source stringlengths 3 92 | c stringlengths 26 2.25M |
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GB_unaryop__lnot_uint16_int8.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_uint16_int8
// op(A') function: GB_tran__lnot_uint16_int8
// C type: uint16_t
// A type: int8_t
// cast: uint16_t cij = (uint16_t) aij
// unaryop: cij = !(aij != 0)
#define GB_ATYPE \
int8_t
#define GB_CTYPE \
uint16_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 != 0) ;
// 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_LNOT || GxB_NO_UINT16 || GxB_NO_INT8)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__lnot_uint16_int8
(
uint16_t *restrict Cx,
const int8_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_uint16_int8
(
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
|
search.h | // -*- C++ -*-
// Copyright (C) 2007, 2008, 2009, 2010, 2011 Free Software Foundation, Inc.
//
// This file is part of the GNU ISO C++ Library. This library 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.
// This 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
// General Public License for more details.
// Under Section 7 of GPL version 3, you are granted additional
// permissions described in the GCC Runtime Library Exception, version
// 3.1, as published by the Free Software Foundation.
// You should have received a copy of the GNU General Public License and
// a copy of the GCC Runtime Library Exception along with this program;
// see the files COPYING3 and COPYING.RUNTIME respectively. If not, see
// <http://www.gnu.org/licenses/>.
/** @file parallel/search.h
* @brief Parallel implementation base for std::search() and
* std::search_n().
* This file is a GNU parallel extension to the Standard C++ Library.
*/
// Written by Felix Putze.
#ifndef _GLIBCXX_PARALLEL_SEARCH_H
#define _GLIBCXX_PARALLEL_SEARCH_H 1
#include <bits/stl_algobase.h>
#include <parallel/parallel.h>
#include <parallel/equally_split.h>
namespace __gnu_parallel
{
/**
* @brief Precalculate __advances for Knuth-Morris-Pratt algorithm.
* @param __elements Begin iterator of sequence to search for.
* @param __length Length of sequence to search for.
* @param __off Returned __offsets.
*/
template<typename _RAIter, typename _DifferenceTp>
void
__calc_borders(_RAIter __elements, _DifferenceTp __length,
_DifferenceTp* __off)
{
typedef _DifferenceTp _DifferenceType;
__off[0] = -1;
if (__length > 1)
__off[1] = 0;
_DifferenceType __k = 0;
for (_DifferenceType __j = 2; __j <= __length; __j++)
{
while ((__k >= 0) && !(__elements[__k] == __elements[__j-1]))
__k = __off[__k];
__off[__j] = ++__k;
}
}
// Generic parallel find algorithm (requires random access iterator).
/** @brief Parallel std::search.
* @param __begin1 Begin iterator of first sequence.
* @param __end1 End iterator of first sequence.
* @param __begin2 Begin iterator of second sequence.
* @param __end2 End iterator of second sequence.
* @param __pred Find predicate.
* @return Place of finding in first sequences. */
template<typename __RAIter1,
typename __RAIter2,
typename _Pred>
__RAIter1
__search_template(__RAIter1 __begin1, __RAIter1 __end1,
__RAIter2 __begin2, __RAIter2 __end2,
_Pred __pred)
{
typedef std::iterator_traits<__RAIter1> _TraitsType;
typedef typename _TraitsType::difference_type _DifferenceType;
_GLIBCXX_CALL((__end1 - __begin1) + (__end2 - __begin2));
_DifferenceType __pattern_length = __end2 - __begin2;
// Pattern too short.
if(__pattern_length <= 0)
return __end1;
// Last point to start search.
_DifferenceType __input_length = (__end1 - __begin1) - __pattern_length;
// Where is first occurrence of pattern? defaults to end.
_DifferenceType __result = (__end1 - __begin1);
_DifferenceType *__splitters;
// Pattern too long.
if (__input_length < 0)
return __end1;
omp_lock_t __result_lock;
omp_init_lock(&__result_lock);
_ThreadIndex __num_threads = std::max<_DifferenceType>
(1, std::min<_DifferenceType>(__input_length,
__get_max_threads()));
_DifferenceType __advances[__pattern_length];
__calc_borders(__begin2, __pattern_length, __advances);
# pragma omp parallel num_threads(__num_threads)
{
# pragma omp single
{
__num_threads = omp_get_num_threads();
__splitters = new _DifferenceType[__num_threads + 1];
__equally_split(__input_length, __num_threads, __splitters);
}
_ThreadIndex __iam = omp_get_thread_num();
_DifferenceType __start = __splitters[__iam],
__stop = __splitters[__iam + 1];
_DifferenceType __pos_in_pattern = 0;
bool __found_pattern = false;
while (__start <= __stop && !__found_pattern)
{
// Get new value of result.
#pragma omp flush(__result)
// No chance for this thread to find first occurrence.
if (__result < __start)
break;
while (__pred(__begin1[__start + __pos_in_pattern],
__begin2[__pos_in_pattern]))
{
++__pos_in_pattern;
if (__pos_in_pattern == __pattern_length)
{
// Found new candidate for result.
omp_set_lock(&__result_lock);
__result = std::min(__result, __start);
omp_unset_lock(&__result_lock);
__found_pattern = true;
break;
}
}
// Make safe jump.
__start += (__pos_in_pattern - __advances[__pos_in_pattern]);
__pos_in_pattern = (__advances[__pos_in_pattern] < 0
? 0 : __advances[__pos_in_pattern]);
}
} //parallel
omp_destroy_lock(&__result_lock);
delete[] __splitters;
// Return iterator on found element.
return (__begin1 + __result);
}
} // end namespace
#endif /* _GLIBCXX_PARALLEL_SEARCH_H */
|
lstm_fwd.c | #include <libxsmm.h>
#if defined(__linux__)
# include <sys/syscall.h>
# define gettid() syscall(SYS_gettid)
#else
# define gettid() libxsmm_get_tid()
#endif
#if defined(LIBXSMM_OFFLOAD_TARGET)
# pragma offload_attribute(push,target(LIBXSMM_OFFLOAD_TARGET))
#endif
#include <stdlib.h>
#include <string.h>
#include <stdio.h>
#if defined(_OPENMP)
# include <omp.h>
#endif
#include "lstm_fwd.h"
#if defined(LIBXSMM_OFFLOAD_TARGET)
# pragma offload_attribute(pop)
#endif
#define CHKERR_LIBXSMM_DNN(A) if ( A != LIBXSMM_DNN_SUCCESS ) fprintf(stderr, "%s\n", libxsmm_dnn_get_error(A) );
#if 0
# define PRINT_LAYOUT(DESC, LAYOUT) print_layout(DESC, LAYOUT)
#else
# define PRINT_LAYOUT(DESC, LAYOUT)
#endif
void print_layout(char *desc, libxsmm_dnn_tensor_datalayout *layout) {
char *dim_name[] = {"N", "H", "W", "C", "K", "R", "S", "X", "RLM", "RLK", "RLN"};
int i;
printf("%s: F:%d IF:%d TT: %d [", desc, layout->format, layout->custom_format, layout->tensor_type);
for(i = layout->num_dims - 1; i >= 0; i--) {
printf("%s:%d%s", dim_name[layout->dim_type[i]], layout->dim_size[i], i == 0 ? "" : ", ");
}
printf("]\n");
}
static void zero_buf(float* buf, size_t size) {
int i;
#if defined(_OPENMP)
# pragma omp parallel for private(i)
#endif
for (i = 0; i < (int)size; ++i) {
buf[i] = 0.0f;
}
}
void* lstm_fwd_create( int N, /* minibatch size */
int C, /* input size */
int K, /* output size */
int t, /* timesteps = 1 */
int nThreads, /* number of threads */
const float forget_bias,
const int w_in_kcck,
const float *xt,
const float *csp,
const float *hp,
const float *w,
const float *r,
const float *b,
float *cst,
float *ht,
float *it,
float *ft,
float *ot,
float *cit,
float *cot )
{
libxsmm_dnn_rnncell_desc lstmcell_desc;
libxsmm_dnn_rnncell* libxsmm_handle;
libxsmm_dnn_tensor* libxsmm_input;
libxsmm_dnn_tensor* libxsmm_cs_prev;
libxsmm_dnn_tensor* libxsmm_hidden_state_prev;
libxsmm_dnn_tensor* libxsmm_weight;
libxsmm_dnn_tensor* libxsmm_recur_weight;
libxsmm_dnn_tensor* libxsmm_bias;
libxsmm_dnn_tensor* libxsmm_cs;
libxsmm_dnn_tensor* libxsmm_hidden_state;
libxsmm_dnn_tensor* libxsmm_i;
libxsmm_dnn_tensor* libxsmm_f;
libxsmm_dnn_tensor* libxsmm_o;
libxsmm_dnn_tensor* libxsmm_ci;
libxsmm_dnn_tensor* libxsmm_co;
libxsmm_dnn_tensor_datalayout* libxsmm_layout;
libxsmm_dnn_err_t status;
if (N <= 0) {
printf("N: %d should be > 0\n", N);
}
if (C <= 0) {
printf("C: %d should be > 0\n", C);
}
if (K <= 0) {
printf("K: %d should be > 0\n", K);
}
if (xt == 0 || csp == 0 || hp == 0 || w == 0 || r == 0 || b == 0 ||
cst == 0 || ht == 0 || it == 0 || ft == 0 || ot == 0 || cit == 0 || cot == 0) {
printf("None of the pointers should be NULL::\n");
printf("x:%p\n", xt);
printf("cs_prev:%p\n", csp);
printf("h_prev:%p\n", hp);
printf("w:%p\n", w);
printf("r:%p\n", r);
printf("b:%p\n", b);
printf("cs:%p\n", cst);
printf("h:%p\n", ht);
printf("i:%p\n", it);
printf("f:%p\n", ft);
printf("o:%p\n", ot);
printf("ci:%p\n", cit);
printf("co:%p\n", cot);
}
/* setup LIBXSMM handle */
lstmcell_desc.threads = nThreads;
lstmcell_desc.N = N;
lstmcell_desc.C = C;
lstmcell_desc.K = K;
lstmcell_desc.max_T = t;
lstmcell_desc.bn = 24;
if(N % 24 == 0) lstmcell_desc.bn = 24;
else if(N % 16 == 0) lstmcell_desc.bn = 16;
else if(N % 12 == 0) lstmcell_desc.bn = 12;
else if(N % 8 == 0) lstmcell_desc.bn = 8;
else if(N % 6 == 0) lstmcell_desc.bn = 6;
lstmcell_desc.bc = 64;
lstmcell_desc.bk = 64;
lstmcell_desc.cell_type = LIBXSMM_DNN_RNNCELL_LSTM;
lstmcell_desc.datatype_in = LIBXSMM_DNN_DATATYPE_F32;
lstmcell_desc.datatype_out = LIBXSMM_DNN_DATATYPE_F32;
lstmcell_desc.buffer_format = LIBXSMM_DNN_TENSOR_FORMAT_NC;
lstmcell_desc.filter_format = (w_in_kcck ? LIBXSMM_DNN_TENSOR_FORMAT_CKPACKED : LIBXSMM_DNN_TENSOR_FORMAT_CK);
libxsmm_handle = libxsmm_dnn_create_rnncell( lstmcell_desc, &status );
CHKERR_LIBXSMM_DNN( status );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_allocate_forget_bias(libxsmm_handle, forget_bias) );
/* setup LIBXSMM buffers and filter */
libxsmm_layout = libxsmm_dnn_rnncell_create_tensor_datalayout( libxsmm_handle, LIBXSMM_DNN_RNN_REGULAR_INPUT, &status ); CHKERR_LIBXSMM_DNN( status );
PRINT_LAYOUT("Xt", libxsmm_layout);
libxsmm_input = libxsmm_dnn_link_tensor( libxsmm_layout, xt, &status ); CHKERR_LIBXSMM_DNN( status );
libxsmm_dnn_destroy_tensor_datalayout( libxsmm_layout );
libxsmm_layout = libxsmm_dnn_rnncell_create_tensor_datalayout( libxsmm_handle, LIBXSMM_DNN_RNN_REGULAR_CS_PREV, &status ); CHKERR_LIBXSMM_DNN( status );
PRINT_LAYOUT("CSP", libxsmm_layout);
libxsmm_cs_prev = libxsmm_dnn_link_tensor( libxsmm_layout, csp, &status ); CHKERR_LIBXSMM_DNN( status );
libxsmm_dnn_destroy_tensor_datalayout( libxsmm_layout );
libxsmm_layout = libxsmm_dnn_rnncell_create_tensor_datalayout( libxsmm_handle, LIBXSMM_DNN_RNN_REGULAR_HIDDEN_STATE_PREV, &status ); CHKERR_LIBXSMM_DNN( status );
PRINT_LAYOUT("HP", libxsmm_layout);
libxsmm_hidden_state_prev = libxsmm_dnn_link_tensor( libxsmm_layout, hp, &status ); CHKERR_LIBXSMM_DNN( status );
libxsmm_dnn_destroy_tensor_datalayout( libxsmm_layout );
libxsmm_layout = libxsmm_dnn_rnncell_create_tensor_datalayout( libxsmm_handle, LIBXSMM_DNN_RNN_REGULAR_WEIGHT, &status ); CHKERR_LIBXSMM_DNN( status );
PRINT_LAYOUT("W", libxsmm_layout);
libxsmm_weight = libxsmm_dnn_link_tensor( libxsmm_layout, w, &status ); CHKERR_LIBXSMM_DNN( status );
libxsmm_dnn_destroy_tensor_datalayout( libxsmm_layout );
libxsmm_layout = libxsmm_dnn_rnncell_create_tensor_datalayout( libxsmm_handle, LIBXSMM_DNN_RNN_REGULAR_RECUR_WEIGHT, &status ); CHKERR_LIBXSMM_DNN( status );
PRINT_LAYOUT("R", libxsmm_layout);
libxsmm_recur_weight = libxsmm_dnn_link_tensor( libxsmm_layout, r, &status ); CHKERR_LIBXSMM_DNN( status );
libxsmm_dnn_destroy_tensor_datalayout( libxsmm_layout );
libxsmm_layout = libxsmm_dnn_rnncell_create_tensor_datalayout( libxsmm_handle, LIBXSMM_DNN_RNN_REGULAR_BIAS, &status ); CHKERR_LIBXSMM_DNN( status );
PRINT_LAYOUT("B", libxsmm_layout);
libxsmm_bias = libxsmm_dnn_link_tensor( libxsmm_layout, b, &status ); CHKERR_LIBXSMM_DNN( status );
libxsmm_dnn_destroy_tensor_datalayout( libxsmm_layout );
libxsmm_layout = libxsmm_dnn_rnncell_create_tensor_datalayout( libxsmm_handle, LIBXSMM_DNN_RNN_REGULAR_CS, &status ); CHKERR_LIBXSMM_DNN( status );
PRINT_LAYOUT("CSt", libxsmm_layout);
libxsmm_cs = libxsmm_dnn_link_tensor( libxsmm_layout, cst, &status ); CHKERR_LIBXSMM_DNN( status );
libxsmm_dnn_destroy_tensor_datalayout( libxsmm_layout );
libxsmm_layout = libxsmm_dnn_rnncell_create_tensor_datalayout( libxsmm_handle, LIBXSMM_DNN_RNN_REGULAR_HIDDEN_STATE, &status ); CHKERR_LIBXSMM_DNN( status );
PRINT_LAYOUT("Ht", libxsmm_layout);
libxsmm_hidden_state = libxsmm_dnn_link_tensor( libxsmm_layout, ht, &status ); CHKERR_LIBXSMM_DNN( status );
libxsmm_dnn_destroy_tensor_datalayout( libxsmm_layout );
libxsmm_layout = libxsmm_dnn_rnncell_create_tensor_datalayout( libxsmm_handle, LIBXSMM_DNN_RNN_INTERNAL_I, &status ); CHKERR_LIBXSMM_DNN( status );
PRINT_LAYOUT("It", libxsmm_layout);
libxsmm_i = libxsmm_dnn_link_tensor( libxsmm_layout, it, &status ); CHKERR_LIBXSMM_DNN( status );
libxsmm_dnn_destroy_tensor_datalayout( libxsmm_layout );
libxsmm_layout = libxsmm_dnn_rnncell_create_tensor_datalayout( libxsmm_handle, LIBXSMM_DNN_RNN_INTERNAL_F, &status ); CHKERR_LIBXSMM_DNN( status );
PRINT_LAYOUT("Ft", libxsmm_layout);
libxsmm_f = libxsmm_dnn_link_tensor( libxsmm_layout, ft, &status ); CHKERR_LIBXSMM_DNN( status );
libxsmm_dnn_destroy_tensor_datalayout( libxsmm_layout );
libxsmm_layout = libxsmm_dnn_rnncell_create_tensor_datalayout( libxsmm_handle, LIBXSMM_DNN_RNN_INTERNAL_O, &status ); CHKERR_LIBXSMM_DNN( status );
PRINT_LAYOUT("Ot", libxsmm_layout);
libxsmm_o = libxsmm_dnn_link_tensor( libxsmm_layout, ot, &status ); CHKERR_LIBXSMM_DNN( status );
libxsmm_dnn_destroy_tensor_datalayout( libxsmm_layout );
libxsmm_layout = libxsmm_dnn_rnncell_create_tensor_datalayout( libxsmm_handle, LIBXSMM_DNN_RNN_INTERNAL_CI, &status ); CHKERR_LIBXSMM_DNN( status );
PRINT_LAYOUT("CIt", libxsmm_layout);
libxsmm_ci = libxsmm_dnn_link_tensor( libxsmm_layout, cit, &status ); CHKERR_LIBXSMM_DNN( status );
libxsmm_dnn_destroy_tensor_datalayout( libxsmm_layout );
libxsmm_layout = libxsmm_dnn_rnncell_create_tensor_datalayout( libxsmm_handle, LIBXSMM_DNN_RNN_INTERNAL_CO, &status ); CHKERR_LIBXSMM_DNN( status );
PRINT_LAYOUT("COt", libxsmm_layout);
libxsmm_co = libxsmm_dnn_link_tensor( libxsmm_layout, cot, &status ); CHKERR_LIBXSMM_DNN( status );
libxsmm_dnn_destroy_tensor_datalayout( libxsmm_layout );
/* bind buffers and filter to handle */
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_bind_tensor( libxsmm_handle, libxsmm_input, LIBXSMM_DNN_RNN_REGULAR_INPUT ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_bind_tensor( libxsmm_handle, libxsmm_cs_prev, LIBXSMM_DNN_RNN_REGULAR_CS_PREV ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_bind_tensor( libxsmm_handle, libxsmm_hidden_state_prev, LIBXSMM_DNN_RNN_REGULAR_HIDDEN_STATE_PREV ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_bind_tensor( libxsmm_handle, libxsmm_weight, LIBXSMM_DNN_RNN_REGULAR_WEIGHT ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_bind_tensor( libxsmm_handle, libxsmm_recur_weight, LIBXSMM_DNN_RNN_REGULAR_RECUR_WEIGHT ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_bind_tensor( libxsmm_handle, libxsmm_bias, LIBXSMM_DNN_RNN_REGULAR_BIAS ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_bind_tensor( libxsmm_handle, libxsmm_cs, LIBXSMM_DNN_RNN_REGULAR_CS ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_bind_tensor( libxsmm_handle, libxsmm_hidden_state, LIBXSMM_DNN_RNN_REGULAR_HIDDEN_STATE ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_bind_tensor( libxsmm_handle, libxsmm_i, LIBXSMM_DNN_RNN_INTERNAL_I ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_bind_tensor( libxsmm_handle, libxsmm_f, LIBXSMM_DNN_RNN_INTERNAL_F ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_bind_tensor( libxsmm_handle, libxsmm_o, LIBXSMM_DNN_RNN_INTERNAL_O ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_bind_tensor( libxsmm_handle, libxsmm_ci, LIBXSMM_DNN_RNN_INTERNAL_CI ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_bind_tensor( libxsmm_handle, libxsmm_co, LIBXSMM_DNN_RNN_INTERNAL_CO ) );
size_t scratch_size = libxsmm_dnn_rnncell_get_scratch_size( libxsmm_handle, LIBXSMM_DNN_COMPUTE_KIND_FWD, &status );
CHKERR_LIBXSMM_DNN( status );
if(scratch_size > 0) {
void *scratch = libxsmm_aligned_malloc( scratch_size, 2097152 );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_bind_scratch( libxsmm_handle, LIBXSMM_DNN_COMPUTE_KIND_FWD, scratch ) );
zero_buf( (float*)scratch, scratch_size/4 );
}
return (void*)libxsmm_handle;
}
void lstm_fwd_set_ptr( void* libxsmm_handle_,
const float forget_bias,
const int t,
const float *xt,
const float *csp,
const float *hp,
const float *w,
const float *r,
const float *b,
float *cst,
float *ht,
float *it,
float *ft,
float *ot,
float *cit,
float *cot )
{
libxsmm_dnn_err_t status = LIBXSMM_DNN_SUCCESS;
libxsmm_dnn_rnncell* handle = (libxsmm_dnn_rnncell*) libxsmm_handle_;
if (xt == 0 || csp == 0 || hp == 0 || w == 0 || r == 0 || b == 0 ||
cst == 0 || ht == 0 || it == 0 || ft == 0 || ot == 0 || cit == 0 || cot == 0) {
printf("None of the pointers should be NULL::\n");
printf("x:%p\n", xt);
printf("cs_prev:%p\n", csp);
printf("h_prev:%p\n", hp);
printf("w:%p\n", w);
printf("r:%p\n", r);
printf("b:%p\n", b);
printf("cs:%p\n", cst);
printf("h:%p\n", ht);
printf("i:%p\n", it);
printf("f:%p\n", ft);
printf("o:%p\n", ot);
printf("ci:%p\n", cit);
printf("co:%p\n", cot);
}
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_allocate_forget_bias(handle, forget_bias) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_set_sequence_length( handle, t) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_set_tensor_data_ptr(libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_REGULAR_INPUT, &status), xt) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_set_tensor_data_ptr(libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_REGULAR_CS_PREV, &status), csp) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_set_tensor_data_ptr(libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_REGULAR_HIDDEN_STATE_PREV, &status), hp) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_set_tensor_data_ptr(libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_REGULAR_WEIGHT, &status), w) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_set_tensor_data_ptr(libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_REGULAR_RECUR_WEIGHT, &status), r) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_set_tensor_data_ptr(libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_REGULAR_BIAS, &status), b) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_set_tensor_data_ptr(libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_REGULAR_CS, &status), cst) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_set_tensor_data_ptr(libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_REGULAR_HIDDEN_STATE, &status), ht) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_set_tensor_data_ptr(libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_INTERNAL_I, &status), it) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_set_tensor_data_ptr(libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_INTERNAL_F, &status), ft) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_set_tensor_data_ptr(libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_INTERNAL_O, &status), ot) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_set_tensor_data_ptr(libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_INTERNAL_CI, &status), cit) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_set_tensor_data_ptr(libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_INTERNAL_CO, &status), cot) );
}
void lstm_fwd_execute_omp( void* libxsmm_handle_)
{
#ifdef _OPENMP
libxsmm_dnn_rnncell* handle = (libxsmm_dnn_rnncell*) libxsmm_handle_;
/* run LIBXSMM LSTM FWD */
#pragma omp parallel
{
int tid = omp_get_thread_num();
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_execute_st( handle, LIBXSMM_DNN_COMPUTE_KIND_FWD, 0, tid ) );
}
#else
printf("%s:%d Shouldn't come here... exiting\n", __FILE__, __LINE__);
exit(1);
#endif
}
void lstm_fwd_execute_st( void* libxsmm_handle_, int tid )
{
libxsmm_dnn_rnncell* handle = (libxsmm_dnn_rnncell*) libxsmm_handle_;
/* run LIBXSMM LSTM FWD */
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_execute_st( handle, LIBXSMM_DNN_COMPUTE_KIND_FWD, 0, tid ) );
}
void lstm_fwd_destroy( void* libxsmm_handle_ )
{
libxsmm_dnn_rnncell* handle = (libxsmm_dnn_rnncell*) libxsmm_handle_;
libxsmm_dnn_err_t status = LIBXSMM_DNN_SUCCESS;
CHKERR_LIBXSMM_DNN( libxsmm_dnn_destroy_tensor( libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_REGULAR_INPUT, &status) ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_destroy_tensor( libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_REGULAR_CS_PREV, &status) ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_destroy_tensor( libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_REGULAR_HIDDEN_STATE_PREV, &status) ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_destroy_tensor( libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_REGULAR_WEIGHT, &status) ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_destroy_tensor( libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_REGULAR_RECUR_WEIGHT, &status) ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_destroy_tensor( libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_REGULAR_BIAS, &status) ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_destroy_tensor( libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_REGULAR_CS, &status) ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_destroy_tensor( libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_REGULAR_HIDDEN_STATE, &status) ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_destroy_tensor( libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_INTERNAL_I, &status) ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_destroy_tensor( libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_INTERNAL_F, &status) ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_destroy_tensor( libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_INTERNAL_O, &status) ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_destroy_tensor( libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_INTERNAL_CI, &status) ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_destroy_tensor( libxsmm_dnn_rnncell_get_tensor(handle, LIBXSMM_DNN_RNN_INTERNAL_CO, &status) ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_release_tensor( handle, LIBXSMM_DNN_RNN_REGULAR_INPUT ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_release_tensor( handle, LIBXSMM_DNN_RNN_REGULAR_CS_PREV ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_release_tensor( handle, LIBXSMM_DNN_RNN_REGULAR_HIDDEN_STATE_PREV ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_release_tensor( handle, LIBXSMM_DNN_RNN_REGULAR_WEIGHT ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_release_tensor( handle, LIBXSMM_DNN_RNN_REGULAR_RECUR_WEIGHT ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_release_tensor( handle, LIBXSMM_DNN_RNN_REGULAR_BIAS ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_release_tensor( handle, LIBXSMM_DNN_RNN_REGULAR_CS ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_release_tensor( handle, LIBXSMM_DNN_RNN_REGULAR_HIDDEN_STATE ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_release_tensor( handle, LIBXSMM_DNN_RNN_INTERNAL_I ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_release_tensor( handle, LIBXSMM_DNN_RNN_INTERNAL_F ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_release_tensor( handle, LIBXSMM_DNN_RNN_INTERNAL_O ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_release_tensor( handle, LIBXSMM_DNN_RNN_INTERNAL_CI ) );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_release_tensor( handle, LIBXSMM_DNN_RNN_INTERNAL_CO ) );
size_t scratch_size = libxsmm_dnn_rnncell_get_scratch_size( handle, LIBXSMM_DNN_COMPUTE_KIND_FWD, &status );
if(scratch_size > 0) {
void *scratch = libxsmm_dnn_rnncell_get_scratch_ptr( handle, /*LIBXSMM_DNN_COMPUTE_KIND_FWD,*/ &status );
CHKERR_LIBXSMM_DNN( libxsmm_dnn_rnncell_release_scratch( handle, LIBXSMM_DNN_COMPUTE_KIND_FWD ) );
if(scratch) libxsmm_free(scratch);
}
CHKERR_LIBXSMM_DNN( libxsmm_dnn_destroy_rnncell( handle ) );
}
|
GB_unaryop__lnot_fp32_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__lnot_fp32_uint32
// op(A') function: GB_tran__lnot_fp32_uint32
// C type: float
// A type: uint32_t
// cast: float cij = (float) aij
// unaryop: cij = !(aij != 0)
#define GB_ATYPE \
uint32_t
#define GB_CTYPE \
float
// 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 = !(x != 0) ;
// casting
#define GB_CASTING(z, x) \
float z = (float) 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_FP32 || GxB_NO_UINT32)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__lnot_fp32_uint32
(
float *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__lnot_fp32_uint32
(
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
|
core_zsyrk.c | /**
*
* @file
*
* PLASMA is a software package provided by:
* University of Tennessee, US,
* University of Manchester, UK.
*
* @precisions normal z -> c d s
*
**/
#include <plasma_core_blas.h>
#include "plasma_types.h"
#include "core_lapack.h"
/***************************************************************************//**
*
* @ingroup core_syrk
*
* Performs one of the symmetric rank k operations
*
* \f[ C = \alpha A \times A^T + \beta C, \f]
* or
* \f[ C = \alpha A^T \times A + \beta C, \f]
*
* where alpha and beta are scalars, C is an n-by-n symmetric
* matrix, and A is an n-by-k matrix in the first case and a k-by-n
* matrix in the second case.
*
*******************************************************************************
*
* @param[in] uplo
* - PlasmaUpper: Upper triangle of C is stored;
* - PlasmaLower: Lower triangle of C is stored.
*
* @param[in] trans
* - PlasmaNoTrans: \f[ C = \alpha A \times A^T + \beta C; \f]
* - PlasmaTrans: \f[ C = \alpha A^T \times A + \beta C. \f]
*
* @param[in] n
* The order of the matrix C. n >= 0.
*
* @param[in] k
* If trans = PlasmaNoTrans, number of columns of the A matrix;
* if trans = PlasmaTrans, number of rows of the A matrix.
*
* @param[in] alpha
* The scalar alpha.
*
* @param[in] A
* A is an lda-by-ka matrix.
* If trans = PlasmaNoTrans, ka = k;
* if trans = PlasmaTrans, ka = n.
*
* @param[in] lda
* The leading dimension of the array A.
* If trans = PlasmaNoTrans, lda >= max(1, n);
* if trans = PlasmaTrans, lda >= max(1, k).
*
* @param[in] beta
* The scalar beta.
*
* @param[in,out] C
* C is an ldc-by-n matrix.
* On exit, the uplo part of the matrix is overwritten
* by the uplo part of the updated matrix.
*
* @param[in] ldc
* The leading dimension of the array C. ldc >= max(1, n).
*
******************************************************************************/
__attribute__((weak))
void plasma_core_zsyrk(plasma_enum_t uplo, plasma_enum_t trans,
int n, int k,
plasma_complex64_t alpha, const plasma_complex64_t *A, int lda,
plasma_complex64_t beta, plasma_complex64_t *C, int ldc)
{
cblas_zsyrk(CblasColMajor,
(CBLAS_UPLO)uplo, (CBLAS_TRANSPOSE)trans,
n, k,
CBLAS_SADDR(alpha), A, lda,
CBLAS_SADDR(beta), C, ldc);
}
/******************************************************************************/
void plasma_core_omp_zsyrk(
plasma_enum_t uplo, plasma_enum_t trans,
int n, int k,
plasma_complex64_t alpha, const plasma_complex64_t *A, int lda,
plasma_complex64_t beta, plasma_complex64_t *C, int ldc,
plasma_sequence_t *sequence, plasma_request_t *request)
{
int ak;
if (trans == PlasmaNoTrans)
ak = k;
else
ak = n;
#pragma omp task depend(in:A[0:lda*ak]) \
depend(inout:C[0:ldc*n])
{
if (sequence->status == PlasmaSuccess)
plasma_core_zsyrk(uplo, trans,
n, k,
alpha, A, lda,
beta, C, ldc);
}
}
|
main.c |
#include <stdio.h>
#include <mpi.h>
#if defined(_OPENMP)
#include <omp.h>
#endif
int main(int argc, char **argv) {
MPI_Init(&argc, &argv);
#if defined(_OPENMP)
omp_set_num_threads(4);
#endif
#pragma omp parallel
{
#if defined(_OPENMP)
printf("Thread ID: %d\n", omp_get_thread_num());
#endif
}
printf("Done!\n");
MPI_Finalize();
return 0;
}
|
constitute.c | /*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% CCCC OOO N N SSSSS TTTTT IIIII TTTTT U U TTTTT EEEEE %
% C O O NN N SS T I T U U T E %
% C O O N N N ESSS T I T U U T EEE %
% C O O N NN SS T I T U U T E %
% CCCC OOO N N SSSSS T IIIII T UUU T EEEEE %
% %
% %
% MagickCore Methods to Consitute an Image %
% %
% Software Design %
% Cristy %
% October 1998 %
% %
% %
% Copyright 1999-2019 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 "MagickCore/studio.h"
#include "MagickCore/attribute.h"
#include "MagickCore/blob.h"
#include "MagickCore/blob-private.h"
#include "MagickCore/exception.h"
#include "MagickCore/exception-private.h"
#include "MagickCore/cache.h"
#include "MagickCore/client.h"
#include "MagickCore/coder-private.h"
#include "MagickCore/colorspace-private.h"
#include "MagickCore/constitute.h"
#include "MagickCore/constitute-private.h"
#include "MagickCore/delegate.h"
#include "MagickCore/geometry.h"
#include "MagickCore/identify.h"
#include "MagickCore/image-private.h"
#include "MagickCore/list.h"
#include "MagickCore/magick.h"
#include "MagickCore/memory_.h"
#include "MagickCore/monitor.h"
#include "MagickCore/monitor-private.h"
#include "MagickCore/option.h"
#include "MagickCore/pixel.h"
#include "MagickCore/pixel-accessor.h"
#include "MagickCore/policy.h"
#include "MagickCore/profile.h"
#include "MagickCore/profile-private.h"
#include "MagickCore/property.h"
#include "MagickCore/quantum.h"
#include "MagickCore/resize.h"
#include "MagickCore/resource_.h"
#include "MagickCore/semaphore.h"
#include "MagickCore/statistic.h"
#include "MagickCore/stream.h"
#include "MagickCore/string_.h"
#include "MagickCore/string-private.h"
#include "MagickCore/timer.h"
#include "MagickCore/token.h"
#include "MagickCore/transform.h"
#include "MagickCore/utility.h"
#include "MagickCore/utility-private.h"
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% C o n s t i t u t e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ConstituteImage() returns an image from the pixel data you supply.
% The pixel data must be in scanline order top-to-bottom. The data can be
% char, short int, int, float, or double. Float and double require the
% pixels to be normalized [0..1], otherwise [0..QuantumRange]. For example, to
% create a 640x480 image from unsigned red-green-blue character data, use:
%
% image = ConstituteImage(640,480,"RGB",CharPixel,pixels,&exception);
%
% The format of the ConstituteImage method is:
%
% Image *ConstituteImage(const size_t columns,const size_t rows,
% const char *map,const StorageType storage,const void *pixels,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o columns: width in pixels of the image.
%
% o rows: height in pixels of the image.
%
% o map: This string reflects the expected ordering of the pixel array.
% It can be any combination or order of R = red, G = green, B = blue,
% A = alpha (0 is transparent), O = opacity (0 is opaque), C = cyan,
% Y = yellow, M = magenta, K = black, I = intensity (for grayscale),
% P = pad.
%
% o storage: Define the data type of the pixels. Float and double types are
% expected to be normalized [0..1] otherwise [0..QuantumRange]. Choose
% from these types: CharPixel, DoublePixel, FloatPixel, IntegerPixel,
% LongPixel, QuantumPixel, or ShortPixel.
%
% o pixels: This array of values contain the pixel components as defined by
% map and type. You must preallocate this array where the expected
% length varies depending on the values of width, height, map, and type.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *ConstituteImage(const size_t columns,const size_t rows,
const char *map,const StorageType storage,const void *pixels,
ExceptionInfo *exception)
{
Image
*image;
MagickBooleanType
status;
register ssize_t
i;
size_t
length;
/*
Allocate image structure.
*/
assert(map != (const char *) NULL);
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",map);
assert(pixels != (void *) NULL);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
image=AcquireImage((ImageInfo *) NULL,exception);
if (image == (Image *) NULL)
return((Image *) NULL);
length=strlen(map);
for (i=0; i < (ssize_t) length; i++)
{
switch (map[i])
{
case 'a':
case 'A':
case 'O':
case 'o':
{
image->alpha_trait=BlendPixelTrait;
break;
}
case 'C':
case 'c':
case 'm':
case 'M':
case 'Y':
case 'y':
case 'K':
case 'k':
{
image->colorspace=CMYKColorspace;
break;
}
case 'I':
case 'i':
{
image->colorspace=GRAYColorspace;
break;
}
default:
{
if (length == 1)
image->colorspace=GRAYColorspace;
break;
}
}
}
status=SetImageExtent(image,columns,rows,exception);
if (status == MagickFalse)
return(DestroyImageList(image));
status=ResetImagePixels(image,exception);
if (status == MagickFalse)
return(DestroyImageList(image));
status=ImportImagePixels(image,0,0,columns,rows,map,storage,pixels,exception);
if (status == MagickFalse)
image=DestroyImage(image);
return(image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% P i n g I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% PingImage() returns all the properties of an image or image sequence
% except for the pixels. It is much faster and consumes far less memory
% than ReadImage(). On failure, a NULL image is returned and exception
% describes the reason for the failure.
%
% The format of the PingImage method is:
%
% Image *PingImage(const ImageInfo *image_info,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image_info: Ping the image defined by the file or filename members of
% this structure.
%
% o exception: return any errors or warnings in this structure.
%
*/
#if defined(__cplusplus) || defined(c_plusplus)
extern "C" {
#endif
static size_t PingStream(const Image *magick_unused(image),
const void *magick_unused(pixels),const size_t columns)
{
magick_unreferenced(image);
magick_unreferenced(pixels);
return(columns);
}
#if defined(__cplusplus) || defined(c_plusplus)
}
#endif
MagickExport Image *PingImage(const ImageInfo *image_info,
ExceptionInfo *exception)
{
Image
*image;
ImageInfo
*ping_info;
assert(image_info != (ImageInfo *) NULL);
assert(image_info->signature == MagickCoreSignature);
if (image_info->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",
image_info->filename);
assert(exception != (ExceptionInfo *) NULL);
ping_info=CloneImageInfo(image_info);
ping_info->ping=MagickTrue;
image=ReadStream(ping_info,&PingStream,exception);
if (image != (Image *) NULL)
{
ResetTimer(&image->timer);
if (ping_info->verbose != MagickFalse)
(void) IdentifyImage(image,stdout,MagickFalse,exception);
}
ping_info=DestroyImageInfo(ping_info);
return(image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% P i n g I m a g e s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% PingImages() pings one or more images and returns them as an image list.
%
% The format of the PingImage method is:
%
% Image *PingImages(ImageInfo *image_info,const char *filename,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image_info: the image info.
%
% o filename: the image filename.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *PingImages(ImageInfo *image_info,const char *filename,
ExceptionInfo *exception)
{
char
ping_filename[MagickPathExtent];
Image
*image,
*images;
ImageInfo
*read_info;
/*
Ping image list from a file.
*/
assert(image_info != (ImageInfo *) NULL);
assert(image_info->signature == MagickCoreSignature);
if (image_info->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",
image_info->filename);
assert(exception != (ExceptionInfo *) NULL);
(void) SetImageOption(image_info,"filename",filename);
(void) CopyMagickString(image_info->filename,filename,MagickPathExtent);
(void) InterpretImageFilename(image_info,(Image *) NULL,image_info->filename,
(int) image_info->scene,ping_filename,exception);
if (LocaleCompare(ping_filename,image_info->filename) != 0)
{
ExceptionInfo
*sans;
ssize_t
extent,
scene;
/*
Images of the form image-%d.png[1-5].
*/
read_info=CloneImageInfo(image_info);
sans=AcquireExceptionInfo();
(void) SetImageInfo(read_info,0,sans);
sans=DestroyExceptionInfo(sans);
if (read_info->number_scenes == 0)
{
read_info=DestroyImageInfo(read_info);
return(PingImage(image_info,exception));
}
(void) CopyMagickString(ping_filename,read_info->filename,
MagickPathExtent);
images=NewImageList();
extent=(ssize_t) (read_info->scene+read_info->number_scenes);
for (scene=(ssize_t) read_info->scene; scene < (ssize_t) extent; scene++)
{
(void) InterpretImageFilename(image_info,(Image *) NULL,ping_filename,
(int) scene,read_info->filename,exception);
image=PingImage(read_info,exception);
if (image == (Image *) NULL)
continue;
AppendImageToList(&images,image);
}
read_info=DestroyImageInfo(read_info);
return(images);
}
return(PingImage(image_info,exception));
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% R e a d I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ReadImage() reads an image or image sequence from a file or file handle.
% The method returns a NULL if there is a memory shortage or if the image
% cannot be read. On failure, a NULL image is returned and exception
% describes the reason for the failure.
%
% The format of the ReadImage method is:
%
% Image *ReadImage(const ImageInfo *image_info,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image_info: Read the image defined by the file or filename members of
% this structure.
%
% o exception: return any errors or warnings in this structure.
%
*/
static MagickBooleanType IsCoderAuthorized(const char *coder,
const PolicyRights rights,ExceptionInfo *exception)
{
if (IsRightsAuthorized(CoderPolicyDomain,rights,coder) == MagickFalse)
{
errno=EPERM;
(void) ThrowMagickException(exception,GetMagickModule(),PolicyError,
"NotAuthorized","`%s'",coder);
return(MagickFalse);
}
return(MagickTrue);
}
MagickExport Image *ReadImage(const ImageInfo *image_info,
ExceptionInfo *exception)
{
char
filename[MagickPathExtent],
magick[MagickPathExtent],
magick_filename[MagickPathExtent];
const char
*value;
const DelegateInfo
*delegate_info;
const MagickInfo
*magick_info;
DecodeImageHandler
*decoder;
ExceptionInfo
*sans_exception;
GeometryInfo
geometry_info;
Image
*image,
*next;
ImageInfo
*read_info;
MagickBooleanType
status;
MagickStatusType
flags;
/*
Determine image type from filename prefix or suffix (e.g. image.jpg).
*/
assert(image_info != (ImageInfo *) NULL);
assert(image_info->signature == MagickCoreSignature);
assert(image_info->filename != (char *) NULL);
if (image_info->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",
image_info->filename);
assert(exception != (ExceptionInfo *) NULL);
read_info=CloneImageInfo(image_info);
(void) CopyMagickString(magick_filename,read_info->filename,MagickPathExtent);
(void) SetImageInfo(read_info,0,exception);
(void) CopyMagickString(filename,read_info->filename,MagickPathExtent);
(void) CopyMagickString(magick,read_info->magick,MagickPathExtent);
/*
Call appropriate image reader based on image type.
*/
sans_exception=AcquireExceptionInfo();
magick_info=GetMagickInfo(read_info->magick,sans_exception);
if (sans_exception->severity == PolicyError)
magick_info=GetMagickInfo(read_info->magick,exception);
sans_exception=DestroyExceptionInfo(sans_exception);
if (magick_info != (const MagickInfo *) NULL)
{
if (GetMagickEndianSupport(magick_info) == MagickFalse)
read_info->endian=UndefinedEndian;
else
if ((image_info->endian == UndefinedEndian) &&
(GetMagickRawSupport(magick_info) != MagickFalse))
{
unsigned long
lsb_first;
lsb_first=1;
read_info->endian=(*(char *) &lsb_first) == 1 ? LSBEndian :
MSBEndian;
}
}
if ((magick_info != (const MagickInfo *) NULL) &&
(GetMagickDecoderSeekableStream(magick_info) != MagickFalse))
{
image=AcquireImage(read_info,exception);
(void) CopyMagickString(image->filename,read_info->filename,
MagickPathExtent);
status=OpenBlob(image_info,image,ReadBinaryBlobMode,exception);
if (status == MagickFalse)
{
read_info=DestroyImageInfo(read_info);
image=DestroyImage(image);
return((Image *) NULL);
}
if (IsBlobSeekable(image) == MagickFalse)
{
/*
Coder requires a seekable stream.
*/
*read_info->filename='\0';
status=ImageToFile(image,read_info->filename,exception);
if (status == MagickFalse)
{
(void) CloseBlob(image);
read_info=DestroyImageInfo(read_info);
image=DestroyImage(image);
return((Image *) NULL);
}
read_info->temporary=MagickTrue;
}
(void) CloseBlob(image);
image=DestroyImage(image);
}
image=NewImageList();
decoder=GetImageDecoder(magick_info);
if (decoder == (DecodeImageHandler *) NULL)
{
delegate_info=GetDelegateInfo(read_info->magick,(char *) NULL,exception);
if (delegate_info == (const DelegateInfo *) NULL)
{
(void) SetImageInfo(read_info,0,exception);
(void) CopyMagickString(read_info->filename,filename,
MagickPathExtent);
magick_info=GetMagickInfo(read_info->magick,exception);
decoder=GetImageDecoder(magick_info);
}
}
if (decoder != (DecodeImageHandler *) NULL)
{
/*
Call appropriate image reader based on image type.
*/
if (GetMagickDecoderThreadSupport(magick_info) == MagickFalse)
LockSemaphoreInfo(magick_info->semaphore);
status=IsCoderAuthorized(read_info->magick,ReadPolicyRights,exception);
image=(Image *) NULL;
if (status != MagickFalse)
image=decoder(read_info,exception);
if (GetMagickDecoderThreadSupport(magick_info) == MagickFalse)
UnlockSemaphoreInfo(magick_info->semaphore);
}
else
{
delegate_info=GetDelegateInfo(read_info->magick,(char *) NULL,exception);
if (delegate_info == (const DelegateInfo *) NULL)
{
(void) ThrowMagickException(exception,GetMagickModule(),
MissingDelegateError,"NoDecodeDelegateForThisImageFormat","`%s'",
read_info->magick);
if (read_info->temporary != MagickFalse)
(void) RelinquishUniqueFileResource(read_info->filename);
read_info=DestroyImageInfo(read_info);
return((Image *) NULL);
}
/*
Let our decoding delegate process the image.
*/
image=AcquireImage(read_info,exception);
if (image == (Image *) NULL)
{
read_info=DestroyImageInfo(read_info);
return((Image *) NULL);
}
(void) CopyMagickString(image->filename,read_info->filename,
MagickPathExtent);
*read_info->filename='\0';
if (GetDelegateThreadSupport(delegate_info) == MagickFalse)
LockSemaphoreInfo(delegate_info->semaphore);
status=InvokeDelegate(read_info,image,read_info->magick,(char *) NULL,
exception);
if (GetDelegateThreadSupport(delegate_info) == MagickFalse)
UnlockSemaphoreInfo(delegate_info->semaphore);
image=DestroyImageList(image);
read_info->temporary=MagickTrue;
if (status != MagickFalse)
(void) SetImageInfo(read_info,0,exception);
magick_info=GetMagickInfo(read_info->magick,exception);
decoder=GetImageDecoder(magick_info);
if (decoder == (DecodeImageHandler *) NULL)
{
if (IsPathAccessible(read_info->filename) != MagickFalse)
(void) ThrowMagickException(exception,GetMagickModule(),
MissingDelegateError,"NoDecodeDelegateForThisImageFormat","`%s'",
read_info->magick);
else
ThrowFileException(exception,FileOpenError,"UnableToOpenFile",
read_info->filename);
read_info=DestroyImageInfo(read_info);
return((Image *) NULL);
}
/*
Call appropriate image reader based on image type.
*/
if (GetMagickDecoderThreadSupport(magick_info) == MagickFalse)
LockSemaphoreInfo(magick_info->semaphore);
status=IsCoderAuthorized(read_info->magick,ReadPolicyRights,exception);
image=(Image *) NULL;
if (status != MagickFalse)
image=(decoder)(read_info,exception);
if (GetMagickDecoderThreadSupport(magick_info) == MagickFalse)
UnlockSemaphoreInfo(magick_info->semaphore);
}
if (read_info->temporary != MagickFalse)
{
(void) RelinquishUniqueFileResource(read_info->filename);
read_info->temporary=MagickFalse;
if (image != (Image *) NULL)
(void) CopyMagickString(image->filename,filename,MagickPathExtent);
}
if (image == (Image *) NULL)
{
read_info=DestroyImageInfo(read_info);
return(image);
}
if (exception->severity >= ErrorException)
(void) LogMagickEvent(ExceptionEvent,GetMagickModule(),
"Coder (%s) generated an image despite an error (%d), "
"notify the developers",image->magick,exception->severity);
if (IsBlobTemporary(image) != MagickFalse)
(void) RelinquishUniqueFileResource(read_info->filename);
if ((IsSceneGeometry(read_info->scenes,MagickFalse) != MagickFalse) &&
(GetImageListLength(image) != 1))
{
Image
*clones;
clones=CloneImages(image,read_info->scenes,exception);
if (clones != (Image *) NULL)
{
image=DestroyImageList(image);
image=GetFirstImageInList(clones);
}
}
for (next=image; next != (Image *) NULL; next=GetNextImageInList(next))
{
char
magick_path[MagickPathExtent],
*property,
timestamp[MagickPathExtent];
const char
*option;
const StringInfo
*profile;
ssize_t
option_type;
next->taint=MagickFalse;
GetPathComponent(magick_filename,MagickPath,magick_path);
if (*magick_path == '\0' && *next->magick == '\0')
(void) CopyMagickString(next->magick,magick,MagickPathExtent);
(void) CopyMagickString(next->magick_filename,magick_filename,
MagickPathExtent);
if (IsBlobTemporary(image) != MagickFalse)
(void) CopyMagickString(next->filename,filename,MagickPathExtent);
if (next->magick_columns == 0)
next->magick_columns=next->columns;
if (next->magick_rows == 0)
next->magick_rows=next->rows;
value=GetImageProperty(next,"exif:Orientation",exception);
if (value == (char *) NULL)
value=GetImageProperty(next,"tiff:Orientation",exception);
if (value != (char *) NULL)
{
next->orientation=(OrientationType) StringToLong(value);
(void) DeleteImageProperty(next,"tiff:Orientation");
(void) DeleteImageProperty(next,"exif:Orientation");
}
value=GetImageProperty(next,"exif:XResolution",exception);
if (value != (char *) NULL)
{
geometry_info.rho=next->resolution.x;
geometry_info.sigma=1.0;
flags=ParseGeometry(value,&geometry_info);
if (geometry_info.sigma != 0)
next->resolution.x=geometry_info.rho/geometry_info.sigma;
if (strchr(value,',') != (char *) NULL)
next->resolution.x=geometry_info.rho+geometry_info.sigma/1000.0;
(void) DeleteImageProperty(next,"exif:XResolution");
}
value=GetImageProperty(next,"exif:YResolution",exception);
if (value != (char *) NULL)
{
geometry_info.rho=next->resolution.y;
geometry_info.sigma=1.0;
flags=ParseGeometry(value,&geometry_info);
if (geometry_info.sigma != 0)
next->resolution.y=geometry_info.rho/geometry_info.sigma;
if (strchr(value,',') != (char *) NULL)
next->resolution.y=geometry_info.rho+geometry_info.sigma/1000.0;
(void) DeleteImageProperty(next,"exif:YResolution");
}
value=GetImageProperty(next,"exif:ResolutionUnit",exception);
if (value == (char *) NULL)
value=GetImageProperty(next,"tiff:ResolutionUnit",exception);
if (value != (char *) NULL)
{
option_type=ParseCommandOption(MagickResolutionOptions,MagickFalse,
value);
if (option_type >= 0)
next->units=(ResolutionType) option_type;
(void) DeleteImageProperty(next,"exif:ResolutionUnit");
(void) DeleteImageProperty(next,"tiff:ResolutionUnit");
}
if (next->page.width == 0)
next->page.width=next->columns;
if (next->page.height == 0)
next->page.height=next->rows;
option=GetImageOption(read_info,"caption");
if (option != (const char *) NULL)
{
property=InterpretImageProperties(read_info,next,option,exception);
(void) SetImageProperty(next,"caption",property,exception);
property=DestroyString(property);
}
option=GetImageOption(read_info,"comment");
if (option != (const char *) NULL)
{
property=InterpretImageProperties(read_info,next,option,exception);
(void) SetImageProperty(next,"comment",property,exception);
property=DestroyString(property);
}
option=GetImageOption(read_info,"label");
if (option != (const char *) NULL)
{
property=InterpretImageProperties(read_info,next,option,exception);
(void) SetImageProperty(next,"label",property,exception);
property=DestroyString(property);
}
if (LocaleCompare(next->magick,"TEXT") == 0)
(void) ParseAbsoluteGeometry("0x0+0+0",&next->page);
if ((read_info->extract != (char *) NULL) &&
(read_info->stream == (StreamHandler) NULL))
{
RectangleInfo
geometry;
SetGeometry(next,&geometry);
flags=ParseAbsoluteGeometry(read_info->extract,&geometry);
if ((next->columns != geometry.width) ||
(next->rows != geometry.height))
{
if (((flags & XValue) != 0) || ((flags & YValue) != 0))
{
Image
*crop_image;
crop_image=CropImage(next,&geometry,exception);
if (crop_image != (Image *) NULL)
ReplaceImageInList(&next,crop_image);
}
else
if (((flags & WidthValue) != 0) || ((flags & HeightValue) != 0))
{
Image
*size_image;
flags=ParseRegionGeometry(next,read_info->extract,&geometry,
exception);
size_image=ResizeImage(next,geometry.width,geometry.height,
next->filter,exception);
if (size_image != (Image *) NULL)
ReplaceImageInList(&next,size_image);
}
}
}
profile=GetImageProfile(next,"icc");
if (profile == (const StringInfo *) NULL)
profile=GetImageProfile(next,"icm");
profile=GetImageProfile(next,"iptc");
if (profile == (const StringInfo *) NULL)
profile=GetImageProfile(next,"8bim");
(void) FormatMagickTime((time_t) GetBlobProperties(next)->st_mtime,
MagickPathExtent,timestamp);
(void) SetImageProperty(next,"date:modify",timestamp,exception);
(void) FormatMagickTime((time_t) GetBlobProperties(next)->st_ctime,
MagickPathExtent,timestamp);
(void) SetImageProperty(next,"date:create",timestamp,exception);
option=GetImageOption(image_info,"delay");
if (option != (const char *) NULL)
{
flags=ParseGeometry(option,&geometry_info);
if ((flags & GreaterValue) != 0)
{
if (next->delay > (size_t) floor(geometry_info.rho+0.5))
next->delay=(size_t) floor(geometry_info.rho+0.5);
}
else
if ((flags & LessValue) != 0)
{
if (next->delay < (size_t) floor(geometry_info.rho+0.5))
next->ticks_per_second=(ssize_t) floor(geometry_info.sigma+0.5);
}
else
next->delay=(size_t) floor(geometry_info.rho+0.5);
if ((flags & SigmaValue) != 0)
next->ticks_per_second=(ssize_t) floor(geometry_info.sigma+0.5);
}
option=GetImageOption(image_info,"dispose");
if (option != (const char *) NULL)
{
option_type=ParseCommandOption(MagickDisposeOptions,MagickFalse,
option);
if (option_type >= 0)
next->dispose=(DisposeType) option_type;
}
if (read_info->verbose != MagickFalse)
(void) IdentifyImage(next,stderr,MagickFalse,exception);
image=next;
}
read_info=DestroyImageInfo(read_info);
return(GetFirstImageInList(image));
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% R e a d I m a g e s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ReadImages() reads one or more images and returns them as an image list.
%
% The format of the ReadImage method is:
%
% Image *ReadImages(ImageInfo *image_info,const char *filename,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image_info: the image info.
%
% o filename: the image filename.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *ReadImages(ImageInfo *image_info,const char *filename,
ExceptionInfo *exception)
{
char
read_filename[MagickPathExtent];
Image
*image,
*images;
ImageInfo
*read_info;
/*
Read image list from a file.
*/
assert(image_info != (ImageInfo *) NULL);
assert(image_info->signature == MagickCoreSignature);
if (image_info->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",
image_info->filename);
assert(exception != (ExceptionInfo *) NULL);
read_info=CloneImageInfo(image_info);
*read_info->magick='\0';
(void) SetImageOption(read_info,"filename",filename);
(void) CopyMagickString(read_info->filename,filename,MagickPathExtent);
(void) InterpretImageFilename(read_info,(Image *) NULL,filename,
(int) read_info->scene,read_filename,exception);
if (LocaleCompare(read_filename,read_info->filename) != 0)
{
ExceptionInfo
*sans;
ssize_t
extent,
scene;
/*
Images of the form image-%d.png[1-5].
*/
sans=AcquireExceptionInfo();
(void) SetImageInfo(read_info,0,sans);
sans=DestroyExceptionInfo(sans);
if (read_info->number_scenes != 0)
{
(void) CopyMagickString(read_filename,read_info->filename,
MagickPathExtent);
images=NewImageList();
extent=(ssize_t) (read_info->scene+read_info->number_scenes);
scene=(ssize_t) read_info->scene;
for ( ; scene < (ssize_t) extent; scene++)
{
(void) InterpretImageFilename(image_info,(Image *) NULL,
read_filename,(int) scene,read_info->filename,exception);
image=ReadImage(read_info,exception);
if (image == (Image *) NULL)
continue;
AppendImageToList(&images,image);
}
read_info=DestroyImageInfo(read_info);
return(images);
}
}
(void) CopyMagickString(read_info->filename,filename,MagickPathExtent);
image=ReadImage(read_info,exception);
read_info=DestroyImageInfo(read_info);
return(image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
+ R e a d I n l i n e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ReadInlineImage() reads a Base64-encoded inline image or image sequence.
% The method returns a NULL if there is a memory shortage or if the image
% cannot be read. On failure, a NULL image is returned and exception
% describes the reason for the failure.
%
% The format of the ReadInlineImage method is:
%
% Image *ReadInlineImage(const ImageInfo *image_info,const char *content,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image_info: the image info.
%
% o content: the image encoded in Base64.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *ReadInlineImage(const ImageInfo *image_info,
const char *content,ExceptionInfo *exception)
{
Image
*image;
ImageInfo
*read_info;
unsigned char
*blob;
size_t
length;
register const char
*p;
/*
Skip over header (e.g. data:image/gif;base64,).
*/
image=NewImageList();
for (p=content; (*p != ',') && (*p != '\0'); p++) ;
if (*p == '\0')
ThrowReaderException(CorruptImageError,"CorruptImage");
p++;
length=0;
blob=Base64Decode(p,&length);
if (length == 0)
{
blob=(unsigned char *) RelinquishMagickMemory(blob);
ThrowReaderException(CorruptImageError,"CorruptImage");
}
read_info=CloneImageInfo(image_info);
(void) SetImageInfoProgressMonitor(read_info,(MagickProgressMonitor) NULL,
(void *) NULL);
*read_info->filename='\0';
*read_info->magick='\0';
image=BlobToImage(read_info,blob,length,exception);
blob=(unsigned char *) RelinquishMagickMemory(blob);
read_info=DestroyImageInfo(read_info);
return(image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% W r i t e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% WriteImage() writes an image or an image sequence to a file or file handle.
% If writing to a file is on disk, the name is defined by the filename member
% of the image structure. WriteImage() returns MagickFalse is there is a
% memory shortage or if the image cannot be written. Check the exception
% member of image to determine the cause for any failure.
%
% The format of the WriteImage method is:
%
% MagickBooleanType WriteImage(const ImageInfo *image_info,Image *image,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image_info: the image info.
%
% o image: the image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport MagickBooleanType WriteImage(const ImageInfo *image_info,
Image *image,ExceptionInfo *exception)
{
char
filename[MagickPathExtent];
const char
*option;
const DelegateInfo
*delegate_info;
const MagickInfo
*magick_info;
EncodeImageHandler
*encoder;
ExceptionInfo
*sans_exception;
ImageInfo
*write_info;
MagickBooleanType
status,
temporary;
/*
Determine image type from filename prefix or suffix (e.g. image.jpg).
*/
assert(image_info != (ImageInfo *) NULL);
assert(image_info->signature == MagickCoreSignature);
assert(image != (Image *) NULL);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",
image_info->filename);
assert(image->signature == MagickCoreSignature);
assert(exception != (ExceptionInfo *) NULL);
sans_exception=AcquireExceptionInfo();
write_info=CloneImageInfo(image_info);
(void) CopyMagickString(write_info->filename,image->filename,
MagickPathExtent);
(void) SetImageInfo(write_info,1,sans_exception);
if (*write_info->magick == '\0')
(void) CopyMagickString(write_info->magick,image->magick,MagickPathExtent);
(void) CopyMagickString(filename,image->filename,MagickPathExtent);
(void) CopyMagickString(image->filename,write_info->filename,
MagickPathExtent);
/*
Call appropriate image writer based on image type.
*/
magick_info=GetMagickInfo(write_info->magick,sans_exception);
if (sans_exception->severity == PolicyError)
magick_info=GetMagickInfo(write_info->magick,exception);
sans_exception=DestroyExceptionInfo(sans_exception);
if (magick_info != (const MagickInfo *) NULL)
{
if (GetMagickEndianSupport(magick_info) == MagickFalse)
image->endian=UndefinedEndian;
else
if ((image_info->endian == UndefinedEndian) &&
(GetMagickRawSupport(magick_info) != MagickFalse))
{
unsigned long
lsb_first;
lsb_first=1;
image->endian=(*(char *) &lsb_first) == 1 ? LSBEndian : MSBEndian;
}
}
(void) SyncImageProfiles(image);
DisassociateImageStream(image);
option=GetImageOption(image_info,"delegate:bimodal");
if ((IsStringTrue(option) != MagickFalse) &&
(write_info->page == (char *) NULL) &&
(GetPreviousImageInList(image) == (Image *) NULL) &&
(GetNextImageInList(image) == (Image *) NULL) &&
(IsTaintImage(image) == MagickFalse) )
{
delegate_info=GetDelegateInfo(image->magick,write_info->magick,exception);
if ((delegate_info != (const DelegateInfo *) NULL) &&
(GetDelegateMode(delegate_info) == 0) &&
(IsPathAccessible(image->magick_filename) != MagickFalse))
{
/*
Process image with bi-modal delegate.
*/
(void) CopyMagickString(image->filename,image->magick_filename,
MagickPathExtent);
status=InvokeDelegate(write_info,image,image->magick,
write_info->magick,exception);
write_info=DestroyImageInfo(write_info);
(void) CopyMagickString(image->filename,filename,MagickPathExtent);
return(status);
}
}
status=MagickFalse;
temporary=MagickFalse;
if ((magick_info != (const MagickInfo *) NULL) &&
(GetMagickEncoderSeekableStream(magick_info) != MagickFalse))
{
char
image_filename[MagickPathExtent];
(void) CopyMagickString(image_filename,image->filename,MagickPathExtent);
status=OpenBlob(image_info,image,WriteBinaryBlobMode,exception);
(void) CopyMagickString(image->filename, image_filename,MagickPathExtent);
if (status != MagickFalse)
{
if (IsBlobSeekable(image) == MagickFalse)
{
/*
A seekable stream is required by the encoder.
*/
write_info->adjoin=MagickTrue;
(void) CopyMagickString(write_info->filename,image->filename,
MagickPathExtent);
(void) AcquireUniqueFilename(image->filename);
temporary=MagickTrue;
}
(void) CloseBlob(image);
}
}
encoder=GetImageEncoder(magick_info);
if (encoder != (EncodeImageHandler *) NULL)
{
/*
Call appropriate image writer based on image type.
*/
if (GetMagickEncoderThreadSupport(magick_info) == MagickFalse)
LockSemaphoreInfo(magick_info->semaphore);
status=IsCoderAuthorized(write_info->magick,WritePolicyRights,exception);
if (status != MagickFalse)
status=encoder(write_info,image,exception);
if (GetMagickEncoderThreadSupport(magick_info) == MagickFalse)
UnlockSemaphoreInfo(magick_info->semaphore);
}
else
{
delegate_info=GetDelegateInfo((char *) NULL,write_info->magick,exception);
if (delegate_info != (DelegateInfo *) NULL)
{
/*
Process the image with delegate.
*/
*write_info->filename='\0';
if (GetDelegateThreadSupport(delegate_info) == MagickFalse)
LockSemaphoreInfo(delegate_info->semaphore);
status=InvokeDelegate(write_info,image,(char *) NULL,
write_info->magick,exception);
if (GetDelegateThreadSupport(delegate_info) == MagickFalse)
UnlockSemaphoreInfo(delegate_info->semaphore);
(void) CopyMagickString(image->filename,filename,MagickPathExtent);
}
else
{
sans_exception=AcquireExceptionInfo();
magick_info=GetMagickInfo(write_info->magick,sans_exception);
if (sans_exception->severity == PolicyError)
magick_info=GetMagickInfo(write_info->magick,exception);
sans_exception=DestroyExceptionInfo(sans_exception);
if ((write_info->affirm == MagickFalse) &&
(magick_info == (const MagickInfo *) NULL))
{
(void) CopyMagickString(write_info->magick,image->magick,
MagickPathExtent);
magick_info=GetMagickInfo(write_info->magick,exception);
}
encoder=GetImageEncoder(magick_info);
if (encoder == (EncodeImageHandler *) NULL)
{
char
extension[MagickPathExtent];
GetPathComponent(image->filename,ExtensionPath,extension);
if (*extension != '\0')
magick_info=GetMagickInfo(extension,exception);
else
magick_info=GetMagickInfo(image->magick,exception);
(void) CopyMagickString(image->filename,filename,
MagickPathExtent);
encoder=GetImageEncoder(magick_info);
}
if (encoder == (EncodeImageHandler *) NULL)
{
magick_info=GetMagickInfo(image->magick,exception);
encoder=GetImageEncoder(magick_info);
if (encoder == (EncodeImageHandler *) NULL)
(void) ThrowMagickException(exception,GetMagickModule(),
MissingDelegateError,"NoEncodeDelegateForThisImageFormat",
"`%s'",write_info->magick);
}
if (encoder != (EncodeImageHandler *) NULL)
{
/*
Call appropriate image writer based on image type.
*/
if (GetMagickEncoderThreadSupport(magick_info) == MagickFalse)
LockSemaphoreInfo(magick_info->semaphore);
status=IsCoderAuthorized(write_info->magick,WritePolicyRights,
exception);
if (status != MagickFalse)
status=encoder(write_info,image,exception);
if (GetMagickEncoderThreadSupport(magick_info) == MagickFalse)
UnlockSemaphoreInfo(magick_info->semaphore);
}
}
}
if (temporary != MagickFalse)
{
/*
Copy temporary image file to permanent.
*/
status=OpenBlob(write_info,image,ReadBinaryBlobMode,exception);
if (status != MagickFalse)
{
(void) RelinquishUniqueFileResource(write_info->filename);
status=ImageToFile(image,write_info->filename,exception);
}
(void) CloseBlob(image);
(void) RelinquishUniqueFileResource(image->filename);
(void) CopyMagickString(image->filename,write_info->filename,
MagickPathExtent);
}
if ((LocaleCompare(write_info->magick,"info") != 0) &&
(write_info->verbose != MagickFalse))
(void) IdentifyImage(image,stdout,MagickFalse,exception);
write_info=DestroyImageInfo(write_info);
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% W r i t e I m a g e s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% WriteImages() writes an image sequence into one or more files. While
% WriteImage() can write an image sequence, it is limited to writing
% the sequence into a single file using a format which supports multiple
% frames. WriteImages(), however, does not have this limitation, instead it
% generates multiple output files if necessary (or when requested). When
% ImageInfo's adjoin flag is set to MagickFalse, the file name is expected
% to include a printf-style formatting string for the frame number (e.g.
% "image%02d.png").
%
% The format of the WriteImages method is:
%
% MagickBooleanType WriteImages(const ImageInfo *image_info,Image *images,
% const char *filename,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image_info: the image info.
%
% o images: the image list.
%
% o filename: the image filename.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport MagickBooleanType WriteImages(const ImageInfo *image_info,
Image *images,const char *filename,ExceptionInfo *exception)
{
#define WriteImageTag "Write/Image"
ExceptionInfo
*sans_exception;
ImageInfo
*write_info;
MagickBooleanType
proceed;
MagickOffsetType
progress;
MagickProgressMonitor
progress_monitor;
MagickSizeType
number_images;
MagickStatusType
status;
register Image
*p;
assert(image_info != (const ImageInfo *) NULL);
assert(image_info->signature == MagickCoreSignature);
assert(images != (Image *) NULL);
assert(images->signature == MagickCoreSignature);
if (images->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",images->filename);
assert(exception != (ExceptionInfo *) NULL);
write_info=CloneImageInfo(image_info);
*write_info->magick='\0';
images=GetFirstImageInList(images);
if (filename != (const char *) NULL)
for (p=images; p != (Image *) NULL; p=GetNextImageInList(p))
(void) CopyMagickString(p->filename,filename,MagickPathExtent);
(void) CopyMagickString(write_info->filename,images->filename,
MagickPathExtent);
sans_exception=AcquireExceptionInfo();
(void) SetImageInfo(write_info,(unsigned int) GetImageListLength(images),
sans_exception);
sans_exception=DestroyExceptionInfo(sans_exception);
if (*write_info->magick == '\0')
(void) CopyMagickString(write_info->magick,images->magick,MagickPathExtent);
p=images;
for ( ; GetNextImageInList(p) != (Image *) NULL; p=GetNextImageInList(p))
{
register Image
*next;
next=GetNextImageInList(p);
if (next == (Image *) NULL)
break;
if (p->scene >= next->scene)
{
register ssize_t
i;
/*
Generate consistent scene numbers.
*/
i=(ssize_t) images->scene;
for (p=images; p != (Image *) NULL; p=GetNextImageInList(p))
p->scene=(size_t) i++;
break;
}
}
/*
Write images.
*/
status=MagickTrue;
progress_monitor=(MagickProgressMonitor) NULL;
progress=0;
number_images=GetImageListLength(images);
for (p=images; p != (Image *) NULL; p=GetNextImageInList(p))
{
if (number_images != 1)
progress_monitor=SetImageProgressMonitor(p,(MagickProgressMonitor) NULL,
p->client_data);
status&=WriteImage(write_info,p,exception);
if (number_images != 1)
(void) SetImageProgressMonitor(p,progress_monitor,p->client_data);
if (write_info->adjoin != MagickFalse)
break;
if (number_images != 1)
{
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(p,WriteImageTag,progress,number_images);
if (proceed == MagickFalse)
break;
}
}
write_info=DestroyImageInfo(write_info);
return(status != 0 ? MagickTrue : MagickFalse);
}
|
omp_for_schedule_static_3.c | <ompts:test>
<ompts:testdescription>Test which checks the static option of the omp for schedule directive considering the specifications for the chunk distribution of several loop regions is the same as specified in the Open MP standard version 3.0.</ompts:testdescription>
<ompts:ompversion>3.0</ompts:ompversion>
<ompts:directive>omp for schedule(static)</ompts:directive>
<ompts:dependences>omp for nowait,omp flush,omp critical,omp single</ompts:dependences>
<ompts:testcode>
#include <stdio.h>
#include <unistd.h>
#include <stdlib.h>
#include "omp_testsuite.h"
#include "omp_my_sleep.h"
#define NUMBER_OF_THREADS 10
#define CFSMAX_SIZE 1000
#define MAX_TIME 0.01
#ifdef SLEEPTIME
#undef SLEEPTIME
#define SLEEPTIME 0.0005
#endif
#define VERBOSE 0
int <ompts:testcode:functionname>omp_for_schedule_static_3</ompts:testcode:functionname> (FILE * logFile)
{
int threads;
int i,lasttid;
<ompts:orphan:vars>
int * tids;
int * tids2;
int notout;
int maxiter;
int chunk_size;
</ompts:orphan:vars>
int counter = 0;
int tmp_count=1;
int lastthreadsstarttid = -1;
int result = 1;
chunk_size = 7;
tids = (int *) malloc (sizeof (int) * (CFSMAX_SIZE + 1));
notout = 1;
maxiter = 0;
#pragma omp parallel shared(tids,counter)
{ /* begin of parallel*/
#pragma omp single
{
threads = omp_get_num_threads ();
} /* end of single */
} /* end of parallel */
if (threads < 2)
{
printf ("This test only works with at least two threads");
fprintf (logFile,"This test only works with at least two threads");
return 0;
}
else
{
fprintf (logFile,"Using an internal count of %d\nUsing a specified chunksize of %d\n", CFSMAX_SIZE, chunk_size);
tids[CFSMAX_SIZE] = -1; /* setting endflag */
#pragma omp parallel shared(tids)
{ /* begin of parallel */
<ompts:orphan>
double count;
int tid;
int j;
tid = omp_get_thread_num ();
#pragma omp for nowait <ompts:check>schedule(static,chunk_size)</ompts:check>
for(j = 0; j < CFSMAX_SIZE; ++j)
{
count = 0.;
#pragma omp flush(maxiter)
if (j > maxiter)
{
#pragma omp critical
{
maxiter = j;
} /* end of critical */
}
/*printf ("thread %d sleeping\n", tid);*/
while (notout && (count < MAX_TIME) && (maxiter == j))
{
#pragma omp flush(maxiter,notout)
my_sleep (SLEEPTIME);
count += SLEEPTIME;
printf(".");
}
#ifdef VERBOSE
if (count > 0.) printf(" waited %lf s\n", count);
#endif
/*printf ("thread %d awake\n", tid);*/
tids[j] = tid;
#ifdef VERBOSE
printf("%d finished by %d\n",j,tid);
#endif
} /* end of for */
notout = 0;
#pragma omp flush(maxiter,notout)
</ompts:orphan>
} /* end of parallel */
/**** analysing the data in array tids ****/
lasttid = tids[0];
tmp_count = 0;
for (i = 0; i < CFSMAX_SIZE + 1; ++i)
{
/* If the work was done by the same thread increase tmp_count by one. */
if (tids[i] == lasttid) {
tmp_count++;
#ifdef VERBOSE
fprintf (logFile, "%d: %d \n", i, tids[i]);
#endif
continue;
}
/* Check if the next thread had has the right thread number. When finding
* threadnumber -1 the end should be reached.
*/
if (tids[i] == (lasttid + 1) % threads || tids[i] == -1) {
/* checking for the right chunk size */
if (tmp_count == chunk_size) {
tmp_count = 1;
lasttid = tids[i];
#ifdef VERBOSE
fprintf (logFile, "OK\n");
#endif
}
/* If the chunk size was wrong, check if the end was reached */
else {
if (tids[i] == -1) {
if (i == CFSMAX_SIZE) {
fprintf (logFile, "Last thread had chunk size %d\n", tmp_count);
break;
}
else {
fprintf (logFile, "ERROR: Last thread (thread with number -1) was found before the end.\n");
result = 0;
}
}
else {
fprintf (logFile, "ERROR: chunk size was %d. (assigned was %d)\n", tmp_count, chunk_size);
result = 0;
}
}
}
else {
fprintf(logFile, "ERROR: Found thread with number %d (should be inbetween 0 and %d).", tids[i], threads - 1);
result = 0;
}
#ifdef VERBOSE
fprintf (logFile, "%d: %d \n", i, tids[i]);
#endif
}
}
/* Now we check if several loop regions in one parallel region have the same
* logical assignement of chunks to threads.
* We use the nowait clause to increase the probability to get an error. */
/* First we allocate some more memmory */
free (tids);
tids = (int *) malloc (sizeof (int) * LOOPCOUNT);
tids2 = (int *) malloc (sizeof (int) * LOOPCOUNT);
#pragma omp parallel
{
<ompts:orphan>
{
int n;
#pragma omp for <ompts:check>schedule(static)</ompts:check> nowait
for (n = 0; n < LOOPCOUNT; n++)
{
if (LOOPCOUNT == n + 1 )
my_sleep(SLEEPTIME);
tids[n] = omp_get_thread_num();
}
}
</ompts:orphan>
<ompts:orphan>
{
int m;
#pragma omp for <ompts:check>schedule(static)</ompts:check> nowait
for (m = 1; m <= LOOPCOUNT; m++)
{
tids2[m-1] = omp_get_thread_num();
}
}
</ompts:orphan>
}
for (i = 0; i < LOOPCOUNT; i++)
if (tids[i] != tids2[i]) {
fprintf (logFile, "Chunk no. %d was assigned once to thread %d and later to thread %d.\n", i, tids[i],tids2[i]);
result = 0;
}
free (tids);
free (tids2);
return result;
}
</ompts:testcode>
</ompts:test>
|
Interp1PrimFifthOrderCRWENOChar.c | /*! @file Interp1PrimFifthOrderCRWENOChar.c
@author Debojyoti Ghosh
@brief Characteristic-based CRWENO5 Scheme
*/
#include <stdio.h>
#include <basic.h>
#include <arrayfunctions.h>
#include <mathfunctions.h>
#include <interpolation.h>
#include <tridiagLU.h>
#include <mpivars.h>
#include <hypar.h>
#ifdef with_omp
#include <omp.h>
#endif
#undef _MINIMUM_GHOSTS_
/*! \def _MINIMUM_GHOSTS_
* Minimum number of ghost points required for this interpolation
* method.
*/
#define _MINIMUM_GHOSTS_ 3
/*! @brief 5th order CRWENO reconstruction (characteristic-based) on a uniform grid
Computes the interpolated values of the first primitive of a function \f${\bf f}\left({\bf u}\right)\f$
at the interfaces from the cell-centered values of the function using the fifth order CRWENO scheme on a
uniform grid. The first primitive is defined as a function \f${\bf h}\left({\bf u}\right)\f$ that satisfies:
\f{equation}{
{\bf f}\left({\bf u}\left(x\right)\right) = \frac{1}{\Delta x} \int_{x-\Delta x/2}^{x+\Delta x/2} {\bf h}\left({\bf u}\left(\zeta\right)\right)d\zeta,
\f}
where \f$x\f$ is the spatial coordinate along the dimension of the interpolation. This function computes the 5th order CRWENO numerical approximation
\f$\hat{\bf f}_{j+1/2} \approx {\bf h}_{j+1/2}\f$ as the convex combination of three 3rd order methods:
\f{align}{
&\ \omega_1\ \times\ \left[ \frac{2}{3}\hat{\alpha}^k_{j-1/2} + \frac{1}{3}\hat{\alpha}^k_{j+1/2} = \frac{1}{6} \left( f_{j-1} + 5f_j \right) \right]\\
+ &\ \omega_2\ \times\ \left[ \frac{1}{3}\hat{\alpha}^k_{j-1/2}+\frac{2}{3}\hat{\alpha}^k_{j+1/2} = \frac{1}{6} \left( 5f_j + f_{j+1} \right) \right] \\
+ &\ \omega_3\ \times\ \left[ \frac{2}{3}\hat{\alpha}^k_{j+1/2} + \frac{1}{3}\hat{\alpha}^k_{j+3/2} = \frac{1}{6} \left( f_j + 5f_{j+1} \right) \right] \\
\Rightarrow &\ \left(\frac{2}{3}\omega_1+\frac{1}{3}\omega_2\right)\hat{\alpha}^k_{j-1/2} + \left[\frac{1}{3}\omega_1+\frac{2}{3}(\omega_2+\omega_3)\right]\hat{\alpha}^k_{j+1/2} + \frac{1}{3}\omega_3\hat{\alpha}^k_{j+3/2} = \frac{\omega_1}{6}{\alpha}^k_{j-1} + \frac{5(\omega_1+\omega_2)+\omega_3}{6}{\alpha}^k_j + \frac{\omega_2+5\omega_3}{6}{\alpha}^k_{j+1},
\f}
where
\f{equation}{
\alpha^k = {\bf l}_k \cdot {\bf f},\ k=1,\cdots,n
\f}
is the \f$k\f$-th characteristic quantity, and \f${\bf l}_k\f$ is the \f$k\f$-th left eigenvector, \f${\bf r}_k\f$ is the \f$k\f$-th right eigenvector, and \f$n\f$ is #HyPar::nvars. The nonlinear weights \f$\omega_k; k=1,2,3\f$ are the WENO weights computed in WENOFifthOrderCalculateWeightsChar(). The resulting block tridiagonal system is solved using blocktridiagLU() (see also #TridiagLU, tridiagLU.h). The final interpolated function is computed from the interpolated characteristic quantities as:
\f{equation}{
\hat{\bf f}_{j+1/2} = \sum_{k=1}^n \alpha^k_{j+1/2} {\bf r}_k
\f}
\b Implementation \b Notes:
+ This method assumes a uniform grid in the spatial dimension corresponding to the interpolation.
+ The method described above corresponds to a left-biased interpolation. The corresponding right-biased
interpolation can be obtained by reflecting the equations about interface j+1/2.
+ The left and right eigenvectors are computed at an averaged quantity at j+1/2. Thus, this function requires
functions to compute the average state, and the left and right eigenvectors. These are provided by the physical
model through
- #HyPar::GetLeftEigenvectors()
- #HyPar::GetRightEigenvectors()
- #HyPar::AveragingFunction()
If these functions are not provided by the physical model, then a characteristic-based interpolation cannot be used.
+ The function computes the interpolant for the entire grid in one call. It loops over all the grid lines along the interpolation direction
and carries out the 1D interpolation along these grid lines.
+ Location of cell-centers and cell interfaces along the spatial dimension of the interpolation is shown in the following figure:
@image html chap1_1Ddomain.png
@image latex chap1_1Ddomain.eps width=0.9\textwidth
\b Function \b arguments:
Argument | Type | Explanation
--------- | --------- | ---------------------------------------------
fI | double* | Array to hold the computed interpolant at the grid interfaces. This array must have the same layout as the solution, but with \b no \b ghost \b points. Its size should be the same as u in all dimensions, except dir (the dimension along which to interpolate) along which it should be larger by 1 (number of interfaces is 1 more than the number of interior cell centers).
fC | double* | Array with the cell-centered values of the flux function \f${\bf f}\left({\bf u}\right)\f$. This array must have the same layout and size as the solution, \b with \b ghost \b points.
u | double* | The solution array \f${\bf u}\f$ (with ghost points). If the interpolation is characteristic based, this is needed to compute the eigendecomposition. For a multidimensional problem, the layout is as follows: u is a contiguous 1D array of size (nvars*dim[0]*dim[1]*...*dim[D-1]) corresponding to the multi-dimensional solution, with the following ordering - nvars, dim[0], dim[1], ..., dim[D-1], where nvars is the number of solution components (#HyPar::nvars), dim is the local size (#HyPar::dim_local), D is the number of spatial dimensions.
x | double* | The grid array (with ghost points). This is used only by non-uniform-grid interpolation methods. For multidimensional problems, the layout is as follows: x is a contiguous 1D array of size (dim[0]+dim[1]+...+dim[D-1]), with the spatial coordinates along dim[0] stored from 0,...,dim[0]-1, the spatial coordinates along dim[1] stored along dim[0],...,dim[0]+dim[1]-1, and so forth.
upw | int | Upwinding direction: if positive, a left-biased interpolant will be computed; if negative, a right-biased interpolant will be computed. If the interpolation method is central, then this has no effect.
dir | int | Spatial dimension along which to interpolate (eg: 0 for 1D; 0 or 1 for 2D; 0,1 or 2 for 3D)
s | void* | Solver object of type #HyPar: the following variables are needed - #HyPar::ghosts, #HyPar::ndims, #HyPar::nvars, #HyPar::dim_local.
m | void* | MPI object of type #MPIVariables: this is needed only by compact interpolation method that need to solve a global implicit system across MPI ranks.
uflag | int | A flag indicating if the function being interpolated \f${\bf f}\f$ is the solution itself \f${\bf u}\f$ (if 1, \f${\bf f}\left({\bf u}\right) \equiv {\bf u}\f$).
\b Reference:
+ Ghosh, D., Baeder, J. D., Compact Reconstruction Schemes with Weighted ENO Limiting
for Hyperbolic Conservation Laws, SIAM Journal on Scientific Computing, 34 (3), 2012, A1678–A1706,
http://dx.doi.org/10.1137/110857659
+ Ghosh, D., Constantinescu, E. M., Brown, J., Efficient Implementation of Nonlinear Compact Schemes on Massively Parallel Platforms,
SIAM Journal on Scientific Computing, 37 (3), 2015, C354–C383,
http://dx.doi.org/10.1137/140989261
*/
int Interp1PrimFifthOrderCRWENOChar(
double *fI, /*!< Array of interpolated function values at the interfaces */
double *fC, /*!< Array of cell-centered values of the function \f${\bf f}\left({\bf u}\right)\f$ */
double *u, /*!< Array of cell-centered values of the solution \f${\bf u}\f$ */
double *x, /*!< Grid coordinates */
int upw, /*!< Upwind direction (left or right biased) */
int dir, /*!< Spatial dimension along which to interpolation */
void *s, /*!< Object of type #HyPar containing solver-related variables */
void *m, /*!< Object of type #MPIVariables containing MPI-related variables */
int uflag /*!< Flag to indicate if \f$f(u) \equiv u\f$, i.e, if the solution is being reconstructed */
)
{
HyPar *solver = (HyPar*) s;
MPIVariables *mpi = (MPIVariables*) m;
CompactScheme *compact= (CompactScheme*) solver->compact;
WENOParameters *weno = (WENOParameters*) solver->interp;
TridiagLU *lu = (TridiagLU*) solver->lusolver;
int sys,Nsys,d,v,k;
_DECLARE_IERR_;
int ghosts = solver->ghosts;
int ndims = solver->ndims;
int nvars = solver->nvars;
int *dim = solver->dim_local;
/* define some constants */
static const double one_third = 1.0/3.0;
static const double one_sixth = 1.0/6.0;
double *ww1, *ww2, *ww3;
ww1 = weno->w1 + (upw < 0 ? 2*weno->size : 0) + (uflag ? weno->size : 0) + weno->offset[dir];
ww2 = weno->w2 + (upw < 0 ? 2*weno->size : 0) + (uflag ? weno->size : 0) + weno->offset[dir];
ww3 = weno->w3 + (upw < 0 ? 2*weno->size : 0) + (uflag ? weno->size : 0) + weno->offset[dir];
/* create index and bounds for the outer loop, i.e., to loop over all 1D lines along
dimension "dir" */
int indexC[ndims], indexI[ndims], index_outer[ndims], bounds_outer[ndims], bounds_inter[ndims];
_ArrayCopy1D_(dim,bounds_outer,ndims); bounds_outer[dir] = 1;
_ArrayCopy1D_(dim,bounds_inter,ndims); bounds_inter[dir] += 1;
/* calculate total number of block tridiagonal systems to solve */
_ArrayProduct1D_(bounds_outer,ndims,Nsys);
/* allocate arrays for the averaged state, eigenvectors and characteristic interpolated f */
double R[nvars*nvars], L[nvars*nvars], uavg[nvars];
/* Allocate arrays for tridiagonal system */
double *A = compact->A;
double *B = compact->B;
double *C = compact->C;
double *F = compact->R;
#pragma omp parallel for schedule(auto) default(shared) private(sys,d,v,k,R,L,uavg,index_outer,indexC,indexI)
for (sys=0; sys<Nsys; sys++) {
_ArrayIndexnD_(ndims,sys,bounds_outer,index_outer,0);
_ArrayCopy1D_(index_outer,indexC,ndims);
_ArrayCopy1D_(index_outer,indexI,ndims);
for (indexI[dir] = 0; indexI[dir] < dim[dir]+1; indexI[dir]++) {
int qm1,qm2,qm3,qp1,qp2;
if (upw > 0) {
indexC[dir] = indexI[dir]-3; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qm3);
indexC[dir] = indexI[dir]-2; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qm2);
indexC[dir] = indexI[dir]-1; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qm1);
indexC[dir] = indexI[dir] ; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qp1);
indexC[dir] = indexI[dir]+1; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qp2);
} else {
indexC[dir] = indexI[dir]+2; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qm3);
indexC[dir] = indexI[dir]+1; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qm2);
indexC[dir] = indexI[dir] ; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qm1);
indexC[dir] = indexI[dir]-1; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qp1);
indexC[dir] = indexI[dir]-2; _ArrayIndex1D_(ndims,dim,indexC,ghosts,qp2);
}
int p; /* 1D index of the interface */
_ArrayIndex1D_(ndims,bounds_inter,indexI,0,p);
/* find averaged state at this interface */
IERR solver->AveragingFunction(uavg,&u[nvars*qm1],&u[nvars*qp1],solver->physics); CHECKERR(ierr);
/* Get the left and right eigenvectors */
IERR solver->GetLeftEigenvectors (uavg,L,solver->physics,dir); CHECKERR(ierr);
IERR solver->GetRightEigenvectors (uavg,R,solver->physics,dir); CHECKERR(ierr);
for (v=0; v<nvars; v++) {
/* calculate the characteristic flux components along this characteristic */
double fm3, fm2, fm1, fp1, fp2;
fm3 = fm2 = fm1 = fp1 = fp2 = 0;
for (k = 0; k < nvars; k++) {
fm3 += L[v*nvars+k] * fC[qm3*nvars+k];
fm2 += L[v*nvars+k] * fC[qm2*nvars+k];
fm1 += L[v*nvars+k] * fC[qm1*nvars+k];
fp1 += L[v*nvars+k] * fC[qp1*nvars+k];
fp2 += L[v*nvars+k] * fC[qp2*nvars+k];
}
/* Candidate stencils and their optimal weights*/
double f1, f2, f3;
if ( ((mpi->ip[dir] == 0 ) && (indexI[dir] == 0 ))
|| ((mpi->ip[dir] == mpi->iproc[dir]-1) && (indexI[dir] == dim[dir])) ) {
/* Use WENO5 at the physical boundaries */
f1 = (2*one_sixth)*fm3 - (7.0*one_sixth)*fm2 + (11.0*one_sixth)*fm1;
f2 = (-one_sixth)*fm2 + (5.0*one_sixth)*fm1 + (2*one_sixth)*fp1;
f3 = (2*one_sixth)*fm1 + (5*one_sixth)*fp1 - (one_sixth)*fp2;
} else {
/* CRWENO5 at the interior points */
f1 = (one_sixth) * (fm2 + 5*fm1);
f2 = (one_sixth) * (5*fm1 + fp1);
f3 = (one_sixth) * (fm1 + 5*fp1);
}
/* calculate WENO weights */
double w1,w2,w3;
w1 = *(ww1+p*nvars+v);
w2 = *(ww2+p*nvars+v);
w3 = *(ww3+p*nvars+v);
if ( ((mpi->ip[dir] == 0 ) && (indexI[dir] == 0 ))
|| ((mpi->ip[dir] == mpi->iproc[dir]-1) && (indexI[dir] == dim[dir])) ) {
for (k=0; k<nvars; k++) {
A[(Nsys*indexI[dir]+sys)*nvars*nvars+v*nvars+k] = 0.0;
C[(Nsys*indexI[dir]+sys)*nvars*nvars+v*nvars+k] = 0.0;
B[(Nsys*indexI[dir]+sys)*nvars*nvars+v*nvars+k] = L[v*nvars+k];
}
} else {
if (upw > 0) {
for (k=0; k<nvars; k++) {
A[(Nsys*indexI[dir]+sys)*nvars*nvars+v*nvars+k] = ((2*one_third)*w1 + (one_third)*w2) * L[v*nvars+k];
B[(Nsys*indexI[dir]+sys)*nvars*nvars+v*nvars+k] = ((one_third)*w1 + (2*one_third)*(w2+w3)) * L[v*nvars+k];
C[(Nsys*indexI[dir]+sys)*nvars*nvars+v*nvars+k] = ((one_third)*w3) * L[v*nvars+k];
}
} else {
for (k=0; k<nvars; k++) {
C[(Nsys*indexI[dir]+sys)*nvars*nvars+v*nvars+k] = ((2*one_third)*w1 + (one_third)*w2) * L[v*nvars+k];
B[(Nsys*indexI[dir]+sys)*nvars*nvars+v*nvars+k] = ((one_third)*w1 + (2*one_third)*(w2+w3)) * L[v*nvars+k];
A[(Nsys*indexI[dir]+sys)*nvars*nvars+v*nvars+k] = ((one_third)*w3) * L[v*nvars+k];
}
}
}
F[(Nsys*indexI[dir]+sys)*nvars+v] = w1*f1 + w2*f2 + w3*f3;
}
}
}
#ifdef serial
/* Solve the tridiagonal system */
IERR blocktridiagLU(A,B,C,F,dim[dir]+1,Nsys,nvars,lu,NULL); CHECKERR(ierr);
#else
/* Solve the tridiagonal system */
/* all processes except the last will solve without the last interface to avoid overlap */
if (mpi->ip[dir] != mpi->iproc[dir]-1) {
IERR blocktridiagLU(A,B,C,F,dim[dir] ,Nsys,nvars,lu,&mpi->comm[dir]); CHECKERR(ierr);
} else {
IERR blocktridiagLU(A,B,C,F,dim[dir]+1,Nsys,nvars,lu,&mpi->comm[dir]); CHECKERR(ierr);
}
/* Now get the solution to the last interface from the next proc */
double *sendbuf = compact->sendbuf;
double *recvbuf = compact->recvbuf;
MPI_Request req[2] = {MPI_REQUEST_NULL,MPI_REQUEST_NULL};
if (mpi->ip[dir]) for (d=0; d<Nsys*nvars; d++) sendbuf[d] = F[d];
if (mpi->ip[dir] != mpi->iproc[dir]-1) MPI_Irecv(recvbuf,Nsys*nvars,MPI_DOUBLE,mpi->ip[dir]+1,214,mpi->comm[dir],&req[0]);
if (mpi->ip[dir]) MPI_Isend(sendbuf,Nsys*nvars,MPI_DOUBLE,mpi->ip[dir]-1,214,mpi->comm[dir],&req[1]);
MPI_Waitall(2,&req[0],MPI_STATUS_IGNORE);
if (mpi->ip[dir] != mpi->iproc[dir]-1) for (d=0; d<Nsys*nvars; d++) F[d+Nsys*nvars*dim[dir]] = recvbuf[d];
#endif
/* save the solution to fI */
#pragma omp parallel for schedule(auto) default(shared) private(sys,d,v,k,R,L,uavg,index_outer,indexC,indexI)
for (sys=0; sys<Nsys; sys++) {
_ArrayIndexnD_(ndims,sys,bounds_outer,index_outer,0);
_ArrayCopy1D_(index_outer,indexI,ndims);
for (indexI[dir] = 0; indexI[dir] < dim[dir]+1; indexI[dir]++) {
int p; _ArrayIndex1D_(ndims,bounds_inter,indexI,0,p);
_ArrayCopy1D_((F+sys*nvars+Nsys*nvars*indexI[dir]),(fI+nvars*p),nvars);
}
}
return(0);
}
|
ast-dump-openmp-teams-distribute-parallel-for.c | // RUN: %clang_cc1 -triple x86_64-unknown-unknown -fopenmp -ast-dump %s | FileCheck --match-full-lines -implicit-check-not=openmp_structured_block %s
void test_one(int x) {
#pragma omp target
#pragma omp teams distribute parallel for
for (int i = 0; i < x; i++)
;
}
void test_two(int x, int y) {
#pragma omp target
#pragma omp teams distribute parallel for
for (int i = 0; i < x; i++)
for (int i = 0; i < y; i++)
;
}
void test_three(int x, int y) {
#pragma omp target
#pragma omp teams distribute parallel for collapse(1)
for (int i = 0; i < x; i++)
for (int i = 0; i < y; i++)
;
}
void test_four(int x, int y) {
#pragma omp target
#pragma omp teams distribute parallel for collapse(2)
for (int i = 0; i < x; i++)
for (int i = 0; i < y; i++)
;
}
void test_five(int x, int y, int z) {
#pragma omp target
#pragma omp teams distribute parallel for collapse(2)
for (int i = 0; i < x; i++)
for (int i = 0; i < y; i++)
for (int i = 0; i < z; i++)
;
}
// CHECK: TranslationUnitDecl {{.*}} <<invalid sloc>> <invalid sloc>
// CHECK: |-FunctionDecl {{.*}} <{{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:3:1, line:8:1> line:3:6 test_one 'void (int)'
// CHECK-NEXT: | |-ParmVarDecl {{.*}} <col:15, col:19> col:19 used x 'int'
// CHECK-NEXT: | `-CompoundStmt {{.*}} <col:22, line:8:1>
// CHECK-NEXT: | `-OMPTargetDirective {{.*}} <line:4:1, col:19>
// CHECK-NEXT: | |-OMPFirstprivateClause {{.*}} <<invalid sloc>> <implicit>
// CHECK-NEXT: | | `-DeclRefExpr {{.*}} <line:6:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | `-CapturedStmt {{.*}} <line:5:1, col:42>
// CHECK-NEXT: | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | |-CapturedStmt {{.*}} <col:1, col:42>
// CHECK-NEXT: | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | |-OMPTeamsDistributeParallelForDirective {{.*}} <col:1, col:42>
// CHECK-NEXT: | | | | | `-CapturedStmt {{.*}} <line:6:3, line:7:5>
// CHECK-NEXT: | | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | |-CapturedStmt {{.*}} <line:6:3, line:7:5>
// CHECK-NEXT: | | | | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | | | |-ForStmt {{.*}} <line:6:3, line:7:5>
// CHECK-NEXT: | | | | | | | | | |-DeclStmt {{.*}} <line:6:8, col:17>
// CHECK-NEXT: | | | | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | `-NullStmt {{.*}} <line:7:5>
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <line:5:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:5:1) *const restrict'
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <line:6:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <line:5:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:5:1) *const restrict'
// CHECK-NEXT: | | | | | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | | | | `-FieldDecl {{.*}} <line:6:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | |-ForStmt {{.*}} <col:3, line:7:5>
// CHECK-NEXT: | | | | | | | |-DeclStmt {{.*}} <line:6:8, col:17>
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-NullStmt {{.*}} <line:7:5>
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <line:5:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:5:1) *const restrict'
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <line:6:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <line:4:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:4:1) *const restrict'
// CHECK-NEXT: | | | | |-RecordDecl {{.*}} <line:5:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | | `-FieldDecl {{.*}} <line:6:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | |-CapturedStmt {{.*}} <col:3, line:7:5>
// CHECK-NEXT: | | | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | | |-ForStmt {{.*}} <line:6:3, line:7:5>
// CHECK-NEXT: | | | | | | | | |-DeclStmt {{.*}} <line:6:8, col:17>
// CHECK-NEXT: | | | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-NullStmt {{.*}} <line:7:5>
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <line:5:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:5:1) *const restrict'
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <line:6:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <line:5:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:5:1) *const restrict'
// CHECK-NEXT: | | | | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | | | `-FieldDecl {{.*}} <line:6:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | |-ForStmt {{.*}} <col:3, line:7:5>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:6:8, col:17>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-NullStmt {{.*}} <line:7:5>
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <line:5:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:5:1) *const restrict'
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <line:6:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | |-OMPCapturedExprDecl {{.*}} <col:23> col:23 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | `-OMPCapturedExprDecl {{.*}} <col:3, <invalid sloc>> col:3 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | | | `-BinaryOperator {{.*}} <col:3, <invalid sloc>> 'int' '-'
// CHECK-NEXT: | | | | |-BinaryOperator {{.*}} <col:3, col:26> 'int' '/'
// CHECK-NEXT: | | | | | |-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | | | `-BinaryOperator {{.*}} <col:23, col:3> 'int' '-'
// CHECK-NEXT: | | | | | | |-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue OMPCapturedExpr {{.*}} '.capture_expr.' 'int'
// CHECK-NEXT: | | | | | | `-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | | | `-BinaryOperator {{.*}} <col:16, <invalid sloc>> 'int' '+'
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:16, col:26> 'int' '-'
// CHECK-NEXT: | | | | | | | |-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | | | `-DeclRefExpr {{.*}} <col:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | |-AlwaysInlineAttr {{.*}} <<invalid sloc>> Implicit __forceinline
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <line:4:1> col:1 implicit .global_tid. 'const int'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .part_id. 'const int *const restrict'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .privates. 'void *const restrict'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .copy_fn. 'void (*const restrict)(void *const restrict, ...)'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .task_t. 'void *const'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:4:1) *const restrict'
// CHECK-NEXT: | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | `-FieldDecl {{.*}} <line:6:3> col:3 implicit 'int'
// CHECK-NEXT: | | | `-OMPCaptureKindAttr {{.*}} <<invalid sloc>> Implicit {{.*}}
// CHECK-NEXT: | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | |-OMPTeamsDistributeParallelForDirective {{.*}} <line:5:1, col:42>
// CHECK-NEXT: | | | `-CapturedStmt {{.*}} <line:6:3, line:7:5>
// CHECK-NEXT: | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | |-CapturedStmt {{.*}} <line:6:3, line:7:5>
// CHECK-NEXT: | | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | |-ForStmt {{.*}} <line:6:3, line:7:5>
// CHECK-NEXT: | | | | | | | |-DeclStmt {{.*}} <line:6:8, col:17>
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-NullStmt {{.*}} <line:7:5>
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <line:5:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:5:1) *const restrict'
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <line:6:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <line:5:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:5:1) *const restrict'
// CHECK-NEXT: | | | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | | `-FieldDecl {{.*}} <line:6:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | |-ForStmt {{.*}} <col:3, line:7:5>
// CHECK-NEXT: | | | | | |-DeclStmt {{.*}} <line:6:8, col:17>
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-NullStmt {{.*}} <line:7:5>
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <line:5:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:5:1) *const restrict'
// CHECK-NEXT: | | | | `-VarDecl {{.*}} <line:6:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | `-DeclRefExpr {{.*}} <col:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <line:4:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:4:1) *const restrict'
// CHECK-NEXT: | | |-RecordDecl {{.*}} <line:5:1> col:1 implicit struct definition
// CHECK-NEXT: | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | `-FieldDecl {{.*}} <line:6:3> col:3 implicit 'int &'
// CHECK-NEXT: | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | |-CapturedStmt {{.*}} <col:3, line:7:5>
// CHECK-NEXT: | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | |-ForStmt {{.*}} <line:6:3, line:7:5>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:6:8, col:17>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-NullStmt {{.*}} <line:7:5>
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <line:5:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:5:1) *const restrict'
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <line:6:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | `-DeclRefExpr {{.*}} <col:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <line:5:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:5:1) *const restrict'
// CHECK-NEXT: | | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | `-FieldDecl {{.*}} <line:6:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | |-ForStmt {{.*}} <col:3, line:7:5>
// CHECK-NEXT: | | | | |-DeclStmt {{.*}} <line:6:8, col:17>
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | `-NullStmt {{.*}} <line:7:5>
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <line:5:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:5:1) *const restrict'
// CHECK-NEXT: | | | `-VarDecl {{.*}} <line:6:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | |-OMPCapturedExprDecl {{.*}} <col:23> col:23 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | `-OMPCapturedExprDecl {{.*}} <col:3, <invalid sloc>> col:3 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | `-BinaryOperator {{.*}} <col:3, <invalid sloc>> 'int' '-'
// CHECK-NEXT: | | |-BinaryOperator {{.*}} <col:3, col:26> 'int' '/'
// CHECK-NEXT: | | | |-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | `-BinaryOperator {{.*}} <col:23, col:3> 'int' '-'
// CHECK-NEXT: | | | | |-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue OMPCapturedExpr {{.*}} '.capture_expr.' 'int'
// CHECK-NEXT: | | | | `-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | `-BinaryOperator {{.*}} <col:16, <invalid sloc>> 'int' '+'
// CHECK-NEXT: | | | | |-BinaryOperator {{.*}} <col:16, col:26> 'int' '-'
// CHECK-NEXT: | | | | | |-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | `-DeclRefExpr {{.*}} <col:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: |-FunctionDecl {{.*}} <line:10:1, line:16:1> line:10:6 test_two 'void (int, int)'
// CHECK-NEXT: | |-ParmVarDecl {{.*}} <col:15, col:19> col:19 used x 'int'
// CHECK-NEXT: | |-ParmVarDecl {{.*}} <col:22, col:26> col:26 used y 'int'
// CHECK-NEXT: | `-CompoundStmt {{.*}} <col:29, line:16:1>
// CHECK-NEXT: | `-OMPTargetDirective {{.*}} <line:11:1, col:19>
// CHECK-NEXT: | |-OMPFirstprivateClause {{.*}} <<invalid sloc>> <implicit>
// CHECK-NEXT: | | |-DeclRefExpr {{.*}} <line:13:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | `-DeclRefExpr {{.*}} <line:14:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | `-CapturedStmt {{.*}} <line:12:1, col:42>
// CHECK-NEXT: | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | |-CapturedStmt {{.*}} <col:1, col:42>
// CHECK-NEXT: | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | |-OMPTeamsDistributeParallelForDirective {{.*}} <col:1, col:42>
// CHECK-NEXT: | | | | | `-CapturedStmt {{.*}} <line:13:3, line:15:7>
// CHECK-NEXT: | | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | |-CapturedStmt {{.*}} <line:13:3, line:15:7>
// CHECK-NEXT: | | | | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | | | |-ForStmt {{.*}} <line:13:3, line:15:7>
// CHECK-NEXT: | | | | | | | | | |-DeclStmt {{.*}} <line:13:8, col:17>
// CHECK-NEXT: | | | | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | `-ForStmt {{.*}} <line:14:5, line:15:7>
// CHECK-NEXT: | | | | | | | | | |-DeclStmt {{.*}} <line:14:10, col:19>
// CHECK-NEXT: | | | | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | `-NullStmt {{.*}} <line:15:7>
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <line:12:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:12:1) *const restrict'
// CHECK-NEXT: | | | | | | | | |-VarDecl {{.*}} <line:13:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <line:14:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | | |-DeclRefExpr {{.*}} <line:13:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <line:14:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <line:12:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:12:1) *const restrict'
// CHECK-NEXT: | | | | | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | | | | |-FieldDecl {{.*}} <line:13:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | | | | `-FieldDecl {{.*}} <line:14:25> col:25 implicit 'int &'
// CHECK-NEXT: | | | | | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | |-ForStmt {{.*}} <line:13:3, line:15:7>
// CHECK-NEXT: | | | | | | | |-DeclStmt {{.*}} <line:13:8, col:17>
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ForStmt {{.*}} <line:14:5, line:15:7>
// CHECK-NEXT: | | | | | | | |-DeclStmt {{.*}} <line:14:10, col:19>
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-NullStmt {{.*}} <line:15:7>
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <line:12:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:12:1) *const restrict'
// CHECK-NEXT: | | | | | | |-VarDecl {{.*}} <line:13:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <line:14:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | |-DeclRefExpr {{.*}} <line:13:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <line:14:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <line:11:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:11:1) *const restrict'
// CHECK-NEXT: | | | | |-RecordDecl {{.*}} <line:12:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | | |-FieldDecl {{.*}} <line:13:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | | `-FieldDecl {{.*}} <line:14:25> col:25 implicit 'int &'
// CHECK-NEXT: | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | |-CapturedStmt {{.*}} <line:13:3, line:15:7>
// CHECK-NEXT: | | | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | | |-ForStmt {{.*}} <line:13:3, line:15:7>
// CHECK-NEXT: | | | | | | | | |-DeclStmt {{.*}} <line:13:8, col:17>
// CHECK-NEXT: | | | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ForStmt {{.*}} <line:14:5, line:15:7>
// CHECK-NEXT: | | | | | | | | |-DeclStmt {{.*}} <line:14:10, col:19>
// CHECK-NEXT: | | | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-NullStmt {{.*}} <line:15:7>
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <line:12:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:12:1) *const restrict'
// CHECK-NEXT: | | | | | | | |-VarDecl {{.*}} <line:13:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <line:14:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | |-DeclRefExpr {{.*}} <line:13:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <line:14:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <line:12:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:12:1) *const restrict'
// CHECK-NEXT: | | | | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | | | |-FieldDecl {{.*}} <line:13:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | | | `-FieldDecl {{.*}} <line:14:25> col:25 implicit 'int &'
// CHECK-NEXT: | | | | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | |-ForStmt {{.*}} <line:13:3, line:15:7>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:13:8, col:17>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ForStmt {{.*}} <line:14:5, line:15:7>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:14:10, col:19>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-NullStmt {{.*}} <line:15:7>
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <line:12:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:12:1) *const restrict'
// CHECK-NEXT: | | | | | |-VarDecl {{.*}} <line:13:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <line:14:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | |-OMPCapturedExprDecl {{.*}} <line:13:23> col:23 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | `-OMPCapturedExprDecl {{.*}} <col:3, <invalid sloc>> col:3 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | | | `-BinaryOperator {{.*}} <col:3, <invalid sloc>> 'int' '-'
// CHECK-NEXT: | | | | |-BinaryOperator {{.*}} <col:3, col:26> 'int' '/'
// CHECK-NEXT: | | | | | |-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | | | `-BinaryOperator {{.*}} <col:23, col:3> 'int' '-'
// CHECK-NEXT: | | | | | | |-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue OMPCapturedExpr {{.*}} '.capture_expr.' 'int'
// CHECK-NEXT: | | | | | | `-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | | | `-BinaryOperator {{.*}} <col:16, <invalid sloc>> 'int' '+'
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:16, col:26> 'int' '-'
// CHECK-NEXT: | | | | | | | |-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | | | |-DeclRefExpr {{.*}} <col:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | `-DeclRefExpr {{.*}} <line:14:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | |-AlwaysInlineAttr {{.*}} <<invalid sloc>> Implicit __forceinline
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <line:11:1> col:1 implicit .global_tid. 'const int'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .part_id. 'const int *const restrict'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .privates. 'void *const restrict'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .copy_fn. 'void (*const restrict)(void *const restrict, ...)'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .task_t. 'void *const'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:11:1) *const restrict'
// CHECK-NEXT: | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | |-FieldDecl {{.*}} <line:13:3> col:3 implicit 'int'
// CHECK-NEXT: | | | | `-OMPCaptureKindAttr {{.*}} <<invalid sloc>> Implicit {{.*}}
// CHECK-NEXT: | | | `-FieldDecl {{.*}} <line:14:25> col:25 implicit 'int'
// CHECK-NEXT: | | | `-OMPCaptureKindAttr {{.*}} <<invalid sloc>> Implicit {{.*}}
// CHECK-NEXT: | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | |-OMPTeamsDistributeParallelForDirective {{.*}} <line:12:1, col:42>
// CHECK-NEXT: | | | `-CapturedStmt {{.*}} <line:13:3, line:15:7>
// CHECK-NEXT: | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | |-CapturedStmt {{.*}} <line:13:3, line:15:7>
// CHECK-NEXT: | | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | |-ForStmt {{.*}} <line:13:3, line:15:7>
// CHECK-NEXT: | | | | | | | |-DeclStmt {{.*}} <line:13:8, col:17>
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ForStmt {{.*}} <line:14:5, line:15:7>
// CHECK-NEXT: | | | | | | | |-DeclStmt {{.*}} <line:14:10, col:19>
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-NullStmt {{.*}} <line:15:7>
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <line:12:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:12:1) *const restrict'
// CHECK-NEXT: | | | | | | |-VarDecl {{.*}} <line:13:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <line:14:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | |-DeclRefExpr {{.*}} <line:13:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <line:14:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <line:12:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:12:1) *const restrict'
// CHECK-NEXT: | | | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | | |-FieldDecl {{.*}} <line:13:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | | `-FieldDecl {{.*}} <line:14:25> col:25 implicit 'int &'
// CHECK-NEXT: | | | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | |-ForStmt {{.*}} <line:13:3, line:15:7>
// CHECK-NEXT: | | | | | |-DeclStmt {{.*}} <line:13:8, col:17>
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-ForStmt {{.*}} <line:14:5, line:15:7>
// CHECK-NEXT: | | | | | |-DeclStmt {{.*}} <line:14:10, col:19>
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-NullStmt {{.*}} <line:15:7>
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <line:12:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:12:1) *const restrict'
// CHECK-NEXT: | | | | |-VarDecl {{.*}} <line:13:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | `-VarDecl {{.*}} <line:14:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | |-DeclRefExpr {{.*}} <line:13:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | `-DeclRefExpr {{.*}} <line:14:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <line:11:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:11:1) *const restrict'
// CHECK-NEXT: | | |-RecordDecl {{.*}} <line:12:1> col:1 implicit struct definition
// CHECK-NEXT: | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | |-FieldDecl {{.*}} <line:13:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | `-FieldDecl {{.*}} <line:14:25> col:25 implicit 'int &'
// CHECK-NEXT: | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | |-CapturedStmt {{.*}} <line:13:3, line:15:7>
// CHECK-NEXT: | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | |-ForStmt {{.*}} <line:13:3, line:15:7>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:13:8, col:17>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ForStmt {{.*}} <line:14:5, line:15:7>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:14:10, col:19>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-NullStmt {{.*}} <line:15:7>
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <line:12:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:12:1) *const restrict'
// CHECK-NEXT: | | | | | |-VarDecl {{.*}} <line:13:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <line:14:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | |-DeclRefExpr {{.*}} <line:13:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | `-DeclRefExpr {{.*}} <line:14:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <line:12:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:12:1) *const restrict'
// CHECK-NEXT: | | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | |-FieldDecl {{.*}} <line:13:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | `-FieldDecl {{.*}} <line:14:25> col:25 implicit 'int &'
// CHECK-NEXT: | | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | |-ForStmt {{.*}} <line:13:3, line:15:7>
// CHECK-NEXT: | | | | |-DeclStmt {{.*}} <line:13:8, col:17>
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | `-ForStmt {{.*}} <line:14:5, line:15:7>
// CHECK-NEXT: | | | | |-DeclStmt {{.*}} <line:14:10, col:19>
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | `-NullStmt {{.*}} <line:15:7>
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <line:12:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:12:1) *const restrict'
// CHECK-NEXT: | | | |-VarDecl {{.*}} <line:13:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | `-VarDecl {{.*}} <line:14:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | |-OMPCapturedExprDecl {{.*}} <line:13:23> col:23 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | `-OMPCapturedExprDecl {{.*}} <col:3, <invalid sloc>> col:3 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | `-BinaryOperator {{.*}} <col:3, <invalid sloc>> 'int' '-'
// CHECK-NEXT: | | |-BinaryOperator {{.*}} <col:3, col:26> 'int' '/'
// CHECK-NEXT: | | | |-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | `-BinaryOperator {{.*}} <col:23, col:3> 'int' '-'
// CHECK-NEXT: | | | | |-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue OMPCapturedExpr {{.*}} '.capture_expr.' 'int'
// CHECK-NEXT: | | | | `-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | `-BinaryOperator {{.*}} <col:16, <invalid sloc>> 'int' '+'
// CHECK-NEXT: | | | | |-BinaryOperator {{.*}} <col:16, col:26> 'int' '-'
// CHECK-NEXT: | | | | | |-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | |-DeclRefExpr {{.*}} <col:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | `-DeclRefExpr {{.*}} <line:14:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: |-FunctionDecl {{.*}} <line:18:1, line:24:1> line:18:6 test_three 'void (int, int)'
// CHECK-NEXT: | |-ParmVarDecl {{.*}} <col:17, col:21> col:21 used x 'int'
// CHECK-NEXT: | |-ParmVarDecl {{.*}} <col:24, col:28> col:28 used y 'int'
// CHECK-NEXT: | `-CompoundStmt {{.*}} <col:31, line:24:1>
// CHECK-NEXT: | `-OMPTargetDirective {{.*}} <line:19:1, col:19>
// CHECK-NEXT: | |-OMPFirstprivateClause {{.*}} <<invalid sloc>> <implicit>
// CHECK-NEXT: | | |-DeclRefExpr {{.*}} <line:21:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | `-DeclRefExpr {{.*}} <line:22:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | `-CapturedStmt {{.*}} <line:20:1, col:54>
// CHECK-NEXT: | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | |-CapturedStmt {{.*}} <col:1, col:54>
// CHECK-NEXT: | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | |-OMPTeamsDistributeParallelForDirective {{.*}} <col:1, col:54>
// CHECK-NEXT: | | | | | |-OMPCollapseClause {{.*}} <col:43, col:53>
// CHECK-NEXT: | | | | | | `-ConstantExpr {{.*}} <col:52> 'int'
// CHECK-NEXT: | | | | | | |-value: Int 1
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:52> 'int' 1
// CHECK-NEXT: | | | | | `-CapturedStmt {{.*}} <line:21:3, line:23:7>
// CHECK-NEXT: | | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | |-CapturedStmt {{.*}} <line:21:3, line:23:7>
// CHECK-NEXT: | | | | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | | | |-ForStmt {{.*}} <line:21:3, line:23:7>
// CHECK-NEXT: | | | | | | | | | |-DeclStmt {{.*}} <line:21:8, col:17>
// CHECK-NEXT: | | | | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | `-ForStmt {{.*}} <line:22:5, line:23:7>
// CHECK-NEXT: | | | | | | | | | |-DeclStmt {{.*}} <line:22:10, col:19>
// CHECK-NEXT: | | | | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | `-NullStmt {{.*}} <line:23:7>
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <line:20:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:20:1) *const restrict'
// CHECK-NEXT: | | | | | | | | |-VarDecl {{.*}} <line:21:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <line:22:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | | |-DeclRefExpr {{.*}} <line:21:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <line:22:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <line:20:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:20:1) *const restrict'
// CHECK-NEXT: | | | | | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | | | | |-FieldDecl {{.*}} <line:21:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | | | | `-FieldDecl {{.*}} <line:22:25> col:25 implicit 'int &'
// CHECK-NEXT: | | | | | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | |-ForStmt {{.*}} <line:21:3, line:23:7>
// CHECK-NEXT: | | | | | | | |-DeclStmt {{.*}} <line:21:8, col:17>
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ForStmt {{.*}} <line:22:5, line:23:7>
// CHECK-NEXT: | | | | | | | |-DeclStmt {{.*}} <line:22:10, col:19>
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-NullStmt {{.*}} <line:23:7>
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <line:20:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:20:1) *const restrict'
// CHECK-NEXT: | | | | | | |-VarDecl {{.*}} <line:21:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <line:22:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | |-DeclRefExpr {{.*}} <line:21:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <line:22:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <line:19:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:19:1) *const restrict'
// CHECK-NEXT: | | | | |-RecordDecl {{.*}} <line:20:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | | |-FieldDecl {{.*}} <line:21:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | | `-FieldDecl {{.*}} <line:22:25> col:25 implicit 'int &'
// CHECK-NEXT: | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | |-CapturedStmt {{.*}} <line:21:3, line:23:7>
// CHECK-NEXT: | | | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | | |-ForStmt {{.*}} <line:21:3, line:23:7>
// CHECK-NEXT: | | | | | | | | |-DeclStmt {{.*}} <line:21:8, col:17>
// CHECK-NEXT: | | | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ForStmt {{.*}} <line:22:5, line:23:7>
// CHECK-NEXT: | | | | | | | | |-DeclStmt {{.*}} <line:22:10, col:19>
// CHECK-NEXT: | | | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-NullStmt {{.*}} <line:23:7>
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <line:20:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:20:1) *const restrict'
// CHECK-NEXT: | | | | | | | |-VarDecl {{.*}} <line:21:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <line:22:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | |-DeclRefExpr {{.*}} <line:21:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <line:22:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <line:20:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:20:1) *const restrict'
// CHECK-NEXT: | | | | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | | | |-FieldDecl {{.*}} <line:21:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | | | `-FieldDecl {{.*}} <line:22:25> col:25 implicit 'int &'
// CHECK-NEXT: | | | | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | |-ForStmt {{.*}} <line:21:3, line:23:7>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:21:8, col:17>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ForStmt {{.*}} <line:22:5, line:23:7>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:22:10, col:19>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-NullStmt {{.*}} <line:23:7>
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <line:20:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:20:1) *const restrict'
// CHECK-NEXT: | | | | | |-VarDecl {{.*}} <line:21:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <line:22:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | |-OMPCapturedExprDecl {{.*}} <line:21:23> col:23 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | `-OMPCapturedExprDecl {{.*}} <col:3, <invalid sloc>> col:3 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | | | `-BinaryOperator {{.*}} <col:3, <invalid sloc>> 'int' '-'
// CHECK-NEXT: | | | | |-BinaryOperator {{.*}} <col:3, col:26> 'int' '/'
// CHECK-NEXT: | | | | | |-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | | | `-BinaryOperator {{.*}} <col:23, col:3> 'int' '-'
// CHECK-NEXT: | | | | | | |-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue OMPCapturedExpr {{.*}} '.capture_expr.' 'int'
// CHECK-NEXT: | | | | | | `-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | | | `-BinaryOperator {{.*}} <col:16, <invalid sloc>> 'int' '+'
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:16, col:26> 'int' '-'
// CHECK-NEXT: | | | | | | | |-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | | | |-DeclRefExpr {{.*}} <col:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | `-DeclRefExpr {{.*}} <line:22:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | |-AlwaysInlineAttr {{.*}} <<invalid sloc>> Implicit __forceinline
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <line:19:1> col:1 implicit .global_tid. 'const int'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .part_id. 'const int *const restrict'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .privates. 'void *const restrict'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .copy_fn. 'void (*const restrict)(void *const restrict, ...)'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .task_t. 'void *const'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:19:1) *const restrict'
// CHECK-NEXT: | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | |-FieldDecl {{.*}} <line:21:3> col:3 implicit 'int'
// CHECK-NEXT: | | | | `-OMPCaptureKindAttr {{.*}} <<invalid sloc>> Implicit {{.*}}
// CHECK-NEXT: | | | `-FieldDecl {{.*}} <line:22:25> col:25 implicit 'int'
// CHECK-NEXT: | | | `-OMPCaptureKindAttr {{.*}} <<invalid sloc>> Implicit {{.*}}
// CHECK-NEXT: | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | |-OMPTeamsDistributeParallelForDirective {{.*}} <line:20:1, col:54>
// CHECK-NEXT: | | | |-OMPCollapseClause {{.*}} <col:43, col:53>
// CHECK-NEXT: | | | | `-ConstantExpr {{.*}} <col:52> 'int'
// CHECK-NEXT: | | | | |-value: Int 1
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <col:52> 'int' 1
// CHECK-NEXT: | | | `-CapturedStmt {{.*}} <line:21:3, line:23:7>
// CHECK-NEXT: | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | |-CapturedStmt {{.*}} <line:21:3, line:23:7>
// CHECK-NEXT: | | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | |-ForStmt {{.*}} <line:21:3, line:23:7>
// CHECK-NEXT: | | | | | | | |-DeclStmt {{.*}} <line:21:8, col:17>
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ForStmt {{.*}} <line:22:5, line:23:7>
// CHECK-NEXT: | | | | | | | |-DeclStmt {{.*}} <line:22:10, col:19>
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-NullStmt {{.*}} <line:23:7>
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <line:20:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:20:1) *const restrict'
// CHECK-NEXT: | | | | | | |-VarDecl {{.*}} <line:21:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <line:22:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | |-DeclRefExpr {{.*}} <line:21:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <line:22:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <line:20:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:20:1) *const restrict'
// CHECK-NEXT: | | | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | | |-FieldDecl {{.*}} <line:21:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | | `-FieldDecl {{.*}} <line:22:25> col:25 implicit 'int &'
// CHECK-NEXT: | | | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | |-ForStmt {{.*}} <line:21:3, line:23:7>
// CHECK-NEXT: | | | | | |-DeclStmt {{.*}} <line:21:8, col:17>
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-ForStmt {{.*}} <line:22:5, line:23:7>
// CHECK-NEXT: | | | | | |-DeclStmt {{.*}} <line:22:10, col:19>
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-NullStmt {{.*}} <line:23:7>
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <line:20:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:20:1) *const restrict'
// CHECK-NEXT: | | | | |-VarDecl {{.*}} <line:21:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | `-VarDecl {{.*}} <line:22:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | |-DeclRefExpr {{.*}} <line:21:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | `-DeclRefExpr {{.*}} <line:22:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <line:19:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:19:1) *const restrict'
// CHECK-NEXT: | | |-RecordDecl {{.*}} <line:20:1> col:1 implicit struct definition
// CHECK-NEXT: | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | |-FieldDecl {{.*}} <line:21:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | `-FieldDecl {{.*}} <line:22:25> col:25 implicit 'int &'
// CHECK-NEXT: | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | |-CapturedStmt {{.*}} <line:21:3, line:23:7>
// CHECK-NEXT: | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | |-ForStmt {{.*}} <line:21:3, line:23:7>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:21:8, col:17>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ForStmt {{.*}} <line:22:5, line:23:7>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:22:10, col:19>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-NullStmt {{.*}} <line:23:7>
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <line:20:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:20:1) *const restrict'
// CHECK-NEXT: | | | | | |-VarDecl {{.*}} <line:21:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <line:22:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | |-DeclRefExpr {{.*}} <line:21:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | `-DeclRefExpr {{.*}} <line:22:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <line:20:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:20:1) *const restrict'
// CHECK-NEXT: | | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | |-FieldDecl {{.*}} <line:21:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | `-FieldDecl {{.*}} <line:22:25> col:25 implicit 'int &'
// CHECK-NEXT: | | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | |-ForStmt {{.*}} <line:21:3, line:23:7>
// CHECK-NEXT: | | | | |-DeclStmt {{.*}} <line:21:8, col:17>
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | `-ForStmt {{.*}} <line:22:5, line:23:7>
// CHECK-NEXT: | | | | |-DeclStmt {{.*}} <line:22:10, col:19>
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | `-NullStmt {{.*}} <line:23:7>
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <line:20:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:20:1) *const restrict'
// CHECK-NEXT: | | | |-VarDecl {{.*}} <line:21:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | `-VarDecl {{.*}} <line:22:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | |-OMPCapturedExprDecl {{.*}} <line:21:23> col:23 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | `-OMPCapturedExprDecl {{.*}} <col:3, <invalid sloc>> col:3 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | `-BinaryOperator {{.*}} <col:3, <invalid sloc>> 'int' '-'
// CHECK-NEXT: | | |-BinaryOperator {{.*}} <col:3, col:26> 'int' '/'
// CHECK-NEXT: | | | |-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | `-BinaryOperator {{.*}} <col:23, col:3> 'int' '-'
// CHECK-NEXT: | | | | |-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue OMPCapturedExpr {{.*}} '.capture_expr.' 'int'
// CHECK-NEXT: | | | | `-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | `-BinaryOperator {{.*}} <col:16, <invalid sloc>> 'int' '+'
// CHECK-NEXT: | | | | |-BinaryOperator {{.*}} <col:16, col:26> 'int' '-'
// CHECK-NEXT: | | | | | |-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | |-DeclRefExpr {{.*}} <col:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | `-DeclRefExpr {{.*}} <line:22:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: |-FunctionDecl {{.*}} <line:26:1, line:32:1> line:26:6 test_four 'void (int, int)'
// CHECK-NEXT: | |-ParmVarDecl {{.*}} <col:16, col:20> col:20 used x 'int'
// CHECK-NEXT: | |-ParmVarDecl {{.*}} <col:23, col:27> col:27 used y 'int'
// CHECK-NEXT: | `-CompoundStmt {{.*}} <col:30, line:32:1>
// CHECK-NEXT: | `-OMPTargetDirective {{.*}} <line:27:1, col:19>
// CHECK-NEXT: | |-OMPFirstprivateClause {{.*}} <<invalid sloc>> <implicit>
// CHECK-NEXT: | | |-DeclRefExpr {{.*}} <line:29:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | `-DeclRefExpr {{.*}} <line:30:5> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | `-CapturedStmt {{.*}} <line:28:1, col:54>
// CHECK-NEXT: | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | |-CapturedStmt {{.*}} <col:1, col:54>
// CHECK-NEXT: | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | |-OMPTeamsDistributeParallelForDirective {{.*}} <col:1, col:54>
// CHECK-NEXT: | | | | | |-OMPCollapseClause {{.*}} <col:43, col:53>
// CHECK-NEXT: | | | | | | `-ConstantExpr {{.*}} <col:52> 'int'
// CHECK-NEXT: | | | | | | |-value: Int 2
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:52> 'int' 2
// CHECK-NEXT: | | | | | `-CapturedStmt {{.*}} <line:29:3, line:31:7>
// CHECK-NEXT: | | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | |-CapturedStmt {{.*}} <line:29:3, line:31:7>
// CHECK-NEXT: | | | | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | | | |-ForStmt {{.*}} <line:29:3, line:31:7>
// CHECK-NEXT: | | | | | | | | | |-DeclStmt {{.*}} <line:29:8, col:17>
// CHECK-NEXT: | | | | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | `-ForStmt {{.*}} <line:30:5, line:31:7>
// CHECK-NEXT: | | | | | | | | | |-DeclStmt {{.*}} <line:30:10, col:19>
// CHECK-NEXT: | | | | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | `-NullStmt {{.*}} <line:31:7>
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <line:28:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:28:1) *const restrict'
// CHECK-NEXT: | | | | | | | | |-VarDecl {{.*}} <line:29:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <line:30:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | | |-DeclRefExpr {{.*}} <line:29:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <line:30:5> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <line:28:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:28:1) *const restrict'
// CHECK-NEXT: | | | | | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | | | | |-FieldDecl {{.*}} <line:29:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | | | | `-FieldDecl {{.*}} <line:30:5> col:5 implicit 'int &'
// CHECK-NEXT: | | | | | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | |-ForStmt {{.*}} <line:29:3, line:31:7>
// CHECK-NEXT: | | | | | | | |-DeclStmt {{.*}} <line:29:8, col:17>
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ForStmt {{.*}} <line:30:5, line:31:7>
// CHECK-NEXT: | | | | | | | |-DeclStmt {{.*}} <line:30:10, col:19>
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-NullStmt {{.*}} <line:31:7>
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <line:28:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:28:1) *const restrict'
// CHECK-NEXT: | | | | | | |-VarDecl {{.*}} <line:29:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <line:30:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | |-DeclRefExpr {{.*}} <line:29:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <line:30:5> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <line:27:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:27:1) *const restrict'
// CHECK-NEXT: | | | | |-RecordDecl {{.*}} <line:28:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | | |-FieldDecl {{.*}} <line:29:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | | `-FieldDecl {{.*}} <line:30:5> col:5 implicit 'int &'
// CHECK-NEXT: | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | |-CapturedStmt {{.*}} <line:29:3, line:31:7>
// CHECK-NEXT: | | | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | | |-ForStmt {{.*}} <line:29:3, line:31:7>
// CHECK-NEXT: | | | | | | | | |-DeclStmt {{.*}} <line:29:8, col:17>
// CHECK-NEXT: | | | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ForStmt {{.*}} <line:30:5, line:31:7>
// CHECK-NEXT: | | | | | | | | |-DeclStmt {{.*}} <line:30:10, col:19>
// CHECK-NEXT: | | | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-NullStmt {{.*}} <line:31:7>
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <line:28:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:28:1) *const restrict'
// CHECK-NEXT: | | | | | | | |-VarDecl {{.*}} <line:29:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <line:30:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | |-DeclRefExpr {{.*}} <line:29:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <line:30:5> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <line:28:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:28:1) *const restrict'
// CHECK-NEXT: | | | | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | | | |-FieldDecl {{.*}} <line:29:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | | | `-FieldDecl {{.*}} <line:30:5> col:5 implicit 'int &'
// CHECK-NEXT: | | | | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | |-ForStmt {{.*}} <line:29:3, line:31:7>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:29:8, col:17>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ForStmt {{.*}} <line:30:5, line:31:7>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:30:10, col:19>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-NullStmt {{.*}} <line:31:7>
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <line:28:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:28:1) *const restrict'
// CHECK-NEXT: | | | | | |-VarDecl {{.*}} <line:29:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <line:30:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | |-OMPCapturedExprDecl {{.*}} <line:29:23> col:23 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | |-OMPCapturedExprDecl {{.*}} <line:30:25> col:25 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | `-OMPCapturedExprDecl {{.*}} <line:29:3, <invalid sloc>> col:3 implicit used .capture_expr. 'long'
// CHECK-NEXT: | | | | `-BinaryOperator {{.*}} <col:3, <invalid sloc>> 'long' '-'
// CHECK-NEXT: | | | | |-BinaryOperator {{.*}} <col:3, line:30:28> 'long' '*'
// CHECK-NEXT: | | | | | |-ImplicitCastExpr {{.*}} <line:29:3, col:26> 'long' <IntegralCast>
// CHECK-NEXT: | | | | | | `-BinaryOperator {{.*}} <col:3, col:26> 'int' '/'
// CHECK-NEXT: | | | | | | |-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | | | | `-BinaryOperator {{.*}} <col:23, col:3> 'int' '-'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue OMPCapturedExpr {{.*}} '.capture_expr.' 'int'
// CHECK-NEXT: | | | | | | | `-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | | | | `-BinaryOperator {{.*}} <col:16, <invalid sloc>> 'int' '+'
// CHECK-NEXT: | | | | | | | |-BinaryOperator {{.*}} <col:16, col:26> 'int' '-'
// CHECK-NEXT: | | | | | | | | |-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | | | | `-ImplicitCastExpr {{.*}} <line:30:5, col:28> 'long' <IntegralCast>
// CHECK-NEXT: | | | | | `-BinaryOperator {{.*}} <col:5, col:28> 'int' '/'
// CHECK-NEXT: | | | | | |-ParenExpr {{.*}} <col:5> 'int'
// CHECK-NEXT: | | | | | | `-BinaryOperator {{.*}} <col:25, col:5> 'int' '-'
// CHECK-NEXT: | | | | | | |-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue OMPCapturedExpr {{.*}} '.capture_expr.' 'int'
// CHECK-NEXT: | | | | | | `-ParenExpr {{.*}} <col:5> 'int'
// CHECK-NEXT: | | | | | | `-BinaryOperator {{.*}} <col:18, <invalid sloc>> 'int' '+'
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:18, col:28> 'int' '-'
// CHECK-NEXT: | | | | | | | |-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:28> 'int' 1
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:28> 'int' 1
// CHECK-NEXT: | | | | `-ImplicitCastExpr {{.*}} <<invalid sloc>> 'long' <IntegralCast>
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | | | |-DeclRefExpr {{.*}} <line:29:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | `-DeclRefExpr {{.*}} <line:30:5> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | |-AlwaysInlineAttr {{.*}} <<invalid sloc>> Implicit __forceinline
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <line:27:1> col:1 implicit .global_tid. 'const int'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .part_id. 'const int *const restrict'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .privates. 'void *const restrict'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .copy_fn. 'void (*const restrict)(void *const restrict, ...)'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .task_t. 'void *const'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:27:1) *const restrict'
// CHECK-NEXT: | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | |-FieldDecl {{.*}} <line:29:3> col:3 implicit 'int'
// CHECK-NEXT: | | | | `-OMPCaptureKindAttr {{.*}} <<invalid sloc>> Implicit {{.*}}
// CHECK-NEXT: | | | `-FieldDecl {{.*}} <line:30:5> col:5 implicit 'int'
// CHECK-NEXT: | | | `-OMPCaptureKindAttr {{.*}} <<invalid sloc>> Implicit {{.*}}
// CHECK-NEXT: | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | |-OMPTeamsDistributeParallelForDirective {{.*}} <line:28:1, col:54>
// CHECK-NEXT: | | | |-OMPCollapseClause {{.*}} <col:43, col:53>
// CHECK-NEXT: | | | | `-ConstantExpr {{.*}} <col:52> 'int'
// CHECK-NEXT: | | | | |-value: Int 2
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <col:52> 'int' 2
// CHECK-NEXT: | | | `-CapturedStmt {{.*}} <line:29:3, line:31:7>
// CHECK-NEXT: | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | |-CapturedStmt {{.*}} <line:29:3, line:31:7>
// CHECK-NEXT: | | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | |-ForStmt {{.*}} <line:29:3, line:31:7>
// CHECK-NEXT: | | | | | | | |-DeclStmt {{.*}} <line:29:8, col:17>
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ForStmt {{.*}} <line:30:5, line:31:7>
// CHECK-NEXT: | | | | | | | |-DeclStmt {{.*}} <line:30:10, col:19>
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-NullStmt {{.*}} <line:31:7>
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <line:28:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:28:1) *const restrict'
// CHECK-NEXT: | | | | | | |-VarDecl {{.*}} <line:29:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <line:30:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | |-DeclRefExpr {{.*}} <line:29:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <line:30:5> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <line:28:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:28:1) *const restrict'
// CHECK-NEXT: | | | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | | |-FieldDecl {{.*}} <line:29:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | | `-FieldDecl {{.*}} <line:30:5> col:5 implicit 'int &'
// CHECK-NEXT: | | | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | |-ForStmt {{.*}} <line:29:3, line:31:7>
// CHECK-NEXT: | | | | | |-DeclStmt {{.*}} <line:29:8, col:17>
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-ForStmt {{.*}} <line:30:5, line:31:7>
// CHECK-NEXT: | | | | | |-DeclStmt {{.*}} <line:30:10, col:19>
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-NullStmt {{.*}} <line:31:7>
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <line:28:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:28:1) *const restrict'
// CHECK-NEXT: | | | | |-VarDecl {{.*}} <line:29:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | `-VarDecl {{.*}} <line:30:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | |-DeclRefExpr {{.*}} <line:29:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | `-DeclRefExpr {{.*}} <line:30:5> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <line:27:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:27:1) *const restrict'
// CHECK-NEXT: | | |-RecordDecl {{.*}} <line:28:1> col:1 implicit struct definition
// CHECK-NEXT: | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | |-FieldDecl {{.*}} <line:29:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | `-FieldDecl {{.*}} <line:30:5> col:5 implicit 'int &'
// CHECK-NEXT: | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | |-CapturedStmt {{.*}} <line:29:3, line:31:7>
// CHECK-NEXT: | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | |-ForStmt {{.*}} <line:29:3, line:31:7>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:29:8, col:17>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ForStmt {{.*}} <line:30:5, line:31:7>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:30:10, col:19>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-NullStmt {{.*}} <line:31:7>
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <line:28:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:28:1) *const restrict'
// CHECK-NEXT: | | | | | |-VarDecl {{.*}} <line:29:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <line:30:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | |-DeclRefExpr {{.*}} <line:29:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | `-DeclRefExpr {{.*}} <line:30:5> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <line:28:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:28:1) *const restrict'
// CHECK-NEXT: | | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | |-FieldDecl {{.*}} <line:29:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | `-FieldDecl {{.*}} <line:30:5> col:5 implicit 'int &'
// CHECK-NEXT: | | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | |-ForStmt {{.*}} <line:29:3, line:31:7>
// CHECK-NEXT: | | | | |-DeclStmt {{.*}} <line:29:8, col:17>
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | `-ForStmt {{.*}} <line:30:5, line:31:7>
// CHECK-NEXT: | | | | |-DeclStmt {{.*}} <line:30:10, col:19>
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | `-NullStmt {{.*}} <line:31:7>
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <line:28:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:28:1) *const restrict'
// CHECK-NEXT: | | | |-VarDecl {{.*}} <line:29:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | `-VarDecl {{.*}} <line:30:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | |-OMPCapturedExprDecl {{.*}} <line:29:23> col:23 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | |-OMPCapturedExprDecl {{.*}} <line:30:25> col:25 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | `-OMPCapturedExprDecl {{.*}} <line:29:3, <invalid sloc>> col:3 implicit used .capture_expr. 'long'
// CHECK-NEXT: | | `-BinaryOperator {{.*}} <col:3, <invalid sloc>> 'long' '-'
// CHECK-NEXT: | | |-BinaryOperator {{.*}} <col:3, line:30:28> 'long' '*'
// CHECK-NEXT: | | | |-ImplicitCastExpr {{.*}} <line:29:3, col:26> 'long' <IntegralCast>
// CHECK-NEXT: | | | | `-BinaryOperator {{.*}} <col:3, col:26> 'int' '/'
// CHECK-NEXT: | | | | |-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | | `-BinaryOperator {{.*}} <col:23, col:3> 'int' '-'
// CHECK-NEXT: | | | | | |-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue OMPCapturedExpr {{.*}} '.capture_expr.' 'int'
// CHECK-NEXT: | | | | | `-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | | `-BinaryOperator {{.*}} <col:16, <invalid sloc>> 'int' '+'
// CHECK-NEXT: | | | | | |-BinaryOperator {{.*}} <col:16, col:26> 'int' '-'
// CHECK-NEXT: | | | | | | |-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | | `-ImplicitCastExpr {{.*}} <line:30:5, col:28> 'long' <IntegralCast>
// CHECK-NEXT: | | | `-BinaryOperator {{.*}} <col:5, col:28> 'int' '/'
// CHECK-NEXT: | | | |-ParenExpr {{.*}} <col:5> 'int'
// CHECK-NEXT: | | | | `-BinaryOperator {{.*}} <col:25, col:5> 'int' '-'
// CHECK-NEXT: | | | | |-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue OMPCapturedExpr {{.*}} '.capture_expr.' 'int'
// CHECK-NEXT: | | | | `-ParenExpr {{.*}} <col:5> 'int'
// CHECK-NEXT: | | | | `-BinaryOperator {{.*}} <col:18, <invalid sloc>> 'int' '+'
// CHECK-NEXT: | | | | |-BinaryOperator {{.*}} <col:18, col:28> 'int' '-'
// CHECK-NEXT: | | | | | |-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:28> 'int' 1
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | | | `-IntegerLiteral {{.*}} <col:28> 'int' 1
// CHECK-NEXT: | | `-ImplicitCastExpr {{.*}} <<invalid sloc>> 'long' <IntegralCast>
// CHECK-NEXT: | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | |-DeclRefExpr {{.*}} <line:29:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | `-DeclRefExpr {{.*}} <line:30:5> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: `-FunctionDecl {{.*}} <line:34:1, line:41:1> line:34:6 test_five 'void (int, int, int)'
// CHECK-NEXT: |-ParmVarDecl {{.*}} <col:16, col:20> col:20 used x 'int'
// CHECK-NEXT: |-ParmVarDecl {{.*}} <col:23, col:27> col:27 used y 'int'
// CHECK-NEXT: |-ParmVarDecl {{.*}} <col:30, col:34> col:34 used z 'int'
// CHECK-NEXT: `-CompoundStmt {{.*}} <col:37, line:41:1>
// CHECK-NEXT: `-OMPTargetDirective {{.*}} <line:35:1, col:19>
// CHECK-NEXT: |-OMPFirstprivateClause {{.*}} <<invalid sloc>> <implicit>
// CHECK-NEXT: | |-DeclRefExpr {{.*}} <line:37:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | |-DeclRefExpr {{.*}} <line:38:5> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | `-DeclRefExpr {{.*}} <line:39:27> 'int' lvalue ParmVar {{.*}} 'z' 'int'
// CHECK-NEXT: `-CapturedStmt {{.*}} <line:36:1, col:54>
// CHECK-NEXT: |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | |-CapturedStmt {{.*}} <col:1, col:54>
// CHECK-NEXT: | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | |-OMPTeamsDistributeParallelForDirective {{.*}} <col:1, col:54>
// CHECK-NEXT: | | | | |-OMPCollapseClause {{.*}} <col:43, col:53>
// CHECK-NEXT: | | | | | `-ConstantExpr {{.*}} <col:52> 'int'
// CHECK-NEXT: | | | | | |-value: Int 2
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:52> 'int' 2
// CHECK-NEXT: | | | | `-CapturedStmt {{.*}} <line:37:3, line:40:9>
// CHECK-NEXT: | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | |-CapturedStmt {{.*}} <line:37:3, line:40:9>
// CHECK-NEXT: | | | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | | |-ForStmt {{.*}} <line:37:3, line:40:9>
// CHECK-NEXT: | | | | | | | | |-DeclStmt {{.*}} <line:37:8, col:17>
// CHECK-NEXT: | | | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ForStmt {{.*}} <line:38:5, line:40:9>
// CHECK-NEXT: | | | | | | | | |-DeclStmt {{.*}} <line:38:10, col:19>
// CHECK-NEXT: | | | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ForStmt {{.*}} <line:39:7, line:40:9>
// CHECK-NEXT: | | | | | | | | |-DeclStmt {{.*}} <line:39:12, col:21>
// CHECK-NEXT: | | | | | | | | | `-VarDecl {{.*}} <col:12, col:20> col:16 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | | `-IntegerLiteral {{.*}} <col:20> 'int' 0
// CHECK-NEXT: | | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | | |-BinaryOperator {{.*}} <col:23, col:27> 'int' '<'
// CHECK-NEXT: | | | | | | | | | |-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | | `-ImplicitCastExpr {{.*}} <col:27> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:27> 'int' lvalue ParmVar {{.*}} 'z' 'int'
// CHECK-NEXT: | | | | | | | | |-UnaryOperator {{.*}} <col:30, col:31> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:30> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-NullStmt {{.*}} <line:40:9>
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <line:36:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:36:1) *const restrict'
// CHECK-NEXT: | | | | | | | |-VarDecl {{.*}} <line:37:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | |-VarDecl {{.*}} <line:38:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <line:39:12, col:20> col:16 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:20> 'int' 0
// CHECK-NEXT: | | | | | | |-DeclRefExpr {{.*}} <line:37:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | |-DeclRefExpr {{.*}} <line:38:5> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <line:39:27> 'int' lvalue ParmVar {{.*}} 'z' 'int'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <line:36:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:36:1) *const restrict'
// CHECK-NEXT: | | | | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | | | |-FieldDecl {{.*}} <line:37:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | | | |-FieldDecl {{.*}} <line:38:5> col:5 implicit 'int &'
// CHECK-NEXT: | | | | | | `-FieldDecl {{.*}} <line:39:27> col:27 implicit 'int &'
// CHECK-NEXT: | | | | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | |-ForStmt {{.*}} <line:37:3, line:40:9>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:37:8, col:17>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ForStmt {{.*}} <line:38:5, line:40:9>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:38:10, col:19>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ForStmt {{.*}} <line:39:7, line:40:9>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:39:12, col:21>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:12, col:20> col:16 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:20> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:23, col:27> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:27> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:27> 'int' lvalue ParmVar {{.*}} 'z' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:30, col:31> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:30> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-NullStmt {{.*}} <line:40:9>
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <line:36:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:36:1) *const restrict'
// CHECK-NEXT: | | | | | |-VarDecl {{.*}} <line:37:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | |-VarDecl {{.*}} <line:38:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <line:39:12, col:20> col:16 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:20> 'int' 0
// CHECK-NEXT: | | | | |-DeclRefExpr {{.*}} <line:37:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | |-DeclRefExpr {{.*}} <line:38:5> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | `-DeclRefExpr {{.*}} <line:39:27> 'int' lvalue ParmVar {{.*}} 'z' 'int'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <line:35:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:35:1) *const restrict'
// CHECK-NEXT: | | | |-RecordDecl {{.*}} <line:36:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | |-FieldDecl {{.*}} <line:37:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | |-FieldDecl {{.*}} <line:38:5> col:5 implicit 'int &'
// CHECK-NEXT: | | | | `-FieldDecl {{.*}} <line:39:27> col:27 implicit 'int &'
// CHECK-NEXT: | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | |-CapturedStmt {{.*}} <line:37:3, line:40:9>
// CHECK-NEXT: | | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | | |-ForStmt {{.*}} <line:37:3, line:40:9>
// CHECK-NEXT: | | | | | | | |-DeclStmt {{.*}} <line:37:8, col:17>
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ForStmt {{.*}} <line:38:5, line:40:9>
// CHECK-NEXT: | | | | | | | |-DeclStmt {{.*}} <line:38:10, col:19>
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ForStmt {{.*}} <line:39:7, line:40:9>
// CHECK-NEXT: | | | | | | | |-DeclStmt {{.*}} <line:39:12, col:21>
// CHECK-NEXT: | | | | | | | | `-VarDecl {{.*}} <col:12, col:20> col:16 used i 'int' cinit
// CHECK-NEXT: | | | | | | | | `-IntegerLiteral {{.*}} <col:20> 'int' 0
// CHECK-NEXT: | | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | | |-BinaryOperator {{.*}} <col:23, col:27> 'int' '<'
// CHECK-NEXT: | | | | | | | | |-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | | `-ImplicitCastExpr {{.*}} <col:27> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:27> 'int' lvalue ParmVar {{.*}} 'z' 'int'
// CHECK-NEXT: | | | | | | | |-UnaryOperator {{.*}} <col:30, col:31> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:30> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-NullStmt {{.*}} <line:40:9>
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <line:36:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:36:1) *const restrict'
// CHECK-NEXT: | | | | | | |-VarDecl {{.*}} <line:37:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | |-VarDecl {{.*}} <line:38:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <line:39:12, col:20> col:16 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:20> 'int' 0
// CHECK-NEXT: | | | | | |-DeclRefExpr {{.*}} <line:37:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | |-DeclRefExpr {{.*}} <line:38:5> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <line:39:27> 'int' lvalue ParmVar {{.*}} 'z' 'int'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <line:36:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:36:1) *const restrict'
// CHECK-NEXT: | | | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | | |-FieldDecl {{.*}} <line:37:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | | |-FieldDecl {{.*}} <line:38:5> col:5 implicit 'int &'
// CHECK-NEXT: | | | | | `-FieldDecl {{.*}} <line:39:27> col:27 implicit 'int &'
// CHECK-NEXT: | | | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | |-ForStmt {{.*}} <line:37:3, line:40:9>
// CHECK-NEXT: | | | | | |-DeclStmt {{.*}} <line:37:8, col:17>
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-ForStmt {{.*}} <line:38:5, line:40:9>
// CHECK-NEXT: | | | | | |-DeclStmt {{.*}} <line:38:10, col:19>
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-ForStmt {{.*}} <line:39:7, line:40:9>
// CHECK-NEXT: | | | | | |-DeclStmt {{.*}} <line:39:12, col:21>
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <col:12, col:20> col:16 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:20> 'int' 0
// CHECK-NEXT: | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | |-BinaryOperator {{.*}} <col:23, col:27> 'int' '<'
// CHECK-NEXT: | | | | | | |-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ImplicitCastExpr {{.*}} <col:27> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:27> 'int' lvalue ParmVar {{.*}} 'z' 'int'
// CHECK-NEXT: | | | | | |-UnaryOperator {{.*}} <col:30, col:31> 'int' postfix '++'
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:30> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-NullStmt {{.*}} <line:40:9>
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <line:36:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:36:1) *const restrict'
// CHECK-NEXT: | | | | |-VarDecl {{.*}} <line:37:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | |-VarDecl {{.*}} <line:38:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | `-VarDecl {{.*}} <line:39:12, col:20> col:16 used i 'int' cinit
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <col:20> 'int' 0
// CHECK-NEXT: | | | |-OMPCapturedExprDecl {{.*}} <line:37:23> col:23 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | |-OMPCapturedExprDecl {{.*}} <line:38:25> col:25 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | `-OMPCapturedExprDecl {{.*}} <line:37:3, <invalid sloc>> col:3 implicit used .capture_expr. 'long'
// CHECK-NEXT: | | | `-BinaryOperator {{.*}} <col:3, <invalid sloc>> 'long' '-'
// CHECK-NEXT: | | | |-BinaryOperator {{.*}} <col:3, line:38:28> 'long' '*'
// CHECK-NEXT: | | | | |-ImplicitCastExpr {{.*}} <line:37:3, col:26> 'long' <IntegralCast>
// CHECK-NEXT: | | | | | `-BinaryOperator {{.*}} <col:3, col:26> 'int' '/'
// CHECK-NEXT: | | | | | |-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | | | `-BinaryOperator {{.*}} <col:23, col:3> 'int' '-'
// CHECK-NEXT: | | | | | | |-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue OMPCapturedExpr {{.*}} '.capture_expr.' 'int'
// CHECK-NEXT: | | | | | | `-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | | | `-BinaryOperator {{.*}} <col:16, <invalid sloc>> 'int' '+'
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:16, col:26> 'int' '-'
// CHECK-NEXT: | | | | | | | |-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | | | `-ImplicitCastExpr {{.*}} <line:38:5, col:28> 'long' <IntegralCast>
// CHECK-NEXT: | | | | `-BinaryOperator {{.*}} <col:5, col:28> 'int' '/'
// CHECK-NEXT: | | | | |-ParenExpr {{.*}} <col:5> 'int'
// CHECK-NEXT: | | | | | `-BinaryOperator {{.*}} <col:25, col:5> 'int' '-'
// CHECK-NEXT: | | | | | |-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue OMPCapturedExpr {{.*}} '.capture_expr.' 'int'
// CHECK-NEXT: | | | | | `-ParenExpr {{.*}} <col:5> 'int'
// CHECK-NEXT: | | | | | `-BinaryOperator {{.*}} <col:18, <invalid sloc>> 'int' '+'
// CHECK-NEXT: | | | | | |-BinaryOperator {{.*}} <col:18, col:28> 'int' '-'
// CHECK-NEXT: | | | | | | |-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:28> 'int' 1
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <col:28> 'int' 1
// CHECK-NEXT: | | | `-ImplicitCastExpr {{.*}} <<invalid sloc>> 'long' <IntegralCast>
// CHECK-NEXT: | | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | | |-DeclRefExpr {{.*}} <line:37:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | |-DeclRefExpr {{.*}} <line:38:5> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | `-DeclRefExpr {{.*}} <line:39:27> 'int' lvalue ParmVar {{.*}} 'z' 'int'
// CHECK-NEXT: | |-AlwaysInlineAttr {{.*}} <<invalid sloc>> Implicit __forceinline
// CHECK-NEXT: | |-ImplicitParamDecl {{.*}} <line:35:1> col:1 implicit .global_tid. 'const int'
// CHECK-NEXT: | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .part_id. 'const int *const restrict'
// CHECK-NEXT: | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .privates. 'void *const restrict'
// CHECK-NEXT: | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .copy_fn. 'void (*const restrict)(void *const restrict, ...)'
// CHECK-NEXT: | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .task_t. 'void *const'
// CHECK-NEXT: | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:35:1) *const restrict'
// CHECK-NEXT: | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | |-FieldDecl {{.*}} <line:37:3> col:3 implicit 'int'
// CHECK-NEXT: | | | `-OMPCaptureKindAttr {{.*}} <<invalid sloc>> Implicit {{.*}}
// CHECK-NEXT: | | |-FieldDecl {{.*}} <line:38:5> col:5 implicit 'int'
// CHECK-NEXT: | | | `-OMPCaptureKindAttr {{.*}} <<invalid sloc>> Implicit {{.*}}
// CHECK-NEXT: | | `-FieldDecl {{.*}} <line:39:27> col:27 implicit 'int'
// CHECK-NEXT: | | `-OMPCaptureKindAttr {{.*}} <<invalid sloc>> Implicit {{.*}}
// CHECK-NEXT: | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | |-OMPTeamsDistributeParallelForDirective {{.*}} <line:36:1, col:54>
// CHECK-NEXT: | | |-OMPCollapseClause {{.*}} <col:43, col:53>
// CHECK-NEXT: | | | `-ConstantExpr {{.*}} <col:52> 'int'
// CHECK-NEXT: | | | |-value: Int 2
// CHECK-NEXT: | | | `-IntegerLiteral {{.*}} <col:52> 'int' 2
// CHECK-NEXT: | | `-CapturedStmt {{.*}} <line:37:3, line:40:9>
// CHECK-NEXT: | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | |-CapturedStmt {{.*}} <line:37:3, line:40:9>
// CHECK-NEXT: | | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | | |-ForStmt {{.*}} <line:37:3, line:40:9>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:37:8, col:17>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ForStmt {{.*}} <line:38:5, line:40:9>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:38:10, col:19>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ForStmt {{.*}} <line:39:7, line:40:9>
// CHECK-NEXT: | | | | | | |-DeclStmt {{.*}} <line:39:12, col:21>
// CHECK-NEXT: | | | | | | | `-VarDecl {{.*}} <col:12, col:20> col:16 used i 'int' cinit
// CHECK-NEXT: | | | | | | | `-IntegerLiteral {{.*}} <col:20> 'int' 0
// CHECK-NEXT: | | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | | |-BinaryOperator {{.*}} <col:23, col:27> 'int' '<'
// CHECK-NEXT: | | | | | | | |-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | | `-ImplicitCastExpr {{.*}} <col:27> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:27> 'int' lvalue ParmVar {{.*}} 'z' 'int'
// CHECK-NEXT: | | | | | | |-UnaryOperator {{.*}} <col:30, col:31> 'int' postfix '++'
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:30> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-NullStmt {{.*}} <line:40:9>
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <line:36:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:36:1) *const restrict'
// CHECK-NEXT: | | | | | |-VarDecl {{.*}} <line:37:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | |-VarDecl {{.*}} <line:38:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <line:39:12, col:20> col:16 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:20> 'int' 0
// CHECK-NEXT: | | | | |-DeclRefExpr {{.*}} <line:37:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | |-DeclRefExpr {{.*}} <line:38:5> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | `-DeclRefExpr {{.*}} <line:39:27> 'int' lvalue ParmVar {{.*}} 'z' 'int'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <line:36:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:36:1) *const restrict'
// CHECK-NEXT: | | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | | |-FieldDecl {{.*}} <line:37:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | | |-FieldDecl {{.*}} <line:38:5> col:5 implicit 'int &'
// CHECK-NEXT: | | | | `-FieldDecl {{.*}} <line:39:27> col:27 implicit 'int &'
// CHECK-NEXT: | | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | |-ForStmt {{.*}} <line:37:3, line:40:9>
// CHECK-NEXT: | | | | |-DeclStmt {{.*}} <line:37:8, col:17>
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | `-ForStmt {{.*}} <line:38:5, line:40:9>
// CHECK-NEXT: | | | | |-DeclStmt {{.*}} <line:38:10, col:19>
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | `-ForStmt {{.*}} <line:39:7, line:40:9>
// CHECK-NEXT: | | | | |-DeclStmt {{.*}} <line:39:12, col:21>
// CHECK-NEXT: | | | | | `-VarDecl {{.*}} <col:12, col:20> col:16 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:20> 'int' 0
// CHECK-NEXT: | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | |-BinaryOperator {{.*}} <col:23, col:27> 'int' '<'
// CHECK-NEXT: | | | | | |-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-ImplicitCastExpr {{.*}} <col:27> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:27> 'int' lvalue ParmVar {{.*}} 'z' 'int'
// CHECK-NEXT: | | | | |-UnaryOperator {{.*}} <col:30, col:31> 'int' postfix '++'
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:30> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | `-NullStmt {{.*}} <line:40:9>
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <line:36:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:36:1) *const restrict'
// CHECK-NEXT: | | | |-VarDecl {{.*}} <line:37:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | |-VarDecl {{.*}} <line:38:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | `-VarDecl {{.*}} <line:39:12, col:20> col:16 used i 'int' cinit
// CHECK-NEXT: | | | `-IntegerLiteral {{.*}} <col:20> 'int' 0
// CHECK-NEXT: | | |-DeclRefExpr {{.*}} <line:37:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | |-DeclRefExpr {{.*}} <line:38:5> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | `-DeclRefExpr {{.*}} <line:39:27> 'int' lvalue ParmVar {{.*}} 'z' 'int'
// CHECK-NEXT: | |-ImplicitParamDecl {{.*}} <line:35:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:35:1) *const restrict'
// CHECK-NEXT: | |-RecordDecl {{.*}} <line:36:1> col:1 implicit struct definition
// CHECK-NEXT: | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | |-FieldDecl {{.*}} <line:37:3> col:3 implicit 'int &'
// CHECK-NEXT: | | |-FieldDecl {{.*}} <line:38:5> col:5 implicit 'int &'
// CHECK-NEXT: | | `-FieldDecl {{.*}} <line:39:27> col:27 implicit 'int &'
// CHECK-NEXT: | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | |-CapturedStmt {{.*}} <line:37:3, line:40:9>
// CHECK-NEXT: | | | |-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | | | |-ForStmt {{.*}} <line:37:3, line:40:9>
// CHECK-NEXT: | | | | | |-DeclStmt {{.*}} <line:37:8, col:17>
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-ForStmt {{.*}} <line:38:5, line:40:9>
// CHECK-NEXT: | | | | | |-DeclStmt {{.*}} <line:38:10, col:19>
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-ForStmt {{.*}} <line:39:7, line:40:9>
// CHECK-NEXT: | | | | | |-DeclStmt {{.*}} <line:39:12, col:21>
// CHECK-NEXT: | | | | | | `-VarDecl {{.*}} <col:12, col:20> col:16 used i 'int' cinit
// CHECK-NEXT: | | | | | | `-IntegerLiteral {{.*}} <col:20> 'int' 0
// CHECK-NEXT: | | | | | |-<<<NULL>>>
// CHECK-NEXT: | | | | | |-BinaryOperator {{.*}} <col:23, col:27> 'int' '<'
// CHECK-NEXT: | | | | | | |-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | | `-ImplicitCastExpr {{.*}} <col:27> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:27> 'int' lvalue ParmVar {{.*}} 'z' 'int'
// CHECK-NEXT: | | | | | |-UnaryOperator {{.*}} <col:30, col:31> 'int' postfix '++'
// CHECK-NEXT: | | | | | | `-DeclRefExpr {{.*}} <col:30> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | | `-NullStmt {{.*}} <line:40:9>
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <line:36:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:36:1) *const restrict'
// CHECK-NEXT: | | | | |-VarDecl {{.*}} <line:37:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | |-VarDecl {{.*}} <line:38:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | `-VarDecl {{.*}} <line:39:12, col:20> col:16 used i 'int' cinit
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <col:20> 'int' 0
// CHECK-NEXT: | | | |-DeclRefExpr {{.*}} <line:37:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | |-DeclRefExpr {{.*}} <line:38:5> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | `-DeclRefExpr {{.*}} <line:39:27> 'int' lvalue ParmVar {{.*}} 'z' 'int'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <line:36:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:36:1) *const restrict'
// CHECK-NEXT: | | |-RecordDecl {{.*}} <col:1> col:1 implicit struct definition
// CHECK-NEXT: | | | |-CapturedRecordAttr {{.*}} <<invalid sloc>> Implicit
// CHECK-NEXT: | | | |-FieldDecl {{.*}} <line:37:3> col:3 implicit 'int &'
// CHECK-NEXT: | | | |-FieldDecl {{.*}} <line:38:5> col:5 implicit 'int &'
// CHECK-NEXT: | | | `-FieldDecl {{.*}} <line:39:27> col:27 implicit 'int &'
// CHECK-NEXT: | | `-CapturedDecl {{.*}} <<invalid sloc>> <invalid sloc> nothrow
// CHECK-NEXT: | | |-ForStmt {{.*}} <line:37:3, line:40:9>
// CHECK-NEXT: | | | |-DeclStmt {{.*}} <line:37:8, col:17>
// CHECK-NEXT: | | | | `-VarDecl {{.*}} <col:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | |-<<<NULL>>>
// CHECK-NEXT: | | | |-BinaryOperator {{.*}} <col:19, col:23> 'int' '<'
// CHECK-NEXT: | | | | |-ImplicitCastExpr {{.*}} <col:19> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:19> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | | | |-UnaryOperator {{.*}} <col:26, col:27> 'int' postfix '++'
// CHECK-NEXT: | | | | `-DeclRefExpr {{.*}} <col:26> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | `-ForStmt {{.*}} <line:38:5, line:40:9>
// CHECK-NEXT: | | | |-DeclStmt {{.*}} <line:38:10, col:19>
// CHECK-NEXT: | | | | `-VarDecl {{.*}} <col:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | |-<<<NULL>>>
// CHECK-NEXT: | | | |-BinaryOperator {{.*}} <col:21, col:25> 'int' '<'
// CHECK-NEXT: | | | | |-ImplicitCastExpr {{.*}} <col:21> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:21> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | | | |-UnaryOperator {{.*}} <col:28, col:29> 'int' postfix '++'
// CHECK-NEXT: | | | | `-DeclRefExpr {{.*}} <col:28> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | `-ForStmt {{.*}} <line:39:7, line:40:9>
// CHECK-NEXT: | | | |-DeclStmt {{.*}} <line:39:12, col:21>
// CHECK-NEXT: | | | | `-VarDecl {{.*}} <col:12, col:20> col:16 used i 'int' cinit
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <col:20> 'int' 0
// CHECK-NEXT: | | | |-<<<NULL>>>
// CHECK-NEXT: | | | |-BinaryOperator {{.*}} <col:23, col:27> 'int' '<'
// CHECK-NEXT: | | | | |-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | | `-ImplicitCastExpr {{.*}} <col:27> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | `-DeclRefExpr {{.*}} <col:27> 'int' lvalue ParmVar {{.*}} 'z' 'int'
// CHECK-NEXT: | | | |-UnaryOperator {{.*}} <col:30, col:31> 'int' postfix '++'
// CHECK-NEXT: | | | | `-DeclRefExpr {{.*}} <col:30> 'int' lvalue Var {{.*}} 'i' 'int'
// CHECK-NEXT: | | | `-NullStmt {{.*}} <line:40:9>
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <line:36:1> col:1 implicit .global_tid. 'const int *const restrict'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit .bound_tid. 'const int *const restrict'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.lb. 'const unsigned long'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit used .previous.ub. 'const unsigned long'
// CHECK-NEXT: | | |-ImplicitParamDecl {{.*}} <col:1> col:1 implicit __context 'struct (anonymous at {{.*}}ast-dump-openmp-teams-distribute-parallel-for.c:36:1) *const restrict'
// CHECK-NEXT: | | |-VarDecl {{.*}} <line:37:8, col:16> col:12 used i 'int' cinit
// CHECK-NEXT: | | | `-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | |-VarDecl {{.*}} <line:38:10, col:18> col:14 used i 'int' cinit
// CHECK-NEXT: | | | `-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | `-VarDecl {{.*}} <line:39:12, col:20> col:16 used i 'int' cinit
// CHECK-NEXT: | | `-IntegerLiteral {{.*}} <col:20> 'int' 0
// CHECK-NEXT: | |-OMPCapturedExprDecl {{.*}} <line:37:23> col:23 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | `-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: | |-OMPCapturedExprDecl {{.*}} <line:38:25> col:25 implicit used .capture_expr. 'int'
// CHECK-NEXT: | | `-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: | `-OMPCapturedExprDecl {{.*}} <line:37:3, <invalid sloc>> col:3 implicit used .capture_expr. 'long'
// CHECK-NEXT: | `-BinaryOperator {{.*}} <col:3, <invalid sloc>> 'long' '-'
// CHECK-NEXT: | |-BinaryOperator {{.*}} <col:3, line:38:28> 'long' '*'
// CHECK-NEXT: | | |-ImplicitCastExpr {{.*}} <line:37:3, col:26> 'long' <IntegralCast>
// CHECK-NEXT: | | | `-BinaryOperator {{.*}} <col:3, col:26> 'int' '/'
// CHECK-NEXT: | | | |-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | `-BinaryOperator {{.*}} <col:23, col:3> 'int' '-'
// CHECK-NEXT: | | | | |-ImplicitCastExpr {{.*}} <col:23> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | | `-DeclRefExpr {{.*}} <col:23> 'int' lvalue OMPCapturedExpr {{.*}} '.capture_expr.' 'int'
// CHECK-NEXT: | | | | `-ParenExpr {{.*}} <col:3> 'int'
// CHECK-NEXT: | | | | `-BinaryOperator {{.*}} <col:16, <invalid sloc>> 'int' '+'
// CHECK-NEXT: | | | | |-BinaryOperator {{.*}} <col:16, col:26> 'int' '-'
// CHECK-NEXT: | | | | | |-IntegerLiteral {{.*}} <col:16> 'int' 0
// CHECK-NEXT: | | | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | | | `-IntegerLiteral {{.*}} <col:26> 'int' 1
// CHECK-NEXT: | | `-ImplicitCastExpr {{.*}} <line:38:5, col:28> 'long' <IntegralCast>
// CHECK-NEXT: | | `-BinaryOperator {{.*}} <col:5, col:28> 'int' '/'
// CHECK-NEXT: | | |-ParenExpr {{.*}} <col:5> 'int'
// CHECK-NEXT: | | | `-BinaryOperator {{.*}} <col:25, col:5> 'int' '-'
// CHECK-NEXT: | | | |-ImplicitCastExpr {{.*}} <col:25> 'int' <LValueToRValue>
// CHECK-NEXT: | | | | `-DeclRefExpr {{.*}} <col:25> 'int' lvalue OMPCapturedExpr {{.*}} '.capture_expr.' 'int'
// CHECK-NEXT: | | | `-ParenExpr {{.*}} <col:5> 'int'
// CHECK-NEXT: | | | `-BinaryOperator {{.*}} <col:18, <invalid sloc>> 'int' '+'
// CHECK-NEXT: | | | |-BinaryOperator {{.*}} <col:18, col:28> 'int' '-'
// CHECK-NEXT: | | | | |-IntegerLiteral {{.*}} <col:18> 'int' 0
// CHECK-NEXT: | | | | `-IntegerLiteral {{.*}} <col:28> 'int' 1
// CHECK-NEXT: | | | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: | | `-IntegerLiteral {{.*}} <col:28> 'int' 1
// CHECK-NEXT: | `-ImplicitCastExpr {{.*}} <<invalid sloc>> 'long' <IntegralCast>
// CHECK-NEXT: | `-IntegerLiteral {{.*}} <<invalid sloc>> 'int' 1
// CHECK-NEXT: |-DeclRefExpr {{.*}} <line:37:3> 'int' lvalue ParmVar {{.*}} 'x' 'int'
// CHECK-NEXT: |-DeclRefExpr {{.*}} <line:38:5> 'int' lvalue ParmVar {{.*}} 'y' 'int'
// CHECK-NEXT: `-DeclRefExpr {{.*}} <line:39:27> 'int' lvalue ParmVar {{.*}} 'z' 'int'
|
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
|
serial_tree_learner.h | #ifndef LIGHTGBM_TREELEARNER_SERIAL_TREE_LEARNER_H_
#define LIGHTGBM_TREELEARNER_SERIAL_TREE_LEARNER_H_
#include <LightGBM/tree_learner.h>
#include <LightGBM/utils/random.h>
#include <LightGBM/utils/array_args.h>
#include <LightGBM/dataset.h>
#include <LightGBM/tree.h>
#include "feature_histogram.hpp"
#include "split_info.hpp"
#include "data_partition.hpp"
#include "leaf_splits.hpp"
#include <cstdio>
#include <vector>
#include <random>
#include <cmath>
#include <memory>
#ifdef USE_GPU
// Use 4KBytes aligned allocator for ordered gradients and ordered hessians when GPU is enabled.
// This is necessary to pin the two arrays in memory and make transferring faster.
#include <boost/align/aligned_allocator.hpp>
#endif
using namespace json11;
namespace LightGBM {
/*!
* \brief Used for learning a tree by single machine
*/
class SerialTreeLearner: public TreeLearner {
public:
explicit SerialTreeLearner(const Config* config);
~SerialTreeLearner();
void Init(const Dataset* train_data, bool is_constant_hessian) override;
void ResetTrainingData(const Dataset* train_data) override;
void ResetConfig(const Config* config) override;
Tree* Train(const score_t* gradients, const score_t *hessians, bool is_constant_hessian,
Json& forced_split_json) override;
Tree* FitByExistingTree(const Tree* old_tree, const score_t* gradients, const score_t* hessians) const override;
Tree* FitByExistingTree(const Tree* old_tree, const std::vector<int>& leaf_pred,
const score_t* gradients, const score_t* hessians) override;
void SetBaggingData(const data_size_t* used_indices, data_size_t num_data) override {
data_partition_->SetUsedDataIndices(used_indices, num_data);
}
void AddPredictionToScore(const Tree* tree, double* out_score) const override {
if (tree->num_leaves() <= 1) { return; }
CHECK(tree->num_leaves() <= data_partition_->num_leaves());
#pragma omp parallel for schedule(static)
for (int i = 0; i < tree->num_leaves(); ++i) {
double output = static_cast<double>(tree->LeafOutput(i));
data_size_t cnt_leaf_data = 0;
auto tmp_idx = data_partition_->GetIndexOnLeaf(i, &cnt_leaf_data);
for (data_size_t j = 0; j < cnt_leaf_data; ++j) {
out_score[tmp_idx[j]] += output;
}
}
}
void RenewTreeOutput(Tree* tree, const ObjectiveFunction* obj, const double* prediction,
data_size_t total_num_data, const data_size_t* bag_indices, data_size_t bag_cnt) const override;
void RenewTreeOutput(Tree* tree, const ObjectiveFunction* obj, double prediction,
data_size_t total_num_data, const data_size_t* bag_indices, data_size_t bag_cnt) const override;
protected:
/*!
* \brief Some initial works before training
*/
virtual void BeforeTrain();
/*!
* \brief Some initial works before FindBestSplit
*/
virtual bool BeforeFindBestSplit(const Tree* tree, int left_leaf, int right_leaf);
virtual void FindBestSplits();
virtual void ConstructHistograms(const std::vector<int8_t>& is_feature_used, bool use_subtract);
virtual void FindBestSplitsFromHistograms(const std::vector<int8_t>& is_feature_used, bool use_subtract);
/*!
* \brief Partition tree and data according best split.
* \param tree Current tree, will be splitted on this function.
* \param best_leaf The index of leaf that will be splitted.
* \param left_leaf The index of left leaf after splitted.
* \param right_leaf The index of right leaf after splitted.
*/
virtual void Split(Tree* tree, int best_leaf, int* left_leaf, int* right_leaf);
/* Force splits with forced_split_json dict and then return num splits forced.*/
virtual int32_t ForceSplits(Tree* tree, Json& forced_split_json, int* left_leaf,
int* right_leaf, int* cur_depth,
bool *aborted_last_force_split);
/*!
