernel0 + 3;
const float* k2 = kernel0 + 6;
int i = 0;
for (; i+1 < outh; i+=2)
{
int remain = outw;
for (; remain>0; remain--)
{
float sum = bias0;
sum += r0[0] * k0[0];
sum += r0[1] * k0[1];
sum += r0[2] * k0[2];
sum += r1[0] * k1[0];
sum += r1[1] * k1[1];
sum += r1[2] * k1[2];
sum += r2[0] * k2[0];
sum += r2[1] * k2[1];
sum += r2[2] * k2[2];
float sum2 = bias0;
sum2 += r1[0] * k0[0];
sum2 += r1[1] * k0[1];
sum2 += r1[2] * k0[2];
sum2 += r2[0] * k1[0];
sum2 += r2[1] * k1[1];
sum2 += r2[2] * k1[2];
sum2 += r3[0] * k2[0];
sum2 += r3[1] * k2[1];
sum2 += r3[2] * k2[2];
*outptr = sum;
*outptr2 = sum2;
r0++;
r1++;
r2++;
r3++;
outptr++;
outptr2++;
}
r0 += 2 + w;
r1 += 2 + w;
r2 += 2 + w;
r3 += 2 + w;
outptr += outw;
outptr2 += outw;
}
for (; i < outh; i++)
{
int remain = outw;
for (; remain>0; remain--)
{
float sum = bias0;
sum += r0[0] * k0[0];
sum += r0[1] * k0[1];
sum += r0[2] * k0[2];
sum += r1[0] * k1[0];
sum += r1[1] * k1[1];
sum += r1[2] * k1[2];
sum += r2[0] * k2[0];
sum += r2[1] * k2[1];
sum += r2[2] * k2[2];
*outptr = sum;
r0++;
r1++;
r2++;
outptr++;
}
r0 += 2;
r1 += 2;
r2 += 2;
}
}
}
void convdw3x3s2(float* output, float* input, float* _kernel, float* _bias, int channel, int in_h, int in_w, int out_h, int out_w, int num_thread)
{
int w = in_w;
int h = in_h;
int c_step_in = w * h;
int outw = out_w;
int outh = out_h;
int c_step_out = outw * outh;
const int group = channel;
const int tailstep = w - 2*outw + w;
const float* kernel = _kernel;
#pragma omp parallel for num_threads(num_thread)
for (int g=0; g<group; g++)
{
float* out = output + g * c_step_out;
float* outptr = out;
const float* kernel0 = kernel + g*9;
const float bias0 = _bias ? _bias[g] : 0.f;
const float* img0 = input + g * c_step_in;
const float* r0 = img0;
const float* r1 = img0 + w;
const float* r2 = img0 + w*2;
const float* k0 = kernel0;
const float* k1 = kernel0 + 3;
const float* k2 = kernel0 + 6;
int i = 0;
for (; i < outh; i++)
{
int remain = outw;
for (; remain>0; remain--)
{
float sum = bias0;
sum += r0[0] * k0[0];
sum += r0[1] * k0[1];
sum += r0[2] * k0[2];
sum += r1[0] * k1[0];
sum += r1[1] * k1[1];
sum += r1[2] * k1[2];
sum += r2[0] * k2[0];
sum += r2[1] * k2[1];
sum += r2[2] * k2[2];
*outptr = sum;
r0 += 2;
r1 += 2;
r2 += 2;
outptr++;
}
r0 += tailstep;
r1 += tailstep;
r2 += tailstep;
}
}
}
void pad(float* input, float* output, int in_h, int in_w, int out_h, int out_w, int top, int left, float v)
{
float* ptr = input;
float* outptr = output;
int y = 0;
// fill top
for (; y < top; y++)
{
int x = 0;
for (; x < out_w; x++)
{
outptr[x] = v;
}
outptr += out_w;
}
// fill center
for (; y < (top + in_h); y++)
{
int x = 0;
for (; x < left; x++)
{
outptr[x] = v;
}
if (in_w < 12)
{
for (; x < (left + in_w); x++)
{
outptr[x] = ptr[x - left];
}
}
else
{
memcpy(outptr + left, ptr, in_w * sizeof(float));
x += in_w;
}
for (; x < out_w; x++)
{
outptr[x] = v;
}
ptr += in_w;
outptr += out_w;
}
// fill bottom
for (; y < out_h; y++)
{
int x = 0;
for (; x < out_w; x++)
{
outptr[x] = v;
}
outptr += out_w;
}
}
int conv_dw_run(struct tensor* input_tensor, struct tensor* weight_tensor, struct tensor* bias_tensor,
struct tensor* output_tensor, struct conv_priv_info* conv_info, struct conv_param* param, int num_thread, int cpu_affinity)
{
float* input = ( float* )input_tensor->data;
float* output = ( float* )output_tensor->data;
float* kernel = ( float* )weight_tensor->data;
float* biases = NULL;
if (bias_tensor)
biases = (float*)bias_tensor->data;
int batch_number = input_tensor->dims[0];
int inc = input_tensor->dims[1];
int inh = input_tensor->dims[2];
int inw = input_tensor->dims[3];
int in_chw = inc * inh * inw;
int outc = output_tensor->dims[1];
int outh = output_tensor->dims[2];
int outw = output_tensor->dims[3];
int out_hw = outh * outw;
int out_chw = out_hw * outc;
int ksize_h = param->kernel_h;
int ksize_w = param->kernel_w;
int pad_w = param->pad_w0;
int pad_h = param->pad_h0;
int stride_w = param->stride_w;
int stride_h = param->stride_h;
int dilation_w = param->dilation_w;
int dilation_h = param->dilation_h;
int group = param->group;
int activation = param->activation;
/* pading */
int inh_tmp = inh + pad_h + pad_h;
int inw_tmp = inw + pad_w + pad_w;
float* input_tmp = NULL;
if (inh_tmp == inh && inw_tmp == inw)
input_tmp = input;
else
{
input_tmp = (float*)malloc(inh_tmp * inw_tmp * group * sizeof(float));
for (int g=0; g<group; g++)
{
float* pad_in = input + g * inh * inw;
float* pad_out = input_tmp + g * inh_tmp * inw_tmp;
pad(pad_in, pad_out, inh, inw, inh_tmp, inw_tmp, pad_h, pad_w, 0.f);
}
}
/* process */
for(int i = 0; i < batch_number; i++)
{
if (stride_h == 1)
convdw3x3s1(output, input_tmp, kernel, biases, group, inh_tmp, inw_tmp, outh, outw, num_thread);
else
convdw3x3s2(output, input_tmp, kernel, biases, group, inh_tmp, inw_tmp, outh, outw, num_thread);
}
/* relu */
if (activation >= 0)
relu(output, batch_number * out_chw, activation);
if (!(inh_tmp == inh && inw_tmp == inw))
free(input_tmp);
return 0;
}
|
cpu_adagrad.h | #pragma once
#include <cuda_fp16.h>
#include <cuda_runtime_api.h>
#include <stdio.h>
#include <cassert>
#include "cuda.h"
#include "custom_cuda_layers.h"
#include "simd.h"
#define STEP(SPAN) \
void Step_##SPAN(float* _params, \
float* grads, \
float* _exp_avg_sq, \
size_t _param_size, \
__half* dev_param = nullptr, \
bool half_precision = false);
class Adagrad_Optimizer {
public:
Adagrad_Optimizer(float alpha = 1e-2, float eps = 1e-8, float weight_decay = 0)
: _alpha(alpha), _eps(eps), _weight_decay(weight_decay), _buf_index(false)
{
cudaMallocHost((void**)_doubled_buffer, TILE * sizeof(float));
cudaMallocHost((void**)(_doubled_buffer + 1), TILE * sizeof(float));
_streams[0] = Context::Instance().GetCurrentStream();
_streams[1] = Context::Instance().GetNewStream();
}
~Adagrad_Optimizer()
{
cudaFreeHost(_doubled_buffer[0]);
cudaFreeHost(_doubled_buffer[1]);
}
#if defined(__AVX512__) or defined(__AVX256__)
template <int span>
void Step_AVX(size_t* rounded_size,
float* _params,
float* grads,
float* _exp_avg_sq,
size_t param_size,
__half* dev_param = nullptr,
bool half_precision = false);
#endif
STEP(1)
STEP(4)
STEP(8)
inline void SynchronizeStreams()
{
for (int i = 0; i < 2; i++) cudaStreamSynchronize(_streams[i]);
}
inline void IncrementStep(size_t step)
{
_step++;
if (_step != step) { _step = step; }
}
inline void update_state(float lr, float epsilon, float weight_decay)
{
_alpha = lr;
_eps = epsilon;
_weight_decay = weight_decay;
}
private:
float _alpha;
float _eps;
float _weight_decay;
float _betta1_t;
float _betta2_t;
size_t _step;
float* _doubled_buffer[2];
bool _buf_index;
cudaStream_t _streams[2];
};
#if defined(__AVX512__) or defined(__AVX256__)
template <int span>
void Adagrad_Optimizer::Step_AVX(size_t* rounded_size,
float* _params,
float* grads,
float* _exp_avg_sq,
size_t _param_size,
__half* dev_params,
bool half_precision)
{
size_t new_rounded_size = 0;
AVX_Data eps_4;
eps_4.data = SIMD_SET(_eps);
float step_size = -1 * _alpha;
AVX_Data step_size_4;
step_size_4.data = SIMD_SET(step_size);
AVX_Data weight_decay4;
if (_weight_decay > 0) weight_decay4.data = SIMD_SET(_weight_decay);
new_rounded_size = ROUND_DOWN(_param_size, SIMD_WIDTH * span);
for (size_t t = 0; t < new_rounded_size; t += TILE) {
size_t copy_size = TILE;
if ((t + TILE) > new_rounded_size) copy_size = new_rounded_size - t;
size_t offset = copy_size + t;
if ((t / TILE) >= 2) { cudaStreamSynchronize(_streams[_buf_index]); }
#pragma omp parallel for
for (size_t i = t; i < offset; i += SIMD_WIDTH * span) {
AVX_Data grad_4[span];
simd_load<span>(grad_4, grads + i, half_precision);
AVX_Data momentum_4[span];
simd_load<span>(momentum_4, grads + i, false);
AVX_Data variance_4[span];
simd_load<span>(variance_4, _exp_avg_sq + i, false);
AVX_Data param_4[span];
simd_load<span>(param_4, _params + i, half_precision);
if (_weight_decay > 0) { simd_fma<span>(grad_4, param_4, weight_decay4, grad_4); }
simd_fma<span>(variance_4, grad_4, grad_4, variance_4);
simd_sqrt<span>(grad_4, variance_4);
simd_add<span>(grad_4, grad_4, eps_4);
simd_div<span>(grad_4, momentum_4, grad_4);
simd_fma<span>(param_4, grad_4, step_size_4, param_4);
simd_store<span>(_params + i, param_4, half_precision);
if (dev_params) {
simd_store<span>(_doubled_buffer[_buf_index] + (i - t), param_4, half_precision);
}
simd_store<span>(_exp_avg_sq + i, variance_4, false);
}
if (dev_params) {
if (half_precision)
launch_param_update_half(
_doubled_buffer[_buf_index], dev_params + t, copy_size, _streams[_buf_index]);
else
launch_param_update(
_doubled_buffer[_buf_index], dev_params + t, copy_size, _streams[_buf_index]);
_buf_index = !_buf_index;
}
}
*rounded_size = new_rounded_size;
}
#endif
|
collision.c | /**
* @file collision.c
* @brief Collision search routine.
* @author Hanno Rein <hanno@hanno-rein.de>
*
* @details A collision is defined as an overlap between two particles. This
* is only an approximation and works only if the timestep is small
* enough. More precisely, dt << v / Rp, where v is the typical velocity
* and Rp the radius of a particle. Furthermore, particles must be
* approaching each other at the time when they overlap.
*
*
* @section LICENSE
* Copyright (c) 2011 Hanno Rein, Shangfei Liu
*
* This file is part of rebound.
*
* rebound is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* rebound is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with rebound. If not, see <http://www.gnu.org/licenses/>.
*
*/
#include <stdio.h>
#include <stdlib.h>
#include <unistd.h>
#include <math.h>
#include <time.h>
#include "particle.h"
#include "collision.h"
#include "rebound.h"
#include "boundary.h"
#include "tree.h"
#ifdef MPI
#include "communication_mpi.h"
#endif // MPI
static void reb_tree_get_nearest_neighbour_in_cell(struct reb_simulation* const r, int* collisions_N, struct reb_ghostbox gb, struct reb_ghostbox gbunmod, int ri, double p1_r, double* nearest_r2, struct reb_collision* collision_nearest, struct reb_treecell* c);
void reb_collision_search(struct reb_simulation* const r){
const int N = r->N;
int collisions_N = 0;
const struct reb_particle* const particles = r->particles;
switch (r->collision){
case REB_COLLISION_NONE:
break;
case REB_COLLISION_DIRECT:
{
// Loop over ghost boxes, but only the inner most ring.
int nghostxcol = (r->nghostx>1?1:r->nghostx);
int nghostycol = (r->nghosty>1?1:r->nghosty);
int nghostzcol = (r->nghostz>1?1:r->nghostz);
for (int gbx=-nghostxcol; gbx<=nghostxcol; gbx++){
for (int gby=-nghostycol; gby<=nghostycol; gby++){
for (int gbz=-nghostzcol; gbz<=nghostzcol; gbz++){
// Loop over all particles
for (int i=0;i<N;i++){
struct reb_particle p1 = particles[i];
struct reb_ghostbox gborig = reb_boundary_get_ghostbox(r, gbx,gby,gbz);
struct reb_ghostbox gb = gborig;
// Precalculate shifted position
gb.shiftx += p1.x;
gb.shifty += p1.y;
gb.shiftz += p1.z;
gb.shiftvx += p1.vx;
gb.shiftvy += p1.vy;
gb.shiftvz += p1.vz;
// Loop over all particles again
for (int j=0;j<N;j++){
// Do not collide particle with itself.
if (i==j) continue;
struct reb_particle p2 = particles[j];
double dx = gb.shiftx - p2.x;
double dy = gb.shifty - p2.y;
double dz = gb.shiftz - p2.z;
double sr = p1.r + p2.r;
double r2 = dx*dx+dy*dy+dz*dz;
// Check if particles are overlapping
if (r2>sr*sr) continue;
double dvx = gb.shiftvx - p2.vx;
double dvy = gb.shiftvy - p2.vy;
double dvz = gb.shiftvz - p2.vz;
// Check if particles are approaching each other
if (dvx*dx + dvy*dy + dvz*dz >0) continue;
// Add particles to collision array.
if (r->collisions_allocatedN<=collisions_N){
// Allocate memory if there is no space in array.
// Doing it in chunks of 32 to avoid having to do it too often.
r->collisions_allocatedN += 32;
r->collisions = realloc(r->collisions,sizeof(struct reb_collision)*r->collisions_allocatedN);
}
r->collisions[collisions_N].p1 = i;
r->collisions[collisions_N].p2 = j;
r->collisions[collisions_N].gb = gborig;
collisions_N++;
}
}
}
}
}
}
break;
case REB_COLLISION_TREE:
{
// Update and simplify tree.
// Prepare particles for distribution to other nodes.
reb_tree_update(r);
#ifdef MPI
// Distribute particles and add newly received particles to tree.
reb_communication_mpi_distribute_particles(r);
// Prepare essential tree (and particles close to the boundary needed for collisions) for distribution to other nodes.
reb_tree_prepare_essential_tree_for_collisions(r);
// Transfer essential tree and particles needed for collisions.
reb_communication_mpi_distribute_essential_tree_for_collisions(r);
#endif // MPI
// Loop over ghost boxes, but only the inner most ring.
int nghostxcol = (r->nghostx>1?1:r->nghostx);
int nghostycol = (r->nghosty>1?1:r->nghosty);
int nghostzcol = (r->nghostz>1?1:r->nghostz);
const struct reb_particle* const particles = r->particles;
const int N = r->N;
// Loop over all particles
#pragma omp parallel for schedule(guided)
for (int i=0;i<N;i++){
struct reb_particle p1 = particles[i];
struct reb_collision collision_nearest;
collision_nearest.p1 = i;
collision_nearest.p2 = -1;
double p1_r = p1.r;
double nearest_r2 = r->boxsize_max*r->boxsize_max/4.;
// Loop over ghost boxes.
for (int gbx=-nghostxcol; gbx<=nghostxcol; gbx++){
for (int gby=-nghostycol; gby<=nghostycol; gby++){
for (int gbz=-nghostzcol; gbz<=nghostzcol; gbz++){
// Calculated shifted position (for speedup).
struct reb_ghostbox gb = reb_boundary_get_ghostbox(r, gbx,gby,gbz);
struct reb_ghostbox gbunmod = gb;
gb.shiftx += p1.x;
gb.shifty += p1.y;
gb.shiftz += p1.z;
gb.shiftvx += p1.vx;
gb.shiftvy += p1.vy;
gb.shiftvz += p1.vz;
// Loop over all root boxes.
for (int ri=0;ri<r->root_n;ri++){
struct reb_treecell* rootcell = r->tree_root[ri];
if (rootcell!=NULL){
reb_tree_get_nearest_neighbour_in_cell(r, &collisions_N, gb, gbunmod,ri,p1_r,&nearest_r2,&collision_nearest,rootcell);
}
}
}
}
}
// Continue if no collision was found
if (collision_nearest.p2==-1) continue;
}
}
break;
default:
reb_exit("Collision routine not implemented.");
}
// randomize
for (int i=0;i<collisions_N;i++){
int new = rand()%collisions_N;
struct reb_collision c1 = r->collisions[i];
r->collisions[i] = r->collisions[new];
r->collisions[new] = c1;
}
// Loop over all collisions previously found in reb_collision_search().
int (*resolve) (struct reb_simulation* const r, struct reb_collision c) = r->collision_resolve;
if (resolve==NULL){
// Default is hard sphere
resolve = reb_collision_resolve_hardsphere;
}
for (int i=0;i<collisions_N;i++){
struct reb_collision c = r->collisions[i];
if (c.p1 != -1 && c.p2 != -1){
// Resolve collision
int outcome = resolve(r, c);
// Remove particles
if (outcome & 1){
// Remove p1
if (c.p2==r->N-1 && !(r->tree_root)){
// Particles swapped
c.p2 = c.p1;
}
reb_remove(r,c.p1,r->collision_resolve_keep_sorted);
// Check for pair
for (int j=i+1;j<collisions_N;j++){
struct reb_collision cp = r->collisions[j];
if (cp.p1==c.p1 || cp.p2==c.p1){
r->collisions[j].p1 = -1;
r->collisions[j].p2 = -1;
// Will be skipped.
}
if (cp.p1==r->N){
r->collisions[j].p1 = c.p1;
}
if (cp.p2==r->N){
r->collisions[j].p2 = c.p1;
}
}
}
if (outcome & 2){
// Remove p2
reb_remove(r,c.p2,r->collision_resolve_keep_sorted);
// Check for pair
for (int j=i+1;j<collisions_N;j++){
struct reb_collision cp = r->collisions[j];
if (cp.p1==c.p2 || cp.p2==c.p2){
r->collisions[j].p1 = -1;
r->collisions[j].p2 = -1;
// Will be skipped.
}
if (cp.p1==r->N){
r->collisions[j].p1 = c.p2;
}
if (cp.p2==r->N){
r->collisions[j].p2 = c.p2;
}
}
}
}
}
}
/**
* @brief Workaround for python setters.
**/
void reb_set_collision_resolve(struct reb_simulation* r, int (*resolve) (struct reb_simulation* const r, struct reb_collision c)){
r->collision_resolve = resolve;
}
/**
* @brief Find the nearest neighbour in a cell or its daughters.
* @details The function only returns a positive result if the particles
* are overlapping. Thus, the name nearest neighbour is not
* exactly true.
* @param r REBOUND simulation to work on.
* @param gb (Shifted) position and velocity of the particle.
* @param ri Index of the root box currently being searched in.
* @param p1_r Radius of the particle (this is not in gb).
* @param nearest_r2 Pointer to the nearest neighbour found so far.
* @param collision_nearest Pointer to the nearest collision found so far.
* @param c Pointer to the cell currently being searched in.
* @param collisions_N Pointer to current number of collisions
* @param gbunmod Ghostbox unmodified
*/
static void reb_tree_get_nearest_neighbour_in_cell(struct reb_simulation* const r, int* collisions_N, struct reb_ghostbox gb, struct reb_ghostbox gbunmod, int ri, double p1_r, double* nearest_r2, struct reb_collision* collision_nearest, struct reb_treecell* c){
const struct reb_particle* const particles = r->particles;
if (c->pt>=0){
// c is a leaf node
int condition = 1;
#ifdef MPI
int isloc = 1 ;
isloc = reb_communication_mpi_rootbox_is_local(r, ri);
if (isloc==1){
#endif // MPI
/**
* If this is a local cell, make sure particle is not colliding with itself.
* If this is a remote cell, the particle number might be the same, even for
* different particles.
* TODO: This can probably be written in a cleaner way.
*/
condition = (c->pt != collision_nearest->p1);
#ifdef MPI
}
#endif // MPI
if (condition){
struct reb_particle p2;
#ifdef MPI
if (isloc==1){
#endif // MPI
p2 = particles[c->pt];
#ifdef MPI
}else{
int root_n_per_node = r->root_n/r->mpi_num;
int proc_id = ri/root_n_per_node;
p2 = r->particles_recv[proc_id][c->pt];
}
#endif // MPI
double dx = gb.shiftx - p2.x;
double dy = gb.shifty - p2.y;
double dz = gb.shiftz - p2.z;
double r2 = dx*dx+dy*dy+dz*dz;
// A closer neighbour has already been found
//if (r2 > *nearest_r2) return;
double rp = p1_r+p2.r;
// reb_particles are not overlapping
if (r2 > rp*rp) return;
double dvx = gb.shiftvx - p2.vx;
double dvy = gb.shiftvy - p2.vy;
double dvz = gb.shiftvz - p2.vz;
// reb_particles are not approaching each other
if (dvx*dx + dvy*dy + dvz*dz >0) return;
// Found a new nearest neighbour. Save it for later.
*nearest_r2 = r2;
collision_nearest->ri = ri;
collision_nearest->p2 = c->pt;
collision_nearest->gb = gbunmod;
// Save collision in collisions array.
#pragma omp critical
{
if (r->collisions_allocatedN<=(*collisions_N)){
r->collisions_allocatedN += 32;
r->collisions = realloc(r->collisions,sizeof(struct reb_collision)*r->collisions_allocatedN);
}
r->collisions[(*collisions_N)] = *collision_nearest;
(*collisions_N)++;
}
}
}else{
// c is not a leaf node
double dx = gb.shiftx - c->x;
double dy = gb.shifty - c->y;
double dz = gb.shiftz - c->z;
double r2 = dx*dx + dy*dy + dz*dz;
double rp = p1_r + r->max_radius[1] + 0.86602540378443*c->w;
// Check if we need to decent into daughter cells
if (r2 < rp*rp ){
for (int o=0;o<8;o++){
struct reb_treecell* d = c->oct[o];
if (d!=NULL){
reb_tree_get_nearest_neighbour_in_cell(r, collisions_N, gb,gbunmod,ri,p1_r,nearest_r2,collision_nearest,d);
}
}
}
}
}
int reb_collision_resolve_hardsphere(struct reb_simulation* const r, struct reb_collision c){
struct reb_particle* const particles = r->particles;
struct reb_particle p1 = particles[c.p1];
struct reb_particle p2;
#ifdef MPI
int isloc = reb_communication_mpi_rootbox_is_local(r, c.ri);
if (isloc==1){
#endif // MPI
p2 = particles[c.p2];
#ifdef MPI
}else{
int root_n_per_node = r->root_n/r->mpi_num;
int proc_id = c.ri/root_n_per_node;
p2 = r->particles_recv[proc_id][c.p2];
}
#endif // MPI
// if (p1.lastcollision==t || p2.lastcollision==t) return;
struct reb_ghostbox gb = c.gb;
double x21 = p1.x + gb.shiftx - p2.x;
double y21 = p1.y + gb.shifty - p2.y;
double z21 = p1.z + gb.shiftz - p2.z;
double rp = p1.r+p2.r;
double oldvyouter;
if (x21>0){
oldvyouter = p1.vy;
}else{
oldvyouter = p2.vy;
}
if (rp*rp < x21*x21 + y21*y21 + z21*z21) return 0;
double vx21 = p1.vx + gb.shiftvx - p2.vx;
double vy21 = p1.vy + gb.shiftvy - p2.vy;
double vz21 = p1.vz + gb.shiftvz - p2.vz;
if (vx21*x21 + vy21*y21 + vz21*z21 >0) return 0; // not approaching
// Bring the to balls in the xy plane.
// NOTE: this could probabely be an atan (which is faster than atan2)
double theta = atan2(z21,y21);
double stheta = sin(theta);
double ctheta = cos(theta);
double vy21n = ctheta * vy21 + stheta * vz21;
double y21n = ctheta * y21 + stheta * z21;
// Bring the two balls onto the positive x axis.
double phi = atan2(y21n,x21);
double cphi = cos(phi);
double sphi = sin(phi);
double vx21nn = cphi * vx21 + sphi * vy21n;
// Coefficient of restitution
double eps= 1; // perfect bouncing by default
if (r->coefficient_of_restitution){
eps = r->coefficient_of_restitution(r, vx21nn);
}
double dvx2 = -(1.0+eps)*vx21nn;
double minr = (p1.r>p2.r)?p2.r:p1.r;
double maxr = (p1.r<p2.r)?p2.r:p1.r;
double mindv= minr*r->minimum_collision_velocity;
double _r = sqrt(x21*x21 + y21*y21 + z21*z21);
mindv *= 1.-(_r - maxr)/minr;
if (mindv>maxr*r->minimum_collision_velocity)mindv = maxr*r->minimum_collision_velocity;
if (dvx2<mindv) dvx2 = mindv;
// Now we are rotating backwards
double dvx2n = cphi * dvx2;
double dvy2n = sphi * dvx2;
double dvy2nn = ctheta * dvy2n;
double dvz2nn = stheta * dvy2n;
// Applying the changes to the particles.
#ifdef MPI
if (isloc==1){
#endif // MPI
const double p2pf = p1.m/(p1.m+p2.m);
particles[c.p2].vx -= p2pf*dvx2n;
particles[c.p2].vy -= p2pf*dvy2nn;
particles[c.p2].vz -= p2pf*dvz2nn;
particles[c.p2].lastcollision = r->t;
#ifdef MPI
}
#endif // MPI
const double p1pf = p2.m/(p1.m+p2.m);
particles[c.p1].vx += p1pf*dvx2n;
particles[c.p1].vy += p1pf*dvy2nn;
particles[c.p1].vz += p1pf*dvz2nn;
particles[c.p1].lastcollision = r->t;
// Return y-momentum change
if (x21>0){
r->collisions_plog += -fabs(x21)*(oldvyouter-particles[c.p1].vy) * p1.m;
r->collisions_Nlog ++;
}else{
r->collisions_plog += -fabs(x21)*(oldvyouter-particles[c.p2].vy) * p2.m;
r->collisions_Nlog ++;
}
return 0;
}
int reb_collision_resolve_merge(struct reb_simulation* const r, struct reb_collision c){
if (r->particles[c.p1].lastcollision==r->t || r->particles[c.p2].lastcollision==r->t) return 0;
// Every collision will cause two callbacks (with p1/p2 interchanged).
// Always remove particle with larger index and merge into lower index particle.
// This will keep N_active meaningful even after mergers.
int swap = 0;
int i = c.p1;
int j = c.p2; //want j to be removed particle
if (j<i){
swap = 1;
i = c.p2;
j = c.p1;
}
struct reb_particle* pi = &(r->particles[i]);
struct reb_particle* pj = &(r->particles[j]);
double invmass = 1.0/(pi->m + pj->m);
//Scale out energy from collision - initial energy
double Ei=0, Ef=0;
if(r->track_energy_offset) Ei = reb_tools_energy(r);
// Merge by conserving mass, volume and momentum
pi->vx = (pi->vx*pi->m + pj->vx*pj->m)*invmass;
pi->vy = (pi->vy*pi->m + pj->vy*pj->m)*invmass;
pi->vz = (pi->vz*pi->m + pj->vz*pj->m)*invmass;
pi->x = (pi->x*pi->m + pj->x*pj->m)*invmass;
pi->y = (pi->y*pi->m + pj->y*pj->m)*invmass;
pi->z = (pi->z*pi->m + pj->z*pj->m)*invmass;
pi->m = pi->m + pj->m;
pi->r = pow(pow(pi->r,3.)+pow(pj->r,3.),1./3.);
pi->lastcollision = r->t;
//Scale out energy from collision - final energy
if(r->track_energy_offset){
Ef = r->energy_offset;
const int N = r->N;
const int N_var = r->N_var;
const int _N_active = ((r->N_active==-1)?N:r->N_active) - N_var;
int N_interact = (r->testparticle_type==0)?_N_active:(N-N_var);
const struct reb_particle* restrict const particles = r->particles;
for (int k=0;k<N_interact;k++){
if(k==j) continue; //j is the particle that will be removed but hasn't yet
struct reb_particle pk = particles[k];
Ef += 0.5 * pk.m * (pk.vx*pk.vx + pk.vy*pk.vy + pk.vz*pk.vz);
}
for (int k=0;k<_N_active;k++){
if(k==j) continue;
struct reb_particle pk = particles[k];
for (int l=k+1;l<N_interact;l++){
if(l==j)continue;
struct reb_particle pl = particles[l];
double dx = pl.x - pk.x;
double dy = pl.y - pk.y;
double dz = pl.z - pk.z;
Ef -= r->G*pk.m*pl.m/sqrt(dx*dx + dy*dy + dz*dz);
}
}
r->energy_offset += Ei - Ef;
}
// If hermes calculate energy offset in global - hasn't been removed from global yet
if (r->ri_hermes.global){
if(r->ri_hermes.global->ri_hermes.mini_active){
r->ri_hermes.global->ri_hermes.collision_this_global_dt = 1;
}
}
return swap?1:2; // Remove particle p2 from simulation
}
|
ark_heat1D_omp.c | /*---------------------------------------------------------------
* Programmer(s): Shelby Lockhart @ LLNL
*---------------------------------------------------------------
* Based on the serial code ark_heat1D.c developed by
* Daniel R. Reynolds @ SMU and parallelized with OpenMP
*---------------------------------------------------------------
* SUNDIALS Copyright Start
* Copyright (c) 2002-2020, Lawrence Livermore National Security
* and Southern Methodist University.
* All rights reserved.
*
* See the top-level LICENSE and NOTICE files for details.
*
* SPDX-License-Identifier: BSD-3-Clause
* SUNDIALS Copyright End
*---------------------------------------------------------------
* Example problem:
*
* The following test simulates a simple 1D heat equation,
* u_t = k*u_xx + f
* for t in [0, 10], x in [0, 1], with initial conditions
* u(0,x) = 0
* Dirichlet boundary conditions, i.e.
* u_t(t,0) = u_t(t,1) = 0,
* and a point-source heating term,
* f = 1 for x=0.5.
*
* The spatial derivatives are computed using second-order
* centered differences, with the data distributed over N points
* on a uniform spatial grid.
*
* This program solves the problem with either an ERK or DIRK
* method. For the DIRK method, we use a Newton iteration with
* the SUNPCG linear solver, and a user-supplied Jacobian-vector
* product routine.
*
* 100 outputs are printed at equal intervals, and run statistics
* are printed at the end.
*---------------------------------------------------------------*/
/* Header files */
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <arkode/arkode_arkstep.h> /* prototypes for ARKStep fcts., consts */
#include <nvector/nvector_openmp.h> /* OpenMP N_Vector types, fcts., macros */
#include <sunlinsol/sunlinsol_pcg.h> /* access to PCG SUNLinearSolver */
#include <sundials/sundials_types.h> /* defs. of realtype, sunindextype, etc */
#ifdef _OPENMP
#include <omp.h> /* OpenMP function defs. */
#endif
#if defined(SUNDIALS_EXTENDED_PRECISION)
#define GSYM "Lg"
#define ESYM "Le"
#define FSYM "Lf"
#else
#define GSYM "g"
#define ESYM "e"
#define FSYM "f"
#endif
/* user data structure */
typedef struct {
sunindextype N; /* number of intervals */
int nthreads; /* number of OpenMP threads */
realtype dx; /* mesh spacing */
realtype k; /* diffusion coefficient */
} *UserData;
/* User-supplied Functions Called by the Solver */
static int f(realtype t, N_Vector y, N_Vector ydot, void *user_data);
static int Jac(N_Vector v, N_Vector Jv, realtype t, N_Vector y,
N_Vector fy, void *user_data, N_Vector tmp);
/* Private function to check function return values */
static int check_flag(void *flagvalue, const char *funcname, int opt);
/* Main Program */
int main(int argc, char *argv[]) {
/* general problem parameters */
realtype T0 = RCONST(0.0); /* initial time */
realtype Tf = RCONST(1.0); /* final time */
int Nt = 10; /* total number of output times */
realtype rtol = 1.e-6; /* relative tolerance */
realtype atol = 1.e-10; /* absolute tolerance */
UserData udata = NULL;
realtype *data;
sunindextype N = 201; /* spatial mesh size */
realtype k = 0.5; /* heat conductivity */
sunindextype i;
/* general problem variables */
int flag; /* reusable error-checking flag */
N_Vector y = NULL; /* empty vector for storing solution */
SUNLinearSolver LS = NULL; /* empty linear solver object */
void *arkode_mem = NULL; /* empty ARKStep memory structure */
FILE *FID, *UFID;
realtype t, dTout, tout;
int iout, num_threads;
long int nst, nst_a, nfe, nfi, nsetups, nli, nJv, nlcf, nni, ncfn, netf;
/* set the number of threads to use */
num_threads = 1; /* default value */
#ifdef _OPENMP
num_threads = omp_get_max_threads(); /* overwrite with OMP_NUM_THREADS environment variable */
#endif
if (argc > 1) /* overwrite with command line value, if supplied */
num_threads = (int) strtol(argv[1], NULL, 0);
/* allocate and fill udata structure */
udata = (UserData) malloc(sizeof(*udata));
udata->N = N;
udata->k = k;
udata->dx = RCONST(1.0)/(N-1); /* mesh spacing */
udata->nthreads = num_threads;
/* Initial problem output */
printf("\n1D Heat PDE test problem:\n");
printf(" N = %li\n", (long int) udata->N);
printf(" diffusion coefficient: k = %"GSYM"\n", udata->k);
/* Initialize data structures */
y = N_VNew_OpenMP(N, num_threads); /* Create OpenMP vector for solution */
if (check_flag((void *) y, "N_VNew_OpenMP", 0)) return 1;
N_VConst(0.0, y); /* Set initial conditions */
arkode_mem = ARKStepCreate(NULL, f, T0, y); /* Create the solver memory */
if (check_flag((void *) arkode_mem, "ARKStepCreate", 0)) return 1;
/* Set routines */
flag = ARKStepSetUserData(arkode_mem, (void *) udata); /* Pass udata to user functions */
if (check_flag(&flag, "ARKStepSetUserData", 1)) return 1;
flag = ARKStepSetMaxNumSteps(arkode_mem, 10000); /* Increase max num steps */
if (check_flag(&flag, "ARKStepSetMaxNumSteps", 1)) return 1;
flag = ARKStepSetPredictorMethod(arkode_mem, 1); /* Specify maximum-order predictor */
if (check_flag(&flag, "ARKStepSetPredictorMethod", 1)) return 1;
flag = ARKStepSStolerances(arkode_mem, rtol, atol); /* Specify tolerances */
if (check_flag(&flag, "ARKStepSStolerances", 1)) return 1;
/* Initialize PCG solver -- no preconditioning, with up to N iterations */
LS = SUNLinSol_PCG(y, 0, (int) N);
if (check_flag((void *)LS, "SUNLinSol_PCG", 0)) return 1;
/* Linear solver interface -- set user-supplied J*v routine (no 'jtsetup' required) */
flag = ARKStepSetLinearSolver(arkode_mem, LS, NULL); /* Attach linear solver to ARKStep */
if (check_flag(&flag, "ARKStepSetLinearSolver", 1)) return 1;
flag = ARKStepSetJacTimes(arkode_mem, NULL, Jac); /* Set the Jacobian routine */
if (check_flag(&flag, "ARKStepSetJacTimes", 1)) return 1;
/* Specify linearly implicit RHS, with non-time-dependent Jacobian */
flag = ARKStepSetLinear(arkode_mem, 0);
if (check_flag(&flag, "ARKStepSetLinear", 1)) return 1;
/* output mesh to disk */
FID=fopen("heat_mesh.txt","w");
for (i=0; i<N; i++) fprintf(FID," %.16"ESYM"\n", udata->dx*i);
fclose(FID);
/* Open output stream for results, access data array */
UFID=fopen("heat1D.txt","w");
data = N_VGetArrayPointer(y);
/* output initial condition to disk */
for (i=0; i<N; i++) fprintf(UFID," %.16"ESYM"", data[i]);
fprintf(UFID,"\n");
/* Main time-stepping loop: calls ARKStep to perform the integration, then
prints results. Stops when the final time has been reached */
t = T0;
dTout = (Tf-T0)/Nt;
tout = T0+dTout;
printf(" t ||u||_rms\n");
printf(" -------------------------\n");
printf(" %10.6"FSYM" %10.6f\n", t, sqrt(N_VDotProd(y,y)/N));
for (iout=0; iout<Nt; iout++) {
flag = ARKStepEvolve(arkode_mem, tout, y, &t, ARK_NORMAL); /* call integrator */
if (check_flag(&flag, "ARKStepEvolve", 1)) break;
printf(" %10.6"FSYM" %10.6f\n", t, sqrt(N_VDotProd(y,y)/N)); /* print solution stats */
if (flag >= 0) { /* successful solve: update output time */
tout += dTout;
tout = (tout > Tf) ? Tf : tout;
} else { /* unsuccessful solve: break */
fprintf(stderr,"Solver failure, stopping integration\n");
break;
}
/* output results to disk */
for (i=0; i<N; i++) fprintf(UFID," %.16"ESYM"", data[i]);
fprintf(UFID,"\n");
}
printf(" -------------------------\n");
fclose(UFID);
/* Print some final statistics */
flag = ARKStepGetNumSteps(arkode_mem, &nst);
check_flag(&flag, "ARKStepGetNumSteps", 1);
flag = ARKStepGetNumStepAttempts(arkode_mem, &nst_a);
check_flag(&flag, "ARKStepGetNumStepAttempts", 1);
flag = ARKStepGetNumRhsEvals(arkode_mem, &nfe, &nfi);
check_flag(&flag, "ARKStepGetNumRhsEvals", 1);
flag = ARKStepGetNumLinSolvSetups(arkode_mem, &nsetups);
check_flag(&flag, "ARKStepGetNumLinSolvSetups", 1);
flag = ARKStepGetNumErrTestFails(arkode_mem, &netf);
check_flag(&flag, "ARKStepGetNumErrTestFails", 1);
flag = ARKStepGetNumNonlinSolvIters(arkode_mem, &nni);
check_flag(&flag, "ARKStepGetNumNonlinSolvIters", 1);
flag = ARKStepGetNumNonlinSolvConvFails(arkode_mem, &ncfn);
check_flag(&flag, "ARKStepGetNumNonlinSolvConvFails", 1);
flag = ARKStepGetNumLinIters(arkode_mem, &nli);
check_flag(&flag, "ARKStepGetNumLinIters", 1);
flag = ARKStepGetNumJtimesEvals(arkode_mem, &nJv);
check_flag(&flag, "ARKStepGetNumJtimesEvals", 1);
flag = ARKStepGetNumLinConvFails(arkode_mem, &nlcf);
check_flag(&flag, "ARKStepGetNumLinConvFails", 1);
printf("\nFinal Solver Statistics:\n");
printf(" Internal solver steps = %li (attempted = %li)\n", nst, nst_a);
printf(" Total RHS evals: Fe = %li, Fi = %li\n", nfe, nfi);
printf(" Total linear solver setups = %li\n", nsetups);
printf(" Total linear iterations = %li\n", nli);
printf(" Total number of Jacobian-vector products = %li\n", nJv);
printf(" Total number of linear solver convergence failures = %li\n", nlcf);
printf(" Total number of Newton iterations = %li\n", nni);
printf(" Total number of nonlinear solver convergence failures = %li\n", ncfn);
printf(" Total number of error test failures = %li\n", netf);
/* Clean up and return with successful completion */
N_VDestroy(y); /* Free vectors */
free(udata); /* Free user data */
ARKStepFree(&arkode_mem); /* Free integrator memory */
SUNLinSolFree(LS); /* Free linear solver */
return 0;
}
/*--------------------------------
* Functions called by the solver
*--------------------------------*/
/* f routine to compute the ODE RHS function f(t,y). */
static int f(realtype t, N_Vector y, N_Vector ydot, void *user_data)
{
UserData udata = (UserData) user_data; /* access problem data */
sunindextype N = udata->N; /* set variable shortcuts */
realtype k = udata->k;
realtype dx = udata->dx;
realtype *Y=NULL, *Ydot=NULL;
realtype c1, c2;
sunindextype i = 0;
sunindextype isource;
Y = N_VGetArrayPointer(y); /* access data arrays */
if (check_flag((void *) Y, "N_VGetArrayPointer", 0)) return 1;
Ydot = N_VGetArrayPointer(ydot);
if (check_flag((void *) Ydot, "N_VGetArrayPointer", 0)) return 1;
N_VConst(0.0, ydot); /* Initialize ydot to zero */
/* iterate over domain, computing all equations */
c1 = k/dx/dx;
c2 = -RCONST(2.0)*k/dx/dx;
isource = N/2;
Ydot[0] = 0.0; /* left boundary condition */
#pragma omp parallel for default(shared) private(i) schedule(static) num_threads(udata->nthreads)
for (i=1; i<N-1; i++)
Ydot[i] = c1*Y[i-1] + c2*Y[i] + c1*Y[i+1];
Ydot[N-1] = 0.0; /* right boundary condition */
Ydot[isource] += 0.01/dx; /* source term */
return 0; /* Return with success */
}
/* Jacobian routine to compute J(t,y) = df/dy. */
static int Jac(N_Vector v, N_Vector Jv, realtype t, N_Vector y,
N_Vector fy, void *user_data, N_Vector tmp)
{
UserData udata = (UserData) user_data; /* variable shortcuts */
sunindextype N = udata->N;
realtype k = udata->k;
realtype dx = udata->dx;
realtype *V=NULL, *JV=NULL;
realtype c1, c2;
sunindextype i = 0;
V = N_VGetArrayPointer(v); /* access data arrays */
if (check_flag((void *) V, "N_VGetArrayPointer", 0)) return 1;
JV = N_VGetArrayPointer(Jv);
if (check_flag((void *) JV, "N_VGetArrayPointer", 0)) return 1;
N_VConst(0.0, Jv); /* initialize Jv product to zero */
/* iterate over domain, computing all Jacobian-vector products */
c1 = k/dx/dx;
c2 = -RCONST(2.0)*k/dx/dx;
JV[0] = 0.0;
#pragma omp parallel for default(shared) private(i) schedule(static) num_threads(udata->nthreads)
for (i=1; i<N-1; i++)
JV[i] = c1*V[i-1] + c2*V[i] + c1*V[i+1];
JV[N-1] = 0.0;
return 0; /* Return with success */
}
/*-------------------------------
* Private helper functions
*-------------------------------*/
/* Check function return value...
opt == 0 means SUNDIALS function allocates memory so check if
returned NULL pointer
opt == 1 means SUNDIALS function returns a flag so check if
flag >= 0
opt == 2 means function allocates memory so check if returned
NULL pointer
*/
static int check_flag(void *flagvalue, const char *funcname, int opt)
{
int *errflag;
/* Check if SUNDIALS function returned NULL pointer - no memory allocated */
if (opt == 0 && flagvalue == NULL) {
fprintf(stderr, "\nSUNDIALS_ERROR: %s() failed - returned NULL pointer\n\n",
funcname);
return 1; }
/* Check if flag < 0 */
else if (opt == 1) {
errflag = (int *) flagvalue;
if (*errflag < 0) {
fprintf(stderr, "\nSUNDIALS_ERROR: %s() failed with flag = %d\n\n",
funcname, *errflag);
return 1; }}
/* Check if function returned NULL pointer - no memory allocated */
else if (opt == 2 && flagvalue == NULL) {
fprintf(stderr, "\nMEMORY_ERROR: %s() failed - returned NULL pointer\n\n",
funcname);
return 1; }
return 0;
}
/*---- end of file ----*/
|
convolution_3x3_pack4_fp16s.h | // Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2020 THL A29 Limited, a Tencent company. All rights reserved.
//
// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
// in compliance with the License. You may obtain a copy of the License at
//
// https://opensource.org/licenses/BSD-3-Clause
//
// Unless required by applicable law or agreed to in writing, software distributed
// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
// CONDITIONS OF ANY KIND, either express or implied. See the License for the
// specific language governing permissions and limitations under the License.
static void conv3x3s1_winograd64_transform_kernel_pack4_fp16sa_neon(const Mat& kernel, Mat& kernel_tm_pack4, int inch, int outch, const Option& opt)
{
// winograd63 transform kernel
Mat kernel_tm;
kernel_tm.create(8 * 8, inch, outch);
const float ktm[8][3] = {
{1.0f, 0.0f, 0.0f},
{-2.0f / 9, -2.0f / 9, -2.0f / 9},
{-2.0f / 9, 2.0f / 9, -2.0f / 9},
{1.0f / 90, 1.0f / 45, 2.0f / 45},
{1.0f / 90, -1.0f / 45, 2.0f / 45},
{1.0f / 45, 1.0f / 90, 1.0f / 180},
{1.0f / 45, -1.0f / 90, 1.0f / 180},
{0.0f, 0.0f, 1.0f}
};
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < outch; p++)
{
for (int q = 0; q < inch; q++)
{
const float* kernel0 = (const float*)kernel + p * inch * 9 + q * 9;
float* kernel_tm0 = kernel_tm.channel(p).row(q);
// transform kernel, transposed
const float* k0 = kernel0;
const float* k1 = kernel0 + 3;
const float* k2 = kernel0 + 6;
// h
float tmp[8][3];
for (int i = 0; i < 8; i++)
{
tmp[i][0] = k0[0] * ktm[i][0] + k0[1] * ktm[i][1] + k0[2] * ktm[i][2];
tmp[i][1] = k1[0] * ktm[i][0] + k1[1] * ktm[i][1] + k1[2] * ktm[i][2];
tmp[i][2] = k2[0] * ktm[i][0] + k2[1] * ktm[i][1] + k2[2] * ktm[i][2];
}
// v
for (int j = 0; j < 8; j++)
{
float* tmpp = &tmp[j][0];
for (int i = 0; i < 8; i++)
{
kernel_tm0[j * 8 + i] = tmpp[0] * ktm[i][0] + tmpp[1] * ktm[i][1] + tmpp[2] * ktm[i][2];
}
}
}
}
// interleave
// src = 64-inch-outch
// dst = 4b-4a-inch/4a-64-outch/4b;
kernel_tm_pack4.create(2 * inch / 4, 64, (outch / 4) / 2 + (outch / 4) % 2, (size_t)2u * 16, 16);
int q = 0;
for (; q + 7 < outch; q += 8)
{
const Mat k0 = kernel_tm.channel(q);
const Mat k1 = kernel_tm.channel(q + 1);
const Mat k2 = kernel_tm.channel(q + 2);
const Mat k3 = kernel_tm.channel(q + 3);
const Mat k4 = kernel_tm.channel(q + 4);
const Mat k5 = kernel_tm.channel(q + 5);
const Mat k6 = kernel_tm.channel(q + 6);
const Mat k7 = kernel_tm.channel(q + 7);
Mat g0 = kernel_tm_pack4.channel(q / 8);
for (int k = 0; k < 64; k++)
{
__fp16* g00 = g0.row<__fp16>(k);
for (int p = 0; p + 3 < inch; p += 4)
{
const float* k00 = k0.row(p);
const float* k01 = k0.row(p + 1);
const float* k02 = k0.row(p + 2);
const float* k03 = k0.row(p + 3);
const float* k10 = k1.row(p);
const float* k11 = k1.row(p + 1);
const float* k12 = k1.row(p + 2);
const float* k13 = k1.row(p + 3);
const float* k20 = k2.row(p);
const float* k21 = k2.row(p + 1);
const float* k22 = k2.row(p + 2);
const float* k23 = k2.row(p + 3);
const float* k30 = k3.row(p);
const float* k31 = k3.row(p + 1);
const float* k32 = k3.row(p + 2);
const float* k33 = k3.row(p + 3);
const float* k40 = k4.row(p);
const float* k41 = k4.row(p + 1);
const float* k42 = k4.row(p + 2);
const float* k43 = k4.row(p + 3);
const float* k50 = k5.row(p);
const float* k51 = k5.row(p + 1);
const float* k52 = k5.row(p + 2);
const float* k53 = k5.row(p + 3);
const float* k60 = k6.row(p);
const float* k61 = k6.row(p + 1);
const float* k62 = k6.row(p + 2);
const float* k63 = k6.row(p + 3);
const float* k70 = k7.row(p);
const float* k71 = k7.row(p + 1);
const float* k72 = k7.row(p + 2);
const float* k73 = k7.row(p + 3);
g00[0] = (__fp16)k00[k];
g00[1] = (__fp16)k10[k];
g00[2] = (__fp16)k20[k];
g00[3] = (__fp16)k30[k];
g00[4] = (__fp16)k40[k];
g00[5] = (__fp16)k50[k];
g00[6] = (__fp16)k60[k];
g00[7] = (__fp16)k70[k];
g00[8] = (__fp16)k01[k];
g00[9] = (__fp16)k11[k];
g00[10] = (__fp16)k21[k];
g00[11] = (__fp16)k31[k];
g00[12] = (__fp16)k41[k];
g00[13] = (__fp16)k51[k];
g00[14] = (__fp16)k61[k];
g00[15] = (__fp16)k71[k];
g00[16] = (__fp16)k02[k];
g00[17] = (__fp16)k12[k];
g00[18] = (__fp16)k22[k];
g00[19] = (__fp16)k32[k];
g00[20] = (__fp16)k42[k];
g00[21] = (__fp16)k52[k];
g00[22] = (__fp16)k62[k];
g00[23] = (__fp16)k72[k];
g00[24] = (__fp16)k03[k];
g00[25] = (__fp16)k13[k];
g00[26] = (__fp16)k23[k];
g00[27] = (__fp16)k33[k];
g00[28] = (__fp16)k43[k];
g00[29] = (__fp16)k53[k];
g00[30] = (__fp16)k63[k];
g00[31] = (__fp16)k73[k];
g00 += 32;
}
}
}
for (; q + 3 < outch; q += 4)
{
const Mat k0 = kernel_tm.channel(q);
const Mat k1 = kernel_tm.channel(q + 1);
const Mat k2 = kernel_tm.channel(q + 2);
const Mat k3 = kernel_tm.channel(q + 3);
Mat g0 = kernel_tm_pack4.channel(q / 8 + (q % 8) / 4);
for (int k = 0; k < 64; k++)
{
__fp16* g00 = g0.row<__fp16>(k);
for (int p = 0; p + 3 < inch; p += 4)
{
const float* k00 = k0.row(p);
const float* k01 = k0.row(p + 1);
const float* k02 = k0.row(p + 2);
const float* k03 = k0.row(p + 3);
const float* k10 = k1.row(p);
const float* k11 = k1.row(p + 1);
const float* k12 = k1.row(p + 2);
const float* k13 = k1.row(p + 3);
const float* k20 = k2.row(p);
const float* k21 = k2.row(p + 1);
const float* k22 = k2.row(p + 2);
const float* k23 = k2.row(p + 3);
const float* k30 = k3.row(p);
const float* k31 = k3.row(p + 1);
const float* k32 = k3.row(p + 2);
const float* k33 = k3.row(p + 3);
g00[0] = (__fp16)k00[k];
g00[1] = (__fp16)k10[k];
g00[2] = (__fp16)k20[k];
g00[3] = (__fp16)k30[k];
g00[4] = (__fp16)k01[k];
g00[5] = (__fp16)k11[k];
g00[6] = (__fp16)k21[k];
g00[7] = (__fp16)k31[k];
g00[8] = (__fp16)k02[k];
g00[9] = (__fp16)k12[k];
g00[10] = (__fp16)k22[k];
g00[11] = (__fp16)k32[k];
g00[12] = (__fp16)k03[k];
g00[13] = (__fp16)k13[k];
g00[14] = (__fp16)k23[k];
g00[15] = (__fp16)k33[k];
g00 += 16;
}
}
}
}
static void conv3x3s1_winograd64_pack4_fp16sa_neon(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel_tm, const Mat& bias, const Option& opt)
{
int w = bottom_blob.w;
int h = bottom_blob.h;
int inch = bottom_blob.c;
size_t elemsize = bottom_blob.elemsize;
int elempack = bottom_blob.elempack;
int outw = top_blob.w;
int outh = top_blob.h;
int outch = top_blob.c;
// pad to 6n+2
Mat bottom_blob_bordered = bottom_blob;
outw = (outw + 5) / 6 * 6;
outh = (outh + 5) / 6 * 6;
w = outw + 2;
h = outh + 2;
copy_make_border(bottom_blob, bottom_blob_bordered, 0, h - bottom_blob.h, 0, w - bottom_blob.w, BORDER_CONSTANT, 0.f, opt);
// BEGIN transform input
Mat bottom_blob_tm;
{
int w_tiles = outw / 6;
int h_tiles = outh / 6;
const int tiles = w_tiles * h_tiles;
bottom_blob_tm.create(tiles, 64, inch, elemsize, elempack, opt.workspace_allocator);
conv3x3s1_winograd64_transform_input_pack4_fp16sa_neon(bottom_blob_bordered, bottom_blob_tm, opt);
}
bottom_blob_bordered = Mat();
// END transform input
// BEGIN dot
Mat top_blob_tm;
{
int w_tm = outw / 6 * 8;
int h_tm = outh / 6 * 8;
const int tiles = h_tm / 8 * w_tm / 8;
// permute
// bottom_blob_tm.create(tiles, 64, inch, elemsize, elempack, opt.workspace_allocator);
Mat bottom_blob_tm2;
if (tiles >= 8)
bottom_blob_tm2.create(8 * inch, tiles / 8 + (tiles % 8) / 4 + tiles % 4, 64, 2u * elempack, elempack, opt.workspace_allocator);
else if (tiles >= 4)
bottom_blob_tm2.create(4 * inch, tiles / 4 + tiles % 4, 64, 2u * elempack, elempack, opt.workspace_allocator);
else // if (tiles >= 1)
bottom_blob_tm2.create(1 * inch, tiles, 64, 2u * elempack, elempack, opt.workspace_allocator);
#pragma omp parallel for num_threads(opt.num_threads)
for (int r = 0; r < 64; r++)
{
Mat tm2 = bottom_blob_tm2.channel(r);
// tile
int i = 0;
for (; i + 7 < tiles; i += 8)
{
__fp16* tm2p = tm2.row<__fp16>(i / 8);
const __fp16* r0 = bottom_blob_tm;
r0 += (r * tiles + i) * 4;
for (int q = 0; q < inch; q++)
{
// transpose 4x8
asm volatile(
"prfm pldl1keep, [%0, #512] \n"
"ld4 {v0.8h, v1.8h, v2.8h, v3.8h}, [%0] \n"
"st1 {v0.8h, v1.8h, v2.8h, v3.8h}, [%1], #64 \n"
: "=r"(r0), // %0
"=r"(tm2p) // %1
: "0"(r0),
"1"(tm2p)
: "memory", "v0", "v1", "v2", "v3");
r0 += bottom_blob_tm.cstep * 4;
}
}
for (; i + 3 < tiles; i += 4)
{
__fp16* tm2p = tm2.row<__fp16>(i / 8 + (i % 8) / 4);
const __fp16* r0 = bottom_blob_tm;
r0 += (r * tiles + i) * 4;
for (int q = 0; q < inch; q++)
{
// transpose 4x4
asm volatile(
"prfm pldl1keep, [%0, #256] \n"
"ld4 {v0.4h, v1.4h, v2.4h, v3.4h}, [%0] \n"
"st1 {v0.4h, v1.4h, v2.4h, v3.4h}, [%1], #32 \n"
: "=r"(r0), // %0
"=r"(tm2p) // %1
: "0"(r0),
"1"(tm2p)
: "memory", "v0", "v1", "v2", "v3");
r0 += bottom_blob_tm.cstep * 4;
}
}
for (; i < tiles; i++)
{
__fp16* tm2p = tm2.row<__fp16>(i / 8 + (i % 8) / 4 + i % 4);
const __fp16* r0 = bottom_blob_tm;
r0 += (r * tiles + i) * 4;
for (int q = 0; q < inch; q++)
{
asm volatile(
"prfm pldl1keep, [%0, #64] \n"
"ld1 {v0.4h}, [%0] \n"
"st1 {v0.4h}, [%1], #8 \n"
: "=r"(r0), // %0
"=r"(tm2p) // %1
: "0"(r0),
"1"(tm2p)
: "memory", "v0");
r0 += bottom_blob_tm.cstep * 4;
}
}
}
bottom_blob_tm = Mat();
// permute end
top_blob_tm.create(tiles, 64, outch, 2u * elempack, elempack, opt.workspace_allocator);
int nn_outch = 0;
int remain_outch_start = 0;
nn_outch = outch >> 1;
remain_outch_start = nn_outch << 1;
#pragma omp parallel for num_threads(opt.num_threads)
for (int pp = 0; pp < nn_outch; pp++)
{
int p = pp * 2;
__fp16* output0_tm = top_blob_tm.channel(p);
__fp16* output1_tm = top_blob_tm.channel(p + 1);
const Mat kernel01_tm = kernel_tm.channel(pp);
for (int r = 0; r < 64; r++)
{
const Mat bb2 = bottom_blob_tm2.channel(r);
int i = 0;
for (; i + 7 < tiles; i += 8)
{
const __fp16* r0 = bb2.row<const __fp16>(i / 8);
const __fp16* kptr = kernel01_tm.row<const __fp16>(r);
int nn = inch; // inch always > 0
asm volatile(
"eor v24.16b, v24.16b, v24.16b \n"
"eor v25.16b, v25.16b, v25.16b \n"
"eor v26.16b, v26.16b, v26.16b \n"
"eor v27.16b, v27.16b, v27.16b \n"
"eor v28.16b, v28.16b, v28.16b \n"
"eor v29.16b, v29.16b, v29.16b \n"
"eor v30.16b, v30.16b, v30.16b \n"
"eor v31.16b, v31.16b, v31.16b \n"
"0: \n"
"prfm pldl1keep, [%3, #512] \n"
"ld1 {v0.8h, v1.8h, v2.8h, v3.8h}, [%3], #64 \n" // r01 r23 r45 r67
"prfm pldl1keep, [%4, #512] \n"
"ld1 {v4.8h, v5.8h, v6.8h, v7.8h}, [%4], #64 \n" // k0123
"fmla v24.8h, v4.8h, v0.h[0] \n"
"fmla v25.8h, v4.8h, v0.h[1] \n"
"fmla v26.8h, v4.8h, v0.h[2] \n"
"fmla v27.8h, v4.8h, v0.h[3] \n"
"fmla v28.8h, v4.8h, v0.h[4] \n"
"fmla v29.8h, v4.8h, v0.h[5] \n"
"fmla v30.8h, v4.8h, v0.h[6] \n"
"fmla v31.8h, v4.8h, v0.h[7] \n"
"fmla v24.8h, v5.8h, v1.h[0] \n"
"fmla v25.8h, v5.8h, v1.h[1] \n"
"fmla v26.8h, v5.8h, v1.h[2] \n"
"fmla v27.8h, v5.8h, v1.h[3] \n"
"fmla v28.8h, v5.8h, v1.h[4] \n"
"fmla v29.8h, v5.8h, v1.h[5] \n"
"fmla v30.8h, v5.8h, v1.h[6] \n"
"fmla v31.8h, v5.8h, v1.h[7] \n"
"fmla v24.8h, v6.8h, v2.h[0] \n"
"fmla v25.8h, v6.8h, v2.h[1] \n"
"fmla v26.8h, v6.8h, v2.h[2] \n"
"fmla v27.8h, v6.8h, v2.h[3] \n"
"fmla v28.8h, v6.8h, v2.h[4] \n"
"fmla v29.8h, v6.8h, v2.h[5] \n"
"fmla v30.8h, v6.8h, v2.h[6] \n"
"fmla v31.8h, v6.8h, v2.h[7] \n"
"subs %w0, %w0, #1 \n"
"fmla v24.8h, v7.8h, v3.h[0] \n"
"fmla v25.8h, v7.8h, v3.h[1] \n"
"fmla v26.8h, v7.8h, v3.h[2] \n"
"fmla v27.8h, v7.8h, v3.h[3] \n"
"fmla v28.8h, v7.8h, v3.h[4] \n"
"fmla v29.8h, v7.8h, v3.h[5] \n"
"fmla v30.8h, v7.8h, v3.h[6] \n"
"fmla v31.8h, v7.8h, v3.h[7] \n"
"bne 0b \n"
"st1 {v24.4h, v25.4h, v26.4h, v27.4h}, [%1], #32 \n"
"st1 {v28.4h, v29.4h, v30.4h, v31.4h}, [%1], #32 \n"
"ext v24.16b, v24.16b, v24.16b, #8 \n"
"ext v25.16b, v25.16b, v25.16b, #8 \n"
"ext v26.16b, v26.16b, v26.16b, #8 \n"
"ext v27.16b, v27.16b, v27.16b, #8 \n"
"ext v28.16b, v28.16b, v28.16b, #8 \n"
"ext v29.16b, v29.16b, v29.16b, #8 \n"
"ext v30.16b, v30.16b, v30.16b, #8 \n"
"ext v31.16b, v31.16b, v31.16b, #8 \n"
"st1 {v24.4h, v25.4h, v26.4h, v27.4h}, [%2], #32 \n"
"st1 {v28.4h, v29.4h, v30.4h, v31.4h}, [%2], #32 \n"
: "=r"(nn), // %0
"=r"(output0_tm), // %1
"=r"(output1_tm), // %2
"=r"(r0), // %3
"=r"(kptr) // %4
: "0"(nn),
"1"(output0_tm),
"2"(output1_tm),
"3"(r0),
"4"(kptr)
: "cc", "memory", "v0", "v1", "v2", "v3", "v4", "v5", "v6", "v7", "v24", "v25", "v26", "v27", "v28", "v29", "v30", "v31");
}
for (; i + 3 < tiles; i += 4)
{
const __fp16* r0 = bb2.row<const __fp16>(i / 8 + (i % 8) / 4);
const __fp16* kptr = kernel01_tm.row<const __fp16>(r);
int nn = inch; // inch always > 0
asm volatile(
"eor v24.16b, v24.16b, v24.16b \n"
"eor v25.16b, v25.16b, v25.16b \n"
"eor v26.16b, v26.16b, v26.16b \n"
"eor v27.16b, v27.16b, v27.16b \n"
"0: \n"
"prfm pldl1keep, [%3, #256] \n"
"ld1 {v0.4h, v1.4h, v2.4h, v3.4h}, [%3], #32 \n" // r01 r23 r45 r67
"prfm pldl1keep, [%4, #512] \n"
"ld1 {v4.8h, v5.8h, v6.8h, v7.8h}, [%4], #64 \n" // k0123
"fmla v24.8h, v4.8h, v0.h[0] \n"
"fmla v25.8h, v4.8h, v0.h[1] \n"
"fmla v26.8h, v4.8h, v0.h[2] \n"
"fmla v27.8h, v4.8h, v0.h[3] \n"
"fmla v24.8h, v5.8h, v1.h[0] \n"
"fmla v25.8h, v5.8h, v1.h[1] \n"
"fmla v26.8h, v5.8h, v1.h[2] \n"
"fmla v27.8h, v5.8h, v1.h[3] \n"
"fmla v24.8h, v6.8h, v2.h[0] \n"
"fmla v25.8h, v6.8h, v2.h[1] \n"
"fmla v26.8h, v6.8h, v2.h[2] \n"
"fmla v27.8h, v6.8h, v2.h[3] \n"
"subs %w0, %w0, #1 \n"
"fmla v24.8h, v7.8h, v3.h[0] \n"
"fmla v25.8h, v7.8h, v3.h[1] \n"
"fmla v26.8h, v7.8h, v3.h[2] \n"
"fmla v27.8h, v7.8h, v3.h[3] \n"
"bne 0b \n"
"st1 {v24.4h, v25.4h, v26.4h, v27.4h}, [%1], #32 \n"
"ext v24.16b, v24.16b, v24.16b, #8 \n"
"ext v25.16b, v25.16b, v25.16b, #8 \n"
"ext v26.16b, v26.16b, v26.16b, #8 \n"
"ext v27.16b, v27.16b, v27.16b, #8 \n"
"st1 {v24.4h, v25.4h, v26.4h, v27.4h}, [%2], #32 \n"
: "=r"(nn), // %0
"=r"(output0_tm), // %1
"=r"(output1_tm), // %2
"=r"(r0), // %3
"=r"(kptr) // %4
: "0"(nn),
"1"(output0_tm),
"2"(output1_tm),
"3"(r0),
"4"(kptr)
: "cc", "memory", "v0", "v1", "v2", "v3", "v4", "v5", "v6", "v7", "v24", "v25", "v26", "v27");
}
for (; i < tiles; i++)
{
const __fp16* r0 = bb2.row<const __fp16>(i / 8 + (i % 8) / 4 + i % 4);
const __fp16* kptr = kernel01_tm.row<const __fp16>(r);
float16x8_t _sum0 = vdupq_n_f16(0.f);
for (int q = 0; q < inch; q++)
{
float16x4_t _r0 = vld1_f16(r0);
float16x8_t _k0 = vld1q_f16(kptr);
float16x8_t _k1 = vld1q_f16(kptr + 8);
float16x8_t _k2 = vld1q_f16(kptr + 16);
float16x8_t _k3 = vld1q_f16(kptr + 24);
_sum0 = vfmaq_lane_f16(_sum0, _k0, _r0, 0);
_sum0 = vfmaq_lane_f16(_sum0, _k1, _r0, 1);
_sum0 = vfmaq_lane_f16(_sum0, _k2, _r0, 2);
_sum0 = vfmaq_lane_f16(_sum0, _k3, _r0, 3);
kptr += 32;
r0 += 4;
}
vst1_f16(output0_tm, vget_low_f16(_sum0));
vst1_f16(output1_tm, vget_high_f16(_sum0));
output0_tm += 4;
output1_tm += 4;
}
}
}
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = remain_outch_start; p < outch; p++)
{
__fp16* output0_tm = top_blob_tm.channel(p);
const Mat kernel0_tm = kernel_tm.channel(p / 2 + p % 2);
for (int r = 0; r < 64; r++)
{
const Mat bb2 = bottom_blob_tm2.channel(r);
int i = 0;
for (; i + 7 < tiles; i += 8)
{
const __fp16* r0 = bb2.row<const __fp16>(i / 8);
const __fp16* kptr = kernel0_tm.row<const __fp16>(r);
int nn = inch; // inch always > 0
asm volatile(
"eor v24.16b, v24.16b, v24.16b \n"
"eor v25.16b, v25.16b, v25.16b \n"
"eor v26.16b, v26.16b, v26.16b \n"
"eor v27.16b, v27.16b, v27.16b \n"
"eor v28.16b, v28.16b, v28.16b \n"
"eor v29.16b, v29.16b, v29.16b \n"
"eor v30.16b, v30.16b, v30.16b \n"
"eor v31.16b, v31.16b, v31.16b \n"
"0: \n"
"prfm pldl1keep, [%2, #512] \n"
"ld1 {v0.8h, v1.8h, v2.8h, v3.8h}, [%2], #64 \n" // r01 r23 r45 r67
"prfm pldl1keep, [%3, #256] \n"
"ld1 {v4.4h, v5.4h, v6.4h, v7.4h}, [%3], #32 \n" // k0123
"fmla v24.4h, v4.4h, v0.h[0] \n"
"fmla v25.4h, v4.4h, v0.h[1] \n"
"fmla v26.4h, v4.4h, v0.h[2] \n"
"fmla v27.4h, v4.4h, v0.h[3] \n"
"fmla v28.4h, v4.4h, v0.h[4] \n"
"fmla v29.4h, v4.4h, v0.h[5] \n"
"fmla v30.4h, v4.4h, v0.h[6] \n"
"fmla v31.4h, v4.4h, v0.h[7] \n"
"fmla v24.4h, v5.4h, v1.h[0] \n"
"fmla v25.4h, v5.4h, v1.h[1] \n"
"fmla v26.4h, v5.4h, v1.h[2] \n"
"fmla v27.4h, v5.4h, v1.h[3] \n"
"fmla v28.4h, v5.4h, v1.h[4] \n"
"fmla v29.4h, v5.4h, v1.h[5] \n"
"fmla v30.4h, v5.4h, v1.h[6] \n"
"fmla v31.4h, v5.4h, v1.h[7] \n"
"fmla v24.4h, v6.4h, v2.h[0] \n"
"fmla v25.4h, v6.4h, v2.h[1] \n"
"fmla v26.4h, v6.4h, v2.h[2] \n"
"fmla v27.4h, v6.4h, v2.h[3] \n"
"fmla v28.4h, v6.4h, v2.h[4] \n"
"fmla v29.4h, v6.4h, v2.h[5] \n"
"fmla v30.4h, v6.4h, v2.h[6] \n"
"fmla v31.4h, v6.4h, v2.h[7] \n"
"subs %w0, %w0, #1 \n"
"fmla v24.4h, v7.4h, v3.h[0] \n"
"fmla v25.4h, v7.4h, v3.h[1] \n"
"fmla v26.4h, v7.4h, v3.h[2] \n"
"fmla v27.4h, v7.4h, v3.h[3] \n"
"fmla v28.4h, v7.4h, v3.h[4] \n"
"fmla v29.4h, v7.4h, v3.h[5] \n"
"fmla v30.4h, v7.4h, v3.h[6] \n"
"fmla v31.4h, v7.4h, v3.h[7] \n"
"bne 0b \n"
"st1 {v24.4h, v25.4h, v26.4h, v27.4h}, [%1], #32 \n"
"st1 {v28.4h, v29.4h, v30.4h, v31.4h}, [%1], #32 \n"
: "=r"(nn), // %0
"=r"(output0_tm), // %1
"=r"(r0), // %2
"=r"(kptr) // %3
: "0"(nn),
"1"(output0_tm),
"2"(r0),
"3"(kptr)
: "cc", "memory", "v0", "v1", "v2", "v3", "v4", "v5", "v6", "v7", "v24", "v25", "v26", "v27", "v28", "v29", "v30", "v31");
}
for (; i + 3 < tiles; i += 4)
{
const __fp16* r0 = bb2.row<const __fp16>(i / 8 + (i % 8) / 4);
const __fp16* kptr = kernel0_tm.row<const __fp16>(r);
int nn = inch; // inch always > 0
asm volatile(
"eor v24.16b, v24.16b, v24.16b \n"
"eor v25.16b, v25.16b, v25.16b \n"
"eor v26.16b, v26.16b, v26.16b \n"
"eor v27.16b, v27.16b, v27.16b \n"
"0: \n"
"prfm pldl1keep, [%2, #256] \n"
"ld1 {v0.4h, v1.4h, v2.4h, v3.4h}, [%2], #32 \n" // r01 r23 r45 r67
"prfm pldl1keep, [%3, #256] \n"
"ld1 {v4.4h, v5.4h, v6.4h, v7.4h}, [%3], #32 \n" // k0123
"fmla v24.4h, v4.4h, v0.h[0] \n"
"fmla v25.4h, v4.4h, v0.h[1] \n"
"fmla v26.4h, v4.4h, v0.h[2] \n"
"fmla v27.4h, v4.4h, v0.h[3] \n"
"fmla v24.4h, v5.4h, v1.h[0] \n"
"fmla v25.4h, v5.4h, v1.h[1] \n"
"fmla v26.4h, v5.4h, v1.h[2] \n"
"fmla v27.4h, v5.4h, v1.h[3] \n"
"fmla v24.4h, v6.4h, v2.h[0] \n"
"fmla v25.4h, v6.4h, v2.h[1] \n"
"fmla v26.4h, v6.4h, v2.h[2] \n"
"fmla v27.4h, v6.4h, v2.h[3] \n"
"subs %w0, %w0, #1 \n"
"fmla v24.4h, v7.4h, v3.h[0] \n"
"fmla v25.4h, v7.4h, v3.h[1] \n"
"fmla v26.4h, v7.4h, v3.h[2] \n"
"fmla v27.4h, v7.4h, v3.h[3] \n"
"bne 0b \n"
"st1 {v24.4h, v25.4h, v26.4h, v27.4h}, [%1], #32 \n"
: "=r"(nn), // %0
"=r"(output0_tm), // %1
"=r"(r0), // %2
"=r"(kptr) // %3
: "0"(nn),
"1"(output0_tm),
"2"(r0),
"3"(kptr)
: "cc", "memory", "v0", "v1", "v2", "v3", "v4", "v5", "v6", "v7", "v24", "v25", "v26", "v27");
}
for (; i < tiles; i++)
{
const __fp16* r0 = bb2.row<const __fp16>(i / 8 + (i % 8) / 4 + i % 4);
const __fp16* kptr = kernel0_tm.row<const __fp16>(r);
float16x4_t _sum0 = vdup_n_f16(0.f);
for (int q = 0; q < inch; q++)
{
float16x4_t _r0 = vld1_f16(r0);
float16x4_t _k0 = vld1_f16(kptr);
float16x4_t _k1 = vld1_f16(kptr + 4);
float16x4_t _k2 = vld1_f16(kptr + 8);
float16x4_t _k3 = vld1_f16(kptr + 12);
_sum0 = vfma_lane_f16(_sum0, _k0, _r0, 0);
_sum0 = vfma_lane_f16(_sum0, _k1, _r0, 1);
_sum0 = vfma_lane_f16(_sum0, _k2, _r0, 2);
_sum0 = vfma_lane_f16(_sum0, _k3, _r0, 3);
kptr += 16;
r0 += 4;
}
vst1_f16(output0_tm, _sum0);
output0_tm += 4;
}
}
}
}
bottom_blob_tm = Mat();
// END dot
// BEGIN transform output
Mat top_blob_bordered;
if (outw == top_blob.w && outh == top_blob.h)
{
top_blob_bordered = top_blob;
}
else
{
top_blob_bordered.create(outw, outh, outch, 2u * 4, 4, opt.workspace_allocator);
}
{
conv3x3s1_winograd64_transform_output_pack4_fp16sa_neon(top_blob_tm, top_blob_bordered, bias, opt);
}
// END transform output
// cut result pad
copy_cut_border(top_blob_bordered, top_blob, 0, top_blob_bordered.h - top_blob.h, 0, top_blob_bordered.w - top_blob.w, opt);
}
static void conv3x3s1_pack4_fp16sa_neon(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Mat& _bias, const Option& opt)
{
int inch = bottom_blob.c;
int outw = top_blob.w;
int outh = top_blob.h;
int outch = top_blob.c;
const __fp16* bias = _bias;
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < outch; p++)
{
Mat out0 = top_blob.channel(p);
float16x4_t _bias0 = bias ? vld1_f16(bias + p * 4) : vdup_n_f16((__fp16)0.f);
out0.fill(_bias0);
int q = 0;
for (; q < inch; q++)
{
__fp16* outptr0 = out0.row<__fp16>(0);
const Mat img0 = bottom_blob.channel(q);
const __fp16* r0 = img0.row<const __fp16>(0);
const __fp16* r1 = img0.row<const __fp16>(1);
const __fp16* r2 = img0.row<const __fp16>(2);
const __fp16* kptr = kernel.channel(p).row<const __fp16>(q);
// 16 * 9
float16x8_t _k00_01 = vld1q_f16(kptr);
float16x8_t _k00_23 = vld1q_f16(kptr + 8);
float16x8_t _k01_01 = vld1q_f16(kptr + 16);
float16x8_t _k01_23 = vld1q_f16(kptr + 24);
float16x8_t _k02_01 = vld1q_f16(kptr + 32);
float16x8_t _k02_23 = vld1q_f16(kptr + 40);
float16x8_t _k10_01 = vld1q_f16(kptr + 48);
float16x8_t _k10_23 = vld1q_f16(kptr + 56);
float16x8_t _k11_01 = vld1q_f16(kptr + 64);
float16x8_t _k11_23 = vld1q_f16(kptr + 72);
float16x8_t _k12_01 = vld1q_f16(kptr + 80);
float16x8_t _k12_23 = vld1q_f16(kptr + 88);
float16x8_t _k20_01 = vld1q_f16(kptr + 96);
float16x8_t _k20_23 = vld1q_f16(kptr + 104);
float16x8_t _k21_01 = vld1q_f16(kptr + 112);
float16x8_t _k21_23 = vld1q_f16(kptr + 120);
float16x8_t _k22_01 = vld1q_f16(kptr + 128);
float16x8_t _k22_23 = vld1q_f16(kptr + 136);
int i = 0;
for (; i < outh; i++)
{
int j = 0;
for (; j + 3 < outw; j += 4)
{
asm volatile(
"prfm pldl1keep, [%0, #256] \n"
"ld1 {v10.4h, v11.4h, v12.4h, v13.4h}, [%0] \n" // sum0 sum1 sum2 sum3
"prfm pldl1keep, [%1, #384] \n"
"ld1 {v0.8h, v1.8h, v2.8h}, [%1] \n" // r00 r01 r02 r03 r04 r05
"ext v6.16b, %8.16b, %8.16b, #8 \n"
"fmla v10.4h, %8.4h, v0.h[0] \n"
"fmla v11.4h, %8.4h, v0.h[4] \n"
"fmla v12.4h, %8.4h, v1.h[0] \n"
"fmla v13.4h, %8.4h, v1.h[4] \n"
"fmla v10.4h, v6.4h, v0.h[1] \n"
"fmla v11.4h, v6.4h, v0.h[5] \n"
"fmla v12.4h, v6.4h, v1.h[1] \n"
"fmla v13.4h, v6.4h, v1.h[5] \n"
"ext v7.16b, %9.16b, %9.16b, #8 \n"
"fmla v10.4h, %9.4h, v0.h[2] \n"
"fmla v11.4h, %9.4h, v0.h[6] \n"
"fmla v12.4h, %9.4h, v1.h[2] \n"
"fmla v13.4h, %9.4h, v1.h[6] \n"
"fmla v10.4h, v7.4h, v0.h[3] \n"
"fmla v11.4h, v7.4h, v0.h[7] \n"
"fmla v12.4h, v7.4h, v1.h[3] \n"
"fmla v13.4h, v7.4h, v1.h[7] \n"
"ext v8.16b, %10.16b, %10.16b, #8 \n"
"fmla v10.4h, %10.4h, v0.h[4] \n"
"fmla v11.4h, %10.4h, v1.h[0] \n"
"fmla v12.4h, %10.4h, v1.h[4] \n"
"fmla v13.4h, %10.4h, v2.h[0] \n"
"fmla v10.4h, v8.4h, v0.h[5] \n"
"fmla v11.4h, v8.4h, v1.h[1] \n"
"fmla v12.4h, v8.4h, v1.h[5] \n"
"fmla v13.4h, v8.4h, v2.h[1] \n"
"ext v9.16b, %11.16b, %11.16b, #8 \n"
"fmla v10.4h, %11.4h, v0.h[6] \n"
"fmla v11.4h, %11.4h, v1.h[2] \n"
"fmla v12.4h, %11.4h, v1.h[6] \n"
"fmla v13.4h, %11.4h, v2.h[2] \n"
"fmla v10.4h, v9.4h, v0.h[7] \n"
"fmla v11.4h, v9.4h, v1.h[3] \n"
"fmla v12.4h, v9.4h, v1.h[7] \n"
"fmla v13.4h, v9.4h, v2.h[3] \n"
"prfm pldl1keep, [%2, #384] \n"
"ld1 {v3.8h, v4.8h, v5.8h}, [%2] \n" // r10 r11 r12 r13 r14 r15
"ext v6.16b, %12.16b, %12.16b, #8 \n"
"fmla v10.4h, %12.4h, v1.h[0] \n"
"fmla v11.4h, %12.4h, v1.h[4] \n"
"fmla v12.4h, %12.4h, v2.h[0] \n"
"fmla v13.4h, %12.4h, v2.h[4] \n"
"fmla v10.4h, v6.4h, v1.h[1] \n"
"fmla v11.4h, v6.4h, v1.h[5] \n"
"fmla v12.4h, v6.4h, v2.h[1] \n"
"fmla v13.4h, v6.4h, v2.h[5] \n"
"ext v7.16b, %13.16b, %13.16b, #8 \n"
"fmla v10.4h, %13.4h, v1.h[2] \n"
"fmla v11.4h, %13.4h, v1.h[6] \n"
"fmla v12.4h, %13.4h, v2.h[2] \n"
"fmla v13.4h, %13.4h, v2.h[6] \n"
"fmla v10.4h, v7.4h, v1.h[3] \n"
"fmla v11.4h, v7.4h, v1.h[7] \n"
"fmla v12.4h, v7.4h, v2.h[3] \n"
"fmla v13.4h, v7.4h, v2.h[7] \n"
"ext v8.16b, %14.16b, %14.16b, #8 \n"
"fmla v10.4h, %14.4h, v3.h[0] \n"
"fmla v11.4h, %14.4h, v3.h[4] \n"
"fmla v12.4h, %14.4h, v4.h[0] \n"
"fmla v13.4h, %14.4h, v4.h[4] \n"
"fmla v10.4h, v8.4h, v3.h[1] \n"
"fmla v11.4h, v8.4h, v3.h[5] \n"
"fmla v12.4h, v8.4h, v4.h[1] \n"
"fmla v13.4h, v8.4h, v4.h[5] \n"
"ext v9.16b, %15.16b, %15.16b, #8 \n"
"fmla v10.4h, %15.4h, v3.h[2] \n"
"fmla v11.4h, %15.4h, v3.h[6] \n"
"fmla v12.4h, %15.4h, v4.h[2] \n"
"fmla v13.4h, %15.4h, v4.h[6] \n"
"fmla v10.4h, v9.4h, v3.h[3] \n"
"fmla v11.4h, v9.4h, v3.h[7] \n"
"fmla v12.4h, v9.4h, v4.h[3] \n"
"fmla v13.4h, v9.4h, v4.h[7] \n"
"ext v6.16b, %16.16b, %16.16b, #8 \n"
"fmla v10.4h, %16.4h, v3.h[4] \n"
"fmla v11.4h, %16.4h, v4.h[0] \n"
"fmla v12.4h, %16.4h, v4.h[4] \n"
"fmla v13.4h, %16.4h, v5.h[0] \n"
"fmla v10.4h, v6.4h, v3.h[5] \n"
"fmla v11.4h, v6.4h, v4.h[1] \n"
"fmla v12.4h, v6.4h, v4.h[5] \n"
"fmla v13.4h, v6.4h, v5.h[1] \n"
"ext v7.16b, %17.16b, %17.16b, #8 \n"
"fmla v10.4h, %17.4h, v3.h[6] \n"
"fmla v11.4h, %17.4h, v4.h[2] \n"
"fmla v12.4h, %17.4h, v4.h[6] \n"
"fmla v13.4h, %17.4h, v5.h[2] \n"
"fmla v10.4h, v7.4h, v3.h[7] \n"
"fmla v11.4h, v7.4h, v4.h[3] \n"
"fmla v12.4h, v7.4h, v4.h[7] \n"
"fmla v13.4h, v7.4h, v5.h[3] \n"
"prfm pldl1keep, [%3, #384] \n"
"ld1 {v0.8h, v1.8h, v2.8h}, [%3] \n" // r20 r21 r22 r23 r24 r25
"ext v8.16b, %18.16b, %18.16b, #8 \n"
"fmla v10.4h, %18.4h, v4.h[0] \n"
"fmla v11.4h, %18.4h, v4.h[4] \n"
"fmla v12.4h, %18.4h, v5.h[0] \n"
"fmla v13.4h, %18.4h, v5.h[4] \n"
"fmla v10.4h, v8.4h, v4.h[1] \n"
"fmla v11.4h, v8.4h, v4.h[5] \n"
"fmla v12.4h, v8.4h, v5.h[1] \n"
"fmla v13.4h, v8.4h, v5.h[5] \n"
"ext v9.16b, %19.16b, %19.16b, #8 \n"
"fmla v10.4h, %19.4h, v4.h[2] \n"
"fmla v11.4h, %19.4h, v4.h[6] \n"
"fmla v12.4h, %19.4h, v5.h[2] \n"
"fmla v13.4h, %19.4h, v5.h[6] \n"
"fmla v10.4h, v9.4h, v4.h[3] \n"
"fmla v11.4h, v9.4h, v4.h[7] \n"
"fmla v12.4h, v9.4h, v5.h[3] \n"
"fmla v13.4h, v9.4h, v5.h[7] \n"
"ext v6.16b, %20.16b, %20.16b, #8 \n"
"fmla v10.4h, %20.4h, v0.h[0] \n"
"fmla v11.4h, %20.4h, v0.h[4] \n"
"fmla v12.4h, %20.4h, v1.h[0] \n"
"fmla v13.4h, %20.4h, v1.h[4] \n"
"fmla v10.4h, v6.4h, v0.h[1] \n"
"fmla v11.4h, v6.4h, v0.h[5] \n"
"fmla v12.4h, v6.4h, v1.h[1] \n"
"fmla v13.4h, v6.4h, v1.h[5] \n"
"ext v7.16b, %21.16b, %21.16b, #8 \n"
"fmla v10.4h, %21.4h, v0.h[2] \n"
"fmla v11.4h, %21.4h, v0.h[6] \n"
"fmla v12.4h, %21.4h, v1.h[2] \n"
"fmla v13.4h, %21.4h, v1.h[6] \n"
"fmla v10.4h, v7.4h, v0.h[3] \n"
"fmla v11.4h, v7.4h, v0.h[7] \n"
"fmla v12.4h, v7.4h, v1.h[3] \n"
"fmla v13.4h, v7.4h, v1.h[7] \n"
"ext v8.16b, %22.16b, %22.16b, #8 \n"
"fmla v10.4h, %22.4h, v0.h[4] \n"
"fmla v11.4h, %22.4h, v1.h[0] \n"
"fmla v12.4h, %22.4h, v1.h[4] \n"
"fmla v13.4h, %22.4h, v2.h[0] \n"
"fmla v10.4h, v8.4h, v0.h[5] \n"
"fmla v11.4h, v8.4h, v1.h[1] \n"
"fmla v12.4h, v8.4h, v1.h[5] \n"
"fmla v13.4h, v8.4h, v2.h[1] \n"
"ext v9.16b, %23.16b, %23.16b, #8 \n"
"fmla v10.4h, %23.4h, v0.h[6] \n"
"fmla v11.4h, %23.4h, v1.h[2] \n"
"fmla v12.4h, %23.4h, v1.h[6] \n"
"fmla v13.4h, %23.4h, v2.h[2] \n"
"fmla v10.4h, v9.4h, v0.h[7] \n"
"fmla v11.4h, v9.4h, v1.h[3] \n"
"fmla v12.4h, v9.4h, v1.h[7] \n"
"fmla v13.4h, v9.4h, v2.h[3] \n"
"ext v6.16b, %24.16b, %24.16b, #8 \n"
"fmla v10.4h, %24.4h, v1.h[0] \n"
"fmla v11.4h, %24.4h, v1.h[4] \n"
"fmla v12.4h, %24.4h, v2.h[0] \n"
"fmla v13.4h, %24.4h, v2.h[4] \n"
"add %1, %1, #32 \n"
"fmla v10.4h, v6.4h, v1.h[1] \n"
"fmla v11.4h, v6.4h, v1.h[5] \n"
"fmla v12.4h, v6.4h, v2.h[1] \n"
"fmla v13.4h, v6.4h, v2.h[5] \n"
"ext v7.16b, %25.16b, %25.16b, #8 \n"
"fmla v10.4h, %25.4h, v1.h[2] \n"
"fmla v11.4h, %25.4h, v1.h[6] \n"
"fmla v12.4h, %25.4h, v2.h[2] \n"
"fmla v13.4h, %25.4h, v2.h[6] \n"
"add %2, %2, #32 \n"
"fmla v10.4h, v7.4h, v1.h[3] \n"
"fmla v11.4h, v7.4h, v1.h[7] \n"
"fmla v12.4h, v7.4h, v2.h[3] \n"
"fmla v13.4h, v7.4h, v2.h[7] \n"
"add %3, %3, #32 \n"
"st1 {v10.4h, v11.4h, v12.4h, v13.4h}, [%0], #32 \n"
: "=r"(outptr0), // %0
"=r"(r0), // %1
"=r"(r1), // %2
"=r"(r2) // %3
: "0"(outptr0),
"1"(r0),
"2"(r1),
"3"(r2),
"w"(_k00_01), // %8
"w"(_k00_23), // %9
"w"(_k01_01), // %10
"w"(_k01_23), // %11
"w"(_k02_01), // %12
"w"(_k02_23), // %13
"w"(_k10_01), // %14
"w"(_k10_23), // %15
"w"(_k11_01), // %16
"w"(_k11_23), // %17
"w"(_k12_01), // %18
"w"(_k12_23), // %19
"w"(_k20_01), // %20
"w"(_k20_23), // %21
"w"(_k21_01), // %22
"w"(_k21_23), // %23
"w"(_k22_01), // %24
"w"(_k22_23) // %25
: "memory", "v0", "v1", "v2", "v3", "v4", "v5", "v6", "v7", "v8", "v9", "v10", "v11", "v12", "v13");
}
for (; j + 1 < outw; j += 2)
{
asm volatile(
"prfm pldl1keep, [%1, #256] \n"
"ld1 {v0.8h, v1.8h}, [%1] \n" // r00 r01 r02 r03
"prfm pldl1keep, [%0, #128] \n"
"ld1 {v12.4h, v13.4h}, [%0] \n" // sum0 sum1
"ext v4.16b, %8.16b, %8.16b, #8 \n"
"fmul v10.4h, %8.4h, v0.h[0] \n"
"fmul v11.4h, %8.4h, v0.h[4] \n"
"fmla v12.4h, v4.4h, v0.h[1] \n"
"fmla v13.4h, v4.4h, v0.h[5] \n"
"ext v5.16b, %9.16b, %9.16b, #8 \n"
"fmla v10.4h, %9.4h, v0.h[2] \n"
"fmla v11.4h, %9.4h, v0.h[6] \n"
"fmla v12.4h, v5.4h, v0.h[3] \n"
"fmla v13.4h, v5.4h, v0.h[7] \n"
"ext v6.16b, %10.16b, %10.16b, #8 \n"
"fmla v10.4h, %10.4h, v0.h[4] \n"
"fmla v11.4h, %10.4h, v1.h[0] \n"
"fmla v12.4h, v6.4h, v0.h[5] \n"
"fmla v13.4h, v6.4h, v1.h[1] \n"
"ext v7.16b, %11.16b, %11.16b, #8 \n"
"fmla v10.4h, %11.4h, v0.h[6] \n"
"fmla v11.4h, %11.4h, v1.h[2] \n"
"fmla v12.4h, v7.4h, v0.h[7] \n"
"fmla v13.4h, v7.4h, v1.h[3] \n"
"prfm pldl1keep, [%2, #256] \n"
"ld1 {v2.8h, v3.8h}, [%2] \n" // r10 r11 r12 r13
"ext v8.16b, %12.16b, %12.16b, #8 \n"
"fmla v10.4h, %12.4h, v1.h[0] \n"
"fmla v11.4h, %12.4h, v1.h[4] \n"
"fmla v12.4h, v8.4h, v1.h[1] \n"
"fmla v13.4h, v8.4h, v1.h[5] \n"
"ext v9.16b, %13.16b, %13.16b, #8 \n"
"fmla v10.4h, %13.4h, v1.h[2] \n"
"fmla v11.4h, %13.4h, v1.h[6] \n"
"fmla v12.4h, v9.4h, v1.h[3] \n"
"fmla v13.4h, v9.4h, v1.h[7] \n"
"ext v4.16b, %14.16b, %14.16b, #8 \n"
"fmla v10.4h, %14.4h, v2.h[0] \n"
"fmla v11.4h, %14.4h, v2.h[4] \n"
"fmla v12.4h, v4.4h, v2.h[1] \n"
"fmla v13.4h, v4.4h, v2.h[5] \n"
"ext v5.16b, %15.16b, %15.16b, #8 \n"
"fmla v10.4h, %15.4h, v2.h[2] \n"
"fmla v11.4h, %15.4h, v2.h[6] \n"
"fmla v12.4h, v5.4h, v2.h[3] \n"
"fmla v13.4h, v5.4h, v2.h[7] \n"
"ext v6.16b, %16.16b, %16.16b, #8 \n"
"fmla v10.4h, %16.4h, v2.h[4] \n"
"fmla v11.4h, %16.4h, v3.h[0] \n"
"fmla v12.4h, v6.4h, v2.h[5] \n"
"fmla v13.4h, v6.4h, v3.h[1] \n"
"ext v7.16b, %17.16b, %17.16b, #8 \n"
"fmla v10.4h, %17.4h, v2.h[6] \n"
"fmla v11.4h, %17.4h, v3.h[2] \n"
"fmla v12.4h, v7.4h, v2.h[7] \n"
"fmla v13.4h, v7.4h, v3.h[3] \n"
"prfm pldl1keep, [%3, #256] \n"
"ld1 {v0.8h, v1.8h}, [%3] \n" // r20 r21 r22 r23
"ext v8.16b, %18.16b, %18.16b, #8 \n"
"fmla v10.4h, %18.4h, v3.h[0] \n"
"fmla v11.4h, %18.4h, v3.h[4] \n"
"fmla v12.4h, v8.4h, v3.h[1] \n"
"fmla v13.4h, v8.4h, v3.h[5] \n"
"ext v9.16b, %19.16b, %19.16b, #8 \n"
"fmla v10.4h, %19.4h, v3.h[2] \n"
"fmla v11.4h, %19.4h, v3.h[6] \n"
"fmla v12.4h, v9.4h, v3.h[3] \n"
"fmla v13.4h, v9.4h, v3.h[7] \n"
"ext v4.16b, %20.16b, %20.16b, #8 \n"
"fmla v10.4h, %20.4h, v0.h[0] \n"
"fmla v11.4h, %20.4h, v0.h[4] \n"
"fmla v12.4h, v4.4h, v0.h[1] \n"
"fmla v13.4h, v4.4h, v0.h[5] \n"
"ext v5.16b, %21.16b, %21.16b, #8 \n"
"fmla v10.4h, %21.4h, v0.h[2] \n"
"fmla v11.4h, %21.4h, v0.h[6] \n"
"fmla v12.4h, v5.4h, v0.h[3] \n"
"fmla v13.4h, v5.4h, v0.h[7] \n"
"ext v6.16b, %22.16b, %22.16b, #8 \n"
"fmla v10.4h, %22.4h, v0.h[4] \n"
"fmla v11.4h, %22.4h, v1.h[0] \n"
"fmla v12.4h, v6.4h, v0.h[5] \n"
"fmla v13.4h, v6.4h, v1.h[1] \n"
"ext v7.16b, %23.16b, %23.16b, #8 \n"
"fmla v10.4h, %23.4h, v0.h[6] \n"
"fmla v11.4h, %23.4h, v1.h[2] \n"
"fmla v12.4h, v7.4h, v0.h[7] \n"
"fmla v13.4h, v7.4h, v1.h[3] \n"
"ext v8.16b, %24.16b, %24.16b, #8 \n"
"fmla v10.4h, %24.4h, v1.h[0] \n"
"fmla v11.4h, %24.4h, v1.h[4] \n"
"fmla v12.4h, v8.4h, v1.h[1] \n"
"fmla v13.4h, v8.4h, v1.h[5] \n"
"ext v9.16b, %25.16b, %25.16b, #8 \n"
"fmla v10.4h, %25.4h, v1.h[2] \n"
"fmla v11.4h, %25.4h, v1.h[6] \n"
"fmla v12.4h, v9.4h, v1.h[3] \n"
"fmla v13.4h, v9.4h, v1.h[7] \n"
"add %1, %1, #16 \n"
"fadd v10.4h, v10.4h, v12.4h \n"
"add %2, %2, #16 \n"
"fadd v11.4h, v11.4h, v13.4h \n"
"add %3, %3, #16 \n"
"st1 {v10.4h, v11.4h}, [%0], #16 \n"
: "=r"(outptr0), // %0
"=r"(r0), // %1
"=r"(r1), // %2
"=r"(r2) // %3
: "0"(outptr0),
"1"(r0),
"2"(r1),
"3"(r2),
"w"(_k00_01), // %8
"w"(_k00_23), // %9
"w"(_k01_01), // %10
"w"(_k01_23), // %11
"w"(_k02_01), // %12
"w"(_k02_23), // %13
"w"(_k10_01), // %14
"w"(_k10_23), // %15
"w"(_k11_01), // %16
"w"(_k11_23), // %17
"w"(_k12_01), // %18
"w"(_k12_23), // %19
"w"(_k20_01), // %20
"w"(_k20_23), // %21
"w"(_k21_01), // %22
"w"(_k21_23), // %23
"w"(_k22_01), // %24
"w"(_k22_23) // %25
: "memory", "v0", "v1", "v2", "v3", "v4", "v5", "v6", "v7", "v8", "v9", "v10", "v11", "v12", "v13");
}
for (; j < outw; j++)
{
asm volatile(
"prfm pldl1keep, [%1, #192] \n"
"ld1 {v0.4h, v1.4h, v2.4h}, [%1] \n" // r00 r01 r02
"prfm pldl1keep, [%0, #64] \n"
"ld1 {v13.4h}, [%0] \n" // sum0
"ext v6.16b, %8.16b, %8.16b, #8 \n"
"fmul v10.4h, %8.4h, v0.h[0] \n"
"fmul v11.4h, v6.4h, v0.h[1] \n"
"ext v7.16b, %9.16b, %9.16b, #8 \n"
"fmul v12.4h, %9.4h, v0.h[2] \n"
"fmla v13.4h, v7.4h, v0.h[3] \n"
"ext v8.16b, %10.16b, %10.16b, #8 \n"
"fmla v10.4h, %10.4h, v1.h[0] \n"
"fmla v11.4h, v8.4h, v1.h[1] \n"
"ext v9.16b, %11.16b, %11.16b, #8 \n"
"fmla v12.4h, %11.4h, v1.h[2] \n"
"fmla v13.4h, v9.4h, v1.h[3] \n"
"prfm pldl1keep, [%2, #192] \n"
"ld1 {v3.4h, v4.4h, v5.4h}, [%2] \n" // r10 r11 r12
"ext v6.16b, %12.16b, %12.16b, #8 \n"
"fmla v10.4h, %12.4h, v2.h[0] \n"
"fmla v11.4h, v6.4h, v2.h[1] \n"
"ext v7.16b, %13.16b, %13.16b, #8 \n"
"fmla v12.4h, %13.4h, v2.h[2] \n"
"fmla v13.4h, v7.4h, v2.h[3] \n"
"ext v8.16b, %14.16b, %14.16b, #8 \n"
"fmla v10.4h, %14.4h, v3.h[0] \n"
"fmla v11.4h, v8.4h, v3.h[1] \n"
"ext v9.16b, %15.16b, %15.16b, #8 \n"
"fmla v12.4h, %15.4h, v3.h[2] \n"
"fmla v13.4h, v9.4h, v3.h[3] \n"
"ext v6.16b, %16.16b, %16.16b, #8 \n"
"fmla v10.4h, %16.4h, v4.h[0] \n"
"fmla v11.4h, v6.4h, v4.h[1] \n"
"ext v7.16b, %17.16b, %17.16b, #8 \n"
"fmla v12.4h, %17.4h, v4.h[2] \n"
"fmla v13.4h, v7.4h, v4.h[3] \n"
"prfm pldl1keep, [%3, #192] \n"
"ld1 {v0.4h, v1.4h, v2.4h}, [%3] \n" // r20 r21 r22
"ext v8.16b, %18.16b, %18.16b, #8 \n"
"fmla v10.4h, %18.4h, v5.h[0] \n"
"fmla v11.4h, v8.4h, v5.h[1] \n"
"ext v9.16b, %19.16b, %19.16b, #8 \n"
"fmla v12.4h, %19.4h, v5.h[2] \n"
"fmla v13.4h, v9.4h, v5.h[3] \n"
"ext v6.16b, %20.16b, %20.16b, #8 \n"
"fmla v10.4h, %20.4h, v0.h[0] \n"
"fmla v11.4h, v6.4h, v0.h[1] \n"
"ext v7.16b, %21.16b, %21.16b, #8 \n"
"fmla v12.4h, %21.4h, v0.h[2] \n"
"fmla v13.4h, v7.4h, v0.h[3] \n"
"ext v8.16b, %22.16b, %22.16b, #8 \n"
"fmla v10.4h, %22.4h, v1.h[0] \n"
"fmla v11.4h, v8.4h, v1.h[1] \n"
"ext v9.16b, %23.16b, %23.16b, #8 \n"
"fmla v12.4h, %23.4h, v1.h[2] \n"
"fmla v13.4h, v9.4h, v1.h[3] \n"
"ext v6.16b, %24.16b, %24.16b, #8 \n"
"fmla v10.4h, %24.4h, v2.h[0] \n"
"fmla v11.4h, v6.4h, v2.h[1] \n"
"ext v7.16b, %25.16b, %25.16b, #8 \n"
"fmla v12.4h, %25.4h, v2.h[2] \n"
"fmla v13.4h, v7.4h, v2.h[3] \n"
"fadd v10.4h, v10.4h, v11.4h \n"
"add %1, %1, #8 \n"
"fadd v12.4h, v12.4h, v13.4h \n"
"add %2, %2, #8 \n"
"fadd v10.4h, v10.4h, v12.4h \n"
"add %3, %3, #8 \n"
"st1 {v10.4h}, [%0], #8 \n"
: "=r"(outptr0), // %0
"=r"(r0), // %1
"=r"(r1), // %2
"=r"(r2) // %3
: "0"(outptr0),
"1"(r0),
"2"(r1),
"3"(r2),
"w"(_k00_01), // %8
"w"(_k00_23), // %9
"w"(_k01_01), // %10
"w"(_k01_23), // %11
"w"(_k02_01), // %12
"w"(_k02_23), // %13
"w"(_k10_01), // %14
"w"(_k10_23), // %15
"w"(_k11_01), // %16
"w"(_k11_23), // %17
"w"(_k12_01), // %18
"w"(_k12_23), // %19
"w"(_k20_01), // %20
"w"(_k20_23), // %21
"w"(_k21_01), // %22
"w"(_k21_23), // %23
"w"(_k22_01), // %24
"w"(_k22_23) // %25
: "memory", "v0", "v1", "v2", "v3", "v4", "v5", "v6", "v7", "v8", "v9", "v10", "v11", "v12", "v13");
}
r0 += 8;
r1 += 8;
r2 += 8;
}
}
}
}
|
compare.c | /*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% CCCC OOO M M PPPP AAA RRRR EEEEE %
% C O O MM MM P P A A R R E %
% C O O M M M PPPP AAAAA RRRR EEE %
% C O O M M P A A R R E %
% CCCC OOO M M P A A R R EEEEE %
% %
% %
% MagickCore Image Comparison Methods %
% %
% Software Design %
% John Cristy %
% December 2003 %
% %
% %
% Copyright 1999-2013 ImageMagick Studio LLC, a non-profit organization %
% dedicated to making software imaging solutions freely available. %
% %
% You may not use this file except in compliance with the License. You may %
% obtain a copy of the License at %
% %
% http://www.imagemagick.org/script/license.php %
% %
% Unless required by applicable law or agreed to in writing, software %
% distributed under the License is distributed on an "AS IS" BASIS, %
% WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. %
% See the License for the specific language governing permissions and %
% limitations under the License. %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
%
%
*/
/*
Include declarations.
*/
#include "magick/studio.h"
#include "magick/artifact.h"
#include "magick/cache-view.h"
#include "magick/channel.h"
#include "magick/client.h"
#include "magick/color.h"
#include "magick/color-private.h"
#include "magick/colorspace.h"
#include "magick/colorspace-private.h"
#include "magick/compare.h"
#include "magick/composite-private.h"
#include "magick/constitute.h"
#include "magick/exception-private.h"
#include "magick/geometry.h"
#include "magick/image-private.h"
#include "magick/list.h"
#include "magick/log.h"
#include "magick/memory_.h"
#include "magick/monitor.h"
#include "magick/monitor-private.h"
#include "magick/option.h"
#include "magick/pixel-private.h"
#include "magick/property.h"
#include "magick/resource_.h"
#include "magick/string_.h"
#include "magick/string-private.h"
#include "magick/statistic.h"
#include "magick/thread-private.h"
#include "magick/transform.h"
#include "magick/utility.h"
#include "magick/version.h"
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% C o m p a r e I m a g e C h a n n e l s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% CompareImageChannels() compares one or more image channels of an image
% to a reconstructed image and returns the difference image.
%
% The format of the CompareImageChannels method is:
%
% Image *CompareImageChannels(const Image *image,
% const Image *reconstruct_image,const ChannelType channel,
% const MetricType metric,double *distortion,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o reconstruct_image: the reconstruct image.
%
% o channel: the channel.
%
% o metric: the metric.
%
% o distortion: the computed distortion between the images.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *CompareImages(Image *image,const Image *reconstruct_image,
const MetricType metric,double *distortion,ExceptionInfo *exception)
{
Image
*highlight_image;
highlight_image=CompareImageChannels(image,reconstruct_image,
CompositeChannels,metric,distortion,exception);
return(highlight_image);
}
MagickExport Image *CompareImageChannels(Image *image,
const Image *reconstruct_image,const ChannelType channel,
const MetricType metric,double *distortion,ExceptionInfo *exception)
{
CacheView
*highlight_view,
*image_view,
*reconstruct_view;
const char
*artifact;
Image
*difference_image,
*highlight_image;
MagickBooleanType
status;
MagickPixelPacket
highlight,
lowlight,
zero;
ssize_t
y;
assert(image != (Image *) NULL);
assert(image->signature == MagickSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(reconstruct_image != (const Image *) NULL);
assert(reconstruct_image->signature == MagickSignature);
assert(distortion != (double *) NULL);
*distortion=0.0;
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if ((reconstruct_image->columns != image->columns) ||
(reconstruct_image->rows != image->rows))
ThrowImageException(ImageError,"ImageSizeDiffers");
status=GetImageChannelDistortion(image,reconstruct_image,channel,metric,
distortion,exception);
if (status == MagickFalse)
return((Image *) NULL);
difference_image=CloneImage(image,0,0,MagickTrue,exception);
if (difference_image == (Image *) NULL)
return((Image *) NULL);
(void) SetImageAlphaChannel(difference_image,OpaqueAlphaChannel);
highlight_image=CloneImage(image,image->columns,image->rows,MagickTrue,
exception);
if (highlight_image == (Image *) NULL)
{
difference_image=DestroyImage(difference_image);
return((Image *) NULL);
}
if (SetImageStorageClass(highlight_image,DirectClass) == MagickFalse)
{
InheritException(exception,&highlight_image->exception);
difference_image=DestroyImage(difference_image);
highlight_image=DestroyImage(highlight_image);
return((Image *) NULL);
}
(void) SetImageAlphaChannel(highlight_image,OpaqueAlphaChannel);
(void) QueryMagickColor("#f1001ecc",&highlight,exception);
artifact=GetImageArtifact(image,"highlight-color");
if (artifact != (const char *) NULL)
(void) QueryMagickColor(artifact,&highlight,exception);
(void) QueryMagickColor("#ffffffcc",&lowlight,exception);
artifact=GetImageArtifact(image,"lowlight-color");
if (artifact != (const char *) NULL)
(void) QueryMagickColor(artifact,&lowlight,exception);
if (highlight_image->colorspace == CMYKColorspace)
{
ConvertRGBToCMYK(&highlight);
ConvertRGBToCMYK(&lowlight);
}
/*
Generate difference image.
*/
status=MagickTrue;
GetMagickPixelPacket(image,&zero);
image_view=AcquireVirtualCacheView(image,exception);
reconstruct_view=AcquireVirtualCacheView(reconstruct_image,exception);
highlight_view=AcquireAuthenticCacheView(highlight_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status) \
magick_threads(image,highlight_image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
MagickBooleanType
sync;
MagickPixelPacket
pixel,
reconstruct_pixel;
register const IndexPacket
*restrict indexes,
*restrict reconstruct_indexes;
register const PixelPacket
*restrict p,
*restrict q;
register IndexPacket
*restrict highlight_indexes;
register PixelPacket
*restrict r;
register ssize_t
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=GetCacheViewVirtualPixels(reconstruct_view,0,y,reconstruct_image->columns,
1,exception);
r=QueueCacheViewAuthenticPixels(highlight_view,0,y,highlight_image->columns,
1,exception);
if ((p == (const PixelPacket *) NULL) ||
(q == (const PixelPacket *) NULL) || (r == (PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
reconstruct_indexes=GetCacheViewVirtualIndexQueue(reconstruct_view);
highlight_indexes=GetCacheViewAuthenticIndexQueue(highlight_view);
pixel=zero;
reconstruct_pixel=zero;
for (x=0; x < (ssize_t) image->columns; x++)
{
MagickStatusType
difference;
SetMagickPixelPacket(image,p,indexes+x,&pixel);
SetMagickPixelPacket(reconstruct_image,q,reconstruct_indexes+x,
&reconstruct_pixel);
difference=MagickFalse;
if (channel == CompositeChannels)
{
if (IsMagickColorSimilar(&pixel,&reconstruct_pixel) == MagickFalse)
difference=MagickTrue;
}
else
{
if (((channel & RedChannel) != 0) &&
(GetPixelRed(p) != GetPixelRed(q)))
difference=MagickTrue;
if (((channel & GreenChannel) != 0) &&
(GetPixelGreen(p) != GetPixelGreen(q)))
difference=MagickTrue;
if (((channel & BlueChannel) != 0) &&
(GetPixelBlue(p) != GetPixelBlue(q)))
difference=MagickTrue;
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse) &&
(GetPixelOpacity(p) != GetPixelOpacity(q)))
difference=MagickTrue;
if ((((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace) &&
(reconstruct_image->colorspace == CMYKColorspace)) &&
(GetPixelIndex(indexes+x) !=
GetPixelIndex(reconstruct_indexes+x)))
difference=MagickTrue;
}
if (difference != MagickFalse)
SetPixelPacket(highlight_image,&highlight,r,highlight_indexes+x);
else
SetPixelPacket(highlight_image,&lowlight,r,highlight_indexes+x);
p++;
q++;
r++;
}
sync=SyncCacheViewAuthenticPixels(highlight_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
highlight_view=DestroyCacheView(highlight_view);
reconstruct_view=DestroyCacheView(reconstruct_view);
image_view=DestroyCacheView(image_view);
(void) CompositeImage(difference_image,image->compose,highlight_image,0,0);
highlight_image=DestroyImage(highlight_image);
if (status == MagickFalse)
difference_image=DestroyImage(difference_image);
return(difference_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e C h a n n e l D i s t o r t i o n %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageChannelDistortion() compares one or more image channels of an image
% to a reconstructed image and returns the specified distortion metric.
%
% The format of the GetImageChannelDistortion method is:
%
% MagickBooleanType GetImageChannelDistortion(const Image *image,
% const Image *reconstruct_image,const ChannelType channel,
% const MetricType metric,double *distortion,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o reconstruct_image: the reconstruct image.
%
% o channel: the channel.
%
% o metric: the metric.
%
% o distortion: the computed distortion between the images.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport MagickBooleanType GetImageDistortion(Image *image,
const Image *reconstruct_image,const MetricType metric,double *distortion,
ExceptionInfo *exception)
{
MagickBooleanType
status;
status=GetImageChannelDistortion(image,reconstruct_image,CompositeChannels,
metric,distortion,exception);
return(status);
}
static MagickBooleanType GetAbsoluteDistortion(const Image *image,
const Image *reconstruct_image,const ChannelType channel,double *distortion,
ExceptionInfo *exception)
{
CacheView
*image_view,
*reconstruct_view;
MagickBooleanType
status;
MagickPixelPacket
zero;
ssize_t
y;
/*
Compute the absolute difference in pixels between two images.
*/
status=MagickTrue;
GetMagickPixelPacket(image,&zero);
image_view=AcquireVirtualCacheView(image,exception);
reconstruct_view=AcquireVirtualCacheView(reconstruct_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status) \
magick_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
double
channel_distortion[CompositeChannels+1];
MagickPixelPacket
pixel,
reconstruct_pixel;
register const IndexPacket
*restrict indexes,
*restrict reconstruct_indexes;
register const PixelPacket
*restrict p,
*restrict q;
register ssize_t
i,
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=GetCacheViewVirtualPixels(reconstruct_view,0,y,reconstruct_image->columns,
1,exception);
if ((p == (const PixelPacket *) NULL) || (q == (const PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
reconstruct_indexes=GetCacheViewVirtualIndexQueue(reconstruct_view);
pixel=zero;
reconstruct_pixel=pixel;
(void) ResetMagickMemory(channel_distortion,0,sizeof(channel_distortion));
for (x=0; x < (ssize_t) image->columns; x++)
{
SetMagickPixelPacket(image,p,indexes+x,&pixel);
SetMagickPixelPacket(reconstruct_image,q,reconstruct_indexes+x,
&reconstruct_pixel);
if (IsMagickColorSimilar(&pixel,&reconstruct_pixel) == MagickFalse)
{
if ((channel & RedChannel) != 0)
channel_distortion[RedChannel]++;
if ((channel & GreenChannel) != 0)
channel_distortion[GreenChannel]++;
if ((channel & BlueChannel) != 0)
channel_distortion[BlueChannel]++;
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
channel_distortion[OpacityChannel]++;
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace))
channel_distortion[BlackChannel]++;
channel_distortion[CompositeChannels]++;
}
p++;
q++;
}
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_GetAbsoluteError)
#endif
for (i=0; i <= (ssize_t) CompositeChannels; i++)
distortion[i]+=channel_distortion[i];
}
reconstruct_view=DestroyCacheView(reconstruct_view);
image_view=DestroyCacheView(image_view);
return(status);
}
static size_t GetNumberChannels(const Image *image,
const ChannelType channel)
{
size_t
channels;
channels=0;
if ((channel & RedChannel) != 0)
channels++;
if ((channel & GreenChannel) != 0)
channels++;
if ((channel & BlueChannel) != 0)
channels++;
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
channels++;
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace))
channels++;
return(channels);
}
static MagickBooleanType GetFuzzDistortion(const Image *image,
const Image *reconstruct_image,const ChannelType channel,
double *distortion,ExceptionInfo *exception)
{
CacheView
*image_view,
*reconstruct_view;
MagickBooleanType
status;
register ssize_t
i;
ssize_t
y;
status=MagickTrue;
image_view=AcquireVirtualCacheView(image,exception);
reconstruct_view=AcquireVirtualCacheView(reconstruct_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status) \
magick_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
double
channel_distortion[CompositeChannels+1];
register const IndexPacket
*restrict indexes,
*restrict reconstruct_indexes;
register const PixelPacket
*restrict p,
*restrict q;
register ssize_t
i,
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=GetCacheViewVirtualPixels(reconstruct_view,0,y,reconstruct_image->columns,
1,exception);
if ((p == (const PixelPacket *) NULL) || (q == (const PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
reconstruct_indexes=GetCacheViewVirtualIndexQueue(reconstruct_view);
(void) ResetMagickMemory(channel_distortion,0,sizeof(channel_distortion));
for (x=0; x < (ssize_t) image->columns; x++)
{
MagickRealType
distance,
Da,
Sa;
Sa=QuantumScale*(image->matte != MagickFalse ? GetPixelAlpha(p) :
(QuantumRange-OpaqueOpacity));
Da=QuantumScale*(reconstruct_image->matte != MagickFalse ?
GetPixelAlpha(q) : (QuantumRange-OpaqueOpacity));
if ((channel & RedChannel) != 0)
{
distance=QuantumScale*(Sa*GetPixelRed(p)-Da*GetPixelRed(q));
channel_distortion[RedChannel]+=distance*distance;
channel_distortion[CompositeChannels]+=distance*distance;
}
if ((channel & GreenChannel) != 0)
{
distance=QuantumScale*(Sa*GetPixelGreen(p)-Da*GetPixelGreen(q));
channel_distortion[GreenChannel]+=distance*distance;
channel_distortion[CompositeChannels]+=distance*distance;
}
if ((channel & BlueChannel) != 0)
{
distance=QuantumScale*(Sa*GetPixelBlue(p)-Da*GetPixelBlue(q));
channel_distortion[BlueChannel]+=distance*distance;
channel_distortion[CompositeChannels]+=distance*distance;
}
if (((channel & OpacityChannel) != 0) && ((image->matte != MagickFalse) ||
(reconstruct_image->matte != MagickFalse)))
{
distance=QuantumScale*((image->matte != MagickFalse ?
GetPixelOpacity(p) : OpaqueOpacity)-
(reconstruct_image->matte != MagickFalse ?
GetPixelOpacity(q): OpaqueOpacity));
channel_distortion[OpacityChannel]+=distance*distance;
channel_distortion[CompositeChannels]+=distance*distance;
}
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace) &&
(reconstruct_image->colorspace == CMYKColorspace))
{
distance=QuantumScale*(Sa*GetPixelIndex(indexes+x)-
Da*GetPixelIndex(reconstruct_indexes+x));
channel_distortion[BlackChannel]+=distance*distance;
channel_distortion[CompositeChannels]+=distance*distance;
}
p++;
q++;
}
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_GetFuzzDistortion)
#endif
for (i=0; i <= (ssize_t) CompositeChannels; i++)
distortion[i]+=channel_distortion[i];
}
reconstruct_view=DestroyCacheView(reconstruct_view);
image_view=DestroyCacheView(image_view);
for (i=0; i <= (ssize_t) CompositeChannels; i++)
distortion[i]/=((double) image->columns*image->rows);
if (((channel & OpacityChannel) != 0) && ((image->matte != MagickFalse) ||
(reconstruct_image->matte != MagickFalse)))
distortion[CompositeChannels]/=(double) (GetNumberChannels(image,channel)-1);
else
distortion[CompositeChannels]/=(double) GetNumberChannels(image,channel);
distortion[CompositeChannels]=sqrt(distortion[CompositeChannels]);
return(status);
}
static MagickBooleanType GetMeanAbsoluteDistortion(const Image *image,
const Image *reconstruct_image,const ChannelType channel,
double *distortion,ExceptionInfo *exception)
{
CacheView
*image_view,
*reconstruct_view;
MagickBooleanType
status;
register ssize_t
i;
ssize_t
y;
status=MagickTrue;
image_view=AcquireVirtualCacheView(image,exception);
reconstruct_view=AcquireVirtualCacheView(reconstruct_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status) \
magick_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
double
channel_distortion[CompositeChannels+1];
register const IndexPacket
*restrict indexes,
*restrict reconstruct_indexes;
register const PixelPacket
*restrict p,
*restrict q;
register ssize_t
i,
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=GetCacheViewVirtualPixels(reconstruct_view,0,y,
reconstruct_image->columns,1,exception);
if ((p == (const PixelPacket *) NULL) || (q == (const PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
reconstruct_indexes=GetCacheViewVirtualIndexQueue(reconstruct_view);
(void) ResetMagickMemory(channel_distortion,0,sizeof(channel_distortion));
for (x=0; x < (ssize_t) image->columns; x++)
{
MagickRealType
distance,
Da,
Sa;
Sa=QuantumScale*(image->matte != MagickFalse ? GetPixelAlpha(p) :
(QuantumRange-OpaqueOpacity));
Da=QuantumScale*(reconstruct_image->matte != MagickFalse ?
GetPixelAlpha(q) : (QuantumRange-OpaqueOpacity));
if ((channel & RedChannel) != 0)
{
distance=QuantumScale*fabs(Sa*GetPixelRed(p)-Da*GetPixelRed(q));
channel_distortion[RedChannel]+=distance;
channel_distortion[CompositeChannels]+=distance;
}
if ((channel & GreenChannel) != 0)
{
distance=QuantumScale*fabs(Sa*GetPixelGreen(p)-Da*GetPixelGreen(q));
channel_distortion[GreenChannel]+=distance;
channel_distortion[CompositeChannels]+=distance;
}
if ((channel & BlueChannel) != 0)
{
distance=QuantumScale*fabs(Sa*GetPixelBlue(p)-Da*GetPixelBlue(q));
channel_distortion[BlueChannel]+=distance;
channel_distortion[CompositeChannels]+=distance;
}
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
{
distance=QuantumScale*fabs(GetPixelOpacity(p)-(double)
GetPixelOpacity(q));
channel_distortion[OpacityChannel]+=distance;
channel_distortion[CompositeChannels]+=distance;
}
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace))
{
distance=QuantumScale*fabs(Sa*GetPixelIndex(indexes+x)-Da*
GetPixelIndex(reconstruct_indexes+x));
channel_distortion[BlackChannel]+=distance;
channel_distortion[CompositeChannels]+=distance;
}
p++;
q++;
}
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_GetMeanAbsoluteError)
#endif
for (i=0; i <= (ssize_t) CompositeChannels; i++)
distortion[i]+=channel_distortion[i];
}
reconstruct_view=DestroyCacheView(reconstruct_view);
image_view=DestroyCacheView(image_view);
for (i=0; i <= (ssize_t) CompositeChannels; i++)
distortion[i]/=((double) image->columns*image->rows);
distortion[CompositeChannels]/=(double) GetNumberChannels(image,channel);
return(status);
}
static MagickBooleanType GetMeanErrorPerPixel(Image *image,
const Image *reconstruct_image,const ChannelType channel,double *distortion,
ExceptionInfo *exception)
{
CacheView
*image_view,
*reconstruct_view;
MagickBooleanType
status;
MagickRealType
area,
maximum_error,
mean_error;
ssize_t
y;
status=MagickTrue;
area=0.0;
maximum_error=0.0;
mean_error=0.0;
image_view=AcquireVirtualCacheView(image,exception);
reconstruct_view=AcquireVirtualCacheView(reconstruct_image,exception);
for (y=0; y < (ssize_t) image->rows; y++)
{
register const IndexPacket
*restrict indexes,
*restrict reconstruct_indexes;
register const PixelPacket
*restrict p,
*restrict q;
register ssize_t
x;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=GetCacheViewVirtualPixels(reconstruct_view,0,y,reconstruct_image->columns,
1,exception);
if ((p == (const PixelPacket *) NULL) || (q == (const PixelPacket *) NULL))
{
status=MagickFalse;
break;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
reconstruct_indexes=GetCacheViewVirtualIndexQueue(reconstruct_view);
for (x=0; x < (ssize_t) image->columns; x++)
{
MagickRealType
distance,
Da,
Sa;
Sa=QuantumScale*(image->matte != MagickFalse ? GetPixelAlpha(p) :
(QuantumRange-OpaqueOpacity));
Da=QuantumScale*(reconstruct_image->matte != MagickFalse ?
GetPixelAlpha(q) : (QuantumRange-OpaqueOpacity));
if ((channel & RedChannel) != 0)
{
distance=fabs(Sa*GetPixelRed(p)-Da*GetPixelRed(q));
distortion[RedChannel]+=distance;
distortion[CompositeChannels]+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
}
if ((channel & GreenChannel) != 0)
{
distance=fabs(Sa*GetPixelGreen(p)-Da*GetPixelGreen(q));
distortion[GreenChannel]+=distance;
distortion[CompositeChannels]+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
}
if ((channel & BlueChannel) != 0)
{
distance=fabs(Sa*GetPixelBlue(p)-Da*GetPixelBlue(q));
distortion[BlueChannel]+=distance;
distortion[CompositeChannels]+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
}
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
{
distance=fabs((double) GetPixelOpacity(p)-
GetPixelOpacity(q));
distortion[OpacityChannel]+=distance;
distortion[CompositeChannels]+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
}
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace) &&
(reconstruct_image->colorspace == CMYKColorspace))
{
distance=fabs(Sa*GetPixelIndex(indexes+x)-Da*
GetPixelIndex(reconstruct_indexes+x));
distortion[BlackChannel]+=distance;
distortion[CompositeChannels]+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
}
p++;
q++;
}
}
reconstruct_view=DestroyCacheView(reconstruct_view);
image_view=DestroyCacheView(image_view);
image->error.mean_error_per_pixel=distortion[CompositeChannels]/area;
image->error.normalized_mean_error=QuantumScale*QuantumScale*mean_error/area;
image->error.normalized_maximum_error=QuantumScale*maximum_error;
return(status);
}
static MagickBooleanType GetMeanSquaredDistortion(const Image *image,
const Image *reconstruct_image,const ChannelType channel,
double *distortion,ExceptionInfo *exception)
{
CacheView
*image_view,
*reconstruct_view;
MagickBooleanType
status;
register ssize_t
i;
ssize_t
y;
status=MagickTrue;
image_view=AcquireVirtualCacheView(image,exception);
reconstruct_view=AcquireVirtualCacheView(reconstruct_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status) \
magick_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
double
channel_distortion[CompositeChannels+1];
register const IndexPacket
*restrict indexes,
*restrict reconstruct_indexes;
register const PixelPacket
*restrict p,
*restrict q;
register ssize_t
i,
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=GetCacheViewVirtualPixels(reconstruct_view,0,y,
reconstruct_image->columns,1,exception);
if ((p == (const PixelPacket *) NULL) || (q == (const PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
reconstruct_indexes=GetCacheViewVirtualIndexQueue(reconstruct_view);
(void) ResetMagickMemory(channel_distortion,0,sizeof(channel_distortion));
for (x=0; x < (ssize_t) image->columns; x++)
{
MagickRealType
distance,
Da,
Sa;
Sa=QuantumScale*(image->matte != MagickFalse ? GetPixelAlpha(p) :
(QuantumRange-OpaqueOpacity));
Da=QuantumScale*(reconstruct_image->matte != MagickFalse ?
GetPixelAlpha(q) : (QuantumRange-OpaqueOpacity));
if ((channel & RedChannel) != 0)
{
distance=QuantumScale*(Sa*GetPixelRed(p)-Da*GetPixelRed(q));
channel_distortion[RedChannel]+=distance*distance;
channel_distortion[CompositeChannels]+=distance*distance;
}
if ((channel & GreenChannel) != 0)
{
distance=QuantumScale*(Sa*GetPixelGreen(p)-Da*GetPixelGreen(q));
channel_distortion[GreenChannel]+=distance*distance;
channel_distortion[CompositeChannels]+=distance*distance;
}
if ((channel & BlueChannel) != 0)
{
distance=QuantumScale*(Sa*GetPixelBlue(p)-Da*GetPixelBlue(q));
channel_distortion[BlueChannel]+=distance*distance;
channel_distortion[CompositeChannels]+=distance*distance;
}
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
{
distance=QuantumScale*(GetPixelOpacity(p)-(MagickRealType)
GetPixelOpacity(q));
channel_distortion[OpacityChannel]+=distance*distance;
channel_distortion[CompositeChannels]+=distance*distance;
}
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace) &&
(reconstruct_image->colorspace == CMYKColorspace))
{
distance=QuantumScale*(Sa*GetPixelIndex(indexes+x)-Da*
GetPixelIndex(reconstruct_indexes+x));
channel_distortion[BlackChannel]+=distance*distance;
channel_distortion[CompositeChannels]+=distance*distance;
}
p++;
q++;
}
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_GetMeanSquaredError)
#endif
for (i=0; i <= (ssize_t) CompositeChannels; i++)
distortion[i]+=channel_distortion[i];
}
reconstruct_view=DestroyCacheView(reconstruct_view);
image_view=DestroyCacheView(image_view);
for (i=0; i <= (ssize_t) CompositeChannels; i++)
distortion[i]/=((double) image->columns*image->rows);
distortion[CompositeChannels]/=(double) GetNumberChannels(image,channel);
return(status);
}
static MagickBooleanType GetNormalizedCrossCorrelationDistortion(
const Image *image,const Image *reconstruct_image,const ChannelType channel,
double *distortion,ExceptionInfo *exception)
{
#define SimilarityImageTag "Similarity/Image"
CacheView
*image_view,
*reconstruct_view;
ChannelStatistics
*image_statistics,
*reconstruct_statistics;
MagickBooleanType
status;
MagickOffsetType
progress;
MagickRealType
area;
register ssize_t
i;
ssize_t
y;
/*
Normalize to account for variation due to lighting and exposure condition.
*/
image_statistics=GetImageChannelStatistics(image,exception);
reconstruct_statistics=GetImageChannelStatistics(reconstruct_image,exception);
if ((image_statistics == (ChannelStatistics *) NULL) ||
(reconstruct_statistics == (ChannelStatistics *) NULL))
{
if (image_statistics != (ChannelStatistics *) NULL)
image_statistics=(ChannelStatistics *) RelinquishMagickMemory(
image_statistics);
if (reconstruct_statistics != (ChannelStatistics *) NULL)
reconstruct_statistics=(ChannelStatistics *) RelinquishMagickMemory(
reconstruct_statistics);
return(MagickFalse);
}
status=MagickTrue;
progress=0;
for (i=0; i <= (ssize_t) CompositeChannels; i++)
distortion[i]=0.0;
area=1.0/((MagickRealType) image->columns*image->rows-1);
image_view=AcquireVirtualCacheView(image,exception);
reconstruct_view=AcquireVirtualCacheView(reconstruct_image,exception);
for (y=0; y < (ssize_t) image->rows; y++)
{
register const IndexPacket
*restrict indexes,
*restrict reconstruct_indexes;
register const PixelPacket
*restrict p,
*restrict q;
register ssize_t
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=GetCacheViewVirtualPixels(reconstruct_view,0,y,reconstruct_image->columns,
1,exception);
if ((p == (const PixelPacket *) NULL) || (q == (const PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
reconstruct_indexes=GetCacheViewVirtualIndexQueue(reconstruct_view);
for (x=0; x < (ssize_t) image->columns; x++)
{
MagickRealType
Da,
Sa;
Sa=QuantumScale*(image->matte != MagickFalse ? GetPixelAlpha(p) :
(QuantumRange-OpaqueOpacity));
Da=QuantumScale*(reconstruct_image->matte != MagickFalse ?
GetPixelAlpha(q) : (QuantumRange-OpaqueOpacity));
if ((channel & RedChannel) != 0)
distortion[RedChannel]+=area*QuantumScale*(Sa*GetPixelRed(p)-
image_statistics[RedChannel].mean)*(Da*GetPixelRed(q)-
reconstruct_statistics[RedChannel].mean);
if ((channel & GreenChannel) != 0)
distortion[GreenChannel]+=area*QuantumScale*(Sa*GetPixelGreen(p)-
image_statistics[GreenChannel].mean)*(Da*GetPixelGreen(q)-
reconstruct_statistics[GreenChannel].mean);
if ((channel & BlueChannel) != 0)
distortion[BlueChannel]+=area*QuantumScale*(Sa*GetPixelBlue(p)-
image_statistics[BlueChannel].mean)*(Da*GetPixelBlue(q)-
reconstruct_statistics[BlueChannel].mean);
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
distortion[OpacityChannel]+=area*QuantumScale*(
GetPixelOpacity(p)-image_statistics[OpacityChannel].mean)*
(GetPixelOpacity(q)-reconstruct_statistics[OpacityChannel].mean);
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace) &&
(reconstruct_image->colorspace == CMYKColorspace))
distortion[BlackChannel]+=area*QuantumScale*(Sa*
GetPixelIndex(indexes+x)-
image_statistics[OpacityChannel].mean)*(Da*
GetPixelIndex(reconstruct_indexes+x)-
reconstruct_statistics[OpacityChannel].mean);
p++;
q++;
}
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
proceed=SetImageProgress(image,SimilarityImageTag,progress++,
image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
reconstruct_view=DestroyCacheView(reconstruct_view);
image_view=DestroyCacheView(image_view);
/*
Divide by the standard deviation.
*/
for (i=0; i < (ssize_t) CompositeChannels; i++)
{
double
gamma;
gamma=image_statistics[i].standard_deviation*
reconstruct_statistics[i].standard_deviation;
gamma=PerceptibleReciprocal(gamma);
distortion[i]=QuantumRange*gamma*distortion[i];
}
distortion[CompositeChannels]=0.0;
if ((channel & RedChannel) != 0)
distortion[CompositeChannels]+=distortion[RedChannel]*
distortion[RedChannel];
if ((channel & GreenChannel) != 0)
distortion[CompositeChannels]+=distortion[GreenChannel]*
distortion[GreenChannel];
if ((channel & BlueChannel) != 0)
distortion[CompositeChannels]+=distortion[BlueChannel]*
distortion[BlueChannel];
if (((channel & OpacityChannel) != 0) && (image->matte != MagickFalse))
distortion[CompositeChannels]+=distortion[OpacityChannel]*
distortion[OpacityChannel];
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace))
distortion[CompositeChannels]+=distortion[BlackChannel]*
distortion[BlackChannel];
distortion[CompositeChannels]=sqrt(distortion[CompositeChannels]/
GetNumberChannels(image,channel));
/*
Free resources.
*/
reconstruct_statistics=(ChannelStatistics *) RelinquishMagickMemory(
reconstruct_statistics);
image_statistics=(ChannelStatistics *) RelinquishMagickMemory(
image_statistics);
return(status);
}
static MagickBooleanType GetPeakAbsoluteDistortion(const Image *image,
const Image *reconstruct_image,const ChannelType channel,
double *distortion,ExceptionInfo *exception)
{
CacheView
*image_view,
*reconstruct_view;
MagickBooleanType
status;
ssize_t
y;
status=MagickTrue;
image_view=AcquireVirtualCacheView(image,exception);
reconstruct_view=AcquireVirtualCacheView(reconstruct_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status) \
magick_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
double
channel_distortion[CompositeChannels+1];
register const IndexPacket
*restrict indexes,
*restrict reconstruct_indexes;
register const PixelPacket
*restrict p,
*restrict q;
register ssize_t
i,
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=GetCacheViewVirtualPixels(reconstruct_view,0,y,
reconstruct_image->columns,1,exception);
if ((p == (const PixelPacket *) NULL) || (q == (const PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
reconstruct_indexes=GetCacheViewVirtualIndexQueue(reconstruct_view);
(void) ResetMagickMemory(channel_distortion,0,sizeof(channel_distortion));
for (x=0; x < (ssize_t) image->columns; x++)
{
MagickRealType
distance,
Da,
Sa;
Sa=QuantumScale*(image->matte != MagickFalse ? GetPixelAlpha(p) :
(QuantumRange-OpaqueOpacity));
Da=QuantumScale*(reconstruct_image->matte != MagickFalse ?
GetPixelAlpha(q) : (QuantumRange-OpaqueOpacity));
if ((channel & RedChannel) != 0)
{
distance=QuantumScale*fabs(Sa*GetPixelRed(p)-Da*GetPixelRed(q));
if (distance > channel_distortion[RedChannel])
channel_distortion[RedChannel]=distance;
if (distance > channel_distortion[CompositeChannels])
channel_distortion[CompositeChannels]=distance;
}
if ((channel & GreenChannel) != 0)
{
distance=QuantumScale*fabs(Sa*GetPixelGreen(p)-Da*GetPixelGreen(q));
if (distance > channel_distortion[GreenChannel])
channel_distortion[GreenChannel]=distance;
if (distance > channel_distortion[CompositeChannels])
channel_distortion[CompositeChannels]=distance;
}
if ((channel & BlueChannel) != 0)
{
distance=QuantumScale*fabs(Sa*GetPixelBlue(p)-Da*GetPixelBlue(q));
if (distance > channel_distortion[BlueChannel])
channel_distortion[BlueChannel]=distance;
if (distance > channel_distortion[CompositeChannels])
channel_distortion[CompositeChannels]=distance;
}
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
{
distance=QuantumScale*fabs(GetPixelOpacity(p)-(double)
GetPixelOpacity(q));
if (distance > channel_distortion[OpacityChannel])
channel_distortion[OpacityChannel]=distance;
if (distance > channel_distortion[CompositeChannels])
channel_distortion[CompositeChannels]=distance;
}
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace) &&
(reconstruct_image->colorspace == CMYKColorspace))
{
distance=QuantumScale*fabs(Sa*GetPixelIndex(indexes+x)-Da*
GetPixelIndex(reconstruct_indexes+x));
if (distance > channel_distortion[BlackChannel])
channel_distortion[BlackChannel]=distance;
if (distance > channel_distortion[CompositeChannels])
channel_distortion[CompositeChannels]=distance;
}
p++;
q++;
}
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_GetPeakAbsoluteError)
#endif
for (i=0; i <= (ssize_t) CompositeChannels; i++)
if (channel_distortion[i] > distortion[i])
distortion[i]=channel_distortion[i];
}
reconstruct_view=DestroyCacheView(reconstruct_view);
image_view=DestroyCacheView(image_view);
return(status);
}
static MagickBooleanType GetPeakSignalToNoiseRatio(const Image *image,
const Image *reconstruct_image,const ChannelType channel,
double *distortion,ExceptionInfo *exception)
{
MagickBooleanType
status;
status=GetMeanSquaredDistortion(image,reconstruct_image,channel,distortion,
exception);
if ((channel & RedChannel) != 0)
distortion[RedChannel]=20.0*log10((double) 1.0/sqrt(
distortion[RedChannel]));
if ((channel & GreenChannel) != 0)
distortion[GreenChannel]=20.0*log10((double) 1.0/sqrt(
distortion[GreenChannel]));
if ((channel & BlueChannel) != 0)
distortion[BlueChannel]=20.0*log10((double) 1.0/sqrt(
distortion[BlueChannel]));
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
distortion[OpacityChannel]=20.0*log10((double) 1.0/sqrt(
distortion[OpacityChannel]));
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace))
distortion[BlackChannel]=20.0*log10((double) 1.0/sqrt(
distortion[BlackChannel]));
distortion[CompositeChannels]=20.0*log10((double) 1.0/sqrt(
distortion[CompositeChannels]));
return(status);
}
static MagickBooleanType GetRootMeanSquaredDistortion(const Image *image,
const Image *reconstruct_image,const ChannelType channel,
double *distortion,ExceptionInfo *exception)
{
MagickBooleanType
status;
status=GetMeanSquaredDistortion(image,reconstruct_image,channel,distortion,
exception);
if ((channel & RedChannel) != 0)
distortion[RedChannel]=sqrt(distortion[RedChannel]);
if ((channel & GreenChannel) != 0)
distortion[GreenChannel]=sqrt(distortion[GreenChannel]);
if ((channel & BlueChannel) != 0)
distortion[BlueChannel]=sqrt(distortion[BlueChannel]);
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
distortion[OpacityChannel]=sqrt(distortion[OpacityChannel]);
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace))
distortion[BlackChannel]=sqrt(distortion[BlackChannel]);
distortion[CompositeChannels]=sqrt(distortion[CompositeChannels]);
return(status);
}
MagickExport MagickBooleanType GetImageChannelDistortion(Image *image,
const Image *reconstruct_image,const ChannelType channel,
const MetricType metric,double *distortion,ExceptionInfo *exception)
{
double
*channel_distortion;
MagickBooleanType
status;
size_t
length;
assert(image != (Image *) NULL);
assert(image->signature == MagickSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(reconstruct_image != (const Image *) NULL);
assert(reconstruct_image->signature == MagickSignature);
assert(distortion != (double *) NULL);
*distortion=0.0;
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if ((reconstruct_image->columns != image->columns) ||
(reconstruct_image->rows != image->rows))
ThrowBinaryException(ImageError,"ImageSizeDiffers",image->filename);
/*
Get image distortion.
*/
length=CompositeChannels+1UL;
channel_distortion=(double *) AcquireQuantumMemory(length,
sizeof(*channel_distortion));
if (channel_distortion == (double *) NULL)
ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
(void) ResetMagickMemory(channel_distortion,0,length*
sizeof(*channel_distortion));
switch (metric)
{
case AbsoluteErrorMetric:
{
status=GetAbsoluteDistortion(image,reconstruct_image,channel,
channel_distortion,exception);
break;
}
case FuzzErrorMetric:
{
status=GetFuzzDistortion(image,reconstruct_image,channel,
channel_distortion,exception);
break;
}
case MeanAbsoluteErrorMetric:
{
status=GetMeanAbsoluteDistortion(image,reconstruct_image,channel,
channel_distortion,exception);
break;
}
case MeanErrorPerPixelMetric:
{
status=GetMeanErrorPerPixel(image,reconstruct_image,channel,
channel_distortion,exception);
break;
}
case MeanSquaredErrorMetric:
{
status=GetMeanSquaredDistortion(image,reconstruct_image,channel,
channel_distortion,exception);
break;
}
case NormalizedCrossCorrelationErrorMetric:
default:
{
status=GetNormalizedCrossCorrelationDistortion(image,reconstruct_image,
channel,channel_distortion,exception);
break;
}
case PeakAbsoluteErrorMetric:
{
status=GetPeakAbsoluteDistortion(image,reconstruct_image,channel,
channel_distortion,exception);
break;
}
case PeakSignalToNoiseRatioMetric:
{
status=GetPeakSignalToNoiseRatio(image,reconstruct_image,channel,
channel_distortion,exception);
break;
}
case RootMeanSquaredErrorMetric:
{
status=GetRootMeanSquaredDistortion(image,reconstruct_image,channel,
channel_distortion,exception);
break;
}
}
*distortion=channel_distortion[CompositeChannels];
channel_distortion=(double *) RelinquishMagickMemory(channel_distortion);
(void) FormatImageProperty(image,"distortion","%.*g",GetMagickPrecision(),
*distortion);
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e C h a n n e l D i s t o r t i o n s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageChannelDistortions() compares the image channels of an image to a
% reconstructed image and returns the specified distortion metric for each
% channel.
%
% The format of the GetImageChannelDistortions method is:
%
% double *GetImageChannelDistortions(const Image *image,
% const Image *reconstruct_image,const MetricType metric,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o reconstruct_image: the reconstruct image.
%
% o metric: the metric.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport double *GetImageChannelDistortions(Image *image,
const Image *reconstruct_image,const MetricType metric,
ExceptionInfo *exception)
{
double
*channel_distortion;
MagickBooleanType
status;
size_t
length;
assert(image != (Image *) NULL);
assert(image->signature == MagickSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(reconstruct_image != (const Image *) NULL);
assert(reconstruct_image->signature == MagickSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if ((reconstruct_image->columns != image->columns) ||
(reconstruct_image->rows != image->rows))
{
(void) ThrowMagickException(&image->exception,GetMagickModule(),
ImageError,"ImageSizeDiffers","`%s'",image->filename);
return((double *) NULL);
}
/*
Get image distortion.
*/
length=CompositeChannels+1UL;
channel_distortion=(double *) AcquireQuantumMemory(length,
sizeof(*channel_distortion));
if (channel_distortion == (double *) NULL)
ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
(void) ResetMagickMemory(channel_distortion,0,length*
sizeof(*channel_distortion));
status=MagickTrue;
switch (metric)
{
case AbsoluteErrorMetric:
{
status=GetAbsoluteDistortion(image,reconstruct_image,CompositeChannels,
channel_distortion,exception);
break;
}
case FuzzErrorMetric:
{
status=GetFuzzDistortion(image,reconstruct_image,CompositeChannels,
channel_distortion,exception);
break;
}
case MeanAbsoluteErrorMetric:
{
status=GetMeanAbsoluteDistortion(image,reconstruct_image,
CompositeChannels,channel_distortion,exception);
break;
}
case MeanErrorPerPixelMetric:
{
status=GetMeanErrorPerPixel(image,reconstruct_image,CompositeChannels,
channel_distortion,exception);
break;
}
case MeanSquaredErrorMetric:
{
status=GetMeanSquaredDistortion(image,reconstruct_image,CompositeChannels,
channel_distortion,exception);
break;
}
case NormalizedCrossCorrelationErrorMetric:
default:
{
status=GetNormalizedCrossCorrelationDistortion(image,reconstruct_image,
CompositeChannels,channel_distortion,exception);
break;
}
case PeakAbsoluteErrorMetric:
{
status=GetPeakAbsoluteDistortion(image,reconstruct_image,
CompositeChannels,channel_distortion,exception);
break;
}
case PeakSignalToNoiseRatioMetric:
{
status=GetPeakSignalToNoiseRatio(image,reconstruct_image,
CompositeChannels,channel_distortion,exception);
break;
}
case RootMeanSquaredErrorMetric:
{
status=GetRootMeanSquaredDistortion(image,reconstruct_image,
CompositeChannels,channel_distortion,exception);
break;
}
}
if (status == MagickFalse)
{
channel_distortion=(double *) RelinquishMagickMemory(channel_distortion);
return((double *) NULL);
}
return(channel_distortion);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% I s I m a g e s E q u a l %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% IsImagesEqual() measures the difference between colors at each pixel
% location of two images. A value other than 0 means the colors match
% exactly. Otherwise an error measure is computed by summing over all
% pixels in an image the distance squared in RGB space between each image
% pixel and its corresponding pixel in the reconstruct image. The error
% measure is assigned to these image members:
%
% o mean_error_per_pixel: The mean error for any single pixel in
% the image.
%
% o normalized_mean_error: The normalized mean quantization error for
% any single pixel in the image. This distance measure is normalized to
% a range between 0 and 1. It is independent of the range of red, green,
% and blue values in the image.
%
% o normalized_maximum_error: The normalized maximum quantization
% error for any single pixel in the image. This distance measure is
% normalized to a range between 0 and 1. It is independent of the range
% of red, green, and blue values in your image.
%
% A small normalized mean square error, accessed as
% image->normalized_mean_error, suggests the images are very similar in
% spatial layout and color.
%
% The format of the IsImagesEqual method is:
%
% MagickBooleanType IsImagesEqual(Image *image,
% const Image *reconstruct_image)
%
% A description of each parameter follows.
%
% o image: the image.
%
% o reconstruct_image: the reconstruct image.
%
*/
MagickExport MagickBooleanType IsImagesEqual(Image *image,
const Image *reconstruct_image)
{
CacheView
*image_view,
*reconstruct_view;
ExceptionInfo
*exception;
MagickBooleanType
status;
MagickRealType
area,
maximum_error,
mean_error,
mean_error_per_pixel;
ssize_t
y;
assert(image != (Image *) NULL);
assert(image->signature == MagickSignature);
assert(reconstruct_image != (const Image *) NULL);
assert(reconstruct_image->signature == MagickSignature);
if ((reconstruct_image->columns != image->columns) ||
(reconstruct_image->rows != image->rows))
ThrowBinaryException(ImageError,"ImageSizeDiffers",image->filename);
area=0.0;
maximum_error=0.0;
mean_error_per_pixel=0.0;
mean_error=0.0;
exception=(&image->exception);
image_view=AcquireVirtualCacheView(image,exception);
reconstruct_view=AcquireVirtualCacheView(reconstruct_image,exception);
for (y=0; y < (ssize_t) image->rows; y++)
{
register const IndexPacket
*restrict indexes,
*restrict reconstruct_indexes;
register const PixelPacket
*restrict p,
*restrict q;
register ssize_t
x;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=GetCacheViewVirtualPixels(reconstruct_view,0,y,reconstruct_image->columns,
1,exception);
if ((p == (const PixelPacket *) NULL) || (q == (const PixelPacket *) NULL))
break;
indexes=GetCacheViewVirtualIndexQueue(image_view);
reconstruct_indexes=GetCacheViewVirtualIndexQueue(reconstruct_view);
for (x=0; x < (ssize_t) image->columns; x++)
{
MagickRealType
distance;
distance=fabs(GetPixelRed(p)-(double) GetPixelRed(q));
mean_error_per_pixel+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
distance=fabs(GetPixelGreen(p)-(double) GetPixelGreen(q));
mean_error_per_pixel+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
distance=fabs(GetPixelBlue(p)-(double) GetPixelBlue(q));
mean_error_per_pixel+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
if (image->matte != MagickFalse)
{
distance=fabs(GetPixelOpacity(p)-(double) GetPixelOpacity(q));
mean_error_per_pixel+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
}
if ((image->colorspace == CMYKColorspace) &&
(reconstruct_image->colorspace == CMYKColorspace))
{
distance=fabs(GetPixelIndex(indexes+x)-(double)
GetPixelIndex(reconstruct_indexes+x));
mean_error_per_pixel+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
}
p++;
q++;
}
}
reconstruct_view=DestroyCacheView(reconstruct_view);
image_view=DestroyCacheView(image_view);
image->error.mean_error_per_pixel=(double) (mean_error_per_pixel/area);
image->error.normalized_mean_error=(double) (QuantumScale*QuantumScale*
mean_error/area);
image->error.normalized_maximum_error=(double) (QuantumScale*maximum_error);
status=image->error.mean_error_per_pixel == 0.0 ? MagickTrue : MagickFalse;
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S i m i l a r i t y I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SimilarityImage() compares the reference image of the image and returns the
% best match offset. In addition, it returns a similarity image such that an
% exact match location is completely white and if none of the pixels match,
% black, otherwise some gray level in-between.
%
% The format of the SimilarityImageImage method is:
%
% Image *SimilarityImage(const Image *image,const Image *reference,
% RectangleInfo *offset,double *similarity,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o reference: find an area of the image that closely resembles this image.
%
% o the best match offset of the reference image within the image.
%
% o similarity: the computed similarity between the images.
%
% o exception: return any errors or warnings in this structure.
%
*/
static double GetSimilarityMetric(const Image *image,const Image *reference,
const MetricType metric,const ssize_t x_offset,const ssize_t y_offset,
ExceptionInfo *exception)
{
double
distortion;
Image
*similarity_image;
MagickBooleanType
status;
RectangleInfo
geometry;
SetGeometry(reference,&geometry);
geometry.x=x_offset;
geometry.y=y_offset;
similarity_image=CropImage(image,&geometry,exception);
if (similarity_image == (Image *) NULL)
return(0.0);
distortion=0.0;
status=GetImageDistortion(similarity_image,reference,metric,&distortion,
exception);
(void) status;
similarity_image=DestroyImage(similarity_image);
return(distortion);
}
MagickExport Image *SimilarityImage(Image *image,const Image *reference,
RectangleInfo *offset,double *similarity_metric,ExceptionInfo *exception)
{
Image
*similarity_image;
similarity_image=SimilarityMetricImage(image,reference,
RootMeanSquaredErrorMetric,offset,similarity_metric,exception);
return(similarity_image);
}
MagickExport Image *SimilarityMetricImage(Image *image,const Image *reference,
const MetricType metric,RectangleInfo *offset,double *similarity_metric,
ExceptionInfo *exception)
{
#define SimilarityImageTag "Similarity/Image"
CacheView
*similarity_view;
const char
*artifact;
double
similarity_threshold;
Image
*similarity_image;
MagickBooleanType
status;
MagickOffsetType
progress;
ssize_t
y;
assert(image != (const Image *) NULL);
assert(image->signature == MagickSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickSignature);
assert(offset != (RectangleInfo *) NULL);
SetGeometry(reference,offset);
*similarity_metric=1.0;
if ((reference->columns > image->columns) || (reference->rows > image->rows))
ThrowImageException(ImageError,"ImageSizeDiffers");
similarity_image=CloneImage(image,image->columns-reference->columns+1,
image->rows-reference->rows+1,MagickTrue,exception);
if (similarity_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(similarity_image,DirectClass) == MagickFalse)
{
InheritException(exception,&similarity_image->exception);
similarity_image=DestroyImage(similarity_image);
return((Image *) NULL);
}
(void) SetImageAlphaChannel(similarity_image,DeactivateAlphaChannel);
/*
Measure similarity of reference image against image.
*/
similarity_threshold=(-1.0);
artifact=GetImageArtifact(image,"compare:similarity-threshold");
if (artifact != (const char *) NULL)
similarity_threshold=StringToDouble(artifact,(char **) NULL);
status=MagickTrue;
progress=0;
similarity_view=AcquireVirtualCacheView(similarity_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) \
shared(progress,status,similarity_metric) \
magick_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) (image->rows-reference->rows+1); y++)
{
double
similarity;
register ssize_t
x;
register PixelPacket
*restrict q;
if (status == MagickFalse)
continue;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp flush(similarity_metric)
#endif
if (*similarity_metric <= similarity_threshold)
continue;
q=GetCacheViewAuthenticPixels(similarity_view,0,y,similarity_image->columns,
1,exception);
if (q == (const PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) (image->columns-reference->columns+1); x++)
{
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp flush(similarity_metric)
#endif
if (*similarity_metric <= similarity_threshold)
break;
similarity=GetSimilarityMetric(image,reference,metric,x,y,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_SimilarityImage)
#endif
if (similarity < *similarity_metric)
{
*similarity_metric=similarity;
offset->x=x;
offset->y=y;
}
SetPixelRed(q,ClampToQuantum(QuantumRange-QuantumRange*similarity));
SetPixelGreen(q,GetPixelRed(q));
SetPixelBlue(q,GetPixelRed(q));
q++;
}
if (SyncCacheViewAuthenticPixels(similarity_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_SimilarityImage)
#endif
proceed=SetImageProgress(image,SimilarityImageTag,progress++,
image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
similarity_view=DestroyCacheView(similarity_view);
if (status == MagickFalse)
similarity_image=DestroyImage(similarity_image);
return(similarity_image);
}
|
GB_unaryop__ainv_int32_uint16.c | //------------------------------------------------------------------------------
// GB_unaryop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2020, All Rights Reserved.
// http://suitesparse.com See GraphBLAS/Doc/License.txt for license.
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_iterator.h"
#include "GB_unaryop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB_unop__ainv_int32_uint16
// op(A') function: GB_tran__ainv_int32_uint16
// C type: int32_t
// A type: uint16_t
// cast: int32_t cij = (int32_t) aij
// unaryop: cij = -aij
#define GB_ATYPE \
uint16_t
#define GB_CTYPE \
int32_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
uint16_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = -x ;
// casting
#define GB_CASTING(z, aij) \
int32_t z = (int32_t) aij ;
// cij = op (cast (aij))
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GB_GETA (aij, Ax, pA) ; \
/* Cx [pC] = op (cast (aij)) */ \
GB_CASTING (z, aij) ; \
GB_OP (GB_CX (pC), z) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_AINV || GxB_NO_INT32 || GxB_NO_UINT16)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__ainv_int32_uint16
(
int32_t *Cx, // Cx and Ax may be aliased
uint16_t *Ax,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
GB_CAST_OP (p, p) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_tran__ainv_int32_uint16
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *GB_RESTRICT *Rowcounts,
GBI_single_iterator Iter,
const int64_t *GB_RESTRICT A_slice,
int naslice
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#define GB_PHASE_2_OF_2
#include "GB_unaryop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
GB_unaryop__lnot_uint32_int16.c | //------------------------------------------------------------------------------
// GB_unaryop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2019, All Rights Reserved.
// http://suitesparse.com See GraphBLAS/Doc/License.txt for license.
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_iterator.h"
#include "GB_unaryop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB_unop__lnot_uint32_int16
// op(A') function: GB_tran__lnot_uint32_int16
// C type: uint32_t
// A type: int16_t
// cast: uint32_t cij = (uint32_t) aij
// unaryop: cij = !(aij != 0)
#define GB_ATYPE \
int16_t
#define GB_CTYPE \
uint32_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
int16_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = !(x != 0) ;
// casting
#define GB_CASTING(z, x) \
uint32_t z = (uint32_t) x ;
// cij = op (cast (aij))
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GB_GETA (aij, Ax, pA) ; \
/* Cx [pC] = op (cast (aij)) */ \
GB_CASTING (x, aij) ; \
GB_OP (GB_CX (pC), x) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_LNOT || GxB_NO_UINT32 || GxB_NO_INT16)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__lnot_uint32_int16
(
uint32_t *restrict Cx,
const int16_t *restrict Ax,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (int64_t p = 0 ; p < anz ; p++)
{
GB_CAST_OP (p, p) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_tran__lnot_uint32_int16
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *restrict *Rowcounts,
GBI_single_iterator Iter,
const int64_t *restrict A_slice,
int naslice
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#define GB_PHASE_2_OF_2
#include "GB_unaryop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
convert.c | /*
This file is part of ParTI!.
ParTI! is free software: you can redistribute it and/or modify
it under the terms of the GNU Lesser General Public License as
published by the Free Software Foundation, either version 3 of
the License, or (at your option) any later version.
ParTI! is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with ParTI!.
If not, see <http://www.gnu.org/licenses/>.
*/
#include <HiParTI.h>
#include "../sptensor.h"
#include "hicoo.h"
/**
* Compare two coordinates, in the order of mode-0,...,N-1. One from the sparse tensor, the other is specified.
* @param tsr a pointer to a sparse tensor
* @return 1, z > item; otherwise, 0.
*/
static int ptiLargerThanCoordinates(
ptiSparseTensor *tsr,
const ptiNnzIndex z,
const ptiIndex * item)
{
ptiIndex nmodes = tsr->nmodes;
ptiIndex i1, i2;
for(ptiIndex m=0; m<nmodes; ++m) {
i1 = tsr->inds[m].data[z];
i2 = item[m];
if(i1 > i2) {
return 1;
break;
}
}
return 0;
}
/**
* Compare two coordinates, in the order of mode-0,...,N-1. One from the sparse tensor, the other is specified.
* @param tsr a pointer to a sparse tensor
* @return 1, z < item; otherwise, 0.
*/
static int ptiSmallerThanCoordinates(
ptiSparseTensor *tsr,
const ptiNnzIndex z,
const ptiIndex * item)
{
ptiIndex nmodes = tsr->nmodes;
ptiIndex i1, i2;
for(ptiIndex m=0; m<nmodes; ++m) {
i1 = tsr->inds[m].data[z];
i2 = item[m];
if(i1 < i2) {
return 1;
break;
}
}
return 0;
}
/**
* Compare two coordinates, in the order of mode-0,...,N-1. One from the sparse tensor, the other is specified.
* @param tsr a pointer to a sparse tensor
* @return 1, z = item; otherwise, 0.
*/
static int ptiEqualWithCoordinates(
ptiSparseTensor *tsr,
const ptiNnzIndex z,
const ptiIndex * item)
{
ptiIndex nmodes = tsr->nmodes;
ptiIndex i1, i2;
for(ptiIndex m=0; m<nmodes; ++m) {
i1 = tsr->inds[m].data[z];
i2 = item[m];
if(i1 != i2) {
return 0;
break;
}
}
return 1;
}
/**
* Compare two specified coordinates.
* @param tsr a pointer to a sparse tensor
* @return 1, z == item; otherwise, 0.
*/
static int ptiEqualWithTwoCoordinates(
const ptiIndex * item1,
const ptiIndex * item2,
const ptiIndex nmodes)
{
ptiIndex i1, i2;
for(ptiIndex m=0; m<nmodes; ++m) {
i1 = item1[m];
i2 = item2[m];
if(i1 != i2) {
return 0;
break;
}
}
return 1;
}
/**
* Check if a nonzero item is in the range of two given coordinates, in the order of mode-0,...,N-1.
* @param tsr a pointer to a sparse tensor
* @return 1, yes; 0, no.
*/
static int ptiCoordinatesInRange(
ptiSparseTensor *tsr,
const ptiNnzIndex z,
const ptiIndex * range_begin,
const ptiIndex * range_end)
{
if ( (ptiLargerThanCoordinates(tsr, z, range_begin) == 1 ||
ptiEqualWithCoordinates(tsr, z, range_begin) == 1) &&
ptiSmallerThanCoordinates(tsr, z, range_end) == 1) {
return 1;
}
return 0;
}
/**
* Compute the beginning of the next block
* @param tsr a pointer to a sparse tensor
* @return out_item the beginning indices of the next block
*/
static int ptiNextBlockBegin(
ptiIndex * out_item,
ptiSparseTensor *tsr,
const ptiIndex * in_item,
const ptiElementIndex sb)
{
ptiIndex nmodes = tsr->nmodes;
for(int32_t m=nmodes-1; m>=0; --m) {
if(in_item[m] < tsr->ndims[m]-1) {
out_item[m] = in_item[m]+sb-1 < tsr->ndims[m] ? in_item[m]+sb-1 : tsr->ndims[m] - 1;
break;
}
}
return 0;
}
/**
* Compute the end of this block
* @param tsr a pointer to a sparse tensor
* @return out_item the end indices of this block
*/
static int ptiBlockEnd(
ptiIndex * out_item,
ptiSparseTensor *tsr,
const ptiIndex * in_item,
const ptiElementIndex sb)
{
ptiIndex nmodes = tsr->nmodes;
for(ptiIndex m=0; m<nmodes; ++m) {
ptiAssert(in_item[m] < tsr->ndims[m]);
out_item[m] = in_item[m]+sb < tsr->ndims[m] ? in_item[m]+sb : tsr->ndims[m]; // exclusive
}
return 0;
}
/**
* Locate the beginning of the block/kernel containing the coordinates
* @param tsr a pointer to a sparse tensor
* @return out_item the beginning indices of this block
*/
static int ptiLocateBeginCoord(
ptiIndex * out_item,
ptiSparseTensor *tsr,
const ptiIndex * in_item,
const ptiElementIndex bits)
{
ptiIndex nmodes = tsr->nmodes;
for(ptiIndex m=0; m<nmodes; ++m) {
out_item[m] = in_item[m] >> bits;
}
return 0;
}
/**
* Compute the strides for kernels, mode order N-1, ..., 0 (row-like major)
* @param tsr a pointer to a sparse tensor
* @return out_item the beginning indices of this block
*/
static int ptiKernelStrides(
ptiIndex * strides,
ptiSparseTensor *tsr,
const ptiIndex sk)
{
ptiIndex nmodes = tsr->nmodes;
ptiIndex kernel_size = 0;
// TODO: efficiently use bitwise operation
strides[nmodes-1] = 1;
for(ptiIndex m=nmodes-2; m>=1; --m) {
kernel_size = (ptiIndex)(tsr->ndims[m+1] + sk - 1) / sk;
strides[m] = strides[m+1] * kernel_size;
}
kernel_size = (ptiIndex)(tsr->ndims[1] + sk - 1) / sk;
strides[0] = strides[1] * kernel_size;
return 0;
}
/**
* Compute the end of this kernel
* @param tsr a pointer to a sparse tensor
* @return out_item the end indices of this block
*/
static int ptiKernelEnd(
ptiIndex * out_item,
ptiSparseTensor *tsr,
const ptiIndex * in_item,
const ptiIndex sk)
{
ptiIndex nmodes = tsr->nmodes;
for(ptiIndex m=0; m<nmodes; ++m) {
ptiAssert(in_item[m] < tsr->ndims[m]);
out_item[m] = in_item[m]+sk < tsr->ndims[m] ? in_item[m]+sk : tsr->ndims[m]; // exclusive
}
return 0;
}
/**
* Record mode pointers for kernel rows, from a sorted tensor.
* @param mptr a vector of pointers as a dense array
* @param tsr a pointer to a sparse tensor
* @return mode pointers
*/
int ptiGetRowBlockPointers(
ptiNnzIndexVector *mptr,
ptiSparseTensor *tsr,
const ptiIndex sk)
{
ptiNnzIndex nnz = tsr->nnz;
ptiIndex i = tsr->inds[0].data[0];
ptiNnzIndex k = 0; // count blocks
ptiNnzIndex knnz = 0; // #Nonzeros per block
mptr->data[0] = 0;
while(1) {
/* check if mode-0 index in block-b */
if(i >= sk * k && i < sk * (k+1)) {
++ knnz;
break;
} else {
++ k;
mptr->data[k] = knnz + mptr->data[k-1];
knnz = 0;
}
}
for(ptiNnzIndex z=1; z<nnz; ++z) {
i = tsr->inds[0].data[z];
/* Compare with the next block row index */
while(1) {
if(i >= sk * k && i < sk * (k+1)) {
++ knnz;
break;
} else {
++ k;
mptr->data[k] = knnz + mptr->data[k-1];
knnz = 0;
}
}
}
ptiAssert(k < (tsr->ndims[0] + sk -1 ) / sk);
ptiAssert(mptr->data[mptr->len-1] + knnz == nnz);
return 0;
}
/**
* Record mode pointers for kernel rows, from a sorted tensor.
* @param kptr a vector of kernel pointers
* @param tsr a pointer to a sparse tensor
* @return mode pointers
*/
int ptiSetKernelPointers(
ptiNnzIndexVector *kptr,
ptiNnzIndexVector *knnzs,
ptiSparseTensor *tsr,
const ptiElementIndex sk_bits)
{
ptiIndex nmodes = tsr->nmodes;
ptiNnzIndex nnz = tsr->nnz;
ptiNnzIndex k = 0; // count kernels
ptiNnzIndex knnz = 0; // #Nonzeros per kernel
int result = 0;
result = ptiAppendNnzIndexVector(kptr, 0);
pti_CheckError(result, "HiSpTns Convert", NULL);
ptiIndex * coord = (ptiIndex *)malloc(nmodes * sizeof(*coord));
ptiIndex * kernel_coord = (ptiIndex *)malloc(nmodes * sizeof(*kernel_coord));
ptiIndex * kernel_coord_prior = (ptiIndex *)malloc(nmodes * sizeof(*kernel_coord_prior));
/* Process first nnz to get the first kernel_coord_prior */
for(ptiIndex m=0; m<nmodes; ++m)
coord[m] = tsr->inds[m].data[0]; // first nonzero indices
result = ptiLocateBeginCoord(kernel_coord_prior, tsr, coord, sk_bits);
pti_CheckError(result, "HiSpTns Convert", NULL);
for(ptiNnzIndex z=0; z<nnz; ++z) {
for(ptiIndex m=0; m<nmodes; ++m)
coord[m] = tsr->inds[m].data[z];
result = ptiLocateBeginCoord(kernel_coord, tsr, coord, sk_bits);
pti_CheckError(result, "HiSpTns Convert", NULL);
if(ptiEqualWithTwoCoordinates(kernel_coord, kernel_coord_prior, nmodes) == 1) {
++ knnz;
} else {
++ k;
result = ptiAppendNnzIndexVector(kptr, knnz + kptr->data[k-1]);
pti_CheckError(result, "HiSpTns Convert", NULL);
result = ptiAppendNnzIndexVector(knnzs, knnz);
pti_CheckError(result, "HiSpTns Convert", NULL);
for(ptiIndex m=0; m<nmodes; ++m)
kernel_coord_prior[m] = kernel_coord[m];
knnz = 1;
}
}
ptiAssert(k < kptr->len);
ptiAssert(kptr->data[kptr->len-1] + knnz == nnz);
/* Set the last element for kptr */
ptiAppendNnzIndexVector(kptr, nnz);
ptiAppendNnzIndexVector(knnzs, knnz);
free(coord);
free(kernel_coord);
free(kernel_coord_prior);
return 0;
}
/**
* Set scheduler for kernels.
* @param kschr nmodes kernel schedulers.
* @param tsr a pointer to a sparse tensor
* @return mode pointers
*/
static int ptiSetKernelScheduler(
ptiIndexVector **kschr,
ptiIndex *nkiters,
ptiNnzIndexVector * const kptr,
ptiSparseTensor *tsr,
const ptiElementIndex sk_bits)
{
ptiIndex nmodes = tsr->nmodes;
ptiIndex * ndims = tsr->ndims;
int result = 0;
ptiIndex * coord = (ptiIndex *)malloc(nmodes * sizeof(*coord));
ptiIndex * kernel_coord = (ptiIndex *)malloc(nmodes * sizeof(*kernel_coord));
for(ptiNnzIndex k=0; k<kptr->len - 1; ++k) {
ptiNnzIndex z = kptr->data[k];
for(ptiIndex m=0; m<nmodes; ++m)
coord[m] = tsr->inds[m].data[z];
result = ptiLocateBeginCoord(kernel_coord, tsr, coord, sk_bits);
pti_CheckError(result, "HiSpTns Convert", NULL);
for(ptiIndex m=0; m<nmodes; ++m) {
result = ptiAppendIndexVector(&(kschr[m][kernel_coord[m]]), k);
pti_CheckError(result, "HiSpTns Convert", NULL);
}
}
free(coord);
free(kernel_coord);
ptiIndex sk = (ptiIndex)pow(2, sk_bits);
ptiIndex tmp;
for(ptiIndex m=0; m<nmodes; ++m) {
tmp = 0;
ptiIndex kernel_ndim = (ndims[m] + sk - 1) / sk;
for(ptiIndex i=0; i<kernel_ndim; ++i) {
if(tmp < kschr[m][i].len)
tmp = kschr[m][i].len;
}
nkiters[m] = tmp;
}
return 0;
}
/**
* Pre-process COO sparse tensor by permuting, sorting, and record pointers to blocked rows. Kernels in Row-major order, blocks and elements are in Z-Morton order.
* @param tsr a pointer to a sparse tensor
* @return mode pointers
*/
int ptiPreprocessSparseTensor(
ptiNnzIndexVector * kptr,
ptiIndexVector **kschr,
ptiIndex *nkiters,
ptiIndexVector **kschr_balanced,
ptiIndexVector **kschr_balanced_pos,
ptiIndex *nkpars,
ptiIndexVector * kschr_rest,
ptiNnzIndexVector * knnzs,
ptiSparseTensor *tsr,
const ptiElementIndex sb_bits,
const ptiElementIndex sk_bits,
int const tk)
{
ptiNnzIndex nnz = tsr->nnz;
int result;
// TODO: possible permute modes to improve parallelism
/* Sort tsr in a Row-major Block order to get all kernels. Not use Morton-order for kernels: 1. better support for higher-order tensors by limiting kernel size, because Morton key bit <= 128; */
ptiTimer rowblock_sort_timer;
ptiNewTimer(&rowblock_sort_timer, 0);
ptiStartTimer(rowblock_sort_timer);
ptiSparseTensorSortIndexRowBlock(tsr, 1, 0, nnz, sk_bits, tk); // Parallelized inside
ptiStopTimer(rowblock_sort_timer);
ptiPrintElapsedTime(rowblock_sort_timer, "\t\trowblock sorting");
ptiFreeTimer(rowblock_sort_timer);
#if PARTI_DEBUG == 3
printf("Sorted by ptiSparseTensorSortIndexRowBlock.\n");
ptiAssert(ptiDumpSparseTensor(tsr, 0, stdout) == 0);
#endif
ptiTimer set_kernel_timer;
ptiNewTimer(&set_kernel_timer, 0);
ptiStartTimer(set_kernel_timer);
result = ptiSetKernelPointers(kptr, knnzs, tsr, sk_bits);
pti_CheckError(result, "HiSpTns Preprocess", NULL);
result = ptiSetKernelScheduler(kschr, nkiters, kptr, tsr, sk_bits);
pti_CheckError(result, "HiSpTns Preprocess", NULL);
// printf("OK\n"); fflush(stdout);
/* Set balanced data structures: kschr_balanced, kschr_rest */
ptiNnzIndex avg_nnzk = tsr->nnz / (kptr->len - 1);
ptiNnzIndex max_nnzk = 0;
for(ptiIndex k=0; k<kptr->len - 1; ++k) {
ptiNnzIndex nnzk = knnzs->data[k];
if(max_nnzk < nnzk) max_nnzk = nnzk;
}
// ptiNnzIndex par_nnzk_th = 20 * avg_nnzk; // threshold for nnzk per thread
ptiNnzIndex par_nnzk_th = 5 * max_nnzk; // threshold for nnzk per thread
printf("par_nnzk_th: %lu\n", par_nnzk_th);
ptiIndex sk = (ptiIndex)pow(2, sk_bits);
// printf("OK-2\n"); fflush(stdout);
for(ptiIndex m=0; m < tsr->nmodes; ++m) { // Loop kschr for each mode
ptiIndexVector * restrict kschr_mode = kschr[m];
ptiIndexVector * restrict kschr_balanced_mode = kschr_balanced[m];
ptiIndexVector * restrict kschr_balanced_pos_mode = kschr_balanced_pos[m];
ptiIndex kernel_ndim = (tsr->ndims[m] + sk - 1)/sk;
for(ptiIndex i=0; i < kernel_ndim; ++i) {
ptiAppendIndexVector(&(kschr_balanced_pos_mode[i]), 0);
}
ptiIndex j_rest = nkiters[m];
ptiIndex npars = 0;
int tag_rest = 0;
ptiIndex count_nk = 0;
ptiIndex empty_schr_rows_th = 1.0 * kernel_ndim > 1 ? 1.0 * kernel_ndim : 1;
printf("[mode %u] empty_schr_rows_th: %u\n", m, empty_schr_rows_th);
while(tag_rest == 0 && count_nk < kptr->len - 1) { // Loop for partitions. tag_rest = 1, maybe there is no rest.
/* Check two ranges: npars and j or tmp_j !!! */
ptiIndex max_nnzk_per_col = 0, par_nnzk = 0;
ptiIndex count_empty_schr_rows = 0;
for(ptiIndex i=0; i < kernel_ndim; ++i) { // Find the max nnzk
if(count_empty_schr_rows > empty_schr_rows_th) {
tag_rest = 1;
break;
}
if(npars >= kschr_balanced_pos_mode[i].len) {
++ count_empty_schr_rows;
continue;
} else {
ptiIndex j = kschr_balanced_pos_mode[i].data[npars];
if(j >= kschr_mode[i].len) {
++ count_empty_schr_rows;
continue;
}
ptiIndex kernel_num = kschr_mode[i].data[j];
ptiNnzIndex kernel_nnz = knnzs->data[kernel_num];
if (max_nnzk_per_col < kernel_nnz) {
max_nnzk_per_col = kernel_nnz;
}
}
} // End of i
if(tag_rest == 1) { // an empty superblock met, to kschr_rest
for(ptiIndex i=0; i < kernel_ndim; ++i) {
if(npars >= kschr_balanced_pos_mode[i].len) continue;
ptiIndex j2 = kschr_balanced_pos_mode[i].data[npars];
for(; j2 < kschr_mode[i].len; ++j2) {
ptiAppendIndexVector(&kschr_rest[m], kschr_mode[i].data[j2]);
++ count_nk;
}
}
} else { // all non-empty superblocks for this column, to kschr_balanced, kschr_balanced_pos
/* set par_nnzk */
if(max_nnzk_per_col > par_nnzk_th) {
par_nnzk = max_nnzk_per_col; // split according to the superblock with the max nnzk
} else {
par_nnzk = par_nnzk_th;
}
/* Real partition */
for(ptiIndex i=0; i < kernel_ndim; ++i) {
if(npars >= kschr_balanced_pos_mode[i].len) continue;
ptiIndex tmp_j = kschr_balanced_pos_mode[i].data[npars];
if(tmp_j >= kschr_mode[i].len) continue;
ptiIndex kernel_num = kschr_mode[i].data[tmp_j];
ptiNnzIndex sum_nnzk = knnzs->data[kernel_num];
while(sum_nnzk <= par_nnzk) {
ptiAppendIndexVector(&(kschr_balanced_mode[i]), kernel_num);
++ count_nk;
++ tmp_j;
if(tmp_j < kschr_mode[i].len) {
kernel_num = kschr_mode[i].data[tmp_j]; // j + 1
sum_nnzk += knnzs->data[kernel_num];
} else {
break;
}
} // End of while
ptiAppendIndexVector(&(kschr_balanced_pos_mode[i]), tmp_j);
}
++ npars;
}
// printf("count_nk: %u\n", count_nk); fflush(stdout);
} // End of while
nkpars[m] = npars; // kschr_balanced_pos.len is npars + 1.
} // End loop of modes
ptiStopTimer(set_kernel_timer);
ptiPrintElapsedTime(set_kernel_timer, "\t\tSet Kernel Ptrs");
ptiFreeTimer(set_kernel_timer);
ptiTimer morton_sort_timer;
ptiNewTimer(&morton_sort_timer, 0);
ptiStartTimer(morton_sort_timer);
/* Sort blocks in each kernel in Morton-order */
ptiNnzIndex k_begin, k_end;
/* Loop for all kernels, 0-kptr.len for OMP code */
#pragma omp parallel for num_threads(tk)
for(ptiNnzIndex k=0; k<kptr->len - 1; ++k) {
k_begin = kptr->data[k];
k_end = kptr->data[k+1]; // exclusive
/* Sort blocks in each kernel in Morton-order */
ptiSparseTensorSortIndexMorton(tsr, 1, k_begin, k_end, sb_bits, tk);
// ptiSparseTensorSortIndexRowBlock(tsr, 1, k_begin, k_end, sb_bits, tk);
#if PARTI_DEBUG == 3
printf("Kernel %"HIPARTI_PRI_NNZ_INDEX ": Sorted by ptiSparseTensorSortIndexMorton.\n", k);
ptiAssert(ptiDumpSparseTensor(tsr, 0, stdout) == 0);
#endif
}
ptiStopTimer(morton_sort_timer);
ptiPrintElapsedTime(morton_sort_timer, "\t\tMorton sorting");
// ptiPrintElapsedTime(morton_sort_timer, "\t\t2nd Rowblock sorting");
ptiFreeTimer(morton_sort_timer);
return 0;
}
/**
* Pre-process COO sparse tensor by permuting, sorting, and record pointers to blocked rows for TTM. Kernels, blocks are both in row-major order, elements in a block is in an arbitrary order.
* @param tsr a pointer to a sparse tensor
* @return mode pointers
*/
int ptiPreprocessSparseTensor_RowBlock(
ptiNnzIndexVector * kptr,
ptiIndexVector **kschr,
ptiIndex *nkiters,
ptiIndex *nfibs,
ptiNnzIndexVector * knnzs,
ptiSparseTensor *tsr,
const ptiElementIndex sb_bits,
const ptiElementIndex sk_bits,
int const tk)
{
ptiNnzIndex nnz = tsr->nnz;
int result;
/* Sort tsr in a Row-major Block order to get all kernels. */
ptiSparseTensorSortIndexRowBlock(tsr, 1, 0, nnz, sk_bits, tk);
result = ptiSetKernelPointers(kptr, knnzs, tsr, sk_bits);
pti_CheckError(result, "HiSpTns Preprocess", NULL);
// result = ptiSetKernelScheduler(kschr, nkiters, kptr, tsr, sk_bits);
// pti_CheckError(result, "HiSpTns Preprocess", NULL);
/* Sort blocks in each kernel in Row-major block order. */
ptiNnzIndex k_begin, k_end;
/* Loop for all kernels, 0-kptr.len for OMP code */
for(ptiNnzIndex k=0; k<kptr->len - 1; ++k) {
k_begin = kptr->data[k];
k_end = kptr->data[k+1]; // exclusive
ptiSparseTensorSortIndexRowBlock(tsr, 1, k_begin, k_end, sb_bits, tk);
}
return 0;
}
int ptiSparseTensorToHiCOO(
ptiSparseTensorHiCOO *hitsr,
ptiNnzIndex *max_nnzb,
ptiSparseTensor *tsr,
const ptiElementIndex sb_bits,
const ptiElementIndex sk_bits,
const ptiElementIndex sc_bits,
int const tk)
{
ptiAssert(sk_bits >= sb_bits);
ptiAssert(sc_bits >= sb_bits);
ptiIndex i;
int result;
ptiIndex nmodes = tsr->nmodes;
ptiNnzIndex nnz = tsr->nnz;
ptiElementIndex sb = pow(2, sb_bits);
ptiIndex sc = pow(2, sc_bits);
/* Set HiCOO parameters. ndims for type conversion, size_t -> ptiIndex */
ptiIndex * ndims = malloc(nmodes * sizeof *ndims);
pti_CheckOSError(!ndims, "HiSpTns Convert");
for(i = 0; i < nmodes; ++i) {
ndims[i] = (ptiIndex)tsr->ndims[i];
}
result = ptiNewSparseTensorHiCOO(hitsr, (ptiIndex)tsr->nmodes, ndims, (ptiNnzIndex)tsr->nnz, sb_bits, sk_bits, sc_bits);
pti_CheckError(result, "HiSpTns Convert", NULL);
/* Pre-process tensor to get hitsr->kptr, values are nonzero locations. */
ptiTimer sort_timer;
ptiNewTimer(&sort_timer, 0);
ptiStartTimer(sort_timer);
ptiPreprocessSparseTensor(&hitsr->kptr, hitsr->kschr, hitsr->nkiters, hitsr->kschr_balanced, hitsr->kschr_balanced_pos, hitsr->nkpars, hitsr->kschr_rest, &hitsr->knnzs, tsr, sb_bits, sk_bits, tk);
ptiStopTimer(sort_timer);
ptiPrintElapsedTime(sort_timer, "\tHiCOO sorting (rowblock + morton)");
ptiFreeTimer(sort_timer);
#if PARTI_DEBUG >= 2
printf("Kernels: Row-major, blocks: Morton-order sorted:\n");
ptiAssert(ptiDumpSparseTensor(tsr, 0, stdout) == 0);
printf("hitsr->kptr:\n");
ptiDumpNnzIndexVector(&hitsr->kptr, stdout);
#endif
ptiTimer gen_timer;
ptiNewTimer(&gen_timer, 0);
ptiStartTimer(gen_timer);
/* Temporary storage */
ptiIndex * block_begin = (ptiIndex *)malloc(nmodes * sizeof(*block_begin));
ptiIndex * block_end = (ptiIndex *)malloc(nmodes * sizeof(*block_end));
ptiIndex * block_begin_prior = (ptiIndex *)malloc(nmodes * sizeof(*block_begin_prior));
ptiIndex * block_coord = (ptiIndex *)malloc(nmodes * sizeof(*block_coord));
ptiNnzIndex k_begin, k_end; // #Nonzeros locations
ptiNnzIndex nk = 0; // #Kernels
ptiNnzIndex nc = 0; // #Chunks
ptiNnzIndex nb = 1; // #Blocks // counting from the first nnz
ptiNnzIndex nb_tmp = 0;
ptiNnzIndex ne = 0; // #Nonzeros per block
ptiIndex eindex = 0;
ptiBlockIndex chunk_size = 0;
/* different appending methods:
* elements: append every nonzero entry
* blocks: append when seeing a new block.
* chunks: appending when seeting a new chunk. Notice the boundary of kernels and the last chunk of the whole tensor may be larger than the sc.
* kernels: append when seeing a new kernel. Not appending a vector, just write data into an allocated array.
*/
/* Process first nnz */
for(ptiIndex m=0; m<nmodes; ++m)
block_coord[m] = tsr->inds[m].data[0]; // first nonzero indices
result = ptiLocateBeginCoord(block_begin_prior, tsr, block_coord, sb_bits);
pti_CheckError(result, "HiSpTns Convert", NULL);
for(ptiIndex m=0; m<nmodes; ++m)
ptiAppendBlockIndexVector(&hitsr->binds[m], (ptiBlockIndex)block_begin_prior[m]);
ptiAppendNnzIndexVector(&hitsr->bptr, 0);
/* Loop for all kernels, 0 - hitsr->kptr.len - 1 for OMP code */
for(ptiNnzIndex k=0; k<hitsr->kptr.len - 1; ++k) {
k_begin = hitsr->kptr.data[k];
k_end = hitsr->kptr.data[k+1]; // exclusive
nb_tmp = k == 0 ? 0: nb;
/* Modify kptr pointing to block locations */
hitsr->kptr.data[k] = nb_tmp;
++ nk;
/* Only append a chunk for the new kernel, the last chunk in the old kernel may be larger than sc */
ptiAppendNnzIndexVector(&hitsr->cptr, nb_tmp);
// printf("cptr 1:\n");
// ptiDumpNnzIndexVector(&hitsr->cptr, stdout);
++ nc;
chunk_size = 0;
/* Loop nonzeros in each kernel */
for(ptiNnzIndex z = k_begin; z < k_end; ++z) {
#if PARTI_DEBUG == 5
printf("z: %"HIPARTI_PRI_NNZ_INDEX "\n", z);
#endif
for(ptiIndex m=0; m<nmodes; ++m)
block_coord[m] = tsr->inds[m].data[z]; // first nonzero indices
#if PARTI_DEBUG == 5
printf("block_coord:\n");
ptiAssert(ptiDumpIndexArray(block_coord, nmodes, stdout) == 0);
#endif
result = ptiLocateBeginCoord(block_begin, tsr, block_coord, sb_bits);
// pti_CheckError(result, "HiSpTns Convert", NULL);
#if PARTI_DEBUG == 5
printf("block_begin_prior:\n");
ptiAssert(ptiDumpIndexArray(block_begin_prior, nmodes, stdout) == 0);
printf("block_begin:\n");
ptiAssert(ptiDumpIndexArray(block_begin, nmodes, stdout) == 0);
#endif
result = ptiBlockEnd(block_end, tsr, block_begin, sb); // exclusive
// pti_CheckError(result, "HiSpTns Convert", NULL);
/* Append einds and values */
for(ptiIndex m=0; m<nmodes; ++m) {
eindex = tsr->inds[m].data[z] < (block_begin[m] << sb_bits) ? tsr->inds[m].data[z] : tsr->inds[m].data[z] - (block_begin[m] << sb_bits);
ptiAssert(eindex < sb);
ptiAppendElementIndexVector(&hitsr->einds[m], (ptiElementIndex)eindex);
}
ptiAppendValueVector(&hitsr->values, tsr->values.data[z]);
/* z in the same block with last z */
if (ptiEqualWithTwoCoordinates(block_begin, block_begin_prior, nmodes) == 1)
{
/* ne: #Elements in current block */
++ ne;
} else { /* New block */
/* ne: #Elements in the last block */
/* Append block bptr and bidx */
ptiAppendNnzIndexVector(&hitsr->bptr, (ptiBlockIndex)z);
for(ptiIndex m=0; m<nmodes; ++m)
ptiAppendBlockIndexVector(&hitsr->binds[m], (ptiBlockIndex)block_begin[m]);
for(ptiIndex m=0; m<nmodes; ++m)
block_begin_prior[m] = block_begin[m];
/* ne: old block's number of nonzeros */
// if(chunk_size + ne > sc || ne >= sc) {
// if(chunk_size + ne >= sc && chunk_size > 0) { // calculate the prior block
// /* Append a chunk ending by the old block */
// ptiAppendNnzIndexVector(&hitsr->cptr, nb-1);
// // printf("cptr 2:\n");
// // ptiDumpNnzIndexVector(&hitsr->cptr, stdout);
// ++ nc;
// chunk_size = ne;
// } else {
// chunk_size += ne;
// }
if(chunk_size + ne >= sc) { // calculate the prior block
/* Append a chunk ending by the old block */
ptiAppendNnzIndexVector(&hitsr->cptr, nb);
// printf("cptr 2:\n");
// ptiDumpNnzIndexVector(&hitsr->cptr, stdout);
// printf("nb: %u, chunk_size: %u, ne: %u\n", nb, chunk_size, ne);
++ nc;
chunk_size = 0;
} else {
chunk_size += ne;
}
++ nb;
ne = 1;
} // End new block
#if PARTI_DEBUG == 5
printf("nk: %u, nc: %u, nb: %u, ne: %u, chunk_size: %lu\n\n", nk, nc, nb, ne, chunk_size);
#endif
} // End z loop
} // End k loop
ptiAssert(nb <= nnz);
ptiAssert(nb == hitsr->binds[0].len);
// ptiAssert(nc <= nb);
ptiAssert(nk == hitsr->kptr.len - 1);
/* Last element for kptr, cptr, bptr */
hitsr->kptr.data[hitsr->kptr.len - 1] = hitsr->bptr.len;
ptiAppendNnzIndexVector(&hitsr->cptr, hitsr->bptr.len);
ptiAppendNnzIndexVector(&hitsr->bptr, nnz);
*max_nnzb = hitsr->bptr.data[1] - hitsr->bptr.data[0];
ptiNnzIndex sum_nnzb = 0;
for(ptiIndex i=0; i < hitsr->bptr.len - 1; ++i) {
ptiNnzIndex nnzb = hitsr->bptr.data[i+1] - hitsr->bptr.data[i];
sum_nnzb += nnzb;
if(*max_nnzb < nnzb) {
*max_nnzb = nnzb;
}
}
ptiAssert(sum_nnzb == hitsr->nnz);
ptiStopTimer(gen_timer);
ptiPrintElapsedTime(gen_timer, "\tGenerate HiCOO");
ptiFreeTimer(gen_timer);
free(block_begin);
free(block_end);
free(block_begin_prior);
free(block_coord);
return 0;
}
|
image-view.c | /*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% IIIII M M AAA GGGG EEEEE %
% I MM MM A A G E %
% I M M M AAAAA G GG EEE %
% I M M A A G G E %
% IIIII M M A A GGGG EEEEE %
% %
% V V IIIII EEEEE W W %
% V V I E W W %
% V V I EEE W W W %
% V V I E WW WW %
% V IIIII EEEEE W W %
% %
% %
% MagickCore Image View Methods %
% %
% Software Design %
% Cristy %
% March 2003 %
% %
% %
% Copyright 1999-2020 ImageMagick Studio LLC, a non-profit organization %
% dedicated to making software imaging solutions freely available. %
% %
% You may not use this file except in compliance with the License. You may %
% obtain a copy of the License at %
% %
% https://imagemagick.org/script/license.php %
% %
% Unless required by applicable law or agreed to in writing, software %
% distributed under the License is distributed on an "AS IS" BASIS, %
% WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. %
% See the License for the specific language governing permissions and %
% limitations under the License. %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
%
%
*/
/*
Include declarations.
*/
#include "magick/studio.h"
#include "magick/MagickCore.h"
#include "magick/exception-private.h"
#include "magick/monitor-private.h"
#include "magick/thread-private.h"
/*
Typedef declarations.
*/
struct _ImageView
{
char
*description;
RectangleInfo
extent;
Image
*image;
CacheView
*view;
size_t
number_threads;
ExceptionInfo
*exception;
MagickBooleanType
debug;
size_t
signature;
};
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% C l o n e I m a g e V i e w %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% CloneImageView() makes a copy of the specified image view.
%
% The format of the CloneImageView method is:
%
% ImageView *CloneImageView(const ImageView *image_view)
%
% A description of each parameter follows:
%
% o image_view: the image view.
%
*/
MagickExport ImageView *CloneImageView(const ImageView *image_view)
{
ImageView
*clone_view;
assert(image_view != (ImageView *) NULL);
assert(image_view->signature == MagickCoreSignature);
clone_view=(ImageView *) AcquireMagickMemory(sizeof(*clone_view));
if (clone_view == (ImageView *) NULL)
ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
(void) memset(clone_view,0,sizeof(*clone_view));
clone_view->description=ConstantString(image_view->description);
clone_view->extent=image_view->extent;
clone_view->view=CloneCacheView(image_view->view);
clone_view->number_threads=image_view->number_threads;
clone_view->exception=AcquireExceptionInfo();
InheritException(clone_view->exception,image_view->exception);
clone_view->debug=image_view->debug;
clone_view->signature=MagickCoreSignature;
return(clone_view);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% D e s t r o y I m a g e V i e w %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% DestroyImageView() deallocates memory associated with a image view.
%
% The format of the DestroyImageView method is:
%
% ImageView *DestroyImageView(ImageView *image_view)
%
% A description of each parameter follows:
%
% o image_view: the image view.
%
*/
MagickExport ImageView *DestroyImageView(ImageView *image_view)
{
assert(image_view != (ImageView *) NULL);
assert(image_view->signature == MagickCoreSignature);
if (image_view->description != (char *) NULL)
image_view->description=DestroyString(image_view->description);
image_view->view=DestroyCacheView(image_view->view);
image_view->exception=DestroyExceptionInfo(image_view->exception);
image_view->signature=(~MagickCoreSignature);
image_view=(ImageView *) RelinquishMagickMemory(image_view);
return(image_view);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% D u p l e x T r a n s f e r I m a g e V i e w I t e r a t o r %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% DuplexTransferImageViewIterator() iterates over three image views in
% parallel and calls your transfer method for each scanline of the view. The
% source and duplex pixel extent is not confined to the image canvas-- that is
% you can include negative offsets or widths or heights that exceed the image
% dimension. However, the destination image view is confined to the image
% canvas-- that is no negative offsets or widths or heights that exceed the
% image dimension are permitted.
%
% The callback signature is:
%
% MagickBooleanType DuplexTransferImageViewMethod(const ImageView *source,
% const ImageView *duplex,ImageView *destination,const ssize_t y,
% const int thread_id,void *context)
%
% Use this pragma if the view is not single threaded:
%
% #pragma omp critical
%
% to define a section of code in your callback transfer method that must be
% executed by a single thread at a time.
%
% The format of the DuplexTransferImageViewIterator method is:
%
% MagickBooleanType DuplexTransferImageViewIterator(ImageView *source,
% ImageView *duplex,ImageView *destination,
% DuplexTransferImageViewMethod transfer,void *context)
%
% A description of each parameter follows:
%
% o source: the source image view.
%
% o duplex: the duplex image view.
%
% o destination: the destination image view.
%
% o transfer: the transfer callback method.
%
% o context: the user defined context.
%
*/
MagickExport MagickBooleanType DuplexTransferImageViewIterator(
ImageView *source,ImageView *duplex,ImageView *destination,
DuplexTransferImageViewMethod transfer,void *context)
{
ExceptionInfo
*exception;
Image
*destination_image,
*source_image;
MagickBooleanType
status;
MagickOffsetType
progress;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
size_t
height;
#endif
ssize_t
y;
assert(source != (ImageView *) NULL);
assert(source->signature == MagickCoreSignature);
if (transfer == (DuplexTransferImageViewMethod) NULL)
return(MagickFalse);
source_image=source->image;
destination_image=destination->image;
if (SetImageStorageClass(destination_image,DirectClass) == MagickFalse)
return(MagickFalse);
status=MagickTrue;
progress=0;
exception=destination->exception;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
height=(size_t) (source->extent.height-source->extent.y);
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(source_image,destination_image,height,1)
#endif
for (y=source->extent.y; y < (ssize_t) source->extent.height; y++)
{
const int
id = GetOpenMPThreadId();
MagickBooleanType
sync;
register const PixelPacket
*magick_restrict duplex_pixels,
*magick_restrict pixels;
register PixelPacket
*magick_restrict destination_pixels;
if (status == MagickFalse)
continue;
pixels=GetCacheViewVirtualPixels(source->view,source->extent.x,y,
source->extent.width,1,source->exception);
if (pixels == (const PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
duplex_pixels=GetCacheViewVirtualPixels(duplex->view,duplex->extent.x,y,
duplex->extent.width,1,duplex->exception);
if (duplex_pixels == (const PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
destination_pixels=GetCacheViewAuthenticPixels(destination->view,
destination->extent.x,y,destination->extent.width,1,exception);
if (destination_pixels == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
if (transfer(source,duplex,destination,y,id,context) == MagickFalse)
status=MagickFalse;
sync=SyncCacheViewAuthenticPixels(destination->view,exception);
if (sync == MagickFalse)
{
InheritException(destination->exception,GetCacheViewException(
source->view));
status=MagickFalse;
}
if (source_image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(source_image,source->description,progress,
source->extent.height);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e V i e w A u t h e n t i c I n d e x e s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageViewAuthenticIndexes() returns the image view authentic indexes.
%
% The format of the GetImageViewAuthenticPixels method is:
%
% IndexPacket *GetImageViewAuthenticIndexes(const ImageView *image_view)
%
% A description of each parameter follows:
%
% o image_view: the image view.
%
*/
MagickExport IndexPacket *GetImageViewAuthenticIndexes(
const ImageView *image_view)
{
assert(image_view != (ImageView *) NULL);
assert(image_view->signature == MagickCoreSignature);
return(GetCacheViewAuthenticIndexQueue(image_view->view));
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e V i e w A u t h e n t i c P i x e l s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageViewAuthenticPixels() returns the image view authentic pixels.
%
% The format of the GetImageViewAuthenticPixels method is:
%
% PixelPacket *GetImageViewAuthenticPixels(const ImageView *image_view)
%
% A description of each parameter follows:
%
% o image_view: the image view.
%
*/
MagickExport PixelPacket *GetImageViewAuthenticPixels(
const ImageView *image_view)
{
assert(image_view != (ImageView *) NULL);
assert(image_view->signature == MagickCoreSignature);
return(GetCacheViewAuthenticPixelQueue(image_view->view));
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e V i e w E x c e p t i o n %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageViewException() returns the severity, reason, and description of any
% error that occurs when utilizing a image view.
%
% The format of the GetImageViewException method is:
%
% char *GetImageViewException(const PixelImage *image_view,
% ExceptionType *severity)
%
% A description of each parameter follows:
%
% o image_view: the pixel image_view.
%
% o severity: the severity of the error is returned here.
%
*/
MagickExport char *GetImageViewException(const ImageView *image_view,
ExceptionType *severity)
{
char
*description;
assert(image_view != (const ImageView *) NULL);
assert(image_view->signature == MagickCoreSignature);
assert(severity != (ExceptionType *) NULL);
*severity=image_view->exception->severity;
description=(char *) AcquireQuantumMemory(2UL*MaxTextExtent,
sizeof(*description));
if (description == (char *) NULL)
ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
*description='\0';
if (image_view->exception->reason != (char *) NULL)
(void) CopyMagickString(description,GetLocaleExceptionMessage(
image_view->exception->severity,image_view->exception->reason),
MaxTextExtent);
if (image_view->exception->description != (char *) NULL)
{
(void) ConcatenateMagickString(description," (",MaxTextExtent);
(void) ConcatenateMagickString(description,GetLocaleExceptionMessage(
image_view->exception->severity,image_view->exception->description),
MaxTextExtent);
(void) ConcatenateMagickString(description,")",MaxTextExtent);
}
return(description);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e V i e w E x t e n t %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageViewExtent() returns the image view extent.
%
% The format of the GetImageViewExtent method is:
%
% RectangleInfo GetImageViewExtent(const ImageView *image_view)
%
% A description of each parameter follows:
%
% o image_view: the image view.
%
*/
MagickExport RectangleInfo GetImageViewExtent(const ImageView *image_view)
{
assert(image_view != (ImageView *) NULL);
assert(image_view->signature == MagickCoreSignature);
return(image_view->extent);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e V i e w I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageViewImage() returns the image associated with the image view.
%
% The format of the GetImageViewImage method is:
%
% MagickCore *GetImageViewImage(const ImageView *image_view)
%
% A description of each parameter follows:
%
% o image_view: the image view.
%
*/
MagickExport Image *GetImageViewImage(const ImageView *image_view)
{
assert(image_view != (ImageView *) NULL);
assert(image_view->signature == MagickCoreSignature);
return(image_view->image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e V i e w I t e r a t o r %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageViewIterator() iterates over the image view in parallel and calls
% your get method for each scanline of the view. The pixel extent is
% not confined to the image canvas-- that is you can include negative offsets
% or widths or heights that exceed the image dimension. Any updates to
% the pixels in your callback are ignored.
%
% The callback signature is:
%
% MagickBooleanType GetImageViewMethod(const ImageView *source,
% const ssize_t y,const int thread_id,void *context)
%
% Use this pragma if the view is not single threaded:
%
% #pragma omp critical
%
% to define a section of code in your callback get method that must be
% executed by a single thread at a time.
%
% The format of the GetImageViewIterator method is:
%
% MagickBooleanType GetImageViewIterator(ImageView *source,
% GetImageViewMethod get,void *context)
%
% A description of each parameter follows:
%
% o source: the source image view.
%
% o get: the get callback method.
%
% o context: the user defined context.
%
*/
MagickExport MagickBooleanType GetImageViewIterator(ImageView *source,
GetImageViewMethod get,void *context)
{
Image
*source_image;
MagickBooleanType
status;
MagickOffsetType
progress;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
size_t
height;
#endif
ssize_t
y;
assert(source != (ImageView *) NULL);
assert(source->signature == MagickCoreSignature);
if (get == (GetImageViewMethod) NULL)
return(MagickFalse);
source_image=source->image;
status=MagickTrue;
progress=0;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
height=(size_t) (source->extent.height-source->extent.y);
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(source_image,source_image,height,1)
#endif
for (y=source->extent.y; y < (ssize_t) source->extent.height; y++)
{
const int
id = GetOpenMPThreadId();
register const PixelPacket
*pixels;
if (status == MagickFalse)
continue;
pixels=GetCacheViewVirtualPixels(source->view,source->extent.x,y,
source->extent.width,1,source->exception);
if (pixels == (const PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
if (get(source,y,id,context) == MagickFalse)
status=MagickFalse;
if (source_image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(source_image,source->description,progress,
source->extent.height);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e V i e w V i r t u a l I n d e x e s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageViewVirtualIndexes() returns the image view virtual indexes.
%
% The format of the GetImageViewVirtualIndexes method is:
%
% const IndexPacket *GetImageViewVirtualIndexes(
% const ImageView *image_view)
%
% A description of each parameter follows:
%
% o image_view: the image view.
%
*/
MagickExport const IndexPacket *GetImageViewVirtualIndexes(
const ImageView *image_view)
{
assert(image_view != (ImageView *) NULL);
assert(image_view->signature == MagickCoreSignature);
return(GetCacheViewVirtualIndexQueue(image_view->view));
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e V i e w V i r t u a l P i x e l s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageViewVirtualPixels() returns the image view virtual pixels.
%
% The format of the GetImageViewVirtualPixels method is:
%
% const PixelPacket *GetImageViewVirtualPixels(const ImageView *image_view)
%
% A description of each parameter follows:
%
% o image_view: the image view.
%
*/
MagickExport const PixelPacket *GetImageViewVirtualPixels(
const ImageView *image_view)
{
assert(image_view != (ImageView *) NULL);
assert(image_view->signature == MagickCoreSignature);
return(GetCacheViewVirtualPixelQueue(image_view->view));
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% I s I m a g e V i e w %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% IsImageView() returns MagickTrue if the parameter is verified as a image
% view object.
%
% The format of the IsImageView method is:
%
% MagickBooleanType IsImageView(const ImageView *image_view)
%
% A description of each parameter follows:
%
% o image_view: the image view.
%
*/
MagickExport MagickBooleanType IsImageView(const ImageView *image_view)
{
if (image_view == (const ImageView *) NULL)
return(MagickFalse);
if (image_view->signature != MagickCoreSignature)
return(MagickFalse);
return(MagickTrue);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% N e w I m a g e V i e w %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% NewImageView() returns a image view required for all other methods in the
% Image View API.
%
% The format of the NewImageView method is:
%
% ImageView *NewImageView(MagickCore *wand)
%
% A description of each parameter follows:
%
% o wand: the wand.
%
*/
MagickExport ImageView *NewImageView(Image *image)
{
ImageView
*image_view;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
image_view=(ImageView *) AcquireMagickMemory(sizeof(*image_view));
if (image_view == (ImageView *) NULL)
ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
(void) memset(image_view,0,sizeof(*image_view));
image_view->description=ConstantString("ImageView");
image_view->image=image;
image_view->exception=AcquireExceptionInfo();
image_view->view=AcquireVirtualCacheView(image_view->image,
image_view->exception);
image_view->extent.width=image->columns;
image_view->extent.height=image->rows;
image_view->extent.x=0;
image_view->extent.y=0;
image_view->number_threads=(size_t) GetMagickResourceLimit(ThreadResource);
image_view->debug=IsEventLogging();
image_view->signature=MagickCoreSignature;
return(image_view);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% N e w I m a g e V i e w R e g i o n %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% NewImageViewRegion() returns a image view required for all other methods
% in the Image View API.
%
% The format of the NewImageViewRegion method is:
%
% ImageView *NewImageViewRegion(MagickCore *wand,const ssize_t x,
% const ssize_t y,const size_t width,const size_t height)
%
% A description of each parameter follows:
%
% o wand: the magick wand.
%
% o x,y,columns,rows: These values define the perimeter of a extent of
% pixel_wands view.
%
*/
MagickExport ImageView *NewImageViewRegion(Image *image,const ssize_t x,
const ssize_t y,const size_t width,const size_t height)
{
ImageView
*image_view;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
image_view=(ImageView *) AcquireMagickMemory(sizeof(*image_view));
if (image_view == (ImageView *) NULL)
ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
(void) memset(image_view,0,sizeof(*image_view));
image_view->description=ConstantString("ImageView");
image_view->exception=AcquireExceptionInfo();
image_view->view=AcquireVirtualCacheView(image_view->image,
image_view->exception);
image_view->image=image;
image_view->extent.width=width;
image_view->extent.height=height;
image_view->extent.x=x;
image_view->extent.y=y;
image_view->number_threads=(size_t) GetMagickResourceLimit(ThreadResource);
image_view->debug=IsEventLogging();
image_view->signature=MagickCoreSignature;
return(image_view);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S e t I m a g e V i e w D e s c r i p t i o n %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SetImageViewDescription() associates a description with an image view.
%
% The format of the SetImageViewDescription method is:
%
% void SetImageViewDescription(ImageView *image_view,
% const char *description)
%
% A description of each parameter follows:
%
% o image_view: the image view.
%
% o description: the image view description.
%
*/
MagickExport void SetImageViewDescription(ImageView *image_view,
const char *description)
{
assert(image_view != (ImageView *) NULL);
assert(image_view->signature == MagickCoreSignature);
image_view->description=ConstantString(description);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S e t I m a g e V i e w I t e r a t o r %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SetImageViewIterator() iterates over the image view in parallel and calls
% your set method for each scanline of the view. The pixel extent is
% confined to the image canvas-- that is no negative offsets or widths or
% heights that exceed the image dimension. The pixels are initiallly
% undefined and any settings you make in the callback method are automagically
% synced back to your image.
%
% The callback signature is:
%
% MagickBooleanType SetImageViewMethod(ImageView *destination,
% const ssize_t y,const int thread_id,void *context)
%
% Use this pragma if the view is not single threaded:
%
% #pragma omp critical
%
% to define a section of code in your callback set method that must be
% executed by a single thread at a time.
%
% The format of the SetImageViewIterator method is:
%
% MagickBooleanType SetImageViewIterator(ImageView *destination,
% SetImageViewMethod set,void *context)
%
% A description of each parameter follows:
%
% o destination: the image view.
%
% o set: the set callback method.
%
% o context: the user defined context.
%
*/
MagickExport MagickBooleanType SetImageViewIterator(ImageView *destination,
SetImageViewMethod set,void *context)
{
ExceptionInfo
*exception;
Image
*destination_image;
MagickBooleanType
status;
MagickOffsetType
progress;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
size_t
height;
#endif
ssize_t
y;
assert(destination != (ImageView *) NULL);
assert(destination->signature == MagickCoreSignature);
if (set == (SetImageViewMethod) NULL)
return(MagickFalse);
destination_image=destination->image;
if (SetImageStorageClass(destination_image,DirectClass) == MagickFalse)
return(MagickFalse);
status=MagickTrue;
progress=0;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
height=(size_t) (destination->extent.height-destination->extent.y);
#endif
exception=destination->exception;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(destination_image,destination_image,height,1)
#endif
for (y=destination->extent.y; y < (ssize_t) destination->extent.height; y++)
{
const int
id = GetOpenMPThreadId();
MagickBooleanType
sync;
register PixelPacket
*magick_restrict pixels;
if (status == MagickFalse)
continue;
pixels=GetCacheViewAuthenticPixels(destination->view,destination->extent.x,
y,destination->extent.width,1,exception);
if (pixels == (PixelPacket *) NULL)
{
InheritException(destination->exception,GetCacheViewException(
destination->view));
status=MagickFalse;
continue;
}
if (set(destination,y,id,context) == MagickFalse)
status=MagickFalse;
sync=SyncCacheViewAuthenticPixels(destination->view,exception);
if (sync == MagickFalse)
{
InheritException(destination->exception,GetCacheViewException(
destination->view));
status=MagickFalse;
}
if (destination_image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(destination_image,destination->description,
progress,destination->extent.height);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S e t I m a g e V i e w T h r e a d s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SetImageViewThreads() sets the number of threads in a thread team.
%
% The format of the SetImageViewDescription method is:
%
% void SetImageViewThreads(ImageView *image_view,
% const size_t number_threads)
%
% A description of each parameter follows:
%
% o image_view: the image view.
%
% o number_threads: the number of threads in a thread team.
%
*/
MagickExport void SetImageViewThreads(ImageView *image_view,
const size_t number_threads)
{
assert(image_view != (ImageView *) NULL);
assert(image_view->signature == MagickCoreSignature);
image_view->number_threads=number_threads;
if (number_threads > (size_t) GetMagickResourceLimit(ThreadResource))
image_view->number_threads=(size_t) GetMagickResourceLimit(ThreadResource);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% T r a n s f e r I m a g e V i e w I t e r a t o r %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% TransferImageViewIterator() iterates over two image views in parallel and
% calls your transfer method for each scanline of the view. The source pixel
% extent is not confined to the image canvas-- that is you can include
% negative offsets or widths or heights that exceed the image dimension.
% However, the destination image view is confined to the image canvas-- that
% is no negative offsets or widths or heights that exceed the image dimension
% are permitted.
%
% The callback signature is:
%
% MagickBooleanType TransferImageViewMethod(const ImageView *source,
% ImageView *destination,const ssize_t y,const int thread_id,
% void *context)
%
% Use this pragma if the view is not single threaded:
%
% #pragma omp critical
%
% to define a section of code in your callback transfer method that must be
% executed by a single thread at a time.
%
% The format of the TransferImageViewIterator method is:
%
% MagickBooleanType TransferImageViewIterator(ImageView *source,
% ImageView *destination,TransferImageViewMethod transfer,void *context)
%
% A description of each parameter follows:
%
% o source: the source image view.
%
% o destination: the destination image view.
%
% o transfer: the transfer callback method.
%
% o context: the user defined context.
%
*/
MagickExport MagickBooleanType TransferImageViewIterator(ImageView *source,
ImageView *destination,TransferImageViewMethod transfer,void *context)
{
ExceptionInfo
*exception;
Image
*destination_image,
*source_image;
MagickBooleanType
status;
MagickOffsetType
progress;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
size_t
height;
#endif
ssize_t
y;
assert(source != (ImageView *) NULL);
assert(source->signature == MagickCoreSignature);
if (transfer == (TransferImageViewMethod) NULL)
return(MagickFalse);
source_image=source->image;
destination_image=destination->image;
if (SetImageStorageClass(destination_image,DirectClass) == MagickFalse)
return(MagickFalse);
status=MagickTrue;
progress=0;
exception=destination->exception;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
height=(size_t) (source->extent.height-source->extent.y);
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(source_image,destination_image,height,1)
#endif
for (y=source->extent.y; y < (ssize_t) source->extent.height; y++)
{
const int
id = GetOpenMPThreadId();
MagickBooleanType
sync;
register const PixelPacket
*magick_restrict pixels;
register PixelPacket
*magick_restrict destination_pixels;
if (status == MagickFalse)
continue;
pixels=GetCacheViewVirtualPixels(source->view,source->extent.x,y,
source->extent.width,1,source->exception);
if (pixels == (const PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
destination_pixels=GetCacheViewAuthenticPixels(destination->view,
destination->extent.x,y,destination->extent.width,1,exception);
if (destination_pixels == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
if (transfer(source,destination,y,id,context) == MagickFalse)
status=MagickFalse;
sync=SyncCacheViewAuthenticPixels(destination->view,exception);
if (sync == MagickFalse)
{
InheritException(destination->exception,GetCacheViewException(
source->view));
status=MagickFalse;
}
if (source_image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(source_image,source->description,progress,
source->extent.height);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% U p d a t e I m a g e V i e w I t e r a t o r %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% UpdateImageViewIterator() iterates over the image view in parallel and calls
% your update method for each scanline of the view. The pixel extent is
% confined to the image canvas-- that is no negative offsets or widths or
% heights that exceed the image dimension are permitted. Updates to pixels
% in your callback are automagically synced back to the image.
%
% The callback signature is:
%
% MagickBooleanType UpdateImageViewMethod(ImageView *source,
% const ssize_t y,const int thread_id,void *context)
%
% Use this pragma if the view is not single threaded:
%
% #pragma omp critical
%
% to define a section of code in your callback update method that must be
% executed by a single thread at a time.
%
% The format of the UpdateImageViewIterator method is:
%
% MagickBooleanType UpdateImageViewIterator(ImageView *source,
% UpdateImageViewMethod update,void *context)
%
% A description of each parameter follows:
%
% o source: the source image view.
%
% o update: the update callback method.
%
% o context: the user defined context.
%
*/
MagickExport MagickBooleanType UpdateImageViewIterator(ImageView *source,
UpdateImageViewMethod update,void *context)
{
ExceptionInfo
*exception;
Image
*source_image;
MagickBooleanType
status;
MagickOffsetType
progress;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
size_t
height;
#endif
ssize_t
y;
assert(source != (ImageView *) NULL);
assert(source->signature == MagickCoreSignature);
if (update == (UpdateImageViewMethod) NULL)
return(MagickFalse);
source_image=source->image;
if (SetImageStorageClass(source_image,DirectClass) == MagickFalse)
return(MagickFalse);
status=MagickTrue;
progress=0;
exception=source->exception;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
height=(size_t) (source->extent.height-source->extent.y);
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(source_image,source_image,height,1)
#endif
for (y=source->extent.y; y < (ssize_t) source->extent.height; y++)
{
const int
id = GetOpenMPThreadId();
register PixelPacket
*magick_restrict pixels;
if (status == MagickFalse)
continue;
pixels=GetCacheViewAuthenticPixels(source->view,source->extent.x,y,
source->extent.width,1,exception);
if (pixels == (PixelPacket *) NULL)
{
InheritException(source->exception,GetCacheViewException(source->view));
status=MagickFalse;
continue;
}
if (update(source,y,id,context) == MagickFalse)
status=MagickFalse;
if (SyncCacheViewAuthenticPixels(source->view,exception) == MagickFalse)
{
InheritException(source->exception,GetCacheViewException(source->view));
status=MagickFalse;
}
if (source_image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(source_image,source->description,progress,
source->extent.height);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
return(status);
}
|
openmp.c | /* This file is part of CMake-easytest.
*
* Copyright (c) 2017 RWTH Aachen University, Federal Republic of Germany
*
* See the LICENSE file in the package base directory for details
*
* Written by Alexander Haase, alexander.haase@rwth-aachen.de
*/
#include <stdio.h>
#include <omp.h>
int main()
{
#pragma omp parallel
{
printf("%d of %d\n", omp_get_thread_num() + 1, omp_get_num_threads());
}
return 0;
}
/* CMake-easytest configuration.
*
* CONFIGS: sort env
*
* COMPILE_FLAGS: @OpenMP_C_FLAGS@
* LINK: @OpenMP_C_FLAGS@
*
*
* ENVIRONMENT-sort: OMP_NUM_THREADS=4
* RUN-sort: @BINARY@ | @sort@
* PASS-sort: 1.*2.*3.*4
*
* ENVIRONMENT-env: OMP_NUM_THREADS=1
* FAIL-env: 2
*/
|
main.c | #include <stdio.h>
#include<omp.h>
#include <stdlib.h>
int main()
{
// Define the domain
double x_len = 2.0; // Define x length of domain
int x_points = 101; // Define number of grid points
double del_x = x_len/(x_points-1); // Length of an element
// Define the parameters
int num_itr = 1500; // Number of time iterations
double sigma = 0.2;
double nu = 0.3;
double del_t = (sigma/nu)*(del_x*del_x); // CFL criteria
double x[x_points];
double u[x_points];
double u_new[x_points];
#pragma omp parallel for
for (int i = 0; i < x_points; i++){
x[i] = i * del_x; // Co-ordinates of the grid points
if (x[i] > 0.5 && x[i] < 1.0){ // Applying I.C.s for velocity values
u[i] = 2.0;
u_new[i] = 2.0;
}
else{
u[i] = 1.0;
u_new[i] = 1.0;
}
}
printf("\n x co-ordinates at the grid points are: \n \t");
for (int i = 0; i < x_points; i++){
printf("%f \t", x[i]);
}
printf("\n Initial u velocity at the grid points are: \n \t");
for (int i = 0; i < x_points; i++){
printf("%f \t", u[i]);
}
// Start iteration
double parr_start_time = omp_get_wtime();
#pragma omp parallel
for (int it = 0; it < num_itr; it++){
double temp_next;
double temp_prev;
#pragma omp for nowait private(temp_next, temp_prev)
for (int i = 1; i < x_points-1; i++){
temp_next = u[i+1];
temp_prev = u[i-1];
u_new[i] = u[i] + (nu * del_t/(del_x * del_x))*(temp_next + temp_prev - 2*u[i]);
// u_new[i] = u[i] + (nu * del_t/(del_x * del_x))*(u[i+1] + u[i-1] - 2*u[i]);
}
#pragma omp for
for (int i = 0; i < x_points; i++){
u[i] = u_new[i];
}
}
double parr_end_time = omp_get_wtime();
// Printing output
printf("\n Final u velocity at the grid points are: \n \t");
for (int i = 0; i < x_points; i++){
printf("%f \t", u[i]);
}
printf("\n Parallel computing time taken: %f \n \t", parr_end_time - parr_start_time);
// Serial Execution - For comparison
for (int i = 0; i < x_points; i++){
x[i] = i * del_x; // Co-ordinates of the grid points
if (x[i] > 0.5 && x[i] < 1.0){ // Applying I.C.s for velocity values
u[i] = 2.0;
u_new[i] = 2.0;
}
else{
u[i] = 1.0;
u_new[i] = 1.0;
}
}
// Start iteration
double ser_start_time = omp_get_wtime();
for (int it = 0; it < num_itr; it++){
for (int i = 1; i < x_points-1; i++){
u_new[i] = u[i] + (nu * del_t/(del_x * del_x))*(u[i+1] + u[i-1] - 2*u[i]);
}
for (int i = 0; i < x_points; i++){
u[i] = u_new[i];
}
}
double ser_end_time = omp_get_wtime();
printf("\n Serial computing time taken: %f \n", ser_end_time - ser_start_time);
printf("\n The speed-up is : %f \n", (ser_end_time - ser_start_time)/(parr_end_time - parr_start_time));
return 0;
}
|
for-4.c | void bar (short *);
void
foo (short *q, short *r, short *s, long t)
{
short *p;
#pragma omp for
for (p = q; p != r; p = p + 5) /* { dg-error "increment is not constant 1 or -1" } */
bar (p);
#pragma omp for
for (p = s; p != r; p = p - 2) /* { dg-error "increment is not constant 1 or -1" } */
bar (p);
#pragma omp for
for (p = q; p != r; p = t + p) /* { dg-error "increment is not constant 1 or -1" } */
bar (p);
#pragma omp for
for (p = s; p != r; p = -t + p) /* { dg-error "increment is not constant 1 or -1" } */
bar (p);
#pragma omp for
for (p = q; p != r; p += t) /* { dg-error "increment is not constant 1 or -1" } */
bar (p);
#pragma omp for
for (p = s; p != r; p -= 7) /* { dg-error "increment is not constant 1 or -1" } */
bar (p);
}
|
GB_unop__identity_int16_int64.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2020, All Rights Reserved.
// http://suitesparse.com See GraphBLAS/Doc/License.txt for license.
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_unop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB_unop_apply__identity_int16_int64
// op(A') function: GB_unop_tran__identity_int16_int64
// C type: int16_t
// A type: int64_t
// cast: int16_t cij = (int16_t) aij
// unaryop: cij = aij
#define GB_ATYPE \
int64_t
#define GB_CTYPE \
int16_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
int64_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = x ;
// casting
#define GB_CAST(z, aij) \
int16_t z = (int16_t) aij ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
int64_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
int16_t z = (int16_t) aij ; \
Cx [pC] = z ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_IDENTITY || GxB_NO_INT16 || GxB_NO_INT64)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop_apply__identity_int16_int64
(
int16_t *Cx, // Cx and Ax may be aliased
const int64_t *Ax,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
int64_t aij = Ax [p] ;
int16_t z = (int16_t) aij ;
Cx [p] = z ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop_tran__identity_int16_int64
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *GB_RESTRICT *Rowcounts,
GBI_single_iterator Iter,
const int64_t *GB_RESTRICT A_slice,
int naslice
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#define GB_PHASE_2_OF_2
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
GB_unop__acos_fp32_fp32.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_atomics.h"
#include "GB_unop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB_unop_apply__acos_fp32_fp32
// op(A') function: GB_unop_tran__acos_fp32_fp32
// C type: float
// A type: float
// cast: float cij = aij
// unaryop: cij = acosf (aij)
#define GB_ATYPE \
float
#define GB_CTYPE \
float
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
float aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = acosf (x) ;
// casting
#define GB_CAST(z, aij) \
float z = aij ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
float aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
float z = aij ; \
Cx [pC] = acosf (z) ; \
}
// true if operator is the identity op with no typecasting
#define GB_OP_IS_IDENTITY_WITH_NO_TYPECAST \
0
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_ACOS || GxB_NO_FP32)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop_apply__acos_fp32_fp32
(
float *Cx, // Cx and Ax may be aliased
const float *Ax,
const int8_t *GB_RESTRICT Ab, // A->b if A is bitmap
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
if (Ab == NULL)
{
#if ( GB_OP_IS_IDENTITY_WITH_NO_TYPECAST )
GB_memcpy (Cx, Ax, anz * sizeof (float), nthreads) ;
#else
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
float aij = Ax [p] ;
float z = aij ;
Cx [p] = acosf (z) ;
}
#endif
}
else
{
// bitmap case, no transpose; A->b already memcpy'd into C->b
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!Ab [p]) continue ;
float aij = Ax [p] ;
float z = aij ;
Cx [p] = acosf (z) ;
}
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop_tran__acos_fp32_fp32
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *GB_RESTRICT *Workspaces,
const int64_t *GB_RESTRICT A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
par_strength.c | /*BHEADER**********************************************************************
* Copyright (c) 2008, Lawrence Livermore National Security, LLC.
* Produced at the Lawrence Livermore National Laboratory.
* This file is part of HYPRE. See file COPYRIGHT for details.
*
* HYPRE is free software; you can redistribute it and/or modify it under the
* terms of the GNU Lesser General Public License (as published by the Free
* Software Foundation) version 2.1 dated February 1999.
*
* $Revision$
***********************************************************************EHEADER*/
/******************************************************************************
*
*****************************************************************************/
/* following should be in a header file */
#include "_hypre_parcsr_ls.h"
#include "hypre_hopscotch_hash.h"
/*==========================================================================*/
/*==========================================================================*/
/**
Generates strength matrix
Notes:
\begin{itemize}
\item The underlying matrix storage scheme is a hypre_ParCSR matrix.
\item The routine returns the following:
\begin{itemize}
\item S - a ParCSR matrix representing the "strength matrix". This is
used in the coarsening and interpolation routines.
\end{itemize}
\item The graph of the "strength matrix" for A is a subgraph of the
graph of A, but requires nonsymmetric storage even if A is
symmetric. This is because of the directional nature of the
"strengh of dependence" notion (see below). Since we are using
nonsymmetric storage for A right now, this is not a problem. If we
ever add the ability to store A symmetrically, then we could store
the strength graph as floats instead of doubles to save space.
\item This routine currently "compresses" the strength matrix. We
should consider the possibility of defining this matrix to have the
same "nonzero structure" as A. To do this, we could use the same
A\_i and A\_j arrays, and would need only define the S\_data array.
There are several pros and cons to discuss.
\end{itemize}
Terminology:
\begin{itemize}
\item Ruge's terminology: A point is "strongly connected to" $j$, or
"strongly depends on" $j$, if $-a_ij >= \theta max_{l != j} \{-a_il\}$.
\item Here, we retain some of this terminology, but with a more
generalized notion of "strength". We also retain the "natural"
graph notation for representing the directed graph of a matrix.
That is, the nonzero entry $a_ij$ is represented as: i --> j. In
the strength matrix, S, the entry $s_ij$ is also graphically denoted
as above, and means both of the following:
\begin{itemize}
\item $i$ "depends on" $j$ with "strength" $s_ij$
\item $j$ "influences" $i$ with "strength" $s_ij$
\end{itemize}
\end{itemize}
{\bf Input files:}
_hypre_parcsr_ls.h
@return Error code.
@param A [IN]
coefficient matrix
@param strength_threshold [IN]
threshold parameter used to define strength
@param max_row_sum [IN]
parameter used to modify definition of strength for diagonal dominant matrices
@param S_ptr [OUT]
strength matrix
@see */
/*--------------------------------------------------------------------------*/
HYPRE_Int
hypre_BoomerAMGCreateS(hypre_ParCSRMatrix *A,
HYPRE_Real strength_threshold,
HYPRE_Real max_row_sum,
HYPRE_Int num_functions,
HYPRE_Int *dof_func,
hypre_ParCSRMatrix **S_ptr)
{
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_CREATES] -= hypre_MPI_Wtime();
#endif
MPI_Comm comm = hypre_ParCSRMatrixComm(A);
hypre_ParCSRCommPkg *comm_pkg = hypre_ParCSRMatrixCommPkg(A);
hypre_ParCSRCommHandle *comm_handle;
hypre_CSRMatrix *A_diag = hypre_ParCSRMatrixDiag(A);
HYPRE_Int *A_diag_i = hypre_CSRMatrixI(A_diag);
HYPRE_Real *A_diag_data = hypre_CSRMatrixData(A_diag);
hypre_CSRMatrix *A_offd = hypre_ParCSRMatrixOffd(A);
HYPRE_Int *A_offd_i = hypre_CSRMatrixI(A_offd);
HYPRE_Real *A_offd_data = NULL;
HYPRE_Int *A_diag_j = hypre_CSRMatrixJ(A_diag);
HYPRE_Int *A_offd_j = hypre_CSRMatrixJ(A_offd);
HYPRE_BigInt *row_starts = hypre_ParCSRMatrixRowStarts(A);
HYPRE_Int num_variables = hypre_CSRMatrixNumRows(A_diag);
HYPRE_BigInt global_num_vars = hypre_ParCSRMatrixGlobalNumRows(A);
HYPRE_Int num_nonzeros_diag;
HYPRE_Int num_nonzeros_offd = 0;
HYPRE_Int num_cols_offd = 0;
hypre_ParCSRMatrix *S;
hypre_CSRMatrix *S_diag;
HYPRE_Int *S_diag_i;
HYPRE_Int *S_diag_j;
/* HYPRE_Real *S_diag_data; */
hypre_CSRMatrix *S_offd;
HYPRE_Int *S_offd_i = NULL;
HYPRE_Int *S_offd_j = NULL;
/* HYPRE_Real *S_offd_data; */
HYPRE_Real diag, row_scale, row_sum;
HYPRE_Int i, jA, jS;
HYPRE_Int ierr = 0;
HYPRE_Int *dof_func_offd;
HYPRE_Int num_sends;
HYPRE_Int *int_buf_data;
HYPRE_Int index, start, j;
HYPRE_Int *prefix_sum_workspace;
/*--------------------------------------------------------------
* Compute a ParCSR strength matrix, S.
*
* For now, the "strength" of dependence/influence is defined in
* the following way: i depends on j if
* aij > hypre_max (k != i) aik, aii < 0
* or
* aij < hypre_min (k != i) aik, aii >= 0
* Then S_ij = 1, else S_ij = 0.
*
* NOTE: the entries are negative initially, corresponding
* to "unaccounted-for" dependence.
*----------------------------------------------------------------*/
num_nonzeros_diag = A_diag_i[num_variables];
num_cols_offd = hypre_CSRMatrixNumCols(A_offd);
A_offd_i = hypre_CSRMatrixI(A_offd);
num_nonzeros_offd = A_offd_i[num_variables];
S = hypre_ParCSRMatrixCreate(comm, global_num_vars, global_num_vars,
row_starts, row_starts,
num_cols_offd, num_nonzeros_diag, num_nonzeros_offd);
/* row_starts is owned by A, col_starts = row_starts */
hypre_ParCSRMatrixSetRowStartsOwner(S,0);
S_diag = hypre_ParCSRMatrixDiag(S);
hypre_CSRMatrixI(S_diag) = hypre_CTAlloc(HYPRE_Int, num_variables+1, HYPRE_MEMORY_HOST);
hypre_CSRMatrixJ(S_diag) = hypre_CTAlloc(HYPRE_Int, num_nonzeros_diag, HYPRE_MEMORY_HOST);
S_offd = hypre_ParCSRMatrixOffd(S);
hypre_CSRMatrixI(S_offd) = hypre_CTAlloc(HYPRE_Int, num_variables+1, HYPRE_MEMORY_HOST);
S_diag_i = hypre_CSRMatrixI(S_diag);
HYPRE_Int *S_temp_diag_j = hypre_CSRMatrixJ(S_diag);
S_offd_i = hypre_CSRMatrixI(S_offd);
S_diag_j = hypre_TAlloc(HYPRE_Int, num_nonzeros_diag, HYPRE_MEMORY_HOST);
HYPRE_Int *S_temp_offd_j = NULL;
dof_func_offd = NULL;
if (num_cols_offd)
{
A_offd_data = hypre_CSRMatrixData(A_offd);
hypre_CSRMatrixJ(S_offd) = hypre_CTAlloc(HYPRE_Int, num_nonzeros_offd, HYPRE_MEMORY_HOST);
S_temp_offd_j = hypre_CSRMatrixJ(S_offd);
HYPRE_BigInt *col_map_offd_S = hypre_TAlloc(HYPRE_BigInt, num_cols_offd, HYPRE_MEMORY_HOST);
hypre_ParCSRMatrixColMapOffd(S) = col_map_offd_S;
if (num_functions > 1)
dof_func_offd = hypre_CTAlloc(HYPRE_Int, num_cols_offd, HYPRE_MEMORY_HOST);
S_offd_j = hypre_TAlloc(HYPRE_Int, num_nonzeros_offd, HYPRE_MEMORY_HOST);
HYPRE_BigInt *col_map_offd_A = hypre_ParCSRMatrixColMapOffd(A);
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_cols_offd; i++)
col_map_offd_S[i] = col_map_offd_A[i];
}
/*-------------------------------------------------------------------
* Get the dof_func data for the off-processor columns
*-------------------------------------------------------------------*/
if (!comm_pkg)
{
hypre_MatvecCommPkgCreate(A);
comm_pkg = hypre_ParCSRMatrixCommPkg(A);
}
num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg);
if (num_functions > 1)
{
int_buf_data = hypre_CTAlloc(HYPRE_Int, hypre_ParCSRCommPkgSendMapStart(comm_pkg,
num_sends), HYPRE_MEMORY_HOST);
index = 0;
for (i = 0; i < num_sends; i++)
{
start = hypre_ParCSRCommPkgSendMapStart(comm_pkg, i);
for (j=start; j < hypre_ParCSRCommPkgSendMapStart(comm_pkg, i+1); j++)
int_buf_data[index++]
= dof_func[hypre_ParCSRCommPkgSendMapElmt(comm_pkg,j)];
}
comm_handle = hypre_ParCSRCommHandleCreate( 11, comm_pkg, int_buf_data,
dof_func_offd);
hypre_ParCSRCommHandleDestroy(comm_handle);
hypre_TFree(int_buf_data, HYPRE_MEMORY_HOST);
}
/*HYPRE_Int prefix_sum_workspace[2*(hypre_NumThreads() + 1)];*/
prefix_sum_workspace = hypre_TAlloc(HYPRE_Int, 2*(hypre_NumThreads() + 1), HYPRE_MEMORY_HOST);
/* give S same nonzero structure as A */
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel private(i,diag,row_scale,row_sum,jA,jS)
#endif
{
HYPRE_Int start, stop;
hypre_GetSimpleThreadPartition(&start, &stop, num_variables);
HYPRE_Int jS_diag = 0, jS_offd = 0;
for (i = start; i < stop; i++)
{
S_diag_i[i] = jS_diag;
if (num_cols_offd)
{
S_offd_i[i] = jS_offd;
}
diag = A_diag_data[A_diag_i[i]];
/* compute scaling factor and row sum */
row_scale = 0.0;
row_sum = diag;
if (num_functions > 1)
{
if (diag < 0)
{
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
if (dof_func[i] == dof_func[A_diag_j[jA]])
{
row_scale = hypre_max(row_scale, A_diag_data[jA]);
row_sum += A_diag_data[jA];
}
}
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
if (dof_func[i] == dof_func_offd[A_offd_j[jA]])
{
row_scale = hypre_max(row_scale, A_offd_data[jA]);
row_sum += A_offd_data[jA];
}
}
}
else
{
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
if (dof_func[i] == dof_func[A_diag_j[jA]])
{
row_scale = hypre_min(row_scale, A_diag_data[jA]);
row_sum += A_diag_data[jA];
}
}
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
if (dof_func[i] == dof_func_offd[A_offd_j[jA]])
{
row_scale = hypre_min(row_scale, A_offd_data[jA]);
row_sum += A_offd_data[jA];
}
}
} /* diag >= 0 */
} /* num_functions > 1 */
else
{
if (diag < 0)
{
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
row_scale = hypre_max(row_scale, A_diag_data[jA]);
row_sum += A_diag_data[jA];
}
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
row_scale = hypre_max(row_scale, A_offd_data[jA]);
row_sum += A_offd_data[jA];
}
}
else
{
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
row_scale = hypre_min(row_scale, A_diag_data[jA]);
row_sum += A_diag_data[jA];
}
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
row_scale = hypre_min(row_scale, A_offd_data[jA]);
row_sum += A_offd_data[jA];
}
} /* diag >= 0*/
} /* num_functions <= 1 */
jS_diag += A_diag_i[i + 1] - A_diag_i[i] - 1;
jS_offd += A_offd_i[i + 1] - A_offd_i[i];
/* compute row entries of S */
S_temp_diag_j[A_diag_i[i]] = -1;
if ((fabs(row_sum) > fabs(diag)*max_row_sum) && (max_row_sum < 1.0))
{
/* make all dependencies weak */
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
S_temp_diag_j[jA] = -1;
}
jS_diag -= A_diag_i[i + 1] - (A_diag_i[i] + 1);
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
S_temp_offd_j[jA] = -1;
}
jS_offd -= A_offd_i[i + 1] - A_offd_i[i];
}
else
{
if (num_functions > 1)
{
if (diag < 0)
{
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
if (A_diag_data[jA] <= strength_threshold * row_scale
|| dof_func[i] != dof_func[A_diag_j[jA]])
{
S_temp_diag_j[jA] = -1;
--jS_diag;
}
else
{
S_temp_diag_j[jA] = A_diag_j[jA];
}
}
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
if (A_offd_data[jA] <= strength_threshold * row_scale
|| dof_func[i] != dof_func_offd[A_offd_j[jA]])
{
S_temp_offd_j[jA] = -1;
--jS_offd;
}
else
{
S_temp_offd_j[jA] = A_offd_j[jA];
}
}
}
else
{
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
if (A_diag_data[jA] >= strength_threshold * row_scale
|| dof_func[i] != dof_func[A_diag_j[jA]])
{
S_temp_diag_j[jA] = -1;
--jS_diag;
}
else
{
S_temp_diag_j[jA] = A_diag_j[jA];
}
}
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
if (A_offd_data[jA] >= strength_threshold * row_scale
|| dof_func[i] != dof_func_offd[A_offd_j[jA]])
{
S_temp_offd_j[jA] = -1;
--jS_offd;
}
else
{
S_temp_offd_j[jA] = A_offd_j[jA];
}
}
} /* diag >= 0 */
} /* num_functions > 1 */
else
{
if (diag < 0)
{
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
if (A_diag_data[jA] <= strength_threshold * row_scale)
{
S_temp_diag_j[jA] = -1;
--jS_diag;
}
else
{
S_temp_diag_j[jA] = A_diag_j[jA];
}
}
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
if (A_offd_data[jA] <= strength_threshold * row_scale)
{
S_temp_offd_j[jA] = -1;
--jS_offd;
}
else
{
S_temp_offd_j[jA] = A_offd_j[jA];
}
}
}
else
{
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
if (A_diag_data[jA] >= strength_threshold * row_scale)
{
S_temp_diag_j[jA] = -1;
--jS_diag;
}
else
{
S_temp_diag_j[jA] = A_diag_j[jA];
}
}
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
if (A_offd_data[jA] >= strength_threshold * row_scale)
{
S_temp_offd_j[jA] = -1;
--jS_offd;
}
else
{
S_temp_offd_j[jA] = A_offd_j[jA];
}
}
} /* diag >= 0 */
} /* num_functions <= 1 */
} /* !((row_sum > max_row_sum) && (max_row_sum < 1.0)) */
} /* for each variable */
hypre_prefix_sum_pair(&jS_diag, S_diag_i + num_variables, &jS_offd, S_offd_i + num_variables, prefix_sum_workspace);
/*--------------------------------------------------------------
* "Compress" the strength matrix.
*
* NOTE: S has *NO DIAGONAL ELEMENT* on any row. Caveat Emptor!
*
* NOTE: This "compression" section of code may be removed, and
* coarsening will still be done correctly. However, the routine
* that builds interpolation would have to be modified first.
*----------------------------------------------------------------*/
for (i = start; i < stop; i++)
{
S_diag_i[i] += jS_diag;
S_offd_i[i] += jS_offd;
jS = S_diag_i[i];
for (jA = A_diag_i[i]; jA < A_diag_i[i+1]; jA++)
{
if (S_temp_diag_j[jA] > -1)
{
S_diag_j[jS] = S_temp_diag_j[jA];
jS++;
}
}
jS = S_offd_i[i];
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
if (S_temp_offd_j[jA] > -1)
{
S_offd_j[jS] = S_temp_offd_j[jA];
jS++;
}
}
} /* for each variable */
} /* omp parallel */
hypre_CSRMatrixNumNonzeros(S_diag) = S_diag_i[num_variables];
hypre_CSRMatrixNumNonzeros(S_offd) = S_offd_i[num_variables];
hypre_CSRMatrixJ(S_diag) = S_diag_j;
hypre_CSRMatrixJ(S_offd) = S_offd_j;
hypre_ParCSRMatrixCommPkg(S) = NULL;
*S_ptr = S;
hypre_TFree(prefix_sum_workspace, HYPRE_MEMORY_HOST);
hypre_TFree(dof_func_offd, HYPRE_MEMORY_HOST);
hypre_TFree(S_temp_diag_j, HYPRE_MEMORY_HOST);
hypre_TFree(S_temp_offd_j, HYPRE_MEMORY_HOST);
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_CREATES] += hypre_MPI_Wtime();
#endif
return (ierr);
}
/*
Create Strength matrix from CF marker array data. Provides a more
general form to build S for specific nodes of the 'global' matrix
(for example, F points or A_FF part), given the entire matrix.
These nodes have the SMRK tag.
Currently assumes num_functions == 1, hence separate routine is used
for now. Could possibly be merged with BoomerAMGCreateS() to yield a
more general function.
*/
HYPRE_Int
hypre_BoomerAMGCreateSFromCFMarker(hypre_ParCSRMatrix *A,
HYPRE_Real strength_threshold,
HYPRE_Real max_row_sum,
HYPRE_Int *CF_marker,
HYPRE_Int SMRK,
hypre_ParCSRMatrix **S_ptr)
{
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_CREATES] -= hypre_MPI_Wtime();
#endif
MPI_Comm comm = hypre_ParCSRMatrixComm(A);
hypre_ParCSRCommPkg *comm_pkg = hypre_ParCSRMatrixCommPkg(A);
hypre_CSRMatrix *A_diag = hypre_ParCSRMatrixDiag(A);
HYPRE_Int *A_diag_i = hypre_CSRMatrixI(A_diag);
HYPRE_Real *A_diag_data = hypre_CSRMatrixData(A_diag);
hypre_CSRMatrix *A_offd = hypre_ParCSRMatrixOffd(A);
HYPRE_Int *A_offd_i = hypre_CSRMatrixI(A_offd);
HYPRE_Real *A_offd_data = NULL;
HYPRE_Int *A_diag_j = hypre_CSRMatrixJ(A_diag);
HYPRE_Int *A_offd_j = hypre_CSRMatrixJ(A_offd);
HYPRE_BigInt *row_starts = hypre_ParCSRMatrixRowStarts(A);
HYPRE_Int num_variables = hypre_CSRMatrixNumRows(A_diag);
HYPRE_BigInt global_num_vars = hypre_ParCSRMatrixGlobalNumRows(A);
HYPRE_Int num_nonzeros_diag;
HYPRE_Int num_nonzeros_offd = 0;
HYPRE_Int num_cols_offd = 0;
hypre_ParCSRMatrix *S;
hypre_CSRMatrix *S_diag;
HYPRE_Int *S_diag_i;
HYPRE_Int *S_diag_j;
/* HYPRE_Real *S_diag_data; */
hypre_CSRMatrix *S_offd;
HYPRE_Int *S_offd_i = NULL;
HYPRE_Int *S_offd_j = NULL;
/* HYPRE_Real *S_offd_data; */
HYPRE_Real diag, row_scale, row_sum;
HYPRE_Int i, jj, jA, jS;
HYPRE_Int ierr = 0;
HYPRE_Int *prefix_sum_workspace;
/*--------------------------------------------------------------
* Compute a ParCSR strength matrix, S.
*
* For now, the "strength" of dependence/influence is defined in
* the following way: i depends on j if
* aij > hypre_max (k != i) aik, aii < 0
* or
* aij < hypre_min (k != i) aik, aii >= 0
* Then S_ij = 1, else S_ij = 0.
*
* NOTE: the entries are negative initially, corresponding
* to "unaccounted-for" dependence.
*----------------------------------------------------------------*/
num_nonzeros_diag = A_diag_i[num_variables];
num_cols_offd = hypre_CSRMatrixNumCols(A_offd);
A_offd_i = hypre_CSRMatrixI(A_offd);
num_nonzeros_offd = A_offd_i[num_variables];
S = hypre_ParCSRMatrixCreate(comm, global_num_vars, global_num_vars,
row_starts, row_starts,
num_cols_offd, num_nonzeros_diag, num_nonzeros_offd);
/* row_starts is owned by A, col_starts = row_starts */
hypre_ParCSRMatrixSetRowStartsOwner(S,0);
S_diag = hypre_ParCSRMatrixDiag(S);
hypre_CSRMatrixI(S_diag) = hypre_CTAlloc(HYPRE_Int, num_variables+1, HYPRE_MEMORY_HOST);
hypre_CSRMatrixJ(S_diag) = hypre_CTAlloc(HYPRE_Int, num_nonzeros_diag, HYPRE_MEMORY_HOST);
S_offd = hypre_ParCSRMatrixOffd(S);
hypre_CSRMatrixI(S_offd) = hypre_CTAlloc(HYPRE_Int, num_variables+1, HYPRE_MEMORY_HOST);
S_diag_i = hypre_CSRMatrixI(S_diag);
HYPRE_Int *S_temp_diag_j = hypre_CSRMatrixJ(S_diag);
S_offd_i = hypre_CSRMatrixI(S_offd);
S_diag_j = hypre_CTAlloc(HYPRE_Int, num_nonzeros_diag, HYPRE_MEMORY_HOST);
/*
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_nonzeros_diag; i++)
S_diag_j[i] = 0;
*/
HYPRE_Int *S_temp_offd_j = NULL;
if (num_cols_offd)
{
A_offd_data = hypre_CSRMatrixData(A_offd);
hypre_CSRMatrixJ(S_offd) = hypre_CTAlloc(HYPRE_Int, num_nonzeros_offd, HYPRE_MEMORY_HOST);
S_temp_offd_j = hypre_CSRMatrixJ(S_offd);
HYPRE_BigInt *col_map_offd_S = hypre_TAlloc(HYPRE_BigInt, num_cols_offd, HYPRE_MEMORY_HOST);
hypre_ParCSRMatrixColMapOffd(S) = col_map_offd_S;
S_offd_j = hypre_CTAlloc(HYPRE_Int, num_nonzeros_offd, HYPRE_MEMORY_HOST);
/*
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_nonzeros_offd; i++)
S_offd_j[i] = 0;
*/
HYPRE_BigInt *col_map_offd_A = hypre_ParCSRMatrixColMapOffd(A);
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_cols_offd; i++)
col_map_offd_S[i] = col_map_offd_A[i];
}
/*-------------------------------------------------------------------
* Get the dof_func data for the off-processor columns
*-------------------------------------------------------------------*/
if (!comm_pkg)
{
hypre_MatvecCommPkgCreate(A);
comm_pkg = hypre_ParCSRMatrixCommPkg(A);
}
/*HYPRE_Int prefix_sum_workspace[2*(hypre_NumThreads() + 1)];*/
prefix_sum_workspace = hypre_TAlloc(HYPRE_Int, 2*(hypre_NumThreads() + 1), HYPRE_MEMORY_HOST);
/* give S same nonzero structure as A */
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel private(i,diag,row_scale,row_sum,jA,jS)
#endif
{
HYPRE_Int start, stop;
hypre_GetSimpleThreadPartition(&start, &stop, num_variables);
HYPRE_Int jS_diag = 0, jS_offd = 0;
for (i = start; i < stop; i++)
{
if (CF_marker[i] == SMRK) {
S_diag_i[i] = jS_diag;
if (num_cols_offd)
{
S_offd_i[i] = jS_offd;
}
diag = A_diag_data[A_diag_i[i]];
/* compute scaling factor and row sum */
row_scale = 0.0;
row_sum = diag;
if (diag < 0)
{
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
jj = A_diag_j[jA];
if (CF_marker[jj] == SMRK) {
row_scale = hypre_max(row_scale, A_diag_data[jA]);
row_sum += A_diag_data[jA];
}
}
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
jj = A_offd_j[jA];
if (CF_marker[jj] == SMRK) {
row_scale = hypre_max(row_scale, A_offd_data[jA]);
row_sum += A_offd_data[jA];
}
}
}
else
{
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
jj = A_diag_j[jA];
if (CF_marker[jj] == SMRK) {
row_scale = hypre_min(row_scale, A_diag_data[jA]);
row_sum += A_diag_data[jA];
}
}
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
jj = A_offd_j[jA];
if (CF_marker[jj] == SMRK) {
row_scale = hypre_min(row_scale, A_offd_data[jA]);
row_sum += A_offd_data[jA];
}
}
} /* diag >= 0*/
jS_diag += A_diag_i[i + 1] - A_diag_i[i] - 1;
jS_offd += A_offd_i[i + 1] - A_offd_i[i];
/* compute row entries of S */
S_temp_diag_j[A_diag_i[i]] = -1;
if ((fabs(row_sum) > fabs(diag)*max_row_sum) && (max_row_sum < 1.0))
{
/* make all dependencies weak */
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
jj = A_diag_j[jA];
S_temp_diag_j[jA] = -1;
}
jS_diag -= A_diag_i[i + 1] - (A_diag_i[i] + 1);
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
S_temp_offd_j[jA] = -1;
}
jS_offd -= A_offd_i[i + 1] - A_offd_i[i];
}
else
{
if (diag < 0)
{
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
jj = A_diag_j[jA];
if (CF_marker[jj] == SMRK) {
if (A_diag_data[jA] <= strength_threshold * row_scale)
{
S_temp_diag_j[jA] = -1;
--jS_diag;
}
else
{
S_temp_diag_j[jA] = jj;
}
} else {
S_temp_diag_j[jA] = -1;
}
}
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
jj = A_offd_j[jA];
if (CF_marker[jj] == SMRK) {
if (A_offd_data[jA] <= strength_threshold * row_scale)
{
S_temp_offd_j[jA] = -1;
--jS_offd;
}
else
{
S_temp_offd_j[jA] = jj;
}
} else {
S_temp_offd_j[jA] = -1;
}
}
} /* diag < 0 */
else
{
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
jj = A_diag_j[jA];
if (CF_marker[jj] == SMRK) {
if (A_diag_data[jA] >= strength_threshold * row_scale)
{
S_temp_diag_j[jA] = -1;
--jS_diag;
}
else
{
S_temp_diag_j[jA] = jj;
}
} else {
S_temp_diag_j[jA] = -1;
}
}
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
jj = A_offd_j[jA];
if (CF_marker[jj] == SMRK) {
if (A_offd_data[jA] >= strength_threshold * row_scale)
{
S_temp_offd_j[jA] = -1;
--jS_offd;
}
else
{
S_temp_offd_j[jA] = jj;
}
} else {
S_temp_offd_j[jA] = -1;
}
}
} /* diag >= 0 */
} /* !((row_sum > max_row_sum) && (max_row_sum < 1.0)) */
} /* CF_marker == SMRK */
else
{
S_diag_i[i] = jS_diag;
if (num_cols_offd)
{
S_offd_i[i] = jS_offd;
}
jS_diag += A_diag_i[i + 1] - A_diag_i[i] - 1;
jS_offd += A_offd_i[i + 1] - A_offd_i[i];
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
S_temp_diag_j[jA] = -1;
}
jS_diag -= A_diag_i[i + 1] - (A_diag_i[i] + 1);
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
S_temp_offd_j[jA] = -1;
}
jS_offd -= A_offd_i[i + 1] - A_offd_i[i];
} /* CF_marker != SMRK */
} /* for each variable */
hypre_prefix_sum_pair(&jS_diag, S_diag_i + num_variables, &jS_offd, S_offd_i + num_variables, prefix_sum_workspace);
/*--------------------------------------------------------------
* "Compress" the strength matrix.
*
* NOTE: S has *NO DIAGONAL ELEMENT* on any row. Caveat Emptor!
*
* NOTE: This "compression" section of code may be removed, and
* coarsening will still be done correctly. However, the routine
* that builds interpolation would have to be modified first.
*----------------------------------------------------------------*/
for (i = start; i < stop; i++)
{
S_diag_i[i] += jS_diag;
S_offd_i[i] += jS_offd;
jS = S_diag_i[i];
for (jA = A_diag_i[i]; jA < A_diag_i[i+1]; jA++)
{
if (S_temp_diag_j[jA] > -1)
{
S_diag_j[jS] = S_temp_diag_j[jA];
jS++;
}
}
jS = S_offd_i[i];
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
if (S_temp_offd_j[jA] > -1)
{
S_offd_j[jS] = S_temp_offd_j[jA];
jS++;
}
}
} /* for each variable */
} /* omp parallel */
hypre_CSRMatrixNumNonzeros(S_diag) = S_diag_i[num_variables];
hypre_CSRMatrixNumNonzeros(S_offd) = S_offd_i[num_variables];
hypre_CSRMatrixJ(S_diag) = S_diag_j;
hypre_CSRMatrixJ(S_offd) = S_offd_j;
hypre_ParCSRMatrixCommPkg(S) = NULL;
*S_ptr = S;
hypre_TFree(prefix_sum_workspace, HYPRE_MEMORY_HOST);
hypre_TFree(S_temp_diag_j, HYPRE_MEMORY_HOST);
hypre_TFree(S_temp_offd_j, HYPRE_MEMORY_HOST);
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_CREATES] += hypre_MPI_Wtime();
#endif
return (ierr);
}
/*==========================================================================*/
/*==========================================================================*/
/**
Generates strength matrix
Notes:
\begin{itemize}
\item The underlying matrix storage scheme is a hypre_ParCSR matrix.
\item The routine returns the following:
\begin{itemize}
\item S - a ParCSR matrix representing the "strength matrix". This is
used in the coarsening and interpolation routines.
\end{itemize}
\item The graph of the "strength matrix" for A is a subgraph of the
graph of A, but requires nonsymmetric storage even if A is
symmetric. This is because of the directional nature of the
"strengh of dependence" notion (see below). Since we are using
nonsymmetric storage for A right now, this is not a problem. If we
ever add the ability to store A symmetrically, then we could store
the strength graph as floats instead of doubles to save space.
\item This routine currently "compresses" the strength matrix. We
should consider the possibility of defining this matrix to have the
same "nonzero structure" as A. To do this, we could use the same
A\_i and A\_j arrays, and would need only define the S\_data array.
There are several pros and cons to discuss.
\end{itemize}
Terminology:
\begin{itemize}
\item Ruge's terminology: A point is "strongly connected to" $j$, or
"strongly depends on" $j$, if $|a_ij| >= \theta max_{l != j} |a_il|}$.
\item Here, we retain some of this terminology, but with a more
generalized notion of "strength". We also retain the "natural"
graph notation for representing the directed graph of a matrix.
That is, the nonzero entry $a_ij$ is represented as: i --> j. In
the strength matrix, S, the entry $s_ij$ is also graphically denoted
as above, and means both of the following:
\begin{itemize}
\item $i$ "depends on" $j$ with "strength" $s_ij$
\item $j$ "influences" $i$ with "strength" $s_ij$
\end{itemize}
\end{itemize}
{\bf Input files:}
_hypre_parcsr_ls.h
@return Error code.
@param A [IN]
coefficient matrix
@param strength_threshold [IN]
threshold parameter used to define strength
@param max_row_sum [IN]
parameter used to modify definition of strength for diagonal dominant matrices
@param S_ptr [OUT]
strength matrix
@see */
/*--------------------------------------------------------------------------*/
HYPRE_Int
hypre_BoomerAMGCreateSabs(hypre_ParCSRMatrix *A,
HYPRE_Real strength_threshold,
HYPRE_Real max_row_sum,
HYPRE_Int num_functions,
HYPRE_Int *dof_func,
hypre_ParCSRMatrix **S_ptr)
{
MPI_Comm comm = hypre_ParCSRMatrixComm(A);
hypre_ParCSRCommPkg *comm_pkg = hypre_ParCSRMatrixCommPkg(A);
hypre_ParCSRCommHandle *comm_handle;
hypre_CSRMatrix *A_diag = hypre_ParCSRMatrixDiag(A);
HYPRE_Int *A_diag_i = hypre_CSRMatrixI(A_diag);
HYPRE_Real *A_diag_data = hypre_CSRMatrixData(A_diag);
hypre_CSRMatrix *A_offd = hypre_ParCSRMatrixOffd(A);
HYPRE_Int *A_offd_i = hypre_CSRMatrixI(A_offd);
HYPRE_Real *A_offd_data = NULL;
HYPRE_Int *A_diag_j = hypre_CSRMatrixJ(A_diag);
HYPRE_Int *A_offd_j = hypre_CSRMatrixJ(A_offd);
HYPRE_BigInt *row_starts = hypre_ParCSRMatrixRowStarts(A);
HYPRE_Int num_variables = hypre_CSRMatrixNumRows(A_diag);
HYPRE_BigInt global_num_vars = hypre_ParCSRMatrixGlobalNumRows(A);
HYPRE_Int num_nonzeros_diag;
HYPRE_Int num_nonzeros_offd = 0;
HYPRE_Int num_cols_offd = 0;
hypre_ParCSRMatrix *S;
hypre_CSRMatrix *S_diag;
HYPRE_Int *S_diag_i;
HYPRE_Int *S_diag_j;
/* HYPRE_Real *S_diag_data; */
hypre_CSRMatrix *S_offd;
HYPRE_Int *S_offd_i = NULL;
HYPRE_Int *S_offd_j = NULL;
/* HYPRE_Real *S_offd_data; */
HYPRE_Real diag, row_scale, row_sum;
HYPRE_Int i, jA, jS;
HYPRE_Int ierr = 0;
HYPRE_Int *dof_func_offd;
HYPRE_Int num_sends;
HYPRE_Int *int_buf_data;
HYPRE_Int index, start, j;
/*--------------------------------------------------------------
* Compute a ParCSR strength matrix, S.
*
* For now, the "strength" of dependence/influence is defined in
* the following way: i depends on j if
* aij > hypre_max (k != i) aik, aii < 0
* or
* aij < hypre_min (k != i) aik, aii >= 0
* Then S_ij = 1, else S_ij = 0.
*
* NOTE: the entries are negative initially, corresponding
* to "unaccounted-for" dependence.
*----------------------------------------------------------------*/
num_nonzeros_diag = A_diag_i[num_variables];
num_cols_offd = hypre_CSRMatrixNumCols(A_offd);
A_offd_i = hypre_CSRMatrixI(A_offd);
num_nonzeros_offd = A_offd_i[num_variables];
S = hypre_ParCSRMatrixCreate(comm, global_num_vars, global_num_vars,
row_starts, row_starts,
num_cols_offd, num_nonzeros_diag, num_nonzeros_offd);
/* row_starts is owned by A, col_starts = row_starts */
hypre_ParCSRMatrixSetRowStartsOwner(S,0);
S_diag = hypre_ParCSRMatrixDiag(S);
hypre_CSRMatrixI(S_diag) = hypre_CTAlloc(HYPRE_Int, num_variables+1, HYPRE_MEMORY_HOST);
hypre_CSRMatrixJ(S_diag) = hypre_CTAlloc(HYPRE_Int, num_nonzeros_diag, HYPRE_MEMORY_HOST);
S_offd = hypre_ParCSRMatrixOffd(S);
hypre_CSRMatrixI(S_offd) = hypre_CTAlloc(HYPRE_Int, num_variables+1, HYPRE_MEMORY_HOST);
S_diag_i = hypre_CSRMatrixI(S_diag);
S_diag_j = hypre_CSRMatrixJ(S_diag);
S_offd_i = hypre_CSRMatrixI(S_offd);
dof_func_offd = NULL;
if (num_cols_offd)
{
A_offd_data = hypre_CSRMatrixData(A_offd);
hypre_CSRMatrixJ(S_offd) = hypre_CTAlloc(HYPRE_Int, num_nonzeros_offd, HYPRE_MEMORY_HOST);
S_offd_j = hypre_CSRMatrixJ(S_offd);
hypre_ParCSRMatrixColMapOffd(S) = hypre_CTAlloc(HYPRE_BigInt, num_cols_offd, HYPRE_MEMORY_HOST);
if (num_functions > 1)
dof_func_offd = hypre_CTAlloc(HYPRE_Int, num_cols_offd, HYPRE_MEMORY_HOST);
}
/*-------------------------------------------------------------------
* Get the dof_func data for the off-processor columns
*-------------------------------------------------------------------*/
if (!comm_pkg)
{
hypre_MatvecCommPkgCreate(A);
comm_pkg = hypre_ParCSRMatrixCommPkg(A);
}
num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg);
if (num_functions > 1)
{
int_buf_data = hypre_CTAlloc(HYPRE_Int, hypre_ParCSRCommPkgSendMapStart(comm_pkg,
num_sends), HYPRE_MEMORY_HOST);
index = 0;
for (i = 0; i < num_sends; i++)
{
start = hypre_ParCSRCommPkgSendMapStart(comm_pkg, i);
for (j=start; j < hypre_ParCSRCommPkgSendMapStart(comm_pkg, i+1); j++)
int_buf_data[index++]
= dof_func[hypre_ParCSRCommPkgSendMapElmt(comm_pkg,j)];
}
comm_handle = hypre_ParCSRCommHandleCreate( 11, comm_pkg, int_buf_data,
dof_func_offd);
hypre_ParCSRCommHandleDestroy(comm_handle);
hypre_TFree(int_buf_data, HYPRE_MEMORY_HOST);
}
/* give S same nonzero structure as A */
hypre_ParCSRMatrixCopy(A,S,0);
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i,diag,row_scale,row_sum,jA) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_variables; i++)
{
diag = A_diag_data[A_diag_i[i]];
/* compute scaling factor and row sum */
row_scale = 0.0;
row_sum = diag;
if (num_functions > 1)
{
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
if (dof_func[i] == dof_func[A_diag_j[jA]])
{
row_scale = hypre_max(row_scale, fabs(A_diag_data[jA]));
row_sum += fabs(A_diag_data[jA]);
}
}
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
if (dof_func[i] == dof_func_offd[A_offd_j[jA]])
{
row_scale = hypre_max(row_scale, fabs(A_offd_data[jA]));
row_sum += fabs(A_offd_data[jA]);
}
}
}
else
{
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
row_scale = hypre_max(row_scale, fabs(A_diag_data[jA]));
row_sum += fabs(A_diag_data[jA]);
}
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
row_scale = hypre_max(row_scale, fabs(A_offd_data[jA]));
row_sum += fabs(A_offd_data[jA]);
}
}
/* compute row entries of S */
S_diag_j[A_diag_i[i]] = -1;
if ((fabs(row_sum) > fabs(diag)*max_row_sum) && (max_row_sum < 1.0))
{
/* make all dependencies weak */
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
S_diag_j[jA] = -1;
}
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
S_offd_j[jA] = -1;
}
}
else
{
if (num_functions > 1)
{
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
if (fabs(A_diag_data[jA]) <= strength_threshold * row_scale
|| dof_func[i] != dof_func[A_diag_j[jA]])
{
S_diag_j[jA] = -1;
}
}
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
if (fabs(A_offd_data[jA]) <= strength_threshold * row_scale
|| dof_func[i] != dof_func_offd[A_offd_j[jA]])
{
S_offd_j[jA] = -1;
}
}
}
else
{
for (jA = A_diag_i[i]+1; jA < A_diag_i[i+1]; jA++)
{
if (fabs(A_diag_data[jA]) <= strength_threshold * row_scale)
{
S_diag_j[jA] = -1;
}
}
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
if (fabs(A_offd_data[jA]) <= strength_threshold * row_scale)
{
S_offd_j[jA] = -1;
}
}
}
}
}
/*--------------------------------------------------------------
* "Compress" the strength matrix.
*
* NOTE: S has *NO DIAGONAL ELEMENT* on any row. Caveat Emptor!
*
* NOTE: This "compression" section of code may be removed, and
* coarsening will still be done correctly. However, the routine
* that builds interpolation would have to be modified first.
*----------------------------------------------------------------*/
/* RDF: not sure if able to thread this loop */
jS = 0;
for (i = 0; i < num_variables; i++)
{
S_diag_i[i] = jS;
for (jA = A_diag_i[i]; jA < A_diag_i[i+1]; jA++)
{
if (S_diag_j[jA] > -1)
{
S_diag_j[jS] = S_diag_j[jA];
jS++;
}
}
}
S_diag_i[num_variables] = jS;
hypre_CSRMatrixNumNonzeros(S_diag) = jS;
/* RDF: not sure if able to thread this loop */
jS = 0;
for (i = 0; i < num_variables; i++)
{
S_offd_i[i] = jS;
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
if (S_offd_j[jA] > -1)
{
S_offd_j[jS] = S_offd_j[jA];
jS++;
}
}
}
S_offd_i[num_variables] = jS;
hypre_CSRMatrixNumNonzeros(S_offd) = jS;
hypre_ParCSRMatrixCommPkg(S) = NULL;
*S_ptr = S;
hypre_TFree(dof_func_offd, HYPRE_MEMORY_HOST);
return (ierr);
}
/*--------------------------------------------------------------------------*/
HYPRE_Int
hypre_BoomerAMGCreateSCommPkg(hypre_ParCSRMatrix *A,
hypre_ParCSRMatrix *S,
HYPRE_Int **col_offd_S_to_A_ptr)
{
MPI_Comm comm = hypre_ParCSRMatrixComm(A);
hypre_MPI_Status *status;
hypre_MPI_Request *requests;
hypre_ParCSRCommPkg *comm_pkg_A = hypre_ParCSRMatrixCommPkg(A);
hypre_ParCSRCommPkg *comm_pkg_S;
hypre_ParCSRCommHandle *comm_handle;
hypre_CSRMatrix *A_offd = hypre_ParCSRMatrixOffd(A);
HYPRE_BigInt *col_map_offd_A = hypre_ParCSRMatrixColMapOffd(A);
hypre_CSRMatrix *S_diag = hypre_ParCSRMatrixDiag(S);
hypre_CSRMatrix *S_offd = hypre_ParCSRMatrixOffd(S);
HYPRE_Int *S_offd_i = hypre_CSRMatrixI(S_offd);
HYPRE_Int *S_offd_j = hypre_CSRMatrixJ(S_offd);
HYPRE_BigInt *col_map_offd_S = hypre_ParCSRMatrixColMapOffd(S);
HYPRE_Int *recv_procs_A = hypre_ParCSRCommPkgRecvProcs(comm_pkg_A);
HYPRE_Int *recv_vec_starts_A =
hypre_ParCSRCommPkgRecvVecStarts(comm_pkg_A);
HYPRE_Int *send_procs_A =
hypre_ParCSRCommPkgSendProcs(comm_pkg_A);
HYPRE_Int *send_map_starts_A =
hypre_ParCSRCommPkgSendMapStarts(comm_pkg_A);
HYPRE_Int *recv_procs_S;
HYPRE_Int *recv_vec_starts_S;
HYPRE_Int *send_procs_S;
HYPRE_Int *send_map_starts_S;
HYPRE_Int *send_map_elmts_S = NULL;
HYPRE_BigInt *big_send_map_elmts_S = NULL;
HYPRE_Int *col_offd_S_to_A;
HYPRE_Int *S_marker;
HYPRE_Int *send_change;
HYPRE_Int *recv_change;
HYPRE_Int num_variables = hypre_CSRMatrixNumRows(S_diag);
HYPRE_Int num_cols_offd_A = hypre_CSRMatrixNumCols(A_offd);
HYPRE_Int num_cols_offd_S;
HYPRE_Int i, j, jcol;
HYPRE_Int proc, cnt, proc_cnt, total_nz;
HYPRE_BigInt first_row;
HYPRE_Int ierr = 0;
HYPRE_Int num_sends_A = hypre_ParCSRCommPkgNumSends(comm_pkg_A);
HYPRE_Int num_recvs_A = hypre_ParCSRCommPkgNumRecvs(comm_pkg_A);
HYPRE_Int num_sends_S;
HYPRE_Int num_recvs_S;
HYPRE_Int num_nonzeros;
num_nonzeros = S_offd_i[num_variables];
S_marker = NULL;
if (num_cols_offd_A)
S_marker = hypre_CTAlloc(HYPRE_Int, num_cols_offd_A, HYPRE_MEMORY_HOST);
for (i=0; i < num_cols_offd_A; i++)
S_marker[i] = -1;
for (i=0; i < num_nonzeros; i++)
{
jcol = S_offd_j[i];
S_marker[jcol] = 0;
}
proc = 0;
proc_cnt = 0;
cnt = 0;
num_recvs_S = 0;
for (i=0; i < num_recvs_A; i++)
{
for (j=recv_vec_starts_A[i]; j < recv_vec_starts_A[i+1]; j++)
{
if (!S_marker[j])
{
S_marker[j] = cnt;
cnt++;
proc = 1;
}
}
if (proc) {num_recvs_S++; proc = 0;}
}
num_cols_offd_S = cnt;
recv_change = NULL;
recv_procs_S = NULL;
send_change = NULL;
if (col_map_offd_S) hypre_TFree(col_map_offd_S, HYPRE_MEMORY_HOST);
col_map_offd_S = NULL;
col_offd_S_to_A = NULL;
if (num_recvs_A) recv_change = hypre_CTAlloc(HYPRE_Int, num_recvs_A, HYPRE_MEMORY_HOST);
if (num_sends_A) send_change = hypre_CTAlloc(HYPRE_Int, num_sends_A, HYPRE_MEMORY_HOST);
if (num_recvs_S) recv_procs_S = hypre_CTAlloc(HYPRE_Int, num_recvs_S, HYPRE_MEMORY_HOST);
recv_vec_starts_S = hypre_CTAlloc(HYPRE_Int, num_recvs_S+1, HYPRE_MEMORY_HOST);
if (num_cols_offd_S)
{
col_map_offd_S = hypre_CTAlloc(HYPRE_BigInt, num_cols_offd_S, HYPRE_MEMORY_HOST);
col_offd_S_to_A = hypre_CTAlloc(HYPRE_Int, num_cols_offd_S, HYPRE_MEMORY_HOST);
}
if (num_cols_offd_S < num_cols_offd_A)
{
for (i=0; i < num_nonzeros; i++)
{
jcol = S_offd_j[i];
S_offd_j[i] = S_marker[jcol];
}
proc = 0;
proc_cnt = 0;
cnt = 0;
recv_vec_starts_S[0] = 0;
for (i=0; i < num_recvs_A; i++)
{
for (j=recv_vec_starts_A[i]; j < recv_vec_starts_A[i+1]; j++)
{
if (S_marker[j] != -1)
{
col_map_offd_S[cnt] = col_map_offd_A[j];
col_offd_S_to_A[cnt++] = j;
proc = 1;
}
}
recv_change[i] = j-cnt-recv_vec_starts_A[i]
+recv_vec_starts_S[proc_cnt];
if (proc)
{
recv_procs_S[proc_cnt++] = recv_procs_A[i];
recv_vec_starts_S[proc_cnt] = cnt;
proc = 0;
}
}
}
else
{
for (i=0; i < num_recvs_A; i++)
{
for (j=recv_vec_starts_A[i]; j < recv_vec_starts_A[i+1]; j++)
{
col_map_offd_S[j] = col_map_offd_A[j];
col_offd_S_to_A[j] = j;
}
recv_procs_S[i] = recv_procs_A[i];
recv_vec_starts_S[i] = recv_vec_starts_A[i];
}
recv_vec_starts_S[num_recvs_A] = recv_vec_starts_A[num_recvs_A];
}
requests = hypre_CTAlloc(hypre_MPI_Request, num_sends_A+num_recvs_A, HYPRE_MEMORY_HOST);
j=0;
for (i=0; i < num_sends_A; i++)
hypre_MPI_Irecv(&send_change[i],1,HYPRE_MPI_INT,send_procs_A[i],
0,comm,&requests[j++]);
for (i=0; i < num_recvs_A; i++)
hypre_MPI_Isend(&recv_change[i],1,HYPRE_MPI_INT,recv_procs_A[i],
0,comm,&requests[j++]);
status = hypre_CTAlloc(hypre_MPI_Status, j, HYPRE_MEMORY_HOST);
hypre_MPI_Waitall(j,requests,status);
hypre_TFree(status, HYPRE_MEMORY_HOST);
hypre_TFree(requests, HYPRE_MEMORY_HOST);
num_sends_S = 0;
total_nz = send_map_starts_A[num_sends_A];
for (i=0; i < num_sends_A; i++)
{
if (send_change[i])
{
if ((send_map_starts_A[i+1]-send_map_starts_A[i]) > send_change[i])
num_sends_S++;
}
else
num_sends_S++;
total_nz -= send_change[i];
}
send_procs_S = NULL;
if (num_sends_S)
send_procs_S = hypre_CTAlloc(HYPRE_Int, num_sends_S, HYPRE_MEMORY_HOST);
send_map_starts_S = hypre_CTAlloc(HYPRE_Int, num_sends_S+1, HYPRE_MEMORY_HOST);
send_map_elmts_S = NULL;
if (total_nz)
{
send_map_elmts_S = hypre_CTAlloc(HYPRE_Int, total_nz, HYPRE_MEMORY_HOST);
big_send_map_elmts_S = hypre_CTAlloc(HYPRE_BigInt, total_nz, HYPRE_MEMORY_HOST);
}
proc = 0;
proc_cnt = 0;
for (i=0; i < num_sends_A; i++)
{
cnt = send_map_starts_A[i+1]-send_map_starts_A[i]-send_change[i];
if (cnt)
{
send_procs_S[proc_cnt++] = send_procs_A[i];
send_map_starts_S[proc_cnt] = send_map_starts_S[proc_cnt-1]+cnt;
}
}
comm_pkg_S = hypre_CTAlloc(hypre_ParCSRCommPkg, 1, HYPRE_MEMORY_HOST);
hypre_ParCSRCommPkgComm(comm_pkg_S) = comm;
hypre_ParCSRCommPkgNumRecvs(comm_pkg_S) = num_recvs_S;
hypre_ParCSRCommPkgRecvProcs(comm_pkg_S) = recv_procs_S;
hypre_ParCSRCommPkgRecvVecStarts(comm_pkg_S) = recv_vec_starts_S;
hypre_ParCSRCommPkgNumSends(comm_pkg_S) = num_sends_S;
hypre_ParCSRCommPkgSendProcs(comm_pkg_S) = send_procs_S;
hypre_ParCSRCommPkgSendMapStarts(comm_pkg_S) = send_map_starts_S;
comm_handle = hypre_ParCSRCommHandleCreate(22, comm_pkg_S, col_map_offd_S,
big_send_map_elmts_S);
hypre_ParCSRCommHandleDestroy(comm_handle);
first_row = hypre_ParCSRMatrixFirstRowIndex(A);
if (first_row)
for (i=0; i < send_map_starts_S[num_sends_S]; i++)
send_map_elmts_S[i] = (HYPRE_Int)(big_send_map_elmts_S[i]-first_row);
hypre_ParCSRCommPkgSendMapElmts(comm_pkg_S) = send_map_elmts_S;
hypre_ParCSRMatrixCommPkg(S) = comm_pkg_S;
hypre_ParCSRMatrixColMapOffd(S) = col_map_offd_S;
hypre_CSRMatrixNumCols(S_offd) = num_cols_offd_S;
hypre_TFree(S_marker, HYPRE_MEMORY_HOST);
hypre_TFree(send_change, HYPRE_MEMORY_HOST);
hypre_TFree(recv_change, HYPRE_MEMORY_HOST);
*col_offd_S_to_A_ptr = col_offd_S_to_A;
return ierr;
}
/*--------------------------------------------------------------------------
* hypre_BoomerAMGCreate2ndS : creates strength matrix on coarse points
* for second coarsening pass in aggressive coarsening (S*S+2S)
*--------------------------------------------------------------------------*/
HYPRE_Int hypre_BoomerAMGCreate2ndS( hypre_ParCSRMatrix *S, HYPRE_Int *CF_marker,
HYPRE_Int num_paths, HYPRE_BigInt *coarse_row_starts, hypre_ParCSRMatrix **C_ptr)
{
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_CREATE_2NDS] -= hypre_MPI_Wtime();
#endif
MPI_Comm comm = hypre_ParCSRMatrixComm(S);
hypre_ParCSRCommPkg *comm_pkg = hypre_ParCSRMatrixCommPkg(S);
hypre_ParCSRCommPkg *tmp_comm_pkg;
hypre_ParCSRCommHandle *comm_handle;
hypre_CSRMatrix *S_diag = hypre_ParCSRMatrixDiag(S);
HYPRE_Int *S_diag_i = hypre_CSRMatrixI(S_diag);
HYPRE_Int *S_diag_j = hypre_CSRMatrixJ(S_diag);
hypre_CSRMatrix *S_offd = hypre_ParCSRMatrixOffd(S);
HYPRE_Int *S_offd_i = hypre_CSRMatrixI(S_offd);
HYPRE_Int *S_offd_j = hypre_CSRMatrixJ(S_offd);
HYPRE_Int num_cols_diag_S = hypre_CSRMatrixNumCols(S_diag);
HYPRE_Int num_cols_offd_S = hypre_CSRMatrixNumCols(S_offd);
hypre_ParCSRMatrix *S2;
HYPRE_BigInt *col_map_offd_C = NULL;
hypre_CSRMatrix *C_diag;
/*HYPRE_Int *C_diag_data = NULL;*/
HYPRE_Int *C_diag_i;
HYPRE_Int *C_diag_j = NULL;
hypre_CSRMatrix *C_offd;
/*HYPRE_Int *C_offd_data=NULL;*/
HYPRE_Int *C_offd_i;
HYPRE_Int *C_offd_j=NULL;
HYPRE_Int num_cols_offd_C = 0;
HYPRE_Int *S_ext_diag_i = NULL;
HYPRE_Int *S_ext_diag_j = NULL;
HYPRE_Int S_ext_diag_size = 0;
HYPRE_Int *S_ext_offd_i = NULL;
HYPRE_Int *S_ext_offd_j = NULL;
HYPRE_Int S_ext_offd_size = 0;
HYPRE_Int *CF_marker_offd = NULL;
HYPRE_Int *S_marker = NULL;
HYPRE_Int *S_marker_offd = NULL;
//HYPRE_Int *temp = NULL;
HYPRE_Int *fine_to_coarse = NULL;
HYPRE_BigInt *fine_to_coarse_offd = NULL;
HYPRE_Int *map_S_to_C = NULL;
HYPRE_Int num_sends = 0;
HYPRE_Int num_recvs = 0;
HYPRE_Int *send_map_starts;
HYPRE_Int *tmp_send_map_starts = NULL;
HYPRE_Int *send_map_elmts;
HYPRE_Int *recv_vec_starts;
HYPRE_Int *tmp_recv_vec_starts = NULL;
HYPRE_Int *int_buf_data = NULL;
HYPRE_BigInt *big_int_buf_data = NULL;
HYPRE_BigInt *temp = NULL;
HYPRE_Int i, j, k;
HYPRE_Int i1, i2, i3;
HYPRE_BigInt big_i1;
HYPRE_Int jj1, jj2, jrow, j_cnt;
/*HYPRE_Int cnt, cnt_offd, cnt_diag;*/
HYPRE_Int num_procs, my_id;
HYPRE_Int index;
/*HYPRE_Int value;*/
HYPRE_Int num_coarse;
HYPRE_Int num_nonzeros;
HYPRE_BigInt global_num_coarse;
HYPRE_BigInt my_first_cpt, my_last_cpt;
HYPRE_Int *S_int_i = NULL;
HYPRE_BigInt *S_int_j = NULL;
HYPRE_Int *S_ext_i = NULL;
HYPRE_BigInt *S_ext_j = NULL;
/*HYPRE_Int prefix_sum_workspace[2*(hypre_NumThreads() + 1)];*/
HYPRE_Int *prefix_sum_workspace;
HYPRE_Int *num_coarse_prefix_sum;
prefix_sum_workspace = hypre_TAlloc(HYPRE_Int, 2*(hypre_NumThreads() + 1), HYPRE_MEMORY_HOST);
num_coarse_prefix_sum = hypre_TAlloc(HYPRE_Int, hypre_NumThreads() + 1, HYPRE_MEMORY_HOST);
/*-----------------------------------------------------------------------
* Extract S_ext, i.e. portion of B that is stored on neighbor procs
* and needed locally for matrix matrix product
*-----------------------------------------------------------------------*/
hypre_MPI_Comm_size(comm, &num_procs);
hypre_MPI_Comm_rank(comm, &my_id);
#ifdef HYPRE_NO_GLOBAL_PARTITION
my_first_cpt = coarse_row_starts[0];
my_last_cpt = coarse_row_starts[1]-1;
if (my_id == (num_procs -1)) global_num_coarse = coarse_row_starts[1];
hypre_MPI_Bcast(&global_num_coarse, 1, HYPRE_MPI_BIG_INT, num_procs-1, comm);
#else
my_first_cpt = coarse_row_starts[my_id];
my_last_cpt = coarse_row_starts[my_id+1]-1;
global_num_coarse = coarse_row_starts[num_procs];
#endif
if (num_cols_offd_S)
{
CF_marker_offd = hypre_TAlloc(HYPRE_Int, num_cols_offd_S, HYPRE_MEMORY_HOST);
fine_to_coarse_offd = hypre_TAlloc(HYPRE_BigInt, num_cols_offd_S, HYPRE_MEMORY_HOST);
}
HYPRE_Int *coarse_to_fine = NULL;
if (num_cols_diag_S)
{
fine_to_coarse = hypre_TAlloc(HYPRE_Int, num_cols_diag_S, HYPRE_MEMORY_HOST);
coarse_to_fine = hypre_TAlloc(HYPRE_Int, num_cols_diag_S, HYPRE_MEMORY_HOST);
}
/*HYPRE_Int num_coarse_prefix_sum[hypre_NumThreads() + 1];*/
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel private(i)
#endif
{
HYPRE_Int num_coarse_private = 0;
HYPRE_Int i_begin, i_end;
hypre_GetSimpleThreadPartition(&i_begin, &i_end, num_cols_diag_S);
for (i = i_begin; i < i_end; i++)
{
if (CF_marker[i] > 0) num_coarse_private++;
}
hypre_prefix_sum(&num_coarse_private, &num_coarse, num_coarse_prefix_sum);
for (i = i_begin; i < i_end; i++)
{
if (CF_marker[i] > 0)
{
fine_to_coarse[i] = num_coarse_private;
coarse_to_fine[num_coarse_private] = i;
num_coarse_private++;
}
else
{
fine_to_coarse[i] = -1;
}
}
} /* omp parallel */
if (num_procs > 1)
{
if (!comm_pkg)
{
hypre_MatvecCommPkgCreate(S);
comm_pkg = hypre_ParCSRMatrixCommPkg(S);
}
num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg);
send_map_starts = hypre_ParCSRCommPkgSendMapStarts(comm_pkg);
send_map_elmts = hypre_ParCSRCommPkgSendMapElmts(comm_pkg);
num_recvs = hypre_ParCSRCommPkgNumRecvs(comm_pkg);
recv_vec_starts = hypre_ParCSRCommPkgRecvVecStarts(comm_pkg);
HYPRE_Int begin = send_map_starts[0];
HYPRE_Int end = send_map_starts[num_sends];
big_int_buf_data = hypre_TAlloc(HYPRE_BigInt, end, HYPRE_MEMORY_HOST);
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for HYPRE_SMP_SCHEDULE
#endif
for (index = begin; index < end; index++)
{
big_int_buf_data[index - begin] = (HYPRE_BigInt)fine_to_coarse[send_map_elmts[index]] + my_first_cpt;
}
comm_handle = hypre_ParCSRCommHandleCreate( 21, comm_pkg, big_int_buf_data,
fine_to_coarse_offd);
hypre_ParCSRCommHandleDestroy(comm_handle);
int_buf_data = hypre_TAlloc(HYPRE_Int, end, HYPRE_MEMORY_HOST);
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for HYPRE_SMP_SCHEDULE
#endif
for (index = begin; index < end; index++)
{
int_buf_data[index - begin] = CF_marker[send_map_elmts[index]];
}
comm_handle = hypre_ParCSRCommHandleCreate(11, comm_pkg, int_buf_data,
CF_marker_offd);
hypre_ParCSRCommHandleDestroy(comm_handle);
hypre_TFree(int_buf_data, HYPRE_MEMORY_HOST);
hypre_TFree(big_int_buf_data, HYPRE_MEMORY_HOST);
S_int_i = hypre_TAlloc(HYPRE_Int, end+1, HYPRE_MEMORY_HOST);
S_ext_i = hypre_CTAlloc(HYPRE_Int, recv_vec_starts[num_recvs]+1, HYPRE_MEMORY_HOST);
/*--------------------------------------------------------------------------
* generate S_int_i through adding number of coarse row-elements of offd and diag
* for corresponding rows. S_int_i[j+1] contains the number of coarse elements of
* a row j (which is determined through send_map_elmts)
*--------------------------------------------------------------------------*/
S_int_i[0] = 0;
num_nonzeros = 0;
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(j,k) reduction(+:num_nonzeros) HYPRE_SMP_SCHEDULE
#endif
for (j = begin; j < end; j++)
{
HYPRE_Int jrow = send_map_elmts[j];
HYPRE_Int index = 0;
for (k = S_diag_i[jrow]; k < S_diag_i[jrow+1]; k++)
{
if (CF_marker[S_diag_j[k]] > 0) index++;
}
for (k = S_offd_i[jrow]; k < S_offd_i[jrow+1]; k++)
{
if (CF_marker_offd[S_offd_j[k]] > 0) index++;
}
S_int_i[j - begin + 1] = index;
num_nonzeros += S_int_i[j - begin + 1];
}
/*--------------------------------------------------------------------------
* initialize communication
*--------------------------------------------------------------------------*/
if (num_procs > 1)
comm_handle =
hypre_ParCSRCommHandleCreate(11,comm_pkg,&S_int_i[1],&S_ext_i[1]);
if (num_nonzeros) S_int_j = hypre_TAlloc(HYPRE_BigInt, num_nonzeros, HYPRE_MEMORY_HOST);
tmp_send_map_starts = hypre_CTAlloc(HYPRE_Int, num_sends+1, HYPRE_MEMORY_HOST);
tmp_recv_vec_starts = hypre_CTAlloc(HYPRE_Int, num_recvs+1, HYPRE_MEMORY_HOST);
tmp_send_map_starts[0] = 0;
j_cnt = 0;
for (i=0; i < num_sends; i++)
{
for (j = send_map_starts[i]; j < send_map_starts[i+1]; j++)
{
jrow = send_map_elmts[j];
for (k=S_diag_i[jrow]; k < S_diag_i[jrow+1]; k++)
{
if (CF_marker[S_diag_j[k]] > 0)
S_int_j[j_cnt++] = (HYPRE_BigInt)fine_to_coarse[S_diag_j[k]]+my_first_cpt;
}
for (k=S_offd_i[jrow]; k < S_offd_i[jrow+1]; k++)
{
if (CF_marker_offd[S_offd_j[k]] > 0)
S_int_j[j_cnt++] = fine_to_coarse_offd[S_offd_j[k]];
}
}
tmp_send_map_starts[i+1] = j_cnt;
}
tmp_comm_pkg = hypre_CTAlloc(hypre_ParCSRCommPkg, 1, HYPRE_MEMORY_HOST);
hypre_ParCSRCommPkgComm(tmp_comm_pkg) = comm;
hypre_ParCSRCommPkgNumSends(tmp_comm_pkg) = num_sends;
hypre_ParCSRCommPkgNumRecvs(tmp_comm_pkg) = num_recvs;
hypre_ParCSRCommPkgSendProcs(tmp_comm_pkg) =
hypre_ParCSRCommPkgSendProcs(comm_pkg);
hypre_ParCSRCommPkgRecvProcs(tmp_comm_pkg) =
hypre_ParCSRCommPkgRecvProcs(comm_pkg);
hypre_ParCSRCommPkgSendMapStarts(tmp_comm_pkg) = tmp_send_map_starts;
hypre_ParCSRCommHandleDestroy(comm_handle);
comm_handle = NULL;
/*--------------------------------------------------------------------------
* after communication exchange S_ext_i[j+1] contains the number of coarse elements
* of a row j !
