source stringlengths 3 92 | c stringlengths 26 2.25M |
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main.c | //===============================================================================================================================================================================================================
//===============================================================================================================================================================================================================
// DEFINE / INCLUDE
//===============================================================================================================================================================================================================
//===============================================================================================================================================================================================================
#include <stdlib.h>
#include <math.h>
#include <string.h>
#include <time.h>
#include "AVI/avilib.h"
#include "AVI/avimod.h"
#include <omp.h>
//#include "define.c"
#include "kernel.c"
//===============================================================================================================================================================================================================200
// WRITE DATA FUNCTION
//===============================================================================================================================================================================================================200
void write_data( char* filename,
int frameNo,
int frames_processed,
int endoPoints,
int* input_a,
int* input_b,
int epiPoints,
int* input_2a,
int* input_2b){
//================================================================================80
// VARIABLES
//================================================================================80
FILE* fid;
int i,j;
char c;
//================================================================================80
// OPEN FILE FOR READING
//================================================================================80
fid = fopen(filename, "w+");
if( fid == NULL ){
printf( "The file was not opened for writing\n" );
return;
}
//================================================================================80
// WRITE VALUES TO THE FILE
//================================================================================80
fprintf(fid, "Total AVI Frames: %d\n", frameNo);
fprintf(fid, "Frames Processed: %d\n", frames_processed);
fprintf(fid, "endoPoints: %d\n", endoPoints);
fprintf(fid, "epiPoints: %d", epiPoints);
for(j=0; j<frames_processed;j++)
{
fprintf(fid, "\n---Frame %d---",j);
fprintf(fid, "\n--endo--\n",j);
for(i=0; i<endoPoints; i++){
fprintf(fid, "%d\t", input_a[j+i*frameNo]);
}
fprintf(fid, "\n");
for(i=0; i<endoPoints; i++){
// if(input_b[j*size+i] > 2000) input_b[j*size+i]=0;
fprintf(fid, "%d\t", input_b[j+i*frameNo]);
}
fprintf(fid, "\n--epi--\n",j);
for(i=0; i<epiPoints; i++){
//if(input_2a[j*size_2+i] > 2000) input_2a[j*size_2+i]=0;
fprintf(fid, "%d\t", input_2a[j+i*frameNo]);
}
fprintf(fid, "\n");
for(i=0; i<epiPoints; i++){
//if(input_2b[j*size_2+i] > 2000) input_2b[j*size_2+i]=0;
fprintf(fid, "%d\t", input_2b[j+i*frameNo]);
}
}
// ================================================================================80
// CLOSE FILE
// ================================================================================80
fclose(fid);
}
//===============================================================================================================================================================================================================
//===============================================================================================================================================================================================================
// MAIN FUNCTION
//===============================================================================================================================================================================================================
//===============================================================================================================================================================================================================
int main(int argc, char *argv []){
//======================================================================================================================================================
// VARIABLES
//======================================================================================================================================================
// counters
int i;
int frames_processed;
// parameters
public_struct public;
private_struct private[ALL_POINTS];
//======================================================================================================================================================
// FRAMES
//======================================================================================================================================================
if(argc!=4){
printf("ERROR: usage: heartwall <inputfile> <num of frames> <num of threads>\n");
exit(1);
}
char* video_file_name;
video_file_name = argv[1];
avi_t* d_frames = (avi_t*)AVI_open_input_file(video_file_name, 1); // added casting
if (d_frames == NULL) {
AVI_print_error((char *) "Error with AVI_open_input_file");
return -1;
}
public.d_frames = d_frames;
public.frames = AVI_video_frames(public.d_frames);
public.frame_rows = AVI_video_height(public.d_frames);
public.frame_cols = AVI_video_width(public.d_frames);
public.frame_elem = public.frame_rows * public.frame_cols;
public.frame_mem = sizeof(fp) * public.frame_elem;
//======================================================================================================================================================
// CHECK INPUT ARGUMENTS
//======================================================================================================================================================
frames_processed = atoi(argv[2]);
if(frames_processed<0 || frames_processed>public.frames){
printf("ERROR: %d is an incorrect number of frames specified, select in the range of 0-%d\n", frames_processed, public.frames);
return 0;
}
int omp_num_threads;
omp_num_threads = atoi(argv[3]);
if (omp_num_threads <=0){
printf ("num of threads must be a positive integer");
return 0;
}
printf("num of threads: %d\n", omp_num_threads);
//======================================================================================================================================================
// INPUTS
//======================================================================================================================================================
//====================================================================================================
// ENDO POINTS
//====================================================================================================
public.endoPoints = ENDO_POINTS;
public.d_endo_mem = sizeof(int) * public.endoPoints;
public.d_endoRow = (int *)malloc(public.d_endo_mem);
public.d_endoRow[ 0] = 369;
public.d_endoRow[ 1] = 400;
public.d_endoRow[ 2] = 429;
public.d_endoRow[ 3] = 452;
public.d_endoRow[ 4] = 476;
public.d_endoRow[ 5] = 486;
public.d_endoRow[ 6] = 479;
public.d_endoRow[ 7] = 458;
public.d_endoRow[ 8] = 433;
public.d_endoRow[ 9] = 404;
public.d_endoRow[10] = 374;
public.d_endoRow[11] = 346;
public.d_endoRow[12] = 318;
public.d_endoRow[13] = 294;
public.d_endoRow[14] = 277;
public.d_endoRow[15] = 269;
public.d_endoRow[16] = 275;
public.d_endoRow[17] = 287;
public.d_endoRow[18] = 311;
public.d_endoRow[19] = 339;
public.d_endoCol = (int *)malloc(public.d_endo_mem);
public.d_endoCol[ 0] = 408;
public.d_endoCol[ 1] = 406;
public.d_endoCol[ 2] = 397;
public.d_endoCol[ 3] = 383;
public.d_endoCol[ 4] = 354;
public.d_endoCol[ 5] = 322;
public.d_endoCol[ 6] = 294;
public.d_endoCol[ 7] = 270;
public.d_endoCol[ 8] = 250;
public.d_endoCol[ 9] = 237;
public.d_endoCol[10] = 235;
public.d_endoCol[11] = 241;
public.d_endoCol[12] = 254;
public.d_endoCol[13] = 273;
public.d_endoCol[14] = 300;
public.d_endoCol[15] = 328;
public.d_endoCol[16] = 356;
public.d_endoCol[17] = 383;
public.d_endoCol[18] = 401;
public.d_endoCol[19] = 411;
public.d_tEndoRowLoc = (int *)malloc(public.d_endo_mem * public.frames);
public.d_tEndoColLoc = (int *)malloc(public.d_endo_mem * public.frames);
//====================================================================================================
// EPI POINTS
//====================================================================================================
public.epiPoints = EPI_POINTS;
public.d_epi_mem = sizeof(int) * public.epiPoints;
public.d_epiRow = (int *)malloc(public.d_epi_mem);
public.d_epiRow[ 0] = 390;
public.d_epiRow[ 1] = 419;
public.d_epiRow[ 2] = 448;
public.d_epiRow[ 3] = 474;
public.d_epiRow[ 4] = 501;
public.d_epiRow[ 5] = 519;
public.d_epiRow[ 6] = 535;
public.d_epiRow[ 7] = 542;
public.d_epiRow[ 8] = 543;
public.d_epiRow[ 9] = 538;
public.d_epiRow[10] = 528;
public.d_epiRow[11] = 511;
public.d_epiRow[12] = 491;
public.d_epiRow[13] = 466;
public.d_epiRow[14] = 438;
public.d_epiRow[15] = 406;
public.d_epiRow[16] = 376;
public.d_epiRow[17] = 347;
public.d_epiRow[18] = 318;
public.d_epiRow[19] = 291;
public.d_epiRow[20] = 275;
public.d_epiRow[21] = 259;
public.d_epiRow[22] = 256;
public.d_epiRow[23] = 252;
public.d_epiRow[24] = 252;
public.d_epiRow[25] = 257;
public.d_epiRow[26] = 266;
public.d_epiRow[27] = 283;
public.d_epiRow[28] = 305;
public.d_epiRow[29] = 331;
public.d_epiRow[30] = 360;
public.d_epiCol = (int *)malloc(public.d_epi_mem);
public.d_epiCol[ 0] = 457;
public.d_epiCol[ 1] = 454;
public.d_epiCol[ 2] = 446;
public.d_epiCol[ 3] = 431;
public.d_epiCol[ 4] = 411;
public.d_epiCol[ 5] = 388;
public.d_epiCol[ 6] = 361;
public.d_epiCol[ 7] = 331;
public.d_epiCol[ 8] = 301;
public.d_epiCol[ 9] = 273;
public.d_epiCol[10] = 243;
public.d_epiCol[11] = 218;
public.d_epiCol[12] = 196;
public.d_epiCol[13] = 178;
public.d_epiCol[14] = 166;
public.d_epiCol[15] = 157;
public.d_epiCol[16] = 155;
public.d_epiCol[17] = 165;
public.d_epiCol[18] = 177;
public.d_epiCol[19] = 197;
public.d_epiCol[20] = 218;
public.d_epiCol[21] = 248;
public.d_epiCol[22] = 276;
public.d_epiCol[23] = 304;
public.d_epiCol[24] = 333;
public.d_epiCol[25] = 361;
public.d_epiCol[26] = 391;
public.d_epiCol[27] = 415;
public.d_epiCol[28] = 434;
public.d_epiCol[29] = 448;
public.d_epiCol[30] = 455;
public.d_tEpiRowLoc = (int *)malloc(public.d_epi_mem * public.frames);
public.d_tEpiColLoc = (int *)malloc(public.d_epi_mem * public.frames);
//====================================================================================================
// ALL POINTS
//====================================================================================================
public.allPoints = ALL_POINTS;
//======================================================================================================================================================
// CONSTANTS
//======================================================================================================================================================
public.tSize = 25;
public.sSize = 40;
public.maxMove = 10;
public.alpha = 0.87;
//======================================================================================================================================================
// SUMS
//======================================================================================================================================================
for(i=0; i<public.allPoints; i++){
private[i].in_partial_sum = (fp *)malloc(sizeof(fp) * 2*public.tSize+1);
private[i].in_sqr_partial_sum = (fp *)malloc(sizeof(fp) * 2*public.tSize+1);
private[i].par_max_val = (fp *)malloc(sizeof(fp) * (2*public.tSize+2*public.sSize+1));
private[i].par_max_coo = (int *)malloc(sizeof(int) * (2*public.tSize+2*public.sSize+1));
}
//======================================================================================================================================================
// INPUT 2 (SAMPLE AROUND POINT)
//======================================================================================================================================================
public.in2_rows = 2 * public.sSize + 1;
public.in2_cols = 2 * public.sSize + 1;
public.in2_elem = public.in2_rows * public.in2_cols;
public.in2_mem = sizeof(fp) * public.in2_elem;
for(i=0; i<public.allPoints; i++){
private[i].d_in2 = (fp *)malloc(public.in2_mem);
private[i].d_in2_sqr = (fp *)malloc(public.in2_mem);
}
//======================================================================================================================================================
// INPUT (POINT TEMPLATE)
//======================================================================================================================================================
public.in_mod_rows = public.tSize+1+public.tSize;
public.in_mod_cols = public.in_mod_rows;
public.in_mod_elem = public.in_mod_rows * public.in_mod_cols;
public.in_mod_mem = sizeof(fp) * public.in_mod_elem;
for(i=0; i<public.allPoints; i++){
private[i].d_in_mod = (fp *)malloc(public.in_mod_mem);
private[i].d_in_sqr = (fp *)malloc(public.in_mod_mem);
}
//======================================================================================================================================================
// ARRAY OF TEMPLATES FOR ALL POINTS
//======================================================================================================================================================
public.d_endoT = (fp *)malloc(public.in_mod_mem * public.endoPoints);
public.d_epiT = (fp *)malloc(public.in_mod_mem * public.epiPoints);
//======================================================================================================================================================
// SETUP private POINTERS TO ROWS, COLS AND TEMPLATE
//======================================================================================================================================================
for(i=0; i<public.endoPoints; i++){
private[i].point_no = i;
private[i].in_pointer = private[i].point_no * public.in_mod_elem;
private[i].d_Row = public.d_endoRow; // original row coordinates
private[i].d_Col = public.d_endoCol; // original col coordinates
private[i].d_tRowLoc = public.d_tEndoRowLoc; // updated row coordinates
private[i].d_tColLoc = public.d_tEndoColLoc; // updated row coordinates
private[i].d_T = public.d_endoT; // templates
}
for(i=public.endoPoints; i<public.allPoints; i++){
private[i].point_no = i-public.endoPoints;
private[i].in_pointer = private[i].point_no * public.in_mod_elem;
private[i].d_Row = public.d_epiRow;
private[i].d_Col = public.d_epiCol;
private[i].d_tRowLoc = public.d_tEpiRowLoc;
private[i].d_tColLoc = public.d_tEpiColLoc;
private[i].d_T = public.d_epiT;
}
//======================================================================================================================================================
// CONVOLUTION
//======================================================================================================================================================
public.ioffset = 0;
public.joffset = 0;
public.conv_rows = public.in_mod_rows + public.in2_rows - 1; // number of rows in I
public.conv_cols = public.in_mod_cols + public.in2_cols - 1; // number of columns in I
public.conv_elem = public.conv_rows * public.conv_cols; // number of elements
public.conv_mem = sizeof(fp) * public.conv_elem;
for(i=0; i<public.allPoints; i++){
private[i].d_conv = (fp *)malloc(public.conv_mem);
}
//======================================================================================================================================================
// CUMULATIVE SUM
//======================================================================================================================================================
//====================================================================================================
// PAD ARRAY
//====================================================================================================
//====================================================================================================
// VERTICAL CUMULATIVE SUM
//====================================================================================================
public.in2_pad_add_rows = public.in_mod_rows;
public.in2_pad_add_cols = public.in_mod_cols;
public.in2_pad_rows = public.in2_rows + 2*public.in2_pad_add_rows;
public.in2_pad_cols = public.in2_cols + 2*public.in2_pad_add_cols;
public.in2_pad_elem = public.in2_pad_rows * public.in2_pad_cols;
public.in2_pad_mem = sizeof(fp) * public.in2_pad_elem;
for(i=0; i<public.allPoints; i++){
private[i].d_in2_pad = (fp *)malloc(public.in2_pad_mem);
}
//====================================================================================================
// SELECTION, SELECTION 2, SUBTRACTION
//====================================================================================================
//====================================================================================================
// HORIZONTAL CUMULATIVE SUM
//====================================================================================================
public.in2_pad_cumv_sel_rowlow = 1 + public.in_mod_rows; // (1 to n+1)
public.in2_pad_cumv_sel_rowhig = public.in2_pad_rows - 1;
public.in2_pad_cumv_sel_collow = 1;
public.in2_pad_cumv_sel_colhig = public.in2_pad_cols;
public.in2_pad_cumv_sel2_rowlow = 1;
public.in2_pad_cumv_sel2_rowhig = public.in2_pad_rows - public.in_mod_rows - 1;
public.in2_pad_cumv_sel2_collow = 1;
public.in2_pad_cumv_sel2_colhig = public.in2_pad_cols;
public.in2_sub_rows = public.in2_pad_cumv_sel_rowhig - public.in2_pad_cumv_sel_rowlow + 1;
public.in2_sub_cols = public.in2_pad_cumv_sel_colhig - public.in2_pad_cumv_sel_collow + 1;
public.in2_sub_elem = public.in2_sub_rows * public.in2_sub_cols;
public.in2_sub_mem = sizeof(fp) * public.in2_sub_elem;
for(i=0; i<public.allPoints; i++){
private[i].d_in2_sub = (fp *)malloc(public.in2_sub_mem);
}
//====================================================================================================
// SELECTION, SELECTION 2, SUBTRACTION, SQUARE, NUMERATOR
//====================================================================================================
public.in2_sub_cumh_sel_rowlow = 1;
public.in2_sub_cumh_sel_rowhig = public.in2_sub_rows;
public.in2_sub_cumh_sel_collow = 1 + public.in_mod_cols;
public.in2_sub_cumh_sel_colhig = public.in2_sub_cols - 1;
public.in2_sub_cumh_sel2_rowlow = 1;
public.in2_sub_cumh_sel2_rowhig = public.in2_sub_rows;
public.in2_sub_cumh_sel2_collow = 1;
public.in2_sub_cumh_sel2_colhig = public.in2_sub_cols - public.in_mod_cols - 1;
public.in2_sub2_sqr_rows = public.in2_sub_cumh_sel_rowhig - public.in2_sub_cumh_sel_rowlow + 1;
public.in2_sub2_sqr_cols = public.in2_sub_cumh_sel_colhig - public.in2_sub_cumh_sel_collow + 1;
public.in2_sub2_sqr_elem = public.in2_sub2_sqr_rows * public.in2_sub2_sqr_cols;
public.in2_sub2_sqr_mem = sizeof(fp) * public.in2_sub2_sqr_elem;
for(i=0; i<public.allPoints; i++){
private[i].d_in2_sub2_sqr = (fp *)malloc(public.in2_sub2_sqr_mem);
}
//======================================================================================================================================================
// CUMULATIVE SUM 2
//======================================================================================================================================================
//====================================================================================================
// PAD ARRAY
//====================================================================================================
//====================================================================================================
// VERTICAL CUMULATIVE SUM
//====================================================================================================
//====================================================================================================
// SELECTION, SELECTION 2, SUBTRACTION
//====================================================================================================
//====================================================================================================
// HORIZONTAL CUMULATIVE SUM
//====================================================================================================
//====================================================================================================
// SELECTION, SELECTION 2, SUBTRACTION, DIFFERENTIAL LOCAL SUM, DENOMINATOR A, DENOMINATOR, CORRELATION
//====================================================================================================
//======================================================================================================================================================
// TEMPLATE MASK CREATE
//======================================================================================================================================================
public.tMask_rows = public.in_mod_rows + (public.sSize+1+public.sSize) - 1;
public.tMask_cols = public.tMask_rows;
public.tMask_elem = public.tMask_rows * public.tMask_cols;
public.tMask_mem = sizeof(fp) * public.tMask_elem;
for(i=0; i<public.allPoints; i++){
private[i].d_tMask = (fp *)malloc(public.tMask_mem);
}
//======================================================================================================================================================
// POINT MASK INITIALIZE
//======================================================================================================================================================
public.mask_rows = public.maxMove;
public.mask_cols = public.mask_rows;
public.mask_elem = public.mask_rows * public.mask_cols;
public.mask_mem = sizeof(fp) * public.mask_elem;
//======================================================================================================================================================
// MASK CONVOLUTION
//======================================================================================================================================================
public.mask_conv_rows = public.tMask_rows; // number of rows in I
public.mask_conv_cols = public.tMask_cols; // number of columns in I
public.mask_conv_elem = public.mask_conv_rows * public.mask_conv_cols; // number of elements
public.mask_conv_mem = sizeof(fp) * public.mask_conv_elem;
public.mask_conv_ioffset = (public.mask_rows-1)/2;
if((public.mask_rows-1) % 2 > 0.5){
public.mask_conv_ioffset = public.mask_conv_ioffset + 1;
}
public.mask_conv_joffset = (public.mask_cols-1)/2;
if((public.mask_cols-1) % 2 > 0.5){
public.mask_conv_joffset = public.mask_conv_joffset + 1;
}
for(i=0; i<public.allPoints; i++){
private[i].d_mask_conv = (fp *)malloc(public.mask_conv_mem);
}
//======================================================================================================================================================
// PRINT FRAME PROGRESS START
//======================================================================================================================================================
printf("frame progress: ");
fflush(NULL);
//======================================================================================================================================================
// KERNEL
//======================================================================================================================================================
for(public.frame_no=0; public.frame_no<frames_processed; public.frame_no++){
//====================================================================================================
// GETTING FRAME
//====================================================================================================
// Extract a cropped version of the first frame from the video file
public.d_frame = get_frame(public.d_frames, // pointer to video file
public.frame_no, // number of frame that needs to be returned
0, // cropped?
0, // scaled?
1); // converted
//====================================================================================================
// PROCESSING
//====================================================================================================
omp_set_num_threads(omp_num_threads);
#pragma omp parallel for
for(i=0; i<public.allPoints; i++){
kernel( public,
private[i]);
}
//====================================================================================================
// FREE MEMORY FOR FRAME
//====================================================================================================
// free frame after each loop iteration, since AVI library allocates memory for every frame fetched
free(public.d_frame);
//====================================================================================================
// PRINT FRAME PROGRESS
//====================================================================================================
printf("%d ", public.frame_no);
fflush(NULL);
}
//======================================================================================================================================================
// PRINT FRAME PROGRESS END
//======================================================================================================================================================
printf("\n");
fflush(NULL);
//======================================================================================================================================================
// DEALLOCATION
//======================================================================================================================================================
//==================================================50
// DUMP DATA TO FILE
//==================================================50
#ifdef OUTPUT
write_data( "result.txt",
public.frames,
frames_processed,
public.endoPoints,
public.d_tEndoRowLoc,
public.d_tEndoColLoc,
public.epiPoints,
public.d_tEpiRowLoc,
public.d_tEpiColLoc);
#endif
//====================================================================================================
// COMMON
//====================================================================================================
free(public.d_endoRow);
free(public.d_endoCol);
free(public.d_tEndoRowLoc);
free(public.d_tEndoColLoc);
free(public.d_endoT);
free(public.d_epiRow);
free(public.d_epiCol);
free(public.d_tEpiRowLoc);
free(public.d_tEpiColLoc);
free(public.d_epiT);
//====================================================================================================
// POINTERS
//====================================================================================================
for(i=0; i<public.allPoints; i++){
free(private[i].in_partial_sum);
free(private[i].in_sqr_partial_sum);
free(private[i].par_max_val);
free(private[i].par_max_coo);
free(private[i].d_in2);
free(private[i].d_in2_sqr);
free(private[i].d_in_mod);
free(private[i].d_in_sqr);
free(private[i].d_conv);
free(private[i].d_in2_pad);
free(private[i].d_in2_sub);
free(private[i].d_in2_sub2_sqr);
free(private[i].d_tMask);
free(private[i].d_mask_conv);
}
}
//========================================================================================================================================================================================================
//========================================================================================================================================================================================================
// END OF FILE
//========================================================================================================================================================================================================
//========================================================================================================================================================================================================
|
convolutiondepthwise_3x3_int8.h | // BUG1989 is pleased to support the open source community by supporting ncnn available.