* \brief Get the number of data in a leaf
* \param leaf_idx The index of leaf
* \return The number of data in the leaf_idx leaf
*/
inline virtual data_size_t GetGlobalDataCountInLeaf(int leaf_idx) const;
double CalculateOndemandCosts(int feature_index, int leaf_index);
/*! \brief number of data */
data_size_t num_data_;
/*! \brief number of features */
int num_features_;
/*! \brief training data */
const Dataset* train_data_;
/*! \brief gradients of current iteration */
const score_t* gradients_;
/*! \brief hessians of current iteration */
const score_t* hessians_;
/*! \brief training data partition on leaves */
std::unique_ptr<DataPartition> data_partition_;
/*! \brief used for generate used features */
Random random_;
/*! \brief used for sub feature training, is_feature_used_[i] = false means don't used feature i */
std::vector<int8_t> is_feature_used_;
/*! \brief pointer to histograms array of parent of current leaves */
FeatureHistogram* parent_leaf_histogram_array_;
/*! \brief pointer to histograms array of smaller leaf */
FeatureHistogram* smaller_leaf_histogram_array_;
/*! \brief pointer to histograms array of larger leaf */
FeatureHistogram* larger_leaf_histogram_array_;
/*! \brief store best split points for all leaves */
std::vector<SplitInfo> best_split_per_leaf_;
/*! \brief store best split per feature for all leaves */
std::vector<SplitInfo> splits_per_leaf_;
/*! \brief stores best thresholds for all feature for smaller leaf */
std::unique_ptr<LeafSplits> smaller_leaf_splits_;
/*! \brief stores best thresholds for all feature for larger leaf */
std::unique_ptr<LeafSplits> larger_leaf_splits_;
std::vector<int> valid_feature_indices_;
#ifdef USE_GPU
/*! \brief gradients of current iteration, ordered for cache optimized, aligned to 4K page */
std::vector<score_t, boost::alignment::aligned_allocator<score_t, 4096>> ordered_gradients_;
/*! \brief hessians of current iteration, ordered for cache optimized, aligned to 4K page */
std::vector<score_t, boost::alignment::aligned_allocator<score_t, 4096>> ordered_hessians_;
#else
/*! \brief gradients of current iteration, ordered for cache optimized */
std::vector<score_t> ordered_gradients_;
/*! \brief hessians of current iteration, ordered for cache optimized */
std::vector<score_t> ordered_hessians_;
#endif
/*! \brief Store ordered bin */
std::vector<std::unique_ptr<OrderedBin>> ordered_bins_;
/*! \brief True if has ordered bin */
bool has_ordered_bin_ = false;
/*! \brief is_data_in_leaf_[i] != 0 means i-th data is marked */
std::vector<char> is_data_in_leaf_;
/*! \brief used to cache historical histogram to speed up*/
HistogramPool histogram_pool_;
/*! \brief config of tree learner*/
const Config* config_;
int num_threads_;
std::vector<int> ordered_bin_indices_;
bool is_constant_hessian_;
std::vector<bool> feature_used;
std::vector<uint32_t> feature_used_in_data;
};
inline data_size_t SerialTreeLearner::GetGlobalDataCountInLeaf(int leaf_idx) const {
if (leaf_idx >= 0) {
return data_partition_->leaf_count(leaf_idx);
} else {
return 0;
}
}
} // namespace LightGBM
#endif // LightGBM_TREELEARNER_SERIAL_TREE_LEARNER_H_
|
ndarray.c | #include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <stdarg.h>
#include <assert.h>
#include <time.h>
#include <math.h>
#include <omp.h>
#include "ndarray.h"
#include "ndshape.h"
size_t get_item_size(DataType datatype) {
switch(datatype) {
case DT_INT:
return sizeof(int);
break;
case DT_DOUBLE:
return sizeof(double);
break;
case DT_BOOL:
return sizeof(char);
default:
return -1;
}
}
NdArray* NdArray_new(void *data, NdShape *ndshape, DataType datatype) {
NdArray *ndarray = (NdArray*)malloc(sizeof(NdArray));
ndarray->shape = NdShape_copy(ndshape);
ndarray->datatype = datatype;
ndarray->item_size = get_item_size(ndarray->datatype);
ndarray->size = ndarray->item_size * ndarray->shape->len;
ndarray->data = malloc(ndarray->size);
if(data == NULL) {
memset(ndarray->data, 0, ndarray->size);
} else {
memcpy(ndarray->data, data, ndarray->size);
}
return ndarray;
}
NdArray* NdArray_copy(NdArray *src) {
NdArray *dest = NdArray_new(NULL, src->shape, src->datatype);
memcpy(dest->data, src->data, src->size);
return dest;
}
void NdArray_free(NdArray **dptr_ndarray) {
NdShape_free(&((*dptr_ndarray)->shape));
free((*dptr_ndarray)->data);
free(*dptr_ndarray);
*dptr_ndarray= NULL;
}
void NdArray_sub_free(NdArray **dptr_ndarray) {
NdShape_free(&((*dptr_ndarray)->shape));
free(*dptr_ndarray);
*dptr_ndarray= NULL;
}
NdArray* NdArray_zeros(unsigned int len, DataType datatype) {
NdShape *ndshape = NdShape_new(1, len);
NdArray *ndarray = NdArray_new(NULL, ndshape, datatype);
NdShape_free(&ndshape);
return ndarray;
}
NdArray* NdArray_ones(unsigned int len, DataType datatype) {
NdArray *ndarray = NdArray_zeros(len, datatype);
void *cur = ndarray->data;
for(int i = 0; i < len; i++) {
switch(datatype) {
case DT_INT:
*((int*)cur + i) = 1;
break;
case DT_DOUBLE:
*((double*)cur + i) = 1.0;
break;
default:
abort();
}
}
return ndarray;
}
NdArray* NdArray_arange(unsigned int start, unsigned int end, DataType datatype) {
int len = end - start;
NdArray *ndarray = NdArray_zeros(len, datatype);
void *cur = ndarray->data;
for(int i = 0; i < len; i++) {
switch(datatype) {
case DT_INT:
*((int*)cur + i) = start + i;
break;
case DT_DOUBLE:
*((double*)cur + i) = (double)(start + i);
break;
default:
abort();
}
}
return ndarray;
}
NdArray* NdArray_random(unsigned int len, DataType datatype) {
NdArray *ndarray = NdArray_zeros(len, datatype);
void* cur = ndarray->data;
srand(time(NULL));
for(int i = 0; i < ndarray->shape->len; i++) {
switch(datatype) {
case DT_INT:
*((int*)cur + i) = rand();
break;
case DT_DOUBLE:
*((double*)cur + i) = (double)rand() / (RAND_MAX - 10);
break;
default:
abort();
}
}
return ndarray;
}
NdArray* NdArray_random_range(unsigned int len, unsigned int low, unsigned int high, DataType datatype) {
assert(len > 0);
assert(low < high);
NdArray *ndarray = NdArray_zeros(len, datatype);
void* cur = ndarray->data;
int bound = high - low;
srand(time(NULL));
for(int i = 0; i < ndarray->shape->len; i++) {
switch(datatype) {
case DT_INT:
*((int*)cur + i) = rand() % bound + low;
break;
case DT_DOUBLE:
*((double*)cur + i) = (double)rand() / (RAND_MAX) + rand() % bound + low;
break;
default:
abort();
}
}
return ndarray;
}
double get_gaussian_random_value() {
double v1, v2, s;
do {
v1 = 2 * ((double) rand() / RAND_MAX) - 1;
v2 = 2 * ((double) rand() / RAND_MAX) - 1;
s = v1 * v1 + v2 * v2;
} while(s >= 1 || s == 0);
s = sqrt((-2 * log(s)) / s);
return v1 * s;
}
NdArray* NdArray_random_gaussian(unsigned int len) {
NdArray *ndarray = NdArray_zeros(len, DT_DOUBLE);
double *cur = ndarray->data;
srand(time(NULL));
for(int i = 0; i < len; i++) {
cur[i] = get_gaussian_random_value();
}
return ndarray;
}
NdArray* NdArray_shuffle(NdArray *array) {
srand(time(NULL));
for(int i = array->shape->len-1; i > 0; i--) {
int random_idx = rand() % i;
switch(array->datatype) {
case DT_INT:
{
int *cur = array->data;
int temp = cur[i];
cur[i] = cur[random_idx];
cur[random_idx] = temp;
}
break;
case DT_DOUBLE:
{
double *cur = array->data;
double temp = cur[i];
cur[i] = cur[random_idx];
cur[random_idx] = temp;
}
break;
default:
abort();
}
}
return array;
}
NdArray* NdArray_choice(unsigned int pick_len, unsigned int len, DataType datatype) {
assert(len >= pick_len );
NdArray* choices = NdArray_zeros(pick_len, datatype);
NdArray* temp = NdArray_arange(0, len, datatype);
NdArray_shuffle(temp);
memcpy(choices->data, temp->data, choices->size);
NdArray_free(&temp);
return choices;
}
int NdArray_reshape(NdArray *ndarray, NdShape *ndshape) {
return NdShape_reshape(ndarray->shape, ndshape);
}
int NdArray_reshape_fixed_array(NdArray *self, unsigned int dim, unsigned int *arr) {
return NdShape_reshape_fixed_array(self->shape, dim, arr);
}
int NdArray_reshape_variadic(NdArray *self, unsigned int dim, ...) {
unsigned int arr[dim];
va_list args;
va_start(args, dim);
for(int i = 0; i < dim; i++) {
arr[i] = va_arg(args, unsigned int);
}
va_end(args);
return NdShape_reshape_fixed_array(self->shape, dim, arr);
}
unsigned int get_offset(NdArray *ndarray, unsigned int *position, int pdim) {
unsigned int offset = 0;
unsigned int len = ndarray->shape->len;
for(int i = 0; i < pdim; i++) {
len /= ndarray->shape->arr[i];
offset += position[i] * len;
}
offset *= ndarray->item_size;
return offset;
}
void* NdArray_getAt(NdArray *ndarray, unsigned int *position) {
unsigned int offset = get_offset(ndarray, position, ndarray->shape->dim);
return ndarray->data + offset;
}
void NdArray_setAt(NdArray *ndarray, unsigned int *position, void* data) {
void *target_address = NdArray_getAt(ndarray, position);
switch(ndarray->datatype) {
case DT_INT:
*((int*)target_address) = *(int*)data;
break;
case DT_DOUBLE:
*((double*)target_address) = *(double*)data;
break;
default:
fprintf(stderr, "invalid datatype");
abort();
}
}
NdArray* NdArray_subarray(NdArray *ndarray, unsigned int *position, int pdim) {
unsigned int offset = get_offset(ndarray, position, pdim);
unsigned int subarray_dim = ndarray->shape->dim - pdim;
NdShape *subshape = NdShape_empty(subarray_dim);
for(int i = 0; i < subarray_dim; i++) {
subshape->arr[i] = ndarray->shape->arr[pdim + i];
subshape->len *= subshape->arr[i];
}
NdArray *subarray = NdArray_new(ndarray->data + offset, subshape, ndarray->datatype);
return subarray;
}
void print_element(NdArray *ndarray, unsigned int *position) {
void* ptr_element = NdArray_getAt(ndarray, position);
switch(ndarray->datatype) {
case DT_INT:
printf("%d ", *(int*)ptr_element);
break;
case DT_DOUBLE:
printf("%f ", *(double*)ptr_element);
break;
case DT_BOOL:
printf("%d ", *(char*)ptr_element);
break;
default:
abort();
}
}
void printArray(NdArray *ndarray, unsigned int *position, int dim) {
if(dim == ndarray->shape->dim) {
print_element(ndarray, position);
return;
}
printf("[ ");
for(int i = 0; i < ndarray->shape->arr[dim]; i++) {
position[dim] = i;
printArray(ndarray, position, dim+1);
}
printf("] ");
}
void NdArray_printArray(NdArray *ndarray) {
unsigned int position[ndarray->shape->dim];
memset(position, 0, sizeof(unsigned int) * ndarray->shape->dim);
printArray(ndarray, position, 0);
printf("\n");
}
void NdArray_printShape(NdArray *ndarray) {
return NdShape_print(ndarray->shape);
}
int NdArray_is_arithmetically_vaild(NdArray *a, NdArray *b){
if(a->datatype != b->datatype) {
return 0;
}
if(a->shape->dim < b->shape->dim) {
return 0;
}
for(int i = 0; i < b->shape->dim; i++) {
if(a->shape->arr[a->shape->dim-i-1] != b->shape->arr[b->shape->dim-i-1]) {
return 0;
}
}
return 1;
}
int NdArray_add(NdArray *dest, NdArray *src) {
void *cur_dest;
void *cur_src;
if(!NdArray_is_arithmetically_vaild(dest, src)) {
return 0;
}
cur_dest = dest->data;
for(int i = 0; i < dest->shape->len / src->shape->len; i++) {
cur_src = src->data;
for(int j = 0; j < src->shape->len; j++) {
switch(dest->datatype) {
case DT_INT:
*((int*)cur_dest) += *((int*)cur_src);
break;
case DT_DOUBLE:
*((double*)cur_dest) += *((double*)cur_src);
break;
default:
abort();
}
cur_dest += dest->item_size;
cur_src += src->item_size;
}
}
return 1;
}
int NdArray_sub(NdArray *dest, NdArray *src) {
void *cur_dest;
void *cur_src;
if(!NdArray_is_arithmetically_vaild(dest, src)) {
return 0;
}
cur_dest = dest->data;
for(int i = 0; i < dest->shape->len / src->shape->len; i++) {
cur_src = src->data;
for(int j = 0; j < src->shape->len; j++) {
switch(dest->datatype) {
case DT_INT:
*((int*)cur_dest) -= *((int*)cur_src);
break;
case DT_DOUBLE:
*((double*)cur_dest) -= *((double*)cur_src);
break;
default:
abort();
}
cur_dest += dest->item_size;
cur_src += src->item_size;
}
}
return 1;
}
int NdArray_mul(NdArray *dest, NdArray *src) {
void *cur_dest;
void *cur_src;
if(!NdArray_is_arithmetically_vaild(dest, src)) {
return 0;
}
cur_dest = dest->data;
for(int i = 0; i < dest->shape->len / src->shape->len; i++) {
cur_src = src->data;
for(int j = 0; j < src->shape->len; j++) {
switch(dest->datatype) {
case DT_INT:
*((int*)cur_dest) *= *((int*)cur_src);
break;
case DT_DOUBLE:
*((double*)cur_dest) *= *((double*)cur_src);
break;
default:
abort();
}
cur_dest += dest->item_size;
cur_src += src->item_size;
}
}
return 1;
}
int NdArray_div(NdArray *dest, NdArray *src) {
void *cur_dest;
void *cur_src;
if(!NdArray_is_arithmetically_vaild(dest, src)) {
return 0;
}
cur_dest = dest->data;
for(int i = 0; i < dest->shape->len / src->shape->len; i++) {
cur_src = src->data;
for(int j = 0; j < src->shape->len; j++) {
switch(dest->datatype) {
case DT_INT:
*((int*)cur_dest) /= *((int*)cur_src);
break;
case DT_DOUBLE:
*((double*)cur_dest) /= *((double*)cur_src);
break;
default:
abort();
}
cur_dest += dest->item_size;
cur_src += src->item_size;
}
}
return 1;
}
int NdArray_mod(NdArray *dest, NdArray *src) {
assert(dest->datatype != DT_DOUBLE || src->datatype != DT_DOUBLE);
if(!NdShape_compare(dest->shape, src->shape)) {
return 0;
}
void *ptr_data_dest = dest->data;
void *ptr_data_src = src->data;
for(int i = 0; i < dest->shape->len; i++) {
switch(dest->datatype) {
case DT_INT:
*((int*)ptr_data_dest) %= *((int*)ptr_data_src);
break;
case DT_DOUBLE:
default:
abort();
}
ptr_data_dest += dest->item_size;
ptr_data_src += src->item_size;
}
return 1;
}
void matmul_int(int *a, int *b, int *c, int p, int q, int r) {
#pragma omp parallel for
for(int i = 0; i < p; i++) {
for(int k = 0; k < q; k++) {
register int v = a[i * q + k];
for(int j = 0; j < r; j++) {
c[i * r + j] += v * b[k * r + j];
}
}
}
}
void matmul_double(double *a, double *b, double *c, int p, int q, int r) {
#pragma omp parallel for
for(int i = 0; i < p; i++) {
for(int k = 0; k < q; k++) {
register double v = a[i * q + k];
for(int j = 0; j < r; j++) {
c[i * r + j] += v * b[k * r + j];
}
}
}
}
NdArray* matmul_2d(NdArray *a, NdArray *b) {
NdShape *shape_result = NdShape_new(2, a->shape->arr[0], b->shape->arr[1]);
NdArray *result = NdArray_new(NULL, shape_result, a->datatype);
switch(result->datatype) {
case DT_INT:
matmul_int(a->data, b->data, result->data,
result->shape->arr[0], a->shape->arr[1], result->shape->arr[1]);
break;
case DT_DOUBLE:
matmul_double(a->data, b->data, result->data,
result->shape->arr[0], a->shape->arr[1], result->shape->arr[1]);
break;
default:
abort();
}
return result;
}
void matmul_recursive(NdArray *result, NdArray *a, NdArray *b, unsigned int *position, unsigned int dim) {
NdShape *shape_result = result->shape;
if(dim >= shape_result->dim-2) {
NdShape *shape_a = a->shape;
NdShape *shape_b = b->shape;
unsigned int position_a[shape_a->dim-2];
unsigned int position_b[shape_b->dim-2];
int offset_a = (shape_a->dim >= shape_b->dim) ? 0 : shape_b->dim - shape_a->dim;
int offset_b = (shape_a->dim >= shape_b->dim) ? shape_a->dim - shape_b->dim : 0;
memcpy(position_a, position + offset_a, sizeof(unsigned int) * (shape_a->dim-2));
memcpy(position_b, position + offset_b, sizeof(unsigned int) * (shape_b->dim-2));
void *mat_a = a->data + get_offset(a, position_a, shape_a->dim-2);
void *mat_b = b->data + get_offset(b, position_b, shape_b->dim-2);
void *mat_result = result->data + get_offset(result, position, dim);
int p = a->shape->arr[shape_a->dim-2];
int q = a->shape->arr[shape_a->dim-1];
int r = b->shape->arr[shape_b->dim-1];
switch(result->datatype) {
case DT_INT:
matmul_int(mat_a, mat_b, mat_result, p, q, r);
break;
case DT_DOUBLE:
matmul_double(mat_a, mat_b, mat_result, p, q, r);
break;
default:
abort();
}
return;
}
for(int i = 0; i < shape_result->arr[dim]; i++) {
position[dim] = i;
matmul_recursive(result, a, b, position, dim+1);
}
}
NdArray* matmul_nd(NdArray *a, NdArray *b) {
NdArray *result;
NdShape *shape_result;
DataType datatype_result;
datatype_result = a->datatype;
NdShape *shape_a = a->shape;
NdShape *shape_b = b->shape;
int bound = (shape_a->dim >= shape_b->dim) ? shape_b->dim-2 : shape_a->dim-2;
for(int i = 0; i < bound; i++) {
if(shape_a->arr[shape_a->dim-i-3] != shape_b->arr[shape_b->dim-i-3]) {
return NULL;
}
}
if(shape_a->dim >= shape_b->dim) {
shape_result = NdShape_copy(shape_a);
shape_result->arr[shape_result->dim-1] = shape_b->arr[shape_b->dim-1];
} else {
shape_result = NdShape_copy(shape_b);
shape_result->arr[shape_result->dim-2] = shape_a->arr[shape_a->dim-2];
}
result = NdArray_new(NULL, shape_result, datatype_result);
unsigned int position[shape_result->dim-2];
memset(position, 0, sizeof(unsigned int) * (shape_result->dim-2));
matmul_recursive(result, a, b, position, 0);
return result;
}
NdArray* dot_2d(NdArray *a, NdArray *b) {
return matmul_2d(a, b);
}
void dot_recursive(NdArray *result, NdArray *a, NdArray *b, unsigned int *position, unsigned int dim) {
NdShape *shape_result = result->shape;
if(dim >= shape_result->dim) {
NdShape *shape_a = a->shape;
NdShape *shape_b = b->shape;
unsigned int position_a[shape_a->dim];
unsigned int position_b[shape_b->dim];
memcpy(position_a, position, sizeof(unsigned int) * (shape_a->dim-1));
memcpy(position_b, position + (shape_a->dim-1), sizeof(unsigned int) * (shape_b->dim-1));
position_b[shape_b->dim-1] = position_b[shape_b->dim-2];
void *ptr_value_a;
void *ptr_value_b;
void *ptr_value_result = NdArray_getAt(result, position);
memset(ptr_value_result, 0, result->item_size);
for(int i = 0; i < shape_a->arr[shape_a->dim-1]; i++) {
position_a[shape_a->dim-1] = i;
position_b[shape_b->dim-2] = i;
ptr_value_a = NdArray_getAt(a, position_a);
ptr_value_b = NdArray_getAt(b, position_b);
if(result->datatype == DT_INT) {
*(int*)ptr_value_result += (*(int*)ptr_value_a) * (*(int*)ptr_value_b);
} else if(result->datatype == DT_DOUBLE) {
*(double*)ptr_value_result += (*(double*)ptr_value_a) * (*(double*)ptr_value_b);
}
}
return;
}
for(int i = 0; i < shape_result->arr[dim]; i++) {
position[dim] = i;
dot_recursive(result, a, b, position, dim+1);
}
}
NdArray* dot_nd(NdArray *a, NdArray *b) {
NdArray *result;
NdShape *shape_result;
DataType datatype_result;
datatype_result = a->datatype;
NdShape *shape_a = a->shape;
NdShape *shape_b = b->shape;
shape_result = NdShape_empty(shape_a->dim + shape_b->dim - 2);
memcpy(shape_result->arr, shape_a->arr, sizeof(unsigned int) * (shape_a->dim-1));
memcpy(shape_result->arr + (shape_a->dim-1), shape_b->arr, sizeof(unsigned int) * (shape_b->dim-1));
shape_result->arr[shape_result->dim-1] = shape_b->arr[shape_b->dim-1];
for(int i = 0; i < shape_result->dim; i++) {
shape_result->len *= shape_result->arr[i];
}
result = NdArray_new(NULL, shape_result, datatype_result);
unsigned int position[shape_result->dim];
memset(position, 0, sizeof(unsigned int) * shape_result->dim);
dot_recursive(result, a, b, position, 0);
return result;
}
NdArray* NdArray_dot(NdArray *a, NdArray *b) {
if(a->shape->arr[a->shape->dim-1] != b->shape->arr[b->shape->dim-2]) {
abort();
}
if(a->shape->dim == 2 && b->shape->dim == 2) {
return dot_2d(a, b);
} else {
return dot_nd(a, b);
}
}
NdArray* NdArray_matmul(NdArray *a, NdArray *b) {
if(a->shape->arr[a->shape->dim-1] != b->shape->arr[b->shape->dim-2]) {
abort();
}
if(a->shape->dim == 2 && b->shape->dim == 2) {
return matmul_2d(a, b);
} else {
return matmul_nd(a, b);
}
}
void transpose_recursive(NdArray* array, NdArray *transposed, unsigned int *position, int dim) {
if(dim >= array->shape->dim) {
unsigned int tdim = transposed->shape->dim;
unsigned int position_transpose[tdim];
for(int i = 0; i < tdim; i++) {
position_transpose[i] = position[tdim-i-1];
}
unsigned int offset_array = get_offset(array, position, array->shape->dim);
unsigned int offset_transposed = get_offset(transposed, position_transpose, transposed->shape->dim);
void *cur_array = array->data + offset_array;
void *cur_transposed = transposed->data + offset_transposed;
memcpy(cur_transposed, cur_array, array->item_size);
return;
}
for(int i = 0; i < array->shape->arr[dim]; i++) {
position[dim] = i;
transpose_recursive(array, transposed, position, dim+1);
}
}
NdArray* NdArray_transpose(NdArray *self) {
NdShape *shape_transposed = NdShape_reverse(self->shape);
NdArray *transposed = NdArray_zeros(self->shape->len, self->datatype);
NdArray_reshape(transposed, shape_transposed);
unsigned int position[self->shape->dim];
transpose_recursive(self, transposed, position, 0);
NdShape_free(&shape_transposed);
return transposed;
}
void NdArray_add_scalar(NdArray *ndarray, double value) {
void *ptr_data = ndarray->data;
for(int i = 0; i < ndarray->shape->len; i++) {
switch(ndarray->datatype) {
case DT_INT:
*(int*)ptr_data += (int)value;
break;
case DT_DOUBLE:
*(double*)ptr_data += value;
break;
default:
abort();
}
ptr_data += ndarray->item_size;
}
}
void NdArray_sub_scalar(NdArray *ndarray, double value) {
void *ptr_data = ndarray->data;
for(int i = 0; i < ndarray->shape->len; i++) {
switch(ndarray->datatype) {
case DT_INT:
*(int*)ptr_data -= (int)value;
break;
case DT_DOUBLE:
*(double*)ptr_data -= value;
break;
default:
abort();
}
ptr_data += ndarray->item_size;
}
}
void NdArray_mul_scalar(NdArray *ndarray, double value) {
void *ptr_data = ndarray->data;
for(int i = 0; i < ndarray->shape->len; i++) {
switch(ndarray->datatype) {
case DT_INT:
*(int*)ptr_data *= (int)value;
break;
case DT_DOUBLE:
*(double*)ptr_data *= value;
break;
default:
abort();
}
ptr_data += ndarray->item_size;
}
}
void NdArray_div_scalar(NdArray *ndarray, double value) {
assert(value != 0);
void *ptr_data = ndarray->data;
for(int i = 0; i < ndarray->shape->len; i++) {
switch(ndarray->datatype) {
case DT_INT:
*(int*)ptr_data /= (int)value;
break;
case DT_DOUBLE:
*(double*)ptr_data /= value;
break;
default:
abort();
}
ptr_data += ndarray->item_size;
}
}
void NdArray_mod_scalar(NdArray *ndarray, int value) {
assert(ndarray->datatype != DT_DOUBLE);
assert(value != 0);
void *ptr_data = ndarray->data;
for(int i = 0; i < ndarray->shape->len; i++) {
switch(ndarray->datatype) {
case DT_INT:
*(int*)ptr_data %= (int)value;
break;
case DT_DOUBLE:
default:
abort();
}
ptr_data += ndarray->item_size;
}
}
void NdArray_broadcast(NdArray *ndarray, broadcast_func bfunc) {
void *ptr_data = ndarray->data;
for(int i = 0; i < ndarray->shape->len; i++) {
switch(ndarray->datatype) {
case DT_INT:
case DT_DOUBLE:
bfunc(ptr_data);
break;
default:
abort();
}
ptr_data += ndarray->item_size;
}
}
long NdArray_sum_char(NdArray *ndarray) {
char *data = (char*)ndarray->data;
long sum = 0;
for(int i = 0; i < ndarray->shape->len; i++) {
sum += data[i];
}
return sum;
}
long NdArray_sum_int(NdArray *ndarray) {
int *data = (int*)ndarray->data;
long sum = 0;
for(int i = 0; i < ndarray->shape->len; i++) {
sum += data[i];
}
return sum;
}
long double NdArray_sum_double(NdArray *ndarray) {
double *data = (double*)ndarray->data;
long double sum = 0;
for(int i = 0; i < ndarray->shape->len; i++) {
sum += data[i];
}
return sum;
}
void* NdArray_sum(NdArray *ndarray) {
void *ptr_sum = malloc(ndarray->item_size);
if(ndarray->datatype == DT_INT) {
*(int*)ptr_sum = NdArray_sum_int(ndarray);
} else if(ndarray->datatype == DT_DOUBLE) {
*(double*)ptr_sum = NdArray_sum_double(ndarray);
} else if(ndarray->datatype == DT_BOOL) {
*(char*)ptr_sum = NdArray_sum_char(ndarray);
} else {
abort();
}
return ptr_sum;
}
NdShape* get_ndshape_axis(NdShape *self, unsigned int axis) {
NdShape *shape_sum = NdShape_empty(self->dim-1);
for(int i = 0; i < shape_sum->dim; i++) {
shape_sum->arr[i] = (i >= axis) ? self->arr[i+1] : self->arr[i];
shape_sum->len *= shape_sum->arr[i];
}
return shape_sum;
}
NdArray* get_ndarray_axis(NdArray *self, unsigned int axis, DataType datatype) {
NdShape *shape_self = self->shape;
NdShape *shape_sum = get_ndshape_axis(self->shape, axis);
NdArray *array_sum = NdArray_new(NULL, shape_sum, datatype);
return array_sum;
}
unsigned int get_step_axis(NdShape *self, unsigned int axis) {
unsigned int step = self->len;
for(int i = 0; i <= axis; i++) {
step /= self->arr[i];
}
return step;
}
NdArray* cal_array_sum_axis(NdArray *self, NdArray *result, unsigned int axis) {
unsigned int step = get_step_axis(self->shape, axis);
unsigned int memo[self->shape->len];
for(int i = 0; i < self->shape->len; i++) {
memo[i] = 0;
}
void *cur = self->data;
void *cur_result = result->data;
void *sum = malloc(result->item_size);
for(int i = 0; i < self->shape->len; i++) {
if(memo[i] == 1) {
continue;
}
memset(sum, 0, result->item_size);
for(int j = 0; j < self->shape->arr[axis]; j++) {
int idx = i + j * step;
switch(result->datatype) {
case DT_INT:
*(int*)sum += *((int*)cur + idx);
break;
case DT_DOUBLE:
*(double*)sum += *((double*)cur + idx);
break;
default:
abort();
}
memo[idx] = 1;
}
memcpy(cur_result, sum, result->item_size);
cur_result += result->item_size;
}
free(sum);
return result;
}
NdArray* cal_array_argmax_axis(NdArray *self, NdArray *result, unsigned int axis) {
unsigned int step = get_step_axis(self->shape, axis);
unsigned int memo[self->shape->len];
for(int i = 0; i < self->shape->len; i++) {
memo[i] = 0;
}
void *cur = self->data;
int *cur_result = result->data;
void *max = malloc(self->item_size);
int max_idx;
for(int i = 0; i < self->shape->len; i++) {
if(memo[i] == 1) {
continue;
}
memcpy(max, cur + i * self->item_size, self->item_size);
max_idx = 0;
for(int j = 1; j < self->shape->arr[axis]; j++) {
int idx = i + j * step;
switch(self->datatype) {
case DT_INT:
if(*(int*)max < *((int*)cur + idx)) {
*(int*)max = *((int*)cur + idx);
max_idx = j;
}
break;
case DT_DOUBLE:
if(*(double*)max < *((double*)cur + idx)) {
*(double*)max = *((double*)cur + idx);
max_idx = j;
}
break;
default:
abort();
}
memo[idx] = 1;
}
*cur_result = max_idx;
cur_result++;
}
return result;
}
NdArray* cal_array_max_axis(NdArray *self, NdArray *result, unsigned int axis) {
unsigned int step = get_step_axis(self->shape, axis);
unsigned int memo[self->shape->len];
for(int i = 0; i < self->shape->len; i++) {
memo[i] = 0;
}
void *cur = self->data;
void *cur_result = result->data;
void *max = malloc(self->item_size);
for(int i = 0; i < self->shape->len; i++) {
if(memo[i] == 1) {
continue;
}
memcpy(max, cur + i * self->item_size, self->item_size);
for(int j = 1; j < self->shape->arr[axis]; j++) {
int idx = i + j * step;
switch(self->datatype) {
case DT_INT:
if(*(int*)max < *((int*)cur + idx)) {
*(int*)max = *((int*)cur + idx);
}
break;
case DT_DOUBLE:
if(*(double*)max < *((double*)cur + idx)) {
*(double*)max = *((double*)cur + idx);
}
break;
default:
abort();
}
memo[idx] = 1;
}
memcpy(cur_result, max, result->item_size);
cur_result += result->item_size;
}
return result;
}
NdArray* NdArray_sum_axis(NdArray *self, unsigned int axis) {
if(axis > self->shape->dim) {
return NULL;
}
NdArray *array_sum = get_ndarray_axis(self, axis, self->datatype);
cal_array_sum_axis(self, array_sum, axis);
return array_sum;
}
NdArray* NdArray_max_axis(NdArray *self, unsigned int axis) {
if(axis > self->shape->dim) {
return NULL;
}
NdArray *array_max = get_ndarray_axis(self, axis, self->datatype);
cal_array_max_axis(self, array_max, axis);
return array_max;
}
NdArray* NdArray_argmax_axis(NdArray *self, unsigned int axis) {
if(axis > self->shape->dim) {
return NULL;
}
NdArray *array_argmax = get_ndarray_axis(self, axis, DT_INT);
cal_array_argmax_axis(self, array_argmax, axis);
return array_argmax;
}
int NdArray_max_int(NdArray *ndarray) {
int *data = (int*)ndarray->data;
int max = data[0];
for(int i = 1; i < ndarray->shape->len; i++) {
max = (max < data[i]) ? data[i] : max;
}
return max;
}
double NdArray_max_double(NdArray *ndarray) {
double *data = (double*)ndarray->data;
double max = data[0];
for(int i = 1; i < ndarray->shape->len; i++) {
max = (max < data[i]) ? data[i] : max;
}
return max;
}
void* NdArray_max(NdArray *ndarray) {
void *ptr_max = malloc(ndarray->item_size);
if(ndarray->datatype == DT_INT) {
*(int*)ptr_max = NdArray_max_int(ndarray);
} else if(ndarray->datatype == DT_DOUBLE) {
*(double*)ptr_max = NdArray_max_double(ndarray);
}
return ptr_max;
}
int NdArray_min_int(NdArray *ndarray) {
int *data = (int*)ndarray->data;
int min = data[0];
for(int i = 1; i < ndarray->shape->len; i++) {
min = (min > data[i]) ? data[i] : min;
}
return min;
}
double NdArray_min_double(NdArray *ndarray) {
double *data = (double*)ndarray->data;
double min = data[0];
for(int i = 1; i < ndarray->shape->len; i++) {
min = (min > data[i]) ? data[i] : min;
}
return min;
}
void* NdArray_min(NdArray *ndarray) {
void *ptr_min = malloc(ndarray->item_size);
if(ndarray->datatype == DT_INT) {
*(int*)ptr_min = NdArray_min_int(ndarray);
} else if(ndarray->datatype == DT_DOUBLE) {
*(double*)ptr_min = NdArray_min_double(ndarray);
}
return ptr_min;
}
double NdArray_mean_int(NdArray *ndarray) {
int *data = (int*)ndarray->data;
double mean = (double)NdArray_sum_int(ndarray) / ndarray->shape->len;
return mean;
}
double NdArray_mean_double(NdArray *ndarray) {
double *data = (double*)ndarray->data;
double mean = NdArray_sum_double(ndarray) / ndarray->shape->len;
return mean;
}
void* NdArray_mean(NdArray *ndarray) {
void *ptr_mean = malloc(ndarray->item_size);
if(ndarray->datatype == DT_INT) {
*(int*)ptr_mean = NdArray_mean_int(ndarray);
} else if(ndarray->datatype == DT_DOUBLE) {
*(double*)ptr_mean = NdArray_mean_double(ndarray);
}
return ptr_mean;
}
int NdArray_argmax_int(NdArray *ndarray) {
int *cur = ndarray->data;
int max = *cur;
unsigned int idx_max = 0;
for(int i = 0; i < ndarray->shape->len; i++) {
if(max < *cur) {
max = *cur;
idx_max = i;
}
cur++;
}
return idx_max;
}
int NdArray_argmax_double(NdArray *ndarray) {
double *cur = ndarray->data;
double max = *cur;
unsigned int idx_max = 0;
for(int i = 0; i < ndarray->shape->len; i++) {
if(max < *cur) {
max = *cur;
idx_max = i;
}
cur++;
}
return idx_max;
}
int NdArray_argmax(NdArray *ndarray) {
void *cur = ndarray->data;
if(ndarray->datatype == DT_INT) {
return NdArray_argmax_int(ndarray);
} else if(ndarray->datatype == DT_DOUBLE) {
return NdArray_argmax_double(ndarray);
}
return -1;
}
int NdArray_argmin_int(NdArray *ndarray) {
int *cur = ndarray->data;
int min = *cur;
unsigned int idx_min = 0;
for(int i = 0; i < ndarray->shape->len; i++) {
if(min > *cur) {
min = *cur;
idx_min = i;
}
cur++;
}
return idx_min;
}
int NdArray_argmin_double(NdArray *ndarray) {
double *cur = ndarray->data;
double min = *cur;
unsigned int idx_min = 0;
for(int i = 0; i < ndarray->shape->len; i++) {
if(min > *cur) {
min = *cur;
idx_min = i;
}
cur++;
}
return idx_min;
}
int NdArray_argmin(NdArray *ndarray) {
void *cur = ndarray->data;
if(ndarray->datatype == DT_INT) {
return NdArray_argmin_int(ndarray);
} else if(ndarray->datatype == DT_DOUBLE) {
return NdArray_argmin_double(ndarray);
}
return -1;
}
void _convert_datatype_from_int_to_double(NdArray **ptr_self) {
NdArray *self = *ptr_self;
NdArray *converted = NdArray_new(NULL, self->shape, DT_DOUBLE);
int* cur_self = self->data;
double* cur_conv = converted->data;
for(int i = 0; i < converted->shape->len; i++) {
cur_conv[i] = (double)cur_self[i];
}
NdArray_free(&self);
*ptr_self = converted;
}
void _convert_datatype_from_double_to_int(NdArray **ptr_self) {
NdArray *self = *ptr_self;
NdArray *converted = NdArray_new(NULL, self->shape, DT_INT);
double* cur_self = self->data;
int* cur_conv = converted->data;
for(int i = 0; i < converted->shape->len; i++) {
cur_conv[i] = (int)cur_self[i];
}
NdArray_free(&self);
*ptr_self = converted;
}
void NdArray_convert_type(NdArray **ptr_self, DataType datatype) {
NdArray *self = *ptr_self;
if(self->datatype == datatype) {
return;
}
if(self->datatype == DT_INT && datatype == DT_DOUBLE) {
_convert_datatype_from_int_to_double(ptr_self);
} else if(self->datatype == DT_DOUBLE && datatype == DT_INT) {
_convert_datatype_from_double_to_int(ptr_self);
}
}
int _compare_int(int a, int b) {
return a - b;
}
int _compare_double(double a, double b) {
double temp = a - b;
if(temp > 0) {
return 1;
} else if(temp < 0) {
return -1;
} else {
return 0;
}
}
int _compare_element(const void *a, const void *b, DataType datatype) {
if(datatype == DT_INT) {
return _compare_int(*(int*)a, *(int*)b);
} else if(datatype == DT_DOUBLE) {
return _compare_double(*(double*)a, *(double*)b);
} else {
abort();
}
}
int _compare_element_scalar(const void *self, double value, DataType datatype) {
if(datatype == DT_INT) {
double temp = (double)(*(int*)self);
return _compare_double(temp, value);
} else if(datatype == DT_DOUBLE) {
return _compare_double(*(double*)self, value);
} else {
abort();
}
}
void _set_bool(void *cur, DataType datatype, int bool_value, CompareTag ct) {
if(ct == CT_GT && bool_value <= 0) {
memset(cur, 0, get_item_size(datatype));
} else if(ct == CT_GE && bool_value < 0) {
memset(cur, 0, get_item_size(datatype));
} else if(ct == CT_LT && bool_value >= 0) {
memset(cur, 0, get_item_size(datatype));
} else if(ct == CT_LE && bool_value > 0) {
memset(cur, 0, get_item_size(datatype));
} else if(ct == CT_EQ && bool_value != 0) {
memset(cur, 0, get_item_size(datatype));
} else {
*(char*)cur= 1;
}
}
NdArray* NdArray_compare(NdArray *a, NdArray *b, CompareTag ct) {
assert(a->shape->dim == b->shape->dim);
assert(a->shape->len == b->shape->len);
assert(a->datatype == b->datatype);
NdArray *result = NdArray_new(NULL, a->shape, DT_BOOL);
void *cur_a = a->data;
void *cur_b = b->data;
void *cur_result = result->data;
int bool_value = 0;
for(int i = 0; i < a->shape->len; i++) {
int bool_value = _compare_element(cur_a, cur_b, a->datatype);
_set_bool(cur_result, result->datatype, bool_value, ct);
cur_a += a->item_size;
cur_b += b->item_size;
cur_result += result->item_size;
}
return result;
}
NdArray* NdArray_compare_scalar(NdArray *self, double value, CompareTag ct) {
NdArray *result = NdArray_new(NULL, self->shape, DT_BOOL);
void *cur_self = self->data;
void *cur_result = result->data;
int bool_value = 0;
for(int i = 0; i < self->shape->len; i++) {
int bool_value = _compare_element_scalar(cur_self, value, self->datatype);
_set_bool(cur_result, result->datatype, bool_value, ct);
cur_self += self->item_size;
cur_result += result->item_size;
}
return result;
}
NdArray* NdArray_mask(NdArray *self, NdArray *mask) {
NdArray* result = NdArray_new(NULL, self->shape, self->datatype);
void* cur_self = self->data;
void* cur_mask = mask->data;
void* cur_result = result->data;
for(int i = 0; i < self->shape->len; i++) {
if(*(char*)cur_mask) {
memcpy(cur_result, cur_self, self->item_size);
}
cur_self += self->item_size;
cur_mask += mask->item_size;
cur_result += result->item_size;
}
return result;
}
|
dufu17r.c | /*
* Date: 11 December 2015
* Contact: Thomas Peyrin - thomas.peyrin@gmail.com
*/
/*
* Boomerang cryptanalysis of SKINNY
* Date: March 21, 2020
* Author: Hosein Hadipour
* Contact: hsn.hadipour@gmail.com
*/
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <time.h>
#include <math.h>
#include <omp.h>
#include <stdbool.h>
typedef unsigned long long uint64_t;
// #define DEBUG 1
#define Nthreads 16 // Number of parallel threads utilized in this program
#define NumOfExperiments 1 // Number of independent experiments
#define STEP ((1 << 10) - 1)
// Table that encodes the parameters of the various Skinny versions:
// (block size, key size, number of rounds)
//Skinny-64-64: 32 rounds
//Skinny-64-128: 36 rounds
//Skinny-64-192: 40 rounds
//Skinny-128-128: 40 rounds
//Skinny-128-256: 48 rounds
//Skinny-128-384: 56 rounds
int versions[6][3] = {{64, 64, 32}, {64, 128, 36}, {64, 192, 40}, {128, 128, 40}, {128, 256, 48}, {128, 384, 56}};
// Packing of data is done as follows (state[i][j] stands for row i and column j):
// 0 1 2 3
// 4 5 6 7
// 8 9 10 11
//12 13 14 15
// 4-bit Sbox
const unsigned char sbox_4[16] = {12, 6, 9, 0, 1, 10, 2, 11, 3, 8, 5, 13, 4, 14, 7, 15};
const unsigned char sbox_4_inv[16] = {3, 4, 6, 8, 12, 10, 1, 14, 9, 2, 5, 7, 0, 11, 13, 15};
// 8-bit Sbox
const unsigned char sbox_8[256] = {0x65, 0x4c, 0x6a, 0x42, 0x4b, 0x63, 0x43, 0x6b, 0x55, 0x75, 0x5a, 0x7a, 0x53, 0x73, 0x5b, 0x7b, 0x35, 0x8c, 0x3a, 0x81, 0x89, 0x33, 0x80, 0x3b, 0x95, 0x25, 0x98, 0x2a, 0x90, 0x23, 0x99, 0x2b, 0xe5, 0xcc, 0xe8, 0xc1, 0xc9, 0xe0, 0xc0, 0xe9, 0xd5, 0xf5, 0xd8, 0xf8, 0xd0, 0xf0, 0xd9, 0xf9, 0xa5, 0x1c, 0xa8, 0x12, 0x1b, 0xa0, 0x13, 0xa9, 0x05, 0xb5, 0x0a, 0xb8, 0x03, 0xb0, 0x0b, 0xb9, 0x32, 0x88, 0x3c, 0x85, 0x8d, 0x34, 0x84, 0x3d, 0x91, 0x22, 0x9c, 0x2c, 0x94, 0x24, 0x9d, 0x2d, 0x62, 0x4a, 0x6c, 0x45, 0x4d, 0x64, 0x44, 0x6d, 0x52, 0x72, 0x5c, 0x7c, 0x54, 0x74, 0x5d, 0x7d, 0xa1, 0x1a, 0xac, 0x15, 0x1d, 0xa4, 0x14, 0xad, 0x02, 0xb1, 0x0c, 0xbc, 0x04, 0xb4, 0x0d, 0xbd, 0xe1, 0xc8, 0xec, 0xc5, 0xcd, 0xe4, 0xc4, 0xed, 0xd1, 0xf1, 0xdc, 0xfc, 0xd4, 0xf4, 0xdd, 0xfd, 0x36, 0x8e, 0x38, 0x82, 0x8b, 0x30, 0x83, 0x39, 0x96, 0x26, 0x9a, 0x28, 0x93, 0x20, 0x9b, 0x29, 0x66, 0x4e, 0x68, 0x41, 0x49, 0x60, 0x40, 0x69, 0x56, 0x76, 0x58, 0x78, 0x50, 0x70, 0x59, 0x79, 0xa6, 0x1e, 0xaa, 0x11, 0x19, 0xa3, 0x10, 0xab, 0x06, 0xb6, 0x08, 0xba, 0x00, 0xb3, 0x09, 0xbb, 0xe6, 0xce, 0xea, 0xc2, 0xcb, 0xe3, 0xc3, 0xeb, 0xd6, 0xf6, 0xda, 0xfa, 0xd3, 0xf3, 0xdb, 0xfb, 0x31, 0x8a, 0x3e, 0x86, 0x8f, 0x37, 0x87, 0x3f, 0x92, 0x21, 0x9e, 0x2e, 0x97, 0x27, 0x9f, 0x2f, 0x61, 0x48, 0x6e, 0x46, 0x4f, 0x67, 0x47, 0x6f, 0x51, 0x71, 0x5e, 0x7e, 0x57, 0x77, 0x5f, 0x7f, 0xa2, 0x18, 0xae, 0x16, 0x1f, 0xa7, 0x17, 0xaf, 0x01, 0xb2, 0x0e, 0xbe, 0x07, 0xb7, 0x0f, 0xbf, 0xe2, 0xca, 0xee, 0xc6, 0xcf, 0xe7, 0xc7, 0xef, 0xd2, 0xf2, 0xde, 0xfe, 0xd7, 0xf7, 0xdf, 0xff};
const unsigned char sbox_8_inv[256] = {0xac, 0xe8, 0x68, 0x3c, 0x6c, 0x38, 0xa8, 0xec, 0xaa, 0xae, 0x3a, 0x3e, 0x6a, 0x6e, 0xea, 0xee, 0xa6, 0xa3, 0x33, 0x36, 0x66, 0x63, 0xe3, 0xe6, 0xe1, 0xa4, 0x61, 0x34, 0x31, 0x64, 0xa1, 0xe4, 0x8d, 0xc9, 0x49, 0x1d, 0x4d, 0x19, 0x89, 0xcd, 0x8b, 0x8f, 0x1b, 0x1f, 0x4b, 0x4f, 0xcb, 0xcf, 0x85, 0xc0, 0x40, 0x15, 0x45, 0x10, 0x80, 0xc5, 0x82, 0x87, 0x12, 0x17, 0x42, 0x47, 0xc2, 0xc7, 0x96, 0x93, 0x03, 0x06, 0x56, 0x53, 0xd3, 0xd6, 0xd1, 0x94, 0x51, 0x04, 0x01, 0x54, 0x91, 0xd4, 0x9c, 0xd8, 0x58, 0x0c, 0x5c, 0x08, 0x98, 0xdc, 0x9a, 0x9e, 0x0a, 0x0e, 0x5a, 0x5e, 0xda, 0xde, 0x95, 0xd0, 0x50, 0x05, 0x55, 0x00, 0x90, 0xd5, 0x92, 0x97, 0x02, 0x07, 0x52, 0x57, 0xd2, 0xd7, 0x9d, 0xd9, 0x59, 0x0d, 0x5d, 0x09, 0x99, 0xdd, 0x9b, 0x9f, 0x0b, 0x0f, 0x5b, 0x5f, 0xdb, 0xdf, 0x16, 0x13, 0x83, 0x86, 0x46, 0x43, 0xc3, 0xc6, 0x41, 0x14, 0xc1, 0x84, 0x11, 0x44, 0x81, 0xc4, 0x1c, 0x48, 0xc8, 0x8c, 0x4c, 0x18, 0x88, 0xcc, 0x1a, 0x1e, 0x8a, 0x8e, 0x4a, 0x4e, 0xca, 0xce, 0x35, 0x60, 0xe0, 0xa5, 0x65, 0x30, 0xa0, 0xe5, 0x32, 0x37, 0xa2, 0xa7, 0x62, 0x67, 0xe2, 0xe7, 0x3d, 0x69, 0xe9, 0xad, 0x6d, 0x39, 0xa9, 0xed, 0x3b, 0x3f, 0xab, 0xaf, 0x6b, 0x6f, 0xeb, 0xef, 0x26, 0x23, 0xb3, 0xb6, 0x76, 0x73, 0xf3, 0xf6, 0x71, 0x24, 0xf1, 0xb4, 0x21, 0x74, 0xb1, 0xf4, 0x2c, 0x78, 0xf8, 0xbc, 0x7c, 0x28, 0xb8, 0xfc, 0x2a, 0x2e, 0xba, 0xbe, 0x7a, 0x7e, 0xfa, 0xfe, 0x25, 0x70, 0xf0, 0xb5, 0x75, 0x20, 0xb0, 0xf5, 0x22, 0x27, 0xb2, 0xb7, 0x72, 0x77, 0xf2, 0xf7, 0x2d, 0x79, 0xf9, 0xbd, 0x7d, 0x29, 0xb9, 0xfd, 0x2b, 0x2f, 0xbb, 0xbf, 0x7b, 0x7f, 0xfb, 0xff};
// ShiftAndSwitchRows permutation
const unsigned char P[16] = {0, 1, 2, 3, 7, 4, 5, 6, 10, 11, 8, 9, 13, 14, 15, 12};
const unsigned char P_inv[16] = {0, 1, 2, 3, 5, 6, 7, 4, 10, 11, 8, 9, 15, 12, 13, 14};
// Tweakey permutation
const unsigned char TWEAKEY_P[16] = {9, 15, 8, 13, 10, 14, 12, 11, 0, 1, 2, 3, 4, 5, 6, 7};
const unsigned char TWEAKEY_P_inv[16] = {8, 9, 10, 11, 12, 13, 14, 15, 2, 0, 4, 7, 6, 3, 5, 1};
// round constants
const unsigned char RC[62] = {
0x01, 0x03, 0x07, 0x0F, 0x1F, 0x3E, 0x3D, 0x3B, 0x37, 0x2F,
0x1E, 0x3C, 0x39, 0x33, 0x27, 0x0E, 0x1D, 0x3A, 0x35, 0x2B,
0x16, 0x2C, 0x18, 0x30, 0x21, 0x02, 0x05, 0x0B, 0x17, 0x2E,
0x1C, 0x38, 0x31, 0x23, 0x06, 0x0D, 0x1B, 0x36, 0x2D, 0x1A,
0x34, 0x29, 0x12, 0x24, 0x08, 0x11, 0x22, 0x04, 0x09, 0x13,
0x26, 0x0c, 0x19, 0x32, 0x25, 0x0a, 0x15, 0x2a, 0x14, 0x28,
0x10, 0x20};
FILE *fic;
void init_prng(int offset) {
//int initial_seed = 0x5EC7F2B0;
//int initial_seed = 0x30051991; My birthday!
unsigned int initial_seed = 10*time(NULL) + 11*offset;
srand(initial_seed); // Initialization, should only be called once. int r = rand();
printf("[+] PRNG initialized to 0x%08X\n", initial_seed);
}
void display_matrix(unsigned char state[4][4], int ver)
{
int i;
unsigned char input[16];
if (versions[ver][0] == 64)
{
for (i = 0; i < 8; i++)
input[i] = ((state[(2 * i) >> 2][(2 * i) & 0x3] & 0xF) << 4) | (state[(2 * i + 1) >> 2][(2 * i + 1) & 0x3] & 0xF);
for (i = 0; i < 8; i++)
fprintf(fic, "%02x", input[i]);
}
else if (versions[ver][0] == 128)
{
for (i = 0; i < 16; i++)
input[i] = state[i >> 2][i & 0x3] & 0xFF;
for (i = 0; i < 16; i++)
fprintf(fic, "%02x", input[i]);
}
}
void display_cipher_state(unsigned char state[4][4], unsigned char keyCells[3][4][4], int ver)
{
int k;
fprintf(fic, "S = ");
display_matrix(state, ver);
for (k = 0; k < (int)(versions[ver][1] / versions[ver][0]); k++)
{
fprintf(fic, " - TK%i = ", k + 1);
display_matrix(keyCells[k], ver);
}
}
// Extract and apply the subtweakey to the internal state (must be the two top rows XORed together), then update the tweakey state
void AddKey(unsigned char state[4][4], unsigned char keyCells[3][4][4], int ver)
{
int i, j, k;
unsigned char pos;
unsigned char keyCells_tmp[3][4][4];
// apply the subtweakey to the internal state
for (i = 0; i <= 1; i++)
{
for (j = 0; j < 4; j++)
{
state[i][j] ^= keyCells[0][i][j];
if (2 * versions[ver][0] == versions[ver][1])
state[i][j] ^= keyCells[1][i][j];
else if (3 * versions[ver][0] == versions[ver][1])
state[i][j] ^= keyCells[1][i][j] ^ keyCells[2][i][j];
}
}
// update the subtweakey states with the permutation
for (k = 0; k < (int)(versions[ver][1] / versions[ver][0]); k++)
{
for (i = 0; i < 4; i++)
{
for (j = 0; j < 4; j++)
{
//application of the TWEAKEY permutation
pos = TWEAKEY_P[j + 4 * i];
keyCells_tmp[k][i][j] = keyCells[k][pos >> 2][pos & 0x3];
}
}
}
// update the subtweakey states with the LFSRs
for (k = 0; k < (int)(versions[ver][1] / versions[ver][0]); k++)
{
for (i = 0; i <= 1; i++)
{
for (j = 0; j < 4; j++)
{
//application of LFSRs for TK updates
if (k == 1)
{
if (versions[ver][0] == 64)
keyCells_tmp[k][i][j] = ((keyCells_tmp[k][i][j] << 1) & 0xE) ^ ((keyCells_tmp[k][i][j] >> 3) & 0x1) ^ ((keyCells_tmp[k][i][j] >> 2) & 0x1);
else
keyCells_tmp[k][i][j] = ((keyCells_tmp[k][i][j] << 1) & 0xFE) ^ ((keyCells_tmp[k][i][j] >> 7) & 0x01) ^ ((keyCells_tmp[k][i][j] >> 5) & 0x01);
}
else if (k == 2)
{
if (versions[ver][0] == 64)
keyCells_tmp[k][i][j] = ((keyCells_tmp[k][i][j] >> 1) & 0x7) ^ ((keyCells_tmp[k][i][j]) & 0x8) ^ ((keyCells_tmp[k][i][j] << 3) & 0x8);
else
keyCells_tmp[k][i][j] = ((keyCells_tmp[k][i][j] >> 1) & 0x7F) ^ ((keyCells_tmp[k][i][j] << 7) & 0x80) ^ ((keyCells_tmp[k][i][j] << 1) & 0x80);
}
}
}
}
for (k = 0; k < (int)(versions[ver][1] / versions[ver][0]); k++)
{
for (i = 0; i < 4; i++)
{
for (j = 0; j < 4; j++)
{
keyCells[k][i][j] = keyCells_tmp[k][i][j];
}
}
}
}
// Extract and apply the subtweakey to the internal state (must be the two top rows XORed together), then update the tweakey state (inverse function}
void AddKey_inv(unsigned char state[4][4], unsigned char keyCells[3][4][4], int ver)
{
int i, j, k;
unsigned char pos;
unsigned char keyCells_tmp[3][4][4];
// update the subtweakey states with the permutation
for (k = 0; k < (int)(versions[ver][1] / versions[ver][0]); k++)
{
for (i = 0; i < 4; i++)
{
for (j = 0; j < 4; j++)
{
//application of the inverse TWEAKEY permutation
pos = TWEAKEY_P_inv[j + 4 * i];
keyCells_tmp[k][i][j] = keyCells[k][pos >> 2][pos & 0x3];
}
}
}
// update the subtweakey states with the LFSRs
for (k = 0; k < (int)(versions[ver][1] / versions[ver][0]); k++)
{
for (i = 2; i <= 3; i++)
{
for (j = 0; j < 4; j++)
{
//application of inverse LFSRs for TK updates
if (k == 1)
{
if (versions[ver][0] == 64)
keyCells_tmp[k][i][j] = ((keyCells_tmp[k][i][j] >> 1) & 0x7) ^ ((keyCells_tmp[k][i][j] << 3) & 0x8) ^ ((keyCells_tmp[k][i][j]) & 0x8);
else
keyCells_tmp[k][i][j] = ((keyCells_tmp[k][i][j] >> 1) & 0x7F) ^ ((keyCells_tmp[k][i][j] << 7) & 0x80) ^ ((keyCells_tmp[k][i][j] << 1) & 0x80);
}
else if (k == 2)
{
if (versions[ver][0] == 64)
keyCells_tmp[k][i][j] = ((keyCells_tmp[k][i][j] << 1) & 0xE) ^ ((keyCells_tmp[k][i][j] >> 3) & 0x1) ^ ((keyCells_tmp[k][i][j] >> 2) & 0x1);
else
keyCells_tmp[k][i][j] = ((keyCells_tmp[k][i][j] << 1) & 0xFE) ^ ((keyCells_tmp[k][i][j] >> 7) & 0x01) ^ ((keyCells_tmp[k][i][j] >> 5) & 0x01);
}
}
}
}
for (k = 0; k < (int)(versions[ver][1] / versions[ver][0]); k++)
{
for (i = 0; i < 4; i++)
{
for (j = 0; j < 4; j++)
{
keyCells[k][i][j] = keyCells_tmp[k][i][j];
}
}
}
// apply the subtweakey to the internal state
for (i = 0; i <= 1; i++)
{
for (j = 0; j < 4; j++)
{
state[i][j] ^= keyCells[0][i][j];
if (2 * versions[ver][0] == versions[ver][1])
state[i][j] ^= keyCells[1][i][j];
else if (3 * versions[ver][0] == versions[ver][1])
state[i][j] ^= keyCells[1][i][j] ^ keyCells[2][i][j];
}
}
}
// Apply the constants: using a LFSR counter on 6 bits, we XOR the 6 bits to the first 6 bits of the internal state
void AddConstants(unsigned char state[4][4], int r)
{
state[0][0] ^= (RC[r] & 0xf);
state[1][0] ^= ((RC[r] >> 4) & 0x3);
state[2][0] ^= 0x2;
}
// apply the 4-bit Sbox
void SubCell4(unsigned char state[4][4])
{
int i, j;
for (i = 0; i < 4; i++)
for (j = 0; j < 4; j++)
state[i][j] = sbox_4[state[i][j]];
}
// apply the 4-bit inverse Sbox
void SubCell4_inv(unsigned char state[4][4])
{
int i, j;
for (i = 0; i < 4; i++)
for (j = 0; j < 4; j++)
state[i][j] = sbox_4_inv[state[i][j]];
}
// apply the 8-bit Sbox
void SubCell8(unsigned char state[4][4])
{
int i, j;
for (i = 0; i < 4; i++)
for (j = 0; j < 4; j++)
state[i][j] = sbox_8[state[i][j]];
}
// apply the 8-bit inverse Sbox
void SubCell8_inv(unsigned char state[4][4])
{
int i, j;
for (i = 0; i < 4; i++)
for (j = 0; j < 4; j++)
state[i][j] = sbox_8_inv[state[i][j]];
}
// Apply the ShiftRows function
void ShiftRows(unsigned char state[4][4])
{
int i, j, pos;
unsigned char state_tmp[4][4];
for (i = 0; i < 4; i++)
{
for (j = 0; j < 4; j++)
{
//application of the ShiftRows permutation
pos = P[j + 4 * i];
state_tmp[i][j] = state[pos >> 2][pos & 0x3];
}
}
for (i = 0; i < 4; i++)
{
for (j = 0; j < 4; j++)
{
state[i][j] = state_tmp[i][j];
}
}
}
// Apply the inverse ShiftRows function
void ShiftRows_inv(unsigned char state[4][4])
{
int i, j, pos;
unsigned char state_tmp[4][4];
for (i = 0; i < 4; i++)
{
for (j = 0; j < 4; j++)
{
//application of the inverse ShiftRows permutation
pos = P_inv[j + 4 * i];
state_tmp[i][j] = state[pos >> 2][pos & 0x3];
}
}
for (i = 0; i < 4; i++)
{
for (j = 0; j < 4; j++)
{
state[i][j] = state_tmp[i][j];
}
}
}
// Apply the linear diffusion matrix
//M =
//1 0 1 1
//1 0 0 0
//0 1 1 0
//1 0 1 0
void MixColumn(unsigned char state[4][4])
{
int j;
unsigned char temp;
for (j = 0; j < 4; j++)
{
state[1][j] ^= state[2][j];
state[2][j] ^= state[0][j];
state[3][j] ^= state[2][j];
temp = state[3][j];
state[3][j] = state[2][j];
state[2][j] = state[1][j];
state[1][j] = state[0][j];
state[0][j] = temp;
}
}
// Apply the inverse linear diffusion matrix
void MixColumn_inv(unsigned char state[4][4])
{
int j;
unsigned char temp;
for (j = 0; j < 4; j++)
{
temp = state[3][j];
state[3][j] = state[0][j];
state[0][j] = state[1][j];
state[1][j] = state[2][j];
state[2][j] = temp;
state[3][j] ^= state[2][j];
state[2][j] ^= state[0][j];
state[1][j] ^= state[2][j];
}
}
// decryption function of Skinny
void dec(unsigned char *input, const unsigned char *userkey, int ver, int r)
{
unsigned char state[4][4];
unsigned char dummy[4][4] = {{0}};
unsigned char keyCells[3][4][4];
int i;
memset(keyCells, 0, 48);
for (i = 0; i < 16; i++)
{
if (versions[ver][0] == 64)
{
if (i & 1)
{
state[i >> 2][i & 0x3] = input[i >> 1] & 0xF;
keyCells[0][i >> 2][i & 0x3] = userkey[i >> 1] & 0xF;
if (versions[ver][1] >= 128)
keyCells[1][i >> 2][i & 0x3] = userkey[(i + 16) >> 1] & 0xF;
if (versions[ver][1] >= 192)
keyCells[2][i >> 2][i & 0x3] = userkey[(i + 32) >> 1] & 0xF;
}
else
{
state[i >> 2][i & 0x3] = (input[i >> 1] >> 4) & 0xF;
keyCells[0][i >> 2][i & 0x3] = (userkey[i >> 1] >> 4) & 0xF;
if (versions[ver][1] >= 128)
keyCells[1][i >> 2][i & 0x3] = (userkey[(i + 16) >> 1] >> 4) & 0xF;
if (versions[ver][1] >= 192)
keyCells[2][i >> 2][i & 0x3] = (userkey[(i + 32) >> 1] >> 4) & 0xF;
}
}
else if (versions[ver][0] == 128)
{
state[i >> 2][i & 0x3] = input[i] & 0xFF;
keyCells[0][i >> 2][i & 0x3] = userkey[i] & 0xFF;
if (versions[ver][1] >= 256)
keyCells[1][i >> 2][i & 0x3] = userkey[i + 16] & 0xFF;
if (versions[ver][1] >= 384)
keyCells[2][i >> 2][i & 0x3] = userkey[i + 32] & 0xFF;
}
}
for (i = r - 1; i >= 0; i--)
{
AddKey(dummy, keyCells, ver);
}
#ifdef DEBUG
fprintf(fic, "DEC - initial state: ");
display_cipher_state(state, keyCells, ver);
fprintf(fic, "\n");
#endif
for (i = r - 1; i >= 0; i--)
{
MixColumn_inv(state);
#ifdef DEBUG
fprintf(fic, "DEC - round %.2i - after MixColumn_inv: ", i);
display_cipher_state(state, keyCells, ver);
fprintf(fic, "\n");
#endif
ShiftRows_inv(state);
#ifdef DEBUG
fprintf(fic, "DEC - round %.2i - after ShiftRows_inv: ", i);
display_cipher_state(state, keyCells, ver);
fprintf(fic, "\n");
#endif
AddKey_inv(state, keyCells, ver);
#ifdef DEBUG
fprintf(fic, "DEC - round %.2i - after AddKey_inv: ", i);
display_cipher_state(state, keyCells, ver);
fprintf(fic, "\n");
#endif
AddConstants(state, i);
#ifdef DEBUG
fprintf(fic, "DEC - round %.2i - after AddConstants_inv: ", i);
display_cipher_state(state, keyCells, ver);
fprintf(fic, "\n");
#endif
if (versions[ver][0] == 64)
SubCell4_inv(state);
else
SubCell8_inv(state);
#ifdef DEBUG
fprintf(fic, "DEC - round %.2i - after SubCell_inv: ", i);
display_cipher_state(state, keyCells, ver);
fprintf(fic, "\n");
#endif
}
#ifdef DEBUG
fprintf(fic, "DEC - final state: ");
display_cipher_state(state, keyCells, ver);
fprintf(fic, "\n");
#endif
if (versions[ver][0] == 64)
{
for (i = 0; i < 8; i++)
input[i] = ((state[(2 * i) >> 2][(2 * i) & 0x3] & 0xF) << 4) | (state[(2 * i + 1) >> 2][(2 * i + 1) & 0x3] & 0xF);
}
else if (versions[ver][0] == 128)
{
for (i = 0; i < 16; i++)
input[i] = state[i >> 2][i & 0x3] & 0xFF;
}
}
// encryption function of Skinny
void enc(unsigned char *input, const unsigned char *userkey, int ver, int r)
{
unsigned char state[4][4];
unsigned char keyCells[3][4][4];
int i;
memset(keyCells, 0, 48);
for (i = 0; i < 16; i++)
{
if (versions[ver][0] == 64)
{
if (i & 1)
{
state[i >> 2][i & 0x3] = input[i >> 1] & 0xF;
keyCells[0][i >> 2][i & 0x3] = userkey[i >> 1] & 0xF;
if (versions[ver][1] >= 128)
keyCells[1][i >> 2][i & 0x3] = userkey[(i + 16) >> 1] & 0xF;
if (versions[ver][1] >= 192)
keyCells[2][i >> 2][i & 0x3] = userkey[(i + 32) >> 1] & 0xF;
}
else
{
state[i >> 2][i & 0x3] = (input[i >> 1] >> 4) & 0xF;
keyCells[0][i >> 2][i & 0x3] = (userkey[i >> 1] >> 4) & 0xF;
if (versions[ver][1] >= 128)
keyCells[1][i >> 2][i & 0x3] = (userkey[(i + 16) >> 1] >> 4) & 0xF;
if (versions[ver][1] >= 192)
keyCells[2][i >> 2][i & 0x3] = (userkey[(i + 32) >> 1] >> 4) & 0xF;
}
}
else if (versions[ver][0] == 128)
{
state[i >> 2][i & 0x3] = input[i] & 0xFF;
keyCells[0][i >> 2][i & 0x3] = userkey[i] & 0xFF;
if (versions[ver][1] >= 256)
keyCells[1][i >> 2][i & 0x3] = userkey[i + 16] & 0xFF;
if (versions[ver][1] >= 384)
keyCells[2][i >> 2][i & 0x3] = userkey[i + 32] & 0xFF;
}
}
#ifdef DEBUG
fprintf(fic, "ENC - initial state: ");
display_cipher_state(state, keyCells, ver);
fprintf(fic, "\n");
#endif
for (i = 0; i < r; i++)
{
if (versions[ver][0] == 64)
SubCell4(state);
else
SubCell8(state);
#ifdef DEBUG
fprintf(fic, "ENC - round %.2i - after SubCell: ", i);
display_cipher_state(state, keyCells, ver);
fprintf(fic, "\n");
#endif
AddConstants(state, i);
#ifdef DEBUG
fprintf(fic, "ENC - round %.2i - after AddConstants: ", i);
display_cipher_state(state, keyCells, ver);
fprintf(fic, "\n");
#endif
AddKey(state, keyCells, ver);
#ifdef DEBUG
fprintf(fic, "ENC - round %.2i - after AddKey: ", i);
display_cipher_state(state, keyCells, ver);
fprintf(fic, "\n");
#endif
ShiftRows(state);
#ifdef DEBUG
fprintf(fic, "ENC - round %.2i - after ShiftRows: ", i);
display_cipher_state(state, keyCells, ver);
fprintf(fic, "\n");
#endif
MixColumn(state);
#ifdef DEBUG
fprintf(fic, "ENC - round %.2i - after MixColumn: ", i);
display_cipher_state(state, keyCells, ver);
fprintf(fic, "\n");
#endif
} //The last subtweakey should not be added
#ifdef DEBUG
fprintf(fic, "ENC - final state: ");
display_cipher_state(state, keyCells, ver);
fprintf(fic, "\n");
#endif
if (versions[ver][0] == 64)
{
for (i = 0; i < 8; i++)
input[i] = ((state[(2 * i) >> 2][(2 * i) & 0x3] & 0xF) << 4) | (state[(2 * i + 1) >> 2][(2 * i + 1) & 0x3] & 0xF);
}
else if (versions[ver][0] == 128)
{
for (i = 0; i < 16; i++)
input[i] = state[i >> 2][i & 0x3] & 0xFF;
}
}
// generate test vectors for all the versions of Skinny
void TestVectors(int ver)
{
unsigned char p[16];
unsigned char c[16];
unsigned char k[48];
int n;
for (n = 1; n < 10; n++)
{
int i;
for (i = 0; i < (versions[ver][0] >> 3); i++)
c[i] = p[i] = rand() & 0xff;
for (i = 0; i < (versions[ver][0] >> 3); i++)
printf("%02x", p[i]);
printf("\n");
for (i = 0; i < (versions[ver][1] >> 3); i++)
k[i] = rand() & 0xff;
fprintf(fic, "TK = ");
for (i = 0; i < (versions[ver][1] >> 3); i++)
fprintf(fic, "%02x", k[i]);
fprintf(fic, "\n");
fprintf(fic, "P = ");
for (i = 0; i < (versions[ver][0] >> 3); i++)
fprintf(fic, "%02x", p[i]);
fprintf(fic, "\n");
enc(c, k, ver, 10);
fprintf(fic, "C = ");
for (i = 0; i < (versions[ver][0] >> 3); i++)
fprintf(fic, "%02x", c[i]);
fprintf(fic, "\n");
dec(c, k, ver, 10);
fprintf(fic, "P' = ");
for (i = 0; i < (versions[ver][0] >> 3); i++)
fprintf(fic, "%02x", c[i]);
fprintf(fic, "\n\n");
}
}
int boomerang(int r, int ver, unsigned long long N3, unsigned char *dp, unsigned char *dc, unsigned char *dk1, unsigned char *dk2)
{
int i;
unsigned char p1[16], p2[16];
unsigned char c3[16], c4[16];
unsigned char k1[48], k2[48], k3[48], k4[48];
// randomly choose k1
for (i = 0; i < (versions[ver][1] >> 3); i++)
k1[i] = rand() & 0xff;
// derive k2
for (i = 0; i < (versions[ver][1] >> 3); i++)
k2[i] = k1[i] ^ dk1[i];
// derive k3
for (i = 0; i < (versions[ver][1] >> 3); i++)
k3[i] = k1[i] ^ dk2[i];
// derive k4
for (i = 0; i < (versions[ver][1] >> 3); i++)
k4[i] = k2[i] ^ dk2[i];
int num = 0;
for (uint64_t t = 0; t < N3; t++)
{
// randomly choose p1
for (i = 0; i < (versions[ver][0] >> 3); i++)
p1[i] = rand() & 0xff;
// derive p2
for (i = 0; i < (versions[ver][0] >> 3); i++)
p2[i] = p1[i] ^ dp[i];
enc(p1, k1, ver, r);
enc(p2, k2, ver, r);
// derive c3
for (i = 0; i < (versions[ver][0] >> 3); i++)
c3[i] = p1[i] ^ dc[i];
// derive c4
for (i = 0; i < (versions[ver][0] >> 3); i++)
c4[i] = p2[i] ^ dc[i];
dec(c3, k3, ver, r);
dec(c4, k4, ver, r);
bool flag = 1;
for (i = 0; i < (versions[ver][0] >> 3); i++)
if ((c3[i] ^ c4[i]) != dp[i])
flag = 0;
if (flag)
{
num++;
}
}
return num;
}
double send_boomerangs(int R, int ver, int N1, uint64_t N2, uint64_t N3, unsigned char *dp, unsigned char *dc, unsigned char *dk1, unsigned char *dk2)
{
// Parallel execution
int NUM[N1];
int counter;
printf("#Rounds: %d rounds\n", R);
printf("#Total Queries = (#Parallel threads) * (#Bunches per thread) * (#Queries per bunch) = %d * %llu * %llu = 2^(%f)\n", N1, N2, N3, log(N1 * N2 * N3) / log(2));
printf("#Queries per thread = (#Bunches per thread) * (#Queries per bunch) = %llu * %llu = 2^(%f)\n", N2, N3, log(N2 * N3) / log(2));
clock_t clock_timer;
double wall_timer;
clock_timer = clock();
wall_timer = omp_get_wtime();
omp_set_num_threads(N1);
#pragma omp parallel for
for (counter = 0; counter < N1; counter++)
{
int num = 0;
int ID = omp_get_thread_num();
init_prng(ID);
for (uint64_t j = 0; j < N2; j++)
{
num += boomerang(R, ver, N3, dp, dc, dk1, dk2);
if ((j & STEP) == 0){
printf("PID: %d \t Bunch Number: %llu/%llu\n", ID, j, N2);
}
}
NUM[ID] = num;
}
printf("%s: %0.4f\n", "time on clock", (double)(clock() - clock_timer) / CLOCKS_PER_SEC);
printf("%s: %0.4f\n", "time on wall", omp_get_wtime() - wall_timer);
double sum = 0;
double sum_temp = 1;
for (int i = 0; i < N1; i++)
sum += NUM[i];
printf("sum = %f\n", sum);
sum_temp = (double)(N1 * N2 * N3) / sum;
printf("2^(-%f)\n\n", log(sum_temp) / log(2));
printf("##########################\n");
return sum;
}
void convert_hexstr_to_statearray(int ver, char hex_str[], unsigned char dx[16])
{
for (int i = 0; i < (versions[ver][0] >> 3); i++)
{
char hex[2];
hex[0] = hex_str[2 * i];
hex[1] = hex_str[2 * i + 1];
dx[i] = (unsigned char)(strtol(hex, NULL, 16) & 0xff);
}
}
void convert_hexstr_to_tweakarray(int ver, char hex_str[], unsigned char dt[48])
{
for (int i = 0; i < (versions[ver][1] >> 3); i++)
{
char hex[2];
hex[0] = hex_str[2 * i];
hex[1] = hex_str[2 * i + 1];
dt[i] = (unsigned char)(strtol(hex, NULL, 16) & 0xff);
}
}
int main()
{
// srand((unsigned)time(NULL)); // Initialization, should only be called once. int r = rand();
// init_prng(1);
// //test all versions of Skinny
// for (i = 0; i < (sizeof(versions) / sizeof(*versions)); i++)
// {
// sprintf(name, "test_vectors_%i_%i.txt", versions[i][0], versions[i][1]);
// fic = fopen(name, "w");
// fprintf(fic, "\n\nSkinny-%i/%i: \n", versions[i][0], versions[i][1]);
// TestVectors(i);
// fclose(fic);
// printf("Generating test vectors for Skinny-%i/%i - saved in file test_vectors_%i_%i.txt \n", versions[i][0], versions[i][1], versions[i][0], versions[i][1]);
// }
unsigned char dp[16];
unsigned char dc[16];
unsigned char dk1[48];
unsigned char dk2[48];
// #######################################################################################################
// #######################################################################################################
// ############################## User must change only the following lines ##############################
int R = 17; // Number of rounds
int ver = 1; // Determine the version:
// [0 = Skinny-64-64]
// [1 = Skinny-64-128]
// [2 = Skinny-64-192]
// [3 = Skinny-128-128]
// [4 = Skinny-128-256]
// [5 = Skinny-128-384]
char dp_str[] = "0000000000000800";
char dc_str[] = "0200000002000200";
char dk1_str[] = "000000000C000000000000000F000000";
char dk2_str[] = "00000000000000400000000000000070";
// #######################################################################################################
// #######################################################################################################
convert_hexstr_to_statearray(ver, dp_str, dp);
convert_hexstr_to_statearray(ver, dc_str, dc);
convert_hexstr_to_tweakarray(ver, dk1_str, dk1);
convert_hexstr_to_tweakarray(ver, dk2_str, dk2);
//########################## Number of queries #########################
int N1 = Nthreads; // Number of parallel threads : N1
int deg1 = 3;
int deg2 = 23;
int N2 = 1 << deg1; // Number of bunches per thread : N2 = 2^(deg1)
int N3 = 1 << deg2; // Number of queries per bunche : N3 = 2^(deg2)
//################### Number of total queries : N1*N2*N3 ###############
char all_results[NumOfExperiments][20];
double sum = 0;
double sum_temp = 0;
for (int i = 0; i < NumOfExperiments; i++)
{
printf("Experiment Number %d:\n", i);
sum_temp = send_boomerangs(R, ver, N1, N2, N3, dp, dc, dk1, dk2);
sum += sum_temp;
sum_temp = (double)(N1 * N2 * N3) / sum_temp;
sprintf(all_results[i], "2^(-%0.2f), ", log(sum_temp) / log(2));
}
printf("A summary of all results:\n");
for (int i = 0; i < NumOfExperiments; i++)
{
printf("%s", all_results[i]);
}
printf("\n##########################\nAverage = 2^(-%0.4f)\n",
(log(NumOfExperiments) + log(N1) + log(N2) + log(N3) - log(sum))/log(2));
}
|
rmse.c | /*************************************************************************/
/** File: rmse.c **/
/** Description: calculate root mean squared error of particular **/
/** clustering. **/
/** Author: Sang-Ha Lee **/
/** University of Virginia. **/
/** **/
/** Note: euclid_dist_2() and find_nearest_point() adopted from **/
/** Minebench code. **/
/** **/
/*************************************************************************/
#include <stdio.h>
#include <stdlib.h>
#include <float.h>
#include <math.h>
#include <omp.h>
#include "kmeans.h"
extern double wtime(void);
/*----< euclid_dist_2() >----------------------------------------------------*/
/* multi-dimensional spatial Euclid distance square */
__inline
float euclid_dist_2(float *pt1,
float *pt2,
int numdims)
{
int i;
float ans=0.0;
for (i=0; i<numdims; i++)
ans += (pt1[i]-pt2[i]) * (pt1[i]-pt2[i]);
return(ans);
}
/*----< find_nearest_point() >-----------------------------------------------*/
__inline
int find_nearest_point(float *pt, /* [nfeatures] */
int nfeatures,
float **pts, /* [npts][nfeatures] */
int npts)
{
int index, i;
float max_dist=FLT_MAX;
/* find the cluster center id with min distance to pt */
for (i=0; i<npts; i++) {
float dist;
dist = euclid_dist_2(pt, pts[i], nfeatures); /* no need square root */
if (dist < max_dist) {
max_dist = dist;
index = i;
}
}
return(index);
}
/*----< rms_err(): calculates RMSE of clustering >-------------------------------------*/
float rms_err (float **feature, /* [npoints][nfeatures] */
int nfeatures,
int npoints,
float **cluster_centres, /* [nclusters][nfeatures] */
int nclusters)
{
int i;
int nearest_cluster_index; /* cluster center id with min distance to pt */
float sum_euclid = 0.0; /* sum of Euclidean distance squares */
float ret; /* return value */
/* calculate and sum the sqaure of euclidean distance*/
/*#pragma omp parallel for \
shared(feature,cluster_centres) \
firstprivate(npoints,nfeatures,nclusters) \
private(i, nearest_cluster_index) \
schedule (static)*/
for (i=0; i<npoints; i++) {
nearest_cluster_index = find_nearest_point(feature[i],
nfeatures,
cluster_centres,
nclusters);
sum_euclid += euclid_dist_2(feature[i],
cluster_centres[nearest_cluster_index],
nfeatures);
}
/* divide by n, then take sqrt */
ret = sqrt(sum_euclid / npoints);
return(ret);
}
|
pbkdf2-hmac-md4_fmt_plug.c | /*
* This software is Copyright (c) 2015 magnum 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.
*/
#if FMT_EXTERNS_H
extern struct fmt_main fmt_pbkdf2_hmac_md4;
#elif FMT_REGISTERS_H
john_register_one(&fmt_pbkdf2_hmac_md4);
#else
#include <ctype.h>
#include <string.h>
#include <assert.h>
#include "arch.h"
//#undef SIMD_COEF_32
#include "misc.h"
#include "common.h"
#include "formats.h"
#include "stdint.h"
#include "pbkdf2_hmac_md4.h"
#include "pbkdf2_hmac_common.h"
#ifdef _OPENMP
#include <omp.h>
#ifndef OMP_SCALE
#define OMP_SCALE 256
#endif
#endif
#include "memdbg.h"
#define FORMAT_LABEL "PBKDF2-HMAC-MD4"
#ifdef SIMD_COEF_32
#define ALGORITHM_NAME "PBKDF2-MD4 " MD4_ALGORITHM_NAME
#else
#define ALGORITHM_NAME "PBKDF2-MD4 32/" ARCH_BITS_STR
#endif
#define SALT_SIZE sizeof(struct custom_salt)
#define SALT_ALIGN sizeof(ARCH_WORD_32)
#if SIMD_COEF_32
#define MIN_KEYS_PER_CRYPT (SIMD_COEF_32 * SIMD_PARA_MD4)
#define MAX_KEYS_PER_CRYPT (SIMD_COEF_32 * SIMD_PARA_MD4)
#else
#define MIN_KEYS_PER_CRYPT 1
#define MAX_KEYS_PER_CRYPT 1
#endif
#define PLAINTEXT_LENGTH 125
static struct custom_salt {
unsigned int length;
unsigned int rounds;
char salt[PBKDF2_32_MAX_SALT_SIZE];
} *cur_salt;
static char (*saved_key)[PLAINTEXT_LENGTH + 1];
static ARCH_WORD_32 (*crypt_out)[PBKDF2_MDx_BINARY_SIZE / sizeof(ARCH_WORD_32)];
static void init(struct fmt_main *self)
{
#ifdef _OPENMP
int 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));
}
static void done(void)
{
MEM_FREE(crypt_out);
MEM_FREE(saved_key);
}
static void *get_salt(char *ciphertext)
{
static struct custom_salt cs;
char *p;
int saltlen;
char delim;
if (!strncmp(ciphertext, PBKDF2_MD4_FORMAT_TAG, sizeof(PBKDF2_MD4_FORMAT_TAG) - 1))
ciphertext += sizeof(PBKDF2_MD4_FORMAT_TAG) - 1;
memset(&cs, 0, sizeof(cs));
cs.rounds = atoi(ciphertext);
delim = strchr(ciphertext, '.') ? '.' : '$';
ciphertext = strchr(ciphertext, delim) + 1;
p = strchr(ciphertext, delim);
saltlen = 0;
memset(cs.salt, 0, sizeof(cs.salt));
while (ciphertext < p) { /** extract salt **/
cs.salt[saltlen++] =
atoi16[ARCH_INDEX(ciphertext[0])] * 16 +
atoi16[ARCH_INDEX(ciphertext[1])];
ciphertext += 2;
}
cs.length = saltlen;
return (void*)&cs;
}
static void set_salt(void *salt)
{
cur_salt = (struct custom_salt *)salt;
}
static int get_hash_0(int index) { return crypt_out[index][0] & PH_MASK_0; }
static int get_hash_1(int index) { return crypt_out[index][0] & PH_MASK_1; }
static int get_hash_2(int index) { return crypt_out[index][0] & PH_MASK_2; }
static int get_hash_3(int index) { return crypt_out[index][0] & PH_MASK_3; }
static int get_hash_4(int index) { return crypt_out[index][0] & PH_MASK_4; }
static int get_hash_5(int index) { return crypt_out[index][0] & PH_MASK_5; }
static int get_hash_6(int index) { return crypt_out[index][0] & PH_MASK_6; }
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 += MAX_KEYS_PER_CRYPT)
{
#if SIMD_COEF_32
int lens[SSE_GROUP_SZ_MD4], i;
unsigned char *pin[SSE_GROUP_SZ_MD4];
union {
ARCH_WORD_32 *pout[SSE_GROUP_SZ_MD4];
unsigned char *poutc;
} x;
for (i = 0; i < SSE_GROUP_SZ_MD4; ++i) {
lens[i] = strlen(saved_key[index+i]);
pin[i] = (unsigned char*)saved_key[index+i];
x.pout[i] = crypt_out[index+i];
}
pbkdf2_md4_sse((const unsigned char **)pin, lens,
(unsigned char*)cur_salt->salt, cur_salt->length,
cur_salt->rounds, &(x.poutc),
PBKDF2_MDx_BINARY_SIZE, 0);
#else
pbkdf2_md4((unsigned char*)(saved_key[index]),
strlen(saved_key[index]),
(unsigned char*)cur_salt->salt, cur_salt->length,
cur_salt->rounds, (unsigned char*)crypt_out[index],
PBKDF2_MDx_BINARY_SIZE, 0);
#endif
}
return count;
}
static int cmp_all(void *binary, int count)
{
int index = 0;
#if defined(_OPENMP) || MAX_KEYS_PER_CRYPT > 1
for (; index < count; index++)
#endif
if (!memcmp(binary, crypt_out[index], ARCH_SIZE))
return 1;
//dump_stuff_msg("\nbinary", crypt_out[count - 1], 16);
return 0;
}
static int cmp_one(void *binary, int index)
{
return !memcmp(binary, crypt_out[index], PBKDF2_MDx_BINARY_SIZE);
}
static void set_key(char *key, int index)
{
int saved_len = strlen(key);
if (saved_len > PLAINTEXT_LENGTH)
saved_len = PLAINTEXT_LENGTH;
memcpy(saved_key[index], key, saved_len);
saved_key[index][saved_len] = 0;
}
static char *get_key(int index)
{
return saved_key[index];
}
static int cmp_exact(char *source, int index)
{
/* does a FULL compare, if the binary buffer of the hash is larger than 16 bytes */
return pbkdf2_hmac_md4_cmp_exact(get_key(index), source, (unsigned char*)cur_salt->salt, cur_salt->length, cur_salt->rounds);
}
static unsigned int iteration_count(void *salt)
{
struct custom_salt *my_salt;
my_salt = salt;
return (unsigned int) my_salt->rounds;
}
struct fmt_main fmt_pbkdf2_hmac_md4 = {
{
FORMAT_LABEL,
FORMAT_NAME,
ALGORITHM_NAME,
BENCHMARK_COMMENT,
BENCHMARK_LENGTH,
0,
PLAINTEXT_LENGTH,
PBKDF2_MDx_BINARY_SIZE,
PBKDF2_32_BINARY_ALIGN,
SALT_SIZE,
SALT_ALIGN,
MIN_KEYS_PER_CRYPT,
MAX_KEYS_PER_CRYPT,
FMT_CASE | FMT_8_BIT | FMT_OMP,
{
"iteration count",
},
pbkdf2_hmac_md4_common_tests
}, {
init,
done,
fmt_default_reset,
fmt_default_prepare,
pbkdf2_hmac_md4_valid,
pbkdf2_hmac_md4_split,
pbkdf2_hmac_md4_binary,
get_salt,
{
iteration_count,
},
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,
set_salt,
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 */
|
GB_binop__rdiv_uint64.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__rdiv_uint64)
// A.*B function (eWiseMult): GB (_AemultB_08__rdiv_uint64)
// A.*B function (eWiseMult): GB (_AemultB_02__rdiv_uint64)
// A.*B function (eWiseMult): GB (_AemultB_04__rdiv_uint64)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__rdiv_uint64)
// A*D function (colscale): GB (_AxD__rdiv_uint64)
// D*A function (rowscale): GB (_DxB__rdiv_uint64)
// C+=B function (dense accum): GB (_Cdense_accumB__rdiv_uint64)
// C+=b function (dense accum): GB (_Cdense_accumb__rdiv_uint64)
// C+=A+B function (dense ewise3): GB (_Cdense_ewise3_accum__rdiv_uint64)
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__rdiv_uint64)
// C=scalar+B GB (_bind1st__rdiv_uint64)
// C=scalar+B' GB (_bind1st_tran__rdiv_uint64)
// C=A+scalar GB (_bind2nd__rdiv_uint64)
// C=A'+scalar GB (_bind2nd_tran__rdiv_uint64)
// C type: uint64_t
// A type: uint64_t
// B,b type: uint64_t
// BinaryOp: cij = GB_IDIV_UNSIGNED (bij, aij, 64)
#define GB_ATYPE \
uint64_t
#define GB_BTYPE \
uint64_t
#define GB_CTYPE \
uint64_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) \
uint64_t aij = GBX (Ax, pA, A_iso)
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB,B_iso) \
uint64_t bij = GBX (Bx, pB, B_iso)
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
uint64_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 = GB_IDIV_UNSIGNED (y, x, 64) ;
// 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_RDIV || GxB_NO_UINT64 || GxB_NO_RDIV_UINT64)
//------------------------------------------------------------------------------
// 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__rdiv_uint64)
(
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
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_ewise3_noaccum__rdiv_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__rdiv_uint64)
(
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__rdiv_uint64)
(
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 uint64_t
uint64_t bwork = (*((uint64_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__rdiv_uint64)
(
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
uint64_t *restrict Cx = (uint64_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__rdiv_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
uint64_t *restrict Cx = (uint64_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__rdiv_uint64)
(
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__rdiv_uint64)
(
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__rdiv_uint64)
(
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__rdiv_uint64)
(
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__rdiv_uint64)
(
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__rdiv_uint64)
(
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
uint64_t *Cx = (uint64_t *) 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 < bnz ; p++)
{
if (!GBB (Bb, p)) continue ;
uint64_t bij = GBX (Bx, p, false) ;
Cx [p] = GB_IDIV_UNSIGNED (bij, x, 64) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__rdiv_uint64)
(
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 ;
uint64_t *Cx = (uint64_t *) 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++)
{
if (!GBB (Ab, p)) continue ;
uint64_t aij = GBX (Ax, p, false) ;
Cx [p] = GB_IDIV_UNSIGNED (y, aij, 64) ;
}
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) \
{ \
uint64_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = GB_IDIV_UNSIGNED (aij, x, 64) ; \
}
GrB_Info GB (_bind1st_tran__rdiv_uint64)
(
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 \
uint64_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint64_t x = (*((const uint64_t *) x_input)) ;
#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 typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
uint64_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = GB_IDIV_UNSIGNED (y, aij, 64) ; \
}
GrB_Info GB (_bind2nd_tran__rdiv_uint64)
(
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
uint64_t y = (*((const uint64_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
GB_binop__isne_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 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__isne_fc64)
// A.*B function (eWiseMult): GB (_AemultB_08__isne_fc64)
// A.*B function (eWiseMult): GB (_AemultB_02__isne_fc64)
// A.*B function (eWiseMult): GB (_AemultB_04__isne_fc64)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__isne_fc64)
// A*D function (colscale): GB ((none))
// D*A function (rowscale): GB ((none))
// C+=B function (dense accum): GB (_Cdense_accumB__isne_fc64)
// C+=b function (dense accum): GB (_Cdense_accumb__isne_fc64)
// C+=A+B function (dense ewise3): GB ((none))
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__isne_fc64)
// C=scalar+B GB (_bind1st__isne_fc64)
// C=scalar+B' GB (_bind1st_tran__isne_fc64)
// C=A+scalar GB (_bind2nd__isne_fc64)
// C=A'+scalar GB (_bind2nd_tran__isne_fc64)
// C type: GxB_FC64_t
// A type: GxB_FC64_t
// B,b type: GxB_FC64_t
// BinaryOp: cij = GB_FC64_isne (aij, bij)
#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,A_iso) \
GxB_FC64_t aij = GBX (Ax, pA, A_iso)
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB,B_iso) \
GxB_FC64_t bij = GBX (Bx, pB, B_iso)
// 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,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 = GB_FC64_isne (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_ISNE || GxB_NO_FC64 || GxB_NO_ISNE_FC64)
//------------------------------------------------------------------------------
// 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__isne_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__isne_fc64)
(
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__isne_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
//------------------------------------------------------------------------------
#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
GxB_FC64_t *restrict Cx = (GxB_FC64_t *) 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, 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 *restrict Cx = (GxB_FC64_t *) 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__isne_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 *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__isne_fc64)
(
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__isne_fc64)
(
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__isne_fc64)
(
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__isne_fc64)
(
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__isne_fc64)
(
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
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 < bnz ; p++)
{
if (!GBB (Bb, p)) continue ;
GxB_FC64_t bij = GBX (Bx, p, false) ;
Cx [p] = GB_FC64_isne (x, bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__isne_fc64)
(
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 ;
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 ;
GxB_FC64_t aij = GBX (Ax, p, false) ;
Cx [p] = GB_FC64_isne (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_FC64_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = GB_FC64_isne (x, aij) ; \
}
GrB_Info GB (_bind1st_tran__isne_fc64)
(
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_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
}
//------------------------------------------------------------------------------
// 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_FC64_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = GB_FC64_isne (aij, y) ; \
}
GrB_Info GB (_bind2nd_tran__isne_fc64)
(
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_FC64_t y = (*((const GxB_FC64_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
RungeSolver8_10.h | #include "../DifferentialSolver.h"
#include <assert.h>
/*
Copy-past of DormandPrince method & light differences, based on http://sce.uhcl.edu/feagin/courses/rk10.pdf
results to Runge-Kutta 10th order method
with 17th stages
see also:
http://sce.uhcl.edu/rungekutta/
http://sce.uhcl.edu/rungekutta/rk108.txt
*/
template<typename Scalar>
class RungeSolver8_10 : public DifferentialSolver<Scalar>
{
public:
RungeSolver8_10()
{
}
void SetSystem(DifferentialSystem<Scalar> *system) override
{
this->system = system;
int maxDimentionsCount = system->GetMaxDimentionsCount();
currCoords = new Scalar[maxDimentionsCount];
nextCoords1 = new Scalar[maxDimentionsCount];
nextCoords2 = new Scalar[maxDimentionsCount];
derivatives = new Scalar[maxDimentionsCount];
probeCoords = new Scalar[maxDimentionsCount];
k1 = new Scalar[maxDimentionsCount];
k2 = new Scalar[maxDimentionsCount];
k3 = new Scalar[maxDimentionsCount];
k4 = new Scalar[maxDimentionsCount];
k5 = new Scalar[maxDimentionsCount];
k6 = new Scalar[maxDimentionsCount];
k7 = new Scalar[maxDimentionsCount];
k8 = new Scalar[maxDimentionsCount];
k9 = new Scalar[maxDimentionsCount];
k10 = new Scalar[maxDimentionsCount];
k11 = new Scalar[maxDimentionsCount];
k12 = new Scalar[maxDimentionsCount];
k13 = new Scalar[maxDimentionsCount];
k14 = new Scalar[maxDimentionsCount];
k15 = new Scalar[maxDimentionsCount];
k16 = new Scalar[maxDimentionsCount];
k17 = new Scalar[maxDimentionsCount];
this->currTime = 0;
}
virtual ~RungeSolver8_10()
{
delete[] currCoords;
delete[] nextCoords1;
delete[] nextCoords2;
delete[] derivatives;
delete[] probeCoords;
delete[] k1;
delete[] k2;
delete[] k3;
delete[] k4;
delete[] k5;
delete[] k6;
delete[] k7;
delete[] k8;
delete[] k9;
delete[] k10;
delete[] k11;
delete[] k12;
delete[] k13;
delete[] k14;
delete[] k15;
delete[] k16;
delete[] k17;
}
Scalar pow(Scalar a, Scalar b)
{
return exp(log(a) * b);
}
int GetPhasesCount() const override
{
return 17;
}
void InitStep(Scalar timeStep, Scalar tolerance,
int globalStepIndex, int hierarchyPhase)
{
assert(system->GetHierarchyLevelsCount() == 1);
DifferentialSolver<Scalar>::InitStep(timeStep, tolerance, globalStepIndex, hierarchyPhase);
system->GetCurrCoords(this->currTime, currCoords, globalStepIndex, hierarchyPhase);
}
virtual void AdvancePhase(int phaseIndex)
{
switch (phaseIndex)
{
case 0:
{
Scalar b1_0(0.100000000000000000000000000000000000000000000000000000000000);
system->GetCurrDerivatives(k1, this->globalStepIndex, this->hierarchyPhase);
#pragma omp parallel for
for (int coordIndex = 0; coordIndex < system->GetDimentionsCount(this->globalStepIndex, this->hierarchyPhase); coordIndex++)
{
probeCoords[coordIndex] = currCoords[coordIndex] + b1_0 * k1[coordIndex] * this->timeStep;
}
system->SetCurrCoords(this->currTime + this->timeStep * Scalar(0.000000000000000000000000000000000000000000000000000000000000), probeCoords, this->globalStepIndex, this->hierarchyPhase);
}break;
case 1:
{
Scalar b2_0(-0.915176561375291440520015019275342154318951387664369720564660);
Scalar b2_1(1.45453440217827322805250021715664459117622483736537873607016);
system->GetCurrDerivatives(k2, this->globalStepIndex, this->hierarchyPhase);
#pragma omp parallel for
for (int coordIndex = 0; coordIndex < system->GetDimentionsCount(this->globalStepIndex, this->hierarchyPhase); coordIndex++)
{
probeCoords[coordIndex] = currCoords[coordIndex] + b2_0 * k1[coordIndex] * this->timeStep
+b2_1 * k2[coordIndex] * this->timeStep;
}
system->SetCurrCoords(this->currTime + this->timeStep * Scalar(0.100000000000000000000000000000000000000000000000000000000000), probeCoords, this->globalStepIndex, this->hierarchyPhase);
} break;
case 2:
{
Scalar b3_0(0.202259190301118170324681949205488413821477543637878380814562);
Scalar b3_1(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b3_2(0.606777570903354510974045847616465241464432630913635142443687);
system->GetCurrDerivatives(k3, this->globalStepIndex, this->hierarchyPhase);
#pragma omp parallel for
for (int coordIndex = 0; coordIndex < system->GetDimentionsCount(this->globalStepIndex, this->hierarchyPhase); coordIndex++)
{
probeCoords[coordIndex] = currCoords[coordIndex] + b3_0 * k1[coordIndex] * this->timeStep
+ b3_1 * k2[coordIndex] * this->timeStep
+ b3_2 * k3[coordIndex] * this->timeStep;
}
system->SetCurrCoords(this->currTime + this->timeStep * Scalar(0.539357840802981787532485197881302436857273449701009015505500), probeCoords, this->globalStepIndex, this->hierarchyPhase);
}break;
case 3:
{
Scalar b4_0(0.184024714708643575149100693471120664216774047979591417844635);
Scalar b4_1(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b4_2(0.197966831227192369068141770510388793370637287463360401555746);
Scalar b4_3(-0.0729547847313632629185146671595558023015011608914382961421311);
system->GetCurrDerivatives(k4, this->globalStepIndex, this->hierarchyPhase);
#pragma omp parallel for
for (int coordIndex = 0; coordIndex < system->GetDimentionsCount(this->globalStepIndex, this->hierarchyPhase); coordIndex++)
{
probeCoords[coordIndex] = currCoords[coordIndex] + b4_0 * k1[coordIndex] * this->timeStep
+ b4_1 * k2[coordIndex] * this->timeStep
+ b4_2 * k3[coordIndex] * this->timeStep
+ b4_3 * k4[coordIndex] * this->timeStep;
}
system->SetCurrCoords(this->currTime + this->timeStep * Scalar(0.809036761204472681298727796821953655285910174551513523258250), probeCoords, this->globalStepIndex, this->hierarchyPhase);
} break;
case 4:
{
Scalar b5_0(0.0879007340206681337319777094132125475918886824944548534041378);
Scalar b5_1(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b5_2(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b5_3(0.410459702520260645318174895920453426088035325902848695210406);
Scalar b5_4(0.482713753678866489204726942976896106809132737721421333413261);
system->GetCurrDerivatives(k5, this->globalStepIndex, this->hierarchyPhase);
#pragma omp parallel for
for (int coordIndex = 0; coordIndex < system->GetDimentionsCount(this->globalStepIndex, this->hierarchyPhase); coordIndex++)
{
probeCoords[coordIndex] = currCoords[coordIndex] + b5_0 * k1[coordIndex] * this->timeStep
+ b5_1 * k2[coordIndex] * this->timeStep
+ b5_2 * k3[coordIndex] * this->timeStep
+ b5_3 * k4[coordIndex] * this->timeStep
+ b5_4 * k5[coordIndex] * this->timeStep;
}
system->SetCurrCoords(this->currTime + this->timeStep * Scalar(0.309036761204472681298727796821953655285910174551513523258250), probeCoords, this->globalStepIndex, this->hierarchyPhase);
}break;
case 5:
{
Scalar b6_0(0.0859700504902460302188480225945808401411132615636600222593880);
Scalar b6_1(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b6_2(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b6_3(0.330885963040722183948884057658753173648240154838402033448632);
Scalar b6_4(0.489662957309450192844507011135898201178015478433790097210790);
Scalar b6_5(-0.0731856375070850736789057580558988816340355615025188195854775);
system->GetCurrDerivatives(k6, this->globalStepIndex, this->hierarchyPhase);
#pragma omp parallel for
for (int coordIndex = 0; coordIndex < system->GetDimentionsCount(this->globalStepIndex, this->hierarchyPhase); coordIndex++)
{
probeCoords[coordIndex] = currCoords[coordIndex] + b6_0 * k1[coordIndex] * this->timeStep
+ b6_1 * k2[coordIndex] * this->timeStep
+ b6_2 * k3[coordIndex] * this->timeStep
+ b6_3 * k4[coordIndex] * this->timeStep
+ b6_4 * k5[coordIndex] * this->timeStep
+ b6_5 * k6[coordIndex] * this->timeStep;
}
system->SetCurrCoords(this->currTime + this->timeStep * Scalar(0.981074190219795268254879548310562080489056746118724882027805), probeCoords, this->globalStepIndex, this->hierarchyPhase);
} break;
case 6:
{
Scalar b7_0(0.120930449125333720660378854927668953958938996999703678812621);
Scalar b7_1(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b7_2(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b7_3(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b7_4(0.260124675758295622809007617838335174368108756484693361887839);
Scalar b7_5(0.0325402621549091330158899334391231259332716675992700000776101);
Scalar b7_6(-0.0595780211817361001560122202563305121444953672762930724538856);
system->GetCurrDerivatives(k7, this->globalStepIndex, this->hierarchyPhase);
#pragma omp parallel for
for (int coordIndex = 0; coordIndex < system->GetDimentionsCount(this->globalStepIndex, this->hierarchyPhase); coordIndex++)
{
probeCoords[coordIndex] = currCoords[coordIndex] + this->timeStep * (
b7_0 * k1[coordIndex]
+ b7_1 * k2[coordIndex]
+ b7_2 * k3[coordIndex]
+ b7_3 * k4[coordIndex]
+ b7_4 * k5[coordIndex]
+ b7_5 * k6[coordIndex]
+ b7_6 * k7[coordIndex]
);
}
system->SetCurrCoords(this->currTime + this->timeStep * Scalar(0.833333333333333333333333333333333333333333333333333333333333), probeCoords, this->globalStepIndex, this->hierarchyPhase);
} break;
case 7:
{
Scalar b8_0(0.110854379580391483508936171010218441909425780168656559807038);
Scalar b8_1(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b8_2(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b8_3(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b8_4(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b8_5(-0.0605761488255005587620924953655516875526344415354339234619466);
Scalar b8_6(0.321763705601778390100898799049878904081404368603077129251110);
Scalar b8_7(0.510485725608063031577759012285123416744672137031752354067590);
system->GetCurrDerivatives(k8, this->globalStepIndex, this->hierarchyPhase);
#pragma omp parallel for
for (int coordIndex = 0; coordIndex < system->GetDimentionsCount(this->globalStepIndex, this->hierarchyPhase); coordIndex++)
{
probeCoords[coordIndex] = currCoords[coordIndex] + this->timeStep * (
b8_0 * k1[coordIndex]
+ b8_1 * k2[coordIndex]
+ b8_2 * k3[coordIndex]
+ b8_3 * k4[coordIndex]
+ b8_4 * k5[coordIndex]
+ b8_5 * k6[coordIndex]
+ b8_6 * k7[coordIndex]
+ b8_7 * k8[coordIndex]
);
}
system->SetCurrCoords(this->currTime + this->timeStep * Scalar(0.354017365856802376329264185948796742115824053807373968324184), probeCoords, this->globalStepIndex, this->hierarchyPhase);
} break;
case 8:
{
Scalar b9_0(0.112054414752879004829715002761802363003717611158172229329393);
Scalar b9_1(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b9_2(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b9_3(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b9_4(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b9_5(-0.144942775902865915672349828340980777181668499748506838876185);
Scalar b9_6(-0.333269719096256706589705211415746871709467423992115497968724);
Scalar b9_7(0.499269229556880061353316843969978567860276816592673201240332);
Scalar b9_8(0.509504608929686104236098690045386253986643232352989602185060);
system->GetCurrDerivatives(k9, this->globalStepIndex, this->hierarchyPhase);
#pragma omp parallel for
for (int coordIndex = 0; coordIndex < system->GetDimentionsCount(this->globalStepIndex, this->hierarchyPhase); coordIndex++)
{
probeCoords[coordIndex] = currCoords[coordIndex] + this->timeStep * (
b9_0 * k1[coordIndex]
+ b9_1 * k2[coordIndex]
+ b9_2 * k3[coordIndex]
+ b9_3 * k4[coordIndex]
+ b9_4 * k5[coordIndex]
+ b9_5 * k6[coordIndex]
+ b9_6 * k7[coordIndex]
+ b9_7 * k8[coordIndex]
+ b9_8 * k9[coordIndex]
);
}
system->SetCurrCoords(this->currTime + this->timeStep * Scalar(0.882527661964732346425501486979669075182867844268052119663791), probeCoords, this->globalStepIndex, this->hierarchyPhase);
} break;
case 9:
{
Scalar b10_0(0.113976783964185986138004186736901163890724752541486831640341);
Scalar b10_1(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b10_2(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b10_3(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b10_4(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b10_5(-0.0768813364203356938586214289120895270821349023390922987406384);
Scalar b10_6(0.239527360324390649107711455271882373019741311201004119339563);
Scalar b10_7(0.397774662368094639047830462488952104564716416343454639902613);
Scalar b10_8(0.0107558956873607455550609147441477450257136782823280838547024);
Scalar b10_9(-0.327769124164018874147061087350233395378262992392394071906457);
system->GetCurrDerivatives(k10, this->globalStepIndex, this->hierarchyPhase);
#pragma omp parallel for
for (int coordIndex = 0; coordIndex < system->GetDimentionsCount(this->globalStepIndex, this->hierarchyPhase); coordIndex++)
{
probeCoords[coordIndex] = currCoords[coordIndex] + this->timeStep * (
b10_0 * k1[coordIndex]
+ b10_1 * k2[coordIndex]
+ b10_2 * k3[coordIndex]
+ b10_3 * k4[coordIndex]
+ b10_4 * k5[coordIndex]
+ b10_5 * k6[coordIndex]
+ b10_6 * k7[coordIndex]
+ b10_7 * k8[coordIndex]
+ b10_8 * k9[coordIndex]
+ b10_9 * k10[coordIndex]
);
}
system->SetCurrCoords(this->currTime + this->timeStep * Scalar(0.642615758240322548157075497020439535959501736363212695909875), probeCoords, this->globalStepIndex, this->hierarchyPhase);
} break;
case 10:
{
Scalar b11_0(0.0798314528280196046351426864486400322758737630423413945356284);
Scalar b11_1(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b11_2(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b11_3(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b11_4(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b11_5(-0.0520329686800603076514949887612959068721311443881683526937298);
Scalar b11_6(-0.0576954146168548881732784355283433509066159287152968723021864);
Scalar b11_7(0.194781915712104164976306262147382871156142921354409364738090);
Scalar b11_8(0.145384923188325069727524825977071194859203467568236523866582);
Scalar b11_9(-0.0782942710351670777553986729725692447252077047239160551335016);
Scalar b11_10(-0.114503299361098912184303164290554670970133218405658122674674);
system->GetCurrDerivatives(k11, this->globalStepIndex, this->hierarchyPhase);
#pragma omp parallel for
for (int coordIndex = 0; coordIndex < system->GetDimentionsCount(this->globalStepIndex, this->hierarchyPhase); coordIndex++)
{
probeCoords[coordIndex] = currCoords[coordIndex] + this->timeStep * (
b11_0 * k1[coordIndex]
+ b11_1 * k2[coordIndex]
+ b11_2 * k3[coordIndex]
+ b11_3 * k4[coordIndex]
+ b11_4 * k5[coordIndex]
+ b11_5 * k6[coordIndex]
+ b11_6 * k7[coordIndex]
+ b11_7 * k8[coordIndex]
+ b11_8 * k9[coordIndex]
+ b11_9 * k10[coordIndex]
+ b11_10 * k11[coordIndex]
);
}
system->SetCurrCoords(this->currTime + this->timeStep * Scalar(0.357384241759677451842924502979560464040498263636787304090125), probeCoords, this->globalStepIndex, this->hierarchyPhase);
} break;
case 11:
{
Scalar b12_0(0.985115610164857280120041500306517278413646677314195559520529);
Scalar b12_1(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b12_2(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b12_3(0.330885963040722183948884057658753173648240154838402033448632);
Scalar b12_4(0.489662957309450192844507011135898201178015478433790097210790);
Scalar b12_5(-1.37896486574843567582112720930751902353904327148559471526397);
Scalar b12_6(-0.861164195027635666673916999665534573351026060987427093314412);
Scalar b12_7(5.78428813637537220022999785486578436006872789689499172601856);
Scalar b12_8(3.28807761985103566890460615937314805477268252903342356581925);
Scalar b12_9(-2.38633905093136384013422325215527866148401465975954104585807);
Scalar b12_10(-3.25479342483643918654589367587788726747711504674780680269911);
Scalar b12_11(-2.16343541686422982353954211300054820889678036420109999154887);
system->GetCurrDerivatives(k12, this->globalStepIndex, this->hierarchyPhase);
#pragma omp parallel for
for (int coordIndex = 0; coordIndex < system->GetDimentionsCount(this->globalStepIndex, this->hierarchyPhase); coordIndex++)
{
probeCoords[coordIndex] = currCoords[coordIndex] + this->timeStep * (
b12_0 * k1[coordIndex]
+ b12_1 * k2[coordIndex]
+ b12_2 * k3[coordIndex]
+ b12_3 * k4[coordIndex]
+ b12_4 * k5[coordIndex]
+ b12_5 * k6[coordIndex]
+ b12_6 * k7[coordIndex]
+ b12_7 * k8[coordIndex]
+ b12_8 * k9[coordIndex]
+ b12_9 * k10[coordIndex]
+ b12_10 * k11[coordIndex]
+ b12_11 * k12[coordIndex]
);
}
system->SetCurrCoords(this->currTime + this->timeStep * Scalar(0.117472338035267653574498513020330924817132155731947880336209), probeCoords, this->globalStepIndex, this->hierarchyPhase);
} break;
case 12:
{
Scalar b13_0(0.895080295771632891049613132336585138148156279241561345991710);
Scalar b13_1(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b13_2(0.197966831227192369068141770510388793370637287463360401555746);
Scalar b13_3(-0.0729547847313632629185146671595558023015011608914382961421311);
Scalar b13_4(0.0000000000000000000000000000000000000000000000000000000000000);
Scalar b13_5(-0.851236239662007619739049371445966793289359722875702227166105);
Scalar b13_6(0.398320112318533301719718614174373643336480918103773904231856);
Scalar b13_7(3.63937263181035606029412920047090044132027387893977804176229);
Scalar b13_8(1.54822877039830322365301663075174564919981736348973496313065);
Scalar b13_9(-2.12221714704053716026062427460427261025318461146260124401561);
Scalar b13_10(-1.58350398545326172713384349625753212757269188934434237975291);
Scalar b13_11(-1.71561608285936264922031819751349098912615880827551992973034);
Scalar b13_12(-0.0244036405750127452135415444412216875465593598370910566069132);
system->GetCurrDerivatives(k13, this->globalStepIndex, this->hierarchyPhase);
#pragma omp parallel for
for (int coordIndex = 0; coordIndex < system->GetDimentionsCount(this->globalStepIndex, this->hierarchyPhase); coordIndex++)
{
probeCoords[coordIndex] = currCoords[coordIndex] + this->timeStep * (
b13_0 * k1[coordIndex]
+ b13_1 * k2[coordIndex]
+ b13_2 * k3[coordIndex]
+ b13_3 * k4[coordIndex]
+ b13_4 * k5[coordIndex]
+ b13_5 * k6[coordIndex]
+ b13_6 * k7[coordIndex]
+ b13_7 * k8[coordIndex]
+ b13_8 * k9[coordIndex]
+ b13_9 * k10[coordIndex]
+ b13_10 * k11[coordIndex]
+ b13_11 * k12[coordIndex]
+ b13_12 * k13[coordIndex]
);
}
system->SetCurrCoords(this->currTime + this->timeStep * Scalar(0.833333333333333333333333333333333333333333333333333333333333), probeCoords, this->globalStepIndex, this->hierarchyPhase);
} break;
case 13:
{
Scalar b14_0(-0.915176561375291440520015019275342154318951387664369720564660);
Scalar b14_1(1.45453440217827322805250021715664459117622483736537873607016);
Scalar b14_2(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b14_3(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b14_4(-0.777333643644968233538931228575302137803351053629547286334469);
Scalar b14_5(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b14_6(-0.0910895662155176069593203555807484200111889091770101799647985);
Scalar b14_7(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b14_8(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b14_9(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b14_10(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b14_11(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b14_12(0.0910895662155176069593203555807484200111889091770101799647985);
Scalar b14_13(0.777333643644968233538931228575302137803351053629547286334469);
system->GetCurrDerivatives(k14, this->globalStepIndex, this->hierarchyPhase);
#pragma omp parallel for
for (int coordIndex = 0; coordIndex < system->GetDimentionsCount(this->globalStepIndex, this->hierarchyPhase); coordIndex++)
{
probeCoords[coordIndex] = currCoords[coordIndex] + this->timeStep * (
b14_0 * k1[coordIndex]
+ b14_1 * k2[coordIndex]
+ b14_2 * k3[coordIndex]
+ b14_3 * k4[coordIndex]
+ b14_4 * k5[coordIndex]
+ b14_5 * k6[coordIndex]
+ b14_6 * k7[coordIndex]
+ b14_7 * k8[coordIndex]
+ b14_8 * k9[coordIndex]
+ b14_9 * k10[coordIndex]
+ b14_10 * k11[coordIndex]
+ b14_11 * k12[coordIndex]
+ b14_12 * k13[coordIndex]
+ b14_13 * k14[coordIndex]
);
}
system->SetCurrCoords(this->currTime + this->timeStep * Scalar(0.309036761204472681298727796821953655285910174551513523258250), probeCoords, this->globalStepIndex, this->hierarchyPhase);
} break;
case 14:
{
Scalar b15_0(0.100000000000000000000000000000000000000000000000000000000000);
Scalar b15_1(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b15_2(-0.157178665799771163367058998273128921867183754126709419409654);
Scalar b15_3(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b15_4(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b15_5(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b15_6(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b15_7(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b15_8(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b15_9(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b15_10(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b15_11(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b15_12(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b15_13(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b15_14(0.157178665799771163367058998273128921867183754126709419409654);
system->GetCurrDerivatives(k15, this->globalStepIndex, this->hierarchyPhase);
#pragma omp parallel for
for (int coordIndex = 0; coordIndex < system->GetDimentionsCount(this->globalStepIndex, this->hierarchyPhase); coordIndex++)
{
probeCoords[coordIndex] = currCoords[coordIndex] + this->timeStep * (
b15_0 * k1[coordIndex]
+ b15_1 * k2[coordIndex]
+ b15_2 * k3[coordIndex]
+ b15_3 * k4[coordIndex]
+ b15_4 * k5[coordIndex]
+ b15_5 * k6[coordIndex]
+ b15_6 * k7[coordIndex]
+ b15_7 * k8[coordIndex]
+ b15_8 * k9[coordIndex]
+ b15_9 * k10[coordIndex]
+ b15_10 * k11[coordIndex]
+ b15_11 * k12[coordIndex]
+ b15_12 * k13[coordIndex]
+ b15_13 * k14[coordIndex]
+ b15_14 * k15[coordIndex]
);
}
system->SetCurrCoords(this->currTime + this->timeStep * Scalar(0.539357840802981787532485197881302436857273449701009015505500), probeCoords, this->globalStepIndex, this->hierarchyPhase);
} break;
case 15:
{
Scalar b16_0(0.181781300700095283888472062582262379650443831463199521664945);
Scalar b16_1(0.675000000000000000000000000000000000000000000000000000000000);
Scalar b16_2(0.342758159847189839942220553413850871742338734703958919937260);
Scalar b16_3(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b16_4(0.259111214548322744512977076191767379267783684543182428778156);
Scalar b16_5(-0.358278966717952089048961276721979397739750634673268802484271);
Scalar b16_6(-1.04594895940883306095050068756409905131588123172378489286080);
Scalar b16_7(0.930327845415626983292300564432428777137601651182965794680397);
Scalar b16_8(1.77950959431708102446142106794824453926275743243327790536000);
Scalar b16_9(0.100000000000000000000000000000000000000000000000000000000000);
Scalar b16_10(-0.282547569539044081612477785222287276408489375976211189952877);
Scalar b16_11(-0.159327350119972549169261984373485859278031542127551931461821);
Scalar b16_12(-0.145515894647001510860991961081084111308650130578626404945571);
Scalar b16_13(-0.259111214548322744512977076191767379267783684543182428778156);
Scalar b16_14(-0.342758159847189839942220553413850871742338734703958919937260);
Scalar b16_15(-0.675000000000000000000000000000000000000000000000000000000000);
system->GetCurrDerivatives(k16, this->globalStepIndex, this->hierarchyPhase);
#pragma omp parallel for
for (int coordIndex = 0; coordIndex < system->GetDimentionsCount(this->globalStepIndex, this->hierarchyPhase); coordIndex++)
{
probeCoords[coordIndex] = currCoords[coordIndex] + this->timeStep * (
b16_0 * k1[coordIndex]
+ b16_1 * k2[coordIndex]
+ b16_2 * k3[coordIndex]
+ b16_3 * k4[coordIndex]
+ b16_4 * k5[coordIndex]
+ b16_5 * k6[coordIndex]
+ b16_6 * k7[coordIndex]
+ b16_7 * k8[coordIndex]
+ b16_8 * k9[coordIndex]
+ b16_9 * k10[coordIndex]
+ b16_10 * k11[coordIndex]
+ b16_11 * k12[coordIndex]
+ b16_12 * k13[coordIndex]
+ b16_13 * k14[coordIndex]
+ b16_14 * k15[coordIndex]
+ b16_15 * k16[coordIndex]
);
}
system->SetCurrCoords(this->currTime + this->timeStep * Scalar(0.100000000000000000000000000000000000000000000000000000000000), probeCoords, this->globalStepIndex, this->hierarchyPhase);
} break;
case 16:
{
Scalar b16_0(0.181781300700095283888472062582262379650443831463199521664945);
Scalar b16_1(0.675000000000000000000000000000000000000000000000000000000000);
Scalar b16_2(0.342758159847189839942220553413850871742338734703958919937260);
Scalar b16_3(0.000000000000000000000000000000000000000000000000000000000000);
Scalar b16_4(0.259111214548322744512977076191767379267783684543182428778156);
Scalar b16_5(-0.358278966717952089048961276721979397739750634673268802484271);
Scalar b16_6(-1.04594895940883306095050068756409905131588123172378489286080);
Scalar b16_7(0.930327845415626983292300564432428777137601651182965794680397);
Scalar b16_8(1.77950959431708102446142106794824453926275743243327790536000);
Scalar b16_9(0.100000000000000000000000000000000000000000000000000000000000);
Scalar b16_10(-0.282547569539044081612477785222287276408489375976211189952877);
Scalar b16_11(-0.159327350119972549169261984373485859278031542127551931461821);
Scalar b16_12(-0.145515894647001510860991961081084111308650130578626404945571);
Scalar b16_13(-0.259111214548322744512977076191767379267783684543182428778156);
Scalar b16_14(-0.342758159847189839942220553413850871742338734703958919937260);
Scalar b16_15(-0.675000000000000000000000000000000000000000000000000000000000);
Scalar c0(0.0333333333333333333333333333333333333333333333333333333333333);
Scalar c1(0.0250000000000000000000000000000000000000000000000000000000000);
Scalar c2(0.0333333333333333333333333333333333333333333333333333333333333);
Scalar c3(0.000000000000000000000000000000000000000000000000000000000000);
Scalar c4(0.0500000000000000000000000000000000000000000000000000000000000);
Scalar c5(0.000000000000000000000000000000000000000000000000000000000000);
Scalar c6(0.0400000000000000000000000000000000000000000000000000000000000);
Scalar c7(0.000000000000000000000000000000000000000000000000000000000000);
Scalar c8(0.189237478148923490158306404106012326238162346948625830327194);
Scalar c9(0.277429188517743176508360262560654340428504319718040836339472);
Scalar c10(0.277429188517743176508360262560654340428504319718040836339472);
Scalar c11(0.189237478148923490158306404106012326238162346948625830327194);
Scalar c12(-0.0400000000000000000000000000000000000000000000000000000000000);
Scalar c13(-0.0500000000000000000000000000000000000000000000000000000000000);
Scalar c14(-0.0333333333333333333333333333333333333333333333333333333333333);
Scalar c15(-0.0250000000000000000000000000000000000000000000000000000000000);
Scalar c16(0.0333333333333333333333333333333333333333333333333333333333333);
system->GetCurrDerivatives(k17, this->globalStepIndex, this->hierarchyPhase);
#pragma omp parallel for
for (int coordIndex = 0; coordIndex < system->GetDimentionsCount(this->globalStepIndex, this->hierarchyPhase); coordIndex++)
{
nextCoords1[coordIndex] = currCoords[coordIndex] + this->timeStep * (
b16_0 * k1[coordIndex]
+ b16_1 * k2[coordIndex]
+ b16_2 * k3[coordIndex]
+ b16_3 * k4[coordIndex]
+ b16_4 * k5[coordIndex]
+ b16_5 * k6[coordIndex]
+ b16_6 * k7[coordIndex]
+ b16_7 * k8[coordIndex]
+ b16_8 * k9[coordIndex]
+ b16_9 * k10[coordIndex]
+ b16_10 * k11[coordIndex]
+ b16_11 * k12[coordIndex]
+ b16_12 * k13[coordIndex]
+ b16_13 * k14[coordIndex]
+ b16_14 * k15[coordIndex]
+ b16_15 * k16[coordIndex]
);
nextCoords2[coordIndex] = currCoords[coordIndex] + this->timeStep * (
c0 * k1[coordIndex]
+ c1 * k2[coordIndex]
+ c2 * k3[coordIndex]
+ c3 * k4[coordIndex]
+ c4 * k5[coordIndex]
+ c5 * k6[coordIndex]
+ c6 * k7[coordIndex]
+ c7 * k8[coordIndex]
+ c8 * k9[coordIndex]
+ c9 * k10[coordIndex]
+ c10 * k11[coordIndex]
+ c11 * k12[coordIndex]
+ c12 * k13[coordIndex]
+ c13 * k14[coordIndex]
+ c14 * k15[coordIndex]
+ c15 * k16[coordIndex]
+ c16 * k17[coordIndex]
);
}
stepError = (system->GetErrorValue(this->currTime, nextCoords1, nextCoords2, this->globalStepIndex, this->hierarchyPhase) / this->tolerance) / this->timeStep;
predictedStep = this->timeStep * Scalar(pow(Scalar(1.0) / stepError, Scalar(0.1)));
} break;
}
}
void AdvanceStep(const SolverState& solverState) override
{
if (this->hierarchyPhase == 1)
{
this->currTime += this->timeStep;
}
system->SetCurrCoords(this->currTime, nextCoords2, this->globalStepIndex, this->hierarchyPhase);
}
void RevertStep(Scalar) override
{
system->SetCurrCoords(this->currTime, currCoords, this->globalStepIndex, this->hierarchyPhase);
}
Scalar GetLastStepError() const override
{
return stepError;
}
Scalar GetTimeStepPrediction() const override
{
return predictedStep;
}
private:
Scalar* currCoords;
Scalar* nextCoords1;
Scalar* nextCoords2;
Scalar* probeCoords;
Scalar* derivatives;
Scalar* k1;
Scalar* k2;
Scalar* k3;
Scalar* k4;
Scalar* k5;
Scalar* k6;
Scalar* k7;
Scalar *k8;
Scalar *k9;
Scalar *k10;
Scalar *k11;
Scalar *k12;
Scalar *k13;
Scalar *k14;
Scalar *k15;
Scalar *k16;
Scalar *k17;
Scalar stepError;
Scalar predictedStep;
DifferentialSystem<Scalar>* system;
};
|
c_jacobi03.c | /* ***********************************************************************
This program is part of the
OpenMP Source Code Repository
http://www.pcg.ull.es/ompscr/
e-mail: ompscr@etsii.ull.es
Copyright (c) 2004, OmpSCR Group
All rights reserved.
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 following disclaimer.
* 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.
* Neither the name of the University of La Laguna 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 OWNER 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.
FILE: c_jacobi03.c
VERSION: 1.0
DATE: Oct 2004
AUTHORS: Author: Joseph Robicheaux, Kuck and Associates, Inc. (KAI), 1998
Modified: Sanjiv Shah, Kuck and Associates, Inc. (KAI), 1998
This version: Dieter an Mey, Aachen University (RWTH), 1999 - 2003
anmey@rz.rwth-aachen.de
http://www.rwth-aachen.de/People/D.an.Mey.html
COMMENTS TO: ompscr@etsii.ull.es
DESCRIPTION: program to solve a finite difference discretization of Helmholtz equation :
(d2/dx2)u + (d2/dy2)u - alpha u = f using Jacobi iterative method.
COMMENTS: OpenMP version 3: 1 PR outside the iteration loop, 4 Barriers
Directives are used in this code to achieve paralleism.
All do loops are parallized with default 'static' scheduling.
REFERENCES: http://www.rz.rwth-aachen.de/computing/hpc/prog/par/openmp/jacobi.html
BASIC PRAGMAS: parallel for
USAGE: ./c_jacobi03.par 5000 5000 0.8 1.0 1000
INPUT: n - grid dimension in x direction
m - grid dimension in y direction
alpha - Helmholtz constant (always greater than 0.0)
tol - error tolerance for iterative solver
relax - Successice over relaxation parameter
mits - Maximum iterations for iterative solver
OUTPUT: Residual and error
u(n,m) - Dependent variable (solutions)
f(n,m) - Right hand side function
FILE FORMATS: -
RESTRICTIONS: -
REVISION HISTORY:
**************************************************************************/
#include <omp.h>
#include <stdio.h>
#include <math.h>
#include <stdlib.h>
//#include "OmpSCR.h"
#define U(i,j) u[(i)*n+(j)]
#define F(i,j) f[(i)*n+(j)]
#define NUM_ARGS 6
#define NUM_TIMERS 1
#define NIN 4
#define MIN 4
#define ALPHA 0.1
#define TOL 0.1
#define RELAX 2
#define MITS 2
int n, m, mits;
double tol, relax, alpha;
void jacobi (int n, int m, double dx, double dy,
double alpha, double omega,
double *u, double *f,
double tol, int maxit );
/******************************************************
* Initializes data
* Assumes exact solution is u(x,y) = (1-x^2)*(1-y^2)
*
******************************************************/
void initialize(
int n,
int m,
double alpha,
double *dx,
double *dy,
double *u,
double *f)
{
int i,j,xx,yy;
*dx = 2.0 / (n-1);
*dy = 2.0 / (m-1);
/* Initilize initial condition and RHS */
for (j=0; j<m; j++){
for (i=0; i<n; i++){
xx = -1.0 + *dx * (i-1);
yy = -1.0 + *dy * (j-1);
U(j,i) = 0.0;
F(j,i) = -alpha * (1.0 - xx*xx) * (1.0 - yy*yy)
- 2.0 * (1.0 - xx*xx) - 2.0 * (1.0 - yy*yy);
}
}
}
/************************************************************
* Checks error between numerical and exact solution
*
************************************************************/
void error_check(
int n,
int m,
double alpha,
double dx,
double dy,
double *u,
double *f)
{
int i,j;
double xx, yy, temp, error;
dx = 2.0 / (n-1);
dy = 2.0 / (n-2);
error = 0.0;
for (j=0; j<m; j++){
for (i=0; i<n; i++){
xx = -1.0 + dx * (i-1);
yy = -1.0 + dy * (j-1);
temp = U(j,i) - (1.0 - xx*xx) * (1.0 - yy*yy);
error += temp*temp;
}
}
error = sqrt(error)/(n*m);
printf("Solution Error : %g\n", error);
}
int main(int argc, char **argv){
double *u, *f, dx, dy;
double dt, mflops;
int NUMTHREADS;
// char *PARAM_NAMES[NUM_ARGS] = {"Grid dimension: X dir =", "Grid dimension: Y dir =", "Helmhotlz constant =",
// "Successive over-relaxation parameter =",
// "error tolerance for iterative solver =", "Maximum iterations for solver ="};
// char *TIMERS_NAMES[NUM_TIMERS] = {"Total_time"};
// char *DEFAULT_VALUES[NUM_ARGS] = {"5000", "5000", "0.8", "1.0", "1e-7", "1000"};
NUMTHREADS = 1; //omp_get_num_threads();
//OSCR_init (NUMTHREADS, "Jacobi Solver v1", "Use 'jacoib03' <n> <m> <alpha> <relax> <tol> <mits>", NUM_ARGS,
// PARAM_NAMES, DEFAULT_VALUES , NUM_TIMERS, NUM_TIMERS, TIMERS_NAMES,
// argc, argv);
n = NIN; // OSCR_getarg_int(1);
m = MIN; // OSCR_getarg_int(2);
alpha = ALPHA; // OSCR_getarg_double(3);
relax = RELAX; // OSCR_getarg_double(4);
tol = TOL; // OSCR_getarg_double(5);
mits = MITS; // OSCR_getarg_int(6);
printf("-> %d, %d, %g, %g, %g, %d\n",
n, m, alpha, relax, tol, mits);
u = (double *) malloc(n*m*sizeof(double));
f = (double *) malloc(n*m*sizeof(double));
/* arrays are allocated and initialzed */
initialize(n, m, alpha, &dx, &dy, u, f);
/* Solve Helmholtz eqiation */
//OSCR_timer_start(0);
jacobi(n, m, dx, dy, alpha, relax, u,f, tol, mits);
//OSCR_timer_stop(0);
dt = 1; //OSCR_timer_read(0);
printf(" elapsed time : %12.6f\n", dt);
mflops = (0.000001*mits*(m-2)*(n-2)*13) / dt;
printf(" MFlops : %12.6g (%d, %d, %d, %g)\n",mflops, mits, m, n, dt);
error_check(n, m, alpha, dx, dy, u, f);
//OSCR_report(1, TIMERS_NAMES);
return 0;
}
/*
subroutine jacobi (n,m,dx,dy,alpha,omega,u,f,tol,maxit)
******************************************************************
* Subroutine HelmholtzJ
* Solves poisson equation on rectangular grid assuming :
* (1) Uniform discretization in each direction, and
* (2) Dirichlect boundary conditions
*
* Jacobi method is used in this routine
*
* Input : n,m Number of grid points in the X/Y directions
* dx,dy Grid spacing in the X/Y directions
* alpha Helmholtz eqn. coefficient
* omega Relaxation factor
* f(n,m) Right hand side function
* u(n,m) Dependent variable/Solution
* tol Tolerance for iterative solver
* maxit Maximum number of iterations
*
* Output : u(n,m) - Solution
*****************************************************************
*/
void jacobi ( const int n, const int m, double dx, double dy, double alpha,
double omega, double *u, double *f, double tol, int maxit )
{
int i,j,k;
double error, resid, ax, ay, b;
double *uold;
/* wegen Array-Kompatibilitaet, werden die Zeilen und Spalten (im Kopf)
getauscht, zB uold[spalten_num][zeilen_num]; bzw. wir tuen so, als ob wir das
gespiegelte Problem loesen wollen */
uold = (double *)malloc(sizeof(double) * n *m);
ax = 1.0/(dx * dx); /* X-direction coef */
ay = 1.0/(dy*dy); /* Y_direction coef */
b = -2.0/(dx*dx)-2.0/(dy*dy) - alpha; /* Central coeff */
error = 10.0 * tol;
k = 1;
#pragma omp parallel private(resid, i)
{
while (k <= maxit && error > tol) {
/* copy new solution into old */
#pragma omp for
for (j=0; j<m; j++)
for (i=0; i<n; i++)
uold[i + m*j] = u[i + m*j];
/* compute stencil, residual and update */
#pragma omp for reduction(+:error)
for (i=1; i<n-1; i++){
resid =(
ax * (uold[i-1 + m*j] + uold[i+1 + m*j])
+ ay * (uold[i + m*(j-1)] + uold[i + m*(j+1)])
+ b * uold[i + m*j] - f[i + m*j]
) / b;
/* update solution */
u[i + m*j] = uold[i + m*j] - omega * resid;
/* accumulate residual error */
error =error + resid*resid;
} /* end for */
/* error check */
#pragma omp master
{
k++;
error = sqrt(error) /(n*m);
}
} /* while */
} /* end parallel */
printf("Total Number of Iteratuons %d\n", k);
printf("Residual %.15f\n", error);
free(uold);
}
|
Diffusion_core.c | /*
* This work is part of the Core Imaging Library developed by
* Visual Analytics and Imaging System Group of the Science Technology
* Facilities Council, STFC
*
* Copyright 2017 Daniil Kazantsev
* Copyright 2017 Srikanth Nagella, Edoardo Pasca
*
* 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.
*/
#include "Diffusion_core.h"
#include "utils.h"
#define EPS 1.0e-5
#define MAX(x, y) (((x) > (y)) ? (x) : (y))
#define MIN(x, y) (((x) < (y)) ? (x) : (y))
/*sign function*/
int signNDFc(float x) {
return (x > 0) - (x < 0);
}
/* C-OMP implementation of linear and nonlinear diffusion with the regularisation model [1,2] (2D/3D case)
* The minimisation is performed using explicit scheme.
*
* Input Parameters:
* 1. Noisy image/volume
* 2. lambda - regularization parameter
* 3. Edge-preserving parameter (sigma), when sigma equals to zero nonlinear diffusion -> linear diffusion
* 4. Number of iterations, for explicit scheme >= 150 is recommended
* 5. tau - time-marching step for explicit scheme
* 6. Penalty type: 1 - Huber, 2 - Perona-Malik, 3 - Tukey Biweight
*
* Output:
* [1] Regularized image/volume
*
* This function is based on the paper by
* [1] Perona, P. and Malik, J., 1990. Scale-space and edge detection using anisotropic diffusion. IEEE Transactions on pattern analysis and machine intelligence, 12(7), pp.629-639.
* [2] Black, M.J., Sapiro, G., Marimont, D.H. and Heeger, D., 1998. Robust anisotropic diffusion. IEEE Transactions on image processing, 7(3), pp.421-432.
*/
float Diffusion_CPU_main(float *Input, float *Output, float lambdaPar, float sigmaPar, int iterationsNumb, float tau, int penaltytype, int dimX, int dimY, int dimZ)
{
int i;
float sigmaPar2;
sigmaPar2 = sigmaPar/sqrt(2.0f);
/* copy into output */
copyIm(Input, Output, (long)(dimX), (long)(dimY), (long)(dimZ));
if (dimZ == 1) {
/* running 2D diffusion iterations */
for(i=0; i < iterationsNumb; i++) {
if (sigmaPar == 0.0f) LinearDiff2D(Input, Output, lambdaPar, tau, (long)(dimX), (long)(dimY)); /* linear diffusion (heat equation) */
else NonLinearDiff2D(Input, Output, lambdaPar, sigmaPar2, tau, penaltytype, (long)(dimX), (long)(dimY)); /* nonlinear diffusion */
}
}
else {
/* running 3D diffusion iterations */
for(i=0; i < iterationsNumb; i++) {
if (sigmaPar == 0.0f) LinearDiff3D(Input, Output, lambdaPar, tau, (long)(dimX), (long)(dimY), (long)(dimZ));
else NonLinearDiff3D(Input, Output, lambdaPar, sigmaPar2, tau, penaltytype, (long)(dimX), (long)(dimY), (long)(dimZ));
}
}
return *Output;
}
/********************************************************************/
/***************************2D Functions*****************************/
/********************************************************************/
/* linear diffusion (heat equation) */
float LinearDiff2D(float *Input, float *Output, float lambdaPar, float tau, long dimX, long dimY)
{
long i,j,i1,i2,j1,j2,index;
float e,w,n,s,e1,w1,n1,s1;
#pragma omp parallel for shared(Input) private(index,i,j,i1,i2,j1,j2,e,w,n,s,e1,w1,n1,s1)
for(i=0; i<dimX; i++) {
/* symmetric boundary conditions (Neuman) */
i1 = i+1; if (i1 == dimX) i1 = i-1;
i2 = i-1; if (i2 < 0) i2 = i+1;
for(j=0; j<dimY; j++) {
/* symmetric boundary conditions (Neuman) */
j1 = j+1; if (j1 == dimY) j1 = j-1;
j2 = j-1; if (j2 < 0) j2 = j+1;
index = j*dimX+i;
e = Output[j*dimX+i1];
w = Output[j*dimX+i2];
n = Output[j1*dimX+i];
s = Output[j2*dimX+i];
e1 = e - Output[index];
w1 = w - Output[index];
n1 = n - Output[index];
s1 = s - Output[index];
Output[index] += tau*(lambdaPar*(e1 + w1 + n1 + s1) - (Output[index] - Input[index]));
}}
return *Output;
}
/* nonlinear diffusion */
float NonLinearDiff2D(float *Input, float *Output, float lambdaPar, float sigmaPar, float tau, int penaltytype, long dimX, long dimY)
{
long i,j,i1,i2,j1,j2,index;
float e,w,n,s,e1,w1,n1,s1;
#pragma omp parallel for shared(Input) private(index,i,j,i1,i2,j1,j2,e,w,n,s,e1,w1,n1,s1)
for(i=0; i<dimX; i++) {
/* symmetric boundary conditions (Neuman) */
i1 = i+1; if (i1 == dimX) i1 = i-1;
i2 = i-1; if (i2 < 0) i2 = i+1;
for(j=0; j<dimY; j++) {
/* symmetric boundary conditions (Neuman) */
j1 = j+1; if (j1 == dimY) j1 = j-1;
j2 = j-1; if (j2 < 0) j2 = j+1;
index = j*dimX+i;
e = Output[j*dimX+i1];
w = Output[j*dimX+i2];
n = Output[j1*dimX+i];
s = Output[j2*dimX+i];
e1 = e - Output[index];
w1 = w - Output[index];
n1 = n - Output[index];
s1 = s - Output[index];
if (penaltytype == 1){
/* Huber penalty */
if (fabs(e1) > sigmaPar) e1 = signNDFc(e1);
else e1 = e1/sigmaPar;
if (fabs(w1) > sigmaPar) w1 = signNDFc(w1);
else w1 = w1/sigmaPar;
if (fabs(n1) > sigmaPar) n1 = signNDFc(n1);
else n1 = n1/sigmaPar;
if (fabs(s1) > sigmaPar) s1 = signNDFc(s1);
else s1 = s1/sigmaPar;
}
else if (penaltytype == 2) {
/* Perona-Malik */
e1 = (e1)/(1.0f + powf((e1/sigmaPar),2));
w1 = (w1)/(1.0f + powf((w1/sigmaPar),2));
n1 = (n1)/(1.0f + powf((n1/sigmaPar),2));
s1 = (s1)/(1.0f + powf((s1/sigmaPar),2));
}
else if (penaltytype == 3) {
/* Tukey Biweight */
if (fabs(e1) <= sigmaPar) e1 = e1*powf((1.0f - powf((e1/sigmaPar),2)), 2);
else e1 = 0.0f;
if (fabs(w1) <= sigmaPar) w1 = w1*powf((1.0f - powf((w1/sigmaPar),2)), 2);
else w1 = 0.0f;
if (fabs(n1) <= sigmaPar) n1 = n1*powf((1.0f - powf((n1/sigmaPar),2)), 2);
else n1 = 0.0f;
if (fabs(s1) <= sigmaPar) s1 = s1*powf((1.0f - powf((s1/sigmaPar),2)), 2);
else s1 = 0.0f;
}
else {
printf("%s \n", "No penalty function selected! Use 1,2 or 3.");
break;
}
Output[index] += tau*(lambdaPar*(e1 + w1 + n1 + s1) - (Output[index] - Input[index]));
}}
return *Output;
}
/********************************************************************/
/***************************3D Functions*****************************/
/********************************************************************/
/* linear diffusion (heat equation) */
float LinearDiff3D(float *Input, float *Output, float lambdaPar, float tau, long dimX, long dimY, long dimZ)
{
long i,j,k,i1,i2,j1,j2,k1,k2,index;
float e,w,n,s,u,d,e1,w1,n1,s1,u1,d1;
#pragma omp parallel for shared(Input) private(index,i,j,i1,i2,j1,j2,e,w,n,s,e1,w1,n1,s1,k,k1,k2,u1,d1,u,d)
for(k=0; k<dimZ; k++) {
k1 = k+1; if (k1 == dimZ) k1 = k-1;
k2 = k-1; if (k2 < 0) k2 = k+1;
for(i=0; i<dimX; i++) {
/* symmetric boundary conditions (Neuman) */
i1 = i+1; if (i1 == dimX) i1 = i-1;
i2 = i-1; if (i2 < 0) i2 = i+1;
for(j=0; j<dimY; j++) {
/* symmetric boundary conditions (Neuman) */
j1 = j+1; if (j1 == dimY) j1 = j-1;
j2 = j-1; if (j2 < 0) j2 = j+1;
index = (dimX*dimY)*k + j*dimX+i;
e = Output[(dimX*dimY)*k + j*dimX+i1];
w = Output[(dimX*dimY)*k + j*dimX+i2];
n = Output[(dimX*dimY)*k + j1*dimX+i];
s = Output[(dimX*dimY)*k + j2*dimX+i];
u = Output[(dimX*dimY)*k1 + j*dimX+i];
d = Output[(dimX*dimY)*k2 + j*dimX+i];
e1 = e - Output[index];
w1 = w - Output[index];
n1 = n - Output[index];
s1 = s - Output[index];
u1 = u - Output[index];
d1 = d - Output[index];
Output[index] += tau*(lambdaPar*(e1 + w1 + n1 + s1 + u1 + d1) - (Output[index] - Input[index]));
}}}
return *Output;
}
float NonLinearDiff3D(float *Input, float *Output, float lambdaPar, float sigmaPar, float tau, int penaltytype, long dimX, long dimY, long dimZ)
{
long i,j,k,i1,i2,j1,j2,k1,k2,index;
float e,w,n,s,u,d,e1,w1,n1,s1,u1,d1;
#pragma omp parallel for shared(Input) private(index,i,j,i1,i2,j1,j2,e,w,n,s,e1,w1,n1,s1,k,k1,k2,u1,d1,u,d)
for(k=0; k<dimZ; k++) {
k1 = k+1; if (k1 == dimZ) k1 = k-1;
k2 = k-1; if (k2 < 0) k2 = k+1;
for(i=0; i<dimX; i++) {
/* symmetric boundary conditions (Neuman) */
i1 = i+1; if (i1 == dimX) i1 = i-1;
i2 = i-1; if (i2 < 0) i2 = i+1;
for(j=0; j<dimY; j++) {
/* symmetric boundary conditions (Neuman) */
j1 = j+1; if (j1 == dimY) j1 = j-1;
j2 = j-1; if (j2 < 0) j2 = j+1;
index = (dimX*dimY)*k + j*dimX+i;
e = Output[(dimX*dimY)*k + j*dimX+i1];
w = Output[(dimX*dimY)*k + j*dimX+i2];
n = Output[(dimX*dimY)*k + j1*dimX+i];
s = Output[(dimX*dimY)*k + j2*dimX+i];
u = Output[(dimX*dimY)*k1 + j*dimX+i];
d = Output[(dimX*dimY)*k2 + j*dimX+i];
e1 = e - Output[index];
w1 = w - Output[index];
n1 = n - Output[index];
s1 = s - Output[index];
u1 = u - Output[index];
d1 = d - Output[index];
if (penaltytype == 1){
/* Huber penalty */
if (fabs(e1) > sigmaPar) e1 = signNDFc(e1);
else e1 = e1/sigmaPar;
if (fabs(w1) > sigmaPar) w1 = signNDFc(w1);
else w1 = w1/sigmaPar;
if (fabs(n1) > sigmaPar) n1 = signNDFc(n1);
else n1 = n1/sigmaPar;
if (fabs(s1) > sigmaPar) s1 = signNDFc(s1);
else s1 = s1/sigmaPar;
if (fabs(u1) > sigmaPar) u1 = signNDFc(u1);
else u1 = u1/sigmaPar;
if (fabs(d1) > sigmaPar) d1 = signNDFc(d1);
else d1 = d1/sigmaPar;
}
else if (penaltytype == 2) {
/* Perona-Malik */
e1 = (e1)/(1.0f + powf((e1/sigmaPar),2));
w1 = (w1)/(1.0f + powf((w1/sigmaPar),2));
n1 = (n1)/(1.0f + powf((n1/sigmaPar),2));
s1 = (s1)/(1.0f + powf((s1/sigmaPar),2));
u1 = (u1)/(1.0f + powf((u1/sigmaPar),2));
d1 = (d1)/(1.0f + powf((d1/sigmaPar),2));
}
else if (penaltytype == 3) {
/* Tukey Biweight */
if (fabs(e1) <= sigmaPar) e1 = e1*powf((1.0f - powf((e1/sigmaPar),2)), 2);
else e1 = 0.0f;
if (fabs(w1) <= sigmaPar) w1 = w1*powf((1.0f - powf((w1/sigmaPar),2)), 2);
else w1 = 0.0f;
if (fabs(n1) <= sigmaPar) n1 = n1*powf((1.0f - powf((n1/sigmaPar),2)), 2);
else n1 = 0.0f;
if (fabs(s1) <= sigmaPar) s1 = s1*powf((1.0f - powf((s1/sigmaPar),2)), 2);
else s1 = 0.0f;
if (fabs(u1) <= sigmaPar) u1 = u1*powf((1.0f - powf((u1/sigmaPar),2)), 2);
else u1 = 0.0f;
if (fabs(d1) <= sigmaPar) d1 = d1*powf((1.0f - powf((d1/sigmaPar),2)), 2);
else d1 = 0.0f;
}
else {
printf("%s \n", "No penalty function selected! Use 1,2 or 3.");
break;
}
Output[index] += tau*(lambdaPar*(e1 + w1 + n1 + s1 + u1 + d1) - (Output[index] - Input[index]));
}}}
return *Output;
}
|
GrB_Matrix_serializeSize.c | //------------------------------------------------------------------------------
// GrB_Matrix_serializeSize: return an upper bound on the blob size
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// GrB_Matrix_serialize and GxB_Matrix_serialize both serialize a GrB_Matrix
// into a blob of bytes. This function provides an estimate of the # of bytes
// the blob would have, assuming the default method and default # of threads,
// using the dryrun option in GB_serialize.
#include "GB.h"
#include "GB_serialize.h"
GrB_Info GrB_Matrix_serializeSize // estimate the size of a blob
(
// output:
GrB_Index *blob_size_handle, // upper bound on the required size of the
// blob on output.
// input:
GrB_Matrix A // matrix to serialize
)
{
//--------------------------------------------------------------------------
// check inputs
//--------------------------------------------------------------------------
GB_WHERE1 ("GrB_Matrix_serializeSize (&blob_size, A)") ;
GB_BURBLE_START ("GrB_Matrix_serialize") ;
GB_RETURN_IF_NULL (blob_size_handle) ;
GB_RETURN_IF_NULL_OR_FAULTY (A) ;
// no descriptor, so assume the default method
int method = GxB_DEFAULT ;
// Context will hold the default # of threads, which can be controlled
// by GxB_Global_Option_set.
//--------------------------------------------------------------------------
// serialize the matrix
//--------------------------------------------------------------------------
size_t blob_size ;
GrB_Info info = GB_serialize (NULL, &blob_size, A, method, Context) ;
(*blob_size_handle) = (GrB_Index) blob_size ;
GB_BURBLE_END ;
#pragma omp flush
return (info) ;
}
|
GB_unaryop__minv_bool_int64.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_bool_int64
// op(A') function: GB_tran__minv_bool_int64
// C type: bool
// A type: int64_t
// cast: ;
// unaryop: cij = true
#define GB_ATYPE \
int64_t
#define GB_CTYPE \
bool
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
;
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = true ;
// casting
#define GB_CASTING(z, 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_BOOL || GxB_NO_INT64)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__minv_bool_int64
(
bool *restrict Cx,
const int64_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_bool_int64
(
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
|
diagmv_x_csr_n.c | #include "alphasparse/kernel.h"
#include "alphasparse/util.h"
#include "alphasparse/opt.h"
#ifdef _OPENMP
#include <omp.h>
#endif
static alphasparse_status_t
diagmv_x_csr_n_omp(const ALPHA_Number alpha,
const ALPHA_SPMAT_CSR *A,
const ALPHA_Number *x,
const ALPHA_Number beta,
ALPHA_Number *y)
{
const ALPHA_INT m = A->rows;
const ALPHA_INT thread_num = alpha_get_thread_num();
#ifdef _OPENMP
#pragma omp parallel for num_threads(thread_num)
#endif
for (ALPHA_INT i = 0; i < m; ++i)
{
register ALPHA_Number tmp;
alpha_setzero(tmp);
for (ALPHA_INT ai = A->rows_start[i]; ai < A->rows_end[i]; ++ai)
{
if (A->col_indx[ai] == i)
{
alpha_mul(tmp, alpha, A->values[ai]);
alpha_mule(tmp, x[i]);
break;
}
}
alpha_madd(y[i], beta, y[i], tmp);
// y[i] = beta * y[i] + tmp;
}
return ALPHA_SPARSE_STATUS_SUCCESS;
}
alphasparse_status_t
ONAME(const ALPHA_Number alpha,
const ALPHA_SPMAT_CSR *A,
const ALPHA_Number *x,
const ALPHA_Number beta,
ALPHA_Number *y)
{
return diagmv_x_csr_n_omp(alpha, A, x, beta, y);
}
|
fx.c | /*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% FFFFF X X %
% F X X %
% FFF X %
% F X X %
% F X X %
% %
% %
% MagickCore Image Special Effects Methods %
% %
% Software Design %
% Cristy %
% October 1996 %
% %
% %
% Copyright 1999-2019 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/accelerate-private.h"
#include "magick/annotate.h"
#include "magick/artifact.h"
#include "magick/attribute.h"
#include "magick/cache.h"
#include "magick/cache-view.h"
#include "magick/channel.h"
#include "magick/color.h"
#include "magick/color-private.h"
#include "magick/colorspace.h"
#include "magick/colorspace-private.h"
#include "magick/composite.h"
#include "magick/decorate.h"
#include "magick/distort.h"
#include "magick/draw.h"
#include "magick/effect.h"
#include "magick/enhance.h"
#include "magick/exception.h"
#include "magick/exception-private.h"
#include "magick/fx.h"
#include "magick/fx-private.h"
#include "magick/gem.h"
#include "magick/geometry.h"
#include "magick/layer.h"
#include "magick/list.h"
#include "magick/log.h"
#include "magick/image.h"
#include "magick/image-private.h"
#include "magick/magick.h"
#include "magick/memory_.h"
#include "magick/monitor.h"
#include "magick/monitor-private.h"
#include "magick/opencl-private.h"
#include "magick/option.h"
#include "magick/pixel-accessor.h"
#include "magick/pixel-private.h"
#include "magick/property.h"
#include "magick/quantum.h"
#include "magick/quantum-private.h"
#include "magick/random_.h"
#include "magick/random-private.h"
#include "magick/resample.h"
#include "magick/resample-private.h"
#include "magick/resize.h"
#include "magick/resource_.h"
#include "magick/splay-tree.h"
#include "magick/statistic.h"
#include "magick/string_.h"
#include "magick/string-private.h"
#include "magick/thread-private.h"
#include "magick/threshold.h"
#include "magick/transform.h"
#include "magick/utility.h"
/*
Define declarations.
*/
#define LeftShiftOperator 0xf5U
#define RightShiftOperator 0xf6U
#define LessThanEqualOperator 0xf7U
#define GreaterThanEqualOperator 0xf8U
#define EqualOperator 0xf9U
#define NotEqualOperator 0xfaU
#define LogicalAndOperator 0xfbU
#define LogicalOrOperator 0xfcU
#define ExponentialNotation 0xfdU
struct _FxInfo
{
const Image
*images;
char
*expression;
FILE
*file;
SplayTreeInfo
*colors,
*symbols;
CacheView
**view;
RandomInfo
*random_info;
ExceptionInfo
*exception;
};
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
+ A c q u i r e F x I n f o %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% AcquireFxInfo() allocates the FxInfo structure.
%
% The format of the AcquireFxInfo method is:
%
% FxInfo *AcquireFxInfo(Image *image,const char *expression)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o expression: the expression.
%
*/
MagickExport FxInfo *AcquireFxInfo(const Image *image,const char *expression)
{
char
fx_op[2];
const Image
*next;
FxInfo
*fx_info;
register ssize_t
i;
fx_info=(FxInfo *) AcquireMagickMemory(sizeof(*fx_info));
if (fx_info == (FxInfo *) NULL)
ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
(void) memset(fx_info,0,sizeof(*fx_info));
fx_info->exception=AcquireExceptionInfo();
fx_info->images=image;
fx_info->colors=NewSplayTree(CompareSplayTreeString,RelinquishMagickMemory,
RelinquishAlignedMemory);
fx_info->symbols=NewSplayTree(CompareSplayTreeString,RelinquishMagickMemory,
RelinquishMagickMemory);
fx_info->view=(CacheView **) AcquireQuantumMemory(GetImageListLength(
fx_info->images),sizeof(*fx_info->view));
if (fx_info->view == (CacheView **) NULL)
ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
i=0;
next=GetFirstImageInList(fx_info->images);
for ( ; next != (Image *) NULL; next=next->next)
{
fx_info->view[i]=AcquireVirtualCacheView(next,fx_info->exception);
i++;
}
fx_info->random_info=AcquireRandomInfo();
fx_info->expression=ConstantString(expression);
fx_info->file=stderr;
(void) SubstituteString(&fx_info->expression," ",""); /* compact string */
/*
Force right-to-left associativity for unary negation.
*/
(void) SubstituteString(&fx_info->expression,"-","-1.0*");
(void) SubstituteString(&fx_info->expression,"^-1.0*","^-");
(void) SubstituteString(&fx_info->expression,"E-1.0*","E-");
(void) SubstituteString(&fx_info->expression,"e-1.0*","e-");
/*
Convert compound to simple operators.
*/
fx_op[1]='\0';
*fx_op=(char) LeftShiftOperator;
(void) SubstituteString(&fx_info->expression,"<<",fx_op);
*fx_op=(char) RightShiftOperator;
(void) SubstituteString(&fx_info->expression,">>",fx_op);
*fx_op=(char) LessThanEqualOperator;
(void) SubstituteString(&fx_info->expression,"<=",fx_op);
*fx_op=(char) GreaterThanEqualOperator;
(void) SubstituteString(&fx_info->expression,">=",fx_op);
*fx_op=(char) EqualOperator;
(void) SubstituteString(&fx_info->expression,"==",fx_op);
*fx_op=(char) NotEqualOperator;
(void) SubstituteString(&fx_info->expression,"!=",fx_op);
*fx_op=(char) LogicalAndOperator;
(void) SubstituteString(&fx_info->expression,"&&",fx_op);
*fx_op=(char) LogicalOrOperator;
(void) SubstituteString(&fx_info->expression,"||",fx_op);
*fx_op=(char) ExponentialNotation;
(void) SubstituteString(&fx_info->expression,"**",fx_op);
return(fx_info);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% A d d N o i s e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% AddNoiseImage() adds random noise to the image.
%
% The format of the AddNoiseImage method is:
%
% Image *AddNoiseImage(const Image *image,const NoiseType noise_type,
% ExceptionInfo *exception)
% Image *AddNoiseImageChannel(const Image *image,const ChannelType channel,
% const NoiseType noise_type,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o channel: the channel type.
%
% o noise_type: The type of noise: Uniform, Gaussian, Multiplicative,
% Impulse, Laplacian, or Poisson.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *AddNoiseImage(const Image *image,const NoiseType noise_type,
ExceptionInfo *exception)
{
Image
*noise_image;
noise_image=AddNoiseImageChannel(image,DefaultChannels,noise_type,exception);
return(noise_image);
}
MagickExport Image *AddNoiseImageChannel(const Image *image,
const ChannelType channel,const NoiseType noise_type,ExceptionInfo *exception)
{
#define AddNoiseImageTag "AddNoise/Image"
CacheView
*image_view,
*noise_view;
const char
*option;
double
attenuate;
Image
*noise_image;
MagickBooleanType
status;
MagickOffsetType
progress;
RandomInfo
**magick_restrict random_info;
ssize_t
y;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
unsigned long
key;
#endif
/*
Initialize noise image attributes.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
#if defined(MAGICKCORE_OPENCL_SUPPORT)
noise_image=AccelerateAddNoiseImage(image,channel,noise_type,exception);
if (noise_image != (Image *) NULL)
return(noise_image);
#endif
noise_image=CloneImage(image,0,0,MagickTrue,exception);
if (noise_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(noise_image,DirectClass) == MagickFalse)
{
InheritException(exception,&noise_image->exception);
noise_image=DestroyImage(noise_image);
return((Image *) NULL);
}
/*
Add noise in each row.
*/
attenuate=1.0;
option=GetImageArtifact(image,"attenuate");
if (option != (char *) NULL)
attenuate=StringToDouble(option,(char **) NULL);
status=MagickTrue;
progress=0;
random_info=AcquireRandomInfoThreadSet();
image_view=AcquireVirtualCacheView(image,exception);
noise_view=AcquireAuthenticCacheView(noise_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
key=GetRandomSecretKey(random_info[0]);
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,noise_image,image->rows,key == ~0UL)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
const int
id = GetOpenMPThreadId();
MagickBooleanType
sync;
register const IndexPacket
*magick_restrict indexes;
register const PixelPacket
*magick_restrict p;
register IndexPacket
*magick_restrict noise_indexes;
register ssize_t
x;
register PixelPacket
*magick_restrict q;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=GetCacheViewAuthenticPixels(noise_view,0,y,noise_image->columns,1,
exception);
if ((p == (PixelPacket *) NULL) || (q == (PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
noise_indexes=GetCacheViewAuthenticIndexQueue(noise_view);
for (x=0; x < (ssize_t) image->columns; x++)
{
if ((channel & RedChannel) != 0)
SetPixelRed(q,ClampToQuantum(GenerateDifferentialNoise(random_info[id],
GetPixelRed(p),noise_type,attenuate)));
if (IsGrayColorspace(image->colorspace) != MagickFalse)
{
SetPixelGreen(q,GetPixelRed(q));
SetPixelBlue(q,GetPixelRed(q));
}
else
{
if ((channel & GreenChannel) != 0)
SetPixelGreen(q,ClampToQuantum(GenerateDifferentialNoise(
random_info[id],GetPixelGreen(p),noise_type,attenuate)));
if ((channel & BlueChannel) != 0)
SetPixelBlue(q,ClampToQuantum(GenerateDifferentialNoise(
random_info[id],GetPixelBlue(p),noise_type,attenuate)));
}
if ((channel & OpacityChannel) != 0)
SetPixelOpacity(q,ClampToQuantum(GenerateDifferentialNoise(
random_info[id],GetPixelOpacity(p),noise_type,attenuate)));
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace))
SetPixelIndex(noise_indexes+x,ClampToQuantum(
GenerateDifferentialNoise(random_info[id],GetPixelIndex(
indexes+x),noise_type,attenuate)));
p++;
q++;
}
sync=SyncCacheViewAuthenticPixels(noise_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(image,AddNoiseImageTag,progress,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
noise_view=DestroyCacheView(noise_view);
image_view=DestroyCacheView(image_view);
random_info=DestroyRandomInfoThreadSet(random_info);
if (status == MagickFalse)
noise_image=DestroyImage(noise_image);
return(noise_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% B l u e S h i f t I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% BlueShiftImage() mutes the colors of the image to simulate a scene at
% nighttime in the moonlight.
%
% The format of the BlueShiftImage method is:
%
% Image *BlueShiftImage(const Image *image,const double factor,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o factor: the shift factor.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *BlueShiftImage(const Image *image,const double factor,
ExceptionInfo *exception)
{
#define BlueShiftImageTag "BlueShift/Image"
CacheView
*image_view,
*shift_view;
Image
*shift_image;
MagickBooleanType
status;
MagickOffsetType
progress;
ssize_t
y;
/*
Allocate blue shift image.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
shift_image=CloneImage(image,0,0,MagickTrue,exception);
if (shift_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(shift_image,DirectClass) == MagickFalse)
{
InheritException(exception,&shift_image->exception);
shift_image=DestroyImage(shift_image);
return((Image *) NULL);
}
/*
Blue-shift DirectClass image.
*/
status=MagickTrue;
progress=0;
image_view=AcquireVirtualCacheView(image,exception);
shift_view=AcquireAuthenticCacheView(shift_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,shift_image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
MagickBooleanType
sync;
MagickPixelPacket
pixel;
Quantum
quantum;
register const PixelPacket
*magick_restrict p;
register ssize_t
x;
register PixelPacket
*magick_restrict q;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=QueueCacheViewAuthenticPixels(shift_view,0,y,shift_image->columns,1,
exception);
if ((p == (const PixelPacket *) NULL) || (q == (PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
quantum=GetPixelRed(p);
if (GetPixelGreen(p) < quantum)
quantum=GetPixelGreen(p);
if (GetPixelBlue(p) < quantum)
quantum=GetPixelBlue(p);
pixel.red=0.5*(GetPixelRed(p)+factor*quantum);
pixel.green=0.5*(GetPixelGreen(p)+factor*quantum);
pixel.blue=0.5*(GetPixelBlue(p)+factor*quantum);
quantum=GetPixelRed(p);
if (GetPixelGreen(p) > quantum)
quantum=GetPixelGreen(p);
if (GetPixelBlue(p) > quantum)
quantum=GetPixelBlue(p);
pixel.red=0.5*(pixel.red+factor*quantum);
pixel.green=0.5*(pixel.green+factor*quantum);
pixel.blue=0.5*(pixel.blue+factor*quantum);
SetPixelRed(q,ClampToQuantum(pixel.red));
SetPixelGreen(q,ClampToQuantum(pixel.green));
SetPixelBlue(q,ClampToQuantum(pixel.blue));
p++;
q++;
}
sync=SyncCacheViewAuthenticPixels(shift_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(image,BlueShiftImageTag,progress,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
image_view=DestroyCacheView(image_view);
shift_view=DestroyCacheView(shift_view);
if (status == MagickFalse)
shift_image=DestroyImage(shift_image);
return(shift_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% C h a r c o a l I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% CharcoalImage() creates a new image that is a copy of an existing one with
% the edge highlighted. It allocates the memory necessary for the new Image
% structure and returns a pointer to the new image.
%
% The format of the CharcoalImage method is:
%
% Image *CharcoalImage(const Image *image,const double radius,
% const double sigma,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o radius: the radius of the pixel neighborhood.
%
% o sigma: the standard deviation of the Gaussian, in pixels.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *CharcoalImage(const Image *image,const double radius,
const double sigma,ExceptionInfo *exception)
{
Image
*charcoal_image,
*edge_image;
MagickBooleanType
status;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
edge_image=EdgeImage(image,radius,exception);
if (edge_image == (Image *) NULL)
return((Image *) NULL);
charcoal_image=(Image *) NULL;
status=ClampImage(edge_image);
if (status != MagickFalse)
charcoal_image=BlurImage(edge_image,radius,sigma,exception);
edge_image=DestroyImage(edge_image);
if (charcoal_image == (Image *) NULL)
return((Image *) NULL);
status=NormalizeImage(charcoal_image);
if (status != MagickFalse)
status=NegateImage(charcoal_image,MagickFalse);
if (status != MagickFalse)
status=GrayscaleImage(charcoal_image,image->intensity);
if (status == MagickFalse)
charcoal_image=DestroyImage(charcoal_image);
return(charcoal_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% C o l o r i z e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ColorizeImage() blends the fill color with each pixel in the image.
% A percentage blend is specified with opacity. Control the application
% of different color components by specifying a different percentage for
% each component (e.g. 90/100/10 is 90% red, 100% green, and 10% blue).
%
% The format of the ColorizeImage method is:
%
% Image *ColorizeImage(const Image *image,const char *opacity,
% const PixelPacket colorize,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o opacity: A character string indicating the level of opacity as a
% percentage.
%
% o colorize: A color value.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *ColorizeImage(const Image *image,const char *opacity,
const PixelPacket colorize,ExceptionInfo *exception)
{
#define ColorizeImageTag "Colorize/Image"
CacheView
*colorize_view,
*image_view;
GeometryInfo
geometry_info;
Image
*colorize_image;
MagickBooleanType
status;
MagickOffsetType
progress;
MagickPixelPacket
pixel;
MagickStatusType
flags;
ssize_t
y;
/*
Allocate colorized image.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
colorize_image=CloneImage(image,0,0,MagickTrue,exception);
if (colorize_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(colorize_image,DirectClass) == MagickFalse)
{
InheritException(exception,&colorize_image->exception);
colorize_image=DestroyImage(colorize_image);
return((Image *) NULL);
}
if ((IsGrayColorspace(image->colorspace) != MagickFalse) ||
(IsPixelGray(&colorize) != MagickFalse))
(void) SetImageColorspace(colorize_image,sRGBColorspace);
if ((colorize_image->matte == MagickFalse) &&
(colorize.opacity != OpaqueOpacity))
(void) SetImageAlphaChannel(colorize_image,OpaqueAlphaChannel);
if (opacity == (const char *) NULL)
return(colorize_image);
/*
Determine RGB values of the pen color.
*/
flags=ParseGeometry(opacity,&geometry_info);
pixel.red=geometry_info.rho;
pixel.green=geometry_info.rho;
pixel.blue=geometry_info.rho;
pixel.opacity=(MagickRealType) OpaqueOpacity;
if ((flags & SigmaValue) != 0)
pixel.green=geometry_info.sigma;
if ((flags & XiValue) != 0)
pixel.blue=geometry_info.xi;
if ((flags & PsiValue) != 0)
pixel.opacity=geometry_info.psi;
/*
Colorize DirectClass image.
*/
status=MagickTrue;
progress=0;
image_view=AcquireVirtualCacheView(image,exception);
colorize_view=AcquireAuthenticCacheView(colorize_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,colorize_image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
MagickBooleanType
sync;
register const PixelPacket
*magick_restrict p;
register ssize_t
x;
register PixelPacket
*magick_restrict q;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=QueueCacheViewAuthenticPixels(colorize_view,0,y,colorize_image->columns,1,
exception);
if ((p == (const PixelPacket *) NULL) || (q == (PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
SetPixelRed(q,((GetPixelRed(p)*(100.0-pixel.red)+
colorize.red*pixel.red)/100.0));
SetPixelGreen(q,((GetPixelGreen(p)*(100.0-pixel.green)+
colorize.green*pixel.green)/100.0));
SetPixelBlue(q,((GetPixelBlue(p)*(100.0-pixel.blue)+
colorize.blue*pixel.blue)/100.0));
if (colorize_image->matte == MagickFalse)
SetPixelOpacity(q,GetPixelOpacity(p));
else
SetPixelOpacity(q,((GetPixelOpacity(p)*(100.0-pixel.opacity)+
colorize.opacity*pixel.opacity)/100.0));
p++;
q++;
}
sync=SyncCacheViewAuthenticPixels(colorize_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(image,ColorizeImageTag,progress,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
image_view=DestroyCacheView(image_view);
colorize_view=DestroyCacheView(colorize_view);
if (status == MagickFalse)
colorize_image=DestroyImage(colorize_image);
return(colorize_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% C o l o r M a t r i x I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ColorMatrixImage() applies color transformation to an image. This method
% permits saturation changes, hue rotation, luminance to alpha, and various
% other effects. Although variable-sized transformation matrices can be used,
% typically one uses a 5x5 matrix for an RGBA image and a 6x6 for CMYKA
% (or RGBA with offsets). The matrix is similar to those used by Adobe Flash
% except offsets are in column 6 rather than 5 (in support of CMYKA images)
% and offsets are normalized (divide Flash offset by 255).
%
% The format of the ColorMatrixImage method is:
%
% Image *ColorMatrixImage(const Image *image,
% const KernelInfo *color_matrix,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o color_matrix: the color matrix.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *ColorMatrixImage(const Image *image,
const KernelInfo *color_matrix,ExceptionInfo *exception)
{
#define ColorMatrixImageTag "ColorMatrix/Image"
CacheView
*color_view,
*image_view;
double
ColorMatrix[6][6] =
{
{ 1.0, 0.0, 0.0, 0.0, 0.0, 0.0 },
{ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0 },
{ 0.0, 0.0, 1.0, 0.0, 0.0, 0.0 },
{ 0.0, 0.0, 0.0, 1.0, 0.0, 0.0 },
{ 0.0, 0.0, 0.0, 0.0, 1.0, 0.0 },
{ 0.0, 0.0, 0.0, 0.0, 0.0, 1.0 }
};
Image
*color_image;
MagickBooleanType
status;
MagickOffsetType
progress;
register ssize_t
i;
ssize_t
u,
v,
y;
/*
Create color matrix.
*/
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
i=0;
for (v=0; v < (ssize_t) color_matrix->height; v++)
for (u=0; u < (ssize_t) color_matrix->width; u++)
{
if ((v < 6) && (u < 6))
ColorMatrix[v][u]=color_matrix->values[i];
i++;
}
/*
Initialize color image.
*/
color_image=CloneImage(image,0,0,MagickTrue,exception);
if (color_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(color_image,DirectClass) == MagickFalse)
{
InheritException(exception,&color_image->exception);
color_image=DestroyImage(color_image);
return((Image *) NULL);
}
if (image->debug != MagickFalse)
{
char
format[MaxTextExtent],
*message;
(void) LogMagickEvent(TransformEvent,GetMagickModule(),
" ColorMatrix image with color matrix:");
message=AcquireString("");
for (v=0; v < 6; v++)
{
*message='\0';
(void) FormatLocaleString(format,MaxTextExtent,"%.20g: ",(double) v);
(void) ConcatenateString(&message,format);
for (u=0; u < 6; u++)
{
(void) FormatLocaleString(format,MaxTextExtent,"%+f ",
ColorMatrix[v][u]);
(void) ConcatenateString(&message,format);
}
(void) LogMagickEvent(TransformEvent,GetMagickModule(),"%s",message);
}
message=DestroyString(message);
}
/*
ColorMatrix image.
*/
status=MagickTrue;
progress=0;
image_view=AcquireVirtualCacheView(image,exception);
color_view=AcquireAuthenticCacheView(color_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,color_image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
MagickRealType
pixel;
register const IndexPacket
*magick_restrict indexes;
register const PixelPacket
*magick_restrict p;
register ssize_t
x;
register IndexPacket
*magick_restrict color_indexes;
register PixelPacket
*magick_restrict q;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=GetCacheViewAuthenticPixels(color_view,0,y,color_image->columns,1,
exception);
if ((p == (const PixelPacket *) NULL) || (q == (PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
color_indexes=GetCacheViewAuthenticIndexQueue(color_view);
for (x=0; x < (ssize_t) image->columns; x++)
{
register ssize_t
v;
size_t
height;
height=color_matrix->height > 6 ? 6UL : color_matrix->height;
for (v=0; v < (ssize_t) height; v++)
{
pixel=ColorMatrix[v][0]*GetPixelRed(p)+ColorMatrix[v][1]*
GetPixelGreen(p)+ColorMatrix[v][2]*GetPixelBlue(p);
if (image->matte != MagickFalse)
pixel+=ColorMatrix[v][3]*(QuantumRange-GetPixelOpacity(p));
if (image->colorspace == CMYKColorspace)
pixel+=ColorMatrix[v][4]*GetPixelIndex(indexes+x);
pixel+=QuantumRange*ColorMatrix[v][5];
switch (v)
{
case 0: SetPixelRed(q,ClampToQuantum(pixel)); break;
case 1: SetPixelGreen(q,ClampToQuantum(pixel)); break;
case 2: SetPixelBlue(q,ClampToQuantum(pixel)); break;
case 3:
{
if (image->matte != MagickFalse)
SetPixelAlpha(q,ClampToQuantum(pixel));
break;
}
case 4:
{
if (image->colorspace == CMYKColorspace)
SetPixelIndex(color_indexes+x,ClampToQuantum(pixel));
break;
}
}
}
p++;
q++;
}
if (SyncCacheViewAuthenticPixels(color_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(image,ColorMatrixImageTag,progress,
image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
color_view=DestroyCacheView(color_view);
image_view=DestroyCacheView(image_view);
if (status == MagickFalse)
color_image=DestroyImage(color_image);
return(color_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
+ D e s t r o y F x I n f o %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% DestroyFxInfo() deallocates memory associated with an FxInfo structure.
%
% The format of the DestroyFxInfo method is:
%
% ImageInfo *DestroyFxInfo(ImageInfo *fx_info)
%
% A description of each parameter follows:
%
% o fx_info: the fx info.
%
*/
MagickExport FxInfo *DestroyFxInfo(FxInfo *fx_info)
{
register ssize_t
i;
fx_info->exception=DestroyExceptionInfo(fx_info->exception);
fx_info->expression=DestroyString(fx_info->expression);
fx_info->symbols=DestroySplayTree(fx_info->symbols);
fx_info->colors=DestroySplayTree(fx_info->colors);
for (i=(ssize_t) GetImageListLength(fx_info->images)-1; i >= 0; i--)
fx_info->view[i]=DestroyCacheView(fx_info->view[i]);
fx_info->view=(CacheView **) RelinquishMagickMemory(fx_info->view);
fx_info->random_info=DestroyRandomInfo(fx_info->random_info);
fx_info=(FxInfo *) RelinquishMagickMemory(fx_info);
return(fx_info);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
+ F x E v a l u a t e C h a n n e l E x p r e s s i o n %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FxEvaluateChannelExpression() evaluates an expression and returns the
% results.
%
% The format of the FxEvaluateExpression method is:
%
% MagickBooleanType FxEvaluateChannelExpression(FxInfo *fx_info,
% const ChannelType channel,const ssize_t x,const ssize_t y,
% double *alpha,Exceptioninfo *exception)
% MagickBooleanType FxEvaluateExpression(FxInfo *fx_info,double *alpha,
% Exceptioninfo *exception)
%
% A description of each parameter follows:
%
% o fx_info: the fx info.
%
% o channel: the channel.
%
% o x,y: the pixel position.
%
% o alpha: the result.
%
% o exception: return any errors or warnings in this structure.
%
*/
static double FxChannelStatistics(FxInfo *fx_info,const Image *image,
ChannelType channel,const char *symbol,ExceptionInfo *exception)
{
char
channel_symbol[MaxTextExtent],
key[MaxTextExtent],
statistic[MaxTextExtent];
const char
*value;
register const char
*p;
for (p=symbol; (*p != '.') && (*p != '\0'); p++) ;
*channel_symbol='\0';
if (*p == '.')
{
ssize_t
option;
(void) CopyMagickString(channel_symbol,p+1,MaxTextExtent);
option=ParseCommandOption(MagickChannelOptions,MagickTrue,channel_symbol);
if (option >= 0)
channel=(ChannelType) option;
}
(void) FormatLocaleString(key,MaxTextExtent,"%p.%.20g.%s",(void *) image,
(double) channel,symbol);
value=(const char *) GetValueFromSplayTree(fx_info->symbols,key);
if (value != (const char *) NULL)
return(QuantumScale*StringToDouble(value,(char **) NULL));
(void) DeleteNodeFromSplayTree(fx_info->symbols,key);
if (LocaleNCompare(symbol,"depth",5) == 0)
{
size_t
depth;
depth=GetImageChannelDepth(image,channel,exception);
(void) FormatLocaleString(statistic,MaxTextExtent,"%.20g",(double) depth);
}
if (LocaleNCompare(symbol,"kurtosis",8) == 0)
{
double
kurtosis,
skewness;
(void) GetImageChannelKurtosis(image,channel,&kurtosis,&skewness,
exception);
(void) FormatLocaleString(statistic,MaxTextExtent,"%.20g",kurtosis);
}
if (LocaleNCompare(symbol,"maxima",6) == 0)
{
double
maxima,
minima;
(void) GetImageChannelRange(image,channel,&minima,&maxima,exception);
(void) FormatLocaleString(statistic,MaxTextExtent,"%.20g",maxima);
}
if (LocaleNCompare(symbol,"mean",4) == 0)
{
double
mean,
standard_deviation;
(void) GetImageChannelMean(image,channel,&mean,&standard_deviation,
exception);
(void) FormatLocaleString(statistic,MaxTextExtent,"%.20g",mean);
}
if (LocaleNCompare(symbol,"minima",6) == 0)
{
double
maxima,
minima;
(void) GetImageChannelRange(image,channel,&minima,&maxima,exception);
(void) FormatLocaleString(statistic,MaxTextExtent,"%.20g",minima);
}
if (LocaleNCompare(symbol,"skewness",8) == 0)
{
double
kurtosis,
skewness;
(void) GetImageChannelKurtosis(image,channel,&kurtosis,&skewness,
exception);
(void) FormatLocaleString(statistic,MaxTextExtent,"%.20g",skewness);
}
if (LocaleNCompare(symbol,"standard_deviation",18) == 0)
{
double
mean,
standard_deviation;
(void) GetImageChannelMean(image,channel,&mean,&standard_deviation,
exception);
(void) FormatLocaleString(statistic,MaxTextExtent,"%.20g",
standard_deviation);
}
(void) AddValueToSplayTree(fx_info->symbols,ConstantString(key),
ConstantString(statistic));
return(QuantumScale*StringToDouble(statistic,(char **) NULL));
}
static double
FxEvaluateSubexpression(FxInfo *,const ChannelType,const ssize_t,
const ssize_t,const char *,const size_t,double *,ExceptionInfo *);
static MagickOffsetType FxGCD(MagickOffsetType alpha,MagickOffsetType beta)
{
if (beta != 0)
return(FxGCD(beta,alpha % beta));
return(alpha);
}
static inline const char *FxSubexpression(const char *expression,
ExceptionInfo *exception)
{
const char
*subexpression;
register ssize_t
level;
level=0;
subexpression=expression;
while ((*subexpression != '\0') &&
((level != 1) || (strchr(")",(int) *subexpression) == (char *) NULL)))
{
if (strchr("(",(int) *subexpression) != (char *) NULL)
level++;
else
if (strchr(")",(int) *subexpression) != (char *) NULL)
level--;
subexpression++;
}
if (*subexpression == '\0')
(void) ThrowMagickException(exception,GetMagickModule(),OptionError,
"UnbalancedParenthesis","`%s'",expression);
return(subexpression);
}
static double FxGetSymbol(FxInfo *fx_info,const ChannelType channel,
const ssize_t x,const ssize_t y,const char *expression,const size_t depth,
ExceptionInfo *exception)
{
char
*q,
symbol[MaxTextExtent];
const char
*p,
*value;
double
alpha,
beta;
Image
*image;
MagickBooleanType
status;
MagickPixelPacket
pixel;
PointInfo
point;
register ssize_t
i;
size_t
level;
p=expression;
i=GetImageIndexInList(fx_info->images);
level=0;
point.x=(double) x;
point.y=(double) y;
if (isalpha((int) ((unsigned char) *(p+1))) == 0)
{
char
*subexpression;
subexpression=AcquireString(expression);
if (strchr("suv",(int) *p) != (char *) NULL)
{
switch (*p)
{
case 's':
default:
{
i=GetImageIndexInList(fx_info->images);
break;
}
case 'u': i=0; break;
case 'v': i=1; break;
}
p++;
if (*p == '[')
{
level++;
q=subexpression;
for (p++; *p != '\0'; )
{
if (*p == '[')
level++;
else
if (*p == ']')
{
level--;
if (level == 0)
break;
}
*q++=(*p++);
}
*q='\0';
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,subexpression,
depth,&beta,exception);
i=(ssize_t) alpha;
if (*p != '\0')
p++;
}
if (*p == '.')
p++;
}
if ((*p == 'p') && (isalpha((int) ((unsigned char) *(p+1))) == 0))
{
p++;
if (*p == '{')
{
level++;
q=subexpression;
for (p++; *p != '\0'; )
{
if (*p == '{')
level++;
else
if (*p == '}')
{
level--;
if (level == 0)
break;
}
*q++=(*p++);
}
*q='\0';
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,subexpression,
depth,&beta,exception);
point.x=alpha;
point.y=beta;
if (*p != '\0')
p++;
}
else
if (*p == '[')
{
level++;
q=subexpression;
for (p++; *p != '\0'; )
{
if (*p == '[')
level++;
else
if (*p == ']')
{
level--;
if (level == 0)
break;
}
*q++=(*p++);
}
*q='\0';
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,subexpression,
depth,&beta,exception);
point.x+=alpha;
point.y+=beta;
if (*p != '\0')
p++;
}
if (*p == '.')
p++;
}
subexpression=DestroyString(subexpression);
}
image=GetImageFromList(fx_info->images,i);
if (image == (Image *) NULL)
{
(void) ThrowMagickException(exception,GetMagickModule(),OptionError,
"NoSuchImage","`%s'",expression);
return(0.0);
}
i=GetImageIndexInList(image);
GetMagickPixelPacket(image,&pixel);
status=InterpolateMagickPixelPacket(image,fx_info->view[i],image->interpolate,
point.x,point.y,&pixel,exception);
(void) status;
if ((strlen(p) > 2) &&
(LocaleCompare(p,"intensity") != 0) &&
(LocaleCompare(p,"luma") != 0) &&
(LocaleCompare(p,"luminance") != 0) &&
(LocaleCompare(p,"hue") != 0) &&
(LocaleCompare(p,"saturation") != 0) &&
(LocaleCompare(p,"lightness") != 0))
{
char
name[MaxTextExtent];
(void) CopyMagickString(name,p,MaxTextExtent);
for (q=name+(strlen(name)-1); q > name; q--)
{
if (*q == ')')
break;
if (*q == '.')