* evaluate S_ext_i and compute num_nonzeros for S_ext
*--------------------------------------------------------------------------*/
for (i=0; i < recv_vec_starts[num_recvs]; i++)
S_ext_i[i+1] += S_ext_i[i];
num_nonzeros = S_ext_i[recv_vec_starts[num_recvs]];
if (num_nonzeros) S_ext_j = hypre_TAlloc(HYPRE_BigInt, num_nonzeros, HYPRE_MEMORY_HOST);
tmp_recv_vec_starts[0] = 0;
for (i=0; i < num_recvs; i++)
tmp_recv_vec_starts[i+1] = S_ext_i[recv_vec_starts[i+1]];
hypre_ParCSRCommPkgRecvVecStarts(tmp_comm_pkg) = tmp_recv_vec_starts;
comm_handle = hypre_ParCSRCommHandleCreate(21,tmp_comm_pkg,S_int_j,S_ext_j);
hypre_ParCSRCommHandleDestroy(comm_handle);
comm_handle = NULL;
hypre_TFree(tmp_send_map_starts, HYPRE_MEMORY_HOST);
hypre_TFree(tmp_recv_vec_starts, HYPRE_MEMORY_HOST);
hypre_TFree(tmp_comm_pkg, HYPRE_MEMORY_HOST);
hypre_TFree(S_int_i, HYPRE_MEMORY_HOST);
hypre_TFree(S_int_j, HYPRE_MEMORY_HOST);
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_RENUMBER_COLIDX] -= hypre_MPI_Wtime();
#endif
#ifdef HYPRE_CONCURRENT_HOPSCOTCH
HYPRE_BigInt *S_big_offd_j = NULL;
S_ext_diag_i = hypre_TAlloc(HYPRE_Int, num_cols_offd_S+1, HYPRE_MEMORY_HOST);
S_ext_diag_i[0] = 0;
S_ext_offd_i = hypre_TAlloc(HYPRE_Int, num_cols_offd_S+1, HYPRE_MEMORY_HOST);
S_ext_offd_i[0] = 0;
hypre_UnorderedBigIntSet found_set;
hypre_UnorderedBigIntSetCreate(&found_set, S_ext_i[num_cols_offd_S] + num_cols_offd_S, 16*hypre_NumThreads());
#pragma omp parallel private(i,j, big_i1)
{
HYPRE_Int S_ext_offd_size_private = 0;
HYPRE_Int S_ext_diag_size_private = 0;
HYPRE_Int i_begin, i_end;
hypre_GetSimpleThreadPartition(&i_begin, &i_end, num_cols_offd_S);
for (i = i_begin; i < i_end; i++)
{
if (CF_marker_offd[i] > 0)
{
hypre_UnorderedBigIntSetPut(&found_set, fine_to_coarse_offd[i]);
}
for (j=S_ext_i[i]; j < S_ext_i[i+1]; j++)
{
big_i1 = S_ext_j[j];
if (big_i1 < my_first_cpt || big_i1 > my_last_cpt)
{
S_ext_offd_size_private++;
hypre_UnorderedBigIntSetPut(&found_set, big_i1);
}
else
S_ext_diag_size_private++;
}
}
hypre_prefix_sum_pair(
&S_ext_diag_size_private, &S_ext_diag_size,
&S_ext_offd_size_private, &S_ext_offd_size,
prefix_sum_workspace);
#pragma omp master
{
if (S_ext_diag_size)
S_ext_diag_j = hypre_TAlloc(HYPRE_Int, S_ext_diag_size, HYPRE_MEMORY_HOST);
if (S_ext_offd_size)
{
S_ext_offd_j = hypre_TAlloc(HYPRE_Int, S_ext_offd_size, HYPRE_MEMORY_HOST);
S_big_offd_j = hypre_TAlloc(HYPRE_BigInt, S_ext_offd_size, HYPRE_MEMORY_HOST);
}
}
#pragma omp barrier
for (i = i_begin; i < i_end; i++)
{
for (j=S_ext_i[i]; j < S_ext_i[i+1]; j++)
{
big_i1 = S_ext_j[j];
if (big_i1 < my_first_cpt || big_i1 > my_last_cpt)
S_big_offd_j[S_ext_offd_size_private++] = big_i1;
//S_ext_offd_j[S_ext_offd_size_private++] = big_i1;
else
S_ext_diag_j[S_ext_diag_size_private++] = (HYPRE_Int)(big_i1 - my_first_cpt);
}
S_ext_diag_i[i + 1] = S_ext_diag_size_private;
S_ext_offd_i[i + 1] = S_ext_offd_size_private;
}
} // omp parallel
temp = hypre_UnorderedBigIntSetCopyToArray(&found_set, &num_cols_offd_C);
hypre_UnorderedBigIntSetDestroy(&found_set);
hypre_TFree(S_ext_i, HYPRE_MEMORY_HOST);
hypre_UnorderedBigIntMap col_map_offd_C_inverse;
hypre_big_sort_and_create_inverse_map(temp, num_cols_offd_C, &col_map_offd_C, &col_map_offd_C_inverse);
#pragma omp parallel for HYPRE_SMP_SCHEDULE
for (i=0 ; i < S_ext_offd_size; i++)
S_ext_offd_j[i] = hypre_UnorderedBigIntMapGet(&col_map_offd_C_inverse, S_big_offd_j[i]);
//S_ext_offd_j[i] = hypre_UnorderedIntMapGet(&col_map_offd_C_inverse, S_ext_offd_j[i]);
hypre_TFree(S_ext_j, HYPRE_MEMORY_HOST);
hypre_TFree(S_big_offd_j, HYPRE_MEMORY_HOST);
if (num_cols_offd_C) hypre_UnorderedBigIntMapDestroy(&col_map_offd_C_inverse);
#else /* !HYPRE_CONCURRENT_HOPSCOTCH */
HYPRE_Int cnt_offd, cnt_diag, cnt, value;
S_ext_diag_size = 0;
S_ext_offd_size = 0;
for (i=0; i < num_cols_offd_S; i++)
{
for (j=S_ext_i[i]; j < S_ext_i[i+1]; j++)
{
if (S_ext_j[j] < my_first_cpt || S_ext_j[j] > my_last_cpt)
S_ext_offd_size++;
else
S_ext_diag_size++;
}
}
S_ext_diag_i = hypre_CTAlloc(HYPRE_Int, num_cols_offd_S+1, HYPRE_MEMORY_HOST);
S_ext_offd_i = hypre_CTAlloc(HYPRE_Int, num_cols_offd_S+1, HYPRE_MEMORY_HOST);
if (S_ext_diag_size)
{
S_ext_diag_j = hypre_CTAlloc(HYPRE_Int, S_ext_diag_size, HYPRE_MEMORY_HOST);
}
if (S_ext_offd_size)
{
S_ext_offd_j = hypre_CTAlloc(HYPRE_Int, S_ext_offd_size, HYPRE_MEMORY_HOST);
}
cnt_offd = 0;
cnt_diag = 0;
cnt = 0;
HYPRE_Int num_coarse_offd = 0;
for (i=0; i < num_cols_offd_S; i++)
{
if (CF_marker_offd[i] > 0) num_coarse_offd++;
for (j=S_ext_i[i]; j < S_ext_i[i+1]; j++)
{
big_i1 = S_ext_j[j];
if (big_i1 < my_first_cpt || big_i1 > my_last_cpt)
S_ext_j[cnt_offd++] = big_i1;
else
S_ext_diag_j[cnt_diag++] = (HYPRE_Int)(big_i1 - my_first_cpt);
}
S_ext_diag_i[++cnt] = cnt_diag;
S_ext_offd_i[cnt] = cnt_offd;
}
hypre_TFree(S_ext_i, HYPRE_MEMORY_HOST);
cnt = 0;
if (S_ext_offd_size || num_coarse_offd)
{
temp = hypre_CTAlloc(HYPRE_BigInt, S_ext_offd_size+num_coarse_offd, HYPRE_MEMORY_HOST);
for (i=0; i < S_ext_offd_size; i++)
temp[i] = S_ext_j[i];
cnt = S_ext_offd_size;
for (i=0; i < num_cols_offd_S; i++)
if (CF_marker_offd[i] > 0) temp[cnt++] = fine_to_coarse_offd[i];
}
if (cnt)
{
hypre_BigQsort0(temp, 0, cnt-1);
num_cols_offd_C = 1;
value = temp[0];
for (i=1; i < cnt; i++)
{
if (temp[i] > value)
{
value = temp[i];
temp[num_cols_offd_C++] = value;
}
}
}
if (num_cols_offd_C)
col_map_offd_C = hypre_CTAlloc(HYPRE_BigInt, num_cols_offd_C, HYPRE_MEMORY_HOST);
for (i=0; i < num_cols_offd_C; i++)
col_map_offd_C[i] = temp[i];
if (S_ext_offd_size || num_coarse_offd)
hypre_TFree(temp, HYPRE_MEMORY_HOST);
for (i=0 ; i < S_ext_offd_size; i++)
S_ext_offd_j[i] = hypre_BigBinarySearch(col_map_offd_C,
S_ext_j[i],
num_cols_offd_C);
hypre_TFree(S_ext_j, HYPRE_MEMORY_HOST);
#endif /* !HYPRE_CONCURRENT_HOPSCOTCH */
if (num_cols_offd_S)
{
map_S_to_C = hypre_TAlloc(HYPRE_Int, num_cols_offd_S, HYPRE_MEMORY_HOST);
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel private(i)
#endif
{
HYPRE_Int i_begin, i_end;
hypre_GetSimpleThreadPartition(&i_begin, &i_end, num_cols_offd_S);
HYPRE_BigInt cnt = 0;
for (i = i_begin; i < i_end; i++)
{
if (CF_marker_offd[i] > 0)
{
cnt = hypre_BigLowerBound(col_map_offd_C + cnt, col_map_offd_C + num_cols_offd_C, fine_to_coarse_offd[i]) - col_map_offd_C;
map_S_to_C[i] = cnt++;
}
else map_S_to_C[i] = -1;
}
} /* omp parallel */
}
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_RENUMBER_COLIDX] += hypre_MPI_Wtime();
#endif
} /* num_procs > 1 */
/*-----------------------------------------------------------------------
* Allocate and initialize some stuff.
*-----------------------------------------------------------------------*/
HYPRE_Int *S_marker_array = NULL, *S_marker_offd_array = NULL;
if (num_coarse) S_marker_array = hypre_TAlloc(HYPRE_Int, num_coarse*hypre_NumThreads(), HYPRE_MEMORY_HOST);
if (num_cols_offd_C) S_marker_offd_array = hypre_TAlloc(HYPRE_Int, num_cols_offd_C*hypre_NumThreads(), HYPRE_MEMORY_HOST);
HYPRE_Int *C_temp_offd_j_array = NULL;
HYPRE_Int *C_temp_diag_j_array = NULL;
HYPRE_Int *C_temp_offd_data_array = NULL;
HYPRE_Int *C_temp_diag_data_array = NULL;
if (num_paths > 1)
{
C_temp_diag_j_array = hypre_TAlloc(HYPRE_Int, num_coarse*hypre_NumThreads(), HYPRE_MEMORY_HOST);
C_temp_offd_j_array = hypre_TAlloc(HYPRE_Int, num_cols_offd_C*hypre_NumThreads(), HYPRE_MEMORY_HOST);
C_temp_diag_data_array = hypre_TAlloc(HYPRE_Int, num_coarse*hypre_NumThreads(), HYPRE_MEMORY_HOST);
C_temp_offd_data_array = hypre_TAlloc(HYPRE_Int, num_cols_offd_C*hypre_NumThreads(), HYPRE_MEMORY_HOST);
}
C_diag_i = hypre_CTAlloc(HYPRE_Int, num_coarse+1, HYPRE_MEMORY_HOST);
C_offd_i = hypre_CTAlloc(HYPRE_Int, num_coarse+1, HYPRE_MEMORY_HOST);
/*-----------------------------------------------------------------------
* Loop over rows of S
*-----------------------------------------------------------------------*/
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel private(i1,i2,i3,jj1,jj2,index)
#endif
{
HYPRE_Int my_thread_num = hypre_GetThreadNum();
HYPRE_Int i1_begin, i1_end;
hypre_GetSimpleThreadPartition(&i1_begin, &i1_end, num_cols_diag_S);
HYPRE_Int *C_temp_diag_j = NULL, *C_temp_offd_j = NULL;
HYPRE_Int *C_temp_diag_data = NULL, *C_temp_offd_data = NULL;
if (num_paths > 1)
{
C_temp_diag_j = C_temp_diag_j_array + num_coarse*my_thread_num;
C_temp_offd_j = C_temp_offd_j_array + num_cols_offd_C*my_thread_num;
C_temp_diag_data = C_temp_diag_data_array + num_coarse*my_thread_num;
C_temp_offd_data = C_temp_offd_data_array + num_cols_offd_C*my_thread_num;
}
HYPRE_Int *S_marker = NULL, *S_marker_offd = NULL;
if (num_coarse) S_marker = S_marker_array + num_coarse*my_thread_num;
if (num_cols_offd_C) S_marker_offd = S_marker_offd_array + num_cols_offd_C*my_thread_num;
for (i1 = 0; i1 < num_coarse; i1++)
{
S_marker[i1] = -1;
}
for (i1 = 0; i1 < num_cols_offd_C; i1++)
{
S_marker_offd[i1] = -1;
}
// These two counters are for before filtering by num_paths
HYPRE_Int jj_count_diag = 0;
HYPRE_Int jj_count_offd = 0;
// These two counters are for after filtering by num_paths
HYPRE_Int num_nonzeros_diag = 0;
HYPRE_Int num_nonzeros_offd = 0;
HYPRE_Int ic_begin = num_coarse_prefix_sum[my_thread_num];
HYPRE_Int ic_end = num_coarse_prefix_sum[my_thread_num + 1];
HYPRE_Int ic;
if (num_paths == 1)
{
for (ic = ic_begin; ic < ic_end; ic++)
{
/*--------------------------------------------------------------------
* Set marker for diagonal entry, C_{i1,i1} (for square matrices).
*--------------------------------------------------------------------*/
i1 = coarse_to_fine[ic];
HYPRE_Int jj_row_begin_diag = num_nonzeros_diag;
HYPRE_Int jj_row_begin_offd = num_nonzeros_offd;
C_diag_i[ic] = num_nonzeros_diag;
if (num_cols_offd_C)
{
C_offd_i[ic] = num_nonzeros_offd;
}
for (jj1 = S_diag_i[i1]; jj1 < S_diag_i[i1+1]; jj1++)
{
i2 = S_diag_j[jj1];
if (CF_marker[i2] > 0)
{
index = fine_to_coarse[i2];
if (S_marker[index] < jj_row_begin_diag)
{
S_marker[index] = num_nonzeros_diag;
num_nonzeros_diag++;
}
}
for (jj2 = S_diag_i[i2]; jj2 < S_diag_i[i2+1]; jj2++)
{
i3 = S_diag_j[jj2];
if (CF_marker[i3] > 0)
{
index = fine_to_coarse[i3];
if (index != ic && S_marker[index] < jj_row_begin_diag)
{
S_marker[index] = num_nonzeros_diag;
num_nonzeros_diag++;
}
}
}
for (jj2 = S_offd_i[i2]; jj2 < S_offd_i[i2+1]; jj2++)
{
i3 = S_offd_j[jj2];
if (CF_marker_offd[i3] > 0)
{
index = map_S_to_C[i3];
if (S_marker_offd[index] < jj_row_begin_offd)
{
S_marker_offd[index] = num_nonzeros_offd;
num_nonzeros_offd++;
}
}
}
}
for (jj1 = S_offd_i[i1]; jj1 < S_offd_i[i1+1]; jj1++)
{
i2 = S_offd_j[jj1];
if (CF_marker_offd[i2] > 0)
{
index = map_S_to_C[i2];
if (S_marker_offd[index] < jj_row_begin_offd)
{
S_marker_offd[index] = num_nonzeros_offd;
num_nonzeros_offd++;
}
}
for (jj2 = S_ext_diag_i[i2]; jj2 < S_ext_diag_i[i2+1]; jj2++)
{
i3 = S_ext_diag_j[jj2];
if (i3 != ic && S_marker[i3] < jj_row_begin_diag)
{
S_marker[i3] = num_nonzeros_diag;
num_nonzeros_diag++;
}
}
for (jj2 = S_ext_offd_i[i2]; jj2 < S_ext_offd_i[i2+1]; jj2++)
{
i3 = S_ext_offd_j[jj2];
if (S_marker_offd[i3] < jj_row_begin_offd)
{
S_marker_offd[i3] = num_nonzeros_offd;
num_nonzeros_offd++;
}
}
}
} /* for each row */
} /* num_paths == 1 */
else
{
for (ic = ic_begin; ic < ic_end; ic++)
{
/*--------------------------------------------------------------------
* Set marker for diagonal entry, C_{i1,i1} (for square matrices).
*--------------------------------------------------------------------*/
i1 = coarse_to_fine[ic];
HYPRE_Int jj_row_begin_diag = jj_count_diag;
HYPRE_Int jj_row_begin_offd = jj_count_offd;
C_diag_i[ic] = num_nonzeros_diag;
if (num_cols_offd_C)
{
C_offd_i[ic] = num_nonzeros_offd;
}
for (jj1 = S_diag_i[i1]; jj1 < S_diag_i[i1+1]; jj1++)
{
i2 = S_diag_j[jj1];
if (CF_marker[i2] > 0)
{
index = fine_to_coarse[i2];
if (S_marker[index] < jj_row_begin_diag)
{
S_marker[index] = jj_count_diag;
C_temp_diag_data[jj_count_diag - jj_row_begin_diag] = 2;
jj_count_diag++;
}
else
{
C_temp_diag_data[S_marker[index] - jj_row_begin_diag] += 2;
}
}
for (jj2 = S_diag_i[i2]; jj2 < S_diag_i[i2+1]; jj2++)
{
i3 = S_diag_j[jj2];
if (CF_marker[i3] > 0 && fine_to_coarse[i3] != ic)
{
index = fine_to_coarse[i3];
if (S_marker[index] < jj_row_begin_diag)
{
S_marker[index] = jj_count_diag;
C_temp_diag_data[jj_count_diag - jj_row_begin_diag] = 1;
jj_count_diag++;
}
else
{
C_temp_diag_data[S_marker[index] - jj_row_begin_diag]++;
}
}
}
for (jj2 = S_offd_i[i2]; jj2 < S_offd_i[i2+1]; jj2++)
{
i3 = S_offd_j[jj2];
if (CF_marker_offd[i3] > 0)
{
index = map_S_to_C[i3];
if (S_marker_offd[index] < jj_row_begin_offd)
{
S_marker_offd[index] = jj_count_offd;
C_temp_offd_data[jj_count_offd - jj_row_begin_offd] = 1;
jj_count_offd++;
}
else
{
C_temp_offd_data[S_marker_offd[index] - jj_row_begin_offd]++;
}
}
}
}
for (jj1 = S_offd_i[i1]; jj1 < S_offd_i[i1+1]; jj1++)
{
i2 = S_offd_j[jj1];
if (CF_marker_offd[i2] > 0)
{
index = map_S_to_C[i2];
if (S_marker_offd[index] < jj_row_begin_offd)
{
S_marker_offd[index] = jj_count_offd;
C_temp_offd_data[jj_count_offd - jj_row_begin_offd] = 2;
jj_count_offd++;
}
else
{
C_temp_offd_data[S_marker_offd[index] - jj_row_begin_offd] += 2;
}
}
for (jj2 = S_ext_diag_i[i2]; jj2 < S_ext_diag_i[i2+1]; jj2++)
{
i3 = S_ext_diag_j[jj2];
if (i3 != ic)
{
if (S_marker[i3] < jj_row_begin_diag)
{
S_marker[i3] = jj_count_diag;
C_temp_diag_data[jj_count_diag - jj_row_begin_diag] = 1;
jj_count_diag++;
}
else
{
C_temp_diag_data[S_marker[i3] - jj_row_begin_diag]++;
}
}
}
for (jj2 = S_ext_offd_i[i2]; jj2 < S_ext_offd_i[i2+1]; jj2++)
{
i3 = S_ext_offd_j[jj2];
if (S_marker_offd[i3] < jj_row_begin_offd)
{
S_marker_offd[i3] = jj_count_offd;
C_temp_offd_data[jj_count_offd - jj_row_begin_offd] = 1;
jj_count_offd++;
}
else
{
C_temp_offd_data[S_marker_offd[i3] - jj_row_begin_offd]++;
}
}
}
for (jj1 = jj_row_begin_diag; jj1 < jj_count_diag; jj1++)
{
if (C_temp_diag_data[jj1 - jj_row_begin_diag] >= num_paths)
{
++num_nonzeros_diag;
}
C_temp_diag_data[jj1 - jj_row_begin_diag] = 0;
}
for (jj1 = jj_row_begin_offd; jj1 < jj_count_offd; jj1++)
{
if (C_temp_offd_data[jj1 - jj_row_begin_offd] >= num_paths)
{
++num_nonzeros_offd;
}
C_temp_offd_data[jj1 - jj_row_begin_offd] = 0;
}
} /* for each row */
} /* num_paths > 1 */
hypre_prefix_sum_pair(
&num_nonzeros_diag, &C_diag_i[num_coarse],
&num_nonzeros_offd, &C_offd_i[num_coarse],
prefix_sum_workspace);
for (i1 = 0; i1 < num_coarse; i1++)
{
S_marker[i1] = -1;
}
for (i1 = 0; i1 < num_cols_offd_C; i1++)
{
S_marker_offd[i1] = -1;
}
#ifdef HYPRE_USING_OPENMP
#pragma omp barrier
#pragma omp master
#endif
{
if (C_diag_i[num_coarse])
{
C_diag_j = hypre_TAlloc(HYPRE_Int, C_diag_i[num_coarse], HYPRE_MEMORY_HOST);
}
if (C_offd_i[num_coarse])
{
C_offd_j = hypre_TAlloc(HYPRE_Int, C_offd_i[num_coarse], HYPRE_MEMORY_HOST);
}
}
#ifdef HYPRE_USING_OPENMP
#pragma omp barrier
#endif
for (ic = ic_begin; ic < ic_end - 1; ic++)
{
if (C_diag_i[ic+1] == C_diag_i[ic] && C_offd_i[ic+1] == C_offd_i[ic])
CF_marker[coarse_to_fine[ic]] = 2;
C_diag_i[ic] += num_nonzeros_diag;
C_offd_i[ic] += num_nonzeros_offd;
}
if (ic_begin < ic_end)
{
C_diag_i[ic] += num_nonzeros_diag;
C_offd_i[ic] += num_nonzeros_offd;
HYPRE_Int next_C_diag_i = prefix_sum_workspace[2*(my_thread_num + 1)];
HYPRE_Int next_C_offd_i = prefix_sum_workspace[2*(my_thread_num + 1) + 1];
if (next_C_diag_i == C_diag_i[ic] && next_C_offd_i == C_offd_i[ic])
CF_marker[coarse_to_fine[ic]] = 2;
}
if (num_paths == 1)
{
for (ic = ic_begin; ic < ic_end; ic++)
{
/*--------------------------------------------------------------------
* Set marker for diagonal entry, C_{i1,i1} (for square matrices).
*--------------------------------------------------------------------*/
i1 = coarse_to_fine[ic];
HYPRE_Int jj_row_begin_diag = num_nonzeros_diag;
HYPRE_Int jj_row_begin_offd = num_nonzeros_offd;
for (jj1 = S_diag_i[i1]; jj1 < S_diag_i[i1+1]; jj1++)
{
i2 = S_diag_j[jj1];
if (CF_marker[i2] > 0)
{
index = fine_to_coarse[i2];
if (S_marker[index] < jj_row_begin_diag)
{
S_marker[index] = num_nonzeros_diag;
C_diag_j[num_nonzeros_diag] = index;
num_nonzeros_diag++;
}
}
for (jj2 = S_diag_i[i2]; jj2 < S_diag_i[i2+1]; jj2++)
{
i3 = S_diag_j[jj2];
if (CF_marker[i3] > 0)
{
index = fine_to_coarse[i3];
if (index != ic && S_marker[index] < jj_row_begin_diag)
{
S_marker[index] = num_nonzeros_diag;
C_diag_j[num_nonzeros_diag] = index;
num_nonzeros_diag++;
}
}
}
for (jj2 = S_offd_i[i2]; jj2 < S_offd_i[i2+1]; jj2++)
{
i3 = S_offd_j[jj2];
if (CF_marker_offd[i3] > 0)
{
index = map_S_to_C[i3];
if (S_marker_offd[index] < jj_row_begin_offd)
{
S_marker_offd[index] = num_nonzeros_offd;
C_offd_j[num_nonzeros_offd] = index;
num_nonzeros_offd++;
}
}
}
}
for (jj1 = S_offd_i[i1]; jj1 < S_offd_i[i1+1]; jj1++)
{
i2 = S_offd_j[jj1];
if (CF_marker_offd[i2] > 0)
{
index = map_S_to_C[i2];
if (S_marker_offd[index] < jj_row_begin_offd)
{
S_marker_offd[index] = num_nonzeros_offd;
C_offd_j[num_nonzeros_offd] = index;
num_nonzeros_offd++;
}
}
for (jj2 = S_ext_diag_i[i2]; jj2 < S_ext_diag_i[i2+1]; jj2++)
{
i3 = S_ext_diag_j[jj2];
if (i3 != ic && S_marker[i3] < jj_row_begin_diag)
{
S_marker[i3] = num_nonzeros_diag;
C_diag_j[num_nonzeros_diag] = i3;
num_nonzeros_diag++;
}
}
for (jj2 = S_ext_offd_i[i2]; jj2 < S_ext_offd_i[i2+1]; jj2++)
{
i3 = S_ext_offd_j[jj2];
if (S_marker_offd[i3] < jj_row_begin_offd)
{
S_marker_offd[i3] = num_nonzeros_offd;
C_offd_j[num_nonzeros_offd] = i3;
num_nonzeros_offd++;
}
}
}
} /* for each row */
} /* num_paths == 1 */
else
{
jj_count_diag = num_nonzeros_diag;
jj_count_offd = num_nonzeros_offd;
for (ic = ic_begin; ic < ic_end; ic++)
{
/*--------------------------------------------------------------------
* Set marker for diagonal entry, C_{i1,i1} (for square matrices).
*--------------------------------------------------------------------*/
i1 = coarse_to_fine[ic];
HYPRE_Int jj_row_begin_diag = jj_count_diag;
HYPRE_Int jj_row_begin_offd = jj_count_offd;
for (jj1 = S_diag_i[i1]; jj1 < S_diag_i[i1+1]; jj1++)
{
i2 = S_diag_j[jj1];
if (CF_marker[i2] > 0)
{
index = fine_to_coarse[i2];
if (S_marker[index] < jj_row_begin_diag)
{
S_marker[index] = jj_count_diag;
C_temp_diag_j[jj_count_diag - jj_row_begin_diag] = index;
C_temp_diag_data[jj_count_diag - jj_row_begin_diag] = 2;
jj_count_diag++;
}
else
{
C_temp_diag_data[S_marker[index] - jj_row_begin_diag] += 2;
}
}
for (jj2 = S_diag_i[i2]; jj2 < S_diag_i[i2+1]; jj2++)
{
i3 = S_diag_j[jj2];
if (CF_marker[i3] > 0 && fine_to_coarse[i3] != ic)
{
index = fine_to_coarse[i3];
if (S_marker[index] < jj_row_begin_diag)
{
S_marker[index] = jj_count_diag;
C_temp_diag_j[jj_count_diag - jj_row_begin_diag] = index;
C_temp_diag_data[jj_count_diag - jj_row_begin_diag] = 1;
jj_count_diag++;
}
else
{
C_temp_diag_data[S_marker[index] - jj_row_begin_diag]++;
}
}
}
for (jj2 = S_offd_i[i2]; jj2 < S_offd_i[i2+1]; jj2++)
{
i3 = S_offd_j[jj2];
if (CF_marker_offd[i3] > 0)
{
index = map_S_to_C[i3];
if (S_marker_offd[index] < jj_row_begin_offd)
{
S_marker_offd[index] = jj_count_offd;
C_temp_offd_j[jj_count_offd - jj_row_begin_offd] = index;
C_temp_offd_data[jj_count_offd - jj_row_begin_offd] = 1;
jj_count_offd++;
}
else
{
C_temp_offd_data[S_marker_offd[index] - jj_row_begin_offd]++;
}
}
}
}
for (jj1 = S_offd_i[i1]; jj1 < S_offd_i[i1+1]; jj1++)
{
i2 = S_offd_j[jj1];
if (CF_marker_offd[i2] > 0)
{
index = map_S_to_C[i2];
if (S_marker_offd[index] < jj_row_begin_offd)
{
S_marker_offd[index] = jj_count_offd;
C_temp_offd_j[jj_count_offd - jj_row_begin_offd] = index;
C_temp_offd_data[jj_count_offd - jj_row_begin_offd] = 2;
jj_count_offd++;
}
else
{
C_temp_offd_data[S_marker_offd[index] - jj_row_begin_offd] += 2;
}
}
for (jj2 = S_ext_diag_i[i2]; jj2 < S_ext_diag_i[i2+1]; jj2++)
{
i3 = S_ext_diag_j[jj2];
if (i3 != ic)
{
if (S_marker[i3] < jj_row_begin_diag)
{
S_marker[i3] = jj_count_diag;
C_temp_diag_j[jj_count_diag - jj_row_begin_diag] = i3;
C_temp_diag_data[jj_count_diag - jj_row_begin_diag] = 1;
jj_count_diag++;
}
else
{
C_temp_diag_data[S_marker[i3] - jj_row_begin_diag]++;
}
}
}
for (jj2 = S_ext_offd_i[i2]; jj2 < S_ext_offd_i[i2+1]; jj2++)
{
i3 = S_ext_offd_j[jj2];
if (S_marker_offd[i3] < jj_row_begin_offd)
{
S_marker_offd[i3] = jj_count_offd;
C_temp_offd_j[jj_count_offd - jj_row_begin_offd] = i3;
C_temp_offd_data[jj_count_offd - jj_row_begin_offd] = 1;
jj_count_offd++;
}
else
{
C_temp_offd_data[S_marker_offd[i3] - jj_row_begin_offd]++;
}
}
}
for (jj1 = jj_row_begin_diag; jj1 < jj_count_diag; jj1++)
{
if (C_temp_diag_data[jj1 - jj_row_begin_diag] >= num_paths)
{
C_diag_j[num_nonzeros_diag++] = C_temp_diag_j[jj1 - jj_row_begin_diag];
}
C_temp_diag_data[jj1 - jj_row_begin_diag] = 0;
}
for (jj1 = jj_row_begin_offd; jj1 < jj_count_offd; jj1++)
{
if (C_temp_offd_data[jj1 - jj_row_begin_offd] >= num_paths)
{
C_offd_j[num_nonzeros_offd++] = C_temp_offd_j[jj1 - jj_row_begin_offd];
}
C_temp_offd_data[jj1 - jj_row_begin_offd] = 0;
}
} /* for each row */
} /* num_paths > 1 */
} /* omp parallel */
S2 = hypre_ParCSRMatrixCreate(comm, global_num_coarse,
global_num_coarse, coarse_row_starts,
coarse_row_starts, num_cols_offd_C, C_diag_i[num_coarse], C_offd_i[num_coarse]);
hypre_ParCSRMatrixOwnsRowStarts(S2) = 0;
C_diag = hypre_ParCSRMatrixDiag(S2);
hypre_CSRMatrixI(C_diag) = C_diag_i;
if (C_diag_i[num_coarse]) hypre_CSRMatrixJ(C_diag) = C_diag_j;
C_offd = hypre_ParCSRMatrixOffd(S2);
hypre_CSRMatrixI(C_offd) = C_offd_i;
hypre_ParCSRMatrixOffd(S2) = C_offd;
if (num_cols_offd_C)
{
if (C_offd_i[num_coarse]) hypre_CSRMatrixJ(C_offd) = C_offd_j;
hypre_ParCSRMatrixColMapOffd(S2) = col_map_offd_C;
}
/*-----------------------------------------------------------------------
* Free various arrays
*-----------------------------------------------------------------------*/
hypre_TFree(C_temp_diag_j_array, HYPRE_MEMORY_HOST);
hypre_TFree(C_temp_diag_data_array, HYPRE_MEMORY_HOST);
hypre_TFree(C_temp_offd_j_array, HYPRE_MEMORY_HOST);
hypre_TFree(C_temp_offd_data_array, HYPRE_MEMORY_HOST);
hypre_TFree(S_marker_array, HYPRE_MEMORY_HOST);
hypre_TFree(S_marker_offd_array, HYPRE_MEMORY_HOST);
hypre_TFree(S_marker, HYPRE_MEMORY_HOST);
hypre_TFree(S_marker_offd, HYPRE_MEMORY_HOST);
hypre_TFree(S_ext_diag_i, HYPRE_MEMORY_HOST);
hypre_TFree(fine_to_coarse, HYPRE_MEMORY_HOST);
hypre_TFree(coarse_to_fine, HYPRE_MEMORY_HOST);
if (S_ext_diag_size)
{
hypre_TFree(S_ext_diag_j, HYPRE_MEMORY_HOST);
}
hypre_TFree(S_ext_offd_i, HYPRE_MEMORY_HOST);
if (S_ext_offd_size)
{
hypre_TFree(S_ext_offd_j, HYPRE_MEMORY_HOST);
}
if (num_cols_offd_S)
{
hypre_TFree(map_S_to_C, HYPRE_MEMORY_HOST);
hypre_TFree(CF_marker_offd, HYPRE_MEMORY_HOST);
hypre_TFree(fine_to_coarse_offd, HYPRE_MEMORY_HOST);
}
*C_ptr = S2;
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_CREATE_2NDS] += hypre_MPI_Wtime();
#endif
hypre_TFree(prefix_sum_workspace, HYPRE_MEMORY_HOST);
hypre_TFree(num_coarse_prefix_sum, HYPRE_MEMORY_HOST);
return 0;
}
/*--------------------------------------------------------------------------
* hypre_BoomerAMGCorrectCFMarker : corrects CF_marker after aggr. coarsening
*--------------------------------------------------------------------------*/
HYPRE_Int
hypre_BoomerAMGCorrectCFMarker(HYPRE_Int *CF_marker, HYPRE_Int num_var, HYPRE_Int *new_CF_marker)
{
HYPRE_Int i, cnt;
cnt = 0;
for (i=0; i < num_var; i++)
{
if (CF_marker[i] > 0 )
{
if (CF_marker[i] == 1) CF_marker[i] = new_CF_marker[cnt++];
else { CF_marker[i] = 1; cnt++;}
}
}
return 0;
}
/*--------------------------------------------------------------------------
* hypre_BoomerAMGCorrectCFMarker2 : corrects CF_marker after aggr. coarsening,
* but marks new F-points (previous C-points) as -2
*--------------------------------------------------------------------------*/
HYPRE_Int
hypre_BoomerAMGCorrectCFMarker2(HYPRE_Int *CF_marker, HYPRE_Int num_var, HYPRE_Int *new_CF_marker)
{
HYPRE_Int i, cnt;
cnt = 0;
for (i=0; i < num_var; i++)
{
if (CF_marker[i] > 0 )
{
if (new_CF_marker[cnt] == -1) CF_marker[i] = -2;
else CF_marker[i] = 1;
cnt++;
}
}
return 0;
}
|
gen.h | #pragma once
#include "GraphHPC/defs.h"
#include <cinttypes>
#include <utility>
#include <iostream>
#define E(x) { std::cerr << #x << " = " << (x) << " "; }
#define Eo(x) { std::cerr << #x << " = " << (x) << std::endl; }
#define EO(x) Eo(x)
typedef int32_t vid_t;
typedef int64_t eid_t;
typedef double weight_t;
typedef uint64_t thread_vector_t;
typedef std::pair<eid_t, int> pei;
typedef std::pair<eid_t, vid_t> pev;
typedef std::pair<vid_t, int> pvi;
typedef std::pair<vid_t, vid_t> pvv;
typedef std::pair<weight_t, vid_t> pwv;
struct Edge {
vid_t dest;
int origOffset;
weight_t weight;
};
struct EdgeDestCmp { bool operator()(const Edge& a, const Edge& b) const; };
struct EdgeWeightCmp { bool operator()(const Edge& a, const Edge& b) const; }; // TODO inline
const int kMaxThreads = 20;
const int kMaxIterations = 30;
extern vid_t vertexCount;
extern eid_t edgesCount;
extern eid_t *edgesIds;
extern Edge *edges;
extern int threadsCount;
extern int iterationNumber;
extern vid_t *graphEdgesTo;
extern weight_t *graphEdgesWeight;
//extern bool *componentEnd;
extern bool *isCoolEdge;
extern const weight_t MAX_WEIGHT;
void initGraphArrays();
void readAll(char *filename);
void convertAll(graph_t *G);
extern vid_t *rev; // original ordering, required to restore answer
extern vid_t *que; // original ordering, required to restore answer
//eid_t *origEdgeIds; // original data
void doReorderBfs();
void doReorderSimple();
static void doReorder() {
#if defined(USE_REORDER_BFS)
doReorderBfs();
#elif defined(USE_REORDER_SIMPLE)
doReorderSimple();
#else
Eo("no reorder");
rev = new vid_t[vertexCount];
que = new vid_t[vertexCount];
#pragma omp parallel for
for (vid_t i = 0; i < vertexCount; ++i) rev[i] = que[i] = i;
#endif
}
inline eid_t vertexDegree(vid_t v) {
return edgesIds[v + 1] - edgesIds[v];
}
template<typename T>
inline T bit(int shift) {
return T(1) << shift;
}
int64_t currentNanoTime();
int stickThisThreadToCore(int coreId);
struct RDTSC {
double timers[1024][64]; // ToDo fix array location on NUMA
double oneSecond;
RDTSC();
double get();
void start(int timerId);
double end(int timerId);
};
extern RDTSC rdtsc;
|
GB_binop__land_uint32.c |
//------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2022, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCUDA_DEV
#include "GB_emult.h"
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB (_AaddB__land_uint32)
// A.*B function (eWiseMult): GB (_AemultB_08__land_uint32)
// A.*B function (eWiseMult): GB (_AemultB_02__land_uint32)
// A.*B function (eWiseMult): GB (_AemultB_04__land_uint32)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__land_uint32)
// A*D function (colscale): GB (_AxD__land_uint32)
// D*A function (rowscale): GB (_DxB__land_uint32)
// C+=B function (dense accum): GB (_Cdense_accumB__land_uint32)
// C+=b function (dense accum): GB (_Cdense_accumb__land_uint32)
// C+=A+B function (dense ewise3): GB ((none))
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__land_uint32)
// C=scalar+B GB (_bind1st__land_uint32)
// C=scalar+B' GB (_bind1st_tran__land_uint32)
// C=A+scalar GB (_bind2nd__land_uint32)
// C=A'+scalar GB (_bind2nd_tran__land_uint32)
// C type: uint32_t
// A type: uint32_t
// A pattern? 0
// B type: uint32_t
// B pattern? 0
// BinaryOp: cij = ((aij != 0) && (bij != 0))
#define GB_ATYPE \
uint32_t
#define GB_BTYPE \
uint32_t
#define GB_CTYPE \
uint32_t
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
1
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
1
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA,A_iso) \
uint32_t aij = GBX (Ax, pA, A_iso)
// true if values of A are not used
#define GB_A_IS_PATTERN \
0 \
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB,B_iso) \
uint32_t bij = GBX (Bx, pB, B_iso)
// true if values of B are not used
#define GB_B_IS_PATTERN \
0 \
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
uint32_t t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA,A_iso) \
cij = GBX (Ax, pA, A_iso)
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB,B_iso) \
cij = GBX (Bx, pB, B_iso)
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z,x,y,i,j) \
z = ((x != 0) && (y != 0)) ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
0
// op is second
#define GB_OP_IS_SECOND \
0
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_LAND || GxB_NO_UINT32 || GxB_NO_LAND_UINT32)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
#if 0
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
#endif
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
void GB (_Cdense_ewise3_noaccum__land_uint32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_noaccum_template.c"
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumB__land_uint32)
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *B_ek_slicing, const int B_ntasks, const int B_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
#include "GB_dense_subassign_23_template.c"
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumb__land_uint32)
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
// get the scalar b for C += b, of type uint32_t
uint32_t bwork = (*((uint32_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_AxD__land_uint32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix D,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint32_t *restrict Cx = (uint32_t *) C->x ;
#include "GB_AxB_colscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_DxB__land_uint32)
(
GrB_Matrix C,
const GrB_Matrix D,
const GrB_Matrix B,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint32_t *restrict Cx = (uint32_t *) C->x ;
#include "GB_AxB_rowscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C=A+B, C<M>=A+B, C<!M>=A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__land_uint32)
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool is_eWiseUnion,
const GB_void *alpha_scalar_in,
const GB_void *beta_scalar_in,
const bool Ch_is_Mh,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GB_WERK_DECLARE (M_ek_slicing, int64_t) ;
GB_WERK_DECLARE (A_ek_slicing, int64_t) ;
GB_WERK_DECLARE (B_ek_slicing, int64_t) ;
uint32_t alpha_scalar ;
uint32_t beta_scalar ;
if (is_eWiseUnion)
{
alpha_scalar = (*((uint32_t *) alpha_scalar_in)) ;
beta_scalar = (*((uint32_t *) beta_scalar_in )) ;
}
#include "GB_add_template.c"
GB_FREE_WORKSPACE ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, or C<M!>=A.*B where C is sparse/hyper
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_08__land_uint32)
(
GrB_Matrix C,
const int C_sparsity,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_08_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<#> = A.*B when A is sparse/hyper and B is bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_02__land_uint32)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool flipxy,
const int64_t *restrict Cp_kfirst,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if GB_BINOP_FLIP
// The operator is not commutative, and does not have a flipped
// variant. For example z=atan2(y,x).
if (flipxy)
{
// use fmult(y,x)
#undef GB_FLIPPED
#define GB_FLIPPED 1
#include "GB_emult_02_template.c"
}
else
{
// use fmult(x,y)
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
}
#else
// No need to handle the flip: the operator is either commutative, or
// has been handled by changing z=div(y,x) to z=rdiv(x,y) for example.
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<M> = A.*B, M sparse/hyper, A and B bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_04__land_uint32)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict Cp_kfirst,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_04_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, C<!M>=A.*B where C is bitmap
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_bitmap__land_uint32)
(
GrB_Matrix C,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_bitmap_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB (_bind1st__land_uint32)
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *restrict Bb,
int64_t bnz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint32_t *Cx = (uint32_t *) Cx_output ;
uint32_t x = (*((uint32_t *) x_input)) ;
uint32_t *Bx = (uint32_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < bnz ; p++)
{
if (!GBB (Bb, p)) continue ;
uint32_t bij = GBX (Bx, p, false) ;
Cx [p] = ((x != 0) && (bij != 0)) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__land_uint32)
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *restrict Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
uint32_t *Cx = (uint32_t *) Cx_output ;
uint32_t *Ax = (uint32_t *) Ax_input ;
uint32_t y = (*((uint32_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
uint32_t aij = GBX (Ax, p, false) ;
Cx [p] = ((aij != 0) && (y != 0)) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
uint32_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = ((x != 0) && (aij != 0)) ; \
}
GrB_Info GB (_bind1st_tran__land_uint32)
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
uint32_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint32_t x = (*((const uint32_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
uint32_t
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
uint32_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = ((aij != 0) && (y != 0)) ; \
}
GrB_Info GB (_bind2nd_tran__land_uint32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint32_t y = (*((const uint32_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
GB_binop__lt_int8.c |
//------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_emult.h"
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB (_AaddB__lt_int8)
// A.*B function (eWiseMult): GB (_AemultB_08__lt_int8)
// A.*B function (eWiseMult): GB (_AemultB_02__lt_int8)
// A.*B function (eWiseMult): GB (_AemultB_04__lt_int8)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__lt_int8)
// A*D function (colscale): GB (_AxD__lt_int8)
// D*A function (rowscale): GB (_DxB__lt_int8)
// C+=B function (dense accum): GB (_Cdense_accumB__lt_int8)
// C+=b function (dense accum): GB (_Cdense_accumb__lt_int8)
// C+=A+B function (dense ewise3): GB ((none))
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__lt_int8)
// C=scalar+B GB (_bind1st__lt_int8)
// C=scalar+B' GB (_bind1st_tran__lt_int8)
// C=A+scalar GB (_bind2nd__lt_int8)
// C=A'+scalar GB (_bind2nd_tran__lt_int8)
// C type: bool
// A type: int8_t
// A pattern? 0
// B type: int8_t
// B pattern? 0
// BinaryOp: cij = (aij < bij)
#define GB_ATYPE \
int8_t
#define GB_BTYPE \
int8_t
#define GB_CTYPE \
bool
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
0
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
0
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA,A_iso) \
int8_t aij = GBX (Ax, pA, A_iso)
// true if values of A are not used
#define GB_A_IS_PATTERN \
0 \
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB,B_iso) \
int8_t bij = GBX (Bx, pB, B_iso)
// true if values of B are not used
#define GB_B_IS_PATTERN \
0 \
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
bool t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA,A_iso) \
cij = GBX (Ax, pA, A_iso)
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB,B_iso) \
cij = GBX (Bx, pB, B_iso)
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z,x,y,i,j) \
z = (x < y) ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
0
// op is second
#define GB_OP_IS_SECOND \
0
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_LT || GxB_NO_INT8 || GxB_NO_LT_INT8)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
#if 0
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
#endif
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
void GB (_Cdense_ewise3_noaccum__lt_int8)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_noaccum_template.c"
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumB__lt_int8)
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *B_ek_slicing, const int B_ntasks, const int B_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if 0
{
#include "GB_dense_subassign_23_template.c"
}
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumb__lt_int8)
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if 0
{
// get the scalar b for C += b, of type int8_t
int8_t bwork = (*((int8_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_AxD__lt_int8)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix D,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *restrict Cx = (bool *) C->x ;
#include "GB_AxB_colscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_DxB__lt_int8)
(
GrB_Matrix C,
const GrB_Matrix D,
const GrB_Matrix B,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *restrict Cx = (bool *) C->x ;
#include "GB_AxB_rowscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C=A+B, C<M>=A+B, C<!M>=A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__lt_int8)
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool is_eWiseUnion,
const GB_void *alpha_scalar_in,
const GB_void *beta_scalar_in,
const bool Ch_is_Mh,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GB_WERK_DECLARE (M_ek_slicing, int64_t) ;
GB_WERK_DECLARE (A_ek_slicing, int64_t) ;
GB_WERK_DECLARE (B_ek_slicing, int64_t) ;
int8_t alpha_scalar ;
int8_t beta_scalar ;
if (is_eWiseUnion)
{
alpha_scalar = (*((int8_t *) alpha_scalar_in)) ;
beta_scalar = (*((int8_t *) beta_scalar_in )) ;
}
#include "GB_add_template.c"
GB_FREE_WORKSPACE ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, or C<M!>=A.*B where C is sparse/hyper
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_08__lt_int8)
(
GrB_Matrix C,
const int C_sparsity,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_08_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<#> = A.*B when A is sparse/hyper and B is bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_02__lt_int8)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool flipxy,
const int64_t *restrict Cp_kfirst,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if GB_BINOP_FLIP
// The operator is not commutative, and does not have a flipped
// variant. For example z=atan2(y,x).
if (flipxy)
{
// use fmult(y,x)
#undef GB_FLIPPED
#define GB_FLIPPED 1
#include "GB_emult_02_template.c"
}
else
{
// use fmult(x,y)
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
}
#else
// No need to handle the flip: the operator is either commutative, or
// has been handled by changing z=div(y,x) to z=rdiv(x,y) for example.
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<M> = A.*B, M sparse/hyper, A and B bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_04__lt_int8)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict Cp_kfirst,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_04_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, C<!M>=A.*B where C is bitmap
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_bitmap__lt_int8)
(
GrB_Matrix C,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_bitmap_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB (_bind1st__lt_int8)
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *restrict Bb,
int64_t bnz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *Cx = (bool *) Cx_output ;
int8_t x = (*((int8_t *) x_input)) ;
int8_t *Bx = (int8_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < bnz ; p++)
{
if (!GBB (Bb, p)) continue ;
int8_t bij = GBX (Bx, p, false) ;
Cx [p] = (x < bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__lt_int8)
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *restrict Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
bool *Cx = (bool *) Cx_output ;
int8_t *Ax = (int8_t *) Ax_input ;
int8_t y = (*((int8_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
int8_t aij = GBX (Ax, p, false) ;
Cx [p] = (aij < y) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
int8_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = (x < aij) ; \
}
GrB_Info GB (_bind1st_tran__lt_int8)
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
int8_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int8_t x = (*((const int8_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
int8_t
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
int8_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = (aij < y) ; \
}
GrB_Info GB (_bind2nd_tran__lt_int8)
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int8_t y = (*((const int8_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
GB_unaryop__ainv_int64_int32.c | //------------------------------------------------------------------------------
// GB_unaryop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2019, All Rights Reserved.
// http://suitesparse.com See GraphBLAS/Doc/License.txt for license.
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_iterator.h"
#include "GB_unaryop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB_unop__ainv_int64_int32
// op(A') function: GB_tran__ainv_int64_int32
// C type: int64_t
// A type: int32_t
// cast: int64_t cij = (int64_t) aij
// unaryop: cij = -aij
#define GB_ATYPE \
int32_t
#define GB_CTYPE \
int64_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
int32_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = -x ;
// casting
#define GB_CASTING(z, x) \
int64_t z = (int64_t) x ;
// cij = op (cast (aij))
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GB_GETA (aij, Ax, pA) ; \
/* Cx [pC] = op (cast (aij)) */ \
GB_CASTING (x, aij) ; \
GB_OP (GB_CX (pC), x) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_AINV || GxB_NO_INT64 || GxB_NO_INT32)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__ainv_int64_int32
(
int64_t *restrict Cx,
const int32_t *restrict Ax,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (int64_t p = 0 ; p < anz ; p++)
{
GB_CAST_OP (p, p) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_tran__ainv_int64_int32
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *restrict *Rowcounts,
GBI_single_iterator Iter,
const int64_t *restrict A_slice,
int naslice
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#define GB_PHASE_2_OF_2
#include "GB_unaryop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
zposv.c | /**
*
* @file
*
* PLASMA is a software package provided by:
* University of Tennessee, US,
* University of Manchester, UK.
*
* @precisions normal z -> s d c
*
**/
#include "plasma.h"
#include "plasma_async.h"
#include "plasma_context.h"
#include "plasma_descriptor.h"
#include "plasma_internal.h"
#include "plasma_tuning.h"
#include "plasma_types.h"
#include "plasma_workspace.h"
/***************************************************************************//**
*
* @ingroup plasma_posv
*
* Computes the solution to a system of linear equations A * X = B,
* where A is an n-by-n Hermitian positive definite matrix and X and B are
* n-by-nrhs matrices. The Cholesky decomposition is used to factor A as
*
* \f[ A = L\times L^H, \f] if uplo = PlasmaLower,
* or
* \f[ A = U^H\times U, \f] if uplo = PlasmaUpper,
*
* where U is an upper triangular matrix and L is a lower triangular matrix.
* The factored form of A is then used to solve the system of equations:
*
* A * X = B.
*
*******************************************************************************
*
* @param[in] uplo
* - PlasmaUpper: Upper triangle of A is stored;
* - PlasmaLower: Lower triangle of A is stored.
*
* @param[in] n
* The number of linear equations, i.e., the order of the matrix A.
* n >= 0.
*
* @param[in] nrhs
* The number of right hand sides, i.e., the number of columns
* of the matrix B. nrhs >= 0.
*
* @param[in,out] pA
* On entry, the Hermitian positive definite matrix A.
* If uplo = PlasmaUpper, the leading n-by-n upper triangular part of A
* contains the upper triangular part of the matrix A, and the strictly
* lower triangular part of A is not referenced.
* If UPLO = 'L', the leading n-by-n lower triangular part of A
* contains the lower triangular part of the matrix A, and the strictly
* upper triangular part of A is not referenced.
* On exit, if return value = 0, the factor U or L from
* the Cholesky factorization A = U^H*U or A = L*L^H.
*
* @param[in] lda
* The leading dimension of the array A. lda >= max(1,n).
*
* @param[in,out] pB
* On entry, the n-by-nrhs right hand side matrix B.
* On exit, if return value = 0, the n-by-nrhs solution matrix X.
*
* @param[in] ldb
* The leading dimension of the array B. ldb >= max(1,n).
*
*******************************************************************************
*
* @retval PlasmaSuccess successful exit
* @retval < 0 if -i, the i-th argument had an illegal value
* @retval > 0 if i, the leading minor of order i of A is not
* positive definite, so the factorization could not
* be completed, and the solution has not been computed.
*
*******************************************************************************
*
* @sa plasma_omp_zposv
* @sa plasma_cposv
* @sa plasma_dposv
* @sa plasma_sposv
*
******************************************************************************/
int plasma_zposv(plasma_enum_t uplo,
int n, int nrhs,
plasma_complex64_t *pA, int lda,
plasma_complex64_t *pB, int ldb)
{
// Get PLASMA context.
plasma_context_t *plasma = plasma_context_self();
if (plasma == NULL) {
plasma_error("PLASMA not initialized");
return PlasmaErrorNotInitialized;
}
// Check input arguments.
if ((uplo != PlasmaUpper) &&
(uplo != PlasmaLower)) {
plasma_error("illegal value of uplo");
return -1;
}
if (n < 0) {
plasma_error("illegal value of n");
return -2;
}
if (nrhs < 0) {
plasma_error("illegal value of nrhs");
return -3;
}
if (lda < imax(1, n)) {
plasma_error("illegal value of lda");
return -5;
}
if (ldb < imax(1, n)) {
plasma_error("illegal value of ldb");
return -7;
}
// quick return
if (imin(n, nrhs) == 0)
return PlasmaSuccess;
// Tune parameters.
if (plasma->tuning)
plasma_tune_potrf(plasma, PlasmaComplexDouble, n);
// Set tiling parameters.
int nb = plasma->nb;
// Create tile matrices.
plasma_desc_t A;
plasma_desc_t B;
int retval;
retval = plasma_desc_triangular_create(PlasmaComplexDouble, uplo, nb, nb,
n, n, 0, 0, n, n, &A);
if (retval != PlasmaSuccess) {
plasma_error("plasma_desc_general_create() failed");
return retval;
}
retval = plasma_desc_general_create(PlasmaComplexDouble, nb, nb,
n, nrhs, 0, 0, n, nrhs, &B);
if (retval != PlasmaSuccess) {
plasma_error("plasma_desc_general_create() failed");
plasma_desc_destroy(&A);
return retval;
}
// Initialize sequence.
plasma_sequence_t sequence;
retval = plasma_sequence_init(&sequence);
// Initialize request.
plasma_request_t request;
retval = plasma_request_init(&request);
// asynchronous block
#pragma omp parallel
#pragma omp master
{
// Translate to tile layout.
plasma_omp_ztr2desc(pA, lda, A, &sequence, &request);
plasma_omp_zge2desc(pB, ldb, B, &sequence, &request);
// Call the tile async function.
plasma_omp_zposv(uplo, A, B, &sequence, &request);
// Translate back to LAPACK layout.
plasma_omp_zdesc2tr(A, pA, lda, &sequence, &request);
plasma_omp_zdesc2ge(B, pB, ldb, &sequence, &request);
}
// implicit synchronization
// Free matrices in tile layout.
plasma_desc_destroy(&A);
plasma_desc_destroy(&B);
// Return status.
int status = sequence.status;
return status;
}
/***************************************************************************//**
*
* @ingroup plasma_posv
*
* Solves a Hermitian positive definite system of linear equations
* using Cholesky factorization.
* Non-blocking tile version of plasma_zposv().
* Operates on matrices stored by tiles.
* All matrices are passed through descriptors.
* All dimensions are taken from the descriptors.
* Allows for pipelining of operations at runtime.
*
*******************************************************************************
*
* @param[in] uplo
* - PlasmaUpper: Upper triangle of A is stored;
* - PlasmaLower: Lower triangle of A is stored.
*
* @param[in,out] A
* On entry, the Hermitian positive definite matrix A.
* If uplo = PlasmaUpper, the leading n-by-n upper triangular part of A
* contains the upper triangular part of the matrix A, and the strictly
* lower triangular part of A is not referenced.
* If UPLO = 'L', the leading n-by-n lower triangular part of A
* contains the lower triangular part of the matrix A, and the strictly
* upper triangular part of A is not referenced.
* On exit, if return value = 0, the factor U or L from
* the Cholesky factorization A = U^H*U or A = L*L^H.
*
* @param[in,out] B
* On entry, the n-by-nrhs right hand side matrix B.
* On exit, if return value = 0, the n-by-nrhs solution matrix X.
*
* @param[in] sequence
* Identifies the sequence of function calls that this call belongs to
* (for completion checks and exception handling purposes). Check
* the sequence->status for errors.
* @param[out] request
* Identifies this function call (for exception handling purposes).
*
* @retval void
* Errors are returned by setting sequence->status and
* request->status to error values. The sequence->status and
* request->status should never be set to PlasmaSuccess (the
* initial values) since another async call may be setting a
* failure value at the same time.
*
*******************************************************************************
*
* @sa plasma_zposv
* @sa plasma_omp_cposv
* @sa plasma_omp_dposv
* @sa plasma_omp_sposv
*
******************************************************************************/
void plasma_omp_zposv(plasma_enum_t uplo, plasma_desc_t A, plasma_desc_t B,
plasma_sequence_t *sequence, plasma_request_t *request)
{
// Get PLASMA context.
plasma_context_t *plasma = plasma_context_self();
if (plasma == NULL) {
plasma_error("PLASMA not initialized");
plasma_request_fail(sequence, request, PlasmaErrorIllegalValue);
return;
}
// Check input arguments.
if ((uplo != PlasmaUpper) &&
(uplo != PlasmaLower)) {
plasma_error("illegal value of uplo");
return;
}
if (plasma_desc_check(A) != PlasmaSuccess) {
plasma_request_fail(sequence, request, PlasmaErrorIllegalValue);
plasma_error("invalid A");
return;
}
if (plasma_desc_check(B) != PlasmaSuccess) {
plasma_error("invalid B");
plasma_request_fail(sequence, request, PlasmaErrorIllegalValue);
return;
}
if (sequence == NULL) {
plasma_error("NULL sequence");
plasma_request_fail(sequence, request, PlasmaErrorIllegalValue);
return;
}
if (request == NULL) {
plasma_error("NULL request");
plasma_request_fail(sequence, request, PlasmaErrorIllegalValue);
return;
}
// quick return
if (A.n == 0 || B.n == 0)
return;
// Call the parallel functions.
plasma_pzpotrf(uplo, A, sequence, request);
plasma_enum_t trans;
trans = uplo == PlasmaUpper ? PlasmaConjTrans : PlasmaNoTrans;
plasma_pztrsm(PlasmaLeft, uplo, trans, PlasmaNonUnit,
1.0, A,
B,
sequence, request);
trans = uplo == PlasmaUpper ? PlasmaNoTrans : PlasmaConjTrans;
plasma_pztrsm(PlasmaLeft, uplo, trans, PlasmaNonUnit,
1.0, A,
B,
sequence, request);
}
|
evaluation.h | #include <omp.h>
#include <fstream>
#include <iostream>
#include <string>
#include <cstdlib>
#include <cstdio>
#include <algorithm>
#include <cmath>
#include <numeric>
#include <vector>
#include <map>
#include <sys/types.h>
#include <sys/stat.h>
#include <math.h>
#include <limits.h>
#include <bitset>
#include <stdio.h>
#include <stdlib.h>
#include <stdint.h>
#include <unistd.h>
#include <ctype.h>
#include <sstream>
#include <set>
#include <memory>
#include <typeinfo>
#include <set>
#include <iomanip>
#include "def.h"
#ifndef DEBUG
#define DEBUG
#endif
void estimateOverlap(int begV, int endV, int lenV, int begH, int endH, int lenH, int& overlap) {
overlap = min(begV, begH) + min(lenV - endV, lenH - endH) + ((endV - begV) + (endH - begH)) / 2;
}
// from mecat index file to a std::map<uint32_t, std::string>
void tomap(std::ifstream& idx2read, std::map<std::string, std::string>& namestable)
{
std::string num, name, seq, idx;
if(idx2read.is_open()) {
std::string line;
while(getline(idx2read, line)) {
std::stringstream lineStream(line);
getline(lineStream, num, ' ');
getline(lineStream, name, ' ');
getline(idx2read, seq);
idx = num;
name.erase(0, 1); // remove first char '>'
namestable.insert(std::make_pair(idx, name));
}
}
else exit(1);
}
// from mecat numeric id to read name
std::string toread(std::string& idx, std::map<std::string, std::string>& namestable)
{
std::string name;
auto it = namestable.find(idx);
if(it != namestable.end()) return namestable[idx];
else exit(1);
}
std::set<entry, classcom> readTruthOutput(std::ifstream& file, int minOverlap, bool isSimulated)
{
int maxt = 1;
#pragma omp parallel
{
maxt = omp_get_num_threads();
}
int nOverlap = std::count(std::istreambuf_iterator<char>(file), std::istreambuf_iterator<char>(), '\n');
file.seekg(0,std::ios_base::beg);
std::vector<std::string> entries;
entries.reserve(nOverlap);
if(file)
for (int i = 0; i < nOverlap; ++i) {
std::string line;
std::getline(file, line);
entries.push_back(line);
}
file.close();
std::map<std::string, std::vector<overlap>> intermediate;
std::vector<std::map<std::string, std::vector<overlap>>> local(maxt);
#pragma omp parallel for
for(int i = 0; i < nOverlap; i++) {
int ithread = omp_get_thread_num();
std::vector<std::string> v = split(entries[i], ' ');
overlap ioverlap;
if(isSimulated) {
ioverlap.ref = v[0];
ioverlap.read = "@" + v[3];
ioverlap.start = stoi(v[1]);
ioverlap.end = stoi(v[2]);
} else {
ioverlap.ref = v[0];
ioverlap.read = "@" + v[1];
ioverlap.start = stoi(v[2]);
ioverlap.end = stoi(v[3]);
}
auto it = local[ithread].find(ioverlap.ref);
if(it == local[ithread].end()) {
std::vector<overlap> tmp;
tmp.push_back(ioverlap);
local[ithread].insert(std::map<std::string, std::vector<overlap>>::value_type(ioverlap.ref, tmp));
}
else {
it->second.push_back(ioverlap);
local[ithread][ioverlap.ref] = it->second;
}
}
for(int i = 0; i < maxt; ++i)
{
intermediate = std::accumulate(local[i].begin(), local[i].end(), intermediate,
[](std::map<std::string, std::vector<overlap>>& m,
const std::pair<std::string, std::vector<overlap>>& v)
{
m[v.first].insert(m[v.first].end(), v.second.begin(), v.second.end());
return m;
});
}
vector<Interval<std::string>> intervals;
vector<Interval<std::string>> queries;
std::set<entry, classcom> Gset;
for(auto key = intermediate.begin(); key != intermediate.end(); ++key) {
for(auto it = key->second.begin(); it != key->second.end(); ++it)
{
intervals.push_back(Interval<std::string>(it->start, it->end, it->read));
queries.push_back(Interval<std::string>(it->start, it->end, it->read));
}
IntervalTree<string> tree;
tree = IntervalTree<std::string>(intervals);
for (auto q = queries.begin(); q != queries.end(); ++q) {
vector<Interval<std::string>> results;
tree.findOverlapping(q->start, q->stop, q->value, results, minOverlap, Gset);
}
intervals.clear();
queries.clear();
}
#ifdef DEBUG
// in sam format all mapped segments in alignment lines are represented on the forward genomic strand
std::cout << std::endl;
std::cout << Gset.size() << " overlaps in the ground truth longer than " << minOverlap << " bp"<< std::endl;
std::cout << std::endl;
#endif
return Gset;
};
std::set<entry, classcom> readBellaOutput(std::ifstream& file, int minOverlap, bool alignment)
{
int maxt = 1;
#pragma omp parallel
{
maxt = omp_get_num_threads();
}
int nOverlap = std::count(std::istreambuf_iterator<char>(file), std::istreambuf_iterator<char>(), '\n');
file.seekg(0,std::ios_base::beg);
std::vector<std::string> entries;
if(file)
for (int i = 0; i < nOverlap; ++i) {
std::string line;
std::getline(file, line);
entries.push_back(line);
}
file.close();
std::set<entry, classcom> result;
std::vector<std::set<entry, classcom>> local(maxt);
#pragma omp parallel for
for(int i = 0; i < nOverlap; i++) {
int ithread = omp_get_thread_num();
std::vector<std::string> v = split(entries[i], '\t');
entry ientry;
// std::cout << "What's up, dude?" << std::endl;
ientry.a = "@" + v[0];
ientry.b = "@" + v[1];
if(ientry.a != ientry.b) {
ientry.overlap = stoi(v[4]);
if(alignment) {
if(ientry.overlap >= minOverlap)
local[ithread].insert(ientry);
}
else {
local[ithread].insert(ientry);
}
}
}
for(int i = 0; i < maxt; ++i)
result.insert(local[i].begin(), local[i].end());
#ifdef DEBUG
std::cout << "Bella identified " << 2*result.size() << " overlaps" << std::endl;
#endif
return result;
};
std::set<entry, classcom> readMinimapOutput(std::ifstream& file, int minOverlap, bool alignment)
{
int maxt = 1;
#pragma omp parallel
{
maxt = omp_get_num_threads();
}
int nOverlap = std::count(std::istreambuf_iterator<char>(file), std::istreambuf_iterator<char>(), '\n');
file.seekg(0,std::ios_base::beg);
std::vector<std::string> entries;
if(file)
for (int i = 0; i < nOverlap; ++i) {
std::string line;
std::getline(file, line);
entries.push_back(line);
}
file.close();
std::set<entry, classcom> result;
std::vector<std::set<entry, classcom>> local(maxt);
#pragma omp parallel for
for(int i = 0; i < nOverlap; i++) {
int ithread = omp_get_thread_num();
std::vector<std::string> v = split(entries[i], '\t');
entry ientry;
// std::cout << "What's up, dude?" << std::endl;
ientry.a = "@" + v[0];
ientry.b = "@" + v[5];
if(ientry.a != ientry.b) {
// paf format
int lenV = std::stoi(v[1]);
int begV = std::stoi(v[2]);
int endV = std::stoi(v[3]);
int lenH = std::stoi(v[6]);
int begH = std::stoi(v[7]);
int endH = std::stoi(v[8]);
// coordinate are reported on the original strand in paf format
if(v[4] == "-") {
int tmp = begH;
begH = lenH - endH;
endH = lenH - tmp;
}
// (int begV, int endV, int lenV, int begH, int endH, int lenH, int overlap)
estimateOverlap(begV, endV, lenV,
begH, endH, lenH, ientry.overlap);
if(alignment) {
if(ientry.overlap >= minOverlap)
local[ithread].insert(ientry);
}
else {
local[ithread].insert(ientry);
}
}
}
for(int i = 0; i < maxt; ++i)
result.insert(local[i].begin(), local[i].end());
#ifdef DEBUG
std::cout << "Minimap2 identified " << 2*result.size() << " overlaps" << std::endl;
#endif
return result;
};
std::set<entry, classcom> readMecatOutput(std::ifstream& file, std::ifstream& index, int minOverlap, bool alignment)
{
std::map<std::string, std::string> namestable;
tomap(index, namestable);
int maxt = 1;
#pragma omp parallel
{
maxt = omp_get_num_threads();
}
int nOverlap = std::count(std::istreambuf_iterator<char>(file), std::istreambuf_iterator<char>(), '\n');
file.seekg(0,std::ios_base::beg);
std::vector<std::string> entries;
if(file)
for (int i = 0; i < nOverlap; ++i) {
std::string line;
std::getline(file, line);
entries.push_back(line);
}
file.close();
std::set<entry, classcom> result;
std::vector<std::set<entry, classcom>> local(maxt);
#pragma omp parallel for
for(int i = 0; i < nOverlap; i++) {
int ithread = omp_get_thread_num();
std::vector<std::string> v = split(entries[i], '\t');
entry ientry;
// std::cout << "What's up, dude?" << std::endl;
ientry.a = "@" + toread(v[0], namestable);
ientry.b = "@" + toread(v[1], namestable);
if(ientry.a != ientry.b) {
// mecat format
int begV = std::stoi(v[5]);
int endV = std::stoi(v[6]);
int lenV = std::stoi(v[7]);
int begH = std::stoi(v[9]);
int endH = std::stoi(v[10]);
int lenH = std::stoi(v[11]);
// the positions are zero-based and are based on the forward strand, whatever which strand the sequence is mapped
// (int begV, int endV, int lenV, int begH, int endH, int lenH, int overlap)
estimateOverlap(begV, endV, lenV,
begH, endH, lenH, ientry.overlap);
if(alignment) {
if(ientry.overlap >= minOverlap)
local[ithread].insert(ientry);
}
else {
local[ithread].insert(ientry);
}
}
}
for(int i = 0; i < maxt; ++i)
result.insert(local[i].begin(), local[i].end());
#ifdef DEBUG
std::cout << "Mecat identified " << 2*result.size() << " overlaps" << std::endl;
#endif
return result;
};
std::set<entry, classcom> readMhapOutput(std::ifstream& file, int minOverlap, bool alignment)
{
int maxt = 1;
#pragma omp parallel
{
maxt = omp_get_num_threads();
}
int nOverlap = std::count(std::istreambuf_iterator<char>(file), std::istreambuf_iterator<char>(), '\n');
file.seekg(0,std::ios_base::beg);
std::vector<std::string> entries;
if(file)
for (int i = 0; i < nOverlap; ++i) {
std::string line;
std::getline(file, line);
entries.push_back(line);
}
file.close();
std::set<entry, classcom> result;
std::vector<std::set<entry, classcom>> local(maxt);
#pragma omp parallel for
for(int i = 0; i < nOverlap; i++) {
int ithread = omp_get_thread_num();
std::vector<std::string> v = split(entries[i], ' ');
entry ientry;
ientry.a = "@" + v[0];
ientry.b = "@" + v[1];
// 0 1 2 3 4 5 6 7 8 9 10 11
// [A ID] [B ID] [% error] [# shared min-mers] [0=A fwd, 1=A rc] [A start] [A end] [A length] [0=B fwd, 1=B rc] [B start] [B end] [B length]
if(ientry.a != ientry.b) {
// mhap m4 format
int begV = std::stoi(v[5]);
int endV = std::stoi(v[6]);
int lenV = std::stoi(v[7]);
int begH = std::stoi(v[9]);
int endH = std::stoi(v[10]);
int lenH = std::stoi(v[11]);
// (int begV, int endV, int lenV, int begH, int endH, int lenH, int overlap)
estimateOverlap(begV, endV, lenV,
begH, endH, lenH, ientry.overlap);
if(alignment) {
if(ientry.overlap >= minOverlap)
local[ithread].insert(ientry);
}
else {
local[ithread].insert(ientry);
}
}
}
for(int i = 0; i < maxt; ++i)
result.insert(local[i].begin(), local[i].end());
#ifdef DEBUG
std::cout << "Mhap identified " << result.size() << " overlaps" << std::endl;
#endif
return result;
};
std::set<entry, classcom> readBlasrOutput(std::ifstream& file, int minOverlap, bool alignment)
{
int maxt = 1;
#pragma omp parallel
{
maxt = omp_get_num_threads();
}
int nOverlap = std::count(std::istreambuf_iterator<char>(file), std::istreambuf_iterator<char>(), '\n');
file.seekg(0,std::ios_base::beg);
std::vector<std::string> entries;
if(file)
for (int i = 0; i < nOverlap; ++i) {
std::string line;
std::getline(file, line);
entries.push_back(line);
}
file.close();
std::set<entry, classcom> result;
std::vector<std::set<entry, classcom>> local(maxt);
#pragma omp parallel for
for(int i = 0; i < nOverlap; i++) {
int ithread = omp_get_thread_num();
std::vector<std::string> v = split(entries[i], ' ');
entry ientry;
// std::cout << "What's up, dude?" << std::endl;
ientry.a = "@" + v[0];
ientry.b = "@" + v[1];
if(ientry.a != ientry.b) {
// blasr 4m format
int begV = std::stoi(v[5]);
int endV = std::stoi(v[6]);
int lenV = std::stoi(v[7]);
int begH = std::stoi(v[9]);
int endH = std::stoi(v[10]);
int lenH = std::stoi(v[11]);
// figure out write to adam/sergey?
//if(v[8] == "1") {
// int tmp = begH;
// begH = lenH - endH;
// endH = lenH - tmp;
//}
// (int begV, int endV, int lenV, int begH, int endH, int lenH, int overlap)
estimateOverlap(begV, endV, lenV,
begH, endH, lenH, ientry.overlap);
if(alignment) {
if(ientry.overlap >= minOverlap)
local[ithread].insert(ientry);
}
else {
local[ithread].insert(ientry);
}
}
}
for(int i = 0; i < maxt; ++i)
result.insert(local[i].begin(), local[i].end());
#ifdef DEBUG
std::cout << "Blasr identified " << result.size() << " overlaps" << std::endl;
#endif
return result;
};
std::set<entry, classcom> readDalignerOutput(std::ifstream& file, int minOverlap, bool alignment)
{
int maxt = 1;
#pragma omp parallel
{
maxt = omp_get_num_threads();
}
int nOverlap = std::count(std::istreambuf_iterator<char>(file), std::istreambuf_iterator<char>(), '\n');
file.seekg(0,std::ios_base::beg);
std::vector<std::string> entries;
if(file)
for (int i = 0; i < nOverlap; ++i) {
std::string line;
std::getline(file, line);
entries.push_back(line);
}
file.close();
std::set<entry, classcom> result;
std::vector<std::set<entry, classcom>> local(maxt);
#pragma omp parallel for
for(int i = 0; i < nOverlap; i++) {
int ithread = omp_get_thread_num();
std::vector<std::string> v = split(entries[i], ' ');
entry ientry;
// std::cout << "What's up, dude?" << std::endl;
ientry.a = "@" + v[0];
ientry.b = "@" + v[1];
if(ientry.a != ientry.b) {
// daligner format according to our script
int begV = std::stoi(v[3]);
int endV = std::stoi(v[4]);
int lenV = std::stoi(v[5]);
int begH = std::stoi(v[6]);
int endH = std::stoi(v[7]);
int lenH = std::stoi(v[8]);
if(v[2] == "c") {
int tmp = begH;
begH = lenH - endH;
endH = lenH - tmp;
}
// (int begV, int endV, int lenV, int begH, int endH, int lenH, int overlap)
estimateOverlap(begV, endV, lenV,
begH, endH, lenH, ientry.overlap);
if(alignment) {
if(ientry.overlap >= minOverlap)
local[ithread].insert(ientry);
}
else {
local[ithread].insert(ientry);
}
}
}
for(int i = 0; i < maxt; ++i)
result.insert(local[i].begin(), local[i].end());
#ifdef DEBUG
std::cout << "Daligner identified " << result.size() << " overlaps" << std::endl;
#endif
return result;
};
void evaluate(std::set<entry, classcom>& Sset, const std::set<entry, classcom>& Gset,
int minOverlap, bool duplicate, bool alignment)
{
std::set<entry, classcom> Tset;
std::set_intersection(
Gset.begin(), Gset.end(),
Sset.begin(), Sset.end(),
std::inserter(Tset, Tset.end())
);
float RC;
if(duplicate)
{
#ifdef DEBUG
std::cout << "\t* " << 2*Sset.size() << " overlaps longer than " << minOverlap << " bp" << std::endl;
std::cout << "\t* " << 2*Tset.size() << " true positives" << std::endl;
#endif
RC = ((float)(2 * Tset.size()) / (float)Gset.size()) * 100;
}
else
{
#ifdef DEBUG
std::cout << "\t* " << Sset.size() << " overlaps longer than " << minOverlap << " bp" << std::endl;
std::cout << "\t* " << Tset.size() << " true positives" << std::endl;
#endif
RC = ((float)Tset.size() / (float)Gset.size()) * 100;
}
float PR = ((float)Tset.size() / (float)Sset.size()) * 100;
float F1 = (2 * RC * PR) / (RC + PR);
std::cout << std::setprecision(2) << std::fixed;
std::cout << "Recall\t\t" << RC << "%"<< std::endl;
std::cout << "Precision\t" << PR << "%"<< std::endl;
std::cout << "F1\t\t" << F1 << "%"<< std::endl;
std::cout << std::endl;
}
|
ASTMatchers.h | //===- ASTMatchers.h - Structural query framework ---------------*- C++ -*-===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
//
// This file implements matchers to be used together with the MatchFinder to
// match AST nodes.
//
// Matchers are created by generator functions, which can be combined in
// a functional in-language DSL to express queries over the C++ AST.
//
// For example, to match a class with a certain name, one would call:
// cxxRecordDecl(hasName("MyClass"))
// which returns a matcher that can be used to find all AST nodes that declare
// a class named 'MyClass'.
//
// For more complicated match expressions we're often interested in accessing
// multiple parts of the matched AST nodes once a match is found. In that case,
// call `.bind("name")` on match expressions that match the nodes you want to
// access.
//
// For example, when we're interested in child classes of a certain class, we
// would write:
// cxxRecordDecl(hasName("MyClass"), has(recordDecl().bind("child")))
// When the match is found via the MatchFinder, a user provided callback will
// be called with a BoundNodes instance that contains a mapping from the
// strings that we provided for the `.bind()` calls to the nodes that were
// matched.
// In the given example, each time our matcher finds a match we get a callback
// where "child" is bound to the RecordDecl node of the matching child
// class declaration.
//
// See ASTMatchersInternal.h for a more in-depth explanation of the
// implementation details of the matcher framework.
//
// See ASTMatchFinder.h for how to use the generated matchers to run over
// an AST.
//
//===----------------------------------------------------------------------===//
#ifndef LLVM_CLANG_ASTMATCHERS_ASTMATCHERS_H
#define LLVM_CLANG_ASTMATCHERS_ASTMATCHERS_H
#include "clang/AST/ASTContext.h"
#include "clang/AST/ASTTypeTraits.h"
#include "clang/AST/Attr.h"
#include "clang/AST/CXXInheritance.h"
#include "clang/AST/Decl.h"
#include "clang/AST/DeclCXX.h"
#include "clang/AST/DeclFriend.h"
#include "clang/AST/DeclObjC.h"
#include "clang/AST/DeclTemplate.h"
#include "clang/AST/Expr.h"
#include "clang/AST/ExprCXX.h"
#include "clang/AST/ExprObjC.h"
#include "clang/AST/LambdaCapture.h"
#include "clang/AST/NestedNameSpecifier.h"
#include "clang/AST/OpenMPClause.h"
#include "clang/AST/OperationKinds.h"
#include "clang/AST/ParentMapContext.h"
#include "clang/AST/Stmt.h"
#include "clang/AST/StmtCXX.h"
#include "clang/AST/StmtObjC.h"
#include "clang/AST/StmtOpenMP.h"
#include "clang/AST/TemplateBase.h"
#include "clang/AST/TemplateName.h"
#include "clang/AST/Type.h"
#include "clang/AST/TypeLoc.h"
#include "clang/ASTMatchers/ASTMatchersInternal.h"
#include "clang/ASTMatchers/ASTMatchersMacros.h"
#include "clang/Basic/AttrKinds.h"
#include "clang/Basic/ExceptionSpecificationType.h"
#include "clang/Basic/FileManager.h"
#include "clang/Basic/IdentifierTable.h"
#include "clang/Basic/LLVM.h"
#include "clang/Basic/SourceManager.h"
#include "clang/Basic/Specifiers.h"
#include "clang/Basic/TypeTraits.h"
#include "llvm/ADT/ArrayRef.h"
#include "llvm/ADT/SmallVector.h"
#include "llvm/ADT/StringRef.h"
#include "llvm/Support/Casting.h"
#include "llvm/Support/Compiler.h"
#include "llvm/Support/ErrorHandling.h"
#include "llvm/Support/Regex.h"
#include <cassert>
#include <cstddef>
#include <iterator>
#include <limits>
#include <string>
#include <utility>
#include <vector>
namespace clang {
namespace ast_matchers {
/// Maps string IDs to AST nodes matched by parts of a matcher.
///
/// The bound nodes are generated by calling \c bind("id") on the node matchers
/// of the nodes we want to access later.
///
/// The instances of BoundNodes are created by \c MatchFinder when the user's
/// callbacks are executed every time a match is found.
class BoundNodes {
public:
/// Returns the AST node bound to \c ID.
///
/// Returns NULL if there was no node bound to \c ID or if there is a node but
/// it cannot be converted to the specified type.
template <typename T>
const T *getNodeAs(StringRef ID) const {
return MyBoundNodes.getNodeAs<T>(ID);
}
/// Type of mapping from binding identifiers to bound nodes. This type
/// is an associative container with a key type of \c std::string and a value
/// type of \c clang::DynTypedNode
using IDToNodeMap = internal::BoundNodesMap::IDToNodeMap;
/// Retrieve mapping from binding identifiers to bound nodes.
const IDToNodeMap &getMap() const {
return MyBoundNodes.getMap();
}
private:
friend class internal::BoundNodesTreeBuilder;
/// Create BoundNodes from a pre-filled map of bindings.
BoundNodes(internal::BoundNodesMap &MyBoundNodes)
: MyBoundNodes(MyBoundNodes) {}
internal::BoundNodesMap MyBoundNodes;
};
/// Types of matchers for the top-level classes in the AST class
/// hierarchy.
/// @{
using DeclarationMatcher = internal::Matcher<Decl>;
using StatementMatcher = internal::Matcher<Stmt>;
using TypeMatcher = internal::Matcher<QualType>;
using TypeLocMatcher = internal::Matcher<TypeLoc>;
using NestedNameSpecifierMatcher = internal::Matcher<NestedNameSpecifier>;
using NestedNameSpecifierLocMatcher = internal::Matcher<NestedNameSpecifierLoc>;
using CXXCtorInitializerMatcher = internal::Matcher<CXXCtorInitializer>;
/// @}
/// Matches any node.
///
/// Useful when another matcher requires a child matcher, but there's no
/// additional constraint. This will often be used with an explicit conversion
/// to an \c internal::Matcher<> type such as \c TypeMatcher.
///
/// Example: \c DeclarationMatcher(anything()) matches all declarations, e.g.,
/// \code
/// "int* p" and "void f()" in
/// int* p;
/// void f();
/// \endcode
///
/// Usable as: Any Matcher
inline internal::TrueMatcher anything() { return internal::TrueMatcher(); }
/// Matches the top declaration context.
///
/// Given
/// \code
/// int X;
/// namespace NS {
/// int Y;
/// } // namespace NS
/// \endcode
/// decl(hasDeclContext(translationUnitDecl()))
/// matches "int X", but not "int Y".
extern const internal::VariadicDynCastAllOfMatcher<Decl, TranslationUnitDecl>
translationUnitDecl;
/// Matches typedef declarations.
///
/// Given
/// \code
/// typedef int X;
/// using Y = int;
/// \endcode
/// typedefDecl()
/// matches "typedef int X", but not "using Y = int"
extern const internal::VariadicDynCastAllOfMatcher<Decl, TypedefDecl>
typedefDecl;
/// Matches typedef name declarations.
///
/// Given
/// \code
/// typedef int X;
/// using Y = int;
/// \endcode
/// typedefNameDecl()
/// matches "typedef int X" and "using Y = int"
extern const internal::VariadicDynCastAllOfMatcher<Decl, TypedefNameDecl>
typedefNameDecl;
/// Matches type alias declarations.
///
/// Given
/// \code
/// typedef int X;
/// using Y = int;
/// \endcode
/// typeAliasDecl()
/// matches "using Y = int", but not "typedef int X"
extern const internal::VariadicDynCastAllOfMatcher<Decl, TypeAliasDecl>
typeAliasDecl;
/// Matches type alias template declarations.
///
/// typeAliasTemplateDecl() matches
/// \code
/// template <typename T>
/// using Y = X<T>;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, TypeAliasTemplateDecl>
typeAliasTemplateDecl;
/// Matches AST nodes that were expanded within the main-file.
///
/// Example matches X but not Y
/// (matcher = cxxRecordDecl(isExpansionInMainFile())
/// \code
/// #include <Y.h>
/// class X {};
/// \endcode
/// Y.h:
/// \code
/// class Y {};
/// \endcode
///
/// Usable as: Matcher<Decl>, Matcher<Stmt>, Matcher<TypeLoc>
AST_POLYMORPHIC_MATCHER(isExpansionInMainFile,
AST_POLYMORPHIC_SUPPORTED_TYPES(Decl, Stmt, TypeLoc)) {
auto &SourceManager = Finder->getASTContext().getSourceManager();
return SourceManager.isInMainFile(
SourceManager.getExpansionLoc(Node.getBeginLoc()));
}
/// Matches AST nodes that were expanded within system-header-files.
///
/// Example matches Y but not X
/// (matcher = cxxRecordDecl(isExpansionInSystemHeader())
/// \code
/// #include <SystemHeader.h>
/// class X {};
/// \endcode
/// SystemHeader.h:
/// \code
/// class Y {};
/// \endcode
///
/// Usable as: Matcher<Decl>, Matcher<Stmt>, Matcher<TypeLoc>
AST_POLYMORPHIC_MATCHER(isExpansionInSystemHeader,
AST_POLYMORPHIC_SUPPORTED_TYPES(Decl, Stmt, TypeLoc)) {
auto &SourceManager = Finder->getASTContext().getSourceManager();
auto ExpansionLoc = SourceManager.getExpansionLoc(Node.getBeginLoc());
if (ExpansionLoc.isInvalid()) {
return false;
}
return SourceManager.isInSystemHeader(ExpansionLoc);
}
/// Matches AST nodes that were expanded within files whose name is
/// partially matching a given regex.
///
/// Example matches Y but not X
/// (matcher = cxxRecordDecl(isExpansionInFileMatching("AST.*"))
/// \code
/// #include "ASTMatcher.h"
/// class X {};
/// \endcode
/// ASTMatcher.h:
/// \code
/// class Y {};
/// \endcode
///
/// Usable as: Matcher<Decl>, Matcher<Stmt>, Matcher<TypeLoc>
AST_POLYMORPHIC_MATCHER_P(isExpansionInFileMatching,
AST_POLYMORPHIC_SUPPORTED_TYPES(Decl, Stmt, TypeLoc),
std::string, RegExp) {
auto &SourceManager = Finder->getASTContext().getSourceManager();
auto ExpansionLoc = SourceManager.getExpansionLoc(Node.getBeginLoc());
if (ExpansionLoc.isInvalid()) {
return false;
}
auto FileEntry =
SourceManager.getFileEntryForID(SourceManager.getFileID(ExpansionLoc));
if (!FileEntry) {
return false;
}
auto Filename = FileEntry->getName();
llvm::Regex RE(RegExp);
return RE.match(Filename);
}
/// Matches statements that are (transitively) expanded from the named macro.
/// Does not match if only part of the statement is expanded from that macro or
/// if different parts of the the statement are expanded from different
/// appearances of the macro.
///
/// FIXME: Change to be a polymorphic matcher that works on any syntactic
/// node. There's nothing `Stmt`-specific about it.
AST_MATCHER_P(Stmt, isExpandedFromMacro, llvm::StringRef, MacroName) {
// Verifies that the statement' beginning and ending are both expanded from
// the same instance of the given macro.
auto& Context = Finder->getASTContext();
llvm::Optional<SourceLocation> B =
internal::getExpansionLocOfMacro(MacroName, Node.getBeginLoc(), Context);
if (!B) return false;
llvm::Optional<SourceLocation> E =
internal::getExpansionLocOfMacro(MacroName, Node.getEndLoc(), Context);
if (!E) return false;
return *B == *E;
}
/// Matches declarations.
///
/// Examples matches \c X, \c C, and the friend declaration inside \c C;
/// \code
/// void X();
/// class C {
/// friend X;
/// };
/// \endcode
extern const internal::VariadicAllOfMatcher<Decl> decl;
/// Matches a declaration of a linkage specification.
///
/// Given
/// \code
/// extern "C" {}
/// \endcode
/// linkageSpecDecl()
/// matches "extern "C" {}"
extern const internal::VariadicDynCastAllOfMatcher<Decl, LinkageSpecDecl>
linkageSpecDecl;
/// Matches a declaration of anything that could have a name.
///
/// Example matches \c X, \c S, the anonymous union type, \c i, and \c U;
/// \code
/// typedef int X;
/// struct S {
/// union {
/// int i;
/// } U;
/// };
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, NamedDecl> namedDecl;
/// Matches a declaration of label.
///
/// Given
/// \code
/// goto FOO;
/// FOO: bar();
/// \endcode
/// labelDecl()
/// matches 'FOO:'
extern const internal::VariadicDynCastAllOfMatcher<Decl, LabelDecl> labelDecl;
/// Matches a declaration of a namespace.
///
/// Given
/// \code
/// namespace {}
/// namespace test {}
/// \endcode
/// namespaceDecl()
/// matches "namespace {}" and "namespace test {}"
extern const internal::VariadicDynCastAllOfMatcher<Decl, NamespaceDecl>
namespaceDecl;
/// Matches a declaration of a namespace alias.
///
/// Given
/// \code
/// namespace test {}
/// namespace alias = ::test;
/// \endcode
/// namespaceAliasDecl()
/// matches "namespace alias" but not "namespace test"
extern const internal::VariadicDynCastAllOfMatcher<Decl, NamespaceAliasDecl>
namespaceAliasDecl;
/// Matches class, struct, and union declarations.
///
/// Example matches \c X, \c Z, \c U, and \c S
/// \code
/// class X;
/// template<class T> class Z {};
/// struct S {};
/// union U {};
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, RecordDecl> recordDecl;
/// Matches C++ class declarations.
///
/// Example matches \c X, \c Z
/// \code
/// class X;
/// template<class T> class Z {};
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, CXXRecordDecl>
cxxRecordDecl;
/// Matches C++ class template declarations.
///
/// Example matches \c Z
/// \code
/// template<class T> class Z {};
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ClassTemplateDecl>
classTemplateDecl;
/// Matches C++ class template specializations.
///
/// Given
/// \code
/// template<typename T> class A {};
/// template<> class A<double> {};
/// A<int> a;
/// \endcode
/// classTemplateSpecializationDecl()
/// matches the specializations \c A<int> and \c A<double>
extern const internal::VariadicDynCastAllOfMatcher<
Decl, ClassTemplateSpecializationDecl>
classTemplateSpecializationDecl;
/// Matches C++ class template partial specializations.
///
/// Given
/// \code
/// template<class T1, class T2, int I>
/// class A {};
///
/// template<class T, int I>
/// class A<T, T*, I> {};
///
/// template<>
/// class A<int, int, 1> {};
/// \endcode
/// classTemplatePartialSpecializationDecl()
/// matches the specialization \c A<T,T*,I> but not \c A<int,int,1>
extern const internal::VariadicDynCastAllOfMatcher<
Decl, ClassTemplatePartialSpecializationDecl>
classTemplatePartialSpecializationDecl;
/// Matches declarator declarations (field, variable, function
/// and non-type template parameter declarations).
///
/// Given
/// \code
/// class X { int y; };
/// \endcode
/// declaratorDecl()
/// matches \c int y.
extern const internal::VariadicDynCastAllOfMatcher<Decl, DeclaratorDecl>
declaratorDecl;
/// Matches parameter variable declarations.
///
/// Given
/// \code
/// void f(int x);
/// \endcode
/// parmVarDecl()
/// matches \c int x.
extern const internal::VariadicDynCastAllOfMatcher<Decl, ParmVarDecl>
parmVarDecl;
/// Matches C++ access specifier declarations.
///
/// Given
/// \code
/// class C {
/// public:
/// int a;
/// };
/// \endcode
/// accessSpecDecl()
/// matches 'public:'
extern const internal::VariadicDynCastAllOfMatcher<Decl, AccessSpecDecl>
accessSpecDecl;
/// Matches constructor initializers.
///
/// Examples matches \c i(42).
/// \code
/// class C {
/// C() : i(42) {}
/// int i;
/// };
/// \endcode
extern const internal::VariadicAllOfMatcher<CXXCtorInitializer>
cxxCtorInitializer;
/// Matches template arguments.
///
/// Given
/// \code
/// template <typename T> struct C {};
/// C<int> c;
/// \endcode
/// templateArgument()
/// matches 'int' in C<int>.
extern const internal::VariadicAllOfMatcher<TemplateArgument> templateArgument;
/// Matches template name.
///
/// Given
/// \code
/// template <typename T> class X { };
/// X<int> xi;
/// \endcode
/// templateName()
/// matches 'X' in X<int>.
extern const internal::VariadicAllOfMatcher<TemplateName> templateName;
/// Matches non-type template parameter declarations.
///
/// Given
/// \code
/// template <typename T, int N> struct C {};
/// \endcode
/// nonTypeTemplateParmDecl()
/// matches 'N', but not 'T'.
extern const internal::VariadicDynCastAllOfMatcher<Decl,
NonTypeTemplateParmDecl>
nonTypeTemplateParmDecl;
/// Matches template type parameter declarations.
///
/// Given
/// \code
/// template <typename T, int N> struct C {};
/// \endcode
/// templateTypeParmDecl()
/// matches 'T', but not 'N'.
extern const internal::VariadicDynCastAllOfMatcher<Decl, TemplateTypeParmDecl>
templateTypeParmDecl;
/// Matches public C++ declarations and C++ base specifers that specify public
/// inheritance.
///
/// Examples:
/// \code
/// class C {
/// public: int a; // fieldDecl(isPublic()) matches 'a'
/// protected: int b;
/// private: int c;
/// };
/// \endcode
///
/// \code
/// class Base {};
/// class Derived1 : public Base {}; // matches 'Base'
/// struct Derived2 : Base {}; // matches 'Base'
/// \endcode
AST_POLYMORPHIC_MATCHER(isPublic,
AST_POLYMORPHIC_SUPPORTED_TYPES(Decl,
CXXBaseSpecifier)) {
return getAccessSpecifier(Node) == AS_public;
}
/// Matches protected C++ declarations and C++ base specifers that specify
/// protected inheritance.
///
/// Examples:
/// \code
/// class C {
/// public: int a;
/// protected: int b; // fieldDecl(isProtected()) matches 'b'
/// private: int c;
/// };
/// \endcode
///
/// \code
/// class Base {};
/// class Derived : protected Base {}; // matches 'Base'
/// \endcode
AST_POLYMORPHIC_MATCHER(isProtected,
AST_POLYMORPHIC_SUPPORTED_TYPES(Decl,
CXXBaseSpecifier)) {
return getAccessSpecifier(Node) == AS_protected;
}
/// Matches private C++ declarations and C++ base specifers that specify private
/// inheritance.
///
/// Examples:
/// \code
/// class C {
/// public: int a;
/// protected: int b;
/// private: int c; // fieldDecl(isPrivate()) matches 'c'
/// };
/// \endcode
///
/// \code
/// struct Base {};
/// struct Derived1 : private Base {}; // matches 'Base'
/// class Derived2 : Base {}; // matches 'Base'
/// \endcode
AST_POLYMORPHIC_MATCHER(isPrivate,
AST_POLYMORPHIC_SUPPORTED_TYPES(Decl,
CXXBaseSpecifier)) {
return getAccessSpecifier(Node) == AS_private;
}
/// Matches non-static data members that are bit-fields.
///
/// Given
/// \code
/// class C {
/// int a : 2;
/// int b;
/// };
/// \endcode
/// fieldDecl(isBitField())
/// matches 'int a;' but not 'int b;'.
AST_MATCHER(FieldDecl, isBitField) {
return Node.isBitField();
}
/// Matches non-static data members that are bit-fields of the specified
/// bit width.
///
/// Given
/// \code
/// class C {
/// int a : 2;
/// int b : 4;
/// int c : 2;
/// };
/// \endcode
/// fieldDecl(hasBitWidth(2))
/// matches 'int a;' and 'int c;' but not 'int b;'.
AST_MATCHER_P(FieldDecl, hasBitWidth, unsigned, Width) {
return Node.isBitField() &&
Node.getBitWidthValue(Finder->getASTContext()) == Width;
}
/// Matches non-static data members that have an in-class initializer.
///
/// Given
/// \code
/// class C {
/// int a = 2;
/// int b = 3;
/// int c;
/// };
/// \endcode
/// fieldDecl(hasInClassInitializer(integerLiteral(equals(2))))
/// matches 'int a;' but not 'int b;'.
/// fieldDecl(hasInClassInitializer(anything()))
/// matches 'int a;' and 'int b;' but not 'int c;'.
AST_MATCHER_P(FieldDecl, hasInClassInitializer, internal::Matcher<Expr>,
InnerMatcher) {
const Expr *Initializer = Node.getInClassInitializer();
return (Initializer != nullptr &&
InnerMatcher.matches(*Initializer, Finder, Builder));
}
/// Determines whether the function is "main", which is the entry point
/// into an executable program.
AST_MATCHER(FunctionDecl, isMain) {
return Node.isMain();
}
/// Matches the specialized template of a specialization declaration.
///
/// Given
/// \code
/// template<typename T> class A {}; #1
/// template<> class A<int> {}; #2
/// \endcode
/// classTemplateSpecializationDecl(hasSpecializedTemplate(classTemplateDecl()))
/// matches '#2' with classTemplateDecl() matching the class template
/// declaration of 'A' at #1.
AST_MATCHER_P(ClassTemplateSpecializationDecl, hasSpecializedTemplate,
internal::Matcher<ClassTemplateDecl>, InnerMatcher) {
const ClassTemplateDecl* Decl = Node.getSpecializedTemplate();
return (Decl != nullptr &&
InnerMatcher.matches(*Decl, Finder, Builder));
}
/// Matches a declaration that has been implicitly added
/// by the compiler (eg. implicit default/copy constructors).
AST_MATCHER(Decl, isImplicit) {
return Node.isImplicit();
}
/// Matches classTemplateSpecializations, templateSpecializationType and
/// functionDecl that have at least one TemplateArgument matching the given
/// InnerMatcher.
///
/// Given
/// \code
/// template<typename T> class A {};
/// template<> class A<double> {};
/// A<int> a;
///
/// template<typename T> f() {};
/// void func() { f<int>(); };
/// \endcode
///
/// \endcode
/// classTemplateSpecializationDecl(hasAnyTemplateArgument(
/// refersToType(asString("int"))))
/// matches the specialization \c A<int>
///
/// functionDecl(hasAnyTemplateArgument(refersToType(asString("int"))))
/// matches the specialization \c f<int>
AST_POLYMORPHIC_MATCHER_P(
hasAnyTemplateArgument,
AST_POLYMORPHIC_SUPPORTED_TYPES(ClassTemplateSpecializationDecl,
TemplateSpecializationType,
FunctionDecl),
internal::Matcher<TemplateArgument>, InnerMatcher) {
ArrayRef<TemplateArgument> List =
internal::getTemplateSpecializationArgs(Node);
return matchesFirstInRange(InnerMatcher, List.begin(), List.end(), Finder,
Builder);
}
/// Causes all nested matchers to be matched with the specified traversal kind.
///
/// Given
/// \code
/// void foo()
/// {
/// int i = 3.0;
/// }
/// \endcode
/// The matcher
/// \code
/// traverse(TK_IgnoreImplicitCastsAndParentheses,
/// varDecl(hasInitializer(floatLiteral().bind("init")))
/// )
/// \endcode
/// matches the variable declaration with "init" bound to the "3.0".
template <typename T>
internal::Matcher<T> traverse(TraversalKind TK,
const internal::Matcher<T> &InnerMatcher) {
return internal::DynTypedMatcher::constructRestrictedWrapper(
new internal::TraversalMatcher<T>(TK, InnerMatcher),
InnerMatcher.getID().first)
.template unconditionalConvertTo<T>();
}
template <typename T>
internal::BindableMatcher<T>
traverse(TraversalKind TK, const internal::BindableMatcher<T> &InnerMatcher) {
return internal::BindableMatcher<T>(
internal::DynTypedMatcher::constructRestrictedWrapper(
new internal::TraversalMatcher<T>(TK, InnerMatcher),
InnerMatcher.getID().first)
.template unconditionalConvertTo<T>());
}
template <typename... T>
internal::TraversalWrapper<internal::VariadicOperatorMatcher<T...>>
traverse(TraversalKind TK,
const internal::VariadicOperatorMatcher<T...> &InnerMatcher) {
return internal::TraversalWrapper<internal::VariadicOperatorMatcher<T...>>(
TK, InnerMatcher);
}
template <template <typename ToArg, typename FromArg> class ArgumentAdapterT,
typename T, typename ToTypes>
internal::TraversalWrapper<
internal::ArgumentAdaptingMatcherFuncAdaptor<ArgumentAdapterT, T, ToTypes>>
traverse(TraversalKind TK, const internal::ArgumentAdaptingMatcherFuncAdaptor<
ArgumentAdapterT, T, ToTypes> &InnerMatcher) {
return internal::TraversalWrapper<
internal::ArgumentAdaptingMatcherFuncAdaptor<ArgumentAdapterT, T,
ToTypes>>(TK, InnerMatcher);
}
template <template <typename T, typename P1> class MatcherT, typename P1,
typename ReturnTypesF>
internal::TraversalWrapper<
internal::PolymorphicMatcherWithParam1<MatcherT, P1, ReturnTypesF>>
traverse(TraversalKind TK, const internal::PolymorphicMatcherWithParam1<
MatcherT, P1, ReturnTypesF> &InnerMatcher) {
return internal::TraversalWrapper<
internal::PolymorphicMatcherWithParam1<MatcherT, P1, ReturnTypesF>>(
TK, InnerMatcher);
}
template <template <typename T, typename P1, typename P2> class MatcherT,
typename P1, typename P2, typename ReturnTypesF>
internal::TraversalWrapper<
internal::PolymorphicMatcherWithParam2<MatcherT, P1, P2, ReturnTypesF>>
traverse(TraversalKind TK, const internal::PolymorphicMatcherWithParam2<
MatcherT, P1, P2, ReturnTypesF> &InnerMatcher) {
return internal::TraversalWrapper<
internal::PolymorphicMatcherWithParam2<MatcherT, P1, P2, ReturnTypesF>>(
TK, InnerMatcher);
}
/// Matches expressions that match InnerMatcher after any implicit AST
/// nodes are stripped off.
///
/// Parentheses and explicit casts are not discarded.
/// Given
/// \code
/// class C {};
/// C a = C();
/// C b;
/// C c = b;
/// \endcode
/// The matchers
/// \code
/// varDecl(hasInitializer(ignoringImplicit(cxxConstructExpr())))
/// \endcode
/// would match the declarations for a, b, and c.
/// While
/// \code
/// varDecl(hasInitializer(cxxConstructExpr()))
/// \endcode
/// only match the declarations for b and c.
AST_MATCHER_P(Expr, ignoringImplicit, internal::Matcher<Expr>,
InnerMatcher) {
return InnerMatcher.matches(*Node.IgnoreImplicit(), Finder, Builder);
}
/// Matches expressions that match InnerMatcher after any implicit casts
/// are stripped off.
///
/// Parentheses and explicit casts are not discarded.
/// Given
/// \code
/// int arr[5];
/// int a = 0;
/// char b = 0;
/// const int c = a;
/// int *d = arr;
/// long e = (long) 0l;
/// \endcode
/// The matchers
/// \code
/// varDecl(hasInitializer(ignoringImpCasts(integerLiteral())))
/// varDecl(hasInitializer(ignoringImpCasts(declRefExpr())))
/// \endcode
/// would match the declarations for a, b, c, and d, but not e.
/// While
/// \code
/// varDecl(hasInitializer(integerLiteral()))
/// varDecl(hasInitializer(declRefExpr()))
/// \endcode
/// only match the declarations for b, c, and d.
AST_MATCHER_P(Expr, ignoringImpCasts,
internal::Matcher<Expr>, InnerMatcher) {
return InnerMatcher.matches(*Node.IgnoreImpCasts(), Finder, Builder);
}
/// Matches expressions that match InnerMatcher after parentheses and
/// casts are stripped off.
///
/// Implicit and non-C Style casts are also discarded.
/// Given
/// \code
/// int a = 0;
/// char b = (0);
/// void* c = reinterpret_cast<char*>(0);
/// char d = char(0);
/// \endcode
/// The matcher
/// varDecl(hasInitializer(ignoringParenCasts(integerLiteral())))
/// would match the declarations for a, b, c, and d.
/// while
/// varDecl(hasInitializer(integerLiteral()))
/// only match the declaration for a.
AST_MATCHER_P(Expr, ignoringParenCasts, internal::Matcher<Expr>, InnerMatcher) {
return InnerMatcher.matches(*Node.IgnoreParenCasts(), Finder, Builder);
}
/// Matches expressions that match InnerMatcher after implicit casts and
/// parentheses are stripped off.
///
/// Explicit casts are not discarded.
/// Given
/// \code
/// int arr[5];
/// int a = 0;
/// char b = (0);
/// const int c = a;
/// int *d = (arr);
/// long e = ((long) 0l);
/// \endcode
/// The matchers
/// varDecl(hasInitializer(ignoringParenImpCasts(integerLiteral())))
/// varDecl(hasInitializer(ignoringParenImpCasts(declRefExpr())))
/// would match the declarations for a, b, c, and d, but not e.
/// while
/// varDecl(hasInitializer(integerLiteral()))
/// varDecl(hasInitializer(declRefExpr()))
/// would only match the declaration for a.
AST_MATCHER_P(Expr, ignoringParenImpCasts,
internal::Matcher<Expr>, InnerMatcher) {
return InnerMatcher.matches(*Node.IgnoreParenImpCasts(), Finder, Builder);
}
/// Matches types that match InnerMatcher after any parens are stripped.
///
/// Given
/// \code
/// void (*fp)(void);
/// \endcode
/// The matcher
/// \code
/// varDecl(hasType(pointerType(pointee(ignoringParens(functionType())))))
/// \endcode
/// would match the declaration for fp.
AST_MATCHER_P_OVERLOAD(QualType, ignoringParens, internal::Matcher<QualType>,
InnerMatcher, 0) {
return InnerMatcher.matches(Node.IgnoreParens(), Finder, Builder);
}
/// Overload \c ignoringParens for \c Expr.
///
/// Given
/// \code
/// const char* str = ("my-string");
/// \endcode
/// The matcher
/// \code
/// implicitCastExpr(hasSourceExpression(ignoringParens(stringLiteral())))
/// \endcode
/// would match the implicit cast resulting from the assignment.
AST_MATCHER_P_OVERLOAD(Expr, ignoringParens, internal::Matcher<Expr>,
InnerMatcher, 1) {
const Expr *E = Node.IgnoreParens();
return InnerMatcher.matches(*E, Finder, Builder);
}
/// Matches expressions that are instantiation-dependent even if it is
/// neither type- nor value-dependent.
///
/// In the following example, the expression sizeof(sizeof(T() + T()))
/// is instantiation-dependent (since it involves a template parameter T),
/// but is neither type- nor value-dependent, since the type of the inner
/// sizeof is known (std::size_t) and therefore the size of the outer
/// sizeof is known.
/// \code
/// template<typename T>
/// void f(T x, T y) { sizeof(sizeof(T() + T()); }
/// \endcode
/// expr(isInstantiationDependent()) matches sizeof(sizeof(T() + T())
AST_MATCHER(Expr, isInstantiationDependent) {
return Node.isInstantiationDependent();
}
/// Matches expressions that are type-dependent because the template type
/// is not yet instantiated.
///
/// For example, the expressions "x" and "x + y" are type-dependent in
/// the following code, but "y" is not type-dependent:
/// \code
/// template<typename T>
/// void add(T x, int y) {
/// x + y;
/// }
/// \endcode
/// expr(isTypeDependent()) matches x + y
AST_MATCHER(Expr, isTypeDependent) { return Node.isTypeDependent(); }
/// Matches expression that are value-dependent because they contain a
/// non-type template parameter.
///
/// For example, the array bound of "Chars" in the following example is
/// value-dependent.
/// \code
/// template<int Size> int f() { return Size; }
/// \endcode
/// expr(isValueDependent()) matches return Size
AST_MATCHER(Expr, isValueDependent) { return Node.isValueDependent(); }
/// Matches classTemplateSpecializations, templateSpecializationType and
/// functionDecl where the n'th TemplateArgument matches the given InnerMatcher.
///
/// Given
/// \code
/// template<typename T, typename U> class A {};
/// A<bool, int> b;
/// A<int, bool> c;
///
/// template<typename T> void f() {}
/// void func() { f<int>(); };
/// \endcode
/// classTemplateSpecializationDecl(hasTemplateArgument(
/// 1, refersToType(asString("int"))))
/// matches the specialization \c A<bool, int>
///
/// functionDecl(hasTemplateArgument(0, refersToType(asString("int"))))
/// matches the specialization \c f<int>
AST_POLYMORPHIC_MATCHER_P2(
hasTemplateArgument,
AST_POLYMORPHIC_SUPPORTED_TYPES(ClassTemplateSpecializationDecl,
TemplateSpecializationType,
FunctionDecl),
unsigned, N, internal::Matcher<TemplateArgument>, InnerMatcher) {
ArrayRef<TemplateArgument> List =
internal::getTemplateSpecializationArgs(Node);
if (List.size() <= N)
return false;
return InnerMatcher.matches(List[N], Finder, Builder);
}
/// Matches if the number of template arguments equals \p N.
///
/// Given
/// \code
/// template<typename T> struct C {};
/// C<int> c;
/// \endcode
/// classTemplateSpecializationDecl(templateArgumentCountIs(1))
/// matches C<int>.
AST_POLYMORPHIC_MATCHER_P(
templateArgumentCountIs,
AST_POLYMORPHIC_SUPPORTED_TYPES(ClassTemplateSpecializationDecl,
TemplateSpecializationType),
unsigned, N) {
return internal::getTemplateSpecializationArgs(Node).size() == N;
}
/// Matches a TemplateArgument that refers to a certain type.
///
/// Given
/// \code
/// struct X {};
/// template<typename T> struct A {};
/// A<X> a;
/// \endcode
/// classTemplateSpecializationDecl(hasAnyTemplateArgument(
/// refersToType(class(hasName("X")))))
/// matches the specialization \c A<X>
AST_MATCHER_P(TemplateArgument, refersToType,
internal::Matcher<QualType>, InnerMatcher) {
if (Node.getKind() != TemplateArgument::Type)
return false;
return InnerMatcher.matches(Node.getAsType(), Finder, Builder);
}
/// Matches a TemplateArgument that refers to a certain template.
///
/// Given
/// \code
/// template<template <typename> class S> class X {};
/// template<typename T> class Y {};
/// X<Y> xi;
/// \endcode
/// classTemplateSpecializationDecl(hasAnyTemplateArgument(
/// refersToTemplate(templateName())))
/// matches the specialization \c X<Y>
AST_MATCHER_P(TemplateArgument, refersToTemplate,
internal::Matcher<TemplateName>, InnerMatcher) {
if (Node.getKind() != TemplateArgument::Template)
return false;
return InnerMatcher.matches(Node.getAsTemplate(), Finder, Builder);
}
/// Matches a canonical TemplateArgument that refers to a certain
/// declaration.
///
/// Given
/// \code
/// struct B { int next; };
/// template<int(B::*next_ptr)> struct A {};
/// A<&B::next> a;
/// \endcode
/// classTemplateSpecializationDecl(hasAnyTemplateArgument(
/// refersToDeclaration(fieldDecl(hasName("next")))))
/// matches the specialization \c A<&B::next> with \c fieldDecl(...) matching
/// \c B::next
AST_MATCHER_P(TemplateArgument, refersToDeclaration,
internal::Matcher<Decl>, InnerMatcher) {
if (Node.getKind() == TemplateArgument::Declaration)
return InnerMatcher.matches(*Node.getAsDecl(), Finder, Builder);
return false;
}
/// Matches a sugar TemplateArgument that refers to a certain expression.
///
/// Given
/// \code
/// struct B { int next; };
/// template<int(B::*next_ptr)> struct A {};
/// A<&B::next> a;
/// \endcode
/// templateSpecializationType(hasAnyTemplateArgument(
/// isExpr(hasDescendant(declRefExpr(to(fieldDecl(hasName("next"))))))))
/// matches the specialization \c A<&B::next> with \c fieldDecl(...) matching
/// \c B::next
AST_MATCHER_P(TemplateArgument, isExpr, internal::Matcher<Expr>, InnerMatcher) {
if (Node.getKind() == TemplateArgument::Expression)
return InnerMatcher.matches(*Node.getAsExpr(), Finder, Builder);
return false;
}
/// Matches a TemplateArgument that is an integral value.
///
/// Given
/// \code
/// template<int T> struct C {};
/// C<42> c;
/// \endcode
/// classTemplateSpecializationDecl(
/// hasAnyTemplateArgument(isIntegral()))
/// matches the implicit instantiation of C in C<42>
/// with isIntegral() matching 42.
AST_MATCHER(TemplateArgument, isIntegral) {
return Node.getKind() == TemplateArgument::Integral;
}
/// Matches a TemplateArgument that referes to an integral type.
///
/// Given
/// \code
/// template<int T> struct C {};
/// C<42> c;
/// \endcode
/// classTemplateSpecializationDecl(
/// hasAnyTemplateArgument(refersToIntegralType(asString("int"))))
/// matches the implicit instantiation of C in C<42>.
AST_MATCHER_P(TemplateArgument, refersToIntegralType,
internal::Matcher<QualType>, InnerMatcher) {
if (Node.getKind() != TemplateArgument::Integral)
return false;
return InnerMatcher.matches(Node.getIntegralType(), Finder, Builder);
}
/// Matches a TemplateArgument of integral type with a given value.
///
/// Note that 'Value' is a string as the template argument's value is
/// an arbitrary precision integer. 'Value' must be euqal to the canonical
/// representation of that integral value in base 10.
///
/// Given
/// \code
/// template<int T> struct C {};
/// C<42> c;
/// \endcode
/// classTemplateSpecializationDecl(
/// hasAnyTemplateArgument(equalsIntegralValue("42")))
/// matches the implicit instantiation of C in C<42>.
AST_MATCHER_P(TemplateArgument, equalsIntegralValue,
std::string, Value) {
if (Node.getKind() != TemplateArgument::Integral)
return false;
return Node.getAsIntegral().toString(10) == Value;
}
/// Matches an Objective-C autorelease pool statement.
///
/// Given
/// \code
/// @autoreleasepool {
/// int x = 0;
/// }
/// \endcode
/// autoreleasePoolStmt(stmt()) matches the declaration of "x"
/// inside the autorelease pool.
extern const internal::VariadicDynCastAllOfMatcher<Stmt,
ObjCAutoreleasePoolStmt> autoreleasePoolStmt;
/// Matches any value declaration.
///
/// Example matches A, B, C and F
/// \code
/// enum X { A, B, C };
/// void F();
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ValueDecl> valueDecl;
/// Matches C++ constructor declarations.
///
/// Example matches Foo::Foo() and Foo::Foo(int)
/// \code
/// class Foo {
/// public:
/// Foo();
/// Foo(int);
/// int DoSomething();
/// };
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, CXXConstructorDecl>
cxxConstructorDecl;
/// Matches explicit C++ destructor declarations.
///
/// Example matches Foo::~Foo()
/// \code
/// class Foo {
/// public:
/// virtual ~Foo();
/// };
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, CXXDestructorDecl>
cxxDestructorDecl;
/// Matches enum declarations.
///
/// Example matches X
/// \code
/// enum X {
/// A, B, C
/// };
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, EnumDecl> enumDecl;
/// Matches enum constants.
///
/// Example matches A, B, C
/// \code
/// enum X {
/// A, B, C
/// };
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, EnumConstantDecl>
enumConstantDecl;
/// Matches tag declarations.
///
/// Example matches X, Z, U, S, E
/// \code
/// class X;
/// template<class T> class Z {};
/// struct S {};
/// union U {};
/// enum E {
/// A, B, C
/// };
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, TagDecl> tagDecl;
/// Matches method declarations.
///
/// Example matches y
/// \code
/// class X { void y(); };
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, CXXMethodDecl>
cxxMethodDecl;
/// Matches conversion operator declarations.
///
/// Example matches the operator.
/// \code
/// class X { operator int() const; };
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, CXXConversionDecl>
cxxConversionDecl;
/// Matches user-defined and implicitly generated deduction guide.
///
/// Example matches the deduction guide.
/// \code
/// template<typename T>
/// class X { X(int) };
/// X(int) -> X<int>;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, CXXDeductionGuideDecl>
cxxDeductionGuideDecl;
/// Matches variable declarations.
///
/// Note: this does not match declarations of member variables, which are
/// "field" declarations in Clang parlance.
///
/// Example matches a
/// \code
/// int a;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, VarDecl> varDecl;
/// Matches field declarations.
///
/// Given
/// \code
/// class X { int m; };
/// \endcode
/// fieldDecl()
/// matches 'm'.
extern const internal::VariadicDynCastAllOfMatcher<Decl, FieldDecl> fieldDecl;
/// Matches indirect field declarations.
///
/// Given
/// \code
/// struct X { struct { int a; }; };
/// \endcode
/// indirectFieldDecl()
/// matches 'a'.
extern const internal::VariadicDynCastAllOfMatcher<Decl, IndirectFieldDecl>
indirectFieldDecl;
/// Matches function declarations.
///
/// Example matches f
/// \code
/// void f();
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, FunctionDecl>
functionDecl;
/// Matches C++ function template declarations.
///
/// Example matches f
/// \code
/// template<class T> void f(T t) {}
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, FunctionTemplateDecl>
functionTemplateDecl;
/// Matches friend declarations.
///
/// Given
/// \code
/// class X { friend void foo(); };
/// \endcode
/// friendDecl()
/// matches 'friend void foo()'.
extern const internal::VariadicDynCastAllOfMatcher<Decl, FriendDecl> friendDecl;
/// Matches statements.
///
/// Given
/// \code
/// { ++a; }
/// \endcode
/// stmt()
/// matches both the compound statement '{ ++a; }' and '++a'.
extern const internal::VariadicAllOfMatcher<Stmt> stmt;
/// Matches declaration statements.
///
/// Given
/// \code
/// int a;
/// \endcode
/// declStmt()
/// matches 'int a'.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, DeclStmt> declStmt;
/// Matches member expressions.
///
/// Given
/// \code
/// class Y {
/// void x() { this->x(); x(); Y y; y.x(); a; this->b; Y::b; }
/// int a; static int b;
/// };
/// \endcode
/// memberExpr()
/// matches this->x, x, y.x, a, this->b
extern const internal::VariadicDynCastAllOfMatcher<Stmt, MemberExpr> memberExpr;
/// Matches unresolved member expressions.
///
/// Given
/// \code
/// struct X {
/// template <class T> void f();
/// void g();
/// };
/// template <class T> void h() { X x; x.f<T>(); x.g(); }
/// \endcode
/// unresolvedMemberExpr()
/// matches x.f<T>
extern const internal::VariadicDynCastAllOfMatcher<Stmt, UnresolvedMemberExpr>
unresolvedMemberExpr;
/// Matches member expressions where the actual member referenced could not be
/// resolved because the base expression or the member name was dependent.
///
/// Given
/// \code
/// template <class T> void f() { T t; t.g(); }
/// \endcode
/// cxxDependentScopeMemberExpr()
/// matches t.g
extern const internal::VariadicDynCastAllOfMatcher<Stmt,
CXXDependentScopeMemberExpr>
cxxDependentScopeMemberExpr;
/// Matches call expressions.
///
/// Example matches x.y() and y()
/// \code
/// X x;
/// x.y();
/// y();
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CallExpr> callExpr;
/// Matches call expressions which were resolved using ADL.
///
/// Example matches y(x) but not y(42) or NS::y(x).
/// \code
/// namespace NS {
/// struct X {};
/// void y(X);
/// }
///
/// void y(...);
///
/// void test() {
/// NS::X x;
/// y(x); // Matches
/// NS::y(x); // Doesn't match
/// y(42); // Doesn't match
/// using NS::y;
/// y(x); // Found by both unqualified lookup and ADL, doesn't match
// }
/// \endcode
AST_MATCHER(CallExpr, usesADL) { return Node.usesADL(); }
/// Matches lambda expressions.
///
/// Example matches [&](){return 5;}
/// \code
/// [&](){return 5;}
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, LambdaExpr> lambdaExpr;
/// Matches member call expressions.
///
/// Example matches x.y()
/// \code
/// X x;
/// x.y();
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXMemberCallExpr>
cxxMemberCallExpr;
/// Matches ObjectiveC Message invocation expressions.
///
/// The innermost message send invokes the "alloc" class method on the
/// NSString class, while the outermost message send invokes the
/// "initWithString" instance method on the object returned from
/// NSString's "alloc". This matcher should match both message sends.
/// \code
/// [[NSString alloc] initWithString:@"Hello"]
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ObjCMessageExpr>
objcMessageExpr;
/// Matches Objective-C interface declarations.
///
/// Example matches Foo
/// \code
/// @interface Foo
/// @end
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ObjCInterfaceDecl>
objcInterfaceDecl;
/// Matches Objective-C implementation declarations.
///
/// Example matches Foo
/// \code
/// @implementation Foo
/// @end
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ObjCImplementationDecl>
objcImplementationDecl;
/// Matches Objective-C protocol declarations.
///
/// Example matches FooDelegate
/// \code
/// @protocol FooDelegate
/// @end
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ObjCProtocolDecl>
objcProtocolDecl;
/// Matches Objective-C category declarations.
///
/// Example matches Foo (Additions)
/// \code
/// @interface Foo (Additions)
/// @end
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ObjCCategoryDecl>
objcCategoryDecl;
/// Matches Objective-C category definitions.
///
/// Example matches Foo (Additions)
/// \code
/// @implementation Foo (Additions)
/// @end
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ObjCCategoryImplDecl>
objcCategoryImplDecl;
/// Matches Objective-C method declarations.
///
/// Example matches both declaration and definition of -[Foo method]
/// \code
/// @interface Foo
/// - (void)method;
/// @end
///
/// @implementation Foo
/// - (void)method {}
/// @end
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ObjCMethodDecl>
objcMethodDecl;
/// Matches block declarations.
///
/// Example matches the declaration of the nameless block printing an input
/// integer.
///
/// \code
/// myFunc(^(int p) {
/// printf("%d", p);
/// })
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, BlockDecl>
blockDecl;
/// Matches Objective-C instance variable declarations.
///
/// Example matches _enabled
/// \code
/// @implementation Foo {
/// BOOL _enabled;
/// }
/// @end
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ObjCIvarDecl>
objcIvarDecl;
/// Matches Objective-C property declarations.
///
/// Example matches enabled
/// \code
/// @interface Foo
/// @property BOOL enabled;
/// @end
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, ObjCPropertyDecl>
objcPropertyDecl;
/// Matches Objective-C \@throw statements.
///
/// Example matches \@throw
/// \code
/// @throw obj;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ObjCAtThrowStmt>
objcThrowStmt;
/// Matches Objective-C @try statements.
///
/// Example matches @try
/// \code
/// @try {}
/// @catch (...) {}
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ObjCAtTryStmt>
objcTryStmt;
/// Matches Objective-C @catch statements.
///
/// Example matches @catch
/// \code
/// @try {}
/// @catch (...) {}
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ObjCAtCatchStmt>
objcCatchStmt;
/// Matches Objective-C @finally statements.
///
/// Example matches @finally
/// \code
/// @try {}
/// @finally {}
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ObjCAtFinallyStmt>
objcFinallyStmt;
/// Matches expressions that introduce cleanups to be run at the end
/// of the sub-expression's evaluation.
///
/// Example matches std::string()
/// \code
/// const std::string str = std::string();
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ExprWithCleanups>
exprWithCleanups;
/// Matches init list expressions.
///
/// Given
/// \code
/// int a[] = { 1, 2 };
/// struct B { int x, y; };
/// B b = { 5, 6 };
/// \endcode
/// initListExpr()
/// matches "{ 1, 2 }" and "{ 5, 6 }"
extern const internal::VariadicDynCastAllOfMatcher<Stmt, InitListExpr>
initListExpr;
/// Matches the syntactic form of init list expressions
/// (if expression have it).
AST_MATCHER_P(InitListExpr, hasSyntacticForm,
internal::Matcher<Expr>, InnerMatcher) {
const Expr *SyntForm = Node.getSyntacticForm();
return (SyntForm != nullptr &&
InnerMatcher.matches(*SyntForm, Finder, Builder));
}
/// Matches C++ initializer list expressions.
///
/// Given
/// \code
/// std::vector<int> a({ 1, 2, 3 });
/// std::vector<int> b = { 4, 5 };
/// int c[] = { 6, 7 };
/// std::pair<int, int> d = { 8, 9 };
/// \endcode
/// cxxStdInitializerListExpr()
/// matches "{ 1, 2, 3 }" and "{ 4, 5 }"
extern const internal::VariadicDynCastAllOfMatcher<Stmt,
CXXStdInitializerListExpr>
cxxStdInitializerListExpr;
/// Matches implicit initializers of init list expressions.
///
/// Given
/// \code
/// point ptarray[10] = { [2].y = 1.0, [2].x = 2.0, [0].x = 1.0 };
/// \endcode
/// implicitValueInitExpr()
/// matches "[0].y" (implicitly)
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ImplicitValueInitExpr>
implicitValueInitExpr;
/// Matches paren list expressions.
/// ParenListExprs don't have a predefined type and are used for late parsing.
/// In the final AST, they can be met in template declarations.
///
/// Given
/// \code
/// template<typename T> class X {
/// void f() {
/// X x(*this);
/// int a = 0, b = 1; int i = (a, b);
/// }
/// };
/// \endcode
/// parenListExpr() matches "*this" but NOT matches (a, b) because (a, b)
/// has a predefined type and is a ParenExpr, not a ParenListExpr.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ParenListExpr>
parenListExpr;
/// Matches substitutions of non-type template parameters.
///
/// Given
/// \code
/// template <int N>
/// struct A { static const int n = N; };
/// struct B : public A<42> {};
/// \endcode
/// substNonTypeTemplateParmExpr()
/// matches "N" in the right-hand side of "static const int n = N;"
extern const internal::VariadicDynCastAllOfMatcher<Stmt,
SubstNonTypeTemplateParmExpr>
substNonTypeTemplateParmExpr;
/// Matches using declarations.
///
/// Given
/// \code
/// namespace X { int x; }
/// using X::x;
/// \endcode
/// usingDecl()
/// matches \code using X::x \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, UsingDecl> usingDecl;
/// Matches using namespace declarations.
///
/// Given
/// \code
/// namespace X { int x; }
/// using namespace X;
/// \endcode
/// usingDirectiveDecl()
/// matches \code using namespace X \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, UsingDirectiveDecl>
usingDirectiveDecl;
/// Matches reference to a name that can be looked up during parsing
/// but could not be resolved to a specific declaration.
///
/// Given
/// \code
/// template<typename T>
/// T foo() { T a; return a; }
/// template<typename T>
/// void bar() {
/// foo<T>();
/// }
/// \endcode
/// unresolvedLookupExpr()
/// matches \code foo<T>() \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, UnresolvedLookupExpr>
unresolvedLookupExpr;
/// Matches unresolved using value declarations.
///
/// Given
/// \code
/// template<typename X>
/// class C : private X {
/// using X::x;
/// };
/// \endcode
/// unresolvedUsingValueDecl()
/// matches \code using X::x \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl,
UnresolvedUsingValueDecl>
unresolvedUsingValueDecl;
/// Matches unresolved using value declarations that involve the
/// typename.
///
/// Given
/// \code
/// template <typename T>
/// struct Base { typedef T Foo; };
///
/// template<typename T>
/// struct S : private Base<T> {
/// using typename Base<T>::Foo;
/// };
/// \endcode
/// unresolvedUsingTypenameDecl()
/// matches \code using Base<T>::Foo \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl,
UnresolvedUsingTypenameDecl>
unresolvedUsingTypenameDecl;
/// Matches a constant expression wrapper.
///
/// Example matches the constant in the case statement:
/// (matcher = constantExpr())
/// \code
/// switch (a) {
/// case 37: break;
/// }
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ConstantExpr>
constantExpr;
/// Matches parentheses used in expressions.
///
/// Example matches (foo() + 1)
/// \code
/// int foo() { return 1; }
/// int a = (foo() + 1);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ParenExpr> parenExpr;
/// Matches constructor call expressions (including implicit ones).
///
/// Example matches string(ptr, n) and ptr within arguments of f
/// (matcher = cxxConstructExpr())
/// \code
/// void f(const string &a, const string &b);
/// char *ptr;
/// int n;
/// f(string(ptr, n), ptr);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXConstructExpr>
cxxConstructExpr;
/// Matches unresolved constructor call expressions.
///
/// Example matches T(t) in return statement of f
/// (matcher = cxxUnresolvedConstructExpr())
/// \code
/// template <typename T>
/// void f(const T& t) { return T(t); }
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt,
CXXUnresolvedConstructExpr>
cxxUnresolvedConstructExpr;
/// Matches implicit and explicit this expressions.
///
/// Example matches the implicit this expression in "return i".
/// (matcher = cxxThisExpr())
/// \code
/// struct foo {
/// int i;
/// int f() { return i; }
/// };
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXThisExpr>
cxxThisExpr;
/// Matches nodes where temporaries are created.
///
/// Example matches FunctionTakesString(GetStringByValue())
/// (matcher = cxxBindTemporaryExpr())
/// \code
/// FunctionTakesString(GetStringByValue());
/// FunctionTakesStringByPointer(GetStringPointer());
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXBindTemporaryExpr>
cxxBindTemporaryExpr;
/// Matches nodes where temporaries are materialized.
///
/// Example: Given
/// \code
/// struct T {void func();};
/// T f();
/// void g(T);
/// \endcode
/// materializeTemporaryExpr() matches 'f()' in these statements
/// \code
/// T u(f());
/// g(f());
/// f().func();
/// \endcode
/// but does not match
/// \code
/// f();
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt,
MaterializeTemporaryExpr>
materializeTemporaryExpr;
/// Matches new expressions.
///
/// Given
/// \code
/// new X;
/// \endcode
/// cxxNewExpr()
/// matches 'new X'.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXNewExpr> cxxNewExpr;
/// Matches delete expressions.
///
/// Given
/// \code
/// delete X;
/// \endcode
/// cxxDeleteExpr()
/// matches 'delete X'.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXDeleteExpr>
cxxDeleteExpr;
/// Matches noexcept expressions.
///
/// Given
/// \code
/// bool a() noexcept;
/// bool b() noexcept(true);
/// bool c() noexcept(false);
/// bool d() noexcept(noexcept(a()));
/// bool e = noexcept(b()) || noexcept(c());
/// \endcode
/// cxxNoexceptExpr()
/// matches `noexcept(a())`, `noexcept(b())` and `noexcept(c())`.
/// doesn't match the noexcept specifier in the declarations a, b, c or d.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXNoexceptExpr>
cxxNoexceptExpr;
/// Matches array subscript expressions.
///
/// Given
/// \code
/// int i = a[1];
/// \endcode
/// arraySubscriptExpr()
/// matches "a[1]"
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ArraySubscriptExpr>
arraySubscriptExpr;
/// Matches the value of a default argument at the call site.
///
/// Example matches the CXXDefaultArgExpr placeholder inserted for the
/// default value of the second parameter in the call expression f(42)
/// (matcher = cxxDefaultArgExpr())
/// \code
/// void f(int x, int y = 0);
/// f(42);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXDefaultArgExpr>
cxxDefaultArgExpr;
/// Matches overloaded operator calls.
///
/// Note that if an operator isn't overloaded, it won't match. Instead, use
/// binaryOperator matcher.
/// Currently it does not match operators such as new delete.
/// FIXME: figure out why these do not match?
///
/// Example matches both operator<<((o << b), c) and operator<<(o, b)
/// (matcher = cxxOperatorCallExpr())
/// \code
/// ostream &operator<< (ostream &out, int i) { };
/// ostream &o; int b = 1, c = 1;
/// o << b << c;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXOperatorCallExpr>
cxxOperatorCallExpr;
/// Matches expressions.
///
/// Example matches x()
/// \code
/// void f() { x(); }
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, Expr> expr;
/// Matches expressions that refer to declarations.
///
/// Example matches x in if (x)
/// \code
/// bool x;
/// if (x) {}
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, DeclRefExpr>
declRefExpr;
/// Matches a reference to an ObjCIvar.
///
/// Example: matches "a" in "init" method:
/// \code
/// @implementation A {
/// NSString *a;
/// }
/// - (void) init {
/// a = @"hello";
/// }
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ObjCIvarRefExpr>
objcIvarRefExpr;
/// Matches a reference to a block.
///
/// Example: matches "^{}":
/// \code
/// void f() { ^{}(); }
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, BlockExpr> blockExpr;
/// Matches if statements.
///
/// Example matches 'if (x) {}'
/// \code
/// if (x) {}
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, IfStmt> ifStmt;
/// Matches for statements.
///
/// Example matches 'for (;;) {}'
/// \code
/// for (;;) {}
/// int i[] = {1, 2, 3}; for (auto a : i);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ForStmt> forStmt;
/// Matches the increment statement of a for loop.
///
/// Example:
/// forStmt(hasIncrement(unaryOperator(hasOperatorName("++"))))
/// matches '++x' in
/// \code
/// for (x; x < N; ++x) { }
/// \endcode
AST_MATCHER_P(ForStmt, hasIncrement, internal::Matcher<Stmt>,
InnerMatcher) {
const Stmt *const Increment = Node.getInc();
return (Increment != nullptr &&
InnerMatcher.matches(*Increment, Finder, Builder));
}
/// Matches the initialization statement of a for loop.
///
/// Example:
/// forStmt(hasLoopInit(declStmt()))
/// matches 'int x = 0' in
/// \code
/// for (int x = 0; x < N; ++x) { }
/// \endcode
AST_MATCHER_P(ForStmt, hasLoopInit, internal::Matcher<Stmt>,
InnerMatcher) {
const Stmt *const Init = Node.getInit();
return (Init != nullptr && InnerMatcher.matches(*Init, Finder, Builder));
}
/// Matches range-based for statements.
///
/// cxxForRangeStmt() matches 'for (auto a : i)'
/// \code
/// int i[] = {1, 2, 3}; for (auto a : i);
/// for(int j = 0; j < 5; ++j);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXForRangeStmt>
cxxForRangeStmt;
/// Matches the initialization statement of a for loop.
///
/// Example:
/// forStmt(hasLoopVariable(anything()))
/// matches 'int x' in
/// \code
/// for (int x : a) { }
/// \endcode
AST_MATCHER_P(CXXForRangeStmt, hasLoopVariable, internal::Matcher<VarDecl>,
InnerMatcher) {
const VarDecl *const Var = Node.getLoopVariable();
return (Var != nullptr && InnerMatcher.matches(*Var, Finder, Builder));
}
/// Matches the range initialization statement of a for loop.
///
/// Example:
/// forStmt(hasRangeInit(anything()))
/// matches 'a' in
/// \code
/// for (int x : a) { }
/// \endcode
AST_MATCHER_P(CXXForRangeStmt, hasRangeInit, internal::Matcher<Expr>,
InnerMatcher) {
const Expr *const Init = Node.getRangeInit();
return (Init != nullptr && InnerMatcher.matches(*Init, Finder, Builder));
}
/// Matches while statements.
///
/// Given
/// \code
/// while (true) {}
/// \endcode
/// whileStmt()
/// matches 'while (true) {}'.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, WhileStmt> whileStmt;
/// Matches do statements.
///
/// Given
/// \code
/// do {} while (true);
/// \endcode
/// doStmt()
/// matches 'do {} while(true)'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, DoStmt> doStmt;
/// Matches break statements.
///
/// Given
/// \code
/// while (true) { break; }
/// \endcode
/// breakStmt()
/// matches 'break'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, BreakStmt> breakStmt;
/// Matches continue statements.
///
/// Given
/// \code
/// while (true) { continue; }
/// \endcode
/// continueStmt()
/// matches 'continue'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ContinueStmt>
continueStmt;
/// Matches return statements.
///
/// Given
/// \code
/// return 1;
/// \endcode
/// returnStmt()
/// matches 'return 1'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ReturnStmt> returnStmt;
/// Matches goto statements.
///
/// Given
/// \code
/// goto FOO;
/// FOO: bar();
/// \endcode
/// gotoStmt()
/// matches 'goto FOO'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, GotoStmt> gotoStmt;
/// Matches label statements.
///
/// Given
/// \code
/// goto FOO;
/// FOO: bar();
/// \endcode
/// labelStmt()
/// matches 'FOO:'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, LabelStmt> labelStmt;
/// Matches address of label statements (GNU extension).
///
/// Given
/// \code
/// FOO: bar();
/// void *ptr = &&FOO;
/// goto *bar;
/// \endcode
/// addrLabelExpr()
/// matches '&&FOO'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, AddrLabelExpr>
addrLabelExpr;
/// Matches switch statements.
///
/// Given
/// \code
/// switch(a) { case 42: break; default: break; }
/// \endcode
/// switchStmt()
/// matches 'switch(a)'.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, SwitchStmt> switchStmt;
/// Matches case and default statements inside switch statements.
///
/// Given
/// \code
/// switch(a) { case 42: break; default: break; }
/// \endcode
/// switchCase()
/// matches 'case 42:' and 'default:'.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, SwitchCase> switchCase;
/// Matches case statements inside switch statements.
///
/// Given
/// \code
/// switch(a) { case 42: break; default: break; }
/// \endcode
/// caseStmt()
/// matches 'case 42:'.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CaseStmt> caseStmt;
/// Matches default statements inside switch statements.
///
/// Given
/// \code
/// switch(a) { case 42: break; default: break; }
/// \endcode
/// defaultStmt()
/// matches 'default:'.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, DefaultStmt>
defaultStmt;
/// Matches compound statements.
///
/// Example matches '{}' and '{{}}' in 'for (;;) {{}}'
/// \code
/// for (;;) {{}}
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CompoundStmt>
compoundStmt;
/// Matches catch statements.
///
/// \code
/// try {} catch(int i) {}
/// \endcode
/// cxxCatchStmt()
/// matches 'catch(int i)'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXCatchStmt>
cxxCatchStmt;
/// Matches try statements.
///
/// \code
/// try {} catch(int i) {}
/// \endcode
/// cxxTryStmt()
/// matches 'try {}'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXTryStmt> cxxTryStmt;
/// Matches throw expressions.
///
/// \code
/// try { throw 5; } catch(int i) {}
/// \endcode
/// cxxThrowExpr()
/// matches 'throw 5'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXThrowExpr>
cxxThrowExpr;
/// Matches null statements.
///
/// \code
/// foo();;
/// \endcode
/// nullStmt()
/// matches the second ';'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, NullStmt> nullStmt;
/// Matches asm statements.
///
/// \code
/// int i = 100;
/// __asm("mov al, 2");
/// \endcode
/// asmStmt()
/// matches '__asm("mov al, 2")'
extern const internal::VariadicDynCastAllOfMatcher<Stmt, AsmStmt> asmStmt;
/// Matches bool literals.
///
/// Example matches true
/// \code
/// true
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXBoolLiteralExpr>
cxxBoolLiteral;
/// Matches string literals (also matches wide string literals).
///
/// Example matches "abcd", L"abcd"
/// \code
/// char *s = "abcd";
/// wchar_t *ws = L"abcd";
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, StringLiteral>
stringLiteral;
/// Matches character literals (also matches wchar_t).
///
/// Not matching Hex-encoded chars (e.g. 0x1234, which is a IntegerLiteral),
/// though.
///
/// Example matches 'a', L'a'
/// \code
/// char ch = 'a';
/// wchar_t chw = L'a';
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CharacterLiteral>
characterLiteral;
/// Matches integer literals of all sizes / encodings, e.g.
/// 1, 1L, 0x1 and 1U.
///
/// Does not match character-encoded integers such as L'a'.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, IntegerLiteral>
integerLiteral;
/// Matches float literals of all sizes / encodings, e.g.
/// 1.0, 1.0f, 1.0L and 1e10.
///
/// Does not match implicit conversions such as
/// \code
/// float a = 10;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, FloatingLiteral>
floatLiteral;
/// Matches imaginary literals, which are based on integer and floating
/// point literals e.g.: 1i, 1.0i
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ImaginaryLiteral>
imaginaryLiteral;
/// Matches fixed point literals
extern const internal::VariadicDynCastAllOfMatcher<Stmt, FixedPointLiteral>
fixedPointLiteral;
/// Matches user defined literal operator call.
///
/// Example match: "foo"_suffix
extern const internal::VariadicDynCastAllOfMatcher<Stmt, UserDefinedLiteral>
userDefinedLiteral;
/// Matches compound (i.e. non-scalar) literals
///
/// Example match: {1}, (1, 2)
/// \code
/// int array[4] = {1};
/// vector int myvec = (vector int)(1, 2);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CompoundLiteralExpr>
compoundLiteralExpr;
/// Matches nullptr literal.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXNullPtrLiteralExpr>
cxxNullPtrLiteralExpr;
/// Matches GNU __builtin_choose_expr.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ChooseExpr>
chooseExpr;
/// Matches GNU __null expression.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, GNUNullExpr>
gnuNullExpr;
/// Matches atomic builtins.
/// Example matches __atomic_load_n(ptr, 1)
/// \code
/// void foo() { int *ptr; __atomic_load_n(ptr, 1); }
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, AtomicExpr> atomicExpr;
/// Matches statement expression (GNU extension).
///
/// Example match: ({ int X = 4; X; })
/// \code
/// int C = ({ int X = 4; X; });
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, StmtExpr> stmtExpr;
/// Matches binary operator expressions.
///
/// Example matches a || b
/// \code
/// !(a || b)
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, BinaryOperator>
binaryOperator;
/// Matches unary operator expressions.
///
/// Example matches !a
/// \code
/// !a || b
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, UnaryOperator>
unaryOperator;
/// Matches conditional operator expressions.
///
/// Example matches a ? b : c
/// \code
/// (a ? b : c) + 42
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ConditionalOperator>
conditionalOperator;
/// Matches binary conditional operator expressions (GNU extension).
///
/// Example matches a ?: b
/// \code
/// (a ?: b) + 42;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt,
BinaryConditionalOperator>
binaryConditionalOperator;
/// Matches opaque value expressions. They are used as helpers
/// to reference another expressions and can be met
/// in BinaryConditionalOperators, for example.
///
/// Example matches 'a'
/// \code
/// (a ?: c) + 42;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, OpaqueValueExpr>
opaqueValueExpr;
/// Matches a C++ static_assert declaration.
///
/// Example:
/// staticAssertExpr()
/// matches
/// static_assert(sizeof(S) == sizeof(int))
/// in
/// \code
/// struct S {
/// int x;
/// };
/// static_assert(sizeof(S) == sizeof(int));
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Decl, StaticAssertDecl>
staticAssertDecl;
/// Matches a reinterpret_cast expression.
///
/// Either the source expression or the destination type can be matched
/// using has(), but hasDestinationType() is more specific and can be
/// more readable.
///
/// Example matches reinterpret_cast<char*>(&p) in
/// \code
/// void* p = reinterpret_cast<char*>(&p);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXReinterpretCastExpr>
cxxReinterpretCastExpr;
/// Matches a C++ static_cast expression.
///
/// \see hasDestinationType
/// \see reinterpretCast
///
/// Example:
/// cxxStaticCastExpr()
/// matches
/// static_cast<long>(8)
/// in
/// \code
/// long eight(static_cast<long>(8));
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXStaticCastExpr>
cxxStaticCastExpr;
/// Matches a dynamic_cast expression.
///
/// Example:
/// cxxDynamicCastExpr()
/// matches
/// dynamic_cast<D*>(&b);
/// in
/// \code
/// struct B { virtual ~B() {} }; struct D : B {};
/// B b;
/// D* p = dynamic_cast<D*>(&b);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXDynamicCastExpr>
cxxDynamicCastExpr;
/// Matches a const_cast expression.
///
/// Example: Matches const_cast<int*>(&r) in
/// \code
/// int n = 42;
/// const int &r(n);
/// int* p = const_cast<int*>(&r);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXConstCastExpr>
cxxConstCastExpr;
/// Matches a C-style cast expression.
///
/// Example: Matches (int) 2.2f in
/// \code
/// int i = (int) 2.2f;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CStyleCastExpr>
cStyleCastExpr;
/// Matches explicit cast expressions.
///
/// Matches any cast expression written in user code, whether it be a
/// C-style cast, a functional-style cast, or a keyword cast.
///
/// Does not match implicit conversions.
///
/// Note: the name "explicitCast" is chosen to match Clang's terminology, as
/// Clang uses the term "cast" to apply to implicit conversions as well as to
/// actual cast expressions.
///
/// \see hasDestinationType.
///
/// Example: matches all five of the casts in
/// \code
/// int((int)(reinterpret_cast<int>(static_cast<int>(const_cast<int>(42)))))
/// \endcode
/// but does not match the implicit conversion in
/// \code
/// long ell = 42;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ExplicitCastExpr>
explicitCastExpr;
/// Matches the implicit cast nodes of Clang's AST.
///
/// This matches many different places, including function call return value
/// eliding, as well as any type conversions.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, ImplicitCastExpr>
implicitCastExpr;
/// Matches any cast nodes of Clang's AST.
///
/// Example: castExpr() matches each of the following:
/// \code
/// (int) 3;
/// const_cast<Expr *>(SubExpr);
/// char c = 0;
/// \endcode
/// but does not match
/// \code
/// int i = (0);
/// int k = 0;
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CastExpr> castExpr;
/// Matches functional cast expressions
///
/// Example: Matches Foo(bar);
/// \code
/// Foo f = bar;
/// Foo g = (Foo) bar;
/// Foo h = Foo(bar);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXFunctionalCastExpr>
cxxFunctionalCastExpr;
/// Matches functional cast expressions having N != 1 arguments
///
/// Example: Matches Foo(bar, bar)
/// \code
/// Foo h = Foo(bar, bar);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CXXTemporaryObjectExpr>
cxxTemporaryObjectExpr;
/// Matches predefined identifier expressions [C99 6.4.2.2].
///
/// Example: Matches __func__
/// \code
/// printf("%s", __func__);
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, PredefinedExpr>
predefinedExpr;
/// Matches C99 designated initializer expressions [C99 6.7.8].
///
/// Example: Matches { [2].y = 1.0, [0].x = 1.0 }
/// \code
/// point ptarray[10] = { [2].y = 1.0, [0].x = 1.0 };
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, DesignatedInitExpr>
designatedInitExpr;
/// Matches designated initializer expressions that contain
/// a specific number of designators.
///
/// Example: Given
/// \code
/// point ptarray[10] = { [2].y = 1.0, [0].x = 1.0 };
/// point ptarray2[10] = { [2].y = 1.0, [2].x = 0.0, [0].x = 1.0 };
/// \endcode
/// designatorCountIs(2)
/// matches '{ [2].y = 1.0, [0].x = 1.0 }',
/// but not '{ [2].y = 1.0, [2].x = 0.0, [0].x = 1.0 }'.
AST_MATCHER_P(DesignatedInitExpr, designatorCountIs, unsigned, N) {
return Node.size() == N;
}
/// Matches \c QualTypes in the clang AST.
extern const internal::VariadicAllOfMatcher<QualType> qualType;
/// Matches \c Types in the clang AST.
extern const internal::VariadicAllOfMatcher<Type> type;
/// Matches \c TypeLocs in the clang AST.
extern const internal::VariadicAllOfMatcher<TypeLoc> typeLoc;
/// Matches if any of the given matchers matches.
///
/// Unlike \c anyOf, \c eachOf will generate a match result for each
/// matching submatcher.
///
/// For example, in:
/// \code
/// class A { int a; int b; };
/// \endcode
/// The matcher:
/// \code
/// cxxRecordDecl(eachOf(has(fieldDecl(hasName("a")).bind("v")),
/// has(fieldDecl(hasName("b")).bind("v"))))
/// \endcode
/// will generate two results binding "v", the first of which binds
/// the field declaration of \c a, the second the field declaration of
/// \c b.
///
/// Usable as: Any Matcher
extern const internal::VariadicOperatorMatcherFunc<
2, std::numeric_limits<unsigned>::max()>
eachOf;
/// Matches if any of the given matchers matches.
///
/// Usable as: Any Matcher
extern const internal::VariadicOperatorMatcherFunc<
2, std::numeric_limits<unsigned>::max()>
anyOf;
/// Matches if all given matchers match.
///
/// Usable as: Any Matcher
extern const internal::VariadicOperatorMatcherFunc<
2, std::numeric_limits<unsigned>::max()>
allOf;
/// Matches any node regardless of the submatcher.
///
/// However, \c optionally will retain any bindings generated by the submatcher.
/// Useful when additional information which may or may not present about a main
/// matching node is desired.
///
/// For example, in:
/// \code
/// class Foo {
/// int bar;
/// }
/// \endcode
/// The matcher:
/// \code
/// cxxRecordDecl(
/// optionally(has(
/// fieldDecl(hasName("bar")).bind("var")
/// ))).bind("record")
/// \endcode
/// will produce a result binding for both "record" and "var".
/// The matcher will produce a "record" binding for even if there is no data
/// member named "bar" in that class.
///
/// Usable as: Any Matcher
extern const internal::VariadicOperatorMatcherFunc<1, 1> optionally;
/// Matches sizeof (C99), alignof (C++11) and vec_step (OpenCL)
///
/// Given
/// \code
/// Foo x = bar;
/// int y = sizeof(x) + alignof(x);
/// \endcode
/// unaryExprOrTypeTraitExpr()
/// matches \c sizeof(x) and \c alignof(x)
extern const internal::VariadicDynCastAllOfMatcher<Stmt,
UnaryExprOrTypeTraitExpr>
unaryExprOrTypeTraitExpr;
/// Matches unary expressions that have a specific type of argument.
///
/// Given
/// \code
/// int a, c; float b; int s = sizeof(a) + sizeof(b) + alignof(c);
/// \endcode
/// unaryExprOrTypeTraitExpr(hasArgumentOfType(asString("int"))
/// matches \c sizeof(a) and \c alignof(c)
AST_MATCHER_P(UnaryExprOrTypeTraitExpr, hasArgumentOfType,
internal::Matcher<QualType>, InnerMatcher) {
const QualType ArgumentType = Node.getTypeOfArgument();
return InnerMatcher.matches(ArgumentType, Finder, Builder);
}
/// Matches unary expressions of a certain kind.
///
/// Given
/// \code
/// int x;
/// int s = sizeof(x) + alignof(x)
/// \endcode
/// unaryExprOrTypeTraitExpr(ofKind(UETT_SizeOf))
/// matches \c sizeof(x)
///
/// If the matcher is use from clang-query, UnaryExprOrTypeTrait parameter
/// should be passed as a quoted string. e.g., ofKind("UETT_SizeOf").
AST_MATCHER_P(UnaryExprOrTypeTraitExpr, ofKind, UnaryExprOrTypeTrait, Kind) {
return Node.getKind() == Kind;
}
/// Same as unaryExprOrTypeTraitExpr, but only matching
/// alignof.
inline internal::BindableMatcher<Stmt> alignOfExpr(
const internal::Matcher<UnaryExprOrTypeTraitExpr> &InnerMatcher) {
return stmt(unaryExprOrTypeTraitExpr(
allOf(anyOf(ofKind(UETT_AlignOf), ofKind(UETT_PreferredAlignOf)),
InnerMatcher)));
}
/// Same as unaryExprOrTypeTraitExpr, but only matching
/// sizeof.
inline internal::BindableMatcher<Stmt> sizeOfExpr(
const internal::Matcher<UnaryExprOrTypeTraitExpr> &InnerMatcher) {
return stmt(unaryExprOrTypeTraitExpr(
allOf(ofKind(UETT_SizeOf), InnerMatcher)));
}
/// Matches NamedDecl nodes that have the specified name.
///
/// Supports specifying enclosing namespaces or classes by prefixing the name
/// with '<enclosing>::'.
/// Does not match typedefs of an underlying type with the given name.
///
/// Example matches X (Name == "X")
/// \code
/// class X;
/// \endcode
///
/// Example matches X (Name is one of "::a::b::X", "a::b::X", "b::X", "X")
/// \code
/// namespace a { namespace b { class X; } }
/// \endcode
inline internal::Matcher<NamedDecl> hasName(StringRef Name) {
return internal::Matcher<NamedDecl>(
new internal::HasNameMatcher({std::string(Name)}));
}
/// Matches NamedDecl nodes that have any of the specified names.
///
/// This matcher is only provided as a performance optimization of hasName.
/// \code
/// hasAnyName(a, b, c)
/// \endcode
/// is equivalent to, but faster than
/// \code
/// anyOf(hasName(a), hasName(b), hasName(c))
/// \endcode
extern const internal::VariadicFunction<internal::Matcher<NamedDecl>, StringRef,
internal::hasAnyNameFunc>
hasAnyName;
/// Matches NamedDecl nodes whose fully qualified names contain
/// a substring matched by the given RegExp.
///
/// Supports specifying enclosing namespaces or classes by
/// prefixing the name with '<enclosing>::'. Does not match typedefs
/// of an underlying type with the given name.
///
/// Example matches X (regexp == "::X")
/// \code
/// class X;
/// \endcode
///
/// Example matches X (regexp is one of "::X", "^foo::.*X", among others)
/// \code
/// namespace foo { namespace bar { class X; } }
/// \endcode
AST_MATCHER_P(NamedDecl, matchesName, std::string, RegExp) {
assert(!RegExp.empty());
std::string FullNameString = "::" + Node.getQualifiedNameAsString();
llvm::Regex RE(RegExp);
return RE.match(FullNameString);
}
/// Matches overloaded operator names.
///
/// Matches overloaded operator names specified in strings without the
/// "operator" prefix: e.g. "<<".
///
/// Given:
/// \code
/// class A { int operator*(); };
/// const A &operator<<(const A &a, const A &b);
/// A a;
/// a << a; // <-- This matches
/// \endcode
///
/// \c cxxOperatorCallExpr(hasOverloadedOperatorName("<<"))) matches the
/// specified line and
/// \c cxxRecordDecl(hasMethod(hasOverloadedOperatorName("*")))
/// matches the declaration of \c A.
///
/// Usable as: Matcher<CXXOperatorCallExpr>, Matcher<FunctionDecl>
inline internal::PolymorphicMatcherWithParam1<
internal::HasOverloadedOperatorNameMatcher, std::vector<std::string>,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXOperatorCallExpr, FunctionDecl)>
hasOverloadedOperatorName(StringRef Name) {
return internal::PolymorphicMatcherWithParam1<
internal::HasOverloadedOperatorNameMatcher, std::vector<std::string>,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXOperatorCallExpr, FunctionDecl)>(
{std::string(Name)});
}
/// Matches overloaded operator names.
///
/// Matches overloaded operator names specified in strings without the
/// "operator" prefix: e.g. "<<".
///
/// hasAnyOverloadesOperatorName("+", "-")
/// Is equivalent to
/// anyOf(hasOverloadedOperatorName("+"), hasOverloadedOperatorName("-"))
extern const internal::VariadicFunction<
internal::PolymorphicMatcherWithParam1<
internal::HasOverloadedOperatorNameMatcher, std::vector<std::string>,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXOperatorCallExpr, FunctionDecl)>,
StringRef, internal::hasAnyOverloadedOperatorNameFunc>
hasAnyOverloadedOperatorName;
/// Matches C++ classes that are directly or indirectly derived from a class
/// matching \c Base, or Objective-C classes that directly or indirectly
/// subclass a class matching \c Base.
///
/// Note that a class is not considered to be derived from itself.
///
/// Example matches Y, Z, C (Base == hasName("X"))
/// \code
/// class X;
/// class Y : public X {}; // directly derived
/// class Z : public Y {}; // indirectly derived
/// typedef X A;
/// typedef A B;
/// class C : public B {}; // derived from a typedef of X
/// \endcode
///
/// In the following example, Bar matches isDerivedFrom(hasName("X")):
/// \code
/// class Foo;
/// typedef Foo X;
/// class Bar : public Foo {}; // derived from a type that X is a typedef of
/// \endcode
///
/// In the following example, Bar matches isDerivedFrom(hasName("NSObject"))
/// \code
/// @interface NSObject @end
/// @interface Bar : NSObject @end
/// \endcode
///
/// Usable as: Matcher<CXXRecordDecl>, Matcher<ObjCInterfaceDecl>
AST_POLYMORPHIC_MATCHER_P(
isDerivedFrom,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXRecordDecl, ObjCInterfaceDecl),
internal::Matcher<NamedDecl>, Base) {
// Check if the node is a C++ struct/union/class.
if (const auto *RD = dyn_cast<CXXRecordDecl>(&Node))
return Finder->classIsDerivedFrom(RD, Base, Builder, /*Directly=*/false);
// The node must be an Objective-C class.
const auto *InterfaceDecl = cast<ObjCInterfaceDecl>(&Node);
return Finder->objcClassIsDerivedFrom(InterfaceDecl, Base, Builder,
/*Directly=*/false);
}
/// Overloaded method as shortcut for \c isDerivedFrom(hasName(...)).
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(
isDerivedFrom,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXRecordDecl, ObjCInterfaceDecl),
std::string, BaseName, 1) {
if (BaseName.empty())
return false;
const auto M = isDerivedFrom(hasName(BaseName));
if (const auto *RD = dyn_cast<CXXRecordDecl>(&Node))
return Matcher<CXXRecordDecl>(M).matches(*RD, Finder, Builder);
const auto *InterfaceDecl = cast<ObjCInterfaceDecl>(&Node);
return Matcher<ObjCInterfaceDecl>(M).matches(*InterfaceDecl, Finder, Builder);
}
/// Matches C++ classes that have a direct or indirect base matching \p
/// BaseSpecMatcher.
///
/// Example:
/// matcher hasAnyBase(hasType(cxxRecordDecl(hasName("SpecialBase")))))
/// \code
/// class Foo;
/// class Bar : Foo {};
/// class Baz : Bar {};
/// class SpecialBase;
/// class Proxy : SpecialBase {}; // matches Proxy
/// class IndirectlyDerived : Proxy {}; //matches IndirectlyDerived
/// \endcode
///
// FIXME: Refactor this and isDerivedFrom to reuse implementation.
AST_MATCHER_P(CXXRecordDecl, hasAnyBase, internal::Matcher<CXXBaseSpecifier>,
BaseSpecMatcher) {
return internal::matchesAnyBase(Node, BaseSpecMatcher, Finder, Builder);
}
/// Similar to \c isDerivedFrom(), but also matches classes that directly
/// match \c Base.
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(
isSameOrDerivedFrom,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXRecordDecl, ObjCInterfaceDecl),
internal::Matcher<NamedDecl>, Base, 0) {
const auto M = anyOf(Base, isDerivedFrom(Base));
if (const auto *RD = dyn_cast<CXXRecordDecl>(&Node))
return Matcher<CXXRecordDecl>(M).matches(*RD, Finder, Builder);
const auto *InterfaceDecl = cast<ObjCInterfaceDecl>(&Node);
return Matcher<ObjCInterfaceDecl>(M).matches(*InterfaceDecl, Finder, Builder);
}
/// Overloaded method as shortcut for
/// \c isSameOrDerivedFrom(hasName(...)).
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(
isSameOrDerivedFrom,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXRecordDecl, ObjCInterfaceDecl),
std::string, BaseName, 1) {
if (BaseName.empty())
return false;
const auto M = isSameOrDerivedFrom(hasName(BaseName));
if (const auto *RD = dyn_cast<CXXRecordDecl>(&Node))
return Matcher<CXXRecordDecl>(M).matches(*RD, Finder, Builder);
const auto *InterfaceDecl = cast<ObjCInterfaceDecl>(&Node);
return Matcher<ObjCInterfaceDecl>(M).matches(*InterfaceDecl, Finder, Builder);
}
/// Matches C++ or Objective-C classes that are directly derived from a class
/// matching \c Base.
///
/// Note that a class is not considered to be derived from itself.
///
/// Example matches Y, C (Base == hasName("X"))
/// \code
/// class X;
/// class Y : public X {}; // directly derived
/// class Z : public Y {}; // indirectly derived
/// typedef X A;
/// typedef A B;
/// class C : public B {}; // derived from a typedef of X
/// \endcode
///
/// In the following example, Bar matches isDerivedFrom(hasName("X")):
/// \code
/// class Foo;
/// typedef Foo X;
/// class Bar : public Foo {}; // derived from a type that X is a typedef of
/// \endcode
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(
isDirectlyDerivedFrom,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXRecordDecl, ObjCInterfaceDecl),
internal::Matcher<NamedDecl>, Base, 0) {
// Check if the node is a C++ struct/union/class.
if (const auto *RD = dyn_cast<CXXRecordDecl>(&Node))
return Finder->classIsDerivedFrom(RD, Base, Builder, /*Directly=*/true);
// The node must be an Objective-C class.
const auto *InterfaceDecl = cast<ObjCInterfaceDecl>(&Node);
return Finder->objcClassIsDerivedFrom(InterfaceDecl, Base, Builder,
/*Directly=*/true);
}
/// Overloaded method as shortcut for \c isDirectlyDerivedFrom(hasName(...)).
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(
isDirectlyDerivedFrom,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXRecordDecl, ObjCInterfaceDecl),
std::string, BaseName, 1) {
if (BaseName.empty())
return false;
const auto M = isDirectlyDerivedFrom(hasName(BaseName));
if (const auto *RD = dyn_cast<CXXRecordDecl>(&Node))
return Matcher<CXXRecordDecl>(M).matches(*RD, Finder, Builder);
const auto *InterfaceDecl = cast<ObjCInterfaceDecl>(&Node);
return Matcher<ObjCInterfaceDecl>(M).matches(*InterfaceDecl, Finder, Builder);
}
/// Matches the first method of a class or struct that satisfies \c
/// InnerMatcher.
///
/// Given:
/// \code
/// class A { void func(); };
/// class B { void member(); };
/// \endcode
///
/// \c cxxRecordDecl(hasMethod(hasName("func"))) matches the declaration of
/// \c A but not \c B.
AST_MATCHER_P(CXXRecordDecl, hasMethod, internal::Matcher<CXXMethodDecl>,
InnerMatcher) {
return matchesFirstInPointerRange(InnerMatcher, Node.method_begin(),
Node.method_end(), Finder, Builder);
}
/// Matches the generated class of lambda expressions.
///
/// Given:
/// \code
/// auto x = []{};
/// \endcode
///
/// \c cxxRecordDecl(isLambda()) matches the implicit class declaration of
/// \c decltype(x)
AST_MATCHER(CXXRecordDecl, isLambda) {
return Node.isLambda();
}
/// Matches AST nodes that have child AST nodes that match the
/// provided matcher.
///
/// Example matches X, Y
/// (matcher = cxxRecordDecl(has(cxxRecordDecl(hasName("X")))
/// \code
/// class X {}; // Matches X, because X::X is a class of name X inside X.
/// class Y { class X {}; };
/// class Z { class Y { class X {}; }; }; // Does not match Z.
/// \endcode
///
/// ChildT must be an AST base type.
///
/// Usable as: Any Matcher
/// Note that has is direct matcher, so it also matches things like implicit
/// casts and paren casts. If you are matching with expr then you should
/// probably consider using ignoringParenImpCasts like:
/// has(ignoringParenImpCasts(expr())).
extern const internal::ArgumentAdaptingMatcherFunc<internal::HasMatcher> has;
/// Matches AST nodes that have descendant AST nodes that match the
/// provided matcher.
///
/// Example matches X, Y, Z
/// (matcher = cxxRecordDecl(hasDescendant(cxxRecordDecl(hasName("X")))))
/// \code
/// class X {}; // Matches X, because X::X is a class of name X inside X.
/// class Y { class X {}; };
/// class Z { class Y { class X {}; }; };
/// \endcode
///
/// DescendantT must be an AST base type.
///
/// Usable as: Any Matcher
extern const internal::ArgumentAdaptingMatcherFunc<
internal::HasDescendantMatcher>
hasDescendant;
/// Matches AST nodes that have child AST nodes that match the
/// provided matcher.
///
/// Example matches X, Y, Y::X, Z::Y, Z::Y::X
/// (matcher = cxxRecordDecl(forEach(cxxRecordDecl(hasName("X")))
/// \code
/// class X {};
/// class Y { class X {}; }; // Matches Y, because Y::X is a class of name X
/// // inside Y.
/// class Z { class Y { class X {}; }; }; // Does not match Z.
/// \endcode
///
/// ChildT must be an AST base type.
///
/// As opposed to 'has', 'forEach' will cause a match for each result that
/// matches instead of only on the first one.
///
/// Usable as: Any Matcher
extern const internal::ArgumentAdaptingMatcherFunc<internal::ForEachMatcher>
forEach;
/// Matches AST nodes that have descendant AST nodes that match the
/// provided matcher.
///
/// Example matches X, A, A::X, B, B::C, B::C::X
/// (matcher = cxxRecordDecl(forEachDescendant(cxxRecordDecl(hasName("X")))))
/// \code
/// class X {};
/// class A { class X {}; }; // Matches A, because A::X is a class of name
/// // X inside A.
/// class B { class C { class X {}; }; };
/// \endcode
///
/// DescendantT must be an AST base type.
///
/// As opposed to 'hasDescendant', 'forEachDescendant' will cause a match for
/// each result that matches instead of only on the first one.
///
/// Note: Recursively combined ForEachDescendant can cause many matches:
/// cxxRecordDecl(forEachDescendant(cxxRecordDecl(
/// forEachDescendant(cxxRecordDecl())
/// )))
/// will match 10 times (plus injected class name matches) on:
/// \code
/// class A { class B { class C { class D { class E {}; }; }; }; };
/// \endcode
///
/// Usable as: Any Matcher
extern const internal::ArgumentAdaptingMatcherFunc<
internal::ForEachDescendantMatcher>
forEachDescendant;
/// Matches if the node or any descendant matches.
///
/// Generates results for each match.
///
/// For example, in:
/// \code
/// class A { class B {}; class C {}; };
/// \endcode
/// The matcher:
/// \code
/// cxxRecordDecl(hasName("::A"),
/// findAll(cxxRecordDecl(isDefinition()).bind("m")))
/// \endcode
/// will generate results for \c A, \c B and \c C.
///
/// Usable as: Any Matcher
template <typename T>
internal::Matcher<T> findAll(const internal::Matcher<T> &Matcher) {
return eachOf(Matcher, forEachDescendant(Matcher));
}
/// Matches AST nodes that have a parent that matches the provided
/// matcher.
///
/// Given
/// \code
/// void f() { for (;;) { int x = 42; if (true) { int x = 43; } } }
/// \endcode
/// \c compoundStmt(hasParent(ifStmt())) matches "{ int x = 43; }".
///
/// Usable as: Any Matcher
extern const internal::ArgumentAdaptingMatcherFunc<
internal::HasParentMatcher,
internal::TypeList<Decl, NestedNameSpecifierLoc, Stmt, TypeLoc>,
internal::TypeList<Decl, NestedNameSpecifierLoc, Stmt, TypeLoc>>
hasParent;
/// Matches AST nodes that have an ancestor that matches the provided
/// matcher.
///
/// Given
/// \code
/// void f() { if (true) { int x = 42; } }
/// void g() { for (;;) { int x = 43; } }
/// \endcode
/// \c expr(integerLiteral(hasAncestor(ifStmt()))) matches \c 42, but not 43.
///
/// Usable as: Any Matcher
extern const internal::ArgumentAdaptingMatcherFunc<
internal::HasAncestorMatcher,
internal::TypeList<Decl, NestedNameSpecifierLoc, Stmt, TypeLoc>,
internal::TypeList<Decl, NestedNameSpecifierLoc, Stmt, TypeLoc>>
hasAncestor;
/// Matches if the provided matcher does not match.
///
/// Example matches Y (matcher = cxxRecordDecl(unless(hasName("X"))))
/// \code
/// class X {};
/// class Y {};
/// \endcode
///
/// Usable as: Any Matcher
extern const internal::VariadicOperatorMatcherFunc<1, 1> unless;
/// Matches a node if the declaration associated with that node
/// matches the given matcher.
///
/// The associated declaration is:
/// - for type nodes, the declaration of the underlying type
/// - for CallExpr, the declaration of the callee
/// - for MemberExpr, the declaration of the referenced member
/// - for CXXConstructExpr, the declaration of the constructor
/// - for CXXNewExpr, the declaration of the operator new
/// - for ObjCIvarExpr, the declaration of the ivar
///
/// For type nodes, hasDeclaration will generally match the declaration of the
/// sugared type. Given
/// \code
/// class X {};
/// typedef X Y;
/// Y y;
/// \endcode
/// in varDecl(hasType(hasDeclaration(decl()))) the decl will match the
/// typedefDecl. A common use case is to match the underlying, desugared type.
/// This can be achieved by using the hasUnqualifiedDesugaredType matcher:
/// \code
/// varDecl(hasType(hasUnqualifiedDesugaredType(
/// recordType(hasDeclaration(decl())))))
/// \endcode
/// In this matcher, the decl will match the CXXRecordDecl of class X.
///
/// Usable as: Matcher<AddrLabelExpr>, Matcher<CallExpr>,
/// Matcher<CXXConstructExpr>, Matcher<CXXNewExpr>, Matcher<DeclRefExpr>,
/// Matcher<EnumType>, Matcher<InjectedClassNameType>, Matcher<LabelStmt>,
/// Matcher<MemberExpr>, Matcher<QualType>, Matcher<RecordType>,
/// Matcher<TagType>, Matcher<TemplateSpecializationType>,
/// Matcher<TemplateTypeParmType>, Matcher<TypedefType>,
/// Matcher<UnresolvedUsingType>
inline internal::PolymorphicMatcherWithParam1<
internal::HasDeclarationMatcher, internal::Matcher<Decl>,
void(internal::HasDeclarationSupportedTypes)>
hasDeclaration(const internal::Matcher<Decl> &InnerMatcher) {
return internal::PolymorphicMatcherWithParam1<
internal::HasDeclarationMatcher, internal::Matcher<Decl>,
void(internal::HasDeclarationSupportedTypes)>(InnerMatcher);
}
/// Matches a \c NamedDecl whose underlying declaration matches the given
/// matcher.
///
/// Given
/// \code
/// namespace N { template<class T> void f(T t); }
/// template <class T> void g() { using N::f; f(T()); }
/// \endcode
/// \c unresolvedLookupExpr(hasAnyDeclaration(
/// namedDecl(hasUnderlyingDecl(hasName("::N::f")))))
/// matches the use of \c f in \c g() .
AST_MATCHER_P(NamedDecl, hasUnderlyingDecl, internal::Matcher<NamedDecl>,
InnerMatcher) {
const NamedDecl *UnderlyingDecl = Node.getUnderlyingDecl();
return UnderlyingDecl != nullptr &&
InnerMatcher.matches(*UnderlyingDecl, Finder, Builder);
}
/// Matches on the implicit object argument of a member call expression, after
/// stripping off any parentheses or implicit casts.
///
/// Given
/// \code
/// class Y { public: void m(); };
/// Y g();
/// class X : public Y {};
/// void z(Y y, X x) { y.m(); (g()).m(); x.m(); }
/// \endcode
/// cxxMemberCallExpr(on(hasType(cxxRecordDecl(hasName("Y")))))
/// matches `y.m()` and `(g()).m()`.
/// cxxMemberCallExpr(on(hasType(cxxRecordDecl(hasName("X")))))
/// matches `x.m()`.
/// cxxMemberCallExpr(on(callExpr()))
/// matches `(g()).m()`.
///
/// FIXME: Overload to allow directly matching types?
AST_MATCHER_P(CXXMemberCallExpr, on, internal::Matcher<Expr>,
InnerMatcher) {
const Expr *ExprNode = Node.getImplicitObjectArgument()
->IgnoreParenImpCasts();
return (ExprNode != nullptr &&
InnerMatcher.matches(*ExprNode, Finder, Builder));
}
/// Matches on the receiver of an ObjectiveC Message expression.
///
/// Example
/// matcher = objCMessageExpr(hasReceiverType(asString("UIWebView *")));
/// matches the [webView ...] message invocation.
/// \code
/// NSString *webViewJavaScript = ...
/// UIWebView *webView = ...
/// [webView stringByEvaluatingJavaScriptFromString:webViewJavascript];
/// \endcode
AST_MATCHER_P(ObjCMessageExpr, hasReceiverType, internal::Matcher<QualType>,
InnerMatcher) {
const QualType TypeDecl = Node.getReceiverType();
return InnerMatcher.matches(TypeDecl, Finder, Builder);
}
/// Returns true when the Objective-C method declaration is a class method.
///
/// Example
/// matcher = objcMethodDecl(isClassMethod())
/// matches
/// \code
/// @interface I + (void)foo; @end
/// \endcode
/// but not
/// \code
/// @interface I - (void)bar; @end
/// \endcode
AST_MATCHER(ObjCMethodDecl, isClassMethod) {
return Node.isClassMethod();
}
/// Returns true when the Objective-C method declaration is an instance method.
///
/// Example
/// matcher = objcMethodDecl(isInstanceMethod())
/// matches
/// \code
/// @interface I - (void)bar; @end
/// \endcode
/// but not
/// \code
/// @interface I + (void)foo; @end
/// \endcode
AST_MATCHER(ObjCMethodDecl, isInstanceMethod) {
return Node.isInstanceMethod();
}
/// Returns true when the Objective-C message is sent to a class.
///
/// Example
/// matcher = objcMessageExpr(isClassMessage())
/// matches
/// \code
/// [NSString stringWithFormat:@"format"];
/// \endcode
/// but not
/// \code
/// NSString *x = @"hello";
/// [x containsString:@"h"];
/// \endcode
AST_MATCHER(ObjCMessageExpr, isClassMessage) {
return Node.isClassMessage();
}
/// Returns true when the Objective-C message is sent to an instance.
///
/// Example
/// matcher = objcMessageExpr(isInstanceMessage())
/// matches
/// \code
/// NSString *x = @"hello";
/// [x containsString:@"h"];
/// \endcode
/// but not
/// \code
/// [NSString stringWithFormat:@"format"];
/// \endcode
AST_MATCHER(ObjCMessageExpr, isInstanceMessage) {
return Node.isInstanceMessage();
}
/// Matches if the Objective-C message is sent to an instance,
/// and the inner matcher matches on that instance.
///
/// For example the method call in
/// \code
/// NSString *x = @"hello";
/// [x containsString:@"h"];
/// \endcode
/// is matched by
/// objcMessageExpr(hasReceiver(declRefExpr(to(varDecl(hasName("x"))))))
AST_MATCHER_P(ObjCMessageExpr, hasReceiver, internal::Matcher<Expr>,
InnerMatcher) {
const Expr *ReceiverNode = Node.getInstanceReceiver();
return (ReceiverNode != nullptr &&
InnerMatcher.matches(*ReceiverNode->IgnoreParenImpCasts(), Finder,
Builder));
}
/// Matches when BaseName == Selector.getAsString()
///
/// matcher = objCMessageExpr(hasSelector("loadHTMLString:baseURL:"));
/// matches the outer message expr in the code below, but NOT the message
/// invocation for self.bodyView.
/// \code
/// [self.bodyView loadHTMLString:html baseURL:NULL];
/// \endcode
AST_MATCHER_P(ObjCMessageExpr, hasSelector, std::string, BaseName) {
Selector Sel = Node.getSelector();
return BaseName.compare(Sel.getAsString()) == 0;
}
/// Matches when at least one of the supplied string equals to the
/// Selector.getAsString()
///
/// matcher = objCMessageExpr(hasSelector("methodA:", "methodB:"));
/// matches both of the expressions below:
/// \code
/// [myObj methodA:argA];
/// [myObj methodB:argB];
/// \endcode
extern const internal::VariadicFunction<internal::Matcher<ObjCMessageExpr>,
StringRef,
internal::hasAnySelectorFunc>
hasAnySelector;
/// Matches ObjC selectors whose name contains
/// a substring matched by the given RegExp.
/// matcher = objCMessageExpr(matchesSelector("loadHTMLString\:baseURL?"));
/// matches the outer message expr in the code below, but NOT the message
/// invocation for self.bodyView.
/// \code
/// [self.bodyView loadHTMLString:html baseURL:NULL];
/// \endcode
AST_MATCHER_P(ObjCMessageExpr, matchesSelector, std::string, RegExp) {
assert(!RegExp.empty());
std::string SelectorString = Node.getSelector().getAsString();
llvm::Regex RE(RegExp);
return RE.match(SelectorString);
}
/// Matches when the selector is the empty selector
///
/// Matches only when the selector of the objCMessageExpr is NULL. This may
/// represent an error condition in the tree!
AST_MATCHER(ObjCMessageExpr, hasNullSelector) {
return Node.getSelector().isNull();
}
/// Matches when the selector is a Unary Selector
///
/// matcher = objCMessageExpr(matchesSelector(hasUnarySelector());
/// matches self.bodyView in the code below, but NOT the outer message
/// invocation of "loadHTMLString:baseURL:".
/// \code
/// [self.bodyView loadHTMLString:html baseURL:NULL];
/// \endcode
AST_MATCHER(ObjCMessageExpr, hasUnarySelector) {
return Node.getSelector().isUnarySelector();
}
/// Matches when the selector is a keyword selector
///
/// objCMessageExpr(hasKeywordSelector()) matches the generated setFrame
/// message expression in
///
/// \code
/// UIWebView *webView = ...;
/// CGRect bodyFrame = webView.frame;
/// bodyFrame.size.height = self.bodyContentHeight;
/// webView.frame = bodyFrame;
/// // ^---- matches here
/// \endcode
AST_MATCHER(ObjCMessageExpr, hasKeywordSelector) {
return Node.getSelector().isKeywordSelector();
}
/// Matches when the selector has the specified number of arguments
///
/// matcher = objCMessageExpr(numSelectorArgs(0));
/// matches self.bodyView in the code below
///
/// matcher = objCMessageExpr(numSelectorArgs(2));
/// matches the invocation of "loadHTMLString:baseURL:" but not that
/// of self.bodyView
/// \code
/// [self.bodyView loadHTMLString:html baseURL:NULL];
/// \endcode
AST_MATCHER_P(ObjCMessageExpr, numSelectorArgs, unsigned, N) {
return Node.getSelector().getNumArgs() == N;
}
/// Matches if the call expression's callee expression matches.
///
/// Given
/// \code
/// class Y { void x() { this->x(); x(); Y y; y.x(); } };
/// void f() { f(); }
/// \endcode
/// callExpr(callee(expr()))
/// matches this->x(), x(), y.x(), f()
/// with callee(...)
/// matching this->x, x, y.x, f respectively
///
/// Note: Callee cannot take the more general internal::Matcher<Expr>
/// because this introduces ambiguous overloads with calls to Callee taking a
/// internal::Matcher<Decl>, as the matcher hierarchy is purely
/// implemented in terms of implicit casts.
AST_MATCHER_P(CallExpr, callee, internal::Matcher<Stmt>,
InnerMatcher) {
const Expr *ExprNode = Node.getCallee();
return (ExprNode != nullptr &&
InnerMatcher.matches(*ExprNode, Finder, Builder));
}
/// Matches if the call expression's callee's declaration matches the
/// given matcher.
///
/// Example matches y.x() (matcher = callExpr(callee(
/// cxxMethodDecl(hasName("x")))))
/// \code
/// class Y { public: void x(); };
/// void z() { Y y; y.x(); }
/// \endcode
AST_MATCHER_P_OVERLOAD(CallExpr, callee, internal::Matcher<Decl>, InnerMatcher,
1) {
return callExpr(hasDeclaration(InnerMatcher)).matches(Node, Finder, Builder);
}
/// Matches if the expression's or declaration's type matches a type
/// matcher.
///
/// Example matches x (matcher = expr(hasType(cxxRecordDecl(hasName("X")))))
/// and z (matcher = varDecl(hasType(cxxRecordDecl(hasName("X")))))
/// and U (matcher = typedefDecl(hasType(asString("int")))
/// and friend class X (matcher = friendDecl(hasType("X"))
/// \code
/// class X {};
/// void y(X &x) { x; X z; }
/// typedef int U;
/// class Y { friend class X; };
/// \endcode
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(
hasType,
AST_POLYMORPHIC_SUPPORTED_TYPES(Expr, FriendDecl, TypedefNameDecl,
ValueDecl),
internal::Matcher<QualType>, InnerMatcher, 0) {
QualType QT = internal::getUnderlyingType(Node);
if (!QT.isNull())
return InnerMatcher.matches(QT, Finder, Builder);
return false;
}
/// Overloaded to match the declaration of the expression's or value
/// declaration's type.
///
/// In case of a value declaration (for example a variable declaration),
/// this resolves one layer of indirection. For example, in the value
/// declaration "X x;", cxxRecordDecl(hasName("X")) matches the declaration of
/// X, while varDecl(hasType(cxxRecordDecl(hasName("X")))) matches the
/// declaration of x.
///
/// Example matches x (matcher = expr(hasType(cxxRecordDecl(hasName("X")))))
/// and z (matcher = varDecl(hasType(cxxRecordDecl(hasName("X")))))
/// and friend class X (matcher = friendDecl(hasType("X"))
/// \code
/// class X {};
/// void y(X &x) { x; X z; }
/// class Y { friend class X; };
/// \endcode
///
/// Example matches class Derived
/// (matcher = cxxRecordDecl(hasAnyBase(hasType(cxxRecordDecl(hasName("Base"))))))
/// \code
/// class Base {};
/// class Derived : Base {};
/// \endcode
///
/// Usable as: Matcher<Expr>, Matcher<FriendDecl>, Matcher<ValueDecl>,
/// Matcher<CXXBaseSpecifier>
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(
hasType,
AST_POLYMORPHIC_SUPPORTED_TYPES(Expr, FriendDecl, ValueDecl,
CXXBaseSpecifier),
internal::Matcher<Decl>, InnerMatcher, 1) {
QualType QT = internal::getUnderlyingType(Node);
if (!QT.isNull())
return qualType(hasDeclaration(InnerMatcher)).matches(QT, Finder, Builder);
return false;
}
/// Matches if the type location of the declarator decl's type matches
/// the inner matcher.
///
/// Given
/// \code
/// int x;
/// \endcode
/// declaratorDecl(hasTypeLoc(loc(asString("int"))))
/// matches int x
AST_MATCHER_P(DeclaratorDecl, hasTypeLoc, internal::Matcher<TypeLoc>, Inner) {
if (!Node.getTypeSourceInfo())
// This happens for example for implicit destructors.
return false;
return Inner.matches(Node.getTypeSourceInfo()->getTypeLoc(), Finder, Builder);
}
/// Matches if the matched type is represented by the given string.
///
/// Given
/// \code
/// class Y { public: void x(); };
/// void z() { Y* y; y->x(); }
/// \endcode
/// cxxMemberCallExpr(on(hasType(asString("class Y *"))))
/// matches y->x()
AST_MATCHER_P(QualType, asString, std::string, Name) {
return Name == Node.getAsString();
}
/// Matches if the matched type is a pointer type and the pointee type
/// matches the specified matcher.
///
/// Example matches y->x()
/// (matcher = cxxMemberCallExpr(on(hasType(pointsTo
/// cxxRecordDecl(hasName("Y")))))))
/// \code
/// class Y { public: void x(); };
/// void z() { Y *y; y->x(); }
/// \endcode
AST_MATCHER_P(
QualType, pointsTo, internal::Matcher<QualType>,
InnerMatcher) {
return (!Node.isNull() && Node->isAnyPointerType() &&
InnerMatcher.matches(Node->getPointeeType(), Finder, Builder));
}
/// Overloaded to match the pointee type's declaration.
AST_MATCHER_P_OVERLOAD(QualType, pointsTo, internal::Matcher<Decl>,
InnerMatcher, 1) {
return pointsTo(qualType(hasDeclaration(InnerMatcher)))
.matches(Node, Finder, Builder);
}
/// Matches if the matched type matches the unqualified desugared
/// type of the matched node.
///
/// For example, in:
/// \code
/// class A {};
/// using B = A;
/// \endcode
/// The matcher type(hasUnqualifiedDesugaredType(recordType())) matches
/// both B and A.
AST_MATCHER_P(Type, hasUnqualifiedDesugaredType, internal::Matcher<Type>,
InnerMatcher) {
return InnerMatcher.matches(*Node.getUnqualifiedDesugaredType(), Finder,
Builder);
}
/// Matches if the matched type is a reference type and the referenced
/// type matches the specified matcher.
///
/// Example matches X &x and const X &y
/// (matcher = varDecl(hasType(references(cxxRecordDecl(hasName("X"))))))
/// \code
/// class X {
/// void a(X b) {
/// X &x = b;
/// const X &y = b;
/// }
/// };
/// \endcode
AST_MATCHER_P(QualType, references, internal::Matcher<QualType>,
InnerMatcher) {
return (!Node.isNull() && Node->isReferenceType() &&
InnerMatcher.matches(Node->getPointeeType(), Finder, Builder));
}
/// Matches QualTypes whose canonical type matches InnerMatcher.
///
/// Given:
/// \code
/// typedef int &int_ref;
/// int a;
/// int_ref b = a;
/// \endcode
///
/// \c varDecl(hasType(qualType(referenceType()))))) will not match the
/// declaration of b but \c
/// varDecl(hasType(qualType(hasCanonicalType(referenceType())))))) does.
AST_MATCHER_P(QualType, hasCanonicalType, internal::Matcher<QualType>,
InnerMatcher) {
if (Node.isNull())
return false;
return InnerMatcher.matches(Node.getCanonicalType(), Finder, Builder);
}
/// Overloaded to match the referenced type's declaration.
AST_MATCHER_P_OVERLOAD(QualType, references, internal::Matcher<Decl>,
InnerMatcher, 1) {
return references(qualType(hasDeclaration(InnerMatcher)))
.matches(Node, Finder, Builder);
}
/// Matches on the implicit object argument of a member call expression. Unlike
/// `on`, matches the argument directly without stripping away anything.
///
/// Given
/// \code
/// class Y { public: void m(); };
/// Y g();
/// class X : public Y { void g(); };
/// void z(Y y, X x) { y.m(); x.m(); x.g(); (g()).m(); }
/// \endcode
/// cxxMemberCallExpr(onImplicitObjectArgument(hasType(
/// cxxRecordDecl(hasName("Y")))))
/// matches `y.m()`, `x.m()` and (g()).m(), but not `x.g()`.
/// cxxMemberCallExpr(on(callExpr()))
/// does not match `(g()).m()`, because the parens are not ignored.
///
/// FIXME: Overload to allow directly matching types?
AST_MATCHER_P(CXXMemberCallExpr, onImplicitObjectArgument,
internal::Matcher<Expr>, InnerMatcher) {
const Expr *ExprNode = Node.getImplicitObjectArgument();
return (ExprNode != nullptr &&
InnerMatcher.matches(*ExprNode, Finder, Builder));
}
/// Matches if the type of the expression's implicit object argument either
/// matches the InnerMatcher, or is a pointer to a type that matches the
/// InnerMatcher.
///
/// Given
/// \code
/// class Y { public: void m(); };
/// class X : public Y { void g(); };
/// void z() { Y y; y.m(); Y *p; p->m(); X x; x.m(); x.g(); }
/// \endcode
/// cxxMemberCallExpr(thisPointerType(hasDeclaration(
/// cxxRecordDecl(hasName("Y")))))
/// matches `y.m()`, `p->m()` and `x.m()`.
/// cxxMemberCallExpr(thisPointerType(hasDeclaration(
/// cxxRecordDecl(hasName("X")))))
/// matches `x.g()`.
AST_MATCHER_P_OVERLOAD(CXXMemberCallExpr, thisPointerType,
internal::Matcher<QualType>, InnerMatcher, 0) {
return onImplicitObjectArgument(
anyOf(hasType(InnerMatcher), hasType(pointsTo(InnerMatcher))))
.matches(Node, Finder, Builder);
}
/// Overloaded to match the type's declaration.
AST_MATCHER_P_OVERLOAD(CXXMemberCallExpr, thisPointerType,
internal::Matcher<Decl>, InnerMatcher, 1) {
return onImplicitObjectArgument(
anyOf(hasType(InnerMatcher), hasType(pointsTo(InnerMatcher))))
.matches(Node, Finder, Builder);
}
/// Matches a DeclRefExpr that refers to a declaration that matches the
/// specified matcher.
///
/// Example matches x in if(x)
/// (matcher = declRefExpr(to(varDecl(hasName("x")))))
/// \code
/// bool x;
/// if (x) {}
/// \endcode
AST_MATCHER_P(DeclRefExpr, to, internal::Matcher<Decl>,
InnerMatcher) {
const Decl *DeclNode = Node.getDecl();
return (DeclNode != nullptr &&
InnerMatcher.matches(*DeclNode, Finder, Builder));
}
/// Matches a \c DeclRefExpr that refers to a declaration through a
/// specific using shadow declaration.
///
/// Given
/// \code
/// namespace a { void f() {} }
/// using a::f;
/// void g() {
/// f(); // Matches this ..
/// a::f(); // .. but not this.
/// }
/// \endcode
/// declRefExpr(throughUsingDecl(anything()))
/// matches \c f()
AST_MATCHER_P(DeclRefExpr, throughUsingDecl,
internal::Matcher<UsingShadowDecl>, InnerMatcher) {
const NamedDecl *FoundDecl = Node.getFoundDecl();
if (const UsingShadowDecl *UsingDecl = dyn_cast<UsingShadowDecl>(FoundDecl))
return InnerMatcher.matches(*UsingDecl, Finder, Builder);
return false;
}
/// Matches an \c OverloadExpr if any of the declarations in the set of
/// overloads matches the given matcher.
///
/// Given
/// \code
/// template <typename T> void foo(T);
/// template <typename T> void bar(T);
/// template <typename T> void baz(T t) {
/// foo(t);
/// bar(t);
/// }
/// \endcode
/// unresolvedLookupExpr(hasAnyDeclaration(
/// functionTemplateDecl(hasName("foo"))))
/// matches \c foo in \c foo(t); but not \c bar in \c bar(t);
AST_MATCHER_P(OverloadExpr, hasAnyDeclaration, internal::Matcher<Decl>,
InnerMatcher) {
return matchesFirstInPointerRange(InnerMatcher, Node.decls_begin(),
Node.decls_end(), Finder, Builder);
}
/// Matches the Decl of a DeclStmt which has a single declaration.
///
/// Given
/// \code
/// int a, b;
/// int c;
/// \endcode
/// declStmt(hasSingleDecl(anything()))
/// matches 'int c;' but not 'int a, b;'.
AST_MATCHER_P(DeclStmt, hasSingleDecl, internal::Matcher<Decl>, InnerMatcher) {
if (Node.isSingleDecl()) {
const Decl *FoundDecl = Node.getSingleDecl();
return InnerMatcher.matches(*FoundDecl, Finder, Builder);
}
return false;
}
/// Matches a variable declaration that has an initializer expression
/// that matches the given matcher.
///
/// Example matches x (matcher = varDecl(hasInitializer(callExpr())))
/// \code
/// bool y() { return true; }
/// bool x = y();
/// \endcode
AST_MATCHER_P(
VarDecl, hasInitializer, internal::Matcher<Expr>,
InnerMatcher) {
const Expr *Initializer = Node.getAnyInitializer();
return (Initializer != nullptr &&
InnerMatcher.matches(*Initializer, Finder, Builder));
}
/// \brief Matches a static variable with local scope.
///
/// Example matches y (matcher = varDecl(isStaticLocal()))
/// \code
/// void f() {
/// int x;
/// static int y;
/// }
/// static int z;
/// \endcode
AST_MATCHER(VarDecl, isStaticLocal) {
return Node.isStaticLocal();
}
/// Matches a variable declaration that has function scope and is a
/// non-static local variable.
///
/// Example matches x (matcher = varDecl(hasLocalStorage())
/// \code
/// void f() {
/// int x;
/// static int y;
/// }
/// int z;
/// \endcode
AST_MATCHER(VarDecl, hasLocalStorage) {
return Node.hasLocalStorage();
}
/// Matches a variable declaration that does not have local storage.
///
/// Example matches y and z (matcher = varDecl(hasGlobalStorage())
/// \code
/// void f() {
/// int x;
/// static int y;
/// }
/// int z;
/// \endcode
AST_MATCHER(VarDecl, hasGlobalStorage) {
return Node.hasGlobalStorage();
}
/// Matches a variable declaration that has automatic storage duration.
///
/// Example matches x, but not y, z, or a.
/// (matcher = varDecl(hasAutomaticStorageDuration())
/// \code
/// void f() {
/// int x;
/// static int y;
/// thread_local int z;
/// }
/// int a;
/// \endcode
AST_MATCHER(VarDecl, hasAutomaticStorageDuration) {
return Node.getStorageDuration() == SD_Automatic;
}
/// Matches a variable declaration that has static storage duration.
/// It includes the variable declared at namespace scope and those declared
/// with "static" and "extern" storage class specifiers.
///
/// \code
/// void f() {
/// int x;
/// static int y;
/// thread_local int z;
/// }
/// int a;
/// static int b;
/// extern int c;
/// varDecl(hasStaticStorageDuration())
/// matches the function declaration y, a, b and c.
/// \endcode
AST_MATCHER(VarDecl, hasStaticStorageDuration) {
return Node.getStorageDuration() == SD_Static;
}
/// Matches a variable declaration that has thread storage duration.
///
/// Example matches z, but not x, z, or a.
/// (matcher = varDecl(hasThreadStorageDuration())
/// \code
/// void f() {
/// int x;
/// static int y;
/// thread_local int z;
/// }
/// int a;
/// \endcode
AST_MATCHER(VarDecl, hasThreadStorageDuration) {
return Node.getStorageDuration() == SD_Thread;
}
/// Matches a variable declaration that is an exception variable from
/// a C++ catch block, or an Objective-C \@catch statement.
///
/// Example matches x (matcher = varDecl(isExceptionVariable())
/// \code
/// void f(int y) {
/// try {
/// } catch (int x) {
/// }
/// }
/// \endcode
AST_MATCHER(VarDecl, isExceptionVariable) {
return Node.isExceptionVariable();
}
/// Checks that a call expression or a constructor call expression has
/// a specific number of arguments (including absent default arguments).
///
/// Example matches f(0, 0) (matcher = callExpr(argumentCountIs(2)))
/// \code
/// void f(int x, int y);
/// f(0, 0);
/// \endcode
AST_POLYMORPHIC_MATCHER_P(argumentCountIs,
AST_POLYMORPHIC_SUPPORTED_TYPES(CallExpr,
CXXConstructExpr,
ObjCMessageExpr),
unsigned, N) {
return Node.getNumArgs() == N;
}
/// Matches the n'th argument of a call expression or a constructor
/// call expression.
///
/// Example matches y in x(y)
/// (matcher = callExpr(hasArgument(0, declRefExpr())))
/// \code
/// void x(int) { int y; x(y); }
/// \endcode
AST_POLYMORPHIC_MATCHER_P2(hasArgument,
AST_POLYMORPHIC_SUPPORTED_TYPES(CallExpr,
CXXConstructExpr,
ObjCMessageExpr),
unsigned, N, internal::Matcher<Expr>, InnerMatcher) {
return (N < Node.getNumArgs() &&
InnerMatcher.matches(
*Node.getArg(N)->IgnoreParenImpCasts(), Finder, Builder));
}
/// Matches the n'th item of an initializer list expression.
///
/// Example matches y.
/// (matcher = initListExpr(hasInit(0, expr())))
/// \code
/// int x{y}.
/// \endcode
AST_MATCHER_P2(InitListExpr, hasInit, unsigned, N,
ast_matchers::internal::Matcher<Expr>, InnerMatcher) {
return N < Node.getNumInits() &&
InnerMatcher.matches(*Node.getInit(N), Finder, Builder);
}
/// Matches declaration statements that contain a specific number of
/// declarations.
///
/// Example: Given
/// \code
/// int a, b;
/// int c;
/// int d = 2, e;
/// \endcode
/// declCountIs(2)
/// matches 'int a, b;' and 'int d = 2, e;', but not 'int c;'.
AST_MATCHER_P(DeclStmt, declCountIs, unsigned, N) {
return std::distance(Node.decl_begin(), Node.decl_end()) == (ptrdiff_t)N;
}
/// Matches the n'th declaration of a declaration statement.
///
/// Note that this does not work for global declarations because the AST
/// breaks up multiple-declaration DeclStmt's into multiple single-declaration
/// DeclStmt's.
/// Example: Given non-global declarations
/// \code
/// int a, b = 0;
/// int c;
/// int d = 2, e;
/// \endcode
/// declStmt(containsDeclaration(
/// 0, varDecl(hasInitializer(anything()))))
/// matches only 'int d = 2, e;', and
/// declStmt(containsDeclaration(1, varDecl()))
/// \code
/// matches 'int a, b = 0' as well as 'int d = 2, e;'
/// but 'int c;' is not matched.
/// \endcode
AST_MATCHER_P2(DeclStmt, containsDeclaration, unsigned, N,
internal::Matcher<Decl>, InnerMatcher) {
const unsigned NumDecls = std::distance(Node.decl_begin(), Node.decl_end());
if (N >= NumDecls)
return false;
DeclStmt::const_decl_iterator Iterator = Node.decl_begin();
std::advance(Iterator, N);
return InnerMatcher.matches(**Iterator, Finder, Builder);
}
/// Matches a C++ catch statement that has a catch-all handler.
///
/// Given
/// \code
/// try {
/// // ...
/// } catch (int) {
/// // ...
/// } catch (...) {
/// // ...
/// }
/// \endcode
/// cxxCatchStmt(isCatchAll()) matches catch(...) but not catch(int).
AST_MATCHER(CXXCatchStmt, isCatchAll) {
return Node.getExceptionDecl() == nullptr;
}
/// Matches a constructor initializer.
///
/// Given
/// \code
/// struct Foo {
/// Foo() : foo_(1) { }
/// int foo_;
/// };
/// \endcode
/// cxxRecordDecl(has(cxxConstructorDecl(
/// hasAnyConstructorInitializer(anything())
/// )))
/// record matches Foo, hasAnyConstructorInitializer matches foo_(1)
AST_MATCHER_P(CXXConstructorDecl, hasAnyConstructorInitializer,
internal::Matcher<CXXCtorInitializer>, InnerMatcher) {
return matchesFirstInPointerRange(InnerMatcher, Node.init_begin(),
Node.init_end(), Finder, Builder);
}
/// Matches the field declaration of a constructor initializer.
///
/// Given
/// \code
/// struct Foo {
/// Foo() : foo_(1) { }
/// int foo_;
/// };
/// \endcode
/// cxxRecordDecl(has(cxxConstructorDecl(hasAnyConstructorInitializer(
/// forField(hasName("foo_"))))))
/// matches Foo
/// with forField matching foo_
AST_MATCHER_P(CXXCtorInitializer, forField,
internal::Matcher<FieldDecl>, InnerMatcher) {
const FieldDecl *NodeAsDecl = Node.getAnyMember();
return (NodeAsDecl != nullptr &&
InnerMatcher.matches(*NodeAsDecl, Finder, Builder));
}
/// Matches the initializer expression of a constructor initializer.
///
/// Given
/// \code
/// struct Foo {
/// Foo() : foo_(1) { }
/// int foo_;
/// };
/// \endcode
/// cxxRecordDecl(has(cxxConstructorDecl(hasAnyConstructorInitializer(
/// withInitializer(integerLiteral(equals(1)))))))
/// matches Foo
/// with withInitializer matching (1)
AST_MATCHER_P(CXXCtorInitializer, withInitializer,
internal::Matcher<Expr>, InnerMatcher) {
const Expr* NodeAsExpr = Node.getInit();
return (NodeAsExpr != nullptr &&
InnerMatcher.matches(*NodeAsExpr, Finder, Builder));
}
/// Matches a constructor initializer if it is explicitly written in
/// code (as opposed to implicitly added by the compiler).
///
/// Given
/// \code
/// struct Foo {
/// Foo() { }
/// Foo(int) : foo_("A") { }
/// string foo_;
/// };
/// \endcode
/// cxxConstructorDecl(hasAnyConstructorInitializer(isWritten()))
/// will match Foo(int), but not Foo()
AST_MATCHER(CXXCtorInitializer, isWritten) {
return Node.isWritten();
}
/// Matches a constructor initializer if it is initializing a base, as
/// opposed to a member.
///
/// Given
/// \code
/// struct B {};
/// struct D : B {
/// int I;
/// D(int i) : I(i) {}
/// };
/// struct E : B {
/// E() : B() {}
/// };
/// \endcode
/// cxxConstructorDecl(hasAnyConstructorInitializer(isBaseInitializer()))
/// will match E(), but not match D(int).
AST_MATCHER(CXXCtorInitializer, isBaseInitializer) {
return Node.isBaseInitializer();
}
/// Matches a constructor initializer if it is initializing a member, as
/// opposed to a base.
///
/// Given
/// \code
/// struct B {};
/// struct D : B {
/// int I;
/// D(int i) : I(i) {}
/// };
/// struct E : B {
/// E() : B() {}
/// };
/// \endcode
/// cxxConstructorDecl(hasAnyConstructorInitializer(isMemberInitializer()))
/// will match D(int), but not match E().
AST_MATCHER(CXXCtorInitializer, isMemberInitializer) {
return Node.isMemberInitializer();
}
/// Matches any argument of a call expression or a constructor call
/// expression, or an ObjC-message-send expression.
///
/// Given
/// \code
/// void x(int, int, int) { int y; x(1, y, 42); }
/// \endcode
/// callExpr(hasAnyArgument(declRefExpr()))
/// matches x(1, y, 42)
/// with hasAnyArgument(...)
/// matching y
///
/// For ObjectiveC, given
/// \code
/// @interface I - (void) f:(int) y; @end
/// void foo(I *i) { [i f:12]; }
/// \endcode
/// objcMessageExpr(hasAnyArgument(integerLiteral(equals(12))))
/// matches [i f:12]
AST_POLYMORPHIC_MATCHER_P(hasAnyArgument,
AST_POLYMORPHIC_SUPPORTED_TYPES(
CallExpr, CXXConstructExpr,
CXXUnresolvedConstructExpr, ObjCMessageExpr),
internal::Matcher<Expr>, InnerMatcher) {
for (const Expr *Arg : Node.arguments()) {
BoundNodesTreeBuilder Result(*Builder);
if (InnerMatcher.matches(*Arg, Finder, &Result)) {
*Builder = std::move(Result);
return true;
}
}
return false;
}
/// Matches any capture of a lambda expression.
///
/// Given
/// \code
/// void foo() {
/// int x;
/// auto f = [x](){};
/// }
/// \endcode
/// lambdaExpr(hasAnyCapture(anything()))
/// matches [x](){};
AST_MATCHER_P_OVERLOAD(LambdaExpr, hasAnyCapture, internal::Matcher<VarDecl>,
InnerMatcher, 0) {
for (const LambdaCapture &Capture : Node.captures()) {
if (Capture.capturesVariable()) {
BoundNodesTreeBuilder Result(*Builder);
if (InnerMatcher.matches(*Capture.getCapturedVar(), Finder, &Result)) {
*Builder = std::move(Result);
return true;
}
}
}
return false;
}
/// Matches any capture of 'this' in a lambda expression.
///
/// Given
/// \code
/// struct foo {
/// void bar() {
/// auto f = [this](){};
/// }
/// }
/// \endcode
/// lambdaExpr(hasAnyCapture(cxxThisExpr()))
/// matches [this](){};
AST_MATCHER_P_OVERLOAD(LambdaExpr, hasAnyCapture,
internal::Matcher<CXXThisExpr>, InnerMatcher, 1) {
return llvm::any_of(Node.captures(), [](const LambdaCapture &LC) {
return LC.capturesThis();
});
}
/// Matches a constructor call expression which uses list initialization.
AST_MATCHER(CXXConstructExpr, isListInitialization) {
return Node.isListInitialization();
}
/// Matches a constructor call expression which requires
/// zero initialization.
///
/// Given
/// \code
/// void foo() {
/// struct point { double x; double y; };
/// point pt[2] = { { 1.0, 2.0 } };
/// }
/// \endcode
/// initListExpr(has(cxxConstructExpr(requiresZeroInitialization()))
/// will match the implicit array filler for pt[1].
AST_MATCHER(CXXConstructExpr, requiresZeroInitialization) {
return Node.requiresZeroInitialization();
}
/// Matches the n'th parameter of a function or an ObjC method
/// declaration or a block.
///
/// Given
/// \code
/// class X { void f(int x) {} };
/// \endcode
/// cxxMethodDecl(hasParameter(0, hasType(varDecl())))
/// matches f(int x) {}
/// with hasParameter(...)
/// matching int x
///
/// For ObjectiveC, given
/// \code
/// @interface I - (void) f:(int) y; @end
/// \endcode
//
/// the matcher objcMethodDecl(hasParameter(0, hasName("y")))
/// matches the declaration of method f with hasParameter
/// matching y.
AST_POLYMORPHIC_MATCHER_P2(hasParameter,
AST_POLYMORPHIC_SUPPORTED_TYPES(FunctionDecl,
ObjCMethodDecl,
BlockDecl),
unsigned, N, internal::Matcher<ParmVarDecl>,
InnerMatcher) {
return (N < Node.parameters().size()
&& InnerMatcher.matches(*Node.parameters()[N], Finder, Builder));
}
/// Matches all arguments and their respective ParmVarDecl.
///
/// Given
/// \code
/// void f(int i);
/// int y;
/// f(y);
/// \endcode
/// callExpr(
/// forEachArgumentWithParam(
/// declRefExpr(to(varDecl(hasName("y")))),
/// parmVarDecl(hasType(isInteger()))
/// ))
/// matches f(y);
/// with declRefExpr(...)
/// matching int y
/// and parmVarDecl(...)
/// matching int i
AST_POLYMORPHIC_MATCHER_P2(forEachArgumentWithParam,
AST_POLYMORPHIC_SUPPORTED_TYPES(CallExpr,
CXXConstructExpr),
internal::Matcher<Expr>, ArgMatcher,
internal::Matcher<ParmVarDecl>, ParamMatcher) {
BoundNodesTreeBuilder Result;
// The first argument of an overloaded member operator is the implicit object
// argument of the method which should not be matched against a parameter, so
// we skip over it here.
BoundNodesTreeBuilder Matches;
unsigned ArgIndex = cxxOperatorCallExpr(callee(cxxMethodDecl()))
.matches(Node, Finder, &Matches)
? 1
: 0;
int ParamIndex = 0;
bool Matched = false;
for (; ArgIndex < Node.getNumArgs(); ++ArgIndex) {
BoundNodesTreeBuilder ArgMatches(*Builder);
if (ArgMatcher.matches(*(Node.getArg(ArgIndex)->IgnoreParenCasts()),
Finder, &ArgMatches)) {
BoundNodesTreeBuilder ParamMatches(ArgMatches);
if (expr(anyOf(cxxConstructExpr(hasDeclaration(cxxConstructorDecl(
hasParameter(ParamIndex, ParamMatcher)))),
callExpr(callee(functionDecl(
hasParameter(ParamIndex, ParamMatcher))))))
.matches(Node, Finder, &ParamMatches)) {
Result.addMatch(ParamMatches);
Matched = true;
}
}
++ParamIndex;
}
*Builder = std::move(Result);
return Matched;
}
/// Matches the ParmVarDecl nodes that are at the N'th position in the parameter
/// list. The parameter list could be that of either a block, function, or
/// objc-method.
///
///
/// Given
///
/// \code
/// void f(int a, int b, int c) {
/// }
/// \endcode
///
/// ``parmVarDecl(isAtPosition(0))`` matches ``int a``.
///
/// ``parmVarDecl(isAtPosition(1))`` matches ``int b``.
AST_MATCHER_P(clang::ParmVarDecl, isAtPosition, unsigned, N) {
const clang::DeclContext *Context = Node.getParentFunctionOrMethod();
if (const auto *Decl = dyn_cast_or_null<FunctionDecl>(Context))
return N < Decl->param_size() && Decl->getParamDecl(N) == &Node;
if (const auto *Decl = dyn_cast_or_null<BlockDecl>(Context))
return N < Decl->param_size() && Decl->getParamDecl(N) == &Node;
if (const auto *Decl = dyn_cast_or_null<ObjCMethodDecl>(Context))
return N < Decl->param_size() && Decl->getParamDecl(N) == &Node;
return false;
}
/// Matches any parameter of a function or an ObjC method declaration or a
/// block.
///
/// Does not match the 'this' parameter of a method.
///
/// Given
/// \code
/// class X { void f(int x, int y, int z) {} };
/// \endcode
/// cxxMethodDecl(hasAnyParameter(hasName("y")))
/// matches f(int x, int y, int z) {}
/// with hasAnyParameter(...)
/// matching int y
///
/// For ObjectiveC, given
/// \code
/// @interface I - (void) f:(int) y; @end
/// \endcode
//
/// the matcher objcMethodDecl(hasAnyParameter(hasName("y")))
/// matches the declaration of method f with hasParameter
/// matching y.
///
/// For blocks, given
/// \code
/// b = ^(int y) { printf("%d", y) };
/// \endcode
///
/// the matcher blockDecl(hasAnyParameter(hasName("y")))
/// matches the declaration of the block b with hasParameter
/// matching y.
AST_POLYMORPHIC_MATCHER_P(hasAnyParameter,
AST_POLYMORPHIC_SUPPORTED_TYPES(FunctionDecl,
ObjCMethodDecl,
BlockDecl),
internal::Matcher<ParmVarDecl>,
InnerMatcher) {
return matchesFirstInPointerRange(InnerMatcher, Node.param_begin(),
Node.param_end(), Finder, Builder);
}
/// Matches \c FunctionDecls and \c FunctionProtoTypes that have a
/// specific parameter count.
///
/// Given
/// \code
/// void f(int i) {}
/// void g(int i, int j) {}
/// void h(int i, int j);
/// void j(int i);
/// void k(int x, int y, int z, ...);
/// \endcode
/// functionDecl(parameterCountIs(2))
/// matches \c g and \c h
/// functionProtoType(parameterCountIs(2))
/// matches \c g and \c h
/// functionProtoType(parameterCountIs(3))
/// matches \c k
AST_POLYMORPHIC_MATCHER_P(parameterCountIs,
AST_POLYMORPHIC_SUPPORTED_TYPES(FunctionDecl,
FunctionProtoType),
unsigned, N) {
return Node.getNumParams() == N;
}
/// Matches \c FunctionDecls that have a noreturn attribute.
///
/// Given
/// \code
/// void nope();
/// [[noreturn]] void a();
/// __attribute__((noreturn)) void b();
/// struct c { [[noreturn]] c(); };
/// \endcode
/// functionDecl(isNoReturn())
/// matches all of those except
/// \code
/// void nope();
/// \endcode
AST_MATCHER(FunctionDecl, isNoReturn) { return Node.isNoReturn(); }
/// Matches the return type of a function declaration.
///
/// Given:
/// \code
/// class X { int f() { return 1; } };
/// \endcode
/// cxxMethodDecl(returns(asString("int")))
/// matches int f() { return 1; }
AST_MATCHER_P(FunctionDecl, returns,
internal::Matcher<QualType>, InnerMatcher) {
return InnerMatcher.matches(Node.getReturnType(), Finder, Builder);
}
/// Matches extern "C" function or variable declarations.
///
/// Given:
/// \code
/// extern "C" void f() {}
/// extern "C" { void g() {} }
/// void h() {}
/// extern "C" int x = 1;
/// extern "C" int y = 2;
/// int z = 3;
/// \endcode
/// functionDecl(isExternC())
/// matches the declaration of f and g, but not the declaration of h.
/// varDecl(isExternC())
/// matches the declaration of x and y, but not the declaration of z.
AST_POLYMORPHIC_MATCHER(isExternC, AST_POLYMORPHIC_SUPPORTED_TYPES(FunctionDecl,
VarDecl)) {
return Node.isExternC();
}
/// Matches variable/function declarations that have "static" storage
/// class specifier ("static" keyword) written in the source.
///
/// Given:
/// \code
/// static void f() {}
/// static int i = 0;
/// extern int j;
/// int k;
/// \endcode
/// functionDecl(isStaticStorageClass())
/// matches the function declaration f.
/// varDecl(isStaticStorageClass())
/// matches the variable declaration i.
AST_POLYMORPHIC_MATCHER(isStaticStorageClass,
AST_POLYMORPHIC_SUPPORTED_TYPES(FunctionDecl,
VarDecl)) {
return Node.getStorageClass() == SC_Static;
}
/// Matches deleted function declarations.
///
/// Given:
/// \code
/// void Func();
/// void DeletedFunc() = delete;
/// \endcode
/// functionDecl(isDeleted())
/// matches the declaration of DeletedFunc, but not Func.
AST_MATCHER(FunctionDecl, isDeleted) {
return Node.isDeleted();
}
/// Matches defaulted function declarations.
///
/// Given:
/// \code
/// class A { ~A(); };
/// class B { ~B() = default; };
/// \endcode
/// functionDecl(isDefaulted())
/// matches the declaration of ~B, but not ~A.
AST_MATCHER(FunctionDecl, isDefaulted) {
return Node.isDefaulted();
}
/// Matches functions that have a dynamic exception specification.
///
/// Given:
/// \code
/// void f();
/// void g() noexcept;
/// void h() noexcept(true);
/// void i() noexcept(false);
/// void j() throw();
/// void k() throw(int);
/// void l() throw(...);
/// \endcode
/// functionDecl(hasDynamicExceptionSpec()) and
/// functionProtoType(hasDynamicExceptionSpec())
/// match the declarations of j, k, and l, but not f, g, h, or i.
AST_POLYMORPHIC_MATCHER(hasDynamicExceptionSpec,
AST_POLYMORPHIC_SUPPORTED_TYPES(FunctionDecl,
FunctionProtoType)) {
if (const FunctionProtoType *FnTy = internal::getFunctionProtoType(Node))
return FnTy->hasDynamicExceptionSpec();
return false;
}
/// Matches functions that have a non-throwing exception specification.
///
/// Given:
/// \code
/// void f();
/// void g() noexcept;
/// void h() throw();
/// void i() throw(int);
/// void j() noexcept(false);
/// \endcode
/// functionDecl(isNoThrow()) and functionProtoType(isNoThrow())
/// match the declarations of g, and h, but not f, i or j.
AST_POLYMORPHIC_MATCHER(isNoThrow,
AST_POLYMORPHIC_SUPPORTED_TYPES(FunctionDecl,
FunctionProtoType)) {
const FunctionProtoType *FnTy = internal::getFunctionProtoType(Node);
// If the function does not have a prototype, then it is assumed to be a
// throwing function (as it would if the function did not have any exception
// specification).
if (!FnTy)
return false;
// Assume the best for any unresolved exception specification.
if (isUnresolvedExceptionSpec(FnTy->getExceptionSpecType()))
return true;
return FnTy->isNothrow();
}
/// Matches constexpr variable and function declarations,
/// and if constexpr.
///
/// Given:
/// \code
/// constexpr int foo = 42;
/// constexpr int bar();
/// void baz() { if constexpr(1 > 0) {} }
/// \endcode
/// varDecl(isConstexpr())
/// matches the declaration of foo.
/// functionDecl(isConstexpr())
/// matches the declaration of bar.
/// ifStmt(isConstexpr())
/// matches the if statement in baz.
AST_POLYMORPHIC_MATCHER(isConstexpr,
AST_POLYMORPHIC_SUPPORTED_TYPES(VarDecl,
FunctionDecl,
IfStmt)) {
return Node.isConstexpr();
}
/// Matches selection statements with initializer.
///
/// Given:
/// \code
/// void foo() {
/// if (int i = foobar(); i > 0) {}
/// switch (int i = foobar(); i) {}
/// for (auto& a = get_range(); auto& x : a) {}
/// }
/// void bar() {
/// if (foobar() > 0) {}
/// switch (foobar()) {}
/// for (auto& x : get_range()) {}
/// }
/// \endcode
/// ifStmt(hasInitStatement(anything()))
/// matches the if statement in foo but not in bar.
/// switchStmt(hasInitStatement(anything()))
/// matches the switch statement in foo but not in bar.
/// cxxForRangeStmt(hasInitStatement(anything()))
/// matches the range for statement in foo but not in bar.
AST_POLYMORPHIC_MATCHER_P(hasInitStatement,
AST_POLYMORPHIC_SUPPORTED_TYPES(IfStmt, SwitchStmt,
CXXForRangeStmt),
internal::Matcher<Stmt>, InnerMatcher) {
const Stmt *Init = Node.getInit();
return Init != nullptr && InnerMatcher.matches(*Init, Finder, Builder);
}
/// Matches the condition expression of an if statement, for loop,
/// switch statement or conditional operator.
///
/// Example matches true (matcher = hasCondition(cxxBoolLiteral(equals(true))))
/// \code
/// if (true) {}
/// \endcode
AST_POLYMORPHIC_MATCHER_P(
hasCondition,
AST_POLYMORPHIC_SUPPORTED_TYPES(IfStmt, ForStmt, WhileStmt, DoStmt,
SwitchStmt, AbstractConditionalOperator),
internal::Matcher<Expr>, InnerMatcher) {
const Expr *const Condition = Node.getCond();
return (Condition != nullptr &&
InnerMatcher.matches(*Condition, Finder, Builder));
}
/// Matches the then-statement of an if statement.
///
/// Examples matches the if statement
/// (matcher = ifStmt(hasThen(cxxBoolLiteral(equals(true)))))
/// \code
/// if (false) true; else false;
/// \endcode
AST_MATCHER_P(IfStmt, hasThen, internal::Matcher<Stmt>, InnerMatcher) {
const Stmt *const Then = Node.getThen();
return (Then != nullptr && InnerMatcher.matches(*Then, Finder, Builder));
}
/// Matches the else-statement of an if statement.
///
/// Examples matches the if statement
/// (matcher = ifStmt(hasElse(cxxBoolLiteral(equals(true)))))
/// \code
/// if (false) false; else true;
/// \endcode
AST_MATCHER_P(IfStmt, hasElse, internal::Matcher<Stmt>, InnerMatcher) {
const Stmt *const Else = Node.getElse();
return (Else != nullptr && InnerMatcher.matches(*Else, Finder, Builder));
}
/// Matches if a node equals a previously bound node.
///
/// Matches a node if it equals the node previously bound to \p ID.
///
/// Given
/// \code
/// class X { int a; int b; };
/// \endcode
/// cxxRecordDecl(
/// has(fieldDecl(hasName("a"), hasType(type().bind("t")))),
/// has(fieldDecl(hasName("b"), hasType(type(equalsBoundNode("t"))))))
/// matches the class \c X, as \c a and \c b have the same type.
///
/// Note that when multiple matches are involved via \c forEach* matchers,
/// \c equalsBoundNodes acts as a filter.
/// For example:
/// compoundStmt(
/// forEachDescendant(varDecl().bind("d")),
/// forEachDescendant(declRefExpr(to(decl(equalsBoundNode("d"))))))
/// will trigger a match for each combination of variable declaration
/// and reference to that variable declaration within a compound statement.
AST_POLYMORPHIC_MATCHER_P(equalsBoundNode,
AST_POLYMORPHIC_SUPPORTED_TYPES(Stmt, Decl, Type,
QualType),
std::string, ID) {
// FIXME: Figure out whether it makes sense to allow this
// on any other node types.
// For *Loc it probably does not make sense, as those seem
// unique. For NestedNameSepcifier it might make sense, as
// those also have pointer identity, but I'm not sure whether
// they're ever reused.
internal::NotEqualsBoundNodePredicate Predicate;
Predicate.ID = ID;
Predicate.Node = DynTypedNode::create(Node);
return Builder->removeBindings(Predicate);
}
/// Matches the condition variable statement in an if statement.
///
/// Given
/// \code
/// if (A* a = GetAPointer()) {}
/// \endcode
/// hasConditionVariableStatement(...)
/// matches 'A* a = GetAPointer()'.
AST_MATCHER_P(IfStmt, hasConditionVariableStatement,
internal::Matcher<DeclStmt>, InnerMatcher) {
const DeclStmt* const DeclarationStatement =
Node.getConditionVariableDeclStmt();
return DeclarationStatement != nullptr &&
InnerMatcher.matches(*DeclarationStatement, Finder, Builder);
}
/// Matches the index expression of an array subscript expression.
///
/// Given
/// \code
/// int i[5];
/// void f() { i[1] = 42; }
/// \endcode
/// arraySubscriptExpression(hasIndex(integerLiteral()))
/// matches \c i[1] with the \c integerLiteral() matching \c 1
AST_MATCHER_P(ArraySubscriptExpr, hasIndex,
internal::Matcher<Expr>, InnerMatcher) {
if (const Expr* Expression = Node.getIdx())
return InnerMatcher.matches(*Expression, Finder, Builder);
return false;
}
/// Matches the base expression of an array subscript expression.
///
/// Given
/// \code
/// int i[5];
/// void f() { i[1] = 42; }
/// \endcode
/// arraySubscriptExpression(hasBase(implicitCastExpr(
/// hasSourceExpression(declRefExpr()))))
/// matches \c i[1] with the \c declRefExpr() matching \c i
AST_MATCHER_P(ArraySubscriptExpr, hasBase,
internal::Matcher<Expr>, InnerMatcher) {
if (const Expr* Expression = Node.getBase())
return InnerMatcher.matches(*Expression, Finder, Builder);
return false;
}
/// Matches a 'for', 'while', 'do while' statement or a function
/// definition that has a given body.
///
/// Given
/// \code
/// for (;;) {}
/// \endcode
/// hasBody(compoundStmt())
/// matches 'for (;;) {}'
/// with compoundStmt()
/// matching '{}'
AST_POLYMORPHIC_MATCHER_P(hasBody,
AST_POLYMORPHIC_SUPPORTED_TYPES(DoStmt, ForStmt,
WhileStmt,
CXXForRangeStmt,
FunctionDecl),
internal::Matcher<Stmt>, InnerMatcher) {
const Stmt *const Statement = internal::GetBodyMatcher<NodeType>::get(Node);
return (Statement != nullptr &&
InnerMatcher.matches(*Statement, Finder, Builder));
}
/// Matches compound statements where at least one substatement matches
/// a given matcher. Also matches StmtExprs that have CompoundStmt as children.
///
/// Given
/// \code
/// { {}; 1+2; }
/// \endcode
/// hasAnySubstatement(compoundStmt())
/// matches '{ {}; 1+2; }'
/// with compoundStmt()
/// matching '{}'
AST_POLYMORPHIC_MATCHER_P(hasAnySubstatement,
AST_POLYMORPHIC_SUPPORTED_TYPES(CompoundStmt,
StmtExpr),
internal::Matcher<Stmt>, InnerMatcher) {
const CompoundStmt *CS = CompoundStmtMatcher<NodeType>::get(Node);
return CS && matchesFirstInPointerRange(InnerMatcher, CS->body_begin(),
CS->body_end(), Finder, Builder);
}
/// Checks that a compound statement contains a specific number of
/// child statements.
///
/// Example: Given
/// \code
/// { for (;;) {} }
/// \endcode
/// compoundStmt(statementCountIs(0)))
/// matches '{}'
/// but does not match the outer compound statement.
AST_MATCHER_P(CompoundStmt, statementCountIs, unsigned, N) {
return Node.size() == N;
}
/// Matches literals that are equal to the given value of type ValueT.
///
/// Given
/// \code
/// f('\0', false, 3.14, 42);
/// \endcode
/// characterLiteral(equals(0))
/// matches '\0'
/// cxxBoolLiteral(equals(false)) and cxxBoolLiteral(equals(0))
/// match false
/// floatLiteral(equals(3.14)) and floatLiteral(equals(314e-2))
/// match 3.14
/// integerLiteral(equals(42))
/// matches 42
///
/// Note that you cannot directly match a negative numeric literal because the
/// minus sign is not part of the literal: It is a unary operator whose operand
/// is the positive numeric literal. Instead, you must use a unaryOperator()
/// matcher to match the minus sign:
///
/// unaryOperator(hasOperatorName("-"),
/// hasUnaryOperand(integerLiteral(equals(13))))
///
/// Usable as: Matcher<CharacterLiteral>, Matcher<CXXBoolLiteralExpr>,
/// Matcher<FloatingLiteral>, Matcher<IntegerLiteral>
template <typename ValueT>
internal::PolymorphicMatcherWithParam1<internal::ValueEqualsMatcher, ValueT>
equals(const ValueT &Value) {
return internal::PolymorphicMatcherWithParam1<
internal::ValueEqualsMatcher,
ValueT>(Value);
}
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(equals,
AST_POLYMORPHIC_SUPPORTED_TYPES(CharacterLiteral,
CXXBoolLiteralExpr,
IntegerLiteral),
bool, Value, 0) {
return internal::ValueEqualsMatcher<NodeType, ParamT>(Value)
.matchesNode(Node);
}
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(equals,
AST_POLYMORPHIC_SUPPORTED_TYPES(CharacterLiteral,
CXXBoolLiteralExpr,
IntegerLiteral),
unsigned, Value, 1) {
return internal::ValueEqualsMatcher<NodeType, ParamT>(Value)
.matchesNode(Node);
}
AST_POLYMORPHIC_MATCHER_P_OVERLOAD(equals,
AST_POLYMORPHIC_SUPPORTED_TYPES(CharacterLiteral,
CXXBoolLiteralExpr,
FloatingLiteral,
IntegerLiteral),
double, Value, 2) {
return internal::ValueEqualsMatcher<NodeType, ParamT>(Value)
.matchesNode(Node);
}
/// Matches the operator Name of operator expressions (binary or
/// unary).
///
/// Example matches a || b (matcher = binaryOperator(hasOperatorName("||")))
/// \code
/// !(a || b)
/// \endcode
AST_POLYMORPHIC_MATCHER_P(hasOperatorName,
AST_POLYMORPHIC_SUPPORTED_TYPES(BinaryOperator,
UnaryOperator),
std::string, Name) {
return Name == Node.getOpcodeStr(Node.getOpcode());
}
/// Matches operator expressions (binary or unary) that have any of the
/// specified names.
///
/// hasAnyOperatorName("+", "-")
/// Is equivalent to
/// anyOf(hasOperatorName("+"), hasOperatorName("-"))
extern const internal::VariadicFunction<
internal::PolymorphicMatcherWithParam1<
internal::HasAnyOperatorNameMatcher, std::vector<std::string>,
AST_POLYMORPHIC_SUPPORTED_TYPES(BinaryOperator, UnaryOperator)>,
StringRef, internal::hasAnyOperatorNameFunc>
hasAnyOperatorName;
/// Matches all kinds of assignment operators.
///
/// Example 1: matches a += b (matcher = binaryOperator(isAssignmentOperator()))
/// \code
/// if (a == b)
/// a += b;
/// \endcode
///
/// Example 2: matches s1 = s2
/// (matcher = cxxOperatorCallExpr(isAssignmentOperator()))
/// \code
/// struct S { S& operator=(const S&); };
/// void x() { S s1, s2; s1 = s2; }
/// \endcode
AST_POLYMORPHIC_MATCHER(isAssignmentOperator,
AST_POLYMORPHIC_SUPPORTED_TYPES(BinaryOperator,
CXXOperatorCallExpr)) {
return Node.isAssignmentOp();
}
/// Matches comparison operators.
///
/// Example 1: matches a == b (matcher = binaryOperator(isComparisonOperator()))
/// \code
/// if (a == b)
/// a += b;
/// \endcode
///
/// Example 2: matches s1 < s2
/// (matcher = cxxOperatorCallExpr(isComparisonOperator()))
/// \code
/// struct S { bool operator<(const S& other); };
/// void x(S s1, S s2) { bool b1 = s1 < s2; }
/// \endcode
AST_POLYMORPHIC_MATCHER(isComparisonOperator,
AST_POLYMORPHIC_SUPPORTED_TYPES(BinaryOperator,
CXXOperatorCallExpr)) {
return Node.isComparisonOp();
}
/// Matches the left hand side of binary operator expressions.
///
/// Example matches a (matcher = binaryOperator(hasLHS()))
/// \code
/// a || b
/// \endcode
AST_POLYMORPHIC_MATCHER_P(hasLHS,
AST_POLYMORPHIC_SUPPORTED_TYPES(BinaryOperator,
ArraySubscriptExpr),
internal::Matcher<Expr>, InnerMatcher) {
const Expr *LeftHandSide = Node.getLHS();
return (LeftHandSide != nullptr &&
InnerMatcher.matches(*LeftHandSide, Finder, Builder));
}
/// Matches the right hand side of binary operator expressions.
///
/// Example matches b (matcher = binaryOperator(hasRHS()))
/// \code
/// a || b
/// \endcode
AST_POLYMORPHIC_MATCHER_P(hasRHS,
AST_POLYMORPHIC_SUPPORTED_TYPES(BinaryOperator,
ArraySubscriptExpr),
internal::Matcher<Expr>, InnerMatcher) {
const Expr *RightHandSide = Node.getRHS();
return (RightHandSide != nullptr &&
InnerMatcher.matches(*RightHandSide, Finder, Builder));
}
/// Matches if either the left hand side or the right hand side of a
/// binary operator matches.
inline internal::Matcher<BinaryOperator> hasEitherOperand(
const internal::Matcher<Expr> &InnerMatcher) {
return anyOf(hasLHS(InnerMatcher), hasRHS(InnerMatcher));
}
/// Matches if both matchers match with opposite sides of the binary operator.
///
/// Example matcher = binaryOperator(hasOperands(integerLiteral(equals(1),
/// integerLiteral(equals(2)))
/// \code
/// 1 + 2 // Match
/// 2 + 1 // Match
/// 1 + 1 // No match
/// 2 + 2 // No match
/// \endcode
inline internal::Matcher<BinaryOperator>
hasOperands(const internal::Matcher<Expr> &Matcher1,
const internal::Matcher<Expr> &Matcher2) {
return anyOf(allOf(hasLHS(Matcher1), hasRHS(Matcher2)),
allOf(hasLHS(Matcher2), hasRHS(Matcher1)));
}
/// Matches if the operand of a unary operator matches.
///
/// Example matches true (matcher = hasUnaryOperand(
/// cxxBoolLiteral(equals(true))))
/// \code
/// !true
/// \endcode
AST_MATCHER_P(UnaryOperator, hasUnaryOperand,
internal::Matcher<Expr>, InnerMatcher) {
const Expr * const Operand = Node.getSubExpr();
return (Operand != nullptr &&
InnerMatcher.matches(*Operand, Finder, Builder));
}
/// Matches if the cast's source expression
/// or opaque value's source expression matches the given matcher.
///
/// Example 1: matches "a string"
/// (matcher = castExpr(hasSourceExpression(cxxConstructExpr())))
/// \code
/// class URL { URL(string); };
/// URL url = "a string";
/// \endcode
///
/// Example 2: matches 'b' (matcher =
/// opaqueValueExpr(hasSourceExpression(implicitCastExpr(declRefExpr())))
/// \code
/// int a = b ?: 1;
/// \endcode
AST_POLYMORPHIC_MATCHER_P(hasSourceExpression,
AST_POLYMORPHIC_SUPPORTED_TYPES(CastExpr,
OpaqueValueExpr),
internal::Matcher<Expr>, InnerMatcher) {
const Expr *const SubExpression =
internal::GetSourceExpressionMatcher<NodeType>::get(Node);
return (SubExpression != nullptr &&
InnerMatcher.matches(*SubExpression, Finder, Builder));
}
/// Matches casts that has a given cast kind.
///
/// Example: matches the implicit cast around \c 0
/// (matcher = castExpr(hasCastKind(CK_NullToPointer)))
/// \code
/// int *p = 0;
/// \endcode
///
/// If the matcher is use from clang-query, CastKind parameter
/// should be passed as a quoted string. e.g., hasCastKind("CK_NullToPointer").
AST_MATCHER_P(CastExpr, hasCastKind, CastKind, Kind) {
return Node.getCastKind() == Kind;
}
/// Matches casts whose destination type matches a given matcher.
///
/// (Note: Clang's AST refers to other conversions as "casts" too, and calls
/// actual casts "explicit" casts.)
AST_MATCHER_P(ExplicitCastExpr, hasDestinationType,
internal::Matcher<QualType>, InnerMatcher) {
const QualType NodeType = Node.getTypeAsWritten();
return InnerMatcher.matches(NodeType, Finder, Builder);
}
/// Matches implicit casts whose destination type matches a given
/// matcher.
///
/// FIXME: Unit test this matcher
AST_MATCHER_P(ImplicitCastExpr, hasImplicitDestinationType,
internal::Matcher<QualType>, InnerMatcher) {
return InnerMatcher.matches(Node.getType(), Finder, Builder);
}
/// Matches TagDecl object that are spelled with "struct."
///
/// Example matches S, but not C, U or E.
/// \code
/// struct S {};
/// class C {};
/// union U {};
/// enum E {};
/// \endcode
AST_MATCHER(TagDecl, isStruct) {
return Node.isStruct();
}
/// Matches TagDecl object that are spelled with "union."
///
/// Example matches U, but not C, S or E.
/// \code
/// struct S {};
/// class C {};
/// union U {};
/// enum E {};
/// \endcode
AST_MATCHER(TagDecl, isUnion) {
return Node.isUnion();
}
/// Matches TagDecl object that are spelled with "class."
///
/// Example matches C, but not S, U or E.
/// \code
/// struct S {};
/// class C {};
/// union U {};
/// enum E {};
/// \endcode
AST_MATCHER(TagDecl, isClass) {
return Node.isClass();
}
/// Matches TagDecl object that are spelled with "enum."
///
/// Example matches E, but not C, S or U.
/// \code
/// struct S {};
/// class C {};
/// union U {};
/// enum E {};
/// \endcode
AST_MATCHER(TagDecl, isEnum) {
return Node.isEnum();
}
/// Matches the true branch expression of a conditional operator.
///
/// Example 1 (conditional ternary operator): matches a
/// \code
/// condition ? a : b
/// \endcode
///
/// Example 2 (conditional binary operator): matches opaqueValueExpr(condition)
/// \code
/// condition ?: b
/// \endcode
AST_MATCHER_P(AbstractConditionalOperator, hasTrueExpression,
internal::Matcher<Expr>, InnerMatcher) {
const Expr *Expression = Node.getTrueExpr();
return (Expression != nullptr &&
InnerMatcher.matches(*Expression, Finder, Builder));
}
/// Matches the false branch expression of a conditional operator
/// (binary or ternary).
///
/// Example matches b
/// \code
/// condition ? a : b
/// condition ?: b
/// \endcode
AST_MATCHER_P(AbstractConditionalOperator, hasFalseExpression,
internal::Matcher<Expr>, InnerMatcher) {
const Expr *Expression = Node.getFalseExpr();
return (Expression != nullptr &&
InnerMatcher.matches(*Expression, Finder, Builder));
}
/// Matches if a declaration has a body attached.
///
/// Example matches A, va, fa
/// \code
/// class A {};
/// class B; // Doesn't match, as it has no body.
/// int va;
/// extern int vb; // Doesn't match, as it doesn't define the variable.
/// void fa() {}
/// void fb(); // Doesn't match, as it has no body.
/// @interface X
/// - (void)ma; // Doesn't match, interface is declaration.
/// @end
/// @implementation X
/// - (void)ma {}
/// @end
/// \endcode
///
/// Usable as: Matcher<TagDecl>, Matcher<VarDecl>, Matcher<FunctionDecl>,
/// Matcher<ObjCMethodDecl>
AST_POLYMORPHIC_MATCHER(isDefinition,
AST_POLYMORPHIC_SUPPORTED_TYPES(TagDecl, VarDecl,
ObjCMethodDecl,
FunctionDecl)) {
return Node.isThisDeclarationADefinition();
}
/// Matches if a function declaration is variadic.
///
/// Example matches f, but not g or h. The function i will not match, even when
/// compiled in C mode.
/// \code
/// void f(...);
/// void g(int);
/// template <typename... Ts> void h(Ts...);
/// void i();
/// \endcode
AST_MATCHER(FunctionDecl, isVariadic) {
return Node.isVariadic();
}
/// Matches the class declaration that the given method declaration
/// belongs to.
///
/// FIXME: Generalize this for other kinds of declarations.
/// FIXME: What other kind of declarations would we need to generalize
/// this to?
///
/// Example matches A() in the last line
/// (matcher = cxxConstructExpr(hasDeclaration(cxxMethodDecl(
/// ofClass(hasName("A"))))))
/// \code
/// class A {
/// public:
/// A();
/// };
/// A a = A();
/// \endcode
AST_MATCHER_P(CXXMethodDecl, ofClass,
internal::Matcher<CXXRecordDecl>, InnerMatcher) {
const CXXRecordDecl *Parent = Node.getParent();
return (Parent != nullptr &&
InnerMatcher.matches(*Parent, Finder, Builder));
}
/// Matches each method overridden by the given method. This matcher may
/// produce multiple matches.
///
/// Given
/// \code
/// class A { virtual void f(); };
/// class B : public A { void f(); };
/// class C : public B { void f(); };
/// \endcode
/// cxxMethodDecl(ofClass(hasName("C")),
/// forEachOverridden(cxxMethodDecl().bind("b"))).bind("d")
/// matches once, with "b" binding "A::f" and "d" binding "C::f" (Note
/// that B::f is not overridden by C::f).
///
/// The check can produce multiple matches in case of multiple inheritance, e.g.
/// \code
/// class A1 { virtual void f(); };
/// class A2 { virtual void f(); };
/// class C : public A1, public A2 { void f(); };
/// \endcode
/// cxxMethodDecl(ofClass(hasName("C")),
/// forEachOverridden(cxxMethodDecl().bind("b"))).bind("d")
/// matches twice, once with "b" binding "A1::f" and "d" binding "C::f", and
/// once with "b" binding "A2::f" and "d" binding "C::f".
AST_MATCHER_P(CXXMethodDecl, forEachOverridden,
internal::Matcher<CXXMethodDecl>, InnerMatcher) {
BoundNodesTreeBuilder Result;
bool Matched = false;
for (const auto *Overridden : Node.overridden_methods()) {
BoundNodesTreeBuilder OverriddenBuilder(*Builder);
const bool OverriddenMatched =
InnerMatcher.matches(*Overridden, Finder, &OverriddenBuilder);
if (OverriddenMatched) {
Matched = true;
Result.addMatch(OverriddenBuilder);
}
}
*Builder = std::move(Result);
return Matched;
}
/// Matches declarations of virtual methods and C++ base specifers that specify
/// virtual inheritance.
///
/// Example:
/// \code
/// class A {
/// public:
/// virtual void x(); // matches x
/// };
/// \endcode
///
/// Example:
/// \code
/// class Base {};
/// class DirectlyDerived : virtual Base {}; // matches Base
/// class IndirectlyDerived : DirectlyDerived, Base {}; // matches Base
/// \endcode
///
/// Usable as: Matcher<CXXMethodDecl>, Matcher<CXXBaseSpecifier>
AST_POLYMORPHIC_MATCHER(isVirtual,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXMethodDecl,
CXXBaseSpecifier)) {
return Node.isVirtual();
}
/// Matches if the given method declaration has an explicit "virtual".
///
/// Given
/// \code
/// class A {
/// public:
/// virtual void x();
/// };
/// class B : public A {
/// public:
/// void x();
/// };
/// \endcode
/// matches A::x but not B::x
AST_MATCHER(CXXMethodDecl, isVirtualAsWritten) {
return Node.isVirtualAsWritten();
}
/// Matches if the given method or class declaration is final.
///
/// Given:
/// \code
/// class A final {};
///
/// struct B {
/// virtual void f();
/// };
///
/// struct C : B {
/// void f() final;
/// };
/// \endcode
/// matches A and C::f, but not B, C, or B::f
AST_POLYMORPHIC_MATCHER(isFinal,
AST_POLYMORPHIC_SUPPORTED_TYPES(CXXRecordDecl,
CXXMethodDecl)) {
return Node.template hasAttr<FinalAttr>();
}
/// Matches if the given method declaration is pure.
///
/// Given
/// \code
/// class A {
/// public:
/// virtual void x() = 0;
/// };
/// \endcode
/// matches A::x
AST_MATCHER(CXXMethodDecl, isPure) {
return Node.isPure();
}
/// Matches if the given method declaration is const.
///
/// Given
/// \code
/// struct A {
/// void foo() const;
/// void bar();
/// };
/// \endcode
///
/// cxxMethodDecl(isConst()) matches A::foo() but not A::bar()
AST_MATCHER(CXXMethodDecl, isConst) {
return Node.isConst();
}
/// Matches if the given method declaration declares a copy assignment
/// operator.
///
/// Given
/// \code
/// struct A {
/// A &operator=(const A &);
/// A &operator=(A &&);
/// };
/// \endcode
///
/// cxxMethodDecl(isCopyAssignmentOperator()) matches the first method but not
/// the second one.
AST_MATCHER(CXXMethodDecl, isCopyAssignmentOperator) {
return Node.isCopyAssignmentOperator();
}
/// Matches if the given method declaration declares a move assignment
/// operator.
///
/// Given
/// \code
/// struct A {
/// A &operator=(const A &);
/// A &operator=(A &&);
/// };
/// \endcode
///
/// cxxMethodDecl(isMoveAssignmentOperator()) matches the second method but not
/// the first one.
AST_MATCHER(CXXMethodDecl, isMoveAssignmentOperator) {
return Node.isMoveAssignmentOperator();
}
/// Matches if the given method declaration overrides another method.
///
/// Given
/// \code
/// class A {
/// public:
/// virtual void x();
/// };
/// class B : public A {
/// public:
/// virtual void x();
/// };
/// \endcode
/// matches B::x
AST_MATCHER(CXXMethodDecl, isOverride) {
return Node.size_overridden_methods() > 0 || Node.hasAttr<OverrideAttr>();
}
/// Matches method declarations that are user-provided.
///
/// Given
/// \code
/// struct S {
/// S(); // #1
/// S(const S &) = default; // #2
/// S(S &&) = delete; // #3
/// };
/// \endcode
/// cxxConstructorDecl(isUserProvided()) will match #1, but not #2 or #3.
AST_MATCHER(CXXMethodDecl, isUserProvided) {
return Node.isUserProvided();
}
/// Matches member expressions that are called with '->' as opposed
/// to '.'.
///
/// Member calls on the implicit this pointer match as called with '->'.
///
/// Given
/// \code
/// class Y {
/// void x() { this->x(); x(); Y y; y.x(); a; this->b; Y::b; }
/// template <class T> void f() { this->f<T>(); f<T>(); }
/// int a;
/// static int b;
/// };
/// template <class T>
/// class Z {
/// void x() { this->m; }
/// };
/// \endcode
/// memberExpr(isArrow())
/// matches this->x, x, y.x, a, this->b
/// cxxDependentScopeMemberExpr(isArrow())
/// matches this->m
/// unresolvedMemberExpr(isArrow())
/// matches this->f<T>, f<T>
AST_POLYMORPHIC_MATCHER(
isArrow, AST_POLYMORPHIC_SUPPORTED_TYPES(MemberExpr, UnresolvedMemberExpr,
CXXDependentScopeMemberExpr)) {
return Node.isArrow();
}
/// Matches QualType nodes that are of integer type.
///
/// Given
/// \code
/// void a(int);
/// void b(long);
/// void c(double);
/// \endcode
/// functionDecl(hasAnyParameter(hasType(isInteger())))
/// matches "a(int)", "b(long)", but not "c(double)".
AST_MATCHER(QualType, isInteger) {
return Node->isIntegerType();
}
/// Matches QualType nodes that are of unsigned integer type.
///
/// Given
/// \code
/// void a(int);
/// void b(unsigned long);
/// void c(double);
/// \endcode
/// functionDecl(hasAnyParameter(hasType(isUnsignedInteger())))
/// matches "b(unsigned long)", but not "a(int)" and "c(double)".
AST_MATCHER(QualType, isUnsignedInteger) {
return Node->isUnsignedIntegerType();
}
/// Matches QualType nodes that are of signed integer type.
///
/// Given
/// \code
/// void a(int);
/// void b(unsigned long);
/// void c(double);
/// \endcode
/// functionDecl(hasAnyParameter(hasType(isSignedInteger())))
/// matches "a(int)", but not "b(unsigned long)" and "c(double)".
AST_MATCHER(QualType, isSignedInteger) {
return Node->isSignedIntegerType();
}
/// Matches QualType nodes that are of character type.
///
/// Given
/// \code
/// void a(char);
/// void b(wchar_t);
/// void c(double);
/// \endcode
/// functionDecl(hasAnyParameter(hasType(isAnyCharacter())))
/// matches "a(char)", "b(wchar_t)", but not "c(double)".
AST_MATCHER(QualType, isAnyCharacter) {
return Node->isAnyCharacterType();
}
/// Matches QualType nodes that are of any pointer type; this includes
/// the Objective-C object pointer type, which is different despite being
/// syntactically similar.
///
/// Given
/// \code
/// int *i = nullptr;
///
/// @interface Foo
/// @end
/// Foo *f;
///
/// int j;
/// \endcode
/// varDecl(hasType(isAnyPointer()))
/// matches "int *i" and "Foo *f", but not "int j".
AST_MATCHER(QualType, isAnyPointer) {
return Node->isAnyPointerType();
}
/// Matches QualType nodes that are const-qualified, i.e., that
/// include "top-level" const.
///
/// Given
/// \code
/// void a(int);
/// void b(int const);
/// void c(const int);
/// void d(const int*);
/// void e(int const) {};
/// \endcode
/// functionDecl(hasAnyParameter(hasType(isConstQualified())))
/// matches "void b(int const)", "void c(const int)" and
/// "void e(int const) {}". It does not match d as there
/// is no top-level const on the parameter type "const int *".
AST_MATCHER(QualType, isConstQualified) {
return Node.isConstQualified();
}
/// Matches QualType nodes that are volatile-qualified, i.e., that
/// include "top-level" volatile.
///
/// Given
/// \code
/// void a(int);
/// void b(int volatile);
/// void c(volatile int);
/// void d(volatile int*);
/// void e(int volatile) {};
/// \endcode
/// functionDecl(hasAnyParameter(hasType(isVolatileQualified())))
/// matches "void b(int volatile)", "void c(volatile int)" and
/// "void e(int volatile) {}". It does not match d as there
/// is no top-level volatile on the parameter type "volatile int *".
AST_MATCHER(QualType, isVolatileQualified) {
return Node.isVolatileQualified();
}
/// Matches QualType nodes that have local CV-qualifiers attached to
/// the node, not hidden within a typedef.
///
/// Given
/// \code
/// typedef const int const_int;
/// const_int i;
/// int *const j;
/// int *volatile k;
/// int m;
/// \endcode
/// \c varDecl(hasType(hasLocalQualifiers())) matches only \c j and \c k.
/// \c i is const-qualified but the qualifier is not local.
AST_MATCHER(QualType, hasLocalQualifiers) {
return Node.hasLocalQualifiers();
}
/// Matches a member expression where the member is matched by a
/// given matcher.
///
/// Given
/// \code
/// struct { int first, second; } first, second;
/// int i(second.first);
/// int j(first.second);
/// \endcode
/// memberExpr(member(hasName("first")))
/// matches second.first
/// but not first.second (because the member name there is "second").
AST_MATCHER_P(MemberExpr, member,
internal::Matcher<ValueDecl>, InnerMatcher) {
return InnerMatcher.matches(*Node.getMemberDecl(), Finder, Builder);
}
/// Matches a member expression where the object expression is matched by a
/// given matcher. Implicit object expressions are included; that is, it matches
/// use of implicit `this`.
///
/// Given
/// \code
/// struct X {
/// int m;
/// int f(X x) { x.m; return m; }
/// };
/// \endcode
/// memberExpr(hasObjectExpression(hasType(cxxRecordDecl(hasName("X")))))
/// matches `x.m`, but not `m`; however,
/// memberExpr(hasObjectExpression(hasType(pointsTo(
// cxxRecordDecl(hasName("X"))))))
/// matches `m` (aka. `this->m`), but not `x.m`.
AST_POLYMORPHIC_MATCHER_P(
hasObjectExpression,
AST_POLYMORPHIC_SUPPORTED_TYPES(MemberExpr, UnresolvedMemberExpr,
CXXDependentScopeMemberExpr),
internal::Matcher<Expr>, InnerMatcher) {
if (const auto *E = dyn_cast<UnresolvedMemberExpr>(&Node))
if (E->isImplicitAccess())
return false;
if (const auto *E = dyn_cast<CXXDependentScopeMemberExpr>(&Node))
if (E->isImplicitAccess())
return false;
return InnerMatcher.matches(*Node.getBase(), Finder, Builder);
}
/// Matches any using shadow declaration.
///
/// Given
/// \code
/// namespace X { void b(); }
/// using X::b;
/// \endcode
/// usingDecl(hasAnyUsingShadowDecl(hasName("b"))))
/// matches \code using X::b \endcode
AST_MATCHER_P(UsingDecl, hasAnyUsingShadowDecl,
internal::Matcher<UsingShadowDecl>, InnerMatcher) {
return matchesFirstInPointerRange(InnerMatcher, Node.shadow_begin(),
Node.shadow_end(), Finder, Builder);
}
/// Matches a using shadow declaration where the target declaration is
/// matched by the given matcher.
///
/// Given
/// \code
/// namespace X { int a; void b(); }
/// using X::a;
/// using X::b;
/// \endcode
/// usingDecl(hasAnyUsingShadowDecl(hasTargetDecl(functionDecl())))
/// matches \code using X::b \endcode
/// but not \code using X::a \endcode
AST_MATCHER_P(UsingShadowDecl, hasTargetDecl,
internal::Matcher<NamedDecl>, InnerMatcher) {
return InnerMatcher.matches(*Node.getTargetDecl(), Finder, Builder);
}
/// Matches template instantiations of function, class, or static
/// member variable template instantiations.
///
/// Given
/// \code
/// template <typename T> class X {}; class A {}; X<A> x;
/// \endcode
/// or
/// \code
/// template <typename T> class X {}; class A {}; template class X<A>;
/// \endcode
/// or
/// \code
/// template <typename T> class X {}; class A {}; extern template class X<A>;
/// \endcode
/// cxxRecordDecl(hasName("::X"), isTemplateInstantiation())
/// matches the template instantiation of X<A>.
///
/// But given
/// \code
/// template <typename T> class X {}; class A {};
/// template <> class X<A> {}; X<A> x;
/// \endcode
/// cxxRecordDecl(hasName("::X"), isTemplateInstantiation())
/// does not match, as X<A> is an explicit template specialization.
///
/// Usable as: Matcher<FunctionDecl>, Matcher<VarDecl>, Matcher<CXXRecordDecl>
AST_POLYMORPHIC_MATCHER(isTemplateInstantiation,
AST_POLYMORPHIC_SUPPORTED_TYPES(FunctionDecl, VarDecl,
CXXRecordDecl)) {
return (Node.getTemplateSpecializationKind() == TSK_ImplicitInstantiation ||
Node.getTemplateSpecializationKind() ==
TSK_ExplicitInstantiationDefinition ||
Node.getTemplateSpecializationKind() ==
TSK_ExplicitInstantiationDeclaration);
}
/// Matches declarations that are template instantiations or are inside
/// template instantiations.
///
/// Given
/// \code
/// template<typename T> void A(T t) { T i; }
/// A(0);
/// A(0U);
/// \endcode
/// functionDecl(isInstantiated())
/// matches 'A(int) {...};' and 'A(unsigned) {...}'.
AST_MATCHER_FUNCTION(internal::Matcher<Decl>, isInstantiated) {
auto IsInstantiation = decl(anyOf(cxxRecordDecl(isTemplateInstantiation()),
functionDecl(isTemplateInstantiation())));
return decl(anyOf(IsInstantiation, hasAncestor(IsInstantiation)));
}
/// Matches statements inside of a template instantiation.
///
/// Given
/// \code
/// int j;
/// template<typename T> void A(T t) { T i; j += 42;}
/// A(0);
/// A(0U);
/// \endcode
/// declStmt(isInTemplateInstantiation())
/// matches 'int i;' and 'unsigned i'.
/// unless(stmt(isInTemplateInstantiation()))
/// will NOT match j += 42; as it's shared between the template definition and
/// instantiation.
AST_MATCHER_FUNCTION(internal::Matcher<Stmt>, isInTemplateInstantiation) {
return stmt(
hasAncestor(decl(anyOf(cxxRecordDecl(isTemplateInstantiation()),
functionDecl(isTemplateInstantiation())))));
}
/// Matches explicit template specializations of function, class, or
/// static member variable template instantiations.
///
/// Given
/// \code
/// template<typename T> void A(T t) { }
/// template<> void A(int N) { }
/// \endcode
/// functionDecl(isExplicitTemplateSpecialization())
/// matches the specialization A<int>().
///
/// Usable as: Matcher<FunctionDecl>, Matcher<VarDecl>, Matcher<CXXRecordDecl>
AST_POLYMORPHIC_MATCHER(isExplicitTemplateSpecialization,
AST_POLYMORPHIC_SUPPORTED_TYPES(FunctionDecl, VarDecl,
CXXRecordDecl)) {
return (Node.getTemplateSpecializationKind() == TSK_ExplicitSpecialization);
}
/// Matches \c TypeLocs for which the given inner
/// QualType-matcher matches.
AST_MATCHER_FUNCTION_P_OVERLOAD(internal::BindableMatcher<TypeLoc>, loc,
internal::Matcher<QualType>, InnerMatcher, 0) {
return internal::BindableMatcher<TypeLoc>(
new internal::TypeLocTypeMatcher(InnerMatcher));
}
/// Matches type \c bool.
///
/// Given
/// \code
/// struct S { bool func(); };
/// \endcode
/// functionDecl(returns(booleanType()))
/// matches "bool func();"
AST_MATCHER(Type, booleanType) {
return Node.isBooleanType();
}
/// Matches type \c void.
///
/// Given
/// \code
/// struct S { void func(); };
/// \endcode
/// functionDecl(returns(voidType()))
/// matches "void func();"
AST_MATCHER(Type, voidType) {
return Node.isVoidType();
}
template <typename NodeType>
using AstTypeMatcher = internal::VariadicDynCastAllOfMatcher<Type, NodeType>;
/// Matches builtin Types.
///
/// Given
/// \code
/// struct A {};
/// A a;
/// int b;
/// float c;
/// bool d;
/// \endcode
/// builtinType()
/// matches "int b", "float c" and "bool d"
extern const AstTypeMatcher<BuiltinType> builtinType;
/// Matches all kinds of arrays.
///
/// Given
/// \code
/// int a[] = { 2, 3 };
/// int b[4];
/// void f() { int c[a[0]]; }
/// \endcode
/// arrayType()
/// matches "int a[]", "int b[4]" and "int c[a[0]]";
extern const AstTypeMatcher<ArrayType> arrayType;
/// Matches C99 complex types.
///
/// Given
/// \code
/// _Complex float f;
/// \endcode
/// complexType()
/// matches "_Complex float f"
extern const AstTypeMatcher<ComplexType> complexType;
/// Matches any real floating-point type (float, double, long double).
///
/// Given
/// \code
/// int i;
/// float f;
/// \endcode
/// realFloatingPointType()
/// matches "float f" but not "int i"
AST_MATCHER(Type, realFloatingPointType) {
return Node.isRealFloatingType();
}
/// Matches arrays and C99 complex types that have a specific element
/// type.
///
/// Given
/// \code
/// struct A {};
/// A a[7];
/// int b[7];
/// \endcode
/// arrayType(hasElementType(builtinType()))
/// matches "int b[7]"
///
/// Usable as: Matcher<ArrayType>, Matcher<ComplexType>
AST_TYPELOC_TRAVERSE_MATCHER_DECL(hasElementType, getElement,
AST_POLYMORPHIC_SUPPORTED_TYPES(ArrayType,
ComplexType));
/// Matches C arrays with a specified constant size.
///
/// Given
/// \code
/// void() {
/// int a[2];
/// int b[] = { 2, 3 };
/// int c[b[0]];
/// }
/// \endcode
/// constantArrayType()
/// matches "int a[2]"
extern const AstTypeMatcher<ConstantArrayType> constantArrayType;
/// Matches nodes that have the specified size.
///
/// Given
/// \code
/// int a[42];
/// int b[2 * 21];
/// int c[41], d[43];
/// char *s = "abcd";
/// wchar_t *ws = L"abcd";
/// char *w = "a";
/// \endcode
/// constantArrayType(hasSize(42))
/// matches "int a[42]" and "int b[2 * 21]"
/// stringLiteral(hasSize(4))
/// matches "abcd", L"abcd"
AST_POLYMORPHIC_MATCHER_P(hasSize,
AST_POLYMORPHIC_SUPPORTED_TYPES(ConstantArrayType,
StringLiteral),
unsigned, N) {
return internal::HasSizeMatcher<NodeType>::hasSize(Node, N);
}
/// Matches C++ arrays whose size is a value-dependent expression.
///
/// Given
/// \code
/// template<typename T, int Size>
/// class array {
/// T data[Size];
/// };
/// \endcode
/// dependentSizedArrayType
/// matches "T data[Size]"
extern const AstTypeMatcher<DependentSizedArrayType> dependentSizedArrayType;
/// Matches C arrays with unspecified size.
///
/// Given
/// \code
/// int a[] = { 2, 3 };
/// int b[42];
/// void f(int c[]) { int d[a[0]]; };
/// \endcode
/// incompleteArrayType()
/// matches "int a[]" and "int c[]"
extern const AstTypeMatcher<IncompleteArrayType> incompleteArrayType;
/// Matches C arrays with a specified size that is not an
/// integer-constant-expression.
///
/// Given
/// \code
/// void f() {
/// int a[] = { 2, 3 }
/// int b[42];
/// int c[a[0]];
/// }
/// \endcode
/// variableArrayType()
/// matches "int c[a[0]]"
extern const AstTypeMatcher<VariableArrayType> variableArrayType;
/// Matches \c VariableArrayType nodes that have a specific size
/// expression.
///
/// Given
/// \code
/// void f(int b) {
/// int a[b];
/// }
/// \endcode
/// variableArrayType(hasSizeExpr(ignoringImpCasts(declRefExpr(to(
/// varDecl(hasName("b")))))))
/// matches "int a[b]"
AST_MATCHER_P(VariableArrayType, hasSizeExpr,
internal::Matcher<Expr>, InnerMatcher) {
return InnerMatcher.matches(*Node.getSizeExpr(), Finder, Builder);
}
/// Matches atomic types.
///
/// Given
/// \code
/// _Atomic(int) i;
/// \endcode
/// atomicType()
/// matches "_Atomic(int) i"
extern const AstTypeMatcher<AtomicType> atomicType;
/// Matches atomic types with a specific value type.
///
/// Given
/// \code
/// _Atomic(int) i;
/// _Atomic(float) f;
/// \endcode
/// atomicType(hasValueType(isInteger()))
/// matches "_Atomic(int) i"
///
/// Usable as: Matcher<AtomicType>
AST_TYPELOC_TRAVERSE_MATCHER_DECL(hasValueType, getValue,
AST_POLYMORPHIC_SUPPORTED_TYPES(AtomicType));
/// Matches types nodes representing C++11 auto types.
///
/// Given:
/// \code
/// auto n = 4;
/// int v[] = { 2, 3 }
/// for (auto i : v) { }
/// \endcode
/// autoType()
/// matches "auto n" and "auto i"
extern const AstTypeMatcher<AutoType> autoType;
/// Matches types nodes representing C++11 decltype(<expr>) types.
///
/// Given:
/// \code
/// short i = 1;
/// int j = 42;
/// decltype(i + j) result = i + j;
/// \endcode
/// decltypeType()
/// matches "decltype(i + j)"
extern const AstTypeMatcher<DecltypeType> decltypeType;
/// Matches \c AutoType nodes where the deduced type is a specific type.
///
/// Note: There is no \c TypeLoc for the deduced type and thus no
/// \c getDeducedLoc() matcher.
///
/// Given
/// \code
/// auto a = 1;
/// auto b = 2.0;
/// \endcode
/// autoType(hasDeducedType(isInteger()))
/// matches "auto a"
///
/// Usable as: Matcher<AutoType>
AST_TYPE_TRAVERSE_MATCHER(hasDeducedType, getDeducedType,
AST_POLYMORPHIC_SUPPORTED_TYPES(AutoType));
/// Matches \c DecltypeType nodes to find out the underlying type.
///
/// Given
/// \code
/// decltype(1) a = 1;
/// decltype(2.0) b = 2.0;
/// \endcode
/// decltypeType(hasUnderlyingType(isInteger()))
/// matches the type of "a"
///
/// Usable as: Matcher<DecltypeType>
AST_TYPE_TRAVERSE_MATCHER(hasUnderlyingType, getUnderlyingType,
AST_POLYMORPHIC_SUPPORTED_TYPES(DecltypeType));
/// Matches \c FunctionType nodes.
///
/// Given
/// \code
/// int (*f)(int);
/// void g();
/// \endcode
/// functionType()
/// matches "int (*f)(int)" and the type of "g".
extern const AstTypeMatcher<FunctionType> functionType;
/// Matches \c FunctionProtoType nodes.
///
/// Given
/// \code
/// int (*f)(int);
/// void g();
/// \endcode
/// functionProtoType()
/// matches "int (*f)(int)" and the type of "g" in C++ mode.
/// In C mode, "g" is not matched because it does not contain a prototype.
extern const AstTypeMatcher<FunctionProtoType> functionProtoType;
/// Matches \c ParenType nodes.
///
/// Given
/// \code
/// int (*ptr_to_array)[4];
/// int *array_of_ptrs[4];
/// \endcode
///
/// \c varDecl(hasType(pointsTo(parenType()))) matches \c ptr_to_array but not
/// \c array_of_ptrs.
extern const AstTypeMatcher<ParenType> parenType;
/// Matches \c ParenType nodes where the inner type is a specific type.
///
/// Given
/// \code
/// int (*ptr_to_array)[4];
/// int (*ptr_to_func)(int);
/// \endcode
///
/// \c varDecl(hasType(pointsTo(parenType(innerType(functionType()))))) matches
/// \c ptr_to_func but not \c ptr_to_array.