//
// Copyright (C) 2019 BUG1989. 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 convdw3x3s1_int8_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& _kernel, const Option& opt)
{
int w = bottom_blob.w;
//int h = bottom_blob.h;
//int inch = bottom_blob.c;
int outw = top_blob.w;
int outh = top_blob.h;
int outch = top_blob.c;
const signed char* kernel = _kernel;
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < outch; p++)
{
Mat out = top_blob.channel(p);
out.fill(0);
const signed char* kernel0 = (const signed char*)kernel + p * 9;
int* outptr = out;
const signed char* img0 = bottom_blob.channel(p);
const signed char* r0 = img0;
const signed char* r1 = img0 + w;
const signed char* r2 = img0 + w * 2;
int i = 0;
for (; i < outh; i++)
{
int remain = outw;
for (; remain > 0; remain--)
{
int sum = 0;
sum += (int)r0[0] * (int)kernel0[0];
sum += (int)r0[1] * (int)kernel0[1];
sum += (int)r0[2] * (int)kernel0[2];
sum += (int)r1[0] * (int)kernel0[3];
sum += (int)r1[1] * (int)kernel0[4];
sum += (int)r1[2] * (int)kernel0[5];
sum += (int)r2[0] * (int)kernel0[6];
sum += (int)r2[1] * (int)kernel0[7];
sum += (int)r2[2] * (int)kernel0[8];
*outptr += sum;
r0++;
r1++;
r2++;
outptr++;
}
r0 += 2;
r1 += 2;
r2 += 2;
}
}
}
static void convdw3x3s2_int8_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& _kernel, const Option& opt)
{
int w = bottom_blob.w;
//int h = bottom_blob.h;
//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 signed char* kernel = _kernel;
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < outch; p++)
{
Mat out = top_blob.channel(p);
out.fill(0);
const signed char* kernel0 = (const signed char*)kernel + p * 9;
int* outptr = out;
const signed char* img0 = bottom_blob.channel(p);
const signed char* r0 = img0;
const signed char* r1 = img0 + w;
const signed char* r2 = img0 + w * 2;
int i = 0;
for (; i < outh; i++)
{
int remain = outw;
for (; remain > 0; remain--)
{
int sum = 0;
sum += (int)r0[0] * (int)kernel0[0];
sum += (int)r0[1] * (int)kernel0[1];
sum += (int)r0[2] * (int)kernel0[2];
sum += (int)r1[0] * (int)kernel0[3];
sum += (int)r1[1] * (int)kernel0[4];
sum += (int)r1[2] * (int)kernel0[5];
sum += (int)r2[0] * (int)kernel0[6];
sum += (int)r2[1] * (int)kernel0[7];
sum += (int)r2[2] * (int)kernel0[8];
*outptr += sum;
r0 += 2;
r1 += 2;
r2 += 2;
outptr++;
}
r0 += tailstep;
r1 += tailstep;
r2 += tailstep;
}
}
}
static void convdw3x3s1_int8_dequant_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& _kernel, const Mat& _bias, std::vector<float> scales_dequant, const Option& opt)
{
int w = bottom_blob.w;
//int h = bottom_blob.h;
//int inch = bottom_blob.c;
int outw = top_blob.w;
int outh = top_blob.h;
int outch = top_blob.c;
const signed char* kernel = _kernel;
const float* bias = _bias;
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < outch; p++)
{
Mat out = top_blob.channel(p);
float* outptr = out;
const float bias0 = bias ? bias[p] : 0.f;
const float scale_dequant = scales_dequant[p];
out.fill(bias0);
const signed char* kernel0 = (const signed char*)kernel + p * 9;
const signed char* img0 = bottom_blob.channel(p);
const signed char* r0 = img0;
const signed char* r1 = img0 + w;
const signed char* r2 = img0 + w * 2;
int i = 0;
for (; i < outh; i++)
{
int remain = outw;
for (; remain > 0; remain--)
{
int sum = 0;
sum += (int)r0[0] * (int)kernel0[0];
sum += (int)r0[1] * (int)kernel0[1];
sum += (int)r0[2] * (int)kernel0[2];
sum += (int)r1[0] * (int)kernel0[3];
sum += (int)r1[1] * (int)kernel0[4];
sum += (int)r1[2] * (int)kernel0[5];
sum += (int)r2[0] * (int)kernel0[6];
sum += (int)r2[1] * (int)kernel0[7];
sum += (int)r2[2] * (int)kernel0[8];
*outptr += (float)sum * scale_dequant;
r0++;
r1++;
r2++;
outptr++;
}
r0 += 2;
r1 += 2;
r2 += 2;
}
}
}
static void convdw3x3s2_int8_dequant_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& _kernel, const Mat& _bias, std::vector<float> scales_dequant, const Option& opt)
{
int w = bottom_blob.w;
//int h = bottom_blob.h;
//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 signed char* kernel = _kernel;
const float* bias = _bias;
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < outch; p++)
{
Mat out = top_blob.channel(p);
float* outptr = out;
const float bias0 = bias ? bias[p] : 0.f;
const float scale_dequant = scales_dequant[p];
out.fill(bias0);
const signed char* kernel0 = (const signed char*)kernel + p * 9;
const signed char* img0 = bottom_blob.channel(p);
const signed char* r0 = img0;
const signed char* r1 = img0 + w;
const signed char* r2 = img0 + w * 2;
int i = 0;
for (; i < outh; i++)
{
int remain = outw;
for (; remain > 0; remain--)
{
int sum = 0;
sum += (int)r0[0] * (int)kernel0[0];
sum += (int)r0[1] * (int)kernel0[1];
sum += (int)r0[2] * (int)kernel0[2];
sum += (int)r1[0] * (int)kernel0[3];
sum += (int)r1[1] * (int)kernel0[4];
sum += (int)r1[2] * (int)kernel0[5];
sum += (int)r2[0] * (int)kernel0[6];
sum += (int)r2[1] * (int)kernel0[7];
sum += (int)r2[2] * (int)kernel0[8];
*outptr += (float)sum * scale_dequant;
r0 += 2;
r1 += 2;
r2 += 2;
outptr++;
}
r0 += tailstep;
r1 += tailstep;
r2 += tailstep;
}
}
}
static void convdw3x3s1_int8_requant_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& _kernel, const Mat& _bias, std::vector<float> scales_requant, const Option& opt)
{
int w = bottom_blob.w;
//int h = bottom_blob.h;
//int inch = bottom_blob.c;
int outw = top_blob.w;
int outh = top_blob.h;
int outch = top_blob.c;
const signed char* kernel = _kernel;
const float* bias = _bias;
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < outch; p++)
{
Mat out = top_blob.channel(p);
signed char* outptr = out;
const float bias0 = bias ? bias[p] : 0.f;
const float scale_requant_in = scales_requant[2 * p];
const float scale_requant_out = scales_requant[2 * p + 1];
const signed char* kernel0 = (const signed char*)kernel + p * 9;
const signed char* img0 = bottom_blob.channel(p);
const signed char* r0 = img0;
const signed char* r1 = img0 + w;
const signed char* r2 = img0 + w * 2;
int i = 0;
for (; i < outh; i++)
{
int remain = outw;
for (; remain > 0; remain--)
{
int sum = 0;
sum += (int)r0[0] * (int)kernel0[0];
sum += (int)r0[1] * (int)kernel0[1];
sum += (int)r0[2] * (int)kernel0[2];
sum += (int)r1[0] * (int)kernel0[3];
sum += (int)r1[1] * (int)kernel0[4];
sum += (int)r1[2] * (int)kernel0[5];
sum += (int)r2[0] * (int)kernel0[6];
sum += (int)r2[1] * (int)kernel0[7];
sum += (int)r2[2] * (int)kernel0[8];
*outptr = float2int8(((float)sum * scale_requant_in + bias0) * scale_requant_out);
r0++;
r1++;
r2++;
outptr++;
}
r0 += 2;
r1 += 2;
r2 += 2;
}
}
}
static void convdw3x3s2_int8_requant_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& _kernel, const Mat& _bias, std::vector<float> scales_requant, const Option& opt)
{
int w = bottom_blob.w;
//int h = bottom_blob.h;
//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 signed char* kernel = _kernel;
const float* bias = _bias;
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < outch; p++)
{
Mat out = top_blob.channel(p);
signed char* outptr = out;
const float bias0 = bias ? bias[p] : 0.f;
const float scale_requant_in = scales_requant[2 * p];
const float scale_requant_out = scales_requant[2 * p + 1];
const signed char* kernel0 = (const signed char*)kernel + p * 9;
const signed char* img0 = bottom_blob.channel(p);
const signed char* r0 = img0;
const signed char* r1 = img0 + w;
const signed char* r2 = img0 + w * 2;
int i = 0;
for (; i < outh; i++)
{
int remain = outw;
for (; remain > 0; remain--)
{
int sum = 0;
sum += (int)r0[0] * (int)kernel0[0];
sum += (int)r0[1] * (int)kernel0[1];
sum += (int)r0[2] * (int)kernel0[2];
sum += (int)r1[0] * (int)kernel0[3];
sum += (int)r1[1] * (int)kernel0[4];
sum += (int)r1[2] * (int)kernel0[5];
sum += (int)r2[0] * (int)kernel0[6];
sum += (int)r2[1] * (int)kernel0[7];
sum += (int)r2[2] * (int)kernel0[8];
*outptr = float2int8(((float)sum * scale_requant_in + bias0) * scale_requant_out);
r0 += 2;
r1 += 2;
r2 += 2;
outptr++;
}
r0 += tailstep;
r1 += tailstep;
r2 += tailstep;
}
}
} |
multiplication.h | #ifndef MULTIPLICATION_H
#define MULTIPLICATION_H
#include <omp.h>
#include <sys/time.h>
#include "matrix.h"
ull mstandard(ull ar, ull ac, // Matrix A rows and cols
ull br, ull bc, // Matrix B rows and cols
ul threads) // Number of threads
{
timeval start, end;
matrix* A = alloc(ar, ac),
* B = alloc(br, bc),
* C = alloc(ar, bc); // Result
fill(A);
fill(B);
gettimeofday(&start, NULL);
/**
* Simple method
*/
#pragma omp parallel shared(C) num_threads(threads)
{
ull i = 0, j = 0, k = 0;
#pragma omp for private(i, j, k)
iterate(, i, A->rows) {
iterate(, j, B->cols) {
T dot = 0; // Store multiplication result
iterate(, k, A->cols) {
dot += A(i, k) * B(k, j);
}
C(i, j) = dot;
}
}
}
gettimeofday(&end, NULL);
#ifdef WRITE
write(C, "product.txt");
printf("\tResult matrix is written to `product.txt`\n");
#endif
dealloc(A);
dealloc(B);
dealloc(C);
return ELAPSED;
}
ull mblocks(ull ar, ull ac, ull br, ull bc, ul threads)
{
timeval start, end;
matrix* A = alloc(ar, ac),
* B = alloc(br, bc),
* C = alloc(ar, bc);
fill(A);
fill(B);
gettimeofday(&start, NULL);
/**
* Block method
*/
#pragma omp parallel shared(C) num_threads(threads)
{
ull lt = threads,
iv = 0, ih = 0;
#pragma omp for schedule(static) collapse(2)
iterate(, iv, lt) { // Vertical block index
iterate(, ih, lt) { // Horizontal block index
for (ull i = iv * A->rows / lt; i < (iv + 1) * A->rows / lt; ++i) {
for (ull j = ih * A->cols / lt; j < (ih + 1) * A->cols / lt; ++j) {
iterate(ull, k, A->cols) {
C(i, j) += A(i, k) * B(k, j);
}
}
}
}
}
}
gettimeofday(&end, NULL);
#ifdef WRITE
write(C, "product.txt");
#endif
dealloc(A);
dealloc(B);
dealloc(C);
return ELAPSED;
}
ull mcheckerboard(ull ar, ull ac, ull br, ull bc, ul threads)
{
timeval start, end;
matrix* A = alloc(ar, ac),
* B = alloc(br, bc),
* C = alloc(ar, bc);
fill(A);
fill(B);
gettimeofday(&start, NULL);
/**
* Checkerboard method
*/
#pragma omp parallel shared(C)
{
ull bv = threads, // Vertical blocks
bh = threads, // Horizontal blocks
bk = threads, // K blocks
iv = 0, ih = 0, ik = 0; // Indices
#pragma omp for collapse(2)
iterate(, iv, bv) {
iterate(, ih, bh) {
iterate(, ik, bk) {
for (ull i = iv * A->rows / bv; i < (iv + 1) * A->rows / bv; ++i) {
for (ull j = ih * B->cols / bh; j < (ih + 1) * B->cols / bh; ++j) {
for (ull k = ik * A->cols / bk; k < (ik + 1) * A->cols / bk; ++k) {
#pragma omp atomic
C(i, j) += A(i, k) * B(k, j);
}
}
}
}
}
}
}
gettimeofday(&end, NULL);
#ifdef WRITE
write(C, "product.txt");
#endif
dealloc(A);
dealloc(B);
dealloc(C);
return ELAPSED;
}
#endif // MULTIPLICATION_H
|
GB_binop__eq_int8.c | //------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB_AaddB__eq_int8
// A.*B function (eWiseMult): GB_AemultB__eq_int8
// A*D function (colscale): GB_AxD__eq_int8
// D*A function (rowscale): GB_DxB__eq_int8
// C+=B function (dense accum): GB_Cdense_accumB__eq_int8
// C+=b function (dense accum): GB_Cdense_accumb__eq_int8
// C+=A+B function (dense ewise3): (none)
// C=A+B function (dense ewise3): GB_Cdense_ewise3_noaccum__eq_int8
// C=scalar+B GB_bind1st__eq_int8
// C=scalar+B' GB_bind1st_tran__eq_int8
// C=A+scalar GB_bind2nd__eq_int8
// C=A'+scalar GB_bind2nd_tran__eq_int8
// C type: bool
// A type: int8_t
// B,b type: int8_t
// BinaryOp: cij = (aij == bij)
#define GB_ATYPE \
int8_t
#define GB_BTYPE \
int8_t
#define GB_CTYPE \
bool
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
0
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
0
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
int8_t aij = Ax [pA]
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB) \
int8_t bij = Bx [pB]
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
bool t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA) \
cij = Ax [pA]
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB) \
cij = Bx [pB]
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z, x, y, i, j) \
z = (x == y) ;
// 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_EQ || GxB_NO_INT8 || GxB_NO_EQ_INT8)
//------------------------------------------------------------------------------
// 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__eq_int8
(
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__eq_int8
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *GB_RESTRICT kfirst_slice,
const int64_t *GB_RESTRICT klast_slice,
const int64_t *GB_RESTRICT pstart_slice,
const int ntasks,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if 0
{
#include "GB_dense_subassign_23_template.c"
}
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB_Cdense_accumb__eq_int8
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if 0
{
// get the scalar b for C += b, of type int8_t
int8_t bwork = (*((int8_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB_AxD__eq_int8
(
GrB_Matrix C,
const GrB_Matrix A, bool A_is_pattern,
const GrB_Matrix D, bool D_is_pattern,
const int64_t *GB_RESTRICT kfirst_slice,
const int64_t *GB_RESTRICT klast_slice,
const int64_t *GB_RESTRICT pstart_slice,
const int ntasks,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *GB_RESTRICT Cx = (bool *) C->x ;
#include "GB_AxB_colscale_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB_DxB__eq_int8
(
GrB_Matrix C,
const GrB_Matrix D, bool D_is_pattern,
const GrB_Matrix B, bool B_is_pattern,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *GB_RESTRICT Cx = (bool *) C->x ;
#include "GB_AxB_rowscale_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C = A+B or C<M> = A+B
//------------------------------------------------------------------------------
#undef GB_FREE_ALL
#define GB_FREE_ALL \
{ \
GB_ek_slice_free (&pstart_Mslice, &kfirst_Mslice, &klast_Mslice) ; \
GB_ek_slice_free (&pstart_Aslice, &kfirst_Aslice, &klast_Aslice) ; \
GB_ek_slice_free (&pstart_Bslice, &kfirst_Bslice, &klast_Bslice) ; \
}
GrB_Info GB_AaddB__eq_int8
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool Ch_is_Mh,
const int64_t *GB_RESTRICT C_to_M,
const int64_t *GB_RESTRICT C_to_A,
const int64_t *GB_RESTRICT C_to_B,
const GB_task_struct *GB_RESTRICT TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t *pstart_Mslice = NULL, *kfirst_Mslice = NULL, *klast_Mslice = NULL ;
int64_t *pstart_Aslice = NULL, *kfirst_Aslice = NULL, *klast_Aslice = NULL ;
int64_t *pstart_Bslice = NULL, *kfirst_Bslice = NULL, *klast_Bslice = NULL ;
#include "GB_add_template.c"
GB_FREE_ALL ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C = A.*B or C<M> = A.*B
//------------------------------------------------------------------------------
GrB_Info GB_AemultB__eq_int8
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *GB_RESTRICT C_to_M,
const int64_t *GB_RESTRICT C_to_A,
const int64_t *GB_RESTRICT C_to_B,
const GB_task_struct *GB_RESTRICT TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t *pstart_Mslice = NULL, *kfirst_Mslice = NULL, *klast_Mslice = NULL ;
int64_t *pstart_Aslice = NULL, *kfirst_Aslice = NULL, *klast_Aslice = NULL ;
int64_t *pstart_Bslice = NULL, *kfirst_Bslice = NULL, *klast_Bslice = NULL ;
#include "GB_emult_template.c"
GB_FREE_ALL ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB_bind1st__eq_int8
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *GB_RESTRICT Bb,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *Cx = (bool *) Cx_output ;
int8_t x = (*((int8_t *) x_input)) ;
int8_t *Bx = (int8_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Bb, p)) continue ;
int8_t bij = Bx [p] ;
Cx [p] = (x == bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB_bind2nd__eq_int8
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *GB_RESTRICT Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
bool *Cx = (bool *) Cx_output ;
int8_t *Ax = (int8_t *) Ax_input ;
int8_t y = (*((int8_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
int8_t aij = Ax [p] ;
Cx [p] = (aij == y) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
int8_t aij = Ax [pA] ; \
Cx [pC] = (x == aij) ; \
}
GrB_Info GB_bind1st_tran__eq_int8
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *GB_RESTRICT *Workspaces,
const int64_t *GB_RESTRICT A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
int8_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int8_t x = (*((const int8_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
int8_t
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
int8_t aij = Ax [pA] ; \
Cx [pC] = (aij == y) ; \
}
GrB_Info GB_bind2nd_tran__eq_int8
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *GB_RESTRICT *Workspaces,
const int64_t *GB_RESTRICT A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int8_t y = (*((const int8_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
unified_shared_memory.c | // RUN: %libomptarget-compile-generic -fopenmp-version=51
// RUN: %libomptarget-run-generic 2>&1 \
// RUN: | %fcheck-generic
#include <stdio.h>
// The runtime considers unified shared memory to be always present.
#pragma omp requires unified_shared_memory
int main() {
int i;
// CHECK-NOT: Libomptarget
#pragma omp target data map(alloc: i)
#pragma omp target map(present, alloc: i)
;
// CHECK: i is present
fprintf(stderr, "i is present\n");
// CHECK-NOT: Libomptarget
#pragma omp target map(present, alloc: i)
;
// CHECK: is present
fprintf(stderr, "i is present\n");
return 0;
}
|
GB_unaryop__minv_int16_bool.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_int16_bool
// op(A') function: GB_tran__minv_int16_bool
// C type: int16_t
// A type: bool
// cast: int16_t cij = (int16_t) aij
// unaryop: cij = GB_IMINV_SIGNED (aij, 16)
#define GB_ATYPE \
bool
#define GB_CTYPE \
int16_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 = GB_IMINV_SIGNED (x, 16) ;
// casting
#define GB_CASTING(z, x) \
int16_t z = (int16_t) x ;
// cij = op (cast (aij))
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GB_GETA (aij, Ax, pA) ; \
/* Cx [pC] = op (cast (aij)) */ \
GB_CASTING (x, aij) ; \
GB_OP (GB_CX (pC), x) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_MINV || GxB_NO_INT16 || GxB_NO_BOOL)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__minv_int16_bool
(
int16_t *restrict Cx,
const bool *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_int16_bool
(
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
|
conv7x7s2_neon.h | // Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2017 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.
#include "option.h"
#include "mat.h"
namespace ncnn{
static void conv7x7s2_neon(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* kernel = _kernel;
const float* bias = _bias;
#pragma omp parallel for num_threads(opt.num_threads)
for (int p=0; p<outch; p++)
{
Mat out = top_blob.channel(p);
const float bias0 = bias ? bias[p] : 0.f;
out.fill(bias0);
for (int q=0; q<inch; q++)
{
float* outptr = out;
const float* img0 = bottom_blob.channel(q);
const float* kernel0 = kernel + p*inch*49 + q*49;
const float* r0 = img0;
const float* r1 = img0 + w;
const float* r2 = img0 + w*2;
const float* r3 = img0 + w*3;
const float* r4 = img0 + w*4;
const float* r5 = img0 + w*5;
const float* r6 = img0 + w*6;
const float* k0 = kernel0;
const float* k1 = kernel0 + 7;
const float* k2 = kernel0 + 14;
const float* k3 = kernel0 + 21;
const float* k4 = kernel0 + 28;
const float* k5 = kernel0 + 35;
const float* k6 = kernel0 + 42;
int i = 0;
for (; i < outh; i++)
{
#if __ARM_NEON
int nn = outw >> 2;
int remain = outw - (nn << 2);
#else
int remain = outw;
#endif // __ARM_NEON
#if __ARM_NEON
#if __aarch64__
float32x4_t _k0123 = vld1q_f32(k0);
float32x4_t _k4567 = vld1q_f32(k0 + 4);
float32x4_t _k78910 = vld1q_f32(k1);
float32x4_t _k11121314 = vld1q_f32(k1 + 4);
float32x4_t _k14151617 = vld1q_f32(k2);
float32x4_t _k18192021 = vld1q_f32(k2 + 4);
float32x4_t _k21222324 = vld1q_f32(k3);
float32x4_t _k25262728 = vld1q_f32(k3 + 4);
float32x4_t _k28293031 = vld1q_f32(k4);
float32x4_t _k32333435 = vld1q_f32(k4 + 4);
float32x4_t _k35363738 = vld1q_f32(k5);
float32x4_t _k39404142 = vld1q_f32(k5 + 4);
float32x4_t _k42434445 = vld1q_f32(k6);
float32x4_t _k46474849 = vld1q_f32(k6 + 4);
#ifdef __clang__ // __ARM_NEON && __aarch64__ && __clang__
if (nn > 0)
{
asm volatile(
// v0: input / final output
// v1 v2: = _ri0/_ri1 first
// v3 v4: = then _r0_8101214/_r0_9111315
// v5 = ri2 / ri4 / ri6
// v6 = ri3 / ri5
// v9 = intermediate sum register
"0: \n"
"prfm pldl1keep, [%1, #128] \n"
"ld1 {v0.4s}, [%1] \n"
//i = 1
"prfm pldl1keep, [%2, #512] \n"
"ld2 {v1.4s, v2.4s}, [%2] \n" // v1 v2 = _r00 _r01