{
*q='\0';
break;
}
}
if ((strlen(name) > 2) &&
(GetValueFromSplayTree(fx_info->symbols,name) == (const char *) NULL))
{
MagickPixelPacket
*color;
color=(MagickPixelPacket *) GetValueFromSplayTree(fx_info->colors,
name);
if (color != (MagickPixelPacket *) NULL)
{
pixel=(*color);
p+=strlen(name);
}
else
if (QueryMagickColor(name,&pixel,fx_info->exception) != MagickFalse)
{
(void) AddValueToSplayTree(fx_info->colors,ConstantString(name),
CloneMagickPixelPacket(&pixel));
p+=strlen(name);
}
}
}
(void) CopyMagickString(symbol,p,MaxTextExtent);
StripString(symbol);
if (*symbol == '\0')
{
switch (channel)
{
case RedChannel: return(QuantumScale*pixel.red);
case GreenChannel: return(QuantumScale*pixel.green);
case BlueChannel: return(QuantumScale*pixel.blue);
case OpacityChannel:
{
double
alpha;
if (pixel.matte == MagickFalse)
return(1.0);
alpha=(double) (QuantumScale*GetPixelAlpha(&pixel));
return(alpha);
}
case IndexChannel:
{
if (image->colorspace != CMYKColorspace)
{
(void) ThrowMagickException(exception,GetMagickModule(),
ImageError,"ColorSeparatedImageRequired","`%s'",
image->filename);
return(0.0);
}
return(QuantumScale*pixel.index);
}
case DefaultChannels:
return(QuantumScale*GetMagickPixelIntensity(image,&pixel));
default:
break;
}
(void) ThrowMagickException(exception,GetMagickModule(),OptionError,
"UnableToParseExpression","`%s'",p);
return(0.0);
}
switch (*symbol)
{
case 'A':
case 'a':
{
if (LocaleCompare(symbol,"a") == 0)
return((double) (QuantumScale*GetPixelAlpha(&pixel)));
break;
}
case 'B':
case 'b':
{
if (LocaleCompare(symbol,"b") == 0)
return(QuantumScale*pixel.blue);
break;
}
case 'C':
case 'c':
{
if (LocaleNCompare(symbol,"channel",7) == 0)
{
GeometryInfo
channel_info;
MagickStatusType
flags;
flags=ParseGeometry(symbol+7,&channel_info);
if (image->colorspace == CMYKColorspace)
switch (channel)
{
case CyanChannel:
{
if ((flags & RhoValue) == 0)
return(0.0);
return(channel_info.rho);
}
case MagentaChannel:
{
if ((flags & SigmaValue) == 0)
return(0.0);
return(channel_info.sigma);
}
case YellowChannel:
{
if ((flags & XiValue) == 0)
return(0.0);
return(channel_info.xi);
}
case BlackChannel:
{
if ((flags & PsiValue) == 0)
return(0.0);
return(channel_info.psi);
}
case OpacityChannel:
{
if ((flags & ChiValue) == 0)
return(0.0);
return(channel_info.chi);
}
default:
return(0.0);
}
switch (channel)
{
case RedChannel:
{
if ((flags & RhoValue) == 0)
return(0.0);
return(channel_info.rho);
}
case GreenChannel:
{
if ((flags & SigmaValue) == 0)
return(0.0);
return(channel_info.sigma);
}
case BlueChannel:
{
if ((flags & XiValue) == 0)
return(0.0);
return(channel_info.xi);
}
case OpacityChannel:
{
if ((flags & PsiValue) == 0)
return(0.0);
return(channel_info.psi);
}
case IndexChannel:
{
if ((flags & ChiValue) == 0)
return(0.0);
return(channel_info.chi);
}
default:
return(0.0);
}
}
if (LocaleCompare(symbol,"c") == 0)
return(QuantumScale*pixel.red);
break;
}
case 'D':
case 'd':
{
if (LocaleNCompare(symbol,"depth",5) == 0)
return(FxChannelStatistics(fx_info,image,channel,symbol,exception));
break;
}
case 'E':
case 'e':
{
if (LocaleCompare(symbol,"extent") == 0)
{
if (image->extent != 0)
return((double) image->extent);
return((double) GetBlobSize(image));
}
break;
}
case 'G':
case 'g':
{
if (LocaleCompare(symbol,"g") == 0)
return(QuantumScale*pixel.green);
break;
}
case 'K':
case 'k':
{
if (LocaleNCompare(symbol,"kurtosis",8) == 0)
return(FxChannelStatistics(fx_info,image,channel,symbol,exception));
if (LocaleCompare(symbol,"k") == 0)
{
if (image->colorspace != CMYKColorspace)
{
(void) ThrowMagickException(exception,GetMagickModule(),
OptionError,"ColorSeparatedImageRequired","`%s'",
image->filename);
return(0.0);
}
return(QuantumScale*pixel.index);
}
break;
}
case 'H':
case 'h':
{
if (LocaleCompare(symbol,"h") == 0)
return((double) image->rows);
if (LocaleCompare(symbol,"hue") == 0)
{
double
hue,
lightness,
saturation;
ConvertRGBToHSL(ClampToQuantum(pixel.red),ClampToQuantum(pixel.green),
ClampToQuantum(pixel.blue),&hue,&saturation,&lightness);
return(hue);
}
break;
}
case 'I':
case 'i':
{
if ((LocaleCompare(symbol,"image.depth") == 0) ||
(LocaleCompare(symbol,"image.minima") == 0) ||
(LocaleCompare(symbol,"image.maxima") == 0) ||
(LocaleCompare(symbol,"image.mean") == 0) ||
(LocaleCompare(symbol,"image.kurtosis") == 0) ||
(LocaleCompare(symbol,"image.skewness") == 0) ||
(LocaleCompare(symbol,"image.standard_deviation") == 0))
return(FxChannelStatistics(fx_info,image,channel,symbol+6,exception));
if (LocaleCompare(symbol,"image.resolution.x") == 0)
return(image->x_resolution);
if (LocaleCompare(symbol,"image.resolution.y") == 0)
return(image->y_resolution);
if (LocaleCompare(symbol,"intensity") == 0)
return(QuantumScale*GetMagickPixelIntensity(image,&pixel));
if (LocaleCompare(symbol,"i") == 0)
return((double) x);
break;
}
case 'J':
case 'j':
{
if (LocaleCompare(symbol,"j") == 0)
return((double) y);
break;
}
case 'L':
case 'l':
{
if (LocaleCompare(symbol,"lightness") == 0)
{
double
hue,
lightness,
saturation;
ConvertRGBToHSL(ClampToQuantum(pixel.red),ClampToQuantum(pixel.green),
ClampToQuantum(pixel.blue),&hue,&saturation,&lightness);
return(lightness);
}
if (LocaleCompare(symbol,"luma") == 0)
{
double
luma;
luma=0.212656*pixel.red+0.715158*pixel.green+0.072186*pixel.blue;
return(QuantumScale*luma);
}
if (LocaleCompare(symbol,"luminance") == 0)
{
double
luminance;
luminance=0.212656*pixel.red+0.715158*pixel.green+0.072186*pixel.blue;
return(QuantumScale*luminance);
}
break;
}
case 'M':
case 'm':
{
if (LocaleNCompare(symbol,"maxima",6) == 0)
return(FxChannelStatistics(fx_info,image,channel,symbol,exception));
if (LocaleNCompare(symbol,"mean",4) == 0)
return(FxChannelStatistics(fx_info,image,channel,symbol,exception));
if (LocaleNCompare(symbol,"minima",6) == 0)
return(FxChannelStatistics(fx_info,image,channel,symbol,exception));
if (LocaleCompare(symbol,"m") == 0)
return(QuantumScale*pixel.green);
break;
}
case 'N':
case 'n':
{
if (LocaleCompare(symbol,"n") == 0)
return((double) GetImageListLength(fx_info->images));
break;
}
case 'O':
case 'o':
{
if (LocaleCompare(symbol,"o") == 0)
return(QuantumScale*pixel.opacity);
break;
}
case 'P':
case 'p':
{
if (LocaleCompare(symbol,"page.height") == 0)
return((double) image->page.height);
if (LocaleCompare(symbol,"page.width") == 0)
return((double) image->page.width);
if (LocaleCompare(symbol,"page.x") == 0)
return((double) image->page.x);
if (LocaleCompare(symbol,"page.y") == 0)
return((double) image->page.y);
if (LocaleCompare(symbol,"printsize.x") == 0)
return(PerceptibleReciprocal(image->x_resolution)*image->columns);
if (LocaleCompare(symbol,"printsize.y") == 0)
return(PerceptibleReciprocal(image->y_resolution)*image->rows);
break;
}
case 'Q':
case 'q':
{
if (LocaleCompare(symbol,"quality") == 0)
return((double) image->quality);
break;
}
case 'R':
case 'r':
{
if (LocaleCompare(symbol,"resolution.x") == 0)
return(image->x_resolution);
if (LocaleCompare(symbol,"resolution.y") == 0)
return(image->y_resolution);
if (LocaleCompare(symbol,"r") == 0)
return(QuantumScale*pixel.red);
break;
}
case 'S':
case 's':
{
if (LocaleCompare(symbol,"saturation") == 0)
{
double
hue,
lightness,
saturation;
ConvertRGBToHSL(ClampToQuantum(pixel.red),ClampToQuantum(pixel.green),
ClampToQuantum(pixel.blue),&hue,&saturation,&lightness);
return(saturation);
}
if (LocaleNCompare(symbol,"skewness",8) == 0)
return(FxChannelStatistics(fx_info,image,channel,symbol,exception));
if (LocaleNCompare(symbol,"standard_deviation",18) == 0)
return(FxChannelStatistics(fx_info,image,channel,symbol,exception));
break;
}
case 'T':
case 't':
{
if (LocaleCompare(symbol,"t") == 0)
return((double) GetImageIndexInList(fx_info->images));
break;
}
case 'W':
case 'w':
{
if (LocaleCompare(symbol,"w") == 0)
return((double) image->columns);
break;
}
case 'Y':
case 'y':
{
if (LocaleCompare(symbol,"y") == 0)
return(QuantumScale*pixel.blue);
break;
}
case 'Z':
case 'z':
{
if (LocaleCompare(symbol,"z") == 0)
{
double
depth;
depth=(double) GetImageChannelDepth(image,channel,fx_info->exception);
return(depth);
}
break;
}
default:
break;
}
value=(const char *) GetValueFromSplayTree(fx_info->symbols,symbol);
if (value != (const char *) NULL)
return(StringToDouble(value,(char **) NULL));
(void) ThrowMagickException(exception,GetMagickModule(),OptionError,
"UnableToParseExpression","`%s'",symbol);
return(0.0);
}
static const char *FxOperatorPrecedence(const char *expression,
ExceptionInfo *exception)
{
typedef enum
{
UndefinedPrecedence,
NullPrecedence,
BitwiseComplementPrecedence,
ExponentPrecedence,
ExponentialNotationPrecedence,
MultiplyPrecedence,
AdditionPrecedence,
ShiftPrecedence,
RelationalPrecedence,
EquivalencyPrecedence,
BitwiseAndPrecedence,
BitwiseOrPrecedence,
LogicalAndPrecedence,
LogicalOrPrecedence,
TernaryPrecedence,
AssignmentPrecedence,
CommaPrecedence,
SeparatorPrecedence
} FxPrecedence;
FxPrecedence
precedence,
target;
register const char
*subexpression;
register int
c;
size_t
level;
c=(-1);
level=0;
subexpression=(const char *) NULL;
target=NullPrecedence;
while ((c != '\0') && (*expression != '\0'))
{
precedence=UndefinedPrecedence;
if ((isspace((int) ((unsigned char) *expression)) != 0) || (c == (int) '@'))
{
expression++;
continue;
}
switch (*expression)
{
case 'A':
case 'a':
{
#if defined(MAGICKCORE_HAVE_ACOSH)
if (LocaleNCompare(expression,"acosh",5) == 0)
{
expression+=5;
break;
}
#endif
#if defined(MAGICKCORE_HAVE_ASINH)
if (LocaleNCompare(expression,"asinh",5) == 0)
{
expression+=5;
break;
}
#endif
#if defined(MAGICKCORE_HAVE_ATANH)
if (LocaleNCompare(expression,"atanh",5) == 0)
{
expression+=5;
break;
}
#endif
if (LocaleNCompare(expression,"atan2",5) == 0)
{
expression+=5;
break;
}
break;
}
case 'E':
case 'e':
{
if ((isdigit(c) != 0) &&
((LocaleNCompare(expression,"E+",2) == 0) ||
(LocaleNCompare(expression,"E-",2) == 0)))
{
expression+=2; /* scientific notation */
break;
}
}
case 'J':
case 'j':
{
if ((LocaleNCompare(expression,"j0",2) == 0) ||
(LocaleNCompare(expression,"j1",2) == 0))
{
expression+=2;
break;
}
break;
}
case '#':
{
while (isxdigit((int) ((unsigned char) *(expression+1))) != 0)
expression++;
break;
}
default:
break;
}
if ((c == (int) '{') || (c == (int) '['))
level++;
else
if ((c == (int) '}') || (c == (int) ']'))
level--;
if (level == 0)
switch ((unsigned char) *expression)
{
case '~':
case '!':
{
precedence=BitwiseComplementPrecedence;
break;
}
case '^':
case '@':
{
precedence=ExponentPrecedence;
break;
}
default:
{
if (((c != 0) && ((isdigit(c) != 0) ||
(strchr(")",c) != (char *) NULL))) &&
(((islower((int) ((unsigned char) *expression)) != 0) ||
(strchr("(",(int) ((unsigned char) *expression)) != (char *) NULL)) ||
((isdigit(c) == 0) &&
(isdigit((int) ((unsigned char) *expression)) != 0))) &&
(strchr("xy",(int) ((unsigned char) *expression)) == (char *) NULL))
precedence=MultiplyPrecedence;
break;
}
case '*':
case '/':
case '%':
{
precedence=MultiplyPrecedence;
break;
}
case '+':
case '-':
{
if ((strchr("(+-/*%:&^|<>~,",c) == (char *) NULL) ||
(isalpha(c) != 0))
precedence=AdditionPrecedence;
break;
}
case LeftShiftOperator:
case RightShiftOperator:
{
precedence=ShiftPrecedence;
break;
}
case '<':
case LessThanEqualOperator:
case GreaterThanEqualOperator:
case '>':
{
precedence=RelationalPrecedence;
break;
}
case EqualOperator:
case NotEqualOperator:
{
precedence=EquivalencyPrecedence;
break;
}
case '&':
{
precedence=BitwiseAndPrecedence;
break;
}
case '|':
{
precedence=BitwiseOrPrecedence;
break;
}
case LogicalAndOperator:
{
precedence=LogicalAndPrecedence;
break;
}
case LogicalOrOperator:
{
precedence=LogicalOrPrecedence;
break;
}
case ExponentialNotation:
{
precedence=ExponentialNotationPrecedence;
break;
}
case ':':
case '?':
{
precedence=TernaryPrecedence;
break;
}
case '=':
{
precedence=AssignmentPrecedence;
break;
}
case ',':
{
precedence=CommaPrecedence;
break;
}
case ';':
{
precedence=SeparatorPrecedence;
break;
}
}
if ((precedence == BitwiseComplementPrecedence) ||
(precedence == TernaryPrecedence) ||
(precedence == AssignmentPrecedence))
{
if (precedence > target)
{
/*
Right-to-left associativity.
*/
target=precedence;
subexpression=expression;
}
}
else
if (precedence >= target)
{
/*
Left-to-right associativity.
*/
target=precedence;
subexpression=expression;
}
if (strchr("(",(int) *expression) != (char *) NULL)
expression=FxSubexpression(expression,exception);
c=(int) (*expression++);
}
return(subexpression);
}
static double FxEvaluateSubexpression(FxInfo *fx_info,const ChannelType channel,
const ssize_t x,const ssize_t y,const char *expression,const size_t depth,
double *beta,ExceptionInfo *exception)
{
#define FxMaxParenthesisDepth 58
#define FxMaxSubexpressionDepth 200
#define FxReturn(value) \
{ \
subexpression=DestroyString(subexpression); \
return(value); \
}
char
*q,
*subexpression;
double
alpha,
gamma;
register const char
*p;
*beta=0.0;
subexpression=AcquireString(expression);
*subexpression='\0';
if (depth > FxMaxSubexpressionDepth)
{
(void) ThrowMagickException(exception,GetMagickModule(),OptionError,
"UnableToParseExpression","`%s'",expression);
FxReturn(0.0);
}
if (exception->severity >= ErrorException)
FxReturn(0.0);
while (isspace((int) ((unsigned char) *expression)) != 0)
expression++;
if (*expression == '\0')
FxReturn(0.0);
p=FxOperatorPrecedence(expression,exception);
if (p != (const char *) NULL)
{
(void) CopyMagickString(subexpression,expression,(size_t)
(p-expression+1));
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,subexpression,depth+1,
beta,exception);
switch ((unsigned char) *p)
{
case '~':
{
*beta=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
*beta=(double) (~(size_t) *beta);
FxReturn(*beta);
}
case '!':
{
*beta=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
FxReturn(*beta == 0.0 ? 1.0 : 0.0);
}
case '^':
{
*beta=pow(alpha,FxEvaluateSubexpression(fx_info,channel,x,y,++p,
depth+1,beta,exception));
FxReturn(*beta);
}
case '*':
case ExponentialNotation:
{
*beta=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
FxReturn(alpha*(*beta));
}
case '/':
{
*beta=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
FxReturn(PerceptibleReciprocal(*beta)*alpha);
}
case '%':
{
*beta=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
*beta=fabs(floor((*beta)+0.5));
FxReturn(fmod(alpha,(double) *beta));
}
case '+':
{
*beta=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
FxReturn(alpha+(*beta));
}
case '-':
{
*beta=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
FxReturn(alpha-(*beta));
}
case LeftShiftOperator:
{
gamma=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
if ((size_t) (gamma+0.5) > (8*sizeof(size_t)))
{
(void) ThrowMagickException(exception,GetMagickModule(),
OptionError,"ShiftCountOverflow","`%s'",subexpression);
FxReturn(0.0);
}
*beta=(double) ((size_t) (alpha+0.5) << (size_t) (gamma+0.5));
FxReturn(*beta);
}
case RightShiftOperator:
{
gamma=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
if ((size_t) (gamma+0.5) > (8*sizeof(size_t)))
{
(void) ThrowMagickException(exception,GetMagickModule(),
OptionError,"ShiftCountOverflow","`%s'",subexpression);
FxReturn(0.0);
}
*beta=(double) ((size_t) (alpha+0.5) >> (size_t) (gamma+0.5));
FxReturn(*beta);
}
case '<':
{
*beta=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
FxReturn(alpha < *beta ? 1.0 : 0.0);
}
case LessThanEqualOperator:
{
*beta=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
FxReturn(alpha <= *beta ? 1.0 : 0.0);
}
case '>':
{
*beta=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
FxReturn(alpha > *beta ? 1.0 : 0.0);
}
case GreaterThanEqualOperator:
{
*beta=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
FxReturn(alpha >= *beta ? 1.0 : 0.0);
}
case EqualOperator:
{
*beta=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
FxReturn(fabs(alpha-(*beta)) < MagickEpsilon ? 1.0 : 0.0);
}
case NotEqualOperator:
{
*beta=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
FxReturn(fabs(alpha-(*beta)) >= MagickEpsilon ? 1.0 : 0.0);
}
case '&':
{
gamma=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
*beta=(double) ((size_t) (alpha+0.5) & (size_t) (gamma+0.5));
FxReturn(*beta);
}
case '|':
{
gamma=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
*beta=(double) ((size_t) (alpha+0.5) | (size_t) (gamma+0.5));
FxReturn(*beta);
}
case LogicalAndOperator:
{
p++;
if (alpha <= 0.0)
{
*beta=0.0;
FxReturn(*beta);
}
gamma=FxEvaluateSubexpression(fx_info,channel,x,y,p,depth+1,beta,
exception);
*beta=(gamma > 0.0) ? 1.0 : 0.0;
FxReturn(*beta);
}
case LogicalOrOperator:
{
p++;
if (alpha > 0.0)
{
*beta=1.0;
FxReturn(*beta);
}
gamma=FxEvaluateSubexpression(fx_info,channel,x,y,p,depth+1,beta,
exception);
*beta=(gamma > 0.0) ? 1.0 : 0.0;
FxReturn(*beta);
}
case '?':
{
double
gamma;
(void) CopyMagickString(subexpression,++p,MaxTextExtent);
q=subexpression;
p=StringToken(":",&q);
if (q == (char *) NULL)
{
(void) ThrowMagickException(exception,GetMagickModule(),
OptionError,"UnableToParseExpression","`%s'",subexpression);
FxReturn(0.0);
}
if (fabs(alpha) >= MagickEpsilon)
gamma=FxEvaluateSubexpression(fx_info,channel,x,y,p,depth+1,beta,
exception);
else
gamma=FxEvaluateSubexpression(fx_info,channel,x,y,q,depth+1,beta,
exception);
FxReturn(gamma);
}
case '=':
{
char
numeric[MaxTextExtent];
q=subexpression;
while (isalpha((int) ((unsigned char) *q)) != 0)
q++;
if (*q != '\0')
{
(void) ThrowMagickException(exception,GetMagickModule(),
OptionError,"UnableToParseExpression","`%s'",subexpression);
FxReturn(0.0);
}
ClearMagickException(exception);
*beta=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
(void) FormatLocaleString(numeric,MaxTextExtent,"%.20g",(double)
*beta);
(void) DeleteNodeFromSplayTree(fx_info->symbols,subexpression);
(void) AddValueToSplayTree(fx_info->symbols,ConstantString(
subexpression),ConstantString(numeric));
FxReturn(*beta);
}
case ',':
{
if (fabs(alpha) > MagickEpsilon)
*beta=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
FxReturn(alpha);
}
case ';':
{
*beta=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
FxReturn(*beta);
}
default:
{
gamma=alpha*FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,
beta,exception);
FxReturn(gamma);
}
}
}
if (strchr("(",(int) *expression) != (char *) NULL)
{
if (depth >= FxMaxParenthesisDepth)
(void) ThrowMagickException(exception,GetMagickModule(),OptionError,
"ParenthesisNestedTooDeeply","`%s'",expression);
(void) CopyMagickString(subexpression,expression+1,MaxTextExtent);
if (strlen(subexpression) != 0)
subexpression[strlen(subexpression)-1]='\0';
gamma=FxEvaluateSubexpression(fx_info,channel,x,y,subexpression,depth+1,
beta,exception);
FxReturn(gamma);
}
switch (*expression)
{
case '+':
{
gamma=FxEvaluateSubexpression(fx_info,channel,x,y,expression+1,depth+1,
beta,exception);
FxReturn(1.0*gamma);
}
case '-':
{
gamma=FxEvaluateSubexpression(fx_info,channel,x,y,expression+1,depth+1,
beta,exception);
FxReturn(-1.0*gamma);
}
case '~':
{
gamma=FxEvaluateSubexpression(fx_info,channel,x,y,expression+1,depth+1,
beta,exception);
FxReturn((double) (~(size_t) (gamma+0.5)));
}
case 'A':
case 'a':
{
if (LocaleNCompare(expression,"abs",3) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn(fabs(alpha));
}
#if defined(MAGICKCORE_HAVE_ACOSH)
if (LocaleNCompare(expression,"acosh",5) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
FxReturn(acosh(alpha));
}
#endif
if (LocaleNCompare(expression,"acos",4) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
FxReturn(acos(alpha));
}
#if defined(MAGICKCORE_HAVE_J1)
if (LocaleNCompare(expression,"airy",4) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
if (alpha == 0.0)
FxReturn(1.0);
gamma=2.0*j1((MagickPI*alpha))/(MagickPI*alpha);
FxReturn(gamma*gamma);
}
#endif
#if defined(MAGICKCORE_HAVE_ASINH)
if (LocaleNCompare(expression,"asinh",5) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
FxReturn(asinh(alpha));
}
#endif
if (LocaleNCompare(expression,"asin",4) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
FxReturn(asin(alpha));
}
if (LocaleNCompare(expression,"alt",3) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn(((ssize_t) alpha) & 0x01 ? -1.0 : 1.0);
}
if (LocaleNCompare(expression,"atan2",5) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
FxReturn(atan2(alpha,*beta));
}
#if defined(MAGICKCORE_HAVE_ATANH)
if (LocaleNCompare(expression,"atanh",5) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
FxReturn(atanh(alpha));
}
#endif
if (LocaleNCompare(expression,"atan",4) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
FxReturn(atan(alpha));
}
if (LocaleCompare(expression,"a") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
case 'B':
case 'b':
{
if (LocaleCompare(expression,"b") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
case 'C':
case 'c':
{
if (LocaleNCompare(expression,"ceil",4) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
FxReturn(ceil(alpha));
}
if (LocaleNCompare(expression,"clamp",5) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
if (alpha < 0.0)
FxReturn(0.0);
if (alpha > 1.0)
FxReturn(1.0);
FxReturn(alpha);
}
if (LocaleNCompare(expression,"cosh",4) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
FxReturn(cosh(alpha));
}
if (LocaleNCompare(expression,"cos",3) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn(cos(alpha));
}
if (LocaleCompare(expression,"c") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
case 'D':
case 'd':
{
if (LocaleNCompare(expression,"debug",5) == 0)
{
const char
*type;
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
if (fx_info->images->colorspace == CMYKColorspace)
switch (channel)
{
case CyanChannel: type="cyan"; break;
case MagentaChannel: type="magenta"; break;
case YellowChannel: type="yellow"; break;
case OpacityChannel: type="opacity"; break;
case BlackChannel: type="black"; break;
default: type="unknown"; break;
}
else
switch (channel)
{
case RedChannel: type="red"; break;
case GreenChannel: type="green"; break;
case BlueChannel: type="blue"; break;
case OpacityChannel: type="opacity"; break;
default: type="unknown"; break;
}
*subexpression='\0';
if (strlen(subexpression) > 1)
(void) CopyMagickString(subexpression,expression+6,MaxTextExtent);
if (strlen(subexpression) > 1)
subexpression[strlen(subexpression)-1]='\0';
if (fx_info->file != (FILE *) NULL)
(void) FormatLocaleFile(fx_info->file,
"%s[%.20g,%.20g].%s: %s=%.*g\n",fx_info->images->filename,
(double) x,(double) y,type,subexpression,GetMagickPrecision(),
(double) alpha);
FxReturn(0.0);
}
if (LocaleNCompare(expression,"drc",3) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn((alpha/(*beta*(alpha-1.0)+1.0)));
}
break;
}
case 'E':
case 'e':
{
if (LocaleCompare(expression,"epsilon") == 0)
FxReturn(MagickEpsilon);
#if defined(MAGICKCORE_HAVE_ERF)
if (LocaleNCompare(expression,"erp",3) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn(erf(alpha));
}
#endif
if (LocaleNCompare(expression,"exp",3) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn(exp(alpha));
}
if (LocaleCompare(expression,"e") == 0)
FxReturn(2.7182818284590452354);
break;
}
case 'F':
case 'f':
{
if (LocaleNCompare(expression,"floor",5) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
FxReturn(floor(alpha));
}
break;
}
case 'G':
case 'g':
{
if (LocaleNCompare(expression,"gauss",5) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
gamma=exp((-alpha*alpha/2.0))/sqrt(2.0*MagickPI);
FxReturn(gamma);
}
if (LocaleNCompare(expression,"gcd",3) == 0)
{
MagickOffsetType
gcd;
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
gcd=FxGCD((MagickOffsetType) (alpha+0.5),(MagickOffsetType)
(*beta+0.5));
FxReturn((double) gcd);
}
if (LocaleCompare(expression,"g") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
case 'H':
case 'h':
{
if (LocaleCompare(expression,"h") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
if (LocaleCompare(expression,"hue") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
if (LocaleNCompare(expression,"hypot",5) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
FxReturn(hypot(alpha,*beta));
}
break;
}
case 'K':
case 'k':
{
if (LocaleCompare(expression,"k") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
case 'I':
case 'i':
{
if (LocaleCompare(expression,"intensity") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
if (LocaleNCompare(expression,"int",3) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn(floor(alpha));
}
if (LocaleNCompare(expression,"isnan",5) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
FxReturn((double) !!IsNaN(alpha));
}
if (LocaleCompare(expression,"i") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
case 'J':
case 'j':
{
if (LocaleCompare(expression,"j") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
#if defined(MAGICKCORE_HAVE_J0)
if (LocaleNCompare(expression,"j0",2) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+2,
depth+1,beta,exception);
FxReturn(j0(alpha));
}
#endif
#if defined(MAGICKCORE_HAVE_J1)
if (LocaleNCompare(expression,"j1",2) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+2,
depth+1,beta,exception);
FxReturn(j1(alpha));
}
#endif
#if defined(MAGICKCORE_HAVE_J1)
if (LocaleNCompare(expression,"jinc",4) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
if (alpha == 0.0)
FxReturn(1.0);
gamma=(2.0*j1((MagickPI*alpha))/(MagickPI*alpha));
FxReturn(gamma);
}
#endif
break;
}
case 'L':
case 'l':
{
if (LocaleNCompare(expression,"ln",2) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+2,
depth+1,beta,exception);
FxReturn(log(alpha));
}
if (LocaleNCompare(expression,"logtwo",6) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+6,
depth+1,beta,exception);
FxReturn(log10(alpha)/log10(2.0));
}
if (LocaleNCompare(expression,"log",3) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn(log10(alpha));
}
if (LocaleCompare(expression,"lightness") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
case 'M':
case 'm':
{
if (LocaleCompare(expression,"MaxRGB") == 0)
FxReturn((double) QuantumRange);
if (LocaleNCompare(expression,"maxima",6) == 0)
break;
if (LocaleNCompare(expression,"max",3) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn(alpha > *beta ? alpha : *beta);
}
if (LocaleNCompare(expression,"minima",6) == 0)
break;
if (LocaleNCompare(expression,"min",3) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn(alpha < *beta ? alpha : *beta);
}
if (LocaleNCompare(expression,"mod",3) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
gamma=alpha-floor((alpha*PerceptibleReciprocal(*beta)))*(*beta);
FxReturn(gamma);
}
if (LocaleCompare(expression,"m") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
case 'N':
case 'n':
{
if (LocaleNCompare(expression,"not",3) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn((double) (alpha < MagickEpsilon));
}
if (LocaleCompare(expression,"n") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
case 'O':
case 'o':
{
if (LocaleCompare(expression,"Opaque") == 0)
FxReturn(1.0);
if (LocaleCompare(expression,"o") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
case 'P':
case 'p':
{
if (LocaleCompare(expression,"phi") == 0)
FxReturn(MagickPHI);
if (LocaleCompare(expression,"pi") == 0)
FxReturn(MagickPI);
if (LocaleNCompare(expression,"pow",3) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn(pow(alpha,*beta));
}
if (LocaleCompare(expression,"p") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
case 'Q':
case 'q':
{
if (LocaleCompare(expression,"QuantumRange") == 0)
FxReturn((double) QuantumRange);
if (LocaleCompare(expression,"QuantumScale") == 0)
FxReturn(QuantumScale);
break;
}
case 'R':
case 'r':
{
if (LocaleNCompare(expression,"rand",4) == 0)
{
double
alpha;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_FxEvaluateSubexpression)
#endif
alpha=GetPseudoRandomValue(fx_info->random_info);
FxReturn(alpha);
}
if (LocaleNCompare(expression,"round",5) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
FxReturn(floor(alpha+0.5));
}
if (LocaleCompare(expression,"r") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
case 'S':
case 's':
{
if (LocaleCompare(expression,"saturation") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
if (LocaleNCompare(expression,"sign",4) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
FxReturn(alpha < 0.0 ? -1.0 : 1.0);
}
if (LocaleNCompare(expression,"sinc",4) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
if (alpha == 0)
FxReturn(1.0);
gamma=(sin((MagickPI*alpha))/(MagickPI*alpha));
FxReturn(gamma);
}
if (LocaleNCompare(expression,"sinh",4) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
FxReturn(sinh(alpha));
}
if (LocaleNCompare(expression,"sin",3) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn(sin(alpha));
}
if (LocaleNCompare(expression,"sqrt",4) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
FxReturn(sqrt(alpha));
}
if (LocaleNCompare(expression,"squish",6) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+6,
depth+1,beta,exception);
FxReturn((1.0/(1.0+exp(-alpha))));
}
if (LocaleCompare(expression,"s") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
case 'T':
case 't':
{
if (LocaleNCompare(expression,"tanh",4) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
FxReturn(tanh(alpha));
}
if (LocaleNCompare(expression,"tan",3) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn(tan(alpha));
}
if (LocaleCompare(expression,"Transparent") == 0)
FxReturn(0.0);
if (LocaleNCompare(expression,"trunc",5) == 0)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
if (alpha >= 0.0)
FxReturn(floor(alpha));
FxReturn(ceil(alpha));
}
if (LocaleCompare(expression,"t") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
case 'U':
case 'u':
{
if (LocaleCompare(expression,"u") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
case 'V':
case 'v':
{
if (LocaleCompare(expression,"v") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
case 'W':
case 'w':
{
if (LocaleNCompare(expression,"while",5) == 0)
{
do
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
} while (fabs(alpha) >= MagickEpsilon);
FxReturn(*beta);
}
if (LocaleCompare(expression,"w") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
case 'Y':
case 'y':
{
if (LocaleCompare(expression,"y") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
case 'Z':
case 'z':
{
if (LocaleCompare(expression,"z") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
default:
break;
}
q=(char *) expression;
alpha=InterpretSiPrefixValue(expression,&q);
if (q == expression)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
FxReturn(alpha);
}
MagickExport MagickBooleanType FxEvaluateExpression(FxInfo *fx_info,
double *alpha,ExceptionInfo *exception)
{
MagickBooleanType
status;
status=FxEvaluateChannelExpression(fx_info,GrayChannel,0,0,alpha,exception);
return(status);
}
MagickExport MagickBooleanType FxPreprocessExpression(FxInfo *fx_info,
double *alpha,ExceptionInfo *exception)
{
FILE
*file;
MagickBooleanType
status;
file=fx_info->file;
fx_info->file=(FILE *) NULL;
status=FxEvaluateChannelExpression(fx_info,GrayChannel,0,0,alpha,exception);
fx_info->file=file;
return(status);
}
MagickExport MagickBooleanType FxEvaluateChannelExpression(FxInfo *fx_info,
const ChannelType channel,const ssize_t x,const ssize_t y,double *alpha,
ExceptionInfo *exception)
{
double
beta;
beta=0.0;
*alpha=FxEvaluateSubexpression(fx_info,channel,x,y,fx_info->expression,0,
&beta,exception);
return(exception->severity == OptionError ? MagickFalse : MagickTrue);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% F x I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FxImage() applies a mathematical expression to the specified image.
%
% The format of the FxImage method is:
%
% Image *FxImage(const Image *image,const char *expression,
% ExceptionInfo *exception)
% Image *FxImageChannel(const Image *image,const ChannelType channel,
% const char *expression,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o channel: the channel.
%
% o expression: A mathematical expression.
%
% o exception: return any errors or warnings in this structure.
%
*/
static FxInfo **DestroyFxThreadSet(FxInfo **fx_info)
{
register ssize_t
i;
assert(fx_info != (FxInfo **) NULL);
for (i=0; i < (ssize_t) GetMagickResourceLimit(ThreadResource); i++)
if (fx_info[i] != (FxInfo *) NULL)
fx_info[i]=DestroyFxInfo(fx_info[i]);
fx_info=(FxInfo **) RelinquishMagickMemory(fx_info);
return(fx_info);
}
static FxInfo **AcquireFxThreadSet(const Image *image,const char *expression,
ExceptionInfo *exception)
{
char
*fx_expression;
double
alpha;
FxInfo
**fx_info;
register ssize_t
i;
size_t
number_threads;
number_threads=(size_t) GetMagickResourceLimit(ThreadResource);
fx_info=(FxInfo **) AcquireQuantumMemory(number_threads,sizeof(*fx_info));
if (fx_info == (FxInfo **) NULL)
{
(void) ThrowMagickException(exception,GetMagickModule(),
ResourceLimitError,"MemoryAllocationFailed","`%s'",image->filename);
return((FxInfo **) NULL);
}
(void) memset(fx_info,0,number_threads*sizeof(*fx_info));
if (*expression != '@')
fx_expression=ConstantString(expression);
else
fx_expression=FileToString(expression+1,~0UL,exception);
for (i=0; i < (ssize_t) number_threads; i++)
{
MagickBooleanType
status;
fx_info[i]=AcquireFxInfo(image,fx_expression);
if (fx_info[i] == (FxInfo *) NULL)
break;
status=FxPreprocessExpression(fx_info[i],&alpha,exception);
if (status == MagickFalse)
break;
}
fx_expression=DestroyString(fx_expression);
if (i < (ssize_t) number_threads)
fx_info=DestroyFxThreadSet(fx_info);
return(fx_info);
}
MagickExport Image *FxImage(const Image *image,const char *expression,
ExceptionInfo *exception)
{
Image
*fx_image;
fx_image=FxImageChannel(image,GrayChannel,expression,exception);
return(fx_image);
}
MagickExport Image *FxImageChannel(const Image *image,const ChannelType channel,
const char *expression,ExceptionInfo *exception)
{
#define FxImageTag "Fx/Image"
CacheView
*fx_view;
FxInfo
**magick_restrict fx_info;
Image
*fx_image;
MagickBooleanType
status;
MagickOffsetType
progress;
ssize_t
y;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if (expression == (const char *) NULL)
return(CloneImage(image,0,0,MagickTrue,exception));
fx_info=AcquireFxThreadSet(image,expression,exception);
if (fx_info == (FxInfo **) NULL)
return((Image *) NULL);
fx_image=CloneImage(image,0,0,MagickTrue,exception);
if (fx_image == (Image *) NULL)
{
fx_info=DestroyFxThreadSet(fx_info);
return((Image *) NULL);
}
if (SetImageStorageClass(fx_image,DirectClass) == MagickFalse)
{
InheritException(exception,&fx_image->exception);
fx_info=DestroyFxThreadSet(fx_info);
fx_image=DestroyImage(fx_image);
return((Image *) NULL);
}
/*
Fx image.
*/
status=MagickTrue;
progress=0;
fx_view=AcquireAuthenticCacheView(fx_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,fx_image,fx_image->rows,1)
#endif
for (y=0; y < (ssize_t) fx_image->rows; y++)
{
const int
id = GetOpenMPThreadId();
double
alpha;
register IndexPacket
*magick_restrict fx_indexes;
register ssize_t
x;
register PixelPacket
*magick_restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(fx_view,0,y,fx_image->columns,1,exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
fx_indexes=GetCacheViewAuthenticIndexQueue(fx_view);
alpha=0.0;
for (x=0; x < (ssize_t) fx_image->columns; x++)
{
if ((channel & RedChannel) != 0)
{
(void) FxEvaluateChannelExpression(fx_info[id],RedChannel,x,y,
&alpha,exception);
SetPixelRed(q,ClampToQuantum((MagickRealType) QuantumRange*alpha));
}
if ((channel & GreenChannel) != 0)
{
(void) FxEvaluateChannelExpression(fx_info[id],GreenChannel,x,y,
&alpha,exception);
SetPixelGreen(q,ClampToQuantum((MagickRealType) QuantumRange*alpha));
}
if ((channel & BlueChannel) != 0)
{
(void) FxEvaluateChannelExpression(fx_info[id],BlueChannel,x,y,
&alpha,exception);
SetPixelBlue(q,ClampToQuantum((MagickRealType) QuantumRange*alpha));
}
if ((channel & OpacityChannel) != 0)
{
(void) FxEvaluateChannelExpression(fx_info[id],OpacityChannel,x,y,
&alpha,exception);
if (image->matte == MagickFalse)
SetPixelOpacity(q,ClampToQuantum((MagickRealType) QuantumRange*
alpha));
else
SetPixelOpacity(q,ClampToQuantum((MagickRealType) (QuantumRange-
QuantumRange*alpha)));
}
if (((channel & IndexChannel) != 0) &&
(fx_image->colorspace == CMYKColorspace))
{
(void) FxEvaluateChannelExpression(fx_info[id],IndexChannel,x,y,
&alpha,exception);
SetPixelIndex(fx_indexes+x,ClampToQuantum((MagickRealType)
QuantumRange*alpha));
}
q++;
}
if (SyncCacheViewAuthenticPixels(fx_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(image,FxImageTag,progress,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
fx_view=DestroyCacheView(fx_view);
fx_info=DestroyFxThreadSet(fx_info);
if (status == MagickFalse)
fx_image=DestroyImage(fx_image);
return(fx_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% I m p l o d e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ImplodeImage() creates a new image that is a copy of an existing
% one with the image pixels "implode" by the specified percentage. It
% allocates the memory necessary for the new Image structure and returns a
% pointer to the new image.
%
% The format of the ImplodeImage method is:
%
% Image *ImplodeImage(const Image *image,const double amount,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o implode_image: Method ImplodeImage returns a pointer to the image
% after it is implode. A null image is returned if there is a memory
% shortage.
%
% o image: the image.
%
% o amount: Define the extent of the implosion.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *ImplodeImage(const Image *image,const double amount,
ExceptionInfo *exception)
{
#define ImplodeImageTag "Implode/Image"
CacheView
*image_view,
*implode_view;
double
radius;
Image
*implode_image;
MagickBooleanType
status;
MagickOffsetType
progress;
MagickPixelPacket
zero;
PointInfo
center,
scale;
ssize_t
y;
/*
Initialize implode image attributes.
*/
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
implode_image=CloneImage(image,0,0,MagickTrue,exception);
if (implode_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(implode_image,DirectClass) == MagickFalse)
{
InheritException(exception,&implode_image->exception);
implode_image=DestroyImage(implode_image);
return((Image *) NULL);
}
if (implode_image->background_color.opacity != OpaqueOpacity)
implode_image->matte=MagickTrue;
/*
Compute scaling factor.
*/
scale.x=1.0;
scale.y=1.0;
center.x=0.5*image->columns;
center.y=0.5*image->rows;
radius=center.x;
if (image->columns > image->rows)
scale.y=(double) image->columns/(double) image->rows;
else
if (image->columns < image->rows)
{
scale.x=(double) image->rows/(double) image->columns;
radius=center.y;
}
/*
Implode image.
*/
status=MagickTrue;
progress=0;
GetMagickPixelPacket(implode_image,&zero);
image_view=AcquireVirtualCacheView(image,exception);
implode_view=AcquireAuthenticCacheView(implode_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,implode_image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
double
distance;
MagickPixelPacket
pixel;
PointInfo
delta;
register IndexPacket
*magick_restrict implode_indexes;
register ssize_t
x;
register PixelPacket
*magick_restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(implode_view,0,y,implode_image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
implode_indexes=GetCacheViewAuthenticIndexQueue(implode_view);
delta.y=scale.y*(double) (y-center.y);
pixel=zero;
for (x=0; x < (ssize_t) image->columns; x++)
{
/*
Determine if the pixel is within an ellipse.
*/
delta.x=scale.x*(double) (x-center.x);
distance=delta.x*delta.x+delta.y*delta.y;
if (distance < (radius*radius))
{
double
factor;
/*
Implode the pixel.
*/
factor=1.0;
if (distance > 0.0)
factor=pow(sin((double) (MagickPI*sqrt((double) distance)/
radius/2)),-amount);
status=InterpolateMagickPixelPacket(image,image_view,
UndefinedInterpolatePixel,(double) (factor*delta.x/scale.x+
center.x),(double) (factor*delta.y/scale.y+center.y),&pixel,
exception);
if (status == MagickFalse)
break;
SetPixelPacket(implode_image,&pixel,q,implode_indexes+x);
}
q++;
}
if (SyncCacheViewAuthenticPixels(implode_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(image,ImplodeImageTag,progress,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
implode_view=DestroyCacheView(implode_view);
image_view=DestroyCacheView(image_view);
if (status == MagickFalse)
implode_image=DestroyImage(implode_image);
return(implode_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% M o r p h I m a g e s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% The MorphImages() method requires a minimum of two images. The first
% image is transformed into the second by a number of intervening images
% as specified by frames.
%
% The format of the MorphImage method is:
%
% Image *MorphImages(const Image *image,const size_t number_frames,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o number_frames: Define the number of in-between image to generate.
% The more in-between frames, the smoother the morph.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *MorphImages(const Image *image,
const size_t number_frames,ExceptionInfo *exception)
{
#define MorphImageTag "Morph/Image"
double
alpha,
beta;
Image
*morph_image,
*morph_images;
MagickBooleanType
status;
MagickOffsetType
scene;
register const Image
*next;
register ssize_t
i;
ssize_t
y;
/*
Clone first frame in sequence.
*/
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
morph_images=CloneImage(image,0,0,MagickTrue,exception);
if (morph_images == (Image *) NULL)
return((Image *) NULL);
if (GetNextImageInList(image) == (Image *) NULL)
{
/*
Morph single image.
*/
for (i=1; i < (ssize_t) number_frames; i++)
{
morph_image=CloneImage(image,0,0,MagickTrue,exception);
if (morph_image == (Image *) NULL)
{
morph_images=DestroyImageList(morph_images);
return((Image *) NULL);
}
AppendImageToList(&morph_images,morph_image);
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
proceed=SetImageProgress(image,MorphImageTag,(MagickOffsetType) i,
number_frames);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
return(GetFirstImageInList(morph_images));
}
/*
Morph image sequence.
*/
status=MagickTrue;
scene=0;
next=image;
for ( ; GetNextImageInList(next) != (Image *) NULL; next=GetNextImageInList(next))
{
for (i=0; i < (ssize_t) number_frames; i++)
{
CacheView
*image_view,
*morph_view;
beta=(double) (i+1.0)/(double) (number_frames+1.0);
alpha=1.0-beta;
morph_image=ResizeImage(next,(size_t) (alpha*next->columns+beta*
GetNextImageInList(next)->columns+0.5),(size_t) (alpha*
next->rows+beta*GetNextImageInList(next)->rows+0.5),
next->filter,next->blur,exception);
if (morph_image == (Image *) NULL)
{
morph_images=DestroyImageList(morph_images);
return((Image *) NULL);
}
if (SetImageStorageClass(morph_image,DirectClass) == MagickFalse)
{
InheritException(exception,&morph_image->exception);
morph_image=DestroyImage(morph_image);
return((Image *) NULL);
}
AppendImageToList(&morph_images,morph_image);
morph_images=GetLastImageInList(morph_images);
morph_image=ResizeImage(GetNextImageInList(next),morph_images->columns,
morph_images->rows,GetNextImageInList(next)->filter,
GetNextImageInList(next)->blur,exception);
if (morph_image == (Image *) NULL)
{
morph_images=DestroyImageList(morph_images);
return((Image *) NULL);
}
image_view=AcquireVirtualCacheView(morph_image,exception);
morph_view=AcquireAuthenticCacheView(morph_images,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(status) \
magick_number_threads(morph_image,morph_image,morph_image->rows,1)
#endif
for (y=0; y < (ssize_t) morph_images->rows; y++)
{
MagickBooleanType
sync;
register const PixelPacket
*magick_restrict p;
register ssize_t
x;
register PixelPacket
*magick_restrict q;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,morph_image->columns,1,
exception);
q=GetCacheViewAuthenticPixels(morph_view,0,y,morph_images->columns,1,
exception);
if ((p == (const PixelPacket *) NULL) || (q == (PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) morph_images->columns; x++)
{
SetPixelRed(q,ClampToQuantum(alpha*
GetPixelRed(q)+beta*GetPixelRed(p)));
SetPixelGreen(q,ClampToQuantum(alpha*
GetPixelGreen(q)+beta*GetPixelGreen(p)));
SetPixelBlue(q,ClampToQuantum(alpha*
GetPixelBlue(q)+beta*GetPixelBlue(p)));
SetPixelOpacity(q,ClampToQuantum(alpha*
GetPixelOpacity(q)+beta*GetPixelOpacity(p)));
p++;
q++;
}
sync=SyncCacheViewAuthenticPixels(morph_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
morph_view=DestroyCacheView(morph_view);
image_view=DestroyCacheView(image_view);
morph_image=DestroyImage(morph_image);
}
if (i < (ssize_t) number_frames)
break;
/*
Clone last frame in sequence.
*/
morph_image=CloneImage(GetNextImageInList(next),0,0,MagickTrue,exception);
if (morph_image == (Image *) NULL)
{
morph_images=DestroyImageList(morph_images);
return((Image *) NULL);
}
AppendImageToList(&morph_images,morph_image);
morph_images=GetLastImageInList(morph_images);
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
proceed=SetImageProgress(image,MorphImageTag,scene,
GetImageListLength(image));
if (proceed == MagickFalse)
status=MagickFalse;
}
scene++;
}
if (GetNextImageInList(next) != (Image *) NULL)
{
morph_images=DestroyImageList(morph_images);
return((Image *) NULL);
}
return(GetFirstImageInList(morph_images));
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% P l a s m a I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% PlasmaImage() initializes an image with plasma fractal values. The image
% must be initialized with a base color and the random number generator
% seeded before this method is called.
%
% The format of the PlasmaImage method is:
%
% MagickBooleanType PlasmaImage(Image *image,const SegmentInfo *segment,
% size_t attenuate,size_t depth)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o segment: Define the region to apply plasma fractals values.
%
% o attenuate: Define the plasma attenuation factor.
%
% o depth: Limit the plasma recursion depth.
%
*/
static inline Quantum PlasmaPixel(RandomInfo *random_info,
const MagickRealType pixel,const double noise)
{
Quantum
plasma;
plasma=ClampToQuantum(pixel+noise*GetPseudoRandomValue(random_info)-
noise/2.0);
if (plasma <= 0)
return((Quantum) 0);
if (plasma >= QuantumRange)
return(QuantumRange);
return(plasma);
}
MagickExport MagickBooleanType PlasmaImageProxy(Image *image,
CacheView *image_view,CacheView *u_view,CacheView *v_view,
RandomInfo *random_info,const SegmentInfo *segment,size_t attenuate,
size_t depth)
{
ExceptionInfo
*exception;
double
plasma;
PixelPacket
u,
v;
ssize_t
x,
x_mid,
y,
y_mid;
if ((fabs(segment->x2-segment->x1) <= MagickEpsilon) &&
(fabs(segment->y2-segment->y1) <= MagickEpsilon))
return(MagickTrue);
if (depth != 0)
{
MagickBooleanType
status;
SegmentInfo
local_info;
/*
Divide the area into quadrants and recurse.
*/
depth--;
attenuate++;
x_mid=(ssize_t) ceil((segment->x1+segment->x2)/2-0.5);
y_mid=(ssize_t) ceil((segment->y1+segment->y2)/2-0.5);
local_info=(*segment);
local_info.x2=(double) x_mid;
local_info.y2=(double) y_mid;
(void) PlasmaImageProxy(image,image_view,u_view,v_view,random_info,
&local_info,attenuate,depth);
local_info=(*segment);
local_info.y1=(double) y_mid;
local_info.x2=(double) x_mid;
(void) PlasmaImageProxy(image,image_view,u_view,v_view,random_info,
&local_info,attenuate,depth);
local_info=(*segment);
local_info.x1=(double) x_mid;
local_info.y2=(double) y_mid;
(void) PlasmaImageProxy(image,image_view,u_view,v_view,random_info,
&local_info,attenuate,depth);
local_info=(*segment);
local_info.x1=(double) x_mid;
local_info.y1=(double) y_mid;
status=PlasmaImageProxy(image,image_view,u_view,v_view,random_info,
&local_info,attenuate,depth);
return(status);
}
x_mid=(ssize_t) ceil((segment->x1+segment->x2)/2-0.5);
y_mid=(ssize_t) ceil((segment->y1+segment->y2)/2-0.5);
if ((fabs(segment->x1-x_mid) < MagickEpsilon) &&
(fabs(segment->x2-x_mid) < MagickEpsilon) &&
(fabs(segment->y1-y_mid) < MagickEpsilon) &&
(fabs(segment->y2-y_mid) < MagickEpsilon))
return(MagickFalse);
/*
Average pixels and apply plasma.
*/
exception=(&image->exception);
plasma=(double) QuantumRange/(2.0*attenuate);
if ((fabs(segment->x1-x_mid) > MagickEpsilon) ||
(fabs(segment->x2-x_mid) > MagickEpsilon))
{
register PixelPacket
*magick_restrict q;
/*
Left pixel.
*/
x=(ssize_t) ceil(segment->x1-0.5);
(void) GetOneCacheViewVirtualPixel(u_view,x,(ssize_t)
ceil(segment->y1-0.5),&u,exception);
(void) GetOneCacheViewVirtualPixel(v_view,x,(ssize_t)
ceil(segment->y2-0.5),&v,exception);
q=QueueCacheViewAuthenticPixels(image_view,x,y_mid,1,1,exception);
if (q == (PixelPacket *) NULL)
return(MagickTrue);
SetPixelRed(q,PlasmaPixel(random_info,(MagickRealType) (u.red+v.red)/2.0,
plasma));
SetPixelGreen(q,PlasmaPixel(random_info,(MagickRealType) (u.green+
v.green)/2.0,plasma));
SetPixelBlue(q,PlasmaPixel(random_info,(MagickRealType) (u.blue+v.blue)/
2.0,plasma));
(void) SyncCacheViewAuthenticPixels(image_view,exception);
if (fabs(segment->x1-segment->x2) > MagickEpsilon)
{
/*
Right pixel.
*/
x=(ssize_t) ceil(segment->x2-0.5);
(void) GetOneCacheViewVirtualPixel(u_view,x,(ssize_t)
ceil(segment->y1-0.5),&u,exception);
(void) GetOneCacheViewVirtualPixel(v_view,x,(ssize_t)
ceil(segment->y2-0.5),&v,exception);
q=QueueCacheViewAuthenticPixels(image_view,x,y_mid,1,1,exception);
if (q == (PixelPacket *) NULL)
return(MagickTrue);
SetPixelRed(q,PlasmaPixel(random_info,(MagickRealType) (u.red+v.red)/
2.0,plasma));
SetPixelGreen(q,PlasmaPixel(random_info,(MagickRealType) (u.green+
v.green)/2.0,plasma));
SetPixelBlue(q,PlasmaPixel(random_info,(MagickRealType) (u.blue+
v.blue)/2.0,plasma));
(void) SyncCacheViewAuthenticPixels(image_view,exception);
}
}
if ((fabs(segment->y1-y_mid) > MagickEpsilon) ||
(fabs(segment->y2-y_mid) > MagickEpsilon))
{
if ((fabs(segment->x1-x_mid) > MagickEpsilon) ||
(fabs(segment->y2-y_mid) > MagickEpsilon))
{
register PixelPacket
*magick_restrict q;
/*
Bottom pixel.
*/
y=(ssize_t) ceil(segment->y2-0.5);
(void) GetOneCacheViewVirtualPixel(u_view,(ssize_t)
ceil(segment->x1-0.5),y,&u,exception);
(void) GetOneCacheViewVirtualPixel(v_view,(ssize_t)
ceil(segment->x2-0.5),y,&v,exception);
q=QueueCacheViewAuthenticPixels(image_view,x_mid,y,1,1,exception);
if (q == (PixelPacket *) NULL)
return(MagickTrue);
SetPixelRed(q,PlasmaPixel(random_info,(MagickRealType) (u.red+v.red)/
2.0,plasma));
SetPixelGreen(q,PlasmaPixel(random_info,(MagickRealType) (u.green+
v.green)/2.0,plasma));
SetPixelBlue(q,PlasmaPixel(random_info,(MagickRealType) (u.blue+
v.blue)/2.0,plasma));
(void) SyncCacheViewAuthenticPixels(image_view,exception);
}
if (fabs(segment->y1-segment->y2) > MagickEpsilon)
{
register PixelPacket
*magick_restrict q;
/*
Top pixel.
*/
y=(ssize_t) ceil(segment->y1-0.5);
(void) GetOneCacheViewVirtualPixel(u_view,(ssize_t)
ceil(segment->x1-0.5),y,&u,exception);
(void) GetOneCacheViewVirtualPixel(v_view,(ssize_t)
ceil(segment->x2-0.5),y,&v,exception);
q=QueueCacheViewAuthenticPixels(image_view,x_mid,y,1,1,exception);
if (q == (PixelPacket *) NULL)
return(MagickTrue);
SetPixelRed(q,PlasmaPixel(random_info,(MagickRealType) (u.red+
v.red)/2.0,plasma));
SetPixelGreen(q,PlasmaPixel(random_info,(MagickRealType) (u.green+
v.green)/2.0,plasma));
SetPixelBlue(q,PlasmaPixel(random_info,(MagickRealType) (u.blue+
v.blue)/2.0,plasma));
(void) SyncCacheViewAuthenticPixels(image_view,exception);
}
}
if ((fabs(segment->x1-segment->x2) > MagickEpsilon) ||
(fabs(segment->y1-segment->y2) > MagickEpsilon))
{
register PixelPacket
*magick_restrict q;
/*
Middle pixel.
*/
x=(ssize_t) ceil(segment->x1-0.5);
y=(ssize_t) ceil(segment->y1-0.5);
(void) GetOneCacheViewVirtualPixel(u_view,x,y,&u,exception);
x=(ssize_t) ceil(segment->x2-0.5);
y=(ssize_t) ceil(segment->y2-0.5);
(void) GetOneCacheViewVirtualPixel(v_view,x,y,&v,exception);
q=QueueCacheViewAuthenticPixels(image_view,x_mid,y_mid,1,1,exception);
if (q == (PixelPacket *) NULL)
return(MagickTrue);
SetPixelRed(q,PlasmaPixel(random_info,(MagickRealType) (u.red+v.red)/2.0,
plasma));
SetPixelGreen(q,PlasmaPixel(random_info,(MagickRealType) (u.green+
v.green)/2.0,plasma));
SetPixelBlue(q,PlasmaPixel(random_info,(MagickRealType) (u.blue+v.blue)/
2.0,plasma));
(void) SyncCacheViewAuthenticPixels(image_view,exception);
}
if ((fabs(segment->x2-segment->x1) < 3.0) &&
(fabs(segment->y2-segment->y1) < 3.0))
return(MagickTrue);
return(MagickFalse);
}
MagickExport MagickBooleanType PlasmaImage(Image *image,
const SegmentInfo *segment,size_t attenuate,size_t depth)
{
CacheView
*image_view,
*u_view,
*v_view;
MagickBooleanType
status;
RandomInfo
*random_info;
assert(image != (Image *) NULL);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"...");
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"...");
if (SetImageStorageClass(image,DirectClass) == MagickFalse)
return(MagickFalse);
image_view=AcquireAuthenticCacheView(image,&image->exception);
u_view=AcquireVirtualCacheView(image,&image->exception);
v_view=AcquireVirtualCacheView(image,&image->exception);
random_info=AcquireRandomInfo();
status=PlasmaImageProxy(image,image_view,u_view,v_view,random_info,segment,
attenuate,depth);
random_info=DestroyRandomInfo(random_info);
v_view=DestroyCacheView(v_view);
u_view=DestroyCacheView(u_view);
image_view=DestroyCacheView(image_view);
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% P o l a r o i d I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% PolaroidImage() simulates a Polaroid picture.
%
% The format of the AnnotateImage method is:
%
% Image *PolaroidImage(const Image *image,const DrawInfo *draw_info,
% const double angle,ExceptionInfo exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o draw_info: the draw info.
%
% o angle: Apply the effect along this angle.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *PolaroidImage(const Image *image,const DrawInfo *draw_info,
const double angle,ExceptionInfo *exception)
{
const char
*value;
Image
*bend_image,
*caption_image,
*flop_image,
*picture_image,
*polaroid_image,
*rotate_image,
*trim_image;
size_t
height;
ssize_t
quantum;
/*
Simulate a Polaroid picture.
*/
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
quantum=(ssize_t) MagickMax(MagickMax((double) image->columns,(double)
image->rows)/25.0,10.0);
height=image->rows+2*quantum;
caption_image=(Image *) NULL;
value=GetImageProperty(image,"Caption");
if (value != (const char *) NULL)
{
char
*caption;
/*
Generate caption image.
*/
caption_image=CloneImage(image,image->columns,1,MagickTrue,exception);
if (caption_image == (Image *) NULL)
return((Image *) NULL);
caption=InterpretImageProperties((ImageInfo *) NULL,(Image *) image,
value);
if (caption != (char *) NULL)
{
char
geometry[MaxTextExtent];
DrawInfo
*annotate_info;
MagickBooleanType
status;
ssize_t
count;
TypeMetric
metrics;
annotate_info=CloneDrawInfo((const ImageInfo *) NULL,draw_info);
(void) CloneString(&annotate_info->text,caption);
count=FormatMagickCaption(caption_image,annotate_info,MagickTrue,
&metrics,&caption);
status=SetImageExtent(caption_image,image->columns,(size_t)
((count+1)*(metrics.ascent-metrics.descent)+0.5));
if (status == MagickFalse)
caption_image=DestroyImage(caption_image);
else
{
caption_image->background_color=image->border_color;
(void) SetImageBackgroundColor(caption_image);
(void) CloneString(&annotate_info->text,caption);
(void) FormatLocaleString(geometry,MaxTextExtent,"+0+%.20g",
metrics.ascent);
if (annotate_info->gravity == UndefinedGravity)
(void) CloneString(&annotate_info->geometry,AcquireString(
geometry));
(void) AnnotateImage(caption_image,annotate_info);
height+=caption_image->rows;
}
annotate_info=DestroyDrawInfo(annotate_info);
caption=DestroyString(caption);
}
}
picture_image=CloneImage(image,image->columns+2*quantum,height,MagickTrue,
exception);
if (picture_image == (Image *) NULL)
{
if (caption_image != (Image *) NULL)
caption_image=DestroyImage(caption_image);
return((Image *) NULL);
}
picture_image->background_color=image->border_color;
(void) SetImageBackgroundColor(picture_image);
(void) CompositeImage(picture_image,OverCompositeOp,image,quantum,quantum);
if (caption_image != (Image *) NULL)
{
(void) CompositeImage(picture_image,OverCompositeOp,caption_image,
quantum,(ssize_t) (image->rows+3*quantum/2));
caption_image=DestroyImage(caption_image);
}
(void) QueryColorDatabase("none",&picture_image->background_color,exception);
(void) SetImageAlphaChannel(picture_image,OpaqueAlphaChannel);
rotate_image=RotateImage(picture_image,90.0,exception);
picture_image=DestroyImage(picture_image);
if (rotate_image == (Image *) NULL)
return((Image *) NULL);
picture_image=rotate_image;
bend_image=WaveImage(picture_image,0.01*picture_image->rows,2.0*
picture_image->columns,exception);
picture_image=DestroyImage(picture_image);
if (bend_image == (Image *) NULL)
return((Image *) NULL);
InheritException(&bend_image->exception,exception);
picture_image=bend_image;
rotate_image=RotateImage(picture_image,-90.0,exception);
picture_image=DestroyImage(picture_image);
if (rotate_image == (Image *) NULL)
return((Image *) NULL);
picture_image=rotate_image;
picture_image->background_color=image->background_color;
polaroid_image=ShadowImage(picture_image,80.0,2.0,quantum/3,quantum/3,
exception);
if (polaroid_image == (Image *) NULL)
{
picture_image=DestroyImage(picture_image);
return(picture_image);
}
flop_image=FlopImage(polaroid_image,exception);
polaroid_image=DestroyImage(polaroid_image);
if (flop_image == (Image *) NULL)
{
picture_image=DestroyImage(picture_image);
return(picture_image);
}
polaroid_image=flop_image;
(void) CompositeImage(polaroid_image,OverCompositeOp,picture_image,
(ssize_t) (-0.01*picture_image->columns/2.0),0L);
picture_image=DestroyImage(picture_image);
(void) QueryColorDatabase("none",&polaroid_image->background_color,exception);
rotate_image=RotateImage(polaroid_image,angle,exception);
polaroid_image=DestroyImage(polaroid_image);
if (rotate_image == (Image *) NULL)
return((Image *) NULL);
polaroid_image=rotate_image;
trim_image=TrimImage(polaroid_image,exception);
polaroid_image=DestroyImage(polaroid_image);
if (trim_image == (Image *) NULL)
return((Image *) NULL);
polaroid_image=trim_image;
return(polaroid_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S e p i a T o n e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% MagickSepiaToneImage() applies a special effect to the image, similar to the
% effect achieved in a photo darkroom by sepia toning. Threshold ranges from
% 0 to QuantumRange and is a measure of the extent of the sepia toning. A
% threshold of 80% is a good starting point for a reasonable tone.
%
% The format of the SepiaToneImage method is:
%
% Image *SepiaToneImage(const Image *image,const double threshold,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o threshold: the tone threshold.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *SepiaToneImage(const Image *image,const double threshold,
ExceptionInfo *exception)
{
#define SepiaToneImageTag "SepiaTone/Image"
CacheView
*image_view,
*sepia_view;
Image
*sepia_image;
MagickBooleanType
status;
MagickOffsetType
progress;
ssize_t
y;
/*
Initialize sepia-toned image attributes.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
sepia_image=CloneImage(image,0,0,MagickTrue,exception);
if (sepia_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(sepia_image,DirectClass) == MagickFalse)
{
InheritException(exception,&sepia_image->exception);
sepia_image=DestroyImage(sepia_image);
return((Image *) NULL);
}
/*
Tone each row of the image.
*/
status=MagickTrue;
progress=0;
image_view=AcquireVirtualCacheView(image,exception);
sepia_view=AcquireAuthenticCacheView(sepia_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,sepia_image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
register const PixelPacket
*magick_restrict p;
register ssize_t
x;
register PixelPacket
*magick_restrict q;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=QueueCacheViewAuthenticPixels(sepia_view,0,y,sepia_image->columns,1,
exception);
if ((p == (const PixelPacket *) NULL) || (q == (PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
double
intensity,
tone;
intensity=GetPixelIntensity(image,p);
tone=intensity > threshold ? (double) QuantumRange : intensity+
(double) QuantumRange-threshold;
SetPixelRed(q,ClampToQuantum(tone));
tone=intensity > (7.0*threshold/6.0) ? (double) QuantumRange :
intensity+(double) QuantumRange-7.0*threshold/6.0;
SetPixelGreen(q,ClampToQuantum(tone));
tone=intensity < (threshold/6.0) ? 0 : intensity-threshold/6.0;
SetPixelBlue(q,ClampToQuantum(tone));
tone=threshold/7.0;
if ((double) GetPixelGreen(q) < tone)
SetPixelGreen(q,ClampToQuantum(tone));
if ((double) GetPixelBlue(q) < tone)
SetPixelBlue(q,ClampToQuantum(tone));
SetPixelOpacity(q,GetPixelOpacity(p));
p++;
q++;
}
if (SyncCacheViewAuthenticPixels(sepia_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(image,SepiaToneImageTag,progress,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
sepia_view=DestroyCacheView(sepia_view);
image_view=DestroyCacheView(image_view);
(void) NormalizeImage(sepia_image);
(void) ContrastImage(sepia_image,MagickTrue);
if (status == MagickFalse)
sepia_image=DestroyImage(sepia_image);
return(sepia_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S h a d o w I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ShadowImage() simulates a shadow from the specified image and returns it.
%
% The format of the ShadowImage method is:
%
% Image *ShadowImage(const Image *image,const double opacity,
% const double sigma,const ssize_t x_offset,const ssize_t y_offset,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o opacity: percentage transparency.
%
% o sigma: the standard deviation of the Gaussian, in pixels.
%
% o x_offset: the shadow x-offset.
%
% o y_offset: the shadow y-offset.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *ShadowImage(const Image *image,const double opacity,
const double sigma,const ssize_t x_offset,const ssize_t y_offset,
ExceptionInfo *exception)
{
#define ShadowImageTag "Shadow/Image"
CacheView
*image_view;
Image
*border_image,
*clone_image,
*shadow_image;
MagickBooleanType
status;
MagickOffsetType
progress;
RectangleInfo
border_info;
ssize_t
y;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
clone_image=CloneImage(image,0,0,MagickTrue,exception);
if (clone_image == (Image *) NULL)
return((Image *) NULL);
if (IsGrayColorspace(image->colorspace) != MagickFalse)
(void) SetImageColorspace(clone_image,sRGBColorspace);
(void) SetImageVirtualPixelMethod(clone_image,EdgeVirtualPixelMethod);
clone_image->compose=OverCompositeOp;
border_info.width=(size_t) floor(2.0*sigma+0.5);
border_info.height=(size_t) floor(2.0*sigma+0.5);
border_info.x=0;
border_info.y=0;
(void) QueryColorDatabase("none",&clone_image->border_color,exception);
border_image=BorderImage(clone_image,&border_info,exception);
clone_image=DestroyImage(clone_image);
if (border_image == (Image *) NULL)
return((Image *) NULL);
if (border_image->matte == MagickFalse)
(void) SetImageAlphaChannel(border_image,OpaqueAlphaChannel);
/*
Shadow image.
*/
status=MagickTrue;
progress=0;
image_view=AcquireAuthenticCacheView(border_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(border_image,border_image,border_image->rows,1)
#endif
for (y=0; y < (ssize_t) border_image->rows; y++)
{
register PixelPacket
*magick_restrict q;
register ssize_t
x;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,border_image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) border_image->columns; x++)
{
SetPixelRed(q,border_image->background_color.red);
SetPixelGreen(q,border_image->background_color.green);
SetPixelBlue(q,border_image->background_color.blue);
if (border_image->matte == MagickFalse)
SetPixelOpacity(q,border_image->background_color.opacity);
else
SetPixelOpacity(q,ClampToQuantum((double) (QuantumRange-
GetPixelAlpha(q)*opacity/100.0)));
q++;
}
if (SyncCacheViewAuthenticPixels(image_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(image,ShadowImageTag,progress,
border_image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
image_view=DestroyCacheView(image_view);
shadow_image=BlurImageChannel(border_image,AlphaChannel,0.0,sigma,exception);
border_image=DestroyImage(border_image);
if (shadow_image == (Image *) NULL)
return((Image *) NULL);
if (shadow_image->page.width == 0)
shadow_image->page.width=shadow_image->columns;
if (shadow_image->page.height == 0)
shadow_image->page.height=shadow_image->rows;
shadow_image->page.width+=x_offset-(ssize_t) border_info.width;
shadow_image->page.height+=y_offset-(ssize_t) border_info.height;
shadow_image->page.x+=x_offset-(ssize_t) border_info.width;
shadow_image->page.y+=y_offset-(ssize_t) border_info.height;
return(shadow_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S k e t c h I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SketchImage() simulates a pencil sketch. We convolve the image with a
% Gaussian operator of the given radius and standard deviation (sigma). For
% reasonable results, radius should be larger than sigma. Use a radius of 0
% and SketchImage() selects a suitable radius for you. Angle gives the angle
% of the sketch.
%
% The format of the SketchImage method is:
%
% Image *SketchImage(const Image *image,const double radius,
% const double sigma,const double angle,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o radius: the radius of the Gaussian, in pixels, not counting
% the center pixel.
%
% o sigma: the standard deviation of the Gaussian, in pixels.
%
% o angle: Apply the effect along this angle.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *SketchImage(const Image *image,const double radius,
const double sigma,const double angle,ExceptionInfo *exception)
{
CacheView
*random_view;
Image
*blend_image,
*blur_image,
*dodge_image,
*random_image,
*sketch_image;
MagickBooleanType
status;
MagickPixelPacket
zero;
RandomInfo
**magick_restrict random_info;
ssize_t
y;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
unsigned long
key;
#endif
/*
Sketch image.
*/
random_image=CloneImage(image,image->columns << 1,image->rows << 1,
MagickTrue,exception);
if (random_image == (Image *) NULL)
return((Image *) NULL);
status=MagickTrue;
GetMagickPixelPacket(random_image,&zero);
random_info=AcquireRandomInfoThreadSet();
random_view=AcquireAuthenticCacheView(random_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
key=GetRandomSecretKey(random_info[0]);
#pragma omp parallel for schedule(static) shared(status) \
magick_number_threads(random_image,random_image,random_image->rows,key == ~0UL)
#endif
for (y=0; y < (ssize_t) random_image->rows; y++)
{
const int
id = GetOpenMPThreadId();
MagickPixelPacket
pixel;
register IndexPacket
*magick_restrict indexes;
register ssize_t
x;
register PixelPacket
*magick_restrict q;
if (status == MagickFalse)
continue;
q=QueueCacheViewAuthenticPixels(random_view,0,y,random_image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewAuthenticIndexQueue(random_view);
pixel=zero;
for (x=0; x < (ssize_t) random_image->columns; x++)
{
pixel.red=(MagickRealType) (QuantumRange*
GetPseudoRandomValue(random_info[id]));
pixel.green=pixel.red;
pixel.blue=pixel.red;
if (image->colorspace == CMYKColorspace)
pixel.index=pixel.red;
SetPixelPacket(random_image,&pixel,q,indexes+x);
q++;
}
if (SyncCacheViewAuthenticPixels(random_view,exception) == MagickFalse)
status=MagickFalse;
}
random_info=DestroyRandomInfoThreadSet(random_info);
if (status == MagickFalse)
{
random_view=DestroyCacheView(random_view);
random_image=DestroyImage(random_image);
return(random_image);
}
random_view=DestroyCacheView(random_view);
blur_image=MotionBlurImage(random_image,radius,sigma,angle,exception);
random_image=DestroyImage(random_image);
if (blur_image == (Image *) NULL)
return((Image *) NULL);
dodge_image=EdgeImage(blur_image,radius,exception);
blur_image=DestroyImage(blur_image);
if (dodge_image == (Image *) NULL)
return((Image *) NULL);
status=ClampImage(dodge_image);
if (status != MagickFalse)
status=NormalizeImage(dodge_image);
if (status != MagickFalse)
status=NegateImage(dodge_image,MagickFalse);
if (status != MagickFalse)
status=TransformImage(&dodge_image,(char *) NULL,"50%");
sketch_image=CloneImage(image,0,0,MagickTrue,exception);
if (sketch_image == (Image *) NULL)
{
dodge_image=DestroyImage(dodge_image);
return((Image *) NULL);
}
(void) CompositeImage(sketch_image,ColorDodgeCompositeOp,dodge_image,0,0);
dodge_image=DestroyImage(dodge_image);
blend_image=CloneImage(image,0,0,MagickTrue,exception);
if (blend_image == (Image *) NULL)
{
sketch_image=DestroyImage(sketch_image);
return((Image *) NULL);
}
(void) SetImageArtifact(blend_image,"compose:args","20x80");
(void) CompositeImage(sketch_image,BlendCompositeOp,blend_image,0,0);
blend_image=DestroyImage(blend_image);
return(sketch_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S o l a r i z e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SolarizeImage() applies a special effect to the image, similar to the effect
% achieved in a photo darkroom by selectively exposing areas of photo
% sensitive paper to light. Threshold ranges from 0 to QuantumRange and is a
% measure of the extent of the solarization.
%
% The format of the SolarizeImage method is:
%
% MagickBooleanType SolarizeImage(Image *image,const double threshold)
% MagickBooleanType SolarizeImageChannel(Image *image,
% const ChannelType channel,const double threshold,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o channel: the channel type.
%
% o threshold: Define the extent of the solarization.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport MagickBooleanType SolarizeImage(Image *image,
const double threshold)
{
MagickBooleanType
status;
status=SolarizeImageChannel(image,DefaultChannels,threshold,
&image->exception);
return(status);
}
MagickExport MagickBooleanType SolarizeImageChannel(Image *image,
const ChannelType channel,const double threshold,ExceptionInfo *exception)
{
#define SolarizeImageTag "Solarize/Image"
CacheView
*image_view;
MagickBooleanType
status;
MagickOffsetType
progress;
ssize_t
y;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if (IsGrayColorspace(image->colorspace) != MagickFalse)
(void) SetImageColorspace(image,sRGBColorspace);
if (image->storage_class == PseudoClass)
{
register ssize_t
i;
/*
Solarize colormap.
*/
for (i=0; i < (ssize_t) image->colors; i++)
{
if ((channel & RedChannel) != 0)
if ((double) image->colormap[i].red > threshold)
image->colormap[i].red=QuantumRange-image->colormap[i].red;
if ((channel & GreenChannel) != 0)
if ((double) image->colormap[i].green > threshold)
image->colormap[i].green=QuantumRange-image->colormap[i].green;
if ((channel & BlueChannel) != 0)
if ((double) image->colormap[i].blue > threshold)
image->colormap[i].blue=QuantumRange-image->colormap[i].blue;
}
}
/*
Solarize image.
*/
status=MagickTrue;
progress=0;
image_view=AcquireAuthenticCacheView(image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
register ssize_t
x;
register PixelPacket
*magick_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++)
{
if ((channel & RedChannel) != 0)
if ((double) GetPixelRed(q) > threshold)
SetPixelRed(q,QuantumRange-GetPixelRed(q));
if ((channel & GreenChannel) != 0)
if ((double) GetPixelGreen(q) > threshold)
SetPixelGreen(q,QuantumRange-GetPixelGreen(q));
if ((channel & BlueChannel) != 0)
if ((double) GetPixelBlue(q) > threshold)
SetPixelBlue(q,QuantumRange-GetPixelBlue(q));
q++;
}
if (SyncCacheViewAuthenticPixels(image_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(image,SolarizeImageTag,progress,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
image_view=DestroyCacheView(image_view);
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S t e g a n o I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SteganoImage() hides a digital watermark within the image. Recover
% the hidden watermark later to prove that the authenticity of an image.
% Offset defines the start position within the image to hide the watermark.
%
% The format of the SteganoImage method is:
%
% Image *SteganoImage(const Image *image,Image *watermark,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o watermark: the watermark image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *SteganoImage(const Image *image,const Image *watermark,
ExceptionInfo *exception)
{
#define GetBit(alpha,i) ((((size_t) (alpha) >> (size_t) (i)) & 0x01) != 0)
#define SetBit(alpha,i,set) (alpha)=(Quantum) ((set) != 0 ? (size_t) (alpha) \
| (one << (size_t) (i)) : (size_t) (alpha) & ~(one << (size_t) (i)))
#define SteganoImageTag "Stegano/Image"
CacheView
*stegano_view,
*watermark_view;
Image
*stegano_image;
int
c;
MagickBooleanType
status;
PixelPacket
pixel;
register PixelPacket
*q;
register ssize_t
x;
size_t
depth,
one;
ssize_t
i,
j,
k,
y;
/*
Initialize steganographic image attributes.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(watermark != (const Image *) NULL);
assert(watermark->signature == MagickCoreSignature);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
one=1UL;
stegano_image=CloneImage(image,0,0,MagickTrue,exception);
if (stegano_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(stegano_image,DirectClass) == MagickFalse)
{
InheritException(exception,&stegano_image->exception);
stegano_image=DestroyImage(stegano_image);
return((Image *) NULL);
}
stegano_image->depth=MAGICKCORE_QUANTUM_DEPTH;
/*
Hide watermark in low-order bits of image.
*/
c=0;
i=0;
j=0;
depth=stegano_image->depth;
k=image->offset;
status=MagickTrue;
watermark_view=AcquireVirtualCacheView(watermark,exception);
stegano_view=AcquireAuthenticCacheView(stegano_image,exception);
for (i=(ssize_t) depth-1; (i >= 0) && (j < (ssize_t) depth); i--)
{
for (y=0; (y < (ssize_t) watermark->rows) && (j < (ssize_t) depth); y++)
{
for (x=0; (x < (ssize_t) watermark->columns) && (j < (ssize_t) depth); x++)
{
(void) GetOneCacheViewVirtualPixel(watermark_view,x,y,&pixel,exception);
if ((k/(ssize_t) stegano_image->columns) >= (ssize_t) stegano_image->rows)
break;
q=GetCacheViewAuthenticPixels(stegano_view,k % (ssize_t)
stegano_image->columns,k/(ssize_t) stegano_image->columns,1,1,
exception);
if (q == (PixelPacket *) NULL)
break;
switch (c)
{
case 0:
{
SetBit(GetPixelRed(q),j,GetBit(ClampToQuantum(GetPixelIntensity(
image,&pixel)),i));
break;
}
case 1:
{
SetBit(GetPixelGreen(q),j,GetBit(ClampToQuantum(GetPixelIntensity(
image,&pixel)),i));
break;
}
case 2:
{
SetBit(GetPixelBlue(q),j,GetBit(ClampToQuantum(GetPixelIntensity(
image,&pixel)),i));
break;
}
}
if (SyncCacheViewAuthenticPixels(stegano_view,exception) == MagickFalse)
break;
c++;
if (c == 3)
c=0;
k++;
if (k == (ssize_t) (stegano_image->columns*stegano_image->columns))
k=0;
if (k == image->offset)
j++;
}
}
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
proceed=SetImageProgress(image,SteganoImageTag,(MagickOffsetType)
(depth-i),depth);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
stegano_view=DestroyCacheView(stegano_view);
watermark_view=DestroyCacheView(watermark_view);
if (stegano_image->storage_class == PseudoClass)
(void) SyncImage(stegano_image);
if (status == MagickFalse)
stegano_image=DestroyImage(stegano_image);
return(stegano_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S t e r e o A n a g l y p h I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% StereoAnaglyphImage() combines two images and produces a single image that
% is the composite of a left and right image of a stereo pair. Special
% red-green stereo glasses are required to view this effect.
%
% The format of the StereoAnaglyphImage method is:
%
% Image *StereoImage(const Image *left_image,const Image *right_image,
% ExceptionInfo *exception)
% Image *StereoAnaglyphImage(const Image *left_image,
% const Image *right_image,const ssize_t x_offset,const ssize_t y_offset,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o left_image: the left image.
%
% o right_image: the right image.
%
% o exception: return any errors or warnings in this structure.
%
% o x_offset: amount, in pixels, by which the left image is offset to the
% right of the right image.
%
% o y_offset: amount, in pixels, by which the left image is offset to the
% bottom of the right image.
%
%
*/
MagickExport Image *StereoImage(const Image *left_image,
const Image *right_image,ExceptionInfo *exception)
{
return(StereoAnaglyphImage(left_image,right_image,0,0,exception));
}
MagickExport Image *StereoAnaglyphImage(const Image *left_image,
const Image *right_image,const ssize_t x_offset,const ssize_t y_offset,
ExceptionInfo *exception)
{
#define StereoImageTag "Stereo/Image"
const Image
*image;
Image
*stereo_image;
MagickBooleanType
status;
ssize_t
y;
assert(left_image != (const Image *) NULL);
assert(left_image->signature == MagickCoreSignature);
if (left_image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",
left_image->filename);
assert(right_image != (const Image *) NULL);
assert(right_image->signature == MagickCoreSignature);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
image=left_image;
if ((left_image->columns != right_image->columns) ||
(left_image->rows != right_image->rows))
ThrowImageException(ImageError,"LeftAndRightImageSizesDiffer");
/*
Initialize stereo image attributes.
*/
stereo_image=CloneImage(left_image,left_image->columns,left_image->rows,
MagickTrue,exception);
if (stereo_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(stereo_image,DirectClass) == MagickFalse)
{
InheritException(exception,&stereo_image->exception);
stereo_image=DestroyImage(stereo_image);
return((Image *) NULL);
}
(void) SetImageColorspace(stereo_image,sRGBColorspace);
/*
Copy left image to red channel and right image to blue channel.
*/
status=MagickTrue;
for (y=0; y < (ssize_t) stereo_image->rows; y++)
{
register const PixelPacket
*magick_restrict p,
*magick_restrict q;
register ssize_t
x;
register PixelPacket
*magick_restrict r;
p=GetVirtualPixels(left_image,-x_offset,y-y_offset,image->columns,1,
exception);
q=GetVirtualPixels(right_image,0,y,right_image->columns,1,exception);
r=QueueAuthenticPixels(stereo_image,0,y,stereo_image->columns,1,exception);
if ((p == (PixelPacket *) NULL) || (q == (PixelPacket *) NULL) ||
(r == (PixelPacket *) NULL))
break;
for (x=0; x < (ssize_t) stereo_image->columns; x++)
{
SetPixelRed(r,GetPixelRed(p));
SetPixelGreen(r,GetPixelGreen(q));
SetPixelBlue(r,GetPixelBlue(q));
SetPixelOpacity(r,(GetPixelOpacity(p)+q->opacity)/2);
p++;
q++;
r++;
}
if (SyncAuthenticPixels(stereo_image,exception) == MagickFalse)
break;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
proceed=SetImageProgress(image,StereoImageTag,(MagickOffsetType) y,
stereo_image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
if (status == MagickFalse)
stereo_image=DestroyImage(stereo_image);
return(stereo_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S w i r l I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SwirlImage() swirls the pixels about the center of the image, where
% degrees indicates the sweep of the arc through which each pixel is moved.
% You get a more dramatic effect as the degrees move from 1 to 360.
%
% The format of the SwirlImage method is:
%
% Image *SwirlImage(const Image *image,double degrees,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o degrees: Define the tightness of the swirling effect.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *SwirlImage(const Image *image,double degrees,
ExceptionInfo *exception)
{
#define SwirlImageTag "Swirl/Image"
CacheView
*image_view,
*swirl_view;
double
radius;
Image
*swirl_image;
MagickBooleanType
status;
MagickOffsetType
progress;
MagickPixelPacket
zero;
PointInfo
center,
scale;
ssize_t
y;
/*
Initialize swirl image attributes.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
swirl_image=CloneImage(image,0,0,MagickTrue,exception);
if (swirl_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(swirl_image,DirectClass) == MagickFalse)
{
InheritException(exception,&swirl_image->exception);
swirl_image=DestroyImage(swirl_image);
return((Image *) NULL);
}
if (swirl_image->background_color.opacity != OpaqueOpacity)
swirl_image->matte=MagickTrue;
/*
Compute scaling factor.
*/
center.x=(double) image->columns/2.0;
center.y=(double) image->rows/2.0;
radius=MagickMax(center.x,center.y);
scale.x=1.0;
scale.y=1.0;
if (image->columns > image->rows)
scale.y=(double) image->columns/(double) image->rows;
else
if (image->columns < image->rows)
scale.x=(double) image->rows/(double) image->columns;
degrees=(double) DegreesToRadians(degrees);
/*
Swirl image.
*/
status=MagickTrue;
progress=0;
GetMagickPixelPacket(swirl_image,&zero);
image_view=AcquireVirtualCacheView(image,exception);
swirl_view=AcquireAuthenticCacheView(swirl_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,swirl_image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
double
distance;
MagickPixelPacket
pixel;
PointInfo
delta;
register IndexPacket
*magick_restrict swirl_indexes;
register ssize_t
x;
register PixelPacket
*magick_restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(swirl_view,0,y,swirl_image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
swirl_indexes=GetCacheViewAuthenticIndexQueue(swirl_view);
delta.y=scale.y*(double) (y-center.y);
pixel=zero;
for (x=0; x < (ssize_t) image->columns; x++)
{
/*
Determine if the pixel is within an ellipse.
*/
delta.x=scale.x*(double) (x-center.x);
distance=delta.x*delta.x+delta.y*delta.y;
if (distance < (radius*radius))
{
double
cosine,
factor,
sine;
/*
Swirl the pixel.
*/
factor=1.0-sqrt(distance)/radius;
sine=sin((double) (degrees*factor*factor));
cosine=cos((double) (degrees*factor*factor));
status=InterpolateMagickPixelPacket(image,image_view,
UndefinedInterpolatePixel,(double) ((cosine*delta.x-sine*delta.y)/
scale.x+center.x),(double) ((sine*delta.x+cosine*delta.y)/scale.y+
center.y),&pixel,exception);
if (status == MagickFalse)
break;
SetPixelPacket(swirl_image,&pixel,q,swirl_indexes+x);
}
q++;
}
if (SyncCacheViewAuthenticPixels(swirl_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(image,SwirlImageTag,progress,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
swirl_view=DestroyCacheView(swirl_view);
image_view=DestroyCacheView(image_view);
if (status == MagickFalse)
swirl_image=DestroyImage(swirl_image);
return(swirl_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% T i n t I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% TintImage() applies a color vector to each pixel in the image. The length
% of the vector is 0 for black and white and at its maximum for the midtones.
% The vector weighting function is f(x)=(1-(4.0*((x-0.5)*(x-0.5))))
%
% The format of the TintImage method is:
%
% Image *TintImage(const Image *image,const char *opacity,
% const PixelPacket tint,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o opacity: A color value used for tinting.
%
% o tint: A color value used for tinting.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *TintImage(const Image *image,const char *opacity,
const PixelPacket tint,ExceptionInfo *exception)
{
#define TintImageTag "Tint/Image"
CacheView
*image_view,
*tint_view;
GeometryInfo
geometry_info;
Image
*tint_image;
MagickBooleanType
status;
MagickOffsetType
progress;
MagickPixelPacket
color_vector,
pixel;
MagickStatusType
flags;
ssize_t
y;
/*
Allocate tint image.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
tint_image=CloneImage(image,0,0,MagickTrue,exception);
if (tint_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(tint_image,DirectClass) == MagickFalse)
{
InheritException(exception,&tint_image->exception);
tint_image=DestroyImage(tint_image);
return((Image *) NULL);
}
if ((IsGrayColorspace(image->colorspace) != MagickFalse) &&
(IsPixelGray(&tint) == MagickFalse))
(void) SetImageColorspace(tint_image,sRGBColorspace);
if (opacity == (const char *) NULL)
return(tint_image);
/*
Determine RGB values of the tint color.
*/
flags=ParseGeometry(opacity,&geometry_info);
pixel.red=geometry_info.rho;
pixel.green=geometry_info.rho;
pixel.blue=geometry_info.rho;
pixel.opacity=(MagickRealType) OpaqueOpacity;
if ((flags & SigmaValue) != 0)
pixel.green=geometry_info.sigma;
if ((flags & XiValue) != 0)
pixel.blue=geometry_info.xi;
if ((flags & PsiValue) != 0)
pixel.opacity=geometry_info.psi;
color_vector.red=(MagickRealType) (pixel.red*tint.red/100.0-
PixelPacketIntensity(&tint));
color_vector.green=(MagickRealType) (pixel.green*tint.green/100.0-
PixelPacketIntensity(&tint));
color_vector.blue=(MagickRealType) (pixel.blue*tint.blue/100.0-
PixelPacketIntensity(&tint));
/*
Tint image.
*/
status=MagickTrue;
progress=0;
image_view=AcquireVirtualCacheView(image,exception);
tint_view=AcquireAuthenticCacheView(tint_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,tint_image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
register const PixelPacket
*magick_restrict p;
register PixelPacket
*magick_restrict q;
register ssize_t
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=QueueCacheViewAuthenticPixels(tint_view,0,y,tint_image->columns,1,
exception);
if ((p == (const PixelPacket *) NULL) || (q == (PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
double
weight;
MagickPixelPacket
pixel;
weight=QuantumScale*GetPixelRed(p)-0.5;
pixel.red=(MagickRealType) GetPixelRed(p)+color_vector.red*(1.0-(4.0*
(weight*weight)));
SetPixelRed(q,ClampToQuantum(pixel.red));
weight=QuantumScale*GetPixelGreen(p)-0.5;
pixel.green=(MagickRealType) GetPixelGreen(p)+color_vector.green*(1.0-
(4.0*(weight*weight)));
SetPixelGreen(q,ClampToQuantum(pixel.green));
weight=QuantumScale*GetPixelBlue(p)-0.5;
pixel.blue=(MagickRealType) GetPixelBlue(p)+color_vector.blue*(1.0-(4.0*
(weight*weight)));
SetPixelBlue(q,ClampToQuantum(pixel.blue));
SetPixelOpacity(q,GetPixelOpacity(p));
p++;
q++;
}
if (SyncCacheViewAuthenticPixels(tint_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(image,TintImageTag,progress,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
tint_view=DestroyCacheView(tint_view);
image_view=DestroyCacheView(image_view);
if (status == MagickFalse)
tint_image=DestroyImage(tint_image);
return(tint_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% V i g n e t t e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% VignetteImage() softens the edges of the image in vignette style.
%
% The format of the VignetteImage method is:
%
% Image *VignetteImage(const Image *image,const double radius,
% const double sigma,const ssize_t x,const ssize_t y,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o radius: the radius of the pixel neighborhood.
%
% o sigma: the standard deviation of the Gaussian, in pixels.
%
% o x, y: Define the x and y ellipse offset.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *VignetteImage(const Image *image,const double radius,
const double sigma,const ssize_t x,const ssize_t y,ExceptionInfo *exception)
{
char
ellipse[MaxTextExtent];
DrawInfo
*draw_info;
Image
*blur_image,
*canvas_image,
*oval_image,
*vignette_image;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
canvas_image=CloneImage(image,0,0,MagickTrue,exception);
if (canvas_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(canvas_image,DirectClass) == MagickFalse)
{
InheritException(exception,&canvas_image->exception);
canvas_image=DestroyImage(canvas_image);
return((Image *) NULL);
}
canvas_image->matte=MagickTrue;
oval_image=CloneImage(canvas_image,canvas_image->columns,canvas_image->rows,
MagickTrue,exception);
if (oval_image == (Image *) NULL)
{
canvas_image=DestroyImage(canvas_image);
return((Image *) NULL);
}
(void) QueryColorDatabase("#000000",&oval_image->background_color,exception);
(void) SetImageBackgroundColor(oval_image);
draw_info=CloneDrawInfo((const ImageInfo *) NULL,(const DrawInfo *) NULL);
(void) QueryColorDatabase("#ffffff",&draw_info->fill,exception);
(void) QueryColorDatabase("#ffffff",&draw_info->stroke,exception);
(void) FormatLocaleString(ellipse,MaxTextExtent,
"ellipse %g,%g,%g,%g,0.0,360.0",image->columns/2.0,
image->rows/2.0,image->columns/2.0-x,image->rows/2.0-y);
draw_info->primitive=AcquireString(ellipse);
(void) DrawImage(oval_image,draw_info);
draw_info=DestroyDrawInfo(draw_info);
blur_image=BlurImage(oval_image,radius,sigma,exception);
oval_image=DestroyImage(oval_image);
if (blur_image == (Image *) NULL)
{
canvas_image=DestroyImage(canvas_image);
return((Image *) NULL);
}
blur_image->matte=MagickFalse;
(void) CompositeImage(canvas_image,CopyOpacityCompositeOp,blur_image,0,0);
blur_image=DestroyImage(blur_image);
vignette_image=MergeImageLayers(canvas_image,FlattenLayer,exception);
canvas_image=DestroyImage(canvas_image);
if (vignette_image != (Image *) NULL)
(void) TransformImageColorspace(vignette_image,image->colorspace);
return(vignette_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% W a v e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% WaveImage() creates a "ripple" effect in the image by shifting the pixels
% vertically along a sine wave whose amplitude and wavelength is specified
% by the given parameters.
%
% The format of the WaveImage method is:
%
% Image *WaveImage(const Image *image,const double amplitude,
% const double wave_length,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o amplitude, wave_length: Define the amplitude and wave length of the
% sine wave.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *WaveImage(const Image *image,const double amplitude,
const double wave_length,ExceptionInfo *exception)
{
#define WaveImageTag "Wave/Image"
CacheView
*image_view,
*wave_view;
float
*sine_map;
Image
*wave_image;
MagickBooleanType
status;
MagickOffsetType
progress;
MagickPixelPacket
zero;
register ssize_t
i;
ssize_t
y;
/*
Initialize wave image attributes.
*/
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
wave_image=CloneImage(image,image->columns,(size_t) (image->rows+2.0*
fabs(amplitude)),MagickTrue,exception);
if (wave_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(wave_image,DirectClass) == MagickFalse)
{
InheritException(exception,&wave_image->exception);
wave_image=DestroyImage(wave_image);
return((Image *) NULL);
}
if (wave_image->background_color.opacity != OpaqueOpacity)
wave_image->matte=MagickTrue;
/*
Allocate sine map.
*/
sine_map=(float *) AcquireQuantumMemory((size_t) wave_image->columns,
sizeof(*sine_map));
if (sine_map == (float *) NULL)
{
wave_image=DestroyImage(wave_image);
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
}
for (i=0; i < (ssize_t) wave_image->columns; i++)
sine_map[i]=(float) fabs(amplitude)+amplitude*sin((double)
((2.0*MagickPI*i)/wave_length));
/*
Wave image.
*/
status=MagickTrue;
progress=0;
GetMagickPixelPacket(wave_image,&zero);
image_view=AcquireVirtualCacheView(image,exception);
wave_view=AcquireAuthenticCacheView(wave_image,exception);
(void) SetCacheViewVirtualPixelMethod(image_view,
BackgroundVirtualPixelMethod);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(progress,status) \
magick_number_threads(image,wave_image,wave_image->rows,1)
#endif
for (y=0; y < (ssize_t) wave_image->rows; y++)
{
MagickPixelPacket
pixel;
register IndexPacket
*magick_restrict indexes;
register PixelPacket
*magick_restrict q;
register ssize_t
x;
if (status == MagickFalse)
continue;
q=QueueCacheViewAuthenticPixels(wave_view,0,y,wave_image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewAuthenticIndexQueue(wave_view);
pixel=zero;
for (x=0; x < (ssize_t) wave_image->columns; x++)
{
status=InterpolateMagickPixelPacket(image,image_view,
UndefinedInterpolatePixel,(double) x,(double) (y-sine_map[x]),&pixel,
exception);
if (status == MagickFalse)
break;
SetPixelPacket(wave_image,&pixel,q,indexes+x);
q++;
}
if (SyncCacheViewAuthenticPixels(wave_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp atomic
#endif
progress++;
proceed=SetImageProgress(image,WaveImageTag,progress,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
wave_view=DestroyCacheView(wave_view);
image_view=DestroyCacheView(image_view);
sine_map=(float *) RelinquishMagickMemory(sine_map);
if (status == MagickFalse)
wave_image=DestroyImage(wave_image);
return(wave_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% W a v e l e t D e n o i s e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% WaveletDenoiseImage() removes noise from the image using a wavelet
% transform. The wavelet transform is a fast hierarchical scheme for
% processing an image using a set of consecutive lowpass and high_pass filters,
% followed by a decimation. This results in a decomposition into different
% scales which can be regarded as different “frequency bands”, determined by
% the mother wavelet. Adapted from dcraw.c by David Coffin.
%
% The format of the WaveletDenoiseImage method is:
%
% Image *WaveletDenoiseImage(const Image *image,const double threshold,
% const double softness,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o threshold: set the threshold for smoothing.
%
% o softness: attenuate the smoothing threshold.
%
% o exception: return any errors or warnings in this structure.
%
*/
static inline void HatTransform(const float *magick_restrict pixels,
const size_t stride,const size_t extent,const size_t scale,float *kernel)
{
const float
*magick_restrict p,
*magick_restrict q,
*magick_restrict r;
register ssize_t
i;
p=pixels;
q=pixels+scale*stride,
r=pixels+scale*stride;
for (i=0; i < (ssize_t) scale; i++)
{
kernel[i]=0.25f*(*p+(*p)+(*q)+(*r));
p+=stride;
q-=stride;
r+=stride;
}
for ( ; i < (ssize_t) (extent-scale); i++)
{
kernel[i]=0.25f*(2.0f*(*p)+*(p-scale*stride)+*(p+scale*stride));
p+=stride;
}
q=p-scale*stride;
r=pixels+stride*(extent-2);
for ( ; i < (ssize_t) extent; i++)
{
kernel[i]=0.25f*(*p+(*p)+(*q)+(*r));
p+=stride;
q+=stride;
r-=stride;
}
}
MagickExport Image *WaveletDenoiseImage(const Image *image,
const double threshold,const double softness,ExceptionInfo *exception)
{
CacheView
*image_view,
*noise_view;
float
*kernel,
*pixels;
Image
*noise_image;
MagickBooleanType
status;
MagickSizeType
number_pixels;
MemoryInfo
*pixels_info;
size_t
max_channels;
ssize_t
channel;
static const double
noise_levels[]= {
0.8002, 0.2735, 0.1202, 0.0585, 0.0291, 0.0152, 0.0080, 0.0044 };
/*
Initialize noise image attributes.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
noise_image=(Image *) NULL;
#if defined(MAGICKCORE_OPENCL_SUPPORT)
noise_image=AccelerateWaveletDenoiseImage(image,threshold,exception);
if (noise_image != (Image *) NULL)
return(noise_image);
#endif
noise_image=CloneImage(image,0,0,MagickTrue,exception);
if (noise_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(noise_image,DirectClass) == MagickFalse)
{
noise_image=DestroyImage(noise_image);
return((Image *) NULL);
}
if (AcquireMagickResource(WidthResource,3*image->columns) == MagickFalse)
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
pixels_info=AcquireVirtualMemory(3*image->columns,image->rows*
sizeof(*pixels));
kernel=(float *) AcquireQuantumMemory(MagickMax(image->rows,image->columns)+1,
GetOpenMPMaximumThreads()*sizeof(*kernel));
if ((pixels_info == (MemoryInfo *) NULL) || (kernel == (float *) NULL))
{
if (kernel != (float *) NULL)
kernel=(float *) RelinquishMagickMemory(kernel);
if (pixels_info != (MemoryInfo *) NULL)
pixels_info=RelinquishVirtualMemory(pixels_info);
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
}
pixels=(float *) GetVirtualMemoryBlob(pixels_info);
status=MagickTrue;
number_pixels=image->columns*image->rows;
max_channels=(size_t) (image->colorspace == CMYKColorspace ? 4 : 3);
image_view=AcquireAuthenticCacheView(image,exception);
noise_view=AcquireAuthenticCacheView(noise_image,exception);
for (channel=0; channel < (ssize_t) max_channels; channel++)
{
register ssize_t
i;
size_t
high_pass,
low_pass;
ssize_t
level,
y;
if (status == MagickFalse)
continue;
/*
Copy channel from image to wavelet pixel array.
*/
i=0;
for (y=0; y < (ssize_t) image->rows; y++)
{
register const IndexPacket
*magick_restrict indexes;
register const PixelPacket
*magick_restrict p;
ssize_t
x;
p=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,exception);
if (p == (const PixelPacket *) NULL)
{
status=MagickFalse;
break;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
for (x=0; x < (ssize_t) image->columns; x++)
{
switch (channel)
{
case 0: pixels[i]=(float) GetPixelRed(p); break;
case 1: pixels[i]=(float) GetPixelGreen(p); break;
case 2: pixels[i]=(float) GetPixelBlue(p); break;
case 3: pixels[i]=(float) indexes[x]; break;
default: break;
}
i++;
p++;
}
}
/*
Low pass filter outputs are called approximation kernel & high pass
filters are referred to as detail kernel. The detail kernel
have high values in the noisy parts of the signal.
*/
high_pass=0;
for (level=0; level < 5; level++)
{
double
magnitude;
ssize_t
x,
y;
low_pass=(size_t) (number_pixels*((level & 0x01)+1));
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,1) \
magick_number_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
const int
id = GetOpenMPThreadId();
register float
*magick_restrict p,
*magick_restrict q;
register ssize_t
x;
p=kernel+id*image->columns;
q=pixels+y*image->columns;
HatTransform(q+high_pass,1,image->columns,(size_t) (1UL << level),p);
q+=low_pass;
for (x=0; x < (ssize_t) image->columns; x++)
*q++=(*p++);
}
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,1) \
magick_number_threads(image,image,image->columns,1)
#endif
for (x=0; x < (ssize_t) image->columns; x++)
{
const int
id = GetOpenMPThreadId();
register float
*magick_restrict p,
*magick_restrict q;
register ssize_t
y;
p=kernel+id*image->rows;
q=pixels+x+low_pass;
HatTransform(q,image->columns,image->rows,(size_t) (1UL << level),p);
for (y=0; y < (ssize_t) image->rows; y++)
{
*q=(*p++);
q+=image->columns;
}
}
/*
To threshold, each coefficient is compared to a threshold value and
attenuated / shrunk by some factor.
*/
magnitude=threshold*noise_levels[level];
for (i=0; i < (ssize_t) number_pixels; ++i)
{
pixels[high_pass+i]-=pixels[low_pass+i];
if (pixels[high_pass+i] < -magnitude)
pixels[high_pass+i]+=magnitude-softness*magnitude;
else
if (pixels[high_pass+i] > magnitude)
pixels[high_pass+i]-=magnitude-softness*magnitude;
else
pixels[high_pass+i]*=softness;
if (high_pass != 0)
pixels[i]+=pixels[high_pass+i];
}
high_pass=low_pass;
}
/*
Reconstruct image from the thresholded wavelet kernel.
*/
i=0;
for (y=0; y < (ssize_t) image->rows; y++)
{
MagickBooleanType
sync;
register IndexPacket
*magick_restrict noise_indexes;
register PixelPacket
*magick_restrict q;
register ssize_t
x;
q=GetCacheViewAuthenticPixels(noise_view,0,y,noise_image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
break;
}
noise_indexes=GetCacheViewAuthenticIndexQueue(noise_view);
for (x=0; x < (ssize_t) image->columns; x++)
{
float
pixel;
pixel=pixels[i]+pixels[low_pass+i];
switch (channel)
{
case 0: SetPixelRed(q,ClampToQuantum(pixel)); break;
case 1: SetPixelGreen(q,ClampToQuantum(pixel)); break;
case 2: SetPixelBlue(q,ClampToQuantum(pixel)); break;
case 3: SetPixelIndex(noise_indexes+x,ClampToQuantum(pixel)); break;
default: break;
}
i++;
q++;
}
sync=SyncCacheViewAuthenticPixels(noise_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
proceed=SetImageProgress(image,AddNoiseImageTag,(MagickOffsetType)
channel,max_channels);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
noise_view=DestroyCacheView(noise_view);
image_view=DestroyCacheView(image_view);
kernel=(float *) RelinquishMagickMemory(kernel);
pixels_info=RelinquishVirtualMemory(pixels_info);
return(noise_image);
}
|
krb5_tgs_fmt_plug.c | /*
* Based on the work by Tim Medin
* Port from his Pythonscript to John by Michael Kramer (SySS GmbH)
*
* This software is
* Copyright (c) 2015 Michael Kramer <michael.kramer@uni-konstanz.de>,
* Copyright (c) 2015 magnum
* Copyright (c) 2016 Fist0urs <eddy.maaalou@gmail.com>
*
* Modified by Fist0urs to improve performances by proceeding known-plain
* attack, based on defined ASN1 structures (then got rid of RC4 rounds
* + hmac-md5)
*
* 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.
*/
#if FMT_EXTERNS_H
extern struct fmt_main fmt_krb5tgs;
#elif FMT_REGISTERS_H
john_register_one(&fmt_krb5tgs);
#else
#include <stdio.h>
#include <string.h>
#include <ctype.h>
#ifdef _OPENMP
#include <omp.h>
#endif
#include "misc.h"
#include "formats.h"
#include "common.h"
#include "dyna_salt.h"
#include "rc4.h"
#include "md4.h"
#include "hmacmd5.h"
#include "unicode.h"
#include "memdbg.h"
#ifndef OMP_SCALE
#define OMP_SCALE 256
#endif
#define FORMAT_LABEL "krb5tgs"
#define FORMAT_NAME "Kerberos 5 TGS etype 23"
#define FORMAT_TAG "$krb5tgs$23$"
#define FORMAT_TAG_LEN (sizeof(FORMAT_TAG)-1)
#define ALGORITHM_NAME "MD4 HMAC-MD5 RC4"
#define BENCHMARK_COMMENT ""
#define BENCHMARK_LENGTH -1000
#define MIN_PLAINTEXT_LENGTH 0
#define PLAINTEXT_LENGTH 125
#define BINARY_SIZE 0
#define BINARY_ALIGN MEM_ALIGN_NONE
#define SALT_SIZE sizeof(struct custom_salt *)
#define SALT_ALIGN sizeof(struct custom_salt *)
#define MIN_KEYS_PER_CRYPT 1
#define MAX_KEYS_PER_CRYPT 1
/*
assuming checksum == edata1
formats are:
checksum$edata2
$krb5tgs$23$checksum$edata2
$krb5tgs$23$*user*realm*spn*$checksum$edata2
*/
static struct fmt_tests tests[] = {
{"74809c4c83c3c8279c6058d2f206ec2f$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", "test123"},
{"$krb5tgs$23$ee09e292a05e3af870417758b1cdfd04$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", "bluvshop2"},
{"$krb5tgs$23$*Fist0urs$MYDOMAIN$cifs/panda.com*$423cb47a258e5859c13381ae64de7464$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", "jlcirr."},
// 1-40a00000-john@HTTP-adc1.toor.com-TOOR.COM.kirbi file
{"$krb5tgs$23$e43ae991b15bbd11c19395c6c785f4d4$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", "1qaz@WSX"},
{NULL}
};
static char (*saved_key)[PLAINTEXT_LENGTH + 1];
static unsigned char (*saved_K1)[16];
static int any_cracked, *cracked;
static size_t cracked_size;
static int new_keys;
static struct custom_salt {
dyna_salt dsalt;
unsigned char edata1[16];
uint32_t edata2len;
unsigned char* edata2;
} *cur_salt;
static char *split(char *ciphertext, int index, struct fmt_main *self)
{
static char *ptr, *keeptr;
int i;
if (strstr(ciphertext, "$SOURCE_HASH$"))
return ciphertext;
ptr = mem_alloc_tiny(strlen(ciphertext) + FORMAT_TAG_LEN + 1, MEM_ALIGN_NONE);
keeptr = ptr;
if (strncmp(ciphertext, FORMAT_TAG, FORMAT_TAG_LEN) != 0) {
memcpy(ptr, FORMAT_TAG, FORMAT_TAG_LEN);
ptr += FORMAT_TAG_LEN;
}
for (i = 0; i < strlen(ciphertext) + 1; i++)
ptr[i] = tolower(ARCH_INDEX(ciphertext[i]));
return keeptr;
}
static int valid(char *ciphertext, struct fmt_main *self)
{
char *p;
char *ctcopy;
char *keeptr;
int extra;
ctcopy = strdup(ciphertext);
keeptr = ctcopy;
if (strncmp(ciphertext, FORMAT_TAG, FORMAT_TAG_LEN) == 0) {
ctcopy += FORMAT_TAG_LEN;
if (ctcopy[0] == '*') { /* assume account's info provided */
ctcopy++;
p = strtokm(ctcopy, "*");
ctcopy = strtokm(NULL, "");
if (!ctcopy || *ctcopy != '$')
goto err;
++ctcopy; /* set after '$' */
goto edata;
}
if (ctcopy[0] == '$')
ctcopy++;
}
edata:
/* assume checksum */
if (((p = strtokm(ctcopy, "$")) == NULL) || strlen(p) != 32)
goto err;
/* assume edata2 following */
if (((p = strtokm(NULL, "$")) == NULL))
goto err;
if (!ishex(p) && (hexlen(p, &extra) < 64 || extra))
goto err;
if ((strtokm(NULL, "$") != NULL))
goto err;
MEM_FREE(keeptr);
return 1;
err:
MEM_FREE(keeptr);
return 0;
}
static void init(struct fmt_main *self)
{
#ifdef _OPENMP
int omp_t = omp_get_max_threads();
self->params.min_keys_per_crypt *= omp_t;
omp_t *= OMP_SCALE;
self->params.max_keys_per_crypt *= omp_t;
#endif
saved_key = mem_alloc_align(sizeof(*saved_key) *
self->params.max_keys_per_crypt,
MEM_ALIGN_CACHE);
saved_K1 = mem_alloc_align(sizeof(*saved_K1) *
self->params.max_keys_per_crypt,
MEM_ALIGN_CACHE);
any_cracked = 0;
cracked_size = sizeof(*cracked) * self->params.max_keys_per_crypt;
cracked = mem_calloc(cracked_size, 1);
}
static void done(void)
{
MEM_FREE(saved_K1);
MEM_FREE(cracked);
MEM_FREE(saved_key);
}
static void *get_salt(char *ciphertext)
{
int i;
static struct custom_salt cs;
char *p;
char *ctcopy;
char *keeptr;
static void *ptr;
ctcopy = strdup(ciphertext);
keeptr = ctcopy;
memset(&cs, 0, sizeof(cs));
cs.edata2 = NULL;
if (strncmp(ciphertext, FORMAT_TAG, FORMAT_TAG_LEN) == 0) {
ctcopy += FORMAT_TAG_LEN;
if (ctcopy[0] == '*') {
ctcopy++;
p = strtokm(ctcopy, "*");
ctcopy += strlen(p) + 2;
goto edata;
}
if (ctcopy[0]=='$')
ctcopy++;
}
edata:
if (((p = strtokm(ctcopy, "$")) != NULL) && strlen(p) == 32) { /* assume checksum */
for (i = 0; i < 16; i++) {
cs.edata1[i] =
atoi16[ARCH_INDEX(p[i * 2])] * 16 +
atoi16[ARCH_INDEX(p[i * 2 + 1])];
}
/* skip '$' */
p += strlen(p) + 1;
/* retrieve non-constant length of edata2 */
for (i = 0; p[i] != '\0'; i++)
;
cs.edata2len = i/2;
cs.edata2 = (unsigned char*) mem_calloc_tiny(cs.edata2len + 1, sizeof(char));
for (i = 0; i < cs.edata2len; i++) { /* assume edata2 */
cs.edata2[i] =
atoi16[ARCH_INDEX(p[i * 2])] * 16 +
atoi16[ARCH_INDEX(p[i * 2 + 1])];
}
}
MEM_FREE(keeptr);
/* following is used to fool dyna_salt stuff */
cs.dsalt.salt_cmp_offset = SALT_CMP_OFF(struct custom_salt, edata1);
cs.dsalt.salt_cmp_size = SALT_CMP_SIZE(struct custom_salt, edata1, edata2len, 0);
cs.dsalt.salt_alloc_needs_free = 0;
ptr = mem_alloc_tiny(sizeof(struct custom_salt), MEM_ALIGN_WORD);
memcpy(ptr, &cs, sizeof(struct custom_salt));
return (void *) &ptr;
}
static void set_salt(void *salt)
{
cur_salt = *(struct custom_salt**)salt;
}
static void set_key(char *key, int index)
{
strnzcpy(saved_key[index], key, strlen(key) + 1);
new_keys = 1;
}
static char *get_key(int index)
{
return saved_key[index];
}
static int crypt_all(int *pcount, struct db_salt *salt)
{
const int count = *pcount;
const unsigned char data[4] = {2, 0, 0, 0};
int index;
if (any_cracked) {
memset(cracked, 0, cracked_size);
any_cracked = 0;
}
#ifdef _OPENMP
#pragma omp parallel for
#endif
for (index = 0; index < count; index++) {
unsigned char K3[16];
#ifdef _MSC_VER
unsigned char ddata[65536];
#else
unsigned char ddata[cur_salt->edata2len + 1];
#endif
unsigned char checksum[16];
RC4_KEY rckey;
if (new_keys) {
MD4_CTX ctx;
unsigned char key[16];
UTF16 wkey[PLAINTEXT_LENGTH + 1];
int len;
len = enc_to_utf16(wkey, PLAINTEXT_LENGTH,
(UTF8*)saved_key[index],
strlen(saved_key[index]));
if (len <= 0) {
saved_key[index][-len] = 0;
len = strlen16(wkey);
}
MD4_Init(&ctx);
MD4_Update(&ctx, (char*)wkey, 2 * len);
MD4_Final(key, &ctx);
hmac_md5(key, data, 4, saved_K1[index]);
}
hmac_md5(saved_K1[index], cur_salt->edata1, 16, K3);
RC4_set_key(&rckey, 16, K3);
RC4(&rckey, 32, cur_salt->edata2, ddata);
/*
8 first bytes are nonce, then ASN1 structures
(DER encoding: type-length-data)
if length >= 128 bytes:
length is on 2 bytes and type is
\x63\x82 (encode_krb5_enc_tkt_part)
and data is an ASN1 sequence \x30\x82
else:
length is on 1 byte and type is \x63\x81
and data is an ASN1 sequence \x30\x81
next headers follow the same ASN1 "type-length-data" scheme
*/
if (((!memcmp(ddata + 8, "\x63\x82", 2)) && (!memcmp(ddata + 16, "\xA0\x07\x03\x05", 4)))
||
((!memcmp(ddata + 8, "\x63\x81", 2)) && (!memcmp(ddata + 16, "\x03\x05\x00", 3)))) {
/* check the checksum to be sure */
RC4(&rckey, cur_salt->edata2len - 32, cur_salt->edata2 + 32, ddata + 32);
hmac_md5(saved_K1[index], ddata, cur_salt->edata2len, checksum);
if (!memcmp(checksum, cur_salt->edata1, 16)) {
cracked[index] = 1;
#ifdef _OPENMP
#pragma omp atomic
#endif
any_cracked |= 1;
}
}
}
new_keys = 0;
return *pcount;
}
static int cmp_all(void *binary, int count)
{
return any_cracked;
}
static int cmp_one(void *binary, int index)
{
return cracked[index];
}
static int cmp_exact(char *source, int index)
{
return cracked[index];
}
struct fmt_main fmt_krb5tgs = {
{
FORMAT_LABEL,
FORMAT_NAME,
ALGORITHM_NAME,
BENCHMARK_COMMENT,
BENCHMARK_LENGTH,
MIN_PLAINTEXT_LENGTH,
PLAINTEXT_LENGTH,
BINARY_SIZE,
BINARY_ALIGN,
SALT_SIZE,
SALT_ALIGN,
MIN_KEYS_PER_CRYPT,
MAX_KEYS_PER_CRYPT,
FMT_CASE | FMT_8_BIT | FMT_UNICODE | FMT_UTF8 | FMT_OMP | FMT_DYNA_SALT,
{NULL},
{ FORMAT_TAG },
tests
}, {
init,
done,
fmt_default_reset,
fmt_default_prepare,
valid,
split,
fmt_default_binary,
get_salt,
{NULL},
fmt_default_source,
{
fmt_default_binary_hash
},
fmt_default_dyna_salt_hash,
NULL,
set_salt,
set_key,
get_key,
fmt_default_clear_keys,
crypt_all,
{
fmt_default_get_hash
},
cmp_all,
cmp_one,
cmp_exact
}
};
#endif
|
VolumetricDilatedMaxPooling.c | #ifndef TH_GENERIC_FILE
#define TH_GENERIC_FILE "generic/VolumetricDilatedMaxPooling.c"
#else
static inline void THNN_(VolumetricDilatedMaxPooling_shapeCheck)(
THNNState *state,
THTensor *input,
THTensor *gradOutput,
THIndexTensor *indices,
int kT, int kW, int kH,
int dT, int dW, int dH,
int pT, int pW, int pH,
int dilationT, int dilationW, int dilationH,
bool ceilMode) {
int ndim = input->nDimension;
int dimN = 0;
int dimt = 1;
int dimh = 2;
int dimw = 3;
int64_t nslices;
int64_t itime;
int64_t iheight;
int64_t iwidth;
int64_t otime;
int64_t oheight;
int64_t owidth;
THArgCheck(kT > 0 && kW > 0 && kH > 0, 5,
"kernel size should be greater than zero, but got kT: %d kH: %d kW: %d",
kT, kH, kW);
THArgCheck(dT > 0 && dW > 0 && dH > 0, 8,
"stride should be greater than zero, but got dT: %d dH: %d dW: %d",
dT, dH, dW);
THArgCheck(dilationT > 0 && dilationW > 0 && dilationH > 0, 14,
"dilation should be greater than 0, but got dilationT: %d dilationH: %d dilationW: %d",
dilationT, dilationH, dilationW);
THNN_ARGCHECK(input->nDimension == 4 || input->nDimension == 5, 2, input,
"4D or 5D (batch mode) tensor expected for input, but got: %s");
if (input->nDimension == 5)
{
dimN++;
dimt++;
dimh++;
dimw++;
}
THArgCheck(kT/2 >= pT && kW/2 >= pW && kH/2 >= pH, 2,
"pad should be smaller than half of kernel size, but got "
"kT: %d kW: %d, kH: %d, padT: %d, padW: %d, padH: %d",
kT, kW, kH, pT, pW, pH);
nslices = input->size[dimN];
itime = input->size[dimt];
iheight = input->size[dimh];
iwidth = input->size[dimw];
if (ceilMode)
{
otime = (int)(ceil((float)(itime - (dilationT * (kT - 1) + 1) + 2*pT) / dT)) + 1;
oheight = (int)(ceil((float)(iheight - (dilationH * (kH - 1) + 1) + 2*pH) / dH)) + 1;
owidth = (int)(ceil((float)(iwidth - (dilationW * (kW - 1) + 1) + 2*pW) / dW)) + 1;
}
else
{
otime = (int)(floor((float)(itime - (dilationT * (kT - 1) + 1) + 2*pT) / dT)) + 1;
oheight = (int)(floor((float)(iheight - (dilationH * (kH - 1) + 1) + 2*pH) / dH)) + 1;
owidth = (int)(floor((float)(iwidth - (dilationW * (kW - 1) + 1) + 2*pW) / dW)) + 1;
}
if (pT || pW || pH)
{
// ensure that the last pooling starts inside the image
if ((otime - 1)*dT >= itime + pT)
--otime;
if ((oheight - 1)*dH >= iheight + pH)
--oheight;
if ((owidth - 1)*dW >= iwidth + pW)
--owidth;
}
if (otime < 1 || owidth < 1 || oheight < 1)
THError("Given input size: (%dx%dx%dx%d). Calculated output size: (%dx%dx%dx%d). Output size is too small",
nslices,itime,iheight,iwidth,nslices,otime,oheight,owidth);
if (gradOutput != NULL) {
THNN_CHECK_DIM_SIZE(gradOutput, ndim, dimN, nslices);
THNN_CHECK_DIM_SIZE(gradOutput, ndim, dimt, otime);
THNN_CHECK_DIM_SIZE(gradOutput, ndim, dimh, oheight);
THNN_CHECK_DIM_SIZE(gradOutput, ndim, dimw, owidth);
}
if (indices != NULL) {
THNN_CHECK_DIM_SIZE_INDICES(indices, ndim, dimN, nslices);
THNN_CHECK_DIM_SIZE_INDICES(indices, ndim, dimt, otime);
THNN_CHECK_DIM_SIZE_INDICES(indices, ndim, dimh, oheight);
THNN_CHECK_DIM_SIZE_INDICES(indices, ndim, dimw, owidth);
}
}
static void THNN_(VolumetricDilatedMaxPooling_updateOutput_frame)(
real *input_p,
real *output_p,
THIndex_t *indz_p,
int64_t nslices,
int64_t itime,
int64_t iwidth,
int64_t iheight,
int64_t otime,
int64_t owidth,
int64_t oheight,
int kT,
int kW,
int kH,
int dT,
int dW,
int dH,
int pT,
int pW,
int pH,
int dilationT,
int dilationW,
int dilationH)
{
int64_t k;
#pragma omp parallel for private(k)
for (k = 0; k < nslices; k++)
{
/* loop over output */
int64_t i, j, ti;
real *ip = input_p + k * itime * iwidth * iheight;
for (ti = 0; ti < otime; ti++)
{
for (i = 0; i < oheight; i++)
{
for (j = 0; j < owidth; j++)
{
/* local pointers */
int64_t start_t = ti * dT - pT;
int64_t start_h = i * dH - pH;
int64_t start_w = j * dW - pW;
int64_t end_t = fminf(start_t + (kT - 1) * dilationT + 1, itime);
int64_t end_h = fminf(start_h + (kH - 1) * dilationH + 1, iheight);
int64_t end_w = fminf(start_w + (kW - 1) * dilationW + 1, iwidth);
while(start_t < 0)
start_t += dilationT;
while(start_h < 0)
start_h += dilationH;
while(start_w < 0)
start_w += dilationW;
real *op = output_p + k * otime * owidth * oheight
+ ti * owidth * oheight + i * owidth + j;
THIndex_t *indzp = indz_p + k * otime * owidth * oheight
+ ti * owidth * oheight + i * owidth + j;
/* compute local max: */
int64_t maxindex = -1;
real maxval = -THInf;
int64_t x,y,z;
int64_t index = 0;
for (z = start_t; z < end_t; z += dilationT)
{
for (y = start_h; y < end_h; y += dilationH)
{
for (x = start_w; x < end_w; x += dilationW)
{
index = z * iwidth * iheight + y * iwidth + x;
real val = ip[index];
if (val > maxval)
{
maxval = val;
maxindex = index;
}
}
}
}
// store location of max
*indzp = maxindex + TH_INDEX_BASE;
/* set output to local max */
*op = maxval;
}
}
}
}
}
void THNN_(VolumetricDilatedMaxPooling_updateOutput)(
THNNState *state,
THTensor *input,
THTensor *output,
THIndexTensor *indices,
int kT,
int kW,
int kH,
int dT,
int dW,
int dH,
int pT,
int pW,
int pH,
int dilationT,
int dilationW,
int dilationH,
bool ceilMode)
{
int64_t nslices;
int64_t itime;
int64_t iheight;
int64_t iwidth;
int64_t otime;
int64_t oheight;
int64_t owidth;
real *input_data;
real *output_data;
THIndex_t *indices_data;
int dimN = 0;
int dimt = 1;
int dimh = 2;
int dimw = 3;
if (input->nDimension == 5)
{
dimN++;
dimt++;
dimh++;
dimw++;
}
THNN_(VolumetricDilatedMaxPooling_shapeCheck)(
state, input, NULL, NULL,
kT, kW, kH, dT, dW, dH,
pT, pW, pH, dilationT, dilationW, dilationH,
ceilMode);
/* sizes */
nslices = input->size[dimN];
itime = input->size[dimt];
iheight = input->size[dimh];
iwidth = input->size[dimw];
if (ceilMode)
{
otime = (int)(ceil((float)(itime - (dilationT * (kT - 1) + 1) + 2*pT) / dT)) + 1;
oheight = (int)(ceil((float)(iheight - (dilationH * (kH - 1) + 1) + 2*pH) / dH)) + 1;
owidth = (int)(ceil((float)(iwidth - (dilationW * (kW - 1) + 1) + 2*pW) / dW)) + 1;
}
else
{
otime = (int)(floor((float)(itime - (dilationT * (kT - 1) + 1) + 2*pT) / dT)) + 1;
oheight = (int)(floor((float)(iheight - (dilationH * (kH - 1) + 1) + 2*pH) / dH)) + 1;
owidth = (int)(floor((float)(iwidth - (dilationW * (kW - 1) + 1) + 2*pW) / dW)) + 1;
}
if (pT || pW || pH)
{
// ensure that the last pooling starts inside the image
if ((otime - 1)*dT >= itime + pT)
--otime;
if ((oheight - 1)*dH >= iheight + pH)
--oheight;
if ((owidth - 1)*dW >= iwidth + pW)
--owidth;
}
/* get contiguous input */
input = THTensor_(newContiguous)(input);
if (input->nDimension == 4) /* non-batch mode */
{
/* resize output */
THTensor_(resize4d)(output, nslices, otime, oheight, owidth);
/* indices will contain ti,i,j uchar locations packed into float/double */
THIndexTensor_(resize4d)(indices, nslices, otime, oheight, owidth);
input_data = THTensor_(data)(input);
output_data = THTensor_(data)(output);
indices_data = THIndexTensor_(data)(indices);
THNN_(VolumetricDilatedMaxPooling_updateOutput_frame)(
input_data, output_data,
indices_data,
nslices,
itime, iwidth, iheight,
otime, owidth, oheight,
kT, kW, kH,
dT, dW, dH,
pT, pW, pH,
dilationT, dilationW, dilationH
);
}
else /* batch mode */
{
int64_t p;
int64_t nBatch = input->size[0];
int64_t istride = nslices * itime * iwidth * iheight;
int64_t ostride = nslices * otime * owidth * oheight;
/* resize output */
THTensor_(resize5d)(output, nBatch, nslices, otime, oheight, owidth);
/* indices will contain ti,i,j locations for each output point */
THIndexTensor_(resize5d)(indices, nBatch, nslices, otime, oheight, owidth);
input_data = THTensor_(data)(input);
output_data = THTensor_(data)(output);
indices_data = THIndexTensor_(data)(indices);
#pragma omp parallel for private(p)
for (p=0; p < nBatch; p++)
{
THNN_(VolumetricDilatedMaxPooling_updateOutput_frame)(
input_data + p * istride,
output_data + p * ostride,
indices_data + p * ostride,
nslices,
itime, iwidth, iheight,
otime, owidth, oheight,
kT, kW, kH,
dT, dW, dH,
pT, pW, pH,
dilationT, dilationW, dilationH
);
}
}
/* cleanup */
THTensor_(free)(input);
}
static void THNN_(VolumetricDilatedMaxPooling_updateGradInput_frame)(
real *gradInput_p,
real *gradOutput_p,
THIndex_t *indz_p,
int64_t nslices,
int64_t itime,
int64_t iwidth,
int64_t iheight,
int64_t otime,
int64_t owidth,
int64_t oheight,
int dT,
int dW,
int dH,
int pT,
int pW,
int pH,
int dilationT,
int dilationW,
int dilationH)
{
int64_t k;
#pragma omp parallel for private(k)
for (k = 0; k < nslices; k++)
{
real *gradInput_p_k = gradInput_p + k * itime * iwidth * iheight;
real *gradOutput_p_k = gradOutput_p + k * otime * owidth * oheight;
THIndex_t *indz_p_k = indz_p + k * otime * owidth * oheight;
/* calculate max points */
int64_t ti, i, j;
for (ti = 0; ti < otime; ti++)
{
for (i = 0; i < oheight; i++)
{
for (j = 0; j < owidth; j++)
{
/* retrieve position of max */
int64_t index = ti * oheight * owidth + i * owidth + j;
int64_t maxp = indz_p_k[index] - TH_INDEX_BASE;
if (maxp != -1) {
/* update gradient */
gradInput_p_k[maxp] += gradOutput_p_k[index];
}
}
}
}
}
}
void THNN_(VolumetricDilatedMaxPooling_updateGradInput)(
THNNState *state,
THTensor *input,
THTensor *gradOutput,
THTensor *gradInput,
THIndexTensor *indices,
int kT,
int kW,
int kH,
int dT,
int dW,
int dH,
int pT,
int pW,
int pH,
int dilationT,
int dilationW,
int dilationH,
bool ceilMode)
{
int nslices;
int itime;
int iheight;
int iwidth;
int otime;
int oheight;
int owidth;
real *gradInput_data;
real *gradOutput_data;
THIndex_t *indices_data;
int dimN = 0;
int dimt = 1;
int dimh = 2;
int dimw = 3;
THNN_(VolumetricDilatedMaxPooling_shapeCheck)(
state, input, gradOutput, indices,
kT, kW, kH, dT, dW, dH,
pT, pW, pH, dilationT, dilationW, dilationH,
ceilMode);
// TODO: gradOutput shape check
/* get contiguous gradOutput */
gradOutput = THTensor_(newContiguous)(gradOutput);
/* resize */
THTensor_(resizeAs)(gradInput, input);
THTensor_(zero)(gradInput);
if (input->nDimension == 5)
{
dimN++;
dimt++;
dimh++;
dimw++;
}
/* sizes */
nslices = input->size[dimN];
itime = input->size[dimt];
iheight = input->size[dimh];
iwidth = input->size[dimw];
otime = gradOutput->size[dimt];
oheight = gradOutput->size[dimh];
owidth = gradOutput->size[dimw];
/* get raw pointers */
gradInput_data = THTensor_(data)(gradInput);
gradOutput_data = THTensor_(data)(gradOutput);
indices_data = THIndexTensor_(data)(indices);
/* backprop */
if (input->nDimension == 4) /* non-batch mode*/
{
THNN_(VolumetricDilatedMaxPooling_updateGradInput_frame)(
gradInput_data, gradOutput_data,
indices_data,
nslices,
itime, iwidth, iheight,
otime, owidth, oheight,
dT, dW, dH,
pT, pW, pH,
dilationT, dilationW, dilationH
);
}
else /* batch mode */
{
int64_t p;
int64_t nBatch = input->size[0];
int64_t istride = nslices * itime * iwidth * iheight;
int64_t ostride = nslices * otime * owidth * oheight;
#pragma omp parallel for private(p)
for (p = 0; p < nBatch; p++)
{
THNN_(VolumetricDilatedMaxPooling_updateGradInput_frame)(
gradInput_data + p * istride,
gradOutput_data + p * ostride,
indices_data + p * ostride,
nslices,
itime, iwidth, iheight,
otime, owidth, oheight,
dT, dW, dH,
pT, pW, pH,
dilationT, dilationW, dilationH
);
}
}
/* cleanup */
THTensor_(free)(gradOutput);
}
#endif
|
bug2.c | /******************************************************************************
* FILE: omp_bug2.c
* DESCRIPTION:
* Another OpenMP program with a bug.
* AUTHOR: Blaise Barney
* LAST REVISED: 04/06/05
******************************************************************************/
#include <omp.h>
#include <stdio.h>
#include <stdlib.h>
int main (int argc, char *argv[])
{
int nthreads, i, tid;
float total;
/*** Spawn parallel region ***/
#pragma omp parallel private(tid, total)
{
/* Obtain thread number */
tid = omp_get_thread_num();
/* Only master thread does this */
if (tid == 0) {
nthreads = omp_get_num_threads();
printf("Number of threads = %d\n", nthreads);
}
printf("Thread %d is starting...\n",tid);
#pragma omp barrier
/* do some work */
total = 0.0;
#pragma omp for schedule(dynamic,10)
for (i=0; i<1000000; i++)
total = total + i*1.0;
printf ("Thread %d is done! Total= %e\n",tid,total);
} /*** End of parallel region ***/
}
|
Example_tasking.10.c | /*
* @@name: tasking.10c
* @@type: C
* @@compilable: yes
* @@linkable: no
* @@expect: success
* @@version: omp_3.0
*/
#include <omp.h>
void work() {
omp_lock_t lock;
omp_init_lock(&lock);
#pragma omp parallel
{
int i;
#pragma omp for
for (i = 0; i < 100; i++) {
#pragma omp task
{
// lock is shared by default in the task
omp_set_lock(&lock);
// Capture data for the following task
#pragma omp task
// Task Scheduling Point 1
{ /* do work here */ }
omp_unset_lock(&lock);
}
}
}
omp_destroy_lock(&lock);
}
|
GB_transpose_bucket.c | //------------------------------------------------------------------------------
// GB_transpose_bucket: transpose and optionally typecast and/or apply operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2022, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// C = A' or op(A'). Optionally typecasts from A->type to the new type ctype,
// and/or optionally applies a unary operator.
// If an operator z=op(x) is provided, the type of z must be the same as the
// type of C. The type of A must be compatible with the type of of x (A is
// typecasted into the type of x). These conditions must be checked in the
// caller.
// This function is agnostic for the CSR/CSC format of C and A. C_is_csc is
// defined by the caller and assigned to C->is_csc, but otherwise unused.
// A->is_csc is ignored.
// The input can be hypersparse or non-hypersparse. The output C is always
// non-hypersparse, and never shallow. On input, C is a static header.
// If A is m-by-n in CSC format, with e nonzeros, the time and memory taken is
// O(m+n+e) if A is non-hypersparse, or O(m+e) if hypersparse. This is fine if
// most rows and columns of A are non-empty, but can be very costly if A or A'
// is hypersparse. In particular, if A is a non-hypersparse column vector with
// m >> e, the time and memory is O(m), which can be huge. Thus, for
// hypersparse matrices, or for very sparse matrices, the qsort method should
// be used instead (see GB_transpose).
// This method is parallel, but not highly scalable. At most O(e/m) threads
// are used.
#include "GB_transpose.h"
#define GB_FREE_WORKSPACE \
{ \
if (Workspaces != NULL && Workspaces_size != NULL) \
{ \
for (int tid = 0 ; tid < nworkspaces ; tid++) \
{ \
GB_FREE_WORK (&(Workspaces [tid]), Workspaces_size [tid]) ; \
} \
} \
GB_WERK_POP (A_slice, int64_t) ; \
GB_WERK_POP (Workspaces_size, size_t) ; \
GB_WERK_POP (Workspaces, int64_t *) ; \
}
#define GB_FREE_ALL \
{ \
GB_phbix_free (C) ; \
GB_FREE_WORKSPACE ; \
}
GrB_Info GB_transpose_bucket // bucket transpose; typecast and apply op
(
GrB_Matrix C, // output matrix (static header)
const GB_iso_code C_code_iso, // iso code for C
const GrB_Type ctype, // type of output matrix C
const bool C_is_csc, // format of output matrix C
const GrB_Matrix A, // input matrix
// no operator is applied if op is NULL
const GB_Operator op, // unary/idxunop/binop to apply
const GrB_Scalar scalar, // scalar to bind to binary operator
bool binop_bind1st, // if true, binop(x,A) else binop(A,y)
const int nworkspaces, // # of workspaces to use
const int nthreads, // # of threads to use
GB_Context Context
)
{
//--------------------------------------------------------------------------
// check inputs
//--------------------------------------------------------------------------
ASSERT (C != NULL && (C->static_header || GBNSTATIC)) ;
ASSERT_TYPE_OK (ctype, "ctype for transpose", GB0) ;
ASSERT_MATRIX_OK (A, "A input for transpose_bucket", GB0) ;
ASSERT (!GB_PENDING (A)) ;
ASSERT (!GB_ZOMBIES (A)) ;
ASSERT (GB_JUMBLED_OK (A)) ;
// if op is NULL, then no operator is applied
// This method is only be used when A is sparse or hypersparse.
// The full and bitmap cases are handled in GB_transpose.
ASSERT (!GB_IS_FULL (A)) ;
ASSERT (!GB_IS_BITMAP (A)) ;
ASSERT (GB_IS_SPARSE (A) || GB_IS_HYPERSPARSE (A)) ;
GB_WERK_DECLARE (A_slice, int64_t) ; // size nthreads+1
GB_WERK_DECLARE (Workspaces, int64_t *) ; // size nworkspaces
GB_WERK_DECLARE (Workspaces_size, size_t) ; // size nworkspaces
//--------------------------------------------------------------------------
// get A
//--------------------------------------------------------------------------
int64_t anz = GB_nnz (A) ;
int64_t vlen = A->vlen ;
//--------------------------------------------------------------------------
// determine the number of threads to use
//--------------------------------------------------------------------------
// # of threads to use in the O(vlen) loops below
GB_GET_NTHREADS_MAX (nthreads_max, chunk, Context) ;
int nth = GB_nthreads (vlen, chunk, nthreads_max) ;
//--------------------------------------------------------------------------
// allocate C: always sparse
//--------------------------------------------------------------------------
// The bucket transpose only works when C is sparse.
// A can be sparse or hypersparse.
// C->p is allocated but not initialized.
GrB_Info info ;
// set C->iso = C_iso OK
bool C_iso = (C_code_iso != GB_NON_ISO) ;
GB_OK (GB_new_bix (&C, // sparse, existing header
ctype, A->vdim, vlen, GB_Ap_malloc, C_is_csc,
GxB_SPARSE, true, A->hyper_switch, vlen, anz, true, C_iso, Context)) ;
int64_t *restrict Cp = C->p ;
//--------------------------------------------------------------------------
// allocate workspace
//--------------------------------------------------------------------------
GB_WERK_PUSH (Workspaces, nworkspaces, int64_t *) ;
GB_WERK_PUSH (Workspaces_size, nworkspaces, size_t) ;
if (Workspaces == NULL || Workspaces_size == NULL)
{
// out of memory
GB_FREE_ALL ;
return (GrB_OUT_OF_MEMORY) ;
}
bool ok = true ;
for (int tid = 0 ; tid < nworkspaces ; tid++)
{
Workspaces [tid] = GB_MALLOC_WORK (vlen + 1, int64_t,
&Workspaces_size [tid]) ;
ok = ok && (Workspaces [tid] != NULL) ;
}
if (!ok)
{
// out of memory
GB_FREE_ALL ;
return (GrB_OUT_OF_MEMORY) ;
}
//==========================================================================
// phase1: symbolic analysis
//==========================================================================
// slice the A matrix, perfectly balanced for one task per thread
GB_WERK_PUSH (A_slice, nthreads + 1, int64_t) ;
if (A_slice == NULL)
{
// out of memory
GB_FREE_ALL ;
return (GrB_OUT_OF_MEMORY) ;
}
GB_pslice (A_slice, A->p, A->nvec, nthreads, true) ;
// sum up the row counts and find C->p
if (nthreads == 1)
{
//----------------------------------------------------------------------
// sequential method: A is not sliced
//----------------------------------------------------------------------
// Only requires a single int64 workspace of size vlen for a single
// thread. The resulting C matrix is not jumbled.
// compute the row counts of A. No need to scan the A->p pointers
ASSERT (nworkspaces == 1) ;
int64_t *restrict workspace = Workspaces [0] ;
memset (workspace, 0, (vlen + 1) * sizeof (int64_t)) ;
const int64_t *restrict Ai = A->i ;
for (int64_t p = 0 ; p < anz ; p++)
{
int64_t i = Ai [p] ;
workspace [i]++ ;
}
// cumulative sum of the workspace, and copy back into C->p
GB_cumsum (workspace, vlen, &(C->nvec_nonempty), 1, NULL) ;
memcpy (Cp, workspace, (vlen + 1) * sizeof (int64_t)) ;
}
else if (nworkspaces == 1)
{
//----------------------------------------------------------------------
// atomic method: A is sliced but workspace is shared
//----------------------------------------------------------------------
// Only requires a single int64 workspace of size vlen, shared by all
// threads. Scales well, but requires atomics. If the # of rows is
// very small and the average row degree is high, this can be very slow
// because of contention on the atomic workspace. Otherwise, it is
// typically faster than the non-atomic method. The resulting C matrix
// is jumbled.
// compute the row counts of A. No need to scan the A->p pointers
int64_t *restrict workspace = Workspaces [0] ;
GB_memset (workspace, 0, (vlen + 1) * sizeof (int64_t), nth) ;
const int64_t *restrict Ai = A->i ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
int64_t i = Ai [p] ;
// update workspace [i]++ automically:
GB_ATOMIC_UPDATE
workspace [i]++ ;
}
C->jumbled = true ; // atomic transpose leaves C jumbled
// cumulative sum of the workspace, and copy back into C->p
GB_cumsum (workspace, vlen, &(C->nvec_nonempty), nth, Context) ;
GB_memcpy (Cp, workspace, (vlen+ 1) * sizeof (int64_t), nth) ;
}
else
{
//----------------------------------------------------------------------
// non-atomic method
//----------------------------------------------------------------------
// compute the row counts of A for each slice, one per thread; This
// method is parallel, but not highly scalable. Each thread requires
// int64 workspace of size vlen, but no atomics are required. The
// resulting C matrix is not jumbled, so this can save work if C needs
// to be unjumbled later.
ASSERT (nworkspaces == nthreads) ;
const int64_t *restrict Ap = A->p ;
const int64_t *restrict Ah = A->h ;
const int64_t *restrict Ai = A->i ;
int tid ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (tid = 0 ; tid < nthreads ; tid++)
{
// get the row counts for this slice, of size A->vlen
int64_t *restrict workspace = Workspaces [tid] ;
memset (workspace, 0, (vlen + 1) * sizeof (int64_t)) ;
for (int64_t k = A_slice [tid] ; k < A_slice [tid+1] ; k++)
{
// iterate over the entries in A(:,j)
int64_t j = GBH (Ah, k) ;
int64_t pA_start = Ap [k] ;
int64_t pA_end = Ap [k+1] ;
for (int64_t pA = pA_start ; pA < pA_end ; pA++)
{
// count one more entry in C(i,:) for this slice
int64_t i = Ai [pA] ;
workspace [i]++ ;
}
}
}
// cumulative sum of the workspaces across the slices
int64_t i ;
#pragma omp parallel for num_threads(nth) schedule(static)
for (i = 0 ; i < vlen ; i++)
{
int64_t s = 0 ;
for (int tid = 0 ; tid < nthreads ; tid++)
{
int64_t *restrict workspace = Workspaces [tid] ;
int64_t c = workspace [i] ;
workspace [i] = s ;
s += c ;
}
Cp [i] = s ;
}
Cp [vlen] = 0 ;
// compute the vector pointers for C
GB_cumsum (Cp, vlen, &(C->nvec_nonempty), nth, Context) ;
// add Cp back to all Workspaces
#pragma omp parallel for num_threads(nth) schedule(static)
for (i = 0 ; i < vlen ; i++)
{
int64_t s = Cp [i] ;
int64_t *restrict workspace = Workspaces [0] ;
workspace [i] = s ;
for (int tid = 1 ; tid < nthreads ; tid++)
{
int64_t *restrict workspace = Workspaces [tid] ;
workspace [i] += s ;
}
}
}
C->magic = GB_MAGIC ;
//==========================================================================
// phase2: transpose A into C
//==========================================================================
// transpose both the pattern and the values
if (op == NULL)
{
// do not apply an operator; optional typecast to C->type
GB_transpose_ix (C, A, Workspaces, A_slice, nworkspaces, nthreads) ;
}
else
{
// apply an operator, C has type op->ztype
GB_transpose_op (C, C_code_iso, op, scalar, binop_bind1st, A,
Workspaces, A_slice, nworkspaces, nthreads) ;
}
//--------------------------------------------------------------------------
// free workspace and return result
//--------------------------------------------------------------------------
GB_FREE_WORKSPACE ;
ASSERT_MATRIX_OK (C, "C transpose of A", GB0) ;
ASSERT (C->h == NULL) ;
return (GrB_SUCCESS) ;
}
|
whilePeeler1.c | int bar();
void foo(int i, int y) {
bar();
}
int main() {
int i = 10;
int y = 11;
i = i + 1;
#pragma omp parallel
{
i = i + 3;
#pragma omp barrier
while (1) {
i = 10;
#pragma omp barrier
i = i + 1;
#pragma omp barrier
y = y + 1;
#pragma omp barrier
break;
}
}
foo(i, y);
}
|
Kernels.h | /*
Copyright (c) 2005-2016, University of Oxford.
All rights reserved.
University of Oxford means the Chancellor, Masters and Scholars of the
University of Oxford, having an administrative office at Wellington
Square, Oxford OX1 2JD, UK.
This file is part of Aboria.
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 following disclaimer.
* 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.
* Neither the name of the University of Oxford 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 KERNELS_H_
#define KERNELS_H_
#include <type_traits>
#include "Particles.h"
#include "detail/Chebyshev.h"
#include "FastMultipoleMethod.h"
#include "detail/Kernels.h"
#ifdef HAVE_H2LIB
#include "H2Lib.h"
#endif
#ifdef HAVE_EIGEN
#include <Eigen/Core>
namespace Aboria {
template <typename RowElements, typename ColElements, typename F>
class KernelBase {
protected:
typedef typename detail::kernel_helper<RowElements, ColElements, F>
kernel_helper;
static const unsigned int dimension = RowElements::dimension;
typedef Vector<double, dimension> double_d;
typedef Vector<int, dimension> int_d;
typedef position_d<dimension> position;
typedef double_d const &const_position_reference;
typedef typename RowElements::const_reference const_row_reference;
typedef typename ColElements::const_reference const_col_reference;
public:
typedef typename kernel_helper::Block Block;
typedef typename kernel_helper::Scalar Scalar;
static const size_t BlockRows = kernel_helper::BlockRows;
static const size_t BlockCols = kernel_helper::BlockCols;
typedef typename kernel_helper::BlockRHSVector BlockRHSVector;
typedef typename kernel_helper::BlockLHSVector BlockLHSVector;
typedef RowElements row_elements_type;
typedef ColElements col_elements_type;
typedef F function_type;
typedef size_t Index;
enum { ColsAtCompileTime = -1, RowsAtCompileTime = -1 };
KernelBase(const RowElements &row_elements, const ColElements &col_elements,
const F &function)
: m_row_elements(row_elements), m_col_elements(col_elements),
m_function(function){};
RowElements &get_row_elements() { return m_row_elements; }
const RowElements &get_row_elements() const { return m_row_elements; }
ColElements &get_col_elements() { return m_col_elements; }
const function_type &get_kernel_function() const { return m_function; }
const ColElements &get_col_elements() const { return m_col_elements; }
size_t rows() const { return m_row_elements.size() * BlockRows; }
size_t cols() const { return m_col_elements.size() * BlockCols; }
Scalar coeff(const size_t i, const size_t j) const {
ASSERT(i < rows(), "i greater than rows()");
ASSERT(j < cols(), "j greater than cols()");
const int pi = std::floor(static_cast<float>(i) / BlockRows);
const int ioffset = i - pi * BlockRows;
const int pj = std::floor(static_cast<float>(j) / BlockCols);
const int joffset = j - pj * BlockCols;
const Block block =
Block(m_function(m_row_elements[pi], m_col_elements[pj]));
return block(ioffset, joffset);
}
template <typename MatrixType> void assemble(const MatrixType &matrix) const {
MatrixType::MATRIX_ASSEMBLE_NOT_IMPLEMENTED;
}
template <typename Triplet>
void assemble(std::vector<Triplet> &triplets, const size_t startI = 0,
const size_t startJ = 0) const {
Triplet::TRIPLET_ASSEMBLE_NOT_IMPLEMENTED;
}
/// Evaluates a matrix-free linear operator given by \p expr \p if_expr,
/// and particle sets \p a and \p b on a vector rhs and
/// accumulates the result in vector lhs
template <typename VectorLHS, typename VectorRHS>
void evaluate(VectorLHS &lhs, const VectorRHS &rhs) const {
VectorLHS::EVALUATE_NOT_IMPLEMENTED;
}
protected:
const RowElements &m_row_elements;
const ColElements &m_col_elements;
const F m_function;
};
template <typename RowElements, typename ColElements, typename F>
class KernelDense : public KernelBase<RowElements, ColElements, F> {
protected:
typedef KernelBase<RowElements, ColElements, F> base_type;
static const unsigned int dimension = base_type::dimension;
typedef typename base_type::double_d double_d;
typedef typename base_type::position position;
typedef typename base_type::int_d int_d;
typedef typename base_type::const_row_reference const_row_reference;
typedef typename base_type::const_col_reference const_col_reference;
public:
typedef typename base_type::Block Block;
typedef typename base_type::BlockLHSVector BlockLHSVector;
typedef typename base_type::Scalar Scalar;
static const size_t BlockRows = base_type::BlockRows;
static const size_t BlockCols = base_type::BlockCols;
KernelDense(const RowElements &row_elements, const ColElements &col_elements,
const F &function)
: base_type(row_elements, col_elements, function){};
template <typename Derived>
void assemble(const Eigen::DenseBase<Derived> &matrix) const {
const RowElements &a = this->m_row_elements;
const ColElements &b = this->m_col_elements;
const size_t na = a.size();
const size_t nb = b.size();
ASSERT(matrix.rows() == static_cast<typename Derived::Index>(this->rows()),
"matrix has incompatible row size");
ASSERT(matrix.cols() == static_cast<typename Derived::Index>(this->cols()),
"matrix has incompatible col size");
for (size_t i = 0; i < na; ++i) {
for (size_t j = 0; j < nb; ++j) {
const_cast<Eigen::DenseBase<Derived> &>(matrix)
.template block<BlockRows, BlockCols>(i * BlockRows,
j * BlockCols) =
Block(this->m_function(a[i], b[j]));
}
}
}
template <typename Triplet>
void assemble(std::vector<Triplet> &triplets, const size_t startI = 0,
const size_t startJ = 0) const {
const RowElements &a = this->m_row_elements;
const ColElements &b = this->m_col_elements;
const size_t na = a.size();
const size_t nb = b.size();
for (size_t i = 0; i < na; ++i) {
const_row_reference ai = a[i];
for (size_t j = 0; j < nb; ++j) {
const_col_reference bj = b[j];
const Block element = static_cast<Block>(this->m_function(ai, bj));
for (size_t ii = 0; ii < BlockRows; ++ii) {
for (size_t jj = 0; jj < BlockCols; ++jj) {
triplets.push_back(Triplet(i * BlockRows + ii + startI,
j * BlockCols + jj + startJ,
element(ii, jj)));
}
}
}
}
}
/// Evaluates a matrix-free linear operator given by \p expr \p if_expr,
/// and particle sets \p a and \p b on a vector rhs and
/// accumulates the result in vector lhs
template <typename DerivedLHS, typename DerivedRHS>
void evaluate(Eigen::DenseBase<DerivedLHS> &lhs,
const Eigen::DenseBase<DerivedRHS> &rhs) const {
const RowElements &a = this->m_row_elements;
const ColElements &b = this->m_col_elements;
const size_t na = a.size();
const size_t nb = b.size();
CHECK(static_cast<size_t>(lhs.size()) == this->rows(),
"lhs size is inconsistent");
CHECK(static_cast<size_t>(rhs.size()) == this->cols(),
"rhs size is inconsistent");
#ifdef HAVE_OPENMP
#pragma omp parallel for
#endif
for (size_t i = 0; i < na; ++i) {
const_row_reference ai = a[i];
for (size_t j = 0; j < nb; ++j) {
const_col_reference bj = b[j];
lhs.template segment<BlockRows>(i * BlockRows) +=
this->m_function(ai, bj) *
rhs.template segment<BlockCols>(j * BlockCols);
}
}
}
/// Evaluates a matrix-free linear operator given by \p expr \p if_expr,
/// and particle sets \p a and \p b on a vector rhs and
/// accumulates the result in vector lhs
template <typename LHSType, typename RHSType>
void evaluate(std::vector<LHSType> &lhs,
const std::vector<RHSType> &rhs) const {
const RowElements &a = this->m_row_elements;
const ColElements &b = this->m_col_elements;
const size_t na = a.size();
const size_t nb = b.size();
CHECK(lhs.size() == na, "lhs size is inconsistent");
CHECK(rhs.size() == nb, "rhs size is inconsistent");
#ifdef HAVE_OPENMP
#pragma omp parallel for
#endif
for (size_t i = 0; i < na; ++i) {
const_row_reference ai = a[i];
for (size_t j = 0; j < nb; ++j) {
const_col_reference bj = b[j];
lhs[i] += this->m_function(ai, bj) * rhs[j];
}
}
}
};
template <typename RowElements, typename ColElements, typename F>
class KernelMatrix : public KernelBase<RowElements, ColElements, F> {
protected:
typedef KernelBase<RowElements, ColElements, F> base_type;
static const unsigned int dimension = base_type::dimension;
typedef typename base_type::double_d double_d;
typedef typename base_type::int_d int_d;
typedef typename base_type::const_row_reference const_row_reference;
typedef typename base_type::const_col_reference const_col_reference;
typedef Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic> matrix_type;
matrix_type m_matrix;
public:
typedef typename base_type::Scalar Scalar;
typedef typename base_type::Block Block;
static const size_t BlockRows = base_type::BlockRows;
static const size_t BlockCols = base_type::BlockCols;
KernelMatrix(const RowElements &row_elements, const ColElements &col_elements,
const F &function)
: base_type(row_elements, col_elements, function) {
assemble_matrix();
};
void assemble_matrix() {
const RowElements &a = this->m_row_elements;
const ColElements &b = this->m_col_elements;
m_matrix.resize(this->rows(), this->cols());
for (size_t i = 0; i < a.size(); ++i) {
const_row_reference ai = a[i];
for (size_t j = 0; j < b.size(); ++j) {
const_col_reference bj = b[j];
m_matrix.template block<BlockRows, BlockCols>(i * BlockRows,
j * BlockCols) =
static_cast<Block>(this->m_function(ai, bj));
}
}
}
Scalar coeff(const size_t i, const size_t j) const { return m_matrix(i, j); }
template <typename MatrixType> void assemble(const MatrixType &matrix) const {
const_cast<MatrixType &>(matrix) = m_matrix;
}
/// Evaluates a matrix-free linear operator given by \p expr \p if_expr,
/// and particle sets \p a and \p b on a vector rhs and
/// accumulates the result in vector lhs
template <typename LHSType, typename RHSType>
void evaluate(std::vector<LHSType> &lhs,
const std::vector<RHSType> &rhs) const {
const RowElements &a = this->m_row_elements;
const ColElements &b = this->m_col_elements;
const size_t na = a.size();
const size_t nb = b.size();
ASSERT(lhs.size() == na, "lhs size is inconsistent");
ASSERT(rhs.size() == nb, "rhs size is inconsistent");
#ifdef HAVE_OPENMP
#pragma omp parallel for
#endif
for (size_t i = 0; i < na; ++i) {
for (size_t j = 0; j < nb; ++j) {
lhs[i] += m_matrix.template block<BlockRows, BlockCols>(i * BlockRows,
j * BlockCols) *
rhs[j];
}
}
}
/// Evaluates a matrix-free linear operator given by \p expr \p if_expr,
/// and particle sets \p a and \p b on a vector rhs and
/// accumulates the result in vector lhs
template <typename DerivedLHS, typename DerivedRHS>
void evaluate(Eigen::DenseBase<DerivedLHS> &lhs,
const Eigen::DenseBase<DerivedRHS> &rhs) const {
ASSERT(lhs.size() == this->rows(), "lhs size not consistent")
ASSERT(rhs.size() == this->cols(), "lhs size not consistent")
lhs += m_matrix * rhs;
}
};
template <typename RowElements, typename ColElements, typename PositionF,
size_t QuadratureOrder = 8,
typename F =
detail::position_kernel<RowElements, ColElements, PositionF>>
class KernelChebyshev : public KernelDense<RowElements, ColElements, F> {
typedef KernelDense<RowElements, ColElements, F> base_type;
typedef typename base_type::double_d double_d;
typedef typename base_type::int_d int_d;
typedef typename base_type::const_position_reference const_position_reference;
typedef typename base_type::const_row_reference const_row_reference;
typedef typename base_type::const_col_reference const_col_reference;
typedef Eigen::Matrix<double, Eigen::Dynamic, Eigen::Dynamic> matrix_type;
typedef Eigen::Matrix<double, Eigen::Dynamic, 1> vector_type;
typedef Eigen::Map<vector_type> map_type;
static const unsigned int dimension = base_type::dimension;
matrix_type m_col_Rn_matrix, m_row_Rn_matrix, m_kernel_matrix;
unsigned int m_order;
unsigned int m_ncheb;
const int_d m_start;
const int_d m_end;
PositionF m_position_function;
mutable vector_type m_W;
mutable vector_type m_fcheb;
public:
typedef typename base_type::Scalar Scalar;
typedef typename base_type::Block Block;
static const size_t BlockRows = base_type::BlockRows;
static const size_t BlockCols = base_type::BlockCols;
KernelChebyshev(const RowElements &row_elements,
const ColElements &col_elements, const unsigned int n,
const PositionF &function)
: base_type(row_elements, col_elements, F(function)), m_order(n),
m_ncheb(std::pow(n, dimension)), m_start(int_d::Constant(0)),
m_end(int_d::Constant(n)), m_position_function(function) {
set_n(n);
};
void set_n(const unsigned int n) {
m_order = n;
m_ncheb = std::pow(n, dimension);
m_W.resize(m_ncheb * BlockCols);
m_fcheb.resize(m_ncheb * BlockRows);
update_row_positions();
update_col_positions();
update_kernel_matrix();
}
void update_row_positions() {
bbox<dimension> row_box(this->m_row_elements.get_min(),
this->m_row_elements.get_max());
detail::integrate_chebyshev<RowElements, BlockRows, QuadratureOrder>
integrate(this->m_row_elements, m_order, row_box);
// fill row_Rn matrix
m_row_Rn_matrix.resize(this->m_row_elements.size() * BlockRows,
m_ncheb * BlockRows);
integrate(m_row_Rn_matrix);
}
void update_kernel_matrix() {
bbox<dimension> row_box(this->m_row_elements.get_min(),
this->m_row_elements.get_max());
bbox<dimension> col_box(this->m_col_elements.get_min(),
this->m_col_elements.get_max());
detail::ChebyshevRn<dimension> col_Rn(m_order, row_box);
detail::ChebyshevRn<dimension> row_Rn(m_order, col_box);
// fill kernel matrix
m_kernel_matrix.resize(m_ncheb * BlockRows, m_ncheb * BlockCols);
lattice_iterator<dimension> mi(m_start, m_end);
for (size_t i = 0; i < m_ncheb; ++i, ++mi) {
const double_d pi = col_Rn.get_position(*mi);
lattice_iterator<dimension> mj(m_start, m_end);
for (size_t j = 0; j < m_ncheb; ++j, ++mj) {
const double_d pj = row_Rn.get_position(*mj);
m_kernel_matrix.template block<BlockRows, BlockCols>(i * BlockRows,
j * BlockCols) =
static_cast<Block>(m_position_function(pi, pj));
}
}
}
void update_col_positions() {
bbox<dimension> col_box(this->m_col_elements.get_min(),
this->m_col_elements.get_max());
detail::integrate_chebyshev<ColElements, BlockCols, QuadratureOrder>
integrate(this->m_col_elements, m_order, col_box);
// fill row_Rn matrix
m_col_Rn_matrix.resize(this->m_col_elements.size() * BlockCols,
m_ncheb * BlockCols);
integrate(m_col_Rn_matrix);
}
/// Evaluates a matrix-free linear operator given by \p expr \p if_expr,
/// and particle sets \p a and \p b on a vector rhs and
/// accumulates the result in vector lhs
template <typename DerivedLHS, typename DerivedRHS>
void evaluate(Eigen::DenseBase<DerivedLHS> &lhs,
const Eigen::DenseBase<DerivedRHS> &rhs) const {
const ColElements &b = this->m_col_elements;
CHECK(!b.get_periodic().any(), "chebyshev operator assumes not periodic");
ASSERT(static_cast<typename DerivedLHS::Index>(this->rows()) == lhs.rows(),
"lhs vector has incompatible size");
ASSERT(static_cast<typename DerivedRHS::Index>(this->cols()) == rhs.rows(),
"rhs vector has incompatible size");
// First compute the weights at the Chebyshev nodes ym
// by anterpolation
m_W = m_col_Rn_matrix.transpose() * rhs.derived();
// Next compute f ðxÞ at the Chebyshev nodes xl:
m_fcheb = m_kernel_matrix * m_W;
// Last compute f ðxÞ at the observation points xi by interpolation:
lhs = m_row_Rn_matrix * m_fcheb;
}
};
#ifdef HAVE_H2LIB
template <typename RowElements, typename ColElements, typename PositionF,
typename F>
class KernelH2 : public KernelDense<RowElements, ColElements, F> {
typedef KernelDense<RowElements, ColElements, F> base_type;
typedef typename ColElements::query_type query_type;
static const unsigned int dimension = base_type::dimension;
typedef typename detail::H2LibBlackBoxExpansions<
dimension, PositionF, base_type::BlockRows, base_type::BlockCols>
expansions_type;
typedef H2LibMatrix h2_matrix_type;
PositionF m_position_function;
h2_matrix_type m_h2_matrix;
public:
typedef typename base_type::Block Block;
typedef typename base_type::Scalar Scalar;
static const size_t BlockRows = base_type::BlockRows;
static const size_t BlockCols = base_type::BlockCols;
static_assert(detail::is_particles<RowElements>::value &&
detail::is_particles<ColElements>::value,
"only implemented for particle elements");
KernelH2(const RowElements &row_elements, const ColElements &col_elements,
const int order, const PositionF &position_function,
const F &function, const double eta)
: base_type(row_elements, col_elements, function),
m_position_function(position_function),
m_h2_matrix(row_elements, col_elements,
expansions_type(order, position_function), function, eta) {}
const h2_matrix_type &get_h2_matrix() const { return m_h2_matrix; }
const PositionF &get_position_function() const { return m_position_function; }
void compress(const double tol) { m_h2_matrix.compress(tol); }
/// Evaluates a h2 matrix linear operator given by \p expr \p if_expr,
/// and particle sets \p a and \p b on a vector rhs and
/// accumulates the result in vector lhs
template <typename VectorLHS, typename VectorRHS>
void evaluate(VectorLHS &lhs, const VectorRHS &rhs) const {
m_h2_matrix.matrix_vector_multiply(lhs, 1.0, false, rhs);
}
};
#endif
template <typename RowElements, typename ColElements, typename PositionF,
typename F, unsigned int N>
class KernelFMM : public KernelDense<RowElements, ColElements, F> {
typedef KernelDense<RowElements, ColElements, F> base_type;
typedef typename base_type::position position;
typedef typename base_type::double_d double_d;
typedef typename base_type::int_d int_d;
typedef typename base_type::const_position_reference const_position_reference;
typedef typename base_type::const_row_reference const_row_reference;
typedef typename base_type::const_col_reference const_col_reference;
typedef typename ColElements::query_type query_type;
static const unsigned int dimension = base_type::dimension;
typedef typename detail::BlackBoxExpansions<
dimension, N, PositionF, base_type::BlockRows, base_type::BlockCols>
expansions_type;
typedef FastMultipoleMethod<expansions_type, F, RowElements, ColElements>
fmm_type;
expansions_type m_expansions;
fmm_type m_fmm;
public:
typedef typename base_type::Block Block;
typedef typename base_type::Scalar Scalar;
static const size_t BlockRows = base_type::BlockRows;
static const size_t BlockCols = base_type::BlockCols;
static_assert(detail::is_particles<RowElements>::value &&
detail::is_particles<ColElements>::value,
"only implemented for particle elements");
KernelFMM(const RowElements &row_elements, const ColElements &col_elements,
const PositionF &position_function, const F &function)
: base_type(row_elements, col_elements, function),
m_expansions(position_function),
m_fmm(row_elements, col_elements, m_expansions, function){};
/// Evaluates a matrix-free linear operator given by \p expr \p if_expr,
/// and particle sets \p a and \p b on a vector rhs and
/// accumulates the result in vector lhs
template <typename VectorLHS, typename VectorRHS>
void evaluate(VectorLHS &lhs, const VectorRHS &rhs) const {
m_fmm.matrix_vector_multiply(lhs, rhs);
}
};
template <typename RowElements, typename ColElements, typename FRadius,
typename FWithDx,
typename F =
detail::sparse_kernel<RowElements, ColElements, FRadius, FWithDx>>
class KernelSparse : public KernelBase<RowElements, ColElements, F> {
protected:
typedef KernelBase<RowElements, ColElements, F> base_type;
typedef typename base_type::position position;
typedef typename base_type::double_d double_d;
typedef typename base_type::const_position_reference const_position_reference;
typedef typename base_type::const_row_reference const_row_reference;
typedef typename base_type::const_col_reference const_col_reference;
static_assert(detail::is_particles<RowElements>::value &&
detail::is_particles<ColElements>::value,
"only implemented for particle elements");
FRadius m_radius_function;
FWithDx m_dx_function;
public:
typedef typename base_type::Block Block;
typedef typename base_type::Scalar Scalar;
static const size_t BlockRows = base_type::BlockRows;
static const size_t BlockCols = base_type::BlockCols;
KernelSparse(const RowElements &row_elements, const ColElements &col_elements,
const FRadius &radius_function, const FWithDx &withdx_function)
: base_type(row_elements, col_elements,
F(col_elements, radius_function, withdx_function)),
m_radius_function(radius_function), m_dx_function(withdx_function){};
/*
* shouldn't need this anymore....
Block coeff(const size_t i, const size_t j) const {
const int pi = std::floor(static_cast<float>(i)/BlockRows);
const int ioffset = i - pi*BlockRows;
const int pj = std::floor(static_cast<float>(j)/BlockCols);
const int joffset = j - pj*BlockCols;
ASSERT(pi < this->m_row_elements.size(),"pi greater than a.size()");
ASSERT(pj < this->m_col_elements.size(),"pj greater than b.size()");
const_row_reference ai = this->m_row_elements[pi];
const_col_reference bj = this->m_col_elements[pj];
const_position_reference dx = get<position>(bj)-get<position>(ai);
if (dx.squaredNorm() < std::pow(m_radius_function(ai),2)) {
return this->m_function(dx,ai,bj)(ioffset,joffset);
} else {
return 0.0;
}
}
*/
template <typename MatrixType> void assemble(const MatrixType &matrix) const {
const RowElements &a = this->m_row_elements;
const ColElements &b = this->m_col_elements;
const size_t na = a.size();
const_cast<MatrixType &>(matrix).setZero();
// sparse a x b block
for (size_t i = 0; i < na; ++i) {
const_row_reference ai = a[i];
const double radius = m_radius_function(ai);
for (auto pairj =
euclidean_search(b.get_query(), get<position>(ai), radius);
pairj != false; ++pairj) {
const_col_reference bj = *pairj;
const_position_reference dx = pairj.dx();
const size_t j = &get<position>(bj) - get<position>(b).data();
const_cast<MatrixType &>(matrix).template block<BlockRows, BlockCols>(
i * BlockRows, j * BlockCols) =
static_cast<Block>(m_dx_function(dx, ai, bj));
}
}
}
template <typename Triplet>
void assemble(std::vector<Triplet> &triplets, const size_t startI = 0,
const size_t startJ = 0) const {
const RowElements &a = this->m_row_elements;
const ColElements &b = this->m_col_elements;
const size_t na = a.size();
// sparse a x b block
// std::cout << "sparse a x b block" << std::endl;
for (size_t i = 0; i < na; ++i) {
const_row_reference ai = a[i];
const double radius = m_radius_function(ai);
for (auto pairj =
euclidean_search(b.get_query(), get<position>(ai), radius);
pairj != false; ++pairj) {
const_col_reference bj = *pairj;
const_position_reference dx = pairj.dx();
const size_t j = &get<position>(bj) - get<position>(b).data();
const Block element = static_cast<Block>(m_dx_function(dx, ai, bj));
for (size_t ii = 0; ii < BlockRows; ++ii) {
for (size_t jj = 0; jj < BlockCols; ++jj) {
triplets.push_back(Triplet(i * BlockRows + ii + startI,
j * BlockCols + jj + startJ,
element(ii, jj)));
}
}
}
}
}
/// Evaluates a matrix-free linear operator given by \p expr \p if_expr,
/// and particle sets \p a and \p b on a vector rhs and
/// accumulates the result in vector lhs
///
template <typename LHSType, typename RHSType>
void evaluate(std::vector<LHSType> &lhs,
const std::vector<RHSType> &rhs) const {
const RowElements &a = this->m_row_elements;
const ColElements &b = this->m_col_elements;
const size_t na = a.size();
ASSERT(na == rhs.size(), "lhs vector has incompatible size");
ASSERT(b.size() == lhs.size(), "rhs vector has incompatible size");
#ifdef HAVE_OPENMP
#pragma omp parallel for
#endif
for (size_t i = 0; i < na; ++i) {
const_row_reference ai = a[i];
const double radius = m_radius_function(ai);
for (auto pairj =
euclidean_search(b.get_query(), get<position>(ai), radius);
pairj != false; ++pairj) {
const_position_reference dx = pairj.dx();
const_col_reference bj = *pairj;
const size_t j = &get<position>(bj) - get<position>(b).data();
lhs[i] += m_dx_function(dx, ai, bj) * rhs[j];
}
}
}
template <typename DerivedLHS, typename DerivedRHS>
void evaluate(Eigen::DenseBase<DerivedLHS> &lhs,
const Eigen::DenseBase<DerivedRHS> &rhs) const {
ASSERT(static_cast<typename DerivedLHS::Index>(this->rows()) == lhs.rows(),
"lhs vector has incompatible size");
ASSERT(static_cast<typename DerivedRHS::Index>(this->cols()) == rhs.rows(),
"rhs vector has incompatible size");
const RowElements &a = this->m_row_elements;
const ColElements &b = this->m_col_elements;
const size_t na = a.size();
#ifdef HAVE_OPENMP
#pragma omp parallel for
#endif
for (size_t i = 0; i < na; ++i) {
const_row_reference ai = a[i];
const double radius = m_radius_function(ai);
for (auto pairj =
euclidean_search(b.get_query(), get<position>(ai), radius);
pairj != false; ++pairj) {
const_position_reference dx = pairj.dx();
const_col_reference bj = *pairj;
const size_t j = &get<position>(bj) - get<position>(b).data();
lhs.template segment<BlockRows>(i * BlockRows) +=
m_dx_function(dx, ai, bj) *
rhs.template segment<BlockCols>(j * BlockCols);
}
}
}
};
template <typename RowElements, typename ColElements, typename F,
typename RadiusFunction = detail::constant_radius<RowElements>>
class KernelSparseConst
: public KernelSparse<RowElements, ColElements, RadiusFunction, F> {
typedef KernelSparse<RowElements, ColElements, RadiusFunction, F> base_type;
typedef typename base_type::position position;
typedef typename base_type::double_d double_d;
typedef typename base_type::const_position_reference const_position_reference;
typedef typename base_type::const_row_reference const_row_reference;
typedef typename base_type::const_col_reference const_col_reference;
public:
typedef typename base_type::Block Block;
typedef typename base_type::Scalar Scalar;
static const size_t BlockRows = base_type::BlockRows;
static const size_t BlockCols = base_type::BlockCols;
KernelSparseConst(const RowElements &row_elements,
const ColElements &col_elements, const double radius,
const F &function)
: base_type(row_elements, col_elements, RadiusFunction(radius),
function) {}
};
template <typename RowElements, typename ColElements,
typename F = detail::zero_kernel<RowElements, ColElements>>
class KernelZero : public KernelBase<RowElements, ColElements, F> {
typedef KernelBase<RowElements, ColElements, F> base_type;
typedef typename base_type::position position;
typedef typename base_type::double_d double_d;
typedef typename base_type::const_position_reference const_position_reference;
typedef typename base_type::const_row_reference const_row_reference;
typedef typename base_type::const_col_reference const_col_reference;
public:
typedef typename base_type::Block Block;
typedef typename base_type::Scalar Scalar;
KernelZero(const RowElements &row_elements, const ColElements &col_elements)
: base_type(row_elements, col_elements, F()){};
template <typename MatrixType> void assemble(const MatrixType &matrix) const {
const_cast<MatrixType &>(matrix).setZero();
}
template <typename Triplet>
void assemble(std::vector<Triplet> &triplets, const size_t startI = 0,
const size_t startJ = 0) const {}
/// Evaluates a matrix-free linear operator given by \p expr \p if_expr,
/// and particle sets \p a and \p b on a vector rhs and
/// accumulates the result in vector lhs
template <typename VectorLHS, typename VectorRHS>
void evaluate(VectorLHS &lhs, const VectorRHS &rhs) const {}
};
} // namespace Aboria
#endif // HAVE_EIGEN
#endif
|
top_k_v2_op.h | /* Copyright (c) 2016 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. */
/*
The reason why we need the topk v2 is because the compatibility. We redefine
the NaN is maximum value
in the process of comparing. If do not add the topk v2, will affect the
inference result of model that traing
by the older version paddlepaddle.