///
/// Usable as: Matcher<ParenType>
AST_TYPE_TRAVERSE_MATCHER(innerType, getInnerType,
AST_POLYMORPHIC_SUPPORTED_TYPES(ParenType));
/// Matches block pointer types, i.e. types syntactically represented as
/// "void (^)(int)".
///
/// The \c pointee is always required to be a \c FunctionType.
extern const AstTypeMatcher<BlockPointerType> blockPointerType;
/// Matches member pointer types.
/// Given
/// \code
/// struct A { int i; }
/// A::* ptr = A::i;
/// \endcode
/// memberPointerType()
/// matches "A::* ptr"
extern const AstTypeMatcher<MemberPointerType> memberPointerType;
/// Matches pointer types, but does not match Objective-C object pointer
/// types.
///
/// Given
/// \code
/// int *a;
/// int &b = *a;
/// int c = 5;
///
/// @interface Foo
/// @end
/// Foo *f;
/// \endcode
/// pointerType()
/// matches "int *a", but does not match "Foo *f".
extern const AstTypeMatcher<PointerType> pointerType;
/// Matches an Objective-C object pointer type, which is different from
/// a pointer type, despite being syntactically similar.
///
/// Given
/// \code
/// int *a;
///
/// @interface Foo
/// @end
/// Foo *f;
/// \endcode
/// pointerType()
/// matches "Foo *f", but does not match "int *a".
extern const AstTypeMatcher<ObjCObjectPointerType> objcObjectPointerType;
/// Matches both lvalue and rvalue reference types.
///
/// Given
/// \code
/// int *a;
/// int &b = *a;
/// int &&c = 1;
/// auto &d = b;
/// auto &&e = c;
/// auto &&f = 2;
/// int g = 5;
/// \endcode
///
/// \c referenceType() matches the types of \c b, \c c, \c d, \c e, and \c f.
extern const AstTypeMatcher<ReferenceType> referenceType;
/// Matches lvalue reference types.
///
/// Given:
/// \code
/// int *a;
/// int &b = *a;
/// int &&c = 1;
/// auto &d = b;
/// auto &&e = c;
/// auto &&f = 2;
/// int g = 5;
/// \endcode
///
/// \c lValueReferenceType() matches the types of \c b, \c d, and \c e. \c e is
/// matched since the type is deduced as int& by reference collapsing rules.
extern const AstTypeMatcher<LValueReferenceType> lValueReferenceType;
/// Matches rvalue reference types.
///
/// Given:
/// \code
/// int *a;
/// int &b = *a;
/// int &&c = 1;
/// auto &d = b;
/// auto &&e = c;
/// auto &&f = 2;
/// int g = 5;
/// \endcode
///
/// \c rValueReferenceType() matches the types of \c c and \c f. \c e is not
/// matched as it is deduced to int& by reference collapsing rules.
extern const AstTypeMatcher<RValueReferenceType> rValueReferenceType;
/// Narrows PointerType (and similar) matchers to those where the
/// \c pointee matches a given matcher.
///
/// Given
/// \code
/// int *a;
/// int const *b;
/// float const *f;
/// \endcode
/// pointerType(pointee(isConstQualified(), isInteger()))
/// matches "int const *b"
///
/// Usable as: Matcher<BlockPointerType>, Matcher<MemberPointerType>,
/// Matcher<PointerType>, Matcher<ReferenceType>
AST_TYPELOC_TRAVERSE_MATCHER_DECL(
pointee, getPointee,
AST_POLYMORPHIC_SUPPORTED_TYPES(BlockPointerType, MemberPointerType,
PointerType, ReferenceType));
/// Matches typedef types.
///
/// Given
/// \code
/// typedef int X;
/// \endcode
/// typedefType()
/// matches "typedef int X"
extern const AstTypeMatcher<TypedefType> typedefType;
/// Matches enum types.
///
/// Given
/// \code
/// enum C { Green };
/// enum class S { Red };
///
/// C c;
/// S s;
/// \endcode
//
/// \c enumType() matches the type of the variable declarations of both \c c and
/// \c s.
extern const AstTypeMatcher<EnumType> enumType;
/// Matches template specialization types.
///
/// Given
/// \code
/// template <typename T>
/// class C { };
///
/// template class C<int>; // A
/// C<char> var; // B
/// \endcode
///
/// \c templateSpecializationType() matches the type of the explicit
/// instantiation in \c A and the type of the variable declaration in \c B.
extern const AstTypeMatcher<TemplateSpecializationType>
templateSpecializationType;
/// Matches C++17 deduced template specialization types, e.g. deduced class
/// template types.
///
/// Given
/// \code
/// template <typename T>
/// class C { public: C(T); };
///
/// C c(123);
/// \endcode
/// \c deducedTemplateSpecializationType() matches the type in the declaration
/// of the variable \c c.
extern const AstTypeMatcher<DeducedTemplateSpecializationType>
deducedTemplateSpecializationType;
/// Matches types nodes representing unary type transformations.
///
/// Given:
/// \code
/// typedef __underlying_type(T) type;
/// \endcode
/// unaryTransformType()
/// matches "__underlying_type(T)"
extern const AstTypeMatcher<UnaryTransformType> unaryTransformType;
/// Matches record types (e.g. structs, classes).
///
/// Given
/// \code
/// class C {};
/// struct S {};
///
/// C c;
/// S s;
/// \endcode
///
/// \c recordType() matches the type of the variable declarations of both \c c
/// and \c s.
extern const AstTypeMatcher<RecordType> recordType;
/// Matches tag types (record and enum types).
///
/// Given
/// \code
/// enum E {};
/// class C {};
///
/// E e;
/// C c;
/// \endcode
///
/// \c tagType() matches the type of the variable declarations of both \c e
/// and \c c.
extern const AstTypeMatcher<TagType> tagType;
/// Matches types specified with an elaborated type keyword or with a
/// qualified name.
///
/// Given
/// \code
/// namespace N {
/// namespace M {
/// class D {};
/// }
/// }
/// class C {};
///
/// class C c;
/// N::M::D d;
/// \endcode
///
/// \c elaboratedType() matches the type of the variable declarations of both
/// \c c and \c d.
extern const AstTypeMatcher<ElaboratedType> elaboratedType;
/// Matches ElaboratedTypes whose qualifier, a NestedNameSpecifier,
/// matches \c InnerMatcher if the qualifier exists.
///
/// Given
/// \code
/// namespace N {
/// namespace M {
/// class D {};
/// }
/// }
/// N::M::D d;
/// \endcode
///
/// \c elaboratedType(hasQualifier(hasPrefix(specifiesNamespace(hasName("N"))))
/// matches the type of the variable declaration of \c d.
AST_MATCHER_P(ElaboratedType, hasQualifier,
internal::Matcher<NestedNameSpecifier>, InnerMatcher) {
if (const NestedNameSpecifier *Qualifier = Node.getQualifier())
return InnerMatcher.matches(*Qualifier, Finder, Builder);
return false;
}
/// Matches ElaboratedTypes whose named type matches \c InnerMatcher.
///
/// Given
/// \code
/// namespace N {
/// namespace M {
/// class D {};
/// }
/// }
/// N::M::D d;
/// \endcode
///
/// \c elaboratedType(namesType(recordType(
/// hasDeclaration(namedDecl(hasName("D")))))) matches the type of the variable
/// declaration of \c d.
AST_MATCHER_P(ElaboratedType, namesType, internal::Matcher<QualType>,
InnerMatcher) {
return InnerMatcher.matches(Node.getNamedType(), Finder, Builder);
}
/// Matches types that represent the result of substituting a type for a
/// template type parameter.
///
/// Given
/// \code
/// template <typename T>
/// void F(T t) {
/// int i = 1 + t;
/// }
/// \endcode
///
/// \c substTemplateTypeParmType() matches the type of 't' but not '1'
extern const AstTypeMatcher<SubstTemplateTypeParmType>
substTemplateTypeParmType;
/// Matches template type parameter substitutions that have a replacement
/// type that matches the provided matcher.
///
/// Given
/// \code
/// template <typename T>
/// double F(T t);
/// int i;
/// double j = F(i);
/// \endcode
///
/// \c substTemplateTypeParmType(hasReplacementType(type())) matches int
AST_TYPE_TRAVERSE_MATCHER(
hasReplacementType, getReplacementType,
AST_POLYMORPHIC_SUPPORTED_TYPES(SubstTemplateTypeParmType));
/// Matches template type parameter types.
///
/// Example matches T, but not int.
/// (matcher = templateTypeParmType())
/// \code
/// template <typename T> void f(int i);
/// \endcode
extern const AstTypeMatcher<TemplateTypeParmType> templateTypeParmType;
/// Matches injected class name types.
///
/// Example matches S s, but not S<T> s.
/// (matcher = parmVarDecl(hasType(injectedClassNameType())))
/// \code
/// template <typename T> struct S {
/// void f(S s);
/// void g(S<T> s);
/// };
/// \endcode
extern const AstTypeMatcher<InjectedClassNameType> injectedClassNameType;
/// Matches decayed type
/// Example matches i[] in declaration of f.
/// (matcher = valueDecl(hasType(decayedType(hasDecayedType(pointerType())))))
/// Example matches i[1].
/// (matcher = expr(hasType(decayedType(hasDecayedType(pointerType())))))
/// \code
/// void f(int i[]) {
/// i[1] = 0;
/// }
/// \endcode
extern const AstTypeMatcher<DecayedType> decayedType;
/// Matches the decayed type, whos decayed type matches \c InnerMatcher
AST_MATCHER_P(DecayedType, hasDecayedType, internal::Matcher<QualType>,
InnerType) {
return InnerType.matches(Node.getDecayedType(), Finder, Builder);
}
/// Matches declarations whose declaration context, interpreted as a
/// Decl, matches \c InnerMatcher.
///
/// Given
/// \code
/// namespace N {
/// namespace M {
/// class D {};
/// }
/// }
/// \endcode
///
/// \c cxxRcordDecl(hasDeclContext(namedDecl(hasName("M")))) matches the
/// declaration of \c class \c D.
AST_MATCHER_P(Decl, hasDeclContext, internal::Matcher<Decl>, InnerMatcher) {
const DeclContext *DC = Node.getDeclContext();
if (!DC) return false;
return InnerMatcher.matches(*Decl::castFromDeclContext(DC), Finder, Builder);
}
/// Matches nested name specifiers.
///
/// Given
/// \code
/// namespace ns {
/// struct A { static void f(); };
/// void A::f() {}
/// void g() { A::f(); }
/// }
/// ns::A a;
/// \endcode
/// nestedNameSpecifier()
/// matches "ns::" and both "A::"
extern const internal::VariadicAllOfMatcher<NestedNameSpecifier>
nestedNameSpecifier;
/// Same as \c nestedNameSpecifier but matches \c NestedNameSpecifierLoc.
extern const internal::VariadicAllOfMatcher<NestedNameSpecifierLoc>
nestedNameSpecifierLoc;
/// Matches \c NestedNameSpecifierLocs for which the given inner
/// NestedNameSpecifier-matcher matches.
AST_MATCHER_FUNCTION_P_OVERLOAD(
internal::BindableMatcher<NestedNameSpecifierLoc>, loc,
internal::Matcher<NestedNameSpecifier>, InnerMatcher, 1) {
return internal::BindableMatcher<NestedNameSpecifierLoc>(
new internal::LocMatcher<NestedNameSpecifierLoc, NestedNameSpecifier>(
InnerMatcher));
}
/// Matches nested name specifiers that specify a type matching the
/// given \c QualType matcher without qualifiers.
///
/// Given
/// \code
/// struct A { struct B { struct C {}; }; };
/// A::B::C c;
/// \endcode
/// nestedNameSpecifier(specifiesType(
/// hasDeclaration(cxxRecordDecl(hasName("A")))
/// ))
/// matches "A::"
AST_MATCHER_P(NestedNameSpecifier, specifiesType,
internal::Matcher<QualType>, InnerMatcher) {
if (!Node.getAsType())
return false;
return InnerMatcher.matches(QualType(Node.getAsType(), 0), Finder, Builder);
}
/// Matches nested name specifier locs that specify a type matching the
/// given \c TypeLoc.
///
/// Given
/// \code
/// struct A { struct B { struct C {}; }; };
/// A::B::C c;
/// \endcode
/// nestedNameSpecifierLoc(specifiesTypeLoc(loc(type(
/// hasDeclaration(cxxRecordDecl(hasName("A")))))))
/// matches "A::"
AST_MATCHER_P(NestedNameSpecifierLoc, specifiesTypeLoc,
internal::Matcher<TypeLoc>, InnerMatcher) {
return Node && Node.getNestedNameSpecifier()->getAsType() &&
InnerMatcher.matches(Node.getTypeLoc(), Finder, Builder);
}
/// Matches on the prefix of a \c NestedNameSpecifier.
///
/// Given
/// \code
/// struct A { struct B { struct C {}; }; };
/// A::B::C c;
/// \endcode
/// nestedNameSpecifier(hasPrefix(specifiesType(asString("struct A")))) and
/// matches "A::"
AST_MATCHER_P_OVERLOAD(NestedNameSpecifier, hasPrefix,
internal::Matcher<NestedNameSpecifier>, InnerMatcher,
0) {
const NestedNameSpecifier *NextNode = Node.getPrefix();
if (!NextNode)
return false;
return InnerMatcher.matches(*NextNode, Finder, Builder);
}
/// Matches on the prefix of a \c NestedNameSpecifierLoc.
///
/// Given
/// \code
/// struct A { struct B { struct C {}; }; };
/// A::B::C c;
/// \endcode
/// nestedNameSpecifierLoc(hasPrefix(loc(specifiesType(asString("struct A")))))
/// matches "A::"
AST_MATCHER_P_OVERLOAD(NestedNameSpecifierLoc, hasPrefix,
internal::Matcher<NestedNameSpecifierLoc>, InnerMatcher,
1) {
NestedNameSpecifierLoc NextNode = Node.getPrefix();
if (!NextNode)
return false;
return InnerMatcher.matches(NextNode, Finder, Builder);
}
/// Matches nested name specifiers that specify a namespace matching the
/// given namespace matcher.
///
/// Given
/// \code
/// namespace ns { struct A {}; }
/// ns::A a;
/// \endcode
/// nestedNameSpecifier(specifiesNamespace(hasName("ns")))
/// matches "ns::"
AST_MATCHER_P(NestedNameSpecifier, specifiesNamespace,
internal::Matcher<NamespaceDecl>, InnerMatcher) {
if (!Node.getAsNamespace())
return false;
return InnerMatcher.matches(*Node.getAsNamespace(), Finder, Builder);
}
/// Overloads for the \c equalsNode matcher.
/// FIXME: Implement for other node types.
/// @{
/// Matches if a node equals another node.
///
/// \c Decl has pointer identity in the AST.
AST_MATCHER_P_OVERLOAD(Decl, equalsNode, const Decl*, Other, 0) {
return &Node == Other;
}
/// Matches if a node equals another node.
///
/// \c Stmt has pointer identity in the AST.
AST_MATCHER_P_OVERLOAD(Stmt, equalsNode, const Stmt*, Other, 1) {
return &Node == Other;
}
/// Matches if a node equals another node.
///
/// \c Type has pointer identity in the AST.
AST_MATCHER_P_OVERLOAD(Type, equalsNode, const Type*, Other, 2) {
return &Node == Other;
}
/// @}
/// Matches each case or default statement belonging to the given switch
/// statement. This matcher may produce multiple matches.
///
/// Given
/// \code
/// switch (1) { case 1: case 2: default: switch (2) { case 3: case 4: ; } }
/// \endcode
/// switchStmt(forEachSwitchCase(caseStmt().bind("c"))).bind("s")
/// matches four times, with "c" binding each of "case 1:", "case 2:",
/// "case 3:" and "case 4:", and "s" respectively binding "switch (1)",
/// "switch (1)", "switch (2)" and "switch (2)".
AST_MATCHER_P(SwitchStmt, forEachSwitchCase, internal::Matcher<SwitchCase>,
InnerMatcher) {
BoundNodesTreeBuilder Result;
// FIXME: getSwitchCaseList() does not necessarily guarantee a stable
// iteration order. We should use the more general iterating matchers once
// they are capable of expressing this matcher (for example, it should ignore
// case statements belonging to nested switch statements).
bool Matched = false;
for (const SwitchCase *SC = Node.getSwitchCaseList(); SC;
SC = SC->getNextSwitchCase()) {
BoundNodesTreeBuilder CaseBuilder(*Builder);
bool CaseMatched = InnerMatcher.matches(*SC, Finder, &CaseBuilder);
if (CaseMatched) {
Matched = true;
Result.addMatch(CaseBuilder);
}
}
*Builder = std::move(Result);
return Matched;
}
/// Matches each constructor initializer in a constructor definition.
///
/// Given
/// \code
/// class A { A() : i(42), j(42) {} int i; int j; };
/// \endcode
/// cxxConstructorDecl(forEachConstructorInitializer(
/// forField(decl().bind("x"))
/// ))
/// will trigger two matches, binding for 'i' and 'j' respectively.
AST_MATCHER_P(CXXConstructorDecl, forEachConstructorInitializer,
internal::Matcher<CXXCtorInitializer>, InnerMatcher) {
BoundNodesTreeBuilder Result;
bool Matched = false;
for (const auto *I : Node.inits()) {
BoundNodesTreeBuilder InitBuilder(*Builder);
if (InnerMatcher.matches(*I, Finder, &InitBuilder)) {
Matched = true;
Result.addMatch(InitBuilder);
}
}
*Builder = std::move(Result);
return Matched;
}
/// Matches constructor declarations that are copy constructors.
///
/// Given
/// \code
/// struct S {
/// S(); // #1
/// S(const S &); // #2
/// S(S &&); // #3
/// };
/// \endcode
/// cxxConstructorDecl(isCopyConstructor()) will match #2, but not #1 or #3.
AST_MATCHER(CXXConstructorDecl, isCopyConstructor) {
return Node.isCopyConstructor();
}
/// Matches constructor declarations that are move constructors.
///
/// Given
/// \code
/// struct S {
/// S(); // #1
/// S(const S &); // #2
/// S(S &&); // #3
/// };
/// \endcode
/// cxxConstructorDecl(isMoveConstructor()) will match #3, but not #1 or #2.
AST_MATCHER(CXXConstructorDecl, isMoveConstructor) {
return Node.isMoveConstructor();
}
/// Matches constructor declarations that are default constructors.
///
/// Given
/// \code
/// struct S {
/// S(); // #1
/// S(const S &); // #2
/// S(S &&); // #3
/// };
/// \endcode
/// cxxConstructorDecl(isDefaultConstructor()) will match #1, but not #2 or #3.
AST_MATCHER(CXXConstructorDecl, isDefaultConstructor) {
return Node.isDefaultConstructor();
}
/// Matches constructors that delegate to another constructor.
///
/// Given
/// \code
/// struct S {
/// S(); // #1
/// S(int) {} // #2
/// S(S &&) : S() {} // #3
/// };
/// S::S() : S(0) {} // #4
/// \endcode
/// cxxConstructorDecl(isDelegatingConstructor()) will match #3 and #4, but not
/// #1 or #2.
AST_MATCHER(CXXConstructorDecl, isDelegatingConstructor) {
return Node.isDelegatingConstructor();
}
/// Matches constructor, conversion function, and deduction guide declarations
/// that have an explicit specifier if this explicit specifier is resolved to
/// true.
///
/// Given
/// \code
/// template<bool b>
/// struct S {
/// S(int); // #1
/// explicit S(double); // #2
/// operator int(); // #3
/// explicit operator bool(); // #4
/// explicit(false) S(bool) // # 7
/// explicit(true) S(char) // # 8
/// explicit(b) S(S) // # 9
/// };
/// S(int) -> S<true> // #5
/// explicit S(double) -> S<false> // #6
/// \endcode
/// cxxConstructorDecl(isExplicit()) will match #2 and #8, but not #1, #7 or #9.
/// cxxConversionDecl(isExplicit()) will match #4, but not #3.
/// cxxDeductionGuideDecl(isExplicit()) will match #6, but not #5.
AST_POLYMORPHIC_MATCHER(isExplicit, AST_POLYMORPHIC_SUPPORTED_TYPES(
CXXConstructorDecl, CXXConversionDecl,
CXXDeductionGuideDecl)) {
return Node.isExplicit();
}
/// Matches the expression in an explicit specifier if present in the given
/// declaration.
///
/// Given
/// \code
/// template<bool b>
/// struct S {
/// S(int); // #1
/// explicit S(double); // #2
/// operator int(); // #3
/// explicit operator bool(); // #4
/// explicit(false) S(bool) // # 7
/// explicit(true) S(char) // # 8
/// explicit(b) S(S) // # 9
/// };
/// S(int) -> S<true> // #5
/// explicit S(double) -> S<false> // #6
/// \endcode
/// cxxConstructorDecl(hasExplicitSpecifier(constantExpr())) will match #7, #8 and #9, but not #1 or #2.
/// cxxConversionDecl(hasExplicitSpecifier(constantExpr())) will not match #3 or #4.
/// cxxDeductionGuideDecl(hasExplicitSpecifier(constantExpr())) will not match #5 or #6.
AST_MATCHER_P(FunctionDecl, hasExplicitSpecifier, internal::Matcher<Expr>,
InnerMatcher) {
ExplicitSpecifier ES = ExplicitSpecifier::getFromDecl(&Node);
if (!ES.getExpr())
return false;
return InnerMatcher.matches(*ES.getExpr(), Finder, Builder);
}
/// Matches function and namespace declarations that are marked with
/// the inline keyword.
///
/// Given
/// \code
/// inline void f();
/// void g();
/// namespace n {
/// inline namespace m {}
/// }
/// \endcode
/// functionDecl(isInline()) will match ::f().
/// namespaceDecl(isInline()) will match n::m.
AST_POLYMORPHIC_MATCHER(isInline,
AST_POLYMORPHIC_SUPPORTED_TYPES(NamespaceDecl,
FunctionDecl)) {
// This is required because the spelling of the function used to determine
// whether inline is specified or not differs between the polymorphic types.
if (const auto *FD = dyn_cast<FunctionDecl>(&Node))
return FD->isInlineSpecified();
else if (const auto *NSD = dyn_cast<NamespaceDecl>(&Node))
return NSD->isInline();
llvm_unreachable("Not a valid polymorphic type");
}
/// Matches anonymous namespace declarations.
///
/// Given
/// \code
/// namespace n {
/// namespace {} // #1
/// }
/// \endcode
/// namespaceDecl(isAnonymous()) will match #1 but not ::n.
AST_MATCHER(NamespaceDecl, isAnonymous) {
return Node.isAnonymousNamespace();
}
/// Matches declarations in the namespace `std`, but not in nested namespaces.
///
/// Given
/// \code
/// class vector {};
/// namespace foo {
/// class vector {};
/// namespace std {
/// class vector {};
/// }
/// }
/// namespace std {
/// inline namespace __1 {
/// class vector {}; // #1
/// namespace experimental {
/// class vector {};
/// }
/// }
/// }
/// \endcode
/// cxxRecordDecl(hasName("vector"), isInStdNamespace()) will match only #1.
AST_MATCHER(Decl, isInStdNamespace) { return Node.isInStdNamespace(); }
/// If the given case statement does not use the GNU case range
/// extension, matches the constant given in the statement.
///
/// Given
/// \code
/// switch (1) { case 1: case 1+1: case 3 ... 4: ; }
/// \endcode
/// caseStmt(hasCaseConstant(integerLiteral()))
/// matches "case 1:"
AST_MATCHER_P(CaseStmt, hasCaseConstant, internal::Matcher<Expr>,
InnerMatcher) {
if (Node.getRHS())
return false;
return InnerMatcher.matches(*Node.getLHS(), Finder, Builder);
}
/// Matches declaration that has a given attribute.
///
/// Given
/// \code
/// __attribute__((device)) void f() { ... }
/// \endcode
/// decl(hasAttr(clang::attr::CUDADevice)) matches the function declaration of
/// f. If the matcher is used from clang-query, attr::Kind parameter should be
/// passed as a quoted string. e.g., hasAttr("attr::CUDADevice").
AST_MATCHER_P(Decl, hasAttr, attr::Kind, AttrKind) {
for (const auto *Attr : Node.attrs()) {
if (Attr->getKind() == AttrKind)
return true;
}
return false;
}
/// Matches the return value expression of a return statement
///
/// Given
/// \code
/// return a + b;
/// \endcode
/// hasReturnValue(binaryOperator())
/// matches 'return a + b'
/// with binaryOperator()
/// matching 'a + b'
AST_MATCHER_P(ReturnStmt, hasReturnValue, internal::Matcher<Expr>,
InnerMatcher) {
if (const auto *RetValue = Node.getRetValue())
return InnerMatcher.matches(*RetValue, Finder, Builder);
return false;
}
/// Matches CUDA kernel call expression.
///
/// Example matches,
/// \code
/// kernel<<<i,j>>>();
/// \endcode
extern const internal::VariadicDynCastAllOfMatcher<Stmt, CUDAKernelCallExpr>
cudaKernelCallExpr;
/// Matches expressions that resolve to a null pointer constant, such as
/// GNU's __null, C++11's nullptr, or C's NULL macro.
///
/// Given:
/// \code
/// void *v1 = NULL;
/// void *v2 = nullptr;
/// void *v3 = __null; // GNU extension
/// char *cp = (char *)0;
/// int *ip = 0;
/// int i = 0;
/// \endcode
/// expr(nullPointerConstant())
/// matches the initializer for v1, v2, v3, cp, and ip. Does not match the
/// initializer for i.
AST_MATCHER(Expr, nullPointerConstant) {
return Node.isNullPointerConstant(Finder->getASTContext(),
Expr::NPC_ValueDependentIsNull);
}
/// Matches declaration of the function the statement belongs to
///
/// Given:
/// \code
/// F& operator=(const F& o) {
/// std::copy_if(o.begin(), o.end(), begin(), [](V v) { return v > 0; });
/// return *this;
/// }
/// \endcode
/// returnStmt(forFunction(hasName("operator=")))
/// matches 'return *this'
/// but does not match 'return v > 0'
AST_MATCHER_P(Stmt, forFunction, internal::Matcher<FunctionDecl>,
InnerMatcher) {
const auto &Parents = Finder->getASTContext().getParents(Node);
llvm::SmallVector<DynTypedNode, 8> Stack(Parents.begin(), Parents.end());
while(!Stack.empty()) {
const auto &CurNode = Stack.back();
Stack.pop_back();
if(const auto *FuncDeclNode = CurNode.get<FunctionDecl>()) {
if(InnerMatcher.matches(*FuncDeclNode, Finder, Builder)) {
return true;
}
} else if(const auto *LambdaExprNode = CurNode.get<LambdaExpr>()) {
if(InnerMatcher.matches(*LambdaExprNode->getCallOperator(),
Finder, Builder)) {
return true;
}
} else {
for(const auto &Parent: Finder->getASTContext().getParents(CurNode))
Stack.push_back(Parent);
}
}
return false;
}
/// Matches a declaration that has external formal linkage.
///
/// Example matches only z (matcher = varDecl(hasExternalFormalLinkage()))
/// \code
/// void f() {
/// int x;
/// static int y;
/// }
/// int z;
/// \endcode
///
/// Example matches f() because it has external formal linkage despite being
/// unique to the translation unit as though it has internal likage
/// (matcher = functionDecl(hasExternalFormalLinkage()))
///
/// \code
/// namespace {
/// void f() {}
/// }
/// \endcode
AST_MATCHER(NamedDecl, hasExternalFormalLinkage) {
return Node.hasExternalFormalLinkage();
}
/// Matches a declaration that has default arguments.
///
/// Example matches y (matcher = parmVarDecl(hasDefaultArgument()))
/// \code
/// void x(int val) {}
/// void y(int val = 0) {}
/// \endcode
///
/// Deprecated. Use hasInitializer() instead to be able to
/// match on the contents of the default argument. For example:
///
/// \code
/// void x(int val = 7) {}
/// void y(int val = 42) {}
/// \endcode
/// parmVarDecl(hasInitializer(integerLiteral(equals(42))))
/// matches the parameter of y
///
/// A matcher such as
/// parmVarDecl(hasInitializer(anything()))
/// is equivalent to parmVarDecl(hasDefaultArgument()).
AST_MATCHER(ParmVarDecl, hasDefaultArgument) {
return Node.hasDefaultArg();
}
/// Matches array new expressions.
///
/// Given:
/// \code
/// MyClass *p1 = new MyClass[10];
/// \endcode
/// cxxNewExpr(isArray())
/// matches the expression 'new MyClass[10]'.
AST_MATCHER(CXXNewExpr, isArray) {
return Node.isArray();
}
/// Matches placement new expression arguments.
///
/// Given:
/// \code
/// MyClass *p1 = new (Storage, 16) MyClass();
/// \endcode
/// cxxNewExpr(hasPlacementArg(1, integerLiteral(equals(16))))
/// matches the expression 'new (Storage, 16) MyClass()'.
AST_MATCHER_P2(CXXNewExpr, hasPlacementArg, unsigned, Index,
internal::Matcher<Expr>, InnerMatcher) {
return Node.getNumPlacementArgs() > Index &&
InnerMatcher.matches(*Node.getPlacementArg(Index), Finder, Builder);
}
/// Matches any placement new expression arguments.
///
/// Given:
/// \code
/// MyClass *p1 = new (Storage) MyClass();
/// \endcode
/// cxxNewExpr(hasAnyPlacementArg(anything()))
/// matches the expression 'new (Storage, 16) MyClass()'.
AST_MATCHER_P(CXXNewExpr, hasAnyPlacementArg, internal::Matcher<Expr>,
InnerMatcher) {
return llvm::any_of(Node.placement_arguments(), [&](const Expr *Arg) {
return InnerMatcher.matches(*Arg, Finder, Builder);
});
}
/// Matches array new expressions with a given array size.
///
/// Given:
/// \code
/// MyClass *p1 = new MyClass[10];
/// \endcode
/// cxxNewExpr(hasArraySize(integerLiteral(equals(10))))
/// matches the expression 'new MyClass[10]'.
AST_MATCHER_P(CXXNewExpr, hasArraySize, internal::Matcher<Expr>, InnerMatcher) {
return Node.isArray() && *Node.getArraySize() &&
InnerMatcher.matches(**Node.getArraySize(), Finder, Builder);
}
/// Matches a class declaration that is defined.
///
/// Example matches x (matcher = cxxRecordDecl(hasDefinition()))
/// \code
/// class x {};
/// class y;
/// \endcode
AST_MATCHER(CXXRecordDecl, hasDefinition) {
return Node.hasDefinition();
}
/// Matches C++11 scoped enum declaration.
///
/// Example matches Y (matcher = enumDecl(isScoped()))
/// \code
/// enum X {};
/// enum class Y {};
/// \endcode
AST_MATCHER(EnumDecl, isScoped) {
return Node.isScoped();
}
/// Matches a function declared with a trailing return type.
///
/// Example matches Y (matcher = functionDecl(hasTrailingReturn()))
/// \code
/// int X() {}
/// auto Y() -> int {}
/// \endcode
AST_MATCHER(FunctionDecl, hasTrailingReturn) {
if (const auto *F = Node.getType()->getAs<FunctionProtoType>())
return F->hasTrailingReturn();
return false;
}
/// Matches expressions that match InnerMatcher that are possibly wrapped in an
/// elidable constructor and other corresponding bookkeeping nodes.
///
/// In C++17, elidable copy constructors are no longer being generated in the
/// AST as it is not permitted by the standard. They are, however, part of the
/// AST in C++14 and earlier. So, a matcher must abstract over these differences
/// to work in all language modes. This matcher skips elidable constructor-call
/// AST nodes, `ExprWithCleanups` nodes wrapping elidable constructor-calls and
/// various implicit nodes inside the constructor calls, all of which will not
/// appear in the C++17 AST.
///
/// Given
///
/// \code
/// struct H {};
/// H G();
/// void f() {
/// H D = G();
/// }
/// \endcode
///
/// ``varDecl(hasInitializer(ignoringElidableConstructorCall(callExpr())))``
/// matches ``H D = G()`` in C++11 through C++17 (and beyond).
AST_MATCHER_P(Expr, ignoringElidableConstructorCall,
ast_matchers::internal::Matcher<Expr>, InnerMatcher) {
// E tracks the node that we are examining.
const Expr *E = &Node;
// If present, remove an outer `ExprWithCleanups` corresponding to the
// underlying `CXXConstructExpr`. This check won't cover all cases of added
// `ExprWithCleanups` corresponding to `CXXConstructExpr` nodes (because the
// EWC is placed on the outermost node of the expression, which this may not
// be), but, it still improves the coverage of this matcher.
if (const auto *CleanupsExpr = dyn_cast<ExprWithCleanups>(&Node))
E = CleanupsExpr->getSubExpr();
if (const auto *CtorExpr = dyn_cast<CXXConstructExpr>(E)) {
if (CtorExpr->isElidable()) {
if (const auto *MaterializeTemp =
dyn_cast<MaterializeTemporaryExpr>(CtorExpr->getArg(0))) {
return InnerMatcher.matches(*MaterializeTemp->getSubExpr(), Finder,
Builder);
}
}
}
return InnerMatcher.matches(Node, Finder, Builder);
}
//----------------------------------------------------------------------------//
// OpenMP handling.
//----------------------------------------------------------------------------//
/// Matches any ``#pragma omp`` executable directive.
///
/// Given
///
/// \code
/// #pragma omp parallel
/// #pragma omp parallel default(none)
/// #pragma omp taskyield
/// \endcode
///
/// ``ompExecutableDirective()`` matches ``omp parallel``,
/// ``omp parallel default(none)`` and ``omp taskyield``.
extern const internal::VariadicDynCastAllOfMatcher<Stmt, OMPExecutableDirective>
ompExecutableDirective;
/// Matches standalone OpenMP directives,
/// i.e., directives that can't have a structured block.
///
/// Given
///
/// \code
/// #pragma omp parallel
/// {}
/// #pragma omp taskyield
/// \endcode
///
/// ``ompExecutableDirective(isStandaloneDirective()))`` matches
/// ``omp taskyield``.
AST_MATCHER(OMPExecutableDirective, isStandaloneDirective) {
return Node.isStandaloneDirective();
}
/// Matches the structured-block of the OpenMP executable directive
///
/// Prerequisite: the executable directive must not be standalone directive.
/// If it is, it will never match.
///
/// Given
///
/// \code
/// #pragma omp parallel
/// ;
/// #pragma omp parallel
/// {}
/// \endcode
///
/// ``ompExecutableDirective(hasStructuredBlock(nullStmt()))`` will match ``;``
AST_MATCHER_P(OMPExecutableDirective, hasStructuredBlock,
internal::Matcher<Stmt>, InnerMatcher) {
if (Node.isStandaloneDirective())
return false; // Standalone directives have no structured blocks.
return InnerMatcher.matches(*Node.getStructuredBlock(), Finder, Builder);
}
/// Matches any clause in an OpenMP directive.
///
/// Given
///
/// \code
/// #pragma omp parallel
/// #pragma omp parallel default(none)
/// \endcode
///
/// ``ompExecutableDirective(hasAnyClause(anything()))`` matches
/// ``omp parallel default(none)``.
AST_MATCHER_P(OMPExecutableDirective, hasAnyClause,
internal::Matcher<OMPClause>, InnerMatcher) {
ArrayRef<OMPClause *> Clauses = Node.clauses();
return matchesFirstInPointerRange(InnerMatcher, Clauses.begin(),
Clauses.end(), Finder, Builder);
}
/// Matches OpenMP ``default`` clause.
///
/// Given
///
/// \code
/// #pragma omp parallel default(none)
/// #pragma omp parallel default(shared)
/// #pragma omp parallel
/// \endcode
///
/// ``ompDefaultClause()`` matches ``default(none)`` and ``default(shared)``.
extern const internal::VariadicDynCastAllOfMatcher<OMPClause, OMPDefaultClause>
ompDefaultClause;
/// Matches if the OpenMP ``default`` clause has ``none`` kind specified.
///
/// Given
///
/// \code
/// #pragma omp parallel
/// #pragma omp parallel default(none)
/// #pragma omp parallel default(shared)
/// \endcode
///
/// ``ompDefaultClause(isNoneKind())`` matches only ``default(none)``.
AST_MATCHER(OMPDefaultClause, isNoneKind) {
return Node.getDefaultKind() == llvm::omp::OMP_DEFAULT_none;
}
/// Matches if the OpenMP ``default`` clause has ``shared`` kind specified.
///
/// Given
///
/// \code
/// #pragma omp parallel
/// #pragma omp parallel default(none)
/// #pragma omp parallel default(shared)
/// \endcode
///
/// ``ompDefaultClause(isSharedKind())`` matches only ``default(shared)``.
AST_MATCHER(OMPDefaultClause, isSharedKind) {
return Node.getDefaultKind() == llvm::omp::OMP_DEFAULT_shared;
}
/// Matches if the OpenMP directive is allowed to contain the specified OpenMP
/// clause kind.
///
/// Given
///
/// \code
/// #pragma omp parallel
/// #pragma omp parallel for
/// #pragma omp for
/// \endcode
///
/// `ompExecutableDirective(isAllowedToContainClause(OMPC_default))`` matches
/// ``omp parallel`` and ``omp parallel for``.
///
/// If the matcher is use from clang-query, ``OpenMPClauseKind`` parameter
/// should be passed as a quoted string. e.g.,
/// ``isAllowedToContainClauseKind("OMPC_default").``
AST_MATCHER_P(OMPExecutableDirective, isAllowedToContainClauseKind,
OpenMPClauseKind, CKind) {
return llvm::omp::isAllowedClauseForDirective(
Node.getDirectiveKind(), CKind,
Finder->getASTContext().getLangOpts().OpenMP);
}
//----------------------------------------------------------------------------//
// End OpenMP handling.
//----------------------------------------------------------------------------//
} // namespace ast_matchers
} // namespace clang
#endif // LLVM_CLANG_ASTMATCHERS_ASTMATCHERS_H
|
GB_unaryop__ainv_uint64_fp32.c | //------------------------------------------------------------------------------
// GB_unaryop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2019, All Rights Reserved.
// http://suitesparse.com See GraphBLAS/Doc/License.txt for license.
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_iterator.h"
#include "GB_unaryop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB_unop__ainv_uint64_fp32
// op(A') function: GB_tran__ainv_uint64_fp32
// C type: uint64_t
// A type: float
// cast: uint64_t cij ; GB_CAST_UNSIGNED(cij,aij,64)
// unaryop: cij = -aij
#define GB_ATYPE \
float
#define GB_CTYPE \
uint64_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
float aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = -x ;
// casting
#define GB_CASTING(z, x) \
uint64_t z ; GB_CAST_UNSIGNED(z,x,64) ;
// cij = op (cast (aij))
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GB_GETA (aij, Ax, pA) ; \
/* Cx [pC] = op (cast (aij)) */ \
GB_CASTING (x, aij) ; \
GB_OP (GB_CX (pC), x) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_AINV || GxB_NO_UINT64 || GxB_NO_FP32)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__ainv_uint64_fp32
(
uint64_t *restrict Cx,
const float *restrict Ax,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (int64_t p = 0 ; p < anz ; p++)
{
GB_CAST_OP (p, p) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_tran__ainv_uint64_fp32
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t **Rowcounts,
GBI_single_iterator Iter,
const int64_t *restrict A_slice,
int naslice
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#define GB_PHASE_2_OF_2
#include "GB_unaryop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
GraphIO.h | #ifndef __GRAPH_IO_H__
#define __GRAPH_IO_H__
#include <algorithm>
#include <cassert>
#include <cctype>
#include <cstdio>
#include <cstring>
#include <fstream>
#include <iostream>
#include <limits>
#include <sstream>
#include <string>
#include <unordered_map>
#include "Meta.h"
#include "TimeMeasurer.h"
#if defined(OPENMP)
#include <omp.h>
#endif
enum GraphFormat { SNAP, BIN, SNAP_LVID, ADJ };
class GraphIO {
public:
static void ReadDataFile(std::string& filename, bool directed,
size_t& vertex_count, size_t& edge_count,
uintE*& row_ptrs, uintV*& cols,
GraphFormat graph_format) {
switch (graph_format) {
case SNAP:
ReadSNAPFile(filename, directed, vertex_count, edge_count, row_ptrs,
cols);
break;
case BIN:
ReadCSRBinFile(filename, directed, vertex_count, edge_count, row_ptrs,
cols);
break;
case SNAP_LVID:
ReadSNAPLargeVIDFile(filename, directed, vertex_count, edge_count,
row_ptrs, cols);
break;
default:
assert(false);
}
}
static void ReadDataFile(std::string& filename, bool directed,
size_t& vertex_count, size_t& edge_count,
uintE*& row_ptrs, uintV*& cols) {
std::string suffix = filename.substr(filename.rfind(".") + 1);
GraphFormat graph_format;
if (suffix == "txt") {
graph_format = SNAP;
} else if (suffix == "bin") {
graph_format = BIN;
} else if (suffix == "lvid") {
graph_format = SNAP_LVID;
} else {
assert(false);
}
ReadDataFile(filename, directed, vertex_count, edge_count, row_ptrs, cols,
graph_format);
}
static void ReadPartitionFile(std::string& filename, size_t partition_num,
size_t vertex_count,
uintP* vertex_partition_map) {
if (partition_num == 1 || filename.length() == 0) {
partition_num = 1;
for (uintV u = 0; u < vertex_count; u++) {
vertex_partition_map[u] = 0;
}
} else {
std::ifstream file(filename.c_str(), std::fstream::in);
size_t pid;
size_t max_pid = 0;
for (uintV u = 0; u < vertex_count; ++u) {
file >> pid;
max_pid = std::max(max_pid, pid);
vertex_partition_map[u] = pid;
}
file.close();
assert(max_pid + 1 == partition_num);
}
}
static void ReadCSRBinFile(std::string& filename, bool directed,
size_t& vertex_count, size_t& edge_count,
uintE*& row_ptrs, uintV*& cols) {
// CSR is a homemade format
// It removes parallel edges and self loops, but it may contain dangling
// nodes
vertex_count = 0;
edge_count = 0;
row_ptrs = NULL;
cols = NULL;
TimeMeasurer timer;
timer.StartTimer();
std::cout << "start read csr bin file....";
FILE* file_in = fopen(filename.c_str(), "rb");
assert(file_in != NULL);
fseek(file_in, 0, SEEK_SET);
size_t res = 0;
size_t uintV_size = 0, uintE_size = 0;
res += fread(&uintV_size, sizeof(size_t), 1, file_in);
res += fread(&uintE_size, sizeof(size_t), 1, file_in);
res += fread(&vertex_count, sizeof(size_t), 1, file_in);
res += fread(&edge_count, sizeof(size_t), 1, file_in);
std::cout << "uintV_size=" << uintV_size << ",uintE_size=" << uintE_size
<< std::endl;
std::cout << "vertex_count=" << vertex_count << ",edge_count=" << edge_count
<< std::endl;
assert(uintV_size == sizeof(uintV));
assert(uintE_size == sizeof(uintE));
row_ptrs = new uintE[vertex_count + 1];
cols = new uintV[edge_count];
for (uintV u = 0; u <= vertex_count; ++u) {
res += fread(&row_ptrs[u], sizeof(uintE), 1, file_in);
}
for (uintV u = 0; u < vertex_count; ++u) {
for (uintE j = row_ptrs[u]; j < row_ptrs[u + 1]; ++j) {
res += fread(&cols[j], sizeof(uintV), 1, file_in);
}
}
assert(res == (4 + (vertex_count + 1) + edge_count));
fgetc(file_in);
assert(feof(file_in));
fclose(file_in);
timer.EndTimer();
std::cout << "finish read csr bin file, elapsed_time="
<< timer.GetElapsedMicroSeconds() / 1000.0 << "ms" << std::endl;
}
// Some data graphs may contain large vertex ids, e.g., in web graphs,
// the vertex ids could be some large integers that cannot be stored in
// even in long long int.
// So we need to use a map to sequentialize the vertex ids.
static void ReadSNAPLargeVIDFile(std::string& filename, bool directed,
size_t& vertex_count, size_t& edge_count,
uintE*& row_ptrs, uintV*& cols) {
vertex_count = 0;
edge_count = 0;
row_ptrs = NULL;
cols = NULL;
std::cout << "start build csr..." << std::endl;
// const char* kDelimiters = " ,;\t";
const char* kDelimiters = "0123456789";
std::unordered_map<std::string, uintV> ids;
std::vector<uintV> edge_pairs;
{
std::ifstream file(filename.c_str(), std::fstream::in);
std::string line;
while (getline(file, line)) {
if (line.length() == 0 || !std::isdigit(line[0])) continue;
std::vector<std::string> num_strs;
size_t cur_pos = 0;
while (cur_pos < line.length()) {
cur_pos =
line.find_first_of(kDelimiters, cur_pos, strlen(kDelimiters));
if (cur_pos < line.length()) {
size_t next_pos = line.find_first_not_of(kDelimiters, cur_pos,
strlen(kDelimiters));
num_strs.push_back(line.substr(cur_pos, next_pos - cur_pos));
assert(next_pos > cur_pos);
cur_pos = next_pos;
}
}
for (auto& str : num_strs) {
assert(str.length());
for (auto ch : str) {
assert(std::isdigit(ch));
}
}
for (auto& str : num_strs) {
if (ids.find(str) == ids.end()) {
ids.insert(std::make_pair(str, vertex_count++));
}
edge_pairs.push_back(ids[str]);
}
}
file.close();
}
ids.clear();
std::cout << "edge pairs size=" << edge_pairs.size() << std::endl;
assert(edge_pairs.size() % 2 == 0);
edge_count = edge_pairs.size() / 2;
if (!directed) {
edge_count *= 2;
}
std::vector<uintE> offsets(vertex_count + 1, 0);
for (size_t i = 0; i < edge_pairs.size(); i += 2) {
offsets[edge_pairs[i]]++;
if (!directed) {
offsets[edge_pairs[i + 1]]++;
}
}
row_ptrs = new uintE[vertex_count + 1];
cols = new uintV[edge_count];
uintE prefix = 0;
for (uintV i = 0; i <= vertex_count; ++i) {
row_ptrs[i] = prefix;
prefix += offsets[i];
offsets[i] = row_ptrs[i];
}
for (size_t i = 0; i < edge_pairs.size(); i += 2) {
cols[offsets[edge_pairs[i]]++] = edge_pairs[i + 1];
if (!directed) {
cols[offsets[edge_pairs[i + 1]]++] = edge_pairs[i];
}
}
offsets.clear();
edge_pairs.clear();
SortCSRArray(vertex_count, row_ptrs, cols);
std::cout << "finish building CSR" << std::endl;
}
static void ReadSNAPFile(std::string& filename, bool directed,
size_t& vertex_count, size_t& edge_count,
uintE*& row_ptrs, uintV*& cols) {
vertex_count = 0;
edge_count = 0;
row_ptrs = NULL;
cols = NULL;
std::cout << "start build csr..." << std::endl;
uintV min_vertex_id = kMaxuintV;
uintV max_vertex_id = kMinuintV;
{
std::ifstream file(filename.c_str(), std::fstream::in);
std::string line;
uintV vids[2];
while (getline(file, line)) {
if (line.length() == 0 || !std::isdigit(line[0])) continue;
std::istringstream iss(line);
for (int i = 0; i < 2; ++i) {
iss >> vids[i];
min_vertex_id = std::min(min_vertex_id, vids[i]);
max_vertex_id = std::max(max_vertex_id, vids[i]);
}
edge_count++;
}
file.close();
}
vertex_count = max_vertex_id - min_vertex_id + 1;
if (!directed) edge_count *= 2;
std::cout << "vertex_count=" << vertex_count << ",edge_count=" << edge_count
<< std::endl;
row_ptrs = new uintE[vertex_count + 1];
cols = new uintV[edge_count];
auto offsets = new uintE[vertex_count + 1];
memset(offsets, 0, sizeof(uintE) * (vertex_count + 1));
{
std::ifstream file(filename.c_str(), std::fstream::in);
std::string line;
uintV vids[2];
while (getline(file, line)) {
if (line.length() == 0 || !std::isdigit(line[0])) continue;
std::istringstream iss(line);
for (int i = 0; i < 2; ++i) iss >> vids[i], vids[i] -= min_vertex_id;
offsets[vids[0]]++;
if (!directed) {
offsets[vids[1]]++;
}
}
file.close();
}
uintE prefix = 0;
for (size_t i = 0; i < vertex_count + 1; ++i) {
row_ptrs[i] = prefix;
prefix += offsets[i];
offsets[i] = row_ptrs[i];
}
{
std::ifstream file(filename.c_str(), std::fstream::in);
std::string line;
uintV vids[2];
while (getline(file, line)) {
if (line.length() == 0 || !std::isdigit(line[0])) continue;
std::istringstream iss(line);
for (int i = 0; i < 2; ++i) iss >> vids[i], vids[i] -= min_vertex_id;
cols[offsets[vids[0]]++] = vids[1];
if (!directed) {
cols[offsets[vids[1]]++] = vids[0];
}
}
file.close();
}
delete[] offsets;
offsets = NULL;
SortCSRArray(vertex_count, row_ptrs, cols);
std::cout << "finish building CSR" << std::endl;
}
// for the input of testing
static void ReadFromVector(std::vector<std::vector<uintV>>& data,
size_t& vertex_count, size_t& edge_count,
uintE*& row_ptrs, uintV*& cols) {
vertex_count = data.size();
row_ptrs = new uintE[vertex_count + 1];
uintE sum = 0;
for (uintV u = 0; u < data.size(); ++u) {
row_ptrs[u] = sum;
sum += data[u].size();
}
row_ptrs[vertex_count] = sum;
edge_count = sum;
cols = new uintV[edge_count];
for (uintV u = 0; u < data.size(); ++u) {
for (uintE off = 0; off < data[u].size(); ++off) {
cols[row_ptrs[u] + off] = data[u][off];
assert(data[u][off] < vertex_count);
}
}
}
static void WriteDataFile(GraphFormat graph_format, std::string& filename,
bool directed, size_t vertex_count,
size_t edge_count, uintE* row_ptrs, uintV* cols) {
switch (graph_format) {
case SNAP:
WriteCSRSNAPFile(filename, directed, vertex_count, edge_count, row_ptrs,
cols);
break;
case BIN:
WriteCSRBinFile(filename, directed, vertex_count, edge_count, row_ptrs,
cols);
break;
case ADJ:
WriteCSRAdjFile(filename, directed, vertex_count, edge_count, row_ptrs,
cols);
break;
default:
assert(false);
}
}
static void WriteCSRBinFile(std::string& filename, bool directed,
size_t vertex_count, size_t edge_count,
uintE* row_ptrs, uintV* cols) {
TimeMeasurer timer;
timer.StartTimer();
std::cout << "start write csr bin file....";
std::string output_filename = filename + ".bin";
FILE* file_out = fopen(output_filename.c_str(), "wb");
assert(file_out != NULL);
size_t res = 0;
size_t uintV_size = sizeof(uintV), uintE_size = sizeof(uintE);
fwrite(&uintV_size, sizeof(size_t), 1, file_out);
fwrite(&uintE_size, sizeof(size_t), 1, file_out);
fwrite(&vertex_count, sizeof(size_t), 1, file_out);
fwrite(&edge_count, sizeof(size_t), 1, file_out);
for (uintV u = 0; u <= vertex_count; ++u) {
res += fwrite(&row_ptrs[u], sizeof(uintE), 1, file_out);
}
for (uintV u = 0; u < vertex_count; ++u) {
for (uintE j = row_ptrs[u]; j < row_ptrs[u + 1]; ++j) {
auto v = cols[j];
res += fwrite(&v, sizeof(uintV), 1, file_out);
}
}
assert(res == ((vertex_count + 1) + edge_count));
fclose(file_out);
timer.EndTimer();
std::cout << "finish write csr bin file, output_filename="
<< output_filename
<< ",elapsed_time=" << timer.GetElapsedMicroSeconds() / 1000.0
<< "ms" << std::endl;
}
static void WriteCSRSNAPFile(std::string& filename, bool directed,
size_t vertex_count, size_t edge_count,
uintE* row_ptrs, uintV* cols) {
TimeMeasurer timer;
timer.StartTimer();
std::cout << "start write csr snap file....";
std::string output_filename = filename + ".snap.txt";
std::ofstream file(output_filename.c_str(), std::fstream::out);
for (uintV u = 0; u < vertex_count; ++u) {
for (uintE j = row_ptrs[u]; j < row_ptrs[u + 1]; ++j) {
auto v = cols[j];
if (u < v) {
file << u << " " << v << std::endl;
}
}
}
file.close();
timer.EndTimer();
std::cout << "finish write csr snap file, output_filename="
<< output_filename
<< ",elapsed_time=" << timer.GetElapsedMicroSeconds() / 1000.0
<< "ms" << std::endl;
}
// for fennel
static void WriteCSRAdjFile(std::string& filename, bool directed,
size_t vertex_count, size_t edge_count,
uintE* row_ptrs, uintV* cols) {
TimeMeasurer timer;
timer.StartTimer();
std::cout << "start write csr adj file....";
std::string output_filename = filename + ".adj.txt";
std::ofstream file(output_filename.c_str(), std::fstream::out);
for (uintV u = 0; u < vertex_count; ++u) {
file << u << "\t";
for (uintE j = row_ptrs[u]; j < row_ptrs[u + 1]; ++j) {
auto v = cols[j];
file << v << " ";
}
file << std::endl;
}
file.close();
std::string info_output_filename = filename + ".adj.txt.info";
std::ofstream info_file(info_output_filename.c_str(), std::fstream::out);
info_file << vertex_count << " " << edge_count;
info_file.close();
timer.EndTimer();
std::cout << "finish write csr adj file, output_filename="
<< output_filename
<< ",elapsed_time=" << timer.GetElapsedMicroSeconds() / 1000.0
<< "ms" << std::endl;
}
static void SortCSRArray(size_t vertex_count, uintE* row_ptrs, uintV* cols) {
#if defined(OPENMP)
#pragma omp parallel for schedule(dynamic)
for (uintV u = 0; u < vertex_count; ++u) {
std::sort(cols + row_ptrs[u], cols + row_ptrs[u + 1]);
}
#else
std::cout << "start sorting..." << std::endl;
for (uintV u = 0; u < vertex_count; ++u) {
std::sort(cols + row_ptrs[u], cols + row_ptrs[u + 1]);
}
#endif
}
static void Validate(size_t vertex_count, uintE* row_ptrs, uintV* cols) {
// ensure edge list of each vertex is sorted
// ensure no self loops
// ensure no parallel edges
size_t dangling = 0;
size_t self_loops = 0;
size_t parallel_edges = 0;
for (uintV u = 0; u < vertex_count; ++u) {
if (row_ptrs[u] == row_ptrs[u + 1]) {
dangling++;
}
for (uintE j = row_ptrs[u]; j < row_ptrs[u + 1]; ++j) {
auto v = cols[j];
if (u == v) self_loops++;
if (j > row_ptrs[u]) {
if (v == cols[j - 1]) parallel_edges++;
}
}
}
if (dangling)
std::cout << "Warning: dangling_nodes=" << dangling << std::endl;
if (self_loops)
std::cout << "Warning: self_loops=" << self_loops << std::endl;
if (parallel_edges)
std::cout << "Warning: parallel_edges=" << parallel_edges << std::endl;
assert(dangling == 0 && self_loops == 0 && parallel_edges == 0);
}
};
#endif
|
GB_binop__isge_fp32.c | //------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_emult.h"
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB (_AaddB__isge_fp32)
// A.*B function (eWiseMult): GB (_AemultB_01__isge_fp32)
// A.*B function (eWiseMult): GB (_AemultB_02__isge_fp32)
// A.*B function (eWiseMult): GB (_AemultB_03__isge_fp32)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__isge_fp32)
// A*D function (colscale): GB (_AxD__isge_fp32)
// D*A function (rowscale): GB (_DxB__isge_fp32)
// C+=B function (dense accum): GB (_Cdense_accumB__isge_fp32)
// C+=b function (dense accum): GB (_Cdense_accumb__isge_fp32)
// C+=A+B function (dense ewise3): GB ((none))
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__isge_fp32)
// C=scalar+B GB (_bind1st__isge_fp32)
// C=scalar+B' GB (_bind1st_tran__isge_fp32)
// C=A+scalar GB (_bind2nd__isge_fp32)
// C=A'+scalar GB (_bind2nd_tran__isge_fp32)
// C type: float
// A type: float
// B,b type: float
// BinaryOp: cij = (aij >= bij)
#define GB_ATYPE \
float
#define GB_BTYPE \
float
#define GB_CTYPE \
float
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
1
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
1
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA,A_iso) \
float aij = GBX (Ax, pA, A_iso)
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB,B_iso) \
float bij = GBX (Bx, pB, B_iso)
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
float t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA,A_iso) \
cij = GBX (Ax, pA, A_iso)
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB,B_iso) \
cij = GBX (Bx, pB, B_iso)
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z,x,y,i,j) \
z = (x >= y) ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
0
// op is second
#define GB_OP_IS_SECOND \
0
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_ISGE || GxB_NO_FP32 || GxB_NO_ISGE_FP32)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
#if 0
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
#endif
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_ewise3_noaccum__isge_fp32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_dense_ewise3_noaccum_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumB__isge_fp32)
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *B_ek_slicing, const int B_ntasks, const int B_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
#include "GB_dense_subassign_23_template.c"
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumb__isge_fp32)
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
// get the scalar b for C += b, of type float
float bwork = (*((float *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_AxD__isge_fp32)
(
GrB_Matrix C,
const GrB_Matrix A, bool A_is_pattern,
const GrB_Matrix D, bool D_is_pattern,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
float *restrict Cx = (float *) C->x ;
#include "GB_AxB_colscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_DxB__isge_fp32)
(
GrB_Matrix C,
const GrB_Matrix D, bool D_is_pattern,
const GrB_Matrix B, bool B_is_pattern,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
float *restrict Cx = (float *) C->x ;
#include "GB_AxB_rowscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C = A+B or C<M> = A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__isge_fp32)
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool Ch_is_Mh,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GB_WERK_DECLARE (M_ek_slicing, int64_t) ;
GB_WERK_DECLARE (A_ek_slicing, int64_t) ;
GB_WERK_DECLARE (B_ek_slicing, int64_t) ;
#include "GB_add_template.c"
GB_FREE_WORK ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C = A.*B or C<M> = A.*B
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_01__isge_fp32)
(
GrB_Matrix C,
const int C_sparsity,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_01_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<#> = A.*B when A is sparse/hyper and B is bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_02__isge_fp32)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool flipxy,
const int64_t *restrict Cp_kfirst,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if GB_BINOP_FLIP
// The operator is not commutative, and does not have a flipped
// variant. For example z=atan2(y,x).
if (flipxy)
{
// use fmult(y,x)
#undef GB_FLIPPED
#define GB_FLIPPED 1
#include "GB_emult_02_template.c"
}
else
{
// use fmult(x,y)
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
}
#else
// No need to handle the flip: the operator is either commutative, or
// has been handled by changing z=div(y,x) to z=rdiv(x,y) for example.
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<M> = A.*B, M sparse/hyper, A and B bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_03__isge_fp32)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict Cp_kfirst,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_03_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, C<!M>=A.*B where C is bitmap
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_bitmap__isge_fp32)
(
GrB_Matrix C,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_bitmap_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB (_bind1st__isge_fp32)
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *restrict Bb,
int64_t bnz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
float *Cx = (float *) Cx_output ;
float x = (*((float *) x_input)) ;
float *Bx = (float *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < bnz ; p++)
{
if (!GBB (Bb, p)) continue ;
float bij = GBX (Bx, p, false) ;
Cx [p] = (x >= bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__isge_fp32)
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *restrict Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
float *Cx = (float *) Cx_output ;
float *Ax = (float *) Ax_input ;
float y = (*((float *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
float aij = GBX (Ax, p, false) ;
Cx [p] = (aij >= y) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
float aij = GBX (Ax, pA, false) ; \
Cx [pC] = (x >= aij) ; \
}
GrB_Info GB (_bind1st_tran__isge_fp32)
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
float
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
float x = (*((const float *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
float
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
float aij = GBX (Ax, pA, false) ; \
Cx [pC] = (aij >= y) ; \
}
GrB_Info GB (_bind2nd_tran__isge_fp32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
float y = (*((const float *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
mxnet_op.h | /*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
/*!
* Copyright (c) 2017 by Contributors
* \file mxnet_op.h
* \brief
* \author Junyuan Xie
*/
#ifndef MXNET_OPERATOR_MXNET_OP_H_
#define MXNET_OPERATOR_MXNET_OP_H_
#include <dmlc/omp.h>
#include <mxnet/base.h>
#include <mxnet/engine.h>
#include <mxnet/op_attr_types.h>
#include <algorithm>
#include "./operator_tune.h"
#include "../engine/openmp.h"
#ifdef __CUDACC__
#include "../common/cuda_utils.h"
#endif // __CUDACC__
namespace mxnet {
namespace op {
namespace mxnet_op {
using namespace mshadow;
#ifdef __CUDA_ARCH__
__constant__ const float PI = 3.14159265358979323846;
#else
const float PI = 3.14159265358979323846;
using std::isnan;
#endif
template<typename xpu>
int get_num_threads(const int N);
#ifdef __CUDACC__
#define CUDA_KERNEL_LOOP(i, n) \
for (int i = blockIdx.x * blockDim.x + threadIdx.x; \
i < (n); \
i += blockDim.x * gridDim.x)
inline cudaDeviceProp cuda_get_device_prop() {
int device;
CUDA_CALL(cudaGetDevice(&device));
cudaDeviceProp deviceProp;
CUDA_CALL(cudaGetDeviceProperties(&deviceProp, device));
return deviceProp;
}
/*!
* \brief Get the number of blocks for cuda kernel given N
*/
inline int cuda_get_num_blocks(const int N) {
using namespace mshadow::cuda;
return std::min(kMaxGridNum, (N + kBaseThreadNum - 1) / kBaseThreadNum);
}
template<>
inline int get_num_threads<gpu>(const int N) {
using namespace mshadow::cuda;
return kBaseThreadNum * cuda_get_num_blocks(N);
}
#endif // __CUDACC__
template<>
inline int get_num_threads<cpu>(const int N) {
return engine::OpenMP::Get()->GetRecommendedOMPThreadCount();
}
/*! \brief operator request type switch */
#define MXNET_ASSIGN_REQ_SWITCH(req, ReqType, ...) \
switch (req) { \
case kNullOp: \
break; \
case kWriteInplace: \
case kWriteTo: \
{ \
const OpReqType ReqType = kWriteTo; \
{__VA_ARGS__} \
} \
break; \
case kAddTo: \
{ \
const OpReqType ReqType = kAddTo; \
{__VA_ARGS__} \
} \
break; \
default: \
break; \
}
/*! \brief operator request type switch */
#define MXNET_REQ_TYPE_SWITCH(req, ReqType, ...) \
switch (req) { \
case kNullOp: \
{ \
const OpReqType ReqType = kNullOp; \
{__VA_ARGS__} \
} \
break; \
case kWriteInplace: \
case kWriteTo: \
{ \
const OpReqType ReqType = kWriteTo; \
{__VA_ARGS__} \
} \
break; \
case kAddTo: \
{ \
const OpReqType ReqType = kAddTo; \
{__VA_ARGS__} \
} \
break; \
default: \
break; \
}
#define MXNET_NDIM_SWITCH(NDim, ndim, ...) \
if (NDim == 0) { \
} else if (NDim == 1) { \
const int ndim = 1; \
{__VA_ARGS__} \
} else if (NDim == 2) { \
const int ndim = 2; \
{__VA_ARGS__} \
} else if (NDim == 3) { \
const int ndim = 3; \
{__VA_ARGS__} \
} else if (NDim == 4) { \
const int ndim = 4; \
{__VA_ARGS__} \
} else if (NDim == 5) { \
const int ndim = 5; \
{__VA_ARGS__} \
} else { \
LOG(FATAL) << "ndim=" << NDim << "too large "; \
}
#define MXNET_NO_INT8_TYPE_SWITCH(type, DType, ...) \
switch (type) { \
case mshadow::kFloat32: \
{ \
typedef float DType; \
{__VA_ARGS__} \
} \
break; \
case mshadow::kFloat64: \
{ \
typedef double DType; \
{__VA_ARGS__} \
} \
break; \
case mshadow::kFloat16: \
{ \
typedef mshadow::half::half_t DType; \
{__VA_ARGS__} \
} \
break; \
case mshadow::kUint8: \
LOG(FATAL) << "This operation does not " \
"support int8 or uint8"; \
break; \
case mshadow::kInt8: \
LOG(FATAL) << "This operation does not " \
"support int8 or uint8"; \
break; \
case mshadow::kInt32: \
{ \
typedef int32_t DType; \
{__VA_ARGS__} \
} \
break; \
case mshadow::kInt64: \
{ \
typedef int64_t DType; \
{__VA_ARGS__} \
} \
break; \
default: \
LOG(FATAL) << "Unknown type enum " << type; \
}
#define MXNET_NO_FLOAT16_TYPE_SWITCH(type, DType, ...) \
switch (type) { \
case mshadow::kFloat32: \
{ \
typedef float DType; \
{__VA_ARGS__} \
} \
break; \
case mshadow::kFloat64: \
{ \
typedef double DType; \
{__VA_ARGS__} \
} \
break; \
case mshadow::kFloat16: \
LOG(FATAL) << "This operation does not " \
"support float16"; \
break; \
case mshadow::kUint8: \
{ \
typedef uint8_t DType; \
{__VA_ARGS__} \
} \
break; \
case mshadow::kInt8: \
{ \
typedef int8_t DType; \
{__VA_ARGS__} \
} \
break; \
case mshadow::kInt32: \
{ \
typedef int32_t DType; \
{__VA_ARGS__} \
} \
break; \
case mshadow::kInt64: \
{ \
typedef int64_t DType; \
{__VA_ARGS__} \
} \
break; \
default: \
LOG(FATAL) << "Unknown type enum " << type; \
}
/*!
* \brief assign the val to out according
* to request in Kernel::Launch
* \param out the data to be assigned
* \param req the assignment request
* \param val the value to be assigned to out
* \tparam OType output type
* \tparam VType value type
*/
#define KERNEL_ASSIGN(out, req, val) \
{ \
switch (req) { \
case kNullOp: \
break; \
case kWriteTo: \
case kWriteInplace: \
(out) = (val); \
break; \
case kAddTo: \
(out) += (val); \
break; \
default: \
break; \
} \
}
#define MXNET_ADD_ALL_TYPES \
.add_enum("float32", mshadow::kFloat32) \
.add_enum("float64", mshadow::kFloat64) \
.add_enum("float16", mshadow::kFloat16) \
.add_enum("uint8", mshadow::kUint8) \
.add_enum("int8", mshadow::kInt8) \
.add_enum("int32", mshadow::kInt32) \
.add_enum("int64", mshadow::kInt64)
/* \brief Compute flattened index given coordinates and shape. */
template<int ndim>
MSHADOW_XINLINE index_t ravel(const Shape<ndim>& coord, const Shape<ndim>& shape) {
index_t ret = 0;
#pragma unroll
for (int i = 0; i < ndim; ++i) {
ret = ret * shape[i] + (shape[i] > coord[i]) * coord[i];
}
return ret;
}
/* Compute coordinates from flattened index given shape */
template<int ndim>
MSHADOW_XINLINE Shape<ndim> unravel(const index_t idx, const Shape<ndim>& shape) {
Shape<ndim> ret;
#pragma unroll
for (index_t i = ndim-1, j = idx; i >=0; --i) {
auto tmp = j / shape[i];
ret[i] = j - tmp*shape[i];
j = tmp;
}
return ret;
}
/* Compute dot product of two vector */
template<int ndim>
MSHADOW_XINLINE index_t dot(const Shape<ndim>& coord, const Shape<ndim>& stride) {
index_t ret = 0;
#pragma unroll
for (int i = 0; i < ndim; ++i) {
ret += coord[i] * stride[i];
}
return ret;
}
/* Combining unravel and dot */
template<int ndim>
MSHADOW_XINLINE index_t unravel_dot(const index_t idx, const Shape<ndim>& shape,
const Shape<ndim>& stride) {
index_t ret = 0;
#pragma unroll
for (index_t i = ndim-1, j = idx; i >=0; --i) {
auto tmp = j / shape[i];
ret += (j - tmp*shape[i])*stride[i];
j = tmp;
}
return ret;
}
/* Calculate stride of each dim from shape */
template<int ndim>
MSHADOW_XINLINE Shape<ndim> calc_stride(const Shape<ndim>& shape) {
Shape<ndim> stride;
index_t cumprod = 1;
#pragma unroll
for (int i = ndim - 1; i >= 0; --i) {
stride[i] = (shape[i] > 1) ? cumprod : 0;
cumprod *= shape[i];
}
return stride;
}
/* Increment coordinates and modify index */
template<int ndim>
MSHADOW_XINLINE void inc(Shape<ndim>* coord, const Shape<ndim>& shape,
index_t* idx, const Shape<ndim>& stride) {
++(*coord)[ndim-1];
*idx += stride[ndim-1];
#pragma unroll
for (int i = ndim - 1; i > 0 && (*coord)[i] >= shape[i]; --i) {
(*coord)[i] -= shape[i];
++(*coord)[i-1];
*idx = *idx + stride[i-1] - shape[i] * stride[i];
}
}
/* Increment coordinates and modify index */
template<int ndim>
MSHADOW_XINLINE void inc(Shape<ndim>* coord, const Shape<ndim>& shape,
index_t* idx1, const Shape<ndim>& stride1,
index_t* idx2, const Shape<ndim>& stride2) {
++(*coord)[ndim-1];
*idx1 += stride1[ndim-1];
*idx2 += stride2[ndim-1];
#pragma unroll
for (int i = ndim - 1; i > 0 && (*coord)[i] >= shape[i]; --i) {
(*coord)[i] -= shape[i];
++(*coord)[i-1];
*idx1 = *idx1 + stride1[i-1] - shape[i] * stride1[i];
*idx2 = *idx2 + stride2[i-1] - shape[i] * stride2[i];
}
}
/*!
* \brief Simple copy data from one blob to another
* \param to Destination blob
* \param from Source blob
*/
template <typename xpu>
MSHADOW_CINLINE void copy(mshadow::Stream<xpu> *s, const TBlob& to, const TBlob& from) {
CHECK_EQ(from.Size(), to.Size());
CHECK_EQ(from.dev_mask(), to.dev_mask());
MSHADOW_TYPE_SWITCH(to.type_flag_, DType, {
if (to.type_flag_ == from.type_flag_) {
mshadow::Copy(to.FlatTo1D<xpu, DType>(s), from.FlatTo1D<xpu, DType>(s), s);
} else {
MSHADOW_TYPE_SWITCH(from.type_flag_, SrcDType, {
to.FlatTo1D<xpu, DType>(s) = mshadow::expr::tcast<DType>(from.FlatTo1D<xpu, SrcDType>(s));
})
}
})
}
/*! \brief Binary op backward gradient OP wrapper */
template<typename GRAD_OP>
struct backward_grad {
/* \brief Backward calc with grad
* \param a - output grad
* \param args... - data to grad calculation op (what this is -- input, output, etc. -- varies)
* \return input grad
*/
template<typename DType, typename ...Args>
MSHADOW_XINLINE static DType Map(DType a, Args... args) {
return DType(a * GRAD_OP::Map(args...));
}
};
/*! \brief Binary op backward gradient OP wrapper (tuned) */
template<typename GRAD_OP>
struct backward_grad_tuned : public backward_grad<GRAD_OP>, public tunable {
using backward_grad<GRAD_OP>::Map;
};
/*! \brief Select assignment operation based upon the req value
* Also useful for mapping mshadow Compute (F<OP>) to Kernel<OP>::Launch
*/
template<typename OP, int req>
struct op_with_req {
typedef OP Operation;
/*! \brief input is one tensor */
template<typename DType>
MSHADOW_XINLINE static void Map(index_t i, DType *out, const DType *in) {
KERNEL_ASSIGN(out[i], req, OP::Map(in[i]));
}
/*! \brief inputs are two tensors */
template<typename DType>
MSHADOW_XINLINE static void Map(index_t i, DType *out, const DType *lhs, const DType *rhs) {
KERNEL_ASSIGN(out[i], req, OP::Map(lhs[i], rhs[i]));
}
/*! \brief input is tensor and a scalar value */
template<typename DType>
MSHADOW_XINLINE static void Map(index_t i, DType *out, const DType *in, const DType value) {
KERNEL_ASSIGN(out[i], req, OP::Map(in[i], value));
}
/*! \brief input is tensor and two scalar value */
template<typename DType>
MSHADOW_XINLINE static void Map(index_t i, DType *out, const DType *in,
const DType value_1, const DType value_2) {
KERNEL_ASSIGN(out[i], req, OP::Map(in[i], value_1, value_2));
}
/*! \brief No inputs (ie fill to constant value) */
template<typename DType>
MSHADOW_XINLINE static void Map(index_t i, DType *out) {
KERNEL_ASSIGN(out[i], req, OP::Map());
}
/*! \brief input is single scalar value */
template<typename DType>
MSHADOW_XINLINE static void Map(index_t i, DType *out, const DType value) {
KERNEL_ASSIGN(out[i], req, OP::Map(value));
}
/*! \brief inputs are two tensors and a scalar value */
template<typename DType>
MSHADOW_XINLINE static void Map(index_t i, DType *out,
const DType *input_1, const DType *input_2, const DType value) {
KERNEL_ASSIGN(out[i], req, OP::Map(input_1[i], input_2[i], value));
}
/*! \brief inputs are three tensors (ie backward grad with binary grad function) */
template<typename DType>
MSHADOW_XINLINE static void Map(index_t i, DType *out,
const DType *input_1,
const DType *input_2,
const DType *input_3) {
KERNEL_ASSIGN(out[i], req, OP::Map(input_1[i], input_2[i], input_3[i]));
}
};
template<typename OP, typename xpu>
struct Kernel;
/*!
* \brief CPU Kernel launcher
* \tparam OP Operator to launch
*/
template<typename OP>
struct Kernel<OP, cpu> {
/*!
* \brief Launch a generic CPU kernel.
* When using this for a new kernel op, add declaration and tuning objects to
* operator_tune.cc
* \tparam Args Varargs type to eventually pass to the OP::Map() function
* \param N Number of iterations
* \param args Varargs to eventually pass to the OP::Map() function
*/
template<typename ...Args>
inline static bool Launch(mshadow::Stream<cpu> *, const size_t N, Args... args) {
#ifdef _OPENMP
const int omp_threads = engine::OpenMP::Get()->GetRecommendedOMPThreadCount();
if (omp_threads < 2) {
for (size_t i = 0; i < N; ++i) {
OP::Map(i, args...);
}
} else {
#pragma omp parallel for num_threads(omp_threads)
for (index_t i = 0; i < static_cast<index_t>(N); ++i) {
OP::Map(i, args...);
}
}
#else
for (size_t i = 0; i < N; ++i) {
OP::Map(i, args...);
}
#endif
return true;
}
/*!
* \brief Launch a generic CPU kernel with dynamic schedule. This is recommended
* for irregular workloads such as spmv.
* When using this for a new kernel op, add declaration and tuning objects to
* operator_tune.cc
* \tparam Args Varargs type to eventually pass to the OP::Map() function
* \param N Number of iterations
* \param args Varargs to eventually pass to the OP::Map() function
*/
template<typename ...Args>
inline static bool LaunchDynamic(mshadow::Stream<cpu> *, const int64_t N, Args... args) {
#ifdef _OPENMP
const int omp_threads = engine::OpenMP::Get()->GetRecommendedOMPThreadCount(false);
if (omp_threads < 2) {
for (int64_t i = 0; i < N; ++i) {
OP::Map(i, args...);
}
} else {
#pragma omp parallel for num_threads(omp_threads) schedule(dynamic)
for (int64_t i = 0; i < N; ++i) {
OP::Map(i, args...);
}
}
#else
for (int64_t i = 0; i < N; ++i) {
OP::Map(i, args...);
}
#endif
return true;
}
/*!
* \brief Launch CPU kernel which has OMP tuning data available.
* When using this for a new kernel op, add declaration and tuning objects to
* operator_tune.cc
* \tparam PRIMITIVE_OP The primitive operation to use for tuning
* \tparam DType Data type
* \tparam Args Varargs type to eventually pass to the OP::Map() function
* \param N Number of iterations
* \param dest Destination pointer (used to infer DType)
* \param args Varargs to eventually pass to the OP::Map() function
*/
template<typename PRIMITIVE_OP, typename DType, typename ...Args>
static void LaunchTuned(mshadow::Stream<cpu> *, const size_t N, Args... args) {
#ifdef _OPENMP
const int omp_threads = engine::OpenMP::Get()->GetRecommendedOMPThreadCount();
if (omp_threads < 2 || !tuned_op<PRIMITIVE_OP, DType>::UseOMP(
N, static_cast<size_t>(omp_threads))) {
for (size_t i = 0; i < N; ++i) {
OP::Map(i, args...);
}
} else {
#pragma omp parallel for num_threads(omp_threads)
for (index_t i = 0; i < static_cast<index_t>(N); ++i) {
OP::Map(i, args...);
}
}
#else
for (size_t i = 0; i < N; ++i) {
OP::Map(i, args...);
}
#endif
}
/*!
* \brief Launch custom-tuned kernel where each thread is set to
* operate on a contiguous partition
* \tparam Args Varargs type to eventually pass to the OP::Map() function
* \param N Number of iterations
* \param args Varargs to eventually pass to the UseOMP() and OP::Map() functions
*/
template<typename ...Args>
inline static void LaunchEx(mshadow::Stream<cpu> *s, const size_t N, Args... args) {
#ifdef _OPENMP
const int omp_threads = engine::OpenMP::Get()->GetRecommendedOMPThreadCount();
if (omp_threads < 2) {
OP::Map(0, N, args...);
} else {
const auto length = (N + omp_threads - 1) / omp_threads;
#pragma omp parallel for num_threads(omp_threads)
for (index_t i = 0; i < static_cast<index_t>(N); i += length) {
OP::Map(i, i + length > N ? N - i : length, args...);
}
}
#else
OP::Map(0, N, args...);
#endif
}
/*!
* \brief Launch a tunable OP with implicitly-supplied data type
* \tparam DType Data type
* \tparam T OP type
* \tparam Args Varargs type to eventually pass to the OP::Map() function
* \param s Stream (usually null for CPU)
* \param N Number of iterations
* \param args Varargs to eventually pass to the OP::Map() function
* \return Always true
*/
template<typename DType, typename T = OP, typename ...Args>
static MSHADOW_CINLINE
typename std::enable_if<std::is_base_of<tunable, T>::value, bool>::type
Launch(mshadow::Stream<cpu> *s, const size_t N, DType *dest, Args... args) {
LaunchTuned<T, DType>(s, N, dest, args...);
return true;
}
/*!
* \brief Launch a tunable OP wrapper with explicitly-supplied data type (ie op_with_req)
* \tparam DType Data type
* \tparam T Wrapper type
* \tparam Args Varargs type to eventually pass to the OP::Map() function
* \param s Stream (usually null for CPU)
* \param N Number of iterations
* \param args Varargs to eventually pass to the OP::Map() function
* \return Always true
*/
template<typename DType, typename T = OP, typename ...Args>
static MSHADOW_CINLINE
typename std::enable_if<std::is_base_of<tunable, typename T::Operation>::value, bool>::type
Launch(mshadow::Stream<cpu> *s, const size_t N, DType *dest, Args... args) {
LaunchTuned<typename T::Operation, DType>(s, N, dest, args...);
return true;
}
};
#ifdef __CUDACC__
template<typename OP, typename ...Args>
__global__ void mxnet_generic_kernel(int N, Args... args) {
for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < N; i += blockDim.x * gridDim.x) {
OP::Map(i, args...);
}
}
template<typename OP, typename ...Args>
__global__ void mxnet_generic_kernel_ex(int N, Args... args) {
for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < N; i += blockDim.x * gridDim.x) {
OP::Map(i, 1, args...);
}
}
template<typename OP>
struct Kernel<OP, gpu> {
/*! \brief Launch GPU kernel */
template<typename ...Args>
inline static void Launch(mshadow::Stream<gpu> *s, int N, Args... args) {
using namespace mshadow::cuda;
int ngrid = std::min(kMaxGridNum, (N + kBaseThreadNum - 1) / kBaseThreadNum);
mxnet_generic_kernel<OP, Args...>
<<<ngrid, kBaseThreadNum, 0, mshadow::Stream<gpu>::GetStream(s)>>>(
N, args...);
MSHADOW_CUDA_POST_KERNEL_CHECK(mxnet_generic_kernel);
}
template<typename ...Args>
inline static void LaunchEx(mshadow::Stream<gpu> *s, const int N, Args... args) {
using namespace mshadow::cuda;
int ngrid = std::min(kMaxGridNum, (N + kBaseThreadNum - 1) / kBaseThreadNum);
mxnet_generic_kernel_ex<OP, Args...>
<<<ngrid, kBaseThreadNum, 0, mshadow::Stream<gpu>::GetStream(s)>>>(
N, args...);
MSHADOW_CUDA_POST_KERNEL_CHECK(mxnet_generic_kernel_ex);
}
};
#endif // __CUDACC__
/*!
* \brief Set to immediate scalar value kernel
* \tparam val Scalar immediate
*/
template<int val>
struct set_to_int : public tunable {
// mxnet_op version (when used directly with Kernel<>::Launch()) */
template<typename DType>
MSHADOW_XINLINE static void Map(index_t i, DType *out) {
out[i] = DType(val);
}
// mshadow_op version (when used with op_with_req<>)
MSHADOW_XINLINE static int Map() {
return val;
}
};
/*!
* \brief Special-case kernel shortcut for setting to zero and one
*/
using set_zero = set_to_int<0>;
using set_one = set_to_int<1>;
} // namespace mxnet_op
} // namespace op
} // namespace mxnet
#endif // MXNET_OPERATOR_MXNET_OP_H_
|
omp_taskyield.c | // RUN: %libomp-compile-and-run
#include <stdio.h>
#include <math.h>
#include "omp_testsuite.h"
#include "omp_my_sleep.h"
int test_omp_taskyield()
{
int i;
int count = 0;
int start_tid[NUM_TASKS];
int current_tid[NUM_TASKS];
for (i=0; i< NUM_TASKS; i++) {
start_tid[i]=0;
current_tid[i]=0;
}
#pragma omp parallel
{
#pragma omp single
{
for (i = 0; i < NUM_TASKS; i++) {
int myi = i;
#pragma omp task untied
{
my_sleep(SLEEPTIME);
start_tid[myi] = omp_get_thread_num();
#pragma omp taskyield
if((start_tid[myi] %2) ==0){
my_sleep(SLEEPTIME);
current_tid[myi] = omp_get_thread_num();
} /*end of if*/
} /* end of omp task */
} /* end of for */
} /* end of single */
} /* end of parallel */
for (i=0;i<NUM_TASKS; i++) {
//printf("start_tid[%d]=%d, current_tid[%d]=%d\n",
//i, start_tid[i], i , current_tid[i]);
if (current_tid[i] == start_tid[i])
count++;
}
return (count<NUM_TASKS);
}
int main()
{
int i;
int num_failed=0;
if (omp_get_max_threads() < 2)
omp_set_num_threads(8);
for(i = 0; i < REPETITIONS; i++) {
if(!test_omp_taskyield()) {
num_failed++;
}
}
return num_failed;
}
|
colorspace.c | /*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% CCCC OOO L OOO RRRR SSSSS PPPP AAA CCCC EEEEE %
% C O O L O O R R SS P P A A C E %
% C O O L O O RRRR SSS PPPP AAAAA C EEE %
% C O O L O O R R SS P A A C E %
% CCCC OOO LLLLL OOO R R SSSSS P A A CCCC EEEEE %
% %
% %
% MagickCore Image Colorspace Methods %
% %
% Software Design %
% John Cristy %
% July 1992 %
% %
% %
% Copyright 1999-2012 ImageMagick Studio LLC, a non-profit organization %
% dedicated to making software imaging solutions freely available. %
% %
% You may not use this file except in compliance with the License. You may %
% obtain a copy of the License at %
% %
% http://www.imagemagick.org/script/license.php %
% %
% Unless required by applicable law or agreed to in writing, software %
% distributed under the License is distributed on an "AS IS" BASIS, %
% WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. %
% See the License for the specific language governing permissions and %
% limitations under the License. %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
%
*/
/*
Include declarations.
*/
#include "magick/studio.h"
#include "magick/property.h"
#include "magick/cache.h"
#include "magick/cache-private.h"
#include "magick/cache-view.h"
#include "magick/color.h"
#include "magick/color-private.h"
#include "magick/colorspace.h"
#include "magick/colorspace-private.h"
#include "magick/exception.h"
#include "magick/exception-private.h"
#include "magick/image.h"
#include "magick/image-private.h"
#include "magick/gem.h"
#include "magick/memory_.h"
#include "magick/monitor.h"
#include "magick/monitor-private.h"
#include "magick/pixel-private.h"
#include "magick/quantize.h"
#include "magick/quantum.h"
#include "magick/string_.h"
#include "magick/string-private.h"
#include "magick/utility.h"
/*
Typedef declarations.
*/
typedef struct _TransformPacket
{
MagickRealType
x,
y,
z;
} TransformPacket;
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
+ R G B T r a n s f o r m I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% RGBTransformImage() converts the reference image from RGB to an alternate
% colorspace. The transformation matrices are not the standard ones: the
% weights are rescaled to normalized the range of the transformed values to
% be [0..QuantumRange].
%
% The format of the RGBTransformImage method is:
%
% MagickBooleanType RGBTransformImage(Image *image,
% const ColorspaceType colorspace)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o colorspace: the colorspace to transform the image to.
%
*/
static inline void ConvertRGBToXYZ(const Quantum red,const Quantum green,
const Quantum blue,double *X,double *Y,double *Z)
{
double
b,
g,
r;
assert(X != (double *) NULL);
assert(Y != (double *) NULL);
assert(Z != (double *) NULL);
r=QuantumScale*red;
if (r > 0.04045)
r=pow((r+0.055)/1.055,2.4);
else
r/=12.92;
g=QuantumScale*green;
if (g > 0.04045)
g=pow((g+0.055)/1.055,2.4);
else
g/=12.92;
b=QuantumScale*blue;
if (b > 0.04045)
b=pow((b+0.055)/1.055,2.4);
else
b/=12.92;
*X=0.4124240*r+0.3575790*g+0.1804640*b;
*Y=0.2126560*r+0.7151580*g+0.0721856*b;
*Z=0.0193324*r+0.1191930*g+0.9504440*b;
}
static double LabF1(double alpha)
{
if (alpha <= ((24.0/116.0)*(24.0/116.0)*(24.0/116.0)))
return((841.0/108.0)*alpha+(16.0/116.0));
return(pow(alpha,1.0/3.0));
}
static inline void ConvertXYZToLab(const double X,const double Y,const double Z,
double *L,double *a,double *b)
{
#define D50X (0.9642)
#define D50Y (1.0)
#define D50Z (0.8249)
double
fx,
fy,
fz;
assert(L != (double *) NULL);
assert(a != (double *) NULL);
assert(b != (double *) NULL);
*L=0.0;
*a=0.5;
*b=0.5;
if ((X == 0.0) && (Y == 0.0) && (Z == 0.0))
return;
fx=LabF1(X/D50X);
fy=LabF1(Y/D50Y);
fz=LabF1(Z/D50Z);
*L=(116.0*fy-16.0)/100.0;
*a=(500.0*(fx-fy))/255.0;
if (*a < 0.0)
*a+=1.0;
*b=(200.0*(fy-fz))/255.0;
if (*b < 0.0)
*b+=1.0;
}
MagickExport MagickBooleanType RGBTransformImage(Image *image,
const ColorspaceType colorspace)
{
#define RGBTransformImageTag "RGBTransform/Image"
CacheView
*image_view;
ExceptionInfo
*exception;
MagickBooleanType
status;
MagickOffsetType
progress;
PrimaryInfo
primary_info;
register ssize_t
i;
ssize_t
y;
TransformPacket
*x_map,
*y_map,
*z_map;
assert(image != (Image *) NULL);
assert(image->signature == MagickSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(colorspace != RGBColorspace);
assert(colorspace != TransparentColorspace);
assert(colorspace != UndefinedColorspace);
if (SetImageColorspace(image,colorspace) == MagickFalse)
return(MagickFalse);
status=MagickTrue;
progress=0;
exception=(&image->exception);
switch (colorspace)
{
case CMYColorspace:
{
/*
Convert RGB to CMY colorspace.
*/
if (image->storage_class == PseudoClass)
{
if (SyncImage(image) == MagickFalse)
return(MagickFalse);
if (SetImageStorageClass(image,DirectClass) == MagickFalse)
return(MagickFalse);
}
image_view=AcquireCacheView(image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
MagickBooleanType
sync;
register ssize_t
x;
register PixelPacket
*restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
SetPixelRed(q,ClampToQuantum((MagickRealType)
(QuantumRange-GetPixelRed(q))));
SetPixelGreen(q,ClampToQuantum((MagickRealType)
(QuantumRange-GetPixelGreen(q))));
SetPixelBlue(q,ClampToQuantum((MagickRealType)
(QuantumRange-GetPixelBlue(q))));
q++;
}
sync=SyncCacheViewAuthenticPixels(image_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
image_view=DestroyCacheView(image_view);
image->type=image->matte == MagickFalse ? ColorSeparationType :
ColorSeparationMatteType;
return(status);
}
case CMYKColorspace:
{
MagickPixelPacket
zero;
/*
Convert RGB to CMYK colorspace.
*/
if (image->storage_class == PseudoClass)
{
if (SyncImage(image) == MagickFalse)
return(MagickFalse);
if (SetImageStorageClass(image,DirectClass) == MagickFalse)
return(MagickFalse);
}
GetMagickPixelPacket(image,&zero);
image_view=AcquireCacheView(image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
MagickBooleanType
sync;
MagickPixelPacket
pixel;
register IndexPacket
*restrict indexes;
register ssize_t
x;
register PixelPacket
*restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewAuthenticIndexQueue(image_view);
pixel=zero;
for (x=0; x < (ssize_t) image->columns; x++)
{
SetMagickPixelPacket(image,q,indexes+x,&pixel);
ConvertRGBToCMYK(&pixel);
SetPixelPacket(image,&pixel,q,indexes+x);
q++;
}
sync=SyncCacheViewAuthenticPixels(image_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
image_view=DestroyCacheView(image_view);
image->type=image->matte == MagickFalse ? ColorSeparationType :
ColorSeparationMatteType;
return(status);
}
case HSBColorspace:
{
/*
Transform image from RGB to HSB.
*/
if (image->storage_class == PseudoClass)
{
if (SyncImage(image) == MagickFalse)
return(MagickFalse);
if (SetImageStorageClass(image,DirectClass) == MagickFalse)
return(MagickFalse);
}
image_view=AcquireCacheView(image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
double
brightness,
hue,
saturation;
MagickBooleanType
sync;
register ssize_t
x;
register PixelPacket
*restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
hue=0.0;
saturation=0.0;
brightness=0.0;
for (x=0; x < (ssize_t) image->columns; x++)
{
ConvertRGBToHSB(GetPixelRed(q),GetPixelGreen(q),
GetPixelBlue(q),&hue,&saturation,&brightness);
SetPixelRed(q,ClampToQuantum((MagickRealType)
QuantumRange*hue));
SetPixelGreen(q,ClampToQuantum((MagickRealType)
QuantumRange*saturation));
SetPixelBlue(q,ClampToQuantum((MagickRealType)
QuantumRange*brightness));
q++;
}
sync=SyncCacheViewAuthenticPixels(image_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
image_view=DestroyCacheView(image_view);
return(status);
}
case HSLColorspace:
{
/*
Transform image from RGB to HSL.
*/
if (image->storage_class == PseudoClass)
{
if (SyncImage(image) == MagickFalse)
return(MagickFalse);
if (SetImageStorageClass(image,DirectClass) == MagickFalse)
return(MagickFalse);
}
image_view=AcquireCacheView(image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
double
hue,
lightness,
saturation;
MagickBooleanType
sync;
register ssize_t
x;
register PixelPacket
*restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
hue=0.0;
saturation=0.0;
lightness=0.0;
for (x=0; x < (ssize_t) image->columns; x++)
{
ConvertRGBToHSL(GetPixelRed(q),GetPixelGreen(q),
GetPixelBlue(q),&hue,&saturation,&lightness);
SetPixelRed(q,ClampToQuantum((MagickRealType)
QuantumRange*hue));
SetPixelGreen(q,ClampToQuantum((MagickRealType)
QuantumRange*saturation));
SetPixelBlue(q,ClampToQuantum((MagickRealType)
QuantumRange*lightness));
q++;
}
sync=SyncCacheViewAuthenticPixels(image_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
image_view=DestroyCacheView(image_view);
return(status);
}
case HWBColorspace:
{
/*
Transform image from RGB to HWB.
*/
if (image->storage_class == PseudoClass)
{
if (SyncImage(image) == MagickFalse)
return(MagickFalse);
if (SetImageStorageClass(image,DirectClass) == MagickFalse)
return(MagickFalse);
}
image_view=AcquireCacheView(image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
double
blackness,
hue,
whiteness;
MagickBooleanType
sync;
register ssize_t
x;
register PixelPacket
*restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
hue=0.0;
whiteness=0.0;
blackness=0.0;
for (x=0; x < (ssize_t) image->columns; x++)
{
ConvertRGBToHWB(GetPixelRed(q),GetPixelGreen(q),
GetPixelBlue(q),&hue,&whiteness,&blackness);
SetPixelRed(q,ClampToQuantum((MagickRealType)
QuantumRange*hue));
SetPixelGreen(q,ClampToQuantum((MagickRealType)
QuantumRange*whiteness));
SetPixelBlue(q,ClampToQuantum((MagickRealType)
QuantumRange*blackness));
q++;
}
sync=SyncCacheViewAuthenticPixels(image_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
image_view=DestroyCacheView(image_view);
return(status);
}
case LabColorspace:
{
/*
Transform image from RGB to Lab.
*/
if (image->storage_class == PseudoClass)
{
if (SyncImage(image) == MagickFalse)
return(MagickFalse);
if (SetImageStorageClass(image,DirectClass) == MagickFalse)
return(MagickFalse);
}
image_view=AcquireCacheView(image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
double
a,
b,
L,
X,
Y,
Z;
MagickBooleanType
sync;
register ssize_t
x;
register PixelPacket
*restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
L=0.0;
a=0.0;
b=0.0;
X=0.0;
Y=0.0;
Z=0.0;
for (x=0; x < (ssize_t) image->columns; x++)
{
ConvertRGBToXYZ(GetPixelRed(q),GetPixelGreen(q),
GetPixelBlue(q),&X,&Y,&Z);
ConvertXYZToLab(X,Y,Z,&L,&a,&b);
SetPixelRed(q,ClampToQuantum((MagickRealType)
QuantumRange*L));
SetPixelGreen(q,ClampToQuantum((MagickRealType)
QuantumRange*a));
SetPixelBlue(q,ClampToQuantum((MagickRealType)
QuantumRange*b));
q++;
}
sync=SyncCacheViewAuthenticPixels(image_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
image_view=DestroyCacheView(image_view);
return(status);
}
case LogColorspace:
{
#define DisplayGamma (1.0/1.7)
#define FilmGamma 0.6
#define ReferenceBlack 95.0
#define ReferenceWhite 685.0
const char
*value;
double
black,
density,
film_gamma,
gamma,
reference_black,
reference_white;
Quantum
*logmap;
/*
Transform RGB to Log colorspace.
*/
density=DisplayGamma;
gamma=DisplayGamma;
value=GetImageProperty(image,"gamma");
if (value != (const char *) NULL)
gamma=1.0/StringToDouble(value,(char **) NULL) != 0.0 ? StringToDouble(
value,(char **) NULL) : 1.0;
film_gamma=FilmGamma;
value=GetImageProperty(image,"film-gamma");
if (value != (const char *) NULL)
film_gamma=StringToDouble(value,(char **) NULL);
reference_black=ReferenceBlack;
value=GetImageProperty(image,"reference-black");
if (value != (const char *) NULL)
reference_black=StringToDouble(value,(char **) NULL);
reference_white=ReferenceWhite;
value=GetImageProperty(image,"reference-white");
if (value != (const char *) NULL)
reference_white=StringToDouble(value,(char **) NULL);
logmap=(Quantum *) AcquireQuantumMemory((size_t) MaxMap+1UL,
sizeof(*logmap));
if (logmap == (Quantum *) NULL)
ThrowBinaryException(ResourceLimitError,"MemoryAllocationFailed",
image->filename);
black=pow(10.0,(reference_black-reference_white)*(gamma/density)*
0.002/film_gamma);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
logmap[i]=ScaleMapToQuantum((MagickRealType) (MaxMap*(reference_white+
log10(black+((MagickRealType) i/MaxMap)*(1.0-black))/((gamma/density)*
0.002/film_gamma))/1024.0));
image_view=AcquireCacheView(image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
MagickBooleanType
sync;
register ssize_t
x;
register PixelPacket
*restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
for (x=(ssize_t) image->columns; x != 0; x--)
{
SetPixelRed(q,logmap[ScaleQuantumToMap(
GetPixelRed(q))]);
SetPixelGreen(q,logmap[ScaleQuantumToMap(
GetPixelGreen(q))]);
SetPixelBlue(q,logmap[ScaleQuantumToMap(
GetPixelBlue(q))]);
q++;
}
sync=SyncCacheViewAuthenticPixels(image_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
image_view=DestroyCacheView(image_view);
logmap=(Quantum *) RelinquishMagickMemory(logmap);
return(status);
}
default:
break;
}
/*
Allocate the tables.
*/
x_map=(TransformPacket *) AcquireQuantumMemory((size_t) MaxMap+1UL,
sizeof(*x_map));
y_map=(TransformPacket *) AcquireQuantumMemory((size_t) MaxMap+1UL,
sizeof(*y_map));
z_map=(TransformPacket *) AcquireQuantumMemory((size_t) MaxMap+1UL,
sizeof(*z_map));
if ((x_map == (TransformPacket *) NULL) ||
(y_map == (TransformPacket *) NULL) ||
(z_map == (TransformPacket *) NULL))
ThrowBinaryException(ResourceLimitError,"MemoryAllocationFailed",
image->filename);
(void) ResetMagickMemory(&primary_info,0,sizeof(primary_info));
switch (colorspace)
{
case OHTAColorspace:
{
/*
Initialize OHTA tables:
I1 = 0.33333*R+0.33334*G+0.33333*B
I2 = 0.50000*R+0.00000*G-0.50000*B
I3 =-0.25000*R+0.50000*G-0.25000*B
I and Q, normally -0.5 through 0.5, are normalized to the range 0
through QuantumRange.
*/
primary_info.y=(double) (MaxMap+1.0)/2.0;
primary_info.z=(double) (MaxMap+1.0)/2.0;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
x_map[i].x=0.33333f*(MagickRealType) i;
y_map[i].x=0.33334f*(MagickRealType) i;
z_map[i].x=0.33333f*(MagickRealType) i;
x_map[i].y=0.50000f*(MagickRealType) i;
y_map[i].y=0.00000f*(MagickRealType) i;
z_map[i].y=(-0.50000f)*(MagickRealType) i;
x_map[i].z=(-0.25000f)*(MagickRealType) i;
y_map[i].z=0.50000f*(MagickRealType) i;
z_map[i].z=(-0.25000f)*(MagickRealType) i;
}
break;
}
case Rec601LumaColorspace:
case GRAYColorspace:
{
/*
Initialize Rec601 luma tables:
G = 0.29900*R+0.58700*G+0.11400*B
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
x_map[i].x=0.29900f*(MagickRealType) i;
y_map[i].x=0.58700f*(MagickRealType) i;
z_map[i].x=0.11400f*(MagickRealType) i;
x_map[i].y=0.29900f*(MagickRealType) i;
y_map[i].y=0.58700f*(MagickRealType) i;
z_map[i].y=0.11400f*(MagickRealType) i;
x_map[i].z=0.29900f*(MagickRealType) i;
y_map[i].z=0.58700f*(MagickRealType) i;
z_map[i].z=0.11400f*(MagickRealType) i;
}
image->type=GrayscaleType;
break;
}
case Rec601YCbCrColorspace:
case YCbCrColorspace:
{
/*
Initialize YCbCr tables (ITU-R BT.601):
Y = 0.299000*R+0.587000*G+0.114000*B
Cb= -0.168736*R-0.331264*G+0.500000*B
Cr= 0.500000*R-0.418688*G-0.081312*B
Cb and Cr, normally -0.5 through 0.5, are normalized to the range 0
through QuantumRange.
*/
primary_info.y=(double) (MaxMap+1.0)/2.0;
primary_info.z=(double) (MaxMap+1.0)/2.0;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
x_map[i].x=0.299000f*(MagickRealType) i;
y_map[i].x=0.587000f*(MagickRealType) i;
z_map[i].x=0.114000f*(MagickRealType) i;
x_map[i].y=(-0.168730f)*(MagickRealType) i;
y_map[i].y=(-0.331264f)*(MagickRealType) i;
z_map[i].y=0.500000f*(MagickRealType) i;
x_map[i].z=0.500000f*(MagickRealType) i;
y_map[i].z=(-0.418688f)*(MagickRealType) i;
z_map[i].z=(-0.081312f)*(MagickRealType) i;
}
break;
}
case Rec709LumaColorspace:
{
/*
Initialize Rec709 luma tables:
G = 0.21260*R+0.71520*G+0.07220*B
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
x_map[i].x=0.21260f*(MagickRealType) i;
y_map[i].x=0.71520f*(MagickRealType) i;
z_map[i].x=0.07220f*(MagickRealType) i;
x_map[i].y=0.21260f*(MagickRealType) i;
y_map[i].y=0.71520f*(MagickRealType) i;
z_map[i].y=0.07220f*(MagickRealType) i;
x_map[i].z=0.21260f*(MagickRealType) i;
y_map[i].z=0.71520f*(MagickRealType) i;
z_map[i].z=0.07220f*(MagickRealType) i;
}
break;
}
case Rec709YCbCrColorspace:
{
/*
Initialize YCbCr tables (ITU-R BT.709):
Y = 0.212600*R+0.715200*G+0.072200*B
Cb= -0.114572*R-0.385428*G+0.500000*B
Cr= 0.500000*R-0.454153*G-0.045847*B
Cb and Cr, normally -0.5 through 0.5, are normalized to the range 0
through QuantumRange.
*/
primary_info.y=(double) (MaxMap+1.0)/2.0;
primary_info.z=(double) (MaxMap+1.0)/2.0;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
x_map[i].x=0.212600f*(MagickRealType) i;
y_map[i].x=0.715200f*(MagickRealType) i;
z_map[i].x=0.072200f*(MagickRealType) i;
x_map[i].y=(-0.114572f)*(MagickRealType) i;
y_map[i].y=(-0.385428f)*(MagickRealType) i;
z_map[i].y=0.500000f*(MagickRealType) i;
x_map[i].z=0.500000f*(MagickRealType) i;
y_map[i].z=(-0.454153f)*(MagickRealType) i;
z_map[i].z=(-0.045847f)*(MagickRealType) i;
}
break;
}
case sRGBColorspace:
{
/*
Linear sRGB to nonlinear RGB (http://www.w3.org/Graphics/Color/sRGB):
R = 1.0*R+0.0*G+0.0*B
G = 0.0*R+1.0*G+0.0*B
B = 0.0*R+0.0*G+1.0*B
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
MagickRealType
v;
v=(MagickRealType) i/(MagickRealType) MaxMap;
if (((MagickRealType) i/(MagickRealType) MaxMap) <= 0.0031308)
v*=12.92f;
else
v=(MagickRealType) (1.055*pow((double) i/MaxMap,1.0/2.4)-0.055);
x_map[i].x=1.0f*MaxMap*v;
y_map[i].x=0.0f*MaxMap*v;
z_map[i].x=0.0f*MaxMap*v;
x_map[i].y=0.0f*MaxMap*v;
y_map[i].y=1.0f*MaxMap*v;
z_map[i].y=0.0f*MaxMap*v;
x_map[i].z=0.0f*MaxMap*v;
y_map[i].z=0.0f*MaxMap*v;
z_map[i].z=1.0f*MaxMap*v;
}
break;
}
case XYZColorspace:
{
/*
Initialize CIE XYZ tables (ITU-R 709 RGB):
X = 0.4124564*R+0.3575761*G+0.1804375*B
Y = 0.2126729*R+0.7151522*G+0.0721750*B
Z = 0.0193339*R+0.1191920*G+0.9503041*B
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
x_map[i].x=0.4124564f*(MagickRealType) i;
y_map[i].x=0.3575761f*(MagickRealType) i;
z_map[i].x=0.1804375f*(MagickRealType) i;
x_map[i].y=0.2126729f*(MagickRealType) i;
y_map[i].y=0.7151522f*(MagickRealType) i;
z_map[i].y=0.0721750f*(MagickRealType) i;
x_map[i].z=0.0193339f*(MagickRealType) i;
y_map[i].z=0.1191920f*(MagickRealType) i;
z_map[i].z=0.9503041f*(MagickRealType) i;
}
break;
}
case YCCColorspace:
{
/*
Initialize YCC tables:
Y = 0.29900*R+0.58700*G+0.11400*B
C1= -0.29900*R-0.58700*G+0.88600*B
C2= 0.70100*R-0.58700*G-0.11400*B
YCC is scaled by 1.3584. C1 zero is 156 and C2 is at 137.
*/
primary_info.y=(double) ScaleQuantumToMap(ScaleCharToQuantum(156));
primary_info.z=(double) ScaleQuantumToMap(ScaleCharToQuantum(137));
for (i=0; i <= (ssize_t) (0.018*MaxMap); i++)
{
x_map[i].x=0.003962014134275617f*(MagickRealType) i;
y_map[i].x=0.007778268551236748f*(MagickRealType) i;
z_map[i].x=0.001510600706713781f*(MagickRealType) i;
x_map[i].y=(-0.002426619775463276f)*(MagickRealType) i;
y_map[i].y=(-0.004763965913702149f)*(MagickRealType) i;
z_map[i].y=0.007190585689165425f*(MagickRealType) i;
x_map[i].z=0.006927257754597858f*(MagickRealType) i;
y_map[i].z=(-0.005800713697502058f)*(MagickRealType) i;
z_map[i].z=(-0.0011265440570958f)*(MagickRealType) i;
}
for ( ; i <= (ssize_t) MaxMap; i++)
{
x_map[i].x=0.2201118963486454*(1.099f*(MagickRealType) i-0.099f);
y_map[i].x=0.4321260306242638*(1.099f*(MagickRealType) i-0.099f);
z_map[i].x=0.08392226148409894*(1.099f*(MagickRealType) i-0.099f);
x_map[i].y=(-0.1348122097479598)*(1.099f*(MagickRealType) i-0.099f);
y_map[i].y=(-0.2646647729834528)*(1.099f*(MagickRealType) i-0.099f);
z_map[i].y=0.3994769827314126*(1.099f*(MagickRealType) i-0.099f);
x_map[i].z=0.3848476530332144*(1.099f*(MagickRealType) i-0.099f);
y_map[i].z=(-0.3222618720834477)*(1.099f*(MagickRealType) i-0.099f);
z_map[i].z=(-0.06258578094976668)*(1.099f*(MagickRealType) i-0.099f);
}
break;
}
case YIQColorspace:
{
/*
Initialize YIQ tables:
Y = 0.29900*R+0.58700*G+0.11400*B
I = 0.59600*R-0.27400*G-0.32200*B
Q = 0.21100*R-0.52300*G+0.31200*B
I and Q, normally -0.5 through 0.5, are normalized to the range 0
through QuantumRange.
*/
primary_info.y=(double) (MaxMap+1.0)/2.0;
primary_info.z=(double) (MaxMap+1.0)/2.0;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
x_map[i].x=0.29900f*(MagickRealType) i;
y_map[i].x=0.58700f*(MagickRealType) i;
z_map[i].x=0.11400f*(MagickRealType) i;
x_map[i].y=0.59600f*(MagickRealType) i;
y_map[i].y=(-0.27400f)*(MagickRealType) i;
z_map[i].y=(-0.32200f)*(MagickRealType) i;
x_map[i].z=0.21100f*(MagickRealType) i;
y_map[i].z=(-0.52300f)*(MagickRealType) i;
z_map[i].z=0.31200f*(MagickRealType) i;
}
break;
}
case YPbPrColorspace:
{
/*
Initialize YPbPr tables (ITU-R BT.601):
Y = 0.299000*R+0.587000*G+0.114000*B
Pb= -0.168736*R-0.331264*G+0.500000*B
Pr= 0.500000*R-0.418688*G-0.081312*B
Pb and Pr, normally -0.5 through 0.5, are normalized to the range 0
through QuantumRange.
*/
primary_info.y=(double) (MaxMap+1.0)/2.0;
primary_info.z=(double) (MaxMap+1.0)/2.0;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
x_map[i].x=0.299000f*(MagickRealType) i;
y_map[i].x=0.587000f*(MagickRealType) i;
z_map[i].x=0.114000f*(MagickRealType) i;
x_map[i].y=(-0.168736f)*(MagickRealType) i;
y_map[i].y=(-0.331264f)*(MagickRealType) i;
z_map[i].y=0.500000f*(MagickRealType) i;
x_map[i].z=0.500000f*(MagickRealType) i;
y_map[i].z=(-0.418688f)*(MagickRealType) i;
z_map[i].z=(-0.081312f)*(MagickRealType) i;
}
break;
}
case YUVColorspace:
{
/*
Initialize YUV tables:
Y = 0.29900*R+0.58700*G+0.11400*B
U = -0.14740*R-0.28950*G+0.43690*B
V = 0.61500*R-0.51500*G-0.10000*B
U and V, normally -0.5 through 0.5, are normalized to the range 0
through QuantumRange. Note that U = 0.493*(B-Y), V = 0.877*(R-Y).
*/
primary_info.y=(double) (MaxMap+1.0)/2.0;
primary_info.z=(double) (MaxMap+1.0)/2.0;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
x_map[i].x=0.29900f*(MagickRealType) i;
y_map[i].x=0.58700f*(MagickRealType) i;
z_map[i].x=0.11400f*(MagickRealType) i;
x_map[i].y=(-0.14740f)*(MagickRealType) i;
y_map[i].y=(-0.28950f)*(MagickRealType) i;
z_map[i].y=0.43690f*(MagickRealType) i;
x_map[i].z=0.61500f*(MagickRealType) i;
y_map[i].z=(-0.51500f)*(MagickRealType) i;
z_map[i].z=(-0.10000f)*(MagickRealType) i;
}
break;
}
default:
{
/*
Linear conversion tables.
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
x_map[i].x=(MagickRealType) i;
y_map[i].x=0.0f;
z_map[i].x=0.0f;
x_map[i].y=0.0f;
y_map[i].y=(MagickRealType) i;
z_map[i].y=0.0f;
x_map[i].z=0.0f;
y_map[i].z=0.0f;
z_map[i].z=(MagickRealType) i;
}
break;
}
}
/*
Convert from RGB.
*/
switch (image->storage_class)
{
case DirectClass:
default:
{
/*
Convert DirectClass image.
*/
image_view=AcquireCacheView(image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
MagickBooleanType
sync;
MagickPixelPacket
pixel;
register ssize_t
x;
register PixelPacket
*restrict q;
register size_t
blue,
green,
red;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
red=ScaleQuantumToMap(GetPixelRed(q));
green=ScaleQuantumToMap(GetPixelGreen(q));
blue=ScaleQuantumToMap(GetPixelBlue(q));
pixel.red=(x_map[red].x+y_map[green].x+z_map[blue].x)+
(MagickRealType) primary_info.x;
pixel.green=(x_map[red].y+y_map[green].y+z_map[blue].y)+
(MagickRealType) primary_info.y;
pixel.blue=(x_map[red].z+y_map[green].z+z_map[blue].z)+
(MagickRealType) primary_info.z;
SetPixelRed(q,ScaleMapToQuantum(pixel.red));
SetPixelGreen(q,ScaleMapToQuantum(pixel.green));
SetPixelBlue(q,ScaleMapToQuantum(pixel.blue));
q++;
}
sync=SyncCacheViewAuthenticPixels(image_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_RGBTransformImage)
#endif
proceed=SetImageProgress(image,RGBTransformImageTag,progress++,
image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
image_view=DestroyCacheView(image_view);
break;
}
case PseudoClass:
{
register size_t
blue,
green,
red;
/*
Convert PseudoClass image.
*/
image_view=AcquireCacheView(image);
for (i=0; i < (ssize_t) image->colors; i++)
{
MagickPixelPacket
pixel;
red=ScaleQuantumToMap(image->colormap[i].red);
green=ScaleQuantumToMap(image->colormap[i].green);
blue=ScaleQuantumToMap(image->colormap[i].blue);
pixel.red=x_map[red].x+y_map[green].x+z_map[blue].x+primary_info.x;
pixel.green=x_map[red].y+y_map[green].y+z_map[blue].y+primary_info.y;
pixel.blue=x_map[red].z+y_map[green].z+z_map[blue].z+primary_info.z;
image->colormap[i].red=ScaleMapToQuantum(pixel.red);
image->colormap[i].green=ScaleMapToQuantum(pixel.green);
image->colormap[i].blue=ScaleMapToQuantum(pixel.blue);
}
image_view=DestroyCacheView(image_view);
(void) SyncImage(image);
break;
}
}
/*
Relinquish resources.
*/
z_map=(TransformPacket *) RelinquishMagickMemory(z_map);
y_map=(TransformPacket *) RelinquishMagickMemory(y_map);
x_map=(TransformPacket *) RelinquishMagickMemory(x_map);
if (SetImageColorspace(image,colorspace) == MagickFalse)
return(MagickFalse);
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S e t I m a g e C o l o r s p a c e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SetImageColorspace() sets the colorspace member of the Image structure.
%
% The format of the SetImageColorspace method is:
%
% MagickBooleanType SetImageColorspace(Image *image,
% const ColorspaceType colorspace)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o colorspace: the colorspace.
%
*/
MagickExport MagickBooleanType SetImageColorspace(Image *image,
const ColorspaceType colorspace)
{
image->colorspace=colorspace;
return(SyncImagePixelCache(image,&image->exception));
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% T r a n s f o r m I m a g e C o l o r s p a c e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% TransformImageColorspace() transforms an image colorspace.
%
% The format of the TransformImageColorspace method is:
%
% MagickBooleanType TransformImageColorspace(Image *image,
% const ColorspaceType colorspace)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o colorspace: the colorspace.
%
*/
MagickExport MagickBooleanType TransformImageColorspace(Image *image,
const ColorspaceType colorspace)
{
MagickBooleanType
status;
assert(image != (Image *) NULL);
assert(image->signature == MagickSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if (colorspace == UndefinedColorspace)
return(SetImageColorspace(image,colorspace));
if (image->colorspace == colorspace)
return(MagickTrue); /* same colorspace: no op */
/*
Convert the reference image from an alternate colorspace to RGB.
*/
if ((colorspace == RGBColorspace) || (colorspace == TransparentColorspace))
return(TransformRGBImage(image,colorspace));
status=MagickTrue;
if (IsRGBColorspace(image->colorspace) == MagickFalse)
status=TransformRGBImage(image,image->colorspace);
/*
Convert the reference image from RGB to an alternate colorspace.
*/
if (RGBTransformImage(image,colorspace) == MagickFalse)
status=MagickFalse;
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
+ T r a n s f o r m R G B I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% TransformRGBImage() converts the reference image from an alternate
% colorspace to RGB. The transformation matrices are not the standard ones:
% the weights are rescaled to normalize the range of the transformed values to
% be [0..QuantumRange].
%
% The format of the TransformRGBImage method is:
%
% MagickBooleanType TransformRGBImage(Image *image,
% const ColorspaceType colorspace)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o colorspace: the colorspace to transform the image to.
%
*/
static double LabF2(double alpha)
{
double
beta;
if (alpha > (24.0/116.0))
return(alpha*alpha*alpha);
beta=(108.0/841.0)*(alpha-(16.0/116.0));
if (beta > 0.0)
return(beta);
return(0.0);
}
static inline void ConvertLabToXYZ(const double L,const double a,const double b,
double *X,double *Y,double *Z)
{
double
x,
y,
z;
assert(X != (double *) NULL);
assert(Y != (double *) NULL);
assert(Z != (double *) NULL);
*X=0.0;
*Y=0.0;
*Z=0.0;
if (L <= 0.0)
return;
y=(100.0*L+16.0)/116.0;
x=y+255.0*0.002*(a > 0.5 ? a-1.0 : a);
z=y-255.0*0.005*(b > 0.5 ? b-1.0 : b);
*X=D50X*LabF2(x);
*Y=D50Y*LabF2(y);
*Z=D50Z*LabF2(z);
}
static inline ssize_t RoundToYCC(const MagickRealType value)
{
if (value <= 0.0)
return(0);
if (value >= 1388.0)
return(1388);
return((ssize_t) (value+0.5));
}
static inline void ConvertXYZToRGB(const double x,const double y,const double z,
Quantum *red,Quantum *green,Quantum *blue)
{
double
b,
g,
r;
/*
Convert XYZ to RGB colorspace.
*/
assert(red != (Quantum *) NULL);
assert(green != (Quantum *) NULL);
assert(blue != (Quantum *) NULL);
r=3.2404542*x-1.5371385*y-0.4985314*z;
g=(-0.9692660*x+1.8760108*y+0.0415560*z);
b=0.0556434*x-0.2040259*y+1.0572252*z;
if (r > 0.0031308)
r=1.055*pow(r,1.0/2.4)-0.055;
else
r*=12.92;
if (g > 0.0031308)
g=1.055*pow(g,1.0/2.4)-0.055;
else
g*=12.92;
if (b > 0.0031308)
b=1.055*pow(b,1.0/2.4)-0.055;
else
b*=12.92;
*red=RoundToQuantum((MagickRealType) QuantumRange*r);
*green=RoundToQuantum((MagickRealType) QuantumRange*g);
*blue=RoundToQuantum((MagickRealType) QuantumRange*b);
}
static inline void ConvertCMYKToRGB(MagickPixelPacket *pixel)
{
pixel->red=(MagickRealType) QuantumRange-(QuantumScale*pixel->red*
(QuantumRange-pixel->index)+pixel->index);
pixel->green=(MagickRealType) QuantumRange-(QuantumScale*pixel->green*
(QuantumRange-pixel->index)+pixel->index);
pixel->blue=(MagickRealType) QuantumRange-(QuantumScale*pixel->blue*
(QuantumRange-pixel->index)+pixel->index);
}
MagickExport MagickBooleanType TransformRGBImage(Image *image,
const ColorspaceType colorspace)
{
#define D50X (0.9642)
#define D50Y (1.0)
#define D50Z (0.8249)
#define TransformRGBImageTag "Transform/Image"
#if !defined(MAGICKCORE_HDRI_SUPPORT)
static const float
YCCMap[1389] =
{
0.000000f, 0.000720f, 0.001441f, 0.002161f, 0.002882f, 0.003602f,
0.004323f, 0.005043f, 0.005764f, 0.006484f, 0.007205f, 0.007925f,
0.008646f, 0.009366f, 0.010086f, 0.010807f, 0.011527f, 0.012248f,
0.012968f, 0.013689f, 0.014409f, 0.015130f, 0.015850f, 0.016571f,
0.017291f, 0.018012f, 0.018732f, 0.019452f, 0.020173f, 0.020893f,
0.021614f, 0.022334f, 0.023055f, 0.023775f, 0.024496f, 0.025216f,
0.025937f, 0.026657f, 0.027378f, 0.028098f, 0.028818f, 0.029539f,
0.030259f, 0.030980f, 0.031700f, 0.032421f, 0.033141f, 0.033862f,
0.034582f, 0.035303f, 0.036023f, 0.036744f, 0.037464f, 0.038184f,
0.038905f, 0.039625f, 0.040346f, 0.041066f, 0.041787f, 0.042507f,
0.043228f, 0.043948f, 0.044669f, 0.045389f, 0.046110f, 0.046830f,
0.047550f, 0.048271f, 0.048991f, 0.049712f, 0.050432f, 0.051153f,
0.051873f, 0.052594f, 0.053314f, 0.054035f, 0.054755f, 0.055476f,
0.056196f, 0.056916f, 0.057637f, 0.058357f, 0.059078f, 0.059798f,
0.060519f, 0.061239f, 0.061960f, 0.062680f, 0.063401f, 0.064121f,
0.064842f, 0.065562f, 0.066282f, 0.067003f, 0.067723f, 0.068444f,
0.069164f, 0.069885f, 0.070605f, 0.071326f, 0.072046f, 0.072767f,
0.073487f, 0.074207f, 0.074928f, 0.075648f, 0.076369f, 0.077089f,
0.077810f, 0.078530f, 0.079251f, 0.079971f, 0.080692f, 0.081412f,
0.082133f, 0.082853f, 0.083573f, 0.084294f, 0.085014f, 0.085735f,
0.086455f, 0.087176f, 0.087896f, 0.088617f, 0.089337f, 0.090058f,
0.090778f, 0.091499f, 0.092219f, 0.092939f, 0.093660f, 0.094380f,
0.095101f, 0.095821f, 0.096542f, 0.097262f, 0.097983f, 0.098703f,
0.099424f, 0.100144f, 0.100865f, 0.101585f, 0.102305f, 0.103026f,
0.103746f, 0.104467f, 0.105187f, 0.105908f, 0.106628f, 0.107349f,
0.108069f, 0.108790f, 0.109510f, 0.110231f, 0.110951f, 0.111671f,
0.112392f, 0.113112f, 0.113833f, 0.114553f, 0.115274f, 0.115994f,
0.116715f, 0.117435f, 0.118156f, 0.118876f, 0.119597f, 0.120317f,
0.121037f, 0.121758f, 0.122478f, 0.123199f, 0.123919f, 0.124640f,
0.125360f, 0.126081f, 0.126801f, 0.127522f, 0.128242f, 0.128963f,
0.129683f, 0.130403f, 0.131124f, 0.131844f, 0.132565f, 0.133285f,
0.134006f, 0.134726f, 0.135447f, 0.136167f, 0.136888f, 0.137608f,
0.138329f, 0.139049f, 0.139769f, 0.140490f, 0.141210f, 0.141931f,
0.142651f, 0.143372f, 0.144092f, 0.144813f, 0.145533f, 0.146254f,
0.146974f, 0.147695f, 0.148415f, 0.149135f, 0.149856f, 0.150576f,
0.151297f, 0.152017f, 0.152738f, 0.153458f, 0.154179f, 0.154899f,
0.155620f, 0.156340f, 0.157061f, 0.157781f, 0.158501f, 0.159222f,
0.159942f, 0.160663f, 0.161383f, 0.162104f, 0.162824f, 0.163545f,
0.164265f, 0.164986f, 0.165706f, 0.166427f, 0.167147f, 0.167867f,
0.168588f, 0.169308f, 0.170029f, 0.170749f, 0.171470f, 0.172190f,
0.172911f, 0.173631f, 0.174352f, 0.175072f, 0.175793f, 0.176513f,
0.177233f, 0.177954f, 0.178674f, 0.179395f, 0.180115f, 0.180836f,
0.181556f, 0.182277f, 0.182997f, 0.183718f, 0.184438f, 0.185159f,
0.185879f, 0.186599f, 0.187320f, 0.188040f, 0.188761f, 0.189481f,
0.190202f, 0.190922f, 0.191643f, 0.192363f, 0.193084f, 0.193804f,
0.194524f, 0.195245f, 0.195965f, 0.196686f, 0.197406f, 0.198127f,
0.198847f, 0.199568f, 0.200288f, 0.201009f, 0.201729f, 0.202450f,
0.203170f, 0.203890f, 0.204611f, 0.205331f, 0.206052f, 0.206772f,
0.207493f, 0.208213f, 0.208934f, 0.209654f, 0.210375f, 0.211095f,
0.211816f, 0.212536f, 0.213256f, 0.213977f, 0.214697f, 0.215418f,
0.216138f, 0.216859f, 0.217579f, 0.218300f, 0.219020f, 0.219741f,
0.220461f, 0.221182f, 0.221902f, 0.222622f, 0.223343f, 0.224063f,
0.224784f, 0.225504f, 0.226225f, 0.226945f, 0.227666f, 0.228386f,
0.229107f, 0.229827f, 0.230548f, 0.231268f, 0.231988f, 0.232709f,
0.233429f, 0.234150f, 0.234870f, 0.235591f, 0.236311f, 0.237032f,
0.237752f, 0.238473f, 0.239193f, 0.239914f, 0.240634f, 0.241354f,
0.242075f, 0.242795f, 0.243516f, 0.244236f, 0.244957f, 0.245677f,
0.246398f, 0.247118f, 0.247839f, 0.248559f, 0.249280f, 0.250000f,
0.250720f, 0.251441f, 0.252161f, 0.252882f, 0.253602f, 0.254323f,
0.255043f, 0.255764f, 0.256484f, 0.257205f, 0.257925f, 0.258646f,
0.259366f, 0.260086f, 0.260807f, 0.261527f, 0.262248f, 0.262968f,
0.263689f, 0.264409f, 0.265130f, 0.265850f, 0.266571f, 0.267291f,
0.268012f, 0.268732f, 0.269452f, 0.270173f, 0.270893f, 0.271614f,
0.272334f, 0.273055f, 0.273775f, 0.274496f, 0.275216f, 0.275937f,
0.276657f, 0.277378f, 0.278098f, 0.278818f, 0.279539f, 0.280259f,
0.280980f, 0.281700f, 0.282421f, 0.283141f, 0.283862f, 0.284582f,
0.285303f, 0.286023f, 0.286744f, 0.287464f, 0.288184f, 0.288905f,
0.289625f, 0.290346f, 0.291066f, 0.291787f, 0.292507f, 0.293228f,
0.293948f, 0.294669f, 0.295389f, 0.296109f, 0.296830f, 0.297550f,
0.298271f, 0.298991f, 0.299712f, 0.300432f, 0.301153f, 0.301873f,
0.302594f, 0.303314f, 0.304035f, 0.304755f, 0.305476f, 0.306196f,
0.306916f, 0.307637f, 0.308357f, 0.309078f, 0.309798f, 0.310519f,
0.311239f, 0.311960f, 0.312680f, 0.313401f, 0.314121f, 0.314842f,
0.315562f, 0.316282f, 0.317003f, 0.317723f, 0.318444f, 0.319164f,
0.319885f, 0.320605f, 0.321326f, 0.322046f, 0.322767f, 0.323487f,
0.324207f, 0.324928f, 0.325648f, 0.326369f, 0.327089f, 0.327810f,
0.328530f, 0.329251f, 0.329971f, 0.330692f, 0.331412f, 0.332133f,
0.332853f, 0.333573f, 0.334294f, 0.335014f, 0.335735f, 0.336455f,
0.337176f, 0.337896f, 0.338617f, 0.339337f, 0.340058f, 0.340778f,
0.341499f, 0.342219f, 0.342939f, 0.343660f, 0.344380f, 0.345101f,
0.345821f, 0.346542f, 0.347262f, 0.347983f, 0.348703f, 0.349424f,
0.350144f, 0.350865f, 0.351585f, 0.352305f, 0.353026f, 0.353746f,
0.354467f, 0.355187f, 0.355908f, 0.356628f, 0.357349f, 0.358069f,
0.358790f, 0.359510f, 0.360231f, 0.360951f, 0.361671f, 0.362392f,
0.363112f, 0.363833f, 0.364553f, 0.365274f, 0.365994f, 0.366715f,
0.367435f, 0.368156f, 0.368876f, 0.369597f, 0.370317f, 0.371037f,
0.371758f, 0.372478f, 0.373199f, 0.373919f, 0.374640f, 0.375360f,
0.376081f, 0.376801f, 0.377522f, 0.378242f, 0.378963f, 0.379683f,
0.380403f, 0.381124f, 0.381844f, 0.382565f, 0.383285f, 0.384006f,
0.384726f, 0.385447f, 0.386167f, 0.386888f, 0.387608f, 0.388329f,
0.389049f, 0.389769f, 0.390490f, 0.391210f, 0.391931f, 0.392651f,
0.393372f, 0.394092f, 0.394813f, 0.395533f, 0.396254f, 0.396974f,
0.397695f, 0.398415f, 0.399135f, 0.399856f, 0.400576f, 0.401297f,
0.402017f, 0.402738f, 0.403458f, 0.404179f, 0.404899f, 0.405620f,
0.406340f, 0.407061f, 0.407781f, 0.408501f, 0.409222f, 0.409942f,
0.410663f, 0.411383f, 0.412104f, 0.412824f, 0.413545f, 0.414265f,
0.414986f, 0.415706f, 0.416427f, 0.417147f, 0.417867f, 0.418588f,
0.419308f, 0.420029f, 0.420749f, 0.421470f, 0.422190f, 0.422911f,
0.423631f, 0.424352f, 0.425072f, 0.425793f, 0.426513f, 0.427233f,
0.427954f, 0.428674f, 0.429395f, 0.430115f, 0.430836f, 0.431556f,
0.432277f, 0.432997f, 0.433718f, 0.434438f, 0.435158f, 0.435879f,
0.436599f, 0.437320f, 0.438040f, 0.438761f, 0.439481f, 0.440202f,
0.440922f, 0.441643f, 0.442363f, 0.443084f, 0.443804f, 0.444524f,
0.445245f, 0.445965f, 0.446686f, 0.447406f, 0.448127f, 0.448847f,
0.449568f, 0.450288f, 0.451009f, 0.451729f, 0.452450f, 0.453170f,
0.453891f, 0.454611f, 0.455331f, 0.456052f, 0.456772f, 0.457493f,
0.458213f, 0.458934f, 0.459654f, 0.460375f, 0.461095f, 0.461816f,
0.462536f, 0.463256f, 0.463977f, 0.464697f, 0.465418f, 0.466138f,
0.466859f, 0.467579f, 0.468300f, 0.469020f, 0.469741f, 0.470461f,
0.471182f, 0.471902f, 0.472622f, 0.473343f, 0.474063f, 0.474784f,
0.475504f, 0.476225f, 0.476945f, 0.477666f, 0.478386f, 0.479107f,
0.479827f, 0.480548f, 0.481268f, 0.481988f, 0.482709f, 0.483429f,
0.484150f, 0.484870f, 0.485591f, 0.486311f, 0.487032f, 0.487752f,
0.488473f, 0.489193f, 0.489914f, 0.490634f, 0.491354f, 0.492075f,
0.492795f, 0.493516f, 0.494236f, 0.494957f, 0.495677f, 0.496398f,
0.497118f, 0.497839f, 0.498559f, 0.499280f, 0.500000f, 0.500720f,
0.501441f, 0.502161f, 0.502882f, 0.503602f, 0.504323f, 0.505043f,
0.505764f, 0.506484f, 0.507205f, 0.507925f, 0.508646f, 0.509366f,
0.510086f, 0.510807f, 0.511527f, 0.512248f, 0.512968f, 0.513689f,
0.514409f, 0.515130f, 0.515850f, 0.516571f, 0.517291f, 0.518012f,
0.518732f, 0.519452f, 0.520173f, 0.520893f, 0.521614f, 0.522334f,
0.523055f, 0.523775f, 0.524496f, 0.525216f, 0.525937f, 0.526657f,
0.527378f, 0.528098f, 0.528818f, 0.529539f, 0.530259f, 0.530980f,
0.531700f, 0.532421f, 0.533141f, 0.533862f, 0.534582f, 0.535303f,
0.536023f, 0.536744f, 0.537464f, 0.538184f, 0.538905f, 0.539625f,
0.540346f, 0.541066f, 0.541787f, 0.542507f, 0.543228f, 0.543948f,
0.544669f, 0.545389f, 0.546109f, 0.546830f, 0.547550f, 0.548271f,
0.548991f, 0.549712f, 0.550432f, 0.551153f, 0.551873f, 0.552594f,
0.553314f, 0.554035f, 0.554755f, 0.555476f, 0.556196f, 0.556916f,
0.557637f, 0.558357f, 0.559078f, 0.559798f, 0.560519f, 0.561239f,
0.561960f, 0.562680f, 0.563401f, 0.564121f, 0.564842f, 0.565562f,
0.566282f, 0.567003f, 0.567723f, 0.568444f, 0.569164f, 0.569885f,
0.570605f, 0.571326f, 0.572046f, 0.572767f, 0.573487f, 0.574207f,
0.574928f, 0.575648f, 0.576369f, 0.577089f, 0.577810f, 0.578530f,
0.579251f, 0.579971f, 0.580692f, 0.581412f, 0.582133f, 0.582853f,
0.583573f, 0.584294f, 0.585014f, 0.585735f, 0.586455f, 0.587176f,
0.587896f, 0.588617f, 0.589337f, 0.590058f, 0.590778f, 0.591499f,
0.592219f, 0.592939f, 0.593660f, 0.594380f, 0.595101f, 0.595821f,
0.596542f, 0.597262f, 0.597983f, 0.598703f, 0.599424f, 0.600144f,
0.600865f, 0.601585f, 0.602305f, 0.603026f, 0.603746f, 0.604467f,
0.605187f, 0.605908f, 0.606628f, 0.607349f, 0.608069f, 0.608790f,
0.609510f, 0.610231f, 0.610951f, 0.611671f, 0.612392f, 0.613112f,
0.613833f, 0.614553f, 0.615274f, 0.615994f, 0.616715f, 0.617435f,
0.618156f, 0.618876f, 0.619597f, 0.620317f, 0.621037f, 0.621758f,
0.622478f, 0.623199f, 0.623919f, 0.624640f, 0.625360f, 0.626081f,
0.626801f, 0.627522f, 0.628242f, 0.628963f, 0.629683f, 0.630403f,
0.631124f, 0.631844f, 0.632565f, 0.633285f, 0.634006f, 0.634726f,
0.635447f, 0.636167f, 0.636888f, 0.637608f, 0.638329f, 0.639049f,
0.639769f, 0.640490f, 0.641210f, 0.641931f, 0.642651f, 0.643372f,
0.644092f, 0.644813f, 0.645533f, 0.646254f, 0.646974f, 0.647695f,
0.648415f, 0.649135f, 0.649856f, 0.650576f, 0.651297f, 0.652017f,
0.652738f, 0.653458f, 0.654179f, 0.654899f, 0.655620f, 0.656340f,
0.657061f, 0.657781f, 0.658501f, 0.659222f, 0.659942f, 0.660663f,
0.661383f, 0.662104f, 0.662824f, 0.663545f, 0.664265f, 0.664986f,
0.665706f, 0.666427f, 0.667147f, 0.667867f, 0.668588f, 0.669308f,
0.670029f, 0.670749f, 0.671470f, 0.672190f, 0.672911f, 0.673631f,
0.674352f, 0.675072f, 0.675793f, 0.676513f, 0.677233f, 0.677954f,
0.678674f, 0.679395f, 0.680115f, 0.680836f, 0.681556f, 0.682277f,
0.682997f, 0.683718f, 0.684438f, 0.685158f, 0.685879f, 0.686599f,
0.687320f, 0.688040f, 0.688761f, 0.689481f, 0.690202f, 0.690922f,
0.691643f, 0.692363f, 0.693084f, 0.693804f, 0.694524f, 0.695245f,
0.695965f, 0.696686f, 0.697406f, 0.698127f, 0.698847f, 0.699568f,
0.700288f, 0.701009f, 0.701729f, 0.702450f, 0.703170f, 0.703891f,
0.704611f, 0.705331f, 0.706052f, 0.706772f, 0.707493f, 0.708213f,
0.708934f, 0.709654f, 0.710375f, 0.711095f, 0.711816f, 0.712536f,
0.713256f, 0.713977f, 0.714697f, 0.715418f, 0.716138f, 0.716859f,
0.717579f, 0.718300f, 0.719020f, 0.719741f, 0.720461f, 0.721182f,
0.721902f, 0.722622f, 0.723343f, 0.724063f, 0.724784f, 0.725504f,
0.726225f, 0.726945f, 0.727666f, 0.728386f, 0.729107f, 0.729827f,
0.730548f, 0.731268f, 0.731988f, 0.732709f, 0.733429f, 0.734150f,
0.734870f, 0.735591f, 0.736311f, 0.737032f, 0.737752f, 0.738473f,
0.739193f, 0.739914f, 0.740634f, 0.741354f, 0.742075f, 0.742795f,
0.743516f, 0.744236f, 0.744957f, 0.745677f, 0.746398f, 0.747118f,
0.747839f, 0.748559f, 0.749280f, 0.750000f, 0.750720f, 0.751441f,
0.752161f, 0.752882f, 0.753602f, 0.754323f, 0.755043f, 0.755764f,
0.756484f, 0.757205f, 0.757925f, 0.758646f, 0.759366f, 0.760086f,
0.760807f, 0.761527f, 0.762248f, 0.762968f, 0.763689f, 0.764409f,
0.765130f, 0.765850f, 0.766571f, 0.767291f, 0.768012f, 0.768732f,
0.769452f, 0.770173f, 0.770893f, 0.771614f, 0.772334f, 0.773055f,
0.773775f, 0.774496f, 0.775216f, 0.775937f, 0.776657f, 0.777378f,
0.778098f, 0.778818f, 0.779539f, 0.780259f, 0.780980f, 0.781700f,
0.782421f, 0.783141f, 0.783862f, 0.784582f, 0.785303f, 0.786023f,
0.786744f, 0.787464f, 0.788184f, 0.788905f, 0.789625f, 0.790346f,
0.791066f, 0.791787f, 0.792507f, 0.793228f, 0.793948f, 0.794669f,
0.795389f, 0.796109f, 0.796830f, 0.797550f, 0.798271f, 0.798991f,
0.799712f, 0.800432f, 0.801153f, 0.801873f, 0.802594f, 0.803314f,
0.804035f, 0.804755f, 0.805476f, 0.806196f, 0.806916f, 0.807637f,
0.808357f, 0.809078f, 0.809798f, 0.810519f, 0.811239f, 0.811960f,
0.812680f, 0.813401f, 0.814121f, 0.814842f, 0.815562f, 0.816282f,
0.817003f, 0.817723f, 0.818444f, 0.819164f, 0.819885f, 0.820605f,
0.821326f, 0.822046f, 0.822767f, 0.823487f, 0.824207f, 0.824928f,
0.825648f, 0.826369f, 0.827089f, 0.827810f, 0.828530f, 0.829251f,
0.829971f, 0.830692f, 0.831412f, 0.832133f, 0.832853f, 0.833573f,
0.834294f, 0.835014f, 0.835735f, 0.836455f, 0.837176f, 0.837896f,
0.838617f, 0.839337f, 0.840058f, 0.840778f, 0.841499f, 0.842219f,
0.842939f, 0.843660f, 0.844380f, 0.845101f, 0.845821f, 0.846542f,
0.847262f, 0.847983f, 0.848703f, 0.849424f, 0.850144f, 0.850865f,
0.851585f, 0.852305f, 0.853026f, 0.853746f, 0.854467f, 0.855187f,
0.855908f, 0.856628f, 0.857349f, 0.858069f, 0.858790f, 0.859510f,
0.860231f, 0.860951f, 0.861671f, 0.862392f, 0.863112f, 0.863833f,
0.864553f, 0.865274f, 0.865994f, 0.866715f, 0.867435f, 0.868156f,
0.868876f, 0.869597f, 0.870317f, 0.871037f, 0.871758f, 0.872478f,
0.873199f, 0.873919f, 0.874640f, 0.875360f, 0.876081f, 0.876801f,
0.877522f, 0.878242f, 0.878963f, 0.879683f, 0.880403f, 0.881124f,
0.881844f, 0.882565f, 0.883285f, 0.884006f, 0.884726f, 0.885447f,
0.886167f, 0.886888f, 0.887608f, 0.888329f, 0.889049f, 0.889769f,
0.890490f, 0.891210f, 0.891931f, 0.892651f, 0.893372f, 0.894092f,
0.894813f, 0.895533f, 0.896254f, 0.896974f, 0.897695f, 0.898415f,
0.899135f, 0.899856f, 0.900576f, 0.901297f, 0.902017f, 0.902738f,
0.903458f, 0.904179f, 0.904899f, 0.905620f, 0.906340f, 0.907061f,
0.907781f, 0.908501f, 0.909222f, 0.909942f, 0.910663f, 0.911383f,
0.912104f, 0.912824f, 0.913545f, 0.914265f, 0.914986f, 0.915706f,
0.916427f, 0.917147f, 0.917867f, 0.918588f, 0.919308f, 0.920029f,
0.920749f, 0.921470f, 0.922190f, 0.922911f, 0.923631f, 0.924352f,
0.925072f, 0.925793f, 0.926513f, 0.927233f, 0.927954f, 0.928674f,
0.929395f, 0.930115f, 0.930836f, 0.931556f, 0.932277f, 0.932997f,
0.933718f, 0.934438f, 0.935158f, 0.935879f, 0.936599f, 0.937320f,
0.938040f, 0.938761f, 0.939481f, 0.940202f, 0.940922f, 0.941643f,
0.942363f, 0.943084f, 0.943804f, 0.944524f, 0.945245f, 0.945965f,
0.946686f, 0.947406f, 0.948127f, 0.948847f, 0.949568f, 0.950288f,
0.951009f, 0.951729f, 0.952450f, 0.953170f, 0.953891f, 0.954611f,
0.955331f, 0.956052f, 0.956772f, 0.957493f, 0.958213f, 0.958934f,
0.959654f, 0.960375f, 0.961095f, 0.961816f, 0.962536f, 0.963256f,
0.963977f, 0.964697f, 0.965418f, 0.966138f, 0.966859f, 0.967579f,
0.968300f, 0.969020f, 0.969741f, 0.970461f, 0.971182f, 0.971902f,
0.972622f, 0.973343f, 0.974063f, 0.974784f, 0.975504f, 0.976225f,
0.976945f, 0.977666f, 0.978386f, 0.979107f, 0.979827f, 0.980548f,
0.981268f, 0.981988f, 0.982709f, 0.983429f, 0.984150f, 0.984870f,
0.985591f, 0.986311f, 0.987032f, 0.987752f, 0.988473f, 0.989193f,
0.989914f, 0.990634f, 0.991354f, 0.992075f, 0.992795f, 0.993516f,
0.994236f, 0.994957f, 0.995677f, 0.996398f, 0.997118f, 0.997839f,
0.998559f, 0.999280f, 1.000000f
};
#endif
CacheView
*image_view;
ExceptionInfo
*exception;
MagickBooleanType
status;
MagickOffsetType
progress;
register ssize_t
i;
ssize_t
y;
TransformPacket
*y_map,
*x_map,
*z_map;
assert(image != (Image *) NULL);
assert(image->signature == MagickSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
status=MagickTrue;
progress=0;
exception=(&image->exception);
switch (image->colorspace)
{
case CMYColorspace:
{
/*
Transform image from CMY to RGB.
*/
if (image->storage_class == PseudoClass)
{
if (SyncImage(image) == MagickFalse)
return(MagickFalse);
if (SetImageStorageClass(image,DirectClass) == MagickFalse)
return(MagickFalse);
}
image_view=AcquireCacheView(image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
MagickBooleanType
sync;
register ssize_t
x;
register PixelPacket
*restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
SetPixelRed(q,ClampToQuantum((MagickRealType)
(QuantumRange-GetPixelRed(q))));
SetPixelGreen(q,ClampToQuantum((MagickRealType)
(QuantumRange-GetPixelGreen(q))));
SetPixelBlue(q,ClampToQuantum((MagickRealType)
(QuantumRange-GetPixelBlue(q))));
q++;
}
sync=SyncCacheViewAuthenticPixels(image_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
image_view=DestroyCacheView(image_view);
if (SetImageColorspace(image,RGBColorspace) == MagickFalse)
return(MagickFalse);
return(status);
}
case CMYKColorspace:
{
MagickPixelPacket
zero;
/*
Transform image from CMYK to RGB.
*/
if (image->storage_class == PseudoClass)
{
if (SyncImage(image) == MagickFalse)
return(MagickFalse);
if (SetImageStorageClass(image,DirectClass) == MagickFalse)
return(MagickFalse);
}
GetMagickPixelPacket(image,&zero);
image_view=AcquireCacheView(image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
MagickBooleanType
sync;
MagickPixelPacket
pixel;
register IndexPacket
*restrict indexes;
register ssize_t
x;
register PixelPacket
*restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewAuthenticIndexQueue(image_view);
pixel=zero;
for (x=0; x < (ssize_t) image->columns; x++)
{
SetMagickPixelPacket(image,q,indexes+x,&pixel);
ConvertCMYKToRGB(&pixel);
SetPixelPacket(image,&pixel,q,indexes+x);
q++;
}
sync=SyncCacheViewAuthenticPixels(image_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
image_view=DestroyCacheView(image_view);
if (SetImageColorspace(image,RGBColorspace) == MagickFalse)
return(MagickFalse);
return(status);
}
case HSBColorspace:
{
/*
Transform image from HSB to RGB.
*/
if (image->storage_class == PseudoClass)
{
if (SyncImage(image) == MagickFalse)
return(MagickFalse);
if (SetImageStorageClass(image,DirectClass) == MagickFalse)
return(MagickFalse);
}
image_view=AcquireCacheView(image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
double
brightness,
hue,
saturation;
MagickBooleanType
sync;
register ssize_t
x;
register PixelPacket
*restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
Quantum
blue,
green,
red;
hue=(double) (QuantumScale*GetPixelRed(q));
saturation=(double) (QuantumScale*GetPixelGreen(q));
brightness=(double) (QuantumScale*GetPixelBlue(q));
ConvertHSBToRGB(hue,saturation,brightness,&red,&green,&blue);
SetPixelRed(q,red);
SetPixelGreen(q,green);
SetPixelBlue(q,blue);
q++;
}
sync=SyncCacheViewAuthenticPixels(image_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
image_view=DestroyCacheView(image_view);
if (SetImageColorspace(image,RGBColorspace) == MagickFalse)
return(MagickFalse);
return(status);
}
case HSLColorspace:
{
/*
Transform image from HSL to RGB.
*/
if (image->storage_class == PseudoClass)
{
if (SyncImage(image) == MagickFalse)
return(MagickFalse);
if (SetImageStorageClass(image,DirectClass) == MagickFalse)
return(MagickFalse);
}
image_view=AcquireCacheView(image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
double
hue,
lightness,
saturation;
MagickBooleanType
sync;
register ssize_t
x;
register PixelPacket
*restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
Quantum
blue,
green,
red;
hue=(double) (QuantumScale*GetPixelRed(q));
saturation=(double) (QuantumScale*GetPixelGreen(q));
lightness=(double) (QuantumScale*GetPixelBlue(q));
ConvertHSLToRGB(hue,saturation,lightness,&red,&green,&blue);
SetPixelRed(q,red);
SetPixelGreen(q,green);
SetPixelBlue(q,blue);
q++;
}
sync=SyncCacheViewAuthenticPixels(image_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
image_view=DestroyCacheView(image_view);
if (SetImageColorspace(image,RGBColorspace) == MagickFalse)
return(MagickFalse);
return(status);
}
case HWBColorspace:
{
/*
Transform image from HWB to RGB.
*/
if (image->storage_class == PseudoClass)
{
if (SyncImage(image) == MagickFalse)
return(MagickFalse);
if (SetImageStorageClass(image,DirectClass) == MagickFalse)
return(MagickFalse);
}
image_view=AcquireCacheView(image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
double
blackness,
hue,
whiteness;
MagickBooleanType
sync;
register ssize_t
x;
register PixelPacket
*restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
Quantum
blue,
green,
red;
hue=(double) (QuantumScale*GetPixelRed(q));
whiteness=(double) (QuantumScale*GetPixelGreen(q));
blackness=(double) (QuantumScale*GetPixelBlue(q));
ConvertHWBToRGB(hue,whiteness,blackness,&red,&green,&blue);
SetPixelRed(q,red);
SetPixelGreen(q,green);
SetPixelBlue(q,blue);
q++;
}
sync=SyncCacheViewAuthenticPixels(image_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
image_view=DestroyCacheView(image_view);
if (SetImageColorspace(image,RGBColorspace) == MagickFalse)
return(MagickFalse);
return(status);
}
case LabColorspace:
{
/*
Transform image from Lab to RGB.
*/
if (image->storage_class == PseudoClass)
{
if (SyncImage(image) == MagickFalse)
return(MagickFalse);
if (SetImageStorageClass(image,DirectClass) == MagickFalse)
return(MagickFalse);
}
image_view=AcquireCacheView(image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
double
a,
b,
L,
X,
Y,
Z;
MagickBooleanType
sync;
register ssize_t
x;
register PixelPacket
*restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
X=0.0;
Y=0.0;
Z=0.0;
for (x=0; x < (ssize_t) image->columns; x++)
{
Quantum
blue,
green,
red;
L=QuantumScale*GetPixelRed(q);
a=QuantumScale*GetPixelGreen(q);
b=QuantumScale*GetPixelBlue(q);
ConvertLabToXYZ(L,a,b,&X,&Y,&Z);
ConvertXYZToRGB(X,Y,Z,&red,&green,&blue);
SetPixelRed(q,red);
SetPixelGreen(q,green);
SetPixelBlue(q,blue);
q++;
}
sync=SyncCacheViewAuthenticPixels(image_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
image_view=DestroyCacheView(image_view);
if (SetImageColorspace(image,RGBColorspace) == MagickFalse)
return(MagickFalse);
return(status);
}
case LogColorspace:
{
const char
*value;
double
black,
density,
film_gamma,
gamma,
reference_black,
reference_white;
Quantum
*logmap;
/*
Transform Log to RGB colorspace.
*/
density=DisplayGamma;
gamma=DisplayGamma;
value=GetImageProperty(image,"gamma");
if (value != (const char *) NULL)
gamma=1.0/StringToDouble(value,(char **) NULL) != 0.0 ? StringToDouble(
value,(char **) NULL) : 1.0;
film_gamma=FilmGamma;
value=GetImageProperty(image,"film-gamma");
if (value != (const char *) NULL)
film_gamma=StringToDouble(value,(char **) NULL);
reference_black=ReferenceBlack;
value=GetImageProperty(image,"reference-black");
if (value != (const char *) NULL)
reference_black=StringToDouble(value,(char **) NULL);
reference_white=ReferenceWhite;
value=GetImageProperty(image,"reference-white");
if (value != (const char *) NULL)
reference_white=StringToDouble(value,(char **) NULL);
logmap=(Quantum *) AcquireQuantumMemory((size_t) MaxMap+1UL,
sizeof(*logmap));
if (logmap == (Quantum *) NULL)
ThrowBinaryException(ResourceLimitError,"MemoryAllocationFailed",
image->filename);
black=pow(10.0,(reference_black-reference_white)*(gamma/density)*
0.002/film_gamma);
for (i=0; i <= (ssize_t) (reference_black*MaxMap/1024.0); i++)
logmap[i]=(Quantum) 0;
for ( ; i < (ssize_t) (reference_white*MaxMap/1024.0); i++)
logmap[i]=ClampToQuantum((MagickRealType) QuantumRange/(1.0-black)*
(pow(10.0,(1024.0*i/MaxMap-reference_white)*
(gamma/density)*0.002/film_gamma)-black));
for ( ; i <= (ssize_t) MaxMap; i++)
logmap[i]=(Quantum) QuantumRange;
if (SetImageStorageClass(image,DirectClass) == MagickFalse)
return(MagickFalse);
image_view=AcquireCacheView(image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
MagickBooleanType
sync;
register ssize_t
x;
register PixelPacket
*restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
for (x=(ssize_t) image->columns; x != 0; x--)
{
SetPixelRed(q,logmap[ScaleQuantumToMap(
GetPixelRed(q))]);
SetPixelGreen(q,logmap[ScaleQuantumToMap(
GetPixelGreen(q))]);
SetPixelBlue(q,logmap[ScaleQuantumToMap(
GetPixelBlue(q))]);
q++;
}
sync=SyncCacheViewAuthenticPixels(image_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
image_view=DestroyCacheView(image_view);
logmap=(Quantum *) RelinquishMagickMemory(logmap);
if (SetImageColorspace(image,RGBColorspace) == MagickFalse)
return(MagickFalse);
return(status);
}
default:
break;
}
/*
Allocate the tables.
*/
x_map=(TransformPacket *) AcquireQuantumMemory((size_t) MaxMap+1UL,
sizeof(*x_map));
y_map=(TransformPacket *) AcquireQuantumMemory((size_t) MaxMap+1UL,
sizeof(*y_map));
z_map=(TransformPacket *) AcquireQuantumMemory((size_t) MaxMap+1UL,
sizeof(*z_map));
if ((x_map == (TransformPacket *) NULL) ||
(y_map == (TransformPacket *) NULL) ||
(z_map == (TransformPacket *) NULL))
{
if (z_map != (TransformPacket *) NULL)
z_map=(TransformPacket *) RelinquishMagickMemory(z_map);
if (y_map != (TransformPacket *) NULL)
y_map=(TransformPacket *) RelinquishMagickMemory(y_map);
if (x_map != (TransformPacket *) NULL)
x_map=(TransformPacket *) RelinquishMagickMemory(x_map);
ThrowBinaryException(ResourceLimitError,"MemoryAllocationFailed",
image->filename);
}
switch (image->colorspace)
{
case OHTAColorspace:
{
/*
Initialize OHTA tables:
R = I1+1.00000*I2-0.66668*I3
G = I1+0.00000*I2+1.33333*I3
B = I1-1.00000*I2-0.66668*I3
I and Q, normally -0.5 through 0.5, must be normalized to the range 0
through QuantumRange.
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
x_map[i].x=(MagickRealType) i;
y_map[i].x=0.500000f*(2.000000*(MagickRealType) i-(MagickRealType)
MaxMap);
z_map[i].x=(-0.333340f)*(2.000000f*(MagickRealType) i-(MagickRealType)
MaxMap);
x_map[i].y=(MagickRealType) i;
y_map[i].y=0.000000f;
z_map[i].y=0.666665f*(2.000000f*(MagickRealType) i-(MagickRealType)
MaxMap);
x_map[i].z=(MagickRealType) i;
y_map[i].z=(-0.500000f)*(2.000000f*(MagickRealType) i-(MagickRealType)
MaxMap);
z_map[i].z=(-0.333340f)*(2.000000f*(MagickRealType) i-(MagickRealType)
MaxMap);
}
break;
}
case Rec601YCbCrColorspace:
case YCbCrColorspace:
{
/*
Initialize YCbCr tables:
R = Y +1.402000*Cr
G = Y-0.344136*Cb-0.714136*Cr
B = Y+1.772000*Cb
Cb and Cr, normally -0.5 through 0.5, must be normalized to the range 0
through QuantumRange.
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
x_map[i].x=(MagickRealType) i;
y_map[i].x=0.000000f;
z_map[i].x=(1.402000f*0.500000f)*(2.000000f*(MagickRealType) i-
(MagickRealType) MaxMap);
x_map[i].y=(MagickRealType) i;
y_map[i].y=(-0.344136f*0.500000f)*(2.000000f*(MagickRealType) i-
(MagickRealType) MaxMap);
z_map[i].y=(-0.714136f*0.500000f)*(2.000000f*(MagickRealType) i-
(MagickRealType) MaxMap);
x_map[i].z=(MagickRealType) i;
y_map[i].z=(1.772000f*0.500000f)*(2.000000f*(MagickRealType) i-
(MagickRealType) MaxMap);
z_map[i].z=0.000000f;
}
break;
}
case Rec709YCbCrColorspace:
{
/*
Initialize YCbCr tables:
R = Y +1.574800*Cr
G = Y-0.187324*Cb-0.468124*Cr
B = Y+1.855600*Cb
Cb and Cr, normally -0.5 through 0.5, must be normalized to the range 0
through QuantumRange.
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
x_map[i].x=(MagickRealType) i;
y_map[i].x=0.000000f;
z_map[i].x=(1.574800f*0.50000f)*(2.00000f*(MagickRealType) i-
(MagickRealType) MaxMap);
x_map[i].y=(MagickRealType) i;
y_map[i].y=(-0.187324f*0.50000f)*(2.00000f*(MagickRealType) i-
(MagickRealType) MaxMap);
z_map[i].y=(-0.468124f*0.50000f)*(2.00000f*(MagickRealType) i-
(MagickRealType) MaxMap);
x_map[i].z=(MagickRealType) i;
y_map[i].z=(1.855600f*0.50000f)*(2.00000f*(MagickRealType) i-
(MagickRealType) MaxMap);
z_map[i].z=0.00000f;
}
break;
}
case sRGBColorspace:
{
/*
Nonlinear sRGB to linear RGB.
R = 1.0*R+0.0*G+0.0*B
G = 0.0*R+1.0*G+0.0*B
B = 0.0*R+0.0*G+1.0*B
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
MagickRealType
v;
v=(MagickRealType) i/(MagickRealType) MaxMap;
if (((MagickRealType) i/(MagickRealType) MaxMap) <= 0.04045f)
v/=12.92f;
else
v=(MagickRealType) pow((((double) i/MaxMap)+0.055)/1.055,2.4);
x_map[i].x=1.0f*MaxMap*v;
y_map[i].x=0.0f*MaxMap*v;
z_map[i].x=0.0f*MaxMap*v;
x_map[i].y=0.0f*MaxMap*v;
y_map[i].y=1.0f*MaxMap*v;
z_map[i].y=0.0f*MaxMap*v;
x_map[i].z=0.0f*MaxMap*v;
y_map[i].z=0.0f*MaxMap*v;
z_map[i].z=1.0f*MaxMap*v;
}
break;
}
case XYZColorspace:
{
/*
Initialize CIE XYZ tables (ITU R-709 RGB):
R = 3.2404542*X-1.5371385*Y-0.4985314*Z
G = -0.9692660*X+1.8760108*Y+0.0415560*Z
B = 0.0556434*X-0.2040259*Y+1.057225*Z
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
x_map[i].x=3.2404542f*(MagickRealType) i;
x_map[i].y=(-0.9692660f)*(MagickRealType) i;
x_map[i].z=0.0556434f*(MagickRealType) i;
y_map[i].x=(-1.5371385f)*(MagickRealType) i;
y_map[i].y=1.8760108f*(MagickRealType) i;
y_map[i].z=(-0.2040259f)*(MagickRealType) i;
z_map[i].x=(-0.4985314f)*(MagickRealType) i;
z_map[i].y=0.0415560f*(MagickRealType) i;
z_map[i].z=1.0572252f*(MagickRealType) i;
}
break;
}
case YCCColorspace:
{
/*
Initialize YCC tables:
R = Y +1.340762*C2
G = Y-0.317038*C1-0.682243*C2
B = Y+1.632639*C1
YCC is scaled by 1.3584. C1 zero is 156 and C2 is at 137.
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
x_map[i].x=1.3584000f*(MagickRealType) i;
y_map[i].x=0.0000000f;
z_map[i].x=1.8215000f*((MagickRealType) i-(MagickRealType)
ScaleQuantumToMap(ScaleCharToQuantum(137)));
x_map[i].y=1.3584000f*(MagickRealType) i;
y_map[i].y=(-0.4302726f)*((MagickRealType) i-(MagickRealType)
ScaleQuantumToMap(ScaleCharToQuantum(156)));
z_map[i].y=(-0.9271435f)*((MagickRealType) i-(MagickRealType)
ScaleQuantumToMap(ScaleCharToQuantum(137)));
x_map[i].z=1.3584000f*(MagickRealType) i;
y_map[i].z=2.2179000f*((MagickRealType) i-(MagickRealType)
ScaleQuantumToMap(ScaleCharToQuantum(156)));
z_map[i].z=0.0000000f;
}
break;
}
case YIQColorspace:
{
/*
Initialize YIQ tables:
R = Y+0.95620*I+0.62140*Q
G = Y-0.27270*I-0.64680*Q
B = Y-1.10370*I+1.70060*Q
I and Q, normally -0.5 through 0.5, must be normalized to the range 0
through QuantumRange.
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
x_map[i].x=(MagickRealType) i;
y_map[i].x=0.47810f*(2.00000f*(MagickRealType) i-(MagickRealType)
MaxMap);
z_map[i].x=0.31070f*(2.00000f*(MagickRealType) i-(MagickRealType)
MaxMap);
x_map[i].y=(MagickRealType) i;
y_map[i].y=(-0.13635f)*(2.00000f*(MagickRealType) i-(MagickRealType)
MaxMap);
z_map[i].y=(-0.32340f)*(2.00000f*(MagickRealType) i-(MagickRealType)
MaxMap);
x_map[i].z=(MagickRealType) i;
y_map[i].z=(-0.55185f)*(2.00000f*(MagickRealType) i-(MagickRealType)
MaxMap);
z_map[i].z=0.85030f*(2.00000f*(MagickRealType) i-(MagickRealType)
MaxMap);
}
break;
}
case YPbPrColorspace:
{
/*
Initialize YPbPr tables:
R = Y +1.402000*C2
G = Y-0.344136*C1+0.714136*C2
B = Y+1.772000*C1
Pb and Pr, normally -0.5 through 0.5, must be normalized to the range 0
through QuantumRange.
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
x_map[i].x=(MagickRealType) i;
y_map[i].x=0.000000f;
z_map[i].x=0.701000f*(2.00000f*(MagickRealType) i-(MagickRealType)
MaxMap);
x_map[i].y=(MagickRealType) i;
y_map[i].y=(-0.172068f)*(2.00000f*(MagickRealType) i-(MagickRealType)
MaxMap);
z_map[i].y=0.357068f*(2.00000f*(MagickRealType) i-(MagickRealType)
MaxMap);
x_map[i].z=(MagickRealType) i;
y_map[i].z=0.88600f*(2.00000f*(MagickRealType) i-(MagickRealType)
MaxMap);
z_map[i].z=0.00000f;
}
break;
}
case YUVColorspace:
default:
{
/*
Initialize YUV tables:
R = Y +1.13980*V
G = Y-0.39380*U-0.58050*V
B = Y+2.02790*U
U and V, normally -0.5 through 0.5, must be normalized to the range 0
through QuantumRange.
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static)
#endif
for (i=0; i <= (ssize_t) MaxMap; i++)
{
x_map[i].x=(MagickRealType) i;
y_map[i].x=0.00000f;
z_map[i].x=0.56990f*(2.0000f*(MagickRealType) i-(MagickRealType)
MaxMap);
x_map[i].y=(MagickRealType) i;
y_map[i].y=(-0.19690f)*(2.00000f*(MagickRealType) i-(MagickRealType)
MaxMap);
z_map[i].y=(-0.29025f)*(2.00000f*(MagickRealType) i-(MagickRealType)
MaxMap);
x_map[i].z=(MagickRealType) i;
y_map[i].z=1.01395f*(2.00000f*(MagickRealType) i-(MagickRealType)
MaxMap);
z_map[i].z=0.00000f;
}
break;
}
}
/*
Convert to RGB.
*/
switch (image->storage_class)
{
case DirectClass:
default:
{
/*
Convert DirectClass image.
*/
image_view=AcquireCacheView(image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
MagickBooleanType
sync;
MagickPixelPacket
pixel;
register ssize_t
x;
register PixelPacket
*restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
register size_t
blue,
green,
red;
red=ScaleQuantumToMap(GetPixelRed(q));
green=ScaleQuantumToMap(GetPixelGreen(q));
blue=ScaleQuantumToMap(GetPixelBlue(q));
pixel.red=x_map[red].x+y_map[green].x+z_map[blue].x;
pixel.green=x_map[red].y+y_map[green].y+z_map[blue].y;
pixel.blue=x_map[red].z+y_map[green].z+z_map[blue].z;
switch (colorspace)
{
case YCCColorspace:
{
#if !defined(MAGICKCORE_HDRI_SUPPORT)
pixel.red=QuantumRange*YCCMap[RoundToYCC(1024.0*QuantumScale*
pixel.red)];
pixel.green=QuantumRange*YCCMap[RoundToYCC(1024.0*QuantumScale*
pixel.green)];
pixel.blue=QuantumRange*YCCMap[RoundToYCC(1024.0*QuantumScale*
pixel.blue)];
#endif
break;
}
case sRGBColorspace:
{
if ((QuantumScale*pixel.red) <= 0.0031308)
pixel.red*=12.92f;
else
pixel.red=(MagickRealType) QuantumRange*(1.055*
pow(QuantumScale*pixel.red,(1.0/2.4))-0.055);
if ((QuantumScale*pixel.green) <= 0.0031308)
pixel.green*=12.92f;
else
pixel.green=(MagickRealType) QuantumRange*(1.055*
pow(QuantumScale*pixel.green,(1.0/2.4))-0.055);
if ((QuantumScale*pixel.blue) <= 0.0031308)
pixel.blue*=12.92f;
else
pixel.blue=(MagickRealType) QuantumRange*(1.055*
pow(QuantumScale*pixel.blue,(1.0/2.4))-0.055);
break;
}
default:
break;
}
SetPixelRed(q,ScaleMapToQuantum((MagickRealType) MaxMap*
QuantumScale*pixel.red));
SetPixelGreen(q,ScaleMapToQuantum((MagickRealType) MaxMap*
QuantumScale*pixel.green));
SetPixelBlue(q,ScaleMapToQuantum((MagickRealType) MaxMap*
QuantumScale*pixel.blue));
q++;
}
sync=SyncCacheViewAuthenticPixels(image_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_TransformRGBImage)
#endif
proceed=SetImageProgress(image,TransformRGBImageTag,progress++,
image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
image_view=DestroyCacheView(image_view);
break;
}
case PseudoClass:
{
/*
Convert PseudoClass image.
*/
image_view=AcquireCacheView(image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status)
#endif
for (i=0; i < (ssize_t) image->colors; i++)
{
MagickPixelPacket
pixel;
register size_t
blue,
green,
red;
red=ScaleQuantumToMap(image->colormap[i].red);
green=ScaleQuantumToMap(image->colormap[i].green);
blue=ScaleQuantumToMap(image->colormap[i].blue);
pixel.red=x_map[red].x+y_map[green].x+z_map[blue].x;
pixel.green=x_map[red].y+y_map[green].y+z_map[blue].y;
pixel.blue=x_map[red].z+y_map[green].z+z_map[blue].z;
switch (colorspace)
{
case YCCColorspace:
{
#if !defined(MAGICKCORE_HDRI_SUPPORT)
image->colormap[i].red=(Quantum) (QuantumRange*YCCMap[
RoundToYCC(1024.0*QuantumScale*pixel.red)]);
image->colormap[i].green=(Quantum) (QuantumRange*YCCMap[
RoundToYCC(1024.0*QuantumScale*pixel.green)]);
image->colormap[i].blue=(Quantum) (QuantumRange*YCCMap[
RoundToYCC(1024.0*QuantumScale*pixel.blue)]);
#endif
break;
}
case sRGBColorspace:
{
if ((QuantumScale*pixel.red) <= 0.0031308)
pixel.red*=12.92f;
else
pixel.red=(MagickRealType) QuantumRange*(1.055*pow(QuantumScale*
pixel.red,(1.0/2.4))-0.055);
if ((QuantumScale*pixel.green) <= 0.0031308)
pixel.green*=12.92f;
else
pixel.green=(MagickRealType) QuantumRange*(1.055*pow(QuantumScale*
pixel.green,(1.0/2.4))-0.055);
if ((QuantumScale*pixel.blue) <= 0.0031308)
pixel.blue*=12.92f;
else
pixel.blue=(MagickRealType) QuantumRange*(1.055*pow(QuantumScale*
pixel.blue,(1.0/2.4))-0.055);
}
default:
{
image->colormap[i].red=ScaleMapToQuantum((MagickRealType) MaxMap*
QuantumScale*pixel.red);
image->colormap[i].green=ScaleMapToQuantum((MagickRealType) MaxMap*
QuantumScale*pixel.green);
image->colormap[i].blue=ScaleMapToQuantum((MagickRealType) MaxMap*
QuantumScale*pixel.blue);
break;
}
}
}
image_view=DestroyCacheView(image_view);
(void) SyncImage(image);
break;
}
}
/*
Relinquish resources.
*/
z_map=(TransformPacket *) RelinquishMagickMemory(z_map);
y_map=(TransformPacket *) RelinquishMagickMemory(y_map);
x_map=(TransformPacket *) RelinquishMagickMemory(x_map);
if (SetImageColorspace(image,RGBColorspace) == MagickFalse)
return(MagickFalse);
return(MagickTrue);
}
|
sir_omp.c | #include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <omp.h>
void write_solution(char const* filename, int Xmax, int Ymax, double **I)
{
int i, j;
FILE *fp = fopen(filename, "w+");
for (i = 0; i < Ymax; ++i)
{
for (j = 0; j < Xmax; ++j)
{
fprintf(fp, "%g ", I[i][j]);
}
fprintf(fp, "\n");
}
fclose(fp);
}
void initialise(double ** S, double ** I, double ** R, int Xmax, int Ymax)
{
/*
Assume epicenter of spread is NY, which has roughly 15% horizontal width and 20% vertical length.
Assume that NY is hence [0.8, 0.95] horizontally and [0.15, 0.35] vertically.
*/
int NYx_low = 0.8 * Xmax;
int NYx_high = 0.95 * Xmax;
int NYy_low = 0.15 * Ymax;
int NYy_high = 0.35 * Ymax;
for (int i = 0; i < Ymax; ++i)
{
for (int j = 0; j < Xmax; ++j)
{
if ((NYy_low <= i) && (i < NYy_high) && (NYx_low <= j) && (j < NYx_high))
{
I[i][j] = 0.01;
S[i][j] = 0.99;
}
else
{
S[i][j] = 1.0;
}
}
}
}
void simulate(int nsweeps, double **S, double **I, double **R, double beta,
double gamma, double dS, double dI, double dR, int Xmax, int Ymax)
{
/* Initialize tmp arrays */
double **Stmp = calloc(Ymax, sizeof(double * ));
double **Itmp = calloc(Ymax, sizeof(double * ));
double **Rtmp = calloc(Ymax, sizeof(double * ));
for (int i = 0; i < Ymax; ++i)
{
Stmp[i] = calloc(Xmax, sizeof(double));
Itmp[i] = calloc(Xmax, sizeof(double));
Rtmp[i] = calloc(Xmax, sizeof(double));
}
/* Fill boundary conditions into tmp arrays */
for (int i = 0; i < Ymax; ++i)
{
Stmp[i][0] = S[i][0];
Stmp[i][Xmax - 1] = S[i][Xmax - 1];
Itmp[i][0] = I[i][0];
Itmp[i][Xmax - 1] = I[i][Xmax - 1];
Rtmp[i][0] = R[i][0];
Rtmp[i][Xmax - 1] = R[i][Xmax - 1];
}
for (int j = 0; j < Xmax; ++j)
{
Stmp[0][j] = S[0][j];
Stmp[Ymax - 1][j] = S[Ymax - 1][j];
Itmp[0][j] = I[0][j];
Itmp[Ymax - 1][j] = I[Ymax - 1][j];
Rtmp[0][j] = R[0][j];
Rtmp[Ymax - 1][j] = R[Ymax - 1][j];
}
int i, j, sweep;
for (sweep = 0; sweep < nsweeps; sweep += 2)
{
#pragma omp parallel shared(S,I,R,Stmp,Itmp,Rtmp,beta,gamma,dS,dI,dR,Xmax,Ymax) private(i,j)
{
/* Old data in sir; new data in sirtmp */
#pragma omp for collapse(2)
for (i = 1; i < Ymax - 1; ++i)
{
for (j = 1; j < Xmax - 1; ++j)
{
Stmp[i][j] = S[i][j] - beta * S[i][j] * I[i][j]
+ dS * (S[i + 1][j] + S[i - 1][j] - 4 * S[i][j] + S[i][j + 1] + S[i][j - 1]);
Itmp[i][j] = I[i][j] + beta * S[i][j] * I[i][j] - gamma * I[i][j]
+ dI * (I[i + 1][j] + I[i - 1][j] - 4 * I[i][j] + I[i][j + 1] + I[i][j - 1]);
Rtmp[i][j] = R[i][j] + gamma * I[i][j]
+ dR * (R[i + 1][j] + R[i - 1][j] - 4 * R[i][j] + R[i][j + 1] + R[i][j - 1]);
}
}
/* Old data in sirtmp; new data in sir */
#pragma omp for collapse(2)
for (i = 1; i < Ymax - 1; ++i)
{
for (j = 1; j < Xmax - 1; ++j)
{
S[i][j] = Stmp[i][j] - beta * Stmp[i][j] * Itmp[i][j]
+ dS * (Stmp[i + 1][j] + Stmp[i - 1][j] - 4 * Stmp[i][j] + Stmp[i][j + 1] + Stmp[i][j - 1]);
I[i][j] = Itmp[i][j] + beta * Stmp[i][j] * Itmp[i][j] - gamma * Itmp[i][j]
+ dI * (Itmp[i + 1][j] + Itmp[i - 1][j] - 4 * Itmp[i][j] + Itmp[i][j + 1] + Itmp[i][j - 1]);
R[i][j] = Rtmp[i][j] + gamma * Itmp[i][j]
+ dR * (Rtmp[i + 1][j] + Rtmp[i - 1][j] - 4 * Rtmp[i][j] + Rtmp[i][j + 1] + Rtmp[i][j - 1]);
}
}
}
}
free(Stmp);
free(Itmp);
free(Rtmp);
}
int main(int argc, char ** argv)
{
int Xmax, Ymax, nsteps;
double beta, gamma, dS, dI, dR;
double **S, **I, **R;
double tstart, tend;
char *output_filename;
/* Process arguments */
Xmax = (argc > 1) ? atoi(argv[1]) : 100;
Ymax = (argc > 2) ? atoi(argv[2]) : 100;
nsteps = (argc > 3) ? atoi(argv[3]) : 100;
beta = (argc > 4) ? atoi(argv[4]) : 0.2;
gamma = (argc > 5) ? atoi(argv[5]) : 0.01;
dS = (argc > 6) ? atoi(argv[6]) : 0.01;
dI = (argc > 7) ? atoi(argv[7]) : 0.01;
dR = (argc > 8) ? atoi(argv[8]) : 0.01;
output_filename = (argc > 10) ? argv[10] : NULL;
/* Print a diagnostic message */
#pragma omp parallel
if (omp_get_thread_num() == 0)
printf("Threads: %d\n", omp_get_num_threads());
/* Allocate and initialize arrays */
/* Initialize tmp arrays */
printf("Initializing Arrays...\n");
S = calloc(Ymax, sizeof(double * ));
I = calloc(Ymax, sizeof(double * ));
R = calloc(Ymax, sizeof(double * ));
for (int i = 0; i < Ymax; ++i)
{
S[i] = calloc(Xmax, sizeof(double));
I[i] = calloc(Xmax, sizeof(double));
R[i] = calloc(Xmax, sizeof(double));
}
initialise(S, I, R, Xmax, Ymax);
/* Run the solver */
printf("Simulating...\n");
tstart = omp_get_wtime();
simulate(nsteps, S, I, R, beta, gamma, dS, dI, dR, Xmax, Ymax);
tend = omp_get_wtime();
printf("Xmax: %d\n"
"Ymax: %d\n"
"timesteps: %d\n"
"Elapsed time: %g s\n",
Xmax, Ymax, nsteps, tend - tstart);
/* Write the I results */
if (output_filename)
write_solution(output_filename, Xmax, Ymax, I);
free(S);
free(I);
free(R);
return 0;
} |
model_initializer.h | // -----------------------------------------------------------------------------
//
// Copyright (C) 2021 CERN & University of Surrey for the benefit of the
// BioDynaMo collaboration. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
//
// See the LICENSE file distributed with this work for details.
// See the NOTICE file distributed with this work for additional information
// regarding copyright ownership.
//
// -----------------------------------------------------------------------------
#ifndef CORE_MODEL_INITIALIZER_H_
#define CORE_MODEL_INITIALIZER_H_
#include <Math/DistFunc.h>
#include <omp.h>
#include <ctime>
#include <string>
#include <vector>
#include "core/container/math_array.h"
#include "core/diffusion/diffusion_grid.h"
#include "core/resource_manager.h"
#include "core/simulation.h"
#include "core/util/random.h"
class EulerGrid;
class StencilGrid;
class RungaKuttaGrid;
namespace bdm {
struct ModelInitializer {
/// Creates a 3D cubic grid of agents and adds them to the
/// ExecutionContext. Type of the agent is determined by the return
/// type of parameter agent_builder.
///
/// ModelInitializer::Grid3D(8, 10, [](const Double3& pos){
/// return Cell(pos); });
/// @param agents_per_dim number of agents on each axis.
/// Number of generated agents =
/// `agents_per_dim ^ 3`
/// @param space space between the positions - e.g space = 10:
/// positions = `{(0, 0, 0), (0, 0, 10), (0, 0,
/// 20), ... }`
/// @param agent_builder function containing the logic to instantiate a
/// new agent. Takes `const
/// Double3&` as input parameter
///
template <typename Function>
static void Grid3D(size_t agents_per_dim, double space,
Function agent_builder) {
#pragma omp parallel
{
auto* sim = Simulation::GetActive();
auto* ctxt = sim->GetExecutionContext();
#pragma omp for
for (size_t x = 0; x < agents_per_dim; x++) {
auto x_pos = x * space;
for (size_t y = 0; y < agents_per_dim; y++) {
auto y_pos = y * space;
for (size_t z = 0; z < agents_per_dim; z++) {
auto* new_agent = agent_builder({x_pos, y_pos, z * space});
ctxt->AddAgent(new_agent);
}
}
}
}
}
/// Creates a 3D grid of agents and adds them to the
/// ExecutionContext. Type of the agent is determined by the return
/// type of parameter agent_builder.
///
/// ModelInitializer::Grid3D({8,6,4}, 10, [](const Double3&
/// pos){ return Cell(pos); });
/// @param agents_per_dim number of agents on each axis.
/// Number of generated agents =
/// `agents_per_dim[0] * agents_per_dim[1] *
/// agents_per_dim[2]`
/// @param space space between the positions - e.g space = 10:
/// positions = `{(0, 0, 0), (0, 0, 10), (0, 0,
/// 20), ... }`
/// @param agent_builder function containing the logic to instantiate a
/// new agent. Takes `const
/// Double3&` as input parameter
///
template <typename Function>
static void Grid3D(const std::array<size_t, 3>& agents_per_dim, double space,
Function agent_builder) {
#pragma omp parallel
{
auto* sim = Simulation::GetActive();
auto* ctxt = sim->GetExecutionContext();
#pragma omp for
for (size_t x = 0; x < agents_per_dim[0]; x++) {
auto x_pos = x * space;
for (size_t y = 0; y < agents_per_dim[1]; y++) {
auto y_pos = y * space;
for (size_t z = 0; z < agents_per_dim[2]; z++) {
auto* new_agent = agent_builder({x_pos, y_pos, z * space});
ctxt->AddAgent(new_agent);
}
}
}
}
}
/// Creates agents on the given positions and adds them to the
/// ExecutionContext.
///
/// @param positions positions of the agents to be
/// @param agent_builder function containing the logic to instantiate a
/// new agent. Takes `const
/// Double3&` as input parameter
///
template <typename Function>
static void CreateAgents(const std::vector<Double3>& positions,
Function agent_builder) {
#pragma omp parallel
{
auto* sim = Simulation::GetActive();
auto* ctxt = sim->GetExecutionContext();
#pragma omp for
for (size_t i = 0; i < positions.size(); i++) {
auto* new_agent =
agent_builder({positions[i][0], positions[i][1], positions[i][2]});
ctxt->AddAgent(new_agent);
}
}
}
/// Creates agents with random positions and adds them to the
/// ExecutionContext. Agent creation is parallelized.
///
/// @param[in] min The minimum position value
/// @param[in] max The maximum position value
/// @param[in] num_agents The number agents
/// @param[in] agent_builder function containing the logic to instantiate a
/// new agent. Takes `const
/// Double3&` as input parameter
/// \param[in] rng Uses the given DistributionRng.
/// if rng is a nullptr, this function uses a
/// uniform distribution between [min, max[
template <typename Function>
static void CreateAgentsRandom(double min, double max, uint64_t num_agents,
Function agent_builder,
DistributionRng<double>* rng = nullptr) {
#pragma omp parallel
{
auto* sim = Simulation::GetActive();
auto* ctxt = sim->GetExecutionContext();
auto* random = sim->GetRandom();
#pragma omp for
for (uint64_t i = 0; i < num_agents; i++) {
if (rng != nullptr) {
Double3 pos;
bool in_range = false;
do {
pos = rng->Sample3();
in_range = (pos[0] >= min) && (pos[0] <= max) && (pos[1] >= min) &&
(pos[1] <= max) && (pos[2] >= min) && (pos[2] <= max);
} while (!in_range);
auto* new_agent = agent_builder(pos);
ctxt->AddAgent(new_agent);
} else {
auto* new_agent = agent_builder(random->UniformArray<3>(min, max));
ctxt->AddAgent(new_agent);
}
}
}
}
/// Creates agents on surface and adds them to the ExecutionContext.
/// The x and y positions are defined by xmin, xmax, deltax and ymin, ymax,
/// deltay. The z position is calculated using `f`. Agent creation is
/// parallelized.
///
/// auto construct = [](const Double3& position) {
/// Cell* cell = new Cell(position);
/// cell->SetDiameter(10);
/// return cell;
/// };
/// auto f = [](const double* x, const double* params) {
/// // 10 * sin(x/20) + 10 * sin(y/20)
/// return 10 * std::sin(x[0] / 20.) + 10 * std::sin(x[1] / 20.0);
/// };
/// ModelInitializer::CreateAgentsOnSurface(f, {}, -100, 100, 10, -100,
/// 100, 10, construct);
///
/// \param[in] f function that defines the surface
/// \param[in] fn_params Parameters that will be passed to `f` as
/// second argument.
/// @param[in] xmin Minimum x coordinate on which a agent will be
/// created.
/// @param[in] xmax Maximum x coordinate on which a agent will be
/// created.
/// @param[in] deltax Space between two agents on the x-axis.
/// @param[in] ymin Minimum y coordinate on which a agent will be
/// created.
/// @param[in] ymax Maximum y coordinate on which a agent will be
/// created.
/// @param[in] deltay Space between two agents on the y-axis.
/// @param[in] agent_builder function containing the logic to instantiate a
/// new agent. Takes `const Double3&` as input
/// parameter
template <typename Function>
static void CreateAgentsOnSurface(
double (*f)(const double*, const double*),
const FixedSizeVector<double, 10>& fn_params, double xmin, double xmax,
double deltax, double ymin, double ymax, double deltay,
Function agent_builder) {
#pragma omp parallel
{
auto* sim = Simulation::GetActive();
auto* ctxt = sim->GetExecutionContext();
auto xiterations =
static_cast<uint64_t>(std::floor((xmax - xmin) / deltax));
auto yiterations =
static_cast<uint64_t>(std::floor((ymax - ymin) / deltay));
#pragma omp for
for (uint64_t xit = 0; xit < xiterations; ++xit) {
double x = xmin + xit * deltax;
for (uint64_t yit = 0; yit < yiterations; ++yit) {
double y = ymin + yit * deltay;
Double3 pos = {x, y};
pos[2] = f(pos.data(), fn_params.data());
ctxt->AddAgent(agent_builder(pos));
}
}
}
}
/// Creates agents on surface and adds them to the ExecutionContext.
/// The x and y positions are determined by a uniform distribution [xmin,
/// xmax[ and [ymin, ymax[. The z position is calculated using `f`. Agent
/// creation is parallelized.
///
/// auto construct = [](const Double3& position) {
/// Cell* cell = new Cell(position);
/// cell->SetDiameter(10);
/// return cell;
/// };
/// auto f = [](const double* x, const double* params) {
/// // 10 * sin(x/20) + 10 * sin(y/20)
/// return 10 * std::sin(x[0] / 20.) + 10 * std::sin(x[1] / 20.0);
/// };
/// ModelInitializer::CreateAgentsOnSurfaceRndm(f, {}, -100, 100, -100,
/// 100, construct);
///
/// \param[in] f function that defines the surface
/// \param[in] fn_params Parameters that will be passed to `f` as
/// second argument.
/// @param[in] xmin Minimum x coordinate on which a agent will be
/// created.
/// @param[in] xmax Maximum x coordinate on which a agent will be
/// created.
/// @param[in] ymin Minimum y coordinate on which a agent will be
/// created.
/// @param[in] ymax Maximum y coordinate on which a agent will be
/// created.
/// @param[in] agent_builder function containing the logic to instantiate a
/// new agent. Takes `const Double3&` as input
/// parameter
template <typename Function>
static void CreateAgentsOnSurfaceRndm(
double (*f)(const double*, const double*),
const FixedSizeVector<double, 10>& fn_params, double xmin, double xmax,
double ymin, double ymax, uint64_t num_agents, Function agent_builder) {
#pragma omp parallel
{
auto* sim = Simulation::GetActive();
auto* ctxt = sim->GetExecutionContext();
auto* random = sim->GetRandom();
#pragma omp for
for (uint64_t i = 0; i < num_agents; ++i) {
Double3 pos = {random->Uniform(xmin, xmax),
random->Uniform(ymin, ymax)};
pos[2] = f(pos.data(), fn_params.data());
ctxt->AddAgent(agent_builder(pos));
}
}
}
/// Creates agents with random positions on a sphere and adds them to the
/// ExecutionContext. The agents' positions are uniformly distributed accross
/// the surface. Agent creation is parallelized.
/// Algorithm: Knop, 1970, 10.1145/362349.362377 (doi).
///
/// \param[in] center Center of the sphere
/// \param[in] radius Radius of the sphere
/// @param[in] num_agents The number of agents
/// @param[in] agent_builder function containing the logic to instantiate a
/// new agent. Takes `const
/// Double3&` as input parameter
template <typename Function>
static void CreateAgentsOnSphereRndm(const Double3& center, double radius,
uint64_t num_agents,
Function agent_builder) {
#pragma omp parallel
{
auto* sim = Simulation::GetActive();
auto* ctxt = sim->GetExecutionContext();
auto* random = sim->GetRandom();
#pragma omp for
for (uint64_t i = 0; i < num_agents; i++) {
auto pos = random->Sphere(radius) + center;
auto* new_agent = agent_builder(pos);
ctxt->AddAgent(new_agent);
}
}
}
/// Creates agents with random positions in a sphere and adds them to the
/// ExecutionContext. Agents are distributed uniformly inside the sphere.
/// Agent creation is parallelized. Algorithm: Knop,
/// 1970, 10.1145/362349.362377 (doi).
///
/// \param[in] center Center of the sphere
/// \param[in] radius Radius of the sphere
/// @param[in] num_agents The number of agents
/// @param[in] agent_builder function containing the logic to instantiate a
/// new agent. Takes `const
/// Double3&` as input parameter
template <typename Function>
static void CreateAgentsInSphereRndm(const Double3& center, double radius,
uint64_t num_agents,
Function agent_builder) {
#pragma omp parallel
{
// We use a probability density function (PDF) to model the probability of
// an agent to occur at a distance `r>=0` of the center. As the surface of
// a sphere scales as `r^2`, the PDF does as well. Thus
// `p(r)=a*r^2*\Theta(R-r)`, where `\Theta` is a heavyside function and R
// is largest allowed radius (interpretation: no agents outside the
// sphere). We can fix `a` by requiring `\int_0^\inf p(r') dr' = 1` and
// obtain `a=3/R^3`.
auto radial_pdf_sphere = [](const double* x, const double* params) {
double R{params[0]};
double r{x[0]};
if (r > 0.0 && r <= R) {
return 3.0 * std::pow(r, 2.0) / std::pow(R, 3.0);
} else {
return 0.0;
}
};
// Get a random number generator to sample from our PDF.
auto* random = Simulation::GetActive()->GetRandom();
auto rng = random->GetUserDefinedDistRng1D(radial_pdf_sphere, {radius}, 0,
radius);
auto* ctxt = Simulation::GetActive()->GetExecutionContext();
#pragma omp for schedule(static)
for (uint64_t i = 0; i < num_agents; i++) {
// Random position in sphere around center
auto pos = random->Sphere(rng.Sample()) + center;
auto* new_agent = agent_builder(pos);
ctxt->AddAgent(new_agent);
}
}
}
/// Allows agents to secrete the specified substance. Diffusion throughout the
/// simulation space is automatically taken care of by the DiffusionGrid class
///
/// @param[in] substance_id The substance identifier
/// @param[in] substance_name The substance name
/// @param[in] diffusion_coeff The diffusion coefficient
/// @param[in] decay_constant The decay constant
/// @param[in] resolution The resolution of the diffusion grid
///
static void DefineSubstance(size_t substance_id,
const std::string& substance_name,
double diffusion_coeff, double decay_constant,
int resolution = 10);
template <typename F>
static void InitializeSubstance(size_t substance_id, F function) {
auto* sim = Simulation::GetActive();
auto* rm = sim->GetResourceManager();
auto diffusion_grid = rm->GetDiffusionGrid(substance_id);
diffusion_grid->AddInitializer(function);
}
};
} // namespace bdm
#endif // CORE_MODEL_INITIALIZER_H_
|
sparselu.c | /**********************************************************************************************/
/* This program is part of the Barcelona OpenMP Tasks Suite */
/* Copyright (C) 2009 Barcelona Supercomputing Center - Centro Nacional de Supercomputacion */
/* Copyright (C) 2009 Universitat Politecnica de Catalunya */
/* */
/* This program is free software; you can redistribute it and/or modify */
/* it under the terms of the GNU General Public License as published by */
/* the Free Software Foundation; either version 2 of the License, or */
/* (at your option) any later version. */
/* */
/* This program is distributed in the hope that it will be useful, */
/* but WITHOUT ANY WARRANTY; without even the implied warranty of */
/* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the */
/* GNU General Public License for more details. */
/* */
/* You should have received a copy of the GNU General Public License */
/* along with this program; if not, write to the Free Software */
/* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */
/**********************************************************************************************/
#include <stdio.h>
#include <stdint.h>
#include <stdlib.h>
#include <string.h>
#include <math.h>
#include <libgen.h>
//#include "bots.h"
#include "sparselu.h"
#include <omp.h>
#include <taskflow/taskflow.hpp>
#define FALSE 0
#define TRUE 1
/***********************************************************************
* checkmat:
**********************************************************************/
int checkmat (float *M, float *N)
{
int i, j;
float r_err;
for (i = 0; i < submatrix_size; i++)
{
for (j = 0; j < submatrix_size; j++)
{
r_err = M[i*submatrix_size+j] - N[i*submatrix_size+j];
if ( r_err == 0.0 ) continue;
if (r_err < 0.0 ) r_err = -r_err;
if ( M[i*submatrix_size+j] == 0 )
{
printf("Checking failure: A[%d][%d]=%f B[%d][%d]=%f; \n",
i,j, M[i*submatrix_size+j], i,j, N[i*submatrix_size+j]);
return FALSE;
}
r_err = r_err / M[i*submatrix_size+j];
if(r_err > EPSILON)
{
printf("Checking failure: A[%d][%d]=%f B[%d][%d]=%f; Relative Error=%f\n",
i,j, M[i*submatrix_size+j], i,j, N[i*submatrix_size+j], r_err);
return FALSE;
}
}
}
return TRUE;
}
/***********************************************************************
* genmat:
**********************************************************************/
void genmat (float *M[])
{
int null_entry, init_val, i, j, ii, jj;
float *p;
int a=0,b=0;
init_val = 1325;
/* generating the structure */
for (ii=0; ii < matrix_size; ii++)
{
for (jj=0; jj < matrix_size; jj++)
{
/* computing null entries */
null_entry=FALSE;
if ((ii<jj) && (ii%3 !=0)) null_entry = TRUE;
if ((ii>jj) && (jj%3 !=0)) null_entry = TRUE;
if (ii%2==1) null_entry = TRUE;
if (jj%2==1) null_entry = TRUE;
if (ii==jj) null_entry = FALSE;
if (ii==jj-1) null_entry = FALSE;
if (ii-1 == jj) null_entry = FALSE;
/* allocating matrix */
if (null_entry == FALSE){
a++;
M[ii*matrix_size+jj] = (float *) malloc(submatrix_size*submatrix_size*sizeof(float));
if (M[ii*matrix_size+jj] == NULL)
{
printf("Error: Out of memory\n");
exit(101);
}
/* initializing matrix */
p = M[ii*matrix_size+jj];
for (i = 0; i < submatrix_size; i++)
{
for (j = 0; j < submatrix_size; j++)
{
init_val = (3125 * init_val) % 65536;
(*p) = (float)((init_val - 32768.0) / 16384.0);
p++;
}
}
}
else
{
b++;
M[ii*matrix_size+jj] = NULL;
}
}
}
//bots_debug("allo = %d, no = %d, total = %d, factor = %f\n",a,b,a+b,(float)((float)a/(float)(a+b)));
}
/***********************************************************************
* print_structure:
**********************************************************************/
void print_structure(char *name, float *M[])
{
int ii, jj;
printf("Structure for matrix %s @ 0x%p\n",name, M);
for (ii = 0; ii < matrix_size; ii++) {
for (jj = 0; jj < matrix_size; jj++) {
if (M[ii*matrix_size+jj]!=NULL) {printf("x");}
else printf(" ");
}
printf("\n");
}
printf("\n");
}
/***********************************************************************
* allocate_clean_block:
**********************************************************************/
float * allocate_clean_block()
{
int i,j;
float *p, *q;
p = (float *) malloc(submatrix_size*submatrix_size*sizeof(float));
q=p;
if (p!=NULL){
for (i = 0; i < submatrix_size; i++)
for (j = 0; j < submatrix_size; j++){(*p)=0.0; p++;}
}
else
{
printf("Error: Out of memory\n");
exit (101);
}
return (q);
}
/***********************************************************************
* lu0:
**********************************************************************/
void lu0(float *diag)
{
int i, j, k;
for (k=0; k<submatrix_size; k++)
for (i=k+1; i<submatrix_size; i++)
{
diag[i*submatrix_size+k] = diag[i*submatrix_size+k] / diag[k*submatrix_size+k];
for (j=k+1; j<submatrix_size; j++)
diag[i*submatrix_size+j] = diag[i*submatrix_size+j] - diag[i*submatrix_size+k] * diag[k*submatrix_size+j];
}
}
/***********************************************************************
* bdiv:
**********************************************************************/
void bdiv(float *diag, float *row)
{
int i, j, k;
for (i=0; i<submatrix_size; i++)
for (k=0; k<submatrix_size; k++)
{
row[i*submatrix_size+k] = row[i*submatrix_size+k] / diag[k*submatrix_size+k];
for (j=k+1; j<submatrix_size; j++)
row[i*submatrix_size+j] = row[i*submatrix_size+j] - row[i*submatrix_size+k]*diag[k*submatrix_size+j];
}
}
/***********************************************************************
* bmod:
**********************************************************************/
void bmod(float *row, float *col, float *inner)
{
int i, j, k;
for (i=0; i<submatrix_size; i++)
for (j=0; j<submatrix_size; j++)
for (k=0; k<submatrix_size; k++)
inner[i*submatrix_size+j] = inner[i*submatrix_size+j] - row[i*submatrix_size+k]*col[k*submatrix_size+j];
}
/***********************************************************************
* fwd:
**********************************************************************/
void fwd(float *diag, float *col)
{
int i, j, k;
for (j=0; j<submatrix_size; j++)
for (k=0; k<submatrix_size; k++)
for (i=k+1; i<submatrix_size; i++)
col[i*submatrix_size+j] = col[i*submatrix_size+j] - diag[i*submatrix_size+k]*col[k*submatrix_size+j];
}
void sparselu_init (float ***pBENCH, char *pass)
{
*pBENCH = (float **) malloc(matrix_size*matrix_size*sizeof(float *));
genmat(*pBENCH);
//print_structure(pass, *pBENCH);
}
void sparselu_seq_call(float **BENCH)
{
int ii, jj, kk;
for (kk=0; kk<matrix_size; kk++)
{
lu0(BENCH[kk*matrix_size+kk]);
for (jj=kk+1; jj<matrix_size; jj++)
if (BENCH[kk*matrix_size+jj] != NULL)
{
fwd(BENCH[kk*matrix_size+kk], BENCH[kk*matrix_size+jj]);
}
for (ii=kk+1; ii<matrix_size; ii++)
if (BENCH[ii*matrix_size+kk] != NULL)
{
bdiv (BENCH[kk*matrix_size+kk], BENCH[ii*matrix_size+kk]);
}
for (ii=kk+1; ii<matrix_size; ii++)
if (BENCH[ii*matrix_size+kk] != NULL)
for (jj=kk+1; jj<matrix_size; jj++)
if (BENCH[kk*matrix_size+jj] != NULL)
{
if (BENCH[ii*matrix_size+jj]==NULL) BENCH[ii*matrix_size+jj] = allocate_clean_block();
bmod(BENCH[ii*matrix_size+kk], BENCH[kk*matrix_size+jj], BENCH[ii*matrix_size+jj]);
}
}
}
void sparselu_par_call(float **BENCH)
{
omp_set_num_threads(14);
int ii, jj, kk;
printf("Computing SparseLU Factorization (%dx%d matrix with %dx%d blocks) ",
matrix_size,matrix_size,submatrix_size,submatrix_size);
#pragma omp parallel private(kk)
{
for (kk=0; kk<matrix_size; kk++)
{
#pragma omp single
lu0(BENCH[kk*matrix_size+kk]);
#pragma omp for nowait
for (jj=kk+1; jj<matrix_size; jj++)
if (BENCH[kk*matrix_size+jj] != NULL)
#pragma omp task untied firstprivate(kk, jj) shared(BENCH)
{
fwd(BENCH[kk*matrix_size+kk], BENCH[kk*matrix_size+jj]);
}
#pragma omp for
for (ii=kk+1; ii<matrix_size; ii++)
if (BENCH[ii*matrix_size+kk] != NULL)
#pragma omp task untied firstprivate(kk, ii) shared(BENCH)
{
bdiv (BENCH[kk*matrix_size+kk], BENCH[ii*matrix_size+kk]);
}
#pragma omp for private(jj)
for (ii=kk+1; ii<matrix_size; ii++)
if (BENCH[ii*matrix_size+kk] != NULL)
for (jj=kk+1; jj<matrix_size; jj++)
if (BENCH[kk*matrix_size+jj] != NULL)
#pragma omp task untied firstprivate(kk, jj, ii) shared(BENCH)
{
if (BENCH[ii*matrix_size+jj]==NULL) BENCH[ii*matrix_size+jj] = allocate_clean_block();
bmod(BENCH[ii*matrix_size+kk], BENCH[kk*matrix_size+jj], BENCH[ii*matrix_size+jj]);
}
}
}
printf(" completed!\n");
}
void sparselu_fini (float **BENCH, char *pass) {
print_structure(pass, BENCH);
}
int sparselu_check(float **SEQ, float **BENCH)
{
int ii,jj,ok=1;
for (ii=0; ((ii<matrix_size) && ok); ii++)
{
for (jj=0; ((jj<matrix_size) && ok); jj++)
{
if ((SEQ[ii*matrix_size+jj] == NULL) && (BENCH[ii*matrix_size+jj] != NULL)) ok = FALSE;
if ((SEQ[ii*matrix_size+jj] != NULL) && (BENCH[ii*matrix_size+jj] == NULL)) ok = FALSE;
if ((SEQ[ii*matrix_size+jj] != NULL) && (BENCH[ii*matrix_size+jj] != NULL))
ok = checkmat(SEQ[ii*matrix_size+jj], BENCH[ii*matrix_size+jj]);
}
}
assert(ok);
if (ok) return 0; // Success
else return 1; // Fail
}
void sparselu_tf_for(float **BENCH)
{
tf::Taskflow flow;
const unsigned num_threads = 14;
printf("Computing SparseLU Factorization (%dx%d matrix with %dx%d blocks) ",
matrix_size,matrix_size,submatrix_size,submatrix_size);
int kk = -1;
auto t1 = flow.emplace([&](){
kk ++;
lu0(BENCH[kk*matrix_size+kk]);
});
std::vector<tf::Task> tasks;
for(int i=0; i<num_threads; i++) {
tasks.emplace_back(
flow.emplace( [&, id=i] (auto &subflow) {
int part = (matrix_size - kk - 1 + num_threads - 1)/num_threads;
int beg = part*id + kk + 1;
int end = beg + part < matrix_size ? beg+part : matrix_size;
for(int jj=beg; jj<end; jj++) {
if (BENCH[kk*matrix_size+jj] != NULL) {
subflow.emplace([&, jj](){ fwd(BENCH[kk*matrix_size+kk], BENCH[kk*matrix_size+jj]); });
}
}
})
);
}
t1.precede(tasks);
auto sync1 = flow.emplace([](){});
for(auto &t: tasks) {
t.precede(sync1);
}
tasks.clear();
for(int i=0; i<num_threads; i++) {
tasks.emplace_back(
flow.emplace([&, id=i](auto &subflow){
int part = (matrix_size - kk - 1 + num_threads - 1)/num_threads;
int beg = part*id + kk + 1;
int end = beg + part < matrix_size ? beg+part : matrix_size;
for(int ii=beg; ii<end; ii++) {
if (BENCH[ii*matrix_size+kk] != NULL) {
subflow.emplace([&, ii](){ bdiv (BENCH[kk*matrix_size+kk], BENCH[ii*matrix_size+kk]); });
}
}
})
);
}
sync1.precede(tasks);
sync1 = flow.emplace([](){});
sync1.gather(tasks);
tasks.clear();
for(int i=0; i<num_threads; i++) {
tasks.emplace_back(
flow.emplace([&, id=i](auto &subflow){
int part = (matrix_size - kk - 1 + num_threads - 1)/num_threads;
int beg = part*id + kk + 1;
int end = beg + part < matrix_size ? beg+part : matrix_size;
for (int ii=beg; ii<end; ii++)
if (BENCH[ii*matrix_size+kk] != NULL)
for (int jj=kk+1; jj<matrix_size; jj++)
if (BENCH[kk*matrix_size+jj] != NULL)
{
subflow.emplace([&, ii, jj](){
if (BENCH[ii*matrix_size+jj]==NULL) BENCH[ii*matrix_size+jj] = allocate_clean_block();
bmod(BENCH[ii*matrix_size+kk], BENCH[kk*matrix_size+jj], BENCH[ii*matrix_size+jj]);
});
}
})
);
}
sync1.precede(tasks);
tf::Executor executor (num_threads);
executor.run_n(flow, matrix_size).wait();
printf(" completed!\n");
}
|
rt_dplgsy.c | #include "runtime.h"
void RT_CORE_dplgsy( Quark *quark, Quark_Task_Flags *task_flags,
double bump, int m, int n, double *A, int lda,
int bigM, int m0, int n0, unsigned long long int seed )
{
plasma_context_t *plasma;
plasma = plasma_context_self();
if (plasma->runtime == PLASMA_QUARK) {
QUARK_CORE_dplgsy(quark, task_flags,
bump, m, n, A, lda,
bigM, m0, n0, seed );
} else if (plasma->runtime == PLASMA_OMPSS) {
#pragma omp target device (smp) copy_deps
#pragma omp task out([lda*n]A) label(dplgsy)
CORE_dplgsy_rt(bump, m, n, A, lda, bigM, m0, n0, seed);
}
}
void CORE_dplgsy_rt(int bump, int m, int n, double *A, int lda, int bigM,
int m0, int n0, unsigned long long int seed)
{
CORE_dplgsy(bump, m, n, A, lda, bigM, m0, n0, seed);
}
|
GB_unop__ainv_int8_int8.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_atomics.h"
#include "GB_unop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB (_unop_apply__ainv_int8_int8)
// op(A') function: GB (_unop_tran__ainv_int8_int8)
// C type: int8_t
// A type: int8_t
// cast: int8_t cij = aij
// unaryop: cij = -aij
#define GB_ATYPE \
int8_t
#define GB_CTYPE \
int8_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
int8_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = -x ;
// casting
#define GB_CAST(z, aij) \
int8_t z = aij ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
int8_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
int8_t z = aij ; \
Cx [pC] = -z ; \
}
// true if operator is the identity op with no typecasting
#define GB_OP_IS_IDENTITY_WITH_NO_TYPECAST \
0
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_AINV || GxB_NO_INT8)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_apply__ainv_int8_int8)
(
int8_t *Cx, // Cx and Ax may be aliased
const int8_t *Ax,
const int8_t *restrict Ab, // A->b if A is bitmap
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
// TODO: if OP is ONE and uniform-valued matrices are exploited, then
// do this in O(1) time
if (Ab == NULL)
{
#if ( GB_OP_IS_IDENTITY_WITH_NO_TYPECAST )
GB_memcpy (Cx, Ax, anz * sizeof (int8_t), nthreads) ;
#else
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
int8_t aij = Ax [p] ;
int8_t z = aij ;
Cx [p] = -z ;
}
#endif
}
else
{
// bitmap case, no transpose; A->b already memcpy'd into C->b
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!Ab [p]) continue ;
int8_t aij = Ax [p] ;
int8_t z = aij ;
Cx [p] = -z ;
}
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_tran__ainv_int8_int8)
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
dense_inplace.c | /* Copyright (c) 2016 Drew Schmidt
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice,
this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
// Functions for computing covariance, (pearson) correlation, and cosine similarity
#include <stdlib.h>
#include <string.h>
#include "utils/safeomp.h"
#include "coop.h"
#include "utils/fill.h"
#include "utils/inverse.h"
/*
// O(1) storage
static int coop_covar_vecvec_inplace(const int n, const double * const restrict x, const double * const restrict y, double *restrict cor)
{
int i;
const double denom = (double) 1/n;
double meanx;
double meany; // :DDD
double mmcp = 0.0; // minus-mean-crossproduct
meanx = 0.0;
meany = 0.0;
PLEASE_VECTORIZE
for (i=0; i<n; i++)
{
meanx += x[i];
meany += y[i];
}
meanx *= denom;
meany *= denom;
PLEASE_VECTORIZE
for (i=0; i<n; i++)
mmcp += (x[i] - meanx) * (y[i] - meany);
*cor = mmcp / ((double)(n-1));
return COOP_OK;
}
*/
// O(m+n) storage
static int co_mat_inplace(const int m, const int n, const double * const restrict x, double *restrict cov)
{
double *vec = malloc(m * sizeof(*vec));
CHECKMALLOC(vec);
double *means = malloc(n * sizeof(*means));
if (means==NULL)
{
free(vec);
return -1;
}
const double denom_mean = (double) 1./m;
const double denom_cov = (double) 1./(m-1);
// get column means
#pragma omp parallel for shared(means) if (m*n > OMP_MIN_SIZE)
for (int j=0; j<n; j++)
{
const int mj = m*j;
means[j] = 0.0;
SAFE_SIMD
for (int i=0; i<m; i++)
means[j] += x[i + mj];
means[j] *= denom_mean;
}
// co-operation
for (int j=0; j<n; j++)
{
const int mj = m*j;
memcpy(vec, x+mj, m*sizeof(*vec));
const double meanx = means[j];
PLEASE_VECTORIZE
for (int k=0; k<m; k++)
vec[k] -= meanx;
#pragma omp parallel for shared(j, means, vec, cov) if(m*n > OMP_MIN_SIZE)
for (int i=j; i<n; i++)
{
const int mi = m*i;
const double meany = means[i];
double mmcp = 0.0;
SAFE_SIMD
for (int k=0; k<m; k++)
mmcp += vec[k] * (x[k + mi] - meany);
cov[i + n*j] = mmcp * denom_cov;
}
}
free(vec);
free(means);
return COOP_OK;
}
// ---------------------------------------------
// Interface
// ---------------------------------------------
int coop_pcor_mat_inplace(const bool inv, const int m, const int n, const double * const restrict x, double *restrict cor)
{
int check = co_mat_inplace(m, n, x, cor);
CHECKRET(check);
cosim_fill(n, cor);
if (inv)
{
check = inv_sym_chol(n, cor);
CHECKRET(check);
}
symmetrize(n, cor);
return COOP_OK;
}
int coop_covar_mat_inplace(const bool inv, const int m, const int n, const double * const restrict x, double *restrict cov)
{
int check = co_mat_inplace(m, n, x, cov);
CHECKRET(check);
if (inv)
{
check = inv_sym_chol(n, cov);
CHECKRET(check);
}
symmetrize(n, cov);
return COOP_OK;
}
|
GB_binop__pair_fc64.c | //------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB_AaddB__pair_fc64
// A.*B function (eWiseMult): GB_AemultB__pair_fc64
// A*D function (colscale): GB_AxD__pair_fc64
// D*A function (rowscale): GB_DxB__pair_fc64
// C+=B function (dense accum): GB_Cdense_accumB__pair_fc64
// C+=b function (dense accum): GB_Cdense_accumb__pair_fc64
// C+=A+B function (dense ewise3): (none)
// C=A+B function (dense ewise3): GB_Cdense_ewise3_noaccum__pair_fc64
// C=scalar+B (none)
// C=scalar+B' (none)
// C=A+scalar (none)
// C=A'+scalar (none)
// C type: GxB_FC64_t
// A type: GxB_FC64_t
// B,b type: GxB_FC64_t
// BinaryOp: cij = GxB_CMPLX(1,0)
#define GB_ATYPE \
GxB_FC64_t
#define GB_BTYPE \
GxB_FC64_t
#define GB_CTYPE \
GxB_FC64_t
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
1
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
1
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
;
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB) \
;
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
GxB_FC64_t t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA) \
cij = Ax [pA]
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB) \
cij = Bx [pB]
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z, x, y, i, j) \
z = GxB_CMPLX(1,0) ;
// op is second
#define GB_OP_IS_SECOND \
0
// op is plus_fp32 or plus_fp64
#define GB_OP_IS_PLUS_REAL \
0
// op is minus_fp32 or minus_fp64
#define GB_OP_IS_MINUS_REAL \
0
// GB_cblas_*axpy gateway routine, if it exists for this operator and type:
#define GB_CBLAS_AXPY \
(none)
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_PAIR || GxB_NO_FC64 || GxB_NO_PAIR_FC64)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
#if 0
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void (none)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
#endif
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
GrB_Info GB_Cdense_ewise3_noaccum__pair_fc64
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_dense_ewise3_noaccum_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB_Cdense_accumB__pair_fc64
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *GB_RESTRICT kfirst_slice,
const int64_t *GB_RESTRICT klast_slice,
const int64_t *GB_RESTRICT pstart_slice,
const int ntasks,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
#include "GB_dense_subassign_23_template.c"
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB_Cdense_accumb__pair_fc64
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
// get the scalar b for C += b, of type GxB_FC64_t
GxB_FC64_t bwork = (*((GxB_FC64_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB_AxD__pair_fc64
(
GrB_Matrix C,
const GrB_Matrix A, bool A_is_pattern,
const GrB_Matrix D, bool D_is_pattern,
const int64_t *GB_RESTRICT kfirst_slice,
const int64_t *GB_RESTRICT klast_slice,
const int64_t *GB_RESTRICT pstart_slice,
const int ntasks,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC64_t *GB_RESTRICT Cx = (GxB_FC64_t *) C->x ;
#include "GB_AxB_colscale_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB_DxB__pair_fc64
(
GrB_Matrix C,
const GrB_Matrix D, bool D_is_pattern,
const GrB_Matrix B, bool B_is_pattern,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC64_t *GB_RESTRICT Cx = (GxB_FC64_t *) C->x ;
#include "GB_AxB_rowscale_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C = A+B or C<M> = A+B
//------------------------------------------------------------------------------
#undef GB_FREE_ALL
#define GB_FREE_ALL \
{ \
GB_ek_slice_free (&pstart_Mslice, &kfirst_Mslice, &klast_Mslice) ; \
GB_ek_slice_free (&pstart_Aslice, &kfirst_Aslice, &klast_Aslice) ; \
GB_ek_slice_free (&pstart_Bslice, &kfirst_Bslice, &klast_Bslice) ; \
}
GrB_Info GB_AaddB__pair_fc64
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool Ch_is_Mh,
const int64_t *GB_RESTRICT C_to_M,
const int64_t *GB_RESTRICT C_to_A,
const int64_t *GB_RESTRICT C_to_B,
const GB_task_struct *GB_RESTRICT TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t *pstart_Mslice = NULL, *kfirst_Mslice = NULL, *klast_Mslice = NULL ;
int64_t *pstart_Aslice = NULL, *kfirst_Aslice = NULL, *klast_Aslice = NULL ;
int64_t *pstart_Bslice = NULL, *kfirst_Bslice = NULL, *klast_Bslice = NULL ;
#include "GB_add_template.c"
GB_FREE_ALL ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C = A.*B or C<M> = A.*B
//------------------------------------------------------------------------------
GrB_Info GB_AemultB__pair_fc64
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *GB_RESTRICT C_to_M,
const int64_t *GB_RESTRICT C_to_A,
const int64_t *GB_RESTRICT C_to_B,
const GB_task_struct *GB_RESTRICT TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t *pstart_Mslice = NULL, *kfirst_Mslice = NULL, *klast_Mslice = NULL ;
int64_t *pstart_Aslice = NULL, *kfirst_Aslice = NULL, *klast_Aslice = NULL ;
int64_t *pstart_Bslice = NULL, *kfirst_Bslice = NULL, *klast_Bslice = NULL ;
#include "GB_emult_template.c"
GB_FREE_ALL ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
#if 0
GrB_Info (none)
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *GB_RESTRICT Bb,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC64_t *Cx = (GxB_FC64_t *) Cx_output ;
GxB_FC64_t x = (*((GxB_FC64_t *) x_input)) ;
GxB_FC64_t *Bx = (GxB_FC64_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Bb, p)) continue ;
; ;
Cx [p] = GxB_CMPLX(1,0) ;
}
return (GrB_SUCCESS) ;
#endif
}
#endif
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
#if 0
GrB_Info (none)
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *GB_RESTRICT Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
GxB_FC64_t *Cx = (GxB_FC64_t *) Cx_output ;
GxB_FC64_t *Ax = (GxB_FC64_t *) Ax_input ;
GxB_FC64_t y = (*((GxB_FC64_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
; ;
Cx [p] = GxB_CMPLX(1,0) ;
}
return (GrB_SUCCESS) ;
#endif
}
#endif
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
#if 0
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
; ; \
Cx [pC] = GxB_CMPLX(1,0) ; \
}
GrB_Info (none)
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *GB_RESTRICT *Workspaces,
const int64_t *GB_RESTRICT A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
GxB_FC64_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC64_t x = (*((const GxB_FC64_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
GxB_FC64_t
}
#endif
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
#if 0
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
; ; \
Cx [pC] = GxB_CMPLX(1,0) ; \
}
GrB_Info (none)
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *GB_RESTRICT *Workspaces,
const int64_t *GB_RESTRICT A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC64_t y = (*((const GxB_FC64_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
#endif
|
optimize.c | /* Copyright 2014. The Regents of the University of California.
* Copyright 2016-2017. Martin Uecker.
* All rights reserved. Use of this source code is governed by
* a BSD-style license which can be found in the LICENSE file.
*
* Authors:
* 2013-2017 Martin Uecker <martin.uecker@med.uni-goettingen.de>
*
*
* Optimization framework for operations on multi-dimensional arrays.
*
*/
#include <assert.h>
#include <stdbool.h>
#include <stdlib.h>
#include <string.h>
#include <strings.h>
#include <math.h>
#include "misc/misc.h"
#include "misc/debug.h"
#include "misc/nested.h"
#include "num/multind.h"
#include "num/vecops.h"
#ifdef USE_CUDA
#include "num/gpuops.h"
#endif
#include "num/simplex.h"
#include "optimize.h"
/*
* Helper functions:
*
* 1. detect aliasing
* 2. detect if dimensions can be merged
* 3. compute memory footprint
*
*/
#if 0
static bool regular(long dim, long str)
{
return (dim > 0) && (str > 0);
}
static bool singular(long dim, long str)
{
assert(dim > 0);
return (1 == dim) || (0 == str);
}
static bool enclosed(const long dims[2], const long strs[2])
{
assert(regular(dims[0], strs[0]));
assert(regular(dims[1], strs[1]));
return (strs[1] >= dims[0] * strs[0]);
}
// assumes no overlap
static long memory_footprint(int N, const long dims[N], const long strs[N])
{
unsigned int flags = 0;
for (int i = 0; i < N; i++)
flags |= (0 == strs[i]);
long dims2[N];
md_select_dims(N, ~flags, dims2, dims);
return md_calc_size(N, dims2);
}
#endif
/*
* Generic optimizations strategy:
*
* 1. ordering of dimensions by stride
* 2. merging of dimensions
* 3. splitting and ordering (cache-oblivious algorithms)
* 4. parallelization
*
*/
/* strategies:
- cache-oblivous algorithms (e.g. transpose)
- use of accelerators
- parallelization
- vectorization
- reordering of memory access
- temporaries
- loop merging
- splitting
*/
/*
* Each parameter is either input or output. The pointers must valid
* and all accesses using any position inside the range given by
* dimensions and using corresponding strides must be inside of the
* adressed memory region. Pointers pointing inside the same region
* can be passed multipe times.
*/
void merge_dims(unsigned int D, unsigned int N, long dims[N], long (*ostrs[D])[N])
{
for (int i = N - 2; i >= 0; i--) {
bool domerge = true;
for (unsigned int j = 0; j < D; j++) // mergeable
domerge = domerge && ((*ostrs[j])[i + 1] == dims[i] * (*ostrs[j])[i]);
if (domerge) {
for (unsigned int j = 0; j < D; j++)
(*ostrs[j])[i + 1] = 0;
dims[i + 0] *= dims[i + 1];
dims[i + 1] = 1;
}
if (1 == dims[i + 0]) { //everything can be merged with an empty dimension
dims[i + 0] = dims[i + 1];
dims[i + 1] = 1;
for (unsigned int j = 0; j < D; j++) {
(*ostrs[j])[i + 0] = (*ostrs[j])[i + 1];
(*ostrs[j])[i + 1] = 0;
}
}
}
}
unsigned int remove_empty_dims(unsigned int D, unsigned int N, long dims[N], long (*ostrs[D])[N])
{
unsigned int o = 0;
for (unsigned int i = 0; i < N; i++) {
if (1 != dims[i]) {
dims[o] = dims[i];
for (unsigned int j = 0; j < D; j++)
(*ostrs[j])[o] = (*ostrs[j])[i];
o++;
}
}
return o;
}
static void compute_permutation(unsigned int N, int ord[N], const long strs[N])
{
__block const long* strsp = strs; // clang workaround
for (unsigned int i = 0; i < N; i++)
ord[i] = i;
NESTED(int, cmp_strides, (int a, int b))
{
long d = strsp[a] - strsp[b];
if (d > 0)
return 1;
if (d < 0)
return -1;
return 0;
};
quicksort(N, ord, cmp_strides);
}
static void reorder_long(int N, int ord[N], long x[N])
{
long tmp[N];
memcpy(tmp, x, N * sizeof(long));
for (int i = 0; i < N; i++)
x[i] = tmp[ord[i]];
}
/*
* Jim Demmel's generic blocking theorem
*/
static void demmel_factors(unsigned int D, unsigned int N, float blocking[N], long (*strs[D])[N])
{
float delta[D][N];
for (unsigned int d = 0; d < D; d++)
for (unsigned int n = 0; n < N; n++)
delta[d][n] = (0 != (*strs[d])[n]) ? 1. : 0.;
// now maximize 1^T x subject to Delta x <= 1
// M^{x_n} yields blocking factors where M is cache size (maybe needs to be devided by D?)
float ones[MAX(N, D)];
for (unsigned int n = 0; n < MAX(N, D); n++)
ones[n] = 1.;
simplex(D, N, blocking, ones, ones, (const float (*)[N])delta);
}
static long find_factor(long x, float blocking)
{
//long m = (long)(1. + sqrt((double)x));
long m = (long)(1. + pow((double)x, blocking));
for (long i = m; i > 1; i--)
if (0 == x % i)
return (x / i);
return 1;
}
static bool split_dims(unsigned int D, unsigned int N, long dims[N + 1], long (*ostrs[D])[N + 1], float blocking[N])
{
if (0 == N)
return false;
long f;
if ((dims[N - 1] > 1024) && (1 < (f = find_factor(dims[N - 1], blocking[N - 1])))) {
#if 1
dims[N - 1] = dims[N - 1] / f;
dims[N] = f;
for (unsigned int j = 0; j < D; j++)
(*ostrs[j])[N] = (*ostrs[j])[N - 1] * dims[N - 1];
blocking[N - 1] = blocking[N - 1];
blocking[N] = blocking[N - 1];
#else
dims[N] = 1;
for (unsigned int j = 0; j < D; j++)
(*ostrs[j])[N] = 0;
#endif
return true;
}
// could not split, make room and try lower dimensions
dims[N] = dims[N - 1];
blocking[N] = blocking[N - 1];
for (unsigned int j = 0; j < D; j++)
(*ostrs[j])[N] = (*ostrs[j])[N - 1];
if (split_dims(D, N - 1, dims, ostrs, blocking))
return true;
dims[N - 1] = dims[N];
for (unsigned int j = 0; j < D; j++)
(*ostrs[j])[N - 1] = (*ostrs[j])[N];
blocking[N - 1] = blocking[N];
return false;
}
unsigned int simplify_dims(unsigned int D, unsigned int N, long dims[N], long (*strs[D])[N])
{
merge_dims(D, N, dims, strs);
unsigned int ND = remove_empty_dims(D, N, dims, strs);
if (0 == ND) { // atleast return a single dimension
dims[0] = 1;
for (unsigned int j = 0; j < D; j++)
(*strs[j])[0] = 0;
ND = 1;
}
return ND;
}
unsigned int optimize_dims(unsigned int D, unsigned int N, long dims[N], long (*strs[D])[N])
{
unsigned int ND = simplify_dims(D, N, dims, strs);
debug_print_dims(DP_DEBUG4, ND, dims);
float blocking[N];
// actually those are not the blocking factors
// as used below but relative to fast memory
//demmel_factors(D, ND, blocking, strs);
UNUSED(demmel_factors);
#if 0
debug_printf(DP_DEBUG4, "DB: ");
for (unsigned int i = 0; i < ND; i++)
debug_printf(DP_DEBUG4, "%f\t", blocking[i]);
debug_printf(DP_DEBUG4, "\n");
#endif
#if 1
for (unsigned int i = 0; i < ND; i++)
blocking[i] = 0.5;
// blocking[i] = 1.;
#endif
// try to split dimensions according to blocking factors
// use space up to N
bool split = false;
do {
if (N == ND)
break;
split = split_dims(D, ND, dims, strs, blocking);
if (split)
ND++;
} while(split);
// printf("Split %c :", split ? 'y' : 'n');
// print_dims(ND, dims);
long max_strides[ND];
for (unsigned int i = 0; i < ND; i++) {
max_strides[i] = 0;
for (unsigned int j = 0; j < D; j++)
max_strides[i] = MAX(max_strides[i], (*strs[j])[i]);
}
int ord[ND];
compute_permutation(ND, ord, max_strides);
// for (unsigned int i = 0; i < ND; i++)
// printf("%d: %ld %d\n", i, max_strides[i], ord[i]);
#if 1
for (unsigned int j = 0; j < D; j++)
reorder_long(ND, ord, *strs[j]);
reorder_long(ND, ord, dims);
#endif
#if 0
printf("opt dims\n");
print_dims(ND, dims);
if (D > 0)
print_dims(ND, *strs[0]);
if (D > 1)
print_dims(ND, *strs[1]);
if (D > 2)
print_dims(ND, *strs[2]);
#endif
return ND;
}
unsigned int optimize_dims_gpu(unsigned int D, unsigned int N, long dims[N], long (*strs[D])[N])
{
unsigned int ND = simplify_dims(D, N, dims, strs);
debug_print_dims(DP_DEBUG4, ND, dims);
long max_strides[ND];
for (unsigned int i = 0; i < ND; i++) {
max_strides[i] = 0;
for (unsigned int j = 0; j < D; j++)
max_strides[i] = MAX(max_strides[i], (*strs[j])[i]);
}
int ord[ND];
compute_permutation(ND, ord, max_strides);
#if 1
for (unsigned int j = 0; j < D; j++)
reorder_long(ND, ord, *strs[j]);
reorder_long(ND, ord, dims);
#endif
return ND;
}
/**
* compute minimal dimension of largest contiguous block(s)
*
*/
unsigned int min_blockdim(unsigned int D, unsigned int N, const long dims[N], long (*strs[D])[N], size_t size[D])
{
unsigned int mbd = N;
for (unsigned int i = 0; i < D; i++)
mbd = MIN(mbd, md_calc_blockdim(N, dims, *strs[i], size[i]));
return mbd;
}
static void compute_enclosures(unsigned int N, bool matrix[N][N], const long dims[N], const long strides[N])
{
long ext[N];
for (unsigned int i = 0; i < N; i++)
ext[i] = dims[i] * labs(strides[i]);
for (unsigned int i = 0; i < N; i++)
for (unsigned int j = 0; j < N; j++)
matrix[i][j] = (ext[i] <= labs(strides[j]));
}
/**
* compute set of parallelizable dimensions
*
*/
static unsigned long parallelizable(unsigned int D, unsigned int io, unsigned int N, const long dims[N], long (*strs[D])[N], size_t size[D])
{
// we assume no input / output overlap
// (i.e. inputs which are also outputs have to be marked as output)
// a dimension is parallelizable if all output operations
// for that dimension are independent
// for all output operations:
// check - all other dimensions have strides greater or equal
// the extend of this dimension or have an extend smaller or
// equal the stride of this dimension
// no overlap: [222]
// [111111111111]
// [333333333]
// overlap: [222]
// [1111111111111111]
// [333333333]
unsigned long flags = (1 << N) - 1;
for (unsigned int d = 0; d < D; d++) {
if (MD_IS_SET(io, d)) {
bool m[N][N];
compute_enclosures(N, m, dims, *strs[d]);
// print_dims(N, dims);
// print_dims(N, *strs[d]);
for (unsigned int i = 0; i < N; i++) {
unsigned int a = 0;
for (unsigned int j = 0; j < N; j++)
if (m[i][j] || m[j][i])
a++;
// printf("%d %d %d\n", d, i, a);
if ((a != N - 1) || ((size_t)labs((*strs[d])[i]) < size[d]))
flags = MD_CLEAR(flags, i);
}
}
}
return flags;
}
extern long num_chunk_size;
long num_chunk_size = 32 * 256;
/**
* compute set of dimensions to parallelize
*
*/
unsigned long dims_parallel(unsigned int D, unsigned int io, unsigned int N, const long dims[N], long (*strs[D])[N], size_t size[D])
{
unsigned long flags = parallelizable(D, io, N, dims, strs, size);
unsigned int i = N;
unsigned int max_size = 0;
for (unsigned int i = 0; i < D; i++)
max_size = MAX(max_size, size[i]);
long reps = md_calc_size(N, dims) * max_size;
unsigned long oflags = 0;
while (i-- > 0) {
if (MD_IS_SET(flags, i)) {
reps /= dims[i];
if (reps < num_chunk_size)
break;
oflags = MD_SET(oflags, i);
}
}
return oflags;
}
#ifdef USE_CUDA
static bool use_gpu(int p, void* ptr[p])
{
bool gpu = false;
for (int i = 0; i < p; i++)
gpu |= cuda_ondevice(ptr[i]);
for (int i = 0; i < p; i++)
gpu &= cuda_accessible(ptr[i]);
#if 0
// FIXME: fails for copy
if (!gpu) {
for (int i = 0; i < p; i++)
assert(!cuda_ondevice(ptr[i]));
}
#endif
return gpu;
}
static bool one_on_gpu(int p, void* ptr[p])
{
bool gpu = false;
for (int i = 0; i < p; i++)
gpu |= cuda_ondevice(ptr[i]);
return gpu;
}
#endif
extern double md_flp_total_time;
double md_flp_total_time = 0.;
// automatic parallelization
extern bool num_auto_parallelize;
bool num_auto_parallelize = true;
/**
* Optimized n-op.
*
* @param N number of arguments
' @param io bitmask indicating input/output
* @param D number of dimensions
* @param dim dimensions
* @param nstr strides for arguments and dimensions
* @param nptr argument pointers
* @param sizes size of data for each argument, e.g. complex float
* @param too n-op function
* @param data_ptr pointer to additional data used by too
*/
void optimized_nop(unsigned int N, unsigned int io, unsigned int D, const long dim[D], const long (*nstr[N])[D], void* const nptr[N], size_t sizes[N], md_nary_opt_fun_t too)
{
assert(N > 0);
if (0 == D) {
long dim1[1] = { 1 };
long tstrs[N][1];
long (*nstr1[N])[1];
for (unsigned int i = 0; i < N; i++) {
tstrs[i][0] = 0;
nstr1[i] = &tstrs[i];
}
optimized_nop(N, io, 1, dim1, (void*)nstr1, nptr, sizes, too);
return;
}
long tdims[D];
md_copy_dims(D, tdims, dim);
long tstrs[N][D];
long (*nstr1[N])[D];
void* nptr1[N];
for (unsigned int i = 0; i < N; i++) {
md_copy_strides(D, tstrs[i], *nstr[i]);
nstr1[i] = &tstrs[i];
nptr1[i] = nptr[i];
}
#ifdef USE_CUDA
int ND = (use_gpu(N, nptr1) ? optimize_dims_gpu : optimize_dims)(N, D, tdims, nstr1);
#else
int ND = optimize_dims(N, D, tdims, nstr1);
#endif
#if 1
unsigned long cnst_flags = 0;
bool cnst_ok = true;
for (unsigned int i = 0; i < N; i++) {
if (0 == tstrs[i][0]) {
if (MD_IS_SET(io, i)) {
cnst_ok = false;
break;
}
cnst_flags = MD_SET(cnst_flags, i);
for (int d = 0; d < ND; d++)
cnst_ok &= (0 == tstrs[i][d]);
}
}
long cnst_size = 1;
int cnst_dims = 0;
for (; cnst_dims < ND; cnst_dims++) {
cnst_size *= tdims[cnst_dims];
for (unsigned int i = 0; i < N; i++) {
if (cnst_size * sizes[i] > 4096) { // buffer too big
cnst_size /= tdims[cnst_dims];
cnst_dims--;
goto out;
}
}
}
out:
if ((0 == cnst_size) || (1 > cnst_dims))
cnst_ok = false;
#ifdef USE_CUDA
if (use_gpu(N, nptr1)) // not implemented yet
cnst_ok = false;
#endif
if (cnst_ok) {
debug_printf(DP_DEBUG4, "MD constant buffer Io: %d Cnst: %d Size %ld.\n", io, cnst_flags, cnst_size);
for (unsigned int i = 0; i < N; i++) {
if (MD_IS_SET(cnst_flags, i)) {
for (int d = 0; d < cnst_dims; d++)
tstrs[i][d] = ((0 < d) ? tdims[d - 1] : 1) * sizes[i];
void* np = alloca(cnst_size * sizes[i]);
for (long n = 0; n < cnst_size; n++)
memcpy(np + n * sizes[i], nptr[i], sizes[i]);
nptr1[i] = np;
}
}
}
#endif
int skip = min_blockdim(N, ND, tdims, nstr1, sizes);
unsigned long flags = 0;
debug_printf(DP_DEBUG4, "MD-Fun. Io: %d Input: ", io);
debug_print_dims(DP_DEBUG4, D, dim);
#ifdef USE_CUDA
if (num_auto_parallelize && !use_gpu(N, nptr1) && !one_on_gpu(N, nptr1)) {
#else
if (num_auto_parallelize) {
#endif
flags = dims_parallel(N, io, ND, tdims, nstr1, sizes);
while ((0 != flags) && (ffs(flags) <= skip))
skip--;
flags = flags >> skip;
}
const long* nstr2[N];
for (unsigned int i = 0; i < N; i++)
nstr2[i] = *nstr1[i] + skip;
#ifdef USE_CUDA
debug_printf(DP_DEBUG4, "This is a %s call\n.", use_gpu(N, nptr1) ? "gpu" : "cpu");
__block struct nary_opt_data_s data = { md_calc_size(skip, tdims), use_gpu(N, nptr1) ? &gpu_ops : &cpu_ops };
#else
__block struct nary_opt_data_s data = { md_calc_size(skip, tdims), &cpu_ops };
#endif
debug_printf(DP_DEBUG4, "Vec: %d (%ld) Opt.: ", skip, data.size);
debug_print_dims(DP_DEBUG4, ND, tdims);
NESTED(void, nary_opt, (void* ptr[]))
{
NESTED_CALL(too, (&data, ptr));
};
double start = timestamp();
md_parallel_nary(N, ND - skip, tdims + skip, flags, nstr2, nptr1, nary_opt);
double end = timestamp();
#pragma omp critical
md_flp_total_time += end - start;
debug_printf(DP_DEBUG4, "MD time: %f\n", end - start);
}
|
GB_unop__bnot_int8_int8.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_atomics.h"
#include "GB_unop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB (_unop_apply__bnot_int8_int8)
// op(A') function: GB (_unop_tran__bnot_int8_int8)
// C type: int8_t
// A type: int8_t
// cast: int8_t cij = aij
// unaryop: cij = ~(aij)
#define GB_ATYPE \
int8_t
#define GB_CTYPE \
int8_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
int8_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = ~(x) ;
// casting
#define GB_CAST(z, aij) \
int8_t z = aij ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
int8_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
int8_t z = aij ; \
Cx [pC] = ~(z) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_BNOT || GxB_NO_INT8)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_apply__bnot_int8_int8)
(
int8_t *Cx, // Cx and Ax may be aliased
const int8_t *Ax,
const int8_t *restrict Ab, // A->b if A is bitmap
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
if (Ab == NULL)
{
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
int8_t aij = Ax [p] ;
int8_t z = aij ;
Cx [p] = ~(z) ;
}
}
else
{
// bitmap case, no transpose; A->b already memcpy'd into C->b
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!Ab [p]) continue ;
int8_t aij = Ax [p] ;
int8_t z = aij ;
Cx [p] = ~(z) ;
}
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_tran__bnot_int8_int8)
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
boson_basis_core.h | #ifndef _BOSON_BASIS_CORE_H
#define _BOSON_BASIS_CORE_H
#include <complex>
#include <cmath>
#include "general_basis_core.h"
#include "numpy/ndarraytypes.h"
#include "openmp.h"
namespace basis_general {
template<class I>
I inline boson_map_bits(I s,const int map[],const I M[],const int sps,const int N){
I ss = 0;
for(int i=N-1;i>=0;--i){
int j = map[i];
ss += ( j<0 ? (sps-(int)(s%sps)-1)*M[j+N] : (int)(s%sps)*M[N-j-1] );
s /= sps;
}
return ss;
}
template<class I,class P=signed char>
class boson_basis_core : public general_basis_core<I,P>
{
public:
std::vector<I> M;
const int sps;
boson_basis_core(const int _N, const int _sps) : \
general_basis_core<I,P>::general_basis_core(_N), sps(_sps) {
M.resize(_N);
M[0] = (I)1;
for(int i=1;i<_N;i++){
M[i] = (M[i-1] * (I)_sps);
}
}
boson_basis_core(const int _N, const int _sps,const int _nt, \
const int _maps[], const int _pers[], const int _qs[]) : \
general_basis_core<I,P>::general_basis_core(_N,_nt,_maps,_pers,_qs), sps(_sps) {
M.resize(_N);
M[0] = (I)1;
for(int i=1;i<_N;i++){
M[i] = (M[i-1] * (I)_sps);
}
}
~boson_basis_core() {}
I map_state(I s,int n_map,P &sign){
if(general_basis_core<I,P>::nt<=0){
return s;
}
const int n = general_basis_core<I,P>::N;
return boson_map_bits(s,&general_basis_core<I,P>::maps[n_map*n],&M[0],sps,n);
}
void map_state(I s[],npy_intp MM,int n_map,P sign[]){
if(general_basis_core<I,P>::nt<=0){
return;
}
const int n = general_basis_core<I,P>::N;
const int * map = &general_basis_core<I,P>::maps[n_map*n];
#pragma omp for schedule(static)
for(npy_intp i=0;i<MM;i++){
s[i] = boson_map_bits(s[i],map,&M[0],sps,n);
}
}
std::vector<int> count_particles(const I r){
std::vector<int> v(1);
int n = 0;
I s = r;
for(int i=0;i<general_basis_core<I,P>::N;i++){
n += (int)(s%sps);
s /= sps;
}
v[0] = n;
return v;
}
I inline next_state_pcon(const I r,const I nns){
if(r == 0){
return r;
}
I s = r;
int n=0;
for(int i=0;i<general_basis_core<I,P>::N-1;i++){
int b1 = (int)((s/M[i])%sps);
if(b1>0){
n += b1;
int b2 = (int)((s/M[i+1])%sps);
if(b2<(sps-1)){
n -= 1;
s -= M[i];
s += M[i+1];
if(n>0){
int l = n/(sps-1);
int n_left = n%(sps-1);
for(int j=0;j<(i+1);j++){
s -= (int)((s/M[j])%sps) * M[j];
if(j<l){
s += (sps-1)*M[j];
}
else if(j == l){
s += n_left*M[j];
}
}
}
break;
}
}
}
return s;
}
int op(I &r,std::complex<double> &me,const int n_op,const char opstr[],const int indx[]){
const I s = r;
double me_offdiag=1;
double me_diag=1;
double S = (sps-1.0)/2.0;
for(int j=n_op-1;j>-1;j--){
int ind = general_basis_core<I,P>::N-indx[j]-1;
int occ = (int)((r/M[ind])%sps);
I b = M[ind];
char op = opstr[j];
switch(op){
case 'z':
me_diag *= (occ-S);
case 'n':
me_diag *= occ;
break;
case '+':
me_offdiag *= (occ+1)%sps;
r += ((occ+1)<sps?b:0);
break;
case '-':
me_offdiag *= occ;
r -= (occ>0?b:0);
break;
case 'I':
break;
default:
return -1;
}
if(std::abs(me_diag*me_offdiag)==0){
r = s;
break;
}
}
me *= me_diag*std::sqrt(me_offdiag);
return 0;
}
};
}
#endif
|
hhalignment-C.h | /* -*- mode: c; tab-width: 4; c-basic-offset: 4; indent-tabs-mode: nil -*- */
/*********************************************************************
* Clustal Omega - Multiple sequence alignment
*
* Copyright (C) 2010 University College Dublin
*
* Clustal-Omega is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License as
* published by the Free Software Foundation; either version 2 of the
* License, or (at your option) any later version.
*
* This file is part of Clustal-Omega.
*
********************************************************************/
/*
* RCS $Id: hhalignment-C.h 316 2016-12-16 16:14:39Z fabian $
*/
/*
* Changelog: Michael Remmert made changes to hhalign stand-alone code
* FS implemented some of the changes on 2010-10-28 -> MR1
*
* Note: MR seems to have changed all [aijk]++ to ++[aijk],
* FS did not do that on 2010-10-28
*/
// hhalignment.C
//////////////////////////////////////////////////////////////////////////////
//// Class Alignment
//////////////////////////////////////////////////////////////////////////////
// hhalignment.C
#ifndef MAIN
#define MAIN
#include <iostream> // cin, cout, cerr
#include <fstream> // ofstream, ifstream
#include <stdio.h> // printf
using std::cout;
using std::cerr;
using std::endl;
using std::ios;
using std::ifstream;
using std::ofstream;
#include <stdlib.h> // exit
#include <string> // strcmp, strstr
#include <math.h> // sqrt, pow
#include <limits.h> // INT_MIN
#include <float.h> // FLT_MIN
#include <time.h> // clock
#include <ctype.h> // islower, isdigit etc
#include "util-C.h" // imax, fmax, iround, iceil, ifloor, strint, strscn, strcut, substr, uprstr, uprchr, Basename etc.
#include "list.h" // list data structure
#include "hash.h" // hash data structure
#include "hhdecl-C.h"
#include "hhutil-C.h" // imax, fmax, iround, iceil, ifloor, strint, strscn, strcut, substr, uprstr, uprchr, Basename etc.
#include "hhhmm.h"
#endif
#ifdef HAVE_CONFIG_H
#include "config.h"
#endif
//#include "new_new.h" /* memory tracking */
enum {KEEP_NOT = 0, KEEP_CONDITIONALLY, KEEP_ALWAYS};
//////////////////////////////////////////////////////////////////////////////
// Class Alignment
//////////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////////
// Object constructor
//////////////////////////////////////////////////////////////////////////////
Alignment::Alignment(int maxseq, int maxres)
{
//printf(">>>>>>>>%s:%s:%d: maxseq=%d, maxres=%d\n", __FUNCTION__, __FILE__, __LINE__, maxseq, maxres); /* (FS) */
longname = new(char[DESCLEN]);
sname = new char*[maxseq+2]; /* MR1 */
seq = new char*[maxseq+2]; /* MR1 */
l = new int[maxres];
X = new char*[maxseq+2]; /* MR1 */
I = new short unsigned int*[maxseq+2]; /* MR1 */
keep = new char[maxseq+2]; /* MR1 */
display = new char[maxseq+2]; /* MR1 */
wg = new float[maxseq+2]; /* MR1 */
nseqs = new int[maxres+2]; /* MR1 */
N_in=L=0;
nres=NULL; // number of residues per sequence k
first=NULL; // first residue in sequence k
last=NULL; // last residue in sequence k
ksort=NULL; // sequence indices sorted by descending nres[k]
name[0]='\0'; // no name defined yet
longname[0]='\0'; // no name defined yet
fam[0]='\0'; // no name defined yet
file[0]='\0'; // no name defined yet
readCommentLine = '0'; /* MR1 */
}
//////////////////////////////////////////////////////////////////////////////
// Object destructor
//////////////////////////////////////////////////////////////////////////////
Alignment::~Alignment()
{
delete[] longname; longname = NULL;
for(int k=0; k<N_in; k++)
{
delete[] sname[k]; sname[k] = NULL;
delete[] seq[k]; seq[k] = NULL;
delete[] X[k]; X[k] = NULL;
delete[] I[k]; I[k] = NULL;
}
delete[] sname; sname = NULL;
delete[] seq; seq = NULL;
delete[] X; X = NULL;
delete[] I; I = NULL;
delete[] l; l = NULL;
delete[] keep; keep = NULL;
delete[] display; display = NULL;
delete[] wg; wg = NULL;
delete[] nseqs; nseqs = NULL;
delete[] nres; nres = NULL;
delete[] first; first = NULL;
delete[] last; last = NULL;
delete[] ksort; ksort = NULL;
}
/**
* @brief Reads in an alignment from file into matrix seq[k][l] as ASCII
*/
void
Alignment::Read(FILE* inf, char infile[], char* firstline)
{
int l; // Postion in alignment incl. gaps (first=1)
int h; // Position in input line (first=0)
int k; // Index of sequence being read currently (first=0)
char line[LINELEN]=""; // input line
//char cur_seq[MAXCOL]; // Sequence currently read in
char *cur_seq=new char[par.maxColCnt];
char* cur_name; // Sequence currently read in
int linenr=0; // current line number in input file
char skip_sequence=0;
RemoveExtension(file,infile); //copy rootname (w/o path) of infile into file variable of class object
kss_dssp=ksa_dssp=kss_pred=kss_conf=kfirst=-1;
n_display=0;
N_in=0;
N_filtered=0;
N_ss=0;
cur_seq[0]=' '; // overwrite '\0' character at beginning to be able to do strcpy(*,cur_seq)
l=1; k=-1;
// Does firstline already contain first line of file?
if (firstline!= NULL) strcpy(line,firstline);
/////////////////////////////////////////////////////////////////////////
// Read infile line by line
/* FIXME: not safe to use MAXSEQ, however, don't think we ever get here (FS) */
while(firstline || (fgetline(line,LINELEN,inf) && (k<MAXSEQ))) /* FIXME: FS introduced () around &&, precedence! MR1 */
{
linenr++;
firstline=NULL;
if (line[0]=='>') //line contains sequence name
{
if (k>=MAXSEQ-1)
{
if (v>=1 && k>=MAXSEQ)
cerr<<endl<<"WARNING: maximum number "<<MAXSEQ<<" of sequences exceded in file "<<infile<<"\n";
break;
}
cur_name=line+1; //beginning of current sequence name
if (k>=0) //if this is at least the second name line
{
if (strlen(cur_seq)==0)
{
cerr<<endl<<"Error: sequence "<<sname[k]<<" contains no residues."<<endl;
exit(1);
}
// Create space for residues and paste new sequence in
seq[k]=new char[strlen(cur_seq)+2];
if (!seq[k]) MemoryError("array for input sequences");
X[k]=new char[strlen(cur_seq)+2];
if (!X[k]) MemoryError("array for input sequences");
I[k]=new short unsigned int[strlen(cur_seq)+2];
if (!I[k]) MemoryError("array for input sequences");
strcpy(seq[k],cur_seq);
}
skip_sequence=0;
k++;
l=1; //position in current sequence (first=1)
// display[k]= 0: do not show in Q-T alignments 1: show if not filtered out later 2: show in any case (do not filter out)
// keep[k] = 0: do not include in profile 1: include if not filtered out later 2: include in any case (do not filter out)
/* {KEEP_NOT=0, KEEP_CONDITIONALLY=1, KEEP_ALWAYS=2} */
if (line[1]=='@') cur_name++; //skip @-character in name
if (!strncmp(line,">ss_dssp",8)) {
if (kss_dssp<0) {display[k]=2; n_display++; keep[k]=KEEP_NOT; kss_dssp=k; N_ss++;} else {skip_sequence=1; k--; continue;}
}
else if (!strncmp(line,">sa_dssp",8)) {
if (ksa_dssp<0) {display[k]=KEEP_ALWAYS; n_display++; keep[k]=KEEP_NOT; ksa_dssp=k; N_ss++;} else {skip_sequence=1; k--; continue;}
}
else if (!strncmp(line,">ss_pred",8)) {
if (kss_pred<0) {display[k]=KEEP_ALWAYS; n_display++; keep[k]=KEEP_NOT; kss_pred=k; N_ss++;} else {skip_sequence=1; k--; continue;}
}
else if (!strncmp(line,">ss_conf",8)) {
if (kss_conf<0) {display[k]=KEEP_ALWAYS; n_display++; keep[k]=KEEP_NOT; kss_conf=k; N_ss++;} else {skip_sequence=1; k--; continue;}
}
else if (!strncmp(line,">ss_",4) || !strncmp(line,">sa_",4)) {
display[k]=KEEP_ALWAYS; n_display++; keep[k]=KEEP_NOT; N_ss++;
}
else if (!strncmp(line,">aa_",4)) { // ignore sequences beginning with ">aa_"
skip_sequence=1; k--; continue;
}
//store first real seq
else if (kfirst<0)
{
char word[NAMELEN];
strwrd(word,line); // Copies first word in ptr to str
if (strstr(word,"_consensus"))
{display[k]=2; keep[k]=0; n_display++; kfirst=k;} /* MR1 */
else
{display[k]=keep[k]=KEEP_ALWAYS; n_display++; kfirst=k;}
}
//store all sequences
else if (par.mark==0) {display[k]=keep[k]=KEEP_CONDITIONALLY; n_display++;}
//store sequences up to nseqdis
else if (line[1]=='@'&& n_display-N_ss<par.nseqdis) {display[k]=keep[k]=KEEP_ALWAYS; n_display++;}
else {display[k]=KEEP_NOT; keep[k]=KEEP_CONDITIONALLY;}
// store sequence name
if (v>=4) printf("Reading seq %-16.16s k=%3i n_displ=%3i display[k]=%i keep[k]=%i\n",cur_name,k,n_display,display[k],keep[k]);
sname[k] = new char[strlen(cur_name)+1];
if (!sname[k]) {MemoryError("array for sequence names");}
strcpy(sname[k],cur_name);
} // end if(line contains sequence name)
else if (line[0]=='#') // Commentary line?
{
// #PF01367.9 5_3_exonuc: 5'-3' exonuclease, C-terminal SAM fold; PDB 1taq, 1bgx (T:271-174), 1taq (271-174)
if (name[0]) continue; // if already name defined: skip commentary line
char *ptr1, *ptr2;
ptr1=strscn_(line+1); // set ptr1 to first non-whitespace character after '#' -> AC number
strncpy(longname,ptr1,DESCLEN-1); // copy whole commentary line after '# ' into longname
longname[DESCLEN-1]='\0';
strtr(longname,""," ");
ptr2=strcut_(ptr1); // cut after AC number and set ptr2 to first non-whitespace character after AC number
// strcpy(fam,ptr1); // copy AC number to fam
// if (!strncmp(fam,"PF",2)) strcut_(fam,'.'); // if PFAM identifier contains '.' cut it off
// strcut_(ptr2); // cut after first word ...
strcpy(name,ptr1); // ... and copy first word into name
readCommentLine = '1'; /* MR1 */
}
//line contains sequence residues or SS information and does not belong to a >aa_ sequence
else if (!skip_sequence)
{
if (v>=4) cout<<line<<"\n"; //DEBUG
if (k==-1 && v)
{
cerr<<endl<<"WARNING: No sequence name preceding following line in "<<infile<<":\n\'"<<line<<"\'\n";
continue;
}
h=0; //counts characters in current line
// Check whether all characters are correct; store into cur_seq
if (keep[k] || (k == kfirst) ) // normal line containing residues /* MR1 */
{
while (h<LINELEN && line[h]>'\0' && l</*MAXCOL*/par.maxColCnt-1)
{
if (aa2i(line[h])>=0) // ignore white-space characters ' ', \t and \n (aa2i()==-1)
{cur_seq[l]=line[h]; l++;}
else if (aa2i(line[h])==-2 && v)
cerr<<endl<<"WARNING: invalid symbol \'"<<line[h]<<"\' at pos. "<<h<<" in line "<<linenr<<" of "<<infile<<"\n";
h++;
}
}
else if (k==kss_dssp) // lines with dssp secondary structure states (. - H E C S T G B)
{
while (h<LINELEN && line[h]>'\0' && l</*MAXCOL*/par.maxColCnt-1)
{
if (ss2i(line[h])>=0 && ss2i(line[h])<=7)
{cur_seq[l]=ss2ss(line[h]); l++;}
else if (v)
cerr<<endl<<"WARNING: invalid symbol \'"<<line[h]<<"\' at pos. "<<h<<" in line "<<linenr<<" of "<<infile<<"\n";
h++;
}
}
else if (k==ksa_dssp) // lines with dssp solvent accessibility states (. - ???)
{
while (h<LINELEN && line[h]>'\0' && l</*MAXCOL*/par.maxColCnt-1)
{
if (sa2i(line[h])>=0)
cur_seq[l++]=line[h];
else if (v)
cerr<<endl<<"WARNING: invalid symbol \'"<<line[h]<<"\' at pos. "<<h<<" in line "<<linenr<<" of "<<infile<<"\n";
h++;
}
}
else if (k==kss_pred) // lines with predicted secondary structure (. - H E C)
{
while (h<LINELEN && line[h]>'\0' && l</*MAXCOL*/par.maxColCnt-1)
{
if (ss2i(line[h])>=0 && ss2i(line[h])<=3)
{cur_seq[l]=ss2ss(line[h]); l++;}
else if (v)
cerr<<endl<<"WARNING: invalid symbol \'"<<line[h]<<"\' at pos. "<<h<<" in line "<<linenr<<" of "<<infile<<"\n";
h++;
}
}
else if (k==kss_conf) // lines with confidence values should contain only 0-9, '-', or '.'
{
while (h<LINELEN && line[h]>'\0' && l</*MAXCOL*/par.maxColCnt-1)
{
if (line[h]=='-' || line[h]=='.' || (line[h]>='0' && line[h]<='9'))
{cur_seq[l]=line[h]; l++;}
else if (v)
cerr<<endl<<"WARNING: invalid symbol \'"<<line[h]<<"\' at pos. "<<l<<" in line "<<linenr<<" of "<<infile<<"\n";
h++;
}
}
else if (display[k]) // other lines such as >sa_pred etc
{
while (h<LINELEN && line[h]>'\0' && l</*MAXCOL*/par.maxColCnt-1)
{
if (line[h]=='-' || line[h]=='.' || (line[h]>='0' && line[h]<='9') || (line[h]>='A' && line[h]<='B'))
{cur_seq[l]=line[h]; l++;}
else if (v)
cerr<<endl<<"WARNING: invalid symbol \'"<<line[h]<<"\' at pos. "<<l<<" in line "<<linenr<<" of "<<infile<<"\n";
h++;
}
}
if (v && l>=/*MAXCOL*/par.maxColCnt-1)
{
cerr<<endl<<"WARNING: maximum number of residues "<</*MAXCOL*/par.maxColCnt-2<<" exceded in sequence "<<sname[k]<<"\n";
skip_sequence=1;
}
cur_seq[l]='\0'; //Ensure that cur_seq ends with a '\0' character
} //end else
}
/////////////////////////////////////////////////////////////////////////
if (k>=0) //if at least one sequence was read in
{
seq[k]=new char[strlen(cur_seq)+2];
if (!seq[k]) MemoryError("array for input sequences");
X[k]=new char[strlen(cur_seq)+2];
if (!X[k]) MemoryError("array for input sequences");
I[k]=new short unsigned int[strlen(cur_seq)+2];
if (!I[k]) MemoryError("array for input sequences");
strcpy(seq[k],cur_seq);
}
else
{cerr<<endl<<"Error: no sequences found in file "<<infile<<"\n"; exit(1);}
N_in = k+1;
// Set name, longname, fam
if (!*name) // longname, name and family were not set by '#...' line yet -> extract from first sequence
{
char* ptr;
// strtr(sname[kfirst],"~"," "); // 'transpose': replaces the tilde with a blanc everywhere in sname[kfirst]
strncpy(longname,sname[kfirst],DESCLEN-1); // longname is name of first sequence
longname[DESCLEN-1]='\0';
strncpy(name,sname[kfirst],NAMELEN-1); // Shortname is first word of longname...
name[NAMELEN-1]='\0';
ptr = strcut(name); // ...until first white-space character
if (ptr && islower(ptr[0]) && ptr[1]=='.' && isdigit(ptr[2])) //Scop family code present as second word?
{
lwrstr(name); // Transform upper case to lower case
strcut(ptr); // Non-white-space characters until next white-space character..
strcpy(fam,ptr); // ...are the SCOP familiy code
}
else if (name[0]=='P' && name[1]=='F' && isdigit(name[2]) && isdigit(name[3]) ) //Pfam code
{
strcpy(fam,name); // set family name = Pfam code
}
}
delete[] cur_seq; cur_seq = NULL;
// Checking for warning messages
if (v==0) return;
if (v>=2) cout<<"Read "<<infile<<" with "<<N_in<<" sequences\n";
if (v>=3) cout<<"Query sequence for alignment has number "<<kfirst<<" (0 is first)\n";
return;
}
/*
* At this point GetSeqsFromHMM() slots in, however,
* only needed in hhbliys.C, so will skip it for moment, MR1
*/
/////////////////////////////////////////////////////////////////////////////
/**
* @brief Convert ASCII in seq[k][l] to int (0-20) in X[k][i],
* throw out all insert states, record their number in I[k][i]
* and store sequences to be displayed in seq[k] */
/////////////////////////////////////////////////////////////////////////////
void
Alignment::Compress(const char infile[])
{
int i; // Index for match state (first=1)
int l; // Postion in alignment incl. gaps (first=1)
int k; // Index for sequences (first=0)
int a; // amino acid index
char c;
int unequal_lengths=0; /* k: seq k doesn't have same number
of match states as seq 0 => WARNING */
/* points to next character in seq[k] to be written */
/*static short unsigned int h[MAXSEQ];*/
/*short*/ unsigned int *h = NULL; /* short may lead to overflow for long alignments, FS, r235 -> r236 */
h = new /*short*/ unsigned int[N_in+2]; /* short -> overflow, FS, r235 -> r236 */
float *percent_gaps = NULL; /* FS, 2010-Nov */
char *match_state = NULL; /* FS, 2010-Nov */
// Initialize
for (k=0;k<N_in; k++)
{I[k][0]=0;}
if (v>=3)
{
if (par.M==1)
cout<<"Using match state assignment by capital letters (a2m format)\n";
else if (par.M==2) cout<<"Using percentage-rule match state assignment\n";
else if (par.M==3) cout<<"Using residues of first sequence as match states\n";
}
// Create matrices X and I with amino acids represented by integer numbers
switch(par.M)
{
/////////////////////////////////////////////////////////////////////////
/* a2m/a3m format: match states capital case,
inserts lower case, delete states '-', inserted gaps '.'
The confidence values for ss prediction are interpreted as follows:
0-9:match states(!) '-' :match state '.':insert */
case 1:
default:
// Warn if alignment is ment to be -M first or -M NN instead of A2M/A3M
if (v>=2 && strchr(seq[kfirst],'-') ) // Seed/query sequence contains a gap ...
{
for (k=1; k<N_in; k++)
if (strpbrk(seq[k],"abcdefghiklmnpqrstuvwxyz.")) break;
if (k==N_in) // ... but alignment contains no lower case residue
printf("WARNING: input alignment %s looks like aligned FASTA instead of A2M/A3M format. Consider using '-M first' or '-M 50'\n",infile);
}
// Remove '.' characters from seq[k]
for(k=0; k<N_in; k++)
{
char* ptrS=seq[k]; // pointer to source: character in seq[k]
char* ptrD=seq[k]; // pointer to destination: seq[k]
while(1) // omit '.' symbols
{
if (*ptrS!='.') {*ptrD=*ptrS; ptrD++;} //leave out '.' symbols
if (!*ptrS) break;
ptrS++;
}
}
L=/*MAXRES*/par.maxResLen-2; // needed because L=imin(L,i)
for (k=0; k<N_in; k++)
{
i=1; l=1; // start at i=1, not i=0!
if (keep[k]) //skip >ss_dssp, >ss_pred, >ss_conf, >aa_... sequences
{
while((c=seq[k][l++])) // assign residue to c at same time
{
if (c>='a' && c<='z') I[k][i-1]++;//insert state = lower case character
else if (c!='.') //match state = upper case character
{
X[k][i]=aa2i(c);
I[k][i]=0;
i++;
}
}
}
else if (k==kss_dssp || k==kss_pred) // does alignment contain sequence of secondary structure states?
{
while((c=seq[k][l++])) // assign residue to c at same time
if (c!='.' && !(c>='a' && c<='z')) X[k][i++]=ss2i(c); //match state = upper case character
}
else if (k==ksa_dssp) // does alignment contain sequence of prediction confidence values?
{
while((c=seq[k][l++])) // assign residue to c at same time
if (c!='.' && !(c>='a' && c<='z')) X[k][i++]=sa2i(c); //match state = upper case character
}
else if (k==kss_conf) // does alignment contain sequence of prediction confidence values?
{
while((c=seq[k][l++])) // assign residue to c at same time
if (c!='.') X[k][i++]=cf2i(c); //match state = 0-9 or '-'
}
else if (k==kfirst) // does alignment contain sequence of prediction confidence values?
{
while((c=seq[k][l++])) // assign residue to c at same time
if (c!='.')
{
X[k][i]=aa2i(c);
I[k][i]=0;
++i;
}
}
else continue;
i--;
if (L!=i && L!=/*MAXRES*/par.maxResLen-2 && !unequal_lengths) unequal_lengths=k; //sequences have different lengths
L=imin(L,i);
} // end for (k)
if (unequal_lengths) break;
//Replace GAP with ENDGAP for all end gaps /* MR1 */
for (k=0; k<N_in; ++k)
{
if (!keep[k]) continue;
for (i=1; i<=L && X[k][i]==GAP; i++) X[k][i]=ENDGAP; /* MR1: NOTE i++ <- ++i */
for (i=L; i>=1 && X[k][i]==GAP; i--) X[k][i]=ENDGAP; /* MR1 */
}
for (i=1; i<=L; i++) this->l[i]=i; //assign column indices to match states
if (L<=0)
{
cout<<"\nError: Alignment in "<<infile<<" contains no match states. Consider using -M first or -M <int> option"<<endl;
exit(1);
}
if (L==/*MAXRES*/par.maxResLen-2 && v>=2)
{
printf("WARNING: Number of match columns too large. Only first %i match columns will be kept!\n",L);
break;
}
if (v>=2) cout<<"Alignment in "<<infile<<" contains "<<L<<" match states\n";
break;
/////////////////////////////////////////////////////////////////////////
// gap-rule assignment of match states
case 2:
int nl[NAA+2]; //nl[a] = number of seq's with amino acid a at position l
/* Note: allocating statically is fine most of the time
but when the sequences/profiles get really long
we might run out of memory, so must really do it dynamically.
had to move declaration of float *percent_gaps out of switch()
*/
//float percent_gaps[MAXCOL]; //percentage of gaps in column k (with weighted sequences)
percent_gaps = new float[par.maxColCnt];
//determine number of columns L in alignment
L=strlen(seq[kfirst])-1;
// Conversion to integer representation, checking for unequal lengths and initialization
if (nres==NULL) nres=new int[N_in];
#if 0
//#ifdef HAVE_OPENMP
#pragma omp parallel for schedule(static), private(l)
#endif
for (k=0; k<N_in; k++)
{
if (!keep[k]) continue;
int nr=0;
wg[k]=0; nres[k]=0;
for (l=1; l<=L; l++)
{
X[k][l]=aa2i(seq[k][l]);
if (X[k][l]<NAA) nr++;
}
nres[k]=nr;
if (seq[k][L+1]!='\0' && !unequal_lengths) unequal_lengths=k;
}
if (unequal_lengths) break;
// Quick and dirty calculation of the weight per sequence wg[k]
for (l=1; l<=L; l++) // for all positions l in alignment
{
int naa=0; //number of different amino acids
for (a=0; a<20; a++) nl[a]=0;
for (k=0; k<N_in; k++) if (keep[k]) nl[ (int)X[k][l]]++;
for (a=0; a<20; a++) if(nl[a]) naa++;
if (!naa) naa=1; //naa=0 when column consists of only gaps and Xs (=ANY)
#if 0
//#ifdef HAVE_OPENMP
#pragma omp parallel for schedule(static)
#endif
for (k=0; k<N_in; k++)
if (keep[k] && (X[k][l]<20) )
{
//wg[k]+=1.0/float(nl[ (int)X[k][l]]*naa*nres[k]+30.0); /* original version */
wg[k] += 1.0/float(nl[ (int)X[k][l]]*naa*(nres[k]+30.0)); /* MR1 */
// wg[k] += 1.0/float(nl[ (int)X[k][l]]*(nres[k]+30.0)); /* MR1 commented out */
// wg[k] += (naa-1.0)/float(nl[ (int)X[k][l]]*(nres[k]+30.0)); /* MR1 commented out */
}
} /* 1=l<=L*/
//Replace GAP with ENDGAP for all end gaps
for (k=0; k<N_in; ++k)
{
if (!keep[k]) continue;
for (i=1; i<=L && X[k][i]==GAP; i++) X[k][i]=ENDGAP; /* MR1: NOTE i++ <- ++i */
for (i=L; i>=1 && X[k][i]==GAP; i--) X[k][i]=ENDGAP; /* MR1 */
}
// Add up percentage of gaps
#if 0
//#ifdef HAVE_OPENMP
#pragma omp parallel for schedule(static) private(k)
#endif
for (l=1; l<=L; l++)
{
float res=0;
float gap=0;
for (k=0; k< N_in; k++){
if (keep[k]){
if ( X[k][l]<GAP) res+=wg[k]; /* MR1, AA or ANY, changed from <ANY */
else if ( X[k][l] != ENDGAP) gap+=wg[k]; /* MR1, else: GAP. ENDGAPs are ignored for counting percentage */
}
}
percent_gaps[l]=100.*gap/(res+gap);
if (v>=4) cout<<"percent gaps["<<l<<"]="<<percent_gaps[l]<<" first seq:"<<seq[0][l]<<"\n";
}
/* Insert states 'bloat' the HMM,
throwing them out 'slims' down the HMM.
A slimmer HMM takes less time to construct.
However, the marriage of Clustal and Hhalign
is particularly sensitive to residues
at the very end of the profile; these I call
'telomeres'. Telomeres must not be shed when
throwing out insert states, for the telomeres
we set the match threshold to 100%.
*/
#define MGAP_LOGIC 0
#define TELOMERE_LOGIC 1
#define TELOMERE_DYNAMIC 0
#define ALWAYS_ACCEPT 101.0 /* do NOT change this parameter, must be >=100,
make slightly bigger than 100% -- to be sure to be sure */
#define DEFAULT_MGAPS 100.0 /* Soeding's default is 50, omega default prior to telomere logic was 100
FIXME: this used to be par.Mgaps,
in a later version re-introduce par.Mgaps to keep this value flexible */
#define TELOMER_LENGTH 10 /* this parameter must be > 0 (unless DEFAULT_MGAPS=100),
if it is too big (L/2) then telomere logic has no effect,
don't think it should be changed (much) */
#define TELOMER_FRACTION 0.10
//#define HMM_MIN_LENGTH 0.923
#define HMM_MIN_LENGTH 0.950
#define FORTRAN_OFFSET 1
double dDefaultMgaps;
dDefaultMgaps = DEFAULT_MGAPS;
#if TELOMERE_LOGIC /* turn telomere logic on (1) or off (0) */
int iTelomereLength;
#if TELOMERE_DYNAMIC /* keep telomere length 'dynamic' */
iTelomereLength = TELOMER_LENGTH > (int)(L*TELOMER_FRACTION) ? TELOMER_LENGTH : (int)(L*TELOMER_FRACTION);
#else
iTelomereLength = TELOMER_LENGTH;
#endif /* this was dynamic telomere */
#endif /* this was telomere logic */
/* if HMMs get too small (much smaller than profile length L)
then one is liable to get a back-tracking error.
So we should ensure that the DEFAULT_MGAPS parameter does NOT
shrink the HMM too much.
take percentage-gap vector, sort it, and fix dDefaultMgaps,
such that at least (HMM_MIN_LENGTH)*(L) are left
*/
#if MGAP_LOGIC /* try to adapt Mgaps to size of final HMM */
{
float *pfPercentGaps = NULL;
if (NULL == (pfPercentGaps = (float *)malloc((L+1)*sizeof(float)))){
printf("%s:%s:%d: could not malloc %d float for sorted percent-gaps\n",
__FUNCTION__, __FILE__, __LINE__, L+1);
dDefaultMgaps = DEFAULT_MGAPS;
}
else {
for (l = 0; l < L; l++) {
pfPercentGaps[l] = percent_gaps[l+FORTRAN_OFFSET];
}
qsort(pfPercentGaps, L, sizeof(float), CompFltAsc);
dDefaultMgaps = pfPercentGaps[(int)(HMM_MIN_LENGTH*L)];
if (dDefaultMgaps < DEFAULT_MGAPS){
//printf("Mgaps = %f <- %f\n", DEFAULT_MGAPS, dDefaultMgaps);
dDefaultMgaps = DEFAULT_MGAPS;
}
else {
//printf("Mgaps = %f\n", dDefaultMgaps);
}
free(pfPercentGaps); pfPercentGaps = NULL;
}
}
#endif /* tried to adapt Mgaps to size of final HMM */
// Throw out insert states and keep only match states
i=0;
for (k=0; k<N_in; k++) {h[k]=1; seq[k][0]='-';}
for (l=1; l<=L; l++)
{
#if TELOMERE_LOGIC
float fMgaps = ALWAYS_ACCEPT;
if ( (l < iTelomereLength) || (L-l < iTelomereLength) ){
/* residue is in telomere, always retain this position */
fMgaps = ALWAYS_ACCEPT;
}
else if (0){
/* FIXME: would like to put a transition phase in here,
where the Mgap value gradually goes down from 100 to DEFAULT_MGAPS,
however, may not be necessary and will make code more clunky */
}
else {
/* position is in centre of sequence,
retain position if less than DEFAULT_MGAPS% gaps at this position,
for example, if DEFAULT_MGAPS=30 throw out if more than 30% gap.
conversely, if DEFAULT_MGAPS=100 throw out if more than 100% gaps,
which can never happen, so always retain */
fMgaps = dDefaultMgaps;
}
if (percent_gaps[l] <= fMgaps)
#else /* this was telomere logic */
if (percent_gaps[l]<=float(par.Mgaps))
#endif /* this was Soeding default */
{
if (i>=/*MAXRES*/par.maxResLen-2) {
if (v>=1)
printf("WARNING: Number of match columns too large. Only first %i match columns will be kept!\n",i);
break;
}
i++;
this->l[i]=l;
#if 0
//#ifdef HAVE_OPENMP
#pragma omp parallel for schedule(static)
#endif
for (k=0; k<N_in; k++)
{
if (keep[k])
{
seq[k][h[k]++]=MatchChr(seq[k][l]);
X[k][i]=X[k][l];
I[k][i]=0;
}
else if (k==kss_dssp || k==kss_pred)
{
seq[k][h[k]++]=MatchChr(seq[k][l]);
X[k][i]=ss2i(seq[k][l]);
}
else if (k==ksa_dssp)
{
seq[k][h[k]++]=MatchChr(seq[k][l]);
X[k][i]=sa2i(seq[k][l]);
}
else if (k==kss_conf)
{
seq[k][h[k]++]=seq[k][l];
X[k][i]=cf2i(seq[k][l]);
}
}
}
else
{
for (k=0; k<N_in; k++)
if (keep[k] && X[k][l]<GAP)
{
I[k][i]++;
seq[k][h[k]++]=InsertChr(seq[k][l]);
}
}
}
for (k=0; k<N_in; k++) seq[k][h[k]]='\0';
//printf("%d\t%d\t%d\tN/L/M\n", N_in, L, i); /* -------- FIXME */
if (v>=2) cout<<"Alignment in "<<infile<<" contains "<<L<<" columns and "<<i<<" match states\n";
L = i; //Number of match states
delete[] percent_gaps; percent_gaps = NULL;
break;
////////////////////////////////////////////////////////////////////////
// Using residues of first sequence as match states
case 3:
/* Note: allocating statically is fine most of the time
but when the sequences/profiles get really long
we might run out of memory, so must really do it dynamically.
had to move declaration of float *percent_gaps out of switch()
*/
//char match_state[MAXCOL]; //1: column assigned to match state 0: insert state
match_state = new char[par.maxColCnt];
// Determine number of columns L in alignment
L=strlen(seq[0]+1);
if (v>=3) printf("Length of first seq = %i\n",L);
// Check for sequences with unequal lengths
for (k=1; k<N_in; k++)
if (int(strlen(seq[k]+1))!=L) {unequal_lengths=k; break;}
if (unequal_lengths) break;
// Determine match states: seq kfirst has residue at pos l -> match state
for (l=1; l<=L; l++)
if (isalpha(seq[kfirst][l])) match_state[l]=1; else match_state[l]=0;
// Throw out insert states and keep only match states
for (k=0; k<N_in; k++) {h[k]=1; seq[k][0]='-';}
i=0;
for (l=1; l<=L; l++)
{
if (match_state[l]) // does sequence 0 have residue at position l?
{
if (i>=/*MAXRES*/par.maxResLen-2) {
if (v>=1)
printf("WARNING: Number of match columns too large. Only first %i match columns will be kept!\n",i);
break;
}
i++;
this->l[i]=l;
for (k=0; k<N_in; k++)
{
if (keep[k])
{
seq[k][h[k]++]=MatchChr(seq[k][l]);
X[k][i]=aa2i(seq[k][l]);
I[k][i]=0;
}
else if (k==kss_dssp || k==kss_pred)
{
seq[k][h[k]++]=MatchChr(seq[k][l]);
X[k][i]=ss2i(seq[k][l]);
}
else if (k==ksa_dssp)
{
seq[k][h[k]++]=MatchChr(seq[k][l]);
X[k][i]=sa2i(seq[k][l]);
}
else if (k==kss_conf)
{
seq[k][h[k]++]=seq[k][l];
X[k][i]=cf2i(seq[k][l]);
}
}
}
else
{
for (k=0; k<N_in; k++)
if (keep[k] && aa2i(seq[k][l])<GAP)
{
I[k][i]++;
seq[k][h[k]++]=InsertChr(seq[k][l]);
}
}
}
for (k=0; k<N_in; k++) seq[k][h[k]]='\0';
//Replace GAP with ENDGAP for all end gaps /* MR1 */
for (k=0; k<N_in; ++k)
{
if (!keep[k]) continue;
for (i=1; i<=L && X[k][i]==GAP; i++) X[k][i]=ENDGAP; /* MR1, note i++ <- ++i */
for (i=L; i>=1 && X[k][i]==GAP; i--) X[k][i]=ENDGAP; /* MR1 */
}
if (v>=2) cout<<"Alignment in "<<infile<<" contains "<<L<<" columns and "<<i<<" match states\n";
L = i; //Number of match states
delete[] match_state; match_state = NULL;
break;
} //end switch()
///////////////////////////////////////////////////////////////////////////
// Error
if (unequal_lengths)
{
strcut(sname[unequal_lengths]);
cerr<<endl<<"Error: sequences in "<<infile<<" do not all have the same number of columns, \ne.g. first sequence and sequence "<<sname[unequal_lengths]<<".\n";
if(par.M==1) cerr<<".\nCheck input format for '-M a2m' option and consider using '-M first' or '-M 50'\n";
exit(1);
}
// Avert user about -cons option?
if (v>=2 && !par.cons)
{
for (i=1; i<=L; i++)
if (X[kfirst][i]==GAP)
{
printf("NOTE: Use the '-cons' option to calculate a consensus sequence as first sequence of the alignment.\n");
break;
}
}
/* MR1
//Replace GAP with ENDGAP for all end gaps
for (k=0; k<N_in; k++)
{
if (!keep[k]) continue;
for (i=1; i<=L && X[k][i]==GAP; i++) X[k][i]=ENDGAP;
for (i=L; i>=1 && X[k][i]==GAP; i--) X[k][i]=ENDGAP;
}*/
// DEBUG
if (v>=4)
for (k=0; k<N_in; k++)
{
if (!display[k]) continue;
cout<<">"<<sname[k]<<"\n";
if (k==kss_dssp || k==kss_pred) {for (i=1; i<=L; i++) cout<<char(i2ss(X[k][i]));}
else if (k==kss_conf) {for (i=1; i<=L; i++) cout<<char(i2cf(X[k][i]));}
else if (k==ksa_dssp) {for (i=1; i<=L; i++) cout<<char(i2sa(X[k][i]));}
else
{
for (i=1; i<=L; i++) cout<<char(i2aa(X[k][i]));
cout<<"\n";
for (i=1; i<=L; i++)
if (I[k][i]==0) cout<<"-"; else if (I[k][i]>9) cout<<"X"; else cout<<I[k][i];
}
cout<<"\n";
}
delete[](h); h = NULL;
}
/**
* @brief Remove sequences with seq. identity larger than seqid percent
*(remove the shorter of two) or coverage<cov_thr
*
* FIXME: originally max_seqid is a variable that is the cutoff
* above which sequences are thrown out. We want to throw out sequences
* when building the HMM but not for display, there we want to keep all.