"add %2, %2, #32 \n"
"ld2 {v3.4s, v4.4s}, [%2] \n" // v3 v4 = _r0_8101214 / _r0_9111315
"fmul v9.4s, v1.4s, %18.s[0] \n" // *+ _r00
"ext v5.16b, v1.16b, v3.16b, #4 \n" // v5 = _r02
"fmla v0.4s, v2.4s, %18.s[1] \n" // *+ _r01
"ext v6.16b, v2.16b, v4.16b, #4 \n" // v6 = _r03
"fmla v9.4s, v5.4s, %18.s[2] \n" // *+ _r02
"ext v5.16b, v1.16b, v3.16b, #8 \n" // v5 = _r04
"fmla v0.4s, v6.4s, %18.s[3] \n" // *+ _r03
"ext v6.16b, v2.16b, v4.16b, #8 \n" // v6 = _r05
"fmla v9.4s, v5.4s, %19.s[0] \n" // *+ _r04
"ext v5.16b, v1.16b, v3.16b, #12 \n" // v5 = _r06
"fmla v0.4s, v6.4s, %19.s[1] \n" // *+ _r05
"fmla v9.4s, v5.4s, %19.s[2] \n" // *+ _r06
//i = 2
"prfm pldl1keep, [%3, #512] \n"
"ld2 {v1.4s, v2.4s}, [%3] \n"
"add %3, %3, #32 \n"
"ld2 {v3.4s, v4.4s}, [%3] \n"
"fmla v9.4s, v1.4s, %20.s[0] \n"
"ext v5.16b, v1.16b, v3.16b, #4 \n"
"fmla v0.4s, v2.4s, %20.s[1] \n"
"ext v6.16b, v2.16b, v4.16b, #4 \n"
"fmla v9.4s, v5.4s, %20.s[2] \n"
"ext v5.16b, v1.16b, v3.16b, #8 \n"
"fmla v0.4s, v6.4s, %20.s[3] \n"
"ext v6.16b, v2.16b, v4.16b, #8 \n"
"fmla v9.4s, v5.4s, %21.s[0] \n"
"ext v5.16b, v1.16b, v3.16b, #12 \n"
"fmla v0.4s, v6.4s, %21.s[1] \n"
"fmla v9.4s, v5.4s, %21.s[2] \n"
//i = 3
"prfm pldl1keep, [%4, #512] \n"
"ld2 {v1.4s, v2.4s}, [%4] \n"
"add %4, %4, #32 \n"
"ld2 {v3.4s, v4.4s}, [%4] \n"
"fmla v9.4s, v1.4s, %22.s[0] \n"
"ext v5.16b, v1.16b, v3.16b, #4 \n"
"fmla v0.4s, v2.4s, %22.s[1] \n"
"ext v6.16b, v2.16b, v4.16b, #4 \n"
"fmla v9.4s, v5.4s, %22.s[2] \n"
"ext v5.16b, v1.16b, v3.16b, #8 \n"
"fmla v0.4s, v6.4s, %22.s[3] \n"
"ext v6.16b, v2.16b, v4.16b, #8 \n"
"fmla v9.4s, v5.4s, %23.s[0] \n"
"ext v5.16b, v1.16b, v3.16b, #12 \n"
"fmla v0.4s, v6.4s, %23.s[1] \n"
"fmla v9.4s, v5.4s, %23.s[2] \n"
//i = 4
"prfm pldl1keep, [%5, #512] \n"
"ld2 {v1.4s, v2.4s}, [%5] \n"
"add %5, %5, #32 \n"
"ld2 {v3.4s, v4.4s}, [%5] \n"
"fmla v9.4s, v1.4s, %24.s[0] \n"
"ext v5.16b, v1.16b, v3.16b, #4 \n"
"fmla v0.4s, v2.4s, %24.s[1] \n"
"ext v6.16b, v2.16b, v4.16b, #4 \n"
"fmla v9.4s, v5.4s, %24.s[2] \n"
"ext v5.16b, v1.16b, v3.16b, #8 \n"
"fmla v0.4s, v6.4s, %24.s[3] \n"
"ext v6.16b, v2.16b, v4.16b, #8 \n"
"fmla v9.4s, v5.4s, %25.s[0] \n"
"ext v5.16b, v1.16b, v3.16b, #12 \n"
"fmla v0.4s, v6.4s, %25.s[1] \n"
"fmla v9.4s, v5.4s, %25.s[2] \n"
//i = 5
"prfm pldl1keep, [%6, #512] \n"
"ld2 {v1.4s, v2.4s}, [%6] \n"
"add %6, %6, #32 \n"
"ld2 {v3.4s, v4.4s}, [%6] \n"
"fmla v9.4s, v1.4s, %26.s[0] \n"
"ext v5.16b, v1.16b, v3.16b, #4 \n"
"fmla v0.4s, v2.4s, %26.s[1] \n"
"ext v6.16b, v2.16b, v4.16b, #4 \n"
"fmla v9.4s, v5.4s, %26.s[2] \n"
"ext v5.16b, v1.16b, v3.16b, #8 \n"
"fmla v0.4s, v6.4s, %26.s[3] \n"
"ext v6.16b, v2.16b, v4.16b, #8 \n"
"fmla v9.4s, v5.4s, %27.s[0] \n"
"ext v5.16b, v1.16b, v3.16b, #12 \n"
"fmla v0.4s, v6.4s, %27.s[1] \n"
"fmla v9.4s, v5.4s, %27.s[2] \n"
//i = 6
"prfm pldl1keep, [%7, #512] \n"
"ld2 {v1.4s, v2.4s}, [%7] \n"
"add %7, %7, #32 \n"
"ld2 {v3.4s, v4.4s}, [%7] \n"
"fmla v9.4s, v1.4s, %28.s[0] \n"
"ext v5.16b, v1.16b, v3.16b, #4 \n"
"fmla v0.4s, v2.4s, %28.s[1] \n"
"ext v6.16b, v2.16b, v4.16b, #4 \n"
"fmla v9.4s, v5.4s, %28.s[2] \n"
"ext v5.16b, v1.16b, v3.16b, #8 \n"
"fmla v0.4s, v6.4s, %28.s[3] \n"
"ext v6.16b, v2.16b, v4.16b, #8 \n"
"fmla v9.4s, v5.4s, %29.s[0] \n"
"ext v5.16b, v1.16b, v3.16b, #12 \n"
"fmla v0.4s, v6.4s, %29.s[1] \n"
"fmla v9.4s, v5.4s, %29.s[2] \n"
//i = 7
"prfm pldl1keep, [%8, #512] \n"
"ld2 {v1.4s, v2.4s}, [%8] \n"
"add %8, %8, #32 \n"
"ld2 {v3.4s, v4.4s}, [%8] \n"
"fmla v9.4s, v1.4s, %30.s[0] \n"
"ext v5.16b, v1.16b, v3.16b, #4 \n"
"fmla v0.4s, v2.4s, %30.s[1] \n"
"ext v6.16b, v2.16b, v4.16b, #4 \n"
"fmla v9.4s, v5.4s, %30.s[2] \n"
"ext v5.16b, v1.16b, v3.16b, #8 \n"
"fmla v0.4s, v6.4s, %30.s[3] \n"
"ext v6.16b, v2.16b, v4.16b, #8 \n"
"fmla v9.4s, v5.4s, %31.s[0] \n"
"ext v5.16b, v1.16b, v3.16b, #12 \n"
"fmla v0.4s, v6.4s, %31.s[1] \n"
"fmla v9.4s, v5.4s, %31.s[2] \n"
"fadd v0.4s, v0.4s, v9.4s \n"
"st1 {v0.4s}, [%1], #16 \n"
"subs %w0, %w0, #1 \n"
"bne 0b \n"
: "=r"(nn), // %0
"=r"(outptr), // %1
"=r"(r0), // %2
"=r"(r1), // %3
"=r"(r2), // %4
"=r"(r3), // %5
"=r"(r4), // %6
"=r"(r5), // %7
"=r"(r6) // %8
: "0"(nn),
"1"(outptr),
"2"(r0),
"3"(r1),
"4"(r2),
"5"(r3),
"6"(r4),
"7"(r5),
"8"(r6),
"w"(_k0123), // %18
"w"(_k4567), // %19
"w"(_k78910), // %20
"w"(_k11121314), // %21
"w"(_k14151617), // %22
"w"(_k18192021), // %23
"w"(_k21222324), // %24
"w"(_k25262728), // %25
"w"(_k28293031), // %26
"w"(_k32333435), // %27
"w"(_k35363738), // %28
"w"(_k39404142), // %29
"w"(_k42434445), // %30
"w"(_k46474849) // %31
: "cc", "memory","v0", "v1", "v2", "v3", "v4", "v5", "v6", "v9"
);
}
#else // __ARM_NEON && __aarch64__ defined, but __clang__ not defined
// When compiled with gcc, gcc does not accept over 30 operands
for (; nn>0; nn--)
{
float32x4_t _sum = vld1q_f32(outptr);
float32x4x2_t _r00_02461357 = vld2q_f32(r0);
float32x4x2_t _r00nx2 = vld2q_f32(r0 + 8);
float32x4_t _r0_8101214 = _r00nx2.val[0];// 8 10 12 14
float32x4_t _r0_9111315 = _r00nx2.val[1];// 9 11 13 15
float32x4_t _r00 = _r00_02461357.val[0];// 0 2 4 6
float32x4_t _r01 = _r00_02461357.val[1];// 1 3 5 7
float32x4_t _r02 = vextq_f32(_r00, _r0_8101214, 1);// 2 4 6 8
float32x4_t _r03 = vextq_f32(_r01, _r0_9111315, 1);// 3 5 7 9
float32x4_t _r04 = vextq_f32(_r00, _r0_8101214, 2);// 4 6 8 10
float32x4_t _r05 = vextq_f32(_r01, _r0_9111315, 2);// 5 7 9 11
float32x4_t _r06 = vextq_f32(_r00, _r0_8101214, 3);// 6 8 10 12
_sum = vfmaq_laneq_f32(_sum, _r00, _k0123, 0);
_sum = vfmaq_laneq_f32(_sum, _r01, _k0123, 1);
_sum = vfmaq_laneq_f32(_sum, _r02, _k0123, 2);
_sum = vfmaq_laneq_f32(_sum, _r03, _k0123, 3);
_sum = vfmaq_laneq_f32(_sum, _r04, _k4567, 0);
_sum = vfmaq_laneq_f32(_sum, _r05, _k4567, 1);
_sum = vfmaq_laneq_f32(_sum, _r06, _k4567, 2);
float32x4x2_t _r10_02461357 = vld2q_f32(r1);
float32x4x2_t _r10nx2 = vld2q_f32(r1 + 8);
float32x4_t _r1_8101214 = _r10nx2.val[0];
float32x4_t _r1_9111315 = _r10nx2.val[1];
float32x4_t _r10 = _r10_02461357.val[0];
float32x4_t _r11 = _r10_02461357.val[1];
float32x4_t _r12 = vextq_f32(_r10, _r1_8101214, 1);
float32x4_t _r13 = vextq_f32(_r11, _r1_9111315, 1);
float32x4_t _r14 = vextq_f32(_r10, _r1_8101214, 2);
float32x4_t _r15 = vextq_f32(_r11, _r1_9111315, 2);
float32x4_t _r16 = vextq_f32(_r10, _r1_8101214, 3);
_sum = vfmaq_laneq_f32(_sum, _r10, _k78910, 0);
_sum = vfmaq_laneq_f32(_sum, _r11, _k78910, 1);
_sum = vfmaq_laneq_f32(_sum, _r12, _k78910, 2);
_sum = vfmaq_laneq_f32(_sum, _r13, _k78910, 3);
_sum = vfmaq_laneq_f32(_sum, _r14, _k11121314, 0);
_sum = vfmaq_laneq_f32(_sum, _r15, _k11121314, 1);
_sum = vfmaq_laneq_f32(_sum, _r16, _k11121314, 2);
float32x4x2_t _r20_02461357 = vld2q_f32(r2);
float32x4x2_t _r20nx2 = vld2q_f32(r2 + 8);
float32x4_t _r2_8101214 = _r20nx2.val[0];
float32x4_t _r2_9111315 = _r20nx2.val[1];
float32x4_t _r20 = _r20_02461357.val[0];
float32x4_t _r21 = _r20_02461357.val[1];
float32x4_t _r22 = vextq_f32(_r20, _r2_8101214, 1);
float32x4_t _r23 = vextq_f32(_r21, _r2_9111315, 1);
float32x4_t _r24 = vextq_f32(_r20, _r2_8101214, 2);
float32x4_t _r25 = vextq_f32(_r21, _r2_9111315, 2);
float32x4_t _r26 = vextq_f32(_r20, _r2_8101214, 3);
_sum = vfmaq_laneq_f32(_sum, _r20, _k14151617, 0);
_sum = vfmaq_laneq_f32(_sum, _r21, _k14151617, 1);
_sum = vfmaq_laneq_f32(_sum, _r22, _k14151617, 2);
_sum = vfmaq_laneq_f32(_sum, _r23, _k14151617, 3);
_sum = vfmaq_laneq_f32(_sum, _r24, _k18192021, 0);
_sum = vfmaq_laneq_f32(_sum, _r25, _k18192021, 1);
_sum = vfmaq_laneq_f32(_sum, _r26, _k18192021, 2);
float32x4x2_t _r30_02461357 = vld2q_f32(r3);
float32x4x2_t _r30nx2 = vld2q_f32(r3 + 8);
float32x4_t _r3_8101214 = _r30nx2.val[0];
float32x4_t _r3_9111315 = _r30nx2.val[1];
float32x4_t _r30 = _r30_02461357.val[0];
float32x4_t _r31 = _r30_02461357.val[1];
float32x4_t _r32 = vextq_f32(_r30, _r3_8101214, 1);
float32x4_t _r33 = vextq_f32(_r31, _r3_9111315, 1);
float32x4_t _r34 = vextq_f32(_r30, _r3_8101214, 2);
float32x4_t _r35 = vextq_f32(_r31, _r3_9111315, 2);
float32x4_t _r36 = vextq_f32(_r30, _r3_8101214, 3);
_sum = vfmaq_laneq_f32(_sum, _r30, _k21222324, 0);
_sum = vfmaq_laneq_f32(_sum, _r31, _k21222324, 1);
_sum = vfmaq_laneq_f32(_sum, _r32, _k21222324, 2);
_sum = vfmaq_laneq_f32(_sum, _r33, _k21222324, 3);
_sum = vfmaq_laneq_f32(_sum, _r34, _k25262728, 0);
_sum = vfmaq_laneq_f32(_sum, _r35, _k25262728, 1);
_sum = vfmaq_laneq_f32(_sum, _r36, _k25262728, 2);
float32x4x2_t _r40_02461357 = vld2q_f32(r4);
float32x4x2_t _r40nx2 = vld2q_f32(r4 + 8);
float32x4_t _r4_8101214 = _r40nx2.val[0];
float32x4_t _r4_9111315 = _r40nx2.val[1];
float32x4_t _r40 = _r40_02461357.val[0];
float32x4_t _r41 = _r40_02461357.val[1];
float32x4_t _r42 = vextq_f32(_r40, _r4_8101214, 1);
float32x4_t _r43 = vextq_f32(_r41, _r4_9111315, 1);
float32x4_t _r44 = vextq_f32(_r40, _r4_8101214, 2);
float32x4_t _r45 = vextq_f32(_r41, _r4_9111315, 2);
float32x4_t _r46 = vextq_f32(_r40, _r4_8101214, 3);
_sum = vfmaq_laneq_f32(_sum, _r40, _k28293031, 0);
_sum = vfmaq_laneq_f32(_sum, _r41, _k28293031, 1);
_sum = vfmaq_laneq_f32(_sum, _r42, _k28293031, 2);
_sum = vfmaq_laneq_f32(_sum, _r43, _k28293031, 3);
_sum = vfmaq_laneq_f32(_sum, _r44, _k32333435, 0);
_sum = vfmaq_laneq_f32(_sum, _r45, _k32333435, 1);
_sum = vfmaq_laneq_f32(_sum, _r46, _k32333435, 2);
float32x4x2_t _r50_02461357 = vld2q_f32(r5);
float32x4x2_t _r50nx2 = vld2q_f32(r5 + 8);
float32x4_t _r5_8101214 = _r50nx2.val[0];
float32x4_t _r5_9111315 = _r50nx2.val[1];
float32x4_t _r50 = _r50_02461357.val[0];
float32x4_t _r51 = _r50_02461357.val[1];
float32x4_t _r52 = vextq_f32(_r50, _r5_8101214, 1);
float32x4_t _r53 = vextq_f32(_r51, _r5_9111315, 1);
float32x4_t _r54 = vextq_f32(_r50, _r5_8101214, 2);
float32x4_t _r55 = vextq_f32(_r51, _r5_9111315, 2);
float32x4_t _r56 = vextq_f32(_r50, _r5_8101214, 3);
_sum = vfmaq_laneq_f32(_sum, _r50, _k35363738, 0);
_sum = vfmaq_laneq_f32(_sum, _r51, _k35363738, 1);
_sum = vfmaq_laneq_f32(_sum, _r52, _k35363738, 2);
_sum = vfmaq_laneq_f32(_sum, _r53, _k35363738, 3);
_sum = vfmaq_laneq_f32(_sum, _r54, _k39404142, 0);
_sum = vfmaq_laneq_f32(_sum, _r55, _k39404142, 1);
_sum = vfmaq_laneq_f32(_sum, _r56, _k39404142, 2);
float32x4x2_t _r60_02461357 = vld2q_f32(r6);
float32x4x2_t _r60nx2 = vld2q_f32(r6 + 8);
float32x4_t _r6_8101214 = _r60nx2.val[0];
float32x4_t _r6_9111315 = _r60nx2.val[1];
float32x4_t _r60 = _r60_02461357.val[0];
float32x4_t _r61 = _r60_02461357.val[1];
float32x4_t _r62 = vextq_f32(_r60, _r6_8101214, 1);
float32x4_t _r63 = vextq_f32(_r61, _r6_9111315, 1);
float32x4_t _r64 = vextq_f32(_r60, _r6_8101214, 2);
float32x4_t _r65 = vextq_f32(_r61, _r6_9111315, 2);
float32x4_t _r66 = vextq_f32(_r60, _r6_8101214, 3);
_sum = vfmaq_laneq_f32(_sum, _r60, _k42434445, 0);
_sum = vfmaq_laneq_f32(_sum, _r61, _k42434445, 1);
_sum = vfmaq_laneq_f32(_sum, _r62, _k42434445, 2);
_sum = vfmaq_laneq_f32(_sum, _r63, _k42434445, 3);
_sum = vfmaq_laneq_f32(_sum, _r64, _k46474849, 0);
_sum = vfmaq_laneq_f32(_sum, _r65, _k46474849, 1);
_sum = vfmaq_laneq_f32(_sum, _r66, _k46474849, 2);
vst1q_f32(outptr, _sum);
r0 += 8;
r1 += 8;
r2 += 8;
r3 += 8;
r4 += 8;
r5 += 8;
r6 += 8;
outptr += 4;
}
#endif // __clang__
#else
if (nn > 0)
{
asm volatile(
"0: \n"
"pld [%1, #256] \n"
"vld1.f32 {d26-d27}, [%1] \n"// _sum
// "veor q14, q14 \n"// _sum2 = 0;
// "veor q15, q15 \n"// _sum3 = 0;
"pld [%9, #256] \n"
"vld1.f32 {d8-d11}, [%9] \n"// q4 q5 = k0123 k4567
"add %9, #28 \n"
"pld [%2, #512] \n"
"vld2.f32 {d0-d3}, [%2]! \n"// q0 = 0 2 4 6 q1 = 1 3 5 7
"vmla.f32 q13, q0, d8[0] \n"
"vmul.f32 q14, q1, d8[1] \n"
"vld2.f32 {d4-d7}, [%2] \n"// q2 = 8 10 12 14 q3 = 9 11 13 15
"vext.32 q8, q0, q2, #1 \n"// q8 = 2 4 6 8
"vext.32 q9, q1, q3, #1 \n"// q9 = 3 5 7 9
"vmul.f32 q15, q8, d9[0] \n"
"vmla.f32 q13, q9, d9[1] \n"
"vext.32 q10, q0, q2, #2 \n"// q10= 4 6 8 10
"vext.32 q11, q1, q3, #2 \n"// q11= 5 7 9 11
"vmla.f32 q14, q10, d10[0] \n"
"vmla.f32 q15, q11, d10[1] \n"
"vext.32 q12, q0, q2, #3 \n"// q12= 6 8 10 12
"vmla.f32 q13, q12, d11[0] \n"
"pld [%9, #256] \n"
"vld1.f32 {d12-d15}, [%9] \n"// q6 q7 = k78910 k11121314
"add %9, #28 \n"
"pld [%3, #512] \n"
"vld2.f32 {d0-d3}, [%3]! \n"
"vmla.f32 q14, q0, d12[0] \n"
"vmla.f32 q15, q1, d12[1] \n"
"vld2.f32 {d4-d7}, [%3] \n"
"vext.32 q8, q0, q2, #1 \n"
"vext.32 q9, q1, q3, #1 \n"
"vmla.f32 q13, q8, d13[0] \n"
"vmla.f32 q14, q9, d13[1] \n"
"vext.32 q10, q0, q2, #2 \n"
"vext.32 q11, q1, q3, #2 \n"
"vmla.f32 q15, q10, d14[0] \n"
"vmla.f32 q13, q11, d14[1] \n"
"vext.32 q12, q0, q2, #3 \n"
"vmla.f32 q14, q12, d15[0] \n"
"pld [%9, #256] \n"
"vld1.f32 {d8-d11}, [%9] \n"// q4 q5 = k14151617 k18192021
"add %9, #28 \n"
"pld [%4, #512] \n"
"vld2.f32 {d0-d3}, [%4]! \n"
"vmla.f32 q15, q0, d8[0] \n"
"vmla.f32 q13, q1, d8[1] \n"
"vld2.f32 {d4-d7}, [%4] \n"
"vext.32 q8, q0, q2, #1 \n"
"vext.32 q9, q1, q3, #1 \n"
"vmla.f32 q14, q8, d9[0] \n"
"vmla.f32 q15, q9, d9[1] \n"
"vext.32 q10, q0, q2, #2 \n"
"vext.32 q11, q1, q3, #2 \n"
"vmla.f32 q13, q10, d10[0] \n"
"vmla.f32 q14, q11, d10[1] \n"
"vext.32 q12, q0, q2, #3 \n"
"vmla.f32 q15, q12, d11[0] \n"
"pld [%9, #256] \n"
"vld1.f32 {d12-d15}, [%9] \n"// q6 q7 = k21222324 k25262728
"add %9, #28 \n"
"pld [%5, #512] \n"
"vld2.f32 {d0-d3}, [%5]! \n"
"vmla.f32 q13, q0, d12[0] \n"
"vmla.f32 q14, q1, d12[1] \n"
"vld2.f32 {d4-d7}, [%5] \n"
"vext.32 q8, q0, q2, #1 \n"
"vext.32 q9, q1, q3, #1 \n"
"vmla.f32 q15, q8, d13[0] \n"
"vmla.f32 q13, q9, d13[1] \n"
"vext.32 q10, q0, q2, #2 \n"
"vext.32 q11, q1, q3, #2 \n"
"vmla.f32 q14, q10, d14[0] \n"
"vmla.f32 q15, q11, d14[1] \n"
"vext.32 q12, q0, q2, #3 \n"
"vmla.f32 q13, q12, d15[0] \n"
"pld [%9, #256] \n"
"vld1.f32 {d8-d11}, [%9] \n"// q4 q5 = k28293031 k32333435
"add %9, #28 \n"
"pld [%6, #512] \n"
"vld2.f32 {d0-d3}, [%6]! \n"
"vmla.f32 q14, q0, d8[0] \n"
"vmla.f32 q15, q1, d8[1] \n"
"vld2.f32 {d4-d7}, [%6] \n"
"vext.32 q8, q0, q2, #1 \n"
"vext.32 q9, q1, q3, #1 \n"
"vmla.f32 q13, q8, d9[0] \n"
"vmla.f32 q14, q9, d9[1] \n"
"vext.32 q10, q0, q2, #2 \n"
"vext.32 q11, q1, q3, #2 \n"
"vmla.f32 q15, q10, d10[0] \n"
"vmla.f32 q13, q11, d10[1] \n"
"vext.32 q12, q0, q2, #3 \n"
"vmla.f32 q14, q12, d11[0] \n"
"pld [%9, #256] \n"
"vld1.f32 {d12-d15}, [%9] \n"// q6 q7 = k35363738 k39404142
"add %9, #28 \n"
"pld [%7, #512] \n"
"vld2.f32 {d0-d3}, [%7]! \n"
"vmla.f32 q15, q0, d12[0] \n"
"vmla.f32 q13, q1, d12[1] \n"
"vld2.f32 {d4-d7}, [%7] \n"
"vext.32 q8, q0, q2, #1 \n"
"vext.32 q9, q1, q3, #1 \n"
"vmla.f32 q14, q8, d13[0] \n"
"vmla.f32 q15, q9, d13[1] \n"
"vext.32 q10, q0, q2, #2 \n"
"vext.32 q11, q1, q3, #2 \n"
"vmla.f32 q13, q10, d14[0] \n"
"vmla.f32 q14, q11, d14[1] \n"
"vext.32 q12, q0, q2, #3 \n"
"vmla.f32 q15, q12, d15[0] \n"
"pld [%9, #256] \n"
"vld1.f32 {d8-d11}, [%9] \n"// q4 q5 = k42434445 k46474849
"sub %9, #168 \n"// restore k0
"pld [%8, #512] \n"
"vld2.f32 {d0-d3}, [%8]! \n"
"vmla.f32 q13, q0, d8[0] \n"
"vmla.f32 q14, q1, d8[1] \n"
"vld2.f32 {d4-d7}, [%8] \n"
"vext.32 q8, q0, q2, #1 \n"
"vext.32 q9, q1, q3, #1 \n"
"vmla.f32 q15, q8, d9[0] \n"
"vmla.f32 q13, q9, d9[1] \n"
"vext.32 q10, q0, q2, #2 \n"
"vext.32 q11, q1, q3, #2 \n"
"vmla.f32 q14, q10, d10[0] \n"
"vmla.f32 q15, q11, d10[1] \n"
"vext.32 q12, q0, q2, #3 \n"
"vmla.f32 q13, q12, d11[0] \n"
"vadd.f32 q14, q14, q15 \n"
"vadd.f32 q13, q13, q14 \n"
"vst1.f32 {d26-d27}, [%1]! \n"
"subs %0, #1 \n"
"bne 0b \n"
: "=r"(nn), // %0
"=r"(outptr), // %1
"=r"(r0), // %2
"=r"(r1), // %3
"=r"(r2), // %4
"=r"(r3), // %5
"=r"(r4), // %6
"=r"(r5), // %7
"=r"(r6), // %8
"=r"(k0) // %9
: "0"(nn),
"1"(outptr),
"2"(r0),
"3"(r1),
"4"(r2),
"5"(r3),
"6"(r4),
"7"(r5),
"8"(r6),
"9"(k0)
: "cc", "memory", "q0", "q1", "q2", "q3", "q4", "q5", "q6", "q7", "q8", "q9", "q10", "q11", "q12", "q13", "q14", "q15"
);
}
#endif // __aarch64__
#endif // __ARM_NEON
for (; remain>0; remain--)
{
float sum = 0;
sum += r0[0] * k0[0];
sum += r0[1] * k0[1];
sum += r0[2] * k0[2];
sum += r0[3] * k0[3];
sum += r0[4] * k0[4];
sum += r0[5] * k0[5];
sum += r0[6] * k0[6];
sum += r1[0] * k1[0];
sum += r1[1] * k1[1];
sum += r1[2] * k1[2];
sum += r1[3] * k1[3];
sum += r1[4] * k1[4];
sum += r1[5] * k1[5];
sum += r1[6] * k1[6];
sum += r2[0] * k2[0];
sum += r2[1] * k2[1];
sum += r2[2] * k2[2];
sum += r2[3] * k2[3];
sum += r2[4] * k2[4];
sum += r2[5] * k2[5];
sum += r2[6] * k2[6];
sum += r3[0] * k3[0];
sum += r3[1] * k3[1];
sum += r3[2] * k3[2];
sum += r3[3] * k3[3];
sum += r3[4] * k3[4];
sum += r3[5] * k3[5];
sum += r3[6] * k3[6];
sum += r4[0] * k4[0];
sum += r4[1] * k4[1];
sum += r4[2] * k4[2];
sum += r4[3] * k4[3];
sum += r4[4] * k4[4];
sum += r4[5] * k4[5];
sum += r4[6] * k4[6];
sum += r5[0] * k5[0];
sum += r5[1] * k5[1];
sum += r5[2] * k5[2];
sum += r5[3] * k5[3];
sum += r5[4] * k5[4];
sum += r5[5] * k5[5];
sum += r5[6] * k5[6];
sum += r6[0] * k6[0];
sum += r6[1] * k6[1];
sum += r6[2] * k6[2];
sum += r6[3] * k6[3];
sum += r6[4] * k6[4];
sum += r6[5] * k6[5];
sum += r6[6] * k6[6];
*outptr += sum;
r0 += 2;
r1 += 2;
r2 += 2;
r3 += 2;
r4 += 2;
r5 += 2;
r6 += 2;
outptr++;
}
r0 += tailstep;
r1 += tailstep;
r2 += tailstep;
r3 += tailstep;
r4 += tailstep;
r5 += tailstep;
r6 += tailstep;
}
}
}
}
}
|
scale_channels_layer.c | #include "scale_channels_layer.h"
#include "dark_cuda.h"
#include "blas.h"
#include <stdio.h>
#include <assert.h>
layer make_scale_channels_layer(int batch, int index, int w, int h, int c, int w2, int h2, int c2, int scale_wh)
{
fprintf(stderr,"scale Layer: %d\n", index);
layer l = { (LAYER_TYPE)0 };
l.type = SCALE_CHANNELS;
l.batch = batch;
l.scale_wh = scale_wh;
l.w = w;
l.h = h;
l.c = c;
if (!l.scale_wh) assert(w == 1 && h == 1);
else assert(c == 1);
l.out_w = w2;
l.out_h = h2;
l.out_c = c2;
if (!l.scale_wh) assert(l.out_c == l.c);
else assert(l.out_w == l.w && l.out_h == l.h);
l.outputs = l.out_w*l.out_h*l.out_c;
l.inputs = l.outputs;
l.index = index;
l.delta = (float*)calloc(l.outputs * batch, sizeof(float));
l.output = (float*)calloc(l.outputs * batch, sizeof(float));
l.forward = forward_scale_channels_layer;
l.backward = backward_scale_channels_layer;
#ifdef GPU
l.forward_gpu = forward_scale_channels_layer_gpu;
l.backward_gpu = backward_scale_channels_layer_gpu;
l.delta_gpu = cuda_make_array(l.delta, l.outputs*batch);
l.output_gpu = cuda_make_array(l.output, l.outputs*batch);
#endif
return l;
}
void resize_scale_channels_layer(layer *l, network *net)
{
layer first = net->layers[l->index];
l->out_w = first.out_w;
l->out_h = first.out_h;
l->outputs = l->out_w*l->out_h*l->out_c;
l->inputs = l->outputs;
l->delta = (float*)realloc(l->delta, l->outputs * l->batch * sizeof(float));
l->output = (float*)realloc(l->output, l->outputs * l->batch * sizeof(float));
#ifdef GPU
cuda_free(l->output_gpu);
cuda_free(l->delta_gpu);
l->output_gpu = cuda_make_array(l->output, l->outputs*l->batch);
l->delta_gpu = cuda_make_array(l->delta, l->outputs*l->batch);
#endif
}
void forward_scale_channels_layer(const layer l, network_state state)
{
int size = l.batch * l.out_c * l.out_w * l.out_h;
int channel_size = l.out_w * l.out_h;
int batch_size = l.out_c * l.out_w * l.out_h;
float *from_output = state.net.layers[l.index].output;
if (l.scale_wh) {
int i;
#pragma omp parallel for
for (i = 0; i < size; ++i) {
int input_index = i % channel_size + (i / batch_size)*channel_size;
l.output[i] = state.input[input_index] * from_output[i];
}
}
else {
int i;
#pragma omp parallel for
for (i = 0; i < size; ++i) {
l.output[i] = state.input[i / channel_size] * from_output[i];
}
}
activate_array(l.output, l.outputs*l.batch, l.activation);
}
void backward_scale_channels_layer(const layer l, network_state state)
{
gradient_array(l.output, l.outputs*l.batch, l.activation, l.delta);
//axpy_cpu(l.outputs*l.batch, 1, l.delta, 1, state.delta, 1);
//scale_cpu(l.batch, l.out_w, l.out_h, l.out_c, l.delta, l.w, l.h, l.c, state.net.layers[l.index].delta);
int size = l.batch * l.out_c * l.out_w * l.out_h;
int channel_size = l.out_w * l.out_h;
int batch_size = l.out_c * l.out_w * l.out_h;
float *from_output = state.net.layers[l.index].output;
float *from_delta = state.net.layers[l.index].delta;
if (l.scale_wh) {
int i;
#pragma omp parallel for
for (i = 0; i < size; ++i) {
int input_index = i % channel_size + (i / batch_size)*channel_size;
state.delta[input_index] += l.delta[i] * from_output[i];// / l.out_c; // l.delta * from (should be divided by l.out_c?)
from_delta[i] += state.input[input_index] * l.delta[i]; // input * l.delta
}
}
else {
int i;
#pragma omp parallel for
for (i = 0; i < size; ++i) {
state.delta[i / channel_size] += l.delta[i] * from_output[i];// / channel_size; // l.delta * from (should be divided by channel_size?)