*/
#pragma once
#include <algorithm>
#include <iostream>
#include <utility>
#include <vector>
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/top_k_op.h"
#include "paddle/fluid/operators/transpose_op.h"
namespace paddle {
namespace operators {
inline void GetDims(const framework::DDim& dim, int axis, int* pre, int* n,
int* post) {
*pre = 1;
*post = 1;
*n = dim[axis];
for (int i = 0; i < axis; ++i) {
(*pre) *= dim[i];
}
for (int i = axis + 1; i < dim.size(); ++i) {
(*post) *= dim[i];
}
}
template <typename T, typename Type>
static void FullTopK(Type input_height, Type input_width, int input_dim,
const framework::Tensor* input, T* t_out, Type* t_indices,
const int& k, const bool& largest, const bool& sorted) {
// when the k is small, will the partial sort
bool partial_sort_flag = (k * 64) < input_width;
#ifdef PADDLE_WITH_MKLML
#pragma omp parallel for
#endif
// Eigen::DSizes<int, 2> flat2dims(input_height, input_width);
for (Type i = 0; i < input_height; ++i) {
std::vector<std::pair<T, Type>> col_vec;
col_vec.reserve(input_width);
if (input_dim == 1) {
auto e_input = framework::EigenVector<T>::Flatten(*input);
for (Type j = 0; j < input_width; ++j) {
col_vec.emplace_back(std::pair<T, Type>(e_input(j), j));
}
} else {
auto e_input = framework::EigenMatrix<T>::Reshape(*input, input_dim - 1);
for (Type j = 0; j < input_width; ++j) {
col_vec.emplace_back(std::pair<T, Type>(e_input(i, j), j));
}
}
if (partial_sort_flag) {
std::partial_sort(
col_vec.begin(), col_vec.begin() + k, col_vec.end(),
[&largest](const std::pair<T, Type>& l, const std::pair<T, Type>& r) {
if (largest) {
return (std::isnan(static_cast<double>(l.first)) &&
!std::isnan(static_cast<double>(r.first))) ||
(l.first > r.first);
} else {
return (!std::isnan(static_cast<double>(l.first)) &&
std::isnan(static_cast<double>(r.first))) ||
(l.first < r.first);
}
});
} else {
// use the nth-element to get the K-larger or K-small element
if (largest) {
std::nth_element(
col_vec.begin(), col_vec.begin() + k - 1, col_vec.end(),
[](const std::pair<T, Type>& l, const std::pair<T, Type>& r) {
return (std::isnan(static_cast<double>(l.first)) &&
!std::isnan(static_cast<double>(r.first))) ||
(l.first > r.first);
});
// the nth-element will get the unorder elements, sort the element
if (sorted) {
std::sort(col_vec.begin(), col_vec.begin() + k - 1,
[&largest](const std::pair<T, Type>& l,
const std::pair<T, Type>& r) {
return (std::isnan(static_cast<double>(l.first)) &&
!std::isnan(static_cast<double>(r.first))) ||
(l.first > r.first);
});
}
} else {
std::nth_element(
col_vec.begin(), col_vec.begin() + k - 1, col_vec.end(),
[](const std::pair<T, Type>& l, const std::pair<T, Type>& r) {
return (!std::isnan(static_cast<double>(l.first)) &&
std::isnan(static_cast<double>(r.first))) ||
(l.first < r.first);
});
// the nth-element will get the unorder elements, sort the element
if (sorted) {
std::sort(
col_vec.begin(), col_vec.begin() + k - 1,
[](const std::pair<T, Type>& l, const std::pair<T, Type>& r) {
return (!std::isnan(static_cast<double>(l.first)) &&
std::isnan(static_cast<double>(r.first))) ||
(l.first < r.first);
});
}
}
}
for (Type j = 0; j < k; ++j) {
t_out[i * k + j] = col_vec[j].first;
t_indices[i * k + j] = col_vec[j].second;
}
}
}
template <typename T, typename Type>
static void FullTopKAssign(const Type& input_height, const Type& input_width,
const int& input_dim, const framework::Tensor* input,
const framework::Tensor* indices, T* output_data,
const int& k) {
#ifdef PADDLE_WITH_MKLML
#pragma omp parallel for
#endif
for (Type i = 0; i < input_height; ++i) {
if (input_dim == 1) {
auto e_input = framework::EigenVector<T>::Flatten(*input);
auto e_indices = framework::EigenVector<Type>::Flatten(*indices);
for (Type j = 0; j < k; ++j) {
output_data[i * input_width + e_indices(j)] = e_input(j);
}
} else {
auto e_input = framework::EigenMatrix<T>::Reshape(*input, input_dim - 1);
auto e_indices =
framework::EigenMatrix<Type>::Reshape(*indices, input_dim - 1);
for (Type j = 0; j < k; ++j) {
output_data[i * input_width + e_indices(i, j)] = e_input(i, j);
}
}
}
}
template <typename DeviceContext, typename T>
class TopkV2Kernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& context) const override {
// Get the top k elements of each row of input tensor
auto* input = context.Input<Tensor>("X");
auto* output = context.Output<Tensor>("Out");
auto* indices = context.Output<Tensor>("Indices");
const auto& in_dims = input->dims();
int k = static_cast<int>(context.Attr<int>("k"));
const auto& sorted = static_cast<bool>(context.Attr<bool>("sorted"));
const auto& largest = static_cast<bool>(context.Attr<bool>("largest"));
// axis < 0, cacluate the real axis
int axis = static_cast<int>(context.Attr<int>("axis"));
if (axis < 0) axis += in_dims.size();
// if K tensor is not null, will the use K tesnor as k
auto* k_t = context.Input<Tensor>("K");
if (k_t) {
k = k_t->data<int>()[0];
framework::DDim output_dims = output->dims();
// accroding to axis to set K value in the dim
output_dims[axis] = k;
output->Resize(output_dims);
indices->Resize(output_dims);
}
T* output_data = output->mutable_data<T>(context.GetPlace());
int64_t* indices_data = indices->mutable_data<int64_t>(context.GetPlace());
const auto& out_dims = output->dims();
if (axis + 1 == in_dims.size()) {
const int64_t& input_height =
phi::product(phi::slice_ddim(in_dims, 0, in_dims.size() - 1));
const int64_t& input_width = in_dims[in_dims.size() - 1];
FullTopK<T, int64_t>(input_height, input_width, in_dims.size(), input,
output_data, indices_data, k, largest, sorted);
} else {
// if the topk dims is not last dim, will tranpose and do topk
std::vector<int> trans;
for (int i = 0; i < axis; i++) {
trans.emplace_back(i);
}
trans.push_back(in_dims.size() - 1);
for (int i = axis + 1; i < in_dims.size() - 1; i++) {
trans.emplace_back(i);
}
trans.emplace_back(axis);
// get the trans input_dims, out_dims
framework::DDim trans_dims(in_dims);
framework::DDim trans_out_dims(output->dims());
for (size_t i = 0; i < trans.size(); i++) {
trans_dims[i] = in_dims[trans[i]];
}
for (size_t i = 0; i < trans.size(); i++) {
trans_out_dims[i] = out_dims[trans[i]];
}
Tensor trans_inp;
trans_inp.mutable_data<T>(trans_dims, context.GetPlace());
int ndims = trans.size();
auto& dev_context =
context.template device_context<platform::CPUDeviceContext>();
// transpose the input value
TransCompute<platform::CPUDeviceContext, T>(ndims, dev_context, *input,
&trans_inp, trans);
const int64_t input_height =
phi::product(phi::slice_ddim(trans_dims, 0, trans_dims.size() - 1));
const int64_t input_width = trans_dims[trans_dims.size() - 1];
// Allocate the temp tensor to the save the topk indices, values
Tensor tmp_out;
T* t_out = tmp_out.mutable_data<T>(trans_out_dims, context.GetPlace());
Tensor tmp_indices;
auto* t_ind =
tmp_indices.mutable_data<int64_t>(trans_out_dims, context.GetPlace());
// get the TopK value
FullTopK<T, int64_t>(input_height, input_width, in_dims.size(),
&trans_inp, t_out, t_ind, k, largest, sorted);
// transpose back
TransCompute<platform::CPUDeviceContext, int64_t>(
ndims, dev_context, tmp_indices, indices, trans);
TransCompute<platform::CPUDeviceContext, T>(ndims, dev_context, tmp_out,
output, trans);
}
}
};
template <typename DeviceContext, typename T>
class TopkV2GradKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& context) const override {
auto* x = context.Input<Tensor>("X");
auto* out_grad = context.Input<Tensor>(framework::GradVarName("Out"));
auto* indices = context.Input<Tensor>("Indices");
auto* x_grad = context.Output<Tensor>(framework::GradVarName("X"));
int axis = static_cast<int>(context.Attr<int>("axis"));
const auto& in_dims = x->dims();
const auto& out_dims = indices->dims();
// axis < 0, get the real axis
axis = (axis < 0) ? (in_dims.size() + axis) : axis;
const size_t& k = out_dims[axis];
T* x_grad_data = x_grad->mutable_data<T>(context.GetPlace());
if (axis + 1 == in_dims.size()) {
// allocate the memory for the input_grad
// assign the out_grad to input_grad directly
const int64_t input_height =
phi::product(phi::slice_ddim(in_dims, 0, in_dims.size() - 1));
const int64_t input_width = in_dims[in_dims.size() - 1];
// init the output grad with 0, because some input elements has no grad
memset(x_grad_data, 0, x_grad->numel() * sizeof(T));
// Assign the output_grad to input_grad
FullTopKAssign(input_height, input_width, in_dims.size(), out_grad,
indices, x_grad_data, k);
} else {
// can not assign grad to input_grad, must do the transpose
std::vector<int> trans;
for (int i = 0; i < axis; i++) {
trans.emplace_back(i);
}
trans.emplace_back(out_dims.size() - 1);
for (int i = axis + 1; i < out_dims.size() - 1; i++) {
trans.emplace_back(i);
}
trans.emplace_back(axis);
framework::DDim trans_dims(out_dims);
framework::DDim trans_in_dims(in_dims);
for (size_t i = 0; i < trans.size(); i++) {
trans_dims[i] = out_dims[trans[i]];
trans_in_dims[i] = in_dims[trans[i]];
}
// transpose the out_grad, indices
Tensor trans_dO;
trans_dO.mutable_data<T>(trans_dims, context.GetPlace());
Tensor trans_ind;
trans_ind.mutable_data<int64_t>(trans_dims, context.GetPlace());
int ndims = trans.size();
auto& dev_context =
context.template device_context<platform::CPUDeviceContext>();
// Do transpose
TransCompute<platform::CPUDeviceContext, T>(ndims, dev_context, *out_grad,
&trans_dO, trans);
TransCompute<platform::CPUDeviceContext, int64_t>(
ndims, dev_context, *indices, &trans_ind, trans);
const int64_t input_height = phi::product(
phi::slice_ddim(trans_in_dims, 0, trans_in_dims.size() - 1));
const int64_t input_width = trans_in_dims[trans_in_dims.size() - 1];
// Assign the out_grad to tranpose input_grad
Tensor tmp_out;
T* t_out = tmp_out.mutable_data<T>(trans_in_dims, context.GetPlace());
memset(t_out, 0, x_grad->numel() * sizeof(T));
FullTopKAssign<T, int64_t>(input_height, input_width, in_dims.size(),
&trans_dO, &trans_ind, t_out, k);
// Transpose back
TransCompute<platform::CPUDeviceContext, T>(ndims, dev_context, tmp_out,
x_grad, trans);
}
}
};
} // namespace operators
} // namespace paddle
|
Example_task_dep.9.c | /*
* @@name: task_dep.6c
* @@type: C
* @@compilable: yes
* @@linkable: yes
* @@expect: success
* @@version: omp_5.0
*/
#include <stdio.h>
int main()
{
int a, b, c, d;
#pragma omp parallel
#pragma omp single
{
#pragma omp task depend(out: c)
c = 1; /* Task T1 */
#pragma omp task depend(out: a)
a = 2; /* Task T2 */
#pragma omp task depend(out: b)
b = 3; /* Task T3 */
#pragma omp task depend(in: a) depend(mutexinoutset: c)
c += a; /* Task T4 */
#pragma omp task depend(in: b) depend(mutexinoutset: c)
c += b; /* Task T5 */
#pragma omp task depend(in: c)
d = c; /* Task T6 */
}
printf("%d\n", d);
return 0;
}
|
DRB114-if-orig-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.
*/
/*
When if() evalutes to true, this program has data races due to true dependence within the loop at 65.
Data race pair: a[i+1]@66:5 vs. a[i]@66:12
*/
#include "omprace.h"
#include <omp.h>
#include <stdlib.h>
#include <stdio.h>
#include <time.h>
int main(int argc, char* argv[])
{
omprace_init();
int i;
int len=100;
int a[100];
for (i=0;i<len;i++)
a[i]=i;
srand(time(NULL));
#pragma omp parallel for //if (rand()%2)
for (i=0;i<len-1;i++)
a[i+1]=a[i]+1;
printf("a[50]=%d\n", a[50]);
omprace_fini();
return 0;
}
|
reader.c | #include <stdio.h>
#include <stdlib.h>
#include <complex.h>
#include <math.h>
#include <omp.h>
#include <time.h>
#include "utils.h"
#include "reader.h"
#define PI 3.14159265358979323846
#define c 0.262465831
WAVECAR* wcopen(char* f, int type) {
WAVECAR* wc = (WAVECAR*) malloc(sizeof(WAVECAR));
if (type == 0) {
wc->type = 0;
wc->fp = fopen(f, "rb");
wc->start = NULL;
wc->curr = NULL;
} else {
wc->type = 1;
wc->fp = NULL;
wc->start = f;
wc->curr = f;
}
return wc;
}
void wcseek(WAVECAR* wc, long loc) {
if (wc->type == 0) {
fseek(wc->fp, loc, SEEK_SET);
} else {
wc->curr = wc->start + loc;
}
}
void wcread(void* ptr0, long size, long nmemb, WAVECAR* wc) {
if (wc->type == 0) {
fread(ptr0, size, nmemb, wc->fp);
} else {
char* ptr = (char*) ptr0;
for (int i = 0; i < size * nmemb; i++) {
ptr[i] = wc->curr[i];
}
}
}
void wcclose(WAVECAR* wc) {
if (wc->type == 0) {
fclose(wc->fp);
}
free(wc);
}
void setup(int nspin, int nwk, int nband,
double* nb1, double* nb2, double* nb3, int* np, double encut,
double* lattice, double* reclattice) {
vcross(reclattice+0, lattice+3, lattice+6);
vcross(reclattice+3, lattice+6, lattice+0);
vcross(reclattice+6, lattice+0, lattice+3);
double Vcell = determinant(lattice);
for (int i = 0; i < 9; i++) {
reclattice[i] *= 2.0 * PI / Vcell;
}
double magb1 = mag(reclattice+0);
double magb2 = mag(reclattice+3);
double magb3 = mag(reclattice+6);
double vtemp[3];
double vmag, sinphi123;
double phi12 = acos(dot(reclattice+0, reclattice+3) / (magb1 * magb2));
vcross(vtemp, reclattice+0, reclattice+3);
vmag = mag(vtemp);
sinphi123 = dot(reclattice+6, vtemp) / (vmag * magb3);
double nb1maxA = pow(encut*c,0.5) / (magb1 * fabs(sin(phi12))) + 1;
double nb2maxA = pow(encut*c,0.5) / (magb2 * fabs(sin(phi12))) + 1;
double nb3maxA = pow(encut*c,0.5) / (magb3 * fabs(sinphi123)) + 1;
//printf("%lf %lf %lf %lf %lf %lf\n", sin(phi12), pow(encut*c,0.5),
// phi12, vmag, sinphi123, magb3*abs(sinphi123));
int npmaxA = (int) round(4.0/3.0*PI*nb1maxA*nb2maxA*nb3maxA);
double phi13 = acos(dot(reclattice+0, reclattice+6) / (magb1 * magb3));
vcross(vtemp, reclattice+0, reclattice+6);
vmag = mag(vtemp);
sinphi123 = dot(reclattice+3, vtemp) / (vmag * magb2);
double nb1maxB = pow(encut*c,0.5) / (magb1 * fabs(sin(phi13))) + 1;
double nb2maxB = pow(encut*c,0.5) / (magb2 * fabs(sinphi123)) + 1;
double nb3maxB = pow(encut*c,0.5) / (magb3 * fabs(sin(phi13))) + 1;
int npmaxB = (int) round(4.0/3.0*PI*nb1maxB*nb2maxB*nb3maxB);
double phi23 = acos(dot(reclattice+6, reclattice+3) / (magb3 * magb2));
vcross(vtemp, reclattice+3, reclattice+6);
vmag = mag(vtemp);
sinphi123 = dot(reclattice+0, vtemp) / (vmag * magb1);
double nb1maxC = pow(encut*c,0.5) / (magb1 * fabs(sinphi123)) + 1;
double nb2maxC = pow(encut*c,0.5) / (magb2 * fabs(sin(phi23))) + 1;
double nb3maxC = pow(encut*c,0.5) / (magb3 * fabs(sin(phi23))) + 1;
int npmaxC = (int) round(4.0/3.0*PI*nb1maxC*nb2maxC*nb3maxC);
double nb1max = fmax(nb1maxA, fmax(nb1maxB, nb1maxC));
double nb2max = fmax(nb2maxA, fmax(nb2maxB, nb2maxC));
double nb3max = fmax(nb3maxA, fmax(nb3maxB, nb3maxC));
//printf("%lf %lf %lf\n", nb1maxA, nb2maxA, nb3maxA);
//printf("%lf %lf %lf\n", nb1maxB, nb2maxB, nb3maxB);
//printf("%lf %lf %lf\n", nb1maxC, nb2maxC, nb3maxC);
int npmax = npmaxA;
if (npmaxB < npmax) npmax = npmaxB;
if (npmaxC < npmax) npmax = npmaxC;
//printf("spin k band %d %d %d\n", nspin, nwk, nband);
//printf(" %lf %lf %lf\n", lattice[0], lattice[1], lattice[2]);
//printf(" %lf %lf %lf\n", lattice[3], lattice[4], lattice[5]);
//printf(" %lf %lf %lf\n", lattice[6], lattice[7], lattice[8]);
//printf(" %lf %lf %lf\n", reclattice[0], reclattice[1], reclattice[2]);
//printf(" %lf %lf %lf\n", reclattice[3], reclattice[4], reclattice[5]);
//printf(" %lf %lf %lf\n", reclattice[6], reclattice[7], reclattice[8]);
//printf("\n %lf %lf %lf %d %d %d\n", nb1max, nb2max, nb3max, npmaxA, npmaxB, npmaxC);
*np = npmax;
*nb1 = nb1max;
*nb2 = nb2max;
*nb3 = nb3max;
}
pswf_t* read_wavecar(WAVECAR* wc, double* kpt_weights) {
int nrecli, nspin, nwk, nband, nprec;
double nb1max, nb2max, nb3max, encut;
int npmax;
double* lattice = (double*) malloc(9*sizeof(double));
double* reclattice = (double*) malloc(9*sizeof(double));
double readin[3];
double* ptr = readin;
wcread(ptr,24,1,wc);
//fread(ptr,24,1,wc->fp);
nrecli = (int) round(readin[0]);
nspin = (int) round(readin[1]);
nprec = (int) round(readin[2]);
long nrecl = (long)nrecli;
double readarr[nrecl/8];
ptr = readarr;
wcseek(wc,1*nrecl);
wcread(ptr,nrecl,1,wc);
//fseek(wc->fp,1*nrecl,0);
//fread(ptr,nrecl,1,wc->fp);
nwk = (int) round(readarr[0]);
nband = (int) round(readarr[1]);
encut = readarr[2];
for (int i = 0; i < 9; i++) {
lattice[i] = readarr[i+3];
}
setup(nspin, nwk, nband, &nb1max, &nb2max, &nb3max,
&npmax, encut, lattice, reclattice);
double* b1 = reclattice;
double* b2 = reclattice+3;
double* b3 = reclattice+6;
pswf_t* wf = (pswf_t*) malloc(sizeof(pswf_t));
wf->num_sites = 0;
wf->nspin = nspin;
wf->nwk = nwk;
wf->nband = nband;
wf->is_ncl = 0;
wf->dcoords = NULL;
wf->fftg = NULL;
wf->overlaps = NULL;
wf->num_projs = NULL;
kpoint_t** kpts = (kpoint_t**) malloc(nwk*nspin*sizeof(kpoint_t*));
if (kpts == NULL) {
ALLOCATION_FAILED();
}
wf->kpts = kpts;
wf->lattice = lattice;
wf->reclattice = reclattice;
wf->G_bounds = (int*) calloc(6, sizeof(int));
double* kptr = (double*) malloc(nrecl);
float complex* cptr = (float complex*) malloc(nrecl);
//#pragma omp parallel for
for (int iwk = 0; iwk < nwk * nspin; iwk++) {
long irec = iwk * (long)(1 + nband);
kpoint_t* kpt = (kpoint_t*) malloc(sizeof(kpoint_t));
kpt->expansion = NULL;
kpt->num_bands = nband;
band_t** bands = (band_t**) malloc(nband*sizeof(band_t*));
kpt->bands = bands;
if (kpt == NULL || bands == NULL) {
ALLOCATION_FAILED();
}
wcseek(wc, irec*nrecl+2*nrecl);
wcread(kptr, 8, nrecl/8, wc);
//fseek(wc->fp, irec*nrecl+2*nrecl, SEEK_SET);
//fread(kptr, 8, nrecl/8, wc->fp);
int nplane = (int) round(kptr[0]);
kpt->num_waves = nplane;
int* igall = malloc(3*nplane*sizeof(int));
if (igall == NULL) {
ALLOCATION_FAILED();
}
kpt->k = (double*) malloc(3*sizeof(double));
kpt->k[0] = kptr[1];
kpt->k[1] = kptr[2];
kpt->k[2] = kptr[3];
double kx = kpt->k[0], ky = kpt->k[1], kz = kpt->k[2];
for (int i = 0; i < nband; i++) {
band_t* band = (band_t*) malloc(sizeof(band_t));
band->num_waves = nplane;
band->energy = kptr[4+i*3];
band->occ = kptr[6+i*3];
band->projections = NULL;
band->up_projections = NULL;
band->down_projections = NULL;
band->wave_projections = NULL;
band->CRs = NULL;
band->CAs = NULL;
kpt->bands[i] = band;
}
int ncnt = -1;
for (int ig3 = 0; ig3 <= 2 * nb3max; ig3++) {
int ig3p = ig3;
if (ig3 > nb3max) ig3p = ig3 - 2 * nb3max - 1;
for (int ig2 = 0; ig2 <= 2 * nb2max; ig2++) {
int ig2p = ig2;
if (ig2 > nb2max) ig2p = ig2 - 2 * nb2max - 1;
for (int ig1 = 0; ig1 <= 2 * nb1max; ig1++) {
int ig1p = ig1;
if (ig1 > nb1max) ig1p = ig1 - 2 * nb1max - 1;
double sumkg[3];
for (int j = 0; j < 3; j++) {
sumkg[j] = (kx+ig1p) * b1[j]
+ (ky+ig2p) * b2[j]
+ (kz+ig3p) * b3[j];
}
double gtot = mag(sumkg);
double etot = pow(gtot,2.0) / c;
//printf("%lf %lf\n", etot, gtot);
if (etot <= encut) {
ncnt++;
igall[ncnt*3+0] = ig1p;
igall[ncnt*3+1] = ig2p;
igall[ncnt*3+2] = ig3p;
if (ig1p < wf->G_bounds[0]) wf->G_bounds[0] = ig1p;
else if (ig1p > wf->G_bounds[1]) wf->G_bounds[1] = ig1p;
if (ig2p < wf->G_bounds[2]) wf->G_bounds[2] = ig2p;
else if (ig2p > wf->G_bounds[3]) wf->G_bounds[3] = ig2p;
if (ig3p < wf->G_bounds[4]) wf->G_bounds[4] = ig3p;
else if (ig3p > wf->G_bounds[5]) wf->G_bounds[5] = ig3p;
}
}
}
}
ncnt++;
if (ncnt * 2 == nplane) {
//printf("This is an NCL wavefunction!\n");
wf->is_ncl = 1;
for (int iplane = 0; iplane < nplane/2; iplane++) {
igall[3*(nplane/2+iplane)+0] = igall[3*iplane+0];
igall[3*(nplane/2+iplane)+1] = igall[3*iplane+1];
igall[3*(nplane/2+iplane)+2] = igall[3*iplane+2];
}
} else if (ncnt != nplane) {
printf("ERROR %d %d %lf %lf %lf %lf\n", ncnt, nplane, kx,ky,kz, c);
}
//if (ncnt > npmax) printf("BIG ERROR");
//printf("%d %d\n", ncnt, npmax);
for (int iband = 0; iband < nband; iband++) {
irec++;
wcseek(wc, (long)irec*nrecl+2*(long)nrecl);
wcread(cptr, 8, nrecl/8, wc);
//fseek(wc->fp, (long)irec*nrecl+2*(long)nrecl, SEEK_SET);
//fread(cptr, 8, nrecl/8, wc->fp);
float complex* coeff = malloc(nplane*sizeof(float complex));
for (int iplane = 0; iplane < nplane; iplane++) {
coeff[iplane] = cptr[iplane];
}
kpt->bands[iband]->Cs = coeff;
}
//printf("iwk %d\n", iwk);
kpt->weight = kpt_weights[iwk%nwk];
kpt->Gs = igall;
kpts[iwk] = kpt;
}
free(kptr);
free(cptr);
wf->pps = NULL;
wf->overlaps = NULL;
wf->encut = encut;
return wf;
}
pswf_t* read_wavefunctions(char* filename, double* kpt_weights) {
setbuf(stdout,NULL);
WAVECAR* f = wcopen(filename, 0);
pswf_t* wf = read_wavecar(f, kpt_weights);
wcclose(f);
return wf;
}
pswf_t* read_wavefunctions_from_str(char* start, double* kpt_weights) {
WAVECAR* f = wcopen(start, 1);
pswf_t* wf = read_wavecar(f, kpt_weights);
wcclose(f);
return wf;
}
/*
kpoint_t** read_one_band(int* G_bounds, double* kpt_weights, int* ns, int* nk, int* nb, int BAND_NUM, char* filename) {
clock_t start = clock();
int nrecli=0, nspin=0, nwk=0, nband=0;
double nb1max=0, nb2max=0, nb3max=0, encut=0;
double lattice[9] = {0};
double reclattice[9] = {0};
setup(filename, &nrecli, &nspin, &nwk, &nband, &nb1max, &nb2max, &nb3max,
&encut, lattice, reclattice);
double* b1 = reclattice;
double* b2 = reclattice+3;
double* b3 = reclattice+6;
long nrecl = (long) nrecli;
double* kptr = (double*) malloc(nrecl);
float complex* cptr = (float complex*) malloc(nrecl);
kpoint_t** kpts = (kpoint_t**) malloc(nwk*nspin*sizeof(kpoint_t*));
//#pragma omp parallel for
for (int iwk = 0; iwk < nwk * nspin; iwk++) {
int irec = iwk * (1 + nband);
FILE* pfp = fopen(filename, "rb");
kpoint_t* kpt = (kpoint_t*) malloc(sizeof(kpoint_t));
kpt->num_bands = 1;
band_t** bands = (band_t**) malloc(sizeof(band_t*));
kpt->bands = bands;
//void* karr = malloc(nrecl);
fseek(pfp, (long)irec*nrecl+(long)2*nrecl, SEEK_SET);
//printf("reading dat %d\n", fread(kptr, 8, nrecl/8, pfp));
fread(kptr, 8, nrecl/8, pfp);
int nplane = (int) round(kptr[0]);
int* igall = malloc(3*nplane*sizeof(int));
double kx = kptr[1];
double ky = kptr[2];
double kz = kptr[3];
band_t* band = (band_t*) malloc(sizeof(band_t));
band->num_waves = nplane;
band->energy = kptr[4+BAND_NUM*3];
band->occ = kptr[6+BAND_NUM*3];
kpt->bands[0] = band;
int ncnt = -1;
for (int ig3 = 0; ig3 <= 2 * nb3max; ig3++) {
int ig3p = ig3;
if (ig3 > nb3max) ig3p = ig3 - 2 * nb3max - 1;
for (int ig2 = 0; ig2 <= 2 * nb2max; ig2++) {
int ig2p = ig2;
if (ig2 > nb2max) ig2p = ig2 - 2 * nb2max - 1;
for (int ig1 = 0; ig1 <= 2 * nb1max; ig1++) {
int ig1p = ig1;
if (ig1 > nb1max) ig1p = ig1 - 2 * nb1max - 1;
double sumkg[3];
for (int j = 0; j < 3; j++) {
sumkg[j] = (kx+ig1p) * b1[j]
+ (ky+ig2p) * b2[j]
+ (kz+ig3p) * b3[j];
}
double gtot = mag(sumkg);
double etot = pow(gtot,2.0) / c;
//printf("%lf %lf\n", etot, gtot);
if (etot <= encut) {
ncnt++;
igall[ncnt*3+0] = ig1p;
igall[ncnt*3+1] = ig2p;
igall[ncnt*3+2] = ig3p;
}
}
}
}
if (ncnt != nplane - 1) printf("ERROR %d %d", ncnt, nplane);
int iband = BAND_NUM;
irec += 1 + BAND_NUM;
fseek(pfp,(long) irec*nrecl+2*(long)nrecl, SEEK_SET);
fread(cptr, 8, nrecl/8, pfp);
float complex* coeff = malloc(nplane*sizeof(float complex));
for (int iplane = 0; iplane < nplane; iplane++) {
coeff[iplane] = cptr[iplane];
}
kpt->bands[0]->Cs = coeff;
kpt->weight = kpt_weights[iwk%nwk];
kpt->Gs = igall;
kpts[iwk] = kpt;
}
clock_t end = clock();
free(kptr);
free(cptr);
printf("%lf seconds to read defect\n", (double)(end-start) / CLOCKS_PER_SEC);
return kpts;
}
*/
|
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 *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] ;
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 *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
|
GB_unaryop__lnot_fp64_uint16.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_fp64_uint16
// op(A') function: GB_tran__lnot_fp64_uint16
// C type: double
// A type: uint16_t
// cast: double cij = (double) aij
// unaryop: cij = !(aij != 0)
#define GB_ATYPE \
uint16_t
#define GB_CTYPE \
double
// 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 != 0) ;
// casting
#define GB_CASTING(z, x) \
double z = (double) 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_FP64 || GxB_NO_UINT16)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__lnot_fp64_uint16
(
double *restrict Cx,
const uint16_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_fp64_uint16
(
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
|
omp_num_threads.c | // Skip testing on 64 bit systems for now!
#ifndef __LP64__
#include <stdio.h>
#ifdef _OPENMP
#include <omp.h>
#endif
#include "omp_testsuite.h"
int
check_omp_num_threads (FILE * logFile)
{
int failed = 0;
int max_threads = 0;
int threads;
int nthreads;
/* first we check how many threads are available */
#pragma omp parallel
{
#pragma omp master
max_threads = omp_get_num_threads ();
}
/* we increase the number of threads from one to maximum: */
for (threads = 1; threads <= max_threads; threads++)
{
nthreads = 0;
#pragma omp parallel num_threads(threads) reduction(+:failed)
{
failed = failed + !(threads == omp_get_num_threads ());
#pragma omp atomic
nthreads += 1;
}
failed = failed + !(nthreads == threads);
}
return !failed;
}
int
crosscheck_omp_num_threads (FILE * logFile)
{
int failed = 0;
int max_threads = 0;
int threads;
int nthreads;
/* first we check how many threads are available */
#pragma omp parallel
{
#pragma omp master
max_threads = omp_get_num_threads ();
}
/* we increase the number of threads from one to maximum: */
for (threads = 1; threads <= max_threads; threads++)
{
nthreads = 0;
#pragma omp parallel reduction(+:failed)
{
failed = failed + !(threads == omp_get_num_threads ());
#pragma omp atomic
nthreads += 1;
}
failed = failed + !(nthreads == threads);
}
return !failed;
}
#else
#warning "Not tested on 64 bit systems"
#endif
|
target-21.c | extern void abort (void);
union U { int x; long long y; };
struct T { int a; union U b; int c; };
struct S { int s; int u; struct T v; int x[10]; union U w; int y[10]; int z[10]; };
volatile int z;
int
main ()
{
struct S s;
s.s = 0;
s.u = 1;
s.v.a = 2;
s.v.b.y = 3LL;
s.v.c = 19;
s.w.x = 4;
s.x[0] = 7;
s.x[1] = 8;
s.y[3] = 9;
s.y[4] = 10;
s.y[5] = 11;
int err = 0;
#pragma omp target map (to:s.v.b, s.u, s.x[0:z + 2]) \
map (tofrom:s.y[3:3]) \
map (from: s.w, s.z[z + 1:z + 3], err)
{
err = 0;
if (s.u != 1 || s.v.b.y != 3LL || s.x[0] != 7 || s.x[1] != 8
|| s.y[3] != 9 || s.y[4] != 10 || s.y[5] != 11)
err = 1;
s.w.x = 6;
s.y[3] = 12;
s.y[4] = 13;
s.y[5] = 14;
s.z[1] = 15;
s.z[2] = 16;
s.z[3] = 17;
}
if (err || s.w.x != 6 || s.y[3] != 12 || s.y[4] != 13 || s.y[5] != 14
|| s.z[1] != 15 || s.z[2] != 16 || s.z[3] != 17)
abort ();
s.u++;
s.v.a++;
s.v.b.y++;
s.w.x++;
s.x[1] = 18;
s.z[0] = 19;
#pragma omp target data map (tofrom: s)
#pragma omp target map (always to: s.w, s.x[1], err) map (alloc:s.u, s.v.b, s.z[z:z + 1])
{
err = 0;
if (s.u != 2 || s.v.b.y != 4LL || s.w.x != 7 || s.x[1] != 18 || s.z[0] != 19)
err = 1;
s.w.x = 8;
s.x[1] = 20;
s.z[0] = 21;
}
if (err || s.w.x != 8 || s.x[1] != 20 || s.z[0] != 21)
abort ();
s.u++;
s.v.a++;
s.v.b.y++;
s.w.x++;
s.x[0] = 22;
s.x[1] = 23;
#pragma omp target data map (from: s.w, s.x[0:2]) map (to: s.v.b, s.u)
#pragma omp target map (always to: s.w, s.x[0:2], err) map (alloc:s.u, s.v.b)
{
err = 0;
if (s.u != 3 || s.v.b.y != 5LL || s.w.x != 9 || s.x[0] != 22 || s.x[1] != 23)
err = 1;
s.w.x = 11;
s.x[0] = 24;
s.x[1] = 25;
}
if (err || s.w.x != 11 || s.x[0] != 24 || s.x[1] != 25)
abort ();
return 0;
}
|
reciprocal_to_normal.c | /* Copyright (C) 2015 Atsushi Togo */
/* All rights reserved. */
/* This file is part of phonopy. */
/* 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 following disclaimer. */
/* * 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. */
/* * Neither the name of the phonopy project 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. */
#include "reciprocal_to_normal.h"
#include <math.h>
#include <stdlib.h>
#include "lapack_wrapper.h"
#ifdef MEASURE_R2N
#include <time.h>
#include <unistd.h>
#endif
static double get_fc3_sum(const lapack_complex_double *e0,
const lapack_complex_double *e1,
const lapack_complex_double *e2,
const lapack_complex_double *fc3_reciprocal,
const long num_band);
void reciprocal_to_normal_squared(
double *fc3_normal_squared, const long (*g_pos)[4], const long num_g_pos,
const lapack_complex_double *fc3_reciprocal, const double *freqs0,
const double *freqs1, const double *freqs2,
const lapack_complex_double *eigvecs0,
const lapack_complex_double *eigvecs1,
const lapack_complex_double *eigvecs2, const double *masses,
const long *band_indices, const long num_band,
const double cutoff_frequency, const long openmp_at_bands) {
long i, j, k, num_atom;
double real, imag;
double *inv_sqrt_masses;
lapack_complex_double *e0, *e1, *e2;
/* Transpose eigenvectors for the better data alignment in memory. */
/* Memory space for three eigenvector matrices is allocated at once */
/* to make it contiguous. */
e0 = (lapack_complex_double *)malloc(sizeof(lapack_complex_double) * 3 *
num_band * num_band);
e1 = e0 + num_band * num_band;
e2 = e1 + num_band * num_band;
for (i = 0; i < num_band; i++) {
for (j = 0; j < num_band; j++) {
e0[j * num_band + i] = eigvecs0[i * num_band + j];
e1[j * num_band + i] = eigvecs1[i * num_band + j];
e2[j * num_band + i] = eigvecs2[i * num_band + j];
}
}
/* Inverse sqrt mass is multipled with eigenvectors to reduce number of */
/* operations in get_fc3_sum. Three eigenvector matrices are looped by */
/* first loop leveraging contiguous memory layout of [e0, e1, e2]. */
num_atom = num_band / 3;
inv_sqrt_masses = (double *)malloc(sizeof(double) * num_atom);
for (i = 0; i < num_atom; i++) {
inv_sqrt_masses[i] = 1.0 / sqrt(masses[i]);
}
for (i = 0; i < 3 * num_band; i++) {
for (j = 0; j < num_atom; j++) {
for (k = 0; k < 3; k++) {
real = lapack_complex_double_real(e0[i * num_band + j * 3 + k]);
imag = lapack_complex_double_imag(e0[i * num_band + j * 3 + k]);
e0[i * num_band + j * 3 + k] = lapack_make_complex_double(
real * inv_sqrt_masses[j], imag * inv_sqrt_masses[j]);
}
}
}
free(inv_sqrt_masses);
inv_sqrt_masses = NULL;
#ifdef MEASURE_R2N
double loopTotalCPUTime, loopTotalWallTime;
time_t loopStartWallTime;
clock_t loopStartCPUTime;
#endif
#ifdef MEASURE_R2N
loopStartWallTime = time(NULL);
loopStartCPUTime = clock();
#endif
#ifdef PHPYOPENMP
#pragma omp parallel for if (openmp_at_bands)
#endif
for (i = 0; i < num_g_pos; i++) {
if (freqs0[band_indices[g_pos[i][0]]] > cutoff_frequency &&
freqs1[g_pos[i][1]] > cutoff_frequency &&
freqs2[g_pos[i][2]] > cutoff_frequency) {
fc3_normal_squared[g_pos[i][3]] =
get_fc3_sum(e0 + band_indices[g_pos[i][0]] * num_band,
e1 + g_pos[i][1] * num_band,
e2 + g_pos[i][2] * num_band, fc3_reciprocal,
num_band) /
(freqs0[band_indices[g_pos[i][0]]] * freqs1[g_pos[i][1]] *
freqs2[g_pos[i][2]]);
} else {
fc3_normal_squared[g_pos[i][3]] = 0;
}
}
#ifdef MEASURE_R2N
loopTotalCPUTime = (double)(clock() - loopStartCPUTime) / CLOCKS_PER_SEC;
loopTotalWallTime = difftime(time(NULL), loopStartWallTime);
printf(" %1.3fs (%1.3fs CPU)\n", loopTotalWallTime, loopTotalCPUTime);
#endif
free(e0);
e0 = NULL;
e1 = NULL;
e2 = NULL;
}
static double get_fc3_sum(const lapack_complex_double *e0,
const lapack_complex_double *e1,
const lapack_complex_double *e2,
const lapack_complex_double *fc3_reciprocal,
const long num_band) {
long i, j, k;
double sum_real, sum_imag;
lapack_complex_double e_01, e_012, e_012_fc3;
sum_real = 0;
sum_imag = 0;
for (i = 0; i < num_band; i++) {
for (j = 0; j < num_band; j++) {
e_01 = phonoc_complex_prod(e0[i], e1[j]);
for (k = 0; k < num_band; k++) {
e_012 = phonoc_complex_prod(e_01, e2[k]);
e_012_fc3 = phonoc_complex_prod(
e_012,
fc3_reciprocal[i * num_band * num_band + j * num_band + k]);
sum_real += lapack_complex_double_real(e_012_fc3);
sum_imag += lapack_complex_double_imag(e_012_fc3);
}
}
}
return (sum_real * sum_real + sum_imag * sum_imag);
}
|
par_strength.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)
******************************************************************************/
/******************************************************************************
*
*****************************************************************************/
/* 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_BoomerAMGCreateSHost(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_CSRMatrixMemoryLocation(S_diag) = HYPRE_MEMORY_HOST;
hypre_CSRMatrixMemoryLocation(S_offd) = HYPRE_MEMORY_HOST;
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);
}
/* ----------------------------------------------------------------------- */
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)
{
#if defined(HYPRE_USING_CUDA)
hypre_NvtxPushRange("CreateS");
#endif
HYPRE_Int ierr = 0;
#if defined(HYPRE_USING_CUDA)
HYPRE_ExecutionPolicy exec = hypre_GetExecPolicy1( hypre_CSRMatrixMemoryLocation(hypre_ParCSRMatrixDiag(A)) );
if (exec == HYPRE_EXEC_DEVICE)
{
ierr = hypre_BoomerAMGCreateSDevice(A,strength_threshold,max_row_sum,num_functions,dof_func,S_ptr);
}
else
#endif
{
ierr = hypre_BoomerAMGCreateSHost(A,strength_threshold,max_row_sum,num_functions,dof_func,S_ptr);
}
#if defined(HYPRE_USING_CUDA)
hypre_NvtxPopRange();
#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.
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 num_functions,
HYPRE_Int *dof_func,
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_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_Int *dof_func_offd = NULL;
HYPRE_Real diag, row_scale, row_sum;
HYPRE_Int i, jj, jA, jS;
HYPRE_Int num_sends, start, j, index;
HYPRE_Int *int_buf_data;
HYPRE_Int ierr = 0;
HYPRE_Int *CF_marker_offd = NULL;
HYPRE_Int *prefix_sum_workspace;
HYPRE_Int my_id;
/*--------------------------------------------------------------
* 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.
*----------------------------------------------------------------*/
hypre_MPI_Comm_rank(comm, &my_id);
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);
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;
if (num_functions > 1)
{
dof_func_offd = hypre_CTAlloc(HYPRE_Int, num_cols_offd, HYPRE_MEMORY_HOST);
}
S_offd_j = hypre_CTAlloc(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);
}
/*-------------------------------------------------------------------
* Get the CF_marker data for the off-processor columns
*-------------------------------------------------------------------*/
if (num_cols_offd) CF_marker_offd = hypre_CTAlloc(HYPRE_Int, num_cols_offd, HYPRE_MEMORY_HOST);
if (!comm_pkg)
{
hypre_MatvecCommPkgCreate(A);
comm_pkg = hypre_ParCSRMatrixCommPkg(A);
}
num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg);
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++]
= CF_marker[hypre_ParCSRCommPkgSendMapElmt(comm_pkg,j)];
}
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_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 (num_functions > 1)
{
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) && (dof_func[i] == dof_func[jj]))
{
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_offd[jj] == SMRK) && (dof_func[i] == dof_func_offd[jj]))
{
row_scale = hypre_max(row_scale, A_offd_data[jA]);
row_sum += A_offd_data[jA];
}
}
} /* 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) && (dof_func[i] == dof_func[jj]))
{
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_offd[jj] == SMRK) && (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++)
{
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_offd[jj] == SMRK) {
row_scale = hypre_max(row_scale, A_offd_data[jA]);
row_sum += A_offd_data[jA];
}
}
} /* 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) {
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_offd[jj] == SMRK) {
row_scale = hypre_min(row_scale, A_offd_data[jA]);
row_sum += A_offd_data[jA];
}
}
} /* diag >= 0*/
} /* num_functions <=1 */
/* 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;
}
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
S_temp_offd_j[jA] = -1;
}
}
else
{
if (num_functions > 1)
{
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)
|| (dof_func[i] != dof_func[jj]))
{
S_temp_diag_j[jA] = -1;
}
else
{
S_temp_diag_j[jA] = jj;
++jS_diag;
}
}
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_offd[jj] == SMRK)
{
if ((A_offd_data[jA] <= strength_threshold * row_scale)
|| (dof_func[i] != dof_func_offd[jj]))
{
S_temp_offd_j[jA] = -1;
}
else
{
S_temp_offd_j[jA] = jj;
++jS_offd;
}
}
else
{
S_temp_offd_j[jA] = -1;
}
}
} /* end 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)
|| (dof_func[i] != dof_func[jj]))
{
S_temp_diag_j[jA] = -1;
}
else
{
S_temp_diag_j[jA] = jj;
++jS_diag;
}
}
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_offd[jj] == SMRK)
{
if ((A_offd_data[jA] >= strength_threshold * row_scale)
|| (dof_func[i] != dof_func_offd[jj]))
{
S_temp_offd_j[jA] = -1;
}
else
{
S_temp_offd_j[jA] = jj;
++jS_offd;
}
}
else
{
S_temp_offd_j[jA] = -1;
}
}
} /* diag >= 0 */
} /* num_functions > 1 */
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;
}
else
{
S_temp_diag_j[jA] = jj;
++jS_diag;
}
} 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_offd[jj] == SMRK) {
if (A_offd_data[jA] <= strength_threshold * row_scale)
{
S_temp_offd_j[jA] = -1;
}
else
{
S_temp_offd_j[jA] = jj;
++jS_offd;
}
} 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;
}
else
{
S_temp_diag_j[jA] = jj;
++jS_diag;
}
} 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_offd[jj] == SMRK) {
if (A_offd_data[jA] >= strength_threshold * row_scale)
{
S_temp_offd_j[jA] = -1;
}
else
{
S_temp_offd_j[jA] = jj;
++jS_offd;
}
} else {
S_temp_offd_j[jA] = -1;
}
}
} /* diag >= 0 */
} /* num_functions <=1 */
} /* !((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;
}
for (jA = A_diag_i[i]; jA < A_diag_i[i+1]; jA++)
{
S_temp_diag_j[jA] = -1;
}
for (jA = A_offd_i[i]; jA < A_offd_i[i+1]; jA++)
{
S_temp_offd_j[jA] = -1;
}
} /* 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_CSRMatrixMemoryLocation(S_diag) = HYPRE_MEMORY_HOST;
hypre_CSRMatrixMemoryLocation(S_offd) = HYPRE_MEMORY_HOST;
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);
hypre_TFree(dof_func_offd, HYPRE_MEMORY_HOST);
hypre_TFree(CF_marker_offd, 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);
hypre_CSRMatrixMemoryLocation(S_diag) = HYPRE_MEMORY_HOST;
hypre_CSRMatrixMemoryLocation(S_offd) = HYPRE_MEMORY_HOST;
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 = fabs(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; /* reject diag entry */
if ( fabs(row_sum) < fabs(diag)*(2.0-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_BoomerAMGCreate2ndSHost( 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);
}
hypre_CSRMatrixMemoryLocation(C_diag) = HYPRE_MEMORY_HOST;
hypre_CSRMatrixMemoryLocation(C_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_Int
hypre_BoomerAMGCreate2ndS( hypre_ParCSRMatrix *S,
HYPRE_Int *CF_marker,
HYPRE_Int num_paths,
HYPRE_BigInt *coarse_row_starts,
hypre_ParCSRMatrix **C_ptr)
{
#if defined(HYPRE_USING_CUDA)
hypre_NvtxPushRange("Create2ndS");
#endif
HYPRE_Int ierr = 0;
#if defined(HYPRE_USING_CUDA)
HYPRE_ExecutionPolicy exec = hypre_GetExecPolicy1( hypre_CSRMatrixMemoryLocation(hypre_ParCSRMatrixDiag(S)) );
if (exec == HYPRE_EXEC_DEVICE)
{
ierr = hypre_BoomerAMGCreate2ndSDevice( S, CF_marker, num_paths, coarse_row_starts, C_ptr );
}
else
#endif
{
ierr = hypre_BoomerAMGCreate2ndSHost( S, CF_marker, num_paths, coarse_row_starts, C_ptr );
}
#if defined(HYPRE_USING_CUDA)
hypre_NvtxPopRange();
#endif
return ierr;
}
/*--------------------------------------------------------------------------
* 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;
}
|
GB_binop__max_uint8.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__max_uint8)
// A.*B function (eWiseMult): GB (_AemultB_08__max_uint8)
// A.*B function (eWiseMult): GB (_AemultB_02__max_uint8)
// A.*B function (eWiseMult): GB (_AemultB_04__max_uint8)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__max_uint8)
// A*D function (colscale): GB (_AxD__max_uint8)
// D*A function (rowscale): GB (_DxB__max_uint8)
// C+=B function (dense accum): GB (_Cdense_accumB__max_uint8)
// C+=b function (dense accum): GB (_Cdense_accumb__max_uint8)
// C+=A+B function (dense ewise3): GB (_Cdense_ewise3_accum__max_uint8)
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__max_uint8)
// C=scalar+B GB (_bind1st__max_uint8)
// C=scalar+B' GB (_bind1st_tran__max_uint8)
// C=A+scalar GB (_bind2nd__max_uint8)
// C=A'+scalar GB (_bind2nd_tran__max_uint8)
// C type: uint8_t
// A type: uint8_t
// B,b type: uint8_t
// BinaryOp: cij = GB_IMAX (aij, bij)
#define GB_ATYPE \
uint8_t
#define GB_BTYPE \
uint8_t
#define GB_CTYPE \
uint8_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) \
uint8_t aij = GBX (Ax, pA, A_iso)
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB,B_iso) \
uint8_t bij = GBX (Bx, pB, B_iso)
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
uint8_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 = GB_IMAX (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_MAX || GxB_NO_UINT8 || GxB_NO_MAX_UINT8)
//------------------------------------------------------------------------------
// 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__max_uint8)
(
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
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_ewise3_noaccum__max_uint8)
(
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__max_uint8)
(
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__max_uint8)
(
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 uint8_t
uint8_t bwork = (*((uint8_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__max_uint8)
(
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
uint8_t *restrict Cx = (uint8_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__max_uint8)
(
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
uint8_t *restrict Cx = (uint8_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__max_uint8)
(
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__max_uint8)
(
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__max_uint8)
(
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__max_uint8)
(
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__max_uint8)
(
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__max_uint8)
(
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
uint8_t *Cx = (uint8_t *) Cx_output ;
uint8_t x = (*((uint8_t *) x_input)) ;
uint8_t *Bx = (uint8_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 ;
uint8_t bij = GBX (Bx, p, false) ;
Cx [p] = GB_IMAX (x, bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__max_uint8)
(
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 ;
uint8_t *Cx = (uint8_t *) Cx_output ;
uint8_t *Ax = (uint8_t *) Ax_input ;
uint8_t y = (*((uint8_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
uint8_t aij = GBX (Ax, p, false) ;
Cx [p] = GB_IMAX (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) \
{ \
uint8_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = GB_IMAX (x, aij) ; \
}
GrB_Info GB (_bind1st_tran__max_uint8)
(
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 \
uint8_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint8_t x = (*((const uint8_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
uint8_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) \
{ \
uint8_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = GB_IMAX (aij, y) ; \
}
GrB_Info GB (_bind2nd_tran__max_uint8)
(
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
uint8_t y = (*((const uint8_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
classify.c | //
// classify.c
// taxonomer
//
// Created by Steven Flygare on 10/6/14.
// Copyright (c) 2014 yandell lab. All rights reserved.
//
#include "classify.h"
#define READS_PER_BLOCK 10000
#define READ_OUTPUT_SIZE 200
KSEQ_INIT(gzFile, gzread)
char rev_base[] = {'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'T', 'N', 'G', 'N', 'N', 'N', 'C', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'A', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 't', 'N', 'g', 'N', 'N', 'N', 'c', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'a', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N', 'N'};
void classify_read_output_ties(struct read_info ** reads, int num_reads, char ** tied_output){
int i= 0;
#pragma omp parallel for
for (i=0; i < num_reads; i++) {
struct read_tax_info * rti = NULL;
process_read(reads[i]->read, reads[i]->read_len, &rti);
if (tax_globals.protein == 1) {
//get reverse complement
uint64_t rl = reads[i]->read_len;
char rev_seq[rl+1];
memset(rev_seq, '\0', rl+1);
int rev_pos = 0;
int j = 0;
for (j = rl - 1; j >= 0; j--) {
rev_seq[rev_pos] = rev_base[(int)reads[i]->read[j]];
rev_pos++;
}
process_read(rev_seq, rl, &rti);
}
struct read_output_info roi = {0,0, 0.0, 0.0, 0.0};
uint64_t * max_taxids = NULL;
ties_from_taxids(rti, &roi, &max_taxids);
int output_read_buffer_size = 500;
int cur_output_size = 0;
tied_output[i] = (char *)calloc(output_read_buffer_size, sizeof(char));
int j = 0;
struct taxid_seqid * tts = NULL;
if (roi.num_taxids > 0) {
for (j = 0; j < roi.num_taxids; j++) {
//printf("C\t%s\t%llu\t%llu\n",reads[i]->name,max_taxids[j],roi.num_taxids);
char tmp_output[READ_OUTPUT_SIZE];
HASH_FIND(hh, tax_to_seqs, &max_taxids[j], sizeof(uint64_t), tts);
if (tts == NULL) {
printf("problem, taxid %llu not found in structure that contains corresponding seqids, will skip\n",max_taxids[j]);
continue;
}
int tmp_output_size = sprintf(tmp_output, "C\t%s\t%llu\t%s\t%d\t%llu\t%f\t%f\t%llu\n",reads[i]->name,max_taxids[j],tts->seqids[rand() % tts->num_seqids], roi.tax_depth, roi.num_taxids, roi.max_score, roi.mean_score, reads[i]->read_len);
if (j == 0) {
strcpy(tied_output[i], tmp_output);
}
else {
strcat(tied_output[i], tmp_output);
}
cur_output_size += tmp_output_size;
cur_output_size++;
if (output_read_buffer_size - cur_output_size <= READ_OUTPUT_SIZE) {
output_read_buffer_size = 2 * output_read_buffer_size;
tied_output[i] = (char *)realloc(tied_output[i], sizeof(char)*output_read_buffer_size);
}
}
}
else {
sprintf(tied_output[i], "U\t%s\n",reads[i]->name);
}
free(max_taxids);
struct read_tax_info *s, *tmp;
HASH_ITER(hh, rti, s, tmp){ //need to free allocated structs
HASH_DEL(rti, s);
free(s);
}
}
}
char * classify_read_stream(char * read, char * read_name, uint64_t read_length){
struct read_tax_info * rti = NULL;
process_read(read, read_length, &rti);
if (tax_globals.protein == 1) {
//get reverse complement
uint64_t rl = read_length;
char rev_seq[rl+1];
memset(rev_seq, '\0', rl+1);
int rev_pos = 0;
int j = 0;
for (j = rl - 1; j >= 0; j--) {
rev_seq[rev_pos] = rev_base[(int)read[j]];
rev_pos++;
}
process_read(rev_seq, rl, &rti);
}
struct taxid_confidence * ttc = NULL;
struct read_tax_info *s, *tmp;
/*HASH_ITER(hh, rti, s, tmp){ //apply weight
HASH_FIND(hh, tax_c_scores, &s->taxid, sizeof(uint64_t), ttc);
if (ttc == NULL) {
continue;
}
else {
s->score = s->score * ttc->confidence;
}
}*/
char * output = calloc(READ_OUTPUT_SIZE,sizeof(char));
//char output[READ_OUTPUT_SIZE];
//memset(output,'\0', sizeof(char)*READ_OUTPUT_SIZE);
struct read_output_info roi = {0, 0, 0, 0.0, 0.0, 0.0, 0.0, 0.0};
uint64_t * max_taxids = NULL;
lca_from_taxids(rti, &roi, &max_taxids);
//lca_from_taxids_kw(rti, &roi, &max_taxids);
struct taxid_seqid * tts = NULL;
if (roi.lca > 0) {
HASH_FIND(hh, tax_to_seqs, &max_taxids[0], sizeof(uint64_t), tts);
if (tts == NULL) {
printf("problem, taxid %llu not found in structure that contains corresponding seqids, will skip\n",max_taxids[0]);
sprintf(output, "U\t%s\n",read_name);
}
else {
sprintf(output, "C\t%s\t%llu\t%s\t%d\t%llu\t%f\t%f\t%llu\n",read_name,roi.lca,tts->seqids[rand() % tts->num_seqids], roi.tax_depth, roi.num_taxids, roi.max_score, roi.mean_score,read_length);
}
}
else {
sprintf(output, "U\t%s\n",read_name);
}
//fprintf(stdout, "%s", output);
free(max_taxids);
HASH_ITER(hh, rti, s, tmp){ //need to free allocated structs
HASH_DEL(rti, s);
free(s);
}
return output;
}
void add_reads(char * read, char * read_name, uint64_t read_length, int name_length, int classify){
static struct read_info * reads[READS_PER_BLOCK];
static int num_reads = 0;
//printf("%s,%llu,%d,%d\n",read_name,read_length,name_length,num_reads);
if (num_reads >= READS_PER_BLOCK || (classify == 1 && num_reads > 0)) { //enable classification if no more reads and not larger than READS_PER_BLOCK
int i = 0;
#ifdef _OPENMP
omp_set_num_threads(tax_globals.np);
#endif
#pragma omp parallel for
for (i=0; i < num_reads; i++) {
classify_read_stream(reads[i]->read, reads[i]->name, reads[i]->read_len);
free(reads[i]->read);
free(reads[i]->name);
free(reads[i]);
}
num_reads = 0;
}
if (classify == 1) { //return without adding reads
return;
}
reads[num_reads] = (struct read_info *)malloc(sizeof(struct read_info));
reads[num_reads]->read = (char *)calloc(read_length+1,sizeof(char));
memcpy(reads[num_reads]->read, read, read_length*sizeof(char));
reads[num_reads]->name = (char *)calloc(name_length+1,sizeof(char));
memcpy(reads[num_reads]->name, read_name, name_length*sizeof(char));
reads[num_reads]->read_len = read_length;
num_reads++;
}
void classify_read_chunk(struct read_info ** reads, int num_reads, char output[READS_PER_BLOCK][READ_OUTPUT_SIZE]){
int i= 0;
#pragma omp parallel for
for (i=0; i < num_reads; i++) {
struct read_tax_info * rti = NULL;
//printf("%s\t%llu\n",reads[i]->name,reads[i]->read_len);
process_read(reads[i]->read, reads[i]->read_len, &rti);
if (tax_globals.protein == 1) {
//get reverse complement
uint64_t rl = reads[i]->read_len;
char rev_seq[rl+1];
memset(rev_seq, '\0', rl+1);
int rev_pos = 0;
int j = 0;
for (j = rl - 1; j >= 0; j--) {
rev_seq[rev_pos] = rev_base[(int)reads[i]->read[j]];
rev_pos++;
}
process_read(rev_seq, rl, &rti);
}
struct taxid_confidence * ttc = NULL;
struct read_tax_info *s, *tmp;
/*HASH_ITER(hh, rti, s, tmp){ //apply weight
HASH_FIND(hh, tax_c_scores, &s->taxid, sizeof(uint64_t), ttc);
if (ttc == NULL) {
continue;
}
else {
s->score = s->score * ttc->confidence;
}
}*/
struct read_output_info roi = {0, 0, 0, 0.0, 0.0, 0.0, 0.0, 0.0};
uint64_t * max_taxids = NULL;
lca_from_taxids(rti, &roi, &max_taxids);
//lca_from_taxids_kw(rti, &roi, &max_taxids);
memset(output[i],'\0', sizeof(char)*READ_OUTPUT_SIZE);
struct taxid_seqid * tts = NULL;
if (roi.lca > 0) {
HASH_FIND(hh, tax_to_seqs, &max_taxids[0], sizeof(uint64_t), tts);
if (tts == NULL) {
printf("problem, taxid %llu not found in structure that contains corresponding seqids, will skip\n",max_taxids[0]);
continue;
}
sprintf(output[i], "C\t%s\t%llu\t%s\t%d\t%llu\t%f\t%f\t%llu\n",reads[i]->name,roi.lca,tts->seqids[rand() % tts->num_seqids], roi.tax_depth, roi.num_taxids, roi.max_score, roi.mean_score, reads[i]->read_len);
}
else {
sprintf(output[i], "U\t%s\n",reads[i]->name);
}
free(max_taxids);
HASH_ITER(hh, rti, s, tmp){ //need to free allocated structs
HASH_DEL(rti, s);
free(s);
}
}
}
void classify_reads(char * read_file, int np, char * output_file){
srand (time(NULL));
#ifdef _OPENMP
omp_set_num_threads(np);
#endif
FILE * out = fopen(output_file, "w");
gzFile seq_index_file = gzopen(read_file, "r");
kseq_t * seq_t = kseq_init(seq_index_file);
int l = 0;
struct read_info ** reads = (struct read_info **)malloc(sizeof(struct read_info *)*READS_PER_BLOCK);
int num_reads = 0;
uint64_t reads_read = 0;
uint64_t total_processed = 0;
while ((l = kseq_read(seq_t)) >= 0) {
reads_read++;
if (num_reads < READS_PER_BLOCK) {
struct read_info * myseq = (struct read_info *)malloc(sizeof(struct read_info));
myseq->read = (char *)calloc(seq_t->seq.l, sizeof(char));
memcpy(myseq->read, seq_t->seq.s, sizeof(char)*seq_t->seq.l);
myseq->name = (char *)calloc(seq_t->name.l + 1, sizeof(char));
memcpy(myseq->name, seq_t->name.s, sizeof(char)*seq_t->name.l);
myseq->read_len = seq_t->seq.l;
reads[num_reads] = myseq;
num_reads++;
}
else {
if (tax_globals.output_ties == 0) {
char output[READS_PER_BLOCK][READ_OUTPUT_SIZE];
classify_read_chunk(reads, num_reads, output);
int i = 0;
for (i=0; i < num_reads; i++) {
fprintf(out, "%s", output[i]);
free(reads[i]->read);
free(reads[i]->name);
free(reads[i]);
}
}
else {
char ** output = (char **)malloc(sizeof(char *)*READS_PER_BLOCK);
classify_read_output_ties(reads, num_reads, output);
int i = 0;
for (i=0; i < num_reads; i++) {
fprintf(out, "%s", output[i]);
free(output[i]);
free(reads[i]->read);
free(reads[i]->name);
free(reads[i]);
}
free(output);
}
//free(output);
total_processed += num_reads;
num_reads = 0;
struct read_info * myseq = (struct read_info *)malloc(sizeof(struct read_info));
myseq->read = (char *)calloc(seq_t->seq.l, sizeof(char));
memcpy(myseq->read, seq_t->seq.s, sizeof(char)*seq_t->seq.l);
myseq->name = (char *)calloc(seq_t->name.l + 1, sizeof(char));
memcpy(myseq->name, seq_t->name.s, sizeof(char)*seq_t->name.l);
myseq->read_len = seq_t->seq.l;
reads[num_reads] = myseq;
num_reads++;
}
}
if (tax_globals.output_ties == 0) {
char output[READS_PER_BLOCK][READ_OUTPUT_SIZE];
classify_read_chunk(reads, num_reads, output);
int i = 0;
for (i=0; i < num_reads; i++) {
fprintf(out, "%s", output[i]);
free(reads[i]->read);
free(reads[i]->name);
free(reads[i]);
}
}
else {
char ** output = (char **)malloc(sizeof(char *)*READS_PER_BLOCK);
classify_read_output_ties(reads, num_reads, output);
int i = 0;
for (i=0; i < num_reads; i++) {
fprintf(out, "%s", output[i]);
free(output[i]);
free(reads[i]->read);
free(reads[i]->name);
free(reads[i]);
}
free(output);
}
total_processed += num_reads;
printf("total reads processed: %llu\n",total_processed);
gzclose(seq_index_file);
kseq_destroy(seq_t);
free(reads);
fclose(out);
}
int64_t score_sort(struct read_tax_info * a, struct read_tax_info * b){
return a->score - b->score;
}
float score_sort_kw(struct read_tax_info * a, struct read_tax_info * b){
return a->score/(float)a->counts - b->score/(float)b->counts;
}
struct read_tax_scores * classify_read(char * read, uint64_t read_len){
//<classify> <db_prefix> <tri> <sti> <read>
srand (time(NULL));
struct read_tax_info * rti = NULL;
process_read(read, read_len, &rti);
if (tax_globals.protein == 1) {
//get reverse complement
uint64_t rl = read_len;
char rev_seq[rl+1];
memset(rev_seq, '\0', rl+1);
int rev_pos = 0;
int j = 0;
for (j = rl - 1; j >= 0; j--) {
rev_seq[rev_pos] = rev_base[(int)read[j]];
rev_pos++;
}
process_read(rev_seq, rl, &rti);
}
struct read_output_info roi = {0,0, 0.0, 0.0, 0.0};
uint64_t * max_taxids = NULL;
lca_from_taxids(rti, &roi, &max_taxids);
//free(max_taxids);
struct read_tax_scores * rts = (struct read_tax_scores *)malloc(sizeof(struct read_tax_scores));
rts->lca = (uint64_t *)calloc(1, sizeof(uint64_t));
rts->ntaxids = (int *)calloc(1, sizeof(int));
rts->seqid = (char *)calloc(100, sizeof(char));
memset(rts->seqid, '\0', sizeof(char)*100);
*rts->lca = roi.lca;
struct taxid_seqid * tts = NULL;
if (roi.lca > 0) {
HASH_FIND(hh, tax_to_seqs, &max_taxids[0], sizeof(uint64_t), tts);
if (tts == NULL) {
printf("problem, taxid %llu not found in structure that contains corresponding seqids, will skip\n",max_taxids[0]);
}
else{
strcpy(rts->seqid, tts->seqids[rand() % tts->num_seqids]);
}
}
free(max_taxids);
*rts->ntaxids = HASH_COUNT(rti);
rts->taxids = (uint64_t *)malloc(sizeof(uint64_t)*(*rts->ntaxids));
rts->scores = (float *)malloc(sizeof(float)*(*rts->ntaxids));
rts->counts = (int *)malloc(sizeof(int)*(*rts->ntaxids));
struct read_tax_info *s, *tmp;
HASH_SORT(rti, score_sort);
//HASH_SORT(rti, score_sort_kw);
int i = 0;
HASH_ITER(hh, rti, s, tmp){ //need to free allocated structs
//printf("%llu\t%f\t%d\n",s->taxid,s->score,s->counts);
rts->taxids[i] = s->taxid;
rts->scores[i] = s->score;
rts->counts[i] = s->counts;
i++;
HASH_DEL(rti, s);
free(s);
}
return rts;
}
void classify_db(char * db_file, char * sti_file, int read_len, char * output_file, int np){
#ifdef _OPENMP
omp_set_num_threads(np);
#endif
printf("loading .sti file...");
load_seqid_taxid_rel(sti_file);
printf("done\n");
FILE * out = fopen(output_file, "w");
gzFile db_seq = gzopen(db_file, "r");
kseq_t * seq_t = kseq_init(db_seq);
int l = 0;
struct seqid_taxid_single * stsr;
while ((l = kseq_read(seq_t)) >= 0) {
HASH_FIND_STR(seqid_taxid_rel, seq_t->name.s, stsr);
if (stsr == NULL) {
printf("seqid %s has no associated taxid, will skip reference\n", seq_t->name.s);
continue;
}
uint64_t taxid = stsr->taxid;
uint64_t i = 0;
int correct = 0;
//#pragma omp parallel for
for (i=0; i + read_len <= seq_t->seq.l; i++) {
char read[read_len+1];
read[read_len] = '\0';
memcpy(read, (seq_t->seq.s)+i, read_len);
//printf("read: %s\n",read);
struct read_tax_info * rti = NULL;
process_read(read, read_len, &rti);
struct read_output_info roi = {0,0, 0.0, 0.0, 0.0};
uint64_t * max_taxids = NULL;
lca_from_taxids(rti, &roi, &max_taxids);
free(max_taxids);
int tmp_correct = roi.lca == taxid ? 1 : 0;
//#pragma omp atomic
correct += tmp_correct;
struct read_tax_info *s, *tmp;
HASH_ITER(hh, rti, s, tmp){ //need to free allocated structs
HASH_DEL(rti, s);
free(s);
}
}
fprintf(out, "%s\t%llu\t%f\n",seq_t->name.s,taxid,(float)correct/(float)i );
}
gzclose(db_seq);
fclose(out);
}
uint64_t * get_kmer_info(char * kmer){
uint64_t * res = (uint64_t *)calloc(4, sizeof(uint64_t));
//uint64_t * info = (uint64_t *)calloc(2, sizeof(uint64_t));
uint64_t info[2];
memset(info, '\0', 2*sizeof(uint64_t));
uint64_t k = 0;
int ret = tax_globals.protein == 0 ? next_kmer(kmer, &k) : next_protein_kmer(kmer, &k);
if (ret == tax_globals.KMER_FLAG) {
query_kcrn(k, info);
res[0] = info[0];
res[1] = info[1];
}
if (tax_globals.protein == 1) {
//get reverse complement
uint64_t rl = tax_globals.kl;
char rev_seq[rl+1];
memset(rev_seq, '\0', rl+1);
int rev_pos = 0;
int j = 0;
for (j = rl - 1; j >= 0; j--) {
rev_seq[rev_pos] = rev_base[(int)kmer[j]];
rev_pos++;
}
int ret = next_protein_kmer(rev_seq, &k);
if (ret == tax_globals.KMER_FLAG) {
memset(info, '\0', 2*sizeof(uint64_t));
query_kcrn(k, info);
res[2] = info[0];
res[3] = info[1];
}
}
return res;
}
void load_classification_dbs(char * mi_file, char * db_file, char * rsi_file, char * tri_file, char * sti_file,int load_mem, int ties, int protein, int afterburner){
set_tax_globals();
tax_globals.output_ties = ties;
tax_globals.protein = protein;
tax_globals.afterburner = afterburner;
tax_globals.load_mem = load_mem;
printf("loading kmer index...\n");
load_kmer_db(db_file);
printf("done loading kmer index\n");
printf("loading minimizer index...");
load_minimizer_index(mi_file);
printf("done\n");
printf("loading rsi db...");
load_rsi_db(rsi_file);
printf("done\n");
printf("loading taxid relationships...");
load_tri_file(tri_file);
printf("done\n");
printf("loading seqid taxid relationships...");
load_seqid_taxid_rel(sti_file);
printf("done\n");
if (protein == 1 && tax_globals.kl%3 != 0) {
printf("kmer length MUST be a multiple of 3 to classify in protein space\ndatabase must be built specifically for this, going to exit");
exit(0);
}
//printf("loading taxid scores...");
//load_taxid_confidence(taxid_confidence);
//printf("done\n");
}
int get_kmer_length(){
return tax_globals.kl;
}
uint64_t get_total_kmer_count(){
return tax_globals.total_kmer_count;
}
uint64_t get_unique_kmer_count(){
return tax_globals.unique_kmer_count;
}
void set_kmer_cutoff(int kc){
tax_globals.kmer_cutoff = kc;
}
void set_number_processors(int np){
tax_globals.np = np;
}
|
parallel-reduction-nowait.c | /*
* parallel-reduction-nowait.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
// REQUIRES: tsan
#include <omp.h>
#include <stdio.h>
int main(int argc, char *argv[]) {
int var = 0, i;
int sum1 = 0;
int sum2 = 0;
// Number of threads is empirical: We need enough threads so that
// the reduction is really performed hierarchically in the barrier!
#pragma omp parallel num_threads(5) reduction(+ : var)
{
#pragma omp for schedule(static) nowait reduction(+ : sum1)
for (i = 0; i < 5; i++)
sum1 += i;
#pragma omp for schedule(static) reduction(+ : sum2)
for (i = 0; i < 5; i++)
sum2 += i;
var = sum1 + sum2;
}
fprintf(stderr, "DONE\n");
int error = (var != 100);
return error;
}
// CHECK-NOT: ThreadSanitizer: data race
// CHECK-NOT: ThreadSanitizer: reported
// CHECK: DONE
|
ranking.c | #include "ranking.h"
double l1_distance(double *vec_1, double *vec_2, int N) {
double result = 0;
int i;
#pragma omp parallel private(i) shared(result, vec_1, vec_2, N)
{
#pragma omp for reduction(+:result)
for (i = 0; i < N; ++i) {
result += fabs(vec_1[i] - vec_2[i]);
}
}
return result;
}
void naive_ranking(double *matrix, double *result, int N) {
int i, j;
double total_links = 0;
#pragma omp parallel private(i, j) shared(result, total_links, N)
{
#pragma omp for reduction(+:total_links)
for (j = 0; j < N; ++j) {
result[j] = 0;
for (i = 0; i < N; ++i) {
result[j] += matrix[i * N + j];
}
total_links += result[j];
}
#pragma omp for
for (i = 0; i < N; ++i) {
result[i] /= total_links;
}
}
}
void pagerank(double *matrix, double *pagerank_vector, int N,
double tolerance, double damping_factor, int max_iter) {
/*
* Iterative method from
* https://en.wikipedia.org/wiki/PageRank#Computation
*/
int i, j;
double *fixed_matrix = (double *) malloc(N * N * sizeof(double));
#pragma omp parallel private(i, j) shared(matrix, fixed_matrix, N)
{
#pragma omp for
for (i = 0; i < N; ++i) {
double num_outbound_links = 0;
for (j = 0; j < N; ++j) {
num_outbound_links += matrix[i * N + j];
}
for (j = 0; j < N; ++j) {
fixed_matrix[j * N + i] = (num_outbound_links == 0) ? 1.0 / N : matrix[i * N + j] / num_outbound_links;
}
}
}
double *prev_pagerank_vector = (double *) malloc(N * sizeof(double));
// initial probability distribution
for (i = 0; i < N; ++i) {
prev_pagerank_vector[i] = 1.0 / N;
}
for (i = 0; i < max_iter; ++i) {
// X = M * R
matrix_vector_mult(fixed_matrix, prev_pagerank_vector, pagerank_vector, N);
// R' = d * X + (1 - d) / N
for (j = 0; j < N; ++j) {
pagerank_vector[j] = damping_factor * pagerank_vector[j] + (1 - damping_factor) / N;
}
// check for convergence
double l1_dist = l1_distance(prev_pagerank_vector, pagerank_vector, N);
if (l1_dist < tolerance) break;
memcpy(prev_pagerank_vector, pagerank_vector, N * sizeof(double));
}
free(fixed_matrix);
free(prev_pagerank_vector);
}
|
sum_pressure.h | #pragma omp target teams num_teams((NUM*NUM/2)/BLOCK_SIZE) thread_limit(BLOCK_SIZE)
{
Real sum_cache[BLOCK_SIZE];
#pragma omp parallel
{
int lid = omp_get_thread_num();
int tid = omp_get_team_num();
int gid = tid * BLOCK_SIZE + lid;
int row = (gid % (NUM/2)) + 1;
int col = (gid / (NUM/2)) + 1;
int NUM_2 = NUM >> 1;
Real pres_r = pres_red(col, row);
Real pres_b = pres_black(col, row);
// add squared pressure
sum_cache[lid] = (pres_r * pres_r) + (pres_b * pres_b);
// synchronize threads in block to ensure all thread values stored
#pragma omp barrier
// add up values for block
int i = BLOCK_SIZE >> 1;
while (i != 0) {
if (lid < i) {
sum_cache[lid] += sum_cache[lid + i];
}
#pragma omp barrier
i >>= 1;
}
// store block's summed values
if (lid == 0) {
pres_sum[tid] = sum_cache[0];
}
}
}
|
GB_unop__identity_int32_bool.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_int32_bool
// op(A') function: GB_unop_tran__identity_int32_bool
// C type: int32_t
// A type: bool
// cast: int32_t cij = (int32_t) aij
// unaryop: cij = aij
#define GB_ATYPE \
bool
#define GB_CTYPE \
int32_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
bool aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = x ;
// casting
#define GB_CAST(z, aij) \
int32_t z = (int32_t) aij ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
bool aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
int32_t z = (int32_t) 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_INT32 || GxB_NO_BOOL)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop_apply__identity_int32_bool
(
int32_t *Cx, // Cx and Ax may be aliased
const bool *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 (bool), nthreads) ;
#else
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
bool aij = Ax [p] ;
int32_t z = (int32_t) 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 ;
bool aij = Ax [p] ;
int32_t z = (int32_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_int32_bool
(
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
|
convolution_winograd_transform.h | // Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2022 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_output_neon(const Mat& top_blob_tm, Mat& top_blob, const Mat& bias, const Option& opt)
{
const int outw = top_blob.w;
const int outh = top_blob.h;
const int outch = top_blob.c;
const int w_tiles = outw / 6;
const int h_tiles = outh / 6;
const int tiles = w_tiles * h_tiles;
const float* biasptr = bias;
// const float otm[6][8] = {
// {1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 32.0f, 32.0f, 0.0f},
// {0.0f, 1.0f, -1.0f, 2.0f, -2.0f, 16.0f,-16.0f, 0.0f},
// {0.0f, 1.0f, 1.0f, 4.0f, 4.0f, 8.0f, 8.0f, 0.0f},
// {0.0f, 1.0f, -1.0f, 8.0f, -8.0f, 4.0f, -4.0f, 0.0f},
// {0.0f, 1.0f, 1.0f, 16.0f, 16.0f, 2.0f, 2.0f, 0.0f},
// {0.0f, 1.0f, -1.0f, 32.0f, -32.0f, 1.0f, -1.0f, 1.0f}
// };
// 0 = r0 + (r1 + r2) + (r3 + r4) + (r5 + r6) * 32
// 1 = (r1 - r2) + (r3 - r4) * 2 + (r5 - r6) * 16
// 2 = (r1 + r2) + (r3 + r4) * 4 + (r5 + r6) * 8
// 3 = (r1 - r2) + (r3 - r4) * 8 + (r5 - r6) * 4
// 4 = (r1 + r2) + (r3 + r4) * 16+ (r5 + r6) * 2
// 5 = r7 + (r1 - r2) + (r3 - r4) * 32+ (r5 - r6)
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < outch; p++)
{
const Mat out0_tm = top_blob_tm.channel(p);
Mat out0 = top_blob.channel(p);
const float bias0 = biasptr ? biasptr[p] : 0.f;
float tmp[6][8];
// tile
for (int i = 0; i < h_tiles; i++)
{
for (int j = 0; j < w_tiles; j++)
{
const float* output0_tm_0 = (const float*)out0_tm + (i * w_tiles + j);
const float* output0_tm_1 = output0_tm_0 + tiles * 1;
const float* output0_tm_2 = output0_tm_0 + tiles * 2;
const float* output0_tm_3 = output0_tm_0 + tiles * 3;
const float* output0_tm_4 = output0_tm_0 + tiles * 4;
const float* output0_tm_5 = output0_tm_0 + tiles * 5;
const float* output0_tm_6 = output0_tm_0 + tiles * 6;
const float* output0_tm_7 = output0_tm_0 + tiles * 7;
// TODO neon optimize
for (int m = 0; m < 8; m++)
{
float tmp024a = output0_tm_1[0] + output0_tm_2[0];
float tmp135a = output0_tm_1[0] - output0_tm_2[0];
float tmp024b = output0_tm_3[0] + output0_tm_4[0];
float tmp135b = output0_tm_3[0] - output0_tm_4[0];
float tmp024c = output0_tm_5[0] + output0_tm_6[0];
float tmp135c = output0_tm_5[0] - output0_tm_6[0];
tmp[0][m] = output0_tm_0[0] + tmp024a + tmp024b + tmp024c * 32;
tmp[2][m] = tmp024a + tmp024b * 4 + tmp024c * 8;
tmp[4][m] = tmp024a + tmp024b * 16 + tmp024c + tmp024c;
tmp[1][m] = tmp135a + tmp135b + tmp135b + tmp135c * 16;
tmp[3][m] = tmp135a + tmp135b * 8 + tmp135c * 4;
tmp[5][m] = output0_tm_7[0] + tmp135a + tmp135b * 32 + tmp135c;
output0_tm_0 += tiles * 8;
output0_tm_1 += tiles * 8;
output0_tm_2 += tiles * 8;
output0_tm_3 += tiles * 8;
output0_tm_4 += tiles * 8;
output0_tm_5 += tiles * 8;
output0_tm_6 += tiles * 8;
output0_tm_7 += tiles * 8;
}
float* output0 = out0.row(i * 6) + j * 6;
for (int m = 0; m < 6; m++)
{
const float* tmp0 = tmp[m];
float tmp024a = tmp0[1] + tmp0[2];
float tmp135a = tmp0[1] - tmp0[2];
float tmp024b = tmp0[3] + tmp0[4];
float tmp135b = tmp0[3] - tmp0[4];
float tmp024c = tmp0[5] + tmp0[6];
float tmp135c = tmp0[5] - tmp0[6];
output0[0] = bias0 + tmp0[0] + tmp024a + tmp024b + tmp024c * 32;
output0[2] = bias0 + tmp024a + tmp024b * 4 + tmp024c * 8;
output0[4] = bias0 + tmp024a + tmp024b * 16 + tmp024c + tmp024c;
output0[1] = bias0 + tmp135a + tmp135b + tmp135b + tmp135c * 16;
output0[3] = bias0 + tmp135a + tmp135b * 8 + tmp135c * 4;
output0[5] = bias0 + tmp0[7] + tmp135a + tmp135b * 32 + tmp135c;
output0 += outw;
}
}
}
}
}
|
13_omp_loops.c | // clang-format off
// RUN: %c-to-llvm -fno-discard-value-names %omp_c_flags %s | %apply-typeart -typeart-alloca -call-filter -S 2>&1 | %filecheck %s
// RUN: %c-to-llvm -fno-discard-value-names %omp_c_flags %s | %opt -O2 -S | %apply-typeart -typeart-alloca -call-filter -S 2>&1 | %filecheck %s
// RUN: %c-to-llvm -fno-discard-value-names %omp_c_flags %s | %opt -O2 -S | %apply-typeart -typeart-alloca -call-filter -call-filter-impl=cg -call-filter-cg-file=%p/05_cg.ipcg -S 2>&1
// RUN: %c-to-llvm -fno-discard-value-names %omp_c_flags %s | %apply-typeart -typeart-alloca -call-filter -S | %filecheck %s --check-prefix=check-inst
// RUN: %c-to-llvm -fno-discard-value-names %omp_c_flags %s | %opt -O2 -S | %apply-typeart -typeart-alloca -call-filter -S | %filecheck %s --check-prefix=check-inst
// RUN: %c-to-llvm -fno-discard-value-names %omp_c_flags %s | %opt -O2 -S | %apply-typeart -typeart-alloca -call-filter -call-filter-impl=cg -call-filter-cg-file=%p/05_cg.ipcg -S | %filecheck %s --check-prefix=check-inst
// REQUIRES: openmp
// clang-format on
#include "omp.h"
extern void MPI_Mock(int, int, int);
extern void MPI_Send(void*, int);
void foo(int count) {
int a = 0;
int b = 1;
int c = 2;
// check-inst: define {{.*}} @foo
// check-inst: %d = alloca
// check-inst: %0 = bitcast i32* %d to i8*
// check-inst: call void @__typeart_alloc_stack(i8* %0, i32 2, i64 1)
// check-inst-not: __typeart_alloc_stack_omp
int d = 3;
int e = 4;
#pragma omp parallel for schedule(dynamic, 1)
for (int i = 0; i < count; ++i) {
// no (void*), so we assume benign (with deep analysis)
MPI_Mock(a, b, c);
for (int j = 0; j < count; ++j) {
// Analysis should not filter d, but e...
MPI_Send((void*)&d, e);
}
}
}
// CHECK: TypeArtPass [Heap & Stack]
// CHECK-NEXT: Malloc : 0
// CHECK-NEXT: Free : 0
// CHECK-NEXT: Alloca : 1
// CHECK-NEXT: Global : 0
|
csr_matvec.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)
******************************************************************************/
/******************************************************************************
*
* Matvec functions for hypre_CSRMatrix class.
*
*****************************************************************************/
#include "seq_mv.h"
/*--------------------------------------------------------------------------
* hypre_CSRMatrixMatvec
*--------------------------------------------------------------------------*/
/* y[offset:end] = alpha*A[offset:end,:]*x + beta*b[offset:end] */
HYPRE_Int
hypre_CSRMatrixMatvecOutOfPlaceHost( HYPRE_Complex alpha,
hypre_CSRMatrix *A,
hypre_Vector *x,
HYPRE_Complex beta,
hypre_Vector *b,
hypre_Vector *y,
HYPRE_Int offset )
{
HYPRE_Complex *A_data = hypre_CSRMatrixData(A);
HYPRE_Int *A_i = hypre_CSRMatrixI(A) + offset;
HYPRE_Int *A_j = hypre_CSRMatrixJ(A);
HYPRE_Int num_rows = hypre_CSRMatrixNumRows(A) - offset;
HYPRE_Int num_cols = hypre_CSRMatrixNumCols(A);
/*HYPRE_Int num_nnz = hypre_CSRMatrixNumNonzeros(A);*/
HYPRE_Int *A_rownnz = hypre_CSRMatrixRownnz(A);
HYPRE_Int num_rownnz = hypre_CSRMatrixNumRownnz(A);
HYPRE_Complex *x_data = hypre_VectorData(x);
HYPRE_Complex *b_data = hypre_VectorData(b) + offset;
HYPRE_Complex *y_data = hypre_VectorData(y) + offset;
HYPRE_Int x_size = hypre_VectorSize(x);
HYPRE_Int b_size = hypre_VectorSize(b) - offset;
HYPRE_Int y_size = hypre_VectorSize(y) - offset;
HYPRE_Int num_vectors = hypre_VectorNumVectors(x);
HYPRE_Int idxstride_y = hypre_VectorIndexStride(y);
HYPRE_Int vecstride_y = hypre_VectorVectorStride(y);
/*HYPRE_Int idxstride_b = hypre_VectorIndexStride(b);
HYPRE_Int vecstride_b = hypre_VectorVectorStride(b);*/
HYPRE_Int idxstride_x = hypre_VectorIndexStride(x);
HYPRE_Int vecstride_x = hypre_VectorVectorStride(x);
HYPRE_Complex temp, tempx;
HYPRE_Int i, j, jj, m, ierr = 0;
HYPRE_Real xpar = 0.7;
hypre_Vector *x_tmp = NULL;
/*---------------------------------------------------------------------
* Check for size compatibility. Matvec returns ierr = 1 if
* length of X doesn't equal the number of columns of A,
* ierr = 2 if the length of Y doesn't equal the number of rows
* of A, and ierr = 3 if both are true.
*
* Because temporary vectors are often used in Matvec, none of
* these conditions terminates processing, and the ierr flag
* is informational only.
*--------------------------------------------------------------------*/
hypre_assert(num_vectors == hypre_VectorNumVectors(y));
hypre_assert(num_vectors == hypre_VectorNumVectors(b));
if (num_cols != x_size)
{
ierr = 1;
}
if (num_rows != y_size || num_rows != b_size)
{
ierr = 2;
}
if (num_cols != x_size && (num_rows != y_size || num_rows != b_size))
{
ierr = 3;
}
/*-----------------------------------------------------------------------
* Do (alpha == 0.0) computation - RDF: USE MACHINE EPS
*-----------------------------------------------------------------------*/
if (alpha == 0.0)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows * num_vectors; i++)
{
y_data[i] = beta * b_data[i];
}
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_MATVEC] += hypre_MPI_Wtime() - time_begin;
#endif
return ierr;
}
if (x == y)
{
x_tmp = hypre_SeqVectorCloneDeep(x);
x_data = hypre_VectorData(x_tmp);
}
temp = beta / alpha;
if (num_vectors > 1)
{
/*-----------------------------------------------------------------------
* y = (beta/alpha)*b
*-----------------------------------------------------------------------*/
if (temp == 0.0)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows * num_vectors; i++)
{
y_data[i] = 0.0;
}
}
else if (temp == 1.0)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows * num_vectors; i++)
{
y_data[i] = b_data[i];
}
}
else if (temp == -1.0)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows * num_vectors; i++)
{
y_data[i] = -b_data[i];
}
}
else
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows * num_vectors; i++)
{
y_data[i] = temp * b_data[i];
}
}
/*-----------------------------------------------------------------
* y += A*x
*-----------------------------------------------------------------*/
if (num_rownnz < xpar * num_rows)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i,j,jj,m,tempx) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rownnz; i++)
{
m = A_rownnz[i];
for (j = 0; j < num_vectors; j++)
{
tempx = 0.0;
for (jj = A_i[m]; jj < A_i[m + 1]; jj++)
{
tempx += A_data[jj] * x_data[j * vecstride_x + A_j[jj] * idxstride_x];
}
y_data[j * vecstride_y + m * idxstride_y] += tempx;
}
}
}
else
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i,j,jj,tempx) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows; i++)
{
for (j = 0; j < num_vectors; ++j)
{
tempx = 0.0;
for (jj = A_i[i]; jj < A_i[i + 1]; jj++)
{
tempx += A_data[jj] * x_data[j * vecstride_x + A_j[jj] * idxstride_x];
}
y_data[j * vecstride_y + i * idxstride_y] += tempx;
}
}
}
/*-----------------------------------------------------------------
* y = alpha*y
*-----------------------------------------------------------------*/
if (alpha != 1.0)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows * num_vectors; i++)
{
y_data[i] *= alpha;
}
}
}
else if (num_rownnz < xpar * num_rows)
{
/* use rownnz pointer to do the A*x multiplication when
num_rownnz is smaller than xpar*num_rows */
if (temp == 0.0)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows; i++)
{
y_data[i] = 0.0;
}
if (alpha == 1.0)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i,j,m,tempx) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rownnz; i++)
{
m = A_rownnz[i];
tempx = 0.0;
for (j = A_i[m]; j < A_i[m + 1]; j++)
{
tempx += A_data[j] * x_data[A_j[j]];
}
y_data[m] = tempx;
}
} // y = A*x
else if (alpha == -1.0)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i,j,m,tempx) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rownnz; i++)
{
m = A_rownnz[i];
tempx = 0.0;
for (j = A_i[m]; j < A_i[m + 1]; j++)
{
tempx -= A_data[j] * x_data[A_j[j]];
}
y_data[m] = tempx;
}
} // y = -A*x
else
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i,j,m,tempx) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rownnz; i++)
{
m = A_rownnz[i];
tempx = 0.0;
for (j = A_i[m]; j < A_i[m + 1]; j++)
{
tempx += A_data[j] * x_data[A_j[j]];
}
y_data[m] = alpha * tempx;
}
} // y = alpha*A*x
} // temp == 0
else if (temp == -1.0) // beta == -alpha
{
if (alpha == 1.0)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows; i++)
{
y_data[i] = -b_data[i];
}
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i,j,m,tempx) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rownnz; i++)
{
m = A_rownnz[i];
tempx = 0.0;
for (j = A_i[m]; j < A_i[m + 1]; j++)
{
tempx += A_data[j] * x_data[A_j[j]];
}
y_data[m] += tempx;
}
} // y = A*x - b
else if (alpha == -1.0)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows; i++)
{
y_data[i] = b_data[i];
}
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i,j,m,tempx) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rownnz; i++)
{
m = A_rownnz[i];
tempx = 0.0;
for (j = A_i[m]; j < A_i[m + 1]; j++)
{
tempx += A_data[j] * x_data[A_j[j]];
}
y_data[m] -= tempx;
}
} // y = -A*x + b
else
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows; i++)
{
y_data[i] = -alpha * b_data[i];
}
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i,j,m,tempx) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rownnz; i++)
{
m = A_rownnz[i];
tempx = 0.0;
for (j = A_i[m]; j < A_i[m + 1]; j++)
{
tempx += A_data[j] * x_data[A_j[j]];
}
y_data[m] += alpha * tempx;
}
} // y = alpha*(A*x - b)
} // temp == -1
else if (temp == 1.0) // beta == alpha
{
if (alpha == 1.0)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows; i++)
{
y_data[i] = b_data[i];
}
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i,j,m,tempx) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rownnz; i++)
{
m = A_rownnz[i];
tempx = 0.0;
for (j = A_i[m]; j < A_i[m + 1]; j++)
{
tempx += A_data[j] * x_data[A_j[j]];
}
y_data[m] += tempx;
}
} // y = A*x + b
else if (alpha == -1.0)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows; i++)
{
y_data[i] = -b_data[i];
}
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i,j,m,tempx) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rownnz; i++)
{
m = A_rownnz[i];
tempx = 0.0;
for (j = A_i[m]; j < A_i[m + 1]; j++)
{
tempx -= A_data[j] * x_data[A_j[j]];
}
y_data[m] += tempx;
}
} // y = -A*x - b
else
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows; i++)
{
y_data[i] = alpha * b_data[i];
}
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i,j,m,tempx) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rownnz; i++)
{
m = A_rownnz[i];
tempx = 0.0;
for (j = A_i[m]; j < A_i[m + 1]; j++)
{
tempx += A_data[j] * x_data[A_j[j]];
}
y_data[m] += alpha * tempx;
}
} // y = alpha*(A*x + b)
}
else
{
if (alpha == 1.0)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows; i++)
{
y_data[i] = beta * b_data[i];
}
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i,j,m,tempx) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rownnz; i++)
{
m = A_rownnz[i];
tempx = 0.0;
for (j = A_i[m]; j < A_i[m + 1]; j++)
{
tempx += A_data[j] * x_data[A_j[j]];
}
y_data[m] += tempx;
}
} // y = A*x + beta*b
else if (-1 == alpha)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows; i++)
{
y_data[i] = -temp * b_data[i];
}
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i,j,m,tempx) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rownnz; i++)
{
m = A_rownnz[i];
tempx = 0.0;
for (j = A_i[m]; j < A_i[m + 1]; j++)
{
tempx -= A_data[j] * x_data[A_j[j]];
}
y_data[m] += tempx;
}
} // y = -A*x - temp*b
else
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows; i++)
{
y_data[i] = beta * b_data[i];
}
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i,j,m,tempx) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rownnz; i++)
{
m = A_rownnz[i];
tempx = 0.0;
for (j = A_i[m]; j < A_i[m + 1]; j++)
{
tempx += A_data[j] * x_data[A_j[j]];
}
y_data[m] += alpha * tempx;
}
} // y = alpha*(A*x + temp*b)
} // temp != 0 && temp != -1 && temp != 1
}
else
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel private(i,jj,tempx)
#endif
{
HYPRE_Int iBegin = hypre_CSRMatrixGetLoadBalancedPartitionBegin(A);
HYPRE_Int iEnd = hypre_CSRMatrixGetLoadBalancedPartitionEnd(A);
hypre_assert(iBegin <= iEnd);
hypre_assert(iBegin >= 0 && iBegin <= num_rows);
hypre_assert(iEnd >= 0 && iEnd <= num_rows);
if (temp == 0.0)
{
if (alpha == 1.0) // JSP: a common path
{
for (i = iBegin; i < iEnd; i++)
{
tempx = 0.0;
for (jj = A_i[i]; jj < A_i[i + 1]; jj++)
{
tempx += A_data[jj] * x_data[A_j[jj]];
}
y_data[i] = tempx;
}
} // y = A*x
else if (alpha == -1.0)
{
for (i = iBegin; i < iEnd; i++)
{
tempx = 0.0;
for (jj = A_i[i]; jj < A_i[i + 1]; jj++)
{
tempx -= A_data[jj] * x_data[A_j[jj]];
}
y_data[i] = tempx;
}
} // y = -A*x
else
{
for (i = iBegin; i < iEnd; i++)
{
tempx = 0.0;
for (jj = A_i[i]; jj < A_i[i + 1]; jj++)
{
tempx += A_data[jj] * x_data[A_j[jj]];
}
y_data[i] = alpha * tempx;
}
} // y = alpha*A*x
} // temp == 0
else if (temp == -1.0) // beta == -alpha
{
if (alpha == 1.0) // JSP: a common path
{
for (i = iBegin; i < iEnd; i++)
{
y_data[i] = -b_data[i];
tempx = 0.0;
for (jj = A_i[i]; jj < A_i[i + 1]; jj++)
{
tempx += A_data[jj] * x_data[A_j[jj]];
}
y_data[i] += tempx;
}
} // y = A*x - y
else if (alpha == -1.0) // JSP: a common path
{
for (i = iBegin; i < iEnd; i++)
{
y_data[i] = b_data[i];
tempx = 0.0;
for (jj = A_i[i]; jj < A_i[i + 1]; jj++)
{
tempx -= A_data[jj] * x_data[A_j[jj]];
}
y_data[i] += tempx;
}
} // y = -A*x + y
else
{
for (i = iBegin; i < iEnd; i++)
{
y_data[i] = -alpha * b_data[i];
tempx = 0.0;
for (jj = A_i[i]; jj < A_i[i + 1]; jj++)
{
tempx += A_data[jj] * x_data[A_j[jj]];
}
y_data[i] += alpha * tempx;
}
} // y = alpha*(A*x - y)
} // temp == -1
else if (temp == 1.0)
{
if (alpha == 1.0) // JSP: a common path
{
for (i = iBegin; i < iEnd; i++)
{
y_data[i] = b_data[i];
tempx = 0.0;
for (jj = A_i[i]; jj < A_i[i + 1]; jj++)
{
tempx += A_data[jj] * x_data[A_j[jj]];
}
y_data[i] += tempx;
}
} // y = A*x + y
else if (alpha == -1.0)
{
for (i = iBegin; i < iEnd; i++)
{
y_data[i] = -b_data[i];
tempx = 0.0;
for (jj = A_i[i]; jj < A_i[i + 1]; jj++)
{
tempx -= A_data[jj] * x_data[A_j[jj]];
}
y_data[i] += tempx;
}
} // y = -A*x - y
else
{
for (i = iBegin; i < iEnd; i++)
{
y_data[i] = alpha * b_data[i];
tempx = 0.0;
for (jj = A_i[i]; jj < A_i[i + 1]; jj++)
{
tempx += A_data[jj] * x_data[A_j[jj]];
}
y_data[i] += alpha * tempx;
}
} // y = alpha*(A*x + y)
}
else
{
if (alpha == 1.0) // JSP: a common path
{
for (i = iBegin; i < iEnd; i++)
{
y_data[i] = b_data[i] * temp;
tempx = 0.0;
for (jj = A_i[i]; jj < A_i[i + 1]; jj++)
{
tempx += A_data[jj] * x_data[A_j[jj]];
}
y_data[i] += tempx;
}
} // y = A*x + temp*y
else if (alpha == -1.0)
{
for (i = iBegin; i < iEnd; i++)
{
y_data[i] = -b_data[i] * temp;
tempx = 0.0;
for (jj = A_i[i]; jj < A_i[i + 1]; jj++)
{
tempx -= A_data[jj] * x_data[A_j[jj]];
}
y_data[i] += tempx;
}
} // y = -A*x - temp*y
else
{
for (i = iBegin; i < iEnd; i++)
{
y_data[i] = b_data[i] * beta;
tempx = 0.0;
for (jj = A_i[i]; jj < A_i[i + 1]; jj++)
{
tempx += A_data[jj] * x_data[A_j[jj]];
}
y_data[i] += alpha * tempx;
}
} // y = alpha*(A*x + temp*y)
} // temp != 0 && temp != -1 && temp != 1
} // omp parallel
}
if (x == y)
{
hypre_SeqVectorDestroy(x_tmp);
}
return ierr;
}
HYPRE_Int
hypre_CSRMatrixMatvecOutOfPlace( HYPRE_Complex alpha,
hypre_CSRMatrix *A,
hypre_Vector *x,
HYPRE_Complex beta,
hypre_Vector *b,
hypre_Vector *y,
HYPRE_Int offset )
{
#ifdef HYPRE_PROFILE
HYPRE_Real time_begin = hypre_MPI_Wtime();
#endif
HYPRE_Int ierr = 0;
#if defined(HYPRE_USING_GPU)
HYPRE_ExecutionPolicy exec = hypre_GetExecPolicy1( hypre_CSRMatrixMemoryLocation(A) );
if (exec == HYPRE_EXEC_DEVICE)
{
ierr = hypre_CSRMatrixMatvecDevice(0, alpha, A, x, beta, b, y, offset);
}
else
#endif
{
ierr = hypre_CSRMatrixMatvecOutOfPlaceHost(alpha, A, x, beta, b, y, offset);
}
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_MATVEC] += hypre_MPI_Wtime() - time_begin;
#endif
return ierr;
}
HYPRE_Int
hypre_CSRMatrixMatvec( HYPRE_Complex alpha,
hypre_CSRMatrix *A,
hypre_Vector *x,
HYPRE_Complex beta,
hypre_Vector *y )
{
return hypre_CSRMatrixMatvecOutOfPlace(alpha, A, x, beta, y, y, 0);
}
/*--------------------------------------------------------------------------
* hypre_CSRMatrixMatvecT
*
* This version is using a different (more efficient) threading scheme
* Performs y <- alpha * A^T * x + beta * y
*
* From Van Henson's modification of hypre_CSRMatrixMatvec.
*--------------------------------------------------------------------------*/
HYPRE_Int
hypre_CSRMatrixMatvecTHost( HYPRE_Complex alpha,
hypre_CSRMatrix *A,
hypre_Vector *x,
HYPRE_Complex beta,
hypre_Vector *y )
{
HYPRE_Complex *A_data = hypre_CSRMatrixData(A);
HYPRE_Int *A_i = hypre_CSRMatrixI(A);
HYPRE_Int *A_j = hypre_CSRMatrixJ(A);
HYPRE_Int num_rows = hypre_CSRMatrixNumRows(A);
HYPRE_Int num_cols = hypre_CSRMatrixNumCols(A);
HYPRE_Complex *x_data = hypre_VectorData(x);
HYPRE_Complex *y_data = hypre_VectorData(y);
HYPRE_Int x_size = hypre_VectorSize(x);
HYPRE_Int y_size = hypre_VectorSize(y);
HYPRE_Int num_vectors = hypre_VectorNumVectors(x);
HYPRE_Int idxstride_y = hypre_VectorIndexStride(y);
HYPRE_Int vecstride_y = hypre_VectorVectorStride(y);
HYPRE_Int idxstride_x = hypre_VectorIndexStride(x);
HYPRE_Int vecstride_x = hypre_VectorVectorStride(x);
HYPRE_Complex temp;
HYPRE_Complex *y_data_expand;
HYPRE_Int my_thread_num = 0, offset = 0;
HYPRE_Int i, j, jv, jj;
HYPRE_Int num_threads;
HYPRE_Int ierr = 0;
hypre_Vector *x_tmp = NULL;
/*---------------------------------------------------------------------
* Check for size compatibility. MatvecT returns ierr = 1 if
* length of X doesn't equal the number of rows of A,
* ierr = 2 if the length of Y doesn't equal the number of
* columns of A, and ierr = 3 if both are true.
*
* Because temporary vectors are often used in MatvecT, none of
* these conditions terminates processing, and the ierr flag
* is informational only.
*--------------------------------------------------------------------*/
hypre_assert( num_vectors == hypre_VectorNumVectors(y) );
if (num_rows != x_size)
{
ierr = 1;
}
if (num_cols != y_size)
{
ierr = 2;
}
if (num_rows != x_size && num_cols != y_size)
{
ierr = 3;
}
/*-----------------------------------------------------------------------
* Do (alpha == 0.0) computation - RDF: USE MACHINE EPS
*-----------------------------------------------------------------------*/
if (alpha == 0.0)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_cols * num_vectors; i++)
{
y_data[i] *= beta;
}
return ierr;
}
if (x == y)
{
x_tmp = hypre_SeqVectorCloneDeep(x);
x_data = hypre_VectorData(x_tmp);
}
/*-----------------------------------------------------------------------
* y = (beta/alpha)*y
*-----------------------------------------------------------------------*/
temp = beta / alpha;
if (temp != 1.0)
{
if (temp == 0.0)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_cols * num_vectors; i++)
{
y_data[i] = 0.0;
}
}
else
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_cols * num_vectors; i++)
{
y_data[i] *= temp;
}
}
}
/*-----------------------------------------------------------------
* y += A^T*x
*-----------------------------------------------------------------*/
num_threads = hypre_NumThreads();
if (num_threads > 1)
{
y_data_expand = hypre_CTAlloc(HYPRE_Complex, num_threads * y_size, HYPRE_MEMORY_HOST);
if ( num_vectors == 1 )
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel private(i,jj,j,my_thread_num,offset)
#endif
{
my_thread_num = hypre_GetThreadNum();
offset = y_size * my_thread_num;
#ifdef HYPRE_USING_OPENMP
#pragma omp for HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows; i++)
{
for (jj = A_i[i]; jj < A_i[i + 1]; jj++)
{
j = A_j[jj];
y_data_expand[offset + j] += A_data[jj] * x_data[i];
}
}
/* implied barrier (for threads)*/
#ifdef HYPRE_USING_OPENMP
#pragma omp for HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < y_size; i++)
{
for (j = 0; j < num_threads; j++)
{
y_data[i] += y_data_expand[j * y_size + i];
}
}
} /* end parallel threaded region */
}
else
{
/* multiple vector case is not threaded */
for (i = 0; i < num_rows; i++)
{
for ( jv = 0; jv < num_vectors; ++jv )
{
for (jj = A_i[i]; jj < A_i[i + 1]; jj++)
{
j = A_j[jj];
y_data[ j * idxstride_y + jv * vecstride_y ] +=
A_data[jj] * x_data[ i * idxstride_x + jv * vecstride_x];
}
}
}
}
hypre_TFree(y_data_expand, HYPRE_MEMORY_HOST);
}
else
{
for (i = 0; i < num_rows; i++)
{
if ( num_vectors == 1 )
{
for (jj = A_i[i]; jj < A_i[i + 1]; jj++)
{
j = A_j[jj];
y_data[j] += A_data[jj] * x_data[i];
}
}
else
{
for ( jv = 0; jv < num_vectors; ++jv )
{
for (jj = A_i[i]; jj < A_i[i + 1]; jj++)
{
j = A_j[jj];
y_data[ j * idxstride_y + jv * vecstride_y ] +=
A_data[jj] * x_data[ i * idxstride_x + jv * vecstride_x ];
}
}
}
}
}
/*-----------------------------------------------------------------
* y = alpha*y
*-----------------------------------------------------------------*/
if (alpha != 1.0)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_cols * num_vectors; i++)
{
y_data[i] *= alpha;
}
}
if (x == y)
{
hypre_SeqVectorDestroy(x_tmp);
}
return ierr;
}
HYPRE_Int
hypre_CSRMatrixMatvecT( HYPRE_Complex alpha,
hypre_CSRMatrix *A,
hypre_Vector *x,
HYPRE_Complex beta,
hypre_Vector *y )
{
#ifdef HYPRE_PROFILE
HYPRE_Real time_begin = hypre_MPI_Wtime();
#endif
HYPRE_Int ierr = 0;
#if defined(HYPRE_USING_GPU)
HYPRE_ExecutionPolicy exec = hypre_GetExecPolicy1( hypre_CSRMatrixMemoryLocation(A) );
if (exec == HYPRE_EXEC_DEVICE)
{
ierr = hypre_CSRMatrixMatvecDevice(1, alpha, A, x, beta, y, y, 0 );
}
else
#endif
{
ierr = hypre_CSRMatrixMatvecTHost(alpha, A, x, beta, y);
}
#ifdef HYPRE_PROFILE
hypre_profile_times[HYPRE_TIMER_ID_MATVEC] += hypre_MPI_Wtime() - time_begin;
#endif
return ierr;
}
/*--------------------------------------------------------------------------
* hypre_CSRMatrixMatvec_FF
*--------------------------------------------------------------------------*/
HYPRE_Int
hypre_CSRMatrixMatvec_FF( HYPRE_Complex alpha,
hypre_CSRMatrix *A,
hypre_Vector *x,
HYPRE_Complex beta,
hypre_Vector *y,
HYPRE_Int *CF_marker_x,
HYPRE_Int *CF_marker_y,
HYPRE_Int fpt )
{
HYPRE_Complex *A_data = hypre_CSRMatrixData(A);
HYPRE_Int *A_i = hypre_CSRMatrixI(A);
HYPRE_Int *A_j = hypre_CSRMatrixJ(A);
HYPRE_Int num_rows = hypre_CSRMatrixNumRows(A);
HYPRE_Int num_cols = hypre_CSRMatrixNumCols(A);
HYPRE_Complex *x_data = hypre_VectorData(x);
HYPRE_Complex *y_data = hypre_VectorData(y);
HYPRE_Int x_size = hypre_VectorSize(x);
HYPRE_Int y_size = hypre_VectorSize(y);
HYPRE_Complex temp;
HYPRE_Int i, jj;
HYPRE_Int ierr = 0;
/*---------------------------------------------------------------------
* Check for size compatibility. Matvec returns ierr = 1 if
* length of X doesn't equal the number of columns of A,
* ierr = 2 if the length of Y doesn't equal the number of rows
* of A, and ierr = 3 if both are true.
*
* Because temporary vectors are often used in Matvec, none of
* these conditions terminates processing, and the ierr flag
* is informational only.
*--------------------------------------------------------------------*/
if (num_cols != x_size)
{
ierr = 1;
}
if (num_rows != y_size)
{
ierr = 2;
}
if (num_cols != x_size && num_rows != y_size)
{
ierr = 3;
}
/*-----------------------------------------------------------------------
* Do (alpha == 0.0) computation - RDF: USE MACHINE EPS
*-----------------------------------------------------------------------*/
if (alpha == 0.0)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows; i++)
if (CF_marker_x[i] == fpt) { y_data[i] *= beta; }
return ierr;
}
/*-----------------------------------------------------------------------
* y = (beta/alpha)*y
*-----------------------------------------------------------------------*/
temp = beta / alpha;
if (temp != 1.0)
{
if (temp == 0.0)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows; i++)
if (CF_marker_x[i] == fpt) { y_data[i] = 0.0; }
}
else
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows; i++)
if (CF_marker_x[i] == fpt) { y_data[i] *= temp; }
}
}
/*-----------------------------------------------------------------
* y += A*x
*-----------------------------------------------------------------*/
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i,jj) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows; i++)
{
if (CF_marker_x[i] == fpt)
{
temp = y_data[i];
for (jj = A_i[i]; jj < A_i[i + 1]; jj++)
if (CF_marker_y[A_j[jj]] == fpt) { temp += A_data[jj] * x_data[A_j[jj]]; }
y_data[i] = temp;
}
}
/*-----------------------------------------------------------------
* y = alpha*y
*-----------------------------------------------------------------*/
if (alpha != 1.0)
{
#ifdef HYPRE_USING_OPENMP
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < num_rows; i++)
if (CF_marker_x[i] == fpt) { y_data[i] *= alpha; }
}
return ierr;
}
|
3d7pt.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
* 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, 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]);
double ****A = (double ****) malloc(sizeof(double***)*2);
A[0] = (double ***) malloc(sizeof(double**)*Nz);
A[1] = (double ***) malloc(sizeof(double**)*Nz);
for(i=0; i<Nz; i++){
A[0][i] = (double**) malloc(sizeof(double*)*Ny);
A[1][i] = (double**) malloc(sizeof(double*)*Ny);
for(j=0;j<Ny;j++){
A[0][i][j] = (double*) malloc(sizeof(double)*Nx);
A[1][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] = 4;
tile_size[1] = 4;
tile_size[2] = 8;
tile_size[3] = 512;
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;
const double alpha = 0.0876;
const double beta = 0.0765;
// 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);
}
}
}
#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-2,2);t1++) {
lbp=max(ceild(t1,2),ceild(4*t1-Nt+3,4));
ubp=min(floord(Nt+Nz-4,4),floord(2*t1+Nz-1,4));
#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(t1-3,4)),ceild(4*t2-Nz-4,8));t3<=min(min(min(floord(4*t2+Ny,8),floord(Nt+Ny-4,8)),floord(2*t1+Ny+1,8)),floord(4*t1-4*t2+Nz+Ny-1,8));t3++) {
for (t4=max(max(max(0,ceild(t1-255,256)),ceild(4*t2-Nz-508,512)),ceild(8*t3-Ny-508,512));t4<=min(min(min(min(floord(4*t2+Nx,512),floord(Nt+Nx-4,512)),floord(2*t1+Nx+1,512)),floord(8*t3+Nx+4,512)),floord(4*t1-4*t2+Nz+Nx-1,512));t4++) {
for (t5=max(max(max(max(max(0,2*t1),4*t1-4*t2+1),4*t2-Nz+2),8*t3-Ny+2),512*t4-Nx+2);t5<=min(min(min(min(min(Nt-2,2*t1+3),4*t2+2),8*t3+6),512*t4+510),4*t1-4*t2+Nz+1);t5++) {
for (t6=max(max(4*t2,t5+1),-4*t1+4*t2+2*t5-3);t6<=min(min(4*t2+3,-4*t1+4*t2+2*t5),t5+Nz-2);t6++) {
for (t7=max(8*t3,t5+1);t7<=min(8*t3+7,t5+Ny-2);t7++) {
lbv=max(512*t4,t5+1);
ubv=min(512*t4+511,t5+Nx-2);
#pragma ivdep
#pragma vector always
for (t8=lbv;t8<=ubv;t8++) {
A[( t5 + 1) % 2][ (-t5+t6)][ (-t5+t7)][ (-t5+t8)] = ((alpha * A[ t5 % 2][ (-t5+t6)][ (-t5+t7)][ (-t5+t8)]) + (beta * (((((A[ t5 % 2][ (-t5+t6) - 1][ (-t5+t7)][ (-t5+t8)] + A[ t5 % 2][ (-t5+t6)][ (-t5+t7) - 1][ (-t5+t8)]) + A[ t5 % 2][ (-t5+t6)][ (-t5+t7)][ (-t5+t8) - 1]) + A[ t5 % 2][ (-t5+t6) + 1][ (-t5+t7)][ (-t5+t8)]) + A[ t5 % 2][ (-t5+t6)][ (-t5+t7) + 1][ (-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, "constant")
#ifdef LIKWID_PERFMON
#pragma omp parallel
{
LIKWID_MARKER_STOP("calc");
}
LIKWID_MARKER_CLOSE;
#endif
// Free allocated arrays (Causing performance degradation
/* 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]);
*/
return 0;
}
|
atomic-10.c | /* PR middle-end/28046 */
/* { dg-do compile } */
/* { dg-options "-fopenmp -fdump-tree-ompexp" } */
/* { dg-require-effective-target cas_int } */
int a[3], b;
struct C { int x; int y; } c;
int bar (void), *baz (void);
void
foo (void)
{
#pragma omp atomic
a[2] += bar ();
#pragma omp atomic
b += bar ();
#pragma omp atomic
c.y += bar ();
#pragma omp atomic
*baz () += bar ();
}
/* { dg-final { scan-tree-dump-times "__atomic_fetch_add" 4 "ompexp" } } */
|
DRB039-truedepsingleelement-orig-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.
*/
/*
Data race pair: a[i]@62:5 vs. a[0]@62:15
*/
#include "omprace.h"
#include <omp.h>
#include <stdlib.h>
#include <stdio.h>
int main (int argc, char* argv[])
{
omprace_init();
int len=1000;
int i;
int a[1000];
a[0] = 2;
#pragma omp parallel for
for (i=0;i<len;i++)
a[i]=a[i]+a[0];
printf("a[500]=%d\n", a[500]);
omprace_fini();
return 0;
}
|
atomic-5.c | /* PR middle-end/36106 */
/* { dg-options "-O2" } */
/* { dg-options "-O2 -mcx16" { target { { i?86-*-* x86_64-*-* } && lp64 } } } */
#ifdef __x86_64__
# include "cpuid.h"
#endif
extern void abort (void);
int __attribute__((noinline))
do_test (void)
{
long double d = .0L;
int i;
#pragma omp parallel for shared (d)
for (i = 0; i < 10; i++)
#pragma omp atomic
d += 1.0L;
if (d != 10.0L)
abort ();
return 0;
}
int
main (void)
{
#ifdef __x86_64__
unsigned int eax, ebx, ecx, edx;
if (!__get_cpuid (1, &eax, &ebx, &ecx, &edx))
return 0;
if (!(ecx & bit_CMPXCHG16B))
return 0;
#endif
do_test ();
return 0;
}
|
GB_binop__pair_int32.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__pair_int32
// A.*B function (eWiseMult): GB_AemultB__pair_int32
// A*D function (colscale): GB_AxD__pair_int32
// D*A function (rowscale): GB_DxB__pair_int32
// C+=B function (dense accum): GB_Cdense_accumB__pair_int32
// C+=b function (dense accum): GB_Cdense_accumb__pair_int32
// C+=A+B function (dense ewise3): (none)
// C=A+B function (dense ewise3): GB_Cdense_ewise3_noaccum__pair_int32
// C=scalar+B (none)
// C=scalar+B' (none)
// C=A+scalar (none)
// C=A'+scalar (none)
// C type: int32_t
// A type: int32_t
// B,b type: int32_t
// BinaryOp: cij = 1
#define GB_ATYPE \
int32_t
#define GB_BTYPE \
int32_t
#define GB_CTYPE \
int32_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) \
int32_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) \
z = 1 ;
// 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_INT32 || GxB_NO_PAIR_INT32)
//------------------------------------------------------------------------------
// 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_int32
(
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_int32
(
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_int32
(
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 int32_t
int32_t bwork = (*((int32_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_int32
(
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
int32_t *GB_RESTRICT Cx = (int32_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_int32
(
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
int32_t *GB_RESTRICT Cx = (int32_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_int32
(
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__pair_int32
(
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
//------------------------------------------------------------------------------
#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,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int32_t *Cx = (int32_t *) Cx_output ;
int32_t x = (*((int32_t *) x_input)) ;
int32_t *Bx = (int32_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
; ;
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 (none)
(
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 ;
int32_t *Cx = (int32_t *) Cx_output ;
int32_t *Ax = (int32_t *) Ax_input ;
int32_t y = (*((int32_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
; ;
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 typcasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
; ; \
Cx [pC] = 1 ; \
}
GrB_Info (none)
(
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 \
int32_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int32_t x = (*((const int32_t *) x_input)) ;
#define GB_PHASE_2_OF_2
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
int32_t
}
#endif
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
#if 0
// cij = op (aij, y), no typcasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
; ; \
Cx [pC] = 1 ; \
}
GrB_Info (none)
(
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
int32_t y = (*((const int32_t *) y_input)) ;
#define GB_PHASE_2_OF_2
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
#endif
|
tstfft.c | /* -*- mode: C; tab-width: 2; indent-tabs-mode: nil; fill-column: 79; coding: iso-latin-1-unix -*- */
/* tstfft.c
*/
#include <hpcc.h>
#include "hpccfft.h"
static int
TestFFT1(HPCC_Params *params, int doIO, FILE *outFile, double *UGflops, int *Un, int *Ufailure) {
fftw_complex *in, *out;
fftw_plan p;
hpcc_fftw_plan ip;
double Gflops = -1.0;
double maxErr, tmp1, tmp2, tmp3, t0, t1, t2, t3;
int i, n, flags, failure = 1;
double deps = HPL_dlamch( HPL_MACH_EPS );
#ifdef HPCC_FFT_235
int f[3];
/* Need 2 vectors */
n = HPCC_LocalVectorSize( params, 2, sizeof(fftw_complex), 0 );
/* Adjust local size for factors */
for ( ; HPCC_factor235( n, f ); n--)
; /* EMPTY */
#else
/* Need 2 vectors and vectors' sizes as power of 2 */
n = HPCC_LocalVectorSize( params, 2, sizeof(fftw_complex), 1 );
#endif
/* need to use fftw_malloc() so that the returned pointers will be aligned properly for SSE
instructions on Intel/AMD systems */
in = (fftw_complex *)HPCC_fftw_malloc( (sizeof *in) * n );
out = (fftw_complex *)HPCC_fftw_malloc( (sizeof *out) * n );
if (! in || ! out) goto comp_end;
/* Make sure that `inout' and `work' are initialized in parallel if using
Open MP: this will ensure better placement of pages if first-touch policy
is used by a distrubuted shared memory machine. */
#ifdef _OPENMP
#pragma omp parallel for
for (i = 0; i < n; ++i) {
c_re( in[i] ) = c_re( out[i] ) = 0.0;
c_re( in[i] ) = c_im( out[i] ) = 0.0;
}
#endif
t0 = -MPI_Wtime();
HPCC_bcnrand( 2*n, 0, in );
t0 += MPI_Wtime();
#ifdef HPCC_FFTW_ESTIMATE
flags = FFTW_ESTIMATE;
#else
flags = FFTW_MEASURE;
#endif
t1 = -MPI_Wtime();
p = fftw_create_plan( n, FFTW_FORWARD, flags );
t1 += MPI_Wtime();
if (! p) goto comp_end;
t2 = -MPI_Wtime();
fftw_one( p, in, out );
t2 += MPI_Wtime();
fftw_destroy_plan(p);
ip = HPCC_fftw_create_plan( n, FFTW_BACKWARD, FFTW_ESTIMATE );
if (ip) {
t3 = -MPI_Wtime();
HPCC_fftw_one( ip, out, in );
t3 += MPI_Wtime();
HPCC_fftw_destroy_plan( ip );
}
HPCC_bcnrand( 2*n, 0, out ); /* regenerate data */
maxErr = 0.0;
for (i = 0; i < n; i++) {
tmp1 = c_re( in[i] ) - c_re( out[i] );
tmp2 = c_im( in[i] ) - c_im( out[i] );
tmp3 = sqrt( tmp1*tmp1 + tmp2*tmp2 );
maxErr = maxErr >= tmp3 ? maxErr : tmp3;
}
if (maxErr / log(n) / deps < params->test.thrsh) failure = 0;
if (doIO) {
fprintf( outFile, "Vector size: %d\n", n );
fprintf( outFile, "Generation time: %9.3f\n", t0 );
fprintf( outFile, "Tuning: %9.3f\n", t1 );
fprintf( outFile, "Computing: %9.3f\n", t2 );
fprintf( outFile, "Inverse FFT: %9.3f\n", t3 );
fprintf( outFile, "max(|x-x0|): %9.3e\n", maxErr );
}
if (t2 > 0.0) Gflops = 1e-9 * (5.0 * n * log(n) / log(2.0)) / t2;
comp_end:
if (out) HPCC_fftw_free( out );
if (in) HPCC_fftw_free( in );
*UGflops = Gflops;
*Un = n;
*Ufailure = failure;
return 0;
}
int
HPCC_TestFFT(HPCC_Params *params, int doIO, double *UGflops, int *Un, int *Ufailure) {
int rv, n, failure = 1;
double Gflops;
FILE *outFile;
if (doIO) {
outFile = fopen( params->outFname, "a" );
if (! outFile) {
outFile = stderr;
fprintf( outFile, "Cannot open output file.\n" );
return 1;
}
}
n = 0;
Gflops = -1.0;
rv = TestFFT1( params, doIO, outFile, &Gflops, &n, &failure );
if (doIO) {
fflush( outFile );
fclose( outFile );
}
if (UGflops) *UGflops = Gflops;
if (Un) *Un = n;
if (Ufailure) *Ufailure = failure;
return rv;
}
|
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] = 4;
tile_size[1] = 4;
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-2,2);t1++) {
lbp=max(ceild(t1,2),ceild(4*t1-Nt+3,4));
ubp=min(floord(Nt+Nz-4,4),floord(2*t1+Nz-1,4));
#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(t1-11,12)),ceild(4*t2-Nz-20,24));t3<=min(min(min(floord(4*t2+Ny,24),floord(Nt+Ny-4,24)),floord(2*t1+Ny+1,24)),floord(4*t1-4*t2+Nz+Ny-1,24));t3++) {
for (t4=max(max(max(0,ceild(t1-1023,1024)),ceild(4*t2-Nz-2044,2048)),ceild(24*t3-Ny-2044,2048));t4<=min(min(min(min(floord(4*t2+Nx,2048),floord(Nt+Nx-4,2048)),floord(2*t1+Nx+1,2048)),floord(24*t3+Nx+20,2048)),floord(4*t1-4*t2+Nz+Nx-1,2048));t4++) {
for (t5=max(max(max(max(max(0,2*t1),4*t1-4*t2+1),4*t2-Nz+2),24*t3-Ny+2),2048*t4-Nx+2);t5<=min(min(min(min(min(Nt-2,2*t1+3),4*t2+2),24*t3+22),2048*t4+2046),4*t1-4*t2+Nz+1);t5++) {
for (t6=max(max(4*t2,t5+1),-4*t1+4*t2+2*t5-3);t6<=min(min(4*t2+3,-4*t1+4*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;
}
|
primitives.h | #pragma once
#include <cassert>
#include <vector>
#include <cstdint>
#include <omp.h>
#include "local_buffer.h"
#include "util/timer.h"
#include "util/log/log.h"
using namespace std;
#define CACHE_LINE_ENTRY (16)
#define LOCAL_BUDGET (8*1024*1024)
//#define FOR_LOOP_MEMSET
//#define FOR_LOOP_MEMCPY
template<typename T>
void MemSetOMP(T *arr, int val, size_t size) {
size_t tid = omp_get_thread_num();
size_t max_omp_threads = omp_get_num_threads();
size_t task_num = size;
size_t avg = (task_num + max_omp_threads - 1) / max_omp_threads;
auto it_beg = avg * tid;
auto it_end = min(avg * (tid + 1), task_num);
#ifndef FOR_LOOP_MEMSET
if (it_beg < it_end) {
memset(arr + it_beg, val, sizeof(T) * (it_end - it_beg));
}
#else
T bits = 0;
for (auto i = 0; i < sizeof(T); i++) {
bits |= static_cast<T>(val) << (8 * i);
}
for (auto i = it_beg; i < it_end; i++) {
arr[i] = bits;
}
#endif
#pragma omp barrier
}
template<typename T>
void MemCpyOMP(T *dst, T *src, size_t size) {
size_t tid = omp_get_thread_num();
size_t max_omp_threads = omp_get_num_threads();
size_t task_num = size;
size_t avg = (task_num + max_omp_threads - 1) / max_omp_threads;
auto it_beg = avg * tid;
auto it_end = min(avg * (tid + 1), task_num);
if (it_beg >= it_end) return;
#ifndef FOR_LOOP_MEMCPY
if (it_beg < it_end) {
memcpy(dst + it_beg, src + it_beg, sizeof(T) * (it_end - it_beg));
}
#else
for (auto i = it_beg; i < it_end; i++) {
dst[i] = src[i];
}
#endif
#pragma omp barrier
}
/*
* InclusivePrefixSumOMP: General Case Inclusive Prefix Sum
* histogram: is for cache-aware thread-local histogram purpose
* output: should be different from the variables captured in function object f
* size: is the original size for the flagged prefix sum
* f: requires it as the parameter, f(it) return the histogram value of that it
*/
template<typename H, typename T, typename F>
void InclusivePrefixSumOMP(vector<H> &histogram, T *output, size_t size, F f) {
int omp_num_threads = omp_get_num_threads();
#pragma omp single
{
histogram = vector<H>((omp_num_threads + 1) * CACHE_LINE_ENTRY, 0);
}
static thread_local int tid = omp_get_thread_num();
// 1st Pass: Histogram.
auto avg = size / omp_num_threads;
auto it_beg = avg * tid;
auto histogram_idx = (tid + 1) * CACHE_LINE_ENTRY;
histogram[histogram_idx] = 0;
auto it_end = tid == omp_num_threads - 1 ? size : avg * (tid + 1);
size_t prev = 0u;
for (auto it = it_beg; it < it_end; it++) {
auto value = f(it);
histogram[histogram_idx] += value;
prev += value;
output[it] = prev;
}
#pragma omp barrier
// 2nd Pass: single-prefix-sum & Add previous sum.
#pragma omp single
{
for (auto local_tid = 0; local_tid < omp_num_threads; local_tid++) {
auto local_histogram_idx = (local_tid + 1) * CACHE_LINE_ENTRY;
auto prev_histogram_idx = (local_tid) * CACHE_LINE_ENTRY;
histogram[local_histogram_idx] += histogram[prev_histogram_idx];
}
}
{
auto prev_sum = histogram[tid * CACHE_LINE_ENTRY];
for (auto it = it_beg; it < it_end; it++) {
output[it] += prev_sum;
}
#pragma omp barrier
}
}
/*
* FlagPrefixSumOMP: special case of InclusivePrefixSumOMP
*/
template<typename H, typename T, typename F>
void FlagPrefixSumOMP(vector<H> &histogram, T *output, size_t size, F f) {
InclusivePrefixSumOMP(histogram, output, size, [&f](size_t it) {
return f(it) ? 1 : 0;
});
}
template<typename T>
void InitIdentity(T *identity, size_t size) {
#pragma omp for
for (size_t i = 0; i < size; i++) {
identity[i] = i;
}
}
/*
* SelectNotFOMP: selection primitive
* !f(it) returns selected
*/
template<typename H, typename T, typename OFF, typename F>
void SelectNotFOMP(vector<H> &histogram, T *output, T *input,
OFF *relative_off, size_t size, F f) {
FlagPrefixSumOMP(histogram, relative_off, size, f);
#pragma omp for
for (size_t i = 0u; i < size; i++) {
if (!(f(i))) {
auto off = i - relative_off[i];
output[off] = input[i];
}
}
#pragma omp single
{
if (size >= 1) {
log_info("Selected: %zu", size - relative_off[size - 1]);
}
}
}
/*
* SelectNotFOMP: selection primitive
* !f(it) returns selected
*/
template<typename H, typename T, typename OFF, typename F, typename P>
void SelectNotFOMP(vector<H> &histogram, T *output, T *input,
OFF *relative_off, size_t size, F f, P p) {
FlagPrefixSumOMP(histogram, relative_off, size, f);
#pragma omp for
for (size_t i = 0u; i < size; i++) {
if (!(p(i))) {
auto off = i - relative_off[i];
output[off] = input[i];
}
}
#pragma omp single
{
if (size >= 1) {
log_info("Selected: %zu", size - relative_off[size - 1]);
}
}
}
template<typename OFF, typename F>
void Histogram(size_t size, OFF *&bucket_ptrs, int32_t num_buckets, F f, Timer *timer = nullptr) {
// Histogram.
auto local_buf = (uint8_t *) calloc(num_buckets, sizeof(uint8_t));
#pragma omp for
for (size_t i = 0u; i < size; i++) {
auto src = f(i);
local_buf[src]++;
if (local_buf[src] == 0xff) {
__sync_fetch_and_add(&bucket_ptrs[src], 0xff);
local_buf[src] = 0;
}
}
#pragma omp single
if (timer != nullptr)log_info("[%s]: Local Comp Time: %.9lfs", __FUNCTION__, timer->elapsed());
for (size_t i = 0; i < num_buckets; i++) {
if (local_buf[i] != 0) {
__sync_fetch_and_add(&bucket_ptrs[i], local_buf[i]);
}
}
#pragma omp barrier
free(local_buf);
}
template<typename OFF, typename F>
void HistogramAtomic(size_t size, OFF *&bucket_ptrs, int32_t num_buckets, F f) {
// Histogram.
#pragma omp for
for (size_t i = 0u; i < size; i++) {
auto src = f(i);
__sync_fetch_and_add(&bucket_ptrs[src], 1);
}
}
/*
* Require an output array,
* f: is the property for the bucket ID, given an index on the input array
* Inefficient when there are lots of contentions because of atomic operations
*/
template<typename H, typename T, typename OFF, typename F>
void BucketSort(vector<H> &histogram, T *&input, T *&output,
OFF *&cur_write_off, OFF *&bucket_ptrs,
size_t size, int32_t num_buckets, F f, Timer *timer = nullptr) {
// Populate.
#pragma omp single
{
bucket_ptrs = (OFF *) malloc(sizeof(OFF) * (num_buckets + 1));
cur_write_off = (OFF *) malloc(sizeof(OFF) * (num_buckets + 1));
cur_write_off[0] = 0;
}
MemSetOMP(bucket_ptrs, 0, num_buckets + 1);
Histogram(size, bucket_ptrs, num_buckets, f, timer);
// HistogramAtomic(size, bucket_ptrs, num_buckets, f);
#pragma omp single
if (timer != nullptr)log_info("[%s]: Histogram, Time: %.9lfs", __FUNCTION__, timer->elapsed());
InclusivePrefixSumOMP(histogram, cur_write_off + 1, num_buckets, [&bucket_ptrs](uint32_t it) {
return bucket_ptrs[it];
});
MemCpyOMP(bucket_ptrs, cur_write_off, num_buckets + 1);
#pragma omp single
{
if (timer != nullptr)log_info("[%s]: Before Scatter, Time: %.9lfs", __FUNCTION__, timer->elapsed());
}
// Scatter.
#pragma omp for
for (size_t i = 0u; i < size; i++) {
auto element = input[i];
auto bucket_id = f(i);
auto old_offset = __sync_fetch_and_add(&(cur_write_off[bucket_id]), 1);
output[old_offset] = element;
}
#pragma omp single
{
if (timer != nullptr)log_info("[%s]: Before Sort, Time: %.9lfs", __FUNCTION__, timer->elapsed());
}
#pragma omp barrier
}
template<typename H, typename T, typename OFF, typename F>
void BucketSortSmallBuckets(vector<H> &histogram, T *&input, T *&output,
OFF *&cur_write_off, OFF *&bucket_ptrs,
size_t size, int32_t num_buckets, F f, Timer *timer = nullptr) {
using BufT= LocalWriteBuffer<T, uint32_t>;
auto cap = max<int>(CACHE_LINE_ENTRY, LOCAL_BUDGET / num_buckets / sizeof(T));
auto bucket_write_buffers = (BufT *) malloc(num_buckets * sizeof(BufT));
auto bucket_buffers = (T *) malloc(cap * num_buckets * sizeof(T));
// Populate.
#pragma omp single
{
int max_omp_threads = omp_get_num_threads();
log_info("[%s]: Mem Size Buckets: %zu, Bucket#: %d",
__FUNCTION__,
cap * num_buckets * sizeof(T) * max_omp_threads, num_buckets);
bucket_ptrs = (uint32_t *) malloc(sizeof(OFF) * (num_buckets + 1));
cur_write_off = (uint32_t *) malloc(sizeof(OFF) * (num_buckets + 1));
cur_write_off[0] = 0;
}
MemSetOMP(bucket_ptrs, 0, num_buckets + 1);
Histogram(size, bucket_ptrs, num_buckets, f);
#pragma omp barrier
InclusivePrefixSumOMP(histogram, cur_write_off + 1, num_buckets, [&bucket_ptrs](uint32_t it) {
return bucket_ptrs[it];
});
MemCpyOMP(bucket_ptrs, cur_write_off, num_buckets + 1);
#pragma omp single
{
if (timer != nullptr)log_info("[%s]: Before Scatter, Time: %.9lfs", __FUNCTION__, timer->elapsed());
}
for (auto i = 0; i < num_buckets; i++) {
bucket_write_buffers[i] = BufT(bucket_buffers + cap * i, cap, output, &cur_write_off[i]);
}
#pragma omp barrier
// Scatter.
#pragma omp for
for (size_t i = 0u; i < size; i++) {
auto element = input[i];
auto bucket_id = f(i);
bucket_write_buffers[bucket_id].push(element);
}
for (auto i = 0; i < num_buckets; i++) {
bucket_write_buffers[i].submit_if_possible();
}
#pragma omp barrier
#pragma omp single
{
if (timer != nullptr)log_info("[%s]: Before Sort, Time: %.9lfs", __FUNCTION__, timer->elapsed());
}
free(bucket_buffers);
free(bucket_write_buffers);
#pragma omp barrier
} |
GB_unop__erf_fp32_fp32.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__erf_fp32_fp32
// op(A') function: GB_unop_tran__erf_fp32_fp32
// C type: float
// A type: float
// cast: float cij = aij
// unaryop: cij = erff (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 = erff (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] = erff (z) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_ERF || GxB_NO_FP32)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop_apply__erf_fp32_fp32
(
float *Cx, // Cx and Ax may be aliased
const float *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++)
{
float aij = Ax [p] ;
float z = aij ;
Cx [p] = erff (z) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop_tran__erf_fp32_fp32
(
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
|
convolution_3x3_pack4.h | // Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2022 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_winograd63_transform_kernel_pack4_sse(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 = pb-pa-inch/pa-64-outch/pb
kernel_tm_pack4.create(inch / 4, 64, outch / 4, (size_t)4u * 4 * 4, 4 * 4);
for (int q = 0; q + 3 < outch; q += 4)
{
Mat g0 = kernel_tm_pack4.channel(q / 4);
for (int k = 0; k < 64; k++)
{
float* g00 = g0.row<float>(k);
for (int p = 0; p + 3 < inch; p += 4)
{
for (int i = 0; i < 4; i++)
{
for (int j = 0; j < 4; j++)
{
const float* k00 = kernel_tm.channel(q + j).row(p + i);
g00[0] = k00[k];
g00++;
}
}
}
}
}
}
static void conv3x3s1_winograd63_pack4_sse(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;
int tiles = w_tiles * h_tiles;
bottom_blob_tm.create(tiles, 64, inch, elemsize, elempack, opt.workspace_allocator);
conv3x3s1_winograd63_transform_input_pack4_sse(bottom_blob_bordered, bottom_blob_tm, opt);
}
bottom_blob_bordered = Mat();
// END transform input
// BEGIN dot
Mat top_blob_tm;
convolution_winograd_dot_pack4_sse(bottom_blob_tm, outch, kernel_tm, top_blob_tm, opt);
// 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, elemsize, elempack, opt.workspace_allocator);
}
{
conv3x3s1_winograd63_transform_output_pack4_sse(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_winograd43_transform_kernel_pack4_sse(const Mat& kernel, Mat& kernel_tm_pack4, int inch, int outch, const Option& opt)
{
// winograd43 transform kernel
Mat kernel_tm(6 * 6, inch, outch);
const float ktm[6][3] = {
{1.0f / 4, 0.0f, 0.0f},
{-1.0f / 6, -1.0f / 6, -1.0f / 6},
{-1.0f / 6, 1.0f / 6, -1.0f / 6},
{1.0f / 24, 1.0f / 12, 1.0f / 6},
{1.0f / 24, -1.0f / 12, 1.0f / 6},
{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
const float* k0 = kernel0;
const float* k1 = kernel0 + 3;
const float* k2 = kernel0 + 6;
// h
float tmp[6][3];
for (int i = 0; i < 6; 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];
}
// U
for (int j = 0; j < 6; j++)
{
float* tmpp = &tmp[j][0];
for (int i = 0; i < 6; i++)
{
kernel_tm0[j * 6 + i] = tmpp[0] * ktm[i][0] + tmpp[1] * ktm[i][1] + tmpp[2] * ktm[i][2];
}
}
}
}
// interleave
// src = 36-inch-outch
// dst = pb-pa-inch/pa-36-outch/pb
kernel_tm_pack4.create(inch / 4, 36, outch / 4, (size_t)4u * 4 * 4, 4 * 4);
for (int q = 0; q + 3 < outch; q += 4)
{
Mat g0 = kernel_tm_pack4.channel(q / 4);
for (int k = 0; k < 36; k++)
{
float* g00 = g0.row<float>(k);
for (int p = 0; p + 3 < inch; p += 4)
{
for (int i = 0; i < 4; i++)
{
for (int j = 0; j < 4; j++)
{
const float* k00 = kernel_tm.channel(q + j).row(p + i);
g00[0] = k00[k];
g00++;
}
}
}
}
}
}
static void conv3x3s1_winograd43_pack4_sse(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 4n+2
Mat bottom_blob_bordered = bottom_blob;
outw = (outw + 3) / 4 * 4;
outh = (outh + 3) / 4 * 4;
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 / 4;
int h_tiles = outh / 4;
int tiles = w_tiles * h_tiles;
bottom_blob_tm.create(tiles, 36, inch, elemsize, elempack, opt.workspace_allocator);
conv3x3s1_winograd43_transform_input_pack4_sse(bottom_blob_bordered, bottom_blob_tm, opt);
}
bottom_blob_bordered = Mat();
// END transform input
// BEGIN dot
Mat top_blob_tm;
convolution_winograd_dot_pack4_sse(bottom_blob_tm, outch, kernel_tm, top_blob_tm, opt);
// 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, elemsize, elempack, opt.workspace_allocator);
}
{
conv3x3s1_winograd43_transform_output_pack4_sse(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_winograd23_transform_kernel_pack4_sse(const Mat& kernel, Mat& kernel_tm_pack4, int inch, int outch, const Option& opt)
{
// winograd23 transform kernel
Mat kernel_tm(4 * 4, inch, outch);
const float ktm[4][3] = {
{1.0f, 0.0f, 0.0f},
{1.0f / 2, 1.0f / 2, 1.0f / 2},
{1.0f / 2, -1.0f / 2, 1.0f / 2},
{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
const float* k0 = kernel0;
const float* k1 = kernel0 + 3;
const float* k2 = kernel0 + 6;
// h
float tmp[4][3];
for (int i = 0; i < 4; 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];
}
// U
for (int j = 0; j < 4; j++)
{
float* tmpp = &tmp[j][0];
for (int i = 0; i < 4; i++)
{
kernel_tm0[j * 4 + i] = tmpp[0] * ktm[i][0] + tmpp[1] * ktm[i][1] + tmpp[2] * ktm[i][2];
}
}
}
}
// interleave
// src = 16-inch-outch
// dst = pb-pa-inch/pa-16-outch/pb
kernel_tm_pack4.create(inch / 4, 16, outch / 4, (size_t)4u * 4 * 4, 4 * 4);
for (int q = 0; q + 3 < outch; q += 4)
{
Mat g0 = kernel_tm_pack4.channel(q / 4);
for (int k = 0; k < 16; k++)
{
float* g00 = g0.row<float>(k);
for (int p = 0; p + 3 < inch; p += 4)
{
for (int i = 0; i < 4; i++)
{
for (int j = 0; j < 4; j++)
{
const float* k00 = kernel_tm.channel(q + j).row(p + i);
g00[0] = k00[k];
g00++;
}
}
}
}
}
}
static void conv3x3s1_winograd23_pack4_sse(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 2n+2
Mat bottom_blob_bordered = bottom_blob;
outw = (outw + 1) / 2 * 2;
outh = (outh + 1) / 2 * 2;
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 / 2;
int h_tiles = outh / 2;
int tiles = w_tiles * h_tiles;
bottom_blob_tm.create(tiles, 16, inch, elemsize, elempack, opt.workspace_allocator);
conv3x3s1_winograd23_transform_input_pack4_sse(bottom_blob_bordered, bottom_blob_tm, opt);
}
bottom_blob_bordered = Mat();
// END transform input
// BEGIN dot
Mat top_blob_tm;
convolution_winograd_dot_pack4_sse(bottom_blob_tm, outch, kernel_tm, top_blob_tm, opt);
// 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, elemsize, elempack, opt.workspace_allocator);
}
{
conv3x3s1_winograd23_transform_output_pack4_sse(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);
}
|
llinear_openmp.c | /*
mex llinear_openmp.c CFLAGS='\$CFLAGS -fopenmp -O3' LDFLAGS='\$LDFLAGS -fopenmp'
*/
#include <math.h>
#include <stdio.h>
#include <stdint.h>
typedef uint16_t char16_t;
#include "mex.h"
#define max(a,b) (a > b) ? a : b
void forward_elim(int, double **, int *);
void solve(int, double **, int *, double * , double *);
/*******************************************************/
void forward_elim (int matrix_size, double **A, int *L)
{
int i,j,k, tempi, tempk;
double *S;
double xmult, smax, rmax, ratio;
S = calloc((matrix_size+1), sizeof(double));
for (i = 1; i <= matrix_size; i++)
{
L[i] = i;
smax = 0.0;
for (j = 1; j <= matrix_size; j++)
smax = max (smax, fabs(A[i][j]));
S[i] = smax;
}
for (k = 1; k < matrix_size; k++)
{
rmax = 0.0;
for (i = k ; i <= matrix_size; i++)
{
tempi = L[i];
ratio = fabs(A[tempi][k]/ S[tempi]);
if (ratio > rmax)
{
rmax = ratio;
j = i;
}
}
tempk = L[j];
L[j] = L[k];
L[k] = tempk;
for (i = k+1; i <= matrix_size; i++)
{
tempi = L[i];
xmult = A[tempi][k] /A[tempk][k];
A[tempi][k] = xmult;
for (j = k+1; j<= matrix_size; j++)
A[tempi][j] -= xmult * A[tempk][j];
}
}
}/* forward_elim */
/**********************************************************/
void solve (int matrix_size, double **A, int *L, double *B, double *X)
{
int i,j, k, tempi, tempk, tempn;
double sum;
for (k = 1; k < matrix_size ; k++)
{
tempk = L[k];
for (i = k+1; i <= matrix_size; i++)
{
tempi = L[i];
B[tempi] -= A[tempi][k] * B[tempk];
}
}
tempn = L[matrix_size];
X[matrix_size] = B[tempn] / A[tempn][matrix_size];
for (i = matrix_size -1; i>= 1; i--)
{
tempi = L[i];
sum = B[tempi];
for (j = i+1; j <= matrix_size ; j++)
sum -= A[tempi][j] * X[j];
X[i] = sum / A[tempi][i];
}
}
double lfitlinear(double *xin, double *yin, double *x, const double *bw, const int n, const int p)
{
int i, j, k, matrix_size = p+1;
double K, Z, yout;
double **A, *t, *b;
int *L;
A = calloc((matrix_size+1),sizeof(double *));
for (j=0;j<=matrix_size;j++){
A[j] = calloc((matrix_size+1),sizeof(double));
}
t = calloc((matrix_size+1),sizeof(double));
b = calloc((matrix_size+1),sizeof(double));
L = calloc((matrix_size+1),sizeof(double));
for (i=0;i<n;i++){
/* check if i-th xin falls between (x-h,x+h) */
K = 1;
for (j=1;j<=p;j++){
Z = xin[j-1+i*p]-x[j-1];
if (fabs(Z)<bw[j-1]){
Z = Z/bw[j-1];
K *= 0.75*(1-Z*Z);
}
else{
K = 0;
break;
}
}
if (K==0)
continue;
A[1][1] += K; t[1] += K*yin[i];
for (k=2;k<=matrix_size;k++){
A[1][k] += K*(xin[k-2+i*p]-x[k-2]);
t[k] += K*(xin[k-2+i*p]-x[k-2])*yin[i];
}
for (j=2;j<=matrix_size;j++){
for (k=j;k<=matrix_size;k++){
A[j][k] += K*(xin[j-2+i*p]-x[j-2])*(xin[k-2+i*p]-x[k-2]);
}
}
}
for (j=1;j<=matrix_size;j++){
for (k=j;k<=matrix_size;k++)
A[k][j] = A[j][k];
}
for (j=2;j<=matrix_size;j++)
A[j][j] += 1e-8;
forward_elim(matrix_size,A,L);
solve(matrix_size,A,L,t,b);
yout = b[1];
for (j=0;j<=matrix_size;j++)
free(A[j]);
free(A);
free(t);
free(b);
free(L);
return yout;
}
void llinear(double *xin, double *yin, double *xout, double *yout, const double *bw, const int m, const int n, const int p)
{
int i, j;
double *x;
#pragma omp parallel private(i,x)
{
x = calloc(p,sizeof(double *));
#pragma omp for
for (i=0;i<m;i++)
{
for (j=0;j<p;j++){
x[j] = xout[j+i*p];
}
yout[i] = (double)lfitlinear(xin,yin,x,bw,n,p);
}
free(x);
}
}
/* --------------------------------------------------------------------------
Gateway function for MATLAB
Usage in MATLAB: yhat = llineard(xin,yin,xout,bw);
xin: input designs; p*n matrix (in fact, an p*n by 1 array)
yin: input data points; n*1 array
xout: grid points to estimate; p*m matrix (in fact, an p*m by 1 array)
bw: bandwidth; p*1 array
-------------------------------------------------------------------------- */
void mexFunction( int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[])
{
double *xin, *yin, *xout, *yout, *bw;
int m,n,p;
/* create a pointer to the real data in the input matrix */
xin = mxGetPr(prhs[0]);
/* get the value of the scalar input */
yin = mxGetPr(prhs[1]);
xout = mxGetPr(prhs[2]);
bw = mxGetPr(prhs[3]);
/* get dimensions of the input matrix */
p = mxGetM(prhs[0]); /* dimension of xin */
n = mxGetN(prhs[0]); /* length of xin */
m = mxGetN(prhs[2]); /* length of xout */
/* create the output matrix */
plhs[0] = mxCreateDoubleMatrix(m,1,mxREAL);
/* get a pointer to the real data in the output matrix */
yout = mxGetPr(plhs[0]);
/* call the computational routine */
llinear(xin,yin,xout,yout,bw,m,n,p);
}
|
threadpool.h | /* Copyright 2015 The TensorFlow 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.
==============================================================================*/
/* Modifications Copyright (c) Microsoft. */
#pragma once
#include <string>
#include <vector>
#include <functional>
#include <memory>
#include "core/common/common.h"
#include "core/platform/env.h"
#include "core/common/optional.h"
#include <functional>
#include <memory>
// This file use PIMPL to avoid having eigen headers here
namespace Eigen {
class Allocator;
class ThreadPoolInterface;
struct ThreadPoolDevice;
} // namespace Eigen
namespace onnxruntime {
struct TensorOpCost {
double bytes_loaded;
double bytes_stored;
double compute_cycles;
};
template <typename Environment>
class ThreadPoolTempl;
namespace concurrency {
class ThreadPool {
public:
// Scheduling strategies for ParallelFor. The strategy governs how the given
// units of work are distributed among the available threads in the
// threadpool.
enum class SchedulingStrategy {
// The Adaptive scheduling strategy adaptively chooses the shard sizes based
// on the cost of each unit of work, and the cost model of the underlying
// threadpool device.
//
// The 'cost_per_unit' is an estimate of the number of CPU cycles (or
// nanoseconds if not CPU-bound) to complete a unit of work. Overestimating
// creates too many shards and CPU time will be dominated by per-shard
// overhead, such as Context creation. Underestimating may not fully make
// use of the specified parallelism, and may also cause inefficiencies due
// to load balancing issues and stragglers.
kAdaptive,
// The Fixed Block Size scheduling strategy shards the given units of work
// into shards of fixed size. In case the total number of units is not
// evenly divisible by 'block_size', at most one of the shards may be of
// smaller size. The exact number of shards may be found by a call to
// NumShardsUsedByFixedBlockSizeScheduling.
//
// Each shard may be executed on a different thread in parallel, depending
// on the number of threads available in the pool. Note that when there
// aren't enough threads in the pool to achieve full parallelism, function
// calls will be automatically queued.
kFixedBlockSize
};
// Contains additional parameters for either the Adaptive or the Fixed Block
// Size scheduling strategy.
class SchedulingParams {
public:
explicit SchedulingParams(SchedulingStrategy strategy, optional<int64_t> cost_per_unit,
optional<std::ptrdiff_t> block_size)
: strategy_(strategy), cost_per_unit_(cost_per_unit), block_size_(block_size) {
}
SchedulingStrategy strategy() const {
return strategy_;
}
optional<int64_t> cost_per_unit() const {
return cost_per_unit_;
}
optional<std::ptrdiff_t> block_size() const {
return block_size_;
}
private:
// The underlying Scheduling Strategy for which this instance contains
// additional parameters.
SchedulingStrategy strategy_;
// The estimated cost per unit of work in number of CPU cycles (or
// nanoseconds if not CPU-bound). Only applicable for Adaptive scheduling
// strategy.
optional<int64_t> cost_per_unit_;
// The block size of each shard. Only applicable for Fixed Block Size
// scheduling strategy.
optional<std::ptrdiff_t> block_size_;
};
#ifdef _WIN32
using NAME_CHAR_TYPE = wchar_t;
#else
using NAME_CHAR_TYPE = char;
#endif
// Constructs a pool that contains "num_threads" threads with specified
// "name". env->StartThread() is used to create individual threads with the
// given ThreadOptions. If "low_latency_hint" is true the thread pool
// implementation may use it as a hint that lower latency is preferred at the
// cost of higher CPU usage, e.g. by letting one or more idle threads spin
// wait. Conversely, if the threadpool is used to schedule high-latency
// operations like I/O the hint should be set to false.
//
// REQUIRES: num_threads > 0
// The allocator parameter is only used for creating a Eigen::ThreadPoolDevice to be used with Eigen Tensor classes.
ThreadPool(Env* env, const ThreadOptions& thread_options, const NAME_CHAR_TYPE* name, int num_threads,
bool low_latency_hint, Eigen::Allocator* allocator = nullptr);
// Constructs a pool that wraps around the thread::ThreadPoolInterface
// instance provided by the caller. Caller retains ownership of
// `user_threadpool` and must ensure its lifetime is longer than the
// ThreadPool instance.
ThreadPool(Eigen::ThreadPoolInterface* user_threadpool, Eigen::Allocator* allocator);
// Waits until all scheduled work has finished and then destroy the
// set of threads.
~ThreadPool();
// Schedules fn() for execution in the pool of threads.
void Schedule(std::function<void()> fn);
// Returns the number of shards used by ParallelForFixedBlockSizeScheduling
// with these parameters.
int NumShardsUsedByFixedBlockSizeScheduling(std::ptrdiff_t total, std::ptrdiff_t block_size);
// ParallelFor shards the "total" units of work assuming each unit of work
// having roughly "cost_per_unit" cost, in cycles. Each unit of work is
// indexed 0, 1, ..., total - 1. Each shard contains 1 or more units of work
// and the total cost of each shard is roughly the same.
//
// "cost_per_unit" is an estimate of the number of CPU cycles (or nanoseconds
// if not CPU-bound) to complete a unit of work. Overestimating creates too
// many shards and CPU time will be dominated by per-shard overhead, such as
// Context creation. Underestimating may not fully make use of the specified
// parallelism, and may also cause inefficiencies due to load balancing
// issues and stragglers.
void ParallelFor(std::ptrdiff_t total, double cost_per_unit,
const std::function<void(std::ptrdiff_t first, std::ptrdiff_t last)>& fn);
static void TryParallelFor(concurrency::ThreadPool* tp, std::ptrdiff_t total, double cost_per_unit,
const std::function<void(std::ptrdiff_t first, std::ptrdiff_t last)>& fn) {
TryParallelFor(tp, total, TensorOpCost{0, 0, static_cast<double>(cost_per_unit)}, fn);
}
void ParallelFor(std::ptrdiff_t total, const TensorOpCost& cost_per_unit,
const std::function<void(std::ptrdiff_t first, std::ptrdiff_t)>& fn);
static void TryParallelFor(concurrency::ThreadPool* tp, std::ptrdiff_t total, const TensorOpCost& cost_per_unit,
const std::function<void(std::ptrdiff_t first, std::ptrdiff_t last)>& fn) {
#ifdef _OPENMP
ORT_UNUSED_PARAMETER(cost_per_unit);
std::ptrdiff_t num_threads = concurrency::ThreadPool::NumThreads(tp);
if (total < num_threads) {
num_threads = total;
}
#pragma omp parallel for
for (std::ptrdiff_t i = 0; i < num_threads; i++) {
std::ptrdiff_t start, work_remaining;
PartitionWork(i, num_threads, total, &start, &work_remaining);
std::ptrdiff_t end = start + work_remaining;
fn(start, end);
}
#else
if (tp == nullptr) {
fn(0, total);
return;
}
tp->ParallelFor(total, cost_per_unit, fn);
#endif
}
// Similar to ParallelFor above, but takes the specified scheduling strategy
// into account.
void
ParallelFor(std::ptrdiff_t total, const SchedulingParams& scheduling_params,
const std::function<void(std::ptrdiff_t, std::ptrdiff_t)>& fn);
static void TryParallelFor(concurrency::ThreadPool* tp, std::ptrdiff_t total, const SchedulingParams& scheduling_params,
const std::function<void(std::ptrdiff_t first, std::ptrdiff_t last)>& fn) {
#ifdef _OPENMP
ORT_UNUSED_PARAMETER(scheduling_params);
std::ptrdiff_t num_threads = concurrency::ThreadPool::NumThreads(tp);
if (total < num_threads) {
num_threads = total;
}
#pragma omp parallel for
for (std::ptrdiff_t i = 0; i < num_threads; i++) {
std::ptrdiff_t start, work_remaining;
PartitionWork(i, num_threads, total, &start, &work_remaining);
std::ptrdiff_t end = start + work_remaining;
fn(start, end);
}
#else
if (tp == nullptr) {
fn(0, total);
return;
}
tp->ParallelFor(total, scheduling_params, fn);
#endif
} // namespace concurrency
// Prefer using this API to get the number of threads unless you know what you're doing.
// This API takes into account if openmp is enabled/disabled and if the thread pool ptr is nullptr.
static int NumThreads(const concurrency::ThreadPool* tp);
// Returns the number of threads in the pool. Preferably use the static version of this API instead.
int NumThreads() const;
// Returns current thread id between 0 and NumThreads() - 1, if called from a
// thread in the pool. Returns -1 otherwise.
int CurrentThreadId() const;
// If ThreadPool implementation is compatible with Eigen::ThreadPoolInterface,
// returns a non-null pointer. The caller does not own the object the returned
// pointer points to, and should not attempt to delete.
Eigen::ThreadPoolInterface* AsEigenThreadPool() const;
// Directly schedule the 'total' tasks to the underlying threadpool, without
// cutting them by halves
void SimpleParallelFor(std::ptrdiff_t total, std::function<void(std::ptrdiff_t)> fn);
/**
* Tries to call the given function in parallel, with calls split into (num_batches) batches.
*\param num_batches If it is zero, it will be replaced to the value of NumThreads().
*\param fn A std::function or STL style functor with signature of "void f(int32_t);"
* Pitfall: Caller should cap `num_batches` to a reasonable value based on the cost of `fn` and the value of `total`.
*For example, if fn is as simple as: int sum=0; fn = [&](int i){sum +=i;} and `total` is 100, then num_batches should
*be just 1.
*
* ```
**/
template <typename F>
inline static void TryBatchParallelFor(ThreadPool* tp, std::ptrdiff_t total, F&& fn, std::ptrdiff_t num_batches) {
#ifdef _OPENMP
ORT_UNUSED_PARAMETER(tp);
ORT_UNUSED_PARAMETER(num_batches);
#pragma omp parallel for
for (std::ptrdiff_t i = 0; i < total; ++i) {
fn(i);
}
#else
if (tp == nullptr) {
for (std::ptrdiff_t i = 0; i < total; ++i) {
// In many cases, fn can be inlined here.
fn(i);
}
return;
}
if (total <= 0)
return;
if (total == 1) {
fn(0);
return;
}
if (num_batches <= 0) {
num_batches = std::min<ptrdiff_t>(total, tp->NumThreads());
}
if (num_batches <= 1) {
for (int i = 0; i < total; i++) {
fn(i);
}
return;
}
tp->SimpleParallelFor(num_batches, [&](std::ptrdiff_t batch_index) {
std::ptrdiff_t start, work_remaining;
PartitionWork(batch_index, num_batches, total, &start, &work_remaining);
std::ptrdiff_t end = start + work_remaining;
for (std::ptrdiff_t i = start; i < end; i++) {
fn(i);
}
});
#endif
}
#ifndef _OPENMP
//Deprecated. Please avoid using Eigen Tensor because it will blow up binary size quickly.
Eigen::ThreadPoolDevice& Device() {
return *threadpool_device_;
}
#endif
ORT_DISALLOW_COPY_AND_ASSIGNMENT(ThreadPool);
private:
// Divides the work represented by the range [0, total) into k shards.
// Calls fn(i*block_size, (i+1)*block_size) from the ith shard (0 <= i < k).
// Each shard may be executed on a different thread in parallel, depending on
// the number of threads available in the pool.
// When (i+1)*block_size > total, fn(i*block_size, total) is called instead.
// Here, k = NumShardsUsedByFixedBlockSizeScheduling(total, block_size).
// Requires 0 < block_size <= total.
void ParallelForFixedBlockSizeScheduling(std::ptrdiff_t total, std::ptrdiff_t block_size,
const std::function<void(std::ptrdiff_t, std::ptrdiff_t)>& fn);
ThreadOptions thread_options_;
// underlying_threadpool_ is the user_threadpool if user_threadpool is
// provided in the constructor. Otherwise it is the eigen_threadpool_.
Eigen::ThreadPoolInterface* underlying_threadpool_;
// eigen_threadpool_ is instantiated and owned by thread::ThreadPool if
// user_threadpool is not in the constructor.
std::unique_ptr<ThreadPoolTempl<Env> > eigen_threadpool_;
#ifndef _OPENMP
std::unique_ptr<Eigen::ThreadPoolDevice> threadpool_device_;
#endif
// Copied from MlasPartitionWork
static void PartitionWork(std::ptrdiff_t ThreadId, std::ptrdiff_t ThreadCount, std::ptrdiff_t TotalWork,
std::ptrdiff_t* WorkIndex, std::ptrdiff_t* WorkRemaining) {
const std::ptrdiff_t WorkPerThread = TotalWork / ThreadCount;
const std::ptrdiff_t WorkPerThreadExtra = TotalWork % ThreadCount;
if (ThreadId < WorkPerThreadExtra) {
*WorkIndex = (WorkPerThread + 1) * ThreadId;
*WorkRemaining = WorkPerThread + 1;
} else {
*WorkIndex = WorkPerThread * ThreadId + WorkPerThreadExtra;
*WorkRemaining = WorkPerThread;
}
}
}; // namespace concurrency
} // namespace concurrency
} // namespace onnxruntime
|
GeneralMatrixMatrix.h | // This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#ifndef EIGEN_GENERAL_MATRIX_MATRIX_H
#define EIGEN_GENERAL_MATRIX_MATRIX_H
namespace Eigen {
namespace internal {
template<typename _LhsScalar, typename _RhsScalar> class level3_blocking;
/* Specialization for a row-major destination matrix => simple transposition of the product */
template<
typename Index,
typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs,
typename RhsScalar, int RhsStorageOrder, bool ConjugateRhs>
struct general_matrix_matrix_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,RhsStorageOrder,ConjugateRhs,RowMajor>
{
typedef gebp_traits<RhsScalar,LhsScalar> Traits;
typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
static EIGEN_STRONG_INLINE void run(
Index rows, Index cols, Index depth,
const LhsScalar* lhs, Index lhsStride,
const RhsScalar* rhs, Index rhsStride,
ResScalar* res, Index resStride,
ResScalar alpha,
level3_blocking<RhsScalar,LhsScalar>& blocking,
GemmParallelInfo<Index>* info = 0)
{
// transpose the product such that the result is column major
general_matrix_matrix_product<Index,
RhsScalar, RhsStorageOrder==RowMajor ? ColMajor : RowMajor, ConjugateRhs,
LhsScalar, LhsStorageOrder==RowMajor ? ColMajor : RowMajor, ConjugateLhs,
ColMajor>
::run(cols,rows,depth,rhs,rhsStride,lhs,lhsStride,res,resStride,alpha,blocking,info);
}
};
/* Specialization for a col-major destination matrix
* => Blocking algorithm following Goto's paper */
template<
typename Index,
typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs,
typename RhsScalar, int RhsStorageOrder, bool ConjugateRhs>
struct general_matrix_matrix_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,RhsStorageOrder,ConjugateRhs,ColMajor>
{
typedef gebp_traits<LhsScalar,RhsScalar> Traits;
typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
static void run(Index rows, Index cols, Index depth,
const LhsScalar* _lhs, Index lhsStride,
const RhsScalar* _rhs, Index rhsStride,
ResScalar* _res, Index resStride,
ResScalar alpha,
level3_blocking<LhsScalar,RhsScalar>& blocking,
GemmParallelInfo<Index>* info = 0)
{
typedef const_blas_data_mapper<LhsScalar, Index, LhsStorageOrder> LhsMapper;
typedef const_blas_data_mapper<RhsScalar, Index, RhsStorageOrder> RhsMapper;
typedef blas_data_mapper<typename Traits::ResScalar, Index, ColMajor> ResMapper;
LhsMapper lhs(_lhs,lhsStride);
RhsMapper rhs(_rhs,rhsStride);
ResMapper res(_res, resStride);
Index kc = blocking.kc(); // cache block size along the K direction
Index mc = (std::min)(rows,blocking.mc()); // cache block size along the M direction
Index nc = (std::min)(cols,blocking.nc()); // cache block size along the N direction
gemm_pack_lhs<LhsScalar, Index, LhsMapper, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
gemm_pack_rhs<RhsScalar, Index, RhsMapper, Traits::nr, RhsStorageOrder> pack_rhs;
gebp_kernel<LhsScalar, RhsScalar, Index, ResMapper, Traits::mr, Traits::nr, ConjugateLhs, ConjugateRhs> gebp;
#ifdef EIGEN_HAS_OPENMP
if(info)
{
// this is the parallel version!
Index tid = omp_get_thread_num();
Index threads = omp_get_num_threads();
LhsScalar* blockA = blocking.blockA();
eigen_internal_assert(blockA!=0);
std::size_t sizeB = kc*nc;
ei_declare_aligned_stack_constructed_variable(RhsScalar, blockB, sizeB, 0);
// For each horizontal panel of the rhs, and corresponding vertical panel of the lhs...
for(Index k=0; k<depth; k+=kc)
{
const Index actual_kc = (std::min)(k+kc,depth)-k; // => rows of B', and cols of the A'
// In order to reduce the chance that a thread has to wait for the other,
// let's start by packing B'.
pack_rhs(blockB, rhs.getSubMapper(k,0), actual_kc, nc);
// Pack A_k to A' in a parallel fashion:
// each thread packs the sub block A_k,i to A'_i where i is the thread id.
// However, before copying to A'_i, we have to make sure that no other thread is still using it,
// i.e., we test that info[tid].users equals 0.
// Then, we set info[tid].users to the number of threads to mark that all other threads are going to use it.
while(info[tid].users!=0) {}
info[tid].users += threads;
pack_lhs(blockA+info[tid].lhs_start*actual_kc, lhs.getSubMapper(info[tid].lhs_start,k), actual_kc, info[tid].lhs_length);
// Notify the other threads that the part A'_i is ready to go.
info[tid].sync = k;
// Computes C_i += A' * B' per A'_i
for(Index shift=0; shift<threads; ++shift)
{
Index i = (tid+shift)%threads;
// At this point we have to make sure that A'_i has been updated by the thread i,
// we use testAndSetOrdered to mimic a volatile access.
// However, no need to wait for the B' part which has been updated by the current thread!
if (shift>0) {
while(info[i].sync!=k) {
}
}
gebp(res.getSubMapper(info[i].lhs_start, 0), blockA+info[i].lhs_start*actual_kc, blockB, info[i].lhs_length, actual_kc, nc, alpha);
}
// Then keep going as usual with the remaining B'
for(Index j=nc; j<cols; j+=nc)
{
const Index actual_nc = (std::min)(j+nc,cols)-j;
// pack B_k,j to B'
pack_rhs(blockB, rhs.getSubMapper(k,j), actual_kc, actual_nc);
// C_j += A' * B'
gebp(res.getSubMapper(0, j), blockA, blockB, rows, actual_kc, actual_nc, alpha);
}
// Release all the sub blocks A'_i of A' for the current thread,
// i.e., we simply decrement the number of users by 1
for(Index i=0; i<threads; ++i)
#pragma omp atomic
info[i].users -= 1;
}
}
else
#endif // EIGEN_HAS_OPENMP
{
EIGEN_UNUSED_VARIABLE(info);
// this is the sequential version!
std::size_t sizeA = kc*mc;
std::size_t sizeB = kc*nc;
ei_declare_aligned_stack_constructed_variable(LhsScalar, blockA, sizeA, blocking.blockA());
ei_declare_aligned_stack_constructed_variable(RhsScalar, blockB, sizeB, blocking.blockB());
const bool pack_rhs_once = mc!=rows && kc==depth && nc==cols;
// For each horizontal panel of the rhs, and corresponding panel of the lhs...
for(Index i2=0; i2<rows; i2+=mc)
{
const Index actual_mc = (std::min)(i2+mc,rows)-i2;
for(Index k2=0; k2<depth; k2+=kc)
{
const Index actual_kc = (std::min)(k2+kc,depth)-k2;
// OK, here we have selected one horizontal panel of rhs and one vertical panel of lhs.