* This should be really easy, but there is some hidden stuff going on
* in this function, so I did a minimal-invasive change and just stuck
* (effectively) a hard-wired 100 instead of the variable.
* At a later stage we should get rid of this function alltogether
* as it does gobble up some time (and is quadratic in noof sequences, I think)
* FS, 2010-10-04
*/
////////////////////////////////////////////////////////////////////////////
/*
*/
inline int
Alignment::FilterForDisplay(int max_seqid, int coverage, int qid, float qsc, int N)
{
/* FIXME
* by just returning n_display and not doing anything
* I think we display everything and not do any work for it
*/
return n_display; /* FS, 2010-10-04*/
if (par.mark) return n_display;
char *dummy = new char[N_in+1];
int vtmp=v, seqid;
v=0;
n_display=0;
if (kss_dssp>=0) display[kss_dssp]=KEEP_NOT;
if (ksa_dssp>=0) display[ksa_dssp]=KEEP_NOT;
if (kss_pred>=0) display[kss_pred]=KEEP_NOT;
if (kss_conf>=0) display[kss_conf]=KEEP_NOT;
for (seqid=imin(10,max_seqid); n_display<N && seqid<=max_seqid; seqid++)
{
for (int k=0; k<N_in; k++) dummy[k]=display[k];
n_display = Filter2(dummy,coverage,qid,qsc,20,seqid,0);
// printf("Seqid=%3i n_display=%4i\n",seqid,n_display);
}
if (n_display>N)
{
for (int k=0; k<N_in; k++) dummy[k]=display[k];
n_display = Filter2(dummy,coverage,qid,qsc,20,--(--seqid),0);
}
v=vtmp;
for (int k=0; k<N_in; k++) display[k]=dummy[k];
if (kss_dssp>=0) {display[kss_dssp]=KEEP_CONDITIONALLY; n_display++;}
if (ksa_dssp>=0) {display[ksa_dssp]=KEEP_CONDITIONALLY; n_display++;}
if (kss_pred>=0) {display[kss_pred]=KEEP_CONDITIONALLY; n_display++;}
if (kss_conf>=0) {display[kss_conf]=KEEP_CONDITIONALLY; n_display++;}
delete[] dummy; dummy = NULL;
return n_display;
}
/////////////////////////////////////////////////////////////////////////////////////
// Remove sequences with seq. identity larger than seqid percent (remove the shorter of two) or coverage<cov_thr
/////////////////////////////////////////////////////////////////////////////////////
inline int Alignment::Filter(int max_seqid, int coverage, int qid, float qsc, int N)
{
return Filter2(keep,coverage,qid,qsc,20,max_seqid,N);
}
/////////////////////////////////////////////////////////////////////////////
/*
* @brief Select set of representative sequences in the multiple sequence alignment
*
* Filter criteria:
* Remove sequences with coverage of query less than "coverage" percent
* Remove sequences with sequence identity to query of less than "qid" percent
* If Ndiff==0, remove sequences with seq. identity larger than seqid2(=max_seqid) percent
* If Ndiff>0, remove sequences with minimum-sequence-identity filter of between seqid1
* and seqid2 (%), where the minimum seqid threshold is determined such that,
* in all column blocks of at least WMIN=25 residues, at least Ndiff sequences are left.
* This ensures that in multi-domain proteins sequences covering one domain are not
* removed completely because sequences covering other domains are more diverse.
*
* Allways the shorter of two compared sequences is removed (=> sort sequences by length first).
* Please note: sequence identity of sequence x with y when filtering x is calculated as
* number of residues in sequence x that are identical to an aligned residue in y / number of residues in x
* Example: two sequences x and y are 100% identical in their overlapping region but one overlaps by 10% of its
* length on the left and the other by 20% on the right. Then x has 10% seq.id with y and y has 20% seq.id. with x.
*/
//////////////////////////////////////////////////////////////////////////////
int
Alignment::Filter2(char keep[], int coverage, int qid, float qsc, int seqid1, int seqid2, int Ndiff)
{
// In the beginnning, keep[k] is 1 for all regular amino acid sequences and 0 for all others (ss_conf, ss_pred,...)
// In the end, keep[k] will be 1 for all regular representative sequences kept in the alignment, 0 for all others
char* in=new char[N_in+1]; // in[k]=1: seq k has been accepted; in[k]=0: seq k has not yet been accepted at current seqid
char* inkk=new char[N_in+1]; // inkk[k]=1 iff in[ksort[k]]=1 else 0;
int* Nmax=new int[L+2]; // position-dependent maximum-sequence-identity threshold for filtering /* MR1, used to be called idmax*/
int* idmaxwin=new int[L+2]; // minimum value of idmax[i-WFIL,i+WFIL]
int* seqid_prev=new int[N_in+1]; // maximum-sequence-identity threshold used in previous round of filtering (with lower seqid)
int* N=new int[L+2]; // N[i] number of already accepted sequences at position i
const int WFIL=25; // see previous line
int diffNmax=Ndiff; // current maximum difference of Nmax[i] and Ndiff /* MR1 */
int diffNmax_prev=0; // previous maximum difference of Nmax[i] and Ndiff /* MR1 */
int seqid; // current maximum value for the position-dependent maximum-sequence-identity thresholds in idmax[]
int seqid_step=0; // previous increment of seqid /* MR1 */
float diff_min_frac; // minimum fraction of differing positions between sequence j and k needed to accept sequence k
float qdiff_max_frac=0.9999-0.01*qid; // maximum allowable number of residues different from query sequence
int diff; // number of differing positions between sequences j and k (counted so far)
int diff_suff; // number of differing positions between sequences j and k that would be sufficient
int qdiff_max; // maximum number of residues required to be different from query
int cov_kj; // upper limit of number of positions where both sequence k and j have a residue
int first_kj; // first non-gap position in sequence j AND k
int last_kj; // last non-gap position in sequence j AND k
int kk, jj; // indices for sequence from 1 to N_in
int k, j; // kk=ksort[k], jj=ksort[j]
int i; // counts residues
int n; // number of sequences accepted so far
// Initialize in[k]
for (n=k=0; k<N_in; k++) if (keep[k]==KEEP_ALWAYS) {in[k]=2/*KEEP_ALWAYS??*/; n++;} else in[k]=0;
// Determine first[k], last[k]?
if (first==NULL)
{
first=new int[N_in];// first non-gap position in sequence k
last =new int[N_in];// last non-gap position in sequence k
for (k=0; k<N_in; k++) // do this for ALL sequences, not only those with in[k]==1 (since in[k] may be display[k])
{
for (i=1; i<=L; i++) if (X[k][i]<NAA) break;
first[k]=i;
for (i=L; i>=1; i--) if (X[k][i]<NAA) break;
last[k]=i;
}
}
// Determine number of residues nres[k]?
// KB: memory leak as sizeof(nres) just gives the size of an int pointer
//if ( (nres==NULL) || (sizeof(nres)<N_in*sizeof(int)) )
if (nres==NULL)
{
nres=new int[N_in];
for (k=0; k<N_in; k++) // do this for ALL sequences, not only those with in[k]==1 (since in[k] may be display[k])
{
int nr=0;
for (i=first[k]; i<=last[k]; i++)
if (X[k][i]<NAA) nr++;
nres[k]=nr;
// printf("%20.20s nres=%3i first=%3i last=%3i\n",sname[k],nr,first[k],last[k]);
}
}
// Sort sequences according to length; afterwards, nres[ksort[kk]] is sorted by size
if (ksort==NULL)
{
ksort=new int[N_in]; // never reuse alignment object for new alignment with more sequences
for (k=0; k<N_in; k++) ksort[k]=k;
QSortInt(nres,ksort,kfirst+1,N_in-1,-1); //Sort sequences after kfirst (query) in descending order
}
for (kk=0; kk<N_in; kk++) inkk[kk]=in[ksort[kk]];
// Initialize N[i], idmax[i], idprev[i]
for (i=1; i<first[kfirst]; i++) N[i]=0;
for (i=first[kfirst]; i<=last[kfirst]; i++) N[i]=1;
for (i=last[kfirst]+1; i<=L; i++) N[i]=0;
//for (i=1; i<=L; i++) {idmax[i]=seqid1; idmaxwin[i]=-1;}
for (i=1; i<=L; ++i) {Nmax[i]=0; idmaxwin[i]=-1;} /* MR1 */
for (k=0; k<N_in; k++) seqid_prev[k]=-1;
if (Ndiff<=0 || Ndiff>=N_in) {seqid1=seqid2; Ndiff=N_in; diffNmax=Ndiff;}
// Check coverage and sim-to-query criteria for each sequence k
for (k=0; k<N_in; k++)
{
if (keep[k]==KEEP_NOT || keep[k]==KEEP_ALWAYS) continue; // seq k not regular sequence OR is marked sequence
if (100*nres[k]<coverage*L) {keep[k]=KEEP_NOT; continue;} // coverage too low? => reject once and for all
float qsc_sum=0.0;
// Check if score-per-column with query is at least qsc
if (qsc>-10)
{
float qsc_min = qsc*nres[k]; // minimum total score of seq k with query
int gapq=0, gapk=0; // number of consecutive gaps in query or k'th sequence at position i
for (int i=first[k]; i<=last[k]; i++)
{
if (X[k][i]<20)
{
gapk=0;
if (X[kfirst][i]<20)
{
gapq=0;
qsc_sum += S[(int)X[kfirst][i]][(int)X[k][i]];
}
else if (gapq++) qsc_sum-=PLTY_GAPEXTD; else qsc_sum-=PLTY_GAPOPEN;
}
else if (X[kfirst][i]<20)
{
gapq=0;
if (gapk++) qsc_sum-=PLTY_GAPEXTD; else qsc_sum-=PLTY_GAPOPEN;
}
}
// printf("k=%3i qsc=%6.2f\n",k,qsc_sum);
if (qsc_sum<qsc_min) {keep[k]=KEEP_NOT; continue;} // too different from query? => reject once and for all
}
//Check if sequence similarity with query at least qid?
if (qdiff_max_frac<0.999)
{
qdiff_max=int(qdiff_max_frac*nres[k]+0.9999);
// printf("k=%-4i nres=%-4i qdiff_max=%-4i first=%-4i last=%-4i",k,nres[k],qdiff_max,first[k],last[k]);
diff=0;
for (int i=first[k]; i<=last[k]; i++)
// enough different residues to reject based on minimum qid with query? => break
if (X[k][i]<20 && X[k][i]!=X[kfirst][i] && ++diff>=qdiff_max) break;
// printf(" diff=%4i\n",diff);
if (diff>=qdiff_max) {keep[k]=KEEP_NOT; continue;} // too different from query? => reject once and for all
}
// printf(" qsc=%6.2f qid=%6.2f \n",qsc_sum/nres[k],100.0*(1.0-(float)(diff)/nres[k]));
} // end for (k)
if (seqid1>seqid2)
{
for (n=k=0; k<N_in; k++) if (keep[k]>KEEP_NOT) n++;
return n;
}
// Successively increment idmax[i] at positons where N[i]<Ndiff
//for (seqid=seqid1; seqid<=seqid2; seqid+=1+(seqid>=50)) /* MR1 */
seqid=seqid1;
while (seqid<=seqid2)
{
/*
// Update idmax[i]
for (i=1; i<=L; i++) if (N[i]<Ndiff) idmax[i]=seqid;
// Update idmaxwin[i] as minimum of idmax[i-WFIL,i+WFIL]. If idmaxwin[] has not changed then stop
char stop=1;
for (i=1; i<=L; i++)
{
int idmax_min=seqid2;
for (j=imax(1,imin(L-2*WFIL+1,i-WFIL)); j<=imin(L,imax(2*WFIL,i+WFIL)); j++)
if (idmax[j]<idmax_min) idmax_min=idmax[j];
if (idmax_min>idmaxwin[i]) stop=0; // idmaxwin[i] has changed => do not stop
idmaxwin[i]=idmax_min;
}
*/
char stop=1;
// Update Nmax[i]
diffNmax_prev = diffNmax;
diffNmax = 0;
for (i=1; i<=L; ++i)
{
int max=0;
for (j=imax(1,imin(L-2*WFIL+1,i-WFIL)); j<=imin(L,imax(2*WFIL,i+WFIL)); ++j)
if (N[j]>max) max=N[j];
if (Nmax[i]<max) Nmax[i]=max;
if (Nmax[i]<Ndiff)
{
stop=0;
idmaxwin[i]=seqid;
if (diffNmax<Ndiff-Nmax[i]) diffNmax=Ndiff-Nmax[i];
}
}
//printf("seqid=%3i diffNmax_prev= %-4i diffNmax= %-4i n=%-5i N_in-N_ss=%-5i\n",seqid,diffNmax_prev,diffNmax,n,N_in-N_ss);
if (stop) break;
// // DEBUG
// printf("idmax ");
// for (i=1; i<=L; i++) printf("%2i ",idmax[i]);
// printf("\n");
// printf("idmaxwin ");
// for (i=1; i<=L; i++) printf("%2i ",idmaxwin[i]);
// printf("\n");
// printf("N[i] ");
// for (i=1; i<=L; i++) printf("%2i ",N[i]);
// printf("\n");
// Loop over all candidate sequences kk (-> k)
#if 0
//#ifdef HAVE_OPENMP
#pragma omp parallel for schedule(static) private(k, i, diff_min_frac, jj, j, first_kj, last_kj, cov_kj, diff_suff, diff)
#endif
for (kk=0; kk<N_in; kk++)
{
if (inkk[kk]) continue; // seq k already accepted
k=ksort[kk];
if (!keep[k]) continue; // seq k is not regular aa sequence or already suppressed by coverage or qid criterion
if (keep[k]==KEEP_ALWAYS) {inkk[kk]=2; continue;} // accept all marked sequences (no n++, since this has been done already)
// Calculate max-seq-id threshold seqidk for sequence k (as maximum over idmaxwin[i])
// if (seqid>=100) {in[k]=inkk[kk]=1; n++; continue;}
if (seqid>=100) {
in[k]=inkk[kk]=1;
#if 0
//#ifdef HAVE_OPENMP
#pragma omp atomic
#endif
n++;
continue;
}
float seqidk=seqid1;
for (i=first[k]; i<=last[k]; i++)
if (idmaxwin[i]>seqidk) seqidk=idmaxwin[i];
if (seqid==seqid_prev[k]) continue; // sequence has already been rejected at this seqid threshold => reject this time
seqid_prev[k]=seqid;
diff_min_frac =0.9999-0.01*seqidk; // min fraction of differing positions between sequence j and k needed to accept sequence k
// Loop over already accepted sequences
for (jj=0; jj<kk; jj++)
{
if (!inkk[jj]) continue;
j=ksort[jj];
first_kj=imax(first[k],first[j]);
last_kj =imin(last[k],last[j]);
cov_kj = last_kj-first_kj+1;
diff_suff=int(diff_min_frac*imin(nres[k],cov_kj)+0.999); // nres[j]>nres[k] anyway because of sorting /* MR1 0.999 */
diff=0;
for (int i=first_kj; i<=last_kj; i++)
{
// enough different residues to accept? => break
if (X[k][i]>=NAA || X[j][i]>=NAA)
cov_kj--;
else
if (X[k][i]!=X[j][i] && ++diff>=diff_suff) break; // accept (k,j)
}
// // DEBUG
// printf("%20.20s with %20.20s: diff=%i diff_min_frac*cov_kj=%f diff_suff=%i nres=%i cov_kj=%i\n",sname[k],sname[j],diff,diff_min_frac*cov_kj,diff_suff,nres[k],cov_kj);
// printf("%s\n%s\n\n",seq[k],seq[j]);
//if (float(diff)<fmin(diff_min_frac*cov_kj,diff_suff)) break; //similarity > acceptace threshold? Reject! /* MR1 */
if (diff<diff_suff && float(diff)<=diff_min_frac*cov_kj) break; //dissimilarity < acceptace threshold? Reject! /* MR1 */
}
if (jj>=kk) // did loop reach end? => accept k. Otherwise reject k (the shorter of the two)
{
in[k]=inkk[kk]=1;
#if 0
//#ifdef HAVE_OPENMP
#pragma omp atomic
#endif
n++;
for (i=first[k]; i<=last[k]; i++) {
#if 0
//#ifdef HAVE_OPENMP
#pragma omp atomic
#endif
N[i]++; // update number of sequences at position i
}
// printf("%i %20.20s accepted\n",k,sname[k]);
}
// else
// {
// printf("%20.20s rejected: too similar with seq %20.20s diff=%i diff_min_frac*cov_kj=%f diff_suff=%i nres=%i cov_kj=%i\n",sname[k],sname[j],diff,diff_min_frac*cov_kj,diff_suff,nres[k],cov_kj);
// printf("%s\n%s\n\n",seq[k],seq[j]);
// }
} // End Loop over all candidate sequences kk
// // DEBUG
// printf("\n");
// printf("seqid_prev[k]= \n");
// for (k=0; k<N_in; k++) printf("%2i ",seqid_prev[k]);
// printf("\n");
// Increment seqid /* MR1 */
seqid_step = imax(1,imin(5,diffNmax/(diffNmax_prev-diffNmax+1)*seqid_step/2));
seqid += seqid_step;
} // End Loop over seqid
if (v>=2)
{
printf("%i out of %i sequences passed filter (",n,N_in-N_ss);
if (par.coverage)
printf("%i%% min coverage, ",coverage);
if (qid)
printf("%i%% min sequence identity to query, ",qid);
if (qsc>-10)
printf("%.2f bits min score per column to query, ",qsc);
if (Ndiff<N_in && Ndiff>0)
printf("up to %i%% position-dependent max pairwise sequence identity)\n",seqid);
else
printf("%i%% max pairwise sequence identity)\n",seqid1);
}
for (k=0; k<N_in; k++) keep[k]=in[k];
delete[] in; in = NULL;
delete[] inkk; inkk = NULL;
//delete[] idmax; idmax = NULL;
delete[] Nmax; /* MR1 */
delete[] idmaxwin; idmaxwin = NULL;
delete[] seqid_prev; seqid_prev = NULL;
delete[] N; N = NULL;
#if 0
printf("%s:%s:%d: sequences accepted = %d/%d\n", __FUNCTION__, __FILE__, __LINE__, n, N_in-N_ss);
#endif
return n;
}
/* MR1: the Alignment::HomologyFilter is no longer needed in hhalign-stand-alone */
/////////////////////////////////////////////////////////////////////////////
/**
* @brief Filter for min score per column coresc with core query profile,
* defined by coverage_core and qsc_core
*/
/////////////////////////////////////////////////////////////////////////////
int
Alignment::HomologyFilter(int coverage_core, float qsc_core, float coresc)
{
const int seqid_core=90; //maximum sequence identity in core alignment
const int qid_core=0;
const int Ndiff_core=0;
int n;
HMM qcore;
char* coreseq=new char[N_in]; // coreseq[k]=1 if sequence belongs to core of alignment (i.e. it is very similar to query)
for (int k=0; k<N_in; k++) coreseq[k]=keep[k]; // Copy keep[] into coreseq[]
// Remove sequences with seq. identity larger than seqid percent (remove the shorter of two)
int v1=v; v=1;
n = Filter2(coreseq,coverage_core,qid_core,qsc_core,seqid_core,seqid_core,Ndiff_core);
v=v1;
if (v>=2)
{
printf("%i out of %i core alignment sequences passed filter (",n,N_in-N_ss);
if (par.coverage_core)
printf("%i%% min coverage, ",coverage_core);
if (qid_core)
printf("%i%% min sequence identity to query, ",qid_core);
if (qsc_core>-10)
printf("%.2f bits min score per column to query, ",qsc_core);
printf("%i%% max pairwise sequence identity)\n",seqid_core);
}
// Calculate bare AA frequencies and transition probabilities -> qcore.f[i][a], qcore.tr[i][a]
FrequenciesAndTransitions(qcore,coreseq);
// Add transition pseudocounts to query -> q.p[i][a] (gapd=1.0, gape=0.333, gapf=gapg=1.0, gaph=gapi=1.0, gapb=1.0
qcore.AddTransitionPseudocounts(1.0,0.333,1.0,1.0,1.0,1.0,1.0);
// Generate an amino acid frequency matrix from f[i][a] with full pseudocount admixture (tau=1) -> g[i][a]
qcore.PreparePseudocounts();
// Add amino acid pseudocounts to query: qcore.p[i][a] = (1-tau)*f[i][a] + tau*g[i][a]
qcore.AddAminoAcidPseudocounts(2,1.5,2.0,1.0); // pcm=2, pca=1.0, pcb=2.5, pcc=1.0
// Filter out all sequences below min score per column with qcore
n=FilterWithCoreHMM(keep, coresc, qcore);
if (v>=2) cout<<n<<" out of "<<N_in-N_ss<<" sequences filtered by minimum score-per-column threshold of "<<qsc_core<<"\n";
delete[] coreseq; coreseq = NULL;
return n;
}
/////////////////////////////////////////////////////////////////////////////////////
/**
* @brief Filter out all sequences below a minimum score per column with profile qcore
*/
int
Alignment::FilterWithCoreHMM(char in[], float coresc, HMM& qcore)
{
int k; // count sequences in alignment
int i; // column in query alignment
int a; // amino acid (0..19)
int n=1; // number of sequences that passed filter
float** logodds=new float*[L+1]; // log-odds ratios for HMM qcore
char gap; // 1: previous state in seq k was a gap 0: previous state in seq k was an amino acid
float score; // score of sequence k aligned with qcore
for (i=1; i<=L; i++) logodds[i]=new(float[21]);
// Determine first[k], last[k]?
if (first==NULL)
{
first=new int[N_in];// first non-gap position in sequence k
last =new int[N_in];// last non-gap position in sequence k
for (k=0; k<N_in; k++) // do this for ALL sequences, not only those with in[k]==1 (since in[k] may be display[k])
{
for (i=1; i<=L; i++) if (X[k][i]<NAA) break;
first[k]=i;
for (i=L; i>=1; i--) if (X[k][i]<NAA) break;
last[k]=i;
}
}
// Determine number of residues nres[k]?
if (nres==NULL)
{
nres=new int[N_in];
for (k=0; k<N_in; k++) // do this for ALL sequences, not only those with in[k]==1 (since in[k] may be display[k])
{
int nr=0;
for (i=first[k]; i<=last[k]; i++)
if (X[k][i]<NAA) nr++;
nres[k]=nr;
// printf("%20.20s nres=%3i first=%3i last=%3i\n",sname[k],nr,f,l);
}
}
// Precalculate the log-odds for qcore
for (i=1; i<=L; i++)
{
for (a=0; a<NAA; a++)
logodds[i][a]=fast_log2(qcore.p[i][a]/pb[a]);
logodds[i][ANY]=-0.5; // half a bit penalty for X
// printf(" A R N D C Q E G H I L K M F P S T W Y V\n");
// printf("%6i ",i);
// for (a=0; a<20; ++a) fprintf(stdout,"%5.1f ",100*qcore.f[i][a]);
// printf("\n");
// printf(" ");
// for (a=0; a<20; ++a) fprintf(stdout,"%5.1f ",100*qcore.g[i][a]);
// printf("\n");
// printf(" ");
// for (a=0; a<20; ++a) fprintf(stdout,"%5.1f ",100*qcore.p[i][a]);
// printf("\n");
// printf(" ");
// for (a=0; a<20; ++a) fprintf(stdout,"%5.1f ",100*pb[a]);
// printf("\n");
// printf(" ");
// for (a=0; a<20; ++a) fprintf(stdout,"%5.2f ",fast_log2(qcore.p[i][a]/pb[a]));
// printf("\n");
}
// Main loop: test all sequences k
for (k=kfirst+1; k<N_in; k++)
{
if (!in[k]) continue; // if in[k]==0 sequence k will be suppressed directly
float score_M=0.0;
float score_prev=0.0;
// Calculate score of sequence k with core HMM
score=0; gap=0;
for (i=first[k]; i<=last[k]; i++)
{
score_M=0.0;
if (X[k][i]<=ANY) // current state is Match
{
score_M=logodds[i][ (int)X[k][i]];
score+=logodds[i][ (int)X[k][i]];
if (gap) score+=qcore.tr[i][D2M]; else score+=qcore.tr[i][M2M];
gap=0;
}
else if (X[k][i]==GAP) // current state is Delete (ignore ENDGAPs)
{
if (gap) score+=qcore.tr[i][D2D]; else score+=qcore.tr[i][M2D];
gap=1;
}
if (I[k][i]) score+=qcore.tr[i][M2I]+(I[k][i]-1)*qcore.tr[i][I2I]+qcore.tr[i][I2M];
// if (k==2) printf("i=%3i %c:%c score_M=%6.2f score=%6.2f score_sum=%6.2f \n",i,i2aa(X[kfirst][i]),i2aa(X[k][i]),score_M,score-score_prev,score);
score_prev=score;
}
printf("k=%3i score=%6.2f\n",k,score);
if (score<nres[k]*coresc) in[k]=0; else n++;// reject sequence k?
}
for (i=1; i<=L; i++){
delete[] logodds[i]; logodds[i] = NULL;
}
delete[] logodds; logodds = NULL;
return n;
}
/* MR1 */
#if 0
/////////////////////////////////////////////////////////////////////////////////////
/**
* @brief Filter alignment to given diversity/Neff
*/
bool
Alignment::FilterNeff()
{
int v1=v;
v=v1-1;
const float TOLX=0.001;
const float TOLY=0.02;
char dummy[N_in+1];
for (int k=0; k<N_in; ++k) dummy[k]=keep[k];
float x=0.0,y=0.0;
float x0=-1.0;
float x1=+2.0;
float y0=filter_by_qsc(x0,dummy);
float y1=filter_by_qsc(x1,dummy);
int i=2;
while (y0-par.Neff>0 && par.Neff-y1>0)
{
x = x0 + (par.Neff-y0)*(x1-x0)/(y1-y0); // linear interpolation between (x0,y0) and (x1,y1)
y = filter_by_qsc(x,dummy);
if (v>=2) printf(" %3i x0=%6.3f -> %6.3f x=%6.3f -> %6.3f x1=%6.3f -> %6.3f \n",++i,x0,y0,x,y,x1,y1);
if (y>par.Neff) {x0=x; y0=y;} else {x1=x; y1=y;}
if (fabs(par.Neff-y)<TOLY || x1-x0<TOLX) break;
}
v=v1;
if (y0>=par.Neff && y1<=par.Neff)
{
// Write filtered alignment WITH insert states (lower case) to alignment file
if (v>=2) printf("Found Neff=%6.3f at filter threshold qsc=%6.3f\n",y,x);
return true;
}
else if (v>=1)
printf("Diversity of unfiltered alignment %.2f is below target diversity %.2f. No alignment written\n",y0,par.Neff);
return false;
}
float Alignment::filter_by_qsc(float qsc, char* dummy)
{
HMM q;
for (int k=0; k<N_in; ++k) keep[k]=dummy[k];
Filter2(keep,par.coverage,0,qsc,par.max_seqid+1,par.max_seqid,0);
FrequenciesAndTransitions(q);
// printf("qsc=%4.1f N_filtered=%-3i Neff=%6.3f\n",qsc,n,q.Neff_HMM);
return q.Neff_HMM;
}
#endif
/////////////////////////////////////////////////////////////////////////////////////
/**
* @brief Calculate AA frequencies q.p[i][a] and transition probabilities q.tr[i][a] from alignment
*/
void
Alignment::FrequenciesAndTransitions(HMM& q, char* in)
{
int k; // index of sequence
int i; // position in alignment
int a; // amino acid (0..19)
int ni[NAA+3]; // number of times amino acid a occurs at position i
int naa; // number of different amino acids
if (v>=3)
cout<<"Calculating position-dependent weights on subalignments\n";
if (in==NULL) in=keep; // what's this good for?
if (N_filtered>1)
{
for (k=0; k<N_in; k++) wg[k]=0.0; // initialized wg[k]
// Calculate global weights
for (i=1; i<=L; i++) // for all positions i in alignment
{
for (a=0; a<20; a++) ni[a]=0;
for (k=0; k<N_in; k++) if (in[k]) ni[ (int)X[k][i]]++;
naa=0; for (a=0; a<20; a++) if(ni[a]) naa++;
if (!naa) naa=1; //naa=0 when column consists of only gaps and Xs (=ANY)
for (k=0; k<N_in; k++)
if (in[k] && X[k][i]<20)
wg[k] += 1.0/float(ni[ (int)X[k][i]]*naa*(nres[k]+30));
// ensure that each residue of a short sequence contributes as much as a residue of a long sequence:
// contribution is proportional to one over sequence length nres[k] plus 30.
}
NormalizeTo1(wg,N_in);
// Do pos-specific sequence weighting and calculate amino acid frequencies and transitions
for (k=0; k<N_in; k++) X[k][0]=ENDGAP; // make sure that sequences ENTER subalignment j for j=1
for (k=0; k<N_in; k++) X[k][L+1]=ENDGAP; // does it have an influence?
#if 0
//#ifdef HAVE_OPENMP
if(par.wg != 1)
{
#pragma omp parallel sections
{
#pragma omp section
Amino_acid_frequencies_and_transitions_from_M_state(q,in); // use subalignments of seqs with residue in i
#pragma omp section
Transitions_from_I_state(q,in); // use subalignments of seqs with insert in i
#pragma omp section
Transitions_from_D_state(q,in); // use subalignments of seqs with delete in i. Must be last of these three calls if par.wg==1!
}
}
else
{
#pragma omp parallel sections
{
#pragma omp section
Amino_acid_frequencies_and_transitions_from_M_state(q,in); // use subalignments of seqs with residue in i
#pragma omp section
Transitions_from_I_state(q,in); // use subalignments of seqs with insert in i
}
Transitions_from_D_state(q,in); // use subalignments of seqs with delete in i. Must be last of these three calls if par.wg==1!
}
#else
Amino_acid_frequencies_and_transitions_from_M_state(q,in);
Transitions_from_I_state(q,in);
Transitions_from_D_state(q,in);
#endif
}
else // N_filtered==1
{
X[kfirst][0]=X[kfirst][L+1]=ANY; // (to avoid anallowed access within loop)
q.Neff_HMM=1.0f;
for (i=0; i<=L+1; i++) // for all positions i in alignment
{
q.Neff_M[i]=1.0f;
q.Neff_I[i]=q.Neff_D[i]=0.0f;
for (a=0; a<20; a++) q.f[i][a]=0.0;
/* this is the crucial change that makes terminal-X work */
//q.f[i][ (int)(X[kfirst][i]) ] = 1.0; /* MR1 */
if (X[kfirst][i] < ANY) /* MR1 */
q.f[i][(unsigned int) X[kfirst][i] ] = 1.0;
else
for (a=0; a<20; ++a) q.f[i][a]=pb[a];
q.tr[i][M2M]=0;
q.tr[i][M2I]=-100000.0;
q.tr[i][M2D]=-100000.0;
q.tr[i][I2M]=-100000.0;
q.tr[i][I2I]=-100000.0;
q.tr[i][D2M]=-100000.0;
q.tr[i][D2D]=-100000.0;
}
q.tr[0][I2M]=0;
q.tr[L][I2M]=0;
q.tr[0][D2M]=0;
q.Neff_M[0]=q.Neff_I[0]=q.Neff_D[0]=99.999; // Neff_av[0] is used for calculation of transition pseudocounts for the start state
}
if (v>=3)
{
printf("\nMatches:\n");
printf("col Neff nseqs\n");
for (i=1; i<=imin(L,100); i++)
printf("%3i %5.2f %3i\n",i,q.Neff_M[i],nseqs[i]);
printf("\nInserts:\n");
printf("col Neff nseqs\n");
for (i=1; i<=imin(L,100); i++)
printf("%3i %5.2f %3i\n",i,q.Neff_I[i],nseqs[i]);
printf("\nDeletes:\n");
printf("col Neff nseqs\n");
for (i=1; i<=imin(L,100); i++)
printf("%3i %5.2f %3i\n",i,q.Neff_D[i],nseqs[i]);
}
// Copy column information into HMM q
q.L=L;
q.N_in=N_in;
q.N_filtered=N_filtered;
for (i=1; i<=L; i++) q.l[i]=l[i];
// Set names in HMM q
if (strlen(q.name)==0) strcpy(q.name,name);
if (strlen(q.longname)==0) strcpy(q.longname,longname);
if (strlen(q.fam)==0) strcpy(q.fam,fam);
ScopID(q.cl,q.fold,q.sfam,q.fam); // derive superfamily, fold and class code from family name
strcpy(q.file,file); // Store basename of alignment file name in q.file
// Copy sequences to be displayed into HMM
q.nss_dssp=q.nsa_dssp=q.nss_pred=q.nss_conf=q.nfirst=-1;
int n=0;
if (kss_dssp>=0) q.nss_dssp=n++; // copy dssp sequence?
if (ksa_dssp>=0) q.nsa_dssp=n++; // copy dssp sequence?
if (kss_pred>=0) q.nss_pred=n++; // copy psipred sequence?
if (kss_conf>=0) q.nss_conf=n++; // copy confidence value sequence?
// Calculate consensus sequence?
if (par.showcons || par.cons)
{
float maxw;
int maxa;
if (par.showcons)
{
// Reserve space for consensus/conservation sequence as Q-T alignment mark-up
q.ncons=n++;
q.sname[q.ncons]=new(char[10]);
if (!q.sname[q.ncons]) {MemoryError("array of names for displayed sequences");}
strcpy(q.sname[q.ncons],"Consensus");
q.seq[q.ncons]=new char[L+2];
if (!q.seq[q.ncons]) {MemoryError("array of names for displayed sequences");}
}
if (par.cons)
{
// Reserve space for consensus sequence as first sequence in alignment
q.nfirst=n++; kfirst=-1;
q.sname[q.nfirst]=new char[strlen(name)+11];
if (!q.sname[q.nfirst]) {MemoryError("array of names for displayed sequences");}
strcpy(q.sname[q.nfirst],name);
strcat(q.sname[q.nfirst],"_consensus");
q.seq[q.nfirst]=new char[L+2];
if (!q.seq[q.nfirst]) {MemoryError("array of names for displayed sequences");}
}
// Calculate consensus amino acids using similarity matrix
for (i=1; i<=L; i++)
{
maxw=0.0; maxa=0;
for (a=0; a<20; a++)
if (q.f[i][a]-pb[a]>maxw) {maxw = q.f[i][a]-pb[a]; maxa = a;}
if (par.showcons)
{
maxw =0.0;
for (int b=0; b<20; b++) maxw += q.f[i][b]*Sim[maxa][b]*Sim[maxa][b];
maxw *= q.Neff_M[i]/(q.Neff_HMM+1); // columns with many gaps don't get consensus symbol
if (maxw>0.6) q.seq[q.ncons][i] = uprchr(i2aa(maxa));
else if (maxw>0.4) q.seq[q.ncons][i] = lwrchr(i2aa(maxa));
else q.seq[q.ncons][i] = 'x';
}
if (par.cons) q.seq[q.nfirst][i] = uprchr(i2aa(maxa));
}
if (par.showcons)
{
q.seq[q.ncons][0]='-';
q.seq[q.ncons][L+1]='\0';
}
if (par.cons)
{
q.seq[q.nfirst][0]='-';
q.seq[q.nfirst][L+1]='\0';
}
}
// Copy sequences to be displayed from alignment to HMM
for (k=0; k<N_in; k++)
{
int nn;
if (display[k])
{
if (0 && (n>=MAXSEQDIS)) {
/* FIXME: the test was if(n>=MAXSEQDIS),
this test was necessary because alignment memory was static,
now it should be dynamic, and should always have the right size,
there are at least number-of-sequences plus a 'bit' more
however, I do not know what that 'bit' is likely to be (in the future).
at the moment it is 1 for the consnseus and 1 for structure,
but this might change (FS)
*/
if (par.mark) cerr<<"WARNING: maximum number "<<MAXSEQDIS<<" of sequences for display of alignment exceeded\n";
break;
}
if (k==kss_dssp) nn=q.nss_dssp; // copy dssp sequence to nss_dssp
else if (k==ksa_dssp) nn=q.nsa_dssp;
else if (k==kss_pred) nn=q.nss_pred;
else if (k==kss_conf) nn=q.nss_conf;
else if (k==kfirst) nn=q.nfirst=n++;
else nn=n++;
// strcut(sname[k]," "); // delete rest of name line beginning with two spaces " " // Why this?? Problem for pdb seqs without chain
q.sname[nn]=new char[strlen(sname[k])+1];
if (!q.sname[nn]) {MemoryError("array of names for displayed sequences");}
strcpy(q.sname[nn],sname[k]);
q.seq[nn]=new char[strlen(seq[k])+1];
if (!q.seq[nn]) {MemoryError("array of names for displayed sequences");}
strcpy(q.seq[nn],seq[k]);
}
}
q.n_display=n; // how many sequences to be displayed in alignments?
// Copy secondary structure information into HMM
if (kss_dssp>=0)
for (i=1; i<=L; i++) q.ss_dssp[i]=X[kss_dssp][i];
if (ksa_dssp>=0)
for (i=1; i<=L; i++) q.sa_dssp[i]=X[ksa_dssp][i];
if (kss_pred>=0)
{
for (i=1; i<=L; i++) q.ss_pred[i]=X[kss_pred][i];
if (kss_conf>=0)
for (i=1; i<=L; i++) q.ss_conf[i]=X[kss_conf][i];
else
for (i=1; i<=L; i++) q.ss_conf[i]=5;
}
q.lamda=0.0;
q.mu=0.0;
// Debug: print occurence of amino acids for each position i
if (v>=2) printf("Effective number of sequences exp(entropy) = %-4.1f\n",q.Neff_HMM); //PRINT
if (v>=3)
{
cout<<"\nMatr: ";
for (a=0; a<20; a++) printf("%4.1f ",100*pb[a]);
cout<<"\nAmino acid frequencies without pseudocounts:\n";
cout<<" A R N D C Q E G H I L K M F P S T W Y V\n";
for (i=1; i<=L; i++)
{
printf("%3i: ",i);
for (a=0; a<20; a++) printf("%4.0f ",100*q.f[i][a]);
cout<<endl;
}
cout<<"\n";
printf("\nListing transition probabilities without pseudocounts:\n");
printf(" i M->M M->I M->D I->M I->I D->M D->D Neff_M Neff_I Neff_D\n");
for (i=0; i<=L; i++)
{
printf("%4i %6.3f %6.3f %6.3f ",i,pow(2.0,q.tr[i][M2M]),pow(2.0,q.tr[i][M2I]),pow(2.0,q.tr[i][M2D]));
printf("%6.3f %6.3f ",pow(2.0,q.tr[i][I2M]),pow(2.0,q.tr[i][I2I]));
printf("%6.3f %6.3f ",pow(2.0,q.tr[i][D2M]),pow(2.0,q.tr[i][D2D]));
printf("%6.3f %6.3f %6.3f\n",q.Neff_M[i],q.Neff_I[i],q.Neff_D[i]);
}
}
q.trans_lin=0;
q.has_pseudocounts=false; /* MR1 */
return;
}
/////////////////////////////////////////////////////////////////////////////////////
/*
* FIXME: one of the most time consuming routines (according to gprof on r112)
*/
/**
* @brief Calculate freqs q.f[i][a] and transitions q.tr[i][a] (a=MM,MI,MD) with pos-specific subalignments
* Pos-specific weights are calculated like in "GetPositionSpecificWeights()"
*/
void
Alignment::Amino_acid_frequencies_and_transitions_from_M_state(HMM& q, char* in)
{
// Calculate position-dependent weights wi[k] for each i.
// For calculation of weights in column i use sub-alignment
// over sequences which have a *residue* in column i (no gap, no end gap)
// and over columns where none of these sequences has an end gap.
// This is done by updating the arrays n[j][a] at each step i-1->i while letting i run from 1 to L.
// n[j][a] = number of occurences of amino acid a at column j of the subalignment,
// => only columns with n[j][ENDGAP]=0 are contained in the subalignment!
// If no sequences enter or leave the subalignment at the step i-1 -> i (i.e. change=0)
// then the old values wi[k], Neff[i-1], and ncol are used for the new position i.
// Index a can be an amino acid (0-19), ANY=20, GAP=21, or ENDGAP=22
int k; // index of sequence
int i,j; // position in alignment
int a; // amino acid (0..19)
int naa; // number of different amino acids
int** n; // n[j][a] = number of seq's with some residue at column i AND a at position j
//float wi[MAXSEQ]; // weight of sequence k in column i, calculated from subalignment i
float *wi=NULL; // weight of sequence k in column i, calculated from subalignment i
//float Neff[MAXRES]; // diversity of subalignment i
float *Neff = new float[par.maxResLen]; // diversity of subalignment i
int nseqi=0; // number of sequences in subalignment i
int ncol=0; // number of columns j that contribute to Neff[i]
char change; // has the set of sequences in subalignment changed? 0:no 1:yes
float fj[NAA+3]; // to calculate entropy
float sum;
wi = new float[N_in+2];
// Global weights?
if (par.wg==1)
for (k=0; k<N_in; k++)
wi[k]=wg[k];
// Initialization
q.Neff_HMM=0.0f;
Neff[0]=0.0; // if the first column has no residues (i.e. change==0), Neff[i]=Neff[i-1]=Neff[0]
n = new int*[L+2];
//#if 0
#ifdef HAVE_OPENMP
#pragma omp parallel for schedule(static) private(a)
#endif
for (j=1; j<=L; j++) {
n[j]=new(int[NAA+3]);
for (a=0; a<NAA+3; a++)
n[j][a]=0;
}
//////////////////////////////////////////////////////////////////////////////////////////////
// Main loop through alignment columns
for (i=1; i<=L; i++) // Calculate wi[k] at position i as well as Neff[i]
{
if (par.wg==0)
{
change=0;
// Check all sequences k and update n[j][a] and ri[j] if necessary
for (k=0; k<N_in; k++)
{
if (!in[k]) continue;
if (X[k][i-1]>=ANY && X[k][i]<ANY)
{ // ... if sequence k was NOT included in i-1 and has to be included for column i
change=1;
nseqi++;
//#if 0
#ifdef HAVE_OPENMP
#pragma omp parallel for schedule(static)
#endif
for (int j=1; j<=L; j++)
n[j][ (int)X[k][j]]++;
}
else if (X[k][i-1]<ANY && X[k][i]>=ANY)
{ // ... if sequence k WAS included in i-1 and has to be thrown out for column i
change=1;
nseqi--;
//#if 0
#ifdef HAVE_OPENMP
#pragma omp parallel for schedule(static)
#endif
for (int j=1; j<=L; j++)
n[j][ (int)X[k][j]]--;
}
} //end for (k)
nseqs[i]=nseqi;
// If subalignment changed: update weights wi[k] and Neff[i]
if (change)
{
// Initialize weights and numbers of residues for subalignment i
ncol=0;
for (k=0; k<N_in; k++)
wi[k]=1E-8; // for pathological alignments all wi[k] can get 0; /* MR1 */
// sum wi[k] over all columns j and sequences k of subalignment
//#if 0
#ifdef HAVE_OPENMP
#pragma omp parallel for schedule(static) private(naa, a, k)
#endif
for (j=1; j<=L; j++)
{
// do at least a fraction MAXENDGAPFRAC of sequences in subalignment contain an end gap in j?
if (n[j][ENDGAP]>MAXENDGAPFRAC*nseqi) continue;
naa=0;
for (a=0; a<20; a++)
if(n[j][a])
naa++;
if (naa==0) continue;
//#if 0
#ifdef HAVE_OPENMP
#pragma omp atomic
#endif
ncol++;
for (k=0; k<N_in; k++)
{
if (in[k] && X[k][i]<ANY && X[k][j]<ANY)
{
// if (!n[j][ (int)X[k][j]]) {fprintf(stderr,"Error: Mi=%i: n[%i][X[%i]]=0! (X[%i]=%i)\n",i,j,k,k,X[k][j]);}
//#if 0
#ifdef HAVE_OPENMP
#pragma omp atomic
#endif
wi[k]+=1.0/float(n[j][ (int)X[k][j] ]*naa);
}
}
} // end for (j)
// Check whether number of columns in subalignment is sufficient
if (ncol<NCOLMIN)
// Take global weights
for (k=0; k<N_in; k++)
if(in[k] && X[k][i]<ANY)
wi[k]=wg[k];
else wi[k]=0.0;
// Calculate Neff[i]
Neff[i]=0.0;
//#if 0
#ifdef HAVE_OPENMP
#pragma omp parallel for schedule(static) private(a, k, fj)
#endif
for (j=1; j<=L; j++)
{
// do at least a fraction MAXENDGAPFRA of sequences in subalignment contain an end gap in j?
if (n[j][ENDGAP]>MAXENDGAPFRAC*nseqi) continue;
for (a=0; a<20; a++) fj[a]=0;
for (k=0; k<N_in; k++)
if (in[k] && X[k][i]<ANY && X[k][j]<ANY)
fj[ (int)X[k][j] ]+=wi[k];
NormalizeTo1(fj,NAA);
for (a=0; a<20; a++)
if (fj[a]>1E-10)
//#if 0
#ifdef HAVE_OPENMP
#pragma omp atomic
#endif
Neff[i]-=fj[a]*fast_log2(fj[a]);
}
if (ncol>0)
Neff[i]=pow(2.0,Neff[i]/ncol);
else
Neff[i]=1.0;
} // end change
else //no update was necessary; copy values for i-1
{
Neff[i]=Neff[i-1];
}
} // end par.wg==0
// Calculate amino acid frequencies q.f[i][a] from weights wi[k]
for (a=0; a<20; a++)
q.f[i][a]=0;
for (k=0; k<N_in; k++)
if (in[k])
q.f[i][ (int)X[k][i] ]+=wi[k];
NormalizeTo1(q.f[i],NAA,pb);
// Calculate transition probabilities from M state
q.tr[i][M2M]=q.tr[i][M2D]=q.tr[i][M2I]=0.0;
for (k=0; k<N_in; k++) //for all sequences
{
if (!in[k]) continue;
//if input alignment is local ignore transitions from and to end gaps
if (X[k][i]<ANY) //current state is M
{
if (I[k][i]) //next state is I
q.tr[i][M2I]+=wi[k];
else if (X[k][i+1]<=ANY) //next state is M
q.tr[i][M2M]+=wi[k];
else if (X[k][i+1]==GAP) //next state is D
q.tr[i][M2D]+=wi[k];
}
} // end for(k)
// Normalize and take log
sum = q.tr[i][M2M]+q.tr[i][M2I]+q.tr[i][M2D]+FLT_MIN;
q.tr[i][M2M]=Log2(q.tr[i][M2M]/sum);
q.tr[i][M2I]=Log2(q.tr[i][M2I]/sum);
q.tr[i][M2D]=Log2(q.tr[i][M2D]/sum);
// for (k=0; k<N_in; k++) if (in[k]) w[k][i]=wi[k];
} // end loop through alignment columns i
// DD TODO:fill in all the missing Neff values
//////////////////////////////////////////////////////////////////////////////////////////////
delete[](wi); wi=NULL;
// delete n[][]
for (j=1; j<=L; j++){
delete[](n[j]);
(n[j]) = NULL;
}
delete[](n); (n) = NULL;
q.tr[0][M2M]=0;
q.tr[0][M2I]=-100000;
q.tr[0][M2D]=-100000;
q.tr[L][M2M]=0;
q.tr[L][M2I]=-100000;
q.tr[L][M2D]=-100000;
q.Neff_M[0]=99.999; // Neff_av[0] is used for calculation of transition pseudocounts for the start state
// Set emission probabilities of zero'th (begin) state and L+1st (end) state to background probabilities
for (a=0; a<20; a++)
q.f[0][a]=q.f[L+1][a]=pb[a];
// Assign Neff_M[i] and calculate average over alignment, Neff_M[0]
if (par.wg==1)
{
//#if 0
#ifdef HAVE_OPENMP
#pragma omp parallel for schedule(static) private(a)
#endif
for (i=1; i<=L; i++)
{
float sum=0.0f;
for (a=0; a<20; a++)
if (q.f[i][a]>1E-10)
sum -= q.f[i][a]*fast_log2(q.f[i][a]);
//#if 0
#ifdef HAVE_OPENMP
#pragma omp atomic
#endif
q.Neff_HMM+=pow(2.0,sum);
}
q.Neff_HMM/=L;
float Nlim=fmax(10.0,q.Neff_HMM+1.0); // limiting Neff
float scale=Log2((Nlim-q.Neff_HMM)/(Nlim-1.0)); // for calculating Neff for those seqs with inserts at specific pos
//#if 0
#ifdef HAVE_OPENMP
#pragma omp parallel for schedule(static) private(k)
#endif
for (i=1; i<=L; i++)
{
float w_M=-1.0/N_filtered;
for (k=0; k<N_in; k++)
if (in[k] && X[k][i]<=ANY)
w_M+=wg[k];
if (w_M<0)
q.Neff_M[i]=1.0;
else
q.Neff_M[i] = Nlim - (Nlim-1.0)*fpow2(scale*w_M);
// fprintf(stderr,"M i=%3i ncol=--- Neff_M=%5.2f Nlim=%5.2f w_M=%5.3f Neff_M=%5.2f\n",i,q.Neff_HMM,Nlim,w_M,q.Neff_M[i]);
}
}
else
{
for (i=1; i<=L; i++)
{
q.Neff_HMM+=Neff[i];
q.Neff_M[i]=Neff[i];
if (q.Neff_M[i] == 0) {
q.Neff_M[i] = 1;
} /* MR1 */
}
q.Neff_HMM/=L;
} // end par.wg==1
delete[] Neff; Neff = NULL;
return;
} /* this is the end of Alignment::Amino_acid_frequencies_and_transitions_from_M_state() */
/////////////////////////////////////////////////////////////////////////////////////
/**
* @brief Calculate transitions q.tr[i][a] (a=DM,DD) with pos-specific subalignments
*/
void
Alignment::Transitions_from_I_state(HMM& q, char* in)
{
// Calculate position-dependent weights wi[k] for each i.
// For calculation of weights in column i use sub-alignment
// over sequences which have a INSERT in column i
// and over columns where none of these sequences has an end gap.
// This is done by calculating the arrays n[j][a] and rj[j] at each step i-1->i while letting i run from 1 to L.
// n[j][a] = number of occurences of amino acid a at column j of the subalignment,
// => only columns with n[j][ENDGAP]=0 are contained in the subalignment!
// If no sequences enter or leave the subalignment at the step i-1 -> i (i.e. change=0)
// then the old values wi[k], Neff[i-1], and ncol are used for the new position i.
// Index a can be an amino acid (0-19), ANY=20, GAP=21, or ENDGAP=22
int k; // index of sequence
int i,j; // position in alignment
int a; // amino acid (0..19)
int naa; // number of different amino acids
int** n; // n[j][a] = number of seq's with some residue at column i AND a at position j
//float wi[MAXSEQ]; // weight of sequence k in column i, calculated from subalignment i
float *wi = NULL; // weight of sequence k in column i, calculated from subalignment i
//float Neff[MAXRES]; // diversity of subalignment i
float *Neff = new float[par.maxResLen]; // diversity of subalignment i
int nseqi; // number of sequences in subalignment i
int ncol; // number of columns j that contribute to Neff[i]
float fj[NAA+3]; // to calculate entropy
float sum;
float Nlim=0.0; // only for global weights
float scale=0.0; // only for global weights
wi = new float[N_in+2];
// Global weights?
if (par.wg==1)
{
for (k=0; k<N_in; k++) wi[k]=wg[k];
Nlim=fmax(10.0,q.Neff_HMM+1.0); // limiting Neff
scale=Log2((Nlim-q.Neff_HMM)/(Nlim-1.0)); // for calculating Neff for those seqs with inserts at specific pos
}
// Initialization
n = new int*[L+2];
for (j=1; j<=L; j++) n[j]=new(int[NAA+3]);
//////////////////////////////////////////////////////////////////////////////////////////////
// Main loop through alignment columns
for (i=1; i<=L; i++) // Calculate wi[k] at position i as well as Neff[i]
{
if (par.wg==0) // local weights?
{
// Calculate n[j][a] and ri[j]
nseqi=0;
for (k=0; k<N_in; k++)
{
if (in[k] && I[k][i]>0)
{
if (nseqi==0) // Initialize only if inserts present! Otherwise O(L*L) even for single sequences!
{
// Initialization of n[j][a]
for (j=1; j<=L; j++)
for (a=0; a<NAA+3; a++) n[j][a]=0;
}
nseqi++;
for (int j=1; j<=L; j++) n[j][ (int)X[k][j]]++;
}
} //end for (k)
nseqs[i]=nseqi;
// If there is no sequence in subalignment j ...
if (nseqi==0)
{
ncol=0;
Neff[i]=0.0; // effective number of sequence = 0!
q.tr[i][I2M]=-100000;
q.tr[i][I2I]=-100000;
continue;
}
// update weights wi[k] and Neff[i]
// if (1)
{
// Initialize weights and numbers of residues for subalignment i
ncol=0;
for (k=0; k<N_in; k++) wi[k]=0.0;
// sum wi[k] over all columns j and sequences k of subalignment
for (j=1; j<=L; j++)
{
if (n[j][ENDGAP]>MAXENDGAPFRAC*nseqi) continue;
naa=0; for (a=0; a<20; a++) if(n[j][a]) naa++;
if (naa==0) continue;
ncol++;
for (k=0; k<N_in; k++)
{
if (in[k] && I[k][i]>0 && X[k][j]<ANY)
{
if (!n[j][ (int)X[k][j]]) {fprintf(stderr,"Error: Ii=%i: n[%i][X[%i]]=0! (X[%i]=%i)\n",i,j,k,k,X[k][j]);}
wi[k]+=1.0/float(n[j][ (int)X[k][j] ]*naa);
}
}
}
// Check whether number of columns in subalignment is sufficient
if (ncol>=NCOLMIN)
// Take global weights
for (k=0; k<N_in; k++)
if(in[k] && I[k][i]>0) wi[k]=wg[k]; else wi[k]=0.0;
// Calculate Neff[i]
Neff[i]=0.0;
for (j=1; j<=L; j++)
{
if (n[j][ENDGAP]>MAXENDGAPFRAC*nseqi) continue;
for (a=0; a<20; a++) fj[a]=0;
for (k=0; k<N_in; k++)
if (in[k] && I[k][i]>0 && X[k][j]<ANY)
fj[ (int)X[k][j] ]+=wi[k];
NormalizeTo1(fj,NAA);
for (a=0; a<20; a++)
if (fj[a]>1E-10) Neff[i]-=fj[a]*fast_log2(fj[a]);
}
if (ncol>0) Neff[i]=pow(2.0,Neff[i]/ncol); else Neff[i]=1.0;
}
// Calculate transition probabilities from I state
q.tr[i][I2M]=q.tr[i][I2I]=0.0;
for (k=0; k<N_in; k++) //for all sequences
{
if (in[k] && I[k][i]>0) //current state is I
{
q.tr[i][I2M]+=wi[k];
q.tr[i][I2I]+=wi[k]*(I[k][i]-1);
}
} // end for(k)
}
else // fast global weights?
{
float w_I=-1.0/N_filtered;
ncol=0;
q.tr[i][I2M]=q.tr[i][I2I]=0.0;
// Calculate amino acid frequencies fj[a] from weights wg[k]
for (k=0; k<N_in; k++)
if (in[k] && I[k][i]>0)
{
ncol++;
w_I+=wg[k];
q.tr[i][I2M]+=wi[k];
q.tr[i][I2I]+=wi[k]*(I[k][i]-1);
}
if (ncol>0)
{
if (w_I<0) Neff[i]=1.0;
else Neff[i] = Nlim - (Nlim-1.0)*fpow2(scale*w_I);
// fprintf(stderr,"I i=%3i ncol=%3i Neff_M=%5.2f Nlim=%5.2f w_I=%5.3f Neff_I=%5.2f\n",i,ncol,q.Neff_HMM,Nlim,w_I,Neff[i]);
}
else
{
Neff[i]=0.0;
q.tr[i][I2M]=-100000;
q.tr[i][I2I]=-100000;
continue;
}
}
// Normalize and take log
sum = q.tr[i][I2M]+q.tr[i][I2I];
q.tr[i][I2M]=Log2(q.tr[i][I2M]/sum);
q.tr[i][I2I]=Log2(q.tr[i][I2I]/sum);
}
// end loop through alignment columns i
//////////////////////////////////////////////////////////////////////////////////////////////
delete[](wi); wi = NULL;
// delete n[][]
for (j=1; j<=L; j++){
delete[](n[j]); (n[j]) = NULL;
}
delete[](n); (n) = NULL;
q.tr[0][I2M]=0;
q.tr[0][I2I]=-100000;
q.tr[L][I2M]=0;
q.tr[L][I2I]=-100000;
q.Neff_I[0]=99.999;
// Assign Neff_I[i]
for (i=1; i<=L; i++) // Calculate wi[k] at position i as well as Neff[i] and Neff[i]
q.Neff_I[i]=Neff[i];
delete[] Neff; Neff = NULL;
return;
} /* this is the end of Alignment::Transitions_from_I_state() */
/////////////////////////////////////////////////////////////////////////////////////
/**
* @brief Calculate transitions q.tr[i][a] (a=DM,DD) with pos-specific subalignments
*/
void
Alignment::Transitions_from_D_state(HMM& q, char* in)
{
// Calculate position-dependent weights wi[k] for each i.
// For calculation of weights in column i use sub-alignment
// over sequences which have a DELETE in column i
// and over columns where none of these sequences has an end gap.
// This is done by updating the arrays n[j][a] and rj[j] at each step i-1->i while letting i run from 1 to L.
// n[j][a] = number of occurences of index a at column j of the subalignment,
// => only columns with n[j][ENDGAP]=0 are contained in the subalignment!
// If no sequences enter or leave the subalignment at the step i-1 -> i (i.e. change=0)
// then the old values wi[k], Neff[i-1], and ncol are used for the new position i.
// Index a can be an amino acid (0-19), ANY=20, GAP=21, or ENDGAP=22
int k; // index of sequence
int i,j; // position in alignment
int a; // amino acid (0..19)
int naa; // number of different amino acids
int** n; // n[j][a] = number of seq's with some residue at column i AND a at position j
//float wi[MAXSEQ]; // weight of sequence k in column i, calculated from subalignment i
float *wi=NULL; // weight of sequence k in column i, calculated from subalignment i
//float Neff[MAXRES]; // diversity of subalignment i
float *Neff = new float[par.maxResLen]; // diversity of subalignment i
int nseqi=0; // number of sequences in subalignment i (for DEBUGGING)
int ncol=0; // number of columns j that contribute to Neff[i]
char change; // has the set of sequences in subalignment changed? 0:no 1:yes
float fj[NAA+3]; // to calculate entropy
float sum;
float Nlim=0.0; // only for global weights
float scale=0.0; // only for global weights
wi = new float[N_in+2]; /* FIXME: FS */
// Global weights?
if (par.wg==1)
{
for (k=0; k<N_in; k++)
wi[k]=wg[k];
Nlim=fmax(10.0,q.Neff_HMM+1.0); // limiting Neff
scale=Log2((Nlim-q.Neff_HMM)/(Nlim-1.0)); // for calculating Neff for those seqs with dels at specific pos
}
// Initialization
n = new int*[L+2];
//#if 0
#ifdef HAVE_OPENMP
#pragma omp parallel for schedule(static) private(a)
#endif
for (j=1; j<=L; j++) {
n[j]=new(int[NAA+3]);
for (a=0; a<NAA+3; a++)
n[j][a]=0;
}
//////////////////////////////////////////////////////////////////////////////////////////////
// Main loop through alignment columns
for (i=1; i<=L; i++) // Calculate wi[k] at position i as well as Neff[i]
{
if (par.wg==0) // if local weights
{
change=0;
// Check all sequences k and update n[j][a] and ri[j] if necessary
for (k=0; k<N_in; k++)
{
if (!in[k]) continue;
if (X[k][i-1]!=GAP && X[k][i]==GAP)
{ // ... if sequence k was NOT included in i-1 and has to be included for column i
change=1;
nseqi++;
//#if 0
#ifdef HAVE_OPENMP
#pragma omp parallel for schedule(static)
#endif
for (int j=1; j<=L; j++)
n[j][ (int)X[k][j]]++;
}
else if (X[k][i-1]==GAP && X[k][i]!=GAP)
{ // ... if sequence k WAS included in i-1 and has to be thrown out for column i
change=1;
nseqi--;
//#if 0
#ifdef HAVE_OPENMP
#pragma omp parallel for schedule(static)
#endif
for (int j=1; j<=L; j++)
n[j][ (int)X[k][j]]--;
}
} //end for (k)
nseqs[i]=nseqi;
// If there is no sequence in subalignment j ...
if (nseqi==0)
{
ncol=0;
Neff[i]=0.0; // effective number of sequences = 0!
q.tr[i][D2M]=-100000;
q.tr[i][D2D]=-100000;
continue;
}
// If subalignment changed: update weights wi[k] and Neff[i]
if (change)
{
// Initialize weights and numbers of residues for subalignment i
ncol=0;
for (k=0; k<N_in; k++)
wi[k]=0.0;
// sum wg[k][i] over all columns j and sequences k of subalignment
//#if 0
#ifdef HAVE_OPENMP
#pragma omp parallel for schedule(static) private(naa, a, k)
#endif
for (j=1; j<=L; j++)
{
if (n[j][ENDGAP]>MAXENDGAPFRAC*nseqi) continue;
naa=0;
for (a=0; a<20; a++)
if(n[j][a])
naa++;
if (naa==0) continue;
//#if 0
#ifdef HAVE_OPENMP
#pragma omp atomic
#endif
ncol++;
for (k=0; k<N_in; k++)
{
if (in[k] && X[k][i]==GAP && X[k][j]<ANY)
{
if (!n[j][ (int)X[k][j]]) {fprintf(stderr,"Error: Di=%i: n[%i][X[%i]]=0! (X[%i]=%i)\n",i,j,k,k,X[k][j]);}
//#if 0
#ifdef HAVE_OPENMP
#pragma omp atomic
#endif
wi[k]+=1.0/float(n[j][ (int)X[k][j] ]*naa);
}
}
} // end for (j)
// Check whether number of columns in subalignment is sufficient
if (ncol<NCOLMIN)
// Take global weights
for (k=0; k<N_in; k++)
if(in[k] && X[k][i]==GAP)
wi[k]=wg[k];
else
wi[k]=0.0;
// Calculate Neff[i]
Neff[i]=0.0;
//#if 0
#ifdef HAVE_OPENMP
#pragma omp parallel for schedule(static) private(a, k, fj)
#endif
for (j=1; j<=L; j++)
{
if (n[j][ENDGAP]>MAXENDGAPFRAC*nseqi) continue;
for (a=0; a<20; a++) fj[a]=0;
for (k=0; k<N_in; k++)
if (in[k] && X[k][i]==GAP && X[k][j]<ANY)
fj[ (int)X[k][j] ]+=wi[k];
NormalizeTo1(fj,NAA);
for (a=0; a<20; a++)
if (fj[a]>1E-10)
//#if 0
#ifdef HAVE_OPENMP
#pragma omp atomic
#endif
Neff[i]-=fj[a]*fast_log2(fj[a]);
}
if (ncol>0) Neff[i]=pow(2.0,Neff[i]/ncol); else Neff[i]=1.0;
}
else //no update was necessary; copy values for i-1
{
Neff[i]=Neff[i-1];
}
// Calculate transition probabilities from D state
q.tr[i][D2M]=q.tr[i][D2D]=0.0;
for (k=0; k<N_in; k++) //for all sequences
{
if (in[k] && X[k][i]==GAP) //current state is D
{
if (X[k][i+1]==GAP) //next state is D
q.tr[i][D2D]+=wi[k];
else if (X[k][i+1]<=ANY) //next state is M
q.tr[i][D2M]+=wi[k];
}
} // end for(k)
}
else // fast global weights?
{
float w_D=-1.0/N_filtered;
ncol=0;
q.tr[i][D2M]=q.tr[i][D2D]=0.0;
// Calculate amino acid frequencies fj[a] from weights wg[k]
for (k=0; k<N_in; k++) //for all sequences
if (in[k] && X[k][i]==GAP) //current state is D
{
ncol++;
w_D+=wg[k];
if (X[k][i+1]==GAP) //next state is D
q.tr[i][D2D]+=wi[k];
else if (X[k][i+1]<=ANY) //next state is M
q.tr[i][D2M]+=wi[k];
}
if (ncol>0)
{
if (w_D<0) Neff[i]=1.0;
else Neff[i] = Nlim - (Nlim-1.0)*fpow2(scale*w_D);
// fprintf(stderr,"D i=%3i ncol=%3i Neff_M=%5.2f Nlim=%5.2f w_D=%5.3f Neff_D=%5.2f\n",i,ncol,q.Neff_HMM,Nlim,w_D,Neff[i]);
}
else
{
Neff[i]=0.0; // effective number of sequences = 0!
q.tr[i][D2M]=-100000;
q.tr[i][D2D]=-100000;
continue;
}
}
// Normalize and take log
sum = q.tr[i][D2M]+q.tr[i][D2D];
q.tr[i][D2M]=Log2(q.tr[i][D2M]/sum);
q.tr[i][D2D]=Log2(q.tr[i][D2D]/sum);
}
// end loop through alignment columns i
//////////////////////////////////////////////////////////////////////////////////////////////
q.tr[0][D2M]=0;
q.tr[0][D2D]=-100000;
q.Neff_D[0]=99.999;
// Assign Neff_D[i]
for (i=1; i<=L; i++) {
q.Neff_D[i]=Neff[i];
delete[](n[i]);
(n[i]) = NULL;
}
delete[](n); (n) = NULL;
delete[](wi); wi = NULL;/* FIXME: FS */
delete[] Neff; Neff = NULL;
return;
} /* this is the end of Alignment::Transitions_from_D_state() */
/////////////////////////////////////////////////////////////////////////////////////
/**
* @brief Write alignment without insert states (lower case) to alignment file?
*/
void
Alignment::WriteWithoutInsertsToFile(char* alnfile)
{
if (v>=2) cout<<"Writing alignment to "<<alnfile<<"\n";
FILE* alnf;
if (!par.append) alnf = fopen(alnfile,"w"); else alnf = fopen(alnfile,"a");
if (!alnf) OpenFileError(alnfile);
// If alignment name is different from that of query: write name into commentary line
if (strncmp(longname,sname[kfirst],DESCLEN-1)) fprintf(alnf,"#%s\n",longname);
if (v>=2) cout<<"Writing alignment to "<<alnfile<<"\n";
for (int k=0; k<N_in; k++)
if (keep[k] || display[k]==KEEP_ALWAYS) // print if either in profile (keep[k]>0) or display is obligatory (display[k]==2)
{
fprintf(alnf,">%s\n",sname[k]);
for (int i=1; i<=L; i++) fprintf(alnf,"%c",i2aa(X[k][i]));
fprintf(alnf,"\n");
}
fclose(alnf);
}
/////////////////////////////////////////////////////////////////////////////////////
// Write stored,filtered sequences WITH insert states (lower case) to alignment file?
/////////////////////////////////////////////////////////////////////////////////////
void Alignment::WriteToFile(char* alnfile, const char format[])
{
FILE* alnf;
if (!par.append) alnf = fopen(alnfile,"w"); else alnf = fopen(alnfile,"a");
if (!alnf) OpenFileError(alnfile);
// If alignment name is different from that of query: write name into commentary line
if (strncmp(longname,sname[kfirst],DESCLEN-1)) fprintf(alnf,"#%s\n",longname);
if (!format || !strcmp(format,"a3m"))
{
if (v>=2) cout<<"Writing A3M alignment to "<<alnfile<<"\n";
for (int k=0; k<N_in; k++)
if (keep[k] || display[k]==KEEP_ALWAYS) // print if either in profile (keep[k]>0) or display obligatory (display[k]==2)
fprintf(alnf,">%s\n%s\n",sname[k],seq[k]+1);
}
else // PSI-BLAST format
{
if (v>=2) cout<<"Writing PSI-BLAST-formatted alignment to "<<alnfile<<"\n";
for (int k=kfirst; k<N_in; k++) // skip sequences before kfirst!!
if (keep[k] || display[k]==KEEP_ALWAYS) // print if either in profile (keep[k]>0) or display obligatory (display[k]==2)
{
strcut(sname[k]);
fprintf(alnf,"%-20.20s ",sname[k]);
// for (int i=1; i<=L; i++) fprintf(alnf,"%c",i2aa(X[k][i]));
// fprintf(alnf,"\n");
char* ptr=seq[k];
for (; *ptr!='\0'; ptr++)
if (*ptr==45 || (*ptr>=65 && *ptr<=90)) fprintf(alnf,"%c",*ptr);
fprintf(alnf,"\n");
}
}
fclose(alnf);
}
/*
* FIXME: this function contains a reference to MAXSEQ & MAXCOL
* however, this may not be accessed (FS)
*/
/////////////////////////////////////////////////////////////////////////////////////
/**
* @brief Read a3m slave alignment of hit from file and merge into (query) master alignment
*/
void
Alignment::MergeMasterSlave(Hit& hit, char ta3mfile[])
{
Alignment Tali;
char* cur_seq = new(char[MAXCOL]); // Sequence currently read in
int maxcol=MAXCOL;
int l,ll; // position in unaligned template (T) sequence Tali.seq[l]
int i; // counts match states in query (Q) HMM
int j; // counts match states in T sequence Tali.seq[l]
int h; // position in aligned T sequence cur_seq[h]
int k; // sequence index
char c; //
printf("****************%s:%s:%d: did get into MergeMasterSlave\n", __FUNCTION__, __FILE__, __LINE__);
if (v>=3) printf("Merging %s to query alignment\n",ta3mfile);
// If par.append==1 do not print query alignment
if (par.append) for (k=0; k<N_in; k++) keep[k]=display[k]=KEEP_NOT;
// Read template alignment into Tali
FILE* ta3mf=fopen(ta3mfile,"r");
if (!ta3mf) OpenFileError(ta3mfile);
Tali.Read(ta3mf,ta3mfile);
fclose(ta3mf);
// Filter Tali alignment
Tali.Compress(ta3mfile);
N_filtered = Tali.Filter(par.max_seqid,par.coverage,par.qid,par.qsc,par.Ndiff);
// Record imatch[j]
int* imatch=new int[hit.j2+1];
int step = hit.nsteps;
for (j=hit.j1; j<=hit.j2; j++)
{
// Advance to position of next T match state j
while (hit.j[step]<j) step--;
imatch[j] = hit.i[step];
// printf("step=%-3i i=%-3i j=%-3i\n",step,imatch[j],j);
}
// Determine number of match states of Qali
for (L=0,l=1; seq[kfirst][l]>'\0'; l++)
if ((seq[kfirst][l]>='A' && seq[kfirst][l]<='Z') || seq[kfirst][l]=='-') L++;
// For each sequence in T alignment: align to Qali
for (k=0; k<Tali.N_in; k++)
{
if (!Tali.keep[k]) continue;
if (N_in>=MAXSEQ)
{
fprintf(stderr,"WARNING in %s: maximum number of %i sequences exceeded while reading %s. Skipping all following sequences\n",program_name,MAXSEQ,ta3mfile);
break;
}
cur_seq[0]=' '; // 0'th position not used
// Add the hit.i1-1 left end gaps to aligned sequence
for (h=1; h<hit.i1; h++) cur_seq[h]='-';
// Advance to match state hit.j1 of Tali.seq[k]
for (j=0, l=1; (c=Tali.seq[k][l])>'\0'; l++)
if ((c>='A' && c<='Z') || c=='-') // match state at position l?
if ((++j)==hit.j1) break; // yes: increment j. Reached hit,j1? yes: break
if (j<hit.j1)
{printf("Error: did not find %i match states in sequence %i of %s. Sequence:\n%s\n",hit.j1,k,Tali.name,Tali.seq[k]); exit(1);}
// Write first match state to cur_seq
int iprev=hit.i1; // index of previous query match state
int lprev=l; // previous T match state in Tali.seq[k][l]
cur_seq[h++] = Tali.seq[k][l]; // first column of alignment is Match-Match state
// For each further match state j in alignment
step = hit.nsteps;
for (j=hit.j1+1; j<=hit.j2; j++)
{
// Advance to position of next T match state j
i=imatch[j];
// Advance to position of next T match state j
while ((c=Tali.seq[k][++l])>'\0' && ((c>='a' && c<='z') || c=='.')) ;
int di=i-iprev; // number of Match states in Q between T match state j-1 and j
int dl=l-lprev; // 1 + number of inserted residues in T sequence between T match state j-1 and j
if (di==1)
{
// One Q match state for one T match state (treated as special case for speed reasons)
// i: i-1 i di=1
// Q: XXXXXX.....XXXXXX
// T: YYYYYYyyyyyYYYYYY
// j: j-1 j
// l: lprev l dl=6
// Inserts in lower case
for (ll=lprev+1; ll<l; ll++)
if (Tali.seq[k][ll]!='-' && Tali.seq[k][ll]!='.') cur_seq[h++] = lwrchr(Tali.seq[k][ll]);
// Template Match state -> upper case
cur_seq[h++] = Tali.seq[k][ll];
}
else if (di==0)
{
// Gap in query: no Q match state for on T match state (special case for speed reasons)
// i: i-1 i-1 di=0
// Q: XXXXXX.....~~~XXX
// T: YYYYYYyyyyyYYYYYY
// j: j-1 j
// l: lprev l dl=6
// All T residues (including T match state) in lower case
for (ll=lprev+1; ll<=l; ll++)
if (Tali.seq[k][ll]!='-' && Tali.seq[k][ll]!='.') cur_seq[h++] = lwrchr(Tali.seq[k][ll]);
}
else if (di>=dl)
{
// More Match states in Q than Inserts in the T sequence
// => half T inserts y left, half right-aligned in uc, gaps to fill up
// Number of T insert residues to be left-aligned: (int)(dl/2)
// i: iprev i di=7
// Q: XXXXXXXXXXXXXXXXXX
// T: YYYYYYYyyy-yyYYYYY
// j: j-1 j
// l: lprev l dl=6
// Add left-bounded template residues
for (ll=lprev+1; ll<=lprev+(int)(dl/2); ll++)
cur_seq[h++]=uprchr(Tali.seq[k][ll]);
// Add central gaps
for (int gap=1; gap<=di-dl; gap++) cur_seq[h++]='-';
// Add right-bounded residues
for (; ll<=l; ll++)
cur_seq[h++]=uprchr(Tali.seq[k][ll]);
}
else if (di<dl)
{
// Fewer Match states in Q than inserts in T sequence
// => half of available space di for left- half for right-aligned T inserts, rest in lc
// number of T inserts to be left-aligned in uc: (int)(di/2),
// i: iprev i di=5
// Q: XXXXXXXXX.XXXXXXX
// T: YYYYYYYyyyyyYYYYY
// j: j-1 j
// l: lprev l dl=6
// Add left-bounded template residues
for (ll=lprev+1; ll<=lprev+(int)(di/2); ll++)
cur_seq[h++]=uprchr(Tali.seq[k][ll]);
// Add central inserts
for (int ins=1; ins<=dl-di; ins++,ll++)
if (Tali.seq[k][ll]!='-' && Tali.seq[k][ll]!='.') cur_seq[h++] = lwrchr(Tali.seq[k][ll]);
// Add right-bounded residues
for (; ll<=l; ll++)
cur_seq[h++]=uprchr(Tali.seq[k][ll]);
}
// printf("i=%-3i j=%-3i l=%-3i cur_seq=%s\n",i,j,l,cur_seq);
iprev=i; lprev=l;
if (h>=maxcol-1000) // too few columns? Reserve double space
{
char* new_seq=new char[2*maxcol];
strncpy(new_seq,cur_seq,maxcol); //////// check: maxcol-1 ????
delete[](cur_seq); (cur_seq) = NULL;
cur_seq=new_seq;
maxcol*=2;
}
}
// Add the remaining gaps '-' to the end of the template sequence
for (i=hit.i2+1; i<=L; i++) cur_seq[h++]='-';
cur_seq[h++]='\0';
keep[N_in] = display[N_in] = KEEP_CONDITIONALLY;
seq[N_in]=new char[h];
if (!seq[N_in]) MemoryError("array for input sequences");
strcpy(seq[N_in],cur_seq);
X[N_in]=new char[h];
if (!X[N_in]) MemoryError("array for input sequences");
I[N_in]=new short unsigned int[h];
if (!I[N_in]) MemoryError("array for input sequences");
sname[N_in]=new char[strlen(Tali.sname[k])+1];
if (!sname[N_in]) MemoryError("array for input sequences");
strcpy(sname[N_in],Tali.sname[k]);
N_in++;
// printf("k=%-3i %s\n",k,Tali.seq[k]);
// printf("Query %s\n",seq[kfirst]);
// printf("k=%-3i %s\n\n",k,cur_seq);
} // end for (k)
// printf("N_in=%-5i HMM=%s with %i sequences\n",N_in,ta3mfile,N_filtered);
delete[] cur_seq; cur_seq = NULL;
delete[] imatch; imatch = NULL;
delete[] ksort; ksort=NULL; // if ksort already existed it will be to short for merged alignment
delete[] first; first=NULL; // if first already existed it will be to short for merged alignment
delete[] last; last=NULL; // if last already existed it will be to short for merged alignment
} /* this is the end of Alignment::MergeMasterSlave() */
/////////////////////////////////////////////////////////////////////////////////////
/**
* @brief Add a sequence to Qali
*/
void
Alignment::AddSequence(char Xk[], int Ik[])
{
int i; // position in query and target
if (L<=0) InternalError("L is not set in AddSequence()");
X[N_in]=new char[L+2];
for (i=0; i<=L+1; i++) X[N_in][i]=Xk[i];
if (Ik==NULL)
for (i=0; i<=L+1; i++) I[N_in][i]=0;
else
for (i=0; i<=L+1; i++) I[N_in][i]=Ik[i];
N_in++;
}
/////////////////////////////////////////////////////////////////////////////////////
/**
* @brief Determine matrix of position-specific weights w[k][i] for multiple alignment
* Pos-specific weights are calculated like in "Amino_acid_frequencies_and_transitions_from_M_state()"
*/
void
Alignment::GetPositionSpecificWeights(float* w[])
{
// Calculate position-dependent weights wi[k] for each i.
// For calculation of weights in column i use sub-alignment
// over sequences which have a *residue* in column i (no gap, no end gap)
// and over columns where none of these sequences has an end gap.
// This is done by updating the arrays n[j][a] at each step i-1->i while letting i run from 1 to L.
// n[j][a] = number of occurences of amino acid a at column j of the subalignment,
// => only columns with n[j][ENDGAP]=0 are contained in the subalignment!
// If no sequences enter or leave the subalignment at the step i-1 -> i (i.e. change=0)
// then the old values w[k][i] and ncol are used for the new position i.
// Index a can be an amino acid (0-19), ANY=20, GAP=21, or ENDGAP=22
char* in=keep; // to keep the code similar to Amino_acid_frequencies_and_transitions_from_M_state()
int k; // index of sequence
int i,j; // position in alignment
int a; // amino acid (0..19)
int naa; // number of different amino acids
int** n; // n[j][a] = number of seq's with some residue at column i AND a at position j
int nseqi=0; // number of sequences in subalignment i
int ncol=0; // number of columns j that contribute to Neff[i]
char change; // has the set of sequences in subalignment changed? 0:no 1:yes
// Global weights?
if (par.wg==1)
{
for (k=0; k<N_in; k++)
for (i=1; i<=L; i++) w[k][i]=wg[k];
}
else
{
// Initialization
n = new int*[L+2];
for (j=1; j<=L; j++) n[j]=new(int[NAA+3]);
for (j=1; j<=L; j++)
for (a=0; a<NAA+3; a++) n[j][a]=0;
//////////////////////////////////////////////////////////////////////////////////////////////
// Main loop through alignment columns
for (i=1; i<=L; i++) // Calculate w[k][i]
{
change=0;
// Check all sequences k and update n[j][a] and ri[j] if necessary
for (k=0; k<N_in; k++)
{
if (!in[k]) continue;
if (X[k][i-1]>=ANY && X[k][i]<ANY)
{ // ... if sequence k was NOT included in i-1 and has to be included for column i
change=1;
nseqi++;
for (int j=1; j<=L; j++) n[j][ (int)X[k][j]]++;
}
else if (X[k][i-1]<ANY && X[k][i]>=ANY)
{ // ... if sequence k WAS included in i-1 and has to be thrown out for column i
change=1;
nseqi--;
for (int j=1; j<=L; j++) n[j][ (int)X[k][j]]--;
}
} //end for (k)
nseqs[i]=nseqi;
// If subalignment changed: update weights w[k][i] and Neff[i]
if (change)
{
// Initialize weights and numbers of residues for subalignment i
ncol=0;
for (k=0; k<N_in; k++) w[k][i]=0.0;
// sum wi[k] over all columns j and sequences k of subalignment
for (j=1; j<=L; j++)
{
// do at least a fraction MAXENDGAPFRAC of sequences in subalignment contain an end gap in j?
if (n[j][ENDGAP]>MAXENDGAPFRAC*nseqi) continue;
naa=0; for (a=0; a<20; a++) if(n[j][a]) naa++;
if (naa==0) continue;
ncol++;
for (k=0; k<N_in; k++)
{
if (in[k] && X[k][i]<ANY && X[k][j]<ANY)
{
// if (!n[j][ (int)X[k][j]]) {fprintf(stderr,"Error: Mi=%i: n[%i][X[%i]]=0! (X[%i]=%i)\n",i,j,k,k,X[k][j]);}
w[k][i]+=1.0/float(n[j][ (int)X[k][j] ]*naa);
}
}
}
// Check whether number of columns in subalignment is sufficient
if (ncol<NCOLMIN)
// Take global weights
for (k=0; k<N_in; k++)
if(in[k]) {if(X[k][i]<ANY) w[k][i]=wg[k]; else w[k][i]=0.0;}
}
}
// end loop through alignment columns i
///////////////////////////////////////////////////////////////////////
// delete n[][]
for (j=1; j<=L; j++){
delete[](n[j]); (n[j]) = NULL;
}
delete[](n); (n) = NULL;
}
return;
}
#ifdef CLUSTALO
/* @* Transfer
*
* take sequence data from Clustal and transfer it into
* hhalign accessible information (structure/class)
*
* Note that hhalign does not see all sequences/profiles
* but only sequences that are elements of the 2 profiles
* to be aligned.
*
* References to the required sequences are passed into hhalign
* through auxilliary pointers that are shallow copies of the
* sequence/profile data available to Clustal.
*
* Re-allocating memory for these auxilliary pointers
* would be desaterous, as it might detach the memory
* seen by Clustal.
*/
void
Alignment::Transfer(char **ppcProf, int iCnt){
/* @<variables local to Transfer@> */
int iLen; /* length of profile */
int k; /* generic iterator */
/* @<initialisation@> */
N_in = iCnt;
N_filtered = N_ss = 0;
kss_dssp = ksa_dssp = kss_pred = kss_conf = -1;
kfirst = 0;
strcpy(longname, "unknown_long_seq_name");
strcpy(name, "unknown_seq_name");
strcpy(file, "unknown_file_name");
n_display = iCnt;
/* @<determine length of profile@>
all sequences in profile should have same length,
so only do it for 1st */
for (iLen = 0; '\0' != ppcProf[0][iLen]; iLen++);
/* @<allocate memory for sequences etc@> */
for (k = 0; k < iCnt; k++){
#define GOOD_MEASURE 1000 /* Temporary -- can be removed once rest in place */
I[k] = new short unsigned int[iLen+2+GOOD_MEASURE];
X[k] = new char[iLen+2+GOOD_MEASURE];
seq[k] = new char[iLen+2+GOOD_MEASURE];
seq[k][0] = ' ';
seq[k][1] = '\0';
if (NULL == ppcProf[k]){
printf("%s:%d: Arena[%d]=NULL, cnt=%d\n", __FILE__, __LINE__, k, iCnt);
exit(-1);
}
strcat(seq[k], ppcProf[k]);
keep[k] = KEEP_CONDITIONALLY;
display[k] = KEEP_CONDITIONALLY;
sname[k] = new(char[GOOD_MEASURE]);
strcpy(sname[k], "unknown_sname");
} /* (0 <= k < iCnt) */
/* FIXME: Soeding always makes 1st sequence permanent */
/*keep[0] = KEEP_ALWAYS;
display[k] = KEEP_ALWAYS;*/
#if 1
/* Believe that the first and last positions are
most important in stability of this algorithm.
Must make sure that at least 2 sequences with
residues in these positions are kept.
Think any sequence will do, but better to keep
the one with the longest 'contig'
*/
int iSeq; /* sequence iterator */
int iHeadLen = 0, iHeadID = -1; /* length & ID of longest head contig */
int iTailLen = 0, iTailID = -1; /* length & ID of longest head contig */
int iCont = -1;
char *pcFind = NULL;
#if 0
printf("%s:%s:%d: NEW PROFILE (%d seq) ================\n",
__FUNCTION__, __FILE__, __LINE__, iCnt);
#endif
for (iSeq = 0; iSeq < iCnt; iSeq++){
#if 0
printf("%s:%s:%d: consider seq %d ------------------\n",
__FUNCTION__, __FILE__, __LINE__, iSeq);
#endif
pcFind = strchr(&seq[iSeq][1], '-');
if (NULL == pcFind){
/* no gap at all in this sequences, spans entire profile */
iHeadID = iTailID = iSeq;
iHeadLen = iTailLen = iLen;
break;
}
iCont = (int)(pcFind - &seq[iSeq][1]);
if (iCont > iHeadLen){
iHeadLen = iCont;
iHeadID = iSeq;
}
pcFind = strrchr(seq[iSeq], '-');
iCont = iLen - (int)(pcFind - seq[iSeq]);
if (iCont > iTailLen){
iTailLen = iCont;
iTailID = iSeq;
}
#if 0
printf("%s:%s:%d: seq %3d: len = %d(%d) %s\n",
__FUNCTION__, __FILE__, __LINE__, iSeq, iCont, iLen, seq[iSeq]);
#endif
} /* 0 <= iSeq < iCnt */
#if 0
printf("%s:%s:%d: seq %d is winner with head contig of %d, seq %d tail contig of %d\n"
, __FUNCTION__, __FILE__, __LINE__, iHeadID, iHeadLen, iTailID, iTailLen);
#endif
if ( (-1 == iHeadID) || (-1 == iTailID) ){
printf("%s:%s:%d: profile has no leading and/or trailing residues (h=%d:t=%d:#=%d)\n",
__FUNCTION__, __FILE__, __LINE__, iHeadID, iTailID, iCnt);
}
else{
keep[iHeadID] = KEEP_ALWAYS;
keep[iTailID] = KEEP_ALWAYS;
}
#endif
/* @= */
return;
} /* this is the end of Transfer() */
#endif
#ifdef CLUSTALO
/* @* Alignment::ClobberGlobal (eg: qali)
*
* Note: originally hhalign() was stand-alone code,
* there are a couple of GLOBAL (!) variables,
* which would have been destroyed on exit.
* However, now there is no 'exit' from hhalign(),
* and on re-entry the global variable must be clean again.
*/
void
Alignment::ClobberGlobal(void){
/* @<essentials@>
these are essential to re-set (as some of them are used as flags) */
for(int k=0; k<N_in; k++)
{
delete[] sname[k]; sname[k] = NULL;
delete[] seq[k]; seq[k] = NULL;
delete[] X[k]; X[k] = NULL;
delete[] I[k]; I[k] = NULL;
}
delete[] nres; nres = NULL;
delete[] first; first = NULL;
delete[] last; last = NULL;
delete[] ksort; ksort = NULL;
N_in = N_filtered = n_display = 0;
L = 0;
kss_dssp = ksa_dssp = kss_pred = kss_conf = kfirst = -1;
/* @<re-set but keep memory@>
do not free the memory but re-set content */
longname[0] = '\0'; //delete[] longname; longname = NULL;
keep[0] = '\0'; //delete[] keep; keep = NULL;
display[0] = '\0'; //delete[] display; display = NULL;
wg[0] = 0; //delete[] wg; wg = NULL;
nseqs[0] = 0; //delete[] nseqs; nseqs = NULL;
name[0]='\0';
fam[0]='\0';
file[0]='\0';
//delete[] sname; sname = NULL;
//delete[] seq; seq = NULL;
//delete[] X; X = NULL;
//delete[] I; I = NULL;
//delete[] l; l = NULL;
/* @= */
return;
}
#endif
|
a.17.1.c | /* { dg-do compile } */
void
a17_1_wrong ()
{
union
{
int n;
float x;
} u;
#pragma omp parallel
{
#pragma omp atomic
u.n++;
#pragma omp atomic
u.x += 1.0;
/* Incorrect because the atomic constructs reference the same location
through incompatible types */
}
}
|
progress.c | /*
* Copyright (c) 2009, 2010, 2011, ETH Zurich.
* All rights reserved.
*
* This file is distributed under the terms in the attached LICENSE file.
* If you do not find this file, copies can be found by writing to:
* ETH Zurich D-INFK, Haldeneggsteig 4, CH-8092 Zurich. Attn: Systems Group.
*/
#include <assert.h>
#include <stdbool.h>
#include <stdlib.h>
#include <stdio.h>
#include <time.h>
#include <assert.h>
#include <stdint.h>
#include <omp.h>
#define GANG_SCHEDULING
#define MEASURE_BARRIER
#define PERIOD 2500000000UL
#define ITERATIONS 10
#define STACK_SIZE (64 * 1024)
static inline uint64_t rdtsc(void)
{
uint64_t eax, edx;
__asm volatile ("rdtsc" : "=a" (eax), "=d" (edx));
return (edx << 32) | eax;
}
int main(int argc, char *argv[])
{
int nthreads;
if(argc == 2) {
nthreads = atoi(argv[1]);
backend_span_domain(14, STACK_SIZE);
bomp_custom_init();
omp_set_num_threads(nthreads);
} else {
assert(!"Specify number of threads");
}
volatile uint64_t workcnt[32] = { 0 };
uint64_t last = rdtsc();
#ifndef CPU_BOUND
volatile uint64_t exittime[ITERATIONS] = { 0 };
#endif
for(int iter = 0;; iter = (iter + 1) % ITERATIONS) {
#ifdef CPU_BOUND
volatile bool exitnow = false;
#else
#ifdef MEASURE_BARRIER
# define MAXTHREADS 16
# define WORKMAX 5000000
static uint64_t starta[MAXTHREADS][WORKMAX];
#endif
#endif
#ifdef GANG_SCHEDULING
#pragma omp parallel
{
bomp_synchronize();
}
#endif
// Do some work
#pragma omp parallel
for(uint64_t i = 0;; i++) {
#ifndef CPU_BOUND
# ifdef MEASURE_BARRIER
uint64_t lasta = rdtsc();
# endif
# pragma omp barrier
# ifdef MEASURE_BARRIER
if(i < WORKMAX) {
starta[omp_get_thread_num()][i] = rdtsc() - lasta;
}
# endif
#endif
workcnt[omp_get_thread_num()]++;
#pragma omp master
if(rdtsc() >= last + PERIOD) {
printf("%lu: threads %d (%s), progress ", rdtsc(), nthreads, "static");
for(int n = 0; n < 32; n++) {
printf("%lu ", workcnt[n]);
}
printf("\n");
last += PERIOD;
#ifndef CPU_BOUND
if(exittime[iter] == 0) {
exittime[iter] = i + 3;
exittime[(iter + ITERATIONS - 2) % ITERATIONS] = 0;
}
}
if(exittime[iter] != 0 && exittime[iter] == i) {
break;
}
#else
exitnow = true;
}
if(exitnow) {
break;
}
#endif
}
#ifndef CPU_BOUND
static uint64_t hgram[15] = { 0 };
printf("exittime = %lu\n", exittime[iter]);
assert(exittime[iter] <= WORKMAX);
uint64_t endtime = exittime[iter] < WORKMAX ? exittime[iter] : WORKMAX;
for(int i = 0; i < endtime; i++) {
for(int n = 0; n < nthreads; n++) {
uint64_t val = starta[n][i];
for(int j = 0; j < 15; j++) {
val /= 10;
if(val == 0) {
hgram[j]++;
break;
}
}
}
}
uint64_t val = 1;
for(int i = 0; i < 15; i++) {
val *= 10;
printf("%lu\t%lu\n", val, hgram[i]);
}
#endif
}
}
|
GB_unop__identity_uint32_fp32.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_atomics.h"
#include "GB_unop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB (_unop_apply__identity_uint32_fp32)
// op(A') function: GB (_unop_tran__identity_uint32_fp32)
// C type: uint32_t
// A type: float
// cast: uint32_t cij = GB_cast_to_uint32_t ((double) (aij))
// unaryop: cij = aij
#define GB_ATYPE \
float
#define GB_CTYPE \
uint32_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
float aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = x ;
// casting
#define GB_CAST(z, aij) \
uint32_t z = GB_cast_to_uint32_t ((double) (aij)) ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
float aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
uint32_t z = GB_cast_to_uint32_t ((double) (aij)) ; \
Cx [pC] = z ; \
}
// true if operator is the identity op with no typecasting
#define GB_OP_IS_IDENTITY_WITH_NO_TYPECAST \
0
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_IDENTITY || GxB_NO_UINT32 || GxB_NO_FP32)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_apply__identity_uint32_fp32)
(
uint32_t *Cx, // Cx and Ax may be aliased
const float *Ax,
const int8_t *restrict Ab, // A->b if A is bitmap
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
// TODO: if OP is ONE and uniform-valued matrices are exploited, then
// do this in O(1) time
if (Ab == NULL)
{
#if ( GB_OP_IS_IDENTITY_WITH_NO_TYPECAST )
GB_memcpy (Cx, Ax, anz * sizeof (float), nthreads) ;
#else
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
float aij = Ax [p] ;
uint32_t z = GB_cast_to_uint32_t ((double) (aij)) ;
Cx [p] = z ;
}
#endif
}
else
{
// bitmap case, no transpose; A->b already memcpy'd into C->b
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!Ab [p]) continue ;
float aij = Ax [p] ;
uint32_t z = GB_cast_to_uint32_t ((double) (aij)) ;
Cx [p] = z ;
}
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_tran__identity_uint32_fp32)
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
fig4.57-critical-region-print.c | /*
DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS HEADER.
Copyright 2009 Sun Microsystems, Inc. All rights reserved.
The contents of this file are subject to the terms of the BSD License("BSD")(the "License").
You can obtain a copy of the License at: http://www.opensparc.net/pubs/t1/licenses/BSD+_License.txt
The BSD License
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistribution of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistribution in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in
the documentation and/or other materials provided with the
distribution.
* Neither the name of Sun Microsystems, Inc. or the names of
contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
This software is provided "AS IS," without a warranty of any kind. ALL
EXPRESS OR IMPLIED CONDITIONS, REPRESENTATIONS AND WARRANTIES, INCLUDING ANY
IMPLIED WARRANTY OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE OR
NON-INFRINGEMENT, ARE HEREBY EXCLUDED. SUN MICROSYSTEMS, INC. ("SUN") AND
ITS LICENSORS SHALL NOT BE LIABLE FOR ANY DAMAGES SUFFERED BY LICENSEE AS A
RESULT OF USING, MODIFYING OR DISTRIBUTING THIS SOFTWARE OR ITS DERIVATIVES.
IN NO EVENT WILL SUN OR ITS LICENSORS BE LIABLE FOR ANY LOST REVENUE, PROFIT
OR DATA, OR FOR DIRECT, INDIRECT, SPECIAL, CONSEQUENTIAL, INCIDENTAL OR
PUNITIVE DAMAGES, HOWEVER CAUSED AND REGARDLESS OF THE THEORY OF LIABILITY,
ARISING OUT OF THE USE OF OR INABILITY TO USE THIS SOFTWARE, EVEN IF SUN HAS
BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.
You acknowledge that this software is not designed, licensed or intended for
use in the design, construction, operation or maintenance of any nuclear facility.
*/
#include <stdio.h>
#include <stdlib.h>
#ifdef _OPENMP
#include <omp.h>
#define TRUE 1
#define FALSE 0
#else
#define omp_get_thread_num() 0
#define omp_get_num_threads() 1
#endif
int main()
{
int TID;
#ifdef _OPENMP
(void) omp_set_dynamic(FALSE);
if (omp_get_dynamic()) {printf("Warning: dynamic adjustment of threads has been set\n");}
(void) omp_set_num_threads(3);
#endif
#pragma omp parallel
{
#pragma omp single
printf("Number of threads is %d\n",omp_get_num_threads());
}
#pragma omp parallel default(none) private(TID)
{
TID = omp_get_thread_num();
#pragma omp critical (print_tid)
{
printf("I am thread %d\n",TID);
}
} /*-- End of parallel region --*/
return(0);
}
|
declare_mapper_messages.c | // RUN: %clang_cc1 -verify -fopenmp -ferror-limit 100 %s
// RUN: %clang_cc1 -verify -fopenmp-simd -ferror-limit 100 %s
int temp; // expected-note {{'temp' declared here}}
struct vec { // expected-note {{definition of 'struct vec' is not complete until the closing '}'}}
int len;
#pragma omp declare mapper(id: struct vec v) map(v.len) // expected-error {{incomplete definition of type 'struct vec'}}
double *data;
};
#pragma omp declare mapper // expected-error {{expected '(' after 'declare mapper'}}
#pragma omp declare mapper { // expected-error {{expected '(' after 'declare mapper'}}
#pragma omp declare mapper( // expected-error {{expected a type}} expected-error {{expected declarator on 'omp declare mapper' directive}}
#pragma omp declare mapper(# // expected-error {{expected a type}} expected-error {{expected declarator on 'omp declare mapper' directive}}
#pragma omp declare mapper(struct v // expected-error {{expected declarator on 'omp declare mapper' directive}}
#pragma omp declare mapper(struct vec // expected-error {{expected declarator on 'omp declare mapper' directive}}
#pragma omp declare mapper(S v // expected-error {{unknown type name 'S'}}
#pragma omp declare mapper(struct vec v // expected-error {{expected ')'}} expected-note {{to match this '('}}
#pragma omp declare mapper(aa:struct vec v) // expected-error {{expected at least one clause on '#pragma omp declare mapper' directive}}
#pragma omp declare mapper(bb:struct vec v) private(v) // expected-error {{expected at least one clause on '#pragma omp declare mapper' directive}} // expected-error {{unexpected OpenMP clause 'private' in directive '#pragma omp declare mapper'}}
#pragma omp declare mapper(cc:struct vec v) map(v) ( // expected-warning {{extra tokens at the end of '#pragma omp declare mapper' are ignored}}
#pragma omp declare mapper(++: struct vec v) map(v.len) // expected-error {{illegal OpenMP user-defined mapper identifier}}
#pragma omp declare mapper(id1: struct vec v) map(v.len, temp) // expected-error {{only variable v is allowed in map clauses of this 'omp declare mapper' directive}}
#pragma omp declare mapper(default : struct vec kk) map(kk.data[0:2]) // expected-note {{previous definition is here}}
#pragma omp declare mapper(struct vec v) map(v.len) // expected-error {{redefinition of user-defined mapper for type 'struct vec' with name 'default'}}
#pragma omp declare mapper(int v) map(v) // expected-error {{mapper type must be of struct, union or class type}}
int fun(int arg) {
#pragma omp declare mapper(id: struct vec v) map(v.len)
{
#pragma omp declare mapper(id: struct vec v) map(v.len) // expected-note {{previous definition is here}}
#pragma omp declare mapper(id: struct vec v) map(v.len) // expected-error {{redefinition of user-defined mapper for type 'struct vec' with name 'id'}}
{
#pragma omp declare mapper(id: struct vec v) map(v.len) allocate(v) // expected-error {{unexpected OpenMP clause 'allocate' in directive '#pragma omp declare mapper'}}
struct vec vv, v1;
#pragma omp target map(mapper) // expected-error {{use of undeclared identifier 'mapper'}}
{}
#pragma omp target map(mapper:vv) // expected-error {{expected '(' after 'mapper'}}
{}
#pragma omp target map(mapper( :vv) // expected-error {{expected expression}} expected-error {{expected ')'}} expected-warning {{implicit declaration of function 'mapper' is invalid in C99}} expected-note {{to match this '('}}
{}
#pragma omp target map(mapper(aa :vv) // expected-error {{use of undeclared identifier 'aa'}} expected-error {{expected ')'}} expected-warning {{implicit declaration of function 'mapper' is invalid in C99}} expected-note {{to match this '('}}
{}
#pragma omp target map(mapper(ab) :vv) // expected-error {{missing map type}} expected-error {{cannot find a valid user-defined mapper for type 'struct vec' with name 'ab'}}
{}
#pragma omp target map(mapper(aa) :vv) // expected-error {{missing map type}}
{}
#pragma omp target map(mapper(aa) to:vv) map(close mapper(aa) from:v1)
{}
#pragma omp target update to(mapper) // expected-error {{expected '(' after 'mapper'}} expected-error {{expected expression}} expected-error {{expected at least one 'to' clause or 'from' clause specified to '#pragma omp target update'}}
#pragma omp target update to(mapper() // expected-error {{illegal OpenMP user-defined mapper identifier}} expected-error {{expected expression}} expected-error {{expected at least one 'to' clause or 'from' clause specified to '#pragma omp target update'}}
#pragma omp target update to(mapper:vv) // expected-error {{expected '(' after 'mapper'}} expected-error {{expected at least one 'to' clause or 'from' clause specified to '#pragma omp target update'}}
#pragma omp target update to(mapper(:vv) // expected-error {{illegal OpenMP user-defined mapper identifier}} expected-error {{expected at least one 'to' clause or 'from' clause specified to '#pragma omp target update'}}
#pragma omp target update to(mapper(aa :vv) // expected-error {{expected ')'}} expected-note {{to match this '('}} expected-error {{expected at least one 'to' clause or 'from' clause specified to '#pragma omp target update'}}
#pragma omp target update to(mapper(ab):vv) // expected-error {{cannot find a valid user-defined mapper for type 'struct vec' with name 'ab'}} expected-error {{expected at least one 'to' clause or 'from' clause specified to '#pragma omp target update'}}
#pragma omp target update to(mapper(aa):vv)
#pragma omp target update from(mapper) // expected-error {{expected '(' after 'mapper'}} expected-error {{expected expression}} expected-error {{expected at least one 'to' clause or 'from' clause specified to '#pragma omp target update'}}
#pragma omp target update from(mapper() // expected-error {{illegal OpenMP user-defined mapper identifier}} expected-error {{expected expression}} expected-error {{expected at least one 'to' clause or 'from' clause specified to '#pragma omp target update'}}
#pragma omp target update from(mapper:vv) // expected-error {{expected '(' after 'mapper'}} expected-error {{expected at least one 'to' clause or 'from' clause specified to '#pragma omp target update'}}
#pragma omp target update from(mapper(:vv) // expected-error {{illegal OpenMP user-defined mapper identifier}} expected-error {{expected at least one 'to' clause or 'from' clause specified to '#pragma omp target update'}}
#pragma omp target update from(mapper(aa :vv) // expected-error {{expected ')'}} expected-note {{to match this '('}} expected-error {{expected at least one 'to' clause or 'from' clause specified to '#pragma omp target update'}}
#pragma omp target update from(mapper(ab):vv) // expected-error {{cannot find a valid user-defined mapper for type 'struct vec' with name 'ab'}} expected-error {{expected at least one 'to' clause or 'from' clause specified to '#pragma omp target update'}}
#pragma omp target update from(mapper(aa) a:vv) // expected-warning {{missing ':' after ) - ignoring}}
#pragma omp target update from(mapper(aa):vv)
}
}
return arg;
}
|
matmult.c | /******************************************************************************
* OpenMp Example - Matrix Multiply - C Version
* Demonstrates a matrix multiply using OpenMP.
*
* Modified from here:
* https://computing.llnl.gov/tutorials/openMP/samples/C/omp_mm.c
*
* For PAPI_FP_INS, the exclusive count for the event:
* for (null) [OpenMP location: file:matmult.c ]
* should be 2E+06 / Number of Threads
******************************************************************************/
#include <stdio.h>
#include <stdlib.h>
#ifdef TAU_MPI
int provided;
#include <mpi.h>
/* NOTE: MPI is just used to spawn multiple copies of the kernel to different ranks.
This is not a parallel implementation */
#endif /* TAU_MPI */
#ifdef PTHREADS
#include <pthread.h>
#include <unistd.h>
#include <errno.h>
/*** NOTE THE ATTR INITIALIZER HERE! ***/
pthread_mutex_t mutexsum;
#endif /* PTHREADS */
#define APP_USE_INLINE_MULTIPLY 1
#ifndef MATRIX_SIZE
#define MATRIX_SIZE 512
#endif
#define NRA MATRIX_SIZE /* number of rows in matrix A */
#define NCA MATRIX_SIZE /* number of columns in matrix A */
#define NCB MATRIX_SIZE /* number of columns in matrix B */
void initialize(double **matrix, int rows, int cols) {
int i,j;
#pragma omp parallel private(i,j) shared(matrix)
{
//set_num_threads();
/*** Initialize matrices ***/
#pragma omp for nowait
for (i=0; i<rows; i++) {
for (j=0; j<cols; j++) {
matrix[i][j]= i+j;
}
}
}
}
double** allocateMatrix(int rows, int cols) {
int i;
double **matrix = (double**)malloc((sizeof(double*)) * rows);
for (i=0; i<rows; i++) {
matrix[i] = (double*)malloc((sizeof(double)) * cols);
}
return matrix;
}
void freeMatrix(double** matrix, int rows, int cols) {
int i;
for (i=0; i<rows; i++) {
free(matrix[i]);
}
free(matrix);
}
double multiply(double a, double b) {
return a * b;
}
#ifdef TAU_OPENMP
// cols_a and rows_b are the same value
void compute_nested(double **a, double **b, double **c, int rows_a, int cols_a, int cols_b) {
int i,j,k;
double tmp = 0.0;
/*** Do matrix multiply sharing iterations on outer loop ***/
/*** Display who does which iterations for demonstration purposes ***/
#pragma omp parallel for private(i,j,k) shared(a,b,c)
for (i=0; i<rows_a; i++) {
{
for (k=0; k<cols_a; k++) {
for(j=0; j<cols_b; j++) {
#ifdef APP_USE_INLINE_MULTIPLY
c[i][j] += multiply(a[i][k], b[k][j]);
#else
tmp = a[i][k];
tmp = tmp * b[k][j];
c[i][j] += tmp;
#endif
}
}
}
}
}
#endif
// cols_a and rows_b are the same value
void compute(double **a, double **b, double **c, int rows_a, int cols_a, int cols_b) {
int i,j,k;
#pragma omp parallel private(i,j,k) shared(a,b,c)
{
/*** Do matrix multiply sharing iterations on outer loop ***/
/*** Display who does which iterations for demonstration purposes ***/
#pragma omp for nowait
for (i=0; i<rows_a; i++) {
for(j=0; j<cols_b; j++) {
for (k=0; k<cols_a; k++) {
#ifdef APP_USE_INLINE_MULTIPLY
c[i][j] += multiply(a[i][k], b[k][j]);
#else /* APP_USE_INLINE_MULTIPLY */
c[i][j] += a[i][k] * b[k][j];
#endif /* APP_USE_INLINE_MULTIPLY */
}
}
}
} /*** End of parallel region ***/
}
void compute_interchange(double **a, double **b, double **c, int rows_a, int cols_a, int cols_b) {
int i,j,k;
#pragma omp parallel private(i,j,k) shared(a,b,c)
{
/*** Do matrix multiply sharing iterations on outer loop ***/
/*** Display who does which iterations for demonstration purposes ***/
#pragma omp for nowait
for (i=0; i<rows_a; i++) {
for (k=0; k<cols_a; k++) {
for(j=0; j<cols_b; j++) {
#ifdef APP_USE_INLINE_MULTIPLY
c[i][j] += multiply(a[i][k], b[k][j]);
#else /* APP_USE_INLINE_MULTIPLY */
c[i][j] += a[i][k] * b[k][j];
#endif /* APP_USE_INLINE_MULTIPLY */
}
}
}
} /*** End of parallel region ***/
}
double do_work(void) {
double **a, /* matrix A to be multiplied */
**b, /* matrix B to be multiplied */
**c; /* result matrix C */
a = allocateMatrix(NRA, NCA);
b = allocateMatrix(NCA, NCB);
c = allocateMatrix(NRA, NCB);
/*** Spawn a parallel region explicitly scoping all variables ***/
initialize(a, NRA, NCA);
initialize(b, NCA, NCB);
initialize(c, NRA, NCB);
compute(a, b, c, NRA, NCA, NCB);
#if defined(TAU_OPENMP)
//if (omp_get_nested()) {
compute_nested(a, b, c, NRA, NCA, NCB);
//}
#endif
#ifdef TAU_MPI
if (provided == MPI_THREAD_MULTIPLE) {
printf("provided is MPI_THREAD_MULTIPLE\n");
} else if (provided == MPI_THREAD_FUNNELED) {
printf("provided is MPI_THREAD_FUNNELED\n");
}
#endif /* TAU_MPI */
compute_interchange(a, b, c, NRA, NCA, NCB);
double result = c[0][1];
freeMatrix(a, NRA, NCA);
freeMatrix(b, NCA, NCB);
freeMatrix(c, NCA, NCB);
return result;
}
#ifdef PTHREADS
int busy_sleep() {
int i, sum = 0;
for (i = 0 ; i < 100000000 ; i++) {
sum = sum+i;
}
return sum;
}
void * threaded_func(void *data)
{
int rc;
int sum = 0;
// compute
do_work();
#ifdef APP_DO_LOCK_TEST
// test locking - sampling should catch this
if ((rc = pthread_mutex_lock(&mutexsum)) != 0)
{
errno = rc;
perror("thread lock error");
exit(1);
}
fprintf(stderr,"Thread 'sleeping'...\n"); fflush(stderr);
sum += busy_sleep();
fprintf(stderr,"Thread 'awake'...\n"); fflush(stderr);
if ((rc = pthread_mutex_unlock(&mutexsum)) != 0)
{
errno = rc;
perror("thread unlock error");
exit(1);
}
pthread_exit((void*) 0);
//return NULL;
#endif // APP_DO_LOCK_TEST
}
#endif // PTHREADS
int main (int argc, char *argv[])
{
#ifdef PTHREADS
int ret;
pthread_attr_t attr;
pthread_t tid1, tid2, tid3;
pthread_mutexattr_t Attr;
pthread_mutexattr_init(&Attr);
pthread_mutexattr_settype(&Attr, PTHREAD_MUTEX_ERRORCHECK);
if (pthread_mutex_init(&mutexsum, &Attr)) {
printf("Error while using pthread_mutex_init\n");
}
#endif /* PTHREADS */
#ifdef TAU_MPI
int rc = MPI_SUCCESS;
#if defined(PTHREADS)
rc = MPI_Init_thread(&argc, &argv, MPI_THREAD_MULTIPLE, &provided);
printf("MPI_Init_thread: provided = %d, MPI_THREAD_MULTIPLE=%d\n", provided, MPI_THREAD_MULTIPLE);
#elif defined(TAU_OPENMP)
rc = MPI_Init_thread(&argc, &argv, MPI_THREAD_FUNNELED, &provided);
printf("MPI_Init_thread: provided = %d, MPI_THREAD_FUNNELED=%d\n", provided, MPI_THREAD_FUNNELED);
#else
rc = MPI_Init(&argc, &argv);
#endif /* THREADS */
if (rc != MPI_SUCCESS) {
char *errorstring;
int length = 0;
MPI_Error_string(rc, errorstring, &length);
printf("Error: MPI_Init failed, rc = %d\n%s\n", rc, errorstring);
exit(1);
}
#endif /* TAU_MPI */
#ifdef PTHREADS
if (ret = pthread_create(&tid1, NULL, threaded_func, NULL) )
{
printf("Error: pthread_create (1) fails ret = %d\n", ret);
exit(1);
}
if (ret = pthread_create(&tid2, NULL, threaded_func, NULL) )
{
printf("Error: pthread_create (2) fails ret = %d\n", ret);
exit(1);
}
if (ret = pthread_create(&tid3, NULL, threaded_func, NULL) )
{
printf("Error: pthread_create (3) fails ret = %d\n", ret);
exit(1);
}
#endif /* PTHREADS */
/* On thread 0: */
int i;
//for (i = 0 ; i < 100 ; i++) {
do_work();
//}
#ifdef PTHREADS
if (ret = pthread_join(tid1, NULL) )
{
printf("Error: pthread_join (1) fails ret = %d\n", ret);
exit(1);
}
if (ret = pthread_join(tid2, NULL) )
{
printf("Error: pthread_join (2) fails ret = %d\n", ret);
exit(1);
}
if (ret = pthread_join(tid3, NULL) )
{
printf("Error: pthread_join (3) fails ret = %d\n", ret);
exit(1);
}
pthread_mutex_destroy(&mutexsum);
#endif /* PTHREADS */
#ifdef TAU_MPI
MPI_Finalize();
#endif /* TAU_MPI */
printf ("Done.\n");
return 0;
}
|
energy.h | #pragma once
#include "bonds.h"
#include "externalpotential.h" // Energybase implemented here
#include "space.h"
#include "aux/iteratorsupport.h"
#include <range/v3/view.hpp>
#include <Eigen/Dense>
#include "spdlog/spdlog.h"
#ifdef ENABLE_FREESASA
#include <freesasa.h>
#endif
namespace Faunus {
namespace ReactionCoordinate {
struct ReactionCoordinateBase;
}
namespace Potential {
struct PairPotentialBase;
}
namespace Energy {
class Hamiltonian;
/**
* @brief Check for overlap between atoms and the simulation container
*
* If found infinite energy is returned. Not needed for cuboidal geometry
* as there's nover any overlap due to PBC.
*/
struct ContainerOverlap : public Energybase {
const Space &spc;
ContainerOverlap(const Space &spc) : spc(spc) { name = "ContainerOverlap"; }
double energy(Change &change) override;
};
/**
* This holds Ewald setup and must *not* depend on particle type, nor depend on Space
*/
struct EwaldData {
typedef std::complex<double> Tcomplex;
Eigen::Matrix3Xd kVectors; // k-vectors, 3xK
Eigen::VectorXd Aks; // 1xK, to minimize computational effort (Eq.24,DOI:10.1063/1.481216)
Eigen::VectorXcd Qion, Qdip; // 1xK
double alpha, rc, kc, check_k2_zero, lB;
double const_inf, eps_surf, kappa, kappa2;
bool spherical_sum = true;
bool ipbc = false;
int kVectorsInUse = 0;
Point L; //!< Box dimensions
EwaldData(const json &);
void update(const Point &box);
};
void to_json(json &, const EwaldData &);
#ifdef DOCTEST_LIBRARY_INCLUDED
TEST_CASE("[Faunus] Ewald - EwaldData") {
using doctest::Approx;
EwaldData data(R"({
"ipbc": false, "epsr": 1.0, "alpha": 0.894427190999916, "epss": 1.0,
"kcutoff": 11.0, "spherical_sum": true, "cutoff": 5.0})"_json);
data.update(Point(10, 10, 10));
CHECK(data.ipbc == false);
CHECK(data.const_inf == 1);
CHECK(data.alpha == 0.894427190999916);
CHECK(data.kVectors.cols() == 2975);
CHECK(data.Qion.size() == data.kVectors.cols());
data.ipbc = true;
data.update(Point(10, 10, 10));
CHECK(data.kVectors.cols() == 846);
CHECK(data.Qion.size() == data.kVectors.cols());
}
#endif
/**
* @brief recipe or policies for ion-ion ewald
* @todo
* - eliminate raw pointers
* - undefined bahevior if ipbc==true adn eigenopt==true
*/
template <bool eigenopt = false /** use Eigen matrix ops where possible */> struct PolicyIonIon {
typedef typename ParticleVector::iterator iter;
Space *spc;
Space *old = nullptr; // set only if key==NEW at first call to `sync()`
PolicyIonIon(Space &spc) : spc(&spc) {}
/**
* @brief Updates the reciprocal space terms 'Q^q' and 'A_k'. See eqs. 24 and 25 in ref. for PBC Ewald, and eq. 2 in doi:10/css8 for IPBC Ewald.
*/
void updateComplex(EwaldData &data) const {
auto active = spc->activeParticles();
if (eigenopt) { // calculate using Eigen operations. Faster for large systems?
if(data.ipbc) {
auto pos = asEigenMatrix(active.begin().base(), active.end().base(), &Space::Tparticle::pos); // N x 3
auto charge =
asEigenVector(active.begin().base(), active.end().base(), &Space::Tparticle::charge); // N x 1
data.Qion.real() = ( data.kVectors.array().cwiseProduct(pos).array().cos().prod() * charge ).colwise().sum(); // see eq. 2 in doi:10/css8
} else {
auto pos = asEigenMatrix(active.begin().base(), active.end().base(), &Space::Tparticle::pos); // N x 3
auto charge =
asEigenVector(active.begin().base(), active.end().base(), &Space::Tparticle::charge); // N x 1
Eigen::MatrixXd kr = pos.matrix() * data.kVectors; // ( N x 3 ) * ( 3 x K ) = N x K
data.Qion.real() = (kr.array().cos().colwise() * charge).colwise().sum(); // real part of 'Q^q', see eq. 25 in ref.
data.Qion.imag() = kr.array().sin().colwise().sum(); // imaginary part of 'Q^q', see eq. 25 in ref.
}
} else { // calculate using generic loops
for (int k = 0; k < data.kVectors.cols(); k++) {
const Point &kv = data.kVectors.col(k);
EwaldData::Tcomplex Q(0, 0);
if (data.ipbc)
for (auto &i : active)
Q += kv.cwiseProduct(i.pos).array().cos().prod() * i.charge; // see eq. 2 in doi:10/css8
else {
for (auto &i : active) {
double dot = kv.dot(i.pos);
Q += i.charge * EwaldData::Tcomplex(std::cos(dot), std::sin(dot)); // 'Q^q', see eq. 25 in ref.
}
}
data.Qion[k] = Q;
}
}
} //!< Update all k vectors
void updateComplex(EwaldData &data, Change &change) const {
assert(old != nullptr);
assert(spc->p.size() == old->p.size());
for (int k = 0; k < data.kVectors.cols(); k++) {
auto &Q = data.Qion[k];
Point q = data.kVectors.col(k);
if (data.ipbc) {
for (auto cg : change.groups) {
auto g_new = spc->groups.at(cg.index);
auto g_old = old->groups.at(cg.index);
for (auto i : cg.atoms) {
if (i < g_new.size())
Q += q.cwiseProduct((g_new.begin() + i)->pos).array().cos().prod() *
(g_new.begin() + i)->charge;
if (i < g_old.size())
Q -= q.cwiseProduct((g_old.begin() + i)->pos).array().cos().prod() *
(g_old.begin() + i)->charge;
}
}
} else {
for (auto cg : change.groups) {
auto g_new = spc->groups.at(cg.index);
auto g_old = old->groups.at(cg.index);
for (auto i : cg.atoms) {
if (i < g_new.size()) {
double _new = q.dot((g_new.begin() + i)->pos);
Q += (g_new.begin() + i)->charge * EwaldData::Tcomplex(std::cos(_new), std::sin(_new));
}
if (i < g_old.size()) {
double _old = q.dot((g_old.begin() + i)->pos);
Q -= (g_old.begin() + i)->charge * EwaldData::Tcomplex(std::cos(_old), std::sin(_old));
}
}
}
}
}
} //!< Optimized update of k subset. Require access to old positions through `old` pointer
// selfEnergies should be handled by the real-space pair-potential
// todo: this should not be used, but replaced by selfEnergy in PairPotential
double selfEnergy(const EwaldData &d, Change &change) {
#ifndef NDEBUG
// std::cerr << "we should ideally not arrive here!\n";
#endif
double Eq = 0;
if (change.dN) {
for (auto cg : change.groups) {
auto g = spc->groups.at(cg.index);
for (auto i : cg.atoms)
if (i < g.size())
Eq += std::pow((g.begin() + i)->charge, 2);
}
} else if (change.all and not change.dV) {
for (auto g : spc->groups)
for (auto i : g)
Eq += i.charge * i.charge;
}
return -d.alpha * Eq / std::sqrt(pc::pi) * d.lB;
}
double surfaceEnergy(const EwaldData &d, Change &change) {
if (d.const_inf < 0.5)
return 0;
Point qr(0, 0, 0);
if (change.all or change.dV)
for (auto g : spc->groups)
for (auto i : g)
qr += i.charge * i.pos;
else if (change.groups.size() > 0) {
for (auto cg : change.groups) {
auto g = spc->groups.at(cg.index);
for (auto i : cg.atoms)
if (i < g.size())
qr += (g.begin() + i)->charge * (g.begin() + i)->pos;
}
}
return d.const_inf * 2 * pc::pi / ((2 * d.eps_surf + 1) * spc->geo.getVolume()) * qr.dot(qr) * d.lB;
}
double reciprocalEnergy(const EwaldData &d) {
double E = 0;
if (eigenopt) // known at compile time
E = d.Aks.cwiseProduct(d.Qion.cwiseAbs2()).sum();
else
for (int k = 0; k < d.Qion.size(); k++)
E += d.Aks[k] * std::norm(d.Qion[k]);
return 2 * pc::pi / spc->geo.getVolume() * E * d.lB;
}
};
#ifdef DOCTEST_LIBRARY_INCLUDED
TEST_CASE("[Faunus] Ewald - IonIonPolicy") {
using doctest::Approx;
Space spc;
spc.p.resize(2);
spc.geo = R"( {"type": "cuboid", "length": 10} )"_json;
spc.p[0] = R"( {"pos": [0,0,0], "q": 1.0} )"_json;
spc.p[1] = R"( {"pos": [1,0,0], "q": -1.0} )"_json;
Group<Particle> g(spc.p.begin(), spc.p.end());
spc.groups.push_back(g);
EwaldData data = R"({
"epsr": 1.0, "alpha": 0.894427190999916, "epss": 1.0,
"kcutoff": 11.0, "spherical_sum": true, "cutoff": 5.0})"_json;
Change c;
c.all = true;
data.ipbc = false; // PBC Ewald (http://dx.doi.org/10.1063/1.481216)
data.update(spc.geo.getLength());
SUBCASE("standard loop") {
PolicyIonIon<false> ionion(spc);
ionion.updateComplex(data);
CHECK(ionion.selfEnergy(data, c) == Approx(-1.0092530088080642 * data.lB));
CHECK(ionion.surfaceEnergy(data, c) == Approx(0.0020943951023931952 * data.lB));
CHECK(ionion.reciprocalEnergy(data) == Approx(0.21303063979675319 * data.lB));
data.ipbc = true; // IPBC Ewald
data.update(spc.geo.getLength());
ionion.updateComplex(data);
CHECK(ionion.selfEnergy(data, c) == Approx(-1.0092530088080642 * data.lB));
CHECK(ionion.surfaceEnergy(data, c) == Approx(0.0020943951023931952 * data.lB));
CHECK(ionion.reciprocalEnergy(data) == Approx(0.0865107467 * data.lB));
}
SUBCASE("eigen operations") {
data.ipbc = false;
data.update(spc.geo.getLength());
PolicyIonIon<true> ionion(spc);
ionion.updateComplex(data);
CHECK(ionion.selfEnergy(data, c) == Approx(-1.0092530088080642 * data.lB));
CHECK(ionion.surfaceEnergy(data, c) == Approx(0.0020943951023931952 * data.lB));
CHECK(ionion.reciprocalEnergy(data) == Approx(0.21303063979675319 * data.lB));
}
}
#endif
/** @brief Ewald summation reciprocal energy */
template <class Policy = PolicyIonIon<>> class Ewald : public Energybase {
private:
EwaldData data;
Policy policy;
Space &spc;
public:
Ewald(const json &j, Space &spc) : data(j), policy(spc), spc(spc) {
name = "ewald";
cite = "doi:10.1063/1.481216";
init();
}
void init() override {
data.update(spc.geo.getLength());
policy.updateComplex(data); // brute force. todo: be selective
}
double energy(Change &change) override {
double u = 0;
if (change) {
// If the state is NEW (trial state), then update all k-vectors
if (key == NEW) {
if (change.all or change.dV) { // everything changes
data.update(spc.geo.getLength());
policy.updateComplex(data); // update all (expensive!)
} else {
if (change.groups.size() > 0)
policy.updateComplex(data, change);
}
}
// todo: omit selfEnergy() call as this should be added as a separate term in `Hamiltonian`
u = policy.surfaceEnergy(data, change) +
policy.reciprocalEnergy(data); // + policy.selfEnergy(data, change);
}
return u;
}
void sync(Energybase *basePtr, Change &) override {
auto other = dynamic_cast<decltype(this)>(basePtr);
assert(other);
if (other->key == OLD)
policy.old = &(other->spc); // give NEW access to OLD space for optimized updates
data = other->data; // copy everything!
} //!< Called after a move is rejected/accepted as well as before simulation
void to_json(json &j) const override { j = data; }
};
class Isobaric : public Energybase {
private:
Space &spc;
double P; // P/kT
public:
Isobaric(const json &, Space &);
double energy(Change &) override;
void to_json(json &) const override;
};
/**
* @brief Constrain system using reaction coordinates
*
* If outside specified `range`, infinity energy is returned, causing rejection.
*/
class Constrain : public Energybase {
private:
std::string type;
std::shared_ptr<ReactionCoordinate::ReactionCoordinateBase> rc = nullptr;
public:
Constrain(const json &, Space &);
double energy(Change &) override;
void to_json(json &) const override;
};
/*
* The keys of the `intra` map are group index and the values
* is a vector of `BondData`. For bonds between groups, fill
* in `inter` which is evaluated for every update of call to
* `energy`.
*
* @todo Optimize.
*/
class Bonded : public Energybase {
private:
Space &spc;
typedef BasePointerVector<Potential::BondData> BondVector;
BondVector inter; // inter-molecular bonds
std::map<int, BondVector> intra; // intra-molecular bonds
private:
void update_intra(); // finds and adds all intra-molecular bonds of active molecules
double sum_energy(const BondVector &) const; // sum energy in vector of BondData
double sum_energy(const BondVector &,
const std::vector<int> &) const; // sum energy in vector of BondData for matching particle indices
public:
Bonded(const json &, Space &);
void to_json(json &) const override;
double energy(Change &) override; // brute force -- refine this!
};
/**
* @brief Nonbonded energy using a pair-potential
*/
template <typename Tpairpot> class Nonbonded : public Energybase {
private:
double g2gcnt = 0, g2gskip = 0;
PairMatrix<double> cutoff2; // matrix w. group-to-group cutoff
std::vector<const Particle *> i_interact_with_these;
protected:
typedef typename Space::Tgroup Tgroup;
double Rc2_g2g = pc::infty;
// control of when OpenMP should be used
bool omp_enable = false;
bool omp_i2all = false;
bool omp_g2g = false;
bool omp_p2p = false;
void to_json(json &j) const override {
j["pairpot"] = pairpot;
if (omp_enable) {
json _a = json::array();
if (omp_p2p)
_a.push_back("p2p");
if (omp_g2g)
_a.push_back("g2g");
if (omp_i2all)
_a.push_back("i2all");
j["openmp"] = _a;
}
j["cutoff_g2g"] = json::object();
auto &_j = j["cutoff_g2g"];
for (auto &a : Faunus::molecules)
for (auto &b : Faunus::molecules)
if (a.id() >= b.id())
_j[a.name + " " + b.name] = sqrt(cutoff2(a.id(), b.id()));
}
template <typename T> inline bool cut(const T &g1, const T &g2) {
g2gcnt++;
if (g1.atomic || g2.atomic)
return false;
if (spc.geo.sqdist(g1.cm, g2.cm) < cutoff2(g1.id, g2.id))
return false;
g2gskip++;
return true;
} //!< true if group<->group interaction can be skipped
template <typename T> inline double i2i(const T &a, const T &b) {
assert(&a != &b && "a and b cannot be the same particle");
return pairpot(a, b, spc.geo.vdist(a.pos, b.pos));
}
/*
* Internal energy in group, calculating all with all or, if `index`
* is given, only a subset. Index specifies the internal index (starting
* from zero) of changed particles within the group.
*/
double g_internal(const Tgroup &g, const std::vector<int> &index = std::vector<int>()) {
using namespace ranges;
double u = 0;
auto &molecule = molecules.at(g.id);
if (index.empty() && !molecule.rigid) { // assume that all atoms have changed
for (auto particle_i = g.begin(); particle_i != g.end(); ++particle_i) {
int i = std::distance(g.begin(), particle_i);
for (auto particle_j = std::next(particle_i); particle_j != g.end(); ++particle_j) {
int j = std::distance(g.begin(), particle_j);
if (!molecule.isPairExcluded(i, j)) {
u += i2i(*particle_i, *particle_j);
}
}
}
} else { // only a subset has changed
auto fixed = view::ints(0, int(g.size())) |
view::remove_if([&index](int i) { return std::binary_search(index.begin(), index.end(), i); });
for (int i : index) {
for (int j : fixed) { // moved<->static
if (!molecule.isPairExcluded(i, j)) {
u += i2i(*(g.begin() + i), *(g.begin() + j));
}
}
for (int j : index) { // moved<->moved
if (j <= i) {
continue;
}
if (!molecule.isPairExcluded(i, j)) {
u += i2i(*(g.begin() + i), *(g.begin() + j));
}
}
}
}
return u;
}
/*
* Calculates the interaction energy of a particle, `i`,
* and checks (1) if it is already part of Space, or (2)
* external to space.
*/
double i2all(const typename Space::Tparticle &i) {
if (omp_enable and omp_i2all) {
return i2all_parallel(i);
}
double u = 0;
auto it = spc.findGroupContaining(i); // iterator to group
if (it != spc.groups.end()) { // check if i belongs to group in space
for (size_t ig = 0; ig < spc.groups.size(); ig++) {
auto &g = spc.groups[ig];
if (&g != &(*it)) // avoid self-interaction
if (not cut(g, *it)) // check g2g cut-off
for (auto &j : g) // loop over particles in other group
u += i2i(i, j);
}
std::ptrdiff_t i_ndx = &i - &(*(it->begin())); // fixme c++ style
u += g_internal(*it, {static_cast<int>(i_ndx)}); // only int indices are used internally
} else { // particle does not belong to any group
for (auto &g : spc.groups) { // i with all other *active* particles
for (auto &j : g) { // (this will include only active particles)
u += i2i(i, j);
}
}
}
return u;
}
double i2all_parallel(const typename Space::Tparticle &i) {
i_interact_with_these.clear();
double u = 0;
auto it = spc.findGroupContaining(i); // iterator to group
if (it != spc.groups.end()) { // check if i belongs to group in space
for (size_t ig = 0; ig < spc.groups.size(); ig++) {
auto &g = spc.groups[ig];
if (&g != &(*it)) // avoid self-interaction
if (not cut(g, *it)) // check g2g cut-off
for (auto &j : g) // loop over particles in other group
i_interact_with_these.push_back(&j); // u += i2i(i, j);
}
for (auto &j : *it) // i with all particles in own group
if (&j != &i)
i_interact_with_these.push_back(&j); // u += i2i(i, j);
} else // particle does not belong to any group
for (auto &g : spc.groups) // i with all other *active* particles
for (auto &j : g) // (this will include only active particles)
i_interact_with_these.push_back(&j); // u += i2i(i, j);
#pragma omp parallel for reduction(+ : u) if (omp_enable and omp_i2all)
for (size_t k = 0; k < i_interact_with_these.size(); k++)
u += i2i(i, *i_interact_with_these[k]);
return u;
}
/*
* Group-to-group energy. A subset of `g1` can be given with `index` which refers
* to the internal index (starting at zero) of the first group, `g1
* NOTE: the interpretation of this function is extended to also consider the mutual interactions
* of a subset of each group and in such case returns sub1 <-> 2 and !sub1<->sub2,
* hence excluding !sub1 <-> !sub2 in comparision to calling onconstrained g2g. In absence
* of sub1 any sub2 is ignored.
*/
virtual double g2g(const Tgroup &g1, const Tgroup &g2, const std::vector<int> &index = std::vector<int>(),
const std::vector<int> &jndex = std::vector<int>()) {
using namespace ranges;
double u = 0;
if (not cut(g1, g2)) {
if (index.empty() && jndex.empty()) // if index is empty, assume all in g1 have changed
#pragma omp parallel for reduction(+ : u) schedule(dynamic) if (omp_enable and omp_p2p)
for (size_t i = 0; i < g1.size(); i++)
for (size_t j = 0; j < g2.size(); j++)
u += i2i(*(g1.begin() + i), *(g2.begin() + j));
else { // only a subset of g1
for (auto i : index)
for (auto j = g2.begin(); j != g2.end(); ++j)
u += i2i(*(g1.begin() + i), *j);
if (not jndex.empty()) {
auto fixed = view::ints(0, int(g1.size())) | view::remove_if([&index](int i) {
return std::binary_search(index.begin(), index.end(), i);
});
for (auto i : jndex) // moved2 <-|
for (auto j : fixed) // static1 <-|
u += i2i(*(g2.begin() + i), *(g1.begin() + j));
}
}
}
return u;
}
// add self energy term to Hamiltonian if appropriate
void addPairPotentialSelfEnergy() {
if (pairpot.selfEnergy) { // only add if self energy is defined
faunus_logger->debug("{} is adding self-energy from {} to Hamiltonian", name, pairpot.name);
pot.emplace_back<Energy::ParticleSelfEnergy>(spc, pairpot.selfEnergy);
}
}
void configureOpenMP(const json &j) {
auto it = j.find("openmp");
if (it != j.end())
if (it->is_array())
if (it->size() > 0) {
omp_enable = true;
for (const std::string &k : *it)
if (k == "g2g")
omp_g2g = true;
else if (k == "p2p")
omp_p2p = true;
else if (k == "i2all")
omp_i2all = true;
#ifndef _OPENMP
faunus_logger->warn("{}: requested openmp unavailable", name);
#endif
}
}
public:
Space &spc; //!< Space to operate on
BasePointerVector<Energybase> &pot;
Tpairpot pairpot; //!< Pair potential
Nonbonded(const json &j, Space &spc, BasePointerVector<Energybase> &pot) : spc(spc), pot(pot) {
name = "nonbonded";
pairpot.from_json(j);
// some pair-potentials give rise to self-energies (Wolf etc.)
// which are added here if needed
addPairPotentialSelfEnergy();
configureOpenMP(j);
// disable all group-to-group cutoffs by setting infinity
for (auto &i : Faunus::molecules)
for (auto &j : Faunus::molecules)
cutoff2.set(i.id(), j.id(), pc::infty);
auto it = j.find("cutoff_g2g");
if (it != j.end()) {
// old style input w. only a single cutoff
if (it->is_number()) {
Rc2_g2g = std::pow(it->get<double>(), 2);
for (auto &i : Faunus::molecules)
for (auto &j : Faunus::molecules)
cutoff2.set(i.id(), j.id(), Rc2_g2g);
}
// new style input w. multiple cutoffs between molecules
else if (it->is_object()) {
// ensure that there is a default, fallback cutoff
Rc2_g2g = std::pow(it->at("default").get<double>(), 2);
for (auto &i : Faunus::molecules)
for (auto &j : Faunus::molecules)
cutoff2.set(i.id(), j.id(), Rc2_g2g);
// loop for space separated molecule pairs in keys
for (auto &i : it->items()) {
auto v = words2vec<std::string>(i.key());
if (v.size() == 2) {
int id1 = (*findName(Faunus::molecules, v[0])).id();
int id2 = (*findName(Faunus::molecules, v[1])).id();
cutoff2.set(id1, id2, std::pow(i.value().get<double>(), 2));
}
}
}
}
}
/**
* Calculates the force on all particles
* @todo Change to reflect only active particle, see Space::activeParticles()
*/
void force(std::vector<Point> &forces) override {
auto &p = spc.p; // alias to particle vector (reference)
assert(forces.size() == p.size() && "the forces size must match the particle size");
for (size_t i = 0; i < p.size() - 1; i++) {
for (size_t j = i + 1; j < p.size(); j++) {
Point r = spc.geo.vdist(p[i].pos, p[j].pos); // minimum distance vector
Point f = pairpot.force(p[i], p[j], r.squaredNorm(), r);
forces[i] += f;
forces[j] -= f;
}
}
}
double energy(Change &change) override {
using namespace ranges;
double u = 0;
if (change) {
// there's a change in system volume
if (change.dV) {
#pragma omp parallel for reduction(+ : u) schedule(dynamic) if (omp_enable and omp_g2g)
for (auto i = spc.groups.begin(); i < spc.groups.end(); ++i) {
for (auto j = i; ++j != spc.groups.end();)
u += g2g(*i, *j);
if (i->atomic or i->compressible)
u += g_internal(*i);
}
return u;
}
// did everything change?
if (change.all) {
#pragma omp parallel for reduction(+ : u) schedule(dynamic) if (omp_enable and omp_g2g)
for (auto i = spc.groups.begin(); i < spc.groups.end(); ++i) {
for (auto j = i; ++j != spc.groups.end();)
u += g2g(*i, *j);
u += g_internal(*i);
}
// more todo here...
return u;
}
// if exactly ONE molecule is changed
if (change.groups.size() == 1 && not change.dN) {
auto &d = change.groups[0];
auto gindex = spc.groups.at(d.index).to_index(spc.p.begin()).first;
// exactly one atom has move
if (d.atoms.size() == 1)
return i2all(spc.p.at(gindex + d.atoms[0]));
// more atoms moved
auto &g1 = spc.groups.at(d.index);
// for (auto &g2 : spc.groups)
#pragma omp parallel for reduction(+ : u) schedule(dynamic) if (omp_enable and omp_g2g)
for (size_t i = 0; i < spc.groups.size(); i++) {
auto &g2 = spc.groups[i];
if (&g1 != &g2)
u += g2g(g1, g2, d.atoms);
}
if (d.internal)
u += g_internal(g1, d.atoms);
return u;
}
auto moved = change.touchedGroupIndex(); // index of moved groups
auto fixed = view::ints(0, int(spc.groups.size())) | view::remove_if([&moved](int i) {
return std::binary_search(moved.begin(), moved.end(), i);
}); // index of static groups
if (change.dN) {
/*auto moved = change.touchedGroupIndex(); // index of moved groups
std::vector<int> Moved;
for (auto i: moved) {
Moved.push_back(i);
}
std::sort( Moved.begin(), Moved.end() );
auto fixed = view::ints( 0, int(spc.groups.size()) )
| view::remove_if(
[&Moved](int i){return std::binary_search(Moved.begin(), Moved.end(), i);}
); // index of static groups*/
for (auto cg1 = change.groups.begin(); cg1 < change.groups.end();
++cg1) { // Loop over all changed groups
std::vector<int> ifiltered, jfiltered; // Active atoms
auto g1 = &spc.groups.at(cg1->index);
for (auto i : cg1->atoms) {
if (i < g1->size())
ifiltered.push_back(i);
}
// Skip if the group is empty
if (not ifiltered.empty())
for (auto j : fixed)
u += g2g(*g1, spc.groups[j], ifiltered, jfiltered);
for (auto cg2 = cg1; ++cg2 != change.groups.end();) {
for (auto i : cg2->atoms)
if (i < spc.groups.at(cg2->index).size())
jfiltered.push_back(i);
// Skip if both groups are empty
if (not(ifiltered.empty() && jfiltered.empty()))
u += g2g(*g1, spc.groups.at(cg2->index), ifiltered, jfiltered);
jfiltered.clear();
}
if (not ifiltered.empty() and not molecules.at(g1->id).rigid) {
if (cg1->all) {
u += g_internal(*g1);
} else
u += g_internal(*g1, ifiltered);
}
}
return u;
}
// moved<->moved
if (change.moved2moved) {
for (auto i = moved.begin(); i != moved.end(); ++i)
for (auto j = i; ++j != moved.end();)
u += g2g(spc.groups[*i], spc.groups[*j]);
}
// moved<->static
if (omp_enable and omp_g2g) {
std::vector<std::pair<int, int>> pairs(size(moved) * size(fixed));
size_t cnt = 0;
for (auto i : moved)
for (auto j : fixed)
pairs[cnt++] = {i, j};
#pragma omp parallel for reduction(+ : u) schedule(dynamic) if (omp_enable and omp_g2g)
for (size_t i = 0; i < pairs.size(); i++)
u += g2g(spc.groups[pairs[i].first], spc.groups[pairs[i].second]);
} else
for (auto i : moved)
for (auto j : fixed)
u += g2g(spc.groups[i], spc.groups[j]);
// more todo!
}
return u;
}
}; //!< Nonbonded, pair-wise additive energy term
template <typename Tpairpot> class NonbondedCached : public Nonbonded<Tpairpot> {
private:
typedef Nonbonded<Tpairpot> base;
typedef typename Space::Tgroup Tgroup;
Eigen::MatrixXf cache;
Space &spc;
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wunused-parameter"
double g2g(const Tgroup &g1, const Tgroup &g2, const std::vector<int> &index = std::vector<int>(),
const std::vector<int> &jndex = std::vector<int>()) override {
#pragma GCC diagnostic pop
//assert(index.empty() && "unimplemented");
//assert(jndex.empty() && "unimplemented");
int i = &g1 - &base::spc.groups.front();
int j = &g2 - &base::spc.groups.front();
if (j < i)
std::swap(i, j);
if (base::key == Energybase::NEW) { // if this is from the trial system,
double u = 0;
if (not base::cut(g1, g2)) {
for (auto &i : g1)
for (auto &j : g2)
u += base::i2i(i, j);
}
cache(i, j) = u;
}
return cache(i, j); // return (cached) value
}
public:
NonbondedCached(const json &j, Space &spc, BasePointerVector<Energybase> &pot) : base(j, spc, pot), spc(spc) {
base::name += "EM";
init();
}
void init() override {
cache.resize(spc.groups.size(), spc.groups.size());
cache.setZero();
for (auto i = base::spc.groups.begin(); i < base::spc.groups.end(); ++i) {
for (auto j = i; ++j != base::spc.groups.end();) {
int k = &(*i) - &base::spc.groups.front();
int l = &(*j) - &base::spc.groups.front();
if (l < k)
std::swap(k, l);
double u = 0;
if (!base::cut(*i, *j)) {
for (auto &k : *i)
for (auto &l : *j)
u += base::i2i(k, l);
}
cache(k, l) = u;
}
}
} //!< Cache pair interactions in matrix
double energy(Change &change) override {
using namespace ranges;
double u = 0;
if (change) {
if (change.all || change.dV) {
#pragma omp parallel for reduction(+ : u) schedule(dynamic) if (this->omp_enable)
for (auto i = base::spc.groups.begin(); i < base::spc.groups.end(); ++i) {
for (auto j = i; ++j != base::spc.groups.end();)
u += g2g(*i, *j);
}
return u;
}
// if exactly ONE molecule is changed
if (change.groups.size() == 1) {
auto &d = change.groups[0];
auto &g1 = base::spc.groups.at(d.index);
#pragma omp parallel for reduction(+ : u) schedule(dynamic) if (this->omp_enable and this->omp_g2g)
for (size_t i = 0; i < spc.groups.size(); i++) {
auto &g2 = spc.groups[i];
if (&g1 != &g2)
u += g2g(g1, g2, d.atoms);
}
return u;
}
auto moved = change.touchedGroupIndex(); // index of moved groups
auto fixed = view::ints(0, int(base::spc.groups.size())) | view::remove_if([&moved](int i) {
return std::binary_search(moved.begin(), moved.end(), i);
}); // index of static groups
// moved<->moved
if (change.moved2moved)
for (auto i = moved.begin(); i != moved.end(); ++i)
for (auto j = i; ++j != moved.end();)
u += g2g(base::spc.groups[*i], base::spc.groups[*j]);
// moved<->static
if (this->omp_enable and this->omp_g2g) {
std::vector<std::pair<int, int>> pairs(size(moved) * size(fixed));
size_t cnt = 0;
for (auto i : moved)
for (auto j : fixed)
pairs[cnt++] = {i, j};
#pragma omp parallel for reduction(+ : u) schedule(dynamic) if (this->omp_enable and this->omp_g2g)
for (size_t i = 0; i < pairs.size(); i++)
u += g2g(spc.groups[pairs[i].first], spc.groups[pairs[i].second]);
} else
for (auto i : moved)
for (auto j : fixed)
u += g2g(base::spc.groups[i], base::spc.groups[j]);
// more todo!
}
return u;
}
void sync(Energybase *basePtr, Change &change) override {
auto other = dynamic_cast<decltype(this)>(basePtr);
assert(other);
if (change.all || change.dV)
cache.triangularView<Eigen::StrictlyUpper>() =
(other->cache).template triangularView<Eigen::StrictlyUpper>();
else
for (auto &d : change.groups) {
for (int i = 0; i < d.index; i++)
cache(i, d.index) = other->cache(i, d.index);
for (size_t i = d.index + 1; i < base::spc.groups.size(); i++)
cache(d.index, i) = other->cache(d.index, i);
}
} //!< Copy energy matrix from other
}; //!< Nonbonded with cached energies (Energy Matrix)
#ifdef ENABLE_FREESASA
/**
* @brief Interface to the FreeSASA C-library. Experimental and unoptimized.
*
* https://freesasa.github.io/
*/
class SASAEnergy : public Energybase {
public:
std::vector<double> sasa, radii, positions;
private:
Space &spc;
double cosolute_concentration; // co-solute concentration (mol/l)
freesasa_parameters parameters;
Average<double> avgArea; // average surface area
void updatePositions(const ParticleVector &p);
void updateRadii(const ParticleVector &p);
void updateSASA(const ParticleVector &p, const Change &change);
void to_json(json &j) const override;
void sync(Energybase *basePtr, Change &c) override;
public:
/**
* @param spc
* @param cosolute_concentration in particles per angstrom cubed
* @param probe_radius in angstrom
*/
SASAEnergy(Space &spc, double cosolute_concentration = 0.0, double probe_radius = 1.4);
SASAEnergy(const json &j, Space &spc);
void init() override;
double energy(Change &) override;
}; //!< SASA energy from transfer free energies
#endif
struct Example2D : public Energybase {
Point &i; // reference to 1st particle in the system
Example2D(const json &, Space &spc);
double energy(Change &change) override;
};
class Hamiltonian : public Energybase, public BasePointerVector<Energybase> {
protected:
double maxenergy = pc::infty; //!< Maximum allowed energy change
void to_json(json &j) const override;
void addEwald(const json &j, Space &spc); //!< Adds an instance of reciprocal space Ewald energies (if appropriate)
public:
Hamiltonian(Space &spc, const json &j);
double energy(Change &change) override; //!< Energy due to changes
void init() override;
void sync(Energybase *basePtr, Change &change) override;
}; //!< Aggregates and sum energy terms
} // namespace Energy
} // namespace Faunus
|
3d7pt_var.lbpar.c | #include <omp.h>
#include <math.h>
#define ceild(n,d) ceil(((double)(n))/((double)(d)))
#define floord(n,d) floor(((double)(n))/((double)(d)))
#define max(x,y) ((x) > (y)? (x) : (y))
#define min(x,y) ((x) < (y)? (x) : (y))
/*
* Order-1, 3D 7 point stencil with variable coefficients
* Adapted from PLUTO and Pochoir test bench
*
* Tareq Malas
*/
#include <stdio.h>
#include <stdlib.h>
#include <sys/time.h>
#ifdef LIKWID_PERFMON
#include <likwid.h>
#endif
#include "print_utils.h"
#define TESTS 2
#define MAX(a,b) ((a) > (b) ? a : b)
#define MIN(a,b) ((a) < (b) ? a : b)
/* Subtract the `struct timeval' values X and Y,
* storing the result in RESULT.
*
* Return 1 if the difference is negative, otherwise 0.
*/
int timeval_subtract(struct timeval *result, struct timeval *x, struct timeval *y)
{
/* Perform the carry for the later subtraction by updating y. */
if (x->tv_usec < y->tv_usec)
{
int nsec = (y->tv_usec - x->tv_usec) / 1000000 + 1;
y->tv_usec -= 1000000 * nsec;
y->tv_sec += nsec;
}
if (x->tv_usec - y->tv_usec > 1000000)
{
int nsec = (x->tv_usec - y->tv_usec) / 1000000;
y->tv_usec += 1000000 * nsec;
y->tv_sec -= nsec;
}
/* Compute the time remaining to wait.
* tv_usec is certainly positive.
*/
result->tv_sec = x->tv_sec - y->tv_sec;
result->tv_usec = x->tv_usec - y->tv_usec;
/* Return 1 if result is negative. */
return x->tv_sec < y->tv_sec;
}
int main(int argc, char *argv[])
{
int t, i, j, k, m, test;
int Nx, Ny, Nz, Nt;
if (argc > 3) {
Nx = atoi(argv[1])+2;
Ny = atoi(argv[2])+2;
Nz = atoi(argv[3])+2;
}
if (argc > 4)
Nt = atoi(argv[4]);
// allocate the arrays
double ****A = (double ****) malloc(sizeof(double***)*2);
for(m=0; m<2;m++){
A[m] = (double ***) malloc(sizeof(double**)*Nz);
for(i=0; i<Nz; i++){
A[m][i] = (double**) malloc(sizeof(double*)*Ny);
for(j=0;j<Ny;j++){
A[m][i][j] = (double*) malloc(sizeof(double)*Nx);
}
}
}
double ****coef = (double ****) malloc(sizeof(double***)*7);
for(m=0; m<7;m++){
coef[m] = (double ***) malloc(sizeof(double**)*Nz);
for(i=0; i<Nz; i++){
coef[m][i] = (double**) malloc(sizeof(double*)*Ny);
for(j=0;j<Ny;j++){
coef[m][i][j] = (double*) malloc(sizeof(double)*Nx);
}
}
}
// tile size information, including extra element to decide the list length
int *tile_size = (int*) malloc(sizeof(int));
tile_size[0] = -1;
// The list is modified here before source-to-source transformations
tile_size = (int*) realloc((void *)tile_size, sizeof(int)*5);
tile_size[0] = 8;
tile_size[1] = 8;
tile_size[2] = 24;
tile_size[3] = 2048;
tile_size[4] = -1;
// for timekeeping
int ts_return = -1;
struct timeval start, end, result;
double tdiff = 0.0, min_tdiff=1.e100;
const int BASE = 1024;
// initialize variables
//
srand(42);
for (i = 1; i < Nz; i++) {
for (j = 1; j < Ny; j++) {
for (k = 1; k < Nx; k++) {
A[0][i][j][k] = 1.0 * (rand() % BASE);
}
}
}
for (m=0; m<7; m++) {
for (i=1; i<Nz; i++) {
for (j=1; j<Ny; j++) {
for (k=1; k<Nx; k++) {
coef[m][i][j][k] = 1.0 * (rand() % BASE);
}
}
}
}
#ifdef LIKWID_PERFMON
LIKWID_MARKER_INIT;
#pragma omp parallel
{
LIKWID_MARKER_THREADINIT;
#pragma omp barrier
LIKWID_MARKER_START("calc");
}
#endif
int num_threads = 1;
#if defined(_OPENMP)
num_threads = omp_get_max_threads();
#endif
for(test=0; test<TESTS; test++){
gettimeofday(&start, 0);
// serial execution - Addition: 6 && Multiplication: 2
/* Copyright (C) 1991-2014 Free Software Foundation, Inc.
This file is part of the GNU C Library.
The GNU C Library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
The GNU C Library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with the GNU C Library; if not, see
<http://www.gnu.org/licenses/>. */
/* This header is separate from features.h so that the compiler can
include it implicitly at the start of every compilation. It must
not itself include <features.h> or any other header that includes
<features.h> because the implicit include comes before any feature
test macros that may be defined in a source file before it first
explicitly includes a system header. GCC knows the name of this
header in order to preinclude it. */
/* glibc's intent is to support the IEC 559 math functionality, real
and complex. If the GCC (4.9 and later) predefined macros
specifying compiler intent are available, use them to determine
whether the overall intent is to support these features; otherwise,
presume an older compiler has intent to support these features and
define these macros by default. */
/* wchar_t uses ISO/IEC 10646 (2nd ed., published 2011-03-15) /
Unicode 6.0. */
/* We do not support C11 <threads.h>. */
int t1, t2, t3, t4, t5, t6, t7, t8;
int lb, ub, lbp, ubp, lb2, ub2;
register int lbv, ubv;
/* Start of CLooG code */
if ((Nt >= 2) && (Nx >= 3) && (Ny >= 3) && (Nz >= 3)) {
for (t1=-1;t1<=floord(Nt-2,4);t1++) {
lbp=max(ceild(t1,2),ceild(8*t1-Nt+3,8));
ubp=min(floord(Nt+Nz-4,8),floord(4*t1+Nz+1,8));
#pragma omp parallel for private(lbv,ubv,t3,t4,t5,t6,t7,t8)
for (t2=lbp;t2<=ubp;t2++) {
for (t3=max(max(0,ceild(t1-5,6)),ceild(8*t2-Nz-20,24));t3<=min(min(min(floord(Nt+Ny-4,24),floord(4*t1+Ny+5,24)),floord(8*t2+Ny+4,24)),floord(8*t1-8*t2+Nz+Ny+3,24));t3++) {
for (t4=max(max(max(0,ceild(t1-511,512)),ceild(8*t2-Nz-2044,2048)),ceild(24*t3-Ny-2044,2048));t4<=min(min(min(min(floord(Nt+Nx-4,2048),floord(4*t1+Nx+5,2048)),floord(8*t2+Nx+4,2048)),floord(24*t3+Nx+20,2048)),floord(8*t1-8*t2+Nz+Nx+3,2048));t4++) {
for (t5=max(max(max(max(max(0,4*t1),8*t1-8*t2+1),8*t2-Nz+2),24*t3-Ny+2),2048*t4-Nx+2);t5<=min(min(min(min(min(Nt-2,4*t1+7),8*t2+6),24*t3+22),2048*t4+2046),8*t1-8*t2+Nz+5);t5++) {
for (t6=max(max(8*t2,t5+1),-8*t1+8*t2+2*t5-7);t6<=min(min(8*t2+7,-8*t1+8*t2+2*t5),t5+Nz-2);t6++) {
for (t7=max(24*t3,t5+1);t7<=min(24*t3+23,t5+Ny-2);t7++) {
lbv=max(2048*t4,t5+1);
ubv=min(2048*t4+2047,t5+Nx-2);
#pragma ivdep
#pragma vector always
for (t8=lbv;t8<=ubv;t8++) {
A[( t5 + 1) % 2][ (-t5+t6)][ (-t5+t7)][ (-t5+t8)] = (((((((coef[0][ (-t5+t6)][ (-t5+t7)][ (-t5+t8)] * A[ t5 % 2][ (-t5+t6)][ (-t5+t7)][ (-t5+t8)]) + (coef[1][ (-t5+t6)][ (-t5+t7)][ (-t5+t8)] * A[ t5 % 2][ (-t5+t6) - 1][ (-t5+t7)][ (-t5+t8)])) + (coef[2][ (-t5+t6)][ (-t5+t7)][ (-t5+t8)] * A[ t5 % 2][ (-t5+t6)][ (-t5+t7) - 1][ (-t5+t8)])) + (coef[3][ (-t5+t6)][ (-t5+t7)][ (-t5+t8)] * A[ t5 % 2][ (-t5+t6)][ (-t5+t7)][ (-t5+t8) - 1])) + (coef[4][ (-t5+t6)][ (-t5+t7)][ (-t5+t8)] * A[ t5 % 2][ (-t5+t6) + 1][ (-t5+t7)][ (-t5+t8)])) + (coef[5][ (-t5+t6)][ (-t5+t7)][ (-t5+t8)] * A[ t5 % 2][ (-t5+t6)][ (-t5+t7) + 1][ (-t5+t8)])) + (coef[6][ (-t5+t6)][ (-t5+t7)][ (-t5+t8)] * A[ t5 % 2][ (-t5+t6)][ (-t5+t7)][ (-t5+t8) + 1]));;
}
}
}
}
}
}
}
}
}
/* End of CLooG code */
gettimeofday(&end, 0);
ts_return = timeval_subtract(&result, &end, &start);
tdiff = (double) (result.tv_sec + result.tv_usec * 1.0e-6);
min_tdiff = min(min_tdiff, tdiff);
printf("Rank 0 TEST# %d time: %f\n", test, tdiff);
}
PRINT_RESULTS(1, "variable no-symmetry")
#ifdef LIKWID_PERFMON
#pragma omp parallel
{
LIKWID_MARKER_STOP("calc");
}
LIKWID_MARKER_CLOSE;
#endif
// Free allocated arrays
for(i=0; i<Nz; i++){
for(j=0;j<Ny;j++){
free(A[0][i][j]);
free(A[1][i][j]);
}
free(A[0][i]);
free(A[1][i]);
}
free(A[0]);
free(A[1]);
for(m=0; m<7;m++){
for(i=0; i<Nz; i++){
for(j=0;j<Ny;j++){
free(coef[m][i][j]);
}
free(coef[m][i]);
}
free(coef[m]);
}
return 0;
}
|
omp_bug3.c | /******************************************************************************
* FILE: omp_bug3.c
* DESCRIPTION:
* Run time error
* AUTHOR: Blaise Barney 01/09/04
* LAST REVISED: 06/28/05
******************************************************************************/
#include <omp.h>
#include <stdio.h>
#include <stdlib.h>
#define N 50
int main (int argc, char *argv[])
{
int i, nthreads, tid, section;
float a[N], b[N], c[N];
void print_results(float array[N], int tid, int section);
/* Some initializations */
for (i=0; i<N; i++)
a[i] = b[i] = i * 1.0;
#pragma omp parallel private(c,i,tid,section)
{
tid = omp_get_thread_num();
if (tid == 0)
{
nthreads = omp_get_num_threads();
printf("Number of threads = %d\n", nthreads);
}
/*** Use barriers for clean output ***/
#pragma omp barrier
printf("Thread %d starting...\n",tid);
#pragma omp barrier
#pragma omp sections nowait
{
#pragma omp section
{
section = 1;
for (i=0; i<N; i++)
c[i] = a[i] * b[i];
print_results(c, tid, section);
}
#pragma omp section
{
section = 2;
for (i=0; i<N; i++)
c[i] = a[i] + b[i];
print_results(c, tid, section);
}
} /* end of sections */
/*** Use barrier for clean output ***/
#pragma omp barrier
printf("Thread %d exiting...\n",tid);
} /* end of parallel section */
}
void print_results(float array[N], int tid, int section)
{
int i,j;
j = 1;
/*** use critical for clean output ***/
#pragma omp critical
{
printf("\nThread %d did section %d. The results are:\n", tid, section);
for (i=0; i<N; i++) {
printf("%e ",array[i]);
j++;
if (j == 6) {
printf("\n");
j = 1;
}
}
printf("\n");
} /*** end of critical ***/
#pragma omp barrier
printf("Thread %d done and synchronized.\n", tid);
}
|
for_lastprivate.c |
#include <stdio.h>
#include <math.h>
#include "omp_testsuite.h"
int
check_for_lastprivate (FILE * logFile)
{
int sum = 0;
int sum0 = 0;
int known_sum;
int i;
int i0 = -1;
#pragma omp parallel firstprivate(sum0)
{
/*sum0=0; */
#pragma omp for schedule(static,7) lastprivate(i0)
for (i = 1; i <= LOOPCOUNT; i++)
{
sum0 = sum0 + i;
i0 = i;
} /*end of for */
#pragma omp critical
{
sum = sum + sum0;
} /*end of critical */
} /* end of parallel */
known_sum = (LOOPCOUNT * (LOOPCOUNT + 1)) / 2;
return ((known_sum == sum) && (i0 == LOOPCOUNT));
} /* end of check_for_lastprivate */
int
crosscheck_for_lastprivate (FILE * logFile)
{
int sum = 0;
int sum0 = 0;
int known_sum;
int i;
int i0 = -1;
#pragma omp parallel firstprivate(sum0)
{
/*sum0=0; */
#pragma omp for schedule(static,7)
for (i = 1; i <= LOOPCOUNT; i++)
{
sum0 = sum0 + i;
i0 = i;
} /*end of for */
#pragma omp critical
{
sum = sum + sum0;
} /*end of critical */
} /* end of parallel */
known_sum = (LOOPCOUNT * (LOOPCOUNT + 1)) / 2;
return ((known_sum == sum) && (i0 == LOOPCOUNT));
} /* end of check_for_lastprivate */
|
sort.c | /**********************************************************************************************/
/* This program is part of the Barcelona OpenMP Tasks Suite */
/* Copyright (C) 2009 Barcelona Supercomputing Center - Centro Nacional de Supercomputacion */
/* Copyright (C) 2009 Universitat Politecnica de Catalunya */
/* */
/* This program is free software; you can redistribute it and/or modify */
/* it under the terms of the GNU General Public License as published by */
/* the Free Software Foundation; either version 2 of the License, or */
/* (at your option) any later version. */
/* */
/* This program is distributed in the hope that it will be useful, */
/* but WITHOUT ANY WARRANTY; without even the implied warranty of */
/* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the */
/* GNU General Public License for more details. */
/* */
/* You should have received a copy of the GNU General Public License */
/* along with this program; if not, write to the Free Software */
/* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */
/**********************************************************************************************/
/*
* Original code from the Cilk project
*
* Copyright (c) 2000 Massachusetts Institute of Technology
* Copyright (c) 2000 Matteo Frigo
*/
/*
* this program uses an algorithm that we call `cilksort'.
* The algorithm is essentially mergesort:
*
* cilksort(in[1..n]) =
* spawn cilksort(in[1..n/2], tmp[1..n/2])
* spawn cilksort(in[n/2..n], tmp[n/2..n])
* sync
* spawn cilkmerge(tmp[1..n/2], tmp[n/2..n], in[1..n])
*
*
* The procedure cilkmerge does the following:
*
* cilkmerge(A[1..n], B[1..m], C[1..(n+m)]) =
* find the median of A \union B using binary
* search. The binary search gives a pair
* (ma, mb) such that ma + mb = (n + m)/2
* and all elements in A[1..ma] are smaller than
* B[mb..m], and all the B[1..mb] are smaller
* than all elements in A[ma..n].
*
* spawn cilkmerge(A[1..ma], B[1..mb], C[1..(n+m)/2])
* spawn cilkmerge(A[ma..m], B[mb..n], C[(n+m)/2 .. (n+m)])
* sync
*
* The algorithm appears for the first time (AFAIK) in S. G. Akl and
* N. Santoro, "Optimal Parallel Merging and Sorting Without Memory
* Conflicts", IEEE Trans. Comp., Vol. C-36 No. 11, Nov. 1987 . The
* paper does not express the algorithm using recursion, but the
* idea of finding the median is there.
*
* For cilksort of n elements, T_1 = O(n log n) and
* T_\infty = O(log^3 n). There is a way to shave a
* log factor in the critical path (left as homework).
*/
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include "bots.h"
#include "app-desc.h"
ELM *array, *tmp;
static unsigned long rand_nxt = 0;
static inline unsigned long my_rand(void)
{
rand_nxt = rand_nxt * 1103515245 + 12345;
return rand_nxt;
}
static inline void my_srand(unsigned long seed)
{
rand_nxt = seed;
}
static inline ELM med3(ELM a, ELM b, ELM c)
{
if (a < b) {
if (b < c) {
return b;
} else {
if (a < c)
return c;
else
return a;
}
} else {
if (b > c) {
return b;
} else {
if (a > c)
return c;
else
return a;
}
}
}
/*
* simple approach for now; a better median-finding
* may be preferable
*/
static inline ELM choose_pivot(ELM *low, ELM *high)
{
return med3(*low, *high, low[(high - low) / 2]);
}
static ELM *seqpart(ELM *low, ELM *high)
{
ELM pivot;
ELM h, l;
ELM *curr_low = low;
ELM *curr_high = high;
pivot = choose_pivot(low, high);
while (1) {
while ((h = *curr_high) > pivot)
curr_high--;
while ((l = *curr_low) < pivot)
curr_low++;
if (curr_low >= curr_high)
break;
*curr_high-- = l;
*curr_low++ = h;
}
/*
* I don't know if this is really necessary.
* The problem is that the pivot is not always the
* first element, and the partition may be trivial.
* However, if the partition is trivial, then
* *high is the largest element, whence the following
* code.
*/
if (curr_high < high)
return curr_high;
else
return curr_high - 1;
}
#define swap(a, b) \
{ \
ELM tmp;\
tmp = a;\
a = b;\
b = tmp;\
}
static void insertion_sort(ELM *low, ELM *high)
{
ELM *p, *q;
ELM a, b;
for (q = low + 1; q <= high; ++q) {
a = q[0];
for (p = q - 1; p >= low && (b = p[0]) > a; p--)
p[1] = b;
p[1] = a;
}
}
/*
* tail-recursive quicksort, almost unrecognizable :-)
*/
void seqquick(ELM *low, ELM *high)
{
ELM *p;
while (high - low >= bots_app_cutoff_value_2) {
p = seqpart(low, high);
seqquick(low, p);
low = p + 1;
}
insertion_sort(low, high);
}
void seqmerge(ELM *low1, ELM *high1, ELM *low2, ELM *high2,
ELM *lowdest)
{
ELM a1, a2;
/*
* The following 'if' statement is not necessary
* for the correctness of the algorithm, and is
* in fact subsumed by the rest of the function.
* However, it is a few percent faster. Here is why.
*
* The merging loop below has something like
* if (a1 < a2) {
* *dest++ = a1;
* ++low1;
* if (end of array) break;
* a1 = *low1;
* }
*
* Now, a1 is needed immediately in the next iteration
* and there is no way to mask the latency of the load.
* A better approach is to load a1 *before* the end-of-array
* check; the problem is that we may be speculatively
* loading an element out of range. While this is
* probably not a problem in practice, yet I don't feel
* comfortable with an incorrect algorithm. Therefore,
* I use the 'fast' loop on the array (except for the last
* element) and the 'slow' loop for the rest, saving both
* performance and correctness.
*/
if (low1 < high1 && low2 < high2) {
a1 = *low1;
a2 = *low2;
for (;;) {
if (a1 < a2) {
*lowdest++ = a1;
a1 = *++low1;
if (low1 >= high1)
break;
} else {
*lowdest++ = a2;
a2 = *++low2;
if (low2 >= high2)
break;
}
}
}
if (low1 <= high1 && low2 <= high2) {
a1 = *low1;
a2 = *low2;
for (;;) {
if (a1 < a2) {
*lowdest++ = a1;
++low1;
if (low1 > high1)
break;
a1 = *low1;
} else {
*lowdest++ = a2;
++low2;
if (low2 > high2)
break;
a2 = *low2;
}
}
}
if (low1 > high1) {
memcpy(lowdest, low2, sizeof(ELM) * (high2 - low2 + 1));
} else {
memcpy(lowdest, low1, sizeof(ELM) * (high1 - low1 + 1));
}
}
#define swap_indices(a, b) \
{ \
ELM *tmp;\
tmp = a;\
a = b;\
b = tmp;\
}
ELM *binsplit(ELM val, ELM *low, ELM *high)
{
/*
* returns index which contains greatest element <= val. If val is
* less than all elements, returns low-1
*/
ELM *mid;
while (low != high) {
mid = low + ((high - low + 1) >> 1);
if (val <= *mid)
high = mid - 1;
else
low = mid;
}
if (*low > val)
return low - 1;
else
return low;
}
void cilkmerge_par(ELM *low1, ELM *high1, ELM *low2, ELM *high2, ELM *lowdest)
{
/*
* Cilkmerge: Merges range [low1, high1] with range [low2, high2]
* into the range [lowdest, ...]
*/
ELM *split1, *split2; /*
* where each of the ranges are broken for
* recursive merge
*/
long int lowsize; /*
* total size of lower halves of two
* ranges - 2
*/
/*
* We want to take the middle element (indexed by split1) from the
* larger of the two arrays. The following code assumes that split1
* is taken from range [low1, high1]. So if [low1, high1] is
* actually the smaller range, we should swap it with [low2, high2]
*/
if (high2 - low2 > high1 - low1) {
swap_indices(low1, low2);
swap_indices(high1, high2);
}
if (high2 < low2) {
/* smaller range is empty */
memcpy(lowdest, low1, sizeof(ELM) * (high1 - low1));
return;
}
if (high2 - low2 < bots_app_cutoff_value ) {
seqmerge(low1, high1, low2, high2, lowdest);
return;
}
/*
* Basic approach: Find the middle element of one range (indexed by
* split1). Find where this element would fit in the other range
* (indexed by split 2). Then merge the two lower halves and the two
* upper halves.
*/
split1 = ((high1 - low1 + 1) / 2) + low1;
split2 = binsplit(*split1, low2, high2);
lowsize = split1 - low1 + split2 - low2;
/*
* directly put the splitting element into
* the appropriate location
*/
*(lowdest + lowsize + 1) = *split1;
#pragma omp task
cilkmerge_par(low1, split1 - 1, low2, split2, lowdest);
#pragma omp task
cilkmerge_par(split1 + 1, high1, split2 + 1, high2,
lowdest + lowsize + 2);
#pragma omp taskwait
return;
}
void cilksort_par(ELM *low, ELM *tmp, long size)
{
/*
* divide the input in four parts of the same size (A, B, C, D)
* Then:
* 1) recursively sort A, B, C, and D (in parallel)
* 2) merge A and B into tmp1, and C and D into tmp2 (in parallel)
* 3) merge tmp1 and tmp2 into the original array
*/
long quarter = size / 4;
ELM *A, *B, *C, *D, *tmpA, *tmpB, *tmpC, *tmpD;
if (size < bots_app_cutoff_value_1 ) {
/* quicksort when less than 1024 elements */
seqquick(low, low + size - 1);
return;
}
A = low;
tmpA = tmp;
B = A + quarter;
tmpB = tmpA + quarter;
C = B + quarter;
tmpC = tmpB + quarter;
D = C + quarter;
tmpD = tmpC + quarter;
#pragma omp task
cilksort_par(A, tmpA, quarter);
#pragma omp task
cilksort_par(B, tmpB, quarter);
#pragma omp task
cilksort_par(C, tmpC, quarter);
#pragma omp task
cilksort_par(D, tmpD, size - 3 * quarter);
#pragma omp taskwait
#pragma omp task
cilkmerge_par(A, A + quarter - 1, B, B + quarter - 1, tmpA);
#pragma omp task
cilkmerge_par(C, C + quarter - 1, D, low + size - 1, tmpC);
#pragma omp taskwait
cilkmerge_par(tmpA, tmpC - 1, tmpC, tmpA + size - 1, A);
}
void scramble_array( ELM *array )
{
unsigned long i;
unsigned long j;
for (i = 0; i < bots_arg_size; ++i) {
j = my_rand();
j = j % bots_arg_size;
swap(array[i], array[j]);
}
}
void fill_array( ELM *array )
{
unsigned long i;
my_srand(1);
/* first, fill with integers 1..size */
for (i = 0; i < bots_arg_size; ++i) {
array[i] = i;
}
}
void sort_init ( void )
{
/* Checking arguments */
if (bots_arg_size < 4) {
bots_message("%s can not be less than 4, using 4 as a parameter.\n", BOTS_APP_DESC_ARG_SIZE );
bots_arg_size = 4;
}
if (bots_app_cutoff_value < 2) {
bots_message("%s can not be less than 2, using 2 as a parameter.\n", BOTS_APP_DESC_ARG_CUTOFF);
bots_app_cutoff_value = 2;
}
else if (bots_app_cutoff_value > bots_arg_size ) {
bots_message("%s can not be greather than vector size, using %d as a parameter.\n", BOTS_APP_DESC_ARG_CUTOFF, bots_arg_size);
bots_app_cutoff_value = bots_arg_size;
}
if (bots_app_cutoff_value_1 > bots_arg_size ) {
bots_message("%s can not be greather than vector size, using %d as a parameter.\n", BOTS_APP_DESC_ARG_CUTOFF_1, bots_arg_size);
bots_app_cutoff_value_1 = bots_arg_size;
}
if (bots_app_cutoff_value_2 > bots_arg_size ) {
bots_message("%s can not be greather than vector size, using %d as a parameter.\n", BOTS_APP_DESC_ARG_CUTOFF_2, bots_arg_size);
bots_app_cutoff_value_2 = bots_arg_size;
}
if (bots_app_cutoff_value_2 > bots_app_cutoff_value_1) {
bots_message("%s can not be greather than %s, using %d as a parameter.\n",
BOTS_APP_DESC_ARG_CUTOFF_2,
BOTS_APP_DESC_ARG_CUTOFF_1,
bots_app_cutoff_value_1
);
bots_app_cutoff_value_2 = bots_app_cutoff_value_1;
}
array = (ELM *) malloc(bots_arg_size * sizeof(ELM));
tmp = (ELM *) malloc(bots_arg_size * sizeof(ELM));
fill_array(array);
scramble_array(array);
}
void sort_par ( void )
{
bots_message("Computing multisort algorithm (n=%d) ", bots_arg_size);
#pragma omp parallel
#pragma omp single nowait
#pragma omp task
cilksort_par(array, tmp, bots_arg_size);
bots_message(" completed!\n");
}
int sort_verify ( void )
{
int i, success = 1;
for (i = 0; i < bots_arg_size; ++i)
if (array[i] != i)
success = 0;
return success ? BOTS_RESULT_SUCCESSFUL : BOTS_RESULT_UNSUCCESSFUL;
}
|
CPUMatrixImpl.h | //
// Copyright (c) Microsoft. All rights reserved.
// Licensed under the MIT license. See LICENSE.md file in the project root for full license information.
//
// CPUMatrix.h : template implementation of all matrix functions on the CPU side
//
#pragma once
#include "Basics.h"
#include "File.h"
#include "CPUMatrix.h"
#include "TensorOps.h"
#include <assert.h>
#include <stdexcept>
#include <omp.h>
#include <math.h>
#include <random>
#include <chrono>
#include <exception>
#include <thread>
#include <iostream>
#include <algorithm>
#pragma warning(push)
#pragma warning(disable:4244) // 'conversion' conversion from 'type1' to 'type2', possible loss of data
#include <boost/random/normal_distribution.hpp>
#pragma warning(pop)
#include <boost/random/uniform_real_distribution.hpp>
#ifdef _WIN32
#define NOMINMAX
#include "Windows.h"
#else
#include <cfloat>
#endif
#ifdef LEAKDETECT
#include <vld.h>
#endif
#pragma warning(disable : 4100) // unreferenced formal parameter; "struct TensorOpReduction<ElemType, OPFN, typename ReductionOp, N, -1>" trigger this
#pragma warning(disable : 4127) // conditional expression is constant; "if (sizeof(ElemType)==sizeof(float))" triggers this
#pragma warning(disable : 4244) // unreachable code; triggered for unknown reasons
#pragma warning(disable : 4702) // conversion from 'double' to 'float'
#ifdef USE_MKL
// requires MKL 10.0 and above
#include <mkl.h>
#else
#ifdef _MSC_VER
// Visual Studio doesn't define standard complex types properly
#define HAVE_LAPACK_CONFIG_H
#define LAPACK_COMPLEX_STRUCTURE
#endif
#include <cblas.h>
#include <lapacke.h>
#endif
#define SWAP(a, b) \
{ \
(a) ^= (b); \
(b) ^= (a); \
(a) ^= (b); \
}
#define IDX2C(i, j, ld) (((j) * (ld)) + (i)) // 0 based indexing
namespace Microsoft { namespace MSR { namespace CNTK {
#pragma region Helpful Enum Definitions
enum class MatrixOrder
{
RowMajor = 101, // row-major arrays
ColMajor = 102 // column-major arrays
};
enum class MatrixTranspose : char
{
NoTrans = 'N', // trans='N'
Trans = 'T', // trans='T'
ConjTrans = 'C' // trans='C'
};
enum class SymMatrixType : char
{
Up = 'U', // symmetric matrix is stored in the upper part
Low = 'L', // symmetric matrix is stored in thelower part
Full = 'F', // full populated
NotSymmetric = 'N' // not a symmetric matrix
};
enum class MatrixOpSide : char
{
Left = 'L', // left multiply
Right = 'R', // right multiply
};
#pragma endregion Helpful Enum Definitions
#pragma region Constructors and Destructor
template <class ElemType>
CPUMatrix<ElemType>::CPUMatrix()
{
ZeroInit();
}
// helper to allocate an array of ElemType
// Use this instead of new[] to get NaN initialization for debugging.
template <class ElemType>
static ElemType* NewArray(size_t n)
{
ElemType* p = new ElemType[n]();
#if 0 // _DEBUG
ElemType nan = Matrix<ElemType>::MakeNan(__LINE__);
for (size_t i = 0; i < n; i++)
p[i] = nan;
#endif
return p;
}
template <class ElemType>
CPUMatrix<ElemType>::CPUMatrix(const size_t numRows, const size_t numCols)
{
ZeroInit();
m_numRows = numRows;
m_numCols = numCols;
SetSizeAllocated(GetNumElements());
if (GetNumElements() != 0)
{
SetBuffer(NewArray<ElemType>(GetNumElements()), GetNumElements() * sizeof(ElemType));
}
}
template <class ElemType>
CPUMatrix<ElemType>::CPUMatrix(const size_t numRows, const size_t numCols, ElemType* pArray, const size_t matrixFlags)
{
ZeroInit();
SetValue(numRows, numCols, pArray, matrixFlags);
}
//copy constructor, deep copy
template <class ElemType>
CPUMatrix<ElemType>::CPUMatrix(const CPUMatrix<ElemType>& deepCopyFrom)
{
ZeroInit();
SetValue(deepCopyFrom);
}
//assignment operator, deep copy
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::operator=(const CPUMatrix<ElemType>& deepCopyFrom)
{
SetValue(deepCopyFrom);
return *this;
}
//move constructor, shallow copy
template <class ElemType>
CPUMatrix<ElemType>::CPUMatrix(CPUMatrix<ElemType>&& moveFrom)
: Base(/* shallow */ true)
{
ShallowCopyFrom(moveFrom);
moveFrom.ZeroValues();
}
// Shortcut of default constructor + shallow copy, to avoid one initialization
template <class ElemType>
CPUMatrix<ElemType>::CPUMatrix(const CPUMatrix<ElemType>& shallowCopyFrom, bool shallow)
: Base(shallow)
{
ShallowCopyFrom(shallowCopyFrom);
}
//move assignment operator, shallow copy
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::operator=(CPUMatrix<ElemType>&& moveFrom)
{
if (this != &moveFrom)
{
ShallowCopyFrom(moveFrom);
// release the pointer from the source object so that the destructor won't release it twice
moveFrom.ZeroValues();
}
return *this;
}
template <class ElemType>
void CPUMatrix<ElemType>::Clear()
{
ZeroInit();
}
#pragma endregion Constructors and Destructor
#pragma region Basic Operators
template <class ElemType>
CPUMatrix<ElemType> CPUMatrix<ElemType>::ColumnSlice(size_t startColumn, size_t numCols) const
{
if (startColumn + numCols > m_numCols)
InvalidArgument("The slice (%d+%d) is out of range of the source matrix (%d).", (int) startColumn, (int) numCols, (int) m_numCols);
CPUMatrix<ElemType> slice(*this, /* shallow= */ true);
slice.m_numCols = numCols;
slice.m_sliceViewOffset = m_sliceViewOffset + startColumn * m_numRows;
return slice;
}
// set this(:, 0:numCols-1) = fromMatrix(:, startColumn : startColumn+numCols-1)
// TODO: why not say *this = ColumnSlice()?
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignColumnSlice(const CPUMatrix<ElemType>& fromMatrix, size_t startColumn, size_t numCols)
{
if (startColumn + numCols > fromMatrix.m_numCols)
InvalidArgument("The slice (%d+%d) is out of range of the source matrix (%d).", (int) startColumn, (int) numCols, (int) fromMatrix.m_numCols);
Clear();
ShallowCopyFrom(fromMatrix);
m_numCols = numCols;
m_sliceViewOffset = fromMatrix.m_sliceViewOffset + startColumn * m_numRows;
return *this;
}
// set this(: , startColumn:startColumn+numCols-1)= fromMatrix;
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::SetColumnSlice(const CPUMatrix<ElemType>& fromMatrix, size_t startColumn, size_t numCols)
{
if (startColumn + numCols > m_numCols)
LogicError("The slice is out of range of the destination matrix.");
if (numCols > fromMatrix.GetNumCols())
InvalidArgument("The slice (%d) is out of range of the source matrix (%d).", (int) numCols, (int) fromMatrix.GetNumCols());
if (m_numRows != fromMatrix.m_numRows)
LogicError("The number of rows in source and destination matrices do not match");
memcpy(Data() + startColumn * m_numRows, fromMatrix.Data(), numCols * m_numRows * sizeof(ElemType));
return *this;
}
template <class ElemType>
void CPUMatrix<ElemType>::CopyColumnsStrided(const CPUMatrix<ElemType>& fromMatrix, size_t numCols, size_t srcNumColsStride, size_t destNumColsStride)
{
if ((((numCols - 1) * srcNumColsStride) + 1) > fromMatrix.m_numCols)
LogicError("The numCols to copy and srcNumColsStride specified is out of range of the source matrix.");
if ((((numCols - 1) * destNumColsStride) + 1) > m_numCols)
LogicError("The numCols to copy and srcNumColsStride specified is out of range of the destination matrix.");
if (m_numRows != fromMatrix.m_numRows)
LogicError("The number of rows in source and destination matrices do not match");
long n = (long) numCols, m = (long) m_numRows;
auto& us = *this;
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (size_t i = 0; i < (m & ~3); i += 4)
{
us(i, j * destNumColsStride) = fromMatrix(i, j * srcNumColsStride);
us(i + 1, j * destNumColsStride) = fromMatrix(i + 1, j * srcNumColsStride);
us(i + 2, j * destNumColsStride) = fromMatrix(i + 2, j * srcNumColsStride);
us(i + 3, j * destNumColsStride) = fromMatrix(i + 3, j * srcNumColsStride);
}
// handle remaining
for (size_t i = m & ~3; i < m; i++)
{
us(i, j * destNumColsStride) = fromMatrix(i, j * srcNumColsStride);
}
}
}
//for each column of a, we add all rows of a to this starting from startIndex
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignToRowSliceValuesOf(const CPUMatrix<ElemType>& a, const size_t startIndex, const size_t numRows)
{
if (a.GetNumRows() != numRows)
LogicError("AddToRowSliceValuesOf: a.GetNumRows() != numRows.");
if (startIndex + numRows > GetNumRows())
LogicError("AddToRowSliceValuesOf: startIndex + numRows exceeds GetNumRows().");
if (a.GetNumCols() != GetNumCols())
LogicError("AddToRowSliceValuesOf: columns does not match.");
long n = (long) a.GetNumCols(), m = (long) numRows;
auto& us = *this;
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (size_t i = 0, startRow = startIndex; i < (m & ~3); i += 4, startRow += 4)
{
us(startRow, j) = a(i, j);
us(startRow + 1, j) = a(i + 1, j);
us(startRow + 2, j) = a(i + 2, j);
us(startRow + 3, j) = a(i + 3, j);
}
// handle remaining stuffs
for (size_t i = m & ~3, startRow = startIndex + (m & ~3); i < m; i++, startRow++)
{
us(startRow, j) = a(i, j);
}
}
return *this;
}
//for each column of a, we assign numRows starting from startIndex to this
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignRowSliceValuesOf(const CPUMatrix<ElemType>& a, const size_t startIndex, const size_t numRows)
{
if (startIndex + numRows > a.GetNumRows())
LogicError("AssignRowSliceValuesOf: startIndex + numRows exceeds a.GetNumRows().");
RequireSize(numRows, a.GetNumCols());
long n = (long) a.GetNumCols(); // note: OpenMP requires loop indices to be long, not size_t
long k = (long) a.GetNumRows();
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// memory copy might be faster?
memcpy(Data() + j * numRows, a.Data() + j * k + startIndex, sizeof(ElemType) * numRows);
// //four-way unrolling
// for (long i=0, startRow = startIndex; i<(m & ~3); i+=4, startRow+=4)
// {
// us(i,j) = a(startRow,j);
// us(i+1,j) = a(startRow+1,j);
// us(i+2,j) = a(startRow+2,j);
// us(i+3,j) = a(startRow+3,j);
// }
// //handle remaining stuffs
// for (long i=m & ~3, startRow = startIndex+(m & ~3); i<m; i++, startRow++)
// {
// us(i,j) = a(startRow,j);
// }
}
return *this;
}
//for the row slice of this starting from startIndex we add a to it.
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AddToRowSliceValuesOf(const CPUMatrix<ElemType>& a, const size_t startIndex, const size_t numRows)
{
if (a.IsEmpty())
LogicError("AddToRowSliceValuesOf: input matrix a is empty.");
if (a.GetNumRows() != numRows)
LogicError("AddToRowSliceValuesOf: a.GetNumRows() != numRows.");
if (startIndex + numRows > GetNumRows())
LogicError("AddToRowSliceValuesOf: startIndex + numRows exceeds GetNumRows().");
if (a.GetNumCols() != GetNumCols())
LogicError("AddToRowSliceValuesOf: columns does not match.");
long n = (long) a.GetNumCols(), m = (long) numRows;
auto& us = *this;
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0, startRow = (long) startIndex; i < (m & ~3); i += 4, startRow += 4)
{
us(startRow, j) += a(i, j);
us(startRow + 1, j) += a(i + 1, j);
us(startRow + 2, j) += a(i + 2, j);
us(startRow + 3, j) += a(i + 3, j);
}
// handle remaining stuffs
for (long i = m & ~3, startRow = (long) startIndex + (m & ~3); i < m; i++, startRow++)
{
us(startRow, j) += a(i, j);
}
}
return *this;
}
//for each column of this, we add row slice of a starting from startIndex
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AddWithRowSliceValuesOf(const CPUMatrix<ElemType>& a, const size_t startIndex, const size_t numRows)
{
if (a.IsEmpty())
LogicError("AddWithRowSliceValuesOf: input matrix a is empty.");
if (GetNumRows() != numRows)
LogicError("AddWithRowSliceValuesOf: GetNumRows() != numRows.");
if (startIndex + numRows > a.GetNumRows())
LogicError("AddWithRowSliceValuesOf: startIndex + numRows exceeds a.GetNumRows().");
if (a.GetNumCols() != GetNumCols())
LogicError("AddWithRowSliceValuesOf: columns does not match.");
long n = (long) a.GetNumCols(), m = (long) numRows;
auto& us = *this;
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0, startRow = (long) startIndex; i < (m & ~3); i += 4, startRow += 4)
{
us(i, j) += a(startRow, j);
us(i + 1, j) += a(startRow + 1, j);
us(i + 2, j) += a(startRow + 2, j);
us(i + 3, j) += a(startRow + 3, j);
}
// handle remaining stuffs
for (long i = m & ~3, startRow = (long) startIndex + (m & ~3); i < m; i++, startRow++)
{
us(i, j) += a(startRow, j);
}
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType> CPUMatrix<ElemType>::Diagonal() const
{
if (m_numRows != m_numCols)
LogicError("Diagonal can be called only for square matrix. (rows=%d, cols=%d)", (int) m_numRows, (int) m_numCols);
CPUMatrix<ElemType> diag(1, m_numCols);
auto& us = *this;
#pragma omp parallel for
for (long i = 0; i < m_numRows; i++)
{
diag(0, (size_t) i) = us(i, i);
}
return diag;
}
template <class ElemType>
void CPUMatrix<ElemType>::MinusOneAt(CPUMatrix<ElemType>& c, const size_t position)
{
if (position < c.GetNumElements())
c.Data()[position] -= 1.0;
else
RuntimeError("MinusOneAt: position is out of CPU matrix size");
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignRepeatOf(const CPUMatrix<ElemType>& a, const size_t numRowRepeats, const size_t numColRepeats)
{
if (this == &a)
LogicError("AssignRepeatOf: a is the same as [this]. Does not support inplace repeat.");
if (a.IsEmpty())
LogicError("AssignRepeatOf: Matrix a is empty.");
RequireSize(a.GetNumRows() * numRowRepeats, a.GetNumCols() * numColRepeats);
long n = (long) a.GetNumCols(), m = (long) a.GetNumRows();
auto& us = *this;
#pragma omp parallel for
for (long q = 0; q < numColRepeats; q++)
{
for (long p = 0; p < numRowRepeats; p++)
{
long colOffset = q * n;
for (long j = 0; j < n; j++, colOffset++)
{
long rowOffset = p * m;
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4, rowOffset += 4)
{
us(rowOffset, colOffset) = a(i, j);
us(rowOffset + 1, colOffset) = a(i + 1, j);
us(rowOffset + 2, colOffset) = a(i + 2, j);
us(rowOffset + 3, colOffset) = a(i + 3, j);
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++, rowOffset++)
{
us(rowOffset, colOffset) = a(i, j);
}
}
}
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AddToRowRepeatValuesOf(const CPUMatrix<ElemType>& a, const size_t numRepeats)
{
if (a.IsEmpty())
LogicError("AddToRowRepeatValuesOf: input matrix a is empty.");
if (a.GetNumRows() != GetNumRows() * numRepeats)
LogicError("AddToRowRepeatValuesOf: a.GetNumRows() != GetNumRows() * numRepeats.");
long n = (long) a.GetNumCols(), m = (long) GetNumRows();
auto& us = *this;
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
for (long k = 0; k < numRepeats; k++)
{
us(i, j) += a(k * m + i, j);
us(i + 1, j) += a(k * m + i + 1, j);
us(i + 2, j) += a(k * m + i + 2, j);
us(i + 3, j) += a(k * m + i + 3, j);
}
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
for (long k = 0; k < numRepeats; k++)
{
us(i, j) += a(k * m + i, j);
}
}
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignPositiveAndShiftedNegSample(const CPUMatrix<ElemType>& a, const size_t posNumber, const size_t negNumber, const size_t shiftNumber)
{
a;
posNumber;
negNumber;
shiftNumber;
NOT_IMPLEMENTED;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AddFoldedPositiveAndShiftedNegSample(const CPUMatrix<ElemType>& a, const size_t posNumber, const size_t negNumber, const size_t shiftNumber)
{
a;
posNumber;
negNumber;
shiftNumber;
NOT_IMPLEMENTED;
}
template <class ElemType>
CPUMatrix<ElemType> CPUMatrix<ElemType>::Transpose()
{
if (IsEmpty())
LogicError("Transpose: Matrix is empty.");
CPUMatrix<ElemType> c;
c.AssignTransposeOf(*this);
return c;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignTransposeOf(const CPUMatrix<ElemType>& a)
{
if (this == &a)
LogicError("AssignTransposeOf: a is the same as [this]. Does not support inplace transpose.");
if (a.IsEmpty())
LogicError("AssignTransposeOf: Matrix a is empty.");
RequireSize(a.GetNumCols(), a.GetNumRows());
long n = (long) a.GetNumCols(), m = (long) a.GetNumRows();
auto& us = *this;
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(j, i) = a(i, j);
us(j, i + 1) = a(i + 1, j);
us(j, i + 2) = a(i + 2, j);
us(j, i + 3) = a(i + 3, j);
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(j, i) = a(i, j);
}
}
return *this;
}
// dst[i] = src[i] * alpha + dst[i] * beta
// scale a column vector and add it to another
// The usual special case: If beta = 0, then dst[] is not read, and may be uninitialized or NaN.
template <class ElemType>
static void ScaleAndAddColumn(ElemType beta, ElemType* dst, const ElemType* src, size_t numRows, ElemType alpha)
{
if (alpha != 1) // rare case: just do the full thing
for (size_t i = 0; i < numRows; i++)
dst[i] = beta * dst[i] + alpha * src[i];
else if (beta == 1) // used in backprop
for (size_t i = 0; i < numRows; i++)
dst[i] += src[i];
else if (beta == 0) // plain assignment
memcpy(dst, src, sizeof(ElemType) * numRows);
else // alpha=1, arbitrary beta: also rare case
for (size_t i = 0; i < numRows; i++)
dst[i] = beta * dst[i] + src[i];
}
// *this[:,j] = a[:,idx[j]] * alpha + *this[:,j] * beta
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::DoGatherColumnsOf(ElemType beta, const CPUMatrix<ElemType>& idx, const CPUMatrix<ElemType>& a, ElemType alpha)
{
if (idx.GetNumRows() != 1) // index is 1-dimensional only
InvalidArgument("DoGatherColumnsOf: Map must be a row vector.");
if (beta)
VerifySize(a.GetNumRows(), idx.GetNumCols());
else
Resize(a.GetNumRows(), idx.GetNumCols());
auto& us = *this;
// race-condition consideration: Since this loops over independent output columns, this has no race condition. Cf. DoScatterColumnsOf().
#pragma omp parallel for // TODO: Depending in circumstance, it may be more efficient to parallelize over rows.
foreach_column(jOut, us)
{
auto jInF = idx(0, jOut); // this is the column we need to get
if (std::isnan(jInF) || jInF < 0) // negative index means gap
continue;
size_t jIn = (size_t)jInF;
if (jIn >= a.GetNumCols())
InvalidArgument("DoGatherColumnsOf: Map out of bounds. %ld >= %ld", (long int)jIn, (long int)a.GetNumCols());
ScaleAndAddColumn(beta, &us(0,jOut), &a(0,jIn), us.GetNumRows(), alpha);
}
return *this;
}
// *this[:,idx[j]] = a[:,j] * alpha + *this[:,idx[j]] * beta
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::DoScatterColumnsOf(ElemType beta, const CPUMatrix<ElemType>& idx, const CPUMatrix<ElemType>& a, ElemType alpha)
{
if (idx.GetNumRows() != 1) // index is 1-dimensional only
InvalidArgument("DoScatterColumnsOf: Map must be a row vector.");
if (idx.GetNumCols() != a.GetNumCols())
InvalidArgument("DoScatterColumnsOf: Map must have width of input vector.");
if (a.GetNumRows() != GetNumRows())
InvalidArgument("DoScatterColumnsOf: Output must have same height as input vector.");
auto& us = *this;
// pre-scale with beta upfront
// Scatter may add more than one source column to the same target, so we must pre-scale with beta, and then just keep adding.
Scale(beta, us); // if beta is 0, then this will be a memset()
ScatterValues(idx.Data(), a.Data(), us.Data(), alpha, idx.GetNumCols(), a.GetNumRows(), GetNumCols(), idx.GetNumRows());
return *this;
}
template <class ElemType>
void CPUMatrix<ElemType>::SetValue(const ElemType v)
{
if (IsEmpty())
LogicError("SetValue: Matrix is empty.");
bool isFinite = std::numeric_limits<ElemType>::is_integer || std::isfinite((double) v);
if (isFinite && v == 0)
{
memset(Data(), 0, sizeof(ElemType) * GetNumElements());
}
else
{
ElemType* bufPtr = Data();
long m = (long) GetNumElements();
// 2-way thread parallelism is sufficient for the memory bound
// operation of just setting the values of an array.
const unsigned SETVALUE_NUM_THREADS = 2;
UNUSED(SETVALUE_NUM_THREADS); // in case OMP is turned off.
#pragma omp parallel for num_threads(SETVALUE_NUM_THREADS)
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
bufPtr[i] = v;
bufPtr[i + 1] = v;
bufPtr[i + 2] = v;
bufPtr[i + 3] = v;
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
bufPtr[i] = v;
}
}
}
template <class ElemType>
void CPUMatrix<ElemType>::MaskColumnsValue(const CPUMatrix<char>& columnsMask, ElemType val, size_t numColsPerMaskEntry)
{
if (GetNumCols() != (columnsMask.GetNumCols() * numColsPerMaskEntry))
RuntimeError("MaskColumnsValue: Matrix number of columns must equal 'column mask number of columns * numColsPerMaskEntry'.");
auto& us = *this;
long n = (long)columnsMask.GetNumCols(), m = (long) GetNumRows();
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
if (columnsMask(0, j) == 1)
continue;
for (long k = 0; k < numColsPerMaskEntry; ++k)
{
// four-way unrolling
for (size_t i = 0; i < (m & ~3); i += 4)
{
us(i, (j * numColsPerMaskEntry) + k) = val;
us(i + 1, (j * numColsPerMaskEntry) + k) = val;
us(i + 2, (j * numColsPerMaskEntry) + k) = val;
us(i + 3, (j * numColsPerMaskEntry) + k) = val;
}
// handle remaining
for (size_t i = m & ~3; i < m; i++)
{
us(i, (j * numColsPerMaskEntry) + k) = val;
}
}
}
}
template <class ElemType>
void CPUMatrix<ElemType>::SetColumn(const ElemType* colPointer, size_t j)
{
if (IsEmpty())
LogicError("SetColumn: Matrix is empty.");
if (colPointer == NULL)
return;
auto& us = *this;
long m = (long) GetNumRows();
#pragma omp parallel for
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, j) = colPointer[i];
us(i + 1, j) = colPointer[i + 1];
us(i + 2, j) = colPointer[i + 2];
us(i + 3, j) = colPointer[i + 3];
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(i, j) = colPointer[i];
}
}
template <class ElemType>
void CPUMatrix<ElemType>::SetColumn(const ElemType val, size_t j)
{
if (IsEmpty())
LogicError("SetColumn: Matrix is empty.");
auto& us = *this;
long m = (long) GetNumRows();
#pragma omp parallel for
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, j) = val;
us(i + 1, j) = val;
us(i + 2, j) = val;
us(i + 3, j) = val;
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(i, j) = val;
}
}
template <class ElemType>
void CPUMatrix<ElemType>::SetColumn(const CPUMatrix<ElemType>& valMat, size_t j)
{
if (IsEmpty())
LogicError("SetColumn: Matrix is empty.");
if (valMat.GetNumRows() != GetNumRows() || valMat.GetNumCols() != 1)
LogicError("The valMat matrix has incorrect number of rows or columns.");
auto& us = *this;
long m = (long) GetNumRows();
#pragma omp parallel for
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, j) = valMat(i, 0);
us(i + 1, j) = valMat(i + 1, 0);
us(i + 2, j) = valMat(i + 2, 0);
us(i + 3, j) = valMat(i + 3, 0);
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(i, j) = valMat(i, 0);
}
}
template <class ElemType>
void CPUMatrix<ElemType>::SetValue(const CPUMatrix<ElemType>& deepCopyFrom)
{
if (this == &deepCopyFrom)
return;
SetValue(deepCopyFrom.GetNumRows(), deepCopyFrom.GetNumCols(), deepCopyFrom.Data(), 0);
}
#if 0
template <class ElemType>
void CPUMatrix<ElemType>::SetValue(const GPUMatrix<ElemType>& /*deepCopyFrom*/)
{
NOT_IMPLEMENTED;
}
template <class ElemType>
void CPUMatrix<ElemType>::SetValue(const CPUSparseMatrix<ElemType>& deepCopyFrom)
{
deepCopyFrom.AssignColumnSliceToDense(*this, 0, deepCopyFrom.GetNumCols());
}
template <class ElemType>
void CPUMatrix<ElemType>::SetValue(const GPUSparseMatrix<ElemType>& /*deepCopyFrom*/)
{
NOT_IMPLEMENTED;
}
#endif
template <class ElemType>
void CPUMatrix<ElemType>::SetValue(const size_t numRows, const size_t numCols, ElemType* pArray, const size_t matrixFlags)
{
if (pArray == nullptr && numRows * numCols > 0)
InvalidArgument("Invalid pArray. pArray == nullptr, but matrix is of size %d * %d = %d.", (int)numRows, (int)numCols, (int)(numRows * numCols));
SetFormat(matrixFormatDense);
SetComputeDeviceId(CPUDEVICE);
// if it's externally managed, then populate the structure
if (matrixFlags & matrixFlagDontOwnBuffer)
{
// free previous array allocation if any before overwriting
delete[] Buffer();
m_numRows = numRows;
m_numCols = numCols;
SetBuffer(pArray, GetNumElements() * sizeof(ElemType), true);
SetSizeAllocated(GetNumElements());
}
else
{
RequireSize(numRows, numCols);
if (!IsEmpty())
{
if (!(matrixFlags & matrixFormatRowMajor)) // compatible to internal structure
memcpy(Data(), pArray, GetNumElements() * sizeof(ElemType));
else // need to transpose
{
ElemType* bufPtr = Data();
auto& us = *this;
if (sizeof(ElemType) == sizeof(double))
{
#pragma omp parallel for
foreach_column (j, us)
{
cblas_dcopy((int) numRows, reinterpret_cast<double*>(pArray + j), (int) numCols, reinterpret_cast<double*>(bufPtr + LocateColumn(j)), 1);
}
}
else
{
#pragma omp parallel for
foreach_column (j, us)
{
{
#pragma warning(suppress : 4244)
cblas_scopy((int) numRows, reinterpret_cast<float*>(pArray + j), (int) numCols, reinterpret_cast<float*>(bufPtr + LocateColumn(j)), 1);
}
}
}
}
}
}
}
template <class ElemType>
void CPUMatrix<ElemType>::SetDiagonalValue(const ElemType v)
{
if (GetNumRows() != GetNumCols())
LogicError("SetDiagonalValue: NumRows and NumCols do not agree.");
auto& us = *this;
long m = (long) GetNumRows();
#pragma omp parallel for
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, i) = v;
us(i + 1, i + 1) = v;
us(i + 2, i + 2) = v;
us(i + 3, i + 3) = v;
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(i, i) = v;
}
}
template <class ElemType>
void CPUMatrix<ElemType>::SetDiagonalValue(const CPUMatrix<ElemType>& vector)
{
if (IsEmpty() || vector.IsEmpty())
LogicError("SetDiagonalValue: Matrix is empty.");
if (GetNumRows() != GetNumCols())
LogicError("SetDiagonalValue: NumRows and NumCols do not agree.");
if (vector.GetNumRows() != 1 && vector.GetNumCols() != 1)
LogicError("SetDiagonalValue: input vector must be a vector.");
if (vector.GetNumElements() == 1) // reduce to simple form
SetDiagonalValue(vector(0, 0));
else if (vector.GetNumRows() != GetNumRows() && vector.GetNumCols() != GetNumRows())
LogicError("SetDiagonalValue: input vector's dimension does not agree with [this].");
else
{
auto& us = *this;
long m = (long) GetNumRows();
if (vector.GetNumRows() == 1) // row vector
{
#pragma omp parallel for
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, i) = vector(0, i);
us(i + 1, i + 1) = vector(0, i + 1);
us(i + 2, i + 2) = vector(0, i + 2);
us(i + 3, i + 3) = vector(0, i + 3);
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(i, i) = vector(0, i);
}
}
else
{
#pragma omp parallel for
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, i) = vector(i, 0);
us(i + 1, i + 1) = vector(i + 1, 0);
us(i + 2, i + 2) = vector(i + 2, 0);
us(i + 3, i + 3) = vector(i + 3, 0);
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(i, i) = vector(i, 0);
}
}
}
}
template <class ElemType>
void CPUMatrix<ElemType>::SetUniformRandomValue(const ElemType low, const ElemType high, unsigned long seed)
{
if (IsEmpty())
LogicError("SetUniformRandomValue: Matrix is empty.");
std::mt19937_64 generator;
generator.seed(seed == USE_TIME_BASED_SEED ? (unsigned long) time(NULL) : seed);
boost::random::uniform_real_distribution<ElemType> r(low, high);
ElemType* bufPtr = Data();
long m = (long) GetNumElements();
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
bufPtr[i] = r(generator);
bufPtr[i + 1] = r(generator);
bufPtr[i + 2] = r(generator);
bufPtr[i + 3] = r(generator);
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
bufPtr[i] = r(generator);
}
}
template <class ElemType>
void CPUMatrix<ElemType>::SetGaussianRandomValue(const ElemType mean, const ElemType sigma, unsigned long seed)
{
if (sigma <= 0)
InvalidArgument("SetUniformRandomValue: sigma must be a positive value.");
if (IsEmpty())
LogicError("SetUniformRandomValue: Matrix is empty.");
auto& us = *this;
std::mt19937_64 generator(seed == USE_TIME_BASED_SEED ? (unsigned long) time(NULL) : seed);
boost::random::normal_distribution<ElemType> r(mean, sigma);
// #pragma omp parallel for // is it thread safe?
foreach_coord (i, j, us)
{
us(i, j) = r(generator);
}
}
template <class ElemType>
void CPUMatrix<ElemType>::AddGaussianRandomValue(const ElemType mean, const ElemType sigma, unsigned long seed)
{
if (sigma <= 0)
InvalidArgument("SetUniformRandomValue: sigma must be a positive value.");
if (IsEmpty())
LogicError("SetUniformRandomValue: Matrix is empty.");
auto& us = *this;
std::mt19937_64 generator;
generator.seed(seed == USE_TIME_BASED_SEED ? (unsigned long) time(NULL) : seed);
boost::random::normal_distribution<ElemType> r(mean, sigma);
long m = (long) GetNumRows(), n = (long) GetNumCols();
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, j) = r(generator);
us(i + 1, j) = r(generator);
us(i + 2, j) = r(generator);
us(i + 3, j) = r(generator);
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(i, j) = r(generator);
}
}
}
//maskRate: percentage of values masked out (similar to dropout rate)
//scaleValue: which scale value to set to the left ones (unmasked items).
template <class ElemType>
void CPUMatrix<ElemType>::SetUniformRandomMask(const ElemType maskRate, const ElemType scaleValue, RNGHandle& rngHandle)
{
if (IsEmpty())
LogicError("SetUniformRandomValue: Matrix is empty.");
CPURNGHandle* cpuRNGHandle = dynamic_cast<CPURNGHandle*>(&rngHandle);
if (cpuRNGHandle == nullptr)
LogicError("rngHandle must be a CPURNGHandle.");
auto& us = *this;
boost::random::uniform_real_distribution<ElemType> r(0, 1);
long m = (long) GetNumRows(), n = (long) GetNumCols();
ElemType v;
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
v = r(cpuRNGHandle->Generator());
us(i, j) = v <= maskRate ? 0 : scaleValue;
v = r(cpuRNGHandle->Generator());
us(i + 1, j) = v <= maskRate ? 0 : scaleValue;
v = r(cpuRNGHandle->Generator());
us(i + 2, j) = v <= maskRate ? 0 : scaleValue;
v = r(cpuRNGHandle->Generator());
us(i + 3, j) = v <= maskRate ? 0 : scaleValue;
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
v = r(cpuRNGHandle->Generator());
us(i, j) = v <= maskRate ? 0 : scaleValue;
}
}
}
template <class ElemType>
ElemType CPUMatrix<ElemType>::Adagrad(CPUMatrix<ElemType>& gradients, const bool needAveMultiplier)
{
ElemType aveMultiplier = 0;
if (IsEmpty() || gradients.GetNumCols() != GetNumCols() || gradients.GetNumRows() != GetNumRows())
{
RequireSize(gradients.GetNumRows(), gradients.GetNumCols());
SetValue(0.0);
}
if (GetNumRows() != gradients.GetNumRows() || GetNumCols() != gradients.GetNumCols())
LogicError("The matrix gradients must have the same rows and columns as this matrix.");
ElemType *a = Data(), *d_v = gradients.Data();
size_t n = GetNumElements();
const ElemType floor = 1e-16f;
ElemType a0, a1, a2, a3;
// disable omp here because aveMultiper needs to be added atomically. however, it seems the result is incorrect even if rmp atomic and amp critical are used.
// #pragma omp parallel for
for (long i = 0; i < (n & ~3); i += 4) // four-way unrolling
{
a[i] += d_v[i] * d_v[i];
a[i + 1] += d_v[i + 1] * d_v[i + 1];
a[i + 2] += d_v[i + 2] * d_v[i + 2];
a[i + 3] += d_v[i + 3] * d_v[i + 3];
a0 = sqrt(a[i] + floor);
a1 = sqrt(a[i + 1] + floor);
a2 = sqrt(a[i + 2] + floor);
a3 = sqrt(a[i + 3] + floor);
d_v[i] /= a0;
d_v[i + 1] /= a1;
d_v[i + 2] /= a2;
d_v[i + 3] /= a3;
if (needAveMultiplier)
{
aveMultiplier += 1 / a0 + 1 / a1 + 1 / a2 + 1 / a3;
}
}
// get the last few elements if any
for (long i = n & ~3; i < n; i++)
{
a[i] += d_v[i] * d_v[i];
a0 = sqrt(a[i] + floor);
d_v[i] /= a0;
if (needAveMultiplier)
{
aveMultiplier += 1 / a0;
}
}
if (needAveMultiplier && n > 0)
return aveMultiplier / n;
else
return 1;
}
template <class ElemType>
void CPUMatrix<ElemType>::FSAdagrad(CPUMatrix<ElemType>& gradients,
CPUMatrix<ElemType>& functionValues,
ElemType learnRatePerSample,
ElemType momentum,
ElemType adaWeight,
ElemType adaMul,
bool unitGainMomentum)
{
auto unitGainFactor = ElemType(unitGainMomentum ? (1.0 - momentum) : 1.0);
size_t numColsNeeded = 2 * gradients.GetNumCols();
if (IsEmpty() || (GetNumCols() < numColsNeeded))
{
RequireSize(gradients.GetNumRows(), numColsNeeded);
SetValue(0.0);
}
if (GetNumRows() != gradients.GetNumRows() || GetNumCols() != numColsNeeded)
LogicError("The matrix gradients does not have expected dimensions.");
size_t n = gradients.GetNumElements();
ElemType* grad = gradients.Data();
ElemType* smoothAda = Data();
ElemType* smoothMom = Data() + n;
ElemType* val = functionValues.Data();
#pragma omp parallel for
// TODO: Unroll 4-times for better performance leveraging vectorization
for (long i = 0; i < n; i++)
{
ElemType g = grad[i];
ElemType adaSqr = adaWeight * smoothAda[i] + (1.0f - adaWeight) * g * g;
smoothAda[i] = adaSqr;
if (adaSqr != 0.0f)
{
ElemType ada = sqrt(adaSqr);
ElemType w = adaMul * ((ElemType) 1.0 / ada);
if (w > 10.0f)
w = 10.0f;
g *= w;
}
if (momentum > 0.0f)
{
g = momentum * smoothMom[i] + unitGainFactor * g;
smoothMom[i] = g;
}
g *= learnRatePerSample;
val[i] -= g;
}
}
template <class ElemType>
void CPUMatrix<ElemType>::Adam(CPUMatrix<ElemType>& gradients, CPUMatrix<ElemType>& functionValues, ElemType learnRatePerSample,
ElemType momentum, ElemType adaWeight, ElemType adaMul, ElemType epsilon, bool unitGainMomentum)
{
size_t numColsNeeded = 2 * gradients.GetNumCols();
auto unitGainFactor = ElemType(unitGainMomentum ? (1.0 - momentum) : 1.0);
if (IsEmpty() || (GetNumCols() < numColsNeeded))
{
RequireSize(gradients.GetNumRows(), numColsNeeded);
SetValue(0.0);
}
if (GetNumRows() != gradients.GetNumRows() || GetNumCols() != numColsNeeded)
LogicError("The matrix gradients does not have expected dimensions.");
size_t n = gradients.GetNumElements();
ElemType* grad = gradients.Data();
ElemType* smoothAda = Data();
ElemType* smoothMom = Data() + n;
ElemType* val = functionValues.Data();
#pragma omp parallel for
// TODO: Unroll 4-times for better performance leveraging vectorization
for (long i = 0; i < n; i++)
{
ElemType g = grad[i];
ElemType adaSqr = adaWeight * smoothAda[i] + (1.0f - adaWeight) * g * g;
smoothAda[i] = adaSqr;
ElemType ada = sqrt(adaSqr);
ElemType w = adaMul * (ElemType)( 1.0 / (ada + epsilon));
g = momentum * smoothMom[i] + unitGainFactor * g;
smoothMom[i] = g;
val[i] -= g * w * learnRatePerSample;
}
}
template <class ElemType>
ElemType CPUMatrix<ElemType>::RmsProp(CPUMatrix<ElemType>& gradients,
ElemType RMS_GAMMA,
ElemType RMS_WGT_INC,
ElemType RMS_WGT_MAX,
ElemType RMS_WGT_DEC,
ElemType RMS_WGT_MIN,
const bool needAveMultiplier)
{
const ElemType floor = 1e-6f;
size_t n = gradients.GetNumElements();
ElemType* curr_grad = gradients.Data();
if (IsEmpty() || GetNumCols() < gradients.GetNumCols() * 3)
{
RequireSize(gradients.GetNumRows(), gradients.GetNumCols() * 3);
SetValue(0.0);
ElemType* avars = Data(); // accumulated variances for RMS scaling
ElemType* steps = Data() + 2 * n; // current step size
// initialize moving average of gradient-squared
for (long i = 0; i < n; i++)
avars[i] = curr_grad[i] * curr_grad[i];
// initialize starting step size
for (long i = 0; i < n; i++)
steps[i] = ElemType(0.02);
}
ElemType* avars = Data(); // accumulated variances for RMS scaling
ElemType* signs = Data() + n; // sign of previous gradient
ElemType* steps = Data() + 2 * n; // current step size
if (GetNumRows() != gradients.GetNumRows() || GetNumCols() != gradients.GetNumCols() * 3)
LogicError("The matrix gradients does not have expected dimensions.");
ElemType ONE_MINUS_GAMMA = ElemType(1.0) - RMS_GAMMA;
// int upd[] = {
// 2,2,0,
// 2,2,0,
// 1,1,1,
// 2,2,0,
// 1,2,1,
// 0,2,2,
// 1,1,1,
// 0,2,2,
// 0,2,2,
// };
// for (long i=0; i<n; i++)
// {
// avars[i] = RMS_GAMMA * avars[i] + ONE_MINUS_GAMMA * (curr_grad[i] * curr_grad[i]);
// // grad sign base 3: 0->neg, 1->zero, 2->pos
// const int grad_sign = 1 + (ElemType(0) < curr_grad[i]) - (curr_grad[i] < ElemType(0));
// // signs[i] contains three consecutive grad_sign
// signs[i] = 3*(int(signs[i]) % 9) + grad_sign;
// switch(upd[int(signs[i])])
// {
// case 0:
// steps[i] = max(steps[i] * RMS_WGT_DEC, RMS_WGT_MIN);
// break;
// case 2:
// steps[i] = min(steps[i] * RMS_WGT_INC, RMS_WGT_MAX);
// break;
// }
// curr_grad[i] *= steps[i] / sqrt(avars[i] + floor);
// }
ElemType aveMultiplier = 0, a;
for (long i = 0; i < n; i++)
{
avars[i] = RMS_GAMMA * avars[i] + ONE_MINUS_GAMMA * (curr_grad[i] * curr_grad[i]);
const int grad_sign = (ElemType(0) < curr_grad[i]) - (curr_grad[i] < ElemType(0));
if (signs[i] * grad_sign > 0)
steps[i] = std::min(steps[i] * RMS_WGT_INC, RMS_WGT_MAX);
else
steps[i] = std::max(steps[i] * RMS_WGT_DEC, RMS_WGT_MIN);
a = steps[i] / sqrt(avars[i] + floor);
curr_grad[i] *= a;
signs[i] = (ElemType) grad_sign;
if (needAveMultiplier)
aveMultiplier += a;
}
if (needAveMultiplier)
return aveMultiplier / n;
else
return 1;
}
template <class ElemType>
void CPUMatrix<ElemType>::AdaDelta(CPUMatrix<ElemType>& gradients, CPUMatrix<ElemType>& functionValues, ElemType learningRate, ElemType rho, ElemType epsilon)
{
size_t numColsNeeded = 2 * gradients.GetNumCols();
if (IsEmpty() || (GetNumCols() < numColsNeeded))
{
RequireSize(gradients.GetNumRows(), numColsNeeded);
SetValue(0.0);
}
if (GetNumRows() != gradients.GetNumRows() || GetNumCols() != numColsNeeded)
LogicError("The matrix gradients does not have expected dimensions.");
size_t n = gradients.GetNumElements();
ElemType* grad = gradients.Data();
ElemType* smoothAda = Data();
ElemType* smoothX2 = Data() + n;
ElemType* val = functionValues.Data();
#pragma omp parallel for
// TODO: Unroll 4-times for better performance leveraging vectorization
for (long i = 0; i < n; i++)
{
ElemType g = grad[i];
ElemType adaSqr = rho * smoothAda[i] + (1 - rho) * g * g;
smoothAda[i] = adaSqr;
ElemType x2 = smoothX2[i];
ElemType deltaX = -sqrt(x2 + epsilon) / sqrt(adaSqr + epsilon) * g;
smoothX2[i] = rho * smoothX2[i] + (1 - rho) * deltaX * deltaX;
val[i] += learningRate * deltaX;
}
}
template <class ElemType>
void CPUMatrix<ElemType>::Reshape(const size_t numRows, const size_t numCols)
{
if (numRows * numCols != GetNumElements())
InvalidArgument("Reshape: Total number of elements does not match.");
m_numRows = numRows;
m_numCols = numCols;
}
// RequireSize() -- Tests if the matrix is the right size. If not, resizes the matrix. This avoids the VerifyResizable check if we're already the right size.
template <class ElemType>
void CPUMatrix<ElemType>::RequireSize(const size_t numRows, const size_t numCols, bool growOnly /*=true*/)
{
if (GetNumRows() != numRows || GetNumCols() != numCols)
Resize(numRows, numCols, growOnly);
}
// Resize() -- change matrix size
// This function is cheap if the matrix size does not change.
// Current content is not preserved.
// If growOnly is true, resize will not reallocate memory if the current memory is large enough (i.e., will not shrink).
// If this object does not own its memory then new memory cannot be allocated (one can still shrink and/or reshape).
template <class ElemType>
void CPUMatrix<ElemType>::Resize(const size_t numRows, const size_t numCols, bool growOnly /*=true*/)
{
if (GetNumRows() == numRows && GetNumCols() == numCols)
return;
VerifyResizable(__func__);
size_t numElements = numRows * numCols;
if (numElements > GetSizeAllocated() || // grow allocation
(!growOnly && (numElements != GetSizeAllocated()))) // shrink allocation (not if 'growOnly')
{
// reallocate buffer
ElemType* pArray = nullptr;
if (numElements > 0)
{
pArray = NewArray<ElemType>(numElements);
}
// success: update the object
delete[] Buffer();
SetBuffer(pArray, numElements * sizeof(ElemType));
SetSizeAllocated(numElements);
}
// success
m_sliceViewOffset = 0;
m_numRows = numRows;
m_numCols = numCols;
}
// allocated by the callee but should be deleted by the caller
// TODO: change to use STL vector instead
template <class ElemType>
ElemType* CPUMatrix<ElemType>::CopyToArray() const
{
size_t numElements = GetNumElements();
if (numElements != 0)
{
ElemType* arrayCopyTo = NewArray<ElemType>(numElements);
memcpy(arrayCopyTo, Data(), sizeof(ElemType) * numElements);
return arrayCopyTo;
}
else
{
return nullptr;
}
}
//memory will be allocated by the callee if not enough but need to be deleted by the caller after it's done
//return number of elements copied
template <class ElemType>
size_t CPUMatrix<ElemType>::CopyToArray(ElemType*& arrayCopyTo, size_t& currentArraySize) const
{
size_t numElements = GetNumElements();
if (numElements > currentArraySize)
{
delete arrayCopyTo;
arrayCopyTo = NewArray<ElemType>(numElements);
currentArraySize = numElements;
}
if (numElements != 0)
{
memcpy(arrayCopyTo, Data(), sizeof(ElemType) * numElements);
}
return numElements;
}
template <typename ElemType>
void CPUMatrix<ElemType>::CopySection(size_t /*numRows*/, size_t /*numCols*/, ElemType* /*dst*/, size_t /*colStride*/) const
{
// REVIEW alexeyk: currently not used by CPU, but implement when possible.
RuntimeError("Not implemented.");
}
template <class ElemType>
inline size_t CPUMatrix<ElemType>::LocateColumn(const size_t col) const
{
// For performance reason avoid extra validation in release.
assert(col == 0 || col < GetNumCols());
return col * m_numRows; // matrix in column-wise storage
}
template <class ElemType>
inline size_t CPUMatrix<ElemType>::LocateElement(const size_t row, const size_t col) const
{
// For performance reason avoid extra validation in release.
assert(row < m_numRows);
return LocateColumn(col) + row; // matrix in column-wise storage
}
#pragma endregion Basic Operators
#pragma region Member BLAS Functions
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::operator+=(ElemType alpha)
{
return AssignSumOf(alpha, *this);
}
template <class ElemType>
CPUMatrix<ElemType> CPUMatrix<ElemType>::operator+(ElemType alpha) const
{
CPUMatrix<ElemType> c(GetNumRows(), GetNumCols());
c.AssignSumOf(alpha, *this);
return c;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignSumOf(const ElemType alpha, const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty())
LogicError("AssignSumOf: Matrix a is empty.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
long m = (long) GetNumRows(), n = (long) GetNumCols();
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, j) = alpha + a(i, j);
us(i + 1, j) = alpha + a(i + 1, j);
us(i + 2, j) = alpha + a(i + 2, j);
us(i + 3, j) = alpha + a(i + 3, j);
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(i, j) = alpha + a(i, j);
}
}
return *this;
}
//if [this] and a have same dimension then [this]=[this]+a
//if a is a column vector, add to all columns of [this]
//if a is a row vector, add to all rows of [this]
//if a is a scalar, add it to all elements.
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::operator+=(const CPUMatrix<ElemType>& a)
{
// if (a.GetNumElements() == 1)
// *this += a(0,0);
// else
ScaleAndAdd(1, a, *this);
return *this;
}
//if [this] and a have same dimension then OUTPUT=[this]+a
//if a is a column vector, add to all columns of [this]
//if a is a row vector, add to all rows of [this]
template <class ElemType>
CPUMatrix<ElemType> CPUMatrix<ElemType>::operator+(const CPUMatrix<ElemType>& a) const
{
if (GetNumElements() == 1)
{
CPUMatrix<ElemType> c(a);
c += (*this)(0, 0);
return c;
}
else if (a.GetNumElements() == 1)
{
CPUMatrix<ElemType> c(*this);
c += a(0, 0);
return c;
}
else
{
CPUMatrix<ElemType> c(*this); // this implementation will introduce a copy overhead. but make resue of the code
c += a;
return c;
}
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignSumOf(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b)
{
if (a.GetNumElements() == 1)
{
SetValue(b);
(*this) += a;
}
else
{
SetValue(a);
(*this) += b;
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::operator-=(ElemType alpha)
{
return AssignDifferenceOf(*this, alpha);
}
template <class ElemType>
CPUMatrix<ElemType> CPUMatrix<ElemType>::operator-(ElemType alpha) const
{
CPUMatrix<ElemType> c(GetNumRows(), GetNumCols());
c.AssignDifferenceOf(*this, alpha);
return c;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignDifferenceOf(const ElemType alpha, const CPUMatrix<ElemType>& a)
{
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
long m = (long) GetNumRows(), n = (long) GetNumCols();
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, j) = alpha - a(i, j);
us(i + 1, j) = alpha - a(i + 1, j);
us(i + 2, j) = alpha - a(i + 2, j);
us(i + 3, j) = alpha - a(i + 3, j);
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(i, j) = alpha - a(i, j);
}
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignDifferenceOf(const CPUMatrix<ElemType>& a, const ElemType alpha)
{
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
long m = (long) GetNumRows(), n = (long) GetNumCols();
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, j) = a(i, j) - alpha;
us(i + 1, j) = a(i + 1, j) - alpha;
us(i + 2, j) = a(i + 2, j) - alpha;
us(i + 3, j) = a(i + 3, j) - alpha;
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(i, j) = a(i, j) - alpha;
}
}
return *this;
}
//if [this] and a have same dimension then [this]=[this]-a
//if a is a column vector, minus it from all columns of [this]
//if a is a row vector, minus it from all rows of [this]
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::operator-=(const CPUMatrix<ElemType>& a)
{
ScaleAndAdd(-1, a, *this);
return *this;
}
//if [this] and a have same dimension then output=[this]-a
//if a is a column vector, minus it from all columns of [this]
//if a is a row vector, minus it from all rows of [this]
template <class ElemType>
CPUMatrix<ElemType> CPUMatrix<ElemType>::operator-(const CPUMatrix<ElemType>& a) const
{
CPUMatrix<ElemType> c(*this); // this implementation will introduce a copy overhead. but make resue of the code
c -= a;
return c;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignDifferenceOf(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b)
{
if (this != &a)
{
RequireSize(a.GetNumRows(), a.GetNumCols());
SetValue(a);
}
(*this) -= b;
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::operator*=(ElemType alpha)
{
Scale(alpha, *this);
return *this;
}
template <class ElemType>
CPUMatrix<ElemType> CPUMatrix<ElemType>::operator*(ElemType alpha) const
{
CPUMatrix<ElemType> c(GetNumRows(), GetNumCols());
Scale(alpha, *this, c);
return c;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignProductOf(const ElemType alpha, const CPUMatrix<ElemType>& a)
{
Scale(alpha, a, *this);
return *this;
}
// [this]=a*b
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignProductOf(const CPUMatrix<ElemType>& a, const bool transposeA, const CPUMatrix<ElemType>& b, const bool transposeB)
{
if (a.GetNumElements() == 1)
{
if (transposeB)
AssignTransposeOf(b);
(*this) *= a(0, 0);
}
else if (b.GetNumElements() == 1)
{
if (transposeA)
AssignTransposeOf(a);
(*this) *= b(0, 0);
}
else
Multiply(a, transposeA, b, transposeB, *this);
return *this;
}
template <class ElemType>
CPUMatrix<ElemType> CPUMatrix<ElemType>::operator*(const CPUMatrix<ElemType>& a) const
{
auto& us = *this;
if (GetNumElements() == 1)
{
CPUMatrix<ElemType> c;
c.AssignProductOf(us(0, 0), a);
return c;
}
else if (a.GetNumElements() == 1)
{
CPUMatrix<ElemType> c;
c.AssignProductOf(a(0, 0), us);
return c;
}
else
{
CPUMatrix<ElemType> c;
Multiply(*this, a, c);
return c;
}
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::operator/=(ElemType alpha)
{
(*this) *= 1 / alpha;
return (*this);
}
template <class ElemType>
CPUMatrix<ElemType> CPUMatrix<ElemType>::operator/(ElemType alpha) const
{
return ((*this) * (1 / alpha));
}
//element-wise power
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::operator^=(ElemType alpha)
{
auto& us = *this;
ElementWisePower(alpha, us, us);
return us;
}
//element-wise power
template <class ElemType>
CPUMatrix<ElemType> CPUMatrix<ElemType>::operator^(ElemType alpha) const
{
CPUMatrix<ElemType> c(GetNumRows(), GetNumCols());
ElementWisePower(alpha, *this, c);
return c;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignElementPowerOf(const CPUMatrix<ElemType>& a, const ElemType power)
{
ElementWisePower(power, a, *this);
return *this;
}
//[this]=[this] .* a (we cannot override operator .* in c++)
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::ElementMultiplyWith(const CPUMatrix<ElemType>& a)
{
return AssignElementProductOf(*this, a);
}
//[this]=[this] .* a (we cannot override operator .* in c++)
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::ElementDivideBy(const CPUMatrix<ElemType>& a)
{
return AssignElementDivisionOf(*this, a);
}
//[this]=a .* b
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignElementProductOf(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b)
{
if (a.IsEmpty() || b.IsEmpty())
LogicError("AssignElementProductOf: Matrix is empty.");
if (!(a.GetNumRows() == b.GetNumRows() && a.GetNumCols() == b.GetNumCols()))
InvalidArgument("AssignElementProductOf: The input matrix dimensions do not match.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
long m = (long) GetNumRows(), n = (long) GetNumCols();
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, j) = a(i, j) * b(i, j);
us(i + 1, j) = a(i + 1, j) * b(i + 1, j);
us(i + 2, j) = a(i + 2, j) * b(i + 2, j);
us(i + 3, j) = a(i + 3, j) * b(i + 3, j);
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(i, j) = a(i, j) * b(i, j);
}
}
return *this;
}
//[this] +=a .* b
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AddElementProductOf(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b)
{
if (a.IsEmpty() || b.IsEmpty())
LogicError("AddElementProductOf: Matrix is empty.");
if (!(a.GetNumRows() == b.GetNumRows() && a.GetNumCols() == b.GetNumCols()))
InvalidArgument("AddElementProductOf : The input matrix dimensions do not match.");
if (!(a.GetNumRows() == GetNumRows() && a.GetNumCols() == GetNumCols()))
InvalidArgument("AddElementProductOf : The input matrix dimensions do not match [this].");
auto& us = *this;
long m = (long) GetNumRows(), n = (long) GetNumCols();
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, j) += a(i, j) * b(i, j);
us(i + 1, j) += a(i + 1, j) * b(i + 1, j);
us(i + 2, j) += a(i + 2, j) * b(i + 2, j);
us(i + 3, j) += a(i + 3, j) * b(i + 3, j);
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(i, j) += a(i, j) * b(i, j);
}
}
return *this;
}
//[this]=a ./ b
// TODO: This clips the divisor by a small value. Is that really what one would want?
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignElementDivisionOf(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b)
{
if (a.IsEmpty() || b.IsEmpty())
LogicError("AssignElementDivisionOf: Matrix is empty.");
if (!(a.GetNumRows() == b.GetNumRows() && a.GetNumCols() == b.GetNumCols()))
InvalidArgument("AssignElementDivisionOf : The input matrix dimensions do not match.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
ElemType smallValue = EPS_IN_INVERSE;
#pragma omp parallel for
foreach_coord (i, j, us)
{
ElemType v = b(i, j);
if (v >= 0 && v < smallValue)
us(i, j) = a(i, j) / smallValue;
else if (v < 0 && v > -smallValue)
us(i, j) = a(i, j) / (-smallValue);
else
us(i, j) = a(i, j) / v;
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::ColumnElementMultiplyWith(const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty() || IsEmpty())
LogicError("ColumnElementMultiplyWith: Matrix is empty.");
if (!(a.GetNumRows() == GetNumRows() && a.GetNumCols() == 1))
InvalidArgument("ColumnElementMultiplyWith: The input matrix should be a col vector and match [this]'s rows.");
auto& us = *this;
long m = (long) GetNumRows(), n = (long) GetNumCols();
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, j) *= a(i, 0);
us(i + 1, j) *= a(i + 1, 0);
us(i + 2, j) *= a(i + 2, 0);
us(i + 3, j) *= a(i + 3, 0);
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(i, j) *= a(i, 0);
}
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::RowElementMultiplyWith(const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty() || IsEmpty())
LogicError("RowElementMultiplyWith: Matrix is empty.");
if (!(a.GetNumRows() == 1 && a.GetNumCols() == GetNumCols()))
InvalidArgument("RowElementMultiplyWith: The input matrix should be a row vector and match [this]'s columns.");
auto& us = *this;
long m = (long) GetNumRows(), n = (long) GetNumCols();
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
ElemType v = a(0, j);
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, j) *= v;
us(i + 1, j) *= v;
us(i + 2, j) *= v;
us(i + 3, j) *= v;
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(i, j) *= v;
}
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::RowElementDivideBy(const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty() || IsEmpty())
LogicError("RowElementDivideBy: Matrix is empty.");
if (!(a.GetNumRows() == 1 && a.GetNumCols() == GetNumCols()))
InvalidArgument("RowElementDivideBy: The input matrix should be a row vector and match [this]'s columns.");
auto& us = *this;
long m = (long) GetNumRows(), n = (long) GetNumCols();
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
ElemType v = a(0, j);
if (v >= 0 && v < EPS_IN_INVERSE)
v = EPS_IN_INVERSE;
else if (v < 0 && v > -EPS_IN_INVERSE)
v = (-EPS_IN_INVERSE);
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, j) /= v;
us(i + 1, j) /= v;
us(i + 2, j) /= v;
us(i + 3, j) /= v;
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(i, j) /= v;
}
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::ColumnElementDivideBy(const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty() || IsEmpty())
LogicError("ColumnElementDivideBy: Matrix is empty.");
if (!(a.GetNumRows() == GetNumRows() && a.GetNumCols() == 1))
InvalidArgument("ColumnElementDivideBy: The input matrix should be a col vector and match [this]'s rows.");
auto& us = *this;
long m = (long) GetNumRows(), n = (long) GetNumCols();
ElemType smallValue = EPS_IN_INVERSE;
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
for (long i = 0; i < m; i++)
{
ElemType v = a(i, 0);
if (v >= 0 && v < smallValue)
us(i, j) /= smallValue;
else if (v < 0 && v > -smallValue)
us(i, j) /= (-smallValue);
else
us(i, j) /= v;
}
}
return *this;
}
//[this]=1 ./ a
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::ElementInverse()
{
return AssignElementInverseOf(*this);
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignElementInverseOf(const CPUMatrix<ElemType>& a)
{
ElemType smallValue = EPS_IN_INVERSE;
if (a.IsEmpty())
LogicError("AssignElementInverseOf: Matrix a is empty.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
#pragma omp parallel for
foreach_coord (i, j, us)
{
if (a(i, j) < 0 && a(i, j) > -smallValue)
us(i, j) = 1 / (-smallValue);
else if (a(i, j) >= 0 && a(i, j) < smallValue)
us(i, j) = 1 / smallValue;
else
us(i, j) = 1 / a(i, j);
}
return *this;
}
//[this]=sigmoid([this]) element wise
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::InplaceSigmoid()
{
return AssignSigmoidOf(*this);
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignSigmoidOf(const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty())
LogicError("AssignSigmoidOf: Matrix a is empty.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
#pragma omp parallel for
foreach_coord (i, j, us)
{
if (a(i, j) >= 0)
us(i, j) = 1 / (1 + exp(-a(i, j)));
else
{
ElemType v = exp(a(i, j));
us(i, j) = v / (1 + v);
}
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::InplaceLinearRectifierDerivative()
{
return AssignLinearRectifierDerivativeOf(*this);
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignLinearRectifierDerivativeOf(const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty())
LogicError("AssignLinearRectifierDerivativeOf: Matrix a is empty.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
long m = (long) GetNumRows(), n = (long) GetNumCols();
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, j) = a(i, j) > 0.0f ? 1.0f : 0.0f;
us(i + 1, j) = a(i + 1, j) > 0.0f ? 1.0f : 0.0f;
us(i + 2, j) = a(i + 2, j) > 0.0f ? 1.0f : 0.0f;
us(i + 3, j) = a(i + 3, j) > 0.0f ? 1.0f : 0.0f;
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(i, j) = a(i, j) > 0.0f ? 1.0f : 0.0f;
}
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::InplaceSigmoidDerivative()
{
return AssignSigmoidDerivativeOf(*this);
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignSigmoidDerivativeOf(const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty())
LogicError("AssignSigmoidDerivativeOf: Matrix a is empty.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
long m = (long) GetNumRows(), n = (long) GetNumCols();
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
ElemType v = a(i, j);
us(i, j) = v * (1 - v);
ElemType v1 = a(i + 1, j);
us(i + 1, j) = v1 * (1 - v1);
ElemType v2 = a(i + 2, j);
us(i + 2, j) = v2 * (1 - v2);
ElemType v3 = a(i + 3, j);
us(i + 3, j) = v3 * (1 - v3);
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
ElemType v = a(i, j);
us(i, j) = v * (1 - v);
}
}
return *this;
}
//[this]=tanh([this]) element wise
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::InplaceTanh()
{
return AssignTanhOf(*this);
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignTanhOf(const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty())
LogicError("AssignTanhOf: Matrix a is empty.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
long m = (long) GetNumRows(), n = (long) GetNumCols();
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, j) = tanh(a(i, j));
us(i + 1, j) = tanh(a(i + 1, j));
us(i + 2, j) = tanh(a(i + 2, j));
us(i + 3, j) = tanh(a(i + 3, j));
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(i, j) = tanh(a(i, j));
}
}
return *this;
}
//[this]=softmax([this]) element wise
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::InplaceLogSoftmax(const bool isColWise)
{
return AssignLogSoftmaxOf(*this, isColWise);
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignLogSoftmaxOf(const CPUMatrix<ElemType>& a, const bool isColWise)
{
if (a.IsEmpty())
LogicError("AssignLogSoftmaxOf: Matrix a is empty.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
if (isColWise)
{
#pragma omp parallel for
foreach_column (j, a)
{
// we need to extract max before applying exp to avoid overflow
ElemType maxV = a(0, j);
foreach_row (i, a)
maxV = std::max(maxV, a(i, j));
ElemType sum = 0;
foreach_row (i, a)
sum += exp(us(i, j) = a(i, j) - maxV);
sum = log(sum);
foreach_row (i, us)
us(i, j) -= sum;
}
}
else
{
#pragma omp parallel for
foreach_row (i, a)
{
// we need to extract max before applying exp to avoid overflow
ElemType maxV = a(i, 0);
foreach_column (j, a)
maxV = std::max(maxV, a(i, j));
ElemType sum = 0;
foreach_column (j, a)
sum += exp(us(i, j) = a(i, j) - maxV);
sum = log(sum);
foreach_column (j, us)
us(i, j) -= sum;
}
}
return *this;
}
//[this]=hardmax([this])
//the max element is 1 else is 0
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::InplaceHardmax(const bool isColWise)
{
return AssignHardmaxOf(*this, isColWise);
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignHardmaxOf(const CPUMatrix<ElemType>& a, const bool isColWise)
{
if (a.IsEmpty())
LogicError("AssignHardmaxOf: Matrix a is empty.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
if (isColWise)
{
#pragma omp parallel for
foreach_column (j, a)
{
// we need to extract max
ElemType maxV = a(0, j);
long maxI = 0;
foreach_row (i, a)
{
if (maxV < a(i, j))
{
maxV = a(i, j);
maxI = i;
}
}
foreach_row (i, us)
us(i, j) = (i == maxI) ? 1.0f : 0.0f;
}
}
else
{
#pragma omp parallel for
foreach_row (i, a)
{
// we need to extract max
ElemType maxV = a(i, 0);
long maxJ = 0;
foreach_column (j, a)
{
if (maxV < a(i, j))
{
maxV = a(i, j);
maxJ = j;
}
}
foreach_column (j, us)
us(i, j) = (j == maxJ) ? 1.0f : 0.0f;
}
}
return *this;
}
//[this]=sqrt([this]) element wise
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::InplaceSqrt()
{
return AssignSqrtOf(*this);
}
//to prevent negative values caused by floating operations, we force inputs to be >=0
//this may, however, hide problems in the caller.
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignSqrtOf(const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty())
LogicError("AssignSqrtOf: Matrix a is empty.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
long m = (long) GetNumRows(), n = (long) GetNumCols();
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, j) = sqrt(max((ElemType)0, a(i, j)));
us(i + 1, j) = sqrt(max((ElemType)0, a(i + 1, j)));
us(i + 2, j) = sqrt(max((ElemType)0, a(i + 2, j)));
us(i + 3, j) = sqrt(max((ElemType)0, a(i + 3, j)));
}
// remaining
for (long i = m & ~3; i < m; i++)
{
us(i, j) = sqrt(max((ElemType)0, a(i, j)));
}
}
return *this;
}
//[this]=exp([this]) element wise
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::InplaceExp()
{
return AssignExpOf(*this);
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignExpOf(const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty())
LogicError("AssignExpOf: Matrix a is empty.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
long m = (long) GetNumRows(), n = (long) GetNumCols();
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, j) = exp(a(i, j));
us(i + 1, j) = exp(a(i + 1, j));
us(i + 2, j) = exp(a(i + 2, j));
us(i + 3, j) = exp(a(i + 3, j));
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(i, j) = exp(a(i, j));
}
}
return *this;
}
//[this]=exp([this]) element wise
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::InplaceAbs()
{
return AssignAbsOf(*this);
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignAbsOf(const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty())
LogicError("AssignAbsOf: Matrix a is empty.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
long m = (long) GetNumRows(), n = (long) GetNumCols();
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
us(i, j) = abs(a(i, j));
us(i + 1, j) = abs(a(i + 1, j));
us(i + 2, j) = abs(a(i + 2, j));
us(i + 3, j) = abs(a(i + 3, j));
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
us(i, j) = abs(a(i, j));
}
}
return *this;
}
//[this]=log([this]) element wise
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::InplaceLog()
{
return AssignLogOf(*this);
}
//[this]=log([this]) element wise
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::InplaceLog10()
{
return AssignLog10Of(*this);
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignLogOf(const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty())
LogicError("AssignLogOf: Matrix a is empty.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
#pragma omp parallel for
foreach_coord (i, j, a)
{
const ElemType v = a(i, j);
if (v < EPS_IN_LOG)
{
us(i, j) = LOG_OF_EPS_IN_LOG;
}
else
us(i, j) = log(v);
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignLog10Of(const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty())
LogicError("AssignLogOf: Matrix a is empty.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
#pragma omp parallel for
foreach_coord (i, j, a)
{
const ElemType v = a(i, j);
if (v <= 0)
LogicError("AssignLogOf: Log can only applied to numbers larger than 0.");
else if (v < EPS_IN_LOG)
{
us(i, j) = LOG10_OF_EPS_IN_LOG;
}
else
us(i, j) = log10(v);
}
return *this;
}
//[this]=cos([this]) element wise
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::InplaceCosine()
{
return AssignCosineOf(*this);
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignCosineOf(const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty())
LogicError("AssignCosineOf: Matrix a is empty.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
#pragma omp parallel for
foreach_coord (i, j, a)
{
const ElemType v = a(i, j);
us(i, j) = cos(v);
}
return *this;
}
//[this]=-sin([this]) element wise
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::InplaceNegativeSine()
{
return AssignNegativeSineOf(*this);
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignNegativeSineOf(const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty())
LogicError("AssignCosineOf: Matrix a is empty.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
#pragma omp parallel for
foreach_coord (i, j, a)
{
const ElemType v = a(i, j);
us(i, j) = -sin(v);
}
return *this;
}
//Threshold truncating: this[i] = max( this[i], threshold )
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::InplaceTruncateBottom(const ElemType threshold)
{
if (IsEmpty())
LogicError("InplaceTruncateBottom: Matrix is empty.");
auto& us = *this;
long m = (long) GetNumRows(), n = (long) GetNumCols();
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
if (us(i, j) < threshold)
us(i, j) = threshold;
if (us(i + 1, j) < threshold)
us(i + 1, j) = threshold;
if (us(i + 2, j) < threshold)
us(i + 2, j) = threshold;
if (us(i + 3, j) < threshold)
us(i + 3, j) = threshold;
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
if (us(i, j) < threshold)
us(i, j) = threshold;
}
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::InplaceTruncate(const ElemType threshold)
{
if (IsEmpty())
LogicError("InplaceTruncate: Matrix is empty.");
auto& us = *this;
ElemType locThresholdPos = abs(threshold);
ElemType locTHresholdNeg = -locThresholdPos;
long m = (long) GetNumRows(), n = (long) GetNumCols();
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
if (us(i, j) > locThresholdPos)
us(i, j) = locThresholdPos;
else if (us(i, j) < locTHresholdNeg)
us(i, j) = locTHresholdNeg;
if (us(i + 1, j) > locThresholdPos)
us(i + 1, j) = locThresholdPos;
else if (us(i + 1, j) < locTHresholdNeg)
us(i + 1, j) = locTHresholdNeg;
if (us(i + 2, j) > locThresholdPos)
us(i + 2, j) = locThresholdPos;
else if (us(i + 2, j) < locTHresholdNeg)
us(i + 2, j) = locTHresholdNeg;
if (us(i + 3, j) > locThresholdPos)
us(i + 3, j) = locThresholdPos;
else if (us(i + 3, j) < locTHresholdNeg)
us(i + 3, j) = locTHresholdNeg;
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
if (us(i, j) > locThresholdPos)
us(i, j) = locThresholdPos;
else if (us(i, j) < locTHresholdNeg)
us(i, j) = locTHresholdNeg;
}
}
return *this;
}
//x= x-threshold if x>threshold, x+threshold if x<-threshold, 0 otherwise
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::InplaceSoftThreshold(const ElemType threshold)
{
if (IsEmpty())
LogicError("InplaceTruncate: Matrix is empty.");
long m = (long) GetNumElements();
ElemType* bufPtr = Data();
#pragma omp parallel for
for (long i = 0; i < (m & ~3); i += 4) // four-way unrolling
{
if (bufPtr[i] > threshold)
bufPtr[i] -= threshold;
else if (bufPtr[i] < -threshold)
bufPtr[i] += threshold;
else
bufPtr[i] = 0;
if (bufPtr[i + 1] > threshold)
bufPtr[i + 1] -= threshold;
else if (bufPtr[i + 1] < -threshold)
bufPtr[i + 1] += threshold;
else
bufPtr[i + 1] = 0;
if (bufPtr[i + 2] > threshold)
bufPtr[i + 2] -= threshold;
else if (bufPtr[i + 2] < -threshold)
bufPtr[i + 2] += threshold;
else
bufPtr[i + 2] = 0;
if (bufPtr[i + 3] > threshold)
bufPtr[i + 3] -= threshold;
else if (bufPtr[i + 3] < -threshold)
bufPtr[i + 3] += threshold;
else
bufPtr[i + 3] = 0;
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
if (bufPtr[i] > threshold)
bufPtr[i] -= threshold;
else if (bufPtr[i] < -threshold)
bufPtr[i] += threshold;
else
bufPtr[i] = 0;
}
return *this;
}
//Threshold truncating: this[i] = max( a[i], threshold )
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignTruncateBottomOf(const CPUMatrix<ElemType>& a, const ElemType threshold)
{
if (a.IsEmpty())
LogicError("AssignTruncateBottomOf: Matrix a is empty.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
#pragma omp parallel for
foreach_coord (i, j, a)
{
if (a(i, j) < threshold)
us(i, j) = threshold;
else
us(i, j) = a(i, j);
}
return *this;
}
//Threshold truncating: this[i] = min( this[i], threshold )
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::InplaceTruncateTop(const ElemType threshold)
{
if (IsEmpty())
LogicError("InplaceTruncateTop: Matrix is empty.");
auto& us = *this;
#pragma omp parallel for
foreach_coord (i, j, us)
{
if (us(i, j) > threshold)
us(i, j) = threshold;
}
return *this;
}
//Threshold truncating: this[i] = min( a[i], threshold )
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignTruncateTopOf(const CPUMatrix<ElemType>& a, const ElemType threshold)
{
if (a.IsEmpty())
LogicError("AssignTruncateTopOf: Matrix a is empty.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
#pragma omp parallel for
foreach_coord (i, j, a)
{
if (a(i, j) > threshold)
us(i, j) = threshold;
else
us(i, j) = a(i, j);
}
return *this;
}
//Threshold truncating: this[i] = 0 if abs(this[i]<threshold).
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::SetToZeroIfAbsLessThan(const ElemType threshold)
{
if (IsEmpty())
LogicError("SetToZeroIfAbsLessThan: Matrix is empty.");
auto& us = *this;
#pragma omp parallel for
foreach_coord (i, j, us)
{
if (abs(us(i, j)) < threshold)
us(i, j) = 0;
}
return *this;
}
//sum of all abs(elements)
template <class ElemType>
ElemType CPUMatrix<ElemType>::SumOfAbsElements() const
{
if (IsEmpty())
LogicError("SumOfAbsElements: Matrix is empty.");
if (sizeof(ElemType) == sizeof(double))
{
return (ElemType) cblas_dasum((int) GetNumElements(), reinterpret_cast<double*>(Data()), 1);
}
else
{
#pragma warning(suppress : 4244)
return cblas_sasum((int) GetNumElements(), reinterpret_cast<float*>(Data()), 1);
}
}
//sum of all elements
template <class ElemType>
ElemType CPUMatrix<ElemType>::SumOfElements() const
{
if (IsEmpty())
LogicError("SumOfElements: Matrix is empty.");
ElemType sum = 0;
long m = (long) GetNumElements(); // note: OpenMP requires loop indices to be long, not size_t
ElemType* bufPtr = Data();
//four-way unrolling
#pragma omp parallel for reduction(+ : sum)
for (long i = 0; i < (m & ~3); i += 4)
{
sum += bufPtr[i] + bufPtr[i + 1] + bufPtr[i + 2] + bufPtr[i + 3];
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
sum += bufPtr[i];
}
return sum;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignSumOfElements(const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty())
LogicError("AssignSumOfElements: Matrix a is empty.");
auto& us = *this;
us.RequireSize(1, 1);
us(0, 0) = a.SumOfElements();
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignOneHot(const CPUMatrix<ElemType>& a, vector<size_t>& shape, size_t axis)
{
if (a.IsEmpty())
LogicError("AssignOneHot: Matrix a is empty.");
if (axis >= shape.size())
LogicError("AssignOneHot: axis is not correct");
size_t item_size = 1;
for (size_t i = 0; i < shape.size() && i < axis; i++)
item_size *= shape[i];
size_t num_class = shape[axis];
auto& us = *this;
auto nCols = a.GetNumCols();
auto nRows = num_class * a.GetNumRows();
us.RequireSize(nRows, nCols);
ElemType* bufPtr = Data();
ElemType* aBufPtr = a.Data();
memset(bufPtr, 0, sizeof(ElemType) * nRows *nCols);
#pragma omp parallel for
for (long i = 0; i < a.GetNumElements(); i++)
{
if (aBufPtr[i] >= 0 && aBufPtr[i] < num_class)
{
size_t block_id = i / item_size;
size_t item_id = i % item_size;
bufPtr[block_id * num_class * item_size + item_id + item_size * (size_t)aBufPtr[i]] = 1;
}
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::GatherFromTarget(const CPUMatrix<ElemType>& indices, const CPUMatrix<ElemType>& target, size_t row_elements)
{
if (indices.IsEmpty() || target.IsEmpty())
LogicError("GatherFromTarget: input matrix is empty.");
if (row_elements == 0)
LogicError("GatherFromTarget: target matrix at least need 1 dim.");
auto nCols = indices.GetNumCols();
auto nRows = indices.GetNumRows() * row_elements;
this->RequireSize(nRows, nCols);
ElemType* indicesBufPtr = indices.Data();
ElemType* targetBufPtr = target.Data();
ElemType* buffer = Data();
#pragma omp parallel for
for (int i = 0; i < indices.GetNumElements(); i++)
{
memcpy(buffer + i * row_elements, targetBufPtr + ((size_t)indicesBufPtr[i] * row_elements), sizeof(ElemType) * row_elements);
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::ScatterToIndices(const CPUMatrix<ElemType>& values, const CPUMatrix<ElemType>& indices, size_t row_elements)
{
if (indices.IsEmpty() || values.IsEmpty())
LogicError("ScatterToIndices: input matrix is empty.");
ElemType* indicesBufPtr = indices.Data();
ElemType* valueBufPtr = values.Data();
ElemType* buffer = Data();
ScatterValues(indicesBufPtr, valueBufPtr, buffer, (ElemType)1, indices.GetNumElements(), row_elements, this->GetNumCols());
return *this;
}
template <class ElemType>
bool CPUMatrix<ElemType>::IsEqualTo(const CPUMatrix<ElemType>& a, const ElemType threshold /*= 1e-8*/) const
{
return AreEqual(*this, a, threshold);
}
template <class ElemType>
void CPUMatrix<ElemType>::VectorSum(const CPUMatrix<ElemType>& a, CPUMatrix<ElemType>& c, const bool isColWise)
{
if (a.IsEmpty())
LogicError("VectorSum: Input matrix a is empty.");
const int m = (int) a.GetNumRows();
const int n = (int) a.GetNumCols();
assert(m > 0 && n > 0); // converting from size_t to int may cause overflow
if (isColWise) // col-wise
{
c.RequireSize(1, n);
#pragma omp parallel for
foreach_column (j, a)
{
ElemType v = 0;
foreach_row (i, a)
{
#pragma omp atomic
v += a(i, j);
}
c(0, j) = v;
}
}
else
{
c.RequireSize(m, 1);
#pragma omp parallel for
foreach_row (i, a)
{
ElemType v = 0;
foreach_column (j, a)
{
#pragma omp atomic
v += a(i, j);
}
c(i, 0) = v;
}
}
}
template <class ElemType>
void CPUMatrix<ElemType>::VectorNorm1(CPUMatrix<ElemType>& c, const bool isColWise) const
{
if (IsEmpty())
LogicError("VectorNorm1: Matrix is empty.");
auto& us = *this;
const int m = (int) us.GetNumRows();
const int n = (int) us.GetNumCols();
assert(m > 0 && n > 0); // converting from size_t to int may cause overflow
if (isColWise) // col-wise
{
c.RequireSize(1, n);
#pragma omp parallel for
foreach_column (j, us)
{
ElemType v = 0;
foreach_row (i, us)
{
#pragma omp atomic
v += abs(us(i, j));
}
c(0, j) = v;
}
}
else
{
c.RequireSize(m, 1);
#pragma omp parallel for
foreach_row (i, us)
{
ElemType v = 0;
foreach_column (j, us)
{
#pragma omp atomic
v += abs(us(i, j));
}
c(i, 0) = v;
}
}
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignVectorNorm1Of(CPUMatrix<ElemType>& a, const bool isColWise)
{
a.VectorNorm1(*this, isColWise);
return *this;
}
template <class ElemType>
void CPUMatrix<ElemType>::VectorNorm2(CPUMatrix<ElemType>& c, const bool isColWise) const
{
if (IsEmpty())
LogicError("VectorNorm2: Matrix is empty.");
auto& us = *this;
const int m = (int) us.GetNumRows();
const int n = (int) us.GetNumCols();
assert(m > 0 && n > 0); // converting from size_t to int may cause overflow
ElemType* bufPtr = us.Data();
if (isColWise) // col-wise
{
c.RequireSize(1, n);
if (sizeof(ElemType) == sizeof(double))
{
#pragma omp parallel for
foreach_column (j, c)
{
c(0, j) = (ElemType) cblas_dnrm2(m, reinterpret_cast<double*>(bufPtr + us.LocateColumn(j)), 1);
}
}
else
{
#pragma omp parallel for
foreach_column (j, c)
{
#pragma warning(suppress : 4244)
c(0, j) = cblas_snrm2(m, reinterpret_cast<float*>(bufPtr + us.LocateColumn(j)), 1);
}
}
}
else
{
c.RequireSize(m, 1);
if (sizeof(ElemType) == sizeof(double))
{
#pragma omp parallel for
foreach_row (i, c)
{
c(i, 0) = cblas_dnrm2(n, reinterpret_cast<double*>(bufPtr + i), m);
}
}
else
{
#pragma omp parallel for
foreach_row (i, c)
{
#pragma warning(suppress : 4244)
c(i, 0) = cblas_snrm2(n, reinterpret_cast<float*>(bufPtr + i), m);
}
}
}
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignVectorNorm2Of(CPUMatrix<ElemType>& a, const bool isColWise)
{
a.VectorNorm2(*this, isColWise);
return *this;
}
template <class ElemType>
void CPUMatrix<ElemType>::VectorNormInf(CPUMatrix<ElemType>& c, const bool isColWise) const
{
if (IsEmpty())
LogicError("VectorNormInf: Matrix is empty.");
auto& us = *this;
const int m = (int) us.GetNumRows();
const int n = (int) us.GetNumCols();
assert(m > 0 && n > 0); // converting from size_t to int may cause overflow
if (isColWise) // col-wise
{
c.RequireSize(1, n);
// #pragma omp parallel for
foreach_column (j, us)
{
ElemType v = 0;
foreach_row (i, us)
{
v = std::max(v, abs(us(i, j)));
}
c(0, j) = v;
}
}
else
{
c.RequireSize(m, 1);
// #pragma omp parallel for
foreach_row (i, us)
{
ElemType v = 0;
foreach_column (j, us)
{
v = std::max(v, abs(us(i, j)));
}
c(i, 0) = v;
}
}
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignVectorNormInfOf(CPUMatrix<ElemType>& a, const bool isColWise)
{
a.VectorNormInf(*this, isColWise);
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignInnerProductOf(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, const bool isColWise)
{
InnerProduct(a, b, *this, isColWise);
return *this;
}
//column-wise crossproduct
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignKhatriRaoProductOf(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b)
{
if (a.IsEmpty() || b.IsEmpty())
LogicError("AssignKhatriRaoProductOf: Matrix is empty.");
long cols = (long) a.GetNumCols();
if (cols != b.GetNumCols())
InvalidArgument("a.GetNumCols() != b.GetNumCols()");
long rowsA = (long) a.GetNumRows();
long rowsB = (long) b.GetNumRows();
RequireSize(rowsA * rowsB, cols);
#ifdef __INTEL_COMPILER // TODO: check this
#pragma simd statement
#endif
#pragma omp parallel for
for (long k = 0; k < cols; k++)
{
long jj = 0;
for (long j = 0; j < rowsB; j++)
{
for (long i = 0; i < rowsA; i++)
{
(*this)(jj++, k) = a(i, k) * b(j, k);
}
}
}
return *this;
}
//column-wise reshaped product. Used to compute KhatriRaoProduct Gradient
// this = reshape each column of a from (K1xK2,1) to (K1, K2)
// if each column of a is not transposed, each (K1, K2) times each column of b (K2, frames).
// the output is a (K1, frames) matrix
// if each column of a is tranposed, each (K1, K2)^T times each column of b(K1, frames) and output is (K2, frames)
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AddColumnReshapeProductOf(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, const bool transposeAColumn)
{
if (a.IsEmpty() || b.IsEmpty())
LogicError("AddColumnReshapeProductOf: Matrix is empty.");
long cols = (long) a.GetNumCols();
if (cols != b.GetNumCols())
InvalidArgument("AddColumnReshapeProductOf: a.GetNumCols() != b.GetNumCols()");
long rowsA = (long) a.GetNumRows();
long rowsB = (long) b.GetNumRows();
if (rowsA % rowsB != 0)
InvalidArgument("AddColumnReshapeProductOf: number of rows in a should be multiples of that in b.");
long rowsC = rowsA / rowsB;
if (rowsC != GetNumRows() || cols != GetNumCols())
InvalidArgument("AddColumnReshapeProductOf: This matrix does not have the right size.");
auto& us = *this;
if (transposeAColumn)
{
// find nrows and ncols of tbe reshaped a
long nrows = rowsB;
long ncols = rowsC;
#ifdef __INTEL_COMPILER // TODO: check this
#pragma simd statement
#endif
#pragma omp parallel for
foreach_column (t, a)
{
size_t k = 0;
for (size_t j = 0; j < ncols; j++) // row and col is transposed
{
ElemType v = 0;
for (size_t i = 0; i < nrows; i++)
{
v += a(k, t) * b(i, t);
k++;
}
us(j, t) += v;
}
}
}
else
{
size_t ncols = rowsB;
size_t nrows = rowsC;
#ifdef __INTEL_COMPILER // TODO: check this
#pragma simd statement
#endif
#pragma omp parallel for
foreach_column (t, a)
{
size_t k = 0;
for (size_t j = 0; j < ncols; j++)
{
for (size_t i = 0; i < nrows; i++)
{
us(i, t) += a(k, t) * b(j, t);
k++;
}
}
}
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AddWithScaleOf(ElemType alpha, const CPUMatrix<ElemType>& a)
{
ScaleAndAdd(alpha, a, *this);
return *this;
}
template <class ElemType>
ElemType CPUMatrix<ElemType>::FrobeniusNorm() const
{
if (IsEmpty())
LogicError("FrobeniusNorm: Matrix is empty.");
ElemType v = 0;
long m = (long) GetNumElements();
ElemType* bufPtr = Data();
//four-way unrolling
#pragma omp parallel for reduction(+ : v)
for (long i = 0; i < (m & ~3); i += 4)
{
v += bufPtr[i] * bufPtr[i] + bufPtr[i + 1] * bufPtr[i + 1] + bufPtr[i + 2] * bufPtr[i + 2] + bufPtr[i + 3] * bufPtr[i + 3];
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
v += bufPtr[i] * bufPtr[i];
}
return sqrt(v);
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignFrobeniusNormOf(const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty())
LogicError("AssignFrobeniusNormOf: Matrix a is empty.");
auto& us = *this;
us.RequireSize(1, 1);
us(0, 0) = a.FrobeniusNorm();
return us;
}
template <class ElemType>
ElemType CPUMatrix<ElemType>::MatrixNormInf() const
{
if (IsEmpty())
LogicError("MatrixNormInf: Matrix is empty.");
auto& us = *this;
ElemType v = 0;
#pragma omp parallel for
foreach_coord (i, j, us)
{
#pragma omp critical
{
v = std::max(v, abs(us(i, j)));
}
}
return v;
}
template <class ElemType>
ElemType CPUMatrix<ElemType>::MatrixNorm0() const
{
if (IsEmpty())
LogicError("MatrixNorm0: Matrix is empty.");
auto& us = *this;
ElemType v = 0;
#pragma omp parallel for
foreach_coord (i, j, us)
{
if (us(i, j) != 0)
{
#pragma omp critical
{
++v;
}
}
}
return v;
}
template <class ElemType>
ElemType CPUMatrix<ElemType>::MatrixNorm1() const
{
if (IsEmpty())
LogicError("MatrixNorm1: Matrix is empty.");
auto& us = *this;
ElemType sum = 0;
#pragma omp parallel for reduction(+ : sum)
foreach_coord (i, j, us)
{
sum += abs(us(i, j));
}
return sum;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignSignOf(const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty())
LogicError("AssignSignOf: Matrix a is empty.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
#pragma omp parallel for
foreach_column (j, us)
{
foreach_row (i, us)
{
ElemType v = a(i, j);
if (!std::isnan(v))
us(i, j) = (v == (ElemType) 0 ? (ElemType) 0 : (v > 0 ? (ElemType) 1 : (ElemType)(-1)));
else
us(i, j) = v;
}
}
return us;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AddSignOf(const CPUMatrix<ElemType>& a)
{
if (a.IsEmpty())
LogicError("AddSignOf: Matrix a is empty.");
auto& us = *this;
if (this != &a)
RequireSize(a.GetNumRows(), a.GetNumCols());
#pragma omp parallel for
foreach_column (j, us)
{
foreach_row (i, us)
{
ElemType v = a(i, j);
if (!std::isnan(v))
us(i, j) += (v == (ElemType) 0 ? (ElemType) 0 : (v > 0 ? (ElemType) 1 : (ElemType)(-1)));
else
us(i, j) = v;
}
}
return us;
}
//I decided to use CPUMatrix<ElemType>& maxIndexes instead of integer vector because the result may be used to do additional calculation
template <class ElemType>
void CPUMatrix<ElemType>::VectorMax(CPUMatrix<ElemType>& maxIndexes, CPUMatrix<ElemType>& maxValues, const bool isColWise, int topK) const
{
if (IsEmpty())
LogicError("VectorMax: Matrix is empty.");
auto& us = *this;
const int m = (int) GetNumRows();
const int n = (int) GetNumCols();
if (topK > m)
InvalidArgument("VectorMax: TopK must be less or equal than the number of rows");
assert(m > 0 && n > 0); // converting from size_t to int may cause overflow
if (isColWise) // col-wise
{
maxValues.RequireSize(topK, n);
maxIndexes.RequireSize(topK, n);
if (topK == 1)
{
#pragma omp parallel for
for (int j = 0; j < n; j++)
{
ElemType v = us(0, j);
size_t index = 0;
foreach_row (i, us)
{
if (v < us(i, j))
{
index = i;
v = us(i, j);
}
}
maxValues(0, j) = v;
maxIndexes(0, j) = (ElemType) index;
}
}
else
{
std::vector<int> indices(m);
int i = 0;
std::generate(indices.begin(), indices.end(), [&i]
{
return i++;
});
const ElemType* curVal = Data();
ElemType* curIdx = maxIndexes.Data();
ElemType* curMax = maxValues.Data();
for (int icol = 0; icol < n; icol++, curVal += m, curIdx += topK, curMax += topK)
{
// Partial sort, descending order.
std::nth_element(indices.begin(), indices.begin() + topK, indices.end(),
[curVal](const int& a, const int& b)
{
return curVal[a] > curVal[b];
});
// REVIEW alexeyk: the following produces warning (see SCL_SECURE_NO_WARNINGS) so use loop instead.