from_delta[i] += state.input[i / channel_size] * l.delta[i]; // input * l.delta
}
}
}
#ifdef GPU
void forward_scale_channels_layer_gpu(const layer l, network_state state)
{
int size = l.batch * l.out_c * l.out_w * l.out_h;
int channel_size = l.out_w * l.out_h;
int batch_size = l.out_c * l.out_w * l.out_h;
scale_channels_gpu(state.net.layers[l.index].output_gpu, size, channel_size, batch_size, l.scale_wh, state.input, l.output_gpu);
activate_array_ongpu(l.output_gpu, l.outputs*l.batch, l.activation);
}
void backward_scale_channels_layer_gpu(const layer l, network_state state)
{
gradient_array_ongpu(l.output_gpu, l.outputs*l.batch, l.activation, l.delta_gpu);
int size = l.batch * l.out_c * l.out_w * l.out_h;
int channel_size = l.out_w * l.out_h;
int batch_size = l.out_c * l.out_w * l.out_h;
float *from_output = state.net.layers[l.index].output_gpu;
float *from_delta = state.net.layers[l.index].delta_gpu;
backward_scale_channels_gpu(l.delta_gpu, size, channel_size, batch_size, l.scale_wh, state.input, from_delta, from_output, state.delta);
}
#endif
|
pairwise3.c | /* Generated by Cython 0.25.2 */
/* BEGIN: Cython Metadata
{
"distutils": {
"depends": [],
"extra_compile_args": [
"-Wno-unused-function",
"-Wno-maybe-uninitialized",
"-O3",
"-ffast-math",
"-fopenmp"
],
"extra_link_args": [
"-fopenmp"
]
},
"module_name": "pairwise3"
}
END: Cython Metadata */
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#define CYTHON_USE_TYPE_SLOTS 0
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#define CYTHON_USE_ASYNC_SLOTS 0
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#define CYTHON_USE_PYLIST_INTERNALS 0
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#define CYTHON_USE_UNICODE_INTERNALS 0
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#define CYTHON_USE_UNICODE_WRITER 0
#undef CYTHON_USE_PYLONG_INTERNALS
#define CYTHON_USE_PYLONG_INTERNALS 0
#undef CYTHON_AVOID_BORROWED_REFS
#define CYTHON_AVOID_BORROWED_REFS 1
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#define CYTHON_ASSUME_SAFE_MACROS 0
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#define CYTHON_UNPACK_METHODS 0
#undef CYTHON_FAST_THREAD_STATE
#define CYTHON_FAST_THREAD_STATE 0
#undef CYTHON_FAST_PYCALL
#define CYTHON_FAST_PYCALL 0
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#define CYTHON_COMPILING_IN_PYSTON 1
#define CYTHON_COMPILING_IN_CPYTHON 0
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#define CYTHON_USE_TYPE_SLOTS 1
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#define CYTHON_USE_ASYNC_SLOTS 0
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#define CYTHON_USE_PYLIST_INTERNALS 0
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#define CYTHON_USE_PYLONG_INTERNALS 0
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#define CYTHON_ASSUME_SAFE_MACROS 1
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#ifndef CYTHON_UNPACK_METHODS
#define CYTHON_UNPACK_METHODS 1
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#undef CYTHON_FAST_THREAD_STATE
#define CYTHON_FAST_THREAD_STATE 0
#undef CYTHON_FAST_PYCALL
#define CYTHON_FAST_PYCALL 0
#else
#define CYTHON_COMPILING_IN_PYPY 0
#define CYTHON_COMPILING_IN_PYSTON 0
#define CYTHON_COMPILING_IN_CPYTHON 1
#ifndef CYTHON_USE_TYPE_SLOTS
#define CYTHON_USE_TYPE_SLOTS 1
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#undef CYTHON_USE_ASYNC_SLOTS
#define CYTHON_USE_ASYNC_SLOTS 0
#elif !defined(CYTHON_USE_ASYNC_SLOTS)
#define CYTHON_USE_ASYNC_SLOTS 1
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#define CYTHON_USE_PYLONG_INTERNALS 0
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#undef CYTHON_USE_UNICODE_WRITER
#define CYTHON_USE_UNICODE_WRITER 0
#elif !defined(CYTHON_USE_UNICODE_WRITER)
#define CYTHON_USE_UNICODE_WRITER 1
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#define CYTHON_AVOID_BORROWED_REFS 0
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#ifndef CYTHON_ASSUME_SAFE_MACROS
#define CYTHON_ASSUME_SAFE_MACROS 1
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#ifndef CYTHON_UNPACK_METHODS
#define CYTHON_UNPACK_METHODS 1
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#define CYTHON_FAST_THREAD_STATE 1
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#define CYTHON_FAST_PYCALL 1
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#if !defined(CYTHON_FAST_PYCCALL)
#define CYTHON_FAST_PYCCALL (CYTHON_FAST_PYCALL && PY_VERSION_HEX >= 0x030600B1)
#endif
#if CYTHON_USE_PYLONG_INTERNALS
#include "longintrepr.h"
#undef SHIFT
#undef BASE
#undef MASK
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#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag)
#define Py_OptimizeFlag 0
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#define __PYX_BUILD_PY_SSIZE_T "n"
#define CYTHON_FORMAT_SSIZE_T "z"
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#define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\
PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
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#define __Pyx_BUILTIN_MODULE_NAME "builtins"
#define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\
PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
#define __Pyx_DefaultClassType PyType_Type
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#ifndef Py_TPFLAGS_CHECKTYPES
#define Py_TPFLAGS_CHECKTYPES 0
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#define Py_TPFLAGS_HAVE_INDEX 0
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#define Py_TPFLAGS_HAVE_NEWBUFFER 0
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#define Py_TPFLAGS_HAVE_FINALIZE 0
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#ifndef METH_FASTCALL
#define METH_FASTCALL 0x80
typedef PyObject *(*__Pyx_PyCFunctionFast) (PyObject *self, PyObject **args,
Py_ssize_t nargs, PyObject *kwnames);
#else
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#if CYTHON_FAST_PYCCALL
#define __Pyx_PyFastCFunction_Check(func)\
((PyCFunction_Check(func) && (METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST)))))
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#define CYTHON_PEP393_ENABLED 1
#define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\
0 : _PyUnicode_Ready((PyObject *)(op)))
#define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u)
#define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i)
#define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) PyUnicode_MAX_CHAR_VALUE(u)
#define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u)
#define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u)
#define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i)
#define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch)
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#else
#define CYTHON_PEP393_ENABLED 0
#define PyUnicode_1BYTE_KIND 1
#define PyUnicode_2BYTE_KIND 2
#define PyUnicode_4BYTE_KIND 4
#define __Pyx_PyUnicode_READY(op) (0)
#define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u)
#define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i]))
#define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111)
#define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE))
#define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u))
#define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i]))
#define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch)
#define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u))
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#if CYTHON_COMPILING_IN_PYPY
#define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b)
#define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b)
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#define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b)
#define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\
PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b))
#endif
#if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains)
#define PyUnicode_Contains(u, s) PySequence_Contains(u, s)
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#if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check)
#define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type)
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#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format)
#define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, "__format__", "O", fmt)
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#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc)
#define PyObject_Malloc(s) PyMem_Malloc(s)
#define PyObject_Free(p) PyMem_Free(p)
#define PyObject_Realloc(p) PyMem_Realloc(p)
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#if CYTHON_COMPILING_IN_PYSTON
#define __Pyx_PyCode_HasFreeVars(co) PyCode_HasFreeVars(co)
#define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno)
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#define __Pyx_PyCode_HasFreeVars(co) (PyCode_GetNumFree(co) > 0)
#define __Pyx_PyFrame_SetLineNumber(frame, lineno) (frame)->f_lineno = (lineno)
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#define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b))
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#if PY_MAJOR_VERSION >= 3
#define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b)
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#define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception)
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#define PyInt_FromUnicode PyLong_FromUnicode
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#define PyInt_FromSsize_t PyLong_FromSsize_t
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#define PyInt_AS_LONG PyLong_AS_LONG
#define PyInt_AsSsize_t PyLong_AsSsize_t
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#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l)
#define __Pyx_PyBytes_FromString PyBytes_FromString
#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize
static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*);
#if PY_MAJOR_VERSION < 3
#define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString
#define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize
#else
#define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString
#define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize
#endif
#define __Pyx_PyObject_AsSString(s) ((signed char*) __Pyx_PyObject_AsString(s))
#define __Pyx_PyObject_AsUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s))
#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s)
#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s)
#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s)
#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s)
#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s)
#if PY_MAJOR_VERSION < 3
static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u)
{
const Py_UNICODE *u_end = u;
while (*u_end++) ;
return (size_t)(u_end - u - 1);
}
#else
#define __Pyx_Py_UNICODE_strlen Py_UNICODE_strlen
#endif
#define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u))
#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode
#define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode
#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj)
#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None)
#define __Pyx_PyBool_FromLong(b) ((b) ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False))
static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*);
static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x);
static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*);
static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t);
#if CYTHON_ASSUME_SAFE_MACROS
#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x))
#else
#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x)
#endif
#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x))
#if PY_MAJOR_VERSION >= 3
#define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x))
#else
#define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x))
#endif
#define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x))
#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
static int __Pyx_sys_getdefaultencoding_not_ascii;
static int __Pyx_init_sys_getdefaultencoding_params(void) {
PyObject* sys;
PyObject* default_encoding = NULL;
PyObject* ascii_chars_u = NULL;
PyObject* ascii_chars_b = NULL;
const char* default_encoding_c;
sys = PyImport_ImportModule("sys");
if (!sys) goto bad;
default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL);
Py_DECREF(sys);
if (!default_encoding) goto bad;
default_encoding_c = PyBytes_AsString(default_encoding);
if (!default_encoding_c) goto bad;
if (strcmp(default_encoding_c, "ascii") == 0) {
__Pyx_sys_getdefaultencoding_not_ascii = 0;
} else {
char ascii_chars[128];
int c;
for (c = 0; c < 128; c++) {
ascii_chars[c] = c;
}
__Pyx_sys_getdefaultencoding_not_ascii = 1;
ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL);
if (!ascii_chars_u) goto bad;
ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL);
if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) {
PyErr_Format(
PyExc_ValueError,
"This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.",
default_encoding_c);
goto bad;
}
Py_DECREF(ascii_chars_u);
Py_DECREF(ascii_chars_b);
}
Py_DECREF(default_encoding);
return 0;
bad:
Py_XDECREF(default_encoding);
Py_XDECREF(ascii_chars_u);
Py_XDECREF(ascii_chars_b);
return -1;
}
#endif
#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3
#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL)
#else
#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL)
#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
static char* __PYX_DEFAULT_STRING_ENCODING;
static int __Pyx_init_sys_getdefaultencoding_params(void) {
PyObject* sys;
PyObject* default_encoding = NULL;
char* default_encoding_c;
sys = PyImport_ImportModule("sys");
if (!sys) goto bad;
default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL);
Py_DECREF(sys);
if (!default_encoding) goto bad;
default_encoding_c = PyBytes_AsString(default_encoding);
if (!default_encoding_c) goto bad;
__PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c));
if (!__PYX_DEFAULT_STRING_ENCODING) goto bad;
strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c);
Py_DECREF(default_encoding);
return 0;
bad:
Py_XDECREF(default_encoding);
return -1;
}
#endif
#endif
/* Test for GCC > 2.95 */
#if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95)))
#define likely(x) __builtin_expect(!!(x), 1)
#define unlikely(x) __builtin_expect(!!(x), 0)
#else /* !__GNUC__ or GCC < 2.95 */
#define likely(x) (x)
#define unlikely(x) (x)
#endif /* __GNUC__ */
static PyObject *__pyx_m;
static PyObject *__pyx_d;
static PyObject *__pyx_b;
static PyObject *__pyx_empty_tuple;
static PyObject *__pyx_empty_bytes;
static PyObject *__pyx_empty_unicode;
static int __pyx_lineno;
static int __pyx_clineno = 0;
static const char * __pyx_cfilenm= __FILE__;
static const char *__pyx_filename;
static const char *__pyx_f[] = {
"pairwise3.pyx",
"stringsource",
};
/* MemviewSliceStruct.proto */
struct __pyx_memoryview_obj;
typedef struct {
struct __pyx_memoryview_obj *memview;
char *data;
Py_ssize_t shape[8];
Py_ssize_t strides[8];
Py_ssize_t suboffsets[8];
} __Pyx_memviewslice;
/* BufferFormatStructs.proto */
#define IS_UNSIGNED(type) (((type) -1) > 0)
struct __Pyx_StructField_;
#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0)
typedef struct {
const char* name;
struct __Pyx_StructField_* fields;
size_t size;
size_t arraysize[8];
int ndim;
char typegroup;
char is_unsigned;
int flags;
} __Pyx_TypeInfo;
typedef struct __Pyx_StructField_ {
__Pyx_TypeInfo* type;
const char* name;
size_t offset;
} __Pyx_StructField;
typedef struct {
__Pyx_StructField* field;
size_t parent_offset;
} __Pyx_BufFmt_StackElem;
typedef struct {
__Pyx_StructField root;
__Pyx_BufFmt_StackElem* head;
size_t fmt_offset;
size_t new_count, enc_count;
size_t struct_alignment;
int is_complex;
char enc_type;
char new_packmode;
char enc_packmode;
char is_valid_array;
} __Pyx_BufFmt_Context;
/* Atomics.proto */
#include <pythread.h>
#ifndef CYTHON_ATOMICS
#define CYTHON_ATOMICS 1
#endif
#define __pyx_atomic_int_type int
#if CYTHON_ATOMICS && __GNUC__ >= 4 && (__GNUC_MINOR__ > 1 ||\
(__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL >= 2)) &&\
!defined(__i386__)
#define __pyx_atomic_incr_aligned(value, lock) __sync_fetch_and_add(value, 1)
#define __pyx_atomic_decr_aligned(value, lock) __sync_fetch_and_sub(value, 1)
#ifdef __PYX_DEBUG_ATOMICS
#warning "Using GNU atomics"
#endif
#elif CYTHON_ATOMICS && defined(_MSC_VER) && 0
#include <Windows.h>
#undef __pyx_atomic_int_type
#define __pyx_atomic_int_type LONG
#define __pyx_atomic_incr_aligned(value, lock) InterlockedIncrement(value)
#define __pyx_atomic_decr_aligned(value, lock) InterlockedDecrement(value)
#ifdef __PYX_DEBUG_ATOMICS
#pragma message ("Using MSVC atomics")
#endif
#elif CYTHON_ATOMICS && (defined(__ICC) || defined(__INTEL_COMPILER)) && 0
#define __pyx_atomic_incr_aligned(value, lock) _InterlockedIncrement(value)
#define __pyx_atomic_decr_aligned(value, lock) _InterlockedDecrement(value)
#ifdef __PYX_DEBUG_ATOMICS
#warning "Using Intel atomics"
#endif
#else
#undef CYTHON_ATOMICS
#define CYTHON_ATOMICS 0
#ifdef __PYX_DEBUG_ATOMICS
#warning "Not using atomics"
#endif
#endif
typedef volatile __pyx_atomic_int_type __pyx_atomic_int;
#if CYTHON_ATOMICS
#define __pyx_add_acquisition_count(memview)\
__pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock)
#define __pyx_sub_acquisition_count(memview)\
__pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock)
#else
#define __pyx_add_acquisition_count(memview)\
__pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock)
#define __pyx_sub_acquisition_count(memview)\
__pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock)
#endif
/*--- Type declarations ---*/
struct __pyx_array_obj;
struct __pyx_MemviewEnum_obj;
struct __pyx_memoryview_obj;
struct __pyx_memoryviewslice_obj;
/* "View.MemoryView":103
*
* @cname("__pyx_array")
* cdef class array: # <<<<<<<<<<<<<<
*
* cdef:
*/
struct __pyx_array_obj {
PyObject_HEAD
struct __pyx_vtabstruct_array *__pyx_vtab;
char *data;
Py_ssize_t len;
char *format;
int ndim;
Py_ssize_t *_shape;
Py_ssize_t *_strides;
Py_ssize_t itemsize;
PyObject *mode;
PyObject *_format;
void (*callback_free_data)(void *);
int free_data;
int dtype_is_object;
};
/* "View.MemoryView":275
*
* @cname('__pyx_MemviewEnum')
* cdef class Enum(object): # <<<<<<<<<<<<<<
* cdef object name
* def __init__(self, name):
*/
struct __pyx_MemviewEnum_obj {
PyObject_HEAD
PyObject *name;
};
/* "View.MemoryView":326
*
* @cname('__pyx_memoryview')
* cdef class memoryview(object): # <<<<<<<<<<<<<<
*
* cdef object obj
*/
struct __pyx_memoryview_obj {
PyObject_HEAD
struct __pyx_vtabstruct_memoryview *__pyx_vtab;
PyObject *obj;
PyObject *_size;
PyObject *_array_interface;
PyThread_type_lock lock;
__pyx_atomic_int acquisition_count[2];
__pyx_atomic_int *acquisition_count_aligned_p;
Py_buffer view;
int flags;
int dtype_is_object;
__Pyx_TypeInfo *typeinfo;
};
/* "View.MemoryView":951
*
* @cname('__pyx_memoryviewslice')
* cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<<
* "Internal class for passing memoryview slices to Python"
*
*/
struct __pyx_memoryviewslice_obj {
struct __pyx_memoryview_obj __pyx_base;
__Pyx_memviewslice from_slice;
PyObject *from_object;
PyObject *(*to_object_func)(char *);
int (*to_dtype_func)(char *, PyObject *);
};
/* "View.MemoryView":103
*
* @cname("__pyx_array")
* cdef class array: # <<<<<<<<<<<<<<
*
* cdef:
*/
struct __pyx_vtabstruct_array {
PyObject *(*get_memview)(struct __pyx_array_obj *);
};
static struct __pyx_vtabstruct_array *__pyx_vtabptr_array;
/* "View.MemoryView":326
*
* @cname('__pyx_memoryview')
* cdef class memoryview(object): # <<<<<<<<<<<<<<
*
* cdef object obj
*/
struct __pyx_vtabstruct_memoryview {
char *(*get_item_pointer)(struct __pyx_memoryview_obj *, PyObject *);
PyObject *(*is_slice)(struct __pyx_memoryview_obj *, PyObject *);
PyObject *(*setitem_slice_assignment)(struct __pyx_memoryview_obj *, PyObject *, PyObject *);
PyObject *(*setitem_slice_assign_scalar)(struct __pyx_memoryview_obj *, struct __pyx_memoryview_obj *, PyObject *);
PyObject *(*setitem_indexed)(struct __pyx_memoryview_obj *, PyObject *, PyObject *);
PyObject *(*convert_item_to_object)(struct __pyx_memoryview_obj *, char *);
PyObject *(*assign_item_from_object)(struct __pyx_memoryview_obj *, char *, PyObject *);
};
static struct __pyx_vtabstruct_memoryview *__pyx_vtabptr_memoryview;
/* "View.MemoryView":951
*
* @cname('__pyx_memoryviewslice')
* cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<<
* "Internal class for passing memoryview slices to Python"
*
*/
struct __pyx_vtabstruct__memoryviewslice {
struct __pyx_vtabstruct_memoryview __pyx_base;
};
static struct __pyx_vtabstruct__memoryviewslice *__pyx_vtabptr__memoryviewslice;
/* --- Runtime support code (head) --- */
/* Refnanny.proto */
#ifndef CYTHON_REFNANNY
#define CYTHON_REFNANNY 0
#endif
#if CYTHON_REFNANNY
typedef struct {
void (*INCREF)(void*, PyObject*, int);
void (*DECREF)(void*, PyObject*, int);
void (*GOTREF)(void*, PyObject*, int);
void (*GIVEREF)(void*, PyObject*, int);
void* (*SetupContext)(const char*, int, const char*);
void (*FinishContext)(void**);
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static __Pyx_RefNannyAPIStruct *__Pyx_RefNanny = NULL;
static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname);
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PyGILState_Release(__pyx_gilstate_save);\
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#define __Pyx_RefNannySetupContext(name, acquire_gil)\
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#define __Pyx_RefNannyFinishContext()\
__Pyx_RefNanny->FinishContext(&__pyx_refnanny)
#define __Pyx_INCREF(r) __Pyx_RefNanny->INCREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
#define __Pyx_DECREF(r) __Pyx_RefNanny->DECREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
#define __Pyx_GOTREF(r) __Pyx_RefNanny->GOTREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
#define __Pyx_GIVEREF(r) __Pyx_RefNanny->GIVEREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
#define __Pyx_XINCREF(r) do { if((r) != NULL) {__Pyx_INCREF(r); }} while(0)
#define __Pyx_XDECREF(r) do { if((r) != NULL) {__Pyx_DECREF(r); }} while(0)
#define __Pyx_XGOTREF(r) do { if((r) != NULL) {__Pyx_GOTREF(r); }} while(0)
#define __Pyx_XGIVEREF(r) do { if((r) != NULL) {__Pyx_GIVEREF(r);}} while(0)
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#define __Pyx_RefNannyDeclarations
#define __Pyx_RefNannySetupContext(name, acquire_gil)
#define __Pyx_RefNannyFinishContext()
#define __Pyx_INCREF(r) Py_INCREF(r)
#define __Pyx_DECREF(r) Py_DECREF(r)
#define __Pyx_GOTREF(r)
#define __Pyx_GIVEREF(r)
#define __Pyx_XINCREF(r) Py_XINCREF(r)
#define __Pyx_XDECREF(r) Py_XDECREF(r)
#define __Pyx_XGOTREF(r)
#define __Pyx_XGIVEREF(r)
#endif
#define __Pyx_XDECREF_SET(r, v) do {\
PyObject *tmp = (PyObject *) r;\
r = v; __Pyx_XDECREF(tmp);\
} while (0)
#define __Pyx_DECREF_SET(r, v) do {\
PyObject *tmp = (PyObject *) r;\
r = v; __Pyx_DECREF(tmp);\
} while (0)
#define __Pyx_CLEAR(r) do { PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);} while(0)
#define __Pyx_XCLEAR(r) do { if((r) != NULL) {PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);}} while(0)
/* PyObjectGetAttrStr.proto */
#if CYTHON_USE_TYPE_SLOTS
static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name) {
PyTypeObject* tp = Py_TYPE(obj);
if (likely(tp->tp_getattro))
return tp->tp_getattro(obj, attr_name);
#if PY_MAJOR_VERSION < 3
if (likely(tp->tp_getattr))
return tp->tp_getattr(obj, PyString_AS_STRING(attr_name));
#endif
return PyObject_GetAttr(obj, attr_name);
}
#else
#define __Pyx_PyObject_GetAttrStr(o,n) PyObject_GetAttr(o,n)
#endif
/* GetBuiltinName.proto */
static PyObject *__Pyx_GetBuiltinName(PyObject *name);
/* GetModuleGlobalName.proto */
static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name);
/* PyObjectCall.proto */
#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw);
#else
#define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw)
#endif
/* BufferFormatCheck.proto */
static CYTHON_INLINE int __Pyx_GetBufferAndValidate(Py_buffer* buf, PyObject* obj,
__Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack);
static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info);
static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts);
static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx,
__Pyx_BufFmt_StackElem* stack,
__Pyx_TypeInfo* type); // PROTO
/* MemviewSliceInit.proto */
#define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d
#define __Pyx_MEMVIEW_DIRECT 1
#define __Pyx_MEMVIEW_PTR 2
#define __Pyx_MEMVIEW_FULL 4
#define __Pyx_MEMVIEW_CONTIG 8
#define __Pyx_MEMVIEW_STRIDED 16
#define __Pyx_MEMVIEW_FOLLOW 32
#define __Pyx_IS_C_CONTIG 1
#define __Pyx_IS_F_CONTIG 2
static int __Pyx_init_memviewslice(
struct __pyx_memoryview_obj *memview,
int ndim,
__Pyx_memviewslice *memviewslice,
int memview_is_new_reference);
static CYTHON_INLINE int __pyx_add_acquisition_count_locked(
__pyx_atomic_int *acquisition_count, PyThread_type_lock lock);
static CYTHON_INLINE int __pyx_sub_acquisition_count_locked(
__pyx_atomic_int *acquisition_count, PyThread_type_lock lock);
#define __pyx_get_slice_count_pointer(memview) (memview->acquisition_count_aligned_p)
#define __pyx_get_slice_count(memview) (*__pyx_get_slice_count_pointer(memview))
#define __PYX_INC_MEMVIEW(slice, have_gil) __Pyx_INC_MEMVIEW(slice, have_gil, __LINE__)
#define __PYX_XDEC_MEMVIEW(slice, have_gil) __Pyx_XDEC_MEMVIEW(slice, have_gil, __LINE__)
static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *, int, int);
static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *, int, int);
/* RaiseArgTupleInvalid.proto */
static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact,
Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found);
/* RaiseDoubleKeywords.proto */
static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name);
/* ParseKeywords.proto */
static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[],\
PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args,\
const char* function_name);
/* ArgTypeTest.proto */
static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed,
const char *name, int exact);
/* PyThreadStateGet.proto */
#if CYTHON_FAST_THREAD_STATE
#define __Pyx_PyThreadState_declare PyThreadState *__pyx_tstate;
#define __Pyx_PyThreadState_assign __pyx_tstate = PyThreadState_GET();
#else
#define __Pyx_PyThreadState_declare
#define __Pyx_PyThreadState_assign
#endif
/* PyErrFetchRestore.proto */
#if CYTHON_FAST_THREAD_STATE
#define __Pyx_ErrRestoreWithState(type, value, tb) __Pyx_ErrRestoreInState(PyThreadState_GET(), type, value, tb)
#define __Pyx_ErrFetchWithState(type, value, tb) __Pyx_ErrFetchInState(PyThreadState_GET(), type, value, tb)
#define __Pyx_ErrRestore(type, value, tb) __Pyx_ErrRestoreInState(__pyx_tstate, type, value, tb)
#define __Pyx_ErrFetch(type, value, tb) __Pyx_ErrFetchInState(__pyx_tstate, type, value, tb)
static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb);
static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb);
#else
#define __Pyx_ErrRestoreWithState(type, value, tb) PyErr_Restore(type, value, tb)
#define __Pyx_ErrFetchWithState(type, value, tb) PyErr_Fetch(type, value, tb)
#define __Pyx_ErrRestore(type, value, tb) PyErr_Restore(type, value, tb)
#define __Pyx_ErrFetch(type, value, tb) PyErr_Fetch(type, value, tb)
#endif
/* RaiseException.proto */
static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause);
/* IncludeStringH.proto */
#include <string.h>
/* BytesEquals.proto */