// => Pack lhs's panel into a sequential chunk of memory (L2/L3 caching)
// Note that this panel will be read as many times as the number of blocks in the rhs's
// horizontal panel which is, in practice, a very low number.
pack_lhs(blockA, lhs.getSubMapper(i2,k2), actual_kc, actual_mc);
// For each kc x nc block of the rhs's horizontal panel...
for(Index j2=0; j2<cols; j2+=nc)
{
const Index actual_nc = (std::min)(j2+nc,cols)-j2;
// We pack the rhs's block into a sequential chunk of memory (L2 caching)
// Note that this block will be read a very high number of times, which is equal to the number of
// micro horizontal panel of the large rhs's panel (e.g., rows/12 times).
if((!pack_rhs_once) || i2==0)
pack_rhs(blockB, rhs.getSubMapper(k2,j2), actual_kc, actual_nc);
// Everything is packed, we can now call the panel * block kernel:
gebp(res.getSubMapper(i2, j2), blockA, blockB, actual_mc, actual_kc, actual_nc, alpha);
}
}
}
}
}
};
/*********************************************************************************
* Specialization of generic_product_impl for "large" GEMM, i.e.,
* implementation of the high level wrapper to general_matrix_matrix_product
**********************************************************************************/
template<typename Scalar, typename Index, typename Gemm, typename Lhs, typename Rhs, typename Dest, typename BlockingType>
struct gemm_functor
{
gemm_functor(const Lhs& lhs, const Rhs& rhs, Dest& dest, const Scalar& actualAlpha, BlockingType& blocking)
: m_lhs(lhs), m_rhs(rhs), m_dest(dest), m_actualAlpha(actualAlpha), m_blocking(blocking)
{}
void initParallelSession(Index num_threads) const
{
m_blocking.initParallel(m_lhs.rows(), m_rhs.cols(), m_lhs.cols(), num_threads);
m_blocking.allocateA();
}
void operator() (Index row, Index rows, Index col=0, Index cols=-1, GemmParallelInfo<Index>* info=0) const
{
if(cols==-1)
cols = m_rhs.cols();
Gemm::run(rows, cols, m_lhs.cols(),
&m_lhs.coeffRef(row,0), m_lhs.outerStride(),
&m_rhs.coeffRef(0,col), m_rhs.outerStride(),
(Scalar*)&(m_dest.coeffRef(row,col)), m_dest.outerStride(),
m_actualAlpha, m_blocking, info);
}
typedef typename Gemm::Traits Traits;
protected:
const Lhs& m_lhs;
const Rhs& m_rhs;
Dest& m_dest;
Scalar m_actualAlpha;
BlockingType& m_blocking;
};
template<int StorageOrder, typename LhsScalar, typename RhsScalar, int MaxRows, int MaxCols, int MaxDepth, int KcFactor=1,
bool FiniteAtCompileTime = MaxRows!=Dynamic && MaxCols!=Dynamic && MaxDepth != Dynamic> class gemm_blocking_space;
template<typename _LhsScalar, typename _RhsScalar>
class level3_blocking
{
typedef _LhsScalar LhsScalar;
typedef _RhsScalar RhsScalar;
protected:
LhsScalar* m_blockA;
RhsScalar* m_blockB;
Index m_mc;
Index m_nc;
Index m_kc;
public:
level3_blocking()
: m_blockA(0), m_blockB(0), m_mc(0), m_nc(0), m_kc(0)
{}
inline Index mc() const { return m_mc; }
inline Index nc() const { return m_nc; }
inline Index kc() const { return m_kc; }
inline LhsScalar* blockA() { return m_blockA; }
inline RhsScalar* blockB() { return m_blockB; }
};
template<int StorageOrder, typename _LhsScalar, typename _RhsScalar, int MaxRows, int MaxCols, int MaxDepth, int KcFactor>
class gemm_blocking_space<StorageOrder,_LhsScalar,_RhsScalar,MaxRows, MaxCols, MaxDepth, KcFactor, true /* == FiniteAtCompileTime */>
: public level3_blocking<
typename conditional<StorageOrder==RowMajor,_RhsScalar,_LhsScalar>::type,
typename conditional<StorageOrder==RowMajor,_LhsScalar,_RhsScalar>::type>
{
enum {
Transpose = StorageOrder==RowMajor,
ActualRows = Transpose ? MaxCols : MaxRows,
ActualCols = Transpose ? MaxRows : MaxCols
};
typedef typename conditional<Transpose,_RhsScalar,_LhsScalar>::type LhsScalar;
typedef typename conditional<Transpose,_LhsScalar,_RhsScalar>::type RhsScalar;
typedef gebp_traits<LhsScalar,RhsScalar> Traits;
enum {
SizeA = ActualRows * MaxDepth,
SizeB = ActualCols * MaxDepth
};
#if EIGEN_MAX_STATIC_ALIGN_BYTES >= EIGEN_DEFAULT_ALIGN_BYTES
EIGEN_ALIGN_MAX LhsScalar m_staticA[SizeA];
EIGEN_ALIGN_MAX RhsScalar m_staticB[SizeB];
#else
EIGEN_ALIGN_MAX char m_staticA[SizeA * sizeof(LhsScalar) + EIGEN_DEFAULT_ALIGN_BYTES-1];
EIGEN_ALIGN_MAX char m_staticB[SizeB * sizeof(RhsScalar) + EIGEN_DEFAULT_ALIGN_BYTES-1];
#endif
public:
gemm_blocking_space(Index /*rows*/, Index /*cols*/, Index /*depth*/, Index /*num_threads*/, bool /*full_rows = false*/)
{
this->m_mc = ActualRows;
this->m_nc = ActualCols;
this->m_kc = MaxDepth;
#if EIGEN_MAX_STATIC_ALIGN_BYTES >= EIGEN_DEFAULT_ALIGN_BYTES
this->m_blockA = m_staticA;
this->m_blockB = m_staticB;
#else
this->m_blockA = reinterpret_cast<LhsScalar*>((internal::UIntPtr(m_staticA) + (EIGEN_DEFAULT_ALIGN_BYTES-1)) & ~std::size_t(EIGEN_DEFAULT_ALIGN_BYTES-1));
this->m_blockB = reinterpret_cast<RhsScalar*>((internal::UIntPtr(m_staticB) + (EIGEN_DEFAULT_ALIGN_BYTES-1)) & ~std::size_t(EIGEN_DEFAULT_ALIGN_BYTES-1));
#endif
}
void initParallel(Index, Index, Index, Index)
{}
inline void allocateA() {}
inline void allocateB() {}
inline void allocateAll() {}
};
template<int StorageOrder, typename _LhsScalar, typename _RhsScalar, int MaxRows, int MaxCols, int MaxDepth, int KcFactor>
class gemm_blocking_space<StorageOrder,_LhsScalar,_RhsScalar,MaxRows, MaxCols, MaxDepth, KcFactor, false>
: public level3_blocking<
typename conditional<StorageOrder==RowMajor,_RhsScalar,_LhsScalar>::type,
typename conditional<StorageOrder==RowMajor,_LhsScalar,_RhsScalar>::type>
{
enum {
Transpose = StorageOrder==RowMajor
};
typedef typename conditional<Transpose,_RhsScalar,_LhsScalar>::type LhsScalar;
typedef typename conditional<Transpose,_LhsScalar,_RhsScalar>::type RhsScalar;
typedef gebp_traits<LhsScalar,RhsScalar> Traits;
Index m_sizeA;
Index m_sizeB;
public:
gemm_blocking_space(Index rows, Index cols, Index depth, Index num_threads, bool l3_blocking)
{
this->m_mc = Transpose ? cols : rows;
this->m_nc = Transpose ? rows : cols;
this->m_kc = depth;
if(l3_blocking)
{
computeProductBlockingSizes<LhsScalar,RhsScalar,KcFactor>(this->m_kc, this->m_mc, this->m_nc, num_threads);
}
else // no l3 blocking
{
Index n = this->m_nc;
computeProductBlockingSizes<LhsScalar,RhsScalar,KcFactor>(this->m_kc, this->m_mc, n, num_threads);
}
m_sizeA = this->m_mc * this->m_kc;
m_sizeB = this->m_kc * this->m_nc;
}
void initParallel(Index rows, Index cols, Index depth, Index num_threads)
{
this->m_mc = Transpose ? cols : rows;
this->m_nc = Transpose ? rows : cols;
this->m_kc = depth;
eigen_internal_assert(this->m_blockA==0 && this->m_blockB==0);
Index m = this->m_mc;
computeProductBlockingSizes<LhsScalar,RhsScalar,KcFactor>(this->m_kc, m, this->m_nc, num_threads);
m_sizeA = this->m_mc * this->m_kc;
m_sizeB = this->m_kc * this->m_nc;
}
void allocateA()
{
if(this->m_blockA==0)
this->m_blockA = aligned_new<LhsScalar>(m_sizeA);
}
void allocateB()
{
if(this->m_blockB==0)
this->m_blockB = aligned_new<RhsScalar>(m_sizeB);
}
void allocateAll()
{
allocateA();
allocateB();
}
~gemm_blocking_space()
{
aligned_delete(this->m_blockA, m_sizeA);
aligned_delete(this->m_blockB, m_sizeB);
}
};
} // end namespace internal
namespace internal {
template<typename Lhs, typename Rhs>
struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,GemmProduct>
: generic_product_impl_base<Lhs,Rhs,generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,GemmProduct> >
{
typedef typename Product<Lhs,Rhs>::Scalar Scalar;
typedef typename Lhs::Scalar LhsScalar;
typedef typename Rhs::Scalar RhsScalar;
typedef internal::blas_traits<Lhs> LhsBlasTraits;
typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
typedef typename internal::remove_all<ActualLhsType>::type ActualLhsTypeCleaned;
typedef internal::blas_traits<Rhs> RhsBlasTraits;
typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
typedef typename internal::remove_all<ActualRhsType>::type ActualRhsTypeCleaned;
enum {
MaxDepthAtCompileTime = EIGEN_SIZE_MIN_PREFER_FIXED(Lhs::MaxColsAtCompileTime,Rhs::MaxRowsAtCompileTime)
};
typedef generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,CoeffBasedProductMode> lazyproduct;
template<typename Dst>
static void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
if((rhs.rows()+dst.rows()+dst.cols())<20 && rhs.rows()>0)
lazyproduct::evalTo(dst, lhs, rhs);
else
{
dst.setZero();
scaleAndAddTo(dst, lhs, rhs, Scalar(1));
}
}
template<typename Dst>
static void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
if((rhs.rows()+dst.rows()+dst.cols())<20 && rhs.rows()>0)
lazyproduct::addTo(dst, lhs, rhs);
else
scaleAndAddTo(dst,lhs, rhs, Scalar(1));
}
template<typename Dst>
static void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs)
{
if((rhs.rows()+dst.rows()+dst.cols())<20 && rhs.rows()>0)
lazyproduct::subTo(dst, lhs, rhs);
else
scaleAndAddTo(dst, lhs, rhs, Scalar(-1));
}
template<typename Dest>
static void scaleAndAddTo(Dest& dst, const Lhs& a_lhs, const Rhs& a_rhs, const Scalar& alpha)
{
eigen_assert(dst.rows()==a_lhs.rows() && dst.cols()==a_rhs.cols());
if(a_lhs.cols()==0 || a_lhs.rows()==0 || a_rhs.cols()==0)
return;
typename internal::add_const_on_value_type<ActualLhsType>::type lhs = LhsBlasTraits::extract(a_lhs);
typename internal::add_const_on_value_type<ActualRhsType>::type rhs = RhsBlasTraits::extract(a_rhs);
Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(a_lhs)
* RhsBlasTraits::extractScalarFactor(a_rhs);
typedef internal::gemm_blocking_space<(Dest::Flags&RowMajorBit) ? RowMajor : ColMajor,LhsScalar,RhsScalar,
Dest::MaxRowsAtCompileTime,Dest::MaxColsAtCompileTime,MaxDepthAtCompileTime> BlockingType;
typedef internal::gemm_functor<
Scalar, Index,
internal::general_matrix_matrix_product<
Index,
LhsScalar, (ActualLhsTypeCleaned::Flags&RowMajorBit) ? RowMajor : ColMajor, bool(LhsBlasTraits::NeedToConjugate),
RhsScalar, (ActualRhsTypeCleaned::Flags&RowMajorBit) ? RowMajor : ColMajor, bool(RhsBlasTraits::NeedToConjugate),
(Dest::Flags&RowMajorBit) ? RowMajor : ColMajor>,
ActualLhsTypeCleaned, ActualRhsTypeCleaned, Dest, BlockingType> GemmFunctor;
BlockingType blocking(dst.rows(), dst.cols(), lhs.cols(), 1, true);
internal::parallelize_gemm<(Dest::MaxRowsAtCompileTime>32 || Dest::MaxRowsAtCompileTime==Dynamic)>
(GemmFunctor(lhs, rhs, dst, actualAlpha, blocking), a_lhs.rows(), a_rhs.cols(), Dest::Flags&RowMajorBit);
}
};
} // end namespace internal
} // end namespace Eigen
#endif // EIGEN_GENERAL_MATRIX_MATRIX_H
|
data.c | #include "data.h"
#include "utils.h"
#include "image.h"
#include "dark_cuda.h"
#include "box.h"
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
extern int check_mistakes;
#define NUMCHARS 37
pthread_mutex_t mutex = PTHREAD_MUTEX_INITIALIZER;
list *get_paths(char *filename)
{
char *path;
FILE *file = fopen(filename, "r");
if(!file) file_error(filename);
list *lines = make_list();
while((path=fgetl(file))){
list_insert(lines, path);
}
fclose(file);
return lines;
}
/*
char **get_random_paths_indexes(char **paths, int n, int m, int *indexes)
{
char **random_paths = calloc(n, sizeof(char*));
int i;
pthread_mutex_lock(&mutex);
for(i = 0; i < n; ++i){
int index = random_gen()%m;
indexes[i] = index;
random_paths[i] = paths[index];
if(i == 0) printf("%s\n", paths[index]);
}
pthread_mutex_unlock(&mutex);
return random_paths;
}
*/
char **get_sequential_paths(char **paths, int n, int m, int mini_batch, int augment_speed)
{
int speed = rand_int(1, augment_speed);
if (speed < 1) speed = 1;
char** sequentia_paths = (char**)xcalloc(n, sizeof(char*));
int i;
pthread_mutex_lock(&mutex);
//printf("n = %d, mini_batch = %d \n", n, mini_batch);
unsigned int *start_time_indexes = (unsigned int *)xcalloc(mini_batch, sizeof(unsigned int));
for (i = 0; i < mini_batch; ++i) {
start_time_indexes[i] = random_gen() % m;
//printf(" start_time_indexes[i] = %u, ", start_time_indexes[i]);
}
for (i = 0; i < n; ++i) {
do {
int time_line_index = i % mini_batch;
unsigned int index = start_time_indexes[time_line_index] % m;
start_time_indexes[time_line_index] += speed;
//int index = random_gen() % m;
sequentia_paths[i] = paths[index];
//if(i == 0) printf("%s\n", paths[index]);
//printf(" index = %u - grp: %s \n", index, paths[index]);
if (strlen(sequentia_paths[i]) <= 4) printf(" Very small path to the image: %s \n", sequentia_paths[i]);
} while (strlen(sequentia_paths[i]) == 0);
}
free(start_time_indexes);
pthread_mutex_unlock(&mutex);
return sequentia_paths;
}
char **get_random_paths(char **paths, int n, int m)
{
char** random_paths = (char**)xcalloc(n, sizeof(char*));
int i;
pthread_mutex_lock(&mutex);
//printf("n = %d \n", n);
for(i = 0; i < n; ++i){
do {
int index = random_gen() % m;
random_paths[i] = paths[index];
//if(i == 0) printf("%s\n", paths[index]);
//printf("grp: %s\n", paths[index]);
if (strlen(random_paths[i]) <= 4) printf(" Very small path to the image: %s \n", random_paths[i]);
} while (strlen(random_paths[i]) == 0);
}
pthread_mutex_unlock(&mutex);
return random_paths;
}
char **find_replace_paths(char **paths, int n, char *find, char *replace)
{
char** replace_paths = (char**)xcalloc(n, sizeof(char*));
int i;
for(i = 0; i < n; ++i){
char replaced[4096];
find_replace(paths[i], find, replace, replaced);
replace_paths[i] = copy_string(replaced);
}
return replace_paths;
}
matrix load_image_paths_gray(char **paths, int n, int w, int h)
{
int i;
matrix X;
X.rows = n;
X.vals = (float**)xcalloc(X.rows, sizeof(float*));
X.cols = 0;
for(i = 0; i < n; ++i){
image im = load_image(paths[i], w, h, 3);
image gray = grayscale_image(im);
free_image(im);
im = gray;
X.vals[i] = im.data;
X.cols = im.h*im.w*im.c;
}
return X;
}
matrix load_image_paths(char **paths, int n, int w, int h)
{
int i;
matrix X;
X.rows = n;
X.vals = (float**)xcalloc(X.rows, sizeof(float*));
X.cols = 0;
for(i = 0; i < n; ++i){
image im = load_image_color(paths[i], w, h);
X.vals[i] = im.data;
X.cols = im.h*im.w*im.c;
}
return X;
}
matrix load_image_augment_paths(char **paths, int n, int use_flip, int min, int max, int w, int h, float angle, float aspect, float hue, float saturation, float exposure, int dontuse_opencv)
{
int i;
matrix X;
X.rows = n;
X.vals = (float**)xcalloc(X.rows, sizeof(float*));
X.cols = 0;
for(i = 0; i < n; ++i){
int size = w > h ? w : h;
image im;
if(dontuse_opencv) im = load_image_stb_resize(paths[i], 0, 0, 3);
else im = load_image_color(paths[i], 0, 0);
image crop = random_augment_image(im, angle, aspect, min, max, size);
int flip = use_flip ? random_gen() % 2 : 0;
if (flip)
flip_image(crop);
random_distort_image(crop, hue, saturation, exposure);
image sized = resize_image(crop, w, h);
//show_image(im, "orig");
//show_image(sized, "sized");
//show_image(sized, paths[i]);
//wait_until_press_key_cv();
//printf("w = %d, h = %d \n", sized.w, sized.h);
free_image(im);
free_image(crop);
X.vals[i] = sized.data;
X.cols = sized.h*sized.w*sized.c;
}
return X;
}
box_label *read_boxes(char *filename, int *n)
{
box_label* boxes = (box_label*)xcalloc(1, sizeof(box_label));
FILE *file = fopen(filename, "r");
if (!file) {
printf("Can't open label file. (This can be normal only if you use MSCOCO): %s \n", filename);
//file_error(filename);
FILE* fw = fopen("bad.list", "a");
fwrite(filename, sizeof(char), strlen(filename), fw);
char *new_line = "\n";
fwrite(new_line, sizeof(char), strlen(new_line), fw);
fclose(fw);
if (check_mistakes) {
printf("\n Error in read_boxes() \n");
getchar();
}
*n = 0;
return boxes;
}
float x, y, h, w;
int id;
int count = 0;
while(fscanf(file, "%d %f %f %f %f", &id, &x, &y, &w, &h) == 5){
boxes = (box_label*)xrealloc(boxes, (count + 1) * sizeof(box_label));
boxes[count].id = id;
boxes[count].x = x;
boxes[count].y = y;
boxes[count].h = h;
boxes[count].w = w;
boxes[count].left = x - w/2;
boxes[count].right = x + w/2;
boxes[count].top = y - h/2;
boxes[count].bottom = y + h/2;
++count;
}
fclose(file);
*n = count;
return boxes;
}
void randomize_boxes(box_label *b, int n)
{
int i;
for(i = 0; i < n; ++i){
box_label swap = b[i];
int index = random_gen()%n;
b[i] = b[index];
b[index] = swap;
}
}
void correct_boxes(box_label *boxes, int n, float dx, float dy, float sx, float sy, int flip)
{
int i;
for(i = 0; i < n; ++i){
if(boxes[i].x == 0 && boxes[i].y == 0) {
boxes[i].x = 999999;
boxes[i].y = 999999;
boxes[i].w = 999999;
boxes[i].h = 999999;
continue;
}
if ((boxes[i].x + boxes[i].w / 2) < 0 || (boxes[i].y + boxes[i].h / 2) < 0 ||
(boxes[i].x - boxes[i].w / 2) > 1 || (boxes[i].y - boxes[i].h / 2) > 1)
{
boxes[i].x = 999999;
boxes[i].y = 999999;
boxes[i].w = 999999;
boxes[i].h = 999999;
continue;
}
boxes[i].left = boxes[i].left * sx - dx;
boxes[i].right = boxes[i].right * sx - dx;
boxes[i].top = boxes[i].top * sy - dy;
boxes[i].bottom = boxes[i].bottom* sy - dy;
if(flip){
float swap = boxes[i].left;
boxes[i].left = 1. - boxes[i].right;
boxes[i].right = 1. - swap;
}
boxes[i].left = constrain(0, 1, boxes[i].left);
boxes[i].right = constrain(0, 1, boxes[i].right);
boxes[i].top = constrain(0, 1, boxes[i].top);
boxes[i].bottom = constrain(0, 1, boxes[i].bottom);
boxes[i].x = (boxes[i].left+boxes[i].right)/2;
boxes[i].y = (boxes[i].top+boxes[i].bottom)/2;
boxes[i].w = (boxes[i].right - boxes[i].left);
boxes[i].h = (boxes[i].bottom - boxes[i].top);
boxes[i].w = constrain(0, 1, boxes[i].w);
boxes[i].h = constrain(0, 1, boxes[i].h);
}
}
void fill_truth_swag(char *path, float *truth, int classes, int flip, float dx, float dy, float sx, float sy)
{
char labelpath[4096];
replace_image_to_label(path, labelpath);
int count = 0;
box_label *boxes = read_boxes(labelpath, &count);
randomize_boxes(boxes, count);
correct_boxes(boxes, count, dx, dy, sx, sy, flip);
float x,y,w,h;
int id;
int i;
for (i = 0; i < count && i < 30; ++i) {
x = boxes[i].x;
y = boxes[i].y;
w = boxes[i].w;
h = boxes[i].h;
id = boxes[i].id;
if (w < .0 || h < .0) continue;
int index = (4+classes) * i;
truth[index++] = x;
truth[index++] = y;
truth[index++] = w;
truth[index++] = h;
if (id < classes) truth[index+id] = 1;
}
free(boxes);
}
void fill_truth_region(char *path, float *truth, int classes, int num_boxes, int flip, float dx, float dy, float sx, float sy)
{
char labelpath[4096];
replace_image_to_label(path, labelpath);
int count = 0;
box_label *boxes = read_boxes(labelpath, &count);
randomize_boxes(boxes, count);
correct_boxes(boxes, count, dx, dy, sx, sy, flip);
float x,y,w,h;
int id;
int i;
for (i = 0; i < count; ++i) {
x = boxes[i].x;
y = boxes[i].y;
w = boxes[i].w;
h = boxes[i].h;
id = boxes[i].id;
if (w < .001 || h < .001) continue;
int col = (int)(x*num_boxes);
int row = (int)(y*num_boxes);
x = x*num_boxes - col;
y = y*num_boxes - row;
int index = (col+row*num_boxes)*(5+classes);
if (truth[index]) continue;
truth[index++] = 1;
if (id < classes) truth[index+id] = 1;
index += classes;
truth[index++] = x;
truth[index++] = y;
truth[index++] = w;
truth[index++] = h;
}
free(boxes);
}
int fill_truth_detection(const char *path, int num_boxes, float *truth, int classes, int flip, float dx, float dy, float sx, float sy,
int net_w, int net_h)
{
char labelpath[4096];
replace_image_to_label(path, labelpath);
int count = 0;
int i;
box_label *boxes = read_boxes(labelpath, &count);
int min_w_h = 0;
float lowest_w = 1.F / net_w;
float lowest_h = 1.F / net_h;
randomize_boxes(boxes, count);
correct_boxes(boxes, count, dx, dy, sx, sy, flip);
if (count > num_boxes) count = num_boxes;
float x, y, w, h;
int id;
int sub = 0;
for (i = 0; i < count; ++i) {
x = boxes[i].x;
y = boxes[i].y;
w = boxes[i].w;
h = boxes[i].h;
id = boxes[i].id;
// not detect small objects
//if ((w < 0.001F || h < 0.001F)) continue;
// if truth (box for object) is smaller than 1x1 pix
char buff[256];
if (id >= classes) {
printf("\n Wrong annotation: class_id = %d. But class_id should be [from 0 to %d], file: %s \n", id, (classes-1), labelpath);
sprintf(buff, "echo %s \"Wrong annotation: class_id = %d. But class_id should be [from 0 to %d]\" >> bad_label.list", labelpath, id, (classes-1));
system(buff);
if (check_mistakes) getchar();
++sub;
continue;
}
if ((w < lowest_w || h < lowest_h)) {
//sprintf(buff, "echo %s \"Very small object: w < lowest_w OR h < lowest_h\" >> bad_label.list", labelpath);
//system(buff);
++sub;
continue;
}
if (x == 999999 || y == 999999) {
printf("\n Wrong annotation: x = 0, y = 0, < 0 or > 1, file: %s \n", labelpath);
sprintf(buff, "echo %s \"Wrong annotation: x = 0 or y = 0\" >> bad_label.list", labelpath);
system(buff);
++sub;
if (check_mistakes) getchar();
continue;
}
if (x <= 0 || x > 1 || y <= 0 || y > 1) {
printf("\n Wrong annotation: x = %f, y = %f, file: %s \n", x, y, labelpath);
sprintf(buff, "echo %s \"Wrong annotation: x = %f, y = %f\" >> bad_label.list", labelpath, x, y);
system(buff);
++sub;
if (check_mistakes) getchar();
continue;
}
if (w > 1) {
printf("\n Wrong annotation: w = %f, file: %s \n", w, labelpath);
sprintf(buff, "echo %s \"Wrong annotation: w = %f\" >> bad_label.list", labelpath, w);
system(buff);
w = 1;
if (check_mistakes) getchar();
}
if (h > 1) {
printf("\n Wrong annotation: h = %f, file: %s \n", h, labelpath);
sprintf(buff, "echo %s \"Wrong annotation: h = %f\" >> bad_label.list", labelpath, h);
system(buff);
h = 1;
if (check_mistakes) getchar();
}
if (x == 0) x += lowest_w;
if (y == 0) y += lowest_h;
truth[(i-sub)*5+0] = x;
truth[(i-sub)*5+1] = y;
truth[(i-sub)*5+2] = w;
truth[(i-sub)*5+3] = h;
truth[(i-sub)*5+4] = id;
if (min_w_h == 0) min_w_h = w*net_w;
if (min_w_h > w*net_w) min_w_h = w*net_w;
if (min_w_h > h*net_h) min_w_h = h*net_h;
}
free(boxes);
return min_w_h;
}
void print_letters(float *pred, int n)
{
int i;
for(i = 0; i < n; ++i){
int index = max_index(pred+i*NUMCHARS, NUMCHARS);
printf("%c", int_to_alphanum(index));
}
printf("\n");
}
void fill_truth_captcha(char *path, int n, float *truth)
{
char *begin = strrchr(path, '/');
++begin;
int i;
for(i = 0; i < strlen(begin) && i < n && begin[i] != '.'; ++i){
int index = alphanum_to_int(begin[i]);
if(index > 35) printf("Bad %c\n", begin[i]);
truth[i*NUMCHARS+index] = 1;
}
for(;i < n; ++i){
truth[i*NUMCHARS + NUMCHARS-1] = 1;
}
}
data load_data_captcha(char **paths, int n, int m, int k, int w, int h)
{
if(m) paths = get_random_paths(paths, n, m);
data d = {0};
d.shallow = 0;
d.X = load_image_paths(paths, n, w, h);
d.y = make_matrix(n, k*NUMCHARS);
int i;
for(i = 0; i < n; ++i){
fill_truth_captcha(paths[i], k, d.y.vals[i]);
}
if(m) free(paths);
return d;
}
data load_data_captcha_encode(char **paths, int n, int m, int w, int h)
{
if(m) paths = get_random_paths(paths, n, m);
data d = {0};
d.shallow = 0;
d.X = load_image_paths(paths, n, w, h);
d.X.cols = 17100;
d.y = d.X;
if(m) free(paths);
return d;
}
void fill_truth(char *path, char **labels, int k, float *truth)
{
int i;
memset(truth, 0, k*sizeof(float));
int count = 0;
for(i = 0; i < k; ++i){
if(strstr(path, labels[i])){
truth[i] = 1;
++count;
}
}
if (count != 1) {
printf("Too many or too few labels: %d, %s\n", count, path);
count = 0;
for (i = 0; i < k; ++i) {
if (strstr(path, labels[i])) {
printf("\t label %d: %s \n", count, labels[i]);
count++;
}
}
}
}
void fill_truth_smooth(char *path, char **labels, int k, float *truth, float label_smooth_eps)
{
int i;
memset(truth, 0, k * sizeof(float));
int count = 0;
for (i = 0; i < k; ++i) {
if (strstr(path, labels[i])) {
truth[i] = (1 - label_smooth_eps);
++count;
}
else {
truth[i] = label_smooth_eps / (k - 1);
}
}
if (count != 1) {
printf("Too many or too few labels: %d, %s\n", count, path);
count = 0;
for (i = 0; i < k; ++i) {
if (strstr(path, labels[i])) {
printf("\t label %d: %s \n", count, labels[i]);
count++;
}
}
}
}
void fill_hierarchy(float *truth, int k, tree *hierarchy)
{
int j;
for(j = 0; j < k; ++j){
if(truth[j]){
int parent = hierarchy->parent[j];
while(parent >= 0){
truth[parent] = 1;
parent = hierarchy->parent[parent];
}
}
}
int i;
int count = 0;
for(j = 0; j < hierarchy->groups; ++j){
//printf("%d\n", count);
int mask = 1;
for(i = 0; i < hierarchy->group_size[j]; ++i){
if(truth[count + i]){
mask = 0;
break;
}
}
if (mask) {
for(i = 0; i < hierarchy->group_size[j]; ++i){
truth[count + i] = SECRET_NUM;
}
}
count += hierarchy->group_size[j];
}
}
matrix load_labels_paths(char **paths, int n, char **labels, int k, tree *hierarchy, float label_smooth_eps)
{
matrix y = make_matrix(n, k);
int i;
for(i = 0; i < n && labels; ++i){
fill_truth_smooth(paths[i], labels, k, y.vals[i], label_smooth_eps);
if(hierarchy){
fill_hierarchy(y.vals[i], k, hierarchy);
}
}
return y;
}
matrix load_tags_paths(char **paths, int n, int k)
{
matrix y = make_matrix(n, k);
int i;
int count = 0;
for(i = 0; i < n; ++i){
char label[4096];
find_replace(paths[i], "imgs", "labels", label);
find_replace(label, "_iconl.jpeg", ".txt", label);
FILE *file = fopen(label, "r");
if(!file){
find_replace(label, "labels", "labels2", label);
file = fopen(label, "r");
if(!file) continue;
}
++count;
int tag;
while(fscanf(file, "%d", &tag) == 1){
if(tag < k){
y.vals[i][tag] = 1;
}
}
fclose(file);
}
printf("%d/%d\n", count, n);
return y;
}
char **get_labels_custom(char *filename, int *size)
{
list *plist = get_paths(filename);
if(size) *size = plist->size;
char **labels = (char **)list_to_array(plist);
free_list(plist);
return labels;
}
char **get_labels(char *filename)
{
return get_labels_custom(filename, NULL);
}
void free_data(data d)
{
if(!d.shallow){
free_matrix(d.X);
free_matrix(d.y);
}else{
free(d.X.vals);
free(d.y.vals);
}
}
data load_data_region(int n, char **paths, int m, int w, int h, int size, int classes, float jitter, float hue, float saturation, float exposure)
{
char **random_paths = get_random_paths(paths, n, m);
int i;
data d = {0};
d.shallow = 0;
d.X.rows = n;
d.X.vals = (float**)xcalloc(d.X.rows, sizeof(float*));
d.X.cols = h*w*3;
int k = size*size*(5+classes);
d.y = make_matrix(n, k);
for(i = 0; i < n; ++i){
image orig = load_image_color(random_paths[i], 0, 0);
int oh = orig.h;
int ow = orig.w;
int dw = (ow*jitter);
int dh = (oh*jitter);
int pleft = rand_uniform(-dw, dw);
int pright = rand_uniform(-dw, dw);
int ptop = rand_uniform(-dh, dh);
int pbot = rand_uniform(-dh, dh);
int swidth = ow - pleft - pright;
int sheight = oh - ptop - pbot;
float sx = (float)swidth / ow;
float sy = (float)sheight / oh;
int flip = random_gen()%2;
image cropped = crop_image(orig, pleft, ptop, swidth, sheight);
float dx = ((float)pleft/ow)/sx;
float dy = ((float)ptop /oh)/sy;
image sized = resize_image(cropped, w, h);
if(flip) flip_image(sized);
random_distort_image(sized, hue, saturation, exposure);
d.X.vals[i] = sized.data;
fill_truth_region(random_paths[i], d.y.vals[i], classes, size, flip, dx, dy, 1./sx, 1./sy);
free_image(orig);
free_image(cropped);
}
free(random_paths);
return d;
}
data load_data_compare(int n, char **paths, int m, int classes, int w, int h)
{
if(m) paths = get_random_paths(paths, 2*n, m);
int i,j;
data d = {0};
d.shallow = 0;
d.X.rows = n;
d.X.vals = (float**)xcalloc(d.X.rows, sizeof(float*));
d.X.cols = h*w*6;
int k = 2*(classes);
d.y = make_matrix(n, k);
for(i = 0; i < n; ++i){
image im1 = load_image_color(paths[i*2], w, h);
image im2 = load_image_color(paths[i*2+1], w, h);
d.X.vals[i] = (float*)xcalloc(d.X.cols, sizeof(float));
memcpy(d.X.vals[i], im1.data, h*w*3*sizeof(float));
memcpy(d.X.vals[i] + h*w*3, im2.data, h*w*3*sizeof(float));
int id;
float iou;
char imlabel1[4096];
char imlabel2[4096];
find_replace(paths[i*2], "imgs", "labels", imlabel1);
find_replace(imlabel1, "jpg", "txt", imlabel1);
FILE *fp1 = fopen(imlabel1, "r");
while(fscanf(fp1, "%d %f", &id, &iou) == 2){
if (d.y.vals[i][2*id] < iou) d.y.vals[i][2*id] = iou;
}
find_replace(paths[i*2+1], "imgs", "labels", imlabel2);
find_replace(imlabel2, "jpg", "txt", imlabel2);
FILE *fp2 = fopen(imlabel2, "r");
while(fscanf(fp2, "%d %f", &id, &iou) == 2){
if (d.y.vals[i][2*id + 1] < iou) d.y.vals[i][2*id + 1] = iou;
}
for (j = 0; j < classes; ++j){
if (d.y.vals[i][2*j] > .5 && d.y.vals[i][2*j+1] < .5){
d.y.vals[i][2*j] = 1;
d.y.vals[i][2*j+1] = 0;
} else if (d.y.vals[i][2*j] < .5 && d.y.vals[i][2*j+1] > .5){
d.y.vals[i][2*j] = 0;
d.y.vals[i][2*j+1] = 1;
} else {
d.y.vals[i][2*j] = SECRET_NUM;
d.y.vals[i][2*j+1] = SECRET_NUM;
}
}
fclose(fp1);
fclose(fp2);
free_image(im1);
free_image(im2);
}
if(m) free(paths);
return d;
}
data load_data_swag(char **paths, int n, int classes, float jitter)
{
int index = random_gen()%n;
char *random_path = paths[index];
image orig = load_image_color(random_path, 0, 0);
int h = orig.h;
int w = orig.w;
data d = {0};
d.shallow = 0;
d.w = w;
d.h = h;
d.X.rows = 1;
d.X.vals = (float**)xcalloc(d.X.rows, sizeof(float*));
d.X.cols = h*w*3;
int k = (4+classes)*30;
d.y = make_matrix(1, k);
int dw = w*jitter;
int dh = h*jitter;
int pleft = rand_uniform(-dw, dw);
int pright = rand_uniform(-dw, dw);
int ptop = rand_uniform(-dh, dh);
int pbot = rand_uniform(-dh, dh);
int swidth = w - pleft - pright;
int sheight = h - ptop - pbot;
float sx = (float)swidth / w;
float sy = (float)sheight / h;
int flip = random_gen()%2;
image cropped = crop_image(orig, pleft, ptop, swidth, sheight);
float dx = ((float)pleft/w)/sx;
float dy = ((float)ptop /h)/sy;
image sized = resize_image(cropped, w, h);
if(flip) flip_image(sized);
d.X.vals[0] = sized.data;
fill_truth_swag(random_path, d.y.vals[0], classes, flip, dx, dy, 1./sx, 1./sy);
free_image(orig);
free_image(cropped);
return d;
}
void blend_truth(float *new_truth, int boxes, float *old_truth)
{
const int t_size = 4 + 1;
int count_new_truth = 0;
int t;
for (t = 0; t < boxes; ++t) {
float x = new_truth[t*(4 + 1)];
if (!x) break;
count_new_truth++;
}
for (t = count_new_truth; t < boxes; ++t) {
float *new_truth_ptr = new_truth + t*t_size;
float *old_truth_ptr = old_truth + (t - count_new_truth)*t_size;
float x = old_truth_ptr[0];
if (!x) break;
new_truth_ptr[0] = old_truth_ptr[0];
new_truth_ptr[1] = old_truth_ptr[1];
new_truth_ptr[2] = old_truth_ptr[2];
new_truth_ptr[3] = old_truth_ptr[3];
new_truth_ptr[4] = old_truth_ptr[4];
}
//printf("\n was %d bboxes, now %d bboxes \n", count_new_truth, t);
}
void blend_truth_mosaic(float *new_truth, int boxes, float *old_truth, int w, int h, float cut_x, float cut_y, int i_mixup,
int left_shift, int right_shift, int top_shift, int bot_shift)
{
const int t_size = 4 + 1;
int count_new_truth = 0;
int t;
for (t = 0; t < boxes; ++t) {
float x = new_truth[t*(4 + 1)];
if (!x) break;
count_new_truth++;
}
int new_t = count_new_truth;
for (t = count_new_truth; t < boxes; ++t) {
float *new_truth_ptr = new_truth + new_t*t_size;
new_truth_ptr[0] = 0;
float *old_truth_ptr = old_truth + (t - count_new_truth)*t_size;
float x = old_truth_ptr[0];
if (!x) break;
float xb = old_truth_ptr[0];
float yb = old_truth_ptr[1];
float wb = old_truth_ptr[2];
float hb = old_truth_ptr[3];
// shift 4 images
if (i_mixup == 0) {
xb = xb - (float)(w - cut_x - right_shift) / w;
yb = yb - (float)(h - cut_y - bot_shift) / h;
}
if (i_mixup == 1) {
xb = xb + (float)(cut_x - left_shift) / w;
yb = yb - (float)(h - cut_y - bot_shift) / h;
}
if (i_mixup == 2) {
xb = xb - (float)(w - cut_x - right_shift) / w;
yb = yb + (float)(cut_y - top_shift) / h;
}
if (i_mixup == 3) {
xb = xb + (float)(cut_x - left_shift) / w;
yb = yb + (float)(cut_y - top_shift) / h;
}
int left = (xb - wb / 2)*w;
int right = (xb + wb / 2)*w;
int top = (yb - hb / 2)*h;
int bot = (yb + hb / 2)*h;
// fix out of bound
if (left < 0) {
float diff = (float)left / w;
xb = xb - diff / 2;
wb = wb + diff;
}
if (right > w) {
float diff = (float)(right - w) / w;
xb = xb - diff / 2;
wb = wb - diff;
}
if (top < 0) {
float diff = (float)top / h;
yb = yb - diff / 2;
hb = hb + diff;
}
if (bot > h) {
float diff = (float)(bot - h) / h;
yb = yb - diff / 2;
hb = hb - diff;
}
left = (xb - wb / 2)*w;
right = (xb + wb / 2)*w;
top = (yb - hb / 2)*h;
bot = (yb + hb / 2)*h;
// leave only within the image
if(left >= 0 && right <= w && top >= 0 && bot <= h &&
wb > 0 && wb < 1 && hb > 0 && hb < 1 &&
xb > 0 && xb < 1 && yb > 0 && yb < 1)
{
new_truth_ptr[0] = xb;
new_truth_ptr[1] = yb;
new_truth_ptr[2] = wb;
new_truth_ptr[3] = hb;
new_truth_ptr[4] = old_truth_ptr[4];
new_t++;
}
}
//printf("\n was %d bboxes, now %d bboxes \n", count_new_truth, t);
}
#ifdef OPENCV
#include "http_stream.h"
data load_data_detection(int n, char **paths, int m, int w, int h, int c, int boxes, int classes, int use_flip, int use_gaussian_noise, int use_blur, int use_mixup,
float jitter, float hue, float saturation, float exposure, int mini_batch, int track, int augment_speed, int letter_box, int show_imgs)
{
const int random_index = random_gen();
c = c ? c : 3;
if (use_mixup == 2) {
printf("\n cutmix=1 - isn't supported for Detector \n");
exit(0);
}
if (use_mixup == 3 && letter_box) {
printf("\n Combination: letter_box=1 & mosaic=1 - isn't supported, use only 1 of these parameters \n");
exit(0);
}
if (random_gen() % 2 == 0) use_mixup = 0;
int i;
int *cut_x = NULL, *cut_y = NULL;
if (use_mixup == 3) {
cut_x = (int*)calloc(n, sizeof(int));
cut_y = (int*)calloc(n, sizeof(int));
const float min_offset = 0.2; // 20%
for (i = 0; i < n; ++i) {
cut_x[i] = rand_int(w*min_offset, w*(1 - min_offset));
cut_y[i] = rand_int(h*min_offset, h*(1 - min_offset));
}
}
data d = {0};
d.shallow = 0;
d.X.rows = n;
d.X.vals = (float**)xcalloc(d.X.rows, sizeof(float*));
d.X.cols = h*w*c;
float r1 = 0, r2 = 0, r3 = 0, r4 = 0, r_scale = 0;
float dhue = 0, dsat = 0, dexp = 0, flip = 0, blur = 0;
int augmentation_calculated = 0, gaussian_noise = 0;
d.y = make_matrix(n, 5*boxes);
int i_mixup = 0;
for (i_mixup = 0; i_mixup <= use_mixup; i_mixup++) {
if (i_mixup) augmentation_calculated = 0; // recalculate augmentation for the 2nd sequence if(track==1)
char **random_paths;
if (track) random_paths = get_sequential_paths(paths, n, m, mini_batch, augment_speed);
else random_paths = get_random_paths(paths, n, m);
for (i = 0; i < n; ++i) {
float *truth = (float*)xcalloc(5 * boxes, sizeof(float));
const char *filename = random_paths[i];
int flag = (c >= 3);
mat_cv *src;
src = load_image_mat_cv(filename, flag);
if (src == NULL) {
if (check_mistakes) {
printf("\n Error in load_data_detection() - OpenCV \n");
getchar();
}
continue;
}
int oh = get_height_mat(src);
int ow = get_width_mat(src);
int dw = (ow*jitter);
int dh = (oh*jitter);
if (!augmentation_calculated || !track)
{
augmentation_calculated = 1;
r1 = random_float();
r2 = random_float();
r3 = random_float();
r4 = random_float();
r_scale = random_float();
dhue = rand_uniform_strong(-hue, hue);
dsat = rand_scale(saturation);
dexp = rand_scale(exposure);
flip = use_flip ? random_gen() % 2 : 0;
if (use_blur) {
int tmp_blur = rand_int(0, 2); // 0 - disable, 1 - blur background, 2 - blur the whole image
if (tmp_blur == 0) blur = 0;
else if (tmp_blur == 1) blur = 1;
else blur = use_blur;
}
if (use_gaussian_noise && rand_int(0, 1) == 1) gaussian_noise = use_gaussian_noise;
else gaussian_noise = 0;
}
int pleft = rand_precalc_random(-dw, dw, r1);
int pright = rand_precalc_random(-dw, dw, r2);
int ptop = rand_precalc_random(-dh, dh, r3);
int pbot = rand_precalc_random(-dh, dh, r4);
//printf("\n pleft = %d, pright = %d, ptop = %d, pbot = %d, ow = %d, oh = %d \n", pleft, pright, ptop, pbot, ow, oh);
//float scale = rand_precalc_random(.25, 2, r_scale); // unused currently
if (letter_box)
{
float img_ar = (float)ow / (float)oh;
float net_ar = (float)w / (float)h;
float result_ar = img_ar / net_ar;
//printf(" ow = %d, oh = %d, w = %d, h = %d, img_ar = %f, net_ar = %f, result_ar = %f \n", ow, oh, w, h, img_ar, net_ar, result_ar);
if (result_ar > 1) // sheight - should be increased
{
float oh_tmp = ow / net_ar;
float delta_h = (oh_tmp - oh)/2;
ptop = ptop - delta_h;
pbot = pbot - delta_h;
//printf(" result_ar = %f, oh_tmp = %f, delta_h = %d, ptop = %f, pbot = %f \n", result_ar, oh_tmp, delta_h, ptop, pbot);
}
else // swidth - should be increased
{
float ow_tmp = oh * net_ar;
float delta_w = (ow_tmp - ow)/2;
pleft = pleft - delta_w;
pright = pright - delta_w;
//printf(" result_ar = %f, ow_tmp = %f, delta_w = %d, pleft = %f, pright = %f \n", result_ar, ow_tmp, delta_w, pleft, pright);
}
}
int swidth = ow - pleft - pright;
int sheight = oh - ptop - pbot;
float sx = (float)swidth / ow;
float sy = (float)sheight / oh;
float dx = ((float)pleft / ow) / sx;
float dy = ((float)ptop / oh) / sy;
int min_w_h = fill_truth_detection(filename, boxes, truth, classes, flip, dx, dy, 1. / sx, 1. / sy, w, h);
if ((min_w_h / 8) < blur && blur > 1) blur = min_w_h / 8; // disable blur if one of the objects is too small
image ai = image_data_augmentation(src, w, h, pleft, ptop, swidth, sheight, flip, dhue, dsat, dexp,
gaussian_noise, blur, boxes, truth);
if (use_mixup == 0) {
d.X.vals[i] = ai.data;
memcpy(d.y.vals[i], truth, 5 * boxes * sizeof(float));
}
else if (use_mixup == 1) {
if (i_mixup == 0) {
d.X.vals[i] = ai.data;
memcpy(d.y.vals[i], truth, 5 * boxes * sizeof(float));
}
else if (i_mixup == 1) {
image old_img = make_empty_image(w, h, c);
old_img.data = d.X.vals[i];
//show_image(ai, "new");
//show_image(old_img, "old");
//wait_until_press_key_cv();
blend_images_cv(ai, 0.5, old_img, 0.5);
blend_truth(d.y.vals[i], boxes, truth);
free_image(old_img);
d.X.vals[i] = ai.data;
}
}
else if (use_mixup == 3) {
if (i_mixup == 0) {
image tmp_img = make_image(w, h, c);
d.X.vals[i] = tmp_img.data;
}
if (flip) {
int tmp = pleft;
pleft = pright;
pright = tmp;
}
const int left_shift = min_val_cmp(cut_x[i], max_val_cmp(0, (-pleft*w / ow)));
const int top_shift = min_val_cmp(cut_y[i], max_val_cmp(0, (-ptop*h / oh)));
const int right_shift = min_val_cmp((w - cut_x[i]), max_val_cmp(0, (-pright*w / ow)));
const int bot_shift = min_val_cmp(h - cut_y[i], max_val_cmp(0, (-pbot*h / oh)));
int k, x, y;
for (k = 0; k < c; ++k) {
for (y = 0; y < h; ++y) {
int j = y*w + k*w*h;
if (i_mixup == 0 && y < cut_y[i]) {
int j_src = (w - cut_x[i] - right_shift) + (y + h - cut_y[i] - bot_shift)*w + k*w*h;
memcpy(&d.X.vals[i][j + 0], &ai.data[j_src], cut_x[i] * sizeof(float));
}
if (i_mixup == 1 && y < cut_y[i]) {
int j_src = left_shift + (y + h - cut_y[i] - bot_shift)*w + k*w*h;
memcpy(&d.X.vals[i][j + cut_x[i]], &ai.data[j_src], (w-cut_x[i]) * sizeof(float));
}
if (i_mixup == 2 && y >= cut_y[i]) {
int j_src = (w - cut_x[i] - right_shift) + (top_shift + y - cut_y[i])*w + k*w*h;
memcpy(&d.X.vals[i][j + 0], &ai.data[j_src], cut_x[i] * sizeof(float));
}
if (i_mixup == 3 && y >= cut_y[i]) {
int j_src = left_shift + (top_shift + y - cut_y[i])*w + k*w*h;
memcpy(&d.X.vals[i][j + cut_x[i]], &ai.data[j_src], (w - cut_x[i]) * sizeof(float));
}
}
}
blend_truth_mosaic(d.y.vals[i], boxes, truth, w, h, cut_x[i], cut_y[i], i_mixup, left_shift, right_shift, top_shift, bot_shift);
free_image(ai);
ai.data = d.X.vals[i];
}
if (show_imgs && i_mixup == use_mixup) // delete i_mixup
{
image tmp_ai = copy_image(ai);
char buff[1000];
//sprintf(buff, "aug_%d_%d_%s_%d", random_index, i, basecfg((char*)filename), random_gen());
sprintf(buff, "aug_%d_%d_%d", random_index, i, random_gen());
int t;
for (t = 0; t < boxes; ++t) {
box b = float_to_box_stride(d.y.vals[i] + t*(4 + 1), 1);
if (!b.x) break;
int left = (b.x - b.w / 2.)*ai.w;
int right = (b.x + b.w / 2.)*ai.w;
int top = (b.y - b.h / 2.)*ai.h;
int bot = (b.y + b.h / 2.)*ai.h;
draw_box_width(tmp_ai, left, top, right, bot, 1, 150, 100, 50); // 3 channels RGB
}
save_image(tmp_ai, buff);
if (show_imgs == 1) {
//char buff_src[1000];
//sprintf(buff_src, "src_%d_%d_%s_%d", random_index, i, basecfg((char*)filename), random_gen());
//show_image_mat(src, buff_src);
show_image(tmp_ai, buff);
wait_until_press_key_cv();
}
printf("\nYou use flag -show_imgs, so will be saved aug_...jpg images. Click on window and press ESC button \n");
free_image(tmp_ai);
}
release_mat(&src);
free(truth);
}
if (random_paths) free(random_paths);
}
return d;
}
#else // OPENCV
void blend_images(image new_img, float alpha, image old_img, float beta)
{
int data_size = new_img.w * new_img.h * new_img.c;
int i;
#pragma omp parallel for
for (i = 0; i < data_size; ++i)
new_img.data[i] = new_img.data[i] * alpha + old_img.data[i] * beta;
}
data load_data_detection(int n, char **paths, int m, int w, int h, int c, int boxes, int classes, int use_flip, int gaussian_noise, int use_blur, int use_mixup, float jitter,
float hue, float saturation, float exposure, int mini_batch, int track, int augment_speed, int letter_box, int show_imgs)
{
const int random_index = random_gen();
c = c ? c : 3;
char **random_paths;
char **mixup_random_paths = NULL;
if(track) random_paths = get_sequential_paths(paths, n, m, mini_batch, augment_speed);
else random_paths = get_random_paths(paths, n, m);
//assert(use_mixup < 2);
if (use_mixup == 2) {
printf("\n cutmix=1 - isn't supported for Detector \n");
exit(0);
}
if (use_mixup == 3) {
printf("\n mosaic=1 - compile Darknet with OpenCV for using mosaic=1 \n");
exit(0);
}
int mixup = use_mixup ? random_gen() % 2 : 0;
//printf("\n mixup = %d \n", mixup);
if (mixup) {
if (track) mixup_random_paths = get_sequential_paths(paths, n, m, mini_batch, augment_speed);
else mixup_random_paths = get_random_paths(paths, n, m);
}
int i;
data d = { 0 };
d.shallow = 0;
d.X.rows = n;
d.X.vals = (float**)xcalloc(d.X.rows, sizeof(float*));
d.X.cols = h*w*c;
float r1 = 0, r2 = 0, r3 = 0, r4 = 0, r_scale;
float dhue = 0, dsat = 0, dexp = 0, flip = 0;
int augmentation_calculated = 0;
d.y = make_matrix(n, 5 * boxes);
int i_mixup = 0;
for (i_mixup = 0; i_mixup <= mixup; i_mixup++) {
if (i_mixup) augmentation_calculated = 0;
for (i = 0; i < n; ++i) {
float *truth = (float*)xcalloc(5 * boxes, sizeof(float));
char *filename = (i_mixup) ? mixup_random_paths[i] : random_paths[i];
image orig = load_image(filename, 0, 0, c);
int oh = orig.h;
int ow = orig.w;
int dw = (ow*jitter);
int dh = (oh*jitter);
if (!augmentation_calculated || !track)
{
augmentation_calculated = 1;
r1 = random_float();
r2 = random_float();
r3 = random_float();
r4 = random_float();
r_scale = random_float();
dhue = rand_uniform_strong(-hue, hue);
dsat = rand_scale(saturation);
dexp = rand_scale(exposure);
flip = use_flip ? random_gen() % 2 : 0;
}
int pleft = rand_precalc_random(-dw, dw, r1);
int pright = rand_precalc_random(-dw, dw, r2);
int ptop = rand_precalc_random(-dh, dh, r3);
int pbot = rand_precalc_random(-dh, dh, r4);
float scale = rand_precalc_random(.25, 2, r_scale); // unused currently
if (letter_box)
{
float img_ar = (float)ow / (float)oh;
float net_ar = (float)w / (float)h;
float result_ar = img_ar / net_ar;
//printf(" ow = %d, oh = %d, w = %d, h = %d, img_ar = %f, net_ar = %f, result_ar = %f \n", ow, oh, w, h, img_ar, net_ar, result_ar);
if (result_ar > 1) // sheight - should be increased
{
float oh_tmp = ow / net_ar;
float delta_h = (oh_tmp - oh) / 2;
ptop = ptop - delta_h;
pbot = pbot - delta_h;
//printf(" result_ar = %f, oh_tmp = %f, delta_h = %d, ptop = %f, pbot = %f \n", result_ar, oh_tmp, delta_h, ptop, pbot);
}
else // swidth - should be increased
{
float ow_tmp = oh * net_ar;
float delta_w = (ow_tmp - ow) / 2;
pleft = pleft - delta_w;
pright = pright - delta_w;
//printf(" result_ar = %f, ow_tmp = %f, delta_w = %d, pleft = %f, pright = %f \n", result_ar, ow_tmp, delta_w, pleft, pright);
}
}
int swidth = ow - pleft - pright;
int sheight = oh - ptop - pbot;
float sx = (float)swidth / ow;
float sy = (float)sheight / oh;
image cropped = crop_image(orig, pleft, ptop, swidth, sheight);
float dx = ((float)pleft / ow) / sx;
float dy = ((float)ptop / oh) / sy;
image sized = resize_image(cropped, w, h);
if (flip) flip_image(sized);
distort_image(sized, dhue, dsat, dexp);
//random_distort_image(sized, hue, saturation, exposure);
fill_truth_detection(filename, boxes, truth, classes, flip, dx, dy, 1. / sx, 1. / sy, w, h);
if (i_mixup) {
image old_img = sized;
old_img.data = d.X.vals[i];
//show_image(sized, "new");
//show_image(old_img, "old");
//wait_until_press_key_cv();
blend_images(sized, 0.5, old_img, 0.5);
blend_truth(truth, boxes, d.y.vals[i]);
free_image(old_img);
}
d.X.vals[i] = sized.data;
memcpy(d.y.vals[i], truth, 5 * boxes * sizeof(float));
if (show_imgs)// && i_mixup)
{
char buff[1000];
sprintf(buff, "aug_%d_%d_%s_%d", random_index, i, basecfg(filename), random_gen());
int t;
for (t = 0; t < boxes; ++t) {
box b = float_to_box_stride(d.y.vals[i] + t*(4 + 1), 1);
if (!b.x) break;
int left = (b.x - b.w / 2.)*sized.w;
int right = (b.x + b.w / 2.)*sized.w;
int top = (b.y - b.h / 2.)*sized.h;
int bot = (b.y + b.h / 2.)*sized.h;
draw_box_width(sized, left, top, right, bot, 1, 150, 100, 50); // 3 channels RGB
}
save_image(sized, buff);
if (show_imgs == 1) {
show_image(sized, buff);
wait_until_press_key_cv();
}
printf("\nYou use flag -show_imgs, so will be saved aug_...jpg images. Press Enter: \n");
//getchar();
}
free_image(orig);
free_image(cropped);
free(truth);
}
}
free(random_paths);
if (mixup_random_paths) free(mixup_random_paths);
return d;
}
#endif // OPENCV
void *load_thread(void *ptr)
{
//srand(time(0));
//printf("Loading data: %d\n", random_gen());
load_args a = *(struct load_args*)ptr;
if(a.exposure == 0) a.exposure = 1;
if(a.saturation == 0) a.saturation = 1;
if(a.aspect == 0) a.aspect = 1;
if (a.type == OLD_CLASSIFICATION_DATA){
*a.d = load_data_old(a.paths, a.n, a.m, a.labels, a.classes, a.w, a.h);
} else if (a.type == CLASSIFICATION_DATA){
*a.d = load_data_augment(a.paths, a.n, a.m, a.labels, a.classes, a.hierarchy, a.flip, a.min, a.max, a.w, a.h, a.angle, a.aspect, a.hue, a.saturation, a.exposure, a.mixup, a.blur, a.show_imgs, a.label_smooth_eps, a.dontuse_opencv);
} else if (a.type == SUPER_DATA){
*a.d = load_data_super(a.paths, a.n, a.m, a.w, a.h, a.scale);
} else if (a.type == WRITING_DATA){
*a.d = load_data_writing(a.paths, a.n, a.m, a.w, a.h, a.out_w, a.out_h);
} else if (a.type == REGION_DATA){
*a.d = load_data_region(a.n, a.paths, a.m, a.w, a.h, a.num_boxes, a.classes, a.jitter, a.hue, a.saturation, a.exposure);
} else if (a.type == DETECTION_DATA){
*a.d = load_data_detection(a.n, a.paths, a.m, a.w, a.h, a.c, a.num_boxes, a.classes, a.flip, a.gaussian_noise, a.blur, a.mixup, a.jitter,
a.hue, a.saturation, a.exposure, a.mini_batch, a.track, a.augment_speed, a.letter_box, a.show_imgs);
} else if (a.type == SWAG_DATA){
*a.d = load_data_swag(a.paths, a.n, a.classes, a.jitter);
} else if (a.type == COMPARE_DATA){
*a.d = load_data_compare(a.n, a.paths, a.m, a.classes, a.w, a.h);
} else if (a.type == IMAGE_DATA){
*(a.im) = load_image(a.path, 0, 0, a.c);
*(a.resized) = resize_image(*(a.im), a.w, a.h);
}else if (a.type == LETTERBOX_DATA) {
*(a.im) = load_image(a.path, 0, 0, a.c);
*(a.resized) = letterbox_image(*(a.im), a.w, a.h);
} else if (a.type == TAG_DATA){
*a.d = load_data_tag(a.paths, a.n, a.m, a.classes, a.flip, a.min, a.max, a.w, a.h, a.angle, a.aspect, a.hue, a.saturation, a.exposure);
}
free(ptr);
return 0;
}
pthread_t load_data_in_thread(load_args args)
{
pthread_t thread;
struct load_args* ptr = (load_args*)xcalloc(1, sizeof(struct load_args));
*ptr = args;
if(pthread_create(&thread, 0, load_thread, ptr)) error("Thread creation failed");
return thread;
}
void *load_threads(void *ptr)
{
//srand(time(0));
int i;
load_args args = *(load_args *)ptr;
if (args.threads == 0) args.threads = 1;
data *out = args.d;
int total = args.n;
free(ptr);
data* buffers = (data*)xcalloc(args.threads, sizeof(data));
pthread_t* threads = (pthread_t*)xcalloc(args.threads, sizeof(pthread_t));
for(i = 0; i < args.threads; ++i){
args.d = buffers + i;
args.n = (i+1) * total/args.threads - i * total/args.threads;
threads[i] = load_data_in_thread(args);
}
for(i = 0; i < args.threads; ++i){
pthread_join(threads[i], 0);
}
*out = concat_datas(buffers, args.threads);
out->shallow = 0;
for(i = 0; i < args.threads; ++i){
buffers[i].shallow = 1;
free_data(buffers[i]);
}
free(buffers);
free(threads);
return 0;
}
pthread_t load_data(load_args args)
{
pthread_t thread;
struct load_args* ptr = (load_args*)xcalloc(1, sizeof(struct load_args));
*ptr = args;
if(pthread_create(&thread, 0, load_threads, ptr)) error("Thread creation failed");
return thread;
}
data load_data_writing(char **paths, int n, int m, int w, int h, int out_w, int out_h)
{
if(m) paths = get_random_paths(paths, n, m);
char **replace_paths = find_replace_paths(paths, n, ".png", "-label.png");
data d = {0};
d.shallow = 0;
d.X = load_image_paths(paths, n, w, h);
d.y = load_image_paths_gray(replace_paths, n, out_w, out_h);
if(m) free(paths);
int i;
for(i = 0; i < n; ++i) free(replace_paths[i]);
free(replace_paths);
return d;
}
data load_data_old(char **paths, int n, int m, char **labels, int k, int w, int h)
{
if(m) paths = get_random_paths(paths, n, m);
data d = {0};
d.shallow = 0;
d.X = load_image_paths(paths, n, w, h);
d.y = load_labels_paths(paths, n, labels, k, 0, 0);
if(m) free(paths);
return d;
}
/*
data load_data_study(char **paths, int n, int m, char **labels, int k, int min, int max, int size, float angle, float aspect, float hue, float saturation, float exposure)
{
data d = {0};
d.indexes = calloc(n, sizeof(int));
if(m) paths = get_random_paths_indexes(paths, n, m, d.indexes);
d.shallow = 0;
d.X = load_image_augment_paths(paths, n, flip, min, max, size, angle, aspect, hue, saturation, exposure);
d.y = load_labels_paths(paths, n, labels, k);
if(m) free(paths);
return d;
}
*/
data load_data_super(char **paths, int n, int m, int w, int h, int scale)
{
if(m) paths = get_random_paths(paths, n, m);
data d = {0};
d.shallow = 0;
int i;
d.X.rows = n;
d.X.vals = (float**)xcalloc(n, sizeof(float*));
d.X.cols = w*h*3;
d.y.rows = n;
d.y.vals = (float**)xcalloc(n, sizeof(float*));
d.y.cols = w*scale * h*scale * 3;
for(i = 0; i < n; ++i){
image im = load_image_color(paths[i], 0, 0);
image crop = random_crop_image(im, w*scale, h*scale);
int flip = random_gen()%2;
if (flip) flip_image(crop);
image resize = resize_image(crop, w, h);
d.X.vals[i] = resize.data;
d.y.vals[i] = crop.data;
free_image(im);
}
if(m) free(paths);
return d;
}
data load_data_augment(char **paths, int n, int m, char **labels, int k, tree *hierarchy, int use_flip, int min, int max, int w, int h, float angle, float aspect, float hue, float saturation, float exposure, int use_mixup, int use_blur, int show_imgs, float label_smooth_eps, int dontuse_opencv)
{
char **paths_stored = paths;
if(m) paths = get_random_paths(paths, n, m);
data d = {0};
d.shallow = 0;
d.X = load_image_augment_paths(paths, n, use_flip, min, max, w, h, angle, aspect, hue, saturation, exposure, dontuse_opencv);
d.y = load_labels_paths(paths, n, labels, k, hierarchy, label_smooth_eps);
if (use_mixup && rand_int(0, 1)) {
char **paths_mix = get_random_paths(paths_stored, n, m);
data d2 = { 0 };
d2.shallow = 0;
d2.X = load_image_augment_paths(paths_mix, n, use_flip, min, max, w, h, angle, aspect, hue, saturation, exposure, dontuse_opencv);
d2.y = load_labels_paths(paths_mix, n, labels, k, hierarchy, label_smooth_eps);
free(paths_mix);
data d3 = { 0 };
d3.shallow = 0;
data d4 = { 0 };
d4.shallow = 0;
if (use_mixup >= 3) {
char **paths_mix3 = get_random_paths(paths_stored, n, m);
d3.X = load_image_augment_paths(paths_mix3, n, use_flip, min, max, w, h, angle, aspect, hue, saturation, exposure, dontuse_opencv);
d3.y = load_labels_paths(paths_mix3, n, labels, k, hierarchy, label_smooth_eps);
free(paths_mix3);
char **paths_mix4 = get_random_paths(paths_stored, n, m);
d4.X = load_image_augment_paths(paths_mix4, n, use_flip, min, max, w, h, angle, aspect, hue, saturation, exposure, dontuse_opencv);
d4.y = load_labels_paths(paths_mix4, n, labels, k, hierarchy, label_smooth_eps);
free(paths_mix4);
}
// mix
int i, j;
for (i = 0; i < d2.X.rows; ++i) {
int mixup = use_mixup;
if (use_mixup == 4) mixup = rand_int(2, 3); // alternate CutMix and Mosaic
// MixUp -----------------------------------
if (mixup == 1) {
// mix images
for (j = 0; j < d2.X.cols; ++j) {
d.X.vals[i][j] = (d.X.vals[i][j] + d2.X.vals[i][j]) / 2.0f;
}
// mix labels
for (j = 0; j < d2.y.cols; ++j) {
d.y.vals[i][j] = (d.y.vals[i][j] + d2.y.vals[i][j]) / 2.0f;
}
}
// CutMix -----------------------------------
else if (mixup == 2) {
const float min = 0.3; // 0.3*0.3 = 9%
const float max = 0.8; // 0.8*0.8 = 64%
const int cut_w = rand_int(w*min, w*max);
const int cut_h = rand_int(h*min, h*max);
const int cut_x = rand_int(0, w - cut_w - 1);
const int cut_y = rand_int(0, h - cut_h - 1);
const int left = cut_x;
const int right = cut_x + cut_w;
const int top = cut_y;
const int bot = cut_y + cut_h;
assert(cut_x >= 0 && cut_x <= w);
assert(cut_y >= 0 && cut_y <= h);
assert(cut_w >= 0 && cut_w <= w);
assert(cut_h >= 0 && cut_h <= h);
assert(right >= 0 && right <= w);
assert(bot >= 0 && bot <= h);
assert(top <= bot);
assert(left <= right);
const float alpha = (float)(cut_w*cut_h) / (float)(w*h);
const float beta = 1 - alpha;
int c, x, y;
for (c = 0; c < 3; ++c) {
for (y = top; y < bot; ++y) {
for (x = left; x < right; ++x) {
int j = x + y*w + c*w*h;
d.X.vals[i][j] = d2.X.vals[i][j];
}
}
}
//printf("\n alpha = %f, beta = %f \n", alpha, beta);
// mix labels
for (j = 0; j < d.y.cols; ++j) {
d.y.vals[i][j] = d.y.vals[i][j] * beta + d2.y.vals[i][j] * alpha;
}
}
// Mosaic -----------------------------------
else if (mixup == 3)
{
const float min_offset = 0.2; // 20%
const int cut_x = rand_int(w*min_offset, w*(1 - min_offset));
const int cut_y = rand_int(h*min_offset, h*(1 - min_offset));
float s1 = (float)(cut_x * cut_y) / (w*h);
float s2 = (float)((w - cut_x) * cut_y) / (w*h);
float s3 = (float)(cut_x * (h - cut_y)) / (w*h);
float s4 = (float)((w - cut_x) * (h - cut_y)) / (w*h);
int c, x, y;
for (c = 0; c < 3; ++c) {
for (y = 0; y < h; ++y) {
for (x = 0; x < w; ++x) {
int j = x + y*w + c*w*h;
if (x < cut_x && y < cut_y) d.X.vals[i][j] = d.X.vals[i][j];
if (x >= cut_x && y < cut_y) d.X.vals[i][j] = d2.X.vals[i][j];
if (x < cut_x && y >= cut_y) d.X.vals[i][j] = d3.X.vals[i][j];
if (x >= cut_x && y >= cut_y) d.X.vals[i][j] = d4.X.vals[i][j];
}
}
}
for (j = 0; j < d.y.cols; ++j) {
const float max_s = 1;// max_val_cmp(s1, max_val_cmp(s2, max_val_cmp(s3, s4)));
d.y.vals[i][j] = d.y.vals[i][j] * s1 / max_s + d2.y.vals[i][j] * s2 / max_s + d3.y.vals[i][j] * s3 / max_s + d4.y.vals[i][j] * s4 / max_s;
}
}
}
free_data(d2);
if (use_mixup >= 3) {
free_data(d3);
free_data(d4);
}
}
#ifdef OPENCV
if (use_blur) {
int i;
for (i = 0; i < d.X.rows; ++i) {
if (random_gen() % 2) {
image im = make_empty_image(w, h, 3);
im.data = d.X.vals[i];
int ksize = use_blur;
if (use_blur == 1) ksize = 17;
image blurred = blur_image(im, ksize);
free_image(im);
d.X.vals[i] = blurred.data;
//if (i == 0) {
// show_image(im, "Not blurred");
// show_image(blurred, "blurred");
// wait_until_press_key_cv();
//}
}
}
}
#endif // OPENCV
if (show_imgs) {
int i, j;
for (i = 0; i < d.X.rows; ++i) {
image im = make_empty_image(w, h, 3);
im.data = d.X.vals[i];
char buff[1000];
sprintf(buff, "aug_%d_%s_%d", i, basecfg((char*)paths[i]), random_gen());
save_image(im, buff);
char buff_string[1000];
sprintf(buff_string, "\n Classes: ");
for (j = 0; j < d.y.cols; ++j) {
if (d.y.vals[i][j] > 0) {
char buff_tmp[100];
sprintf(buff_tmp, " %d (%f), ", j, d.y.vals[i][j]);
strcat(buff_string, buff_tmp);
}
}
printf("%s \n", buff_string);
if (show_imgs == 1) {
show_image(im, buff);
wait_until_press_key_cv();
}
}
printf("\nYou use flag -show_imgs, so will be saved aug_...jpg images. Click on window and press ESC button \n");
}
if (m) free(paths);
return d;
}
data load_data_tag(char **paths, int n, int m, int k, int use_flip, int min, int max, int w, int h, float angle, float aspect, float hue, float saturation, float exposure)
{
if(m) paths = get_random_paths(paths, n, m);
data d = {0};
d.w = w;
d.h = h;
d.shallow = 0;
d.X = load_image_augment_paths(paths, n, use_flip, min, max, w, h, angle, aspect, hue, saturation, exposure, 0);
d.y = load_tags_paths(paths, n, k);
if(m) free(paths);
return d;
}
matrix concat_matrix(matrix m1, matrix m2)
{
int i, count = 0;
matrix m;
m.cols = m1.cols;
m.rows = m1.rows+m2.rows;
m.vals = (float**)xcalloc(m1.rows + m2.rows, sizeof(float*));
for(i = 0; i < m1.rows; ++i){
m.vals[count++] = m1.vals[i];
}
for(i = 0; i < m2.rows; ++i){
m.vals[count++] = m2.vals[i];
}
return m;
}
data concat_data(data d1, data d2)
{
data d = {0};
d.shallow = 1;
d.X = concat_matrix(d1.X, d2.X);
d.y = concat_matrix(d1.y, d2.y);
return d;
}
data concat_datas(data *d, int n)
{
int i;
data out = {0};
for(i = 0; i < n; ++i){
data newdata = concat_data(d[i], out);
free_data(out);
out = newdata;
}
return out;
}
data load_categorical_data_csv(char *filename, int target, int k)
{
data d = {0};
d.shallow = 0;
matrix X = csv_to_matrix(filename);
float *truth_1d = pop_column(&X, target);
float **truth = one_hot_encode(truth_1d, X.rows, k);
matrix y;
y.rows = X.rows;
y.cols = k;
y.vals = truth;
d.X = X;
d.y = y;
free(truth_1d);
return d;
}
data load_cifar10_data(char *filename)
{
data d = {0};
d.shallow = 0;
long i,j;
matrix X = make_matrix(10000, 3072);
matrix y = make_matrix(10000, 10);
d.X = X;
d.y = y;
FILE *fp = fopen(filename, "rb");
if(!fp) file_error(filename);
for(i = 0; i < 10000; ++i){
unsigned char bytes[3073];
fread(bytes, 1, 3073, fp);
int class_id = bytes[0];
y.vals[i][class_id] = 1;
for(j = 0; j < X.cols; ++j){
X.vals[i][j] = (double)bytes[j+1];
}
}
//translate_data_rows(d, -128);
scale_data_rows(d, 1./255);
//normalize_data_rows(d);
fclose(fp);
return d;
}
void get_random_batch(data d, int n, float *X, float *y)
{
int j;
for(j = 0; j < n; ++j){
int index = random_gen()%d.X.rows;
memcpy(X+j*d.X.cols, d.X.vals[index], d.X.cols*sizeof(float));
memcpy(y+j*d.y.cols, d.y.vals[index], d.y.cols*sizeof(float));
}
}
void get_next_batch(data d, int n, int offset, float *X, float *y)
{
int j;
for(j = 0; j < n; ++j){
int index = offset + j;
memcpy(X+j*d.X.cols, d.X.vals[index], d.X.cols*sizeof(float));
memcpy(y+j*d.y.cols, d.y.vals[index], d.y.cols*sizeof(float));
}
}
void smooth_data(data d)
{
int i, j;
float scale = 1. / d.y.cols;
float eps = .1;
for(i = 0; i < d.y.rows; ++i){
for(j = 0; j < d.y.cols; ++j){
d.y.vals[i][j] = eps * scale + (1-eps) * d.y.vals[i][j];
}
}
}
data load_all_cifar10()
{
data d = {0};
d.shallow = 0;
int i,j,b;
matrix X = make_matrix(50000, 3072);
matrix y = make_matrix(50000, 10);
d.X = X;
d.y = y;
for(b = 0; b < 5; ++b){
char buff[256];
sprintf(buff, "data/cifar/cifar-10-batches-bin/data_batch_%d.bin", b+1);
FILE *fp = fopen(buff, "rb");
if(!fp) file_error(buff);
for(i = 0; i < 10000; ++i){
unsigned char bytes[3073];
fread(bytes, 1, 3073, fp);
int class_id = bytes[0];
y.vals[i+b*10000][class_id] = 1;
for(j = 0; j < X.cols; ++j){
X.vals[i+b*10000][j] = (double)bytes[j+1];
}
}
fclose(fp);
}
//normalize_data_rows(d);
//translate_data_rows(d, -128);
scale_data_rows(d, 1./255);
smooth_data(d);
return d;
}
data load_go(char *filename)
{
FILE *fp = fopen(filename, "rb");
matrix X = make_matrix(3363059, 361);
matrix y = make_matrix(3363059, 361);
int row, col;
if(!fp) file_error(filename);
char *label;
int count = 0;
while((label = fgetl(fp))){
int i;
if(count == X.rows){
X = resize_matrix(X, count*2);
y = resize_matrix(y, count*2);
}
sscanf(label, "%d %d", &row, &col);
char *board = fgetl(fp);
int index = row*19 + col;
y.vals[count][index] = 1;
for(i = 0; i < 19*19; ++i){
float val = 0;
if(board[i] == '1') val = 1;
else if(board[i] == '2') val = -1;
X.vals[count][i] = val;
}
++count;
free(label);
free(board);
}
X = resize_matrix(X, count);
y = resize_matrix(y, count);
data d = {0};
d.shallow = 0;
d.X = X;
d.y = y;
fclose(fp);
return d;
}
void randomize_data(data d)
{
int i;
for(i = d.X.rows-1; i > 0; --i){
int index = random_gen()%i;
float *swap = d.X.vals[index];
d.X.vals[index] = d.X.vals[i];
d.X.vals[i] = swap;
swap = d.y.vals[index];
d.y.vals[index] = d.y.vals[i];
d.y.vals[i] = swap;
}
}
void scale_data_rows(data d, float s)
{
int i;
for(i = 0; i < d.X.rows; ++i){
scale_array(d.X.vals[i], d.X.cols, s);
}
}
void translate_data_rows(data d, float s)
{
int i;
for(i = 0; i < d.X.rows; ++i){
translate_array(d.X.vals[i], d.X.cols, s);
}
}
void normalize_data_rows(data d)
{
int i;
for(i = 0; i < d.X.rows; ++i){
normalize_array(d.X.vals[i], d.X.cols);
}
}
data get_data_part(data d, int part, int total)
{
data p = {0};
p.shallow = 1;
p.X.rows = d.X.rows * (part + 1) / total - d.X.rows * part / total;
p.y.rows = d.y.rows * (part + 1) / total - d.y.rows * part / total;
p.X.cols = d.X.cols;
p.y.cols = d.y.cols;
p.X.vals = d.X.vals + d.X.rows * part / total;
p.y.vals = d.y.vals + d.y.rows * part / total;
return p;
}
data get_random_data(data d, int num)
{
data r = {0};
r.shallow = 1;
r.X.rows = num;
r.y.rows = num;
r.X.cols = d.X.cols;
r.y.cols = d.y.cols;
r.X.vals = (float**)xcalloc(num, sizeof(float*));
r.y.vals = (float**)xcalloc(num, sizeof(float*));
int i;
for(i = 0; i < num; ++i){
int index = random_gen()%d.X.rows;
r.X.vals[i] = d.X.vals[index];
r.y.vals[i] = d.y.vals[index];
}
return r;
}
data *split_data(data d, int part, int total)
{
data* split = (data*)xcalloc(2, sizeof(data));
int i;
int start = part*d.X.rows/total;
int end = (part+1)*d.X.rows/total;
data train ={0};
data test ={0};
train.shallow = test.shallow = 1;
test.X.rows = test.y.rows = end-start;
train.X.rows = train.y.rows = d.X.rows - (end-start);
train.X.cols = test.X.cols = d.X.cols;
train.y.cols = test.y.cols = d.y.cols;
train.X.vals = (float**)xcalloc(train.X.rows, sizeof(float*));
test.X.vals = (float**)xcalloc(test.X.rows, sizeof(float*));
train.y.vals = (float**)xcalloc(train.y.rows, sizeof(float*));
test.y.vals = (float**)xcalloc(test.y.rows, sizeof(float*));
for(i = 0; i < start; ++i){
train.X.vals[i] = d.X.vals[i];
train.y.vals[i] = d.y.vals[i];
}
for(i = start; i < end; ++i){
test.X.vals[i-start] = d.X.vals[i];
test.y.vals[i-start] = d.y.vals[i];
}
for(i = end; i < d.X.rows; ++i){
train.X.vals[i-(end-start)] = d.X.vals[i];
train.y.vals[i-(end-start)] = d.y.vals[i];
}
split[0] = train;
split[1] = test;
return split;
}
|
GB_binop__isle_int64.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__isle_int64)
// A.*B function (eWiseMult): GB (_AemultB_08__isle_int64)
// A.*B function (eWiseMult): GB (_AemultB_02__isle_int64)
// A.*B function (eWiseMult): GB (_AemultB_04__isle_int64)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__isle_int64)
// A*D function (colscale): GB (_AxD__isle_int64)
// D*A function (rowscale): GB (_DxB__isle_int64)
// C+=B function (dense accum): GB (_Cdense_accumB__isle_int64)
// C+=b function (dense accum): GB (_Cdense_accumb__isle_int64)
// C+=A+B function (dense ewise3): GB ((none))
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__isle_int64)
// C=scalar+B GB (_bind1st__isle_int64)
// C=scalar+B' GB (_bind1st_tran__isle_int64)
// C=A+scalar GB (_bind2nd__isle_int64)
// C=A'+scalar GB (_bind2nd_tran__isle_int64)
// C type: int64_t
// A type: int64_t
// B,b type: int64_t
// BinaryOp: cij = (aij <= bij)
#define GB_ATYPE \
int64_t
#define GB_BTYPE \
int64_t
#define GB_CTYPE \
int64_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) \
int64_t aij = GBX (Ax, pA, A_iso)
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB,B_iso) \
int64_t bij = GBX (Bx, pB, B_iso)
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
int64_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_ISLE || GxB_NO_INT64 || GxB_NO_ISLE_INT64)
//------------------------------------------------------------------------------
// 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__isle_int64)
(
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__isle_int64)
(
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__isle_int64)
(
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 int64_t
int64_t bwork = (*((int64_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__isle_int64)
(
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
int64_t *restrict Cx = (int64_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__isle_int64)
(
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
int64_t *restrict Cx = (int64_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__isle_int64)
(
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__isle_int64)
(
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__isle_int64)
(
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__isle_int64)
(
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__isle_int64)
(
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__isle_int64)
(
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
int64_t *Cx = (int64_t *) Cx_output ;
int64_t x = (*((int64_t *) x_input)) ;
int64_t *Bx = (int64_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 ;
int64_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__isle_int64)
(
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 ;
int64_t *Cx = (int64_t *) Cx_output ;
int64_t *Ax = (int64_t *) Ax_input ;
int64_t y = (*((int64_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
int64_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) \
{ \
int64_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = (x <= aij) ; \
}
GrB_Info GB (_bind1st_tran__isle_int64)
(
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 \
int64_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t x = (*((const int64_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
int64_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) \
{ \
int64_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = (aij <= y) ; \
}
GrB_Info GB (_bind2nd_tran__isle_int64)
(
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
int64_t y = (*((const int64_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
yolov2.h | #ifndef YOLOV2_H
#define YOLOV2_H
#include <stdio.h>
#include <stdlib.h>
#include <iostream>
#include <math.h>
#include <fcntl.h>
#include <string.h>
#include <assert.h>
#define STB_IMAGE_IMPLEMENTATION
#include "stb_image.h"
#define STB_IMAGE_WRITE_IMPLEMENTATION
#include "stb_image_write.h"
#include "cnn.h"
#define FLT_MAX 3.402823466e+38F
typedef enum{
LOGISTIC, RELU, RELIE, LINEAR, RAMP, TANH, PLSE, LEAKY, ELU, LOGGY, STAIR, HARDTAN, LHTAN
} ACTIVATION;
typedef enum {
CONVOLUTIONAL,
DECONVOLUTIONAL,
CONNECTED,
MAXPOOL,
SOFTMAX,
DETECTION,
DROPOUT,
CROP,
ROUTE,
COST,
NORMALIZATION,
AVGPOOL,
LOCAL,
SHORTCUT,
ACTIVE,
RNN,
GRU,
LSTM,
CRNN,
BATCHNORM,
NETWORK,
XNOR,
REGION,
YOLO,
REORG,
UPSAMPLE,
LOGXENT,
L2NORM,
BLANK
} LAYER_TYPE;
struct network;
typedef struct network network;
struct layer;
typedef struct layer layer;
struct layer{
LAYER_TYPE type;
ACTIVATION activation;
void (*forward) (struct layer, struct network);
int batch_normalize;
int shortcut;
int batch;
int forced;
int flipped;
int inputs;
int outputs;
int nweights;
int nbiases;
int extra;
int truths;
int h,w,c;
int out_h, out_w, out_c;
int n;
int max_boxes;
int groups;
int size;
int side;
int stride;
int reverse;
int flatten;
int spatial;
int pad;
int sqrt;
int flip;
int index;
int binary;
int xnor;
int steps;
int hidden;
int truth;
float smooth;
float dot;
float angle;
float jitter;
float saturation;
float exposure;
float shift;
float ratio;
float learning_rate_scale;
float clip;
int softmax;
int classes;
int coords;
int background;
int rescore;
int objectness;
int joint;
int noadjust;
int reorg;
int log;
int tanh;
int *mask;
int total;
float alpha;
float beta;
float kappa;
float coord_scale;
float object_scale;
float noobject_scale;
float mask_scale;
float class_scale;
int bias_match;
int random;
float ignore_thresh;
float truth_thresh;
float thresh;
float focus;
int classfix;
int absolute;
int onlyforward;
int stopbackward;
// int dontload;
int dontsave;
// int dontloadscales;
float temperature;
float probability;
float scale;
char * cweights;
int * indexes;
int * input_layers;
int * input_sizes;
int * map;
float * rand;
float * cost;
float * state;
float * prev_state;
float * forgot_state;
float * forgot_delta;
float * state_delta;
float * combine_cpu;
float * combine_delta_cpu;
float * concat;
float * concat_delta;
float * binary_weights;
float * biases;
float * bias_updates;
float * scales;
float * scale_updates;
float * weights;
float * weight_updates;
float * delta;
float * output;
float * loss;
float * squared;
float * norms;
float * spatial_mean;
float * mean;
float * variance;
float * mean_delta;
float * variance_delta;
float * rolling_mean;
float * rolling_variance;
float * x;
float * x_norm;
float * m;
float * v;
float * bias_m;
float * bias_v;
float * scale_m;
float * scale_v;
float *z_cpu;
float *r_cpu;
float *h_cpu;
float * prev_state_cpu;
float *temp_cpu;
float *temp2_cpu;
float *temp3_cpu;
float *dh_cpu;
float *hh_cpu;
float *prev_cell_cpu;
float *cell_cpu;
float *f_cpu;
float *i_cpu;
float *g_cpu;
float *o_cpu;
float *c_cpu;
float *dc_cpu;
float * binary_input;
struct layer *input_layer;
struct layer *self_layer;
struct layer *output_layer;
struct layer *reset_layer;
struct layer *update_layer;
struct layer *state_layer;
struct layer *input_gate_layer;
struct layer *state_gate_layer;
struct layer *input_save_layer;
struct layer *state_save_layer;
struct layer *input_state_layer;
struct layer *state_state_layer;
struct layer *input_z_layer;
struct layer *state_z_layer;
struct layer *input_r_layer;
struct layer *state_r_layer;
struct layer *input_h_layer;
struct layer *state_h_layer;
struct layer *wz;
struct layer *uz;
struct layer *wr;
struct layer *ur;
struct layer *wh;
struct layer *uh;
struct layer *uo;
struct layer *wo;
struct layer *uf;
struct layer *wf;
struct layer *ui;
struct layer *wi;
struct layer *ug;
struct layer *wg;
//tree *softmax_tree;
size_t workspace_size;
};
void free_layer(layer l)
{
if(l.cweights) free(l.cweights);
if(l.indexes) free(l.indexes);
if(l.input_layers) free(l.input_layers);
if(l.input_sizes) free(l.input_sizes);
if(l.map) free(l.map);
if(l.rand) free(l.rand);
if(l.cost) free(l.cost);
if(l.state) free(l.state);
if(l.prev_state) free(l.prev_state);
if(l.forgot_state) free(l.forgot_state);
if(l.forgot_delta) free(l.forgot_delta);
if(l.state_delta) free(l.state_delta);
if(l.concat) free(l.concat);
if(l.concat_delta) free(l.concat_delta);
if(l.binary_weights) free(l.binary_weights);
if(l.biases) free(l.biases);
if(l.bias_updates) free(l.bias_updates);
if(l.scales) free(l.scales);
if(l.scale_updates) free(l.scale_updates);
if(l.weights) free(l.weights);
if(l.weight_updates) free(l.weight_updates);
if(l.delta) free(l.delta);
if(l.output) free(l.output);
if(l.squared) free(l.squared);
if(l.norms) free(l.norms);
if(l.spatial_mean) free(l.spatial_mean);
if(l.mean) free(l.mean);
if(l.variance) free(l.variance);
if(l.mean_delta) free(l.mean_delta);
if(l.variance_delta) free(l.variance_delta);
if(l.rolling_mean) free(l.rolling_mean);
if(l.rolling_variance) free(l.rolling_variance);
if(l.x) free(l.x);
if(l.x_norm) free(l.x_norm);
if(l.m) free(l.m);
if(l.v) free(l.v);
if(l.z_cpu) free(l.z_cpu);
if(l.r_cpu) free(l.r_cpu);
if(l.h_cpu) free(l.h_cpu);
if(l.binary_input) free(l.binary_input);
}
//void free_layer(layer);
typedef enum {
CONSTANT, STEP, EXP, POLY, STEPS, SIG, RANDOM
} learning_rate_policy;
typedef struct network{
int n;
int batch;
size_t *seen;
int *t;
float epoch;
int subdivisions;
layer *layers;
float *output;
learning_rate_policy policy;
float learning_rate;
float momentum;
float decay;
float gamma;
float scale;
float power;
int time_steps;
int step;
int max_batches;
float *scales;
int *steps;
int num_steps;
int burn_in;
int adam;
float B1;
float B2;
float eps;
int inputs;
int outputs;
int truths;
int notruth;
int h, w, c;
int max_crop;
int min_crop;
float max_ratio;
float min_ratio;
int center;
float angle;
float aspect;
float exposure;
float saturation;
float hue;
int random;
int gpu_index;
// tree *hierarchy;
float *input;
float *truth;
float *delta;
float *workspace;
int train;
int index;
float *cost;
float clip;
} network;
network *make_network(int n);
layer get_network_output_layer(network *net);
typedef struct {
int w;
int h;
float scale;
float rad;
float dx;
float dy;
float aspect;
} augment_args;
typedef struct {
int w;
int h;
int c;
float *data;
} image;
typedef struct{
float x, y, w, h;
} box;
typedef struct detection{
box bbox;
int classes;
float *prob;
float *mask;
float objectness;
int sort_class;
} detection;
typedef struct matrix{
int rows, cols;
float **vals;
} matrix;
typedef struct{
int w, h;
matrix X;
matrix y;
int shallow;
int *num_boxes;
box **boxes;
} data;
typedef enum {
CLASSIFICATION_DATA, DETECTION_DATA, CAPTCHA_DATA, REGION_DATA, IMAGE_DATA, COMPARE_DATA, WRITING_DATA, SWAG_DATA, TAG_DATA, OLD_CLASSIFICATION_DATA, STUDY_DATA, DET_DATA, SUPER_DATA, LETTERBOX_DATA, REGRESSION_DATA, SEGMENTATION_DATA, INSTANCE_DATA
} data_type;
typedef struct load_args{
int threads;
char **paths;
char *path;
int n;
int m;
char **labels;
int h;
int w;
int out_w;
int out_h;
int nh;
int nw;
int num_boxes;
int min, max, size;
int classes;
int background;
int scale;
int center;
int coords;
float jitter;
float angle;
float aspect;
float saturation;
float exposure;
float hue;
data *d;
image *im;
image *resized;
data_type type;
// tree *hierarchy;
} load_args;
typedef struct{
int id;
float x,y,w,h;
float left, right, top, bottom;
} box_label;
//network *load_network(char *cfg, char *weights, int clear);
//load_args get_base_args(network *net);
//void free_data(data d);
typedef struct{
char *key;
char *val;
int used;
} kvp;
typedef struct node{
void *val;
struct node *next;
struct node *prev;
} node;
typedef struct list{
int size;
node *front;
node *back;
} list;
void error(const char *s)
{
perror(s);
assert(0);
exit(-1);
}
void malloc_error()
{
fprintf(stderr, "Malloc error\n");
exit(-1);
}
void file_error(char *s)
{
fprintf(stderr, "Couldn't open file: %s\n", s);
exit(0);
}
/////////////////list begin
list *make_list()
{
list *l = (list *)malloc(sizeof(list));
l->size = 0;
l->front = 0;
l->back = 0;
return l;
}
void *list_pop(list *l){
if(!l->back) return 0;
node *b = l->back;
void *val = b->val;
l->back = b->prev;
if(l->back) l->back->next = 0;
free(b);
--l->size;
return val;
}
void list_insert(list *l, void *val)
{
node *new_node = (node *)malloc(sizeof(node));
new_node->val = val;
new_node->next = 0;
if(!l->back){
l->front = new_node;
new_node->prev = 0;
}else{
l->back->next = new_node;
new_node->prev = l->back;
}
l->back = new_node;
++l->size;
}
void free_node(node *n)
{
node *next;
while(n) {
next = n->next;
free(n);
n = next;
}
}
void free_list(list *l)
{
free_node(l->front);
free(l);
}
void free_list_contents(list *l)
{
node *n = l->front;
while(n){
free(n->val);
n = n->next;
}
}
void **list_to_array(list *l)
{
void **a = (void **)calloc(l->size, sizeof(void*));
int count = 0;
node *n = l->front;
while(n){
a[count++] = n->val;
n = n->next;
}
return a;
}
/////////////////list end
/////////////////////utils begin
void del_arg(int argc, char **argv, int index)
{
int i;
for(i = index; i < argc-1; ++i) argv[i] = argv[i+1];
argv[i] = 0;
}
int find_arg(int argc, char* argv[], char *arg)
{
int i;
for(i = 0; i < argc; ++i) {
if(!argv[i]) continue;
if(0==strcmp(argv[i], arg)) {
del_arg(argc, argv, i);
return 1;
}
}
return 0;
}
int find_int_arg(int argc, char **argv, char *arg, int def)
{
int i;
for(i = 0; i < argc-1; ++i){
if(!argv[i]) continue;
if(0==strcmp(argv[i], arg)){
def = atoi(argv[i+1]);
del_arg(argc, argv, i);
del_arg(argc, argv, i);
break;
}
}
return def;
}
float find_float_arg(int argc, char **argv, char *arg, float def)
{
int i;
for(i = 0; i < argc-1; ++i){
if(!argv[i]) continue;
if(0==strcmp(argv[i], arg)){
def = atof(argv[i+1]);
del_arg(argc, argv, i);
del_arg(argc, argv, i);
break;
}
}
return def;
}
char *find_char_arg(int argc, char **argv, char *arg, char *def)
{
int i;
for(i = 0; i < argc-1; ++i){
if(!argv[i]) continue;
if(0==strcmp(argv[i], arg)){
def = argv[i+1];
del_arg(argc, argv, i);
del_arg(argc, argv, i);
break;
}
}
return def;
}
unsigned char *read_file(char *filename)
{
FILE *fp = fopen(filename, "rb");
size_t size;
fseek(fp, 0, SEEK_END);
size = ftell(fp);
fseek(fp, 0, SEEK_SET);
unsigned char *text = (unsigned char *)calloc(size+1, sizeof(unsigned char));
fread(text, 1, size, fp);
fclose(fp);
return text;
}
list *split_str(char *s, char delim)
{
size_t i;
size_t len = strlen(s);
list *l = make_list();
list_insert(l, s);
for(i = 0; i < len; ++i){
if(s[i] == delim){
s[i] = '\0';
list_insert(l, &(s[i+1]));
}
}
return l;
}
void strip(char *s)
{
size_t i;
size_t len = strlen(s);
size_t offset = 0;
for(i = 0; i < len; ++i){
char c = s[i];
if(c==' '||c=='\t'||c=='\n') ++offset;
else s[i-offset] = c;
}
s[len-offset] = '\0';
}
void strip_char(char *s, char bad)
{
size_t i;
size_t len = strlen(s);
size_t offset = 0;
for(i = 0; i < len; ++i){
char c = s[i];
if(c==bad) ++offset;
else s[i-offset] = c;
}
s[len-offset] = '\0';
}
void free_ptrs(void **ptrs, int n)
{
int i;
for(i = 0; i < n; ++i) free(ptrs[i]);
free(ptrs);
}
char *fgetl(FILE *fp)
{
if(feof(fp)) return 0;
size_t size = 512;
char *line = (char *)malloc(size*sizeof(char));
if(!fgets(line, size, fp)){
free(line);
return 0;
}
size_t curr = strlen(line);
while((line[curr-1] != '\n') && !feof(fp)){
if(curr == size-1){
size *= 2;
line = (char *)realloc(line, size*sizeof(char));
if(!line) {
printf("%ld\n", size);
malloc_error();
}
}
size_t readsize = size-curr;
if(readsize > INT_MAX) readsize = INT_MAX-1;
fgets(&line[curr], readsize, fp);
curr = strlen(line);
}
if(line[curr-1] == '\n') line[curr-1] = '\0';
return line;
}
/////////////////////utils end
////////////////////option_list begin
void option_insert(list *l, char *key, char *val)
{
kvp *p = (kvp *)malloc(sizeof(kvp));
p->key = key;
p->val = val;
p->used = 0;
list_insert(l, p);
}
int read_option(char *s, list *options)
{
size_t i;
size_t len = strlen(s);
char *val = 0;
for(i = 0; i < len; ++i){
if(s[i] == '='){
s[i] = '\0';
val = s+i+1;
break;
}
}
if(i == len-1) return 0;
char *key = s;
option_insert(options, key, val);
return 1;
}
void option_unused(list *l)
{
node *n = l->front;
while(n){
kvp *p = (kvp *)n->val;
if(!p->used){
fprintf(stderr, "Unused field: '%s = %s'\n", p->key, p->val);
}
n = n->next;
}
}
char *option_find(list *l, char *key)
{
node *n = l->front;
while(n){
kvp *p = (kvp *)n->val;
if(strcmp(p->key, key) == 0){
p->used = 1;
return p->val;
}
n = n->next;
}
return 0;
}
char *option_find_str(list *l, char *key, char *def)
{
char *v = option_find(l, key);
if(v) return v;
if(def) fprintf(stderr, "%s: Using default '%s'\n", key, def);
return def;
}
int option_find_int(list *l, char *key, int def)
{
char *v = option_find(l, key);
if(v) return atoi(v);
fprintf(stderr, "%s: Using default '%d'\n", key, def);
return def;
}
int option_find_int_quiet(list *l, char *key, int def)
{
char *v = option_find(l, key);
if(v) return atoi(v);
return def;
}
float option_find_float_quiet(list *l, char *key, float def)
{
char *v = option_find(l, key);
if(v) return atof(v);
return def;
}
float option_find_float(list *l, char *key, float def)
{
char *v = option_find(l, key);
if(v) return atof(v);
fprintf(stderr, "%s: Using default '%lf'\n", key, def);
return def;
}
list *read_data_cfg(char *filename)
{
FILE *file = fopen(filename, "r");
if(file == 0) file_error(filename);
char *line;
int nu = 0;
list *options = make_list();
while((line=fgetl(file)) != 0){
++ nu;
strip(line);
switch(line[0]){
case '\0':
case '#':
case ';':
free(line);
break;
default:
if(!read_option(line, options)){
fprintf(stderr, "Config file error line %d, could parse: %s\n", nu, line);
free(line);
}
break;
}
}
fclose(file);
return options;
}
///////////////////option_list end
image make_empty_image(int w, int h, int c)
{
image out;
out.data = 0;
out.h = h;
out.w = w;
out.c = c;
return out;
}
list *get_paths(char *filename)
{
char *path;
FILE *file = fopen(filename, "r");
if(!file) file_error(filename);
list *lines = make_list();
while((path=fgetl(file))){
list_insert(lines, path);
}
fclose(file);
return lines;
}
char **get_labels(char *filename)
{
list *plist = get_paths(filename);
char **labels = (char **)list_to_array(plist);
free_list(plist);
return labels;
}
image make_image(int w, int h, int c)
{
image out = make_empty_image(w,h,c);
out.data = (float *)calloc(h*w*c, sizeof(float));
return out;
}
static float get_pixel(image m, int x, int y, int c)
{
assert(x < m.w && y < m.h && c < m.c);
return m.data[c*m.h*m.w + y*m.w + x];
}
static void set_pixel(image m, int x, int y, int c, float val)
{
if (x < 0 || y < 0 || c < 0 || x >= m.w || y >= m.h || c >= m.c) return;
assert(x < m.w && y < m.h && c < m.c);
m.data[c*m.h*m.w + y*m.w + x] = val;
}
static void add_pixel(image m, int x, int y, int c, float val)
{
assert(x < m.w && y < m.h && c < m.c);
m.data[c*m.h*m.w + y*m.w + x] += val;
}
void free_image(image m)
{
if(m.data){
free(m.data);
}
}
image resize_image(image im, int w, int h)
{
image resized = make_image(w, h, im.c);
image part = make_image(w, im.h, im.c);
int r, c, k;
float w_scale = (float)(im.w - 1) / (w - 1);
float h_scale = (float)(im.h - 1) / (h - 1);
for(k = 0; k < im.c; ++k){
for(r = 0; r < im.h; ++r){
for(c = 0; c < w; ++c){
float val = 0;
if(c == w-1 || im.w == 1){
val = get_pixel(im, im.w-1, r, k);
} else {
float sx = c*w_scale;
int ix = (int) sx;
float dx = sx - ix;
val = (1 - dx) * get_pixel(im, ix, r, k) + dx * get_pixel(im, ix+1, r, k);
}
set_pixel(part, c, r, k, val);
}
}
}
for(k = 0; k < im.c; ++k){
for(r = 0; r < h; ++r){
float sy = r*h_scale;
int iy = (int) sy;
float dy = sy - iy;
for(c = 0; c < w; ++c){
float val = (1-dy) * get_pixel(part, c, iy, k);
set_pixel(resized, c, r, k, val);
}
if(r == h-1 || im.h == 1) continue;
for(c = 0; c < w; ++c){
float val = dy * get_pixel(part, c, iy+1, k);
add_pixel(resized, c, r, k, val);
}
}
}
free_image(part);
return resized;
}
void fill_image(image m, float s)
{
int i;
for(i = 0; i < m.h*m.w*m.c; ++i) m.data[i] = s;
}
void embed_image(image source, image dest, int dx, int dy)
{
int x,y,k;
for(k = 0; k < source.c; ++k){
for(y = 0; y < source.h; ++y){
for(x = 0; x < source.w; ++x){
float val = get_pixel(source, x,y,k);
set_pixel(dest, dx+x, dy+y, k, val);
}
}
}
}
image letterbox_image(image im, int w, int h)
{
int new_w = im.w;
int new_h = im.h;
if (((float)w/im.w) < ((float)h/im.h)) {
new_w = w;
new_h = (im.h * w)/im.w;
} else {
new_h = h;
new_w = (im.w * h)/im.h;
}
image resized = resize_image(im, new_w, new_h);
image boxed = make_image(w, h, im.c);
fill_image(boxed, .5);
//int i;
//for(i = 0; i < boxed.w*boxed.h*boxed.c; ++i) boxed.data[i] = 0;
embed_image(resized, boxed, (w-new_w)/2, (h-new_h)/2);
free_image(resized);
return boxed;
}
image load_image_stb(char *filename, int channels)
{
int w, h, c;
unsigned char *data = stbi_load(filename, &w, &h, &c, channels);
if (!data) {
fprintf(stderr, "Cannot load image \"%s\"\nSTB Reason: %s\n", filename, stbi_failure_reason());
exit(0);
}
if(channels) c = channels;
int i,j,k;
image im = make_image(w, h, c);
for(k = 0; k < c; ++k){
for(j = 0; j < h; ++j){
for(i = 0; i < w; ++i){
int dst_index = i + w*j + w*h*k;
int src_index = k + c*i + c*w*j;
im.data[dst_index] = (float)data[src_index]/255.;
}
}
}
free(data);
return im;
}
void save_image_png(image im, const char *name)
{
char buff[256];
//sprintf(buff, "%s (%d)", name, windows);
sprintf(buff, "%s.png", name);
unsigned char *data = (unsigned char *)calloc(im.w*im.h*im.c, sizeof(char));
int i,k;
for(k = 0; k < im.c; ++k){
for(i = 0; i < im.w*im.h; ++i){
data[i*im.c+k] = (unsigned char) (255*im.data[i + k*im.w*im.h]);
}
}
int success = stbi_write_png(buff, im.w, im.h, im.c, data, im.w*im.c);
free(data);
if(!success) fprintf(stderr, "Failed to write image %s\n", buff);
}
image **load_alphabet()
{
int i, j;
const int nsize = 8;
image **alphabets = (image **)calloc(nsize, sizeof(image));
for(j = 0; j < nsize; ++j){
alphabets[j] = (image *)calloc(128, sizeof(image));
for(i = 32; i < 127; ++i){
char buff[256];
sprintf(buff, "labels/%d_%d.png", i, j);
//alphabets[j][i] = load_image_color(buff, 0, 0);
alphabets[j][i] = load_image_stb(buff, 3);
}
}
return alphabets;
}
///////////////////activation begin
static inline float stair_activate(float x)
{
int n = floor(x);
if (n%2 == 0) return floor(x/2.);
else return (x - n) + floor(x/2.);
}
static inline float hardtan_activate(float x)
{
if (x < -1) return -1;
if (x > 1) return 1;
return x;
}
static inline float linear_activate(float x){return x;}
static inline float logistic_activate(float x){return 1./(1. + exp(-x));}
static inline float loggy_activate(float x){return 2./(1. + exp(-x)) - 1;}
static inline float relu_activate(float x){return x*(x>0);}
static inline float elu_activate(float x){return (x >= 0)*x + (x < 0)*(exp(x)-1);}
static inline float relie_activate(float x){return (x>0) ? x : .01*x;}
static inline float ramp_activate(float x){return x*(x>0)+.1*x;}
static inline float leaky_activate(float x){return (x>0) ? x : .1*x;}
static inline float tanh_activate(float x){return (exp(2*x)-1)/(exp(2*x)+1);}
static inline float plse_activate(float x)
{
if(x < -4) return .01 * (x + 4);
if(x > 4) return .01 * (x - 4) + 1;
return .125*x + .5;
}
static inline float lhtan_activate(float x)
{
if(x < 0) return .001*x;
if(x > 1) return .001*(x-1) + 1;
return x;
}
static inline float lhtan_gradient(float x)
{
if(x > 0 && x < 1) return 1;
return .001;
}
static inline float hardtan_gradient(float x)
{
if (x > -1 && x < 1) return 1;
return 0;
}
static inline float linear_gradient(float x){return 1;}
static inline float logistic_gradient(float x){return (1-x)*x;}
static inline float loggy_gradient(float x)
{
float y = (x+1.)/2.;
return 2*(1-y)*y;
}
static inline float stair_gradient(float x)
{
if (floor(x) == x) return 0;
return 1;
}
static inline float relu_gradient(float x){return (x>0);}
static inline float elu_gradient(float x){return (x >= 0) + (x < 0)*(x + 1);}
static inline float relie_gradient(float x){return (x>0) ? 1 : .01;}
static inline float ramp_gradient(float x){return (x>0)+.1;}
static inline float leaky_gradient(float x){return (x>0) ? 1 : .1;}
static inline float tanh_gradient(float x){return 1-x*x;}
static inline float plse_gradient(float x){return (x < 0 || x > 1) ? .01 : .125;}
char *get_activation_string(ACTIVATION a)
{
switch(a){
case LOGISTIC:
return "logistic";
case LOGGY:
return "loggy";
case RELU:
return "relu";
case ELU:
return "elu";
case RELIE:
return "relie";
case RAMP:
return "ramp";
case LINEAR:
return "linear";
case TANH:
return "tanh";
case PLSE:
return "plse";
case LEAKY:
return "leaky";
case STAIR:
return "stair";
case HARDTAN:
return "hardtan";
case LHTAN:
return "lhtan";
default:
break;
}
return "relu";
}
ACTIVATION get_activation(char *s)
{
if (strcmp(s, "logistic")==0) return LOGISTIC;
if (strcmp(s, "loggy")==0) return LOGGY;
if (strcmp(s, "relu")==0) return RELU;
if (strcmp(s, "elu")==0) return ELU;
if (strcmp(s, "relie")==0) return RELIE;
if (strcmp(s, "plse")==0) return PLSE;
if (strcmp(s, "hardtan")==0) return HARDTAN;
if (strcmp(s, "lhtan")==0) return LHTAN;
if (strcmp(s, "linear")==0) return LINEAR;
if (strcmp(s, "ramp")==0) return RAMP;
if (strcmp(s, "leaky")==0) return LEAKY;
if (strcmp(s, "tanh")==0) return TANH;
if (strcmp(s, "stair")==0) return STAIR;
fprintf(stderr, "Couldn't find activation function %s, going with ReLU\n", s);
return RELU;
}
float activate(float x, ACTIVATION a)
{
switch(a){
case LINEAR:
return linear_activate(x);
case LOGISTIC:
return logistic_activate(x);
case LOGGY:
return loggy_activate(x);
case RELU:
return relu_activate(x);
case ELU:
return elu_activate(x);
case RELIE:
return relie_activate(x);
case RAMP:
return ramp_activate(x);
case LEAKY:
return leaky_activate(x);
case TANH:
return tanh_activate(x);
case PLSE:
return plse_activate(x);
case STAIR:
return stair_activate(x);
case HARDTAN:
return hardtan_activate(x);
case LHTAN:
return lhtan_activate(x);
}
return 0;
}
void activate_array(float *x, const int n, const ACTIVATION a)
{
int i;
for(i = 0; i < n; ++i){
x[i] = activate(x[i], a);
}
}
float gradient(float x, ACTIVATION a)
{
switch(a){
case LINEAR:
return linear_gradient(x);
case LOGISTIC:
return logistic_gradient(x);
case LOGGY:
return loggy_gradient(x);
case RELU:
return relu_gradient(x);
case ELU:
return elu_gradient(x);
case RELIE:
return relie_gradient(x);
case RAMP:
return ramp_gradient(x);
case LEAKY:
return leaky_gradient(x);
case TANH:
return tanh_gradient(x);
case PLSE:
return plse_gradient(x);
case STAIR:
return stair_gradient(x);
case HARDTAN:
return hardtan_gradient(x);
case LHTAN:
return lhtan_gradient(x);
}
return 0;
}
///////////////////activation end
void copy_cpu(int N, float *X, int INCX, float *Y, int INCY)
{
int i;
for(i = 0; i < N; ++i) Y[i*INCY] = X[i*INCX];
}
void fill_cpu(int N, float ALPHA, float *X, int INCX)
{
int i;
for(i = 0; i < N; ++i) X[i*INCX] = ALPHA;
}
void shortcut_cpu(int batch, int w1, int h1, int c1, float *add, int w2, int h2, int c2, float s1, float s2, float *out)
{
int stride = w1/w2;
int sample = w2/w1;
assert(stride == h1/h2);
assert(sample == h2/h1);
//printf("shorcut_layer batch=%d,stride=%d,sample=%d\n",batch,stride,sample);
if(stride < 1) stride = 1;
if(sample < 1) sample = 1;
int minw = (w1 < w2) ? w1 : w2;
int minh = (h1 < h2) ? h1 : h2;
int minc = (c1 < c2) ? c1 : c2;
int i,j,k,b;
for(b = 0; b < batch; ++b){
for(k = 0; k < minc; ++k){
for(j = 0; j < minh; ++j){
for(i = 0; i < minw; ++i){
int out_index = i*sample + w2*(j*sample + h2*(k + c2*b));
int add_index = i*stride + w1*(j*stride + h1*(k + c1*b));
out[out_index] = s1*out[out_index] + s2*add[add_index];
}
}
}
}
}
void forward_shortcut_layer(const layer l, network net)
{
//copy_cpu(l.outputs*l.batch, net.input, 1, l.output, 1);
//shortcut_cpu(l.batch, l.w, l.h, l.c, net.layers[l.index].output, l.out_w, l.out_h, l.out_c, l.alpha, l.beta, l.output);
//activate_array(l.output, l.outputs*l.batch, l.activation);
int w = l.w;
int h = l.h;
int c = l.c;
float *add = net.layers[l.index].output;
float *out = l.output;
float *in = net.input;
int i,j,k;
for(k = 0; k < c; ++k){
for(j = 0; j < h; ++j){
for(i = 0; i < w; ++i){
int index = i + w*(j + h*k );
out[index] = in[index] + add[index];
}
}
}
}
layer make_shortcut_layer(int batch, int index, int w, int h, int c, int w2, int h2, int c2)
{
fprintf(stderr, "res %3d %4d x%4d x%4d -> %4d x%4d x%4d\n",index, w2,h2,c2, w,h,c);
layer l;
memset(&l,0,sizeof(layer));
l.type = SHORTCUT;
l.batch = batch;
l.w = w2;
l.h = h2;
l.c = c2;
l.out_w = w;
l.out_h = h;
l.out_c = c;
l.outputs = w*h*c;
l.inputs = l.outputs;
l.index = index;
l.output = (float *)calloc(l.outputs*batch, sizeof(float));;
l.forward = forward_shortcut_layer;
return l;
}
int convolutional_out_height(layer l)
{
return (l.h + 2*l.pad - l.size) / l.stride + 1;
}
int convolutional_out_width(layer l)
{
return (l.w + 2*l.pad - l.size) / l.stride + 1;
}
static size_t get_workspace_size(layer l){
return (size_t)l.out_h*l.out_w*l.size*l.size*l.c/l.groups*sizeof(float);
}
void add_bias(float *output, float *biases, int batch, int n, int size)
{
int i,j,b;
for(b = 0; b < batch; ++b){
for(i = 0; i < n; ++i){
for(j = 0; j < size; ++j){
output[(b*n + i)*size + j] += biases[i];
}
}
}
}
void scale_bias(float *output, float *scales, int batch, int n, int size)
{
int i,j,b;
for(b = 0; b < batch; ++b){
for(i = 0; i < n; ++i){
for(j = 0; j < size; ++j){
output[(b*n + i)*size + j] *= scales[i];
}
}
}
}
float im2col_get_pixel(float *im, int height, int width, int channels,
int row, int col, int channel, int pad)
{
row -= pad;
col -= pad;
if (row < 0 || col < 0 ||
row >= height || col >= width) return 0;
return im[col + width*(row + height*channel)];
}
//From Berkeley Vision's Caffe!
//https://github.com/BVLC/caffe/blob/master/LICENSE
void im2col_cpu(float* data_im,
int channels, int height, int width,
int ksize, int stride, int pad, float* data_col)
{
int c,h,w;
int height_col = (height + 2*pad - ksize) / stride + 1;
int width_col = (width + 2*pad - ksize) / stride + 1;
int channels_col = channels * ksize * ksize;
for (c = 0; c < channels_col; ++c) {
int w_offset = c % ksize;
int h_offset = (c / ksize) % ksize;
int c_im = c / ksize / ksize;
for (h = 0; h < height_col; ++h) {
for (w = 0; w < width_col; ++w) {
int im_row = h_offset + h * stride;
int im_col = w_offset + w * stride;
int col_index = (c * height_col + h) * width_col + w;
data_col[col_index] = im2col_get_pixel(data_im, height, width, channels,
im_row, im_col, c_im, pad);
}
}
}
}
void gemm_nn(int M, int N, int K, float ALPHA,
float *A, int lda,
float *B, int ldb,
float *C, int ldc)
{
int i,j,k;
#pragma omp parallel for
for(i = 0; i < M; ++i){
for(k = 0; k < K; ++k){
register float A_PART = ALPHA*A[i*lda+k];
for(j = 0; j < N; ++j){
C[i*ldc+j] += A_PART*B[k*ldb+j];
}
}
}
}
void gemm_cpu(int TA, int TB, int M, int N, int K, float ALPHA,
float *A, int lda,
float *B, int ldb,
float BETA,
float *C, int ldc)
{
//printf("cpu: %d %d %d %d %d %f %d %d %f %d\n",TA, TB, M, N, K, ALPHA, lda, ldb, BETA, ldc);
int i, j;
for(i = 0; i < M; ++i){
for(j = 0; j < N; ++j){
C[i*ldc + j] *= BETA;
}
}
if(!TA && !TB)
gemm_nn(M, N, K, ALPHA,A,lda, B, ldb,C,ldc);
//else if(TA && !TB)
// gemm_tn(M, N, K, ALPHA,A,lda, B, ldb,C,ldc);
//else if(!TA && TB)
// gemm_nt(M, N, K, ALPHA,A,lda, B, ldb,C,ldc);
//else
// gemm_tt(M, N, K, ALPHA,A,lda, B, ldb,C,ldc);
}
void gemm(int TA, int TB, int M, int N, int K, float ALPHA,
float *A, int lda,
float *B, int ldb,
float BETA,
float *C, int ldc)
{
gemm_cpu( TA, TB, M, N, K, ALPHA,A,lda, B, ldb,BETA,C,ldc);
}
void normalize_cpu(float *x, float *mean, float *variance, int batch, int filters, int spatial)
{
int b, f, i;
for(b = 0; b < batch; ++b){
for(f = 0; f < filters; ++f){
for(i = 0; i < spatial; ++i){
int index = b*filters*spatial + f*spatial + i;
x[index] = (x[index] - mean[f])/(sqrt(variance[f]) + .000001f);
}
}
}
}
void forward_batchnorm_layer(layer l, network net)//for conv
{
normalize_cpu(l.output, l.rolling_mean, l.rolling_variance, l.batch, l.out_c, l.out_h*l.out_w);
scale_bias(l.output, l.scales, l.batch, l.out_c, l.out_h*l.out_w);
add_bias(l.output, l.biases, l.batch, l.out_c, l.out_h*l.out_w);
}
void CONV_Padding_Relu(float *Input,float *Output,float *Weight,const int InFM_num,const int OutFM_num,const int Kernel_size,const int Kernel_stride,const int Input_w,const int Input_h,const int Padding)
{
// (output_w - 1)*Kernel_stride + Kernel_size = Input_w
const int output_w = (Input_w - Kernel_size + 2*Padding)/Kernel_stride + 1 ;
const int output_h = (Input_h - Kernel_size + 2*Padding)/Kernel_stride + 1 ;
int x, y, of, inf;
int m,n;
for( of = 0; of < OutFM_num; of++){
for( y = 0; y < output_h; y++) {
for( x = 0; x < output_w; x++){
float tmp = 0.0;
for(inf = 0;inf < InFM_num; inf++)
{
int intput_offset = inf*Input_w*Input_h + (y*Kernel_stride - Padding)*Input_w + x*Kernel_stride - Padding;
for(m = 0;m < Kernel_size; m++)
{
for(n = 0;n < Kernel_size; n++)
{
int kernel_offset = of*InFM_num*Kernel_size*Kernel_size + inf*Kernel_size*Kernel_size;
bool inFM_width = ((x*Kernel_stride + n - Padding) >= 0)&&((x*Kernel_stride + n - Padding) < Input_w);
bool inFM_height = ((y*Kernel_stride + m - Padding) >= 0)&&((y*Kernel_stride + m - Padding) < Input_h);
if(inFM_width&&inFM_height)
tmp += Weight[kernel_offset + m*Kernel_size + n]*Input[intput_offset + m*Input_w + n];
}
}
}
Output[of*output_w*output_h + y*output_w + x] = tmp;
}
}
}
}
layer make_convolutional_layer(int batch, int h, int w, int c, int n, int groups, int size, int stride, int padding, ACTIVATION activation, int batch_normalize, int binary, int xnor, int adam)
{
int i;
layer l;
memset(&l,0,sizeof(layer));
l.type = CONVOLUTIONAL;
l.groups = groups;
l.h = h;
l.w = w;
l.c = c;
l.n = n;
l.binary = binary;
l.xnor = xnor;
l.batch = batch;
l.stride = stride;
l.size = size;
l.pad = padding;
l.batch_normalize = batch_normalize;
// l.weights = (float *)calloc(c/groups*n*size*size, sizeof(float));
// l.biases = (float *)calloc(n, sizeof(float));
l.nweights = c/groups*n*size*size;
l.nbiases = n;
int out_w = convolutional_out_width(l);
int out_h = convolutional_out_height(l);
l.out_h = out_h;
l.out_w = out_w;
l.out_c = n;
l.outputs = l.out_h * l.out_w * l.out_c;
l.inputs = l.w * l.h * l.c;
// l.output = (float *)calloc(l.batch*l.outputs, sizeof(float));
// l.forward = forward_convolutional_layer;
if(batch_normalize){
// l.scales = (float *)calloc(n, sizeof(float));
// l.rolling_mean = (float *)calloc(n, sizeof(float));
//l.rolling_variance = (float *)calloc(n, sizeof(float));
}
l.workspace_size = get_workspace_size(l);
l.activation = activation;
fprintf(stderr, "conv %5d %2d x%2d /%2d %4d x%4d x%4d -> %4d x%4d x%4d %5.3f BFLOPs\n", n, size, size, stride, w, h, c, l.out_w, l.out_h, l.out_c, (2.0 * l.n * l.size*l.size*l.c/l.groups * l.out_h*l.out_w)/1000000000.);
return l;
}
void upsample_cpu(float *in, int w, int h, int c, int batch, int stride, int forward, float scale, float *out)
{
int i, j, k, b;
for(b = 0; b < batch; ++b){
for(k = 0; k < c; ++k){
for(j = 0; j < h*stride; ++j){
for(i = 0; i < w*stride; ++i){
int in_index = b*w*h*c + k*w*h + (j/stride)*w + i/stride;
int out_index = b*w*h*c*stride*stride + k*w*h*stride*stride + j*w*stride + i;
if(forward) out[out_index] = scale*in[in_index];
else in[in_index] += scale*out[out_index];
}
}
}
}
}
void forward_upsample_layer(const layer l, network net)
{
//fill_cpu(l.outputs*l.batch, 0, l.output, 1);
//upsample_cpu(net.input, l.w, l.h, l.c, l.batch, l.stride, 1, l.scale, l.output);
int c = l.c;
int h = l.h;
int w = l.w;
int stride = l.stride;
float *in = net.input;
float *out = l.output;
int i, j, k;
for(k = 0; k < c; ++k){
for(j = 0; j < h*stride; ++j){
for(i = 0; i < w*stride; ++i){
int in_index = k*w*h + (j/stride)*w + i/stride;
int out_index = k*w*h*stride*stride + j*w*stride + i;
out[out_index] = in[in_index];
}
}
}
}
layer make_upsample_layer(int batch, int w, int h, int c, int stride)
{
layer l;
memset(&l,0,sizeof(layer));
l.type = UPSAMPLE;
l.batch = batch;
l.w = w;
l.h = h;
l.c = c;
l.out_w = w*stride;
l.out_h = h*stride;
l.out_c = c;
if(stride < 0){
stride = -stride;
l.reverse=1;
l.out_w = w/stride;
l.out_h = h/stride;
}
l.stride = stride;
l.outputs = l.out_w*l.out_h*l.out_c;
l.inputs = l.w*l.h*l.c;
l.output = (float *)calloc(l.outputs*batch, sizeof(float));;
l.forward = forward_upsample_layer;
if(l.reverse) fprintf(stderr, "downsample %2dx %4d x%4d x%4d -> %4d x%4d x%4d\n", stride, w, h, c, l.out_w, l.out_h, l.out_c);
else fprintf(stderr, "upsample %2dx %4d x%4d x%4d -> %4d x%4d x%4d\n", stride, w, h, c, l.out_w, l.out_h, l.out_c);
return l;
}
void forward_route_layer(const layer l, network net)
{
int i, j;
int offset = 0;
for(i = 0; i < l.n; ++i){
int index = l.input_layers[i];
float *input = net.layers[index].output;
int input_size = l.input_sizes[i];
copy_cpu(input_size, input, 1, l.output + offset, 1);
offset += input_size;
}
}
layer make_route_layer(int batch, int n, int *input_layers, int *input_sizes)
{
fprintf(stderr,"route ");
layer l;
memset(&l,0,sizeof(layer));
l.type = ROUTE;
l.batch = batch;
l.n = n;
l.input_layers = input_layers;
l.input_sizes = input_sizes;
int i;
int outputs = 0;
for(i = 0; i < n; ++i){
fprintf(stderr," %d", input_layers[i]);
outputs += input_sizes[i];
}
fprintf(stderr, "\n");
l.outputs = outputs;
l.inputs = outputs;
// l.output = (float *)calloc(outputs*batch, sizeof(float));;
l.forward = forward_route_layer;
return l;
}
static int entry_index(layer l, int batch, int location, int entry)
{
int n = location / (l.w*l.h);
int loc = location % (l.w*l.h);
return batch*l.outputs + n*l.w*l.h*(4+l.classes+1) + entry*l.w*l.h + loc;
}
void forward_yolo_layer(const layer l, network net)
{
int i,j,b,t,n;
//char line[256];
//FILE *fp3;
//char filename[256];
//sprintf(filename, "yolo_layer_%d.txt", l.outputs);
//printf("YOLO_layer:outputs=%d,%s\n",l.outputs,filename);
// if( (fp3 = fopen(filename, "w")) == NULL)fprintf(stderr,"CANNOT OPEN\n");
//int x;
// for( x = 0; x < l.outputs; x++)
//{
// sprintf(line, "%f\n", net.input[x]);
// if(fputs(line,fp3)<0)fprintf(stderr,"write FILE failed\n");
// }
// fclose(fp3);
memcpy(l.output, net.input, l.outputs*l.batch*sizeof(float));
for (b = 0; b < l.batch; ++b){
for(n = 0; n < l.n; ++n){
int index = entry_index(l, b, n*l.w*l.h, 0);
activate_array(l.output + index, 2*l.w*l.h, LOGISTIC);
index = entry_index(l, b, n*l.w*l.h, 4);
activate_array(l.output + index, (1+l.classes)*l.w*l.h, LOGISTIC);
}
}
return ;
}
layer make_yolo_layer(int batch, int w, int h, int n, int total, int *mask, int classes)
{
int i;
layer l;
memset(&l,0,sizeof(layer));
l.type = YOLO;
l.n = n;
l.total = total;
l.batch = batch;
l.h = h;
l.w = w;
l.c = n*(classes + 4 + 1);
l.out_w = l.w;
l.out_h = l.h;
l.out_c = l.c;
l.classes = classes;
//l.cost = (float *)calloc(1, sizeof(float));
l.biases = (float *)calloc(total*2, sizeof(float));
if(mask) l.mask = mask;
else{
l.mask = (int *)calloc(n, sizeof(int));
for(i = 0; i < n; ++i){
l.mask[i] = i;
}
}
//l.bias_updates = (float *)calloc(n*2, sizeof(float));
l.outputs = h*w*n*(classes + 4 + 1);
l.inputs = l.outputs;
//l.truths = 90*(4 + 1);
//l.delta = (float *)calloc(batch*l.outputs, sizeof(float));
l.output = (float *)calloc(batch*l.outputs, sizeof(float));
for(i = 0; i < total*2; ++i){
l.biases[i] = .5;
}
l.forward = forward_yolo_layer;
fprintf(stderr, "detection\n");
srand(0);
return l;
}
/////////////////praser begin
typedef struct{
char *type;
list *options;
}section;
list *read_cfg(char *filename);
LAYER_TYPE string_to_layer_type(char * type)
{
if (strcmp(type, "[shortcut]")==0) return SHORTCUT;
if (strcmp(type, "[crop]")==0) return CROP;
if (strcmp(type, "[cost]")==0) return COST;
if (strcmp(type, "[detection]")==0) return DETECTION;
if (strcmp(type, "[region]")==0) return REGION;
if (strcmp(type, "[yolo]")==0) return YOLO;
if (strcmp(type, "[local]")==0) return LOCAL;
if (strcmp(type, "[conv]")==0
|| strcmp(type, "[convolutional]")==0) return CONVOLUTIONAL;
if (strcmp(type, "[deconv]")==0
|| strcmp(type, "[deconvolutional]")==0) return DECONVOLUTIONAL;
if (strcmp(type, "[activation]")==0) return ACTIVE;
if (strcmp(type, "[logistic]")==0) return LOGXENT;
if (strcmp(type, "[l2norm]")==0) return L2NORM;
if (strcmp(type, "[net]")==0
|| strcmp(type, "[network]")==0) return NETWORK;
if (strcmp(type, "[crnn]")==0) return CRNN;
if (strcmp(type, "[gru]")==0) return GRU;
if (strcmp(type, "[lstm]") == 0) return LSTM;
if (strcmp(type, "[rnn]")==0) return RNN;
if (strcmp(type, "[conn]")==0
|| strcmp(type, "[connected]")==0) return CONNECTED;
if (strcmp(type, "[max]")==0
|| strcmp(type, "[maxpool]")==0) return MAXPOOL;
if (strcmp(type, "[reorg]")==0) return REORG;
if (strcmp(type, "[avg]")==0
|| strcmp(type, "[avgpool]")==0) return AVGPOOL;
if (strcmp(type, "[dropout]")==0) return DROPOUT;
if (strcmp(type, "[lrn]")==0
|| strcmp(type, "[normalization]")==0) return NORMALIZATION;
if (strcmp(type, "[batchnorm]")==0) return BATCHNORM;
if (strcmp(type, "[soft]")==0
|| strcmp(type, "[softmax]")==0) return SOFTMAX;
if (strcmp(type, "[route]")==0) return ROUTE;
if (strcmp(type, "[upsample]")==0) return UPSAMPLE;
return BLANK;
}
void free_section(section *s)
{
free(s->type);
node *n = s->options->front;
while(n){
kvp *pair = (kvp *)n->val;
free(pair->key);
free(pair);
node *next = n->next;
free(n);
n = next;
}
free(s->options);
free(s);
}
void parse_data(char *data, float *a, int n)
{
int i;
if(!data) return;
char *curr = data;
char *next = data;
int done = 0;
for(i = 0; i < n && !done; ++i){
while(*++next !='\0' && *next != ',');
if(*next == '\0') done = 1;
*next = '\0';
sscanf(curr, "%g", &a[i]);
curr = next+1;
}
}
typedef struct size_params{
int batch;
int inputs;
int h;
int w;
int c;
int index;
int time_steps;
network *net;
} size_params;
layer parse_convolutional(list *options, size_params params)
{
int n = option_find_int(options, "filters",1);
int size = option_find_int(options, "size",1);
int stride = option_find_int(options, "stride",1);
int pad = option_find_int_quiet(options, "pad",0);
int padding = option_find_int_quiet(options, "padding",0);
int groups = option_find_int_quiet(options, "groups", 1);
if(pad) padding = size/2;
char *activation_s = option_find_str(options, "activation", "logistic");
ACTIVATION activation = get_activation(activation_s);
int batch,h,w,c;
h = params.h;
w = params.w;
c = params.c;
batch=params.batch;
if(!(h && w && c)) error("Layer before convolutional layer must output image.");
int batch_normalize = option_find_int_quiet(options, "batch_normalize", 0);
int binary = option_find_int_quiet(options, "binary", 0);
int xnor = option_find_int_quiet(options, "xnor", 0);
layer l = make_convolutional_layer(batch,h,w,c,n,groups,size,stride,padding,activation, batch_normalize, binary, xnor, params.net->adam);
l.flipped = option_find_int_quiet(options, "flipped", 0);
l.dot = option_find_float_quiet(options, "dot", 0);
return l;
}
int *parse_yolo_mask(char *a, int *num)
{
int *mask = 0;
if(a){
int len = strlen(a);
int n = 1;
int i;
for(i = 0; i < len; ++i){
if (a[i] == ',') ++n;
}
mask = (int *)calloc(n, sizeof(int));
for(i = 0; i < n; ++i){
int val = atoi(a);
mask[i] = val;
a = strchr(a, ',')+1;
}
*num = n;
}
return mask;
}
layer parse_yolo(list *options, size_params params)
{
int classes = option_find_int(options, "classes", 20);
int total = option_find_int(options, "num", 1);
int num = total;
char *a = option_find_str(options, "mask", 0);
int *mask = parse_yolo_mask(a, &num);
layer l = make_yolo_layer(params.batch, params.w, params.h, num, total, mask, classes);
assert(l.outputs == params.inputs);
l.max_boxes = option_find_int_quiet(options, "max",90);
l.jitter = option_find_float(options, "jitter", .2);
l.ignore_thresh = option_find_float(options, "ignore_thresh", .5);
l.truth_thresh = option_find_float(options, "truth_thresh", 1);
l.random = option_find_int_quiet(options, "random", 0);
a = option_find_str(options, "anchors", 0);
if(a){
int len = strlen(a);
int n = 1;
int i;
for(i = 0; i < len; ++i){
if (a[i] == ',') ++n;
}
for(i = 0; i < n; ++i){
float bias = atof(a);
l.biases[i] = bias;
a = strchr(a, ',')+1;
}
}
return l;
}
layer parse_shortcut(list *options, size_params params, network *net)
{
char *l = option_find(options, "from");
int index = atoi(l);
if(index < 0) index = params.index + index;
int batch = params.batch;
layer from = net->layers[index];
layer s = make_shortcut_layer(batch, index, params.w, params.h, params.c, from.out_w, from.out_h, from.out_c);
char *activation_s = option_find_str(options, "activation", "linear");
ACTIVATION activation = get_activation(activation_s);
s.activation = activation;
s.alpha = option_find_float_quiet(options, "alpha", 1);
s.beta = option_find_float_quiet(options, "beta", 1);
return s;
}
layer parse_upsample(list *options, size_params params, network *net)
{
int stride = option_find_int(options, "stride",2);
layer l = make_upsample_layer(params.batch, params.w, params.h, params.c, stride);
l.scale = option_find_float_quiet(options, "scale", 1);
return l;
}
layer parse_route(list *options, size_params params, network *net)
{
char *l = option_find(options, "layers");
int len = strlen(l);
if(!l) error("Route Layer must specify input layers");
int n = 1;
int i;
for(i = 0; i < len; ++i){
if (l[i] == ',') ++n;
}
int *layers = (int *)calloc(n, sizeof(int));
int *sizes = (int *)calloc(n, sizeof(int));
for(i = 0; i < n; ++i){
int index = atoi(l);
l = strchr(l, ',')+1;
if(index < 0) index = params.index + index;
layers[i] = index;
sizes[i] = net->layers[index].outputs;
}
int batch = params.batch;
layer route_layer = make_route_layer(batch, n, layers, sizes);
layer first = net->layers[layers[0]];
route_layer.out_w = first.out_w;
route_layer.out_h = first.out_h;
route_layer.out_c = first.out_c;
for(i = 1; i < n; ++i){
int index = layers[i];
layer next = net->layers[index];
if(next.out_w == first.out_w && next.out_h == first.out_h){
route_layer.out_c += next.out_c;
}else{
route_layer.out_h = route_layer.out_w = route_layer.out_c = 0;
}
}
return route_layer;
}
void softmax(float *input, int n, float temp, int stride, float *output)
{
int i;
float sum = 0;
float largest = -FLT_MAX;
for(i = 0; i < n; ++i){
if(input[i*stride] > largest) largest = input[i*stride];
}
for(i = 0; i < n; ++i){
float e = exp(input[i*stride]/temp - largest/temp);
sum += e;
output[i*stride] = e;
}
for(i = 0; i < n; ++i){
output[i*stride] /= sum;
}
}
void softmax_cpu(float *input, int n, int batch, int batch_offset, int groups, int group_offset, int stride, float temp, float *output)
{
int g, b;
for(b = 0; b < batch; ++b){
for(g = 0; g < groups; ++g){
softmax(input + b*batch_offset + g*group_offset, n, temp, stride, output + b*batch_offset + g*group_offset);
}
}
}
void forward_region_layer(const layer l, network net)
{
int i,j,b,t,n;
memcpy(l.output, net.input, l.outputs*l.batch*sizeof(float));
#ifndef GPU
for (b = 0; b < l.batch; ++b){
for(n = 0; n < l.n; ++n){
int index = entry_index(l, b, n*l.w*l.h, 0);
activate_array(l.output + index, 2*l.w*l.h, LOGISTIC);
index = entry_index(l, b, n*l.w*l.h, l.coords);
if(!l.background) activate_array(l.output + index, l.w*l.h, LOGISTIC);
index = entry_index(l, b, n*l.w*l.h, l.coords + 1);
//if(!l.softmax) activate_array(l.output + index, l.classes*l.w*l.h, LOGISTIC);
}
}
if (l.softmax){
int index = entry_index(l, 0, 0, l.coords + !l.background);
softmax_cpu(net.input + index, l.classes + l.background, l.batch*l.n, l.inputs/l.n, l.w*l.h, 1, l.w*l.h, 1, l.output + index);
}
char line[256];
FILE *fp3;
char filename[256];
sprintf(filename, "yolo_layer_%d.txt", 123123);
printf("YOLO_layer:outputs=%d,%s\n",l.outputs,filename);
if( (fp3 = fopen(filename, "w")) == NULL)fprintf(stderr,"CANNOT OPEN\n");
int x;
for( x = 0; x < l.outputs; x++)
{
sprintf(line, "%f\n", net.input[x]);
if(fputs(line,fp3)<0)fprintf(stderr,"write FILE failed\n");
}
fclose(fp3);
#endif
if(!net.train) return;
}
layer make_region_layer(int batch, int w, int h, int n, int classes, int coords)
{
layer l;
memset(&l,0,sizeof(layer));
l.type = REGION;
l.n = n;
l.batch = batch;
l.h = h;
l.w = w;
l.c = n*(classes + coords + 1);
l.out_w = l.w;
l.out_h = l.h;
l.out_c = l.c;
l.classes = classes;
l.coords = coords;
l.biases = (float *)calloc(n*2, sizeof(float));
l.outputs = h*w*n*(classes + coords + 1);
l.inputs = l.outputs;
l.truths = 30*(l.coords + 1);
l.output = (float *)calloc(batch*l.outputs, sizeof(float));
int i;
for(i = 0; i < n*2; ++i){
l.biases[i] = .5;
}
l.forward = forward_region_layer;
fprintf(stderr, "detection\n");
srand(0);
return l;
}
layer parse_region(list *options, size_params params)
{
int coords = option_find_int(options, "coords", 4);
int classes = option_find_int(options, "classes", 20);
int num = option_find_int(options, "num", 1);
layer l = make_region_layer(params.batch, params.w, params.h, num, classes, coords);
assert(l.outputs == params.inputs);
l.log = option_find_int_quiet(options, "log", 0);
l.sqrt = option_find_int_quiet(options, "sqrt", 0);
l.softmax = option_find_int(options, "softmax", 0);
l.background = option_find_int_quiet(options, "background", 0);
l.max_boxes = option_find_int_quiet(options, "max",30);
l.jitter = option_find_float(options, "jitter", .2);
l.rescore = option_find_int_quiet(options, "rescore",0);
l.thresh = option_find_float(options, "thresh", .5);
l.classfix = option_find_int_quiet(options, "classfix", 0);
l.absolute = option_find_int_quiet(options, "absolute", 0);
l.random = option_find_int_quiet(options, "random", 0);
l.coord_scale = option_find_float(options, "coord_scale", 1);
l.object_scale = option_find_float(options, "object_scale", 1);
l.noobject_scale = option_find_float(options, "noobject_scale", 1);
l.mask_scale = option_find_float(options, "mask_scale", 1);
l.class_scale = option_find_float(options, "class_scale", 1);
l.bias_match = option_find_int_quiet(options, "bias_match",0);
char *tree_file = option_find_str(options, "tree", 0);
// if (tree_file) l.softmax_tree = read_tree(tree_file);
char *map_file = option_find_str(options, "map", 0);
// if (map_file) l.map = read_map(map_file);
char *a = option_find_str(options, "anchors", 0);
if(a){
int len = strlen(a);
int n = 1;
int i;
for(i = 0; i < len; ++i){
if (a[i] == ',') ++n;
}
for(i = 0; i < n; ++i){
float bias = atof(a);
l.biases[i] = bias;
a = strchr(a, ',')+1;
}
}
return l;
}
void reorg_cpu(float *x, int w, int h, int c, int batch, int stride, int forward, float *out)
{
int b,i,j,k;
int out_c = c/(stride*stride);
for(b = 0; b < batch; ++b){
for(k = 0; k < c; ++k){
for(j = 0; j < h; ++j){
for(i = 0; i < w; ++i){
int in_index = i + w*(j + h*(k + c*b));
int c2 = k % out_c;
int offset = k / out_c;
int w2 = i*stride + offset % stride;
int h2 = j*stride + offset / stride;
int out_index = w2 + w*stride*(h2 + h*stride*(c2 + out_c*b));
if(forward) out[out_index] = x[in_index];
else out[in_index] = x[out_index];
}
}
}
}
}
void forward_reorg_layer(const layer l, network net)
{
int i;
//if(l.flatten){
// memcpy(l.output, net.input, l.outputs*l.batch*sizeof(float));
// if(l.reverse){
// flatten(l.output, l.w*l.h, l.c, l.batch, 0);
// }else{
// flatten(l.output, l.w*l.h, l.c, l.batch, 1);
// }
//} else if (l.extra) {
// for(i = 0; i < l.batch; ++i){
// copy_cpu(l.inputs, net.input + i*l.inputs, 1, l.output + i*l.outputs, 1);
// }
//} else if (l.reverse){
// reorg_cpu(net.input, l.w, l.h, l.c, l.batch, l.stride, 1, l.output);
//} else {
reorg_cpu(net.input, l.w, l.h, l.c, l.batch, l.stride, 0, l.output);
//}
}
layer make_reorg_layer(int batch, int w, int h, int c, int stride, int reverse, int flatten, int extra)
{
layer l;
memset(&l,0,sizeof(layer));
l.type = REORG;
l.batch = batch;
l.stride = stride;
l.extra = extra;
l.h = h;
l.w = w;
l.c = c;
l.flatten = flatten;
if(reverse){
l.out_w = w*stride;
l.out_h = h*stride;
l.out_c = c/(stride*stride);
}else{
l.out_w = w/stride;
l.out_h = h/stride;
l.out_c = c*(stride*stride);
}
l.reverse = reverse;
l.outputs = l.out_h * l.out_w * l.out_c;
l.inputs = h*w*c;
if(l.extra){
l.out_w = l.out_h = l.out_c = 0;
l.outputs = l.inputs + l.extra;
}
if(extra){
fprintf(stderr, "reorg %4d -> %4d\n", l.inputs, l.outputs);
} else {
fprintf(stderr, "reorg /%2d %4d x%4d x%4d -> %4d x%4d x%4d\n", stride, w, h, c, l.out_w, l.out_h, l.out_c);
}
int output_size = l.outputs * batch;
//l.output = (float *)calloc(output_size, sizeof(float));
l.forward = forward_reorg_layer;
return l;
}
layer parse_reorg(list *options, size_params params)
{
int stride = option_find_int(options, "stride",1);
int reverse = option_find_int_quiet(options, "reverse",0);
int flatten = option_find_int_quiet(options, "flatten",0);
int extra = option_find_int_quiet(options, "extra",0);
int batch,h,w,c;
h = params.h;
w = params.w;
c = params.c;
batch=params.batch;
if(!(h && w && c)) error("Layer before reorg layer must output image.");
layer layer = make_reorg_layer(batch,w,h,c,stride,reverse, flatten, extra);
return layer;
}
void forward_maxpool_layer(layer l, network net)
{
int b,i,j,k,m,n;
int w_offset = -l.pad;
int h_offset = -l.pad;
int h = l.out_h;
int w = l.out_w;
int c = l.c;
for(b = 0; b < l.batch; ++b){
for(k = 0; k < c; ++k){
for(i = 0; i < h; ++i){
for(j = 0; j < w; ++j){
int out_index = j + w*(i + h*(k + c*b));
float max = -FLT_MAX;
int max_i = -1;
for(n = 0; n < l.size; ++n){
for(m = 0; m < l.size; ++m){
int cur_h = h_offset + i*l.stride + n;
int cur_w = w_offset + j*l.stride + m;
int index = cur_w + l.w*(cur_h + l.h*(k + b*l.c));
int valid = (cur_h >= 0 && cur_h < l.h &&
cur_w >= 0 && cur_w < l.w);
float val = (valid != 0) ? net.input[index] : -FLT_MAX;
max_i = (val > max) ? index : max_i;
max = (val > max) ? val : max;
}
}
l.output[out_index] = max;
l.indexes[out_index] = max_i;
}
}
}
}
}
//layer make_maxpool_layer(int batch, int h, int w, int c, int size, int stride, int padding)
//{
// layer l;
// memset(&l,0,sizeof(layer));
// l.type = MAXPOOL;
// l.batch = batch;
// l.h = h;
// l.w = w;
// l.c = c;
// l.pad = padding;
// l.out_w = (w + 2*padding)/stride;
// l.out_h = (h + 2*padding)/stride;
// l.out_c = c;
// l.outputs = l.out_h * l.out_w * l.out_c;
// l.inputs = h*w*c;
// l.size = size;
// l.stride = stride;
// int output_size = l.out_h * l.out_w * l.out_c * batch;
// //l.indexes = (int *)calloc(output_size, sizeof(int));
// //l.output = (float *)calloc(output_size, sizeof(float));
// l.forward = forward_maxpool_layer;
//
// fprintf(stderr, "max %d x %d / %d %4d x%4d x%4d -> %4d x%4d x%4d\n", size, size, stride, w, h, c, l.out_w, l.out_h, l.out_c);
// return l;
//}
layer make_maxpool_layer(int batch, int h, int w, int c, int size, int stride, int padding)
{
layer l;
memset(&l,0,sizeof(layer));
l.type = MAXPOOL;
l.batch = batch;
l.h = h;
l.w = w;
l.c = c;
l.pad = padding;
l.out_w = (w + padding - size)/stride + 1;
l.out_h = (h + padding - size)/stride + 1;
l.out_c = c;
l.outputs = l.out_h * l.out_w * l.out_c;
l.inputs = h*w*c;
l.size = size;
l.stride = stride;
int output_size = l.out_h * l.out_w * l.out_c * batch;
//l.indexes = calloc(output_size, sizeof(int));
//l.output = calloc(output_size, sizeof(float));
//l.delta = calloc(output_size, sizeof(float));
l.forward = forward_maxpool_layer;
//l.backward = backward_maxpool_layer;
fprintf(stderr, "max %d x %d / %d %4d x%4d x%4d -> %4d x%4d x%4d\n", size, size, stride, w, h, c, l.out_w, l.out_h, l.out_c);
return l;
}
layer parse_maxpool(list *options, size_params params)
{
int stride = option_find_int(options, "stride",1);
int size = option_find_int(options, "size",stride);
int padding = option_find_int_quiet(options, "padding", size-1);
int batch,h,w,c;
h = params.h;
w = params.w;
c = params.c;
batch=params.batch;
if(!(h && w && c)) error("Layer before maxpool layer must output image.");
layer maxpool_layer = make_maxpool_layer(batch,h,w,c,size,stride,padding);
return maxpool_layer;
}
learning_rate_policy get_policy(char *s)
{
if (strcmp(s, "random")==0) return RANDOM;
if (strcmp(s, "poly")==0) return POLY;
if (strcmp(s, "constant")==0) return CONSTANT;
if (strcmp(s, "step")==0) return STEP;
if (strcmp(s, "exp")==0) return EXP;
if (strcmp(s, "sigmoid")==0) return SIG;
if (strcmp(s, "steps")==0) return STEPS;
fprintf(stderr, "Couldn't find policy %s, going with constant\n", s);
return CONSTANT;
}
void parse_net_options(list *options, network *net)
{
net->batch = option_find_int(options, "batch",1);
net->learning_rate = option_find_float(options, "learning_rate", .001);
net->momentum = option_find_float(options, "momentum", .9);
net->decay = option_find_float(options, "decay", .0001);
int subdivs = option_find_int(options, "subdivisions",1);
net->time_steps = option_find_int_quiet(options, "time_steps",1);
net->notruth = option_find_int_quiet(options, "notruth",0);
net->batch /= subdivs;
net->batch *= net->time_steps;
net->subdivisions = subdivs;
net->random = option_find_int_quiet(options, "random", 0);
net->adam = option_find_int_quiet(options, "adam", 0);
if(net->adam){
net->B1 = option_find_float(options, "B1", .9);
net->B2 = option_find_float(options, "B2", .999);
net->eps = option_find_float(options, "eps", .0000001);
}
net->h = option_find_int_quiet(options, "height",0);
net->w = option_find_int_quiet(options, "width",0);
net->c = option_find_int_quiet(options, "channels",0);
net->inputs = option_find_int_quiet(options, "inputs", net->h * net->w * net->c);
net->max_crop = option_find_int_quiet(options, "max_crop",net->w*2);
net->min_crop = option_find_int_quiet(options, "min_crop",net->w);
net->max_ratio = option_find_float_quiet(options, "max_ratio", (float) net->max_crop / net->w);
net->min_ratio = option_find_float_quiet(options, "min_ratio", (float) net->min_crop / net->w);
net->center = option_find_int_quiet(options, "center",0);
net->clip = option_find_float_quiet(options, "clip", 0);
net->angle = option_find_float_quiet(options, "angle", 0);
net->aspect = option_find_float_quiet(options, "aspect", 1);
net->saturation = option_find_float_quiet(options, "saturation", 1);
net->exposure = option_find_float_quiet(options, "exposure", 1);
net->hue = option_find_float_quiet(options, "hue", 0);
if(!net->inputs && !(net->h && net->w && net->c)) error("No input parameters supplied");
char *policy_s = option_find_str(options, "policy", "constant");
net->policy = get_policy(policy_s);
net->burn_in = option_find_int_quiet(options, "burn_in", 0);
net->power = option_find_float_quiet(options, "power", 4);
if(net->policy == STEP){
net->step = option_find_int(options, "step", 1);
net->scale = option_find_float(options, "scale", 1);
} else if (net->policy == STEPS){
char *l = option_find(options, "steps");
char *p = option_find(options, "scales");
if(!l || !p) error("STEPS policy must have steps and scales in cfg file");
int len = strlen(l);
int n = 1;
int i;
for(i = 0; i < len; ++i){
if (l[i] == ',') ++n;
}
int *steps = (int *)calloc(n, sizeof(int));
float *scales = (float *)calloc(n, sizeof(float));
for(i = 0; i < n; ++i){
int step = atoi(l);
float scale = atof(p);
l = strchr(l, ',')+1;
p = strchr(p, ',')+1;
steps[i] = step;
scales[i] = scale;
}
net->scales = scales;
net->steps = steps;
net->num_steps = n;
} else if (net->policy == EXP){
net->gamma = option_find_float(options, "gamma", 1);
} else if (net->policy == SIG){
net->gamma = option_find_float(options, "gamma", 1);
net->step = option_find_int(options, "step", 1);
} else if (net->policy == POLY || net->policy == RANDOM){
}
net->max_batches = option_find_int(options, "max_batches", 0);
}
int is_network(section *s)
{
return (strcmp(s->type, "[net]")==0
|| strcmp(s->type, "[network]")==0);
}
network *parse_network_cfg(char *filename)
{
list *sections = read_cfg(filename);
node *n = sections->front;
if(!n) error("Config file has no sections");
network *net = make_network(sections->size - 1);
net->gpu_index = -1;
size_params params;
section *s = (section *)n->val;
list *options = s->options;
if(!is_network(s)) error("First section must be [net] or [network]");
parse_net_options(options, net);
params.h = net->h;
params.w = net->w;
params.c = net->c;
params.inputs = net->inputs;
params.batch = net->batch;
params.time_steps = net->time_steps;
params.net = net;
size_t workspace_size = 0;
n = n->next;
int count = 0;
free_section(s);
fprintf(stderr, "layer filters size input output\n");
while(n){
params.index = count;
fprintf(stderr, "%5d ", count);
s = (section *)n->val;
options = s->options;
//layer l = {0};
layer l;
memset(&l,0,sizeof(layer));
LAYER_TYPE lt = string_to_layer_type(s->type);
if(lt == CONVOLUTIONAL){
l = parse_convolutional(options, params);
}else if(lt == YOLO){
l = parse_yolo(options, params);
}else if(lt == ROUTE){
l = parse_route(options, params, net);
}else if(lt == UPSAMPLE){
l = parse_upsample(options, params, net);
}else if(lt == SHORTCUT){
l = parse_shortcut(options, params, net);
}else if(lt == REGION){
l = parse_region(options, params);
}else if(lt == YOLO){
l = parse_yolo(options, params);
}else if(lt == MAXPOOL){
l = parse_maxpool(options, params);
}else if(lt == REORG){
l = parse_reorg(options, params);
}else{
fprintf(stderr, "Type not recognized: %s\n", s->type);
}
l.clip = net->clip;
l.truth = option_find_int_quiet(options, "truth", 0);
l.onlyforward = option_find_int_quiet(options, "onlyforward", 0);
l.stopbackward = option_find_int_quiet(options, "stopbackward", 0);
l.dontsave = option_find_int_quiet(options, "dontsave", 0);
// l.dontload = option_find_int_quiet(options, "dontload", 0);
// l.dontloadscales = option_find_int_quiet(options, "dontloadscales", 0);
//l.learning_rate_scale = option_find_float_quiet(options, "learning_rate", 1);
l.smooth = option_find_float_quiet(options, "smooth", 0);
option_unused(options);
net->layers[count] = l;
if (l.workspace_size > workspace_size) workspace_size = l.workspace_size;
free_section(s);
n = n->next;
++count;
if(n){
params.h = l.out_h;
params.w = l.out_w;
params.c = l.out_c;
params.inputs = l.outputs;
}
}
free_list(sections);
layer out = get_network_output_layer(net);
net->outputs = out.outputs;
net->output = out.output;
//net->input = (float *)calloc(net->inputs*net->batch, sizeof(float));
workspace_size = 0;//donot calloc workspace
//if(workspace_size){
// //printf("%ld\n", workspace_size);
// net->workspace = (float *)calloc(1, workspace_size);
//}
return net;
}
list *read_cfg(char *filename)
{
FILE *file = fopen(filename, "r");
if(file == 0) file_error(filename);
char *line;
int nu = 0;
list *options = make_list();
section *current = 0;
while((line=fgetl(file)) != 0){
++ nu;
strip(line);
switch(line[0]){
case '[':
current = (section *)malloc(sizeof(section));
list_insert(options, current);
current->options = make_list();
current->type = line;
break;
case '\0':
case '#':
case ';':
free(line);
break;
default:
if(!read_option(line, current->options)){
fprintf(stderr, "Config file error line %d, could parse: %s\n", nu, line);
free(line);
}
break;
}
}
fclose(file);
return options;
}
void load_convolutional_weights(layer l, FILE *fp)
{
int num = l.nweights;
fread(l.biases, sizeof(float), l.n, fp);
if (l.batch_normalize){
fread(l.scales, sizeof(float), l.n, fp);
fread(l.rolling_mean, sizeof(float), l.n, fp);
fread(l.rolling_variance, sizeof(float), l.n, fp);
}
fread(l.weights, sizeof(float), num, fp);
}
void load_weights_upto(network *net, char *filename, int start, int cutoff)
{
fprintf(stderr, "Loading weights from %s...", filename);
fflush(stdout);
FILE *fp = fopen(filename, "rb");
if(!fp) file_error(filename);
int major;
int minor;
int revision;
fread(&major, sizeof(int), 1, fp);
fread(&minor, sizeof(int), 1, fp);
fread(&revision, sizeof(int), 1, fp);
printf("major=%d;minor=%d;revision=%d\n",major,minor,revision);// 0 2 0
printf("if true ro false:%d\n",(major*10 + minor) >= 2 && major < 1000 && minor < 1000);
if ((major*10 + minor) >= 2 && major < 1000 && minor < 1000){
//fread(net->seen, sizeof(size_t), 1, fp);
fread(net->seen, sizeof(size_t), 1, fp);
fread(net->seen, sizeof(size_t), 1, fp);
}else {
int iseen = 0;
fread(&iseen, sizeof(int), 1, fp);
*net->seen = iseen;
}
//printf("sizeof(size_t)=%u\n",sizeof(size_t));// in my PC is 4
int i;
for(i = start; i < net->n && i < cutoff; ++i){
layer l = net->layers[i];
if(l.type == CONVOLUTIONAL){
load_convolutional_weights(l, fp);
}
}
fprintf(stderr, "Done!\n");
fclose(fp);
}
void load_weights(network *net, char *filename)
{
load_weights_upto(net, filename, 0, net->n);
}
/////////////////praser end
/////////////////network begin
load_args get_base_args(network *net)
{
load_args args = {0};
args.w = net->w;
args.h = net->h;
args.size = net->w;
args.min = net->min_crop;
args.max = net->max_crop;
args.angle = net->angle;
args.aspect = net->aspect;
args.exposure = net->exposure;
args.center = net->center;
args.saturation = net->saturation;
args.hue = net->hue;
return args;
}
network *load_network(char *cfg, char *weights, int clear)
{
network *net = parse_network_cfg(cfg);
//if(weights && weights[0] != 0){
// load_weights(net, weights);
//}
if(clear) (*net->seen) = 0;
return net;
}
char *get_layer_string(LAYER_TYPE a)
{
switch(a){
case CONVOLUTIONAL:
return "convolutional";
case ACTIVE:
return "activation";
case LOCAL:
return "local";
case DECONVOLUTIONAL:
return "deconvolutional";
case CONNECTED:
return "connected";
case RNN:
return "rnn";
case GRU:
return "gru";
case LSTM:
return "lstm";
case CRNN:
return "crnn";
case MAXPOOL:
return "maxpool";
case REORG:
return "reorg";
case AVGPOOL:
return "avgpool";
case SOFTMAX:
return "softmax";
case DETECTION:
return "detection";
case REGION:
return "region";
case YOLO:
return "yolo";
case DROPOUT:
return "dropout";
case CROP:
return "crop";
case COST:
return "cost";
case ROUTE:
return "route";
case SHORTCUT:
return "shortcut";
case NORMALIZATION:
return "normalization";
case BATCHNORM:
return "batchnorm";
default:
break;
}
return "none";
}
network *make_network(int n)
{
network *net = (network *)calloc(1, sizeof(network));
net->n = n;
net->layers = (layer *)calloc(net->n, sizeof(layer));
net->seen = (size_t *)calloc(1, sizeof(size_t));
net->t = (int *)calloc(1, sizeof(int));
net->cost = (float *)calloc(1, sizeof(float));
return net;
}
void forward_network(network *netp)
{
network net = *netp;
int i;
for(i = 0; i < net.n; ++i){
net.index = i;
layer l = net.layers[i];
l.forward(l, net);
net.input = l.output;
// printf("layer [%d]\n",i);
}
}
void set_temp_network(network *net, float t)
{
int i;
for(i = 0; i < net->n; ++i){
net->layers[i].temperature = t;
}
}
void set_batch_network(network *net, int b)
{
net->batch = b;
int i;
for(i = 0; i < net->n; ++i){
net->layers[i].batch = b;
}
}
float *network_predict(network *net, float *input)
{
network orig = *net;
net->input = input;
net->truth = 0;
net->train = 0;
net->delta = 0;
forward_network(net);
float *out = net->output;
*net = orig;
return out;
}
int yolo_num_detections(layer l, float thresh)
{
int i, n;
int count = 0;
for (i = 0; i < l.w*l.h; ++i){
for(n = 0; n < l.n; ++n){
int obj_index = entry_index(l, 0, n*l.w*l.h + i, 4);
if(l.output[obj_index] > thresh){
++count;
}
}
}
return count;
}
int num_detections(network *net, float thresh)
{
int i;
int s = 0;
for(i = 0; i < net->n; ++i){
layer l = net->layers[i];
if(l.type == YOLO){
s += yolo_num_detections(l, thresh);
}
if(l.type == DETECTION || l.type == REGION){
s += l.w*l.h*l.n;
}
}
return s;
}
detection *make_network_boxes(network *net, float thresh, int *num)
{
layer l = net->layers[net->n - 1];
int i;
int nboxes = num_detections(net, thresh);
//printf("num_detections nboxes = %d\n",nboxes);
if(num) *num = nboxes;
detection *dets = (detection *)calloc(nboxes, sizeof(detection));
for(i = 0; i < nboxes; ++i){
dets[i].prob = (float *)calloc(l.classes, sizeof(float));
}
return dets;
}
box get_yolo_box(float *x, float *biases, int n, int index, int i, int j, int lw, int lh, int w, int h, int stride)
{
box b;
b.x = (i + x[index + 0*stride]) / lw;
b.y = (j + x[index + 1*stride]) / lh;
b.w = exp(x[index + 2*stride]) * biases[2*n] / w;
b.h = exp(x[index + 3*stride]) * biases[2*n+1] / h;
return b;
}
void correct_yolo_boxes(detection *dets, int n, int w, int h, int netw, int neth, int relative)
{
int i;
int new_w=0;
int new_h=0;
if (((float)netw/w) < ((float)neth/h)) {
new_w = netw;
new_h = (h * netw)/w;
} else {
new_h = neth;
new_w = (w * neth)/h;
}
for (i = 0; i < n; ++i){
box b = dets[i].bbox;
b.x = (b.x - (netw - new_w)/2./netw) / ((float)new_w/netw);
b.y = (b.y - (neth - new_h)/2./neth) / ((float)new_h/neth);
b.w *= (float)netw/new_w;
b.h *= (float)neth/new_h;
if(!relative){
b.x *= w;
b.w *= w;
b.y *= h;
b.h *= h;
}
dets[i].bbox = b;
}
}
int get_yolo_detections(layer l, int w, int h, int netw, int neth, float thresh, int *map, int relative, detection *dets)
{
int i,j,n;
float *predictions = l.output;
// if (l.batch == 2) avg_flipped_yolo(l);
int count = 0;
for (i = 0; i < l.w*l.h; ++i){
int row = i / l.w;
int col = i % l.w;
for(n = 0; n < l.n; ++n){
int obj_index = entry_index(l, 0, n*l.w*l.h + i, 4);
float objectness = predictions[obj_index];
if(objectness <= thresh) continue;
int box_index = entry_index(l, 0, n*l.w*l.h + i, 0);
dets[count].bbox = get_yolo_box(predictions, l.biases, l.mask[n], box_index, col, row, l.w, l.h, netw, neth, l.w*l.h);
dets[count].objectness = objectness;
dets[count].classes = l.classes;
for(j = 0; j < l.classes; ++j){
int class_index = entry_index(l, 0, n*l.w*l.h + i, 4 + 1 + j);
float prob = objectness*predictions[class_index];
dets[count].prob[j] = (prob > thresh) ? prob : 0;
}
++count;
}
}
correct_yolo_boxes(dets, count, w, h, netw, neth, relative);
return count;
}
box get_region_box(float *x, float *biases, int n, int index, int i, int j, int w, int h, int stride)
{
box b;
b.x = (i + x[index + 0*stride]) / w;
b.y = (j + x[index + 1*stride]) / h;
b.w = exp(x[index + 2*stride]) * biases[2*n] / w;
b.h = exp(x[index + 3*stride]) * biases[2*n+1] / h;
return b;
}
void correct_region_boxes(detection *dets, int n, int w, int h, int netw, int neth, int relative)
{
int i;
int new_w=0;
int new_h=0;
if (((float)netw/w) < ((float)neth/h)) {
new_w = netw;
new_h = (h * netw)/w;
} else {
new_h = neth;
new_w = (w * neth)/h;
}
for (i = 0; i < n; ++i){
box b = dets[i].bbox;
b.x = (b.x - (netw - new_w)/2./netw) / ((float)new_w/netw);
b.y = (b.y - (neth - new_h)/2./neth) / ((float)new_h/neth);
b.w *= (float)netw/new_w;
b.h *= (float)neth/new_h;
if(!relative){
b.x *= w;
b.w *= w;
b.y *= h;
b.h *= h;
}
dets[i].bbox = b;
}
}
void get_region_detections(layer l, int w, int h, int netw, int neth, float thresh, int *map, float tree_thresh, int relative, detection *dets)
{
int i,j,n,z;
float *predictions = l.output;
if (l.batch == 2) {
float *flip = l.output + l.outputs;
for (j = 0; j < l.h; ++j) {
for (i = 0; i < l.w/2; ++i) {
for (n = 0; n < l.n; ++n) {
for(z = 0; z < l.classes + l.coords + 1; ++z){
int i1 = z*l.w*l.h*l.n + n*l.w*l.h + j*l.w + i;
int i2 = z*l.w*l.h*l.n + n*l.w*l.h + j*l.w + (l.w - i - 1);
float swap = flip[i1];
flip[i1] = flip[i2];
flip[i2] = swap;
if(z == 0){
flip[i1] = -flip[i1];
flip[i2] = -flip[i2];
}
}
}
}
}
for(i = 0; i < l.outputs; ++i){
l.output[i] = (l.output[i] + flip[i])/2.;
}
}
for (i = 0; i < l.w*l.h; ++i){
int row = i / l.w;
int col = i % l.w;
for(n = 0; n < l.n; ++n){
int index = n*l.w*l.h + i;
for(j = 0; j < l.classes; ++j){
dets[index].prob[j] = 0;
}
int obj_index = entry_index(l, 0, n*l.w*l.h + i, l.coords);
int box_index = entry_index(l, 0, n*l.w*l.h + i, 0);
int mask_index = entry_index(l, 0, n*l.w*l.h + i, 4);
float scale = l.background ? 1 : predictions[obj_index];
dets[index].bbox = get_region_box(predictions, l.biases, n, box_index, col, row, l.w, l.h, l.w*l.h);
dets[index].objectness = scale > thresh ? scale : 0;
if(dets[index].mask){
for(j = 0; j < l.coords - 4; ++j){
dets[index].mask[j] = l.output[mask_index + j*l.w*l.h];
}
}
int class_index = entry_index(l, 0, n*l.w*l.h + i, l.coords + !l.background);
if(dets[index].objectness){
for(j = 0; j < l.classes; ++j){
int class_index = entry_index(l, 0, n*l.w*l.h + i, l.coords + 1 + j);
float prob = scale*predictions[class_index];
dets[index].prob[j] = (prob > thresh) ? prob : 0;
}
}
}
}
correct_region_boxes(dets, l.w*l.h*l.n, w, h, netw, neth, relative);
}
void fill_network_boxes(network *net, int w, int h, float thresh, float hier, int *map, int relative, detection *dets)
{
int j;
for(j = 0; j < net->n; ++j){
layer l = net->layers[j];
if(l.type == YOLO){
int count = get_yolo_detections(l, w, h, net->w, net->h, thresh, map, relative, dets);
dets += count;
}
if(l.type == REGION){
get_region_detections(l, w, h, net->w, net->h, thresh, map, hier, relative, dets);
dets += l.w*l.h*l.n;
}
}
}
detection *get_network_boxes(network *net, int w, int h, float thresh, float hier, int *map, int relative, int *num)
{
detection *dets = make_network_boxes(net, thresh, num);
fill_network_boxes(net, w, h, thresh, hier, map, relative, dets);
return dets;
}
void free_detections(detection *dets, int n)
{
int i;
for(i = 0; i < n; ++i){
free(dets[i].prob);
if(dets[i].mask) free(dets[i].mask);
}
free(dets);
}
int network_width(network *net){return net->w;}
int network_height(network *net){return net->h;}
layer get_network_output_layer(network *net)
{
int i;
for(i = net->n - 1; i >= 0; --i){
if(net->layers[i].type != COST) break;
}
return net->layers[i];
}
void free_network(network *net)
{
int i;
for(i = 0; i < net->n; ++i){
free_layer(net->layers[i]);
}
free(net->layers);
if(net->input) free(net->input);
if(net->truth) free(net->truth);
free(net);
}
layer network_output_layer(network *net)
{
int i;
for(i = net->n - 1; i >= 0; --i){
if(net->layers[i].type != COST) break;
}
return net->layers[i];
}
int network_inputs(network *net)
{
return net->layers[0].inputs;
}
int network_outputs(network *net)
{
return network_output_layer(net).outputs;
}
float *network_output(network *net)
{
return network_output_layer(net).output;
}
//////////////////network end
//////////////////////box begin
int nms_comparator(const void *pa, const void *pb)
{
detection a = *(detection *)pa;
detection b = *(detection *)pb;
float diff = 0;
if(b.sort_class >= 0){
diff = a.prob[b.sort_class] - b.prob[b.sort_class];
} else {
diff = a.objectness - b.objectness;
}
if(diff < 0) return 1;
else if(diff > 0) return -1;
return 0;
}
float overlap(float x1, float w1, float x2, float w2)
{
float l1 = x1 - w1/2;
float l2 = x2 - w2/2;
float left = l1 > l2 ? l1 : l2;
float r1 = x1 + w1/2;
float r2 = x2 + w2/2;
float right = r1 < r2 ? r1 : r2;
return right - left;
}
float box_intersection(box a, box b)
{
float w = overlap(a.x, a.w, b.x, b.w);
float h = overlap(a.y, a.h, b.y, b.h);
if(w < 0 || h < 0) return 0;
float area = w*h;
return area;
}
float box_union(box a, box b)
{
float i = box_intersection(a, b);
float u = a.w*a.h + b.w*b.h - i;
return u;
}
float box_iou(box a, box b)
{
return box_intersection(a, b)/box_union(a, b);
}
void do_nms_sort(detection *dets, int total, int classes, float thresh)
{
int i, j, k;
k = total-1;
for(i = 0; i <= k; ++i){
if(dets[i].objectness == 0){
detection swap = dets[i];
dets[i] = dets[k];
dets[k] = swap;
--k;
--i;
}
}
total = k+1;
for(k = 0; k < classes; ++k){
for(i = 0; i < total; ++i){
dets[i].sort_class = k;
}
qsort(dets, total, sizeof(detection), nms_comparator);
for(i = 0; i < total; ++i){
if(dets[i].prob[k] == 0) continue;
box a = dets[i].bbox;
for(j = i+1; j < total; ++j){
box b = dets[j].bbox;
if (box_iou(a, b) > thresh){
dets[j].prob[k] = 0;
}
}
}
}
}
//////////////////////box end
//////////////////////image begin
float colors[6][3] = { {1,0,1}, {0,0,1},{0,1,1},{0,1,0},{1,1,0},{1,0,0} };
float get_color(int c, int x, int max)
{
float ratio = ((float)x/max)*5;
int i = floor(ratio);
int j = ceil(ratio);
ratio -= i;
float r = (1-ratio) * colors[i][c] + ratio*colors[j][c];
//printf("%f\n", r);
return r;
}
static float get_pixel_extend(image m, int x, int y, int c)
{
if(x < 0 || x >= m.w || y < 0 || y >= m.h) return 0;
/*
if(x < 0) x = 0;
if(x >= m.w) x = m.w-1;
if(y < 0) y = 0;
if(y >= m.h) y = m.h-1;
*/
if(c < 0 || c >= m.c) return 0;
return get_pixel(m, x, y, c);
}
void composite_image(image source, image dest, int dx, int dy)
{
int x,y,k;
for(k = 0; k < source.c; ++k){
for(y = 0; y < source.h; ++y){
for(x = 0; x < source.w; ++x){
float val = get_pixel(source, x, y, k);
float val2 = get_pixel_extend(dest, dx+x, dy+y, k);
set_pixel(dest, dx+x, dy+y, k, val * val2);
}
}
}
}
image border_image(image a, int border)
{
image b = make_image(a.w + 2*border, a.h + 2*border, a.c);
int x,y,k;
for(k = 0; k < b.c; ++k){
for(y = 0; y < b.h; ++y){
for(x = 0; x < b.w; ++x){
float val = get_pixel_extend(a, x - border, y - border, k);
if(x - border < 0 || x - border >= a.w || y - border < 0 || y - border >= a.h) val = 1;
set_pixel(b, x, y, k, val);
}
}
}
return b;
}
image copy_image(image p)
{
image copy = p;
copy.data = (float *)calloc(p.h*p.w*p.c, sizeof(float));
memcpy(copy.data, p.data, p.h*p.w*p.c*sizeof(float));
return copy;
}
image tile_images(image a, image b, int dx)
{
if(a.w == 0) return copy_image(b);
image c = make_image(a.w + b.w + dx, (a.h > b.h) ? a.h : b.h, (a.c > b.c) ? a.c : b.c);
fill_cpu(c.w*c.h*c.c, 1, c.data, 1);
embed_image(a, c, 0, 0);
composite_image(b, c, a.w + dx, 0);
return c;
}
image get_label(image **characters, char *string, int size)
{
size = size/10;
if(size > 7) size = 7;
image label = make_empty_image(0,0,0);
while(*string){
image l = characters[size][(int)*string];
image n = tile_images(label, l, -size - 1 + (size+1)/2);
free_image(label);
label = n;
++string;
}
image b = border_image(label, label.h*.25);
free_image(label);
return b;
}
void draw_label(image a, int r, int c, image label, const float *rgb)
{
int w = label.w;
int h = label.h;
if (r - h >= 0) r = r - h;
int i, j, k;
for(j = 0; j < h && j + r < a.h; ++j){
for(i = 0; i < w && i + c < a.w; ++i){
for(k = 0; k < label.c; ++k){
float val = get_pixel(label, i, j, k);
set_pixel(a, i+c, j+r, k, rgb[k] * val);
}
}
}
}
void draw_box(image a, int x1, int y1, int x2, int y2, float r, float g, float b)
{
//normalize_image(a);
int i;
if(x1 < 0) x1 = 0;
if(x1 >= a.w) x1 = a.w-1;
if(x2 < 0) x2 = 0;
if(x2 >= a.w) x2 = a.w-1;
if(y1 < 0) y1 = 0;
if(y1 >= a.h) y1 = a.h-1;
if(y2 < 0) y2 = 0;
if(y2 >= a.h) y2 = a.h-1;
for(i = x1; i <= x2; ++i){
a.data[i + y1*a.w + 0*a.w*a.h] = r;
a.data[i + y2*a.w + 0*a.w*a.h] = r;
a.data[i + y1*a.w + 1*a.w*a.h] = g;
a.data[i + y2*a.w + 1*a.w*a.h] = g;
a.data[i + y1*a.w + 2*a.w*a.h] = b;
a.data[i + y2*a.w + 2*a.w*a.h] = b;
}
for(i = y1; i <= y2; ++i){
a.data[x1 + i*a.w + 0*a.w*a.h] = r;
a.data[x2 + i*a.w + 0*a.w*a.h] = r;
a.data[x1 + i*a.w + 1*a.w*a.h] = g;
a.data[x2 + i*a.w + 1*a.w*a.h] = g;
a.data[x1 + i*a.w + 2*a.w*a.h] = b;
a.data[x2 + i*a.w + 2*a.w*a.h] = b;
}
}
void draw_box_width(image a, int x1, int y1, int x2, int y2, int w, float r, float g, float b)
{
int i;
for(i = 0; i < w; ++i){
draw_box(a, x1+i, y1+i, x2-i, y2-i, r, g, b);
}
}
image float_to_image(int w, int h, int c, float *data)
{
image out = make_empty_image(w,h,c);
out.data = data;
return out;
}
image threshold_image(image im, float thresh)
{
int i;
image t = make_image(im.w, im.h, im.c);
for(i = 0; i < im.w*im.h*im.c; ++i){
t.data[i] = im.data[i]>thresh ? 1 : 0;
}
return t;
}
void draw_detections(image im, detection *dets, int num, float thresh, char **names, image **alphabet, int classes)
{
int i,j;
for(i = 0; i < num; ++i){
char labelstr[4096] = {0};
int class_t = -1;
for(j = 0; j < classes; ++j){
if (dets[i].prob[j] > thresh){
if (class_t < 0) {
strcat(labelstr, names[j]);
class_t = j;
} else {
strcat(labelstr, ", ");
strcat(labelstr, names[j]);
}
printf("%s: %.0f%%\n", names[j], dets[i].prob[j]*100);
}
}
if(class_t >= 0){
int width = im.h * .006;
//printf("%d %s: %.0f%%\n", i, names[class], prob*100);
int offset = class_t*123457 % classes;
float red = get_color(2,offset,classes);
float green = get_color(1,offset,classes);
float blue = get_color(0,offset,classes);
float rgb[3];
//width = prob*20+2;
rgb[0] = red;
rgb[1] = green;
rgb[2] = blue;
box b = dets[i].bbox;
//printf("%f %f %f %f\n", b.x, b.y, b.w, b.h);
int left = (b.x-b.w/2.)*im.w;
int right = (b.x+b.w/2.)*im.w;
int top = (b.y-b.h/2.)*im.h;
int bot = (b.y+b.h/2.)*im.h;
if(left < 0) left = 0;
if(right > im.w-1) right = im.w-1;
if(top < 0) top = 0;
if(bot > im.h-1) bot = im.h-1;
draw_box_width(im, left, top, right, bot, width, red, green, blue);
if (alphabet) {
image label = get_label(alphabet, labelstr, (im.h*.03));
draw_label(im, top + width, left, label, rgb);
free_image(label);
}
if (dets[i].mask){
image mask = float_to_image(14, 14, 1, dets[i].mask);
image resized_mask = resize_image(mask, b.w*im.w, b.h*im.h);
image tmask = threshold_image(resized_mask, .5);
embed_image(tmask, im, left, top);
free_image(mask);
free_image(resized_mask);
free_image(tmask);
}
}
}
}
//////////////////////image end
/////////////////////////////////////////////////////////////////////20181229 reorg WeightQ BetaQ ok InputQ ok start input opt ok input_g eval op1 wuxiaoguo layer1 still 0.14s relu opt // input opt ok //output opt ok// wieght opt ok //out4 gg (4)n4m32i1o1 ok
#define MAX(x,y) ((x)>(y)?(x):(y))
#define MIN(x,y) ((x)<(y)?(x):(y))
#define S 2
#define K 3
#define Tn 4
#define Tm 32
#define Tr 26
#define Tc 26
#define OnChipIB_Width ((Tc-1)*S+K)
#define OnChipIB_Height ((Tr-1)*S+K)
#define MAX_BETA_LENGTH (1024)
#define INTERWIDTH 20
void yolov2_hls_ps(network *net, float *input)
{
int x;
int weight_offset[32] = {864, 18432, 73728, 8192, 73728,
294912, 32768, 294912, 1179648, 131072, 1179648, 131072,
1179648, 4718592, 524288, 4718592, 524288, 4718592, 9437184,
9437184, 32768, 11796480, 435200, 0, 0, 0, 0, 0, 0, 0, 0, 0};
int beta_offset[32] = {32, 64, 128, 64, 128, 256, 128, 256, 512, 256, 512, 256, 512, 1024,
512, 1024, 512, 1024, 1024, 1024, 64, 1024, 425, 0, 0, 0, 0, 0, 0, 0, 0, 0};
int offset_index = 0;
int *Weight_buf = (int *)calloc(203767168/4/2,sizeof(int));
int *Beta_buf = (int *)calloc((43044+4)/4/2,sizeof(int));
FILE *fp_w = fopen("weights_reorg_ap16.bin", "rb");
if(!fp_w) file_error("weights_reorg_ap16.bin");
FILE *fp_b = fopen("bias_ap16.bin", "rb");
if(!fp_b) file_error("bias_ap16.bin");
fread(Weight_buf, sizeof(int), 203767168/4/2, fp_w);
fread(Beta_buf, sizeof(int), (43044+4)/4/2, fp_b);
fclose(fp_w);
fclose(fp_b);
#define QNUM 23
int inputQ[QNUM+1];
int weightQ[QNUM];
int betaQ[QNUM];
FILE *Qin;
Qin = fopen("yolov2_ap16_inout_maxQ_24.bin","rb");
if(!Qin) file_error("Qin error 1\n");
fread(inputQ,sizeof(int),QNUM+1,Qin);
fclose(Qin);
if(inputQ[20] < inputQ[21])
inputQ[21] = inputQ[20];
else
inputQ[20] = inputQ[21];
for(x=0;x<QNUM+1;x++)
printf("[%2d inputQ]=%2d\n",x,inputQ[x]);
Qin = fopen("weights_reorg_ap16_maxQ_23.bin","rb");
if(!Qin) file_error("Qin error 2\n");
fread(weightQ,sizeof(int),QNUM,Qin);
fclose(Qin);
for(x=0;x<QNUM;x++)
printf("[%2d weightQ]=%2d\n",x,weightQ[x]);
Qin = fopen("bias_ap16_maxQ_23.bin","rb");
if(!Qin) file_error("Qin error 4\n");
fread(betaQ,sizeof(int),QNUM,Qin);
fclose(Qin);
for(x=0;x<QNUM;x++)
printf("[%2d betaQ]=%2d\n",x,betaQ[x]);
#define MEM_LEN (416*416*32/2+208*208*32/2)
int *Memory_buf = (int*)calloc(MEM_LEN+1024/2+1024/2,sizeof(int));
int *Memory_top = Memory_buf+1024/2;
int *Memory_bottom = Memory_top + MEM_LEN;
int tmp_in;
short current_in,next_in;
bool NextPixelInFlag = true;
int InputPixelOffset = 0;
int *Input_ptr = (int *)Memory_top;
for(x=0;x<416*416*3;x++)//1st Layer input Q14
{
if(NextPixelInFlag)
{
current_in = (short)(input[x]*pow(2.0,14));
NextPixelInFlag = false;
}
else
{
next_in = (short)(input[x]*pow(2.0,14));
tmp_in = (next_in<<16) + (current_in);
Input_ptr[InputPixelOffset] = tmp_in;
InputPixelOffset++;
NextPixelInFlag = true;
}
}
float *region_buf = (float *)calloc(sizeof(float),13*13*425);
int* in_ptr[32];
int* out_ptr[32];
#define ROUTE16_LEN (26*26*512/2)
#define CONV27_LEN (13*13*256/2)
#define CONV24_LEN (13*13*1024/2)
for(x=0;x<18;x++)
{
if(x%2==0)
{
in_ptr[x] = Memory_top;
out_ptr[x] = Memory_bottom - net->layers[x].outputs/2 ;
}
else
{
in_ptr[x] = out_ptr[x-1];
out_ptr[x] = Memory_top;
}
}
for(x=18;x<25;x++)
{
if(x%2==0)
{
in_ptr[x] = Memory_top;
out_ptr[x] = Memory_bottom - ROUTE16_LEN - net->layers[x].outputs/2;
}else
{
in_ptr[x] = out_ptr[x-1];
out_ptr[x] = Memory_top;
}
}
in_ptr[26] = Memory_bottom - ROUTE16_LEN;
out_ptr[26] = Memory_top;
in_ptr[27] = Memory_top;
out_ptr[27] = Memory_bottom - ROUTE16_LEN - CONV24_LEN - CONV27_LEN;
in_ptr[29] = out_ptr[27];
out_ptr[29] = Memory_top;
in_ptr[30] = Memory_top;
out_ptr[30] = Memory_bottom - (net->layers[30].outputs + 13*13*3)/2;
in_ptr[31] = out_ptr[30];
int i;
int woffset = 0;
int aoffset = 0;
int boffset = 0;
int TR,TC,TM,TN;
int output_w,output_h;
int rLoops,cLoops,mLoops,nLoops;
double sum_gop = 0.0;
int INPUTQ;
unsigned char TRow;
int trow_loops;
int T2Rate;
for(i = 0; i < net->n; ++i)
{
layer l = net->layers[i];
printf("Layer[%2d]: ",i);
switch(l.type)
{
case CONVOLUTIONAL:
printf("outputMemory:%8d;BN=%d;Activation=%d;conv %5d %2d x%2d /%2d %4d x%4d x%4d -> %4d x%4d x%4d %5.3f BFLOPs\n",l.outputs,l.batch_normalize,l.activation, l.n, l.size, l.size, l.stride, l.w, l.h, l.c, l.out_w, l.out_h, l.out_c, (2.0 * l.n * l.size*l.size*l.c/l.groups * l.out_h*l.out_w)/1000000000.);
sum_gop += (2.0 * l.n * l.size*l.size*l.c/l.groups * l.out_h*l.out_w)/1000000000.;
output_w = (l.w - l.size + 2*l.pad)/l.stride + 1 ;
output_h = (l.h - l.size + 2*l.pad)/l.stride + 1 ;
TR = MIN(((OnChipIB_Height-l.size)/l.stride+1),Tr);//keep Kernel_stride>=1
TR = MIN(output_h,TR);
TC = MIN(((OnChipIB_Width-l.size)/l.stride+1),Tc);
TC = MIN(output_w,TC);
TM = MIN(l.n,Tm);
TN = MIN(l.c,Tn);
rLoops = (int)ceil(((float)output_h)/TR);
cLoops = (int)ceil(((float)output_w)/TC);
mLoops = (int)ceil(((float)l.n)/TM);
nLoops = (int)ceil(((float)l.c)/TN);
switch(l.w)
{
case 26:
T2Rate = 2;
break;
case 13:
T2Rate = 4;
break;
default:
T2Rate = 1;
break;
}
TRow = (TR-1)*l.stride+l.size;
trow_loops = (int)ceil(((float)TRow/T2Rate));
INPUTQ = inputQ[offset_index];
if(i==26)
INPUTQ = inputQ[12];
YOLO2_FPGA(in_ptr[i],in_ptr[i],in_ptr[i],in_ptr[i],out_ptr[i],out_ptr[i],Weight_buf+woffset/2,Beta_buf+boffset/2,
l.c,l.n,l.size,
l.stride,l.w,l.h,output_w,output_h,
l.pad,l.activation==LEAKY?1:0,l.batch_normalize?1:0,
TM,TN,TR,TC,
mLoops,nLoops,rLoops,cLoops,0,
INPUTQ,inputQ[offset_index+1],weightQ[offset_index],betaQ[offset_index],trow_loops);
printf("TR=%d,TC=%d,TM=%d,TN=%d,rLoops=%d,cLoops=%d,mLoops=%d,nLoops=%d\n",TR,TC,TM,TN,rLoops,cLoops,mLoops,nLoops);
woffset += weight_offset[offset_index];
boffset += beta_offset[offset_index];
offset_index++;
break;
case MAXPOOL:
printf("outputMemory:%8d;max %d x %d / %d %4d x%4d x%4d -> %4d x%4d x%4d\n",l.outputs, l.size, l.size, l.stride, l.w, l.h, l.c, l.out_w, l.out_h, l.out_c);
//output_w = (l.w - l.size)/l.stride + 1 ;
//output_h = (l.h - l.size)/l.stride + 1 ;
output_w = l.out_h;
output_h = l.out_w;
TR = MIN(((OnChipIB_Height-l.size)/l.stride+1),Tr);//keep Kernel_stride>=1
TC = MIN(((OnChipIB_Width-l.size)/l.stride+1),Tc);
TR = MIN(output_h,TR);
TC = MIN(output_w,TC);
TM = MIN(Tm,Tn);
TM = MIN(l.c,TM);
TN = TM;
rLoops = (int)ceil(((float)output_h)/TR);
cLoops = (int)ceil(((float)output_w)/TC);
mLoops = (int)ceil(((float)l.c)/TM);
switch(l.w)
{
case 26:
T2Rate = 2;
break;
case 13:
T2Rate = 4;
break;
default:
T2Rate = 1;
break;
}
TRow = (TR-1)*l.stride+l.size;
trow_loops = (int)ceil(((float)TRow/T2Rate));
YOLO2_FPGA(in_ptr[i],in_ptr[i],in_ptr[i],in_ptr[i],out_ptr[i],out_ptr[i],NULL,NULL,l.c,l.c,
l.size,l.stride,l.w,l.h,output_w,output_h,
0,0,0,TM,TN,TR,TC,mLoops,1,rLoops,cLoops,1,
inputQ[offset_index],inputQ[offset_index],INTERWIDTH,INTERWIDTH,trow_loops);
break;
case REORG:
printf("outputMemory:%8d;reorg /%2d %4d x%4d x%4d -> %4d x%4d x%4d\n",l.outputs, l.stride, l.w, l.h, l.c, l.out_w, l.out_h, l.out_c);
output_w = 26;
output_h = 32*13;
TR = MIN(((OnChipIB_Height-l.stride)/l.stride+1),Tr);//keep Kernel_stride>=1
TR = MIN(output_h,TR);
TC = MIN(((OnChipIB_Width-l.stride)/l.stride+1),Tc);
TC = MIN(output_w,TC);
TM = 4;
TN = TM;
rLoops = (int)ceil(((float)output_h)/TR);
cLoops = (int)ceil(((float)output_w)/TC);
mLoops = 1;
switch(52)
{
case 26:
T2Rate = 2;
break;
case 13:
T2Rate = 4;
break;
default:
T2Rate = 1;
break;
}
TRow = (TR-1)*l.stride+l.stride;
trow_loops = (int)ceil(((float)TRow/T2Rate));
YOLO2_FPGA(in_ptr[i],in_ptr[i],in_ptr[i],in_ptr[i],out_ptr[i],out_ptr[i],NULL,NULL,1,4,
l.stride,l.stride,52,32*26,output_w,output_h,
0,0,0,TM,TN,TR,TC,mLoops,1,rLoops,cLoops,2,
inputQ[offset_index],inputQ[offset_index],INTERWIDTH,INTERWIDTH,trow_loops);
break;
case ROUTE:
printf("outputMemory:%8d;route ",l.outputs);
int j;
for(j = 0; j < l.n; ++j){
printf(" %d", l.input_layers[j]);
}
printf("\n");
break;
case REGION:
printf("outputMemory:%8d;Detection\n",l.outputs);
//netp.input = in_ptr[i];
double LastLayerOutputPara = pow(2.0,-inputQ[QNUM]);
bool NextPixelFlag = true;
int OutputPixelOffset = 0;
short current_p,next_p,output_p;
int *Output_ptr = (int *)(in_ptr[i]);
for(j=0;j<l.outputs;j++)
{
if(NextPixelFlag)
{
int tmp_p = Output_ptr[OutputPixelOffset];
OutputPixelOffset++;
current_p = tmp_p;
next_p = tmp_p >> 16;
output_p = current_p;
NextPixelFlag = false;
}else
{
output_p = next_p;
NextPixelFlag = true;
}
region_buf[j] = output_p*LastLayerOutputPara;
}
net->input = region_buf;
forward_region_layer(l, net);
break;
}
}
printf("SUM_GOP=%g\n",sum_gop);
free(region_buf);
free(Memory_buf);
free(Weight_buf);
free(Beta_buf);
}
///////////////////////////////////////////////////////////////////////20181229 reorg WeightQ BetaQ ok InputQ ok end input opt ok input_g eval op1 //(4)n4m32i1o1 ok
#endif
|
general_basis_op.h | #ifndef _GENERAL_BASIS_OP_H
#define _GENERAL_BASIS_OP_H
#include <iostream>
#include <complex>
#include <algorithm>
#include <limits>
#include <tuple>
#include <utility>
#include <boost/iterator/zip_iterator.hpp>
#include "general_basis_core.h"
#include "numpy/ndarraytypes.h"
#include "misc.h"
#include "openmp.h"
//#include "complex_ops.h"
namespace basis_general {
int general_inplace_op_get_switch_num(PyArray_Descr * dtype)
{
int T = dtype->type_num;
if(T==NPY_COMPLEX128){return 0;}
else if(T==NPY_FLOAT64){return 1;}
else if(T==NPY_COMPLEX64){return 2;}
else if(T==NPY_FLOAT32){return 3;}
else {return -1;}
}
template<bool transpose>
struct transpose_indices {
inline static void call(npy_intp &i,npy_intp &j){};
};
template<>
struct transpose_indices<true> {
inline static void call(npy_intp &i,npy_intp &j)
{
npy_intp k = j;
j = i;
i = k;
}
};
template<bool conjugate>
struct conj
{
inline static void call(std::complex<double> &z){}
};
template<>
struct conj<true>
{
inline static void call(std::complex<double> &z){
z = std::conj(z);
}
};
template<class I,class P,
bool full_basis,
bool symmetries,
bool bracket_basis>
struct get_index {};
template<class I,class P>
struct get_index<I,P,true,false,false>{
inline static npy_intp call(general_basis_core<I,P> *B,
const int nt,
const I r,
const npy_intp Ns,
const I basis[],
const npy_intp basis_begin[],
const npy_intp basis_end[],
const int N_p,
int g[],
P &sign)
{
return Ns - (npy_intp)r - 1;
}
};
template<class I,class P>
struct get_index<I,P,false,false,false>
{
inline static npy_intp call(general_basis_core<I,P> *B,
const int nt,
const I r,
const npy_intp Ns,
const I basis[],
const npy_intp basis_begin[],
const npy_intp basis_end[],
const int N_p,
int g[],
P &sign)
{
return rep_position<npy_intp,I>(Ns,basis,r);
}
};
template<class I,class P>
struct get_index<I,P,false,true,false> {
inline static npy_intp call(general_basis_core<I,P> *B,
const int nt,
const I r,
const npy_intp Ns,
const I basis[],
const npy_intp basis_begin[],
const npy_intp basis_end[],
const int N_p,
int g[],
P &sign)
{
for(int k=0;k<nt;k++){
g[k]=0;
}
I rr = B->ref_state(r,g,sign);
return rep_position<npy_intp,I>(Ns,basis,rr);
}
};
template<class I,class P>
struct get_index<I,P,false,true,true>
{
inline static npy_intp call(general_basis_core<I,P> *B,
const int nt,
const I r,
const npy_intp Ns,
const I basis[],
const npy_intp basis_begin[],
const npy_intp basis_end[],
const int N_p,
int g[],
P &sign)
{
for(int k=0;k<nt;k++){
g[k]=0;
}
I rr = B->ref_state(r,g,sign);
npy_intp rr_prefix = B->get_prefix(rr,N_p);
return rep_position<npy_intp,I>(basis_begin,basis_end,basis,rr_prefix,rr);
}
};
template<class I,class P>
struct get_index<I,P,false,false,true>
{
inline static npy_intp call(general_basis_core<I,P> *B,
const int nt,
const I r,
const npy_intp Ns,
const I basis[],
const npy_intp basis_begin[],
const npy_intp basis_end[],
const int N_p,
int g[],
P &sign)
{
npy_intp r_prefix = B->get_prefix(r,N_p);
return rep_position<npy_intp,I>(basis_begin,basis_end,basis,r_prefix,r);
}
};
template<class J,class P,bool symmetries>
struct scale_matrix_ele
{
inline static void call(const int nt,
const npy_intp i,
const npy_intp j,
const P sign,
const J n[],
const int g[],
const double kk[],
std::complex<double> &m) {}
};
template<class J,class P>
struct scale_matrix_ele<J,P,true>
{
inline static void call(const int nt,
const npy_intp i,
const npy_intp j,
const P sign,
const J n[],
const int g[],
const double kk[],
std::complex<double> &m)
{
double q = 0;
for(int k=0;k<nt;k++){
q += kk[k]*g[k];
}
m *= sign * std::sqrt(double(n[j])/double(n[i])) * std::exp(std::complex<double>(0,-q));
}
};
template<class I, class J, class K,class P=signed char,
bool full_basis,bool symmetries,bool bracket_basis,
bool transpose,bool conjugate>
int general_inplace_op_core(general_basis_core<I,P> *B,
const int n_op,
const char opstr[],
const int indx[],
const std::complex<double> A,
const npy_intp Ns,
const npy_intp nvecs,
const I basis[],
const J n[],
const npy_intp basis_begin[],
const npy_intp basis_end[],
const int N_p,
const K v_in[],
K v_out[])
{
int err = 0;
#pragma omp parallel shared(err) firstprivate(A)
{
const int nt = B->get_nt();
const int nthread = omp_get_num_threads();
const npy_intp chunk = std::max(Ns/(1000*nthread),(npy_intp)1);
std::complex<double> m;
int g[__GENERAL_BASIS_CORE__max_nt];
double kk[__GENERAL_BASIS_CORE__max_nt];
for(int k=0;k<nt;k++)
kk[k] = (2.0*M_PI*B->qs[k])/B->pers[k];
#pragma omp for schedule(dynamic,chunk)
for(npy_intp ii=0;ii<Ns;ii++){
if(err != 0){
continue;
}
npy_intp i = ii;
const I s = basis[ii];
I r = s;
m = A;
int local_err = B->op(r,m,n_op,opstr,indx);
if(local_err == 0){
P sign = 1;
npy_intp j = i;
bool not_diag = (r != s);
if(not_diag){
j = get_index<I,P,full_basis,symmetries,bracket_basis>::call(B,nt,r,Ns,basis,basis_begin,basis_end,N_p,g,sign);
}
if(j >= 0){
if(symmetries && not_diag){
scale_matrix_ele<J,P,symmetries>::call(nt,i,j,sign,n,g,kk,m);
}
transpose_indices<transpose>::call(i,j);
conj<conjugate>::call(m);
const K * v_in_col = v_in + i * nvecs;
K * v_out_row = v_out + j * nvecs;
local_err = type_checks<K>(m);
if(local_err){
#pragma omp atomic write
err = local_err;
}
for(int k=0;k<nvecs;k++){
const std::complex<double> M = mul(v_in_col[k],m);
atomic_add(M,&v_out_row[k]);
}
}
}
else if(err==0){
#pragma omp atomic write
err = local_err;
}
}
}
return err;
}
template<class I, class J, class K,class P=signed char>
int general_inplace_op(general_basis_core<I,P> *B,
const bool conjugate,
const bool transpose,
const int n_op,
const char opstr[],
const int indx[],
const std::complex<double> A,
const bool full_basis,
const npy_intp Ns,
const npy_intp nvecs,
const I basis[],
const J n[],
const npy_intp basis_begin[],
const npy_intp basis_end[],
const int N_p,
const K v_in[],
K v_out[])
{
int err = 0;
const int nt = B->get_nt();
if(full_basis){ // full_basis = true, symmetries = false, // bracket_basis = false
if(transpose){ // transpose = true
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,true,false,false,true,true>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,true,false,false,true,false>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
else{ // transpose = false
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,true,false,false,false,true>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,true,false,false,false,false>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
}
else if(nt>0){ // full_basis = false, symmetries = true
if(N_p>0){ // bracket_basis = true
if(transpose){ // transpose = true
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,false,true,true,true,true>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,false,true,true,true,false>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
else{ // transpose = false
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,false,true,true,false,true>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,false,true,true,false,false>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
}
else{ // bracket_basis = false
if(transpose){ // transpose = true
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,false,true,false,true,true>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,false,true,false,true,false>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
else{ // transpose = false
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,false,true,false,false,true>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,false,true,false,false,false>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
}
}
else{ // full_basis = flase, symmetries = false
if(N_p>0){ // bracket_basis = true
if(transpose){ // transpose = true
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,false,false,true,true,true>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,false,false,true,true,false>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
else{ // transpose = false
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,false,false,true,false,true>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,false,false,true,false,false>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
}
else{ // bracket_basis = false
if(transpose){ // transpose = true
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,false,false,false,true,true>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,false,false,false,true,false>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
else{ // transpose = false
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,false,false,false,false,true>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,false,false,false,false,false>(
B,n_op,opstr,indx,A,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
}
}
}
template<class I, class J,class P=signed char>
int general_inplace_op_impl(general_basis_core<I,P> *B,
const bool conjugate,
const bool transpose,
const int n_op,
const char opstr[],
const int indx[],
void * A,
const bool full_basis,
const npy_intp Ns,
const npy_intp nvecs,
const I basis[],
const J n[],
const npy_intp basis_begin[],
const npy_intp basis_end[],
const int N_p,
PyArray_Descr * dtype,
void * v_in,
void * v_out)
{
int type_num = dtype->type_num;
switch (type_num)
{
case NPY_COMPLEX128:
return general_inplace_op<I,J,std::complex<double>,P>(B,conjugate,transpose,n_op,opstr,indx,*(std::complex<double> *)A,full_basis,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,(const std::complex<double> *)v_in,(std::complex<double> *)v_out);
case NPY_FLOAT64:
return general_inplace_op<I,J,double,P>(B,conjugate,transpose,n_op,opstr,indx,*(std::complex<double> *)A,full_basis,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,(const double *)v_in,(double *)v_out);
case NPY_COMPLEX64:
return general_inplace_op<I,J,std::complex<float>,P>(B,conjugate,transpose,n_op,opstr,indx,*(std::complex<double> *)A,full_basis,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,(const std::complex<float> *)v_in,(std::complex<float> *)v_out);
case NPY_FLOAT32:
return general_inplace_op<I,J,float,P>(B,conjugate,transpose,n_op,opstr,indx,*(std::complex<double> *)A,full_basis,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,(const float *)v_in,(float *)v_out);
default:
return -2;
}
}
// template<class Tuple>
// struct compare_Tuple : std::binary_function<Tuple,Tuple,bool>
// {
// bool operator()(const Tuple &a, const Tuple &b) const {
// return (std::get<0>(a) == std::get<0>(b) ? std::get<1>(a) < std::get<1>(b) : std::get<0>(a) < std::get<0>(b));
// }
// };
template<class T,class K>
using Tuple = boost::tuple<T&,K&,K&>;
template<class T>
struct nonzero : std::unary_function<T,bool>
{
inline bool operator()(const T& tup) const {
return equal_zero(boost::get<0>(tup));
}
};
template<class I, class J, class K, class T,class P=signed char,
bool full_basis,bool symmetries,bool bracket_basis>
std::pair<int,int>
general_op_core(general_basis_core<I,P> *B,
const int n_op,
const char opstr[],
const int indx[],
const std::complex<double> A,
const npy_intp Ns,
const I basis[],
const J n[],
const npy_intp basis_begin[],
const npy_intp basis_end[],
const int N_p,
K row[],
K col[],
T M[]
)
{
int err = 0, warn = 0;
#pragma omp parallel firstprivate(N_p,Ns,A,n_op)
{
std::complex<double> m;
const int N = B->get_N();
const int nt = B->get_nt();
const int nthread = omp_get_num_threads();
const int threadn = omp_get_thread_num();
const npy_intp chunk = (Ns+nthread-1)/nthread;
const npy_intp begin = std::min(threadn*chunk,Ns);
const npy_intp end = std::min((threadn+1)*chunk,Ns);
const npy_intp dyn_chunk = std::max(Ns/(1000*nthread),(npy_intp)1);
int g[__GENERAL_BASIS_CORE__max_nt];
double kk[__GENERAL_BASIS_CORE__max_nt];
for(int k=0;k<nt;k++){
kk[k] = 2.0*M_PI*B->qs[k]/B->pers[k];
}
std::fill(M+begin,M+end,T(0));
std::fill(row+begin,row+end,K(0));
std::fill(col+begin,col+end,K(0));
#pragma omp barrier
#pragma omp for schedule(dynamic,dyn_chunk)
for(npy_intp i=0;i<Ns;i++){
I r = basis[i];
const I s = r;
m = A;
int local_err = B->op(r,m,n_op,&opstr[0],&indx[0]);
if(local_err == 0){
P sign = 1;
npy_intp j = i;
bool not_diag = (r != s);
if(not_diag){
j = get_index<I,P,full_basis,symmetries,bracket_basis>::call(B,nt,r,Ns,basis,basis_begin,basis_end,N_p,g,sign);
}
if(j >= 0){
if(symmetries && not_diag){
scale_matrix_ele<J,P,symmetries>::call(nt,i,j,sign,n,g,kk,m);
}
T me = 0;
int local_warn = type_checks(m,&me);
if(local_err){
#pragma omp atomic write
err = local_err;
}
if(warn == 0 && local_warn != 0){
#pragma omp atomic write
warn = local_warn;
}
M[i] = me;
col[i] = i;
row[i] = j;
}
}
else if(err == 0){
#pragma omp atomic write
err = local_err;
}
}
}
return std::make_pair(err,warn);
}
template<class I, class J, class K,class T,class P=signed char>
std::pair<int,int>
general_op(general_basis_core<I,P> *B,
const int n_op,
const char opstr[],
const int indx[],
const std::complex<double> A,
const bool full_basis,
const npy_intp Ns,
const I basis[],
const J n[],
const npy_intp basis_begin[],
const npy_intp basis_end[],
const int N_p,
K row[],
K col[],
T M[]
)
{
int err = 0;
const int nt = B->get_nt();
if(full_basis){ // full_basis = true, symmetries = false, // bracket_basis = false
return general_op_core<I,J,K,T,P,true,false,false>(B,n_op,opstr,indx,A,Ns,basis,n,basis_begin,basis_end,N_p,row,col,M);
}
else if(nt>0){ // full_basis = false, symmetries = true
if(N_p>0){ // bracket_basis = true
return general_op_core<I,J,K,T,P,false,true,true>(B,n_op,opstr,indx,A,Ns,basis,n,basis_begin,basis_end,N_p,row,col,M);
}
else{ // bracket_basis = false
return general_op_core<I,J,K,T,P,false,true,false>(B,n_op,opstr,indx,A,Ns,basis,n,basis_begin,basis_end,N_p,row,col,M);
}
}
else{ // full_basis = flase, symmetries = false
if(N_p>0){ // bracket_basis = true
return general_op_core<I,J,K,T,P,false,false,true>(B,n_op,opstr,indx,A,Ns,basis,n,basis_begin,basis_end,N_p,row,col,M);
}
else{ // bracket_basis = false
return general_op_core<I,J,K,T,P,false,false,false>(B,n_op,opstr,indx,A,Ns,basis,n,basis_begin,basis_end,N_p,row,col,M);
}
}
}
/*
typedef std::vector<std::complex<double>> J_list_type;
typedef std::vector<std::vector<int>> indx_list_type;
typedef std::vector<std::string> op_list_type;
template<class I, class J, class K,class P=signed char,
bool full_basis,bool symmetries,bool bracket_basis,
bool transpose,bool conjugate>
int general_inplace_op_core(general_basis_core<I,P> *B,
op_list_type op_list,
indx_list_type indx_list,
J_list_type J_list,
const npy_intp Ns,
const npy_intp nvecs,
const I basis[],
const J n[],
const npy_intp basis_begin[],
const npy_intp basis_end[],
const int N_p,
const K v_in[],
K v_out[])
{
int err = 0;
const int nt = B->get_nt();
const int nthread = omp_get_max_threads();
const npy_intp chunk = std::max(Ns/(1000*nthread),(npy_intp)1);
const int n_ops = J_list.size();
std::vector<std::pair<npy_intp,K>> ME_vec(Ns);
std::vector<std::complex<double>> tmp(nvecs*nthread);
std::pair<npy_intp,K> * ME = &ME_vec[0];
#pragma omp parallel shared(err,ME)
{
std::complex<double> m;
K M = 0;
int g[__GENERAL_BASIS_CORE__max_nt];
double kk[__GENERAL_BASIS_CORE__max_nt];
for(int k=0;k<nt;k++)
kk[k] = (2.0*M_PI*B->qs[k])/B->pers[k];
for(int o=0;o<n_ops;o++){
if(err!=0){
break;
}
const int n_op = indx_list[o].size();
const char * opstr = op_list[o].c_str();
const int * indx = indx_list[o].data();
#pragma omp for schedule(dynamic,chunk)
for(npy_intp ii=0;ii<Ns;ii++){
if(err!=0){
continue;
}
int i = ii;
const I s = basis[ii];
I r = s;
m = A;
int local_err = B->op(r,m,n_op,opstr,indx);
if(local_err == 0){
P sign = 1;
npy_intp j = i;
bool not_diag = (r != s);
if(not_diag){
j = get_index<I,P,full_basis,symmetries,bracket_basis>::call(B,nt,r,Ns,basis,basis_begin,basis_end,N_p,g,sign);
}
if(j >= 0){
if(not_diag){
scale_matrix_ele<J,P,symmetries>::call(nt,i,j,sign,n,g,kk,m);
}
transpose_indices<transpose>::call(i,j);
local_err = type_checks(conj<conjugate>::call(m),&M);
ME[ii] = std::make_pair(j,M);
if(local_err){
#pragma omp atomic write
err = local_err;
}
}
else{
M = 0;
ME[ii] = std::make_pair(j,M);
}
}
else{
#pragma omp atomic write
err = local_err;
}
}
if(err!=0){
break;
}
}
}
return err;
}
template<class I, class J, class K,class P=signed char>
int general_inplace_op(general_basis_core<I,P> *B,
const bool conjugate,
const bool transpose,
const bool full_basis,
op_list_type op_list,
indx_list_type indx_list,
J_list_type J_list,
const npy_intp Ns,
const npy_intp nvecs,
const I basis[],
const J n[],
const npy_intp basis_begin[],
const npy_intp basis_end[],
const int N_p,
const K v_in[],
K v_out[])
{
int err = 0;
const int nt = B->get_nt();
if(full_basis){ // full_basis = true, symmetries = false, // bracket_basis = false
if(transpose){ // transpose = true
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,true,false,false,true,true>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,true,false,false,true,false>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
else{ // transpose = false
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,true,false,false,false,true>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,true,false,false,false,false>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
}
else if(nt>0){ // full_basis = false, symmetries = true
if(N_p>0){ // bracket_basis = true
if(transpose){ // transpose = true
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,false,true,true,true,true>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,false,true,true,true,false>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
else{ // transpose = false
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,false,true,true,false,true>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,false,true,true,false,false>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
}
else{ // bracket_basis = false
if(transpose){ // transpose = true
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,false,true,false,true,true>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,false,true,false,true,false>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
else{ // transpose = false
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,false,true,false,false,true>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,false,true,false,false,false>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
}
}
else{ // full_basis = flase, symmetries = false
if(N_p>0){ // bracket_basis = true
if(transpose){ // transpose = true
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,false,false,true,true,true>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,false,false,true,true,false>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
else{ // transpose = false
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,false,false,true,false,true>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,false,false,true,false,false>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
}
else{ // bracket_basis = false
if(transpose){ // transpose = true
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,false,false,false,true,true>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,false,false,false,true,false>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
else{ // transpose = false
if(conjugate){ // conjugate = true
return general_inplace_op_core<I,J,K,P,false,false,false,false,true>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
else{ // conjugate = false
return general_inplace_op_core<I,J,K,P,false,false,false,false,false>(
B,op_list,indx_list,J_list,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,v_in,v_out);
}
}
}
}
}
template<class I, class J,class P=signed char>
int general_inplace_op_impl(general_basis_core<I,P> *B,
const bool conjugate,
const bool transpose,
const bool full_basis,
op_list_type op_list,
indx_list_type indx_list,
J_list_type J_list,
const npy_intp Ns,
const npy_intp nvecs,
const I basis[],
const J n[],
const npy_intp basis_begin[],
const npy_intp basis_end[],
const int N_p,
PyArray_Descr * dtype,
void * v_in,
void * v_out)
{
int type_num = dtype->type_num;
switch (type_num)
{
case NPY_COMPLEX128:
return general_inplace_op<I,J,std::complex<double>,P>(B,conjugate,transpose,op_list,indx_list,J_list,full_basis,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,(const std::complex<double> *)v_in,(std::complex<double> *)v_out);
case NPY_FLOAT64:
return general_inplace_op<I,J,double,P>(B,conjugate,transpose,op_list,indx_list,J_list,full_basis,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,(const double *)v_in,(double *)v_out);
case NPY_COMPLEX64:
return general_inplace_op<I,J,std::complex<float>,P>(B,conjugate,transpose,op_list,indx_list,J_list,full_basis,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,(const std::complex<float> *)v_in,(std::complex<float> *)v_out);
case NPY_FLOAT32:
return general_inplace_op<I,J,float,P>(B,conjugate,transpose,op_list,indx_list,J_list,full_basis,Ns,nvecs,basis,n,basis_begin,basis_end,N_p,(const float *)v_in,(float *)v_out);
default:
return -2;
}
}
*/
/*
template<class I, class J, class K, class T,class P=signed char>
int general_op(general_basis_core<I,P> *B,
const int n_op,
const char opstr[],
const int indx[],
const std::complex<double> A,
const bool full_basis,
const npy_intp Ns,
const I basis[],
const J n[],
K row[],
K col[],
T M[]
)
{
int err = 0;
#pragma omp parallel
{
const int nt = B->get_nt();
const int N = B->get_N();
const npy_intp chunk = std::max(Ns/(1000*omp_get_num_threads()),(npy_intp)1);
int g[__GENERAL_BASIS_CORE__max_nt];
double kk[__GENERAL_BASIS_CORE__max_nt];
for(int k=0;k<nt;k++)
kk[k] = 2.0*M_PI*B->qs[k]/B->pers[k];
#pragma omp for schedule(dynamic,chunk)
for(npy_intp i=0;i<Ns;i++){
if(err != 0){
continue;
}
I r = basis[i];
std::complex<double> m = A;
int local_err = B->op(r,m,n_op,opstr,indx);
if(local_err == 0){
P sign = 1;
for(int k=0;k<nt;k++){
g[k]=0;
}
K j = i;
if(r != basis[i]){
I rr = B->ref_state(r,g,sign);
if(full_basis){
j = Ns - (npy_intp)rr - 1;
}
else{
j = rep_position(Ns,basis,rr);
}
}
if(j >= 0){
double q = 0;
for(int k=0;k<nt;k++){
q += kk[k]*g[k];
}
m *= sign * std::sqrt(double(n[j])/double(n[i])) * std::exp(std::complex<double>(0,-q));
local_err = type_checks(m,&M[i]);
col[i]=i;
row[i]=j;
}
else{
col[i] = i;
row[i] = i;
M[i] = std::numeric_limits<T>::quiet_NaN();
}
}
else{
#pragma omp critical
err = local_err;
}
}
}
return err;
}
template<class I, class J, class K, class T,class P=signed char>
int general_op(general_basis_core<I,P> *B,
const int n_op,
const char opstr[],
const int indx[],
const std::complex<double> A,
const bool full_basis,
const npy_intp Ns,
const I basis[],
const J n[],
const npy_intp basis_begin[],
const npy_intp basis_end[],
const int N_p,
K row[],
K col[],
T M[]
)
{
int err = 0;
#pragma omp parallel
{
const int N = B->get_N();
const int nt = B->get_nt();
const npy_intp chunk = std::max(Ns/(1000*omp_get_num_threads()),(npy_intp)1);
int g[__GENERAL_BASIS_CORE__max_nt];
double kk[__GENERAL_BASIS_CORE__max_nt];
for(int k=0;k<nt;k++)
kk[k] = 2.0*M_PI*B->qs[k]/B->pers[k];
#pragma omp for schedule(dynamic,chunk)
for(npy_intp i=0;i<Ns;i++){
if(err != 0){
continue;
}
I r = basis[i];
const I s = r;
std::complex<double> m = A;
int local_err = B->op(r,m,n_op,opstr,indx);
if(local_err == 0){
P sign = 1;
for(int k=0;k<nt;k++){
g[k]=0;
}
K j = i;
const bool not_diag = r != s;
if(r != basis[i]){
I rr = B->ref_state(r,g,sign);
if(full_basis){
j = Ns - (K)rr - 1;
}
else{
npy_intp rr_prefix = B->get_prefix(rr,N_p);
j = rep_position<K,I>(basis_begin,basis_end,basis,rr_prefix,rr);
}
}
if(j >= 0){
if(not_diag){
double q = 0;
for(int k=0;k<nt;k++){
q += kk[k]*g[k];
}
m *= sign * std::sqrt(double(n[j])/double(n[i])) * std::exp(std::complex<double>(0,-q));
}
local_err = type_checks(m,&M[i]);
col[i] = i;
row[i] = j;
}
else{
col[i] = i;
row[i] = i;
M[i] = std::numeric_limits<double>::quiet_NaN();
}
}
else{
#pragma omp critical
err = local_err;
}
}
}
return err;
}
*/
template<class I1,class J1,class I2,class J2,class K,class P=signed char>
int general_op_shift_sectors(general_basis_core<I1,P> *B_out,
const int n_op,
const char opstr[],
const int indx[],
const std::complex<double> A,
const npy_intp Ns_out,
const I1 basis_out[],
const J1 n_out[],
const npy_intp Ns_in,
const I2 basis_in[],
const J2 n_in[],
const npy_intp nvecs,
const K v_in[],
K v_out[])
{
int err = 0;
#pragma omp parallel firstprivate(A)
{
const int nt = B_out->get_nt();
const int nthread = omp_get_num_threads();
const npy_intp dyn_chunk = std::max(Ns_in/(1000*nthread),(npy_intp)1);
int g[__GENERAL_BASIS_CORE__max_nt];
double kk[__GENERAL_BASIS_CORE__max_nt];
for(int k=0;k<nt;k++){
kk[k] = (2.0*M_PI*B_out->qs[k])/B_out->pers[k];
}
#pragma omp for schedule(dynamic,dyn_chunk)
for(npy_intp i=0;i<Ns_in;i++){
std::complex<double> m = A;
const I1 s = (I1)basis_in[i];
I1 r = s;
int local_err = B_out->op(r,m,n_op,opstr,indx);
if(local_err == 0){
P sign = 1;
if(r != s){ // off-diagonal matrix element
for(int k=0;k<nt;k++){g[k]=0;}
r = B_out->ref_state(r,g,sign);
}
npy_intp j = rep_position<npy_intp,I1>(Ns_out,basis_out,r);
if(j>=0){ // ref_state is a representative
if(r != s){
double q = 0;
for(int k=0;k<nt;k++){
q += kk[k]*g[k];
}
m *= (double)sign * std::exp(std::complex<double>(0,-q));
}
m *= std::sqrt(double(n_out[j])/double(n_in[i]));
const K * v_in_col = v_in + i * nvecs;
K * v_out_row = v_out + j * nvecs;
local_err = type_checks<K>(m);
if(local_err && err==0){
#pragma omp atomic write
err = local_err;
}
for(int k=0;k<nvecs;k++){
const std::complex<double> M = mul(v_in_col[k],m);
atomic_add(M,&v_out_row[k]);
}
}
}
else if(err==0){
#pragma omp atomic write
err = local_err;
}
}
}
return err;
}
template<class I, class T, class P=signed char>
int general_op_bra_ket(general_basis_core<I,P> *B,
const int n_op,
const char opstr[],
const int indx[],
const std::complex<double> A,
const npy_intp Ns,
const I ket[], // col
I bra[], // row
T M[]
)
{
int err = 0;
#pragma omp parallel
{
const int nt = B->get_nt();
int g[__GENERAL_BASIS_CORE__max_nt];
#pragma omp for schedule(static)
for(npy_intp i=0;i<Ns;i++){
if(err != 0){
continue;
}
std::complex<double> m = A;
const I s = ket[i];
I r = ket[i];
int local_err = B->op(r,m,n_op,opstr,indx);
if(local_err == 0){
P sign = 1;
if(r != s){ // off-diagonal matrix element
r = B->ref_state(r,g,sign);
// use check_state to determine if state is a representative (same routine as in make-general_basis)
double norm_r = B->check_state(r);
npy_intp int_norm = norm_r;
if(!check_nan(norm_r) && int_norm > 0){ // ref_state is a representative
for(int k=0;k<nt;k++){
double q = (2.0*M_PI*B->qs[k]*g[k])/B->pers[k];
m *= std::exp(std::complex<double>(0,-q));
}
double norm_s = B->check_state(s);
m *= sign * std::sqrt(norm_r/norm_s);
local_err = type_checks(m,&M[i]); // assigns value to M[i]
bra[i] = r;
}
else{ // ref state in different particle number sector
M[i] = std::numeric_limits<T>::quiet_NaN();
bra[i] = s;
}
}
else{ // diagonal matrix element
m *= sign;
local_err = type_checks(m,&M[i]); // assigns value to M[i]
bra[i] = s;
}
}
else{
#pragma omp critical
err = local_err;
}
}
}
return err;
}
template<class I, class T, class P=signed char>
int general_op_bra_ket_pcon(general_basis_core<I,P> *B,
const int n_op,
const char opstr[],
const int indx[],
const std::complex<double> A,
const npy_intp Ns,
const std::set<std::vector<int>> &Np_set, // array with particle conserving sectors
const I ket[], // col
I bra[], // row
T M[]
)
{
int err = 0;
#pragma omp parallel
{
const std::set<std::vector<int>> Np_set_local = Np_set;
const int nt = B->get_nt();
int g[__GENERAL_BASIS_CORE__max_nt];
#pragma omp for schedule(static)
for(npy_intp i=0;i<Ns;i++){
if(err != 0){
continue;
}
std::complex<double> m = A;
const I s = ket[i];
I r = ket[i];
int local_err = B->op(r,m,n_op,opstr,indx);
if(local_err == 0){
P sign = 1;
if(r != s){ // off-diagonal matrix element
r = B->ref_state(r,g,sign);
bool pcon_bool = B->check_pcon(r,Np_set_local);
if(pcon_bool){ // reference state within same particle-number sector(s)
// use check_state to determine if state is a representative (same routine as in make-general_basis)
double norm_r = B->check_state(r);
if(!check_nan(norm_r) && norm_r > 0){ // ref_state is a representative
for(int k=0;k<nt;k++){
double q = (2.0*M_PI*B->qs[k]*g[k])/B->pers[k];
m *= std::exp(std::complex<double>(0,-q));
}
double norm_s = B->check_state(s);
m *= sign * std::sqrt(norm_r/norm_s);
local_err = type_checks(m,&M[i]); // assigns value to M[i]
bra[i] = r;
}
else{ // ref_state not a representative
M[i] = std::numeric_limits<T>::quiet_NaN();
bra[i] = s;
}
}
else{ // ref state in different particle number sector
M[i] = std::numeric_limits<T>::quiet_NaN();
bra[i] = s;
}
}
else{ // diagonal matrix element
for(int k=0;k<nt;k++){
double q = (2.0*M_PI*B->qs[k]*g[k])/B->pers[k];
m *= std::exp(std::complex<double>(0,-q));
}
m *= sign;
local_err = type_checks(m,&M[i]); // assigns value to M[i]
bra[i] = s;
}
}
else{
#pragma omp critical
err = local_err;
}
}
}
return err;
}
}
#endif
|
core_scamax.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_dzamax.c, normal z -> c, Fri Sep 28 17:38:20 2018
*
**/
#include <plasma_core_blas.h>
#include "plasma_types.h"
#include "core_lapack.h"
#include <math.h>
/******************************************************************************/
void plasma_core_omp_scamax(int colrow, int m, int n,
const plasma_complex32_t *A, int lda,
float *values,
plasma_sequence_t *sequence, plasma_request_t *request)
{
switch (colrow) {
case PlasmaColumnwise:
#pragma omp task depend(in:A[0:lda*n]) \
depend(out:values[0:n])
{
if (sequence->status == PlasmaSuccess) {
for (int j = 0; j < n; j++) {
values[j] = plasma_core_scabs1(A[lda*j]);
for (int i = 1; i < m; i++) {
float tmp = plasma_core_scabs1(A[lda*j+i]);
if (tmp > values[j])
values[j] = tmp;
}
}
}
}
break;
case PlasmaRowwise:
#pragma omp task depend(in:A[0:lda*n]) \
depend(out:values[0:m])
{
if (sequence->status == PlasmaSuccess) {
for (int i = 0; i < m; i++)
values[i] = plasma_core_scabs1(A[i]);
for (int j = 1; j < n; j++) {
for (int i = 0; i < m; i++) {
float tmp = plasma_core_scabs1(A[lda*j+i]);
if (tmp > values[i])
values[i] = tmp;
}
}
}
}
break;
}
}
|
resample.c | /*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% RRRR EEEEE SSSSS AAA M M PPPP L EEEEE %
% R R E SS A A MM MM P P L E %
% RRRR EEE SSS AAAAA M M M PPPP L EEE %
% R R E SS A A M M P L E %
% R R EEEEE SSSSS A A M M P LLLLL EEEEE %
% %
% %
% MagickCore Pixel Resampling Methods %
% %
% Software Design %
% Cristy %
% Anthony Thyssen %
% August 2007 %
% %
% %
% Copyright 1999-2017 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://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 "MagickCore/studio.h"
#include "MagickCore/artifact.h"
#include "MagickCore/color-private.h"
#include "MagickCore/cache.h"
#include "MagickCore/draw.h"
#include "MagickCore/exception-private.h"
#include "MagickCore/gem.h"
#include "MagickCore/image.h"
#include "MagickCore/image-private.h"
#include "MagickCore/log.h"
#include "MagickCore/magick.h"
#include "MagickCore/memory_.h"
#include "MagickCore/memory-private.h"
#include "MagickCore/pixel.h"
#include "MagickCore/pixel-accessor.h"
#include "MagickCore/quantum.h"
#include "MagickCore/random_.h"
#include "MagickCore/resample.h"
#include "MagickCore/resize.h"
#include "MagickCore/resize-private.h"
#include "MagickCore/resource_.h"
#include "MagickCore/token.h"
#include "MagickCore/transform.h"
#include "MagickCore/signature-private.h"
#include "MagickCore/utility.h"
#include "MagickCore/utility-private.h"
#include "MagickCore/option.h"
/*
EWA Resampling Options
*/
/* select ONE resampling method */
#define EWA 1 /* Normal EWA handling - raw or clamped */
/* if 0 then use "High Quality EWA" */
#define EWA_CLAMP 1 /* EWA Clamping from Nicolas Robidoux */
#define FILTER_LUT 1 /* Use a LUT rather then direct filter calls */
/* output debugging information */
#define DEBUG_ELLIPSE 0 /* output ellipse info for debug */
#define DEBUG_HIT_MISS 0 /* output hit/miss pixels (as gnuplot commands) */
#define DEBUG_NO_PIXEL_HIT 0 /* Make pixels that fail to hit anything - RED */
#if ! FILTER_DIRECT
#define WLUT_WIDTH 1024 /* size of the filter cache */
#endif
/*
Typedef declarations.