// std::transform(indices.begin(), indices.begin() + topK, curIdx, [](const int& a) { return static_cast<ElemType>(a); });
for (int i2 = 0; i2 < topK; i2++)
{
curIdx[i2] = static_cast<ElemType>(indices[i2]);
curMax[i2] = curVal[indices[i2]];
}
}
}
}
else
{
if (topK > 1)
RuntimeError("Row-wise TopK max is not supported.");
maxValues.RequireSize(m, 1);
maxIndexes.RequireSize(m, 1);
#pragma omp parallel for
for (int i = 0; i < m; i++)
{
ElemType v = us(i, 0);
size_t index = 0;
foreach_column (j, us)
{
if (v < us(i, j))
{
index = j;
v = us(i, j);
}
}
maxValues(i, 0) = v;
maxIndexes(i, 0) = (ElemType) index;
}
}
}
template <class ElemType>
void CPUMatrix<ElemType>::VectorMin(CPUMatrix<ElemType>& minIndexes, CPUMatrix<ElemType>& minValues, const bool isColWise) const
{
if (IsEmpty())
LogicError("VectorMin: Matrix is empty.");
auto& us = *this;
const int m = (int) GetNumRows();
const int n = (int) GetNumCols();
assert(m > 0 && n > 0); // converting from size_t to int may cause overflow
if (isColWise) // col-wise
{
minValues.RequireSize(1, n);
minIndexes.RequireSize(1, n);
#pragma omp parallel for
for (int j = 0; j < n; j++)
{
ElemType v = us(0, j);
size_t index = 0;
foreach_row (i, us)
{
if (v > us(i, j))
{
index = i;
v = us(i, j);
}
}
minValues(0, j) = v;
minIndexes(0, j) = (ElemType) index;
}
}
else
{
minValues.RequireSize(m, 1);
minIndexes.RequireSize(m, 1);
#pragma omp parallel for
for (int i = 0; i < m; i++)
{
ElemType v = us(i, 0);
size_t index = 0;
foreach_column (j, us)
{
if (v > us(i, j))
{
index = j;
v = us(i, j);
}
}
minValues(i, 0) = v;
minIndexes(i, 0) = (ElemType) index;
}
}
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignNumOfDiff(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, bool searchInCol)
{
if (a.GetNumCols() != b.GetNumCols())
throw std::invalid_argument("AssignNumOfDiff: a and b must have the same number of columns.");
if (!searchInCol && a.GetNumRows() != b.GetNumRows())
throw std::invalid_argument("AssignNumOfDiff: a and b must have the same number of rows.");
ElemType n = 0;
if (!searchInCol)
{
foreach_coord (i, j, a)
{
n += (a(i, j) != b(i, j));
}
}
else
{
size_t crow = b.GetNumRows();
const ElemType* curCol = b.Data();
for (size_t icol = 0; icol < a.GetNumCols(); icol++, curCol += crow)
{
auto res = std::find(curCol, curCol + crow, a(0, icol));
if (res == curCol + crow)
n++;
}
}
RequireSize(1, 1); // result should be one element
(*this)(0, 0) = n;
return *this;
}
#pragma endregion Member BLAS Functions
#pragma region Other helper Functions
struct PrintRange
{
// print from begin to skipBegin, then from skipEnd to end
// skipBegin = end if no split
size_t begin;
size_t skipBegin;
size_t skipEnd;
size_t end;
bool IsEmpty() const { return end <= begin; }
// examples:
// * 3..10
// * -3..-3: include end-3..end and 0..3
PrintRange(ptrdiff_t first, ptrdiff_t last, size_t total)
{
if (first >= 0 && last >= 0)
{
begin = (size_t)first;
end = (size_t)last + 1;
if (end > total) // allow INT_MAX, meaning to end
end = total;
skipBegin = end;
skipEnd = end;
}
else if (first < 0 && last < 0)
{
begin = 0;
skipBegin = (size_t)(-last);
skipEnd = (size_t)(total + first);
if (skipEnd <= skipBegin)
skipBegin = skipEnd = total;
end = total;
}
else // if other combinations are ever of interest then implement them here
LogicError("Print: Bounds must be either both positive or both negative.");
}
};
// use negative ranges to print corners, e.g. Print("name", -3, -3, -3, -3) will print the first 3 and last 3 rows/cols
template <class ElemType>
void CPUMatrix<ElemType>::Print(const char* matrixName, ptrdiff_t rowFirst, ptrdiff_t rowLast, ptrdiff_t colFirst, ptrdiff_t colLast) const
{
fprintf(stderr, "\n###### ");
if (matrixName != nullptr)
fprintf(stderr, "%s ", matrixName);
fprintf(stderr, "(%lu, %lu)", (unsigned long)GetNumRows(), (unsigned long)GetNumCols());
if (rowFirst != 0 || colFirst != 0 || (size_t)(rowLast + 1) != GetNumRows() || (size_t)(colLast + 1) != GetNumCols())
fprintf(stderr, " [%ld:%ld, %ld:%ld]", (long)rowFirst, (long)rowLast, (long)colFirst, (long)colLast);
fprintf(stderr, " ######\n\n");
if (IsEmpty())
{
fprintf(stderr, "(empty)\n");
return;
}
PrintRange rowRange(rowFirst, rowLast, GetNumRows());
PrintRange colRange(colFirst, colLast, GetNumCols());
if (rowRange.IsEmpty() || colRange.IsEmpty())
{
fprintf(stderr, "(empty)\n");
return;
}
const auto& us = *this;
if (rowRange.begin > 0)
fprintf(stderr, "...\n");
for (size_t i = rowRange.begin; i < rowRange.end; i++)
{
if (i == rowRange.skipBegin) // insert ... between the two blocks if any
{
fprintf(stderr, "...\n");
i = rowRange.skipEnd;
}
if (colRange.begin > 0) // ... at line start
fprintf(stderr, "...\t");
for (size_t j = colRange.begin; j < colRange.end; j++)
{
if (j == colRange.skipBegin)
{
fprintf(stderr, "...\t");
j = colRange.skipEnd;
}
fprintf(stderr, "%.10f\t", us(i, j));
}
if (colRange.end < GetNumCols()) // ... at line end
fprintf(stderr, "...");
fprintf(stderr, "\n");
}
if (rowRange.end < GetNumRows())
fprintf(stderr, "...\n");
}
template <class ElemType>
void CPUMatrix<ElemType>::Print(const char* matrixName /*=nullptr*/) const
{
Print(matrixName, 0, GetNumRows() - 1, 0, GetNumCols() - 1);
}
// file I/O
//matrixName is used to verify that correct matrix is read.
template <class ElemType>
void CPUMatrix<ElemType>::ReadFromFile(FILE*, const char* /*matrixName*/)
{
RuntimeError("not implemented.");
}
//matrixName is used to verify that correct matrix is read.
template <class ElemType>
void CPUMatrix<ElemType>::WriteToFile(FILE*, const char* /*matrixName*/)
{
RuntimeError("not implemented.");
}
//assume each column is an input sample. Each sample is stored in [channel, row, col] (r00, g00, b00, r01, g01, b01, r10, g10, b10, r11, g11, b11)
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignPackedConvolutionInput(const CPUMatrix<ElemType>& inputSubBatch,
const size_t inputWidth, const size_t inputHeight, const size_t inputChannels,
const size_t outputWidth, const size_t outputHeight, const size_t /*outputChannels*/,
const size_t kernelWidth, const size_t kernelHeight, const size_t horizontalSubsample, const size_t verticalSubsample,
const bool zeroPadding)
{
if (verticalSubsample > kernelHeight || horizontalSubsample > kernelWidth)
LogicError("Arguments verticalSubsample (or horitzontalSubsample) must be less or equal than kernelHeight (or kernelWidth).");
const size_t packedInputRows = kernelWidth * kernelHeight * inputChannels;
const size_t packedInputColsPerSample = outputWidth * outputHeight; // output size per channel
const size_t inputDim = inputWidth * inputHeight * inputChannels;
const size_t smallBatchSize = inputSubBatch.GetNumCols();
const long inputHeightTimesChannel = (long) (inputHeight * inputChannels);
RequireSize(packedInputRows, packedInputColsPerSample * smallBatchSize);
if (zeroPadding)
SetValue((ElemType) 0);
const long halfKernelWidth = (long) kernelWidth / 2;
const long halfKernelHeight = (long) kernelHeight / 2;
#pragma omp parallel for // each input element is copied to many places
for (long sample = 0; sample < smallBatchSize; sample++)
{
for (long id = 0; id < inputDim; id++)
{
// IN_ELEM_ROWPOS(channel, row, col) = (channel + (row + col * inputHeight) * inputChannels)
// IN_ELEM_COLPOS = sample
const long y = id / inputHeightTimesChannel; // inputCol
const long nXC = id % inputHeightTimesChannel; // channel + inputRow*inputChannels
const long x = nXC / (long) inputChannels; // inputRow
const long c = nXC % (long) inputChannels; // channel
long x0 = 0, y0 = 0, x1 = 0, y1 = 0;
if (zeroPadding)
{
x0 = (long) max((ElemType)0, ceil((x - (ElemType)kernelHeight + 1.0f + halfKernelHeight) / (ElemType)verticalSubsample)); // row : first wrow in which x is in
x1 = (long) (x + halfKernelHeight - x0 * verticalSubsample); // first posxInKernel
y0 = (long) max((ElemType)0, ceil((y - (ElemType)kernelWidth + 1.0f + halfKernelWidth) / (ElemType)horizontalSubsample)); // col : first wcol in which y is in
y1 = (long) (y + halfKernelWidth - y0 * horizontalSubsample); // first posyInKernel
}
else
{
x0 = (long) max((ElemType)0, ceil((x - (ElemType)kernelHeight + 1) / (ElemType)verticalSubsample)); // row : first wrow in which x is in
x1 = (long) (x - x0 * verticalSubsample); // first posxInKernel
y0 = (long) max((ElemType)0, ceil((y - (ElemType)kernelWidth + 1) / (ElemType)horizontalSubsample)); // col : first wcol in which y is in
y1 = (long) (y - y0 * horizontalSubsample); // first posyInKernel
}
assert(x1 >= 0 && x1 < kernelHeight && y1 >= 0 && y1 < kernelWidth);
// PACK_ELEM_ROWPOS(channel, posxInKernel, posyInKernel) = (channel * kernelWidth * kernelHeight + posxInKernel + posyInKernel * kernelHeight)
// PACK_ELEM_COLPOS(sample, wrow, wcol) = (sample*packedInputColsPerSample + outputHeight*wcol + wrow
ElemType currentInputValue = inputSubBatch(id, sample);
long packColBase = (long) (sample * packedInputColsPerSample + y0 * outputHeight);
for (long wcol = y0, posyInKernel = y1; wcol < (long) outputWidth && posyInKernel >= 0; wcol++, posyInKernel -= (long) horizontalSubsample)
{
long packRowBase = (long) (c * kernelWidth * kernelHeight + posyInKernel * kernelHeight);
for (long wrow = x0, posxInKernel = x1; wrow < (long) outputHeight && posxInKernel >= 0; wrow++, posxInKernel -= (long) verticalSubsample)
{
const long packRow = packRowBase + posxInKernel;
const long packCol = packColBase + wrow;
(*this)(packRow, packCol) = currentInputValue;
}
packColBase += (long) outputHeight;
}
}
}
return *this;
}
//assume each column is an input sample. Each sample is stored in [channel, row, col] (r00, g00, b00, r01, g01, b01, r10, g10, b10, r11, g11, b11)
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::UnpackConvolutionInput(CPUMatrix<ElemType>& inputSubBatch,
const size_t inputWidth, const size_t inputHeight, const size_t inputChannels,
const size_t outputWidth, const size_t outputHeight, const size_t /*outputChannels*/,
const size_t kernelWidth, const size_t kernelHeight, const size_t horizontalSubsample, const size_t verticalSubsample,
const bool zeroPadding) const
{
if (verticalSubsample > kernelHeight || horizontalSubsample > kernelWidth)
LogicError("Arguments verticalSubsample (or horizonSubsample) must be less than or equal to kernelHeight (or kernelWidth).");
const size_t packedInputColsPerSample = outputWidth * outputHeight; // output size per channel
const size_t inputDim = inputWidth * inputHeight * inputChannels;
const size_t smallBatchSize = inputSubBatch.GetNumCols();
const long inputHeightTimesChannel = (long) (inputHeight * inputChannels);
const long halfKernelWidth = (long) kernelWidth / 2;
const long halfKernelHeight = (long) kernelHeight / 2;
#pragma omp parallel for // each input element is copied to many places
for (long sample = 0; sample < smallBatchSize; sample++)
{
for (long id = 0; id < inputDim; id++)
{
// IN_ELEM_ROWPOS(channel, row, col) = (channel + (row + col * inputHeight) * inputChannels)
// IN_ELEM_COLPOS = sample
const long y = id / inputHeightTimesChannel; // inputCol
const long nXC = id % inputHeightTimesChannel; // channel + inputRow*inputChannels
const long x = nXC / (long) inputChannels; // inputRow
const long c = nXC % (long) inputChannels; // channel
long x0 = 0, y0 = 0, x1 = 0, y1 = 0;
if (zeroPadding)
{
x0 = (long) max((ElemType)0, ceil((x - (ElemType) kernelHeight + 1.0f + halfKernelHeight) / (ElemType) verticalSubsample)); // row : first wrow in which x is in
x1 = (long) (x + halfKernelHeight - x0 * verticalSubsample); // first posxInKernel
y0 = (long) max((ElemType)0, ceil((y - (ElemType) kernelWidth + 1.0f + halfKernelWidth) / (ElemType) horizontalSubsample)); // col : first wcol in which y is in
y1 = (long) (y + halfKernelWidth - y0 * horizontalSubsample); // first posyInKernel
}
else
{
x0 = (long) max((ElemType)0, ceil((x - (ElemType) kernelHeight + 1) / (ElemType) verticalSubsample)); // row : first wrow in which x is in
x1 = (long) (x - x0 * verticalSubsample); // first posxInKernel
y0 = (long) max((ElemType)0, ceil((y - (ElemType) kernelWidth + 1) / (ElemType) horizontalSubsample)); // col : first wcol in which y is in
y1 = (long) (y - y0 * horizontalSubsample); // first posyInKernel
}
assert(x1 >= 0 && x1 < kernelHeight && y1 >= 0 && y1 < kernelWidth);
// PACK_ELEM_ROWPOS(channel, posxInKernel, posyInKernel) = (channel * kernelWidth * kernelHeight + posxInKernel + posyInKernel * kernelHeight)
// PACK_ELEM_COLPOS(sample, wrow, wcol) = (sample*packedInputColsPerSample + outputHeight*wcol + wrow
ElemType currentInputValue = inputSubBatch(id, sample);
long packColBase = (long) (sample * packedInputColsPerSample + y0 * outputHeight);
for (long wcol = y0, posyInKernel = y1; wcol < (long) outputWidth && posyInKernel >= 0; wcol++, posyInKernel -= (long) horizontalSubsample)
{
long packRowBase = (long) (c * kernelWidth * kernelHeight + posyInKernel * kernelHeight);
for (long wrow = x0, posxInKernel = x1; wrow < (long) outputHeight && posxInKernel >= 0; wrow++, posxInKernel -= (long) verticalSubsample)
{
const long packRow = packRowBase + posxInKernel;
const long packCol = packColBase + wrow;
currentInputValue += (*this)(packRow, packCol);
}
packColBase += (long) outputHeight;
}
inputSubBatch(id, sample) = currentInputValue;
}
}
return inputSubBatch;
}
//assume each column is an input sample. Each sample is stored in (r00, g00, b00, r01, g01, b01, r10, g10, b10, r11, g11, b11)
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignMaxPoolingResult(const CPUMatrix<ElemType>& inputBatch, const size_t channels,
const size_t /*inputWidth*/, const size_t inputHeight, const size_t /*inputSizePerSample*/,
const size_t /*outputWidth*/, const size_t outputHeight, const size_t outputSizePerSample,
const size_t windowWidth, const size_t windowHeight, const size_t horizontalSubsample, const size_t verticalSubsample)
{
const long inputHeightTimesChannel = (long) (inputHeight * channels);
const long outputHeightTimesChannel = (long) (outputHeight * channels);
const size_t batchSize = inputBatch.GetNumCols();
RequireSize(outputSizePerSample, batchSize);
// IN_ELEM_ROWPOS(channel, row, col) = (channel + (row + col * inputHeight) * channels)
// IN_ELEM_COLPOS = sample
// OUT_ELEM_ROWPOS(channel, wrow, wcol) = (channel + (wrow + wcol * outputHeight) * channels)
// OUT_ELEM_COLPOS = sample
#pragma omp parallel for
for (long sample = 0; sample < (long) batchSize; sample++)
{
for (long outputIndexWithinSample = 0; outputIndexWithinSample < outputSizePerSample; outputIndexWithinSample++)
{
const long y = outputIndexWithinSample / outputHeightTimesChannel; // wcol
const long nXC = outputIndexWithinSample % outputHeightTimesChannel; // channel + wrow*channels
const long x = (long) (nXC / channels); // wrow
const long c = (long) (nXC % channels); // channel
ElemType maxVal = -FLT_MAX;
ElemType minVal = FLT_MAX;
const long rowInWindowBase = (long) ((x * verticalSubsample + y * horizontalSubsample * inputHeight) * channels + c);
for (long colInWindow = 0; colInWindow < windowWidth; colInWindow++)
{
long rowInInput = rowInWindowBase + colInWindow * inputHeightTimesChannel;
for (long rowInWindow = 0; rowInWindow < windowHeight; rowInWindow++)
{
const ElemType val = inputBatch(rowInInput, sample); // pf[rowInWindow*channels];
maxVal = std::max(maxVal, val);
minVal = std::min(minVal, val);
rowInInput += (long) channels;
}
}
(*this)(outputIndexWithinSample, sample) = maxVal;
}
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AddMaxPoolingGradient(const CPUMatrix<ElemType>& outputGradientBatch, const CPUMatrix<ElemType>& inputBatch, const CPUMatrix<ElemType>& outputBatch,
const size_t channels,
const size_t /*inputWidth*/, const size_t inputHeight, const size_t inputSizePerSample,
const size_t outputWidth, const size_t outputHeight, const size_t /*outputSizePerSample*/,
const size_t windowWidth, const size_t windowHeight, const size_t horizontalSubsample, const size_t verticalSubsample)
{
size_t batchSize = inputBatch.GetNumCols();
const long inputHeightTimesChannel = (long) (inputHeight * channels);
const long outputHeightTimesChannel = (long) (outputHeight * channels);
// IN_ELEM_ROWPOS(channel, row, col) = (channel + (row + col * inputHeight) * channels)
// IN_ELEM_COLPOS = sample
// OUT_ELEM_ROWPOS(channel, wrow, wcol) = (channel + (wrow + wcol * outputHeight) * channels)
// OUT_ELEM_COLPOS = sample
#pragma omp parallel for
for (long sample = 0; sample < batchSize; sample++)
{
for (long inputIndexWithinSample = 0; inputIndexWithinSample < inputSizePerSample; inputIndexWithinSample++)
{
const long y = inputIndexWithinSample / inputHeightTimesChannel; // col in input
const long nXC = inputIndexWithinSample % inputHeightTimesChannel; // channel + row*chanels
const long x = (long) (nXC / channels); // row in input
const long c = (long) (nXC % channels); // channel
long startOutX = (long) max((ElemType)0, ceil((x - (ElemType) windowHeight + 1) / (ElemType) verticalSubsample)); // inclusive start
long endOutX = (long) ((x / verticalSubsample < outputHeight - 1) ? x / verticalSubsample : outputHeight - 1); // inclusive end
long startOutY = (long) max((ElemType)0, ceil((y - (ElemType) windowWidth + 1) / (ElemType) horizontalSubsample)); // inclusive start
long endOutY = (long) ((y / horizontalSubsample < outputWidth - 1) ? y / horizontalSubsample : outputWidth - 1); // inclusive end
ElemType inputValue = inputBatch(inputIndexWithinSample, sample);
for (long outY = startOutY; outY <= endOutY; outY++)
{
for (long outX = startOutX; outX <= endOutX; outX++)
{
long outputIndex = (long) (outY * outputHeightTimesChannel + outX * channels + c);
if (inputValue == outputBatch(outputIndex, sample))
(*this)(inputIndexWithinSample, sample) += outputGradientBatch(outputIndex, sample);
}
}
}
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignAveragePoolingResult(const CPUMatrix<ElemType>& inputBatch, const size_t channels,
const size_t /*inputWidth*/, const size_t inputHeight, const size_t /*inputSizePerSample*/,
const size_t /*outputWidth*/, const size_t outputHeight, const size_t outputSizePerSample,
const size_t windowWidth, const size_t windowHeight, const size_t horizontalSubsample, const size_t verticalSubsample)
{
const long inputHeightTimesChannel = (long) (inputHeight * channels);
const long outputHeightTimesChannel = (long) (outputHeight * channels);
const size_t batchSize = inputBatch.GetNumCols();
const size_t windowSize = windowWidth * windowHeight;
RequireSize(outputSizePerSample, batchSize);
// IN_ELEM_ROWPOS(channel, row, col) = (channel + (row + col * inputHeight) * channels)
// IN_ELEM_COLPOS = sample
// OUT_ELEM_ROWPOS(channel, wrow, wcol) = (channel + (wrow + wcol * outputHeight) * channels)
// OUT_ELEM_COLPOS = sample
#pragma omp parallel for
for (long sample = 0; sample < batchSize; sample++)
{
for (long outputIndexWithinSample = 0; outputIndexWithinSample < outputSizePerSample; outputIndexWithinSample++)
{
const long y = outputIndexWithinSample / outputHeightTimesChannel; // wcol
const long nXC = outputIndexWithinSample % outputHeightTimesChannel; // channel + wrow*channels
const long x = (long) (nXC / channels); // wrow
const long c = (long) (nXC % channels); // channel
ElemType sum = 0;
const long rowInWindowBase = (long) ((x * verticalSubsample + y * horizontalSubsample * inputHeight) * channels + c);
for (long colInWindow = 0; colInWindow < windowWidth; colInWindow++)
{
long rowInInput = rowInWindowBase + colInWindow * inputHeightTimesChannel;
for (long rowInWindow = 0; rowInWindow < windowHeight; rowInWindow++)
{
sum += inputBatch(rowInInput, sample);
rowInInput += (long) channels;
}
}
(*this)(outputIndexWithinSample, sample) = sum / windowSize;
}
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AddAveragePoolingGradient(const CPUMatrix<ElemType>& outputGradientBatch,
const size_t channels,
const size_t /*inputWidth*/, const size_t inputHeight, const size_t inputSizePerSample,
const size_t outputWidth, const size_t outputHeight, const size_t /*outputSizePerSample*/,
const size_t windowWidth, const size_t windowHeight, const size_t horizontalSubsample, const size_t verticalSubsample)
{
size_t batchSize = outputGradientBatch.GetNumCols();
const long inputHeightTimesChannel = (long) (inputHeight * channels);
const long outputHeightTimesChannel = (long) (outputHeight * channels);
const long windowSize = (long) (windowWidth * windowHeight);
// IN_ELEM_ROWPOS(channel, row, col) = (channel + (row + col * inputHeight) * channels)
// IN_ELEM_COLPOS = sample
// OUT_ELEM_ROWPOS(channel, wrow, wcol) = (channel + (wrow + wcol * outputHeight) * channels)
// OUT_ELEM_COLPOS = sample
#pragma omp parallel for
for (long sample = 0; sample < batchSize; sample++)
{
for (long inputIndexWithinSample = 0; inputIndexWithinSample < inputSizePerSample; inputIndexWithinSample++)
{
const long y = inputIndexWithinSample / inputHeightTimesChannel; // col in input
const long nXC = inputIndexWithinSample % inputHeightTimesChannel; // channel + row*chanels
const long x = nXC / (long) channels; // row in input
const long c = nXC % (long) channels; // channel
long startOutX = (long) max((ElemType)0, ceil((x - (ElemType) windowHeight + 1) / (ElemType) verticalSubsample)); // inclusive start
long endOutX = (long) ((x / verticalSubsample < outputHeight - 1) ? x / (long) verticalSubsample : outputHeight - 1); // inclusive end
long startOutY = (long) max((ElemType)0, ceil((y - (ElemType) windowWidth + 1) / (ElemType) horizontalSubsample)); // inclusive start
long endOutY = (long) ((y / horizontalSubsample < outputWidth - 1) ? y / horizontalSubsample : outputWidth - 1); // inclusive end
for (long outY = startOutY; outY <= endOutY; outY++)
{
for (long outX = startOutX; outX <= endOutX; outX++)
{
long outputIndex = outY * outputHeightTimesChannel + outX * (long) channels + c;
(*this)(inputIndexWithinSample, sample) += outputGradientBatch(outputIndex, sample) / windowSize;
}
}
}
}
return *this;
}
#pragma endregion Other Helper Functions
template <class ElemType>
void CPUMatrix<ElemType>::ConvolutionForward(const CPUMatrix<ElemType>& kernel, const CPUMatrix<int>& mpRowCol, const CPUMatrix<int>& mpRowIwht,
const CPUMatrix<int>& mpRowRun, const CPUMatrix<int>& runs, CPUMatrix<ElemType>& output) const
{
#pragma omp parallel for
for (int64_t sample = 0; sample < (int64_t)output.GetNumCols(); sample++)
{
for (size_t row = 0; row < output.GetNumRows(); row++)
{
int colBase = mpRowCol(row, 0);
int ivBase = mpRowIwht(row, 0);
assert(0 <= colBase && colBase < GetNumRows());
ElemType sum = 0;
int i0 = mpRowRun(row, 0);
int skip = runs(i0++, 0);
int size = runs(i0++, 0);
int imask = i0 + size;
for (int i = 0; i < size; i++)
{
if (runs(imask + i, 0) == 0)
continue;
int dcol = runs(i0 + i, 0);
assert(0 <= colBase + dcol && colBase + dcol < GetNumRows());
sum += kernel.Data()[ivBase + skip + i] * (*this)(colBase + dcol, sample);
}
output(row, sample) = sum;
}
}
}
template <class ElemType>
void CPUMatrix<ElemType>::ConvolutionBackwardData(const CPUMatrix<ElemType>& kernel, const CPUMatrix<int>& mpRowCol, const CPUMatrix<int>& mpRowIwht,
const CPUMatrix<int>& mpRowRun, const CPUMatrix<int>& runs, CPUMatrix<ElemType>& grad) const
{
#pragma omp parallel for
for (int64_t sample = 0; sample < (int64_t)GetNumCols(); sample++)
{
for (size_t row = 0; row < GetNumRows(); row++)
{
int colBase = mpRowCol(row, 0);
int ivBase = mpRowIwht(row, 0);
assert(0 <= colBase && colBase < grad.GetNumRows());
ElemType curGrad = (*this)(row, sample);
int i0 = mpRowRun(row, 0);
int skip = runs(i0++, 0);
int size = runs(i0++, 0);
int imask = i0 + size;
for (int i = 0; i < size; i++)
{
if (runs(imask + i, 0) == 0)
continue;
int dcol = runs(i0 + i, 0);
assert(0 <= colBase + dcol && colBase + dcol < grad.GetNumRows());
grad(colBase + dcol, sample) += curGrad * kernel.Data()[ivBase + skip + i];
}
}
}
}
template <class ElemType>
void CPUMatrix<ElemType>::ConvolutionBackwardKernel(const CPUMatrix<ElemType>& in, const CPUMatrix<int>& mpRowCol, const CPUMatrix<int>& mpRowIwht,
const CPUMatrix<int>& mpRowRun, const CPUMatrix<int>& runs, CPUMatrix<ElemType>& kernelGrad) const
{
// Do NOT parallelize these loops!
for (size_t sample = 0; sample < GetNumCols(); sample++)
{
for (size_t row = 0; row < GetNumRows(); row++)
{
int colBase = mpRowCol(row, 0);
int ivBase = mpRowIwht(row, 0);
assert(0 <= colBase && colBase < in.GetNumRows());
ElemType curGrad = (*this)(row, sample);
int i0 = mpRowRun(row, 0);
int skip = runs(i0++, 0);
int size = runs(i0++, 0);
int imask = i0 + size;
for (int i = 0; i < size; i++)
{
if (runs(imask + i, 0) == 0)
continue;
int dcol = runs(i0 + i, 0);
assert(0 <= colBase + dcol && colBase + dcol < in.GetNumRows());
kernelGrad.Data()[ivBase + skip + i] += curGrad * in(colBase + dcol, sample);
}
}
}
}
template <class ElemType>
void CPUMatrix<ElemType>::UnrollConvolutionInput(size_t unrollCols, size_t mapOutSize, const CPUMatrix<int>& mpRowCol,
const CPUMatrix<int>& mpRowRun, const CPUMatrix<int>& runs, CPUMatrix<ElemType>& output) const
{
size_t batchSize = GetNumCols();
#pragma omp parallel for
for (int64_t sample = 0; sample < (int64_t)batchSize; sample++)
{
for (size_t row = 0; row < mapOutSize; row++)
{
int colBase = mpRowCol(row, 0);
assert(0 <= colBase && colBase < GetNumRows());
int i0 = mpRowRun(row, 0);
int skip = runs(i0++, 0);
int size = runs(i0++, 0);
int imask = i0 + size;
for (int i = 0; i < size; i++)
{
if (runs(imask + i, 0) == 0)
continue;
int dcol = runs(i0 + i, 0);
assert(0 <= colBase + dcol && colBase + dcol < GetNumRows());
output.Data()[(row * batchSize + sample) * unrollCols + skip + i] = (*this)(colBase + dcol, sample);
}
}
}
}
template <class ElemType>
void CPUMatrix<ElemType>::UnrollConvolutionOutput(size_t unrollCols, size_t mapInCount, size_t mapOutCount, const CPUMatrix<int>& mpRowCol,
const CPUMatrix<int>& mpRowRun, const CPUMatrix<int>& runs, CPUMatrix<ElemType>& output) const
{
if (mpRowCol.GetNumRows() % mapOutCount != 0)
InvalidArgument("The number of rows in mpRowCol must be multiple of mapOutCount.");
size_t mapOutSize = mpRowCol.GetNumRows() / mapOutCount;
size_t batchSize = GetNumCols();
size_t kernelSize = runs(1, 0);
if (kernelSize % mapInCount != 0)
InvalidArgument("kernelSize must be multiple of mapInCount.");
size_t kernelMapSize = kernelSize / mapInCount;
#pragma omp parallel for
for (int64_t sample = 0; sample < (int64_t)GetNumCols(); sample++)
{
for (size_t row = 0; row < mapOutSize; row++)
{
int colBase = mpRowCol(row, 0);
int i0 = mpRowRun(row, 0);
int skip = runs(i0++, 0);
int size = runs(i0++, 0);
int imask = i0 + size;
for (int i = 0; i < std::min(size, (int)kernelMapSize); i++)
{
if (runs(imask + i, 0) == 0)
continue;
int dcol = runs(i0 + i, 0);
size_t isrc = row;
size_t idst = ((colBase + dcol) * batchSize + sample) * unrollCols + ((skip + i) % kernelMapSize) * mapOutCount;
for (size_t outMap = 0; outMap < mapOutCount; outMap++, isrc += mapOutSize)
{
assert(isrc < GetNumElements());
assert(idst + outMap < output.GetNumElements());
output.Data()[idst + outMap] = (*this)(isrc, sample);
}
}
}
}
}
template <class ElemType>
void CPUMatrix<ElemType>::UnrollConvolutionInputForKernelBackprop(size_t mapOutSize, const CPUMatrix<int>& mpRowCol,
const CPUMatrix<int>& mpRowRun, const CPUMatrix<int>& runs, CPUMatrix<ElemType>& output) const
{
size_t batchSize = GetNumCols();
size_t unrollCols = mapOutSize * batchSize;
#pragma omp parallel for
for (int64_t sample = 0; sample < (int64_t)batchSize; sample++)
{
for (size_t row = 0; row < mapOutSize; row++)
{
int colBase = mpRowCol(row, 0);
assert(0 <= colBase && colBase < GetNumRows());
int i0 = mpRowRun(row, 0);
int skip = runs(i0++, 0);
int size = runs(i0++, 0);
int imask = i0 + size;
for (int i = 0; i < size; i++)
{
if (runs(imask + i, 0) == 0)
continue;
int dcol = runs(i0 + i, 0);
assert(0 <= colBase + dcol && colBase + dcol < GetNumRows());
size_t idst = (skip + i) * unrollCols + row * batchSize + sample;
assert(idst < output.GetNumElements());
output.Data()[idst] = (*this)(colBase + dcol, sample);
}
}
}
}
template <class ElemType>
void CPUMatrix<ElemType>::MaxPoolingForward(const CPUMatrix<int>& mpRowCol, const CPUMatrix<int>& mpRowIndices, const CPUMatrix<int>& indices, CPUMatrix<ElemType>& output) const
{
#pragma omp parallel for
for (int64_t sample = 0; sample < (int64_t)output.GetNumCols(); sample++)
{
for (size_t row = 0; row < output.GetNumRows(); row++)
{
int colBase = mpRowCol(row, 0);
assert(0 <= colBase && colBase < GetNumRows());
assert(std::numeric_limits<ElemType>::has_infinity);
ElemType res = -std::numeric_limits<ElemType>::infinity();
int i0 = mpRowIndices(row, 0);
int size = indices(i0++, 0);
assert(size > 0);
for (int i = 0; i < size; i++)
{
int dcol = indices(i0 + i, 0);
assert(0 <= colBase + dcol && colBase + dcol < GetNumRows());
res = std::max(res, (*this)(colBase + dcol, sample));
}
output(row, sample) = res;
}
}
}
template <class ElemType>
void CPUMatrix<ElemType>::MaxPoolingBackward(const CPUMatrix<ElemType>& out, const CPUMatrix<ElemType>& in,
const CPUMatrix<int>& mpRowCol, const CPUMatrix<int>& mpRowIndices, const CPUMatrix<int>& indices,
CPUMatrix<ElemType>& grad) const
{
#pragma omp parallel for
for (int64_t sample = 0; sample < (int64_t)GetNumCols(); sample++)
{
for (size_t row = 0; row < GetNumRows(); row++)
{
int colBase = mpRowCol(row, 0);
assert(0 <= colBase && colBase < grad.GetNumRows());
int i0 = mpRowIndices(row, 0);
int size = indices(i0++, 0);
assert(size > 0);
ElemType g = (*this)(row, sample);
ElemType m = out(row, sample);
for (int i = 0; i < size; i++)
{
int dcol = indices(i0 + i, 0);
assert(0 <= colBase + dcol && colBase + dcol < grad.GetNumRows());
if (in(colBase + dcol, sample) >= m)
{
#pragma omp atomic
grad(colBase + dcol, sample) += g;
break;
}
}
}
}
}
// For each image, for each ROI, this function treats that ROI as an image
// and does max pooling so that it has output size pooledHeight x pooledWidth.
// It loops over each location in the output tensor, computes which ROI
// and image should populate that location, computes the subset of the image
// corresponding to the ROI and which pixels in that subset should go into the
// output location, then takes the max value over that window.
// src: Images [W x H x C x N]
// roiData: ROIs [4 x numROIs x N],
// dst: Pooled ROIs [PW x PH x C x numROIs x N]
// argmax: max positions [PW x PH x C x numROIs x N]
// where PW = Pooled Width, PH = Pooled Height, C = Channels, N = Batch Size
template <class ElemType>
void CPUMatrix<ElemType>::ROIPoolingForward(const size_t numRois, const size_t numImg, const size_t channels, const size_t width, const size_t height,
const size_t pooledWidth, const size_t pooledHeight, const CPUMatrix<ElemType>& roiData, CPUMatrix<ElemType>& output,
CPUMatrix<ElemType>& argmax) const
{
size_t roiOutputSize = pooledHeight * pooledWidth * channels;
#pragma omp parallel for
for (int imgIdx = 0; imgIdx < numImg; imgIdx++)
{
auto img = ColumnSlice(imgIdx, 1);
auto rois = roiData.ColumnSlice(imgIdx, 1);
#pragma omp parallel for
for (int roiIdx = 0; roiIdx < numRois; roiIdx++)
{
// each ROI is 4 elements: (x, y, w, h).
int base = roiIdx * 4;
// scaled ROI numbers (relative to original image size)
// roi points are doubles that represent location relative to image
ElemType scX = rois(base, (ElemType)0);
ElemType scY = rois(base + (ElemType)1, (ElemType)0);
ElemType scW = rois(base + (ElemType)2, (ElemType)0);
ElemType scH = rois(base + (ElemType)3, (ElemType)0);
// compute actual spatial location of the ROI in our featuremap.
size_t x = (size_t)round(scX * width);
size_t y = (size_t)round(scY * height);
ElemType roiW = (ElemType)max(round(scW * width), (ElemType)1);
ElemType roiH = (ElemType)max(round(scH * height), (ElemType)1);
const ElemType winW = roiW / (ElemType)pooledWidth;
const ElemType winH = roiH / (ElemType)pooledHeight;
// inspired by Ross Girshick fast-rcnn caffe cpu: https://github.com/rbgirshick/fast-rcnn
// loop over spatial locations in output.
#pragma omp parallel for
for (int outw = 0; outw < pooledWidth; outw++)
{
for (int outh = 0; outh < pooledHeight; outh++)
{
// compute the top left corner of the input
// spatial window corresponding to this output unit
size_t hstart = (size_t)floor(outh * winH);
size_t wstart = (size_t)floor(outw * winW);
// compute bottom right corner (not included)
size_t hend = (size_t)ceil((outh + 1) * winH);
size_t wend = (size_t)ceil((outw + 1) * winW);
// offset window based on ROI top left corner.
// these indices are into the input slice.
hstart = min(max(hstart + y, (size_t)0), height);
wstart = min(max(wstart + x, (size_t)0), width);
hend = min(max(hend + y, (size_t)0), height);
wend = min(max(wend + x, (size_t)0), width);
bool isempty = (hend <= hstart) || (wend <= wstart);
for (size_t c = 0; c < channels; c++)
{
// [W x H x C x R x N]; R = ROIs per image
size_t outputIdx = roiIdx * roiOutputSize + outw + outh * pooledWidth + c * pooledHeight * pooledWidth;
size_t maxidx = 0;
ElemType maxval = isempty ? (ElemType)0 : -FLT_MAX;
size_t baseIdx = c * height * width;
for (size_t h = hstart; h < hend; h++)
{
for (size_t w = wstart; w < wend; w++)
{
// stored argmax indices are relative to the current channel.
size_t dataIdx = w + h * width;
if (img(baseIdx + dataIdx, 0) > maxval)
{
maxval = img(baseIdx + dataIdx, 0);
maxidx = dataIdx;
}
}
}
output(outputIdx, imgIdx) = maxval;
argmax(outputIdx, imgIdx) = maxidx;
}
}
}
}
}
}
// This function loops over locations in the input to the ROIPoolingNode (image locations).
// It loops over the ROIs corresponding to that image, seeing which ones could contain the current location
// in their output. For each ROI, it checks the argmax data to see if that ROI indeed chose
// this pixel location as the maximum. If so, it increments the gradient term for the input location.
template <class ElemType>
void CPUMatrix<ElemType>::ROIPoolingBackward(const size_t numRois, const size_t numImg, const size_t channels, const size_t width, const size_t height,
const size_t pooledWidth, const size_t pooledHeight, const CPUMatrix<ElemType>& roiData, CPUMatrix<ElemType>& grad,
CPUMatrix<ElemType>& argmax) const
{
// loop over images in the batch.
#pragma omp parallel for
for (int imgIdx = 0; imgIdx < numImg; imgIdx++)
{
// ROIs for this image. length 4*numRois;
auto rois = roiData.ColumnSlice(imgIdx, 1).Data();
// gradient values for all ROIs from this image. length numRois*pooledHeight*pooledWidth*channels;
auto pooledGrad = ColumnSlice(imgIdx, 1).Data();
auto argmaxCol = argmax.ColumnSlice(imgIdx, 1).Data();
// loop over spatial locations in the image.
#pragma omp parallel for
for (int w = 0; w < width; w++)
{
#pragma omp parallel for
for (int h = 0; h < width; h++)
{
// loop over the ROIs seeing which ones contain this location.
for (int roiN = 0; roiN < numRois; roiN++)
{
// each ROI is 4 elements: (x, y, w, h).
int roiOffset = roiN * 4;
// ROI data is relative to original image size
size_t roiStartW = (size_t)round(rois[roiOffset + 0] * width);
size_t roiStartH = (size_t)round(rois[roiOffset + 1] * height);
size_t roiWidth = max((size_t)round(rois[roiOffset + 2] * width), (size_t)1);
size_t roiHeight = max((size_t)round(rois[roiOffset + 3] * height), (size_t)1);
// skip this ROI if it doesn't contain the current input location.
const bool inROI = (w >= roiStartW && w < roiStartW + roiWidth &&
h >= roiStartH && h < roiStartH + roiHeight);
if (!inROI)
continue;
ElemType winH = (ElemType)roiHeight / (ElemType)pooledHeight;
ElemType winW = (ElemType)roiWidth / (ElemType)pooledWidth;
// what pooled nodes in the output for this ROI could have pooled this input location?
size_t phstart = (size_t)((h - roiStartH) / winH);
size_t pwstart = (size_t)((w - roiStartW) / winW);
size_t phend = (size_t)(ceil((h - roiStartH + 1) / winH));
size_t pwend = (size_t)(ceil((w - roiStartW + 1) / winW));
phstart = min(max(phstart, (size_t)0), pooledHeight);
phend = min(max(phend, (size_t)0), pooledHeight);
pwstart = min(max(pwstart, (size_t)0), pooledWidth);
pwend = min(max(pwend, (size_t)0), pooledWidth);
for (size_t c = 0; c < channels; c++)
{
ElemType gradient = 0;
// [W x H x C x N]
size_t index = w + h*width + c*height*width;
// go right up to channel c of the current ROI.
size_t offset = (roiN * channels + c) * pooledWidth * pooledHeight;
const ElemType* offsetPoolGrad = pooledGrad + offset;
const ElemType* offsetArgmax = argmaxCol + offset;
for (size_t ph = phstart; ph < phend; ph++)
{
for (size_t pw = pwstart; pw < pwend; pw++)
{
if ((size_t)offsetArgmax[ph * pooledWidth + pw] == (w + h * width))
gradient += offsetPoolGrad[ph * pooledWidth + pw];
}
}
grad(index, imgIdx) = gradient;
}
}
}
}
}
}
template <class ElemType>
void CPUMatrix<ElemType>::MaxUnpooling(const CPUMatrix<int>& mpRowCol, const CPUMatrix<int>& mpRowIndices,
const CPUMatrix<int>& indices, const CPUMatrix<ElemType>& poolInput,
CPUMatrix<ElemType>& input) const
{
#pragma omp parallel for
for (int64_t sample = 0; sample < (int64_t)GetNumCols(); sample++)
{
for (size_t row = 0; row < GetNumRows(); row++)
{
int colBase = mpRowCol(row, 0);
assert(0 <= colBase && colBase < input.GetNumRows());
int i0 = mpRowIndices(row, 0);
int size = indices(i0++, 0);
assert(size > 0);
ElemType curMax = poolInput(colBase + indices(i0, 0), sample);
ElemType prevMax = curMax;
int imax = 0;
for (int i = 1; i < size; i++)
{
int dcol = indices(i0 + i, 0);
assert(0 <= colBase + dcol && colBase + dcol < poolInput.GetNumRows());
curMax = std::max(curMax, poolInput(colBase + dcol, sample));
if (curMax > prevMax)
{
prevMax = curMax;
imax = i;
}
}
int dcol = indices(i0 + imax, 0);
assert(0 <= colBase + dcol && colBase + dcol < input.GetNumRows());
input(colBase + dcol, sample) = (*this)(row, sample);
//int i = (int)poolIn(row, sample);
//assert(0 <= i && i < size);
//int dcol = indices(i0 + i, 0);
//assert(0 <= colBase + dcol && colBase + dcol < input.GetNumRows());
//input(colBase + dcol, sample) = (*this)(row, sample);
}
}
}
template <class ElemType>
void CPUMatrix<ElemType>::AveragePoolingForward(const CPUMatrix<int>& mpRowCol, const CPUMatrix<int>& mpRowIndices, const CPUMatrix<int>& indices, CPUMatrix<ElemType>& output, const bool poolIncludePad) const
{
#pragma omp parallel for
for (int64_t sample = 0; sample < (int64_t)output.GetNumCols(); sample++)
{
for (size_t row = 0; row < output.GetNumRows(); row++)
{
int colBase = mpRowCol(row, 0);
assert(0 <= colBase && colBase < GetNumRows());
ElemType sum = 0;
int i0 = mpRowIndices(row, 0);
int size = indices(i0++, 0);
assert(size > 0);
for (int i = 0; i < size; i++)
{
int dcol = indices(i0 + i, 0);
assert(0 <= colBase + dcol && colBase + dcol < GetNumRows());
sum += (*this)(colBase + dcol, sample);
}
// Note that we divide by size which is the number of actual elements (does not include padding).
// if poolIncludePad == true, use avg_pool_include_pad
if (poolIncludePad)
size = indices(0, 0);
output(row, sample) = sum / size;
}
}
}
template <class ElemType>
void CPUMatrix<ElemType>::AveragePoolingBackward(const CPUMatrix<int>& mpRowCol, const CPUMatrix<int>& mpRowIndices, const CPUMatrix<int>& indices, CPUMatrix<ElemType>& grad, const bool poolIncludePad) const
{
#pragma omp parallel for
for (int64_t sample = 0; sample < (int64_t)GetNumCols(); sample++)
{
for (size_t row = 0; row < GetNumRows(); row++)
{
int colBase = mpRowCol(row, 0);
assert(0 <= colBase && colBase < grad.GetNumRows());
int i0 = mpRowIndices(row, 0);
int size = indices(i0++, 0);
int tmp = size;
if (poolIncludePad)
size = indices(0, 0);
assert(size > 0);
ElemType g = (*this)(row, sample) / size;
size = tmp;
for (int i = 0; i < size; i++)
{
int dcol = indices(i0 + i, 0);
assert(0 <= colBase + dcol && colBase + dcol < grad.GetNumRows());
#pragma omp atomic
grad(colBase + dcol, sample) += g;
}
}
}
}
template <class ElemType>
void CPUMatrix<ElemType>::BatchNormalizationForward(const CPUMatrix<ElemType>& scale, const CPUMatrix<ElemType>& bias, bool inferenceOnly, double expAvgFactor, double blendFactor,
CPUMatrix<ElemType>& runMean, CPUMatrix<ElemType>& runVariance, CPUMatrix<ElemType>& out, double epsilon,
CPUMatrix<ElemType>& saveMean, CPUMatrix<ElemType>& saveInvStdDev) const
{
if (GetNumRows() % scale.GetNumRows() != 0)
LogicError("The number of rows of this matrx must be multiple of the number of rows of the scale matrix.");
if (!inferenceOnly || expAvgFactor != 0 || blendFactor != 1)
RuntimeError("Batch normalization training on CPU is not yet implemented.");
saveMean.Resize(0, 0); // only doing inference: these two are not produced
saveInvStdDev.Resize(0, 0);
bool spatial = GetNumRows() != scale.GetNumRows();
if (spatial)
{
size_t spatialSize = GetNumRows() / scale.GetNumRows();
#pragma omp parallel for
for (long icol = 0; icol < out.GetNumCols(); icol++)
{
for (long irow = 0; irow < out.GetNumRows(); irow++)
{
size_t imap = irow / spatialSize;
ElemType stdDev = sqrt(runVariance(imap, 0) + epsilon);
out(irow, icol) = scale(imap, 0) * ((*this)(irow, icol) - runMean(imap, 0)) / stdDev + bias(imap, 0);
}
}
}
else
{
#pragma omp parallel for
for (long icol = 0; icol < out.GetNumCols(); icol++)
{
for (long irow = 0; irow < out.GetNumRows(); irow++)
{
ElemType stdDev = sqrt(runVariance(irow, 0) + epsilon);
out(irow, icol) = scale(irow, 0) * ((*this)(irow, icol) - runMean(irow, 0)) / stdDev + bias(irow, 0);
}
}
}
}
template <class ElemType>
void CPUMatrix<ElemType>::BatchNormalizationBackward(const CPUMatrix<ElemType>& in, CPUMatrix<ElemType>& grad, const CPUMatrix<ElemType>& scale, double blendFactor,
const CPUMatrix<ElemType>& saveMean, const CPUMatrix<ElemType>& saveInvStdDev,
CPUMatrix<ElemType>& scaleGrad, CPUMatrix<ElemType>& biasGrad) const
{
UNUSED(in); UNUSED(grad); UNUSED(scale); UNUSED(blendFactor), UNUSED(saveMean); UNUSED(saveInvStdDev); UNUSED(scaleGrad); UNUSED(biasGrad);
RuntimeError("Batch normalization training on CPU is not yet implemented.");
}
#pragma region Static BLAS Functions
/// <summary>Matrix-matrix multiply with col-major matrices (a and b may be transposed): c = alpha * op(a) * op(b) + beta*c</summary>
/// <param name="alpha">Scalar</param>
/// <param name="a">Input matrix</param>
/// <param name="transposeA">Whether matrix a is transposed</param>
/// <param name="b">Input matrix</param>
/// <param name="transposeB">Whether matrix b is transposed</param>
/// <param name="beta">Scalar</param>
/// <param name="c">Resulting matrix, user is responsible for allocating this</param>
template <class ElemType>
void CPUMatrix<ElemType>::MultiplyAndWeightedAdd(ElemType alpha, const CPUMatrix<ElemType>& a, const bool transposeA, const CPUMatrix<ElemType>& b, const bool transposeB,
ElemType beta, CPUMatrix<ElemType>& c, shared_ptr<QuantizedMultiplier<ElemType>> pQuantizedMultiplier)
{
if (a.IsEmpty() || b.IsEmpty())
return;
int m, n, k, l;
int lda, ldb, ldc;
CBLAS_TRANSPOSE mklTransA;
CBLAS_TRANSPOSE mklTransB;
if (transposeA)
{
m = (int) a.GetNumCols();
k = (int) a.GetNumRows();
lda = k;
mklTransA = CBLAS_TRANSPOSE::CblasTrans;
}
else
{
m = (int) a.GetNumRows();
k = (int) a.GetNumCols();
lda = m;
mklTransA = CBLAS_TRANSPOSE::CblasNoTrans;
}
if (transposeB)
{
l = (int) b.GetNumCols();
n = (int) b.GetNumRows();
ldb = n;
mklTransB = CBLAS_TRANSPOSE::CblasTrans;
}
else
{
l = (int) b.GetNumRows();
n = (int) b.GetNumCols();
ldb = l;
mklTransB = CBLAS_TRANSPOSE::CblasNoTrans;
}
assert(m > 0 && k > 0 && l > 0 && n > 0); // converting from size_t to int may cause overflow
if (k != l)
InvalidArgument("CPUMatrix<ElemType>::MultiplyAndWeightedAdd : The inner dimensions of a and b must match.");
if (beta == 0)
c.RequireSize(m, n);
else
c.VerifySize(m, n); // Can't resize if beta != 0
ldc = (int) c.GetNumRows();
if (pQuantizedMultiplier == nullptr)
{
if (sizeof(ElemType) == sizeof(double))
{
cblas_dgemm((CBLAS_ORDER) (int)MatrixOrder::ColMajor, mklTransA, mklTransB, m, n, k, alpha, reinterpret_cast<double*>(a.Data()), lda, reinterpret_cast<double*>(b.Data()), ldb, beta, reinterpret_cast<double*>(c.Data()), ldc);
}
else
{
#pragma warning(suppress : 4244)
cblas_sgemm((CBLAS_ORDER) (int)MatrixOrder::ColMajor, mklTransA, mklTransB, m, n, k, alpha, reinterpret_cast<float*>(a.Data()), lda, reinterpret_cast<float*>(b.Data()), ldb, beta, reinterpret_cast<float*>(c.Data()), ldc);
}
}
else
{
// TODO: support transpose product
if (mklTransA == CBLAS_TRANSPOSE::CblasTrans || mklTransB == CBLAS_TRANSPOSE::CblasTrans)
LogicError("Quantized multiplier currently doesn't support transpose.");
pQuantizedMultiplier->Multiply(m, n, k, a.Data(), b.Data(), c.Data());
}
}
template <class ElemType>
void CPUMatrix<ElemType>::Multiply1x1AndWeightedAdd(ElemType alpha, const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b,
ElemType beta, CPUMatrix<ElemType>& c)
{
if (a.GetNumElements() != 1)
InvalidArgument("the argument a must be a scalar"); // a is a scalar
ElemType f = alpha * a.Get00Element();
if (beta == 0) // don't even read the memory if beta is 0
#pragma omp parallel for
foreach_coord (i, j, c)
c(i, j) = b(i, j) * f;
else
#pragma omp parallel for
foreach_coord (i, j, c)
c(i, j) = b(i, j) * f + c(i, j) * beta;
}
template <class ElemType>
void CPUMatrix<ElemType>::ColumnwiseScaleAndWeightedAdd(ElemType alpha, const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& v, ElemType beta, CPUMatrix<ElemType>& c)
{
if (v.GetNumRows() != 1 && v.GetNumCols() != 1)
InvalidArgument("the argument v must be a vector"); // v is a vector
if (beta == 0)
c.RequireSize(a.GetNumRows(), a.GetNumCols());
else
c.VerifySize(a.GetNumRows(), a.GetNumCols()); // Can't resize if beta != 0
const ElemType* vd = v.Data();
if (beta == 0) // don't even read the memory if beta is 0
#pragma omp parallel for
foreach_coord(i, j, c)
c(i, j) = alpha * a(i, j) * vd[j];
else
#pragma omp parallel for
foreach_coord(i, j, c)
c(i, j) = alpha * a(i, j) * vd[j] + c(i, j) * beta;
}
/* compute singular value decomposition as
A = U*SIGMA*VT
W is used as temp working memory
*/
template <class ElemType>
void CPUMatrix<ElemType>::SVD(const CPUMatrix<ElemType>& A, CPUMatrix<ElemType>& SIGMA, CPUMatrix<ElemType>& U, CPUMatrix<ElemType>& VT, CPUMatrix<ElemType>& W)
{
if (A.IsEmpty())
LogicError("SVD: input matrix is empty.");
int info;
int m, n, lda, ldu, ldvt;
m = (int) A.GetNumRows();
n = (int) A.GetNumCols();
W.GetNumRows(); // W is used as temp working memory
lda = m;
ldu = m;
ldvt = n;
U.RequireSize(m, m);
SIGMA.RequireSize(std::min(m, n), 1);
VT.RequireSize(n, n);
if (sizeof(ElemType) == sizeof(double))
{
#ifdef USE_MKL
double wkopt;
int lwork = -1;
dgesvd("All", "All", &m, &n, reinterpret_cast<double*>(A.Data()), &lda, reinterpret_cast<double*>(SIGMA.Data()), reinterpret_cast<double*>(U.Data()), &ldu, reinterpret_cast<double*>(VT.Data()), &ldvt, &wkopt, &lwork, &info);
lwork = (int) wkopt;
W.RequireSize(lwork, 1);
dgesvd("All", "All", &m, &n, reinterpret_cast<double*>(A.Data()), &lda, reinterpret_cast<double*>(SIGMA.Data()), reinterpret_cast<double*>(U.Data()), &ldu, reinterpret_cast<double*>(VT.Data()), &ldvt, reinterpret_cast<double*>(W.Data()), &lwork, &info);
#else
std::vector<double> superb(std::max(std::min(m, n) - 1, 1));
info = LAPACKE_dgesvd((int) MatrixOrder::ColMajor, 'A', 'A', (int) m, (int) n, reinterpret_cast<double*>(A.Data()), (int) lda, reinterpret_cast<double*>(SIGMA.Data()),
reinterpret_cast<double*>(U.Data()), (int) ldu, reinterpret_cast<double*>(VT.Data()), (int) ldvt, &superb[0]);
#endif
}
else
{
#ifdef USE_MKL
float wkopt;
int lwork = -1;
sgesvd("All", "All", &m, &n, reinterpret_cast<float*>(A.Data()), &lda, reinterpret_cast<float*>(SIGMA.Data()), reinterpret_cast<float*>(U.Data()), &ldu, reinterpret_cast<float*>(VT.Data()), &ldvt, &wkopt, &lwork, &info);
lwork = (int) wkopt;
W.RequireSize(lwork, 1);
sgesvd("All", "All", &m, &n, reinterpret_cast<float*>(A.Data()), &lda, reinterpret_cast<float*>(SIGMA.Data()), reinterpret_cast<float*>(U.Data()), &ldu, reinterpret_cast<float*>(VT.Data()), &ldvt, reinterpret_cast<float*>(W.Data()), &lwork, &info);
#else
std::vector<float> superb(std::max(std::min(m, n) - 1, 1));
info = LAPACKE_sgesvd((int) MatrixOrder::ColMajor, 'A', 'A', (int) m, (int) n, reinterpret_cast<float*>(A.Data()), (int) lda, reinterpret_cast<float*>(SIGMA.Data()),
reinterpret_cast<float*>(U.Data()), (int) ldu, reinterpret_cast<float*>(VT.Data()), (int) ldvt, &superb[0]);
#endif
}
if (info > 0)
{
RuntimeError("The algorithm computing SVD failed to converge.\n");
}
}
/// <summary>Matrix-matrix multiply with col-major matrices (a and b may be transposed): c = op(a) * op(b) + c</summary>
/// <param name="a">Input matrix</param>
/// <param name="transposeA">Whether matrix a is transposed</param>
/// <param name="b">Input matrix</param>
/// <param name="transposeB">Whether matrix b is transposed</param>
/// <param name="c">Resulting matrix, user is responsible for allocating this</param>
template <class ElemType>
void CPUMatrix<ElemType>::MultiplyAndAdd(const CPUMatrix<ElemType>& a, const bool transposeA, const CPUMatrix<ElemType>& b, const bool transposeB,
CPUMatrix<ElemType>& c)
{
return CPUMatrix<ElemType>::MultiplyAndWeightedAdd(1.0, a, transposeA, b, transposeB, 1.0, c);
}
template <class ElemType>
void CPUMatrix<ElemType>::AssignSoftmaxSum(const CPUMatrix<ElemType>& softmax, CPUMatrix<ElemType>& c)
{
ElemType log_likelihood = 0.0;
size_t batch_size = GetNumCols();
#pragma omp parallel for reduction(+ : log_likelihood)
for (int instance_id = 0; instance_id < batch_size; instance_id++)
{
int sample = (int) (*this)(0, instance_id);
log_likelihood += softmax(instance_id, sample);
}
c(0, 0) = -log_likelihood;
}
template <class ElemType>
void CPUMatrix<ElemType>::AssignNCEUnnormalizedEval(const CPUMatrix<ElemType>& a,
const CPUMatrix<ElemType>& b, const CPUMatrix<ElemType>& bias, CPUMatrix<ElemType>& c)
//this: samples+probs
// a: hidden
// b: embedding
// tmp: softmax
// c: loglikelihood
{
ElemType log_likelihood = 0.0;
size_t batch_size = GetNumCols();
#pragma omp parallel for reduction(+ : log_likelihood)
for (int instance_id = 0; instance_id < batch_size; instance_id++)
{
int sample = -(int) (*this)(0, instance_id);
ElemType score = bias(sample, 0);
for (int dim = 0; dim < b.GetNumRows(); dim++)
score += b(dim, sample) * a(dim, instance_id);
log_likelihood += score;
}
c(0, 0) = -log_likelihood;
}
//samples+prob gradient hidden embedding embedding/hidden
//a.m_CPUMatrix->AssignNCEDerivative(*tmp.m_CPUMatrix, *a.m_CPUMatrix, *b.m_CPUMatrix, inputIndex, *c.m_CPUMatrix);
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignNCEDerivative(const CPUMatrix<ElemType>& tmp, const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, size_t inputIndex, CPUMatrix<ElemType>& c)
{
size_t sample_size = GetNumRows() / 2;
size_t batch_size = GetNumCols();
if (inputIndex == 1)
{
#pragma omp parallel for
for (int instance_id = 0; instance_id < batch_size; instance_id++)
for (int sample_id = 0; sample_id < sample_size; sample_id++)
{
int sample = (int) (*this)(2 * sample_id, instance_id);
for (int dim = 0; dim < b.GetNumRows(); dim++)
c(dim, instance_id) -= b(dim, sample) * tmp(sample_id, instance_id);
}
}
else if (inputIndex == 2)
{
int i_blocks = omp_get_num_threads() * 16;
// Assume only one block in k direction.
// We don't need to explicitly block in the j direction.
#pragma omp parallel for
for (int ib = 0; ib < i_blocks; ib++)
for (int instance_id = 0; instance_id < batch_size; instance_id++)
for (int sample_id = 0; sample_id < sample_size; sample_id++)
{
int sample = (int) (*this)(2 * sample_id, instance_id);
if (sample % i_blocks == ib)
for (int dim = 0; dim < b.GetNumRows(); dim++)
c(dim, sample) -= a(dim, instance_id) * tmp(sample_id, instance_id);
}
}
else if (inputIndex == 3)
{
// Assume only one block in k direction.
// We don't need to explicitly block in the j direction.
for (int instance_id = 0; instance_id < batch_size; instance_id++)
for (int sample_id = 0; sample_id < sample_size; sample_id++)
{
int sample = (int) (*this)(2 * sample_id, instance_id);
c(0, sample) -= tmp(sample_id, instance_id);
}
}
else
InvalidArgument("The argument inputIndex must be 1 or 2 or 3.");
return *this;
}
template <class ElemType>
void CPUMatrix<ElemType>::AssignNoiseContrastiveEstimation(const CPUMatrix<ElemType>& a,
const CPUMatrix<ElemType>& b, const CPUMatrix<ElemType>& bias, CPUMatrix<ElemType>& tmp, CPUMatrix<ElemType>& c)
//this: samples+probs
// a: hidden
// b: embedding
// tmp: softmax
// c: loglikelihood
{
double log_likelihood = 0.0;
size_t sample_size = GetNumRows() / 2;
size_t batch_size = GetNumCols();
size_t num_noise_samples = sample_size - 1;
double log_num_noise_samples = std::log(num_noise_samples);
#pragma omp parallel for reduction(+ : log_likelihood)
for (int instance_id = 0; instance_id < batch_size; instance_id++)
for (int sample_id = 0; sample_id < sample_size; sample_id++)
{
int sample = (int) (*this)(2 * sample_id, instance_id);
double score = bias(0, sample);
for (int dim = 0; dim < b.GetNumRows(); dim++)
score += a(dim, instance_id) * b(dim, sample);
double sample_prob = -(*this)(2 * sample_id + 1, instance_id);
if (sample_id == 0)
sample_prob = -sample_prob;
double score_noise = log_num_noise_samples + sample_prob;
double z = LogAdd(score, score_noise);
double logprob = score - z;
double logprob_noise = score_noise - z;
tmp(sample_id, instance_id) = (ElemType) -std::exp(logprob);
if (sample_id == 0)
tmp(sample_id, instance_id) += 1;
log_likelihood += sample_id == 0 ? logprob : logprob_noise;
}
c(0, 0) = (ElemType) -log_likelihood;
}
/// <summary>Matrix-matrix multiply with col-major matrices (a and b may be transposed): c = op(a) * op(b)</summary>
/// <param name="a">Input matrix</param>
/// <param name="transposeA">Whether matrix a is transposed</param>
/// <param name="b">Input matrix</param>
/// <param name="transposeB">Whether matrix b is transposed</param>
/// <param name="c">Resulting matrix, user is responsible for allocating this</param>
template <class ElemType>
void CPUMatrix<ElemType>::Multiply(const CPUMatrix<ElemType>& a, const bool transposeA, const CPUMatrix<ElemType>& b, const bool transposeB,
CPUMatrix<ElemType>& c)
{
return CPUMatrix<ElemType>::MultiplyAndWeightedAdd(1.0, a, transposeA, b, transposeB, 0.0, c);
}
/// <summary>Matrix-matrix multiply with col-major matrices (a and b are not transposed): c = a * b</summary>
/// <param name="a">Input matrix</param>
/// <param name="b">Input matrix</param>
/// <param name="c">Resulting matrix, user is responsible for allocating this</param>
template <class ElemType>
void CPUMatrix<ElemType>::Multiply(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, CPUMatrix<ElemType>& c)
{
return CPUMatrix<ElemType>::MultiplyAndWeightedAdd(1.0, a, false, b, false, 0.0, c);
}
/// <summary>Matrix-scalar multiply with col-major matrices: c = alpha * a + c</summary>
/// if a is a column vector, add to all columns of c
/// if a is a row vector, add to all rows of c
/// if a is a scalar, add to all rows of c
/// <param name="alpha">Scalar</param>
/// <param name="a">Input matrix</param>
/// <param name="c">Resulting matrix, user is responsible for allocating this</param>
template <class ElemType>
void CPUMatrix<ElemType>::ScaleAndAdd(ElemType alpha, const CPUMatrix<ElemType>& a, CPUMatrix<ElemType>& c)
{
if (a.IsEmpty() || c.IsEmpty())
LogicError("ScaleAndAdd: one of the input matrices is empty.");
if (a.GetNumRows() != 1 && a.GetNumCols() != 1) // a is not a col or row vector
{
const int m = (int) a.GetNumRows();
const int n = (int) a.GetNumCols();
const int len = m * n;
const int incx = 1;
const int incy = 1;
assert(m > 0 && n > 0 && len > 0); // converting from size_t to int may cause overflow
if ((int) c.GetNumRows() != m || (int) c.GetNumCols() != n)
InvalidArgument("Dimension of matrix c does not match dimension of matrix a.");
if (sizeof(ElemType) == sizeof(double))
{
cblas_daxpy(len, alpha, reinterpret_cast<double*>(a.Data()), incx, reinterpret_cast<double*>(c.Data()), incy);
}
else
{
#pragma warning(suppress : 4244)
cblas_saxpy(len, alpha, reinterpret_cast<float*>(a.Data()), incx, reinterpret_cast<float*>(c.Data()), incy);
}
}
else if (a.GetNumElements() == 1) // scalar, add to all elements
{
ElemType v = alpha * a(0, 0);
long m = (long) c.GetNumRows(), n = (long) c.GetNumCols();
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
c(i, j) += v;
c(i + 1, j) += v;
c(i + 2, j) += v;
c(i + 3, j) += v;
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
c(i, j) += v;
}
}
}
else if (a.GetNumCols() == 1) // col vector, add it to all columns
{
int m = (int) c.GetNumRows();
if (m != (int) a.GetNumRows())
InvalidArgument("To add column vector, rows should match.");
ElemType* aBufPtr = a.Data();
ElemType* cBufPtr = c.Data();
if (sizeof(ElemType) == sizeof(double))
{
#pragma omp parallel for
foreach_column (j, c)
{
cblas_daxpy(m, alpha, reinterpret_cast<double*>(aBufPtr), 1, reinterpret_cast<double*>(cBufPtr + c.LocateColumn(j)), 1);
}
}
else
{
#pragma omp parallel for
foreach_column (j, c)
{
#pragma warning(suppress : 4244)
cblas_saxpy(m, alpha, reinterpret_cast<float*>(aBufPtr), 1, reinterpret_cast<float*>(cBufPtr + c.LocateColumn(j)), 1);
}
}
}
else // row vector, add it to all rows
{
int m = (int) c.GetNumRows();
int n = (int) c.GetNumCols();
if (n != (int) a.GetNumCols())
InvalidArgument("To add row vector, cols should match.");
ElemType* aBufPtr = a.Data();
ElemType* cBufPtr = c.Data();
if (sizeof(ElemType) == sizeof(double))
{
#pragma omp parallel for
foreach_row (i, c)
{
cblas_daxpy(n, alpha, reinterpret_cast<double*>(aBufPtr), 1, reinterpret_cast<double*>(cBufPtr + i), m);
}
}
else
{
#pragma omp parallel for
foreach_row (i, c)
{
#pragma warning(suppress : 4244)
cblas_saxpy(n, alpha, reinterpret_cast<float*>(aBufPtr), 1, reinterpret_cast<float*>(cBufPtr + i), m);
}
}
}
}
/// <summary>c += alpha * (a-b)</summary>
/// if a, b, c must have same dim
/// <param name="alpha">Scalar</param>
/// <param name="a">Input matrix</param>
/// <param name="b">Input matrix</param>
/// <param name="c">Resulting matrix, user is responsible for allocating this</param>
template <class ElemType>
void CPUMatrix<ElemType>::AddScaledDifference(const ElemType alpha, const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, CPUMatrix<ElemType>& c)
{
if (!(a.GetNumRows() == b.GetNumRows() && a.GetNumRows() == c.GetNumRows() &&
a.GetNumCols() == b.GetNumCols() && a.GetNumCols() == c.GetNumCols()))
{
InvalidArgument("AddScaledDifference: a, b, and c must have same dimension.");
}
if (a.IsEmpty())
LogicError("AddScaledDifference: Input matrix a is empty.");
ElemType* aBufPtr = a.Data();
ElemType* bBufPtr = b.Data();
ElemType* cBufPtr = c.Data();
long m = (long) c.GetNumElements();
#pragma omp parallel for
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
cBufPtr[i] += alpha * (aBufPtr[i] - bBufPtr[i]);
cBufPtr[i + 1] += alpha * (aBufPtr[i + 1] - bBufPtr[i + 1]);
cBufPtr[i + 2] += alpha * (aBufPtr[i + 2] - bBufPtr[i + 2]);
cBufPtr[i + 3] += alpha * (aBufPtr[i + 3] - bBufPtr[i + 3]);
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
cBufPtr[i] += alpha * (aBufPtr[i] - bBufPtr[i]);
}
}
/// <summary> c = alpha * (a-b)</summary>
/// if a, b, c must have same dim
/// <param name="alpha">Scalar</param>
/// <param name="a">Input matrix</param>
/// <param name="b">Input matrix</param>
/// <param name="c">Resulting matrix, user is responsible for allocating this</param>
template <class ElemType>
void CPUMatrix<ElemType>::AssignScaledDifference(const ElemType alpha, const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, CPUMatrix<ElemType>& c)
{
if (!(a.GetNumRows() == b.GetNumRows() && a.GetNumCols() == b.GetNumCols()))
{
InvalidArgument("AssignScaledDifference: a, b must have same dimension.");
}
if (a.IsEmpty())
LogicError("AssignScaledDifference: Input matrix a is empty.");
if (&c != &a && &c != &b)
c.RequireSize(a.GetNumRows(), a.GetNumCols());
ElemType* aBufPtr = a.Data();
ElemType* bBufPtr = b.Data();
ElemType* cBufPtr = c.Data();
long m = (long) c.GetNumElements();
#pragma omp parallel for
// four-way unrolling
for (long i = 0; i < (m & ~3); i += 4)
{
cBufPtr[i] = alpha * (aBufPtr[i] - bBufPtr[i]);
cBufPtr[i + 1] = alpha * (aBufPtr[i + 1] - bBufPtr[i + 1]);
cBufPtr[i + 2] = alpha * (aBufPtr[i + 2] - bBufPtr[i + 2]);
cBufPtr[i + 3] = alpha * (aBufPtr[i + 3] - bBufPtr[i + 3]);
}
// handle remaining stuffs
for (long i = m & ~3; i < m; i++)
{
cBufPtr[i] = alpha * (aBufPtr[i] - bBufPtr[i]);
}
}
// c[ci,cj] += a[ai,aj]
template <class ElemType>
void CPUMatrix<ElemType>::AddElementToElement(ElemType beta, const CPUMatrix<ElemType>& a, const size_t ai, const size_t aj, CPUMatrix<ElemType>& c, const size_t ci, const size_t cj)
{
if (ai >= a.GetNumRows() || aj >= a.GetNumCols() ||
ci >= c.GetNumRows() || cj >= c.GetNumCols())
InvalidArgument("AddElementToElement: index out of range.");
ElemType us = beta ? beta * c(ci, cj) : 0; // do not multiply if beta is 0, could be a NaN
us += a(ai, aj);
c(ci, cj) = us;
}
////c[ci,cj] += a[ai,aj]
//template<class ElemType>
//void CPUMatrix<ElemType>::AddLogElementToElement(const CPUMatrix<ElemType>& a, const size_t ai, const size_t aj, CPUMatrix<ElemType>& c, const size_t ci, const size_t cj)
//{
// if (ai >= a.GetNumRows() || aj >=a.GetNumCols() ||
// ci >= c.GetNumRows() || cj >=c.GetNumCols())
// InvalidArgument("AddElementToElement: index out of range.");
//
// ElemType v = a(ai,aj);
// c(ci, cj) += ((v < EPS_IN_LOG) ? LOG_OF_EPS_IN_LOG : log(v));
//}
#if 0 // now done as AddElementToElement (beta=0)
// c[ci,cj] = a[ai,aj]
template <class ElemType>
void CPUMatrix<ElemType>::AssignElementToElement(const CPUMatrix<ElemType>& a, const size_t ai, const size_t aj, CPUMatrix<ElemType>& c, const size_t ci, const size_t cj)
{
if (ai >= a.GetNumRows() || aj >= a.GetNumCols() ||
ci >= c.GetNumRows() || cj >= c.GetNumCols())
InvalidArgument("AssignElementToElement: index out of range.");
c(ci, cj) = a(ai, aj);
}
#endif
/// <summary>c += alpha * (a-b)</summary>
/// if a, b, c must have same dim
/// <param name="alpha">1X1 matrix</param>
/// <param name="a">Input matrix</param>
/// <param name="b">Input matrix</param>
/// <param name="c">Resulting matrix, user is responsible for allocating this</param>
template <class ElemType>
void CPUMatrix<ElemType>::AddScaledDifference(const CPUMatrix<ElemType>& alpha, const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, CPUMatrix<ElemType>& c)
{
if (alpha.GetNumElements() != 1)
InvalidArgument("AddScaledDifference: alpha must be a 1X1 matrix.");
AddScaledDifference(alpha(0, 0), a, b, c);
}
/// <summary> c = alpha * (a-b)</summary>
/// if a, b, c must have same dim
/// <param name="alpha">1X1 matrix</param>
/// <param name="a">Input matrix</param>
/// <param name="b">Input matrix</param>
/// <param name="c">Resulting matrix, user is responsible for allocating this</param>
template <class ElemType>
void CPUMatrix<ElemType>::AssignScaledDifference(const CPUMatrix<ElemType>& alpha, const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, CPUMatrix<ElemType>& c)
{
if (alpha.GetNumElements() != 1)
InvalidArgument("AddScaledDifference: alpha must be a 1X1 matrix.");
AssignScaledDifference(alpha(0, 0), a, b, c);
}
/// <summary>Matrix-scalar multiply with col-major matrices: c = alpha * a</summary>
/// <param name="alpha">Scalar</param>
/// <param name="a">Input matrix</param>
/// <param name="c">Resulting matrix, user is responsible for allocating this</param>
template <class ElemType>
/*static*/ void CPUMatrix<ElemType>::Scale(ElemType alpha, const CPUMatrix<ElemType>& a, CPUMatrix<ElemType>& c)
{
if (a.IsEmpty())
LogicError("Scale: Input matrix a is empty.");
const int m = (int) a.GetNumRows();
const int n = (int) a.GetNumCols();
assert(m > 0 && n > 0); // converting from size_t to int may cause overflow
c.RequireSize(m, n);
ElemType* aBufPtr = a.Data();
ElemType* cBufPtr = c.Data();
if (alpha == 0)
{
memset(cBufPtr, 0, sizeof(ElemType) * c.GetNumElements());
return;
}
long size = (long) c.GetNumElements();
#pragma omp parallel for
// four-way unrolling
for (long i = 0; i < (size & ~3); i += 4)
{
cBufPtr[i] = alpha * aBufPtr[i];
cBufPtr[i + 1] = alpha * aBufPtr[i + 1];
cBufPtr[i + 2] = alpha * aBufPtr[i + 2];
cBufPtr[i + 3] = alpha * aBufPtr[i + 3];
}
// remaining elements
for (long i = size & ~3; i < size; i++)
{
cBufPtr[i] = alpha * aBufPtr[i];
}
}
/// <summary>Matrix-scalar multiply with col-major matrices: a = alpha * a</summary>
/// <param name="alpha">Scalar</param>
/// <param name="a">Input matrix</param>
template <class ElemType>
/*static*/ void CPUMatrix<ElemType>::Scale(ElemType alpha, CPUMatrix<ElemType>& a)
{
if (a.IsEmpty())
LogicError("Scale: Input matrix a is empty.");
const int m = (int) a.GetNumRows();
const int n = (int) a.GetNumCols();
const int len = m * n;
const int incx = 1;
assert(m > 0 && n > 0 && len > 0); // converting from size_t to int may cause overflow
if (alpha == 0 && incx == 1)
{
memset(a.Data(), 0, sizeof(ElemType) * len);
}
else if (sizeof(ElemType) == sizeof(double))
{
cblas_dscal(len, alpha, reinterpret_cast<double*>(a.Data()), incx);
}
else
{
#pragma warning(suppress : 4244)
cblas_sscal(len, alpha, reinterpret_cast<float*>(a.Data()), incx);
}
}
/// <summary>Matrix multiply with col-major matrices: a = alpha[1,1] * a</summary>
/// <param name="alpha">1x1 matrix</param>
/// <param name="a">Input matrix</param>
template <class ElemType>
/*static*/ void CPUMatrix<ElemType>::Scale(CPUMatrix<ElemType> alpha, CPUMatrix<ElemType>& a)
{
if (a.IsEmpty())
LogicError("Scale: Input matrix a is empty.");
if (alpha.GetNumElements() != 1)
LogicError("Matrix alpha must be 1x1");
CPUMatrix<ElemType>::Scale(alpha(0, 0), a);
}
template <class ElemType>
void CPUMatrix<ElemType>::InnerProduct(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, CPUMatrix<ElemType>& c, const bool isColWise)
{
if (a.IsEmpty() || b.IsEmpty())
LogicError("InnerProduct: one of the input matrices is empty.");
const int m = (int) a.GetNumRows();
const int n = (int) a.GetNumCols();
const int k = (int) b.GetNumRows();
const int l = (int) b.GetNumCols();
assert(m > 0 && n > 0 && k > 0 && l > 0); // converting from size_t to int may cause overflow
if (m != k || n != l)
InvalidArgument("InnerProduct: Matrices a and b should have same dimension.");
if ((isColWise && m == 1) || !isColWise && n == 1) // in this case it's equivalent to element-wise product
{
c.AssignElementProductOf(a, b);
}
else if (isColWise) // col-wise
{
c.RequireSize(1, n);
ElemType* aBufPtr = a.Data();
ElemType* bBufPtr = b.Data();
if (sizeof(ElemType) == sizeof(double))
{
#pragma omp parallel for
foreach_column (j, c)
{
c(0, j) = (ElemType) cblas_ddot(m, reinterpret_cast<double*>(aBufPtr + a.LocateColumn(j)), 1, reinterpret_cast<double*>(bBufPtr + b.LocateColumn(j)), 1);
}
}
else
{
#pragma omp parallel for
foreach_column (j, c)
{
#pragma warning(suppress : 4244)
c(0, j) = (ElemType) cblas_sdot(m, reinterpret_cast<float*>(aBufPtr + a.LocateColumn(j)), 1, reinterpret_cast<float*>(bBufPtr + b.LocateColumn(j)), 1);
}
}
}
else
{
c.RequireSize(m, 1);
ElemType* aBufPtr = a.Data();
ElemType* bBufPtr = b.Data();
if (sizeof(ElemType) == sizeof(double))
{
#pragma omp parallel for
foreach_row (i, c)
{
c(i, 0) = cblas_ddot(n, reinterpret_cast<double*>(aBufPtr + i), m, reinterpret_cast<double*>(bBufPtr + i), m);
}
}
else
{
#pragma omp parallel for
foreach_row (i, c)
{
#pragma warning(suppress : 4244)
c(i, 0) = cblas_sdot(n, reinterpret_cast<float*>(aBufPtr + i), m, reinterpret_cast<float*>(bBufPtr + i), m);
}
}
}
}
// treat matrices as vectors. do vec(a)^T vec(b)
template <class ElemType>
ElemType CPUMatrix<ElemType>::InnerProductOfMatrices(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b)
{
if (a.IsEmpty() || b.IsEmpty())
LogicError("InnerProductOfMatrices: one of the input matrices is empty.");
const int m = (int) a.GetNumRows();
const int n = (int) a.GetNumCols();
const int k = (int) b.GetNumRows();
const int l = (int) b.GetNumCols();
assert(m > 0 && n > 0 && k > 0 && l > 0); // converting from size_t to int may cause overflow
if (m != k || n != l)
InvalidArgument("InnerProductOfMatrices: Matrices a and b should have same dimension.");
if (sizeof(ElemType) == sizeof(double))
{
return (ElemType) cblas_ddot((int) a.GetNumElements(), reinterpret_cast<double*>(a.Data()), 1, reinterpret_cast<double*>(b.Data()), 1);
}
else
{
#pragma warning(suppress : 4244)
return (ElemType) cblas_sdot((int) a.GetNumElements(), reinterpret_cast<float*>(a.Data()), 1, reinterpret_cast<float*>(b.Data()), 1);
}
}
template <class ElemType>
void CPUMatrix<ElemType>::ElementWisePower(ElemType alpha, const CPUMatrix<ElemType>& a, CPUMatrix<ElemType>& c)
{
if (a.IsEmpty())
LogicError("Scale: The input matrix a is empty.");
c.RequireSize(a.GetNumRows(), a.GetNumCols());
if (alpha == 2)
{
#pragma omp parallel for
foreach_coord (i, j, c)
{
c(i, j) = a(i, j) * a(i, j);
}
}
else if (alpha == 3)
{
#pragma omp parallel for
foreach_coord (i, j, c)
{
c(i, j) = a(i, j) * a(i, j) * a(i, j);
}
}
else
{
#pragma omp parallel for
foreach_coord (i, j, c)
{
c(i, j) = pow(a(i, j), alpha);
}
}
}
template <class ElemType>
bool CPUMatrix<ElemType>::AreEqual(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, const ElemType threshold /*= 1e-8*/)
{
if (a.GetNumRows() != b.GetNumRows() || a.GetNumCols() != b.GetNumCols())
return false;
bool result = true;
#pragma omp parallel for
foreach_coord (i, j, a)
{
if (abs(a(i, j) - b(i, j)) > threshold)
{
result = false;
break;
}
}
return result;
}
// see Matrix<ElemType>::TensorShuffleScaleAndAdd() for comments
template <class ElemType>
void CPUMatrix<ElemType>::TensorShuffleScaleAndAdd(ElemType keepWeight, const CPUMatrix<ElemType>& a, size_t D, size_t S, size_t M, size_t K, size_t T, ElemType scaleFactor, const CPUMatrix<ElemType>& b, CPUMatrix<ElemType>& c)
{
size_t N = D * S * M * K * T;
const auto pa = a.Data();
const auto pb = b.Data();
auto pc = c.Data();
// Note: This code is written to match a GPU implementation. It is not super-efficient on the CPU.
for (size_t na = 0; na < N; na++) // loop over all elements
{
// recover the 5 indices from the loop counter
size_t d = na % D;
size_t s = (na / D) % S;
size_t m = (na / D / S) % M;
size_t k = (na / D / S / M) % K;
size_t t = (na / D / S / M / K) % T;
// compute index for the a and b/c tensors
assert(na == (((t * K + k) * M + m) * S + s) * D + d); // input tensor of dimension (D x S x M x K x T)
size_t nb = (((t * S + s) * M + m) * K + k) * D + d; // output tensor of dimension (D x K x M x S x T): k/K and s/S swapped
assert(nb < N);
// perform the computation
ElemType cval = keepWeight ? keepWeight * pb[nb] : 0; // if weight is 0 then don't bother to read memory (efficiency) or to multiply (NaN-safe)
cval += scaleFactor * pa[na];
pc[nb] = cval;
}
}
template <class ElemType>
CPUMatrix<ElemType> CPUMatrix<ElemType>::Ones(const size_t rows, const size_t cols)
{
CPUMatrix<ElemType> c(rows, cols); // will initialize to 0
c.SetValue(1);
return c;
}
template <class ElemType>
CPUMatrix<ElemType> CPUMatrix<ElemType>::Zeros(const size_t rows, const size_t cols)
{
CPUMatrix<ElemType> c(rows, cols); // will initialize to 0
c.SetValue(0);
return c;
}
template <class ElemType>
CPUMatrix<ElemType> CPUMatrix<ElemType>::Eye(const size_t rows)
{
CPUMatrix<ElemType> c(rows, rows); // will initialize to 0
c.SetDiagonalValue(1);
return c;
}
template <class ElemType>
CPUMatrix<ElemType> CPUMatrix<ElemType>::RandomUniform(const size_t rows, const size_t cols, const ElemType low, const ElemType high, unsigned long seed)
{
CPUMatrix<ElemType> c(rows, cols); // will initialize to 0
c.SetUniformRandomValue(low, high, seed);
return c;
}
template <class ElemType>
CPUMatrix<ElemType> CPUMatrix<ElemType>::RandomGaussian(const size_t rows, const size_t cols, const ElemType mean, const ElemType sigma, unsigned long seed)
{
CPUMatrix<ElemType> c(rows, cols); // will initialize to 0
c.SetGaussianRandomValue(mean, sigma, seed);
return c;
}
template <class ElemType>
bool CPUMatrix<ElemType>::HasElement(const CPUMatrix<ElemType>& mat, const ElemType v)
{
bool bHas = false;
bool isvFinite = std::isfinite(v);
#pragma omp parallel for
for (long j = 0; j < mat.GetNumElements(); j++)
{
#pragma omp flush(bHas)
if (!bHas)
{
ElemType cur = mat.Data()[j];
if (isvFinite && std::isfinite(cur))
{
if (cur == v)
bHas = true;
}
else if (std::isnan(v) && std::isnan(cur))
bHas = true;
else if (std::isinf(v) && std::isinf(cur) && std::signbit(v) == std::signbit(cur))
bHas = true;
}
}
return bHas;
}
// CPUMatrix<ElemType>& AssignElementProductOfWithShiftNeg(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, size_t shift, size_t negnumber);
//[this]=a .* b
// here, a and b must be two row vectors of the same size, i.e. [1,m]
// the inputs are two rwo vectors
// the output is a matrix of size(neg+1, col)
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignElementProductOfWithShiftNeg(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, size_t shift, size_t negnumber)
{
if (a.IsEmpty() || b.IsEmpty())
LogicError("AssignElementProductOfWithShiftNeg: Matrix is empty.");
if (!(a.GetNumRows() == b.GetNumRows() && a.GetNumCols() == b.GetNumCols()))
InvalidArgument("AssignElementProductOfWithShiftNeg: The input matrix dimensions do not match.");
if (a.GetNumRows() != 1)
InvalidArgument("AssignElementProductOfWithShiftNeg: The input matrix must be a row vector.");
auto& us = *this;
if (this != &a)
{
RequireSize(negnumber + 1, a.GetNumCols());
// RequireSize(a.GetNumRows(), a.GetNumCols());
}
long m = (long) GetNumRows(), n = (long) GetNumCols(); // a and b are of size (1,n)
// #pragma omp parallel for
for (long j = 0; j < n; j++)
{
us(0, j) = a(0, j) * b(0, j);
}
for (long j = 0; j < n; j++)
{
for (long i = 1; i < m; i++)
{
us(i, j) = a(0, j) * b(0, (j + shift + i - 1) % n);
}
}
return *this;
}
template <class ElemType>
void CPUMatrix<ElemType>::InnerProductWithShiftNeg(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, CPUMatrix<ElemType>& c, const bool isColWise, size_t shift, size_t negnumber)
{
if (a.IsEmpty() || b.IsEmpty())
LogicError("InnerProduct: one of the input matrices is empty.");
const int m = (int) a.GetNumRows();
const int n = (int) a.GetNumCols();
const int k = (int) b.GetNumRows();
const int l = (int) b.GetNumCols();
assert(m > 0 && n > 0 && k > 0 && l > 0); // converting from size_t to int may cause overflow
if (m != k || n != l)
InvalidArgument("InnerProduct: Matrices a and b should have same dimension.");
if ((isColWise && m == 1) || !isColWise && n == 1) // in this case it's equivalent to element-wise product
{
InvalidArgument("InnerProduct: Both matrices should be normal ones, not vectors");
// c.AssignElementProductOf(a, b);
}
else if (isColWise) // col-wise
{
c.RequireSize(negnumber + 1, n); // this line ischanged
ElemType* aBufPtr = a.Data();
ElemType* bBufPtr = b.Data();
if (sizeof(ElemType) == sizeof(double))
{
for (long j = 0; j < n; j++)
{
c(0, j) = (ElemType) cblas_ddot(m, reinterpret_cast<double*>(aBufPtr + a.LocateColumn(j)), 1, reinterpret_cast<double*>(bBufPtr + b.LocateColumn(j)), 1);
}
for (long j = 0; j < n; j++)
{
for (long i = 1; i < negnumber + 1; i++)
{
c(i, j) = (ElemType) cblas_ddot(m, reinterpret_cast<double*>(aBufPtr + a.LocateColumn(j)), 1, reinterpret_cast<double*>(bBufPtr + b.LocateColumn((j + shift + i - 1) % n)), 1);
}
}
}
else
{
for (long j = 0; j < n; j++)
{
c(0, j) = (ElemType) cblas_sdot(m, reinterpret_cast<float*>(aBufPtr + a.LocateColumn(j)), 1, reinterpret_cast<float*>(bBufPtr + b.LocateColumn(j)), 1);
}
for (long j = 0; j < n; j++)
{
for (long i = 1; i < negnumber + 1; i++)
{
c(i, j) = (ElemType) cblas_sdot(m, reinterpret_cast<float*>(aBufPtr + a.LocateColumn(j)), 1, reinterpret_cast<float*>(bBufPtr + b.LocateColumn((j + shift + i - 1) % n)), 1);
}
}
}
}
else
{
InvalidArgument("InnerProduct: Rowwise is not supported yet");
c.RequireSize(m, 1);
ElemType* aBufPtr = a.Data();
ElemType* bBufPtr = b.Data();
if (sizeof(ElemType) == sizeof(double))
{
#pragma omp parallel for
foreach_row (i, c)
{
c(i, 0) = (ElemType) cblas_ddot(n, reinterpret_cast<double*>(aBufPtr + i), m, reinterpret_cast<double*>(bBufPtr + i), m);
}
}
else
{
#pragma omp parallel for
foreach_row (i, c)
{
#pragma warning(suppress : 4244)
c(i, 0) = cblas_sdot(n, reinterpret_cast<float*>(aBufPtr + i), m, reinterpret_cast<float*>(bBufPtr + i), m);
}
}
}
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::GetARowByIndex(const CPUMatrix<ElemType>& a, size_t index)
{
if (a.IsEmpty())
LogicError("GetARowByIndex: the input matrices is empty.");
const int m = (int) a.GetNumRows();
const int n = (int) a.GetNumCols();
if (index < 0 || index >= m)
LogicError("GetARowByIndex: the row index is out of range.");
assert(m > 0 && n > 0); // converting from size_t to int may cause overflow
auto& us = *this;
RequireSize(1, n);
for (long j = 0; j < n; j++)
{
us(0, j) = a(index, j);
}
return *this;
}
// input: a, a row vector
// input: b, a matrix. b.col == a.col
// input firstmatrixfixed: If true, keep a's order. Otherwise, keep b's order
// output: c, a matrix. c.size == b.size
/*
Example, a = [a1 a2 a3]
b = [b11 b12 b13;
b21 b22 b23 ]
if true:
shift = 1
then c = [a1*b12 a2*b13 a3*b11
a1*b22 a2*b23 a3*b21]
if shift = 2
then c = [ a1*b13 a2*b11 a3*b12
a1*b23 a2*b21 a3*b22]
i.e. we do column-wise shift
if false:
shift = 1
then c = [a2*b11 a3*b12 a1*b13
a2*b21 a3*b22 a1*b23]
shift = 2
then c = [ a3*b11 a1*b12 a2*b13
a3*b21 a1*b22 a2*b23]
*/
template <class ElemType>
void CPUMatrix<ElemType>::ConductRowElementMultiplyWithShift(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, CPUMatrix<ElemType>& c, size_t shift, bool bFirstmatrixfixed)
{
if (a.IsEmpty() || b.IsEmpty())
LogicError("InnerProduct: one of the input matrices is empty.");
const int m = (int) a.GetNumRows();
const int n = (int) a.GetNumCols();
const int k = (int) b.GetNumRows();
const int l = (int) b.GetNumCols();
assert(m > 0 && n > 0 && k > 0 && l > 0); // converting from size_t to int may cause overflow
if (m != 1 || n != l)
InvalidArgument("InnerProduct: Matrices a and b should have same dimension.");
c.RequireSize(k, l); // c must the the same size of b
if (bFirstmatrixfixed)
{
for (long j = 0; j < l; j++)
{
for (long i = 0; i < k; i++)
{
c(i, j) = a(0, j) * b(i, (j + shift) % l);
}
}
}
else
{
for (long j = 0; j < l; j++)
{
for (long i = 0; i < k; i++)
{
c(i, j) = a(0, (j + shift) % l) * b(i, j);
}
}
}
}
// CPUMatrix<ElemType>& AssignElementProductOfWithShift(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, size_t shift);
//[this]=a .* b
// here, a and b must be two row vectors of the same size, i.e. [1,m]. We will do element product with shift.
// inputs are 2 row vectors
// output is a row vector
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignElementProductOfWithShift(const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, size_t shift)
{
if (a.IsEmpty() || b.IsEmpty())
LogicError("AssignElementProductOfWithShiftNeg: Matrix is empty.");
if (a.GetNumRows() != b.GetNumRows() || a.GetNumCols() != b.GetNumCols())
InvalidArgument("AssignElementProductOfWithShiftNeg: The input matrix dimensions do not match.");
if (a.GetNumRows() != 1)
InvalidArgument("AssignElementProductOfWithShiftNeg: The input matrix must be a row vector.");
auto& us = *this;
if (this != &a)
{
RequireSize(1, a.GetNumCols());
// RequireSize(a.GetNumRows(), a.GetNumCols());
}
// long m = (long)GetNumRows(), n = (long)GetNumCols(); // a and b are of size (1,n)
long n = (long) GetNumCols(); // a and b are of size (1,n)
#pragma omp parallel for
for (long j = 0; j < n; j++)
{
us(0, j) = a(0, j) * b(0, (j + shift) % n);
}
return *this;
}
#pragma endregion Static BLAS Functions
// 'double' version of LogAdd
inline double LogAddD(double x, double y)
{
return LogAdd(x, y);
}
template <class ElemType>
ElemType CPUMatrix<ElemType>::LogSumOfElements() const
{
ElemType fAlpha = (ElemType) LZERO;
ElemType* bufPtr = Data();
for (int k = 0; k < GetNumElements(); k++)
fAlpha = (ElemType) LogAddD(fAlpha, bufPtr[k]);
return fAlpha;
}
template <class ElemType>
void CPUMatrix<ElemType>::RCRFBackwardCompute(const CPUMatrix<ElemType>& alpha, CPUMatrix<ElemType>& beta,
const CPUMatrix<ElemType>& lbls,
const CPUMatrix<ElemType>& pair_scores)
{
int iNumPos = (int) lbls.GetNumCols();
int iNumLab = (int) lbls.GetNumRows();
int lastLbl = -1;
for (int ik = 0; ik < lbls.GetNumRows(); ik++)
if (lbls(ik, iNumPos - 1) != 0)
{
lastLbl = ik;
break;
}
beta.RequireSize(iNumLab, iNumPos);
for (int t = iNumPos - 1; t >= 0; t--)
{
#pragma omp parallel for
for (int k = 0; k < iNumLab; k++)
{
_rcrfBackwardCompute(t, k, alpha, beta, pair_scores);
}
}
};
// Calculate alpha in forward-backward calculation. equation (6), (7) in ftp://ftp.idsia.ch/pub/juergen/icml2006.pdf
// GPU x dimension corresponds to utterances, y dimension corresponds to phone sequence in each utterance
// prob (input): the posterior output from the network
// alpha (output): alpha for forward-backward calculation.
// phoneSeq (input): phone ID sequence for each utterance in this minibatch, each col is one utterance
// phoneBound (input): phone boundary (frame index) of each phone for each utterance in this minibatch, each col is one utterance
// uttToChanInd (input): map from utterance ID to minibatch channel ID. We need this because each channel may contain more than one utterance.
// uttFrameNum (input): the frame number of each utterance. The size of this vector = the number of all utterances in this minibatch
// uttBeginFrame(input): the positon of the first frame of each utterance in the minibatch channel. We need this because each channel may contain more than one utterance.
// uttPhoneNum (input): the phone number of each utterance. The size of this vector = the number of all utterances in this minibatch
// numChannels (input): channel number in this minibatch
// uttNum (input): number of utterances
// t (input): time stamp to process
// maxPhoneNum (input): the max number of phones between utterances
// totalPhoneNum (input): the total number of phones of all utterances
// blankTokenId (input): id of the CTC blank token
// delayConstraint -- label output delay constraint introduced during training that allows to have shorter delay during inference.
// Alpha and Beta scores outside of the delay boundary are set to zero.
// Setting this parameter smaller will result in shorted delay between label output during decoding.
// delayConstraint=-1 means no constraint
template<class ElemType>
void _assignAlphaScore(
const ElemType *prob,
ElemType *alphaScore,
ElemType *phoneSeq,
ElemType *phoneBound,
const std::vector<size_t>& uttToChanInd,
const std::vector<size_t>& uttFrameNum,
const std::vector<size_t>& uttBeginFrame,
const std::vector<size_t>& uttPhoneNum,
size_t numChannels,
const size_t uttNum,
const size_t t,
const size_t maxPhoneNum, // Maximum length of utterance in this MB
const size_t totalPhoneNum, // Total number of phones
const size_t blankTokenId,
const int delayConstraint)
{
for (size_t uttId = 0;uttId < uttNum;uttId++) {
// Number of phones and frames in this utterance
size_t frameNum = uttFrameNum[uttId];
if (t >= frameNum) continue;
size_t phoneNum = uttPhoneNum[uttId];
#pragma omp parallel for
for (int phoneSeqId = 1;phoneSeqId < phoneNum - 1;phoneSeqId++) {
// Index of the label in the sequence
// Current and previous phone indices in phoneSeq matrix
size_t labelid = uttId*maxPhoneNum + phoneSeqId;
// Actual current phone label
size_t phoneId = (size_t)(phoneSeq[labelid]);
// Index of the current frame in minibatch
size_t timeId = (t + uttBeginFrame[uttId])*numChannels + uttToChanInd[uttId];
// Index of probability of observing phoneId at frame timeId
size_t probId = timeId*totalPhoneNum + phoneId;
size_t alphaId = maxPhoneNum* timeId + phoneSeqId; // alpha_t(s)
if (t == 0)
{
// Initialize recursion
if (phoneSeqId == 1 || phoneSeqId == 2)
{
alphaScore[alphaId] = prob[probId];
}
}
else
{
if (phoneSeqId >= 1)
{
size_t timeId_1 = timeId - numChannels; // Index corresponding to (t-1)
size_t alphaId_0 = maxPhoneNum* timeId_1 + phoneSeqId; // alpha_{t-1}(s)
size_t alphaId_1 = alphaId_0 - 1; // alpha_{t-1}(s-1)
size_t alphaId_2 = alphaId_0 - 2; // alpha_{t-1}(s-2)
ElemType x = LZERO;
ElemType ascore;
if (phoneSeqId > 2)
{
size_t labelid_2 = labelid - 2;
// if current label is not blank and not equal prev non-blank label
if ((size_t)(phoneSeq[labelid]) != blankTokenId && phoneId != (size_t)(phoneSeq[labelid_2]))
{
x = LogAdd(x, alphaScore[alphaId_2]);
}
}
if (phoneSeqId > 1)
{
x = LogAdd(x, alphaScore[alphaId_1]);
}
x = LogAdd(x, alphaScore[alphaId_0]);
if (phoneId != SIZE_MAX)
ascore = prob[probId]; // Probability of observing given label at given time
else
ascore = 0;
alphaScore[alphaId] = (ElemType)x + ascore;
if (delayConstraint != -1)
{
size_t labelid_r = labelid + 2;
size_t phoneBoundId_r = (size_t)(phoneBound[labelid_r]);
if (phoneId == blankTokenId)
{
// only constraint right side
if (t > phoneBoundId_r + delayConstraint - 1)
alphaScore[alphaId] = LZERO;
}
else if (phoneId != blankTokenId)
{
if (t > phoneBoundId_r + delayConstraint)
alphaScore[alphaId] = LZERO;
}
}
}
}
}
}
}
// Calculate beta in forward-backward calculation, equation (10), (11) in ftp://ftp.idsia.ch/pub/juergen/icml2006.pdf
// See _assignAlphaScore for the explanation of parameters
template<class ElemType>
void _assignBetaScore(
const ElemType *prob,
ElemType *betaScore,
ElemType *phoneSeq,
ElemType *phoneBound,
const std::vector<size_t>& uttToChanInd,
const std::vector<size_t>& uttFrameNum,
const std::vector<size_t>& uttBeginFrame,
const std::vector<size_t>& uttPhoneNum,
const size_t numChannels,
const size_t uttNum,
const long t,
const size_t maxPhoneNum,
const size_t totalPhoneNum,
const size_t blankTokenId,
const int delayConstraint)
{
for (size_t uttId = 0;uttId < uttNum;uttId++) {
// Number of phones and frames in this utterance
size_t frameNum = uttFrameNum[uttId];
if (t >= frameNum) continue;
size_t phoneNum = uttPhoneNum[uttId];
#pragma omp parallel for
for (int phoneSeqId = 1;phoneSeqId < phoneNum - 1;phoneSeqId++) {
size_t labelid = uttId*maxPhoneNum + phoneSeqId;
size_t labelid_2 = labelid + 2;
size_t phoneId = (LONG64)(phoneSeq[labelid]);
size_t timeId = (t + uttBeginFrame[uttId])*numChannels + uttToChanInd[uttId];
size_t probId = timeId*totalPhoneNum + phoneId;
size_t betaid = maxPhoneNum* timeId + phoneSeqId;
size_t timeId_1 = timeId + numChannels;
size_t betaid_0 = maxPhoneNum* timeId_1 + phoneSeqId;
size_t betaid_1 = betaid_0 + 1;
size_t betaid_2 = betaid_0 + 2;
if (t == frameNum - 1)
{
if (phoneSeqId == phoneNum - 3 || phoneSeqId == phoneNum - 2)
{
betaScore[betaid] = prob[probId];
}
}
else
{
if (phoneSeqId >= 1)
{
ElemType x = LZERO;
ElemType ascore;
if (phoneSeqId < phoneNum - 3)
{
if (phoneSeq[labelid] != blankTokenId && phoneId != phoneSeq[labelid_2])
{
x = LogAdd(x, betaScore[betaid_2]);
}
}
if (phoneSeqId < phoneNum - 2)
{
x = LogAdd(x, betaScore[betaid_1]);
}
x = LogAdd(x, betaScore[betaid_0]);
if (phoneId != SIZE_MAX)
ascore = prob[probId];
else
ascore = 0;
betaScore[betaid] = (ElemType)x + ascore;
if (delayConstraint != -1)
{
size_t phoneBoundId_r = (size_t)(phoneBound[labelid_2]);
if (phoneId == blankTokenId)
{
if (t > phoneBoundId_r + delayConstraint - 1)
betaScore[betaid] = LZERO;
}
else if (phoneId != blankTokenId)
{
if (t > phoneBoundId_r + delayConstraint)
betaScore[betaid] = LZERO;
}
}
}
}
}
}
}
// Calculate CTC score. equation (8) in ftp://ftp.idsia.ch/pub/juergen/icml2006.pdf
template<class ElemType>
void _assignTotalScore(ElemType *betaScore,
std::vector<ElemType>& totalScore,
const size_t uttNum,
const std::vector<size_t>& uttToChanInd,
const std::vector<size_t>& uttBeginFrame,
const size_t numChannels,
const size_t maxPhoneNum)
{
#pragma omp parallel for
for (int uttId = 0; uttId < uttNum; uttId++) {
if (uttId < uttNum)
{
LONG64 alphaId_0 = (uttBeginFrame[uttId] * numChannels + uttToChanInd[uttId]) * maxPhoneNum;
betaScore[alphaId_0] = LogAdd(betaScore[alphaId_0 + 1], betaScore[alphaId_0 + 2]);
totalScore[uttId] = betaScore[alphaId_0];
}
}
}
// Calculate derivative, equation (15) in ftp://ftp.idsia.ch/pub/juergen/icml2006.pdf
// See _assignAlphaScore for the explanation of parameters
template<class ElemType>
void _assignCTCScore(
ElemType *CTCscore,
ElemType *prob,
ElemType *alphaScore,
ElemType *betaScore,
ElemType *phoneSeq,
const size_t uttNum,
const std::vector<size_t>& uttToChanInd,
const std::vector<size_t>& uttBeginFrame,
const std::vector<size_t>& uttPhoneNum,
const std::vector<size_t>& uttFrameNum,
const size_t numChannels,
const size_t maxPhoneNum,
const size_t totalPhoneNum)
{
for (size_t uttId = 0;uttId < uttNum;uttId++) {
#pragma omp parallel for
for (int t = 0; t < uttFrameNum[uttId]; t++) {
size_t phoneNum = uttPhoneNum[uttId];
size_t alphaId_0 = (uttBeginFrame[uttId] * numChannels + uttToChanInd[uttId]) * maxPhoneNum;
size_t timeId = (t + uttBeginFrame[uttId])*numChannels + uttToChanInd[uttId];
ElemType P_lx = betaScore[alphaId_0];
for (int s = 1; s < phoneNum - 1; s++)
{
long phoneId = phoneSeq[uttId*maxPhoneNum + s];
size_t alphaId = maxPhoneNum* timeId + s;
size_t probId = timeId*totalPhoneNum + phoneId;
if (phoneId != SIZE_MAX)
{
ElemType logoccu = alphaScore[alphaId] + betaScore[alphaId] - prob[probId] - (ElemType)P_lx;
CTCscore[probId] = LogAdd(CTCscore[probId], logoccu);
}
}
for (int s = 0; s < totalPhoneNum; s++)
{
size_t probId = timeId*totalPhoneNum + s;
ElemType logoccu = CTCscore[probId];
if (logoccu < LZERO)
CTCscore[probId] = 0.0f;
else
CTCscore[probId] = exp(logoccu);
}
}
}
}
template<class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignCTCScore(
const CPUMatrix<ElemType>& prob, CPUMatrix<ElemType>& alpha, CPUMatrix<ElemType>& beta,
const CPUMatrix<ElemType>& phoneSeq, const CPUMatrix<ElemType>& phoneBoundary, CPUMatrix<ElemType> & totalScore, const std::vector<size_t>& uttToChanInd, const std::vector<size_t> & uttBeginFrame, const std::vector<size_t> & uttFrameNum,
const std::vector<size_t> & uttPhoneNum, const size_t numParallelSequences, const size_t maxFrameNum, const size_t blankTokenId, const int delayConstraint, const bool isColWise)
{
// Column wise representation of sequences in input matrices (each column is one sequence/utterance)
if (isColWise)
{
// Total number of phones
size_t totalPhoneNum = prob.GetNumRows();
size_t uttNum = uttFrameNum.size();
// Max number of phones in utterances in this minibatch
size_t maxPhoneNum = phoneSeq.GetNumRows();
for (size_t t = 0; t < maxFrameNum; t++)
{
_assignAlphaScore(prob.Data(), alpha.Data(), phoneSeq.Data(), phoneBoundary.Data(), uttToChanInd,
uttFrameNum, uttBeginFrame, uttPhoneNum, numParallelSequences, uttNum, t, maxPhoneNum, totalPhoneNum, blankTokenId, delayConstraint);
}
for (LONG64 t = maxFrameNum - 1; t >= 0; t--)
{
_assignBetaScore(prob.Data(), beta.Data(), phoneSeq.Data(), phoneBoundary.Data(), uttToChanInd,
uttFrameNum, uttBeginFrame, uttPhoneNum, numParallelSequences, uttNum, t, maxPhoneNum, totalPhoneNum, blankTokenId, delayConstraint);
}
std::vector<ElemType> scores(uttNum);
_assignTotalScore(beta.Data(), scores, uttNum, uttToChanInd, uttBeginFrame, numParallelSequences, maxPhoneNum);
_assignCTCScore(Data(), prob.Data(), alpha.Data(), beta.Data(), phoneSeq.Data(), uttNum, uttToChanInd,
uttBeginFrame, uttPhoneNum, uttFrameNum, numParallelSequences, maxPhoneNum, totalPhoneNum);
totalScore(0, 0) = 0.0;
for (size_t utt = 0; utt < uttNum; utt++)
{
totalScore(0,0) -= scores[utt];
}
return *this;
}
else {
LogicError("Only ColWise minibatch layout is supported.");
}
return *this;
}
/// the kernel function for RCRF backward computation
template <class ElemType>
void CPUMatrix<ElemType>::_rcrfBackwardCompute(size_t t, size_t k, const CPUMatrix<ElemType>& alpha,
CPUMatrix<ElemType>& beta,
const CPUMatrix<ElemType>& pair_scores)
{
size_t iNumLab = alpha.GetNumRows();
size_t iNumPos = alpha.GetNumCols();
ElemType fSum;
ElemType fTmp = (ElemType) LZERO;
if (t == iNumPos - 1)
{
fSum = (ElemType) LZERO;
for (int j = 0; j < iNumLab; j++)
{
fSum = (ElemType) LogAddD(fSum, alpha(j, t));
}
fTmp = alpha(k, t) - fSum;
beta(k, t) = fTmp;
}
else
{
for (int j = 0; j < iNumLab; j++)
{
fSum = (ElemType) LZERO;
for (int m = 0; m < iNumLab; m++)
{
fSum = (ElemType) LogAddD(fSum, alpha(m, t) + pair_scores(j, m));
}
fTmp = (ElemType) LogAddD(fTmp, beta(j, t + 1) + alpha(k, t) + pair_scores(j, k) - fSum);
}
beta(k, t) = fTmp;
}
}
template <class ElemType>
void CPUMatrix<ElemType>::RCRFTransGrdCompute(const CPUMatrix<ElemType>& lbls,
const CPUMatrix<ElemType>& alpha,
const CPUMatrix<ElemType>& beta,
const CPUMatrix<ElemType>& pair_scores,
CPUMatrix<ElemType>& grd)
{
int iNumPos = (int) alpha.GetNumCols();
int iNumLab = (int) alpha.GetNumRows();
int firstLbl = -1;
for (int ik = 0; ik < lbls.GetNumRows(); ik++)
if (lbls(ik, 0) != 0)
{
firstLbl = ik;
break;
}
for (size_t tPos = 0; tPos < iNumPos; tPos++)
{
CPUMatrix<ElemType> b = beta.ColumnSlice(tPos, 1);
CPUMatrix<ElemType> a;
if (tPos > 0)
a = alpha.ColumnSlice(tPos - 1, 1);
#pragma omp parallel for
for (int i = 0; i < iNumLab; i++)
{
_rcrfTransGrdCompute(i, lbls, alpha, beta, pair_scores, grd, tPos);
}
// transition score
int i = -1;
if (tPos == 0)
i = firstLbl;
else
{
for (int ik = 0; ik < lbls.GetNumRows(); ik++)
if (lbls(ik, tPos - 1) != 0)
{
i = ik;
break;
}
}
int j = -1;
for (int ik = 0; ik < lbls.GetNumRows(); ik++)
{
if (lbls(ik, tPos) != 0)
{
j = ik;
break;
}
}
grd(j, i) -= 1.0;
}
};
template <class ElemType>
void CPUMatrix<ElemType>::_rcrfTransGrdCompute(size_t i,
const CPUMatrix<ElemType>& lbls,
const CPUMatrix<ElemType>& alpha,
const CPUMatrix<ElemType>& beta,
const CPUMatrix<ElemType>& pair_scores,
CPUMatrix<ElemType>& grd,
const size_t tPos // position
)
{
int iNumLab = (int) alpha.GetNumRows();
int firstLbl = -1;
for (int ik = 0; ik < lbls.GetNumRows(); ik++)
if (lbls(ik, 0) != 0)
{
firstLbl = ik;
break;
}
CPUMatrix<ElemType> b = beta.ColumnSlice(tPos, 1);
CPUMatrix<ElemType> a;
if (tPos > 0)
a = alpha.ColumnSlice(tPos - 1, 1);
{
ElemType fTmp = (ElemType) LZERO;
for (int j = 0; j < iNumLab; j++)
{
if (tPos == 0)
{
if (i == firstLbl)
{
fTmp = 0;
}
else
{
fTmp = (ElemType) LZERO;
}
}
else
{
fTmp = a(i, 0);
}
fTmp += pair_scores(j, i);
ElemType fSum = (ElemType) LZERO;
for (int k = 0; k < iNumLab; k++)
{
ElemType fTmp2;
if (tPos == 0)
{
if (k == firstLbl)
{
fTmp2 = 0;
}
else
{
fTmp2 = (ElemType) LZERO;
}
}
else
{
fTmp2 = a(k, 0);
}
fSum = (ElemType) LogAddD(fSum, fTmp2 + pair_scores(j, k));
}
fTmp -= fSum;
fTmp += b(j, 0);
grd(j, i) += exp(fTmp);
}
}
};
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::DropFrame(const CPUMatrix<ElemType>& label, const CPUMatrix<ElemType>& gamma, const ElemType& threshhold)
{
auto& us = *this;
if (us.GetNumCols() != gamma.GetNumCols() || us.GetNumRows() != gamma.GetNumRows())
LogicError("DropFrame: target matrix is not in the same size as gamm matrix.");
#pragma omp parallel for
foreach_column (j, label)
{
bool dropframe = false;
foreach_row (i, label)
{
if (fabs(label(i, j) - 1.0f) < 0.1)
{
if (gamma(i, j) < threshhold)
dropframe = true;
break;
}
}
foreach_row (i, label)
{
us(i, j) = 0.0f;
}
}
return *this;
}
template <class ElemType>
CPUMatrix<ElemType>& CPUMatrix<ElemType>::AssignSequenceError(const ElemType hsmoothingWeight, const CPUMatrix<ElemType>& label,
const CPUMatrix<ElemType>& dnnoutput, const CPUMatrix<ElemType>& gamma, ElemType alpha)
{
auto& us = *this;
foreach_coord (i, j, us)
us(i, j) += alpha * (label(i, j) - (1 - hsmoothingWeight) * dnnoutput(i, j) - hsmoothingWeight * gamma(i, j));
return *this;
}
// note: this function does not depend on the <ElemType> parameter
template <class ElemType>
int CPUMatrix<ElemType>::SetNumThreads(int numThreads)
{
if (numThreads == 0) // use default
return numThreads;
int mthreads = (int) std::thread::hardware_concurrency();
if (numThreads <= 0)
numThreads = std::max(1, mthreads + numThreads);
if (numThreads > mthreads)
numThreads = mthreads;
#ifdef _OPENMP
omp_set_num_threads(numThreads);
numThreads = omp_get_max_threads();
#ifdef USE_MKL
mkl_set_num_threads(numThreads);
#elif defined(USE_OPENBLAS)
openblas_set_num_threads(numThreads);
#endif
#endif
return numThreads;
}
template <class ElemType>
int CPUMatrix<ElemType>::GetMaxNumThreads()
{
int numThreads = (int)std::thread::hardware_concurrency();
#ifdef _OPENMP
numThreads = omp_get_max_threads();
#endif
return numThreads;
}
// To ensure Intel MKL calls return the same results on all Intel or Intel compatible CPUs,
// the function set CBWR compatible mode.
template <class ElemType>
void CPUMatrix<ElemType>::SetCompatibleMode()
{
#ifdef USE_MKL
if (mkl_cbwr_set(MKL_CBWR_COMPATIBLE) != MKL_CBWR_SUCCESS)
RuntimeError("Could not set MKL compatible mode.");
#endif
}
// =======================================================================
// TensorView support
// =======================================================================
// To save time, this makes extensive use of templates and macros.
// -----------------------------------------------------------------------
// function to compute the value for a given output location (perform reduction if needed)
// -----------------------------------------------------------------------
// perform loop over reduction index m
// This function is declared inside a wrapper struct to allow partial specialization (m = -1).
template <class ElemType, typename OPFN, typename ReductionOp, size_t N, int m>
struct TensorOpReduction
{
// reduction case (non-reduction case is specialized)
static inline ElemType Loop(array<ElemType*, N> pointers, const OPFN& opfn, const ReductionOp& reductionOp,
const SmallVector<size_t>& reducingOpDims, const array<SmallVector<ptrdiff_t>, N>& reducingStrides)
{
array<ptrdiff_t, N - 1> strides; // N-1 because last one is the result pointer, which is unused in reduction
for (size_t i = 0; i < N - 1; i++) // N = a small constant, this will be unrolled
strides[i] = reducingStrides[i][(size_t) m];
double aggregate = TensorOpReduction<ElemType, OPFN, ReductionOp, N, m - 1>::Loop(pointers, opfn, reductionOp, reducingOpDims, reducingStrides);
for (size_t dim = reducingOpDims[(size_t)m] - 1; dim-- > 0;)
{
// advance the pointers
for (size_t i = 0; i < N - 1; i++)
pointers[i] += strides[i]; // note: last pointer (result) is unused and untouched here
// need to descend into one loop deeper
aggregate = reductionOp(aggregate, TensorOpReduction<ElemType, OPFN, ReductionOp, N, m - 1>::Loop(pointers, opfn, reductionOp, reducingOpDims, reducingStrides));
}
// Actually it would be nicer to return double but we keep ElementType so that test don't return different numbers than previous implementation.
return static_cast<double>(aggregate);
}
};
// perform loop over reduction index m
// This is the specialized version for m = -1, which terminates the recursion.
template <class ElemType, typename OPFN, typename ReductionOp, size_t N>
struct TensorOpReduction<ElemType, OPFN, ReductionOp, N, -1>
{
static inline ElemType Loop(array<ElemType*, N> pointers, const OPFN& opfn, const ReductionOp& reductionOp,
const SmallVector<size_t>&, const array<SmallVector<ptrdiff_t>, N>&)
{
return opfn(pointers); // finally we are doing some work!!!
}
};
// perform loop over reduction index m, while keeping track of the number of elements and their corresponding indices.
// This function is declared inside a wrapper struct to allow partial specialization (m = -1).
template <class ElemType, size_t N, int m>
struct TensorArgOpReduction
{
static inline std::pair<ElemType, size_t> ReduceAll(array<ElemType*, N> pointers, const SmallVector<size_t>& reducingOpDims, const array<SmallVector<ptrdiff_t>, N>& reducingStrides,
ElementWiseOperator reductionOp)
{
size_t counter = 0;
size_t index = 0;
ElemType val = (ElemType)0;
switch (reducingOpDims.size())
{
case 3:
val = TensorArgOpReduction<ElemType, N, 2>::Loop(pointers, reducingOpDims, reducingStrides, reductionOp, counter, index);
break;
case 2:
val = TensorArgOpReduction<ElemType, N, 1>::Loop(pointers, reducingOpDims, reducingStrides, reductionOp, counter, index);
break;
case 1:
val = TensorArgOpReduction<ElemType, N, 0>::Loop(pointers, reducingOpDims, reducingStrides, reductionOp, counter, index);
break;
case 0:
val = TensorArgOpReduction<ElemType, N, -1>::Loop(pointers, reducingOpDims, reducingStrides, reductionOp, counter, index);
break;
default:
LogicError("TensorOp: %d non-flattened input dimensions are not supported.", (int)reducingOpDims.size());
}
return make_pair(val, index);
}
// reduction case (non-reduction case is specialized)
static inline ElemType Loop(array<ElemType*, N> pointers, const SmallVector<size_t>& reducingOpDims, const array<SmallVector<ptrdiff_t>, N>& reducingStrides,
ElementWiseOperator reductionOp, size_t& counter, size_t& index)
{
array<ptrdiff_t, N - 1> strides; // N-1 because last one is the result pointer, which is unused in reduction
for (size_t i = 0; i < N - 1; i++) // N = a small constant, this will be unrolled
strides[i] = reducingStrides[i][(size_t)m];
ElemType aggregate = TensorArgOpReduction<ElemType, N, m - 1>::Loop(pointers, reducingOpDims, reducingStrides, reductionOp, counter, index);
for (size_t dim = reducingOpDims[(size_t)m] - 1; dim-- > 0;)
{
// advance the pointers
for (size_t i = 0; i < N - 1; i++)
pointers[i] += strides[i]; // note: last pointer (result) is unused and untouched here
ElemType val = TensorArgOpReduction<ElemType, N, m - 1>::Loop(pointers, reducingOpDims, reducingStrides, reductionOp, counter, index);
bool update = false;
switch (reductionOp)
{
case ElementWiseOperator::opArgmin:
update = (aggregate > val);
break;
case ElementWiseOperator::opArgmax:
update = (aggregate < val);
break;
}
if (update)
{
aggregate = val;
index = counter - 1;
}
}
return aggregate;
}
};
// perform loop over reduction index m
// This is the specialized version for m = -1, which terminates the recursion.
template <class ElemType, size_t N>
struct TensorArgOpReduction<ElemType, N, -1>
{
static inline ElemType Loop(array<ElemType*, N> pointers,
const SmallVector<size_t>&, const array<SmallVector<ptrdiff_t>, N>&, ElementWiseOperator reductionOp, size_t& counter, size_t& index)
{
counter++;
return *pointers[0]; // finally we are doing some work!!!
}
};
// -----------------------------------------------------------------------
// perform loop over regular index k for N-nary operations (N counting the output)
// -----------------------------------------------------------------------
// perform loop over regular index k and reducing index m for N operands (counting the output)
template <class ElemType, typename OPFN, typename ReductionOp, size_t N, bool vectorizable, int m, int k>
struct TensorOpIteration
{
static inline void Loop(ElemType beta, array<ElemType*, N> pointers, ElemType alpha, const OPFN& opfn, const ReductionOp& reductionOp,
const SmallVector<size_t>& regularOpDims, const array<SmallVector<ptrdiff_t>, N>& regularStrides,
const SmallVector<size_t>& reducingOpDims, const array<SmallVector<ptrdiff_t>, N>& reducingStrides)
{
// non-scalar case: still nested result loops left
array<ptrdiff_t, N> strides;
for (size_t i = 0; i < N; i++) // N = a small constant, this will be unrolled
strides[i] = regularStrides[i][(size_t) k];
for (size_t dim = regularOpDims[(size_t) k]; dim-- > 0;)
{
// need to descend into one loop deeper
TensorOpIteration<ElemType, OPFN, ReductionOp, N, vectorizable, m, k - 1>::Loop(beta, pointers, alpha, opfn, reductionOp, regularOpDims, regularStrides, reducingOpDims, reducingStrides);
// advance the pointers
for (size_t i = 0; i < N; i++)
pointers[i] += strides[i];
}
}
};
// Special version for innermost loop with strides all being 1 and no further reduction. Compiler can use SSE.
// This is a very common case, e.g. adding vectors or computing the Sigmoid.
template <class ElemType, typename OPFN, typename ReductionOp>
struct TensorOpIteration<ElemType, OPFN, ReductionOp, 3, true /*vectorizable*/, -1 /*no reduction*/, 0 /*innermost loop*/>
{
static inline void Loop(ElemType beta, array<ElemType*, 3> pointers, ElemType alpha, const OPFN& opfn, const ReductionOp& reductionOp,
const SmallVector<size_t>& regularOpDims, const array<SmallVector<ptrdiff_t>, 3>& regularStrides,
const SmallVector<size_t>& reducingOpDims, const array<SmallVector<ptrdiff_t>, 3>& reducingStrides)
{
ElemType* pa = pointers[0];
ElemType* pb = pointers[1];
ElemType* pc = pointers[2];
size_t K = regularOpDims[0];
// special-case beta and alpha to allow the compiler to short-circuit it
if (beta != 0)
#pragma omp parallel for
for (int k = 0; k < (int) K; k++)
TensorOpIteration<ElemType, OPFN, ReductionOp, 3, true /*vectorizable*/, -1 /*no reduction*/, -1 /*scalar*/>::Loop(beta, array<ElemType*, 3>{pa + k, pb + k, pc + k}, alpha, opfn, reductionOp, regularOpDims, regularStrides, reducingOpDims, reducingStrides);
else if (alpha != 1)
#pragma omp parallel for
for (int k = 0; k < (int) K; k++)
TensorOpIteration<ElemType, OPFN, ReductionOp, 3, true /*vectorizable*/, -1 /*no reduction*/, -1 /*scalar*/>::Loop(0, array<ElemType*, 3>{pa + k, pb + k, pc + k}, alpha, opfn, reductionOp, regularOpDims, regularStrides, reducingOpDims, reducingStrides);
else
#pragma omp parallel for
for (int k = 0; k < (int) K; k++)
TensorOpIteration<ElemType, OPFN, ReductionOp, 3, true /*vectorizable*/, -1 /*no reduction*/, -1 /*scalar*/>::Loop(0, array<ElemType*, 3>{pa + k, pb + k, pc + k}, 1, opfn, reductionOp, regularOpDims, regularStrides, reducingOpDims, reducingStrides);
// TODO: According to Amit, the VS compiler is not able to vectorize into lambdas. Solution: change the lambda to take an N, or to implement the loop inside (with 1 element by default).
// TODO: The signedness of k (required for omp) causes an extra sign-extend.
// TODO: OMP adds LOTS of overhead. Do we need a guard, a min size when to use it?
}
};
// and unary
template <class ElemType, typename OPFN, typename ReductionOp>
struct TensorOpIteration<ElemType, OPFN, ReductionOp, 2, true /*vectorizable*/, -1 /*no reduction*/, 0 /*innermost loop*/>
{
static inline void Loop(ElemType beta, array<ElemType*, 2> pointers, ElemType alpha, const OPFN& opfn, const ReductionOp& reductionOp,
const SmallVector<size_t>& regularOpDims, const array<SmallVector<ptrdiff_t>, 2>& regularStrides,
const SmallVector<size_t>& reducingOpDims, const array<SmallVector<ptrdiff_t>, 2>& reducingStrides)
{
ElemType* pa = pointers[0];
ElemType* pb = pointers[1];
size_t K = regularOpDims[0];
// special-case beta and alpha to allow the compiler to short-circuit it
if (beta != 0)
#pragma omp parallel for
for (int k = 0; k < (int) K; k++)
TensorOpIteration<ElemType, OPFN, ReductionOp, 2, true /*vectorizable*/, -1 /*no reduction*/, -1 /*scalar*/>::Loop(beta, array<ElemType*, 2>{pa + k, pb + k}, alpha, opfn, reductionOp, regularOpDims, regularStrides, reducingOpDims, reducingStrides);
else if (alpha != 1)
#pragma omp parallel for
for (int k = 0; k < (int) K; k++)
TensorOpIteration<ElemType, OPFN, ReductionOp, 2, true /*vectorizable*/, -1 /*no reduction*/, -1 /*scalar*/>::Loop(0, array<ElemType*, 2>{pa + k, pb + k}, alpha, opfn, reductionOp, regularOpDims, regularStrides, reducingOpDims, reducingStrides);
else
#pragma omp parallel for
for (int k = 0; k < (int) K; k++)
TensorOpIteration<ElemType, OPFN, ReductionOp, 2, true /*vectorizable*/, -1 /*no reduction*/, -1 /*scalar*/>::Loop(0, array<ElemType*, 2>{pa + k, pb + k}, 1, opfn, reductionOp, regularOpDims, regularStrides, reducingOpDims, reducingStrides);
}
};
template <class ElemType, typename OPFN, typename ReductionOp, size_t N, bool vectorizable, int m>
struct TensorOpIteration<ElemType, OPFN, ReductionOp, N, vectorizable, m, -1>
{
static inline void Loop(ElemType beta, array<ElemType*, N> pointers, ElemType alpha, const OPFN& opfn, const ReductionOp& reductionOp,
const SmallVector<size_t>&, const array<SmallVector<ptrdiff_t>, N>&,
const SmallVector<size_t>& reducingOpDims, const array<SmallVector<ptrdiff_t>, N>& reducingStrides)
{
// we are at element level for the result: perform the op (there may still be reduction)
ElemType val = TensorOpReduction<ElemType, OPFN, ReductionOp, N, m>::Loop(pointers, opfn, reductionOp, reducingOpDims, reducingStrides);
// scale
val *= alpha;
// combine with previous value in target matrix, then write it out
auto* pout = pointers.back();
if (beta != 0)
val += beta * *pout;
// save
*pout = val;
return;
}
};
// perform loop over regular index k and reducing index m for N operands (counting the output), the difference
// between TensorOpIteration and TensorArgOpIteration, is that the latter store the index of the result, instead of
// the result. The reason that they aren't combined is because of performance.
template <class ElemType, size_t N, int k>
struct TensorArgOpIteration
{
static inline void Loop(array<ElemType*, N> pointers,
const SmallVector<size_t>& regularOpDims, const array<SmallVector<ptrdiff_t>, N>& regularStrides,
const SmallVector<size_t>& reducingOpDims, const array<SmallVector<ptrdiff_t>, N>& reducingStrides, ElementWiseOperator reductionOp)
{
// non-scalar case: still nested result loops left
array<ptrdiff_t, N> strides;
for (size_t i = 0; i < N; i++) // N = a small constant, this will be unrolled
strides[i] = regularStrides[i][(size_t)k];
for (size_t dim = regularOpDims[(size_t)k]; dim-- > 0;)
{
// need to descend into one loop deeper
TensorArgOpIteration<ElemType, N, k - 1>::Loop(pointers, regularOpDims, regularStrides, reducingOpDims, reducingStrides, reductionOp);
// advance the pointers
for (size_t i = 0; i < N; i++)
pointers[i] += strides[i];
}
}
};
template <class ElemType, size_t N>
struct TensorArgOpIteration<ElemType, N, -1>
{
static inline void Loop(array<ElemType*, N> pointers,
const SmallVector<size_t>&, const array<SmallVector<ptrdiff_t>, N>&,
const SmallVector<size_t>& reducingOpDims, const array<SmallVector<ptrdiff_t>, N>& reducingStrides, ElementWiseOperator reductionOp)
{
// we are at element level for the result: perform the op (there may still be reduction)
auto val = TensorArgOpReduction<ElemType, N, 2>::ReduceAll(pointers, reducingOpDims, reducingStrides, reductionOp);
auto* pout = pointers.back();
*pout = (ElemType)val.second;
return;
}
};
// -----------------------------------------------------------------------
// map runtime parameters N to template parameters
// -----------------------------------------------------------------------
// tensor operation with k+1 dimensions (-1 means scalar)
template <class ElemType, typename OPFN, typename ReductionOp, size_t N, int k>
static void TensorOpWithRegularLoop(ElemType beta, const array<ElemType*, N>& pointers, ElemType alpha, const OPFN& opfn, ReductionOp reductionOp,
const SmallVector<size_t>& regularOpDims, const array<SmallVector<ptrdiff_t>, N>& regularStrides,
const SmallVector<size_t>& reducingOpDims, const array<SmallVector<ptrdiff_t>, N>& reducingStrides)
{
size_t dims = reducingOpDims.size();
switch (dims)
{
case 2:
return TensorOpIteration<ElemType, OPFN, ReductionOp, N, false /*vectorizable*/, 1, k>::Loop(beta, pointers, alpha, opfn, reductionOp, regularOpDims, regularStrides, reducingOpDims, reducingStrides);
case 1:
return TensorOpIteration<ElemType, OPFN, ReductionOp, N, false /*vectorizable*/, 0, k>::Loop(beta, pointers, alpha, opfn, reductionOp, regularOpDims, regularStrides, reducingOpDims, reducingStrides);
case 0:
{
// if all leading dimensions are 1, we can let the compiler do some unrolling
bool leadingAllOne = true;
for (size_t i = 0; i < N; i++)
leadingAllOne &= k >= 0 && regularStrides[i][0] == 1;
if (leadingAllOne) // special version that uses a hard-coded increment of 1 for all leading dimensions
return TensorOpIteration<ElemType, OPFN, ReductionOp, N, true /*vectorizable*/, -1, k>::Loop(beta, pointers, alpha, opfn, reductionOp, regularOpDims, regularStrides, reducingOpDims, reducingStrides);
else
return TensorOpIteration<ElemType, OPFN, ReductionOp, N, false /*vectorizable*/, -1, k>::Loop(beta, pointers, alpha, opfn, reductionOp, regularOpDims, regularStrides, reducingOpDims, reducingStrides);
}
default:
LogicError("TensorOp: %d non-flattened reduction dimensions are not supported.", (int) dims);
}
}
// tensor operation, generalized in number of arguments, operation already provided as a lambda
// This function now expands into different k.
template <class ElemType, typename OPFN, typename ReductionOp, size_t N>
static void TensorOpWithFnAndReduction(ElemType beta, array<ElemType*, N> pointers, ElemType alpha, const OPFN& opfn, const ReductionOp& reductionOp,
const array<size_t, N>& offsets,
const SmallVector<size_t>& regularOpDims, const array<SmallVector<ptrdiff_t>, N>& regularStrides,
const SmallVector<size_t>& reducingOpDims, const array<SmallVector<ptrdiff_t>, N>& reducingStrides)
{
for (size_t i = 0; i < N; i++) // N = a small constant, this will be unrolled
pointers[i] += offsets[i];
size_t dims = regularOpDims.size();
switch (dims)
{
case 4:
return TensorOpWithRegularLoop<ElemType, OPFN, ReductionOp, N, 3>(beta, pointers, alpha, opfn, reductionOp, regularOpDims, regularStrides, reducingOpDims, reducingStrides);
case 3:
return TensorOpWithRegularLoop<ElemType, OPFN, ReductionOp, N, 2>(beta, pointers, alpha, opfn, reductionOp, regularOpDims, regularStrides, reducingOpDims, reducingStrides);
case 2:
return TensorOpWithRegularLoop<ElemType, OPFN, ReductionOp, N, 1>(beta, pointers, alpha, opfn, reductionOp, regularOpDims, regularStrides, reducingOpDims, reducingStrides);
case 1:
return TensorOpWithRegularLoop<ElemType, OPFN, ReductionOp, N, 0>(beta, pointers, alpha, opfn, reductionOp, regularOpDims, regularStrides, reducingOpDims, reducingStrides);
case 0:
return TensorOpWithRegularLoop<ElemType, OPFN, ReductionOp, N, -1>(beta, pointers, alpha, opfn, reductionOp, regularOpDims, regularStrides, reducingOpDims, reducingStrides);
default:
LogicError("TensorOp: %d non-flattened input dimensions are not supported.", (int)dims);
}
}
// tensor operation, generalized in number of arguments, operation already provided as a lambda
// This function now expands into different reductionOps
template <class ElemType, typename OPFN, size_t N>
static void TensorOpWithFn(ElemType beta, array<ElemType*, N> pointers, ElemType alpha, const OPFN& opfn, ElementWiseOperator reductionOp,
const array<size_t, N>& offsets,
const SmallVector<size_t>& regularOpDims, const array<SmallVector<ptrdiff_t>, N>& regularStrides,
const SmallVector<size_t>& reducingOpDims, const array<SmallVector<ptrdiff_t>, N>& reducingStrides)
{
// BUGBUG: Using always 'double' as type of aggregator even for ElemType==float. Reason: otherwise some e2e test would fail as historically we
// used double for aggregator of sum. But:
// * for min and max reductions this is meaningless.
// * It is not consitent with what we do on GPU, there we aggregate on ElemType.
// * It costs performance.
// TODO: apdapt e2e tests to run with aggregator of type ElemType.
#define CaseTensorOpWithFnAndReduction(oper) \
case ElementWiseOperator::op##oper: \
return TensorOpWithFnAndReduction(beta, pointers, alpha, opfn, [](double a, double b) \
{ \
return Op##oper(a, b); \
}, \
offsets, regularOpDims, regularStrides, reducingOpDims, reducingStrides)
switch (reductionOp)
{
CaseTensorOpWithFnAndReduction(Sum);
CaseTensorOpWithFnAndReduction(LogSum);
CaseTensorOpWithFnAndReduction(Min);
CaseTensorOpWithFnAndReduction(Max);
CaseTensorOpWithFnAndReduction(ElementwiseProduct);
default:
LogicError("Specified ElementWiseOperator op %d not suported as reduction operation.", (int)reductionOp);
}
}
// -----------------------------------------------------------------------
// entry points from Matrix.cpp; also map op to a lambda
// -----------------------------------------------------------------------
// perform unary operation 'op' on a giving 'this', reinterpreting the matrices as tensors as specified by the dims and strides
// This maps 'op' to a lambda.
template <class ElemType>
void CPUMatrix<ElemType>::TensorOp(ElemType beta, const CPUMatrix<ElemType>& a, ElemType alpha, ElementWiseOperator op, ElementWiseOperator reductionOp,
const array<size_t, 2>& offsets,
const SmallVector<size_t>& regularOpDims, const array<SmallVector<ptrdiff_t>, 2>& regularStrides,
const SmallVector<size_t>& reducingOpDims, const array<SmallVector<ptrdiff_t>, 2>& reducingStrides)
{
if (reductionOp != ElementWiseOperator::opSum &&
reductionOp != ElementWiseOperator::opLogSum &&
reductionOp != ElementWiseOperator::opMin &&
reductionOp != ElementWiseOperator::opMax &&
reductionOp != ElementWiseOperator::opElementwiseProduct)
InvalidArgument("TensorOp: Unary reduction operations other than opMax, opMin, opSum, and opLogSum are not implemented.");
// TODO: Change the lambda to take a pointer and a number of elements, so that we can pass it 1 or 4 elements, in order for it to SSE-vectorize.
#define CaseUnaryTensorOp(oper) \
case ElementWiseOperator::op##oper: \
return TensorOpWithFn(beta, pointers, alpha, [](const array<ElemType*, 2>& pp) \
{ \
return Op##oper((*(pp[0]))); \
}, \
reductionOp, offsets, regularOpDims, regularStrides, reducingOpDims, reducingStrides)
array<ElemType*, 2> pointers = {a.Data(), Data()};
switch (op)
{
ForAllUnaryOps(CaseUnaryTensorOp);
default:
LogicError("TensorOp: Unknown unary op code %d.", (int) op);
}
}
// perform binary operation 'op' on a and b giving 'this', reinterpreting the matrices as tensors as specified by the dims and strides
// This maps 'op' to a lambda.
template <class ElemType>
void CPUMatrix<ElemType>::TensorOp(ElemType beta, const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, ElemType alpha, ElementWiseOperator op, ElementWiseOperator reductionOp,
const array<size_t, 3>& offsets,
const SmallVector<size_t>& regularOpDims, const array<SmallVector<ptrdiff_t>, 3>& regularStrides,
const SmallVector<size_t>& reducingOpDims, const array<SmallVector<ptrdiff_t>, 3>& reducingStrides)
{
if (reductionOp != ElementWiseOperator::opSum)
InvalidArgument("TensorOp (binary): The only permitted binary reduction operation is opSum.");
#define CaseBinaryTensorOp(oper) \
case ElementWiseOperator::op##oper: \
return TensorOpWithFn(beta, pointers, alpha, [](const array<ElemType*, 3>& pp) \
{ \
return Op##oper((*(pp[0])), (*(pp[1]))); \
}, \
reductionOp, offsets, regularOpDims, regularStrides, reducingOpDims, reducingStrides)
array<ElemType*, 3> pointers = {a.Data(), b.Data(), Data()};
switch (op)
{
ForAllBinaryOps(CaseBinaryTensorOp);
default:
LogicError("TensorOp: Unknown op binary code %d.", (int) op);
}
}
// perform ternary operation 'op' on a, and c giving 'this', reinterpreting the matrices as tensors as specified by the dims and strides
// This maps 'op' to a lambda.
template <class ElemType>
void CPUMatrix<ElemType>::TensorOp(ElemType beta, const CPUMatrix<ElemType>& a, const CPUMatrix<ElemType>& b, const CPUMatrix<ElemType>& c, ElemType alpha, ElementWiseOperator op, ElementWiseOperator reductionOp,
const array<size_t, 4>& offsets,
const SmallVector<size_t>& regularOpDims, const array<SmallVector<ptrdiff_t>, 4>& regularStrides,
const SmallVector<size_t>& reducingOpDims, const array<SmallVector<ptrdiff_t>, 4>& reducingStrides)
{
if (reductionOp != ElementWiseOperator::opSum)
InvalidArgument("TensorOp: The only permitted ternary reduction operation is opSum.");
#define CaseTernaryTensorOp(oper) \
case ElementWiseOperator::op##oper: \
return TensorOpWithFn(beta, pointers, alpha, [](const array<ElemType*, 4>& pp) \
{ \
return Op##oper((*(pp[0])), (*(pp[1])), (*(pp[2]))); \
}, \
reductionOp, offsets, regularOpDims, regularStrides, reducingOpDims, reducingStrides)
array<ElemType*, 4> pointers = {a.Data(), b.Data(), c.Data(), Data()};
switch (op)
{
ForAllTernaryOps(CaseTernaryTensorOp);
default:
LogicError("TensorOp: Unknown ternary op code %d.", (int) op);
}
}
template <class ElemType>
int CPUMatrix<ElemType>::Argmin() const
{
int minArg = -1;
ElemType minValue = std::numeric_limits<ElemType>::max();
#pragma omp parallel
{
int localMinArg = -1;
ElemType localMinValue = std::numeric_limits<ElemType>::max();
#pragma omp for
for (int index = 0; index < (int)GetNumElements(); ++index)
{
if (localMinValue > Data()[index])
{
localMinArg = index;
localMinValue = Data()[index];
}
// If we have more then one min value, select the one with lower index.
else if ((localMinValue == Data()[index]) && (localMinArg > index))
{
localMinArg = index;
}
}
#pragma omp critical
{
if (minValue > localMinValue)
{
minArg = localMinArg;
minValue = localMinValue;
}
// If we have more then one min value, select the one with lower index.
else if ((minValue == localMinValue) && (minArg > localMinArg))
{
minArg = localMinArg;
}
}
}
return minArg;
}
template <class ElemType>
int CPUMatrix<ElemType>::Argmax() const
{
int maxArg = -1;
ElemType maxValue = std::numeric_limits<ElemType>::min();
#pragma omp parallel
{
int localMaxArg = -1;
ElemType localMaxValue = std::numeric_limits<ElemType>::min();
#pragma omp for
for (int index = 0; index < (int)GetNumElements(); ++index)
{
if (localMaxValue < Data()[index])
{
localMaxArg = index;
localMaxValue = Data()[index];
}
// If we have more then one max value, select the one with lower index.
else if ((localMaxValue == Data()[index]) && (localMaxArg > index))
{
localMaxArg = index;
}
}
#pragma omp critical
{
if (maxValue < localMaxValue)
{
maxArg = localMaxArg;
maxValue = localMaxValue;
}
// If we have more then one max value, select the one with lower index.
else if ((maxValue == localMaxValue) && (maxArg > localMaxArg))
{
maxArg = localMaxArg;
}
}
}
return maxArg;
}
template <class ElemType>
int CPUMatrix<ElemType>::ArgOp(ElementWiseOperator reductionOp) const
{
switch (reductionOp)
{
case ElementWiseOperator::opArgmin:
return Argmin();
break;
case ElementWiseOperator::opArgmax:
return Argmax();
break;
}
InvalidArgument("ArgOp: Arg reduction operations other than opArgmax, and opArgmin are not implemented.");
return -1;
}
template <class ElemType>
void CPUMatrix<ElemType>::TensorArgOp(const CPUMatrix<ElemType>& a, ElementWiseOperator reductionOp,
const array<size_t, 2>& offsets,
const SmallVector<size_t>& regularOpDims, const array<SmallVector<ptrdiff_t>, 2>& regularStrides,
const SmallVector<size_t>& reducingOpDims, const array<SmallVector<ptrdiff_t>, 2>& reducingStrides)
{
if (reductionOp != ElementWiseOperator::opArgmin &&
reductionOp != ElementWiseOperator::opArgmax)
InvalidArgument("TensorOp: Arg reduction operations other than opArgmax, and opArgmin are not implemented.");
if (GetNumElements() == 1)
{
Data()[0] = (ElemType) a.ArgOp(reductionOp);
}
else
{
const size_t N = 2;
array<ElemType*, N> pointers = { a.Data(), Data() };
for (size_t i = 0; i < N; i++)
pointers[i] += offsets[i];
switch (regularOpDims.size())
{
case 2:
TensorArgOpIteration<ElemType, N, 1>::Loop(pointers, regularOpDims, regularStrides, reducingOpDims, reducingStrides, reductionOp);
break;
case 1:
TensorArgOpIteration<ElemType, N, 0>::Loop(pointers, regularOpDims, regularStrides, reducingOpDims, reducingStrides, reductionOp);
break;
case 0:
TensorArgOpIteration<ElemType, N, -1>::Loop(pointers, regularOpDims, regularStrides, reducingOpDims, reducingStrides, reductionOp);
break;
default:
LogicError("TensorOp: %d non-flattened input dimensions are not supported.", (int)regularOpDims.size());
}
}
}
template <class ElemType>
void CPUMatrix<ElemType>::ScatterValues(ElemType* indices, ElemType* value, ElemType* data, ElemType alpha, size_t num_indices, size_t rows, size_t cols, size_t indices_step)
{
if (!indices || !value || !data)
LogicError("ScatterValues: input data is null.");
#pragma omp parallel
{
int ithread = omp_get_thread_num();
int nthread = omp_get_num_threads();
for (auto i = 0; i < num_indices; i++)
{
auto col_r = indices[i * indices_step];
if (std::isnan(col_r) || col_r < 0)
continue;
auto col = (size_t)col_r;
//ignore the elements that is not partitioned into this thread
if (col % nthread != ithread)
continue;
if (col >= cols)
InvalidArgument("ScatterValues: Indices map out of bounds. %ld >= %ld", (long int)col, (long int)cols);
auto index = col * rows;
auto offset = i * rows;
for (auto j = 0; j < rows; j++)
data[index + j] = data[index + j] + alpha * value[offset + j];
}
}
}
// We use Matrix<char> as the backing store for QuantizedMatrix
// Let's explicitly instantiate the methods we need for that purpose
template CPUMatrix<char>::CPUMatrix(const size_t numRows, const size_t numCols);
template CPUMatrix<char>::CPUMatrix(const size_t numRows, const size_t numCols, char* pArray, const size_t matrixFlags);
template CPUMatrix<char>::CPUMatrix();
template CPUMatrix<char>::CPUMatrix(CPUMatrix<char> const&);
template CPUMatrix<char>::CPUMatrix(CPUMatrix<char>&&);
template size_t CPUMatrix<char>::LocateElement(size_t, size_t) const;
template CPUMatrix<char> CPUMatrix<char>::ColumnSlice(size_t startColumn, size_t numCols) const;
template CPUMatrix<char>& CPUMatrix<char>::operator=(CPUMatrix<char>&&);
template void CPUMatrix<char>::SetValue(const char);
template void CPUMatrix<char>::SetValue(const size_t numRows, const size_t numCols, char* pArray, size_t matrixFlags);
template void CPUMatrix<char>::SetValue(CPUMatrix<char> const&);
//template void CPUMatrix<char>::SetValue(GPUMatrix<char> const&);
//template void CPUMatrix<char>::SetValue(CPUSparseMatrix<char> const&);
//template void CPUMatrix<char>::SetValue(GPUSparseMatrix<char> const&);
template void CPUMatrix<char>::RequireSize(const size_t numRows, const size_t numCols, bool growOnly);
template void CPUMatrix<char>::Resize(const size_t numRows, const size_t numCols, bool growOnly);
template char* CPUMatrix<char>::CopyToArray(void) const;
template void CPUMatrix<char>::CopySection(size_t numRows, size_t numCols, char* dst, size_t colStride) const;
template void CPUMatrix<char>::Reshape(const size_t, const size_t);
// Support <short>
template CPUMatrix<short>::CPUMatrix(const size_t numRows, const size_t numCols);
template CPUMatrix<short>::CPUMatrix(const size_t numRows, const size_t numCols, short* pArray, const size_t matrixFlags);
template CPUMatrix<short>::CPUMatrix();
template CPUMatrix<short>::CPUMatrix(CPUMatrix<short> const&);
template CPUMatrix<short>::CPUMatrix(CPUMatrix<short>&&);
template size_t CPUMatrix<short>::LocateElement(size_t, size_t) const;
template CPUMatrix<short> CPUMatrix<short>::ColumnSlice(size_t startColumn, size_t numCols) const;
template CPUMatrix<short>& CPUMatrix<short>::operator=(CPUMatrix<short>&&);
template void CPUMatrix<short>::SetValue(const short);
template void CPUMatrix<short>::SetValue(const size_t numRows, const size_t numCols, short* pArray, size_t matrixFlags);
template void CPUMatrix<short>::SetValue(CPUMatrix<short> const&);
//template void CPUMatrix<short>::SetValue(GPUMatrix<short> const&);
//template void CPUMatrix<short>::SetValue(CPUSparseMatrix<short> const&);
//template void CPUMatrix<short>::SetValue(GPUSparseMatrix<short> const&);
template void CPUMatrix<short>::RequireSize(const size_t numRows, const size_t numCols, bool growOnly);
template void CPUMatrix<short>::Resize(const size_t numRows, const size_t numCols, bool growOnly);
template short* CPUMatrix<short>::CopyToArray(void) const;
template void CPUMatrix<short>::CopySection(size_t numRows, size_t numCols, short* dst, size_t colStride) const;
template void CPUMatrix<short>::Reshape(const size_t, const size_t);
template CPUMatrix<int>::CPUMatrix(const size_t, const size_t, int*, const size_t);
}}}
|
gmx_isdcmds.c | /*
*
* Tim Connolly - tconnolly@ucmerced.edu
* Copyright (c) 2014, Regents of the University of California
* Released under BSD 2-Clause License (see "LICENSE" file)
*
* This code was modified from the file src/tools/gmx_gyrate.c
*/
#include <math.h>
#include <string.h>
#include "libisdm.h"
#include "eigensolver.h"
#include <gromacs/statutil.h>
#include <gromacs/sysstuff.h>
#include <gromacs/typedefs.h>
#include <gromacs/smalloc.h>
#include <gromacs/macros.h>
#include <gromacs/vec.h>
#include <gromacs/pbc.h>
#include <gromacs/copyrite.h>
#include <gromacs/futil.h>
#include <gromacs/statutil.h>
#include <gromacs/index.h>
#include <gromacs/mshift.h>
#include <gromacs/xvgr.h>
#include <gromacs/rmpbc.h>
#include <gromacs/txtdump.h>
#include <gromacs/tpxio.h>
#include <gromacs/gstat.h>
#include <gromacs/gmx_ana.h>
void mat_mult_mat(real* mat1, real* mat2, int m, int n, int o, real* out, gmx_bool bMP)
{
/* Assume a is an array of doubles m by n in dimensions.
* Assume b is an array of doubles n by o in dimensions.
* Out should point to enough memory to store m by o doubles.
*/
int i, percent_calcs, finished_calcs;
percent_calcs = 1;
finished_calcs = 0;
#pragma omp parallel for schedule(dynamic) if (bMP)
for (i = 0; i < m; i++) {
int j, k;
for (k = 0; k < o; k++) {
out[(i * m) + k] = 0;
for (j = 0; j < n; j++) {
out[(i * m) + k] += mat1[(i * m) + j] * mat2[(j * n) + k];
}
}
// Output progress. OpenMP critical section.
#pragma omp critical
{
finished_calcs++;
while ((double)(finished_calcs) / m >= (double)percent_calcs / 100)
{
fprintf(stderr, "Approximately %i percent complete. \r", percent_calcs);
percent_calcs++;
}
} // End of OpenMP critical section.
} // End of OpenMP parallel for loop.
fprintf(stderr, "\n");
}
void scl_mult_mat(real scl, real* mat, int m, int n, real* out)
{
/* Multiply all elements of matrix mat by scalar scl.
*
* This should still work even if mat and out point to the same thing.
*/
int i, j;
for (i = 0; i < m; i++) {
for (j = 0; j < n; j++) {
out[(i * m) + j] = scl * mat[(i * m) + j];
}
}
}
void mat_transpose(real* mat, int m,int n, real* out)
{
/* Transpose m by n array of reals a into n by m array of reals out.
*/
int i, j;
for (i = 0; i < m; i++) {
for (j = 0; j < n; j++) {
out[(j * n) + i] = mat[(i * m) + j];
}
}
}
void calc_EISD(real** MDS, int nframes, int d, real** EISD)
{
/* Calculate the approximate ISD from the euclidean dimensionally reduced
* coordinates in MDS. Uses the number of dimensions specified by d. The
* number of structures is specified by nframes, and EISD should be a
* matrix of nframes x nframes.
*/
int i, j, k;
real kEISD;
for (i = 0; i < nframes; i++)
{
for (j = 0; j < nframes; j++)
{
// Same structure.
if (i == j)
{
EISD[i][j] = 0.0;
continue;
}
// Different structures.
EISD[i][j] = 0.0;
for (k = 0; k < d; k++)
{
kEISD = MDS[i][k] - MDS[j][k];
EISD[i][j] += kEISD * kEISD;
}
EISD[i][j] = sqrt(EISD[i][j]);
}
}
}
real calc_rcc(real** ISD, real** EISD, int nframes)
{
int i, j;
int N = nframes * (nframes - 1) / 2;
double sCov, sISD, sEISD, sISD2, sEISD2, mISD, mEISD, vISD, vEISD;
sCov = 0.0; sISD = 0.0; sEISD = 0.0; sISD2 = 0.0; sEISD2 = 0.0;
// Variances, means, and the means of squares.
for (i = 0; i < (nframes - 1); i++)
{
for (j = (i + 1); j < nframes; j++)
{
sISD += ISD[i][j];
sEISD += EISD[i][j];
sISD2 += ISD[i][j] * ISD[i][j];
sEISD2 += EISD[i][j] * EISD[i][j];
}
}
mISD = sISD / N;
mEISD = sEISD / N;
vISD = (sISD2 / N) - (mISD * mISD);
vEISD = (sEISD2 / N) - (mEISD * mEISD);
// Covariance.
for (i = 0; i < (nframes - 1); i++)
{
for (j = (i + 1); j < nframes; j++)
{
sCov += (ISD[i][j] - mISD) * (EISD[i][j] - mEISD);
}
}
// Correlation coefficient, R.
return (sCov / N) / (sqrt(vISD) * sqrt(vEISD));
}
int gmx_isdcmds(int argc,char *argv[])
{
const char *desc[] = {
"[TT]g_isdcmds[tt] implements classical multi-dimensional scaling ",
"by first calculating the matrix of inter-structure distances (ISD). ",
"The default ISDM if one is not, chosen by the user is RMSD. Only ",
"one ISDM can be chosen at a time. The -xpm option is required. An ",
"upper threshold for the ISD can be specified with the setmax option."
};
static gmx_bool bANG=FALSE, bDIH=FALSE, bANGDIH=FALSE, bDRMS=FALSE;
static gmx_bool bPHIPSI=FALSE, bSRMS=FALSE, bPCOR=FALSE, bMAMMOTH=FALSE;
static gmx_bool bACOR=FALSE, bESA=FALSE, bRMSD=FALSE, bMIR=FALSE;
static gmx_bool bRG=FALSE, bSRG=FALSE, bE2E=FALSE, bSE2E=FALSE;
static gmx_bool bANG2=FALSE, bDIH2=FALSE, bANGDIH2=FALSE, bANGDIH2G=FALSE;
static gmx_bool bRROT=FALSE, bSDRMS=FALSE, bPHIPSI2=FALSE, bRMSDIH=FALSE;
static int nt = -1;
static real setmax = -1.0;
static real rcutoff = 1.1;
static real noisefloor = 0.0;
static gmx_bool bNoise = FALSE;
static gmx_bool bMP = FALSE;
t_pargs pa[] = {
{ "-ang", FALSE, etBOOL, {&bANG},
"ISDM: Mean cosine of difference of backbone angles for each "
"set of three atoms. Assumes only CA atoms." },
{ "-dih", FALSE, etBOOL, {&bDIH},
"ISDM: Mean cosine of difference of backbone dihedrals for "
"each set of four atoms. Assumes only CA atoms." },
{ "-angdih", FALSE, etBOOL, {&bANGDIH},
"ISDM: Geometric mean of ang and dih ISDMs." },
{ "-ang2", FALSE, etBOOL, {&bANG2},
"ISDM: Attempts to euclideanize -ang." },
{ "-dih2", FALSE, etBOOL, {&bDIH2},
"ISDM: Attempts to euclideanize -dih." },
{ "-angdih2", FALSE, etBOOL, {&bANGDIH2},
"ISDM: Attempts to euclideanize -angdih." },
{ "-angdih2g", FALSE, etBOOL, {&bANGDIH2G},
"ISDM: Attempts to euclideanize -angdih. Geometric mean." },
{ "-rmsdih", FALSE, etBOOL, {&bRMSDIH},
"ISDM: Distances between points aligned by backbone dihedrals. " },
{ "-phipsi", FALSE, etBOOL, {&bPHIPSI},
"ISDM: Mean cosine of difference of phi and psi angles. "
"Assumes only backbone atoms." },
{ "-phipsi2", FALSE, etBOOL, {&bPHIPSI2},
"ISDM: Attempts to euclideanize -phipsi." },
{ "-drms", FALSE, etBOOL, {&bDRMS},
"ISDM: Mean difference of the paired distances matrix for all "
"atoms. Distance RMS(D)." },
{ "-sdrms", FALSE, etBOOL, {&bSDRMS},
"ISDM: Mean difference of the paired distances matrix for all "
"atoms scaled by 2 * geometric mean of Rg. Scaled distance "
"RMS(D)." },
{ "-rg", FALSE, etBOOL, {&bRG},
"ISDM: Calculates difference in Rg. Only compares size. " },
{ "-srg", FALSE, etBOOL, {&bSRG},
"ISDM: Calculates difference in Rg scaled by mean Rg. " },
{ "-e2e", FALSE, etBOOL, {&bE2E},
"ISDM: Calculates difference in end-to-end distance. " },
{ "-se2e", FALSE, etBOOL, {&bSE2E},
"ISDM: Calculates difference in end-to-end distance scaled "
"by (2 * Rg). " },
{ "-mir", FALSE, etBOOL, {&bMIR},
"ISDM: RMSD with the mirror of the reference structure. " },
{ "-rrot", FALSE, etBOOL, {&bRROT},
"ISDM: RMSD with random rotation of reference structure. " },
{ "-srms", FALSE, etBOOL, {&bSRMS},
"ISDM: Scaled RMSD. RMSD between the structure and reference "
"divided by the RMSD between the structure and mirror of the "
"reference created by multiplying the coordinates by the "
"negative identity matrix." },
{ "-rmsd", FALSE, etBOOL, {&bRMSD},
"ISDM: Standard RMSD." },
{ "-pcor", FALSE, etBOOL, {&bPCOR},
"ISDM: Position correlation. Correlation coefficient of the "
"positions is computed after alignment. Only positive "
"correlation is considered. Negative correlations are set to "
"zero." },
{ "-acor", FALSE, etBOOL, {&bACOR},
"ISDM: Angle correlation. Correlation coefficient of the "
"backbone angles (see ang ISDM) is computed. "
"Only positive correlation is considered. Negative correlations "
"are set to zero." },
{ "-mammoth", FALSE, etBOOL, {&bMAMMOTH},
"ISDM: MAMMOTH (MAtching Molecular Models Obtained from "
"Theory). Compares segments of residues chosen by sequence "
"alignment. Attempts to focus on correct secondary structure "
"moreso than tertiary structure. Source code modified for "
"compatibility. For this ISDM, please cite: \n\n"
"Ortiz, AR, Strauss, CE, Olmea, O (2002). MAMMOTH "
"(Matching molecular models obtained from theory): An automated "
"method for model comparison. Protein Sci. 11 (11), 2606–2621.\n"},
{ "-esa", FALSE, etBOOL, {&bESA},
"ISDM: Elastic shape analysis. Based on image analysis. "
"Warps structure onto the reference structure. Original source "
"code ported from Matlab to C. For this ISDM, please cite: \n\n"
"Liu W, Srivastava A, Zhang J (2011) A Mathematical Framework "
"for Protein Structure Comparison. PLoS Comput Biol 7(2): "
"e1001075.\n\nAssume only CA atoms." },
{ "-mp", FALSE, etBOOL, {&bMP},
"Use OpenMP commands for parallel processing. "},
{ "-nt", FALSE, etINT, {&nt},
"Limit the maximum number of threads for parallel processing. "},
{ "-noise", FALSE, etBOOL, {&bNoise},
"If this flag is set, additional information is sent to "
"stdout. The tool calculates the number of positive eigenvalues "
"and the number of positive eigenvalues that can be accounted "
"by two sources of noise. (1) Algorithmic noise based on the "
"negative eigenvalues, (2) thermal noise based on the expected "
"variation of folded proteins, and (3) the combined noise. "
"An estimate of thermal noise can be set manually with the "
"option -noisefloor." },
{ "-setmax", FALSE, etREAL, {&setmax},
"Set maximum value to threshold the xpm file. Must be greater "
"than the average inter-structure distance." },
{ "-rcutoff", FALSE, etREAL, {&rcutoff},
"Set cutoff value for the correlation coefficient. Only applies "
"if the -rcc output is set. The correlation coefficient (R) "
"will be calculated for each dimensional until rcutoff is "
"reached. The value should be between 0 and 1." },
{ "-noisefloor", FALSE, etREAL, {&noisefloor},
"Only applies if the -noise option is set. Manually sets the "
"the estimate of thermal noise used by the dimensionality "
"estimator." },
};
FILE *out;
t_trxstatus *status;
t_topology top;
int ePBC;
rvec *x, **frames;
real *nweights, *iweights, abscoor, maxcoor;
real *diff, **ISDmat, *P2, *J, *P2J, *B, *BT, *E, *V, *MDSa;
real **Va, **MDS, **EISD, *EISDm, Rcc, sumne, cumpe;
double *avgdiff, *maxdiff, avgISD, maxISD;
matrix box;
real t, xpm_max, pi = 3.14159265358979;
int *maxframe, *rnum, maxcoori;
int i, k, m, n, p, np, d, iatoms, natoms, nframes, nframes2;
int percent_calcs, finished_calcs, noptions;
gmx_bool bDFLT, bFit, bISD, bMDS, bEig, bVec, bRcc, bMRg, bDRg, bPy, bM;
char buf[256];
char *ISDM, *grpname, title[256], title2[256], *rname;
atom_id *index;
output_env_t oenv;
gmx_rmpbc_t gpbc=NULL;
const char *leg[] = { "D" };
#define NLEG asize(leg)
t_filenm fnm[] = {
{ efTRX, "-f", NULL, ffREAD },
{ efTPS, NULL, NULL, ffREAD },
{ efNDX, NULL, NULL, ffOPTRD },
{ efXVG, "-eig", "eigvals", ffOPTWR },
{ efXVG, "-rcc", "corrcoef", ffOPTWR },
{ efXVG, "-mrg", "mrgcorr", ffOPTWR },
{ efXVG, "-drg", "drgcorr", ffOPTWR },
{ efDAT, "-vec", "eigvecs", ffOPTWR },
{ efDAT, "-isd", "isdcsv", ffOPTWR },
{ efDAT, "-mds", "mdscsv", ffOPTWR },
{ efDAT, "-py", "mayapy", ffOPTWR },
{ efDAT, "-m", "disp6D", ffOPTWR },
};
#define NFILE asize(fnm)
int npargs;
CopyRight(stderr,argv[0]);
npargs = asize(pa);
// Lots of black magic with this one. The oenv is used by many things.
parse_common_args(&argc,argv,PCA_CAN_TIME | PCA_CAN_VIEW | PCA_BE_NICE,
NFILE,fnm,npargs,pa,asize(desc),desc,0,NULL,&oenv);
// If there are no options at command line, do default behavior.
bDFLT = !(bANG || bDIH || bANGDIH || bPHIPSI || bDRMS || bSRMS || bRMSD ||
bPCOR || bACOR || bMAMMOTH || bESA || bRG || bSRG || bE2E ||
bSE2E || bMIR || bRROT || bSDRMS || bANG2 || bDIH2 ||
bANGDIH2 || bPHIPSI2 || bANGDIH2G || bRMSDIH);
bFit = (bDFLT || bRMSD || bMIR || bSRMS || bPCOR);
#ifdef _OPENMP
if (nt > 0)
{
omp_set_num_threads(nt);
}
#endif
/* Reads the tpr file. Outputs a ton of info.
*
* I think this is the line that forces you to have a -s at prompt.
*/
read_tps_conf(ftp2fn(efTPS, NFILE, fnm), title, &top, &ePBC, &x, NULL, box, TRUE);
// Asks you to choose a selection of atoms at prompt.
get_index(&top.atoms, ftp2fn_null(efNDX, NFILE, fnm), 1, &iatoms, &index, &grpname);
// For error checking.
noptions = 0;
// Check which ISDM will be used. Default is RMSD.
if (bDFLT || bRMSD)
{
fprintf(stderr,"\nUsing RMSD as ISDM.\n");
ISDM = "RMSD";
noptions++;
}
if (bANG)
{
fprintf(stderr,"\nUsing backbone angles as ISDM.\n");
ISDM = "ANG";
noptions++;
}
if (bDIH)
{
fprintf(stderr,"\nUsing backbone dihedrals as ISDM.\n");
ISDM = "DIH";
noptions++;
}
if (bANG2)
{
fprintf(stderr,"\nUsing backbone angles as ISDM.\n");
ISDM = "ANG2";
noptions++;
}
if (bDIH2)
{
fprintf(stderr,"\nUsing backbone dihedrals as ISDM.\n");
ISDM = "DIH2";
noptions++;
}
if (bANGDIH)
{
fprintf(stderr,"\nUsing geometric mean of angles and dihedrals as ISDM.\n");
ISDM = "ANGDIH";
noptions++;
}
if (bANGDIH2)
{
fprintf(stderr,"\nUsing geometric mean of angles and dihedrals as ISDM.\n");
ISDM = "ANGDIH2";
noptions++;
}
if (bANGDIH2G)
{
fprintf(stderr,"\nUsing geometric mean of angles and dihedrals as ISDM.\n");
ISDM = "ANGDIH2G";
noptions++;
}
if (bRMSDIH)
{
fprintf(stderr,"\nUsing RMSD of dihedrals as ISDM.\n");
ISDM = "RMSDIH";
noptions++;
}
if (bPHIPSI)
{
fprintf(stderr,"\nUsing phi and psi angles as ISDM.\n");
ISDM = "PHIPSI";
noptions++;
}
if (bPHIPSI2)
{
fprintf(stderr,"\nUsing phi and psi angles as ISDM.\n");
ISDM = "PHIPSI2";
noptions++;
}
if (bDRMS)
{
fprintf(stderr,"\nUsing distance RMS as ISDM.\n");
ISDM = "DRMS";
noptions++;
}
if (bSDRMS)
{
fprintf(stderr,"\nUsing scaled distance RMS as ISDM.\n");
ISDM = "SDRMS";
noptions++;
}
if (bRG)
{
fprintf(stderr,"\nUsing Rg difference as ISDM.\n");
ISDM = "RG";
noptions++;
}
if (bSRG)
{
fprintf(stderr,"\nUsing scaled Rg difference as ISDM.\n");
ISDM = "SRG";
noptions++;
}
if (bE2E)
{
fprintf(stderr,"\nUsing end-to-end distance as ISDM.\n");
ISDM = "E2E";
noptions++;
}
if (bSE2E)
{
fprintf(stderr,"\nUsing scaled end-to-end distance as ISDM.\n");
ISDM = "SE2E";
noptions++;
}
if (bMIR)
{
fprintf(stderr,"\nUsing mirrored RMSD as ISDM.\n");
ISDM = "MIR";
noptions++;
}
if (bSRMS)
{
fprintf(stderr,"\nUsing scaled RMSD as ISDM.\n");
ISDM = "SRMS";
noptions++;
}
if (bPCOR)
{
fprintf(stderr,"\nUsing position correlation as ISDM.\n");
ISDM = "PCOR";
noptions++;
}
if (bACOR)
{
fprintf(stderr,"\nUsing backbone angle correlation as ISDM.\n");
ISDM = "ACOR";
noptions++;
}
if (bRROT)
{
fprintf(stderr,"\nUsing RMSD with random rotation as ISDM.\n");
noptions++;
// Additional stuff for option.
srand(time(NULL));
}
if (bMAMMOTH)
{
fprintf(stderr,"\nUsing MAMMOTH comparison as ISDM.\n");
noptions++;
// Additional stuff for option.
snew(rnum,iatoms);
//printf(stderr,"\nOutput sequence (tool).\n\n");
for (i = 0; i < iatoms; i++)
{
rname = *(top.atoms.resinfo[top.atoms.atom[index[i]].resind].name);
// Convert to integers.
if (!(strcmp(rname, "ALA")))
{
rnum[i] = 0;
}
else if (!(strcmp(rname, "CYS")))
{
rnum[i] = 1;
}
else if (!(strcmp(rname, "ASP")))
{
rnum[i] = 2;
}
else if (!(strcmp(rname, "GLU")))
{
rnum[i] = 3;
}
else if (!(strcmp(rname, "PHE")))
{
rnum[i] = 4;
}
else if (!(strcmp(rname, "GLY")))
{
rnum[i] = 5;
}
else if (!(strcmp(rname, "HIS")) || !(strcmp(rname, "HID")) ||
!(strcmp(rname, "HIE")) || !(strcmp(rname, "HIP")) ||
!(strcmp(rname, "HSD")) || !(strcmp(rname, "HSE")) ||
!(strcmp(rname, "HSP")))
{
rnum[i] = 6;
}
else if (!(strcmp(rname, "ILE")))
{
rnum[i] = 7;
}
else if (!(strcmp(rname, "LYS")))
{
rnum[i] = 8;
}
else if (!(strcmp(rname, "LEU")))
{
rnum[i] = 9;
}
else if (!(strcmp(rname, "MET")))
{
rnum[i] = 10;
}
else if (!(strcmp(rname, "ASN")))
{
rnum[i] = 11;
}
else if (!(strcmp(rname, "PRO")))
{
rnum[i] = 12;
}
else if (!(strcmp(rname, "GLN")))
{
rnum[i] = 13;
}
else if (!(strcmp(rname, "ARG")))
{
rnum[i] = 14;
}
else if (!(strcmp(rname, "SER")))
{
rnum[i] = 15;
}
else if (!(strcmp(rname, "THR")))
{
rnum[i] = 16;
}
else if (!(strcmp(rname, "VAL")))
{
rnum[i] = 17;
}
else if (!(strcmp(rname, "TRP")))
{
rnum[i] = 18;
}
else if (!(strcmp(rname, "TYR")))
{
rnum[i] = 19;
}
else
{
rnum[i] = 20;
}
}
}
if (bESA)
{
fprintf(stderr,"\nUsing ESA comparison as ISDM.\n"
"For this ISDM, please cite: \n\n"
"Liu W, Srivastava A, Zhang J (2011) A Mathematical Framework "
"for Protein Structure Comparison. PLoS Comput Biol 7(2): "
"e1001075.\n" );
noptions++;
}
// Throw an error if multiple -ISDM options were given by the user.
if (noptions > 1)
{
gmx_fatal(FARGS,"\nThis tool only supports using one optional ISDM at a time.\n");
}
// Check for error on -setmax before doing the calculations.
if (setmax != -1.0)
{
if (setmax <= 0.0)
{
gmx_fatal(FARGS,"\nThe argument for -setmax must be greater than 0.\n");
}
}
/* Opens trj. Reads first frame. Returns status. Allocates mem for x.
*
* Not sure which argument determines which atoms to pull info for.
*/
printf("\nCounting the number of frames.\n");
natoms=read_first_x(oenv, &status, ftp2fn(efTRX, NFILE, fnm), &t, &x, box);
// Now that we have iatoms, allocate memory for other arrays.
snew(nweights, natoms);
snew(iweights, iatoms);
snew(diff, iatoms);
// Initialize nweights to zeros.
for (i=0; i < natoms; i++)
{
nweights[i] = 0;
}
// Makes an array of weights. Necessary for reset_x.
for (i=0; i < iatoms; i++)
{
// Give a value for the weights.
nweights[(int)index[i]] = 1;
iweights[i] = 1;
// While we're at it, initialize diff to zeros.
diff[i] = 0;
}
// Output which files?
bEig = opt2bSet("-eig", NFILE, fnm);
bRcc = opt2bSet("-rcc", NFILE, fnm);
bMRg = opt2bSet("-mrg", NFILE, fnm);
bDRg = opt2bSet("-drg", NFILE, fnm);
bVec = opt2bSet("-vec", NFILE, fnm);
bISD = opt2bSet("-isd", NFILE, fnm);
bMDS = opt2bSet("-mds", NFILE, fnm);
bPy = opt2bSet("-py", NFILE, fnm);
bM = opt2bSet("-m", NFILE, fnm);
nframes = 0;
do
{
/* This loop doesn't do anything.
*
* It's just the most reliable way to find the number of frames.
*/
nframes++;
} while(read_next_x(oenv, status, &t, natoms, x, box));
// Close the trajectory.
close_trj(status);
// Throw an error if there aren't enough frames.
if (nframes < 2)
{
gmx_fatal(FARGS, "\nThe trajectory must have at least 2 frames.\n");
}
// Create an array to hold all frames.
snew(frames, nframes);
// Create arrays based on nframes.
snew(maxdiff, nframes);
snew(avgdiff, nframes);
snew(ISDmat, nframes);
for (i = 0; i < nframes; i++)
{
maxdiff[i] = 0.0;
avgdiff[i] = 0.0;
snew(ISDmat[i], nframes);
}
nframes2 = nframes * nframes;
/* Opens trj. Reads first frame. Returns status. Allocates mem for x.
*
* Not sure which argument determines which atoms to pull info for.
*/
printf("\nStoring trajectory to memory.\n");
natoms=read_first_x(oenv, &status, ftp2fn(efTRX, NFILE, fnm), &t, &x, box);
// Initialize index to keep track of current frame.
i = 0;
// This is for removing periodic boundary conditions.
gpbc = gmx_rmpbc_init(&top.idef, ePBC, natoms,box);
do
{
// Set aside new memory to store this frame.
snew(frames[i], iatoms);
// Removes periodic boundary conditions from x.
gmx_rmpbc(gpbc, natoms, box, x);
// Centers x. The NULL arguments are necessary to fit based on subset.
reset_x(natoms, NULL, natoms, NULL, x, nweights);
// Saves the current frame into frames.
for (n=0; n<iatoms; n++)
{
copy_rvec(x[(int)index[n]], frames[i][n]);
}
// Increment frame index.
i++;
} while(read_next_x(oenv, status, &t, natoms, x, box));
// Close the trajectory.
close_trj(status);
// Closes the thing that removes periodic boundary conditions.
gmx_rmpbc_done(gpbc);
// Initialize to 0.
maxISD = 0.0;
avgISD = 0.0;
/* Main calculation loop.
*/
printf("\nCalculating inter-structure distances. \n");
/* Originally this was designed to only loop through each pair of i and j
* one time to save half of the calculations. Eventually it became
* impractical to make sure that each ISDM was symmetrical, so now the
* algorithm takes the performance hit in favor of accuracy and simplicity.
*/
percent_calcs = 1;
finished_calcs = 0;
// Loop through reference frames.
#pragma omp parallel for schedule(dynamic) if (bMP)
for (i = 0; i < nframes; i++)
{
// Some memory required by each thread.
int j;
real ISD;
double dISD;
matrix rrot, rrotx, rroty, rrotz;
rvec *iframe, *jframe, *cframe, *rframe, rrot_xyz, xold;
if (bRROT)
{
snew(iframe,iatoms);
// Use up the first few random numbers that usually aren't random.
rrot_xyz[0] = (real)rand();
rrot_xyz[1] = (real)rand();
rrot_xyz[2] = (real)rand();
}
if (bFit)
{
snew(jframe,iatoms);
}
// Loop through fitting frames.
for (j = 0; j < nframes; j++)
{
/* In this section, we'll put calls to all of the ISDMs.
*
* Each should have its own if statement, so it is only executed
* if that option is specified at the command line.
*
* This function doesn't use the output stored in diff.
*/
// Skip for i == j (comparing structure with self).
if (i == j)
{
ISDmat[i][j] = 0;
continue;
}
// Copy ith frame.
if (bRROT)
{
// Make a copy of the ith frame.
copy_rvecn(frames[i], iframe, 0, iatoms);
rframe = iframe;
}
else
{
rframe = frames[i];
}
// Fit the jth frame.
if (bFit)
{
// Need to make a copy of the fit frame or bad stuff will happen.
copy_rvecn(frames[j], jframe, 0, iatoms);
// Aligns jframe to current reference frame.
do_fit(iatoms, iweights, frames[i], jframe);
cframe = jframe;
}
else
{
cframe = frames[j];
}
// Calls most ISDM options.
if (bDFLT || bRMSD || bSRMS || bRG || bSRG || bE2E || bSE2E ||
bMIR || bANG || bDIH || bANGDIH || bPHIPSI || bDRMS ||
bSDRMS || bPCOR || bACOR || bANG2 || bDIH2 || bANGDIH2 ||
bPHIPSI2 || bANGDIH2G || bRMSDIH)
{
ISD = call_ISDM(iatoms, cframe, rframe, ISDM);
}
// RMSD with random rotation. User gives -rrot option.
if (bRROT)
{
// Solve for three random numbers.
for (k = 0; k < 3; k++)
{
rrot_xyz[k] = 2.0 * pi * ((real)rand() / RAND_MAX) - pi;
}
// Create x, y, z rotation matrices and multiply.
clear_mat(rrotx);
clear_mat(rroty);
clear_mat(rrotz);
/* Rx = rrotx[rows][cols]
*
* | 1.0 | 0.0 | 0.0 |
* Rx = | 0.0 | cos(x) | sin(x) |
* | 0.0 | -sin(x) | cos(x) |
*/
rrotx[0][0] = 1.0;
rrotx[1][1] = cos(rrot_xyz[0]);
rrotx[2][2] = rrotx[1][1];
rrotx[1][2] = sin(rrot_xyz[0]);
rrotx[2][1] = -1.0 * rrotx[1][2];
/* Ry = rroty[rows][cols]
*
* | cos(x) | 0.0 | -sin(x) |
* Ry = | 0.0 | 1.0 | 0.0 |
* | sin(x) | 0.0 | cos(x) |
*/
rroty[1][1] = 1.0;
rroty[0][0] = cos(rrot_xyz[1]);
rroty[2][2] = rroty[0][0];
rroty[2][0] = sin(rrot_xyz[1]);
rroty[0][2] = -1.0 * rroty[2][0];
/* Rz = rrotz[rows][cols]
*
* | cos(x) | sin(x) | 0.0 |
* Rz = | -sin(x) | cos(x) | 0.0 |
* | 0.0 | 0.0 | 1.0 |
*/
rrotz[2][2] = 1.0;
rrotz[0][0] = cos(rrot_xyz[2]);
rrotz[1][1] = rrotz[0][0];
rrotz[0][1] = sin(rrot_xyz[2]);
rrotz[1][0] = -1.0 * rrotz[0][1];
// Multiply rotation matrices.
mmul(rrotx, rroty, rrot);
copy_mat(rrot, rrotx);
mmul(rrotx, rrotz, rrot);
// Apply random rotation.
for (k = 0; k < iatoms; k++)
{
for (m = 0; m < 3; m++)
{
xold[m] = rframe[k][m];
}
for (m = 0; m < 3; m++)
{
rframe[k][m] = 0;
for (n = 0; n < 3; n++)
{
rframe[k][m] += rrot[m][n] * xold[n];
}
}
}
// Calculate RMSD after rotation.
ISD = sqrt(calc_msd(iatoms, cframe, rframe));
}
// MAMMOTH. User gives -mammoth option.
if (bMAMMOTH)
{
// Calculate MAMMOTH comparison.
ISD = calc_mammoth(iatoms, cframe, rframe, rnum);
}
// ESA.
if (bESA)
{
// Calculate ESA comparison.
ISD = calc_esa(iatoms, cframe, rframe);
}
// Use doubles instead of reals for the summations.
dISD = (double)ISD;
// Add difference to the difference matrix.
ISDmat[i][j] = ISD;
// Update the max and avg difference for scaling.
if (dISD > maxdiff[i])
{
maxdiff[i] = dISD;
}
avgdiff[i] += dISD;
// Debugging.
//printf("On the %i th loop. \n",j);
}
// Average difference for each frame.
avgdiff[i] /= (nframes - 1);
// Update progress output. OpenMP critical section.
#pragma omp critical
{
finished_calcs += nframes;
while ((double)(finished_calcs) / nframes2 >= (double)percent_calcs / 100)
{
fprintf(stderr, "Approximately %i percent complete. \r", percent_calcs);
percent_calcs++;
}
} // End of OpenMP critical section.
// Free memory used in parallel section.
if (bRROT)
{
sfree(iframe);
}
if (bFit)
{
sfree(jframe);
}
} // End of OpenMP parallel for loop.
fprintf(stderr, "\n\n\n");
// Find the final average of differences.
for (i = 0; i < nframes; i++)
{
avgISD += avgdiff[i];
}
avgISD /= nframes;
int j;
if (bISD)
{
// Opens the output file.
out = opt2FILE("-isd", NFILE, fnm, "w");
// Write output.
for (i = 0; i < nframes; i++)
{
fprintf(out, "%12.8f", ISDmat[i][0]);
for (j = 1; j < nframes; j++)
{
fprintf(out, ",%12.8f", ISDmat[i][j]);
}
fprintf(out, "\n");
}
// Close the output file.
ffclose(out);
}
/* Implements Torgerson's classical multi-dimensional scaling (CMDS)
* algorithm.
*
* 1) Convert the ISD matrix to the squared proximities matrix (P2).
*
* 2) Perform double centering on P2.
* [B = (-1/2) * J * P2 * J, where J = I - (UnitMatrix / nframes)]
*
* 3) Solve for the eigenvalues and eigenvectors.
*
* 4) Keep only the dimensions corresponding to positive eigenvalues.
* The rest are imaginary dimensions.
* [The requirement to keep the dimension here is that both the
* eigenvalue and the root of the eigenvalue must be greater than
* zero to rule out dimensions below the precision limit.]
*
* 5) Sign convention. This may not be necessary.
*/
fprintf(stderr, "Performing MDS.\n");
// Allocate memory.
snew(J, nframes * nframes);
snew(P2, nframes * nframes);
snew(P2J, nframes * nframes);
snew(V, nframes * nframes);
snew(E, nframes);
snew(Va, nframes);
for (i = 0; i < nframes; i++)
{
Va[i] = &V[i * nframes];
}
// Step 1.
fprintf(stderr, "MDS step 1 of 5. \n");
for (i = 0; i < nframes; i++)
{
for (j = 0; j < nframes; j++)
{
P2[(i * nframes) + j] = ISDmat[i][j] * ISDmat[i][j];
}
}
// Step 2.
fprintf(stderr, "MDS step 2 of 5. \n");
// Constructs J.
for (i = 0; i < nframes; i++)
{
for (j = 0; j < nframes; j++)
{
if (i == j)
{
J[(i * nframes) + j] = 1.0 - (1.0 / nframes);
}
else
{
J[(i * nframes) + j] = -1.0 / nframes;
}
}
}
// Solve for B.
mat_mult_mat(P2, J, nframes, nframes, nframes, P2J, bMP);
B = P2; // Finished with the memory in P2. Reuse it to store B.
scl_mult_mat(-0.5, J, nframes, nframes, J);
mat_mult_mat(J, P2J, nframes, nframes, nframes, B, bMP);
// Step 3.
fprintf(stderr, "MDS step 3 of 5. \n");
// Fix assymetry in B caused by precision limits.
BT = J; // Finished with the memory in J. Reuse it to store BT.
mat_transpose(B, nframes, nframes, BT);
for (i = 0; i < nframes; i++)
{
for (j = 0; j < nframes; j++)
{
B[(i * nframes) + j] = (B[(i * nframes) + j] +
BT[(i * nframes) + j]) / 2.0;
}
}
// Call the eigensolver which uses a lapack backend.
// E and V are sorted ascending by eigensolver.
eigensolver(B, nframes, 0, nframes, E, V);
// Step 4.
fprintf(stderr, "MDS step 4 of 5. \n");
// Find eigenvalues > 0.0.
for (i = 0; i < nframes; i++)
{
if (E[i] > 0.0)
{
if (sqrt(E[i]) > 0.0)
{
p = i;
np = nframes - p;
break;
}
}
if (i == (nframes - 1))
{
gmx_fatal(FARGS,"\nThere are zero positive eigenvalues.\n");
}
}
// Save coordinates in reduced dimensions.
snew(MDSa, nframes * np);
snew(MDS, nframes);
for (i = 0; i < nframes; i++)
{
MDS[i] = &MDSa[np * i];
}
for (i = 0; i < nframes; i++)
{
for (j = 0; j < np; j++)
{
MDS[i][j] = sqrt(E[nframes - j - 1]) * Va[nframes - j - 1][i];
}
}
// Step 5.
fprintf(stderr, "MDS step 5 of 5. \n");
for (j = 0; j < np; j++)
{
maxcoor = -1.0;
for (i = 0; i < nframes; i++)
{
abscoor = abs(MDS[i][j]);
if (abscoor > maxcoor)
{
maxcoor = abscoor;
maxcoori = i;
}
}
if (MDS[maxcoori][j] < 0.0)
{
for (i = 0; i < nframes; i++)
{
MDS[i][j] *= -1.0;
}
}
}
// Output the eigenvectors.
if (bVec)
{
// Opens the output file.
out = opt2FILE("-vec", NFILE, fnm, "w");
// Write output.
for (j = 0; j < nframes; j++)
{
fprintf(out, "%15.6e", Va[0][j]);
for (i = 1; i < nframes; i++)
{
fprintf(out, ",%15.6e", Va[i][j]);
}
fprintf(out, "\n");
}
// Close the output file.
ffclose(out);
}
// Release memory.
sfree(J);
sfree(P2);
sfree(P2J);
sfree(V);
sfree(Va);
fprintf(stderr, "\nClassical MDS Complete. \n\n");
// Output the eigenvalues.
if (bEig)
{
// Opens the output file.
out = xvgropen(opt2fn("-eig", NFILE, fnm),
"MDS Eigenvalues",
"Dimension",
"Eigenvalue",
oenv);
// Write output.
for (i = 1; i <= nframes; i++)
{
// Print in reversed order.
fprintf(out, "%-6i %15.8f \n", i, E[nframes - i]);
}
// Close the output file.
ffclose(out);
}
// Estimate the number of dimensions explained by noise.
if (bNoise)
{
printf("\n\n");
printf("Positive eigenvalues correspond to real dimensions. ");
printf("Negative eigenvalues correspond to imaginary dimensions.\n\n");
// Sum the positive and negative eigenvalues.
cumpe = 0.0;
for (i = p; i < nframes; i++)
{
cumpe += E[i];
}
sumne = 0.0;
for (i = 0; i < p; i++)
{
sumne += E[i];
}
printf("Sum of positive eigenvalues: %12.6f \n", cumpe);
printf("Sum of negative eigenvalues: %12.6f \n", sumne);
// Output the explained noise.
printf("%-6i eigenvalues are positive.\n", np);
printf("%-6i eigenvalues are zero or negative.\n", nframes - np);
cumpe = 0.0;
for (i = p; i < nframes; i++)
{
cumpe += E[i];
if (cumpe > abs(sumne))
{
break;
}
}
printf("%-6i positive eigenvalues can be explained by negative "
"eigenvalues.\n", i - p);
cumpe = 0.0;
for (i = p; i < nframes; i++)
{
cumpe += E[i];
if (cumpe > noisefloor)
{
break;
}
}
printf("%-6i positive eigenvalues can be explained by estimated "
"thermal noise.\n", i - p);
cumpe = 0.0;
for (i = p; i < nframes; i++)
{
cumpe += E[i];
if (cumpe > (abs(sumne) + noisefloor))
{
break;
}
}
printf("%-6i positive eigenvalues can be explained by estimated "
"thermal noise and algorithmic noise combined.\n\n", i - p);
}
// Output dimensionally reduced coordinates.
if (bMDS)
{
// Opens the output file.
out = opt2FILE("-mds", NFILE, fnm, "w");
// Write output.
for (i = 0; i < nframes; i++)
{
fprintf(out, "%12.8f", MDS[i][0]);
for (j = 1; j < np; j++)
{
fprintf(out, ",%12.8f", MDS[i][j]);
}
fprintf(out, "\n");
}
// Close the output file.
ffclose(out);
}
// Allocates memory to store the approximated ISD.
if (bRcc || bMRg || bDRg || bPy || bM)
{
snew(EISD, nframes);
snew(EISDm, nframes * nframes);
for (i = 0; i < nframes; i++)
{
EISD[i] = &EISDm[nframes * i];
}
}
// Reduced dimensional visualization.
if (bPy)
{
// Calculate accuracy of the displayed results.
calc_EISD(MDS, nframes, 6, EISD);
Rcc = calc_rcc(ISDmat, EISD, nframes);
fprintf(stdout, "The accuracy for 6D MDS is R = %8.4f.\n\n", Rcc);
// Opens the output file.
out = opt2FILE("-py", NFILE, fnm, "w");
// Python script header (py).
fprintf(out, "# Plots MDS output in 6 dimensions:\n");
fprintf(out, "# x, y, z, r, g, b\n\n");
// Import modules (py).
fprintf(out, "from mayavi import mlab\n");
fprintf(out, "import numpy as np\n\n");
// Save data to numpy array (py).
fprintf(out, "# Save data to numpy array.\n");
fprintf(out, "MDS = np.array([[%8.4f", MDS[0][0]);
for (j = 1; j < 6; j++)
{
fprintf(out, ",%8.4f", MDS[0][j]);
}
fprintf(out, "]");
for (i = 1; i < nframes; i++)
{
fprintf(out, ",\n [%8.4f", MDS[i][0]);
for (j = 1; j < 6; j++)
{
fprintf(out, ",%8.4f", MDS[i][j]);
}
fprintf(out, "]");
}
fprintf(out, "])\n\n");
// Calculate box center and range, center at zero (py).
fprintf(out, "# Calculate box center and range.\n");
fprintf(out, "bctr = np.mean(MDS, 0)\n");
fprintf(out, "MDS = np.subtract(MDS, bctr)\n");
fprintf(out, "bmin = np.min(MDS) #- Rbead\n");
fprintf(out, "bmax = np.max(MDS) #+ Rbead\n\n");
// Split MDS by dimensions. Recenter and rescale rgb dimensions (py).
fprintf(out, "# Split MDS by dimensions. Recenter to 0.5.\n");
fprintf(out, "xyz, rgb = np.hsplit(MDS, 2)\n");
fprintf(out, "color_sf = 0.8 / (bmax - bmin)\n");
fprintf(out, "rgb = np.add(np.multiply(rgb, color_sf), 0.5)\n");
fprintf(out, "s = np.array([0.01])\n");
fprintf(out, "s = s[0]\n\n");
/*
* // Display first coordinate and set up figure (py).
* fprintf(out, "# Display first coordinate and set up figure.\n");
* fprintf(out, "x = xyz[0, 0]\n");
* fprintf(out, "y = xyz[0, 1]\n");
* fprintf(out, "z = xyz[0, 2]\n");
* fprintf(out, "r = rgb[0, 0]\n");
* fprintf(out, "g = rgb[0, 1]\n");
* fprintf(out, "b = rgb[0, 2]\n");
* fprintf(out, "if r > 1.0:\n r = 1.0\n");
* fprintf(out, "if r < 0.0:\n r = 0.0\n");
* fprintf(out, "if g > 1.0:\n g = 1.0\n");
* fprintf(out, "if g < 0.0:\n g = 0.0\n");
* fprintf(out, "if b > 1.0:\n b = 1.0\n");
* fprintf(out, "if b < 0.0:\n b = 0.0\n");
* fprintf(out, "mlab.points3d(x, y, z, color=(r, g, b), ");
* fprintf(out, "extent=[bmin, bmax, bmin, bmax, bmin, bmax])\n\n");
*/
// Display coordinates (py).
fprintf(out, "# Display coordinates.\n");
fprintf(out, "for i in range(0, %i):\n", nframes);
fprintf(out, " x = xyz[i, 0]\n");
fprintf(out, " y = xyz[i, 1]\n");
fprintf(out, " z = xyz[i, 2]\n");
fprintf(out, " r = rgb[i, 0]\n");
fprintf(out, " g = rgb[i, 1]\n");
fprintf(out, " b = rgb[i, 2]\n");
fprintf(out, " if r > 1.0:\n r = 1.0\n");
fprintf(out, " if r < 0.0:\n r = 0.0\n");
fprintf(out, " if g > 1.0:\n g = 1.0\n");
fprintf(out, " if g < 0.0:\n g = 0.0\n");
fprintf(out, " if b > 1.0:\n b = 1.0\n");
fprintf(out, " if b < 0.0:\n b = 0.0\n");
fprintf(out, " mlab.points3d(x, y, z, s, color=(r, g, b), scale_factor=1)\n\n");
// Close the output file.
ffclose(out);
}
// Reduced dimensional visualization.
if (bM)
{
// Calculate accuracy of the displayed results.
calc_EISD(MDS, nframes, 6, EISD);
Rcc = calc_rcc(ISDmat, EISD, nframes);
fprintf(stdout, "The accuracy for 6D MDS is R = %8.4f.\n\n", Rcc);
// Opens the output file.
out = opt2FILE("-m", NFILE, fnm, "w");
// Octave function and comments.
fprintf(out,
"function [MDSout, MDS] = disp6D(varargin)\n"
"%% function [MDSout, MDS] = disp6D(varargin)\n"
"%%\n"
"%% 'Delay' : Pause between frames (numeric, units = ps).\n"
"%% Setting Delay creates a movie-like output.\n"
"%% 'TimeStep' : Time per frame (numeric, units = ps).\n"
"%% 'NSims' : Display N simulations independently (numeric).\n"
"%% 'NAvg' : Runs an averaging window of size 2 * NAvg + 1.\n"
"%% 'Radius' : Sphere size (numeric).\n"
"%% 'Res' : Sphere resolution (numeric).\n"
"%% 'NSkip' : Only display every NSkip + 1 sphere (numeric).\n"
"%% 'NClust' : Enables clustering with n clusters (numeric).\n"
"%% 'Title' : Figure title (char).\n"
"%% 'PNGClust' : Create PNG of clustering (char).\n"
"%% 'PNGName' : Create PNG of CMDS (char).\n"
"%% 'GIFName' : Create animated GIF (char).\n"
"%% 'GIFStep' : Frames per image (numeric).\n"
"%% 'bShow' : Plot even if no image is written (logical).\n"
"%% 'ShowLine' : Connect spheres (logical).\n"
"%% 'Vis3D' : Better, but causes error in Octave (logical).\n"
"%% 'Out2D' : Output in 2D even if NSims > 1 (logical).\n"
"%%\n"
"%% Defaults : \n"
"%% No delay, 1.0 ps time step, one simulation, no averaging \n"
"%% window, radius auto, sphere resolution 6, no skipping, no \n"
"%% title, no PNG, no GIF, 1.0 frame GIF step, do not show \n"
"%% no line, no Vis3D, output MDSout in 2D.\n"
"%%\n"
"%% Plots MDS output in 6 dimensions:\n"
"%% x, y, z, r, g, b\n"
"\n"
);
// Defaults.
fprintf(out,
"%% Set defaults.\n"
"defDelay = -1.0;\n"
"defTimeStep = -1.0;\n"
"defNSims = -1.0;\n"
"defNAvg = -1.0;\n"
"defRadius = -1.0;\n"
"defRes = -1.0;\n"
"defNSkip = -1.0;\n"
"defNClust = -1.0;\n"
"defTitle = '';\n"
"defPNGClust = '';\n"
"defPNGName = '';\n"
"defGIFName = '';\n"
"defGIFStep = -1.0;\n"
"defbShow = false;\n"
"defShowLine = false;\n"
"defVis3D = false;\n"
"defOut2D = true;\n"
"\n"
);
fprintf(out,
"%% Initialize parser.\n"
"p = inputParser;\n"
"addOptional(p, 'Delay', defDelay, @isnumeric);\n"
"addOptional(p, 'TimeStep', defTimeStep, @isnumeric);\n"
"addOptional(p, 'NSims', defNSims, @isnumeric);\n"
"addOptional(p, 'NAvg', defNAvg, @isnumeric);\n"
"addOptional(p, 'Radius', defRadius, @isnumeric);\n"
"addOptional(p, 'Res', defRes, @isnumeric);\n"
"addOptional(p, 'NSkip', defNSkip, @isnumeric);\n"
"addOptional(p, 'NClust', defNClust, @isnumeric);\n"
"addOptional(p, 'Title', defTitle, @ischar);\n"
"addOptional(p, 'PNGClust', defPNGClust, @ischar);\n"
"addOptional(p, 'PNGName', defPNGName, @ischar);\n"
"addOptional(p, 'GIFName', defGIFName, @ischar);\n"
"addOptional(p, 'GIFStep', defGIFStep, @isnumeric);\n"
"addOptional(p, 'bShow', defbShow);\n"
"addOptional(p, 'ShowLine', defShowLine);\n"
"addOptional(p, 'Vis3D', defVis3D);\n"
"addOptional(p, 'Out2D', defOut2D);\n"
"\n"
"parse(p, varargin{:});\n"
"PNGClust = p.Results.PNGClust;\n"
"PNGName = p.Results.PNGName;\n"
"GIFName = p.Results.GIFName;\n"
"bShow = p.Results.bShow;\n"
"\n"
);
// Save data to matrix.
fprintf(out, "%% Save data to matrix called MDS.\n");
fprintf(out, "MDS = [%8.4f", MDS[0][0]);
for (j = 1; j < 6; j++)
{
fprintf(out, ", %8.4f", MDS[0][j]);
}
for (i = 1; i < nframes; i++)
{
fprintf(out, ";\n %8.4f", MDS[i][0]);
for (j = 1; j < 6; j++)
{
fprintf(out, ", %8.4f", MDS[i][j]);
}
}
fprintf(out, "];\n\n");
// Accuracy of MDS.
fprintf(out, "%% Print correlation coefficient of MDS and ISD.\n");
fprintf(out, "fprintf('The accuracy of MDS is: %%8.4f \\n', %8.4f)\n\n", Rcc);
// Test NAvg, NSkip, NSims, and NClust.
fprintf(out,
"%% Test NAvg, NSkip, NSims, and NClust.\n"
"NSims = p.Results.NSims;\n"
"NSkip = p.Results.NSkip;\n"
"NAvg = p.Results.NAvg;\n"
"NClust = p.Results.NClust;\n"
"if (rem(NSims, 1) ~= 0)\n"
" error('NSims should have a positive integer value.')\n"
"end\n"
"\n"
"if (rem(NSkip, 1) ~= 0)\n"
" error('NSkip should have a positive integer value.')\n"
"end\n"
"\n"
"if (rem(NAvg, 1) ~= 0)\n"
" error('NAvg should have a positive integer value.')\n"
"end\n"
"\n"
"if (rem(NClust, 1) ~= 0)\n"
" error('NClust should have a positive integer value.')\n"
"end\n"
"\n"
);
fprintf(out,
"%% Rearrange MDS matrix by simulation.\n"
"nframes = size(MDS, 1);\n"
"if (NSims < 1)\n"
" NSims = 1;\n"
" NPerSim = nframes;\n"
" MDSmat = MDS;\n"
"else\n"
" NSims = fix(NSims);\n"
" NPerSim = fix(nframes / NSims);\n"
" MDSmat = zeros(NPerSim, 6, NSims);\n"
" for i = 1:NSims\n"
" i1 = (i - 1) * NPerSim + 1;\n"
" i2 = i * NPerSim;\n"
" MDSmat(:, :, i) = MDS(i1:i2, :);\n"
" end\n"
"end\n"
);
fprintf(out,
"%% Apply averaging filter.\n"
"MDSout = MDSmat;\n"
"if (NAvg >= 1)\n"
" NAvg = fix(NAvg);\n"
" for i = 1:NSims\n"
" for j = 1:NPerSim\n"
" j1 = j - NAvg;\n"
" if (j1 < 1)\n"
" j1 = 1;\n"
" end\n"
" j2 = j + NAvg;\n"
" if (j2 > NPerSim)\n"
" j2 = NPerSim;\n"
" end\n"
" for k = 1:6\n"
" MDSijk = mean(MDSmat(j1:j2, k, i));\n"
" MDSout(j, k, i) = MDSijk;\n"
" end\n"
" end\n"
" end\n"
"end\n"
);
// Set bead radius. Calculate box center and range.
fprintf(out,
"%% Calculate plot limits.\n"
"bsize = max(max(max(MDSout))) - min(min(min(MDSout)));\n"
"if (p.Results.Radius < 0.0)\n"
" R = 0.01 * bsize;\n"
"else\n"
" R = p.Results.Radius;\n"
"end\n"
"bctr = mean(mean(MDSout, 3));\n"
"bmin = min(min(min(MDSout))) - R;\n"
"bmax = max(max(max(MDSout))) + R;\n"
"color_sf = 0.8 / bsize;\n"
"\n"
);
// Split MDS by dimensions. Recenter and rescale rgb dimensions.
fprintf(out,
"%% Split MDS by dimensions. Recenter rgb to 0.5.\n"
"x = zeros(NPerSim, NSims);\n"
"y = x;\n"
"z = x;\n"
"r = x;\n"
"g = x;\n"
"b = x;\n"
"for i = 1:NSims\n"
" x(:, i) = MDSout(:, 1, i);\n"
" y(:, i) = MDSout(:, 2, i);\n"
" z(:, i) = MDSout(:, 3, i);\n"
" r(:, i) = MDSout(:, 4, i);\n"
" g(:, i) = MDSout(:, 5, i);\n"
" b(:, i) = MDSout(:, 6, i);\n"
" \n"
" %% Rescale colors.\n"
" r(:, i) = (r(:, i) - bctr(4)) * color_sf + 0.5;\n"
" g(:, i) = (g(:, i) - bctr(5)) * color_sf + 0.5;\n"
" b(:, i) = (b(:, i) - bctr(6)) * color_sf + 0.5;\n"
"end\n"
"\n"
);
// Setup main figure.
fprintf(out, "%% Setup figure.\n");
fprintf(out, "n = %6i;\n", nframes);
fprintf(out,
"if (p.Results.Res < 0.0)\n"
" Res = 6;\n"
"else\n"
" Res = p.Results.Res;\n"
"end\n"
"[Sx, Sy, Sz] = sphere(Res);\n"
"Sx = R * Sx; Sy = R * Sy; Sz = R * Sz;\n"
"figure;\n"
"axis([bmin, bmax, bmin, bmax, bmin, bmax]);\n"
"\n"
"%% Choose axis display style.\n"
"if (p.Results.Vis3D)\n"
" axis('vis3d');\n"
"else\n"
" axis('equal');\n"
"end\n"
"\n"
);
// Display coordinates.
fprintf(out,
"%% Display 6D coordinates.\n"
"hold on;\n"
"if (NSkip < 1)\n"
" NSkip = 1;\n"
"else\n"
" NSkip = fix(NSkip);\n"
"end\n"
"\n"
"if (~strcmp(GIFName, '') || ~strcmp(PNGName, '') || bShow)\n"
" for i = 1:NPerSim\n"
" if (p.Results.Delay > 0.0)\n"
" pause(p.Results.Delay);\n"
" end\n"
" if (p.Results.TimeStep > 0.0)\n"
" iTime = num2str(i * p.Results.TimeStep);\n"
" iTime = strcat(iTime,' ns');\n"
" else\n"
" iTime = '';\n"
" end\n"
" iTitle = strcat(p.Results.Title,' ',iTime);\n"
" title(iTitle);\n"
" \n"
" for j = 1:NSims\n"
" if (mod(i, NSkip) == 0)\n"
" c = [r(i, j), g(i, j), b(i, j)];\n"
" h = surf(Sx + x(i, j), Sy + y(i, j), Sz + z(i, j));\n"
" set(h, 'FaceColor', c, 'EdgeColor', 'none');\n"
" end\n"
" end\n"
" if (~strcmp(GIFName, ''))\n"
" if (i == 1)\n"
" n = 0;\n"
" f = getframe(gcf);\n"
" im = frame2im(f);\n"
" [imind,cm] = rgb2ind(im,256);\n"
" imwrite(imind, cm, GIFName, 'gif', 'Loopcount', inf);\n"
" continue\n"
" end\n"
" n = n + 1;\n"
" if (n >= p.Results.GIFStep)\n"
" n = 0;\n"
" f = getframe(gcf);\n"
" im = frame2im(f);\n"
" [imind,cm] = rgb2ind(im,256);\n"
" imwrite(imind, cm, GIFName, 'gif', 'WriteMode', 'append');\n"
" end\n"
" end\n"
" end\n"
" if (~strcmp(PNGName, ''))\n"
" print(PNGName, '-dpng')\n"
" end\n"
"end\n"
"\n"
);
// Line option.
fprintf(out,
"%% Optionally draw a line to show the time component.\n"
"if (p.Results.ShowLine)\n"
" c = [0.75, 0.75, 0.75];\n"
" plot3(x, y, z, 'LineWidth', 1, 'Color', c);\n"
"end\n"
"hold off;\n"
"\n"
);
// Convert MDSout.
fprintf(out,
"%% Convert MDSout.\n"
"if (p.Results.Out2D || (NClust >= 1))\n"
" MDSmat = zeros(NPerSim * NSims, 6);\n"
" for i = 1:NSims\n"
" i1 = (i - 1) * NPerSim + 1;\n"
" i2 = i * NPerSim;\n"
" MDSmat(i1:i2, :) = MDSout(:, :, i);\n"
" end\n"
" if (p.Results.Out2D)\n"
" MDSout = MDSmat;\n"
" end\n"
"end\n"
"\n"
);
// Apply kmeans clustering.
fprintf(out,
"%% Apply clustering.\n"
"if (NClust >= 1)\n"
" figure;\n"
" colormap(gcf, jet(NClust));\n"
" idx = kmeans(MDSmat, NClust);\n"
" for i = 1:NClust\n"
" end\n"
"end\n"
"\n"
);
// Close .m script.
fprintf(out, "end");
// Close the output file.
ffclose(out);
}
// Tests the accuracy of the dimensionally reduced coordinates.
if (bRcc)
{
// Error checking for rcutoff.
if (rcutoff < 0.0)
{
gmx_fatal(FARGS,"\nThe argument for -rcutoff must be greater "
"than or equal to 0.\n");
}
fprintf(stderr, "\nCalculating accuracy of dimensionality reduction."
"\n");
// Opens the output file.
out = xvgropen(opt2fn("-rcc", NFILE, fnm),
"Accuracy of Dimensionality Reduction",
"Dimension",
"Correlation Coefficient, R",
oenv);
for (d = 1; d <= np; d++)
{
// Calculate correlation coefficient.
calc_EISD(MDS, nframes, d, EISD);
Rcc = calc_rcc(ISDmat, EISD, nframes);
// Write to file.
fprintf(out, "%-6i %12.8f \n", i, Rcc);
if (Rcc > rcutoff)
{
break;
}
}
// Close file.
ffclose(out);
printf("\nThe rcutoff is: %12.8f \n", rcutoff);
printf("The final correlation coefficient is: %12.8f \n", Rcc);
printf("The estimated dimensionality is: %-6i \n", d);
}
// Tests correlation between ISD and Rg.
if (bMRg)
{
fprintf(stderr, "\nCalculating correlation of ISD with Rg.\n");
// Opens the output file.
out = xvgropen(opt2fn("-mrg", NFILE, fnm),
"Correlation of Rg with ISD",
"Radius of Gyration, Rg (nm)",
"ISD",
oenv);
/* Main calculation loop.
*/
printf("\nCalculating Rg matrix. \n");
percent_calcs = 1;
// Loop through reference frames.
for (i = 0; i < nframes; i++)
{
// Loop through fitting frames.
for (j = 0; j < nframes; j++)
{
// Skip for i == j (comparing structure with self).
if (i == j)
{
EISD[i][j] = 0.0;
continue;
}
EISD[i][j] = call_ISDM(iatoms, frames[j], frames[i], "MRG");
// Write to file.
fprintf(out, "%12.8f %12.8f \n", EISD[i][j], ISDmat[i][j]);
}
// Update progress output.
while ((double)(i+1)/nframes >= (double)percent_calcs/100)
{
fprintf(stderr, "Approximately %i percent complete. \r",
percent_calcs);
percent_calcs++;
}
}
Rcc = calc_rcc(ISDmat, EISD, nframes);
printf("The Rg vs ISD correlation coefficient is: %12.8f \n", Rcc);
// Close file.
ffclose(out);
}
// Tests correlation between ISD and Rg difference.
if (bDRg)
{
fprintf(stderr, "\nCalculating correlation of ISD with Rg difference."
"\n");
// Opens the output file.
out = xvgropen(opt2fn("-drg", NFILE, fnm),
"Correlation of Rg difference with ISD",
"Radius of Gyration Difference (nm)",
"ISD",
oenv);
/* Main calculation loop.
*/
printf("\nCalculating Rg difference matrix. \n");
percent_calcs = 1;
// Loop through reference frames.
for (i = 0; i < nframes; i++)
{
// Loop through fitting frames.
for (j = 0; j < nframes; j++)
{
// Skip for i == j (comparing structure with self).
if (i == j)
{
EISD[i][j] = 0;
continue;
}
EISD[i][j] = call_ISDM(iatoms, frames[j], frames[i], "RG");
// Write to file.
fprintf(out, "%12.8f %12.8f \n", EISD[i][j], ISDmat[i][j]);
}
// Update progress output.
while ((double)(i+1)/nframes >= (double)percent_calcs/100)
{
fprintf(stderr, "Approximately %i percent complete. \r",
percent_calcs);
fflush(stderr);
percent_calcs++;
}
}
Rcc = calc_rcc(ISDmat, EISD, nframes);
printf("The Rg difference vs ISD correlation coefficient is: "
"%12.8f \n", Rcc);
// Close file.
ffclose(out);
}
// Closing.
thanx(stderr);
return 0;
}
|
main.c | /*BHEADER****************************************************************
* (c) 2007 The Regents of the University of California *
* *
* See the file COPYRIGHT_and_DISCLAIMER for a complete copyright *
* notice and disclaimer. *
* *
*EHEADER****************************************************************/
//--------------
// A micro kernel
//--------------
#include <stdio.h>
#include <stdlib.h>
#include "omp.h"
#include "headers.h"
//
const int testIter = 1000;//50000;//500;
double totalWallTime = 0.0;
//
void test_Matvec();
void test_Relax();
void test_Axpy();
//
int main(int argc, char *argv[])
{
double t0 = 0.0,
t1 = 0.0,
del_wtime = 0.0;
int max_num_threads;
printf("\n");
printf("//------------ \n");
printf("// \n");
printf("// CORAL AMGmk Benchmark Version 1.0 \n");
printf("// \n");
printf("//------------ \n");
#pragma omp parallel
#pragma omp master
max_num_threads = omp_get_num_threads();
printf("\nmax_num_threads = %d \n\n",max_num_threads );
printf("\n testIter = %d \n\n", testIter );
t0 = omp_get_wtime();
// Matvec
totalWallTime = 0.0;
test_Matvec();
printf("\n");
printf("//------------ \n");
printf("// \n");
printf("// MATVEC\n");
printf("// \n");
printf("//------------ \n");
printf("\nWall time = %f seconds. \n", totalWallTime);
// Relax
totalWallTime = 0.0;
test_Relax();
//__WHATIF__BEGIN__
printf("\n");
printf("//------------ \n");
printf("// \n");
printf("// Relax\n");
printf("// \n");
printf("//------------ \n");
printf("\nWall time = %f seconds. \n", totalWallTime);
// Axpy
totalWallTime = 0.0;
test_Axpy();
printf("\n");
printf("//------------ \n");
printf("// \n");
printf("// Axpy\n");
printf("// \n");
printf("//------------ \n");
printf("\nWall time = %f seconds. \n", totalWallTime);
t1 = omp_get_wtime();;
del_wtime = t1 - t0;
printf("\nTotal Wall time = %f seconds. \n", del_wtime);
//__WHATIF__END__
return 0;
}
void test_Matvec()
{
double t0 = 0.0,
t1 = 0.0;
hypre_CSRMatrix *A;
hypre_Vector *x, *y, *sol;
int nx, ny, nz, i;
double *values;
double *y_data, *sol_data;
double error, diff;
nx = 50; /* size per proc nx*ny*nz */
ny = 50;
nz = 50;
values = hypre_CTAlloc(double, 4);
values[0] = 6;
values[1] = -1;
values[2] = -1;
values[3] = -1;
A = GenerateSeqLaplacian(nx, ny, nz, values, &y, &x, &sol);
hypre_SeqVectorSetConstantValues(x,1);
hypre_SeqVectorSetConstantValues(y,0);
t0 = omp_get_wtime();
for (i=0; i<testIter; ++i)
hypre_CSRMatrixMatvec(1,A,x,0,y);
t1 = omp_get_wtime() ;
totalWallTime += t1 - t0;
y_data = hypre_VectorData(y);
sol_data = hypre_VectorData(sol);
error = 0;
for (i=0; i < nx*ny*nz; i++)
{
diff = fabs(y_data[i]-sol_data[i]);
if (diff > error) error = diff;
}
if (error > 0) printf(" \n Matvec: error: %e\n", error);
hypre_TFree(values);
hypre_CSRMatrixDestroy(A);
hypre_SeqVectorDestroy(x);
hypre_SeqVectorDestroy(y);
hypre_SeqVectorDestroy(sol);
}
void test_Relax()
{
double t0 = 0.0,
t1 = 0.0;
hypre_CSRMatrix *A;
hypre_Vector *x, *y, *sol;
int nx, ny, nz, i;
double *values;
double *x_data;
double diff, error;
nx = 50; /* size per proc nx*ny*nz */
ny = 50;
nz = 50;
values = hypre_CTAlloc(double, 4);
values[0] = 6;
values[1] = -1;
values[2] = -1;
values[3] = -1;
A = GenerateSeqLaplacian(nx, ny, nz, values, &y, &x, &sol);
hypre_SeqVectorSetConstantValues(x,1);
t0 = omp_get_wtime();
for (i=0; i<testIter; ++i)
hypre_BoomerAMGSeqRelax(A, sol, x);
t1 = omp_get_wtime();
totalWallTime += t1 - t0;
x_data = hypre_VectorData(x);
error = 0;
for (i=0; i < nx*ny*nz; i++)
{
diff = fabs(x_data[i]-1);
if (diff > error) error = diff;
}
if (error > 0) printf(" \n Relax: error: %e\n", error);
hypre_TFree(values);
hypre_CSRMatrixDestroy(A);
hypre_SeqVectorDestroy(x);
hypre_SeqVectorDestroy(y);
hypre_SeqVectorDestroy(sol);
}
void test_Axpy()
{
double t0 = 0.0,
t1 = 0.0;
hypre_Vector *x, *y;
int nx, i;
double alpha=0.5;
double diff, error;
double *y_data;
nx = 125000; /* size per proc */
x = hypre_SeqVectorCreate(nx);
y = hypre_SeqVectorCreate(nx);
hypre_SeqVectorInitialize(x);
hypre_SeqVectorInitialize(y);
hypre_SeqVectorSetConstantValues(x,1);
hypre_SeqVectorSetConstantValues(y,1);
t0 = omp_get_wtime();
for (i=0; i<testIter; ++i)
hypre_SeqVectorAxpy(alpha,x,y);
t1 = omp_get_wtime();
y_data = hypre_VectorData(y);
error = 0;
for (i=0; i < nx; i++)
{
diff = fabs(y_data[i]-1-0.5*(double)testIter);
if (diff > error) error = diff;
}
if (error > 0) printf(" \n Axpy: error: %e\n", error);
totalWallTime += t1 - t0;
hypre_SeqVectorDestroy(x);
hypre_SeqVectorDestroy(y);
}
|
coordination.c | /*
* Copyright (C) 2017 by Benedict Paten (benedictpaten@gmail.com)
*
* Released under the MIT license, see LICENSE.txt
*/
#include "margin.h"
// OpenMP
#if defined(_OPENMP)
#include <omp.h>
#define CELL_BUFFER_SIZE 1000
#endif
/*
* Functions to create a set of read partitioning HMMs that include a given input set of reads.
*/
stRPHmm *getNextClosestNonoverlappingHmm(stRPHmm *hmm1, stSortedSet *readHmms) {
/*
* Returns the HMM from the set readHmms that does not overlap hmm1
* but whose start coordinate is closest to
* the end coordinate of hmm1. If does not exist returns NULL.
*/
// Iterator in the set starting from hmm1
assert(stSortedSet_search(readHmms, hmm1) == hmm1);
stSortedSetIterator *it = stSortedSet_getIteratorFrom(readHmms, hmm1);
stRPHmm *hmm2 = stSortedSet_getNext(it);
assert(hmm2 == hmm1);
// For each hmm in readHmms whose coordinate is >= than hmm1's
while ((hmm2 = stSortedSet_getNext(it)) != NULL) {
// Compare the hmm coordinates just to check that hmm2 has a coordinate >= to hmm1s
int i = stRPHmm_cmpFn(hmm1, hmm2);
assert(i <= 0);
// If hmm1 and hmm2 are on different references, then hmm2 is the closest non-overlapping
// hmm to hmm1 in reference space
i = strcmp(hmm1->ref->referenceName, hmm2->ref->referenceName);
if (i != 0) {
break;
}
// If hmm2 does not overlap hmm1 it must be the closest non-overlapping hmm to hmm1
if (hmm1->refStart + hmm1->refLength <= hmm2->refStart) {
break;
}
}
// Cleanup
stSortedSet_destructIterator(it);
return hmm2;
}
stSortedSet *makeComponent(stRPHmm *hmm, stSet *components, stHash *componentsHash) {
/*
* Create a component containing hmm and add the component to components.
*/
stSortedSet *component = stSortedSet_construct3(stRPHmm_cmpFn, NULL);
stSortedSet_insert(component, hmm);
stSet_insert(components, component);
assert(stHash_search(componentsHash, hmm) == NULL);
stHash_insert(componentsHash, hmm, component);
return component;
}
stSet *getOverlappingComponents(stList *tilingPath1, stList *tilingPath2) {
/*
* Two hmms overlap if their reference coordinate intervals overlaps.
* The transitive closure of the overlap relation
* partitions a set of hmms into connected components.
* This function returns this partition for the hmms in tilingPath1
* and tilingPath2, each of which is a set of hmms sorted by reference
* coordinate and which do not overlap in reference
* coordinates. Each component is a stSortedSet.
*/
// A map of hmms to components
stHash *componentsHash = stHash_construct();
// The set of components
stSet *components = stSet_construct2((void (*)(void *)) stSortedSet_destruct);
// The "lagging" index of the hmm in tilingPath2 that could possibly overlap hmm1
int64_t j = 0;
// For each hmm in tilingPath1, in order
for (int64_t i = 0; i < stList_length(tilingPath1); i++) {
stRPHmm *hmm1 = stList_get(tilingPath1, i);
// Start with the component being undefined
stSortedSet *component = NULL;
// The "leading" index of the hmm in tilingPath2 that could possibly overlap hmm1
int64_t k = 0;
// While there exists an hmm in tilingPath2 that precedes or overlaps with hmm1
while (j + k < stList_length(tilingPath2)) {
stRPHmm *hmm2 = stList_get(tilingPath2, j + k); // Note the j+k
// If hmm1 and hmm2 overlap
if (stRPHmm_overlapOnReference(hmm1, hmm2)) {
// The leading index is increased
k++;
// If component is still NULL
if (component == NULL) {
// Look for a component for hmm2
component = stHash_search(componentsHash, hmm2);
// If hmm2 has no component make one
if (component == NULL) {
component = makeComponent(hmm2, components, componentsHash);
}
// Add hmm1 to the component
assert(stSortedSet_search(component, hmm1) == NULL);
assert(stHash_search(componentsHash, hmm1) == NULL);
stSortedSet_insert(component, hmm1);
stHash_insert(componentsHash, hmm1, component);
}
// Otherwise component is defined
else {
// Add hmm2 to the component
assert(stSortedSet_search(component, hmm2) == NULL);
assert(stHash_search(componentsHash, hmm2) == NULL); // Impossible to be defined,
// as implies that two
// hmms in tilingPath2 each both overlap two hmms in tilingPath1.
stSortedSet_insert(component, hmm2);
stHash_insert(componentsHash, hmm2, component);
}
}
// Else hmm1 and hmm2 do not overlap
else {
// If hmm1 occurs before hmm2 in the reference ordering
if (stRPHmm_cmpFn(hmm1, hmm2) < 0) {
// If has no component, make a trivial component containing just hmm1
// (it doesn't overlap with any other hmm)
if (component == NULL) {
component = makeComponent(hmm1, components, componentsHash);
}
// Done with hmm1
break;
}
// else hmm2 occurs before hmm1 in the reference ordering
else {
// Add hmm2 to a trivial component if it does not overlap an HMM in tiling path1
if (stHash_search(componentsHash, hmm2) == NULL) {
makeComponent(hmm2, components, componentsHash);
}
// Increase the lagging index as hmm1 and proceding hmms can not overlap with hmm2
j++;
}
}
}
if (component == NULL) {
//
assert(stHash_search(componentsHash, hmm1) == NULL);
makeComponent(hmm1, components, componentsHash);
}
}
// For any remaining hmms in tilingPath2 that have not been placed in a component
// put them in a component
while (j < stList_length(tilingPath2)) {
stRPHmm *hmm2 = stList_get(tilingPath2, j++);
if (stHash_search(componentsHash, hmm2) == NULL) {
makeComponent(hmm2, components, componentsHash);
}
}
// Cleanup
stHash_destruct(componentsHash);
return components;
}
stList *getTilingPaths(stSortedSet *hmms) {
/*
* Takes set of hmms ordered by reference coordinate (see stRPHmm_cmpFn) and returns
* a list of tiling paths. Each tiling path consisting of maximal sequences of hmms
* that do not overlap. Destroys sortedSet in the process.
*/
stList *tilingPaths = stList_construct();
while (stSortedSet_size(hmms) > 0) {
// Make an empty tiling path and add to set of tiling paths built so far
stList *tilingPath = stList_construct();
stList_append(tilingPaths, tilingPath);
// Get the hmm with lowest reference coordinate and add to the tiling path
stRPHmm *hmm = stSortedSet_getFirst(hmms);
assert(hmm != NULL);
assert(stSortedSet_search(hmms, hmm) == hmm);
stList_append(tilingPath, hmm);
// While it exists, get the next closest non-overlapping hmm
// and add to the tiling path progressively, removing the chain of hmms from the
// set of hmms left to tile
stRPHmm *hmm2;
while ((hmm2 = getNextClosestNonoverlappingHmm(hmm, hmms)) != NULL) {
stSortedSet_remove(hmms, hmm);
stList_append(tilingPath, hmm2);
hmm = hmm2;
assert(stSortedSet_search(hmms, hmm) == hmm);
}
stSortedSet_remove(hmms, hmm);
}
// Cleanup the input set
stSortedSet_destruct(hmms);
return tilingPaths;
}
stList *getTilingPaths2(stList *profileSeqs, stRPHmmParameters *params) {
/*
* Takes a set of profile sequences (stProfileSeq) and returns
* a list of tiling paths. Each tiling path consisting of maximal sequences of hmms
* that do not overlap.
*/
// Create a read partitioning HMM for every sequence and put in ordered set, ordered by reference coordinate
stSortedSet *readHmms = stSortedSet_construct3(stRPHmm_cmpFn, (void (*)(void *)) stRPHmm_destruct2);
for (int64_t i = 0; i < stList_length(profileSeqs); i++) {
stProfileSeq *pSeq = stList_get(profileSeqs, i);
stRPHmm *hmm = stRPHmm_construct(pSeq, params);
stSortedSet_insert(readHmms, hmm);
}
assert(stSortedSet_size(readHmms) == stList_length(profileSeqs));
// Organise HMMs into "tiling paths" consisting of sequences of hmms that do not overlap
return getTilingPaths(readHmms);
}
stRPHmm *fuseTilingPath(stList *tilingPath) {
/*
* Fuse together the hmms in the tiling path into one hmm.
* Destroys the tiling path and cleans it up.
*/
stRPHmm *rightHmm = stList_pop(tilingPath);
// While there remain other hmms in the list fuse them together
while (stList_length(tilingPath) > 0) {
stRPHmm *leftHmm = stList_pop(tilingPath);
rightHmm = stRPHmm_fuse(leftHmm, rightHmm);
}
// Cleanup
stList_destruct(tilingPath);
return rightHmm;
}
stList *mergeTwoTilingPaths(stList *tilingPath1, stList *tilingPath2) {
/*
* Takes two lists, tilingPath1 and tilingPath2, each of which is a set of hmms
* ordered by reference coordinates and
* non-overlapping in reference coordinates.
* Merges together the hmms and returns a single tiling path as a result in the
* same format as the input lists.
* Destroys the input tilingPaths in the process and cleans them up.
*/
// Partition of the hmms into overlapping connected components
stSet *components = getOverlappingComponents(tilingPath1, tilingPath2);
// Cleanup the input tiling paths
stList_destruct(tilingPath1);
stList_destruct(tilingPath2);
// The output tiling path, which starts out empty
stList *newTilingPath = stList_construct();
// Fuse the hmms
// For each component of overlapping hmms
stList *componentsList = stSet_getList(components);
for (int64_t i = 0; i < stList_length(componentsList); i++) {
stSortedSet *component = stList_get(componentsList, i);
stSet_remove(components, component);
// Make two sub-tiling paths (there can only be two maximal paths, by definition)
stList *tilingPaths = getTilingPaths(component);
stRPHmm *hmm = NULL;
if (stList_length(tilingPaths) == 2) {
stList *subTilingPath1 = stList_get(tilingPaths, 0);
stList *subTilingPath2 = stList_get(tilingPaths, 1);
// Fuse the hmms in each sub tiling path
stRPHmm *hmm1 = fuseTilingPath(subTilingPath1);
stRPHmm *hmm2 = fuseTilingPath(subTilingPath2);
// Align
stRPHmm_alignColumns(hmm1, hmm2);
// Merge
hmm = stRPHmm_createCrossProductOfTwoAlignedHmm(hmm1, hmm2);
stRPHmm_destruct(hmm1, 1);
stRPHmm_destruct(hmm2, 1);
// Prune
stRPHmm_forwardBackward(hmm);
stRPHmm_prune(hmm);
} else { // Case that component is just one hmm that does not
// overlap anything else
assert(stList_length(tilingPaths) == 1);
stList *subTilingPath1 = stList_get(tilingPaths, 0);
assert(stList_length(subTilingPath1) == 1);
hmm = stList_pop(subTilingPath1);
stList_destruct(subTilingPath1);
}
// Add to output tiling path
stList_append(newTilingPath, hmm);
stList_destruct(tilingPaths);
}
//Cleanup
stList_destruct(componentsList);
stSet_destruct(components);
// Sort new tiling path
stList_sort(newTilingPath, stRPHmm_cmpFn);
return newTilingPath;
}
stList *mergeTilingPaths(stList *tilingPaths) {
/*
* Like mergeTwoTilingPaths(), except instead of just two tiling paths it takes a list.
* Destroys the tiling path as it goes.
*/
// If no tiling paths in input warn and return an empty tiling path
if (stList_length(tilingPaths) == 0) {
stList_destruct(tilingPaths);
return stList_construct();
}
// If only one tiling path in the input, the output is just the single input tiling path
if (stList_length(tilingPaths) == 1) {
stList *tilingPath = stList_get(tilingPaths, 0);
stList_destruct(tilingPaths);
return tilingPath;
}
stList *tilingPath1;
stList *tilingPath2;
// If there are more than two tiling paths
// split the problem into two recursively until there are just two remaining
// tiling paths
if (stList_length(tilingPaths) > 2) {
// Recursively turn the first half of the tiling paths into one tiling path
stList *tilingPaths1 = stList_construct();
for (int64_t i = 0; i < stList_length(tilingPaths) / 2; i++) {
stList_append(tilingPaths1, stList_get(tilingPaths, i));
}
// Recursively turn the other half of the tiling paths into the other tiling path
stList *tilingPaths2 = stList_construct();
for (int64_t i = stList_length(tilingPaths) / 2; i < stList_length(tilingPaths); i++) {
stList_append(tilingPaths2, stList_get(tilingPaths, i));
}
#if defined(_OPENMP)
#pragma omp parallel
{
#pragma omp sections nowait
{
#pragma omp section
tilingPath1 = mergeTilingPaths(tilingPaths1);
#pragma omp section
tilingPath2 = mergeTilingPaths(tilingPaths2);
}
}
#else
tilingPath1 = mergeTilingPaths(tilingPaths1);
tilingPath2 = mergeTilingPaths(tilingPaths2);
#endif
}
// Otherwise the number of tiling paths is two
else {
tilingPath1 = stList_get(tilingPaths, 0);
tilingPath2 = stList_get(tilingPaths, 1);
}
// Merge together the two tiling paths and return result
assert(tilingPath1 != NULL);
assert(tilingPath2 != NULL);
stList_destruct(tilingPaths);
return mergeTwoTilingPaths(tilingPath1, tilingPath2);
}
static void getProfileSeqs(stList *tilingPath, stList *pSeqs) {
while (stList_length(tilingPath) > 0) {
stRPHmm *hmm = stList_pop(tilingPath);
assert(stList_length(hmm->profileSeqs) == 1);
stProfileSeq *pSeq = stList_peek(hmm->profileSeqs);
stRPHmm_destruct(hmm, 1);
stList_append(pSeqs, pSeq);
}
stList_destruct(tilingPath);
}
static int64_t tilingPathSize(stList *tilingPath) {
/*
* Returns the sum of the length of the profile sequences the tiling path contains
*/
int64_t totalLength = 0;
for (int64_t i = 0; i < stList_length(tilingPath); i++) {
stRPHmm *hmm = stList_get(tilingPath, i);
assert(stList_length(hmm->profileSeqs) == 1);
stProfileSeq *pSeq = stList_peek(hmm->profileSeqs);
totalLength += pSeq->length;
}
return totalLength;
}
int tilingPathsCmpFn(stList *tilingPath1, stList *tilingPath2, stHash *tilingPathLengths) {
int64_t length1 = *(int64_t *) stHash_search(tilingPathLengths, tilingPath1);
int64_t length2 = *(int64_t *) stHash_search(tilingPathLengths, tilingPath2);
return length1 < length2 ? 1 : (length1 > length2 ? -1 : 0);
}
stList *filterReadsByCoverageDepth(stList *profileSeqs, stRPHmmParameters *params,
stList *filteredProfileSeqs, stList *discardedProfileSeqs) {
/*
* Takes a set of profile sequences and returns a subset such that maximum coverage depth of the subset is
* less than or equal to params->maxCoverageDepth. The discarded sequences are placed in the list
* "discardedProfileSeqs", the retained sequences are placed in filteredProfileSeqs.
*/
// Create a set of tiling paths
char *logIdentifier = getLogIdentifier();
stList *tilingPaths = getTilingPaths2(profileSeqs, params);
st_logDebug(" %s Got maximum tiling depth of: %i\n", logIdentifier, (int) stList_length(tilingPaths));
// Sort tiling paths my numbers of reads included
stHash *tilingPathLengths = stHash_construct2(NULL, free);
for (int64_t i = 0; i < stList_length(tilingPaths); i++) {
stList *tilingPath = stList_get(tilingPaths, i);
int64_t *length = st_calloc(1, sizeof(int64_t));
*length = tilingPathSize(tilingPath);
stHash_insert(tilingPathLengths, tilingPath, length);
}
stList_sort2(tilingPaths, (int (*)(const void *, const void *, const void *)) tilingPathsCmpFn, tilingPathLengths);
stHash_destruct(tilingPathLengths);
// Eliminate reads until the maximum coverage depth to less than the give threshold
while (stList_length(tilingPaths) > params->maxCoverageDepth) {
stList *tilingPath = stList_pop(tilingPaths);
st_logDebug(" %s Discarding %i profiling sequences of total length: %i\n", logIdentifier,
(int) stList_length(tilingPath), (int) tilingPathSize(tilingPath));
getProfileSeqs(tilingPath, discardedProfileSeqs);
}
while (stList_length(tilingPaths) > 0) {
getProfileSeqs(stList_pop(tilingPaths), filteredProfileSeqs);
}
st_logInfo(" %s Filtered %" PRIi64 " reads of %" PRIi64 " to achieve maximum coverage depth of %" PRIi64 "\n",
logIdentifier, stList_length(discardedProfileSeqs), stList_length(profileSeqs),
params->maxCoverageDepth);
// Cleanup
stList_destruct(tilingPaths);
free(logIdentifier);
return filteredProfileSeqs;
}
stList *getRPHmms(stList *profileSeqs, stRPHmmParameters *params) {
/*
* Takes a set of profile sequences (stProfileSeq) and returns a list of read partitioning
* hmms (stRPHmm) ordered and non-overlapping in reference coordinates.
* referenceNamesToReferencePriors is a map from reference sequence names to corresponding
* stReferencePriorProbs objects.
*/
// Create a read partitioning HMM for every sequence and put in ordered set, ordered by reference coordinate
stList *tilingPaths = getTilingPaths2(profileSeqs, params);
if (stList_length(tilingPaths) > MAX_READ_PARTITIONING_DEPTH
|| stList_length(tilingPaths) > params->maxCoverageDepth) {
st_errAbort("\nCoverage depth: read depth of %" PRIi64 " exceeds hard maximum of %" PRIi64
" with configured maximum of %" PRIi64 "\n",
stList_length(tilingPaths), MAX_READ_PARTITIONING_DEPTH, params->maxCoverageDepth);
} else {
st_logDebug("Got %i tiling paths from which to build hmms for max coverage depth of: %i\n",
(int) stList_length(tilingPaths), (int) params->maxCoverageDepth);
}
// Merge together the tiling paths into one merged tiling path, merging the individual hmms when
// they overlap on the reference
stList *finalTilingPath = mergeTilingPaths(tilingPaths);
stList_setDestructor(finalTilingPath, (void (*)(void *)) stRPHmm_destruct2);
return finalTilingPath;
}
|
cp-tree.h | /* Definitions for C++ parsing and type checking.
Copyright (C) 1987, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999,
2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009
Free Software Foundation, Inc.
Contributed by Michael Tiemann (tiemann@cygnus.com)
This file is part of GCC.
GCC is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 3, or (at your option)
any later version.
GCC is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with GCC; see the file COPYING3. If not see
<http://www.gnu.org/licenses/>. */
#ifndef GCC_CP_TREE_H
#define GCC_CP_TREE_H
#include "ggc.h"
#include "function.h"
#include "hashtab.h"
#include "splay-tree.h"
#include "vec.h"
#include "varray.h"
#include "c-common.h"
#include "name-lookup.h"
/* In order for the format checking to accept the C++ front end
diagnostic framework extensions, you must include this file before
toplev.h, not after. We override the definition of GCC_DIAG_STYLE
in c-common.h. */
#undef GCC_DIAG_STYLE
#define GCC_DIAG_STYLE __gcc_cxxdiag__
#if GCC_VERSION >= 4001
#define ATTRIBUTE_GCC_CXXDIAG(m, n) __attribute__ ((__format__ (GCC_DIAG_STYLE, m, n))) ATTRIBUTE_NONNULL(m)
#else
#define ATTRIBUTE_GCC_CXXDIAG(m, n) ATTRIBUTE_NONNULL(m)
#endif
extern void cp_cpp_error (cpp_reader *, int,
const char *, va_list *)
ATTRIBUTE_GCC_CXXDIAG(3,0);
#ifdef GCC_TOPLEV_H
#error \
In order for the format checking to accept the C++ front end diagnostic \
framework extensions, you must include this file before toplev.h, not after.
#endif
#include "toplev.h"
#include "diagnostic.h"
/* Usage of TREE_LANG_FLAG_?:
0: IDENTIFIER_MARKED (IDENTIFIER_NODEs)
NEW_EXPR_USE_GLOBAL (in NEW_EXPR).
DELETE_EXPR_USE_GLOBAL (in DELETE_EXPR).
COMPOUND_EXPR_OVERLOADED (in COMPOUND_EXPR).
TREE_INDIRECT_USING (in NAMESPACE_DECL).
CLEANUP_P (in TRY_BLOCK)
AGGR_INIT_VIA_CTOR_P (in AGGR_INIT_EXPR)
PTRMEM_OK_P (in ADDR_EXPR, OFFSET_REF)
PAREN_STRING_LITERAL (in STRING_CST)
DECL_PRETTY_FUNCTION_P (in VAR_DECL)
KOENIG_LOOKUP_P (in CALL_EXPR)
STATEMENT_LIST_NO_SCOPE (in STATEMENT_LIST).
EXPR_STMT_STMT_EXPR_RESULT (in EXPR_STMT)
STMT_EXPR_NO_SCOPE (in STMT_EXPR)
BIND_EXPR_TRY_BLOCK (in BIND_EXPR)
TYPENAME_IS_ENUM_P (in TYPENAME_TYPE)
REFERENCE_REF_P (in INDIRECT_EXPR)
QUALIFIED_NAME_IS_TEMPLATE (in SCOPE_REF)
OMP_FOR_GIMPLIFYING_P (in OMP_FOR)
BASELINK_QUALIFIED_P (in BASELINK)
TARGET_EXPR_IMPLICIT_P (in TARGET_EXPR)
TEMPLATE_PARM_PARAMETER_PACK (in TEMPLATE_PARM_INDEX)
TYPE_REF_IS_RVALUE (in REFERENCE_TYPE)
ATTR_IS_DEPENDENT (in the TREE_LIST for an attribute)
CONSTRUCTOR_IS_DIRECT_INIT (in CONSTRUCTOR)
1: IDENTIFIER_VIRTUAL_P (in IDENTIFIER_NODE)
TI_PENDING_TEMPLATE_FLAG.
TEMPLATE_PARMS_FOR_INLINE.
DELETE_EXPR_USE_VEC (in DELETE_EXPR).
(TREE_CALLS_NEW) (in _EXPR or _REF) (commented-out).
ICS_ELLIPSIS_FLAG (in _CONV)
DECL_INITIALIZED_P (in VAR_DECL)
TYPENAME_IS_CLASS_P (in TYPENAME_TYPE)
STMT_IS_FULL_EXPR_P (in _STMT)
TARGET_EXPR_LIST_INIT_P (in TARGET_EXPR)
2: IDENTIFIER_OPNAME_P (in IDENTIFIER_NODE)
ICS_THIS_FLAG (in _CONV)
DECL_INITIALIZED_BY_CONSTANT_EXPRESSION_P (in VAR_DECL)
STATEMENT_LIST_TRY_BLOCK (in STATEMENT_LIST)
TYPENAME_IS_RESOLVING_P (in TYPE_NAME_TYPE)
3: (TREE_REFERENCE_EXPR) (in NON_LVALUE_EXPR) (commented-out).
ICS_BAD_FLAG (in _CONV)
FN_TRY_BLOCK_P (in TRY_BLOCK)
IDENTIFIER_CTOR_OR_DTOR_P (in IDENTIFIER_NODE)
BIND_EXPR_BODY_BLOCK (in BIND_EXPR)
DECL_NON_TRIVIALLY_INITIALIZED_P (in VAR_DECL)
4: TREE_HAS_CONSTRUCTOR (in INDIRECT_REF, SAVE_EXPR, CONSTRUCTOR,
or FIELD_DECL).
IDENTIFIER_TYPENAME_P (in IDENTIFIER_NODE)
DECL_TINFO_P (in VAR_DECL)
5: C_IS_RESERVED_WORD (in IDENTIFIER_NODE)
DECL_VTABLE_OR_VTT_P (in VAR_DECL)
6: IDENTIFIER_REPO_CHOSEN (in IDENTIFIER_NODE)
DECL_CONSTRUCTION_VTABLE_P (in VAR_DECL)
TYPE_MARKED_P (in _TYPE)
Usage of TYPE_LANG_FLAG_?:
0: TYPE_DEPENDENT_P
1: TYPE_HAS_USER_CONSTRUCTOR.
2: Unused
3: TYPE_FOR_JAVA.
4: TYPE_HAS_NONTRIVIAL_DESTRUCTOR
5: CLASS_TYPE_P (in RECORD_TYPE and UNION_TYPE)
SCOPED_ENUM_P (in ENUMERAL_TYPE)
6: TYPE_DEPENDENT_P_VALID
Usage of DECL_LANG_FLAG_?:
0: DECL_ERROR_REPORTED (in VAR_DECL).
DECL_TEMPLATE_PARM_P (in PARM_DECL, CONST_DECL, TYPE_DECL, or TEMPLATE_DECL)
DECL_LOCAL_FUNCTION_P (in FUNCTION_DECL)
DECL_MUTABLE_P (in FIELD_DECL)
DECL_DEPENDENT_P (in USING_DECL)
1: C_TYPEDEF_EXPLICITLY_SIGNED (in TYPE_DECL).
DECL_TEMPLATE_INSTANTIATED (in a VAR_DECL or a FUNCTION_DECL)
DECL_MEMBER_TEMPLATE_P (in TEMPLATE_DECL)
FUNCTION_PARAMETER_PACK_P (in PARM_DECL)
2: DECL_THIS_EXTERN (in VAR_DECL or FUNCTION_DECL).
DECL_IMPLICIT_TYPEDEF_P (in a TYPE_DECL)
3: DECL_IN_AGGR_P.
4: DECL_C_BIT_FIELD (in a FIELD_DECL)
DECL_ANON_UNION_VAR_P (in a VAR_DECL)
DECL_SELF_REFERENCE_P (in a TYPE_DECL)
DECL_INVALID_OVERRIDER_P (in a FUNCTION_DECL)
5: DECL_INTERFACE_KNOWN.
6: DECL_THIS_STATIC (in VAR_DECL or FUNCTION_DECL).
DECL_FIELD_IS_BASE (in FIELD_DECL)
7: DECL_DEAD_FOR_LOCAL (in VAR_DECL).
DECL_THUNK_P (in a member FUNCTION_DECL)
Usage of language-independent fields in a language-dependent manner:
TYPE_ALIAS_SET
This field is used by TYPENAME_TYPEs, TEMPLATE_TYPE_PARMs, and so
forth as a substitute for the mark bits provided in `lang_type'.
At present, only the six low-order bits are used.
TYPE_LANG_SLOT_1
For an ENUMERAL_TYPE, this is ENUM_TEMPLATE_INFO.
For a FUNCTION_TYPE or METHOD_TYPE, this is TYPE_RAISES_EXCEPTIONS
BINFO_VIRTUALS
For a binfo, this is a TREE_LIST. There is an entry for each
virtual function declared either in BINFO or its direct and
indirect primary bases.
The BV_DELTA of each node gives the amount by which to adjust the
`this' pointer when calling the function. If the method is an
overridden version of a base class method, then it is assumed
that, prior to adjustment, the this pointer points to an object
of the base class.
The BV_VCALL_INDEX of each node, if non-NULL, gives the vtable
index of the vcall offset for this entry.
The BV_FN is the declaration for the virtual function itself.
BINFO_VTABLE
This is an expression with POINTER_TYPE that gives the value
to which the vptr should be initialized. Use get_vtbl_decl_for_binfo
to extract the VAR_DECL for the complete vtable.
DECL_VINDEX
This field is NULL for a non-virtual function. For a virtual
function, it is eventually set to an INTEGER_CST indicating the
index in the vtable at which this function can be found. When
a virtual function is declared, but before it is known what
function is overridden, this field is the error_mark_node.
Temporarily, it may be set to a TREE_LIST whose TREE_VALUE is
the virtual function this one overrides, and whose TREE_CHAIN is
the old DECL_VINDEX. */
/* Language-specific tree checkers. */
#define VAR_OR_FUNCTION_DECL_CHECK(NODE) \
TREE_CHECK2(NODE,VAR_DECL,FUNCTION_DECL)
#define VAR_FUNCTION_OR_PARM_DECL_CHECK(NODE) \
TREE_CHECK3(NODE,VAR_DECL,FUNCTION_DECL,PARM_DECL)
#define VAR_TEMPL_TYPE_OR_FUNCTION_DECL_CHECK(NODE) \
TREE_CHECK4(NODE,VAR_DECL,FUNCTION_DECL,TYPE_DECL,TEMPLATE_DECL)
#define BOUND_TEMPLATE_TEMPLATE_PARM_TYPE_CHECK(NODE) \
TREE_CHECK(NODE,BOUND_TEMPLATE_TEMPLATE_PARM)
#if defined ENABLE_TREE_CHECKING && (GCC_VERSION >= 2007)
#define NON_THUNK_FUNCTION_CHECK(NODE) __extension__ \
({ __typeof(NODE) const __t = (NODE); \
if (TREE_CODE (__t) != FUNCTION_DECL && \
TREE_CODE (__t) != TEMPLATE_DECL && __t->decl_common.lang_specific \
&& __t->decl_common.lang_specific->decl_flags.thunk_p) \
tree_check_failed (__t, __FILE__, __LINE__, __FUNCTION__, 0); \
__t; })
#define THUNK_FUNCTION_CHECK(NODE) __extension__ \
({ __typeof (NODE) const __t = (NODE); \
if (TREE_CODE (__t) != FUNCTION_DECL || !__t->decl_common.lang_specific \
|| !__t->decl_common.lang_specific->decl_flags.thunk_p) \
tree_check_failed (__t, __FILE__, __LINE__, __FUNCTION__, 0); \
__t; })
#else
#define NON_THUNK_FUNCTION_CHECK(NODE) (NODE)
#define THUNK_FUNCTION_CHECK(NODE) (NODE)
#endif
/* Language-dependent contents of an identifier. */
struct lang_identifier GTY(())
{
struct c_common_identifier c_common;
cxx_binding *namespace_bindings;
cxx_binding *bindings;
tree class_template_info;
tree label_value;
};
/* In an IDENTIFIER_NODE, nonzero if this identifier is actually a
keyword. C_RID_CODE (node) is then the RID_* value of the keyword,
and C_RID_YYCODE is the token number wanted by Yacc. */
#define C_IS_RESERVED_WORD(ID) TREE_LANG_FLAG_5 (ID)
#define LANG_IDENTIFIER_CAST(NODE) \
((struct lang_identifier*)IDENTIFIER_NODE_CHECK (NODE))
struct template_parm_index_s GTY(())
{
struct tree_common common;
int index;
int level;
int orig_level;
tree decl;
};
typedef struct template_parm_index_s template_parm_index;
struct ptrmem_cst GTY(())
{
struct tree_common common;
/* This isn't used, but the middle-end expects all constants to have
this field. */
rtx rtl;
tree member;
};
typedef struct ptrmem_cst * ptrmem_cst_t;
#define IDENTIFIER_GLOBAL_VALUE(NODE) \
namespace_binding ((NODE), global_namespace)
#define SET_IDENTIFIER_GLOBAL_VALUE(NODE, VAL) \
set_namespace_binding ((NODE), global_namespace, (VAL))
#define IDENTIFIER_NAMESPACE_VALUE(NODE) \
namespace_binding ((NODE), current_namespace)
#define SET_IDENTIFIER_NAMESPACE_VALUE(NODE, VAL) \
set_namespace_binding ((NODE), current_namespace, (VAL))
#define CLEANUP_P(NODE) TREE_LANG_FLAG_0 (TRY_BLOCK_CHECK (NODE))
#define BIND_EXPR_TRY_BLOCK(NODE) \
TREE_LANG_FLAG_0 (BIND_EXPR_CHECK (NODE))
/* Used to mark the block around the member initializers and cleanups. */
#define BIND_EXPR_BODY_BLOCK(NODE) \
TREE_LANG_FLAG_3 (BIND_EXPR_CHECK (NODE))
#define FUNCTION_NEEDS_BODY_BLOCK(NODE) \
(DECL_CONSTRUCTOR_P (NODE) || DECL_DESTRUCTOR_P (NODE))
#define STATEMENT_LIST_NO_SCOPE(NODE) \
TREE_LANG_FLAG_0 (STATEMENT_LIST_CHECK (NODE))
#define STATEMENT_LIST_TRY_BLOCK(NODE) \
TREE_LANG_FLAG_2 (STATEMENT_LIST_CHECK (NODE))
/* Nonzero if this statement should be considered a full-expression,
i.e., if temporaries created during this statement should have
their destructors run at the end of this statement. */
#define STMT_IS_FULL_EXPR_P(NODE) TREE_LANG_FLAG_1 ((NODE))
/* Marks the result of a statement expression. */
#define EXPR_STMT_STMT_EXPR_RESULT(NODE) \
TREE_LANG_FLAG_0 (EXPR_STMT_CHECK (NODE))
/* Nonzero if this statement-expression does not have an associated scope. */
#define STMT_EXPR_NO_SCOPE(NODE) \
TREE_LANG_FLAG_0 (STMT_EXPR_CHECK (NODE))
/* Returns nonzero iff TYPE1 and TYPE2 are the same type, in the usual
sense of `same'. */
#define same_type_p(TYPE1, TYPE2) \
comptypes ((TYPE1), (TYPE2), COMPARE_STRICT)
/* Returns nonzero iff TYPE1 and TYPE2 are the same type, ignoring
top-level qualifiers. */
#define same_type_ignoring_top_level_qualifiers_p(TYPE1, TYPE2) \
same_type_p (TYPE_MAIN_VARIANT (TYPE1), TYPE_MAIN_VARIANT (TYPE2))
/* Nonzero if we are presently building a statement tree, rather
than expanding each statement as we encounter it. */
#define building_stmt_tree() (cur_stmt_list != NULL_TREE)
/* Returns nonzero iff NODE is a declaration for the global function
`main'. */
#define DECL_MAIN_P(NODE) \
(DECL_EXTERN_C_FUNCTION_P (NODE) \
&& DECL_NAME (NODE) != NULL_TREE \
&& MAIN_NAME_P (DECL_NAME (NODE)) \
&& flag_hosted)
/* The overloaded FUNCTION_DECL. */
#define OVL_FUNCTION(NODE) \
(((struct tree_overload*)OVERLOAD_CHECK (NODE))->function)
#define OVL_CHAIN(NODE) TREE_CHAIN (NODE)
/* Polymorphic access to FUNCTION and CHAIN. */
#define OVL_CURRENT(NODE) \
((TREE_CODE (NODE) == OVERLOAD) ? OVL_FUNCTION (NODE) : (NODE))
#define OVL_NEXT(NODE) \
((TREE_CODE (NODE) == OVERLOAD) ? TREE_CHAIN (NODE) : NULL_TREE)
/* If set, this was imported in a using declaration.
This is not to confuse with being used somewhere, which
is not important for this node. */
#define OVL_USED(NODE) TREE_USED (NODE)
struct tree_overload GTY(())
{
struct tree_common common;
tree function;
};
/* Returns true iff NODE is a BASELINK. */
#define BASELINK_P(NODE) \
(TREE_CODE (NODE) == BASELINK)
/* The BINFO indicating the base from which the BASELINK_FUNCTIONS came. */
#define BASELINK_BINFO(NODE) \
(((struct tree_baselink*) BASELINK_CHECK (NODE))->binfo)
/* The functions referred to by the BASELINK; either a FUNCTION_DECL,
a TEMPLATE_DECL, an OVERLOAD, or a TEMPLATE_ID_EXPR. */
#define BASELINK_FUNCTIONS(NODE) \
(((struct tree_baselink*) BASELINK_CHECK (NODE))->functions)
/* The BINFO in which the search for the functions indicated by this baselink
began. This base is used to determine the accessibility of functions
selected by overload resolution. */
#define BASELINK_ACCESS_BINFO(NODE) \
(((struct tree_baselink*) BASELINK_CHECK (NODE))->access_binfo)
/* For a type-conversion operator, the BASELINK_OPTYPE indicates the type
to which the conversion should occur. This value is important if
the BASELINK_FUNCTIONS include a template conversion operator --
the BASELINK_OPTYPE can be used to determine what type the user
requested. */
#define BASELINK_OPTYPE(NODE) \
(TREE_CHAIN (BASELINK_CHECK (NODE)))
/* Nonzero if this baselink was from a qualified lookup. */
#define BASELINK_QUALIFIED_P(NODE) \
TREE_LANG_FLAG_0 (BASELINK_CHECK (NODE))
struct tree_baselink GTY(())
{
struct tree_common common;
tree binfo;
tree functions;
tree access_binfo;
};
/* The different kinds of ids that we encounter. */
typedef enum cp_id_kind
{
/* Not an id at all. */
CP_ID_KIND_NONE,
/* An unqualified-id that is not a template-id. */
CP_ID_KIND_UNQUALIFIED,
/* An unqualified-id that is a dependent name. */
CP_ID_KIND_UNQUALIFIED_DEPENDENT,
/* An unqualified template-id. */
CP_ID_KIND_TEMPLATE_ID,
/* A qualified-id. */
CP_ID_KIND_QUALIFIED
} cp_id_kind;
/* Macros for access to language-specific slots in an identifier. */
#define IDENTIFIER_NAMESPACE_BINDINGS(NODE) \
(LANG_IDENTIFIER_CAST (NODE)->namespace_bindings)
#define IDENTIFIER_TEMPLATE(NODE) \
(LANG_IDENTIFIER_CAST (NODE)->class_template_info)
/* The IDENTIFIER_BINDING is the innermost cxx_binding for the
identifier. It's PREVIOUS is the next outermost binding. Each
VALUE field is a DECL for the associated declaration. Thus,
name lookup consists simply of pulling off the node at the front
of the list (modulo oddities for looking up the names of types,
and such.) You can use SCOPE field to determine the scope
that bound the name. */
#define IDENTIFIER_BINDING(NODE) \
(LANG_IDENTIFIER_CAST (NODE)->bindings)
/* TREE_TYPE only indicates on local and class scope the current
type. For namespace scope, the presence of a type in any namespace
is indicated with global_type_node, and the real type behind must
be found through lookup. */
#define IDENTIFIER_TYPE_VALUE(NODE) identifier_type_value (NODE)
#define REAL_IDENTIFIER_TYPE_VALUE(NODE) TREE_TYPE (NODE)
#define SET_IDENTIFIER_TYPE_VALUE(NODE,TYPE) (TREE_TYPE (NODE) = (TYPE))
#define IDENTIFIER_HAS_TYPE_VALUE(NODE) (IDENTIFIER_TYPE_VALUE (NODE) ? 1 : 0)
#define IDENTIFIER_LABEL_VALUE(NODE) \
(LANG_IDENTIFIER_CAST (NODE)->label_value)
#define SET_IDENTIFIER_LABEL_VALUE(NODE, VALUE) \
IDENTIFIER_LABEL_VALUE (NODE) = (VALUE)
/* Nonzero if this identifier is used as a virtual function name somewhere
(optimizes searches). */
#define IDENTIFIER_VIRTUAL_P(NODE) TREE_LANG_FLAG_1 (NODE)
/* Nonzero if this identifier is the prefix for a mangled C++ operator
name. */
#define IDENTIFIER_OPNAME_P(NODE) TREE_LANG_FLAG_2 (NODE)
/* Nonzero if this identifier is the name of a type-conversion
operator. */
#define IDENTIFIER_TYPENAME_P(NODE) \
TREE_LANG_FLAG_4 (NODE)
/* Nonzero if this identifier is the name of a constructor or
destructor. */
#define IDENTIFIER_CTOR_OR_DTOR_P(NODE) \
TREE_LANG_FLAG_3 (NODE)
/* True iff NAME is the DECL_ASSEMBLER_NAME for an entity with vague
linkage which the prelinker has assigned to this translation
unit. */
#define IDENTIFIER_REPO_CHOSEN(NAME) \
(TREE_LANG_FLAG_6 (NAME))
/* In a RECORD_TYPE or UNION_TYPE, nonzero if any component is read-only. */
#define C_TYPE_FIELDS_READONLY(TYPE) \
(LANG_TYPE_CLASS_CHECK (TYPE)->fields_readonly)
/* The tokens stored in the default argument. */
#define DEFARG_TOKENS(NODE) \
(((struct tree_default_arg *)DEFAULT_ARG_CHECK (NODE))->tokens)
#define DEFARG_INSTANTIATIONS(NODE) \
(((struct tree_default_arg *)DEFAULT_ARG_CHECK (NODE))->instantiations)
struct tree_default_arg GTY (())
{
struct tree_common common;
struct cp_token_cache *tokens;
VEC(tree,gc) *instantiations;
};
/* The condition associated with the static assertion. This must be
an integral constant expression. */
#define STATIC_ASSERT_CONDITION(NODE) \
(((struct tree_static_assert *)STATIC_ASSERT_CHECK (NODE))->condition)
/* The message associated with the static assertion. This must be a
string constant, which will be emitted as an error message when the
static assert condition is false. */
#define STATIC_ASSERT_MESSAGE(NODE) \
(((struct tree_static_assert *)STATIC_ASSERT_CHECK (NODE))->message)
/* Source location information for a static assertion. */
#define STATIC_ASSERT_SOURCE_LOCATION(NODE) \
(((struct tree_static_assert *)STATIC_ASSERT_CHECK (NODE))->location)
struct tree_static_assert GTY (())
{
struct tree_common common;
tree condition;
tree message;
location_t location;
};
struct tree_argument_pack_select GTY (())
{
struct tree_common common;
tree argument_pack;
int index;
};
/* The different kinds of traits that we encounter. */
typedef enum cp_trait_kind
{
CPTK_HAS_NOTHROW_ASSIGN,
CPTK_HAS_NOTHROW_CONSTRUCTOR,
CPTK_HAS_NOTHROW_COPY,
CPTK_HAS_TRIVIAL_ASSIGN,
CPTK_HAS_TRIVIAL_CONSTRUCTOR,
CPTK_HAS_TRIVIAL_COPY,
CPTK_HAS_TRIVIAL_DESTRUCTOR,
CPTK_HAS_VIRTUAL_DESTRUCTOR,
CPTK_IS_ABSTRACT,
CPTK_IS_BASE_OF,
CPTK_IS_CLASS,
CPTK_IS_CONVERTIBLE_TO,
CPTK_IS_EMPTY,
CPTK_IS_ENUM,
CPTK_IS_POD,
CPTK_IS_POLYMORPHIC,
CPTK_IS_UNION
} cp_trait_kind;
/* The types that we are processing. */
#define TRAIT_EXPR_TYPE1(NODE) \
(((struct tree_trait_expr *)TRAIT_EXPR_CHECK (NODE))->type1)
#define TRAIT_EXPR_TYPE2(NODE) \
(((struct tree_trait_expr *)TRAIT_EXPR_CHECK (NODE))->type2)
/* The specific trait that we are processing. */
#define TRAIT_EXPR_KIND(NODE) \
(((struct tree_trait_expr *)TRAIT_EXPR_CHECK (NODE))->kind)
struct tree_trait_expr GTY (())
{
struct tree_common common;
tree type1;
tree type2;
enum cp_trait_kind kind;
};
enum cp_tree_node_structure_enum {
TS_CP_GENERIC,
TS_CP_IDENTIFIER,
TS_CP_TPI,
TS_CP_PTRMEM,
TS_CP_BINDING,
TS_CP_OVERLOAD,
TS_CP_BASELINK,
TS_CP_WRAPPER,
TS_CP_DEFAULT_ARG,
TS_CP_STATIC_ASSERT,
TS_CP_ARGUMENT_PACK_SELECT,
TS_CP_TRAIT_EXPR,
LAST_TS_CP_ENUM
};
/* The resulting tree type. */
union lang_tree_node GTY((desc ("cp_tree_node_structure (&%h)"),
chain_next ("(union lang_tree_node *)TREE_CHAIN (&%h.generic)")))
{
union tree_node GTY ((tag ("TS_CP_GENERIC"),
desc ("tree_node_structure (&%h)"))) generic;
struct template_parm_index_s GTY ((tag ("TS_CP_TPI"))) tpi;
struct ptrmem_cst GTY ((tag ("TS_CP_PTRMEM"))) ptrmem;
struct tree_overload GTY ((tag ("TS_CP_OVERLOAD"))) overload;
struct tree_baselink GTY ((tag ("TS_CP_BASELINK"))) baselink;
struct tree_default_arg GTY ((tag ("TS_CP_DEFAULT_ARG"))) default_arg;
struct lang_identifier GTY ((tag ("TS_CP_IDENTIFIER"))) identifier;
struct tree_static_assert GTY ((tag ("TS_CP_STATIC_ASSERT")))
static_assertion;
struct tree_argument_pack_select GTY ((tag ("TS_CP_ARGUMENT_PACK_SELECT")))
argument_pack_select;
struct tree_trait_expr GTY ((tag ("TS_CP_TRAIT_EXPR")))
trait_expression;
};
enum cp_tree_index
{
CPTI_JAVA_BYTE_TYPE,
CPTI_JAVA_SHORT_TYPE,
CPTI_JAVA_INT_TYPE,
CPTI_JAVA_LONG_TYPE,
CPTI_JAVA_FLOAT_TYPE,
CPTI_JAVA_DOUBLE_TYPE,
CPTI_JAVA_CHAR_TYPE,
CPTI_JAVA_BOOLEAN_TYPE,
CPTI_WCHAR_DECL,
CPTI_VTABLE_ENTRY_TYPE,
CPTI_DELTA_TYPE,
CPTI_VTABLE_INDEX_TYPE,
CPTI_CLEANUP_TYPE,
CPTI_VTT_PARM_TYPE,
CPTI_CLASS_TYPE,
CPTI_UNKNOWN_TYPE,
CPTI_INIT_LIST_TYPE,
CPTI_VTBL_TYPE,
CPTI_VTBL_PTR_TYPE,
CPTI_STD,
CPTI_ABI,
CPTI_CONST_TYPE_INFO_TYPE,
CPTI_TYPE_INFO_PTR_TYPE,
CPTI_ABORT_FNDECL,
CPTI_GLOBAL_DELETE_FNDECL,
CPTI_AGGR_TAG,
CPTI_CTOR_IDENTIFIER,
CPTI_COMPLETE_CTOR_IDENTIFIER,
CPTI_BASE_CTOR_IDENTIFIER,
CPTI_DTOR_IDENTIFIER,
CPTI_COMPLETE_DTOR_IDENTIFIER,
CPTI_BASE_DTOR_IDENTIFIER,
CPTI_DELETING_DTOR_IDENTIFIER,
CPTI_DELTA_IDENTIFIER,
CPTI_IN_CHARGE_IDENTIFIER,
CPTI_VTT_PARM_IDENTIFIER,
CPTI_NELTS_IDENTIFIER,
CPTI_THIS_IDENTIFIER,
CPTI_PFN_IDENTIFIER,
CPTI_VPTR_IDENTIFIER,
CPTI_STD_IDENTIFIER,
CPTI_LANG_NAME_C,
CPTI_LANG_NAME_CPLUSPLUS,
CPTI_LANG_NAME_JAVA,
CPTI_EMPTY_EXCEPT_SPEC,
CPTI_JCLASS,
CPTI_TERMINATE,
CPTI_CALL_UNEXPECTED,
CPTI_ATEXIT_FN_PTR_TYPE,
CPTI_ATEXIT,
CPTI_DSO_HANDLE,
CPTI_DCAST,
CPTI_KEYED_CLASSES,
CPTI_MAX
};
extern GTY(()) tree cp_global_trees[CPTI_MAX];
#define java_byte_type_node cp_global_trees[CPTI_JAVA_BYTE_TYPE]
#define java_short_type_node cp_global_trees[CPTI_JAVA_SHORT_TYPE]
#define java_int_type_node cp_global_trees[CPTI_JAVA_INT_TYPE]
#define java_long_type_node cp_global_trees[CPTI_JAVA_LONG_TYPE]
#define java_float_type_node cp_global_trees[CPTI_JAVA_FLOAT_TYPE]
#define java_double_type_node cp_global_trees[CPTI_JAVA_DOUBLE_TYPE]
#define java_char_type_node cp_global_trees[CPTI_JAVA_CHAR_TYPE]
#define java_boolean_type_node cp_global_trees[CPTI_JAVA_BOOLEAN_TYPE]
#define wchar_decl_node cp_global_trees[CPTI_WCHAR_DECL]
#define vtable_entry_type cp_global_trees[CPTI_VTABLE_ENTRY_TYPE]
/* The type used to represent an offset by which to adjust the `this'
pointer in pointer-to-member types. */
#define delta_type_node cp_global_trees[CPTI_DELTA_TYPE]
/* The type used to represent an index into the vtable. */
#define vtable_index_type cp_global_trees[CPTI_VTABLE_INDEX_TYPE]
#define class_type_node cp_global_trees[CPTI_CLASS_TYPE]
#define unknown_type_node cp_global_trees[CPTI_UNKNOWN_TYPE]
#define init_list_type_node cp_global_trees[CPTI_INIT_LIST_TYPE]
#define vtbl_type_node cp_global_trees[CPTI_VTBL_TYPE]
#define vtbl_ptr_type_node cp_global_trees[CPTI_VTBL_PTR_TYPE]
#define std_node cp_global_trees[CPTI_STD]
#define abi_node cp_global_trees[CPTI_ABI]
#define const_type_info_type_node cp_global_trees[CPTI_CONST_TYPE_INFO_TYPE]
#define type_info_ptr_type cp_global_trees[CPTI_TYPE_INFO_PTR_TYPE]
#define abort_fndecl cp_global_trees[CPTI_ABORT_FNDECL]
#define global_delete_fndecl cp_global_trees[CPTI_GLOBAL_DELETE_FNDECL]
#define current_aggr cp_global_trees[CPTI_AGGR_TAG]
/* We cache these tree nodes so as to call get_identifier less
frequently. */
/* The name of a constructor that takes an in-charge parameter to
decide whether or not to construct virtual base classes. */
#define ctor_identifier cp_global_trees[CPTI_CTOR_IDENTIFIER]
/* The name of a constructor that constructs virtual base classes. */
#define complete_ctor_identifier cp_global_trees[CPTI_COMPLETE_CTOR_IDENTIFIER]
/* The name of a constructor that does not construct virtual base classes. */
#define base_ctor_identifier cp_global_trees[CPTI_BASE_CTOR_IDENTIFIER]
/* The name of a destructor that takes an in-charge parameter to
decide whether or not to destroy virtual base classes and whether
or not to delete the object. */
#define dtor_identifier cp_global_trees[CPTI_DTOR_IDENTIFIER]
/* The name of a destructor that destroys virtual base classes. */
#define complete_dtor_identifier cp_global_trees[CPTI_COMPLETE_DTOR_IDENTIFIER]
/* The name of a destructor that does not destroy virtual base
classes. */
#define base_dtor_identifier cp_global_trees[CPTI_BASE_DTOR_IDENTIFIER]
/* The name of a destructor that destroys virtual base classes, and
then deletes the entire object. */
#define deleting_dtor_identifier cp_global_trees[CPTI_DELETING_DTOR_IDENTIFIER]
#define delta_identifier cp_global_trees[CPTI_DELTA_IDENTIFIER]
#define in_charge_identifier cp_global_trees[CPTI_IN_CHARGE_IDENTIFIER]
/* The name of the parameter that contains a pointer to the VTT to use
for this subobject constructor or destructor. */
#define vtt_parm_identifier cp_global_trees[CPTI_VTT_PARM_IDENTIFIER]
#define nelts_identifier cp_global_trees[CPTI_NELTS_IDENTIFIER]
#define this_identifier cp_global_trees[CPTI_THIS_IDENTIFIER]
#define pfn_identifier cp_global_trees[CPTI_PFN_IDENTIFIER]
#define vptr_identifier cp_global_trees[CPTI_VPTR_IDENTIFIER]
/* The name of the std namespace. */
#define std_identifier cp_global_trees[CPTI_STD_IDENTIFIER]
#define lang_name_c cp_global_trees[CPTI_LANG_NAME_C]
#define lang_name_cplusplus cp_global_trees[CPTI_LANG_NAME_CPLUSPLUS]
#define lang_name_java cp_global_trees[CPTI_LANG_NAME_JAVA]
/* Exception specifier used for throw(). */
#define empty_except_spec cp_global_trees[CPTI_EMPTY_EXCEPT_SPEC]
/* If non-NULL, a POINTER_TYPE equivalent to (java::lang::Class*). */
#define jclass_node cp_global_trees[CPTI_JCLASS]
/* The declaration for `std::terminate'. */
#define terminate_node cp_global_trees[CPTI_TERMINATE]
/* The declaration for "__cxa_call_unexpected". */
#define call_unexpected_node cp_global_trees[CPTI_CALL_UNEXPECTED]
/* The type of the function-pointer argument to "__cxa_atexit" (or
"std::atexit", if "__cxa_atexit" is not being used). */
#define atexit_fn_ptr_type_node cp_global_trees[CPTI_ATEXIT_FN_PTR_TYPE]
/* A pointer to `std::atexit'. */
#define atexit_node cp_global_trees[CPTI_ATEXIT]
/* A pointer to `__dso_handle'. */
#define dso_handle_node cp_global_trees[CPTI_DSO_HANDLE]
/* The declaration of the dynamic_cast runtime. */
#define dynamic_cast_node cp_global_trees[CPTI_DCAST]
/* The type of a destructor. */
#define cleanup_type cp_global_trees[CPTI_CLEANUP_TYPE]
/* The type of the vtt parameter passed to subobject constructors and
destructors. */
#define vtt_parm_type cp_global_trees[CPTI_VTT_PARM_TYPE]
/* A TREE_LIST of the dynamic classes whose vtables may have to be
emitted in this translation unit. */
#define keyed_classes cp_global_trees[CPTI_KEYED_CLASSES]
/* Node to indicate default access. This must be distinct from the
access nodes in tree.h. */
#define access_default_node null_node
/* Global state. */
struct saved_scope GTY(())
{
VEC(cxx_saved_binding,gc) *old_bindings;
tree old_namespace;
tree decl_ns_list;
tree class_name;
tree class_type;
tree access_specifier;
tree function_decl;
VEC(tree,gc) *lang_base;
tree lang_name;
tree template_parms;
struct cp_binding_level *x_previous_class_level;
tree x_saved_tree;
int x_processing_template_decl;
int x_processing_specialization;
BOOL_BITFIELD x_processing_explicit_instantiation : 1;
BOOL_BITFIELD need_pop_function_context : 1;
BOOL_BITFIELD skip_evaluation : 1;
struct stmt_tree_s x_stmt_tree;
struct cp_binding_level *class_bindings;
struct cp_binding_level *bindings;
struct saved_scope *prev;
};
/* The current open namespace. */
#define current_namespace scope_chain->old_namespace
/* The stack for namespaces of current declarations. */
#define decl_namespace_list scope_chain->decl_ns_list
/* IDENTIFIER_NODE: name of current class */
#define current_class_name scope_chain->class_name
/* _TYPE: the type of the current class */
#define current_class_type scope_chain->class_type
/* When parsing a class definition, the access specifier most recently
given by the user, or, if no access specifier was given, the
default value appropriate for the kind of class (i.e., struct,
class, or union). */
#define current_access_specifier scope_chain->access_specifier
/* Pointer to the top of the language name stack. */
#define current_lang_base scope_chain->lang_base
#define current_lang_name scope_chain->lang_name
/* When parsing a template declaration, a TREE_LIST represents the
active template parameters. Each node in the list represents one
level of template parameters. The innermost level is first in the
list. The depth of each level is stored as an INTEGER_CST in the
TREE_PURPOSE of each node. The parameters for that level are
stored in the TREE_VALUE. */
#define current_template_parms scope_chain->template_parms
#define processing_template_decl scope_chain->x_processing_template_decl
#define processing_specialization scope_chain->x_processing_specialization
#define processing_explicit_instantiation scope_chain->x_processing_explicit_instantiation
/* The cached class binding level, from the most recently exited
class, or NULL if none. */
#define previous_class_level scope_chain->x_previous_class_level
/* A list of private types mentioned, for deferred access checking. */
extern GTY(()) struct saved_scope *scope_chain;
struct cxx_int_tree_map GTY(())
{
unsigned int uid;
tree to;
};
extern unsigned int cxx_int_tree_map_hash (const void *);
extern int cxx_int_tree_map_eq (const void *, const void *);
/* Global state pertinent to the current function. */
struct language_function GTY(())
{
struct c_language_function base;
tree x_cdtor_label;
tree x_current_class_ptr;
tree x_current_class_ref;
tree x_eh_spec_block;
tree x_in_charge_parm;
tree x_vtt_parm;
tree x_return_value;
BOOL_BITFIELD returns_value : 1;
BOOL_BITFIELD returns_null : 1;
BOOL_BITFIELD returns_abnormally : 1;
BOOL_BITFIELD in_function_try_handler : 1;
BOOL_BITFIELD in_base_initializer : 1;
/* True if this function can throw an exception. */
BOOL_BITFIELD can_throw : 1;
htab_t GTY((param_is(struct named_label_entry))) x_named_labels;
struct cp_binding_level *bindings;
VEC(tree,gc) *x_local_names;
htab_t GTY((param_is (struct cxx_int_tree_map))) extern_decl_map;
};
/* The current C++-specific per-function global variables. */
#define cp_function_chain (cfun->language)
/* In a constructor destructor, the point at which all derived class
destroying/construction has been done. I.e., just before a
constructor returns, or before any base class destroying will be done
in a destructor. */
#define cdtor_label cp_function_chain->x_cdtor_label
/* When we're processing a member function, current_class_ptr is the
PARM_DECL for the `this' pointer. The current_class_ref is an
expression for `*this'. */
#define current_class_ptr \
(cfun && cp_function_chain \
? cp_function_chain->x_current_class_ptr : NULL_TREE)
#define current_class_ref \
(cfun ? cp_function_chain->x_current_class_ref : NULL_TREE)
/* The EH_SPEC_BLOCK for the exception-specifiers for the current
function, if any. */
#define current_eh_spec_block cp_function_chain->x_eh_spec_block
/* The `__in_chrg' parameter for the current function. Only used for
constructors and destructors. */
#define current_in_charge_parm cp_function_chain->x_in_charge_parm
/* The `__vtt_parm' parameter for the current function. Only used for
constructors and destructors. */
#define current_vtt_parm cp_function_chain->x_vtt_parm
/* Set to 0 at beginning of a function definition, set to 1 if
a return statement that specifies a return value is seen. */
#define current_function_returns_value cp_function_chain->returns_value
/* Set to 0 at beginning of a function definition, set to 1 if
a return statement with no argument is seen. */
#define current_function_returns_null cp_function_chain->returns_null
/* Set to 0 at beginning of a function definition, set to 1 if
a call to a noreturn function is seen. */
#define current_function_returns_abnormally \
cp_function_chain->returns_abnormally
/* Nonzero if we are processing a base initializer. Zero elsewhere. */
#define in_base_initializer cp_function_chain->in_base_initializer
#define in_function_try_handler cp_function_chain->in_function_try_handler
/* Expression always returned from function, or error_mark_node
otherwise, for use by the automatic named return value optimization. */
#define current_function_return_value \
(cp_function_chain->x_return_value)
/* True if NAME is the IDENTIFIER_NODE for an overloaded "operator
new" or "operator delete". */
#define NEW_DELETE_OPNAME_P(NAME) \
((NAME) == ansi_opname (NEW_EXPR) \
|| (NAME) == ansi_opname (VEC_NEW_EXPR) \
|| (NAME) == ansi_opname (DELETE_EXPR) \
|| (NAME) == ansi_opname (VEC_DELETE_EXPR))
#define ansi_opname(CODE) \
(operator_name_info[(int) (CODE)].identifier)
#define ansi_assopname(CODE) \
(assignment_operator_name_info[(int) (CODE)].identifier)
/* True if NODE is an erroneous expression. */
#define error_operand_p(NODE) \
((NODE) == error_mark_node \
|| ((NODE) && TREE_TYPE ((NODE)) == error_mark_node))
/* TRUE if a tree code represents a statement. */
extern bool statement_code_p[MAX_TREE_CODES];
#define STATEMENT_CODE_P(CODE) statement_code_p[(int) (CODE)]
enum languages { lang_c, lang_cplusplus, lang_java };
/* Macros to make error reporting functions' lives easier. */
#define TYPE_IDENTIFIER(NODE) (DECL_NAME (TYPE_NAME (NODE)))
#define TYPE_LINKAGE_IDENTIFIER(NODE) \
(TYPE_IDENTIFIER (TYPE_MAIN_VARIANT (NODE)))
#define TYPE_NAME_STRING(NODE) (IDENTIFIER_POINTER (TYPE_IDENTIFIER (NODE)))
#define TYPE_NAME_LENGTH(NODE) (IDENTIFIER_LENGTH (TYPE_IDENTIFIER (NODE)))
/* Nonzero if NODE has no name for linkage purposes. */
#define TYPE_ANONYMOUS_P(NODE) \
(TAGGED_TYPE_P (NODE) && ANON_AGGRNAME_P (TYPE_LINKAGE_IDENTIFIER (NODE)))
/* The _DECL for this _TYPE. */
#define TYPE_MAIN_DECL(NODE) (TYPE_STUB_DECL (TYPE_MAIN_VARIANT (NODE)))
/* Nonzero if T is a class (or struct or union) type. Also nonzero
for template type parameters, typename types, and instantiated
template template parameters. Keep these checks in ascending code
order. */
#define MAYBE_CLASS_TYPE_P(T) \
(TREE_CODE (T) == TEMPLATE_TYPE_PARM \
|| TREE_CODE (T) == TYPENAME_TYPE \
|| TREE_CODE (T) == TYPEOF_TYPE \
|| TREE_CODE (T) == BOUND_TEMPLATE_TEMPLATE_PARM \
|| TREE_CODE (T) == DECLTYPE_TYPE \
|| CLASS_TYPE_P (T))
/* Set CLASS_TYPE_P for T to VAL. T must be a class, struct, or
union type. */
#define SET_CLASS_TYPE_P(T, VAL) \
(TYPE_LANG_FLAG_5 (T) = (VAL))
/* Nonzero if T is a class type. Zero for template type parameters,
typename types, and so forth. */
#define CLASS_TYPE_P(T) \
(RECORD_OR_UNION_CODE_P (TREE_CODE (T)) && TYPE_LANG_FLAG_5 (T))
/* Nonzero if T is a class type but not an union. */
#define NON_UNION_CLASS_TYPE_P(T) \
(CLASS_TYPE_P (T) && TREE_CODE (T) != UNION_TYPE)
/* Keep these checks in ascending code order. */
#define RECORD_OR_UNION_CODE_P(T) \
((T) == RECORD_TYPE || (T) == UNION_TYPE)
#define TAGGED_TYPE_P(T) \
(CLASS_TYPE_P (T) || TREE_CODE (T) == ENUMERAL_TYPE)
#define IS_OVERLOAD_TYPE(T) TAGGED_TYPE_P (T)
/* True if this a "Java" type, defined in 'extern "Java"'. */
#define TYPE_FOR_JAVA(NODE) TYPE_LANG_FLAG_3 (NODE)
/* True if this type is dependent. This predicate is only valid if
TYPE_DEPENDENT_P_VALID is true. */
#define TYPE_DEPENDENT_P(NODE) TYPE_LANG_FLAG_0 (NODE)
/* True if dependent_type_p has been called for this type, with the
result that TYPE_DEPENDENT_P is valid. */
#define TYPE_DEPENDENT_P_VALID(NODE) TYPE_LANG_FLAG_6(NODE)
/* Nonzero if this type is const-qualified. */
#define CP_TYPE_CONST_P(NODE) \
((cp_type_quals (NODE) & TYPE_QUAL_CONST) != 0)
/* Nonzero if this type is volatile-qualified. */
#define CP_TYPE_VOLATILE_P(NODE) \
((cp_type_quals (NODE) & TYPE_QUAL_VOLATILE) != 0)
/* Nonzero if this type is restrict-qualified. */
#define CP_TYPE_RESTRICT_P(NODE) \
((cp_type_quals (NODE) & TYPE_QUAL_RESTRICT) != 0)
/* Nonzero if this type is const-qualified, but not
volatile-qualified. Other qualifiers are ignored. This macro is
used to test whether or not it is OK to bind an rvalue to a
reference. */
#define CP_TYPE_CONST_NON_VOLATILE_P(NODE) \
((cp_type_quals (NODE) & (TYPE_QUAL_CONST | TYPE_QUAL_VOLATILE)) \
== TYPE_QUAL_CONST)
#define FUNCTION_ARG_CHAIN(NODE) \
TREE_CHAIN (TYPE_ARG_TYPES (TREE_TYPE (NODE)))
/* Given a FUNCTION_DECL, returns the first TREE_LIST out of TYPE_ARG_TYPES
which refers to a user-written parameter. */
#define FUNCTION_FIRST_USER_PARMTYPE(NODE) \
skip_artificial_parms_for ((NODE), TYPE_ARG_TYPES (TREE_TYPE (NODE)))
/* Similarly, but for DECL_ARGUMENTS. */
#define FUNCTION_FIRST_USER_PARM(NODE) \
skip_artificial_parms_for ((NODE), DECL_ARGUMENTS (NODE))
/* Nonzero iff TYPE is derived from PARENT. Ignores accessibility and
ambiguity issues. */
#define DERIVED_FROM_P(PARENT, TYPE) \
(lookup_base ((TYPE), (PARENT), ba_any, NULL) != NULL_TREE)
/* Nonzero iff TYPE is uniquely derived from PARENT. Ignores
accessibility. */
#define UNIQUELY_DERIVED_FROM_P(PARENT, TYPE) \
(lookup_base ((TYPE), (PARENT), ba_unique | ba_quiet, NULL) != NULL_TREE)
/* Nonzero iff TYPE is publicly & uniquely derived from PARENT. */
#define PUBLICLY_UNIQUELY_DERIVED_P(PARENT, TYPE) \
(lookup_base ((TYPE), (PARENT), ba_ignore_scope | ba_check | ba_quiet, \
NULL) != NULL_TREE)
/* Gives the visibility specification for a class type. */
#define CLASSTYPE_VISIBILITY(TYPE) \
DECL_VISIBILITY (TYPE_NAME (TYPE))
#define CLASSTYPE_VISIBILITY_SPECIFIED(TYPE) \
DECL_VISIBILITY_SPECIFIED (TYPE_NAME (TYPE))
typedef struct tree_pair_s GTY (())
{
tree purpose;
tree value;
} tree_pair_s;
typedef tree_pair_s *tree_pair_p;
DEF_VEC_O (tree_pair_s);
DEF_VEC_ALLOC_O (tree_pair_s,gc);
/* This is a few header flags for 'struct lang_type'. Actually,
all but the first are used only for lang_type_class; they
are put in this structure to save space. */
struct lang_type_header GTY(())
{
BOOL_BITFIELD is_lang_type_class : 1;
BOOL_BITFIELD has_type_conversion : 1;
BOOL_BITFIELD has_init_ref : 1;
BOOL_BITFIELD has_default_ctor : 1;
BOOL_BITFIELD const_needs_init : 1;
BOOL_BITFIELD ref_needs_init : 1;
BOOL_BITFIELD has_const_assign_ref : 1;
BOOL_BITFIELD spare : 1;
};
/* This structure provides additional information above and beyond
what is provide in the ordinary tree_type. In the past, we used it
for the types of class types, template parameters types, typename
types, and so forth. However, there can be many (tens to hundreds
of thousands) of template parameter types in a compilation, and
there's no need for this additional information in that case.