static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals);
/* UnicodeEquals.proto */
static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals);
/* StrEquals.proto */
#if PY_MAJOR_VERSION >= 3
#define __Pyx_PyString_Equals __Pyx_PyUnicode_Equals
#else
#define __Pyx_PyString_Equals __Pyx_PyBytes_Equals
#endif
/* None.proto */
static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t, Py_ssize_t);
/* UnaryNegOverflows.proto */
#define UNARY_NEG_WOULD_OVERFLOW(x)\
(((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x)))
static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/
static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *); /*proto*/
/* GetAttr.proto */
static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *);
/* decode_c_string.proto */
static CYTHON_INLINE PyObject* __Pyx_decode_c_string(
const char* cstring, Py_ssize_t start, Py_ssize_t stop,
const char* encoding, const char* errors,
PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors));
/* RaiseTooManyValuesToUnpack.proto */
static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected);
/* RaiseNeedMoreValuesToUnpack.proto */
static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index);
/* RaiseNoneIterError.proto */
static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void);
/* ExtTypeTest.proto */
static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type);
/* SaveResetException.proto */
#if CYTHON_FAST_THREAD_STATE
#define __Pyx_ExceptionSave(type, value, tb) __Pyx__ExceptionSave(__pyx_tstate, type, value, tb)
static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb);
#define __Pyx_ExceptionReset(type, value, tb) __Pyx__ExceptionReset(__pyx_tstate, type, value, tb)
static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb);
#else
#define __Pyx_ExceptionSave(type, value, tb) PyErr_GetExcInfo(type, value, tb)
#define __Pyx_ExceptionReset(type, value, tb) PyErr_SetExcInfo(type, value, tb)
#endif
/* PyErrExceptionMatches.proto */
#if CYTHON_FAST_THREAD_STATE
#define __Pyx_PyErr_ExceptionMatches(err) __Pyx_PyErr_ExceptionMatchesInState(__pyx_tstate, err)
static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err);
#else
#define __Pyx_PyErr_ExceptionMatches(err) PyErr_ExceptionMatches(err)
#endif
/* GetException.proto */
#if CYTHON_FAST_THREAD_STATE
#define __Pyx_GetException(type, value, tb) __Pyx__GetException(__pyx_tstate, type, value, tb)
static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb);
#else
static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb);
#endif
/* SwapException.proto */
#if CYTHON_FAST_THREAD_STATE
#define __Pyx_ExceptionSwap(type, value, tb) __Pyx__ExceptionSwap(__pyx_tstate, type, value, tb)
static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb);
#else
static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb);
#endif
/* Import.proto */
static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level);
/* PyFunctionFastCall.proto */
#if CYTHON_FAST_PYCALL
#define __Pyx_PyFunction_FastCall(func, args, nargs)\
__Pyx_PyFunction_FastCallDict((func), (args), (nargs), NULL)
#if 1 || PY_VERSION_HEX < 0x030600B1
static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, int nargs, PyObject *kwargs);
#else
#define __Pyx_PyFunction_FastCallDict(func, args, nargs, kwargs) _PyFunction_FastCallDict(func, args, nargs, kwargs)
#endif
#endif
/* PyCFunctionFastCall.proto */
#if CYTHON_FAST_PYCCALL
static CYTHON_INLINE PyObject *__Pyx_PyCFunction_FastCall(PyObject *func, PyObject **args, Py_ssize_t nargs);
#else
#define __Pyx_PyCFunction_FastCall(func, args, nargs) (assert(0), NULL)
#endif
/* GetItemInt.proto */
#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\
(__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\
__Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) :\
(is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) :\
__Pyx_GetItemInt_Generic(o, to_py_func(i))))
#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\
(__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\
__Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\
(PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL))
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
int wraparound, int boundscheck);
#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\
(__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\
__Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\
(PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL))
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
int wraparound, int boundscheck);
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j);
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i,
int is_list, int wraparound, int boundscheck);
static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/
/* ListCompAppend.proto */
#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS
static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) {
PyListObject* L = (PyListObject*) list;
Py_ssize_t len = Py_SIZE(list);
if (likely(L->allocated > len)) {
Py_INCREF(x);
PyList_SET_ITEM(list, len, x);
Py_SIZE(list) = len+1;
return 0;
}
return PyList_Append(list, x);
}
#else
#define __Pyx_ListComp_Append(L,x) PyList_Append(L,x)
#endif
/* PyIntBinop.proto */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace);
#else
#define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace)\
(inplace ? PyNumber_InPlaceAdd(op1, op2) : PyNumber_Add(op1, op2))
#endif
/* ListExtend.proto */
static CYTHON_INLINE int __Pyx_PyList_Extend(PyObject* L, PyObject* v) {
#if CYTHON_COMPILING_IN_CPYTHON
PyObject* none = _PyList_Extend((PyListObject*)L, v);
if (unlikely(!none))
return -1;
Py_DECREF(none);
return 0;
#else
return PyList_SetSlice(L, PY_SSIZE_T_MAX, PY_SSIZE_T_MAX, v);
#endif
}
/* ListAppend.proto */
#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS
static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) {
PyListObject* L = (PyListObject*) list;
Py_ssize_t len = Py_SIZE(list);
if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) {
Py_INCREF(x);
PyList_SET_ITEM(list, len, x);
Py_SIZE(list) = len+1;
return 0;
}
return PyList_Append(list, x);
}
#else
#define __Pyx_PyList_Append(L,x) PyList_Append(L,x)
#endif
/* None.proto */
static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname);
/* ForceInitThreads.proto */
#ifndef __PYX_FORCE_INIT_THREADS
#define __PYX_FORCE_INIT_THREADS 0
#endif
/* None.proto */
static CYTHON_INLINE long __Pyx_div_long(long, long);
/* WriteUnraisableException.proto */
static void __Pyx_WriteUnraisable(const char *name, int clineno,
int lineno, const char *filename,
int full_traceback, int nogil);
/* PyObjectCallMethO.proto */
#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg);
#endif
/* PyObjectCallOneArg.proto */
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg);
/* SetVTable.proto */
static int __Pyx_SetVtable(PyObject *dict, void *vtable);
/* CodeObjectCache.proto */
typedef struct {
PyCodeObject* code_object;
int code_line;
} __Pyx_CodeObjectCacheEntry;
struct __Pyx_CodeObjectCache {
int count;
int max_count;
__Pyx_CodeObjectCacheEntry* entries;
};
static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL};
static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line);
static PyCodeObject *__pyx_find_code_object(int code_line);
static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object);
/* AddTraceback.proto */
static void __Pyx_AddTraceback(const char *funcname, int c_line,
int py_line, const char *filename);
#if PY_MAJOR_VERSION < 3
static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags);
static void __Pyx_ReleaseBuffer(Py_buffer *view);
#else
#define __Pyx_GetBuffer PyObject_GetBuffer
#define __Pyx_ReleaseBuffer PyBuffer_Release
#endif
/* BufferStructDeclare.proto */
typedef struct {
Py_ssize_t shape, strides, suboffsets;
} __Pyx_Buf_DimInfo;
typedef struct {
size_t refcount;
Py_buffer pybuffer;
} __Pyx_Buffer;
typedef struct {
__Pyx_Buffer *rcbuffer;
char *data;
__Pyx_Buf_DimInfo diminfo[8];
} __Pyx_LocalBuf_ND;
/* None.proto */
static Py_ssize_t __Pyx_zeros[] = {0, 0, 0, 0, 0, 0, 0, 0};
static Py_ssize_t __Pyx_minusones[] = {-1, -1, -1, -1, -1, -1, -1, -1};
/* MemviewSliceIsContig.proto */
static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs,
char order, int ndim);
/* OverlappingSlices.proto */
static int __pyx_slices_overlap(__Pyx_memviewslice *slice1,
__Pyx_memviewslice *slice2,
int ndim, size_t itemsize);
/* Capsule.proto */
static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig);
/* TypeInfoCompare.proto */
static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b);
/* MemviewSliceValidateAndInit.proto */
static int __Pyx_ValidateAndInit_memviewslice(
int *axes_specs,
int c_or_f_flag,
int buf_flags,
int ndim,
__Pyx_TypeInfo *dtype,
__Pyx_BufFmt_StackElem stack[],
__Pyx_memviewslice *memviewslice,
PyObject *original_obj);
/* ObjectToMemviewSlice.proto */
static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_double(PyObject *);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value);
/* MemviewDtypeToObject.proto */
static CYTHON_INLINE PyObject *__pyx_memview_get_double(const char *itemp);
static CYTHON_INLINE int __pyx_memview_set_double(const char *itemp, PyObject *obj);
/* MemviewSliceCopyTemplate.proto */
static __Pyx_memviewslice
__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs,
const char *mode, int ndim,
size_t sizeof_dtype, int contig_flag,
int dtype_is_object);
/* CIntFromPy.proto */
static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *);
/* CIntFromPy.proto */
static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *);
/* CIntFromPy.proto */
static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *);
/* CheckBinaryVersion.proto */
static int __Pyx_check_binary_version(void);
/* InitStrings.proto */
static int __Pyx_InitStrings(__Pyx_StringTabEntry *t);
static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *__pyx_v_self); /* proto*/
static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/
static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/
static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/
static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/
static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/
static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/
static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/
static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/
static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/
/* Module declarations from 'cython.view' */
/* Module declarations from 'cython' */
/* Module declarations from 'libc.math' */
/* Module declarations from 'pairwise3' */
static PyTypeObject *__pyx_array_type = 0;
static PyTypeObject *__pyx_MemviewEnum_type = 0;
static PyTypeObject *__pyx_memoryview_type = 0;
static PyTypeObject *__pyx_memoryviewslice_type = 0;
static PyObject *generic = 0;
static PyObject *strided = 0;
static PyObject *indirect = 0;
static PyObject *contiguous = 0;
static PyObject *indirect_contiguous = 0;
static int __pyx_memoryview_thread_locks_used;
static PyThread_type_lock __pyx_memoryview_thread_locks[8];
static CYTHON_INLINE double __pyx_f_9pairwise3_euclidean_distance(__Pyx_memviewslice, int, int, int); /*proto*/
static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/
static void *__pyx_align_pointer(void *, size_t); /*proto*/
static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/
static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/
static PyObject *_unellipsify(PyObject *, int); /*proto*/
static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/
static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/
static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/
static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/
static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/
static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/
static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/
static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/
static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/
static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/
static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/
static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/
static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/
static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/
static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/
static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/
static int __pyx_memoryview_err(PyObject *, char *); /*proto*/
static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/
static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/
static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/
static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/
static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/
static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/
static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/
static __Pyx_TypeInfo __Pyx_TypeInfo_double = { "double", NULL, sizeof(double), { 0 }, 0, 'R', 0, 0 };
#define __Pyx_MODULE_NAME "pairwise3"
int __pyx_module_is_main_pairwise3 = 0;
/* Implementation of 'pairwise3' */
static PyObject *__pyx_builtin_range;
static PyObject *__pyx_builtin_ValueError;
static PyObject *__pyx_builtin_MemoryError;
static PyObject *__pyx_builtin_enumerate;
static PyObject *__pyx_builtin_Ellipsis;
static PyObject *__pyx_builtin_TypeError;
static PyObject *__pyx_builtin_id;
static PyObject *__pyx_builtin_IndexError;
static const char __pyx_k_D[] = "D";
static const char __pyx_k_O[] = "O";
static const char __pyx_k_X[] = "X";
static const char __pyx_k_c[] = "c";
static const char __pyx_k_i[] = "i";
static const char __pyx_k_j[] = "j";
static const char __pyx_k_id[] = "id";
static const char __pyx_k_np[] = "np";
static const char __pyx_k_obj[] = "obj";
static const char __pyx_k_base[] = "base";
static const char __pyx_k_dist[] = "dist";
static const char __pyx_k_main[] = "__main__";
static const char __pyx_k_mode[] = "mode";
static const char __pyx_k_name[] = "name";
static const char __pyx_k_ndim[] = "ndim";
static const char __pyx_k_pack[] = "pack";
static const char __pyx_k_size[] = "size";
static const char __pyx_k_step[] = "step";
static const char __pyx_k_stop[] = "stop";
static const char __pyx_k_test[] = "__test__";
static const char __pyx_k_ASCII[] = "ASCII";
static const char __pyx_k_class[] = "__class__";
static const char __pyx_k_dtype[] = "dtype";
static const char __pyx_k_error[] = "error";
static const char __pyx_k_flags[] = "flags";
static const char __pyx_k_n_dim[] = "n_dim";
static const char __pyx_k_numpy[] = "numpy";
static const char __pyx_k_range[] = "range";
static const char __pyx_k_shape[] = "shape";
static const char __pyx_k_start[] = "start";
static const char __pyx_k_zeros[] = "zeros";
static const char __pyx_k_encode[] = "encode";
static const char __pyx_k_format[] = "format";
static const char __pyx_k_import[] = "__import__";
static const char __pyx_k_name_2[] = "__name__";
static const char __pyx_k_struct[] = "struct";
static const char __pyx_k_unpack[] = "unpack";
static const char __pyx_k_float64[] = "float64";
static const char __pyx_k_fortran[] = "fortran";
static const char __pyx_k_memview[] = "memview";
static const char __pyx_k_Ellipsis[] = "Ellipsis";
static const char __pyx_k_itemsize[] = "itemsize";
static const char __pyx_k_TypeError[] = "TypeError";
static const char __pyx_k_enumerate[] = "enumerate";
static const char __pyx_k_n_samples[] = "n_samples";
static const char __pyx_k_pairwise3[] = "pairwise3";
static const char __pyx_k_IndexError[] = "IndexError";
static const char __pyx_k_ValueError[] = "ValueError";
static const char __pyx_k_pyx_vtable[] = "__pyx_vtable__";
static const char __pyx_k_MemoryError[] = "MemoryError";
static const char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer";
static const char __pyx_k_allocate_buffer[] = "allocate_buffer";
static const char __pyx_k_dtype_is_object[] = "dtype_is_object";
static const char __pyx_k_strided_and_direct[] = "<strided and direct>";
static const char __pyx_k_strided_and_indirect[] = "<strided and indirect>";
static const char __pyx_k_contiguous_and_direct[] = "<contiguous and direct>";
static const char __pyx_k_MemoryView_of_r_object[] = "<MemoryView of %r object>";
static const char __pyx_k_MemoryView_of_r_at_0x_x[] = "<MemoryView of %r at 0x%x>";
static const char __pyx_k_contiguous_and_indirect[] = "<contiguous and indirect>";
static const char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'";
static const char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d.";
static const char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array";
static const char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data.";
static const char __pyx_k_Users_r631854_machine_learning[] = "/Users/r631854/machine-learning/python/cython/pairwise3.pyx";
static const char __pyx_k_strided_and_direct_or_indirect[] = "<strided and direct or indirect>";
static const char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides";
static const char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory.";
static const char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array";
static const char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported";
static const char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s";
static const char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)";
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if (__pyx_t_2) {
/* "View.MemoryView":818
* start += shape
* if not 0 <= start < shape:
* _err_dim(IndexError, "Index out of bounds (axis %d)", dim) # <<<<<<<<<<<<<<
* else:
*
*/
__pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, ((char *)"Index out of bounds (axis %d)"), __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) __PYX_ERR(1, 818, __pyx_L1_error)
/* "View.MemoryView":817
* if start < 0:
* start += shape
* if not 0 <= start < shape: # <<<<<<<<<<<<<<
* _err_dim(IndexError, "Index out of bounds (axis %d)", dim)
* else:
*/
}
/* "View.MemoryView":813
* cdef bint negative_step
*
* if not is_slice: # <<<<<<<<<<<<<<
*
* if start < 0:
*/
goto __pyx_L3;
}
/* "View.MemoryView":821
* else:
*
* negative_step = have_step != 0 and step < 0 # <<<<<<<<<<<<<<
*
* if have_step and step == 0:
*/
/*else*/ {
__pyx_t_1 = ((__pyx_v_have_step != 0) != 0);
if (__pyx_t_1) {
} else {
__pyx_t_2 = __pyx_t_1;
goto __pyx_L6_bool_binop_done;
}
__pyx_t_1 = ((__pyx_v_step < 0) != 0);
__pyx_t_2 = __pyx_t_1;
__pyx_L6_bool_binop_done:;
__pyx_v_negative_step = __pyx_t_2;
/* "View.MemoryView":823
* negative_step = have_step != 0 and step < 0
*
* if have_step and step == 0: # <<<<<<<<<<<<<<
* _err_dim(ValueError, "Step may not be zero (axis %d)", dim)
*
*/
__pyx_t_1 = (__pyx_v_have_step != 0);
if (__pyx_t_1) {
} else {
__pyx_t_2 = __pyx_t_1;
goto __pyx_L9_bool_binop_done;
}
__pyx_t_1 = ((__pyx_v_step == 0) != 0);
__pyx_t_2 = __pyx_t_1;
__pyx_L9_bool_binop_done:;
if (__pyx_t_2) {
/* "View.MemoryView":824
*
* if have_step and step == 0:
* _err_dim(ValueError, "Step may not be zero (axis %d)", dim) # <<<<<<<<<<<<<<
*
*
*/
__pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, ((char *)"Step may not be zero (axis %d)"), __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) __PYX_ERR(1, 824, __pyx_L1_error)
/* "View.MemoryView":823
* negative_step = have_step != 0 and step < 0
*
* if have_step and step == 0: # <<<<<<<<<<<<<<
* _err_dim(ValueError, "Step may not be zero (axis %d)", dim)
*
*/
}
/* "View.MemoryView":827
*
*
* if have_start: # <<<<<<<<<<<<<<
* if start < 0:
* start += shape
*/
__pyx_t_2 = (__pyx_v_have_start != 0);
if (__pyx_t_2) {
/* "View.MemoryView":828
*
* if have_start:
* if start < 0: # <<<<<<<<<<<<<<
* start += shape
* if start < 0:
*/
__pyx_t_2 = ((__pyx_v_start < 0) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":829
* if have_start:
* if start < 0:
* start += shape # <<<<<<<<<<<<<<
* if start < 0:
* start = 0
*/
__pyx_v_start = (__pyx_v_start + __pyx_v_shape);
/* "View.MemoryView":830
* if start < 0:
* start += shape
* if start < 0: # <<<<<<<<<<<<<<
* start = 0
* elif start >= shape:
*/
__pyx_t_2 = ((__pyx_v_start < 0) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":831
* start += shape
* if start < 0:
* start = 0 # <<<<<<<<<<<<<<
* elif start >= shape:
* if negative_step:
*/
__pyx_v_start = 0;
/* "View.MemoryView":830
* if start < 0:
* start += shape
* if start < 0: # <<<<<<<<<<<<<<
* start = 0
* elif start >= shape:
*/
}
/* "View.MemoryView":828
*
* if have_start:
* if start < 0: # <<<<<<<<<<<<<<
* start += shape
* if start < 0:
*/
goto __pyx_L12;
}
/* "View.MemoryView":832
* if start < 0:
* start = 0
* elif start >= shape: # <<<<<<<<<<<<<<
* if negative_step:
* start = shape - 1
*/
__pyx_t_2 = ((__pyx_v_start >= __pyx_v_shape) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":833
* start = 0
* elif start >= shape:
* if negative_step: # <<<<<<<<<<<<<<
* start = shape - 1
* else:
*/
__pyx_t_2 = (__pyx_v_negative_step != 0);
if (__pyx_t_2) {
/* "View.MemoryView":834
* elif start >= shape:
* if negative_step:
* start = shape - 1 # <<<<<<<<<<<<<<
* else:
* start = shape
*/
__pyx_v_start = (__pyx_v_shape - 1);
/* "View.MemoryView":833
* start = 0
* elif start >= shape:
* if negative_step: # <<<<<<<<<<<<<<
* start = shape - 1
* else:
*/
goto __pyx_L14;
}
/* "View.MemoryView":836
* start = shape - 1
* else:
* start = shape # <<<<<<<<<<<<<<
* else:
* if negative_step:
*/
/*else*/ {
__pyx_v_start = __pyx_v_shape;
}
__pyx_L14:;
/* "View.MemoryView":832
* if start < 0:
* start = 0
* elif start >= shape: # <<<<<<<<<<<<<<
* if negative_step:
* start = shape - 1
*/
}
__pyx_L12:;
/* "View.MemoryView":827
*
*
* if have_start: # <<<<<<<<<<<<<<
* if start < 0:
* start += shape
*/
goto __pyx_L11;
}
/* "View.MemoryView":838
* start = shape
* else:
* if negative_step: # <<<<<<<<<<<<<<
* start = shape - 1
* else:
*/
/*else*/ {
__pyx_t_2 = (__pyx_v_negative_step != 0);
if (__pyx_t_2) {
/* "View.MemoryView":839
* else:
* if negative_step:
* start = shape - 1 # <<<<<<<<<<<<<<
* else:
* start = 0
*/
__pyx_v_start = (__pyx_v_shape - 1);
/* "View.MemoryView":838
* start = shape
* else:
* if negative_step: # <<<<<<<<<<<<<<
* start = shape - 1
* else:
*/
goto __pyx_L15;
}
/* "View.MemoryView":841
* start = shape - 1
* else:
* start = 0 # <<<<<<<<<<<<<<
*
* if have_stop:
*/
/*else*/ {
__pyx_v_start = 0;
}
__pyx_L15:;
}
__pyx_L11:;
/* "View.MemoryView":843
* start = 0
*
* if have_stop: # <<<<<<<<<<<<<<
* if stop < 0:
* stop += shape
*/
__pyx_t_2 = (__pyx_v_have_stop != 0);
if (__pyx_t_2) {
/* "View.MemoryView":844
*
* if have_stop:
* if stop < 0: # <<<<<<<<<<<<<<
* stop += shape
* if stop < 0:
*/
__pyx_t_2 = ((__pyx_v_stop < 0) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":845
* if have_stop:
* if stop < 0:
* stop += shape # <<<<<<<<<<<<<<
* if stop < 0:
* stop = 0
*/
__pyx_v_stop = (__pyx_v_stop + __pyx_v_shape);
/* "View.MemoryView":846
* if stop < 0:
* stop += shape
* if stop < 0: # <<<<<<<<<<<<<<
* stop = 0
* elif stop > shape:
*/
__pyx_t_2 = ((__pyx_v_stop < 0) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":847
* stop += shape
* if stop < 0:
* stop = 0 # <<<<<<<<<<<<<<
* elif stop > shape:
* stop = shape
*/
__pyx_v_stop = 0;
/* "View.MemoryView":846
* if stop < 0:
* stop += shape
* if stop < 0: # <<<<<<<<<<<<<<
* stop = 0
* elif stop > shape:
*/
}
/* "View.MemoryView":844
*
* if have_stop:
* if stop < 0: # <<<<<<<<<<<<<<
* stop += shape
* if stop < 0:
*/
goto __pyx_L17;
}
/* "View.MemoryView":848
* if stop < 0:
* stop = 0
* elif stop > shape: # <<<<<<<<<<<<<<
* stop = shape
* else:
*/
__pyx_t_2 = ((__pyx_v_stop > __pyx_v_shape) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":849
* stop = 0
* elif stop > shape:
* stop = shape # <<<<<<<<<<<<<<
* else:
* if negative_step:
*/
__pyx_v_stop = __pyx_v_shape;
/* "View.MemoryView":848
* if stop < 0:
* stop = 0
* elif stop > shape: # <<<<<<<<<<<<<<
* stop = shape
* else:
*/
}
__pyx_L17:;
/* "View.MemoryView":843
* start = 0
*
* if have_stop: # <<<<<<<<<<<<<<
* if stop < 0:
* stop += shape
*/
goto __pyx_L16;
}
/* "View.MemoryView":851
* stop = shape
* else:
* if negative_step: # <<<<<<<<<<<<<<
* stop = -1
* else:
*/
/*else*/ {
__pyx_t_2 = (__pyx_v_negative_step != 0);
if (__pyx_t_2) {
/* "View.MemoryView":852
* else:
* if negative_step:
* stop = -1 # <<<<<<<<<<<<<<
* else:
* stop = shape
*/
__pyx_v_stop = -1L;
/* "View.MemoryView":851
* stop = shape
* else:
* if negative_step: # <<<<<<<<<<<<<<
* stop = -1
* else:
*/
goto __pyx_L19;
}
/* "View.MemoryView":854
* stop = -1
* else:
* stop = shape # <<<<<<<<<<<<<<
*
* if not have_step:
*/
/*else*/ {
__pyx_v_stop = __pyx_v_shape;
}
__pyx_L19:;
}
__pyx_L16:;
/* "View.MemoryView":856
* stop = shape
*
* if not have_step: # <<<<<<<<<<<<<<
* step = 1
*
*/
__pyx_t_2 = ((!(__pyx_v_have_step != 0)) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":857
*
* if not have_step:
* step = 1 # <<<<<<<<<<<<<<
*
*
*/
__pyx_v_step = 1;
/* "View.MemoryView":856
* stop = shape
*
* if not have_step: # <<<<<<<<<<<<<<
* step = 1
*
*/
}
/* "View.MemoryView":861
*
* with cython.cdivision(True):
* new_shape = (stop - start) // step # <<<<<<<<<<<<<<
*
* if (stop - start) - step * new_shape:
*/
__pyx_v_new_shape = ((__pyx_v_stop - __pyx_v_start) / __pyx_v_step);
/* "View.MemoryView":863
* new_shape = (stop - start) // step
*
* if (stop - start) - step * new_shape: # <<<<<<<<<<<<<<
* new_shape += 1
*
*/
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if (__pyx_t_2) {
/* "View.MemoryView":864
*
* if (stop - start) - step * new_shape:
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*
* if new_shape < 0:
*/
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/* "View.MemoryView":863
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*
* if (stop - start) - step * new_shape: # <<<<<<<<<<<<<<
* new_shape += 1
*
*/
}
/* "View.MemoryView":866
* new_shape += 1
*
* if new_shape < 0: # <<<<<<<<<<<<<<
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*
*/
__pyx_t_2 = ((__pyx_v_new_shape < 0) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":867
*
* if new_shape < 0:
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*
*
*/
__pyx_v_new_shape = 0;
/* "View.MemoryView":866
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* if new_shape < 0: # <<<<<<<<<<<<<<
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*/
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/* "View.MemoryView":870
*
*
* dst.strides[new_ndim] = stride * step # <<<<<<<<<<<<<<
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* dst.suboffsets[new_ndim] = suboffset
*/
(__pyx_v_dst->strides[__pyx_v_new_ndim]) = (__pyx_v_stride * __pyx_v_step);
/* "View.MemoryView":871
*
* dst.strides[new_ndim] = stride * step
* dst.shape[new_ndim] = new_shape # <<<<<<<<<<<<<<
* dst.suboffsets[new_ndim] = suboffset
*
*/
(__pyx_v_dst->shape[__pyx_v_new_ndim]) = __pyx_v_new_shape;
/* "View.MemoryView":872
* dst.strides[new_ndim] = stride * step
* dst.shape[new_ndim] = new_shape
* dst.suboffsets[new_ndim] = suboffset # <<<<<<<<<<<<<<
*
*
*/
(__pyx_v_dst->suboffsets[__pyx_v_new_ndim]) = __pyx_v_suboffset;
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__pyx_L3:;
/* "View.MemoryView":875
*
*
* if suboffset_dim[0] < 0: # <<<<<<<<<<<<<<
* dst.data += start * stride
* else:
*/
__pyx_t_2 = (((__pyx_v_suboffset_dim[0]) < 0) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":876
*
* if suboffset_dim[0] < 0:
* dst.data += start * stride # <<<<<<<<<<<<<<
* else:
* dst.suboffsets[suboffset_dim[0]] += start * stride
*/
__pyx_v_dst->data = (__pyx_v_dst->data + (__pyx_v_start * __pyx_v_stride));
/* "View.MemoryView":875
*
*
* if suboffset_dim[0] < 0: # <<<<<<<<<<<<<<
* dst.data += start * stride
* else:
*/
goto __pyx_L23;
}
/* "View.MemoryView":878
* dst.data += start * stride
* else:
* dst.suboffsets[suboffset_dim[0]] += start * stride # <<<<<<<<<<<<<<
*
* if suboffset >= 0:
*/
/*else*/ {
__pyx_t_3 = (__pyx_v_suboffset_dim[0]);
(__pyx_v_dst->suboffsets[__pyx_t_3]) = ((__pyx_v_dst->suboffsets[__pyx_t_3]) + (__pyx_v_start * __pyx_v_stride));
}
__pyx_L23:;
/* "View.MemoryView":880
* dst.suboffsets[suboffset_dim[0]] += start * stride
*
* if suboffset >= 0: # <<<<<<<<<<<<<<
* if not is_slice:
* if new_ndim == 0:
*/
__pyx_t_2 = ((__pyx_v_suboffset >= 0) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":881
*
* if suboffset >= 0:
* if not is_slice: # <<<<<<<<<<<<<<
* if new_ndim == 0:
* dst.data = (<char **> dst.data)[0] + suboffset
*/
__pyx_t_2 = ((!(__pyx_v_is_slice != 0)) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":882
* if suboffset >= 0:
* if not is_slice:
* if new_ndim == 0: # <<<<<<<<<<<<<<
* dst.data = (<char **> dst.data)[0] + suboffset
* else:
*/
__pyx_t_2 = ((__pyx_v_new_ndim == 0) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":883
* if not is_slice:
* if new_ndim == 0:
* dst.data = (<char **> dst.data)[0] + suboffset # <<<<<<<<<<<<<<
* else:
* _err_dim(IndexError, "All dimensions preceding dimension %d "
*/
__pyx_v_dst->data = ((((char **)__pyx_v_dst->data)[0]) + __pyx_v_suboffset);
/* "View.MemoryView":882
* if suboffset >= 0:
* if not is_slice:
* if new_ndim == 0: # <<<<<<<<<<<<<<
* dst.data = (<char **> dst.data)[0] + suboffset
* else:
*/
goto __pyx_L26;
}
/* "View.MemoryView":885
* dst.data = (<char **> dst.data)[0] + suboffset
* else:
* _err_dim(IndexError, "All dimensions preceding dimension %d " # <<<<<<<<<<<<<<
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* else:
*/
/*else*/ {
/* "View.MemoryView":886
* else:
* _err_dim(IndexError, "All dimensions preceding dimension %d "
* "must be indexed and not sliced", dim) # <<<<<<<<<<<<<<
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*/
__pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, ((char *)"All dimensions preceding dimension %d must be indexed and not sliced"), __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) __PYX_ERR(1, 885, __pyx_L1_error)
}
__pyx_L26:;
/* "View.MemoryView":881
*
* if suboffset >= 0:
* if not is_slice: # <<<<<<<<<<<<<<
* if new_ndim == 0:
* dst.data = (<char **> dst.data)[0] + suboffset
*/
goto __pyx_L25;
}
/* "View.MemoryView":888
* "must be indexed and not sliced", dim)
* else:
* suboffset_dim[0] = new_ndim # <<<<<<<<<<<<<<
*
* return 0
*/
/*else*/ {
(__pyx_v_suboffset_dim[0]) = __pyx_v_new_ndim;
}
__pyx_L25:;
/* "View.MemoryView":880
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*
* if suboffset >= 0: # <<<<<<<<<<<<<<
* if not is_slice:
* if new_ndim == 0:
*/
}
/* "View.MemoryView":890
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*
* return 0 # <<<<<<<<<<<<<<
*
*
*/
__pyx_r = 0;
goto __pyx_L0;
/* "View.MemoryView":793
*
* @cname('__pyx_memoryview_slice_memviewslice')
* cdef int slice_memviewslice( # <<<<<<<<<<<<<<
* __Pyx_memviewslice *dst,
* Py_ssize_t shape, Py_ssize_t stride, Py_ssize_t suboffset,
*/
/* function exit code */
__pyx_L1_error:;
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PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure();
#endif
__Pyx_AddTraceback("View.MemoryView.slice_memviewslice", __pyx_clineno, __pyx_lineno, __pyx_filename);
#ifdef WITH_THREAD
PyGILState_Release(__pyx_gilstate_save);
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__pyx_L0:;
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/* "View.MemoryView":896
*
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* Py_ssize_t dim) except NULL:
* cdef Py_ssize_t shape, stride, suboffset = -1
*/
static char *__pyx_pybuffer_index(Py_buffer *__pyx_v_view, char *__pyx_v_bufp, Py_ssize_t __pyx_v_index, Py_ssize_t __pyx_v_dim) {
Py_ssize_t __pyx_v_shape;
Py_ssize_t __pyx_v_stride;
Py_ssize_t __pyx_v_suboffset;
Py_ssize_t __pyx_v_itemsize;
char *__pyx_v_resultp;
char *__pyx_r;
__Pyx_RefNannyDeclarations
Py_ssize_t __pyx_t_1;
int __pyx_t_2;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
__Pyx_RefNannySetupContext("pybuffer_index", 0);
/* "View.MemoryView":898
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* cdef Py_ssize_t shape, stride, suboffset = -1 # <<<<<<<<<<<<<<
* cdef Py_ssize_t itemsize = view.itemsize
* cdef char *resultp
*/
__pyx_v_suboffset = -1L;
/* "View.MemoryView":899
* Py_ssize_t dim) except NULL:
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* cdef Py_ssize_t itemsize = view.itemsize # <<<<<<<<<<<<<<
* cdef char *resultp
*
*/
__pyx_t_1 = __pyx_v_view->itemsize;
__pyx_v_itemsize = __pyx_t_1;
/* "View.MemoryView":902
* cdef char *resultp
*
* if view.ndim == 0: # <<<<<<<<<<<<<<
* shape = view.len / itemsize
* stride = itemsize
*/
__pyx_t_2 = ((__pyx_v_view->ndim == 0) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":903
*
* if view.ndim == 0:
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* else:
*/
if (unlikely(__pyx_v_itemsize == 0)) {
PyErr_SetString(PyExc_ZeroDivisionError, "integer division or modulo by zero");
__PYX_ERR(1, 903, __pyx_L1_error)
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PyErr_SetString(PyExc_OverflowError, "value too large to perform division");
__PYX_ERR(1, 903, __pyx_L1_error)
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/* "View.MemoryView":904
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* stride = itemsize # <<<<<<<<<<<<<<
* else:
* shape = view.shape[dim]
*/
__pyx_v_stride = __pyx_v_itemsize;
/* "View.MemoryView":902
* cdef char *resultp
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* if view.ndim == 0: # <<<<<<<<<<<<<<
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*/
goto __pyx_L3;
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/* "View.MemoryView":906
* stride = itemsize
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*/
/*else*/ {
__pyx_v_shape = (__pyx_v_view->shape[__pyx_v_dim]);
/* "View.MemoryView":907
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*/
__pyx_v_stride = (__pyx_v_view->strides[__pyx_v_dim]);
/* "View.MemoryView":908
* shape = view.shape[dim]
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* if view.suboffsets != NULL: # <<<<<<<<<<<<<<
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*
*/
__pyx_t_2 = ((__pyx_v_view->suboffsets != NULL) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":909
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Py_ssize_t __pyx_r;
int __pyx_t_1;
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/* "View.MemoryView":1093
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/* "View.MemoryView":1092
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/* "View.MemoryView":1099
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__pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0);
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/* "View.MemoryView":1109
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*/
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* for i in range(ndim):
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goto __pyx_L4_break;
/* "View.MemoryView":1108
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}
}
__pyx_L4_break:;
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__pyx_v_i = __pyx_t_3;
/* "View.MemoryView":1113
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__pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0);
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/* "View.MemoryView":1114
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goto __pyx_L7_break;
/* "View.MemoryView":1113
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__pyx_L7_break:;
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/* "View.MemoryView":1099
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/* "View.MemoryView":1123
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* char *dst_data, Py_ssize_t *dst_strides,
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CYTHON_UNUSED Py_ssize_t __pyx_v_i;
CYTHON_UNUSED Py_ssize_t __pyx_v_src_extent;
Py_ssize_t __pyx_v_dst_extent;
Py_ssize_t __pyx_v_src_stride;
Py_ssize_t __pyx_v_dst_stride;
int __pyx_t_1;
int __pyx_t_2;
int __pyx_t_3;
Py_ssize_t __pyx_t_4;
Py_ssize_t __pyx_t_5;
/* "View.MemoryView":1130
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/* "View.MemoryView":1131
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/* "View.MemoryView":1132
* cdef Py_ssize_t src_extent = src_shape[0]
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__pyx_v_src_stride = (__pyx_v_src_strides[0]);
/* "View.MemoryView":1133
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/* "View.MemoryView":1135
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if (__pyx_t_1) {
/* "View.MemoryView":1136
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__pyx_t_2 = ((__pyx_v_src_stride > 0) != 0);
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__pyx_t_1 = __pyx_t_2;
goto __pyx_L5_bool_binop_done;
}
__pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0);
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} else {
__pyx_t_1 = __pyx_t_2;
goto __pyx_L5_bool_binop_done;
}
/* "View.MemoryView":1137
* if ndim == 1:
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/* "View.MemoryView":1136
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/* "View.MemoryView":1138
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memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent));
/* "View.MemoryView":1136
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goto __pyx_L4;
}
/* "View.MemoryView":1140
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memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize);
/* "View.MemoryView":1142
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/* "View.MemoryView":1143
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* else:
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__pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride);
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__pyx_L4:;
/* "View.MemoryView":1135
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goto __pyx_L3;
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/* "View.MemoryView":1145
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__pyx_v_i = __pyx_t_5;
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* src_shape + 1, dst_shape + 1,
*/
_copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize);
/* "View.MemoryView":1150
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*
*/
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/* "View.MemoryView":1151
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*/
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__pyx_L3:;
/* "View.MemoryView":1123
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/* function exit code */
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/* "View.MemoryView":1156
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*/
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/* "View.MemoryView":1153
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/* function exit code */
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/* "View.MemoryView":1160
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int __pyx_v_i;
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Py_ssize_t __pyx_r;
Py_ssize_t __pyx_t_1;
int __pyx_t_2;
int __pyx_t_3;
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/* "View.MemoryView":1165
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/* "View.MemoryView":1166
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/* "View.MemoryView":1180
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__pyx_t_6 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_6 == NULL)) __PYX_ERR(1, 1291, __pyx_L1_error)
__pyx_v_tmpdata = __pyx_t_6;
/* "View.MemoryView":1292
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* tmpdata = copy_data_to_temp(&src, &tmp, order, ndim)
* src = tmp # <<<<<<<<<<<<<<
*
* if not broadcasting:
*/
__pyx_v_src = __pyx_v_tmp;
/* "View.MemoryView":1286
* _err_dim(ValueError, "Dimension %d is not direct", i)
*
* if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<<
*
* if not slice_is_contig(src, order, ndim):
*/
}
/* "View.MemoryView":1294
* src = tmp
*
* if not broadcasting: # <<<<<<<<<<<<<<
*
*
*/
__pyx_t_2 = ((!(__pyx_v_broadcasting != 0)) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":1297
*
*
* if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<<
* direct_copy = slice_is_contig(dst, 'C', ndim)
* elif slice_is_contig(src, 'F', ndim):
*/
__pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, 'C', __pyx_v_ndim) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":1298
*
* if slice_is_contig(src, 'C', ndim):
* direct_copy = slice_is_contig(dst, 'C', ndim) # <<<<<<<<<<<<<<
* elif slice_is_contig(src, 'F', ndim):
* direct_copy = slice_is_contig(dst, 'F', ndim)
*/
__pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'C', __pyx_v_ndim);
/* "View.MemoryView":1297
*
*
* if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<<
* direct_copy = slice_is_contig(dst, 'C', ndim)
* elif slice_is_contig(src, 'F', ndim):
*/
goto __pyx_L12;
}
/* "View.MemoryView":1299
* if slice_is_contig(src, 'C', ndim):
* direct_copy = slice_is_contig(dst, 'C', ndim)
* elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<<
* direct_copy = slice_is_contig(dst, 'F', ndim)
*
*/
__pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, 'F', __pyx_v_ndim) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":1300
* direct_copy = slice_is_contig(dst, 'C', ndim)
* elif slice_is_contig(src, 'F', ndim):
* direct_copy = slice_is_contig(dst, 'F', ndim) # <<<<<<<<<<<<<<
*
* if direct_copy:
*/
__pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'F', __pyx_v_ndim);
/* "View.MemoryView":1299
* if slice_is_contig(src, 'C', ndim):
* direct_copy = slice_is_contig(dst, 'C', ndim)
* elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<<
* direct_copy = slice_is_contig(dst, 'F', ndim)
*
*/
}
__pyx_L12:;
/* "View.MemoryView":1302
* direct_copy = slice_is_contig(dst, 'F', ndim)
*
* if direct_copy: # <<<<<<<<<<<<<<
*
* refcount_copying(&dst, dtype_is_object, ndim, False)
*/
__pyx_t_2 = (__pyx_v_direct_copy != 0);
if (__pyx_t_2) {
/* "View.MemoryView":1304
* if direct_copy:
*
* refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<<
* memcpy(dst.data, src.data, slice_get_size(&src, ndim))
* refcount_copying(&dst, dtype_is_object, ndim, True)
*/
__pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0);
/* "View.MemoryView":1305
*
* refcount_copying(&dst, dtype_is_object, ndim, False)
* memcpy(dst.data, src.data, slice_get_size(&src, ndim)) # <<<<<<<<<<<<<<
* refcount_copying(&dst, dtype_is_object, ndim, True)
* free(tmpdata)
*/
memcpy(__pyx_v_dst.data, __pyx_v_src.data, __pyx_memoryview_slice_get_size((&__pyx_v_src), __pyx_v_ndim));
/* "View.MemoryView":1306
* refcount_copying(&dst, dtype_is_object, ndim, False)
* memcpy(dst.data, src.data, slice_get_size(&src, ndim))
* refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<<
* free(tmpdata)
* return 0
*/
__pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1);
/* "View.MemoryView":1307
* memcpy(dst.data, src.data, slice_get_size(&src, ndim))
* refcount_copying(&dst, dtype_is_object, ndim, True)
* free(tmpdata) # <<<<<<<<<<<<<<
* return 0
*
*/
free(__pyx_v_tmpdata);
/* "View.MemoryView":1308
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* free(tmpdata)
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* if order == 'F' == get_best_order(&dst, ndim):
*/
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/* "View.MemoryView":1302
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*
* if direct_copy: # <<<<<<<<<<<<<<
*
* refcount_copying(&dst, dtype_is_object, ndim, False)
*/
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/* "View.MemoryView":1294
* src = tmp
*
* if not broadcasting: # <<<<<<<<<<<<<<
*
*
*/
}
/* "View.MemoryView":1310
* return 0
*
* if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<<
*
*
*/
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if (__pyx_t_2) {
__pyx_t_2 = ('F' == __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim));
}
__pyx_t_7 = (__pyx_t_2 != 0);
if (__pyx_t_7) {
/* "View.MemoryView":1313
*
*
* transpose_memslice(&src) # <<<<<<<<<<<<<<
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*/
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/* "View.MemoryView":1314
*
* transpose_memslice(&src)
* transpose_memslice(&dst) # <<<<<<<<<<<<<<
*
* refcount_copying(&dst, dtype_is_object, ndim, False)
*/
__pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_dst)); if (unlikely(__pyx_t_5 == 0)) __PYX_ERR(1, 1314, __pyx_L1_error)
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*
* if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<<
*
*
*/
}
/* "View.MemoryView":1316
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*
* refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<<
* copy_strided_to_strided(&src, &dst, ndim, itemsize)
* refcount_copying(&dst, dtype_is_object, ndim, True)
*/
__pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0);
/* "View.MemoryView":1317
*
* refcount_copying(&dst, dtype_is_object, ndim, False)
* copy_strided_to_strided(&src, &dst, ndim, itemsize) # <<<<<<<<<<<<<<
* refcount_copying(&dst, dtype_is_object, ndim, True)
*
*/
copy_strided_to_strided((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize);
/* "View.MemoryView":1318
* refcount_copying(&dst, dtype_is_object, ndim, False)
* copy_strided_to_strided(&src, &dst, ndim, itemsize)
* refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<<
*
* free(tmpdata)
*/
__pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1);
/* "View.MemoryView":1320
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*
* free(tmpdata) # <<<<<<<<<<<<<<
* return 0
*
*/
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/* "View.MemoryView":1321
*
* free(tmpdata)
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*/
__pyx_r = 0;
goto __pyx_L0;
/* "View.MemoryView":1252
*
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/* function exit code */
__pyx_L1_error:;
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/* "View.MemoryView":1324
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* int ndim,
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static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim, int __pyx_v_ndim_other) {
int __pyx_v_i;
int __pyx_v_offset;
int __pyx_t_1;
int __pyx_t_2;
/* "View.MemoryView":1328
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/* "View.MemoryView":1330
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*
* for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<<
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for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1L; __pyx_t_1-=1) {
__pyx_v_i = __pyx_t_1;
/* "View.MemoryView":1331
*
* for i in range(ndim - 1, -1, -1):
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(__pyx_v_mslice->shape[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->shape[__pyx_v_i]);
/* "View.MemoryView":1332
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*/
(__pyx_v_mslice->strides[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->strides[__pyx_v_i]);
/* "View.MemoryView":1333
* mslice.shape[i + offset] = mslice.shape[i]
* mslice.strides[i + offset] = mslice.strides[i]
* mslice.suboffsets[i + offset] = mslice.suboffsets[i] # <<<<<<<<<<<<<<
*
* for i in range(offset):
*/
(__pyx_v_mslice->suboffsets[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->suboffsets[__pyx_v_i]);
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/* "View.MemoryView":1335
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*
* for i in range(offset): # <<<<<<<<<<<<<<
* mslice.shape[i] = 1
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*/
__pyx_t_1 = __pyx_v_offset;
for (__pyx_t_2 = 0; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) {
__pyx_v_i = __pyx_t_2;
/* "View.MemoryView":1336
*
* for i in range(offset):
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* mslice.suboffsets[i] = -1
*/
(__pyx_v_mslice->shape[__pyx_v_i]) = 1;
/* "View.MemoryView":1337
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*/
(__pyx_v_mslice->strides[__pyx_v_i]) = (__pyx_v_mslice->strides[0]);
/* "View.MemoryView":1338
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*
*/
(__pyx_v_mslice->suboffsets[__pyx_v_i]) = -1L;
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/* "View.MemoryView":1324
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* @cname('__pyx_memoryview_broadcast_leading')
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/* function exit code */
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/* "View.MemoryView":1346
*
* @cname('__pyx_memoryview_refcount_copying')
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int __pyx_t_1;
/* "View.MemoryView":1350
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*
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/* "View.MemoryView":1351
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*/
__pyx_memoryview_refcount_objects_in_slice_with_gil(__pyx_v_dst->data, __pyx_v_dst->shape, __pyx_v_dst->strides, __pyx_v_ndim, __pyx_v_inc);
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*
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/* "View.MemoryView":1346
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/* "View.MemoryView":1355
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* @cname('__pyx_memoryview_refcount_objects_in_slice_with_gil')
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static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *__pyx_v_data, Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, int __pyx_v_ndim, int __pyx_v_inc) {
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__pyx_memoryview_refcount_objects_in_slice(__pyx_v_data, __pyx_v_shape, __pyx_v_strides, __pyx_v_ndim, __pyx_v_inc);
/* "View.MemoryView":1355
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Py_INCREF((((PyObject **)__pyx_v_data)[0]));
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__pyx_memoryview_refcount_objects_in_slice(__pyx_v_data, (__pyx_v_shape + 1), (__pyx_v_strides + 1), (__pyx_v_ndim - 1), __pyx_v_inc);
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/* "View.MemoryView":1361
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/* "View.MemoryView":1381
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static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item, int __pyx_v_dtype_is_object) {
/* "View.MemoryView":1384
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__pyx_memoryview_refcount_copying(__pyx_v_dst, __pyx_v_dtype_is_object, __pyx_v_ndim, 0);
/* "View.MemoryView":1385
* bint dtype_is_object) nogil:
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*/
__pyx_memoryview__slice_assign_scalar(__pyx_v_dst->data, __pyx_v_dst->shape, __pyx_v_dst->strides, __pyx_v_ndim, __pyx_v_itemsize, __pyx_v_item);
/* "View.MemoryView":1387
* _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim,
* itemsize, item)
* refcount_copying(dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<<
*
*
*/
__pyx_memoryview_refcount_copying(__pyx_v_dst, __pyx_v_dtype_is_object, __pyx_v_ndim, 1);
/* "View.MemoryView":1381
*
* @cname('__pyx_memoryview_slice_assign_scalar')
* cdef void slice_assign_scalar(__Pyx_memviewslice *dst, int ndim, # <<<<<<<<<<<<<<
* size_t itemsize, void *item,
* bint dtype_is_object) nogil:
*/
/* function exit code */
}
/* "View.MemoryView":1391
*
* @cname('__pyx_memoryview__slice_assign_scalar')
* cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<<
* Py_ssize_t *strides, int ndim,
* size_t itemsize, void *item) nogil:
*/
static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, int __pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item) {
CYTHON_UNUSED Py_ssize_t __pyx_v_i;
Py_ssize_t __pyx_v_stride;
Py_ssize_t __pyx_v_extent;
int __pyx_t_1;
Py_ssize_t __pyx_t_2;
Py_ssize_t __pyx_t_3;
/* "View.MemoryView":1395
* size_t itemsize, void *item) nogil:
* cdef Py_ssize_t i
* cdef Py_ssize_t stride = strides[0] # <<<<<<<<<<<<<<
* cdef Py_ssize_t extent = shape[0]
*
*/
__pyx_v_stride = (__pyx_v_strides[0]);
/* "View.MemoryView":1396
* cdef Py_ssize_t i
* cdef Py_ssize_t stride = strides[0]
* cdef Py_ssize_t extent = shape[0] # <<<<<<<<<<<<<<
*
* if ndim == 1:
*/
__pyx_v_extent = (__pyx_v_shape[0]);
/* "View.MemoryView":1398
* cdef Py_ssize_t extent = shape[0]
*
* if ndim == 1: # <<<<<<<<<<<<<<
* for i in range(extent):
* memcpy(data, item, itemsize)
*/
__pyx_t_1 = ((__pyx_v_ndim == 1) != 0);
if (__pyx_t_1) {
/* "View.MemoryView":1399
*
* if ndim == 1:
* for i in range(extent): # <<<<<<<<<<<<<<
* memcpy(data, item, itemsize)
* data += stride
*/
__pyx_t_2 = __pyx_v_extent;
for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
__pyx_v_i = __pyx_t_3;
/* "View.MemoryView":1400
* if ndim == 1:
* for i in range(extent):
* memcpy(data, item, itemsize) # <<<<<<<<<<<<<<
* data += stride
* else:
*/
memcpy(__pyx_v_data, __pyx_v_item, __pyx_v_itemsize);
/* "View.MemoryView":1401
* for i in range(extent):
* memcpy(data, item, itemsize)
* data += stride # <<<<<<<<<<<<<<
* else:
* for i in range(extent):
*/
__pyx_v_data = (__pyx_v_data + __pyx_v_stride);
}
/* "View.MemoryView":1398
* cdef Py_ssize_t extent = shape[0]
*
* if ndim == 1: # <<<<<<<<<<<<<<
* for i in range(extent):
* memcpy(data, item, itemsize)
*/
goto __pyx_L3;
}
/* "View.MemoryView":1403
* data += stride
* else:
* for i in range(extent): # <<<<<<<<<<<<<<
* _slice_assign_scalar(data, shape + 1, strides + 1,
* ndim - 1, itemsize, item)
*/
/*else*/ {
__pyx_t_2 = __pyx_v_extent;
for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
__pyx_v_i = __pyx_t_3;
/* "View.MemoryView":1404
* else:
* for i in range(extent):
* _slice_assign_scalar(data, shape + 1, strides + 1, # <<<<<<<<<<<<<<
* ndim - 1, itemsize, item)
* data += stride
*/
__pyx_memoryview__slice_assign_scalar(__pyx_v_data, (__pyx_v_shape + 1), (__pyx_v_strides + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize, __pyx_v_item);
/* "View.MemoryView":1406
* _slice_assign_scalar(data, shape + 1, strides + 1,
* ndim - 1, itemsize, item)
* data += stride # <<<<<<<<<<<<<<
*
*
*/
__pyx_v_data = (__pyx_v_data + __pyx_v_stride);
}
}
__pyx_L3:;
/* "View.MemoryView":1391
*
* @cname('__pyx_memoryview__slice_assign_scalar')
* cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<<
* Py_ssize_t *strides, int ndim,
* size_t itemsize, void *item) nogil:
*/
/* function exit code */
}
static struct __pyx_vtabstruct_array __pyx_vtable_array;
static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_array_obj *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_array_obj *)o);
p->__pyx_vtab = __pyx_vtabptr_array;
p->mode = ((PyObject*)Py_None); Py_INCREF(Py_None);
p->_format = ((PyObject*)Py_None); Py_INCREF(Py_None);
if (unlikely(__pyx_array___cinit__(o, a, k) < 0)) goto bad;
return o;
bad:
Py_DECREF(o); o = 0;
return NULL;
}
static void __pyx_tp_dealloc_array(PyObject *o) {
struct __pyx_array_obj *p = (struct __pyx_array_obj *)o;
#if PY_VERSION_HEX >= 0x030400a1
if (unlikely(Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
{
PyObject *etype, *eval, *etb;
PyErr_Fetch(&etype, &eval, &etb);
++Py_REFCNT(o);
__pyx_array___dealloc__(o);
--Py_REFCNT(o);
PyErr_Restore(etype, eval, etb);
}
Py_CLEAR(p->mode);
Py_CLEAR(p->_format);
(*Py_TYPE(o)->tp_free)(o);
}
static PyObject *__pyx_sq_item_array(PyObject *o, Py_ssize_t i) {
PyObject *r;
PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0;
r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x);
Py_DECREF(x);
return r;
}