*/
struct _ResampleFilter
{
CacheView
*view;
Image
*image;
ExceptionInfo
*exception;
MagickBooleanType
debug;
/* Information about image being resampled */
ssize_t
image_area;
PixelInterpolateMethod
interpolate;
VirtualPixelMethod
virtual_pixel;
FilterType
filter;
/* processing settings needed */
MagickBooleanType
limit_reached,
do_interpolate,
average_defined;
PixelInfo
average_pixel;
/* current ellipitical area being resampled around center point */
double
A, B, C,
Vlimit, Ulimit, Uwidth, slope;
#if FILTER_LUT
/* LUT of weights for filtered average in elliptical area */
double
filter_lut[WLUT_WIDTH];
#else
/* Use a Direct call to the filter functions */
ResizeFilter
*filter_def;
double
F;
#endif
/* the practical working support of the filter */
double
support;
size_t
signature;
};
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% A c q u i r e R e s a m p l e I n f o %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% AcquireResampleFilter() initializes the information resample needs do to a
% scaled lookup of a color from an image, using area sampling.
%
% The algorithm is based on a Elliptical Weighted Average, where the pixels
% found in a large elliptical area is averaged together according to a
% weighting (filter) function. For more details see "Fundamentals of Texture
% Mapping and Image Warping" a master's thesis by Paul.S.Heckbert, June 17,
% 1989. Available for free from, http://www.cs.cmu.edu/~ph/
%
% As EWA resampling (or any sort of resampling) can require a lot of
% calculations to produce a distorted scaling of the source image for each
% output pixel, the ResampleFilter structure generated holds that information
% between individual image resampling.
%
% This function will make the appropriate AcquireCacheView() calls
% to view the image, calling functions do not need to open a cache view.
%
% Usage Example...
% resample_filter=AcquireResampleFilter(image,exception);
% SetResampleFilter(resample_filter, GaussianFilter);
% for (y=0; y < (ssize_t) image->rows; y++) {
% for (x=0; x < (ssize_t) image->columns; x++) {
% u= ....; v= ....;
% ScaleResampleFilter(resample_filter, ... scaling vectors ...);
% (void) ResamplePixelColor(resample_filter,u,v,&pixel);
% ... assign resampled pixel value ...
% }
% }
% DestroyResampleFilter(resample_filter);
%
% The format of the AcquireResampleFilter method is:
%
% ResampleFilter *AcquireResampleFilter(const Image *image,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport ResampleFilter *AcquireResampleFilter(const Image *image,
ExceptionInfo *exception)
{
register ResampleFilter
*resample_filter;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
resample_filter=(ResampleFilter *) AcquireCriticalMemory(sizeof(
*resample_filter));
(void) ResetMagickMemory(resample_filter,0,sizeof(*resample_filter));
resample_filter->exception=exception;
resample_filter->image=ReferenceImage((Image *) image);
resample_filter->view=AcquireVirtualCacheView(resample_filter->image,
exception);
resample_filter->debug=IsEventLogging();
resample_filter->image_area=(ssize_t) (image->columns*image->rows);
resample_filter->average_defined=MagickFalse;
resample_filter->signature=MagickCoreSignature;
SetResampleFilter(resample_filter,image->filter);
(void) SetResampleFilterInterpolateMethod(resample_filter,image->interpolate);
(void) SetResampleFilterVirtualPixelMethod(resample_filter,
GetImageVirtualPixelMethod(image));
return(resample_filter);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% D e s t r o y R e s a m p l e I n f o %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% DestroyResampleFilter() finalizes and cleans up the resampling
% resample_filter as returned by AcquireResampleFilter(), freeing any memory
% or other information as needed.
%
% The format of the DestroyResampleFilter method is:
%
% ResampleFilter *DestroyResampleFilter(ResampleFilter *resample_filter)
%
% A description of each parameter follows:
%
% o resample_filter: resampling information structure
%
*/
MagickExport ResampleFilter *DestroyResampleFilter(
ResampleFilter *resample_filter)
{
assert(resample_filter != (ResampleFilter *) NULL);
assert(resample_filter->signature == MagickCoreSignature);
assert(resample_filter->image != (Image *) NULL);
if (resample_filter->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",
resample_filter->image->filename);
resample_filter->view=DestroyCacheView(resample_filter->view);
resample_filter->image=DestroyImage(resample_filter->image);
#if ! FILTER_LUT
resample_filter->filter_def=DestroyResizeFilter(resample_filter->filter_def);
#endif
resample_filter->signature=(~MagickCoreSignature);
resample_filter=(ResampleFilter *) RelinquishMagickMemory(resample_filter);
return(resample_filter);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% R e s a m p l e P i x e l C o l o r %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ResamplePixelColor() samples the pixel values surrounding the location
% given using an elliptical weighted average, at the scale previously
% calculated, and in the most efficent manner possible for the
% VirtualPixelMethod setting.
%
% The format of the ResamplePixelColor method is:
%
% MagickBooleanType ResamplePixelColor(ResampleFilter *resample_filter,
% const double u0,const double v0,PixelInfo *pixel,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o resample_filter: the resample filter.
%
% o u0,v0: A double representing the center of the area to resample,
% The distortion transformed transformed x,y coordinate.
%
% o pixel: the resampled pixel is returned here.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport MagickBooleanType ResamplePixelColor(
ResampleFilter *resample_filter,const double u0,const double v0,
PixelInfo *pixel,ExceptionInfo *exception)
{
MagickBooleanType
status;
ssize_t u,v, v1, v2, uw, hit;
double u1;
double U,V,Q,DQ,DDQ;
double divisor_c,divisor_m;
register double weight;
register const Quantum *pixels;
assert(resample_filter != (ResampleFilter *) NULL);
assert(resample_filter->signature == MagickCoreSignature);
status=MagickTrue;
/* GetPixelInfo(resample_filter->image,pixel); */
if ( resample_filter->do_interpolate ) {
status=InterpolatePixelInfo(resample_filter->image,resample_filter->view,
resample_filter->interpolate,u0,v0,pixel,resample_filter->exception);
return(status);
}
#if DEBUG_ELLIPSE
(void) FormatLocaleFile(stderr, "u0=%lf; v0=%lf;\n", u0, v0);
#endif
/*
Does resample area Miss the image Proper?
If and that area a simple solid color - then simply return that color!
This saves a lot of calculation when resampling outside the bounds of
the source image.
However it probably should be expanded to image bounds plus the filters
scaled support size.
*/
hit = 0;
switch ( resample_filter->virtual_pixel ) {
case BackgroundVirtualPixelMethod:
case TransparentVirtualPixelMethod:
case BlackVirtualPixelMethod:
case GrayVirtualPixelMethod:
case WhiteVirtualPixelMethod:
case MaskVirtualPixelMethod:
if ( resample_filter->limit_reached
|| u0 + resample_filter->Ulimit < 0.0
|| u0 - resample_filter->Ulimit > (double) resample_filter->image->columns-1.0
|| v0 + resample_filter->Vlimit < 0.0
|| v0 - resample_filter->Vlimit > (double) resample_filter->image->rows-1.0
)
hit++;
break;
case UndefinedVirtualPixelMethod:
case EdgeVirtualPixelMethod:
if ( ( u0 + resample_filter->Ulimit < 0.0 && v0 + resample_filter->Vlimit < 0.0 )
|| ( u0 + resample_filter->Ulimit < 0.0
&& v0 - resample_filter->Vlimit > (double) resample_filter->image->rows-1.0 )
|| ( u0 - resample_filter->Ulimit > (double) resample_filter->image->columns-1.0
&& v0 + resample_filter->Vlimit < 0.0 )
|| ( u0 - resample_filter->Ulimit > (double) resample_filter->image->columns-1.0
&& v0 - resample_filter->Vlimit > (double) resample_filter->image->rows-1.0 )
)
hit++;
break;
case HorizontalTileVirtualPixelMethod:
if ( v0 + resample_filter->Vlimit < 0.0
|| v0 - resample_filter->Vlimit > (double) resample_filter->image->rows-1.0
)
hit++; /* outside the horizontally tiled images. */
break;
case VerticalTileVirtualPixelMethod:
if ( u0 + resample_filter->Ulimit < 0.0
|| u0 - resample_filter->Ulimit > (double) resample_filter->image->columns-1.0
)
hit++; /* outside the vertically tiled images. */
break;
case DitherVirtualPixelMethod:
if ( ( u0 + resample_filter->Ulimit < -32.0 && v0 + resample_filter->Vlimit < -32.0 )
|| ( u0 + resample_filter->Ulimit < -32.0
&& v0 - resample_filter->Vlimit > (double) resample_filter->image->rows+31.0 )
|| ( u0 - resample_filter->Ulimit > (double) resample_filter->image->columns+31.0
&& v0 + resample_filter->Vlimit < -32.0 )
|| ( u0 - resample_filter->Ulimit > (double) resample_filter->image->columns+31.0
&& v0 - resample_filter->Vlimit > (double) resample_filter->image->rows+31.0 )
)
hit++;
break;
case TileVirtualPixelMethod:
case MirrorVirtualPixelMethod:
case RandomVirtualPixelMethod:
case HorizontalTileEdgeVirtualPixelMethod:
case VerticalTileEdgeVirtualPixelMethod:
case CheckerTileVirtualPixelMethod:
/* resampling of area is always needed - no VP limits */
break;
}
if ( hit ) {
/* The area being resampled is simply a solid color
* just return a single lookup color.
*
* Should this return the users requested interpolated color?
*/
status=InterpolatePixelInfo(resample_filter->image,resample_filter->view,
IntegerInterpolatePixel,u0,v0,pixel,resample_filter->exception);
return(status);
}
/*
When Scaling limits reached, return an 'averaged' result.
*/
if ( resample_filter->limit_reached ) {
switch ( resample_filter->virtual_pixel ) {
/* This is always handled by the above, so no need.
case BackgroundVirtualPixelMethod:
case ConstantVirtualPixelMethod:
case TransparentVirtualPixelMethod:
case GrayVirtualPixelMethod,
case WhiteVirtualPixelMethod
case MaskVirtualPixelMethod:
*/
case UndefinedVirtualPixelMethod:
case EdgeVirtualPixelMethod:
case DitherVirtualPixelMethod:
case HorizontalTileEdgeVirtualPixelMethod:
case VerticalTileEdgeVirtualPixelMethod:
/* We need an average edge pixel, from the correct edge!
How should I calculate an average edge color?
Just returning an averaged neighbourhood,
works well in general, but falls down for TileEdge methods.
This needs to be done properly!!!!!!
*/
status=InterpolatePixelInfo(resample_filter->image,
resample_filter->view,AverageInterpolatePixel,u0,v0,pixel,
resample_filter->exception);
break;
case HorizontalTileVirtualPixelMethod:
case VerticalTileVirtualPixelMethod:
/* just return the background pixel - Is there more direct way? */
status=InterpolatePixelInfo(resample_filter->image,
resample_filter->view,IntegerInterpolatePixel,-1.0,-1.0,pixel,
resample_filter->exception);
break;
case TileVirtualPixelMethod:
case MirrorVirtualPixelMethod:
case RandomVirtualPixelMethod:
case CheckerTileVirtualPixelMethod:
default:
/* generate a average color of the WHOLE image */
if ( resample_filter->average_defined == MagickFalse ) {
Image
*average_image;
CacheView
*average_view;
GetPixelInfo(resample_filter->image,(PixelInfo *)
&resample_filter->average_pixel);
resample_filter->average_defined=MagickTrue;
/* Try to get an averaged pixel color of whole image */
average_image=ResizeImage(resample_filter->image,1,1,BoxFilter,
resample_filter->exception);
if (average_image == (Image *) NULL)
{
*pixel=resample_filter->average_pixel; /* FAILED */
break;
}
average_view=AcquireVirtualCacheView(average_image,exception);
pixels=GetCacheViewVirtualPixels(average_view,0,0,1,1,
resample_filter->exception);
if (pixels == (const Quantum *) NULL) {
average_view=DestroyCacheView(average_view);
average_image=DestroyImage(average_image);
*pixel=resample_filter->average_pixel; /* FAILED */
break;
}
GetPixelInfoPixel(resample_filter->image,pixels,
&(resample_filter->average_pixel));
average_view=DestroyCacheView(average_view);
average_image=DestroyImage(average_image);
if ( resample_filter->virtual_pixel == CheckerTileVirtualPixelMethod )
{
/* CheckerTile is a alpha blend of the image's average pixel
color and the current background color */
/* image's average pixel color */
weight = QuantumScale*((double)
resample_filter->average_pixel.alpha);
resample_filter->average_pixel.red *= weight;
resample_filter->average_pixel.green *= weight;
resample_filter->average_pixel.blue *= weight;
divisor_c = weight;
/* background color */
weight = QuantumScale*((double)
resample_filter->image->background_color.alpha);
resample_filter->average_pixel.red +=
weight*resample_filter->image->background_color.red;
resample_filter->average_pixel.green +=
weight*resample_filter->image->background_color.green;
resample_filter->average_pixel.blue +=
weight*resample_filter->image->background_color.blue;
resample_filter->average_pixel.alpha +=
resample_filter->image->background_color.alpha;
divisor_c += weight;
/* alpha blend */
resample_filter->average_pixel.red /= divisor_c;
resample_filter->average_pixel.green /= divisor_c;
resample_filter->average_pixel.blue /= divisor_c;
resample_filter->average_pixel.alpha /= 2; /* 50% blend */
}
}
*pixel=resample_filter->average_pixel;
break;
}
return(status);
}
/*
Initialize weighted average data collection
*/
hit = 0;
divisor_c = 0.0;
divisor_m = 0.0;
pixel->red = pixel->green = pixel->blue = 0.0;
if (pixel->colorspace == CMYKColorspace)
pixel->black = 0.0;
if (pixel->alpha_trait != UndefinedPixelTrait)
pixel->alpha = 0.0;
/*
Determine the parellelogram bounding box fitted to the ellipse
centered at u0,v0. This area is bounding by the lines...
*/
v1 = (ssize_t)ceil(v0 - resample_filter->Vlimit); /* range of scan lines */
v2 = (ssize_t)floor(v0 + resample_filter->Vlimit);
/* scan line start and width accross the parallelogram */
u1 = u0 + (v1-v0)*resample_filter->slope - resample_filter->Uwidth;
uw = (ssize_t)(2.0*resample_filter->Uwidth)+1;
#if DEBUG_ELLIPSE
(void) FormatLocaleFile(stderr, "v1=%ld; v2=%ld\n", (long)v1, (long)v2);
(void) FormatLocaleFile(stderr, "u1=%ld; uw=%ld\n", (long)u1, (long)uw);
#else
# define DEBUG_HIT_MISS 0 /* only valid if DEBUG_ELLIPSE is enabled */
#endif
/*
Do weighted resampling of all pixels, within the scaled ellipse,
bound by a Parellelogram fitted to the ellipse.
*/
DDQ = 2*resample_filter->A;
for( v=v1; v<=v2; v++ ) {
#if DEBUG_HIT_MISS
long uu = ceil(u1); /* actual pixel location (for debug only) */
(void) FormatLocaleFile(stderr, "# scan line from pixel %ld, %ld\n", (long)uu, (long)v);
#endif
u = (ssize_t)ceil(u1); /* first pixel in scanline */
u1 += resample_filter->slope; /* start of next scan line */
/* location of this first pixel, relative to u0,v0 */
U = (double)u-u0;
V = (double)v-v0;
/* Q = ellipse quotent ( if Q<F then pixel is inside ellipse) */
Q = (resample_filter->A*U + resample_filter->B*V)*U + resample_filter->C*V*V;
DQ = resample_filter->A*(2.0*U+1) + resample_filter->B*V;
/* get the scanline of pixels for this v */
pixels=GetCacheViewVirtualPixels(resample_filter->view,u,v,(size_t) uw,
1,resample_filter->exception);
if (pixels == (const Quantum *) NULL)
return(MagickFalse);
/* count up the weighted pixel colors */
for( u=0; u<uw; u++ ) {
#if FILTER_LUT
/* Note that the ellipse has been pre-scaled so F = WLUT_WIDTH */
if ( Q < (double)WLUT_WIDTH ) {
weight = resample_filter->filter_lut[(int)Q];
#else
/* Note that the ellipse has been pre-scaled so F = support^2 */
if ( Q < (double)resample_filter->F ) {
weight = GetResizeFilterWeight(resample_filter->filter_def,
sqrt(Q)); /* a SquareRoot! Arrggghhhhh... */
#endif
pixel->alpha += weight*GetPixelAlpha(resample_filter->image,pixels);
divisor_m += weight;
if (pixel->alpha_trait != UndefinedPixelTrait)
weight *= QuantumScale*((double) GetPixelAlpha(resample_filter->image,pixels));
pixel->red += weight*GetPixelRed(resample_filter->image,pixels);
pixel->green += weight*GetPixelGreen(resample_filter->image,pixels);
pixel->blue += weight*GetPixelBlue(resample_filter->image,pixels);
if (pixel->colorspace == CMYKColorspace)
pixel->black += weight*GetPixelBlack(resample_filter->image,pixels);
divisor_c += weight;
hit++;
#if DEBUG_HIT_MISS
/* mark the pixel according to hit/miss of the ellipse */
(void) FormatLocaleFile(stderr, "set arrow from %lf,%lf to %lf,%lf nohead ls 3\n",
(long)uu-.1,(double)v-.1,(long)uu+.1,(long)v+.1);
(void) FormatLocaleFile(stderr, "set arrow from %lf,%lf to %lf,%lf nohead ls 3\n",
(long)uu+.1,(double)v-.1,(long)uu-.1,(long)v+.1);
} else {
(void) FormatLocaleFile(stderr, "set arrow from %lf,%lf to %lf,%lf nohead ls 1\n",
(long)uu-.1,(double)v-.1,(long)uu+.1,(long)v+.1);
(void) FormatLocaleFile(stderr, "set arrow from %lf,%lf to %lf,%lf nohead ls 1\n",
(long)uu+.1,(double)v-.1,(long)uu-.1,(long)v+.1);
}
uu++;
#else
}
#endif
pixels+=GetPixelChannels(resample_filter->image);
Q += DQ;
DQ += DDQ;
}
}
#if DEBUG_ELLIPSE
(void) FormatLocaleFile(stderr, "Hit=%ld; Total=%ld;\n", (long)hit, (long)uw*(v2-v1) );
#endif
/*
Result sanity check -- this should NOT happen
*/
if ( hit == 0 || divisor_m <= MagickEpsilon || divisor_c <= MagickEpsilon ) {
/* not enough pixels, or bad weighting in resampling,
resort to direct interpolation */
#if DEBUG_NO_PIXEL_HIT
pixel->alpha = pixel->red = pixel->green = pixel->blue = 0;
pixel->red = QuantumRange; /* show pixels for which EWA fails */
#else
status=InterpolatePixelInfo(resample_filter->image,
resample_filter->view,resample_filter->interpolate,u0,v0,pixel,
resample_filter->exception);
#endif
return status;
}
/*
Finialize results of resampling
*/
divisor_m = 1.0/divisor_m;
if (pixel->alpha_trait != UndefinedPixelTrait)
pixel->alpha = (double) ClampToQuantum(divisor_m*pixel->alpha);
divisor_c = 1.0/divisor_c;
pixel->red = (double) ClampToQuantum(divisor_c*pixel->red);
pixel->green = (double) ClampToQuantum(divisor_c*pixel->green);
pixel->blue = (double) ClampToQuantum(divisor_c*pixel->blue);
if (pixel->colorspace == CMYKColorspace)
pixel->black = (double) ClampToQuantum(divisor_c*pixel->black);
return(MagickTrue);
}
#if EWA && EWA_CLAMP
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
- C l a m p U p A x e s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ClampUpAxes() function converts the input vectors into a major and
% minor axis unit vectors, and their magnitude. This allows us to
% ensure that the ellipse generated is never smaller than the unit
% circle and thus never too small for use in EWA resampling.
%
% This purely mathematical 'magic' was provided by Professor Nicolas
% Robidoux and his Masters student Chantal Racette.
%
% Reference: "We Recommend Singular Value Decomposition", David Austin
% http://www.ams.org/samplings/feature-column/fcarc-svd
%
% By generating major and minor axis vectors, we can actually use the
% ellipse in its "canonical form", by remapping the dx,dy of the
% sampled point into distances along the major and minor axis unit
% vectors.
%
% Reference: http://en.wikipedia.org/wiki/Ellipse#Canonical_form
*/
static inline void ClampUpAxes(const double dux,
const double dvx,
const double duy,
const double dvy,
double *major_mag,
double *minor_mag,
double *major_unit_x,
double *major_unit_y,
double *minor_unit_x,
double *minor_unit_y)
{
/*
* ClampUpAxes takes an input 2x2 matrix
*
* [ a b ] = [ dux duy ]
* [ c d ] = [ dvx dvy ]
*
* and computes from it the major and minor axis vectors [major_x,
* major_y] and [minor_x,minor_y] of the smallest ellipse containing
* both the unit disk and the ellipse which is the image of the unit
* disk by the linear transformation
*
* [ dux duy ] [S] = [s]
* [ dvx dvy ] [T] = [t]
*
* (The vector [S,T] is the difference between a position in output
* space and [X,Y]; the vector [s,t] is the difference between a
* position in input space and [x,y].)
*/
/*
* Output:
*
* major_mag is the half-length of the major axis of the "new"
* ellipse.
*
* minor_mag is the half-length of the minor axis of the "new"
* ellipse.
*
* major_unit_x is the x-coordinate of the major axis direction vector
* of both the "old" and "new" ellipses.
*
* major_unit_y is the y-coordinate of the major axis direction vector.
*
* minor_unit_x is the x-coordinate of the minor axis direction vector.
*
* minor_unit_y is the y-coordinate of the minor axis direction vector.
*
* Unit vectors are useful for computing projections, in particular,
* to compute the distance between a point in output space and the
* center of a unit disk in output space, using the position of the
* corresponding point [s,t] in input space. Following the clamping,
* the square of this distance is
*
* ( ( s * major_unit_x + t * major_unit_y ) / major_mag )^2
* +
* ( ( s * minor_unit_x + t * minor_unit_y ) / minor_mag )^2
*
* If such distances will be computed for many [s,t]'s, it makes
* sense to actually compute the reciprocal of major_mag and
* minor_mag and multiply them by the above unit lengths.
*
* Now, if you want to modify the input pair of tangent vectors so
* that it defines the modified ellipse, all you have to do is set
*
* newdux = major_mag * major_unit_x
* newdvx = major_mag * major_unit_y
* newduy = minor_mag * minor_unit_x = minor_mag * -major_unit_y
* newdvy = minor_mag * minor_unit_y = minor_mag * major_unit_x
*
* and use these tangent vectors as if they were the original ones.
* Usually, this is a drastic change in the tangent vectors even if
* the singular values are not clamped; for example, the minor axis
* vector always points in a direction which is 90 degrees
* counterclockwise from the direction of the major axis vector.
*/
/*
* Discussion:
*
* GOAL: Fix things so that the pullback, in input space, of a disk
* of radius r in output space is an ellipse which contains, at
* least, a disc of radius r. (Make this hold for any r>0.)
*
* ESSENCE OF THE METHOD: Compute the product of the first two
* factors of an SVD of the linear transformation defining the
* ellipse and make sure that both its columns have norm at least 1.
* Because rotations and reflexions map disks to themselves, it is
* not necessary to compute the third (rightmost) factor of the SVD.
*
* DETAILS: Find the singular values and (unit) left singular
* vectors of Jinv, clampling up the singular values to 1, and
* multiply the unit left singular vectors by the new singular
* values in order to get the minor and major ellipse axis vectors.
*
* Image resampling context:
*
* The Jacobian matrix of the transformation at the output point
* under consideration is defined as follows:
*
* Consider the transformation (x,y) -> (X,Y) from input locations
* to output locations. (Anthony Thyssen, elsewhere in resample.c,
* uses the notation (u,v) -> (x,y).)
*
* The Jacobian matrix of the transformation at (x,y) is equal to
*
* J = [ A, B ] = [ dX/dx, dX/dy ]
* [ C, D ] [ dY/dx, dY/dy ]
*
* that is, the vector [A,C] is the tangent vector corresponding to
* input changes in the horizontal direction, and the vector [B,D]
* is the tangent vector corresponding to input changes in the
* vertical direction.
*
* In the context of resampling, it is natural to use the inverse
* Jacobian matrix Jinv because resampling is generally performed by
* pulling pixel locations in the output image back to locations in
* the input image. Jinv is
*
* Jinv = [ a, b ] = [ dx/dX, dx/dY ]
* [ c, d ] [ dy/dX, dy/dY ]
*
* Note: Jinv can be computed from J with the following matrix
* formula:
*
* Jinv = 1/(A*D-B*C) [ D, -B ]
* [ -C, A ]
*
* What we do is modify Jinv so that it generates an ellipse which
* is as close as possible to the original but which contains the
* unit disk. This can be accomplished as follows:
*
* Let
*
* Jinv = U Sigma V^T
*
* be an SVD decomposition of Jinv. (The SVD is not unique, but the
* final ellipse does not depend on the particular SVD.)
*
* We could clamp up the entries of the diagonal matrix Sigma so
* that they are at least 1, and then set
*
* Jinv = U newSigma V^T.
*
* However, we do not need to compute V for the following reason:
* V^T is an orthogonal matrix (that is, it represents a combination
* of rotations and reflexions) so that it maps the unit circle to
* itself. For this reason, the exact value of V does not affect the
* final ellipse, and we can choose V to be the identity
* matrix. This gives
*
* Jinv = U newSigma.
*
* In the end, we return the two diagonal entries of newSigma
* together with the two columns of U.
*/
/*
* ClampUpAxes was written by Nicolas Robidoux and Chantal Racette
* of Laurentian University with insightful suggestions from Anthony
* Thyssen and funding from the National Science and Engineering
* Research Council of Canada. It is distinguished from its
* predecessors by its efficient handling of degenerate cases.
*
* The idea of clamping up the EWA ellipse's major and minor axes so
* that the result contains the reconstruction kernel filter support
* is taken from Andreas Gustaffson's Masters thesis "Interactive
* Image Warping", Helsinki University of Technology, Faculty of
* Information Technology, 59 pages, 1993 (see Section 3.6).
*
* The use of the SVD to clamp up the singular values of the
* Jacobian matrix of the pullback transformation for EWA resampling
* is taken from the astrophysicist Craig DeForest. It is
* implemented in his PDL::Transform code (PDL = Perl Data
* Language).
*/
const double a = dux;
const double b = duy;
const double c = dvx;
const double d = dvy;
/*
* n is the matrix Jinv * transpose(Jinv). Eigenvalues of n are the
* squares of the singular values of Jinv.
*/
const double aa = a*a;
const double bb = b*b;
const double cc = c*c;
const double dd = d*d;
/*
* Eigenvectors of n are left singular vectors of Jinv.
*/
const double n11 = aa+bb;
const double n12 = a*c+b*d;
const double n21 = n12;
const double n22 = cc+dd;
const double det = a*d-b*c;
const double twice_det = det+det;
const double frobenius_squared = n11+n22;
const double discriminant =
(frobenius_squared+twice_det)*(frobenius_squared-twice_det);
/*
* In exact arithmetic, discriminant can't be negative. In floating
* point, it can, because of the bad conditioning of SVD
* decompositions done through the associated normal matrix.
*/
const double sqrt_discriminant =
sqrt(discriminant > 0.0 ? discriminant : 0.0);
/*
* s1 is the largest singular value of the inverse Jacobian
* matrix. In other words, its reciprocal is the smallest singular
* value of the Jacobian matrix itself.
* If s1 = 0, both singular values are 0, and any orthogonal pair of
* left and right factors produces a singular decomposition of Jinv.
*/
/*
* Initially, we only compute the squares of the singular values.
*/
const double s1s1 = 0.5*(frobenius_squared+sqrt_discriminant);
/*
* s2 the smallest singular value of the inverse Jacobian
* matrix. Its reciprocal is the largest singular value of the
* Jacobian matrix itself.
*/
const double s2s2 = 0.5*(frobenius_squared-sqrt_discriminant);
const double s1s1minusn11 = s1s1-n11;
const double s1s1minusn22 = s1s1-n22;
/*
* u1, the first column of the U factor of a singular decomposition
* of Jinv, is a (non-normalized) left singular vector corresponding
* to s1. It has entries u11 and u21. We compute u1 from the fact
* that it is an eigenvector of n corresponding to the eigenvalue
* s1^2.
*/
const double s1s1minusn11_squared = s1s1minusn11*s1s1minusn11;
const double s1s1minusn22_squared = s1s1minusn22*s1s1minusn22;
/*
* The following selects the largest row of n-s1^2 I as the one
* which is used to find the eigenvector. If both s1^2-n11 and
* s1^2-n22 are zero, n-s1^2 I is the zero matrix. In that case,
* any vector is an eigenvector; in addition, norm below is equal to
* zero, and, in exact arithmetic, this is the only case in which
* norm = 0. So, setting u1 to the simple but arbitrary vector [1,0]
* if norm = 0 safely takes care of all cases.
*/
const double temp_u11 =
( (s1s1minusn11_squared>=s1s1minusn22_squared) ? n12 : s1s1minusn22 );
const double temp_u21 =
( (s1s1minusn11_squared>=s1s1minusn22_squared) ? s1s1minusn11 : n21 );
const double norm = sqrt(temp_u11*temp_u11+temp_u21*temp_u21);
/*
* Finalize the entries of first left singular vector (associated
* with the largest singular value).
*/
const double u11 = ( (norm>0.0) ? temp_u11/norm : 1.0 );
const double u21 = ( (norm>0.0) ? temp_u21/norm : 0.0 );
/*
* Clamp the singular values up to 1.
*/
*major_mag = ( (s1s1<=1.0) ? 1.0 : sqrt(s1s1) );
*minor_mag = ( (s2s2<=1.0) ? 1.0 : sqrt(s2s2) );
/*
* Return the unit major and minor axis direction vectors.
*/
*major_unit_x = u11;
*major_unit_y = u21;
*minor_unit_x = -u21;
*minor_unit_y = u11;
}
#endif
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S c a l e R e s a m p l e F i l t e r %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ScaleResampleFilter() does all the calculations needed to resample an image
% at a specific scale, defined by two scaling vectors. This not using
% a orthogonal scaling, but two distorted scaling vectors, to allow the
% generation of a angled ellipse.
%
% As only two deritive scaling vectors are used the center of the ellipse
% must be the center of the lookup. That is any curvature that the
% distortion may produce is discounted.
%
% The input vectors are produced by either finding the derivitives of the
% distortion function, or the partial derivitives from a distortion mapping.
% They do not need to be the orthogonal dx,dy scaling vectors, but can be
% calculated from other derivatives. For example you could use dr,da/r
% polar coordinate vector scaling vectors
%
% If u,v = DistortEquation(x,y) OR u = Fu(x,y); v = Fv(x,y)
% Then the scaling vectors are determined from the deritives...
% du/dx, dv/dx and du/dy, dv/dy
% If the resulting scaling vectors is othogonally aligned then...
% dv/dx = 0 and du/dy = 0
% Producing an othogonally alligned ellipse in source space for the area to
% be resampled.
%
% Note that scaling vectors are different to argument order. Argument order
% is the general order the deritives are extracted from the distortion
% equations, and not the scaling vectors. As such the middle two vaules
% may be swapped from what you expect. Caution is advised.
%
% WARNING: It is assumed that any SetResampleFilter() method call will
% always be performed before the ScaleResampleFilter() method, so that the
% size of the ellipse will match the support for the resampling filter being
% used.
%
% The format of the ScaleResampleFilter method is:
%
% void ScaleResampleFilter(const ResampleFilter *resample_filter,
% const double dux,const double duy,const double dvx,const double dvy)
%
% A description of each parameter follows:
%
% o resample_filter: the resampling resample_filterrmation defining the
% image being resampled
%
% o dux,duy,dvx,dvy:
% The deritives or scaling vectors defining the EWA ellipse.
% NOTE: watch the order, which is based on the order deritives
% are usally determined from distortion equations (see above).
% The middle two values may need to be swapped if you are thinking
% in terms of scaling vectors.
%
*/
MagickExport void ScaleResampleFilter(ResampleFilter *resample_filter,
const double dux,const double duy,const double dvx,const double dvy)
{
double A,B,C,F;
assert(resample_filter != (ResampleFilter *) NULL);
assert(resample_filter->signature == MagickCoreSignature);
resample_filter->limit_reached = MagickFalse;
/* A 'point' filter forces use of interpolation instead of area sampling */
if ( resample_filter->filter == PointFilter )
return; /* EWA turned off - nothing to do */
#if DEBUG_ELLIPSE
(void) FormatLocaleFile(stderr, "# -----\n" );
(void) FormatLocaleFile(stderr, "dux=%lf; dvx=%lf; duy=%lf; dvy=%lf;\n",
dux, dvx, duy, dvy);
#endif
/* Find Ellipse Coefficents such that
A*u^2 + B*u*v + C*v^2 = F
With u,v relative to point around which we are resampling.
And the given scaling dx,dy vectors in u,v space
du/dx,dv/dx and du/dy,dv/dy
*/
#if EWA
/* Direct conversion of derivatives into elliptical coefficients
However when magnifying images, the scaling vectors will be small
resulting in a ellipse that is too small to sample properly.
As such we need to clamp the major/minor axis to a minumum of 1.0
to prevent it getting too small.
*/
#if EWA_CLAMP
{ double major_mag,
minor_mag,
major_x,
major_y,
minor_x,
minor_y;
ClampUpAxes(dux,dvx,duy,dvy, &major_mag, &minor_mag,
&major_x, &major_y, &minor_x, &minor_y);
major_x *= major_mag; major_y *= major_mag;
minor_x *= minor_mag; minor_y *= minor_mag;
#if DEBUG_ELLIPSE
(void) FormatLocaleFile(stderr, "major_x=%lf; major_y=%lf; minor_x=%lf; minor_y=%lf;\n",
major_x, major_y, minor_x, minor_y);
#endif
A = major_y*major_y+minor_y*minor_y;
B = -2.0*(major_x*major_y+minor_x*minor_y);
C = major_x*major_x+minor_x*minor_x;
F = major_mag*minor_mag;
F *= F; /* square it */
}
#else /* raw unclamped EWA */
A = dvx*dvx+dvy*dvy;
B = -2.0*(dux*dvx+duy*dvy);
C = dux*dux+duy*duy;
F = dux*dvy-duy*dvx;
F *= F; /* square it */
#endif /* EWA_CLAMP */
#else /* HQ_EWA */
/*
This Paul Heckbert's "Higher Quality EWA" formula, from page 60 in his
thesis, which adds a unit circle to the elliptical area so as to do both
Reconstruction and Prefiltering of the pixels in the resampling. It also
means it is always likely to have at least 4 pixels within the area of the
ellipse, for weighted averaging. No scaling will result with F == 4.0 and
a circle of radius 2.0, and F smaller than this means magnification is
being used.
NOTE: This method produces a very blury result at near unity scale while
producing perfect results for strong minitification and magnifications.
However filter support is fixed to 2.0 (no good for Windowed Sinc filters)
*/
A = dvx*dvx+dvy*dvy+1;
B = -2.0*(dux*dvx+duy*dvy);
C = dux*dux+duy*duy+1;
F = A*C - B*B/4;
#endif
#if DEBUG_ELLIPSE
(void) FormatLocaleFile(stderr, "A=%lf; B=%lf; C=%lf; F=%lf\n", A,B,C,F);
/* Figure out the various information directly about the ellipse.
This information currently not needed at this time, but may be
needed later for better limit determination.
It is also good to have as a record for future debugging
*/
{ double alpha, beta, gamma, Major, Minor;
double Eccentricity, Ellipse_Area, Ellipse_Angle;
alpha = A+C;
beta = A-C;
gamma = sqrt(beta*beta + B*B );
if ( alpha - gamma <= MagickEpsilon )
Major=MagickMaximumValue;
else
Major=sqrt(2*F/(alpha - gamma));
Minor = sqrt(2*F/(alpha + gamma));
(void) FormatLocaleFile(stderr, "# Major=%lf; Minor=%lf\n", Major, Minor );
/* other information about ellipse include... */
Eccentricity = Major/Minor;
Ellipse_Area = MagickPI*Major*Minor;
Ellipse_Angle = atan2(B, A-C);
(void) FormatLocaleFile(stderr, "# Angle=%lf Area=%lf\n",
(double) RadiansToDegrees(Ellipse_Angle), Ellipse_Area);
}
#endif
/* If one or both of the scaling vectors is impossibly large
(producing a very large raw F value), we may as well not bother
doing any form of resampling since resampled area is very large.
In this case some alternative means of pixel sampling, such as
the average of the whole image is needed to get a reasonable
result. Calculate only as needed.
*/
if ( (4*A*C - B*B) > MagickMaximumValue ) {
resample_filter->limit_reached = MagickTrue;
return;
}
/* Scale ellipse to match the filters support
(that is, multiply F by the square of the support)
Simplier to just multiply it by the support twice!
*/
F *= resample_filter->support;
F *= resample_filter->support;
/* Orthogonal bounds of the ellipse */
resample_filter->Ulimit = sqrt(C*F/(A*C-0.25*B*B));
resample_filter->Vlimit = sqrt(A*F/(A*C-0.25*B*B));
/* Horizontally aligned parallelogram fitted to Ellipse */
resample_filter->Uwidth = sqrt(F/A); /* Half of the parallelogram width */
resample_filter->slope = -B/(2.0*A); /* Reciprocal slope of the parallelogram */
#if DEBUG_ELLIPSE
(void) FormatLocaleFile(stderr, "Ulimit=%lf; Vlimit=%lf; UWidth=%lf; Slope=%lf;\n",
resample_filter->Ulimit, resample_filter->Vlimit,
resample_filter->Uwidth, resample_filter->slope );
#endif
/* Check the absolute area of the parallelogram involved.
* This limit needs more work, as it is too slow for larger images
* with tiled views of the horizon.
*/
if ( (resample_filter->Uwidth * resample_filter->Vlimit)
> (4.0*resample_filter->image_area)) {
resample_filter->limit_reached = MagickTrue;
return;
}
/* Scale ellipse formula to directly index the Filter Lookup Table */
{ register double scale;
#if FILTER_LUT
/* scale so that F = WLUT_WIDTH; -- hardcoded */
scale = (double)WLUT_WIDTH/F;
#else
/* scale so that F = resample_filter->F (support^2) */
scale = resample_filter->F/F;
#endif
resample_filter->A = A*scale;
resample_filter->B = B*scale;
resample_filter->C = C*scale;
}
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S e t R e s a m p l e F i l t e r %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SetResampleFilter() set the resampling filter lookup table based on a
% specific filter. Note that the filter is used as a radial filter not as a
% two pass othogonally aligned resampling filter.
%
% The format of the SetResampleFilter method is:
%
% void SetResampleFilter(ResampleFilter *resample_filter,
% const FilterType filter)
%
% A description of each parameter follows:
%
% o resample_filter: resampling resample_filterrmation structure
%
% o filter: the resize filter for elliptical weighting LUT
%
*/
MagickExport void SetResampleFilter(ResampleFilter *resample_filter,
const FilterType filter)
{
ResizeFilter
*resize_filter;
assert(resample_filter != (ResampleFilter *) NULL);
assert(resample_filter->signature == MagickCoreSignature);
resample_filter->do_interpolate = MagickFalse;
resample_filter->filter = filter;
/* Default cylindrical filter is a Cubic Keys filter */
if ( filter == UndefinedFilter )
resample_filter->filter = RobidouxFilter;
if ( resample_filter->filter == PointFilter ) {
resample_filter->do_interpolate = MagickTrue;
return; /* EWA turned off - nothing more to do */
}
resize_filter = AcquireResizeFilter(resample_filter->image,
resample_filter->filter,MagickTrue,resample_filter->exception);
if (resize_filter == (ResizeFilter *) NULL) {
(void) ThrowMagickException(resample_filter->exception,GetMagickModule(),
ModuleError, "UnableToSetFilteringValue",
"Fall back to Interpolated 'Point' filter");
resample_filter->filter = PointFilter;
resample_filter->do_interpolate = MagickTrue;
return; /* EWA turned off - nothing more to do */
}
/* Get the practical working support for the filter,
* after any API call blur factors have been accoded for.
*/
#if EWA
resample_filter->support = GetResizeFilterSupport(resize_filter);
#else
resample_filter->support = 2.0; /* fixed support size for HQ-EWA */
#endif
#if FILTER_LUT
/* Fill the LUT with the weights from the selected filter function */
{ register int
Q;
double
r_scale;
/* Scale radius so the filter LUT covers the full support range */
r_scale = resample_filter->support*sqrt(1.0/(double)WLUT_WIDTH);
for(Q=0; Q<WLUT_WIDTH; Q++)
resample_filter->filter_lut[Q] = (double)
GetResizeFilterWeight(resize_filter,sqrt((double)Q)*r_scale);
/* finished with the resize filter */
resize_filter = DestroyResizeFilter(resize_filter);
}
#else
/* save the filter and the scaled ellipse bounds needed for filter */
resample_filter->filter_def = resize_filter;
resample_filter->F = resample_filter->support*resample_filter->support;
#endif
/*
Adjust the scaling of the default unit circle
This assumes that any real scaling changes will always
take place AFTER the filter method has been initialized.
*/
ScaleResampleFilter(resample_filter, 1.0, 0.0, 0.0, 1.0);
#if 0
/*
This is old code kept as a reference only. Basically it generates
a Gaussian bell curve, with sigma = 0.5 if the support is 2.0
Create Normal Gaussian 2D Filter Weighted Lookup Table.
A normal EWA guassual lookup would use exp(Q*ALPHA)
where Q = distance squared from 0.0 (center) to 1.0 (edge)
and ALPHA = -4.0*ln(2.0) ==> -2.77258872223978123767
The table is of length 1024, and equates to support radius of 2.0
thus needs to be scaled by ALPHA*4/1024 and any blur factor squared
The it comes from reference code provided by Fred Weinhaus.
*/
r_scale = -2.77258872223978123767/(WLUT_WIDTH*blur*blur);
for(Q=0; Q<WLUT_WIDTH; Q++)
resample_filter->filter_lut[Q] = exp((double)Q*r_scale);
resample_filter->support = WLUT_WIDTH;
#endif
#if FILTER_LUT
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp single
#endif
{
if (IsStringTrue(GetImageArtifact(resample_filter->image,
"resample:verbose")) != MagickFalse)
{
register int
Q;
double
r_scale;
/* Debug output of the filter weighting LUT
Gnuplot the LUT data, the x scale index has been adjusted
plot [0:2][-.2:1] "lut.dat" with lines
The filter values should be normalized for comparision
*/
printf("#\n");
printf("# Resampling Filter LUT (%d values) for '%s' filter\n",
WLUT_WIDTH, CommandOptionToMnemonic(MagickFilterOptions,
resample_filter->filter) );
printf("#\n");
printf("# Note: values in table are using a squared radius lookup.\n");
printf("# As such its distribution is not uniform.\n");
printf("#\n");
printf("# The X value is the support distance for the Y weight\n");
printf("# so you can use gnuplot to plot this cylindrical filter\n");
printf("# plot [0:2][-.2:1] \"lut.dat\" with lines\n");
printf("#\n");
/* Scale radius so the filter LUT covers the full support range */
r_scale = resample_filter->support*sqrt(1.0/(double)WLUT_WIDTH);
for(Q=0; Q<WLUT_WIDTH; Q++)
printf("%8.*g %.*g\n",
GetMagickPrecision(),sqrt((double)Q)*r_scale,
GetMagickPrecision(),resample_filter->filter_lut[Q] );
printf("\n\n"); /* generate a 'break' in gnuplot if multiple outputs */
}
/* Output the above once only for each image, and each setting
(void) DeleteImageArtifact(resample_filter->image,"resample:verbose");
*/
}
#endif /* FILTER_LUT */
return;
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S e t R e s a m p l e F i l t e r I n t e r p o l a t e M e t h o d %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SetResampleFilterInterpolateMethod() sets the resample filter interpolation
% method.
%
% The format of the SetResampleFilterInterpolateMethod method is:
%
% MagickBooleanType SetResampleFilterInterpolateMethod(
% ResampleFilter *resample_filter,const InterpolateMethod method)
%
% A description of each parameter follows:
%
% o resample_filter: the resample filter.
%
% o method: the interpolation method.
%
*/
MagickExport MagickBooleanType SetResampleFilterInterpolateMethod(
ResampleFilter *resample_filter,const PixelInterpolateMethod method)
{
assert(resample_filter != (ResampleFilter *) NULL);
assert(resample_filter->signature == MagickCoreSignature);
assert(resample_filter->image != (Image *) NULL);
if (resample_filter->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",
resample_filter->image->filename);
resample_filter->interpolate=method;
return(MagickTrue);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S e t R e s a m p l e F i l t e r V i r t u a l P i x e l M e t h o d %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SetResampleFilterVirtualPixelMethod() changes the virtual pixel method
% associated with the specified resample filter.
%
% The format of the SetResampleFilterVirtualPixelMethod method is:
%
% MagickBooleanType SetResampleFilterVirtualPixelMethod(
% ResampleFilter *resample_filter,const VirtualPixelMethod method)
%
% A description of each parameter follows:
%
% o resample_filter: the resample filter.
%
% o method: the virtual pixel method.
%
*/
MagickExport MagickBooleanType SetResampleFilterVirtualPixelMethod(
ResampleFilter *resample_filter,const VirtualPixelMethod method)
{
assert(resample_filter != (ResampleFilter *) NULL);
assert(resample_filter->signature == MagickCoreSignature);
assert(resample_filter->image != (Image *) NULL);
if (resample_filter->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",
resample_filter->image->filename);
resample_filter->virtual_pixel=method;
if (method != UndefinedVirtualPixelMethod)
(void) SetCacheViewVirtualPixelMethod(resample_filter->view,method);
return(MagickTrue);
}
|
GB_unop__identity_fc32_int16.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_fc32_int16)
// op(A') function: GB (_unop_tran__identity_fc32_int16)
// C type: GxB_FC32_t
// A type: int16_t
// cast: GxB_FC32_t cij = GxB_CMPLXF ((float) (aij), 0)
// unaryop: cij = aij
#define GB_ATYPE \
int16_t
#define GB_CTYPE \
GxB_FC32_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 ;
// casting
#define GB_CAST(z, aij) \
GxB_FC32_t z = GxB_CMPLXF ((float) (aij), 0) ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
int16_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
GxB_FC32_t z = GxB_CMPLXF ((float) (aij), 0) ; \
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_FC32 || GxB_NO_INT16)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_apply__identity_fc32_int16)
(
GxB_FC32_t *Cx, // Cx and Ax may be aliased
const int16_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 (int16_t), nthreads) ;
#else
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
int16_t aij = Ax [p] ;
GxB_FC32_t z = GxB_CMPLXF ((float) (aij), 0) ;
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 ;
int16_t aij = Ax [p] ;
GxB_FC32_t z = GxB_CMPLXF ((float) (aij), 0) ;
Cx [p] = z ;
}
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_tran__identity_fc32_int16)
(
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
|
QuadNodeCartesianEuclid.h | /*
* QuadNodePolarEuclid.h
*
* Created on: 21.05.2014
* Author: Moritz v. Looz (moritz.looz-corswarem@kit.edu)
*
* Note: This is similar enough to QuadNode.h that one could merge these two classes.
*/
#ifndef QUADNODECARTESIANEUCLID_H_
#define QUADNODECARTESIANEUCLID_H_
#include <vector>
#include <algorithm>
#include <functional>
#include <assert.h>
#include "../../auxiliary/Log.h"
#include "../../geometric/HyperbolicSpace.h"
using std::vector;
using std::min;
using std::max;
using std::cos;
namespace NetworKit {
template <class T>
class QuadNodeCartesianEuclid {
friend class QuadTreeGTest;
private:
Point<double> minPoint;
Point<double> maxPoint;
count dimension;
unsigned capacity;
static const unsigned coarsenLimit = 4;
count subTreeSize;
std::vector<T> content;
std::vector<Point<double> > positions;
bool isLeaf;
bool splitTheoretical;
index ID;
double lowerBoundR;
public:
std::vector<QuadNodeCartesianEuclid> children;
/**
* Construct a QuadNode for polar coordinates.
*
*
* @param lower Minimal coordinates of region
* @param upper Maximal coordinates of region (excluded)
* @param capacity Number of points a leaf cell can store before splitting
* @param splitTheoretical Whether to split in a theoretically optimal way or in a way to decrease measured running times
*
*/
QuadNodeCartesianEuclid(Point<double> lower = Point<double>({0.0, 0.0}), Point<double> upper = Point<double>({1.0, 1.0}), unsigned capacity = 1000, bool splitTheoretical = false) {
this->minPoint = lower;
this->maxPoint = upper;
this->dimension = minPoint.getDimensions();
assert(maxPoint.getDimensions() == dimension);
this->capacity = capacity;
this->splitTheoretical = splitTheoretical;
this->ID = 0;
isLeaf = true;
subTreeSize = 0;
}
void split() {
assert(isLeaf);
assert(children.size() == 0);
vector<double> middle(dimension);
if (splitTheoretical) {
//Euclidean space is distributed equally
for (index d = 0; d < dimension; d++) {
middle[d] = (minPoint[d] + maxPoint[d]) / 2;
}
} else {
//median of points
const count numPoints = positions.size();
assert(numPoints > 0);//otherwise, why split?
vector<vector<double> > sorted(dimension);
for (index d = 0; d < dimension; d++) {
sorted[d].resize(numPoints);
for (index i = 0; i < numPoints; i++) {
sorted[d][i] = positions[i][d];
}
std::sort(sorted[d].begin(), sorted[d].end());
middle[d] = sorted[d][numPoints/2];//this will crash if no points are there!
assert(middle[d] <= maxPoint[d]);
assert(middle[d] >= minPoint[d]);
}
}
count childCount = pow(2,dimension);
for (index i = 0; i < childCount; i++) {
vector<double> lowerValues(dimension);
vector<double> upperValues(dimension);
index bitCopy = i;
for (index d = 0; d < dimension; d++) {
if (bitCopy & 1) {
lowerValues[d] = middle[d];
upperValues[d] = maxPoint[d];
} else {
lowerValues[d] = minPoint[d];
upperValues[d] = middle[d];
}
bitCopy = bitCopy >> 1;
}
QuadNodeCartesianEuclid child(Point<double>(lowerValues), Point<double>(upperValues), capacity, splitTheoretical);
assert(child.isLeaf);
children.push_back(child);
}
isLeaf = false;
}
/**
* Add a point at polar coordinates (angle, R) with content input. May split node if capacity is full
*
* @param input arbitrary content, in our case an index
* @param angle angular coordinate of point, between 0 and 2 pi.
* @param R radial coordinate of point, between 0 and 1.
*/
void addContent(T input, Point<double> pos) {
assert(content.size() == positions.size());
assert(this->responsible(pos));
if (isLeaf) {
if (content.size() + 1 < capacity) {
content.push_back(input);
positions.push_back(pos);
} else {
split();
for (index i = 0; i < content.size(); i++) {
this->addContent(content[i], positions[i]);
}
assert(subTreeSize == content.size());//we have added everything twice
subTreeSize = content.size();
content.clear();
positions.clear();
this->addContent(input, pos);
}
}
else {
assert(children.size() > 0);
bool foundResponsibleChild = false;
for (index i = 0; i < children.size(); i++) {
if (children[i].responsible(pos)) {
foundResponsibleChild = true;
children[i].addContent(input, pos);
break;
}
}
assert(foundResponsibleChild);
subTreeSize++;
}
}
/**
* Remove content at coordinate pos. May cause coarsening of the quadtree
*
* @param input Content to be removed
* @param pos Coordinate of content
*
* @return True if content was found and removed, false otherwise
*/
bool removeContent(T input, Point<double> pos) {
if (!responsible(pos)) return false;
if (isLeaf) {
index i = 0;
for (; i < content.size(); i++) {
if (content[i] == input) break;
}
if (i < content.size()) {
assert(positions[i].distance(pos) == 0);
//remove element
content.erase(content.begin()+i);
positions.erase(positions.begin()+i);
return true;
} else {
return false;
}
}
else {
bool removed = false;
bool allLeaves = true;
assert(children.size() > 0);
for (index i = 0; i < children.size(); i++) {
if (!children[i].isLeaf) allLeaves = false;
if (children[i].removeContent(input, pos)) {
assert(!removed);
removed = true;
}
}
if (removed) subTreeSize--;
//coarsen?
if (removed && allLeaves && size() < coarsenLimit) {
//coarsen!!
//why not assert empty containers and then insert directly?
vector<T> allContent;
vector<Point<double> > allPositions;
for (index i = 0; i < children.size(); i++) {
allContent.insert(allContent.end(), children[i].content.begin(), children[i].content.end());
allPositions.insert(allPositions.end(), children[i].positions.begin(), children[i].positions.end());
}
assert(allContent.size() == allPositions.size());
children.clear();
content.swap(allContent);
positions.swap(allPositions);
isLeaf = true;
}
return removed;
}
}
/**
* Check whether the region managed by this node lies outside of an Euclidean circle.
*
* @param query Center of the Euclidean query circle, given in Cartesian coordinates
* @param radius Radius of the Euclidean query circle
*
* @return True if the region managed by this node lies completely outside of the circle
*/
bool outOfReach(Point<double> query, double radius) const {
return EuclideanDistances(query).first > radius;
}
/**
* @param query Position of the query point
*/
std::pair<double, double> EuclideanDistances(Point<double> query) const {
/**
* If the query point is not within the quadnode, the distance minimum is on the border.
* Need to check whether extremum is between corners.
*/
double maxDistance = 0;
double minDistance = std::numeric_limits<double>::max();
//Point<double> minCopy(minPoint);
//Point<double> maxCopy(minPoint);
if (responsible(query)) minDistance = 0;
auto updateMinMax = [&minDistance, &maxDistance, query](Point<double> pos){
double extremalValue = pos.distance(query);
maxDistance = std::max(extremalValue, maxDistance);
minDistance = std::min(minDistance, extremalValue);
};
vector<double> closestValues(dimension);
vector<double> farthestValues(dimension);
for (index d = 0; d < dimension; d++) {
if (std::abs(query[d] - minPoint.at(d)) < std::abs(query[d] - maxPoint.at(d))) {
closestValues[d] = minPoint.at(d);
farthestValues[d] = maxPoint.at(d);
} else {
farthestValues[d] = minPoint.at(d);
closestValues[d] = maxPoint.at(d);
}
if (query[d] >= minPoint.at(d) && query[d] <= maxPoint.at(d)) {
closestValues[d] = query[d];
}
}
updateMinMax(Point<double>(closestValues));
updateMinMax(Point<double>(farthestValues));
assert(minDistance < query.length() + maxPoint.length());
assert(minDistance < maxDistance);
return std::pair<double, double>(minDistance, maxDistance);
}
/**
* Does the point at (angle, r) fall inside the region managed by this QuadNode?
*
* @param angle Angular coordinate of input point
* @param r Radial coordinate of input points
*
* @return True if input point lies within the region of this QuadNode
*/
bool responsible(Point<double> pos) const {
for (index d = 0; d < dimension; d++) {
if (pos[d] < minPoint.at(d) || pos[d] >= maxPoint.at(d)) return false;
}
return true;
}
/**
* Get all Elements in this QuadNode or a descendant of it
*
* @return vector of content type T
*/
std::vector<T> getElements() const {
if (isLeaf) {
return content;
} else {
assert(content.size() == 0);
assert(positions.size() == 0);
vector<T> result;
for (index i = 0; i < children.size(); i++) {
std::vector<T> subresult = children[i].getElements();
result.insert(result.end(), subresult.begin(), subresult.end());
}
return result;
}
}
void getCoordinates(vector<Point<double> > &pointContainer) const {
if (isLeaf) {
pointContainer.insert(pointContainer.end(), positions.begin(), positions.end());
}
else {
assert(content.size() == 0);
assert(positions.size() == 0);
for (index i = 0; i < children.size(); i++) {
children[i].getCoordinates(pointContainer);
}
}
}
/**
* Main query method, get points lying in a Euclidean circle around the center point.
* Optional limits can be given to get a different result or to reduce unnecessary comparisons
*
* Elements are pushed onto a vector which is a required argument. This is done to reduce copying.
* (Maybe not necessary due to copy elisison)
*
* Safe to call in parallel.
*
* @param center Center of the query circle
* @param radius Radius of the query circle
* @param result Reference to the vector where the results will be stored
* @param minAngle Optional value for the minimum angular coordinate of the query region
* @param maxAngle Optional value for the maximum angular coordinate of the query region
* @param lowR Optional value for the minimum radial coordinate of the query region
* @param highR Optional value for the maximum radial coordinate of the query region
*/
void getElementsInEuclideanCircle(Point<double> center, double radius, vector<T> &result) const {
if (outOfReach(center, radius)) {
return;
}
if (isLeaf) {
const double rsq = radius*radius;
const count cSize = content.size();
for (index i=0; i < cSize; i++) {
if (positions[i].squaredDistance(center) < rsq) {
result.push_back(content[i]);
}
}
} else {
for (index i = 0; i < children.size(); i++) {
children[i].getElementsInEuclideanCircle(center, radius, result);
}
}
}
count getElementsProbabilistically(Point<double> euQuery, std::function<double(double)> prob, vector<T> &result) const {
TRACE("Getting Euclidean distances");
auto distancePair = EuclideanDistances(euQuery);
double probUB = prob(distancePair.first);
double probLB = prob(distancePair.second);
assert(probLB <= probUB);
if (probUB > 0.5) probUB = 1;
if (probUB == 0) return 0;
//TODO: return whole if probLB == 1
double probdenom = std::log(1-probUB);
if (probdenom == 0) return 0;//there is a very small probability, but we cannot process it.
TRACE("probUB: ", probUB, ", probdenom: ", probdenom);
count expectedNeighbours = probUB*size();
count candidatesTested = 0;
count incomingNeighbours = result.size();
count ownsize = size();
if (isLeaf) {
const count lsize = content.size();
TRACE("Leaf of size ", lsize);
for (index i = 0; i < lsize; i++) {
//jump!
if (probUB < 1) {
double random = Aux::Random::real();
double delta = std::log(random) / probdenom;
assert(delta >= 0);
i += delta;
if (i >= lsize) break;
TRACE("Jumped with delta ", delta, " arrived at ", i);
}
assert(i >= 0);
//see where we've arrived
candidatesTested++;
double distance = positions[i].distance(euQuery);
assert(distance >= distancePair.first);//TODO: These should not fail!
assert(distance <= distancePair.second);
double q = prob(distance);
q = q / probUB; //since the candidate was selected by the jumping process, we have to adjust the probabilities
assert(q <= 1);
//accept?
double acc = Aux::Random::real();
if (acc < q) {
TRACE("Accepted node ", i, " with probability ", q, ".");
result.push_back(content[i]);
}
}
} else {
if (expectedNeighbours < 4 || probUB < 1/1000) {//select candidates directly instead of calling recursively
TRACE("probUB = ", probUB, ", switching to direct candidate selection.");
assert(probUB < 1);
const count stsize = size();
for (index i = 0; i < stsize; i++) {
double delta = std::log(Aux::Random::real()) / probdenom;
assert(delta >= 0);
i += delta;
TRACE("Jumped with delta ", delta, " arrived at ", i, ". Calling maybeGetKthElement.");
if (i < size()) maybeGetKthElement(probUB, euQuery, prob, i, result);//this could be optimized. As of now, the offset is subtracted separately for each point
else break;
candidatesTested++;
}
} else {//carry on as normal
for (index i = 0; i < children.size(); i++) {
TRACE("Recursively calling child ", i);
candidatesTested += children[i].getElementsProbabilistically(euQuery, prob, result);
}
}
}
count finalNeighbours = result.size();
if (probLB == 1) assert(finalNeighbours == incomingNeighbours + ownsize);
return candidatesTested;
}
void maybeGetKthElement(double upperBound, Point<double> euQuery, std::function<double(double)> prob, index k, vector<T> &circleDenizens) const {
TRACE("Maybe get element ", k, " with upper Bound ", upperBound);
assert(k < size());
if (isLeaf) {
double acceptance = prob(euQuery.distance(positions[k]))/upperBound;
TRACE("Is leaf, accept with ", acceptance);
if (Aux::Random::real() < acceptance) circleDenizens.push_back(content[k]);
} else {
TRACE("Call recursively.");
index offset = 0;
for (index i = 0; i < children.size(); i++) {
count childsize = children[i].size();
if (k - offset < childsize) {
children[i].maybeGetKthElement(upperBound, euQuery, prob, k - offset, circleDenizens);
break;
}
offset += childsize;
}
}
}
/**
* Shrink all vectors in this subtree to fit the content.
* Call after quadtree construction is complete, causes better memory usage and cache efficiency
*/
void trim() {
content.shrink_to_fit();
positions.shrink_to_fit();
if (!isLeaf) {
for (index i = 0; i < children.size(); i++) {
children[i].trim();
}
}
}
/**
* Number of points lying in the region managed by this QuadNode
*/
count size() const {
return isLeaf ? content.size() : subTreeSize;
}
void recount() {
subTreeSize = 0;
for (index i = 0; i < children.size(); i++) {
children[i].recount();
subTreeSize += children[i].size();
}
}
/**
* Height of subtree hanging from this QuadNode
*/
count height() const {
count result = 1;//if leaf node, the children loop will not execute
for (auto child : children) result = std::max(result, child.height()+1);
return result;
}
/**
* Leaf cells in the subtree hanging from this QuadNode
*/
count countLeaves() const {
if (isLeaf) return 1;
count result = 0;
for (index i = 0; i < children.size(); i++) {
result += children[i].countLeaves();
}
return result;
}
index getID() const {
return ID;
}
index indexSubtree(index nextID) {
index result = nextID;
assert(children.size() == pow(2,dimension) || children.size() == 0);
for (int i = 0; i < children.size(); i++) {
result = children[i].indexSubtree(result);
}
this->ID = result;
return result+1;
}
index getCellID(Point<double> pos) const {
if (!responsible(pos)) return NetworKit::none;
if (isLeaf) return getID();
else {
for (int i = 0; i < children.size(); i++) {
index childresult = children[i].getCellID(pos);
if (childresult != NetworKit::none) return childresult;
}
throw std::runtime_error("No responsible child node found even though this node is responsible.");
}
}
index getMaxIDInSubtree() const {
if (isLeaf) return getID();
else {
index result = -1;
for (int i = 0; i < children.size(); i++) {
result = std::max(children[i].getMaxIDInSubtree(), result);
}
return std::max(result, getID());
}
}
count reindex(count offset) {
if (isLeaf)
{
#pragma omp task
{
index p = offset;
std::generate(content.begin(), content.end(), [&p](){return p++;});
}
offset += size();
} else {
for (int i = 0; i < children.size(); i++) {
offset = children[i].reindex(offset);
}
}
return offset;
}
};
}
#endif /* QUADNODE_H_ */
|
GB_unop__identity_int64_fc64.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_int64_fc64
// op(A') function: GB_unop_tran__identity_int64_fc64
// C type: int64_t
// A type: GxB_FC64_t
// cast: int64_t cij = GB_cast_to_int64_t (creal (aij))
// unaryop: cij = aij
#define GB_ATYPE \
GxB_FC64_t
#define GB_CTYPE \
int64_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
GxB_FC64_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) \
int64_t z = GB_cast_to_int64_t (creal (aij)) ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GxB_FC64_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
int64_t z = GB_cast_to_int64_t (creal (aij)) ; \
Cx [pC] = z ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_IDENTITY || GxB_NO_INT64 || GxB_NO_FC64)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop_apply__identity_int64_fc64
(
int64_t *Cx, // Cx and Ax may be aliased
const GxB_FC64_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++)
{
GxB_FC64_t aij = Ax [p] ;
int64_t z = GB_cast_to_int64_t (creal (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_int64_fc64
(
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
|
bucle-sections-modificado.c | #include <stdio.h>
#include <omp.h>
void funcA() {
printf("En funcA: esta sección la ejecuta el thread %d\n",
omp_get_thread_num());
}
void funcB() {
printf("En funcB: esta sección la ejecuta el thread %d\n",
omp_get_thread_num());
}
int main() {
int i = 0, j = 5, n = 10;
#pragma omp parallel sections
{
#pragma omp section
{
(void) funcA();
}
#pragma omp section
{
(void) funcB();
}
}
|
elemwise_binary_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.
*/
/*!
* \file elemwise_binary_op.h
* \brief Function definition of elementwise binary operators
*/
#ifndef MXNET_OPERATOR_TENSOR_ELEMWISE_BINARY_OP_H_
#define MXNET_OPERATOR_TENSOR_ELEMWISE_BINARY_OP_H_
#include <mxnet/operator_util.h>
#include <mxnet/op_attr_types.h>
#include <vector>
#include <string>
#include <utility>
#include <typeinfo>
#include <algorithm>
#include "../mxnet_op.h"
#include "../mshadow_op.h"
#include "../../engine/openmp.h"
#include "elemwise_unary_op.h"
#include "../../common/utils.h"
#include "./init_op.h"
#include "../operator_common.h"
namespace mxnet {
namespace op {
/*! Gather binary operator functions into ElemwiseBinaryOp class */
class ElemwiseBinaryOp : public OpBase {
public:
/*! \brief For sparse, assume missing rvalue is 0 */
template <typename OP, int Req>
struct MissingRValueOp {
typedef OP Operation;
template <typename DType>
MSHADOW_XINLINE static void Map(int i, DType* out, const DType* lhs) {
KERNEL_ASSIGN(out[i], Req, OP::Map(lhs[i], DType(0)));
}
};
/*! \brief For sparse, assume missing lvalue is 0 */
template <typename OP, int Req>
struct MissingLValueOp {
typedef OP Operation;
template <typename DType>
MSHADOW_XINLINE static void Map(int i, DType* out, const DType* rhs) {
KERNEL_ASSIGN(out[i], Req, OP::Map(DType(0), rhs[i]));
}
};
private:
/*!
* \brief CSR operation requires temp space
*/
enum ResourceRequestType { kTempSpace };
/*!
* \brief Fill contiguous dense output rows with value computed from 0 lhs and 0 rhs input
* CPU-Only version
*/
template <typename DType, typename OP, typename xpu>
static inline size_t FillDense(mshadow::Stream<xpu>* s,
const size_t idx_l,
const size_t idx_r,
const OpReqType req,
mshadow::Tensor<xpu, 2, DType>* out,
const size_t iter_out) {
const int index_out_min = static_cast<int>(std::min(idx_l, idx_r));
if (static_cast<size_t>(index_out_min) > iter_out) {
const DType zero_input_val = OP::Map(DType(0), DType(0));
#pragma omp parallel for num_threads(engine::OpenMP::Get()->GetRecommendedOMPThreadCount())
for (int i = static_cast<int>(iter_out); i < index_out_min; ++i) {
Fill<false>(s, (*out)[i], req, zero_input_val);
}
}
return static_cast<size_t>(index_out_min); // MSVC wants OMP loops to always use 'int'
}
static inline bool IsSameArray(const NDArray& a1, const NDArray& a2) {
return a1.var() == a2.var();
}
public:
/*! \brief Minimum of three */
static MSHADOW_XINLINE size_t minthree(const size_t a, const size_t b, const size_t c) {
return a < b ? (a < c ? a : c) : (b < c ? b : c);
}
private:
template <typename LOP, typename ROP>
static void BackwardUseNone_(const nnvm::NodeAttrs& attrs,
mshadow::Stream<cpu>* s,
const std::vector<TBlob>& inputs,
const std::vector<OpReqType>& req,
const std::vector<TBlob>& outputs) {
MSHADOW_TYPE_SWITCH(outputs[0].type_flag_, DType, {
using namespace mxnet_op;
const size_t size = static_cast<size_t>((outputs[0].Size() + DataType<DType>::kLanes - 1) /
DataType<DType>::kLanes);
const DType* ograd_dptr = inputs[0].dptr<DType>();
if (std::is_same<LOP, mshadow_op::identity>::value && req[0] == kWriteInplace) {
CHECK_EQ(ograd_dptr, outputs[0].dptr<DType>());
} else if (req[0] != kNullOp) {
DType* lgrad_dptr = outputs[0].dptr<DType>();
MXNET_ASSIGN_REQ_SWITCH(req[0], Req, {
Kernel<mxnet_op::op_with_req<LOP, Req>, cpu>::Launch(s, size, lgrad_dptr, ograd_dptr);
});
}
if (std::is_same<ROP, mshadow_op::identity>::value && req[1] == kWriteInplace) {
CHECK_EQ(ograd_dptr, outputs[1].dptr<DType>());
} else if (req[1] != kNullOp) {
DType* rgrad_dptr = outputs[1].dptr<DType>();
MXNET_ASSIGN_REQ_SWITCH(req[1], Req, {
Kernel<mxnet_op::op_with_req<ROP, Req>, cpu>::Launch(s, size, rgrad_dptr, ograd_dptr);
});
}
});
}
template <typename LOP, typename ROP>
static void BackwardUseIn_(const nnvm::NodeAttrs& attrs,
mshadow::Stream<cpu>* s,
const std::vector<TBlob>& inputs,
const std::vector<OpReqType>& req,
const std::vector<TBlob>& outputs) {
MSHADOW_TYPE_SWITCH(outputs[0].type_flag_, DType, {
DCHECK_EQ(outputs.size(), 2U);
DCHECK_EQ(inputs.size(), 3U);
const DType* ograd_dptr = inputs[0].dptr<DType>();
const DType* lhs_dptr = inputs[1].dptr<DType>();
const DType* rhs_dptr = inputs[2].dptr<DType>();
MXNET_ASSIGN_REQ_SWITCH(req[0], Req, {
const size_t size =
static_cast<size_t>((outputs[0].Size() + mxnet_op::DataType<DType>::kLanes - 1) /
mxnet_op::DataType<DType>::kLanes);
DType* lgrad_dptr = outputs[0].dptr<DType>();
mxnet_op::Kernel<mxnet_op::op_with_req<mxnet_op::backward_grad_tuned<LOP>, Req>,
cpu>::Launch(s, size, lgrad_dptr, ograd_dptr, lhs_dptr, rhs_dptr);
});
MXNET_ASSIGN_REQ_SWITCH(req[1], Req, {
const size_t size =
static_cast<size_t>((outputs[1].Size() + mxnet_op::DataType<DType>::kLanes - 1) /
mxnet_op::DataType<DType>::kLanes);
DType* rgrad_dptr = outputs[1].dptr<DType>();
mxnet_op::Kernel<mxnet_op::op_with_req<mxnet_op::backward_grad_tuned<ROP>, Req>,
cpu>::Launch(s, size, rgrad_dptr, ograd_dptr, lhs_dptr, rhs_dptr);
});
});
}
template <typename xpu,
typename LOP,
typename ROP,
bool in0_ok_dense = false,
bool in1_ok_dense = false,
bool in2_ok_dense = false,
typename BackupCompute>
static inline void RspRspOpBackward(const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const std::vector<NDArray>& inputs,
const std::vector<OpReqType>& req,
const std::vector<NDArray>& outputs,
BackupCompute backup_compute) {
mshadow::Stream<xpu>* s = ctx.get_stream<xpu>();
// lhs grad
if (req[0] != kNullOp) {
// RspRspOp can handle dense outputs so long as OP(0, 0) == 0
RspRspOp<LOP>(
s, attrs, ctx, inputs[1], inputs[2], req[0], outputs[0], false, false, false, false);
// lhs in-place
RspRspOp<op::mshadow_op::mul>(
s, attrs, ctx, outputs[0], inputs[0], req[0], outputs[0], false, false, true, false);
}
// rhs grad
if (req[1] != kNullOp) {
RspRspOp<ROP>(
s, attrs, ctx, inputs[1], inputs[2], req[1], outputs[1], false, false, false, false);
// rhs in-place
RspRspOp<op::mshadow_op::mul>(
s, attrs, ctx, inputs[0], outputs[1], req[1], outputs[1], false, false, true, false);
}
}
public:
/*! \brief Binary op handling for lhr/rhs: RspDns, RspRsp, DnsRsp, or RspRsp->Dns result */
template <typename OP>
static void RspRspOp(mshadow::Stream<cpu>* s,
const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const NDArray& lhs,
const NDArray& rhs,
OpReqType req,
const NDArray& output,
bool lhs_may_be_dense,
bool rhs_may_be_dense,
bool allow_inplace,
bool scatter);
/*! \brief Binary op handling for lhr/rhs: RspDns, RspRsp, DnsRsp, or RspRsp->Dns result */
template <typename OP>
static void RspRspOp(mshadow::Stream<gpu>* s,
const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const NDArray& lhs,
const NDArray& rhs,
OpReqType req,
const NDArray& output,
bool lhs_may_be_dense,
bool rhs_may_be_dense,
bool allow_inplace,
bool scatter);
/*! \brief CSR -op- CSR binary operator for non-canonical NDArray */
template <typename OP>
static void CsrCsrOp(mshadow::Stream<cpu>* s,
const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const NDArray& lhs,
const NDArray& rhs,
OpReqType req,
const NDArray& output);
/*! \brief CSR -op- CSR binary operator for non-canonical NDArray */
template <typename OP>
static void CsrCsrOp(mshadow::Stream<gpu>* s,
const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const NDArray& lhs,
const NDArray& rhs,
OpReqType req,
const NDArray& output);
/*! \brief DNS -op- CSR binary operator for non-canonical NDArray */
template <typename OP>
static void DnsCsrDnsOp(mshadow::Stream<cpu>* s,
const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const NDArray& lhs,
const NDArray& rhs,
OpReqType req,
const NDArray& output,
const bool reverse);
/*! \brief DNS -op- CSR binary operator for non-canonical NDArray */
template <typename OP>
static void DnsCsrDnsOp(mshadow::Stream<gpu>* s,
const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const NDArray& lhs,
const NDArray& rhs,
OpReqType req,
const NDArray& output,
const bool reverse);
/*! \brief DNS -op- CSR binary operator for non-canonical NDArray */
template <typename xpu, typename OP>
static void DnsCsrCsrOp(const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const NDArray& lhs,
const NDArray& rhs,
OpReqType req,
const NDArray& output,
const bool reverse);
/*! \brief DNS -op- RSP binary operator for non-canonical NDArray */
template <typename xpu, typename OP>
static void DnsRspDnsOp(mshadow::Stream<xpu>* s,
const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const NDArray& lhs,
const NDArray& rhs,
OpReqType req,
const NDArray& output,
const bool reverse);
public:
/*!
* \brief Rsp-op-Rsp operation which produces a dense result
* \param attrs Attributes
* \param dev_mask Device mask
* \param dispatch_mode Dispatch Mode
* \param in_attrs Input storage attributes
* \param out_attrs Output storage attributes
* \return true if handled
*/
static bool SparseSparseWithDenseResult(const nnvm::NodeAttrs& attrs,
int dev_mask,
DispatchMode* dispatch_mode,
std::vector<int>* in_attrs,
std::vector<int>* out_attrs);
/*!
* \brief Allow one of the binary inputs to be dense and still produce a sparse output.
* Typically used for sparse * dense = sparse.
* Note: for csr, it dispatches to fallback other than csr, csr -> csr
* \param attrs Attributes
* \param dev_mask Device mask
* \param dispatch_mode Dispatch Mode
* \param in_attrs Input storage attributes
* \param out_attrs Output storage attributes
* \return true if handled
*/
static bool PreferSparseStorageType(const nnvm::NodeAttrs& attrs,
int dev_mask,
DispatchMode* dispatch_mode,
std::vector<int>* in_attrs,
std::vector<int>* out_attrs) {
using namespace common;
CHECK_EQ(in_attrs->size(), 2U) << " in operator " << attrs.name;
CHECK_EQ(out_attrs->size(), 1U) << " in operator " << attrs.name;
const auto& lhs_stype = in_attrs->at(0);
const auto& rhs_stype = in_attrs->at(1);
auto& out_stype = out_attrs->at(0);
bool dispatched = false;
const bool invalid_ctx = dev_mask != mshadow::cpu::kDevMask;
const auto dispatch_ex =
invalid_ctx ? DispatchMode::kFComputeFallback : DispatchMode::kFComputeEx;
if (!dispatched && ContainsOnlyStorage(*in_attrs, kDefaultStorage)) {
// dns, dns -> dns
dispatched =
storage_type_assign(&out_stype, kDefaultStorage, dispatch_mode, DispatchMode::kFCompute);
}
if (!dispatched && ContainsOnlyStorage(*in_attrs, kRowSparseStorage)) {
// rsp, rsp -> rsp
dispatched = storage_type_assign(&out_stype, kRowSparseStorage, dispatch_mode, dispatch_ex);
}
if (!dispatched && ContainsOnlyStorage(*in_attrs, kCSRStorage)) {
// csr, csr -> csr
dispatched = storage_type_assign(&out_stype, kCSRStorage, dispatch_mode, dispatch_ex);
}
if (!dispatched && ((lhs_stype == kRowSparseStorage && rhs_stype == kDefaultStorage) ||
(lhs_stype == kDefaultStorage && rhs_stype == kRowSparseStorage))) {
// rsp, dns -> rsp
// dns, rsp -> rsp
dispatched = storage_type_assign(&out_stype, kRowSparseStorage, dispatch_mode, dispatch_ex);
}
if (!dispatched && ((lhs_stype == kCSRStorage && rhs_stype == kDefaultStorage) ||
(lhs_stype == kDefaultStorage && rhs_stype == kCSRStorage))) {
// csr, dns -> csr
// dns, csr -> csr
dispatched =
storage_type_assign(&out_stype, kCSRStorage, dispatch_mode, DispatchMode::kFComputeEx);
}
if (!dispatched) {
dispatched = dispatch_fallback(out_attrs, dispatch_mode);
}
return dispatched;
}
/*!
* \brief Allow one of the inputs to be dense and produce a dense output,
* for rsp inputs only support when both inputs are rsp type.
* \param attrs Attributes
* \param dev_mask Device mask
* \param dispatch_mode Dispatch Mode
* \param in_attrs Input storage attributes
* \param out_attrs Output storage attributes
* \return true if handled
*/
template <bool cpu_only, bool rsp, bool csr>
static bool PreferDenseStorageType(const nnvm::NodeAttrs& attrs,
const int dev_mask,
DispatchMode* dispatch_mode,
std::vector<int>* in_attrs,
std::vector<int>* out_attrs) {
using namespace common;
CHECK_EQ(in_attrs->size(), 2);
CHECK_EQ(out_attrs->size(), 1);
const auto lhs_stype = (*in_attrs)[0];
const auto rhs_stype = (*in_attrs)[1];
bool dispatched = false;
const bool invalid_ctx = cpu_only && dev_mask != mshadow::cpu::kDevMask;
const auto dispatch_ex =
invalid_ctx ? DispatchMode::kFComputeFallback : DispatchMode::kFComputeEx;
if (!dispatched && ContainsOnlyStorage(*in_attrs, kDefaultStorage)) {
// dns, dns ... -> dns
dispatched =
storage_type_assign(out_attrs, kDefaultStorage, dispatch_mode, DispatchMode::kFCompute);
}
if (!dispatched && rsp && ContainsOnlyStorage(*in_attrs, kRowSparseStorage)) {
// rsp, rsp, ... -> rsp
dispatched = storage_type_assign(
out_attrs, kRowSparseStorage, dispatch_mode, DispatchMode::kFComputeEx);
}
if (!dispatched && csr && ContainsOnlyStorage(*in_attrs, kCSRStorage)) {
// csr, csr, ... -> csr
dispatched = storage_type_assign(out_attrs, kCSRStorage, dispatch_mode, dispatch_ex);
}
if (!dispatched && ((lhs_stype == kDefaultStorage && rhs_stype == kCSRStorage) ||
(lhs_stype == kCSRStorage && rhs_stype == kDefaultStorage))) {
// dense, csr -> dense / csr, dense -> dense
dispatched =
storage_type_assign(out_attrs, kDefaultStorage, dispatch_mode, DispatchMode::kFComputeEx);
}
if (!dispatched && ((lhs_stype == kDefaultStorage && rhs_stype == kRowSparseStorage) ||
(lhs_stype == kRowSparseStorage && rhs_stype == kDefaultStorage))) {
// dense, rsp -> dense / rsp, dense -> dense
dispatched =
storage_type_assign(out_attrs, kDefaultStorage, dispatch_mode, DispatchMode::kFComputeEx);
}
if (!dispatched) {
dispatch_fallback(out_attrs, dispatch_mode);
}
return true;
}
/*!
* \brief Backward pass computing input gradient using forward inputs
* \param attrs Attributes
* \param dev_mask Device mask
* \param dispatch_mode Dispatch Mode
* \param in_attrs Input storage attributes
* \param out_attrs Output storage attributes
* \return true if handled
*/
static bool BackwardUseInStorageType(const nnvm::NodeAttrs& attrs,
int dev_mask,
DispatchMode* dispatch_mode,
std::vector<int>* in_attrs,
std::vector<int>* out_attrs);
template <typename xpu, typename OP>
static void ComputeInt(const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const std::vector<TBlob>& inputs,
const std::vector<OpReqType>& req,
const std::vector<TBlob>& outputs) {
using namespace mxnet_op;
if (req[0] == kNullOp)
return;
Stream<xpu>* s = ctx.get_stream<xpu>();
CHECK_EQ(inputs.size(), 2U);
CHECK_EQ(outputs.size(), 1U);
MXNET_ASSIGN_REQ_SWITCH(req[0], Req, {
MXNET_INT_TYPE_SWITCH(outputs[0].type_flag_, DType, {
const size_t size = (minthree(outputs[0].Size(), inputs[0].Size(), inputs[1].Size()) +
DataType<DType>::kLanes - 1) /
DataType<DType>::kLanes;
if (size != 0) {
Kernel<mxnet_op::op_with_req<OP, Req>, xpu>::Launch(
s, size, outputs[0].dptr<DType>(), inputs[0].dptr<DType>(), inputs[1].dptr<DType>());
}
});
});
}
template <typename xpu, typename OP>
static void Compute(const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const std::vector<TBlob>& inputs,
const std::vector<OpReqType>& req,
const std::vector<TBlob>& outputs) {
using namespace mxnet_op;
if (req[0] == kNullOp)
return;
mshadow::Stream<xpu>* s = ctx.get_stream<xpu>();
CHECK_EQ(inputs.size(), 2U);
CHECK_EQ(outputs.size(), 1U);
if (outputs[0].type_flag_ == mshadow::kBool) {
LOG(FATAL) << "Operator " << attrs.op->name << " does not support boolean type";
}
MXNET_ASSIGN_REQ_SWITCH(req[0], Req, {
MSHADOW_TYPE_SWITCH(outputs[0].type_flag_, DType, {
const size_t size = (minthree(outputs[0].Size(), inputs[0].Size(), inputs[1].Size()) +
DataType<DType>::kLanes - 1) /
DataType<DType>::kLanes;
if (size != 0) {
Kernel<mxnet_op::op_with_req<OP, Req>, xpu>::Launch(
s, size, outputs[0].dptr<DType>(), inputs[0].dptr<DType>(), inputs[1].dptr<DType>());
}
});
});
}
template <typename xpu, typename OP>
static void MixedUnaryBackwardUseInCompute(const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const std::vector<TBlob>& inputs,
const std::vector<OpReqType>& req,
const std::vector<TBlob>& outputs) {
using namespace mxnet_op;
if (req[0] == kNullOp)
return;
Stream<xpu>* s = ctx.get_stream<xpu>();
CHECK_EQ(inputs.size(), 2U);
CHECK_EQ(outputs.size(), 1U);
if (mxnet::common::is_int(outputs[0].type_flag_) || outputs[0].type_flag_ == mshadow::kBool) {
LOG(FATAL) << "gradient computation of operator " << attrs.op->name << " for "
<< mshadow::dtype_string(outputs[0].type_flag_) << " type is not supported";
}
MXNET_ASSIGN_REQ_SWITCH(req[0], Req, {
MSHADOW_REAL_TYPE_SWITCH(outputs[0].type_flag_, DType, {
const size_t size = (minthree(outputs[0].Size(), inputs[0].Size(), inputs[1].Size()) +
DataType<DType>::kLanes - 1) /
DataType<DType>::kLanes;
if (size != 0) {
Kernel<mxnet_op::op_with_req<OP, Req>, xpu>::Launch(
s, size, outputs[0].dptr<DType>(), inputs[0].dptr<DType>(), inputs[1].dptr<DType>());
}
});
});
}
template <typename xpu, typename OP>
static void MixedUnaryBackwardUseInOutCompute(const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const std::vector<TBlob>& inputs,
const std::vector<OpReqType>& req,
const std::vector<TBlob>& outputs) {
using namespace mxnet_op;
if (req[0] == kNullOp)
return;
Stream<xpu>* s = ctx.get_stream<xpu>();
CHECK_EQ(inputs.size(), 3U);
CHECK_EQ(outputs.size(), 1U);
if (mxnet::common::is_int(outputs[0].type_flag_) || outputs[0].type_flag_ == mshadow::kBool) {
LOG(FATAL) << "gradient computation of operator " << attrs.op->name << " for "
<< mshadow::dtype_string(outputs[0].type_flag_) << " type is not supported";
}
MXNET_ASSIGN_REQ_SWITCH(req[0], Req, {
MSHADOW_REAL_TYPE_SWITCH(outputs[0].type_flag_, DType, {
const size_t size = (minthree(outputs[0].Size(), inputs[0].Size(), inputs[2].Size()) +
DataType<DType>::kLanes - 1) /
DataType<DType>::kLanes;
if (size != 0) {
Kernel<mxnet_op::op_with_req<OP, Req>, xpu>::Launch(
s, size, outputs[0].dptr<DType>(), inputs[0].dptr<DType>(), inputs[2].dptr<DType>());
}
});
});
}
template <typename xpu, typename OP>
static void ComputeWithBool(const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const std::vector<TBlob>& inputs,
const std::vector<OpReqType>& req,
const std::vector<TBlob>& outputs) {
using namespace mxnet_op;
if (req[0] == kNullOp)
return;
Stream<xpu>* s = ctx.get_stream<xpu>();
CHECK_EQ(inputs.size(), 2U);
CHECK_EQ(outputs.size(), 1U);
MXNET_ASSIGN_REQ_SWITCH(req[0], Req, {
MSHADOW_TYPE_SWITCH_WITH_BOOL(outputs[0].type_flag_, DType, {
const size_t size = (minthree(outputs[0].Size(), inputs[0].Size(), inputs[1].Size()) +
DataType<DType>::kLanes - 1) /
DataType<DType>::kLanes;
if (size != 0) {
Kernel<mxnet_op::op_with_req<OP, Req>, xpu>::Launch(
s, size, outputs[0].dptr<DType>(), inputs[0].dptr<DType>(), inputs[1].dptr<DType>());
}
});
});
}
template <typename xpu, typename OP>
static void ComputeLogic(const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const std::vector<TBlob>& inputs,
const std::vector<OpReqType>& req,
const std::vector<TBlob>& outputs) {
using namespace mxnet_op;
if (req[0] == kNullOp)
return;
Stream<xpu>* s = ctx.get_stream<xpu>();
CHECK_EQ(inputs.size(), 2U);
CHECK_EQ(outputs.size(), 1U);
MXNET_ASSIGN_REQ_SWITCH(req[0], Req, {
MSHADOW_TYPE_SWITCH_EXT_WITH_BOOL(inputs[0].type_flag_, DType, {
MSHADOW_TYPE_SWITCH_EXT_WITH_BOOL(inputs[1].type_flag_, EType, {
const size_t size = (minthree(outputs[0].Size(), inputs[0].Size(), inputs[1].Size()) +
DataType<DType>::kLanes - 1) /
DataType<DType>::kLanes;
if (size != 0) {
Kernel<mxnet_op::op_with_req<OP, Req>, xpu>::Launch(
s, size, outputs[0].dptr<bool>(), inputs[0].dptr<DType>(), inputs[1].dptr<EType>());
}
});
});
});
}
template <typename xpu, typename OP>
static void ComputeEx(const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const std::vector<NDArray>& inputs,
const std::vector<OpReqType>& req,
const std::vector<NDArray>& outputs) {
using namespace common;
CHECK_EQ(inputs.size(), 2);
CHECK_EQ(outputs.size(), 1);
if (req[0] == kNullOp)
return;
const auto lhs_stype = inputs[0].storage_type();
const auto rhs_stype = inputs[1].storage_type();
const auto out_stype = outputs[0].storage_type();
mshadow::Stream<xpu>* s = ctx.get_stream<xpu>();
if ((ContainsOnlyStorage(inputs, kRowSparseStorage)) &&
(out_stype == kRowSparseStorage || out_stype == kDefaultStorage)) {
// rsp, rsp -> rsp
// rsp, rsp -> dns
RspRspOp<OP>(
s, attrs, ctx, inputs[0], inputs[1], req[0], outputs[0], false, false, false, false);
} else if (ContainsOnlyStorage(inputs, kCSRStorage) && out_stype == kCSRStorage) {
// csr, csr -> csr
CsrCsrOp<OP>(s, attrs, ctx, inputs[0], inputs[1], req[0], outputs[0]);
} else if (((lhs_stype == kCSRStorage && rhs_stype == kDefaultStorage) ||
(lhs_stype == kDefaultStorage && rhs_stype == kCSRStorage)) &&
out_stype == kDefaultStorage) {
const NDArray& dns = (lhs_stype == kDefaultStorage) ? inputs[0] : inputs[1];
const NDArray& csr = (lhs_stype == kCSRStorage) ? inputs[0] : inputs[1];
const bool reverse = (lhs_stype == kCSRStorage);
DnsCsrDnsOp<OP>(s, attrs, ctx, dns, csr, req[0], outputs[0], reverse);
} else if (((lhs_stype == kRowSparseStorage && rhs_stype == kDefaultStorage) ||
(lhs_stype == kDefaultStorage && rhs_stype == kRowSparseStorage)) &&
out_stype == kDefaultStorage) {
const NDArray& dns = (lhs_stype == kDefaultStorage) ? inputs[0] : inputs[1];
const bool reverse = (lhs_stype == kRowSparseStorage);
const NDArray& rsp = (reverse) ? inputs[0] : inputs[1];
DnsRspDnsOp<xpu, OP>(s, attrs, ctx, dns, rsp, req[0], outputs[0], reverse);
} else {
LogUnimplementedOp(attrs, ctx, inputs, req, outputs);
}
}
/*! \brief ComputeEx allowing dense lvalue and/or rvalue */
template <typename xpu, typename OP, bool lhs_may_be_dense, bool rhs_may_be_dense>
static void ComputeDnsLRValueEx(const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const std::vector<NDArray>& inputs,
const std::vector<OpReqType>& req,
const std::vector<NDArray>& outputs) {
using namespace mshadow;
using namespace mshadow::expr;
CHECK_EQ(inputs.size(), 2);
CHECK_EQ(outputs.size(), 1);
if (req[0] == kNullOp)
return;
const auto lhs_stype = inputs[0].storage_type();
const auto rhs_stype = inputs[1].storage_type();
const auto out_stype = outputs[0].storage_type();
if ((out_stype == kRowSparseStorage || out_stype == kDefaultStorage) &&
((lhs_stype == kRowSparseStorage && rhs_stype == kRowSparseStorage) ||
(lhs_stype == kRowSparseStorage && rhs_stype == kDefaultStorage) ||
(lhs_stype == kDefaultStorage && rhs_stype == kRowSparseStorage)) &&
lhs_may_be_dense && rhs_may_be_dense) {
// rsp, rsp -> rsp
// rsp, rsp -> dns
// rsp, dns -> rsp
// dns, rsp -> rsp
// More than once dense not allowed (this will be checked in RspRspOp):
// rsp, dns -> dns <-- NOT ALLOWED
// dns, rsp -> dns <-- NOT ALLOWED
mshadow::Stream<xpu>* s = ctx.get_stream<xpu>();
RspRspOp<OP>(s,
attrs,
ctx,
inputs[0],
inputs[1],
req[0],
outputs[0],
lhs_may_be_dense,
rhs_may_be_dense,
false,
false);
} else if (lhs_stype == kCSRStorage && rhs_stype == kCSRStorage) {
ComputeEx<xpu, OP>(attrs, ctx, inputs, req, outputs);
} else if (((lhs_stype == kCSRStorage && rhs_stype == kDefaultStorage) ||
(lhs_stype == kDefaultStorage && rhs_stype == kCSRStorage)) &&
out_stype == kCSRStorage) {
const NDArray& dns = (lhs_stype == kDefaultStorage) ? inputs[0] : inputs[1];
const NDArray& csr = (lhs_stype == kCSRStorage) ? inputs[0] : inputs[1];
const bool reverse = (lhs_stype == kCSRStorage);
DnsCsrCsrOp<xpu, OP>(attrs, ctx, dns, csr, req[0], outputs[0], reverse);
} else {
LogUnimplementedOp(attrs, ctx, inputs, req, outputs);
}
}
template <typename xpu, typename LOP, typename ROP>
static inline void BackwardUseNone(const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const std::vector<TBlob>& inputs,
const std::vector<OpReqType>& req,
const std::vector<TBlob>& outputs) {
mshadow::Stream<xpu>* s = ctx.get_stream<xpu>();
BackwardUseNone_<LOP, ROP>(attrs, s, inputs, req, outputs);
}
template <typename xpu, typename LOP, typename ROP>
static inline void BackwardUseNoneEx(const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const std::vector<NDArray>& inputs,
const std::vector<OpReqType>& req,
const std::vector<NDArray>& outputs) {
CHECK_EQ(inputs.size(), 1U); // output grad
CHECK_EQ(outputs.size(), 2U); // lhs input grad, rhs input grad
const auto in_stype = inputs[0].storage_type();
const auto lhs_stype = outputs[0].storage_type();
const auto rhs_stype = outputs[1].storage_type();
// lhs grad
if (req[0] != kNullOp) {
if (in_stype == lhs_stype && (in_stype == kRowSparseStorage || in_stype == kCSRStorage)) {
CHECK_EQ(outputs[0].storage_type(), in_stype);
// rsp -> rsp, _. op requires 0-input returns 0-output
DCHECK_LT(std::fabs(static_cast<float>(LOP::Map(0))), 1e-5f);
UnaryOp::ComputeEx<xpu, LOP>(attrs, ctx, inputs, req, {outputs[0]});
} else {
LogUnimplementedOp(attrs, ctx, inputs, req, outputs);
}
}
// rhs grad
if (req[1] != kNullOp) {
if (in_stype == rhs_stype && (in_stype == kRowSparseStorage || in_stype == kCSRStorage)) {
CHECK_EQ(outputs[0].storage_type(), in_stype);
// rsp -> _, rsp. op requires 0-input returns 0-output
DCHECK_LT(std::fabs(static_cast<float>(ROP::Map(0))), 1e-5f);
UnaryOp::ComputeEx<xpu, ROP>(attrs, ctx, inputs, req, {outputs[1]});
} else {
LogUnimplementedOp(attrs, ctx, inputs, req, outputs);
}
}
}
template <typename xpu, typename LOP, typename ROP>
static inline void BackwardUseIn(const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const std::vector<TBlob>& inputs,
const std::vector<OpReqType>& req,
const std::vector<TBlob>& outputs) {
mshadow::Stream<xpu>* s = ctx.get_stream<xpu>();
BackwardUseIn_<LOP, ROP>(attrs, s, inputs, req, outputs);
}
template <typename xpu, typename LOP, typename ROP>
static inline void BackwardUseInEx(const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const std::vector<NDArray>& inputs,
const std::vector<OpReqType>& req,
const std::vector<NDArray>& outputs) {
using namespace common;
CHECK_EQ(inputs.size(), 3U);
CHECK_EQ(outputs.size(), 2U); // lhs input grad, rhs input grad
const auto lhs_grad_stype = outputs[0].storage_type();
const auto rhs_grad_stype = outputs[1].storage_type();
if (ContainsOnlyStorage(inputs, kRowSparseStorage) &&
(lhs_grad_stype == kDefaultStorage || lhs_grad_stype == kRowSparseStorage) &&
(rhs_grad_stype == kDefaultStorage || rhs_grad_stype == kRowSparseStorage)) {
// rsp, rsp, rsp -> [dns, rsp], [dns, rsp]
RspRspOpBackward<xpu, LOP, ROP, false, false, false>(
attrs, ctx, inputs, req, outputs, BackwardUseIn<xpu, LOP, ROP>);
} else {
LOG(FATAL) << "Not Implemented";
}
}
}; // class ElemwiseBinaryOp
/*! \brief Binary launch */
#define MXNET_OPERATOR_REGISTER_BINARY(name) \
NNVM_REGISTER_OP(name) \
.set_num_inputs(2) \
.set_num_outputs(1) \
.set_attr<nnvm::FListInputNames>("FListInputNames", \
[](const NodeAttrs& attrs) { \
return std::vector<std::string>{"lhs", "rhs"}; \
}) \
.set_attr<mxnet::FInferShape>("FInferShape", ElemwiseShape<2, 1>) \
.set_attr<nnvm::FInferType>("FInferType", ElemwiseType<2, 1>) \
.set_attr<nnvm::FInplaceOption>("FInplaceOption", \
[](const NodeAttrs& attrs) { \
return std::vector<std::pair<int, int> >{{0, 0}, {1, 0}}; \
}) \
.add_argument("lhs", "NDArray-or-Symbol", "first input") \
.add_argument("rhs", "NDArray-or-Symbol", "second input")
/*! \brief Binary launch, with FComputeEx for csr and rsp available */
#define MXNET_OPERATOR_REGISTER_BINARY_WITH_SPARSE_CPU(__name$, __kernel$) \
MXNET_OPERATOR_REGISTER_BINARY(__name$) \
.set_attr<FInferStorageType>("FInferStorageType", \
ElemwiseStorageType<2, 1, true, true, true>) \
.set_attr<FCompute>("FCompute<cpu>", ElemwiseBinaryOp::Compute<cpu, __kernel$>) \
.set_attr<FComputeEx>("FComputeEx<cpu>", ElemwiseBinaryOp::ComputeEx<cpu, __kernel$>) \
.set_attr<FResourceRequest>( \
"FResourceRequest", /* For Sparse CSR */ \
[](const NodeAttrs& attrs) { \
return std::vector<ResourceRequest>{ResourceRequest::kTempSpace}; \
})
/*! \brief Binary launch, with FComputeEx for csr and rsp available.
when inputs contain both sparse and dense, sparse output is preferred. */
#define MXNET_OPERATOR_REGISTER_BINARY_WITH_SPARSE_CPU_PS(__name$, __kernel$) \
MXNET_OPERATOR_REGISTER_BINARY(__name$) \
.set_attr<FInferStorageType>("FInferStorageType", ElemwiseBinaryOp::PreferSparseStorageType) \
.set_attr<FCompute>("FCompute<cpu>", ElemwiseBinaryOp::Compute<cpu, __kernel$>) \
.set_attr<FComputeEx>("FComputeEx<cpu>", ElemwiseBinaryOp::ComputeEx<cpu, __kernel$>) \
.set_attr<FResourceRequest>( \
"FResourceRequest", /* For Sparse CSR */ \
[](const NodeAttrs& attrs) { \
return std::vector<ResourceRequest>{ResourceRequest::kTempSpace}; \
})
/*! \brief Binary launch, dense result
* FInferStorageType attr is not set using this macro.
* By default DefaultStorageType is used.
*/
#define MXNET_OPERATOR_REGISTER_BINARY_WITH_SPARSE_CPU_DR(__name$, __kernel$) \
MXNET_OPERATOR_REGISTER_BINARY(__name$) \
.set_attr<FInferStorageType>("FInferStorageType", \
ElemwiseBinaryOp::SparseSparseWithDenseResult) \
.set_attr<FCompute>("FCompute<cpu>", ElemwiseBinaryOp::Compute<cpu, __kernel$>) \
.set_attr<FComputeEx>("FComputeEx<cpu>", ElemwiseBinaryOp::ComputeEx<cpu, __kernel$>)
/*! \brief Binary launch, with FComputeEx for prefer dense */
#define MXNET_OPERATOR_REGISTER_BINARY_WITH_SPARSE_CPU_PD(__name$, __kernel$) \
MXNET_OPERATOR_REGISTER_BINARY(__name$) \
.set_attr<FInferStorageType>("FInferStorageType", \
ElemwiseBinaryOp::PreferDenseStorageType<true, true, true>) \
.set_attr<FCompute>("FCompute<cpu>", ElemwiseBinaryOp::Compute<cpu, __kernel$>) \
.set_attr<FComputeEx>("FComputeEx<cpu>", ElemwiseBinaryOp::ComputeEx<cpu, __kernel$>) \
.set_attr<FResourceRequest>( \
"FResourceRequest", /* For Sparse CSR */ \
[](const NodeAttrs& attrs) { \
return std::vector<ResourceRequest>{ResourceRequest::kTempSpace}; \
})
#if MXNET_USE_CUDA
struct ElemwiseBinaryRTCCompute {
std::string OP;
void operator()(const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const std::vector<TBlob>& inputs,
const std::vector<OpReqType>& req,
const std::vector<TBlob>& outputs);
};
struct ElemwiseBinaryRTCBwdUseNone {
std::string LOP;
std::string ROP;
void operator()(const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const std::vector<TBlob>& inputs,
const std::vector<OpReqType>& req,
const std::vector<TBlob>& outputs);
};
struct ElemwiseBinaryRTCBwdUseIn {
std::string LOP;
std::string ROP;
void operator()(const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const std::vector<TBlob>& inputs,
const std::vector<OpReqType>& req,
const std::vector<TBlob>& outputs);
};
#endif
} // namespace op
} // namespace mxnet
#endif // MXNET_OPERATOR_TENSOR_ELEMWISE_BINARY_OP_H_
|
papi_hl.c | /****************************/
/* THIS IS OPEN SOURCE CODE */
/****************************/
/**
* @file papi_hl.c
* @author Frank Winkler
* frank.winkler@icl.utk.edu
* @author Philip Mucci
* mucci@cs.utk.edu
* @brief This file contains the 'high level' interface to PAPI.
* BASIC is a high level language. ;-) */
#include <string.h>
#include <stdlib.h>
#include <stdio.h>
#include <stdbool.h>
#include <pthread.h>
#include <search.h>
#include <sys/types.h>
#include <sys/stat.h>
#include <errno.h>
#include <time.h>
#include <stdint.h>
#include <unistd.h>
#include "papi.h"
#include "papi_internal.h"
/* For dynamic linking to libpapi */
/* Weak symbol for pthread_once to avoid additional linking
* against libpthread when not used. */
#pragma weak pthread_once
#define verbose_fprintf \
if (verbosity == 1) fprintf
/* defaults for number of components and events */
#define PAPIHL_NUM_OF_COMPONENTS 10
#define PAPIHL_NUM_OF_EVENTS_PER_COMPONENT 10
#define PAPIHL_ACTIVE 1
#define PAPIHL_DEACTIVATED 0
/* global components data begin *****************************************/
typedef struct components
{
int component_id;
int num_of_events;
int max_num_of_events;
char **event_names;
int *event_codes;
short *event_types;
int EventSet; //only for testing at initialization phase
} components_t;
components_t *components = NULL;
int num_of_components = 0;
int max_num_of_components = PAPIHL_NUM_OF_COMPONENTS;
int total_num_events = 0;
int num_of_cleaned_threads = 0;
/* global components data end *******************************************/
/* thread local components data begin ***********************************/
typedef struct local_components
{
int EventSet;
/** Return values for the eventsets */
long_long *values;
} local_components_t;
PAPI_TLS_KEYWORD local_components_t *_local_components = NULL;
PAPI_TLS_KEYWORD long_long _local_cycles;
PAPI_TLS_KEYWORD volatile bool _local_state = PAPIHL_ACTIVE;
PAPI_TLS_KEYWORD int _local_region_begin_cnt = 0; /**< Count each PAPI_hl_region_begin call */
PAPI_TLS_KEYWORD int _local_region_end_cnt = 0; /**< Count each PAPI_hl_region_end call */
/* thread local components data end *************************************/
/* global event storage data begin **************************************/
typedef struct reads
{
struct reads *next;
struct reads *prev;
long_long value; /**< Event value */
} reads_t;
typedef struct
{
long_long offset; /**< Event value for region_begin */
long_long total; /**< Event value for region_end - region_begin + previous value */
reads_t *read_values; /**< List of read event values inside a region */
} value_t;
typedef struct regions
{
char *region; /**< Region name */
struct regions *next;
struct regions *prev;
value_t values[]; /**< Array of event values based on current eventset */
} regions_t;
typedef struct
{
unsigned long key; /**< Thread ID */
regions_t *value; /**< List of regions */
} threads_t;
int compar(const void *l, const void *r)
{
const threads_t *lm = l;
const threads_t *lr = r;
return lm->key - lr->key;
}
typedef struct
{
void *root; /**< Root of binary tree */
threads_t *find_p; /**< Pointer that is used for finding a thread node */
} binary_tree_t;
/**< Global binary tree that stores events from all threads */
binary_tree_t* binary_tree = NULL;
/* global event storage data end ****************************************/
/* global auxiliary variables begin *************************************/
enum region_type { REGION_BEGIN, REGION_READ, REGION_END };
char **requested_event_names = NULL; /**< Events from user or default */
int num_of_requested_events = 0;
bool hl_initiated = false; /**< Check PAPI-HL has been initiated */
bool hl_finalized = false; /**< Check PAPI-HL has been fininalized */
bool events_determined = false; /**< Check if events are determined */
bool output_generated = false; /**< Check if output has been already generated */
static char *absolute_output_file_path = NULL;
static int output_counter = 0; /**< Count each output generation. Not used yet */
short verbosity = 1; /**< Verbose output is always generated */
bool state = PAPIHL_ACTIVE; /**< PAPIHL is active until first error or finalization */
static int region_begin_cnt = 0; /**< Count each PAPI_hl_region_begin call */
static int region_end_cnt = 0; /**< Count each PAPI_hl_region_end call */
unsigned long master_thread_id = -1; /**< Remember id of master thread */
/* global auxiliary variables end ***************************************/
static void _internal_hl_library_init(void);
static void _internal_hl_onetime_library_init(void);
/* functions for creating eventsets for different components */
static int _internal_hl_checkCounter ( char* counter );
static int _internal_hl_determine_rank();
static char *_internal_hl_remove_spaces( char *str );
static int _internal_hl_determine_default_events();
static int _internal_hl_read_user_events();
static int _internal_hl_new_component(int component_id, components_t *component);
static int _internal_hl_add_event_to_component(char *event_name, int event,
short event_type, components_t *component);
static int _internal_hl_create_components();
static int _internal_hl_read_events(const char* events);
static int _internal_hl_create_event_sets();
/* functions for storing events */
static inline reads_t* _internal_hl_insert_read_node( reads_t** head_node );
static inline int _internal_hl_add_values_to_region( regions_t *node, enum region_type reg_typ );
static inline regions_t* _internal_hl_insert_region_node( regions_t** head_node, const char *region );
static inline regions_t* _internal_hl_find_region_node( regions_t* head_node, const char *region );
static inline threads_t* _internal_hl_insert_thread_node( unsigned long tid );
static inline threads_t* _internal_hl_find_thread_node( unsigned long tid );
static int _internal_hl_store_counters( unsigned long tid, const char *region,
enum region_type reg_typ );
static int _internal_hl_read_counters();
static int _internal_hl_read_and_store_counters( const char *region, enum region_type reg_typ );
static int _internal_hl_create_global_binary_tree();
/* functions for output generation */
static int _internal_hl_mkdir(const char *dir);
static int _internal_hl_determine_output_path();
static void _internal_hl_json_line_break_and_indent(FILE* f, bool b, int width);
static void _internal_hl_json_region_events(FILE* f, bool beautifier, regions_t *regions);
static void _internal_hl_json_regions(FILE* f, bool beautifier, threads_t* thread_node);
static void _internal_hl_json_threads(FILE* f, bool beautifier, unsigned long* tids, int threads_num);
static void _internal_hl_write_output();
/* functions for cleaning up heap memory */
static void _internal_hl_clean_up_local_data();
static void _internal_hl_clean_up_global_data();
static void _internal_hl_clean_up_all(bool deactivate);
static int _internal_hl_check_for_clean_thread_states();
static void _internal_hl_library_init(void)
{
/* This function is only called by one thread! */
int retval;
/* check VERBOSE level */
if ( getenv("PAPI_NO_WARNING") != NULL ) {
verbosity = 0;
}
if ( ( retval = PAPI_library_init(PAPI_VER_CURRENT) ) != PAPI_VER_CURRENT )
verbose_fprintf(stdout, "PAPI-HL Error: PAPI_library_init failed!\n");
/* PAPI_thread_init only suceeds if PAPI_library_init has suceeded */
if ((retval = PAPI_thread_init(&pthread_self)) == PAPI_OK) {
/* determine output directory and output file */
if ( ( retval = _internal_hl_determine_output_path() ) != PAPI_OK ) {
verbose_fprintf(stdout, "PAPI-HL Error: _internal_hl_determine_output_path failed!\n");
state = PAPIHL_DEACTIVATED;
verbose_fprintf(stdout, "PAPI-HL Error: PAPI could not be initiated!\n");
} else {
/* register the termination function for output */
atexit(PAPI_hl_print_output);
verbose_fprintf(stdout, "PAPI-HL Info: PAPI has been initiated!\n");
/* remember thread id */
master_thread_id = PAPI_thread_id();
HLDBG("master_thread_id=%lu\n", master_thread_id);
}
} else {
verbose_fprintf(stdout, "PAPI-HL Error: PAPI_thread_init failed!\n");
state = PAPIHL_DEACTIVATED;
verbose_fprintf(stdout, "PAPI-HL Error: PAPI could not be initiated!\n");
}
/* Support multiplexing if user wants to */
if ( getenv("PAPI_MULTIPLEX") != NULL ) {
retval = PAPI_multiplex_init();
if ( retval == PAPI_ENOSUPP) {
verbose_fprintf(stdout, "PAPI-HL Info: Multiplex is not supported!\n");
} else if ( retval != PAPI_OK ) {
verbose_fprintf(stdout, "PAPI-HL Error: PAPI_multiplex_init failed!\n");
} else if ( retval == PAPI_OK ) {
verbose_fprintf(stdout, "PAPI-HL Info: Multiplex has been initiated!\n");
}
}
hl_initiated = true;
}
static void _internal_hl_onetime_library_init(void)
{
static pthread_once_t library_is_initialized = PTHREAD_ONCE_INIT;
if ( pthread_once ) {
/* we assume that PAPI_hl_init() is called from a parallel region */
pthread_once(&library_is_initialized, _internal_hl_library_init);
/* wait until first thread has finished */
int i = 0;
/* give it 5 seconds in case PAPI_thread_init crashes */
while ( !hl_initiated && (i++) < 500000 )
usleep(10);
} else {
/* we assume that PAPI_hl_init() is called from a serial application
* that was not linked against libpthread */
_internal_hl_library_init();
}
}
static int
_internal_hl_checkCounter ( char* counter )
{
int EventSet = PAPI_NULL;
int eventcode;
int retval;
if ( ( retval = PAPI_create_eventset( &EventSet ) ) != PAPI_OK )
return ( retval );
if ( ( retval = PAPI_event_name_to_code( counter, &eventcode ) ) != PAPI_OK )
return ( retval );
if ( ( retval = PAPI_add_event (EventSet, eventcode) ) != PAPI_OK )
return ( retval );
if ( ( retval = PAPI_cleanup_eventset (EventSet) ) != PAPI_OK )
return ( retval );
if ( ( retval = PAPI_destroy_eventset (&EventSet) ) != PAPI_OK )
return ( retval );
return ( PAPI_OK );
}
static int _internal_hl_determine_rank()
{
int rank = -1;
/* check environment variables for rank identification */
if ( getenv("OMPI_COMM_WORLD_RANK") != NULL )
rank = atoi(getenv("OMPI_COMM_WORLD_RANK"));
else if ( getenv("ALPS_APP_PE") != NULL )
rank = atoi(getenv("ALPS_APP_PE"));
else if ( getenv("PMI_RANK") != NULL )
rank = atoi(getenv("PMI_RANK"));
else if ( getenv("SLURM_PROCID") != NULL )
rank = atoi(getenv("SLURM_PROCID"));
return rank;
}
static char *_internal_hl_remove_spaces( char *str )
{
char *out = str, *put = str;
for(; *str != '\0'; ++str) {
if(*str != ' ')
*put++ = *str;
}
*put = '\0';
return out;
}
static int _internal_hl_determine_default_events()
{
int i;
char *default_events[] = {
"perf::TASK-CLOCK",
"PAPI_TOT_INS",
"PAPI_TOT_CYC",
"PAPI_FP_INS",
"PAPI_FP_OPS"
};
int num_of_defaults = sizeof(default_events) / sizeof(char*);
/* allocate memory for requested events */
requested_event_names = (char**)malloc(num_of_defaults * sizeof(char*));
if ( requested_event_names == NULL )
return ( PAPI_ENOMEM );
/* check if default events are available on the current machine */
for ( i = 0; i < num_of_defaults; i++ ) {
if ( _internal_hl_checkCounter( default_events[i] ) == PAPI_OK ) {
requested_event_names[num_of_requested_events++] = strdup(default_events[i]);
if ( requested_event_names[num_of_requested_events -1] == NULL )
return ( PAPI_ENOMEM );
}
}
return ( PAPI_OK );
}
static int _internal_hl_read_user_events(const char *user_events)
{
char* user_events_copy;
const char *separator; //separator for events
int num_of_req_events = 1; //number of events in string
int req_event_index = 0; //index of event
const char *position = NULL; //current position in processed string
char *token;
user_events_copy = strdup(user_events);
if ( user_events_copy == NULL )
return ( PAPI_ENOMEM );
/* check if string is not empty */
if ( strlen( user_events_copy ) > 0 )
{
/* count number of separator characters */
position = user_events_copy;
separator=",";
while ( *position ) {
if ( strchr( separator, *position ) ) {
num_of_req_events++;
}
position++;
}
/* allocate memory for requested events */
requested_event_names = (char**)malloc(num_of_req_events * sizeof(char*));
if ( requested_event_names == NULL )
return ( PAPI_ENOMEM );
/* parse list of event names */
token = strtok( user_events_copy, separator );
while ( token ) {
if ( req_event_index >= num_of_req_events ){
/* more entries as in the first run */
return PAPI_EINVAL;
}
requested_event_names[req_event_index] = strdup(_internal_hl_remove_spaces(token));
if ( requested_event_names[req_event_index] == NULL )
return ( PAPI_ENOMEM );
token = strtok( NULL, separator );
req_event_index++;
}
}
num_of_requested_events = num_of_req_events;
free(user_events_copy);
if ( num_of_requested_events == 0 )
return PAPI_EINVAL;
return ( PAPI_OK );
}
static int _internal_hl_new_component(int component_id, components_t *component)
{
int retval;
/* create new EventSet */
component->EventSet = PAPI_NULL;
if ( ( retval = PAPI_create_eventset( &component->EventSet ) ) != PAPI_OK ) {
verbose_fprintf(stdout, "PAPI-HL Error: Cannot create EventSet for component %d.\n", component_id);
return ( retval );
}
/* Support multiplexing if user wants to */
if ( getenv("PAPI_MULTIPLEX") != NULL ) {
/* multiplex only for cpu core events */
if ( component_id == 0 ) {
retval = PAPI_assign_eventset_component(component->EventSet, component_id);
if ( retval != PAPI_OK ) {
verbose_fprintf(stdout, "PAPI-HL Error: PAPI_assign_eventset_component failed.\n");
} else {
if ( PAPI_get_multiplex(component->EventSet) == false ) {
retval = PAPI_set_multiplex(component->EventSet);
if ( retval != PAPI_OK ) {
verbose_fprintf(stdout, "PAPI-HL Error: PAPI_set_multiplex failed.\n");
}
}
}
}
}
component->component_id = component_id;
component->num_of_events = 0;
component->max_num_of_events = PAPIHL_NUM_OF_EVENTS_PER_COMPONENT;
component->event_names = NULL;
component->event_names = (char**)malloc(component->max_num_of_events * sizeof(char*));
if ( component->event_names == NULL )
return ( PAPI_ENOMEM );
component->event_codes = NULL;
component->event_codes = (int*)malloc(component->max_num_of_events * sizeof(int));
if ( component->event_codes == NULL )
return ( PAPI_ENOMEM );
component->event_types = NULL;
component->event_types = (short*)malloc(component->max_num_of_events * sizeof(short));
if ( component->event_types == NULL )
return ( PAPI_ENOMEM );
num_of_components += 1;
return ( PAPI_OK );
}
static int _internal_hl_add_event_to_component(char *event_name, int event,
short event_type, components_t *component)
{
int i, retval;
/* check if we need to reallocate memory for event_names, event_codes and event_types */
if ( component->num_of_events == component->max_num_of_events ) {
component->max_num_of_events *= 2;
component->event_names = (char**)realloc(component->event_names, component->max_num_of_events * sizeof(char*));
if ( component->event_names == NULL )
return ( PAPI_ENOMEM );
component->event_codes = (int*)realloc(component->event_codes, component->max_num_of_events * sizeof(int));
if ( component->event_codes == NULL )
return ( PAPI_ENOMEM );
component->event_types = (short*)realloc(component->event_types, component->max_num_of_events * sizeof(short));
if ( component->event_types == NULL )
return ( PAPI_ENOMEM );
}
retval = PAPI_add_event( component->EventSet, event );
if ( retval != PAPI_OK ) {
const PAPI_component_info_t* cmpinfo;
cmpinfo = PAPI_get_component_info( component->component_id );
verbose_fprintf(stdout, "PAPI-HL Warning: Cannot add %s to component %s.\n", event_name, cmpinfo->name);
verbose_fprintf(stdout, "The following event combination is not supported:\n");
for ( i = 0; i < component->num_of_events; i++ )
verbose_fprintf(stdout, " %s\n", component->event_names[i]);
verbose_fprintf(stdout, " %s\n", event_name);
verbose_fprintf(stdout, "Advice: Use papi_event_chooser to obtain an appropriate event set for this component or set PAPI_MULTIPLEX=1.\n");
return PAPI_EINVAL;
}
component->event_names[component->num_of_events] = event_name;
component->event_codes[component->num_of_events] = event;
component->event_types[component->num_of_events] = event_type;
component->num_of_events += 1;
total_num_events += 1;
return PAPI_OK;
}
static int _internal_hl_create_components()
{
int i, j, retval, event;
int component_id = -1;
int comp_index = 0;
bool component_exists = false;
short event_type = 0;
components = (components_t*)malloc(max_num_of_components * sizeof(components_t));
if ( components == NULL )
return ( PAPI_ENOMEM );
for ( i = 0; i < num_of_requested_events; i++ ) {
/* check if requested event contains event type (instant or delta) */
const char sep = '=';
char *ret;
int index;
/* search for '=' in event name */
ret = strchr(requested_event_names[i], sep);
if (ret) {
if ( strcmp(ret, "=instant") == 0 )
event_type = 1;
else
event_type = 0;
/* get index of '=' in event name */
index = (int)(ret - requested_event_names[i]);
/* remove event type from string if '=instant' or '=delta' */
if ( (strcmp(ret, "=instant") == 0) || (strcmp(ret, "=delta") == 0) )
requested_event_names[i][index] = '\0';
}
/* determine event code and corresponding component id */
retval = PAPI_event_name_to_code( requested_event_names[i], &event );
if ( retval != PAPI_OK ) {
verbose_fprintf(stdout, "PAPI-HL Warning: \"%s\" does not exist or is not supported on this machine.\n", requested_event_names[i]);
} else {
component_id = PAPI_COMPONENT_INDEX( event );
/* check if component_id already exists in global components structure */
for ( j = 0; j < num_of_components; j++ ) {
if ( components[j].component_id == component_id ) {
component_exists = true;
comp_index = j;
break;
}
else {
component_exists = false;
}
}
/* create new component */
if ( false == component_exists ) {
/* check if we need to reallocate memory for components */
if ( num_of_components == max_num_of_components ) {
max_num_of_components *= 2;
components = (components_t*)realloc(components, max_num_of_components * sizeof(components_t));
if ( components == NULL )
return ( PAPI_ENOMEM );
}
comp_index = num_of_components;
retval = _internal_hl_new_component(component_id, &components[comp_index]);
if ( retval != PAPI_OK )
return ( retval );
}
/* add event to current component */
retval = _internal_hl_add_event_to_component(requested_event_names[i], event, event_type, &components[comp_index]);
if ( retval == PAPI_ENOMEM )
return ( retval );
}
}
verbose_fprintf(stdout, "PAPI-HL Info: Using the following events:\n");
/* destroy all EventSets from global data */
for ( i = 0; i < num_of_components; i++ ) {
if ( ( retval = PAPI_cleanup_eventset (components[i].EventSet) ) != PAPI_OK )
return ( retval );
if ( ( retval = PAPI_destroy_eventset (&components[i].EventSet) ) != PAPI_OK )
return ( retval );
components[i].EventSet = PAPI_NULL;
HLDBG("component_id = %d\n", components[i].component_id);
HLDBG("num_of_events = %d\n", components[i].num_of_events);
for ( j = 0; j < components[i].num_of_events; j++ ) {
HLDBG(" %s type=%d\n", components[i].event_names[j], components[i].event_types[j]);
verbose_fprintf(stdout, " %s\n", components[i].event_names[j]);
}
}
if ( num_of_components == 0 )
return PAPI_EINVAL;
return PAPI_OK;
}
static int _internal_hl_read_events(const char* events)
{
int i, retval;
if ( events != NULL ) {
if ( _internal_hl_read_user_events(events) != PAPI_OK )
if ( ( retval = _internal_hl_determine_default_events() ) != PAPI_OK )
return ( retval );
/* check if user specified events via environment variable */
} else if ( getenv("PAPI_EVENTS") != NULL ) {
char *user_events_from_env = strdup( getenv("PAPI_EVENTS") );
if ( user_events_from_env == NULL )
return ( PAPI_ENOMEM );
if ( _internal_hl_read_user_events(user_events_from_env) != PAPI_OK )
if ( ( retval = _internal_hl_determine_default_events() ) != PAPI_OK ) {
free(user_events_from_env);
return ( retval );
}
free(user_events_from_env);
} else {
if ( ( retval = _internal_hl_determine_default_events() ) != PAPI_OK )
return ( retval );
}
/* create components based on requested events */
if ( _internal_hl_create_components() != PAPI_OK )
{
/* requested events do not work at all, use default events */
verbose_fprintf(stdout, "PAPI-HL Warning: All requested events do not work, using default.\n");
for ( i = 0; i < num_of_requested_events; i++ )
free(requested_event_names[i]);
free(requested_event_names);
num_of_requested_events = 0;
if ( ( retval = _internal_hl_determine_default_events() ) != PAPI_OK )
return ( retval );
if ( ( retval = _internal_hl_create_components() ) != PAPI_OK )
return ( retval );
}
events_determined = true;
return ( PAPI_OK );
}
static int _internal_hl_create_event_sets()
{
int i, j, retval;
long_long cycles;
if ( state == PAPIHL_ACTIVE ) {
/* allocate memory for local components */
_local_components = (local_components_t*)malloc(num_of_components * sizeof(local_components_t));
if ( _local_components == NULL )
return ( PAPI_ENOMEM );
for ( i = 0; i < num_of_components; i++ ) {
/* create EventSet */
_local_components[i].EventSet = PAPI_NULL;
if ( ( retval = PAPI_create_eventset( &_local_components[i].EventSet ) ) != PAPI_OK ) {
return (retval );
}
/* Support multiplexing if user wants to */
if ( getenv("PAPI_MULTIPLEX") != NULL ) {
/* multiplex only for cpu core events */
if ( components[i].component_id == 0 ) {
retval = PAPI_assign_eventset_component(_local_components[i].EventSet, components[i].component_id );
if ( retval != PAPI_OK ) {
verbose_fprintf(stdout, "PAPI-HL Error: PAPI_assign_eventset_component failed.\n");
} else {
if ( PAPI_get_multiplex(_local_components[i].EventSet) == false ) {
retval = PAPI_set_multiplex(_local_components[i].EventSet);
if ( retval != PAPI_OK ) {
verbose_fprintf(stdout, "PAPI-HL Error: PAPI_set_multiplex failed.\n");
}
}
}
}
}
/* add event to current EventSet */
for ( j = 0; j < components[i].num_of_events; j++ ) {
retval = PAPI_add_event( _local_components[i].EventSet, components[i].event_codes[j] );
if ( retval != PAPI_OK ) {
return (retval );
}
}
/* allocate memory for return values */
_local_components[i].values = (long_long*)malloc(components[i].num_of_events * sizeof(long_long));
if ( _local_components[i].values == NULL )
return ( PAPI_ENOMEM );
}
for ( i = 0; i < num_of_components; i++ ) {
if ( ( retval = PAPI_start( _local_components[i].EventSet ) ) != PAPI_OK )
return (retval );
/* warm up PAPI code paths and data structures */
if ( ( retval = PAPI_read_ts( _local_components[i].EventSet, _local_components[i].values, &cycles ) != PAPI_OK ) ) {
return (retval );
}
}
return PAPI_OK;
}
return ( PAPI_EMISC );
}
static inline reads_t* _internal_hl_insert_read_node(reads_t** head_node)
{
reads_t *new_node;
/* create new region node */
if ( ( new_node = malloc(sizeof(reads_t)) ) == NULL )
return ( NULL );
new_node->next = NULL;
new_node->prev = NULL;
/* insert node in list */
if ( *head_node == NULL ) {
*head_node = new_node;
return new_node;
}
(*head_node)->prev = new_node;
new_node->next = *head_node;
*head_node = new_node;
return new_node;
}
static inline int _internal_hl_add_values_to_region( regions_t *node, enum region_type reg_typ )
{
int i, j;
int region_count = 1;
int cmp_iter = 2;
if ( reg_typ == REGION_BEGIN ) {
/* set first fixed counters */
node->values[0].offset = region_count;
node->values[1].offset = _local_cycles;
/* events from components */
for ( i = 0; i < num_of_components; i++ )
for ( j = 0; j < components[i].num_of_events; j++ )
node->values[cmp_iter++].offset = _local_components[i].values[j];
} else if ( reg_typ == REGION_READ ) {
/* create a new read node and add values*/
reads_t* read_node;
if ( ( read_node = _internal_hl_insert_read_node(&node->values[1].read_values) ) == NULL )
return ( PAPI_ENOMEM );
read_node->value = _local_cycles - node->values[1].offset;
for ( i = 0; i < num_of_components; i++ ) {
for ( j = 0; j < components[i].num_of_events; j++ ) {
reads_t* read_node;
if ( ( read_node = _internal_hl_insert_read_node(&node->values[cmp_iter].read_values) ) == NULL )
return ( PAPI_ENOMEM );
if ( components[i].event_types[j] == 1 )
read_node->value = _local_components[i].values[j];
else
read_node->value = _local_components[i].values[j] - node->values[cmp_iter].offset;
cmp_iter++;
}
}
} else if ( reg_typ == REGION_END ) {
/* determine difference of current value and offset and add
previous total value */
node->values[0].total += node->values[0].offset;
node->values[1].total += _local_cycles - node->values[1].offset;
/* events from components */
for ( i = 0; i < num_of_components; i++ )
for ( j = 0; j < components[i].num_of_events; j++ ) {
/* if event type is istant only save last value */
if ( components[i].event_types[j] == 1 )
node->values[cmp_iter].total += _local_components[i].values[j];
else
node->values[cmp_iter].total += _local_components[i].values[j] - node->values[cmp_iter].offset;
cmp_iter++;
}
}
return ( PAPI_OK );
}
static inline regions_t* _internal_hl_insert_region_node(regions_t** head_node, const char *region )
{
regions_t *new_node;
int i;
int extended_total_num_events;
/* number of all events including region count and CPU cycles */
extended_total_num_events = total_num_events + 2;
/* create new region node */
new_node = malloc(sizeof(regions_t) + extended_total_num_events * sizeof(value_t));
if ( new_node == NULL )
return ( NULL );
new_node->region = (char *)malloc((strlen(region) + 1) * sizeof(char));
if ( new_node->region == NULL )
return ( NULL );
new_node->next = NULL;
new_node->prev = NULL;
strcpy(new_node->region, region);
for ( i = 0; i < extended_total_num_events; i++ ) {
new_node->values[i].total = 0;
new_node->values[i].read_values = NULL;
}
/* insert node in list */
if ( *head_node == NULL ) {
*head_node = new_node;
return new_node;
}
(*head_node)->prev = new_node;
new_node->next = *head_node;
*head_node = new_node;
return new_node;
}
static inline regions_t* _internal_hl_find_region_node(regions_t* head_node, const char *region )
{
regions_t* find_node = head_node;
while ( find_node != NULL ) {
if ( strcmp(find_node->region, region) == 0 ) {
return find_node;
}
find_node = find_node->next;
}
find_node = NULL;
return find_node;
}
static inline threads_t* _internal_hl_insert_thread_node(unsigned long tid)
{
threads_t *new_node = (threads_t*)malloc(sizeof(threads_t));
if ( new_node == NULL )
return ( NULL );
new_node->key = tid;
new_node->value = NULL; /* head node of region list */
tsearch(new_node, &binary_tree->root, compar);
return new_node;
}
static inline threads_t* _internal_hl_find_thread_node(unsigned long tid)
{
threads_t *find_node = binary_tree->find_p;
find_node->key = tid;
void *found = tfind(find_node, &binary_tree->root, compar);
if ( found != NULL ) {
find_node = (*(threads_t**)found);
return find_node;
}
return NULL;
}
static int _internal_hl_store_counters( unsigned long tid, const char *region,
enum region_type reg_typ )
{
int retval;
_papi_hwi_lock( HIGHLEVEL_LOCK );
threads_t* current_thread_node;
/* check if current thread is already stored in tree */
current_thread_node = _internal_hl_find_thread_node(tid);
if ( current_thread_node == NULL ) {
/* insert new node for current thread in tree if type is REGION_BEGIN */
if ( reg_typ == REGION_BEGIN ) {
if ( ( current_thread_node = _internal_hl_insert_thread_node(tid) ) == NULL ) {
_papi_hwi_unlock( HIGHLEVEL_LOCK );
return ( PAPI_ENOMEM );
}
} else {
_papi_hwi_unlock( HIGHLEVEL_LOCK );
return ( PAPI_EINVAL );
}
}
regions_t* current_region_node;
/* check if node for current region already exists */
current_region_node = _internal_hl_find_region_node(current_thread_node->value, region);
if ( current_region_node == NULL ) {
/* create new node for current region in list if type is REGION_BEGIN */
if ( reg_typ == REGION_BEGIN ) {
if ( ( current_region_node = _internal_hl_insert_region_node(¤t_thread_node->value,region) ) == NULL ) {
_papi_hwi_unlock( HIGHLEVEL_LOCK );
return ( PAPI_ENOMEM );
}
} else {
/* ignore no matching REGION_READ */
if ( reg_typ == REGION_READ ) {
verbose_fprintf(stdout, "PAPI-HL Warning: Cannot find matching region for PAPI_hl_read(\"%s\") for thread id=%lu.\n", region, PAPI_thread_id());
retval = PAPI_OK;
} else {
verbose_fprintf(stdout, "PAPI-HL Warning: Cannot find matching region for PAPI_hl_region_end(\"%s\") for thread id=%lu.\n", region, PAPI_thread_id());
retval = PAPI_EINVAL;
}
_papi_hwi_unlock( HIGHLEVEL_LOCK );
return ( retval );
}
}
/* add recorded values to current region */
if ( ( retval = _internal_hl_add_values_to_region( current_region_node, reg_typ ) ) != PAPI_OK ) {
_papi_hwi_unlock( HIGHLEVEL_LOCK );
return ( retval );
}
/* count all REGION_BEGIN and REGION_END calls */
if ( reg_typ == REGION_BEGIN ) region_begin_cnt++;
if ( reg_typ == REGION_END ) region_end_cnt++;
_papi_hwi_unlock( HIGHLEVEL_LOCK );
return ( PAPI_OK );
}
static int _internal_hl_read_counters()
{
int i, j, retval;
for ( i = 0; i < num_of_components; i++ ) {
if ( i < ( num_of_components - 1 ) ) {
retval = PAPI_read( _local_components[i].EventSet, _local_components[i].values);
} else {
/* get cycles for last component */
retval = PAPI_read_ts( _local_components[i].EventSet, _local_components[i].values, &_local_cycles );
}
HLDBG("Thread-ID:%lu, Component-ID:%d\n", PAPI_thread_id(), components[i].component_id);
for ( j = 0; j < components[i].num_of_events; j++ ) {
HLDBG("Thread-ID:%lu, %s:%lld\n", PAPI_thread_id(), components[i].event_names[j], _local_components[i].values[j]);
}
if ( retval != PAPI_OK )
return ( retval );
}
return ( PAPI_OK );
}
static int _internal_hl_read_and_store_counters( const char *region, enum region_type reg_typ )
{
int retval;
/* read all events */
if ( ( retval = _internal_hl_read_counters() ) != PAPI_OK ) {
verbose_fprintf(stdout, "PAPI-HL Error: Could not read counters for thread %lu.\n", PAPI_thread_id());
_internal_hl_clean_up_all(true);
return ( retval );
}
/* store all events */
if ( ( retval = _internal_hl_store_counters( PAPI_thread_id(), region, reg_typ) ) != PAPI_OK ) {
verbose_fprintf(stdout, "PAPI-HL Error: Could not store counters for thread %lu.\n", PAPI_thread_id());
verbose_fprintf(stdout, "PAPI-HL Advice: Check if your regions are matching.\n");
_internal_hl_clean_up_all(true);
return ( retval );
}
return ( PAPI_OK );
}
static int _internal_hl_create_global_binary_tree()
{
if ( ( binary_tree = (binary_tree_t*)malloc(sizeof(binary_tree_t)) ) == NULL )
return ( PAPI_ENOMEM );
binary_tree->root = NULL;
if ( ( binary_tree->find_p = (threads_t*)malloc(sizeof(threads_t)) ) == NULL )
return ( PAPI_ENOMEM );
return ( PAPI_OK );
}
static int _internal_hl_mkdir(const char *dir)
{
int retval;
int errno;
char *tmp = NULL;
char *p = NULL;
size_t len;
if ( ( tmp = strdup(dir) ) == NULL )
return ( PAPI_ENOMEM );
len = strlen(tmp);
if(tmp[len - 1] == '/')
tmp[len - 1] = 0;
for(p = tmp + 1; *p; p++)
{
if(*p == '/')
{
*p = 0;
errno = 0;
retval = mkdir(tmp, S_IRWXU);
if ( retval != 0 && errno != EEXIST )
return ( PAPI_ESYS );
*p = '/';
}
}
retval = mkdir(tmp, S_IRWXU);
if ( retval != 0 && errno != EEXIST )
return ( PAPI_ESYS );
free(tmp);
return ( PAPI_OK );
}
static int _internal_hl_determine_output_path()
{
/* check if PAPI_OUTPUT_DIRECTORY is set */
char *output_prefix = NULL;
if ( getenv("PAPI_OUTPUT_DIRECTORY") != NULL ) {
if ( ( output_prefix = strdup( getenv("PAPI_OUTPUT_DIRECTORY") ) ) == NULL )
return ( PAPI_ENOMEM );
} else {
if ( ( output_prefix = strdup( getcwd(NULL,0) ) ) == NULL )
return ( PAPI_ENOMEM );
}
/* generate absolute path for measurement directory */
if ( ( absolute_output_file_path = (char *)malloc((strlen(output_prefix) + 64) * sizeof(char)) ) == NULL )
return ( PAPI_ENOMEM );
if ( output_counter > 0 )
sprintf(absolute_output_file_path, "%s/papi_%d", output_prefix, output_counter);
else
sprintf(absolute_output_file_path, "%s/papi", output_prefix);
/* check if directory already exists */
struct stat buf;
if ( stat(absolute_output_file_path, &buf) == 0 && S_ISDIR(buf.st_mode) ) {
/* rename old directory by adding a timestamp */
char *new_absolute_output_file_path = NULL;
if ( ( new_absolute_output_file_path = (char *)malloc((strlen(absolute_output_file_path) + 64) * sizeof(char)) ) == NULL )
return ( PAPI_ENOMEM );
/* create timestamp */
time_t t = time(NULL);
struct tm tm = *localtime(&t);
char m_time[32];
sprintf(m_time, "%d%02d%02d-%02d%02d%02d", tm.tm_year+1900, tm.tm_mon + 1, tm.tm_mday, tm.tm_hour, tm.tm_min, tm.tm_sec);
/* add timestamp to existing folder string */
sprintf(new_absolute_output_file_path, "%s-%s", absolute_output_file_path, m_time);
uintmax_t current_unix_time = (uintmax_t)t;
uintmax_t unix_time_from_old_directory = buf.st_mtime;
/* This is a workaround for MPI applications!!!
* Only rename existing measurement directory when it is older than
* current timestamp. If it's not, we assume that another MPI process already created a new measurement directory. */
if ( unix_time_from_old_directory < current_unix_time ) {
if ( rename(absolute_output_file_path, new_absolute_output_file_path) != 0 ) {
verbose_fprintf(stdout, "PAPI-HL Warning: Cannot rename old measurement directory.\n");
verbose_fprintf(stdout, "If you use MPI, another process may have already renamed the directory.\n");
}
}
free(new_absolute_output_file_path);
}
free(output_prefix);
output_counter++;
return ( PAPI_OK );
}
static void _internal_hl_json_line_break_and_indent( FILE* f, bool b, int width )
{
int i;
if ( b ) {
fprintf(f, "\n");
for ( i = 0; i < width; ++i )
fprintf(f, " ");
}
}
static void _internal_hl_json_region_events(FILE* f, bool beautifier, regions_t *regions)
{
char **all_event_names = NULL;
int extended_total_num_events;
int i, j, cmp_iter;
/* generate array of all events including region count and CPU cycles for output */
extended_total_num_events = total_num_events + 2;
all_event_names = (char**)malloc(extended_total_num_events * sizeof(char*));
all_event_names[0] = "region_count";
all_event_names[1] = "cycles";
cmp_iter = 2;
for ( i = 0; i < num_of_components; i++ ) {
for ( j = 0; j < components[i].num_of_events; j++ ) {
all_event_names[cmp_iter++] = components[i].event_names[j];
}
}
for ( j = 0; j < extended_total_num_events; j++ ) {
_internal_hl_json_line_break_and_indent(f, beautifier, 6);
/* print read values if available */
if ( regions->values[j].read_values != NULL) {
reads_t* read_node = regions->values[j].read_values;
/* going to last node */
while ( read_node->next != NULL ) {
read_node = read_node->next;
}
/* read values in reverse order */
int read_cnt = 1;
fprintf(f, "\"%s\":{", all_event_names[j]);
_internal_hl_json_line_break_and_indent(f, beautifier, 7);
fprintf(f, "\"total\":\"%lld\",", regions->values[j].total);
while ( read_node != NULL ) {
_internal_hl_json_line_break_and_indent(f, beautifier, 7);
fprintf(f, "\"read_%d\":\"%lld\"", read_cnt,read_node->value);
read_node = read_node->prev;
if ( read_node == NULL ) {
_internal_hl_json_line_break_and_indent(f, beautifier, 6);
fprintf(f, "}");
if ( j < extended_total_num_events - 1 )
fprintf(f, ",");
} else {
fprintf(f, ",");
}
read_cnt++;
}
} else {
HLDBG(" %s:%lld\n", all_event_names[j], regions->values[j].total);
if ( j == ( extended_total_num_events - 1 ) ) {
fprintf(f, "\"%s\":\"%lld\"", all_event_names[j], regions->values[j].total);
} else {
fprintf(f, "\"%s\":\"%lld\",", all_event_names[j], regions->values[j].total);
}
}
}
free(all_event_names);
}
static void _internal_hl_json_regions(FILE* f, bool beautifier, threads_t* thread_node)
{
/* iterate over regions list */
regions_t *regions = thread_node->value;
/* going to last node */
while ( regions->next != NULL ) {
regions = regions->next;
}
/* read regions in reverse order */
while (regions != NULL) {
HLDBG(" Region:%s\n", regions->region);
_internal_hl_json_line_break_and_indent(f, beautifier, 4);
fprintf(f, "{");
_internal_hl_json_line_break_and_indent(f, beautifier, 5);
fprintf(f, "\"%s\":{", regions->region);
_internal_hl_json_region_events(f, beautifier, regions);
_internal_hl_json_line_break_and_indent(f, beautifier, 5);
fprintf(f, "}");
regions = regions->prev;
_internal_hl_json_line_break_and_indent(f, beautifier, 4);
if (regions == NULL ) {
fprintf(f, "}");
} else {
fprintf(f, "},");
}
}
}
static void _internal_hl_json_threads(FILE* f, bool beautifier, unsigned long* tids, int threads_num)
{
int i;
_internal_hl_json_line_break_and_indent(f, beautifier, 1);
fprintf(f, "\"threads\":[");
/* get regions of all threads */
for ( i = 0; i < threads_num; i++ )
{
HLDBG("Thread ID:%lu\n", tids[i]);
/* find values of current thread in global binary tree */
threads_t* thread_node = _internal_hl_find_thread_node(tids[i]);
if ( thread_node != NULL ) {
/* do we really need the exact thread id? */
_internal_hl_json_line_break_and_indent(f, beautifier, 2);
fprintf(f, "{");
_internal_hl_json_line_break_and_indent(f, beautifier, 3);
fprintf(f, "\"id\":\"%lu\",", thread_node->key);
/* in case we only store iterator id as thread id */
//fprintf(f, "\"ID\":%d,", i);
_internal_hl_json_line_break_and_indent(f, beautifier, 3);
fprintf(f, "\"regions\":[");
_internal_hl_json_regions(f, beautifier, thread_node);
_internal_hl_json_line_break_and_indent(f, beautifier, 3);
fprintf(f, "]");
_internal_hl_json_line_break_and_indent(f, beautifier, 2);
if ( i < threads_num - 1 ) {
fprintf(f, "},");
} else {
fprintf(f, "}");
}
}
}
_internal_hl_json_line_break_and_indent(f, beautifier, 1);
fprintf(f, "]");
}
static void _internal_hl_write_output()
{
if ( output_generated == false )
{
_papi_hwi_lock( HIGHLEVEL_LOCK );
if ( output_generated == false ) {
unsigned long *tids = NULL;
int number_of_threads;
FILE *output_file;
/* current CPU frequency in MHz */
int cpu_freq;
if ( region_begin_cnt == region_end_cnt ) {
verbose_fprintf(stdout, "PAPI-HL Info: Print results...\n");
} else {
verbose_fprintf(stdout, "PAPI-HL Warning: Cannot generate output due to not matching regions.\n");
output_generated = true;
HLDBG("region_begin_cnt=%d, region_end_cnt=%d\n", region_begin_cnt, region_end_cnt);
_papi_hwi_unlock( HIGHLEVEL_LOCK );
return;
}
/* create new measurement directory */
if ( ( _internal_hl_mkdir(absolute_output_file_path) ) != PAPI_OK ) {
verbose_fprintf(stdout, "PAPI-HL Error: Cannot create measurement directory %s.\n", absolute_output_file_path);
return;
}
/* determine rank for output file */
int rank = _internal_hl_determine_rank();
if ( rank < 0 )
{
/* generate unique rank number */
sprintf(absolute_output_file_path + strlen(absolute_output_file_path), "/rank_XXXXXX");
int fd;
fd = mkstemp(absolute_output_file_path);
close(fd);
}
else
{
sprintf(absolute_output_file_path + strlen(absolute_output_file_path), "/rank_%04d", rank);
}
/* determine current cpu frequency */
cpu_freq = PAPI_get_opt( PAPI_CLOCKRATE, NULL );
output_file = fopen(absolute_output_file_path, "w");
if ( output_file == NULL )
{
verbose_fprintf(stdout, "PAPI-HL Error: Cannot create output file %s!\n", absolute_output_file_path);
return;
}
else
{
/* list all threads */
if ( PAPI_list_threads( tids, &number_of_threads ) != PAPI_OK ) {
verbose_fprintf(stdout, "PAPI-HL Error: PAPI_list_threads call failed!\n");
return;
}
if ( ( tids = malloc( number_of_threads * sizeof(unsigned long) ) ) == NULL ) {
verbose_fprintf(stdout, "PAPI-HL Error: OOM!\n");
return;
}
if ( PAPI_list_threads( tids, &number_of_threads ) != PAPI_OK ) {
verbose_fprintf(stdout, "PAPI-HL Error: PAPI_list_threads call failed!\n");
return;
}
/* start writing json file */
/* JSON beautifier (line break and indent) */
bool beautifier = true;
/* start of JSON file */
fprintf(output_file, "{");
_internal_hl_json_line_break_and_indent(output_file, beautifier, 1);
fprintf(output_file, "\"cpu in mhz\":\"%d\",", cpu_freq);
/* write all regions with events per thread */
_internal_hl_json_threads(output_file, beautifier, tids, number_of_threads);
/* end of JSON file */
_internal_hl_json_line_break_and_indent(output_file, beautifier, 0);
fprintf(output_file, "}");
fprintf(output_file, "\n");
fclose(output_file);
free(tids);
if ( getenv("PAPI_REPORT") != NULL ) {
/* print output to stdout */
printf("\n\nPAPI-HL Output:\n");
output_file = fopen(absolute_output_file_path, "r");
int c = fgetc(output_file);
while (c != EOF)
{
printf("%c", c);
c = fgetc(output_file);
}
printf("\n");
fclose(output_file);
}
}
output_generated = true;
}
_papi_hwi_unlock( HIGHLEVEL_LOCK );
}
}
static void _internal_hl_clean_up_local_data()
{
int i, retval;
/* destroy all EventSets from local data */
if ( _local_components != NULL ) {
HLDBG("Thread-ID:%lu\n", PAPI_thread_id());
for ( i = 0; i < num_of_components; i++ ) {
if ( ( retval = PAPI_stop( _local_components[i].EventSet, _local_components[i].values ) ) != PAPI_OK )
/* only print error when event set is running */
if ( retval != -9 )
verbose_fprintf(stdout, "PAPI-HL Error: PAPI_stop failed: %d.\n", retval);
if ( ( retval = PAPI_cleanup_eventset (_local_components[i].EventSet) ) != PAPI_OK )
verbose_fprintf(stdout, "PAPI-HL Error: PAPI_cleanup_eventset failed: %d.\n", retval);
if ( ( retval = PAPI_destroy_eventset (&_local_components[i].EventSet) ) != PAPI_OK )
verbose_fprintf(stdout, "PAPI-HL Error: PAPI_destroy_eventset failed: %d.\n", retval);
free(_local_components[i].values);
}
free(_local_components);
_local_components = NULL;
/* count global thread variable */
_papi_hwi_lock( HIGHLEVEL_LOCK );
num_of_cleaned_threads++;
_papi_hwi_unlock( HIGHLEVEL_LOCK );
}
_local_state = PAPIHL_DEACTIVATED;
}
static void _internal_hl_clean_up_global_data()
{
int i;
int extended_total_num_events;
/* clean up binary tree of recorded events */
threads_t *thread_node;
if ( binary_tree != NULL ) {
while ( binary_tree->root != NULL ) {
thread_node = *(threads_t **)binary_tree->root;
/* clean up double linked list of region data */
regions_t *region = thread_node->value;
regions_t *tmp;
while ( region != NULL ) {
/* clean up read node list */
extended_total_num_events = total_num_events + 2;
for ( i = 0; i < extended_total_num_events; i++ ) {
reads_t *read_node = region->values[i].read_values;
reads_t *read_node_tmp;
while ( read_node != NULL ) {
read_node_tmp = read_node;
read_node = read_node->next;
free(read_node_tmp);
}
}
tmp = region;
region = region->next;
free(tmp->region);
free(tmp);
}
free(region);
tdelete(thread_node, &binary_tree->root, compar);
free(thread_node);
}
}
/* we cannot free components here since other threads could still use them */
/* clean up requested event names */
for ( i = 0; i < num_of_requested_events; i++ )
free(requested_event_names[i]);
free(requested_event_names);
free(absolute_output_file_path);
}
static void _internal_hl_clean_up_all(bool deactivate)
{
int i, num_of_threads;
/* we assume that output has been already generated or
* cannot be generated due to previous errors */
output_generated = true;
/* clean up thread local data */
if ( _local_state == PAPIHL_ACTIVE ) {
HLDBG("Clean up thread local data for thread %lu\n", PAPI_thread_id());
_internal_hl_clean_up_local_data();
}
/* clean up global data */
if ( state == PAPIHL_ACTIVE ) {
_papi_hwi_lock( HIGHLEVEL_LOCK );
if ( state == PAPIHL_ACTIVE ) {
verbose_fprintf(stdout, "PAPI-HL Info: Output generation is deactivated!\n");
HLDBG("Clean up global data for thread %lu\n", PAPI_thread_id());
_internal_hl_clean_up_global_data();
/* check if all other registered threads have cleaned up */
PAPI_list_threads(NULL, &num_of_threads);
HLDBG("Number of registered threads: %d.\n", num_of_threads);
HLDBG("Number of cleaned threads: %d.\n", num_of_cleaned_threads);
if ( _internal_hl_check_for_clean_thread_states() == PAPI_OK &&
num_of_threads == num_of_cleaned_threads ) {
PAPI_shutdown();
/* clean up components */
for ( i = 0; i < num_of_components; i++ ) {
free(components[i].event_names);
free(components[i].event_codes);
free(components[i].event_types);
}
free(components);
HLDBG("PAPI-HL shutdown!\n");
} else {
verbose_fprintf(stdout, "PAPI-HL Warning: Could not call PAPI_shutdown() since some threads still have running event sets. Make sure to call PAPI_hl_cleanup_thread() at the end of all parallel regions and PAPI_hl_finalize() in the master thread!\n");
}
/* deactivate PAPI-HL */
if ( deactivate )
state = PAPIHL_DEACTIVATED;
}
_papi_hwi_unlock( HIGHLEVEL_LOCK );
}
}
static int _internal_hl_check_for_clean_thread_states()
{
EventSetInfo_t *ESI;
DynamicArray_t *map = &_papi_hwi_system_info.global_eventset_map;
int i;
for( i = 0; i < map->totalSlots; i++ ) {
ESI = map->dataSlotArray[i];
if ( ESI ) {
if ( ESI->state & PAPI_RUNNING )
return ( PAPI_EISRUN );
}
}
return ( PAPI_OK );
}
/** @class PAPI_hl_init
* @brief Initializes the high-level PAPI library.