Therefore, we now use this data structure only for class types.
In the past, it was thought that there would be relatively few
class types. However, in the presence of heavy use of templates,
many (i.e., thousands) of classes can easily be generated.
Therefore, we should endeavor to keep the size of this structure to
a minimum. */
struct lang_type_class GTY(())
{
struct lang_type_header h;
unsigned char align;
unsigned has_mutable : 1;
unsigned com_interface : 1;
unsigned non_pod_class : 1;
unsigned nearly_empty_p : 1;
unsigned user_align : 1;
unsigned has_assign_ref : 1;
unsigned has_new : 1;
unsigned has_array_new : 1;
unsigned gets_delete : 2;
unsigned interface_only : 1;
unsigned interface_unknown : 1;
unsigned contains_empty_class_p : 1;
unsigned anon_aggr : 1;
unsigned non_zero_init : 1;
unsigned empty_p : 1;
unsigned vec_new_uses_cookie : 1;
unsigned declared_class : 1;
unsigned diamond_shaped : 1;
unsigned repeated_base : 1;
unsigned being_defined : 1;
unsigned java_interface : 1;
unsigned debug_requested : 1;
unsigned fields_readonly : 1;
unsigned use_template : 2;
unsigned ptrmemfunc_flag : 1;
unsigned was_anonymous : 1;
unsigned lazy_default_ctor : 1;
unsigned lazy_copy_ctor : 1;
unsigned lazy_assignment_op : 1;
unsigned lazy_destructor : 1;
unsigned has_const_init_ref : 1;
unsigned has_complex_init_ref : 1;
unsigned has_complex_assign_ref : 1;
unsigned non_aggregate : 1;
unsigned has_complex_dflt : 1;
unsigned has_list_ctor : 1;
/* When adding a flag here, consider whether or not it ought to
apply to a template instance if it applies to the template. If
so, make sure to copy it in instantiate_class_template! */
/* There are some bits left to fill out a 32-bit word. Keep track
of this by updating the size of this bitfield whenever you add or
remove a flag. */
unsigned dummy : 10;
tree primary_base;
VEC(tree_pair_s,gc) *vcall_indices;
tree vtables;
tree typeinfo_var;
VEC(tree,gc) *vbases;
binding_table nested_udts;
tree as_base;
VEC(tree,gc) *pure_virtuals;
tree friend_classes;
VEC(tree,gc) * GTY((reorder ("resort_type_method_vec"))) methods;
tree key_method;
tree decl_list;
tree template_info;
tree befriending_classes;
/* In a RECORD_TYPE, information specific to Objective-C++, such
as a list of adopted protocols or a pointer to a corresponding
@interface. See objc/objc-act.h for details. */
tree objc_info;
};
struct lang_type_ptrmem GTY(())
{
struct lang_type_header h;
tree record;
};
struct lang_type GTY(())
{
union lang_type_u
{
struct lang_type_header GTY((skip (""))) h;
struct lang_type_class GTY((tag ("1"))) c;
struct lang_type_ptrmem GTY((tag ("0"))) ptrmem;
} GTY((desc ("%h.h.is_lang_type_class"))) u;
};
#if defined ENABLE_TREE_CHECKING && (GCC_VERSION >= 2007)
#define LANG_TYPE_CLASS_CHECK(NODE) __extension__ \
({ struct lang_type *lt = TYPE_LANG_SPECIFIC (NODE); \
if (! lt->u.h.is_lang_type_class) \
lang_check_failed (__FILE__, __LINE__, __FUNCTION__); \
<->u.c; })
#define LANG_TYPE_PTRMEM_CHECK(NODE) __extension__ \
({ struct lang_type *lt = TYPE_LANG_SPECIFIC (NODE); \
if (lt->u.h.is_lang_type_class) \
lang_check_failed (__FILE__, __LINE__, __FUNCTION__); \
<->u.ptrmem; })
#else
#define LANG_TYPE_CLASS_CHECK(NODE) (&TYPE_LANG_SPECIFIC (NODE)->u.c)
#define LANG_TYPE_PTRMEM_CHECK(NODE) (&TYPE_LANG_SPECIFIC (NODE)->u.ptrmem)
#endif /* ENABLE_TREE_CHECKING */
/* Fields used for storing information before the class is defined.
After the class is defined, these fields hold other information. */
/* VEC(tree) of friends which were defined inline in this class
definition. */
#define CLASSTYPE_INLINE_FRIENDS(NODE) CLASSTYPE_PURE_VIRTUALS (NODE)
/* Nonzero for _CLASSTYPE means that operator delete is defined. */
#define TYPE_GETS_DELETE(NODE) (LANG_TYPE_CLASS_CHECK (NODE)->gets_delete)
#define TYPE_GETS_REG_DELETE(NODE) (TYPE_GETS_DELETE (NODE) & 1)
/* Nonzero if `new NODE[x]' should cause the allocation of extra
storage to indicate how many array elements are in use. */
#define TYPE_VEC_NEW_USES_COOKIE(NODE) \
(CLASS_TYPE_P (NODE) \
&& LANG_TYPE_CLASS_CHECK (NODE)->vec_new_uses_cookie)
/* Nonzero means that this _CLASSTYPE node defines ways of converting
itself to other types. */
#define TYPE_HAS_CONVERSION(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->h.has_type_conversion)
/* Nonzero means that NODE (a class type) has a default constructor --
but that it has not yet been declared. */
#define CLASSTYPE_LAZY_DEFAULT_CTOR(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->lazy_default_ctor)
/* Nonzero means that NODE (a class type) has a copy constructor --
but that it has not yet been declared. */
#define CLASSTYPE_LAZY_COPY_CTOR(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->lazy_copy_ctor)
/* Nonzero means that NODE (a class type) has an assignment operator
-- but that it has not yet been declared. */
#define CLASSTYPE_LAZY_ASSIGNMENT_OP(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->lazy_assignment_op)
/* Nonzero means that NODE (a class type) has a destructor -- but that
it has not yet been declared. */
#define CLASSTYPE_LAZY_DESTRUCTOR(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->lazy_destructor)
/* Nonzero means that this _CLASSTYPE node overloads operator=(X&). */
#define TYPE_HAS_ASSIGN_REF(NODE) (LANG_TYPE_CLASS_CHECK (NODE)->has_assign_ref)
/* True iff the class type NODE has an "operator =" whose parameter
has a parameter of type "const X&". */
#define TYPE_HAS_CONST_ASSIGN_REF(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->h.has_const_assign_ref)
/* Nonzero means that this _CLASSTYPE node has an X(X&) constructor. */
#define TYPE_HAS_INIT_REF(NODE) (LANG_TYPE_CLASS_CHECK (NODE)->h.has_init_ref)
#define TYPE_HAS_CONST_INIT_REF(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->has_const_init_ref)
/* Nonzero if this class has an X(initializer_list<T>) constructor. */
#define TYPE_HAS_LIST_CTOR(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->has_list_ctor)
/* Nonzero if this class defines an overloaded operator new. (An
operator new [] doesn't count.) */
#define TYPE_HAS_NEW_OPERATOR(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->has_new)
/* Nonzero if this class defines an overloaded operator new[]. */
#define TYPE_HAS_ARRAY_NEW_OPERATOR(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->has_array_new)
/* Nonzero means that this type is being defined. I.e., the left brace
starting the definition of this type has been seen. */
#define TYPE_BEING_DEFINED(NODE) (LANG_TYPE_CLASS_CHECK (NODE)->being_defined)
/* Mark bits for repeated base checks. */
#define TYPE_MARKED_P(NODE) TREE_LANG_FLAG_6 (TYPE_CHECK (NODE))
/* Nonzero if the class NODE has multiple paths to the same (virtual)
base object. */
#define CLASSTYPE_DIAMOND_SHAPED_P(NODE) \
(LANG_TYPE_CLASS_CHECK(NODE)->diamond_shaped)
/* Nonzero if the class NODE has multiple instances of the same base
type. */
#define CLASSTYPE_REPEATED_BASE_P(NODE) \
(LANG_TYPE_CLASS_CHECK(NODE)->repeated_base)
/* The member function with which the vtable will be emitted:
the first noninline non-pure-virtual member function. NULL_TREE
if there is no key function or if this is a class template */
#define CLASSTYPE_KEY_METHOD(NODE) (LANG_TYPE_CLASS_CHECK (NODE)->key_method)
/* Vector member functions defined in this class. Each element is
either a FUNCTION_DECL, a TEMPLATE_DECL, or an OVERLOAD. All
functions with the same name end up in the same slot. The first
two elements are for constructors, and destructors, respectively.
All template conversion operators to innermost template dependent
types are overloaded on the next slot, if they exist. Note, the
names for these functions will not all be the same. The
non-template conversion operators & templated conversions to
non-innermost template types are next, followed by ordinary member
functions. There may be empty entries at the end of the vector.
The conversion operators are unsorted. The ordinary member
functions are sorted, once the class is complete. */
#define CLASSTYPE_METHOD_VEC(NODE) (LANG_TYPE_CLASS_CHECK (NODE)->methods)
/* For class templates, this is a TREE_LIST of all member data,
functions, types, and friends in the order of declaration.
The TREE_PURPOSE of each TREE_LIST is NULL_TREE for a friend,
and the RECORD_TYPE for the class template otherwise. */
#define CLASSTYPE_DECL_LIST(NODE) (LANG_TYPE_CLASS_CHECK (NODE)->decl_list)
/* The slot in the CLASSTYPE_METHOD_VEC where constructors go. */
#define CLASSTYPE_CONSTRUCTOR_SLOT 0
/* The slot in the CLASSTYPE_METHOD_VEC where destructors go. */
#define CLASSTYPE_DESTRUCTOR_SLOT 1
/* The first slot in the CLASSTYPE_METHOD_VEC where conversion
operators can appear. */
#define CLASSTYPE_FIRST_CONVERSION_SLOT 2
/* A FUNCTION_DECL or OVERLOAD for the constructors for NODE. These
are the constructors that take an in-charge parameter. */
#define CLASSTYPE_CONSTRUCTORS(NODE) \
(VEC_index (tree, CLASSTYPE_METHOD_VEC (NODE), CLASSTYPE_CONSTRUCTOR_SLOT))
/* A FUNCTION_DECL for the destructor for NODE. These are the
destructors that take an in-charge parameter. If
CLASSTYPE_LAZY_DESTRUCTOR is true, then this entry will be NULL
until the destructor is created with lazily_declare_fn. */
#define CLASSTYPE_DESTRUCTORS(NODE) \
(CLASSTYPE_METHOD_VEC (NODE) \
? VEC_index (tree, CLASSTYPE_METHOD_VEC (NODE), CLASSTYPE_DESTRUCTOR_SLOT) \
: NULL_TREE)
/* A dictionary of the nested user-defined-types (class-types, or enums)
found within this class. This table includes nested member class
templates. */
#define CLASSTYPE_NESTED_UTDS(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->nested_udts)
/* Nonzero if NODE has a primary base class, i.e., a base class with
which it shares the virtual function table pointer. */
#define CLASSTYPE_HAS_PRIMARY_BASE_P(NODE) \
(CLASSTYPE_PRIMARY_BINFO (NODE) != NULL_TREE)
/* If non-NULL, this is the binfo for the primary base class, i.e.,
the base class which contains the virtual function table pointer
for this class. */
#define CLASSTYPE_PRIMARY_BINFO(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->primary_base)
/* A vector of BINFOs for the direct and indirect virtual base classes
that this type uses in a post-order depth-first left-to-right
order. (In other words, these bases appear in the order that they
should be initialized.) */
#define CLASSTYPE_VBASECLASSES(NODE) (LANG_TYPE_CLASS_CHECK (NODE)->vbases)
/* The type corresponding to NODE when NODE is used as a base class,
i.e., NODE without virtual base classes. */
#define CLASSTYPE_AS_BASE(NODE) (LANG_TYPE_CLASS_CHECK (NODE)->as_base)
/* True iff NODE is the CLASSTYPE_AS_BASE version of some type. */
#define IS_FAKE_BASE_TYPE(NODE) \
(TREE_CODE (NODE) == RECORD_TYPE \
&& TYPE_CONTEXT (NODE) && CLASS_TYPE_P (TYPE_CONTEXT (NODE)) \
&& CLASSTYPE_AS_BASE (TYPE_CONTEXT (NODE)) == (NODE))
/* These are the size and alignment of the type without its virtual
base classes, for when we use this type as a base itself. */
#define CLASSTYPE_SIZE(NODE) TYPE_SIZE (CLASSTYPE_AS_BASE (NODE))
#define CLASSTYPE_SIZE_UNIT(NODE) TYPE_SIZE_UNIT (CLASSTYPE_AS_BASE (NODE))
#define CLASSTYPE_ALIGN(NODE) TYPE_ALIGN (CLASSTYPE_AS_BASE (NODE))
#define CLASSTYPE_USER_ALIGN(NODE) TYPE_USER_ALIGN (CLASSTYPE_AS_BASE (NODE))
/* The alignment of NODE, without its virtual bases, in bytes. */
#define CLASSTYPE_ALIGN_UNIT(NODE) \
(CLASSTYPE_ALIGN (NODE) / BITS_PER_UNIT)
/* True if this a Java interface type, declared with
'__attribute__ ((java_interface))'. */
#define TYPE_JAVA_INTERFACE(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->java_interface)
/* A VEC(tree) of virtual functions which cannot be inherited by
derived classes. When deriving from this type, the derived
class must provide its own definition for each of these functions. */
#define CLASSTYPE_PURE_VIRTUALS(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->pure_virtuals)
/* Nonzero means that this type has an X() constructor. */
#define TYPE_HAS_DEFAULT_CONSTRUCTOR(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->h.has_default_ctor)
/* Nonzero means that this type contains a mutable member. */
#define CLASSTYPE_HAS_MUTABLE(NODE) (LANG_TYPE_CLASS_CHECK (NODE)->has_mutable)
#define TYPE_HAS_MUTABLE_P(NODE) (cp_has_mutable_p (NODE))
/* Nonzero means that this class type is a non-POD class. */
#define CLASSTYPE_NON_POD_P(NODE) (LANG_TYPE_CLASS_CHECK (NODE)->non_pod_class)
/* Nonzero means that this class contains pod types whose default
initialization is not a zero initialization (namely, pointers to
data members). */
#define CLASSTYPE_NON_ZERO_INIT_P(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->non_zero_init)
/* Nonzero if this class is "empty" in the sense of the C++ ABI. */
#define CLASSTYPE_EMPTY_P(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->empty_p)
/* Nonzero if this class is "nearly empty", i.e., contains only a
virtual function table pointer. */
#define CLASSTYPE_NEARLY_EMPTY_P(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->nearly_empty_p)
/* Nonzero if this class contains an empty subobject. */
#define CLASSTYPE_CONTAINS_EMPTY_CLASS_P(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->contains_empty_class_p)
/* A list of class types of which this type is a friend. The
TREE_VALUE is normally a TYPE, but will be a TEMPLATE_DECL in the
case of a template friend. */
#define CLASSTYPE_FRIEND_CLASSES(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->friend_classes)
/* A list of the classes which grant friendship to this class. */
#define CLASSTYPE_BEFRIENDING_CLASSES(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->befriending_classes)
/* Say whether this node was declared as a "class" or a "struct". */
#define CLASSTYPE_DECLARED_CLASS(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->declared_class)
/* Nonzero if this class has const members
which have no specified initialization. */
#define CLASSTYPE_READONLY_FIELDS_NEED_INIT(NODE) \
(TYPE_LANG_SPECIFIC (NODE) \
? LANG_TYPE_CLASS_CHECK (NODE)->h.const_needs_init : 0)
#define SET_CLASSTYPE_READONLY_FIELDS_NEED_INIT(NODE, VALUE) \
(LANG_TYPE_CLASS_CHECK (NODE)->h.const_needs_init = (VALUE))
/* Nonzero if this class has ref members
which have no specified initialization. */
#define CLASSTYPE_REF_FIELDS_NEED_INIT(NODE) \
(TYPE_LANG_SPECIFIC (NODE) \
? LANG_TYPE_CLASS_CHECK (NODE)->h.ref_needs_init : 0)
#define SET_CLASSTYPE_REF_FIELDS_NEED_INIT(NODE, VALUE) \
(LANG_TYPE_CLASS_CHECK (NODE)->h.ref_needs_init = (VALUE))
/* Nonzero if this class is included from a header file which employs
`#pragma interface', and it is not included in its implementation file. */
#define CLASSTYPE_INTERFACE_ONLY(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->interface_only)
/* True if we have already determined whether or not vtables, VTTs,
typeinfo, and other similar per-class data should be emitted in
this translation unit. This flag does not indicate whether or not
these items should be emitted; it only indicates that we know one
way or the other. */
#define CLASSTYPE_INTERFACE_KNOWN(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->interface_unknown == 0)
/* The opposite of CLASSTYPE_INTERFACE_KNOWN. */
#define CLASSTYPE_INTERFACE_UNKNOWN(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->interface_unknown)
#define SET_CLASSTYPE_INTERFACE_UNKNOWN_X(NODE,X) \
(LANG_TYPE_CLASS_CHECK (NODE)->interface_unknown = !!(X))
#define SET_CLASSTYPE_INTERFACE_UNKNOWN(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->interface_unknown = 1)
#define SET_CLASSTYPE_INTERFACE_KNOWN(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->interface_unknown = 0)
/* Nonzero if a _DECL node requires us to output debug info for this class. */
#define CLASSTYPE_DEBUG_REQUESTED(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->debug_requested)
/* Additional macros for inheritance information. */
/* Nonzero means that this class is on a path leading to a new vtable. */
#define BINFO_VTABLE_PATH_MARKED(NODE) BINFO_FLAG_1 (NODE)
/* Nonzero means B (a BINFO) has its own vtable. Any copies will not
have this flag set. */
#define BINFO_NEW_VTABLE_MARKED(B) (BINFO_FLAG_2 (B))
/* Compare a BINFO_TYPE with another type for equality. For a binfo,
this is functionally equivalent to using same_type_p, but
measurably faster. At least one of the arguments must be a
BINFO_TYPE. The other can be a BINFO_TYPE or a regular type. If
BINFO_TYPE(T) ever stops being the main variant of the class the
binfo is for, this macro must change. */
#define SAME_BINFO_TYPE_P(A, B) ((A) == (B))
/* Any subobject that needs a new vtable must have a vptr and must not
be a non-virtual primary base (since it would then use the vtable from a
derived class and never become non-primary.) */
#define SET_BINFO_NEW_VTABLE_MARKED(B) \
(BINFO_NEW_VTABLE_MARKED (B) = 1, \
gcc_assert (!BINFO_PRIMARY_P (B) || BINFO_VIRTUAL_P (B)), \
gcc_assert (TYPE_VFIELD (BINFO_TYPE (B))))
/* Nonzero if this binfo is for a dependent base - one that should not
be searched. */
#define BINFO_DEPENDENT_BASE_P(NODE) BINFO_FLAG_3 (NODE)
/* Nonzero if this binfo has lost its primary base binfo (because that
is a nearly-empty virtual base that has been taken by some other
base in the complete hierarchy. */
#define BINFO_LOST_PRIMARY_P(NODE) BINFO_FLAG_4 (NODE)
/* Nonzero if this BINFO is a primary base class. */
#define BINFO_PRIMARY_P(NODE) BINFO_FLAG_5(NODE)
/* Used by various search routines. */
#define IDENTIFIER_MARKED(NODE) TREE_LANG_FLAG_0 (NODE)
/* A VEC(tree_pair_s) of the vcall indices associated with the class
NODE. The PURPOSE of each element is a FUNCTION_DECL for a virtual
function. The VALUE is the index into the virtual table where the
vcall offset for that function is stored, when NODE is a virtual
base. */
#define CLASSTYPE_VCALL_INDICES(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->vcall_indices)
/* The various vtables for the class NODE. The primary vtable will be
first, followed by the construction vtables and VTT, if any. */
#define CLASSTYPE_VTABLES(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->vtables)
/* The std::type_info variable representing this class, or NULL if no
such variable has been created. This field is only set for the
TYPE_MAIN_VARIANT of the class. */
#define CLASSTYPE_TYPEINFO_VAR(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->typeinfo_var)
/* Accessor macros for the BINFO_VIRTUALS list. */
/* The number of bytes by which to adjust the `this' pointer when
calling this virtual function. Subtract this value from the this
pointer. Always non-NULL, might be constant zero though. */
#define BV_DELTA(NODE) (TREE_PURPOSE (NODE))
/* If non-NULL, the vtable index at which to find the vcall offset
when calling this virtual function. Add the value at that vtable
index to the this pointer. */
#define BV_VCALL_INDEX(NODE) (TREE_TYPE (NODE))
/* The function to call. */
#define BV_FN(NODE) (TREE_VALUE (NODE))
/* For FUNCTION_TYPE or METHOD_TYPE, a list of the exceptions that
this type can raise. Each TREE_VALUE is a _TYPE. The TREE_VALUE
will be NULL_TREE to indicate a throw specification of `()', or
no exceptions allowed. */
#define TYPE_RAISES_EXCEPTIONS(NODE) TYPE_LANG_SLOT_1 (NODE)
/* For FUNCTION_TYPE or METHOD_TYPE, return 1 iff it is declared `throw()'. */
#define TYPE_NOTHROW_P(NODE) \
(TYPE_RAISES_EXCEPTIONS (NODE) \
&& TREE_VALUE (TYPE_RAISES_EXCEPTIONS (NODE)) == NULL_TREE)
/* The binding level associated with the namespace. */
#define NAMESPACE_LEVEL(NODE) \
(DECL_LANG_SPECIFIC (NODE)->decl_flags.u.level)
/* If a DECL has DECL_LANG_SPECIFIC, it is either a lang_decl_flags or
a lang_decl (which has lang_decl_flags as its initial prefix).
This macro is nonzero for tree nodes whose DECL_LANG_SPECIFIC is
the full lang_decl, and not just lang_decl_flags. Keep these
checks in ascending code order. */
#define CAN_HAVE_FULL_LANG_DECL_P(NODE) \
(!(TREE_CODE (NODE) == FIELD_DECL \
|| TREE_CODE (NODE) == VAR_DECL \
|| TREE_CODE (NODE) == CONST_DECL \
|| TREE_CODE (NODE) == USING_DECL))
struct lang_decl_flags GTY(())
{
ENUM_BITFIELD(languages) language : 4;
unsigned global_ctor_p : 1;
unsigned global_dtor_p : 1;
unsigned anticipated_p : 1;
unsigned template_conv_p : 1;
unsigned operator_attr : 1;
unsigned constructor_attr : 1;
unsigned destructor_attr : 1;
unsigned friend_attr : 1;
unsigned static_function : 1;
unsigned pure_virtual : 1;
unsigned has_in_charge_parm_p : 1;
unsigned has_vtt_parm_p : 1;
unsigned deferred : 1;
unsigned use_template : 2;
unsigned nonconverting : 1;
unsigned not_really_extern : 1;
unsigned initialized_in_class : 1;
unsigned assignment_operator_p : 1;
unsigned u1sel : 1;
unsigned u2sel : 1;
unsigned can_be_full : 1;
unsigned thunk_p : 1;
unsigned this_thunk_p : 1;
unsigned repo_available_p : 1;
unsigned hidden_friend_p : 1;
unsigned threadprivate_or_deleted_p : 1;
unsigned defaulted_p : 1;
union lang_decl_u {
/* In a FUNCTION_DECL for which DECL_THUNK_P holds, this is
THUNK_ALIAS.
In a FUNCTION_DECL for which DECL_THUNK_P does not hold,
VAR_DECL, TYPE_DECL, or TEMPLATE_DECL, this is
DECL_TEMPLATE_INFO. */
tree GTY ((tag ("0"))) template_info;
/* In a NAMESPACE_DECL, this is NAMESPACE_LEVEL. */
struct cp_binding_level * GTY ((tag ("1"))) level;
} GTY ((desc ("%1.u1sel"))) u;
union lang_decl_u2 {
/* In a FUNCTION_DECL for which DECL_THUNK_P holds, this is
THUNK_VIRTUAL_OFFSET.
Otherwise this is DECL_ACCESS. */
tree GTY ((tag ("0"))) access;
/* For VAR_DECL in function, this is DECL_DISCRIMINATOR. */
int GTY ((tag ("1"))) discriminator;
} GTY ((desc ("%1.u2sel"))) u2;
};
/* sorted_fields is sorted based on a pointer, so we need to be able
to resort it if pointers get rearranged. */
struct lang_decl GTY(())
{
struct lang_decl_flags decl_flags;
union lang_decl_u4
{
struct full_lang_decl
{
/* In an overloaded operator, this is the value of
DECL_OVERLOADED_OPERATOR_P. */
ENUM_BITFIELD (tree_code) operator_code : 16;
unsigned u3sel : 1;
unsigned pending_inline_p : 1;
unsigned spare : 14;
/* For a non-thunk function decl, this is a tree list of
friendly classes. For a thunk function decl, it is the
thunked to function decl. */
tree befriending_classes;
/* For a non-virtual FUNCTION_DECL, this is
DECL_FRIEND_CONTEXT. For a virtual FUNCTION_DECL for which
DECL_THIS_THUNK_P does not hold, this is DECL_THUNKS. Both
this pointer and result pointer adjusting thunks are
chained here. This pointer thunks to return pointer thunks
will be chained on the return pointer thunk. */
tree context;
union lang_decl_u5
{
/* In a non-thunk FUNCTION_DECL or TEMPLATE_DECL, this is
DECL_CLONED_FUNCTION. */
tree GTY ((tag ("0"))) cloned_function;
/* In a FUNCTION_DECL for which THUNK_P holds this is the
THUNK_FIXED_OFFSET. */
HOST_WIDE_INT GTY ((tag ("1"))) fixed_offset;
} GTY ((desc ("%0.decl_flags.thunk_p"))) u5;
union lang_decl_u3
{
struct sorted_fields_type * GTY ((tag ("0"), reorder ("resort_sorted_fields")))
sorted_fields;
struct cp_token_cache * GTY ((tag ("2"))) pending_inline_info;
struct language_function * GTY ((tag ("1")))
saved_language_function;
} GTY ((desc ("%1.u3sel + %1.pending_inline_p"))) u;
} GTY ((tag ("1"))) f;
} GTY ((desc ("%1.decl_flags.can_be_full"))) u;
};
#if defined ENABLE_TREE_CHECKING && (GCC_VERSION >= 2007)
#define LANG_DECL_U2_CHECK(NODE, TF) __extension__ \
({ struct lang_decl *lt = DECL_LANG_SPECIFIC (NODE); \
if (lt->decl_flags.u2sel != TF) \
lang_check_failed (__FILE__, __LINE__, __FUNCTION__); \
<->decl_flags.u2; })
#else
#define LANG_DECL_U2_CHECK(NODE, TF) \
(&DECL_LANG_SPECIFIC (NODE)->decl_flags.u2)
#endif /* ENABLE_TREE_CHECKING */
/* For a FUNCTION_DECL or a VAR_DECL, the language linkage for the
declaration. Some entities (like a member function in a local
class, or a local variable) do not have linkage at all, and this
macro should not be used in those cases.
Implementation note: A FUNCTION_DECL without DECL_LANG_SPECIFIC was
created by language-independent code, and has C linkage. Most
VAR_DECLs have C++ linkage, and do not have DECL_LANG_SPECIFIC, but
we do create DECL_LANG_SPECIFIC for variables with non-C++ linkage. */
#define DECL_LANGUAGE(NODE) \
(DECL_LANG_SPECIFIC (NODE) \
? DECL_LANG_SPECIFIC (NODE)->decl_flags.language \
: (TREE_CODE (NODE) == FUNCTION_DECL \
? lang_c : lang_cplusplus))
/* Set the language linkage for NODE to LANGUAGE. */
#define SET_DECL_LANGUAGE(NODE, LANGUAGE) \
(DECL_LANG_SPECIFIC (NODE)->decl_flags.language = (LANGUAGE))
/* For FUNCTION_DECLs: nonzero means that this function is a constructor. */
#define DECL_CONSTRUCTOR_P(NODE) \
(DECL_LANG_SPECIFIC (NODE)->decl_flags.constructor_attr)
/* Nonzero if NODE (a FUNCTION_DECL) is a constructor for a complete
object. */
#define DECL_COMPLETE_CONSTRUCTOR_P(NODE) \
(DECL_CONSTRUCTOR_P (NODE) \
&& DECL_NAME (NODE) == complete_ctor_identifier)
/* Nonzero if NODE (a FUNCTION_DECL) is a constructor for a base
object. */
#define DECL_BASE_CONSTRUCTOR_P(NODE) \
(DECL_CONSTRUCTOR_P (NODE) \
&& DECL_NAME (NODE) == base_ctor_identifier)
/* Nonzero if NODE (a FUNCTION_DECL) is a constructor, but not either the
specialized in-charge constructor or the specialized not-in-charge
constructor. */
#define DECL_MAYBE_IN_CHARGE_CONSTRUCTOR_P(NODE) \
(DECL_CONSTRUCTOR_P (NODE) && !DECL_CLONED_FUNCTION_P (NODE))
/* Nonzero if NODE (a FUNCTION_DECL) is a copy constructor. */
#define DECL_COPY_CONSTRUCTOR_P(NODE) \
(DECL_CONSTRUCTOR_P (NODE) && copy_fn_p (NODE) > 0)
/* Nonzero if NODE (a FUNCTION_DECL) is a move constructor. */
#define DECL_MOVE_CONSTRUCTOR_P(NODE) \
(DECL_CONSTRUCTOR_P (NODE) && move_fn_p (NODE))
/* Nonzero if NODE is a destructor. */
#define DECL_DESTRUCTOR_P(NODE) \
(DECL_LANG_SPECIFIC (NODE)->decl_flags.destructor_attr)
/* Nonzero if NODE (a FUNCTION_DECL) is a destructor, but not the
specialized in-charge constructor, in-charge deleting constructor,
or the base destructor. */
#define DECL_MAYBE_IN_CHARGE_DESTRUCTOR_P(NODE) \
(DECL_DESTRUCTOR_P (NODE) && !DECL_CLONED_FUNCTION_P (NODE))
/* Nonzero if NODE (a FUNCTION_DECL) is a destructor for a complete
object. */
#define DECL_COMPLETE_DESTRUCTOR_P(NODE) \
(DECL_DESTRUCTOR_P (NODE) \
&& DECL_NAME (NODE) == complete_dtor_identifier)
/* Nonzero if NODE (a FUNCTION_DECL) is a destructor for a base
object. */
#define DECL_BASE_DESTRUCTOR_P(NODE) \
(DECL_DESTRUCTOR_P (NODE) \
&& DECL_NAME (NODE) == base_dtor_identifier)
/* Nonzero if NODE (a FUNCTION_DECL) is a destructor for a complete
object that deletes the object after it has been destroyed. */
#define DECL_DELETING_DESTRUCTOR_P(NODE) \
(DECL_DESTRUCTOR_P (NODE) \
&& DECL_NAME (NODE) == deleting_dtor_identifier)
/* Nonzero if NODE (a FUNCTION_DECL) is a cloned constructor or
destructor. */
#define DECL_CLONED_FUNCTION_P(NODE) \
((TREE_CODE (NODE) == FUNCTION_DECL \
|| TREE_CODE (NODE) == TEMPLATE_DECL) \
&& DECL_LANG_SPECIFIC (NODE) \
&& !DECL_LANG_SPECIFIC (NODE)->decl_flags.thunk_p \
&& DECL_CLONED_FUNCTION (NODE) != NULL_TREE)
/* If DECL_CLONED_FUNCTION_P holds, this is the function that was
cloned. */
#define DECL_CLONED_FUNCTION(NODE) \
(DECL_LANG_SPECIFIC (NON_THUNK_FUNCTION_CHECK(NODE))->u.f.u5.cloned_function)
/* Perform an action for each clone of FN, if FN is a function with
clones. This macro should be used like:
FOR_EACH_CLONE (clone, fn)
{ ... }
*/
#define FOR_EACH_CLONE(CLONE, FN) \
if (TREE_CODE (FN) == FUNCTION_DECL \
&& (DECL_MAYBE_IN_CHARGE_CONSTRUCTOR_P (FN) \
|| DECL_MAYBE_IN_CHARGE_DESTRUCTOR_P (FN))) \
for (CLONE = TREE_CHAIN (FN); \
CLONE && DECL_CLONED_FUNCTION_P (CLONE); \
CLONE = TREE_CHAIN (CLONE))
/* Nonzero if NODE has DECL_DISCRIMINATOR and not DECL_ACCESS. */
#define DECL_DISCRIMINATOR_P(NODE) \
(TREE_CODE (NODE) == VAR_DECL \
&& DECL_FUNCTION_SCOPE_P (NODE))
/* Discriminator for name mangling. */
#define DECL_DISCRIMINATOR(NODE) (LANG_DECL_U2_CHECK (NODE, 1)->discriminator)
/* Nonzero if the VTT parm has been added to NODE. */
#define DECL_HAS_VTT_PARM_P(NODE) \
(DECL_LANG_SPECIFIC (NODE)->decl_flags.has_vtt_parm_p)
/* Nonzero if NODE is a FUNCTION_DECL for which a VTT parameter is
required. */
#define DECL_NEEDS_VTT_PARM_P(NODE) \
(CLASSTYPE_VBASECLASSES (DECL_CONTEXT (NODE)) \
&& (DECL_BASE_CONSTRUCTOR_P (NODE) \
|| DECL_BASE_DESTRUCTOR_P (NODE)))
/* Nonzero if NODE is a user-defined conversion operator. */
#define DECL_CONV_FN_P(NODE) \
(DECL_NAME (NODE) && IDENTIFIER_TYPENAME_P (DECL_NAME (NODE)))
/* If FN is a conversion operator, the type to which it converts.
Otherwise, NULL_TREE. */
#define DECL_CONV_FN_TYPE(FN) \
(DECL_CONV_FN_P (FN) ? TREE_TYPE (DECL_NAME (FN)) : NULL_TREE)
/* Nonzero if NODE, which is a TEMPLATE_DECL, is a template
conversion operator to a type dependent on the innermost template
args. */
#define DECL_TEMPLATE_CONV_FN_P(NODE) \
(DECL_LANG_SPECIFIC (NODE)->decl_flags.template_conv_p)
/* Set the overloaded operator code for NODE to CODE. */
#define SET_OVERLOADED_OPERATOR_CODE(NODE, CODE) \
(DECL_LANG_SPECIFIC (NODE)->u.f.operator_code = (CODE))
/* If NODE is an overloaded operator, then this returns the TREE_CODE
associated with the overloaded operator.
DECL_ASSIGNMENT_OPERATOR_P must also be checked to determine
whether or not NODE is an assignment operator. If NODE is not an
overloaded operator, ERROR_MARK is returned. Since the numerical
value of ERROR_MARK is zero, this macro can be used as a predicate
to test whether or not NODE is an overloaded operator. */
#define DECL_OVERLOADED_OPERATOR_P(NODE) \
(IDENTIFIER_OPNAME_P (DECL_NAME (NODE)) \
? DECL_LANG_SPECIFIC (NODE)->u.f.operator_code : ERROR_MARK)
/* Nonzero if NODE is an assignment operator (including += and such). */
#define DECL_ASSIGNMENT_OPERATOR_P(NODE) \
(DECL_LANG_SPECIFIC (NODE)->decl_flags.assignment_operator_p)
/* For FUNCTION_DECLs: nonzero means that this function is a
constructor or a destructor with an extra in-charge parameter to
control whether or not virtual bases are constructed. */
#define DECL_HAS_IN_CHARGE_PARM_P(NODE) \
(DECL_LANG_SPECIFIC (NODE)->decl_flags.has_in_charge_parm_p)
/* Nonzero if DECL is a declaration of __builtin_constant_p. */
#define DECL_IS_BUILTIN_CONSTANT_P(NODE) \
(TREE_CODE (NODE) == FUNCTION_DECL \
&& DECL_BUILT_IN_CLASS (NODE) == BUILT_IN_NORMAL \
&& DECL_FUNCTION_CODE (NODE) == BUILT_IN_CONSTANT_P)
/* Nonzero for _DECL means that this decl appears in (or will appear
in) as a member in a RECORD_TYPE or UNION_TYPE node. It is also for
detecting circularity in case members are multiply defined. In the
case of a VAR_DECL, it is also used to determine how program storage
should be allocated. */
#define DECL_IN_AGGR_P(NODE) (DECL_LANG_FLAG_3 (NODE))
/* Nonzero for a VAR_DECL means that the variable's initialization (if
any) has been processed. (In general, DECL_INITIALIZED_P is
!DECL_EXTERN, but static data members may be initialized even if
not defined.) */
#define DECL_INITIALIZED_P(NODE) \
(TREE_LANG_FLAG_1 (VAR_DECL_CHECK (NODE)))
/* Nonzero for a VAR_DECL iff an explicit initializer was provided. */
#define DECL_NONTRIVIALLY_INITIALIZED_P(NODE) \
(TREE_LANG_FLAG_3 (VAR_DECL_CHECK (NODE)))
/* Nonzero for a VAR_DECL that was initialized with a
constant-expression. */
#define DECL_INITIALIZED_BY_CONSTANT_EXPRESSION_P(NODE) \
(TREE_LANG_FLAG_2 (VAR_DECL_CHECK (NODE)))
/* Nonzero for a VAR_DECL that can be used in an integral constant
expression.
[expr.const]
An integral constant-expression can only involve ... const
variables of static or enumeration types initialized with
constant expressions ...
The standard does not require that the expression be non-volatile.
G++ implements the proposed correction in DR 457. */
#define DECL_INTEGRAL_CONSTANT_VAR_P(NODE) \
(TREE_CODE (NODE) == VAR_DECL \
&& CP_TYPE_CONST_NON_VOLATILE_P (TREE_TYPE (NODE)) \
&& INTEGRAL_OR_ENUMERATION_TYPE_P (TREE_TYPE (NODE)) \
&& DECL_INITIALIZED_BY_CONSTANT_EXPRESSION_P (NODE))
/* Nonzero if the DECL was initialized in the class definition itself,
rather than outside the class. This is used for both static member
VAR_DECLS, and FUNCTION_DECLS that are defined in the class. */
#define DECL_INITIALIZED_IN_CLASS_P(DECL) \
(DECL_LANG_SPECIFIC (DECL)->decl_flags.initialized_in_class)
/* Nonzero for DECL means that this decl is just a friend declaration,
and should not be added to the list of members for this class. */
#define DECL_FRIEND_P(NODE) (DECL_LANG_SPECIFIC (NODE)->decl_flags.friend_attr)
/* A TREE_LIST of the types which have befriended this FUNCTION_DECL. */
#define DECL_BEFRIENDING_CLASSES(NODE) \
(DECL_LANG_SPECIFIC (NODE)->u.f.befriending_classes)
/* Nonzero for FUNCTION_DECL means that this decl is a static
member function. */
#define DECL_STATIC_FUNCTION_P(NODE) \
(DECL_LANG_SPECIFIC (NODE)->decl_flags.static_function)
/* Nonzero for FUNCTION_DECL means that this decl is a non-static
member function. */
#define DECL_NONSTATIC_MEMBER_FUNCTION_P(NODE) \
(TREE_CODE (TREE_TYPE (NODE)) == METHOD_TYPE)
/* Nonzero for FUNCTION_DECL means that this decl is a member function
(static or non-static). */
#define DECL_FUNCTION_MEMBER_P(NODE) \
(DECL_NONSTATIC_MEMBER_FUNCTION_P (NODE) || DECL_STATIC_FUNCTION_P (NODE))
/* Nonzero for FUNCTION_DECL means that this member function
has `this' as const X *const. */
#define DECL_CONST_MEMFUNC_P(NODE) \
(DECL_NONSTATIC_MEMBER_FUNCTION_P (NODE) \
&& CP_TYPE_CONST_P (TREE_TYPE (TREE_VALUE \
(TYPE_ARG_TYPES (TREE_TYPE (NODE))))))
/* Nonzero for FUNCTION_DECL means that this member function
has `this' as volatile X *const. */
#define DECL_VOLATILE_MEMFUNC_P(NODE) \
(DECL_NONSTATIC_MEMBER_FUNCTION_P (NODE) \
&& CP_TYPE_VOLATILE_P (TREE_TYPE (TREE_VALUE \
(TYPE_ARG_TYPES (TREE_TYPE (NODE))))))
/* Nonzero for a DECL means that this member is a non-static member. */
#define DECL_NONSTATIC_MEMBER_P(NODE) \
(DECL_NONSTATIC_MEMBER_FUNCTION_P (NODE) \
|| TREE_CODE (NODE) == FIELD_DECL)
/* Nonzero for _DECL means that this member object type
is mutable. */
#define DECL_MUTABLE_P(NODE) (DECL_LANG_FLAG_0 (NODE))
/* Nonzero for _DECL means that this constructor is a non-converting
constructor. */
#define DECL_NONCONVERTING_P(NODE) \
(DECL_LANG_SPECIFIC (NODE)->decl_flags.nonconverting)
/* Nonzero for FUNCTION_DECL means that this member function is a pure
virtual function. */
#define DECL_PURE_VIRTUAL_P(NODE) \
(DECL_LANG_SPECIFIC (NODE)->decl_flags.pure_virtual)
/* True (in a FUNCTION_DECL) if NODE is a virtual function that is an
invalid overrider for a function from a base class. Once we have
complained about an invalid overrider we avoid complaining about it
again. */
#define DECL_INVALID_OVERRIDER_P(NODE) \
(DECL_LANG_FLAG_4 (NODE))
/* The thunks associated with NODE, a FUNCTION_DECL. */
#define DECL_THUNKS(NODE) \
(DECL_LANG_SPECIFIC (NODE)->u.f.context)
/* Nonzero if NODE is a thunk, rather than an ordinary function. */
#define DECL_THUNK_P(NODE) \
(TREE_CODE (NODE) == FUNCTION_DECL \
&& DECL_LANG_SPECIFIC (NODE) \
&& DECL_LANG_SPECIFIC (NODE)->decl_flags.thunk_p)
/* Set DECL_THUNK_P for node. */
#define SET_DECL_THUNK_P(NODE, THIS_ADJUSTING) \
(DECL_LANG_SPECIFIC (NODE)->decl_flags.thunk_p = 1, \
DECL_LANG_SPECIFIC (NODE)->u.f.u3sel = 1, \
DECL_LANG_SPECIFIC (NODE)->decl_flags.this_thunk_p = (THIS_ADJUSTING))
/* Nonzero if NODE is a this pointer adjusting thunk. */
#define DECL_THIS_THUNK_P(NODE) \
(DECL_THUNK_P (NODE) && DECL_LANG_SPECIFIC (NODE)->decl_flags.this_thunk_p)
/* Nonzero if NODE is a result pointer adjusting thunk. */
#define DECL_RESULT_THUNK_P(NODE) \
(DECL_THUNK_P (NODE) && !DECL_LANG_SPECIFIC (NODE)->decl_flags.this_thunk_p)
/* Nonzero if NODE is a FUNCTION_DECL, but not a thunk. */
#define DECL_NON_THUNK_FUNCTION_P(NODE) \
(TREE_CODE (NODE) == FUNCTION_DECL && !DECL_THUNK_P (NODE))
/* Nonzero if NODE is `extern "C"'. */
#define DECL_EXTERN_C_P(NODE) \
(DECL_LANGUAGE (NODE) == lang_c)
/* Nonzero if NODE is an `extern "C"' function. */
#define DECL_EXTERN_C_FUNCTION_P(NODE) \
(DECL_NON_THUNK_FUNCTION_P (NODE) && DECL_EXTERN_C_P (NODE))
/* True iff DECL is an entity with vague linkage whose definition is
available in this translation unit. */
#define DECL_REPO_AVAILABLE_P(NODE) \
(DECL_LANG_SPECIFIC (NODE)->decl_flags.repo_available_p)
/* Nonzero if this DECL is the __PRETTY_FUNCTION__ variable in a
template function. */
#define DECL_PRETTY_FUNCTION_P(NODE) \
(TREE_LANG_FLAG_0 (VAR_DECL_CHECK (NODE)))
/* The _TYPE context in which this _DECL appears. This field holds the
class where a virtual function instance is actually defined. */
#define DECL_CLASS_CONTEXT(NODE) \
(DECL_CLASS_SCOPE_P (NODE) ? DECL_CONTEXT (NODE) : NULL_TREE)
/* For a non-member friend function, the class (if any) in which this
friend was defined. For example, given:
struct S { friend void f (); };
the DECL_FRIEND_CONTEXT for `f' will be `S'. */
#define DECL_FRIEND_CONTEXT(NODE) \
((DECL_FRIEND_P (NODE) && !DECL_FUNCTION_MEMBER_P (NODE)) \
? DECL_LANG_SPECIFIC (NODE)->u.f.context \
: NULL_TREE)
/* Set the DECL_FRIEND_CONTEXT for NODE to CONTEXT. */
#define SET_DECL_FRIEND_CONTEXT(NODE, CONTEXT) \
(DECL_LANG_SPECIFIC (NODE)->u.f.context = (CONTEXT))
/* NULL_TREE in DECL_CONTEXT represents the global namespace. */
#define CP_DECL_CONTEXT(NODE) \
(DECL_CONTEXT (NODE) ? DECL_CONTEXT (NODE) : global_namespace)
#define CP_TYPE_CONTEXT(NODE) \
(TYPE_CONTEXT (NODE) ? TYPE_CONTEXT (NODE) : global_namespace)
#define FROB_CONTEXT(NODE) ((NODE) == global_namespace ? NULL_TREE : (NODE))
/* 1 iff NODE has namespace scope, including the global namespace. */
#define DECL_NAMESPACE_SCOPE_P(NODE) \
(!DECL_TEMPLATE_PARM_P (NODE) \
&& TREE_CODE (CP_DECL_CONTEXT (NODE)) == NAMESPACE_DECL)
/* 1 iff NODE is a class member. */
#define DECL_CLASS_SCOPE_P(NODE) \
(DECL_CONTEXT (NODE) && TYPE_P (DECL_CONTEXT (NODE)))
#define TYPE_CLASS_SCOPE_P(NODE) \
(TYPE_CONTEXT (NODE) && TYPE_P (TYPE_CONTEXT (NODE)))
/* 1 iff NODE is function-local. */
#define DECL_FUNCTION_SCOPE_P(NODE) \
(DECL_CONTEXT (NODE) \
&& TREE_CODE (DECL_CONTEXT (NODE)) == FUNCTION_DECL)
/* 1 iff VAR_DECL node NODE is a type-info decl. This flag is set for
both the primary typeinfo object and the associated NTBS name. */
#define DECL_TINFO_P(NODE) TREE_LANG_FLAG_4 (VAR_DECL_CHECK (NODE))
/* 1 iff VAR_DECL node NODE is virtual table or VTT. */
#define DECL_VTABLE_OR_VTT_P(NODE) TREE_LANG_FLAG_5 (VAR_DECL_CHECK (NODE))
/* Returns 1 iff VAR_DECL is a construction virtual table.
DECL_VTABLE_OR_VTT_P will be true in this case and must be checked
before using this macro. */
#define DECL_CONSTRUCTION_VTABLE_P(NODE) \
TREE_LANG_FLAG_6 (VAR_DECL_CHECK (NODE))
/* 1 iff NODE is function-local, but for types. */
#define LOCAL_CLASS_P(NODE) \
(decl_function_context (TYPE_MAIN_DECL (NODE)) != NULL_TREE)
/* For a NAMESPACE_DECL: the list of using namespace directives
The PURPOSE is the used namespace, the value is the namespace
that is the common ancestor. */
#define DECL_NAMESPACE_USING(NODE) DECL_VINDEX (NAMESPACE_DECL_CHECK (NODE))
/* In a NAMESPACE_DECL, the DECL_INITIAL is used to record all users
of a namespace, to record the transitive closure of using namespace. */
#define DECL_NAMESPACE_USERS(NODE) DECL_INITIAL (NAMESPACE_DECL_CHECK (NODE))
/* In a NAMESPACE_DECL, the list of namespaces which have associated
themselves with this one. */
#define DECL_NAMESPACE_ASSOCIATIONS(NODE) \
(NAMESPACE_DECL_CHECK (NODE)->decl_non_common.saved_tree)
/* In a NAMESPACE_DECL, points to the original namespace if this is
a namespace alias. */
#define DECL_NAMESPACE_ALIAS(NODE) \
DECL_ABSTRACT_ORIGIN (NAMESPACE_DECL_CHECK (NODE))
#define ORIGINAL_NAMESPACE(NODE) \
(DECL_NAMESPACE_ALIAS (NODE) ? DECL_NAMESPACE_ALIAS (NODE) : (NODE))
/* Nonzero if NODE is the std namespace. */
#define DECL_NAMESPACE_STD_P(NODE) \
(TREE_CODE (NODE) == NAMESPACE_DECL \
&& CP_DECL_CONTEXT (NODE) == global_namespace \
&& DECL_NAME (NODE) == std_identifier)
/* In a TREE_LIST concatenating using directives, indicate indirect
directives */
#define TREE_INDIRECT_USING(NODE) (TREE_LIST_CHECK (NODE)->base.lang_flag_0)
/* In a TREE_LIST in an attribute list, indicates that the attribute
must be applied at instantiation time. */
#define ATTR_IS_DEPENDENT(NODE) (TREE_LIST_CHECK (NODE)->base.lang_flag_0)
extern tree decl_shadowed_for_var_lookup (tree);
extern void decl_shadowed_for_var_insert (tree, tree);
/* Non zero if this is a using decl for a dependent scope. */
#define DECL_DEPENDENT_P(NODE) DECL_LANG_FLAG_0 (USING_DECL_CHECK (NODE))
/* The scope named in a using decl. */
#define USING_DECL_SCOPE(NODE) TREE_TYPE (USING_DECL_CHECK (NODE))
/* The decls named by a using decl. */
#define USING_DECL_DECLS(NODE) DECL_INITIAL (USING_DECL_CHECK (NODE))
/* In a VAR_DECL, true if we have a shadowed local variable
in the shadowed var table for this VAR_DECL. */
#define DECL_HAS_SHADOWED_FOR_VAR_P(NODE) \
(VAR_DECL_CHECK (NODE)->decl_with_vis.shadowed_for_var_p)
/* In a VAR_DECL for a variable declared in a for statement,
this is the shadowed (local) variable. */
#define DECL_SHADOWED_FOR_VAR(NODE) \
(DECL_HAS_SHADOWED_FOR_VAR_P(NODE) ? decl_shadowed_for_var_lookup (NODE) : NULL)
#define SET_DECL_SHADOWED_FOR_VAR(NODE, VAL) \
(decl_shadowed_for_var_insert (NODE, VAL))
/* In a FUNCTION_DECL, this is nonzero if this function was defined in
the class definition. We have saved away the text of the function,
but have not yet processed it. */
#define DECL_PENDING_INLINE_P(NODE) \
(DECL_LANG_SPECIFIC (NODE)->u.f.pending_inline_p)
/* If DECL_PENDING_INLINE_P holds, this is the saved text of the
function. */
#define DECL_PENDING_INLINE_INFO(NODE) \
(DECL_LANG_SPECIFIC (NODE)->u.f.u.pending_inline_info)
/* For a TYPE_DECL: if this structure has many fields, we'll sort them
and put them into a TREE_VEC. */
#define DECL_SORTED_FIELDS(NODE) \
(DECL_LANG_SPECIFIC (TYPE_DECL_CHECK (NODE))->u.f.u.sorted_fields)
/* True if on the deferred_fns (see decl2.c) list. */
#define DECL_DEFERRED_FN(DECL) \
(DECL_LANG_SPECIFIC (DECL)->decl_flags.deferred)
/* If non-NULL for a VAR_DECL, FUNCTION_DECL, TYPE_DECL or
TEMPLATE_DECL, the entity is either a template specialization (if
DECL_USE_TEMPLATE is nonzero) or the abstract instance of the
template itself.
In either case, DECL_TEMPLATE_INFO is a TREE_LIST, whose
TREE_PURPOSE is the TEMPLATE_DECL of which this entity is a
specialization or abstract instance. The TREE_VALUE is the
template arguments used to specialize the template.
Consider:
template <typename T> struct S { friend void f(T) {} };
In this case, S<int>::f is, from the point of view of the compiler,
an instantiation of a template -- but, from the point of view of
the language, each instantiation of S results in a wholly unrelated
global function f. In this case, DECL_TEMPLATE_INFO for S<int>::f
will be non-NULL, but DECL_USE_TEMPLATE will be zero. */
#define DECL_TEMPLATE_INFO(NODE) \
(DECL_LANG_SPECIFIC (VAR_TEMPL_TYPE_OR_FUNCTION_DECL_CHECK (NODE)) \
->decl_flags.u.template_info)
/* For a VAR_DECL, indicates that the variable is actually a
non-static data member of anonymous union that has been promoted to
variable status. */
#define DECL_ANON_UNION_VAR_P(NODE) \
(DECL_LANG_FLAG_4 (VAR_DECL_CHECK (NODE)))
/* Template information for a RECORD_TYPE or UNION_TYPE. */
#define CLASSTYPE_TEMPLATE_INFO(NODE) \
(LANG_TYPE_CLASS_CHECK (RECORD_OR_UNION_CHECK (NODE))->template_info)
/* Template information for an ENUMERAL_TYPE. Although an enumeration may
not be a primary template, it may be declared within the scope of a
primary template and the enumeration constants may depend on
non-type template parameters. */
#define ENUM_TEMPLATE_INFO(NODE) \
(TYPE_LANG_SLOT_1 (ENUMERAL_TYPE_CHECK (NODE)))
/* Template information for a template template parameter. */
#define TEMPLATE_TEMPLATE_PARM_TEMPLATE_INFO(NODE) \
(LANG_TYPE_CLASS_CHECK (BOUND_TEMPLATE_TEMPLATE_PARM_TYPE_CHECK (NODE)) \
->template_info)
/* Template information for an ENUMERAL_, RECORD_, or UNION_TYPE. */
#define TYPE_TEMPLATE_INFO(NODE) \
(TREE_CODE (NODE) == ENUMERAL_TYPE \
? ENUM_TEMPLATE_INFO (NODE) : \
(TREE_CODE (NODE) == BOUND_TEMPLATE_TEMPLATE_PARM \
? TEMPLATE_TEMPLATE_PARM_TEMPLATE_INFO (NODE) : \
(TYPE_LANG_SPECIFIC (NODE) \
? CLASSTYPE_TEMPLATE_INFO (NODE) \
: NULL_TREE)))
/* Set the template information for an ENUMERAL_, RECORD_, or
UNION_TYPE to VAL. */
#define SET_TYPE_TEMPLATE_INFO(NODE, VAL) \
(TREE_CODE (NODE) == ENUMERAL_TYPE \
? (ENUM_TEMPLATE_INFO (NODE) = (VAL)) \
: (CLASSTYPE_TEMPLATE_INFO (NODE) = (VAL)))
#define TI_TEMPLATE(NODE) (TREE_PURPOSE (NODE))
#define TI_ARGS(NODE) (TREE_VALUE (NODE))
#define TI_PENDING_TEMPLATE_FLAG(NODE) TREE_LANG_FLAG_1 (NODE)
/* We use TREE_VECs to hold template arguments. If there is only one
level of template arguments, then the TREE_VEC contains the
arguments directly. If there is more than one level of template
arguments, then each entry in the TREE_VEC is itself a TREE_VEC,
containing the template arguments for a single level. The first
entry in the outer TREE_VEC is the outermost level of template
parameters; the last is the innermost.
It is incorrect to ever form a template argument vector containing
only one level of arguments, but which is a TREE_VEC containing as
its only entry the TREE_VEC for that level. */
/* Nonzero if the template arguments is actually a vector of vectors,
rather than just a vector. */
#define TMPL_ARGS_HAVE_MULTIPLE_LEVELS(NODE) \
(NODE && TREE_VEC_LENGTH (NODE) && TREE_VEC_ELT (NODE, 0) \
&& TREE_CODE (TREE_VEC_ELT (NODE, 0)) == TREE_VEC)
/* The depth of a template argument vector. When called directly by
the parser, we use a TREE_LIST rather than a TREE_VEC to represent
template arguments. In fact, we may even see NULL_TREE if there
are no template arguments. In both of those cases, there is only
one level of template arguments. */
#define TMPL_ARGS_DEPTH(NODE) \
(TMPL_ARGS_HAVE_MULTIPLE_LEVELS (NODE) ? TREE_VEC_LENGTH (NODE) : 1)
/* The LEVELth level of the template ARGS. The outermost level of
args is level 1, not level 0. */
#define TMPL_ARGS_LEVEL(ARGS, LEVEL) \
(TMPL_ARGS_HAVE_MULTIPLE_LEVELS (ARGS) \
? TREE_VEC_ELT (ARGS, (LEVEL) - 1) : (ARGS))
/* Set the LEVELth level of the template ARGS to VAL. This macro does
not work with single-level argument vectors. */
#define SET_TMPL_ARGS_LEVEL(ARGS, LEVEL, VAL) \
(TREE_VEC_ELT (ARGS, (LEVEL) - 1) = (VAL))
/* Accesses the IDXth parameter in the LEVELth level of the ARGS. */
#define TMPL_ARG(ARGS, LEVEL, IDX) \
(TREE_VEC_ELT (TMPL_ARGS_LEVEL (ARGS, LEVEL), IDX))
/* Given a single level of template arguments in NODE, return the
number of arguments. */
#define NUM_TMPL_ARGS(NODE) \
(TREE_VEC_LENGTH (NODE))
/* Returns the innermost level of template arguments in ARGS. */
#define INNERMOST_TEMPLATE_ARGS(NODE) \
(get_innermost_template_args ((NODE), 1))
/* The number of levels of template parameters given by NODE. */
#define TMPL_PARMS_DEPTH(NODE) \
((HOST_WIDE_INT) TREE_INT_CST_LOW (TREE_PURPOSE (NODE)))
/* The TEMPLATE_DECL instantiated or specialized by NODE. This
TEMPLATE_DECL will be the immediate parent, not the most general
template. For example, in:
template <class T> struct S { template <class U> void f(U); }
the FUNCTION_DECL for S<int>::f<double> will have, as its
DECL_TI_TEMPLATE, `template <class U> S<int>::f<U>'.
As a special case, for a member friend template of a template
class, this value will not be a TEMPLATE_DECL, but rather an
IDENTIFIER_NODE or OVERLOAD indicating the name of the template and
any explicit template arguments provided. For example, in:
template <class T> struct S { friend void f<int>(int, double); }
the DECL_TI_TEMPLATE will be an IDENTIFIER_NODE for `f' and the
DECL_TI_ARGS will be {int}. */
#define DECL_TI_TEMPLATE(NODE) TI_TEMPLATE (DECL_TEMPLATE_INFO (NODE))
/* The template arguments used to obtain this decl from the most
general form of DECL_TI_TEMPLATE. For the example given for
DECL_TI_TEMPLATE, the DECL_TI_ARGS will be {int, double}. These
are always the full set of arguments required to instantiate this
declaration from the most general template specialized here. */
#define DECL_TI_ARGS(NODE) TI_ARGS (DECL_TEMPLATE_INFO (NODE))
/* The TEMPLATE_DECL associated with NODE, a class type. Even if NODE
will be generated from a partial specialization, the TEMPLATE_DECL
referred to here will be the original template. For example,
given:
template <typename T> struct S {};
template <typename T> struct S<T*> {};
the CLASSTPYE_TI_TEMPLATE for S<int*> will be S, not the S<T*>. */
#define CLASSTYPE_TI_TEMPLATE(NODE) TI_TEMPLATE (CLASSTYPE_TEMPLATE_INFO (NODE))
#define CLASSTYPE_TI_ARGS(NODE) TI_ARGS (CLASSTYPE_TEMPLATE_INFO (NODE))
/* For a template instantiation TYPE, returns the TYPE corresponding
to the primary template. Otherwise returns TYPE itself. */
#define CLASSTYPE_PRIMARY_TEMPLATE_TYPE(TYPE) \
((CLASSTYPE_USE_TEMPLATE ((TYPE)) \
&& !CLASSTYPE_TEMPLATE_SPECIALIZATION ((TYPE))) \
? TREE_TYPE (DECL_TEMPLATE_RESULT (DECL_PRIMARY_TEMPLATE \
(CLASSTYPE_TI_TEMPLATE ((TYPE))))) \
: (TYPE))
/* Like CLASS_TI_TEMPLATE, but also works for ENUMERAL_TYPEs. */
#define TYPE_TI_TEMPLATE(NODE) \
(TI_TEMPLATE (TYPE_TEMPLATE_INFO (NODE)))
/* Like DECL_TI_ARGS, but for an ENUMERAL_, RECORD_, or UNION_TYPE. */
#define TYPE_TI_ARGS(NODE) \
(TI_ARGS (TYPE_TEMPLATE_INFO (NODE)))
#define INNERMOST_TEMPLATE_PARMS(NODE) TREE_VALUE (NODE)
/* Nonzero if NODE (a TEMPLATE_DECL) is a member template, in the
sense of [temp.mem]. */
#define DECL_MEMBER_TEMPLATE_P(NODE) \
(DECL_LANG_FLAG_1 (TEMPLATE_DECL_CHECK (NODE)))
/* Nonzero if the NODE corresponds to the template parameters for a
member template, whose inline definition is being processed after
the class definition is complete. */
#define TEMPLATE_PARMS_FOR_INLINE(NODE) TREE_LANG_FLAG_1 (NODE)
/* Determine if a parameter (i.e., a PARM_DECL) is a function
parameter pack. */
#define FUNCTION_PARAMETER_PACK_P(NODE) \
(DECL_LANG_FLAG_1 (PARM_DECL_CHECK (NODE)))
/* Determines if NODE is an expansion of one or more parameter packs,
e.g., a TYPE_PACK_EXPANSION or EXPR_PACK_EXPANSION. */
#define PACK_EXPANSION_P(NODE) \
(TREE_CODE (NODE) == TYPE_PACK_EXPANSION \
|| TREE_CODE (NODE) == EXPR_PACK_EXPANSION)
/* Extracts the type or expression pattern from a TYPE_PACK_EXPANSION or
EXPR_PACK_EXPANSION. */
#define PACK_EXPANSION_PATTERN(NODE) \
(TREE_CODE (NODE) == TYPE_PACK_EXPANSION? TREE_TYPE (NODE) \
: TREE_OPERAND (NODE, 0))
/* Sets the type or expression pattern for a TYPE_PACK_EXPANSION or
EXPR_PACK_EXPANSION. */
#define SET_PACK_EXPANSION_PATTERN(NODE,VALUE) \
if (TREE_CODE (NODE) == TYPE_PACK_EXPANSION) \
TREE_TYPE (NODE) = VALUE; \
else \
TREE_OPERAND (NODE, 0) = VALUE
/* The list of parameter packs used in the PACK_EXPANSION_* node. The
TREE_VALUE of each TREE_LIST contains the parameter packs. */
#define PACK_EXPANSION_PARAMETER_PACKS(NODE) TREE_CHAIN (NODE)
/* Determine if this is an argument pack. */
#define ARGUMENT_PACK_P(NODE) \
(TREE_CODE (NODE) == TYPE_ARGUMENT_PACK \
|| TREE_CODE (NODE) == NONTYPE_ARGUMENT_PACK)
/* The arguments stored in an argument pack. Arguments are stored in a
TREE_VEC, which may have length zero. */
#define ARGUMENT_PACK_ARGS(NODE) \
(TREE_CODE (NODE) == TYPE_ARGUMENT_PACK? TREE_TYPE (NODE) \
: TREE_OPERAND (NODE, 0))
/* Set the arguments stored in an argument pack. VALUE must be a
TREE_VEC. */
#define SET_ARGUMENT_PACK_ARGS(NODE,VALUE) \
if (TREE_CODE (NODE) == TYPE_ARGUMENT_PACK) \
TREE_TYPE (NODE) = VALUE; \
else \
TREE_OPERAND (NODE, 0) = VALUE
/* Whether the argument pack is "incomplete", meaning that more
arguments can still be deduced. Incomplete argument packs are only
used when the user has provided an explicit template argument list
for a variadic function template. Some of the explicit template
arguments will be placed into the beginning of the argument pack,
but additional arguments might still be deduced. */
#define ARGUMENT_PACK_INCOMPLETE_P(NODE) \
TREE_LANG_FLAG_0 (ARGUMENT_PACK_ARGS (NODE))
/* When ARGUMENT_PACK_INCOMPLETE_P, stores the explicit template
arguments used to fill this pack. */
#define ARGUMENT_PACK_EXPLICIT_ARGS(NODE) \
TREE_TYPE (ARGUMENT_PACK_ARGS (NODE))
/* In an ARGUMENT_PACK_SELECT, the argument pack from which an
argument will be selected. */
#define ARGUMENT_PACK_SELECT_FROM_PACK(NODE) \
(((struct tree_argument_pack_select *)ARGUMENT_PACK_SELECT_CHECK (NODE))->argument_pack)
/* In an ARGUMENT_PACK_SELECT, the index of the argument we want to
select. */
#define ARGUMENT_PACK_SELECT_INDEX(NODE) \
(((struct tree_argument_pack_select *)ARGUMENT_PACK_SELECT_CHECK (NODE))->index)
/* In an ARGUMENT_PACK_SELECT, the actual underlying argument that the
ARGUMENT_PACK_SELECT represents. */
#define ARGUMENT_PACK_SELECT_ARG(NODE) \
TREE_VEC_ELT (ARGUMENT_PACK_ARGS (ARGUMENT_PACK_SELECT_FROM_PACK (NODE)), \
ARGUMENT_PACK_SELECT_INDEX (NODE));
/* In a FUNCTION_DECL, the saved language-specific per-function data. */
#define DECL_SAVED_FUNCTION_DATA(NODE) \
(DECL_LANG_SPECIFIC (FUNCTION_DECL_CHECK (NODE)) \
->u.f.u.saved_language_function)
/* Indicates an indirect_expr is for converting a reference. */
#define REFERENCE_REF_P(NODE) \
TREE_LANG_FLAG_0 (INDIRECT_REF_CHECK (NODE))
#define NEW_EXPR_USE_GLOBAL(NODE) \
TREE_LANG_FLAG_0 (NEW_EXPR_CHECK (NODE))
#define DELETE_EXPR_USE_GLOBAL(NODE) \
TREE_LANG_FLAG_0 (DELETE_EXPR_CHECK (NODE))
#define DELETE_EXPR_USE_VEC(NODE) \
TREE_LANG_FLAG_1 (DELETE_EXPR_CHECK (NODE))
/* Indicates that this is a non-dependent COMPOUND_EXPR which will
resolve to a function call. */
#define COMPOUND_EXPR_OVERLOADED(NODE) \
TREE_LANG_FLAG_0 (COMPOUND_EXPR_CHECK (NODE))
/* In a CALL_EXPR appearing in a template, true if Koenig lookup
should be performed at instantiation time. */
#define KOENIG_LOOKUP_P(NODE) TREE_LANG_FLAG_0 (CALL_EXPR_CHECK (NODE))
/* Indicates whether a string literal has been parenthesized. Such
usages are disallowed in certain circumstances. */
#define PAREN_STRING_LITERAL_P(NODE) \
TREE_LANG_FLAG_0 (STRING_CST_CHECK (NODE))
/* Nonzero if this AGGR_INIT_EXPR provides for initialization via a
constructor call, rather than an ordinary function call. */
#define AGGR_INIT_VIA_CTOR_P(NODE) \
TREE_LANG_FLAG_0 (AGGR_INIT_EXPR_CHECK (NODE))
/* Nonzero if expanding this AGGR_INIT_EXPR should first zero-initialize
the object. */
#define AGGR_INIT_ZERO_FIRST(NODE) \
TREE_LANG_FLAG_2 (AGGR_INIT_EXPR_CHECK (NODE))
/* AGGR_INIT_EXPR accessors. These are equivalent to the CALL_EXPR
accessors, except for AGGR_INIT_EXPR_SLOT (which takes the place of
CALL_EXPR_STATIC_CHAIN). */
#define AGGR_INIT_EXPR_FN(NODE) TREE_OPERAND (AGGR_INIT_EXPR_CHECK (NODE), 1)
#define AGGR_INIT_EXPR_SLOT(NODE) \
TREE_OPERAND (AGGR_INIT_EXPR_CHECK (NODE), 2)
#define AGGR_INIT_EXPR_ARG(NODE, I) \
TREE_OPERAND (AGGR_INIT_EXPR_CHECK (NODE), (I) + 3)
#define aggr_init_expr_nargs(NODE) (VL_EXP_OPERAND_LENGTH(NODE) - 3)
/* AGGR_INIT_EXPR_ARGP returns a pointer to the argument vector for NODE.
We can't use &AGGR_INIT_EXPR_ARG (NODE, 0) because that will complain if
the argument count is zero when checking is enabled. Instead, do
the pointer arithmetic to advance past the 3 fixed operands in a
AGGR_INIT_EXPR. That produces a valid pointer to just past the end of
the operand array, even if it's not valid to dereference it. */
#define AGGR_INIT_EXPR_ARGP(NODE) \
(&(TREE_OPERAND (AGGR_INIT_EXPR_CHECK (NODE), 0)) + 3)
/* Abstract iterators for AGGR_INIT_EXPRs. */
/* Structure containing iterator state. */
typedef struct aggr_init_expr_arg_iterator_d GTY (())
{
tree t; /* the aggr_init_expr */
int n; /* argument count */
int i; /* next argument index */
} aggr_init_expr_arg_iterator;
/* Initialize the abstract argument list iterator object ITER with the
arguments from AGGR_INIT_EXPR node EXP. */
static inline void
init_aggr_init_expr_arg_iterator (tree exp,
aggr_init_expr_arg_iterator *iter)
{
iter->t = exp;
iter->n = aggr_init_expr_nargs (exp);
iter->i = 0;
}
/* Return the next argument from abstract argument list iterator object ITER,
and advance its state. Return NULL_TREE if there are no more arguments. */
static inline tree
next_aggr_init_expr_arg (aggr_init_expr_arg_iterator *iter)
{
tree result;
if (iter->i >= iter->n)
return NULL_TREE;
result = AGGR_INIT_EXPR_ARG (iter->t, iter->i);
iter->i++;
return result;
}
/* Initialize the abstract argument list iterator object ITER, then advance
past and return the first argument. Useful in for expressions, e.g.
for (arg = first_aggr_init_expr_arg (exp, &iter); arg;
arg = next_aggr_init_expr_arg (&iter)) */
static inline tree
first_aggr_init_expr_arg (tree exp, aggr_init_expr_arg_iterator *iter)
{
init_aggr_init_expr_arg_iterator (exp, iter);
return next_aggr_init_expr_arg (iter);
}
/* Test whether there are more arguments in abstract argument list iterator
ITER, without changing its state. */
static inline bool
more_aggr_init_expr_args_p (const aggr_init_expr_arg_iterator *iter)
{
return (iter->i < iter->n);
}
/* Iterate through each argument ARG of AGGR_INIT_EXPR CALL, using variable
ITER (of type aggr_init_expr_arg_iterator) to hold the iteration state. */
#define FOR_EACH_AGGR_INIT_EXPR_ARG(arg, iter, call) \
for ((arg) = first_aggr_init_expr_arg ((call), &(iter)); (arg); \
(arg) = next_aggr_init_expr_arg (&(iter)))
/* The TYPE_MAIN_DECL for a class template type is a TYPE_DECL, not a
TEMPLATE_DECL. This macro determines whether or not a given class
type is really a template type, as opposed to an instantiation or
specialization of one. */
#define CLASSTYPE_IS_TEMPLATE(NODE) \
(CLASSTYPE_TEMPLATE_INFO (NODE) \
&& !CLASSTYPE_USE_TEMPLATE (NODE) \
&& PRIMARY_TEMPLATE_P (CLASSTYPE_TI_TEMPLATE (NODE)))
/* The name used by the user to name the typename type. Typically,
this is an IDENTIFIER_NODE, and the same as the DECL_NAME on the
corresponding TYPE_DECL. However, this may also be a
TEMPLATE_ID_EXPR if we had something like `typename X::Y<T>'. */
#define TYPENAME_TYPE_FULLNAME(NODE) (TYPENAME_TYPE_CHECK (NODE))->type.values
/* True if a TYPENAME_TYPE was declared as an "enum". */
#define TYPENAME_IS_ENUM_P(NODE) \
(TREE_LANG_FLAG_0 (TYPENAME_TYPE_CHECK (NODE)))
/* True if a TYPENAME_TYPE was declared as a "class", "struct", or
"union". */
#define TYPENAME_IS_CLASS_P(NODE) \
(TREE_LANG_FLAG_1 (TYPENAME_TYPE_CHECK (NODE)))
/* True if a TYPENAME_TYPE is in the process of being resolved. */
#define TYPENAME_IS_RESOLVING_P(NODE) \
(TREE_LANG_FLAG_2 (TYPENAME_TYPE_CHECK (NODE)))
/* Nonzero in INTEGER_CST means that this int is negative by dint of
using a twos-complement negated operand. */
#define TREE_NEGATED_INT(NODE) TREE_LANG_FLAG_0 (INTEGER_CST_CHECK (NODE))
/* [class.virtual]
A class that declares or inherits a virtual function is called a
polymorphic class. */
#define TYPE_POLYMORPHIC_P(NODE) (TREE_LANG_FLAG_2 (NODE))
/* Nonzero if this class has a virtual function table pointer. */
#define TYPE_CONTAINS_VPTR_P(NODE) \
(TYPE_POLYMORPHIC_P (NODE) || CLASSTYPE_VBASECLASSES (NODE))
/* This flag is true of a local VAR_DECL if it was declared in a for
statement, but we are no longer in the scope of the for. */
#define DECL_DEAD_FOR_LOCAL(NODE) DECL_LANG_FLAG_7 (VAR_DECL_CHECK (NODE))
/* This flag is set on a VAR_DECL that is a DECL_DEAD_FOR_LOCAL
if we already emitted a warning about using it. */
#define DECL_ERROR_REPORTED(NODE) DECL_LANG_FLAG_0 (VAR_DECL_CHECK (NODE))
/* Nonzero if NODE is a FUNCTION_DECL (for a function with global
scope) declared in a local scope. */
#define DECL_LOCAL_FUNCTION_P(NODE) \
DECL_LANG_FLAG_0 (FUNCTION_DECL_CHECK (NODE))
/* Nonzero if NODE is a DECL which we know about but which has not
been explicitly declared, such as a built-in function or a friend
declared inside a class. In the latter case DECL_HIDDEN_FRIEND_P
will be set. */
#define DECL_ANTICIPATED(NODE) \
(DECL_LANG_SPECIFIC (DECL_COMMON_CHECK (NODE))->decl_flags.anticipated_p)
/* Nonzero if NODE is a FUNCTION_DECL which was declared as a friend
within a class but has not been declared in the surrounding scope.
The function is invisible except via argument dependent lookup. */
#define DECL_HIDDEN_FRIEND_P(NODE) \
(DECL_LANG_SPECIFIC (DECL_COMMON_CHECK (NODE))->decl_flags.hidden_friend_p)
/* Nonzero if DECL has been declared threadprivate by
#pragma omp threadprivate. */
#define CP_DECL_THREADPRIVATE_P(DECL) \
(DECL_LANG_SPECIFIC (VAR_DECL_CHECK (DECL))->decl_flags.threadprivate_or_deleted_p)
/* Nonzero if DECL was declared with '= delete'. */
#define DECL_DELETED_FN(DECL) \
(DECL_LANG_SPECIFIC (FUNCTION_DECL_CHECK (DECL))->decl_flags.threadprivate_or_deleted_p)
/* Nonzero if DECL was declared with '= default'. */
#define DECL_DEFAULTED_FN(DECL) \
(DECL_LANG_SPECIFIC (FUNCTION_DECL_CHECK (DECL))->decl_flags.defaulted_p)
/* Record whether a typedef for type `int' was actually `signed int'. */
#define C_TYPEDEF_EXPLICITLY_SIGNED(EXP) DECL_LANG_FLAG_1 (EXP)
/* Returns nonzero if DECL has external linkage, as specified by the
language standard. (This predicate may hold even when the
corresponding entity is not actually given external linkage in the
object file; see decl_linkage for details.) */
#define DECL_EXTERNAL_LINKAGE_P(DECL) \
(decl_linkage (DECL) == lk_external)
/* Keep these codes in ascending code order. */
#define INTEGRAL_CODE_P(CODE) \
((CODE) == ENUMERAL_TYPE \
|| (CODE) == BOOLEAN_TYPE \
|| (CODE) == INTEGER_TYPE)
/* [basic.fundamental]
Types bool, char, wchar_t, and the signed and unsigned integer types
are collectively called integral types.
Note that INTEGRAL_TYPE_P, as defined in tree.h, allows enumeration
types as well, which is incorrect in C++. Keep these checks in
ascending code order. */
#define CP_INTEGRAL_TYPE_P(TYPE) \
(TREE_CODE (TYPE) == BOOLEAN_TYPE \
|| TREE_CODE (TYPE) == INTEGER_TYPE)
/* Returns true if TYPE is an integral or enumeration name. Keep
these checks in ascending code order. */
#define INTEGRAL_OR_ENUMERATION_TYPE_P(TYPE) \
(TREE_CODE (TYPE) == ENUMERAL_TYPE || CP_INTEGRAL_TYPE_P (TYPE))
/* Returns true if TYPE is an integral or unscoped enumeration type. */
#define INTEGRAL_OR_UNSCOPED_ENUMERATION_TYPE_P(TYPE) \
(UNSCOPED_ENUM_P (TYPE) || CP_INTEGRAL_TYPE_P (TYPE))
/* [basic.fundamental]
Integral and floating types are collectively called arithmetic
types.
As a GNU extension, we also accept complex types.
Keep these checks in ascending code order. */
#define ARITHMETIC_TYPE_P(TYPE) \
(CP_INTEGRAL_TYPE_P (TYPE) \
|| TREE_CODE (TYPE) == REAL_TYPE \
|| TREE_CODE (TYPE) == COMPLEX_TYPE)
/* [basic.types]
Arithmetic types, enumeration types, pointer types, and
pointer-to-member types, are collectively called scalar types.
Keep these checks in ascending code order. */
#define SCALAR_TYPE_P(TYPE) \
(TYPE_PTRMEM_P (TYPE) \
|| TREE_CODE (TYPE) == ENUMERAL_TYPE \
|| ARITHMETIC_TYPE_P (TYPE) \
|| TYPE_PTR_P (TYPE) \
|| TYPE_PTRMEMFUNC_P (TYPE))
/* Determines whether this type is a C++0x scoped enumeration
type. Scoped enumerations types are introduced via "enum class" or
"enum struct", e.g.,
enum class Color {
Red, Green, Blue
};
Scoped enumeration types are different from normal (unscoped)
enumeration types in several ways:
- The enumerators of a scoped enumeration type are only available
within the scope of the enumeration type and not in the
enclosing scope. For example, the Red color can be referred to
with "Color::Red" but not "Red".
- Scoped enumerators and enumerations do not implicitly convert
to integers or 'bool'.
- The underlying type of the enum is well-defined. */
#define SCOPED_ENUM_P(TYPE) \
(TREE_CODE (TYPE) == ENUMERAL_TYPE && TYPE_LANG_FLAG_5 (TYPE))
/* Determine whether this is an unscoped enumeration type. */
#define UNSCOPED_ENUM_P(TYPE) \
(TREE_CODE (TYPE) == ENUMERAL_TYPE && !TYPE_LANG_FLAG_5 (TYPE))
/* Set the flag indicating whether an ENUMERAL_TYPE is a C++0x scoped
enumeration type (1) or a normal (unscoped) enumeration type
(0). */
#define SET_SCOPED_ENUM_P(TYPE, VAL) \
(TYPE_LANG_FLAG_5 (ENUMERAL_TYPE_CHECK (TYPE)) = (VAL))
/* Returns the underlying type of the given enumeration type. The
underlying type is determined in different ways, depending on the
properties of the enum:
- In C++0x, the underlying type can be explicitly specified, e.g.,
enum E1 : char { ... } // underlying type is char
- In a C++0x scoped enumeration, the underlying type is int
unless otherwises specified:
enum class E2 { ... } // underlying type is int
- Otherwise, the underlying type is determined based on the
values of the enumerators. In this case, the
ENUM_UNDERLYING_TYPE will not be set until after the definition
of the enumeration is completed by finish_enum. */
#define ENUM_UNDERLYING_TYPE(TYPE) \
TREE_TYPE (ENUMERAL_TYPE_CHECK (TYPE))
/* [dcl.init.aggr]
An aggregate is an array or a class with no user-declared
constructors, no private or protected non-static data members, no
base classes, and no virtual functions.
As an extension, we also treat vectors as aggregates. Keep these
checks in ascending code order. */
#define CP_AGGREGATE_TYPE_P(TYPE) \
(TREE_CODE (TYPE) == VECTOR_TYPE \
||TREE_CODE (TYPE) == ARRAY_TYPE \
|| (CLASS_TYPE_P (TYPE) && !CLASSTYPE_NON_AGGREGATE (TYPE)))
/* Nonzero for a class type means that the class type has a
user-declared constructor. */
#define TYPE_HAS_USER_CONSTRUCTOR(NODE) (TYPE_LANG_FLAG_1 (NODE))
/* When appearing in an INDIRECT_REF, it means that the tree structure
underneath is actually a call to a constructor. This is needed
when the constructor must initialize local storage (which can
be automatically destroyed), rather than allowing it to allocate
space from the heap.
When appearing in a SAVE_EXPR, it means that underneath
is a call to a constructor.
When appearing in a CONSTRUCTOR, the expression is a
compound literal.
When appearing in a FIELD_DECL, it means that this field
has been duly initialized in its constructor. */
#define TREE_HAS_CONSTRUCTOR(NODE) (TREE_LANG_FLAG_4 (NODE))
/* True if NODE is a brace-enclosed initializer. */
#define BRACE_ENCLOSED_INITIALIZER_P(NODE) \
(TREE_CODE (NODE) == CONSTRUCTOR && TREE_TYPE (NODE) == init_list_type_node)
/* True if NODE is a compound-literal, i.e., a brace-enclosed
initializer cast to a particular type. */
#define COMPOUND_LITERAL_P(NODE) \
(TREE_CODE (NODE) == CONSTRUCTOR && TREE_HAS_CONSTRUCTOR (NODE))
#define EMPTY_CONSTRUCTOR_P(NODE) (TREE_CODE (NODE) == CONSTRUCTOR \
&& VEC_empty (constructor_elt, \
CONSTRUCTOR_ELTS (NODE)) \
&& !TREE_HAS_CONSTRUCTOR (NODE))
/* True if NODE is a init-list used as a direct-initializer, i.e.
B b{1,2}, not B b({1,2}) or B b = {1,2}. */
#define CONSTRUCTOR_IS_DIRECT_INIT(NODE) (TREE_LANG_FLAG_0 (CONSTRUCTOR_CHECK (NODE)))
/* Nonzero means that an object of this type can not be initialized using
an initializer list. */
#define CLASSTYPE_NON_AGGREGATE(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->non_aggregate)
#define TYPE_NON_AGGREGATE_CLASS(NODE) \
(CLASS_TYPE_P (NODE) && CLASSTYPE_NON_AGGREGATE (NODE))
/* Nonzero if there is a user-defined X::op=(x&) for this class. */
#define TYPE_HAS_COMPLEX_ASSIGN_REF(NODE) (LANG_TYPE_CLASS_CHECK (NODE)->has_complex_assign_ref)
/* Nonzero if there is a user-defined X::X(x&) for this class. */
#define TYPE_HAS_COMPLEX_INIT_REF(NODE) (LANG_TYPE_CLASS_CHECK (NODE)->has_complex_init_ref)
/* Nonzero if there is a user-defined default constructor for this class. */
#define TYPE_HAS_COMPLEX_DFLT(NODE) (LANG_TYPE_CLASS_CHECK (NODE)->has_complex_dflt)
/* Nonzero if TYPE has a trivial destructor. From [class.dtor]:
A destructor is trivial if it is an implicitly declared
destructor and if:
- all of the direct base classes of its class have trivial
destructors,
- for all of the non-static data members of its class that are
of class type (or array thereof), each such class has a
trivial destructor. */
#define TYPE_HAS_TRIVIAL_DESTRUCTOR(NODE) \
(!TYPE_HAS_NONTRIVIAL_DESTRUCTOR (NODE))
/* Nonzero for _TYPE node means that this type does not have a trivial
destructor. Therefore, destroying an object of this type will
involve a call to a destructor. This can apply to objects of
ARRAY_TYPE is the type of the elements needs a destructor. */
#define TYPE_HAS_NONTRIVIAL_DESTRUCTOR(NODE) \
(TYPE_LANG_FLAG_4 (NODE))
/* Nonzero for class type means that the default constructor is trivial. */
#define TYPE_HAS_TRIVIAL_DFLT(NODE) \
(TYPE_HAS_DEFAULT_CONSTRUCTOR (NODE) && ! TYPE_HAS_COMPLEX_DFLT (NODE))
/* Nonzero for class type means that copy initialization of this type can use
a bitwise copy. */
#define TYPE_HAS_TRIVIAL_INIT_REF(NODE) \
(TYPE_HAS_INIT_REF (NODE) && ! TYPE_HAS_COMPLEX_INIT_REF (NODE))
/* Nonzero for class type means that assignment of this type can use
a bitwise copy. */
#define TYPE_HAS_TRIVIAL_ASSIGN_REF(NODE) \
(TYPE_HAS_ASSIGN_REF (NODE) && ! TYPE_HAS_COMPLEX_ASSIGN_REF (NODE))
/* Returns true if NODE is a pointer-to-data-member. */
#define TYPE_PTRMEM_P(NODE) \
(TREE_CODE (NODE) == OFFSET_TYPE)
/* Returns true if NODE is a pointer. */
#define TYPE_PTR_P(NODE) \
(TREE_CODE (NODE) == POINTER_TYPE)
/* Returns true if NODE is an object type:
[basic.types]
An object type is a (possibly cv-qualified) type that is not a
function type, not a reference type, and not a void type.
Keep these checks in ascending order, for speed. */
#define TYPE_OBJ_P(NODE) \
(TREE_CODE (NODE) != REFERENCE_TYPE \
&& TREE_CODE (NODE) != VOID_TYPE \
&& TREE_CODE (NODE) != FUNCTION_TYPE \
&& TREE_CODE (NODE) != METHOD_TYPE)
/* Returns true if NODE is a pointer to an object. Keep these checks
in ascending tree code order. */
#define TYPE_PTROB_P(NODE) \
(TYPE_PTR_P (NODE) && TYPE_OBJ_P (TREE_TYPE (NODE)))
/* Returns true if NODE is a reference to an object. Keep these checks
in ascending tree code order. */
#define TYPE_REF_OBJ_P(NODE) \
(TREE_CODE (NODE) == REFERENCE_TYPE && TYPE_OBJ_P (TREE_TYPE (NODE)))
/* True if reference type NODE is an rvalue reference */
#define TYPE_REF_IS_RVALUE(NODE) \
TREE_LANG_FLAG_0 (REFERENCE_TYPE_CHECK (NODE))
/* Returns true if NODE is a pointer to an object, or a pointer to
void. Keep these checks in ascending tree code order. */
#define TYPE_PTROBV_P(NODE) \
(TYPE_PTR_P (NODE) \
&& !(TREE_CODE (TREE_TYPE (NODE)) == FUNCTION_TYPE \
|| TREE_CODE (TREE_TYPE (NODE)) == METHOD_TYPE))
/* Returns true if NODE is a pointer to function. */
#define TYPE_PTRFN_P(NODE) \
(TREE_CODE (NODE) == POINTER_TYPE \
&& TREE_CODE (TREE_TYPE (NODE)) == FUNCTION_TYPE)
/* Returns true if NODE is a reference to function. */
#define TYPE_REFFN_P(NODE) \
(TREE_CODE (NODE) == REFERENCE_TYPE \
&& TREE_CODE (TREE_TYPE (NODE)) == FUNCTION_TYPE)
/* Nonzero for _TYPE node means that this type is a pointer to member
function type. */
#define TYPE_PTRMEMFUNC_P(NODE) \
(TREE_CODE (NODE) == RECORD_TYPE \
&& TYPE_LANG_SPECIFIC (NODE) \
&& TYPE_PTRMEMFUNC_FLAG (NODE))
#define TYPE_PTRMEMFUNC_FLAG(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->ptrmemfunc_flag)
/* Returns true if NODE is a pointer-to-member. */
#define TYPE_PTR_TO_MEMBER_P(NODE) \
(TYPE_PTRMEM_P (NODE) || TYPE_PTRMEMFUNC_P (NODE))
/* Indicates when overload resolution may resolve to a pointer to
member function. [expr.unary.op]/3 */
#define PTRMEM_OK_P(NODE) \
TREE_LANG_FLAG_0 (TREE_CHECK2 ((NODE), ADDR_EXPR, OFFSET_REF))
/* Get the POINTER_TYPE to the METHOD_TYPE associated with this
pointer to member function. TYPE_PTRMEMFUNC_P _must_ be true,
before using this macro. */
#define TYPE_PTRMEMFUNC_FN_TYPE(NODE) \
(TREE_TYPE (TYPE_FIELDS (NODE)))
/* Returns `A' for a type like `int (A::*)(double)' */
#define TYPE_PTRMEMFUNC_OBJECT_TYPE(NODE) \
TYPE_METHOD_BASETYPE (TREE_TYPE (TYPE_PTRMEMFUNC_FN_TYPE (NODE)))
/* These are use to manipulate the canonical RECORD_TYPE from the
hashed POINTER_TYPE, and can only be used on the POINTER_TYPE. */
#define TYPE_GET_PTRMEMFUNC_TYPE(NODE) \
(TYPE_LANG_SPECIFIC (NODE) ? LANG_TYPE_PTRMEM_CHECK (NODE)->record : NULL)
#define TYPE_SET_PTRMEMFUNC_TYPE(NODE, VALUE) \
do { \
if (TYPE_LANG_SPECIFIC (NODE) == NULL) \
{ \
TYPE_LANG_SPECIFIC (NODE) = GGC_CNEWVAR \
(struct lang_type, sizeof (struct lang_type_ptrmem)); \
TYPE_LANG_SPECIFIC (NODE)->u.ptrmem.h.is_lang_type_class = 0; \
} \
TYPE_LANG_SPECIFIC (NODE)->u.ptrmem.record = (VALUE); \
} while (0)
/* For a pointer-to-member type of the form `T X::*', this is `X'.
For a type like `void (X::*)() const', this type is `X', not `const
X'. To get at the `const X' you have to look at the
TYPE_PTRMEM_POINTED_TO_TYPE; there, the first parameter will have
type `const X*'. */
#define TYPE_PTRMEM_CLASS_TYPE(NODE) \
(TYPE_PTRMEM_P (NODE) \
? TYPE_OFFSET_BASETYPE (NODE) \
: TYPE_PTRMEMFUNC_OBJECT_TYPE (NODE))
/* For a pointer-to-member type of the form `T X::*', this is `T'. */
#define TYPE_PTRMEM_POINTED_TO_TYPE(NODE) \
(TYPE_PTRMEM_P (NODE) \
? TREE_TYPE (NODE) \
: TREE_TYPE (TYPE_PTRMEMFUNC_FN_TYPE (NODE)))
/* For a pointer-to-member constant `X::Y' this is the RECORD_TYPE for
`X'. */
#define PTRMEM_CST_CLASS(NODE) \
TYPE_PTRMEM_CLASS_TYPE (TREE_TYPE (PTRMEM_CST_CHECK (NODE)))
/* For a pointer-to-member constant `X::Y' this is the _DECL for
`Y'. */
#define PTRMEM_CST_MEMBER(NODE) (((ptrmem_cst_t)PTRMEM_CST_CHECK (NODE))->member)
/* The expression in question for a TYPEOF_TYPE. */
#define TYPEOF_TYPE_EXPR(NODE) (TYPEOF_TYPE_CHECK (NODE))->type.values
/* The expression in question for a DECLTYPE_TYPE. */
#define DECLTYPE_TYPE_EXPR(NODE) (DECLTYPE_TYPE_CHECK (NODE))->type.values
/* Whether the DECLTYPE_TYPE_EXPR of NODE was originally parsed as an
id-expression or a member-access expression. When false, it was
parsed as a full expression. */
#define DECLTYPE_TYPE_ID_EXPR_OR_MEMBER_ACCESS_P(NODE) \
(DECLTYPE_TYPE_CHECK (NODE))->type.string_flag
/* Nonzero for VAR_DECL and FUNCTION_DECL node means that `extern' was
specified in its declaration. This can also be set for an
erroneously declared PARM_DECL. */
#define DECL_THIS_EXTERN(NODE) \
DECL_LANG_FLAG_2 (VAR_FUNCTION_OR_PARM_DECL_CHECK (NODE))
/* Nonzero for VAR_DECL and FUNCTION_DECL node means that `static' was
specified in its declaration. This can also be set for an
erroneously declared PARM_DECL. */
#define DECL_THIS_STATIC(NODE) \
DECL_LANG_FLAG_6 (VAR_FUNCTION_OR_PARM_DECL_CHECK (NODE))
/* Nonzero for FIELD_DECL node means that this field is a base class
of the parent object, as opposed to a member field. */
#define DECL_FIELD_IS_BASE(NODE) \
DECL_LANG_FLAG_6 (FIELD_DECL_CHECK (NODE))
/* Nonzero if TYPE is an anonymous union or struct type. We have to use a
flag for this because "A union for which objects or pointers are
declared is not an anonymous union" [class.union]. */
#define ANON_AGGR_TYPE_P(NODE) \
(CLASS_TYPE_P (NODE) && LANG_TYPE_CLASS_CHECK (NODE)->anon_aggr)
#define SET_ANON_AGGR_TYPE_P(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->anon_aggr = 1)
/* Nonzero if TYPE is an anonymous union type. */
#define ANON_UNION_TYPE_P(NODE) \
(TREE_CODE (NODE) == UNION_TYPE && ANON_AGGR_TYPE_P (NODE))
#define UNKNOWN_TYPE LANG_TYPE
/* Define fields and accessors for nodes representing declared names. */
#define TYPE_WAS_ANONYMOUS(NODE) (LANG_TYPE_CLASS_CHECK (NODE)->was_anonymous)
/* C++: all of these are overloaded! These apply only to TYPE_DECLs. */
/* The format of each node in the DECL_FRIENDLIST is as follows:
The TREE_PURPOSE will be the name of a function, i.e., an
IDENTIFIER_NODE. The TREE_VALUE will be itself a TREE_LIST, whose
TREE_VALUEs are friends with the given name. */
#define DECL_FRIENDLIST(NODE) (DECL_INITIAL (NODE))
#define FRIEND_NAME(LIST) (TREE_PURPOSE (LIST))
#define FRIEND_DECLS(LIST) (TREE_VALUE (LIST))
/* The DECL_ACCESS, if non-NULL, is a TREE_LIST. The TREE_PURPOSE of
each node is a type; the TREE_VALUE is the access granted for this
DECL in that type. The DECL_ACCESS is set by access declarations.
For example, if a member that would normally be public in a
derived class is made protected, then the derived class and the
protected_access_node will appear in the DECL_ACCESS for the node. */
#define DECL_ACCESS(NODE) (LANG_DECL_U2_CHECK (NODE, 0)->access)
/* Nonzero if the FUNCTION_DECL is a global constructor. */
#define DECL_GLOBAL_CTOR_P(NODE) \
(DECL_LANG_SPECIFIC (NODE)->decl_flags.global_ctor_p)
/* Nonzero if the FUNCTION_DECL is a global destructor. */
#define DECL_GLOBAL_DTOR_P(NODE) \
(DECL_LANG_SPECIFIC (NODE)->decl_flags.global_dtor_p)
/* Accessor macros for C++ template decl nodes. */
/* The DECL_TEMPLATE_PARMS are a list. The TREE_PURPOSE of each node
is a INT_CST whose TREE_INT_CST_LOW indicates the level of the
template parameters, with 1 being the outermost set of template
parameters. The TREE_VALUE is a vector, whose elements are the
template parameters at each level. Each element in the vector is a
TREE_LIST, whose TREE_VALUE is a PARM_DECL (if the parameter is a
non-type parameter), or a TYPE_DECL (if the parameter is a type
parameter). The TREE_PURPOSE is the default value, if any. The
TEMPLATE_PARM_INDEX for the parameter is available as the
DECL_INITIAL (for a PARM_DECL) or as the TREE_TYPE (for a
TYPE_DECL). */
#define DECL_TEMPLATE_PARMS(NODE) DECL_NON_COMMON_CHECK (NODE)->decl_non_common.arguments
#define DECL_INNERMOST_TEMPLATE_PARMS(NODE) \
INNERMOST_TEMPLATE_PARMS (DECL_TEMPLATE_PARMS (NODE))
#define DECL_NTPARMS(NODE) \
TREE_VEC_LENGTH (DECL_INNERMOST_TEMPLATE_PARMS (NODE))
/* For function, method, class-data templates. */
#define DECL_TEMPLATE_RESULT(NODE) DECL_RESULT_FLD (NODE)
/* For a static member variable template, the
DECL_TEMPLATE_INSTANTIATIONS list contains the explicitly and
implicitly generated instantiations of the variable. There are no
partial instantiations of static member variables, so all of these
will be full instantiations.
For a class template the DECL_TEMPLATE_INSTANTIATIONS lists holds
all instantiations and specializations of the class type, including
partial instantiations and partial specializations.
In both cases, the TREE_PURPOSE of each node contains the arguments
used; the TREE_VALUE contains the generated variable. The template
arguments are always complete. For example, given:
template <class T> struct S1 {
template <class U> struct S2 {};
template <class U> struct S2<U*> {};
};
the record for the partial specialization will contain, as its
argument list, { {T}, {U*} }, and will be on the
DECL_TEMPLATE_INSTANTIATIONS list for `template <class T> template
<class U> struct S1<T>::S2'.
This list is not used for function templates. */
#define DECL_TEMPLATE_INSTANTIATIONS(NODE) DECL_VINDEX (NODE)
/* For a function template, the DECL_TEMPLATE_SPECIALIZATIONS lists
contains all instantiations and specializations of the function,
including partial instantiations. For a partial instantiation
which is a specialization, this list holds only full
specializations of the template that are instantiations of the
partial instantiation. For example, given:
template <class T> struct S {
template <class U> void f(U);
template <> void f(T);
};
the `S<int>::f<int>(int)' function will appear on the
DECL_TEMPLATE_SPECIALIZATIONS list for both `template <class T>
template <class U> void S<T>::f(U)' and `template <class T> void
S<int>::f(T)'. In the latter case, however, it will have only the
innermost set of arguments (T, in this case). The DECL_TI_TEMPLATE
for the function declaration will point at the specialization, not
the fully general template.
For a class template, this list contains the partial
specializations of this template. (Full specializations are not
recorded on this list.) The TREE_PURPOSE holds the arguments used
in the partial specialization (e.g., for `template <class T> struct
S<T*, int>' this will be `T*'.) The arguments will also include
any outer template arguments. The TREE_VALUE holds the innermost
template parameters for the specialization (e.g., `T' in the
example above.) The TREE_TYPE is the _TYPE node for the partial
specialization.
This list is not used for static variable templates. */
#define DECL_TEMPLATE_SPECIALIZATIONS(NODE) DECL_SIZE (NODE)
/* Nonzero for a DECL which is actually a template parameter. Keep
these checks in ascending tree code order. */
#define DECL_TEMPLATE_PARM_P(NODE) \
(DECL_LANG_FLAG_0 (NODE) \
&& (TREE_CODE (NODE) == CONST_DECL \
|| TREE_CODE (NODE) == PARM_DECL \
|| TREE_CODE (NODE) == TYPE_DECL \
|| TREE_CODE (NODE) == TEMPLATE_DECL))
/* Mark NODE as a template parameter. */
#define SET_DECL_TEMPLATE_PARM_P(NODE) \
(DECL_LANG_FLAG_0 (NODE) = 1)
/* Nonzero if NODE is a template template parameter. */
#define DECL_TEMPLATE_TEMPLATE_PARM_P(NODE) \
(TREE_CODE (NODE) == TEMPLATE_DECL && DECL_TEMPLATE_PARM_P (NODE))
/* Nonzero if NODE is a TEMPLATE_DECL representing an
UNBOUND_CLASS_TEMPLATE tree node. */
#define DECL_UNBOUND_CLASS_TEMPLATE_P(NODE) \
(TREE_CODE (NODE) == TEMPLATE_DECL && !DECL_TEMPLATE_RESULT (NODE))
#define DECL_FUNCTION_TEMPLATE_P(NODE) \
(TREE_CODE (NODE) == TEMPLATE_DECL \
&& !DECL_UNBOUND_CLASS_TEMPLATE_P (NODE) \
&& TREE_CODE (DECL_TEMPLATE_RESULT (NODE)) == FUNCTION_DECL)
/* Nonzero for a DECL that represents a template class. */
#define DECL_CLASS_TEMPLATE_P(NODE) \
(TREE_CODE (NODE) == TEMPLATE_DECL \
&& !DECL_UNBOUND_CLASS_TEMPLATE_P (NODE) \
&& TREE_CODE (DECL_TEMPLATE_RESULT (NODE)) == TYPE_DECL \
&& !DECL_TEMPLATE_TEMPLATE_PARM_P (NODE))
/* Nonzero if NODE which declares a type. */
#define DECL_DECLARES_TYPE_P(NODE) \
(TREE_CODE (NODE) == TYPE_DECL || DECL_CLASS_TEMPLATE_P (NODE))
/* Nonzero if NODE is the typedef implicitly generated for a type when
the type is declared. In C++, `struct S {};' is roughly
equivalent to `struct S {}; typedef struct S S;' in C.
DECL_IMPLICIT_TYPEDEF_P will hold for the typedef indicated in this
example. In C++, there is a second implicit typedef for each
class, in the scope of `S' itself, so that you can say `S::S'.
DECL_SELF_REFERENCE_P will hold for that second typedef. */
#define DECL_IMPLICIT_TYPEDEF_P(NODE) \
(TREE_CODE (NODE) == TYPE_DECL && DECL_LANG_FLAG_2 (NODE))
#define SET_DECL_IMPLICIT_TYPEDEF_P(NODE) \
(DECL_LANG_FLAG_2 (NODE) = 1)
#define DECL_SELF_REFERENCE_P(NODE) \
(TREE_CODE (NODE) == TYPE_DECL && DECL_LANG_FLAG_4 (NODE))
#define SET_DECL_SELF_REFERENCE_P(NODE) \
(DECL_LANG_FLAG_4 (NODE) = 1)
/* A `primary' template is one that has its own template header. A
member function of a class template is a template, but not primary.
A member template is primary. Friend templates are primary, too. */
/* Returns the primary template corresponding to these parameters. */
#define DECL_PRIMARY_TEMPLATE(NODE) \
(TREE_TYPE (DECL_INNERMOST_TEMPLATE_PARMS (NODE)))
/* Returns nonzero if NODE is a primary template. */
#define PRIMARY_TEMPLATE_P(NODE) (DECL_PRIMARY_TEMPLATE (NODE) == (NODE))
/* Nonzero iff NODE is a specialization of a template. The value
indicates the type of specializations:
1=implicit instantiation
2=partial or explicit specialization, e.g.:
template <> int min<int> (int, int),
3=explicit instantiation, e.g.:
template int min<int> (int, int);
Note that NODE will be marked as a specialization even if the
template it is instantiating is not a primary template. For
example, given:
template <typename T> struct O {
void f();
struct I {};
};
both O<int>::f and O<int>::I will be marked as instantiations.
If DECL_USE_TEMPLATE is nonzero, then DECL_TEMPLATE_INFO will also
be non-NULL. */
#define DECL_USE_TEMPLATE(NODE) (DECL_LANG_SPECIFIC (NODE)->decl_flags.use_template)
/* Like DECL_USE_TEMPLATE, but for class types. */
#define CLASSTYPE_USE_TEMPLATE(NODE) \
(LANG_TYPE_CLASS_CHECK (NODE)->use_template)
/* True if NODE is a specialization of a primary template. */
#define CLASSTYPE_SPECIALIZATION_OF_PRIMARY_TEMPLATE_P(NODE) \
(CLASS_TYPE_P (NODE) \
&& CLASSTYPE_USE_TEMPLATE (NODE) \
&& PRIMARY_TEMPLATE_P (CLASSTYPE_TI_TEMPLATE (arg)))
#define DECL_TEMPLATE_INSTANTIATION(NODE) (DECL_USE_TEMPLATE (NODE) & 1)
#define CLASSTYPE_TEMPLATE_INSTANTIATION(NODE) \
(CLASSTYPE_USE_TEMPLATE (NODE) & 1)
#define DECL_TEMPLATE_SPECIALIZATION(NODE) (DECL_USE_TEMPLATE (NODE) == 2)
#define SET_DECL_TEMPLATE_SPECIALIZATION(NODE) (DECL_USE_TEMPLATE (NODE) = 2)
/* Returns true for an explicit or partial specialization of a class
template. */
#define CLASSTYPE_TEMPLATE_SPECIALIZATION(NODE) \
(CLASSTYPE_USE_TEMPLATE (NODE) == 2)
#define SET_CLASSTYPE_TEMPLATE_SPECIALIZATION(NODE) \
(CLASSTYPE_USE_TEMPLATE (NODE) = 2)
#define DECL_IMPLICIT_INSTANTIATION(NODE) (DECL_USE_TEMPLATE (NODE) == 1)
#define SET_DECL_IMPLICIT_INSTANTIATION(NODE) (DECL_USE_TEMPLATE (NODE) = 1)
#define CLASSTYPE_IMPLICIT_INSTANTIATION(NODE) \
(CLASSTYPE_USE_TEMPLATE (NODE) == 1)
#define SET_CLASSTYPE_IMPLICIT_INSTANTIATION(NODE) \
(CLASSTYPE_USE_TEMPLATE (NODE) = 1)
#define DECL_EXPLICIT_INSTANTIATION(NODE) (DECL_USE_TEMPLATE (NODE) == 3)
#define SET_DECL_EXPLICIT_INSTANTIATION(NODE) (DECL_USE_TEMPLATE (NODE) = 3)
#define CLASSTYPE_EXPLICIT_INSTANTIATION(NODE) \
(CLASSTYPE_USE_TEMPLATE (NODE) == 3)
#define SET_CLASSTYPE_EXPLICIT_INSTANTIATION(NODE) \
(CLASSTYPE_USE_TEMPLATE (NODE) = 3)
/* Nonzero if DECL is a friend function which is an instantiation
from the point of view of the compiler, but not from the point of
view of the language. For example given:
template <class T> struct S { friend void f(T) {}; };
the declaration of `void f(int)' generated when S<int> is
instantiated will not be a DECL_TEMPLATE_INSTANTIATION, but will be
a DECL_FRIEND_PSEUDO_TEMPLATE_INSTANTIATION. */
#define DECL_FRIEND_PSEUDO_TEMPLATE_INSTANTIATION(DECL) \
(DECL_TEMPLATE_INFO (DECL) && !DECL_USE_TEMPLATE (DECL))
/* Nonzero iff we are currently processing a declaration for an
entity with its own template parameter list, and which is not a
full specialization. */
#define PROCESSING_REAL_TEMPLATE_DECL_P() \
(processing_template_decl > template_class_depth (current_scope ()))
/* Nonzero if this VAR_DECL or FUNCTION_DECL has already been
instantiated, i.e. its definition has been generated from the
pattern given in the template. */
#define DECL_TEMPLATE_INSTANTIATED(NODE) \
DECL_LANG_FLAG_1 (VAR_OR_FUNCTION_DECL_CHECK (NODE))
/* We know what we're doing with this decl now. */
#define DECL_INTERFACE_KNOWN(NODE) DECL_LANG_FLAG_5 (NODE)
/* DECL_EXTERNAL must be set on a decl until the decl is actually emitted,
so that assemble_external will work properly. So we have this flag to
tell us whether the decl is really not external.
This flag does not indicate whether or not the decl is defined in the
current translation unit; it indicates whether or not we should emit the
decl at the end of compilation if it is defined and needed. */
#define DECL_NOT_REALLY_EXTERN(NODE) \
(DECL_LANG_SPECIFIC (NODE)->decl_flags.not_really_extern)
#define DECL_REALLY_EXTERN(NODE) \
(DECL_EXTERNAL (NODE) && ! DECL_NOT_REALLY_EXTERN (NODE))
/* A thunk is a stub function.
A thunk is an alternate entry point for an ordinary FUNCTION_DECL.
The address of the ordinary FUNCTION_DECL is given by the
DECL_INITIAL, which is always an ADDR_EXPR whose operand is a
FUNCTION_DECL. The job of the thunk is to either adjust the this
pointer before transferring control to the FUNCTION_DECL, or call
FUNCTION_DECL and then adjust the result value. Note, the result
pointer adjusting thunk must perform a call to the thunked
function, (or be implemented via passing some invisible parameter
to the thunked function, which is modified to perform the
adjustment just before returning).
A thunk may perform either, or both, of the following operations:
o Adjust the this or result pointer by a constant offset.
o Adjust the this or result pointer by looking up a vcall or vbase offset
in the vtable.
A this pointer adjusting thunk converts from a base to a derived
class, and hence adds the offsets. A result pointer adjusting thunk
converts from a derived class to a base, and hence subtracts the
offsets. If both operations are performed, then the constant
adjustment is performed first for this pointer adjustment and last
for the result pointer adjustment.
The constant adjustment is given by THUNK_FIXED_OFFSET. If the
vcall or vbase offset is required, THUNK_VIRTUAL_OFFSET is
used. For this pointer adjusting thunks, it is the vcall offset
into the vtable. For result pointer adjusting thunks it is the
binfo of the virtual base to convert to. Use that binfo's vbase
offset.
It is possible to have equivalent covariant thunks. These are
distinct virtual covariant thunks whose vbase offsets happen to
have the same value. THUNK_ALIAS is used to pick one as the
canonical thunk, which will get all the this pointer adjusting
thunks attached to it. */
/* An integer indicating how many bytes should be subtracted from the
this or result pointer when this function is called. */
#define THUNK_FIXED_OFFSET(DECL) \
(DECL_LANG_SPECIFIC (THUNK_FUNCTION_CHECK (DECL))->u.f.u5.fixed_offset)
/* A tree indicating how to perform the virtual adjustment. For a this
adjusting thunk it is the number of bytes to be added to the vtable
to find the vcall offset. For a result adjusting thunk, it is the
binfo of the relevant virtual base. If NULL, then there is no
virtual adjust. (The vptr is always located at offset zero from
the this or result pointer.) (If the covariant type is within the
class hierarchy being laid out, the vbase index is not yet known
at the point we need to create the thunks, hence the need to use
binfos.) */
#define THUNK_VIRTUAL_OFFSET(DECL) \
(LANG_DECL_U2_CHECK (FUNCTION_DECL_CHECK (DECL), 0)->access)
/* A thunk which is equivalent to another thunk. */
#define THUNK_ALIAS(DECL) \
(DECL_LANG_SPECIFIC (FUNCTION_DECL_CHECK (DECL))->decl_flags.u.template_info)
/* For thunk NODE, this is the FUNCTION_DECL thunked to. It is
possible for the target to be a thunk too. */
#define THUNK_TARGET(NODE) \
(DECL_LANG_SPECIFIC (NODE)->u.f.befriending_classes)
/* True for a SCOPE_REF iff the "template" keyword was used to
indicate that the qualified name denotes a template. */
#define QUALIFIED_NAME_IS_TEMPLATE(NODE) \
(TREE_LANG_FLAG_0 (SCOPE_REF_CHECK (NODE)))
/* True for an OMP_ATOMIC that has dependent parameters. These are stored
as an expr in operand 1, and integer_zero_node in operand 0. */
#define OMP_ATOMIC_DEPENDENT_P(NODE) \
(TREE_CODE (TREE_OPERAND (OMP_ATOMIC_CHECK (NODE), 0)) == INTEGER_CST)
/* Used while gimplifying continue statements bound to OMP_FOR nodes. */
#define OMP_FOR_GIMPLIFYING_P(NODE) \
(TREE_LANG_FLAG_0 (OMP_FOR_CHECK (NODE)))
/* A language-specific token attached to the OpenMP data clauses to
hold code (or code fragments) related to ctors, dtors, and op=.
See semantics.c for details. */
#define CP_OMP_CLAUSE_INFO(NODE) \
TREE_TYPE (OMP_CLAUSE_RANGE_CHECK (NODE, OMP_CLAUSE_PRIVATE, \
OMP_CLAUSE_COPYPRIVATE))
/* These macros provide convenient access to the various _STMT nodes
created when parsing template declarations. */
#define TRY_STMTS(NODE) TREE_OPERAND (TRY_BLOCK_CHECK (NODE), 0)
#define TRY_HANDLERS(NODE) TREE_OPERAND (TRY_BLOCK_CHECK (NODE), 1)
#define EH_SPEC_STMTS(NODE) TREE_OPERAND (EH_SPEC_BLOCK_CHECK (NODE), 0)
#define EH_SPEC_RAISES(NODE) TREE_OPERAND (EH_SPEC_BLOCK_CHECK (NODE), 1)
#define USING_STMT_NAMESPACE(NODE) TREE_OPERAND (USING_STMT_CHECK (NODE), 0)
/* Nonzero if this try block is a function try block. */
#define FN_TRY_BLOCK_P(NODE) TREE_LANG_FLAG_3 (TRY_BLOCK_CHECK (NODE))
#define HANDLER_PARMS(NODE) TREE_OPERAND (HANDLER_CHECK (NODE), 0)
#define HANDLER_BODY(NODE) TREE_OPERAND (HANDLER_CHECK (NODE), 1)
#define HANDLER_TYPE(NODE) TREE_TYPE (HANDLER_CHECK (NODE))
/* CLEANUP_STMT accessors. The statement(s) covered, the cleanup to run
and the VAR_DECL for which this cleanup exists. */
#define CLEANUP_BODY(NODE) TREE_OPERAND (CLEANUP_STMT_CHECK (NODE), 0)
#define CLEANUP_EXPR(NODE) TREE_OPERAND (CLEANUP_STMT_CHECK (NODE), 1)
#define CLEANUP_DECL(NODE) TREE_OPERAND (CLEANUP_STMT_CHECK (NODE), 2)
/* IF_STMT accessors. These give access to the condition of the if
statement, the then block of the if statement, and the else block
of the if statement if it exists. */
#define IF_COND(NODE) TREE_OPERAND (IF_STMT_CHECK (NODE), 0)
#define THEN_CLAUSE(NODE) TREE_OPERAND (IF_STMT_CHECK (NODE), 1)
#define ELSE_CLAUSE(NODE) TREE_OPERAND (IF_STMT_CHECK (NODE), 2)
/* WHILE_STMT accessors. These give access to the condition of the
while statement and the body of the while statement, respectively. */
#define WHILE_COND(NODE) TREE_OPERAND (WHILE_STMT_CHECK (NODE), 0)
#define WHILE_BODY(NODE) TREE_OPERAND (WHILE_STMT_CHECK (NODE), 1)
/* DO_STMT accessors. These give access to the condition of the do
statement and the body of the do statement, respectively. */
#define DO_COND(NODE) TREE_OPERAND (DO_STMT_CHECK (NODE), 0)
#define DO_BODY(NODE) TREE_OPERAND (DO_STMT_CHECK (NODE), 1)
/* FOR_STMT accessors. These give access to the init statement,
condition, update expression, and body of the for statement,
respectively. */
#define FOR_INIT_STMT(NODE) TREE_OPERAND (FOR_STMT_CHECK (NODE), 0)
#define FOR_COND(NODE) TREE_OPERAND (FOR_STMT_CHECK (NODE), 1)
#define FOR_EXPR(NODE) TREE_OPERAND (FOR_STMT_CHECK (NODE), 2)
#define FOR_BODY(NODE) TREE_OPERAND (FOR_STMT_CHECK (NODE), 3)
#define SWITCH_STMT_COND(NODE) TREE_OPERAND (SWITCH_STMT_CHECK (NODE), 0)
#define SWITCH_STMT_BODY(NODE) TREE_OPERAND (SWITCH_STMT_CHECK (NODE), 1)
#define SWITCH_STMT_TYPE(NODE) TREE_OPERAND (SWITCH_STMT_CHECK (NODE), 2)
/* STMT_EXPR accessor. */
#define STMT_EXPR_STMT(NODE) TREE_OPERAND (STMT_EXPR_CHECK (NODE), 0)
/* EXPR_STMT accessor. This gives the expression associated with an
expression statement. */
#define EXPR_STMT_EXPR(NODE) TREE_OPERAND (EXPR_STMT_CHECK (NODE), 0)
/* True if this TARGET_EXPR was created by build_cplus_new, and so we can
discard it if it isn't useful. */
#define TARGET_EXPR_IMPLICIT_P(NODE) \
TREE_LANG_FLAG_0 (TARGET_EXPR_CHECK (NODE))
/* True if this TARGET_EXPR is the result of list-initialization of a
temporary. */
#define TARGET_EXPR_LIST_INIT_P(NODE) \
TREE_LANG_FLAG_1 (TARGET_EXPR_CHECK (NODE))
/* An enumeration of the kind of tags that C++ accepts. */
enum tag_types {
none_type = 0, /* Not a tag type. */
record_type, /* "struct" types. */
class_type, /* "class" types. */
union_type, /* "union" types. */
enum_type, /* "enum" types. */
typename_type /* "typename" types. */
};
/* The various kinds of lvalues we distinguish. */
typedef enum cp_lvalue_kind {
clk_none = 0, /* Things that are not an lvalue. */
clk_ordinary = 1, /* An ordinary lvalue. */
clk_rvalueref = 2,/* An rvalue formed using an rvalue reference */
clk_class = 4, /* An rvalue of class-type. */
clk_bitfield = 8, /* An lvalue for a bit-field. */
clk_packed = 16 /* An lvalue for a packed field. */
} cp_lvalue_kind;
/* Various kinds of template specialization, instantiation, etc. */
typedef enum tmpl_spec_kind {
tsk_none, /* Not a template at all. */
tsk_invalid_member_spec, /* An explicit member template
specialization, but the enclosing
classes have not all been explicitly
specialized. */
tsk_invalid_expl_inst, /* An explicit instantiation containing
template parameter lists. */
tsk_excessive_parms, /* A template declaration with too many
template parameter lists. */
tsk_insufficient_parms, /* A template declaration with too few
parameter lists. */
tsk_template, /* A template declaration. */
tsk_expl_spec, /* An explicit specialization. */
tsk_expl_inst /* An explicit instantiation. */
} tmpl_spec_kind;
/* The various kinds of access. BINFO_ACCESS depends on these being
two bit quantities. The numerical values are important; they are
used to initialize RTTI data structures, so changing them changes
the ABI. */
typedef enum access_kind {
ak_none = 0, /* Inaccessible. */
ak_public = 1, /* Accessible, as a `public' thing. */
ak_protected = 2, /* Accessible, as a `protected' thing. */
ak_private = 3 /* Accessible, as a `private' thing. */
} access_kind;
/* The various kinds of special functions. If you add to this list,
you should update special_function_p as well. */
typedef enum special_function_kind {
sfk_none = 0, /* Not a special function. This enumeral
must have value zero; see
special_function_p. */
sfk_constructor, /* A constructor. */
sfk_copy_constructor, /* A copy constructor. */
sfk_assignment_operator, /* An assignment operator. */
sfk_destructor, /* A destructor. */
sfk_complete_destructor, /* A destructor for complete objects. */
sfk_base_destructor, /* A destructor for base subobjects. */
sfk_deleting_destructor, /* A destructor for complete objects that
deletes the object after it has been
destroyed. */
sfk_conversion /* A conversion operator. */
} special_function_kind;
/* The various kinds of linkage. From [basic.link],
A name is said to have linkage when it might denote the same
object, reference, function, type, template, namespace or value
as a name introduced in another scope:
-- When a name has external linkage, the entity it denotes can
be referred to from scopes of other translation units or from
other scopes of the same translation unit.
-- When a name has internal linkage, the entity it denotes can
be referred to by names from other scopes in the same
translation unit.
-- When a name has no linkage, the entity it denotes cannot be
referred to by names from other scopes. */
typedef enum linkage_kind {
lk_none, /* No linkage. */
lk_internal, /* Internal linkage. */
lk_external /* External linkage. */
} linkage_kind;
/* Bitmask flags to control type substitution. */
typedef enum tsubst_flags_t {
tf_none = 0, /* nothing special */
tf_error = 1 << 0, /* give error messages */
tf_warning = 1 << 1, /* give warnings too */
tf_ignore_bad_quals = 1 << 2, /* ignore bad cvr qualifiers */
tf_keep_type_decl = 1 << 3, /* retain typedef type decls
(make_typename_type use) */
tf_ptrmem_ok = 1 << 4, /* pointers to member ok (internal
instantiate_type use) */
tf_user = 1 << 5, /* found template must be a user template
(lookup_template_class use) */
tf_conv = 1 << 6, /* We are determining what kind of
conversion might be permissible,
not actually performing the
conversion. */
tf_no_access_control = 1 << 7, /* Do not perform access checks, even
when issuing other errors. */
/* Convenient substitution flags combinations. */
tf_warning_or_error = tf_warning | tf_error
} tsubst_flags_t;
/* The kind of checking we can do looking in a class hierarchy. */
typedef enum base_access {
ba_any = 0, /* Do not check access, allow an ambiguous base,
prefer a non-virtual base */
ba_unique = 1 << 0, /* Must be a unique base. */
ba_check_bit = 1 << 1, /* Check access. */
ba_check = ba_unique | ba_check_bit,
ba_ignore_scope = 1 << 2, /* Ignore access allowed by local scope. */
ba_quiet = 1 << 3 /* Do not issue error messages. */
} base_access;
/* The various kinds of access check during parsing. */
typedef enum deferring_kind {
dk_no_deferred = 0, /* Check access immediately */
dk_deferred = 1, /* Deferred check */
dk_no_check = 2 /* No access check */
} deferring_kind;
/* The kind of base we can find, looking in a class hierarchy.
Values <0 indicate we failed. */
typedef enum base_kind {
bk_inaccessible = -3, /* The base is inaccessible */
bk_ambig = -2, /* The base is ambiguous */
bk_not_base = -1, /* It is not a base */
bk_same_type = 0, /* It is the same type */
bk_proper_base = 1, /* It is a proper base */
bk_via_virtual = 2 /* It is a proper base, but via a virtual
path. This might not be the canonical
binfo. */
} base_kind;
/* Node for "pointer to (virtual) function".
This may be distinct from ptr_type_node so gdb can distinguish them. */
#define vfunc_ptr_type_node vtable_entry_type
/* For building calls to `delete'. */
extern GTY(()) tree integer_two_node;
extern GTY(()) tree integer_three_node;
/* The number of function bodies which we are currently processing.
(Zero if we are at namespace scope, one inside the body of a
function, two inside the body of a function in a local class, etc.) */
extern int function_depth;
/* in pt.c */
/* These values are used for the `STRICT' parameter to type_unification and
fn_type_unification. Their meanings are described with the
documentation for fn_type_unification. */
typedef enum unification_kind_t {
DEDUCE_CALL,
DEDUCE_CONV,
DEDUCE_EXACT
} unification_kind_t;
/* in class.c */
extern int current_class_depth;
/* An array of all local classes present in this translation unit, in
declaration order. */
extern GTY(()) VEC(tree,gc) *local_classes;
/* Here's where we control how name mangling takes place. */
/* Cannot use '$' up front, because this confuses gdb
(names beginning with '$' are gdb-local identifiers).
Note that all forms in which the '$' is significant are long enough
for direct indexing (meaning that if we know there is a '$'
at a particular location, we can index into the string at
any other location that provides distinguishing characters). */
/* Define NO_DOT_IN_LABEL in your favorite tm file if your assembler
doesn't allow '.' in symbol names. */
#ifndef NO_DOT_IN_LABEL
#define JOINER '.'
#define AUTO_TEMP_NAME "_.tmp_"
#define VFIELD_BASE ".vf"
#define VFIELD_NAME "_vptr."
#define VFIELD_NAME_FORMAT "_vptr.%s"
#define ANON_AGGRNAME_FORMAT "._%d"
#else /* NO_DOT_IN_LABEL */
#ifndef NO_DOLLAR_IN_LABEL
#define JOINER '$'
#define AUTO_TEMP_NAME "_$tmp_"
#define VFIELD_BASE "$vf"
#define VFIELD_NAME "_vptr$"
#define VFIELD_NAME_FORMAT "_vptr$%s"
#define ANON_AGGRNAME_FORMAT "$_%d"
#else /* NO_DOLLAR_IN_LABEL */
#define IN_CHARGE_NAME "__in_chrg"
#define AUTO_TEMP_NAME "__tmp_"
#define TEMP_NAME_P(ID_NODE) \
(!strncmp (IDENTIFIER_POINTER (ID_NODE), AUTO_TEMP_NAME, \
sizeof (AUTO_TEMP_NAME) - 1))
#define VTABLE_NAME "__vt_"
#define VTABLE_NAME_P(ID_NODE) \
(!strncmp (IDENTIFIER_POINTER (ID_NODE), VTABLE_NAME, \
sizeof (VTABLE_NAME) - 1))
#define VFIELD_BASE "__vfb"
#define VFIELD_NAME "__vptr_"
#define VFIELD_NAME_P(ID_NODE) \
(!strncmp (IDENTIFIER_POINTER (ID_NODE), VFIELD_NAME, \
sizeof (VFIELD_NAME) - 1))
#define VFIELD_NAME_FORMAT "__vptr_%s"
#define ANON_AGGRNAME_PREFIX "__anon_"
#define ANON_AGGRNAME_P(ID_NODE) \
(!strncmp (IDENTIFIER_POINTER (ID_NODE), ANON_AGGRNAME_PREFIX, \
sizeof (ANON_AGGRNAME_PREFIX) - 1))
#define ANON_AGGRNAME_FORMAT "__anon_%d"
#endif /* NO_DOLLAR_IN_LABEL */
#endif /* NO_DOT_IN_LABEL */
#define THIS_NAME "this"
#define IN_CHARGE_NAME "__in_chrg"
#define VTBL_PTR_TYPE "__vtbl_ptr_type"
#define VTABLE_DELTA_NAME "__delta"
#define VTABLE_PFN_NAME "__pfn"
#if !defined(NO_DOLLAR_IN_LABEL) || !defined(NO_DOT_IN_LABEL)
#define VTABLE_NAME_P(ID_NODE) (IDENTIFIER_POINTER (ID_NODE)[1] == 'v' \
&& IDENTIFIER_POINTER (ID_NODE)[2] == 't' \
&& IDENTIFIER_POINTER (ID_NODE)[3] == JOINER)
#define TEMP_NAME_P(ID_NODE) \
(!strncmp (IDENTIFIER_POINTER (ID_NODE), AUTO_TEMP_NAME, sizeof (AUTO_TEMP_NAME)-1))
#define VFIELD_NAME_P(ID_NODE) \
(!strncmp (IDENTIFIER_POINTER (ID_NODE), VFIELD_NAME, sizeof(VFIELD_NAME)-1))
/* For anonymous aggregate types, we need some sort of name to
hold on to. In practice, this should not appear, but it should
not be harmful if it does. */
#define ANON_AGGRNAME_P(ID_NODE) (IDENTIFIER_POINTER (ID_NODE)[0] == JOINER \
&& IDENTIFIER_POINTER (ID_NODE)[1] == '_')
#endif /* !defined(NO_DOLLAR_IN_LABEL) || !defined(NO_DOT_IN_LABEL) */
/* Nonzero if we're done parsing and into end-of-file activities. */
extern int at_eof;
/* A list of namespace-scope objects which have constructors or
destructors which reside in the global scope. The decl is stored
in the TREE_VALUE slot and the initializer is stored in the
TREE_PURPOSE slot. */
extern GTY(()) tree static_aggregates;
enum overload_flags { NO_SPECIAL = 0, DTOR_FLAG, OP_FLAG, TYPENAME_FLAG };
/* These are uses as bits in flags passed to various functions to
control their behavior. Despite the LOOKUP_ prefix, many of these
do not control name lookup. ??? Functions using these flags should
probably be modified to accept explicit boolean flags for the
behaviors relevant to them. */
/* Check for access violations. */
#define LOOKUP_PROTECT (1 << 0)
/* Complain if no suitable member function matching the arguments is
found. */
#define LOOKUP_COMPLAIN (1 << 1)
#define LOOKUP_NORMAL (LOOKUP_PROTECT | LOOKUP_COMPLAIN)
/* Even if the function found by lookup is a virtual function, it
should be called directly. */
#define LOOKUP_NONVIRTUAL (1 << 2)
/* Non-converting (i.e., "explicit") constructors are not tried. */
#define LOOKUP_ONLYCONVERTING (1 << 3)
/* If a temporary is created, it should be created so that it lives
as long as the current variable bindings; otherwise it only lives
until the end of the complete-expression. It also forces
direct-initialization in cases where other parts of the compiler
have already generated a temporary, such as reference
initialization and the catch parameter. */
#define DIRECT_BIND (1 << 4)
/* User-defined conversions are not permitted. (Built-in conversions
are permitted.) */
#define LOOKUP_NO_CONVERSION (1 << 5)
/* The user has explicitly called a destructor. (Therefore, we do
not need to check that the object is non-NULL before calling the
destructor.) */
#define LOOKUP_DESTRUCTOR (1 << 6)
/* Do not permit references to bind to temporaries. */
#define LOOKUP_NO_TEMP_BIND (1 << 7)
/* Do not accept objects, and possibly namespaces. */
#define LOOKUP_PREFER_TYPES (1 << 8)
/* Do not accept objects, and possibly types. */
#define LOOKUP_PREFER_NAMESPACES (1 << 9)
/* Accept types or namespaces. */
#define LOOKUP_PREFER_BOTH (LOOKUP_PREFER_TYPES | LOOKUP_PREFER_NAMESPACES)
/* Return friend declarations and un-declared builtin functions.
(Normally, these entities are registered in the symbol table, but
not found by lookup.) */
#define LOOKUP_HIDDEN (LOOKUP_PREFER_NAMESPACES << 1)
/* Prefer that the lvalue be treated as an rvalue. */
#define LOOKUP_PREFER_RVALUE (LOOKUP_HIDDEN << 1)
/* We're inside an init-list, so narrowing conversions are ill-formed. */
#define LOOKUP_NO_NARROWING (LOOKUP_PREFER_RVALUE << 1)
/* Avoid user-defined conversions for the first parameter of a copy
constructor. */
#define LOOKUP_NO_COPY_CTOR_CONVERSION (LOOKUP_NO_NARROWING << 1)
#define LOOKUP_NAMESPACES_ONLY(F) \
(((F) & LOOKUP_PREFER_NAMESPACES) && !((F) & LOOKUP_PREFER_TYPES))
#define LOOKUP_TYPES_ONLY(F) \
(!((F) & LOOKUP_PREFER_NAMESPACES) && ((F) & LOOKUP_PREFER_TYPES))
#define LOOKUP_QUALIFIERS_ONLY(F) ((F) & LOOKUP_PREFER_BOTH)
/* These flags are used by the conversion code.
CONV_IMPLICIT : Perform implicit conversions (standard and user-defined).
CONV_STATIC : Perform the explicit conversions for static_cast.
CONV_CONST : Perform the explicit conversions for const_cast.
CONV_REINTERPRET: Perform the explicit conversions for reinterpret_cast.
CONV_PRIVATE : Perform upcasts to private bases.
CONV_FORCE_TEMP : Require a new temporary when converting to the same
aggregate type. */
#define CONV_IMPLICIT 1
#define CONV_STATIC 2
#define CONV_CONST 4
#define CONV_REINTERPRET 8
#define CONV_PRIVATE 16
/* #define CONV_NONCONVERTING 32 */
#define CONV_FORCE_TEMP 64
#define CONV_OLD_CONVERT (CONV_IMPLICIT | CONV_STATIC | CONV_CONST \
| CONV_REINTERPRET)
#define CONV_C_CAST (CONV_IMPLICIT | CONV_STATIC | CONV_CONST \
| CONV_REINTERPRET | CONV_PRIVATE | CONV_FORCE_TEMP)
/* Used by build_expr_type_conversion to indicate which types are
acceptable as arguments to the expression under consideration. */
#define WANT_INT 1 /* integer types, including bool */
#define WANT_FLOAT 2 /* floating point types */
#define WANT_ENUM 4 /* enumerated types */
#define WANT_POINTER 8 /* pointer types */
#define WANT_NULL 16 /* null pointer constant */
#define WANT_VECTOR 32 /* vector types */
#define WANT_ARITH (WANT_INT | WANT_FLOAT | WANT_VECTOR)
/* Used with comptypes, and related functions, to guide type
comparison. */
#define COMPARE_STRICT 0 /* Just check if the types are the
same. */
#define COMPARE_BASE 1 /* Check to see if the second type is
derived from the first. */
#define COMPARE_DERIVED 2 /* Like COMPARE_BASE, but in
reverse. */
#define COMPARE_REDECLARATION 4 /* The comparison is being done when
another declaration of an existing
entity is seen. */
#define COMPARE_STRUCTURAL 8 /* The comparison is intended to be
structural. The actual comparison
will be identical to
COMPARE_STRICT. */
/* Used with push_overloaded_decl. */
#define PUSH_GLOBAL 0 /* Push the DECL into namespace scope,
regardless of the current scope. */
#define PUSH_LOCAL 1 /* Push the DECL into the current
scope. */
#define PUSH_USING 2 /* We are pushing this DECL as the
result of a using declaration. */
/* Used with start function. */
#define SF_DEFAULT 0 /* No flags. */
#define SF_PRE_PARSED 1 /* The function declaration has
already been parsed. */
#define SF_INCLASS_INLINE 2 /* The function is an inline, defined
in the class body. */
/* Used with start_decl's initialized parameter. */
#define SD_UNINITIALIZED 0
#define SD_INITIALIZED 1
#define SD_DEFAULTED 2
#define SD_DELETED 3
/* Returns nonzero iff TYPE1 and TYPE2 are the same type, or if TYPE2
is derived from TYPE1, or if TYPE2 is a pointer (reference) to a
class derived from the type pointed to (referred to) by TYPE1. */
#define same_or_base_type_p(TYPE1, TYPE2) \
comptypes ((TYPE1), (TYPE2), COMPARE_BASE)
/* These macros are used to access a TEMPLATE_PARM_INDEX. */
#define TEMPLATE_PARM_INDEX_CAST(NODE) \
((template_parm_index*)TEMPLATE_PARM_INDEX_CHECK (NODE))
#define TEMPLATE_PARM_IDX(NODE) (TEMPLATE_PARM_INDEX_CAST (NODE)->index)
#define TEMPLATE_PARM_LEVEL(NODE) (TEMPLATE_PARM_INDEX_CAST (NODE)->level)
#define TEMPLATE_PARM_DESCENDANTS(NODE) (TREE_CHAIN (NODE))
#define TEMPLATE_PARM_ORIG_LEVEL(NODE) (TEMPLATE_PARM_INDEX_CAST (NODE)->orig_level)
#define TEMPLATE_PARM_DECL(NODE) (TEMPLATE_PARM_INDEX_CAST (NODE)->decl)
#define TEMPLATE_PARM_PARAMETER_PACK(NODE) \
(TREE_LANG_FLAG_0 (TEMPLATE_PARM_INDEX_CHECK (NODE)))
/* These macros are for accessing the fields of TEMPLATE_TYPE_PARM,
TEMPLATE_TEMPLATE_PARM and BOUND_TEMPLATE_TEMPLATE_PARM nodes. */
#define TEMPLATE_TYPE_PARM_INDEX(NODE) \
(TREE_CHECK3 ((NODE), TEMPLATE_TYPE_PARM, TEMPLATE_TEMPLATE_PARM, \
BOUND_TEMPLATE_TEMPLATE_PARM))->type.values
#define TEMPLATE_TYPE_IDX(NODE) \
(TEMPLATE_PARM_IDX (TEMPLATE_TYPE_PARM_INDEX (NODE)))
#define TEMPLATE_TYPE_LEVEL(NODE) \
(TEMPLATE_PARM_LEVEL (TEMPLATE_TYPE_PARM_INDEX (NODE)))
#define TEMPLATE_TYPE_ORIG_LEVEL(NODE) \
(TEMPLATE_PARM_ORIG_LEVEL (TEMPLATE_TYPE_PARM_INDEX (NODE)))
#define TEMPLATE_TYPE_DECL(NODE) \
(TEMPLATE_PARM_DECL (TEMPLATE_TYPE_PARM_INDEX (NODE)))
#define TEMPLATE_TYPE_PARAMETER_PACK(NODE) \
(TEMPLATE_PARM_PARAMETER_PACK (TEMPLATE_TYPE_PARM_INDEX (NODE)))
/* These constants can used as bit flags in the process of tree formatting.
TFF_PLAIN_IDENTIFIER: unqualified part of a name.
TFF_SCOPE: include the class and namespace scope of the name.
TFF_CHASE_TYPEDEF: print the original type-id instead of the typedef-name.
TFF_DECL_SPECIFIERS: print decl-specifiers.
TFF_CLASS_KEY_OR_ENUM: precede a class-type name (resp. enum name) with
a class-key (resp. `enum').
TFF_RETURN_TYPE: include function return type.
TFF_FUNCTION_DEFAULT_ARGUMENTS: include function default parameter values.
TFF_EXCEPTION_SPECIFICATION: show function exception specification.
TFF_TEMPLATE_HEADER: show the template<...> header in a
template-declaration.
TFF_TEMPLATE_NAME: show only template-name.
TFF_EXPR_IN_PARENS: parenthesize expressions.
TFF_NO_FUNCTION_ARGUMENTS: don't show function arguments.
TFF_UNQUALIFIED_NAME: do not print the qualifying scope of the
top-level entity. */
#define TFF_PLAIN_IDENTIFIER (0)
#define TFF_SCOPE (1)
#define TFF_CHASE_TYPEDEF (1 << 1)
#define TFF_DECL_SPECIFIERS (1 << 2)
#define TFF_CLASS_KEY_OR_ENUM (1 << 3)
#define TFF_RETURN_TYPE (1 << 4)
#define TFF_FUNCTION_DEFAULT_ARGUMENTS (1 << 5)
#define TFF_EXCEPTION_SPECIFICATION (1 << 6)
#define TFF_TEMPLATE_HEADER (1 << 7)
#define TFF_TEMPLATE_NAME (1 << 8)
#define TFF_EXPR_IN_PARENS (1 << 9)
#define TFF_NO_FUNCTION_ARGUMENTS (1 << 10)
#define TFF_UNQUALIFIED_NAME (1 << 11)
/* Returns the TEMPLATE_DECL associated to a TEMPLATE_TEMPLATE_PARM
node. */
#define TEMPLATE_TEMPLATE_PARM_TEMPLATE_DECL(NODE) \
((TREE_CODE (NODE) == BOUND_TEMPLATE_TEMPLATE_PARM) \
? TYPE_TI_TEMPLATE (NODE) \
: TYPE_NAME (NODE))
/* in lex.c */
extern void init_reswords (void);
/* Indexed by TREE_CODE, these tables give C-looking names to
operators represented by TREE_CODES. For example,
opname_tab[(int) MINUS_EXPR] == "-". */
extern const char **opname_tab, **assignop_tab;
typedef struct operator_name_info_t GTY(())
{
/* The IDENTIFIER_NODE for the operator. */
tree identifier;
/* The name of the operator. */
const char *name;
/* The mangled name of the operator. */
const char *mangled_name;
/* The arity of the operator. */
int arity;
} operator_name_info_t;
/* A mapping from tree codes to operator name information. */
extern GTY(()) operator_name_info_t operator_name_info
[(int) MAX_TREE_CODES];
/* Similar, but for assignment operators. */
extern GTY(()) operator_name_info_t assignment_operator_name_info
[(int) MAX_TREE_CODES];
/* A type-qualifier, or bitmask therefore, using the TYPE_QUAL
constants. */
typedef int cp_cv_quals;
/* A storage class. */
typedef enum cp_storage_class {
/* sc_none must be zero so that zeroing a cp_decl_specifier_seq
sets the storage_class field to sc_none. */
sc_none = 0,
sc_auto,
sc_register,
sc_static,
sc_extern,
sc_mutable
} cp_storage_class;
/* An individual decl-specifier. */
typedef enum cp_decl_spec {
ds_first,
ds_signed = ds_first,
ds_unsigned,
ds_short,
ds_long,
ds_const,
ds_volatile,
ds_restrict,
ds_inline,
ds_virtual,
ds_explicit,
ds_friend,
ds_typedef,
ds_complex,
ds_thread,
ds_last
} cp_decl_spec;
/* A decl-specifier-seq. */
typedef struct cp_decl_specifier_seq {
/* The number of times each of the keywords has been seen. */
unsigned specs[(int) ds_last];
/* The primary type, if any, given by the decl-specifier-seq.
Modifiers, like "short", "const", and "unsigned" are not
reflected here. This field will be a TYPE, unless a typedef-name
was used, in which case it will be a TYPE_DECL. */
tree type;
/* The location of the primary type. Mainly used for error
reporting. */
location_t type_location;
/* The attributes, if any, provided with the specifier sequence. */
tree attributes;
/* If non-NULL, a built-in type that the user attempted to redefine
to some other type. */
tree redefined_builtin_type;
/* The storage class specified -- or sc_none if no storage class was
explicitly specified. */
cp_storage_class storage_class;
/* True iff TYPE_SPEC indicates a user-defined type. */
BOOL_BITFIELD user_defined_type_p : 1;
/* True iff multiple types were (erroneously) specified for this
decl-specifier-seq. */
BOOL_BITFIELD multiple_types_p : 1;
/* True iff multiple storage classes were (erroneously) specified
for this decl-specifier-seq or a combination of a storage class
with a typedef specifier. */
BOOL_BITFIELD conflicting_specifiers_p : 1;
/* True iff at least one decl-specifier was found. */
BOOL_BITFIELD any_specifiers_p : 1;
/* True iff "int" was explicitly provided. */
BOOL_BITFIELD explicit_int_p : 1;
/* True iff "char" was explicitly provided. */
BOOL_BITFIELD explicit_char_p : 1;
} cp_decl_specifier_seq;
/* The various kinds of declarators. */
typedef enum cp_declarator_kind {
cdk_id,
cdk_function,
cdk_array,
cdk_pointer,
cdk_reference,
cdk_ptrmem,
cdk_error
} cp_declarator_kind;
/* A declarator. */
typedef struct cp_declarator cp_declarator;
typedef struct cp_parameter_declarator cp_parameter_declarator;
/* A parameter, before it has been semantically analyzed. */
struct cp_parameter_declarator {
/* The next parameter, or NULL_TREE if none. */
cp_parameter_declarator *next;
/* The decl-specifiers-seq for the parameter. */
cp_decl_specifier_seq decl_specifiers;
/* The declarator for the parameter. */
cp_declarator *declarator;
/* The default-argument expression, or NULL_TREE, if none. */
tree default_argument;
/* True iff this is the first parameter in the list and the
parameter sequence ends with an ellipsis. */
bool ellipsis_p;
};
/* A declarator. */
struct cp_declarator {
/* The kind of declarator. */
ENUM_BITFIELD (cp_declarator_kind) kind : 4;
/* Whether we parsed an ellipsis (`...') just before the declarator,
to indicate this is a parameter pack. */
BOOL_BITFIELD parameter_pack_p : 1;
/* Attributes that apply to this declarator. */
tree attributes;
/* For all but cdk_id and cdk_error, the contained declarator. For
cdk_id and cdk_error, guaranteed to be NULL. */
cp_declarator *declarator;
location_t id_loc; /* Currently only set for cdk_id and cdk_function. */
union {
/* For identifiers. */
struct {
/* If non-NULL, the qualifying scope (a NAMESPACE_DECL or
*_TYPE) for this identifier. */
tree qualifying_scope;
/* The unqualified name of the entity -- an IDENTIFIER_NODE,
BIT_NOT_EXPR, or TEMPLATE_ID_EXPR. */
tree unqualified_name;
/* If this is the name of a function, what kind of special
function (if any). */
special_function_kind sfk;
} id;
/* For functions. */
struct {
/* The parameters to the function as a TREE_LIST of decl/default. */
tree parameters;
/* The cv-qualifiers for the function. */
cp_cv_quals qualifiers;
/* The exception-specification for the function. */
tree exception_specification;
/* The late-specified return type, if any. */
tree late_return_type;
} function;
/* For arrays. */
struct {
/* The bounds to the array. */
tree bounds;
} array;
/* For cdk_pointer and cdk_ptrmem. */
struct {
/* The cv-qualifiers for the pointer. */
cp_cv_quals qualifiers;
/* For cdk_ptrmem, the class type containing the member. */
tree class_type;
} pointer;
/* For cdk_reference */
struct {
/* The cv-qualifiers for the reference. These qualifiers are
only used to diagnose ill-formed code. */
cp_cv_quals qualifiers;
/* Whether this is an rvalue reference */
bool rvalue_ref;
} reference;
} u;
};
/* A level of template instantiation. */
struct tinst_level GTY(())
{
/* The immediately deeper level in the chain. */
struct tinst_level *next;
/* The original node. Can be either a DECL (for a function or static
data member) or a TYPE (for a class), depending on what we were
asked to instantiate. */
tree decl;
/* The location where the template is instantiated. */
location_t locus;
/* True if the location is in a system header. */
bool in_system_header_p;
};
/* A parameter list indicating for a function with no parameters,
e.g "int f(void)". */
extern cp_parameter_declarator *no_parameters;
/* True if we saw "#pragma GCC java_exceptions". */
extern bool pragma_java_exceptions;
/* in call.c */
extern bool check_dtor_name (tree, tree);
extern tree build_vfield_ref (tree, tree);
extern tree build_conditional_expr (tree, tree, tree,
tsubst_flags_t);
extern tree build_addr_func (tree);
extern tree build_call_a (tree, int, tree*);
extern tree build_call_n (tree, int, ...);
extern bool null_ptr_cst_p (tree);
extern bool sufficient_parms_p (const_tree);
extern tree type_decays_to (tree);
extern tree build_user_type_conversion (tree, tree, int);
extern tree build_new_function_call (tree, tree, bool,
tsubst_flags_t);
extern tree build_operator_new_call (tree, tree, tree *, tree *,
tree *);
extern tree build_object_call (tree, tree, tsubst_flags_t);
extern tree build_new_method_call (tree, tree, tree, tree, int,
tree *, tsubst_flags_t);
extern tree build_special_member_call (tree, tree, tree, tree, int,
tsubst_flags_t);
extern tree build_new_op (enum tree_code, int, tree,
tree, tree, bool *,
tsubst_flags_t);
extern tree build_op_delete_call (enum tree_code, tree, tree, bool, tree, tree);
extern bool can_convert (tree, tree);
extern bool can_convert_arg (tree, tree, tree, int);
extern bool can_convert_arg_bad (tree, tree, tree);
extern bool enforce_access (tree, tree, tree);
extern tree convert_default_arg (tree, tree, tree, int);
extern tree convert_arg_to_ellipsis (tree);
extern tree build_x_va_arg (tree, tree);
extern tree cxx_type_promotes_to (tree);
extern tree type_passed_as (tree);
extern tree convert_for_arg_passing (tree, tree);
extern bool is_properly_derived_from (tree, tree);
extern tree set_up_extended_ref_temp (tree, tree, tree *, tree *);
extern tree initialize_reference (tree, tree, tree, tree *);
extern tree make_temporary_var_for_ref_to_temp (tree, tree);
extern tree strip_top_quals (tree);
extern tree perform_implicit_conversion (tree, tree, tsubst_flags_t);
extern tree perform_direct_initialization_if_possible (tree, tree, bool,
tsubst_flags_t);
extern tree in_charge_arg_for_name (tree);
extern tree build_cxx_call (tree, int, tree *);
extern bool is_std_init_list (tree);
extern bool is_list_ctor (tree);
#ifdef ENABLE_CHECKING
extern void validate_conversion_obstack (void);
#endif /* ENABLE_CHECKING */
/* in class.c */
extern tree build_base_path (enum tree_code, tree,
tree, int);
extern tree convert_to_base (tree, tree, bool, bool);
extern tree convert_to_base_statically (tree, tree);
extern tree build_vtbl_ref (tree, tree);
extern tree build_vfn_ref (tree, tree);
extern tree get_vtable_decl (tree, int);
extern void resort_type_method_vec (void *, void *,
gt_pointer_operator, void *);
extern bool add_method (tree, tree, tree);
extern bool currently_open_class (tree);
extern tree currently_open_derived_class (tree);
extern tree finish_struct (tree, tree);
extern void finish_struct_1 (tree);
extern int resolves_to_fixed_type_p (tree, int *);
extern void init_class_processing (void);
extern int is_empty_class (tree);
extern bool is_really_empty_class (tree);
extern void pushclass (tree);
extern void popclass (void);
extern void push_nested_class (tree);
extern void pop_nested_class (void);
extern int current_lang_depth (void);
extern void push_lang_context (tree);
extern void pop_lang_context (void);
extern tree instantiate_type (tree, tree, tsubst_flags_t);
extern void print_class_statistics (void);
extern void cxx_print_statistics (void);
extern void cxx_print_xnode (FILE *, tree, int);
extern void cxx_print_decl (FILE *, tree, int);
extern void cxx_print_type (FILE *, tree, int);
extern void cxx_print_identifier (FILE *, tree, int);
extern void cxx_print_error_function (struct diagnostic_context *,
const char *,
struct diagnostic_info *);
extern void build_self_reference (void);
extern int same_signature_p (const_tree, const_tree);
extern void maybe_add_class_template_decl_list (tree, tree, int);
extern void unreverse_member_declarations (tree);
extern void invalidate_class_lookup_cache (void);
extern void maybe_note_name_used_in_class (tree, tree);
extern void note_name_declared_in_class (tree, tree);
extern tree get_vtbl_decl_for_binfo (tree);
extern void debug_class (tree);
extern void debug_thunks (tree);
extern tree cp_fold_obj_type_ref (tree, tree);
extern void set_linkage_according_to_type (tree, tree);
extern void determine_key_method (tree);
extern void check_for_override (tree, tree);
extern void push_class_stack (void);
extern void pop_class_stack (void);
extern bool type_has_user_nondefault_constructor (tree);
extern bool type_has_user_provided_constructor (tree);
extern bool type_has_user_provided_default_constructor (tree);
extern bool defaultable_fn_p (tree);
/* in cvt.c */
extern tree convert_to_reference (tree, tree, int, int, tree);
extern tree convert_from_reference (tree);
extern tree force_rvalue (tree);
extern tree ocp_convert (tree, tree, int, int);
extern tree cp_convert (tree, tree);
extern tree cp_convert_and_check (tree, tree);
extern tree convert_to_void (tree, const char */*implicit context*/,
tsubst_flags_t);
extern tree convert_force (tree, tree, int);
extern tree build_expr_type_conversion (int, tree, bool);
extern tree type_promotes_to (tree);
extern tree perform_qualification_conversions (tree, tree);
extern void clone_function_decl (tree, int);
extern void adjust_clone_args (tree);
/* decl.c */
extern tree poplevel (int, int, int);
extern void insert_block (tree);
extern tree pushdecl (tree);
extern tree pushdecl_maybe_friend (tree, bool);
extern void cxx_init_decl_processing (void);
enum cp_tree_node_structure_enum cp_tree_node_structure
(union lang_tree_node *);
extern bool cxx_mark_addressable (tree);
extern void maybe_push_cleanup_level (tree);
extern void finish_scope (void);
extern void push_switch (tree);
extern void pop_switch (void);
extern tree pushtag (tree, tree, tag_scope);
extern tree make_anon_name (void);
extern int decls_match (tree, tree);
extern tree duplicate_decls (tree, tree, bool);
extern tree pushdecl_top_level_maybe_friend (tree, bool);
extern tree pushdecl_top_level_and_finish (tree, tree);
extern tree declare_local_label (tree);
extern tree define_label (location_t, tree);
extern void check_goto (tree);
extern bool check_omp_return (void);
extern tree make_typename_type (tree, tree, enum tag_types, tsubst_flags_t);
extern tree make_unbound_class_template (tree, tree, tree, tsubst_flags_t);
extern tree check_for_out_of_scope_variable (tree);
extern tree build_library_fn_ptr (const char *, tree);
extern tree build_cp_library_fn_ptr (const char *, tree);
extern tree push_library_fn (tree, tree, tree);
extern tree push_void_library_fn (tree, tree);
extern tree push_throw_library_fn (tree, tree);
extern tree check_tag_decl (cp_decl_specifier_seq *);
extern tree shadow_tag (cp_decl_specifier_seq *);
extern tree groktypename (cp_decl_specifier_seq *, const cp_declarator *, bool);
extern tree start_decl (const cp_declarator *, cp_decl_specifier_seq *, int, tree, tree, tree *);
extern void start_decl_1 (tree, bool);
extern bool check_array_initializer (tree, tree, tree);
extern void cp_finish_decl (tree, tree, bool, tree, int);
extern void finish_decl (tree, tree, tree);
extern int cp_complete_array_type (tree *, tree, bool);
extern tree build_ptrmemfunc_type (tree);
extern tree build_ptrmem_type (tree, tree);
/* the grokdeclarator prototype is in decl.h */
extern tree build_this_parm (tree, cp_cv_quals);
extern int copy_fn_p (const_tree);
extern bool move_fn_p (const_tree);
extern tree get_scope_of_declarator (const cp_declarator *);
extern void grok_special_member_properties (tree);
extern int grok_ctor_properties (const_tree, const_tree);
extern bool grok_op_properties (tree, bool);
extern tree xref_tag (enum tag_types, tree, tag_scope, bool);
extern tree xref_tag_from_type (tree, tree, tag_scope);
extern bool xref_basetypes (tree, tree);
extern tree start_enum (tree, tree, bool);
extern void finish_enum (tree);
extern void build_enumerator (tree, tree, tree);
extern tree lookup_enumerator (tree, tree);
extern void start_preparsed_function (tree, tree, int);
extern int start_function (cp_decl_specifier_seq *, const cp_declarator *, tree);
extern tree begin_function_body (void);
extern void finish_function_body (tree);
extern tree outer_curly_brace_block (tree);
extern tree finish_function (int);
extern tree start_method (cp_decl_specifier_seq *, const cp_declarator *, tree);
extern tree finish_method (tree);
extern void maybe_register_incomplete_var (tree);
extern void maybe_commonize_var (tree);
extern void complete_vars (tree);
extern void finish_stmt (void);
extern void print_other_binding_stack (struct cp_binding_level *);
extern void revert_static_member_fn (tree);
extern void fixup_anonymous_aggr (tree);
extern int check_static_variable_definition (tree, tree);
extern tree compute_array_index_type (tree, tree);
extern tree check_default_argument (tree, tree);
typedef int (*walk_namespaces_fn) (tree, void *);
extern int walk_namespaces (walk_namespaces_fn,
void *);
extern int wrapup_globals_for_namespace (tree, void *);
extern tree create_implicit_typedef (tree, tree);
extern tree maybe_push_decl (tree);
extern tree force_target_expr (tree, tree);
extern tree build_target_expr_with_type (tree, tree);
extern int local_variable_p (const_tree);
extern tree register_dtor_fn (tree);
extern tmpl_spec_kind current_tmpl_spec_kind (int);
extern tree cp_fname_init (const char *, tree *);
extern tree cxx_builtin_function (tree decl);
extern tree cxx_builtin_function_ext_scope (tree decl);
extern tree check_elaborated_type_specifier (enum tag_types, tree, bool);
extern void warn_extern_redeclared_static (tree, tree);
extern const char *cxx_comdat_group (tree);
extern bool cp_missing_noreturn_ok_p (tree);
extern void initialize_artificial_var (tree, tree);
extern tree check_var_type (tree, tree);
extern tree reshape_init (tree, tree);
extern bool defer_mark_used_calls;
extern GTY(()) VEC(tree, gc) *deferred_mark_used_calls;
/* in decl2.c */
extern bool check_java_method (tree);
extern tree build_memfn_type (tree, tree, cp_cv_quals);
extern void maybe_retrofit_in_chrg (tree);
extern void maybe_make_one_only (tree);
extern void grokclassfn (tree, tree,
enum overload_flags);
extern tree grok_array_decl (tree, tree);
extern tree delete_sanity (tree, tree, bool, int);
extern tree check_classfn (tree, tree, tree);
extern void check_member_template (tree);
extern tree grokfield (const cp_declarator *, cp_decl_specifier_seq *,
tree, bool, tree, tree);
extern tree grokbitfield (const cp_declarator *, cp_decl_specifier_seq *,
tree, tree);
extern tree cp_reconstruct_complex_type (tree, tree);
extern void cplus_decl_attributes (tree *, tree, int);
extern void finish_anon_union (tree);
extern void cp_write_global_declarations (void);
extern tree coerce_new_type (tree);
extern tree coerce_delete_type (tree);
extern void comdat_linkage (tree);
extern void determine_visibility (tree);
extern void constrain_class_visibility (tree);
extern void update_member_visibility (tree);
extern void import_export_decl (tree);
extern tree build_cleanup (tree);
extern tree build_offset_ref_call_from_tree (tree, tree);
extern void check_default_args (tree);
extern void mark_used (tree);
extern void finish_static_data_member_decl (tree, tree, bool, tree, int);
extern tree cp_build_parm_decl (tree, tree);
extern tree get_guard (tree);
extern tree get_guard_cond (tree);
extern tree set_guard (tree);
extern tree cxx_callgraph_analyze_expr (tree *, int *);
extern void mark_needed (tree);
extern bool decl_needed_p (tree);
extern void note_vague_linkage_fn (tree);
extern tree build_artificial_parm (tree, tree);
extern bool possibly_inlined_p (tree);
extern int parm_index (tree);
/* in error.c */
extern void init_error (void);
extern const char *type_as_string (tree, int);
extern const char *decl_as_string (tree, int);
extern const char *expr_as_string (tree, int);
extern const char *lang_decl_name (tree, int);
extern const char *language_to_string (enum languages);
extern const char *class_key_or_enum_as_string (tree);
extern void print_instantiation_context (void);
extern void maybe_warn_variadic_templates (void);
extern void maybe_warn_cpp0x (const char *);
/* in except.c */
extern void init_exception_processing (void);
extern tree expand_start_catch_block (tree);
extern void expand_end_catch_block (void);
extern tree build_exc_ptr (void);
extern tree build_throw (tree);
extern int nothrow_libfn_p (const_tree);
extern void check_handlers (tree);
extern void choose_personality_routine (enum languages);
extern tree eh_type_info (tree);
/* in expr.c */
extern tree cplus_expand_constant (tree);
/* friend.c */
extern int is_friend (tree, tree);
extern void make_friend_class (tree, tree, bool);
extern void add_friend (tree, tree, bool);
extern tree do_friend (tree, tree, tree, tree, enum overload_flags, bool);
/* in init.c */
extern tree expand_member_init (tree);
extern void emit_mem_initializers (tree);
extern tree build_aggr_init (tree, tree, int,
tsubst_flags_t);
extern int is_class_type (tree, int);
extern tree get_type_value (tree);
extern tree build_zero_init (tree, tree, bool);
extern tree build_value_init (tree);
extern tree build_value_init_noctor (tree);
extern tree build_offset_ref (tree, tree, bool);
extern tree build_new (tree, tree, tree, tree, int,
tsubst_flags_t);
extern tree build_vec_init (tree, tree, tree, bool, int,
tsubst_flags_t);
extern tree build_delete (tree, tree,
special_function_kind,
int, int);
extern void push_base_cleanups (void);
extern tree build_vec_delete (tree, tree,
special_function_kind, int);
extern tree create_temporary_var (tree);
extern void initialize_vtbl_ptrs (tree);
extern tree build_java_class_ref (tree);
extern tree integral_constant_value (tree);
/* in lex.c */
extern void cxx_dup_lang_specific_decl (tree);
extern void yyungetc (int, int);
extern tree unqualified_name_lookup_error (tree);
extern tree unqualified_fn_lookup_error (tree);
extern tree build_lang_decl (enum tree_code, tree, tree);
extern void retrofit_lang_decl (tree);
extern tree copy_decl (tree);
extern tree copy_type (tree);
extern tree cxx_make_type (enum tree_code);
extern tree make_class_type (enum tree_code);
extern void yyerror (const char *);
extern void yyhook (int);
extern bool cxx_init (void);
extern void cxx_finish (void);
extern bool in_main_input_context (void);
/* in method.c */
extern void init_method (void);
extern tree make_thunk (tree, bool, tree, tree);
extern void finish_thunk (tree);
extern void use_thunk (tree, bool);
extern void synthesize_method (tree);
extern tree lazily_declare_fn (special_function_kind,
tree);
extern tree skip_artificial_parms_for (const_tree, tree);
extern int num_artificial_parms_for (const_tree);
extern tree make_alias_for (tree, tree);
extern tree locate_copy (tree, void *);
extern tree locate_ctor (tree, void *);
extern tree locate_dtor (tree, void *);
/* In optimize.c */
extern bool maybe_clone_body (tree);
/* in pt.c */
extern bool check_template_shadow (tree);
extern tree get_innermost_template_args (tree, int);
extern void maybe_begin_member_template_processing (tree);
extern void maybe_end_member_template_processing (void);
extern tree finish_member_template_decl (tree);
extern void begin_template_parm_list (void);
extern bool begin_specialization (void);
extern void reset_specialization (void);
extern void end_specialization (void);
extern void begin_explicit_instantiation (void);
extern void end_explicit_instantiation (void);
extern tree check_explicit_specialization (tree, tree, int, int);
extern tree make_auto (void);
extern tree do_auto_deduction (tree, tree, tree);
extern tree type_uses_auto (tree);
extern tree splice_late_return_type (tree, tree);
extern bool is_auto (const_tree);
extern tree process_template_parm (tree, tree, bool, bool);
extern tree end_template_parm_list (tree);
extern void end_template_decl (void);
extern bool check_default_tmpl_args (tree, tree, int, int, int);
extern tree push_template_decl (tree);
extern tree push_template_decl_real (tree, bool);
extern bool redeclare_class_template (tree, tree);
extern tree lookup_template_class (tree, tree, tree, tree,
int, tsubst_flags_t);
extern tree lookup_template_function (tree, tree);
extern int uses_template_parms (tree);
extern int uses_template_parms_level (tree, int);
extern tree instantiate_class_template (tree);
extern tree instantiate_template (tree, tree, tsubst_flags_t);
extern int fn_type_unification (tree, tree, tree, tree,
tree, unification_kind_t, int);
extern void mark_decl_instantiated (tree, int);
extern int more_specialized_fn (tree, tree, int);
extern void do_decl_instantiation (tree, tree);
extern void do_type_instantiation (tree, tree, tsubst_flags_t);
extern tree instantiate_decl (tree, int, bool);
extern int comp_template_parms (const_tree, const_tree);
extern bool uses_parameter_packs (tree);
extern bool template_parameter_pack_p (const_tree);
extern tree make_pack_expansion (tree);
extern bool check_for_bare_parameter_packs (tree);
extern tree get_template_info (tree);
extern int template_class_depth (tree);
extern int is_specialization_of (tree, tree);
extern bool is_specialization_of_friend (tree, tree);
extern tree get_pattern_parm (tree, tree);
extern int comp_template_args (tree, tree);
extern tree maybe_process_partial_specialization (tree);
extern tree most_specialized_instantiation (tree);
extern void print_candidates (tree);
extern void instantiate_pending_templates (int);
extern tree tsubst_default_argument (tree, tree, tree);
extern tree tsubst_copy_and_build (tree, tree, tsubst_flags_t,
tree, bool, bool);
extern tree most_general_template (tree);
extern tree get_mostly_instantiated_function_type (tree);
extern int problematic_instantiation_changed (void);
extern void record_last_problematic_instantiation (void);
extern struct tinst_level *current_instantiation(void);
extern tree maybe_get_template_decl_from_type_decl (tree);
extern int processing_template_parmlist;
extern bool dependent_type_p (tree);
extern bool dependent_scope_p (tree);
extern bool any_dependent_template_arguments_p (const_tree);
extern bool dependent_template_p (tree);
extern bool dependent_template_id_p (tree, tree);
extern bool type_dependent_expression_p (tree);
extern bool any_type_dependent_arguments_p (const_tree);
extern bool type_dependent_expression_p_push (tree);
extern bool value_dependent_expression_p (tree);
extern bool any_value_dependent_elements_p (const_tree);
extern bool dependent_omp_for_p (tree, tree, tree, tree);
extern tree resolve_typename_type (tree, bool);
extern tree template_for_substitution (tree);
extern tree build_non_dependent_expr (tree);
extern tree build_non_dependent_args (tree);
extern bool reregister_specialization (tree, tree, tree);
extern tree fold_non_dependent_expr (tree);
extern bool explicit_class_specialization_p (tree);
extern struct tinst_level *outermost_tinst_level(void);
extern bool parameter_of_template_p (tree, tree);
/* in repo.c */
extern void init_repo (void);
extern int repo_emit_p (tree);
extern bool repo_export_class_p (const_tree);
extern void finish_repo (void);
/* in rtti.c */
/* A vector of all tinfo decls that haven't been emitted yet. */
extern GTY(()) VEC(tree,gc) *unemitted_tinfo_decls;
extern void init_rtti_processing (void);
extern tree build_typeid (tree);
extern tree get_tinfo_decl (tree);
extern tree get_typeid (tree);
extern tree build_headof (tree);
extern tree build_dynamic_cast (tree, tree, tsubst_flags_t);
extern void emit_support_tinfos (void);
extern bool emit_tinfo_decl (tree);
/* in search.c */
extern bool accessible_base_p (tree, tree, bool);
extern tree lookup_base (tree, tree, base_access,
base_kind *);
extern tree dcast_base_hint (tree, tree);
extern int accessible_p (tree, tree, bool);
extern tree lookup_field_1 (tree, tree, bool);
extern tree lookup_field (tree, tree, int, bool);
extern int lookup_fnfields_1 (tree, tree);
extern int class_method_index_for_fn (tree, tree);
extern tree lookup_fnfields (tree, tree, int);
extern tree lookup_member (tree, tree, int, bool);
extern int look_for_overrides (tree, tree);
extern void get_pure_virtuals (tree);
extern void maybe_suppress_debug_info (tree);
extern void note_debug_info_needed (tree);
extern void print_search_statistics (void);
extern void reinit_search_statistics (void);
extern tree current_scope (void);
extern int at_function_scope_p (void);
extern bool at_class_scope_p (void);
extern bool at_namespace_scope_p (void);
extern tree context_for_name_lookup (tree);
extern tree lookup_conversions (tree);
extern tree binfo_from_vbase (tree);
extern tree binfo_for_vbase (tree, tree);
extern tree look_for_overrides_here (tree, tree);
#define dfs_skip_bases ((tree)1)
extern tree dfs_walk_all (tree, tree (*) (tree, void *),
tree (*) (tree, void *), void *);
extern tree dfs_walk_once (tree, tree (*) (tree, void *),
tree (*) (tree, void *), void *);
extern tree binfo_via_virtual (tree, tree);
extern tree build_baselink (tree, tree, tree, tree);
extern tree adjust_result_of_qualified_name_lookup
(tree, tree, tree);
extern tree copied_binfo (tree, tree);
extern tree original_binfo (tree, tree);
extern int shared_member_p (tree);
/* The representation of a deferred access check. */
typedef struct deferred_access_check GTY(())
{
/* The base class in which the declaration is referenced. */
tree binfo;
/* The declaration whose access must be checked. */
tree decl;
/* The declaration that should be used in the error message. */
tree diag_decl;
} deferred_access_check;
DEF_VEC_O(deferred_access_check);
DEF_VEC_ALLOC_O(deferred_access_check,gc);
/* in semantics.c */
extern void push_deferring_access_checks (deferring_kind);
extern void resume_deferring_access_checks (void);
extern void stop_deferring_access_checks (void);
extern void pop_deferring_access_checks (void);
extern VEC (deferred_access_check,gc)* get_deferred_access_checks (void);
extern void pop_to_parent_deferring_access_checks (void);
extern void perform_access_checks (VEC (deferred_access_check,gc)*);
extern void perform_deferred_access_checks (void);
extern void perform_or_defer_access_check (tree, tree, tree);
extern int stmts_are_full_exprs_p (void);
extern void init_cp_semantics (void);
extern tree do_poplevel (tree);
extern void add_decl_expr (tree);
extern tree finish_expr_stmt (tree);
extern tree begin_if_stmt (void);
extern void finish_if_stmt_cond (tree, tree);
extern tree finish_then_clause (tree);
extern void begin_else_clause (tree);
extern void finish_else_clause (tree);
extern void finish_if_stmt (tree);
extern tree begin_while_stmt (void);
extern void finish_while_stmt_cond (tree, tree);
extern void finish_while_stmt (tree);
extern tree begin_do_stmt (void);
extern void finish_do_body (tree);
extern void finish_do_stmt (tree, tree);
extern tree finish_return_stmt (tree);
extern tree begin_for_stmt (void);
extern void finish_for_init_stmt (tree);
extern void finish_for_cond (tree, tree);
extern void finish_for_expr (tree, tree);
extern void finish_for_stmt (tree);
extern tree finish_break_stmt (void);
extern tree finish_continue_stmt (void);
extern tree begin_switch_stmt (void);
extern void finish_switch_cond (tree, tree);
extern void finish_switch_stmt (tree);
extern tree finish_case_label (tree, tree);
extern tree finish_goto_stmt (tree);
extern tree begin_try_block (void);
extern void finish_try_block (tree);
extern tree begin_eh_spec_block (void);
extern void finish_eh_spec_block (tree, tree);
extern void finish_handler_sequence (tree);
extern tree begin_function_try_block (tree *);
extern void finish_function_try_block (tree);
extern void finish_function_handler_sequence (tree, tree);
extern void finish_cleanup_try_block (tree);
extern tree begin_handler (void);
extern void finish_handler_parms (tree, tree);
extern void finish_handler (tree);
extern void finish_cleanup (tree, tree);
enum {
BCS_NO_SCOPE = 1,
BCS_TRY_BLOCK = 2,
BCS_FN_BODY = 4
};
extern tree begin_compound_stmt (unsigned int);
extern void finish_compound_stmt (tree);
extern tree finish_asm_stmt (int, tree, tree, tree, tree);
extern tree finish_label_stmt (tree);
extern void finish_label_decl (tree);
extern tree finish_parenthesized_expr (tree);
extern tree finish_non_static_data_member (tree, tree, tree);
extern tree begin_stmt_expr (void);
extern tree finish_stmt_expr_expr (tree, tree);
extern tree finish_stmt_expr (tree, bool);
extern tree stmt_expr_value_expr (tree);
extern tree perform_koenig_lookup (tree, tree);
extern tree finish_call_expr (tree, tree, bool, bool,
tsubst_flags_t);
extern tree finish_increment_expr (tree, enum tree_code);
extern tree finish_this_expr (void);
extern tree finish_pseudo_destructor_expr (tree, tree, tree);
extern tree finish_unary_op_expr (enum tree_code, tree);
extern tree finish_compound_literal (tree, tree);
extern tree finish_fname (tree);
extern void finish_translation_unit (void);
extern tree finish_template_type_parm (tree, tree);
extern tree finish_template_template_parm (tree, tree);
extern tree begin_class_definition (tree, tree);
extern void finish_template_decl (tree);
extern tree finish_template_type (tree, tree, int);
extern tree finish_base_specifier (tree, tree, bool);
extern void finish_member_declaration (tree);
extern void qualified_name_lookup_error (tree, tree, tree,
location_t);
extern void check_template_keyword (tree);
extern tree finish_id_expression (tree, tree, tree,
cp_id_kind *,
bool, bool, bool *,
bool, bool, bool, bool,
const char **,
location_t);
extern tree finish_typeof (tree);
extern tree finish_offsetof (tree);
extern void finish_decl_cleanup (tree, tree);
extern void finish_eh_cleanup (tree);
extern void emit_associated_thunks (tree);
extern void finish_mem_initializers (tree);
extern tree check_template_template_default_arg (tree);
extern void expand_or_defer_fn (tree);
extern void check_accessibility_of_qualified_id (tree, tree, tree);
extern tree finish_qualified_id_expr (tree, tree, bool, bool,
bool, bool);
extern void simplify_aggr_init_expr (tree *);
extern void finalize_nrv (tree *, tree, tree);
extern void note_decl_for_pch (tree);
extern tree finish_omp_clauses (tree);
extern void finish_omp_threadprivate (tree);
extern tree begin_omp_structured_block (void);
extern tree finish_omp_structured_block (tree);
extern tree begin_omp_parallel (void);
extern tree finish_omp_parallel (tree, tree);
extern tree begin_omp_task (void);
extern tree finish_omp_task (tree, tree);
extern tree finish_omp_for (location_t, tree, tree,
tree, tree, tree, tree, tree);
extern void finish_omp_atomic (enum tree_code, tree, tree);
extern void finish_omp_barrier (void);
extern void finish_omp_flush (void);
extern void finish_omp_taskwait (void);
extern enum omp_clause_default_kind cxx_omp_predetermined_sharing (tree);
extern tree cxx_omp_clause_default_ctor (tree, tree, tree);
extern tree cxx_omp_clause_copy_ctor (tree, tree, tree);
extern tree cxx_omp_clause_assign_op (tree, tree, tree);
extern tree cxx_omp_clause_dtor (tree, tree);
extern void cxx_omp_finish_clause (tree);
extern bool cxx_omp_privatize_by_reference (const_tree);
extern bool cxx_omp_create_clause_info (tree, tree, bool, bool, bool);
extern tree baselink_for_fns (tree);
extern void finish_static_assert (tree, tree, location_t,
bool);
extern tree describable_type (tree);
extern tree finish_decltype_type (tree, bool);
extern tree finish_trait_expr (enum cp_trait_kind, tree, tree);
/* in tree.c */
extern void lang_check_failed (const char *, int,
const char *) ATTRIBUTE_NORETURN;
extern tree stabilize_expr (tree, tree *);
extern void stabilize_call (tree, tree *);
extern void stabilize_aggr_init (tree, tree *);
extern bool stabilize_init (tree, tree *);
extern tree add_stmt_to_compound (tree, tree);
extern tree cxx_maybe_build_cleanup (tree);
extern void init_tree (void);
extern int pod_type_p (const_tree);
extern bool class_tmpl_impl_spec_p (const_tree);
extern int zero_init_p (const_tree);
extern tree canonical_type_variant (tree);
extern tree copy_binfo (tree, tree, tree,
tree *, int);
extern int member_p (const_tree);
extern cp_lvalue_kind real_lvalue_p (tree);
extern bool lvalue_or_rvalue_with_address_p (tree);
extern bool builtin_valid_in_constant_expr_p (const_tree);
extern tree build_min (enum tree_code, tree, ...);
extern tree build_min_nt (enum tree_code, ...);
extern tree build_min_non_dep (enum tree_code, tree, ...);
extern tree build_min_non_dep_call_list (tree, tree, tree);
extern tree build_cplus_new (tree, tree);
extern tree build_aggr_init_expr (tree, tree);
extern tree get_target_expr (tree);
extern tree build_cplus_array_type (tree, tree);
extern tree build_array_of_n_type (tree, int);
extern tree hash_tree_cons (tree, tree, tree);
extern tree hash_tree_chain (tree, tree);
extern tree build_qualified_name (tree, tree, tree, bool);
extern int is_overloaded_fn (tree);
extern tree get_first_fn (tree);
extern tree ovl_cons (tree, tree);
extern tree build_overload (tree, tree);
extern const char *cxx_printable_name (tree, int);
extern tree build_exception_variant (tree, tree);
extern tree bind_template_template_parm (tree, tree);
extern tree array_type_nelts_total (tree);
extern tree array_type_nelts_top (tree);
extern tree break_out_target_exprs (tree);
extern tree get_type_decl (tree);
extern tree decl_namespace_context (tree);
extern bool decl_anon_ns_mem_p (const_tree);
extern tree lvalue_type (tree);
extern tree error_type (tree);
extern int varargs_function_p (const_tree);
extern bool really_overloaded_fn (tree);
extern bool cp_tree_equal (tree, tree);
extern tree no_linkage_check (tree, bool);
extern void debug_binfo (tree);
extern tree build_dummy_object (tree);
extern tree maybe_dummy_object (tree, tree *);
extern int is_dummy_object (const_tree);
extern const struct attribute_spec cxx_attribute_table[];
extern tree make_ptrmem_cst (tree, tree);
extern tree cp_build_type_attribute_variant (tree, tree);
extern tree cp_build_reference_type (tree, bool);
extern tree cp_build_qualified_type_real (tree, int, tsubst_flags_t);
#define cp_build_qualified_type(TYPE, QUALS) \
cp_build_qualified_type_real ((TYPE), (QUALS), tf_warning_or_error)
extern special_function_kind special_function_p (const_tree);
extern int count_trees (tree);
extern int char_type_p (tree);
extern void verify_stmt_tree (tree);
extern linkage_kind decl_linkage (tree);
extern tree cp_walk_subtrees (tree*, int*, walk_tree_fn,
void*, struct pointer_set_t*);
#define cp_walk_tree(a,b,c,d) \
walk_tree_1 (a, b, c, d, cp_walk_subtrees)
#define cp_walk_tree_without_duplicates(a,b,c) \
walk_tree_without_duplicates_1 (a, b, c, cp_walk_subtrees)
extern tree fold_if_not_in_template (tree);
extern tree rvalue (tree);
extern tree convert_bitfield_to_declared_type (tree);
extern tree cp_save_expr (tree);
extern bool cast_valid_in_integral_constant_expression_p (tree);
extern bool cxx_type_hash_eq (const_tree, const_tree);
/* in typeck.c */
extern int string_conv_p (const_tree, const_tree, int);
extern tree cp_truthvalue_conversion (tree);
extern tree condition_conversion (tree);
extern tree require_complete_type (tree);
extern tree complete_type (tree);
extern tree complete_type_or_else (tree, tree);
extern int type_unknown_p (const_tree);
extern bool comp_except_specs (const_tree, const_tree, bool);
extern bool comptypes (tree, tree, int);
extern bool compparms (const_tree, const_tree);
extern int comp_cv_qualification (const_tree, const_tree);
extern int comp_cv_qual_signature (tree, tree);
extern tree cxx_sizeof_or_alignof_expr (tree, enum tree_code, bool);
extern tree cxx_sizeof_or_alignof_type (tree, enum tree_code, bool);
extern tree cxx_sizeof_nowarn (tree);
extern tree is_bitfield_expr_with_lowered_type (const_tree);
extern tree unlowered_expr_type (const_tree);
extern tree decay_conversion (tree);
extern tree build_class_member_access_expr (tree, tree, tree, bool,
tsubst_flags_t);
extern tree finish_class_member_access_expr (tree, tree, bool,
tsubst_flags_t);
extern tree build_x_indirect_ref (tree, const char *,
tsubst_flags_t);
extern tree cp_build_indirect_ref (tree, const char *,
tsubst_flags_t);
extern tree build_array_ref (tree, tree, location_t);
extern tree get_member_function_from_ptrfunc (tree *, tree);
extern tree cp_build_function_call (tree, tree, tsubst_flags_t);
extern tree build_x_binary_op (enum tree_code, tree,
enum tree_code, tree,
enum tree_code, bool *,
tsubst_flags_t);
extern tree build_x_array_ref (tree, tree, tsubst_flags_t);
extern tree build_x_unary_op (enum tree_code, tree,
tsubst_flags_t);
extern tree cp_build_unary_op (enum tree_code, tree, int,
tsubst_flags_t);
extern tree unary_complex_lvalue (enum tree_code, tree);
extern tree build_x_conditional_expr (tree, tree, tree,
tsubst_flags_t);
extern tree build_x_compound_expr_from_list (tree, const char *);
extern tree build_x_compound_expr (tree, tree, tsubst_flags_t);
extern tree build_compound_expr (tree, tree);
extern tree cp_build_compound_expr (tree, tree, tsubst_flags_t);
extern tree build_static_cast (tree, tree, tsubst_flags_t);
extern tree build_reinterpret_cast (tree, tree, tsubst_flags_t);
extern tree build_const_cast (tree, tree, tsubst_flags_t);
extern tree build_c_cast (tree, tree);
extern tree cp_build_c_cast (tree, tree, tsubst_flags_t);
extern tree build_x_modify_expr (tree, enum tree_code, tree,
tsubst_flags_t);
extern tree cp_build_modify_expr (tree, enum tree_code, tree,
tsubst_flags_t);
extern tree convert_for_initialization (tree, tree, tree, int,
const char *, tree, int,
tsubst_flags_t);
extern int comp_ptr_ttypes (tree, tree);
extern bool comp_ptr_ttypes_const (tree, tree);
extern int ptr_reasonably_similar (const_tree, const_tree);
extern tree build_ptrmemfunc (tree, tree, int, bool);
extern int cp_type_quals (const_tree);
extern bool cp_type_readonly (const_tree);
extern bool cp_has_mutable_p (const_tree);
extern bool at_least_as_qualified_p (const_tree, const_tree);
extern void cp_apply_type_quals_to_decl (int, tree);
extern tree build_ptrmemfunc1 (tree, tree, tree);
extern void expand_ptrmemfunc_cst (tree, tree *, tree *);
extern tree type_after_usual_arithmetic_conversions (tree, tree);
extern tree common_pointer_type (tree, tree);
extern tree composite_pointer_type (tree, tree, tree, tree,
const char*, tsubst_flags_t);
extern tree merge_types (tree, tree);
extern tree check_return_expr (tree, bool *);
extern tree cp_build_binary_op (location_t,
enum tree_code, tree, tree,
tsubst_flags_t);
#define cxx_sizeof(T) cxx_sizeof_or_alignof_type (T, SIZEOF_EXPR, true)
extern tree build_ptrmemfunc_access_expr (tree, tree);
extern tree build_address (tree);
extern tree build_nop (tree, tree);
extern tree non_reference (tree);
extern tree lookup_anon_field (tree, tree);
extern bool invalid_nonstatic_memfn_p (const_tree, tsubst_flags_t);
extern tree convert_member_func_to_ptr (tree, tree);
extern tree convert_ptrmem (tree, tree, bool, bool);
extern int lvalue_or_else (tree, enum lvalue_use,
tsubst_flags_t);
extern int lvalue_p (tree);
/* in typeck2.c */
extern void require_complete_eh_spec_types (tree, tree);
extern void cxx_incomplete_type_diagnostic (const_tree, const_tree, diagnostic_t);
#undef cxx_incomplete_type_error
extern void cxx_incomplete_type_error (const_tree, const_tree);
#define cxx_incomplete_type_error(V,T) \
(cxx_incomplete_type_diagnostic ((V), (T), DK_ERROR))
extern tree error_not_base_type (tree, tree);
extern tree binfo_or_else (tree, tree);
extern void readonly_error (tree, const char *);
extern void complete_type_check_abstract (tree);
extern int abstract_virtuals_error (tree, tree);
extern tree store_init_value (tree, tree);
extern void check_narrowing (tree, tree);
extern tree digest_init (tree, tree);
extern tree build_scoped_ref (tree, tree, tree *);
extern tree build_x_arrow (tree);
extern tree build_m_component_ref (tree, tree);
extern tree build_functional_cast (tree, tree, tsubst_flags_t);
extern tree add_exception_specifier (tree, tree, int);
extern tree merge_exception_specifiers (tree, tree);
/* in mangle.c */
extern void init_mangle (void);
extern void mangle_decl (tree);
extern const char *mangle_type_string (tree);
extern tree mangle_typeinfo_for_type (tree);
extern tree mangle_typeinfo_string_for_type (tree);
extern tree mangle_vtbl_for_type (tree);
extern tree mangle_vtt_for_type (tree);
extern tree mangle_ctor_vtbl_for_type (tree, tree);
extern tree mangle_thunk (tree, int, tree, tree);
extern tree mangle_conv_op_name_for_type (tree);
extern tree mangle_guard_variable (tree);
extern tree mangle_ref_init_variable (tree);
extern tree mangle_compound_literal (void);
/* in dump.c */
extern bool cp_dump_tree (void *, tree);
/* In cp/cp-objcp-common.c. */
extern alias_set_type cxx_get_alias_set (tree);
extern bool cxx_warn_unused_global_decl (const_tree);
extern tree cp_expr_size (const_tree);
extern size_t cp_tree_size (enum tree_code);
extern bool cp_var_mod_type_p (tree, tree);
extern void cxx_initialize_diagnostics (struct diagnostic_context *);
extern int cxx_types_compatible_p (tree, tree);
extern void init_shadowed_var_for_decl (void);
extern tree cxx_staticp (tree);
/* in cp-gimplify.c */
extern int cp_gimplify_expr (tree *, gimple_seq *,
gimple_seq *);
extern void cp_genericize (tree);
/* -- end of C++ */
#endif /* ! GCC_CP_TREE_H */
|
gemm.h | /* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include <cstring>
#include <string>
#include "common/log.h"
#include "memory/t_malloc.h"
#ifdef _OPENMP
#include <omp.h>
#endif
// 矩阵取值运算宏，假设矩阵按行存储
#define A(i, j) A[(i)*lda + (j)]
#define B(i, j) B[(i)*ldb + (j)]
#define C(i, j) C[(i)*ldc + (j)]
#if __aarch64__
#define MR_INT8 4
#define NR_INT8 4
#define MR 6
#define NR 16
#else
#define MR_INT8 4
#define NR_INT8 2
#define MR 6
#define NR 8
#endif
#define s_min(i, j) ((i) < (j) ? (i) : (j))
namespace paddle_mobile {
namespace operators {
namespace math {
class Gemm {
public:
typedef void (Gemm::*FnPack)(int, int, int, const float *, int, float *,
const bool);
typedef void (Gemm::*FnAddDot)(int, const float *, const float *, float *,
int);
FnPack procPackA;
FnPack procPackB;
FnAddDot procAddDot;
void PackMatrixA_6r(int m, int k, int m_tail, const float *A, int lda,
float *buffer, const bool parallel);
void PackMatrixA_8r(int m, int k, int m_tail, const float *A, int lda,
float *buffer, const bool parallel);
void PackMatrixB_8c(int k, int n, int n_tail, const float *B, int ldb,
float *buffer, const bool parallel);
#if __aarch64__
void PackMatrixB_12c(int k, int n, int n_tail, const float *B, int ldb,
float *buffer, const bool parallel);
void PackMatrixB_16c(int k, int n, int n_tail, const float *B, int ldb,
float *buffer, const bool parallel);
#endif
// 分块矩阵乘法
void InnerKernel(int mc, int nc, float alpha, const float *a, const float *b,
float beta, float *c, float *C, int ldc, bool relu);
void InnerKernelWithBias(int mc, int nc, float alpha, const float *a,
const float *b, float beta, float *c, float *C,
int ldc, bool relu, float *bias);
void InnerKernelWithBn(int mc, int nc, float alpha, const float *a,
const float *b, float beta, float *c, float *C,
int ldc, bool relu, float *new_scale, float *new_bias);
void InnerKernelWithBnAdd(int mc, int nc, float alpha, const float *a,
const float *b, float beta, float *c, float *C,
int ldc, bool relu, float *new_scale,
float *new_bias, float *bias);
void InnerKernelWithPRelu(int mc, int nc, const float *a, const float *b,
float *c, float *C, int ldc, float *p,
std::string mode, float *bias, float *bias1);
// 计算一个更小的 C 矩阵分块
#if __aarch64__
void AddDot6x8(int k, const float *a, const float *b, float *c, int ldc);
void AddDot8x12(int k, const float *a, const float *b, float *c, int ldc);
void AddDot6x16(int k, const float *a, const float *b, float *c, int ldc);
#else
void AddDot4x4(int k, const float *a, const float *b, float *c, int ldc);
void AddDot4x8(int k, const float *a, const float *b, float *c, int ldc);
void AddDot6x8(int k, const float *a, const float *b, float *c, int ldc);
#endif
// 分块矩阵乘法结果回写
// C = A * B
void WriteBasic(int mc, int nc, float *c, float *C, int ldc);
// C = alpha * A * B + beta * C
void WriteWithAlphaBeta(int mc, int nc, float *c, float *C, int ldc);
// C = A * B + C
void WriteWithAdd(int mc, int nc, float *c, float *C, int ldc);
// C = A * B + bias
void WriteWithAddV1(int mc, int nc, float *c, float *C, int ldc, float *bias);
// C = A * B + C, relu(C)
void WriteWithAddRelu(int mc, int nc, float *c, float *C, int ldc);
// C = A * B + C,prelu(C)
void WriteWithAddPRelu(int mc, int nc, float *c, float *C, int ldc, float *p,
std::string mode, float *bias, float *bias1);
// C = A * B + bias ,relu(C)
void WriteWithAddReluV1(int mc, int nc, float *c, float *C, int ldc,
float *bias);
// C = A * B, batchnorm(C)
void WriteWithBn(int mc, int nc, float *c, float *C, int ldc,
float *new_scale, float *new_bias);
// C = A * B, batchnorm(C), relu(C)
void WriteWithBnRelu(int mc, int nc, float *c, float *C, int ldc,
float *new_scale, float *new_bias);
void WriteWithBnAddRelu(int mc, int nc, float *c, float *C, int ldc,
float *new_scale, float *new_bias, float *bias1);
// 向量矩阵乘法 (M = 1)
#if __aarch64__
#else
void VectorKernel(int m, int n, int k, float alpha, const float *A, int lda,
const float *B, int ldb, float beta, float *C, int ldc,
bool relu);
void VectorKernelWithBn(int m, int n, int k, float alpha, const float *A,
int lda, const float *B, int ldb, float beta,
float *C, int ldc, bool relu, float *new_scale,
float *new_bias);
// 向量矩阵乘法结果回写
// C = A * B
void VecWriteBasic(int n, float *c, float *C, int ldc);
// C = alpha * A * B + beta * C
void VecWriteWithAlphaBeta(int n, float *c, float *C, int ldc);
// C = A * B + C
void VecWriteWithAdd(int n, float *c, float *C, int ldc);
// C = A * B + C, relu(C)
void VecWriteWithAddRelu(int n, float *c, float *C, int ldc);
// C = A * B, batchnorm(C)
void VecWriteWithBn(int n, float *c, float *C, int ldc, float *new_scale,
float *new_bias);
// C = A * B, batchnorm(C), relu(C)
void VecWriteWithBnRelu(int n, float *c, float *C, int ldc, float *new_scale,
float *new_bias);
#endif
// 32位 float 矩阵乘法
void Sgemm(int m, int n, int k, float alpha, const float *A, int lda,
const float *B, int ldb, float beta, float *C, int ldc, bool relu,
float *bias);
// 32位 float 矩阵乘法, 并对结果进行 batchnrom
void SgemmWithBn(int m, int n, int k, float alpha, const float *A, int lda,
const float *B, int ldb, float beta, float *C, int ldc,
bool relu, float *new_scale, float *new_bias, float *bias);
void SgemmWithPRelu(int m, int n, int k, const float *A, int lda,
const float *B, int ldb, float *C, int ldc, float *p,
std::string mode, float *bias, float *bias1);
// 32位 float 矩阵乘法（openmp 多线程版本）
void Sgemm_omp(int m, int n, int k, float alpha, const float *A, int lda,
const float *B, int ldb, float beta, float *C, int ldc,
bool relu, float *bias);
// 32位 float 矩阵乘法, 并对结果进行 batchnrom（openmp 多线程版本）
void SgemmWithBn_omp(int m, int n, int k, float alpha, const float *A,
int lda, const float *B, int ldb, float beta, float *C,
int ldc, bool relu, float *new_scale, float *new_bias,
float *bias);
void SgemmWithPRelu_omp(int m, int n, int k, const float *A, int lda,
const float *B, int ldb, float *C, int ldc, float *p,
std::string mode, float *bias, float *bias1);
// 8 bits function cluster begins
// 8 bits int small block inner product, data packed k = 1
void AddDot4x8(int32_t k, const int8_t *a, const int8_t *b, int32_t *c,
int32_t ldc);
void AddDot6x8(int32_t k, const int8_t *a, const int8_t *b, int32_t *c,
int32_t ldc);
// 8 bits int small block inner product, data packed k = 16
void AddDot4x2(int32_t k, const int8_t *a, const int8_t *b, int32_t *c,
int32_t ldc);
void AddDot4x4(int32_t k, const int8_t *a, const int8_t *b, int32_t *c,
int32_t ldc);
// 8 bits int inner product
template <typename Otype>
void InnerKernel(int32_t mc, int32_t nc, float alpha, const int8_t *a,
const int8_t *b, float beta, int32_t *c, Otype *C,
int32_t ldc, bool relu);
template <typename Otype>
void InnerKernelWithBias(int32_t mc, int32_t nc, float alpha, const int8_t *a,
const int8_t *b, float beta, int32_t *c, Otype *C,
int32_t ldc, bool relu, int32_t *bias,
bool addOnRow = false);
// 8 bits int pack function
void PackMatrixA_4r(int32_t m, int32_t k, int32_t m_tail, const int8_t *A,
int32_t lda, int8_t *buffer);
void PackMatrixA_6r(int32_t m, int32_t k, int32_t m_tail, const int8_t *A,
int32_t lda, int8_t *buffer);
void PackMatrixB_8c(int32_t k, int32_t n, int32_t n_tail, const int8_t *B,
int32_t ldb, int8_t *buffer);
void PackMatrixA_4r_16(int32_t m, int32_t k, int32_t m_tail, const int8_t *A,
int32_t lda, int8_t *buffer);
void PackMatrixB_2c_16(int32_t k, int32_t n, int32_t n_tail, const int8_t *B,
int32_t ldb, int8_t *buffer);
void PackMatrixB_4c_16(int32_t k, int32_t n, int32_t n_tail, const int8_t *B,
int32_t ldb, int8_t *buffer);
void PackMatrixA_omp_4r(int32_t m, int32_t k, int32_t m_tail, const int8_t *A,
int32_t lda, int8_t *buffer);
void PackMatrixB_omp_8c(int32_t k, int32_t n, int32_t n_tail, const int8_t *B,
int32_t ldb, int8_t *buffer);
void PackMatrixA_omp_4r_16(int32_t m, int32_t k, int32_t m_tail,
const int8_t *A, int32_t lda, int8_t *buffer);
void PackMatrixB_omp_2c_16(int32_t k, int32_t n, int32_t n_tail,
const int8_t *B, int32_t ldb, int8_t *buffer);
void PackMatrixB_omp_4c_16(int32_t k, int32_t n, int32_t n_tail,
const int8_t *B, int32_t ldb, int8_t *buffer);
// 8 bits int matrix product
template <typename Itype, typename Btype, typename Otype>
void Sgemm_omp(int32_t m, int32_t n, int32_t k, float alpha, const Itype *A,
int32_t lda, const Itype *B, int32_t ldb, float beta, Otype *C,
int32_t ldc, bool relu, Btype *bias, bool addOnRow = false);
template <typename Otype>
void Sgemm_omp(int32_t m, int32_t n, int32_t k, float alpha, const int8_t *A,
int32_t lda, const int8_t *B, int32_t ldb, float beta,
Otype *C, int32_t ldc, bool relu, int32_t *bias,
bool addOnRow = false);
template <typename Itype, typename Btype, typename Otype>
void Sgemm(int32_t m, int32_t n, int32_t k, float alpha, const Itype *A,
int32_t lda, const Itype *B, int32_t ldb, float beta, Otype *C,
int32_t ldc, bool relu, Btype *bias, bool addOnRow = false);
template <typename Otype>
void Sgemm(int32_t m, int32_t n, int32_t k, float alpha, const int8_t *A,
int32_t lda, const int8_t *B, int32_t ldb, float beta, Otype *C,
int32_t ldc, bool relu, int32_t *bias, bool addOnRow = false);
// 8 bits int write back
// C = A * B
void WriteBasic(int32_t mc, int32_t nc, int32_t *c, int32_t *C, int32_t ldc);
// C = A * B + bias, scale * relu(C)
void WriteWithAddReluScale(int32_t mc, int32_t nc, int32_t *c, int8_t *C,
int32_t ldc, int32_t *bias, float scale);
// C = A * B + bias, scale * C, bias is added on column
void WriteWithAddScale(int32_t mc, int32_t nc, int32_t *c, int8_t *C,
int32_t ldc, int32_t *bias, float scale);
// C = A * B + bias, scale * C, bias is added on row
void WriteWithAddScaleT(int32_t mc, int32_t nc, int32_t *c, int8_t *C,
int32_t ldc, int32_t *bias, float scale);
private:
int MC = 0;
int KC = 0;
int NC = 0;
// 32位 float
float *packedA;
float *packedB;
float *packedC;
// 8 bits int
int8_t *packedA_int8;
int8_t *packedB_int8;
int32_t *packedC_int32;
int8_t *zero_int8;
};
// 8 bits int matrix product (m*k x k*n)
template <typename Otype>
void Gemm::Sgemm(int32_t m, int32_t n, int32_t k, float alpha, const int8_t *A,
int32_t lda, const int8_t *B, int32_t ldb, float beta,
Otype *C, int32_t ldc, bool relu, int32_t *bias,
bool addOnRow) {
// L1 data cache is 32 kib (Per Contex-A57, Contex-A72, Contex-A73)
// L2 cache is 0.5~4 Mib (Contex-A72 cluster)
int32_t L1 = 32 * 1024;
int32_t L2 = 512 * 1024;
const int32_t k_complete = (k + 15) - ((k + 15) & 15);
KC = k_complete;
MC = L1 / (KC * sizeof(int8_t));
NC = L2 / (KC * sizeof(int8_t));
// make sure MC is multiple of MR_INT8, and NC is multiple of NR_INT8
if (MC == 0) {
MC = MR_INT8;
} else {
int32_t mblock_num = (m + MC - 1) / MC;
MC = (m + mblock_num - 1) / mblock_num;
MC = (MC + MR_INT8 - 1) / MR_INT8 * MR_INT8;
}
// DLOG << "mblock_num = " << mblock_num << ", MC = " << MC << "\n";
if (NC == 0) {
NC = NR_INT8;
} else {
int32_t nblock_num = (n + NC - 1) / NC;
NC = (n + nblock_num - 1) / nblock_num;
NC = (NC + NR_INT8 - 1) / NR_INT8 * NR_INT8;
}
// DLOG << "nblock_num = " << nblock_num << ", NC = " << NC << "\n";
packedA_int8 = static_cast<int8_t *>(
paddle_mobile::memory::Alloc(sizeof(int8_t) * MC * KC));
packedB_int8 = static_cast<int8_t *>(
paddle_mobile::memory::Alloc(sizeof(int8_t) * KC * NC));
packedC_int32 = static_cast<int32_t *>(
paddle_mobile::memory::Alloc(sizeof(int32_t) * MC * NC));
zero_int8 =
static_cast<int8_t *>(paddle_mobile::memory::Alloc(sizeof(int8_t) * k));
memset(static_cast<void *>(zero_int8), 0, sizeof(int8_t) * k);
int32_t mc, nc;
for (int32_t j = 0; j < n; j += NC) {
nc = s_min(n - j, NC);
#if __aarch64__
PackMatrixB_4c_16(k, nc, nc % NR_INT8, &B(0, j), ldb, packedB_int8);
#else
PackMatrixB_2c_16(k, nc, nc % NR_INT8, &B(0, j), ldb, packedB_int8);
#endif
for (int32_t i = 0; i < m; i += MC) {
mc = s_min(m - i, MC);
PackMatrixA_4r_16(mc, k, mc % MR_INT8, &A(i, 0), lda, packedA_int8);
if (bias == nullptr) {
InnerKernel(mc, nc, alpha, packedA_int8, packedB_int8, beta,
packedC_int32, &C(i, j), ldc, relu);
} else {
if (addOnRow) {
InnerKernelWithBias(mc, nc, alpha, packedA_int8, packedB_int8, beta,
packedC_int32, &C(i, j), ldc, relu, bias + j,
addOnRow);
} else {
InnerKernelWithBias(mc, nc, alpha, packedA_int8, packedB_int8, beta,
packedC_int32, &C(i, j), ldc, relu, bias + i,
addOnRow);
}
}
}
}
paddle_mobile::memory::Free(packedA_int8);
paddle_mobile::memory::Free(packedB_int8);
paddle_mobile::memory::Free(packedC_int32);
paddle_mobile::memory::Free(zero_int8);
}
// 8 bits int matrix product (m*k x k*n), omp version
template <typename Otype>
void Gemm::Sgemm_omp(int32_t m, int32_t n, int32_t k, float alpha,
const int8_t *A, int32_t lda, const int8_t *B, int32_t ldb,
float beta, Otype *C, int32_t ldc, bool relu,
int32_t *bias, bool addOnRow) {
#ifdef _OPENMP
int32_t max_threads = omp_get_max_threads();
#else
int32_t max_threads = 1;
#endif
int32_t L1 = 64 / max_threads * 1024;
const int32_t k_complete = (k + 15) - ((k + 15) & 15);
KC = k_complete;
zero_int8 =
static_cast<int8_t *>(paddle_mobile::memory::Alloc(sizeof(int8_t) * k));
memset(static_cast<void *>(zero_int8), 0, sizeof(int8_t) * k);
if (m > n) {
// 对 A 分块
MC = L1 / (KC * sizeof(int8_t));
if (MC == 0) {
MC = MR_INT8;
} else {
int32_t mblock_num = (m + MC - 1) / MC;
MC = (m + mblock_num - 1) / mblock_num;
MC = (MC + MR_INT8 - 1) / MR_INT8 * MR_INT8;
}
// 补齐 B
NC = (n + NR_INT8 - 1) / NR_INT8 * NR_INT8;
packedB_int8 = static_cast<int8_t *>(
paddle_mobile::memory::Alloc(sizeof(int8_t) * KC * NC));
#if __aarch64__
PackMatrixB_omp_4c_16(k, n, n % NR_INT8, B, ldb, packedB_int8);
#else
PackMatrixB_omp_2c_16(k, n, n % NR_INT8, B, ldb, packedB_int8);
#endif
packedA_int8 = static_cast<int8_t *>(
paddle_mobile::memory::Alloc(sizeof(int8_t) * MC * KC * max_threads));
} else {
// 对 B 分块
NC = L1 / (KC * sizeof(int8_t));
if (NC == 0) {
NC = NR_INT8;
} else {
int32_t nblock_num = (n + NC - 1) / NC;
NC = (n + nblock_num - 1) / nblock_num;
NC = (NC + NR_INT8 - 1) / NR_INT8 * NR_INT8;
}
// 补齐 A
MC = (m + MR_INT8 - 1) / MR_INT8 * MR_INT8;
packedA_int8 = static_cast<int8_t *>(
paddle_mobile::memory::Alloc(sizeof(int8_t) * MC * KC));
#if __aarch64__
PackMatrixA_omp_4r_16(m, k, m % MR_INT8, A, lda, packedA_int8);
#else
PackMatrixA_omp_4r_16(m, k, m % MR_INT8, A, lda, packedA_int8);
#endif
packedB_int8 = static_cast<int8_t *>(
paddle_mobile::memory::Alloc(sizeof(int8_t) * KC * NC * max_threads));
}
packedC_int32 = static_cast<int32_t *>(
paddle_mobile::memory::Alloc(sizeof(int32_t) * MC * NC * max_threads));
if (m > n) {
#pragma omp parallel for
for (int32_t i = 0; i < m; i += MC) {
#ifdef _OPENMP
int32_t local_threads = omp_get_thread_num();
#else
int32_t local_threads = 0;
#endif
int32_t mc;
mc = s_min(m - i, MC);
int8_t *local_A = packedA_int8 + MC * KC * local_threads;
int32_t *local_C = packedC_int32 + MC * NC * local_threads;
#if __aarch64__
PackMatrixA_4r_16(mc, k, mc % MR_INT8, &A(i, 0), lda, local_A);
#else
PackMatrixA_4r_16(mc, k, mc % MR_INT8, &A(i, 0), lda, local_A);
#endif
if (bias == nullptr) {
InnerKernel(mc, n, alpha, local_A, packedB_int8, beta, local_C,
&C(i, 0), ldc, relu);
} else {
if (addOnRow) {
InnerKernelWithBias(mc, n, alpha, local_A, packedB_int8, beta,
local_C, &C(i, 0), ldc, relu, bias, addOnRow);
} else {
InnerKernelWithBias(mc, n, alpha, local_A, packedB_int8, beta,
local_C, &C(i, 0), ldc, relu, bias + i, addOnRow);
}
}
}
} else {
#pragma omp parallel for
for (int32_t j = 0; j < n; j += NC) {
#ifdef _OPENMP
int32_t local_threads = omp_get_thread_num();
#else
int32_t local_threads = 0;
#endif
int32_t nc;
nc = s_min(n - j, NC);
int8_t *local_B = packedB_int8 + KC * NC * local_threads;
int32_t *local_C = packedC_int32 + MC * NC * local_threads;
#if __aarch64__
PackMatrixB_4c_16(k, nc, nc % NR_INT8, &B(0, j), ldb, local_B);
#else
PackMatrixB_2c_16(k, nc, nc % NR_INT8, &B(0, j), ldb, local_B);
#endif
if (bias == nullptr) {
InnerKernel(m, nc, alpha, packedA_int8, local_B, beta, local_C,
&C(0, j), ldc, relu);
} else {
if (addOnRow) {
InnerKernelWithBias(m, nc, alpha, packedA_int8, local_B, beta,
local_C, &C(0, j), ldc, relu, bias + j, addOnRow);
} else {
InnerKernelWithBias(m, nc, alpha, packedA_int8, local_B, beta,
local_C, &C(0, j), ldc, relu, bias, addOnRow);
}
}
}
}
paddle_mobile::memory::Free(packedA_int8);
paddle_mobile::memory::Free(packedB_int8);
paddle_mobile::memory::Free(packedC_int32);
paddle_mobile::memory::Free(zero_int8);
}
} // namespace math
} // namespace operators
} // namespace paddle_mobile
|
vector.c | /******************************************************************************
* Copyright 1998-2019 Lawrence Livermore National Security, LLC and other
* HYPRE Project Developers. See the top-level COPYRIGHT file for details.
*
* SPDX-License-Identifier: (Apache-2.0 OR MIT)
******************************************************************************/
/******************************************************************************
*
* Member functions for hypre_Vector class.
*
*****************************************************************************/
#include "seq_mv.h"
/*--------------------------------------------------------------------------
* hypre_SeqVectorCreate
*--------------------------------------------------------------------------*/
hypre_Vector *
hypre_SeqVectorCreate( HYPRE_Int size )
{
hypre_Vector *vector;
vector = hypre_CTAlloc(hypre_Vector, 1, HYPRE_MEMORY_HOST);
hypre_VectorData(vector) = NULL;
hypre_VectorSize(vector) = size;
hypre_VectorNumVectors(vector) = 1;
hypre_VectorMultiVecStorageMethod(vector) = 0;
/* set defaults */
hypre_VectorOwnsData(vector) = 1;
hypre_VectorMemoryLocation(vector) = HYPRE_MEMORY_SHARED;
return vector;
}
/*--------------------------------------------------------------------------
* hypre_SeqMultiVectorCreate
*--------------------------------------------------------------------------*/
hypre_Vector *
hypre_SeqMultiVectorCreate( HYPRE_Int size, HYPRE_Int num_vectors )
{
hypre_Vector *vector = hypre_SeqVectorCreate(size);
hypre_VectorNumVectors(vector) = num_vectors;
return vector;
}
/*--------------------------------------------------------------------------
* hypre_SeqVectorDestroy
*--------------------------------------------------------------------------*/
HYPRE_Int
hypre_SeqVectorDestroy( hypre_Vector *vector )
{
HYPRE_Int ierr=0;
if (vector)
{
HYPRE_Int memory_location = hypre_VectorMemoryLocation(vector);
if ( hypre_VectorOwnsData(vector) )
{
hypre_TFree(hypre_VectorData(vector), memory_location);
}
hypre_TFree(vector, HYPRE_MEMORY_HOST);
}
return ierr;
}
/*--------------------------------------------------------------------------
* hypre_SeqVectorInitialize
*--------------------------------------------------------------------------*/
HYPRE_Int
hypre_SeqVectorInitialize_v2( hypre_Vector *vector, HYPRE_Int memory_location )
{
HYPRE_Int size = hypre_VectorSize(vector);
HYPRE_Int ierr = 0;
HYPRE_Int num_vectors = hypre_VectorNumVectors(vector);
HYPRE_Int multivec_storage_method = hypre_VectorMultiVecStorageMethod(vector);
hypre_VectorMemoryLocation(vector) = memory_location;
/* Caveat: for pre-existing data, the memory location must be guaranteed
* to be consistent with `memory_location'
* Otherwise, mismatches will exist and problems will be encountered
* when being used, and freed */
if ( !hypre_VectorData(vector) )
{
hypre_VectorData(vector) = hypre_CTAlloc(HYPRE_Complex, num_vectors*size,
memory_location);
}
if ( multivec_storage_method == 0 )
{
hypre_VectorVectorStride(vector) = size;
hypre_VectorIndexStride(vector) = 1;
}
else if ( multivec_storage_method == 1 )
{
hypre_VectorVectorStride(vector) = 1;
hypre_VectorIndexStride(vector) = num_vectors;
}
else
{
++ierr;
}
return ierr;
}
HYPRE_Int
hypre_SeqVectorInitialize( hypre_Vector *vector )
{
HYPRE_Int ierr;
ierr = hypre_SeqVectorInitialize_v2( vector, hypre_VectorMemoryLocation(vector) );
return ierr;
}
/*--------------------------------------------------------------------------
* hypre_SeqVectorSetDataOwner
*--------------------------------------------------------------------------*/
HYPRE_Int
hypre_SeqVectorSetDataOwner( hypre_Vector *vector,
HYPRE_Int owns_data )
{
HYPRE_Int ierr=0;
hypre_VectorOwnsData(vector) = owns_data;
return ierr;
}
/*--------------------------------------------------------------------------
* ReadVector
*--------------------------------------------------------------------------*/
hypre_Vector *
hypre_SeqVectorRead( char *file_name )
{
hypre_Vector *vector;
FILE *fp;
HYPRE_Complex *data;
HYPRE_Int size;
HYPRE_Int j;
/*----------------------------------------------------------
* Read in the data
*----------------------------------------------------------*/
fp = fopen(file_name, "r");
hypre_fscanf(fp, "%d", &size);
vector = hypre_SeqVectorCreate(size);
hypre_SeqVectorInitialize(vector);
data = hypre_VectorData(vector);
for (j = 0; j < size; j++)
{
hypre_fscanf(fp, "%le", &data[j]);
}
fclose(fp);
/* multivector code not written yet */
hypre_assert( hypre_VectorNumVectors(vector) == 1 );
return vector;
}
/*--------------------------------------------------------------------------
* hypre_SeqVectorPrint
*--------------------------------------------------------------------------*/
HYPRE_Int
hypre_SeqVectorPrint( hypre_Vector *vector,
char *file_name )
{
FILE *fp;
HYPRE_Complex *data;
HYPRE_Int size, num_vectors, vecstride, idxstride;
HYPRE_Int i, j;
HYPRE_Complex value;
HYPRE_Int ierr = 0;
num_vectors = hypre_VectorNumVectors(vector);
vecstride = hypre_VectorVectorStride(vector);
idxstride = hypre_VectorIndexStride(vector);
/*----------------------------------------------------------
* Print in the data
*----------------------------------------------------------*/
data = hypre_VectorData(vector);
size = hypre_VectorSize(vector);
fp = fopen(file_name, "w");
if ( hypre_VectorNumVectors(vector) == 1 )
{
hypre_fprintf(fp, "%d\n", size);
}
else
{
hypre_fprintf(fp, "%d vectors of size %d\n", num_vectors, size );
}
if ( num_vectors>1 )
{
for ( j=0; j<num_vectors; ++j )
{
hypre_fprintf(fp, "vector %d\n", j );
for (i = 0; i < size; i++)
{
value = data[ j*vecstride + i*idxstride ];
#ifdef HYPRE_COMPLEX
hypre_fprintf(fp, "%.14e , %.14e\n",
hypre_creal(value), hypre_cimag(value));
#else
hypre_fprintf(fp, "%.14e\n", value);
#endif
}
}
}
else
{
for (i = 0; i < size; i++)
{
#ifdef HYPRE_COMPLEX
hypre_fprintf(fp, "%.14e , %.14e\n",
hypre_creal(data[i]), hypre_cimag(data[i]));
#else
hypre_fprintf(fp, "%.14e\n", data[i]);
#endif
}
}
fclose(fp);
return ierr;
}
/*--------------------------------------------------------------------------
* hypre_SeqVectorSetConstantValues
*--------------------------------------------------------------------------*/
HYPRE_Int
hypre_SeqVectorSetConstantValues( hypre_Vector *v,
HYPRE_Complex value )
{
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_BLAS1] -= hypre_MPI_Wtime();
#endif
HYPRE_Complex *vector_data = hypre_VectorData(v);
HYPRE_Int size = hypre_VectorSize(v);
HYPRE_Int ierr = 0;
size *= hypre_VectorNumVectors(v);
hypre_SeqVectorPrefetch(v, HYPRE_MEMORY_DEVICE);
#if defined(HYPRE_USING_CUDA)
HYPRE_THRUST_CALL( fill_n, vector_data, size, value );
#else
HYPRE_Int i;
#if defined(HYPRE_USING_DEVICE_OPENMP)
#pragma omp target teams distribute parallel for private(i) is_device_ptr(vector_data)
#elif defined(HYPRE_USING_OPENMP)
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < size; i++)
{
vector_data[i] = value;
}
#endif /* defined(HYPRE_USING_CUDA) */
hypre_SyncCudaComputeStream(hypre_handle);
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_BLAS1] += hypre_MPI_Wtime();
#endif
return ierr;
}
/*--------------------------------------------------------------------------
* hypre_SeqVectorSetRandomValues
*
* returns vector of values randomly distributed between -1.0 and +1.0
*--------------------------------------------------------------------------*/
HYPRE_Int
hypre_SeqVectorSetRandomValues( hypre_Vector *v,
HYPRE_Int seed )
{
HYPRE_Complex *vector_data = hypre_VectorData(v);
HYPRE_Int size = hypre_VectorSize(v);
HYPRE_Int i;
HYPRE_Int ierr = 0;
hypre_SeedRand(seed);
size *= hypre_VectorNumVectors(v);
/* RDF: threading this loop may cause problems because of hypre_Rand() */
for (i = 0; i < size; i++)
{
vector_data[i] = 2.0 * hypre_Rand() - 1.0;
}
return ierr;
}
/*--------------------------------------------------------------------------
* hypre_SeqVectorCopy
* copies data from x to y
* if size of x is larger than y only the first size_y elements of x are
* copied to y
*--------------------------------------------------------------------------*/
HYPRE_Int
hypre_SeqVectorCopy( hypre_Vector *x,
hypre_Vector *y )
{
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_BLAS1] -= hypre_MPI_Wtime();
#endif
hypre_SeqVectorPrefetch(x, HYPRE_MEMORY_DEVICE);
hypre_SeqVectorPrefetch(y, HYPRE_MEMORY_DEVICE);
HYPRE_Complex *x_data = hypre_VectorData(x);
HYPRE_Complex *y_data = hypre_VectorData(y);
HYPRE_Int size = hypre_VectorSize(x);
HYPRE_Int size_y = hypre_VectorSize(y);
HYPRE_Int ierr = 0;
if (size > size_y)
{
size = size_y;
}
size *= hypre_VectorNumVectors(x);
#if defined(HYPRE_USING_CUDA)
#if defined(HYPRE_USING_CUBLAS)
HYPRE_CUBLAS_CALL( cublasDcopy(hypre_HandleCublasHandle(hypre_handle), size, x_data, 1, y_data, 1) );
#else
HYPRE_THRUST_CALL( copy_n, x_data, size, y_data );
#endif
#else
HYPRE_Int i;
#if defined(HYPRE_USING_DEVICE_OPENMP)
#pragma omp target teams distribute parallel for private(i) is_device_ptr(y_data,x_data)
#elif defined(HYPRE_USING_OPENMP)
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < size; i++)
{
y_data[i] = x_data[i];
}
#endif /* defined(HYPRE_USING_CUDA) */
hypre_SyncCudaComputeStream(hypre_handle);
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_BLAS1] += hypre_MPI_Wtime();
#endif
return ierr;
}
/*--------------------------------------------------------------------------
* hypre_SeqVectorCloneDeep
* Returns a complete copy of x - a deep copy, with its own copy of the data.
*--------------------------------------------------------------------------*/
hypre_Vector*
hypre_SeqVectorCloneDeep( hypre_Vector *x )
{
HYPRE_Int size = hypre_VectorSize(x);
HYPRE_Int num_vectors = hypre_VectorNumVectors(x);
hypre_Vector *y = hypre_SeqMultiVectorCreate( size, num_vectors );
hypre_VectorMultiVecStorageMethod(y) = hypre_VectorMultiVecStorageMethod(x);
hypre_VectorVectorStride(y) = hypre_VectorVectorStride(x);
hypre_VectorIndexStride(y) = hypre_VectorIndexStride(x);
hypre_SeqVectorInitialize(y);
hypre_SeqVectorCopy( x, y );
return y;
}
/*--------------------------------------------------------------------------
* hypre_SeqVectorCloneShallow
* Returns a complete copy of x - a shallow copy, pointing the data of x
*--------------------------------------------------------------------------*/
hypre_Vector *
hypre_SeqVectorCloneShallow( hypre_Vector *x )
{
HYPRE_Int size = hypre_VectorSize(x);
HYPRE_Int num_vectors = hypre_VectorNumVectors(x);
hypre_Vector * y = hypre_SeqMultiVectorCreate( size, num_vectors );
hypre_VectorMultiVecStorageMethod(y) = hypre_VectorMultiVecStorageMethod(x);
hypre_VectorVectorStride(y) = hypre_VectorVectorStride(x);
hypre_VectorIndexStride(y) = hypre_VectorIndexStride(x);
hypre_VectorData(y) = hypre_VectorData(x);
hypre_SeqVectorSetDataOwner( y, 0 );
hypre_SeqVectorInitialize(y);
return y;
}
/*--------------------------------------------------------------------------
* hypre_SeqVectorScale
*--------------------------------------------------------------------------*/
HYPRE_Int
hypre_SeqVectorScale( HYPRE_Complex alpha,
hypre_Vector *y )
{
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_BLAS1] -= hypre_MPI_Wtime();
#endif
HYPRE_Complex *y_data = hypre_VectorData(y);
HYPRE_Int size = hypre_VectorSize(y);
HYPRE_Int ierr = 0;
size *= hypre_VectorNumVectors(y);
hypre_SeqVectorPrefetch(y, HYPRE_MEMORY_DEVICE);
#if defined(HYPRE_USING_CUDA)
#if defined(HYPRE_USING_CUBLAS)
HYPRE_CUBLAS_CALL( cublasDscal(hypre_HandleCublasHandle(hypre_handle), size, &alpha, y_data, 1) );
#else
HYPRE_THRUST_CALL( transform, y_data, y_data + size, y_data, alpha * _1 );
#endif
#else
HYPRE_Int i;
#if defined(HYPRE_USING_DEVICE_OPENMP)
#pragma omp target teams distribute parallel for private(i) is_device_ptr(y_data)
#elif defined(HYPRE_USING_OPENMP)
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < size; i++)
{
y_data[i] *= alpha;
}
#endif /* defined(HYPRE_USING_CUDA) */
hypre_SyncCudaComputeStream(hypre_handle);
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_BLAS1] += hypre_MPI_Wtime();
#endif
return ierr;
}
/*--------------------------------------------------------------------------
* hypre_SeqVectorAxpy
*--------------------------------------------------------------------------*/
HYPRE_Int
hypre_SeqVectorAxpy( HYPRE_Complex alpha,
hypre_Vector *x,
hypre_Vector *y )
{
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_BLAS1] -= hypre_MPI_Wtime();
#endif
HYPRE_Complex *x_data = hypre_VectorData(x);
HYPRE_Complex *y_data = hypre_VectorData(y);
HYPRE_Int size = hypre_VectorSize(x);
HYPRE_Int ierr = 0;
size *= hypre_VectorNumVectors(x);
hypre_SeqVectorPrefetch(x, HYPRE_MEMORY_DEVICE);
hypre_SeqVectorPrefetch(y, HYPRE_MEMORY_DEVICE);
#if defined(HYPRE_USING_CUDA)
#if defined(HYPRE_USING_CUBLAS)
HYPRE_CUBLAS_CALL( cublasDaxpy(hypre_HandleCublasHandle(hypre_handle), size, &alpha, x_data, 1, y_data, 1) );
#else
HYPRE_THRUST_CALL( transform, x_data, x_data + size, y_data, y_data, alpha * _1 + _2 );
#endif
#else
HYPRE_Int i;
#if defined(HYPRE_USING_DEVICE_OPENMP)
#pragma omp target teams distribute parallel for private(i) is_device_ptr(y_data, x_data)
#elif defined(HYPRE_USING_OPENMP)
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < size; i++)
{
y_data[i] += alpha * x_data[i];
}
#endif /* defined(HYPRE_USING_CUDA) */
hypre_SyncCudaComputeStream(hypre_handle);
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_BLAS1] += hypre_MPI_Wtime();
#endif
return ierr;
}
/*--------------------------------------------------------------------------
* hypre_SeqVectorInnerProd
*--------------------------------------------------------------------------*/
HYPRE_Real
hypre_SeqVectorInnerProd( hypre_Vector *x,
hypre_Vector *y )
{
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_BLAS1] -= hypre_MPI_Wtime();
#endif
HYPRE_Complex *x_data = hypre_VectorData(x);
HYPRE_Complex *y_data = hypre_VectorData(y);
HYPRE_Int size = hypre_VectorSize(x);
HYPRE_Real result = 0.0;
size *= hypre_VectorNumVectors(x);
hypre_SeqVectorPrefetch(x, HYPRE_MEMORY_DEVICE);
hypre_SeqVectorPrefetch(y, HYPRE_MEMORY_DEVICE);
#if defined(HYPRE_USING_CUDA)
#ifndef HYPRE_COMPLEX
#if defined(HYPRE_USING_CUBLAS)
HYPRE_CUBLAS_CALL( cublasDdot(hypre_HandleCublasHandle(hypre_handle), size, x_data, 1, y_data, 1, &result) );
#else
result = HYPRE_THRUST_CALL( inner_product, x_data, x_data + size, y_data, 0.0 );
#endif
#else
/* TODO */
#error "Complex inner product"
#endif
#else /* #if defined(HYPRE_USING_CUDA) */
HYPRE_Int i;
#if defined(HYPRE_USING_DEVICE_OPENMP)
#pragma omp target teams distribute parallel for private(i) reduction(+:result) is_device_ptr(y_data,x_data) map(result)
#elif defined(HYPRE_USING_OPENMP)
#pragma omp parallel for private(i) reduction(+:result) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < size; i++)
{
result += hypre_conj(y_data[i]) * x_data[i];
}
#endif /* defined(HYPRE_USING_CUDA) */
hypre_SyncCudaComputeStream(hypre_handle);
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_BLAS1] += hypre_MPI_Wtime();
#endif
return result;
}
//TODO
/*--------------------------------------------------------------------------
* hypre_VectorSumElts:
* Returns the sum of all vector elements.
*--------------------------------------------------------------------------*/
HYPRE_Complex hypre_SeqVectorSumElts( hypre_Vector *vector )
{
HYPRE_Complex sum = 0;
HYPRE_Complex *data = hypre_VectorData( vector );
HYPRE_Int size = hypre_VectorSize( vector );
HYPRE_Int i;
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) reduction(+:sum) HYPRE_SMP_SCHEDULE
#endif
for ( i=0; i<size; ++i ) sum += data[i];
return sum;
}
HYPRE_Int
hypre_SeqVectorPrefetch( hypre_Vector *x, HYPRE_Int to_location)
{
HYPRE_Int ierr = 0;
#ifdef HYPRE_USING_UNIFIED_MEMORY
HYPRE_Complex *x_data = hypre_VectorData(x);
HYPRE_Int size = hypre_VectorSize(x) * hypre_VectorNumVectors(x);
if (hypre_GetActualMemLocation(hypre_VectorMemoryLocation(x)) != HYPRE_MEMORY_SHARED)
{
/* hypre_error_w_msg(HYPRE_ERROR_GENERIC," Error! CUDA Prefetch with non-unified momory\n");*/
return ierr;
}
if (size == 0)
{
return ierr;
}
/* speical use of TMemcpy for prefetch */
hypre_TMemcpy(x_data, x_data, HYPRE_Complex, size, to_location, HYPRE_MEMORY_SHARED);
#endif
return ierr;
}
//hypre_int hypre_SeqVectorIsManaged(hypre_Vector *x)
//{
//}
|
gs.c | #include <stdio.h>
#include <stddef.h>
#include <stdlib.h>
#include <string.h>
#include "c99.h"
#include "name.h"
#include "fail.h"
#include "types.h"
#ifdef _OPENMP
#include "omp.h"
#endif
#define gs_op gs_op_t /* fix conflict with fortran */
#include "gs_defs.h"
#include "gs_local.h"
#include "comm.h"
#include "mem.h"
#include "sort.h"
#include "crystal.h"
#include "sarray_sort.h"
#include "sarray_transfer.h"
#define gs PREFIXED_NAME(gs )
#define gs_vec PREFIXED_NAME(gs_vec )
#define gs_many PREFIXED_NAME(gs_many )
#define gs_setup PREFIXED_NAME(gs_setup )
#define gs_free PREFIXED_NAME(gs_free )
#define gs_unique PREFIXED_NAME(gs_unique)
GS_DEFINE_DOM_SIZES()
typedef enum { mode_plain, mode_vec, mode_many,
mode_dry_run } gs_mode;
static buffer static_buffer = null_buffer;
static void gather_noop(
void *out, const void *in, const unsigned vn,
const uint *map, gs_dom dom, gs_op op)
{}
static void scatter_noop(
void *out, const void *in, const unsigned vn,
const uint *map, gs_dom dom)
{}
static void init_noop(
void *out, const unsigned vn,
const uint *map, gs_dom dom, gs_op op)
{}
/*------------------------------------------------------------------------------
Topology Discovery
------------------------------------------------------------------------------*/
struct gs_topology {
ulong total_shared; /* number of globally unique shared ids */
struct array nz; /* array of nonzero_id's, grouped by id,
sorted by primary index, then flag, then index */
struct array sh; /* array of shared_id's, arbitrary ordering */
struct array pr; /* array of primary_shared_id's */
};
static void gs_topology_free(struct gs_topology *top)
{
array_free(&top->pr);
array_free(&top->sh);
array_free(&top->nz);
}
/************** Local topology **************/
/* nonzero_ids (local part)
Creates an array of s_nonzeros, one per nonzero in user id array. The
output array is grouped by id. Within each group, non-flagged entries come
first; otherwise the entries within the group are sorted by the index into
the user id array. The first index in each group is the primary index, and
is stored along with each entry. The groups themselves are ordered in
increasing order of the primary index associated with the group (as opposed
to the user id). */
struct nonzero_id {
ulong id; uint i, flag, primary;
};
static void nonzero_ids(struct array *nz,
const slong *id, const uint n, buffer *buf)
{
ulong last_id = -(ulong)1;
uint i, primary = -(uint)1;
struct nonzero_id *row, *end;
array_init(struct nonzero_id,nz,n), end=row=nz->ptr;
for(i=0;i<n;++i) {
slong id_i = id[i], abs_id = iabsl(id_i);
if(id_i==0) continue;
end->i = i;
end->id = abs_id;
end->flag = id_i!=abs_id;
++end;
}
nz->n = end-row;
array_resize(struct nonzero_id,nz,nz->n);
sarray_sort_2(struct nonzero_id,nz->ptr,nz->n, id,1, flag,0, buf);
for(row=nz->ptr,end=row+nz->n;row!=end;++row) {
ulong this_id = row->id;
if(this_id!=last_id) primary = row->i;
row->primary = primary;
last_id = this_id;
}
sarray_sort(struct nonzero_id,nz->ptr,nz->n, primary,0, buf);
}
/************** Global topology **************/
/* construct list of all unique id's on this proc */
struct unique_id { ulong id; uint work_proc, src_if; };
static void unique_ids(struct array *un, const struct array *nz, const uint np)
{
struct unique_id *un_row;
const struct nonzero_id *nz_row, *nz_end;
array_init(struct unique_id,un,nz->n), un_row=un->ptr;
for(nz_row=nz->ptr,nz_end=nz_row+nz->n;nz_row!=nz_end;++nz_row) {
if(nz_row->i != nz_row->primary) continue;
un_row->id = nz_row->id;
un_row->work_proc = nz_row->id%np;
un_row->src_if = nz_row->flag ? ~nz_row->i : nz_row->i;
++un_row;
}
un->n = un_row - (struct unique_id*)un->ptr;
}
/* shared_ids (global part)
Creates an array of shared_id's from an array of nonzero_id's. Each entry
in the output identifies one id shared with one other processor p.
Note: two procs share an id only when at least one of them has it unflagged.
The primary index is i locally and ri remotely. Bit 1 of flags indicates
the local flag, bit 2 indicates the remote flag. The output has no
particular ordering.
Also creates an array of primary_shared_id's, one for each shared id.
This struct includes ord, a global rank of the id (arbitrary, but unique). */
#define FLAGS_LOCAL 1
#define FLAGS_REMOTE 2
/* i : local primary index
p : remote proc
ri : remote primary index
bi : buffer index (set and used during pw setup) */
struct shared_id {
ulong id; uint i, p, ri, bi; unsigned flags;
};
struct primary_shared_id {
ulong id, ord; uint i; unsigned flag;
};
struct shared_id_work { ulong id,ord; uint p1, p2, i1f, i2f; };
static void shared_ids_aux(struct array *sh, struct array *pr, uint pr_n,
struct array *wa, buffer *buf)
{
const struct shared_id_work *w, *we;
struct shared_id *s;
struct primary_shared_id *p;
ulong last_id = -(ulong)1;
/* translate work array to output arrays */
sarray_sort(struct shared_id_work,wa->ptr,wa->n, id,1, buf);
array_init(struct shared_id,sh,wa->n), sh->n=wa->n, s=sh->ptr;
array_init(struct primary_shared_id,pr,pr_n), p=pr->ptr;
for(w=wa->ptr,we=w+wa->n;w!=we;++w) {
uint i1f = w->i1f, i2f = w->i2f;
uint i1 = ~i1f<i1f?~i1f:i1f, i2 = ~i2f<i2f?~i2f:i2f;
s->id=w->id, s->i=i1, s->p=w->p2, s->ri=i2;
s->flags = ((i2f^i2)&FLAGS_REMOTE) | ((i1f^i1)&FLAGS_LOCAL);
++s;
if(w->id!=last_id) {
last_id=w->id;
p->id=last_id, p->ord=w->ord, p->i=i1, p->flag=(i1f^i1)&FLAGS_LOCAL;
++p;
}
}
pr->n = p-(struct primary_shared_id*)pr->ptr;
sarray_sort(struct primary_shared_id,pr->ptr,pr->n, i,0, buf);
}
static ulong shared_ids(struct array *sh, struct array *pr,
const struct array *nz, struct crystal *cr)
{
struct array un; struct unique_id *un_row, *un_end, *other;
ulong last_id = -(ulong)1;
ulong ordinal[2], n_shared=0, scan_buf[2];
struct array wa; struct shared_id_work *w;
uint n_unique;
/* construct list of all unique id's on this proc */
unique_ids(&un,nz,cr->comm.np);
n_unique = un.n;
/* transfer list to work procs */
sarray_transfer(struct unique_id,&un, work_proc,1, cr);
/* group by id, put flagged entries after unflagged (within each group) */
sarray_sort_2(struct unique_id,un.ptr,un.n, id,1, src_if,0, &cr->data);
/* count shared id's */
for(un_row=un.ptr,un_end=un_row+un.n;un_row!=un_end;++un_row) {
ulong id = un_row->id;
if(~un_row->src_if<un_row->src_if) continue;
if(id==last_id) continue;
other=un_row+1;
if(other!=un_end&&other->id==id) last_id=id, ++n_shared;
}
comm_scan(ordinal, &cr->comm,gs_slong,gs_add, &n_shared,1, scan_buf);
/* there are ordinal[1] globally shared unique ids;
and ordinal[0] of those are seen by work procs of lower rank;
i.e., this work processor sees the range ordinal[0] + (0,n_shared-1) */
/* construct list of shared ids */
last_id = -(ulong)1;
array_init(struct shared_id_work,&wa,un.n), wa.n=0, w=wa.ptr;
for(un_row=un.ptr,un_end=un_row+un.n;un_row!=un_end;++un_row) {
ulong id = un_row->id;
uint p1 = un_row->work_proc, i1f = un_row->src_if;
if(~i1f<i1f) continue;
for(other=un_row+1;other!=un_end&&other->id==id;++other) {
uint p2 = other->work_proc, i2f = other->src_if;
ulong ord;
if(id!=last_id) last_id=id, ++ordinal[0];
ord=ordinal[0]-1;
if(wa.n+2>wa.max)
array_reserve(struct shared_id_work,&wa,wa.n+2),
w=(struct shared_id_work*)wa.ptr+wa.n;
w->id=id, w->ord=ord, w->p1=p1, w->p2=p2, w->i1f=i1f, w->i2f=i2f, ++w;
w->id=id, w->ord=ord, w->p1=p2, w->p2=p1, w->i1f=i2f, w->i2f=i1f, ++w;
wa.n+=2;
}
}
/* transfer shared list to source procs */
sarray_transfer(struct shared_id_work,&wa, p1,0, cr);
/* fill output arrays from work array */
shared_ids_aux(sh,pr,n_unique,&wa,&cr->data);
array_free(&un);
array_free(&wa);
return ordinal[1];
}
static void get_topology(struct gs_topology *top,
const slong *id, uint n, struct crystal *cr)
{
nonzero_ids(&top->nz,id,n,&cr->data);
top->total_shared = shared_ids(&top->sh,&top->pr, &top->nz,cr);
}
static void make_topology_unique(struct gs_topology *top, slong *id,
uint pid, buffer *buf)
{
struct array *const nz=&top->nz, *const sh=&top->sh, *const pr=&top->pr;
struct nonzero_id *pnz;
struct shared_id *pb, *pe, *e, *out;
struct primary_shared_id *q;
/* flag local non-primaries */
sarray_sort(struct nonzero_id,nz->ptr,nz->n, i,0, buf);
if(id) {
struct nonzero_id *p,*e;
for(p=nz->ptr,e=p+nz->n;p!=e;++p)
if(p->i != p->primary) id[p->i]=-(slong)p->id,p->flag=1;
} else {
struct nonzero_id *p,*e;
for(p=nz->ptr,e=p+nz->n;p!=e;++p)
if(p->i != p->primary) p->flag=1;
}
sarray_sort(struct nonzero_id,nz->ptr,nz->n, primary,0, buf);
/* assign owner among shared primaries */
/* create sentinel with i = -1 */
array_reserve(struct shared_id,sh,sh->n+1);
((struct shared_id*)sh->ptr)[sh->n].i = -(uint)1;
/* in the sorted list of procs sharing a given id,
the owner is chosen to be the j^th unflagged proc,
where j = id mod (length of list) */
sarray_sort_2(struct shared_id,sh->ptr,sh->n, i,0, p,0, buf);
out=sh->ptr; pnz=top->nz.ptr;
for(pb=sh->ptr,e=pb+sh->n;pb!=e;pb=pe) {
uint i = pb->i, lt=0,gt=0, owner; struct shared_id *p;
while(pnz->i!=i) ++pnz;
/* note: current proc not in list */
for(pe=pb; pe->i==i && pe->p<pid; ++pe) if(!(pe->flags&FLAGS_REMOTE)) ++lt;
for( ; pe->i==i ; ++pe) if(!(pe->flags&FLAGS_REMOTE)) ++gt;
if(!(pb->flags&FLAGS_LOCAL)) {
owner = pb->id%(lt+gt+1);
if(owner==lt) goto make_sh_unique_mine;
if(owner>lt) --owner;
} else
owner = pb->id%(lt+gt);
/* we don't own pb->id */
if(id) id[i] = -(slong)pb->id;
pnz->flag=1;
/* we only share this id with the owner now; remove the other entries */
for(p=pb; p!=pe; ++p) if(!(p->flags&FLAGS_REMOTE) && !(owner--)) break;
if(p!=pe) *out=*p, out->flags=FLAGS_LOCAL, ++out;
continue;
make_sh_unique_mine:
/* we own pb->id */
if(out==pb) { out=pe; for(p=pb; p!=pe; ++p) p->flags=FLAGS_REMOTE; }
else for(p=pb; p!=pe; ++p) *out=*p,out->flags=FLAGS_REMOTE,++out;
}
sh->n = out - ((struct shared_id*)sh->ptr);
/* set primary_shared_id flags to match */
((struct shared_id*)sh->ptr)[sh->n].i = -(uint)1;
sarray_sort(struct shared_id,sh->ptr,sh->n, id,1, buf);
sarray_sort(struct primary_shared_id,pr->ptr,pr->n, id,1, buf);
q=pr->ptr;
for(pb=sh->ptr,e=pb+sh->n;pb!=e;pb=pe) {
uint i=pb->i;
pe=pb; while(pe->i==i) ++pe;
if(q->id!=pb->id) printf("FAIL!!!\n");
q->flag=pb->flags&FLAGS_LOCAL;
++q;
}
}
/*------------------------------------------------------------------------------
Divide lists for parallel execution
------------------------------------------------------------------------------*/
void sublist(const uint *map, uint ***slPtr) {
// Iterate over array and count items and lists
uint i,j;
int itemCount = 0, listCount = 0;
const uint *lmap = map;
while((i=*lmap++)!=-(unsigned int)1) {
listCount++;
j=*lmap++;
do {
itemCount++;
} while ((j=*lmap++)!=-(unsigned int)1);
}
// Determine number of threads and lists
int maxThreads = 1;
#ifdef _OPENMP
maxThreads = omp_get_max_threads();
#endif
int max = (maxThreads <= listCount) ? maxThreads : listCount;
if (max == 0) max = 1;
// Setup sublists
uint *subListData = tmalloc(uint, max+itemCount+2*listCount);
*slPtr = tmalloc(uint*, maxThreads);
uint **subListPtr = *slPtr;
subListData[0] = -(unsigned int)1;
subListPtr[0] = subListData;
int nextSubList = 1;
// Populate sublists
int copyItemCount = 0;
lmap = map;
while((i=*lmap++)!=-(unsigned int)1) {
*subListData++ = i;
j=*lmap++;
do {
*subListData++ = j;
copyItemCount++;
} while ((j=*lmap++)!=-(unsigned int)1);
*subListData++ = -(unsigned int) 1;
if ( copyItemCount*max >= itemCount*nextSubList ) {
*subListData= -(unsigned int)1;
if (copyItemCount != itemCount) {
subListData++;
subListPtr[nextSubList] = subListData;
nextSubList++;
}
}
}
// Terminate unused sublists
for (; nextSubList < maxThreads; nextSubList++) {
subListPtr[nextSubList] = subListData;
}
return;
}
void subflagged(const uint *map, uint ***slPtr) {
// Iterate over map and count items
int count = 0;
const uint *lmap = map;
while(*lmap++ !=-(unsigned int)1) count++;
// Determine number of threads and sublists
int maxThreads = 1;
#ifdef _OPENMP
maxThreads = omp_get_max_threads();
#endif
int maxLists = (maxThreads <= count) ? maxThreads : count;
if (maxLists == 0) maxLists = 1;
// Setup empty sublists
uint *subFlaggedData = tmalloc(uint, maxLists+count);
*slPtr = tmalloc(uint*, maxThreads);
subFlaggedData[0] = -(unsigned int)1;
(*slPtr)[0] = subFlaggedData;
int nextList = 1;
// Populate sublists
int copyCount=0;
uint i;
lmap = map;
while((i=*lmap++)!=-(unsigned int)1) {
*subFlaggedData++ = i;
copyCount++;
if (copyCount*maxLists >= count*nextList) {
*subFlaggedData = -(unsigned int)1;
if (copyCount != count) {
subFlaggedData++;
(*slPtr)[nextList] = subFlaggedData;
nextList++;
}
}
}
// Terminate unused sublists
for (; nextList < maxThreads; nextList++) {
(*slPtr)[nextList] = subFlaggedData;
}
return;
}
/*------------------------------------------------------------------------------
Local setup
------------------------------------------------------------------------------*/
/* assumes nz is sorted by primary, then flag, then index */
static const uint *local_map(const struct array *nz, const int ignore_flagged)
{
uint *map, *p, count = 1;
const struct nonzero_id *row, *other, *end;
#define DO_COUNT(cond) do \
for(row=nz->ptr,end=row+nz->n;row!=end;) { \
ulong row_id = row->id; int any=0; \
for(other=row+1;other!=end&&other->id==row_id&&cond;++other) \
any=2, ++count; \
count+=any, row=other; \
} while(0)
if(ignore_flagged) DO_COUNT(other->flag==0); else DO_COUNT(1);
#undef DO_COUNT
p = map = tmalloc(uint,count);
#define DO_SET(cond) do \
for(row=nz->ptr,end=row+nz->n;row!=end;) { \
ulong row_id = row->id; int any=0; \
*p++ = row->i; \
for(other=row+1;other!=end&&other->id==row_id&&cond;++other) \
any=1, *p++ = other->i; \
if(any) *p++ = -(uint)1; else --p; \
row=other; \
} while(0)
if(ignore_flagged) DO_SET(other->flag==0); else DO_SET(1);
#undef DO_SET
*p = -(uint)1;
return map;
}
static const uint *flagged_primaries_map(const struct array *nz)
{
uint *map, *p, count=1;
const struct nonzero_id *row, *end;
for(row=nz->ptr,end=row+nz->n;row!=end;++row)
if(row->i==row->primary && row->flag==1) ++count;
p = map = tmalloc(uint,count);
for(row=nz->ptr,end=row+nz->n;row!=end;++row)
if(row->i==row->primary && row->flag==1) *p++ = row->i;
*p = -(uint)1;
return map;
}
/*------------------------------------------------------------------------------
Remote execution and setup
------------------------------------------------------------------------------*/
typedef void exec_fun(
void *data, gs_mode mode, unsigned vn, gs_dom dom, gs_op op,
unsigned transpose, const void *execdata, const struct comm *comm, char *buf);
typedef void fin_fun(void *data);
struct gs_remote {
uint buffer_size;
void *data;
exec_fun *exec;
fin_fun *fin;
};
typedef void setup_fun(struct gs_remote *r, struct gs_topology *top,
const struct comm *comm, buffer *buf);
/*------------------------------------------------------------------------------
Pairwise Execution
------------------------------------------------------------------------------*/
struct pw_comm_data {
uint n; /* number of messages */
uint *p; /* message source/dest proc */
uint *size; /* size of message */
uint total; /* sum of message sizes */
size_t *offsets;
};
struct pw_data {
struct pw_comm_data comm[2];
const uint *map[2];
comm_req *req;
uint buffer_size;
uint **submap[2];
};
static char *pw_exec_recvs(char *buf, const unsigned unit_size,
const struct comm *comm,
const struct pw_comm_data *c, comm_req *req)
{
const uint *p=c->p, *size=c->size;
int i;
char *retVal = buf;
#ifdef MPITHREADS
#pragma omp for
#endif
for (i = 0; i < c->n; i++) {
comm_irecv(&(req[i]),comm,buf+c->offsets[i]*unit_size,size[i]*unit_size,p[i],p[i]);
}
if (c->n != 0) {
retVal += c->offsets[c->n-1]*unit_size + size[c->n-1]*unit_size;
}
return retVal;
}
static char *pw_exec_sends(char *buf, const unsigned unit_size,
const struct comm *comm,
const struct pw_comm_data *c, comm_req *req)
{
const uint *p=c->p, *size=c->size;
int i;
char *retVal = buf;
#ifdef MPITHREADS
#pragma omp for
#endif
for(i = 0; i < c->n; i++) {
comm_isend(&(req[i]),comm,buf+c->offsets[i]*unit_size,size[i]*unit_size,p[i],comm->id);
}
if (c->n != 0) {
retVal += c->offsets[c->n-1]*unit_size + size[c->n-1]*unit_size;
}
return retVal;
}
static void pw_exec(
void *data, gs_mode mode, unsigned vn, gs_dom dom, gs_op op,
unsigned transpose, const void *execdata, const struct comm *comm, char *buf)
{
const struct pw_data *pwd = execdata;
static gs_scatter_fun *const scatter_to_buf[] =
{ &gs_scatter, &gs_scatter_vec, &gs_scatter_many_to_vec, &scatter_noop };
static gs_gather_fun *const gather_from_buf[] =
{ &gs_gather, &gs_gather_vec, &gs_gather_vec_to_many, &gather_noop };
const unsigned recv = 0^transpose, send = 1^transpose;
unsigned unit_size = vn*gs_dom_size[dom];
#ifdef MPITHREADS
char *sendbuf;
#else
static char *sendbuf;
#endif
int thd = 0;
int inp = 0;
#ifdef _OPENMP
thd = omp_get_thread_num();
inp = omp_in_parallel();
#endif
if (inp) {
/* post receives */
#ifndef MPITHREADS
#pragma omp master
#endif
{
sendbuf = pw_exec_recvs(buf,unit_size,comm,&pwd->comm[recv],pwd->req);
}
#pragma omp barrier
/* fill send buffer */
scatter_to_buf[mode](sendbuf,data,vn,(pwd->submap[send])[thd],dom);
#pragma omp barrier
/* post sends */
#ifndef MPITHREADS
#pragma omp master
#endif
{
pw_exec_sends(sendbuf,unit_size,comm,&pwd->comm[send],
&pwd->req[pwd->comm[recv].n]);
}
#pragma omp barrier
#pragma omp master
{
comm_wait(pwd->req,pwd->comm[0].n+pwd->comm[1].n);
}
#pragma omp barrier
/* gather using recv buffer */
gather_from_buf[mode](data,buf,vn,(pwd->submap[recv])[thd],dom,op);
} else {
/* post receives */
sendbuf = pw_exec_recvs(buf,unit_size,comm,&pwd->comm[recv],pwd->req);
/* fill send buffer */
scatter_to_buf[mode](sendbuf,data,vn,pwd->map[send],dom);
/* post sends */
pw_exec_sends(sendbuf,unit_size,comm,&pwd->comm[send],
&pwd->req[pwd->comm[recv].n]);
comm_wait(pwd->req,pwd->comm[0].n+pwd->comm[1].n);
/* gather using recv buffer */
gather_from_buf[mode](data,buf,vn,pwd->map[recv],dom,op);
}
}
/*------------------------------------------------------------------------------
Pairwise setup
------------------------------------------------------------------------------*/
static void pw_comm_setup(struct pw_comm_data *data, struct array *sh,
const unsigned flags_mask, buffer *buf)
{
uint n=0,count=0, lp=-(uint)1;
struct shared_id *s, *se;
/* sort by remote processor and id (a globally consistent ordering) */
sarray_sort_2(struct shared_id,sh->ptr,sh->n, p,0, id,1, buf);
/* assign index into buffer */
for(s=sh->ptr,se=s+sh->n;s!=se;++s) {
if(s->flags&flags_mask) { s->bi = -(uint)1; continue; }
s->bi = count++;
if(s->p!=lp) lp=s->p, ++n;
}
data->n = n;
data->p = tmalloc(uint,2*n);
data->size = data->p + n;
data->total = count;
n = 0, lp=-(uint)1;
for(s=sh->ptr,se=s+sh->n;s!=se;++s) {
if(s->flags&flags_mask) continue;
if(s->p!=lp) {
lp=s->p;
if(n!=0) data->size[n-1] = count;
count=0, data->p[n++]=lp;
}
++count;
}
if(n!=0) data->size[n-1] = count;
data->offsets = malloc(sizeof(size_t)*data->n);
int i;
size_t len = 0;
for (i = 0; i < data->n; i++) {
data->offsets[i] = len;
len += data->size[i];
}
}
static void pw_comm_free(struct pw_comm_data *data) { free(data->p); free(data->offsets);}
/* assumes that the bi field of sh is set */
static const uint *pw_map_setup(struct array *sh, buffer *buf)
{
uint count=0, *map, *p;
struct shared_id *s, *se;
sarray_sort(struct shared_id,sh->ptr,sh->n, i,0, buf);
/* calculate map size */
count=1;
for(s=sh->ptr,se=s+sh->n;s!=se;) {
uint i=s->i;
if(s->bi==-(uint)1) { ++s; continue; }
count+=3;
for(++s;s!=se&&s->i==i;++s) if(s->bi!=-(uint)1) ++count;
}
/* write map */
p = map = tmalloc(uint,count);
for(s=sh->ptr,se=s+sh->n;s!=se;) {
uint i=s->i;
if(s->bi==-(uint)1) { ++s; continue; }
*p++ = i, *p++ = s->bi;
for(++s;s!=se&&s->i==i;++s) if(s->bi!=-(uint)1) *p++ = s->bi;
*p++ = -(uint)1;
}
*p = -(uint)1;
return map;
}
static struct pw_data *pw_setup_aux(struct array *sh, buffer *buf)
{
struct pw_data *pwd = tmalloc(struct pw_data,1);
/* default behavior: receive only remotely unflagged data */
pw_comm_setup(&pwd->comm[0],sh, FLAGS_REMOTE, buf);
pwd->map[0] = pw_map_setup(sh, buf);
sublist(pwd->map[0], &(pwd->submap[0]));
/* default behavior: send only locally unflagged data */
pw_comm_setup(&pwd->comm[1],sh, FLAGS_LOCAL, buf);
pwd->map[1] = pw_map_setup(sh, buf);
sublist(pwd->map[1], &(pwd->submap[1]));
pwd->req = tmalloc(comm_req,pwd->comm[0].n+pwd->comm[1].n);
pwd->buffer_size = pwd->comm[0].total + pwd->comm[1].total;
return pwd;
}
static void pw_free(struct pw_data *data)
{
pw_comm_free(&data->comm[0]);
pw_comm_free(&data->comm[1]);
free((uint*)data->map[0]);
free((uint*)data->map[1]);
free(data->req);
free(data);
free((data->submap[0])[0]);
free(data->submap[0]);
free((data->submap[1])[0]);
free(data->submap[1]);
}
static void pw_setup(struct gs_remote *r, struct gs_topology *top,
const struct comm *comm, buffer *buf)
{
struct pw_data *pwd = pw_setup_aux(&top->sh,buf);
r->buffer_size = pwd->buffer_size;
r->data = pwd;
r->exec = (exec_fun*)&pw_exec;
r->fin = (fin_fun*)&pw_free;
}
/*------------------------------------------------------------------------------
Crystal-Router Execution
------------------------------------------------------------------------------*/
struct cr_stage {
const uint *scatter_map, *gather_map;
uint size_r, size_r1, size_r2;
uint size_sk, size_s, size_total;
uint p1, p2;
unsigned nrecvn;
};
struct cr_data {
struct cr_stage *stage[2];
unsigned nstages;
uint buffer_size, stage_buffer_size;
};
static void cr_exec(
void *data, gs_mode mode, unsigned vn, gs_dom dom, gs_op op,
unsigned transpose, const void *execdata, const struct comm *comm, char *buf)
{
const struct cr_data *crd = execdata;
static gs_scatter_fun *const scatter_user_to_buf[] =
{ &gs_scatter, &gs_scatter_vec, &gs_scatter_many_to_vec, &scatter_noop };
static gs_scatter_fun *const scatter_buf_to_buf[] =
{ &gs_scatter, &gs_scatter_vec, &gs_scatter_vec, &gs_scatter };
static gs_scatter_fun *const scatter_buf_to_user[] =
{ &gs_scatter, &gs_scatter_vec, &gs_scatter_vec_to_many, &scatter_noop };
static gs_gather_fun *const gather_buf_to_user[] =
{ &gs_gather, &gs_gather_vec, &gs_gather_vec_to_many, &gather_noop };
static gs_gather_fun *const gather_buf_to_buf[] =
{ &gs_gather, &gs_gather_vec, &gs_gather_vec, &gs_gather };
const unsigned unit_size = vn*gs_dom_size[dom], nstages=crd->nstages;
unsigned k;
char *sendbuf, *buf_old, *buf_new;
const struct cr_stage *stage = crd->stage[transpose];
buf_old = buf;
buf_new = buf_old + unit_size*crd->stage_buffer_size;
/* crystal router */
for(k=0;k<nstages;++k) {
comm_req req[3];
if(stage[k].nrecvn)
comm_irecv(&req[1],comm,buf_new,unit_size*stage[k].size_r1,
stage[k].p1, comm->np+k);
if(stage[k].nrecvn==2)
comm_irecv(&req[2],comm,buf_new+unit_size*stage[k].size_r1,
unit_size*stage[k].size_r2, stage[k].p2, comm->np+k);
sendbuf = buf_new+unit_size*stage[k].size_r;
if(k==0)
scatter_user_to_buf[mode](sendbuf,data,vn,stage[0].scatter_map,dom);
else
scatter_buf_to_buf[mode](sendbuf,buf_old,vn,stage[k].scatter_map,dom),
gather_buf_to_buf [mode](sendbuf,buf_old,vn,stage[k].gather_map ,dom,op);
comm_isend(&req[0],comm,sendbuf,unit_size*stage[k].size_s,
stage[k].p1, comm->np+k);
comm_wait(&req[0],1+stage[k].nrecvn);
{ char *t = buf_old; buf_old=buf_new; buf_new=t; }
}
scatter_buf_to_user[mode](data,buf_old,vn,stage[k].scatter_map,dom);
gather_buf_to_user [mode](data,buf_old,vn,stage[k].gather_map ,dom,op);
}
/*------------------------------------------------------------------------------
Crystal-Router setup
------------------------------------------------------------------------------*/
static void cr_schedule(struct cr_data *data, const struct comm *comm)
{
const uint id = comm->id;
uint bl=0, n=comm->np;
unsigned k = 0;
while(n>1) {
uint nl = (n+1)/2, bh = bl+nl;
if(id<bh) n=nl; else n-=nl,bl=bh;
++k;
}
data->nstages = k;
data->stage[0] = tmalloc(struct cr_stage,2*(k+1));
data->stage[1] = data->stage[0] + (k+1);
bl=0, n=comm->np, k=0;
while(n>1) {
uint nl = (n+1)/2, bh = bl+nl;
uint targ; unsigned recvn;
recvn = 1, targ = n-1-(id-bl)+bl;
if(id==targ) targ=bh, recvn=0;
if(n&1 && id==bh) recvn=2;
data->stage[1][k].nrecvn=data->stage[0][k].nrecvn=recvn;
data->stage[1][k].p1 =data->stage[0][k].p1 =targ;
data->stage[1][k].p2 =data->stage[0][k].p2 =comm->id-1;
if(id<bh) n=nl; else n-=nl,bl=bh;
++k;
}
}
struct crl_id {
ulong id; uint p, ri, si, bi, send;
};
/* assumes sh is grouped by i (e.g., sorted by i or by id) */
static void crl_work_init(struct array *cw, struct array *sh,
const unsigned send_mask, uint this_p)
{
const unsigned recv_mask = send_mask^(FLAGS_REMOTE|FLAGS_LOCAL);
uint last_i=-(uint)1; int added_myself;
uint cw_n = 0, cw_max = cw->max;
struct crl_id *w = cw->ptr;
struct shared_id *s, *se;
#define CW_ADD(aid,ap,ari,asi) do { \
if(cw_n==cw_max) \
array_reserve(struct crl_id,cw,cw_n+1),cw_max=cw->max, \
w=(struct crl_id*)cw->ptr+cw_n; \
w->id=aid, w->p=ap, w->ri=ari, w->si=asi; \
++w, ++cw_n; \
} while(0)
for(s=sh->ptr,se=s+sh->n;s!=se;++s) {
int send = (s->flags&send_mask)==0;
int recv = (s->flags&recv_mask)==0;
if(s->i!=last_i) last_i=s->i, added_myself=0;
if(!added_myself && recv && (s->flags&FLAGS_LOCAL)==0) {
added_myself=1;
CW_ADD(s->id,this_p,s->i,s->i);
}
if(send) CW_ADD(s->id,s->p,s->ri,s->i);
}
cw->n=cw_n;
#undef CW_ADD
}
static void crl_maps(struct cr_stage *stage, struct array *cw, buffer *buf)
{
struct crl_id *w, *we, *other;
uint scount=1, gcount=1, *sp, *gp;
sarray_sort_2(struct crl_id,cw->ptr,cw->n, bi,0, si,0, buf);
for(w=cw->ptr,we=w+cw->n;w!=we;w=other) {
uint bi=w->bi,any=0,si=w->si;
scount+=3;
for(other=w+1;other!=we&&other->bi==bi;++other)
if(other->si!=si) si=other->si, any=2, ++gcount;
gcount+=any;
}
stage->scatter_map = sp = tmalloc(uint,scount+gcount);
stage->gather_map = gp = sp + scount;
for(w=cw->ptr,we=w+cw->n;w!=we;w=other) {
uint bi=w->bi,any=0,si=w->si;
*sp++ = w->si, *sp++ = bi;
*gp++ = bi;
for(other=w+1;other!=we&&other->bi==bi;++other)
if(other->si!=si) si=other->si, any=1, *gp++ = si;
if(any) *gp++ = -(uint)1; else --gp;
*sp++ = -(uint)1;
}
*sp=-(uint)1, *gp=-(uint)1;
}
static uint crl_work_label(struct array *cw, struct cr_stage *stage,
uint cutoff, int send_hi, buffer *buf)
{
struct crl_id *w, *we, *start;
uint nsend, nkeep = 0, nks = 0, bi=0;
/* here w->send has a reverse meaning */
if(send_hi) for(w=cw->ptr,we=w+cw->n;w!=we;++w) w->send = w->p< cutoff;
else for(w=cw->ptr,we=w+cw->n;w!=we;++w) w->send = w->p>=cutoff;
sarray_sort_2(struct crl_id,cw->ptr,cw->n, id,1, send,0, buf);
for(start=cw->ptr,w=start,we=w+cw->n;w!=we;++w) {
nkeep += w->send;
if(w->id!=start->id) start=w;
if(w->send!=start->send) w->send=0,w->bi=1, ++nks; else w->bi=0;
}
nsend = cw->n-nkeep;
/* assign indices; sent ids have priority (hence w->send is reversed) */
sarray_sort(struct crl_id,cw->ptr,cw->n, send,0, buf);
for(start=cw->ptr,w=start,we=w+nsend+nks;w!=we;++w) {
if(w->id!=start->id) start=w, ++bi;
if(w->bi!=1) w->send=1; /* switch back to the usual semantics */
w->bi = bi;
}
stage->size_s = nsend+nks==0 ? 0 : bi+1;
for(we=(struct crl_id*)cw->ptr+cw->n;w!=we;++w) {
if(w->id!=start->id) start=w, ++bi;
w->send = 0; /* switch back to the usual semantics */
w->bi = bi;
}
stage->size_sk = cw->n==0 ? 0 : bi+1;
crl_maps(stage,cw,buf);
return nsend;
}
static void crl_bi_to_si(struct crl_id *w, uint n, uint v) {
for(;n;--n) w->si=w->bi+v, ++w;
}
static void crl_ri_to_bi(struct crl_id *w, uint n) {
for(;n;--n) w->bi=w->ri, ++w;
}
static uint cr_learn(struct array *cw, struct cr_stage *stage,
const struct comm *comm, buffer *buf)
{
comm_req req[3];
const uint id = comm->id;
uint bl=0, n=comm->np;
uint size_max=0;
uint tag = comm->np;
while(n>1) {
uint nl = (n+1)/2, bh = bl+nl;
uint nkeep, nsend[2], nrecv[2][2] = {{0,0},{0,0}};
struct crl_id *wrecv[2], *wsend;
nsend[0] = crl_work_label(cw,stage,bh,id<bh,buf);
nsend[1] = stage->size_s;
nkeep = cw->n - nsend[0];
if(stage->nrecvn ) comm_irecv(&req[1],comm,nrecv[0],2*sizeof(uint),
stage->p1,tag);
if(stage->nrecvn==2) comm_irecv(&req[2],comm,nrecv[1],2*sizeof(uint),
stage->p2,tag);
comm_isend(&req[0],comm,nsend,2*sizeof(uint),stage->p1,tag);
comm_wait(req,1+stage->nrecvn),++tag;
stage->size_r1 = nrecv[0][1], stage->size_r2 = nrecv[1][1];
stage->size_r = stage->size_r1 + stage->size_r2;
stage->size_total = stage->size_r + stage->size_sk;
if(stage->size_total>size_max) size_max=stage->size_total;
array_reserve(struct crl_id,cw,cw->n+nrecv[0][0]+nrecv[1][0]);
wrecv[0] = cw->ptr, wrecv[0] += cw->n, wrecv[1] = wrecv[0]+nrecv[0][0];
wsend = cw->ptr, wsend += nkeep;
if(stage->nrecvn )
comm_irecv(&req[1],comm,wrecv[0],nrecv[0][0]*sizeof(struct crl_id),
stage->p1,tag);
if(stage->nrecvn==2)
comm_irecv(&req[2],comm,wrecv[1],nrecv[1][0]*sizeof(struct crl_id),
stage->p2,tag);
sarray_sort_2(struct crl_id,cw->ptr,cw->n, send,0, bi,0, buf);
comm_isend(&req[0],comm,wsend,nsend[0]*sizeof(struct crl_id),stage->p1,tag);
comm_wait(req,1+stage->nrecvn),++tag;
crl_bi_to_si(cw->ptr,nkeep,stage->size_r);
if(stage->nrecvn) crl_bi_to_si(wrecv[0],nrecv[0][0],0);
if(stage->nrecvn==2) crl_bi_to_si(wrecv[1],nrecv[1][0],stage->size_r1);
memmove(wsend,wrecv[0],(nrecv[0][0]+nrecv[1][0])*sizeof(struct crl_id));
cw->n += nrecv[0][0] + nrecv[1][0];
cw->n -= nsend[0];
if(id<bh) n=nl; else n-=nl,bl=bh;
++stage;
}
crl_ri_to_bi(cw->ptr,cw->n);
crl_maps(stage,cw,buf);
return size_max;
}
static struct cr_data *cr_setup_aux(
struct array *sh, const struct comm *comm, buffer *buf)
{
uint size_max[2];
struct array cw = null_array;
struct cr_data *crd = tmalloc(struct cr_data,1);
/* default behavior: receive only remotely unflagged data */
/* default behavior: send only locally unflagged data */
cr_schedule(crd,comm);
sarray_sort(struct shared_id,sh->ptr,sh->n, i,0, buf);
crl_work_init(&cw,sh, FLAGS_LOCAL , comm->id);
size_max[0]=cr_learn(&cw,crd->stage[0],comm,buf);
crl_work_init(&cw,sh, FLAGS_REMOTE, comm->id);
size_max[1]=cr_learn(&cw,crd->stage[1],comm,buf);
crd->stage_buffer_size = size_max[1]>size_max[0]?size_max[1]:size_max[0];
array_free(&cw);
crd->buffer_size = 2*crd->stage_buffer_size;
return crd;
}
static void cr_free_stage_maps(struct cr_stage *stage, unsigned kmax)
{
unsigned k;
for(k=0; k<kmax; ++k) {
free((uint*)stage->scatter_map);
++stage;
}
free((uint*)stage->scatter_map);
}
static void cr_free(struct cr_data *data)
{
cr_free_stage_maps(data->stage[0],data->nstages);
cr_free_stage_maps(data->stage[1],data->nstages);
free(data->stage[0]);
free(data);
}
static void cr_setup(struct gs_remote *r, struct gs_topology *top,
const struct comm *comm, buffer *buf)
{
struct cr_data *crd = cr_setup_aux(&top->sh,comm,buf);
r->buffer_size = crd->buffer_size;
r->data = crd;
r->exec = (exec_fun*)&cr_exec;
r->fin = (fin_fun*)&cr_free;
}
/*------------------------------------------------------------------------------
All-reduce Execution
------------------------------------------------------------------------------*/
struct allreduce_data {
const uint *map_to_buf[2], *map_from_buf[2];
uint buffer_size;
};
static void allreduce_exec(
void *data, gs_mode mode, unsigned vn, gs_dom dom, gs_op op,
unsigned transpose, const void *execdata, const struct comm *comm, char *buf)
{
const struct allreduce_data *ard = execdata;
static gs_scatter_fun *const scatter_to_buf[] =
{ &gs_scatter, &gs_scatter_vec, &gs_scatter_many_to_vec, &scatter_noop };
static gs_scatter_fun *const scatter_from_buf[] =
{ &gs_scatter, &gs_scatter_vec, &gs_scatter_vec_to_many, &scatter_noop };
uint gvn = vn*(ard->buffer_size/2);
unsigned unit_size = gs_dom_size[dom];
char *ardbuf;
ardbuf = buf+unit_size*gvn;
/* user array -> buffer */
gs_init_array(buf,gvn,dom,op);
scatter_to_buf[mode](buf,data,vn,ard->map_to_buf[transpose],dom);
/* all reduce */
comm_allreduce(comm,dom,op, buf,gvn, ardbuf);
/* buffer -> user array */
scatter_from_buf[mode](data,buf,vn,ard->map_from_buf[transpose],dom);
}
/*------------------------------------------------------------------------------
All-reduce setup
------------------------------------------------------------------------------*/
static const uint *allreduce_map_setup(
struct array *pr, const unsigned flags_mask, int to_buf)
{
struct primary_shared_id *p, *pe;
uint count=1, *map, *m;
for(p=pr->ptr,pe=p+pr->n;p!=pe;++p)
if((p->flag&flags_mask)==0) count+=3;
m=map=tmalloc(uint,count);
if(to_buf) {
for(p=pr->ptr,pe=p+pr->n;p!=pe;++p)
if((p->flag&flags_mask)==0)
*m++ = p->i, *m++ = p->ord, *m++ = -(uint)1;
} else {
for(p=pr->ptr,pe=p+pr->n;p!=pe;++p)
if((p->flag&flags_mask)==0)
*m++ = p->ord, *m++ = p->i, *m++ = -(uint)1;
}
*m=-(uint)1;
return map;
}
static struct allreduce_data *allreduce_setup_aux(
struct array *pr, ulong total_shared)
{
struct allreduce_data *ard = tmalloc(struct allreduce_data,1);
/* default behavior: reduce only unflagged data, copy to all */
ard->map_to_buf [0] = allreduce_map_setup(pr,1,1);
ard->map_from_buf[0] = allreduce_map_setup(pr,0,0);
/* transpose behavior: reduce all data, copy to unflagged */
ard->map_to_buf [1] = allreduce_map_setup(pr,0,1);
ard->map_from_buf[1] = allreduce_map_setup(pr,1,0);
ard->buffer_size = total_shared*2;
return ard;
}
static void allreduce_free(struct allreduce_data *ard)
{
free((uint*)ard->map_to_buf[0]);
free((uint*)ard->map_to_buf[1]);
free((uint*)ard->map_from_buf[0]);
free((uint*)ard->map_from_buf[1]);
free(ard);
}
static void allreduce_setup(struct gs_remote *r, struct gs_topology *top,
const struct comm *comm, buffer *buf)
{
struct allreduce_data *ard = allreduce_setup_aux(&top->pr,top->total_shared);
r->buffer_size = ard->buffer_size;
r->data = ard;
r->exec = (exec_fun*)&allreduce_exec;
r->fin = (fin_fun*)&allreduce_free;
}
/*------------------------------------------------------------------------------
Automatic Setup --- dynamically picks the fastest method
------------------------------------------------------------------------------*/
static void dry_run_time(double times[3], const struct gs_remote *r,
const struct comm *comm, buffer *buf)
{
int i; double t;
buffer_reserve(buf,gs_dom_size[gs_double]*r->buffer_size);
for(i= 2;i;--i)
r->exec(0,mode_dry_run,1,gs_double,gs_add,0,r->data,comm,buf->ptr);
comm_barrier(comm);
t = comm_time();
for(i=10;i;--i)
r->exec(0,mode_dry_run,1,gs_double,gs_add,0,r->data,comm,buf->ptr);
t = (comm_time() - t)/10;
times[0] = t/comm->np, times[1] = t, times[2] = t;
comm_allreduce(comm,gs_double,gs_add, ×[0],1, &t);
comm_allreduce(comm,gs_double,gs_min, ×[1],1, &t);
comm_allreduce(comm,gs_double,gs_max, ×[2],1, &t);
}
static void auto_setup(struct gs_remote *r, struct gs_topology *top,
const struct comm *comm, buffer *buf)
{
pw_setup(r, top,comm,buf);
if(comm->np>1) {
const char *name = "pairwise";
struct gs_remote r_alt;
double time[2][3];
#define DRY_RUN(i,gsr,str) do { \
if(comm->id==0) printf(" " str ": "); \
dry_run_time(time[i],gsr,comm,buf); \
if(comm->id==0) \
printf("%g %g %g\n",time[i][0],time[i][1],time[i][2]); \
} while(0)
#define DRY_RUN_CHECK(str,new_name) do { \
DRY_RUN(1,&r_alt,str); \
if(time[1][2]<time[0][2]) \
time[0][2]=time[1][2], name=new_name, \
r->fin(r->data), *r = r_alt; \
else \
r_alt.fin(r_alt.data); \
} while(0)
DRY_RUN(0, r, "pairwise times (avg, min, max)");
cr_setup(&r_alt, top,comm,buf);
DRY_RUN_CHECK( "crystal router ", "crystal router");
if(top->total_shared<100000) {
allreduce_setup(&r_alt, top,comm,buf);
DRY_RUN_CHECK( "all reduce ", "allreduce");
}
#undef DRY_RUN_CHECK
#undef DRY_RUN
if(comm->id==0) printf(" used all_to_all method: %s\n",name);
}
}
/*------------------------------------------------------------------------------
Main Execution
------------------------------------------------------------------------------*/
struct gs_data {
struct comm comm;
const uint *map_local[2]; /* 0=unflagged, 1=all */
const uint *flagged_primaries;
struct gs_remote r;
uint **submap_local[2]; /* 0=unflagged, 1=all */
uint **subflagged_primaries;
};
static void gs_aux(
void *u, gs_mode mode, unsigned vn, gs_dom dom, gs_op op, unsigned transpose,
struct gs_data *gsh, buffer *buf)
{
static gs_scatter_fun *const local_scatter[] =
{ &gs_scatter, &gs_scatter_vec, &gs_scatter_many, &scatter_noop };
static gs_gather_fun *const local_gather [] =
{ &gs_gather, &gs_gather_vec, &gs_gather_many, &gather_noop };
static gs_init_fun *const init[] =
{ &gs_init, &gs_init_vec, &gs_init_many, &init_noop };
int thd = 0;
int inp = 0;
#ifdef _OPENMP
thd = omp_get_thread_num();
inp = omp_in_parallel();
#endif
if(!buf) buf = &static_buffer;
#pragma omp single
{
buffer_reserve(buf,vn*gs_dom_size[dom]*gsh->r.buffer_size);
}
if (inp) {
local_gather [mode](u,u,vn,(gsh->submap_local[0^transpose])[thd],dom,op);
#pragma omp barrier
if(transpose==0) init[mode](u,vn,(gsh->subflagged_primaries)[thd],dom,op);
#pragma omp barrier
gsh->r.exec(u,mode,vn,dom,op,transpose,gsh->r.data,&gsh->comm,buf->ptr);
#pragma omp barrier
local_scatter[mode](u,u,vn,(gsh->submap_local[1^transpose])[thd],dom);
#pragma omp barrier
} else {
local_gather [mode](u,u,vn,gsh->map_local[0^transpose],dom,op);
if(transpose==0) init[mode](u,vn,gsh->flagged_primaries,dom,op);
gsh->r.exec(u,mode,vn,dom,op,transpose,gsh->r.data,&gsh->comm,buf->ptr);
local_scatter[mode](u,u,vn,gsh->map_local[1^transpose],dom);
}
}
void gs(void *u, gs_dom dom, gs_op op, unsigned transpose,
struct gs_data *gsh, buffer *buf)
{
gs_aux(u,mode_plain,1,dom,op,transpose,gsh,buf);
}
void gs_vec(void *u, unsigned vn, gs_dom dom, gs_op op,
unsigned transpose, struct gs_data *gsh, buffer *buf)
{
gs_aux(u,mode_vec,vn,dom,op,transpose,gsh,buf);
}
void gs_many(void *const*u, unsigned vn, gs_dom dom, gs_op op,
unsigned transpose, struct gs_data *gsh, buffer *buf)
{
gs_aux((void*)u,mode_many,vn,dom,op,transpose,gsh,buf);
}
/*------------------------------------------------------------------------------
Main Setup
------------------------------------------------------------------------------*/
typedef enum { gs_pairwise, gs_crystal_router, gs_all_reduce,
gs_auto } gs_method;
static void local_setup(struct gs_data *gsh, const struct array *nz)
{
gsh->map_local[0] = local_map(nz,1);
gsh->map_local[1] = local_map(nz,0);
gsh->flagged_primaries = flagged_primaries_map(nz);
sublist(gsh->map_local[0], &(gsh->submap_local[0]));
sublist(gsh->map_local[1], &(gsh->submap_local[1]));
subflagged(gsh->flagged_primaries, &(gsh->subflagged_primaries));
}
static void gs_setup_aux(struct gs_data *gsh, const slong *id, uint n,
int unique, gs_method method, int verbose)
{
static setup_fun *const remote_setup[] =
{ &pw_setup, &cr_setup, &allreduce_setup, &auto_setup };
struct gs_topology top;
struct crystal cr;
crystal_init(&cr,&gsh->comm);
get_topology(&top, id,n, &cr);
if(unique) make_topology_unique(&top,0,gsh->comm.id,&cr.data);
local_setup(gsh,&top.nz);
if(verbose && gsh->comm.id==0)
printf("gs_setup: %ld unique labels shared\n",(long)top.total_shared);
remote_setup[method](&gsh->r, &top,&gsh->comm,&cr.data);
gs_topology_free(&top);
crystal_free(&cr);
}
struct gs_data *gs_setup(const slong *id, uint n, const struct comm *comm,
int unique, gs_method method, int verbose)
{
struct gs_data *gsh = tmalloc(struct gs_data,1);
comm_dup(&gsh->comm,comm);
gs_setup_aux(gsh,id,n,unique,method,verbose);
return gsh;
}
void gs_free(struct gs_data *gsh)
{
comm_free(&gsh->comm);
free((uint*)gsh->map_local[0]), free((uint*)gsh->map_local[1]);
free((uint*)gsh->flagged_primaries);
gsh->r.fin(gsh->r.data);
free((gsh->submap_local[0])[0]);
free(gsh->submap_local[0]);
free((gsh->submap_local[1])[0]);
free(gsh->submap_local[1]);
free((gsh->subflagged_primaries)[0]);
free(gsh->subflagged_primaries);
free(gsh);
}
void gs_unique(slong *id, uint n, const struct comm *comm)
{
struct gs_topology top;
struct crystal cr;
crystal_init(&cr,comm);
get_topology(&top, id,n, &cr);
make_topology_unique(&top,id,comm->id,&cr.data);
gs_topology_free(&top);
crystal_free(&cr);
}
/*------------------------------------------------------------------------------
FORTRAN interface
------------------------------------------------------------------------------*/
#undef gs_op
#undef gs_free
#undef gs_setup
#undef gs_many
#undef gs_vec
#undef gs
#define cgs PREFIXED_NAME(gs )
#define cgs_vec PREFIXED_NAME(gs_vec )
#define cgs_many PREFIXED_NAME(gs_many )
#define cgs_setup PREFIXED_NAME(gs_setup)
#define cgs_free PREFIXED_NAME(gs_free )
#define fgs_setup FORTRAN_NAME(gs_setup ,GS_SETUP )
#define fgs FORTRAN_NAME(gs_op ,GS_OP )
#define fgs_vec FORTRAN_NAME(gs_op_vec ,GS_OP_VEC )
#define fgs_many FORTRAN_NAME(gs_op_many ,GS_OP_MANY )
#define fgs_fields FORTRAN_NAME(gs_op_fields,GS_OP_FIELDS)
#define fgs_free FORTRAN_NAME(gs_free ,GS_FREE )
static struct gs_data **fgs_info = 0;
static int fgs_max = 0;
static int fgs_n = 0;
void fgs_setup(sint *handle, const slong id[], const sint *n,
const MPI_Fint *comm, const sint *np)
{
struct gs_data *gsh;
if(fgs_n==fgs_max) fgs_max+=fgs_max/2+1,
fgs_info=trealloc(struct gs_data*,fgs_info,fgs_max);
gsh=fgs_info[fgs_n]=tmalloc(struct gs_data,1);
comm_init_check(&gsh->comm,*comm,*np);
gs_setup_aux(gsh,id,*n,0,gs_pairwise,1);
*handle = fgs_n++;
}
static void fgs_check_handle(sint handle, const char *func, unsigned line)
{
if(handle<0 || handle>=fgs_n || !fgs_info[handle])
fail(1,__FILE__,line,"%s: invalid handle", func);
}
static void fgs_check_parms(sint handle, sint dom, sint op,
const char *func, unsigned line)
{
if(dom<1 || dom>4)
fail(1,__FILE__,line,"%s: datatype %d not in valid range 1-4",func,dom);
if(op <1 || op >4)
fail(1,__FILE__,line,"%s: op %d not in valid range 1-4",func,op);
fgs_check_handle(handle,func,line);
}
void fgs(const sint *handle, void *u, const sint *dom, const sint *op,
const sint *transpose)
{
fgs_check_parms(*handle,*dom,*op,"gs_op",__LINE__);
cgs(u,(gs_dom)(*dom-1),(gs_op_t)(*op-1),*transpose!=0,fgs_info[*handle],0);
}
void fgs_vec(const sint *handle, void *u, const sint *n,
const sint *dom, const sint *op, const sint *transpose)
{
fgs_check_parms(*handle,*dom,*op,"gs_op_vec",__LINE__);
cgs_vec(u,*n,(gs_dom)(*dom-1),(gs_op_t)(*op-1),*transpose!=0,
fgs_info[*handle],0);
}
void fgs_many(const sint *handle, void *u1, void *u2, void *u3,
void *u4, void *u5, void *u6, const sint *n,
const sint *dom, const sint *op, const sint *transpose)
{
void *uu[6];
uu[0]=u1,uu[1]=u2,uu[2]=u3,uu[3]=u4,uu[4]=u5,uu[5]=u6;
fgs_check_parms(*handle,*dom,*op,"gs_op_many",__LINE__);
cgs_many((void *const*)uu,*n,(gs_dom)(*dom-1),(gs_op_t)(*op-1),*transpose!=0,
fgs_info[*handle],0);
}
static struct array fgs_fields_array = null_array;
void fgs_fields(const sint *handle,
void *u, const sint *stride, const sint *n,
const sint *dom, const sint *op, const sint *transpose)
{
size_t offset;
void **p;
uint i;
fgs_check_parms(*handle,*dom,*op,"gs_op_fields",__LINE__);
if(*n<0) return;
array_reserve(void*,&fgs_fields_array,*n);
p = fgs_fields_array.ptr;
offset = *stride * gs_dom_size[*dom-1];
for(i=*n;i;--i) *p++ = u, u = (char*)u + offset;
cgs_many((void *const*)fgs_fields_array.ptr,*n,
(gs_dom)(*dom-1),(gs_op_t)(*op-1),
*transpose!=0, fgs_info[*handle],0);
}
void fgs_free(const sint *handle)
{
fgs_check_handle(*handle,"gs_free",__LINE__);
cgs_free(fgs_info[*handle]);
fgs_info[*handle] = 0;
}
|
DenseTensor.h | //=================================================================================================
/*!
// \file blaze/math/smp/openmp/DenseTensor.h
// \brief Header file for the OpenMP-based dense tensor SMP implementation
//
// Copyright (C) 2012-2018 Klaus Iglberger - All Rights Reserved
// Copyright (C) 2018 Hartmut Kaiser - All Rights Reserved
//
// This file is part of the Blaze library. You can redistribute it and/or modify it under
// the terms of the New (Revised) BSD License. Redistribution and use in source and binary
// forms, with or without modification, are permitted provided that the following conditions
// are met:
//
// 1. Redistributions of source code must retain the above copyright notice, this list of
// conditions and the following disclaimer.
// 2. Redistributions in binary form must reproduce the above copyright notice, this list
// of conditions and the following disclaimer in the documentation and/or other materials
// provided with the distribution.
// 3. Neither the names of the Blaze development group nor the names of its contributors
// may be used to endorse or promote products derived from this software without specific
// prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY
// EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
// OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT
// SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
// INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
// TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
// BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
// ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH
// DAMAGE.
*/
//=================================================================================================
#ifndef _BLAZE_TENSOR_MATH_SMP_OPENMP_DENSETENSOR_H_
#define _BLAZE_TENSOR_MATH_SMP_OPENMP_DENSETENSOR_H_
//*************************************************************************************************
// Includes
//*************************************************************************************************
#include <blaze/math/Aliases.h>
#include <blaze/math/AlignmentFlag.h>
#include <blaze/math/StorageOrder.h>
#include <blaze/math/constraints/SMPAssignable.h>
#include <blaze/math/simd/SIMDTrait.h>
#include <blaze/math/smp/ParallelSection.h>
#include <blaze/math/smp/SerialSection.h>
#include <blaze/math/smp/ThreadMapping.h>
#include <blaze/math/typetraits/IsSIMDCombinable.h>
#include <blaze/math/typetraits/IsSMPAssignable.h>
#include <blaze/math/views/Submatrix.h>
#include <blaze/system/SMP.h>
#include <blaze/util/Assert.h>
#include <blaze/util/EnableIf.h>
#include <blaze/util/FunctionTrace.h>
#include <blaze/util/StaticAssert.h>
#include <blaze/util/Types.h>
#include <blaze/util/algorithms/Min.h>
#include <omp.h>
#include <blaze_tensor/math/expressions/DenseTensor.h>
#include <blaze_tensor/math/smp/TensorThreadMapping.h>
#include <blaze_tensor/math/typetraits/IsDenseTensor.h>
#include <blaze_tensor/math/views/PageSlice.h>
namespace blaze {
//=================================================================================================
//
// OPENMP-BASED ASSIGNMENT KERNELS
//
//=================================================================================================
//*************************************************************************************************
/*! \cond BLAZE_INTERNAL */
/*!\brief Backend of the OpenMP-based SMP (compound) assignment of a dense tensor to a dense tensor.
// \ingroup math
//
// \param lhs The target left-hand side dense tensor.
// \param rhs The right-hand side dense tensor to be assigned.
// \param op The (compound) assignment operation.
// \return void
//
// This function is the backend implementation of the OpenMP-based SMP assignment of a dense
// tensor to a dense tensor.\n
// This function must \b NOT be called explicitly! It is used internally for the performance
// optimized evaluation of expression templates. Calling this function explicitly might result
// in erroneous results and/or in compilation errors. Instead of using this function use the
// assignment operator.
*/
template< typename MT1 // Type of the left-hand side dense tensor
, typename MT2 // Type of the right-hand side dense tensor
, typename OP > // Type of the assignment operation
void openmpAssign( DenseTensor<MT1>& lhs, const DenseTensor<MT2>& rhs, OP op )
{
BLAZE_FUNCTION_TRACE;
BLAZE_INTERNAL_ASSERT( isParallelSectionActive(), "Invalid call outside a parallel section" );
using ET1 = ElementType_t<MT1>;
using ET2 = ElementType_t<MT2>;
constexpr bool simdEnabled( MT1::simdEnabled && MT2::simdEnabled && IsSIMDCombinable_v<ET1,ET2> );
constexpr size_t SIMDSIZE( SIMDTrait< ElementType_t<MT1> >::size );
const bool lhsAligned( (*lhs).isAligned() );
const bool rhsAligned( (*rhs).isAligned() );
const int threads( omp_get_num_threads() );
const ThreadMapping threadmap( createThreadMapping( threads, *rhs ) );
const size_t addon1 ( ( ( (*rhs).rows() % threadmap.first ) != 0UL )? 1UL : 0UL );
const size_t equalShare1( (*rhs).rows() / threadmap.first + addon1 );
const size_t rest1 ( equalShare1 & ( SIMDSIZE - 1UL ) );
const size_t rowsPerThread( ( simdEnabled && rest1 )?( equalShare1 - rest1 + SIMDSIZE ):( equalShare1 ) );
const size_t addon2 ( ( ( (*rhs).columns() % threadmap.second ) != 0UL )? 1UL : 0UL );
const size_t equalShare2( (*rhs).columns() / threadmap.second + addon2 );
const size_t rest2 ( equalShare2 & ( SIMDSIZE - 1UL ) );
const size_t colsPerThread( ( simdEnabled && rest2 )?( equalShare2 - rest2 + SIMDSIZE ):( equalShare2 ) );
#pragma omp for schedule(dynamic,1) nowait
for( int i=0; i<threads; ++i )
{
const size_t row ( ( i / threadmap.second ) * rowsPerThread );
const size_t column( ( i % threadmap.second ) * colsPerThread );
if( row >= (*rhs).rows() || column >= (*rhs).columns() )
continue;
for (size_t k = 0; k != (*rhs).pages(); ++k)
{
const size_t m( min( rowsPerThread, (*rhs).rows() - row ) );
const size_t n( min( colsPerThread, (*rhs).columns() - column ) );
auto lhs_slice = pageslice( *lhs, k );
auto rhs_slice = pageslice( *rhs, k );
if( simdEnabled && lhsAligned && rhsAligned ) {
auto target( submatrix<aligned> ( *lhs_slice, row, column, m, n ) );
const auto source( submatrix<aligned> ( *rhs_slice, row, column, m, n ) );
op( target, source );
}
else if( simdEnabled && lhsAligned ) {
auto target( submatrix<aligned> ( *lhs_slice, row, column, m, n ) );
const auto source( submatrix<unaligned>( *rhs_slice, row, column, m, n ) );
op( target, source );
}
else if( simdEnabled && rhsAligned ) {
auto target( submatrix<unaligned>( *lhs_slice, row, column, m, n ) );
const auto source( submatrix<aligned> ( *rhs_slice, row, column, m, n ) );
op( target, source );
}
else {
auto target( submatrix<unaligned>( *lhs_slice, row, column, m, n ) );
const auto source( submatrix<unaligned>( *rhs_slice, row, column, m, n ) );
op( target, source );
}
}
}
}
/*! \endcond */
//*************************************************************************************************
//=================================================================================================
//
// PLAIN ASSIGNMENT
//
//=================================================================================================
//*************************************************************************************************
/*! \cond BLAZE_INTERNAL */
/*!\brief Default implementation of the OpenMP-based SMP assignment to a dense tensor.
// \ingroup smp
//
// \param lhs The target left-hand side dense tensor.
// \param rhs The right-hand side tensor to be assigned.
// \return void
//
// This function implements the default OpenMP-based SMP assignment to a dense tensor. Due to
// the explicit application of the SFINAE principle, this function can only be selected by the
// compiler in case both operands are SMP-assignable and the element types of both operands are
// not SMP-assignable.\n
// This function must \b NOT be called explicitly! It is used internally for the performance
// optimized evaluation of expression templates. Calling this function explicitly might result
// in erroneous results and/or in compilation errors. Instead of using this function use the
// assignment operator.
*/
template< typename MT1 // Type of the left-hand side dense tensor
, typename MT2 > // Type of the right-hand side dense tensor
inline EnableIf_t< IsDenseTensor_v<MT1> && ( !IsSMPAssignable_v<MT1> || !IsSMPAssignable_v<MT2> ) >
smpAssign( Tensor<MT1>& lhs, const Tensor<MT2>& rhs )
{
BLAZE_FUNCTION_TRACE;
BLAZE_INTERNAL_ASSERT( (*lhs).rows() == (*rhs).rows() , "Invalid number of rows" );
BLAZE_INTERNAL_ASSERT( (*lhs).columns() == (*rhs).columns(), "Invalid number of columns" );
BLAZE_INTERNAL_ASSERT( (*lhs).pages() == (*rhs).pages(), "Invalid number of pages" );
assign( *lhs, *rhs );
}
/*! \endcond */
//*************************************************************************************************
//*************************************************************************************************
/*! \cond BLAZE_INTERNAL */
/*!\brief Implementation of the OpenMP-based SMP assignment to a dense tensor.
// \ingroup math
//
// \param lhs The target left-hand side dense tensor.
// \param rhs The right-hand side tensor to be assigned.
// \return void
//
// This function implements the OpenMP-based SMP assignment to a dense tensor. Due to the
// explicit application of the SFINAE principle, this function can only be selected by the
// compiler in case both operands are SMP-assignable and the element types of both operands
// are not SMP-assignable.\n
// This function must \b NOT be called explicitly! It is used internally for the performance
// optimized evaluation of expression templates. Calling this function explicitly might result
// in erroneous results and/or in compilation errors. Instead of using this function use the
// assignment operator.
*/
template< typename MT1 // Type of the left-hand side dense tensor
, typename MT2 > // Type of the right-hand side dense tensor
inline EnableIf_t< IsDenseTensor_v<MT1> && IsSMPAssignable_v<MT1> && IsSMPAssignable_v<MT2> >
smpAssign( Tensor<MT1>& lhs, const Tensor<MT2>& rhs )
{
BLAZE_FUNCTION_TRACE;
BLAZE_CONSTRAINT_MUST_NOT_BE_SMP_ASSIGNABLE( ElementType_t<MT1> );
BLAZE_CONSTRAINT_MUST_NOT_BE_SMP_ASSIGNABLE( ElementType_t<MT2> );
BLAZE_INTERNAL_ASSERT( (*lhs).rows() == (*rhs).rows() , "Invalid number of rows" );
BLAZE_INTERNAL_ASSERT( (*lhs).columns() == (*rhs).columns(), "Invalid number of columns" );
BLAZE_INTERNAL_ASSERT( (*lhs).pages() == (*rhs).pages(), "Invalid number of pages" );
BLAZE_PARALLEL_SECTION
{
if( isSerialSectionActive() || !(*rhs).canSMPAssign() ) {
assign( *lhs, *rhs );
}
else {
#pragma omp parallel shared( lhs, rhs )
openmpAssign( *lhs, *rhs, []( auto& a, const auto& b ){ assign( a, b ); } );
}
}
}
/*! \endcond */
//*************************************************************************************************
//=================================================================================================
//
// ADDITION ASSIGNMENT
//
//=================================================================================================
//*************************************************************************************************
/*! \cond BLAZE_INTERNAL */
/*!\brief Default implementation of the OpenMP-based SMP addition assignment to a dense tensor.
// \ingroup smp
//
// \param lhs The target left-hand side dense tensor.
// \param rhs The right-hand side tensor to be added.
// \return void
//
// This function implements the default OpenMP-based SMP addition assignment to a dense tensor.
// Due to the explicit application of the SFINAE principle, this function can only be selected
// by the compiler in case both operands are SMP-assignable and the element types of both operands
// are not SMP-assignable.\n
// This function must \b NOT be called explicitly! It is used internally for the performance
// optimized evaluation of expression templates. Calling this function explicitly might result
// in erroneous results and/or in compilation errors. Instead of using this function use the
// assignment operator.
*/
template< typename MT1 // Type of the left-hand side dense tensor
, typename MT2 > // Type of the right-hand side dense tensor
inline EnableIf_t< IsDenseTensor_v<MT1> && ( !IsSMPAssignable_v<MT1> || !IsSMPAssignable_v<MT2> ) >
smpAddAssign( Tensor<MT1>& lhs, const Tensor<MT2>& rhs )
{
BLAZE_FUNCTION_TRACE;
BLAZE_INTERNAL_ASSERT( (*lhs).rows() == (*rhs).rows() , "Invalid number of rows" );
BLAZE_INTERNAL_ASSERT( (*lhs).columns() == (*rhs).columns(), "Invalid number of columns" );
BLAZE_INTERNAL_ASSERT( (*lhs).pages() == (*rhs).pages(), "Invalid number of pages" );
addAssign( *lhs, *rhs );
}
/*! \endcond */
//*************************************************************************************************
//*************************************************************************************************
/*! \cond BLAZE_INTERNAL */
/*!\brief Implementation of the OpenMP-based SMP addition assignment to a dense tensor.
// \ingroup math
//
// \param lhs The target left-hand side dense tensor.
// \param rhs The right-hand side tensor to be added.
// \return void
//
// This function implements the OpenMP-based SMP addition assignment to a dense tensor. Due to
// the explicit application of the SFINAE principle, this function can only be selected by the
// compiler in case both operands are SMP-assignable and the element types of both operands are
// not SMP-assignable.\n
// This function must \b NOT be called explicitly! It is used internally for the performance
// optimized evaluation of expression templates. Calling this function explicitly might result
// in erroneous results and/or in compilation errors. Instead of using this function use the
// assignment operator.
*/
template< typename MT1 // Type of the left-hand side dense tensor
, typename MT2 > // Type of the right-hand side dense tensor
inline EnableIf_t< IsDenseTensor_v<MT1> && IsSMPAssignable_v<MT1> && IsSMPAssignable_v<MT2> >
smpAddAssign( Tensor<MT1>& lhs, const Tensor<MT2>& rhs )
{
BLAZE_FUNCTION_TRACE;
BLAZE_CONSTRAINT_MUST_NOT_BE_SMP_ASSIGNABLE( ElementType_t<MT1> );
BLAZE_CONSTRAINT_MUST_NOT_BE_SMP_ASSIGNABLE( ElementType_t<MT2> );
BLAZE_INTERNAL_ASSERT( (*lhs).rows() == (*rhs).rows() , "Invalid number of rows" );
BLAZE_INTERNAL_ASSERT( (*lhs).columns() == (*rhs).columns(), "Invalid number of columns" );
BLAZE_INTERNAL_ASSERT( (*lhs).pages() == (*rhs).pages(), "Invalid number of pages" );
BLAZE_PARALLEL_SECTION
{
if( isSerialSectionActive() || !(*rhs).canSMPAssign() ) {
addAssign( *lhs, *rhs );
}
else {
#pragma omp parallel shared( lhs, rhs )
openmpAssign( *lhs, *rhs, []( auto& a, const auto& b ){ addAssign( a, b ); } );
}
}
}
/*! \endcond */
//*************************************************************************************************
//=================================================================================================
//
// SUBTRACTION ASSIGNMENT
//
//=================================================================================================
//*************************************************************************************************
/*! \cond BLAZE_INTERNAL */
/*!\brief Default implementation of the OpenMP-based SMP subtracction assignment to a dense tensor.
// \ingroup smp
//
// \param lhs The target left-hand side dense tensor.
// \param rhs The right-hand side tensor to be subtracted.
// \return void
//
// This function implements the default OpenMP-based SMP subtraction assignment to a dense tensor.
// Due to the explicit application of the SFINAE principle, this function can only be selected by
// the compiler in case both operands are SMP-assignable and the element types of both operands
// are not SMP-assignable.\n
// This function must \b NOT be called explicitly! It is used internally for the performance
// optimized evaluation of expression templates. Calling this function explicitly might result
// in erroneous results and/or in compilation errors. Instead of using this function use the
// assignment operator.
*/
template< typename MT1 // Type of the left-hand side dense tensor
, typename MT2 > // Type of the right-hand side dense tensor
inline EnableIf_t< IsDenseTensor_v<MT1> && ( !IsSMPAssignable_v<MT1> || !IsSMPAssignable_v<MT2> ) >
smpSubAssign( Tensor<MT1>& lhs, const Tensor<MT2>& rhs )
{
BLAZE_FUNCTION_TRACE;
BLAZE_INTERNAL_ASSERT( (*lhs).rows() == (*rhs).rows() , "Invalid number of rows" );
BLAZE_INTERNAL_ASSERT( (*lhs).columns() == (*rhs).columns(), "Invalid number of columns" );
BLAZE_INTERNAL_ASSERT( (*lhs).pages() == (*rhs).pages(), "Invalid number of pages" );
subAssign( *lhs, *rhs );
}
/*! \endcond */
//*************************************************************************************************
//*************************************************************************************************
/*! \cond BLAZE_INTERNAL */
/*!\brief Implementation of the OpenMP-based SMP subtracction assignment to a dense tensor.
// \ingroup smp
//
// \param lhs The target left-hand side dense tensor.
// \param rhs The right-hand side tensor to be subtracted.
// \return void
//
// This function implements the default OpenMP-based SMP subtraction assignment of a tensor to a
// dense tensor. Due to the explicit application of the SFINAE principle, this function can only
// be selected by the compiler in case both operands are SMP-assignable and the element types of
// both operands are not SMP-assignable.\n
// This function must \b NOT be called explicitly! It is used internally for the performance
// optimized evaluation of expression templates. Calling this function explicitly might result
// in erroneous results and/or in compilation errors. Instead of using this function use the
// assignment operator.
*/
template< typename MT1 // Type of the left-hand side dense tensor
, typename MT2 > // Type of the right-hand side dense tensor
inline EnableIf_t< IsDenseTensor_v<MT1> && IsSMPAssignable_v<MT1> && IsSMPAssignable_v<MT2> >
smpSubAssign( Tensor<MT1>& lhs, const Tensor<MT2>& rhs )
{
BLAZE_FUNCTION_TRACE;
BLAZE_CONSTRAINT_MUST_NOT_BE_SMP_ASSIGNABLE( ElementType_t<MT1> );
BLAZE_CONSTRAINT_MUST_NOT_BE_SMP_ASSIGNABLE( ElementType_t<MT2> );
BLAZE_INTERNAL_ASSERT( (*lhs).rows() == (*rhs).rows() , "Invalid number of rows" );
BLAZE_INTERNAL_ASSERT( (*lhs).columns() == (*rhs).columns(), "Invalid number of columns" );
BLAZE_INTERNAL_ASSERT( (*lhs).pages() == (*rhs).pages(), "Invalid number of pages" );
BLAZE_PARALLEL_SECTION
{
if( isSerialSectionActive() || !(*rhs).canSMPAssign() ) {
subAssign( *lhs, *rhs );
}
else {
#pragma omp parallel shared( lhs, rhs )
openmpAssign( *lhs, *rhs, []( auto& a, const auto& b ){ subAssign( a, b ); } );
}
}
}
/*! \endcond */
//*************************************************************************************************
//=================================================================================================
//
// SCHUR PRODUCT ASSIGNMENT
//
//=================================================================================================
//*************************************************************************************************
/*! \cond BLAZE_INTERNAL */
/*!\brief Default implementation of the OpenMP-based SMP Schur product assignment to a dense tensor.
// \ingroup smp
//
// \param lhs The target left-hand side dense tensor.
// \param rhs The right-hand side tensor for the Schur product.
// \return void
//
// This function implements the default OpenMP-based SMP Schur product assignment to a dense
// tensor. Due to the explicit application of the SFINAE principle, this function can only be
// selected by the compiler in case both operands are SMP-assignable and the element types of
// both operands are not SMP-assignable.\n
// This function must \b NOT be called explicitly! It is used internally for the performance
// optimized evaluation of expression templates. Calling this function explicitly might result
// in erroneous results and/or in compilation errors. Instead of using this function use the
// assignment operator.
*/
template< typename MT1 // Type of the left-hand side dense tensor
, typename MT2 > // Type of the right-hand side dense tensor
inline EnableIf_t< IsDenseTensor_v<MT1> && ( !IsSMPAssignable_v<MT1> || !IsSMPAssignable_v<MT2> ) >
smpSchurAssign( Tensor<MT1>& lhs, const Tensor<MT2>& rhs )
{
BLAZE_FUNCTION_TRACE;
BLAZE_INTERNAL_ASSERT( (*lhs).rows() == (*rhs).rows() , "Invalid number of rows" );
BLAZE_INTERNAL_ASSERT( (*lhs).columns() == (*rhs).columns(), "Invalid number of columns" );
BLAZE_INTERNAL_ASSERT( (*lhs).pages() == (*rhs).pages(), "Invalid number of pages" );
schurAssign( *lhs, *rhs );
}
/*! \endcond */
//*************************************************************************************************
//*************************************************************************************************
/*! \cond BLAZE_INTERNAL */
/*!\brief Implementation of the OpenMP-based SMP Schur product assignment to a dense tensor.
// \ingroup math
//
// \param lhs The target left-hand side dense tensor.
// \param rhs The right-hand side tensor for the Schur product.
// \return void
//
// This function implements the OpenMP-based SMP Schur product assignment to a dense tensor. Due
// to the explicit application of the SFINAE principle, this function can only be selected by the
// compiler in case both operands are SMP-assignable and the element types of both operands are
// not SMP-assignable.\n
// This function must \b NOT be called explicitly! It is used internally for the performance
// optimized evaluation of expression templates. Calling this function explicitly might result
// in erroneous results and/or in compilation errors. Instead of using this function use the
// assignment operator.
*/
template< typename MT1 // Type of the left-hand side dense tensor
, typename MT2 > // Type of the right-hand side dense tensor
inline EnableIf_t< IsDenseTensor_v<MT1> && IsSMPAssignable_v<MT1> && IsSMPAssignable_v<MT2> >
smpSchurAssign( Tensor<MT1>& lhs, const Tensor<MT2>& rhs )
{
BLAZE_FUNCTION_TRACE;
BLAZE_CONSTRAINT_MUST_NOT_BE_SMP_ASSIGNABLE( ElementType_t<MT1> );
BLAZE_CONSTRAINT_MUST_NOT_BE_SMP_ASSIGNABLE( ElementType_t<MT2> );
BLAZE_INTERNAL_ASSERT( (*lhs).rows() == (*rhs).rows() , "Invalid number of rows" );
BLAZE_INTERNAL_ASSERT( (*lhs).columns() == (*rhs).columns(), "Invalid number of columns" );
BLAZE_INTERNAL_ASSERT( (*lhs).pages() == (*rhs).pages(), "Invalid number of pages" );
BLAZE_PARALLEL_SECTION
{
if( isSerialSectionActive() || !(*rhs).canSMPAssign() ) {
schurAssign( *lhs, *rhs );
}
else {
#pragma omp parallel shared( lhs, rhs )
openmpAssign( *lhs, *rhs, []( auto& a, const auto& b ){ schurAssign( a, b ); } );
}
}
}
/*! \endcond */
//*************************************************************************************************
//=================================================================================================
//
// MULTIPLICATION ASSIGNMENT
//
//=================================================================================================
//*************************************************************************************************
/*! \cond BLAZE_INTERNAL */
/*!\brief Default implementation of the OpenMP-based SMP multiplication assignment to a dense tensor.
// \ingroup smp
//
// \param lhs The target left-hand side dense tensor.
// \param rhs The right-hand side tensor to be multiplied.
// \return void
//
// This function implements the default OpenMP-based SMP multiplication assignment to a dense
// tensor.\n
// This function must \b NOT be called explicitly! It is used internally for the performance
// optimized evaluation of expression templates. Calling this function explicitly might result
// in erroneous results and/or in compilation errors. Instead of using this function use the
// assignment operator.
*/
template< typename MT1 // Type of the left-hand side dense tensor
, typename MT2 > // Type of the right-hand side dense tensor
inline EnableIf_t< IsDenseTensor_v<MT1> >
smpMultAssign( Tensor<MT1>& lhs, const Tensor<MT2>& rhs )
{
BLAZE_FUNCTION_TRACE;
BLAZE_INTERNAL_ASSERT( (*lhs).rows() == (*rhs).rows() , "Invalid number of rows" );
BLAZE_INTERNAL_ASSERT( (*lhs).columns() == (*rhs).columns(), "Invalid number of columns" );
BLAZE_INTERNAL_ASSERT( (*lhs).pages() == (*rhs).pages(), "Invalid number of pages" );
multAssign( *lhs, *rhs );
}
/*! \endcond */
//*************************************************************************************************
//=================================================================================================
//
// COMPILE TIME CONSTRAINT
//
//=================================================================================================
//*************************************************************************************************
/*! \cond BLAZE_INTERNAL */
namespace {
BLAZE_STATIC_ASSERT( BLAZE_OPENMP_PARALLEL_MODE );
}
/*! \endcond */
//*************************************************************************************************
} // namespace blaze
#endif
|
GB_binop__ne_uint64.c | //------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2020, All Rights Reserved.
// http://suitesparse.com See GraphBLAS/Doc/License.txt for license.
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_mkl.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB_AaddB__ne_uint64
// A.*B function (eWiseMult): GB_AemultB__ne_uint64
// A*D function (colscale): GB_AxD__ne_uint64
// D*A function (rowscale): GB_DxB__ne_uint64
// C+=B function (dense accum): GB_Cdense_accumB__ne_uint64
// C+=b function (dense accum): GB_Cdense_accumb__ne_uint64
// C+=A+B function (dense ewise3): (none)
// C=A+B function (dense ewise3): GB_Cdense_ewise3_noaccum__ne_uint64
// C=scalar+B GB_bind1st__ne_uint64
// C=scalar+B' GB_bind1st_tran__ne_uint64
// C=A+scalar GB_bind2nd__ne_uint64
// C=A'+scalar GB_bind2nd_tran__ne_uint64
// C type: bool
// A type: uint64_t
// B,b type: uint64_t
// BinaryOp: cij = (aij != bij)
#define GB_ATYPE \
uint64_t
#define GB_BTYPE \
uint64_t
#define GB_CTYPE \
bool
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
0
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
0
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
uint64_t aij = Ax [pA]
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB) \
uint64_t bij = Bx [pB]
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
bool t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA) \
cij = Ax [pA]
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB) \
cij = Bx [pB]
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z, x, y) \
z = (x != y) ;
// op is second
#define GB_OP_IS_SECOND \
0
// op is plus_fp32 or plus_fp64
#define GB_OP_IS_PLUS_REAL \
0
// op is minus_fp32 or minus_fp64
#define GB_OP_IS_MINUS_REAL \
0
// GB_cblas_*axpy gateway routine, if it exists for this operator and type:
#define GB_CBLAS_AXPY \
(none)
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_NE || GxB_NO_UINT64 || GxB_NO_NE_UINT64)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
#if 0
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void (none)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
#endif
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
GrB_Info GB_Cdense_ewise3_noaccum__ne_uint64
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_dense_ewise3_noaccum_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB_Cdense_accumB__ne_uint64
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *GB_RESTRICT kfirst_slice,
const int64_t *GB_RESTRICT klast_slice,
const int64_t *GB_RESTRICT pstart_slice,
const int ntasks,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if 0
{
#include "GB_dense_subassign_23_template.c"
}
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB_Cdense_accumb__ne_uint64
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if 0
{
// get the scalar b for C += b, of type uint64_t
uint64_t bwork = (*((uint64_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB_AxD__ne_uint64
(
GrB_Matrix C,
const GrB_Matrix A, bool A_is_pattern,
const GrB_Matrix D, bool D_is_pattern,
const int64_t *GB_RESTRICT kfirst_slice,
const int64_t *GB_RESTRICT klast_slice,
const int64_t *GB_RESTRICT pstart_slice,
const int ntasks,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *GB_RESTRICT Cx = (bool *) C->x ;
#include "GB_AxB_colscale_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB_DxB__ne_uint64
(
GrB_Matrix C,
const GrB_Matrix D, bool D_is_pattern,
const GrB_Matrix B, bool B_is_pattern,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *GB_RESTRICT Cx = (bool *) C->x ;
#include "GB_AxB_rowscale_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C = A+B or C<M> = A+B
//------------------------------------------------------------------------------
GrB_Info GB_AaddB__ne_uint64
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const bool Ch_is_Mh,
const int64_t *GB_RESTRICT C_to_M,
const int64_t *GB_RESTRICT C_to_A,
const int64_t *GB_RESTRICT C_to_B,
const GB_task_struct *GB_RESTRICT TaskList,
const int ntasks,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_add_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C = A.*B or C<M> = A.*B
//------------------------------------------------------------------------------
GrB_Info GB_AemultB__ne_uint64
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *GB_RESTRICT C_to_M,
const int64_t *GB_RESTRICT C_to_A,
const int64_t *GB_RESTRICT C_to_B,
const GB_task_struct *GB_RESTRICT TaskList,
const int ntasks,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB_bind1st__ne_uint64
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *Cx = (bool *) Cx_output ;
uint64_t x = (*((uint64_t *) x_input)) ;
uint64_t *Bx = (uint64_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
uint64_t bij = Bx [p] ;
Cx [p] = (x != bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB_bind2nd__ne_uint64
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
bool *Cx = (bool *) Cx_output ;
uint64_t *Ax = (uint64_t *) Ax_input ;
uint64_t y = (*((uint64_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
uint64_t aij = Ax [p] ;
Cx [p] = (aij != y) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (x, aij), no typcasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
uint64_t aij = Ax [pA] ; \
Cx [pC] = (x != aij) ; \
}
GrB_Info GB_bind1st_tran__ne_uint64
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *GB_RESTRICT *Rowcounts,
GBI_single_iterator Iter,
const int64_t *GB_RESTRICT A_slice,
int naslice
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
uint64_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint64_t x = (*((const uint64_t *) x_input)) ;
#define GB_PHASE_2_OF_2
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
uint64_t
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typcasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
uint64_t aij = Ax [pA] ; \
Cx [pC] = (aij != y) ; \
}
GrB_Info GB_bind2nd_tran__ne_uint64
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *GB_RESTRICT *Rowcounts,
GBI_single_iterator Iter,
const int64_t *GB_RESTRICT A_slice,
int naslice
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint64_t y = (*((const uint64_t *) y_input)) ;
#define GB_PHASE_2_OF_2
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
GB_unaryop__lnot_uint64_int32.c | //------------------------------------------------------------------------------
// GB_unaryop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2019, All Rights Reserved.
// http://suitesparse.com See GraphBLAS/Doc/License.txt for license.
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_iterator.h"
#include "GB_unaryop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB_unop__lnot_uint64_int32
// op(A') function: GB_tran__lnot_uint64_int32
// C type: uint64_t
// A type: int32_t
// cast: uint64_t cij = (uint64_t) aij
// unaryop: cij = !(aij != 0)
#define GB_ATYPE \
int32_t
#define GB_CTYPE \
uint64_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
int32_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = !(x != 0) ;
// casting
#define GB_CASTING(z, x) \
uint64_t z = (uint64_t) x ;
// cij = op (cast (aij))
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GB_GETA (aij, Ax, pA) ; \
/* Cx [pC] = op (cast (aij)) */ \
GB_CASTING (x, aij) ; \
GB_OP (GB_CX (pC), x) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_LNOT || GxB_NO_UINT64 || GxB_NO_INT32)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__lnot_uint64_int32
(
uint64_t *restrict Cx,
const int32_t *restrict Ax,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (int64_t p = 0 ; p < anz ; p++)
{
GB_CAST_OP (p, p) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_tran__lnot_uint64_int32
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *restrict *Rowcounts,
GBI_single_iterator Iter,
const int64_t *restrict A_slice,
int naslice
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#define GB_PHASE_2_OF_2
#include "GB_unaryop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
GB_binop__ne_fc32.c |
//------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_emult.h"
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB (_AaddB__ne_fc32)
// A.*B function (eWiseMult): GB (_AemultB_08__ne_fc32)
// A.*B function (eWiseMult): GB (_AemultB_02__ne_fc32)
// A.*B function (eWiseMult): GB (_AemultB_04__ne_fc32)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__ne_fc32)
// A*D function (colscale): GB ((none))
// D*A function (rowscale): GB ((none))
// C+=B function (dense accum): GB (_Cdense_accumB__ne_fc32)
// C+=b function (dense accum): GB (_Cdense_accumb__ne_fc32)
// C+=A+B function (dense ewise3): GB ((none))
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__ne_fc32)
// C=scalar+B GB (_bind1st__ne_fc32)
// C=scalar+B' GB (_bind1st_tran__ne_fc32)
// C=A+scalar GB (_bind2nd__ne_fc32)
// C=A'+scalar GB (_bind2nd_tran__ne_fc32)
// C type: bool
// A type: GxB_FC32_t
// A pattern? 0
// B type: GxB_FC32_t
// B pattern? 0
// BinaryOp: cij = GB_FC32_ne (aij, bij)
#define GB_ATYPE \
GxB_FC32_t
#define GB_BTYPE \
GxB_FC32_t
#define GB_CTYPE \
bool
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
0
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
0
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA,A_iso) \
GxB_FC32_t aij = GBX (Ax, pA, A_iso)
// true if values of A are not used
#define GB_A_IS_PATTERN \
0 \
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB,B_iso) \
GxB_FC32_t bij = GBX (Bx, pB, B_iso)
// true if values of B are not used
#define GB_B_IS_PATTERN \
0 \
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
bool t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA,A_iso) \
cij = (crealf (GBX (Ax, pA, A_iso)) != 0) || (cimagf (GBX (Ax, pA, A_iso)) != 0)
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB,B_iso) \
cij = (crealf (GBX (Bx, pB, B_iso)) != 0) || (cimagf (GBX (Bx, pB, B_iso)) != 0)
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z,x,y,i,j) \
z = GB_FC32_ne (x, y) ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
0
// op is second
#define GB_OP_IS_SECOND \
0
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_NE || GxB_NO_FC32 || GxB_NO_NE_FC32)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
#if 0
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
#endif
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
void GB (_Cdense_ewise3_noaccum__ne_fc32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_noaccum_template.c"
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumB__ne_fc32)
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *B_ek_slicing, const int B_ntasks, const int B_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if 0
{
#include "GB_dense_subassign_23_template.c"
}
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumb__ne_fc32)
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if 0
{
// get the scalar b for C += b, of type GxB_FC32_t
GxB_FC32_t bwork = (*((GxB_FC32_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
#if 0
GrB_Info GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix D,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *restrict Cx = (bool *) C->x ;
#include "GB_AxB_colscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
#if 0
GrB_Info GB ((none))
(
GrB_Matrix C,
const GrB_Matrix D,
const GrB_Matrix B,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *restrict Cx = (bool *) C->x ;
#include "GB_AxB_rowscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
//------------------------------------------------------------------------------
// eWiseAdd: C=A+B, C<M>=A+B, C<!M>=A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__ne_fc32)
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool is_eWiseUnion,
const GB_void *alpha_scalar_in,
const GB_void *beta_scalar_in,
const bool Ch_is_Mh,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GB_WERK_DECLARE (M_ek_slicing, int64_t) ;
GB_WERK_DECLARE (A_ek_slicing, int64_t) ;
GB_WERK_DECLARE (B_ek_slicing, int64_t) ;
GxB_FC32_t alpha_scalar ;
GxB_FC32_t beta_scalar ;
if (is_eWiseUnion)
{
alpha_scalar = (*((GxB_FC32_t *) alpha_scalar_in)) ;
beta_scalar = (*((GxB_FC32_t *) beta_scalar_in )) ;
}
#include "GB_add_template.c"
GB_FREE_WORKSPACE ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, or C<M!>=A.*B where C is sparse/hyper
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_08__ne_fc32)
(
GrB_Matrix C,
const int C_sparsity,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_08_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<#> = A.*B when A is sparse/hyper and B is bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_02__ne_fc32)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool flipxy,
const int64_t *restrict Cp_kfirst,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if GB_BINOP_FLIP
// The operator is not commutative, and does not have a flipped
// variant. For example z=atan2(y,x).
if (flipxy)
{
// use fmult(y,x)
#undef GB_FLIPPED
#define GB_FLIPPED 1
#include "GB_emult_02_template.c"
}
else
{
// use fmult(x,y)
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
}
#else
// No need to handle the flip: the operator is either commutative, or
// has been handled by changing z=div(y,x) to z=rdiv(x,y) for example.
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<M> = A.*B, M sparse/hyper, A and B bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_04__ne_fc32)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict Cp_kfirst,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_04_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, C<!M>=A.*B where C is bitmap
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_bitmap__ne_fc32)
(
GrB_Matrix C,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_bitmap_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB (_bind1st__ne_fc32)
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *restrict Bb,
int64_t bnz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *Cx = (bool *) Cx_output ;
GxB_FC32_t x = (*((GxB_FC32_t *) x_input)) ;
GxB_FC32_t *Bx = (GxB_FC32_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < bnz ; p++)
{
if (!GBB (Bb, p)) continue ;
GxB_FC32_t bij = GBX (Bx, p, false) ;
Cx [p] = GB_FC32_ne (x, bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__ne_fc32)
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *restrict Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
bool *Cx = (bool *) Cx_output ;
GxB_FC32_t *Ax = (GxB_FC32_t *) Ax_input ;
GxB_FC32_t y = (*((GxB_FC32_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
GxB_FC32_t aij = GBX (Ax, p, false) ;
Cx [p] = GB_FC32_ne (aij, y) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
GxB_FC32_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = GB_FC32_ne (x, aij) ; \
}
GrB_Info GB (_bind1st_tran__ne_fc32)
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
GxB_FC32_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC32_t x = (*((const GxB_FC32_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
GxB_FC32_t
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
GxB_FC32_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = GB_FC32_ne (aij, y) ; \
}
GrB_Info GB (_bind2nd_tran__ne_fc32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GxB_FC32_t y = (*((const GxB_FC32_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
2432.c | /* POLYBENCH/GPU-OPENMP
*
* This file is a part of the Polybench/GPU-OpenMP suite
*
* Contact:
* William Killian <killian@udel.edu>
*
* Copyright 2013, The University of Delaware
*/
#include <stdio.h>
#include <unistd.h>
#include <string.h>
#include <math.h>
/* Include polybench common header. */
#include <polybench.h>
/* Include benchmark-specific header. */
/* Default data type is double, default size is 4000. */
#include "correlation.h"
/* Array initialization. */
static
void init_array (int m,
int n,
DATA_TYPE *float_n,
DATA_TYPE POLYBENCH_2D(data,M,N,m,n))
{
int i, j;
*float_n = 1.2;
for (i = 0; i < m; i++)
for (j = 0; j < n; j++)
data[i][j] = ((DATA_TYPE) i*j) / M;
}
/* DCE code. Must scan the entire live-out data.
Can be used also to check the correctness of the output. */
static
void print_array(int m,
DATA_TYPE POLYBENCH_2D(symmat,M,M,m,m))
{
int i, j;
for (i = 0; i < m; i++)
for (j = 0; j < m; j++) {
fprintf (stderr, DATA_PRINTF_MODIFIER, symmat[i][j]);
if ((i * m + j) % 20 == 0) fprintf (stderr, "\n");
}
fprintf (stderr, "\n");
}
/* Main computational kernel. The whole function will be timed,
including the call and return. */
static
void kernel_correlation(int m, int n,
DATA_TYPE float_n,
DATA_TYPE POLYBENCH_2D(data,M,N,m,n),
DATA_TYPE POLYBENCH_2D(symmat,M,M,m,m),
DATA_TYPE POLYBENCH_1D(mean,M,m),
DATA_TYPE POLYBENCH_1D(stddev,M,m))
{
int i, j, j1, j2;
DATA_TYPE eps = 0.1f;
#define sqrt_of_array_cell(x,j) sqrt(x[j])
#pragma scop
/* Determine mean of column vectors of input data matrix */
{
for (j = 0; j < _PB_M; j++)
{
mean[j] = 0.0;
for (i = 0; i < _PB_N; i++)
mean[j] += data[i][j];
mean[j] /= float_n;
}
/* Determine standard deviations of column vectors of data matrix. */
for (j = 0; j < _PB_M; j++)
{
stddev[j] = 0.0;
for (i = 0; i < _PB_N; i++)
stddev[j] += (data[i][j] - mean[j]) * (data[i][j] - mean[j]);
stddev[j] /= float_n;
stddev[j] = sqrt_of_array_cell(stddev, j);
/* The following in an inelegant but usual way to handle
near-zero std. dev. values, which below would cause a zero-
divide. */
stddev[j] = stddev[j] <= eps ? 1.0 : stddev[j];
}
/* Center and reduce the column vectors. */
for (i = 0; i < _PB_N; i++)
{
#pragma omp target teams distribute
for (j = 0; j < _PB_M; j++)
{
data[i][j] -= mean[j];
data[i][j] /= sqrt(float_n) * stddev[j];
}
}
/* Calculate the m * m correlation matrix. */
for (j1 = 0; j1 < _PB_M-1; j1++)
{
symmat[j1][j1] = 1.0;
for (j2 = j1+1; j2 < _PB_M; j2++)
{
symmat[j1][j2] = 0.0;
for (i = 0; i < _PB_N; i++)
symmat[j1][j2] += (data[i][j1] * data[i][j2]);
symmat[j2][j1] = symmat[j1][j2];
}
}
}
#pragma endscop
symmat[_PB_M-1][_PB_M-1] = 1.0;
}
int main(int argc, char** argv)
{
/* Retrieve problem size. */
int n = N;
int m = M;
/* Variable declaration/allocation. */
DATA_TYPE float_n;
POLYBENCH_2D_ARRAY_DECL(data,DATA_TYPE,M,N,m,n);
POLYBENCH_2D_ARRAY_DECL(symmat,DATA_TYPE,M,M,m,m);
POLYBENCH_1D_ARRAY_DECL(mean,DATA_TYPE,M,m);
POLYBENCH_1D_ARRAY_DECL(stddev,DATA_TYPE,M,m);
/* Initialize array(s). */
init_array (m, n, &float_n, POLYBENCH_ARRAY(data));
/* Start timer. */
polybench_start_instruments;
/* Run kernel. */
kernel_correlation (m, n, float_n,
POLYBENCH_ARRAY(data),
POLYBENCH_ARRAY(symmat),
POLYBENCH_ARRAY(mean),
POLYBENCH_ARRAY(stddev));
/* Stop and print timer. */
polybench_stop_instruments;
polybench_print_instruments;
/* Prevent dead-code elimination. All live-out data must be printed
by the function call in argument. */
polybench_prevent_dce(print_array(m, POLYBENCH_ARRAY(symmat)));
/* Be clean. */
POLYBENCH_FREE_ARRAY(data);
POLYBENCH_FREE_ARRAY(symmat);
POLYBENCH_FREE_ARRAY(mean);
POLYBENCH_FREE_ARRAY(stddev);
return 0;
}
|
DRB012-minusminus-var-yes.c | /*
Copyright (c) 2017, Lawrence Livermore National Security, LLC.
Produced at the Lawrence Livermore National Laboratory
Written by Chunhua Liao, Pei-Hung Lin, Joshua Asplund,
Markus Schordan, and Ian Karlin
(email: liao6@llnl.gov, lin32@llnl.gov, asplund1@llnl.gov,
schordan1@llnl.gov, karlin1@llnl.gov)
LLNL-CODE-732144
All rights reserved.
This file is part of DataRaceBench. For details, see
https://github.com/LLNL/dataracebench. Please also see the LICENSE file
for our additional BSD notice.
Redistribution and use in source and binary forms, with
or without modification, are permitted provided that the following
conditions are met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the disclaimer below.
* Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the disclaimer (as noted below)
in the documentation and/or other materials provided with the
distribution.
* Neither the name of the LLNS/LLNL nor the names of its contributors
may be used to endorse or promote products derived from this
software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND
CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES,
INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL LAWRENCE LIVERMORE NATIONAL
SECURITY, LLC, THE U.S. DEPARTMENT OF ENERGY OR CONTRIBUTORS BE
LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY,
OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING
IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
THE POSSIBILITY OF SUCH DAMAGE.
*/
/*
The -- operation is not protected, causing race condition.
Data race pair: numNodes2@75 vs. numNodes2@75
*/
#include <stdlib.h>
int main(int argc, char* argv[])
{
int i;
int len=100;
if (argc>1)
len = atoi(argv[1]);
int numNodes=len, numNodes2=0;
int x[len];
for (i=0; i< len; i++)
{
if (i%2==0)
x[i]=5;
else
x[i]= -5;
}
#pragma omp parallel for schedule(dynamic)
for (i=numNodes-1 ; i>-1 ; --i) {
if (x[i]<=0) {
numNodes2-- ;
}
}
return 0;
}
|
GB_binop__pair_int16.c | //------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_emult.h"
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB (_AaddB__pair_int16)
// A.*B function (eWiseMult): GB (_AemultB)
// A.*B function (eWiseMult): GB (_AemultB_02__pair_int16)
// A.*B function (eWiseMult): GB (_AemultB_03__pair_int16)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__pair_int16)
// A*D function (colscale): GB (_AxD__pair_int16)
// D*A function (rowscale): GB (_DxB__pair_int16)
// C+=B function (dense accum): GB (_Cdense_accumB__pair_int16)
// C+=b function (dense accum): GB (_Cdense_accumb__pair_int16)
// C+=A+B function (dense ewise3): GB ((none))
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__pair_int16)
// C=scalar+B GB ((none))
// C=scalar+B' GB ((none))
// C=A+scalar GB ((none))
// C=A'+scalar GB ((none))
// C type: int16_t
// A type: int16_t
// B,b type: int16_t
// BinaryOp: cij = 1
#define GB_ATYPE \
int16_t
#define GB_BTYPE \
int16_t
#define GB_CTYPE \
int16_t
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
1
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
1
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
;
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB) \
;
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
int16_t t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA) \
cij = Ax [pA]
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB) \
cij = Bx [pB]
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z, x, y, i, j) \
z = 1 ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
0
// op is second
#define GB_OP_IS_SECOND \
0
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_PAIR || GxB_NO_INT16 || GxB_NO_PAIR_INT16)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
#if 0
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
#endif
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_ewise3_noaccum__pair_int16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_dense_ewise3_noaccum_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumB__pair_int16)
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *B_ek_slicing, const int B_ntasks, const int B_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
#include "GB_dense_subassign_23_template.c"
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumb__pair_int16)
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
// get the scalar b for C += b, of type int16_t
int16_t bwork = (*((int16_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_AxD__pair_int16)
(
GrB_Matrix C,
const GrB_Matrix A, bool A_is_pattern,
const GrB_Matrix D, bool D_is_pattern,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int16_t *restrict Cx = (int16_t *) C->x ;
#include "GB_AxB_colscale_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_DxB__pair_int16)
(
GrB_Matrix C,
const GrB_Matrix D, bool D_is_pattern,
const GrB_Matrix B, bool B_is_pattern,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int16_t *restrict Cx = (int16_t *) C->x ;
#include "GB_AxB_rowscale_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C = A+B or C<M> = A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__pair_int16)
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool Ch_is_Mh,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GB_WERK_DECLARE (M_ek_slicing, int64_t) ;
GB_WERK_DECLARE (A_ek_slicing, int64_t) ;
GB_WERK_DECLARE (B_ek_slicing, int64_t) ;
#include "GB_add_template.c"
GB_FREE_WORK ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C = A.*B or C<M> = A.*B
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_01__pair_int16)
(
GrB_Matrix C,
const int C_sparsity,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_01_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<#> = A.*B when A is sparse/hyper and B is bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_02__pair_int16)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool flipxy,
const int64_t *restrict Cp_kfirst,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if GB_BINOP_FLIP
// The operator is not commutative, and does not have a flipped
// variant. For example z=atan2(y,x).
if (flipxy)
{
// use fmult(y,x)
#undef GB_FLIPPED
#define GB_FLIPPED 1
#include "GB_emult_02_template.c"
}
else
{
// use fmult(x,y)
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
}
#else
// No need to handle the flip: the operator is either commutative, or
// has been handled by changing z=div(y,x) to z=rdiv(x,y) for example.
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<M> = A.*B, M sparse/hyper, A and B bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_03__pair_int16)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict Cp_kfirst,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_03_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, C<!M>=A.*B where C is bitmap
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_bitmap__pair_int16)
(
GrB_Matrix C,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_bitmap_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
#if 0
GrB_Info GB ((none))
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *restrict Bb,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int16_t *Cx = (int16_t *) Cx_output ;
int16_t x = (*((int16_t *) x_input)) ;
int16_t *Bx = (int16_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Bb, p)) continue ;
; ;
Cx [p] = 1 ;
}
return (GrB_SUCCESS) ;
#endif
}
#endif
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
#if 0
GrB_Info GB ((none))
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *restrict Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
int16_t *Cx = (int16_t *) Cx_output ;
int16_t *Ax = (int16_t *) Ax_input ;
int16_t y = (*((int16_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
; ;
Cx [p] = 1 ;
}
return (GrB_SUCCESS) ;
#endif
}
#endif
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
#if 0
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
; ; \
Cx [pC] = 1 ; \
}
GrB_Info GB ((none))
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
int16_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int16_t x = (*((const int16_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
int16_t
}
#endif
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
#if 0
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
; ; \
Cx [pC] = 1 ; \
}
GrB_Info GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int16_t y = (*((const int16_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
#endif
|
host_varfn_function.c | #include <stdio.h>
#include <omp.h>
#include <hostrpc.h>
// This user variable function returns a uint so declare function
// as hostrpc_varfn_uint_t .
hostrpc_varfn_uint_t my3argfn;
hostrpc_varfn_double_t mydoublefn;
// This is an arbitrary 3 arg function
uint my3argfn(void * fnptr, ...) {
va_list args;
va_start(args, fnptr);
int*a = va_arg(args, int*);
int i2 = va_arg(args, int);
int i3 = va_arg(args, int);
printf(" INSIDE my3argfn: fnptr:%p &a:%p int arg2:%d int arg3:%d \n", fnptr,a,i2,i3);
va_end(args);
return i2+i3;
}
// This is an arbitrary 3 arg function
double mydoublefn(void * fnptr, ...) {
va_list args;
va_start(args, fnptr);
int*a = va_arg(args, int*);
int i2 = va_arg(args, int);
int i3 = va_arg(args, int);
double rc = (double) (i2+i3) * 1.1;
printf(" INSIDE mydoublefn: fnptr:%p &a:%p int arg2:%d int arg3:%d rc:%f \n", fnptr,a,i2,i3,rc);
va_end(args);
return rc;
}
int main()
{
int N = 10;
int a[N];
int b[N];
int i;
for (i=0; i<N; i++){
a[i]=0;
b[i]=i;
}
hostrpc_varfn_uint_t * my_host_fn_ptr;
my_host_fn_ptr = &my3argfn;
hostrpc_varfn_double_t * my_host_fn_double;
my_host_fn_double = &mydoublefn;
printf("Testing my3argfn execution as function pointer %p &a:%p\n",(void *) my_host_fn_ptr, &a);
uint sim1 = my_host_fn_ptr(NULL, &a, 2, 3);
double sim1d = my_host_fn_double(NULL, &a, 2, 3);
printf("Return values are %d and %f \n",sim1,sim1d);
printf("\nTesting the host fallback of hostrpc_varfn_double:%p\n",my_host_fn_double);
uint sim2 = hostrpc_varfn_uint(my_host_fn_ptr, &a, 4, 5);
double sim2d = hostrpc_varfn_double(my_host_fn_double, &a, 4, 5);
printf("Return values are %d and %f \n",sim2,sim2d);
printf("\nTesting call to hostrpc_varfn_uint in target region:%p\n",my_host_fn_ptr);
#pragma omp target parallel for map(from: a[0:N]) map(to: b[0:N]) is_device_ptr(my_host_fn_ptr,my_host_fn_double)
for (int j = 0; j< N; j++) {
a[j]=b[j];
uint rc=hostrpc_varfn_uint(my_host_fn_ptr, &a, j, a[j]);
double rcd=hostrpc_varfn_double(my_host_fn_double, &a, j, a[j]);
printf("DEVICE: fnptr:%p dfnptr:%p &a:%p j:%d a[j]:%d hostrpc_varfn_uint return vals are %d %f\n",
(void*) my_host_fn_ptr,
(void*) my_host_fn_double,
(void*) &a, j, a[j],rc,rcd);
}
int rc = 0;
for (i=0; i<N; i++)
if (a[i] != b[i] ) {
rc++;
printf ("Wrong value: a[%d]=%d\n", i, a[i]);
}
if (!rc){
printf("Success\n");
return EXIT_SUCCESS;
} else{
printf("Failure\n");
return EXIT_FAILURE;
}
}
|
pr35549.c | /* PR middle-end/35549 */
/* { dg-do run } */
#include <omp.h>
#include <stdlib.h>
int
main (void)
{
int i = 6, n = 0;
omp_set_dynamic (0);
omp_set_nested (1);
#pragma omp parallel shared (i) num_threads (3)
{
if (omp_get_num_threads () != 3)
#pragma omp atomic
n += 1;
#pragma omp parallel shared (i) num_threads (4)
{
if (omp_get_num_threads () != 4)
#pragma omp atomic
n += 1;
#pragma omp critical
i += 1;
}
}
if (n == 0 && i != 6 + 3 * 4)
abort ();
return 0;
}
|
GB_binop__ge_uint16.c | //------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_emult.h"
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB (_AaddB__ge_uint16)
// A.*B function (eWiseMult): GB (_AemultB)
// A.*B function (eWiseMult): GB (_AemultB_02__ge_uint16)
// A.*B function (eWiseMult): GB (_AemultB_03__ge_uint16)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__ge_uint16)
// A*D function (colscale): GB (_AxD__ge_uint16)
// D*A function (rowscale): GB (_DxB__ge_uint16)
// C+=B function (dense accum): GB (_Cdense_accumB__ge_uint16)
// C+=b function (dense accum): GB (_Cdense_accumb__ge_uint16)
// C+=A+B function (dense ewise3): GB ((none))
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__ge_uint16)
// C=scalar+B GB (_bind1st__ge_uint16)
// C=scalar+B' GB (_bind1st_tran__ge_uint16)
// C=A+scalar GB (_bind2nd__ge_uint16)
// C=A'+scalar GB (_bind2nd_tran__ge_uint16)
// C type: bool
// A type: uint16_t
// B,b type: uint16_t
// BinaryOp: cij = (aij >= bij)
#define GB_ATYPE \
uint16_t
#define GB_BTYPE \
uint16_t
#define GB_CTYPE \
bool
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
0
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
0
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
uint16_t aij = Ax [pA]
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB) \
uint16_t bij = Bx [pB]
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
bool t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA) \
cij = Ax [pA]
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB) \
cij = Bx [pB]
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z, x, y, i, j) \
z = (x >= y) ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
0
// op is second
#define GB_OP_IS_SECOND \
0
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_GE || GxB_NO_UINT16 || GxB_NO_GE_UINT16)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
#if 0
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
#endif
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_ewise3_noaccum__ge_uint16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_dense_ewise3_noaccum_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumB__ge_uint16)
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *B_ek_slicing, const int B_ntasks, const int B_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if 0
{
#include "GB_dense_subassign_23_template.c"
}
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumb__ge_uint16)
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if 0
{
// get the scalar b for C += b, of type uint16_t
uint16_t bwork = (*((uint16_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_AxD__ge_uint16)
(
GrB_Matrix C,
const GrB_Matrix A, bool A_is_pattern,
const GrB_Matrix D, bool D_is_pattern,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *restrict Cx = (bool *) C->x ;
#include "GB_AxB_colscale_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_DxB__ge_uint16)
(
GrB_Matrix C,
const GrB_Matrix D, bool D_is_pattern,
const GrB_Matrix B, bool B_is_pattern,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *restrict Cx = (bool *) C->x ;
#include "GB_AxB_rowscale_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C = A+B or C<M> = A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__ge_uint16)
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool Ch_is_Mh,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GB_WERK_DECLARE (M_ek_slicing, int64_t) ;
GB_WERK_DECLARE (A_ek_slicing, int64_t) ;
GB_WERK_DECLARE (B_ek_slicing, int64_t) ;
#include "GB_add_template.c"
GB_FREE_WORK ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C = A.*B or C<M> = A.*B
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_01__ge_uint16)
(
GrB_Matrix C,
const int C_sparsity,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_01_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<#> = A.*B when A is sparse/hyper and B is bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_02__ge_uint16)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool flipxy,
const int64_t *restrict Cp_kfirst,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if GB_BINOP_FLIP
// The operator is not commutative, and does not have a flipped
// variant. For example z=atan2(y,x).
if (flipxy)
{
// use fmult(y,x)
#undef GB_FLIPPED
#define GB_FLIPPED 1
#include "GB_emult_02_template.c"
}
else
{
// use fmult(x,y)
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
}
#else
// No need to handle the flip: the operator is either commutative, or
// has been handled by changing z=div(y,x) to z=rdiv(x,y) for example.
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<M> = A.*B, M sparse/hyper, A and B bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_03__ge_uint16)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict Cp_kfirst,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_03_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, C<!M>=A.*B where C is bitmap
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_bitmap__ge_uint16)
(
GrB_Matrix C,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_bitmap_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB (_bind1st__ge_uint16)
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *restrict Bb,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *Cx = (bool *) Cx_output ;
uint16_t x = (*((uint16_t *) x_input)) ;
uint16_t *Bx = (uint16_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Bb, p)) continue ;
uint16_t bij = Bx [p] ;
Cx [p] = (x >= bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__ge_uint16)
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *restrict Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
bool *Cx = (bool *) Cx_output ;
uint16_t *Ax = (uint16_t *) Ax_input ;
uint16_t y = (*((uint16_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
uint16_t aij = Ax [p] ;
Cx [p] = (aij >= y) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
uint16_t aij = Ax [pA] ; \
Cx [pC] = (x >= aij) ; \
}
GrB_Info GB (_bind1st_tran__ge_uint16)
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
uint16_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint16_t x = (*((const uint16_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
uint16_t
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
uint16_t aij = Ax [pA] ; \
Cx [pC] = (aij >= y) ; \
}
GrB_Info GB (_bind2nd_tran__ge_uint16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint16_t y = (*((const uint16_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
convert_hyb_x_coo.c | #include "alphasparse/format.h"
#include <stdlib.h>
#include <alphasparse/opt.h>
#include <alphasparse/util.h>
#include <memory.h>
#include <stdio.h>
static void print_coo_s(const spmat_coo_s_t *mat)
{
printf("nnz:%d, cols:%d, rows:%d\n", mat->nnz, mat->cols, mat->rows);
for (ALPHA_INT i = 0; i < mat->nnz; i++)
{
printf("#%d, val:%f, row:%d, col:%d\n", i, mat->values[i], mat->row_indx[i], mat->col_indx[i]);
}
printf("=====================================\n\n");
}
static void print_ell_s(const spmat_ell_s_t *mat)
{
printf("ld:%d, cols:%d, rows:%d\n", mat->ld, mat->cols, mat->rows);
for(ALPHA_INT i = 0; i < mat->ld; i++)
{
for(ALPHA_INT j = 0; j < mat->rows; j++)
{
printf("%f ", mat->values[i*mat->rows + j]);
}
printf("\n");
}
printf("=====================================\n\n");
}
alphasparse_status_t ONAME(const ALPHA_SPMAT_COO *source, ALPHA_SPMAT_HYB **dest)
{
ALPHA_SPMAT_HYB *mat = alpha_malloc(sizeof(ALPHA_SPMAT_HYB));
*dest = mat;
ALPHA_SPMAT_CSR *csr;
convert_csr_coo(source, &csr);
ALPHA_INT m = csr->rows;
ALPHA_INT n = csr->cols;
ALPHA_INT csr_nnz = source->nnz;
ALPHA_INT ell_width = (csr_nnz - 1) / m + 1;
ALPHA_INT coo_nnz = 0;
for (ALPHA_INT i = 0; i < m; i++)
{
ALPHA_INT row_nnz = csr->rows_end[i] - csr->rows_start[i];
ALPHA_INT deta = row_nnz - ell_width;
coo_nnz += deta > 0 ? deta : 0;
}
const ALPHA_INT thread_num = alpha_get_thread_num();
ALPHA_Number *ell_values = alpha_memalign((uint64_t)ell_width * m * sizeof(ALPHA_Number), DEFAULT_ALIGNMENT);
ALPHA_INT *ell_col_ind = alpha_memalign((uint64_t)ell_width * m * sizeof(ALPHA_INT), DEFAULT_ALIGNMENT);
ALPHA_Number *coo_values = alpha_memalign((uint64_t)coo_nnz * sizeof(ALPHA_Number), DEFAULT_ALIGNMENT);
ALPHA_INT *coo_row_val = alpha_memalign((uint64_t)coo_nnz * sizeof(ALPHA_INT), DEFAULT_ALIGNMENT);
ALPHA_INT *coo_col_val = alpha_memalign((uint64_t)coo_nnz * sizeof(ALPHA_INT), DEFAULT_ALIGNMENT);
memset(ell_values, 0, (uint64_t)ell_width * m * sizeof(ALPHA_Number));
memset(ell_col_ind, 0, (uint64_t)ell_width * m * sizeof(ALPHA_INT));
memset(coo_values, 0, (uint64_t)coo_nnz * sizeof(ALPHA_Number));
memset(coo_row_val, 0, (uint64_t)coo_nnz * sizeof(ALPHA_INT));
memset(coo_col_val, 0, (uint64_t)coo_nnz * sizeof(ALPHA_INT));
// i列j行, 列优先
#ifdef _OPENMP
#pragma omp parallel for num_threads(thread_num)
#endif
for (ALPHA_INT i = 0; i < ell_width; i++)
{
for (ALPHA_INT j = 0; j < m; j++)
{
ALPHA_INT csr_rs = csr->rows_start[j];
ALPHA_INT csr_re = csr->rows_end[j];
if (csr_rs + i < csr_re)
{
ell_values [i * m + j] = csr->values[csr_rs + i];
ell_col_ind[i * m + j] = csr->col_indx[csr_rs + i];
}
}
}
ALPHA_INT idx = 0;
for (ALPHA_INT i = ell_width; i < n; i++)
{
for (ALPHA_INT j = 0; j < m; j++)
{
ALPHA_INT csr_rs = csr->rows_start[j];
ALPHA_INT csr_re = csr->rows_end[j];
if (csr_rs + i < csr_re)
{
coo_values [idx] = csr->values[csr_rs + i];
coo_row_val[idx] = j;
coo_col_val[idx] = csr->col_indx[csr_rs +i];
idx++;
}
}
}
// coo part sort
ALPHA_SPMAT_COO *coo = alpha_malloc(sizeof(ALPHA_SPMAT_COO));
coo->col_indx = coo_col_val;
coo->row_indx = coo_row_val;
coo->values = coo_values;
coo->cols = n;
coo->rows = m;
coo->nnz = coo_nnz;
// coo->ordered = false;
// coo_order(coo);
mat->ell_val = ell_values;
mat->ell_col_ind = ell_col_ind;
mat->coo_val = coo->values;
mat->coo_col_val = coo->col_indx;
mat->coo_row_val = coo->row_indx;
mat->nnz = coo_nnz;
mat->rows = m;
mat->cols = n;
mat->ell_width = ell_width;
//#define CHECK
#ifdef CHECK
#ifdef S
print_coo_s(source);
print_coo_s(coo);
ALPHA_SPMAT_ELL *ell = alpha_malloc(sizeof(ALPHA_SPMAT_ELL));
ell->values = ell_values;
ell->indices = ell_col_ind;
ell->ld = ell_width;
ell->rows = m;
ell->cols = n;
print_ell_s(ell);
#endif
#undef CHECK
#endif
return ALPHA_SPARSE_STATUS_SUCCESS;
}
|
bml_submatrix_ellpack_typed.c | #ifdef BML_USE_MAGMA
#include "magma_v2.h"
#endif
#include "../../macros.h"
#include "../../typed.h"
#include "../bml_allocate.h"
#include "../bml_logger.h"
#include "../bml_submatrix.h"
#include "../bml_types.h"
#include "../dense/bml_allocate_dense.h"
#include "bml_allocate_ellpack.h"
#include "bml_submatrix_ellpack.h"
#include "bml_types_ellpack.h"
#include <complex.h>
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#ifdef _OPENMP
#include <omp.h>
#endif
/** Determine element indices for submatrix, given a set of nodes/orbitals.
*
* \ingroup submatrix_group_C
*
* \param A Hamiltonian matrix A
* \param B Graph matrix B
* \param nodelist List of node/orbital indeces
* \param nsize Size of nodelist
* \param core_halo_index List of core+halo indeces
* \param vsize Size of core_halo_index and number of cores
* \param double_jump_flag Flag to use double jump (0=no, 1=yes)
*/
void TYPED_FUNC(
bml_matrix2submatrix_index_ellpack) (
bml_matrix_ellpack_t * A,
bml_matrix_ellpack_t * B,
int *nodelist,
int nsize,
int *core_halo_index,
int *vsize,
int double_jump_flag)
{
int l, ll, ii, ls, k;
int A_N = A->N;
int A_M = A->M;
int *A_nnz = A->nnz;
int *A_index = A->index;
int B_N = B->N;
int B_M = B->M;
int *B_nnz = B->nnz;
int *B_index = B->index;
int ix[A_N];
memset(ix, 0, A_N * sizeof(int));
l = 0;
ll = 0;
#ifdef USE_OMP_OFFLOAD
#pragma omp target update from(A_nnz[:A_N], A_index[:A_N*A_M])
#pragma omp target update from(B_nnz[:B_N], B_index[:B_N*B_M])
#endif
// Cores are first followed by halos
for (int j = 0; j < nsize; j++)
{
ii = nodelist[j];
if (ix[ii] == 0)
{
ix[ii] = ii + 1;
core_halo_index[l] = ii;
l++;
ll++;
}
}
// Collect halo indeces from graph
for (int j = 0; j < nsize; j++)
{
ii = nodelist[j];
for (int jp = 0; jp < B_nnz[ii]; jp++)
{
k = B_index[ROWMAJOR(ii, jp, B_N, B_M)];
if (ix[k] == 0)
{
ix[k] = ii + 1;
core_halo_index[l] = k;
l++;
}
}
}
// Add more halo elements from H
for (int j = 0; j < nsize; j++)
{
ii = nodelist[j];
for (int jp = 0; jp < A_nnz[ii]; jp++)
{
k = A_index[ROWMAJOR(ii, jp, A_N, A_M)];
if (ix[k] == 0)
{
ix[k] = ii + 1;
core_halo_index[l] = k;
l++;
}
}
}
// Perform a "double jump" for extra halo elements
// based on graph, like performing a symbolic X^2
if (double_jump_flag == 1)
{
ls = l;
for (int j = 0; j < ls; j++)
{
ii = core_halo_index[j];
for (int jp = 0; jp < B_nnz[ii]; jp++)
{
k = B_index[ROWMAJOR(ii, jp, B_N, B_M)];
if (ix[k] == 0)
{
ix[k] = ii + 1;
core_halo_index[l] = k;
l++;
}
}
}
}
vsize[0] = l;
vsize[1] = ll;
}
/** Determine element indices for submatrix, given a set of nodes/orbitals.
*
* \ingroup submatrix_group_C
*
* \param B Graph matrix B
* \param nodelist List of node/orbital indeces
* \param nsize Size of nodelist
* \param core_halo_index List of core+halo indeces
* \param vsize Size of core_halo_index and number of cores
* \param double_jump_flag Flag to use double jump (0=no, 1=yes)
*/
void TYPED_FUNC(
bml_matrix2submatrix_index_graph_ellpack) (
bml_matrix_ellpack_t * B,
int *nodelist,
int nsize,
int *core_halo_index,
int *vsize,
int double_jump_flag)
{
int l, ll, ii, ls, k;
int B_N = B->N;
int B_M = B->M;
int *B_index = B->index;
int *B_nnz = B->nnz;
int ix[B_N];
memset(ix, 0, B_N * sizeof(int));
l = 0;
ll = 0;
#ifdef USE_OMP_OFFLOAD
#pragma omp target update from(B_nnz[:B_N], B_index[:B_N*B_M])
#endif
// Cores are first followed by halos
for (int j = 0; j < nsize; j++)
{
ii = nodelist[j];
if (ix[ii] == 0)
{
ix[ii] = ii + 1;
core_halo_index[l] = ii;
l++;
ll++;
}
}
// Collext halo indeces from graph
for (int j = 0; j < nsize; j++)
{
ii = nodelist[j];
for (int jp = 0; jp < B_nnz[ii]; jp++)
{
k = B_index[ROWMAJOR(ii, jp, B_N, B_M)];
if (ix[k] == 0)
{
ix[k] = ii + 1;
core_halo_index[l] = k;
l++;
}
}
}
// Use graph for double jumps
if (double_jump_flag == 1)
{
ls = l;
for (int j = 0; j < ls; j++)
{
ii = core_halo_index[j];
for (int jp = 0; jp < B_nnz[ii]; jp++)
{
k = B_index[ROWMAJOR(ii, jp, B_N, B_M)];
if (ix[k] == 0)
{
ix[k] = ii + 1;
core_halo_index[l] = k;
l++;
}
}
}
}
vsize[0] = l;
vsize[1] = ll;
}
/** Extract a submatrix from a matrix given a set of core+halo rows.
*
* \ingroup submatrix_group_C
*
* \param A Matrix A
* \param B Submatrix B
* \param core_halo_index Set of row indeces for submatrix
* \param llsize Number of indeces
*/
void TYPED_FUNC(
bml_matrix2submatrix_ellpack) (
bml_matrix_ellpack_t * A,
bml_matrix_dense_t * B,
int *core_halo_index,
int lsize)
{
REAL_T *rvalue;
int B_N = B->N;
#ifdef BML_USE_MAGMA
REAL_T *B_matrix = bml_allocate_memory(sizeof(REAL_T) * B->N * B->N);
#else
REAL_T *B_matrix = B->matrix;
#endif
#ifdef USE_OMP_OFFLOAD
int A_N = A->N;
int A_M = A->M;
int *A_nnz = A->nnz;
int *A_index = A->index;
#pragma omp target update from(A_nnz[:A_N], A_index[:A_N*A_M])
#endif
#pragma omp parallel for \
private(rvalue) \
shared(core_halo_index) \
shared(A, B_matrix, B_N)
for (int jb = 0; jb < lsize; jb++)
{
rvalue = TYPED_FUNC(bml_getVector_ellpack) (A, core_halo_index,
core_halo_index[jb],
lsize);
for (int j = 0; j < lsize; j++)
{
B_matrix[ROWMAJOR(jb, j, B_N, B_N)] = rvalue[j];
}
bml_free_memory(rvalue);
}
#ifdef BML_USE_MAGMA
MAGMA(setmatrix) (B_N, B_N, (MAGMA_T *) B_matrix, B_N,
B->matrix, B->ld, B->queue);
bml_free_memory(B_matrix);
#endif
}
/** Assemble submatrix into a full matrix based on core+halo indeces.
*
* \ingroup submatrix_group_C
*
* \param A Submatrix A
* \param B Matrix B
* \param core_halo_index Set of submatrix row indeces
* \param lsize Number of indeces
* \param llsize Number of core positions
*/
void TYPED_FUNC(
bml_submatrix2matrix_ellpack) (
bml_matrix_dense_t * A,
bml_matrix_ellpack_t * B,
int *core_halo_index,
int lsize,
int llsize,
double threshold)
{
int A_N = A->N;
#ifdef BML_USE_MAGMA
REAL_T *A_matrix = bml_allocate_memory(sizeof(REAL_T) * A->N * A->N);
MAGMA(getmatrix) (A->N, A->N,
A->matrix, A->ld, (MAGMA_T *) A_matrix, A->N, A->queue);
#else
REAL_T *A_matrix = A->matrix;
#endif
int B_N = B->N;
int B_M = B->M;
int *B_nnz = B->nnz;
int *B_index = B->index;
REAL_T *B_value = B->value;
int ii, icol;
#ifdef USE_OMP_OFFLOAD
#pragma omp target update from(B_nnz[:B_N], B_index[:B_N*B_M], B_value[:B_N*B_M])
#endif
#pragma omp parallel for \
private(ii, icol) \
shared(core_halo_index) \
shared(A_N, A_matrix) \
shared(B_N, B_M, B_nnz, B_index, B_value)
for (int ja = 0; ja < llsize; ja++)
{
ii = core_halo_index[ja];
icol = 0;
for (int jb = 0; jb < lsize; jb++)
{
if (ABS(A_matrix[ROWMAJOR(ja, jb, A_N, A_N)]) > threshold)
{
B_index[ROWMAJOR(ii, icol, B_N, B_M)] = core_halo_index[jb];
B_value[ROWMAJOR(ii, icol, B_N, B_M)] =
A_matrix[ROWMAJOR(ja, jb, A_N, A_N)];
icol++;
}
}
if (icol > B_M)
{
LOG_ERROR("Number of non-zeroes per row >= M, Increase M\n");
}
B_nnz[ii] = icol;
}
#ifdef BML_USE_MAGMA
bml_free_memory(A_matrix);
#endif
#ifdef USE_OMP_OFFLOAD
#pragma omp target update to(B_nnz[:B_N], B_index[:B_N*B_M], B_value[:B_N*B_M])
#endif
}
// Get matching vector of values
void *TYPED_FUNC(
bml_getVector_ellpack) (
bml_matrix_ellpack_t * A,
int *jj,
int irow,
int colCnt)
{
REAL_T ZERO = 0.0;
int A_N = A->N;
int A_M = A->M;
int *A_nnz = A->nnz;
int *A_index = A->index;
REAL_T *A_value = A->value;
REAL_T *rvalue = bml_noinit_allocate_memory(colCnt * sizeof(REAL_T));
for (int i = 0; i < colCnt; i++)
{
for (int j = 0; j < A_nnz[irow]; j++)
{
if (A_index[ROWMAJOR(irow, j, A_N, A_M)] == jj[i])
{
rvalue[i] = A_value[ROWMAJOR(irow, j, A_N, A_M)];
break;
}
rvalue[i] = ZERO;
}
}
return rvalue;
}
/** Assemble matrix based on groups of rows from a matrix.
*
* \ingroup submatrix_group_C
*
* \param A Matrix A
* \param hindex Indeces of nodes
* \param ngroups Number of groups
* \param threshold Threshold for graph
*/
bml_matrix_ellpack_t
* TYPED_FUNC(bml_group_matrix_ellpack) (bml_matrix_ellpack_t * A,
int *hindex, int ngroups,
double threshold)
{
int A_N = A->N;
int A_M = A->M;
int *A_index = A->index;
int *A_nnz = A->nnz;
REAL_T *A_value = A->value;
#ifdef USE_OMP_OFFLOAD
#pragma omp target update from(A_nnz[:A_N], A_index[:A_N*A_M], A_value[:A_N*A_M])
#endif
#if !(defined(__IBMC_) || defined(__ibmxl__))
int ix[ngroups];
memset(ix, 0, sizeof(int) * ngroups);
#endif
int hnode[A_N];
int hend;
bml_matrix_dimension_t matrix_dimension = { ngroups, ngroups, ngroups };
bml_matrix_ellpack_t *B =
TYPED_FUNC(bml_noinit_matrix_ellpack) (matrix_dimension,
A->distribution_mode);
int B_N = B->N;
int B_M = B->M;
int *B_index = B->index;
int *B_nnz = B->nnz;
REAL_T *B_value = B->value;
#pragma omp parallel for \
private(hend) \
shared(hindex, hnode, A_N)
for (int i = 0; i < ngroups; i++)
{
if (i == ngroups - 1)
hend = A_N;
else
hend = hindex[i + 1] - 1;
for (int j = hindex[i] - 1; j < hend; j++)
{
hnode[j] = i;
}
}
#if defined(__IBMC_) || defined(__ibmxl__)
#pragma omp parallel for \
private(hend) \
shared(hindex, hnode) \
shared(A_nnz, A_index, A_value, A_N, A_M) \
shared(B_nnz, B_index, B_value, B_N, B_M)
#else
#pragma omp parallel for \
private(hend) \
shared(hindex, hnode) \
shared(A_nnz, A_index, A_value, A_N, A_M) \
shared(B_nnz, B_index, B_value, B_N, B_M) \
firstprivate(ix)
#endif
for (int i = 0; i < B_N; i++)
{
#if defined(__IBMC_) || defined(__ibmxl__)
int ix[ngroups];
memset(ix, 0, sizeof(int) * ngroups);
#endif
ix[i] = i + 1;
B_index[ROWMAJOR(i, 0, B_N, B_M)] = i;
B_value[ROWMAJOR(i, 0, B_N, B_M)] = 1.0;
B_nnz[i] = 1;
if (i == B_N - 1)
hend = A_N;
else
hend = hindex[i + 1] - 1;
for (int j = hindex[i] - 1; j < hend; j++)
{
for (int k = 0; k < A_nnz[j]; k++)
{
int ii = hnode[A_index[ROWMAJOR(j, k, A_N, A_M)]];
if (ix[ii] == 0 && ii != i)
{
//printf("row = %d col = %d val = %e\n", j, A_index[ROWMAJOR(j, k, A_N, A_M)], A_value[ROWMAJOR(j, k, A_N, A_M)]);
if (is_above_threshold(A_value[ROWMAJOR(j, k, A_N, A_M)],
threshold))
{
ix[ii] = i + 1;
B_index[ROWMAJOR(i, B_nnz[i], B_N, B_M)] = ii;
B_value[ROWMAJOR(i, B_nnz[i], B_N, B_M)] = 1.0;
B_nnz[i]++;
}
else
{
int kk = A_index[ROWMAJOR(j, k, A_N, A_M)];
for (int l = 0; l < A_nnz[kk]; l++)
{
int jj =
hnode[A_index[ROWMAJOR(kk, l, A_N, A_M)]];
if (jj == i)
{
//printf("sym row = %d col = %d val = %e\n", kk, A_index[ROWMAJOR(kk, l, A_N, A_M)], A_value[ROWMAJOR(kk, l, A_N, A_M)]);
if (is_above_threshold
(A_value[ROWMAJOR(kk, l, A_N, A_M)],
threshold))
{
ix[ii] = i + 1;
B_index[ROWMAJOR(i, B_nnz[i], B_N, B_M)] =
ii;
B_value[ROWMAJOR(i, B_nnz[i], B_N, B_M)] =
1.0;
B_nnz[i]++;
break;
}
}
}
}
}
}
}
}
#ifdef USE_OMP_OFFLOAD
#pragma omp target update to(B_nnz[:B_N], B_index[:B_N*B_M], B_value[:B_N*B_M])
#endif
return B;
}
|
GB_binop__plus_uint16.c |
//------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_emult.h"
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB (_AaddB__plus_uint16)
// A.*B function (eWiseMult): GB (_AemultB_08__plus_uint16)
// A.*B function (eWiseMult): GB (_AemultB_02__plus_uint16)
// A.*B function (eWiseMult): GB (_AemultB_04__plus_uint16)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__plus_uint16)
// A*D function (colscale): GB (_AxD__plus_uint16)
// D*A function (rowscale): GB (_DxB__plus_uint16)
// C+=B function (dense accum): GB (_Cdense_accumB__plus_uint16)
// C+=b function (dense accum): GB (_Cdense_accumb__plus_uint16)
// C+=A+B function (dense ewise3): GB (_Cdense_ewise3_accum__plus_uint16)
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__plus_uint16)
// C=scalar+B GB (_bind1st__plus_uint16)
// C=scalar+B' GB (_bind1st_tran__plus_uint16)
// C=A+scalar GB (_bind2nd__plus_uint16)
// C=A'+scalar GB (_bind2nd_tran__plus_uint16)
// C type: uint16_t
// A type: uint16_t
// A pattern? 0
// B type: uint16_t
// B pattern? 0
// BinaryOp: cij = (aij + bij)
#define GB_ATYPE \
uint16_t
#define GB_BTYPE \
uint16_t
#define GB_CTYPE \
uint16_t
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
1
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
1
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA,A_iso) \
uint16_t aij = GBX (Ax, pA, A_iso)
// true if values of A are not used
#define GB_A_IS_PATTERN \
0 \
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB,B_iso) \
uint16_t bij = GBX (Bx, pB, B_iso)
// true if values of B are not used
#define GB_B_IS_PATTERN \
0 \
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
uint16_t t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA,A_iso) \
cij = GBX (Ax, pA, A_iso)
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB,B_iso) \
cij = GBX (Bx, pB, B_iso)
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z,x,y,i,j) \
z = (x + y) ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
0
// op is second
#define GB_OP_IS_SECOND \
0
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_PLUS || GxB_NO_UINT16 || GxB_NO_PLUS_UINT16)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB (_Cdense_ewise3_accum__plus_uint16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
void GB (_Cdense_ewise3_noaccum__plus_uint16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_noaccum_template.c"
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumB__plus_uint16)
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *B_ek_slicing, const int B_ntasks, const int B_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
#include "GB_dense_subassign_23_template.c"
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumb__plus_uint16)
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
// get the scalar b for C += b, of type uint16_t
uint16_t bwork = (*((uint16_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_AxD__plus_uint16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix D,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint16_t *restrict Cx = (uint16_t *) C->x ;
#include "GB_AxB_colscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_DxB__plus_uint16)
(
GrB_Matrix C,
const GrB_Matrix D,
const GrB_Matrix B,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint16_t *restrict Cx = (uint16_t *) C->x ;
#include "GB_AxB_rowscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C=A+B, C<M>=A+B, C<!M>=A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__plus_uint16)
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool is_eWiseUnion,
const GB_void *alpha_scalar_in,
const GB_void *beta_scalar_in,
const bool Ch_is_Mh,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GB_WERK_DECLARE (M_ek_slicing, int64_t) ;
GB_WERK_DECLARE (A_ek_slicing, int64_t) ;
GB_WERK_DECLARE (B_ek_slicing, int64_t) ;
uint16_t alpha_scalar ;
uint16_t beta_scalar ;
if (is_eWiseUnion)
{
alpha_scalar = (*((uint16_t *) alpha_scalar_in)) ;
beta_scalar = (*((uint16_t *) beta_scalar_in )) ;
}
#include "GB_add_template.c"
GB_FREE_WORKSPACE ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, or C<M!>=A.*B where C is sparse/hyper
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_08__plus_uint16)
(
GrB_Matrix C,
const int C_sparsity,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_08_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<#> = A.*B when A is sparse/hyper and B is bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_02__plus_uint16)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool flipxy,
const int64_t *restrict Cp_kfirst,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if GB_BINOP_FLIP
// The operator is not commutative, and does not have a flipped
// variant. For example z=atan2(y,x).
if (flipxy)
{
// use fmult(y,x)
#undef GB_FLIPPED
#define GB_FLIPPED 1
#include "GB_emult_02_template.c"
}
else
{
// use fmult(x,y)
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
}
#else
// No need to handle the flip: the operator is either commutative, or
// has been handled by changing z=div(y,x) to z=rdiv(x,y) for example.
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<M> = A.*B, M sparse/hyper, A and B bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_04__plus_uint16)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict Cp_kfirst,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_04_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, C<!M>=A.*B where C is bitmap
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_bitmap__plus_uint16)
(
GrB_Matrix C,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_bitmap_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB (_bind1st__plus_uint16)
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *restrict Bb,
int64_t bnz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint16_t *Cx = (uint16_t *) Cx_output ;
uint16_t x = (*((uint16_t *) x_input)) ;
uint16_t *Bx = (uint16_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < bnz ; p++)
{
if (!GBB (Bb, p)) continue ;
uint16_t bij = GBX (Bx, p, false) ;
Cx [p] = (x + bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__plus_uint16)
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *restrict Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
uint16_t *Cx = (uint16_t *) Cx_output ;
uint16_t *Ax = (uint16_t *) Ax_input ;
uint16_t y = (*((uint16_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
uint16_t aij = GBX (Ax, p, false) ;
Cx [p] = (aij + y) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
uint16_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = (x + aij) ; \
}
GrB_Info GB (_bind1st_tran__plus_uint16)
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
uint16_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint16_t x = (*((const uint16_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
uint16_t
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
uint16_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = (aij + y) ; \
}
GrB_Info GB (_bind2nd_tran__plus_uint16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint16_t y = (*((const uint16_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
GB_binop__iseq_fp32.c | //------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_emult.h"
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB (_AaddB__iseq_fp32)
// A.*B function (eWiseMult): GB (_AemultB_08__iseq_fp32)
// A.*B function (eWiseMult): GB (_AemultB_02__iseq_fp32)
// A.*B function (eWiseMult): GB (_AemultB_04__iseq_fp32)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__iseq_fp32)
// A*D function (colscale): GB (_AxD__iseq_fp32)
// D*A function (rowscale): GB (_DxB__iseq_fp32)
// C+=B function (dense accum): GB (_Cdense_accumB__iseq_fp32)
// C+=b function (dense accum): GB (_Cdense_accumb__iseq_fp32)
// C+=A+B function (dense ewise3): GB ((none))
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__iseq_fp32)
// C=scalar+B GB (_bind1st__iseq_fp32)
// C=scalar+B' GB (_bind1st_tran__iseq_fp32)
// C=A+scalar GB (_bind2nd__iseq_fp32)
// C=A'+scalar GB (_bind2nd_tran__iseq_fp32)
// C type: float
// A type: float
// B,b type: float
// BinaryOp: cij = (aij == bij)
#define GB_ATYPE \
float
#define GB_BTYPE \
float
#define GB_CTYPE \
float
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
1
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
1
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA,A_iso) \
float aij = GBX (Ax, pA, A_iso)
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB,B_iso) \
float bij = GBX (Bx, pB, B_iso)
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
float t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA,A_iso) \
cij = GBX (Ax, pA, A_iso)
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB,B_iso) \
cij = GBX (Bx, pB, B_iso)
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z,x,y,i,j) \
z = (x == y) ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
0
// op is second
#define GB_OP_IS_SECOND \
0
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_ISEQ || GxB_NO_FP32 || GxB_NO_ISEQ_FP32)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
#if 0
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
#endif
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_ewise3_noaccum__iseq_fp32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_dense_ewise3_noaccum_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumB__iseq_fp32)
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *B_ek_slicing, const int B_ntasks, const int B_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
#include "GB_dense_subassign_23_template.c"
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumb__iseq_fp32)
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
// get the scalar b for C += b, of type float
float bwork = (*((float *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_AxD__iseq_fp32)
(
GrB_Matrix C,
const GrB_Matrix A, bool A_is_pattern,
const GrB_Matrix D, bool D_is_pattern,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
float *restrict Cx = (float *) C->x ;
#include "GB_AxB_colscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_DxB__iseq_fp32)
(
GrB_Matrix C,
const GrB_Matrix D, bool D_is_pattern,
const GrB_Matrix B, bool B_is_pattern,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
float *restrict Cx = (float *) C->x ;
#include "GB_AxB_rowscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C=A+B, C<M>=A+B, C<!M>=A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__iseq_fp32)
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool Ch_is_Mh,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GB_WERK_DECLARE (M_ek_slicing, int64_t) ;
GB_WERK_DECLARE (A_ek_slicing, int64_t) ;
GB_WERK_DECLARE (B_ek_slicing, int64_t) ;
#include "GB_add_template.c"
GB_FREE_WORK ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, or C<M!>=A.*B where C is sparse/hyper
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_08__iseq_fp32)
(
GrB_Matrix C,
const int C_sparsity,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_08_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<#> = A.*B when A is sparse/hyper and B is bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_02__iseq_fp32)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool flipxy,
const int64_t *restrict Cp_kfirst,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if GB_BINOP_FLIP
// The operator is not commutative, and does not have a flipped
// variant. For example z=atan2(y,x).
if (flipxy)
{
// use fmult(y,x)
#undef GB_FLIPPED
#define GB_FLIPPED 1
#include "GB_emult_02_template.c"
}
else
{
// use fmult(x,y)
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
}
#else
// No need to handle the flip: the operator is either commutative, or
// has been handled by changing z=div(y,x) to z=rdiv(x,y) for example.
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<M> = A.*B, M sparse/hyper, A and B bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_04__iseq_fp32)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict Cp_kfirst,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_04_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, C<!M>=A.*B where C is bitmap
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_bitmap__iseq_fp32)
(
GrB_Matrix C,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_bitmap_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB (_bind1st__iseq_fp32)
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *restrict Bb,
int64_t bnz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
float *Cx = (float *) Cx_output ;
float x = (*((float *) x_input)) ;
float *Bx = (float *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < bnz ; p++)
{
if (!GBB (Bb, p)) continue ;
float bij = GBX (Bx, p, false) ;
Cx [p] = (x == bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__iseq_fp32)
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *restrict Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
float *Cx = (float *) Cx_output ;
float *Ax = (float *) Ax_input ;
float y = (*((float *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
float aij = GBX (Ax, p, false) ;
Cx [p] = (aij == y) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
float aij = GBX (Ax, pA, false) ; \
Cx [pC] = (x == aij) ; \
}
GrB_Info GB (_bind1st_tran__iseq_fp32)
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
float
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
float x = (*((const float *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
float
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
float aij = GBX (Ax, pA, false) ; \
Cx [pC] = (aij == y) ; \
}
GrB_Info GB (_bind2nd_tran__iseq_fp32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
float y = (*((const float *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
GB_unaryop__abs_int32_uint16.c | //------------------------------------------------------------------------------
// GB_unaryop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2020, All Rights Reserved.
// http://suitesparse.com See GraphBLAS/Doc/License.txt for license.
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_iterator.h"
#include "GB_unaryop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB_unop__abs_int32_uint16
// op(A') function: GB_tran__abs_int32_uint16
// C type: int32_t
// A type: uint16_t
// cast: int32_t cij = (int32_t) aij
// unaryop: cij = GB_IABS (aij)
#define GB_ATYPE \
uint16_t
#define GB_CTYPE \
int32_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
uint16_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = GB_IABS (x) ;
// casting
#define GB_CASTING(z, aij) \
int32_t z = (int32_t) aij ;
// cij = op (cast (aij))
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GB_GETA (aij, Ax, pA) ; \
/* Cx [pC] = op (cast (aij)) */ \
GB_CASTING (z, aij) ; \
GB_OP (GB_CX (pC), z) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_ABS || GxB_NO_INT32 || GxB_NO_UINT16)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__abs_int32_uint16
(
int32_t *Cx, // Cx and Ax may be aliased
uint16_t *Ax,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
GB_CAST_OP (p, p) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_tran__abs_int32_uint16
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *GB_RESTRICT *Rowcounts,
GBI_single_iterator Iter,
const int64_t *GB_RESTRICT A_slice,
int naslice
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#define GB_PHASE_2_OF_2
#include "GB_unaryop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
subteam2.c | /* test two omp for loops in two subteams
and a single thread in the 3rd subteam
*/
#include <stdio.h>
#include <stdlib.h>
#if defined(_OPENMP)
#include <omp.h>
#endif /* _OPENMP */
/*by Liao, new data types and functions to support thread subteams*/
/*compiler generated new data type to store thread ids in a subteam*/
typedef struct{
int iCount;
int *iThreadIds;
} omp_id_set_t;
omp_id_set_t idSet1,idSet2,idSet3;
extern int __ompc_is_in_idset();
extern void __ompc_subteam_create();
void *subteam1, *subteam2, *subteam3; /*use it as &threadsubteam*/
#define NUMELEMENT 100
int main(void)
{
int a[NUMELEMENT];
int i,j=0,k,sum=0,sum2=0;
/* assume 5 threads */
#ifdef _OPENMP
omp_set_num_threads(5);
#endif
/* manual code to generate the thread subteams' ID sets currently */
/*stuff code to get ids from the thread ids in the subteam*/
idSet1.iCount=2;
idSet1.iThreadIds=(int *)malloc(2*sizeof(int));
idSet1.iThreadIds[0]=1;
idSet1.iThreadIds[1]=3;
idSet2.iCount=2;
idSet2.iThreadIds=(int *)malloc(2*sizeof(int));
idSet2.iThreadIds[0]=0;
idSet2.iThreadIds[1]=2;
idSet3.iCount=1;
idSet3.iThreadIds=(int *)malloc(1*sizeof(int));
idSet3.iThreadIds[0]=1;
#pragma omp parallel
{
/* onthreads(0,2) */
#pragma omp for reduction(+:sum)
for (i=1;i<=NUMELEMENT;i++)
{
sum = sum +i;
}
/* onthreads(1,3) */
#pragma omp for schedule(dynamic,5)
for (i=0;i<NUMELEMENT;i++)
{
a[i]=9;
}
/* onthread 4 */
#pragma omp single
{
#ifdef _OPENMP
j=omp_get_thread_num();
#endif
printf("I am the single one: %d\n",j );
}
}/*end of parallel */
/*------verify results---------------*/
for (i=0;i<NUMELEMENT;i++)
{
sum2=sum2+a[i];
}
printf("sum=%d\n",sum);
printf("sum2=%d\n",sum2);
return 0;
}
|
palshop_fmt_plug.c | /* This format is reverse engineered from InsidePro Hash Manager!
*
* This software is Copyright (c) 2016, Dhiru Kholia <dhiru.kholia at gmail.com>,
* and it is hereby released to the general public under the following terms:
* Redistribution and use in source and binary forms, with or without modification,
* are permitted.
*
* improved speed, JimF. Reduced amount of hex encoding.
*/
#if FMT_EXTERNS_H
extern struct fmt_main fmt_palshop;
#elif FMT_REGISTERS_H
john_register_one(&fmt_palshop);
#else
#include "arch.h"
#include "sha.h"
#include "md5.h"
#include <string.h>
#include "misc.h"
#include "common.h"
#include "formats.h"
#include "params.h"
#include "options.h"
#include "base64_convert.h"
#ifdef _OPENMP
#include <omp.h>
#ifndef OMP_SCALE
#define OMP_SCALE 1024
#endif
#endif
#include "memdbg.h"
#define FORMAT_LABEL "Palshop"
#define FORMAT_NAME "MD5(Palshop)"
#define ALGORITHM_NAME "MD5 + SHA1 32/" ARCH_BITS_STR
#define BENCHMARK_COMMENT ""
#define BENCHMARK_LENGTH -1
#define PLAINTEXT_LENGTH 125
#define BINARY_SIZE 10 /* 20 characters of "m2", now 10 binary bytes. */
#define SALT_SIZE 0
#define BINARY_ALIGN sizeof(ARCH_WORD_32)
#define SALT_ALIGN sizeof(int)
#define MIN_KEYS_PER_CRYPT 1
#define MAX_KEYS_PER_CRYPT 1
#define FORMAT_TAG "$palshop$"
#define TAG_LENGTH (sizeof(FORMAT_TAG) - 1)
static struct fmt_tests palshop_tests[] = {
{"$palshop$68b11ee90ed17ef14aa0f51af494c2c63ad7d281a9888cb593e", "123"},
{"ea3a8d0f4cd9e5e22ccede1ad59dd2c5c7e839348a8a519d505", "ABC"},
// http://leopard.500mb.net/HashGenerator/
{"$palshop$f2e3babc50b316e6e886f3062a37cead6d1bd16dd2bed49f7bc", "long password"},
{NULL}
};
static char (*saved_key)[PLAINTEXT_LENGTH + 1];
static ARCH_WORD_32 (*crypt_out)[ (BINARY_SIZE+sizeof(ARCH_WORD_32)-1) / sizeof(ARCH_WORD_32)];
static size_t *saved_len;
static void init(struct fmt_main *self)
{
#ifdef _OPENMP
static int omp_t = 1;
omp_t = omp_get_max_threads();
self->params.min_keys_per_crypt *= omp_t;
omp_t *= OMP_SCALE;
self->params.max_keys_per_crypt *= omp_t;
#endif
saved_key = mem_calloc(self->params.max_keys_per_crypt,
sizeof(*saved_key));
crypt_out = mem_calloc(self->params.max_keys_per_crypt,
sizeof(*crypt_out));
saved_len = mem_calloc(self->params.max_keys_per_crypt,
sizeof(*saved_len));
}
static void done(void)
{
MEM_FREE(saved_len);
MEM_FREE(crypt_out);
MEM_FREE(saved_key);
}
static int valid(char *ciphertext, struct fmt_main *self)
{
char *p = ciphertext;
if (!strncmp(ciphertext, FORMAT_TAG, TAG_LENGTH))
p = ciphertext + TAG_LENGTH;
if(!p)
return 0;
if (!ishex_oddOK(p))
return 0;
if (strlen(p) != 51)
return 0;
return 1;
}
static void *get_binary(char *ciphertext)
{
static union {
unsigned char c[BINARY_SIZE+1];
ARCH_WORD dummy;
} buf;
unsigned char *out = buf.c;
char *p = ciphertext;
if (!strncmp(ciphertext, FORMAT_TAG, TAG_LENGTH))
p = ciphertext + TAG_LENGTH;
++p; // skip the first 'nibble'. Take next 10 bytes.
base64_convert(p, e_b64_hex, 20, out, e_b64_raw, 10, 0, 0);
return out;
}
static int get_hash_0(int index) { return crypt_out[index][0] & 0xf; }
static int get_hash_1(int index) { return crypt_out[index][0] & 0xff; }
static int get_hash_2(int index) { return crypt_out[index][0] & 0xfff; }
static int get_hash_3(int index) { return crypt_out[index][0] & 0xffff; }
static int get_hash_4(int index) { return crypt_out[index][0] & 0xfffff; }
static int get_hash_5(int index) { return crypt_out[index][0] & 0xffffff; }
static int get_hash_6(int index) { return crypt_out[index][0] & 0x7ffffff; }
static int crypt_all(int *pcount, struct db_salt *salt)
{
const int count = *pcount;
int index = 0;
#ifdef _OPENMP
#pragma omp parallel for
#endif
for (index = 0; index < count; index++)
{
unsigned char m1[53], buffer[16+20], *cp;
int i;
MD5_CTX mctx;
SHA_CTX sctx;
// m1 = md5($p)
MD5_Init(&mctx);
MD5_Update(&mctx, saved_key[index], saved_len[index]);
MD5_Final(buffer, &mctx);
// s1 = sha1($p)
SHA1_Init(&sctx);
SHA1_Update(&sctx, saved_key[index], saved_len[index]);
SHA1_Final(buffer+16, &sctx);
// data = m1[11:] + s1[:29] + m1[0:1] // 51 bytes!
cp = m1;
*cp++ = itoa16[buffer[5]&0xF];
for (i = 6; i < 25+6; ++i) {
cp[0] = itoa16[buffer[i]>>4];
cp[1] = itoa16[buffer[i]&0xF];
cp += 2;
}
cp[-1] = itoa16[buffer[0]>>4];
// m2
MD5_Init(&mctx);
MD5_Update(&mctx, m1, 51);
MD5_Final(buffer, &mctx);
// s2 = sha1(data)
// SHA1_Init(&sctx);
// SHA1_Update(&sctx, data, 51);
// SHA1_Final((unsigned char*)crypt_out[index], &sctx);
// hex_encode((unsigned char*)crypt_out[index], 20, s1);
// hash = m2[11:] + s2[:29] + m2[0], but starting 20 bytes should be enough!
//memcpy((unsigned char*)crypt_out[index], m2 + 11, 20);
// we actually take m2[12:32] (skipping that first 'odd' byte.0
// in binary now, skipping the unneeded hex conversion.
memcpy((unsigned char*)crypt_out[index], buffer+6, 10);
}
return count;
}
static int cmp_all(void *binary, int count)
{
int index = 0;
for (; index < count; index++)
if (*((ARCH_WORD_32*)binary) == crypt_out[index][0])
return 1;
return 0;
}
static int cmp_one(void *binary, int index)
{
return !memcmp(binary, crypt_out[index], BINARY_SIZE);
}
static int cmp_exact(char *source, int index)
{
return 1;
}
static void palshop_set_key(char *key, int index)
{
saved_len[index] =
strnzcpyn(saved_key[index], key, sizeof(saved_key[index]));
}
static char *get_key(int index)
{
return saved_key[index];
}
struct fmt_main fmt_palshop = {
{
FORMAT_LABEL,
FORMAT_NAME,
ALGORITHM_NAME,
BENCHMARK_COMMENT,
BENCHMARK_LENGTH,
0,
PLAINTEXT_LENGTH,
BINARY_SIZE,
BINARY_ALIGN,
SALT_SIZE,
SALT_ALIGN,
MIN_KEYS_PER_CRYPT,
MAX_KEYS_PER_CRYPT,
FMT_CASE | FMT_8_BIT | FMT_OMP,
#if FMT_MAIN_VERSION > 11
{ NULL },
#endif
{ FORMAT_TAG },
palshop_tests
}, {
init,
done,
fmt_default_reset,
fmt_default_prepare,
valid,
fmt_default_split,
get_binary,
fmt_default_salt,
#if FMT_MAIN_VERSION > 11
{ NULL },
#endif
fmt_default_source,
{
fmt_default_binary_hash_0,
fmt_default_binary_hash_1,
fmt_default_binary_hash_2,
fmt_default_binary_hash_3,
fmt_default_binary_hash_4,
fmt_default_binary_hash_5,
fmt_default_binary_hash_6
},
fmt_default_salt_hash,
NULL,
fmt_default_set_salt,
palshop_set_key,
get_key,
fmt_default_clear_keys,
crypt_all,
{
get_hash_0,
get_hash_1,
get_hash_2,
get_hash_3,
get_hash_4,
get_hash_5,
get_hash_6
},
cmp_all,
cmp_one,
cmp_exact
}
};
#endif /* plugin stanza */
|
test_nest_lock_parallel.c | // RUN: %libomp-compile-and-run | %sort-threads | FileCheck %s
// REQUIRES: ompt
// UNSUPPORTED: gcc-4, gcc-5, gcc-6, gcc-7
#include "callback.h"
#include <omp.h>
int main()
{
omp_nest_lock_t nest_lock;
omp_init_nest_lock(&nest_lock);
#pragma omp parallel num_threads(2)
{
#pragma omp master
{
omp_set_nest_lock(&nest_lock);
print_current_address(1);
}
#pragma omp barrier
omp_test_nest_lock(&nest_lock); //should fail for non-master
print_current_address(2);
#pragma omp barrier
#pragma omp master
{
omp_unset_nest_lock(&nest_lock);
print_current_address(3);
omp_unset_nest_lock(&nest_lock);
print_current_address(4);
}
}
omp_destroy_nest_lock(&nest_lock);
// Check if libomp supports the callbacks for this test.
// CHECK-NOT: {{^}}0: Could not register callback 'ompt_callback_mutex_acquire'
// CHECK-NOT: {{^}}0: Could not register callback 'ompt_callback_mutex_acquired'
// CHECK-NOT: {{^}}0: Could not register callback 'ompt_callback_mutex_released'
// CHECK-NOT: {{^}}0: Could not register callback 'ompt_callback_nest_lock'
// CHECK: 0: NULL_POINTER=[[NULL:.*$]]
// CHECK: {{^}}[[MASTER_ID:[0-9]+]]: ompt_event_wait_nest_lock: wait_id=[[WAIT_ID:[0-9]+]], hint=0, impl={{[0-9]+}}, codeptr_ra=[[RETURN_ADDRESS:0x[0-f]+]]
// CHECK: {{^}}[[MASTER_ID]]: ompt_event_acquired_nest_lock_first: wait_id=[[WAIT_ID]], codeptr_ra=[[RETURN_ADDRESS]]
// CHECK-NEXT: {{^}}[[MASTER_ID]]: current_address={{.*}}[[RETURN_ADDRESS]]
// CHECK: {{^}}[[MASTER_ID]]: ompt_event_wait_nest_lock: wait_id=[[WAIT_ID]], hint=0, impl={{[0-9]+}}, codeptr_ra=[[RETURN_ADDRESS:0x[0-f]+]]
// CHECK: {{^}}[[MASTER_ID]]: ompt_event_acquired_nest_lock_next: wait_id=[[WAIT_ID]], codeptr_ra=[[RETURN_ADDRESS]]
// CHECK-NEXT: {{^}}[[MASTER_ID]]: current_address={{.*}}[[RETURN_ADDRESS]]
// CHECK: {{^}}[[MASTER_ID]]: ompt_event_release_nest_lock_prev: wait_id=[[WAIT_ID]], codeptr_ra=[[RETURN_ADDRESS:0x[0-f]+]]
// CHECK-NEXT: {{^}}[[MASTER_ID]]: current_address={{.*}}[[RETURN_ADDRESS]]
// CHECK: {{^}}[[MASTER_ID]]: ompt_event_release_nest_lock_last: wait_id=[[WAIT_ID]], codeptr_ra=[[RETURN_ADDRESS:0x[0-f]+]]
// CHECK-NEXT: {{^}}[[MASTER_ID]]: current_address={{.*}}[[RETURN_ADDRESS]]
// CHECK: {{^}}[[MASTER_ID]]: ompt_event_destroy_nest_lock: wait_id=[[WAIT_ID]]
// CHECK: {{^}}[[THREAD_ID:[0-9]+]]: ompt_event_wait_nest_lock: wait_id=[[WAIT_ID]], hint=0, impl={{[0-9]+}}, codeptr_ra=[[RETURN_ADDRESS:0x[0-f]+]]
// CHECK-NOT: {{^}}[[THREAD_ID]]: ompt_event_acquired_nest_lock_next: wait_id=[[WAIT_ID]]
// CHECK-NEXT: {{^}}[[THREAD_ID]]: current_address={{.*}}[[RETURN_ADDRESS]]
return 0;
}
|
c-parser.c | /* Parser for C and Objective-C.
Copyright (C) 1987, 1988, 1989, 1992, 1993, 1994, 1995, 1996, 1997, 1998,
1999, 2000, 2001, 2002, 2003, 2004, 2005, 2007, 2008, 2009, 2010, 2011
Free Software Foundation, Inc.
Parser actions based on the old Bison parser; structure somewhat
influenced by and fragments based on the C++ parser.
This file is part of GCC.
GCC is free software; you can redistribute it and/or modify it under
the terms of the GNU General Public License as published by the Free
Software Foundation; either version 3, or (at your option) any later
version.
GCC is distributed in the hope that it will be useful, but WITHOUT ANY
WARRANTY; without even the implied warranty of MERCHANTABILITY or
FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
for more details.
You should have received a copy of the GNU General Public License
along with GCC; see the file COPYING3. If not see
<http://www.gnu.org/licenses/>. */
/* TODO:
Make sure all relevant comments, and all relevant code from all
actions, brought over from old parser. Verify exact correspondence
of syntax accepted.
Add testcases covering every input symbol in every state in old and
new parsers.
Include full syntax for GNU C, including erroneous cases accepted
with error messages, in syntax productions in comments.
Make more diagnostics in the front end generally take an explicit
location rather than implicitly using input_location. */
#include "config.h"
#include "system.h"
#include "coretypes.h"
#include "tm.h" /* For rtl.h: needs enum reg_class. */
#include "tree.h"
#include "langhooks.h"
#include "input.h"
#include "cpplib.h"
#include "timevar.h"
#include "c-family/c-pragma.h"
#include "c-tree.h"
#include "flags.h"
#include "output.h"
#include "ggc.h"
#include "c-family/c-common.h"
#include "c-family/c-objc.h"
#include "vec.h"
#include "target.h"
#include "cgraph.h"
#include "plugin.h"
/* Initialization routine for this file. */
void
c_parse_init (void)
{
/* The only initialization required is of the reserved word
identifiers. */
unsigned int i;
tree id;
int mask = 0;
/* Make sure RID_MAX hasn't grown past the 8 bits used to hold the keyword in
the c_token structure. */
gcc_assert (RID_MAX <= 255);
mask |= D_CXXONLY;
if (!flag_isoc99)
mask |= D_C99;
if (flag_no_asm)
{
mask |= D_ASM | D_EXT;
if (!flag_isoc99)
mask |= D_EXT89;
}
if (!c_dialect_objc ())
mask |= D_OBJC | D_CXX_OBJC;
ridpointers = ggc_alloc_cleared_vec_tree ((int) RID_MAX);
for (i = 0; i < num_c_common_reswords; i++)
{
/* If a keyword is disabled, do not enter it into the table
and so create a canonical spelling that isn't a keyword. */
if (c_common_reswords[i].disable & mask)
{
if (warn_cxx_compat
&& (c_common_reswords[i].disable & D_CXXWARN))
{
id = get_identifier (c_common_reswords[i].word);
C_SET_RID_CODE (id, RID_CXX_COMPAT_WARN);
C_IS_RESERVED_WORD (id) = 1;
}
continue;
}
id = get_identifier (c_common_reswords[i].word);
C_SET_RID_CODE (id, c_common_reswords[i].rid);
C_IS_RESERVED_WORD (id) = 1;
ridpointers [(int) c_common_reswords[i].rid] = id;
}
}
/* The C lexer intermediates between the lexer in cpplib and c-lex.c
and the C parser. Unlike the C++ lexer, the parser structure
stores the lexer information instead of using a separate structure.
Identifiers are separated into ordinary identifiers, type names,
keywords and some other Objective-C types of identifiers, and some
look-ahead is maintained.
??? It might be a good idea to lex the whole file up front (as for
C++). It would then be possible to share more of the C and C++
lexer code, if desired. */
/* The following local token type is used. */
/* A keyword. */
#define CPP_KEYWORD ((enum cpp_ttype) (N_TTYPES + 1))
/* More information about the type of a CPP_NAME token. */
typedef enum c_id_kind {
/* An ordinary identifier. */
C_ID_ID,
/* An identifier declared as a typedef name. */
C_ID_TYPENAME,
/* An identifier declared as an Objective-C class name. */
C_ID_CLASSNAME,
/* An address space identifier. */
C_ID_ADDRSPACE,
/* Not an identifier. */
C_ID_NONE
} c_id_kind;
/* A single C token after string literal concatenation and conversion
of preprocessing tokens to tokens. */
typedef struct GTY (()) c_token {
/* The kind of token. */
ENUM_BITFIELD (cpp_ttype, type, 8);
/* If this token is a CPP_NAME, this value indicates whether also
declared as some kind of type. Otherwise, it is C_ID_NONE. */
ENUM_BITFIELD (c_id_kind, id_kind, 8);
/* If this token is a keyword, this value indicates which keyword.
Otherwise, this value is RID_MAX. */
ENUM_BITFIELD (rid, keyword, 8);
/* If this token is a CPP_PRAGMA, this indicates the pragma that
was seen. Otherwise it is PRAGMA_NONE. */
ENUM_BITFIELD (pragma_kind, pragma_kind, 8);
/* The location at which this token was found. */
location_t location;
/* The value associated with this token, if any. */
tree value;
} c_token;
/* A parser structure recording information about the state and
context of parsing. Includes lexer information with up to two
tokens of look-ahead; more are not needed for C. */
typedef struct GTY(()) c_parser {
/* The look-ahead tokens. */
c_token tokens[2];
/* How many look-ahead tokens are available (0, 1 or 2). */
short tokens_avail;
/* True if a syntax error is being recovered from; false otherwise.
c_parser_error sets this flag. It should clear this flag when
enough tokens have been consumed to recover from the error. */
BOOL_BITFIELD error : 1;
/* True if we're processing a pragma, and shouldn't automatically
consume CPP_PRAGMA_EOL. */
BOOL_BITFIELD in_pragma : 1;
/* True if we're parsing the outermost block of an if statement. */
BOOL_BITFIELD in_if_block : 1;
/* True if we want to lex an untranslated string. */
BOOL_BITFIELD lex_untranslated_string : 1;
/* Objective-C specific parser/lexer information. */
/* True if we are in a context where the Objective-C "PQ" keywords
are considered keywords. */
BOOL_BITFIELD objc_pq_context : 1;
/* True if we are parsing a (potential) Objective-C foreach
statement. This is set to true after we parsed 'for (' and while
we wait for 'in' or ';' to decide if it's a standard C for loop or an
Objective-C foreach loop. */
BOOL_BITFIELD objc_could_be_foreach_context : 1;
/* The following flag is needed to contextualize Objective-C lexical
analysis. In some cases (e.g., 'int NSObject;'), it is
undesirable to bind an identifier to an Objective-C class, even
if a class with that name exists. */
BOOL_BITFIELD objc_need_raw_identifier : 1;
/* True if we are in a context where the Objective-C "Property attribute"
keywords are valid. */
BOOL_BITFIELD objc_property_attr_context : 1;
} c_parser;
/* The actual parser and external interface. ??? Does this need to be
garbage-collected? */
static GTY (()) c_parser *the_parser;
/* Read in and lex a single token, storing it in *TOKEN. */
static void
c_lex_one_token (c_parser *parser, c_token *token)
{
timevar_push (TV_LEX);
token->type = c_lex_with_flags (&token->value, &token->location, NULL,
(parser->lex_untranslated_string
? C_LEX_STRING_NO_TRANSLATE : 0));
token->id_kind = C_ID_NONE;
token->keyword = RID_MAX;
token->pragma_kind = PRAGMA_NONE;
switch (token->type)
{
case CPP_NAME:
{
tree decl;
bool objc_force_identifier = parser->objc_need_raw_identifier;
if (c_dialect_objc ())
parser->objc_need_raw_identifier = false;
if (C_IS_RESERVED_WORD (token->value))
{
enum rid rid_code = C_RID_CODE (token->value);
if (rid_code == RID_CXX_COMPAT_WARN)
{
warning_at (token->location,
OPT_Wc___compat,
"identifier %qE conflicts with C++ keyword",
token->value);
}
else if (rid_code >= RID_FIRST_ADDR_SPACE
&& rid_code <= RID_LAST_ADDR_SPACE)
{
token->id_kind = C_ID_ADDRSPACE;
token->keyword = rid_code;
break;
}
else if (c_dialect_objc () && OBJC_IS_PQ_KEYWORD (rid_code))
{
/* We found an Objective-C "pq" keyword (in, out,
inout, bycopy, byref, oneway). They need special
care because the interpretation depends on the
context. */
if (parser->objc_pq_context)
{
token->type = CPP_KEYWORD;
token->keyword = rid_code;
break;
}
else if (parser->objc_could_be_foreach_context
&& rid_code == RID_IN)
{
/* We are in Objective-C, inside a (potential)
foreach context (which means after having
parsed 'for (', but before having parsed ';'),
and we found 'in'. We consider it the keyword
which terminates the declaration at the
beginning of a foreach-statement. Note that
this means you can't use 'in' for anything else
in that context; in particular, in Objective-C
you can't use 'in' as the name of the running
variable in a C for loop. We could potentially
try to add code here to disambiguate, but it
seems a reasonable limitation. */
token->type = CPP_KEYWORD;
token->keyword = rid_code;
break;
}
/* Else, "pq" keywords outside of the "pq" context are
not keywords, and we fall through to the code for
normal tokens. */
}
else if (c_dialect_objc () && OBJC_IS_PATTR_KEYWORD (rid_code))
{
/* We found an Objective-C "property attribute"
keyword (getter, setter, readonly, etc). These are
only valid in the property context. */
if (parser->objc_property_attr_context)
{
token->type = CPP_KEYWORD;
token->keyword = rid_code;
break;
}
/* Else they are not special keywords.
*/
}
else if (c_dialect_objc ()
&& (OBJC_IS_AT_KEYWORD (rid_code)
|| OBJC_IS_CXX_KEYWORD (rid_code)))
{
/* We found one of the Objective-C "@" keywords (defs,
selector, synchronized, etc) or one of the
Objective-C "cxx" keywords (class, private,
protected, public, try, catch, throw) without a
preceding '@' sign. Do nothing and fall through to
the code for normal tokens (in C++ we would still
consider the CXX ones keywords, but not in C). */
;
}
else
{
token->type = CPP_KEYWORD;
token->keyword = rid_code;
break;
}
}
decl = lookup_name (token->value);
if (decl)
{
if (TREE_CODE (decl) == TYPE_DECL)
{
token->id_kind = C_ID_TYPENAME;
break;
}
}
else if (c_dialect_objc ())
{
tree objc_interface_decl = objc_is_class_name (token->value);
/* Objective-C class names are in the same namespace as
variables and typedefs, and hence are shadowed by local
declarations. */
if (objc_interface_decl
&& (global_bindings_p ()
|| (!objc_force_identifier && !decl)))
{
token->value = objc_interface_decl;
token->id_kind = C_ID_CLASSNAME;
break;
}
}
token->id_kind = C_ID_ID;
}
break;
case CPP_AT_NAME:
/* This only happens in Objective-C; it must be a keyword. */
token->type = CPP_KEYWORD;
switch (C_RID_CODE (token->value))
{
/* Replace 'class' with '@class', 'private' with '@private',
etc. This prevents confusion with the C++ keyword
'class', and makes the tokens consistent with other
Objective-C 'AT' keywords. For example '@class' is
reported as RID_AT_CLASS which is consistent with
'@synchronized', which is reported as
RID_AT_SYNCHRONIZED.
*/
case RID_CLASS: token->keyword = RID_AT_CLASS; break;
case RID_PRIVATE: token->keyword = RID_AT_PRIVATE; break;
case RID_PROTECTED: token->keyword = RID_AT_PROTECTED; break;
case RID_PUBLIC: token->keyword = RID_AT_PUBLIC; break;
case RID_THROW: token->keyword = RID_AT_THROW; break;
case RID_TRY: token->keyword = RID_AT_TRY; break;
case RID_CATCH: token->keyword = RID_AT_CATCH; break;
default: token->keyword = C_RID_CODE (token->value);
}
break;
case CPP_COLON:
case CPP_COMMA:
case CPP_CLOSE_PAREN:
case CPP_SEMICOLON:
/* These tokens may affect the interpretation of any identifiers
following, if doing Objective-C. */
if (c_dialect_objc ())
parser->objc_need_raw_identifier = false;
break;
case CPP_PRAGMA:
/* We smuggled the cpp_token->u.pragma value in an INTEGER_CST. */
token->pragma_kind = (enum pragma_kind) TREE_INT_CST_LOW (token->value);
token->value = NULL;
break;
default:
break;
}
timevar_pop (TV_LEX);
}
/* Return a pointer to the next token from PARSER, reading it in if
necessary. */
static inline c_token *
c_parser_peek_token (c_parser *parser)
{
if (parser->tokens_avail == 0)
{
c_lex_one_token (parser, &parser->tokens[0]);
parser->tokens_avail = 1;
}
return &parser->tokens[0];
}
/* Return true if the next token from PARSER has the indicated
TYPE. */
static inline bool
c_parser_next_token_is (c_parser *parser, enum cpp_ttype type)
{
return c_parser_peek_token (parser)->type == type;
}
/* Return true if the next token from PARSER does not have the
indicated TYPE. */
static inline bool
c_parser_next_token_is_not (c_parser *parser, enum cpp_ttype type)
{
return !c_parser_next_token_is (parser, type);
}
/* Return true if the next token from PARSER is the indicated
KEYWORD. */
static inline bool
c_parser_next_token_is_keyword (c_parser *parser, enum rid keyword)
{
return c_parser_peek_token (parser)->keyword == keyword;
}
/* Return a pointer to the next-but-one token from PARSER, reading it
in if necessary. The next token is already read in. */
static c_token *
c_parser_peek_2nd_token (c_parser *parser)
{
if (parser->tokens_avail >= 2)
return &parser->tokens[1];
gcc_assert (parser->tokens_avail == 1);
gcc_assert (parser->tokens[0].type != CPP_EOF);
gcc_assert (parser->tokens[0].type != CPP_PRAGMA_EOL);
c_lex_one_token (parser, &parser->tokens[1]);
parser->tokens_avail = 2;
return &parser->tokens[1];
}
/* Return true if TOKEN can start a type name,
false otherwise. */
static bool
c_token_starts_typename (c_token *token)
{
switch (token->type)
{
case CPP_NAME:
switch (token->id_kind)
{
case C_ID_ID:
return false;
case C_ID_ADDRSPACE:
return true;
case C_ID_TYPENAME:
return true;
case C_ID_CLASSNAME:
gcc_assert (c_dialect_objc ());
return true;
default:
gcc_unreachable ();
}
case CPP_KEYWORD:
switch (token->keyword)
{
case RID_UNSIGNED:
case RID_LONG:
case RID_INT128:
case RID_SHORT:
case RID_SIGNED:
case RID_COMPLEX:
case RID_INT:
case RID_CHAR:
case RID_FLOAT:
case RID_DOUBLE:
case RID_VOID:
case RID_DFLOAT32:
case RID_DFLOAT64:
case RID_DFLOAT128:
case RID_BOOL:
case RID_ENUM:
case RID_STRUCT:
case RID_UNION:
case RID_TYPEOF:
case RID_CONST:
case RID_VOLATILE:
case RID_RESTRICT:
case RID_ATTRIBUTE:
case RID_FRACT:
case RID_ACCUM:
case RID_SAT:
return true;
default:
return false;
}
case CPP_LESS:
if (c_dialect_objc ())
return true;
return false;
default:
return false;
}
}
enum c_lookahead_kind {
/* Always treat unknown identifiers as typenames. */
cla_prefer_type,
/* Could be parsing a nonabstract declarator. Only treat an identifier
as a typename if followed by another identifier or a star. */
cla_nonabstract_decl,
/* Never treat identifiers as typenames. */
cla_prefer_id
};
/* Return true if the next token from PARSER can start a type name,
false otherwise. LA specifies how to do lookahead in order to
detect unknown type names. If unsure, pick CLA_PREFER_ID. */
static inline bool
c_parser_next_tokens_start_typename (c_parser *parser, enum c_lookahead_kind la)
{
c_token *token = c_parser_peek_token (parser);
if (c_token_starts_typename (token))
return true;
/* Try a bit harder to detect an unknown typename. */
if (la != cla_prefer_id
&& token->type == CPP_NAME
&& token->id_kind == C_ID_ID
/* Do not try too hard when we could have "object in array". */
&& !parser->objc_could_be_foreach_context
&& (la == cla_prefer_type
|| c_parser_peek_2nd_token (parser)->type == CPP_NAME
|| c_parser_peek_2nd_token (parser)->type == CPP_MULT)
/* Only unknown identifiers. */
&& !lookup_name (token->value))
return true;
return false;
}
/* Return true if TOKEN is a type qualifier, false otherwise. */
static bool
c_token_is_qualifier (c_token *token)
{
switch (token->type)
{
case CPP_NAME:
switch (token->id_kind)
{
case C_ID_ADDRSPACE:
return true;
default:
return false;
}
case CPP_KEYWORD:
switch (token->keyword)
{
case RID_CONST:
case RID_VOLATILE:
case RID_RESTRICT:
case RID_ATTRIBUTE:
return true;
default:
return false;
}
case CPP_LESS:
return false;
default:
gcc_unreachable ();
}
}
/* Return true if the next token from PARSER is a type qualifier,
false otherwise. */
static inline bool
c_parser_next_token_is_qualifier (c_parser *parser)
{
c_token *token = c_parser_peek_token (parser);
return c_token_is_qualifier (token);
}
/* Return true if TOKEN can start declaration specifiers, false
otherwise. */
static bool
c_token_starts_declspecs (c_token *token)
{
switch (token->type)
{
case CPP_NAME:
switch (token->id_kind)
{
case C_ID_ID:
return false;
case C_ID_ADDRSPACE:
return true;
case C_ID_TYPENAME:
return true;
case C_ID_CLASSNAME:
gcc_assert (c_dialect_objc ());
return true;
default:
gcc_unreachable ();
}
case CPP_KEYWORD:
switch (token->keyword)
{
case RID_STATIC:
case RID_EXTERN:
case RID_REGISTER:
case RID_TYPEDEF:
case RID_INLINE:
case RID_AUTO:
case RID_THREAD:
case RID_UNSIGNED:
case RID_LONG:
case RID_INT128:
case RID_SHORT:
case RID_SIGNED:
case RID_COMPLEX:
case RID_INT:
case RID_CHAR:
case RID_FLOAT:
case RID_DOUBLE:
case RID_VOID:
case RID_DFLOAT32:
case RID_DFLOAT64:
case RID_DFLOAT128:
case RID_BOOL:
case RID_ENUM:
case RID_STRUCT:
case RID_UNION:
case RID_TYPEOF:
case RID_CONST:
case RID_VOLATILE:
case RID_RESTRICT:
case RID_ATTRIBUTE:
case RID_FRACT:
case RID_ACCUM:
case RID_SAT:
return true;
default:
return false;
}
case CPP_LESS:
if (c_dialect_objc ())
return true;
return false;
default:
return false;
}
}
/* Return true if TOKEN can start declaration specifiers or a static
assertion, false otherwise. */
static bool
c_token_starts_declaration (c_token *token)
{
if (c_token_starts_declspecs (token)
|| token->keyword == RID_STATIC_ASSERT)
return true;
else
return false;
}
/* Return true if the next token from PARSER can start declaration
specifiers, false otherwise. */
static inline bool
c_parser_next_token_starts_declspecs (c_parser *parser)
{
c_token *token = c_parser_peek_token (parser);
/* In Objective-C, a classname normally starts a declspecs unless it
is immediately followed by a dot. In that case, it is the
Objective-C 2.0 "dot-syntax" for class objects, ie, calls the
setter/getter on the class. c_token_starts_declspecs() can't
differentiate between the two cases because it only checks the
current token, so we have a special check here. */
if (c_dialect_objc ()
&& token->type == CPP_NAME
&& token->id_kind == C_ID_CLASSNAME
&& c_parser_peek_2nd_token (parser)->type == CPP_DOT)
return false;
return c_token_starts_declspecs (token);
}
/* Return true if the next tokens from PARSER can start declaration
specifiers or a static assertion, false otherwise. */
static inline bool
c_parser_next_tokens_start_declaration (c_parser *parser)
{
c_token *token = c_parser_peek_token (parser);
/* Same as above. */
if (c_dialect_objc ()
&& token->type == CPP_NAME
&& token->id_kind == C_ID_CLASSNAME
&& c_parser_peek_2nd_token (parser)->type == CPP_DOT)
return false;
/* Labels do not start declarations. */
if (token->type == CPP_NAME
&& c_parser_peek_2nd_token (parser)->type == CPP_COLON)
return false;
if (c_token_starts_declaration (token))
return true;
if (c_parser_next_tokens_start_typename (parser, cla_nonabstract_decl))
return true;
return false;
}
/* Consume the next token from PARSER. */
static void
c_parser_consume_token (c_parser *parser)
{
gcc_assert (parser->tokens_avail >= 1);
gcc_assert (parser->tokens[0].type != CPP_EOF);
gcc_assert (!parser->in_pragma || parser->tokens[0].type != CPP_PRAGMA_EOL);
gcc_assert (parser->error || parser->tokens[0].type != CPP_PRAGMA);
if (parser->tokens_avail == 2)
parser->tokens[0] = parser->tokens[1];
parser->tokens_avail--;
}
/* Expect the current token to be a #pragma. Consume it and remember
that we've begun parsing a pragma. */
static void
c_parser_consume_pragma (c_parser *parser)
{
gcc_assert (!parser->in_pragma);
gcc_assert (parser->tokens_avail >= 1);
gcc_assert (parser->tokens[0].type == CPP_PRAGMA);
if (parser->tokens_avail == 2)
parser->tokens[0] = parser->tokens[1];
parser->tokens_avail--;
parser->in_pragma = true;
}
/* Update the globals input_location and in_system_header from
TOKEN. */
static inline void
c_parser_set_source_position_from_token (c_token *token)
{
if (token->type != CPP_EOF)
{
input_location = token->location;
}
}
/* Issue a diagnostic of the form
FILE:LINE: MESSAGE before TOKEN
where TOKEN is the next token in the input stream of PARSER.
MESSAGE (specified by the caller) is usually of the form "expected
OTHER-TOKEN".
Do not issue a diagnostic if still recovering from an error.
??? This is taken from the C++ parser, but building up messages in
this way is not i18n-friendly and some other approach should be
used. */
static void
c_parser_error (c_parser *parser, const char *gmsgid)
{
c_token *token = c_parser_peek_token (parser);
if (parser->error)
return;
parser->error = true;
if (!gmsgid)
return;
/* This diagnostic makes more sense if it is tagged to the line of
the token we just peeked at. */
c_parser_set_source_position_from_token (token);
c_parse_error (gmsgid,
/* Because c_parse_error does not understand
CPP_KEYWORD, keywords are treated like
identifiers. */
(token->type == CPP_KEYWORD ? CPP_NAME : token->type),
/* ??? The C parser does not save the cpp flags of a
token, we need to pass 0 here and we will not get
the source spelling of some tokens but rather the
canonical spelling. */
token->value, /*flags=*/0);
}
/* If the next token is of the indicated TYPE, consume it. Otherwise,
issue the error MSGID. If MSGID is NULL then a message has already
been produced and no message will be produced this time. Returns
true if found, false otherwise. */
static bool
c_parser_require (c_parser *parser,
enum cpp_ttype type,
const char *msgid)
{
if (c_parser_next_token_is (parser, type))
{
c_parser_consume_token (parser);
return true;
}
else
{
c_parser_error (parser, msgid);
return false;
}
}
/* If the next token is the indicated keyword, consume it. Otherwise,
issue the error MSGID. Returns true if found, false otherwise. */
static bool
c_parser_require_keyword (c_parser *parser,
enum rid keyword,
const char *msgid)
{
if (c_parser_next_token_is_keyword (parser, keyword))
{
c_parser_consume_token (parser);
return true;
}
else
{
c_parser_error (parser, msgid);
return false;
}
}
/* Like c_parser_require, except that tokens will be skipped until the
desired token is found. An error message is still produced if the
next token is not as expected. If MSGID is NULL then a message has
already been produced and no message will be produced this
time. */
static void
c_parser_skip_until_found (c_parser *parser,
enum cpp_ttype type,
const char *msgid)
{
unsigned nesting_depth = 0;
if (c_parser_require (parser, type, msgid))
return;
/* Skip tokens until the desired token is found. */
while (true)
{
/* Peek at the next token. */
c_token *token = c_parser_peek_token (parser);
/* If we've reached the token we want, consume it and stop. */
if (token->type == type && !nesting_depth)
{
c_parser_consume_token (parser);
break;
}
/* If we've run out of tokens, stop. */
if (token->type == CPP_EOF)
return;
if (token->type == CPP_PRAGMA_EOL && parser->in_pragma)
return;
if (token->type == CPP_OPEN_BRACE
|| token->type == CPP_OPEN_PAREN
|| token->type == CPP_OPEN_SQUARE)
++nesting_depth;
else if (token->type == CPP_CLOSE_BRACE
|| token->type == CPP_CLOSE_PAREN
|| token->type == CPP_CLOSE_SQUARE)
{
if (nesting_depth-- == 0)
break;
}
/* Consume this token. */
c_parser_consume_token (parser);
}
parser->error = false;
}
/* Skip tokens until the end of a parameter is found, but do not
consume the comma, semicolon or closing delimiter. */
static void
c_parser_skip_to_end_of_parameter (c_parser *parser)
{
unsigned nesting_depth = 0;
while (true)
{
c_token *token = c_parser_peek_token (parser);
if ((token->type == CPP_COMMA || token->type == CPP_SEMICOLON)
&& !nesting_depth)
break;
/* If we've run out of tokens, stop. */
if (token->type == CPP_EOF)
return;
if (token->type == CPP_PRAGMA_EOL && parser->in_pragma)
return;
if (token->type == CPP_OPEN_BRACE
|| token->type == CPP_OPEN_PAREN
|| token->type == CPP_OPEN_SQUARE)
++nesting_depth;
else if (token->type == CPP_CLOSE_BRACE
|| token->type == CPP_CLOSE_PAREN
|| token->type == CPP_CLOSE_SQUARE)
{
if (nesting_depth-- == 0)
break;
}
/* Consume this token. */
c_parser_consume_token (parser);
}
parser->error = false;
}
/* Expect to be at the end of the pragma directive and consume an
end of line marker. */
static void
c_parser_skip_to_pragma_eol (c_parser *parser)
{
gcc_assert (parser->in_pragma);
parser->in_pragma = false;
if (!c_parser_require (parser, CPP_PRAGMA_EOL, "expected end of line"))
while (true)
{
c_token *token = c_parser_peek_token (parser);
if (token->type == CPP_EOF)
break;
if (token->type == CPP_PRAGMA_EOL)
{
c_parser_consume_token (parser);
break;
}
c_parser_consume_token (parser);
}
parser->error = false;
}
/* Skip tokens until we have consumed an entire block, or until we
have consumed a non-nested ';'. */
static void
c_parser_skip_to_end_of_block_or_statement (c_parser *parser)
{
unsigned nesting_depth = 0;
bool save_error = parser->error;
while (true)
{
c_token *token;
/* Peek at the next token. */
token = c_parser_peek_token (parser);
switch (token->type)
{
case CPP_EOF:
return;
case CPP_PRAGMA_EOL:
if (parser->in_pragma)
return;
break;
case CPP_SEMICOLON:
/* If the next token is a ';', we have reached the
end of the statement. */
if (!nesting_depth)
{
/* Consume the ';'. */
c_parser_consume_token (parser);
goto finished;
}
break;
case CPP_CLOSE_BRACE:
/* If the next token is a non-nested '}', then we have
reached the end of the current block. */
if (nesting_depth == 0 || --nesting_depth == 0)
{
c_parser_consume_token (parser);
goto finished;
}
break;
case CPP_OPEN_BRACE:
/* If it the next token is a '{', then we are entering a new
block. Consume the entire block. */
++nesting_depth;
break;
case CPP_PRAGMA:
/* If we see a pragma, consume the whole thing at once. We
have some safeguards against consuming pragmas willy-nilly.
Normally, we'd expect to be here with parser->error set,
which disables these safeguards. But it's possible to get
here for secondary error recovery, after parser->error has
been cleared. */
c_parser_consume_pragma (parser);
c_parser_skip_to_pragma_eol (parser);
parser->error = save_error;
continue;
default:
break;
}
c_parser_consume_token (parser);
}
finished:
parser->error = false;
}
/* CPP's options (initialized by c-opts.c). */
extern cpp_options *cpp_opts;
/* Save the warning flags which are controlled by __extension__. */
static inline int
disable_extension_diagnostics (void)
{
int ret = (pedantic
| (warn_pointer_arith << 1)
| (warn_traditional << 2)
| (flag_iso << 3)
| (warn_long_long << 4)
| (warn_cxx_compat << 5));
cpp_opts->cpp_pedantic = pedantic = 0;
warn_pointer_arith = 0;
cpp_opts->cpp_warn_traditional = warn_traditional = 0;
flag_iso = 0;
cpp_opts->cpp_warn_long_long = warn_long_long = 0;
warn_cxx_compat = 0;
return ret;
}
/* Restore the warning flags which are controlled by __extension__.
FLAGS is the return value from disable_extension_diagnostics. */
static inline void
restore_extension_diagnostics (int flags)
{
cpp_opts->cpp_pedantic = pedantic = flags & 1;
warn_pointer_arith = (flags >> 1) & 1;
cpp_opts->cpp_warn_traditional = warn_traditional = (flags >> 2) & 1;
flag_iso = (flags >> 3) & 1;
cpp_opts->cpp_warn_long_long = warn_long_long = (flags >> 4) & 1;
warn_cxx_compat = (flags >> 5) & 1;
}
/* Possibly kinds of declarator to parse. */
typedef enum c_dtr_syn {
/* A normal declarator with an identifier. */
C_DTR_NORMAL,
/* An abstract declarator (maybe empty). */
C_DTR_ABSTRACT,
/* A parameter declarator: may be either, but after a type name does
not redeclare a typedef name as an identifier if it can
alternatively be interpreted as a typedef name; see DR#009,
applied in C90 TC1, omitted from C99 and reapplied in C99 TC2
following DR#249. For example, given a typedef T, "int T" and
"int *T" are valid parameter declarations redeclaring T, while
"int (T)" and "int * (T)" and "int (T[])" and "int (T (int))" are
abstract declarators rather than involving redundant parentheses;
the same applies with attributes inside the parentheses before
"T". */
C_DTR_PARM
} c_dtr_syn;
static void c_parser_external_declaration (c_parser *);
static void c_parser_asm_definition (c_parser *);
static void c_parser_declaration_or_fndef (c_parser *, bool, bool, bool,
bool, bool, tree *);
static void c_parser_static_assert_declaration_no_semi (c_parser *);
static void c_parser_static_assert_declaration (c_parser *);
static void c_parser_declspecs (c_parser *, struct c_declspecs *, bool, bool,
bool, enum c_lookahead_kind);
static struct c_typespec c_parser_enum_specifier (c_parser *);
static struct c_typespec c_parser_struct_or_union_specifier (c_parser *);
static tree c_parser_struct_declaration (c_parser *);
static struct c_typespec c_parser_typeof_specifier (c_parser *);
static struct c_declarator *c_parser_declarator (c_parser *, bool, c_dtr_syn,
bool *);
static struct c_declarator *c_parser_direct_declarator (c_parser *, bool,
c_dtr_syn, bool *);
static struct c_declarator *c_parser_direct_declarator_inner (c_parser *,
bool,
struct c_declarator *);
static struct c_arg_info *c_parser_parms_declarator (c_parser *, bool, tree);
static struct c_arg_info *c_parser_parms_list_declarator (c_parser *, tree);
static struct c_parm *c_parser_parameter_declaration (c_parser *, tree);
static tree c_parser_simple_asm_expr (c_parser *);
static tree c_parser_attributes (c_parser *);
static struct c_type_name *c_parser_type_name (c_parser *);
static struct c_expr c_parser_initializer (c_parser *);
static struct c_expr c_parser_braced_init (c_parser *, tree, bool);
static void c_parser_initelt (c_parser *, struct obstack *);
static void c_parser_initval (c_parser *, struct c_expr *,
struct obstack *);
static tree c_parser_compound_statement (c_parser *);
static void c_parser_compound_statement_nostart (c_parser *);
static void c_parser_label (c_parser *);
static void c_parser_statement (c_parser *);
static void c_parser_statement_after_labels (c_parser *);
static void c_parser_if_statement (c_parser *);
static void c_parser_switch_statement (c_parser *);
static void c_parser_while_statement (c_parser *);
static void c_parser_do_statement (c_parser *);
static void c_parser_for_statement (c_parser *);
static tree c_parser_asm_statement (c_parser *);
static tree c_parser_asm_operands (c_parser *, bool);
static tree c_parser_asm_goto_operands (c_parser *);
static tree c_parser_asm_clobbers (c_parser *);
static struct c_expr c_parser_expr_no_commas (c_parser *, struct c_expr *);
static struct c_expr c_parser_conditional_expression (c_parser *,
struct c_expr *);
static struct c_expr c_parser_binary_expression (c_parser *, struct c_expr *);
static struct c_expr c_parser_cast_expression (c_parser *, struct c_expr *);
static struct c_expr c_parser_unary_expression (c_parser *);
static struct c_expr c_parser_sizeof_expression (c_parser *);
static struct c_expr c_parser_alignof_expression (c_parser *);
static struct c_expr c_parser_postfix_expression (c_parser *);
static struct c_expr c_parser_postfix_expression_after_paren_type (c_parser *,
struct c_type_name *,
location_t);
static struct c_expr c_parser_postfix_expression_after_primary (c_parser *,
location_t loc,
struct c_expr);
static struct c_expr c_parser_expression (c_parser *);
static struct c_expr c_parser_expression_conv (c_parser *);
static VEC(tree,gc) *c_parser_expr_list (c_parser *, bool, bool,
VEC(tree,gc) **);
static void c_parser_omp_construct (c_parser *);
static void c_parser_omp_threadprivate (c_parser *);
static void c_parser_omp_barrier (c_parser *);
static void c_parser_omp_flush (c_parser *);
static void c_parser_omp_taskwait (c_parser *);
enum pragma_context { pragma_external, pragma_stmt, pragma_compound };
static bool c_parser_pragma (c_parser *, enum pragma_context);
/* These Objective-C parser functions are only ever called when
compiling Objective-C. */
static void c_parser_objc_class_definition (c_parser *, tree);
static void c_parser_objc_class_instance_variables (c_parser *);
static void c_parser_objc_class_declaration (c_parser *);
static void c_parser_objc_alias_declaration (c_parser *);
static void c_parser_objc_protocol_definition (c_parser *, tree);
static bool c_parser_objc_method_type (c_parser *);
static void c_parser_objc_method_definition (c_parser *);
static void c_parser_objc_methodprotolist (c_parser *);
static void c_parser_objc_methodproto (c_parser *);
static tree c_parser_objc_method_decl (c_parser *, bool, tree *);
static tree c_parser_objc_type_name (c_parser *);
static tree c_parser_objc_protocol_refs (c_parser *);
static void c_parser_objc_try_catch_finally_statement (c_parser *);
static void c_parser_objc_synchronized_statement (c_parser *);
static tree c_parser_objc_selector (c_parser *);
static tree c_parser_objc_selector_arg (c_parser *);
static tree c_parser_objc_receiver (c_parser *);
static tree c_parser_objc_message_args (c_parser *);
static tree c_parser_objc_keywordexpr (c_parser *);
static void c_parser_objc_at_property_declaration (c_parser *);
static void c_parser_objc_at_synthesize_declaration (c_parser *);
static void c_parser_objc_at_dynamic_declaration (c_parser *);
static bool c_parser_objc_diagnose_bad_element_prefix
(c_parser *, struct c_declspecs *);
/* Parse a translation unit (C90 6.7, C99 6.9).
translation-unit:
external-declarations
external-declarations:
external-declaration
external-declarations external-declaration
GNU extensions:
translation-unit:
empty
*/
static void
c_parser_translation_unit (c_parser *parser)
{
if (c_parser_next_token_is (parser, CPP_EOF))
{
pedwarn (c_parser_peek_token (parser)->location, OPT_pedantic,
"ISO C forbids an empty translation unit");
}
else
{
void *obstack_position = obstack_alloc (&parser_obstack, 0);
mark_valid_location_for_stdc_pragma (false);
do
{
ggc_collect ();
c_parser_external_declaration (parser);
obstack_free (&parser_obstack, obstack_position);
}
while (c_parser_next_token_is_not (parser, CPP_EOF));
}
}
/* Parse an external declaration (C90 6.7, C99 6.9).
external-declaration:
function-definition
declaration
GNU extensions:
external-declaration:
asm-definition
;
__extension__ external-declaration
Objective-C:
external-declaration:
objc-class-definition
objc-class-declaration
objc-alias-declaration
objc-protocol-definition
objc-method-definition
@end
*/
static void
c_parser_external_declaration (c_parser *parser)
{
int ext;
switch (c_parser_peek_token (parser)->type)
{
case CPP_KEYWORD:
switch (c_parser_peek_token (parser)->keyword)
{
case RID_EXTENSION:
ext = disable_extension_diagnostics ();
c_parser_consume_token (parser);
c_parser_external_declaration (parser);
restore_extension_diagnostics (ext);
break;
case RID_ASM:
c_parser_asm_definition (parser);
break;
case RID_AT_INTERFACE:
case RID_AT_IMPLEMENTATION:
gcc_assert (c_dialect_objc ());
c_parser_objc_class_definition (parser, NULL_TREE);
break;
case RID_AT_CLASS:
gcc_assert (c_dialect_objc ());
c_parser_objc_class_declaration (parser);
break;
case RID_AT_ALIAS:
gcc_assert (c_dialect_objc ());
c_parser_objc_alias_declaration (parser);
break;
case RID_AT_PROTOCOL:
gcc_assert (c_dialect_objc ());
c_parser_objc_protocol_definition (parser, NULL_TREE);
break;
case RID_AT_PROPERTY:
gcc_assert (c_dialect_objc ());
c_parser_objc_at_property_declaration (parser);
break;
case RID_AT_SYNTHESIZE:
gcc_assert (c_dialect_objc ());
c_parser_objc_at_synthesize_declaration (parser);
break;
case RID_AT_DYNAMIC:
gcc_assert (c_dialect_objc ());
c_parser_objc_at_dynamic_declaration (parser);
break;
case RID_AT_END:
gcc_assert (c_dialect_objc ());
c_parser_consume_token (parser);
objc_finish_implementation ();
break;
default:
goto decl_or_fndef;
}
break;
case CPP_SEMICOLON:
pedwarn (c_parser_peek_token (parser)->location, OPT_pedantic,
"ISO C does not allow extra %<;%> outside of a function");
c_parser_consume_token (parser);
break;
case CPP_PRAGMA:
mark_valid_location_for_stdc_pragma (true);
c_parser_pragma (parser, pragma_external);
mark_valid_location_for_stdc_pragma (false);
break;
case CPP_PLUS:
case CPP_MINUS:
if (c_dialect_objc ())
{
c_parser_objc_method_definition (parser);
break;
}
/* Else fall through, and yield a syntax error trying to parse
as a declaration or function definition. */
default:
decl_or_fndef:
/* A declaration or a function definition (or, in Objective-C,
an @interface or @protocol with prefix attributes). We can
only tell which after parsing the declaration specifiers, if
any, and the first declarator. */
c_parser_declaration_or_fndef (parser, true, true, true, false, true, NULL);
break;
}
}
/* Parse a declaration or function definition (C90 6.5, 6.7.1, C99
6.7, 6.9.1). If FNDEF_OK is true, a function definition is
accepted; otherwise (old-style parameter declarations) only other
declarations are accepted. If STATIC_ASSERT_OK is true, a static
assertion is accepted; otherwise (old-style parameter declarations)
it is not. If NESTED is true, we are inside a function or parsing
old-style parameter declarations; any functions encountered are
nested functions and declaration specifiers are required; otherwise
we are at top level and functions are normal functions and
declaration specifiers may be optional. If EMPTY_OK is true, empty
declarations are OK (subject to all other constraints); otherwise
(old-style parameter declarations) they are diagnosed. If
START_ATTR_OK is true, the declaration specifiers may start with
attributes; otherwise they may not.
OBJC_FOREACH_OBJECT_DECLARATION can be used to get back the parsed
declaration when parsing an Objective-C foreach statement.
declaration:
declaration-specifiers init-declarator-list[opt] ;
static_assert-declaration
function-definition:
declaration-specifiers[opt] declarator declaration-list[opt]
compound-statement
declaration-list:
declaration
declaration-list declaration
init-declarator-list:
init-declarator
init-declarator-list , init-declarator
init-declarator:
declarator simple-asm-expr[opt] attributes[opt]
declarator simple-asm-expr[opt] attributes[opt] = initializer
GNU extensions:
nested-function-definition:
declaration-specifiers declarator declaration-list[opt]
compound-statement
Objective-C:
attributes objc-class-definition
attributes objc-category-definition
attributes objc-protocol-definition
The simple-asm-expr and attributes are GNU extensions.
This function does not handle __extension__; that is handled in its
callers. ??? Following the old parser, __extension__ may start
external declarations, declarations in functions and declarations
at the start of "for" loops, but not old-style parameter
declarations.
C99 requires declaration specifiers in a function definition; the
absence is diagnosed through the diagnosis of implicit int. In GNU
C we also allow but diagnose declarations without declaration
specifiers, but only at top level (elsewhere they conflict with
other syntax).
In Objective-C, declarations of the looping variable in a foreach
statement are exceptionally terminated by 'in' (for example, 'for
(NSObject *object in array) { ... }').
OpenMP:
declaration:
threadprivate-directive */
static void
c_parser_declaration_or_fndef (c_parser *parser, bool fndef_ok,
bool static_assert_ok, bool empty_ok,
bool nested, bool start_attr_ok,
tree *objc_foreach_object_declaration)
{
struct c_declspecs *specs;
tree prefix_attrs;
tree all_prefix_attrs;
bool diagnosed_no_specs = false;
location_t here = c_parser_peek_token (parser)->location;
if (static_assert_ok
&& c_parser_next_token_is_keyword (parser, RID_STATIC_ASSERT))
{
c_parser_static_assert_declaration (parser);
return;
}
specs = build_null_declspecs ();
/* Try to detect an unknown type name when we have "A B" or "A *B". */
if (c_parser_peek_token (parser)->type == CPP_NAME
&& c_parser_peek_token (parser)->id_kind == C_ID_ID
&& (c_parser_peek_2nd_token (parser)->type == CPP_NAME
|| c_parser_peek_2nd_token (parser)->type == CPP_MULT)
&& (!nested || !lookup_name (c_parser_peek_token (parser)->value)))
{
error_at (here, "unknown type name %qE",
c_parser_peek_token (parser)->value);
/* Parse declspecs normally to get a correct pointer type, but avoid
a further "fails to be a type name" error. Refuse nested functions
since it is not how the user likely wants us to recover. */
c_parser_peek_token (parser)->type = CPP_KEYWORD;
c_parser_peek_token (parser)->keyword = RID_VOID;
c_parser_peek_token (parser)->value = error_mark_node;
fndef_ok = !nested;
}
c_parser_declspecs (parser, specs, true, true, start_attr_ok, cla_nonabstract_decl);
if (parser->error)
{
c_parser_skip_to_end_of_block_or_statement (parser);
return;
}
if (nested && !specs->declspecs_seen_p)
{
c_parser_error (parser, "expected declaration specifiers");
c_parser_skip_to_end_of_block_or_statement (parser);
return;
}
finish_declspecs (specs);
if (c_parser_next_token_is (parser, CPP_SEMICOLON))
{
if (empty_ok)
shadow_tag (specs);
else
{
shadow_tag_warned (specs, 1);
pedwarn (here, 0, "empty declaration");
}
c_parser_consume_token (parser);
return;
}
/* Provide better error recovery. Note that a type name here is usually
better diagnosed as a redeclaration. */
if (empty_ok
&& specs->typespec_kind == ctsk_tagdef
&& c_parser_next_token_starts_declspecs (parser)
&& !c_parser_next_token_is (parser, CPP_NAME))
{
c_parser_error (parser, "expected %<;%>, identifier or %<(%>");
parser->error = false;
shadow_tag_warned (specs, 1);
return;
}
else if (c_dialect_objc ())
{
/* Prefix attributes are an error on method decls. */
switch (c_parser_peek_token (parser)->type)
{
case CPP_PLUS:
case CPP_MINUS:
if (c_parser_objc_diagnose_bad_element_prefix (parser, specs))
return;
if (specs->attrs)
{
warning_at (c_parser_peek_token (parser)->location,
OPT_Wattributes,
"prefix attributes are ignored for methods");
specs->attrs = NULL_TREE;
}
if (fndef_ok)
c_parser_objc_method_definition (parser);
else
c_parser_objc_methodproto (parser);
return;
break;
default:
break;
}
/* This is where we parse 'attributes @interface ...',
'attributes @implementation ...', 'attributes @protocol ...'
(where attributes could be, for example, __attribute__
((deprecated)).
*/
switch (c_parser_peek_token (parser)->keyword)
{
case RID_AT_INTERFACE:
{
if (c_parser_objc_diagnose_bad_element_prefix (parser, specs))
return;
c_parser_objc_class_definition (parser, specs->attrs);
return;
}
break;
case RID_AT_IMPLEMENTATION:
{
if (c_parser_objc_diagnose_bad_element_prefix (parser, specs))
return;
if (specs->attrs)
{
warning_at (c_parser_peek_token (parser)->location,
OPT_Wattributes,
"prefix attributes are ignored for implementations");
specs->attrs = NULL_TREE;
}
c_parser_objc_class_definition (parser, NULL_TREE);
return;
}
break;
case RID_AT_PROTOCOL:
{
if (c_parser_objc_diagnose_bad_element_prefix (parser, specs))
return;
c_parser_objc_protocol_definition (parser, specs->attrs);
return;
}
break;
case RID_AT_ALIAS:
case RID_AT_CLASS:
case RID_AT_END:
case RID_AT_PROPERTY:
if (specs->attrs)
{
c_parser_error (parser, "unexpected attribute");
specs->attrs = NULL;
}
break;
default:
break;
}
}
pending_xref_error ();
prefix_attrs = specs->attrs;
all_prefix_attrs = prefix_attrs;
specs->attrs = NULL_TREE;
while (true)
{
struct c_declarator *declarator;
bool dummy = false;
tree fnbody;
/* Declaring either one or more declarators (in which case we
should diagnose if there were no declaration specifiers) or a
function definition (in which case the diagnostic for
implicit int suffices). */
declarator = c_parser_declarator (parser,
specs->typespec_kind != ctsk_none,
C_DTR_NORMAL, &dummy);
if (declarator == NULL)
{
c_parser_skip_to_end_of_block_or_statement (parser);
return;
}
if (c_parser_next_token_is (parser, CPP_EQ)
|| c_parser_next_token_is (parser, CPP_COMMA)
|| c_parser_next_token_is (parser, CPP_SEMICOLON)
|| c_parser_next_token_is_keyword (parser, RID_ASM)
|| c_parser_next_token_is_keyword (parser, RID_ATTRIBUTE)
|| c_parser_next_token_is_keyword (parser, RID_IN))
{
tree asm_name = NULL_TREE;
tree postfix_attrs = NULL_TREE;
if (!diagnosed_no_specs && !specs->declspecs_seen_p)
{
diagnosed_no_specs = true;
pedwarn (here, 0, "data definition has no type or storage class");
}
/* Having seen a data definition, there cannot now be a
function definition. */
fndef_ok = false;
if (c_parser_next_token_is_keyword (parser, RID_ASM))
asm_name = c_parser_simple_asm_expr (parser);
if (c_parser_next_token_is_keyword (parser, RID_ATTRIBUTE))
postfix_attrs = c_parser_attributes (parser);
if (c_parser_next_token_is (parser, CPP_EQ))
{
tree d;
struct c_expr init;
location_t init_loc;
c_parser_consume_token (parser);
/* The declaration of the variable is in effect while
its initializer is parsed. */
d = start_decl (declarator, specs, true,
chainon (postfix_attrs, all_prefix_attrs));
if (!d)
d = error_mark_node;
start_init (d, asm_name, global_bindings_p ());
init_loc = c_parser_peek_token (parser)->location;
init = c_parser_initializer (parser);
finish_init ();
if (d != error_mark_node)
{
maybe_warn_string_init (TREE_TYPE (d), init);
finish_decl (d, init_loc, init.value,
init.original_type, asm_name);
}
}
else
{
tree d = start_decl (declarator, specs, false,
chainon (postfix_attrs,
all_prefix_attrs));
if (d)
finish_decl (d, UNKNOWN_LOCATION, NULL_TREE,
NULL_TREE, asm_name);
if (c_parser_next_token_is_keyword (parser, RID_IN))
{
if (d)
*objc_foreach_object_declaration = d;
else
*objc_foreach_object_declaration = error_mark_node;
}
}
if (c_parser_next_token_is (parser, CPP_COMMA))
{
c_parser_consume_token (parser);
if (c_parser_next_token_is_keyword (parser, RID_ATTRIBUTE))
all_prefix_attrs = chainon (c_parser_attributes (parser),
prefix_attrs);
else
all_prefix_attrs = prefix_attrs;
continue;
}
else if (c_parser_next_token_is (parser, CPP_SEMICOLON))
{
c_parser_consume_token (parser);
return;
}
else if (c_parser_next_token_is_keyword (parser, RID_IN))
{
/* This can only happen in Objective-C: we found the
'in' that terminates the declaration inside an
Objective-C foreach statement. Do not consume the
token, so that the caller can use it to determine
that this indeed is a foreach context. */
return;
}
else
{
c_parser_error (parser, "expected %<,%> or %<;%>");
c_parser_skip_to_end_of_block_or_statement (parser);
return;
}
}
else if (!fndef_ok)
{
c_parser_error (parser, "expected %<=%>, %<,%>, %<;%>, "
"%<asm%> or %<__attribute__%>");
c_parser_skip_to_end_of_block_or_statement (parser);
return;
}
/* Function definition (nested or otherwise). */
if (nested)
{
pedwarn (here, OPT_pedantic, "ISO C forbids nested functions");
c_push_function_context ();
}
if (!start_function (specs, declarator, all_prefix_attrs))
{
/* This can appear in many cases looking nothing like a
function definition, so we don't give a more specific
error suggesting there was one. */
c_parser_error (parser, "expected %<=%>, %<,%>, %<;%>, %<asm%> "
"or %<__attribute__%>");
if (nested)
c_pop_function_context ();
break;
}
/* Parse old-style parameter declarations. ??? Attributes are
not allowed to start declaration specifiers here because of a
syntax conflict between a function declaration with attribute
suffix and a function definition with an attribute prefix on
first old-style parameter declaration. Following the old
parser, they are not accepted on subsequent old-style
parameter declarations either. However, there is no
ambiguity after the first declaration, nor indeed on the
first as long as we don't allow postfix attributes after a
declarator with a nonempty identifier list in a definition;
and postfix attributes have never been accepted here in
function definitions either. */
while (c_parser_next_token_is_not (parser, CPP_EOF)
&& c_parser_next_token_is_not (parser, CPP_OPEN_BRACE))
c_parser_declaration_or_fndef (parser, false, false, false,
true, false, NULL);
store_parm_decls ();
DECL_STRUCT_FUNCTION (current_function_decl)->function_start_locus
= c_parser_peek_token (parser)->location;
fnbody = c_parser_compound_statement (parser);
if (nested)
{
tree decl = current_function_decl;
/* Mark nested functions as needing static-chain initially.
lower_nested_functions will recompute it but the
DECL_STATIC_CHAIN flag is also used before that happens,
by initializer_constant_valid_p. See gcc.dg/nested-fn-2.c. */
DECL_STATIC_CHAIN (decl) = 1;
add_stmt (fnbody);
finish_function ();
c_pop_function_context ();
add_stmt (build_stmt (DECL_SOURCE_LOCATION (decl), DECL_EXPR, decl));
}
else
{
add_stmt (fnbody);
finish_function ();
}
break;
}
}
/* Parse an asm-definition (asm() outside a function body). This is a
GNU extension.
asm-definition:
simple-asm-expr ;
*/
static void
c_parser_asm_definition (c_parser *parser)
{
tree asm_str = c_parser_simple_asm_expr (parser);
if (asm_str)
cgraph_add_asm_node (asm_str);
c_parser_skip_until_found (parser, CPP_SEMICOLON, "expected %<;%>");
}
/* Parse a static assertion (C1X N1425 6.7.10).
static_assert-declaration:
static_assert-declaration-no-semi ;
*/
static void
c_parser_static_assert_declaration (c_parser *parser)
{
c_parser_static_assert_declaration_no_semi (parser);
if (parser->error
|| !c_parser_require (parser, CPP_SEMICOLON, "expected %<;%>"))
c_parser_skip_to_end_of_block_or_statement (parser);
}
/* Parse a static assertion (C1X N1425 6.7.10), without the trailing
semicolon.
static_assert-declaration-no-semi:
_Static_assert ( constant-expression , string-literal )
*/
static void
c_parser_static_assert_declaration_no_semi (c_parser *parser)
{
location_t assert_loc, value_loc;
tree value;
tree string;
gcc_assert (c_parser_next_token_is_keyword (parser, RID_STATIC_ASSERT));
assert_loc = c_parser_peek_token (parser)->location;
if (!flag_isoc1x)
{
if (flag_isoc99)
pedwarn (assert_loc, OPT_pedantic,
"ISO C99 does not support %<_Static_assert%>");
else
pedwarn (assert_loc, OPT_pedantic,
"ISO C90 does not support %<_Static_assert%>");
}
c_parser_consume_token (parser);
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
return;
value_loc = c_parser_peek_token (parser)->location;
value = c_parser_expr_no_commas (parser, NULL).value;
parser->lex_untranslated_string = true;
if (!c_parser_require (parser, CPP_COMMA, "expected %<,%>"))
{
parser->lex_untranslated_string = false;
return;
}
switch (c_parser_peek_token (parser)->type)
{
case CPP_STRING:
case CPP_STRING16:
case CPP_STRING32:
case CPP_WSTRING:
case CPP_UTF8STRING:
string = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
parser->lex_untranslated_string = false;
break;
default:
c_parser_error (parser, "expected string literal");
parser->lex_untranslated_string = false;
return;
}
c_parser_require (parser, CPP_CLOSE_PAREN, "expected %<)%>");
if (!INTEGRAL_TYPE_P (TREE_TYPE (value)))
{
error_at (value_loc, "expression in static assertion is not an integer");
return;
}
if (TREE_CODE (value) != INTEGER_CST)
{
value = c_fully_fold (value, false, NULL);
if (TREE_CODE (value) == INTEGER_CST)
pedwarn (value_loc, OPT_pedantic, "expression in static assertion "
"is not an integer constant expression");
}
if (TREE_CODE (value) != INTEGER_CST)
{
error_at (value_loc, "expression in static assertion is not constant");
return;
}
constant_expression_warning (value);
if (integer_zerop (value))
error_at (assert_loc, "static assertion failed: %E", string);
}
/* Parse some declaration specifiers (possibly none) (C90 6.5, C99
6.7), adding them to SPECS (which may already include some).
Storage class specifiers are accepted iff SCSPEC_OK; type
specifiers are accepted iff TYPESPEC_OK; attributes are accepted at
the start iff START_ATTR_OK.
declaration-specifiers:
storage-class-specifier declaration-specifiers[opt]
type-specifier declaration-specifiers[opt]
type-qualifier declaration-specifiers[opt]
function-specifier declaration-specifiers[opt]
Function specifiers (inline) are from C99, and are currently
handled as storage class specifiers, as is __thread.
C90 6.5.1, C99 6.7.1:
storage-class-specifier:
typedef
extern
static
auto
register
C99 6.7.4:
function-specifier:
inline
C90 6.5.2, C99 6.7.2:
type-specifier:
void
char
short
int
long
float
double
signed
unsigned
_Bool
_Complex
[_Imaginary removed in C99 TC2]
struct-or-union-specifier
enum-specifier
typedef-name
(_Bool and _Complex are new in C99.)
C90 6.5.3, C99 6.7.3:
type-qualifier:
const
restrict
volatile
address-space-qualifier
(restrict is new in C99.)
GNU extensions:
declaration-specifiers:
attributes declaration-specifiers[opt]
type-qualifier:
address-space
address-space:
identifier recognized by the target
storage-class-specifier:
__thread
type-specifier:
typeof-specifier
__int128
_Decimal32
_Decimal64
_Decimal128
_Fract
_Accum
_Sat
(_Fract, _Accum, and _Sat are new from ISO/IEC DTR 18037:
http://www.open-std.org/jtc1/sc22/wg14/www/docs/n1169.pdf)
Objective-C:
type-specifier:
class-name objc-protocol-refs[opt]
typedef-name objc-protocol-refs
objc-protocol-refs
*/
static void
c_parser_declspecs (c_parser *parser, struct c_declspecs *specs,
bool scspec_ok, bool typespec_ok, bool start_attr_ok,
enum c_lookahead_kind la)
{
bool attrs_ok = start_attr_ok;
bool seen_type = specs->typespec_kind != ctsk_none;
if (!typespec_ok)
gcc_assert (la == cla_prefer_id);
while (c_parser_next_token_is (parser, CPP_NAME)
|| c_parser_next_token_is (parser, CPP_KEYWORD)
|| (c_dialect_objc () && c_parser_next_token_is (parser, CPP_LESS)))
{
struct c_typespec t;
tree attrs;
location_t loc = c_parser_peek_token (parser)->location;
/* If we cannot accept a type, exit if the next token must start
one. Also, if we already have seen a tagged definition,
a typename would be an error anyway and likely the user
has simply forgotten a semicolon, so we exit. */
if ((!typespec_ok || specs->typespec_kind == ctsk_tagdef)
&& c_parser_next_tokens_start_typename (parser, la)
&& !c_parser_next_token_is_qualifier (parser))
break;
if (c_parser_next_token_is (parser, CPP_NAME))
{
tree value = c_parser_peek_token (parser)->value;
c_id_kind kind = c_parser_peek_token (parser)->id_kind;
if (kind == C_ID_ADDRSPACE)
{
addr_space_t as
= c_parser_peek_token (parser)->keyword - RID_FIRST_ADDR_SPACE;
declspecs_add_addrspace (specs, as);
c_parser_consume_token (parser);
attrs_ok = true;
continue;
}
gcc_assert (!c_parser_next_token_is_qualifier (parser));
/* If we cannot accept a type, and the next token must start one,
exit. Do the same if we already have seen a tagged definition,
since it would be an error anyway and likely the user has simply
forgotten a semicolon. */
if (seen_type || !c_parser_next_tokens_start_typename (parser, la))
break;
/* Now at an unknown typename (C_ID_ID), a C_ID_TYPENAME or
a C_ID_CLASSNAME. */
c_parser_consume_token (parser);
seen_type = true;
attrs_ok = true;
if (kind == C_ID_ID)
{
error ("unknown type name %qE", value);
t.kind = ctsk_typedef;
t.spec = error_mark_node;
}
else if (kind == C_ID_TYPENAME
&& (!c_dialect_objc ()
|| c_parser_next_token_is_not (parser, CPP_LESS)))
{
t.kind = ctsk_typedef;
/* For a typedef name, record the meaning, not the name.
In case of 'foo foo, bar;'. */
t.spec = lookup_name (value);
}
else
{
tree proto = NULL_TREE;
gcc_assert (c_dialect_objc ());
t.kind = ctsk_objc;
if (c_parser_next_token_is (parser, CPP_LESS))
proto = c_parser_objc_protocol_refs (parser);
t.spec = objc_get_protocol_qualified_type (value, proto);
}
t.expr = NULL_TREE;
t.expr_const_operands = true;
declspecs_add_type (loc, specs, t);
continue;
}
if (c_parser_next_token_is (parser, CPP_LESS))
{
/* Make "<SomeProtocol>" equivalent to "id <SomeProtocol>" -
nisse@lysator.liu.se. */
tree proto;
gcc_assert (c_dialect_objc ());
if (!typespec_ok || seen_type)
break;
proto = c_parser_objc_protocol_refs (parser);
t.kind = ctsk_objc;
t.spec = objc_get_protocol_qualified_type (NULL_TREE, proto);
t.expr = NULL_TREE;
t.expr_const_operands = true;
declspecs_add_type (loc, specs, t);
continue;
}
gcc_assert (c_parser_next_token_is (parser, CPP_KEYWORD));
switch (c_parser_peek_token (parser)->keyword)
{
case RID_STATIC:
case RID_EXTERN:
case RID_REGISTER:
case RID_TYPEDEF:
case RID_INLINE:
case RID_AUTO:
case RID_THREAD:
if (!scspec_ok)
goto out;
attrs_ok = true;
/* TODO: Distinguish between function specifiers (inline)
and storage class specifiers, either here or in
declspecs_add_scspec. */
declspecs_add_scspec (specs, c_parser_peek_token (parser)->value);
c_parser_consume_token (parser);
break;
case RID_UNSIGNED:
case RID_LONG:
case RID_INT128:
case RID_SHORT:
case RID_SIGNED:
case RID_COMPLEX:
case RID_INT:
case RID_CHAR:
case RID_FLOAT:
case RID_DOUBLE:
case RID_VOID:
case RID_DFLOAT32:
case RID_DFLOAT64:
case RID_DFLOAT128:
case RID_BOOL:
case RID_FRACT:
case RID_ACCUM:
case RID_SAT:
if (!typespec_ok)
goto out;
attrs_ok = true;
seen_type = true;
if (c_dialect_objc ())
parser->objc_need_raw_identifier = true;
t.kind = ctsk_resword;
t.spec = c_parser_peek_token (parser)->value;
t.expr = NULL_TREE;
t.expr_const_operands = true;
declspecs_add_type (loc, specs, t);
c_parser_consume_token (parser);
break;
case RID_ENUM:
if (!typespec_ok)
goto out;
attrs_ok = true;
seen_type = true;
t = c_parser_enum_specifier (parser);
declspecs_add_type (loc, specs, t);
break;
case RID_STRUCT:
case RID_UNION:
if (!typespec_ok)
goto out;
attrs_ok = true;
seen_type = true;
t = c_parser_struct_or_union_specifier (parser);
invoke_plugin_callbacks (PLUGIN_FINISH_TYPE, t.spec);
declspecs_add_type (loc, specs, t);
break;
case RID_TYPEOF:
/* ??? The old parser rejected typeof after other type
specifiers, but is a syntax error the best way of
handling this? */
if (!typespec_ok || seen_type)
goto out;
attrs_ok = true;
seen_type = true;
t = c_parser_typeof_specifier (parser);
declspecs_add_type (loc, specs, t);
break;
case RID_CONST:
case RID_VOLATILE:
case RID_RESTRICT:
attrs_ok = true;
declspecs_add_qual (specs, c_parser_peek_token (parser)->value);
c_parser_consume_token (parser);
break;
case RID_ATTRIBUTE:
if (!attrs_ok)
goto out;
attrs = c_parser_attributes (parser);
declspecs_add_attrs (specs, attrs);
break;
default:
goto out;
}
}
out: ;
}
/* Parse an enum specifier (C90 6.5.2.2, C99 6.7.2.2).
enum-specifier:
enum attributes[opt] identifier[opt] { enumerator-list } attributes[opt]
enum attributes[opt] identifier[opt] { enumerator-list , } attributes[opt]
enum attributes[opt] identifier
The form with trailing comma is new in C99. The forms with
attributes are GNU extensions. In GNU C, we accept any expression
without commas in the syntax (assignment expressions, not just
conditional expressions); assignment expressions will be diagnosed
as non-constant.
enumerator-list:
enumerator
enumerator-list , enumerator
enumerator:
enumeration-constant
enumeration-constant = constant-expression
*/
static struct c_typespec
c_parser_enum_specifier (c_parser *parser)
{
struct c_typespec ret;
tree attrs;
tree ident = NULL_TREE;
location_t enum_loc;
location_t ident_loc = UNKNOWN_LOCATION; /* Quiet warning. */
gcc_assert (c_parser_next_token_is_keyword (parser, RID_ENUM));
enum_loc = c_parser_peek_token (parser)->location;
c_parser_consume_token (parser);
attrs = c_parser_attributes (parser);
enum_loc = c_parser_peek_token (parser)->location;
/* Set the location in case we create a decl now. */
c_parser_set_source_position_from_token (c_parser_peek_token (parser));
if (c_parser_next_token_is (parser, CPP_NAME))
{
ident = c_parser_peek_token (parser)->value;
ident_loc = c_parser_peek_token (parser)->location;
enum_loc = ident_loc;
c_parser_consume_token (parser);
}
if (c_parser_next_token_is (parser, CPP_OPEN_BRACE))
{
/* Parse an enum definition. */
struct c_enum_contents the_enum;
tree type = start_enum (enum_loc, &the_enum, ident);
tree postfix_attrs;
/* We chain the enumerators in reverse order, then put them in
forward order at the end. */
tree values = NULL_TREE;
c_parser_consume_token (parser);
while (true)
{
tree enum_id;
tree enum_value;
tree enum_decl;
bool seen_comma;
c_token *token;
location_t comma_loc = UNKNOWN_LOCATION; /* Quiet warning. */
location_t decl_loc, value_loc;
if (c_parser_next_token_is_not (parser, CPP_NAME))
{
c_parser_error (parser, "expected identifier");
c_parser_skip_until_found (parser, CPP_CLOSE_BRACE, NULL);
values = error_mark_node;
break;
}
token = c_parser_peek_token (parser);
enum_id = token->value;
/* Set the location in case we create a decl now. */
c_parser_set_source_position_from_token (token);
decl_loc = value_loc = token->location;
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_EQ))
{
c_parser_consume_token (parser);
value_loc = c_parser_peek_token (parser)->location;
enum_value = c_parser_expr_no_commas (parser, NULL).value;
}
else
enum_value = NULL_TREE;
enum_decl = build_enumerator (decl_loc, value_loc,
&the_enum, enum_id, enum_value);
TREE_CHAIN (enum_decl) = values;
values = enum_decl;
seen_comma = false;
if (c_parser_next_token_is (parser, CPP_COMMA))
{
comma_loc = c_parser_peek_token (parser)->location;
seen_comma = true;
c_parser_consume_token (parser);
}
if (c_parser_next_token_is (parser, CPP_CLOSE_BRACE))
{
if (seen_comma && !flag_isoc99)
pedwarn (comma_loc, OPT_pedantic, "comma at end of enumerator list");
c_parser_consume_token (parser);
break;
}
if (!seen_comma)
{
c_parser_error (parser, "expected %<,%> or %<}%>");
c_parser_skip_until_found (parser, CPP_CLOSE_BRACE, NULL);
values = error_mark_node;
break;
}
}
postfix_attrs = c_parser_attributes (parser);
ret.spec = finish_enum (type, nreverse (values),
chainon (attrs, postfix_attrs));
ret.kind = ctsk_tagdef;
ret.expr = NULL_TREE;
ret.expr_const_operands = true;
return ret;
}
else if (!ident)
{
c_parser_error (parser, "expected %<{%>");
ret.spec = error_mark_node;
ret.kind = ctsk_tagref;
ret.expr = NULL_TREE;
ret.expr_const_operands = true;
return ret;
}
ret = parser_xref_tag (ident_loc, ENUMERAL_TYPE, ident);
/* In ISO C, enumerated types can be referred to only if already
defined. */
if (pedantic && !COMPLETE_TYPE_P (ret.spec))
{
gcc_assert (ident);
pedwarn (enum_loc, OPT_pedantic,
"ISO C forbids forward references to %<enum%> types");
}
return ret;
}
/* Parse a struct or union specifier (C90 6.5.2.1, C99 6.7.2.1).
struct-or-union-specifier:
struct-or-union attributes[opt] identifier[opt]
{ struct-contents } attributes[opt]
struct-or-union attributes[opt] identifier
struct-contents:
struct-declaration-list
struct-declaration-list:
struct-declaration ;
struct-declaration-list struct-declaration ;
GNU extensions:
struct-contents:
empty
struct-declaration
struct-declaration-list struct-declaration
struct-declaration-list:
struct-declaration-list ;
;
(Note that in the syntax here, unlike that in ISO C, the semicolons
are included here rather than in struct-declaration, in order to
describe the syntax with extra semicolons and missing semicolon at
end.)
Objective-C:
struct-declaration-list:
@defs ( class-name )
(Note this does not include a trailing semicolon, but can be
followed by further declarations, and gets a pedwarn-if-pedantic
when followed by a semicolon.) */
static struct c_typespec
c_parser_struct_or_union_specifier (c_parser *parser)
{
struct c_typespec ret;
tree attrs;
tree ident = NULL_TREE;
location_t struct_loc;
location_t ident_loc = UNKNOWN_LOCATION;
enum tree_code code;
switch (c_parser_peek_token (parser)->keyword)
{
case RID_STRUCT:
code = RECORD_TYPE;
break;
case RID_UNION:
code = UNION_TYPE;
break;
default:
gcc_unreachable ();
}
struct_loc = c_parser_peek_token (parser)->location;
c_parser_consume_token (parser);
attrs = c_parser_attributes (parser);
/* Set the location in case we create a decl now. */
c_parser_set_source_position_from_token (c_parser_peek_token (parser));
if (c_parser_next_token_is (parser, CPP_NAME))
{
ident = c_parser_peek_token (parser)->value;
ident_loc = c_parser_peek_token (parser)->location;
struct_loc = ident_loc;
c_parser_consume_token (parser);
}
if (c_parser_next_token_is (parser, CPP_OPEN_BRACE))
{
/* Parse a struct or union definition. Start the scope of the
tag before parsing components. */
struct c_struct_parse_info *struct_info;
tree type = start_struct (struct_loc, code, ident, &struct_info);
tree postfix_attrs;
/* We chain the components in reverse order, then put them in
forward order at the end. Each struct-declaration may
declare multiple components (comma-separated), so we must use
chainon to join them, although when parsing each
struct-declaration we can use TREE_CHAIN directly.
The theory behind all this is that there will be more
semicolon separated fields than comma separated fields, and
so we'll be minimizing the number of node traversals required
by chainon. */
tree contents = NULL_TREE;
c_parser_consume_token (parser);
/* Handle the Objective-C @defs construct,
e.g. foo(sizeof(struct{ @defs(ClassName) }));. */
if (c_parser_next_token_is_keyword (parser, RID_AT_DEFS))
{
tree name;
gcc_assert (c_dialect_objc ());
c_parser_consume_token (parser);
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
goto end_at_defs;
if (c_parser_next_token_is (parser, CPP_NAME)
&& c_parser_peek_token (parser)->id_kind == C_ID_CLASSNAME)
{
name = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
}
else
{
c_parser_error (parser, "expected class name");
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, NULL);
goto end_at_defs;
}
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
contents = nreverse (objc_get_class_ivars (name));
}
end_at_defs:
/* Parse the struct-declarations and semicolons. Problems with
semicolons are diagnosed here; empty structures are diagnosed
elsewhere. */
while (true)
{
tree decls;
/* Parse any stray semicolon. */
if (c_parser_next_token_is (parser, CPP_SEMICOLON))
{
pedwarn (c_parser_peek_token (parser)->location, OPT_pedantic,
"extra semicolon in struct or union specified");
c_parser_consume_token (parser);
continue;
}
/* Stop if at the end of the struct or union contents. */
if (c_parser_next_token_is (parser, CPP_CLOSE_BRACE))
{
c_parser_consume_token (parser);
break;
}
/* Accept #pragmas at struct scope. */
if (c_parser_next_token_is (parser, CPP_PRAGMA))
{
c_parser_pragma (parser, pragma_external);
continue;
}
/* Parse some comma-separated declarations, but not the
trailing semicolon if any. */
decls = c_parser_struct_declaration (parser);
contents = chainon (decls, contents);
/* If no semicolon follows, either we have a parse error or
are at the end of the struct or union and should
pedwarn. */
if (c_parser_next_token_is (parser, CPP_SEMICOLON))
c_parser_consume_token (parser);
else
{
if (c_parser_next_token_is (parser, CPP_CLOSE_BRACE))
pedwarn (c_parser_peek_token (parser)->location, 0,
"no semicolon at end of struct or union");
else if (parser->error
|| !c_parser_next_token_starts_declspecs (parser))
{
c_parser_error (parser, "expected %<;%>");
c_parser_skip_until_found (parser, CPP_CLOSE_BRACE, NULL);
break;
}
/* If we come here, we have already emitted an error
for an expected `;', identifier or `(', and we also
recovered already. Go on with the next field. */
}
}
postfix_attrs = c_parser_attributes (parser);
ret.spec = finish_struct (struct_loc, type, nreverse (contents),
chainon (attrs, postfix_attrs), struct_info);
ret.kind = ctsk_tagdef;
ret.expr = NULL_TREE;
ret.expr_const_operands = true;
return ret;
}
else if (!ident)
{
c_parser_error (parser, "expected %<{%>");
ret.spec = error_mark_node;
ret.kind = ctsk_tagref;
ret.expr = NULL_TREE;
ret.expr_const_operands = true;
return ret;
}
ret = parser_xref_tag (ident_loc, code, ident);
return ret;
}
/* Parse a struct-declaration (C90 6.5.2.1, C99 6.7.2.1), *without*
the trailing semicolon.
struct-declaration:
specifier-qualifier-list struct-declarator-list
static_assert-declaration-no-semi
specifier-qualifier-list:
type-specifier specifier-qualifier-list[opt]
type-qualifier specifier-qualifier-list[opt]
attributes specifier-qualifier-list[opt]
struct-declarator-list:
struct-declarator
struct-declarator-list , attributes[opt] struct-declarator
struct-declarator:
declarator attributes[opt]
declarator[opt] : constant-expression attributes[opt]
GNU extensions:
struct-declaration:
__extension__ struct-declaration
specifier-qualifier-list
Unlike the ISO C syntax, semicolons are handled elsewhere. The use
of attributes where shown is a GNU extension. In GNU C, we accept
any expression without commas in the syntax (assignment
expressions, not just conditional expressions); assignment
expressions will be diagnosed as non-constant. */
static tree
c_parser_struct_declaration (c_parser *parser)
{
struct c_declspecs *specs;
tree prefix_attrs;
tree all_prefix_attrs;
tree decls;
location_t decl_loc;
if (c_parser_next_token_is_keyword (parser, RID_EXTENSION))
{
int ext;
tree decl;
ext = disable_extension_diagnostics ();
c_parser_consume_token (parser);
decl = c_parser_struct_declaration (parser);
restore_extension_diagnostics (ext);
return decl;
}
if (c_parser_next_token_is_keyword (parser, RID_STATIC_ASSERT))
{
c_parser_static_assert_declaration_no_semi (parser);
return NULL_TREE;
}
specs = build_null_declspecs ();
decl_loc = c_parser_peek_token (parser)->location;
c_parser_declspecs (parser, specs, false, true, true, cla_nonabstract_decl);
if (parser->error)
return NULL_TREE;
if (!specs->declspecs_seen_p)
{
c_parser_error (parser, "expected specifier-qualifier-list");
return NULL_TREE;
}
finish_declspecs (specs);
if (c_parser_next_token_is (parser, CPP_SEMICOLON)
|| c_parser_next_token_is (parser, CPP_CLOSE_BRACE))
{
tree ret;
if (specs->typespec_kind == ctsk_none)
{
pedwarn (decl_loc, OPT_pedantic,
"ISO C forbids member declarations with no members");
shadow_tag_warned (specs, pedantic);
ret = NULL_TREE;
}
else
{
/* Support for unnamed structs or unions as members of
structs or unions (which is [a] useful and [b] supports
MS P-SDK). */
tree attrs = NULL;
ret = grokfield (c_parser_peek_token (parser)->location,
build_id_declarator (NULL_TREE), specs,
NULL_TREE, &attrs);
if (ret)
decl_attributes (&ret, attrs, 0);
}
return ret;
}
/* Provide better error recovery. Note that a type name here is valid,
and will be treated as a field name. */
if (specs->typespec_kind == ctsk_tagdef
&& TREE_CODE (specs->type) != ENUMERAL_TYPE
&& c_parser_next_token_starts_declspecs (parser)
&& !c_parser_next_token_is (parser, CPP_NAME))
{
c_parser_error (parser, "expected %<;%>, identifier or %<(%>");
parser->error = false;
return NULL_TREE;
}
pending_xref_error ();
prefix_attrs = specs->attrs;
all_prefix_attrs = prefix_attrs;
specs->attrs = NULL_TREE;
decls = NULL_TREE;
while (true)
{
/* Declaring one or more declarators or un-named bit-fields. */
struct c_declarator *declarator;
bool dummy = false;
if (c_parser_next_token_is (parser, CPP_COLON))
declarator = build_id_declarator (NULL_TREE);
else
declarator = c_parser_declarator (parser,
specs->typespec_kind != ctsk_none,
C_DTR_NORMAL, &dummy);
if (declarator == NULL)
{
c_parser_skip_to_end_of_block_or_statement (parser);
break;
}
if (c_parser_next_token_is (parser, CPP_COLON)
|| c_parser_next_token_is (parser, CPP_COMMA)
|| c_parser_next_token_is (parser, CPP_SEMICOLON)
|| c_parser_next_token_is (parser, CPP_CLOSE_BRACE)
|| c_parser_next_token_is_keyword (parser, RID_ATTRIBUTE))
{
tree postfix_attrs = NULL_TREE;
tree width = NULL_TREE;
tree d;
if (c_parser_next_token_is (parser, CPP_COLON))
{
c_parser_consume_token (parser);
width = c_parser_expr_no_commas (parser, NULL).value;
}
if (c_parser_next_token_is_keyword (parser, RID_ATTRIBUTE))
postfix_attrs = c_parser_attributes (parser);
d = grokfield (c_parser_peek_token (parser)->location,
declarator, specs, width, &all_prefix_attrs);
decl_attributes (&d, chainon (postfix_attrs,
all_prefix_attrs), 0);
DECL_CHAIN (d) = decls;
decls = d;
if (c_parser_next_token_is_keyword (parser, RID_ATTRIBUTE))
all_prefix_attrs = chainon (c_parser_attributes (parser),
prefix_attrs);
else
all_prefix_attrs = prefix_attrs;
if (c_parser_next_token_is (parser, CPP_COMMA))
c_parser_consume_token (parser);
else if (c_parser_next_token_is (parser, CPP_SEMICOLON)
|| c_parser_next_token_is (parser, CPP_CLOSE_BRACE))
{
/* Semicolon consumed in caller. */
break;
}
else
{
c_parser_error (parser, "expected %<,%>, %<;%> or %<}%>");
break;
}
}
else
{
c_parser_error (parser,
"expected %<:%>, %<,%>, %<;%>, %<}%> or "
"%<__attribute__%>");
break;
}
}
return decls;
}
/* Parse a typeof specifier (a GNU extension).
typeof-specifier:
typeof ( expression )
typeof ( type-name )
*/
static struct c_typespec
c_parser_typeof_specifier (c_parser *parser)
{
struct c_typespec ret;
ret.kind = ctsk_typeof;
ret.spec = error_mark_node;
ret.expr = NULL_TREE;
ret.expr_const_operands = true;
gcc_assert (c_parser_next_token_is_keyword (parser, RID_TYPEOF));
c_parser_consume_token (parser);
c_inhibit_evaluation_warnings++;
in_typeof++;
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
{
c_inhibit_evaluation_warnings--;
in_typeof--;
return ret;
}
if (c_parser_next_tokens_start_typename (parser, cla_prefer_id))
{
struct c_type_name *type = c_parser_type_name (parser);
c_inhibit_evaluation_warnings--;
in_typeof--;
if (type != NULL)
{
ret.spec = groktypename (type, &ret.expr, &ret.expr_const_operands);
pop_maybe_used (variably_modified_type_p (ret.spec, NULL_TREE));
}
}
else
{
bool was_vm;
location_t here = c_parser_peek_token (parser)->location;
struct c_expr expr = c_parser_expression (parser);
c_inhibit_evaluation_warnings--;
in_typeof--;
if (TREE_CODE (expr.value) == COMPONENT_REF
&& DECL_C_BIT_FIELD (TREE_OPERAND (expr.value, 1)))
error_at (here, "%<typeof%> applied to a bit-field");
mark_exp_read (expr.value);
ret.spec = TREE_TYPE (expr.value);
was_vm = variably_modified_type_p (ret.spec, NULL_TREE);
/* This is returned with the type so that when the type is
evaluated, this can be evaluated. */
if (was_vm)
ret.expr = c_fully_fold (expr.value, false, &ret.expr_const_operands);
pop_maybe_used (was_vm);
}
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, "expected %<)%>");
return ret;
}
/* Parse a declarator, possibly an abstract declarator (C90 6.5.4,
6.5.5, C99 6.7.5, 6.7.6). If TYPE_SEEN_P then a typedef name may
be redeclared; otherwise it may not. KIND indicates which kind of
declarator is wanted. Returns a valid declarator except in the
case of a syntax error in which case NULL is returned. *SEEN_ID is
set to true if an identifier being declared is seen; this is used
to diagnose bad forms of abstract array declarators and to
determine whether an identifier list is syntactically permitted.
declarator:
pointer[opt] direct-declarator
direct-declarator:
identifier
( attributes[opt] declarator )
direct-declarator array-declarator
direct-declarator ( parameter-type-list )
direct-declarator ( identifier-list[opt] )
pointer:
* type-qualifier-list[opt]
* type-qualifier-list[opt] pointer
type-qualifier-list:
type-qualifier
attributes
type-qualifier-list type-qualifier
type-qualifier-list attributes
parameter-type-list:
parameter-list
parameter-list , ...
parameter-list:
parameter-declaration
parameter-list , parameter-declaration
parameter-declaration:
declaration-specifiers declarator attributes[opt]
declaration-specifiers abstract-declarator[opt] attributes[opt]
identifier-list:
identifier
identifier-list , identifier
abstract-declarator:
pointer
pointer[opt] direct-abstract-declarator
direct-abstract-declarator:
( attributes[opt] abstract-declarator )
direct-abstract-declarator[opt] array-declarator
direct-abstract-declarator[opt] ( parameter-type-list[opt] )
GNU extensions:
direct-declarator:
direct-declarator ( parameter-forward-declarations
parameter-type-list[opt] )
direct-abstract-declarator:
direct-abstract-declarator[opt] ( parameter-forward-declarations
parameter-type-list[opt] )
parameter-forward-declarations:
parameter-list ;
parameter-forward-declarations parameter-list ;
The uses of attributes shown above are GNU extensions.
Some forms of array declarator are not included in C99 in the
syntax for abstract declarators; these are disallowed elsewhere.
This may be a defect (DR#289).
This function also accepts an omitted abstract declarator as being
an abstract declarator, although not part of the formal syntax. */
static struct c_declarator *
c_parser_declarator (c_parser *parser, bool type_seen_p, c_dtr_syn kind,
bool *seen_id)
{
/* Parse any initial pointer part. */
if (c_parser_next_token_is (parser, CPP_MULT))
{
struct c_declspecs *quals_attrs = build_null_declspecs ();
struct c_declarator *inner;
c_parser_consume_token (parser);
c_parser_declspecs (parser, quals_attrs, false, false, true, cla_prefer_id);
inner = c_parser_declarator (parser, type_seen_p, kind, seen_id);
if (inner == NULL)
return NULL;
else
return make_pointer_declarator (quals_attrs, inner);
}
/* Now we have a direct declarator, direct abstract declarator or
nothing (which counts as a direct abstract declarator here). */
return c_parser_direct_declarator (parser, type_seen_p, kind, seen_id);
}
/* Parse a direct declarator or direct abstract declarator; arguments
as c_parser_declarator. */
static struct c_declarator *
c_parser_direct_declarator (c_parser *parser, bool type_seen_p, c_dtr_syn kind,
bool *seen_id)
{
/* The direct declarator must start with an identifier (possibly
omitted) or a parenthesized declarator (possibly abstract). In
an ordinary declarator, initial parentheses must start a
parenthesized declarator. In an abstract declarator or parameter
declarator, they could start a parenthesized declarator or a
parameter list. To tell which, the open parenthesis and any
following attributes must be read. If a declaration specifier
follows, then it is a parameter list; if the specifier is a
typedef name, there might be an ambiguity about redeclaring it,
which is resolved in the direction of treating it as a typedef
name. If a close parenthesis follows, it is also an empty
parameter list, as the syntax does not permit empty abstract
declarators. Otherwise, it is a parenthesized declarator (in
which case the analysis may be repeated inside it, recursively).
??? There is an ambiguity in a parameter declaration "int
(__attribute__((foo)) x)", where x is not a typedef name: it
could be an abstract declarator for a function, or declare x with
parentheses. The proper resolution of this ambiguity needs
documenting. At present we follow an accident of the old
parser's implementation, whereby the first parameter must have
some declaration specifiers other than just attributes. Thus as
a parameter declaration it is treated as a parenthesized
parameter named x, and as an abstract declarator it is
rejected.
??? Also following the old parser, attributes inside an empty
parameter list are ignored, making it a list not yielding a
prototype, rather than giving an error or making it have one
parameter with implicit type int.
??? Also following the old parser, typedef names may be
redeclared in declarators, but not Objective-C class names. */
if (kind != C_DTR_ABSTRACT
&& c_parser_next_token_is (parser, CPP_NAME)
&& ((type_seen_p
&& (c_parser_peek_token (parser)->id_kind == C_ID_TYPENAME
|| c_parser_peek_token (parser)->id_kind == C_ID_CLASSNAME))
|| c_parser_peek_token (parser)->id_kind == C_ID_ID))
{
struct c_declarator *inner
= build_id_declarator (c_parser_peek_token (parser)->value);
*seen_id = true;
inner->id_loc = c_parser_peek_token (parser)->location;
c_parser_consume_token (parser);
return c_parser_direct_declarator_inner (parser, *seen_id, inner);
}
if (kind != C_DTR_NORMAL
&& c_parser_next_token_is (parser, CPP_OPEN_SQUARE))
{
struct c_declarator *inner = build_id_declarator (NULL_TREE);
return c_parser_direct_declarator_inner (parser, *seen_id, inner);
}
/* Either we are at the end of an abstract declarator, or we have
parentheses. */
if (c_parser_next_token_is (parser, CPP_OPEN_PAREN))
{
tree attrs;
struct c_declarator *inner;
c_parser_consume_token (parser);
attrs = c_parser_attributes (parser);
if (kind != C_DTR_NORMAL
&& (c_parser_next_token_starts_declspecs (parser)
|| c_parser_next_token_is (parser, CPP_CLOSE_PAREN)))
{
struct c_arg_info *args
= c_parser_parms_declarator (parser, kind == C_DTR_NORMAL,
attrs);
if (args == NULL)
return NULL;
else
{
inner
= build_function_declarator (args,
build_id_declarator (NULL_TREE));
return c_parser_direct_declarator_inner (parser, *seen_id,
inner);
}
}
/* A parenthesized declarator. */
inner = c_parser_declarator (parser, type_seen_p, kind, seen_id);
if (inner != NULL && attrs != NULL)
inner = build_attrs_declarator (attrs, inner);
if (c_parser_next_token_is (parser, CPP_CLOSE_PAREN))
{
c_parser_consume_token (parser);
if (inner == NULL)
return NULL;
else
return c_parser_direct_declarator_inner (parser, *seen_id, inner);
}
else
{
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
return NULL;
}
}
else
{
if (kind == C_DTR_NORMAL)
{
c_parser_error (parser, "expected identifier or %<(%>");
return NULL;
}
else
return build_id_declarator (NULL_TREE);
}
}
/* Parse part of a direct declarator or direct abstract declarator,
given that some (in INNER) has already been parsed; ID_PRESENT is
true if an identifier is present, false for an abstract
declarator. */
static struct c_declarator *
c_parser_direct_declarator_inner (c_parser *parser, bool id_present,
struct c_declarator *inner)
{
/* Parse a sequence of array declarators and parameter lists. */
if (c_parser_next_token_is (parser, CPP_OPEN_SQUARE))
{
location_t brace_loc = c_parser_peek_token (parser)->location;
struct c_declarator *declarator;
struct c_declspecs *quals_attrs = build_null_declspecs ();
bool static_seen;
bool star_seen;
tree dimen;
c_parser_consume_token (parser);
c_parser_declspecs (parser, quals_attrs, false, false, true, cla_prefer_id);
static_seen = c_parser_next_token_is_keyword (parser, RID_STATIC);
if (static_seen)
c_parser_consume_token (parser);
if (static_seen && !quals_attrs->declspecs_seen_p)
c_parser_declspecs (parser, quals_attrs, false, false, true, cla_prefer_id);
if (!quals_attrs->declspecs_seen_p)
quals_attrs = NULL;
/* If "static" is present, there must be an array dimension.
Otherwise, there may be a dimension, "*", or no
dimension. */
if (static_seen)
{
star_seen = false;
dimen = c_parser_expr_no_commas (parser, NULL).value;
}
else
{
if (c_parser_next_token_is (parser, CPP_CLOSE_SQUARE))
{
dimen = NULL_TREE;
star_seen = false;
}
else if (c_parser_next_token_is (parser, CPP_MULT))
{
if (c_parser_peek_2nd_token (parser)->type == CPP_CLOSE_SQUARE)
{
dimen = NULL_TREE;
star_seen = true;
c_parser_consume_token (parser);
}
else
{
star_seen = false;
dimen = c_parser_expr_no_commas (parser, NULL).value;
}
}
else
{
star_seen = false;
dimen = c_parser_expr_no_commas (parser, NULL).value;
}
}
if (c_parser_next_token_is (parser, CPP_CLOSE_SQUARE))
c_parser_consume_token (parser);
else
{
c_parser_skip_until_found (parser, CPP_CLOSE_SQUARE,
"expected %<]%>");
return NULL;
}
if (dimen)
mark_exp_read (dimen);
declarator = build_array_declarator (brace_loc, dimen, quals_attrs,
static_seen, star_seen);
if (declarator == NULL)
return NULL;
inner = set_array_declarator_inner (declarator, inner);
return c_parser_direct_declarator_inner (parser, id_present, inner);
}
else if (c_parser_next_token_is (parser, CPP_OPEN_PAREN))
{
tree attrs;
struct c_arg_info *args;
c_parser_consume_token (parser);
attrs = c_parser_attributes (parser);
args = c_parser_parms_declarator (parser, id_present, attrs);
if (args == NULL)
return NULL;
else
{
inner = build_function_declarator (args, inner);
return c_parser_direct_declarator_inner (parser, id_present, inner);
}
}
return inner;
}
/* Parse a parameter list or identifier list, including the closing
parenthesis but not the opening one. ATTRS are the attributes at
the start of the list. ID_LIST_OK is true if an identifier list is
acceptable; such a list must not have attributes at the start. */
static struct c_arg_info *
c_parser_parms_declarator (c_parser *parser, bool id_list_ok, tree attrs)
{
push_scope ();
declare_parm_level ();
/* If the list starts with an identifier, it is an identifier list.
Otherwise, it is either a prototype list or an empty list. */
if (id_list_ok
&& !attrs
&& c_parser_next_token_is (parser, CPP_NAME)
&& c_parser_peek_token (parser)->id_kind == C_ID_ID
/* Look ahead to detect typos in type names. */
&& c_parser_peek_2nd_token (parser)->type != CPP_NAME
&& c_parser_peek_2nd_token (parser)->type != CPP_MULT
&& c_parser_peek_2nd_token (parser)->type != CPP_OPEN_PAREN
&& c_parser_peek_2nd_token (parser)->type != CPP_OPEN_SQUARE)
{
tree list = NULL_TREE, *nextp = &list;
while (c_parser_next_token_is (parser, CPP_NAME)
&& c_parser_peek_token (parser)->id_kind == C_ID_ID)
{
*nextp = build_tree_list (NULL_TREE,
c_parser_peek_token (parser)->value);
nextp = & TREE_CHAIN (*nextp);
c_parser_consume_token (parser);
if (c_parser_next_token_is_not (parser, CPP_COMMA))
break;
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_CLOSE_PAREN))
{
c_parser_error (parser, "expected identifier");
break;
}
}
if (c_parser_next_token_is (parser, CPP_CLOSE_PAREN))
{
struct c_arg_info *ret = build_arg_info ();
ret->types = list;
c_parser_consume_token (parser);
pop_scope ();
return ret;
}
else
{
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
pop_scope ();
return NULL;
}
}
else
{
struct c_arg_info *ret = c_parser_parms_list_declarator (parser, attrs);
pop_scope ();
return ret;
}
}
/* Parse a parameter list (possibly empty), including the closing
parenthesis but not the opening one. ATTRS are the attributes at
the start of the list. */
static struct c_arg_info *
c_parser_parms_list_declarator (c_parser *parser, tree attrs)
{
bool bad_parm = false;
/* ??? Following the old parser, forward parameter declarations may
use abstract declarators, and if no real parameter declarations
follow the forward declarations then this is not diagnosed. Also
note as above that attributes are ignored as the only contents of
the parentheses, or as the only contents after forward
declarations. */
if (c_parser_next_token_is (parser, CPP_CLOSE_PAREN))
{
struct c_arg_info *ret = build_arg_info ();
c_parser_consume_token (parser);
return ret;
}
if (c_parser_next_token_is (parser, CPP_ELLIPSIS))
{
struct c_arg_info *ret = build_arg_info ();
/* Suppress -Wold-style-definition for this case. */
ret->types = error_mark_node;
error_at (c_parser_peek_token (parser)->location,
"ISO C requires a named argument before %<...%>");
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_CLOSE_PAREN))
{
c_parser_consume_token (parser);
return ret;
}
else
{
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
return NULL;
}
}
/* Nonempty list of parameters, either terminated with semicolon
(forward declarations; recurse) or with close parenthesis (normal
function) or with ", ... )" (variadic function). */
while (true)
{
/* Parse a parameter. */
struct c_parm *parm = c_parser_parameter_declaration (parser, attrs);
attrs = NULL_TREE;
if (parm == NULL)
bad_parm = true;
else
push_parm_decl (parm);
if (c_parser_next_token_is (parser, CPP_SEMICOLON))
{
tree new_attrs;
c_parser_consume_token (parser);
mark_forward_parm_decls ();
new_attrs = c_parser_attributes (parser);
return c_parser_parms_list_declarator (parser, new_attrs);
}
if (c_parser_next_token_is (parser, CPP_CLOSE_PAREN))
{
c_parser_consume_token (parser);
if (bad_parm)
{
get_pending_sizes ();
return NULL;
}
else
return get_parm_info (false);
}
if (!c_parser_require (parser, CPP_COMMA,
"expected %<;%>, %<,%> or %<)%>"))
{
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, NULL);
get_pending_sizes ();
return NULL;
}
if (c_parser_next_token_is (parser, CPP_ELLIPSIS))
{
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_CLOSE_PAREN))
{
c_parser_consume_token (parser);
if (bad_parm)
{
get_pending_sizes ();
return NULL;
}
else
return get_parm_info (true);
}
else
{
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
get_pending_sizes ();
return NULL;
}
}
}
}
/* Parse a parameter declaration. ATTRS are the attributes at the
start of the declaration if it is the first parameter. */
static struct c_parm *
c_parser_parameter_declaration (c_parser *parser, tree attrs)
{
struct c_declspecs *specs;
struct c_declarator *declarator;
tree prefix_attrs;
tree postfix_attrs = NULL_TREE;
bool dummy = false;
if (!c_parser_next_token_starts_declspecs (parser))
{
c_token *token = c_parser_peek_token (parser);
if (parser->error)
return NULL;
c_parser_set_source_position_from_token (token);
if (c_parser_next_tokens_start_typename (parser, cla_prefer_type))
{
error ("unknown type name %qE", token->value);
parser->error = true;
}
/* ??? In some Objective-C cases '...' isn't applicable so there
should be a different message. */
else
c_parser_error (parser,
"expected declaration specifiers or %<...%>");
c_parser_skip_to_end_of_parameter (parser);
return NULL;
}
specs = build_null_declspecs ();
if (attrs)
{
declspecs_add_attrs (specs, attrs);
attrs = NULL_TREE;
}
c_parser_declspecs (parser, specs, true, true, true, cla_nonabstract_decl);
finish_declspecs (specs);
pending_xref_error ();
prefix_attrs = specs->attrs;
specs->attrs = NULL_TREE;
declarator = c_parser_declarator (parser,
specs->typespec_kind != ctsk_none,
C_DTR_PARM, &dummy);
if (declarator == NULL)
{
c_parser_skip_until_found (parser, CPP_COMMA, NULL);
return NULL;
}
if (c_parser_next_token_is_keyword (parser, RID_ATTRIBUTE))
postfix_attrs = c_parser_attributes (parser);
return build_c_parm (specs, chainon (postfix_attrs, prefix_attrs),
declarator);
}
/* Parse a string literal in an asm expression. It should not be
translated, and wide string literals are an error although
permitted by the syntax. This is a GNU extension.
asm-string-literal:
string-literal
??? At present, following the old parser, the caller needs to have
set lex_untranslated_string to 1. It would be better to follow the
C++ parser rather than using this kludge. */
static tree
c_parser_asm_string_literal (c_parser *parser)
{
tree str;
if (c_parser_next_token_is (parser, CPP_STRING))
{
str = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
}
else if (c_parser_next_token_is (parser, CPP_WSTRING))
{
error_at (c_parser_peek_token (parser)->location,
"wide string literal in %<asm%>");
str = build_string (1, "");
c_parser_consume_token (parser);
}
else
{
c_parser_error (parser, "expected string literal");
str = NULL_TREE;
}
return str;
}
/* Parse a simple asm expression. This is used in restricted
contexts, where a full expression with inputs and outputs does not
make sense. This is a GNU extension.
simple-asm-expr:
asm ( asm-string-literal )
*/
static tree
c_parser_simple_asm_expr (c_parser *parser)
{
tree str;
gcc_assert (c_parser_next_token_is_keyword (parser, RID_ASM));
/* ??? Follow the C++ parser rather than using the
lex_untranslated_string kludge. */
parser->lex_untranslated_string = true;
c_parser_consume_token (parser);
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
{
parser->lex_untranslated_string = false;
return NULL_TREE;
}
str = c_parser_asm_string_literal (parser);
parser->lex_untranslated_string = false;
if (!c_parser_require (parser, CPP_CLOSE_PAREN, "expected %<)%>"))
{
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, NULL);
return NULL_TREE;
}
return str;
}
/* Parse (possibly empty) attributes. This is a GNU extension.
attributes:
empty
attributes attribute
attribute:
__attribute__ ( ( attribute-list ) )
attribute-list:
attrib
attribute_list , attrib
attrib:
empty
any-word
any-word ( identifier )
any-word ( identifier , nonempty-expr-list )
any-word ( expr-list )
where the "identifier" must not be declared as a type, and
"any-word" may be any identifier (including one declared as a
type), a reserved word storage class specifier, type specifier or
type qualifier. ??? This still leaves out most reserved keywords
(following the old parser), shouldn't we include them, and why not
allow identifiers declared as types to start the arguments? */
static tree
c_parser_attributes (c_parser *parser)
{
tree attrs = NULL_TREE;
while (c_parser_next_token_is_keyword (parser, RID_ATTRIBUTE))
{
/* ??? Follow the C++ parser rather than using the
lex_untranslated_string kludge. */
parser->lex_untranslated_string = true;
c_parser_consume_token (parser);
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
{
parser->lex_untranslated_string = false;
return attrs;
}
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
{
parser->lex_untranslated_string = false;
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, NULL);
return attrs;
}
/* Parse the attribute list. */
while (c_parser_next_token_is (parser, CPP_COMMA)
|| c_parser_next_token_is (parser, CPP_NAME)
|| c_parser_next_token_is (parser, CPP_KEYWORD))
{
tree attr, attr_name, attr_args;
VEC(tree,gc) *expr_list;
if (c_parser_next_token_is (parser, CPP_COMMA))
{
c_parser_consume_token (parser);
continue;
}
if (c_parser_next_token_is (parser, CPP_KEYWORD))
{
/* ??? See comment above about what keywords are
accepted here. */
bool ok;
switch (c_parser_peek_token (parser)->keyword)
{
case RID_STATIC:
case RID_UNSIGNED:
case RID_LONG:
case RID_INT128:
case RID_CONST:
case RID_EXTERN:
case RID_REGISTER:
case RID_TYPEDEF:
case RID_SHORT:
case RID_INLINE:
case RID_VOLATILE:
case RID_SIGNED:
case RID_AUTO:
case RID_RESTRICT:
case RID_COMPLEX:
case RID_THREAD:
case RID_INT:
case RID_CHAR:
case RID_FLOAT:
case RID_DOUBLE:
case RID_VOID:
case RID_DFLOAT32:
case RID_DFLOAT64:
case RID_DFLOAT128:
case RID_BOOL:
case RID_FRACT:
case RID_ACCUM:
case RID_SAT:
ok = true;
break;
default:
ok = false;
break;
}
if (!ok)
break;
/* Accept __attribute__((__const)) as __attribute__((const))
etc. */
attr_name
= ridpointers[(int) c_parser_peek_token (parser)->keyword];
}
else
attr_name = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
if (c_parser_next_token_is_not (parser, CPP_OPEN_PAREN))
{
attr = build_tree_list (attr_name, NULL_TREE);
attrs = chainon (attrs, attr);
continue;
}
c_parser_consume_token (parser);
/* Parse the attribute contents. If they start with an
identifier which is followed by a comma or close
parenthesis, then the arguments start with that
identifier; otherwise they are an expression list.
In objective-c the identifier may be a classname. */
if (c_parser_next_token_is (parser, CPP_NAME)
&& (c_parser_peek_token (parser)->id_kind == C_ID_ID
|| (c_dialect_objc ()
&& c_parser_peek_token (parser)->id_kind == C_ID_CLASSNAME))
&& ((c_parser_peek_2nd_token (parser)->type == CPP_COMMA)
|| (c_parser_peek_2nd_token (parser)->type
== CPP_CLOSE_PAREN)))
{
tree arg1 = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_CLOSE_PAREN))
attr_args = build_tree_list (NULL_TREE, arg1);
else
{
tree tree_list;
c_parser_consume_token (parser);
expr_list = c_parser_expr_list (parser, false, true, NULL);
tree_list = build_tree_list_vec (expr_list);
attr_args = tree_cons (NULL_TREE, arg1, tree_list);
release_tree_vector (expr_list);
}
}
else
{
if (c_parser_next_token_is (parser, CPP_CLOSE_PAREN))
attr_args = NULL_TREE;
else
{
expr_list = c_parser_expr_list (parser, false, true, NULL);
attr_args = build_tree_list_vec (expr_list);
release_tree_vector (expr_list);
}
}
attr = build_tree_list (attr_name, attr_args);
if (c_parser_next_token_is (parser, CPP_CLOSE_PAREN))
c_parser_consume_token (parser);
else
{
parser->lex_untranslated_string = false;
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
return attrs;
}
attrs = chainon (attrs, attr);
}
if (c_parser_next_token_is (parser, CPP_CLOSE_PAREN))
c_parser_consume_token (parser);
else
{
parser->lex_untranslated_string = false;
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
return attrs;
}
if (c_parser_next_token_is (parser, CPP_CLOSE_PAREN))
c_parser_consume_token (parser);
else
{
parser->lex_untranslated_string = false;
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
return attrs;
}
parser->lex_untranslated_string = false;
}
return attrs;
}
/* Parse a type name (C90 6.5.5, C99 6.7.6).
type-name:
specifier-qualifier-list abstract-declarator[opt]
*/
static struct c_type_name *
c_parser_type_name (c_parser *parser)
{
struct c_declspecs *specs = build_null_declspecs ();
struct c_declarator *declarator;
struct c_type_name *ret;
bool dummy = false;
c_parser_declspecs (parser, specs, false, true, true, cla_prefer_type);
if (!specs->declspecs_seen_p)
{
c_parser_error (parser, "expected specifier-qualifier-list");
return NULL;
}
if (specs->type != error_mark_node)
{
pending_xref_error ();
finish_declspecs (specs);
}
declarator = c_parser_declarator (parser,
specs->typespec_kind != ctsk_none,
C_DTR_ABSTRACT, &dummy);
if (declarator == NULL)
return NULL;
ret = XOBNEW (&parser_obstack, struct c_type_name);
ret->specs = specs;
ret->declarator = declarator;
return ret;
}
/* Parse an initializer (C90 6.5.7, C99 6.7.8).
initializer:
assignment-expression
{ initializer-list }
{ initializer-list , }
initializer-list:
designation[opt] initializer
initializer-list , designation[opt] initializer
designation:
designator-list =
designator-list:
designator
designator-list designator
designator:
array-designator
. identifier
array-designator:
[ constant-expression ]
GNU extensions:
initializer:
{ }
designation:
array-designator
identifier :
array-designator:
[ constant-expression ... constant-expression ]
Any expression without commas is accepted in the syntax for the
constant-expressions, with non-constant expressions rejected later.
This function is only used for top-level initializers; for nested
ones, see c_parser_initval. */
static struct c_expr
c_parser_initializer (c_parser *parser)
{
if (c_parser_next_token_is (parser, CPP_OPEN_BRACE))
return c_parser_braced_init (parser, NULL_TREE, false);
else
{
struct c_expr ret;
location_t loc = c_parser_peek_token (parser)->location;
ret = c_parser_expr_no_commas (parser, NULL);
if (TREE_CODE (ret.value) != STRING_CST
&& TREE_CODE (ret.value) != COMPOUND_LITERAL_EXPR)
ret = default_function_array_read_conversion (loc, ret);
return ret;
}
}
/* Parse a braced initializer list. TYPE is the type specified for a
compound literal, and NULL_TREE for other initializers and for
nested braced lists. NESTED_P is true for nested braced lists,
false for the list of a compound literal or the list that is the
top-level initializer in a declaration. */
static struct c_expr
c_parser_braced_init (c_parser *parser, tree type, bool nested_p)
{
struct c_expr ret;
struct obstack braced_init_obstack;
location_t brace_loc = c_parser_peek_token (parser)->location;
gcc_obstack_init (&braced_init_obstack);
gcc_assert (c_parser_next_token_is (parser, CPP_OPEN_BRACE));
c_parser_consume_token (parser);
if (nested_p)
push_init_level (0, &braced_init_obstack);
else
really_start_incremental_init (type);
if (c_parser_next_token_is (parser, CPP_CLOSE_BRACE))
{
pedwarn (brace_loc, OPT_pedantic, "ISO C forbids empty initializer braces");
}
else
{
/* Parse a non-empty initializer list, possibly with a trailing
comma. */
while (true)
{
c_parser_initelt (parser, &braced_init_obstack);
if (parser->error)
break;
if (c_parser_next_token_is (parser, CPP_COMMA))
c_parser_consume_token (parser);
else
break;
if (c_parser_next_token_is (parser, CPP_CLOSE_BRACE))
break;
}
}
if (c_parser_next_token_is_not (parser, CPP_CLOSE_BRACE))
{
ret.value = error_mark_node;
ret.original_code = ERROR_MARK;
ret.original_type = NULL;
c_parser_skip_until_found (parser, CPP_CLOSE_BRACE, "expected %<}%>");
pop_init_level (0, &braced_init_obstack);
obstack_free (&braced_init_obstack, NULL);
return ret;
}
c_parser_consume_token (parser);
ret = pop_init_level (0, &braced_init_obstack);
obstack_free (&braced_init_obstack, NULL);
return ret;
}
/* Parse a nested initializer, including designators. */
static void
c_parser_initelt (c_parser *parser, struct obstack * braced_init_obstack)
{
/* Parse any designator or designator list. A single array
designator may have the subsequent "=" omitted in GNU C, but a
longer list or a structure member designator may not. */
if (c_parser_next_token_is (parser, CPP_NAME)
&& c_parser_peek_2nd_token (parser)->type == CPP_COLON)
{
/* Old-style structure member designator. */
set_init_label (c_parser_peek_token (parser)->value,
braced_init_obstack);
/* Use the colon as the error location. */
pedwarn (c_parser_peek_2nd_token (parser)->location, OPT_pedantic,
"obsolete use of designated initializer with %<:%>");
c_parser_consume_token (parser);
c_parser_consume_token (parser);
}
else
{
/* des_seen is 0 if there have been no designators, 1 if there
has been a single array designator and 2 otherwise. */
int des_seen = 0;
/* Location of a designator. */
location_t des_loc = UNKNOWN_LOCATION; /* Quiet warning. */
while (c_parser_next_token_is (parser, CPP_OPEN_SQUARE)
|| c_parser_next_token_is (parser, CPP_DOT))
{
int des_prev = des_seen;
if (!des_seen)
des_loc = c_parser_peek_token (parser)->location;
if (des_seen < 2)
des_seen++;
if (c_parser_next_token_is (parser, CPP_DOT))
{
des_seen = 2;
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_NAME))
{
set_init_label (c_parser_peek_token (parser)->value,
braced_init_obstack);
c_parser_consume_token (parser);
}
else
{
struct c_expr init;
init.value = error_mark_node;
init.original_code = ERROR_MARK;
init.original_type = NULL;
c_parser_error (parser, "expected identifier");
c_parser_skip_until_found (parser, CPP_COMMA, NULL);
process_init_element (init, false, braced_init_obstack);
return;
}
}
else
{
tree first, second;
location_t ellipsis_loc = UNKNOWN_LOCATION; /* Quiet warning. */
/* ??? Following the old parser, [ objc-receiver
objc-message-args ] is accepted as an initializer,
being distinguished from a designator by what follows
the first assignment expression inside the square
brackets, but after a first array designator a
subsequent square bracket is for Objective-C taken to
start an expression, using the obsolete form of
designated initializer without '=', rather than
possibly being a second level of designation: in LALR
terms, the '[' is shifted rather than reducing
designator to designator-list. */
if (des_prev == 1 && c_dialect_objc ())
{
des_seen = des_prev;
break;
}
if (des_prev == 0 && c_dialect_objc ())
{
/* This might be an array designator or an
Objective-C message expression. If the former,
continue parsing here; if the latter, parse the
remainder of the initializer given the starting
primary-expression. ??? It might make sense to
distinguish when des_prev == 1 as well; see
previous comment. */
tree rec, args;
struct c_expr mexpr;
c_parser_consume_token (parser);
if (c_parser_peek_token (parser)->type == CPP_NAME
&& ((c_parser_peek_token (parser)->id_kind
== C_ID_TYPENAME)
|| (c_parser_peek_token (parser)->id_kind
== C_ID_CLASSNAME)))
{
/* Type name receiver. */
tree id = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
rec = objc_get_class_reference (id);
goto parse_message_args;
}
first = c_parser_expr_no_commas (parser, NULL).value;
mark_exp_read (first);
if (c_parser_next_token_is (parser, CPP_ELLIPSIS)
|| c_parser_next_token_is (parser, CPP_CLOSE_SQUARE))
goto array_desig_after_first;
/* Expression receiver. So far only one part
without commas has been parsed; there might be
more of the expression. */
rec = first;
while (c_parser_next_token_is (parser, CPP_COMMA))
{
struct c_expr next;
location_t comma_loc, exp_loc;
comma_loc = c_parser_peek_token (parser)->location;
c_parser_consume_token (parser);
exp_loc = c_parser_peek_token (parser)->location;
next = c_parser_expr_no_commas (parser, NULL);
next = default_function_array_read_conversion (exp_loc,
next);
rec = build_compound_expr (comma_loc, rec, next.value);
}
parse_message_args:
/* Now parse the objc-message-args. */
args = c_parser_objc_message_args (parser);
c_parser_skip_until_found (parser, CPP_CLOSE_SQUARE,
"expected %<]%>");
mexpr.value
= objc_build_message_expr (build_tree_list (rec, args));
mexpr.original_code = ERROR_MARK;
mexpr.original_type = NULL;
/* Now parse and process the remainder of the
initializer, starting with this message
expression as a primary-expression. */
c_parser_initval (parser, &mexpr, braced_init_obstack);
return;
}
c_parser_consume_token (parser);
first = c_parser_expr_no_commas (parser, NULL).value;
mark_exp_read (first);
array_desig_after_first:
if (c_parser_next_token_is (parser, CPP_ELLIPSIS))
{
ellipsis_loc = c_parser_peek_token (parser)->location;
c_parser_consume_token (parser);
second = c_parser_expr_no_commas (parser, NULL).value;
mark_exp_read (second);
}
else
second = NULL_TREE;
if (c_parser_next_token_is (parser, CPP_CLOSE_SQUARE))
{
c_parser_consume_token (parser);
set_init_index (first, second, braced_init_obstack);
if (second)
pedwarn (ellipsis_loc, OPT_pedantic,
"ISO C forbids specifying range of elements to initialize");
}
else
c_parser_skip_until_found (parser, CPP_CLOSE_SQUARE,
"expected %<]%>");
}
}
if (des_seen >= 1)
{
if (c_parser_next_token_is (parser, CPP_EQ))
{
if (!flag_isoc99)
pedwarn (des_loc, OPT_pedantic,
"ISO C90 forbids specifying subobject to initialize");
c_parser_consume_token (parser);
}
else
{
if (des_seen == 1)
pedwarn (c_parser_peek_token (parser)->location, OPT_pedantic,
"obsolete use of designated initializer without %<=%>");
else
{
struct c_expr init;
init.value = error_mark_node;
init.original_code = ERROR_MARK;
init.original_type = NULL;
c_parser_error (parser, "expected %<=%>");
c_parser_skip_until_found (parser, CPP_COMMA, NULL);
process_init_element (init, false, braced_init_obstack);
return;
}
}
}
}
c_parser_initval (parser, NULL, braced_init_obstack);
}
/* Parse a nested initializer; as c_parser_initializer but parses
initializers within braced lists, after any designators have been
applied. If AFTER is not NULL then it is an Objective-C message
expression which is the primary-expression starting the
initializer. */
static void
c_parser_initval (c_parser *parser, struct c_expr *after,
struct obstack * braced_init_obstack)
{
struct c_expr init;
gcc_assert (!after || c_dialect_objc ());
if (c_parser_next_token_is (parser, CPP_OPEN_BRACE) && !after)
init = c_parser_braced_init (parser, NULL_TREE, true);
else
{
location_t loc = c_parser_peek_token (parser)->location;
init = c_parser_expr_no_commas (parser, after);
if (init.value != NULL_TREE
&& TREE_CODE (init.value) != STRING_CST
&& TREE_CODE (init.value) != COMPOUND_LITERAL_EXPR)
init = default_function_array_read_conversion (loc, init);
}
process_init_element (init, false, braced_init_obstack);
}
/* Parse a compound statement (possibly a function body) (C90 6.6.2,
C99 6.8.2).
compound-statement:
{ block-item-list[opt] }
{ label-declarations block-item-list }
block-item-list:
block-item
block-item-list block-item
block-item:
nested-declaration
statement
nested-declaration:
declaration
GNU extensions:
compound-statement:
{ label-declarations block-item-list }
nested-declaration:
__extension__ nested-declaration
nested-function-definition
label-declarations:
label-declaration
label-declarations label-declaration
label-declaration:
__label__ identifier-list ;
Allowing the mixing of declarations and code is new in C99. The
GNU syntax also permits (not shown above) labels at the end of
compound statements, which yield an error. We don't allow labels
on declarations; this might seem like a natural extension, but
there would be a conflict between attributes on the label and
prefix attributes on the declaration. ??? The syntax follows the
old parser in requiring something after label declarations.
Although they are erroneous if the labels declared aren't defined,
is it useful for the syntax to be this way?
OpenMP:
block-item:
openmp-directive
openmp-directive:
barrier-directive
flush-directive */
static tree
c_parser_compound_statement (c_parser *parser)
{
tree stmt;
location_t brace_loc;
brace_loc = c_parser_peek_token (parser)->location;
if (!c_parser_require (parser, CPP_OPEN_BRACE, "expected %<{%>"))
{
/* Ensure a scope is entered and left anyway to avoid confusion
if we have just prepared to enter a function body. */
stmt = c_begin_compound_stmt (true);
c_end_compound_stmt (brace_loc, stmt, true);
return error_mark_node;
}
stmt = c_begin_compound_stmt (true);
c_parser_compound_statement_nostart (parser);
return c_end_compound_stmt (brace_loc, stmt, true);
}
/* Parse a compound statement except for the opening brace. This is
used for parsing both compound statements and statement expressions
(which follow different paths to handling the opening). */
static void
c_parser_compound_statement_nostart (c_parser *parser)
{
bool last_stmt = false;
bool last_label = false;
bool save_valid_for_pragma = valid_location_for_stdc_pragma_p ();
location_t label_loc = UNKNOWN_LOCATION; /* Quiet warning. */
if (c_parser_next_token_is (parser, CPP_CLOSE_BRACE))
{
c_parser_consume_token (parser);
return;
}
mark_valid_location_for_stdc_pragma (true);
if (c_parser_next_token_is_keyword (parser, RID_LABEL))
{
/* Read zero or more forward-declarations for labels that nested
functions can jump to. */
mark_valid_location_for_stdc_pragma (false);
while (c_parser_next_token_is_keyword (parser, RID_LABEL))
{
label_loc = c_parser_peek_token (parser)->location;
c_parser_consume_token (parser);
/* Any identifiers, including those declared as type names,
are OK here. */
while (true)
{
tree label;
if (c_parser_next_token_is_not (parser, CPP_NAME))
{
c_parser_error (parser, "expected identifier");
break;
}
label
= declare_label (c_parser_peek_token (parser)->value);
C_DECLARED_LABEL_FLAG (label) = 1;
add_stmt (build_stmt (label_loc, DECL_EXPR, label));
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_COMMA))
c_parser_consume_token (parser);
else
break;
}
c_parser_skip_until_found (parser, CPP_SEMICOLON, "expected %<;%>");
}
pedwarn (label_loc, OPT_pedantic, "ISO C forbids label declarations");
}
/* We must now have at least one statement, label or declaration. */
if (c_parser_next_token_is (parser, CPP_CLOSE_BRACE))
{
mark_valid_location_for_stdc_pragma (save_valid_for_pragma);
c_parser_error (parser, "expected declaration or statement");
c_parser_consume_token (parser);
return;
}
while (c_parser_next_token_is_not (parser, CPP_CLOSE_BRACE))
{
location_t loc = c_parser_peek_token (parser)->location;
if (c_parser_next_token_is_keyword (parser, RID_CASE)
|| c_parser_next_token_is_keyword (parser, RID_DEFAULT)
|| (c_parser_next_token_is (parser, CPP_NAME)
&& c_parser_peek_2nd_token (parser)->type == CPP_COLON))
{
if (c_parser_next_token_is_keyword (parser, RID_CASE))
label_loc = c_parser_peek_2nd_token (parser)->location;
else
label_loc = c_parser_peek_token (parser)->location;
last_label = true;
last_stmt = false;
mark_valid_location_for_stdc_pragma (false);
c_parser_label (parser);
}
else if (!last_label
&& c_parser_next_tokens_start_declaration (parser))
{
last_label = false;
mark_valid_location_for_stdc_pragma (false);
c_parser_declaration_or_fndef (parser, true, true, true, true, true, NULL);
if (last_stmt)
pedwarn_c90 (loc,
(pedantic && !flag_isoc99)
? OPT_pedantic
: OPT_Wdeclaration_after_statement,
"ISO C90 forbids mixed declarations and code");
last_stmt = false;
}
else if (!last_label
&& c_parser_next_token_is_keyword (parser, RID_EXTENSION))
{
/* __extension__ can start a declaration, but is also an
unary operator that can start an expression. Consume all
but the last of a possible series of __extension__ to
determine which. */
while (c_parser_peek_2nd_token (parser)->type == CPP_KEYWORD
&& (c_parser_peek_2nd_token (parser)->keyword
== RID_EXTENSION))
c_parser_consume_token (parser);
if (c_token_starts_declaration (c_parser_peek_2nd_token (parser)))
{
int ext;
ext = disable_extension_diagnostics ();
c_parser_consume_token (parser);
last_label = false;
mark_valid_location_for_stdc_pragma (false);
c_parser_declaration_or_fndef (parser, true, true, true, true,
true, NULL);
/* Following the old parser, __extension__ does not
disable this diagnostic. */
restore_extension_diagnostics (ext);
if (last_stmt)
pedwarn_c90 (loc, (pedantic && !flag_isoc99)
? OPT_pedantic
: OPT_Wdeclaration_after_statement,
"ISO C90 forbids mixed declarations and code");
last_stmt = false;
}
else
goto statement;
}
else if (c_parser_next_token_is (parser, CPP_PRAGMA))
{
/* External pragmas, and some omp pragmas, are not associated
with regular c code, and so are not to be considered statements
syntactically. This ensures that the user doesn't put them
places that would turn into syntax errors if the directive
were ignored. */
if (c_parser_pragma (parser, pragma_compound))
last_label = false, last_stmt = true;
}
else if (c_parser_next_token_is (parser, CPP_EOF))
{
mark_valid_location_for_stdc_pragma (save_valid_for_pragma);
c_parser_error (parser, "expected declaration or statement");
return;
}
else if (c_parser_next_token_is_keyword (parser, RID_ELSE))
{
if (parser->in_if_block)
{
mark_valid_location_for_stdc_pragma (save_valid_for_pragma);
error_at (loc, """expected %<}%> before %<else%>");
return;
}
else
{
error_at (loc, "%<else%> without a previous %<if%>");
c_parser_consume_token (parser);
continue;
}
}
else
{
statement:
last_label = false;
last_stmt = true;
mark_valid_location_for_stdc_pragma (false);
c_parser_statement_after_labels (parser);
}
parser->error = false;
}
if (last_label)
error_at (label_loc, "label at end of compound statement");
c_parser_consume_token (parser);
/* Restore the value we started with. */
mark_valid_location_for_stdc_pragma (save_valid_for_pragma);
}
/* Parse a label (C90 6.6.1, C99 6.8.1).
label:
identifier : attributes[opt]
case constant-expression :
default :
GNU extensions:
label:
case constant-expression ... constant-expression :
The use of attributes on labels is a GNU extension. The syntax in
GNU C accepts any expressions without commas, non-constant
expressions being rejected later. */
static void
c_parser_label (c_parser *parser)
{
location_t loc1 = c_parser_peek_token (parser)->location;
tree label = NULL_TREE;
if (c_parser_next_token_is_keyword (parser, RID_CASE))
{
tree exp1, exp2;
c_parser_consume_token (parser);
exp1 = c_parser_expr_no_commas (parser, NULL).value;
if (c_parser_next_token_is (parser, CPP_COLON))
{
c_parser_consume_token (parser);
label = do_case (loc1, exp1, NULL_TREE);
}
else if (c_parser_next_token_is (parser, CPP_ELLIPSIS))
{
c_parser_consume_token (parser);
exp2 = c_parser_expr_no_commas (parser, NULL).value;
if (c_parser_require (parser, CPP_COLON, "expected %<:%>"))
label = do_case (loc1, exp1, exp2);
}
else
c_parser_error (parser, "expected %<:%> or %<...%>");
}
else if (c_parser_next_token_is_keyword (parser, RID_DEFAULT))
{
c_parser_consume_token (parser);
if (c_parser_require (parser, CPP_COLON, "expected %<:%>"))
label = do_case (loc1, NULL_TREE, NULL_TREE);
}
else
{
tree name = c_parser_peek_token (parser)->value;
tree tlab;
tree attrs;
location_t loc2 = c_parser_peek_token (parser)->location;
gcc_assert (c_parser_next_token_is (parser, CPP_NAME));
c_parser_consume_token (parser);
gcc_assert (c_parser_next_token_is (parser, CPP_COLON));
c_parser_consume_token (parser);
attrs = c_parser_attributes (parser);
tlab = define_label (loc2, name);
if (tlab)
{
decl_attributes (&tlab, attrs, 0);
label = add_stmt (build_stmt (loc1, LABEL_EXPR, tlab));
}
}
if (label)
{
if (c_parser_next_tokens_start_declaration (parser))
{
error_at (c_parser_peek_token (parser)->location,
"a label can only be part of a statement and "
"a declaration is not a statement");
c_parser_declaration_or_fndef (parser, /*fndef_ok*/ false,
/*static_assert_ok*/ true,
/*nested*/ true, /*empty_ok*/ false,
/*start_attr_ok*/ true, NULL);
}
}
}
/* Parse a statement (C90 6.6, C99 6.8).
statement:
labeled-statement
compound-statement
expression-statement
selection-statement
iteration-statement
jump-statement
labeled-statement:
label statement
expression-statement:
expression[opt] ;
selection-statement:
if-statement
switch-statement
iteration-statement:
while-statement
do-statement
for-statement
jump-statement:
goto identifier ;
continue ;
break ;
return expression[opt] ;
GNU extensions:
statement:
asm-statement
jump-statement:
goto * expression ;
Objective-C:
statement:
objc-throw-statement
objc-try-catch-statement
objc-synchronized-statement
objc-throw-statement:
@throw expression ;
@throw ;
OpenMP:
statement:
openmp-construct
openmp-construct:
parallel-construct
for-construct
sections-construct
single-construct
parallel-for-construct
parallel-sections-construct
master-construct
critical-construct
atomic-construct
ordered-construct
parallel-construct:
parallel-directive structured-block
for-construct:
for-directive iteration-statement
sections-construct:
sections-directive section-scope
single-construct:
single-directive structured-block
parallel-for-construct:
parallel-for-directive iteration-statement
parallel-sections-construct:
parallel-sections-directive section-scope
master-construct:
master-directive structured-block
critical-construct:
critical-directive structured-block
atomic-construct:
atomic-directive expression-statement
ordered-construct:
ordered-directive structured-block */
static void
c_parser_statement (c_parser *parser)
{
while (c_parser_next_token_is_keyword (parser, RID_CASE)
|| c_parser_next_token_is_keyword (parser, RID_DEFAULT)
|| (c_parser_next_token_is (parser, CPP_NAME)
&& c_parser_peek_2nd_token (parser)->type == CPP_COLON))
c_parser_label (parser);
c_parser_statement_after_labels (parser);
}
/* Parse a statement, other than a labeled statement. */
static void
c_parser_statement_after_labels (c_parser *parser)
{
location_t loc = c_parser_peek_token (parser)->location;
tree stmt = NULL_TREE;
bool in_if_block = parser->in_if_block;
parser->in_if_block = false;
switch (c_parser_peek_token (parser)->type)
{
case CPP_OPEN_BRACE:
add_stmt (c_parser_compound_statement (parser));
break;
case CPP_KEYWORD:
switch (c_parser_peek_token (parser)->keyword)
{
case RID_IF:
c_parser_if_statement (parser);
break;
case RID_SWITCH:
c_parser_switch_statement (parser);
break;
case RID_WHILE:
c_parser_while_statement (parser);
break;
case RID_DO:
c_parser_do_statement (parser);
break;
case RID_FOR:
c_parser_for_statement (parser);
break;
case RID_GOTO:
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_NAME))
{
stmt = c_finish_goto_label (loc,
c_parser_peek_token (parser)->value);
c_parser_consume_token (parser);
}
else if (c_parser_next_token_is (parser, CPP_MULT))
{
tree val;
c_parser_consume_token (parser);
val = c_parser_expression (parser).value;
mark_exp_read (val);
stmt = c_finish_goto_ptr (loc, val);
}
else
c_parser_error (parser, "expected identifier or %<*%>");
goto expect_semicolon;
case RID_CONTINUE:
c_parser_consume_token (parser);
stmt = c_finish_bc_stmt (loc, &c_cont_label, false);
goto expect_semicolon;
case RID_BREAK:
c_parser_consume_token (parser);
stmt = c_finish_bc_stmt (loc, &c_break_label, true);
goto expect_semicolon;
case RID_RETURN:
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_SEMICOLON))
{
stmt = c_finish_return (loc, NULL_TREE, NULL_TREE);
c_parser_consume_token (parser);
}
else
{
struct c_expr expr = c_parser_expression_conv (parser);
mark_exp_read (expr.value);
stmt = c_finish_return (loc, expr.value, expr.original_type);
goto expect_semicolon;
}
break;
case RID_ASM:
stmt = c_parser_asm_statement (parser);
break;
case RID_AT_THROW:
gcc_assert (c_dialect_objc ());
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_SEMICOLON))
{
stmt = objc_build_throw_stmt (loc, NULL_TREE);
c_parser_consume_token (parser);
}
else
{
tree expr = c_parser_expression (parser).value;
expr = c_fully_fold (expr, false, NULL);
stmt = objc_build_throw_stmt (loc, expr);
goto expect_semicolon;
}
break;
case RID_AT_TRY:
gcc_assert (c_dialect_objc ());
c_parser_objc_try_catch_finally_statement (parser);
break;
case RID_AT_SYNCHRONIZED:
gcc_assert (c_dialect_objc ());
c_parser_objc_synchronized_statement (parser);
break;
default:
goto expr_stmt;
}
break;
case CPP_SEMICOLON:
c_parser_consume_token (parser);
break;
case CPP_CLOSE_PAREN:
case CPP_CLOSE_SQUARE:
/* Avoid infinite loop in error recovery:
c_parser_skip_until_found stops at a closing nesting
delimiter without consuming it, but here we need to consume
it to proceed further. */
c_parser_error (parser, "expected statement");
c_parser_consume_token (parser);
break;
case CPP_PRAGMA:
c_parser_pragma (parser, pragma_stmt);
break;
default:
expr_stmt:
stmt = c_finish_expr_stmt (loc, c_parser_expression_conv (parser).value);
expect_semicolon:
c_parser_skip_until_found (parser, CPP_SEMICOLON, "expected %<;%>");
break;
}
/* Two cases cannot and do not have line numbers associated: If stmt
is degenerate, such as "2;", then stmt is an INTEGER_CST, which
cannot hold line numbers. But that's OK because the statement
will either be changed to a MODIFY_EXPR during gimplification of
the statement expr, or discarded. If stmt was compound, but
without new variables, we will have skipped the creation of a
BIND and will have a bare STATEMENT_LIST. But that's OK because
(recursively) all of the component statements should already have
line numbers assigned. ??? Can we discard no-op statements
earlier? */
if (CAN_HAVE_LOCATION_P (stmt)
&& EXPR_LOCATION (stmt) == UNKNOWN_LOCATION)
SET_EXPR_LOCATION (stmt, loc);
parser->in_if_block = in_if_block;
}
/* Parse the condition from an if, do, while or for statements. */
static tree
c_parser_condition (c_parser *parser)
{
location_t loc = c_parser_peek_token (parser)->location;
tree cond;
cond = c_parser_expression_conv (parser).value;
cond = c_objc_common_truthvalue_conversion (loc, cond);
cond = c_fully_fold (cond, false, NULL);
if (warn_sequence_point)
verify_sequence_points (cond);
return cond;
}
/* Parse a parenthesized condition from an if, do or while statement.
condition:
( expression )
*/
static tree
c_parser_paren_condition (c_parser *parser)
{
tree cond;
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
return error_mark_node;
cond = c_parser_condition (parser);
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, "expected %<)%>");
return cond;
}
/* Parse a statement which is a block in C99. */
static tree
c_parser_c99_block_statement (c_parser *parser)
{
tree block = c_begin_compound_stmt (flag_isoc99);
location_t loc = c_parser_peek_token (parser)->location;
c_parser_statement (parser);
return c_end_compound_stmt (loc, block, flag_isoc99);
}
/* Parse the body of an if statement. This is just parsing a
statement but (a) it is a block in C99, (b) we track whether the
body is an if statement for the sake of -Wparentheses warnings, (c)
we handle an empty body specially for the sake of -Wempty-body
warnings, and (d) we call parser_compound_statement directly
because c_parser_statement_after_labels resets
parser->in_if_block. */
static tree
c_parser_if_body (c_parser *parser, bool *if_p)
{
tree block = c_begin_compound_stmt (flag_isoc99);
location_t body_loc = c_parser_peek_token (parser)->location;
while (c_parser_next_token_is_keyword (parser, RID_CASE)
|| c_parser_next_token_is_keyword (parser, RID_DEFAULT)
|| (c_parser_next_token_is (parser, CPP_NAME)
&& c_parser_peek_2nd_token (parser)->type == CPP_COLON))
c_parser_label (parser);
*if_p = c_parser_next_token_is_keyword (parser, RID_IF);
if (c_parser_next_token_is (parser, CPP_SEMICOLON))
{
location_t loc = c_parser_peek_token (parser)->location;
add_stmt (build_empty_stmt (loc));
c_parser_consume_token (parser);
if (!c_parser_next_token_is_keyword (parser, RID_ELSE))
warning_at (loc, OPT_Wempty_body,
"suggest braces around empty body in an %<if%> statement");
}
else if (c_parser_next_token_is (parser, CPP_OPEN_BRACE))
add_stmt (c_parser_compound_statement (parser));
else
c_parser_statement_after_labels (parser);
return c_end_compound_stmt (body_loc, block, flag_isoc99);
}
/* Parse the else body of an if statement. This is just parsing a
statement but (a) it is a block in C99, (b) we handle an empty body
specially for the sake of -Wempty-body warnings. */
static tree
c_parser_else_body (c_parser *parser)
{
location_t else_loc = c_parser_peek_token (parser)->location;
tree block = c_begin_compound_stmt (flag_isoc99);
while (c_parser_next_token_is_keyword (parser, RID_CASE)
|| c_parser_next_token_is_keyword (parser, RID_DEFAULT)
|| (c_parser_next_token_is (parser, CPP_NAME)
&& c_parser_peek_2nd_token (parser)->type == CPP_COLON))
c_parser_label (parser);
if (c_parser_next_token_is (parser, CPP_SEMICOLON))
{
location_t loc = c_parser_peek_token (parser)->location;
warning_at (loc,
OPT_Wempty_body,
"suggest braces around empty body in an %<else%> statement");
add_stmt (build_empty_stmt (loc));
c_parser_consume_token (parser);
}
else
c_parser_statement_after_labels (parser);
return c_end_compound_stmt (else_loc, block, flag_isoc99);
}
/* Parse an if statement (C90 6.6.4, C99 6.8.4).
if-statement:
if ( expression ) statement
if ( expression ) statement else statement
*/
static void
c_parser_if_statement (c_parser *parser)
{
tree block;
location_t loc;
tree cond;
bool first_if = false;
tree first_body, second_body;
bool in_if_block;
gcc_assert (c_parser_next_token_is_keyword (parser, RID_IF));
c_parser_consume_token (parser);
block = c_begin_compound_stmt (flag_isoc99);
loc = c_parser_peek_token (parser)->location;
cond = c_parser_paren_condition (parser);
in_if_block = parser->in_if_block;
parser->in_if_block = true;
first_body = c_parser_if_body (parser, &first_if);
parser->in_if_block = in_if_block;
if (c_parser_next_token_is_keyword (parser, RID_ELSE))
{
c_parser_consume_token (parser);
second_body = c_parser_else_body (parser);
}
else
second_body = NULL_TREE;
c_finish_if_stmt (loc, cond, first_body, second_body, first_if);
add_stmt (c_end_compound_stmt (loc, block, flag_isoc99));
}
/* Parse a switch statement (C90 6.6.4, C99 6.8.4).
switch-statement:
switch (expression) statement
*/
static void
c_parser_switch_statement (c_parser *parser)
{
tree block, expr, body, save_break;
location_t switch_loc = c_parser_peek_token (parser)->location;
location_t switch_cond_loc;
gcc_assert (c_parser_next_token_is_keyword (parser, RID_SWITCH));
c_parser_consume_token (parser);
block = c_begin_compound_stmt (flag_isoc99);
if (c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
{
switch_cond_loc = c_parser_peek_token (parser)->location;
expr = c_parser_expression (parser).value;
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, "expected %<)%>");
}
else
{
switch_cond_loc = UNKNOWN_LOCATION;
expr = error_mark_node;
}
c_start_case (switch_loc, switch_cond_loc, expr);
save_break = c_break_label;
c_break_label = NULL_TREE;
body = c_parser_c99_block_statement (parser);
c_finish_case (body);
if (c_break_label)
{
location_t here = c_parser_peek_token (parser)->location;
tree t = build1 (LABEL_EXPR, void_type_node, c_break_label);
SET_EXPR_LOCATION (t, here);
add_stmt (t);
}
c_break_label = save_break;
add_stmt (c_end_compound_stmt (switch_loc, block, flag_isoc99));
}
/* Parse a while statement (C90 6.6.5, C99 6.8.5).
while-statement:
while (expression) statement
*/
static void
c_parser_while_statement (c_parser *parser)
{
tree block, cond, body, save_break, save_cont;
location_t loc;
gcc_assert (c_parser_next_token_is_keyword (parser, RID_WHILE));
c_parser_consume_token (parser);
block = c_begin_compound_stmt (flag_isoc99);
loc = c_parser_peek_token (parser)->location;
cond = c_parser_paren_condition (parser);
save_break = c_break_label;
c_break_label = NULL_TREE;
save_cont = c_cont_label;
c_cont_label = NULL_TREE;
body = c_parser_c99_block_statement (parser);
c_finish_loop (loc, cond, NULL, body, c_break_label, c_cont_label, true);
add_stmt (c_end_compound_stmt (loc, block, flag_isoc99));
c_break_label = save_break;
c_cont_label = save_cont;
}
/* Parse a do statement (C90 6.6.5, C99 6.8.5).
do-statement:
do statement while ( expression ) ;
*/
static void
c_parser_do_statement (c_parser *parser)
{
tree block, cond, body, save_break, save_cont, new_break, new_cont;
location_t loc;
gcc_assert (c_parser_next_token_is_keyword (parser, RID_DO));
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_SEMICOLON))
warning_at (c_parser_peek_token (parser)->location,
OPT_Wempty_body,
"suggest braces around empty body in %<do%> statement");
block = c_begin_compound_stmt (flag_isoc99);
loc = c_parser_peek_token (parser)->location;
save_break = c_break_label;
c_break_label = NULL_TREE;
save_cont = c_cont_label;
c_cont_label = NULL_TREE;
body = c_parser_c99_block_statement (parser);
c_parser_require_keyword (parser, RID_WHILE, "expected %<while%>");
new_break = c_break_label;
c_break_label = save_break;
new_cont = c_cont_label;
c_cont_label = save_cont;
cond = c_parser_paren_condition (parser);
if (!c_parser_require (parser, CPP_SEMICOLON, "expected %<;%>"))
c_parser_skip_to_end_of_block_or_statement (parser);
c_finish_loop (loc, cond, NULL, body, new_break, new_cont, false);
add_stmt (c_end_compound_stmt (loc, block, flag_isoc99));
}
/* Parse a for statement (C90 6.6.5, C99 6.8.5).
for-statement:
for ( expression[opt] ; expression[opt] ; expression[opt] ) statement
for ( nested-declaration expression[opt] ; expression[opt] ) statement
The form with a declaration is new in C99.
??? In accordance with the old parser, the declaration may be a
nested function, which is then rejected in check_for_loop_decls,
but does it make any sense for this to be included in the grammar?
Note in particular that the nested function does not include a
trailing ';', whereas the "declaration" production includes one.
Also, can we reject bad declarations earlier and cheaper than
check_for_loop_decls?
In Objective-C, there are two additional variants:
foreach-statement:
for ( expression in expresssion ) statement
for ( declaration in expression ) statement
This is inconsistent with C, because the second variant is allowed
even if c99 is not enabled.
The rest of the comment documents these Objective-C foreach-statement.
Here is the canonical example of the first variant:
for (object in array) { do something with object }
we call the first expression ("object") the "object_expression" and
the second expression ("array") the "collection_expression".
object_expression must be an lvalue of type "id" (a generic Objective-C
object) because the loop works by assigning to object_expression the
various objects from the collection_expression. collection_expression
must evaluate to something of type "id" which responds to the method
countByEnumeratingWithState:objects:count:.
The canonical example of the second variant is:
for (id object in array) { do something with object }
which is completely equivalent to
{
id object;
for (object in array) { do something with object }
}
Note that initizializing 'object' in some way (eg, "for ((object =
xxx) in array) { do something with object }") is possibly
technically valid, but completely pointless as 'object' will be
assigned to something else as soon as the loop starts. We should
most likely reject it (TODO).
The beginning of the Objective-C foreach-statement looks exactly
like the beginning of the for-statement, and we can tell it is a
foreach-statement only because the initial declaration or
expression is terminated by 'in' instead of ';'.
*/
static void
c_parser_for_statement (c_parser *parser)
{
tree block, cond, incr, save_break, save_cont, body;
/* The following are only used when parsing an ObjC foreach statement. */
tree object_expression;
/* Silence the bogus uninitialized warning. */
tree collection_expression = NULL;
location_t loc = c_parser_peek_token (parser)->location;
location_t for_loc = c_parser_peek_token (parser)->location;
bool is_foreach_statement = false;
gcc_assert (c_parser_next_token_is_keyword (parser, RID_FOR));
c_parser_consume_token (parser);
/* Open a compound statement in Objective-C as well, just in case this is
as foreach expression. */
block = c_begin_compound_stmt (flag_isoc99 || c_dialect_objc ());
cond = error_mark_node;
incr = error_mark_node;
if (c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
{
/* Parse the initialization declaration or expression. */
object_expression = error_mark_node;
parser->objc_could_be_foreach_context = c_dialect_objc ();
if (c_parser_next_token_is (parser, CPP_SEMICOLON))
{
parser->objc_could_be_foreach_context = false;
c_parser_consume_token (parser);
c_finish_expr_stmt (loc, NULL_TREE);
}
else if (c_parser_next_tokens_start_declaration (parser))
{
c_parser_declaration_or_fndef (parser, true, true, true, true, true,
&object_expression);
parser->objc_could_be_foreach_context = false;
if (c_parser_next_token_is_keyword (parser, RID_IN))
{
c_parser_consume_token (parser);
is_foreach_statement = true;
if (check_for_loop_decls (for_loc, true) == NULL_TREE)
c_parser_error (parser, "multiple iterating variables in fast enumeration");
}
else
check_for_loop_decls (for_loc, flag_isoc99);
}
else if (c_parser_next_token_is_keyword (parser, RID_EXTENSION))
{
/* __extension__ can start a declaration, but is also an
unary operator that can start an expression. Consume all
but the last of a possible series of __extension__ to
determine which. */
while (c_parser_peek_2nd_token (parser)->type == CPP_KEYWORD
&& (c_parser_peek_2nd_token (parser)->keyword
== RID_EXTENSION))
c_parser_consume_token (parser);
if (c_token_starts_declaration (c_parser_peek_2nd_token (parser)))
{
int ext;
ext = disable_extension_diagnostics ();
c_parser_consume_token (parser);
c_parser_declaration_or_fndef (parser, true, true, true, true,
true, &object_expression);
parser->objc_could_be_foreach_context = false;
restore_extension_diagnostics (ext);
if (c_parser_next_token_is_keyword (parser, RID_IN))
{
c_parser_consume_token (parser);
is_foreach_statement = true;
if (check_for_loop_decls (for_loc, true) == NULL_TREE)
c_parser_error (parser, "multiple iterating variables in fast enumeration");
}
else
check_for_loop_decls (for_loc, flag_isoc99);
}
else
goto init_expr;
}
else
{
init_expr:
{
tree init_expression;
init_expression = c_parser_expression (parser).value;
parser->objc_could_be_foreach_context = false;
if (c_parser_next_token_is_keyword (parser, RID_IN))
{
c_parser_consume_token (parser);
is_foreach_statement = true;
if (! lvalue_p (init_expression))
c_parser_error (parser, "invalid iterating variable in fast enumeration");
object_expression = c_fully_fold (init_expression, false, NULL);
}
else
{
c_finish_expr_stmt (loc, init_expression);
c_parser_skip_until_found (parser, CPP_SEMICOLON, "expected %<;%>");
}
}
}
/* Parse the loop condition. In the case of a foreach
statement, there is no loop condition. */
gcc_assert (!parser->objc_could_be_foreach_context);
if (!is_foreach_statement)
{
if (c_parser_next_token_is (parser, CPP_SEMICOLON))
{
c_parser_consume_token (parser);
cond = NULL_TREE;
}
else
{
cond = c_parser_condition (parser);
c_parser_skip_until_found (parser, CPP_SEMICOLON, "expected %<;%>");
}
}
/* Parse the increment expression (the third expression in a
for-statement). In the case of a foreach-statement, this is
the expression that follows the 'in'. */
if (c_parser_next_token_is (parser, CPP_CLOSE_PAREN))
{
if (is_foreach_statement)
{
c_parser_error (parser, "missing collection in fast enumeration");
collection_expression = error_mark_node;
}
else
incr = c_process_expr_stmt (loc, NULL_TREE);
}
else
{
if (is_foreach_statement)
collection_expression = c_fully_fold (c_parser_expression (parser).value,
false, NULL);
else
incr = c_process_expr_stmt (loc, c_parser_expression (parser).value);
}
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, "expected %<)%>");
}
save_break = c_break_label;
c_break_label = NULL_TREE;
save_cont = c_cont_label;
c_cont_label = NULL_TREE;
body = c_parser_c99_block_statement (parser);
if (is_foreach_statement)
objc_finish_foreach_loop (loc, object_expression, collection_expression, body, c_break_label, c_cont_label);
else
c_finish_loop (loc, cond, incr, body, c_break_label, c_cont_label, true);
add_stmt (c_end_compound_stmt (loc, block, flag_isoc99 || c_dialect_objc ()));
c_break_label = save_break;
c_cont_label = save_cont;
}
/* Parse an asm statement, a GNU extension. This is a full-blown asm
statement with inputs, outputs, clobbers, and volatile tag
allowed.
asm-statement:
asm type-qualifier[opt] ( asm-argument ) ;
asm type-qualifier[opt] goto ( asm-goto-argument ) ;
asm-argument:
asm-string-literal
asm-string-literal : asm-operands[opt]
asm-string-literal : asm-operands[opt] : asm-operands[opt]
asm-string-literal : asm-operands[opt] : asm-operands[opt] : asm-clobbers[opt]
asm-goto-argument:
asm-string-literal : : asm-operands[opt] : asm-clobbers[opt] \
: asm-goto-operands
Qualifiers other than volatile are accepted in the syntax but
warned for. */
static tree
c_parser_asm_statement (c_parser *parser)
{
tree quals, str, outputs, inputs, clobbers, labels, ret;
bool simple, is_goto;
location_t asm_loc = c_parser_peek_token (parser)->location;
int section, nsections;
gcc_assert (c_parser_next_token_is_keyword (parser, RID_ASM));
c_parser_consume_token (parser);
if (c_parser_next_token_is_keyword (parser, RID_VOLATILE))
{
quals = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
}
else if (c_parser_next_token_is_keyword (parser, RID_CONST)
|| c_parser_next_token_is_keyword (parser, RID_RESTRICT))
{
warning_at (c_parser_peek_token (parser)->location,
0,
"%E qualifier ignored on asm",
c_parser_peek_token (parser)->value);
quals = NULL_TREE;
c_parser_consume_token (parser);
}
else
quals = NULL_TREE;
is_goto = false;
if (c_parser_next_token_is_keyword (parser, RID_GOTO))
{
c_parser_consume_token (parser);
is_goto = true;
}
/* ??? Follow the C++ parser rather than using the
lex_untranslated_string kludge. */
parser->lex_untranslated_string = true;
ret = NULL;
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
goto error;
str = c_parser_asm_string_literal (parser);
if (str == NULL_TREE)
goto error_close_paren;
simple = true;
outputs = NULL_TREE;
inputs = NULL_TREE;
clobbers = NULL_TREE;
labels = NULL_TREE;
if (c_parser_next_token_is (parser, CPP_CLOSE_PAREN) && !is_goto)
goto done_asm;
/* Parse each colon-delimited section of operands. */
nsections = 3 + is_goto;
for (section = 0; section < nsections; ++section)
{
if (!c_parser_require (parser, CPP_COLON,
is_goto
? "expected %<:%>"
: "expected %<:%> or %<)%>"))
goto error_close_paren;
/* Once past any colon, we're no longer a simple asm. */
simple = false;
if ((!c_parser_next_token_is (parser, CPP_COLON)
&& !c_parser_next_token_is (parser, CPP_CLOSE_PAREN))
|| section == 3)
switch (section)
{
case 0:
/* For asm goto, we don't allow output operands, but reserve
the slot for a future extension that does allow them. */
if (!is_goto)
outputs = c_parser_asm_operands (parser, false);
break;
case 1:
inputs = c_parser_asm_operands (parser, true);
break;
case 2:
clobbers = c_parser_asm_clobbers (parser);
break;
case 3:
labels = c_parser_asm_goto_operands (parser);
break;
default:
gcc_unreachable ();
}
if (c_parser_next_token_is (parser, CPP_CLOSE_PAREN) && !is_goto)
goto done_asm;
}
done_asm:
if (!c_parser_require (parser, CPP_CLOSE_PAREN, "expected %<)%>"))
{
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, NULL);
goto error;
}
if (!c_parser_require (parser, CPP_SEMICOLON, "expected %<;%>"))
c_parser_skip_to_end_of_block_or_statement (parser);
ret = build_asm_stmt (quals, build_asm_expr (asm_loc, str, outputs, inputs,
clobbers, labels, simple));
error:
parser->lex_untranslated_string = false;
return ret;
error_close_paren:
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, NULL);
goto error;
}
/* Parse asm operands, a GNU extension. If CONVERT_P (for inputs but
not outputs), apply the default conversion of functions and arrays
to pointers.
asm-operands:
asm-operand
asm-operands , asm-operand
asm-operand:
asm-string-literal ( expression )
[ identifier ] asm-string-literal ( expression )
*/
static tree
c_parser_asm_operands (c_parser *parser, bool convert_p)
{
tree list = NULL_TREE;
location_t loc;
while (true)
{
tree name, str;
struct c_expr expr;
if (c_parser_next_token_is (parser, CPP_OPEN_SQUARE))
{
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_NAME))
{
tree id = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
name = build_string (IDENTIFIER_LENGTH (id),
IDENTIFIER_POINTER (id));
}
else
{
c_parser_error (parser, "expected identifier");
c_parser_skip_until_found (parser, CPP_CLOSE_SQUARE, NULL);
return NULL_TREE;
}
c_parser_skip_until_found (parser, CPP_CLOSE_SQUARE,
"expected %<]%>");
}
else
name = NULL_TREE;
str = c_parser_asm_string_literal (parser);
if (str == NULL_TREE)
return NULL_TREE;
parser->lex_untranslated_string = false;
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
{
parser->lex_untranslated_string = true;
return NULL_TREE;
}
loc = c_parser_peek_token (parser)->location;
expr = c_parser_expression (parser);
mark_exp_read (expr.value);
if (convert_p)
expr = default_function_array_conversion (loc, expr);
expr.value = c_fully_fold (expr.value, false, NULL);
parser->lex_untranslated_string = true;
if (!c_parser_require (parser, CPP_CLOSE_PAREN, "expected %<)%>"))
{
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, NULL);
return NULL_TREE;
}
list = chainon (list, build_tree_list (build_tree_list (name, str),
expr.value));
if (c_parser_next_token_is (parser, CPP_COMMA))
c_parser_consume_token (parser);
else
break;
}
return list;
}
/* Parse asm clobbers, a GNU extension.
asm-clobbers:
asm-string-literal
asm-clobbers , asm-string-literal
*/
static tree
c_parser_asm_clobbers (c_parser *parser)
{
tree list = NULL_TREE;
while (true)
{
tree str = c_parser_asm_string_literal (parser);
if (str)
list = tree_cons (NULL_TREE, str, list);
else
return NULL_TREE;
if (c_parser_next_token_is (parser, CPP_COMMA))
c_parser_consume_token (parser);
else
break;
}
return list;
}
/* Parse asm goto labels, a GNU extension.
asm-goto-operands:
identifier
asm-goto-operands , identifier
*/
static tree
c_parser_asm_goto_operands (c_parser *parser)
{
tree list = NULL_TREE;
while (true)
{
tree name, label;
if (c_parser_next_token_is (parser, CPP_NAME))
{
c_token *tok = c_parser_peek_token (parser);
name = tok->value;
label = lookup_label_for_goto (tok->location, name);
c_parser_consume_token (parser);
TREE_USED (label) = 1;
}
else
{
c_parser_error (parser, "expected identifier");
return NULL_TREE;
}
name = build_string (IDENTIFIER_LENGTH (name),
IDENTIFIER_POINTER (name));
list = tree_cons (name, label, list);
if (c_parser_next_token_is (parser, CPP_COMMA))
c_parser_consume_token (parser);
else
return nreverse (list);
}
}
/* Parse an expression other than a compound expression; that is, an
assignment expression (C90 6.3.16, C99 6.5.16). If AFTER is not
NULL then it is an Objective-C message expression which is the
primary-expression starting the expression as an initializer.
assignment-expression:
conditional-expression
unary-expression assignment-operator assignment-expression
assignment-operator: one of
= *= /= %= += -= <<= >>= &= ^= |=
In GNU C we accept any conditional expression on the LHS and
diagnose the invalid lvalue rather than producing a syntax
error. */
static struct c_expr
c_parser_expr_no_commas (c_parser *parser, struct c_expr *after)
{
struct c_expr lhs, rhs, ret;
enum tree_code code;
location_t op_location, exp_location;
gcc_assert (!after || c_dialect_objc ());
lhs = c_parser_conditional_expression (parser, after);
op_location = c_parser_peek_token (parser)->location;
switch (c_parser_peek_token (parser)->type)
{
case CPP_EQ:
code = NOP_EXPR;
break;
case CPP_MULT_EQ:
code = MULT_EXPR;
break;
case CPP_DIV_EQ:
code = TRUNC_DIV_EXPR;
break;
case CPP_MOD_EQ:
code = TRUNC_MOD_EXPR;
break;
case CPP_PLUS_EQ:
code = PLUS_EXPR;
break;
case CPP_MINUS_EQ:
code = MINUS_EXPR;
break;
case CPP_LSHIFT_EQ:
code = LSHIFT_EXPR;
break;
case CPP_RSHIFT_EQ:
code = RSHIFT_EXPR;
break;
case CPP_AND_EQ:
code = BIT_AND_EXPR;
break;
case CPP_XOR_EQ:
code = BIT_XOR_EXPR;
break;
case CPP_OR_EQ:
code = BIT_IOR_EXPR;
break;
default:
return lhs;
}
c_parser_consume_token (parser);
exp_location = c_parser_peek_token (parser)->location;
rhs = c_parser_expr_no_commas (parser, NULL);
rhs = default_function_array_read_conversion (exp_location, rhs);
ret.value = build_modify_expr (op_location, lhs.value, lhs.original_type,
code, exp_location, rhs.value,
rhs.original_type);
if (code == NOP_EXPR)
ret.original_code = MODIFY_EXPR;
else
{
TREE_NO_WARNING (ret.value) = 1;
ret.original_code = ERROR_MARK;
}
ret.original_type = NULL;
return ret;
}
/* Parse a conditional expression (C90 6.3.15, C99 6.5.15). If AFTER
is not NULL then it is an Objective-C message expression which is
the primary-expression starting the expression as an initializer.
conditional-expression:
logical-OR-expression
logical-OR-expression ? expression : conditional-expression
GNU extensions:
conditional-expression:
logical-OR-expression ? : conditional-expression
*/
static struct c_expr
c_parser_conditional_expression (c_parser *parser, struct c_expr *after)
{
struct c_expr cond, exp1, exp2, ret;
location_t cond_loc, colon_loc, middle_loc;
gcc_assert (!after || c_dialect_objc ());
cond = c_parser_binary_expression (parser, after);
if (c_parser_next_token_is_not (parser, CPP_QUERY))
return cond;
cond_loc = c_parser_peek_token (parser)->location;
cond = default_function_array_read_conversion (cond_loc, cond);
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_COLON))
{
tree eptype = NULL_TREE;
middle_loc = c_parser_peek_token (parser)->location;
pedwarn (middle_loc, OPT_pedantic,
"ISO C forbids omitting the middle term of a ?: expression");
warn_for_omitted_condop (middle_loc, cond.value);
if (TREE_CODE (cond.value) == EXCESS_PRECISION_EXPR)
{
eptype = TREE_TYPE (cond.value);
cond.value = TREE_OPERAND (cond.value, 0);
}
/* Make sure first operand is calculated only once. */
exp1.value = c_save_expr (default_conversion (cond.value));
if (eptype)
exp1.value = build1 (EXCESS_PRECISION_EXPR, eptype, exp1.value);
exp1.original_type = NULL;
cond.value = c_objc_common_truthvalue_conversion (cond_loc, exp1.value);
c_inhibit_evaluation_warnings += cond.value == truthvalue_true_node;
}
else
{
cond.value
= c_objc_common_truthvalue_conversion
(cond_loc, default_conversion (cond.value));
c_inhibit_evaluation_warnings += cond.value == truthvalue_false_node;
exp1 = c_parser_expression_conv (parser);
mark_exp_read (exp1.value);
c_inhibit_evaluation_warnings +=
((cond.value == truthvalue_true_node)
- (cond.value == truthvalue_false_node));
}
colon_loc = c_parser_peek_token (parser)->location;
if (!c_parser_require (parser, CPP_COLON, "expected %<:%>"))
{
c_inhibit_evaluation_warnings -= cond.value == truthvalue_true_node;
ret.value = error_mark_node;
ret.original_code = ERROR_MARK;
ret.original_type = NULL;
return ret;
}
{
location_t exp2_loc = c_parser_peek_token (parser)->location;
exp2 = c_parser_conditional_expression (parser, NULL);
exp2 = default_function_array_read_conversion (exp2_loc, exp2);
}
c_inhibit_evaluation_warnings -= cond.value == truthvalue_true_node;
ret.value = build_conditional_expr (colon_loc, cond.value,
cond.original_code == C_MAYBE_CONST_EXPR,
exp1.value, exp1.original_type,
exp2.value, exp2.original_type);
ret.original_code = ERROR_MARK;
if (exp1.value == error_mark_node || exp2.value == error_mark_node)
ret.original_type = NULL;
else
{
tree t1, t2;
/* If both sides are enum type, the default conversion will have
made the type of the result be an integer type. We want to
remember the enum types we started with. */
t1 = exp1.original_type ? exp1.original_type : TREE_TYPE (exp1.value);
t2 = exp2.original_type ? exp2.original_type : TREE_TYPE (exp2.value);
ret.original_type = ((t1 != error_mark_node
&& t2 != error_mark_node
&& (TYPE_MAIN_VARIANT (t1)
== TYPE_MAIN_VARIANT (t2)))
? t1
: NULL);
}
return ret;
}
/* Parse a binary expression; that is, a logical-OR-expression (C90
6.3.5-6.3.14, C99 6.5.5-6.5.14). If AFTER is not NULL then it is
an Objective-C message expression which is the primary-expression
starting the expression as an initializer.
multiplicative-expression:
cast-expression
multiplicative-expression * cast-expression
multiplicative-expression / cast-expression
multiplicative-expression % cast-expression
additive-expression:
multiplicative-expression
additive-expression + multiplicative-expression
additive-expression - multiplicative-expression
shift-expression:
additive-expression
shift-expression << additive-expression
shift-expression >> additive-expression
relational-expression:
shift-expression
relational-expression < shift-expression
relational-expression > shift-expression
relational-expression <= shift-expression
relational-expression >= shift-expression
equality-expression:
relational-expression
equality-expression == relational-expression
equality-expression != relational-expression
AND-expression:
equality-expression
AND-expression & equality-expression
exclusive-OR-expression:
AND-expression
exclusive-OR-expression ^ AND-expression
inclusive-OR-expression:
exclusive-OR-expression
inclusive-OR-expression | exclusive-OR-expression
logical-AND-expression:
inclusive-OR-expression
logical-AND-expression && inclusive-OR-expression
logical-OR-expression:
logical-AND-expression
logical-OR-expression || logical-AND-expression
*/
static struct c_expr
c_parser_binary_expression (c_parser *parser, struct c_expr *after)
{
/* A binary expression is parsed using operator-precedence parsing,
with the operands being cast expressions. All the binary
operators are left-associative. Thus a binary expression is of
form:
E0 op1 E1 op2 E2 ...
which we represent on a stack. On the stack, the precedence
levels are strictly increasing. When a new operator is
encountered of higher precedence than that at the top of the
stack, it is pushed; its LHS is the top expression, and its RHS
is everything parsed until it is popped. When a new operator is
encountered with precedence less than or equal to that at the top
of the stack, triples E[i-1] op[i] E[i] are popped and replaced
by the result of the operation until the operator at the top of
the stack has lower precedence than the new operator or there is
only one element on the stack; then the top expression is the LHS
of the new operator. In the case of logical AND and OR
expressions, we also need to adjust c_inhibit_evaluation_warnings
as appropriate when the operators are pushed and popped. */
/* The precedence levels, where 0 is a dummy lowest level used for
the bottom of the stack. */
enum prec {
PREC_NONE,
PREC_LOGOR,
PREC_LOGAND,
PREC_BITOR,
PREC_BITXOR,
PREC_BITAND,
PREC_EQ,
PREC_REL,
PREC_SHIFT,
PREC_ADD,
PREC_MULT,
NUM_PRECS
};
struct {
/* The expression at this stack level. */
struct c_expr expr;
/* The precedence of the operator on its left, PREC_NONE at the
bottom of the stack. */
enum prec prec;
/* The operation on its left. */
enum tree_code op;
/* The source location of this operation. */
location_t loc;
} stack[NUM_PRECS];
int sp;
/* Location of the binary operator. */
location_t binary_loc = UNKNOWN_LOCATION; /* Quiet warning. */
#define POP \
do { \
switch (stack[sp].op) \
{ \
case TRUTH_ANDIF_EXPR: \
c_inhibit_evaluation_warnings -= (stack[sp - 1].expr.value \
== truthvalue_false_node); \
break; \
case TRUTH_ORIF_EXPR: \
c_inhibit_evaluation_warnings -= (stack[sp - 1].expr.value \
== truthvalue_true_node); \
break; \
default: \
break; \
} \
stack[sp - 1].expr \
= default_function_array_read_conversion (stack[sp - 1].loc, \
stack[sp - 1].expr); \
stack[sp].expr \
= default_function_array_read_conversion (stack[sp].loc, \
stack[sp].expr); \
stack[sp - 1].expr = parser_build_binary_op (stack[sp].loc, \
stack[sp].op, \
stack[sp - 1].expr, \
stack[sp].expr); \
sp--; \
} while (0)
gcc_assert (!after || c_dialect_objc ());
stack[0].loc = c_parser_peek_token (parser)->location;
stack[0].expr = c_parser_cast_expression (parser, after);
stack[0].prec = PREC_NONE;
sp = 0;
while (true)
{
enum prec oprec;
enum tree_code ocode;
if (parser->error)
goto out;
switch (c_parser_peek_token (parser)->type)
{
case CPP_MULT:
oprec = PREC_MULT;
ocode = MULT_EXPR;
break;
case CPP_DIV:
oprec = PREC_MULT;
ocode = TRUNC_DIV_EXPR;
break;
case CPP_MOD:
oprec = PREC_MULT;
ocode = TRUNC_MOD_EXPR;
break;
case CPP_PLUS:
oprec = PREC_ADD;
ocode = PLUS_EXPR;
break;
case CPP_MINUS:
oprec = PREC_ADD;
ocode = MINUS_EXPR;
break;
case CPP_LSHIFT:
oprec = PREC_SHIFT;
ocode = LSHIFT_EXPR;
break;
case CPP_RSHIFT:
oprec = PREC_SHIFT;
ocode = RSHIFT_EXPR;
break;
case CPP_LESS:
oprec = PREC_REL;
ocode = LT_EXPR;
break;
case CPP_GREATER:
oprec = PREC_REL;
ocode = GT_EXPR;
break;
case CPP_LESS_EQ:
oprec = PREC_REL;
ocode = LE_EXPR;
break;
case CPP_GREATER_EQ:
oprec = PREC_REL;
ocode = GE_EXPR;
break;
case CPP_EQ_EQ:
oprec = PREC_EQ;
ocode = EQ_EXPR;
break;
case CPP_NOT_EQ:
oprec = PREC_EQ;
ocode = NE_EXPR;
break;
case CPP_AND:
oprec = PREC_BITAND;
ocode = BIT_AND_EXPR;
break;
case CPP_XOR:
oprec = PREC_BITXOR;
ocode = BIT_XOR_EXPR;
break;
case CPP_OR:
oprec = PREC_BITOR;
ocode = BIT_IOR_EXPR;
break;
case CPP_AND_AND:
oprec = PREC_LOGAND;
ocode = TRUTH_ANDIF_EXPR;
break;
case CPP_OR_OR:
oprec = PREC_LOGOR;
ocode = TRUTH_ORIF_EXPR;
break;
default:
/* Not a binary operator, so end of the binary
expression. */
goto out;
}
binary_loc = c_parser_peek_token (parser)->location;
c_parser_consume_token (parser);
while (oprec <= stack[sp].prec)
POP;
switch (ocode)
{
case TRUTH_ANDIF_EXPR:
stack[sp].expr
= default_function_array_read_conversion (stack[sp].loc,
stack[sp].expr);
stack[sp].expr.value = c_objc_common_truthvalue_conversion
(stack[sp].loc, default_conversion (stack[sp].expr.value));
c_inhibit_evaluation_warnings += (stack[sp].expr.value
== truthvalue_false_node);
break;
case TRUTH_ORIF_EXPR:
stack[sp].expr
= default_function_array_read_conversion (stack[sp].loc,
stack[sp].expr);
stack[sp].expr.value = c_objc_common_truthvalue_conversion
(stack[sp].loc, default_conversion (stack[sp].expr.value));
c_inhibit_evaluation_warnings += (stack[sp].expr.value
== truthvalue_true_node);
break;
default:
break;
}
sp++;
stack[sp].loc = binary_loc;
stack[sp].expr = c_parser_cast_expression (parser, NULL);
stack[sp].prec = oprec;
stack[sp].op = ocode;
stack[sp].loc = binary_loc;
}
out:
while (sp > 0)
POP;
return stack[0].expr;
#undef POP
}
/* Parse a cast expression (C90 6.3.4, C99 6.5.4). If AFTER is not
NULL then it is an Objective-C message expression which is the
primary-expression starting the expression as an initializer.
cast-expression:
unary-expression
( type-name ) unary-expression
*/
static struct c_expr
c_parser_cast_expression (c_parser *parser, struct c_expr *after)
{
location_t cast_loc = c_parser_peek_token (parser)->location;
gcc_assert (!after || c_dialect_objc ());
if (after)
return c_parser_postfix_expression_after_primary (parser,
cast_loc, *after);
/* If the expression begins with a parenthesized type name, it may
be either a cast or a compound literal; we need to see whether
the next character is '{' to tell the difference. If not, it is
an unary expression. Full detection of unknown typenames here
would require a 3-token lookahead. */
if (c_parser_next_token_is (parser, CPP_OPEN_PAREN)
&& c_token_starts_typename (c_parser_peek_2nd_token (parser)))
{
struct c_type_name *type_name;
struct c_expr ret;
struct c_expr expr;
c_parser_consume_token (parser);
type_name = c_parser_type_name (parser);
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, "expected %<)%>");
if (type_name == NULL)
{
ret.value = error_mark_node;
ret.original_code = ERROR_MARK;
ret.original_type = NULL;
return ret;
}
/* Save casted types in the function's used types hash table. */
used_types_insert (type_name->specs->type);
if (c_parser_next_token_is (parser, CPP_OPEN_BRACE))
return c_parser_postfix_expression_after_paren_type (parser, type_name,
cast_loc);
{
location_t expr_loc = c_parser_peek_token (parser)->location;
expr = c_parser_cast_expression (parser, NULL);
expr = default_function_array_read_conversion (expr_loc, expr);
}
ret.value = c_cast_expr (cast_loc, type_name, expr.value);
ret.original_code = ERROR_MARK;
ret.original_type = NULL;
return ret;
}
else
return c_parser_unary_expression (parser);
}
/* Parse an unary expression (C90 6.3.3, C99 6.5.3).
unary-expression:
postfix-expression
++ unary-expression
-- unary-expression
unary-operator cast-expression
sizeof unary-expression
sizeof ( type-name )
unary-operator: one of
& * + - ~ !