*
* @par C Interface:
* \#include <papi.h> @n
* int PAPI_hl_init();
*
* @retval PAPI_OK
* @retval PAPI_HIGH_LEVEL_INITED
* -- Initialization was already called.
* @retval PAPI_EMISC
* -- Initialization failed.
* @retval PAPI_ENOMEM
* -- Insufficient memory.
*
* PAPI_hl_init initializes the PAPI library and some high-level specific features.
* If your application is making use of threads you do not need to call any other low level
* initialization functions as PAPI_hl_init includes thread support.
* Note that the first call of PAPI_hl_region_begin will automatically call PAPI_hl_init
* if not already called.
*
* @par Example:
*
* @code
* int retval;
*
* retval = PAPI_hl_init();
* if ( retval != PAPI_OK )
* handle_error(1);
*
* @endcode
*
* @see PAPI_hl_cleanup_thread
* @see PAPI_hl_finalize
* @see PAPI_hl_set_events
* @see PAPI_hl_region_begin
* @see PAPI_hl_read
* @see PAPI_hl_region_end
* @see PAPI_hl_print_output
*/
int
PAPI_hl_init()
{
if ( state == PAPIHL_ACTIVE ) {
if ( hl_initiated == false && hl_finalized == false ) {
_internal_hl_onetime_library_init();
/* check if the library has been initialized successfully */
if ( state == PAPIHL_DEACTIVATED )
return ( PAPI_EMISC );
return ( PAPI_OK );
}
return ( PAPI_ENOINIT );
}
return ( PAPI_EMISC );
}
/** @class PAPI_hl_cleanup_thread
* @brief Cleans up all thread-local data.
*
* @par C Interface:
* \#include <papi.h> @n
* void PAPI_hl_cleanup_thread( );
*
* @retval PAPI_OK
* @retval PAPI_EMISC
* -- Thread has been already cleaned up or PAPI is deactivated due to previous errors.
*
* PAPI_hl_cleanup_thread shuts down thread-local event sets and cleans local
* data structures. It is recommended to use this function in combination with
* PAPI_hl_finalize if your application is making use of threads.
*
* @par Example:
*
* @code
* int retval;
*
* #pragma omp parallel
* {
* retval = PAPI_hl_region_begin("computation");
* if ( retval != PAPI_OK )
* handle_error(1);
*
* //Do some computation here
*
* retval = PAPI_hl_region_end("computation");
* if ( retval != PAPI_OK )
* handle_error(1);
*
* retval = PAPI_hl_cleanup_thread();
* if ( retval != PAPI_OK )
* handle_error(1);
* }
*
* retval = PAPI_hl_finalize();
* if ( retval != PAPI_OK )
* handle_error(1);
*
* @endcode
*
* @see PAPI_hl_init
* @see PAPI_hl_finalize
* @see PAPI_hl_set_events
* @see PAPI_hl_region_begin
* @see PAPI_hl_read
* @see PAPI_hl_region_end
* @see PAPI_hl_print_output
*/
int PAPI_hl_cleanup_thread()
{
if ( state == PAPIHL_ACTIVE &&
hl_initiated == true &&
_local_state == PAPIHL_ACTIVE ) {
/* do not clean local data from master thread */
if ( master_thread_id != PAPI_thread_id() )
_internal_hl_clean_up_local_data();
return ( PAPI_OK );
}
return ( PAPI_EMISC );
}
/** @class PAPI_hl_finalize
* @brief Finalizes the high-level PAPI library.
*
* @par C Interface:
* \#include <papi.h> @n
* int PAPI_hl_finalize( );
*
* @retval PAPI_OK
* @retval PAPI_EMISC
* -- PAPI has been already finalized or deactivated due to previous errors.
*
* PAPI_hl_finalize finalizes the high-level library by destroying all counting event sets
* and internal data structures.
*
* @par Example:
*
* @code
* int retval;
*
* retval = PAPI_hl_finalize();
* if ( retval != PAPI_OK )
* handle_error(1);
*
* @endcode
*
* @see PAPI_hl_init
* @see PAPI_hl_cleanup_thread
* @see PAPI_hl_set_events
* @see PAPI_hl_region_begin
* @see PAPI_hl_read
* @see PAPI_hl_region_end
* @see PAPI_hl_print_output
*/
int PAPI_hl_finalize()
{
if ( state == PAPIHL_ACTIVE && hl_initiated == true ) {
_internal_hl_clean_up_all(true);
return ( PAPI_OK );
}
return ( PAPI_EMISC );
}
/** @class PAPI_hl_set_events
* @brief Generates event sets based on a list of hardware events.
*
* @par C Interface:
* \#include <papi.h> @n
* int PAPI_hl_set_events( const char* events );
*
* @param events
* -- list of hardware events separated by commas
*
* @retval PAPI_OK
* @retval PAPI_EMISC
* -- PAPI has been deactivated due to previous errors.
* @retval PAPI_ENOMEM
* -- Insufficient memory.
*
* PAPI_hl_set_events offers the user the possibility to determine hardware events in
* the source code as an alternative to the environment variable PAPI_EVENTS.
* Note that the content of PAPI_EVENTS is ignored if PAPI_hl_set_events was successfully executed.
* If the events argument cannot be interpreted, default hardware events are
* taken for the measurement.
*
* @par Example:
*
* @code
* int retval;
*
* retval = PAPI_hl_set_events("PAPI_TOT_INS,PAPI_TOT_CYC");
* if ( retval != PAPI_OK )
* handle_error(1);
*
* @endcode
*
* @see PAPI_hl_init
* @see PAPI_hl_cleanup_thread
* @see PAPI_hl_finalize
* @see PAPI_hl_region_begin
* @see PAPI_hl_read
* @see PAPI_hl_region_end
* @see PAPI_hl_print_output
*/
int
PAPI_hl_set_events(const char* events)
{
int retval;
if ( state == PAPIHL_ACTIVE ) {
/* This may only be called once after the high-level API was successfully
* initiated. Any second call just returns PAPI_OK without doing an
* expensive lock. */
if ( hl_initiated == true ) {
if ( events_determined == false )
{
_papi_hwi_lock( HIGHLEVEL_LOCK );
if ( events_determined == false && state == PAPIHL_ACTIVE )
{
if ( ( retval = _internal_hl_read_events(events) ) != PAPI_OK ) {
state = PAPIHL_DEACTIVATED;
_internal_hl_clean_up_global_data();
_papi_hwi_unlock( HIGHLEVEL_LOCK );
return ( retval );
}
if ( ( retval = _internal_hl_create_global_binary_tree() ) != PAPI_OK ) {
state = PAPIHL_DEACTIVATED;
_internal_hl_clean_up_global_data();
_papi_hwi_unlock( HIGHLEVEL_LOCK );
return ( retval );
}
}
_papi_hwi_unlock( HIGHLEVEL_LOCK );
}
}
/* in case the first locked thread ran into problems */
if ( state == PAPIHL_DEACTIVATED)
return ( PAPI_EMISC );
return ( PAPI_OK );
}
return ( PAPI_EMISC );
}
/** @class PAPI_hl_print_output
* @brief Prints values of hardware events.
*
* @par C Interface:
* \#include <papi.h> @n
* void PAPI_hl_print_output( );
*
* PAPI_hl_print_output prints the measured values of hardware events in one file for serial
* or thread parallel applications.
* Multi-processing applications, such as MPI, will have one output file per process.
* Each output file contains measured values of all threads.
* The entire measurement can be converted in a better readable output via python.
* For more information, see <a href="https://bitbucket.org/icl/papi/wiki/papi-hl.md">High Level API</a>.
* Note that if PAPI_hl_print_output is not called explicitly PAPI will try to generate output
* at the end of the application. However, for some reason, this feature sometimes does not work.
* It is therefore recommended to call PAPI_hl_print_output for larger applications.
*
* @par Example:
*
* @code
*
* PAPI_hl_print_output();
*
* @endcode
*
* @see PAPI_hl_init
* @see PAPI_hl_cleanup_thread
* @see PAPI_hl_finalize
* @see PAPI_hl_set_events
* @see PAPI_hl_region_begin
* @see PAPI_hl_read
* @see PAPI_hl_region_end
*/
void
PAPI_hl_print_output()
{
if ( state == PAPIHL_ACTIVE &&
hl_initiated == true &&
output_generated == false ) {
_internal_hl_write_output();
}
}
/** @class PAPI_hl_region_begin
* @brief Reads and stores hardware events at the beginning of an instrumented code region.
*
* @par C Interface:
* \#include <papi.h> @n
* int PAPI_hl_region_begin( const char* region );
*
* @param region
* -- a unique region name
*
* @retval PAPI_OK
* @retval PAPI_ENOTRUN
* -- EventSet is currently not running or could not determined.
* @retval PAPI_ESYS
* -- A system or C library call failed inside PAPI, see the errno variable.
* @retval PAPI_EMISC
* -- PAPI has been deactivated due to previous errors.
* @retval PAPI_ENOMEM
* -- Insufficient memory.
*
* PAPI_hl_region_begin reads hardware events and stores them internally at the beginning
* of an instrumented code region.
* If not specified via environment variable PAPI_EVENTS, default events are used.
* The first call sets all counters implicitly to zero and starts counting.
* Note that if PAPI_EVENTS is not set or cannot be interpreted, default hardware events are
* recorded.
*
* @par Example:
*
* @code
* export PAPI_EVENTS="PAPI_TOT_INS,PAPI_TOT_CYC"
* @endcode
*
*
* @code
* int retval;
*
* retval = PAPI_hl_region_begin("computation");
* if ( retval != PAPI_OK )
* handle_error(1);
*
* //Do some computation here
*
* retval = PAPI_hl_region_end("computation");
* if ( retval != PAPI_OK )
* handle_error(1);
*
* @endcode
*
* @see PAPI_hl_read
* @see PAPI_hl_region_end
*/
int
PAPI_hl_region_begin( const char* region )
{
int retval;
if ( state == PAPIHL_DEACTIVATED ) {
/* check if we have to clean up local stuff */
if ( _local_state == PAPIHL_ACTIVE )
_internal_hl_clean_up_local_data();
return ( PAPI_EMISC );
}
if ( hl_finalized == true )
return ( PAPI_ENOTRUN );
if ( hl_initiated == false ) {
if ( ( retval = PAPI_hl_init() ) != PAPI_OK )
return ( retval );
}
if ( events_determined == false ) {
if ( ( retval = PAPI_hl_set_events(NULL) ) != PAPI_OK )
return ( retval );
}
if ( _local_components == NULL ) {
if ( ( retval = _internal_hl_create_event_sets() ) != PAPI_OK ) {
HLDBG("Could not create local events sets for thread %lu.\n", PAPI_thread_id());
_internal_hl_clean_up_all(true);
return ( retval );
}
}
/* read and store all events */
HLDBG("Thread ID:%lu, Region:%s\n", PAPI_thread_id(), region);
if ( ( retval = _internal_hl_read_and_store_counters(region, REGION_BEGIN) ) != PAPI_OK )
return ( retval );
_local_region_begin_cnt++;
return ( PAPI_OK );
}
/** @class PAPI_hl_read
* @brief Reads and stores hardware events inside of an instrumented code region.
*
* @par C Interface:
* \#include <papi.h> @n
* int PAPI_hl_read( const char* region );
*
* @param region
* -- a unique region name corresponding to PAPI_hl_region_begin
*
* @retval PAPI_OK
* @retval PAPI_ENOTRUN
* -- EventSet is currently not running or could not determined.
* @retval PAPI_ESYS
* -- A system or C library call failed inside PAPI, see the errno variable.
* @retval PAPI_EMISC
* -- PAPI has been deactivated due to previous errors.
* @retval PAPI_ENOMEM
* -- Insufficient memory.
*
* PAPI_hl_read reads hardware events and stores them internally inside
* of an instrumented code region.
* Assumes that PAPI_hl_region_begin was called before.
*
* @par Example:
*
* @code
* int retval;
*
* retval = PAPI_hl_region_begin("computation");
* if ( retval != PAPI_OK )
* handle_error(1);
*
* //Do some computation here
*
* retval = PAPI_hl_read("computation");
* if ( retval != PAPI_OK )
* handle_error(1);
*
* //Do some computation here
*
* retval = PAPI_hl_region_end("computation");
* if ( retval != PAPI_OK )
* handle_error(1);
*
* @endcode
*
* @see PAPI_hl_region_begin
* @see PAPI_hl_region_end
*/
int
PAPI_hl_read(const char* region)
{
int retval;
if ( state == PAPIHL_DEACTIVATED ) {
/* check if we have to clean up local stuff */
if ( _local_state == PAPIHL_ACTIVE )
_internal_hl_clean_up_local_data();
return ( PAPI_EMISC );
}
if ( _local_region_begin_cnt == 0 ) {
verbose_fprintf(stdout, "PAPI-HL Warning: Cannot find matching region for PAPI_hl_read(\"%s\") for thread %lu.\n", region, PAPI_thread_id());
return ( PAPI_EMISC );
}
if ( _local_components == NULL )
return ( PAPI_ENOTRUN );
/* read and store all events */
HLDBG("Thread ID:%lu, Region:%s\n", PAPI_thread_id(), region);
if ( ( retval = _internal_hl_read_and_store_counters(region, REGION_READ) ) != PAPI_OK )
return ( retval );
return ( PAPI_OK );
}
/** @class PAPI_hl_region_end
* @brief Reads and stores hardware events at the end of an instrumented code region.
*
* @par C Interface:
* \#include <papi.h> @n
* int PAPI_hl_region_end( const char* region );
*
* @param region
* -- a unique region name corresponding to PAPI_hl_region_begin
*
* @retval PAPI_OK
* @retval PAPI_ENOTRUN
* -- EventSet is currently not running or could not determined.
* @retval PAPI_ESYS
* -- A system or C library call failed inside PAPI, see the errno variable.
* @retval PAPI_EMISC
* -- PAPI has been deactivated due to previous errors.
* @retval PAPI_ENOMEM
* -- Insufficient memory.
*
* PAPI_hl_region_end reads hardware events and stores the difference to the values from
* PAPI_hl_region_begin at the end of an instrumented code region.
* Assumes that PAPI_hl_region_begin was called before.
* Note that an output is automatically generated when your application terminates.
* If the automatic output does not work for any reason, PAPI_hl_print_output must be called.
*
*
* @par Example:
*
* @code
* int retval;
*
* retval = PAPI_hl_region_begin("computation");
* if ( retval != PAPI_OK )
* handle_error(1);
*
* //Do some computation here
*
* retval = PAPI_hl_region_end("computation");
* if ( retval != PAPI_OK )
* handle_error(1);
*
* @endcode
*
* @see PAPI_hl_region_begin
* @see PAPI_hl_read
*/
int
PAPI_hl_region_end( const char* region )
{
int retval;
if ( state == PAPIHL_DEACTIVATED ) {
/* check if we have to clean up local stuff */
if ( _local_state == PAPIHL_ACTIVE )
_internal_hl_clean_up_local_data();
return ( PAPI_EMISC );
}
if ( _local_region_begin_cnt == 0 ) {
verbose_fprintf(stdout, "PAPI-HL Warning: Cannot find matching region for PAPI_hl_region_end(\"%s\") for thread %lu.\n", region, PAPI_thread_id());
return ( PAPI_EMISC );
}
if ( _local_components == NULL )
return ( PAPI_ENOTRUN );
/* read and store all events */
HLDBG("Thread ID:%lu, Region:%s\n", PAPI_thread_id(), region);
if ( ( retval = _internal_hl_read_and_store_counters(region, REGION_END) ) != PAPI_OK )
return ( retval );
_local_region_end_cnt++;
return ( PAPI_OK );
}
|
resize.c | /*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% RRRR EEEEE SSSSS IIIII ZZZZZ EEEEE %
% R R E SS I ZZ E %
% RRRR EEE SSS I ZZZ EEE %
% R R E SS I ZZ E %
% R R EEEEE SSSSS IIIII ZZZZZ EEEEE %
% %
% %
% MagickCore Image Resize Methods %
% %
% Software Design %
% Cristy %
% July 1992 %
% %
% %
% Copyright 1999-2018 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://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/accelerate-private.h"
#include "magick/artifact.h"
#include "magick/blob.h"
#include "magick/cache.h"
#include "magick/cache-view.h"
#include "magick/channel.h"
#include "magick/color.h"
#include "magick/color-private.h"
#include "magick/draw.h"
#include "magick/exception.h"
#include "magick/exception-private.h"
#include "magick/gem.h"
#include "magick/image.h"
#include "magick/image-private.h"
#include "magick/list.h"
#include "magick/memory_.h"
#include "magick/memory-private.h"
#include "magick/magick.h"
#include "magick/pixel-private.h"
#include "magick/property.h"
#include "magick/monitor.h"
#include "magick/monitor-private.h"
#include "magick/nt-base-private.h"
#include "magick/pixel.h"
#include "magick/pixel-private.h"
#include "magick/option.h"
#include "magick/resample.h"
#include "magick/resample-private.h"
#include "magick/resize.h"
#include "magick/resize-private.h"
#include "magick/resource_.h"
#include "magick/string_.h"
#include "magick/string-private.h"
#include "magick/thread-private.h"
#include "magick/token.h"
#include "magick/utility.h"
#include "magick/version.h"
#if defined(MAGICKCORE_LQR_DELEGATE)
#include <lqr.h>
#endif
/*
Typedef declarations.
*/
struct _ResizeFilter
{
MagickRealType
(*filter)(const MagickRealType,const ResizeFilter *),
(*window)(const MagickRealType,const ResizeFilter *),
support, /* filter region of support - the filter support limit */
window_support, /* window support, usally equal to support (expert only) */
scale, /* dimension scaling to fit window support (usally 1.0) */
blur, /* x-scale (blur-sharpen) */
coefficient[7]; /* cubic coefficents for BC-cubic filters */
ResizeWeightingFunctionType
filterWeightingType,
windowWeightingType;
size_t
signature;
};
/*
Forward declaractions.
*/
static MagickRealType
I0(MagickRealType x),
BesselOrderOne(MagickRealType),
Sinc(const MagickRealType, const ResizeFilter *),
SincFast(const MagickRealType, const ResizeFilter *);
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
+ F i l t e r F u n c t i o n s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% These are the various filter and windowing functions that are provided.
%
% They are internal to this module only. See AcquireResizeFilterInfo() for
% details of the access to these functions, via the GetResizeFilterSupport()
% and GetResizeFilterWeight() API interface.
%
% The individual filter functions have this format...
%
% static MagickRealtype *FilterName(const MagickRealType x,
% const MagickRealType support)
%
% A description of each parameter follows:
%
% o x: the distance from the sampling point generally in the range of 0 to
% support. The GetResizeFilterWeight() ensures this a positive value.
%
% o resize_filter: current filter information. This allows function to
% access support, and possibly other pre-calculated information defining
% the functions.
%
*/
static MagickRealType Blackman(const MagickRealType x,
const ResizeFilter *magick_unused(resize_filter))
{
/*
Blackman: 2nd order cosine windowing function:
0.42 + 0.5 cos(pi x) + 0.08 cos(2pi x)
Refactored by Chantal Racette and Nicolas Robidoux to one trig call and
five flops.
*/
const MagickRealType cosine=cos((double) (MagickPI*x));
magick_unreferenced(resize_filter);
return(0.34+cosine*(0.5+cosine*0.16));
}
static MagickRealType Bohman(const MagickRealType x,
const ResizeFilter *magick_unused(resize_filter))
{
/*
Bohman: 2rd Order cosine windowing function:
(1-x) cos(pi x) + sin(pi x) / pi.
Refactored by Nicolas Robidoux to one trig call, one sqrt call, and 7 flops,
taking advantage of the fact that the support of Bohman is 1.0 (so that we
know that sin(pi x) >= 0).
*/
const double cosine=cos((double) (MagickPI*x));
const double sine=sqrt(1.0-cosine*cosine);
magick_unreferenced(resize_filter);
return((MagickRealType) ((1.0-x)*cosine+(1.0/MagickPI)*sine));
}
static MagickRealType Box(const MagickRealType magick_unused(x),
const ResizeFilter *magick_unused(resize_filter))
{
/*
A Box filter is a equal weighting function (all weights equal).
DO NOT LIMIT results by support or resize point sampling will work
as it requests points beyond its normal 0.0 support size.
*/
magick_unreferenced(x);
magick_unreferenced(resize_filter);
return(1.0);
}
static MagickRealType Cosine(const MagickRealType x,
const ResizeFilter *magick_unused(resize_filter))
{
/*
Cosine window function:
cos((pi/2)*x).
*/
magick_unreferenced(resize_filter);
return((MagickRealType)cos((double) (MagickPI2*x)));
}
static MagickRealType CubicBC(const MagickRealType x,
const ResizeFilter *resize_filter)
{
/*
Cubic Filters using B,C determined values:
Mitchell-Netravali B = 1/3 C = 1/3 "Balanced" cubic spline filter
Catmull-Rom B = 0 C = 1/2 Interpolatory and exact on linears
Spline B = 1 C = 0 B-Spline Gaussian approximation
Hermite B = 0 C = 0 B-Spline interpolator
See paper by Mitchell and Netravali, Reconstruction Filters in Computer
Graphics Computer Graphics, Volume 22, Number 4, August 1988
http://www.cs.utexas.edu/users/fussell/courses/cs384g/lectures/mitchell/
Mitchell.pdf.
Coefficents are determined from B,C values:
P0 = ( 6 - 2*B )/6 = coeff[0]
P1 = 0
P2 = (-18 +12*B + 6*C )/6 = coeff[1]
P3 = ( 12 - 9*B - 6*C )/6 = coeff[2]
Q0 = ( 8*B +24*C )/6 = coeff[3]
Q1 = ( -12*B -48*C )/6 = coeff[4]
Q2 = ( 6*B +30*C )/6 = coeff[5]
Q3 = ( - 1*B - 6*C )/6 = coeff[6]
which are used to define the filter:
P0 + P1*x + P2*x^2 + P3*x^3 0 <= x < 1
Q0 + Q1*x + Q2*x^2 + Q3*x^3 1 <= x < 2
which ensures function is continuous in value and derivative (slope).
*/
if (x < 1.0)
return(resize_filter->coefficient[0]+x*(x*
(resize_filter->coefficient[1]+x*resize_filter->coefficient[2])));
if (x < 2.0)
return(resize_filter->coefficient[3]+x*(resize_filter->coefficient[4]+x*
(resize_filter->coefficient[5]+x*resize_filter->coefficient[6])));
return(0.0);
}
static MagickRealType Gaussian(const MagickRealType x,
const ResizeFilter *resize_filter)
{
/*
Gaussian with a sigma = 1/2 (or as user specified)
Gaussian Formula (1D) ...
exp( -(x^2)/((2.0*sigma^2) ) / (sqrt(2*PI)*sigma^2))
Gaussian Formula (2D) ...
exp( -(x^2+y^2)/(2.0*sigma^2) ) / (PI*sigma^2) )
or for radius
exp( -(r^2)/(2.0*sigma^2) ) / (PI*sigma^2) )
Note that it is only a change from 1-d to radial form is in the
normalization multiplier which is not needed or used when Gaussian is used
as a filter.
The constants are pre-calculated...
coeff[0]=sigma;
coeff[1]=1.0/(2.0*sigma^2);
coeff[2]=1.0/(sqrt(2*PI)*sigma^2);
exp( -coeff[1]*(x^2)) ) * coeff[2];
However the multiplier coeff[1] is need, the others are informative only.
This separates the gaussian 'sigma' value from the 'blur/support'
settings allowing for its use in special 'small sigma' gaussians,
without the filter 'missing' pixels because the support becomes too
small.
*/
return(exp((double)(-resize_filter->coefficient[1]*x*x)));
}
static MagickRealType Hanning(const MagickRealType x,
const ResizeFilter *magick_unused(resize_filter))
{
/*
Cosine window function:
0.5+0.5*cos(pi*x).
*/
const MagickRealType cosine=cos((double) (MagickPI*x));
magick_unreferenced(resize_filter);
return(0.5+0.5*cosine);
}
static MagickRealType Hamming(const MagickRealType x,
const ResizeFilter *magick_unused(resize_filter))
{
/*
Offset cosine window function:
.54 + .46 cos(pi x).
*/
const MagickRealType cosine=cos((double) (MagickPI*x));
magick_unreferenced(resize_filter);
return(0.54+0.46*cosine);
}
static MagickRealType Jinc(const MagickRealType x,
const ResizeFilter *magick_unused(resize_filter))
{
/*
See Pratt "Digital Image Processing" p.97 for Jinc/Bessel functions.
http://mathworld.wolfram.com/JincFunction.html and page 11 of
http://www.ph.ed.ac.uk/%7ewjh/teaching/mo/slides/lens/lens.pdf
The original "zoom" program by Paul Heckbert called this "Bessel". But
really it is more accurately named "Jinc".
*/
magick_unreferenced(resize_filter);
if (x == 0.0)
return((MagickRealType) (0.5*MagickPI));
return(BesselOrderOne((MagickRealType) MagickPI*x)/x);
}
static MagickRealType Kaiser(const MagickRealType x,
const ResizeFilter *resize_filter)
{
/*
Kaiser Windowing Function (bessel windowing)
I0( beta * sqrt( 1-x^2) ) / IO(0)
Beta (coeff[0]) is a free value from 5 to 8 (defaults to 6.5).
However it is typically defined in terms of Alpha*PI
The normalization factor (coeff[1]) is not actually needed,
but without it the filters has a large value at x=0 making it
difficult to compare the function with other windowing functions.
*/
return(resize_filter->coefficient[1]*I0(resize_filter->coefficient[0]*
sqrt((double) (1.0-x*x))));
}
static MagickRealType Lagrange(const MagickRealType x,
const ResizeFilter *resize_filter)
{
MagickRealType
value;
register ssize_t
i;
ssize_t
n,
order;
/*
Lagrange piecewise polynomial fit of sinc: N is the 'order' of the lagrange
function and depends on the overall support window size of the filter. That
is: for a support of 2, it gives a lagrange-4 (piecewise cubic function).
"n" identifies the piece of the piecewise polynomial.
See Survey: Interpolation Methods, IEEE Transactions on Medical Imaging,
Vol 18, No 11, November 1999, p1049-1075, -- Equation 27 on p1064.
*/
if (x > resize_filter->support)
return(0.0);
order=(ssize_t) (2.0*resize_filter->window_support); /* number of pieces */
n=(ssize_t) (resize_filter->window_support+x);
value=1.0f;
for (i=0; i < order; i++)
if (i != n)
value*=(n-i-x)/(n-i);
return(value);
}
static MagickRealType Quadratic(const MagickRealType x,
const ResizeFilter *magick_unused(resize_filter))
{
/*
2rd order (quadratic) B-Spline approximation of Gaussian.
*/
magick_unreferenced(resize_filter);
if (x < 0.5)
return(0.75-x*x);
if (x < 1.5)
return(0.5*(x-1.5)*(x-1.5));
return(0.0);
}
static MagickRealType Sinc(const MagickRealType x,
const ResizeFilter *magick_unused(resize_filter))
{
/*
Scaled sinc(x) function using a trig call:
sinc(x) == sin(pi x)/(pi x).
*/
magick_unreferenced(resize_filter);
if (x != 0.0)
{
const MagickRealType alpha=(MagickRealType) (MagickPI*x);
return(sin((double) alpha)/alpha);
}
return((MagickRealType) 1.0);
}
static MagickRealType SincFast(const MagickRealType x,
const ResizeFilter *magick_unused(resize_filter))
{
/*
Approximations of the sinc function sin(pi x)/(pi x) over the interval
[-4,4] constructed by Nicolas Robidoux and Chantal Racette with funding
from the Natural Sciences and Engineering Research Council of Canada.
Although the approximations are polynomials (for low order of
approximation) and quotients of polynomials (for higher order of
approximation) and consequently are similar in form to Taylor polynomials /
Pade approximants, the approximations are computed with a completely
different technique.
Summary: These approximations are "the best" in terms of bang (accuracy)
for the buck (flops). More specifically: Among the polynomial quotients
that can be computed using a fixed number of flops (with a given "+ - * /
budget"), the chosen polynomial quotient is the one closest to the
approximated function with respect to maximum absolute relative error over
the given interval.
The Remez algorithm, as implemented in the boost library's minimax package,
is the key to the construction: http://www.boost.org/doc/libs/1_36_0/libs/
math/doc/sf_and_dist/html/math_toolkit/backgrounders/remez.html
If outside of the interval of approximation, use the standard trig formula.
*/
magick_unreferenced(resize_filter);
if (x > 4.0)
{
const MagickRealType alpha=(MagickRealType) (MagickPI*x);
return(sin((double) alpha)/alpha);
}
{
/*
The approximations only depend on x^2 (sinc is an even function).
*/
const MagickRealType xx = x*x;
#if MAGICKCORE_QUANTUM_DEPTH <= 8
/*
Maximum absolute relative error 6.3e-6 < 1/2^17.
*/
const double c0 = 0.173610016489197553621906385078711564924e-2L;
const double c1 = -0.384186115075660162081071290162149315834e-3L;
const double c2 = 0.393684603287860108352720146121813443561e-4L;
const double c3 = -0.248947210682259168029030370205389323899e-5L;
const double c4 = 0.107791837839662283066379987646635416692e-6L;
const double c5 = -0.324874073895735800961260474028013982211e-8L;
const double c6 = 0.628155216606695311524920882748052490116e-10L;
const double c7 = -0.586110644039348333520104379959307242711e-12L;
const double p =
c0+xx*(c1+xx*(c2+xx*(c3+xx*(c4+xx*(c5+xx*(c6+xx*c7))))));
return((xx-1.0)*(xx-4.0)*(xx-9.0)*(xx-16.0)*p);
#elif MAGICKCORE_QUANTUM_DEPTH <= 16
/*
Max. abs. rel. error 2.2e-8 < 1/2^25.
*/
const double c0 = 0.173611107357320220183368594093166520811e-2L;
const double c1 = -0.384240921114946632192116762889211361285e-3L;
const double c2 = 0.394201182359318128221229891724947048771e-4L;
const double c3 = -0.250963301609117217660068889165550534856e-5L;
const double c4 = 0.111902032818095784414237782071368805120e-6L;
const double c5 = -0.372895101408779549368465614321137048875e-8L;
const double c6 = 0.957694196677572570319816780188718518330e-10L;
const double c7 = -0.187208577776590710853865174371617338991e-11L;
const double c8 = 0.253524321426864752676094495396308636823e-13L;
const double c9 = -0.177084805010701112639035485248501049364e-15L;
const double p =
c0+xx*(c1+xx*(c2+xx*(c3+xx*(c4+xx*(c5+xx*(c6+xx*(c7+xx*(c8+xx*c9))))))));
return((xx-1.0)*(xx-4.0)*(xx-9.0)*(xx-16.0)*p);
#else
/*
Max. abs. rel. error 1.2e-12 < 1/2^39.
*/
const double c0 = 0.173611111110910715186413700076827593074e-2L;
const double c1 = -0.289105544717893415815859968653611245425e-3L;
const double c2 = 0.206952161241815727624413291940849294025e-4L;
const double c3 = -0.834446180169727178193268528095341741698e-6L;
const double c4 = 0.207010104171026718629622453275917944941e-7L;
const double c5 = -0.319724784938507108101517564300855542655e-9L;
const double c6 = 0.288101675249103266147006509214934493930e-11L;
const double c7 = -0.118218971804934245819960233886876537953e-13L;
const double p =
c0+xx*(c1+xx*(c2+xx*(c3+xx*(c4+xx*(c5+xx*(c6+xx*c7))))));
const double d0 = 1.0L;
const double d1 = 0.547981619622284827495856984100563583948e-1L;
const double d2 = 0.134226268835357312626304688047086921806e-2L;
const double d3 = 0.178994697503371051002463656833597608689e-4L;
const double d4 = 0.114633394140438168641246022557689759090e-6L;
const double q = d0+xx*(d1+xx*(d2+xx*(d3+xx*d4)));
return((MagickRealType) ((xx-1.0)*(xx-4.0)*(xx-9.0)*(xx-16.0)/q*p));
#endif
}
}
static MagickRealType Triangle(const MagickRealType x,
const ResizeFilter *magick_unused(resize_filter))
{
/*
1st order (linear) B-Spline, bilinear interpolation, Tent 1D filter, or
a Bartlett 2D Cone filter. Also used as a Bartlett Windowing function
for Sinc().
*/
magick_unreferenced(resize_filter);
if (x < 1.0)
return(1.0-x);
return(0.0);
}
static MagickRealType Welsh(const MagickRealType x,
const ResizeFilter *magick_unused(resize_filter))
{
/*
Welsh parabolic windowing filter.
*/
magick_unreferenced(resize_filter);
if (x < 1.0)
return(1.0-x*x);
return(0.0);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
+ A c q u i r e R e s i z e F i l t e r %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% AcquireResizeFilter() allocates the ResizeFilter structure. Choose from
% these filters:
%
% FIR (Finite impulse Response) Filters
% Box Triangle Quadratic
% Spline Hermite Catrom
% Mitchell
%
% IIR (Infinite impulse Response) Filters
% Gaussian Sinc Jinc (Bessel)
%
% Windowed Sinc/Jinc Filters
% Blackman Bohman Lanczos
% Hann Hamming Cosine
% Kaiser Welch Parzen
% Bartlett
%
% Special Purpose Filters
% Cubic SincFast LanczosSharp Lanczos2 Lanczos2Sharp
% Robidoux RobidouxSharp
%
% The users "-filter" selection is used to lookup the default 'expert'
% settings for that filter from a internal table. However any provided
% 'expert' settings (see below) may override this selection.
%
% FIR filters are used as is, and are limited to that filters support window
% (unless over-ridden). 'Gaussian' while classed as an IIR filter, is also
% simply clipped by its support size (currently 1.5 or approximately 3*sigma
% as recommended by many references)
%
% The special a 'cylindrical' filter flag will promote the default 4-lobed
% Windowed Sinc filter to a 3-lobed Windowed Jinc equivalent, which is better
% suited to this style of image resampling. This typically happens when using
% such a filter for images distortions.
%
% SPECIFIC FILTERS:
%
% Directly requesting 'Sinc', 'Jinc' function as a filter will force the use
% of function without any windowing, or promotion for cylindrical usage. This
% is not recommended, except by image processing experts, especially as part
% of expert option filter function selection.
%
% Two forms of the 'Sinc' function are available: Sinc and SincFast. Sinc is
% computed using the traditional sin(pi*x)/(pi*x); it is selected if the user
% specifically specifies the use of a Sinc filter. SincFast uses highly
% accurate (and fast) polynomial (low Q) and rational (high Q) approximations,
% and will be used by default in most cases.
%
% The Lanczos filter is a special 3-lobed Sinc-windowed Sinc filter (promoted
% to Jinc-windowed Jinc for cylindrical (Elliptical Weighted Average) use).
% The Sinc version is the most popular windowed filter.
%
% LanczosSharp is a slightly sharpened (blur=0.9812505644269356 < 1) form of
% the Lanczos filter, specifically designed for EWA distortion (as a
% Jinc-Jinc); it can also be used as a slightly sharper orthogonal Lanczos
% (Sinc-Sinc) filter. The chosen blur value comes as close as possible to
% satisfying the following condition without changing the character of the
% corresponding EWA filter:
%
% 'No-Op' Vertical and Horizontal Line Preservation Condition: Images with
% only vertical or horizontal features are preserved when performing 'no-op"
% with EWA distortion.
%
% The Lanczos2 and Lanczos2Sharp filters are 2-lobe versions of the Lanczos
% filters. The 'sharp' version uses a blur factor of 0.9549963639785485,
% again chosen because the resulting EWA filter comes as close as possible to
% satisfying the above condition.
%
% Robidoux is another filter tuned for EWA. It is the Keys cubic filter
% defined by B=(228 - 108 sqrt(2))/199. Robidoux satisfies the "'No-Op'
% Vertical and Horizontal Line Preservation Condition" exactly, and it
% moderately blurs high frequency 'pixel-hash' patterns under no-op. It turns
% out to be close to both Mitchell and Lanczos2Sharp. For example, its first
% crossing is at (36 sqrt(2) + 123)/(72 sqrt(2) + 47), almost the same as the
% first crossing of Mitchell and Lanczos2Sharp.
%
% RodidouxSharp is a slightly sharper version of Rodidoux, some believe it
% is too sharp. It is designed to minimize the maximum possible change in
% a pixel value which is at one of the extremes (e.g., 0 or 255) under no-op
% conditions. Amazingly Mitchell falls roughly between Rodidoux and
% RodidouxSharp, though this seems to have been pure coincidence.
%
% 'EXPERT' OPTIONS:
%
% These artifact "defines" are not recommended for production use without
% expert knowledge of resampling, filtering, and the effects they have on the
% resulting resampled (resized or distorted) image.
%
% They can be used to override any and all filter default, and it is
% recommended you make good use of "filter:verbose" to make sure that the
% overall effect of your selection (before and after) is as expected.
%
% "filter:verbose" controls whether to output the exact results of the
% filter selections made, as well as plotting data for graphing the
% resulting filter over the filters support range.
%
% "filter:filter" select the main function associated with this filter
% name, as the weighting function of the filter. This can be used to
% set a windowing function as a weighting function, for special
% purposes, such as graphing.
%
% If a "filter:window" operation has not been provided, a 'Box'
% windowing function will be set to denote that no windowing function is
% being used.
%
% "filter:window" Select this windowing function for the filter. While any
% filter could be used as a windowing function, using the 'first lobe' of
% that filter over the whole support window, using a non-windowing
% function is not advisible. If no weighting filter function is specified
% a 'SincFast' filter is used.
%
% "filter:lobes" Number of lobes to use for the Sinc/Jinc filter. This a
% simpler method of setting filter support size that will correctly
% handle the Sinc/Jinc switch for an operators filtering requirements.
% Only integers should be given.
%
% "filter:support" Set the support size for filtering to the size given.
% This not recommended for Sinc/Jinc windowed filters (lobes should be
% used instead). This will override any 'filter:lobes' option.
%
% "filter:win-support" Scale windowing function to this size instead. This
% causes the windowing (or self-windowing Lagrange filter) to act is if
% the support window it much much larger than what is actually supplied
% to the calling operator. The filter however is still clipped to the
% real support size given, by the support range supplied to the caller.
% If unset this will equal the normal filter support size.
%
% "filter:blur" Scale the filter and support window by this amount. A value
% of > 1 will generally result in a more blurred image with more ringing
% effects, while a value <1 will sharpen the resulting image with more
% aliasing effects.
%
% "filter:sigma" The sigma value to use for the Gaussian filter only.
% Defaults to '1/2'. Using a different sigma effectively provides a
% method of using the filter as a 'blur' convolution. Particularly when
% using it for Distort.
%
% "filter:b"
% "filter:c" Override the preset B,C values for a Cubic filter.
% If only one of these are given it is assumes to be a 'Keys' type of
% filter such that B+2C=1, where Keys 'alpha' value = C.
%
% Examples:
%
% Set a true un-windowed Sinc filter with 10 lobes (very slow):
% -define filter:filter=Sinc
% -define filter:lobes=8
%
% Set an 8 lobe Lanczos (Sinc or Jinc) filter:
% -filter Lanczos
% -define filter:lobes=8
%
% The format of the AcquireResizeFilter method is:
%
% ResizeFilter *AcquireResizeFilter(const Image *image,
% const FilterTypes filter_type,const MagickBooleanType cylindrical,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o filter: the filter type, defining a preset filter, window and support.
% The artifact settings listed above will override those selections.
%
% o blur: blur the filter by this amount, use 1.0 if unknown. Image
% artifact "filter:blur" will override this API call usage, including any
% internal change (such as for cylindrical usage).
%
% o radial: use a 1D orthogonal filter (Sinc) or 2D cylindrical (radial)
% filter (Jinc).
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport ResizeFilter *AcquireResizeFilter(const Image *image,
const FilterTypes filter,const MagickRealType blur,
const MagickBooleanType cylindrical,ExceptionInfo *exception)
{
const char
*artifact;
FilterTypes
filter_type,
window_type;
MagickRealType
B,
C,
value;
register ResizeFilter
*resize_filter;
/*
Table Mapping given Filter, into Weighting and Windowing functions.
A 'Box' windowing function means its a simble non-windowed filter.
An 'SincFast' filter function could be upgraded to a 'Jinc' filter if a
"cylindrical" is requested, unless a 'Sinc' or 'SincFast' filter was
specifically requested by the user.
WARNING: The order of this table must match the order of the FilterTypes
enumeration specified in "resample.h", or the filter names will not match
the filter being setup.
You can check filter setups with the "filter:verbose" expert setting.
*/
static struct
{
FilterTypes
filter,
window;
} const mapping[SentinelFilter] =
{
{ UndefinedFilter, BoxFilter }, /* Undefined (default to Box) */
{ PointFilter, BoxFilter }, /* SPECIAL: Nearest neighbour */
{ BoxFilter, BoxFilter }, /* Box averaging filter */
{ TriangleFilter, BoxFilter }, /* Linear interpolation filter */
{ HermiteFilter, BoxFilter }, /* Hermite interpolation filter */
{ SincFastFilter, HanningFilter }, /* Hanning -- cosine-sinc */
{ SincFastFilter, HammingFilter }, /* Hamming -- '' variation */
{ SincFastFilter, BlackmanFilter }, /* Blackman -- 2*cosine-sinc */
{ GaussianFilter, BoxFilter }, /* Gaussian blur filter */
{ QuadraticFilter, BoxFilter }, /* Quadratic Gaussian approx */
{ CubicFilter, BoxFilter }, /* General Cubic Filter, Spline */
{ CatromFilter, BoxFilter }, /* Cubic-Keys interpolator */
{ MitchellFilter, BoxFilter }, /* 'Ideal' Cubic-Keys filter */
{ JincFilter, BoxFilter }, /* Raw 3-lobed Jinc function */
{ SincFilter, BoxFilter }, /* Raw 4-lobed Sinc function */
{ SincFastFilter, BoxFilter }, /* Raw fast sinc ("Pade"-type) */
{ SincFastFilter, KaiserFilter }, /* Kaiser -- square root-sinc */
{ LanczosFilter, WelshFilter }, /* Welch -- parabolic (3 lobe) */
{ SincFastFilter, CubicFilter }, /* Parzen -- cubic-sinc */
{ SincFastFilter, BohmanFilter }, /* Bohman -- 2*cosine-sinc */
{ SincFastFilter, TriangleFilter }, /* Bartlett -- triangle-sinc */
{ LagrangeFilter, BoxFilter }, /* Lagrange self-windowing */
{ LanczosFilter, LanczosFilter }, /* Lanczos Sinc-Sinc filters */
{ LanczosSharpFilter, LanczosSharpFilter }, /* | these require */
{ Lanczos2Filter, Lanczos2Filter }, /* | special handling */
{ Lanczos2SharpFilter, Lanczos2SharpFilter },
{ RobidouxFilter, BoxFilter }, /* Cubic Keys tuned for EWA */
{ RobidouxSharpFilter, BoxFilter }, /* Sharper Cubic Keys for EWA */
{ LanczosFilter, CosineFilter }, /* Cosine window (3 lobes) */
{ SplineFilter, BoxFilter }, /* Spline Cubic Filter */
{ LanczosRadiusFilter, LanczosFilter }, /* Lanczos with integer radius */
};
/*
Table mapping the filter/window from the above table to an actual function.
The default support size for that filter as a weighting function, the range
to scale with to use that function as a sinc windowing function, (typ 1.0).
Note that the filter_type -> function is 1 to 1 except for Sinc(),
SincFast(), and CubicBC() functions, which may have multiple filter to
function associations.
See "filter:verbose" handling below for the function -> filter mapping.
*/
static struct
{
MagickRealType
(*function)(const MagickRealType,const ResizeFilter*);
double
support, /* Default lobes/support size of the weighting filter. */
scale, /* Support when function used as a windowing function
Typically equal to the location of the first zero crossing. */
B,C; /* BC-spline coefficients, ignored if not a CubicBC filter. */
ResizeWeightingFunctionType weightingFunctionType;
} const filters[SentinelFilter] =
{
/* .--- support window (if used as a Weighting Function)
| .--- first crossing (if used as a Windowing Function)
| | .--- B value for Cubic Function
| | | .---- C value for Cubic Function
| | | | */
{ Box, 0.5, 0.5, 0.0, 0.0, BoxWeightingFunction }, /* Undefined (default to Box) */
{ Box, 0.0, 0.5, 0.0, 0.0, BoxWeightingFunction }, /* Point (special handling) */
{ Box, 0.5, 0.5, 0.0, 0.0, BoxWeightingFunction }, /* Box */
{ Triangle, 1.0, 1.0, 0.0, 0.0, TriangleWeightingFunction }, /* Triangle */
{ CubicBC, 1.0, 1.0, 0.0, 0.0, CubicBCWeightingFunction }, /* Hermite (cubic B=C=0) */
{ Hanning, 1.0, 1.0, 0.0, 0.0, HanningWeightingFunction }, /* Hann, cosine window */
{ Hamming, 1.0, 1.0, 0.0, 0.0, HammingWeightingFunction }, /* Hamming, '' variation */
{ Blackman, 1.0, 1.0, 0.0, 0.0, BlackmanWeightingFunction }, /* Blackman, 2*cosine window */
{ Gaussian, 2.0, 1.5, 0.0, 0.0, GaussianWeightingFunction }, /* Gaussian */
{ Quadratic, 1.5, 1.5, 0.0, 0.0, QuadraticWeightingFunction },/* Quadratic gaussian */
{ CubicBC, 2.0, 2.0, 1.0, 0.0, CubicBCWeightingFunction }, /* General Cubic Filter */
{ CubicBC, 2.0, 1.0, 0.0, 0.5, CubicBCWeightingFunction }, /* Catmull-Rom (B=0,C=1/2) */
{ CubicBC, 2.0, 8.0/7.0, 1./3., 1./3., CubicBCWeightingFunction }, /* Mitchell (B=C=1/3) */
{ Jinc, 3.0, 1.2196698912665045, 0.0, 0.0, JincWeightingFunction }, /* Raw 3-lobed Jinc */
{ Sinc, 4.0, 1.0, 0.0, 0.0, SincWeightingFunction }, /* Raw 4-lobed Sinc */
{ SincFast, 4.0, 1.0, 0.0, 0.0, SincFastWeightingFunction }, /* Raw fast sinc ("Pade"-type) */
{ Kaiser, 1.0, 1.0, 0.0, 0.0, KaiserWeightingFunction }, /* Kaiser (square root window) */
{ Welsh, 1.0, 1.0, 0.0, 0.0, WelshWeightingFunction }, /* Welsh (parabolic window) */
{ CubicBC, 2.0, 2.0, 1.0, 0.0, CubicBCWeightingFunction }, /* Parzen (B-Spline window) */
{ Bohman, 1.0, 1.0, 0.0, 0.0, BohmanWeightingFunction }, /* Bohman, 2*Cosine window */
{ Triangle, 1.0, 1.0, 0.0, 0.0, TriangleWeightingFunction }, /* Bartlett (triangle window) */
{ Lagrange, 2.0, 1.0, 0.0, 0.0, LagrangeWeightingFunction }, /* Lagrange sinc approximation */
{ SincFast, 3.0, 1.0, 0.0, 0.0, SincFastWeightingFunction }, /* Lanczos, 3-lobed Sinc-Sinc */
{ SincFast, 3.0, 1.0, 0.0, 0.0, SincFastWeightingFunction }, /* Lanczos, Sharpened */
{ SincFast, 2.0, 1.0, 0.0, 0.0, SincFastWeightingFunction }, /* Lanczos, 2-lobed */
{ SincFast, 2.0, 1.0, 0.0, 0.0, SincFastWeightingFunction }, /* Lanczos2, sharpened */
/* Robidoux: Keys cubic close to Lanczos2D sharpened */
{ CubicBC, 2.0, 1.1685777620836932,
0.37821575509399867, 0.31089212245300067, CubicBCWeightingFunction },
/* RobidouxSharp: Sharper version of Robidoux */
{ CubicBC, 2.0, 1.105822933719019,
0.2620145123990142, 0.3689927438004929, CubicBCWeightingFunction },
{ Cosine, 1.0, 1.0, 0.0, 0.0, CosineWeightingFunction }, /* Low level cosine window */
{ CubicBC, 2.0, 2.0, 1.0, 0.0, CubicBCWeightingFunction }, /* Cubic B-Spline (B=1,C=0) */
{ SincFast, 3.0, 1.0, 0.0, 0.0, SincFastWeightingFunction }, /* Lanczos, Interger Radius */
};
/*
The known zero crossings of the Jinc() or more accurately the Jinc(x*PI)
function being used as a filter. It is used by the "filter:lobes" expert
setting and for 'lobes' for Jinc functions in the previous table. This way
users do not have to deal with the highly irrational lobe sizes of the Jinc
filter.
Values taken from
http://cose.math.bas.bg/webMathematica/webComputing/BesselZeros.jsp
using Jv-function with v=1, then dividing by PI.
*/
static double
jinc_zeros[16] =
{
1.2196698912665045,
2.2331305943815286,
3.2383154841662362,
4.2410628637960699,
5.2427643768701817,
6.2439216898644877,
7.2447598687199570,
8.2453949139520427,
9.2458926849494673,
10.246293348754916,
11.246622794877883,
12.246898461138105,
13.247132522181061,
14.247333735806849,
15.247508563037300,
16.247661874700962
};
/*
Allocate resize filter.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(UndefinedFilter < filter && filter < SentinelFilter);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
(void) exception;
resize_filter=(ResizeFilter *) AcquireMagickMemory(sizeof(*resize_filter));
if (resize_filter == (ResizeFilter *) NULL)
ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
(void) ResetMagickMemory(resize_filter,0,sizeof(*resize_filter));
/*
Defaults for the requested filter.
*/
filter_type=mapping[filter].filter;
window_type=mapping[filter].window;
resize_filter->blur = blur; /* function argument blur factor (1.0) */
/* Promote 1D Windowed Sinc Filters to a 2D Windowed Jinc filters */
if ((cylindrical != MagickFalse) && (filter_type == SincFastFilter) &&
(filter != SincFastFilter))
filter_type=JincFilter; /* 1D Windowed Sinc => 2D Windowed Jinc filters */
/* Expert filter setting override */
artifact=GetImageArtifact(image,"filter:filter");
if (artifact != (const char *) NULL)
{
ssize_t
option;
option=ParseCommandOption(MagickFilterOptions,MagickFalse,artifact);
if ((UndefinedFilter < option) && (option < SentinelFilter))
{ /* Raw filter request - no window function. */
filter_type=(FilterTypes) option;
window_type=BoxFilter;
}
/* Filter override with a specific window function. */
artifact=GetImageArtifact(image,"filter:window");
if (artifact != (const char *) NULL)
{
option=ParseCommandOption(MagickFilterOptions,MagickFalse,artifact);
if ((UndefinedFilter < option) && (option < SentinelFilter))
window_type=(FilterTypes) option;
}
}
else
{
/* Window specified, but no filter function? Assume Sinc/Jinc. */
artifact=GetImageArtifact(image,"filter:window");
if (artifact != (const char *) NULL)
{
ssize_t
option;
option=ParseCommandOption(MagickFilterOptions,MagickFalse,artifact);
if ((UndefinedFilter < option) && (option < SentinelFilter))
{
filter_type=cylindrical != MagickFalse ?
JincFilter : SincFastFilter;
window_type=(FilterTypes) option;
}
}
}
/* Assign the real functions to use for the filters selected. */
resize_filter->filter=filters[filter_type].function;
resize_filter->support=filters[filter_type].support;
resize_filter->filterWeightingType=filters[filter_type].weightingFunctionType;
resize_filter->window=filters[window_type].function;
resize_filter->windowWeightingType=filters[window_type].weightingFunctionType;
resize_filter->scale=filters[window_type].scale;
resize_filter->signature=MagickCoreSignature;
/* Filter Modifications for orthogonal/cylindrical usage */
if (cylindrical != MagickFalse)
switch (filter_type)
{
case BoxFilter:
/* Support for Cylindrical Box should be sqrt(2)/2 */
resize_filter->support=(MagickRealType) MagickSQ1_2;
break;
case LanczosFilter:
case LanczosSharpFilter:
case Lanczos2Filter:
case Lanczos2SharpFilter:
case LanczosRadiusFilter:
resize_filter->filter=filters[JincFilter].function;
resize_filter->window=filters[JincFilter].function;
resize_filter->scale=filters[JincFilter].scale;
/* number of lobes (support window size) remain unchanged */
break;
default:
break;
}
/* Global Sharpening (regardless of orthoginal/cylindrical) */
switch (filter_type)
{
case LanczosSharpFilter:
resize_filter->blur *= (MagickRealType) 0.9812505644269356;
break;
case Lanczos2SharpFilter:
resize_filter->blur *= (MagickRealType) 0.9549963639785485;
break;
/* case LanczosRadius: blur adjust is done after lobes */
default:
break;
}
/*
Expert Option Modifications.
*/
/* User Gaussian Sigma Override - no support change */
if ((resize_filter->filter == Gaussian) ||
(resize_filter->window == Gaussian) ) {
value=0.5; /* guassian sigma default, half pixel */
artifact=GetImageArtifact(image,"filter:sigma");
if (artifact != (const char *) NULL)
value=StringToDouble(artifact,(char **) NULL);
/* Define coefficents for Gaussian */
resize_filter->coefficient[0]=value; /* note sigma too */
resize_filter->coefficient[1]=PerceptibleReciprocal(2.0*value*value); /* sigma scaling */
resize_filter->coefficient[2]=PerceptibleReciprocal(Magick2PI*value*value);
/* normalization - not actually needed or used! */
if ( value > 0.5 )
resize_filter->support *= value/0.5; /* increase support */
}
/* User Kaiser Alpha Override - no support change */
if ((resize_filter->filter == Kaiser) ||
(resize_filter->window == Kaiser) ) {
value=6.5; /* default beta value for Kaiser bessel windowing function */
artifact=GetImageArtifact(image,"filter:alpha"); /* FUTURE: depreciate */
if (artifact != (const char *) NULL)
value=StringToDouble(artifact,(char **) NULL);
artifact=GetImageArtifact(image,"filter:kaiser-beta");
if (artifact != (const char *) NULL)
value=StringToDouble(artifact,(char **) NULL);
artifact=GetImageArtifact(image,"filter:kaiser-alpha");
if (artifact != (const char *) NULL)
value=(MagickRealType) (StringToDouble(artifact,(char **) NULL)*MagickPI);
/* Define coefficents for Kaiser Windowing Function */
resize_filter->coefficient[0]=value; /* alpha */
resize_filter->coefficient[1]=PerceptibleReciprocal(I0(value)); /* normalization */
}
/* Support Overrides */
artifact=GetImageArtifact(image,"filter:lobes");
if (artifact != (const char *) NULL)
{
ssize_t
lobes;
lobes=(ssize_t) StringToLong(artifact);
if (lobes < 1)
lobes=1;
resize_filter->support=(MagickRealType) lobes;
}
/* Convert a Jinc function lobes value to a real support value */
if (resize_filter->filter == Jinc)
{
if (resize_filter->support > 16)
resize_filter->support=jinc_zeros[15]; /* largest entry in table */
else
resize_filter->support=jinc_zeros[((long)resize_filter->support)-1];
/* blur this filter so support is a integer value (lobes dependant) */
if (filter_type == LanczosRadiusFilter)
{
resize_filter->blur *= floor(resize_filter->support)/
resize_filter->support;
}
}
/* Expert Blur Override */
artifact=GetImageArtifact(image,"filter:blur");
if (artifact != (const char *) NULL)
resize_filter->blur*=StringToDouble(artifact,(char **) NULL);
if (resize_filter->blur < MagickEpsilon)
resize_filter->blur=(MagickRealType) MagickEpsilon;
/* Expert override of the support setting */
artifact=GetImageArtifact(image,"filter:support");
if (artifact != (const char *) NULL)
resize_filter->support=fabs(StringToDouble(artifact,(char **) NULL));
/*
Scale windowing function separately to the support 'clipping'
window that calling operator is planning to actually use. (Expert
override)
*/
resize_filter->window_support=resize_filter->support; /* default */
artifact=GetImageArtifact(image,"filter:win-support");
if (artifact != (const char *) NULL)
resize_filter->window_support=fabs(StringToDouble(artifact,(char **) NULL));
/*
Adjust window function scaling to match windowing support for
weighting function. This avoids a division on every filter call.
*/
resize_filter->scale/=resize_filter->window_support;
/*
* Set Cubic Spline B,C values, calculate Cubic coefficients.
*/
B=0.0;
C=0.0;
if ((resize_filter->filter == CubicBC) ||
(resize_filter->window == CubicBC) )
{
B=filters[filter_type].B;
C=filters[filter_type].C;
if (filters[window_type].function == CubicBC)
{
B=filters[window_type].B;
C=filters[window_type].C;
}
artifact=GetImageArtifact(image,"filter:b");
if (artifact != (const char *) NULL)
{
B=StringToDouble(artifact,(char **) NULL);
C=(1.0-B)/2.0; /* Calculate C to get a Keys cubic filter. */
artifact=GetImageArtifact(image,"filter:c"); /* user C override */
if (artifact != (const char *) NULL)
C=StringToDouble(artifact,(char **) NULL);
}
else
{
artifact=GetImageArtifact(image,"filter:c");
if (artifact != (const char *) NULL)
{
C=StringToDouble(artifact,(char **) NULL);
B=1.0-2.0*C; /* Calculate B to get a Keys cubic filter. */
}
}
/* Convert B,C values into Cubic Coefficents. See CubicBC(). */
{
const double twoB = B+B;
resize_filter->coefficient[0]=1.0-(1.0/3.0)*B;
resize_filter->coefficient[1]=-3.0+twoB+C;
resize_filter->coefficient[2]=2.0-1.5*B-C;
resize_filter->coefficient[3]=(4.0/3.0)*B+4.0*C;
resize_filter->coefficient[4]=-8.0*C-twoB;
resize_filter->coefficient[5]=B+5.0*C;
resize_filter->coefficient[6]=(-1.0/6.0)*B-C;
}
}
/*
Expert Option Request for verbose details of the resulting filter.
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp master
{
#endif
artifact=GetImageArtifact(image,"filter:verbose");
if (IsMagickTrue(artifact) != MagickFalse)
{
double
support,
x;
/*
Set the weighting function properly when the weighting
function may not exactly match the filter of the same name.
EG: a Point filter is really uses a Box weighting function
with a different support than is typically used.
*/
if (resize_filter->filter == Box) filter_type=BoxFilter;
if (resize_filter->filter == Sinc) filter_type=SincFilter;
if (resize_filter->filter == SincFast) filter_type=SincFastFilter;
if (resize_filter->filter == Jinc) filter_type=JincFilter;
if (resize_filter->filter == CubicBC) filter_type=CubicFilter;
if (resize_filter->window == Box) window_type=BoxFilter;
if (resize_filter->window == Sinc) window_type=SincFilter;
if (resize_filter->window == SincFast) window_type=SincFastFilter;
if (resize_filter->window == Jinc) window_type=JincFilter;
if (resize_filter->window == CubicBC) window_type=CubicFilter;
/*
Report Filter Details.
*/
support=GetResizeFilterSupport(resize_filter); /* practical_support */
(void) FormatLocaleFile(stdout,"# Resampling Filter (for graphing)\n#\n");
(void) FormatLocaleFile(stdout,"# filter = %s\n",
CommandOptionToMnemonic(MagickFilterOptions,filter_type));
(void) FormatLocaleFile(stdout,"# window = %s\n",
CommandOptionToMnemonic(MagickFilterOptions,window_type));
(void) FormatLocaleFile(stdout,"# support = %.*g\n",
GetMagickPrecision(),(double) resize_filter->support);
(void) FormatLocaleFile(stdout,"# window-support = %.*g\n",
GetMagickPrecision(),(double) resize_filter->window_support);
(void) FormatLocaleFile(stdout,"# scale-blur = %.*g\n",
GetMagickPrecision(), (double)resize_filter->blur);
if ( filter_type == GaussianFilter || window_type == GaussianFilter )
(void) FormatLocaleFile(stdout,"# gaussian-sigma = %.*g\n",
GetMagickPrecision(), (double)resize_filter->coefficient[0]);
if ( filter_type == KaiserFilter || window_type == KaiserFilter )
(void) FormatLocaleFile(stdout,"# kaiser-beta = %.*g\n",
GetMagickPrecision(),
(double)resize_filter->coefficient[0]);
(void) FormatLocaleFile(stdout,"# practical-support = %.*g\n",
GetMagickPrecision(), (double)support);
if ( filter_type == CubicFilter || window_type == CubicFilter )
(void) FormatLocaleFile(stdout,"# B,C = %.*g,%.*g\n",
GetMagickPrecision(),(double)B, GetMagickPrecision(),(double)C);
(void) FormatLocaleFile(stdout,"\n");
/*
Output values of resulting filter graph -- for graphing
filter result.
*/
for (x=0.0; x <= support; x+=0.01f)
(void) FormatLocaleFile(stdout,"%5.2lf\t%.*g\n",x,GetMagickPrecision(),
(double) GetResizeFilterWeight(resize_filter,x));
/* A final value so gnuplot can graph the 'stop' properly. */
(void) FormatLocaleFile(stdout,"%5.2lf\t%.*g\n",support,
GetMagickPrecision(),0.0);
}
/* Output the above once only for each image - remove setting */
(void) DeleteImageArtifact((Image *) image,"filter:verbose");
#if defined(MAGICKCORE_OPENMP_SUPPORT)
}
#endif
return(resize_filter);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% A d a p t i v e R e s i z e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% AdaptiveResizeImage() adaptively resize image with pixel resampling.
%
% This is shortcut function for a fast interpolative resize using mesh
% interpolation. It works well for small resizes of less than +/- 50%
% of the original image size. For larger resizing on images a full
% filtered and slower resize function should be used instead.
%
% The format of the AdaptiveResizeImage method is:
%
% Image *AdaptiveResizeImage(const Image *image,const size_t columns,
% const size_t rows,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o columns: the number of columns in the resized image.
%
% o rows: the number of rows in the resized image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *AdaptiveResizeImage(const Image *image,
const size_t columns,const size_t rows,ExceptionInfo *exception)
{
return(InterpolativeResizeImage(image,columns,rows,MeshInterpolatePixel,
exception));
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
+ B e s s e l O r d e r O n e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% BesselOrderOne() computes the Bessel function of x of the first kind of
% order 0. This is used to create the Jinc() filter function below.
%
% Reduce x to |x| since j1(x)= -j1(-x), and for x in (0,8]
%
% j1(x) = x*j1(x);
%
% For x in (8,inf)
%
% j1(x) = sqrt(2/(pi*x))*(p1(x)*cos(x1)-q1(x)*sin(x1))
%
% where x1 = x-3*pi/4. Compute sin(x1) and cos(x1) as follow:
%
% cos(x1) = cos(x)cos(3pi/4)+sin(x)sin(3pi/4)
% = 1/sqrt(2) * (sin(x) - cos(x))
% sin(x1) = sin(x)cos(3pi/4)-cos(x)sin(3pi/4)
% = -1/sqrt(2) * (sin(x) + cos(x))
%
% The format of the BesselOrderOne method is:
%
% MagickRealType BesselOrderOne(MagickRealType x)
%
% A description of each parameter follows:
%
% o x: MagickRealType value.
%
*/
#undef I0
static MagickRealType I0(MagickRealType x)
{
MagickRealType
sum,
t,
y;
register ssize_t
i;
/*
Zeroth order Bessel function of the first kind.
*/
sum=1.0;
y=x*x/4.0;
t=y;
for (i=2; t > MagickEpsilon; i++)
{
sum+=t;
t*=y/((MagickRealType) i*i);
}
return(sum);
}
#undef J1
static MagickRealType J1(MagickRealType x)
{
MagickRealType
p,
q;
register ssize_t
i;
static const double
Pone[] =
{
0.581199354001606143928050809e+21,
-0.6672106568924916298020941484e+20,
0.2316433580634002297931815435e+19,
-0.3588817569910106050743641413e+17,
0.2908795263834775409737601689e+15,
-0.1322983480332126453125473247e+13,
0.3413234182301700539091292655e+10,
-0.4695753530642995859767162166e+7,
0.270112271089232341485679099e+4
},
Qone[] =
{
0.11623987080032122878585294e+22,
0.1185770712190320999837113348e+20,
0.6092061398917521746105196863e+17,
0.2081661221307607351240184229e+15,
0.5243710262167649715406728642e+12,
0.1013863514358673989967045588e+10,
0.1501793594998585505921097578e+7,
0.1606931573481487801970916749e+4,
0.1e+1
};
p=Pone[8];
q=Qone[8];
for (i=7; i >= 0; i--)
{
p=p*x*x+Pone[i];
q=q*x*x+Qone[i];
}
return(p/q);
}
#undef P1
static MagickRealType P1(MagickRealType x)
{
MagickRealType
p,
q;
register ssize_t
i;
static const double
Pone[] =
{
0.352246649133679798341724373e+5,
0.62758845247161281269005675e+5,
0.313539631109159574238669888e+5,
0.49854832060594338434500455e+4,
0.2111529182853962382105718e+3,
0.12571716929145341558495e+1
},
Qone[] =
{
0.352246649133679798068390431e+5,
0.626943469593560511888833731e+5,
0.312404063819041039923015703e+5,
0.4930396490181088979386097e+4,
0.2030775189134759322293574e+3,
0.1e+1
};
p=Pone[5];
q=Qone[5];
for (i=4; i >= 0; i--)
{
p=p*(8.0/x)*(8.0/x)+Pone[i];
q=q*(8.0/x)*(8.0/x)+Qone[i];
}
return(p/q);
}
#undef Q1
static MagickRealType Q1(MagickRealType x)
{
MagickRealType
p,
q;
register ssize_t
i;
static const double
Pone[] =
{
0.3511751914303552822533318e+3,
0.7210391804904475039280863e+3,
0.4259873011654442389886993e+3,
0.831898957673850827325226e+2,
0.45681716295512267064405e+1,
0.3532840052740123642735e-1
},
Qone[] =
{
0.74917374171809127714519505e+4,
0.154141773392650970499848051e+5,
0.91522317015169922705904727e+4,
0.18111867005523513506724158e+4,
0.1038187585462133728776636e+3,
0.1e+1
};
p=Pone[5];
q=Qone[5];
for (i=4; i >= 0; i--)
{
p=p*(8.0/x)*(8.0/x)+Pone[i];
q=q*(8.0/x)*(8.0/x)+Qone[i];
}
return(p/q);
}
static MagickRealType BesselOrderOne(MagickRealType x)
{
MagickRealType
p,
q;
if (x == 0.0)
return(0.0);
p=x;
if (x < 0.0)
x=(-x);
if (x < 8.0)
return(p*J1(x));
q=sqrt((double) (2.0/(MagickPI*x)))*(P1(x)*(1.0/sqrt(2.0)*(sin((double) x)-
cos((double) x)))-8.0/x*Q1(x)*(-1.0/sqrt(2.0)*(sin((double) x)+
cos((double) x))));
if (p < 0.0)
q=(-q);
return(q);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
+ D e s t r o y R e s i z e F i l t e r %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% DestroyResizeFilter() destroy the resize filter.
%
% The format of the DestroyResizeFilter method is:
%
% ResizeFilter *DestroyResizeFilter(ResizeFilter *resize_filter)
%
% A description of each parameter follows:
%
% o resize_filter: the resize filter.
%
*/
MagickExport ResizeFilter *DestroyResizeFilter(ResizeFilter *resize_filter)
{
assert(resize_filter != (ResizeFilter *) NULL);
assert(resize_filter->signature == MagickCoreSignature);
resize_filter->signature=(~MagickCoreSignature);
resize_filter=(ResizeFilter *) RelinquishMagickMemory(resize_filter);
return(resize_filter);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
+ G e t R e s i z e F i l t e r S u p p o r t %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetResizeFilterSupport() return the current support window size for this
% filter. Note that this may have been enlarged by filter:blur factor.
%
% The format of the GetResizeFilterSupport method is:
%
% MagickRealType GetResizeFilterSupport(const ResizeFilter *resize_filter)
%
% A description of each parameter follows:
%
% o filter: Image filter to use.
%
*/
MagickExport MagickRealType *GetResizeFilterCoefficient(
const ResizeFilter *resize_filter)
{
assert(resize_filter != (ResizeFilter *) NULL);
assert(resize_filter->signature == MagickCoreSignature);
return((MagickRealType *) resize_filter->coefficient);
}
MagickExport MagickRealType GetResizeFilterBlur(
const ResizeFilter *resize_filter)
{
assert(resize_filter != (ResizeFilter *) NULL);
assert(resize_filter->signature == MagickCoreSignature);
return(resize_filter->blur);
}
MagickExport MagickRealType GetResizeFilterScale(
const ResizeFilter *resize_filter)
{
assert(resize_filter != (ResizeFilter *) NULL);
assert(resize_filter->signature == MagickCoreSignature);
return(resize_filter->scale);
}
MagickExport MagickRealType GetResizeFilterWindowSupport(
const ResizeFilter *resize_filter)
{
assert(resize_filter != (ResizeFilter *) NULL);
assert(resize_filter->signature == MagickCoreSignature);
return(resize_filter->window_support);
}
MagickExport ResizeWeightingFunctionType GetResizeFilterWeightingType(
const ResizeFilter *resize_filter)
{
assert(resize_filter != (ResizeFilter *) NULL);
assert(resize_filter->signature == MagickCoreSignature);
return(resize_filter->filterWeightingType);
}
MagickExport ResizeWeightingFunctionType GetResizeFilterWindowWeightingType(
const ResizeFilter *resize_filter)
{
assert(resize_filter != (ResizeFilter *) NULL);
assert(resize_filter->signature == MagickCoreSignature);
return(resize_filter->windowWeightingType);
}
MagickExport MagickRealType GetResizeFilterSupport(
const ResizeFilter *resize_filter)
{
assert(resize_filter != (ResizeFilter *) NULL);
assert(resize_filter->signature == MagickCoreSignature);
return(resize_filter->support*resize_filter->blur);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
+ G e t R e s i z e F i l t e r W e i g h t %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetResizeFilterWeight evaluates the specified resize filter at the point x
% which usally lies between zero and the filters current 'support' and
% returns the weight of the filter function at that point.
%
% The format of the GetResizeFilterWeight method is:
%
% MagickRealType GetResizeFilterWeight(const ResizeFilter *resize_filter,
% const MagickRealType x)
%
% A description of each parameter follows:
%
% o filter: the filter type.
%
% o x: the point.
%
*/
MagickExport MagickRealType GetResizeFilterWeight(
const ResizeFilter *resize_filter,const MagickRealType x)
{
MagickRealType
scale,
weight,
x_blur;
/*
Windowing function - scale the weighting filter by this amount.
*/
assert(resize_filter != (ResizeFilter *) NULL);
assert(resize_filter->signature == MagickCoreSignature);
x_blur=fabs((double) x)/resize_filter->blur; /* X offset with blur scaling */
if ((resize_filter->window_support < MagickEpsilon) ||
(resize_filter->window == Box))
scale=1.0; /* Point or Box Filter -- avoid division by zero */
else
{
scale=resize_filter->scale;
scale=resize_filter->window(x_blur*scale,resize_filter);
}
weight=scale*resize_filter->filter(x_blur,resize_filter);
return(weight);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% I n t e r p o l a t i v e R e s i z e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% InterpolativeResizeImage() resizes an image using the specified
% interpolation method.
%
% The format of the InterpolativeResizeImage method is:
%
% Image *InterpolativeResizeImage(const Image *image,const size_t columns,
% const size_t rows,const InterpolatePixelMethod method,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o columns: the number of columns in the resized image.
%
% o rows: the number of rows in the resized image.
%
% o method: the pixel interpolation method.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *InterpolativeResizeImage(const Image *image,
const size_t columns,const size_t rows,const InterpolatePixelMethod method,
ExceptionInfo *exception)
{
#define InterpolativeResizeImageTag "Resize/Image"
CacheView
*image_view,
*resize_view;
Image
*resize_image;
MagickBooleanType
status;
MagickOffsetType
progress;
PointInfo
scale;
ssize_t
y;
/*
Interpolatively resize image.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
if ((columns == 0) || (rows == 0))
return((Image *) NULL);
if ((columns == image->columns) && (rows == image->rows))
return(CloneImage(image,0,0,MagickTrue,exception));
resize_image=CloneImage(image,columns,rows,MagickTrue,exception);
if (resize_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(resize_image,DirectClass) == MagickFalse)
{
InheritException(exception,&resize_image->exception);
resize_image=DestroyImage(resize_image);
return((Image *) NULL);
}
status=MagickTrue;
progress=0;
image_view=AcquireVirtualCacheView(image,exception);
resize_view=AcquireAuthenticCacheView(resize_image,exception);
scale.x=(double) image->columns/resize_image->columns;
scale.y=(double) image->rows/resize_image->rows;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(progress,status) \
magick_number_threads(image,resize_image,resize_image->rows,1)
#endif
for (y=0; y < (ssize_t) resize_image->rows; y++)
{
MagickPixelPacket
pixel;
PointInfo
offset;
register IndexPacket
*magick_restrict resize_indexes;
register PixelPacket
*magick_restrict q;
register ssize_t
x;
if (status == MagickFalse)
continue;
q=QueueCacheViewAuthenticPixels(resize_view,0,y,resize_image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
continue;
resize_indexes=GetCacheViewAuthenticIndexQueue(resize_view);
GetMagickPixelPacket(image,&pixel);
offset.y=((MagickRealType) y+0.5)*scale.y-0.5;
for (x=0; x < (ssize_t) resize_image->columns; x++)
{
offset.x=((MagickRealType) x+0.5)*scale.x-0.5;
status=InterpolateMagickPixelPacket(image,image_view,method,offset.x,
offset.y,&pixel,exception);
if (status == MagickFalse)
break;
SetPixelPacket(resize_image,&pixel,q,resize_indexes+x);
q++;
}
if (SyncCacheViewAuthenticPixels(resize_view,exception) == MagickFalse)
continue;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_InterpolativeResizeImage)
#endif
proceed=SetImageProgress(image,InterpolativeResizeImageTag,progress++,
image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
resize_view=DestroyCacheView(resize_view);
image_view=DestroyCacheView(image_view);
if (status == MagickFalse)
resize_image=DestroyImage(resize_image);
return(resize_image);
}
#if defined(MAGICKCORE_LQR_DELEGATE)
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% L i q u i d R e s c a l e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% LiquidRescaleImage() rescales image with seam carving.
%
% The format of the LiquidRescaleImage method is:
%
% Image *LiquidRescaleImage(const Image *image,
% const size_t columns,const size_t rows,
% const double delta_x,const double rigidity,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o columns: the number of columns in the rescaled image.
%
% o rows: the number of rows in the rescaled image.
%
% o delta_x: maximum seam transversal step (0 means straight seams).
%
% o rigidity: introduce a bias for non-straight seams (typically 0).
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *LiquidRescaleImage(const Image *image,const size_t columns,
const size_t rows,const double delta_x,const double rigidity,
ExceptionInfo *exception)
{
#define LiquidRescaleImageTag "Rescale/Image"
CacheView
*rescale_view;
const char
*map;
guchar
*packet;
Image
*rescale_image;
int
x,
y;
LqrCarver
*carver;
LqrRetVal
lqr_status;
MagickBooleanType
status;
MagickPixelPacket
pixel;
MemoryInfo
*pixel_info;
unsigned char
*pixels;
/*
Liquid rescale image.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
if ((columns == 0) || (rows == 0))
return((Image *) NULL);
if ((columns == image->columns) && (rows == image->rows))
return(CloneImage(image,0,0,MagickTrue,exception));
if ((columns <= 2) || (rows <= 2))
return(ResizeImage(image,columns,rows,image->filter,image->blur,exception));
map="RGB";
if (image->matte != MagickFalse)
map="RGBA";
if (image->colorspace == CMYKColorspace)
{
map="CMYK";
if (image->matte != MagickFalse)
map="CMYKA";
}
pixel_info=AcquireVirtualMemory(image->columns,image->rows*strlen(map)*
sizeof(*pixels));
if (pixel_info == (MemoryInfo *) NULL)
return((Image *) NULL);
pixels=(unsigned char *) GetVirtualMemoryBlob(pixel_info);
status=ExportImagePixels(image,0,0,image->columns,image->rows,map,CharPixel,
pixels,exception);
if (status == MagickFalse)
{
pixel_info=RelinquishVirtualMemory(pixel_info);
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
}
carver=lqr_carver_new(pixels,(int) image->columns,(int) image->rows,
(int) strlen(map));
if (carver == (LqrCarver *) NULL)
{
pixel_info=RelinquishVirtualMemory(pixel_info);
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
}
lqr_carver_set_preserve_input_image(carver);
lqr_status=lqr_carver_init(carver,(int) delta_x,rigidity);
lqr_status=lqr_carver_resize(carver,(int) columns,(int) rows);
(void) lqr_status;
rescale_image=CloneImage(image,lqr_carver_get_width(carver),
lqr_carver_get_height(carver),MagickTrue,exception);
if (rescale_image == (Image *) NULL)
{
pixel_info=RelinquishVirtualMemory(pixel_info);
return((Image *) NULL);
}
if (SetImageStorageClass(rescale_image,DirectClass) == MagickFalse)
{
InheritException(exception,&rescale_image->exception);
rescale_image=DestroyImage(rescale_image);
return((Image *) NULL);
}
GetMagickPixelPacket(rescale_image,&pixel);
(void) lqr_carver_scan_reset(carver);
rescale_view=AcquireAuthenticCacheView(rescale_image,exception);
while (lqr_carver_scan(carver,&x,&y,&packet) != 0)
{
register IndexPacket
*magick_restrict rescale_indexes;
register PixelPacket
*magick_restrict q;
q=QueueCacheViewAuthenticPixels(rescale_view,x,y,1,1,exception);
if (q == (PixelPacket *) NULL)
break;
rescale_indexes=GetCacheViewAuthenticIndexQueue(rescale_view);
pixel.red=QuantumRange*(packet[0]/255.0);
pixel.green=QuantumRange*(packet[1]/255.0);
pixel.blue=QuantumRange*(packet[2]/255.0);
if (image->colorspace != CMYKColorspace)
{
if (image->matte != MagickFalse)
pixel.opacity=QuantumRange-QuantumRange*(packet[3]/255.0);
}
else
{
pixel.index=QuantumRange*(packet[3]/255.0);
if (image->matte != MagickFalse)
pixel.opacity=QuantumRange-QuantumRange*(packet[4]/255.0);
}
SetPixelPacket(rescale_image,&pixel,q,rescale_indexes);
if (SyncCacheViewAuthenticPixels(rescale_view,exception) == MagickFalse)
break;
}
rescale_view=DestroyCacheView(rescale_view);
/*
Relinquish resources.
*/
pixel_info=RelinquishVirtualMemory(pixel_info);
lqr_carver_destroy(carver);
return(rescale_image);
}
#else
MagickExport Image *LiquidRescaleImage(const Image *image,
const size_t magick_unused(columns),const size_t magick_unused(rows),
const double magick_unused(delta_x),const double magick_unused(rigidity),
ExceptionInfo *exception)
{
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
(void) ThrowMagickException(exception,GetMagickModule(),MissingDelegateError,
"DelegateLibrarySupportNotBuiltIn","`%s' (LQR)",image->filename);
return((Image *) NULL);
}
#endif
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% M a g n i f y I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% MagnifyImage() doubles the size of the image with a pixel art scaling
% algorithm.
%
% The format of the MagnifyImage method is:
%
% Image *MagnifyImage(const Image *image,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *MagnifyImage(const Image *image,ExceptionInfo *exception)
{
#define MagnifyImageTag "Magnify/Image"
CacheView
*image_view,
*magnify_view;
Image
*magnify_image;
MagickBooleanType
status;
MagickOffsetType
progress;
ssize_t
y;
/*
Initialize magnified image attributes.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
magnify_image=CloneImage(image,2*image->columns,2*image->rows,MagickTrue,
exception);
if (magnify_image == (Image *) NULL)
return((Image *) NULL);
/*
Magnify image.
*/
status=MagickTrue;
progress=0;
image_view=AcquireVirtualCacheView(image,exception);
magnify_view=AcquireAuthenticCacheView(magnify_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(progress,status) \
magick_number_threads(image,magnify_image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
register IndexPacket
*magick_restrict magnify_indexes;
register PixelPacket
*magick_restrict q;
register ssize_t
x;
if (status == MagickFalse)
continue;
q=QueueCacheViewAuthenticPixels(magnify_view,0,2*y,magnify_image->columns,2,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
magnify_indexes=GetCacheViewAuthenticIndexQueue(magnify_view);
for (x=0; x < (ssize_t) image->columns; x++)
{
MagickRealType
intensity[9];
register const IndexPacket
*magick_restrict indexes;
register const PixelPacket
*magick_restrict p;
register PixelPacket
*magick_restrict r;
register ssize_t
i;
/*
Magnify this row of pixels.
*/
p=GetCacheViewVirtualPixels(image_view,x-1,y-1,3,3,exception);
if (p == (const PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
for (i=0; i < 9; i++)
intensity[i]=GetPixelIntensity(image,p+i);
r=q;
if ((fabs(intensity[1]-intensity[7]) < MagickEpsilon) ||
(fabs(intensity[3]-intensity[5]) < MagickEpsilon))
{
/*
Clone center pixel.
*/
*r=p[4];
r++;
*r=p[4];
r+=(magnify_image->columns-1);
*r=p[4];
r++;
*r=p[4];
}
else
{
/*
Selectively clone pixel.
*/
if (fabs(intensity[1]-intensity[3]) < MagickEpsilon)
*r=p[3];
else
*r=p[4];
r++;
if (fabs(intensity[1]-intensity[5]) < MagickEpsilon)
*r=p[5];
else
*r=p[4];
r+=(magnify_image->columns-1);
if (fabs(intensity[3]-intensity[7]) < MagickEpsilon)
*r=p[3];
else
*r=p[4];
r++;
if (fabs(intensity[5]-intensity[7]) < MagickEpsilon)
*r=p[5];
else
*r=p[4];
}
if (indexes != (const IndexPacket *) NULL)
{
register IndexPacket
*r;
/*
Magnify the colormap indexes.
*/
r=magnify_indexes;
if ((fabs(intensity[1]-intensity[7]) < MagickEpsilon) ||
(fabs(intensity[3]-intensity[5]) < MagickEpsilon))
{
/*
Clone center pixel.
*/
*r=indexes[4];
r++;
*r=indexes[4];
r+=(magnify_image->columns-1);
*r=indexes[4];
r++;
*r=indexes[4];
}
else
{
/*
Selectively clone pixel.
*/
if (fabs(intensity[1]-intensity[3]) < MagickEpsilon)
*r=indexes[3];
else
*r=indexes[4];
r++;
if (fabs(intensity[1]-intensity[5]) < MagickEpsilon)
*r=indexes[5];
else
*r=indexes[4];
r+=(magnify_image->columns-1);
if (fabs(intensity[3]-intensity[7]) < MagickEpsilon)
*r=indexes[3];
else
*r=indexes[4];
r++;
if (fabs(intensity[5]-intensity[7]) < MagickEpsilon)
*r=indexes[5];
else
*r=indexes[4];
}
magnify_indexes+=2;
}
q+=2;
}
if (SyncCacheViewAuthenticPixels(magnify_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_MagnifyImage)
#endif
proceed=SetImageProgress(image,MagnifyImageTag,progress++,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
magnify_view=DestroyCacheView(magnify_view);
image_view=DestroyCacheView(image_view);
if (status == MagickFalse)
magnify_image=DestroyImage(magnify_image);
return(magnify_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% M i n i f y I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% MinifyImage() is a convenience method that scales an image proportionally to
% half its size.
%
% The format of the MinifyImage method is:
%
% Image *MinifyImage(const Image *image,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *MinifyImage(const Image *image,ExceptionInfo *exception)
{
Image
*minify_image;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
minify_image=ResizeImage(image,image->columns/2,image->rows/2,SplineFilter,
1.0,exception);
return(minify_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% R e s a m p l e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ResampleImage() resize image in terms of its pixel size, so that when
% displayed at the given resolution it will be the same size in terms of
% real world units as the original image at the original resolution.
%
% The format of the ResampleImage method is:
%
% Image *ResampleImage(Image *image,const double x_resolution,
% const double y_resolution,const FilterTypes filter,const double blur,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image to be resized to fit the given resolution.
%
% o x_resolution: the new image x resolution.
%
% o y_resolution: the new image y resolution.
%
% o filter: Image filter to use.
%
% o blur: the blur factor where > 1 is blurry, < 1 is sharp.
%
*/
MagickExport Image *ResampleImage(const Image *image,const double x_resolution,
const double y_resolution,const FilterTypes filter,const double blur,
ExceptionInfo *exception)
{
#define ResampleImageTag "Resample/Image"
Image
*resample_image;
size_t
height,
width;
/*
Initialize sampled image attributes.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
width=(size_t) (x_resolution*image->columns/(image->x_resolution == 0.0 ?
72.0 : image->x_resolution)+0.5);
height=(size_t) (y_resolution*image->rows/(image->y_resolution == 0.0 ?
72.0 : image->y_resolution)+0.5);
resample_image=ResizeImage(image,width,height,filter,blur,exception);
if (resample_image != (Image *) NULL)
{
resample_image->x_resolution=x_resolution;
resample_image->y_resolution=y_resolution;
}
return(resample_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% R e s i z e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ResizeImage() scales an image to the desired dimensions, using the given
% filter (see AcquireFilterInfo()).
%
% If an undefined filter is given the filter defaults to Mitchell for a
% colormapped image, a image with a matte channel, or if the image is
% enlarged. Otherwise the filter defaults to a Lanczos.
%
% ResizeImage() was inspired by Paul Heckbert's "zoom" program.
%
% The format of the ResizeImage method is:
%
% Image *ResizeImage(Image *image,const size_t columns,
% const size_t rows,const FilterTypes filter,const double blur,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o columns: the number of columns in the scaled image.
%
% o rows: the number of rows in the scaled image.
%
% o filter: Image filter to use.
%
% o blur: the blur factor where > 1 is blurry, < 1 is sharp. Typically set
% this to 1.0.
%
% o exception: return any errors or warnings in this structure.
%
*/
typedef struct _ContributionInfo
{
MagickRealType
weight;
ssize_t
pixel;
} ContributionInfo;
static ContributionInfo **DestroyContributionThreadSet(
ContributionInfo **contribution)
{
register ssize_t
i;
assert(contribution != (ContributionInfo **) NULL);
for (i=0; i < (ssize_t) GetMagickResourceLimit(ThreadResource); i++)
if (contribution[i] != (ContributionInfo *) NULL)
contribution[i]=(ContributionInfo *) RelinquishAlignedMemory(
contribution[i]);
contribution=(ContributionInfo **) RelinquishMagickMemory(contribution);
return(contribution);
}
static ContributionInfo **AcquireContributionThreadSet(const size_t count)
{
register ssize_t
i;
ContributionInfo
**contribution;
size_t
number_threads;
number_threads=(size_t) GetMagickResourceLimit(ThreadResource);
contribution=(ContributionInfo **) AcquireQuantumMemory(number_threads,
sizeof(*contribution));
if (contribution == (ContributionInfo **) NULL)
return((ContributionInfo **) NULL);
(void) ResetMagickMemory(contribution,0,number_threads*sizeof(*contribution));
for (i=0; i < (ssize_t) number_threads; i++)
{
contribution[i]=(ContributionInfo *) MagickAssumeAligned(
AcquireAlignedMemory(count,sizeof(**contribution)));
if (contribution[i] == (ContributionInfo *) NULL)
return(DestroyContributionThreadSet(contribution));
}
return(contribution);
}
static MagickBooleanType HorizontalFilter(const ResizeFilter *resize_filter,
const Image *image,Image *resize_image,const MagickRealType x_factor,
const MagickSizeType span,MagickOffsetType *offset,ExceptionInfo *exception)
{
#define ResizeImageTag "Resize/Image"
CacheView
*image_view,
*resize_view;
ClassType
storage_class;
ContributionInfo
**magick_restrict contributions;
MagickBooleanType
status;
MagickPixelPacket
zero;
MagickRealType
scale,
support;
ssize_t
x;
/*
Apply filter to resize horizontally from image to resize image.
*/
scale=MagickMax(1.0/x_factor+MagickEpsilon,1.0);
support=scale*GetResizeFilterSupport(resize_filter);
storage_class=support > 0.5 ? DirectClass : image->storage_class;
if (SetImageStorageClass(resize_image,storage_class) == MagickFalse)
{
InheritException(exception,&resize_image->exception);
return(MagickFalse);
}
if (support < 0.5)
{
/*
Support too small even for nearest neighbour: Reduce to point
sampling.
*/
support=(MagickRealType) 0.5;
scale=1.0;
}
contributions=AcquireContributionThreadSet((size_t) (2.0*support+3.0));
if (contributions == (ContributionInfo **) NULL)
{
(void) ThrowMagickException(exception,GetMagickModule(),
ResourceLimitError,"MemoryAllocationFailed","`%s'",image->filename);
return(MagickFalse);
}
status=MagickTrue;
scale=PerceptibleReciprocal(scale);
(void) ResetMagickMemory(&zero,0,sizeof(zero));
image_view=AcquireVirtualCacheView(image,exception);
resize_view=AcquireAuthenticCacheView(resize_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status) \
magick_number_threads(image,resize_image,resize_image->columns,1)
#endif
for (x=0; x < (ssize_t) resize_image->columns; x++)
{
const int
id = GetOpenMPThreadId();
MagickRealType
bisect,
density;
register const IndexPacket
*magick_restrict indexes;
register const PixelPacket
*magick_restrict p;
register ContributionInfo
*magick_restrict contribution;
register IndexPacket
*magick_restrict resize_indexes;
register PixelPacket
*magick_restrict q;
register ssize_t
y;
ssize_t
n,
start,
stop;
if (status == MagickFalse)
continue;
bisect=(MagickRealType) (x+0.5)/x_factor+MagickEpsilon;
start=(ssize_t) MagickMax(bisect-support+0.5,0.0);
stop=(ssize_t) MagickMin(bisect+support+0.5,(double) image->columns);
density=0.0;
contribution=contributions[id];
for (n=0; n < (stop-start); n++)
{
contribution[n].pixel=start+n;
contribution[n].weight=GetResizeFilterWeight(resize_filter,scale*
((MagickRealType) (start+n)-bisect+0.5));
density+=contribution[n].weight;
}
if (n == 0)
continue;
if ((density != 0.0) && (density != 1.0))
{
register ssize_t
i;
/*
Normalize.
*/
density=PerceptibleReciprocal(density);
for (i=0; i < n; i++)
contribution[i].weight*=density;
}
p=GetCacheViewVirtualPixels(image_view,contribution[0].pixel,0,(size_t)
(contribution[n-1].pixel-contribution[0].pixel+1),image->rows,exception);
q=QueueCacheViewAuthenticPixels(resize_view,x,0,1,resize_image->rows,
exception);
if ((p == (const PixelPacket *) NULL) || (q == (PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
resize_indexes=GetCacheViewAuthenticIndexQueue(resize_view);
for (y=0; y < (ssize_t) resize_image->rows; y++)
{
MagickPixelPacket
pixel;
MagickRealType
alpha;
register ssize_t
i;
ssize_t
j;
pixel=zero;
if (image->matte == MagickFalse)
{
for (i=0; i < n; i++)
{
j=y*(contribution[n-1].pixel-contribution[0].pixel+1)+
(contribution[i].pixel-contribution[0].pixel);
alpha=contribution[i].weight;
pixel.red+=alpha*GetPixelRed(p+j);
pixel.green+=alpha*GetPixelGreen(p+j);
pixel.blue+=alpha*GetPixelBlue(p+j);
pixel.opacity+=alpha*GetPixelOpacity(p+j);
}
SetPixelRed(q,ClampToQuantum(pixel.red));
SetPixelGreen(q,ClampToQuantum(pixel.green));
SetPixelBlue(q,ClampToQuantum(pixel.blue));
SetPixelOpacity(q,ClampToQuantum(pixel.opacity));
if ((image->colorspace == CMYKColorspace) &&
(resize_image->colorspace == CMYKColorspace))
{
for (i=0; i < n; i++)
{
j=y*(contribution[n-1].pixel-contribution[0].pixel+1)+
(contribution[i].pixel-contribution[0].pixel);
alpha=contribution[i].weight;
pixel.index+=alpha*GetPixelIndex(indexes+j);
}
SetPixelIndex(resize_indexes+y,ClampToQuantum(pixel.index));
}
}
else
{
double
gamma;
gamma=0.0;
for (i=0; i < n; i++)
{
j=y*(contribution[n-1].pixel-contribution[0].pixel+1)+
(contribution[i].pixel-contribution[0].pixel);
alpha=contribution[i].weight*QuantumScale*GetPixelAlpha(p+j);
pixel.red+=alpha*GetPixelRed(p+j);
pixel.green+=alpha*GetPixelGreen(p+j);
pixel.blue+=alpha*GetPixelBlue(p+j);
pixel.opacity+=contribution[i].weight*GetPixelOpacity(p+j);
gamma+=alpha;
}
gamma=PerceptibleReciprocal(gamma);
SetPixelRed(q,ClampToQuantum(gamma*pixel.red));
SetPixelGreen(q,ClampToQuantum(gamma*pixel.green));
SetPixelBlue(q,ClampToQuantum(gamma*pixel.blue));
SetPixelOpacity(q,ClampToQuantum(pixel.opacity));
if ((image->colorspace == CMYKColorspace) &&
(resize_image->colorspace == CMYKColorspace))
{
for (i=0; i < n; i++)
{
j=y*(contribution[n-1].pixel-contribution[0].pixel+1)+
(contribution[i].pixel-contribution[0].pixel);
alpha=contribution[i].weight*QuantumScale*GetPixelAlpha(p+j);
pixel.index+=alpha*GetPixelIndex(indexes+j);
}
SetPixelIndex(resize_indexes+y,ClampToQuantum(gamma*pixel.index));
}
}
if ((resize_image->storage_class == PseudoClass) &&
(image->storage_class == PseudoClass))
{
i=(ssize_t) (MagickMin(MagickMax(bisect,(double) start),(double) stop-
1.0)+0.5);
j=y*(contribution[n-1].pixel-contribution[0].pixel+1)+
(contribution[i-start].pixel-contribution[0].pixel);
SetPixelIndex(resize_indexes+y,GetPixelIndex(indexes+j));
}
q++;
}
if (SyncCacheViewAuthenticPixels(resize_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_HorizontalFilter)
#endif
proceed=SetImageProgress(image,ResizeImageTag,(*offset)++,span);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
resize_view=DestroyCacheView(resize_view);
image_view=DestroyCacheView(image_view);
contributions=DestroyContributionThreadSet(contributions);
return(status);
}
static MagickBooleanType VerticalFilter(const ResizeFilter *resize_filter,
const Image *image,Image *resize_image,const MagickRealType y_factor,
const MagickSizeType span,MagickOffsetType *offset,ExceptionInfo *exception)
{
CacheView
*image_view,
*resize_view;
ClassType
storage_class;
ContributionInfo
**magick_restrict contributions;
MagickBooleanType
status;
MagickPixelPacket
zero;
MagickRealType
scale,
support;
ssize_t
y;
/*
Apply filter to resize vertically from image to resize image.
*/
scale=MagickMax(1.0/y_factor+MagickEpsilon,1.0);
support=scale*GetResizeFilterSupport(resize_filter);
storage_class=support > 0.5 ? DirectClass : image->storage_class;
if (SetImageStorageClass(resize_image,storage_class) == MagickFalse)
{
InheritException(exception,&resize_image->exception);
return(MagickFalse);
}
if (support < 0.5)
{
/*
Support too small even for nearest neighbour: Reduce to point
sampling.
*/
support=(MagickRealType) 0.5;
scale=1.0;
}
contributions=AcquireContributionThreadSet((size_t) (2.0*support+3.0));
if (contributions == (ContributionInfo **) NULL)
{
(void) ThrowMagickException(exception,GetMagickModule(),
ResourceLimitError,"MemoryAllocationFailed","`%s'",image->filename);
return(MagickFalse);
}
status=MagickTrue;
scale=PerceptibleReciprocal(scale);
(void) ResetMagickMemory(&zero,0,sizeof(zero));
image_view=AcquireVirtualCacheView(image,exception);
resize_view=AcquireAuthenticCacheView(resize_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status) \
magick_number_threads(image,resize_image,resize_image->rows,1)
#endif
for (y=0; y < (ssize_t) resize_image->rows; y++)
{
const int
id = GetOpenMPThreadId();
MagickRealType
bisect,
density;
register const IndexPacket
*magick_restrict indexes;
register const PixelPacket
*magick_restrict p;
register ContributionInfo
*magick_restrict contribution;
register IndexPacket
*magick_restrict resize_indexes;
register PixelPacket
*magick_restrict q;
register ssize_t
x;
ssize_t
n,
start,
stop;
if (status == MagickFalse)
continue;
bisect=(MagickRealType) (y+0.5)/y_factor+MagickEpsilon;
start=(ssize_t) MagickMax(bisect-support+0.5,0.0);
stop=(ssize_t) MagickMin(bisect+support+0.5,(double) image->rows);
density=0.0;
contribution=contributions[id];
for (n=0; n < (stop-start); n++)
{
contribution[n].pixel=start+n;
contribution[n].weight=GetResizeFilterWeight(resize_filter,scale*
((MagickRealType) (start+n)-bisect+0.5));
density+=contribution[n].weight;
}
if (n == 0)
continue;
if ((density != 0.0) && (density != 1.0))
{
register ssize_t
i;
/*
Normalize.
*/
density=PerceptibleReciprocal(density);
for (i=0; i < n; i++)
contribution[i].weight*=density;
}
p=GetCacheViewVirtualPixels(image_view,0,contribution[0].pixel,
image->columns,(size_t) (contribution[n-1].pixel-contribution[0].pixel+1),
exception);
q=QueueCacheViewAuthenticPixels(resize_view,0,y,resize_image->columns,1,
exception);
if ((p == (const PixelPacket *) NULL) || (q == (PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
resize_indexes=GetCacheViewAuthenticIndexQueue(resize_view);
for (x=0; x < (ssize_t) resize_image->columns; x++)
{
MagickPixelPacket
pixel;
MagickRealType
alpha;
register ssize_t
i;
ssize_t
j;
pixel=zero;
if (image->matte == MagickFalse)
{
for (i=0; i < n; i++)
{
j=(ssize_t) ((contribution[i].pixel-contribution[0].pixel)*
image->columns+x);
alpha=contribution[i].weight;
pixel.red+=alpha*GetPixelRed(p+j);
pixel.green+=alpha*GetPixelGreen(p+j);
pixel.blue+=alpha*GetPixelBlue(p+j);
pixel.opacity+=alpha*GetPixelOpacity(p+j);
}
SetPixelRed(q,ClampToQuantum(pixel.red));
SetPixelGreen(q,ClampToQuantum(pixel.green));
SetPixelBlue(q,ClampToQuantum(pixel.blue));
SetPixelOpacity(q,ClampToQuantum(pixel.opacity));
if ((image->colorspace == CMYKColorspace) &&
(resize_image->colorspace == CMYKColorspace))
{
for (i=0; i < n; i++)
{
j=(ssize_t) ((contribution[i].pixel-contribution[0].pixel)*
image->columns+x);
alpha=contribution[i].weight;
pixel.index+=alpha*GetPixelIndex(indexes+j);
}
SetPixelIndex(resize_indexes+x,ClampToQuantum(pixel.index));
}
}
else
{
double
gamma;
gamma=0.0;
for (i=0; i < n; i++)
{
j=(ssize_t) ((contribution[i].pixel-contribution[0].pixel)*
image->columns+x);
alpha=contribution[i].weight*QuantumScale*GetPixelAlpha(p+j);
pixel.red+=alpha*GetPixelRed(p+j);
pixel.green+=alpha*GetPixelGreen(p+j);
pixel.blue+=alpha*GetPixelBlue(p+j);
pixel.opacity+=contribution[i].weight*GetPixelOpacity(p+j);
gamma+=alpha;
}
gamma=PerceptibleReciprocal(gamma);
SetPixelRed(q,ClampToQuantum(gamma*pixel.red));
SetPixelGreen(q,ClampToQuantum(gamma*pixel.green));
SetPixelBlue(q,ClampToQuantum(gamma*pixel.blue));
SetPixelOpacity(q,ClampToQuantum(pixel.opacity));
if ((image->colorspace == CMYKColorspace) &&
(resize_image->colorspace == CMYKColorspace))
{
for (i=0; i < n; i++)
{
j=(ssize_t) ((contribution[i].pixel-contribution[0].pixel)*
image->columns+x);
alpha=contribution[i].weight*QuantumScale*GetPixelAlpha(p+j);
pixel.index+=alpha*GetPixelIndex(indexes+j);
}
SetPixelIndex(resize_indexes+x,ClampToQuantum(gamma*pixel.index));
}
}
if ((resize_image->storage_class == PseudoClass) &&
(image->storage_class == PseudoClass))
{
i=(ssize_t) (MagickMin(MagickMax(bisect,(double) start),(double) stop-
1.0)+0.5);
j=(ssize_t) ((contribution[i-start].pixel-contribution[0].pixel)*
image->columns+x);
SetPixelIndex(resize_indexes+x,GetPixelIndex(indexes+j));
}
q++;
}
if (SyncCacheViewAuthenticPixels(resize_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_VerticalFilter)
#endif
proceed=SetImageProgress(image,ResizeImageTag,(*offset)++,span);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
resize_view=DestroyCacheView(resize_view);
image_view=DestroyCacheView(image_view);
contributions=DestroyContributionThreadSet(contributions);
return(status);
}
MagickExport Image *ResizeImage(const Image *image,const size_t columns,
const size_t rows,const FilterTypes filter,const double blur,
ExceptionInfo *exception)
{
FilterTypes
filter_type;
Image
*filter_image,
*resize_image;
MagickOffsetType
offset;
MagickRealType
x_factor,
y_factor;
MagickSizeType
span;
MagickStatusType
status;
ResizeFilter
*resize_filter;
/*
Acquire resize image.
*/
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
if ((columns == 0) || (rows == 0))
ThrowImageException(ImageError,"NegativeOrZeroImageSize");
if ((columns == image->columns) && (rows == image->rows) &&
(filter == UndefinedFilter) && (blur == 1.0))
return(CloneImage(image,0,0,MagickTrue,exception));
/*
Acquire resize filter.
*/
x_factor=(MagickRealType) columns/(MagickRealType) image->columns;
y_factor=(MagickRealType) rows/(MagickRealType) image->rows;
filter_type=LanczosFilter;
if (filter != UndefinedFilter)
filter_type=filter;
else
if ((x_factor == 1.0) && (y_factor == 1.0))
filter_type=PointFilter;
else
if ((image->storage_class == PseudoClass) ||
(image->matte != MagickFalse) || ((x_factor*y_factor) > 1.0))
filter_type=MitchellFilter;
resize_filter=AcquireResizeFilter(image,filter_type,blur,MagickFalse,
exception);
#if defined(MAGICKCORE_OPENCL_SUPPORT)
resize_image=AccelerateResizeImage(image,columns,rows,resize_filter,
exception);
if (resize_image != NULL)
{
resize_filter=DestroyResizeFilter(resize_filter);
return(resize_image);
}
#endif
resize_image=CloneImage(image,columns,rows,MagickTrue,exception);
if (resize_image == (Image *) NULL)
{
resize_filter=DestroyResizeFilter(resize_filter);
return(resize_image);
}
if (x_factor > y_factor)
filter_image=CloneImage(image,columns,image->rows,MagickTrue,exception);
else
filter_image=CloneImage(image,image->columns,rows,MagickTrue,exception);
if (filter_image == (Image *) NULL)
{
resize_filter=DestroyResizeFilter(resize_filter);
return(DestroyImage(resize_image));
}
/*
Resize image.
*/
offset=0;
if (x_factor > y_factor)
{
span=(MagickSizeType) (filter_image->columns+rows);
status=HorizontalFilter(resize_filter,image,filter_image,x_factor,span,
&offset,exception);
status&=VerticalFilter(resize_filter,filter_image,resize_image,y_factor,
span,&offset,exception);
}
else
{
span=(MagickSizeType) (filter_image->rows+columns);
status=VerticalFilter(resize_filter,image,filter_image,y_factor,span,
&offset,exception);
status&=HorizontalFilter(resize_filter,filter_image,resize_image,x_factor,
span,&offset,exception);
}
/*
Free resources.
*/
filter_image=DestroyImage(filter_image);
resize_filter=DestroyResizeFilter(resize_filter);
if (status == MagickFalse)
{
resize_image=DestroyImage(resize_image);
return((Image *) NULL);
}
resize_image->type=image->type;
return(resize_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S a m p l e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SampleImage() scales an image to the desired dimensions with pixel
% sampling. Unlike other scaling methods, this method does not introduce
% any additional color into the scaled image.
%
% The format of the SampleImage method is:
%
% Image *SampleImage(const Image *image,const size_t columns,
% const size_t rows,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o columns: the number of columns in the sampled image.
%
% o rows: the number of rows in the sampled image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *SampleImage(const Image *image,const size_t columns,
const size_t rows,ExceptionInfo *exception)
{
#define SampleImageTag "Sample/Image"
CacheView
*image_view,
*sample_view;
Image
*sample_image;
MagickBooleanType
status;
MagickOffsetType
progress;
register ssize_t
x;
ssize_t
*x_offset,
y;
PointInfo
sample_offset;
/*
Initialize sampled image attributes.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
if ((columns == 0) || (rows == 0))
ThrowImageException(ImageError,"NegativeOrZeroImageSize");
if ((columns == image->columns) && (rows == image->rows))
return(CloneImage(image,0,0,MagickTrue,exception));
sample_image=CloneImage(image,columns,rows,MagickTrue,exception);
if (sample_image == (Image *) NULL)
return((Image *) NULL);
/*
Check for posible user defined sampling offset Artifact
The default sampling offset is in the mid-point of sample regions.
*/
sample_offset.x=sample_offset.y=0.5-MagickEpsilon;
{
const char
*value;
value=GetImageArtifact(image,"sample:offset");
if (value != (char *) NULL)
{
GeometryInfo
geometry_info;
MagickStatusType
flags;
(void) ParseGeometry(value,&geometry_info);
flags=ParseGeometry(value,&geometry_info);
sample_offset.x=sample_offset.y=geometry_info.rho/100.0-MagickEpsilon;
if ((flags & SigmaValue) != 0)
sample_offset.y=geometry_info.sigma/100.0-MagickEpsilon;
}
}
/*
Allocate scan line buffer and column offset buffers.
*/
x_offset=(ssize_t *) AcquireQuantumMemory((size_t) sample_image->columns,
sizeof(*x_offset));
if (x_offset == (ssize_t *) NULL)
{
sample_image=DestroyImage(sample_image);
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
}
for (x=0; x < (ssize_t) sample_image->columns; x++)
x_offset[x]=(ssize_t) ((((double) x+sample_offset.x)*image->columns)/
sample_image->columns);
/*
Sample each row.
*/
status=MagickTrue;
progress=0;
image_view=AcquireVirtualCacheView(image,exception);
sample_view=AcquireAuthenticCacheView(sample_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status) \
magick_number_threads(image,sample_image,sample_image->rows,1)
#endif
for (y=0; y < (ssize_t) sample_image->rows; y++)
{
register const IndexPacket
*magick_restrict indexes;
register const PixelPacket
*magick_restrict p;
register IndexPacket
*magick_restrict sample_indexes;
register PixelPacket
*magick_restrict q;
register ssize_t
x;
ssize_t
y_offset;
if (status == MagickFalse)
continue;
y_offset=(ssize_t) ((((double) y+sample_offset.y)*image->rows)/
sample_image->rows);
p=GetCacheViewVirtualPixels(image_view,0,y_offset,image->columns,1,
exception);
q=QueueCacheViewAuthenticPixels(sample_view,0,y,sample_image->columns,1,
exception);
if ((p == (const PixelPacket *) NULL) || (q == (PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewAuthenticIndexQueue(image_view);
sample_indexes=GetCacheViewAuthenticIndexQueue(sample_view);
/*
Sample each column.
*/
for (x=0; x < (ssize_t) sample_image->columns; x++)
*q++=p[x_offset[x]];
if ((image->storage_class == PseudoClass) ||
(image->colorspace == CMYKColorspace))
for (x=0; x < (ssize_t) sample_image->columns; x++)
SetPixelIndex(sample_indexes+x,GetPixelIndex(indexes+x_offset[x]));
if (SyncCacheViewAuthenticPixels(sample_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_SampleImage)
#endif
proceed=SetImageProgress(image,SampleImageTag,progress++,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
image_view=DestroyCacheView(image_view);
sample_view=DestroyCacheView(sample_view);
x_offset=(ssize_t *) RelinquishMagickMemory(x_offset);
sample_image->type=image->type;
if (status == MagickFalse)
sample_image=DestroyImage(sample_image);
return(sample_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S c a l e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ScaleImage() changes the size of an image to the given dimensions.
%
% The format of the ScaleImage method is:
%
% Image *ScaleImage(const Image *image,const size_t columns,
% const size_t rows,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o columns: the number of columns in the scaled image.
%
% o rows: the number of rows in the scaled image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *ScaleImage(const Image *image,const size_t columns,
const size_t rows,ExceptionInfo *exception)
{
#define ScaleImageTag "Scale/Image"
CacheView
*image_view,
*scale_view;
Image
*scale_image;
MagickBooleanType
next_column,
next_row,
proceed,
status;
MagickPixelPacket
pixel,
*scale_scanline,
*scanline,
*x_vector,
*y_vector,
zero;
MagickRealType
alpha;
PointInfo
scale,
span;
register ssize_t
i;
ssize_t
number_rows,
y;
/*
Initialize scaled image attributes.
*/
assert(image != (const Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
if ((columns == 0) || (rows == 0))
return((Image *) NULL);
if ((columns == image->columns) && (rows == image->rows))
return(CloneImage(image,0,0,MagickTrue,exception));
scale_image=CloneImage(image,columns,rows,MagickTrue,exception);
if (scale_image == (Image *) NULL)
return((Image *) NULL);
if (SetImageStorageClass(scale_image,DirectClass) == MagickFalse)
{
InheritException(exception,&scale_image->exception);
scale_image=DestroyImage(scale_image);
return((Image *) NULL);
}
/*
Allocate memory.
*/
x_vector=(MagickPixelPacket *) AcquireQuantumMemory((size_t) image->columns,
sizeof(*x_vector));
scanline=x_vector;
if (image->rows != scale_image->rows)
scanline=(MagickPixelPacket *) AcquireQuantumMemory((size_t) image->columns,
sizeof(*scanline));
scale_scanline=(MagickPixelPacket *) AcquireQuantumMemory((size_t)
scale_image->columns,sizeof(*scale_scanline));
y_vector=(MagickPixelPacket *) AcquireQuantumMemory((size_t) image->columns,
sizeof(*y_vector));
if ((scanline == (MagickPixelPacket *) NULL) ||
(scale_scanline == (MagickPixelPacket *) NULL) ||
(x_vector == (MagickPixelPacket *) NULL) ||
(y_vector == (MagickPixelPacket *) NULL))
{
if ((image->rows != scale_image->rows) &&
(scanline != (MagickPixelPacket *) NULL))
scanline=(MagickPixelPacket *) RelinquishMagickMemory(scanline);
if (scale_scanline != (MagickPixelPacket *) NULL)
scale_scanline=(MagickPixelPacket *) RelinquishMagickMemory(
scale_scanline);
if (x_vector != (MagickPixelPacket *) NULL)
x_vector=(MagickPixelPacket *) RelinquishMagickMemory(x_vector);
if (y_vector != (MagickPixelPacket *) NULL)
y_vector=(MagickPixelPacket *) RelinquishMagickMemory(y_vector);
scale_image=DestroyImage(scale_image);
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
}
/*
Scale image.
*/
number_rows=0;
next_row=MagickTrue;
span.y=1.0;
scale.y=(double) scale_image->rows/(double) image->rows;
(void) ResetMagickMemory(y_vector,0,(size_t) image->columns*
sizeof(*y_vector));
GetMagickPixelPacket(image,&pixel);
(void) ResetMagickMemory(&zero,0,sizeof(zero));
i=0;
status=MagickTrue;
image_view=AcquireVirtualCacheView(image,exception);
scale_view=AcquireAuthenticCacheView(scale_image,exception);
for (y=0; y < (ssize_t) scale_image->rows; y++)
{
register const IndexPacket
*magick_restrict indexes;
register const PixelPacket
*magick_restrict p;
register IndexPacket
*magick_restrict scale_indexes;
register MagickPixelPacket
*magick_restrict s,
*magick_restrict t;
register PixelPacket
*magick_restrict q;
register ssize_t
x;
if (status == MagickFalse)
break;
q=QueueCacheViewAuthenticPixels(scale_view,0,y,scale_image->columns,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
break;
}
alpha=1.0;
scale_indexes=GetCacheViewAuthenticIndexQueue(scale_view);
if (scale_image->rows == image->rows)
{
/*
Read a new scanline.
*/
p=GetCacheViewVirtualPixels(image_view,0,i++,image->columns,1,
exception);
if (p == (const PixelPacket *) NULL)
{
status=MagickFalse;
break;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
for (x=0; x < (ssize_t) image->columns; x++)
{
if (image->matte != MagickFalse)
alpha=QuantumScale*GetPixelAlpha(p);
x_vector[x].red=(MagickRealType) (alpha*GetPixelRed(p));
x_vector[x].green=(MagickRealType) (alpha*GetPixelGreen(p));
x_vector[x].blue=(MagickRealType) (alpha*GetPixelBlue(p));
if (image->matte != MagickFalse)
x_vector[x].opacity=(MagickRealType) GetPixelOpacity(p);
if (indexes != (IndexPacket *) NULL)
x_vector[x].index=(MagickRealType) (alpha*GetPixelIndex(indexes+x));
p++;
}
}
else
{
/*
Scale Y direction.
*/
while (scale.y < span.y)
{
if ((next_row != MagickFalse) &&
(number_rows < (ssize_t) image->rows))
{
/*
Read a new scanline.
*/
p=GetCacheViewVirtualPixels(image_view,0,i++,image->columns,1,
exception);
if (p == (const PixelPacket *) NULL)
{
status=MagickFalse;
break;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
for (x=0; x < (ssize_t) image->columns; x++)
{
if (image->matte != MagickFalse)
alpha=QuantumScale*GetPixelAlpha(p);
x_vector[x].red=(MagickRealType) (alpha*GetPixelRed(p));
x_vector[x].green=(MagickRealType) (alpha*GetPixelGreen(p));
x_vector[x].blue=(MagickRealType) (alpha*GetPixelBlue(p));
if (image->matte != MagickFalse)
x_vector[x].opacity=(MagickRealType) GetPixelOpacity(p);
if (indexes != (IndexPacket *) NULL)
x_vector[x].index=(MagickRealType) (alpha*
GetPixelIndex(indexes+x));
p++;
}
number_rows++;
}
for (x=0; x < (ssize_t) image->columns; x++)
{
y_vector[x].red+=scale.y*x_vector[x].red;
y_vector[x].green+=scale.y*x_vector[x].green;
y_vector[x].blue+=scale.y*x_vector[x].blue;
if (scale_image->matte != MagickFalse)
y_vector[x].opacity+=scale.y*x_vector[x].opacity;
if (scale_indexes != (IndexPacket *) NULL)
y_vector[x].index+=scale.y*x_vector[x].index;
}
span.y-=scale.y;
scale.y=(double) scale_image->rows/(double) image->rows;
next_row=MagickTrue;
}
if ((next_row != MagickFalse) && (number_rows < (ssize_t) image->rows))
{
/*
Read a new scanline.
*/
p=GetCacheViewVirtualPixels(image_view,0,i++,image->columns,1,
exception);
if (p == (const PixelPacket *) NULL)
{
status=MagickFalse;
break;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
for (x=0; x < (ssize_t) image->columns; x++)
{
if (image->matte != MagickFalse)
alpha=QuantumScale*GetPixelAlpha(p);
x_vector[x].red=(MagickRealType) (alpha*GetPixelRed(p));
x_vector[x].green=(MagickRealType) (alpha*GetPixelGreen(p));
x_vector[x].blue=(MagickRealType) (alpha*GetPixelBlue(p));
if (image->matte != MagickFalse)
x_vector[x].opacity=(MagickRealType) GetPixelOpacity(p);
if (indexes != (IndexPacket *) NULL)
x_vector[x].index=(MagickRealType) (alpha*
GetPixelIndex(indexes+x));
p++;
}
number_rows++;
next_row=MagickFalse;
}
s=scanline;
for (x=0; x < (ssize_t) image->columns; x++)
{
pixel.red=y_vector[x].red+span.y*x_vector[x].red;
pixel.green=y_vector[x].green+span.y*x_vector[x].green;
pixel.blue=y_vector[x].blue+span.y*x_vector[x].blue;
if (image->matte != MagickFalse)
pixel.opacity=y_vector[x].opacity+span.y*x_vector[x].opacity;
if (scale_indexes != (IndexPacket *) NULL)
pixel.index=y_vector[x].index+span.y*x_vector[x].index;
s->red=pixel.red;
s->green=pixel.green;
s->blue=pixel.blue;
if (scale_image->matte != MagickFalse)
s->opacity=pixel.opacity;
if (scale_indexes != (IndexPacket *) NULL)
s->index=pixel.index;
s++;
y_vector[x]=zero;
}
scale.y-=span.y;
if (scale.y <= 0)
{
scale.y=(double) scale_image->rows/(double) image->rows;
next_row=MagickTrue;
}
span.y=1.0;
}
if (scale_image->columns == image->columns)
{
/*
Transfer scanline to scaled image.
*/
s=scanline;
for (x=0; x < (ssize_t) scale_image->columns; x++)
{
if (scale_image->matte != MagickFalse)
alpha=QuantumScale*GetPixelAlpha(s);
alpha=PerceptibleReciprocal(alpha);
SetPixelRed(q,ClampToQuantum(alpha*s->red));
SetPixelGreen(q,ClampToQuantum(alpha*s->green));
SetPixelBlue(q,ClampToQuantum(alpha*s->blue));
if (scale_image->matte != MagickFalse)
SetPixelOpacity(q,ClampToQuantum(s->opacity));
if (scale_indexes != (IndexPacket *) NULL)
SetPixelIndex(scale_indexes+x,ClampToQuantum(alpha*s->index));
q++;
s++;
}
}
else
{
/*
Scale X direction.
*/
pixel=zero;
next_column=MagickFalse;
span.x=1.0;
s=scanline;
t=scale_scanline;
for (x=0; x < (ssize_t) image->columns; x++)
{
scale.x=(double) scale_image->columns/(double) image->columns;
while (scale.x >= span.x)
{
if (next_column != MagickFalse)
{
pixel=zero;
t++;
}
pixel.red+=span.x*s->red;
pixel.green+=span.x*s->green;
pixel.blue+=span.x*s->blue;
if (image->matte != MagickFalse)
pixel.opacity+=span.x*s->opacity;
if (scale_indexes != (IndexPacket *) NULL)
pixel.index+=span.x*s->index;
t->red=pixel.red;
t->green=pixel.green;
t->blue=pixel.blue;
if (scale_image->matte != MagickFalse)
t->opacity=pixel.opacity;
if (scale_indexes != (IndexPacket *) NULL)
t->index=pixel.index;
scale.x-=span.x;
span.x=1.0;
next_column=MagickTrue;
}
if (scale.x > 0)
{
if (next_column != MagickFalse)
{
pixel=zero;
next_column=MagickFalse;
t++;
}
pixel.red+=scale.x*s->red;
pixel.green+=scale.x*s->green;
pixel.blue+=scale.x*s->blue;
if (scale_image->matte != MagickFalse)
pixel.opacity+=scale.x*s->opacity;
if (scale_indexes != (IndexPacket *) NULL)
pixel.index+=scale.x*s->index;
span.x-=scale.x;
}
s++;
}
if (span.x > 0)
{
s--;
pixel.red+=span.x*s->red;
pixel.green+=span.x*s->green;
pixel.blue+=span.x*s->blue;
if (scale_image->matte != MagickFalse)
pixel.opacity+=span.x*s->opacity;
if (scale_indexes != (IndexPacket *) NULL)
pixel.index+=span.x*s->index;
}
if ((next_column == MagickFalse) &&
((ssize_t) (t-scale_scanline) < (ssize_t) scale_image->columns))
{
t->red=pixel.red;
t->green=pixel.green;
t->blue=pixel.blue;
if (scale_image->matte != MagickFalse)
t->opacity=pixel.opacity;
if (scale_indexes != (IndexPacket *) NULL)
t->index=pixel.index;
}
/*
Transfer scanline to scaled image.
*/
t=scale_scanline;
for (x=0; x < (ssize_t) scale_image->columns; x++)
{
if (scale_image->matte != MagickFalse)
alpha=QuantumScale*GetPixelAlpha(t);
alpha=PerceptibleReciprocal(alpha);
SetPixelRed(q,ClampToQuantum(alpha*t->red));
SetPixelGreen(q,ClampToQuantum(alpha*t->green));
SetPixelBlue(q,ClampToQuantum(alpha*t->blue));
if (scale_image->matte != MagickFalse)
SetPixelOpacity(q,ClampToQuantum(t->opacity));
if (scale_indexes != (IndexPacket *) NULL)
SetPixelIndex(scale_indexes+x,ClampToQuantum(alpha*t->index));
t++;
q++;
}
}
if (SyncCacheViewAuthenticPixels(scale_view,exception) == MagickFalse)
{
status=MagickFalse;
break;
}
proceed=SetImageProgress(image,ScaleImageTag,(MagickOffsetType) y,
image->rows);
if (proceed == MagickFalse)
{
status=MagickFalse;
break;
}
}
scale_view=DestroyCacheView(scale_view);
image_view=DestroyCacheView(image_view);
/*
Free allocated memory.
*/
y_vector=(MagickPixelPacket *) RelinquishMagickMemory(y_vector);
scale_scanline=(MagickPixelPacket *) RelinquishMagickMemory(scale_scanline);
if (scale_image->rows != image->rows)
scanline=(MagickPixelPacket *) RelinquishMagickMemory(scanline);
x_vector=(MagickPixelPacket *) RelinquishMagickMemory(x_vector);
scale_image->type=image->type;
if (status == MagickFalse)
scale_image=DestroyImage(scale_image);
return(scale_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% T h u m b n a i l I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ThumbnailImage() changes the size of an image to the given dimensions and
% removes any associated profiles. The goal is to produce small low cost
% thumbnail images suited for display on the Web.
%
% The format of the ThumbnailImage method is:
%
% Image *ThumbnailImage(const Image *image,const size_t columns,
% const size_t rows,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o columns: the number of columns in the scaled image.
%
% o rows: the number of rows in the scaled image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *ThumbnailImage(const Image *image,const size_t columns,
const size_t rows,ExceptionInfo *exception)
{
#define SampleFactor 5
char
*url,
value[MaxTextExtent];
const char
*name;
Image
*thumbnail_image;
MagickRealType
x_factor,
y_factor;
struct stat
attributes;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickCoreSignature);
x_factor=(MagickRealType) columns/(MagickRealType) image->columns;
y_factor=(MagickRealType) rows/(MagickRealType) image->rows;
if ((x_factor*y_factor) > 0.1)
thumbnail_image=ResizeImage(image,columns,rows,image->filter,image->blur,
exception);
else
if (((SampleFactor*columns) < 128) || ((SampleFactor*rows) < 128))
thumbnail_image=ResizeImage(image,columns,rows,image->filter,
image->blur,exception);
else
{
Image
*sample_image;
sample_image=SampleImage(image,SampleFactor*columns,SampleFactor*rows,
exception);
if (sample_image == (Image *) NULL)
return((Image *) NULL);
thumbnail_image=ResizeImage(sample_image,columns,rows,image->filter,
image->blur,exception);
sample_image=DestroyImage(sample_image);
}
if (thumbnail_image == (Image *) NULL)
return(thumbnail_image);
(void) ParseAbsoluteGeometry("0x0+0+0",&thumbnail_image->page);
if (thumbnail_image->matte == MagickFalse)
(void) SetImageAlphaChannel(thumbnail_image,OpaqueAlphaChannel);
thumbnail_image->depth=8;
thumbnail_image->interlace=NoInterlace;
/*
Strip all profiles except color profiles.
*/
ResetImageProfileIterator(thumbnail_image);
for (name=GetNextImageProfile(thumbnail_image); name != (const char *) NULL; )
{
if ((LocaleCompare(name,"icc") != 0) && (LocaleCompare(name,"icm") != 0))
{
(void) DeleteImageProfile(thumbnail_image,name);
ResetImageProfileIterator(thumbnail_image);
}
name=GetNextImageProfile(thumbnail_image);
}
(void) DeleteImageProperty(thumbnail_image,"comment");
(void) CopyMagickString(value,image->magick_filename,MaxTextExtent);
if (strstr(image->magick_filename,"//") == (char *) NULL)
(void) FormatLocaleString(value,MaxTextExtent,"file://%s",
image->magick_filename);
(void) SetImageProperty(thumbnail_image,"Thumb::URI",value);
(void) CopyMagickString(value,image->magick_filename,MaxTextExtent);
if (GetPathAttributes(image->filename,&attributes) != MagickFalse)
{
(void) FormatLocaleString(value,MaxTextExtent,"%.20g",(double)
attributes.st_mtime);
(void) SetImageProperty(thumbnail_image,"Thumb::MTime",value);
}
(void) FormatLocaleString(value,MaxTextExtent,"%.20g",(double)
attributes.st_mtime);
(void) FormatMagickSize(GetBlobSize(image),MagickFalse,value);
(void) ConcatenateMagickString(value,"B",MaxTextExtent);
(void) SetImageProperty(thumbnail_image,"Thumb::Size",value);
(void) FormatLocaleString(value,MaxTextExtent,"image/%s",image->magick);
LocaleLower(value);
(void) SetImageProperty(thumbnail_image,"Thumb::Mimetype",value);
url=GetMagickHomeURL();
(void) SetImageProperty(thumbnail_image,"software",url);
url=DestroyString(url);
(void) FormatLocaleString(value,MaxTextExtent,"%.20g",(double)
image->magick_columns);
(void) SetImageProperty(thumbnail_image,"Thumb::Image::Width",value);
(void) FormatLocaleString(value,MaxTextExtent,"%.20g",(double)
image->magick_rows);
(void) SetImageProperty(thumbnail_image,"Thumb::Image::Height",value);
(void) FormatLocaleString(value,MaxTextExtent,"%.20g",(double)
GetImageListLength(image));
(void) SetImageProperty(thumbnail_image,"Thumb::Document::Pages",value);
return(thumbnail_image);
}
|
GB_unop__identity_fc64_int32.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__identity_fc64_int32)
// op(A') function: GB (_unop_tran__identity_fc64_int32)
// C type: GxB_FC64_t
// A type: int32_t
// cast: GxB_FC64_t cij = GxB_CMPLX ((double) (aij), 0)
// unaryop: cij = aij
#define GB_ATYPE \
int32_t
#define GB_CTYPE \
GxB_FC64_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_CAST(z, aij) \
GxB_FC64_t z = GxB_CMPLX ((double) (aij), 0) ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
int32_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
GxB_FC64_t z = GxB_CMPLX ((double) (aij), 0) ; \
Cx [pC] = z ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_IDENTITY || GxB_NO_FC64 || GxB_NO_INT32)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_apply__identity_fc64_int32)
(
GxB_FC64_t *Cx, // Cx and Ax may be aliased
const int32_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++)
{
int32_t aij = Ax [p] ;
GxB_FC64_t z = GxB_CMPLX ((double) (aij), 0) ;
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 ;
int32_t aij = Ax [p] ;
GxB_FC64_t z = GxB_CMPLX ((double) (aij), 0) ;
Cx [p] = z ;
}
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_tran__identity_fc64_int32)
(
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
|
3d7pt.c | /*
* Order-1, 3D 7 point stencil
* 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, 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]);
double ****A = (double ****) malloc(sizeof(double***)*2);
A[0] = (double ***) malloc(sizeof(double**)*Nz);
A[1] = (double ***) malloc(sizeof(double**)*Nz);
for(i=0; i<Nz; i++){
A[0][i] = (double**) malloc(sizeof(double*)*Ny);
A[1][i] = (double**) malloc(sizeof(double*)*Ny);
for(j=0;j<Ny;j++){
A[0][i][j] = (double*) malloc(sizeof(double)*Nx);
A[1][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] = 16;
tile_size[1] = 16;
tile_size[2] = 16;
tile_size[3] = 128;
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;
const double alpha = 0.0876;
const double beta = 0.0765;
// 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);
}
}
}
#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
#pragma scop
for (t = 0; t < Nt-1; t++) {
for (i = 1; i < Nz-1; i++) {
for (j = 1; j < Ny-1; j++) {
for (k = 1; k < Nx-1; k++) {
A[(t+1)%2][i][j][k] = alpha * (A[t%2][i][j][k])
+ beta * (A[t%2][i - 1][j][k] + A[t%2][i][j - 1][k] + A[t%2][i][j][k - 1] +
A[t%2][i + 1][j][k] + A[t%2][i][j + 1][k] + A[t%2][i][j][k + 1]);
}
}
}
}
#pragma endscop
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, "constant")
#ifdef LIKWID_PERFMON
#pragma omp parallel
{
LIKWID_MARKER_STOP("calc");
}
LIKWID_MARKER_CLOSE;
#endif
// Free allocated arrays (Causing performance degradation
/* 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]);
*/
return 0;
}
|
GB_binop__max_int64.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__max_int64)
// A.*B function (eWiseMult): GB (_AemultB_08__max_int64)
// A.*B function (eWiseMult): GB (_AemultB_02__max_int64)
// A.*B function (eWiseMult): GB (_AemultB_04__max_int64)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__max_int64)
// A*D function (colscale): GB (_AxD__max_int64)
// D*A function (rowscale): GB (_DxB__max_int64)
// C+=B function (dense accum): GB (_Cdense_accumB__max_int64)
// C+=b function (dense accum): GB (_Cdense_accumb__max_int64)
// C+=A+B function (dense ewise3): GB (_Cdense_ewise3_accum__max_int64)
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__max_int64)
// C=scalar+B GB (_bind1st__max_int64)
// C=scalar+B' GB (_bind1st_tran__max_int64)
// C=A+scalar GB (_bind2nd__max_int64)
// C=A'+scalar GB (_bind2nd_tran__max_int64)
// C type: int64_t
// A type: int64_t
// A pattern? 0
// B type: int64_t
// B pattern? 0
// BinaryOp: cij = GB_IMAX (aij, bij)
#define GB_ATYPE \
int64_t
#define GB_BTYPE \
int64_t
#define GB_CTYPE \
int64_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) \
int64_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) \
int64_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) \
int64_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 = GB_IMAX (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_MAX || GxB_NO_INT64 || GxB_NO_MAX_INT64)
//------------------------------------------------------------------------------
// 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__max_int64)
(
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__max_int64)
(
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__max_int64)
(
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__max_int64)
(
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 int64_t
int64_t bwork = (*((int64_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__max_int64)
(
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
int64_t *restrict Cx = (int64_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__max_int64)
(
GrB_Matrix C,
const GrB_Matrix D,
const GrB_Matrix B,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t *restrict Cx = (int64_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__max_int64)
(
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) ;
int64_t alpha_scalar ;
int64_t beta_scalar ;
if (is_eWiseUnion)
{
alpha_scalar = (*((int64_t *) alpha_scalar_in)) ;
beta_scalar = (*((int64_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__max_int64)
(
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__max_int64)
(
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__max_int64)
(
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__max_int64)
(
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__max_int64)
(
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
int64_t *Cx = (int64_t *) Cx_output ;
int64_t x = (*((int64_t *) x_input)) ;
int64_t *Bx = (int64_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 ;
int64_t bij = GBX (Bx, p, false) ;
Cx [p] = GB_IMAX (x, bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__max_int64)
(
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 ;
int64_t *Cx = (int64_t *) Cx_output ;
int64_t *Ax = (int64_t *) Ax_input ;
int64_t y = (*((int64_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
int64_t aij = GBX (Ax, p, false) ;
Cx [p] = GB_IMAX (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) \
{ \
int64_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = GB_IMAX (x, aij) ; \
}
GrB_Info GB (_bind1st_tran__max_int64)
(
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 \
int64_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t x = (*((const int64_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
int64_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) \
{ \
int64_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = GB_IMAX (aij, y) ; \
}
GrB_Info GB (_bind2nd_tran__max_int64)
(
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
int64_t y = (*((const int64_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
schedule-clause.c | #include <stdio.h>
#include <stdlib.h>
#ifdef _OPENMP
#include <omp.h>
#else
#define omp_get_thread_num() 0
#endif
int main(int argc, char **argv) {
int i, n = 16,chunk, a[n],suma=0;
if(argc < 2) {
fprintf(stderr,"\nFalta chunk \n");
exit(-1);
}
chunk = atoi(argv[1]);
for (i=0; i<n; i++) a[i] = i;
#pragma omp parallel for firstprivate(suma) \
lastprivate(suma) schedule(static,chunk)
for (i=0; i<n; i++)
{
suma = suma + a[i];
printf(" thread %d suma a[%d] suma=%d \n",
omp_get_thread_num(),i,suma);
}
printf("Fuera de 'parallel for' suma=%d\n",suma);
}
|
mandelbrot_gcc4.c |
/*
gcc -pipe -Wall -O3 -fomit-frame-pointer -march=native -std=c99 -D_GNU_SOURCE -mfpmath=sse -msse2 -fopenmp mandelbrot.gcc-4.c -o mandelbrot.gcc-4.gcc_run
*/
/* The Computer Language Benchmarks Game
* http://benchmarksgame.alioth.debian.org/
contributed by Paolo Bonzini
further optimized by Jason Garrett-Glaser
pthreads added by Eckehard Berns
further optimized by Ryan Henszey
modified by Samy Al Bahra (use GCC atomic builtins)
modified by Kenneth Jonsson
*/
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
typedef
double v2df __attribute__ ((vector_size(16))); /* vector of two doubles */
#if(0)
typedef int v4si __attribute__ ((vector_size(16))); /* vector of four ints */
#endif
const v2df zero = { 0.0, 0.0 };
const v2df four = { 4.0, 4.0 };
/*
* Constant throughout the program, value depends on N
*/
int bytes_per_row;
double inverse_w;
double inverse_h;
/*
* Program argument: height and width of the image
*/
int N;
/*
* Lookup table for initial real-axis value
*/
v2df *Crvs;
/*
* Mandelbrot bitmap
*/
uint8_t *bitmap;
static void calc_row(int y) {
uint8_t *row_bitmap = bitmap + (bytes_per_row * y);
int x;
const v2df Civ_init = { y*inverse_h-1.0, y*inverse_h-1.0 };
for (x=0; x<N; x+=2)
{
v2df Crv = Crvs[x >> 1];
v2df Civ = Civ_init;
v2df Zrv = zero;
v2df Ziv = zero;
v2df Trv = zero;
v2df Tiv = zero;
int i = 50;
int two_pixels;
v2df is_still_bounded;
do {
Ziv = (Zrv*Ziv) + (Zrv*Ziv) + Civ;
Zrv = Trv - Tiv + Crv;
Trv = Zrv * Zrv;
Tiv = Ziv * Ziv;
/*
* All bits will be set to 1 if 'Trv + Tiv' is less than 4
* and all bits will be set to 0 otherwise. Two elements
* are calculated in parallel here.
*/
is_still_bounded = __builtin_ia32_cmplepd(Trv + Tiv, four);
/*
* Move the sign-bit of the low element to bit 0, move the
* sign-bit of the high element to bit 1. The result is
* that the pixel will be set if the calculation was
* bounded.
*/
two_pixels = __builtin_ia32_movmskpd(is_still_bounded);
} while (--i > 0 && two_pixels);
/*
* The pixel bits must be in the most and second most
* significant position
*/
two_pixels <<= 6;
/*
* Add the two pixels to the bitmap, all bits are
* initially zero since the area was allocated with
* calloc()
*/
row_bitmap[x >> 3] |= (uint8_t) (two_pixels >> (x & 7));
}
}
int main (int argc, char **argv)
{
int i;
N = atoi(argv[1]);
bytes_per_row = (N + 7) >> 3;
inverse_w = 2.0 / (bytes_per_row << 3);
inverse_h = 2.0 / N;
/*
* Crvs must be 16-bytes aligned on some CPU:s.
*/
if (posix_memalign((void**)&Crvs, sizeof(v2df), sizeof(v2df) * N / 2))
return EXIT_FAILURE;
#pragma omp parallel for
for (i = 0; i < N; i+=2) {
v2df Crv = { (i+1.0)*inverse_w-1.5, (i)*inverse_w-1.5 };
Crvs[i >> 1] = Crv;
}
bitmap = calloc(bytes_per_row, N);
if (bitmap == NULL)
return EXIT_FAILURE;
#pragma omp parallel for schedule(static,1)
for (i = 0; i < N; i++)
calc_row(i);
printf("P4\n%d %d\n", N, N);
fwrite(bitmap, bytes_per_row, N, stdout);
free(bitmap);
free(Crvs);
return EXIT_SUCCESS;
}
/* ****** ****** */
/* end of [mandelbrot_gcc4.c] */
|
GB_binop__minus_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__minus_uint16)
// A.*B function (eWiseMult): GB (_AemultB_08__minus_uint16)
// A.*B function (eWiseMult): GB (_AemultB_02__minus_uint16)
// A.*B function (eWiseMult): GB (_AemultB_04__minus_uint16)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__minus_uint16)
// A*D function (colscale): GB (_AxD__minus_uint16)
// D*A function (rowscale): GB (_DxB__minus_uint16)
// C+=B function (dense accum): GB (_Cdense_accumB__minus_uint16)
// C+=b function (dense accum): GB (_Cdense_accumb__minus_uint16)
// C+=A+B function (dense ewise3): GB (_Cdense_ewise3_accum__minus_uint16)
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__minus_uint16)
// C=scalar+B GB (_bind1st__minus_uint16)
// C=scalar+B' GB (_bind1st_tran__minus_uint16)
// C=A+scalar GB (_bind2nd__minus_uint16)
// C=A'+scalar GB (_bind2nd_tran__minus_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_MINUS || GxB_NO_UINT16 || GxB_NO_MINUS_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__minus_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__minus_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__minus_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__minus_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__minus_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__minus_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__minus_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__minus_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__minus_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__minus_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__minus_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__minus_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__minus_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__minus_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__minus_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
|
inputJacobi.c | #include <stdio.h>
#include <math.h>
#ifdef _OPENMP
#include "omp.h"
#endif
void driver (void);
void initialize (void);
void jacobi (void);
void error_check (void);
/************************************************************
* program to solve a finite difference
* discretization of Helmholtz equation :
* (d2/dx2)u + (d2/dy2)u - alpha u = f
* using Jacobi iterative method.
*
* Modified: Sanjiv Shah, Kuck and Associates, Inc. (KAI), 1998
* Author: Joseph Robicheaux, Kuck and Associates, Inc. (KAI), 1998
* This c version program is translated by
* Chunhua Liao, University of Houston, Jan, 2005
*
* Directives are used in this code to achieve paralleism.
* All do loops are parallized with default 'static' scheduling.
*
* Input : n - grid dimension in x direction
* m - grid dimension in y direction
* alpha - Helmholtz constant (always greater than 0.0)
* tol - error tolerance for iterative solver
* relax - Successice over relaxation parameter
* mits - Maximum iterations for iterative solver
*
* On output
* : u(n,m) - Dependent variable (solutions)
* : f(n,m) - Right hand side function
*************************************************************/
#define MSIZE 500
int n, m, mits;
double tol, relax = 1.0, alpha = 0.0543;
double u[MSIZE][MSIZE], f[MSIZE][MSIZE], uold[MSIZE][MSIZE];
double dx, dy;
int
main (void)
{
/*
float toler;
printf("Input n,m (< %d) - grid dimension in x,y direction:\n",MSIZE);
scanf ("%d",&n);
scanf ("%d",&m);
printf("Input tol - error tolerance for iterative solver\n");
scanf("%f",&toler);
tol=(double)toler;
printf("Input mits - Maximum iterations for solver\n");
scanf("%d",&mits);
*/
n = MSIZE;
m = MSIZE;
tol = 0.0000000001;
mits = 5000;
#pragma omp parallel
{
#pragma omp single
printf ("Running using %d threads...\n", omp_get_num_threads ());
}
driver ();
printf ("------------------------\n");
printf ("Correct output should be:\n");
printf ("Total Number of Iterations:5001\n");
printf ("Residual:2.512265E-08\n");
printf ("Solution Error :9.378232E-04\n");
return 0;
}
/*************************************************************
* Subroutine driver ()
* This is where the arrays are allocated and initialzed.
*
* Working varaibles/arrays
* dx - grid spacing in x direction
* dy - grid spacing in y direction
*************************************************************/
void
driver ()
{
initialize ();
/* Solve Helmholtz equation */
jacobi ();
/* error_check (n,m,alpha,dx,dy,u,f) */
error_check ();
}
/* subroutine initialize (n,m,alpha,dx,dy,u,f)
******************************************************
* Initializes data
* Assumes exact solution is u(x,y) = (1-x^2)*(1-y^2)
*
******************************************************/
void
initialize ()
{
int i, j, xx, yy;
//double PI=3.1415926;
dx = 2.0 / (n - 1);
dy = 2.0 / (m - 1);
/* Initilize initial condition and RHS */
#pragma omp parallel for private(xx,yy,j)
for (i = 0; i < n; i++)
for (j = 0; j < m; j++)
{
xx = (int) (-1.0 + dx * (i - 1)); /* -1 < x < 1 */
yy = (int) (-1.0 + dy * (j - 1)); /* -1 < y < 1 */
u[i][j] = 0.0;
f[i][j] = -1.0 * alpha * (1.0 - xx * xx) * (1.0 - yy * yy)
- 2.0 * (1.0 - xx * xx) - 2.0 * (1.0 - yy * yy);
}
}
/* subroutine jacobi (n,m,dx,dy,alpha,omega,u,f,tol,maxit)
******************************************************************
* Subroutine HelmholtzJ
* Solves poisson equation on rectangular grid assuming :
* (1) Uniform discretization in each direction, and
* (2) Dirichlect boundary conditions
*
* Jacobi method is used in this routine
*
* Input : n,m Number of grid points in the X/Y directions
* dx,dy Grid spacing in the X/Y directions
* alpha Helmholtz eqn. coefficient
* omega Relaxation factor
* f(n,m) Right hand side function
* u(n,m) Dependent variable/Solution
* tol Tolerance for iterative solver
* maxit Maximum number of iterations
*
* Output : u(n,m) - Solution
*****************************************************************/
void
jacobi ()
{
double omega;
int i, j, k;
double error, resid, ax, ay, b;
// double error_local;
// float ta,tb,tc,td,te,ta1,ta2,tb1,tb2,tc1,tc2,td1,td2;
// float te1,te2;
// float second;
omega = relax;
/*
* Initialize coefficients */
ax = 1.0 / (dx * dx); /* X-direction coef */
ay = 1.0 / (dy * dy); /* Y-direction coef */
b = -2.0 / (dx * dx) - 2.0 / (dy * dy) - alpha; /* Central coeff */
error = 10.0 * tol;
k = 1;
while ((k <= mits) && (error > tol))
{
error = 0.0;
/* Copy new solution into old */
#pragma omp parallel
{
#pragma omp for private(j)
for (i = 0; i < n; i++)
for (j = 0; j < m; j++)
uold[i][j] = u[i][j];
#pragma omp for private(resid,j) reduction(+:error) nowait
for (i = 1; i < (n - 1); i++)
for (j = 1; j < (m - 1); j++)
{
resid = (ax * (uold[i - 1][j] + uold[i + 1][j])
+ ay * (uold[i][j - 1] + uold[i][j + 1]) +
b * uold[i][j] - f[i][j]) / b;
u[i][j] = uold[i][j] - omega * resid;
error = error + resid * resid;
}
}
/* omp end parallel */
/* Error check */
k = k + 1;
if (k % 500 == 0)
printf ("Finished %d iteration.\n", k);
error = sqrt (error) / (n * m);
} /* End iteration loop */
printf ("Total Number of Iterations:%d\n", k);
printf ("Residual:%E\n", error);
}
/* subroutine error_check (n,m,alpha,dx,dy,u,f)
implicit none
************************************************************
* Checks error between numerical and exact solution
*
************************************************************/
void
error_check ()
{
int i, j;
double xx, yy, temp, error;
dx = 2.0 / (n - 1);
dy = 2.0 / (m - 1);
error = 0.0;
#pragma omp parallel for private(xx,yy,temp,j) reduction(+:error)
for (i = 0; i < n; i++)
for (j = 0; j < m; j++)
{
xx = -1.0 + dx * (i - 1);
yy = -1.0 + dy * (j - 1);
temp = u[i][j] - (1.0 - xx * xx) * (1.0 - yy * yy);
error = error + temp * temp;
}
error = sqrt (error) / (n * m);
printf ("Solution Error :%E \n", error);
}
|
convolution_7x7_pack1to4.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 conv7x7s2_pack1to4_msa(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, const Mat& _bias, const Option& opt)
{
int w = bottom_blob.w;
int inch = bottom_blob.c;
int outw = top_blob.w;
int outh = top_blob.h;
int outch = top_blob.c;
const int tailstep = w - 2 * outw + w;
const float* bias = _bias;
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < outch; p++)
{
Mat out0 = top_blob.channel(p);
v4f32 _bias0 = bias ? (v4f32)__msa_ld_w(bias + p * 4, 0) : (v4f32)__msa_fill_w(0);
out0.fill(_bias0);
for (int q = 0; q < inch; q++)
{
float* outptr0 = out0;
const Mat img0 = bottom_blob.channel(q);
const float* r0 = img0.row(0);
const float* r1 = img0.row(1);
const float* r2 = img0.row(2);
const float* r3 = img0.row(3);
const float* r4 = img0.row(4);
const float* r5 = img0.row(5);
const float* r6 = img0.row(6);
const float* kptr = kernel.channel(p).row(q);
int i = 0;
for (; i < outh; i++)
{
int j = 0;
for (; j + 3 < outw; j += 4)
{
v4f32 _sum0 = (v4f32)__msa_ld_w(outptr0, 0);
v4f32 _sum1 = (v4f32)__msa_ld_w(outptr0 + 4, 0);
v4f32 _sum2 = (v4f32)__msa_ld_w(outptr0 + 4 * 2, 0);
v4f32 _sum3 = (v4f32)__msa_ld_w(outptr0 + 4 * 3, 0);
v4f32 _k00 = (v4f32)__msa_ld_w(kptr, 0);
v4f32 _k01 = (v4f32)__msa_ld_w(kptr + 4, 0);
v4f32 _k02 = (v4f32)__msa_ld_w(kptr + 4 * 2, 0);
v4f32 _k03 = (v4f32)__msa_ld_w(kptr + 4 * 3, 0);
v4f32 _k04 = (v4f32)__msa_ld_w(kptr + 4 * 4, 0);
v4f32 _k05 = (v4f32)__msa_ld_w(kptr + 4 * 5, 0);
v4f32 _k06 = (v4f32)__msa_ld_w(kptr + 4 * 6, 0);
kptr += 4 * 7;
v4i32 _r0 = __msa_ld_w(r0, 0);
v4i32 _r0n = __msa_ld_w(r0 + 4, 0);
v4i32 _r0nn = __msa_ld_w(r0 + 8, 0);
v4f32 _r00 = (v4f32)__msa_splati_w(_r0, 0);
v4f32 _r01 = (v4f32)__msa_splati_w(_r0, 1);
v4f32 _r02 = (v4f32)__msa_splati_w(_r0, 2);
v4f32 _r03 = (v4f32)__msa_splati_w(_r0, 3);
v4f32 _r04 = (v4f32)__msa_splati_w(_r0n, 0);
v4f32 _r05 = (v4f32)__msa_splati_w(_r0n, 1);
v4f32 _r06 = (v4f32)__msa_splati_w(_r0n, 2);
v4f32 _r07 = (v4f32)__msa_splati_w(_r0n, 3);
v4f32 _r08 = (v4f32)__msa_splati_w(_r0nn, 0);
v4f32 _r09 = (v4f32)__msa_splati_w(_r0nn, 1);
v4f32 _r0a = (v4f32)__msa_splati_w(_r0nn, 2);
v4f32 _r0b = (v4f32)__msa_splati_w(_r0nn, 3);
v4f32 _r0c = __msa_fill_w_f32(r0[12]);
_sum0 = __msa_fmadd_w(_sum0, _r00, _k00);
_sum1 = __msa_fmadd_w(_sum1, _r02, _k00);
_sum2 = __msa_fmadd_w(_sum2, _r04, _k00);
_sum3 = __msa_fmadd_w(_sum3, _r06, _k00);
_sum0 = __msa_fmadd_w(_sum0, _r01, _k01);
_sum1 = __msa_fmadd_w(_sum1, _r03, _k01);
_sum2 = __msa_fmadd_w(_sum2, _r05, _k01);
_sum3 = __msa_fmadd_w(_sum3, _r07, _k01);
_sum0 = __msa_fmadd_w(_sum0, _r02, _k02);
_sum1 = __msa_fmadd_w(_sum1, _r04, _k02);
_sum2 = __msa_fmadd_w(_sum2, _r06, _k02);
_sum3 = __msa_fmadd_w(_sum3, _r08, _k02);
_sum0 = __msa_fmadd_w(_sum0, _r03, _k03);
_sum1 = __msa_fmadd_w(_sum1, _r05, _k03);
_sum2 = __msa_fmadd_w(_sum2, _r07, _k03);
_sum3 = __msa_fmadd_w(_sum3, _r09, _k03);
_sum0 = __msa_fmadd_w(_sum0, _r04, _k04);
_sum1 = __msa_fmadd_w(_sum1, _r06, _k04);
_sum2 = __msa_fmadd_w(_sum2, _r08, _k04);
_sum3 = __msa_fmadd_w(_sum3, _r0a, _k04);
_sum0 = __msa_fmadd_w(_sum0, _r05, _k05);
_sum1 = __msa_fmadd_w(_sum1, _r07, _k05);
_sum2 = __msa_fmadd_w(_sum2, _r09, _k05);
_sum3 = __msa_fmadd_w(_sum3, _r0b, _k05);
_sum0 = __msa_fmadd_w(_sum0, _r06, _k06);
_sum1 = __msa_fmadd_w(_sum1, _r08, _k06);
_sum2 = __msa_fmadd_w(_sum2, _r0a, _k06);
_sum3 = __msa_fmadd_w(_sum3, _r0c, _k06);
v4f32 _k10 = (v4f32)__msa_ld_w(kptr, 0);
v4f32 _k11 = (v4f32)__msa_ld_w(kptr + 4, 0);
v4f32 _k12 = (v4f32)__msa_ld_w(kptr + 4 * 2, 0);
v4f32 _k13 = (v4f32)__msa_ld_w(kptr + 4 * 3, 0);
v4f32 _k14 = (v4f32)__msa_ld_w(kptr + 4 * 4, 0);
v4f32 _k15 = (v4f32)__msa_ld_w(kptr + 4 * 5, 0);
v4f32 _k16 = (v4f32)__msa_ld_w(kptr + 4 * 6, 0);
kptr += 4 * 7;
v4i32 _r1 = __msa_ld_w(r1, 0);
v4i32 _r1n = __msa_ld_w(r1 + 4, 0);
v4i32 _r1nn = __msa_ld_w(r1 + 8, 0);
v4f32 _r10 = (v4f32)__msa_splati_w(_r1, 0);
v4f32 _r11 = (v4f32)__msa_splati_w(_r1, 1);
v4f32 _r12 = (v4f32)__msa_splati_w(_r1, 2);
v4f32 _r13 = (v4f32)__msa_splati_w(_r1, 3);
v4f32 _r14 = (v4f32)__msa_splati_w(_r1n, 0);
v4f32 _r15 = (v4f32)__msa_splati_w(_r1n, 1);
v4f32 _r16 = (v4f32)__msa_splati_w(_r1n, 2);
v4f32 _r17 = (v4f32)__msa_splati_w(_r1n, 3);
v4f32 _r18 = (v4f32)__msa_splati_w(_r1nn, 0);
v4f32 _r19 = (v4f32)__msa_splati_w(_r1nn, 1);
v4f32 _r1a = (v4f32)__msa_splati_w(_r1nn, 2);
v4f32 _r1b = (v4f32)__msa_splati_w(_r1nn, 3);
v4f32 _r1c = __msa_fill_w_f32(r1[12]);
_sum0 = __msa_fmadd_w(_sum0, _r10, _k10);
_sum1 = __msa_fmadd_w(_sum1, _r12, _k10);
_sum2 = __msa_fmadd_w(_sum2, _r14, _k10);
_sum3 = __msa_fmadd_w(_sum3, _r16, _k10);
_sum0 = __msa_fmadd_w(_sum0, _r11, _k11);
_sum1 = __msa_fmadd_w(_sum1, _r13, _k11);
_sum2 = __msa_fmadd_w(_sum2, _r15, _k11);
_sum3 = __msa_fmadd_w(_sum3, _r17, _k11);
_sum0 = __msa_fmadd_w(_sum0, _r12, _k12);
_sum1 = __msa_fmadd_w(_sum1, _r14, _k12);
_sum2 = __msa_fmadd_w(_sum2, _r16, _k12);
_sum3 = __msa_fmadd_w(_sum3, _r18, _k12);
_sum0 = __msa_fmadd_w(_sum0, _r13, _k13);
_sum1 = __msa_fmadd_w(_sum1, _r15, _k13);
_sum2 = __msa_fmadd_w(_sum2, _r17, _k13);
_sum3 = __msa_fmadd_w(_sum3, _r19, _k13);
_sum0 = __msa_fmadd_w(_sum0, _r14, _k14);
_sum1 = __msa_fmadd_w(_sum1, _r16, _k14);
_sum2 = __msa_fmadd_w(_sum2, _r18, _k14);
_sum3 = __msa_fmadd_w(_sum3, _r1a, _k14);
_sum0 = __msa_fmadd_w(_sum0, _r15, _k15);
_sum1 = __msa_fmadd_w(_sum1, _r17, _k15);
_sum2 = __msa_fmadd_w(_sum2, _r19, _k15);
_sum3 = __msa_fmadd_w(_sum3, _r1b, _k15);
_sum0 = __msa_fmadd_w(_sum0, _r16, _k16);
_sum1 = __msa_fmadd_w(_sum1, _r18, _k16);
_sum2 = __msa_fmadd_w(_sum2, _r1a, _k16);
_sum3 = __msa_fmadd_w(_sum3, _r1c, _k16);
v4f32 _k20 = (v4f32)__msa_ld_w(kptr, 0);
v4f32 _k21 = (v4f32)__msa_ld_w(kptr + 4, 0);
v4f32 _k22 = (v4f32)__msa_ld_w(kptr + 4 * 2, 0);
v4f32 _k23 = (v4f32)__msa_ld_w(kptr + 4 * 3, 0);
v4f32 _k24 = (v4f32)__msa_ld_w(kptr + 4 * 4, 0);
v4f32 _k25 = (v4f32)__msa_ld_w(kptr + 4 * 5, 0);
v4f32 _k26 = (v4f32)__msa_ld_w(kptr + 4 * 6, 0);
kptr += 4 * 7;
v4i32 _r2 = __msa_ld_w(r2, 0);
v4i32 _r2n = __msa_ld_w(r2 + 4, 0);
v4i32 _r2nn = __msa_ld_w(r2 + 8, 0);
v4f32 _r20 = (v4f32)__msa_splati_w(_r2, 0);
v4f32 _r21 = (v4f32)__msa_splati_w(_r2, 1);
v4f32 _r22 = (v4f32)__msa_splati_w(_r2, 2);
v4f32 _r23 = (v4f32)__msa_splati_w(_r2, 3);
v4f32 _r24 = (v4f32)__msa_splati_w(_r2n, 0);
v4f32 _r25 = (v4f32)__msa_splati_w(_r2n, 1);
v4f32 _r26 = (v4f32)__msa_splati_w(_r2n, 2);
v4f32 _r27 = (v4f32)__msa_splati_w(_r2n, 3);
v4f32 _r28 = (v4f32)__msa_splati_w(_r2nn, 0);
v4f32 _r29 = (v4f32)__msa_splati_w(_r2nn, 1);
v4f32 _r2a = (v4f32)__msa_splati_w(_r2nn, 2);
v4f32 _r2b = (v4f32)__msa_splati_w(_r2nn, 3);
v4f32 _r2c = __msa_fill_w_f32(r2[12]);
_sum0 = __msa_fmadd_w(_sum0, _r20, _k20);
_sum1 = __msa_fmadd_w(_sum1, _r22, _k20);
_sum2 = __msa_fmadd_w(_sum2, _r24, _k20);
_sum3 = __msa_fmadd_w(_sum3, _r26, _k20);
_sum0 = __msa_fmadd_w(_sum0, _r21, _k21);
_sum1 = __msa_fmadd_w(_sum1, _r23, _k21);
_sum2 = __msa_fmadd_w(_sum2, _r25, _k21);
_sum3 = __msa_fmadd_w(_sum3, _r27, _k21);
_sum0 = __msa_fmadd_w(_sum0, _r22, _k22);
_sum1 = __msa_fmadd_w(_sum1, _r24, _k22);
_sum2 = __msa_fmadd_w(_sum2, _r26, _k22);
_sum3 = __msa_fmadd_w(_sum3, _r28, _k22);
_sum0 = __msa_fmadd_w(_sum0, _r23, _k23);
_sum1 = __msa_fmadd_w(_sum1, _r25, _k23);
_sum2 = __msa_fmadd_w(_sum2, _r27, _k23);
_sum3 = __msa_fmadd_w(_sum3, _r29, _k23);
_sum0 = __msa_fmadd_w(_sum0, _r24, _k24);
_sum1 = __msa_fmadd_w(_sum1, _r26, _k24);
_sum2 = __msa_fmadd_w(_sum2, _r28, _k24);
_sum3 = __msa_fmadd_w(_sum3, _r2a, _k24);
_sum0 = __msa_fmadd_w(_sum0, _r25, _k25);
_sum1 = __msa_fmadd_w(_sum1, _r27, _k25);
_sum2 = __msa_fmadd_w(_sum2, _r29, _k25);
_sum3 = __msa_fmadd_w(_sum3, _r2b, _k25);
_sum0 = __msa_fmadd_w(_sum0, _r26, _k26);
_sum1 = __msa_fmadd_w(_sum1, _r28, _k26);
_sum2 = __msa_fmadd_w(_sum2, _r2a, _k26);
_sum3 = __msa_fmadd_w(_sum3, _r2c, _k26);
v4f32 _k30 = (v4f32)__msa_ld_w(kptr, 0);
v4f32 _k31 = (v4f32)__msa_ld_w(kptr + 4, 0);
v4f32 _k32 = (v4f32)__msa_ld_w(kptr + 4 * 2, 0);
v4f32 _k33 = (v4f32)__msa_ld_w(kptr + 4 * 3, 0);
v4f32 _k34 = (v4f32)__msa_ld_w(kptr + 4 * 4, 0);
v4f32 _k35 = (v4f32)__msa_ld_w(kptr + 4 * 5, 0);
v4f32 _k36 = (v4f32)__msa_ld_w(kptr + 4 * 6, 0);
kptr += 4 * 7;
v4i32 _r3 = __msa_ld_w(r3, 0);
v4i32 _r3n = __msa_ld_w(r3 + 4, 0);
v4i32 _r3nn = __msa_ld_w(r3 + 8, 0);
v4f32 _r30 = (v4f32)__msa_splati_w(_r3, 0);
v4f32 _r31 = (v4f32)__msa_splati_w(_r3, 1);
v4f32 _r32 = (v4f32)__msa_splati_w(_r3, 2);
v4f32 _r33 = (v4f32)__msa_splati_w(_r3, 3);
v4f32 _r34 = (v4f32)__msa_splati_w(_r3n, 0);
v4f32 _r35 = (v4f32)__msa_splati_w(_r3n, 1);
v4f32 _r36 = (v4f32)__msa_splati_w(_r3n, 2);
v4f32 _r37 = (v4f32)__msa_splati_w(_r3n, 3);
v4f32 _r38 = (v4f32)__msa_splati_w(_r3nn, 0);
v4f32 _r39 = (v4f32)__msa_splati_w(_r3nn, 1);
v4f32 _r3a = (v4f32)__msa_splati_w(_r3nn, 2);
v4f32 _r3b = (v4f32)__msa_splati_w(_r3nn, 3);
v4f32 _r3c = __msa_fill_w_f32(r3[12]);
_sum0 = __msa_fmadd_w(_sum0, _r30, _k30);
_sum1 = __msa_fmadd_w(_sum1, _r32, _k30);
_sum2 = __msa_fmadd_w(_sum2, _r34, _k30);
_sum3 = __msa_fmadd_w(_sum3, _r36, _k30);
_sum0 = __msa_fmadd_w(_sum0, _r31, _k31);
_sum1 = __msa_fmadd_w(_sum1, _r33, _k31);
_sum2 = __msa_fmadd_w(_sum2, _r35, _k31);
_sum3 = __msa_fmadd_w(_sum3, _r37, _k31);
_sum0 = __msa_fmadd_w(_sum0, _r32, _k32);
_sum1 = __msa_fmadd_w(_sum1, _r34, _k32);
_sum2 = __msa_fmadd_w(_sum2, _r36, _k32);
_sum3 = __msa_fmadd_w(_sum3, _r38, _k32);
_sum0 = __msa_fmadd_w(_sum0, _r33, _k33);
_sum1 = __msa_fmadd_w(_sum1, _r35, _k33);
_sum2 = __msa_fmadd_w(_sum2, _r37, _k33);
_sum3 = __msa_fmadd_w(_sum3, _r39, _k33);
_sum0 = __msa_fmadd_w(_sum0, _r34, _k34);
_sum1 = __msa_fmadd_w(_sum1, _r36, _k34);
_sum2 = __msa_fmadd_w(_sum2, _r38, _k34);
_sum3 = __msa_fmadd_w(_sum3, _r3a, _k34);
_sum0 = __msa_fmadd_w(_sum0, _r35, _k35);
_sum1 = __msa_fmadd_w(_sum1, _r37, _k35);
_sum2 = __msa_fmadd_w(_sum2, _r39, _k35);
_sum3 = __msa_fmadd_w(_sum3, _r3b, _k35);
_sum0 = __msa_fmadd_w(_sum0, _r36, _k36);
_sum1 = __msa_fmadd_w(_sum1, _r38, _k36);
_sum2 = __msa_fmadd_w(_sum2, _r3a, _k36);
_sum3 = __msa_fmadd_w(_sum3, _r3c, _k36);
v4f32 _k40 = (v4f32)__msa_ld_w(kptr, 0);
v4f32 _k41 = (v4f32)__msa_ld_w(kptr + 4, 0);
v4f32 _k42 = (v4f32)__msa_ld_w(kptr + 4 * 2, 0);
v4f32 _k43 = (v4f32)__msa_ld_w(kptr + 4 * 3, 0);
v4f32 _k44 = (v4f32)__msa_ld_w(kptr + 4 * 4, 0);
v4f32 _k45 = (v4f32)__msa_ld_w(kptr + 4 * 5, 0);
v4f32 _k46 = (v4f32)__msa_ld_w(kptr + 4 * 6, 0);
kptr += 4 * 7;
v4i32 _r4 = __msa_ld_w(r4, 0);
v4i32 _r4n = __msa_ld_w(r4 + 4, 0);
v4i32 _r4nn = __msa_ld_w(r4 + 8, 0);
v4f32 _r40 = (v4f32)__msa_splati_w(_r4, 0);
v4f32 _r41 = (v4f32)__msa_splati_w(_r4, 1);
v4f32 _r42 = (v4f32)__msa_splati_w(_r4, 2);
v4f32 _r43 = (v4f32)__msa_splati_w(_r4, 3);
v4f32 _r44 = (v4f32)__msa_splati_w(_r4n, 0);
v4f32 _r45 = (v4f32)__msa_splati_w(_r4n, 1);
v4f32 _r46 = (v4f32)__msa_splati_w(_r4n, 2);
v4f32 _r47 = (v4f32)__msa_splati_w(_r4n, 3);
v4f32 _r48 = (v4f32)__msa_splati_w(_r4nn, 0);
v4f32 _r49 = (v4f32)__msa_splati_w(_r4nn, 1);
v4f32 _r4a = (v4f32)__msa_splati_w(_r4nn, 2);
v4f32 _r4b = (v4f32)__msa_splati_w(_r4nn, 3);
v4f32 _r4c = __msa_fill_w_f32(r4[12]);
_sum0 = __msa_fmadd_w(_sum0, _r40, _k40);
_sum1 = __msa_fmadd_w(_sum1, _r42, _k40);
_sum2 = __msa_fmadd_w(_sum2, _r44, _k40);
_sum3 = __msa_fmadd_w(_sum3, _r46, _k40);
_sum0 = __msa_fmadd_w(_sum0, _r41, _k41);
_sum1 = __msa_fmadd_w(_sum1, _r43, _k41);
_sum2 = __msa_fmadd_w(_sum2, _r45, _k41);
_sum3 = __msa_fmadd_w(_sum3, _r47, _k41);
_sum0 = __msa_fmadd_w(_sum0, _r42, _k42);
_sum1 = __msa_fmadd_w(_sum1, _r44, _k42);
_sum2 = __msa_fmadd_w(_sum2, _r46, _k42);
_sum3 = __msa_fmadd_w(_sum3, _r48, _k42);
_sum0 = __msa_fmadd_w(_sum0, _r43, _k43);
_sum1 = __msa_fmadd_w(_sum1, _r45, _k43);
_sum2 = __msa_fmadd_w(_sum2, _r47, _k43);
_sum3 = __msa_fmadd_w(_sum3, _r49, _k43);
_sum0 = __msa_fmadd_w(_sum0, _r44, _k44);
_sum1 = __msa_fmadd_w(_sum1, _r46, _k44);
_sum2 = __msa_fmadd_w(_sum2, _r48, _k44);
_sum3 = __msa_fmadd_w(_sum3, _r4a, _k44);
_sum0 = __msa_fmadd_w(_sum0, _r45, _k45);
_sum1 = __msa_fmadd_w(_sum1, _r47, _k45);
_sum2 = __msa_fmadd_w(_sum2, _r49, _k45);
_sum3 = __msa_fmadd_w(_sum3, _r4b, _k45);
_sum0 = __msa_fmadd_w(_sum0, _r46, _k46);
_sum1 = __msa_fmadd_w(_sum1, _r48, _k46);
_sum2 = __msa_fmadd_w(_sum2, _r4a, _k46);
_sum3 = __msa_fmadd_w(_sum3, _r4c, _k46);
v4f32 _k50 = (v4f32)__msa_ld_w(kptr, 0);
v4f32 _k51 = (v4f32)__msa_ld_w(kptr + 4, 0);
v4f32 _k52 = (v4f32)__msa_ld_w(kptr + 4 * 2, 0);
v4f32 _k53 = (v4f32)__msa_ld_w(kptr + 4 * 3, 0);
v4f32 _k54 = (v4f32)__msa_ld_w(kptr + 4 * 4, 0);
v4f32 _k55 = (v4f32)__msa_ld_w(kptr + 4 * 5, 0);
v4f32 _k56 = (v4f32)__msa_ld_w(kptr + 4 * 6, 0);
kptr += 4 * 7;
v4i32 _r5 = __msa_ld_w(r5, 0);
v4i32 _r5n = __msa_ld_w(r5 + 4, 0);
v4i32 _r5nn = __msa_ld_w(r5 + 8, 0);
v4f32 _r50 = (v4f32)__msa_splati_w(_r5, 0);
v4f32 _r51 = (v4f32)__msa_splati_w(_r5, 1);
v4f32 _r52 = (v4f32)__msa_splati_w(_r5, 2);
v4f32 _r53 = (v4f32)__msa_splati_w(_r5, 3);
v4f32 _r54 = (v4f32)__msa_splati_w(_r5n, 0);
v4f32 _r55 = (v4f32)__msa_splati_w(_r5n, 1);
v4f32 _r56 = (v4f32)__msa_splati_w(_r5n, 2);
v4f32 _r57 = (v4f32)__msa_splati_w(_r5n, 3);
v4f32 _r58 = (v4f32)__msa_splati_w(_r5nn, 0);
v4f32 _r59 = (v4f32)__msa_splati_w(_r5nn, 1);
v4f32 _r5a = (v4f32)__msa_splati_w(_r5nn, 2);
v4f32 _r5b = (v4f32)__msa_splati_w(_r5nn, 3);
v4f32 _r5c = __msa_fill_w_f32(r5[12]);
_sum0 = __msa_fmadd_w(_sum0, _r50, _k50);
_sum1 = __msa_fmadd_w(_sum1, _r52, _k50);
_sum2 = __msa_fmadd_w(_sum2, _r54, _k50);
_sum3 = __msa_fmadd_w(_sum3, _r56, _k50);
_sum0 = __msa_fmadd_w(_sum0, _r51, _k51);
_sum1 = __msa_fmadd_w(_sum1, _r53, _k51);
_sum2 = __msa_fmadd_w(_sum2, _r55, _k51);
_sum3 = __msa_fmadd_w(_sum3, _r57, _k51);
_sum0 = __msa_fmadd_w(_sum0, _r52, _k52);
_sum1 = __msa_fmadd_w(_sum1, _r54, _k52);
_sum2 = __msa_fmadd_w(_sum2, _r56, _k52);
_sum3 = __msa_fmadd_w(_sum3, _r58, _k52);
_sum0 = __msa_fmadd_w(_sum0, _r53, _k53);
_sum1 = __msa_fmadd_w(_sum1, _r55, _k53);
_sum2 = __msa_fmadd_w(_sum2, _r57, _k53);
_sum3 = __msa_fmadd_w(_sum3, _r59, _k53);
_sum0 = __msa_fmadd_w(_sum0, _r54, _k54);
_sum1 = __msa_fmadd_w(_sum1, _r56, _k54);
_sum2 = __msa_fmadd_w(_sum2, _r58, _k54);
_sum3 = __msa_fmadd_w(_sum3, _r5a, _k54);
_sum0 = __msa_fmadd_w(_sum0, _r55, _k55);
_sum1 = __msa_fmadd_w(_sum1, _r57, _k55);
_sum2 = __msa_fmadd_w(_sum2, _r59, _k55);
_sum3 = __msa_fmadd_w(_sum3, _r5b, _k55);
_sum0 = __msa_fmadd_w(_sum0, _r56, _k56);
_sum1 = __msa_fmadd_w(_sum1, _r58, _k56);
_sum2 = __msa_fmadd_w(_sum2, _r5a, _k56);
_sum3 = __msa_fmadd_w(_sum3, _r5c, _k56);
v4f32 _k60 = (v4f32)__msa_ld_w(kptr, 0);
v4f32 _k61 = (v4f32)__msa_ld_w(kptr + 4, 0);
v4f32 _k62 = (v4f32)__msa_ld_w(kptr + 4 * 2, 0);
v4f32 _k63 = (v4f32)__msa_ld_w(kptr + 4 * 3, 0);
v4f32 _k64 = (v4f32)__msa_ld_w(kptr + 4 * 4, 0);
v4f32 _k65 = (v4f32)__msa_ld_w(kptr + 4 * 5, 0);
v4f32 _k66 = (v4f32)__msa_ld_w(kptr + 4 * 6, 0);
kptr -= 4 * 42;
v4i32 _r6 = __msa_ld_w(r6, 0);
v4i32 _r6n = __msa_ld_w(r6 + 4, 0);
v4i32 _r6nn = __msa_ld_w(r6 + 8, 0);
v4f32 _r60 = (v4f32)__msa_splati_w(_r6, 0);
v4f32 _r61 = (v4f32)__msa_splati_w(_r6, 1);
v4f32 _r62 = (v4f32)__msa_splati_w(_r6, 2);
v4f32 _r63 = (v4f32)__msa_splati_w(_r6, 3);
v4f32 _r64 = (v4f32)__msa_splati_w(_r6n, 0);
v4f32 _r65 = (v4f32)__msa_splati_w(_r6n, 1);
v4f32 _r66 = (v4f32)__msa_splati_w(_r6n, 2);
v4f32 _r67 = (v4f32)__msa_splati_w(_r6n, 3);
v4f32 _r68 = (v4f32)__msa_splati_w(_r6nn, 0);
v4f32 _r69 = (v4f32)__msa_splati_w(_r6nn, 1);
v4f32 _r6a = (v4f32)__msa_splati_w(_r6nn, 2);
v4f32 _r6b = (v4f32)__msa_splati_w(_r6nn, 3);
v4f32 _r6c = __msa_fill_w_f32(r6[12]);
_sum0 = __msa_fmadd_w(_sum0, _r60, _k60);
_sum1 = __msa_fmadd_w(_sum1, _r62, _k60);
_sum2 = __msa_fmadd_w(_sum2, _r64, _k60);
_sum3 = __msa_fmadd_w(_sum3, _r66, _k60);
_sum0 = __msa_fmadd_w(_sum0, _r61, _k61);
_sum1 = __msa_fmadd_w(_sum1, _r63, _k61);
_sum2 = __msa_fmadd_w(_sum2, _r65, _k61);
_sum3 = __msa_fmadd_w(_sum3, _r67, _k61);
_sum0 = __msa_fmadd_w(_sum0, _r62, _k62);
_sum1 = __msa_fmadd_w(_sum1, _r64, _k62);
_sum2 = __msa_fmadd_w(_sum2, _r66, _k62);
_sum3 = __msa_fmadd_w(_sum3, _r68, _k62);
_sum0 = __msa_fmadd_w(_sum0, _r63, _k63);
_sum1 = __msa_fmadd_w(_sum1, _r65, _k63);
_sum2 = __msa_fmadd_w(_sum2, _r67, _k63);
_sum3 = __msa_fmadd_w(_sum3, _r69, _k63);
_sum0 = __msa_fmadd_w(_sum0, _r64, _k64);
_sum1 = __msa_fmadd_w(_sum1, _r66, _k64);
_sum2 = __msa_fmadd_w(_sum2, _r68, _k64);
_sum3 = __msa_fmadd_w(_sum3, _r6a, _k64);
_sum0 = __msa_fmadd_w(_sum0, _r65, _k65);
_sum1 = __msa_fmadd_w(_sum1, _r67, _k65);
_sum2 = __msa_fmadd_w(_sum2, _r69, _k65);
_sum3 = __msa_fmadd_w(_sum3, _r6b, _k65);
_sum0 = __msa_fmadd_w(_sum0, _r66, _k66);
_sum1 = __msa_fmadd_w(_sum1, _r68, _k66);
_sum2 = __msa_fmadd_w(_sum2, _r6a, _k66);
_sum3 = __msa_fmadd_w(_sum3, _r6c, _k66);
__msa_st_w((v4i32)_sum0, outptr0, 0);
__msa_st_w((v4i32)_sum1, outptr0 + 4, 0);
__msa_st_w((v4i32)_sum2, outptr0 + 4 * 2, 0);
__msa_st_w((v4i32)_sum3, outptr0 + 4 * 3, 0);
outptr0 += 4 * 4;
r0 += 8;
r1 += 8;
r2 += 8;
r3 += 8;
r4 += 8;
r5 += 8;
r6 += 8;
}
for (; j < outw; j++)
{
v4f32 _sum0 = (v4f32)__msa_ld_w(outptr0, 0);
v4f32 _k00 = (v4f32)__msa_ld_w(kptr, 0);
v4f32 _k01 = (v4f32)__msa_ld_w(kptr + 4, 0);
v4f32 _k02 = (v4f32)__msa_ld_w(kptr + 4 * 2, 0);
v4f32 _k03 = (v4f32)__msa_ld_w(kptr + 4 * 3, 0);
v4f32 _k04 = (v4f32)__msa_ld_w(kptr + 4 * 4, 0);
v4f32 _k05 = (v4f32)__msa_ld_w(kptr + 4 * 5, 0);
v4f32 _k06 = (v4f32)__msa_ld_w(kptr + 4 * 6, 0);
kptr += 4 * 7;
v4i32 _r0 = __msa_ld_w(r0, 0);
v4i32 _r0n = __msa_ld_w(r0 + 4, 0);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r0, 0), _k00);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r0, 1), _k01);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r0, 2), _k02);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r0, 3), _k03);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r0n, 0), _k04);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r0n, 1), _k05);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r0n, 2), _k06);
v4f32 _k10 = (v4f32)__msa_ld_w(kptr, 0);
v4f32 _k11 = (v4f32)__msa_ld_w(kptr + 4, 0);
v4f32 _k12 = (v4f32)__msa_ld_w(kptr + 4 * 2, 0);
v4f32 _k13 = (v4f32)__msa_ld_w(kptr + 4 * 3, 0);
v4f32 _k14 = (v4f32)__msa_ld_w(kptr + 4 * 4, 0);
v4f32 _k15 = (v4f32)__msa_ld_w(kptr + 4 * 5, 0);
v4f32 _k16 = (v4f32)__msa_ld_w(kptr + 4 * 6, 0);
kptr += 4 * 7;
v4i32 _r1 = __msa_ld_w(r1, 0);
v4i32 _r1n = __msa_ld_w(r1 + 4, 0);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r1, 0), _k10);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r1, 1), _k11);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r1, 2), _k12);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r1, 3), _k13);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r1n, 0), _k14);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r1n, 1), _k15);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r1n, 2), _k16);
v4f32 _k20 = (v4f32)__msa_ld_w(kptr, 0);
v4f32 _k21 = (v4f32)__msa_ld_w(kptr + 4, 0);
v4f32 _k22 = (v4f32)__msa_ld_w(kptr + 4 * 2, 0);
v4f32 _k23 = (v4f32)__msa_ld_w(kptr + 4 * 3, 0);
v4f32 _k24 = (v4f32)__msa_ld_w(kptr + 4 * 4, 0);
v4f32 _k25 = (v4f32)__msa_ld_w(kptr + 4 * 5, 0);
v4f32 _k26 = (v4f32)__msa_ld_w(kptr + 4 * 6, 0);
kptr += 4 * 7;
v4i32 _r2 = __msa_ld_w(r2, 0);
v4i32 _r2n = __msa_ld_w(r2 + 4, 0);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r2, 0), _k20);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r2, 1), _k21);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r2, 2), _k22);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r2, 3), _k23);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r2n, 0), _k24);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r2n, 1), _k25);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r2n, 2), _k26);
v4f32 _k30 = (v4f32)__msa_ld_w(kptr, 0);
v4f32 _k31 = (v4f32)__msa_ld_w(kptr + 4, 0);
v4f32 _k32 = (v4f32)__msa_ld_w(kptr + 4 * 2, 0);
v4f32 _k33 = (v4f32)__msa_ld_w(kptr + 4 * 3, 0);
v4f32 _k34 = (v4f32)__msa_ld_w(kptr + 4 * 4, 0);
v4f32 _k35 = (v4f32)__msa_ld_w(kptr + 4 * 5, 0);
v4f32 _k36 = (v4f32)__msa_ld_w(kptr + 4 * 6, 0);
kptr += 4 * 7;
v4i32 _r3 = __msa_ld_w(r3, 0);
v4i32 _r3n = __msa_ld_w(r3 + 4, 0);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r3, 0), _k30);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r3, 1), _k31);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r3, 2), _k32);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r3, 3), _k33);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r3n, 0), _k34);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r3n, 1), _k35);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r3n, 2), _k36);
v4f32 _k40 = (v4f32)__msa_ld_w(kptr, 0);
v4f32 _k41 = (v4f32)__msa_ld_w(kptr + 4, 0);
v4f32 _k42 = (v4f32)__msa_ld_w(kptr + 4 * 2, 0);
v4f32 _k43 = (v4f32)__msa_ld_w(kptr + 4 * 3, 0);
v4f32 _k44 = (v4f32)__msa_ld_w(kptr + 4 * 4, 0);
v4f32 _k45 = (v4f32)__msa_ld_w(kptr + 4 * 5, 0);
v4f32 _k46 = (v4f32)__msa_ld_w(kptr + 4 * 6, 0);
kptr += 4 * 7;
v4i32 _r4 = __msa_ld_w(r4, 0);
v4i32 _r4n = __msa_ld_w(r4 + 4, 0);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r4, 0), _k40);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r4, 1), _k41);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r4, 2), _k42);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r4, 3), _k43);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r4n, 0), _k44);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r4n, 1), _k45);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r4n, 2), _k46);
v4f32 _k50 = (v4f32)__msa_ld_w(kptr, 0);
v4f32 _k51 = (v4f32)__msa_ld_w(kptr + 4, 0);
v4f32 _k52 = (v4f32)__msa_ld_w(kptr + 4 * 2, 0);
v4f32 _k53 = (v4f32)__msa_ld_w(kptr + 4 * 3, 0);
v4f32 _k54 = (v4f32)__msa_ld_w(kptr + 4 * 4, 0);
v4f32 _k55 = (v4f32)__msa_ld_w(kptr + 4 * 5, 0);
v4f32 _k56 = (v4f32)__msa_ld_w(kptr + 4 * 6, 0);
kptr += 4 * 7;
v4i32 _r5 = __msa_ld_w(r5, 0);
v4i32 _r5n = __msa_ld_w(r5 + 4, 0);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r5, 0), _k50);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r5, 1), _k51);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r5, 2), _k52);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r5, 3), _k53);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r5n, 0), _k54);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r5n, 1), _k55);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r5n, 2), _k56);
v4f32 _k60 = (v4f32)__msa_ld_w(kptr, 0);
v4f32 _k61 = (v4f32)__msa_ld_w(kptr + 4, 0);
v4f32 _k62 = (v4f32)__msa_ld_w(kptr + 4 * 2, 0);
v4f32 _k63 = (v4f32)__msa_ld_w(kptr + 4 * 3, 0);
v4f32 _k64 = (v4f32)__msa_ld_w(kptr + 4 * 4, 0);
v4f32 _k65 = (v4f32)__msa_ld_w(kptr + 4 * 5, 0);
v4f32 _k66 = (v4f32)__msa_ld_w(kptr + 4 * 6, 0);
kptr -= 4 * 42;
v4i32 _r6 = __msa_ld_w(r6, 0);
v4i32 _r6n = __msa_ld_w(r6 + 4, 0);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r6, 0), _k60);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r6, 1), _k61);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r6, 2), _k62);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r6, 3), _k63);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r6n, 0), _k64);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r6n, 1), _k65);
_sum0 = __msa_fmadd_w(_sum0, (v4f32)__msa_splati_w(_r6n, 2), _k66);
__msa_st_w((v4i32)_sum0, outptr0, 0);
outptr0 += 4;
r0 += 2;
r1 += 2;
r2 += 2;
r3 += 2;
r4 += 2;
r5 += 2;
r6 += 2;
}
r0 += tailstep;
r1 += tailstep;
r2 += tailstep;
r3 += tailstep;
r4 += tailstep;
r5 += tailstep;
r6 += tailstep;
}
}
}
}
|
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] = 32;
tile_size[1] = 32;
tile_size[2] = 8;
tile_size[3] = 128;
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-2,16);t1++) {
lbp=max(ceild(t1,2),ceild(32*t1-Nt+3,32));
ubp=min(floord(Nt+Nz-4,32),floord(16*t1+Nz+13,32));
#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(32*t2-Nz-4,8)),2*t1);t3<=min(min(min(floord(Nt+Ny-4,8),floord(16*t1+Ny+29,8)),floord(32*t2+Ny+28,8)),floord(32*t1-32*t2+Nz+Ny+27,8));t3++) {
for (t4=max(max(max(0,ceild(t1-7,8)),ceild(32*t2-Nz-124,128)),ceild(8*t3-Ny-124,128));t4<=min(min(min(min(floord(Nt+Nx-4,128),floord(16*t1+Nx+29,128)),floord(32*t2+Nx+28,128)),floord(8*t3+Nx+4,128)),floord(32*t1-32*t2+Nz+Nx+27,128));t4++) {
for (t5=max(max(max(max(max(0,16*t1),32*t1-32*t2+1),32*t2-Nz+2),8*t3-Ny+2),128*t4-Nx+2);t5<=min(min(min(min(min(Nt-2,16*t1+31),32*t2+30),8*t3+6),128*t4+126),32*t1-32*t2+Nz+29);t5++) {
for (t6=max(max(32*t2,t5+1),-32*t1+32*t2+2*t5-31);t6<=min(min(32*t2+31,-32*t1+32*t2+2*t5),t5+Nz-2);t6++) {
for (t7=max(8*t3,t5+1);t7<=min(8*t3+7,t5+Ny-2);t7++) {
lbv=max(128*t4,t5+1);
ubv=min(128*t4+127,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;
}
|
ParallelBeginLink.c | int main() {
#pragma omp parallel
{
int x;
}
#pragma omp parallel if (1)
{
}
#pragma omp parallel
{
}
}
|
GB_bitmap_assign_A_template.c | //------------------------------------------------------------------------------
// GB_bitmap_assign_A_template: traverse over A for bitmap assignment into C
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2022, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// This template traverses over all the entries of the matrix A and operates on
// the corresponding entry in C(i,j), using the GB_AIJ_WORK macro. A can be
// hypersparse, sparse, bitmap, or full. It is not a scalar. The matrix
// C must be bitmap or full.