GNU extensions:
unary-expression:
__alignof__ unary-expression
__alignof__ ( type-name )
&& identifier
unary-operator: one of
__extension__ __real__ __imag__
In addition, the GNU syntax treats ++ and -- as unary operators, so
they may be applied to cast expressions with errors for non-lvalues
given later. */
static struct c_expr
c_parser_unary_expression (c_parser *parser)
{
int ext;
struct c_expr ret, op;
location_t op_loc = c_parser_peek_token (parser)->location;
location_t exp_loc;
ret.original_code = ERROR_MARK;
ret.original_type = NULL;
switch (c_parser_peek_token (parser)->type)
{
case CPP_PLUS_PLUS:
c_parser_consume_token (parser);
exp_loc = c_parser_peek_token (parser)->location;
op = c_parser_cast_expression (parser, NULL);
op = default_function_array_read_conversion (exp_loc, op);
return parser_build_unary_op (op_loc, PREINCREMENT_EXPR, op);
case CPP_MINUS_MINUS:
c_parser_consume_token (parser);
exp_loc = c_parser_peek_token (parser)->location;
op = c_parser_cast_expression (parser, NULL);
op = default_function_array_read_conversion (exp_loc, op);
return parser_build_unary_op (op_loc, PREDECREMENT_EXPR, op);
case CPP_AND:
c_parser_consume_token (parser);
op = c_parser_cast_expression (parser, NULL);
mark_exp_read (op.value);
return parser_build_unary_op (op_loc, ADDR_EXPR, op);
case CPP_MULT:
c_parser_consume_token (parser);
exp_loc = c_parser_peek_token (parser)->location;
op = c_parser_cast_expression (parser, NULL);
op = default_function_array_read_conversion (exp_loc, op);
ret.value = build_indirect_ref (op_loc, op.value, RO_UNARY_STAR);
return ret;
case CPP_PLUS:
if (!c_dialect_objc () && !in_system_header)
warning_at (op_loc,
OPT_Wtraditional,
"traditional C rejects the unary plus operator");
c_parser_consume_token (parser);
exp_loc = c_parser_peek_token (parser)->location;
op = c_parser_cast_expression (parser, NULL);
op = default_function_array_read_conversion (exp_loc, op);
return parser_build_unary_op (op_loc, CONVERT_EXPR, op);
case CPP_MINUS:
c_parser_consume_token (parser);
exp_loc = c_parser_peek_token (parser)->location;
op = c_parser_cast_expression (parser, NULL);
op = default_function_array_read_conversion (exp_loc, op);
return parser_build_unary_op (op_loc, NEGATE_EXPR, op);
case CPP_COMPL:
c_parser_consume_token (parser);
exp_loc = c_parser_peek_token (parser)->location;
op = c_parser_cast_expression (parser, NULL);
op = default_function_array_read_conversion (exp_loc, op);
return parser_build_unary_op (op_loc, BIT_NOT_EXPR, op);
case CPP_NOT:
c_parser_consume_token (parser);
exp_loc = c_parser_peek_token (parser)->location;
op = c_parser_cast_expression (parser, NULL);
op = default_function_array_read_conversion (exp_loc, op);
return parser_build_unary_op (op_loc, TRUTH_NOT_EXPR, op);
case CPP_AND_AND:
/* Refer to the address of a label as a pointer. */
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_NAME))
{
ret.value = finish_label_address_expr
(c_parser_peek_token (parser)->value, op_loc);
c_parser_consume_token (parser);
}
else
{
c_parser_error (parser, "expected identifier");
ret.value = error_mark_node;
}
return ret;
case CPP_KEYWORD:
switch (c_parser_peek_token (parser)->keyword)
{
case RID_SIZEOF:
return c_parser_sizeof_expression (parser);
case RID_ALIGNOF:
return c_parser_alignof_expression (parser);
case RID_EXTENSION:
c_parser_consume_token (parser);
ext = disable_extension_diagnostics ();
ret = c_parser_cast_expression (parser, NULL);
restore_extension_diagnostics (ext);
return ret;
case RID_REALPART:
c_parser_consume_token (parser);
exp_loc = c_parser_peek_token (parser)->location;
op = c_parser_cast_expression (parser, NULL);
op = default_function_array_conversion (exp_loc, op);
return parser_build_unary_op (op_loc, REALPART_EXPR, op);
case RID_IMAGPART:
c_parser_consume_token (parser);
exp_loc = c_parser_peek_token (parser)->location;
op = c_parser_cast_expression (parser, NULL);
op = default_function_array_conversion (exp_loc, op);
return parser_build_unary_op (op_loc, IMAGPART_EXPR, op);
default:
return c_parser_postfix_expression (parser);
}
default:
return c_parser_postfix_expression (parser);
}
}
/* Parse a sizeof expression. */
static struct c_expr
c_parser_sizeof_expression (c_parser *parser)
{
struct c_expr expr;
location_t expr_loc;
gcc_assert (c_parser_next_token_is_keyword (parser, RID_SIZEOF));
c_parser_consume_token (parser);
c_inhibit_evaluation_warnings++;
in_sizeof++;
if (c_parser_next_token_is (parser, CPP_OPEN_PAREN)
&& c_token_starts_typename (c_parser_peek_2nd_token (parser)))
{
/* Either sizeof ( type-name ) or sizeof unary-expression
starting with a compound literal. */
struct c_type_name *type_name;
c_parser_consume_token (parser);
expr_loc = c_parser_peek_token (parser)->location;
type_name = c_parser_type_name (parser);
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, "expected %<)%>");
if (type_name == NULL)
{
struct c_expr ret;
c_inhibit_evaluation_warnings--;
in_sizeof--;
ret.value = error_mark_node;
ret.original_code = ERROR_MARK;
ret.original_type = NULL;
return ret;
}
if (c_parser_next_token_is (parser, CPP_OPEN_BRACE))
{
expr = c_parser_postfix_expression_after_paren_type (parser,
type_name,
expr_loc);
goto sizeof_expr;
}
/* sizeof ( type-name ). */
c_inhibit_evaluation_warnings--;
in_sizeof--;
return c_expr_sizeof_type (expr_loc, type_name);
}
else
{
expr_loc = c_parser_peek_token (parser)->location;
expr = c_parser_unary_expression (parser);
sizeof_expr:
c_inhibit_evaluation_warnings--;
in_sizeof--;
mark_exp_read (expr.value);
if (TREE_CODE (expr.value) == COMPONENT_REF
&& DECL_C_BIT_FIELD (TREE_OPERAND (expr.value, 1)))
error_at (expr_loc, "%<sizeof%> applied to a bit-field");
return c_expr_sizeof_expr (expr_loc, expr);
}
}
/* Parse an alignof expression. */
static struct c_expr
c_parser_alignof_expression (c_parser *parser)
{
struct c_expr expr;
location_t loc = c_parser_peek_token (parser)->location;
gcc_assert (c_parser_next_token_is_keyword (parser, RID_ALIGNOF));
c_parser_consume_token (parser);
c_inhibit_evaluation_warnings++;
in_alignof++;
if (c_parser_next_token_is (parser, CPP_OPEN_PAREN)
&& c_token_starts_typename (c_parser_peek_2nd_token (parser)))
{
/* Either __alignof__ ( type-name ) or __alignof__
unary-expression starting with a compound literal. */
location_t loc;
struct c_type_name *type_name;
struct c_expr ret;
c_parser_consume_token (parser);
loc = c_parser_peek_token (parser)->location;
type_name = c_parser_type_name (parser);
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, "expected %<)%>");
if (type_name == NULL)
{
struct c_expr ret;
c_inhibit_evaluation_warnings--;
in_alignof--;
ret.value = error_mark_node;
ret.original_code = ERROR_MARK;
ret.original_type = NULL;
return ret;
}
if (c_parser_next_token_is (parser, CPP_OPEN_BRACE))
{
expr = c_parser_postfix_expression_after_paren_type (parser,
type_name,
loc);
goto alignof_expr;
}
/* alignof ( type-name ). */
c_inhibit_evaluation_warnings--;
in_alignof--;
ret.value = c_alignof (loc, groktypename (type_name, NULL, NULL));
ret.original_code = ERROR_MARK;
ret.original_type = NULL;
return ret;
}
else
{
struct c_expr ret;
expr = c_parser_unary_expression (parser);
alignof_expr:
mark_exp_read (expr.value);
c_inhibit_evaluation_warnings--;
in_alignof--;
ret.value = c_alignof_expr (loc, expr.value);
ret.original_code = ERROR_MARK;
ret.original_type = NULL;
return ret;
}
}
/* Parse a postfix expression (C90 6.3.1-6.3.2, C99 6.5.1-6.5.2).
postfix-expression:
primary-expression
postfix-expression [ expression ]
postfix-expression ( argument-expression-list[opt] )
postfix-expression . identifier
postfix-expression -> identifier
postfix-expression ++
postfix-expression --
( type-name ) { initializer-list }
( type-name ) { initializer-list , }
argument-expression-list:
argument-expression
argument-expression-list , argument-expression
primary-expression:
identifier
constant
string-literal
( expression )
GNU extensions:
primary-expression:
__func__
(treated as a keyword in GNU C)
__FUNCTION__
__PRETTY_FUNCTION__
( compound-statement )
__builtin_va_arg ( assignment-expression , type-name )
__builtin_offsetof ( type-name , offsetof-member-designator )
__builtin_choose_expr ( assignment-expression ,
assignment-expression ,
assignment-expression )
__builtin_types_compatible_p ( type-name , type-name )
offsetof-member-designator:
identifier
offsetof-member-designator . identifier
offsetof-member-designator [ expression ]
Objective-C:
primary-expression:
[ objc-receiver objc-message-args ]
@selector ( objc-selector-arg )
@protocol ( identifier )
@encode ( type-name )
objc-string-literal
Classname . identifier
*/
static struct c_expr
c_parser_postfix_expression (c_parser *parser)
{
struct c_expr expr, e1, e2, e3;
struct c_type_name *t1, *t2;
location_t loc = c_parser_peek_token (parser)->location;;
expr.original_code = ERROR_MARK;
expr.original_type = NULL;
switch (c_parser_peek_token (parser)->type)
{
case CPP_NUMBER:
expr.value = c_parser_peek_token (parser)->value;
loc = c_parser_peek_token (parser)->location;
c_parser_consume_token (parser);
if (TREE_CODE (expr.value) == FIXED_CST
&& !targetm.fixed_point_supported_p ())
{
error_at (loc, "fixed-point types not supported for this target");
expr.value = error_mark_node;
}
break;
case CPP_CHAR:
case CPP_CHAR16:
case CPP_CHAR32:
case CPP_WCHAR:
expr.value = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
break;
case CPP_STRING:
case CPP_STRING16:
case CPP_STRING32:
case CPP_WSTRING:
case CPP_UTF8STRING:
expr.value = c_parser_peek_token (parser)->value;
expr.original_code = STRING_CST;
c_parser_consume_token (parser);
break;
case CPP_OBJC_STRING:
gcc_assert (c_dialect_objc ());
expr.value
= objc_build_string_object (c_parser_peek_token (parser)->value);
c_parser_consume_token (parser);
break;
case CPP_NAME:
switch (c_parser_peek_token (parser)->id_kind)
{
case C_ID_ID:
{
tree id = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
expr.value = build_external_ref (loc, id,
(c_parser_peek_token (parser)->type
== CPP_OPEN_PAREN),
&expr.original_type);
break;
}
case C_ID_CLASSNAME:
{
/* Here we parse the Objective-C 2.0 Class.name dot
syntax. */
tree class_name = c_parser_peek_token (parser)->value;
tree component;
c_parser_consume_token (parser);
gcc_assert (c_dialect_objc ());
if (!c_parser_require (parser, CPP_DOT, "expected %<.%>"))
{
expr.value = error_mark_node;
break;
}
if (c_parser_next_token_is_not (parser, CPP_NAME))
{
c_parser_error (parser, "expected identifier");
expr.value = error_mark_node;
break;
}
component = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
expr.value = objc_build_class_component_ref (class_name,
component);
break;
}
default:
c_parser_error (parser, "expected expression");
expr.value = error_mark_node;
break;
}
break;
case CPP_OPEN_PAREN:
/* A parenthesized expression, statement expression or compound
literal. */
if (c_parser_peek_2nd_token (parser)->type == CPP_OPEN_BRACE)
{
/* A statement expression. */
tree stmt;
location_t brace_loc;
c_parser_consume_token (parser);
brace_loc = c_parser_peek_token (parser)->location;
c_parser_consume_token (parser);
if (cur_stmt_list == NULL)
{
error_at (loc, "braced-group within expression allowed "
"only inside a function");
parser->error = true;
c_parser_skip_until_found (parser, CPP_CLOSE_BRACE, NULL);
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, NULL);
expr.value = error_mark_node;
break;
}
stmt = c_begin_stmt_expr ();
c_parser_compound_statement_nostart (parser);
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
pedwarn (loc, OPT_pedantic,
"ISO C forbids braced-groups within expressions");
expr.value = c_finish_stmt_expr (brace_loc, stmt);
mark_exp_read (expr.value);
}
else if (c_token_starts_typename (c_parser_peek_2nd_token (parser)))
{
/* A compound literal. ??? Can we actually get here rather
than going directly to
c_parser_postfix_expression_after_paren_type from
elsewhere? */
location_t loc;
struct c_type_name *type_name;
c_parser_consume_token (parser);
loc = c_parser_peek_token (parser)->location;
type_name = c_parser_type_name (parser);
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
if (type_name == NULL)
{
expr.value = error_mark_node;
}
else
expr = c_parser_postfix_expression_after_paren_type (parser,
type_name,
loc);
}
else
{
/* A parenthesized expression. */
c_parser_consume_token (parser);
expr = c_parser_expression (parser);
if (TREE_CODE (expr.value) == MODIFY_EXPR)
TREE_NO_WARNING (expr.value) = 1;
if (expr.original_code != C_MAYBE_CONST_EXPR)
expr.original_code = ERROR_MARK;
/* Don't change EXPR.ORIGINAL_TYPE. */
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
}
break;
case CPP_KEYWORD:
switch (c_parser_peek_token (parser)->keyword)
{
case RID_FUNCTION_NAME:
case RID_PRETTY_FUNCTION_NAME:
case RID_C99_FUNCTION_NAME:
expr.value = fname_decl (loc,
c_parser_peek_token (parser)->keyword,
c_parser_peek_token (parser)->value);
c_parser_consume_token (parser);
break;
case RID_VA_ARG:
c_parser_consume_token (parser);
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
{
expr.value = error_mark_node;
break;
}
e1 = c_parser_expr_no_commas (parser, NULL);
mark_exp_read (e1.value);
e1.value = c_fully_fold (e1.value, false, NULL);
if (!c_parser_require (parser, CPP_COMMA, "expected %<,%>"))
{
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, NULL);
expr.value = error_mark_node;
break;
}
loc = c_parser_peek_token (parser)->location;
t1 = c_parser_type_name (parser);
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
if (t1 == NULL)
{
expr.value = error_mark_node;
}
else
{
tree type_expr = NULL_TREE;
expr.value = c_build_va_arg (loc, e1.value,
groktypename (t1, &type_expr, NULL));
if (type_expr)
{
expr.value = build2 (C_MAYBE_CONST_EXPR,
TREE_TYPE (expr.value), type_expr,
expr.value);
C_MAYBE_CONST_EXPR_NON_CONST (expr.value) = true;
}
}
break;
case RID_OFFSETOF:
c_parser_consume_token (parser);
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
{
expr.value = error_mark_node;
break;
}
t1 = c_parser_type_name (parser);
if (t1 == NULL)
parser->error = true;
if (!c_parser_require (parser, CPP_COMMA, "expected %<,%>"))
gcc_assert (parser->error);
if (parser->error)
{
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, NULL);
expr.value = error_mark_node;
break;
}
{
tree type = groktypename (t1, NULL, NULL);
tree offsetof_ref;
if (type == error_mark_node)
offsetof_ref = error_mark_node;
else
{
offsetof_ref = build1 (INDIRECT_REF, type, null_pointer_node);
SET_EXPR_LOCATION (offsetof_ref, loc);
}
/* Parse the second argument to __builtin_offsetof. We
must have one identifier, and beyond that we want to
accept sub structure and sub array references. */
if (c_parser_next_token_is (parser, CPP_NAME))
{
offsetof_ref = build_component_ref
(loc, offsetof_ref, c_parser_peek_token (parser)->value);
c_parser_consume_token (parser);
while (c_parser_next_token_is (parser, CPP_DOT)
|| c_parser_next_token_is (parser,
CPP_OPEN_SQUARE)
|| c_parser_next_token_is (parser,
CPP_DEREF))
{
if (c_parser_next_token_is (parser, CPP_DEREF))
{
loc = c_parser_peek_token (parser)->location;
offsetof_ref = build_array_ref (loc,
offsetof_ref,
integer_zero_node);
goto do_dot;
}
else if (c_parser_next_token_is (parser, CPP_DOT))
{
do_dot:
c_parser_consume_token (parser);
if (c_parser_next_token_is_not (parser,
CPP_NAME))
{
c_parser_error (parser, "expected identifier");
break;
}
offsetof_ref = build_component_ref
(loc, offsetof_ref,
c_parser_peek_token (parser)->value);
c_parser_consume_token (parser);
}
else
{
tree idx;
loc = c_parser_peek_token (parser)->location;
c_parser_consume_token (parser);
idx = c_parser_expression (parser).value;
idx = c_fully_fold (idx, false, NULL);
c_parser_skip_until_found (parser, CPP_CLOSE_SQUARE,
"expected %<]%>");
offsetof_ref = build_array_ref (loc, offsetof_ref, idx);
}
}
}
else
c_parser_error (parser, "expected identifier");
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
expr.value = fold_offsetof (offsetof_ref, NULL_TREE);
}
break;
case RID_CHOOSE_EXPR:
c_parser_consume_token (parser);
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
{
expr.value = error_mark_node;
break;
}
loc = c_parser_peek_token (parser)->location;
e1 = c_parser_expr_no_commas (parser, NULL);
if (!c_parser_require (parser, CPP_COMMA, "expected %<,%>"))
{
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, NULL);
expr.value = error_mark_node;
break;
}
e2 = c_parser_expr_no_commas (parser, NULL);
if (!c_parser_require (parser, CPP_COMMA, "expected %<,%>"))
{
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, NULL);
expr.value = error_mark_node;
break;
}
e3 = c_parser_expr_no_commas (parser, NULL);
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
{
tree c;
c = e1.value;
mark_exp_read (e2.value);
mark_exp_read (e3.value);
if (TREE_CODE (c) != INTEGER_CST
|| !INTEGRAL_TYPE_P (TREE_TYPE (c)))
error_at (loc,
"first argument to %<__builtin_choose_expr%> not"
" a constant");
constant_expression_warning (c);
expr = integer_zerop (c) ? e3 : e2;
}
break;
case RID_TYPES_COMPATIBLE_P:
c_parser_consume_token (parser);
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
{
expr.value = error_mark_node;
break;
}
t1 = c_parser_type_name (parser);
if (t1 == NULL)
{
expr.value = error_mark_node;
break;
}
if (!c_parser_require (parser, CPP_COMMA, "expected %<,%>"))
{
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, NULL);
expr.value = error_mark_node;
break;
}
t2 = c_parser_type_name (parser);
if (t2 == NULL)
{
expr.value = error_mark_node;
break;
}
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
{
tree e1, e2;
e1 = TYPE_MAIN_VARIANT (groktypename (t1, NULL, NULL));
e2 = TYPE_MAIN_VARIANT (groktypename (t2, NULL, NULL));
expr.value
= comptypes (e1, e2) ? integer_one_node : integer_zero_node;
}
break;
case RID_AT_SELECTOR:
gcc_assert (c_dialect_objc ());
c_parser_consume_token (parser);
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
{
expr.value = error_mark_node;
break;
}
{
tree sel = c_parser_objc_selector_arg (parser);
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
expr.value = objc_build_selector_expr (loc, sel);
}
break;
case RID_AT_PROTOCOL:
gcc_assert (c_dialect_objc ());
c_parser_consume_token (parser);
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
{
expr.value = error_mark_node;
break;
}
if (c_parser_next_token_is_not (parser, CPP_NAME))
{
c_parser_error (parser, "expected identifier");
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, NULL);
expr.value = error_mark_node;
break;
}
{
tree id = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
expr.value = objc_build_protocol_expr (id);
}
break;
case RID_AT_ENCODE:
/* Extension to support C-structures in the archiver. */
gcc_assert (c_dialect_objc ());
c_parser_consume_token (parser);
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
{
expr.value = error_mark_node;
break;
}
t1 = c_parser_type_name (parser);
if (t1 == NULL)
{
expr.value = error_mark_node;
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, NULL);
break;
}
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
{
tree type = groktypename (t1, NULL, NULL);
expr.value = objc_build_encode_expr (type);
}
break;
default:
c_parser_error (parser, "expected expression");
expr.value = error_mark_node;
break;
}
break;
case CPP_OPEN_SQUARE:
if (c_dialect_objc ())
{
tree receiver, args;
c_parser_consume_token (parser);
receiver = c_parser_objc_receiver (parser);
args = c_parser_objc_message_args (parser);
c_parser_skip_until_found (parser, CPP_CLOSE_SQUARE,
"expected %<]%>");
expr.value = objc_build_message_expr (build_tree_list (receiver,
args));
break;
}
/* Else fall through to report error. */
default:
c_parser_error (parser, "expected expression");
expr.value = error_mark_node;
break;
}
return c_parser_postfix_expression_after_primary (parser, loc, expr);
}
/* Parse a postfix expression after a parenthesized type name: the
brace-enclosed initializer of a compound literal, possibly followed
by some postfix operators. This is separate because it is not
possible to tell until after the type name whether a cast
expression has a cast or a compound literal, or whether the operand
of sizeof is a parenthesized type name or starts with a compound
literal. TYPE_LOC is the location where TYPE_NAME starts--the
location of the first token after the parentheses around the type
name. */
static struct c_expr
c_parser_postfix_expression_after_paren_type (c_parser *parser,
struct c_type_name *type_name,
location_t type_loc)
{
tree type;
struct c_expr init;
bool non_const;
struct c_expr expr;
location_t start_loc;
tree type_expr = NULL_TREE;
bool type_expr_const = true;
check_compound_literal_type (type_loc, type_name);
start_init (NULL_TREE, NULL, 0);
type = groktypename (type_name, &type_expr, &type_expr_const);
start_loc = c_parser_peek_token (parser)->location;
if (type != error_mark_node && C_TYPE_VARIABLE_SIZE (type))
{
error_at (type_loc, "compound literal has variable size");
type = error_mark_node;
}
init = c_parser_braced_init (parser, type, false);
finish_init ();
maybe_warn_string_init (type, init);
if (type != error_mark_node
&& !ADDR_SPACE_GENERIC_P (TYPE_ADDR_SPACE (type))
&& current_function_decl)
{
error ("compound literal qualified by address-space qualifier");
type = error_mark_node;
}
if (!flag_isoc99)
pedwarn (start_loc, OPT_pedantic, "ISO C90 forbids compound literals");
non_const = ((init.value && TREE_CODE (init.value) == CONSTRUCTOR)
? CONSTRUCTOR_NON_CONST (init.value)
: init.original_code == C_MAYBE_CONST_EXPR);
non_const |= !type_expr_const;
expr.value = build_compound_literal (start_loc, type, init.value, non_const);
expr.original_code = ERROR_MARK;
expr.original_type = NULL;
if (type_expr)
{
if (TREE_CODE (expr.value) == C_MAYBE_CONST_EXPR)
{
gcc_assert (C_MAYBE_CONST_EXPR_PRE (expr.value) == NULL_TREE);
C_MAYBE_CONST_EXPR_PRE (expr.value) = type_expr;
}
else
{
gcc_assert (!non_const);
expr.value = build2 (C_MAYBE_CONST_EXPR, type,
type_expr, expr.value);
}
}
return c_parser_postfix_expression_after_primary (parser, start_loc, expr);
}
/* Parse a postfix expression after the initial primary or compound
literal; that is, parse a series of postfix operators.
EXPR_LOC is the location of the primary expression. */
static struct c_expr
c_parser_postfix_expression_after_primary (c_parser *parser,
location_t expr_loc,
struct c_expr expr)
{
struct c_expr orig_expr;
tree ident, idx;
VEC(tree,gc) *exprlist;
VEC(tree,gc) *origtypes;
while (true)
{
location_t op_loc = c_parser_peek_token (parser)->location;
switch (c_parser_peek_token (parser)->type)
{
case CPP_OPEN_SQUARE:
/* Array reference. */
c_parser_consume_token (parser);
idx = c_parser_expression (parser).value;
c_parser_skip_until_found (parser, CPP_CLOSE_SQUARE,
"expected %<]%>");
expr.value = build_array_ref (op_loc, expr.value, idx);
expr.original_code = ERROR_MARK;
expr.original_type = NULL;
break;
case CPP_OPEN_PAREN:
/* Function call. */
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_CLOSE_PAREN))
exprlist = NULL;
else
exprlist = c_parser_expr_list (parser, true, false, &origtypes);
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
orig_expr = expr;
mark_exp_read (expr.value);
/* FIXME diagnostics: Ideally we want the FUNCNAME, not the
"(" after the FUNCNAME, which is what we have now. */
expr.value = build_function_call_vec (op_loc, expr.value, exprlist,
origtypes);
expr.original_code = ERROR_MARK;
if (TREE_CODE (expr.value) == INTEGER_CST
&& TREE_CODE (orig_expr.value) == FUNCTION_DECL
&& DECL_BUILT_IN_CLASS (orig_expr.value) == BUILT_IN_NORMAL
&& DECL_FUNCTION_CODE (orig_expr.value) == BUILT_IN_CONSTANT_P)
expr.original_code = C_MAYBE_CONST_EXPR;
expr.original_type = NULL;
if (exprlist != NULL)
{
release_tree_vector (exprlist);
release_tree_vector (origtypes);
}
break;
case CPP_DOT:
/* Structure element reference. */
c_parser_consume_token (parser);
expr = default_function_array_conversion (expr_loc, expr);
if (c_parser_next_token_is (parser, CPP_NAME))
ident = c_parser_peek_token (parser)->value;
else
{
c_parser_error (parser, "expected identifier");
expr.value = error_mark_node;
expr.original_code = ERROR_MARK;
expr.original_type = NULL;
return expr;
}
c_parser_consume_token (parser);
expr.value = build_component_ref (op_loc, expr.value, ident);
expr.original_code = ERROR_MARK;
if (TREE_CODE (expr.value) != COMPONENT_REF)
expr.original_type = NULL;
else
{
/* Remember the original type of a bitfield. */
tree field = TREE_OPERAND (expr.value, 1);
if (TREE_CODE (field) != FIELD_DECL)
expr.original_type = NULL;
else
expr.original_type = DECL_BIT_FIELD_TYPE (field);
}
break;
case CPP_DEREF:
/* Structure element reference. */
c_parser_consume_token (parser);
expr = default_function_array_conversion (expr_loc, expr);
if (c_parser_next_token_is (parser, CPP_NAME))
ident = c_parser_peek_token (parser)->value;
else
{
c_parser_error (parser, "expected identifier");
expr.value = error_mark_node;
expr.original_code = ERROR_MARK;
expr.original_type = NULL;
return expr;
}
c_parser_consume_token (parser);
expr.value = build_component_ref (op_loc,
build_indirect_ref (op_loc,
expr.value,
RO_ARROW),
ident);
expr.original_code = ERROR_MARK;
if (TREE_CODE (expr.value) != COMPONENT_REF)
expr.original_type = NULL;
else
{
/* Remember the original type of a bitfield. */
tree field = TREE_OPERAND (expr.value, 1);
if (TREE_CODE (field) != FIELD_DECL)
expr.original_type = NULL;
else
expr.original_type = DECL_BIT_FIELD_TYPE (field);
}
break;
case CPP_PLUS_PLUS:
/* Postincrement. */
c_parser_consume_token (parser);
expr = default_function_array_read_conversion (expr_loc, expr);
expr.value = build_unary_op (op_loc,
POSTINCREMENT_EXPR, expr.value, 0);
expr.original_code = ERROR_MARK;
expr.original_type = NULL;
break;
case CPP_MINUS_MINUS:
/* Postdecrement. */
c_parser_consume_token (parser);
expr = default_function_array_read_conversion (expr_loc, expr);
expr.value = build_unary_op (op_loc,
POSTDECREMENT_EXPR, expr.value, 0);
expr.original_code = ERROR_MARK;
expr.original_type = NULL;
break;
default:
return expr;
}
}
}
/* Parse an expression (C90 6.3.17, C99 6.5.17).
expression:
assignment-expression
expression , assignment-expression
*/
static struct c_expr
c_parser_expression (c_parser *parser)
{
struct c_expr expr;
expr = c_parser_expr_no_commas (parser, NULL);
while (c_parser_next_token_is (parser, CPP_COMMA))
{
struct c_expr next;
tree lhsval;
location_t loc = c_parser_peek_token (parser)->location;
location_t expr_loc;
c_parser_consume_token (parser);
expr_loc = c_parser_peek_token (parser)->location;
lhsval = expr.value;
while (TREE_CODE (lhsval) == COMPOUND_EXPR)
lhsval = TREE_OPERAND (lhsval, 1);
if (DECL_P (lhsval) || handled_component_p (lhsval))
mark_exp_read (lhsval);
next = c_parser_expr_no_commas (parser, NULL);
next = default_function_array_conversion (expr_loc, next);
expr.value = build_compound_expr (loc, expr.value, next.value);
expr.original_code = COMPOUND_EXPR;
expr.original_type = next.original_type;
}
return expr;
}
/* Parse an expression and convert functions or arrays to
pointers. */
static struct c_expr
c_parser_expression_conv (c_parser *parser)
{
struct c_expr expr;
location_t loc = c_parser_peek_token (parser)->location;
expr = c_parser_expression (parser);
expr = default_function_array_conversion (loc, expr);
return expr;
}
/* Parse a non-empty list of expressions. If CONVERT_P, convert
functions and arrays to pointers. If FOLD_P, fold the expressions.
nonempty-expr-list:
assignment-expression
nonempty-expr-list , assignment-expression
*/
static VEC(tree,gc) *
c_parser_expr_list (c_parser *parser, bool convert_p, bool fold_p,
VEC(tree,gc) **p_orig_types)
{
VEC(tree,gc) *ret;
VEC(tree,gc) *orig_types;
struct c_expr expr;
location_t loc = c_parser_peek_token (parser)->location;
ret = make_tree_vector ();
if (p_orig_types == NULL)
orig_types = NULL;
else
orig_types = make_tree_vector ();
expr = c_parser_expr_no_commas (parser, NULL);
if (convert_p)
expr = default_function_array_read_conversion (loc, expr);
if (fold_p)
expr.value = c_fully_fold (expr.value, false, NULL);
VEC_quick_push (tree, ret, expr.value);
if (orig_types != NULL)
VEC_quick_push (tree, orig_types, expr.original_type);
while (c_parser_next_token_is (parser, CPP_COMMA))
{
c_parser_consume_token (parser);
loc = c_parser_peek_token (parser)->location;
expr = c_parser_expr_no_commas (parser, NULL);
if (convert_p)
expr = default_function_array_read_conversion (loc, expr);
if (fold_p)
expr.value = c_fully_fold (expr.value, false, NULL);
VEC_safe_push (tree, gc, ret, expr.value);
if (orig_types != NULL)
VEC_safe_push (tree, gc, orig_types, expr.original_type);
}
if (orig_types != NULL)
*p_orig_types = orig_types;
return ret;
}
/* Parse Objective-C-specific constructs. */
/* Parse an objc-class-definition.
objc-class-definition:
@interface identifier objc-superclass[opt] objc-protocol-refs[opt]
objc-class-instance-variables[opt] objc-methodprotolist @end
@implementation identifier objc-superclass[opt]
objc-class-instance-variables[opt]
@interface identifier ( identifier ) objc-protocol-refs[opt]
objc-methodprotolist @end
@interface identifier ( ) objc-protocol-refs[opt]
objc-methodprotolist @end
@implementation identifier ( identifier )
objc-superclass:
: identifier
"@interface identifier (" must start "@interface identifier (
identifier ) ...": objc-methodprotolist in the first production may
not start with a parenthesized identifier as a declarator of a data
definition with no declaration specifiers if the objc-superclass,
objc-protocol-refs and objc-class-instance-variables are omitted. */
static void
c_parser_objc_class_definition (c_parser *parser, tree attributes)
{
bool iface_p;
tree id1;
tree superclass;
if (c_parser_next_token_is_keyword (parser, RID_AT_INTERFACE))
iface_p = true;
else if (c_parser_next_token_is_keyword (parser, RID_AT_IMPLEMENTATION))
iface_p = false;
else
gcc_unreachable ();
c_parser_consume_token (parser);
if (c_parser_next_token_is_not (parser, CPP_NAME))
{
c_parser_error (parser, "expected identifier");
return;
}
id1 = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_OPEN_PAREN))
{
/* We have a category or class extension. */
tree id2;
tree proto = NULL_TREE;
c_parser_consume_token (parser);
if (c_parser_next_token_is_not (parser, CPP_NAME))
{
if (iface_p && c_parser_next_token_is (parser, CPP_CLOSE_PAREN))
{
/* We have a class extension. */
id2 = NULL_TREE;
}
else
{
c_parser_error (parser, "expected identifier or %<)%>");
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, NULL);
return;
}
}
else
{
id2 = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
}
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, "expected %<)%>");
if (!iface_p)
{
objc_start_category_implementation (id1, id2);
return;
}
if (c_parser_next_token_is (parser, CPP_LESS))
proto = c_parser_objc_protocol_refs (parser);
objc_start_category_interface (id1, id2, proto, attributes);
c_parser_objc_methodprotolist (parser);
c_parser_require_keyword (parser, RID_AT_END, "expected %<@end%>");
objc_finish_interface ();
return;
}
if (c_parser_next_token_is (parser, CPP_COLON))
{
c_parser_consume_token (parser);
if (c_parser_next_token_is_not (parser, CPP_NAME))
{
c_parser_error (parser, "expected identifier");
return;
}
superclass = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
}
else
superclass = NULL_TREE;
if (iface_p)
{
tree proto = NULL_TREE;
if (c_parser_next_token_is (parser, CPP_LESS))
proto = c_parser_objc_protocol_refs (parser);
objc_start_class_interface (id1, superclass, proto, attributes);
}
else
objc_start_class_implementation (id1, superclass);
if (c_parser_next_token_is (parser, CPP_OPEN_BRACE))
c_parser_objc_class_instance_variables (parser);
if (iface_p)
{
objc_continue_interface ();
c_parser_objc_methodprotolist (parser);
c_parser_require_keyword (parser, RID_AT_END, "expected %<@end%>");
objc_finish_interface ();
}
else
{
objc_continue_implementation ();
return;
}
}
/* Parse objc-class-instance-variables.
objc-class-instance-variables:
{ objc-instance-variable-decl-list[opt] }
objc-instance-variable-decl-list:
objc-visibility-spec
objc-instance-variable-decl ;
;
objc-instance-variable-decl-list objc-visibility-spec
objc-instance-variable-decl-list objc-instance-variable-decl ;
objc-instance-variable-decl-list ;
objc-visibility-spec:
@private
@protected
@public
objc-instance-variable-decl:
struct-declaration
*/
static void
c_parser_objc_class_instance_variables (c_parser *parser)
{
gcc_assert (c_parser_next_token_is (parser, CPP_OPEN_BRACE));
c_parser_consume_token (parser);
while (c_parser_next_token_is_not (parser, CPP_EOF))
{
tree decls;
/* Parse any stray semicolon. */
if (c_parser_next_token_is (parser, CPP_SEMICOLON))
{
pedwarn (c_parser_peek_token (parser)->location, OPT_pedantic,
"extra semicolon in struct or union specified");
c_parser_consume_token (parser);
continue;
}
/* Stop if at the end of the instance variables. */
if (c_parser_next_token_is (parser, CPP_CLOSE_BRACE))
{
c_parser_consume_token (parser);
break;
}
/* Parse any objc-visibility-spec. */
if (c_parser_next_token_is_keyword (parser, RID_AT_PRIVATE))
{
c_parser_consume_token (parser);
objc_set_visibility (OBJC_IVAR_VIS_PRIVATE);
continue;
}
else if (c_parser_next_token_is_keyword (parser, RID_AT_PROTECTED))
{
c_parser_consume_token (parser);
objc_set_visibility (OBJC_IVAR_VIS_PROTECTED);
continue;
}
else if (c_parser_next_token_is_keyword (parser, RID_AT_PUBLIC))
{
c_parser_consume_token (parser);
objc_set_visibility (OBJC_IVAR_VIS_PUBLIC);
continue;
}
else if (c_parser_next_token_is_keyword (parser, RID_AT_PACKAGE))
{
c_parser_consume_token (parser);
objc_set_visibility (OBJC_IVAR_VIS_PACKAGE);
continue;
}
else if (c_parser_next_token_is (parser, CPP_PRAGMA))
{
c_parser_pragma (parser, pragma_external);
continue;
}
/* Parse some comma-separated declarations. */
decls = c_parser_struct_declaration (parser);
{
/* Comma-separated instance variables are chained together in
reverse order; add them one by one. */
tree ivar = nreverse (decls);
for (; ivar; ivar = DECL_CHAIN (ivar))
objc_add_instance_variable (copy_node (ivar));
}
c_parser_skip_until_found (parser, CPP_SEMICOLON, "expected %<;%>");
}
}
/* Parse an objc-class-declaration.
objc-class-declaration:
@class identifier-list ;
*/
static void
c_parser_objc_class_declaration (c_parser *parser)
{
tree list = NULL_TREE;
gcc_assert (c_parser_next_token_is_keyword (parser, RID_AT_CLASS));
c_parser_consume_token (parser);
/* Any identifiers, including those declared as type names, are OK
here. */
while (true)
{
tree id;
if (c_parser_next_token_is_not (parser, CPP_NAME))
{
c_parser_error (parser, "expected identifier");
c_parser_skip_until_found (parser, CPP_SEMICOLON, NULL);
parser->error = false;
return;
}
id = c_parser_peek_token (parser)->value;
list = chainon (list, build_tree_list (NULL_TREE, id));
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_COMMA))
c_parser_consume_token (parser);
else
break;
}
c_parser_skip_until_found (parser, CPP_SEMICOLON, "expected %<;%>");
objc_declare_class (list);
}
/* Parse an objc-alias-declaration.
objc-alias-declaration:
@compatibility_alias identifier identifier ;
*/
static void
c_parser_objc_alias_declaration (c_parser *parser)
{
tree id1, id2;
gcc_assert (c_parser_next_token_is_keyword (parser, RID_AT_ALIAS));
c_parser_consume_token (parser);
if (c_parser_next_token_is_not (parser, CPP_NAME))
{
c_parser_error (parser, "expected identifier");
c_parser_skip_until_found (parser, CPP_SEMICOLON, NULL);
return;
}
id1 = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
if (c_parser_next_token_is_not (parser, CPP_NAME))
{
c_parser_error (parser, "expected identifier");
c_parser_skip_until_found (parser, CPP_SEMICOLON, NULL);
return;
}
id2 = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
c_parser_skip_until_found (parser, CPP_SEMICOLON, "expected %<;%>");
objc_declare_alias (id1, id2);
}
/* Parse an objc-protocol-definition.
objc-protocol-definition:
@protocol identifier objc-protocol-refs[opt] objc-methodprotolist @end
@protocol identifier-list ;
"@protocol identifier ;" should be resolved as "@protocol
identifier-list ;": objc-methodprotolist may not start with a
semicolon in the first alternative if objc-protocol-refs are
omitted. */
static void
c_parser_objc_protocol_definition (c_parser *parser, tree attributes)
{
gcc_assert (c_parser_next_token_is_keyword (parser, RID_AT_PROTOCOL));
c_parser_consume_token (parser);
if (c_parser_next_token_is_not (parser, CPP_NAME))
{
c_parser_error (parser, "expected identifier");
return;
}
if (c_parser_peek_2nd_token (parser)->type == CPP_COMMA
|| c_parser_peek_2nd_token (parser)->type == CPP_SEMICOLON)
{
tree list = NULL_TREE;
/* Any identifiers, including those declared as type names, are
OK here. */
while (true)
{
tree id;
if (c_parser_next_token_is_not (parser, CPP_NAME))
{
c_parser_error (parser, "expected identifier");
break;
}
id = c_parser_peek_token (parser)->value;
list = chainon (list, build_tree_list (NULL_TREE, id));
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_COMMA))
c_parser_consume_token (parser);
else
break;
}
c_parser_skip_until_found (parser, CPP_SEMICOLON, "expected %<;%>");
objc_declare_protocols (list, attributes);
}
else
{
tree id = c_parser_peek_token (parser)->value;
tree proto = NULL_TREE;
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_LESS))
proto = c_parser_objc_protocol_refs (parser);
parser->objc_pq_context = true;
objc_start_protocol (id, proto, attributes);
c_parser_objc_methodprotolist (parser);
c_parser_require_keyword (parser, RID_AT_END, "expected %<@end%>");
parser->objc_pq_context = false;
objc_finish_interface ();
}
}
/* Parse an objc-method-type.
objc-method-type:
+
-
Return true if it is a class method (+) and false if it is
an instance method (-).
*/
static inline bool
c_parser_objc_method_type (c_parser *parser)
{
switch (c_parser_peek_token (parser)->type)
{
case CPP_PLUS:
c_parser_consume_token (parser);
return true;
case CPP_MINUS:
c_parser_consume_token (parser);
return false;
default:
gcc_unreachable ();
}
}
/* Parse an objc-method-definition.
objc-method-definition:
objc-method-type objc-method-decl ;[opt] compound-statement
*/
static void
c_parser_objc_method_definition (c_parser *parser)
{
bool is_class_method = c_parser_objc_method_type (parser);
tree decl, attributes = NULL_TREE;
parser->objc_pq_context = true;
decl = c_parser_objc_method_decl (parser, is_class_method, &attributes);
if (decl == error_mark_node)
return; /* Bail here. */
if (c_parser_next_token_is (parser, CPP_SEMICOLON))
{
c_parser_consume_token (parser);
pedwarn (c_parser_peek_token (parser)->location, OPT_pedantic,
"extra semicolon in method definition specified");
}
if (!c_parser_next_token_is (parser, CPP_OPEN_BRACE))
{
c_parser_error (parser, "expected %<{%>");
return;
}
parser->objc_pq_context = false;
if (objc_start_method_definition (is_class_method, decl, attributes))
{
add_stmt (c_parser_compound_statement (parser));
objc_finish_method_definition (current_function_decl);
}
else
{
/* This code is executed when we find a method definition
outside of an @implementation context (or invalid for other
reasons). Parse the method (to keep going) but do not emit
any code.
*/
c_parser_compound_statement (parser);
}
}
/* Parse an objc-methodprotolist.
objc-methodprotolist:
empty
objc-methodprotolist objc-methodproto
objc-methodprotolist declaration
objc-methodprotolist ;
@optional
@required
The declaration is a data definition, which may be missing
declaration specifiers under the same rules and diagnostics as
other data definitions outside functions, and the stray semicolon
is diagnosed the same way as a stray semicolon outside a
function. */
static void
c_parser_objc_methodprotolist (c_parser *parser)
{
while (true)
{
/* The list is terminated by @end. */
switch (c_parser_peek_token (parser)->type)
{
case CPP_SEMICOLON:
pedwarn (c_parser_peek_token (parser)->location, OPT_pedantic,
"ISO C does not allow extra %<;%> outside of a function");
c_parser_consume_token (parser);
break;
case CPP_PLUS:
case CPP_MINUS:
c_parser_objc_methodproto (parser);
break;
case CPP_PRAGMA:
c_parser_pragma (parser, pragma_external);
break;
case CPP_EOF:
return;
default:
if (c_parser_next_token_is_keyword (parser, RID_AT_END))
return;
else if (c_parser_next_token_is_keyword (parser, RID_AT_PROPERTY))
c_parser_objc_at_property_declaration (parser);
else if (c_parser_next_token_is_keyword (parser, RID_AT_OPTIONAL))
{
objc_set_method_opt (true);
c_parser_consume_token (parser);
}
else if (c_parser_next_token_is_keyword (parser, RID_AT_REQUIRED))
{
objc_set_method_opt (false);
c_parser_consume_token (parser);
}
else
c_parser_declaration_or_fndef (parser, false, false, true,
false, true, NULL);
break;
}
}
}
/* Parse an objc-methodproto.
objc-methodproto:
objc-method-type objc-method-decl ;
*/
static void
c_parser_objc_methodproto (c_parser *parser)
{
bool is_class_method = c_parser_objc_method_type (parser);
tree decl, attributes = NULL_TREE;
/* Remember protocol qualifiers in prototypes. */
parser->objc_pq_context = true;
decl = c_parser_objc_method_decl (parser, is_class_method, &attributes);
/* Forget protocol qualifiers now. */
parser->objc_pq_context = false;
/* Do not allow the presence of attributes to hide an erroneous
method implementation in the interface section. */
if (!c_parser_next_token_is (parser, CPP_SEMICOLON))
{
c_parser_error (parser, "expected %<;%>");
return;
}
if (decl != error_mark_node)
objc_add_method_declaration (is_class_method, decl, attributes);
c_parser_skip_until_found (parser, CPP_SEMICOLON, "expected %<;%>");
}
/* If we are at a position that method attributes may be present, check that
there are not any parsed already (a syntax error) and then collect any
specified at the current location. Finally, if new attributes were present,
check that the next token is legal ( ';' for decls and '{' for defs). */
static bool
c_parser_objc_maybe_method_attributes (c_parser* parser, tree* attributes)
{
bool bad = false;
if (*attributes)
{
c_parser_error (parser,
"method attributes must be specified at the end only");
*attributes = NULL_TREE;
bad = true;
}
if (c_parser_next_token_is_keyword (parser, RID_ATTRIBUTE))
*attributes = c_parser_attributes (parser);
/* If there were no attributes here, just report any earlier error. */
if (*attributes == NULL_TREE || bad)
return bad;
/* If the attributes are followed by a ; or {, then just report any earlier
error. */
if (c_parser_next_token_is (parser, CPP_SEMICOLON)
|| c_parser_next_token_is (parser, CPP_OPEN_BRACE))
return bad;
/* We've got attributes, but not at the end. */
c_parser_error (parser,
"expected %<;%> or %<{%> after method attribute definition");
return true;
}
/* Parse an objc-method-decl.
objc-method-decl:
( objc-type-name ) objc-selector
objc-selector
( objc-type-name ) objc-keyword-selector objc-optparmlist
objc-keyword-selector objc-optparmlist
attributes
objc-keyword-selector:
objc-keyword-decl
objc-keyword-selector objc-keyword-decl
objc-keyword-decl:
objc-selector : ( objc-type-name ) identifier
objc-selector : identifier
: ( objc-type-name ) identifier
: identifier
objc-optparmlist:
objc-optparms objc-optellipsis
objc-optparms:
empty
objc-opt-parms , parameter-declaration
objc-optellipsis:
empty
, ...
*/
static tree
c_parser_objc_method_decl (c_parser *parser, bool is_class_method, tree *attributes)
{
tree type = NULL_TREE;
tree sel;
tree parms = NULL_TREE;
bool ellipsis = false;
bool attr_err = false;
*attributes = NULL_TREE;
if (c_parser_next_token_is (parser, CPP_OPEN_PAREN))
{
c_parser_consume_token (parser);
type = c_parser_objc_type_name (parser);
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, "expected %<)%>");
}
sel = c_parser_objc_selector (parser);
/* If there is no selector, or a colon follows, we have an
objc-keyword-selector. If there is a selector, and a colon does
not follow, that selector ends the objc-method-decl. */
if (!sel || c_parser_next_token_is (parser, CPP_COLON))
{
tree tsel = sel;
tree list = NULL_TREE;
while (true)
{
tree atype = NULL_TREE, id, keyworddecl;
tree param_attr = NULL_TREE;
if (!c_parser_require (parser, CPP_COLON, "expected %<:%>"))
break;
if (c_parser_next_token_is (parser, CPP_OPEN_PAREN))
{
c_parser_consume_token (parser);
atype = c_parser_objc_type_name (parser);
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
}
/* New ObjC allows attributes on method parameters. */
if (c_parser_next_token_is_keyword (parser, RID_ATTRIBUTE))
param_attr = c_parser_attributes (parser);
if (c_parser_next_token_is_not (parser, CPP_NAME))
{
c_parser_error (parser, "expected identifier");
return error_mark_node;
}
id = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
keyworddecl = objc_build_keyword_decl (tsel, atype, id, param_attr);
list = chainon (list, keyworddecl);
tsel = c_parser_objc_selector (parser);
if (!tsel && c_parser_next_token_is_not (parser, CPP_COLON))
break;
}
attr_err |= c_parser_objc_maybe_method_attributes (parser, attributes) ;
/* Parse the optional parameter list. Optional Objective-C
method parameters follow the C syntax, and may include '...'
to denote a variable number of arguments. */
parms = make_node (TREE_LIST);
while (c_parser_next_token_is (parser, CPP_COMMA))
{
struct c_parm *parm;
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_ELLIPSIS))
{
ellipsis = true;
c_parser_consume_token (parser);
attr_err |= c_parser_objc_maybe_method_attributes
(parser, attributes) ;
break;
}
parm = c_parser_parameter_declaration (parser, NULL_TREE);
if (parm == NULL)
break;
parms = chainon (parms,
build_tree_list (NULL_TREE, grokparm (parm)));
}
sel = list;
}
else
attr_err |= c_parser_objc_maybe_method_attributes (parser, attributes) ;
if (sel == NULL)
{
c_parser_error (parser, "objective-c method declaration is expected");
return error_mark_node;
}
if (attr_err)
return error_mark_node;
return objc_build_method_signature (is_class_method, type, sel, parms, ellipsis);
}
/* Parse an objc-type-name.
objc-type-name:
objc-type-qualifiers[opt] type-name
objc-type-qualifiers[opt]
objc-type-qualifiers:
objc-type-qualifier
objc-type-qualifiers objc-type-qualifier
objc-type-qualifier: one of
in out inout bycopy byref oneway
*/
static tree
c_parser_objc_type_name (c_parser *parser)
{
tree quals = NULL_TREE;
struct c_type_name *type_name = NULL;
tree type = NULL_TREE;
while (true)
{
c_token *token = c_parser_peek_token (parser);
if (token->type == CPP_KEYWORD
&& (token->keyword == RID_IN
|| token->keyword == RID_OUT
|| token->keyword == RID_INOUT
|| token->keyword == RID_BYCOPY
|| token->keyword == RID_BYREF
|| token->keyword == RID_ONEWAY))
{
quals = chainon (build_tree_list (NULL_TREE, token->value), quals);
c_parser_consume_token (parser);
}
else
break;
}
if (c_parser_next_tokens_start_typename (parser, cla_prefer_type))
type_name = c_parser_type_name (parser);
if (type_name)
type = groktypename (type_name, NULL, NULL);
/* If the type is unknown, and error has already been produced and
we need to recover from the error. In that case, use NULL_TREE
for the type, as if no type had been specified; this will use the
default type ('id') which is good for error recovery. */
if (type == error_mark_node)
type = NULL_TREE;
return build_tree_list (quals, type);
}
/* Parse objc-protocol-refs.
objc-protocol-refs:
< identifier-list >
*/
static tree
c_parser_objc_protocol_refs (c_parser *parser)
{
tree list = NULL_TREE;
gcc_assert (c_parser_next_token_is (parser, CPP_LESS));
c_parser_consume_token (parser);
/* Any identifiers, including those declared as type names, are OK
here. */
while (true)
{
tree id;
if (c_parser_next_token_is_not (parser, CPP_NAME))
{
c_parser_error (parser, "expected identifier");
break;
}
id = c_parser_peek_token (parser)->value;
list = chainon (list, build_tree_list (NULL_TREE, id));
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_COMMA))
c_parser_consume_token (parser);
else
break;
}
c_parser_require (parser, CPP_GREATER, "expected %<>%>");
return list;
}
/* Parse an objc-try-catch-finally-statement.
objc-try-catch-finally-statement:
@try compound-statement objc-catch-list[opt]
@try compound-statement objc-catch-list[opt] @finally compound-statement
objc-catch-list:
@catch ( objc-catch-parameter-declaration ) compound-statement
objc-catch-list @catch ( objc-catch-parameter-declaration ) compound-statement
objc-catch-parameter-declaration:
parameter-declaration
'...'
where '...' is to be interpreted literally, that is, it means CPP_ELLIPSIS.
PS: This function is identical to cp_parser_objc_try_catch_finally_statement
for C++. Keep them in sync. */
static void
c_parser_objc_try_catch_finally_statement (c_parser *parser)
{
location_t location;
tree stmt;
gcc_assert (c_parser_next_token_is_keyword (parser, RID_AT_TRY));
c_parser_consume_token (parser);
location = c_parser_peek_token (parser)->location;
objc_maybe_warn_exceptions (location);
stmt = c_parser_compound_statement (parser);
objc_begin_try_stmt (location, stmt);
while (c_parser_next_token_is_keyword (parser, RID_AT_CATCH))
{
struct c_parm *parm;
tree parameter_declaration = error_mark_node;
bool seen_open_paren = false;
c_parser_consume_token (parser);
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
seen_open_paren = true;
if (c_parser_next_token_is (parser, CPP_ELLIPSIS))
{
/* We have "@catch (...)" (where the '...' are literally
what is in the code). Skip the '...'.
parameter_declaration is set to NULL_TREE, and
objc_being_catch_clauses() knows that that means
'...'. */
c_parser_consume_token (parser);
parameter_declaration = NULL_TREE;
}
else
{
/* We have "@catch (NSException *exception)" or something
like that. Parse the parameter declaration. */
parm = c_parser_parameter_declaration (parser, NULL_TREE);
if (parm == NULL)
parameter_declaration = error_mark_node;
else
parameter_declaration = grokparm (parm);
}
if (seen_open_paren)
c_parser_require (parser, CPP_CLOSE_PAREN, "expected %<)%>");
else
{
/* If there was no open parenthesis, we are recovering from
an error, and we are trying to figure out what mistake
the user has made. */
/* If there is an immediate closing parenthesis, the user
probably forgot the opening one (ie, they typed "@catch
NSException *e)". Parse the closing parenthesis and keep
going. */
if (c_parser_next_token_is (parser, CPP_CLOSE_PAREN))
c_parser_consume_token (parser);
/* If these is no immediate closing parenthesis, the user
probably doesn't know that parenthesis are required at
all (ie, they typed "@catch NSException *e"). So, just
forget about the closing parenthesis and keep going. */
}
objc_begin_catch_clause (parameter_declaration);
if (c_parser_require (parser, CPP_OPEN_BRACE, "expected %<{%>"))
c_parser_compound_statement_nostart (parser);
objc_finish_catch_clause ();
}
if (c_parser_next_token_is_keyword (parser, RID_AT_FINALLY))
{
c_parser_consume_token (parser);
location = c_parser_peek_token (parser)->location;
stmt = c_parser_compound_statement (parser);
objc_build_finally_clause (location, stmt);
}
objc_finish_try_stmt ();
}
/* Parse an objc-synchronized-statement.
objc-synchronized-statement:
@synchronized ( expression ) compound-statement
*/
static void
c_parser_objc_synchronized_statement (c_parser *parser)
{
location_t loc;
tree expr, stmt;
gcc_assert (c_parser_next_token_is_keyword (parser, RID_AT_SYNCHRONIZED));
c_parser_consume_token (parser);
loc = c_parser_peek_token (parser)->location;
objc_maybe_warn_exceptions (loc);
if (c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
{
expr = c_parser_expression (parser).value;
expr = c_fully_fold (expr, false, NULL);
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, "expected %<)%>");
}
else
expr = error_mark_node;
stmt = c_parser_compound_statement (parser);
objc_build_synchronized (loc, expr, stmt);
}
/* Parse an objc-selector; return NULL_TREE without an error if the
next token is not an objc-selector.
objc-selector:
identifier
one of
enum struct union if else while do for switch case default
break continue return goto asm sizeof typeof __alignof
unsigned long const short volatile signed restrict _Complex
in out inout bycopy byref oneway int char float double void _Bool
??? Why this selection of keywords but not, for example, storage
class specifiers? */
static tree
c_parser_objc_selector (c_parser *parser)
{
c_token *token = c_parser_peek_token (parser);
tree value = token->value;
if (token->type == CPP_NAME)
{
c_parser_consume_token (parser);
return value;
}
if (token->type != CPP_KEYWORD)
return NULL_TREE;
switch (token->keyword)
{
case RID_ENUM:
case RID_STRUCT:
case RID_UNION:
case RID_IF:
case RID_ELSE:
case RID_WHILE:
case RID_DO:
case RID_FOR:
case RID_SWITCH:
case RID_CASE:
case RID_DEFAULT:
case RID_BREAK:
case RID_CONTINUE:
case RID_RETURN:
case RID_GOTO:
case RID_ASM:
case RID_SIZEOF:
case RID_TYPEOF:
case RID_ALIGNOF:
case RID_UNSIGNED:
case RID_LONG:
case RID_INT128:
case RID_CONST:
case RID_SHORT:
case RID_VOLATILE:
case RID_SIGNED:
case RID_RESTRICT:
case RID_COMPLEX:
case RID_IN:
case RID_OUT:
case RID_INOUT:
case RID_BYCOPY:
case RID_BYREF:
case RID_ONEWAY:
case RID_INT:
case RID_CHAR:
case RID_FLOAT:
case RID_DOUBLE:
case RID_VOID:
case RID_BOOL:
c_parser_consume_token (parser);
return value;
default:
return NULL_TREE;
}
}
/* Parse an objc-selector-arg.
objc-selector-arg:
objc-selector
objc-keywordname-list
objc-keywordname-list:
objc-keywordname
objc-keywordname-list objc-keywordname
objc-keywordname:
objc-selector :
:
*/
static tree
c_parser_objc_selector_arg (c_parser *parser)
{
tree sel = c_parser_objc_selector (parser);
tree list = NULL_TREE;
if (sel && c_parser_next_token_is_not (parser, CPP_COLON))
return sel;
while (true)
{
if (!c_parser_require (parser, CPP_COLON, "expected %<:%>"))
return list;
list = chainon (list, build_tree_list (sel, NULL_TREE));
sel = c_parser_objc_selector (parser);
if (!sel && c_parser_next_token_is_not (parser, CPP_COLON))
break;
}
return list;
}
/* Parse an objc-receiver.
objc-receiver:
expression
class-name
type-name
*/
static tree
c_parser_objc_receiver (c_parser *parser)
{
if (c_parser_peek_token (parser)->type == CPP_NAME
&& (c_parser_peek_token (parser)->id_kind == C_ID_TYPENAME
|| c_parser_peek_token (parser)->id_kind == C_ID_CLASSNAME))
{
tree id = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
return objc_get_class_reference (id);
}
return c_fully_fold (c_parser_expression (parser).value, false, NULL);
}
/* Parse objc-message-args.
objc-message-args:
objc-selector
objc-keywordarg-list
objc-keywordarg-list:
objc-keywordarg
objc-keywordarg-list objc-keywordarg
objc-keywordarg:
objc-selector : objc-keywordexpr
: objc-keywordexpr
*/
static tree
c_parser_objc_message_args (c_parser *parser)
{
tree sel = c_parser_objc_selector (parser);
tree list = NULL_TREE;
if (sel && c_parser_next_token_is_not (parser, CPP_COLON))
return sel;
while (true)
{
tree keywordexpr;
if (!c_parser_require (parser, CPP_COLON, "expected %<:%>"))
return error_mark_node;
keywordexpr = c_parser_objc_keywordexpr (parser);
list = chainon (list, build_tree_list (sel, keywordexpr));
sel = c_parser_objc_selector (parser);
if (!sel && c_parser_next_token_is_not (parser, CPP_COLON))
break;
}
return list;
}
/* Parse an objc-keywordexpr.
objc-keywordexpr:
nonempty-expr-list
*/
static tree
c_parser_objc_keywordexpr (c_parser *parser)
{
tree ret;
VEC(tree,gc) *expr_list = c_parser_expr_list (parser, true, true, NULL);
if (VEC_length (tree, expr_list) == 1)
{
/* Just return the expression, remove a level of
indirection. */
ret = VEC_index (tree, expr_list, 0);
}
else
{
/* We have a comma expression, we will collapse later. */
ret = build_tree_list_vec (expr_list);
}
release_tree_vector (expr_list);
return ret;
}
/* A check, needed in several places, that ObjC interface, implementation or
method definitions are not prefixed by incorrect items. */
static bool
c_parser_objc_diagnose_bad_element_prefix (c_parser *parser,
struct c_declspecs *specs)
{
if (!specs->declspecs_seen_p || specs->non_sc_seen_p
|| specs->typespec_kind != ctsk_none)
{
c_parser_error (parser,
"no type or storage class may be specified here,");
c_parser_skip_to_end_of_block_or_statement (parser);
return true;
}
return false;
}
/* Parse an Objective-C @property declaration. The syntax is:
objc-property-declaration:
'@property' objc-property-attributes[opt] struct-declaration ;
objc-property-attributes:
'(' objc-property-attribute-list ')'
objc-property-attribute-list:
objc-property-attribute
objc-property-attribute-list, objc-property-attribute
objc-property-attribute
'getter' = identifier
'setter' = identifier
'readonly'
'readwrite'
'assign'
'retain'
'copy'
'nonatomic'
For example:
@property NSString *name;
@property (readonly) id object;
@property (retain, nonatomic, getter=getTheName) id name;
@property int a, b, c;
PS: This function is identical to cp_parser_objc_at_propery_declaration
for C++. Keep them in sync. */
static void
c_parser_objc_at_property_declaration (c_parser *parser)
{
/* The following variables hold the attributes of the properties as
parsed. They are 'false' or 'NULL_TREE' if the attribute was not
seen. When we see an attribute, we set them to 'true' (if they
are boolean properties) or to the identifier (if they have an
argument, ie, for getter and setter). Note that here we only
parse the list of attributes, check the syntax and accumulate the
attributes that we find. objc_add_property_declaration() will
then process the information. */
bool property_assign = false;
bool property_copy = false;
tree property_getter_ident = NULL_TREE;
bool property_nonatomic = false;
bool property_readonly = false;
bool property_readwrite = false;
bool property_retain = false;
tree property_setter_ident = NULL_TREE;
/* 'properties' is the list of properties that we read. Usually a
single one, but maybe more (eg, in "@property int a, b, c;" there
are three). */
tree properties;
location_t loc;
loc = c_parser_peek_token (parser)->location;
gcc_assert (c_parser_next_token_is_keyword (parser, RID_AT_PROPERTY));
c_parser_consume_token (parser); /* Eat '@property'. */
/* Parse the optional attribute list... */
if (c_parser_next_token_is (parser, CPP_OPEN_PAREN))
{
/* Eat the '(' */
c_parser_consume_token (parser);
/* Property attribute keywords are valid now. */
parser->objc_property_attr_context = true;
while (true)
{
bool syntax_error = false;
c_token *token = c_parser_peek_token (parser);
enum rid keyword;
if (token->type != CPP_KEYWORD)
{
if (token->type == CPP_CLOSE_PAREN)
c_parser_error (parser, "expected identifier");
else
{
c_parser_consume_token (parser);
c_parser_error (parser, "unknown property attribute");
}
break;
}
keyword = token->keyword;
c_parser_consume_token (parser);
switch (keyword)
{
case RID_ASSIGN: property_assign = true; break;
case RID_COPY: property_copy = true; break;
case RID_NONATOMIC: property_nonatomic = true; break;
case RID_READONLY: property_readonly = true; break;
case RID_READWRITE: property_readwrite = true; break;
case RID_RETAIN: property_retain = true; break;
case RID_GETTER:
case RID_SETTER:
if (c_parser_next_token_is_not (parser, CPP_EQ))
{
if (keyword == RID_GETTER)
c_parser_error (parser,
"missing %<=%> (after %<getter%> attribute)");
else
c_parser_error (parser,
"missing %<=%> (after %<setter%> attribute)");
syntax_error = true;
break;
}
c_parser_consume_token (parser); /* eat the = */
if (c_parser_next_token_is_not (parser, CPP_NAME))
{
c_parser_error (parser, "expected identifier");
syntax_error = true;
break;
}
if (keyword == RID_SETTER)
{
if (property_setter_ident != NULL_TREE)
c_parser_error (parser, "the %<setter%> attribute may only be specified once");
else
property_setter_ident = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
if (c_parser_next_token_is_not (parser, CPP_COLON))
c_parser_error (parser, "setter name must terminate with %<:%>");
else
c_parser_consume_token (parser);
}
else
{
if (property_getter_ident != NULL_TREE)
c_parser_error (parser, "the %<getter%> attribute may only be specified once");
else
property_getter_ident = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
}
break;
default:
c_parser_error (parser, "unknown property attribute");
syntax_error = true;
break;
}
if (syntax_error)
break;
if (c_parser_next_token_is (parser, CPP_COMMA))
c_parser_consume_token (parser);
else
break;
}
parser->objc_property_attr_context = false;
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, "expected %<)%>");
}
/* ... and the property declaration(s). */
properties = c_parser_struct_declaration (parser);
if (properties == error_mark_node)
{
c_parser_skip_until_found (parser, CPP_SEMICOLON, NULL);
parser->error = false;
return;
}
if (properties == NULL_TREE)
c_parser_error (parser, "expected identifier");
else
{
/* Comma-separated properties are chained together in
reverse order; add them one by one. */
properties = nreverse (properties);
for (; properties; properties = TREE_CHAIN (properties))
objc_add_property_declaration (loc, copy_node (properties),
property_readonly, property_readwrite,
property_assign, property_retain,
property_copy, property_nonatomic,
property_getter_ident, property_setter_ident);
}
c_parser_skip_until_found (parser, CPP_SEMICOLON, "expected %<;%>");
parser->error = false;
}
/* Parse an Objective-C @synthesize declaration. The syntax is:
objc-synthesize-declaration:
@synthesize objc-synthesize-identifier-list ;
objc-synthesize-identifier-list:
objc-synthesize-identifier
objc-synthesize-identifier-list, objc-synthesize-identifier
objc-synthesize-identifier
identifier
identifier = identifier
For example:
@synthesize MyProperty;
@synthesize OneProperty, AnotherProperty=MyIvar, YetAnotherProperty;
PS: This function is identical to cp_parser_objc_at_synthesize_declaration
for C++. Keep them in sync.
*/
static void
c_parser_objc_at_synthesize_declaration (c_parser *parser)
{
tree list = NULL_TREE;
location_t loc;
gcc_assert (c_parser_next_token_is_keyword (parser, RID_AT_SYNTHESIZE));
loc = c_parser_peek_token (parser)->location;
c_parser_consume_token (parser);
while (true)
{
tree property, ivar;
if (c_parser_next_token_is_not (parser, CPP_NAME))
{
c_parser_error (parser, "expected identifier");
c_parser_skip_until_found (parser, CPP_SEMICOLON, NULL);
/* Once we find the semicolon, we can resume normal parsing.
We have to reset parser->error manually because
c_parser_skip_until_found() won't reset it for us if the
next token is precisely a semicolon. */
parser->error = false;
return;
}
property = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_EQ))
{
c_parser_consume_token (parser);
if (c_parser_next_token_is_not (parser, CPP_NAME))
{
c_parser_error (parser, "expected identifier");
c_parser_skip_until_found (parser, CPP_SEMICOLON, NULL);
parser->error = false;
return;
}
ivar = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
}
else
ivar = NULL_TREE;
list = chainon (list, build_tree_list (ivar, property));
if (c_parser_next_token_is (parser, CPP_COMMA))
c_parser_consume_token (parser);
else
break;
}
c_parser_skip_until_found (parser, CPP_SEMICOLON, "expected %<;%>");
objc_add_synthesize_declaration (loc, list);
}
/* Parse an Objective-C @dynamic declaration. The syntax is:
objc-dynamic-declaration:
@dynamic identifier-list ;
For example:
@dynamic MyProperty;
@dynamic MyProperty, AnotherProperty;
PS: This function is identical to cp_parser_objc_at_dynamic_declaration
for C++. Keep them in sync.
*/
static void
c_parser_objc_at_dynamic_declaration (c_parser *parser)
{
tree list = NULL_TREE;
location_t loc;
gcc_assert (c_parser_next_token_is_keyword (parser, RID_AT_DYNAMIC));
loc = c_parser_peek_token (parser)->location;
c_parser_consume_token (parser);
while (true)
{
tree property;
if (c_parser_next_token_is_not (parser, CPP_NAME))
{
c_parser_error (parser, "expected identifier");
c_parser_skip_until_found (parser, CPP_SEMICOLON, NULL);
parser->error = false;
return;
}
property = c_parser_peek_token (parser)->value;
list = chainon (list, build_tree_list (NULL_TREE, property));
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_COMMA))
c_parser_consume_token (parser);
else
break;
}
c_parser_skip_until_found (parser, CPP_SEMICOLON, "expected %<;%>");
objc_add_dynamic_declaration (loc, list);
}
/* Handle pragmas. Some OpenMP pragmas are associated with, and therefore
should be considered, statements. ALLOW_STMT is true if we're within
the context of a function and such pragmas are to be allowed. Returns
true if we actually parsed such a pragma. */
static bool
c_parser_pragma (c_parser *parser, enum pragma_context context)
{
unsigned int id;
id = c_parser_peek_token (parser)->pragma_kind;
gcc_assert (id != PRAGMA_NONE);
switch (id)
{
case PRAGMA_OMP_BARRIER:
if (context != pragma_compound)
{
if (context == pragma_stmt)
c_parser_error (parser, "%<#pragma omp barrier%> may only be "
"used in compound statements");
goto bad_stmt;
}
c_parser_omp_barrier (parser);
return false;
case PRAGMA_OMP_FLUSH:
if (context != pragma_compound)
{
if (context == pragma_stmt)
c_parser_error (parser, "%<#pragma omp flush%> may only be "
"used in compound statements");
goto bad_stmt;
}
c_parser_omp_flush (parser);
return false;
case PRAGMA_OMP_TASKWAIT:
if (context != pragma_compound)
{
if (context == pragma_stmt)
c_parser_error (parser, "%<#pragma omp taskwait%> may only be "
"used in compound statements");
goto bad_stmt;
}
c_parser_omp_taskwait (parser);
return false;
case PRAGMA_OMP_THREADPRIVATE:
c_parser_omp_threadprivate (parser);
return false;
case PRAGMA_OMP_SECTION:
error_at (c_parser_peek_token (parser)->location,
"%<#pragma omp section%> may only be used in "
"%<#pragma omp sections%> construct");
c_parser_skip_until_found (parser, CPP_PRAGMA_EOL, NULL);
return false;
case PRAGMA_GCC_PCH_PREPROCESS:
c_parser_error (parser, "%<#pragma GCC pch_preprocess%> must be first");
c_parser_skip_until_found (parser, CPP_PRAGMA_EOL, NULL);
return false;
default:
if (id < PRAGMA_FIRST_EXTERNAL)
{
if (context == pragma_external)
{
bad_stmt:
c_parser_error (parser, "expected declaration specifiers");
c_parser_skip_until_found (parser, CPP_PRAGMA_EOL, NULL);
return false;
}
c_parser_omp_construct (parser);
return true;
}
break;
}
c_parser_consume_pragma (parser);
c_invoke_pragma_handler (id);
/* Skip to EOL, but suppress any error message. Those will have been
generated by the handler routine through calling error, as opposed
to calling c_parser_error. */
parser->error = true;
c_parser_skip_to_pragma_eol (parser);
return false;
}
/* The interface the pragma parsers have to the lexer. */
enum cpp_ttype
pragma_lex (tree *value)
{
c_token *tok = c_parser_peek_token (the_parser);
enum cpp_ttype ret = tok->type;
*value = tok->value;
if (ret == CPP_PRAGMA_EOL || ret == CPP_EOF)
ret = CPP_EOF;
else
{
if (ret == CPP_KEYWORD)
ret = CPP_NAME;
c_parser_consume_token (the_parser);
}
return ret;
}
static void
c_parser_pragma_pch_preprocess (c_parser *parser)
{
tree name = NULL;
c_parser_consume_pragma (parser);
if (c_parser_next_token_is (parser, CPP_STRING))
{
name = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
}
else
c_parser_error (parser, "expected string literal");
c_parser_skip_to_pragma_eol (parser);
if (name)
c_common_pch_pragma (parse_in, TREE_STRING_POINTER (name));
}
/* OpenMP 2.5 parsing routines. */
/* Returns name of the next clause.
If the clause is not recognized PRAGMA_OMP_CLAUSE_NONE is returned and
the token is not consumed. Otherwise appropriate pragma_omp_clause is
returned and the token is consumed. */
static pragma_omp_clause
c_parser_omp_clause_name (c_parser *parser)
{
pragma_omp_clause result = PRAGMA_OMP_CLAUSE_NONE;
if (c_parser_next_token_is_keyword (parser, RID_IF))
result = PRAGMA_OMP_CLAUSE_IF;
else if (c_parser_next_token_is_keyword (parser, RID_DEFAULT))
result = PRAGMA_OMP_CLAUSE_DEFAULT;
else if (c_parser_next_token_is (parser, CPP_NAME))
{
const char *p = IDENTIFIER_POINTER (c_parser_peek_token (parser)->value);
switch (p[0])
{
case 'c':
if (!strcmp ("collapse", p))
result = PRAGMA_OMP_CLAUSE_COLLAPSE;
else if (!strcmp ("copyin", p))
result = PRAGMA_OMP_CLAUSE_COPYIN;
else if (!strcmp ("copyprivate", p))
result = PRAGMA_OMP_CLAUSE_COPYPRIVATE;
break;
case 'f':
if (!strcmp ("firstprivate", p))
result = PRAGMA_OMP_CLAUSE_FIRSTPRIVATE;
break;
case 'l':
if (!strcmp ("lastprivate", p))
result = PRAGMA_OMP_CLAUSE_LASTPRIVATE;
break;
case 'n':
if (!strcmp ("nowait", p))
result = PRAGMA_OMP_CLAUSE_NOWAIT;
else if (!strcmp ("num_threads", p))
result = PRAGMA_OMP_CLAUSE_NUM_THREADS;
break;
case 'o':
if (!strcmp ("ordered", p))
result = PRAGMA_OMP_CLAUSE_ORDERED;
break;
case 'p':
if (!strcmp ("private", p))
result = PRAGMA_OMP_CLAUSE_PRIVATE;
break;
case 'r':
if (!strcmp ("reduction", p))
result = PRAGMA_OMP_CLAUSE_REDUCTION;
break;
case 's':
if (!strcmp ("schedule", p))
result = PRAGMA_OMP_CLAUSE_SCHEDULE;
else if (!strcmp ("shared", p))
result = PRAGMA_OMP_CLAUSE_SHARED;
break;
case 'u':
if (!strcmp ("untied", p))
result = PRAGMA_OMP_CLAUSE_UNTIED;
break;
}
}
if (result != PRAGMA_OMP_CLAUSE_NONE)
c_parser_consume_token (parser);
return result;
}
/* Validate that a clause of the given type does not already exist. */
static void
check_no_duplicate_clause (tree clauses, enum omp_clause_code code,
const char *name)
{
tree c;
for (c = clauses; c ; c = OMP_CLAUSE_CHAIN (c))
if (OMP_CLAUSE_CODE (c) == code)
{
location_t loc = OMP_CLAUSE_LOCATION (c);
error_at (loc, "too many %qs clauses", name);
break;
}
}
/* OpenMP 2.5:
variable-list:
identifier
variable-list , identifier
If KIND is nonzero, create the appropriate node and install the
decl in OMP_CLAUSE_DECL and add the node to the head of the list.
If KIND is nonzero, CLAUSE_LOC is the location of the clause.
If KIND is zero, create a TREE_LIST with the decl in TREE_PURPOSE;
return the list created. */
static tree
c_parser_omp_variable_list (c_parser *parser,
location_t clause_loc,
enum omp_clause_code kind,
tree list)
{
if (c_parser_next_token_is_not (parser, CPP_NAME)
|| c_parser_peek_token (parser)->id_kind != C_ID_ID)
c_parser_error (parser, "expected identifier");
while (c_parser_next_token_is (parser, CPP_NAME)
&& c_parser_peek_token (parser)->id_kind == C_ID_ID)
{
tree t = lookup_name (c_parser_peek_token (parser)->value);
if (t == NULL_TREE)
undeclared_variable (c_parser_peek_token (parser)->location,
c_parser_peek_token (parser)->value);
else if (t == error_mark_node)
;
else if (kind != 0)
{
tree u = build_omp_clause (clause_loc, kind);
OMP_CLAUSE_DECL (u) = t;
OMP_CLAUSE_CHAIN (u) = list;
list = u;
}
else
list = tree_cons (t, NULL_TREE, list);
c_parser_consume_token (parser);
if (c_parser_next_token_is_not (parser, CPP_COMMA))
break;
c_parser_consume_token (parser);
}
return list;
}
/* Similarly, but expect leading and trailing parenthesis. This is a very
common case for omp clauses. */
static tree
c_parser_omp_var_list_parens (c_parser *parser, enum omp_clause_code kind,
tree list)
{
/* The clauses location. */
location_t loc = c_parser_peek_token (parser)->location;
if (c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
{
list = c_parser_omp_variable_list (parser, loc, kind, list);
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, "expected %<)%>");
}
return list;
}
/* OpenMP 3.0:
collapse ( constant-expression ) */
static tree
c_parser_omp_clause_collapse (c_parser *parser, tree list)
{
tree c, num = error_mark_node;
HOST_WIDE_INT n;
location_t loc;
check_no_duplicate_clause (list, OMP_CLAUSE_COLLAPSE, "collapse");
loc = c_parser_peek_token (parser)->location;
if (c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
{
num = c_parser_expr_no_commas (parser, NULL).value;
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, "expected %<)%>");
}
if (num == error_mark_node)
return list;
if (!INTEGRAL_TYPE_P (TREE_TYPE (num))
|| !host_integerp (num, 0)
|| (n = tree_low_cst (num, 0)) <= 0
|| (int) n != n)
{
error_at (loc,
"collapse argument needs positive constant integer expression");
return list;
}
c = build_omp_clause (loc, OMP_CLAUSE_COLLAPSE);
OMP_CLAUSE_COLLAPSE_EXPR (c) = num;
OMP_CLAUSE_CHAIN (c) = list;
return c;
}
/* OpenMP 2.5:
copyin ( variable-list ) */
static tree
c_parser_omp_clause_copyin (c_parser *parser, tree list)
{
return c_parser_omp_var_list_parens (parser, OMP_CLAUSE_COPYIN, list);
}
/* OpenMP 2.5:
copyprivate ( variable-list ) */
static tree
c_parser_omp_clause_copyprivate (c_parser *parser, tree list)
{
return c_parser_omp_var_list_parens (parser, OMP_CLAUSE_COPYPRIVATE, list);
}
/* OpenMP 2.5:
default ( shared | none ) */
static tree
c_parser_omp_clause_default (c_parser *parser, tree list)
{
enum omp_clause_default_kind kind = OMP_CLAUSE_DEFAULT_UNSPECIFIED;
location_t loc = c_parser_peek_token (parser)->location;
tree c;
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
return list;
if (c_parser_next_token_is (parser, CPP_NAME))
{
const char *p = IDENTIFIER_POINTER (c_parser_peek_token (parser)->value);
switch (p[0])
{
case 'n':
if (strcmp ("none", p) != 0)
goto invalid_kind;
kind = OMP_CLAUSE_DEFAULT_NONE;
break;
case 's':
if (strcmp ("shared", p) != 0)
goto invalid_kind;
kind = OMP_CLAUSE_DEFAULT_SHARED;
break;
default:
goto invalid_kind;
}
c_parser_consume_token (parser);
}
else
{
invalid_kind:
c_parser_error (parser, "expected %<none%> or %<shared%>");
}
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, "expected %<)%>");
if (kind == OMP_CLAUSE_DEFAULT_UNSPECIFIED)
return list;
check_no_duplicate_clause (list, OMP_CLAUSE_DEFAULT, "default");
c = build_omp_clause (loc, OMP_CLAUSE_DEFAULT);
OMP_CLAUSE_CHAIN (c) = list;
OMP_CLAUSE_DEFAULT_KIND (c) = kind;
return c;
}
/* OpenMP 2.5:
firstprivate ( variable-list ) */
static tree
c_parser_omp_clause_firstprivate (c_parser *parser, tree list)
{
return c_parser_omp_var_list_parens (parser, OMP_CLAUSE_FIRSTPRIVATE, list);
}
/* OpenMP 2.5:
if ( expression ) */
static tree
c_parser_omp_clause_if (c_parser *parser, tree list)
{
location_t loc = c_parser_peek_token (parser)->location;
if (c_parser_next_token_is (parser, CPP_OPEN_PAREN))
{
tree t = c_parser_paren_condition (parser);
tree c;
check_no_duplicate_clause (list, OMP_CLAUSE_IF, "if");
c = build_omp_clause (loc, OMP_CLAUSE_IF);
OMP_CLAUSE_IF_EXPR (c) = t;
OMP_CLAUSE_CHAIN (c) = list;
list = c;
}
else
c_parser_error (parser, "expected %<(%>");
return list;
}
/* OpenMP 2.5:
lastprivate ( variable-list ) */
static tree
c_parser_omp_clause_lastprivate (c_parser *parser, tree list)
{
return c_parser_omp_var_list_parens (parser, OMP_CLAUSE_LASTPRIVATE, list);
}
/* OpenMP 2.5:
nowait */
static tree
c_parser_omp_clause_nowait (c_parser *parser ATTRIBUTE_UNUSED, tree list)
{
tree c;
location_t loc = c_parser_peek_token (parser)->location;
check_no_duplicate_clause (list, OMP_CLAUSE_NOWAIT, "nowait");
c = build_omp_clause (loc, OMP_CLAUSE_NOWAIT);
OMP_CLAUSE_CHAIN (c) = list;
return c;
}
/* OpenMP 2.5:
num_threads ( expression ) */
static tree
c_parser_omp_clause_num_threads (c_parser *parser, tree list)
{
location_t num_threads_loc = c_parser_peek_token (parser)->location;
if (c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
{
location_t expr_loc = c_parser_peek_token (parser)->location;
tree c, t = c_parser_expression (parser).value;
t = c_fully_fold (t, false, NULL);
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, "expected %<)%>");
if (!INTEGRAL_TYPE_P (TREE_TYPE (t)))
{
c_parser_error (parser, "expected integer expression");
return list;
}
/* Attempt to statically determine when the number isn't positive. */
c = fold_build2_loc (expr_loc, LE_EXPR, boolean_type_node, t,
build_int_cst (TREE_TYPE (t), 0));
if (CAN_HAVE_LOCATION_P (c))
SET_EXPR_LOCATION (c, expr_loc);
if (c == boolean_true_node)
{
warning_at (expr_loc, 0,
"%<num_threads%> value must be positive");
t = integer_one_node;
}
check_no_duplicate_clause (list, OMP_CLAUSE_NUM_THREADS, "num_threads");
c = build_omp_clause (num_threads_loc, OMP_CLAUSE_NUM_THREADS);
OMP_CLAUSE_NUM_THREADS_EXPR (c) = t;
OMP_CLAUSE_CHAIN (c) = list;
list = c;
}
return list;
}
/* OpenMP 2.5:
ordered */
static tree
c_parser_omp_clause_ordered (c_parser *parser, tree list)
{
tree c;
check_no_duplicate_clause (list, OMP_CLAUSE_ORDERED, "ordered");
c = build_omp_clause (c_parser_peek_token (parser)->location,
OMP_CLAUSE_ORDERED);
OMP_CLAUSE_CHAIN (c) = list;
return c;
}
/* OpenMP 2.5:
private ( variable-list ) */
static tree
c_parser_omp_clause_private (c_parser *parser, tree list)
{
return c_parser_omp_var_list_parens (parser, OMP_CLAUSE_PRIVATE, list);
}
/* OpenMP 2.5:
reduction ( reduction-operator : variable-list )
reduction-operator:
One of: + * - & ^ | && || */
static tree
c_parser_omp_clause_reduction (c_parser *parser, tree list)
{
location_t clause_loc = c_parser_peek_token (parser)->location;
if (c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
{
enum tree_code code;
switch (c_parser_peek_token (parser)->type)
{
case CPP_PLUS:
code = PLUS_EXPR;
break;
case CPP_MULT:
code = MULT_EXPR;
break;
case CPP_MINUS:
code = MINUS_EXPR;
break;
case CPP_AND:
code = BIT_AND_EXPR;
break;
case CPP_XOR:
code = BIT_XOR_EXPR;
break;
case CPP_OR:
code = BIT_IOR_EXPR;
break;
case CPP_AND_AND:
code = TRUTH_ANDIF_EXPR;
break;
case CPP_OR_OR:
code = TRUTH_ORIF_EXPR;
break;
default:
c_parser_error (parser,
"expected %<+%>, %<*%>, %<-%>, %<&%>, "
"%<^%>, %<|%>, %<&&%>, or %<||%>");
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, 0);
return list;
}
c_parser_consume_token (parser);
if (c_parser_require (parser, CPP_COLON, "expected %<:%>"))
{
tree nl, c;
nl = c_parser_omp_variable_list (parser, clause_loc,
OMP_CLAUSE_REDUCTION, list);
for (c = nl; c != list; c = OMP_CLAUSE_CHAIN (c))
OMP_CLAUSE_REDUCTION_CODE (c) = code;
list = nl;
}
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, "expected %<)%>");
}
return list;
}
/* OpenMP 2.5:
schedule ( schedule-kind )
schedule ( schedule-kind , expression )
schedule-kind:
static | dynamic | guided | runtime | auto
*/
static tree
c_parser_omp_clause_schedule (c_parser *parser, tree list)
{
tree c, t;
location_t loc = c_parser_peek_token (parser)->location;
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
return list;
c = build_omp_clause (loc, OMP_CLAUSE_SCHEDULE);
if (c_parser_next_token_is (parser, CPP_NAME))
{
tree kind = c_parser_peek_token (parser)->value;
const char *p = IDENTIFIER_POINTER (kind);
switch (p[0])
{
case 'd':
if (strcmp ("dynamic", p) != 0)
goto invalid_kind;
OMP_CLAUSE_SCHEDULE_KIND (c) = OMP_CLAUSE_SCHEDULE_DYNAMIC;
break;
case 'g':
if (strcmp ("guided", p) != 0)
goto invalid_kind;
OMP_CLAUSE_SCHEDULE_KIND (c) = OMP_CLAUSE_SCHEDULE_GUIDED;
break;
case 'r':
if (strcmp ("runtime", p) != 0)
goto invalid_kind;
OMP_CLAUSE_SCHEDULE_KIND (c) = OMP_CLAUSE_SCHEDULE_RUNTIME;
break;
default:
goto invalid_kind;
}
}
else if (c_parser_next_token_is_keyword (parser, RID_STATIC))
OMP_CLAUSE_SCHEDULE_KIND (c) = OMP_CLAUSE_SCHEDULE_STATIC;
else if (c_parser_next_token_is_keyword (parser, RID_AUTO))
OMP_CLAUSE_SCHEDULE_KIND (c) = OMP_CLAUSE_SCHEDULE_AUTO;
else
goto invalid_kind;
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_COMMA))
{
location_t here;
c_parser_consume_token (parser);
here = c_parser_peek_token (parser)->location;
t = c_parser_expr_no_commas (parser, NULL).value;
t = c_fully_fold (t, false, NULL);
if (OMP_CLAUSE_SCHEDULE_KIND (c) == OMP_CLAUSE_SCHEDULE_RUNTIME)
error_at (here, "schedule %<runtime%> does not take "
"a %<chunk_size%> parameter");
else if (OMP_CLAUSE_SCHEDULE_KIND (c) == OMP_CLAUSE_SCHEDULE_AUTO)
error_at (here,
"schedule %<auto%> does not take "
"a %<chunk_size%> parameter");
else if (TREE_CODE (TREE_TYPE (t)) == INTEGER_TYPE)
OMP_CLAUSE_SCHEDULE_CHUNK_EXPR (c) = t;
else
c_parser_error (parser, "expected integer expression");
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, "expected %<)%>");
}
else
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<,%> or %<)%>");
check_no_duplicate_clause (list, OMP_CLAUSE_SCHEDULE, "schedule");
OMP_CLAUSE_CHAIN (c) = list;
return c;
invalid_kind:
c_parser_error (parser, "invalid schedule kind");
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, 0);
return list;
}
/* OpenMP 2.5:
shared ( variable-list ) */
static tree
c_parser_omp_clause_shared (c_parser *parser, tree list)
{
return c_parser_omp_var_list_parens (parser, OMP_CLAUSE_SHARED, list);
}
/* OpenMP 3.0:
untied */
static tree
c_parser_omp_clause_untied (c_parser *parser ATTRIBUTE_UNUSED, tree list)
{
tree c;
/* FIXME: Should we allow duplicates? */
check_no_duplicate_clause (list, OMP_CLAUSE_UNTIED, "untied");
c = build_omp_clause (c_parser_peek_token (parser)->location,
OMP_CLAUSE_UNTIED);
OMP_CLAUSE_CHAIN (c) = list;
return c;
}
/* Parse all OpenMP clauses. The set clauses allowed by the directive
is a bitmask in MASK. Return the list of clauses found; the result
of clause default goes in *pdefault. */
static tree
c_parser_omp_all_clauses (c_parser *parser, unsigned int mask,
const char *where)
{
tree clauses = NULL;
bool first = true;
while (c_parser_next_token_is_not (parser, CPP_PRAGMA_EOL))
{
location_t here;
pragma_omp_clause c_kind;
const char *c_name;
tree prev = clauses;
if (!first && c_parser_next_token_is (parser, CPP_COMMA))
c_parser_consume_token (parser);
first = false;
here = c_parser_peek_token (parser)->location;
c_kind = c_parser_omp_clause_name (parser);
switch (c_kind)
{
case PRAGMA_OMP_CLAUSE_COLLAPSE:
clauses = c_parser_omp_clause_collapse (parser, clauses);
c_name = "collapse";
break;
case PRAGMA_OMP_CLAUSE_COPYIN:
clauses = c_parser_omp_clause_copyin (parser, clauses);
c_name = "copyin";
break;
case PRAGMA_OMP_CLAUSE_COPYPRIVATE:
clauses = c_parser_omp_clause_copyprivate (parser, clauses);
c_name = "copyprivate";
break;
case PRAGMA_OMP_CLAUSE_DEFAULT:
clauses = c_parser_omp_clause_default (parser, clauses);
c_name = "default";
break;
case PRAGMA_OMP_CLAUSE_FIRSTPRIVATE:
clauses = c_parser_omp_clause_firstprivate (parser, clauses);
c_name = "firstprivate";
break;
case PRAGMA_OMP_CLAUSE_IF:
clauses = c_parser_omp_clause_if (parser, clauses);
c_name = "if";
break;
case PRAGMA_OMP_CLAUSE_LASTPRIVATE:
clauses = c_parser_omp_clause_lastprivate (parser, clauses);
c_name = "lastprivate";
break;
case PRAGMA_OMP_CLAUSE_NOWAIT:
clauses = c_parser_omp_clause_nowait (parser, clauses);
c_name = "nowait";
break;
case PRAGMA_OMP_CLAUSE_NUM_THREADS:
clauses = c_parser_omp_clause_num_threads (parser, clauses);
c_name = "num_threads";
break;
case PRAGMA_OMP_CLAUSE_ORDERED:
clauses = c_parser_omp_clause_ordered (parser, clauses);
c_name = "ordered";
break;
case PRAGMA_OMP_CLAUSE_PRIVATE:
clauses = c_parser_omp_clause_private (parser, clauses);
c_name = "private";
break;
case PRAGMA_OMP_CLAUSE_REDUCTION:
clauses = c_parser_omp_clause_reduction (parser, clauses);
c_name = "reduction";
break;
case PRAGMA_OMP_CLAUSE_SCHEDULE:
clauses = c_parser_omp_clause_schedule (parser, clauses);
c_name = "schedule";
break;
case PRAGMA_OMP_CLAUSE_SHARED:
clauses = c_parser_omp_clause_shared (parser, clauses);
c_name = "shared";
break;
case PRAGMA_OMP_CLAUSE_UNTIED:
clauses = c_parser_omp_clause_untied (parser, clauses);
c_name = "untied";
break;
default:
c_parser_error (parser, "expected %<#pragma omp%> clause");
goto saw_error;
}
if (((mask >> c_kind) & 1) == 0 && !parser->error)
{
/* Remove the invalid clause(s) from the list to avoid
confusing the rest of the compiler. */
clauses = prev;
error_at (here, "%qs is not valid for %qs", c_name, where);
}
}
saw_error:
c_parser_skip_to_pragma_eol (parser);
return c_finish_omp_clauses (clauses);
}
/* OpenMP 2.5:
structured-block:
statement
In practice, we're also interested in adding the statement to an
outer node. So it is convenient if we work around the fact that
c_parser_statement calls add_stmt. */
static tree
c_parser_omp_structured_block (c_parser *parser)
{
tree stmt = push_stmt_list ();
c_parser_statement (parser);
return pop_stmt_list (stmt);
}
/* OpenMP 2.5:
# pragma omp atomic new-line
expression-stmt
expression-stmt:
x binop= expr | x++ | ++x | x-- | --x
binop:
+, *, -, /, &, ^, |, <<, >>
where x is an lvalue expression with scalar type.
LOC is the location of the #pragma token. */
static void
c_parser_omp_atomic (location_t loc, c_parser *parser)
{
tree lhs, rhs;
tree stmt;
enum tree_code code;
struct c_expr rhs_expr;
c_parser_skip_to_pragma_eol (parser);
lhs = c_parser_unary_expression (parser).value;
lhs = c_fully_fold (lhs, false, NULL);
switch (TREE_CODE (lhs))
{
case ERROR_MARK:
saw_error:
c_parser_skip_to_end_of_block_or_statement (parser);
return;
case PREINCREMENT_EXPR:
case POSTINCREMENT_EXPR:
lhs = TREE_OPERAND (lhs, 0);
code = PLUS_EXPR;
rhs = integer_one_node;
break;
case PREDECREMENT_EXPR:
case POSTDECREMENT_EXPR:
lhs = TREE_OPERAND (lhs, 0);
code = MINUS_EXPR;
rhs = integer_one_node;
break;
case COMPOUND_EXPR:
if (TREE_CODE (TREE_OPERAND (lhs, 0)) == SAVE_EXPR
&& TREE_CODE (TREE_OPERAND (lhs, 1)) == COMPOUND_EXPR
&& TREE_CODE (TREE_OPERAND (TREE_OPERAND (lhs, 1), 0)) == MODIFY_EXPR
&& TREE_OPERAND (TREE_OPERAND (lhs, 1), 1) == TREE_OPERAND (lhs, 0)
&& TREE_CODE (TREE_TYPE (TREE_OPERAND (TREE_OPERAND
(TREE_OPERAND (lhs, 1), 0), 0)))
== BOOLEAN_TYPE)
/* Undo effects of boolean_increment for post {in,de}crement. */
lhs = TREE_OPERAND (TREE_OPERAND (lhs, 1), 0);
/* FALLTHRU */
case MODIFY_EXPR:
if (TREE_CODE (lhs) == MODIFY_EXPR
&& TREE_CODE (TREE_TYPE (TREE_OPERAND (lhs, 0))) == BOOLEAN_TYPE)
{
/* Undo effects of boolean_increment. */
if (integer_onep (TREE_OPERAND (lhs, 1)))
{
/* This is pre or post increment. */
rhs = TREE_OPERAND (lhs, 1);
lhs = TREE_OPERAND (lhs, 0);
code = NOP_EXPR;
break;
}
if (TREE_CODE (TREE_OPERAND (lhs, 1)) == TRUTH_NOT_EXPR
&& TREE_OPERAND (lhs, 0)
== TREE_OPERAND (TREE_OPERAND (lhs, 1), 0))
{
/* This is pre or post decrement. */
rhs = TREE_OPERAND (lhs, 1);
lhs = TREE_OPERAND (lhs, 0);
code = NOP_EXPR;
break;
}
}
/* FALLTHRU */
default:
switch (c_parser_peek_token (parser)->type)
{
case CPP_MULT_EQ:
code = MULT_EXPR;
break;
case CPP_DIV_EQ:
code = TRUNC_DIV_EXPR;
break;
case CPP_PLUS_EQ:
code = PLUS_EXPR;
break;
case CPP_MINUS_EQ:
code = MINUS_EXPR;
break;
case CPP_LSHIFT_EQ:
code = LSHIFT_EXPR;
break;
case CPP_RSHIFT_EQ:
code = RSHIFT_EXPR;
break;
case CPP_AND_EQ:
code = BIT_AND_EXPR;
break;
case CPP_OR_EQ:
code = BIT_IOR_EXPR;
break;
case CPP_XOR_EQ:
code = BIT_XOR_EXPR;
break;
default:
c_parser_error (parser,
"invalid operator for %<#pragma omp atomic%>");
goto saw_error;
}
/* Arrange to pass the location of the assignment operator to
c_finish_omp_atomic. */
loc = c_parser_peek_token (parser)->location;
c_parser_consume_token (parser);
{
location_t rhs_loc = c_parser_peek_token (parser)->location;
rhs_expr = c_parser_expression (parser);
rhs_expr = default_function_array_read_conversion (rhs_loc, rhs_expr);
}
rhs = rhs_expr.value;
rhs = c_fully_fold (rhs, false, NULL);
break;
}
stmt = c_finish_omp_atomic (loc, code, lhs, rhs);
if (stmt != error_mark_node)
add_stmt (stmt);
c_parser_skip_until_found (parser, CPP_SEMICOLON, "expected %<;%>");
}
/* OpenMP 2.5:
# pragma omp barrier new-line
*/
static void
c_parser_omp_barrier (c_parser *parser)
{
location_t loc = c_parser_peek_token (parser)->location;
c_parser_consume_pragma (parser);
c_parser_skip_to_pragma_eol (parser);
c_finish_omp_barrier (loc);
}
/* OpenMP 2.5:
# pragma omp critical [(name)] new-line
structured-block
LOC is the location of the #pragma itself. */
static tree
c_parser_omp_critical (location_t loc, c_parser *parser)
{
tree stmt, name = NULL;
if (c_parser_next_token_is (parser, CPP_OPEN_PAREN))
{
c_parser_consume_token (parser);
if (c_parser_next_token_is (parser, CPP_NAME))
{
name = c_parser_peek_token (parser)->value;
c_parser_consume_token (parser);
c_parser_require (parser, CPP_CLOSE_PAREN, "expected %<)%>");
}
else
c_parser_error (parser, "expected identifier");
}
else if (c_parser_next_token_is_not (parser, CPP_PRAGMA_EOL))
c_parser_error (parser, "expected %<(%> or end of line");
c_parser_skip_to_pragma_eol (parser);
stmt = c_parser_omp_structured_block (parser);
return c_finish_omp_critical (loc, stmt, name);
}
/* OpenMP 2.5:
# pragma omp flush flush-vars[opt] new-line
flush-vars:
( variable-list ) */
static void
c_parser_omp_flush (c_parser *parser)
{
location_t loc = c_parser_peek_token (parser)->location;
c_parser_consume_pragma (parser);
if (c_parser_next_token_is (parser, CPP_OPEN_PAREN))
c_parser_omp_var_list_parens (parser, OMP_CLAUSE_ERROR, NULL);
else if (c_parser_next_token_is_not (parser, CPP_PRAGMA_EOL))
c_parser_error (parser, "expected %<(%> or end of line");
c_parser_skip_to_pragma_eol (parser);
c_finish_omp_flush (loc);
}
/* Parse the restricted form of the for statement allowed by OpenMP.
The real trick here is to determine the loop control variable early
so that we can push a new decl if necessary to make it private.
LOC is the location of the OMP in "#pragma omp". */
static tree
c_parser_omp_for_loop (location_t loc,
c_parser *parser, tree clauses, tree *par_clauses)
{
tree decl, cond, incr, save_break, save_cont, body, init, stmt, cl;
tree declv, condv, incrv, initv, ret = NULL;
bool fail = false, open_brace_parsed = false;
int i, collapse = 1, nbraces = 0;
location_t for_loc;
VEC(tree,gc) *for_block = make_tree_vector ();
for (cl = clauses; cl; cl = OMP_CLAUSE_CHAIN (cl))
if (OMP_CLAUSE_CODE (cl) == OMP_CLAUSE_COLLAPSE)
collapse = tree_low_cst (OMP_CLAUSE_COLLAPSE_EXPR (cl), 0);
gcc_assert (collapse >= 1);
declv = make_tree_vec (collapse);
initv = make_tree_vec (collapse);
condv = make_tree_vec (collapse);
incrv = make_tree_vec (collapse);
if (!c_parser_next_token_is_keyword (parser, RID_FOR))
{
c_parser_error (parser, "for statement expected");
return NULL;
}
for_loc = c_parser_peek_token (parser)->location;
c_parser_consume_token (parser);
for (i = 0; i < collapse; i++)
{
int bracecount = 0;
if (!c_parser_require (parser, CPP_OPEN_PAREN, "expected %<(%>"))
goto pop_scopes;
/* Parse the initialization declaration or expression. */
if (c_parser_next_tokens_start_declaration (parser))
{
if (i > 0)
VEC_safe_push (tree, gc, for_block, c_begin_compound_stmt (true));
c_parser_declaration_or_fndef (parser, true, true, true, true, true, NULL);
decl = check_for_loop_decls (for_loc, flag_isoc99);
if (decl == NULL)
goto error_init;
if (DECL_INITIAL (decl) == error_mark_node)
decl = error_mark_node;
init = decl;
}
else if (c_parser_next_token_is (parser, CPP_NAME)
&& c_parser_peek_2nd_token (parser)->type == CPP_EQ)
{
struct c_expr decl_exp;
struct c_expr init_exp;
location_t init_loc;
decl_exp = c_parser_postfix_expression (parser);
decl = decl_exp.value;
c_parser_require (parser, CPP_EQ, "expected %<=%>");
init_loc = c_parser_peek_token (parser)->location;
init_exp = c_parser_expr_no_commas (parser, NULL);
init_exp = default_function_array_read_conversion (init_loc,
init_exp);
init = build_modify_expr (init_loc, decl, decl_exp.original_type,
NOP_EXPR, init_loc, init_exp.value,
init_exp.original_type);
init = c_process_expr_stmt (init_loc, init);
c_parser_skip_until_found (parser, CPP_SEMICOLON, "expected %<;%>");
}
else
{
error_init:
c_parser_error (parser,
"expected iteration declaration or initialization");
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN,
"expected %<)%>");
fail = true;
goto parse_next;
}
/* Parse the loop condition. */
cond = NULL_TREE;
if (c_parser_next_token_is_not (parser, CPP_SEMICOLON))
{
location_t cond_loc = c_parser_peek_token (parser)->location;
struct c_expr cond_expr = c_parser_binary_expression (parser, NULL);
cond = cond_expr.value;
cond = c_objc_common_truthvalue_conversion (cond_loc, cond);
cond = c_fully_fold (cond, false, NULL);
switch (cond_expr.original_code)
{
case GT_EXPR:
case GE_EXPR:
case LT_EXPR:
case LE_EXPR:
break;
default:
/* Can't be cond = error_mark_node, because we want to preserve
the location until c_finish_omp_for. */
cond = build1 (NOP_EXPR, boolean_type_node, error_mark_node);
break;
}
protected_set_expr_location (cond, cond_loc);
}
c_parser_skip_until_found (parser, CPP_SEMICOLON, "expected %<;%>");
/* Parse the increment expression. */
incr = NULL_TREE;
if (c_parser_next_token_is_not (parser, CPP_CLOSE_PAREN))
{
location_t incr_loc = c_parser_peek_token (parser)->location;
incr = c_process_expr_stmt (incr_loc,
c_parser_expression (parser).value);
}
c_parser_skip_until_found (parser, CPP_CLOSE_PAREN, "expected %<)%>");
if (decl == NULL || decl == error_mark_node || init == error_mark_node)
fail = true;
else
{
TREE_VEC_ELT (declv, i) = decl;
TREE_VEC_ELT (initv, i) = init;
TREE_VEC_ELT (condv, i) = cond;
TREE_VEC_ELT (incrv, i) = incr;
}
parse_next:
if (i == collapse - 1)
break;
/* FIXME: OpenMP 3.0 draft isn't very clear on what exactly is allowed
in between the collapsed for loops to be still considered perfectly
nested. Hopefully the final version clarifies this.
For now handle (multiple) {'s and empty statements. */
do
{
if (c_parser_next_token_is_keyword (parser, RID_FOR))
{
c_parser_consume_token (parser);
break;
}
else if (c_parser_next_token_is (parser, CPP_OPEN_BRACE))
{
c_parser_consume_token (parser);
bracecount++;
}
else if (bracecount
&& c_parser_next_token_is (parser, CPP_SEMICOLON))
c_parser_consume_token (parser);
else
{
c_parser_error (parser, "not enough perfectly nested loops");
if (bracecount)
{
open_brace_parsed = true;
bracecount--;
}
fail = true;
collapse = 0;
break;
}
}
while (1);
nbraces += bracecount;
}
save_break = c_break_label;
c_break_label = size_one_node;
save_cont = c_cont_label;
c_cont_label = NULL_TREE;
body = push_stmt_list ();
if (open_brace_parsed)
{
location_t here = c_parser_peek_token (parser)->location;
stmt = c_begin_compound_stmt (true);
c_parser_compound_statement_nostart (parser);
add_stmt (c_end_compound_stmt (here, stmt, true));
}
else
add_stmt (c_parser_c99_block_statement (parser));
if (c_cont_label)
{
tree t = build1 (LABEL_EXPR, void_type_node, c_cont_label);
SET_EXPR_LOCATION (t, loc);
add_stmt (t);
}
body = pop_stmt_list (body);
c_break_label = save_break;
c_cont_label = save_cont;
while (nbraces)
{
if (c_parser_next_token_is (parser, CPP_CLOSE_BRACE))
{
c_parser_consume_token (parser);
nbraces--;
}
else if (c_parser_next_token_is (parser, CPP_SEMICOLON))
c_parser_consume_token (parser);
else
{
c_parser_error (parser, "collapsed loops not perfectly nested");
while (nbraces)
{
location_t here = c_parser_peek_token (parser)->location;
stmt = c_begin_compound_stmt (true);
add_stmt (body);
c_parser_compound_statement_nostart (parser);
body = c_end_compound_stmt (here, stmt, true);
nbraces--;
}
goto pop_scopes;
}
}
/* Only bother calling c_finish_omp_for if we haven't already generated
an error from the initialization parsing. */
if (!fail)
{
stmt = c_finish_omp_for (loc, declv, initv, condv, incrv, body, NULL);
if (stmt)
{
if (par_clauses != NULL)
{
tree *c;
for (c = par_clauses; *c ; )
if (OMP_CLAUSE_CODE (*c) != OMP_CLAUSE_FIRSTPRIVATE
&& OMP_CLAUSE_CODE (*c) != OMP_CLAUSE_LASTPRIVATE)
c = &OMP_CLAUSE_CHAIN (*c);
else
{
for (i = 0; i < collapse; i++)
if (TREE_VEC_ELT (declv, i) == OMP_CLAUSE_DECL (*c))
break;
if (i == collapse)
c = &OMP_CLAUSE_CHAIN (*c);
else if (OMP_CLAUSE_CODE (*c) == OMP_CLAUSE_FIRSTPRIVATE)
{
error_at (loc,
"iteration variable %qD should not be firstprivate",
OMP_CLAUSE_DECL (*c));
*c = OMP_CLAUSE_CHAIN (*c);
}
else
{
/* Copy lastprivate (decl) clause to OMP_FOR_CLAUSES,
change it to shared (decl) in
OMP_PARALLEL_CLAUSES. */
tree l = build_omp_clause (OMP_CLAUSE_LOCATION (*c),
OMP_CLAUSE_LASTPRIVATE);
OMP_CLAUSE_DECL (l) = OMP_CLAUSE_DECL (*c);
OMP_CLAUSE_CHAIN (l) = clauses;
clauses = l;
OMP_CLAUSE_SET_CODE (*c, OMP_CLAUSE_SHARED);
}
}
}
OMP_FOR_CLAUSES (stmt) = clauses;
}
ret = stmt;
}
pop_scopes:
while (!VEC_empty (tree, for_block))
{
/* FIXME diagnostics: LOC below should be the actual location of
this particular for block. We need to build a list of
locations to go along with FOR_BLOCK. */
stmt = c_end_compound_stmt (loc, VEC_pop (tree, for_block), true);
add_stmt (stmt);
}
release_tree_vector (for_block);
return ret;
}
/* OpenMP 2.5:
#pragma omp for for-clause[optseq] new-line
for-loop
LOC is the location of the #pragma token.
*/
#define OMP_FOR_CLAUSE_MASK \
( (1u << PRAGMA_OMP_CLAUSE_PRIVATE) \
| (1u << PRAGMA_OMP_CLAUSE_FIRSTPRIVATE) \
| (1u << PRAGMA_OMP_CLAUSE_LASTPRIVATE) \
| (1u << PRAGMA_OMP_CLAUSE_REDUCTION) \
| (1u << PRAGMA_OMP_CLAUSE_ORDERED) \
| (1u << PRAGMA_OMP_CLAUSE_SCHEDULE) \
| (1u << PRAGMA_OMP_CLAUSE_COLLAPSE) \
| (1u << PRAGMA_OMP_CLAUSE_NOWAIT))
static tree
c_parser_omp_for (location_t loc, c_parser *parser)
{
tree block, clauses, ret;
clauses = c_parser_omp_all_clauses (parser, OMP_FOR_CLAUSE_MASK,
"#pragma omp for");
block = c_begin_compound_stmt (true);
ret = c_parser_omp_for_loop (loc, parser, clauses, NULL);
block = c_end_compound_stmt (loc, block, true);
add_stmt (block);
return ret;
}
/* OpenMP 2.5:
# pragma omp master new-line
structured-block
LOC is the location of the #pragma token.
*/
static tree
c_parser_omp_master (location_t loc, c_parser *parser)
{
c_parser_skip_to_pragma_eol (parser);
return c_finish_omp_master (loc, c_parser_omp_structured_block (parser));
}
/* OpenMP 2.5:
# pragma omp ordered new-line
structured-block
LOC is the location of the #pragma itself.
*/
static tree
c_parser_omp_ordered (location_t loc, c_parser *parser)
{
c_parser_skip_to_pragma_eol (parser);
return c_finish_omp_ordered (loc, c_parser_omp_structured_block (parser));
}
/* OpenMP 2.5:
section-scope:
{ section-sequence }
section-sequence:
section-directive[opt] structured-block
section-sequence section-directive structured-block
SECTIONS_LOC is the location of the #pragma omp sections. */
static tree
c_parser_omp_sections_scope (location_t sections_loc, c_parser *parser)
{
tree stmt, substmt;
bool error_suppress = false;
location_t loc;
loc = c_parser_peek_token (parser)->location;
if (!c_parser_require (parser, CPP_OPEN_BRACE, "expected %<{%>"))
{
/* Avoid skipping until the end of the block. */
parser->error = false;
return NULL_TREE;
}
stmt = push_stmt_list ();
if (c_parser_peek_token (parser)->pragma_kind != PRAGMA_OMP_SECTION)
{
substmt = push_stmt_list ();
while (1)
{
c_parser_statement (parser);
if (c_parser_peek_token (parser)->pragma_kind == PRAGMA_OMP_SECTION)
break;
if (c_parser_next_token_is (parser, CPP_CLOSE_BRACE))
break;
if (c_parser_next_token_is (parser, CPP_EOF))
break;
}
substmt = pop_stmt_list (substmt);
substmt = build1 (OMP_SECTION, void_type_node, substmt);
SET_EXPR_LOCATION (substmt, loc);
add_stmt (substmt);
}
while (1)
{
if (c_parser_next_token_is (parser, CPP_CLOSE_BRACE))
break;
if (c_parser_next_token_is (parser, CPP_EOF))
break;
loc = c_parser_peek_token (parser)->location;
if (c_parser_peek_token (parser)->pragma_kind == PRAGMA_OMP_SECTION)
{
c_parser_consume_pragma (parser);
c_parser_skip_to_pragma_eol (parser);
error_suppress = false;
}
else if (!error_suppress)
{
error_at (loc, "expected %<#pragma omp section%> or %<}%>");
error_suppress = true;
}
substmt = c_parser_omp_structured_block (parser);
substmt = build1 (OMP_SECTION, void_type_node, substmt);
SET_EXPR_LOCATION (substmt, loc);
add_stmt (substmt);
}
c_parser_skip_until_found (parser, CPP_CLOSE_BRACE,
"expected %<#pragma omp section%> or %<}%>");
substmt = pop_stmt_list (stmt);
stmt = make_node (OMP_SECTIONS);
SET_EXPR_LOCATION (stmt, sections_loc);
TREE_TYPE (stmt) = void_type_node;
OMP_SECTIONS_BODY (stmt) = substmt;
return add_stmt (stmt);
}
/* OpenMP 2.5:
# pragma omp sections sections-clause[optseq] newline
sections-scope
LOC is the location of the #pragma token.
*/
#define OMP_SECTIONS_CLAUSE_MASK \
( (1u << PRAGMA_OMP_CLAUSE_PRIVATE) \
| (1u << PRAGMA_OMP_CLAUSE_FIRSTPRIVATE) \
| (1u << PRAGMA_OMP_CLAUSE_LASTPRIVATE) \
| (1u << PRAGMA_OMP_CLAUSE_REDUCTION) \
| (1u << PRAGMA_OMP_CLAUSE_NOWAIT))
static tree
c_parser_omp_sections (location_t loc, c_parser *parser)
{
tree block, clauses, ret;
clauses = c_parser_omp_all_clauses (parser, OMP_SECTIONS_CLAUSE_MASK,
"#pragma omp sections");
block = c_begin_compound_stmt (true);
ret = c_parser_omp_sections_scope (loc, parser);
if (ret)
OMP_SECTIONS_CLAUSES (ret) = clauses;
block = c_end_compound_stmt (loc, block, true);
add_stmt (block);
return ret;
}
/* OpenMP 2.5:
# pragma parallel parallel-clause new-line
# pragma parallel for parallel-for-clause new-line
# pragma parallel sections parallel-sections-clause new-line
LOC is the location of the #pragma token.
*/
#define OMP_PARALLEL_CLAUSE_MASK \
( (1u << PRAGMA_OMP_CLAUSE_IF) \
| (1u << PRAGMA_OMP_CLAUSE_PRIVATE) \
| (1u << PRAGMA_OMP_CLAUSE_FIRSTPRIVATE) \
| (1u << PRAGMA_OMP_CLAUSE_DEFAULT) \
| (1u << PRAGMA_OMP_CLAUSE_SHARED) \
| (1u << PRAGMA_OMP_CLAUSE_COPYIN) \
| (1u << PRAGMA_OMP_CLAUSE_REDUCTION) \
| (1u << PRAGMA_OMP_CLAUSE_NUM_THREADS))
static tree
c_parser_omp_parallel (location_t loc, c_parser *parser)
{
enum pragma_kind p_kind = PRAGMA_OMP_PARALLEL;
const char *p_name = "#pragma omp parallel";
tree stmt, clauses, par_clause, ws_clause, block;
unsigned int mask = OMP_PARALLEL_CLAUSE_MASK;
if (c_parser_next_token_is_keyword (parser, RID_FOR))
{
c_parser_consume_token (parser);
p_kind = PRAGMA_OMP_PARALLEL_FOR;
p_name = "#pragma omp parallel for";
mask |= OMP_FOR_CLAUSE_MASK;
mask &= ~(1u << PRAGMA_OMP_CLAUSE_NOWAIT);
}
else if (c_parser_next_token_is (parser, CPP_NAME))
{
const char *p = IDENTIFIER_POINTER (c_parser_peek_token (parser)->value);
if (strcmp (p, "sections") == 0)
{
c_parser_consume_token (parser);
p_kind = PRAGMA_OMP_PARALLEL_SECTIONS;
p_name = "#pragma omp parallel sections";
mask |= OMP_SECTIONS_CLAUSE_MASK;
mask &= ~(1u << PRAGMA_OMP_CLAUSE_NOWAIT);
}
}
clauses = c_parser_omp_all_clauses (parser, mask, p_name);
switch (p_kind)
{
case PRAGMA_OMP_PARALLEL:
block = c_begin_omp_parallel ();
c_parser_statement (parser);
stmt = c_finish_omp_parallel (loc, clauses, block);
break;
case PRAGMA_OMP_PARALLEL_FOR:
block = c_begin_omp_parallel ();
c_split_parallel_clauses (loc, clauses, &par_clause, &ws_clause);
c_parser_omp_for_loop (loc, parser, ws_clause, &par_clause);
stmt = c_finish_omp_parallel (loc, par_clause, block);
OMP_PARALLEL_COMBINED (stmt) = 1;
break;
case PRAGMA_OMP_PARALLEL_SECTIONS:
block = c_begin_omp_parallel ();
c_split_parallel_clauses (loc, clauses, &par_clause, &ws_clause);
stmt = c_parser_omp_sections_scope (loc, parser);
if (stmt)
OMP_SECTIONS_CLAUSES (stmt) = ws_clause;
stmt = c_finish_omp_parallel (loc, par_clause, block);
OMP_PARALLEL_COMBINED (stmt) = 1;
break;
default:
gcc_unreachable ();
}
return stmt;
}
/* OpenMP 2.5:
# pragma omp single single-clause[optseq] new-line
structured-block
LOC is the location of the #pragma.
*/
#define OMP_SINGLE_CLAUSE_MASK \
( (1u << PRAGMA_OMP_CLAUSE_PRIVATE) \
| (1u << PRAGMA_OMP_CLAUSE_FIRSTPRIVATE) \
| (1u << PRAGMA_OMP_CLAUSE_COPYPRIVATE) \
| (1u << PRAGMA_OMP_CLAUSE_NOWAIT))
static tree
c_parser_omp_single (location_t loc, c_parser *parser)
{
tree stmt = make_node (OMP_SINGLE);
SET_EXPR_LOCATION (stmt, loc);
TREE_TYPE (stmt) = void_type_node;
OMP_SINGLE_CLAUSES (stmt)
= c_parser_omp_all_clauses (parser, OMP_SINGLE_CLAUSE_MASK,
"#pragma omp single");
OMP_SINGLE_BODY (stmt) = c_parser_omp_structured_block (parser);
return add_stmt (stmt);
}
/* OpenMP 3.0:
# pragma omp task task-clause[optseq] new-line
LOC is the location of the #pragma.
*/
#define OMP_TASK_CLAUSE_MASK \
( (1u << PRAGMA_OMP_CLAUSE_IF) \
| (1u << PRAGMA_OMP_CLAUSE_UNTIED) \
| (1u << PRAGMA_OMP_CLAUSE_DEFAULT) \
| (1u << PRAGMA_OMP_CLAUSE_PRIVATE) \
| (1u << PRAGMA_OMP_CLAUSE_FIRSTPRIVATE) \
| (1u << PRAGMA_OMP_CLAUSE_SHARED))
static tree
c_parser_omp_task (location_t loc, c_parser *parser)
{
tree clauses, block;
clauses = c_parser_omp_all_clauses (parser, OMP_TASK_CLAUSE_MASK,
"#pragma omp task");
block = c_begin_omp_task ();
c_parser_statement (parser);
return c_finish_omp_task (loc, clauses, block);
}
/* OpenMP 3.0:
# pragma omp taskwait new-line
*/
static void
c_parser_omp_taskwait (c_parser *parser)
{
location_t loc = c_parser_peek_token (parser)->location;
c_parser_consume_pragma (parser);
c_parser_skip_to_pragma_eol (parser);
c_finish_omp_taskwait (loc);
}
/* Main entry point to parsing most OpenMP pragmas. */
static void
c_parser_omp_construct (c_parser *parser)
{
enum pragma_kind p_kind;
location_t loc;
tree stmt;
loc = c_parser_peek_token (parser)->location;
p_kind = c_parser_peek_token (parser)->pragma_kind;
c_parser_consume_pragma (parser);
switch (p_kind)
{
case PRAGMA_OMP_ATOMIC:
c_parser_omp_atomic (loc, parser);
return;
case PRAGMA_OMP_CRITICAL:
stmt = c_parser_omp_critical (loc, parser);
break;
case PRAGMA_OMP_FOR:
stmt = c_parser_omp_for (loc, parser);
break;
case PRAGMA_OMP_MASTER:
stmt = c_parser_omp_master (loc, parser);
break;
case PRAGMA_OMP_ORDERED:
stmt = c_parser_omp_ordered (loc, parser);
break;
case PRAGMA_OMP_PARALLEL:
stmt = c_parser_omp_parallel (loc, parser);
break;
case PRAGMA_OMP_SECTIONS:
stmt = c_parser_omp_sections (loc, parser);
break;
case PRAGMA_OMP_SINGLE:
stmt = c_parser_omp_single (loc, parser);
break;
case PRAGMA_OMP_TASK:
stmt = c_parser_omp_task (loc, parser);
break;
default:
gcc_unreachable ();
}
if (stmt)
gcc_assert (EXPR_LOCATION (stmt) != UNKNOWN_LOCATION);
}
/* OpenMP 2.5:
# pragma omp threadprivate (variable-list) */
static void
c_parser_omp_threadprivate (c_parser *parser)
{
tree vars, t;
location_t loc;
c_parser_consume_pragma (parser);
loc = c_parser_peek_token (parser)->location;
vars = c_parser_omp_var_list_parens (parser, OMP_CLAUSE_ERROR, NULL);
/* Mark every variable in VARS to be assigned thread local storage. */
for (t = vars; t; t = TREE_CHAIN (t))
{
tree v = TREE_PURPOSE (t);
/* FIXME diagnostics: Ideally we should keep individual
locations for all the variables in the var list to make the
following errors more precise. Perhaps
c_parser_omp_var_list_parens() should construct a list of
locations to go along with the var list. */
/* If V had already been marked threadprivate, it doesn't matter
whether it had been used prior to this point. */
if (TREE_CODE (v) != VAR_DECL)
error_at (loc, "%qD is not a variable", v);
else if (TREE_USED (v) && !C_DECL_THREADPRIVATE_P (v))
error_at (loc, "%qE declared %<threadprivate%> after first use", v);
else if (! TREE_STATIC (v) && ! DECL_EXTERNAL (v))
error_at (loc, "automatic variable %qE cannot be %<threadprivate%>", v);
else if (TREE_TYPE (v) == error_mark_node)
;
else if (! COMPLETE_TYPE_P (TREE_TYPE (v)))
error_at (loc, "%<threadprivate%> %qE has incomplete type", v);
else
{
if (! DECL_THREAD_LOCAL_P (v))
{
DECL_TLS_MODEL (v) = decl_default_tls_model (v);
/* If rtl has been already set for this var, call
make_decl_rtl once again, so that encode_section_info
has a chance to look at the new decl flags. */
if (DECL_RTL_SET_P (v))
make_decl_rtl (v);
}
C_DECL_THREADPRIVATE_P (v) = 1;
}
}
c_parser_skip_to_pragma_eol (parser);
}
/* Parse a single source file. */
void
c_parse_file (void)
{
/* Use local storage to begin. If the first token is a pragma, parse it.
If it is #pragma GCC pch_preprocess, then this will load a PCH file
which will cause garbage collection. */
c_parser tparser;
memset (&tparser, 0, sizeof tparser);
the_parser = &tparser;
if (c_parser_peek_token (&tparser)->pragma_kind == PRAGMA_GCC_PCH_PREPROCESS)
c_parser_pragma_pch_preprocess (&tparser);
the_parser = ggc_alloc_c_parser ();
*the_parser = tparser;
/* Initialize EH, if we've been told to do so. */
if (flag_exceptions)
using_eh_for_cleanups ();
c_parser_translation_unit (the_parser);
the_parser = NULL;
}
#include "gt-c-parser.h"
|
convolution_sgemm_pack8to4_int8.h | // Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.
//
// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
// in compliance with the License. You may obtain a copy of the License at
//
// https://opensource.org/licenses/BSD-3-Clause
//
// Unless required by applicable law or agreed to in writing, software distributed
// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
// CONDITIONS OF ANY KIND, either express or implied. See the License for the
// specific language governing permissions and limitations under the License.
static void im2col_sgemm_pack8to4_int8_neon(const Mat& bottom_im2col, Mat& top_blob, const Mat& kernel, const Option& opt)
{
// Mat bottom_im2col(size, maxk, inch, 8u, 8, opt.workspace_allocator);
const int size = bottom_im2col.w;
const int maxk = bottom_im2col.h;
const int inch = bottom_im2col.c;
const int outch = top_blob.c;
// permute
Mat tmp;
#if __aarch64__
#if __ARM_FEATURE_DOTPROD
if (size >= 16)
tmp.create(16 * maxk, inch, size / 16 + (size % 16) / 8 + (size % 8) / 4 + (size % 4) / 2 + size % 2, 8u, 8, opt.workspace_allocator);
else if (size >= 8)
tmp.create(8 * maxk, inch, size / 8 + (size % 8) / 4 + (size % 4) / 2 + size % 2, 8u, 8, opt.workspace_allocator);
else if (size >= 4)
tmp.create(4 * maxk, inch, size / 4 + (size % 4) / 2 + size % 2, 8u, 8, opt.workspace_allocator);
else if (size >= 2)
tmp.create(2 * maxk, inch, size / 2 + size % 2, 8u, 8, opt.workspace_allocator);
else
tmp.create(maxk, inch, size, 8u, 8, opt.workspace_allocator);
#else // __ARM_FEATURE_DOTPROD
if (size >= 4)
tmp.create(4 * maxk, inch, size / 4 + (size % 4) / 2 + size % 2, 8u, 8, opt.workspace_allocator);
else if (size >= 2)
tmp.create(2 * maxk, inch, size / 2 + size % 2, 8u, 8, opt.workspace_allocator);
else
tmp.create(maxk, inch, size, 8u, 8, opt.workspace_allocator);
#endif // __ARM_FEATURE_DOTPROD
#else // __aarch64__
if (size >= 2)
tmp.create(2 * maxk, inch, size / 2 + size % 2, 8u, 8, opt.workspace_allocator);
else
tmp.create(maxk, inch, size, 8u, 8, opt.workspace_allocator);
#endif // __aarch64__
{
#if __aarch64__
#if __ARM_FEATURE_DOTPROD
int nn_size = size >> 4;
int remain_size_start = 0;
#pragma omp parallel for num_threads(opt.num_threads)
for (int ii = 0; ii < nn_size; ii++)
{
int i = remain_size_start + ii * 16;
signed char* tmpptr = tmp.channel(i / 16);
for (int q = 0; q < inch; q++)
{
const signed char* img0 = (const signed char*)bottom_im2col.channel(q) + i * 8;
for (int k = 0; k < maxk; k++)
{
// split pack8 to pack4
asm volatile(
"prfm pldl1keep, [%0, #512] \n"
"ld2 {v0.4s, v1.4s}, [%0], #32 \n"
"ld2 {v2.4s, v3.4s}, [%0], #32 \n"
"ld2 {v4.4s, v5.4s}, [%0], #32 \n"
"ld2 {v6.4s, v7.4s}, [%0] \n"
"sub %0, %0, #96 \n"
"st1 {v0.16b}, [%1], #16 \n"
"st1 {v2.16b}, [%1], #16 \n"
"st1 {v4.16b}, [%1], #16 \n"
"st1 {v6.16b}, [%1], #16 \n"
"st1 {v1.16b}, [%1], #16 \n"
"st1 {v3.16b}, [%1], #16 \n"
"st1 {v5.16b}, [%1], #16 \n"
"st1 {v7.16b}, [%1], #16 \n"
: "=r"(img0), // %0
"=r"(tmpptr) // %1
: "0"(img0),
"1"(tmpptr)
: "memory", "v0", "v1", "v2", "v3", "v4", "v5", "v6", "v7");
img0 += size * 8;
}
}
}
remain_size_start += nn_size << 4;
nn_size = (size - remain_size_start) >> 3;
#pragma omp parallel for num_threads(opt.num_threads)
for (int ii = 0; ii < nn_size; ii++)
{
int i = remain_size_start + ii * 8;
signed char* tmpptr = tmp.channel(i / 16 + (i % 16) / 8);
for (int q = 0; q < inch; q++)
{
const signed char* img0 = (const signed char*)bottom_im2col.channel(q) + i * 8;
for (int k = 0; k < maxk; k++)
{
asm volatile(
"prfm pldl1keep, [%0, #512] \n"
"ld2 {v0.4s, v1.4s}, [%0], #32 \n"
"ld2 {v2.4s, v3.4s}, [%0] \n"
"sub %0, %0, #32 \n"
"st1 {v0.16b}, [%1], #16 \n"
"st1 {v2.16b}, [%1], #16 \n"
"st1 {v1.16b}, [%1], #16 \n"
"st1 {v3.16b}, [%1], #16 \n"
: "=r"(img0), // %0
"=r"(tmpptr) // %1
: "0"(img0),
"1"(tmpptr)
: "memory", "v0", "v1", "v2", "v3");
img0 += size * 8;
}
}
}
remain_size_start += nn_size << 3;
nn_size = (size - remain_size_start) >> 2;
#else // __ARM_FEATURE_DOTPROD
int remain_size_start = 0;
int nn_size = (size - remain_size_start) >> 2;
#endif // __ARM_FEATURE_DOTPROD
#pragma omp parallel for num_threads(opt.num_threads)
for (int ii = 0; ii < nn_size; ii++)
{
int i = remain_size_start + ii * 4;
#if __ARM_FEATURE_DOTPROD
signed char* tmpptr = tmp.channel(i / 16 + (i % 16) / 8 + (i % 8) / 4);
#else
signed char* tmpptr = tmp.channel(i / 4);
#endif
for (int q = 0; q < inch; q++)
{
const signed char* img0 = (const signed char*)bottom_im2col.channel(q) + i * 8;
for (int k = 0; k < maxk; k++)
{
#if __ARM_FEATURE_DOTPROD
asm volatile(
"prfm pldl1keep, [%0, #256] \n"
"ld2 {v0.4s, v1.4s}, [%0] \n"
"st1 {v0.4s, v1.4s}, [%1], #32 \n"
: "=r"(img0), // %0
"=r"(tmpptr) // %1
: "0"(img0),
"1"(tmpptr)
: "memory", "v0", "v1");
#else
asm volatile(
"prfm pldl1keep, [%0, #256] \n"
"ld1 {v0.16b, v1.16b}, [%0] \n"
"st1 {v0.16b, v1.16b}, [%1], #32 \n"
: "=r"(img0), // %0
"=r"(tmpptr) // %1
: "0"(img0),
"1"(tmpptr)
: "memory", "v0", "v1");
#endif // __ARM_FEATURE_DOTPROD
img0 += size * 8;
}
}
}
remain_size_start += nn_size << 2;
nn_size = (size - remain_size_start) >> 1;
#else
int remain_size_start = 0;
int nn_size = (size - remain_size_start) >> 1;
#endif
#pragma omp parallel for num_threads(opt.num_threads)
for (int ii = 0; ii < nn_size; ii++)
{
int i = remain_size_start + ii * 2;
#if __aarch64__
#if __ARM_FEATURE_DOTPROD
signed char* tmpptr = tmp.channel(i / 16 + (i % 16) / 8 + (i % 8) / 4 + (i % 4) / 2);
#else
signed char* tmpptr = tmp.channel(i / 4 + (i % 4) / 2);
#endif
#else
signed char* tmpptr = tmp.channel(i / 2);
#endif
for (int q = 0; q < inch; q++)
{
const signed char* img0 = (const signed char*)bottom_im2col.channel(q) + i * 8;
for (int k = 0; k < maxk; k++)
{
#if __aarch64__
#if __ARM_FEATURE_DOTPROD
asm volatile(
"prfm pldl1keep, [%0, #128] \n"
"ld2 {v0.2s, v1.2s}, [%0] \n"
"st1 {v0.2s, v1.2s}, [%1], #16 \n"
: "=r"(img0), // %0
"=r"(tmpptr) // %1
: "0"(img0),
"1"(tmpptr)
: "memory", "v0", "v1");
#else
asm volatile(
"prfm pldl1keep, [%0, #128] \n"
"ld1 {v0.16b}, [%0] \n"
"st1 {v0.16b}, [%1], #16 \n"
: "=r"(img0), // %0
"=r"(tmpptr) // %1
: "0"(img0),
"1"(tmpptr)
: "memory", "v0");
#endif // __ARM_FEATURE_DOTPROD
#else
asm volatile(
"pld [%0, #128] \n"
"vld1.s8 {d0-d1}, [%0 :64] \n"
"vst1.s8 {d0-d1}, [%1 :64]! \n"
: "=r"(img0), // %0
"=r"(tmpptr) // %1
: "0"(img0),
"1"(tmpptr)
: "memory", "q0");
#endif
img0 += size * 8;
}
}
}
remain_size_start += nn_size << 1;
#pragma omp parallel for num_threads(opt.num_threads)
for (int i = remain_size_start; i < size; i++)
{
#if __aarch64__
#if __ARM_FEATURE_DOTPROD
signed char* tmpptr = tmp.channel(i / 16 + (i % 16) / 8 + (i % 8) / 4 + (i % 4) / 2 + i % 2);
#else
signed char* tmpptr = tmp.channel(i / 4 + (i % 4) / 2 + i % 2);
#endif
#else
signed char* tmpptr = tmp.channel(i / 2 + i % 2);
#endif
for (int q = 0; q < inch; q++)
{
const signed char* img0 = (const signed char*)bottom_im2col.channel(q) + i * 8;
for (int k = 0; k < maxk; k++)
{
#if __aarch64__
asm volatile(
"prfm pldl1keep, [%0, #64] \n"
"ld1 {v0.8b}, [%0] \n"
"st1 {v0.8b}, [%1], #8 \n"
: "=r"(img0), // %0
"=r"(tmpptr) // %1
: "0"(img0),
"1"(tmpptr)
: "memory", "v0");
#else
asm volatile(
"pld [%0, #64] \n"
"vld1.s8 {d0}, [%0 :64] \n"
"vst1.s8 {d0}, [%1 :64]! \n"
: "=r"(img0), // %0
"=r"(tmpptr) // %1
: "0"(img0),
"1"(tmpptr)
: "memory", "d0");
#endif
img0 += size * 8;
}
}
}
}
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < outch; p++)
{
int* outptr0 = top_blob.channel(p);
int i = 0;
#if __aarch64__
#if __ARM_FEATURE_DOTPROD
for (; i + 15 < size; i += 16)
{
const signed char* tmpptr = tmp.channel(i / 16);
const signed char* kptr0 = kernel.channel(p);
int nn = inch * maxk; // inch always > 0
asm volatile(
"ld1 {v24.16b}, [%3], #16 \n" // _w0123_l
"eor v0.16b, v0.16b, v0.16b \n"
"eor v1.16b, v1.16b, v1.16b \n"
"ld1 {v16.16b}, [%2], #16 \n" // _val0123_l
"eor v2.16b, v2.16b, v2.16b \n"
"eor v3.16b, v3.16b, v3.16b \n"
"eor v4.16b, v4.16b, v4.16b \n"
"eor v5.16b, v5.16b, v5.16b \n"
"eor v6.16b, v6.16b, v6.16b \n"
"eor v7.16b, v7.16b, v7.16b \n"
"eor v8.16b, v8.16b, v8.16b \n"
"eor v9.16b, v9.16b, v9.16b \n"
"eor v10.16b, v10.16b, v10.16b \n"
"eor v11.16b, v11.16b, v11.16b \n"
"eor v12.16b, v12.16b, v12.16b \n"
"eor v13.16b, v13.16b, v13.16b \n"
"eor v14.16b, v14.16b, v14.16b \n"
"eor v15.16b, v15.16b, v15.16b \n"
"0: \n"
"ld1 {v17.16b}, [%2], #16 \n" // _val4567_l
"sdot v0.4s, v24.16b, v16.4b[0] \n"
"sdot v1.4s, v24.16b, v16.4b[1] \n"
"sdot v2.4s, v24.16b, v16.4b[2] \n"
"sdot v3.4s, v24.16b, v16.4b[3] \n"
"ld1 {v18.16b}, [%2], #16 \n" // _val891011_l
"sdot v4.4s, v24.16b, v17.4b[0] \n"
"sdot v5.4s, v24.16b, v17.4b[1] \n"
"sdot v6.4s, v24.16b, v17.4b[2] \n"
"sdot v7.4s, v24.16b, v17.4b[3] \n"
"ld1 {v19.16b}, [%2], #16 \n" // _val12131415_l
"sdot v8.4s, v24.16b, v18.4b[0] \n"
"sdot v9.4s, v24.16b, v18.4b[1] \n"
"ld1 {v25.16b}, [%3], #16 \n" // _w0123_h
"sdot v10.4s, v24.16b, v18.4b[2] \n"
"sdot v11.4s, v24.16b, v18.4b[3] \n"
"ld1 {v20.16b}, [%2], #16 \n" // _val0123_h
"sdot v12.4s, v24.16b, v19.4b[0] \n"
"sdot v13.4s, v24.16b, v19.4b[1] \n"
"sdot v14.4s, v24.16b, v19.4b[2] \n"
"sdot v15.4s, v24.16b, v19.4b[3] \n"
"ld1 {v21.16b}, [%2], #16 \n" // _val4567_h
"sdot v0.4s, v25.16b, v20.4b[0] \n"
"sdot v1.4s, v25.16b, v20.4b[1] \n"
"sdot v2.4s, v25.16b, v20.4b[2] \n"
"sdot v3.4s, v25.16b, v20.4b[3] \n"
"ld1 {v22.16b}, [%2], #16 \n" // _val891011_h
"sdot v4.4s, v25.16b, v21.4b[0] \n"
"sdot v5.4s, v25.16b, v21.4b[1] \n"
"sdot v6.4s, v25.16b, v21.4b[2] \n"
"sdot v7.4s, v25.16b, v21.4b[3] \n"
"ld1 {v23.16b}, [%2], #16 \n" // _val12131415_h
"sdot v8.4s, v25.16b, v22.4b[0] \n"
"sdot v9.4s, v25.16b, v22.4b[1] \n"
"ld1 {v24.16b}, [%3], #16 \n" // _w0123_l
"sdot v10.4s, v25.16b, v22.4b[2] \n"
"sdot v11.4s, v25.16b, v22.4b[3] \n"
"ld1 {v16.16b}, [%2], #16 \n" // _val0123_l
"sdot v12.4s, v25.16b, v23.4b[0] \n"
"sdot v13.4s, v25.16b, v23.4b[1] \n"
"subs %w1, %w1, #1 \n"
"sdot v14.4s, v25.16b, v23.4b[2] \n"
"sdot v15.4s, v25.16b, v23.4b[3] \n"
"bne 0b \n"
"sub %2, %2, #16 \n"
"sub %3, %3, #16 \n"
"st1 {v0.4s, v1.4s, v2.4s, v3.4s}, [%0], #64 \n"
"st1 {v4.4s, v5.4s, v6.4s, v7.4s}, [%0], #64 \n"
"st1 {v8.4s, v9.4s, v10.4s, v11.4s}, [%0], #64 \n"
"st1 {v12.4s, v13.4s, v14.4s, v15.4s}, [%0], #64 \n"
: "=r"(outptr0),
"=r"(nn),
"=r"(tmpptr),
"=r"(kptr0)
: "0"(outptr0),
"1"(nn),
"2"(tmpptr),
"3"(kptr0)
: "memory", "x4", "x5", "v0", "v1", "v2", "v3", "v4", "v5", "v6", "v7", "v8", "v9", "v10", "v11", "v12", "v13", "v14", "v15", "v16", "v17", "v18", "v19", "v20", "v21", "v22", "v23", "v24", "v25", "v26", "v27", "v28", "v29", "v30", "v31");
}
for (; i + 7 < size; i += 8)
{
const signed char* tmpptr = tmp.channel(i / 16 + (i % 16) / 8);
const signed char* kptr0 = kernel.channel(p);
int nn = inch * maxk; // inch always > 0
int32x4_t _sum0 = vdupq_n_s32(0);
int32x4_t _sum1 = vdupq_n_s32(0);
int32x4_t _sum2 = vdupq_n_s32(0);
int32x4_t _sum3 = vdupq_n_s32(0);
int32x4_t _sum4 = vdupq_n_s32(0);
int32x4_t _sum5 = vdupq_n_s32(0);
int32x4_t _sum6 = vdupq_n_s32(0);
int32x4_t _sum7 = vdupq_n_s32(0);
for (int j = 0; j < nn; j++)
{
int8x16_t _val0123_l = vld1q_s8(tmpptr);
int8x16_t _val4567_l = vld1q_s8(tmpptr + 16);
int8x16_t _w0123_l = vld1q_s8(kptr0);
_sum0 = vdotq_laneq_s32(_sum0, _w0123_l, _val0123_l, 0);
_sum1 = vdotq_laneq_s32(_sum1, _w0123_l, _val0123_l, 1);
_sum2 = vdotq_laneq_s32(_sum2, _w0123_l, _val0123_l, 2);
_sum3 = vdotq_laneq_s32(_sum3, _w0123_l, _val0123_l, 3);
_sum4 = vdotq_laneq_s32(_sum4, _w0123_l, _val4567_l, 0);
_sum5 = vdotq_laneq_s32(_sum5, _w0123_l, _val4567_l, 1);
_sum6 = vdotq_laneq_s32(_sum6, _w0123_l, _val4567_l, 2);
_sum7 = vdotq_laneq_s32(_sum7, _w0123_l, _val4567_l, 3);
int8x16_t _val0123_h = vld1q_s8(tmpptr + 32);
int8x16_t _val4567_h = vld1q_s8(tmpptr + 48);
int8x16_t _w0123_h = vld1q_s8(kptr0 + 16);
_sum0 = vdotq_laneq_s32(_sum0, _w0123_h, _val0123_h, 0);
_sum1 = vdotq_laneq_s32(_sum1, _w0123_h, _val0123_h, 1);
_sum2 = vdotq_laneq_s32(_sum2, _w0123_h, _val0123_h, 2);
_sum3 = vdotq_laneq_s32(_sum3, _w0123_h, _val0123_h, 3);
_sum4 = vdotq_laneq_s32(_sum4, _w0123_h, _val4567_h, 0);
_sum5 = vdotq_laneq_s32(_sum5, _w0123_h, _val4567_h, 1);
_sum6 = vdotq_laneq_s32(_sum6, _w0123_h, _val4567_h, 2);
_sum7 = vdotq_laneq_s32(_sum7, _w0123_h, _val4567_h, 3);
tmpptr += 64;
kptr0 += 32;
}
vst1q_s32(outptr0, _sum0);
vst1q_s32(outptr0 + 4, _sum1);
vst1q_s32(outptr0 + 8, _sum2);
vst1q_s32(outptr0 + 12, _sum3);
vst1q_s32(outptr0 + 16, _sum4);
vst1q_s32(outptr0 + 20, _sum5);
vst1q_s32(outptr0 + 24, _sum6);
vst1q_s32(outptr0 + 28, _sum7);
outptr0 += 32;
}
#endif
for (; i + 3 < size; i += 4)
{
#if __ARM_FEATURE_DOTPROD
const signed char* tmpptr = tmp.channel(i / 16 + (i % 16) / 8 + (i % 8) / 4);
#else
const signed char* tmpptr = tmp.channel(i / 4);
#endif
const signed char* kptr0 = kernel.channel(p);
int nn = inch * maxk; // inch always > 0
#if __ARM_FEATURE_DOTPROD
int32x4_t _sum0 = vdupq_n_s32(0);
int32x4_t _sum1 = vdupq_n_s32(0);
int32x4_t _sum2 = vdupq_n_s32(0);
int32x4_t _sum3 = vdupq_n_s32(0);
for (int j = 0; j < nn; j++)
{
int8x16_t _val0123_l = vld1q_s8(tmpptr);
int8x16_t _w0123_l = vld1q_s8(kptr0);
_sum0 = vdotq_laneq_s32(_sum0, _w0123_l, _val0123_l, 0);
_sum1 = vdotq_laneq_s32(_sum1, _w0123_l, _val0123_l, 1);
_sum2 = vdotq_laneq_s32(_sum2, _w0123_l, _val0123_l, 2);
_sum3 = vdotq_laneq_s32(_sum3, _w0123_l, _val0123_l, 3);
int8x16_t _val0123_h = vld1q_s8(tmpptr + 16);
int8x16_t _w0123_h = vld1q_s8(kptr0 + 16);
_sum0 = vdotq_laneq_s32(_sum0, _w0123_h, _val0123_h, 0);
_sum1 = vdotq_laneq_s32(_sum1, _w0123_h, _val0123_h, 1);
_sum2 = vdotq_laneq_s32(_sum2, _w0123_h, _val0123_h, 2);
_sum3 = vdotq_laneq_s32(_sum3, _w0123_h, _val0123_h, 3);
tmpptr += 32;
kptr0 += 32;
}
vst1q_s32(outptr0, _sum0);
vst1q_s32(outptr0 + 4, _sum1);
vst1q_s32(outptr0 + 8, _sum2);
vst1q_s32(outptr0 + 12, _sum3);
outptr0 += 16;
#else // __ARM_FEATURE_DOTPROD
asm volatile(
"eor v0.16b, v0.16b, v0.16b \n"
"eor v1.16b, v1.16b, v1.16b \n"
"eor v2.16b, v2.16b, v2.16b \n"
"eor v3.16b, v3.16b, v3.16b \n"
"eor v4.16b, v4.16b, v4.16b \n"
"eor v5.16b, v5.16b, v5.16b \n"
"eor v6.16b, v6.16b, v6.16b \n"
"eor v7.16b, v7.16b, v7.16b \n"
"eor v8.16b, v8.16b, v8.16b \n"
"eor v9.16b, v9.16b, v9.16b \n"
"eor v10.16b, v10.16b, v10.16b \n"
"eor v11.16b, v11.16b, v11.16b \n"
"eor v12.16b, v12.16b, v12.16b \n"
"eor v13.16b, v13.16b, v13.16b \n"
"eor v14.16b, v14.16b, v14.16b \n"
"eor v15.16b, v15.16b, v15.16b \n"
"prfm pldl1keep, [%2, #128] \n"
"prfm pldl1keep, [%3, #256] \n"
"lsr w4, %w1, #1 \n" // w4 = nn >> 1
"cmp w4, #0 \n"
"beq 1f \n"
"prfm pldl1keep, [%3, #512] \n"
"add x5, %2, #16 \n"
"prfm pldl1keep, [x5, #128] \n"
"ld1 {v16.16b}, [%2] \n" // val L H
"ld1 {v20.16b, v21.16b, v22.16b, v23.16b}, [%3], #64 \n"
"add %2, %2, #32 \n"
"ext v17.16b, v16.16b, v16.16b, #8 \n" // val H L
"ld1 {v18.16b}, [%2] \n"
"add %2, %2, #32 \n"
"0: \n"
"smull v24.8h, v16.8b, v20.8b \n"
"prfm pldl1keep, [%3, #256] \n"
"smull2 v25.8h, v17.16b, v20.16b \n"
"prfm pldl1keep, [%3, #512] \n"
"smull v26.8h, v16.8b, v21.8b \n"
"subs w4, w4, #1 \n"
"smull2 v27.8h, v17.16b, v21.16b \n"
"ext v19.16b, v18.16b, v18.16b, #8 \n" // val H L
"smlal v24.8h, v18.8b, v22.8b \n"
"smlal2 v25.8h, v19.16b, v22.16b \n"
"smlal v26.8h, v18.8b, v23.8b \n"
"smlal2 v27.8h, v19.16b, v23.16b \n"
"smull2 v29.8h, v16.16b, v20.16b \n"
"sadalp v0.4s, v24.8h \n"
"smull v28.8h, v17.8b, v20.8b \n"
"sadalp v1.4s, v25.8h \n"
"smull2 v31.8h, v16.16b, v21.16b \n"
"ld1 {v16.16b}, [x5] \n" // val L H
"smull v30.8h, v17.8b, v21.8b \n"
"add x5, x5, #32 \n"
"smlal2 v29.8h, v18.16b, v22.16b \n"
"sadalp v2.4s, v26.8h \n"
"smlal v28.8h, v19.8b, v22.8b \n"
"sadalp v3.4s, v27.8h \n"
"smlal2 v31.8h, v18.16b, v23.16b \n"
"ld1 {v18.16b}, [x5] \n"
"smlal v30.8h, v19.8b, v23.8b \n"
"ext v17.16b, v16.16b, v16.16b, #8 \n" // val H L
"smull v24.8h, v16.8b, v20.8b \n"
"add x5, x5, #32 \n"
"smull2 v25.8h, v17.16b, v20.16b \n"
"prfm pldl1keep, [x5, #128] \n"
"smull v26.8h, v16.8b, v21.8b \n"
"prfm pldl1keep, [x5, #384] \n"
"smull2 v27.8h, v17.16b, v21.16b \n"
"ext v19.16b, v18.16b, v18.16b, #8 \n" // val H L
"smlal v24.8h, v18.8b, v22.8b \n"
"sadalp v5.4s, v29.8h \n"
"smlal2 v25.8h, v19.16b, v22.16b \n"
"sadalp v4.4s, v28.8h \n"
"smlal v26.8h, v18.8b, v23.8b \n"
"sadalp v7.4s, v31.8h \n"
"smlal2 v27.8h, v19.16b, v23.16b \n"
"sadalp v6.4s, v30.8h \n"
"smull2 v29.8h, v16.16b, v20.16b \n"
"sadalp v8.4s, v24.8h \n"
"smull v28.8h, v17.8b, v20.8b \n"
"sadalp v9.4s, v25.8h \n"
"smull2 v31.8h, v16.16b, v21.16b \n"
"ld1 {v16.16b}, [%2] \n" // val L H
"smull v30.8h, v17.8b, v21.8b \n"
"add %2, %2, #32 \n"
"smlal2 v29.8h, v18.16b, v22.16b \n"
"sadalp v10.4s, v26.8h \n"
"smlal v28.8h, v19.8b, v22.8b \n"
"sadalp v11.4s, v27.8h \n"
"smlal2 v31.8h, v18.16b, v23.16b \n"
"ld1 {v18.16b}, [%2] \n"
"smlal v30.8h, v19.8b, v23.8b \n"
"add %2, %2, #32 \n"
"ld1 {v20.16b, v21.16b, v22.16b, v23.16b}, [%3], #64 \n"
"sadalp v13.4s, v29.8h \n"
"prfm pldl1keep, [%2, #128] \n"
"sadalp v12.4s, v28.8h \n"
"prfm pldl1keep, [%2, #384] \n"
"sadalp v15.4s, v31.8h \n"
"ext v17.16b, v16.16b, v16.16b, #8 \n" // val H L
"sadalp v14.4s, v30.8h \n"
"bne 0b \n"
"sub %2, %2, #64 \n"
"sub %3, %3, #64 \n"
"1: \n"
"and w4, %w1, #1 \n" // w4 = remain = nn & 1
"cmp w4, #0 \n" // w4 > 0
"beq 2f \n"
"ld1 {v16.8b, v17.8b}, [%2], #16 \n"
"ld1 {v20.8b, v21.8b, v22.8b, v23.8b}, [%3], #32 \n"
"smull v24.8h, v16.8b, v20.8b \n"
"smull v25.8h, v16.8b, v21.8b \n"
"smull v26.8h, v16.8b, v22.8b \n"
"ld1 {v18.8b, v19.8b}, [%2], #16 \n"
"smull v27.8h, v16.8b, v23.8b \n"
"sadalp v0.4s, v24.8h \n"
"smull v28.8h, v17.8b, v20.8b \n"
"sadalp v1.4s, v25.8h \n"
"smull v29.8h, v17.8b, v21.8b \n"
"sadalp v2.4s, v26.8h \n"
"smull v30.8h, v17.8b, v22.8b \n"
"sadalp v3.4s, v27.8h \n"
"smull v31.8h, v17.8b, v23.8b \n"
"sadalp v4.4s, v28.8h \n"
"smull v24.8h, v18.8b, v20.8b \n"
"sadalp v5.4s, v29.8h \n"
"smull v25.8h, v18.8b, v21.8b \n"
"sadalp v6.4s, v30.8h \n"
"smull v26.8h, v18.8b, v22.8b \n"
"sadalp v7.4s, v31.8h \n"
"smull v27.8h, v18.8b, v23.8b \n"
"sadalp v8.4s, v24.8h \n"
"smull v28.8h, v19.8b, v20.8b \n"
"sadalp v9.4s, v25.8h \n"
"smull v29.8h, v19.8b, v21.8b \n"
"sadalp v10.4s, v26.8h \n"
"smull v30.8h, v19.8b, v22.8b \n"
"sadalp v11.4s, v27.8h \n"
"smull v31.8h, v19.8b, v23.8b \n"
"sadalp v12.4s, v28.8h \n"
"sadalp v13.4s, v29.8h \n"
"sadalp v14.4s, v30.8h \n"
"sadalp v15.4s, v31.8h \n"
"2: \n"
"addp v0.4s, v0.4s, v1.4s \n"
"addp v2.4s, v2.4s, v3.4s \n"
"addp v4.4s, v4.4s, v5.4s \n"
"addp v6.4s, v6.4s, v7.4s \n"
"addp v8.4s, v8.4s, v9.4s \n"
"addp v10.4s, v10.4s, v11.4s \n"
"addp v12.4s, v12.4s, v13.4s \n"
"addp v14.4s, v14.4s, v15.4s \n"
"addp v0.4s, v0.4s, v2.4s \n"
"addp v1.4s, v4.4s, v6.4s \n"
"addp v2.4s, v8.4s, v10.4s \n"
"addp v3.4s, v12.4s, v14.4s \n"
"st1 {v0.4s, v1.4s, v2.4s, v3.4s}, [%0], #64 \n"
: "=r"(outptr0),
"=r"(nn),
"=r"(tmpptr),
"=r"(kptr0)
: "0"(outptr0),
"1"(nn),
"2"(tmpptr),
"3"(kptr0)
: "memory", "x4", "x5", "v0", "v1", "v2", "v3", "v4", "v5", "v6", "v7", "v8", "v9", "v10", "v11", "v12", "v13", "v14", "v15", "v16", "v17", "v18", "v19", "v20", "v21", "v22", "v23", "v24", "v25", "v26", "v27", "v28", "v29", "v30", "v31");
#endif // __ARM_FEATURE_DOTPROD
}
#endif // __aarch64__
for (; i + 1 < size; i += 2)
{
#if __aarch64__
#if __ARM_FEATURE_DOTPROD
const signed char* tmpptr = tmp.channel(i / 16 + (i % 16) / 8 + (i % 8) / 4 + (i % 4) / 2);
#else
const signed char* tmpptr = tmp.channel(i / 4 + (i % 4) / 2);
#endif
#else
const signed char* tmpptr = tmp.channel(i / 2);
#endif
const signed char* kptr0 = kernel.channel(p);
int nn = inch * maxk; // inch always > 0
#if __aarch64__
#if __ARM_FEATURE_DOTPROD
int32x4_t _sum0 = vdupq_n_s32(0);
int32x4_t _sum1 = vdupq_n_s32(0);
for (int j = 0; j < nn; j++)
{
int8x16_t _val01_l_h = vld1q_s8(tmpptr);
int8x16_t _w0123_l = vld1q_s8(kptr0);
_sum0 = vdotq_laneq_s32(_sum0, _w0123_l, _val01_l_h, 0);
_sum1 = vdotq_laneq_s32(_sum1, _w0123_l, _val01_l_h, 1);
int8x16_t _w0123_h = vld1q_s8(kptr0 + 16);
_sum0 = vdotq_laneq_s32(_sum0, _w0123_h, _val01_l_h, 2);
_sum1 = vdotq_laneq_s32(_sum1, _w0123_h, _val01_l_h, 3);
tmpptr += 16;
kptr0 += 32;
}
vst1q_s32(outptr0, _sum0);
vst1q_s32(outptr0 + 4, _sum1);
outptr0 += 8;
#else // __ARM_FEATURE_DOTPROD
int32x4_t _sum00 = vdupq_n_s32(0);
int32x4_t _sum01 = vdupq_n_s32(0);
int32x4_t _sum02 = vdupq_n_s32(0);
int32x4_t _sum03 = vdupq_n_s32(0);
int32x4_t _sum10 = vdupq_n_s32(0);
int32x4_t _sum11 = vdupq_n_s32(0);
int32x4_t _sum12 = vdupq_n_s32(0);
int32x4_t _sum13 = vdupq_n_s32(0);
int j = 0;
for (; j + 1 < nn; j += 2)
{
int8x16_t _val0 = vld1q_s8(tmpptr);
int8x16_t _val1 = vld1q_s8(tmpptr + 16);
int8x16_t _w01 = vld1q_s8(kptr0);
int8x16_t _w23 = vld1q_s8(kptr0 + 16);
int16x8_t _wv00 = vmull_s8(vget_low_s8(_val0), vget_low_s8(_w01));
int16x8_t _wv01 = vmull_s8(vget_low_s8(_val0), vget_high_s8(_w01));
int16x8_t _wv02 = vmull_s8(vget_low_s8(_val0), vget_low_s8(_w23));
int16x8_t _wv03 = vmull_s8(vget_low_s8(_val0), vget_high_s8(_w23));
int16x8_t _wv10 = vmull_s8(vget_high_s8(_val0), vget_low_s8(_w01));
int16x8_t _wv11 = vmull_s8(vget_high_s8(_val0), vget_high_s8(_w01));
int16x8_t _wv12 = vmull_s8(vget_high_s8(_val0), vget_low_s8(_w23));
int16x8_t _wv13 = vmull_s8(vget_high_s8(_val0), vget_high_s8(_w23));
int8x16_t _w45 = vld1q_s8(kptr0 + 32);
int8x16_t _w67 = vld1q_s8(kptr0 + 48);
_wv00 = vmlal_s8(_wv00, vget_low_s8(_val1), vget_low_s8(_w45));
_wv01 = vmlal_s8(_wv01, vget_low_s8(_val1), vget_high_s8(_w45));
_wv02 = vmlal_s8(_wv02, vget_low_s8(_val1), vget_low_s8(_w67));
_wv03 = vmlal_s8(_wv03, vget_low_s8(_val1), vget_high_s8(_w67));
_wv10 = vmlal_s8(_wv10, vget_high_s8(_val1), vget_low_s8(_w45));
_wv11 = vmlal_s8(_wv11, vget_high_s8(_val1), vget_high_s8(_w45));
_wv12 = vmlal_s8(_wv12, vget_high_s8(_val1), vget_low_s8(_w67));
_wv13 = vmlal_s8(_wv13, vget_high_s8(_val1), vget_high_s8(_w67));
_sum00 = vpadalq_s16(_sum00, _wv00);
_sum01 = vpadalq_s16(_sum01, _wv01);
_sum02 = vpadalq_s16(_sum02, _wv02);
_sum03 = vpadalq_s16(_sum03, _wv03);
_sum10 = vpadalq_s16(_sum10, _wv10);
_sum11 = vpadalq_s16(_sum11, _wv11);
_sum12 = vpadalq_s16(_sum12, _wv12);
_sum13 = vpadalq_s16(_sum13, _wv13);
tmpptr += 32;
kptr0 += 64;
}
for (; j < nn; j++)
{
int8x16_t _val = vld1q_s8(tmpptr);
int8x16_t _w01 = vld1q_s8(kptr0);
int8x16_t _w23 = vld1q_s8(kptr0 + 16);
int16x8_t _wv00 = vmull_s8(vget_low_s8(_val), vget_low_s8(_w01));
int16x8_t _wv01 = vmull_s8(vget_low_s8(_val), vget_high_s8(_w01));
int16x8_t _wv02 = vmull_s8(vget_low_s8(_val), vget_low_s8(_w23));
int16x8_t _wv03 = vmull_s8(vget_low_s8(_val), vget_high_s8(_w23));
int16x8_t _wv10 = vmull_s8(vget_high_s8(_val), vget_low_s8(_w01));
int16x8_t _wv11 = vmull_s8(vget_high_s8(_val), vget_high_s8(_w01));
int16x8_t _wv12 = vmull_s8(vget_high_s8(_val), vget_low_s8(_w23));
int16x8_t _wv13 = vmull_s8(vget_high_s8(_val), vget_high_s8(_w23));
_sum00 = vpadalq_s16(_sum00, _wv00);
_sum01 = vpadalq_s16(_sum01, _wv01);
_sum02 = vpadalq_s16(_sum02, _wv02);
_sum03 = vpadalq_s16(_sum03, _wv03);
_sum10 = vpadalq_s16(_sum10, _wv10);
_sum11 = vpadalq_s16(_sum11, _wv11);
_sum12 = vpadalq_s16(_sum12, _wv12);
_sum13 = vpadalq_s16(_sum13, _wv13);
tmpptr += 16;
kptr0 += 32;
}
int32x4_t _s001 = vpaddq_s32(_sum00, _sum01);
int32x4_t _s023 = vpaddq_s32(_sum02, _sum03);
int32x4_t _s101 = vpaddq_s32(_sum10, _sum11);
int32x4_t _s123 = vpaddq_s32(_sum12, _sum13);
int32x4_t _s00123 = vpaddq_s32(_s001, _s023);
int32x4_t _s10123 = vpaddq_s32(_s101, _s123);
vst1q_s32(outptr0, _s00123);
vst1q_s32(outptr0 + 4, _s10123);
outptr0 += 8;
#endif // __ARM_FEATURE_DOTPROD
#else // __aarch64__
asm volatile(
"veor q0, q0 \n"
"veor q1, q1 \n"
"veor q2, q2 \n"
"veor q3, q3 \n"
"veor q4, q4 \n"
"veor q5, q5 \n"
"veor q6, q6 \n"
"veor q7, q7 \n"
"pld [%2, #256] \n"
"lsr r4, %1, #1 \n" // r4 = nn = size >> 1
"cmp r4, #0 \n"
"beq 1f \n"
"add r5, %3, #16 \n"
"pld [%3, #128] \n"
"mov r6, #32 \n"
"pld [%3, #384] \n"
"vld1.s8 {d20-d21}, [%3 :128], r6 \n" // _w01
"vld1.s8 {d16-d19}, [%2 :128]! \n" // _val0 _val1
"vld1.s8 {d22-d23}, [%3 :128], r6 \n" // _w45
"0: \n"
"vmull.s8 q12, d16, d20 \n"
"pld [%2, #256] \n"
"vmull.s8 q13, d16, d21 \n"
"pld [%3, #384] \n"
"vmull.s8 q14, d17, d20 \n"
"vmull.s8 q15, d17, d21 \n"
"vld1.s8 {d20-d21}, [r5 :128], r6 \n" // _w23
"vmlal.s8 q12, d18, d22 \n"
"vmlal.s8 q13, d18, d23 \n"
"subs r4, r4, #1 \n"
"vmlal.s8 q14, d19, d22 \n"
"vmlal.s8 q15, d19, d23 \n"
"vld1.s8 {d22-d23}, [r5 :128], r6 \n" // _w67
"vpadal.s16 q0, q12 \n"
"vmull.s8 q12, d16, d20 \n"
"vpadal.s16 q1, q13 \n"
"vmull.s8 q13, d16, d21 \n"
"vpadal.s16 q4, q14 \n"
"vmull.s8 q14, d17, d20 \n"
"vpadal.s16 q5, q15 \n"
"vmull.s8 q15, d17, d21 \n"
"vld1.s8 {d16-d17}, [%2 :128]! \n" // _val0
"vmlal.s8 q12, d18, d22 \n"
"vld1.s8 {d20-d21}, [%3 :128], r6 \n" // _w01
"vmlal.s8 q13, d18, d23 \n"
"pld [r5, #128] \n"
"vmlal.s8 q14, d19, d22 \n"
"pld [r5, #384] \n"
"vmlal.s8 q15, d19, d23 \n"
"vld1.s8 {d18-d19}, [%2 :128]! \n" // _val1
"vpadal.s16 q2, q12 \n"
"vld1.s8 {d22-d23}, [%3 :128], r6 \n" // _w45
"vpadal.s16 q3, q13 \n"
"pld [%2, #128] \n"
"vpadal.s16 q6, q14 \n"
"pld [%3, #128] \n"
"vpadal.s16 q7, q15 \n"
"bne 0b \n"
"sub %2, %2, #32 \n"
"sub %3, %3, #64 \n"
"1: \n"
"and r4, %1, #1 \n" // r4 = remain = size & 1
"cmp r4, #0 \n" // r4 > 0
"beq 2f \n"
"vld1.s8 {d16-d17}, [%2 :128]! \n" // _val
"vld1.s8 {d20-d21}, [%3 :128]! \n" // _w01
"vmull.s8 q12, d16, d20 \n"
"vld1.s8 {d22-d23}, [%3 :128]! \n" // _w23
"vmull.s8 q13, d16, d21 \n"
"vmull.s8 q14, d17, d20 \n"
"vmull.s8 q15, d17, d21 \n"
"vpadal.s16 q0, q12 \n"
"vmull.s8 q12, d16, d22 \n"
"vpadal.s16 q1, q13 \n"
"vmull.s8 q13, d16, d23 \n"
"vpadal.s16 q4, q14 \n"
"vmull.s8 q14, d17, d22 \n"
"vpadal.s16 q5, q15 \n"
"vmull.s8 q15, d17, d23 \n"
"vpadal.s16 q2, q12 \n"
"vpadal.s16 q3, q13 \n"
"vpadal.s16 q6, q14 \n"
"vpadal.s16 q7, q15 \n"
"2: \n"
"vpadd.s32 d16, d0, d1 \n"
"vpadd.s32 d17, d2, d3 \n"
"vpadd.s32 d18, d4, d5 \n"
"vpadd.s32 d19, d6, d7 \n"
"vpadd.s32 d20, d8, d9 \n"
"vpadd.s32 d21, d10, d11 \n"
"vpadd.s32 d22, d12, d13 \n"
"vpadd.s32 d23, d14, d15 \n"
"vpadd.s32 d0, d16, d17 \n"
"vpadd.s32 d1, d18, d19 \n"
"vpadd.s32 d2, d20, d21 \n"
"vpadd.s32 d3, d22, d23 \n"
"vst1.s32 {d0-d3}, [%0 :128]! \n"
: "=r"(outptr0),
"=r"(nn),
"=r"(tmpptr),
"=r"(kptr0)
: "0"(outptr0),
"1"(nn),
"2"(tmpptr),
"3"(kptr0)
: "memory", "r4", "r5", "r6", "q0", "q1", "q2", "q3", "q4", "q5", "q6", "q7", "q8", "q9", "q10", "q11", "q12", "q13", "q14", "q15");
#endif // __aarch64__
}
for (; i < size; i++)
{
#if __aarch64__
#if __ARM_FEATURE_DOTPROD
const signed char* tmpptr = tmp.channel(i / 16 + (i % 16) / 8 + (i % 8) / 4 + (i % 4) / 2 + i % 2);
#else
const signed char* tmpptr = tmp.channel(i / 4 + (i % 4) / 2 + i % 2);
#endif
#else
const signed char* tmpptr = tmp.channel(i / 2 + i % 2);
#endif
const signed char* kptr0 = kernel.channel(p);
int nn = inch * maxk; // inch always > 0
#if __ARM_FEATURE_DOTPROD
int32x4_t _sum0 = vdupq_n_s32(0);
for (int j = 0; j < nn; j++)
{
int8x8_t _val0_l_h = vld1_s8(tmpptr);
int8x16_t _w0123_l = vld1q_s8(kptr0);
_sum0 = vdotq_lane_s32(_sum0, _w0123_l, _val0_l_h, 0);
int8x16_t _w0123_h = vld1q_s8(kptr0 + 16);
_sum0 = vdotq_lane_s32(_sum0, _w0123_h, _val0_l_h, 1);
tmpptr += 8;
kptr0 += 32;
}
vst1q_s32(outptr0, _sum0);
outptr0 += 4;
#else // __ARM_FEATURE_DOTPROD
int32x4_t _sum0 = vdupq_n_s32(0);
int32x4_t _sum1 = vdupq_n_s32(0);
int32x4_t _sum2 = vdupq_n_s32(0);
int32x4_t _sum3 = vdupq_n_s32(0);
int j = 0;
for (; j + 1 < nn; j += 2)
{
int8x16_t _val = vld1q_s8(tmpptr);
int8x16_t _w01 = vld1q_s8(kptr0);
int8x16_t _w23 = vld1q_s8(kptr0 + 16);
int16x8_t _wv0 = vmull_s8(vget_low_s8(_val), vget_low_s8(_w01));
int16x8_t _wv1 = vmull_s8(vget_low_s8(_val), vget_high_s8(_w01));
int16x8_t _wv2 = vmull_s8(vget_low_s8(_val), vget_low_s8(_w23));
int16x8_t _wv3 = vmull_s8(vget_low_s8(_val), vget_high_s8(_w23));
int8x16_t _w45 = vld1q_s8(kptr0 + 32);
int8x16_t _w67 = vld1q_s8(kptr0 + 48);
_wv0 = vmlal_s8(_wv0, vget_high_s8(_val), vget_low_s8(_w45));
_wv1 = vmlal_s8(_wv1, vget_high_s8(_val), vget_high_s8(_w45));
_wv2 = vmlal_s8(_wv2, vget_high_s8(_val), vget_low_s8(_w67));
_wv3 = vmlal_s8(_wv3, vget_high_s8(_val), vget_high_s8(_w67));
_sum0 = vpadalq_s16(_sum0, _wv0);
_sum1 = vpadalq_s16(_sum1, _wv1);
_sum2 = vpadalq_s16(_sum2, _wv2);
_sum3 = vpadalq_s16(_sum3, _wv3);
tmpptr += 16;
kptr0 += 64;
}
for (; j < nn; j++)
{
int8x8_t _val = vld1_s8(tmpptr);
int8x16_t _w01 = vld1q_s8(kptr0);
int8x16_t _w23 = vld1q_s8(kptr0 + 16);
int16x8_t _wv0 = vmull_s8(_val, vget_low_s8(_w01));
int16x8_t _wv1 = vmull_s8(_val, vget_high_s8(_w01));
int16x8_t _wv2 = vmull_s8(_val, vget_low_s8(_w23));
int16x8_t _wv3 = vmull_s8(_val, vget_high_s8(_w23));
_sum0 = vpadalq_s16(_sum0, _wv0);
_sum1 = vpadalq_s16(_sum1, _wv1);
_sum2 = vpadalq_s16(_sum2, _wv2);
_sum3 = vpadalq_s16(_sum3, _wv3);
tmpptr += 8;
kptr0 += 32;
}
#if __aarch64__
int32x4_t _s01 = vpaddq_s32(_sum0, _sum1);
int32x4_t _s23 = vpaddq_s32(_sum2, _sum3);
int32x4_t _s0123 = vpaddq_s32(_s01, _s23);
#else
int32x2_t _s01_low = vpadd_s32(vget_low_s32(_sum0), vget_high_s32(_sum0));
int32x2_t _s01_high = vpadd_s32(vget_low_s32(_sum1), vget_high_s32(_sum1));
int32x2_t _s23_low = vpadd_s32(vget_low_s32(_sum2), vget_high_s32(_sum2));
int32x2_t _s23_high = vpadd_s32(vget_low_s32(_sum3), vget_high_s32(_sum3));
int32x4_t _s0123 = vcombine_s32(vpadd_s32(_s01_low, _s01_high), vpadd_s32(_s23_low, _s23_high));
#endif
vst1q_s32(outptr0, _s0123);
outptr0 += 4;
#endif // __ARM_FEATURE_DOTPROD
}
}
}
static void convolution_im2col_sgemm_transform_kernel_pack8to4_int8_neon(const Mat& _kernel, Mat& kernel_tm, int inch, int outch, int kernel_w, int kernel_h)
{
const int maxk = kernel_w * kernel_h;
// interleave
// src = maxk-inch-outch
// dst = 8a-4b-maxk-inch/8a-outch/4b
// dst = 4a-4b-2-maxk-inch/8a-outch/4b (arm82)
Mat kernel = _kernel.reshape(maxk, inch, outch);
kernel_tm.create(32 * maxk, inch / 8, outch / 4, 1u);
for (int q = 0; q + 3 < outch; q += 4)
{
signed char* g00 = kernel_tm.channel(q / 4);
for (int p = 0; p + 7 < inch; p += 8)
{
for (int k = 0; k < maxk; k++)
{
#if __ARM_FEATURE_DOTPROD
for (int i = 0; i < 4; i++)
{
for (int j = 0; j < 4; j++)
{
const signed char* k00 = kernel.channel(q + i).row<const signed char>(p + j);
g00[0] = k00[k];
g00++;
}
}
for (int i = 0; i < 4; i++)
{
for (int j = 4; j < 8; j++)
{
const signed char* k00 = kernel.channel(q + i).row<const signed char>(p + j);
g00[0] = k00[k];
g00++;
}
}
#else
for (int i = 0; i < 4; i++)
{
for (int j = 0; j < 8; j++)
{
const signed char* k00 = kernel.channel(q + i).row<const signed char>(p + j);
g00[0] = k00[k];
g00++;
}
}
#endif
}
}
}
}
static void convolution_im2col_sgemm_pack8to4_int8_neon(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, int kernel_w, int kernel_h, int dilation_w, int dilation_h, int stride_w, int stride_h, const Option& opt)
{
int w = bottom_blob.w;
int inch = bottom_blob.c;
int outw = top_blob.w;
int outh = top_blob.h;
const int size = outw * outh;
const int maxk = kernel_w * kernel_h;
// im2col
Mat bottom_im2col(size, maxk, inch, 8u, 8, opt.workspace_allocator);
{
const int gap = (w * stride_h - outw * stride_w) * 8;
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < inch; p++)
{
const Mat img = bottom_blob.channel(p);
signed char* ptr = bottom_im2col.channel(p);
for (int u = 0; u < kernel_h; u++)
{
for (int v = 0; v < kernel_w; v++)
{
const signed char* sptr = img.row<const signed char>(dilation_h * u) + dilation_w * v * 8;
for (int i = 0; i < outh; i++)
{
int j = 0;
for (; j + 3 < outw; j += 4)
{
int8x8_t _val0 = vld1_s8(sptr);
int8x8_t _val1 = vld1_s8(sptr + stride_w * 8);
int8x8_t _val2 = vld1_s8(sptr + stride_w * 16);
int8x8_t _val3 = vld1_s8(sptr + stride_w * 24);
vst1_s8(ptr, _val0);
vst1_s8(ptr + 8, _val1);
vst1_s8(ptr + 16, _val2);
vst1_s8(ptr + 24, _val3);
sptr += stride_w * 32;
ptr += 32;
}
for (; j + 1 < outw; j += 2)
{
int8x8_t _val0 = vld1_s8(sptr);
int8x8_t _val1 = vld1_s8(sptr + stride_w * 8);
vst1_s8(ptr, _val0);
vst1_s8(ptr + 8, _val1);
sptr += stride_w * 16;
ptr += 16;
}
for (; j < outw; j++)
{
int8x8_t _val = vld1_s8(sptr);
vst1_s8(ptr, _val);
sptr += stride_w * 8;
ptr += 8;
}
sptr += gap;
}
}
}
}
}
im2col_sgemm_pack8to4_int8_neon(bottom_im2col, top_blob, kernel, opt);
}
|
GB_binop__bxnor_int16.c | //------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_emult.h"
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB (_AaddB__bxnor_int16)
// A.*B function (eWiseMult): GB (_AemultB)
// A.*B function (eWiseMult): GB (_AemultB_02__bxnor_int16)
// A.*B function (eWiseMult): GB (_AemultB_03__bxnor_int16)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__bxnor_int16)
// A*D function (colscale): GB ((none))
// D*A function (rowscale): GB ((node))
// C+=B function (dense accum): GB (_Cdense_accumB__bxnor_int16)
// C+=b function (dense accum): GB (_Cdense_accumb__bxnor_int16)
// C+=A+B function (dense ewise3): GB ((none))
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__bxnor_int16)
// C=scalar+B GB (_bind1st__bxnor_int16)
// C=scalar+B' GB (_bind1st_tran__bxnor_int16)
// C=A+scalar GB (_bind2nd__bxnor_int16)
// C=A'+scalar GB (_bind2nd_tran__bxnor_int16)
// C type: int16_t
// A type: int16_t
// B,b type: int16_t
// BinaryOp: cij = ~((aij) ^ (bij))
#define GB_ATYPE \
int16_t
#define GB_BTYPE \
int16_t
#define GB_CTYPE \
int16_t
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
1
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
1
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
int16_t aij = Ax [pA]
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB) \
int16_t bij = Bx [pB]
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
int16_t t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA) \
cij = Ax [pA]
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB) \
cij = Bx [pB]
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z, x, y, i, j) \
z = ~((x) ^ (y)) ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
0
// op is second
#define GB_OP_IS_SECOND \
0
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_BXNOR || GxB_NO_INT16 || GxB_NO_BXNOR_INT16)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
#if 0
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
#endif
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_ewise3_noaccum__bxnor_int16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_dense_ewise3_noaccum_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumB__bxnor_int16)
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *B_ek_slicing, const int B_ntasks, const int B_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
#include "GB_dense_subassign_23_template.c"
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumb__bxnor_int16)
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
// get the scalar b for C += b, of type int16_t
int16_t bwork = (*((int16_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
#if 0
GrB_Info GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A, bool A_is_pattern,
const GrB_Matrix D, bool D_is_pattern,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int16_t *restrict Cx = (int16_t *) C->x ;
#include "GB_AxB_colscale_meta.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
#if 0
GrB_Info GB ((node))
(
GrB_Matrix C,
const GrB_Matrix D, bool D_is_pattern,
const GrB_Matrix B, bool B_is_pattern,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int16_t *restrict Cx = (int16_t *) C->x ;
#include "GB_AxB_rowscale_meta.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
//------------------------------------------------------------------------------
// eWiseAdd: C = A+B or C<M> = A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__bxnor_int16)
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool Ch_is_Mh,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GB_WERK_DECLARE (M_ek_slicing, int64_t) ;
GB_WERK_DECLARE (A_ek_slicing, int64_t) ;
GB_WERK_DECLARE (B_ek_slicing, int64_t) ;
#include "GB_add_template.c"
GB_FREE_WORK ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C = A.*B or C<M> = A.*B
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_01__bxnor_int16)
(
GrB_Matrix C,
const int C_sparsity,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_01_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<#> = A.*B when A is sparse/hyper and B is bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_02__bxnor_int16)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool flipxy,
const int64_t *restrict Cp_kfirst,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if GB_BINOP_FLIP
// The operator is not commutative, and does not have a flipped
// variant. For example z=atan2(y,x).
if (flipxy)
{
// use fmult(y,x)
#undef GB_FLIPPED
#define GB_FLIPPED 1
#include "GB_emult_02_template.c"
}
else
{
// use fmult(x,y)
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
}
#else
// No need to handle the flip: the operator is either commutative, or
// has been handled by changing z=div(y,x) to z=rdiv(x,y) for example.
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<M> = A.*B, M sparse/hyper, A and B bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_03__bxnor_int16)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict Cp_kfirst,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_03_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, C<!M>=A.*B where C is bitmap
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_bitmap__bxnor_int16)
(
GrB_Matrix C,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_bitmap_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB (_bind1st__bxnor_int16)
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *restrict Bb,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int16_t *Cx = (int16_t *) Cx_output ;
int16_t x = (*((int16_t *) x_input)) ;
int16_t *Bx = (int16_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Bb, p)) continue ;
int16_t bij = Bx [p] ;
Cx [p] = ~((x) ^ (bij)) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__bxnor_int16)
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *restrict Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
int16_t *Cx = (int16_t *) Cx_output ;
int16_t *Ax = (int16_t *) Ax_input ;
int16_t y = (*((int16_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
int16_t aij = Ax [p] ;
Cx [p] = ~((aij) ^ (y)) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
int16_t aij = Ax [pA] ; \
Cx [pC] = ~((x) ^ (aij)) ; \
}
GrB_Info GB (_bind1st_tran__bxnor_int16)
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
int16_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int16_t x = (*((const int16_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
int16_t
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
int16_t aij = Ax [pA] ; \
Cx [pC] = ~((aij) ^ (y)) ; \
}
GrB_Info GB (_bind2nd_tran__bxnor_int16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int16_t y = (*((const int16_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
target_array_extension.c | // --------------------------------------------------
// Check extends before
// --------------------------------------------------
// RUN: %libomptarget-compile-generic \
// RUN: -fopenmp-version=51 -DEXTENDS=BEFORE
// RUN: %libomptarget-run-fail-generic 2>&1 \
// RUN: | %fcheck-generic
// --------------------------------------------------
// Check extends after
// --------------------------------------------------
// RUN: %libomptarget-compile-generic \
// RUN: -fopenmp-version=51 -DEXTENDS=AFTER
// RUN: %libomptarget-run-fail-generic 2>&1 \
// RUN: | %fcheck-generic
// END.
#include <stdio.h>
#define BEFORE 0
#define AFTER 1
#define SIZE 100
#if EXTENDS == BEFORE
# define SMALL_BEG (SIZE-2)
# define SMALL_END SIZE
# define LARGE_BEG 0
# define LARGE_END SIZE
#elif EXTENDS == AFTER
# define SMALL_BEG 0
# define SMALL_END 2
# define LARGE_BEG 0
# define LARGE_END SIZE
#else
# error EXTENDS undefined
#endif
#define SMALL_SIZE (SMALL_END-SMALL_BEG)
#define LARGE_SIZE (LARGE_END-LARGE_BEG)
#define SMALL SMALL_BEG:SMALL_SIZE
#define LARGE LARGE_BEG:LARGE_SIZE
int main() {
int arr[SIZE];
// CHECK: addr=0x[[#%x,SMALL_ADDR:]], size=[[#%u,SMALL_BYTES:]]
fprintf(stderr, "addr=%p, size=%ld\n", &arr[SMALL_BEG],
SMALL_SIZE * sizeof arr[0]);
// CHECK: addr=0x[[#%x,LARGE_ADDR:]], size=[[#%u,LARGE_BYTES:]]
fprintf(stderr, "addr=%p, size=%ld\n", &arr[LARGE_BEG],
LARGE_SIZE * sizeof arr[0]);
// CHECK-NOT: Libomptarget
#pragma omp target data map(alloc: arr[LARGE])
{
#pragma omp target map(present, tofrom: arr[SMALL])
;
}
// CHECK: arr is present
fprintf(stderr, "arr is present\n");
// CHECK: Libomptarget message: explicit extension not allowed: host address specified is 0x{{0*}}[[#LARGE_ADDR]] ([[#LARGE_BYTES]] bytes), but device allocation maps to host at 0x{{0*}}[[#SMALL_ADDR]] ([[#SMALL_BYTES]] bytes)
// CHECK: Libomptarget message: device mapping required by 'present' map type modifier does not exist for host address 0x{{0*}}[[#LARGE_ADDR]] ([[#LARGE_BYTES]] bytes)
// CHECK: Libomptarget error: Call to getOrAllocTgtPtr returned null pointer ('present' map type modifier).
// CHECK: Libomptarget error: Call to targetDataBegin failed, abort target.
// CHECK: Libomptarget error: Failed to process data before launching the kernel.
// CHECK: Libomptarget fatal error 1: failure of target construct while offloading is mandatory
#pragma omp target data map(alloc: arr[SMALL])
{
#pragma omp target map(present, tofrom: arr[LARGE])
;
}
// CHECK-NOT: arr is present
fprintf(stderr, "arr is present\n");
return 0;
}
|
GB_unop__log2_fc32_fc32.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_atomics.h"
#include "GB_unop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB (_unop_apply__log2_fc32_fc32)
// op(A') function: GB (_unop_tran__log2_fc32_fc32)
// C type: GxB_FC32_t
// A type: GxB_FC32_t
// cast: GxB_FC32_t cij = aij
// unaryop: cij = GB_clog2f (aij)
#define GB_ATYPE \
GxB_FC32_t
#define GB_CTYPE \
GxB_FC32_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
GxB_FC32_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = GB_clog2f (x) ;
// casting
#define GB_CAST(z, aij) \
GxB_FC32_t z = aij ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GxB_FC32_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
GxB_FC32_t z = aij ; \
Cx [pC] = GB_clog2f (z) ; \
}
// true if operator is the identity op with no typecasting
#define GB_OP_IS_IDENTITY_WITH_NO_TYPECAST \
0
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_LOG2 || GxB_NO_FC32)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_apply__log2_fc32_fc32)
(
GxB_FC32_t *Cx, // Cx and Ax may be aliased
const GxB_FC32_t *Ax,
const int8_t *restrict Ab, // A->b if A is bitmap
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
// TODO: if OP is ONE and uniform-valued matrices are exploited, then
// do this in O(1) time
if (Ab == NULL)
{
#if ( GB_OP_IS_IDENTITY_WITH_NO_TYPECAST )
GB_memcpy (Cx, Ax, anz * sizeof (GxB_FC32_t), nthreads) ;
#else
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
GxB_FC32_t aij = Ax [p] ;
GxB_FC32_t z = aij ;
Cx [p] = GB_clog2f (z) ;
}
#endif
}
else
{
// bitmap case, no transpose; A->b already memcpy'd into C->b
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!Ab [p]) continue ;
GxB_FC32_t aij = Ax [p] ;
GxB_FC32_t z = aij ;
Cx [p] = GB_clog2f (z) ;
}
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_tran__log2_fc32_fc32)
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
centr.h | #include <stdio.h>
#include <iostream>
#include <vector>
#include <chrono>
#include <random>
#include <set>
#include <algorithm>
namespace TSnap {
/////////////////////////////////////////////////
// Node centrality measures (See: http://en.wikipedia.org/wiki/Centrality)
/// Returns Degree centrality of a given node NId.
/// Degree centrality if a node is defined as its degree/(N-1), where N is the number of nodes in the network.
double GetDegreeCentr(const PUNGraph& Graph, const int& NId);
/// Returns Group Degree centrality of a given group NId.
/// Degree centrality if a node is defined as its degree/(N-1), where N is the number of nodes in the network.
//double GetGroupDegreeCentr(const PUNGraph& Graph, const PUNGraph& Group);
double GetGroupDegreeCentr(const PUNGraph& Graph, const TIntH& GroupNodes);
/// Returns Group Degree centrality of a given group NId.
/// Degree centrality if a node is defined as its degree/(N-1), where N is the number of nodes in the network.
//double GetGroupDegreeCentr(const PUNGraph& Graph, const PUNGraph& Group);
double GetGroupClosenessCentr(const PUNGraph& Graph, const TIntH& GroupNodes);
/// Returns centrality Maximum k group.
TIntH MaxCPGreedyBetter(const PUNGraph& Graph, const int k);
/// Returns centrality Maximum k group.
TIntH MaxCPGreedyBetter1(const PUNGraph& Graph, const int k);
/// Returns centrality Maximum k group.
TIntH MaxCPGreedyBetter2(const PUNGraph& Graph, const int k);
/// Returns centrality Maximum k group.
TIntH MaxCPGreedyBetter3(const PUNGraph& Graph, const int k);
/// Event importance
TIntFltH EventImportance(const PNGraph& Graph, const int k);
/// Intersect
int Intersect(TUNGraph::TNodeI Node, TIntH NNodes);
/// Intersect
int Intersect(TUNGraph::TNodeI Node, TStr NNodes);
/// Intersect
int Intersect(TUNGraph::TNodeI Node, int *NNodes, int NNodes_br);
//Load nodes list
int Intersect1(TUNGraph::TNodeI Node, TStr NNodes);
//Load nodes list
TIntH LoadNodeList(TStr InFNmNodes);
/// Returns Farness centrality of a given node NId.
/// Farness centrality of a node is the average shortest path length to all other nodes that reside is the same connected component as the given node.
template <class PGraph> double GetFarnessCentr(const PGraph& Graph, const int& NId, const bool& IsDir, const bool& Normalized = true);
template <class PGraph> double GetFarnessCentrMP(const PGraph& Graph, const int& NId, const bool& IsDir, const bool& Normalized = true);
/// Returns weighted Farness centrality of a given node \c NId.
/// Farness centrality of a node is the average shortest path length to all other nodes that reside is the same connected component as the given node.
double GetWeightedFarnessCentr(const PNEANet Graph, const int& NId, const bool& IsDir, const TFltV& Attr, const bool& Normalized = true);
/// Returns Closeness centrality of a given node NId.
/// Closeness centrality of a node is defined as 1/FarnessCentrality.
template <class PGraph> double GetClosenessCentr(const PGraph& Graph, const int& NId, const bool& IsDir, const bool& Normalized = true);
template <class PGraph> double GetClosenessCentrMP(const PGraph& Graph, const int& NId, const bool& IsDir, const bool& Normalized = true);
/// Returns Closeness centrality of a given node \c NId.
/// Closeness centrality of a node is defined as 1/FarnessCentrality.
double GetWeightedClosenessCentr(const PNEANet Graph, const int& NId, const bool& IsDir, const TFltV& Attr, const bool& Normalized = true);
/// Returns node Eccentricity, the largest shortest-path distance from the node NId to any other node in the Graph.
/// @param IsDir false: ignore edge directions and consider edges as undirected (in case they are directed).
template <class PGraph> int GetNodeEcc(const PGraph& Graph, const int& NId, const bool& IsDir=false);
/// Computes (approximate) Node Beetweenness Centrality based on a sample of NodeFrac nodes.
/// @param NIdBtwH hash table mapping node ids to their corresponding betweenness centrality values.
/// @param NodeFrac quality of approximation. NodeFrac=1.0 gives exact betweenness values.
template<class PGraph> void GetBetweennessCentr(const PGraph& Graph, TIntFltH& NIdBtwH, const bool& IsDir=false, const double& NodeFrac=1.0);
template<class PGraph> void GetBetweennessCentr_stl(const PGraph& Graph, std::vector<float>& NIdBtwH, const bool& IsDir=false, const double& NodeFrac=1.0);
/// Computes (approximate) weighted Node Beetweenness Centrality based on a sample of NodeFrac nodes.
/// @param NIdBtwH hash table mapping node ids to their corresponding betweenness centrality values.
/// @param NodeFrac quality of approximation. NodeFrac=1.0 gives exact betweenness values.
void GetWeightedBetweennessCentr(const PNEANet Graph, TIntFltH& NIdBtwH, const TFltV& Attr, const bool& IsDir=false, const double& NodeFrac=1.0);
/// Computes (approximate) Edge Beetweenness Centrality based on a sample of NodeFrac nodes.
/// @param EdgeBtwH hash table mapping edges (pairs of node ids) to their corresponding betweenness centrality values.
/// @param NodeFrac quality of approximation. NodeFrac=1.0 gives exact betweenness values.
template<class PGraph> void GetBetweennessCentr(const PGraph& Graph, TIntPrFltH& EdgeBtwH, const bool& IsDir=false, const double& NodeFrac=1.0);
/// Computes (approximate) weighted Edge Beetweenness Centrality based on a sample of NodeFrac nodes.
/// @param EdgeBtwH hash table mapping edges (pairs of node ids) to their corresponding betweenness centrality values.
/// @param NodeFrac quality of approximation. NodeFrac=1.0 gives exact betweenness values.
void GetWeightedBetweennessCentr(const PNEANet Graph, TIntPrFltH& EdgeBtwH, const TFltV& Attr, const bool& IsDir=false, const double& NodeFrac=1.0);
/// Computes (approximate) Node and Edge Beetweenness Centrality based on a sample of NodeFrac nodes.
/// @param NIdBtwH hash table mapping node ids to their corresponding betweenness centrality values.
/// @param EdgeBtwH hash table mapping edges (pairs of node ids) to their corresponding betweenness centrality values.
/// @param NodeFrac quality of approximation. NodeFrac=1.0 gives exact betweenness values.
template<class PGraph> void GetBetweennessCentr(const PGraph& Graph, TIntFltH& NIdBtwH, TIntPrFltH& EdgeBtwH, const bool& IsDir=false, const double& NodeFrac=1.0);
/// Computes (approximate) weighted Node and Edge Beetweenness Centrality based on a sample of NodeFrac nodes.
/// @param NIdBtwH hash table mapping node ids to their corresponding betweenness centrality values.
/// @param EdgeBtwH hash table mapping edges (pairs of node ids) to their corresponding betweenness centrality values.
/// @param NodeFrac quality of approximation. NodeFrac=1.0 gives exact betweenness values.
void GetWeightedBetweennessCentr(const PNEANet Graph, TIntFltH& NIdBtwH, TIntPrFltH& EdgeBtwH, const TFltV& Attr, const bool& IsDir=false, const double& NodeFrac=1.0);
/// Computes (approximate) Beetweenness Centrality of all nodes and all edges of the network.
/// To obtain exact betweenness values one needs to solve single-source shortest-path problem for every node.
/// To speed up the algorithm we solve the shortest-path problem for the BtwNIdV subset of nodes. This gives centrality values that are about Graph->GetNodes()/BtwNIdV.Len() times lower than the exact betweenness centrality valus.
/// See "A Faster Algorithm for Beetweenness Centrality", Ulrik Brandes, Journal of Mathematical Sociology, 2001, and
/// "Centrality Estimation in Large Networks", Urlik Brandes and Christian Pich, 2006 for more details.
template<class PGraph> void GetBetweennessCentr(const PGraph& Graph, const TIntV& BtwNIdV, TIntFltH& NodeBtwH, const bool& IsDir, const bool& DoNodeCent, TIntPrFltH& EdgeBtwH, const bool& DoEdgeCent);
/// Computes (approximate) weighted Beetweenness Centrality of all nodes and all edges of the network.
void GetWeightedBetweennessCentr(const PNEANet Graph, const TIntV& BtwNIdV, TIntFltH& NodeBtwH, const bool& IsDir, const bool& DoNodeCent, TIntPrFltH& EdgeBtwH, const bool& DoEdgeCent, const TFltV& Attr);
/// Computes Eigenvector Centrality of all nodes in the network
/// Eigenvector Centrality of a node N is defined recursively as the average of centrality values of N's neighbors in the network.
void GetEigenVectorCentr(const PUNGraph& Graph, TIntFltH& NIdEigenH, const double& Eps=1e-4, const int& MaxIter=100);
/// PageRank
/// For more info see: http://en.wikipedia.org/wiki/PageRank
template<class PGraph> void GetPageRank(const PGraph& Graph, TIntFltH& PRankH, const double& C=0.85, const double& Eps=1e-4, const int& MaxIter=100);
template<class PGraph> void GetPageRank_stl(const PGraph& Graph, std::vector<float>& PRankH, const double& C=0.85, const double& Eps=1e-4, const int& MaxIter=100);
template<class PGraph> void GetPageRank_v1(const PGraph& Graph, TIntFltH& PRankH, const double& C=0.85, const double& Eps=1e-4, const int& MaxIter=100);
#ifdef USE_OPENMP
template<class PGraph> void GetPageRankMP(const PGraph& Graph, TIntFltH& PRankH, const double& C=0.85, const double& Eps=1e-4, const int& MaxIter=100);
#endif
/// Weighted PageRank (TODO: Use template)
int GetWeightedPageRank(const PNEANet Graph, TIntFltH& PRankH, const TStr& Attr, const double& C=0.85, const double& Eps=1e-4, const int& MaxIter=100);
#ifdef USE_OPENMP
int GetWeightedPageRankMP(const PNEANet Graph, TIntFltH& PRankH, const TStr& Attr, const double& C=0.85, const double& Eps=1e-4, const int& MaxIter=100);
#endif
/// HITS: Hubs and Authorities
/// For more info see: http://en.wikipedia.org/wiki/HITS_algorithm)
template<class PGraph> void GetHits(const PGraph& Graph, TIntFltH& NIdHubH, TIntFltH& NIdAuthH, const int& MaxIter=20);
template<class PGraph> void GetHits_stl(const PGraph& Graph, std::vector<float>& NIdHubH, std::vector<float>& NIdAuthH, const int& MaxIter=20);
#ifdef USE_OPENMP
template<class PGraph> void GetHitsMP(const PGraph& Graph, TIntFltH& NIdHubH, TIntFltH& NIdAuthH, const int& MaxIter=20);
#endif
/// Dijkstra Algorithm
/// For more info see: https://en.wikipedia.org/wiki/Dijkstra%27s_algorithm
int GetWeightedShortestPath(const PNEANet Graph, const int& SrcNId, TIntFltH& NIdDistH, const TFltV& Attr);
/////////////////////////////////////////////////
// Implementation
template <class PGraph>
double GetFarnessCentr(const PGraph& Graph, const int& NId, const bool& IsDir, const bool& Normalized) {
TIntH NDistH(Graph->GetNodes());
TSnap::GetShortPath<PGraph>(Graph, NId, NDistH, IsDir, TInt::Mx);
double sum = 0;
for (TIntH::TIter I = NDistH.BegI(); I < NDistH.EndI(); I++) {
sum += I->Dat();
}
if (NDistH.Len() > 1) {
double centr = sum/double(NDistH.Len()-1);
if (Normalized) {
centr *= (Graph->GetNodes() - 1)/double(NDistH.Len()-1);
}
return centr;
}
else { return 0.0; }
}
template <class PGraph>
double GetFarnessCentrMP(const PGraph& Graph, const int& NId, const bool& IsDir, const bool& Normalized) {
TIntH NDistH(Graph->GetNodes());
TSnap::GetShortPath<PGraph>(Graph, NId, NDistH, IsDir, TInt::Mx);
double sum = 0;
for (TIntH::TIter I = NDistH.BegI(); I < NDistH.EndI(); I++) {
sum += I->Dat();
}
if (NDistH.Len() > 1) {
double centr = sum/double(NDistH.Len()-1);
if (Normalized) {
centr *= (Graph->GetNodes() - 1)/double(NDistH.Len()-1);
}
return centr;
}
else { return 0.0; }
}
template <class PGraph>
double GetClosenessCentr(const PGraph& Graph, const int& NId, const bool& IsDir, const bool& Normalized) {
const double Farness = GetFarnessCentr<PGraph> (Graph, NId, IsDir, Normalized);
if (Farness != 0.0) { return 1.0/Farness; }
else { return 0.0; }
return 0.0;
}
template <class PGraph>
double GetClosenessCentrMP(const PGraph& Graph, const int& NId, const bool& IsDir, const bool& Normalized) {
const double Farness = GetFarnessCentrMP<PGraph> (Graph, NId, IsDir, Normalized);
if (Farness != 0.0) { return 1.0/Farness; }
else { return 0.0; }
return 0.0;
}
template <class PGraph>
int GetNodeEcc(const PGraph& Graph, const int& NId, const bool& IsDir) {
int NodeEcc;
int Dist;
TBreathFS<PGraph> BFS(Graph);
// get shortest paths to all the nodes
BFS.DoBfs(NId, true, ! IsDir, -1, TInt::Mx);
NodeEcc = 0;
// find the largest value
for (int i = 0; i < BFS.NIdDistH.Len(); i++) {
Dist = BFS.NIdDistH[i];
if (Dist > NodeEcc) {
NodeEcc = Dist;
}
}
return NodeEcc;
}
// Page Rank -- there are two different implementations (uncomment the desired 2 lines):
// Berkhin -- (the correct way) see Algorithm 1 of P. Berkhin, A Survey on PageRank Computing, Internet Mathematics, 2005
// iGraph -- iGraph implementation(which treats leaked PageRank in a funny way)
// This implementation is an unoptimized version, it accesses nodes via a hash table.
template<class PGraph>
void GetPageRank_v1(const PGraph& Graph, TIntFltH& PRankH, const double& C, const double& Eps, const int& MaxIter) {
const int NNodes = Graph->GetNodes();
//const double OneOver = 1.0/double(NNodes);
PRankH.Gen(NNodes);
for (typename PGraph::TObj::TNodeI NI = Graph->BegNI(); NI < Graph->EndNI(); NI++) {
PRankH.AddDat(NI.GetId(), 1.0/NNodes);
//IAssert(NI.GetId() == PRankH.GetKey(PRankH.Len()-1));
}
TFltV TmpV(NNodes);
for (int iter = 0; iter < MaxIter; iter++) {
int j = 0;
for (typename PGraph::TObj::TNodeI NI = Graph->BegNI(); NI < Graph->EndNI(); NI++, j++) {
TmpV[j] = 0;
for (int e = 0; e < NI.GetInDeg(); e++) {
const int InNId = NI.GetInNId(e);
const int OutDeg = Graph->GetNI(InNId).GetOutDeg();
if (OutDeg > 0) {
TmpV[j] += PRankH.GetDat(InNId) / OutDeg; }
}
TmpV[j] = C*TmpV[j]; // Berkhin (the correct way of doing it)
//TmpV[j] = C*TmpV[j] + (1.0-C)*OneOver; // iGraph
}
double diff=0, sum=0, NewVal;
for (int i = 0; i < TmpV.Len(); i++) { sum += TmpV[i]; }
const double Leaked = (1.0-sum) / double(NNodes);
for (int i = 0; i < PRankH.Len(); i++) { // re-instert leaked PageRank
NewVal = TmpV[i] + Leaked; // Berkhin
//NewVal = TmpV[i] / sum; // iGraph
diff += fabs(NewVal-PRankH[i]);
PRankH[i] = NewVal;
}
if (diff < Eps) { break; }
}
}
// Page Rank -- there are two different implementations (uncomment the desired 2 lines):
// Berkhin -- (the correct way) see Algorithm 1 of P. Berkhin, A Survey on PageRank Computing, Internet Mathematics, 2005
// iGraph -- iGraph implementation(which treats leaked PageRank in a funny way)
// This implementation is an optimized version, it builds a vector and accesses nodes via the vector.
template<class PGraph>
void GetPageRank(const PGraph& Graph, TIntFltH& PRankH, const double& C, const double& Eps, const int& MaxIter) {
const int NNodes = Graph->GetNodes();
TVec<typename PGraph::TObj::TNodeI> NV;
PRankH.Gen(NNodes);
int MxId = -1;
for (typename PGraph::TObj::TNodeI NI = Graph->BegNI(); NI < Graph->EndNI(); NI++) {
NV.Add(NI);
PRankH.AddDat(NI.GetId(), 1.0/NNodes);
int Id = NI.GetId();
if (Id > MxId) {
MxId = Id;
}
}
TFltV PRankV(MxId+1);
TIntV OutDegV(MxId+1);
for (int j = 0; j < NNodes; j++) {
typename PGraph::TObj::TNodeI NI = NV[j];
int Id = NI.GetId();
PRankV[Id] = 1.0/NNodes;
OutDegV[Id] = NI.GetOutDeg();
}
TFltV TmpV(NNodes);
for (int iter = 0; iter < MaxIter; iter++) {
for (int j = 0; j < NNodes; j++) {
typename PGraph::TObj::TNodeI NI = NV[j];
TFlt Tmp = 0;
for (int e = 0; e < NI.GetInDeg(); e++) {
const int InNId = NI.GetInNId(e);
const int OutDeg = OutDegV[InNId];
if (OutDeg > 0) {
Tmp += PRankV[InNId] / OutDeg;
}
}
TmpV[j] = C*Tmp; // Berkhin (the correct way of doing it)
}
double sum = 0;
for (int i = 0; i < TmpV.Len(); i++) { sum += TmpV[i]; }
const double Leaked = (1.0-sum) / double(NNodes);
double diff = 0;
for (int i = 0; i < NNodes; i++) {
typename PGraph::TObj::TNodeI NI = NV[i];
double NewVal = TmpV[i] + Leaked; // Berkhin
int Id = NI.GetId();
diff += fabs(NewVal-PRankV[Id]);
PRankV[Id] = NewVal;
}
if (diff < Eps) { break; }
}
for (int i = 0; i < NNodes; i++) {
typename PGraph::TObj::TNodeI NI = NV[i];
PRankH[i] = PRankV[NI.GetId()];
}
}
//Version with stl containers
template<class PGraph>
void GetPageRank_stl(const PGraph& Graph, std::vector<float>& PRankH, const double& C, const double& Eps, const int& MaxIter) {
//std::chrono::system_clock::time_point start = std::chrono::system_clock::now();
const long NNodes = Graph->GetNodes();
PRankH.resize(NNodes);
std::vector<long> OutDegV(NNodes);
long Id = 0;
for (typename PGraph::TObj::TNodeI NI = Graph->BegNI(); NI < Graph->EndNI(); NI++) {
PRankH[Id] = 1.0/NNodes;
OutDegV[Id] = NI.GetOutDeg();
Id++;
}
std::vector<float> TmpV(NNodes);
//std::chrono::seconds durinit = std::chrono::duration_cast<std::chrono::seconds>(std::chrono::system_clock::now() - start);
//std::cout << "Finished initializing the data structures " << durinit.count() << "s" << std::endl;
for (int iter = 0; iter < MaxIter; iter++) {
//std::chrono::seconds dur = std::chrono::duration_cast<std::chrono::seconds>(std::chrono::system_clock::now() - start);
//std::cout << "Iteration " << iter << " " << dur.count() << "s" << std::endl;
for (long j = 0; j < NNodes; j++) {
typename PGraph::TObj::TNodeI NI = Graph->GetNI(j);
TFlt Tmp = 0;
for (int e = 0; e < NI.GetInDeg(); e++) {
const long InNId = NI.GetInNId(e);
const int OutDeg = OutDegV[InNId];
if (OutDeg > 0) {
Tmp += PRankH[InNId] / OutDeg;
}
}
TmpV[j] = C*Tmp; // Berkhin (the correct way of doing it)
}
//dur = std::chrono::duration_cast<std::chrono::seconds>(std::chrono::system_clock::now() - start);
//std::cout << "Finished adding to Tmp " << iter << " " << dur.count() << "s" << std::endl;
double sum = 0;
for (long i = 0; i < TmpV.size(); i++) { sum += TmpV[i]; }
const double Leaked = (1.0-sum) / double(NNodes);
//dur = std::chrono::duration_cast<std::chrono::seconds>(std::chrono::system_clock::now() - start);
//std::cout << "Finished summing to Tmp " << iter << " " << dur.count() << "s" << std::endl;
double diff = 0;
for (long i = 0; i < NNodes; i++) {
typename PGraph::TObj::TNodeI NI = Graph->GetNI(i);
double NewVal = TmpV[i] + Leaked; // Berkhin
long Id = NI.GetId();
diff += fabs(NewVal-PRankH[Id]);
PRankH[Id] = NewVal;
}
if (diff < Eps) { break; }
}
}
#ifdef USE_OPENMP
// Page Rank -- there are two different implementations (uncomment the desired 2 lines):
// Berkhin -- (the correct way) see Algorithm 1 of P. Berkhin, A Survey on PageRank Computing, Internet Mathematics, 2005
// iGraph -- iGraph implementation(which treats leaked PageRank in a funny way)
// This is a parallel, optimized version.
template<class PGraph>
void GetPageRankMP(const PGraph& Graph, TIntFltH& PRankH, const double& C, const double& Eps, const int& MaxIter) {
const int NNodes = Graph->GetNodes();
TVec<typename PGraph::TObj::TNodeI> NV;
PRankH.Gen(NNodes);
int MxId = -1;
for (typename PGraph::TObj::TNodeI NI = Graph->BegNI(); NI < Graph->EndNI(); NI++) {
NV.Add(NI);
PRankH.AddDat(NI.GetId(), 1.0/NNodes);
int Id = NI.GetId();
if (Id > MxId) {
MxId = Id;
}
}
TFltV PRankV(MxId+1);
TIntV OutDegV(MxId+1);
#pragma omp parallel for schedule(dynamic,10000)
for (int j = 0; j < NNodes; j++) {
typename PGraph::TObj::TNodeI NI = NV[j];
int Id = NI.GetId();
PRankV[Id] = 1.0/NNodes;
OutDegV[Id] = NI.GetOutDeg();
}
TFltV TmpV(NNodes);
for (int iter = 0; iter < MaxIter; iter++) {
#pragma omp parallel for schedule(dynamic,10000)
for (int j = 0; j < NNodes; j++) {
typename PGraph::TObj::TNodeI NI = NV[j];
TFlt Tmp = 0;
for (int e = 0; e < NI.GetInDeg(); e++) {
const int InNId = NI.GetInNId(e);
const int OutDeg = OutDegV[InNId];
if (OutDeg > 0) {
Tmp += PRankV[InNId] / OutDeg;
}
}
TmpV[j] = C*Tmp; // Berkhin (the correct way of doing it)
}
double sum = 0;
#pragma omp parallel for reduction(+:sum) schedule(dynamic,10000)
for (int i = 0; i < TmpV.Len(); i++) { sum += TmpV[i]; }
const double Leaked = (1.0-sum) / double(NNodes);
double diff = 0;
#pragma omp parallel for reduction(+:diff) schedule(dynamic,10000)
for (int i = 0; i < NNodes; i++) {
double NewVal = TmpV[i] + Leaked; // Berkhin
int Id = NV[i].GetId();
diff += fabs(NewVal-PRankV[Id]);
PRankV[Id] = NewVal;
}
if (diff < Eps) { break; }
}
#pragma omp parallel for schedule(dynamic,10000)
for (int i = 0; i < NNodes; i++) {
typename PGraph::TObj::TNodeI NI = NV[i];
PRankH[i] = PRankV[NI.GetId()];
}
}
#endif // USE_OPENMP
// Betweenness Centrality
template<class PGraph>
void GetBetweennessCentr(const PGraph& Graph, const TIntV& BtwNIdV, TIntFltH& NodeBtwH, const bool& IsDir, const bool& DoNodeCent, TIntPrFltH& EdgeBtwH, const bool& DoEdgeCent) {
if (DoNodeCent) { NodeBtwH.Clr(); }
if (DoEdgeCent) { EdgeBtwH.Clr(); }
const int nodes = Graph->GetNodes();
TIntS S(nodes);
TIntQ Q(nodes);
TIntIntVH P(nodes); // one vector for every node
TIntFltH delta(nodes);
TIntH sigma(nodes), d(nodes);
// init
for (typename PGraph::TObj::TNodeI NI = Graph->BegNI(); NI < Graph->EndNI(); NI++) {
if (DoNodeCent) {
NodeBtwH.AddDat(NI.GetId(), 0); }
if (DoEdgeCent) {
for (int e = 0; e < NI.GetOutDeg(); e++) {
if (NI.GetId() < NI.GetOutNId(e)) {
EdgeBtwH.AddDat(TIntPr(NI.GetId(), NI.GetOutNId(e)), 0);
}
}
}
sigma.AddDat(NI.GetId(), 0);
d.AddDat(NI.GetId(), -1);
P.AddDat(NI.GetId(), TIntV());
delta.AddDat(NI.GetId(), 0);
}
// calc betweeness
for (int k=0; k < BtwNIdV.Len(); k++) {
const typename PGraph::TObj::TNodeI NI = Graph->GetNI(BtwNIdV[k]);
// reset
for (int i = 0; i < sigma.Len(); i++) {
sigma[i]=0; d[i]=-1; delta[i]=0; P[i].Clr(false);
}
S.Clr(false);
Q.Clr(false);
sigma.AddDat(NI.GetId(), 1);
d.AddDat(NI.GetId(), 0);
Q.Push(NI.GetId());
while (! Q.Empty()) {
const int v = Q.Top(); Q.Pop();
const typename PGraph::TObj::TNodeI NI2 = Graph->GetNI(v);
S.Push(v);
const int VDat = d.GetDat(v);
for (int e = 0; e < NI2.GetOutDeg(); e++) {
const int w = NI2.GetOutNId(e);
if (d.GetDat(w) < 0) { // find w for the first time
Q.Push(w);
d.AddDat(w, VDat+1);
}
//shortest path to w via v ?
if (d.GetDat(w) == VDat+1) {
sigma.AddDat(w) += sigma.GetDat(v);
P.GetDat(w).Add(v);
}
}
}
while (! S.Empty()) {
const int w = S.Top();
const double SigmaW = sigma.GetDat(w);
const double DeltaW = delta.GetDat(w);
const TIntV NIdV = P.GetDat(w);
S.Pop();
for (int i = 0; i < NIdV.Len(); i++) {
const int NId = NIdV[i];
const double c = (sigma.GetDat(NId)*1.0/SigmaW) * (1+DeltaW);
delta.AddDat(NId) += c;
if (DoEdgeCent) {
EdgeBtwH.AddDat(TIntPr(TMath::Mn(NId, w), TMath::Mx(NId, w))) += c; }
}
double factor = (IsDir) ? 1.0 : 2.0;
if (DoNodeCent && w != NI.GetId()) {
NodeBtwH.AddDat(w) += delta.GetDat(w)/factor; }
}
}
}
template<class PGraph>
void GetBetweennessCentr_stl(const PGraph& Graph,
const std::vector<long>& BtwNIdV,
std::vector<float>& NodeBtwH,
const bool& IsDir,
const bool& DoNodeCent,
TIntPrFltH& EdgeBtwH,
const bool& DoEdgeCent) {
if (DoNodeCent) { NodeBtwH.clear(); }
if (DoEdgeCent) { EdgeBtwH.Clr(); }
const long nodes = Graph->GetNodes();
TIntS S(nodes);
TIntQ Q(nodes);
TIntIntVH P(nodes); // one vector for every node
TIntFltH delta(nodes);
TIntH sigma(nodes);
TIntH d(nodes);
// init
for (typename PGraph::TObj::TNodeI NI = Graph->BegNI(); NI < Graph->EndNI(); NI++) {
if (DoNodeCent) {
NodeBtwH.push_back(0); }
if (DoEdgeCent) {
for (int e = 0; e < NI.GetOutDeg(); e++) {
if (NI.GetId() < NI.GetOutNId(e)) {
EdgeBtwH.AddDat(TIntPr(NI.GetId(), NI.GetOutNId(e)), 0);
}
}
}
sigma.AddDat(NI.GetId(), 0);
d.AddDat(NI.GetId(), -1);
P.AddDat(NI.GetId(), TIntV());
delta.AddDat(NI.GetId(), 0);
}
// calc betweeness
for (int k=0; k < BtwNIdV.size(); k++) {
const typename PGraph::TObj::TNodeI NI = Graph->GetNI(BtwNIdV[k]);
// reset
for (int i = 0; i < sigma.Len(); i++) {
sigma[i]=0; d[i]=-1; delta[i]=0; P[i].Clr(false);
}
S.Clr(false);
Q.Clr(false);
sigma.AddDat(NI.GetId(), 1);
d.AddDat(NI.GetId(), 0);
Q.Push(NI.GetId());
while (! Q.Empty()) {
const int v = Q.Top(); Q.Pop();
const typename PGraph::TObj::TNodeI NI2 = Graph->GetNI(v);
S.Push(v);
const int VDat = d.GetDat(v);
for (int e = 0; e < NI2.GetOutDeg(); e++) {
const int w = NI2.GetOutNId(e);
if (d.GetDat(w) < 0) { // find w for the first time
Q.Push(w);
d.AddDat(w, VDat+1);
}
//shortest path to w via v ?
if (d.GetDat(w) == VDat+1) {
sigma.AddDat(w) += sigma.GetDat(v);
P.GetDat(w).Add(v);
}
}
}
while (! S.Empty()) {
const int w = S.Top();
const double SigmaW = sigma.GetDat(w);
const double DeltaW = delta.GetDat(w);
const TIntV NIdV = P.GetDat(w);
S.Pop();
for (int i = 0; i < NIdV.Len(); i++) {
const int NId = NIdV[i];
const double c = (sigma.GetDat(NId)*1.0/SigmaW) * (1+DeltaW);
delta.AddDat(NId) += c;
if (DoEdgeCent) {
EdgeBtwH.AddDat(TIntPr(TMath::Mn(NId, w), TMath::Mx(NId, w))) += c; }
}
double factor = (IsDir) ? 1.0 : 2.0;
if (DoNodeCent && w != NI.GetId()) {
NodeBtwH[w] += delta.GetDat(w)/factor; }
}
}
}
template<class PGraph>
void GetBetweennessCentr(const PGraph& Graph, TIntFltH& NodeBtwH, const bool& IsDir, const double& NodeFrac) {
TIntPrFltH EdgeBtwH;
TIntV NIdV; Graph->GetNIdV(NIdV);
if (NodeFrac < 1.0) { // calculate beetweenness centrality for a subset of nodes
NIdV.Shuffle(TInt::Rnd);
for (int i = int((1.0-NodeFrac)*NIdV.Len()); i > 0; i--) {
NIdV.DelLast(); }
}
GetBetweennessCentr<PGraph> (Graph, NIdV, NodeBtwH, IsDir, true, EdgeBtwH, false);
}
template<class PGraph>
void GetBetweennessCentr_stl(const PGraph& Graph, std::vector<float>& NodeBtwH, const bool& IsDir, const double& NodeFrac) {
TIntPrFltH EdgeBtwH;
std::vector<long> NIdV;
Graph->GetNIdV(NIdV);
if (NodeFrac < 1.0) { // calculate beetweenness centrality for a subset of nodes
const long nodesToConsider = std::max((long)1, (long)(NodeFrac * NIdV.size()));
std::vector<long> randomsample;
std::set<long> selectedids;
std::random_device rd;
std::mt19937 gen(rd());
std::uniform_int_distribution<long> dis(0, NIdV.size());
for(long i = 0; i < nodesToConsider; ++i) {
long idxRandomNode = dis(gen);
while (selectedids.count(idxRandomNode)) {
idxRandomNode = dis(gen);
}
selectedids.insert(idxRandomNode);
randomsample.push_back(idxRandomNode);
}
std::sort(randomsample.begin(), randomsample.end());
long j = 0;
for(long i = 0; i < randomsample.size(); ++i) {
if (randomsample[i] == j) {
//do nothing
} else {
NIdV[j] = NIdV[randomsample[i]];
}
j++;
}
}
GetBetweennessCentr_stl<PGraph>(Graph, NIdV, NodeBtwH, IsDir, true, EdgeBtwH, false);
}
template<class PGraph>
void GetBetweennessCentr(const PGraph& Graph, TIntPrFltH& EdgeBtwH, const bool& IsDir, const double& NodeFrac) {
TIntFltH NodeBtwH;
TIntV NIdV; Graph->GetNIdV(NIdV);
if (NodeFrac < 1.0) { // calculate beetweenness centrality for a subset of nodes
NIdV.Shuffle(TInt::Rnd);
for (int i = int((1.0-NodeFrac)*NIdV.Len()); i > 0; i--) {
NIdV.DelLast(); }
}
GetBetweennessCentr<PGraph> (Graph, NIdV, NodeBtwH, IsDir, false, EdgeBtwH, true);
}
template<class PGraph>
void GetBetweennessCentr(const PGraph& Graph, TIntFltH& NodeBtwH, TIntPrFltH& EdgeBtwH, const bool& IsDir, const double& NodeFrac) {
TIntV NIdV; Graph->GetNIdV(NIdV);
if (NodeFrac < 1.0) { // calculate beetweenness centrality for a subset of nodes
NIdV.Shuffle(TInt::Rnd);
for (int i = int((1.0-NodeFrac)*NIdV.Len()); i > 0; i--) {
NIdV.DelLast(); }
}
GetBetweennessCentr<PGraph> (Graph, NIdV, NodeBtwH, IsDir, true, EdgeBtwH, true);
}
template<class PGraph>
void GetHits(const PGraph& Graph, TIntFltH& NIdHubH, TIntFltH& NIdAuthH, const int& MaxIter) {
const int NNodes = Graph->GetNodes();
NIdHubH.Gen(NNodes);
NIdAuthH.Gen(NNodes);
for (typename PGraph::TObj::TNodeI NI = Graph->BegNI(); NI < Graph->EndNI(); NI++) {
NIdHubH.AddDat(NI.GetId(), 1.0);
NIdAuthH.AddDat(NI.GetId(), 1.0);
}
double Norm=0;
for (int iter = 0; iter < MaxIter; iter++) {
// update authority scores
Norm = 0;
for (typename PGraph::TObj::TNodeI NI = Graph->BegNI(); NI < Graph->EndNI(); NI++) {
double& Auth = NIdAuthH.GetDat(NI.GetId()).Val;
Auth = 0;
for (int e = 0; e < NI.GetInDeg(); e++) {
Auth += NIdHubH.GetDat(NI.GetInNId(e)); }
Norm += Auth*Auth;
}
Norm = sqrt(Norm);
for (int i = 0; i < NIdAuthH.Len(); i++) { NIdAuthH[i] /= Norm; }
// update hub scores
for (typename PGraph::TObj::TNodeI NI = Graph->BegNI(); NI < Graph->EndNI(); NI++) {
double& Hub = NIdHubH.GetDat(NI.GetId()).Val;
Hub = 0;
for (int e = 0; e < NI.GetOutDeg(); e++) {
Hub += NIdAuthH.GetDat(NI.GetOutNId(e)); }
Norm += Hub*Hub;
}
Norm = sqrt(Norm);
for (int i = 0; i < NIdHubH.Len(); i++) { NIdHubH[i] /= Norm; }
}
// make sure Hub and Authority scores normalize to L2 norm 1
Norm = 0.0;
for (int i = 0; i < NIdHubH.Len(); i++) { Norm += TMath::Sqr(NIdHubH[i]); }
Norm = sqrt(Norm);
for (int i = 0; i < NIdHubH.Len(); i++) { NIdHubH[i] /= Norm; }
Norm = 0.0;
for (int i = 0; i < NIdAuthH.Len(); i++) { Norm += TMath::Sqr(NIdAuthH[i]); }
Norm = sqrt(Norm);
for (int i = 0; i < NIdAuthH.Len(); i++) { NIdAuthH[i] /= Norm; }
}
template<class PGraph>
void GetHits_stl(const PGraph& Graph,
std::vector<float>& NIdHubH,
std::vector<float>& NIdAuthH, const int& MaxIter) {
const long NNodes = Graph->GetNodes();
NIdHubH.resize(NNodes);
NIdAuthH.resize(NNodes);
long j = 0;
for (typename PGraph::TObj::TNodeI NI = Graph->BegNI(); NI < Graph->EndNI(); NI++) {
NIdHubH[j] = 1.0;
NIdAuthH[j] = 1.0;
j++;
}
double Norm=0;
for (long iter = 0; iter < MaxIter; iter++) {
// update authority scores
Norm = 0;
for (typename PGraph::TObj::TNodeI NI = Graph->BegNI(); NI < Graph->EndNI(); NI++) {
float& Auth = NIdAuthH[NI.GetId()];
Auth = 0;
for (long e = 0; e < NI.GetInDeg(); e++) {
Auth += NIdHubH[NI.GetInNId(e)]; }
Norm += Auth*Auth;
}
Norm = sqrt(Norm);
for (long i = 0; i < NIdAuthH.size(); i++) { NIdAuthH[i] /= Norm; }
// update hub scores
for (typename PGraph::TObj::TNodeI NI = Graph->BegNI(); NI < Graph->EndNI(); NI++) {
float& Hub = NIdHubH[NI.GetId()];
Hub = 0;
for (long e = 0; e < NI.GetOutDeg(); e++) {
Hub += NIdAuthH[NI.GetOutNId(e)]; }
Norm += Hub*Hub;
}
Norm = sqrt(Norm);
for (long i = 0; i < NIdHubH.size(); i++) { NIdHubH[i] /= Norm; }
}
// make sure Hub and Authority scores normalize to L2 norm 1
Norm = 0.0;
for (long i = 0; i < NIdHubH.size(); i++) { Norm += TMath::Sqr(NIdHubH[i]); }
Norm = sqrt(Norm);
for (long i = 0; i < NIdHubH.size(); i++) { NIdHubH[i] /= Norm; }
Norm = 0.0;
for (long i = 0; i < NIdAuthH.size(); i++) { Norm += TMath::Sqr(NIdAuthH[i]); }
Norm = sqrt(Norm);
for (long i = 0; i < NIdAuthH.size(); i++) { NIdAuthH[i] /= Norm; }
}
#ifdef USE_OPENMP
template<class PGraph>
void GetHitsMP(const PGraph& Graph, TIntFltH& NIdHubH, TIntFltH& NIdAuthH, const int& MaxIter) {
const int NNodes = Graph->GetNodes();
TIntV NV;
NIdHubH.Gen(NNodes);
NIdAuthH.Gen(NNodes);
for (typename PGraph::TObj::TNodeI NI = Graph->BegNI(); NI < Graph->EndNI(); NI++) {
NV.Add(NI.GetId());
NIdHubH.AddDat(NI.GetId(), 1.0);
NIdAuthH.AddDat(NI.GetId(), 1.0);
}
double Norm=0;
for (int iter = 0; iter < MaxIter; iter++) {
// update authority scores
Norm = 0;
#pragma omp parallel for reduction(+:Norm) schedule(dynamic,1000)
for (int i = 0; i < NNodes; i++) {
typename PGraph::TObj::TNodeI NI = Graph->GetNI(NV[i]);
double& Auth = NIdAuthH.GetDat(NI.GetId()).Val;
Auth = 0;
for (int e = 0; e < NI.GetInDeg(); e++) {
Auth += NIdHubH.GetDat(NI.GetInNId(e)); }
Norm = Norm + Auth*Auth;
}
Norm = sqrt(Norm);
for (int i = 0; i < NIdAuthH.Len(); i++) { NIdAuthH[i] /= Norm; }
// update hub scores
#pragma omp parallel for reduction(+:Norm) schedule(dynamic,1000)
for (int i = 0; i < NNodes; i++) {
typename PGraph::TObj::TNodeI NI = Graph->GetNI(NV[i]);
double& Hub = NIdHubH.GetDat(NI.GetId()).Val;
Hub = 0;
for (int e = 0; e < NI.GetOutDeg(); e++) {
Hub += NIdAuthH.GetDat(NI.GetOutNId(e)); }
Norm = Norm + Hub*Hub;
}
Norm = sqrt(Norm);
for (int i = 0; i < NIdHubH.Len(); i++) { NIdHubH[i] /= Norm; }
}
// make sure Hub and Authority scores normalize to L2 norm 1
Norm = 0.0;
for (int i = 0; i < NIdHubH.Len(); i++) { Norm += TMath::Sqr(NIdHubH[i]); }
Norm = sqrt(Norm);
for (int i = 0; i < NIdHubH.Len(); i++) { NIdHubH[i] /= Norm; }
Norm = 0.0;
for (int i = 0; i < NIdAuthH.Len(); i++) { Norm += TMath::Sqr(NIdAuthH[i]); }
Norm = sqrt(Norm);
for (int i = 0; i < NIdAuthH.Len(); i++) { NIdAuthH[i] /= Norm; }
}
#endif
}; // namespace TSnap
|
GB_unaryop__minv_uint16_uint32.c | //------------------------------------------------------------------------------
// GB_unaryop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2019, All Rights Reserved.
// http://suitesparse.com See GraphBLAS/Doc/License.txt for license.
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_iterator.h"
#include "GB_unaryop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB_unop__minv_uint16_uint32
// op(A') function: GB_tran__minv_uint16_uint32
// C type: uint16_t
// A type: uint32_t
// cast: uint16_t cij = (uint16_t) aij
// unaryop: cij = GB_IMINV_UNSIGNED (aij, 16)
#define GB_ATYPE \
uint32_t
#define GB_CTYPE \
uint16_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
uint32_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = GB_IMINV_UNSIGNED (x, 16) ;
// casting
#define GB_CASTING(z, x) \
uint16_t z = (uint16_t) x ;
// cij = op (cast (aij))
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GB_GETA (aij, Ax, pA) ; \
/* Cx [pC] = op (cast (aij)) */ \
GB_CASTING (x, aij) ; \
GB_OP (GB_CX (pC), x) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_MINV || GxB_NO_UINT16 || GxB_NO_UINT32)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__minv_uint16_uint32
(
uint16_t *restrict Cx,
const uint32_t *restrict Ax,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (int64_t p = 0 ; p < anz ; p++)
{
GB_CAST_OP (p, p) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_tran__minv_uint16_uint32
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *restrict *Rowcounts,
GBI_single_iterator Iter,
const int64_t *restrict A_slice,
int naslice
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#define GB_PHASE_2_OF_2
#include "GB_unaryop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
cancellation_for_sections.c | // RUN: %libomp-compile && env OMP_CANCELLATION=true %libomp-run
// XFAIL: gcc
// Regression test for a bug in cancellation to cover effect of `#pragma omp cancel`
// in a loop construct, on sections construct.
// Pass condition: Cancellation status from `for` does not persist
// to `sections`.
#include <stdio.h>
#include <omp.h>
int result[2] = {0, 0};
void cq416850_for_sections() {
unsigned i;
// 1) loop
#pragma omp for
for (i = 0; i < 1; i++) {
result[0] = 1;
#pragma omp cancel for
result[0] = 2;
}
// printf("thread %d: result[0] = %d, result[1] = %d \n", omp_get_thread_num(), result[0], result[1]);
// 2) sections
#pragma omp sections
{
#pragma omp section
{
result[1] = 1;
#pragma omp cancellation point sections
result[1] = 2;
}
}
}
int main(void) {
if(!omp_get_cancellation()) {
printf("Cancellation not enabled!\n");
return 2;
}
#pragma omp parallel num_threads(4)
{
cq416850_for_sections();
}
if (result[0] != 1 || result[1] != 2) {
printf("Incorrect values. "
"result[0] = %d (expected 1), "
"result[1] = %d (expected 2).\n",
result[0], result[1]);
printf("FAILED\n");
return 1;
}
printf("PASSED\n");
return 0;
}
|
core_clacpy.c | /**
*
* @file
*
* PLASMA is a software package provided by:
* University of Tennessee, US,
* University of Manchester, UK.
*
* @generated from /home/luszczek/workspace/plasma/bitbucket/plasma/core_blas/core_zlacpy.c, normal z -> c, Fri Sep 28 17:38:19 2018
*
**/
#include <plasma_core_blas.h>
#include "plasma_types.h"
#include "plasma_internal.h"
#include "core_lapack.h"
/***************************************************************************//**
*
* @ingroup core_lacpy
*
* Copies all or part of a two-dimensional matrix A to another matrix B.
*
*******************************************************************************
*
* @param[in] uplo
* - PlasmaGeneral: entire A,
* - PlasmaUpper: upper triangle,
* - PlasmaLower: lower triangle.
*
* @param[in] transa
* - PlasmaNoTrans: A is not transposed,
* - PlasmaTrans: A is transposed,
* - PlasmaConjTrans: A is conjugate transposed.
*
* @param[in] m
* The number of rows of the matrices A and B.
* m >= 0.
*
* @param[in] n
* The number of columns of the matrices A and B.
* n >= 0.
*
* @param[in] A
* The m-by-n matrix to copy.
*
* @param[in] lda
* The leading dimension of the array A.
* lda >= max(1,m).
*
* @param[out] B
* The m-by-n copy of the matrix A.
* On exit, B = A ONLY in the locations specified by uplo.
*
* @param[in] ldb
* The leading dimension of the array B.
* ldb >= max(1,m).
*
******************************************************************************/
__attribute__((weak))
void plasma_core_clacpy(plasma_enum_t uplo, plasma_enum_t transa,
int m, int n,
const plasma_complex32_t *A, int lda,
plasma_complex32_t *B, int ldb)
{
if (transa == PlasmaNoTrans) {
LAPACKE_clacpy_work(LAPACK_COL_MAJOR,
lapack_const(uplo),
m, n,
A, lda,
B, ldb);
}
else if (transa == PlasmaTrans) {
switch (uplo) {
case PlasmaUpper:
for (int i = 0; i < imin(m, n); i++)
for (int j = i; j < n; j++)
B[j + i*ldb] = A[i + j*lda];
break;
case PlasmaLower:
for (int i = 0; i < m; i++)
for (int j = 0; j <= imin(i, n); j++)
B[j + i*ldb] = A[i + j*lda];
break;
case PlasmaGeneral:
for (int i = 0; i < m; i++)
for (int j = 0; j < n; j++)
B[j + i*ldb] = A[i + j*lda];
break;
}
}
else {
switch (uplo) {
case PlasmaUpper:
for (int i = 0; i < imin(m, n); i++)
for (int j = i; j < n; j++)
B[j + i*ldb] = conjf(A[i + j*lda]);
break;
case PlasmaLower:
for (int i = 0; i < m; i++)
for (int j = 0; j <= imin(i, n); j++)
B[j + i*ldb] = conjf(A[i + j*lda]);
break;
case PlasmaGeneral:
for (int i = 0; i < m; i++)
for (int j = 0; j < n; j++)
B[j + i*ldb] = conjf(A[i + j*lda]);
break;
}
}
}
/******************************************************************************/
void plasma_core_omp_clacpy(plasma_enum_t uplo, plasma_enum_t transa,
int m, int n,
const plasma_complex32_t *A, int lda,
plasma_complex32_t *B, int ldb,
plasma_sequence_t *sequence, plasma_request_t *request)
{
#pragma omp task depend(in:A[0:lda*n]) \
depend(out:B[0:ldb*n])
{
if (sequence->status == PlasmaSuccess)
plasma_core_clacpy(uplo, transa,
m, n,
A, lda,
B, ldb);
}
}
|
utils.h | /*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
/*!
* Copyright (c) 2015 by Contributors
* \file utils.h
* \brief Basic utilility functions.
*/
#ifndef MXNET_COMMON_UTILS_H_
#define MXNET_COMMON_UTILS_H_
#include <dmlc/logging.h>
#include <dmlc/omp.h>
#include <nnvm/graph.h>
#include <nnvm/node.h>
#include <mxnet/engine.h>
#include <mxnet/ndarray.h>
#include <mxnet/storage.h>
#include <mxnet/op_attr_types.h>
#include <mxnet/graph_attr_types.h>
#include <nnvm/graph_attr_types.h>
#include <memory>
#include <vector>
#include <type_traits>
#include <utility>
#include <random>
#include <string>
#include <thread>
#include <algorithm>
#include <functional>
#include <limits>
#include "../operator/mxnet_op.h"
#if MXNET_USE_MKLDNN == 1
#include "../operator/nn/mkldnn/mkldnn_base-inl.h"
#endif
#if defined(_WIN32) || defined(_WIN64) || defined(__WINDOWS__)
#include <windows.h>
#else
#include <unistd.h>
#endif
namespace mxnet {
namespace common {
#if defined(_WIN32) || defined(_WIN64) || defined(__WINDOWS__)
inline size_t current_process_id() { return ::GetCurrentProcessId(); }
#else
inline size_t current_process_id() { return getpid(); }
#endif
/*!
* \brief IndPtr should be non-negative, in non-decreasing order, start with 0
* and end with value equal with size of indices.
*/
struct csr_indptr_check {
template<typename DType, typename IType>
MSHADOW_XINLINE static void Map(int i, DType* out, const IType* indptr,
const nnvm::dim_t end, const nnvm::dim_t idx_size) {
if (indptr[i+1] < 0 || indptr[i+1] < indptr[i] ||
(i == 0 && indptr[i] != 0) ||
(i == end - 1 && indptr[end] != idx_size))
*out = kCSRIndPtrErr;
}
};
/*!
* \brief Indices should be non-negative, less than the number of columns
* and in ascending order per row.
*/
struct csr_idx_check {
template<typename DType, typename IType, typename RType>
MSHADOW_XINLINE static void Map(int i, DType* out, const IType* idx,
const RType* indptr, const nnvm::dim_t ncols) {
for (RType j = indptr[i]; j < indptr[i+1]; j++) {
if (idx[j] >= ncols || idx[j] < 0 ||
(j < indptr[i+1] - 1 && idx[j] >= idx[j+1])) {
*out = kCSRIdxErr;
break;
}
}
}
};
/*!
* \brief Indices of RSPNDArray should be non-negative,
* less than the size of first dimension and in ascending order
*/
struct rsp_idx_check {
template<typename DType, typename IType>
MSHADOW_XINLINE static void Map(int i, DType* out, const IType* idx,
const nnvm::dim_t end, const nnvm::dim_t nrows) {
if ((i < end && idx[i+1] <= idx[i])
|| idx[i] < 0 || idx[i] >= nrows)
*out = kRSPIdxErr;
}
};
template<typename xpu>
void CheckFormatWrapper(const RunContext &rctx, const NDArray &input,
const TBlob &err_cpu, const bool full_check);
/*!
* \brief Check the validity of CSRNDArray.
* \param rctx Execution context.
* \param input Input NDArray of CSRStorage.
* \param err_cpu Error number on cpu.
* \param full_check If true, rigorous check, O(N) operations,
* otherwise basic check, O(1) operations.
*/
template<typename xpu>
void CheckFormatCSRImpl(const RunContext &rctx, const NDArray &input,
const TBlob &err_cpu, const bool full_check) {
using namespace op::mxnet_op;
CHECK_EQ(input.storage_type(), kCSRStorage)
<< "CheckFormatCSRImpl is for CSRNDArray";
const mxnet::TShape shape = input.shape();
const mxnet::TShape idx_shape = input.aux_shape(csr::kIdx);
const mxnet::TShape indptr_shape = input.aux_shape(csr::kIndPtr);
const mxnet::TShape storage_shape = input.storage_shape();
if ((shape.ndim() != 2) ||
(idx_shape.ndim() != 1 || indptr_shape.ndim() != 1 || storage_shape.ndim() != 1) ||
(indptr_shape[0] != shape[0] + 1) ||
(idx_shape[0] != storage_shape[0])) {
MSHADOW_TYPE_SWITCH(err_cpu.type_flag_, DType, {
DType* err = err_cpu.dptr<DType>();
*err = kCSRShapeErr;
});
return;
}
if (full_check) {
MSHADOW_TYPE_SWITCH(err_cpu.type_flag_, DType, {
MSHADOW_IDX_TYPE_SWITCH(input.aux_type(csr::kIndPtr), RType, {
MSHADOW_IDX_TYPE_SWITCH(input.aux_type(csr::kIdx), IType, {
mshadow::Stream<xpu> *s = rctx.get_stream<xpu>();
NDArray ret_xpu = NDArray(mshadow::Shape1(1),
rctx.get_ctx(), false, err_cpu.type_flag_);
TBlob val_xpu = ret_xpu.data();
Kernel<set_to_int<kNormalErr>, xpu>::Launch(s, val_xpu.Size(), val_xpu.dptr<DType>());
Kernel<csr_indptr_check, xpu>::Launch(s, indptr_shape[0] - 1, val_xpu.dptr<DType>(),
input.aux_data(csr::kIndPtr).dptr<RType>(),
indptr_shape[0] - 1, idx_shape[0]);
// no need to check indices if indices are empty
if (idx_shape[0] != 0) {
Kernel<csr_idx_check, xpu>::Launch(s, indptr_shape[0] - 1, val_xpu.dptr<DType>(),
input.aux_data(csr::kIdx).dptr<IType>(),
input.aux_data(csr::kIndPtr).dptr<RType>(), shape[1]);
}
mshadow::Copy(err_cpu.get<cpu, 1, DType>(),
val_xpu.get<xpu, 1, DType>(s), s);
});
});
});
}
}
/*!
* \brief Check the validity of RowSparseNDArray.
* \param rctx Execution context.
* \param input Input NDArray of RowSparseStorage.
* \param err_cpu Error number on cpu.
* \param full_check If true, rigorous check, O(N) operations,
* otherwise basic check, O(1) operations.
*/
template<typename xpu>
void CheckFormatRSPImpl(const RunContext &rctx, const NDArray &input,
const TBlob &err_cpu, const bool full_check) {
using namespace op::mxnet_op;
CHECK_EQ(input.storage_type(), kRowSparseStorage)
<< "CheckFormatRSPImpl is for RSPNDArray";
const mxnet::TShape idx_shape = input.aux_shape(rowsparse::kIdx);
if (idx_shape[0] != input.storage_shape()[0]) {
MSHADOW_TYPE_SWITCH(err_cpu.type_flag_, DType, {
DType* err = err_cpu.dptr<DType>();
*err = kRSPShapeErr;
});
return;
}
if (idx_shape[0] == 0) {
return;
}
if (full_check) {
MSHADOW_TYPE_SWITCH(err_cpu.type_flag_, DType, {
MSHADOW_IDX_TYPE_SWITCH(input.aux_type(rowsparse::kIdx), IType, {
mshadow::Stream<xpu> *s = rctx.get_stream<xpu>();
NDArray ret_xpu = NDArray(mshadow::Shape1(1),
rctx.get_ctx(), false, err_cpu.type_flag_);
TBlob val_xpu = ret_xpu.data();
Kernel<set_to_int<kNormalErr>, xpu>::Launch(s, val_xpu.Size(), val_xpu.dptr<DType>());
Kernel<rsp_idx_check, xpu>::Launch(s, idx_shape[0],
val_xpu.dptr<DType>(), input.aux_data(rowsparse::kIdx).dptr<IType>(),
idx_shape[0] - 1, input.shape()[0]);
mshadow::Copy(err_cpu.get<cpu, 1, DType>(),
val_xpu.get<xpu, 1, DType>(s), s);
});
});
}
}
template<typename xpu>
void CheckFormatImpl(const RunContext &rctx, const NDArray &input,
const TBlob &err_cpu, const bool full_check) {
int stype = input.storage_type();
if (stype == kCSRStorage) {
CheckFormatCSRImpl<xpu>(rctx, input, err_cpu, full_check);
} else if (stype == kRowSparseStorage) {
CheckFormatRSPImpl<xpu>(rctx, input, err_cpu, full_check);
} else if (stype == kDefaultStorage) {
// no-op for default storage
} else {
LOG(FATAL) << "Unknown storage type " << stype;
}
}
/*! \brief Pick rows specified by user input index array from a row sparse ndarray
* and save them in the output sparse ndarray.
*/
template<typename xpu>
void SparseRetainOpForwardRspWrapper(mshadow::Stream<xpu> *s,
const NDArray& input_nd,
const TBlob& idx_data,
const OpReqType req,
NDArray* output_nd);
/* \brief Casts tensor storage type to the new type.
*/
template<typename xpu>
void CastStorageDispatch(const OpContext& ctx, const NDArray& input, const NDArray& output);
/*! \brief returns true if all storage types in `vstorage` are the same as target `stype`.
* false is returned for empty inputs.
*/
inline bool ContainsOnlyStorage(const StorageTypeVector& vstorage,
const NDArrayStorageType stype) {
if (!vstorage.empty()) {
for (const auto& i : vstorage) {
if (i != stype) return false;
}
return true;
}
return false;
}
/*! \brief returns true if all storage types in `vstorage` are the same as target `stype1`
* or `stype2'. Sets boolean if both found.
* false is returned for empty inputs.
*/
inline bool ContainsOnlyStorage(const StorageTypeVector& vstorage,
const NDArrayStorageType stype1,
const NDArrayStorageType stype2,
bool *has_both) {
if (has_both) {
*has_both = false;
}
if (!vstorage.empty()) {
uint8_t has = 0;
for (const auto i : vstorage) {
if (i == stype1) {
has |= 1;
} else if (i == stype2) {
has |= 2;
} else {
return false;
}
}
if (has_both) {
*has_both = has == 3;
}
return true;
}
return false;
}
/*! \brief returns true if the storage types of arrays in `ndarrays`
* are the same as target `stype`. false is returned for empty inputs.
*/
inline bool ContainsOnlyStorage(const std::vector<NDArray>& ndarrays,
const NDArrayStorageType stype) {
if (!ndarrays.empty()) {
for (const auto& nd : ndarrays) {
if (nd.storage_type() != stype) {
return false;
}
}
return true;
}
return false;
}
/*! \brief returns true if the storage types of arrays in `ndarrays`
* are the same as targets `stype1` or `stype2`. false is returned for empty inputs.
*/
inline bool ContainsOnlyStorage(const std::vector<NDArray>& ndarrays,
const NDArrayStorageType stype1,
const NDArrayStorageType stype2,
bool *has_both) {
if (has_both) {
*has_both = false;
}
if (!ndarrays.empty()) {
uint8_t has = 0;
for (const auto& nd : ndarrays) {
const NDArrayStorageType stype = nd.storage_type();
if (stype == stype1) {
has |= 1;
} else if (stype == stype2) {
has |= 2;
} else {
return false;
}
}
if (has_both) {
*has_both = has == 3;
}
return true;
}
return false;
}
/*! \brief returns true if storage type of any array in `ndarrays`
* is the same as the target `stype`. false is returned for empty inputs.
*/
inline bool ContainsStorageType(const std::vector<NDArray>& ndarrays,
const NDArrayStorageType stype) {
if (!ndarrays.empty()) {
for (const auto& nd : ndarrays) {
if (nd.storage_type() == stype) {
return true;
}
}
}
return false;
}
/*! \brief returns true if any storage type `ndstype` in `ndstypes`
* is the same as the target `stype`. false is returned for empty inputs.
*/
inline bool ContainsStorageType(const std::vector<int>& ndstypes,
const NDArrayStorageType stype) {
if (!ndstypes.empty()) {
for (const auto& ndstype : ndstypes) {
if (ndstype == stype) {
return true;
}
}
}
return false;
}
/*! \brief get string representation of dispatch_mode */
inline std::string dispatch_mode_string(const DispatchMode x) {
switch (x) {
case DispatchMode::kFCompute:
return "fcompute";
case DispatchMode::kFComputeEx:
return "fcompute_ex";
case DispatchMode::kFComputeFallback:
return "fcompute_fallback";
case DispatchMode::kVariable:
return "variable";
case DispatchMode::kUndefined:
return "undefined";
}
return "unknown";
}
/*! \brief get string representation of storage_type */
inline std::string stype_string(const int x) {
switch (x) {
case kDefaultStorage:
return "default";
case kCSRStorage:
return "csr";
case kRowSparseStorage:
return "row_sparse";
}
return "unknown";
}
/*! \brief get string representation of device type */
inline std::string dev_type_string(const int dev_type) {
switch (dev_type) {
case Context::kCPU:
return "cpu";
case Context::kGPU:
return "gpu";
case Context::kCPUPinned:
return "cpu_pinned";
case Context::kCPUShared:
return "cpu_shared";
}
return "unknown";
}
inline std::string attr_value_string(const nnvm::NodeAttrs& attrs,
const std::string& attr_name,
std::string default_val = "") {
if (attrs.dict.find(attr_name) == attrs.dict.end()) {
return default_val;
}
return attrs.dict.at(attr_name);
}
/*! \brief get string representation of the operator stypes */
inline std::string operator_stype_string(const nnvm::NodeAttrs& attrs,
const int dev_mask,
const std::vector<int>& in_attrs,
const std::vector<int>& out_attrs) {
std::ostringstream os;
os << "operator = " << attrs.op->name
<< "\ninput storage types = [";
for (const int attr : in_attrs) {
os << stype_string(attr) << ", ";
}
os << "]\n"
<< "output storage types = [";
for (const int attr : out_attrs) {
os << stype_string(attr) << ", ";
}
os << "]\n"
<< "params = {";
for (auto kv : attrs.dict) {
os << "\"" << kv.first << "\" : " << kv.second << ", ";
}
os << "}\n"
<< "context.dev_mask = " << dev_type_string(dev_mask);
return os.str();
}
/*! \brief get string representation of the operator */
inline std::string operator_string(const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const std::vector<NDArray>& inputs,
const std::vector<OpReqType>& req,
const std::vector<NDArray>& outputs) {
std::string result = "";
std::vector<int> in_stypes;
std::vector<int> out_stypes;
in_stypes.reserve(inputs.size());
out_stypes.reserve(outputs.size());
auto xform = [](const NDArray arr) -> int { return arr.storage_type(); };
std::transform(inputs.begin(), inputs.end(), std::back_inserter(in_stypes), xform);
std::transform(outputs.begin(), outputs.end(), std::back_inserter(out_stypes), xform);
result += operator_stype_string(attrs, ctx.run_ctx.ctx.dev_mask(), in_stypes, out_stypes);
return result;
}
/*! \brief log message once. Intended for storage fallback warning messages. */
inline void LogOnce(const std::string& message) {
typedef dmlc::ThreadLocalStore<std::unordered_set<std::string>> LogStore;
auto log_store = LogStore::Get();
if (log_store->find(message) == log_store->end()) {
LOG(INFO) << message;
log_store->insert(message);
}
}
/*! \brief log storage fallback event
*/
inline void LogStorageFallback(const nnvm::NodeAttrs& attrs,
const int dev_mask,
const std::vector<int>* in_attrs,
const std::vector<int>* out_attrs) {
static bool log = dmlc::GetEnv("MXNET_STORAGE_FALLBACK_LOG_VERBOSE", true);
if (!log) return;
const std::string op_str = operator_stype_string(attrs, dev_mask, *in_attrs, *out_attrs);
std::ostringstream os;
const char* warning = "\nThe operator with default storage type will be dispatched "
"for execution. You're seeing this warning message because the operator above is unable "
"to process the given ndarrays with specified storage types, context and parameter. "
"Temporary dense ndarrays are generated in order to execute the operator. "
"This does not affect the correctness of the programme. "
"You can set environment variable MXNET_STORAGE_FALLBACK_LOG_VERBOSE to "
"0 to suppress this warning.";
os << "\nStorage type fallback detected:\n" << op_str << warning;
LogOnce(os.str());
#if MXNET_USE_MKLDNN == 1
if (!MKLDNNEnvSet()) common::LogOnce("MXNET_MKLDNN_ENABLED flag is off. "
"You can re-enable by setting MXNET_MKLDNN_ENABLED=1");
if (GetMKLDNNCacheSize() != -1) common::LogOnce("MXNET_MKLDNN_CACHE_NUM is set."
"Should only be set if "
"your model has variable input shapes, "
"as cache size may grow unbounded");
#endif
}
// heuristic to dermine number of threads per GPU
inline int GetNumThreadsPerGPU() {
// This is resource efficient option.
return dmlc::GetEnv("MXNET_GPU_WORKER_NTHREADS", 2);
}
// heuristic to get number of matching colors.
// this decides how much parallelism we can get in each GPU.
inline int GetExecNumMatchColor() {
// This is resource efficient option.
int num_match_color = dmlc::GetEnv("MXNET_EXEC_NUM_TEMP", 1);
return std::min(num_match_color, GetNumThreadsPerGPU());
}
template<typename T, typename V>
V ParallelAccumulate(const T* a, const int n, V start) {
V sum = start;
#pragma omp parallel for reduction(+:sum)
for (int i = 0; i < n; ++i) {
sum += a[i];
}
return sum;
}
/*!
* \brief
* Helper function for ParallelSort.
* DO NOT call this function directly.
* Use the interface ParallelSort instead.
* Ref: https://github.com/dmlc/difacto/blob/master/src/common/parallel_sort.h
*/
template<typename RandomIt, typename Compare>
void ParallelSortHelper(RandomIt first, size_t len,
size_t grainsize, const Compare& comp) {
if (len < grainsize) {
std::sort(first, first+len, comp);
} else {
std::thread thr(ParallelSortHelper<RandomIt, Compare>, first, len/2, grainsize, comp);
ParallelSortHelper(first+len/2, len - len/2, grainsize, comp);
thr.join();
std::inplace_merge(first, first+len/2, first+len, comp);
}
}
/*!
* \brief
* Sort the elements in the range [first, last) into the ascending order defined by
* the comparator comp.
* If the length of the range [first, last) is greater than a certain threshold,
* the range will be recursively divided into two and assign two threads
* to sort each half range.
* Ref: https://github.com/dmlc/difacto/blob/master/src/common/parallel_sort.h
*/
template<typename RandomIt, typename Compare>
void ParallelSort(RandomIt first, RandomIt last, size_t num_threads, Compare comp) {
const auto num = std::distance(first, last);
size_t grainsize = std::max(num / num_threads + 5, static_cast<size_t>(1024*16));
ParallelSortHelper(first, num, grainsize, comp);
}
/*!
* \brief
* Sort the elements in the range [first, last) into ascending order.
* The elements are compared using the default < operator.
* If the length of the range [first, last) is greater than a certain threshold,
* the range will be recursively divided into two and assign two threads
* to sort each half range.
* Ref: https://github.com/dmlc/difacto/blob/master/src/common/parallel_sort.h
*/
template<typename RandomIt>
void ParallelSort(RandomIt first, RandomIt last, size_t num_threads) {
ParallelSort(first, last, num_threads,
std::less<typename std::iterator_traits<RandomIt>::value_type>());
}
/*!
* \brief Random Engine
*/
typedef std::mt19937 RANDOM_ENGINE;
/*!
* \brief Helper functions.
*/
namespace helper {
/*!
* \brief Helper for non-array type `T`.
*/
template <class T>
struct UniqueIf {
/*!
* \brief Type of `T`.
*/
using SingleObject = std::unique_ptr<T>;
};
/*!
* \brief Helper for an array of unknown bound `T`.
*/
template <class T>
struct UniqueIf<T[]> {
/*!
* \brief Type of `T`.
*/
using UnknownBound = std::unique_ptr<T[]>;
};
/*!
* \brief Helper for an array of known bound `T`.
*/
template <class T, size_t kSize>
struct UniqueIf<T[kSize]> {
/*!
* \brief Type of `T`.
*/
using KnownBound = void;
};
} // namespace helper
/*!
* \brief Constructs an object of type `T` and wraps it in a
* `std``::``unique_ptr`.
* \param args List of arguments with which an instance of `T` will be
* constructed.
* \return `std``::``unique_ptr` of an instance of type `T`.
*
* Constructs a non-array type `T`. The arguments `args` are passed to the
* constructor of `T`. The function does not participate in the overload
* resolution if `T` is an array type.
*/
template <class T, class... Args>
typename helper::UniqueIf<T>::SingleObject MakeUnique(Args&&... args) {
return std::unique_ptr<T>(new T(std::forward<Args>(args)...));
}
/*!
* \brief Constructs an object of type `T` and wraps it in a
* `std``::``unique_ptr`.
* \param n The size of the array to construct.
* \return `std``::``unique_ptr` of an instance of type `T`.
*
* Constructs an array of unknown bound `T`. The function does not participate
* in the overload resolution unless `T` is an array of unknown bound.
*/
template <class T>
typename helper::UniqueIf<T>::UnknownBound MakeUnique(size_t n) {
using U = typename std::remove_extent<T>::type;
return std::unique_ptr<T>(new U[n]{});
}
/*!
* \brief Constructs an object of type `T` and wraps it in a
* `std``::``unique_ptr`.
* \param args List of arguments with which an instance of `T` will be
* constructed.
*
* Constructs an arrays of known bound is disallowed.
*/
template <class T, class... Args>
typename helper::UniqueIf<T>::KnownBound MakeUnique(Args&&... args) = delete;
template<typename FCompType>
FCompType GetFCompute(const nnvm::Op* op, const std::string& name,
const Context& ctx) {
static auto& fcompute_cpu = nnvm::Op::GetAttr<FCompType>(name + "<cpu>");
static auto& fcompute_gpu = nnvm::Op::GetAttr<FCompType>(name + "<gpu>");
if (ctx.dev_mask() == cpu::kDevMask) {
return fcompute_cpu.get(op, nullptr);
} else if (ctx.dev_mask() == gpu::kDevMask) {
return fcompute_gpu.get(op, nullptr);
} else {
LOG(FATAL) << "Unknown device mask " << ctx.dev_mask();
return nullptr;
}
}
/*!
* \brief Return the max integer value representable in the type `T` without loss of precision.
*/
template <typename T>
constexpr size_t MaxIntegerValue() {
return std::is_integral<T>::value ?
std::numeric_limits<T>::max():
size_t(2) << (std::numeric_limits<T>::digits - 1);
}
template <>
constexpr size_t MaxIntegerValue<mshadow::half::half_t>() {
return size_t(2) << 10;
}
template <>
constexpr size_t MaxIntegerValue<mshadow::bfloat::bf16_t>() {
return size_t(2) << 14;
}
MSHADOW_XINLINE int ilog2ul(size_t a) {
int k = 1;
while (a >>= 1) ++k;
return k;
}
MSHADOW_XINLINE int ilog2ui(unsigned int a) {
int k = 1;
while (a >>= 1) ++k;
return k;
}
/*!
* \brief Return an NDArray of all zeros.
*/
inline NDArray InitZeros(const NDArrayStorageType stype, const mxnet::TShape &shape,
const Context &ctx, const int dtype) {
// NDArray with default storage
if (stype == kDefaultStorage) {
NDArray ret(shape, ctx, false, dtype);
ret = 0;
return ret;
}
// NDArray with non-default storage. Storage allocation is always delayed.
return NDArray(stype, shape, ctx, true, dtype);
}
/*!
* \brief Helper to add a NDArray of zeros to a std::vector.
*/
inline void EmplaceBackZeros(const NDArrayStorageType stype,
const mxnet::TShape &shape,
const Context &ctx,
const int dtype,
std::vector<NDArray> *vec) {
// NDArray with default storage
if (stype == kDefaultStorage) {
vec->emplace_back(shape, ctx, false, dtype);
vec->back() = 0;
} else {
// NDArray with non-default storage. Storage allocation is always delayed.
vec->emplace_back(stype, shape, ctx, true, dtype);
}
}
/*!
* \brief parallelize copy by OpenMP.
*/
template<typename DType>
inline void ParallelCopy(DType* dst, const DType* src, index_t size) {
static index_t copy_block_size = dmlc::GetEnv("MXNET_CPU_PARALLEL_SIZE", 200000);
if (size >= copy_block_size) {
#pragma omp parallel for num_threads(engine::OpenMP::Get()->GetRecommendedOMPThreadCount())
for (index_t i = 0; i < size; ++i) {
dst[i] = src[i];
}
} else {
#pragma GCC diagnostic push
#if __GNUC__ >= 8
#pragma GCC diagnostic ignored "-Wclass-memaccess"
#endif
std::memcpy(dst, src, sizeof(DType) * size);
#pragma GCC diagnostic pop
}
}
/*!
* \breif parallelize add by OpenMP
*/
template<typename DType>
inline void ParallelAdd(DType* dst, const DType* src, index_t size) {
static index_t add_block_size = dmlc::GetEnv("MXNET_CPU_PARALLEL_SIZE", 200000);
if (size >= add_block_size) {
#pragma omp parallel for num_threads(engine::OpenMP::Get()->GetRecommendedOMPThreadCount())
for (index_t i = 0; i < size; ++i) {
dst[i] += src[i];
}
} else {
for (index_t i = 0; i < size; ++i) {
dst[i] += src[i];
}
}
}
/*!
* \brief If numpy compatibility is turned off (default), the shapes passed in
* by users follow the legacy shape definition:
* 1. 0 ndim means the shape is completely unknown.
* 2. 0 dim size means the dim size is unknown.
* We need to convert those shapes to use the numpy shape definition:
* 1. 0 ndim means it's a scalar tensor.
* 2. -1 ndim means the shape is unknown.
* 3. 0 dim size means no elements in that dimension.
* 4. -1 dim size means the dimension's size is unknown.
* so that operator's infer shape function can work in backend.
* \param shape to be converted.
* Note: It is possible that the shape to be converted is already
* numpy compatible. For example, when a subgraph operator's infer
* shape function is called from the infer shape pass of the whole
* graph, its input/output shapes have been converted to numpy
* compatible shapes.
*/
inline void ConvertToNumpyShape(mxnet::TShape* shape) {
if (shape->ndim() == 0) { // legacy shape ndim = 0 means unknown
*shape = mxnet::TShape(); // unknown shape ndim = -1
} else {
for (int j = 0; j < shape->ndim(); ++j) {
if ((*shape)[j] == 0) { // legacy shape dim_size = 0 means unknown
(*shape)[j] = -1; // unknown dim size = -1
}
}
}
}
inline void ConvertToNumpyShape(mxnet::ShapeVector* shapes) {
for (size_t i = 0; i < shapes->size(); ++i) {
ConvertToNumpyShape(&(shapes->at(i)));
}
}
/*!
* \brief This is function is used to convert shapes returned by
* the infer shape functions/pass to the legacy shape definition.
*/
inline void ConvertToLegacyShape(mxnet::TShape* shape) {
if (!mxnet::ndim_is_known(*shape)) {
*shape = mxnet::TShape(0, -1);
} else {
for (int j = 0; j < shape->ndim(); ++j) {
if (!mxnet::dim_size_is_known(*shape, j)) {
(*shape)[j] = 0;
}
}
}
}
inline void ConvertToLegacyShape(mxnet::ShapeVector* shapes) {
for (size_t i = 0; i < shapes->size(); ++i) {
ConvertToLegacyShape(&(shapes->at(i)));
}
}
void ExecuteMonInputCallback(
const nnvm::IndexedGraph &idx, const std::vector<NDArray *> &state_arrays,
size_t nid, const std::function<void(const char *, const char *, void *)>
&monitor_callback);
void ExecuteMonOutputCallback(
const nnvm::IndexedGraph &idx, const std::vector<NDArray *> &state_arrays,
size_t nid, const std::function<void(const char *, const char *, void *)>
&monitor_callback);
/*!
* \brief This is function can return the output names of a NodeEntry.
*/
static inline std::string GetOutputName(const nnvm::NodeEntry& e) {
nnvm::Symbol sym;
sym.outputs.push_back(e);
return sym.ListOutputNames()[0];
}
inline mxnet::TShape CanonicalizeAxes(const mxnet::TShape& src) {
// convert negative axes to positive values
const int ndim = src.ndim();
mxnet::TShape axes = src;
for (int i = 0; i < ndim; ++i) {
if (axes[i] < 0) {
axes[i] += ndim;
}
CHECK(axes[i] >= 0 && axes[i] < ndim) << "axes[" << i << "]="
<< axes[i] << " exceeds the range ["
<< 0 << ", " << ndim << ")";
}
return axes;
}
inline bool is_float(const int dtype) {
return dtype == mshadow::kFloat32 || dtype == mshadow::kFloat64 || dtype == mshadow::kFloat16;
}
inline int get_more_precise_type(const int type1, const int type2) {
if (type1 == type2) return type1;
if (is_float(type1) && is_float(type2)) {
if (type1 == mshadow::kFloat64 || type2 == mshadow::kFloat64) {
return mshadow::kFloat64;
}
if (type1 == mshadow::kFloat32 || type2 == mshadow::kFloat32) {
return mshadow::kFloat32;
}
return mshadow::kFloat16;
} else if (is_float(type1) || is_float(type2)) {
return is_float(type1) ? type1 : type2;
}
if (type1 == mshadow::kInt64 || type2 == mshadow::kInt64) {
return mshadow::kInt64;
}
if (type1 == mshadow::kInt32 || type2 == mshadow::kInt32) {
return mshadow::kInt32;
}
CHECK(!((type1 == mshadow::kUint8 && type2 == mshadow::kInt8) ||
(type1 == mshadow::kInt8 && type2 == mshadow::kUint8)))
<< "1 is UInt8 and 1 is Int8 should not get here";
if (type1 == mshadow::kUint8 || type2 == mshadow::kUint8) {
return mshadow::kUint8;
}
return mshadow::kInt8;
}
inline int np_binary_out_infer_type(const int type1, const int type2) {
if ((type1 == mshadow::kUint8 && type2 == mshadow::kInt8) ||
(type1 == mshadow::kInt8 && type2 == mshadow::kUint8)) {
return mshadow::kInt32;
}
return get_more_precise_type(type1, type2);
}
inline const std::string
NodeAttrsGetProfilerScope(const nnvm::NodeAttrs& attrs) {
// obtain the profiler scope name, if assigned previously
std::string profiler_scope = MXNET_STORAGE_DEFAULT_PROFILER_SCOPE_CSTR;
const std::unordered_map<std::string, std::string>& node_attrs_dict = attrs.dict;
const std::unordered_map<std::string, std::string>::const_iterator
profiler_scope_iter = node_attrs_dict.find("__profiler_scope__");
if (profiler_scope_iter != node_attrs_dict.end()) {
profiler_scope = profiler_scope_iter->second;
}
return profiler_scope;
}
} // namespace common
} // namespace mxnet
#endif // MXNET_COMMON_UTILS_H_
|
SPGrid_Threading_Helper.h | //#####################################################################
// Copyright 2013, Raj Setaluri, Eftychios Sifakis.
// This file is part of PhysBAM whose distribution is governed by the license contained in the accompanying file PHYSBAM_COPYRIGHT.txt.
//#####################################################################
// Subroutine SPGrid_Computations::Threading_Helper
//#####################################################################
#ifndef __SPGrid_Threading_Helper_h__
#define __SPGrid_Threading_Helper_h__
#include <vector>
#include <SPGrid/Core/SPGrid_Allocator.h>
#include <Threading_Tools/PTHREAD_QUEUE.h>
extern PTHREAD_QUEUE* pthread_queue;
namespace SPGrid_Computations{
using namespace SPGrid;
template<class T_STRUCT,int d,class T_OPERATION>
struct Threading_Operation_Helper:public PTHREAD_QUEUE::TASK
{
typedef std::pair<const unsigned long*,unsigned> T_BLOCK;
SPGrid_Allocator<T_STRUCT,d>& allocator;
const T_BLOCK blocks;
const T_OPERATION& operation;
Threading_Operation_Helper(SPGrid_Allocator<T_STRUCT,d>& allocator_input,const T_BLOCK& blocks_input,const T_OPERATION& operation_input)
:allocator(allocator_input),blocks(blocks_input),operation(operation_input) {}
void Run(){operation.Run(allocator,blocks);}
};
template<class T_STRUCT,int d>
class Threading_Helper
{
typedef std::pair<const unsigned long*,unsigned> T_BLOCK;
SPGrid_Allocator<T_STRUCT,d>& allocator;
const T_BLOCK& blocks;
public:
Threading_Helper(SPGrid_Allocator<T_STRUCT,d>& allocator_input,const T_BLOCK& blocks_input)
:allocator(allocator_input),blocks(blocks_input)
{}
template<class T_OPERATION>
void Run_Parallel(const T_OPERATION& operation,std::vector<T_BLOCK> list_of_partitions)
{for(int partition=0;partition<list_of_partitions.size();partition++){
Threading_Operation_Helper<T_STRUCT,d,T_OPERATION>* task=
new Threading_Operation_Helper<T_STRUCT,d,T_OPERATION>(allocator,list_of_partitions[partition],operation);
pthread_queue->Queue(task);}
pthread_queue->Wait();}
template<class T_OPERATION>
void Run_Parallel(const T_OPERATION& operation,const int number_of_partitions)
{const unsigned long* block_offsets=blocks.first;
const int size=blocks.second;
if(size<number_of_partitions*16){operation.Run(allocator,blocks);return;}
for(int partition=0;partition<number_of_partitions;partition++){
int first_index_of_partition=(size/number_of_partitions)*(partition)+std::min(size%number_of_partitions,partition);
int block_size=(size/number_of_partitions)+((partition<size%number_of_partitions)?1:0);
T_BLOCK block(block_offsets+first_index_of_partition,block_size);
Threading_Operation_Helper<T_STRUCT,d,T_OPERATION>* task=
new Threading_Operation_Helper<T_STRUCT,d,T_OPERATION>(allocator,block,operation);
pthread_queue->Queue(task);}
pthread_queue->Wait();}
};
template<class Functor>
void Run_Parallel_Blocks(const std::pair<const uint64_t*,uint32_t>& blocks,Functor functor)
{
#pragma omp parallel for
for(int b=0;b<blocks.second;b++)
functor(blocks.first[b]);
}
//#####################################################################
}
#endif
|
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