{
//--------------------------------------------------------------------------
// matrix assignment: slice the entries of A for each task
//--------------------------------------------------------------------------
GB_WERK_DECLARE (A_ek_slicing, int64_t) ;
int A_ntasks, A_nthreads ;
GB_SLICE_MATRIX (A, 8, chunk) ;
//--------------------------------------------------------------------------
// traverse of the entries of the matrix A
//--------------------------------------------------------------------------
int tid ;
#pragma omp parallel for num_threads(A_nthreads) schedule(dynamic,1) \
reduction(+:cnvals)
for (tid = 0 ; tid < A_ntasks ; tid++)
{
// if kfirst > klast then task tid does no work at all
int64_t kfirst = kfirst_Aslice [tid] ;
int64_t klast = klast_Aslice [tid] ;
int64_t task_cnvals = 0 ;
//----------------------------------------------------------------------
// traverse over A (:,kfirst:klast)
//----------------------------------------------------------------------
for (int64_t k = kfirst ; k <= klast ; k++)
{
//------------------------------------------------------------------
// find the part of A(:,k) for this task
//------------------------------------------------------------------
int64_t jA = GBH (Ah, k) ;
int64_t pA_start, pA_end ;
GB_get_pA (&pA_start, &pA_end, tid, k, kfirst,
klast, pstart_Aslice, Ap, nI) ;
//------------------------------------------------------------------
// traverse over A(:,jA), the kth vector of A
//------------------------------------------------------------------
int64_t jC = GB_ijlist (J, jA, Jkind, Jcolon) ;
int64_t pC0 = jC * cvlen ; // first entry in C(:,jC)
for (int64_t pA = pA_start ; pA < pA_end ; pA++)
{
if (!GBB (Ab, pA)) continue ;
int64_t iA = GBI (Ai, pA, nI) ;
int64_t iC = GB_ijlist (I, iA, Ikind, Icolon) ;
int64_t pC = iC + pC0 ;
// operate on C(iC,jC) at pC, and A(iA,jA) at pA. The mask
// can be accessed at pC if M is bitmap or full. A has any
// sparsity format so only A(iA,jA) can be accessed at pA.
// To access a full matrix M for the subassign case, use
// the position (iA + jA*nI).
GB_AIJ_WORK (pC, pA) ;
}
}
cnvals += task_cnvals ;
}
//--------------------------------------------------------------------------
// free workspace
//--------------------------------------------------------------------------
GB_WERK_POP (A_ek_slicing, int64_t) ;
}
|
sudoku_solver_parallel.c | #include <stdio.h>
#include <string.h>
#include <stdlib.h>
#include <math.h>
#include <omp.h>
#define EMPTY 0
#define MAX_SIZE 25
int findEmptyLocation(int matrix[MAX_SIZE][MAX_SIZE], int *row, int *col, int box_size);
int canBeFilled(int matrix[MAX_SIZE][MAX_SIZE], int row, int col, int num, int box_size, int grid_sz);
void printMatrix(int matrix[MAX_SIZE][MAX_SIZE], int box_sz)
{
#pragma omp critical
{
printf("solution matrix\n");
int row, col;
for (row = 0; row < box_sz; row++)
{
for (col = 0; col < box_sz; col++)
printf("%d ", matrix[row][col]);
printf("\n");
}
}
}
int solveSudoku(int row, int col, int matrix[MAX_SIZE][MAX_SIZE], int box_sz, int grid_sz)
{
if(col > (box_sz - 1)) {
col = 0;
row++;
}
if(row > (box_sz - 1)) {
return 1;
}
if(matrix[row][col] != EMPTY) {
//#pragma omp task firstprivate(col, row)
if (solveSudoku(row, col+1, matrix, box_sz, grid_sz)) {
printMatrix(matrix, box_sz);
}
} else {
int num;
for (num = 1; num <= box_sz; num++)
{
if (canBeFilled(matrix, row, col, num, box_sz, grid_sz))
{
#pragma omp task firstprivate(num, col, row)
{
int tempMatrix[MAX_SIZE][MAX_SIZE];
int i;
int j;
for(i=0; i<box_sz; i++) {
for( j=0; j<box_sz; j++){
tempMatrix[i][j] = matrix[i][j];
}
}
tempMatrix[row][col] = num;
if (solveSudoku(row, col+1, tempMatrix, box_sz, grid_sz))
printMatrix(tempMatrix, box_sz);
}
}
}
}
return 0;
}
int existInRow(int matrix[MAX_SIZE][MAX_SIZE], int row, int num, int box_size)
{
int col;
for (col = 0; col < box_size; col++)
if (matrix[row][col] == num)
return 1;
return 0;
}
int existInColumn(int matrix[MAX_SIZE][MAX_SIZE], int col, int num, int box_size)
{
int row;
for (row = 0; row < box_size; row++)
if (matrix[row][col] == num)
return 1;
return 0;
}
int existInGrid(int matrix[MAX_SIZE][MAX_SIZE], int gridOffsetRow, int gridOffsetColumn, int num, int grid_sz)
{
int row, col;
for (row = 0; row < grid_sz; row++)
for (col = 0; col < grid_sz; col++)
if (matrix[row+gridOffsetRow][col+gridOffsetColumn] == num)
return 1;
return 0;
}
int canBeFilled(int matrix[MAX_SIZE][MAX_SIZE], int row, int col, int num, int box_size, int grid_sz)
{
return !existInRow(matrix, row, num, box_size) &&
!existInColumn(matrix, col, num, box_size) &&
!existInGrid(matrix, row - row%grid_sz , col - col%grid_sz, num, grid_sz)&&
matrix[row][col]==EMPTY;
}
void readCSV(int box_sz, char *filename, int matrix[MAX_SIZE][MAX_SIZE]){
FILE *file;
file = fopen(filename, "r");
int i = 0;
char line[4098];
while (fgets(line, 4098, file) && (i < box_sz))
{
char* tmp = strdup(line);
int j = 0;
const char* tok;
for (tok = strtok(line, ","); tok && *tok; j++, tok = strtok(NULL, ",\n"))
{
matrix[i][j] = atof(tok);
}
free(tmp);
i++;
}
}
int main(int argc, char const *argv[])
{
double time1 = omp_get_wtime();
if (argc < 3){
printf("Please specify matrix size and the CSV file name as inputs.\n");
exit(0);
}
int box_sz = atoi(argv[1]);
int grid_sz = sqrt(box_sz);
char filename[256]; strcpy(filename, argv[2]);
int matrix[MAX_SIZE][MAX_SIZE];
readCSV(box_sz, filename, matrix);
#pragma omp parallel
{
#pragma omp single
{
solveSudoku(0, 0, matrix, box_sz, grid_sz);
}
}
printf("Elapsed time: %0.2lf\n", omp_get_wtime() - time1);
return 0;
}
|
GB_binop__minus_fp32.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__minus_fp32
// A.*B function (eWiseMult): GB_AemultB__minus_fp32
// A*D function (colscale): GB_AxD__minus_fp32
// D*A function (rowscale): GB_DxB__minus_fp32
// C+=B function (dense accum): GB_Cdense_accumB__minus_fp32
// C+=b function (dense accum): GB_Cdense_accumb__minus_fp32
// C+=A+B function (dense ewise3): GB_Cdense_ewise3_accum__minus_fp32
// C=A+B function (dense ewise3): GB_Cdense_ewise3_noaccum__minus_fp32
// C=scalar+B GB_bind1st__minus_fp32
// C=scalar+B' GB_bind1st_tran__minus_fp32
// C=A+scalar GB_bind2nd__minus_fp32
// C=A'+scalar GB_bind2nd_tran__minus_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) \
float aij = Ax [pA]
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB) \
float bij = Bx [pB]
// 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) \
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 \
1
// GB_cblas_*axpy gateway routine, if it exists for this operator and type:
#define GB_CBLAS_AXPY \
GB_cblas_saxpy
// 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_MINUS || GxB_NO_FP32 || GxB_NO_MINUS_FP32)
//------------------------------------------------------------------------------
// 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__minus_fp32
(
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
//------------------------------------------------------------------------------
GrB_Info GB_Cdense_ewise3_noaccum__minus_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__minus_fp32
(
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__minus_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__minus_fp32
(
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
float *GB_RESTRICT Cx = (float *) 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__minus_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 *GB_RESTRICT Cx = (float *) 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__minus_fp32
(
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__minus_fp32
(
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__minus_fp32
(
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
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 < anz ; p++)
{
float 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__minus_fp32
(
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 ;
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++)
{
float 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) \
{ \
float aij = Ax [pA] ; \
Cx [pC] = (x - aij) ; \
}
GrB_Info GB_bind1st_tran__minus_fp32
(
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 \
float
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
float x = (*((const float *) x_input)) ;
#define GB_PHASE_2_OF_2
#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 typcasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
float aij = Ax [pA] ; \
Cx [pC] = (aij - y) ; \
}
GrB_Info GB_bind2nd_tran__minus_fp32
(
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
float y = (*((const float *) y_input)) ;
#define GB_PHASE_2_OF_2
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
GB_unaryop__abs_uint8_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__abs_uint8_int16
// op(A') function: GB_tran__abs_uint8_int16
// C type: uint8_t
// A type: int16_t
// cast: uint8_t cij = (uint8_t) aij
// unaryop: cij = aij
#define GB_ATYPE \
int16_t
#define GB_CTYPE \
uint8_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 ;
// casting
#define GB_CASTING(z, x) \
uint8_t z = (uint8_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_ABS || GxB_NO_UINT8 || GxB_NO_INT16)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__abs_uint8_int16
(
uint8_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__abs_uint8_int16
(
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
|
test_omp.c | #include <stdio.h>
#include <assert.h>
#define N 100
int A[N];
int B[N];
int main() {
for(int i=0; i<N; i++){
A[i] =0;
B[i] =i;
}
#pragma omp target map(A,B)
for(int i=0; i<N; i++){
A[i] = B[i];
}
for(int i=0; i<N; i++){
assert(A[i] == B[i]);
}
printf("PASSED\n");
return 0;
}
|
opi.c | #include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <omp.h>
int main(int argc, char **argv) {
//seed random number generator
// Q2b: get the number of threads to run with from agrv and
// add OpenMP API code to set number of threads here
int Nthreads = atoi(argv);
//int Nthreads = 2;
//int Nthreads = 4;
long long int Ntrials = 10000000;
omp_set_num_threads(Nthreads);
struct drand48_data *drandData;
drandData = (struct drand48_data*) malloc(Nthreads*sizeof(struct drand48_data));
// Q2c: add an OpenMP parallel region here, wherein each thread initializes
// one entry in drandData using srand48_r and seed based on thread number
#pragma omp parallel
{
int rank = omp_get_thread_num();
long int seed = rank;
srand48_r(seed, drandData+rank);
}
//need running tallies
long long int Ntotal=0;
long long int Ncircle=0;
double startTime = omp_get_wtime();
#pragma omp parallel for
for (long long int n=0; n<Ntrials; n++) {
int rank = omp_get_thread_num();
double rand1;
double rand2;
//gererate two random numbers (use the thread id to offset drandData)
drand48_r(drandData+0, &rand1);
drand48_r(drandData+0, &rand2);
double x = -1 + 2*rand1; //shift to [-1,1]
double y = -1 + 2*rand2;
//check if its in the circle
if (sqrt(x*x+y*y)<=1) Ncircle++;
Ntotal++;
if (n%100 ==0) {
double pi = 4.0*Ncircle/ (double) (n);
printf("Our estimate of pi is %g \n", pi);
}
}
double endTime = omp_get_wtime();
double pi = 4.0*Ncircle/ (double) (Ntotal);
printf("Our final estimate of pi is %g. The runtime is %g \n", pi, endTime-startTime);
free(drandData);
return 0;
// As I add more threads the speed slows down and increases the runtime.
}
|
adjvectorbqm.h | // Copyright 2020 D-Wave Systems Inc.
//
// 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.
#ifndef DIMOD_ADJVECTORBQM_H_
#define DIMOD_ADJVECTORBQM_H_
#include <stdio.h>
#include <algorithm>
#include <utility>
#include <vector>
#include "dimod/utils.h"
namespace dimod {
template <class V, class B>
class AdjVectorBQM {
public:
using bias_type = B;
using variable_type = V;
using size_type = std::size_t;
using outvars_iterator = typename std::vector<std::pair<V, B>>::iterator;
using const_outvars_iterator =
typename std::vector<std::pair<V, B>>::const_iterator;
// in the future we'd probably like to make this protected
std::vector<std::pair<std::vector<std::pair<V, B>>, B>> adj;
AdjVectorBQM() {}
template <class BQM>
explicit AdjVectorBQM(const BQM &bqm) {
adj.resize(bqm.num_variables());
for (size_type v = 0; v < bqm.num_variables(); ++v) {
linear(v) = bqm.linear(v);
auto span = bqm.neighborhood(v);
adj[v].first.insert(adj[v].first.begin(), span.first, span.second);
}
}
/**
* Construct a BQM from a dense array.
*
* @param dense An array containing the biases. Assumed to contain
* `num_variables`^2 elements. The upper and lower triangle are summed.
* @param num_variables The number of variables.
*/
template <class B2>
AdjVectorBQM(const B2 dense[], size_type num_variables,
bool ignore_diagonal = false) {
// we know how big our linear is going to be
adj.resize(num_variables);
bias_type qbias;
if (!ignore_diagonal) {
for (size_type v = 0; v < num_variables; ++v) {
adj[v].second = dense[v * (num_variables + 1)];
}
}
for (size_type u = 0; u < num_variables; ++u) {
for (size_type v = u + 1; v < num_variables; ++v) {
qbias = dense[u * num_variables + v] +
dense[v * num_variables + u];
if (qbias != 0) {
adj[u].first.emplace_back(v, qbias);
adj[v].first.emplace_back(u, qbias);
}
}
}
}
/**
* Construct a BQM from a dense array. This constructor is parallelized
* and temporarily zeroes out the diagonal of the dense array but restores
* it back.
*
* @param dense An array containing the biases. Assumed to contain
* `num_variables`^2 elements. The upper and lower triangle are summed.
* @param num_variables The number of variables.
*/
template <class B2>
AdjVectorBQM(B2 dense[], size_type num_variables,
bool ignore_diagonal = false) {
// we know how big our linear is going to be
adj.resize(num_variables);
// Backup copy of the diagonal of the dense matrix.
std::vector<B2> dense_diagonal(num_variables);
if (!ignore_diagonal) {
#pragma omp parallel for
for (size_type v = 0; v < num_variables; ++v) {
adj[v].second = dense[v * (num_variables + 1)];
}
}
#pragma omp parallel
{
// Zero out the diagonal to avoid expensive checks inside innermost
// loop in the code for reading the matrix. The diagonal will be
// restored so a backup copy is saved.
#pragma omp for schedule(static)
for (size_type v = 0; v < num_variables; ++v) {
dense_diagonal[v] = dense[v * (num_variables + 1)];
dense[v * (num_variables + 1)] = 0;
}
size_type counters[BLOCK_SIZE] = {0};
size_type buffer_size = num_variables * BLOCK_SIZE *
sizeof(std::pair<variable_type, bias_type>);
std::pair<variable_type, bias_type> *temp_buffer =
(std::pair<variable_type, bias_type> *)malloc(buffer_size);
if (temp_buffer == NULL) {
printf("Memory allocation failure.\n");
exit(0);
}
// We process the matrix in blocks of size BLOCK_SIZE*BLOCK_SIZE to take
// advantage of cache locality. Dynamic scheduling is used as we know some
// blocks may be more sparse than others and processing them may finish earlier.
#pragma omp for schedule(dynamic)
for (size_type u_st = 0; u_st < num_variables; u_st += BLOCK_SIZE) {
size_type u_end = std::min(u_st + BLOCK_SIZE, num_variables);
for (size_type v_st = 0; v_st < num_variables;
v_st += BLOCK_SIZE) {
size_type v_end =
std::min(v_st + BLOCK_SIZE, num_variables);
for (size_type u = u_st, n = 0; u < u_end; u++, n++) {
size_type counter_u = counters[n];
size_type counter_u_old = counter_u;
for (size_type v = v_st; v < v_end; v++) {
bias_type qbias = dense[u * num_variables + v] +
dense[v * num_variables + u];
if (qbias != 0) {
temp_buffer[n * num_variables + counter_u++] = {
v, qbias};
}
}
if (counter_u != counter_u_old) {
counters[n] = counter_u;
}
}
}
for (size_type n = 0; n < BLOCK_SIZE; n++) {
if (counters[n]) {
adj[u_st + n].first.assign(
temp_buffer + n * num_variables,
temp_buffer + n * num_variables + counters[n]);
counters[n] = 0;
}
}
}
free(temp_buffer);
// Restore the diagonal of the original dense matrix
#pragma omp for schedule(static)
for (size_type v = 0; v < num_variables; ++v) {
dense[v * (num_variables + 1)] = dense_diagonal[v];
}
}
}
/**
* Construct a BQM from COO-formated iterators.
*
* A sparse BQM encoded in [COOrdinate] format is specified by three
* arrays of (row, column, value).
*
* [COOrdinate]: https://w.wiki/n$L
*
* @param row_iterator Iterator pointing to the beginning of the row data.
* Must be a random access iterator.
* @param col_iterator Iterator pointing to the beginning of the column
* data. Must be a random access iterator.
* @param bias_iterator Iterator pointing to the beginning of the bias data.
* Must be a random access iterator.
* @param length The number of (row, column, bias) entries.
* @param ignore_diagonal If true, entries on the diagonal of the sparse
* matrix are ignored.
*/
template <class ItRow, class ItCol, class ItBias>
AdjVectorBQM(ItRow row_iterator, ItCol col_iterator, ItBias bias_iterator,
size_type length, bool ignore_diagonal = false) {
// determine the number of variables so we can allocate adj
if (length > 0) {
size_type max_label = std::max(
*std::max_element(row_iterator, row_iterator + length),
*std::max_element(col_iterator, col_iterator + length));
adj.resize(max_label + 1);
}
// Count the degrees and use that to reserve the neighborhood vectors
std::vector<size_type> degrees(adj.size());
ItRow rit(row_iterator);
ItCol cit(col_iterator);
for (size_type i = 0; i < length; ++i, ++rit, ++cit) {
if (*rit != *cit) {
degrees[*rit] += 1;
degrees[*cit] += 1;
}
}
for (size_type i = 0; i < degrees.size(); ++i) {
adj[i].first.reserve(degrees[i]);
}
// add the values to the adjacency, not worrying about order or
// duplicates
for (size_type i = 0; i < length; i++) {
if (*row_iterator == *col_iterator) {
// linear bias
if (!ignore_diagonal) {
linear(*row_iterator) += *bias_iterator;
}
} else {
// quadratic bias
adj[*row_iterator].first.emplace_back(*col_iterator,
*bias_iterator);
adj[*col_iterator].first.emplace_back(*row_iterator,
*bias_iterator);
}
++row_iterator;
++col_iterator;
++bias_iterator;
}
normalize_neighborhood();
}
/// Add one (disconnected) variable to the BQM and return its index.
variable_type add_variable() {
adj.resize(adj.size() + 1);
return adj.size() - 1;
}
/// Get the degree of variable `v`.
size_type degree(variable_type v) const { return adj[v].first.size(); }
[[deprecated("Use AdjVectorBQM::linear(v)")]] bias_type get_linear(
variable_type v) const { return linear(v); }
std::pair<bias_type, bool> get_quadratic(variable_type u,
variable_type v) const {
assert(u >= 0 && (size_type)u < adj.size());
assert(v >= 0 && (size_type)v < adj.size());
assert(u != v);
auto span = neighborhood(u);
auto low = std::lower_bound(span.first, span.second, v,
utils::comp_v<V, B>);
if (low == span.second || low->first != v)
return std::make_pair(0, false);
return std::make_pair(low->second, true);
}
bias_type &linear(variable_type v) {
assert(v >= 0 && (size_type)v < adj.size());
return adj[v].second;
}
const bias_type &linear(variable_type v) const {
assert(v >= 0 && (size_type)v < adj.size());
return adj[v].second;
}
std::pair<outvars_iterator, outvars_iterator> neighborhood(
variable_type u) {
assert(u >= 0 && (size_type)u < adj.size());
return std::make_pair(adj[u].first.begin(), adj[u].first.end());
}
std::pair<const_outvars_iterator, const_outvars_iterator> neighborhood(
variable_type u) const {
assert(u >= 0 && (size_type)u < adj.size());
return std::make_pair(adj[u].first.cbegin(), adj[u].first.cend());
}
/**
* The neighborhood of variable `v`.
*
* @param A variable `v`.
* @param The neighborhood will start with the first out variable that
* does not compare less than `start`.
*
* @returns A pair of iterators pointing to the start and end of the
* neighborhood.
*/
std::pair<const_outvars_iterator, const_outvars_iterator> neighborhood(
variable_type v, variable_type start) const {
auto span = neighborhood(v);
auto low = std::lower_bound(span.first, span.second, start,
utils::comp_v<V, B>);
return std::make_pair(low, span.second);
}
/// sort each neighborhood and merge duplicates
void normalize_neighborhood() {
for (size_type v = 0; v < adj.size(); ++v) {
normalize_neighborhood(v);
}
}
template<class Iter>
void normalize_neighborhood(Iter begin, Iter end) {
while (begin != end) {
normalize_neighborhood(*begin);
++begin;
}
}
void normalize_neighborhood(variable_type v) {
auto span = neighborhood(v);
if (!std::is_sorted(span.first, span.second)) {
std::sort(span.first, span.second);
}
// now merge any duplicate variables, adding the biases
auto it = adj[v].first.begin();
while (it + 1 < adj[v].first.end()) {
if (it->first == (it + 1)->first) {
it->second += (it + 1)->second;
adj[v].first.erase(it + 1);
} else {
++it;
}
}
}
size_type num_variables() const { return adj.size(); }
size_type num_interactions() const {
size_type count = 0;
for (auto it = adj.begin(); it != adj.end(); ++it)
count += it->first.size();
return count / 2;
}
variable_type pop_variable() {
assert(adj.size() > 0);
variable_type v = adj.size() - 1;
// remove v from all of its neighbor's neighborhoods
for (auto it = adj[v].first.cbegin(); it != adj[v].first.cend(); ++it) {
auto span = neighborhood(it->first);
auto low = std::lower_bound(span.first, span.second, v,
utils::comp_v<V, B>);
adj[it->first].first.erase(low);
}
adj.pop_back();
return adj.size();
}
bool remove_interaction(variable_type u, variable_type v) {
assert(u >= 0 && (size_type)u < adj.size());
assert(v >= 0 && (size_type)v < adj.size());
auto span = neighborhood(u);
auto low = std::lower_bound(span.first, span.second, v,
utils::comp_v<V, B>);
bool exists = !(low == span.second || low->first != v);
if (exists) {
adj[u].first.erase(low);
span = neighborhood(v);
low = std::lower_bound(span.first, span.second, u,
utils::comp_v<V, B>);
assert(!(low == span.second || low->first != u) == exists);
adj[v].first.erase(low);
}
return exists;
}
[[deprecated("Use AdjVectorBQM::linear(v)")]] void set_linear(
variable_type v, bias_type b) {
assert(v >= 0 && (size_type)v < adj.size());
linear(v) = b;
}
bool set_quadratic(variable_type u, variable_type v, bias_type b) {
assert(u >= 0 && (size_type)u < adj.size());
assert(v >= 0 && (size_type)v < adj.size());
assert(u != v);
auto span = neighborhood(u);
auto low = std::lower_bound(span.first, span.second, v,
utils::comp_v<V, B>);
bool exists = !(low == span.second || low->first != v);
if (exists) {
low->second = b;
} else {
adj[u].first.emplace(low, v, b);
}
span = neighborhood(v);
low = std::lower_bound(span.first, span.second, u, utils::comp_v<V, B>);
assert(!(low == span.second || low->first != u) == exists);
if (exists) {
low->second = b;
} else {
adj[v].first.emplace(low, u, b);
}
// to be consistent with AdjArrayBQM, we return whether the value was
// set
return true;
}
};
} // namespace dimod
#endif // DIMOD_ADJVECTORBQM_H_
|
d2d_memcpy.c | // RUN: %libomptarget-compile-aarch64-unknown-linux-gnu && env OMP_MAX_ACTIVE_LEVELS=2 %libomptarget-run-aarch64-unknown-linux-gnu | %fcheck-aarch64-unknown-linux-gnu
// RUN: %libomptarget-compile-powerpc64-ibm-linux-gnu && env OMP_MAX_ACTIVE_LEVELS=2 %libomptarget-run-powerpc64-ibm-linux-gnu | %fcheck-powerpc64-ibm-linux-gnu
// RUN: %libomptarget-compile-powerpc64le-ibm-linux-gnu && env OMP_MAX_ACTIVE_LEVELS=2 %libomptarget-run-powerpc64le-ibm-linux-gnu | %fcheck-powerpc64le-ibm-linux-gnu
// RUN: %libomptarget-compile-x86_64-pc-linux-gnu && env OMP_MAX_ACTIVE_LEVELS=2 %libomptarget-run-x86_64-pc-linux-gnu | %fcheck-x86_64-pc-linux-gnu -allow-empty
#include <assert.h>
#include <omp.h>
#include <stdio.h>
#include <stdlib.h>
const int magic_num = 7;
int main(int argc, char *argv[]) {
const int N = 128;
const int num_devices = omp_get_num_devices();
// No target device, just return
if (num_devices == 0) {
printf("PASS\n");
return 0;
}
const int src_device = 0;
int dst_device = 1;
if (dst_device >= num_devices)
dst_device = num_devices - 1;
int length = N * sizeof(int);
int *src_ptr = omp_target_alloc(length, src_device);
int *dst_ptr = omp_target_alloc(length, dst_device);
assert(src_ptr && "src_ptr is NULL");
assert(dst_ptr && "dst_ptr is NULL");
#pragma omp target teams distribute parallel for device(src_device) \
is_device_ptr(src_ptr)
for (int i = 0; i < N; ++i) {
src_ptr[i] = magic_num;
}
int rc =
omp_target_memcpy(dst_ptr, src_ptr, length, 0, 0, dst_device, src_device);
assert(rc == 0 && "error in omp_target_memcpy");
int *buffer = malloc(length);
assert(buffer && "failed to allocate host buffer");
#pragma omp target teams distribute parallel for device(dst_device) \
map(from: buffer[0:N]) is_device_ptr(dst_ptr)
for (int i = 0; i < N; ++i) {
buffer[i] = dst_ptr[i] + magic_num;
}
for (int i = 0; i < N; ++i)
assert(buffer[i] == 2 * magic_num);
printf("PASS\n");
// Free host and device memory
free(buffer);
omp_target_free(src_ptr, src_device);
omp_target_free(dst_ptr, dst_device);
return 0;
}
// CHECK: PASS
|
profile.c | /*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% PPPP RRRR OOO FFFFF IIIII L EEEEE %
% P P R R O O F I L E %
% PPPP RRRR O O FFF I L EEE %
% P R R O O F I L E %
% P R R OOO F IIIII LLLLL EEEEE %
% %
% %
% MagickCore Image Profile Methods %
% %
% Software Design %
% Cristy %
% July 1992 %
% %
% %
% Copyright 1999-2021 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 "MagickCore/studio.h"
#include "MagickCore/artifact.h"
#include "MagickCore/attribute.h"
#include "MagickCore/cache.h"
#include "MagickCore/color.h"
#include "MagickCore/colorspace-private.h"
#include "MagickCore/configure.h"
#include "MagickCore/exception.h"
#include "MagickCore/exception-private.h"
#include "MagickCore/image.h"
#include "MagickCore/linked-list.h"
#include "MagickCore/memory_.h"
#include "MagickCore/monitor.h"
#include "MagickCore/monitor-private.h"
#include "MagickCore/option.h"
#include "MagickCore/option-private.h"
#include "MagickCore/pixel-accessor.h"
#include "MagickCore/profile.h"
#include "MagickCore/profile-private.h"
#include "MagickCore/property.h"
#include "MagickCore/quantum.h"
#include "MagickCore/quantum-private.h"
#include "MagickCore/resource_.h"
#include "MagickCore/splay-tree.h"
#include "MagickCore/string_.h"
#include "MagickCore/string-private.h"
#include "MagickCore/thread-private.h"
#include "MagickCore/token.h"
#include "MagickCore/utility.h"
#if defined(MAGICKCORE_LCMS_DELEGATE)
#if defined(MAGICKCORE_HAVE_LCMS_LCMS2_H)
#include <wchar.h>
#include <lcms/lcms2.h>
#else
#include <wchar.h>
#include "lcms2.h"
#endif
#endif
#if defined(MAGICKCORE_XML_DELEGATE)
# if defined(MAGICKCORE_WINDOWS_SUPPORT)
# if !defined(__MINGW32__)
# include <win32config.h>
# endif
# endif
# include <libxml/parser.h>
# include <libxml/tree.h>
#endif
/*
Forward declarations
*/
static MagickBooleanType
SetImageProfileInternal(Image *,const char *,const StringInfo *,
const MagickBooleanType,ExceptionInfo *);
static void
WriteTo8BimProfile(Image *,const char*,const StringInfo *);
/*
Typedef declarations
*/
struct _ProfileInfo
{
char
*name;
size_t
length;
unsigned char
*info;
size_t
signature;
};
typedef struct _CMSExceptionInfo
{
Image
*image;
ExceptionInfo
*exception;
} CMSExceptionInfo;
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% C l o n e I m a g e P r o f i l e s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% CloneImageProfiles() clones one or more image profiles.
%
% The format of the CloneImageProfiles method is:
%
% MagickBooleanType CloneImageProfiles(Image *image,
% const Image *clone_image)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o clone_image: the clone image.
%
*/
MagickExport MagickBooleanType CloneImageProfiles(Image *image,
const Image *clone_image)
{
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(clone_image != (const Image *) NULL);
assert(clone_image->signature == MagickCoreSignature);
if (clone_image->profiles != (void *) NULL)
{
if (image->profiles != (void *) NULL)
DestroyImageProfiles(image);
image->profiles=CloneSplayTree((SplayTreeInfo *) clone_image->profiles,
(void *(*)(void *)) ConstantString,(void *(*)(void *)) CloneStringInfo);
}
return(MagickTrue);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% D e l e t e I m a g e P r o f i l e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% DeleteImageProfile() deletes a profile from the image by its name.
%
% The format of the DeleteImageProfile method is:
%
% MagickBooleanTyupe DeleteImageProfile(Image *image,const char *name)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o name: the profile name.
%
*/
MagickExport MagickBooleanType DeleteImageProfile(Image *image,const char *name)
{
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if (image->profiles == (SplayTreeInfo *) NULL)
return(MagickFalse);
WriteTo8BimProfile(image,name,(StringInfo *) NULL);
return(DeleteNodeFromSplayTree((SplayTreeInfo *) image->profiles,name));
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% D e s t r o y I m a g e P r o f i l e s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% DestroyImageProfiles() releases memory associated with an image profile map.
%
% The format of the DestroyProfiles method is:
%
% void DestroyImageProfiles(Image *image)
%
% A description of each parameter follows:
%
% o image: the image.
%
*/
MagickExport void DestroyImageProfiles(Image *image)
{
if (image->profiles != (SplayTreeInfo *) NULL)
image->profiles=DestroySplayTree((SplayTreeInfo *) image->profiles);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e P r o f i l e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageProfile() gets a profile associated with an image by name.
%
% The format of the GetImageProfile method is:
%
% const StringInfo *GetImageProfile(const Image *image,const char *name)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o name: the profile name.
%
*/
MagickExport const StringInfo *GetImageProfile(const Image *image,
const char *name)
{
const StringInfo
*profile;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if (image->profiles == (SplayTreeInfo *) NULL)
return((StringInfo *) NULL);
profile=(const StringInfo *) GetValueFromSplayTree((SplayTreeInfo *)
image->profiles,name);
return(profile);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t N e x t I m a g e P r o f i l e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetNextImageProfile() gets the next profile name for an image.
%
% The format of the GetNextImageProfile method is:
%
% char *GetNextImageProfile(const Image *image)
%
% A description of each parameter follows:
%
% o hash_info: the hash info.
%
*/
MagickExport char *GetNextImageProfile(const Image *image)
{
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if (image->profiles == (SplayTreeInfo *) NULL)
return((char *) NULL);
return((char *) GetNextKeyInSplayTree((SplayTreeInfo *) image->profiles));
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% P r o f i l e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ProfileImage() associates, applies, or removes an ICM, IPTC, or generic
% profile with / to / from an image. If the profile is NULL, it is removed
% from the image otherwise added or applied. Use a name of '*' and a profile
% of NULL to remove all profiles from the image.
%
% ICC and ICM profiles are handled as follows: If the image does not have
% an associated color profile, the one you provide is associated with the
% image and the image pixels are not transformed. Otherwise, the colorspace
% transform defined by the existing and new profile are applied to the image
% pixels and the new profile is associated with the image.
%
% The format of the ProfileImage method is:
%
% MagickBooleanType ProfileImage(Image *image,const char *name,
% const void *datum,const size_t length,const MagickBooleanType clone)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o name: Name of profile to add or remove: ICC, IPTC, or generic profile.
%
% o datum: the profile data.
%
% o length: the length of the profile.
%
% o clone: should be MagickFalse.
%
*/
#if defined(MAGICKCORE_LCMS_DELEGATE)
typedef struct _LCMSInfo
{
ColorspaceType
colorspace;
cmsUInt32Number
type;
size_t
channels;
cmsHPROFILE
profile;
int
intent;
double
scale,
translate;
void
**magick_restrict pixels;
} LCMSInfo;
#if LCMS_VERSION < 2060
static void* cmsGetContextUserData(cmsContext ContextID)
{
return(ContextID);
}
static cmsContext cmsCreateContext(void *magick_unused(Plugin),void *UserData)
{
magick_unreferenced(Plugin);
return((cmsContext) UserData);
}
static void cmsSetLogErrorHandlerTHR(cmsContext magick_unused(ContextID),
cmsLogErrorHandlerFunction Fn)
{
magick_unreferenced(ContextID);
cmsSetLogErrorHandler(Fn);
}
static void cmsDeleteContext(cmsContext magick_unused(ContextID))
{
magick_unreferenced(ContextID);
}
#endif
static void **DestroyPixelThreadSet(void **pixels)
{
ssize_t
i;
if (pixels == (void **) NULL)
return((void **) NULL);
for (i=0; i < (ssize_t) GetMagickResourceLimit(ThreadResource); i++)
if (pixels[i] != (void *) NULL)
pixels[i]=RelinquishMagickMemory(pixels[i]);
pixels=(void **) RelinquishMagickMemory(pixels);
return(pixels);
}
static void **AcquirePixelThreadSet(const size_t columns,
const size_t channels,MagickBooleanType highres)
{
ssize_t
i;
size_t
number_threads;
size_t
size;
void
**pixels;
number_threads=(size_t) GetMagickResourceLimit(ThreadResource);
pixels=(void **) AcquireQuantumMemory(number_threads,sizeof(*pixels));
if (pixels == (void **) NULL)
return((void **) NULL);
(void) memset(pixels,0,number_threads*sizeof(*pixels));
size=sizeof(double);
if (highres == MagickFalse)
size=sizeof(Quantum);
for (i=0; i < (ssize_t) number_threads; i++)
{
pixels[i]=AcquireQuantumMemory(columns,channels*size);
if (pixels[i] == (void *) NULL)
return(DestroyPixelThreadSet(pixels));
}
return(pixels);
}
static cmsHTRANSFORM *DestroyTransformThreadSet(cmsHTRANSFORM *transform)
{
ssize_t
i;
assert(transform != (cmsHTRANSFORM *) NULL);
for (i=0; i < (ssize_t) GetMagickResourceLimit(ThreadResource); i++)
if (transform[i] != (cmsHTRANSFORM) NULL)
cmsDeleteTransform(transform[i]);
transform=(cmsHTRANSFORM *) RelinquishMagickMemory(transform);
return(transform);
}
static cmsHTRANSFORM *AcquireTransformThreadSet(const LCMSInfo *source_info,
const LCMSInfo *target_info,const cmsUInt32Number flags,
cmsContext cms_context)
{
cmsHTRANSFORM
*transform;
ssize_t
i;
size_t
number_threads;
number_threads=(size_t) GetMagickResourceLimit(ThreadResource);
transform=(cmsHTRANSFORM *) AcquireQuantumMemory(number_threads,
sizeof(*transform));
if (transform == (cmsHTRANSFORM *) NULL)
return((cmsHTRANSFORM *) NULL);
(void) memset(transform,0,number_threads*sizeof(*transform));
for (i=0; i < (ssize_t) number_threads; i++)
{
transform[i]=cmsCreateTransformTHR(cms_context,source_info->profile,
source_info->type,target_info->profile,target_info->type,
target_info->intent,flags);
if (transform[i] == (cmsHTRANSFORM) NULL)
return(DestroyTransformThreadSet(transform));
}
return(transform);
}
static void CMSExceptionHandler(cmsContext context,cmsUInt32Number severity,
const char *message)
{
CMSExceptionInfo
*cms_exception;
ExceptionInfo
*exception;
Image
*image;
cms_exception=(CMSExceptionInfo *) cmsGetContextUserData(context);
if (cms_exception == (CMSExceptionInfo *) NULL)
return;
exception=cms_exception->exception;
if (exception == (ExceptionInfo *) NULL)
return;
image=cms_exception->image;
if (image == (Image *) NULL)
{
(void) ThrowMagickException(exception,GetMagickModule(),ImageWarning,
"UnableToTransformColorspace","`%s'","unknown context");
return;
}
if (image->debug != MagickFalse)
(void) LogMagickEvent(TransformEvent,GetMagickModule(),"lcms: #%u, %s",
severity,message != (char *) NULL ? message : "no message");
(void) ThrowMagickException(exception,GetMagickModule(),ImageWarning,
"UnableToTransformColorspace","`%s', %s (#%u)",image->filename,
message != (char *) NULL ? message : "no message",severity);
}
static void TransformDoublePixels(const int id,const Image* image,
const LCMSInfo *source_info,const LCMSInfo *target_info,
const cmsHTRANSFORM *transform,Quantum *q)
{
#define GetLCMSPixel(source_info,pixel) \
(source_info->scale*QuantumScale*(pixel)+source_info->translate)
#define SetLCMSPixel(target_info,pixel) \
ClampToQuantum(target_info->scale*QuantumRange*(pixel)+target_info->translate)
double
*p;
ssize_t
x;
p=(double *) source_info->pixels[id];
for (x=0; x < (ssize_t) image->columns; x++)
{
*p++=GetLCMSPixel(source_info,GetPixelRed(image,q));
if (source_info->channels > 1)
{
*p++=GetLCMSPixel(source_info,GetPixelGreen(image,q));
*p++=GetLCMSPixel(source_info,GetPixelBlue(image,q));
}
if (source_info->channels > 3)
*p++=GetLCMSPixel(source_info,GetPixelBlack(image,q));
q+=GetPixelChannels(image);
}
cmsDoTransform(transform[id],source_info->pixels[id],
target_info->pixels[id],(unsigned int) image->columns);
p=(double *) target_info->pixels[id];
q-=GetPixelChannels(image)*image->columns;
for (x=0; x < (ssize_t) image->columns; x++)
{
if (target_info->channels == 1)
SetPixelGray(image,SetLCMSPixel(target_info,*p),q);
else
SetPixelRed(image,SetLCMSPixel(target_info,*p),q);
p++;
if (target_info->channels > 1)
{
SetPixelGreen(image,SetLCMSPixel(target_info,*p),q);
p++;
SetPixelBlue(image,SetLCMSPixel(target_info,*p),q);
p++;
}
if (target_info->channels > 3)
{
SetPixelBlack(image,SetLCMSPixel(target_info,*p),q);
p++;
}
q+=GetPixelChannels(image);
}
}
static void TransformQuantumPixels(const int id,const Image* image,
const LCMSInfo *source_info,const LCMSInfo *target_info,
const cmsHTRANSFORM *transform,Quantum *q)
{
Quantum
*p;
ssize_t
x;
p=(Quantum *) source_info->pixels[id];
for (x=0; x < (ssize_t) image->columns; x++)
{
*p++=GetPixelRed(image,q);
if (source_info->channels > 1)
{
*p++=GetPixelGreen(image,q);
*p++=GetPixelBlue(image,q);
}
if (source_info->channels > 3)
*p++=GetPixelBlack(image,q);
q+=GetPixelChannels(image);
}
cmsDoTransform(transform[id],source_info->pixels[id],
target_info->pixels[id],(unsigned int) image->columns);
p=(Quantum *) target_info->pixels[id];
q-=GetPixelChannels(image)*image->columns;
for (x=0; x < (ssize_t) image->columns; x++)
{
if (target_info->channels == 1)
SetPixelGray(image,*p++,q);
else
SetPixelRed(image,*p++,q);
if (target_info->channels > 1)
{
SetPixelGreen(image,*p++,q);
SetPixelBlue(image,*p++,q);
}
if (target_info->channels > 3)
SetPixelBlack(image,*p++,q);
q+=GetPixelChannels(image);
}
}
#endif
static MagickBooleanType SetsRGBImageProfile(Image *image,
ExceptionInfo *exception)
{
static unsigned char
sRGBProfile[] =
{
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0x86, 0x0e, 0x86, 0x72, 0x86, 0xd7, 0x87, 0x3b, 0x87, 0x9f, 0x88, 0x04,
0x88, 0x69, 0x88, 0xce, 0x89, 0x33, 0x89, 0x99, 0x89, 0xfe, 0x8a, 0x64,
0x8a, 0xca, 0x8b, 0x30, 0x8b, 0x96, 0x8b, 0xfc, 0x8c, 0x63, 0x8c, 0xca,
0x8d, 0x31, 0x8d, 0x98, 0x8d, 0xff, 0x8e, 0x66, 0x8e, 0xce, 0x8f, 0x36,
0x8f, 0x9e, 0x90, 0x06, 0x90, 0x6e, 0x90, 0xd6, 0x91, 0x3f, 0x91, 0xa8,
0x92, 0x11, 0x92, 0x7a, 0x92, 0xe3, 0x93, 0x4d, 0x93, 0xb6, 0x94, 0x20,
0x94, 0x8a, 0x94, 0xf4, 0x95, 0x5f, 0x95, 0xc9, 0x96, 0x34, 0x96, 0x9f,
0x97, 0x0a, 0x97, 0x75, 0x97, 0xe0, 0x98, 0x4c, 0x98, 0xb8, 0x99, 0x24,
0x99, 0x90, 0x99, 0xfc, 0x9a, 0x68, 0x9a, 0xd5, 0x9b, 0x42, 0x9b, 0xaf,
0x9c, 0x1c, 0x9c, 0x89, 0x9c, 0xf7, 0x9d, 0x64, 0x9d, 0xd2, 0x9e, 0x40,
0x9e, 0xae, 0x9f, 0x1d, 0x9f, 0x8b, 0x9f, 0xfa, 0xa0, 0x69, 0xa0, 0xd8,
0xa1, 0x47, 0xa1, 0xb6, 0xa2, 0x26, 0xa2, 0x96, 0xa3, 0x06, 0xa3, 0x76,
0xa3, 0xe6, 0xa4, 0x56, 0xa4, 0xc7, 0xa5, 0x38, 0xa5, 0xa9, 0xa6, 0x1a,
0xa6, 0x8b, 0xa6, 0xfd, 0xa7, 0x6e, 0xa7, 0xe0, 0xa8, 0x52, 0xa8, 0xc4,
0xa9, 0x37, 0xa9, 0xa9, 0xaa, 0x1c, 0xaa, 0x8f, 0xab, 0x02, 0xab, 0x75,
0xab, 0xe9, 0xac, 0x5c, 0xac, 0xd0, 0xad, 0x44, 0xad, 0xb8, 0xae, 0x2d,
0xae, 0xa1, 0xaf, 0x16, 0xaf, 0x8b, 0xb0, 0x00, 0xb0, 0x75, 0xb0, 0xea,
0xb1, 0x60, 0xb1, 0xd6, 0xb2, 0x4b, 0xb2, 0xc2, 0xb3, 0x38, 0xb3, 0xae,
0xb4, 0x25, 0xb4, 0x9c, 0xb5, 0x13, 0xb5, 0x8a, 0xb6, 0x01, 0xb6, 0x79,
0xb6, 0xf0, 0xb7, 0x68, 0xb7, 0xe0, 0xb8, 0x59, 0xb8, 0xd1, 0xb9, 0x4a,
0xb9, 0xc2, 0xba, 0x3b, 0xba, 0xb5, 0xbb, 0x2e, 0xbb, 0xa7, 0xbc, 0x21,
0xbc, 0x9b, 0xbd, 0x15, 0xbd, 0x8f, 0xbe, 0x0a, 0xbe, 0x84, 0xbe, 0xff,
0xbf, 0x7a, 0xbf, 0xf5, 0xc0, 0x70, 0xc0, 0xec, 0xc1, 0x67, 0xc1, 0xe3,
0xc2, 0x5f, 0xc2, 0xdb, 0xc3, 0x58, 0xc3, 0xd4, 0xc4, 0x51, 0xc4, 0xce,
0xc5, 0x4b, 0xc5, 0xc8, 0xc6, 0x46, 0xc6, 0xc3, 0xc7, 0x41, 0xc7, 0xbf,
0xc8, 0x3d, 0xc8, 0xbc, 0xc9, 0x3a, 0xc9, 0xb9, 0xca, 0x38, 0xca, 0xb7,
0xcb, 0x36, 0xcb, 0xb6, 0xcc, 0x35, 0xcc, 0xb5, 0xcd, 0x35, 0xcd, 0xb5,
0xce, 0x36, 0xce, 0xb6, 0xcf, 0x37, 0xcf, 0xb8, 0xd0, 0x39, 0xd0, 0xba,
0xd1, 0x3c, 0xd1, 0xbe, 0xd2, 0x3f, 0xd2, 0xc1, 0xd3, 0x44, 0xd3, 0xc6,
0xd4, 0x49, 0xd4, 0xcb, 0xd5, 0x4e, 0xd5, 0xd1, 0xd6, 0x55, 0xd6, 0xd8,
0xd7, 0x5c, 0xd7, 0xe0, 0xd8, 0x64, 0xd8, 0xe8, 0xd9, 0x6c, 0xd9, 0xf1,
0xda, 0x76, 0xda, 0xfb, 0xdb, 0x80, 0xdc, 0x05, 0xdc, 0x8a, 0xdd, 0x10,
0xdd, 0x96, 0xde, 0x1c, 0xde, 0xa2, 0xdf, 0x29, 0xdf, 0xaf, 0xe0, 0x36,
0xe0, 0xbd, 0xe1, 0x44, 0xe1, 0xcc, 0xe2, 0x53, 0xe2, 0xdb, 0xe3, 0x63,
0xe3, 0xeb, 0xe4, 0x73, 0xe4, 0xfc, 0xe5, 0x84, 0xe6, 0x0d, 0xe6, 0x96,
0xe7, 0x1f, 0xe7, 0xa9, 0xe8, 0x32, 0xe8, 0xbc, 0xe9, 0x46, 0xe9, 0xd0,
0xea, 0x5b, 0xea, 0xe5, 0xeb, 0x70, 0xeb, 0xfb, 0xec, 0x86, 0xed, 0x11,
0xed, 0x9c, 0xee, 0x28, 0xee, 0xb4, 0xef, 0x40, 0xef, 0xcc, 0xf0, 0x58,
0xf0, 0xe5, 0xf1, 0x72, 0xf1, 0xff, 0xf2, 0x8c, 0xf3, 0x19, 0xf3, 0xa7,
0xf4, 0x34, 0xf4, 0xc2, 0xf5, 0x50, 0xf5, 0xde, 0xf6, 0x6d, 0xf6, 0xfb,
0xf7, 0x8a, 0xf8, 0x19, 0xf8, 0xa8, 0xf9, 0x38, 0xf9, 0xc7, 0xfa, 0x57,
0xfa, 0xe7, 0xfb, 0x77, 0xfc, 0x07, 0xfc, 0x98, 0xfd, 0x29, 0xfd, 0xba,
0xfe, 0x4b, 0xfe, 0xdc, 0xff, 0x6d, 0xff, 0xff
};
StringInfo
*profile;
MagickBooleanType
status;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (GetImageProfile(image,"icc") != (const StringInfo *) NULL)
return(MagickFalse);
profile=AcquireStringInfo(sizeof(sRGBProfile));
SetStringInfoDatum(profile,sRGBProfile);
status=SetImageProfile(image,"icc",profile,exception);
profile=DestroyStringInfo(profile);
return(status);
}
MagickExport MagickBooleanType ProfileImage(Image *image,const char *name,
const void *datum,const size_t length,ExceptionInfo *exception)
{
#define ProfileImageTag "Profile/Image"
#ifndef TYPE_XYZ_8
#define TYPE_XYZ_8 (COLORSPACE_SH(PT_XYZ)|CHANNELS_SH(3)|BYTES_SH(1))
#endif
#define ThrowProfileException(severity,tag,context) \
{ \
if (profile != (StringInfo *) NULL) \
profile=DestroyStringInfo(profile); \
if (cms_context != (cmsContext) NULL) \
cmsDeleteContext(cms_context); \
if (source_info.profile != (cmsHPROFILE) NULL) \
(void) cmsCloseProfile(source_info.profile); \
if (target_info.profile != (cmsHPROFILE) NULL) \
(void) cmsCloseProfile(target_info.profile); \
ThrowBinaryException(severity,tag,context); \
}
MagickBooleanType
status;
StringInfo
*profile;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(name != (const char *) NULL);
if ((datum == (const void *) NULL) || (length == 0))
{
char
*next;
/*
Delete image profile(s).
*/
ResetImageProfileIterator(image);
for (next=GetNextImageProfile(image); next != (const char *) NULL; )
{
if (IsOptionMember(next,name) != MagickFalse)
{
(void) DeleteImageProfile(image,next);
ResetImageProfileIterator(image);
}
next=GetNextImageProfile(image);
}
return(MagickTrue);
}
/*
Add a ICC, IPTC, or generic profile to the image.
*/
status=MagickTrue;
profile=AcquireStringInfo((size_t) length);
SetStringInfoDatum(profile,(unsigned char *) datum);
if ((LocaleCompare(name,"icc") != 0) && (LocaleCompare(name,"icm") != 0))
status=SetImageProfile(image,name,profile,exception);
else
{
const StringInfo
*icc_profile;
icc_profile=GetImageProfile(image,"icc");
if ((icc_profile != (const StringInfo *) NULL) &&
(CompareStringInfo(icc_profile,profile) == 0))
{
const char
*value;
value=GetImageProperty(image,"exif:ColorSpace",exception);
(void) value;
if (LocaleCompare(value,"1") != 0)
(void) SetsRGBImageProfile(image,exception);
value=GetImageProperty(image,"exif:InteroperabilityIndex",exception);
if (LocaleCompare(value,"R98.") != 0)
(void) SetsRGBImageProfile(image,exception);
icc_profile=GetImageProfile(image,"icc");
}
if ((icc_profile != (const StringInfo *) NULL) &&
(CompareStringInfo(icc_profile,profile) == 0))
{
profile=DestroyStringInfo(profile);
return(MagickTrue);
}
#if !defined(MAGICKCORE_LCMS_DELEGATE)
(void) ThrowMagickException(exception,GetMagickModule(),
MissingDelegateWarning,"DelegateLibrarySupportNotBuiltIn",
"'%s' (LCMS)",image->filename);
#else
{
cmsContext
cms_context;
CMSExceptionInfo
cms_exception;
LCMSInfo
source_info,
target_info;
/*
Transform pixel colors as defined by the color profiles.
*/
cms_exception.image=image;
cms_exception.exception=exception;
cms_context=cmsCreateContext(NULL,&cms_exception);
if (cms_context == (cmsContext) NULL)
{
profile=DestroyStringInfo(profile);
ThrowBinaryException(ResourceLimitError,
"ColorspaceColorProfileMismatch",name);
}
cmsSetLogErrorHandlerTHR(cms_context,CMSExceptionHandler);
source_info.profile=cmsOpenProfileFromMemTHR(cms_context,
GetStringInfoDatum(profile),(cmsUInt32Number)
GetStringInfoLength(profile));
if (source_info.profile == (cmsHPROFILE) NULL)
{
profile=DestroyStringInfo(profile);
cmsDeleteContext(cms_context);
ThrowBinaryException(ResourceLimitError,
"ColorspaceColorProfileMismatch",name);
}
if ((cmsGetDeviceClass(source_info.profile) != cmsSigLinkClass) &&
(icc_profile == (StringInfo *) NULL))
status=SetImageProfile(image,name,profile,exception);
else
{
CacheView
*image_view;
cmsColorSpaceSignature
signature;
cmsHTRANSFORM
*magick_restrict transform;
cmsUInt32Number
flags;
#if !defined(MAGICKCORE_HDRI_SUPPORT)
const char
*artifact;
#endif
MagickBooleanType
highres;
MagickOffsetType
progress;
ssize_t
y;
target_info.profile=(cmsHPROFILE) NULL;
if (icc_profile != (StringInfo *) NULL)
{
target_info.profile=source_info.profile;
source_info.profile=cmsOpenProfileFromMemTHR(cms_context,
GetStringInfoDatum(icc_profile),
(cmsUInt32Number) GetStringInfoLength(icc_profile));
if (source_info.profile == (cmsHPROFILE) NULL)
ThrowProfileException(ResourceLimitError,
"ColorspaceColorProfileMismatch",name);
}
highres=MagickTrue;
#if !defined(MAGICKCORE_HDRI_SUPPORT)
artifact=GetImageArtifact(image,"profile:highres-transform");
if (IsStringFalse(artifact) != MagickFalse)
highres=MagickFalse;
#endif
source_info.scale=1.0;
source_info.translate=0.0;
source_info.colorspace=sRGBColorspace;
source_info.channels=3;
switch (cmsGetColorSpace(source_info.profile))
{
case cmsSigCmykData:
{
source_info.colorspace=CMYKColorspace;
source_info.channels=4;
#if (MAGICKCORE_QUANTUM_DEPTH == 8)
if (highres == MagickFalse)
source_info.type=(cmsUInt32Number) TYPE_CMYK_8;
else
#elif (MAGICKCORE_QUANTUM_DEPTH == 16)
if (highres == MagickFalse)
source_info.type=(cmsUInt32Number) TYPE_CMYK_16;
else
#endif
{
source_info.type=(cmsUInt32Number) TYPE_CMYK_DBL;
source_info.scale=100.0;
}
break;
}
case cmsSigGrayData:
{
source_info.colorspace=GRAYColorspace;
source_info.channels=1;
#if (MAGICKCORE_QUANTUM_DEPTH == 8)
if (highres == MagickFalse)
source_info.type=(cmsUInt32Number) TYPE_GRAY_8;
else
#elif (MAGICKCORE_QUANTUM_DEPTH == 16)
if (highres == MagickFalse)
source_info.type=(cmsUInt32Number) TYPE_GRAY_16;
else
#endif
source_info.type=(cmsUInt32Number) TYPE_GRAY_DBL;
break;
}
case cmsSigLabData:
{
source_info.colorspace=LabColorspace;
#if (MAGICKCORE_QUANTUM_DEPTH == 8)
if (highres == MagickFalse)
source_info.type=(cmsUInt32Number) TYPE_Lab_8;
else
#elif (MAGICKCORE_QUANTUM_DEPTH == 16)
if (highres == MagickFalse)
source_info.type=(cmsUInt32Number) TYPE_Lab_16;
else
#endif
{
source_info.type=(cmsUInt32Number) TYPE_Lab_DBL;
source_info.scale=100.0;
source_info.translate=(-0.5);
}
break;
}
case cmsSigRgbData:
{
source_info.colorspace=sRGBColorspace;
#if (MAGICKCORE_QUANTUM_DEPTH == 8)
if (highres == MagickFalse)
source_info.type=(cmsUInt32Number) TYPE_RGB_8;
else
#elif (MAGICKCORE_QUANTUM_DEPTH == 16)
if (highres == MagickFalse)
source_info.type=(cmsUInt32Number) TYPE_RGB_16;
else
#endif
source_info.type=(cmsUInt32Number) TYPE_RGB_DBL;
break;
}
case cmsSigXYZData:
{
source_info.colorspace=XYZColorspace;
#if (MAGICKCORE_QUANTUM_DEPTH == 8)
if (highres == MagickFalse)
source_info.type=(cmsUInt32Number) TYPE_XYZ_8;
else
#elif (MAGICKCORE_QUANTUM_DEPTH == 16)
if (highres == MagickFalse)
source_info.type=(cmsUInt32Number) TYPE_XYZ_16;
else
#endif
source_info.type=(cmsUInt32Number) TYPE_XYZ_DBL;
break;
}
default:
ThrowProfileException(ImageError,
"ColorspaceColorProfileMismatch",name);
}
signature=cmsGetPCS(source_info.profile);
if (target_info.profile != (cmsHPROFILE) NULL)
signature=cmsGetColorSpace(target_info.profile);
target_info.scale=1.0;
target_info.translate=0.0;
target_info.channels=3;
switch (signature)
{
case cmsSigCmykData:
{
target_info.colorspace=CMYKColorspace;
target_info.channels=4;
#if (MAGICKCORE_QUANTUM_DEPTH == 8)
if (highres == MagickFalse)
target_info.type=(cmsUInt32Number) TYPE_CMYK_8;
else
#elif (MAGICKCORE_QUANTUM_DEPTH == 16)
if (highres == MagickFalse)
target_info.type=(cmsUInt32Number) TYPE_CMYK_16;
else
#endif
{
target_info.type=(cmsUInt32Number) TYPE_CMYK_DBL;
target_info.scale=0.01;
}
break;
}
case cmsSigGrayData:
{
target_info.colorspace=GRAYColorspace;
target_info.channels=1;
#if (MAGICKCORE_QUANTUM_DEPTH == 8)
if (highres == MagickFalse)
target_info.type=(cmsUInt32Number) TYPE_GRAY_8;
else
#elif (MAGICKCORE_QUANTUM_DEPTH == 16)
if (highres == MagickFalse)
target_info.type=(cmsUInt32Number) TYPE_GRAY_16;
else
#endif
target_info.type=(cmsUInt32Number) TYPE_GRAY_DBL;
break;
}
case cmsSigLabData:
{
target_info.colorspace=LabColorspace;
#if (MAGICKCORE_QUANTUM_DEPTH == 8)
if (highres == MagickFalse)
target_info.type=(cmsUInt32Number) TYPE_Lab_8;
else
#elif (MAGICKCORE_QUANTUM_DEPTH == 16)
if (highres == MagickFalse)
target_info.type=(cmsUInt32Number) TYPE_Lab_16;
else
#endif
{
target_info.type=(cmsUInt32Number) TYPE_Lab_DBL;
target_info.scale=0.01;
target_info.translate=0.5;
}
break;
}
case cmsSigRgbData:
{
target_info.colorspace=sRGBColorspace;
#if (MAGICKCORE_QUANTUM_DEPTH == 8)
if (highres == MagickFalse)
target_info.type=(cmsUInt32Number) TYPE_RGB_8;
else
#elif (MAGICKCORE_QUANTUM_DEPTH == 16)
if (highres == MagickFalse)
target_info.type=(cmsUInt32Number) TYPE_RGB_16;
else
#endif
target_info.type=(cmsUInt32Number) TYPE_RGB_DBL;
break;
}
case cmsSigXYZData:
{
target_info.colorspace=XYZColorspace;
#if (MAGICKCORE_QUANTUM_DEPTH == 8)
if (highres == MagickFalse)
target_info.type=(cmsUInt32Number) TYPE_XYZ_8;
else
#elif (MAGICKCORE_QUANTUM_DEPTH == 16)
if (highres == MagickFalse)
source_info.type=(cmsUInt32Number) TYPE_XYZ_16;
else
#endif
target_info.type=(cmsUInt32Number) TYPE_XYZ_DBL;
break;
}
default:
ThrowProfileException(ImageError,
"ColorspaceColorProfileMismatch",name);
}
switch (image->rendering_intent)
{
case AbsoluteIntent:
{
target_info.intent=INTENT_ABSOLUTE_COLORIMETRIC;
break;
}
case PerceptualIntent:
{
target_info.intent=INTENT_PERCEPTUAL;
break;
}
case RelativeIntent:
{
target_info.intent=INTENT_RELATIVE_COLORIMETRIC;
break;
}
case SaturationIntent:
{
target_info.intent=INTENT_SATURATION;
break;
}
default:
{
target_info.intent=INTENT_PERCEPTUAL;
break;
}
}
flags=cmsFLAGS_HIGHRESPRECALC;
#if defined(cmsFLAGS_BLACKPOINTCOMPENSATION)
if (image->black_point_compensation != MagickFalse)
flags|=cmsFLAGS_BLACKPOINTCOMPENSATION;
#endif
transform=AcquireTransformThreadSet(&source_info,&target_info,
flags,cms_context);
if (transform == (cmsHTRANSFORM *) NULL)
ThrowProfileException(ImageError,"UnableToCreateColorTransform",
name);
/*
Transform image as dictated by the source & target image profiles.
*/
source_info.pixels=AcquirePixelThreadSet(image->columns,
source_info.channels,highres);
target_info.pixels=AcquirePixelThreadSet(image->columns,
target_info.channels,highres);
if ((source_info.pixels == (void **) NULL) ||
(target_info.pixels == (void **) NULL))
{
target_info.pixels=DestroyPixelThreadSet(target_info.pixels);
source_info.pixels=DestroyPixelThreadSet(source_info.pixels);
transform=DestroyTransformThreadSet(transform);
ThrowProfileException(ResourceLimitError,
"MemoryAllocationFailed",image->filename);
}
if (SetImageStorageClass(image,DirectClass,exception) == MagickFalse)
{
target_info.pixels=DestroyPixelThreadSet(target_info.pixels);
source_info.pixels=DestroyPixelThreadSet(source_info.pixels);
transform=DestroyTransformThreadSet(transform);
if (source_info.profile != (cmsHPROFILE) NULL)
(void) cmsCloseProfile(source_info.profile);
if (target_info.profile != (cmsHPROFILE) NULL)
(void) cmsCloseProfile(target_info.profile);
return(MagickFalse);
}
if (target_info.colorspace == CMYKColorspace)
(void) SetImageColorspace(image,target_info.colorspace,exception);
progress=0;
image_view=AcquireAuthenticCacheView(image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static) shared(status) \
magick_number_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
const int
id = GetOpenMPThreadId();
MagickBooleanType
sync;
Quantum
*magick_restrict q;
if (status == MagickFalse)
continue;
q=GetCacheViewAuthenticPixels(image_view,0,y,image->columns,1,
exception);
if (q == (Quantum *) NULL)
{
status=MagickFalse;
continue;
}
if (highres != MagickFalse)
TransformDoublePixels(id,image,&source_info,&target_info,transform,q);
else
TransformQuantumPixels(id,image,&source_info,&target_info,transform,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 atomic
#endif
progress++;
proceed=SetImageProgress(image,ProfileImageTag,progress,
image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
image_view=DestroyCacheView(image_view);
(void) SetImageColorspace(image,target_info.colorspace,exception);
switch (signature)
{
case cmsSigRgbData:
{
image->type=image->alpha_trait == UndefinedPixelTrait ?
TrueColorType : TrueColorAlphaType;
break;
}
case cmsSigCmykData:
{
image->type=image->alpha_trait == UndefinedPixelTrait ?
ColorSeparationType : ColorSeparationAlphaType;
break;
}
case cmsSigGrayData:
{
image->type=image->alpha_trait == UndefinedPixelTrait ?
GrayscaleType : GrayscaleAlphaType;
break;
}
default:
break;
}
target_info.pixels=DestroyPixelThreadSet(target_info.pixels);
source_info.pixels=DestroyPixelThreadSet(source_info.pixels);
transform=DestroyTransformThreadSet(transform);
if ((status != MagickFalse) &&
(cmsGetDeviceClass(source_info.profile) != cmsSigLinkClass))
status=SetImageProfile(image,name,profile,exception);
if (target_info.profile != (cmsHPROFILE) NULL)
(void) cmsCloseProfile(target_info.profile);
}
(void) cmsCloseProfile(source_info.profile);
cmsDeleteContext(cms_context);
}
#endif
}
profile=DestroyStringInfo(profile);
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% R e m o v e I m a g e P r o f i l e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% RemoveImageProfile() removes a named profile from the image and returns its
% value.
%
% The format of the RemoveImageProfile method is:
%
% void *RemoveImageProfile(Image *image,const char *name)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o name: the profile name.
%
*/
MagickExport StringInfo *RemoveImageProfile(Image *image,const char *name)
{
StringInfo
*profile;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if (image->profiles == (SplayTreeInfo *) NULL)
return((StringInfo *) NULL);
WriteTo8BimProfile(image,name,(StringInfo *) NULL);
profile=(StringInfo *) RemoveNodeFromSplayTree((SplayTreeInfo *)
image->profiles,name);
return(profile);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% R e s e t P r o f i l e I t e r a t o r %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ResetImageProfileIterator() resets the image profile iterator. Use it in
% conjunction with GetNextImageProfile() to iterate over all the profiles
% associated with an image.
%
% The format of the ResetImageProfileIterator method is:
%
% ResetImageProfileIterator(Image *image)
%
% A description of each parameter follows:
%
% o image: the image.
%
*/
MagickExport void ResetImageProfileIterator(const Image *image)
{
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if (image->profiles == (SplayTreeInfo *) NULL)
return;
ResetSplayTreeIterator((SplayTreeInfo *) image->profiles);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S e t I m a g e P r o f i l e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SetImageProfile() adds a named profile to the image. If a profile with the
% same name already exists, it is replaced. This method differs from the
% ProfileImage() method in that it does not apply CMS color profiles.
%
% The format of the SetImageProfile method is:
%
% MagickBooleanType SetImageProfile(Image *image,const char *name,
% const StringInfo *profile)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o name: the profile name, for example icc, exif, and 8bim (8bim is the
% Photoshop wrapper for iptc profiles).
%
% o profile: A StringInfo structure that contains the named profile.
%
*/
static void *DestroyProfile(void *profile)
{
return((void *) DestroyStringInfo((StringInfo *) profile));
}
static inline const unsigned char *ReadResourceByte(const unsigned char *p,
unsigned char *quantum)
{
*quantum=(*p++);
return(p);
}
static inline const unsigned char *ReadResourceLong(const unsigned char *p,
unsigned int *quantum)
{
*quantum=(unsigned int) (*p++) << 24;
*quantum|=(unsigned int) (*p++) << 16;
*quantum|=(unsigned int) (*p++) << 8;
*quantum|=(unsigned int) (*p++);
return(p);
}
static inline const unsigned char *ReadResourceShort(const unsigned char *p,
unsigned short *quantum)
{
*quantum=(unsigned short) (*p++) << 8;
*quantum|=(unsigned short) (*p++);
return(p);
}
static inline void WriteResourceLong(unsigned char *p,
const unsigned int quantum)
{
unsigned char
buffer[4];
buffer[0]=(unsigned char) (quantum >> 24);
buffer[1]=(unsigned char) (quantum >> 16);
buffer[2]=(unsigned char) (quantum >> 8);
buffer[3]=(unsigned char) quantum;
(void) memcpy(p,buffer,4);
}
static void WriteTo8BimProfile(Image *image,const char *name,
const StringInfo *profile)
{
const unsigned char
*datum,
*q;
const unsigned char
*p;
size_t
length;
StringInfo
*profile_8bim;
ssize_t
count;
unsigned char
length_byte;
unsigned int
value;
unsigned short
id,
profile_id;
if (LocaleCompare(name,"icc") == 0)
profile_id=0x040f;
else
if (LocaleCompare(name,"iptc") == 0)
profile_id=0x0404;
else
if (LocaleCompare(name,"xmp") == 0)
profile_id=0x0424;
else
return;
profile_8bim=(StringInfo *) GetValueFromSplayTree((SplayTreeInfo *)
image->profiles,"8bim");
if (profile_8bim == (StringInfo *) NULL)
return;
datum=GetStringInfoDatum(profile_8bim);
length=GetStringInfoLength(profile_8bim);
for (p=datum; p < (datum+length-16); )
{
q=p;
if (LocaleNCompare((char *) p,"8BIM",4) != 0)
break;
p+=4;
p=ReadResourceShort(p,&id);
p=ReadResourceByte(p,&length_byte);
p+=length_byte;
if (((length_byte+1) & 0x01) != 0)
p++;
if (p > (datum+length-4))
break;
p=ReadResourceLong(p,&value);
count=(ssize_t) value;
if ((count & 0x01) != 0)
count++;
if ((count < 0) || (p > (datum+length-count)) || (count > (ssize_t) length))
break;
if (id != profile_id)
p+=count;
else
{
size_t
extent,
offset;
ssize_t
extract_extent;
StringInfo
*extract_profile;
extract_extent=0;
extent=(datum+length)-(p+count);
if (profile == (StringInfo *) NULL)
{
offset=(q-datum);
extract_profile=AcquireStringInfo(offset+extent);
(void) memcpy(extract_profile->datum,datum,offset);
}
else
{
offset=(p-datum);
extract_extent=profile->length;
if ((extract_extent & 0x01) != 0)
extract_extent++;
extract_profile=AcquireStringInfo(offset+extract_extent+extent);
(void) memcpy(extract_profile->datum,datum,offset-4);
WriteResourceLong(extract_profile->datum+offset-4,(unsigned int)
profile->length);
(void) memcpy(extract_profile->datum+offset,
profile->datum,profile->length);
}
(void) memcpy(extract_profile->datum+offset+extract_extent,
p+count,extent);
(void) AddValueToSplayTree((SplayTreeInfo *) image->profiles,
ConstantString("8bim"),CloneStringInfo(extract_profile));
extract_profile=DestroyStringInfo(extract_profile);
break;
}
}
}
static void GetProfilesFromResourceBlock(Image *image,
const StringInfo *resource_block,ExceptionInfo *exception)
{
const unsigned char
*datum;
const unsigned char
*p;
size_t
length;
ssize_t
count;
StringInfo
*profile;
unsigned char
length_byte;
unsigned int
value;
unsigned short
id;
datum=GetStringInfoDatum(resource_block);
length=GetStringInfoLength(resource_block);
for (p=datum; p < (datum+length-16); )
{
if (LocaleNCompare((char *) p,"8BIM",4) != 0)
break;
p+=4;
p=ReadResourceShort(p,&id);
p=ReadResourceByte(p,&length_byte);
p+=length_byte;
if (((length_byte+1) & 0x01) != 0)
p++;
if (p > (datum+length-4))
break;
p=ReadResourceLong(p,&value);
count=(ssize_t) value;
if ((p > (datum+length-count)) || (count > (ssize_t) length) || (count < 0))
break;
switch (id)
{
case 0x03ed:
{
unsigned int
resolution;
unsigned short
units;
/*
Resolution.
*/
if (count < 10)
break;
p=ReadResourceLong(p,&resolution);
image->resolution.x=((double) resolution)/65536.0;
p=ReadResourceShort(p,&units)+2;
p=ReadResourceLong(p,&resolution)+4;
image->resolution.y=((double) resolution)/65536.0;
/*
Values are always stored as pixels per inch.
*/
if ((ResolutionType) units != PixelsPerCentimeterResolution)
image->units=PixelsPerInchResolution;
else
{
image->units=PixelsPerCentimeterResolution;
image->resolution.x/=2.54;
image->resolution.y/=2.54;
}
break;
}
case 0x0404:
{
/*
IPTC Profile
*/
profile=AcquireStringInfo(count);
SetStringInfoDatum(profile,p);
(void) SetImageProfileInternal(image,"iptc",profile,MagickTrue,
exception);
profile=DestroyStringInfo(profile);
p+=count;
break;
}
case 0x040c:
{
/*
Thumbnail.
*/
p+=count;
break;
}
case 0x040f:
{
/*
ICC Profile.
*/
profile=AcquireStringInfo(count);
SetStringInfoDatum(profile,p);
(void) SetImageProfileInternal(image,"icc",profile,MagickTrue,
exception);
profile=DestroyStringInfo(profile);
p+=count;
break;
}
case 0x0422:
{
/*
EXIF Profile.
*/
profile=AcquireStringInfo(count);
SetStringInfoDatum(profile,p);
(void) SetImageProfileInternal(image,"exif",profile,MagickTrue,
exception);
profile=DestroyStringInfo(profile);
p+=count;
break;
}
case 0x0424:
{
/*
XMP Profile.
*/
profile=AcquireStringInfo(count);
SetStringInfoDatum(profile,p);
(void) SetImageProfileInternal(image,"xmp",profile,MagickTrue,
exception);
profile=DestroyStringInfo(profile);
p+=count;
break;
}
default:
{
p+=count;
break;
}
}
if ((count & 0x01) != 0)
p++;
}
}
static void PatchCorruptProfile(const char *name,StringInfo *profile)
{
unsigned char
*p;
size_t
length;
/*
Detect corrupt profiles and if discovered, repair.
*/
if (LocaleCompare(name,"xmp") == 0)
{
/*
Remove garbage after xpacket end.
*/
p=GetStringInfoDatum(profile);
p=(unsigned char *) strstr((const char *) p,"<?xpacket end=\"w\"?>");
if (p != (unsigned char *) NULL)
{
p+=19;
length=p-GetStringInfoDatum(profile);
if (length != GetStringInfoLength(profile))
{
*p='\0';
SetStringInfoLength(profile,length);
}
}
return;
}
if (LocaleCompare(name,"exif") == 0)
{
/*
Check if profile starts with byte order marker instead of Exif.
*/
p=GetStringInfoDatum(profile);
if ((LocaleNCompare((const char *) p,"MM",2) == 0) ||
(LocaleNCompare((const char *) p,"II",2) == 0))
{
const unsigned char
profile_start[] = "Exif\0\0";
StringInfo
*exif_profile;
exif_profile=AcquireStringInfo(6);
if (exif_profile != (StringInfo *) NULL)
{
SetStringInfoDatum(exif_profile,profile_start);
ConcatenateStringInfo(exif_profile,profile);
SetStringInfoLength(profile,GetStringInfoLength(exif_profile));
SetStringInfo(profile,exif_profile);
exif_profile=DestroyStringInfo(exif_profile);
}
}
}
}
#if defined(MAGICKCORE_XML_DELEGATE)
static MagickBooleanType ValidateXMPProfile(Image *image,
const StringInfo *profile,ExceptionInfo *exception)
{
xmlDocPtr
document;
/*
Parse XML profile.
*/
document=xmlReadMemory((const char *) GetStringInfoDatum(profile),(int)
GetStringInfoLength(profile),"xmp.xml",NULL,XML_PARSE_NOERROR |
XML_PARSE_NOWARNING);
if (document == (xmlDocPtr) NULL)
{
(void) ThrowMagickException(exception,GetMagickModule(),ImageWarning,
"CorruptImageProfile","`%s' (XMP)",image->filename);
return(MagickFalse);
}
xmlFreeDoc(document);
return(MagickTrue);
}
#else
static MagickBooleanType ValidateXMPProfile(Image *image,
const StringInfo *profile,ExceptionInfo *exception)
{
(void) ThrowMagickException(exception,GetMagickModule(),MissingDelegateWarning,
"DelegateLibrarySupportNotBuiltIn","'%s' (XML)",image->filename);
return(MagickFalse);
}
#endif
static MagickBooleanType SetImageProfileInternal(Image *image,const char *name,
const StringInfo *profile,const MagickBooleanType recursive,
ExceptionInfo *exception)
{
char
key[MagickPathExtent];
MagickBooleanType
status;
StringInfo
*clone_profile;
assert(image != (Image *) NULL);
assert(image->signature == MagickCoreSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
clone_profile=CloneStringInfo(profile);
PatchCorruptProfile(name,clone_profile);
if ((LocaleCompare(name,"xmp") == 0) &&
(ValidateXMPProfile(image,clone_profile,exception) == MagickFalse))
{
clone_profile=DestroyStringInfo(clone_profile);
return(MagickTrue);
}
if (image->profiles == (SplayTreeInfo *) NULL)
image->profiles=NewSplayTree(CompareSplayTreeString,RelinquishMagickMemory,
DestroyProfile);
(void) CopyMagickString(key,name,MagickPathExtent);
LocaleLower(key);
status=AddValueToSplayTree((SplayTreeInfo *) image->profiles,
ConstantString(key),clone_profile);
if (status != MagickFalse)
{
if (LocaleCompare(name,"8bim") == 0)
GetProfilesFromResourceBlock(image,clone_profile,exception);
else
if (recursive == MagickFalse)
WriteTo8BimProfile(image,name,clone_profile);
}
return(status);
}
MagickExport MagickBooleanType SetImageProfile(Image *image,const char *name,
const StringInfo *profile,ExceptionInfo *exception)
{
return(SetImageProfileInternal(image,name,profile,MagickFalse,exception));
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S y n c I m a g e P r o f i l e s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SyncImageProfiles() synchronizes image properties with the image profiles.
% Currently we only support updating the EXIF resolution and orientation.
%
% The format of the SyncImageProfiles method is:
%
% MagickBooleanType SyncImageProfiles(Image *image)
%
% A description of each parameter follows:
%
% o image: the image.
%
*/
static inline int ReadProfileByte(unsigned char **p,size_t *length)
{
int
c;
if (*length < 1)
return(EOF);
c=(int) (*(*p)++);
(*length)--;
return(c);
}
static inline signed short ReadProfileShort(const EndianType endian,
unsigned char *buffer)
{
union
{
unsigned int
unsigned_value;
signed int
signed_value;
} quantum;
unsigned short
value;
if (endian == LSBEndian)
{
value=(unsigned short) buffer[1] << 8;
value|=(unsigned short) buffer[0];
quantum.unsigned_value=value & 0xffff;
return(quantum.signed_value);
}
value=(unsigned short) buffer[0] << 8;
value|=(unsigned short) buffer[1];
quantum.unsigned_value=value & 0xffff;
return(quantum.signed_value);
}
static inline signed int ReadProfileLong(const EndianType endian,
unsigned char *buffer)
{
union
{
unsigned int
unsigned_value;
signed int
signed_value;
} quantum;
unsigned int
value;
if (endian == LSBEndian)
{
value=(unsigned int) buffer[3] << 24;
value|=(unsigned int) buffer[2] << 16;
value|=(unsigned int) buffer[1] << 8;
value|=(unsigned int) buffer[0];
quantum.unsigned_value=value & 0xffffffff;
return(quantum.signed_value);
}
value=(unsigned int) buffer[0] << 24;
value|=(unsigned int) buffer[1] << 16;
value|=(unsigned int) buffer[2] << 8;
value|=(unsigned int) buffer[3];
quantum.unsigned_value=value & 0xffffffff;
return(quantum.signed_value);
}
static inline signed int ReadProfileMSBLong(unsigned char **p,size_t *length)
{
signed int
value;
if (*length < 4)
return(0);
value=ReadProfileLong(MSBEndian,*p);
(*length)-=4;
*p+=4;
return(value);
}
static inline signed short ReadProfileMSBShort(unsigned char **p,
size_t *length)
{
signed short
value;
if (*length < 2)
return(0);
value=ReadProfileShort(MSBEndian,*p);
(*length)-=2;
*p+=2;
return(value);
}
static inline void WriteProfileLong(const EndianType endian,
const size_t value,unsigned char *p)
{
unsigned char
buffer[4];
if (endian == LSBEndian)
{
buffer[0]=(unsigned char) value;
buffer[1]=(unsigned char) (value >> 8);
buffer[2]=(unsigned char) (value >> 16);
buffer[3]=(unsigned char) (value >> 24);
(void) memcpy(p,buffer,4);
return;
}
buffer[0]=(unsigned char) (value >> 24);
buffer[1]=(unsigned char) (value >> 16);
buffer[2]=(unsigned char) (value >> 8);
buffer[3]=(unsigned char) value;
(void) memcpy(p,buffer,4);
}
static void WriteProfileShort(const EndianType endian,
const unsigned short value,unsigned char *p)
{
unsigned char
buffer[2];
if (endian == LSBEndian)
{
buffer[0]=(unsigned char) value;
buffer[1]=(unsigned char) (value >> 8);
(void) memcpy(p,buffer,2);
return;
}
buffer[0]=(unsigned char) (value >> 8);
buffer[1]=(unsigned char) value;
(void) memcpy(p,buffer,2);
}
static MagickBooleanType Sync8BimProfile(Image *image,StringInfo *profile)
{
size_t
length;
ssize_t
count;
unsigned char
*p;
unsigned short
id;
length=GetStringInfoLength(profile);
p=GetStringInfoDatum(profile);
while (length != 0)
{
if (ReadProfileByte(&p,&length) != 0x38)
continue;
if (ReadProfileByte(&p,&length) != 0x42)
continue;
if (ReadProfileByte(&p,&length) != 0x49)
continue;
if (ReadProfileByte(&p,&length) != 0x4D)
continue;
if (length < 7)
return(MagickFalse);
id=ReadProfileMSBShort(&p,&length);
count=(ssize_t) ReadProfileByte(&p,&length);
if ((count >= (ssize_t) length) || (count < 0))
return(MagickFalse);
p+=count;
length-=count;
if ((*p & 0x01) == 0)
(void) ReadProfileByte(&p,&length);
count=(ssize_t) ReadProfileMSBLong(&p,&length);
if ((count > (ssize_t) length) || (count < 0))
return(MagickFalse);
if ((id == 0x3ED) && (count == 16))
{
if (image->units == PixelsPerCentimeterResolution)
WriteProfileLong(MSBEndian,(unsigned int) CastDoubleToLong(
image->resolution.x*2.54*65536.0),p);
else
WriteProfileLong(MSBEndian,(unsigned int) CastDoubleToLong(
image->resolution.x*65536.0),p);
WriteProfileShort(MSBEndian,(unsigned short) image->units,p+4);
if (image->units == PixelsPerCentimeterResolution)
WriteProfileLong(MSBEndian,(unsigned int) CastDoubleToLong(
image->resolution.y*2.54*65536.0),p+8);
else
WriteProfileLong(MSBEndian,(unsigned int) CastDoubleToLong(
image->resolution.y*65536.0),p+8);
WriteProfileShort(MSBEndian,(unsigned short) image->units,p+12);
}
p+=count;
length-=count;
}
return(MagickTrue);
}
MagickBooleanType SyncExifProfile(Image *image,StringInfo *profile)
{
#define MaxDirectoryStack 16
#define EXIF_DELIMITER "\n"
#define EXIF_NUM_FORMATS 12
#define TAG_EXIF_OFFSET 0x8769
#define TAG_INTEROP_OFFSET 0xa005
typedef struct _DirectoryInfo
{
unsigned char
*directory;
size_t
entry;
} DirectoryInfo;
DirectoryInfo
directory_stack[MaxDirectoryStack];
EndianType
endian;
size_t
entry,
length,
number_entries;
SplayTreeInfo
*exif_resources;
ssize_t
id,
level,
offset;
static int
format_bytes[] = {0, 1, 1, 2, 4, 8, 1, 1, 2, 4, 8, 4, 8};
unsigned char
*directory,
*exif;
/*
Set EXIF resolution tag.
*/
length=GetStringInfoLength(profile);
exif=GetStringInfoDatum(profile);
if (length < 16)
return(MagickFalse);
id=(ssize_t) ReadProfileShort(LSBEndian,exif);
if ((id != 0x4949) && (id != 0x4D4D))
{
while (length != 0)
{
if (ReadProfileByte(&exif,&length) != 0x45)
continue;
if (ReadProfileByte(&exif,&length) != 0x78)
continue;
if (ReadProfileByte(&exif,&length) != 0x69)
continue;
if (ReadProfileByte(&exif,&length) != 0x66)
continue;
if (ReadProfileByte(&exif,&length) != 0x00)
continue;
if (ReadProfileByte(&exif,&length) != 0x00)
continue;
break;
}
if (length < 16)
return(MagickFalse);
id=(ssize_t) ReadProfileShort(LSBEndian,exif);
}
endian=LSBEndian;
if (id == 0x4949)
endian=LSBEndian;
else
if (id == 0x4D4D)
endian=MSBEndian;
else
return(MagickFalse);
if (ReadProfileShort(endian,exif+2) != 0x002a)
return(MagickFalse);
/*
This the offset to the first IFD.
*/
offset=(ssize_t) ReadProfileLong(endian,exif+4);
if ((offset < 0) || ((size_t) offset >= length))
return(MagickFalse);
directory=exif+offset;
level=0;
entry=0;
exif_resources=NewSplayTree((int (*)(const void *,const void *)) NULL,
(void *(*)(void *)) NULL,(void *(*)(void *)) NULL);
do
{
if (level > 0)
{
level--;
directory=directory_stack[level].directory;
entry=directory_stack[level].entry;
}
if ((directory < exif) || (directory > (exif+length-2)))
break;
/*
Determine how many entries there are in the current IFD.
*/
number_entries=ReadProfileShort(endian,directory);
for ( ; entry < number_entries; entry++)
{
int
components;
unsigned char
*p,
*q;
size_t
number_bytes;
ssize_t
format,
tag_value;
q=(unsigned char *) (directory+2+(12*entry));
if (q > (exif+length-12))
break; /* corrupt EXIF */
if (GetValueFromSplayTree(exif_resources,q) == q)
break;
(void) AddValueToSplayTree(exif_resources,q,q);
tag_value=(ssize_t) ReadProfileShort(endian,q);
format=(ssize_t) ReadProfileShort(endian,q+2);
if ((format < 0) || ((format-1) >= EXIF_NUM_FORMATS))
break;
components=(int) ReadProfileLong(endian,q+4);
if (components < 0)
break; /* corrupt EXIF */
number_bytes=(size_t) components*format_bytes[format];
if ((ssize_t) number_bytes < components)
break; /* prevent overflow */
if (number_bytes <= 4)
p=q+8;
else
{
/*
The directory entry contains an offset.
*/
offset=(ssize_t) ReadProfileLong(endian,q+8);
if ((offset < 0) || ((size_t) (offset+number_bytes) > length))
continue;
if (~length < number_bytes)
continue; /* prevent overflow */
p=(unsigned char *) (exif+offset);
}
switch (tag_value)
{
case 0x011a:
{
(void) WriteProfileLong(endian,(size_t) (image->resolution.x+0.5),p);
if (number_bytes == 8)
(void) WriteProfileLong(endian,1UL,p+4);
break;
}
case 0x011b:
{
(void) WriteProfileLong(endian,(size_t) (image->resolution.y+0.5),p);
if (number_bytes == 8)
(void) WriteProfileLong(endian,1UL,p+4);
break;
}
case 0x0112:
{
if (number_bytes == 4)
{
(void) WriteProfileLong(endian,(size_t) image->orientation,p);
break;
}
(void) WriteProfileShort(endian,(unsigned short) image->orientation,
p);
break;
}
case 0x0128:
{
if (number_bytes == 4)
{
(void) WriteProfileLong(endian,(size_t) (image->units+1),p);
break;
}
(void) WriteProfileShort(endian,(unsigned short) (image->units+1),p);
break;
}
default:
break;
}
if ((tag_value == TAG_EXIF_OFFSET) || (tag_value == TAG_INTEROP_OFFSET))
{
offset=(ssize_t) ReadProfileLong(endian,p);
if (((size_t) offset < length) && (level < (MaxDirectoryStack-2)))
{
directory_stack[level].directory=directory;
entry++;
directory_stack[level].entry=entry;
level++;
directory_stack[level].directory=exif+offset;
directory_stack[level].entry=0;
level++;
if ((directory+2+(12*number_entries)) > (exif+length))
break;
offset=(ssize_t) ReadProfileLong(endian,directory+2+(12*
number_entries));
if ((offset != 0) && ((size_t) offset < length) &&
(level < (MaxDirectoryStack-2)))
{
directory_stack[level].directory=exif+offset;
directory_stack[level].entry=0;
level++;
}
}
break;
}
}
} while (level > 0);
exif_resources=DestroySplayTree(exif_resources);
return(MagickTrue);
}
MagickPrivate MagickBooleanType SyncImageProfiles(Image *image)
{
MagickBooleanType
status;
StringInfo
*profile;
status=MagickTrue;
profile=(StringInfo *) GetImageProfile(image,"8BIM");
if (profile != (StringInfo *) NULL)
if (Sync8BimProfile(image,profile) == MagickFalse)
status=MagickFalse;
profile=(StringInfo *) GetImageProfile(image,"EXIF");
if (profile != (StringInfo *) NULL)
if (SyncExifProfile(image,profile) == MagickFalse)
status=MagickFalse;
return(status);
}
static void UpdateClipPath(unsigned char *blob,size_t length,
const size_t old_columns,const size_t old_rows,
const RectangleInfo *new_geometry)
{
ssize_t
i;
ssize_t
knot_count,
selector;
knot_count=0;
while (length != 0)
{
selector=(ssize_t) ReadProfileMSBShort(&blob,&length);
switch (selector)
{
case 0:
case 3:
{
if (knot_count != 0)
{
blob+=24;
length-=MagickMin(24,(ssize_t) length);
break;
}
/*
Expected subpath length record.
*/
knot_count=(ssize_t) ReadProfileMSBShort(&blob,&length);
blob+=22;
length-=MagickMin(22,(ssize_t) length);
break;
}
case 1:
case 2:
case 4:
case 5:
{
if (knot_count == 0)
{
/*
Unexpected subpath knot.
*/
blob+=24;
length-=MagickMin(24,(ssize_t) length);
break;
}
/*
Add sub-path knot
*/
for (i=0; i < 3; i++)
{
double
x,
y;
signed int
xx,
yy;
y=(double) ReadProfileMSBLong(&blob,&length);
y=y*old_rows/4096.0/4096.0;
y-=new_geometry->y;
yy=(signed int) ((y*4096*4096)/new_geometry->height);
WriteProfileLong(MSBEndian,(size_t) yy,blob-4);
x=(double) ReadProfileMSBLong(&blob,&length);
x=x*old_columns/4096.0/4096.0;
x-=new_geometry->x;
xx=(signed int) ((x*4096*4096)/new_geometry->width);
WriteProfileLong(MSBEndian,(size_t) xx,blob-4);
}
knot_count--;
break;
}
case 6:
case 7:
case 8:
default:
{
blob+=24;
length-=MagickMin(24,(ssize_t) length);
break;
}
}
}
}
MagickPrivate void Update8BIMClipPath(const Image *image,
const size_t old_columns,const size_t old_rows,
const RectangleInfo *new_geometry)
{
const StringInfo
*profile;
size_t
length;
ssize_t
count,
id;
unsigned char
*info;
assert(image != (Image *) NULL);
assert(new_geometry != (RectangleInfo *) NULL);
profile=GetImageProfile(image,"8bim");
if (profile == (StringInfo *) NULL)
return;
length=GetStringInfoLength(profile);
info=GetStringInfoDatum(profile);
while (length > 0)
{
if (ReadProfileByte(&info,&length) != (unsigned char) '8')
continue;
if (ReadProfileByte(&info,&length) != (unsigned char) 'B')
continue;
if (ReadProfileByte(&info,&length) != (unsigned char) 'I')
continue;
if (ReadProfileByte(&info,&length) != (unsigned char) 'M')
continue;
id=(ssize_t) ReadProfileMSBShort(&info,&length);
count=(ssize_t) ReadProfileByte(&info,&length);
if ((count != 0) && ((size_t) count <= length))
{
info+=count;
length-=count;
}
if ((count & 0x01) == 0)
(void) ReadProfileByte(&info,&length);
count=(ssize_t) ReadProfileMSBLong(&info,&length);
if ((count < 0) || ((size_t) count > length))
{
length=0;
continue;
}
if ((id > 1999) && (id < 2999))
UpdateClipPath(info,(size_t) count,old_columns,old_rows,new_geometry);
info+=count;
length-=MagickMin(count,(ssize_t) length);
}
}
|
GB_extractTuples.c | //------------------------------------------------------------------------------
// GB_extractTuples: extract all the tuples from a matrix
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// Extracts all tuples from a matrix, like [I,J,X] = find (A). If any
// parameter I, J and/or X is NULL, then that component is not extracted. The
// size of the I, J, and X arrays (those that are not NULL) is given by nvals,
// which must be at least as large as GrB_nvals (&nvals, A). The values in the
// matrix are typecasted to the type of X, as needed.
// This function does the work for the user-callable GrB_*_extractTuples
// functions.
#include "GB.h"
#define GB_FREE_ALL \
{ \
GB_FREE_WERK (&Ap, Ap_size) ; \
GB_FREE_WERK (&X_bitmap, X_bitmap_size) ; \
}
GrB_Info GB_extractTuples // extract all tuples from a matrix
(
GrB_Index *I_out, // array for returning row indices of tuples
GrB_Index *J_out, // array for returning col indices of tuples
void *X, // array for returning values of tuples
GrB_Index *p_nvals, // I,J,X size on input; # tuples on output
const GB_Type_code xcode, // type of array X
const GrB_Matrix A, // matrix to extract tuples from
GB_Context Context
)
{
//--------------------------------------------------------------------------
// check inputs
//--------------------------------------------------------------------------
GrB_Info info ;
GB_void *restrict X_bitmap = NULL ; size_t X_bitmap_size = 0 ;
int64_t *restrict Ap = NULL ; size_t Ap_size = 0 ;
ASSERT_MATRIX_OK (A, "A to extract", GB0) ;
ASSERT (p_nvals != NULL) ;
// delete any lingering zombies and assemble any pending tuples;
// allow A to remain jumbled
GB_MATRIX_WAIT_IF_PENDING_OR_ZOMBIES (A) ;
GB_BURBLE_DENSE (A, "(A %s) ") ;
ASSERT (xcode <= GB_UDT_code) ;
const GB_Type_code acode = A->type->code ;
// xcode and A must be compatible
if (!GB_code_compatible (xcode, acode))
{
return (GrB_DOMAIN_MISMATCH) ;
}
const int64_t anz = GB_NNZ (A) ;
if (anz == 0)
{
// no work to do
(*p_nvals) = 0 ;
return (GrB_SUCCESS) ;
}
int64_t nvals = *p_nvals ; // size of I,J,X on input
if (nvals < anz && (I_out != NULL || J_out != NULL || X != NULL))
{
// output arrays are not big enough
return (GrB_INSUFFICIENT_SPACE) ;
}
const size_t asize = A->type->size ;
//-------------------------------------------------------------------------
// determine the number of threads to use
//-------------------------------------------------------------------------
GB_GET_NTHREADS_MAX (nthreads_max, chunk, Context) ;
int nthreads = GB_nthreads (anz + A->nvec, chunk, nthreads_max) ;
//-------------------------------------------------------------------------
// handle the CSR/CSC format
//--------------------------------------------------------------------------
GrB_Index *I, *J ;
if (A->is_csc)
{
I = I_out ;
J = J_out ;
}
else
{
I = J_out ;
J = I_out ;
}
//--------------------------------------------------------------------------
// bitmap case
//--------------------------------------------------------------------------
if (GB_IS_BITMAP (A))
{
//----------------------------------------------------------------------
// allocate workspace
//----------------------------------------------------------------------
bool need_typecast = (X != NULL) && (xcode != acode) ;
if (need_typecast)
{
// X must be typecasted
int64_t anzmax = GB_IMAX (anz, 1) ;
X_bitmap = GB_MALLOC_WERK (anzmax*asize, GB_void, &X_bitmap_size) ;
}
Ap = GB_MALLOC_WERK (A->vdim+1, int64_t, &Ap_size) ;
if (Ap == NULL || (need_typecast && X_bitmap == NULL))
{
// out of memory
GB_FREE_ALL ;
return (GrB_OUT_OF_MEMORY) ;
}
//----------------------------------------------------------------------
// extract the tuples
//----------------------------------------------------------------------
// TODO: pass xcode to GB_convert_bitmap_worker and let it do the
// typecasting. This works for now, however.
GB_OK (GB_convert_bitmap_worker (Ap, (int64_t *) I, (int64_t *) J,
(GB_void *) (need_typecast ? X_bitmap : X), NULL, A, Context)) ;
//----------------------------------------------------------------------
// typecast the result if needed
//----------------------------------------------------------------------
if (need_typecast)
{
// typecast the values from X_bitmap into X
GB_cast_array ((GB_void *) X, xcode, X_bitmap,
acode, NULL, asize, anz, nthreads) ;
}
}
else
{
//----------------------------------------------------------------------
// sparse, hypersparse, or full case
//----------------------------------------------------------------------
//----------------------------------------------------------------------
// extract the row indices
//----------------------------------------------------------------------
if (I != NULL)
{
if (A->i == NULL)
{
// A is full; construct the row indices
int64_t avlen = A->vlen ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
I [p] = (p % avlen) ;
}
}
else
{
GB_memcpy (I, A->i, anz * sizeof (int64_t), nthreads) ;
}
}
//----------------------------------------------------------------------
// extract the column indices
//----------------------------------------------------------------------
if (J != NULL)
{
GB_OK (GB_extract_vector_list ((int64_t *) J, A, Context)) ;
}
//----------------------------------------------------------------------
// extract the values
//----------------------------------------------------------------------
if (X != NULL)
{
// typecast or copy the values from A into X
GB_cast_array ((GB_void *) X, xcode, (GB_void *) A->x,
acode, NULL, asize, anz, nthreads) ;
}
}
//--------------------------------------------------------------------------
// free workspace and return result
//--------------------------------------------------------------------------
*p_nvals = anz ; // number of tuples extracted
GB_FREE_ALL ;
return (GrB_SUCCESS) ;
}
|
compression.h | //
// Created by Bangtian Liu on 6/30/19.
//
#ifndef PROJECT_COMPRESSION_H
#define PROJECT_COMPRESSION_H
#include <vector>
#include <algorithm>
#include <random>
#include <cstring>
#include "../sympiler/HMatrix.h"
#include "HTree.h"
#include "../sympiler/HTree.h"
using namespace Sympiler::Internal;
using namespace Sympiler;
struct cretvalue {
int *skels;
int skels_length;
double *proj;
int proj_column;
};
struct DDcost {
int index;
unsigned long cost;
};
bool fcompare(DDcost lhs, DDcost rhs) {
return lhs.cost > rhs.cost;
}
typedef cretvalue ret;
using namespace std;
void Fsubmatrix(std::vector<int> &amap, std::vector<int> &bmap, double *submatrix, double *X, int n, int d,
Internal::Ktype ktype,
double h) {
switch (ktype) {
case Internal::KS_GAUSSIAN: {
double *source = (double *) mkl_malloc(sizeof(double) * bmap.size() * d, 64);
double *target = (double *) mkl_malloc(sizeof(double) * amap.size() * d, 64);
#pragma omp parallel for
for (int i = 0; i < bmap.size(); i++) {
for (int j = 0; j < d; j++) {
source[i * d + j] = X[bmap[i] * d + j];
}
}
#pragma omp parallel for
for (int i = 0; i < amap.size(); i++) {
for (int j = 0; j < d; j++) {
target[i * d + j] = X[amap[i] * d + j];
}
}
cblas_dgemm(CblasColMajor, CblasTrans, CblasNoTrans,
amap.size(), bmap.size(), d, -2.0,
target, d,
source, d, 0.0,
submatrix, amap.size());
double *target_sqnorms = (double *) mkl_malloc(sizeof(double) * amap.size(), 64);
double *source_sqnorms = (double *) mkl_malloc(sizeof(double) * bmap.size(), 64);
#pragma omp parallel for
for (int i = 0; i < amap.size(); i++) {
target_sqnorms[i] = cblas_ddot(d,
target + i * d, 1,
target + i * d, 1);
}
for (int i = 0; i < bmap.size(); i++) {
source_sqnorms[i] = cblas_ddot(d,
source + i * d, 1,
source + i * d, 1);
}
#pragma omp parallel for
for (int j = 0; j < bmap.size(); j++) {
for (int i = 0; i < amap.size(); i++)
submatrix[j * amap.size() + i] += target_sqnorms[i] + source_sqnorms[j];
}
double kscal = -0.5 / (h * h);
#pragma omp parallel for
for (int i = 0; i < amap.size() * bmap.size(); i++) {
submatrix[i] = std::exp(kscal * submatrix[i]);
}
break;
}
case Internal::KS_LOG: {
//#pragma omp parallel for
// for (int i = 0; i < amap.size() * bmap.size(); i++) {
// submatrix[i] = -0.5 * log(submatrix[i]);
// }
break;
}
case Internal::KS_EXPONENTIAL: {
//#pragma omp parallel for
// for (int i = 0; i < amap.size() * bmap.size(); i++) {
// submatrix[i] = exp(-sqrt(submatrix[i]));;
// }
break;
}
case Internal::KS_NEWTON: {
#pragma omp parallel for
for (int j = 0; j < bmap.size(); j++) {
for (int i = 0; i < amap.size(); i++) {
auto Kij = 0.0;
for (int k = 0; k < d; ++k) {
auto col = bmap[j];
auto row = amap[i];
auto tar = X[col * d + k];
auto src = X[row * d + k];
Kij += (tar - src) * (tar - src);
}
if(Kij==0)Kij=1;
submatrix[j * amap.size() + i] = 1/sqrt(Kij);
}
}
//#pragma omp parallel for
// for (int i = 0; i < amap.size() * bmap.size(); i++) {
// if(submatrix[i]==0) submatrix[i] = 1;
// else submatrix[i] = 1/std::sqrt(submatrix[i]);
// }
break;
}
default: {
printf("invalid kernel type\n");
exit(1);
break;
}
}
}
//
//void DDDFsubmatrix(std::vector<int> &amap, std::vector<int> &bmap, double *submatrix, double *X, int n, int d, Internal::Ktype ktype,
// double h)
//{
//
// double *source = (double *)mkl_malloc(sizeof(double)*bmap.size()*d, 64);
// double *target = (double *)mkl_malloc(sizeof(double)*amap.size()*d, 64);
//
//#pragma omp parallel for
// for(int i=0; i<bmap.size(); i++)
// {
// for(int j=0; j<d; j++)
// {
// source[i*d + j] = X[bmap[i]*d+j];
// }
// }
//
//#pragma omp parallel for
// for(int i=0; i<amap.size(); i++) {
// for (int j = 0; j < d; j++) {
// target[i*d + j] = X[amap[i]*d+j];
// }
// }
//
// cblas_dgemm(CblasColMajor, CblasTrans, CblasNoTrans,
// amap.size(), bmap.size(), d, -2.0,
// target, d,
// source, d, 0.0,
// submatrix, amap.size());
//
// double *target_sqnorms = (double *)mkl_malloc(sizeof(double)*amap.size(), 64);
// double *source_sqnorms = (double *)mkl_malloc(sizeof(double)*bmap.size(), 64);
//
//#pragma omp parallel for
// for(int i=0; i<amap.size(); i++)
// {
// target_sqnorms[i] = cblas_ddot(d,
// target+i*d, 1,
// target+i*d, 1);
// }
//
// for(int i=0; i<bmap.size(); i++)
// {
// source_sqnorms[i] = cblas_ddot(d,
// source+i*d,1,
// source+i*d,1);
// }
//#pragma omp parallel for
// for(int j=0; j<bmap.size(); j++)
// {
// for(int i=0; i<amap.size(); i++)
// submatrix[j*amap.size() + i] += target_sqnorms[i] + source_sqnorms[j];
// }
//
// switch (ktype) {
// case Internal::KS_GAUSSIAN: {
//
// double kscal = -0.5/(h * h);
//#pragma omp parallel for
// for(int i=0; i<amap.size()*bmap.size(); i++)
// {
// submatrix[i] = 1.0;
// }
//
// break;
// }
//
// case Internal::KS_LOG: {
//#pragma omp parallel for
// for(int i=0; i<amap.size()*bmap.size(); i++)
// {
// submatrix[i] = -0.5 * log(submatrix[i]);
// }
//
// break;
// }
//
// case Internal::KS_EXPONENTIAL: {
//#pragma omp parallel for
// for(int i=0; i<amap.size()*bmap.size(); i++)
// {
// submatrix[i] = exp(-sqrt(submatrix[i]));;
// }
// break;
// }
//
// case Internal::KS_NEWTON: {
//
//#pragma omp parallel for
// for(int i=0; i<amap.size()*bmap.size(); i++)
// {
// submatrix[i] = std::sqrt(submatrix[i]);
// }
//
// break;
// }
//
// default: {
// printf("invalid kernel type\n");
// exit(1);
// break;
// }
// }
//
//}
void Fsubmatrix(int *amap, int lena, int *bmap, int lenb, double *submatrix, Internal::Ktype ktype, double *X, int d,
double h) {
switch (ktype) {
case Internal::KS_GAUSSIAN: {
double *source = (double *) mkl_malloc(sizeof(double) * lenb * d, 64);
double *target = (double *) mkl_malloc(sizeof(double) * lena * d, 64);
#pragma omp parallel for
for (int i = 0; i < lenb; i++) {
for (int j = 0; j < d; j++) {
source[i * d + j] = X[bmap[i] * d + j];
}
}
#pragma omp parallel for
for (int i = 0; i < lena; i++) {
for (int j = 0; j < d; j++) {
target[i * d + j] = X[amap[i] * d + j];
}
}
cblas_dgemm(CblasColMajor, CblasTrans, CblasNoTrans,
lena, lenb, d, -2.0,
target, d,
source, d, 0.0,
submatrix, lena);
double *target_sqnorms = (double *) mkl_malloc(sizeof(double) * lena, 64);
double *source_sqnorms = (double *) mkl_malloc(sizeof(double) * lenb, 64);
#pragma omp parallel for
for (int i = 0; i < lena; i++) {
target_sqnorms[i] = cblas_ddot(d,
target + i * d, 1,
target + i * d, 1);
}
#pragma omp parallel for
for (int i = 0; i < lenb; i++) {
source_sqnorms[i] = cblas_ddot(d,
source + i * d, 1,
source + i * d, 1);
}
#pragma omp parallel for
for (int j = 0; j < lenb; j++) {
for (int i = 0; i < lena; i++)
submatrix[j * lena + i] += target_sqnorms[i] + source_sqnorms[j];
}
double kscal = -0.5 / (h * h);
#pragma omp parallel for
for (int i = 0; i < lena * lenb; i++) {
submatrix[i] = std::exp(kscal * submatrix[i]);
}
break;
}
case Internal::KS_LOG: {
//#pragma omp parallel for
// for (int i = 0; i < lena * lenb; i++) {
// submatrix[i] = -0.5 * log(submatrix[i]);
// }
break;
}
case Internal::KS_EXPONENTIAL: {
//#pragma omp parallel for
// for (int i = 0; i < lena * lenb; i++) {
// submatrix[i] = exp(-sqrt(submatrix[i]));;
// }
// break;
}
case Internal::KS_NEWTON: {
#pragma omp parallel for
for (int j = 0; j < lenb; j++) {
for (int i = 0; i < lena; i++) {
auto Kij = 0.0;
for (int k = 0; k < d; ++k) {
auto col = bmap[j];
auto row = amap[i];
auto tar = X[col * d + k];
auto src = X[row * d + k];
Kij += (tar - src) * (tar - src);
}
if(Kij==0)Kij=1;
submatrix[j * lena + i] = 1/sqrt(Kij);
}
}
break;
}
default: {
printf("invalid kernel type\n");
exit(1);
break;
}
}
}
void BuildNeighBorsLeaf(HTree &tree, int idx, int nsamples) {
auto &pnids = tree.pnids[idx];
auto &snids = tree.snids[idx];
int k = 32;
auto &NN = tree.NN;
auto lids = tree.lids + tree.lidsoffset[idx];
int n = tree.lidslen[idx];
// printf("len=%d\n",n);
pnids = std::unordered_set<int>(); // will modify
for (int ii = 0; ii < k / 2; ii++) {
for (int jj = 0; jj < n; jj++) {
auto idx = NN[lids[jj] * k + ii].second;
pnids.insert(idx);
// printf("%lu;",NN[ lids[jj] * k + ii].second);
}
}
for (int i = 0; i < n; i++) {
pnids.erase(lids[i]);
}
// printf("Leaf Size of pruning neighbor set: %lu \n", pnids.size());
snids = std::map<int, double>();
std::vector<std::pair<double, int>> tmp(k / 2 * n);
std::set<int> nodeIdx(lids, lids + n);
// Allocate array for sorting
for (int ii = (k + 1) / 2; ii < k; ii++) {
for (int jj = 0; jj < n; jj++) {
tmp[(ii - (k + 1) / 2) * n + jj] = NN[lids[jj] * k + ii];
}
}
std::sort(tmp.begin(), tmp.end());
int i = 0;
while (snids.size() < nsamples && i < (k - 1) * n / 2) {
if (!pnids.count(tmp[i].second) && !nodeIdx.count(tmp[i].second)) {
snids.insert(std::pair<int, double>(tmp[i].second, tmp[i].first));
}
i++;
}
}
void BuildNeighBorsInternal(HTree &tree, int idx, int nsamples) {
auto &pnids = tree.pnids[idx];
auto &snids = tree.snids[idx];
int k = 32;
auto &NN = tree.NN;
auto lids = tree.lids + tree.lidsoffset[idx];
int n = tree.lidslen[idx];
auto &lsnids = tree.snids[tree.tlchildren[idx]];
auto &rsnids = tree.snids[tree.trchildren[idx]];
auto &lpnids = tree.pnids[tree.tlchildren[idx]];
auto &rpnids = tree.pnids[tree.trchildren[idx]];
snids = lsnids;
for (auto cur = rsnids.begin(); cur != rsnids.end(); cur++) {
auto ret = snids.insert(*cur);
if (ret.second == false) {
// Update distance?
if (ret.first->second > (*cur).first) {
ret.first->second = (*cur).first;
}
}
}
// Remove "own" points
for (int i = 0; i < n; i++) {
snids.erase(lids[i]);
}
// Remove pruning neighbors from left and right
for (auto cur = lpnids.begin(); cur != lpnids.end(); cur++) {
snids.erase(*cur);
}
for (auto cur = rpnids.begin(); cur != rpnids.end(); cur++) {
snids.erase(*cur);
}
}
int decomposition(double *A, int nRows, int nCols, double tolerance, int **skels, double **proj, int **jpvt) {
assert(nRows > nCols);
int s;
int maxRank = 256;
// printf("maxRank=%d\n",maxRank);
*jpvt = (int *) malloc(sizeof(int) * nCols);
memset(*jpvt, 0, sizeof(int) * nCols);
// T *tau = GenMatrix<T>(std::min(nRows,nCols),1);
double *tau = (double *) mkl_malloc(sizeof(double) * std::min(nRows, nCols), 64);
auto info = LAPACKE_dgeqp3(LAPACK_COL_MAJOR, nRows, nCols, A, nRows, *jpvt, tau);
if (info != 0) {
printf("%d-th parameter had an illegal value", -info);
}
#pragma omp parallel for
for (int i = 0; i < nCols; ++i) {
(*jpvt)[i] = (*jpvt)[i] - 1;
}
for (s = 1; s < nCols; ++s) {
// printf("s=%d, a=%e, error=%e nCOls=%d\n",s, A[s*nRows+s],tolerance,nCols);
if (s > maxRank || std::abs(A[s * nRows + s]/A[0]) < tolerance) break;
}
// if(!setup.adaptive)
// {
// s = std::min(maxRank, nCols);
// }
if (s > maxRank) s = maxRank;
*skels = (int *) malloc(sizeof(int) * s);
memcpy(*skels, *jpvt, sizeof(int) * s);
// memcpy(*skels,*proj, sizeof(int)*s);
// *proj = GenMatrix<T>(s,nCols);
*proj = (double *) mkl_malloc(sizeof(double) * s * nCols, 64);
memset(*proj, 0, sizeof(double) * s * nCols);
//#pragma omp parallel for
for (int j = 0; j < nCols; j++) {
for (int i = 0; i < s; i++) {
if (j < s) {
if (j >= i) (*proj)[j * s + i] = A[j * nRows + i];
else (*proj)[j * s + i] = 0.0;
} else {
(*proj)[j * s + i] = A[j * nRows + i];
}
}
}
if ((*proj)[0] == 0) return s; // put on here
double *R1 = (double *) mkl_malloc(sizeof(double) * s * s, 64);
memset(R1, 0, sizeof(double) * s * s); // todo check the segment fault bug here
//#pragma omp parallel for
for (int j = 0; j < s; j++) {
for (int i = 0; i < s; i++) {
if (i <= j) R1[j * s + i] = (*proj)[j * s + i];
// if((*proj)[j*s+i]!=(*proj)[j*s+i])printf("NAN FOUND1!!!\n");
}
}
// T *tmp = GenMatrix<T>(s,nCols);
double *tmp = (double *) mkl_malloc(sizeof(double) * s * nCols, 64);
memcpy(tmp, *proj, sizeof(double) * s * nCols);
cblas_dtrsm(CblasColMajor, CblasLeft, CblasUpper, CblasNoTrans, CblasNonUnit, s, nCols, 1.0, R1, s, tmp, s);
/** Fill in proj */
for (int j = 0; j < nCols; j++) {
for (int i = 0; i < s; i++) {
(*proj)[(*jpvt)[j] * s + i] = tmp[j * s + i];
}
}
return s;
}
void skeletonize_leaf(int idx, int *lids, int *lidslen, int *lidsoffset, ret *rtmp, int *sid, int *sidlen,
int *sidoffset, int *lc, int *rc, int m, int n, double *X, Internal::Ktype ktype, int dim,
double h,
double acc) {
std::vector<int> bmap;
bmap.insert(bmap.end(), lids + lidsoffset[idx], lids + lidsoffset[idx] + lidslen[idx]);
auto nsamples = 2 * bmap.size();
auto numpoints = lidslen[idx];
auto clids = lids + lidsoffset[idx];
nsamples = (nsamples < 2 * m) ? 2 * m : nsamples;
int slen = sidlen[idx];
int offset = sidoffset[idx];
// printf("idx =%d slen=%d\n", idx, slen);
// add sampling points
std::vector<int> amap;
// (sid+offset, sid+offset+slen);
mt19937 generator(idx);
uniform_int_distribution<> uniform_distribution(0, n - 1);
if (nsamples < (n - numpoints)) {
amap.assign(sid + offset, sid + offset + slen);
while (amap.size() < nsamples) {
// auto sample = rand() % setup.n;
auto sample = uniform_distribution(generator);
if (std::find(amap.begin(), amap.end(), sample) == amap.end() &&
std::find(clids, clids + numpoints, sample) == (clids + numpoints)) {
amap.push_back(sample);
}
}
} else {
for (int sample = 0; sample < n; sample++) // TODO: may can be improved here
{
if (std::find(amap.begin(), amap.end(), sample) == amap.end()) {
amap.push_back(sample);
}
}
}
auto Kab = (double *) malloc(sizeof(double) * amap.size() * bmap.size());
memset(Kab, 0, sizeof(double) * amap.size() * bmap.size());
Fsubmatrix(amap, bmap, Kab, X, n, dim, ktype, h);
auto N = n;
auto m1 = amap.size();
auto n1 = bmap.size();
auto q = numpoints;
// std::sqrt((m1 * n1 * 1.0) / (1.0 * N * (N - q))) *
auto tolerance = acc;
int *skels;
double *proj;
int *jpvt;
int s = decomposition(Kab, m1, n1, tolerance, &skels, &proj, &jpvt);
for (int i = 0; i < s; ++i) { // need to check it
skels[i] = bmap[skels[i]];
}
rtmp[idx].skels = skels;
rtmp[idx].skels_length = s;
rtmp[idx].proj = proj;
rtmp[idx].proj_column = (int) bmap.size();
free(Kab);
}
void skeletonize_leaf(int idx, HTree &tree, ret *rtmp, int m, int n, double *X, Internal::Ktype ktype, int dim,
double h, double acc) {
auto lc = tree.tlchildren;
auto rc = tree.trchildren;
auto lids = tree.lids;
auto lidslen = tree.lidslen;
auto lidsoffset = tree.lidsoffset;
std::vector<int> bmap;
bmap.insert(bmap.end(), lids + lidsoffset[idx], lids + lidsoffset[idx] + lidslen[idx]);
auto nsamples = 2 * bmap.size();
auto numpoints = lidslen[idx];
auto clids = lids + lidsoffset[idx];
nsamples = (nsamples < 2 * m) ? 2 * m : nsamples;
BuildNeighBorsLeaf(tree, idx, nsamples);
auto &snids = tree.snids[idx];
auto &pnids = tree.pnids[idx];
std::multimap<double, int> ordered_snids = flip_map(snids);
// add sampling points
std::vector<int> amap;
// (sid+offset, sid+offset+slen);
// mt19937 generator(idx);
// uniform_int_distribution<> uniform_distribution(0, n - 1);
// printf("idx =%d, len=%ld %ld\n", idx, ordered_snids.size(), nsamples);
if (nsamples < (n - numpoints)) {
amap.reserve(nsamples);
for (auto cur = ordered_snids.begin(); cur != ordered_snids.end(); cur++) {
amap.push_back(cur->second);
}
while (amap.size() < nsamples) {
auto sample = rand() % n;
// auto sample = uniform_distribution(generator);
if (std::find(amap.begin(), amap.end(), sample) == amap.end() &&
std::find(clids, clids + numpoints, sample) == (clids + numpoints)) {
amap.push_back(sample);
}
}
} else {
for (int sample = 0; sample < n; sample++) // TODO: may can be improved here
{
if (std::find(amap.begin(), amap.end(), sample) == amap.end()) {
amap.push_back(sample);
}
}
}
auto Kab = (double *) malloc(sizeof(double) * amap.size() * bmap.size());
memset(Kab, 0, sizeof(double) * amap.size() * bmap.size());
Fsubmatrix(amap, bmap, Kab, X, n, dim, ktype, h);
auto N = n;
auto m1 = amap.size();
auto n1 = bmap.size();
auto q = numpoints;
// double scal_tol = std::sqrt((double)n1/q) *std::sqrt((double)m1/(N-q)) * acc;
// auto tolerance = std::sqrt((double)q/N) * scal_tol;
auto tolerance = acc;
int *skels;
double *proj;
int *jpvt;
int s = decomposition(Kab, m1, n1, tolerance, &skels, &proj, &jpvt);
for (int i = 0; i < s; ++i) { // need to check it
skels[i] = bmap[skels[i]];
}
pnids.clear();
auto &NN = tree.NN;
for (int ii = 0; ii < s; ii++) {
for (int jj = 0; jj < 32 / 2; jj++) {
pnids.insert(NN.data()[skels[ii] * 32 + jj].second);
}
}
rtmp[idx].skels = skels;
rtmp[idx].skels_length = s;
rtmp[idx].proj = proj;
rtmp[idx].proj_column = (int) bmap.size();
free(Kab);
}
void skeletonize_internal(int idx, HTree &tree, ret *rtmp, int m, int n, double *X, Internal::Ktype ktype, int dim,
double h, double acc) {
auto lc = tree.tlchildren;
auto rc = tree.trchildren;
auto lids = tree.lids;
auto lidslen = tree.lidslen;
auto lidsoffset = tree.lidsoffset;
std::vector<int> bmap;
auto v = lc[idx];
bmap.insert(bmap.end(), rtmp[v].skels, rtmp[v].skels + rtmp[v].skels_length);
v = rc[idx];
bmap.insert(bmap.end(), rtmp[v].skels, rtmp[v].skels + rtmp[v].skels_length);
auto nsamples = 2 * bmap.size();
auto numpoints = lidslen[idx];
auto clids = lids + lidsoffset[idx];
nsamples = (nsamples < 2 * m) ? 2 * m : nsamples;
BuildNeighBorsInternal(tree, idx, nsamples);
auto &snids = tree.snids[idx];
auto &pnids = tree.pnids[idx];
std::multimap<double, int> ordered_snids = flip_map(snids);
std::vector<int> amap;
// (sid+offset, sid+offset+slen);
// mt19937 generator(idx);
// uniform_int_distribution<> uniform_distribution(0, n - 1);
// printf("idx=%d len=%ld %ld\n", idx, ordered_snids.size(), nsamples);
if (nsamples < (n - numpoints)) {
// printf("idx=%d, len=%d nsamples=%d\n", idx, ordered_snids.size(), nsamples);
amap.reserve(nsamples);
if(ordered_snids.size()>nsamples){
auto cur = ordered_snids.begin();
for(int k=0; k<nsamples; k++)
{
amap.push_back(cur->second);
cur++;
}
}
else {
for (auto cur = ordered_snids.begin(); cur != ordered_snids.end(); cur++) {
amap.push_back(cur->second);}
}
while (amap.size() < nsamples) {
auto sample = rand() % n;
// auto sample = uniform_distribution(generator);
if (std::find(amap.begin(), amap.end(), sample) == amap.end() &&
std::find(clids, clids + numpoints, sample) == (clids + numpoints)) {
amap.push_back(sample);
}
}
} else {
for (int sample = 0; sample < n; sample++) // TODO: may can be improved here
{
if (std::find(amap.begin(), amap.end(), sample) == amap.end()) {
amap.push_back(sample);
}
}
}
auto Kab = (double *) malloc(sizeof(double) * amap.size() * bmap.size());
memset(Kab, 0, sizeof(double) * amap.size() * bmap.size());
Fsubmatrix(amap, bmap, Kab, X, n, dim, ktype, h);
auto N = n;
auto m1 = amap.size();
auto n1 = bmap.size();
auto q = numpoints;
// double scal_tol = std::sqrt((double)n1/q) *std::sqrt((double)m1/(N-q)) * acc;
//
// auto tolerance = std::sqrt((double)q/N) * scal_tol;
auto tolerance = acc;
int *skels;
double *proj;
int *jpvt;
int s = decomposition(Kab, m1, n1, tolerance, &skels, &proj, &jpvt);
for (int i = 0; i < s; ++i) { // need to check it
skels[i] = bmap[skels[i]];
}
pnids.clear();
auto &NN = tree.NN;
for (int ii = 0; ii < s; ii++) {
for (int jj = 0; jj < 32 / 2; jj++) {
pnids.insert(NN.data()[skels[ii] * 32 + jj].second);
}
}
rtmp[idx].skels = skels;
rtmp[idx].skels_length = s;
rtmp[idx].proj = proj;
rtmp[idx].proj_column = (int) bmap.size();
// free(Kab);
}
void skeletonize_internal(int idx, int *lids, int *lidslen, int *lidsoffset, ret *rtmp, int *sid, int *sidlen,
int *sidoffset, int *lc, int *rc, int m, int n, double *X, Internal::Ktype ktype, int dim,
double h, double acc) {
std::vector<int> bmap;
auto v = lc[idx];
bmap.insert(bmap.end(), rtmp[v].skels, rtmp[v].skels + rtmp[v].skels_length);
v = rc[idx];
bmap.insert(bmap.end(), rtmp[v].skels, rtmp[v].skels + rtmp[v].skels_length);
auto nsamples = 2 * bmap.size();
auto numpoints = lidslen[idx];
auto clids = lids + lidsoffset[idx];
nsamples = (nsamples < 2 * m) ? 2 * m : nsamples;
int slen = sidlen[idx];
int offset = sidoffset[idx];
std::vector<int> amap;
mt19937 generator(idx);
uniform_int_distribution<> uniform_distribution(0, n - 1);
if (nsamples < (n - numpoints)) {
// printf("idx=%d, len=%d nsamples=%d\n", idx, slen, nsamples);
amap.assign(sid + offset, sid + offset + slen);
while (amap.size() < nsamples) {
// auto sample = rand() % setup.n;
auto sample = uniform_distribution(generator);
if (std::find(amap.begin(), amap.end(), sample) == amap.end() &&
std::find(clids, clids + numpoints, sample) == (clids + numpoints)) {
amap.push_back(sample);
}
}
} else {
for (int sample = 0; sample < n; sample++) // TODO: may can be improved here
{
if (std::find(amap.begin(), amap.end(), sample) == amap.end()) {
amap.push_back(sample);
}
}
}
auto Kab = (double *) malloc(sizeof(double) * amap.size() * bmap.size());
memset(Kab, 0, sizeof(double) * amap.size() * bmap.size());
Fsubmatrix(amap, bmap, Kab, X, n, dim, ktype, h);
auto N = n;
auto m1 = amap.size();
auto n1 = bmap.size();
auto q = numpoints;
auto tolerance = std::sqrt((m1 * n1 * 1.0) / (1.0 * N * (N - q))) * acc;
int *skels;
double *proj;
int *jpvt;
int s = decomposition(Kab, m1, n1, tolerance, &skels, &proj, &jpvt);
for (int i = 0; i < s; ++i) { // need to check it
skels[i] = bmap[skels[i]];
}
rtmp[idx].skels = skels;
rtmp[idx].skels_length = s;
rtmp[idx].proj = proj;
rtmp[idx].proj_column = (int) bmap.size();
free(Kab);
}
void skeletonize(int idx, int *lids, int *lidslen, int *lidsoffset, ret *rtmp, int *sid, int *sidlen,
int *sidoffset, int *lc, int *rc, int m, int n, double *X, Internal::Ktype ktype, int dim, double h) {
// if(idx==0){
// return;
// }
std::vector<int> bmap;
if (lc[idx] == -1) { // leaf node
bmap.insert(bmap.end(), lids + lidsoffset[idx], lids + lidsoffset[idx] + lidslen[idx]);
} else {
auto v = lc[idx];
bmap.insert(bmap.end(), rtmp[v].skels, rtmp[v].skels + rtmp[v].skels_length);
v = rc[idx];
bmap.insert(bmap.end(), rtmp[v].skels, rtmp[v].skels + rtmp[v].skels_length);
}
// printf("bmap size=%d len=%d\n",bmap.size(), lidslen[idx]);
auto nsamples = 2 * bmap.size();
auto numpoints = lidslen[idx];
auto clids = lids + lidsoffset[idx];
nsamples = (nsamples < 2 * m) ? 2 * m : nsamples;
int slen = sidlen[idx];
int offset = sidoffset[idx];
// add sampling points
std::vector<int> amap(sid + offset, sid + offset + slen);
mt19937 generator(idx);
uniform_int_distribution<> uniform_distribution(0, n - 1);
if (nsamples < (n - numpoints)) {
while (amap.size() < nsamples) {
// auto sample = rand() % setup.n;
auto sample = uniform_distribution(generator);
if (std::find(amap.begin(), amap.end(), sample) == amap.end() &&
std::find(clids, clids + numpoints, sample) == (clids + numpoints)) {
amap.push_back(sample);
}
}
} else {
for (int sample = 0; sample < n; sample++) // TODO: may can be improved here
{
if (std::find(amap.begin(), amap.end(), sample) == amap.end()) {
amap.push_back(sample);
}
}
}
auto Kab = (double *) malloc(sizeof(double) * amap.size() * bmap.size());
memset(Kab, 0, sizeof(double) * amap.size() * bmap.size());
Fsubmatrix(amap, bmap, Kab, X, n, dim, ktype, h);
auto N = n;
auto m1 = amap.size();
auto n1 = bmap.size();
auto q = numpoints;
double error = 1e-5;
// printf("m1=%d, n1=%d N=%d q=%d\n", m1, n1, N, q);
auto tolerance = std::sqrt((m1 * n1 * 1.0) / (1.0 * N * (N - q))) * error;
// printf("error=%lf\n", std::sqrt((m1*n1*1.0)/(1.0*N*(N-q))));
// auto tolerance = 1E-5;
int *skels;
double *proj;
int *jpvt;
int s = decomposition(Kab, m1, n1, tolerance, &skels, &proj, &jpvt);
// printf("s=%d\n",s);
for (int i = 0; i < s; ++i) { // need to check it
skels[i] = bmap[skels[i]];
}
rtmp[idx].skels = skels;
rtmp[idx].skels_length = s;
rtmp[idx].proj = proj;
rtmp[idx].proj_column = (int) bmap.size();
free(Kab);
}
void binpacking(std::vector<std::vector<int>> &wpartitions, std::vector<std::vector<int>> &owpartitions, int numofbins,
clustertree &ctree, HTree &tree, ret *rtmp) {
DDcost *ccost = new DDcost[wpartitions.size()];
for (auto i = 0; i < wpartitions.size(); i++) {
ccost[i].cost = 0;
ccost[i].index = i;
for (auto j = 0; j < wpartitions[i].size(); j++) {
auto idx = wpartitions[i][j];
unsigned long cost = 0;
if (tree.tlchildren[idx] == -1) {
cost += 2 * rtmp[idx].skels_length * rtmp[idx].proj_column;
// leafdim[leafmap.at(idx)] * setup.nrhs;
} else {
auto lc = tree.tlchildren[idx];
auto rc = tree.trchildren[idx];
cost += 2 * rtmp[idx].skels_length * rtmp[lc].skels_length;
cost += 2 * rtmp[idx].skels_length * rtmp[rc].skels_length;
//
// for(auto &v : children[idx])
// {
// cost += 2*tmpresult[idx].skels_length*tmpresult[v].skels_length*setup.nrhs;
// }
}
ccost[i].cost += cost;
}
}
std::sort(ccost, ccost + wpartitions.size(), fcompare);
uint64_t *ocost = new uint64_t[numofbins];
memset(ocost, 0, sizeof(uint64_t) * numofbins);
int partNo = wpartitions.size();
int minBin = 0;
for (int i = 0; i < partNo; i++) {
minBin = findMin(ocost, numofbins);
ocost[minBin] += ccost[i].cost;
int index = ccost[i].index;
//owpartition
owpartitions[minBin].insert(owpartitions[minBin].end(),
wpartitions[index].begin(), wpartitions[index].end());
}
}
void BalanceCoarLevelSet(clustertree &ctree, HTree &tree, ret *rtmp) {
auto &postw = ctree.postw;
auto &opostw = ctree.opostw;
auto len = postw.size();
opostw.resize(len);
// auto &pow=tree->postw;
// auto &opow=tree->opostw;
for (int i = 0; i < postw.size(); i++) {
auto &lpow = postw[i];
int nw = lpow.size();
int nparts;
int nthreads = omp_get_max_threads();
if (nw >= nthreads) {
nparts = nthreads;
} else {
nparts = nw / 2;
}
if (nparts == 0)nparts = 1;
opostw[i].resize(nparts);
binpacking(lpow, opostw[i], nparts, ctree, tree, rtmp);
}
len = opostw.size();
len = 0;
int index = 0;
for (auto &v:postw) {
tree.clevelset[index++] = len;
len += v.size();
}
tree.clevelset[index] = len;
len = 0;
index = 0;
int tidx = 0;
for (auto &v:postw) {
for (auto &w:v) {
tree.wpart[index++] = len;
len += w.size();
for (auto &t:w) {
tree.idx[tidx++] = t;
}
}
}
tree.wpart[index] = len;
}
void compression(clustertree &ctree, HTree &tree, ret *rtmp, double *X, int m, int n, Internal::Ktype ktype, int dim, double h,
double acc = 1e-5) {
#pragma omp parallel for
for (int j = tree.levelset[tree.depth - 1]; j < tree.levelset[tree.depth]; j++) {
auto id = tree.idx[j];
skeletonize_leaf(id, tree, rtmp, m, n, X, ktype, dim, h, acc);
}
for (int i = tree.depth - 2; i > -1; i--) {
#pragma omp parallel for
for (int j = tree.levelset[i]; j < tree.levelset[i + 1]; j++) {
auto id = tree.idx[j];
skeletonize_internal(id, tree, rtmp, m, n, X, ktype, dim, h, acc);
}
}
BalanceCoarLevelSet(ctree,tree,rtmp);
}
unsigned long computeFlops(HTree &tree, ret *rtmp, int m, int nrhs)
{
unsigned long flops = 0;
unsigned long tflops = 0;
unsigned long inflops = 0;
for (int j = tree.levelset[tree.depth - 1]; j < tree.levelset[tree.depth]; j++) {
auto id = tree.idx[j];
flops+=2*rtmp[id].skels_length * nrhs*tree.Dim[tree.lm[id]];
}
for (int i = tree.depth - 2; i > -1; i--) {
for (int j = tree.levelset[i]; j < tree.levelset[i + 1]; j++)
{
auto id = tree.idx[j];
auto lc = tree.tlchildren[id];
auto rc = tree.trchildren[id];
flops += 2 * rtmp[id].skels_length * (rtmp[lc].skels_length+rtmp[rc].skels_length)*nrhs;
}
}
flops = 2*flops;
tflops += flops;
printf("tree flops is %lu\n", tflops);
for(int k=0; k<tree.ncount; k++)
{
auto nx = tree.nxval[k];
auto ny = tree.nyval[k];
auto dimx = tree.Dim[nx];
auto dimy = tree.Dim[ny];
flops += 2*dimx*dimy*nrhs;
}
printf("number of near nodes is %d\n", tree.ncount);
for(int k = 0; k<tree.fcount; k++)
{
auto fx = tree.fxval[k];
auto fy = tree.fyval[k];
auto dimx = rtmp[fx].skels_length;
auto dimy = rtmp[fy].skels_length;
flops += 2*dimx*dimy*nrhs;
}
printf("number of far nodes is %d\n", tree.fcount);
printf("interaction flops is %lu\n", flops-tflops);
return flops;
}
unsigned long computeRanks(HTree &tree, ret *rtmp, int m, int nrhs)
{
unsigned long rank = 0;
int count=0;
for (int j = tree.levelset[tree.depth - 1]; j < tree.levelset[tree.depth]; j++) {
auto id = tree.idx[j];
rank +=rtmp[id].skels_length;
++count;
// flops+=2*rtmp[id].skels_length * nrhs*tree.Dim[tree.lm[id]];
}
for (int i = tree.depth - 2; i > -1; i--) {
for (int j = tree.levelset[i]; j < tree.levelset[i + 1]; j++)
{
auto id = tree.idx[j];
rank +=rtmp[id].skels_length;
++count;
// auto lc = tree.tlchildren[id];
// auto rc = tree.trchildren[id];
// flops += 2 * rtmp[id].skels_length * (rtmp[lc].skels_length+rtmp[rc].skels_length)*nrhs;
}
}
return rank/count;
}
void
coarcompression(HTree &tree, ret *rtmp, double *X, int m, int n, Internal::Ktype ktype, int dim, int h, double acc) {
#pragma omp parallel for
for (int k = tree.clevelset[0]; k < tree.clevelset[1]; k++) {
for (int j = tree.wpart[k]; j < tree.wpart[k + 1]; j++) {
auto id = tree.cidx[j];
if (tree.tlchildren[id] == -1) {
skeletonize_leaf(id, tree.lids, tree.lidslen, tree.lidsoffset, rtmp, tree.sids, tree.sidlen,
tree.sidoffset, tree.tlchildren,
tree.trchildren, m, n, X, ktype, dim, h, acc);
} else {
skeletonize_internal(id, tree.lids, tree.lidslen, tree.lidsoffset, rtmp, tree.sids, tree.sidlen,
tree.sidoffset, tree.tlchildren,
tree.trchildren, m, n, X, ktype, dim, h, acc);
}
// skeletonize(id, tree.lids, tree.lidslen, tree.lidsoffset, rtmp, tree.sids, tree.sidlen, tree.sidoffset, tree.tlchildren,
// tree.trchildren, m, n, X, ktype, dim, h);
}
}
for (int i = 1; i < tree.cdepth; i++) {
#pragma omp parallel for
for (int k = tree.clevelset[i]; k < tree.clevelset[i + 1]; k++) {
//#pragma omp parallel for
for (int j = tree.wpart[k]; j < tree.wpart[k + 1]; j++) {
auto id = tree.cidx[j];
skeletonize_internal(id, tree.lids, tree.lidslen, tree.lidsoffset, rtmp, tree.sids, tree.sidlen,
tree.sidoffset, tree.tlchildren,
tree.trchildren, m, n, X, ktype, dim, h, acc);
}
}
}
}
#endif //PROJECT_COMPRESSION_H
|
GB_unop__identity_int32_fc32.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_int32_fc32
// op(A') function: GB_unop_tran__identity_int32_fc32
// C type: int32_t
// A type: GxB_FC32_t
// cast: int32_t cij = GB_cast_to_int32_t ((double) crealf (aij))
// unaryop: cij = aij
#define GB_ATYPE \
GxB_FC32_t
#define GB_CTYPE \
int32_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 = x ;
// casting
#define GB_CAST(z, aij) \
int32_t z = GB_cast_to_int32_t ((double) crealf (aij)) ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GxB_FC32_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
int32_t z = GB_cast_to_int32_t ((double) crealf (aij)) ; \
Cx [pC] = z ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_IDENTITY || GxB_NO_INT32 || GxB_NO_FC32)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop_apply__identity_int32_fc32
(
int32_t *Cx, // Cx and Ax may be aliased
const GxB_FC32_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++)
{
GxB_FC32_t aij = Ax [p] ;
int32_t z = GB_cast_to_int32_t ((double) crealf (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_int32_fc32
(
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
|
UsefulFunctions.c | // -------------------------------------------------------------------------------------
// Taken from COSMOLOGY.H
// -------------------------------------------------------------------------------------
#define Ho (double) (cosmo_params_ufunc->hlittle*3.2407e-18) // s^-1 at z=0
#define RHOcrit (double) ( (3.0*Ho*Ho / (8.0*PI*G)) * (CMperMPC*CMperMPC*CMperMPC)/Msun) // Msun Mpc^-3 ---- at z=0
#define RHOcrit_cgs (double) (3.0*Ho*Ho / (8.0*PI*G)) // g pcm^-3 ---- at z=0
#define No (double) (RHOcrit_cgs*cosmo_params_ufunc->OMb*(1-global_params.Y_He)/m_p) // current hydrogen number density estimate (#/cm^3) ~1.92e-7
#define He_No (double) (RHOcrit_cgs*cosmo_params_ufunc->OMb*global_params.Y_He/(4.0*m_p)) // current helium number density estimate
#define N_b0 (double) (No+He_No) // present-day baryon num density, H + He
#define f_H (double) (No/(No+He_No)) // hydrogen number fraction
#define f_He (double) (He_No/(No+He_No)) // helium number fraction
struct CosmoParams *cosmo_params_ufunc;
struct UserParams *user_params_ufunc;
void Broadcast_struct_global_UF(struct UserParams *user_params, struct CosmoParams *cosmo_params){
cosmo_params_ufunc = cosmo_params;
user_params_ufunc = user_params;
}
float ComputeFullyIoinizedTemperature(float z_re, float z, float delta){
// z_re: the redshift of reionization
// z: the current redshift
// delta:the density contrast
float result, delta_re;
// just be fully ionized
if (fabs(z - z_re) < 1e-4)
result = 1;
else{
// linearly extrapolate to get density at reionization
delta_re = delta * (1. + z ) / (1. + z_re);
if (delta_re<=-1) delta_re=-1. + global_params.MIN_DENSITY_LOW_LIMIT;
// evolving ionized box eq. 6 of McQuinn 2015, ignored the dependency of density at ionization
if (delta<=-1) delta=-1. + global_params.MIN_DENSITY_LOW_LIMIT;
result = pow((1. + delta) / (1. + delta_re), 1.1333);
result *= pow((1. + z) / (1. + z_re), 3.4);
result *= expf(pow((1. + z)/7.1, 2.5) - pow((1. + z_re)/7.1, 2.5));
}
result *= pow(global_params.T_RE, 1.7);
// 1e4 before helium reionization; double it after
result += pow(1e4 * ((1. + z)/4.), 1.7) * ( 1 + delta);
result = pow(result, 0.5882);
//LOG_DEBUG("z_re=%.4f, z=%.4f, delta=%e, Tk=%.f", z_re, z, delta, result);
return result;
}
float ComputePartiallyIoinizedTemperature(float T_HI, float res_xH){
if (res_xH<=0.) return global_params.T_RE;
if (res_xH>=1) return T_HI;
return T_HI * res_xH + global_params.T_RE * (1. - res_xH);
}
void filter_box(fftwf_complex *box, int RES, int filter_type, float R){
int n_x, n_z, n_y, dimension,midpoint;
float k_x, k_y, k_z, k_mag, kR;
switch(RES) {
case 0:
dimension = user_params_ufunc->DIM;
midpoint = MIDDLE;
break;
case 1:
dimension = user_params_ufunc->HII_DIM;
midpoint = HII_MIDDLE;
break;
}
// loop through k-box
#pragma omp parallel shared(box) private(n_x,n_y,n_z,k_x,k_y,k_z,k_mag,kR) num_threads(user_params_ufunc->N_THREADS)
{
#pragma omp for
for (n_x=0; n_x<dimension; n_x++){
// for (n_x=dimension; n_x--;){
if (n_x>midpoint) {k_x =(n_x-dimension) * DELTA_K;}
else {k_x = n_x * DELTA_K;}
for (n_y=0; n_y<dimension; n_y++){
// for (n_y=dimension; n_y--;){
if (n_y>midpoint) {k_y =(n_y-dimension) * DELTA_K;}
else {k_y = n_y * DELTA_K;}
// for (n_z=(midpoint+1); n_z--;){
for (n_z=0; n_z<=midpoint; n_z++){
k_z = n_z * DELTA_K;
if (filter_type == 0){ // real space top-hat
k_mag = sqrt(k_x*k_x + k_y*k_y + k_z*k_z);
kR = k_mag*R; // real space top-hat
if (kR > 1e-4){
if(RES==1) { box[HII_C_INDEX(n_x, n_y, n_z)] *= 3.0*pow(kR, -3) * (sin(kR) - cos(kR)*kR); }
if(RES==0) { box[C_INDEX(n_x, n_y, n_z)] *= 3.0*pow(kR, -3) * (sin(kR) - cos(kR)*kR); }
}
}
else if (filter_type == 1){ // k-space top hat
// This is actually (kR^2) but since we zero the value and find kR > 1 this is more computationally efficient
// as we don't need to evaluate the slower sqrt function
// kR = 0.17103765852*( k_x*k_x + k_y*k_y + k_z*k_z )*R*R;
k_mag = sqrt(k_x*k_x + k_y*k_y + k_z*k_z);
kR = k_mag*R; // real space top-hat
kR *= 0.413566994; // equates integrated volume to the real space top-hat (9pi/2)^(-1/3)
if (kR > 1){
if(RES==1) { box[HII_C_INDEX(n_x, n_y, n_z)] = 0; }
if(RES==0) { box[C_INDEX(n_x, n_y, n_z)] = 0; }
}
}
else if (filter_type == 2){ // gaussian
// This is actually (kR^2) but since we zero the value and find kR > 1 this is more computationally efficient
// as we don't need to evaluate the slower sqrt function
kR = 0.643*0.643*( k_x*k_x + k_y*k_y + k_z*k_z )*R*R;
// kR *= 0.643; // equates integrated volume to the real space top-hat
if(RES==1) { box[HII_C_INDEX(n_x, n_y, n_z)] *= pow(E, -kR/2.0); }
if(RES==0) { box[C_INDEX(n_x, n_y, n_z)] *= pow(E, -kR/2.0); }
}
else{
if ( (n_x==0) && (n_y==0) && (n_z==0) )
LOG_WARNING("Filter type %i is undefined. Box is unfiltered.", filter_type);
}
}
}
} // end looping through k box
}
return;
}
double MtoR(double M);
double RtoM(double R);
double TtoM(double z, double T, double mu);
double dicke(double z);
double dtdz(float z);
double ddickedt(double z);
double omega_mz(float z);
double Deltac_nonlinear(float z);
double drdz(float z); /* comoving distance, (1+z)*C*dtdz(in cm) per unit z */
double alpha_A(double T);
/* returns the case B hydrogen recombination coefficient (Spitzer 1978) in cm^3 s^-1*/
double alpha_B(double T);
double HeI_ion_crosssec(double nu);
double HeII_ion_crosssec(double nu);
double HI_ion_crosssec(double nu);
/* R in Mpc, M in Msun */
double MtoR(double M){
// set R according to M<->R conversion defined by the filter type in ../Parameter_files/COSMOLOGY.H
if (global_params.FILTER == 0) //top hat M = (4/3) PI <rho> R^3
return pow(3*M/(4*PI*cosmo_params_ufunc->OMm*RHOcrit), 1.0/3.0);
else if (global_params.FILTER == 1) //gaussian: M = (2PI)^1.5 <rho> R^3
return pow( M/(pow(2*PI, 1.5) * cosmo_params_ufunc->OMm * RHOcrit), 1.0/3.0 );
else // filter not defined
LOG_ERROR("No such filter = %i. Results are bogus.", global_params.FILTER);
Throw ValueError;
}
/* R in Mpc, M in Msun */
double RtoM(double R){
// set M according to M<->R conversion defined by the filter type in ../Parameter_files/COSMOLOGY.H
if (global_params.FILTER == 0) //top hat M = (4/3) PI <rho> R^3
return (4.0/3.0)*PI*pow(R,3)*(cosmo_params_ufunc->OMm*RHOcrit);
else if (global_params.FILTER == 1) //gaussian: M = (2PI)^1.5 <rho> R^3
return pow(2*PI, 1.5) * cosmo_params_ufunc->OMm*RHOcrit * pow(R, 3);
else // filter not defined
LOG_ERROR("No such filter = %i. Results are bogus.", global_params.FILTER);
Throw ValueError;
}
/*
T in K, M in Msun, mu is mean molecular weight
from Barkana & Loeb 2001
SUPRESS = 0 for no radiation field supression;
SUPRESS = 1 for supression (step function at z=z_ss, at v=v_zz)
*/
double TtoM(double z, double T, double mu){
return 7030.97 / (cosmo_params_ufunc->hlittle) * sqrt( omega_mz(z) / (cosmo_params_ufunc->OMm*Deltac_nonlinear(z))) *
pow( T/(mu * (1+z)), 1.5 );
/* if (!SUPRESS || (z >= z_re) ) // pre-reionization or don't worry about supression
return 7030.97 / hlittle * sqrt( omega_mz(z) / (OMm*Deltac_nonlinear(z)) ) *
pow( T/(mu * (1+z)), 1.5 );
if (z >= z_ss) // self-shielding dominates, use T = 1e4 K
return 7030.97 / hlittle * sqrt( omega_mz(z) / (OMm*Deltac_nonlinear(z)) ) *
pow( 1.0e4 /(mu * (1+z)), 1.5 );
// optically thin
return 7030.97 / hlittle * sqrt( omega_mz(z) / (OMm*Deltac_nonlinear(z)) ) *
pow( VcirtoT(v_ss, mu) /(mu * (1+z)), 1.5 );
*/
}
/* Physical (non-linear) overdensity at virialization (relative to critical density)
i.e. answer is rho / rho_crit
In Einstein de sitter model = 178
(fitting formula from Bryan & Norman 1998) */
double Deltac_nonlinear(float z){
double d;
d = omega_mz(z) - 1.0;
return 18*PI*PI + 82*d - 39*d*d;
}
/* Omega matter at redshift z */
double omega_mz(float z){
return cosmo_params_ufunc->OMm*pow(1+z,3) / (cosmo_params_ufunc->OMm*pow(1+z,3) + cosmo_params_ufunc->OMl + global_params.OMr*pow(1+z,4) + global_params.OMk*pow(1+z, 2));
}
/*
FUNCTION dicke(z)
Computes the dicke growth function at redshift z, i.e. the z dependance part of sigma
References: Peebles, "Large-Scale...", pg.53 (eq. 11.16). Includes omega<=1
Nonzero Lambda case from Liddle et al, astro-ph/9512102, eqs. 6-8.
and quintessence case from Wang et al, astro-ph/9804015
Normalized to dicke(z=0)=1
*/
double dicke(double z){
double omegaM_z, dick_z, dick_0, x, x_0;
double tiny = 1e-4;
if (fabs(cosmo_params_ufunc->OMm-1.0) < tiny){ //OMm = 1 (Einstein de-Sitter)
return 1.0/(1.0+z);
}
else if ( (cosmo_params_ufunc->OMl > (-tiny)) && (fabs(cosmo_params_ufunc->OMl+cosmo_params_ufunc->OMm+global_params.OMr-1.0) < 0.01) && (fabs(global_params.wl+1.0) < tiny) ){
//this is a flat, cosmological CONSTANT universe, with only lambda, matter and radiation
//it is taken from liddle et al.
omegaM_z = cosmo_params_ufunc->OMm*pow(1+z,3) / ( cosmo_params_ufunc->OMl + cosmo_params_ufunc->OMm*pow(1+z,3) + global_params.OMr*pow(1+z,4) );
dick_z = 2.5*omegaM_z / ( 1.0/70.0 + omegaM_z*(209-omegaM_z)/140.0 + pow(omegaM_z, 4.0/7.0) );
dick_0 = 2.5*cosmo_params_ufunc->OMm / ( 1.0/70.0 + cosmo_params_ufunc->OMm*(209-cosmo_params_ufunc->OMm)/140.0 + pow(cosmo_params_ufunc->OMm, 4.0/7.0) );
return dick_z / (dick_0 * (1.0+z));
}
else if ( (global_params.OMtot < (1+tiny)) && (fabs(cosmo_params_ufunc->OMl) < tiny) ){ //open, zero lambda case (peebles, pg. 53)
x_0 = 1.0/(cosmo_params_ufunc->OMm+0.0) - 1.0;
dick_0 = 1 + 3.0/x_0 + 3*log(sqrt(1+x_0)-sqrt(x_0))*sqrt(1+x_0)/pow(x_0,1.5);
x = fabs(1.0/(cosmo_params_ufunc->OMm+0.0) - 1.0) / (1+z);
dick_z = 1 + 3.0/x + 3*log(sqrt(1+x)-sqrt(x))*sqrt(1+x)/pow(x,1.5);
return dick_z/dick_0;
}
else if ( (cosmo_params_ufunc->OMl > (-tiny)) && (fabs(global_params.OMtot-1.0) < tiny) && (fabs(global_params.wl+1) > tiny) ){
LOG_WARNING("IN WANG.");
Throw ValueError;
}
LOG_ERROR("No growth function!");
Throw ValueError;
}
/* function DTDZ returns the value of dt/dz at the redshift parameter z. */
double dtdz(float z){
double x, dxdz, const1, denom, numer;
x = sqrt( cosmo_params_ufunc->OMl/cosmo_params_ufunc->OMm ) * pow(1+z, -3.0/2.0);
dxdz = sqrt( cosmo_params_ufunc->OMl/cosmo_params_ufunc->OMm ) * pow(1+z, -5.0/2.0) * (-3.0/2.0);
const1 = 2 * sqrt( 1 + cosmo_params_ufunc->OMm/cosmo_params_ufunc->OMl ) / (3.0 * Ho) ;
numer = dxdz * (1 + x*pow( pow(x,2) + 1, -0.5));
denom = x + sqrt(pow(x,2) + 1);
return (const1 * numer / denom);
}
/* Time derivative of the growth function at z */
double ddickedt(double z){
float dz = 1e-10;
double omegaM_z, ddickdz, dick_0, x, x_0, domegaMdz;
double tiny = 1e-4;
return (dicke(z+dz)-dicke(z))/dz/dtdz(z); // lazy non-analytic form getting
if (fabs(cosmo_params_ufunc->OMm-1.0) < tiny){ //OMm = 1 (Einstein de-Sitter)
return -pow(1+z,-2)/dtdz(z);
}
else if ( (cosmo_params_ufunc->OMl > (-tiny)) && (fabs(cosmo_params_ufunc->OMl+cosmo_params_ufunc->OMm+global_params.OMr-1.0) < 0.01) && (fabs(global_params.wl+1.0) < tiny) ){
//this is a flat, cosmological CONSTANT universe, with only lambda, matter and radiation
//it is taken from liddle et al.
omegaM_z = cosmo_params_ufunc->OMm*pow(1+z,3) / ( cosmo_params_ufunc->OMl + cosmo_params_ufunc->OMm*pow(1+z,3) + global_params.OMr*pow(1+z,4) );
domegaMdz = omegaM_z*3/(1+z) - cosmo_params_ufunc->OMm*pow(1+z,3)*pow(cosmo_params_ufunc->OMl + cosmo_params_ufunc->OMm*pow(1+z,3) + global_params.OMr*pow(1+z,4), -2) * (3*cosmo_params_ufunc->OMm*(1+z)*(1+z) + 4*global_params.OMr*pow(1+z,3));
dick_0 = cosmo_params_ufunc->OMm / ( 1.0/70.0 + cosmo_params_ufunc->OMm*(209-cosmo_params_ufunc->OMm)/140.0 + pow(cosmo_params_ufunc->OMm, 4.0/7.0) );
ddickdz = (domegaMdz/(1+z)) * (1.0/70.0*pow(omegaM_z,-2) + 1.0/140.0 + 3.0/7.0*pow(omegaM_z, -10.0/3.0)) * pow(1.0/70.0/omegaM_z + (209.0-omegaM_z)/140.0 + pow(omegaM_z, -3.0/7.0) , -2);
ddickdz -= pow(1+z,-2)/(1.0/70.0/omegaM_z + (209.0-omegaM_z)/140.0 + pow(omegaM_z, -3.0/7.0));
return ddickdz / dick_0 / dtdz(z);
}
LOG_ERROR("No growth function!");
Throw ValueError;
}
/* returns the hubble "constant" (in 1/sec) at z */
double hubble(float z){
return Ho*sqrt(cosmo_params_ufunc->OMm*pow(1+z,3) + global_params.OMr*pow(1+z,4) + cosmo_params_ufunc->OMl);
}
/* returns hubble time (in sec), t_h = 1/H */
double t_hubble(float z){
return 1.0/hubble(z);
}
/* comoving distance (in cm) per unit redshift */
double drdz(float z){
return (1.0+z)*C*dtdz(z);
}
/* returns the case A hydrogen recombination coefficient (Abel et al. 1997) in cm^3 s^-1*/
double alpha_A(double T){
double logT, ans;
logT = log(T/(double)1.1604505e4);
ans = pow(E, -28.6130338 - 0.72411256*logT - 2.02604473e-2*pow(logT, 2)
- 2.38086188e-3*pow(logT, 3) - 3.21260521e-4*pow(logT, 4)
- 1.42150291e-5*pow(logT, 5) + 4.98910892e-6*pow(logT, 6)
+ 5.75561414e-7*pow(logT, 7) - 1.85676704e-8*pow(logT, 8)
- 3.07113524e-9 * pow(logT, 9));
return ans;
}
/* returns the case B hydrogen recombination coefficient (Spitzer 1978) in cm^3 s^-1*/
double alpha_B(double T){
return alphaB_10k * pow (T/1.0e4, -0.75);
}
/*
Function NEUTRAL_FRACTION returns the hydrogen neutral fraction, chi, given:
hydrogen density (pcm^-3)
gas temperature (10^4 K)
ionization rate (1e-12 s^-1)
*/
double neutral_fraction(double density, double T4, double gamma, int usecaseB){
double chi, b, alpha, corr_He = 1.0/(4.0/global_params.Y_He - 3);
if (usecaseB)
alpha = alpha_B(T4*1e4);
else
alpha = alpha_A(T4*1e4);
gamma *= 1e-12;
// approximation chi << 1
chi = (1+corr_He)*density * alpha / gamma;
if (chi < TINY){ return 0;}
if (chi < 1e-5)
return chi;
// this code, while mathematically accurate, is numerically buggy for very small x_HI, so i will use valid approximation x_HI <<1 above when x_HI < 1e-5, and this otherwise... the two converge seemlessly
//get solutions of quadratic of chi (neutral fraction)
b = -2 - gamma / (density*(1+corr_He)*alpha);
chi = ( -b - sqrt(b*b - 4) ) / 2.0; //correct root
return chi;
}
/* function HeI_ion_crosssec returns the HI ionization cross section at parameter frequency
(taken from Verner et al (1996) */
double HeI_ion_crosssec(double nu){
double x,y,Fy;
if (nu < HeI_NUIONIZATION)
return 0;
x = nu/NU_over_EV/13.61 - 0.4434;
y = sqrt(x*x + pow(2.136, 2));
return 9.492e-16*((x-1)*(x-1) + 2.039*2.039) *
pow(y, (0.5 * 3.188 - 5.5))
* pow(1.0 + sqrt(y/1.469), -3.188);
}
/* function HeII_ion_crosssec returns the HeII ionization cross section at parameter frequency
(taken from Osterbrock, pg. 14) */
double HeII_ion_crosssec(double nu){
double epsilon, Z = 2;
if (nu < HeII_NUIONIZATION)
return 0;
if (nu == HeII_NUIONIZATION)
nu+=TINY;
epsilon = sqrt( nu/HeII_NUIONIZATION - 1);
return (6.3e-18)/Z/Z * pow(HeII_NUIONIZATION/nu, 4)
* pow(E, 4-(4*atan(epsilon)/epsilon)) / (1-pow(E, -2*PI/epsilon));
}
/* function HI_ion_crosssec returns the HI ionization cross section at parameter frequency
(taken from Osterbrock, pg. 14) */
double HI_ion_crosssec(double nu){
double epsilon, Z = 1;
if (nu < NUIONIZATION)
return 0;
if (nu == NUIONIZATION)
nu+=TINY;
epsilon = sqrt( nu/NUIONIZATION - 1);
return (6.3e-18)/Z/Z * pow(NUIONIZATION/nu, 4)
* pow(E, 4-(4*atan(epsilon)/epsilon)) / (1-pow(E, -2*PI/epsilon));
}
/* Return the thomspon scattering optical depth from zstart to zend through fully ionized IGM.
The hydrogen reionization history is given by the zarry and xHarry parameters, in increasing
redshift order of length len.*/
typedef struct{
float *z, *xH;
int len;
} tau_e_params;
double dtau_e_dz(double z, void *params){
float xH, xi;
int i=1;
tau_e_params p = *(tau_e_params *)params;
if ((p.len == 0) || !(p.z)) {
return (1+z)*(1+z)*drdz(z);
}
else{
// find where we are in the redshift array
if (p.z[0]>z) // ionization fraction is 1 prior to start of array
return (1+z)*(1+z)*drdz(z);
while ( (i < p.len) && (p.z[i] < z) ) {i++;}
if (i == p.len)
return 0;
// linearly interpolate in redshift
xH = p.xH[i-1] + (p.xH[i] - p.xH[i-1])/(p.z[i] - p.z[i-1]) * (z - p.z[i-1]);
xi = 1.0-xH;
if (xi<0){
LOG_WARNING("in taue: funny business xi=%e, changing to 0.", xi);
xi=0;
}
if (xi>1){
LOG_WARNING("in taue: funny business xi=%e, changing to 1", xi);
xi=1;
}
return xi*(1+z)*(1+z)*drdz(z);
}
}
double tau_e(float zstart, float zend, float *zarry, float *xHarry, int len){
double prehelium, posthelium, error;
gsl_function F;
double rel_tol = 1e-3; //<- relative tolerance
gsl_integration_workspace * w
= gsl_integration_workspace_alloc (1000);
tau_e_params p;
if (zstart >= zend){
LOG_ERROR("in tau_e: First parameter must be smaller than the second.\n");
Throw ValueError;
}
F.function = &dtau_e_dz;
p.z = zarry;
p.xH = xHarry;
p.len = len;
F.params = &p;
if ((len > 0) && zarry)
zend = zarry[len-1] - FRACT_FLOAT_ERR;
if (zend > global_params.Zreion_HeII){// && (zstart < Zreion_HeII)){
if (zstart < global_params.Zreion_HeII){
gsl_integration_qag (&F, global_params.Zreion_HeII, zstart, 0, rel_tol,
1000, GSL_INTEG_GAUSS61, w, &prehelium, &error);
gsl_integration_qag (&F, zend, global_params.Zreion_HeII, 0, rel_tol,
1000, GSL_INTEG_GAUSS61, w, &posthelium, &error);
}
else{
prehelium = 0;
gsl_integration_qag (&F, zend, zstart, 0, rel_tol,
1000, GSL_INTEG_GAUSS61, w, &posthelium, &error);
}
}
else{
posthelium = 0;
gsl_integration_qag (&F, zend, zstart, 0, rel_tol,
1000, GSL_INTEG_GAUSS61, w, &prehelium, &error);
}
gsl_integration_workspace_free (w);
return SIGMAT * ( (N_b0+He_No)*prehelium + N_b0*posthelium );
}
float ComputeTau(struct UserParams *user_params, struct CosmoParams *cosmo_params, int NPoints, float *redshifts, float *global_xHI) {
int i;
float tau;
Broadcast_struct_global_UF(user_params,cosmo_params);
tau = tau_e(0, redshifts[NPoints-1], redshifts, global_xHI, NPoints);
return tau;
}
void writeUserParams(struct UserParams *p){
LOG_INFO("UserParams: [HII_DIM=%d, DIM=%d, BOX_LEN=%f, HMF=%d, POWER_SPECTRUM=%d, USE_RELATIVE_VELOCITIES=%d, N_THREADS=%d, PERTURB_ON_HIGH_RES=%d, NO_RNG=%d, USE_FFTW_WISDOM=%d, USE_INTERPOLATION_TABLES=%d, FAST_FCOLL_TABLES=%d]",
p->HII_DIM, p->DIM, p->BOX_LEN, p->HMF, p->POWER_SPECTRUM, p->USE_RELATIVE_VELOCITIES, p->N_THREADS, p->PERTURB_ON_HIGH_RES, p->NO_RNG, p->USE_FFTW_WISDOM, p->USE_INTERPOLATION_TABLES, p->FAST_FCOLL_TABLES);
}
void writeCosmoParams(struct CosmoParams *p){
LOG_INFO("CosmoParams: [SIGMA_8=%f, hlittle=%f, OMm=%f, OMl=%f, OMb=%f, POWER_INDEX=%f]",
p->SIGMA_8, p->hlittle, p->OMm, p->OMl, p->OMb, p->POWER_INDEX);
}
void writeAstroParams(struct FlagOptions *fo, struct AstroParams *p){
if(fo->USE_MASS_DEPENDENT_ZETA) {
LOG_INFO("AstroParams: [HII_EFF_FACTOR=%f, ALPHA_STAR=%f, F_ESC10=%f (F_ESC7_MINI=%f), ALPHA_ESC=%f, M_TURN=%f, R_BUBBLE_MAX=%f, L_X=%e (L_X_MINI=%e), NU_X_THRESH=%f, X_RAY_SPEC_INDEX=%f, F_STAR10=%f (F_STAR7_MINI=%f), t_STAR=%f, N_RSD_STEPS=%f]",
p->HII_EFF_FACTOR, p->ALPHA_STAR, p->F_ESC10,p->F_ESC7_MINI, p->ALPHA_ESC, p->M_TURN,
p->R_BUBBLE_MAX, p->L_X, p->L_X_MINI, p->NU_X_THRESH, p->X_RAY_SPEC_INDEX, p->F_STAR10, p->F_STAR7_MINI, p->t_STAR, p->N_RSD_STEPS);
}
else {
LOG_INFO("AstroParams: [HII_EFF_FACTOR=%f, ION_Tvir_MIN=%f, X_RAY_Tvir_MIN=%f, R_BUBBLE_MAX=%f, L_X=%e, NU_X_THRESH=%f, X_RAY_SPEC_INDEX=%f, F_STAR10=%f, t_STAR=%f, N_RSD_STEPS=%f]",
p->HII_EFF_FACTOR, p->ION_Tvir_MIN, p->X_RAY_Tvir_MIN,
p->R_BUBBLE_MAX, p->L_X, p->NU_X_THRESH, p->X_RAY_SPEC_INDEX, p->F_STAR10, p->t_STAR, p->N_RSD_STEPS);
}
}
void writeFlagOptions(struct FlagOptions *p){
LOG_INFO("FlagOptions: [USE_HALO_FIELD=%d, USE_MINI_HALOS=%d, USE_MASS_DEPENDENT_ZETA=%d, SUBCELL_RSD=%d, INHOMO_RECO=%d, USE_TS_FLUCT=%d, M_MIN_in_Mass=%d, PHOTON_CONS=%d]",
p->USE_HALO_FIELD, p->USE_MINI_HALOS, p->USE_MASS_DEPENDENT_ZETA, p->SUBCELL_RSD, p->INHOMO_RECO, p->USE_TS_FLUCT, p->M_MIN_in_Mass, p->PHOTON_CONS);
}
char *print_output_header(int print_pid, const char *name){
char * pid = malloc(12*sizeof(char));
if(print_pid){
sprintf(pid, "<%d>\t", getpid());
}else{
sprintf(pid, "");
}
printf("%s%s:\n", pid, name);
return (pid);
}
void print_corners_real(float *x, int size){
int s = size-1;
int i,j,k;
for(i=0;i<size;i=i+s){
for(j=0;j<size;j=j+s){
for(k=0;k<size;k=k+s){
printf("%f, ", x[k + size*(j + size*i)]);
}
}
}
printf("\n");
}
void inspectInitialConditions(struct InitialConditions *x, int print_pid, int print_corners, int print_first,
int HII_DIM){
int i;
char *pid = print_output_header(print_pid, "InitialConditions");
if(print_first){
printf("%s\tFirstRow: ",pid);
printf("%s\t\tlowres_density: ");
for(i=0;i<10;i++){
printf("%f, ", x->lowres_density[i]);
}
printf("\n");
printf("%s\t\tlowres_vx : ");
for(i=0;i<10;i++){
printf("%f, ", x->lowres_vx[i]);
}
printf("\n");
printf("%s\t\tlowres_vx_2LPT: ");
for(i=0;i<10;i++){
printf("%f, ", x->lowres_vx_2LPT[i]);
}
printf("\n");
}
if(print_corners){
printf("%s\tCorners: ",pid);
printf("%s\t\tlowres_density: ",pid);
print_corners_real(x->lowres_density, HII_DIM);
printf("%s\t\tlowres_vx : ", pid);
print_corners_real(x->lowres_vx, HII_DIM);
printf("%s\t\tlowres_vx_2LPT: ", pid);
print_corners_real(x->lowres_vx_2LPT, HII_DIM);
}
}
void inspectPerturbedField(struct PerturbedField *x, int print_pid, int print_corners, int print_first,
int HII_DIM){
int i;
char *pid = print_output_header(print_pid, "PerturbedField");
if(print_first){
printf("%s\tFirstRow: \n",pid);
printf("%s\t\tdensity: ", pid);
for(i=0;i<10;i++){
printf("%f, ", x->density[i]);
}
printf("\n");
printf("%s\t\tvelocity: ", pid);
for(i=0;i<10;i++){
printf("%f, ", x->velocity[i]);
}
printf("\n");
}
if(print_corners){
printf("%s\tCorners: \n",pid);
printf("%s\t\tdensity: ",pid);
print_corners_real(x->density, HII_DIM);
printf("%s\t\tvelocity: ", pid);
print_corners_real(x->velocity, HII_DIM);
}
}
void inspectTsBox(struct TsBox *x, int print_pid, int print_corners, int print_first, int HII_DIM){
int i;
char *pid = print_output_header(print_pid, "TsBox");
if(print_first){
printf("%s\tFirstRow: ",pid);
printf("%s\t\tTs_box : ");
for(i=0;i<10;i++){
printf("%f, ", x->Ts_box[i]);
}
printf("\n");
printf("%s\t\tx_e_box: ");
for(i=0;i<10;i++){
printf("%f, ", x->x_e_box[i]);
}
printf("\n");
printf("%s\t\tTk_box : ");
for(i=0;i<10;i++){
printf("%f, ", x->Tk_box[i]);
}
printf("\n");
}
if(print_corners){
printf("%s\tCorners: ",pid);
printf("%s\t\tTs_box : ",pid);
print_corners_real(x->Ts_box, HII_DIM);
printf("%s\t\tx_e_box: ", pid);
print_corners_real(x->x_e_box, HII_DIM);
printf("%s\t\tTk_box : ", pid);
print_corners_real(x->Tk_box, HII_DIM);
}
}
void inspectIonizedBox(struct IonizedBox *x, int print_pid, int print_corners, int print_first, int HII_DIM){
int i;
char *pid = print_output_header(print_pid, "IonizedBox");
if(print_first){
printf("%s\tFirstRow: ",pid);
printf("%s\t\txH_box : ");
for(i=0;i<10;i++){
printf("%f, ", x->xH_box[i]);
}
printf("\n");
printf("%s\t\tGamma12_box: ");
for(i=0;i<10;i++){
printf("%f, ", x->Gamma12_box[i]);
}
printf("\n");
printf("%s\t\tz_re_box : ");
for(i=0;i<10;i++){
printf("%f, ", x->z_re_box[i]);
}
printf("\n");
printf("%s\t\tdNrec_box : ");
for(i=0;i<10;i++){
printf("%f, ", x->dNrec_box[i]);
}
printf("\n");
}
if(print_corners){
printf("%s\tCorners: ",pid);
printf("%s\t\txH_box : ",pid);
print_corners_real(x->xH_box, HII_DIM);
printf("%s\t\tGamma12_box: ", pid);
print_corners_real(x->Gamma12_box, HII_DIM);
printf("%s\t\tz_re_box : ", pid);
print_corners_real(x->z_re_box, HII_DIM);
printf("%s\t\tdNrec_box : ", pid);
print_corners_real(x->dNrec_box, HII_DIM);
}
}
void inspectBrightnessTemp(struct BrightnessTemp *x, int print_pid, int print_corners, int print_first, int HII_DIM){
int i;
char *pid = print_output_header(print_pid, "BrightnessTemp");
if(print_first){
printf("%s\tFirstRow: ",pid);
printf("%s\t\tbrightness_temp: ");
for(i=0;i<10;i++){
printf("%f, ", x->brightness_temp[i]);
}
printf("\n");
}
if(print_corners){
printf("%s\tCorners: ",pid);
printf("%s\t\tbrightness_temp: ",pid);
print_corners_real(x->brightness_temp, HII_DIM);
}
}
double atomic_cooling_threshold(float z){
return TtoM(z, 1e4, 0.59);
}
double molecular_cooling_threshold(float z){
return TtoM(z, 600, 1.22);
}
double lyman_werner_threshold(float z, float J_21_LW){
// this follows Visbal+15, which is taken as the optimal fit from Fialkov+12 which
// was calibrated with the simulations of Stacy+11 and Greif+11;
double mcrit_noLW = 3.314e7 * pow( 1.+z, -1.5);
return mcrit_noLW * (1. + 22.8685 * pow(J_21_LW, 0.47));
}
double reionization_feedback(float z, float Gamma_halo_HII, float z_IN){
if (z_IN<=1e-19)
return 1e-40;
return REION_SM13_M0 * pow(HALO_BIAS * Gamma_halo_HII, REION_SM13_A) * pow((1.+z)/10, REION_SM13_B) *
pow(1 - pow((1.+z)/(1.+z_IN), REION_SM13_C), REION_SM13_D);
}
/*
The following functions are simply for testing the exception framework
*/
void FunctionThatThrows(){
Throw(ParameterError);
}
int SomethingThatCatches(bool sub_func){
// A simple function that catches a thrown error.
int status;
Try{
if(sub_func) FunctionThatThrows();
else Throw(ParameterError);
}
Catch(status){
return status;
}
return 0;
}
int FunctionThatCatches(bool sub_func, bool pass, double *result){
int status;
if(!pass){
Try{
if(sub_func) FunctionThatThrows();
else Throw(ParameterError);
}
Catch(status){
LOG_DEBUG("Caught the problem with status %d.", status);
return status;
}
}
*result = 5.0;
return 0;
}
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