static int __pyx_mp_ass_subscript_array(PyObject *o, PyObject *i, PyObject *v) {
if (v) {
return __pyx_array___setitem__(o, i, v);
}
else {
PyErr_Format(PyExc_NotImplementedError,
"Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name);
return -1;
}
}
static PyObject *__pyx_tp_getattro_array(PyObject *o, PyObject *n) {
PyObject *v = PyObject_GenericGetAttr(o, n);
if (!v && PyErr_ExceptionMatches(PyExc_AttributeError)) {
PyErr_Clear();
v = __pyx_array___getattr__(o, n);
}
return v;
}
static PyObject *__pyx_getprop___pyx_array_memview(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_5array_7memview_1__get__(o);
}
static PyMethodDef __pyx_methods_array[] = {
{"__getattr__", (PyCFunction)__pyx_array___getattr__, METH_O|METH_COEXIST, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_array[] = {
{(char *)"memview", __pyx_getprop___pyx_array_memview, 0, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PySequenceMethods __pyx_tp_as_sequence_array = {
0, /*sq_length*/
0, /*sq_concat*/
0, /*sq_repeat*/
__pyx_sq_item_array, /*sq_item*/
0, /*sq_slice*/
0, /*sq_ass_item*/
0, /*sq_ass_slice*/
0, /*sq_contains*/
0, /*sq_inplace_concat*/
0, /*sq_inplace_repeat*/
};
static PyMappingMethods __pyx_tp_as_mapping_array = {
0, /*mp_length*/
__pyx_array___getitem__, /*mp_subscript*/
__pyx_mp_ass_subscript_array, /*mp_ass_subscript*/
};
static PyBufferProcs __pyx_tp_as_buffer_array = {
#if PY_MAJOR_VERSION < 3
0, /*bf_getreadbuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getwritebuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getsegcount*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getcharbuffer*/
#endif
__pyx_array_getbuffer, /*bf_getbuffer*/
0, /*bf_releasebuffer*/
};
static PyTypeObject __pyx_type___pyx_array = {
PyVarObject_HEAD_INIT(0, 0)
"pairwise3.array", /*tp_name*/
sizeof(struct __pyx_array_obj), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_array, /*tp_dealloc*/
0, /*tp_print*/
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
&__pyx_tp_as_sequence_array, /*tp_as_sequence*/
&__pyx_tp_as_mapping_array, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
__pyx_tp_getattro_array, /*tp_getattro*/
0, /*tp_setattro*/
&__pyx_tp_as_buffer_array, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
0, /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_array, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_array, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_array, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
};
static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_MemviewEnum_obj *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_MemviewEnum_obj *)o);
p->name = Py_None; Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_Enum(PyObject *o) {
struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
#if PY_VERSION_HEX >= 0x030400a1
if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->name);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_Enum(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
if (p->name) {
e = (*v)(p->name, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_Enum(PyObject *o) {
PyObject* tmp;
struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
tmp = ((PyObject*)p->name);
p->name = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyMethodDef __pyx_methods_Enum[] = {
{0, 0, 0, 0}
};
static PyTypeObject __pyx_type___pyx_MemviewEnum = {
PyVarObject_HEAD_INIT(0, 0)
"pairwise3.Enum", /*tp_name*/
sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_Enum, /*tp_dealloc*/
0, /*tp_print*/
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
__pyx_MemviewEnum___repr__, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_Enum, /*tp_traverse*/
__pyx_tp_clear_Enum, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_Enum, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
__pyx_MemviewEnum___init__, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_Enum, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
};
static struct __pyx_vtabstruct_memoryview __pyx_vtable_memoryview;
static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_memoryview_obj *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_memoryview_obj *)o);
p->__pyx_vtab = __pyx_vtabptr_memoryview;
p->obj = Py_None; Py_INCREF(Py_None);
p->_size = Py_None; Py_INCREF(Py_None);
p->_array_interface = Py_None; Py_INCREF(Py_None);
p->view.obj = NULL;
if (unlikely(__pyx_memoryview___cinit__(o, a, k) < 0)) goto bad;
return o;
bad:
Py_DECREF(o); o = 0;
return NULL;
}
static void __pyx_tp_dealloc_memoryview(PyObject *o) {
struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
#if PY_VERSION_HEX >= 0x030400a1
if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
{
PyObject *etype, *eval, *etb;
PyErr_Fetch(&etype, &eval, &etb);
++Py_REFCNT(o);
__pyx_memoryview___dealloc__(o);
--Py_REFCNT(o);
PyErr_Restore(etype, eval, etb);
}
Py_CLEAR(p->obj);
Py_CLEAR(p->_size);
Py_CLEAR(p->_array_interface);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_memoryview(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
if (p->obj) {
e = (*v)(p->obj, a); if (e) return e;
}
if (p->_size) {
e = (*v)(p->_size, a); if (e) return e;
}
if (p->_array_interface) {
e = (*v)(p->_array_interface, a); if (e) return e;
}
if (p->view.obj) {
e = (*v)(p->view.obj, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_memoryview(PyObject *o) {
PyObject* tmp;
struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
tmp = ((PyObject*)p->obj);
p->obj = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
tmp = ((PyObject*)p->_size);
p->_size = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
tmp = ((PyObject*)p->_array_interface);
p->_array_interface = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
Py_CLEAR(p->view.obj);
return 0;
}
static PyObject *__pyx_sq_item_memoryview(PyObject *o, Py_ssize_t i) {
PyObject *r;
PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0;
r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x);
Py_DECREF(x);
return r;
}
static int __pyx_mp_ass_subscript_memoryview(PyObject *o, PyObject *i, PyObject *v) {
if (v) {
return __pyx_memoryview___setitem__(o, i, v);
}
else {
PyErr_Format(PyExc_NotImplementedError,
"Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name);
return -1;
}
}
static PyObject *__pyx_getprop___pyx_memoryview_T(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_10memoryview_1T_1__get__(o);
}
static PyObject *__pyx_getprop___pyx_memoryview_base(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_10memoryview_4base_1__get__(o);
}
static PyObject *__pyx_getprop___pyx_memoryview_shape(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_10memoryview_5shape_1__get__(o);
}
static PyObject *__pyx_getprop___pyx_memoryview_strides(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_10memoryview_7strides_1__get__(o);
}
static PyObject *__pyx_getprop___pyx_memoryview_suboffsets(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_10memoryview_10suboffsets_1__get__(o);
}
static PyObject *__pyx_getprop___pyx_memoryview_ndim(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_10memoryview_4ndim_1__get__(o);
}
static PyObject *__pyx_getprop___pyx_memoryview_itemsize(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_10memoryview_8itemsize_1__get__(o);
}
static PyObject *__pyx_getprop___pyx_memoryview_nbytes(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_10memoryview_6nbytes_1__get__(o);
}
static PyObject *__pyx_getprop___pyx_memoryview_size(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_10memoryview_4size_1__get__(o);
}
static PyMethodDef __pyx_methods_memoryview[] = {
{"is_c_contig", (PyCFunction)__pyx_memoryview_is_c_contig, METH_NOARGS, 0},
{"is_f_contig", (PyCFunction)__pyx_memoryview_is_f_contig, METH_NOARGS, 0},
{"copy", (PyCFunction)__pyx_memoryview_copy, METH_NOARGS, 0},
{"copy_fortran", (PyCFunction)__pyx_memoryview_copy_fortran, METH_NOARGS, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_memoryview[] = {
{(char *)"T", __pyx_getprop___pyx_memoryview_T, 0, (char *)0, 0},
{(char *)"base", __pyx_getprop___pyx_memoryview_base, 0, (char *)0, 0},
{(char *)"shape", __pyx_getprop___pyx_memoryview_shape, 0, (char *)0, 0},
{(char *)"strides", __pyx_getprop___pyx_memoryview_strides, 0, (char *)0, 0},
{(char *)"suboffsets", __pyx_getprop___pyx_memoryview_suboffsets, 0, (char *)0, 0},
{(char *)"ndim", __pyx_getprop___pyx_memoryview_ndim, 0, (char *)0, 0},
{(char *)"itemsize", __pyx_getprop___pyx_memoryview_itemsize, 0, (char *)0, 0},
{(char *)"nbytes", __pyx_getprop___pyx_memoryview_nbytes, 0, (char *)0, 0},
{(char *)"size", __pyx_getprop___pyx_memoryview_size, 0, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PySequenceMethods __pyx_tp_as_sequence_memoryview = {
__pyx_memoryview___len__, /*sq_length*/
0, /*sq_concat*/
0, /*sq_repeat*/
__pyx_sq_item_memoryview, /*sq_item*/
0, /*sq_slice*/
0, /*sq_ass_item*/
0, /*sq_ass_slice*/
0, /*sq_contains*/
0, /*sq_inplace_concat*/
0, /*sq_inplace_repeat*/
};
static PyMappingMethods __pyx_tp_as_mapping_memoryview = {
__pyx_memoryview___len__, /*mp_length*/
__pyx_memoryview___getitem__, /*mp_subscript*/
__pyx_mp_ass_subscript_memoryview, /*mp_ass_subscript*/
};
static PyBufferProcs __pyx_tp_as_buffer_memoryview = {
#if PY_MAJOR_VERSION < 3
0, /*bf_getreadbuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getwritebuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getsegcount*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getcharbuffer*/
#endif
__pyx_memoryview_getbuffer, /*bf_getbuffer*/
0, /*bf_releasebuffer*/
};
static PyTypeObject __pyx_type___pyx_memoryview = {
PyVarObject_HEAD_INIT(0, 0)
"pairwise3.memoryview", /*tp_name*/
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struct __pyx_memoryviewslice_obj *p;
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p->from_object = Py_None; Py_INCREF(Py_None);
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return o;
}
static void __pyx_tp_dealloc__memoryviewslice(PyObject *o) {
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PyErr_Restore(etype, eval, etb);
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PyObject_GC_Track(o);
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Py_XDECREF(tmp);
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return 0;
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*
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*
*
*/
__pyx_t_1 = __pyx_capsule_create(((void *)(&__pyx_memoryview_getbuffer)), ((char *)"getbuffer(obj, view, flags)")); if (unlikely(!__pyx_t_1)) __PYX_ERR(1, 981, __pyx_L1_error)
__Pyx_GOTREF(__pyx_t_1);
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/* "View.MemoryView":1391
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* Py_ssize_t *strides, int ndim,
* size_t itemsize, void *item) nogil:
*/
/*--- Wrapped vars code ---*/
goto __pyx_L0;
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if (__pyx_m) {
if (__pyx_d) {
__Pyx_AddTraceback("init pairwise3", __pyx_clineno, __pyx_lineno, __pyx_filename);
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Py_DECREF(__pyx_m); __pyx_m = 0;
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PyErr_SetString(PyExc_ImportError, "init pairwise3");
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__pyx_L0:;
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return;
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/* --- Runtime support code --- */
/* Refnanny */
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static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname) {
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void *r = NULL;
m = PyImport_ImportModule((char *)modname);
if (!m) goto end;
p = PyObject_GetAttrString(m, (char *)"RefNannyAPI");
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Py_XDECREF(m);
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/* GetBuiltinName */
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PyObject* result = __Pyx_PyObject_GetAttrStr(__pyx_b, name);
if (unlikely(!result)) {
PyErr_Format(PyExc_NameError,
#if PY_MAJOR_VERSION >= 3
"name '%U' is not defined", name);
#else
"name '%.200s' is not defined", PyString_AS_STRING(name));
#endif
}
return result;
}
/* GetModuleGlobalName */
static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name) {
PyObject *result;
#if !CYTHON_AVOID_BORROWED_REFS
result = PyDict_GetItem(__pyx_d, name);
if (likely(result)) {
Py_INCREF(result);
} else {
#else
result = PyObject_GetItem(__pyx_d, name);
if (!result) {
PyErr_Clear();
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result = __Pyx_GetBuiltinName(name);
}
return result;
}
/* PyObjectCall */
#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) {
PyObject *result;
ternaryfunc call = func->ob_type->tp_call;
if (unlikely(!call))
return PyObject_Call(func, arg, kw);
if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object")))
return NULL;
result = (*call)(func, arg, kw);
Py_LeaveRecursiveCall();
if (unlikely(!result) && unlikely(!PyErr_Occurred())) {
PyErr_SetString(
PyExc_SystemError,
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return result;
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/* BufferFormatCheck */
static CYTHON_INLINE int __Pyx_IsLittleEndian(void) {
unsigned int n = 1;
return *(unsigned char*)(&n) != 0;
}
static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx,
__Pyx_BufFmt_StackElem* stack,
__Pyx_TypeInfo* type) {
stack[0].field = &ctx->root;
stack[0].parent_offset = 0;
ctx->root.type = type;
ctx->root.name = "buffer dtype";
ctx->root.offset = 0;
ctx->head = stack;
ctx->head->field = &ctx->root;
ctx->fmt_offset = 0;
ctx->head->parent_offset = 0;
ctx->new_packmode = '@';
ctx->enc_packmode = '@';
ctx->new_count = 1;
ctx->enc_count = 0;
ctx->enc_type = 0;
ctx->is_complex = 0;
ctx->is_valid_array = 0;
ctx->struct_alignment = 0;
while (type->typegroup == 'S') {
++ctx->head;
ctx->head->field = type->fields;
ctx->head->parent_offset = 0;
type = type->fields->type;
}
}
static int __Pyx_BufFmt_ParseNumber(const char** ts) {
int count;
const char* t = *ts;
if (*t < '0' || *t > '9') {
return -1;
} else {
count = *t++ - '0';
while (*t >= '0' && *t < '9') {
count *= 10;
count += *t++ - '0';
}
}
*ts = t;
return count;
}
static int __Pyx_BufFmt_ExpectNumber(const char **ts) {
int number = __Pyx_BufFmt_ParseNumber(ts);
if (number == -1)
PyErr_Format(PyExc_ValueError,\
"Does not understand character buffer dtype format string ('%c')", **ts);
return number;
}
static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) {
PyErr_Format(PyExc_ValueError,
"Unexpected format string character: '%c'", ch);
}
static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) {
switch (ch) {
case 'c': return "'char'";
case 'b': return "'signed char'";
case 'B': return "'unsigned char'";
case 'h': return "'short'";
case 'H': return "'unsigned short'";
case 'i': return "'int'";
case 'I': return "'unsigned int'";
case 'l': return "'long'";
case 'L': return "'unsigned long'";
case 'q': return "'long long'";
case 'Q': return "'unsigned long long'";
case 'f': return (is_complex ? "'complex float'" : "'float'");
case 'd': return (is_complex ? "'complex double'" : "'double'");
case 'g': return (is_complex ? "'complex long double'" : "'long double'");
case 'T': return "a struct";
case 'O': return "Python object";
case 'P': return "a pointer";
case 's': case 'p': return "a string";
case 0: return "end";
default: return "unparseable format string";
}
}
static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) {
switch (ch) {
case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
case 'h': case 'H': return 2;
case 'i': case 'I': case 'l': case 'L': return 4;
case 'q': case 'Q': return 8;
case 'f': return (is_complex ? 8 : 4);
case 'd': return (is_complex ? 16 : 8);
case 'g': {
PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g')..");
return 0;
}
case 'O': case 'P': return sizeof(void*);
default:
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) {
switch (ch) {
case 'c': case 'b': case 'B': case 's': case 'p': return 1;
case 'h': case 'H': return sizeof(short);
case 'i': case 'I': return sizeof(int);
case 'l': case 'L': return sizeof(long);
#ifdef HAVE_LONG_LONG
case 'q': case 'Q': return sizeof(PY_LONG_LONG);
#endif
case 'f': return sizeof(float) * (is_complex ? 2 : 1);
case 'd': return sizeof(double) * (is_complex ? 2 : 1);
case 'g': return sizeof(long double) * (is_complex ? 2 : 1);
case 'O': case 'P': return sizeof(void*);
default: {
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
}
typedef struct { char c; short x; } __Pyx_st_short;
typedef struct { char c; int x; } __Pyx_st_int;
typedef struct { char c; long x; } __Pyx_st_long;
typedef struct { char c; float x; } __Pyx_st_float;
typedef struct { char c; double x; } __Pyx_st_double;
typedef struct { char c; long double x; } __Pyx_st_longdouble;
typedef struct { char c; void *x; } __Pyx_st_void_p;
#ifdef HAVE_LONG_LONG
typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong;
#endif
static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) {
switch (ch) {
case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short);
case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int);
case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long);
#ifdef HAVE_LONG_LONG
case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG);
#endif
case 'f': return sizeof(__Pyx_st_float) - sizeof(float);
case 'd': return sizeof(__Pyx_st_double) - sizeof(double);
case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double);
case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*);
default:
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
/* These are for computing the padding at the end of the struct to align
on the first member of the struct. This will probably the same as above,
but we don't have any guarantees.
*/
typedef struct { short x; char c; } __Pyx_pad_short;
typedef struct { int x; char c; } __Pyx_pad_int;
typedef struct { long x; char c; } __Pyx_pad_long;
typedef struct { float x; char c; } __Pyx_pad_float;
typedef struct { double x; char c; } __Pyx_pad_double;
typedef struct { long double x; char c; } __Pyx_pad_longdouble;
typedef struct { void *x; char c; } __Pyx_pad_void_p;
#ifdef HAVE_LONG_LONG
typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong;
#endif
static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) {
switch (ch) {
case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short);
case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int);
case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long);
#ifdef HAVE_LONG_LONG
case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG);
#endif
case 'f': return sizeof(__Pyx_pad_float) - sizeof(float);
case 'd': return sizeof(__Pyx_pad_double) - sizeof(double);
case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double);
case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*);
default:
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) {
switch (ch) {
case 'c':
return 'H';
case 'b': case 'h': case 'i':
case 'l': case 'q': case 's': case 'p':
return 'I';
case 'B': case 'H': case 'I': case 'L': case 'Q':
return 'U';
case 'f': case 'd': case 'g':
return (is_complex ? 'C' : 'R');
case 'O':
return 'O';
case 'P':
return 'P';
default: {
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
}
static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) {
if (ctx->head == NULL || ctx->head->field == &ctx->root) {
const char* expected;
const char* quote;
if (ctx->head == NULL) {
expected = "end";
quote = "";
} else {
expected = ctx->head->field->type->name;
quote = "'";
}
PyErr_Format(PyExc_ValueError,
"Buffer dtype mismatch, expected %s%s%s but got %s",
quote, expected, quote,
__Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex));
} else {
__Pyx_StructField* field = ctx->head->field;
__Pyx_StructField* parent = (ctx->head - 1)->field;
PyErr_Format(PyExc_ValueError,
"Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'",
field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex),
parent->type->name, field->name);
}
}
static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) {
char group;
size_t size, offset, arraysize = 1;
if (ctx->enc_type == 0) return 0;
if (ctx->head->field->type->arraysize[0]) {
int i, ndim = 0;
if (ctx->enc_type == 's' || ctx->enc_type == 'p') {
ctx->is_valid_array = ctx->head->field->type->ndim == 1;
ndim = 1;
if (ctx->enc_count != ctx->head->field->type->arraysize[0]) {
PyErr_Format(PyExc_ValueError,
"Expected a dimension of size %zu, got %zu",
ctx->head->field->type->arraysize[0], ctx->enc_count);
return -1;
}
}
if (!ctx->is_valid_array) {
PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d",
ctx->head->field->type->ndim, ndim);
return -1;
}
for (i = 0; i < ctx->head->field->type->ndim; i++) {
arraysize *= ctx->head->field->type->arraysize[i];
}
ctx->is_valid_array = 0;
ctx->enc_count = 1;
}
group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex);
do {
__Pyx_StructField* field = ctx->head->field;
__Pyx_TypeInfo* type = field->type;
if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') {
size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex);
} else {
size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex);
}
if (ctx->enc_packmode == '@') {
size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex);
size_t align_mod_offset;
if (align_at == 0) return -1;
align_mod_offset = ctx->fmt_offset % align_at;
if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset;
if (ctx->struct_alignment == 0)
ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type,
ctx->is_complex);
}
if (type->size != size || type->typegroup != group) {
if (type->typegroup == 'C' && type->fields != NULL) {
size_t parent_offset = ctx->head->parent_offset + field->offset;
++ctx->head;
ctx->head->field = type->fields;
ctx->head->parent_offset = parent_offset;
continue;
}
if ((type->typegroup == 'H' || group == 'H') && type->size == size) {
} else {
__Pyx_BufFmt_RaiseExpected(ctx);
return -1;
}
}
offset = ctx->head->parent_offset + field->offset;
if (ctx->fmt_offset != offset) {
PyErr_Format(PyExc_ValueError,
"Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected",
(Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset);
return -1;
}
ctx->fmt_offset += size;
if (arraysize)
ctx->fmt_offset += (arraysize - 1) * size;
--ctx->enc_count;
while (1) {
if (field == &ctx->root) {
ctx->head = NULL;
if (ctx->enc_count != 0) {
__Pyx_BufFmt_RaiseExpected(ctx);
return -1;
}
break;
}
ctx->head->field = ++field;
if (field->type == NULL) {
--ctx->head;
field = ctx->head->field;
continue;
} else if (field->type->typegroup == 'S') {
size_t parent_offset = ctx->head->parent_offset + field->offset;
if (field->type->fields->type == NULL) continue;
field = field->type->fields;
++ctx->head;
ctx->head->field = field;
ctx->head->parent_offset = parent_offset;
break;
} else {
break;
}
}
} while (ctx->enc_count);
ctx->enc_type = 0;
ctx->is_complex = 0;
return 0;
}
static CYTHON_INLINE PyObject *
__pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp)
{
const char *ts = *tsp;
int i = 0, number;
int ndim = ctx->head->field->type->ndim;
;
++ts;
if (ctx->new_count != 1) {
PyErr_SetString(PyExc_ValueError,
"Cannot handle repeated arrays in format string");
return NULL;
}
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
while (*ts && *ts != ')') {
switch (*ts) {
case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue;
default: break;
}
number = __Pyx_BufFmt_ExpectNumber(&ts);
if (number == -1) return NULL;
if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i])
return PyErr_Format(PyExc_ValueError,
"Expected a dimension of size %zu, got %d",
ctx->head->field->type->arraysize[i], number);
if (*ts != ',' && *ts != ')')
return PyErr_Format(PyExc_ValueError,
"Expected a comma in format string, got '%c'", *ts);
if (*ts == ',') ts++;
i++;
}
if (i != ndim)
return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d",
ctx->head->field->type->ndim, i);
if (!*ts) {
PyErr_SetString(PyExc_ValueError,
"Unexpected end of format string, expected ')'");
return NULL;
}
ctx->is_valid_array = 1;
ctx->new_count = 1;
*tsp = ++ts;
return Py_None;
}
static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) {
int got_Z = 0;
while (1) {
switch(*ts) {
case 0:
if (ctx->enc_type != 0 && ctx->head == NULL) {
__Pyx_BufFmt_RaiseExpected(ctx);
return NULL;
}
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
if (ctx->head != NULL) {
__Pyx_BufFmt_RaiseExpected(ctx);
return NULL;
}
return ts;
case ' ':
case '\r':
case '\n':
++ts;
break;
case '<':
if (!__Pyx_IsLittleEndian()) {
PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler");
return NULL;
}
ctx->new_packmode = '=';
++ts;
break;
case '>':
case '!':
if (__Pyx_IsLittleEndian()) {
PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler");
return NULL;
}
ctx->new_packmode = '=';
++ts;
break;
case '=':
case '@':
case '^':
ctx->new_packmode = *ts++;
break;
case 'T':
{
const char* ts_after_sub;
size_t i, struct_count = ctx->new_count;
size_t struct_alignment = ctx->struct_alignment;
ctx->new_count = 1;
++ts;
if (*ts != '{') {
PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'");
return NULL;
}
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
ctx->enc_type = 0;
ctx->enc_count = 0;
ctx->struct_alignment = 0;
++ts;
ts_after_sub = ts;
for (i = 0; i != struct_count; ++i) {
ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts);
if (!ts_after_sub) return NULL;
}
ts = ts_after_sub;
if (struct_alignment) ctx->struct_alignment = struct_alignment;
}
break;
case '}':
{
size_t alignment = ctx->struct_alignment;
++ts;
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
ctx->enc_type = 0;
if (alignment && ctx->fmt_offset % alignment) {
ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment);
}
}
return ts;
case 'x':
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
ctx->fmt_offset += ctx->new_count;
ctx->new_count = 1;
ctx->enc_count = 0;
ctx->enc_type = 0;
ctx->enc_packmode = ctx->new_packmode;
++ts;
break;
case 'Z':
got_Z = 1;
++ts;
if (*ts != 'f' && *ts != 'd' && *ts != 'g') {
__Pyx_BufFmt_RaiseUnexpectedChar('Z');
return NULL;
}
case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I':
case 'l': case 'L': case 'q': case 'Q':
case 'f': case 'd': case 'g':
case 'O': case 'p':
if (ctx->enc_type == *ts && got_Z == ctx->is_complex &&
ctx->enc_packmode == ctx->new_packmode) {
ctx->enc_count += ctx->new_count;
ctx->new_count = 1;
got_Z = 0;
++ts;
break;
}
case 's':
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
ctx->enc_count = ctx->new_count;
ctx->enc_packmode = ctx->new_packmode;
ctx->enc_type = *ts;
ctx->is_complex = got_Z;
++ts;
ctx->new_count = 1;
got_Z = 0;
break;
case ':':
++ts;
while(*ts != ':') ++ts;
++ts;
break;
case '(':
if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL;
break;
default:
{
int number = __Pyx_BufFmt_ExpectNumber(&ts);
if (number == -1) return NULL;
ctx->new_count = (size_t)number;
}
}
}
}
static CYTHON_INLINE void __Pyx_ZeroBuffer(Py_buffer* buf) {
buf->buf = NULL;
buf->obj = NULL;
buf->strides = __Pyx_zeros;
buf->shape = __Pyx_zeros;
buf->suboffsets = __Pyx_minusones;
}
static CYTHON_INLINE int __Pyx_GetBufferAndValidate(
Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags,
int nd, int cast, __Pyx_BufFmt_StackElem* stack)
{
if (obj == Py_None || obj == NULL) {
__Pyx_ZeroBuffer(buf);
return 0;
}
buf->buf = NULL;
if (__Pyx_GetBuffer(obj, buf, flags) == -1) goto fail;
if (buf->ndim != nd) {
PyErr_Format(PyExc_ValueError,
"Buffer has wrong number of dimensions (expected %d, got %d)",
nd, buf->ndim);
goto fail;
}
if (!cast) {
__Pyx_BufFmt_Context ctx;
__Pyx_BufFmt_Init(&ctx, stack, dtype);
if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail;
}
if ((unsigned)buf->itemsize != dtype->size) {
PyErr_Format(PyExc_ValueError,
"Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)",
buf->itemsize, (buf->itemsize > 1) ? "s" : "",
dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : "");
goto fail;
}
if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones;
return 0;
fail:;
__Pyx_ZeroBuffer(buf);
return -1;
}
static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) {
if (info->buf == NULL) return;
if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL;
__Pyx_ReleaseBuffer(info);
}
/* MemviewSliceInit */
static int
__Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview,
int ndim,
__Pyx_memviewslice *memviewslice,
int memview_is_new_reference)
{
__Pyx_RefNannyDeclarations
int i, retval=-1;
Py_buffer *buf = &memview->view;
__Pyx_RefNannySetupContext("init_memviewslice", 0);
if (!buf) {
PyErr_SetString(PyExc_ValueError,
"buf is NULL.");
goto fail;
} else if (memviewslice->memview || memviewslice->data) {
PyErr_SetString(PyExc_ValueError,
"memviewslice is already initialized!");
goto fail;
}
if (buf->strides) {
for (i = 0; i < ndim; i++) {
memviewslice->strides[i] = buf->strides[i];
}
} else {
Py_ssize_t stride = buf->itemsize;
for (i = ndim - 1; i >= 0; i--) {
memviewslice->strides[i] = stride;
stride *= buf->shape[i];
}
}
for (i = 0; i < ndim; i++) {
memviewslice->shape[i] = buf->shape[i];
if (buf->suboffsets) {
memviewslice->suboffsets[i] = buf->suboffsets[i];
} else {
memviewslice->suboffsets[i] = -1;
}
}
memviewslice->memview = memview;
memviewslice->data = (char *)buf->buf;
if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) {
Py_INCREF(memview);
}
retval = 0;
goto no_fail;
fail:
memviewslice->memview = 0;
memviewslice->data = 0;
retval = -1;
no_fail:
__Pyx_RefNannyFinishContext();
return retval;
}
static CYTHON_INLINE void __pyx_fatalerror(const char *fmt, ...) {
va_list vargs;
char msg[200];
#ifdef HAVE_STDARG_PROTOTYPES
va_start(vargs, fmt);
#else
va_start(vargs);
#endif
vsnprintf(msg, 200, fmt, vargs);
Py_FatalError(msg);
va_end(vargs);
}
static CYTHON_INLINE int
__pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count,
PyThread_type_lock lock)
{
int result;
PyThread_acquire_lock(lock, 1);
result = (*acquisition_count)++;
PyThread_release_lock(lock);
return result;
}
static CYTHON_INLINE int
__pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count,
PyThread_type_lock lock)
{
int result;
PyThread_acquire_lock(lock, 1);
result = (*acquisition_count)--;
PyThread_release_lock(lock);
return result;
}
static CYTHON_INLINE void
__Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno)
{
int first_time;
struct __pyx_memoryview_obj *memview = memslice->memview;
if (!memview || (PyObject *) memview == Py_None)
return;
if (__pyx_get_slice_count(memview) < 0)
__pyx_fatalerror("Acquisition count is %d (line %d)",
__pyx_get_slice_count(memview), lineno);
first_time = __pyx_add_acquisition_count(memview) == 0;
if (first_time) {
if (have_gil) {
Py_INCREF((PyObject *) memview);
} else {
PyGILState_STATE _gilstate = PyGILState_Ensure();
Py_INCREF((PyObject *) memview);
PyGILState_Release(_gilstate);
}
}
}
static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice,
int have_gil, int lineno) {
int last_time;
struct __pyx_memoryview_obj *memview = memslice->memview;
if (!memview ) {
return;
} else if ((PyObject *) memview == Py_None) {
memslice->memview = NULL;
return;
}
if (__pyx_get_slice_count(memview) <= 0)
__pyx_fatalerror("Acquisition count is %d (line %d)",
__pyx_get_slice_count(memview), lineno);
last_time = __pyx_sub_acquisition_count(memview) == 1;
memslice->data = NULL;
if (last_time) {
if (have_gil) {
Py_CLEAR(memslice->memview);
} else {
PyGILState_STATE _gilstate = PyGILState_Ensure();
Py_CLEAR(memslice->memview);
PyGILState_Release(_gilstate);
}
} else {
memslice->memview = NULL;
}
}
/* RaiseArgTupleInvalid */
static void __Pyx_RaiseArgtupleInvalid(
const char* func_name,
int exact,
Py_ssize_t num_min,
Py_ssize_t num_max,
Py_ssize_t num_found)
{
Py_ssize_t num_expected;
const char *more_or_less;
if (num_found < num_min) {
num_expected = num_min;
more_or_less = "at least";
} else {
num_expected = num_max;
more_or_less = "at most";
}
if (exact) {
more_or_less = "exactly";
}
PyErr_Format(PyExc_TypeError,
"%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)",
func_name, more_or_less, num_expected,
(num_expected == 1) ? "" : "s", num_found);
}
/* RaiseDoubleKeywords */
static void __Pyx_RaiseDoubleKeywordsError(
const char* func_name,
PyObject* kw_name)
{
PyErr_Format(PyExc_TypeError,
#if PY_MAJOR_VERSION >= 3
"%s() got multiple values for keyword argument '%U'", func_name, kw_name);
#else
"%s() got multiple values for keyword argument '%s'", func_name,
PyString_AsString(kw_name));
#endif
}
/* ParseKeywords */
static int __Pyx_ParseOptionalKeywords(
PyObject *kwds,
PyObject **argnames[],
PyObject *kwds2,
PyObject *values[],
Py_ssize_t num_pos_args,
const char* function_name)
{
PyObject *key = 0, *value = 0;
Py_ssize_t pos = 0;
PyObject*** name;
PyObject*** first_kw_arg = argnames + num_pos_args;
while (PyDict_Next(kwds, &pos, &key, &value)) {
name = first_kw_arg;
while (*name && (**name != key)) name++;
if (*name) {
values[name-argnames] = value;
continue;
}
name = first_kw_arg;
#if PY_MAJOR_VERSION < 3
if (likely(PyString_CheckExact(key)) || likely(PyString_Check(key))) {
while (*name) {
if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key))
&& _PyString_Eq(**name, key)) {
values[name-argnames] = value;
break;
}
name++;
}
if (*name) continue;
else {
PyObject*** argname = argnames;
while (argname != first_kw_arg) {
if ((**argname == key) || (
(CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key))
&& _PyString_Eq(**argname, key))) {
goto arg_passed_twice;
}
argname++;
}
}
} else
#endif
if (likely(PyUnicode_Check(key))) {
while (*name) {
int cmp = (**name == key) ? 0 :
#if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
(PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
#endif
PyUnicode_Compare(**name, key);
if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
if (cmp == 0) {
values[name-argnames] = value;
break;
}
name++;
}
if (*name) continue;
else {
PyObject*** argname = argnames;
while (argname != first_kw_arg) {
int cmp = (**argname == key) ? 0 :
#if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
(PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
#endif
PyUnicode_Compare(**argname, key);
if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
if (cmp == 0) goto arg_passed_twice;
argname++;
}
}
} else
goto invalid_keyword_type;
if (kwds2) {
if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad;
} else {
goto invalid_keyword;
}
}
return 0;
arg_passed_twice:
__Pyx_RaiseDoubleKeywordsError(function_name, key);
goto bad;
invalid_keyword_type:
PyErr_Format(PyExc_TypeError,
"%.200s() keywords must be strings", function_name);
goto bad;
invalid_keyword:
PyErr_Format(PyExc_TypeError,
#if PY_MAJOR_VERSION < 3
"%.200s() got an unexpected keyword argument '%.200s'",
function_name, PyString_AsString(key));
#else
"%s() got an unexpected keyword argument '%U'",
function_name, key);
#endif
bad:
return -1;
}
/* ArgTypeTest */
static void __Pyx_RaiseArgumentTypeInvalid(const char* name, PyObject *obj, PyTypeObject *type) {
PyErr_Format(PyExc_TypeError,
"Argument '%.200s' has incorrect type (expected %.200s, got %.200s)",
name, type->tp_name, Py_TYPE(obj)->tp_name);
}
static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed,
const char *name, int exact)
{
if (unlikely(!type)) {
PyErr_SetString(PyExc_SystemError, "Missing type object");
return 0;
}
if (none_allowed && obj == Py_None) return 1;
else if (exact) {
if (likely(Py_TYPE(obj) == type)) return 1;
#if PY_MAJOR_VERSION == 2
else if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1;
#endif
}
else {
if (likely(PyObject_TypeCheck(obj, type))) return 1;
}
__Pyx_RaiseArgumentTypeInvalid(name, obj, type);
return 0;
}
/* PyErrFetchRestore */
#if CYTHON_FAST_THREAD_STATE
static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) {
PyObject *tmp_type, *tmp_value, *tmp_tb;
tmp_type = tstate->curexc_type;
tmp_value = tstate->curexc_value;
tmp_tb = tstate->curexc_traceback;
tstate->curexc_type = type;
tstate->curexc_value = value;
tstate->curexc_traceback = tb;
Py_XDECREF(tmp_type);
Py_XDECREF(tmp_value);
Py_XDECREF(tmp_tb);
}
static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) {
*type = tstate->curexc_type;
*value = tstate->curexc_value;
*tb = tstate->curexc_traceback;
tstate->curexc_type = 0;
tstate->curexc_value = 0;
tstate->curexc_traceback = 0;
}
#endif
/* RaiseException */
#if PY_MAJOR_VERSION < 3
static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb,
CYTHON_UNUSED PyObject *cause) {
__Pyx_PyThreadState_declare
Py_XINCREF(type);
if (!value || value == Py_None)
value = NULL;
else
Py_INCREF(value);
if (!tb || tb == Py_None)
tb = NULL;
else {
Py_INCREF(tb);
if (!PyTraceBack_Check(tb)) {
PyErr_SetString(PyExc_TypeError,
"raise: arg 3 must be a traceback or None");
goto raise_error;
}
}
if (PyType_Check(type)) {
#if CYTHON_COMPILING_IN_PYPY
if (!value) {
Py_INCREF(Py_None);
value = Py_None;
}
#endif
PyErr_NormalizeException(&type, &value, &tb);
} else {
if (value) {
PyErr_SetString(PyExc_TypeError,
"instance exception may not have a separate value");
goto raise_error;
}
value = type;
type = (PyObject*) Py_TYPE(type);
Py_INCREF(type);
if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) {
PyErr_SetString(PyExc_TypeError,
"raise: exception class must be a subclass of BaseException");
goto raise_error;
}
}
__Pyx_PyThreadState_assign
__Pyx_ErrRestore(type, value, tb);
return;
raise_error:
Py_XDECREF(value);
Py_XDECREF(type);
Py_XDECREF(tb);
return;
}
#else
static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) {
PyObject* owned_instance = NULL;
if (tb == Py_None) {
tb = 0;
} else if (tb && !PyTraceBack_Check(tb)) {
PyErr_SetString(PyExc_TypeError,
"raise: arg 3 must be a traceback or None");
goto bad;
}
if (value == Py_None)
value = 0;
if (PyExceptionInstance_Check(type)) {
if (value) {
PyErr_SetString(PyExc_TypeError,
"instance exception may not have a separate value");
goto bad;
}
value = type;
type = (PyObject*) Py_TYPE(value);
} else if (PyExceptionClass_Check(type)) {
PyObject *instance_class = NULL;
if (value && PyExceptionInstance_Check(value)) {
instance_class = (PyObject*) Py_TYPE(value);
if (instance_class != type) {
int is_subclass = PyObject_IsSubclass(instance_class, type);
if (!is_subclass) {
instance_class = NULL;
} else if (unlikely(is_subclass == -1)) {
goto bad;
} else {
type = instance_class;
}
}
}
if (!instance_class) {
PyObject *args;
if (!value)
args = PyTuple_New(0);
else if (PyTuple_Check(value)) {
Py_INCREF(value);
args = value;
} else
args = PyTuple_Pack(1, value);
if (!args)
goto bad;
owned_instance = PyObject_Call(type, args, NULL);
Py_DECREF(args);
if (!owned_instance)
goto bad;
value = owned_instance;
if (!PyExceptionInstance_Check(value)) {
PyErr_Format(PyExc_TypeError,
"calling %R should have returned an instance of "
"BaseException, not %R",
type, Py_TYPE(value));
goto bad;
}
}
} else {
PyErr_SetString(PyExc_TypeError,
"raise: exception class must be a subclass of BaseException");
goto bad;
}
#if PY_VERSION_HEX >= 0x03030000
if (cause) {
#else
if (cause && cause != Py_None) {
#endif
PyObject *fixed_cause;
if (cause == Py_None) {
fixed_cause = NULL;
} else if (PyExceptionClass_Check(cause)) {
fixed_cause = PyObject_CallObject(cause, NULL);
if (fixed_cause == NULL)
goto bad;
} else if (PyExceptionInstance_Check(cause)) {
fixed_cause = cause;
Py_INCREF(fixed_cause);
} else {
PyErr_SetString(PyExc_TypeError,
"exception causes must derive from "
"BaseException");
goto bad;
}
PyException_SetCause(value, fixed_cause);
}
PyErr_SetObject(type, value);
if (tb) {
#if CYTHON_COMPILING_IN_PYPY
PyObject *tmp_type, *tmp_value, *tmp_tb;
PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb);
Py_INCREF(tb);
PyErr_Restore(tmp_type, tmp_value, tb);
Py_XDECREF(tmp_tb);
#else
PyThreadState *tstate = PyThreadState_GET();
PyObject* tmp_tb = tstate->curexc_traceback;
if (tb != tmp_tb) {
Py_INCREF(tb);
tstate->curexc_traceback = tb;
Py_XDECREF(tmp_tb);
}
#endif
}
bad:
Py_XDECREF(owned_instance);
return;
}
#endif
/* BytesEquals */
static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) {
#if CYTHON_COMPILING_IN_PYPY
return PyObject_RichCompareBool(s1, s2, equals);
#else
if (s1 == s2) {
return (equals == Py_EQ);
} else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) {
const char *ps1, *ps2;
Py_ssize_t length = PyBytes_GET_SIZE(s1);
if (length != PyBytes_GET_SIZE(s2))
return (equals == Py_NE);
ps1 = PyBytes_AS_STRING(s1);
ps2 = PyBytes_AS_STRING(s2);
if (ps1[0] != ps2[0]) {
return (equals == Py_NE);
} else if (length == 1) {
return (equals == Py_EQ);
} else {
int result = memcmp(ps1, ps2, (size_t)length);
return (equals == Py_EQ) ? (result == 0) : (result != 0);
}
} else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) {
return (equals == Py_NE);
} else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) {
return (equals == Py_NE);
} else {
int result;
PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
if (!py_result)
return -1;
result = __Pyx_PyObject_IsTrue(py_result);
Py_DECREF(py_result);
return result;
}
#endif
}
/* UnicodeEquals */
static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) {
#if CYTHON_COMPILING_IN_PYPY
return PyObject_RichCompareBool(s1, s2, equals);
#else
#if PY_MAJOR_VERSION < 3
PyObject* owned_ref = NULL;
#endif
int s1_is_unicode, s2_is_unicode;
if (s1 == s2) {
goto return_eq;
}
s1_is_unicode = PyUnicode_CheckExact(s1);
s2_is_unicode = PyUnicode_CheckExact(s2);
#if PY_MAJOR_VERSION < 3
if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) {
owned_ref = PyUnicode_FromObject(s2);
if (unlikely(!owned_ref))
return -1;
s2 = owned_ref;
s2_is_unicode = 1;
} else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) {
owned_ref = PyUnicode_FromObject(s1);
if (unlikely(!owned_ref))
return -1;
s1 = owned_ref;
s1_is_unicode = 1;
} else if (((!s2_is_unicode) & (!s1_is_unicode))) {
return __Pyx_PyBytes_Equals(s1, s2, equals);
}
#endif
if (s1_is_unicode & s2_is_unicode) {
Py_ssize_t length;
int kind;
void *data1, *data2;
if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0))
return -1;
length = __Pyx_PyUnicode_GET_LENGTH(s1);
if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) {
goto return_ne;
}
kind = __Pyx_PyUnicode_KIND(s1);
if (kind != __Pyx_PyUnicode_KIND(s2)) {
goto return_ne;
}
data1 = __Pyx_PyUnicode_DATA(s1);
data2 = __Pyx_PyUnicode_DATA(s2);
if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) {
goto return_ne;
} else if (length == 1) {
goto return_eq;
} else {
int result = memcmp(data1, data2, (size_t)(length * kind));
#if PY_MAJOR_VERSION < 3
Py_XDECREF(owned_ref);
#endif
return (equals == Py_EQ) ? (result == 0) : (result != 0);
}
} else if ((s1 == Py_None) & s2_is_unicode) {
goto return_ne;
} else if ((s2 == Py_None) & s1_is_unicode) {
goto return_ne;
} else {
int result;
PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
if (!py_result)
return -1;
result = __Pyx_PyObject_IsTrue(py_result);
Py_DECREF(py_result);
return result;
}
return_eq:
#if PY_MAJOR_VERSION < 3
Py_XDECREF(owned_ref);
#endif
return (equals == Py_EQ);
return_ne:
#if PY_MAJOR_VERSION < 3
Py_XDECREF(owned_ref);
#endif
return (equals == Py_NE);
#endif
}
/* None */
static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t a, Py_ssize_t b) {
Py_ssize_t q = a / b;
Py_ssize_t r = a - q*b;
q -= ((r != 0) & ((r ^ b) < 0));
return q;
}
/* GetAttr */
static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) {
#if CYTHON_COMPILING_IN_CPYTHON
#if PY_MAJOR_VERSION >= 3
if (likely(PyUnicode_Check(n)))
#else
if (likely(PyString_Check(n)))
#endif
return __Pyx_PyObject_GetAttrStr(o, n);
#endif
return PyObject_GetAttr(o, n);
}
/* decode_c_string */
static CYTHON_INLINE PyObject* __Pyx_decode_c_string(
const char* cstring, Py_ssize_t start, Py_ssize_t stop,
const char* encoding, const char* errors,
PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) {
Py_ssize_t length;
if (unlikely((start < 0) | (stop < 0))) {
size_t slen = strlen(cstring);
if (unlikely(slen > (size_t) PY_SSIZE_T_MAX)) {
PyErr_SetString(PyExc_OverflowError,
"c-string too long to convert to Python");
return NULL;
}
length = (Py_ssize_t) slen;
if (start < 0) {
start += length;
if (start < 0)
start = 0;
}
if (stop < 0)
stop += length;
}
length = stop - start;
if (unlikely(length <= 0))
return PyUnicode_FromUnicode(NULL, 0);
cstring += start;
if (decode_func) {
return decode_func(cstring, length, errors);
} else {
return PyUnicode_Decode(cstring, length, encoding, errors);
}
}
/* RaiseTooManyValuesToUnpack */
static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) {
PyErr_Format(PyExc_ValueError,
"too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected);
}
/* RaiseNeedMoreValuesToUnpack */
static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) {
PyErr_Format(PyExc_ValueError,
"need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack",
index, (index == 1) ? "" : "s");
}
/* RaiseNoneIterError */
static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) {
PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable");
}
/* ExtTypeTest */
static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) {
if (unlikely(!type)) {
PyErr_SetString(PyExc_SystemError, "Missing type object");
return 0;
}
if (likely(PyObject_TypeCheck(obj, type)))
return 1;
PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s",
Py_TYPE(obj)->tp_name, type->tp_name);
return 0;
}
/* SaveResetException */
#if CYTHON_FAST_THREAD_STATE
static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) {
*type = tstate->exc_type;
*value = tstate->exc_value;
*tb = tstate->exc_traceback;
Py_XINCREF(*type);
Py_XINCREF(*value);
Py_XINCREF(*tb);
}
static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) {
PyObject *tmp_type, *tmp_value, *tmp_tb;
tmp_type = tstate->exc_type;
tmp_value = tstate->exc_value;
tmp_tb = tstate->exc_traceback;
tstate->exc_type = type;
tstate->exc_value = value;
tstate->exc_traceback = tb;
Py_XDECREF(tmp_type);
Py_XDECREF(tmp_value);
Py_XDECREF(tmp_tb);
}
#endif
/* PyErrExceptionMatches */
#if CYTHON_FAST_THREAD_STATE
static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err) {
PyObject *exc_type = tstate->curexc_type;
if (exc_type == err) return 1;
if (unlikely(!exc_type)) return 0;
return PyErr_GivenExceptionMatches(exc_type, err);
}
#endif
/* GetException */
#if CYTHON_FAST_THREAD_STATE
static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) {
#else
static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) {
#endif
PyObject *local_type, *local_value, *local_tb;
#if CYTHON_FAST_THREAD_STATE
PyObject *tmp_type, *tmp_value, *tmp_tb;
local_type = tstate->curexc_type;
local_value = tstate->curexc_value;
local_tb = tstate->curexc_traceback;
tstate->curexc_type = 0;
tstate->curexc_value = 0;
tstate->curexc_traceback = 0;
#else
PyErr_Fetch(&local_type, &local_value, &local_tb);
#endif
PyErr_NormalizeException(&local_type, &local_value, &local_tb);
#if CYTHON_FAST_THREAD_STATE
if (unlikely(tstate->curexc_type))
#else
if (unlikely(PyErr_Occurred()))
#endif
goto bad;
#if PY_MAJOR_VERSION >= 3
if (local_tb) {
if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0))
goto bad;
}
#endif
Py_XINCREF(local_tb);
Py_XINCREF(local_type);
Py_XINCREF(local_value);
*type = local_type;
*value = local_value;
*tb = local_tb;
#if CYTHON_FAST_THREAD_STATE
tmp_type = tstate->exc_type;
tmp_value = tstate->exc_value;
tmp_tb = tstate->exc_traceback;
tstate->exc_type = local_type;
tstate->exc_value = local_value;
tstate->exc_traceback = local_tb;
Py_XDECREF(tmp_type);
Py_XDECREF(tmp_value);
Py_XDECREF(tmp_tb);
#else
PyErr_SetExcInfo(local_type, local_value, local_tb);
#endif
return 0;
bad:
*type = 0;
*value = 0;
*tb = 0;
Py_XDECREF(local_type);
Py_XDECREF(local_value);
Py_XDECREF(local_tb);
return -1;
}
/* SwapException */
#if CYTHON_FAST_THREAD_STATE
static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) {
PyObject *tmp_type, *tmp_value, *tmp_tb;
tmp_type = tstate->exc_type;
tmp_value = tstate->exc_value;
tmp_tb = tstate->exc_traceback;
tstate->exc_type = *type;
tstate->exc_value = *value;
tstate->exc_traceback = *tb;
*type = tmp_type;
*value = tmp_value;
*tb = tmp_tb;
}
#else
static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) {
PyObject *tmp_type, *tmp_value, *tmp_tb;
PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb);
PyErr_SetExcInfo(*type, *value, *tb);
*type = tmp_type;
*value = tmp_value;
*tb = tmp_tb;
}
#endif
/* Import */
static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) {
PyObject *empty_list = 0;
PyObject *module = 0;
PyObject *global_dict = 0;
PyObject *empty_dict = 0;
PyObject *list;
#if PY_VERSION_HEX < 0x03030000
PyObject *py_import;
py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import);
if (!py_import)
goto bad;
#endif
if (from_list)
list = from_list;
else {
empty_list = PyList_New(0);
if (!empty_list)
goto bad;
list = empty_list;
}
global_dict = PyModule_GetDict(__pyx_m);
if (!global_dict)
goto bad;
empty_dict = PyDict_New();
if (!empty_dict)
goto bad;
{
#if PY_MAJOR_VERSION >= 3
if (level == -1) {
if (strchr(__Pyx_MODULE_NAME, '.')) {
#if PY_VERSION_HEX < 0x03030000
PyObject *py_level = PyInt_FromLong(1);
if (!py_level)
goto bad;
module = PyObject_CallFunctionObjArgs(py_import,
name, global_dict, empty_dict, list, py_level, NULL);
Py_DECREF(py_level);
#else
module = PyImport_ImportModuleLevelObject(
name, global_dict, empty_dict, list, 1);
#endif
if (!module) {
if (!PyErr_ExceptionMatches(PyExc_ImportError))
goto bad;
PyErr_Clear();
}
}
level = 0;
}
#endif
if (!module) {
#if PY_VERSION_HEX < 0x03030000
PyObject *py_level = PyInt_FromLong(level);
if (!py_level)
goto bad;
module = PyObject_CallFunctionObjArgs(py_import,
name, global_dict, empty_dict, list, py_level, NULL);
Py_DECREF(py_level);
#else
module = PyImport_ImportModuleLevelObject(
name, global_dict, empty_dict, list, level);
#endif
}
}
bad:
#if PY_VERSION_HEX < 0x03030000
Py_XDECREF(py_import);
#endif
Py_XDECREF(empty_list);
Py_XDECREF(empty_dict);
return module;
}
/* PyFunctionFastCall */
#if CYTHON_FAST_PYCALL
#include "frameobject.h"
static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args, Py_ssize_t na,
PyObject *globals) {
PyFrameObject *f;
PyThreadState *tstate = PyThreadState_GET();
PyObject **fastlocals;
Py_ssize_t i;
PyObject *result;
assert(globals != NULL);
/* XXX Perhaps we should create a specialized
PyFrame_New() that doesn't take locals, but does
take builtins without sanity checking them.
*/
assert(tstate != NULL);
f = PyFrame_New(tstate, co, globals, NULL);
if (f == NULL) {
return NULL;
}
fastlocals = f->f_localsplus;
for (i = 0; i < na; i++) {
Py_INCREF(*args);
fastlocals[i] = *args++;
}
result = PyEval_EvalFrameEx(f,0);
++tstate->recursion_depth;
Py_DECREF(f);
--tstate->recursion_depth;
return result;
}
#if 1 || PY_VERSION_HEX < 0x030600B1
static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, int nargs, PyObject *kwargs) {
PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func);
PyObject *globals = PyFunction_GET_GLOBALS(func);
PyObject *argdefs = PyFunction_GET_DEFAULTS(func);
PyObject *closure;
#if PY_MAJOR_VERSION >= 3
PyObject *kwdefs;
#endif
PyObject *kwtuple, **k;
PyObject **d;
Py_ssize_t nd;
Py_ssize_t nk;
PyObject *result;
assert(kwargs == NULL || PyDict_Check(kwargs));
nk = kwargs ? PyDict_Size(kwargs) : 0;
if (Py_EnterRecursiveCall((char*)" while calling a Python object")) {
return NULL;
}
if (
#if PY_MAJOR_VERSION >= 3
co->co_kwonlyargcount == 0 &&
#endif
likely(kwargs == NULL || nk == 0) &&
co->co_flags == (CO_OPTIMIZED | CO_NEWLOCALS | CO_NOFREE)) {
if (argdefs == NULL && co->co_argcount == nargs) {
result = __Pyx_PyFunction_FastCallNoKw(co, args, nargs, globals);
goto done;
}
else if (nargs == 0 && argdefs != NULL
&& co->co_argcount == Py_SIZE(argdefs)) {
/* function called with no arguments, but all parameters have
a default value: use default values as arguments .*/
args = &PyTuple_GET_ITEM(argdefs, 0);
result =__Pyx_PyFunction_FastCallNoKw(co, args, Py_SIZE(argdefs), globals);
goto done;
}
}
if (kwargs != NULL) {
Py_ssize_t pos, i;
kwtuple = PyTuple_New(2 * nk);
if (kwtuple == NULL) {
result = NULL;
goto done;
}
k = &PyTuple_GET_ITEM(kwtuple, 0);
pos = i = 0;
while (PyDict_Next(kwargs, &pos, &k[i], &k[i+1])) {
Py_INCREF(k[i]);
Py_INCREF(k[i+1]);
i += 2;
}
nk = i / 2;
}
else {
kwtuple = NULL;
k = NULL;
}
closure = PyFunction_GET_CLOSURE(func);
#if PY_MAJOR_VERSION >= 3
kwdefs = PyFunction_GET_KW_DEFAULTS(func);
#endif
if (argdefs != NULL) {
d = &PyTuple_GET_ITEM(argdefs, 0);
nd = Py_SIZE(argdefs);
}
else {
d = NULL;
nd = 0;
}
#if PY_MAJOR_VERSION >= 3
result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL,
args, nargs,
k, (int)nk,
d, (int)nd, kwdefs, closure);
#else
result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL,
args, nargs,
k, (int)nk,
d, (int)nd, closure);
#endif
Py_XDECREF(kwtuple);
done:
Py_LeaveRecursiveCall();
return result;
}
#endif // CPython < 3.6
#endif // CYTHON_FAST_PYCALL
/* PyCFunctionFastCall */
#if CYTHON_FAST_PYCCALL
static CYTHON_INLINE PyObject * __Pyx_PyCFunction_FastCall(PyObject *func_obj, PyObject **args, Py_ssize_t nargs) {
PyCFunctionObject *func = (PyCFunctionObject*)func_obj;
PyCFunction meth = PyCFunction_GET_FUNCTION(func);
PyObject *self = PyCFunction_GET_SELF(func);
assert(PyCFunction_Check(func));
assert(METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST)));
assert(nargs >= 0);
assert(nargs == 0 || args != NULL);
/* _PyCFunction_FastCallDict() must not be called with an exception set,
because it may clear it (directly or indirectly) and so the
caller loses its exception */
assert(!PyErr_Occurred());
return (*((__Pyx_PyCFunctionFast)meth)) (self, args, nargs, NULL);
}
#endif // CYTHON_FAST_PYCCALL
/* GetItemInt */
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) {
PyObject *r;
if (!j) return NULL;
r = PyObject_GetItem(o, j);
Py_DECREF(j);
return r;
}
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
CYTHON_NCP_UNUSED int wraparound,
CYTHON_NCP_UNUSED int boundscheck) {
#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS
if (wraparound & unlikely(i < 0)) i += PyList_GET_SIZE(o);
if ((!boundscheck) || likely((0 <= i) & (i < PyList_GET_SIZE(o)))) {
PyObject *r = PyList_GET_ITEM(o, i);
Py_INCREF(r);
return r;
}
return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
#else
return PySequence_GetItem(o, i);
#endif
}
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
CYTHON_NCP_UNUSED int wraparound,
CYTHON_NCP_UNUSED int boundscheck) {
#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS
if (wraparound & unlikely(i < 0)) i += PyTuple_GET_SIZE(o);
if ((!boundscheck) || likely((0 <= i) & (i < PyTuple_GET_SIZE(o)))) {
PyObject *r = PyTuple_GET_ITEM(o, i);
Py_INCREF(r);
return r;
}
return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
#else
return PySequence_GetItem(o, i);
#endif
}
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list,
CYTHON_NCP_UNUSED int wraparound,
CYTHON_NCP_UNUSED int boundscheck) {
#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS
if (is_list || PyList_CheckExact(o)) {
Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o);
if ((!boundscheck) || (likely((n >= 0) & (n < PyList_GET_SIZE(o))))) {
PyObject *r = PyList_GET_ITEM(o, n);
Py_INCREF(r);
return r;
}
}
else if (PyTuple_CheckExact(o)) {
Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o);
if ((!boundscheck) || likely((n >= 0) & (n < PyTuple_GET_SIZE(o)))) {
PyObject *r = PyTuple_GET_ITEM(o, n);
Py_INCREF(r);
return r;
}
} else {
PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence;
if (likely(m && m->sq_item)) {
if (wraparound && unlikely(i < 0) && likely(m->sq_length)) {
Py_ssize_t l = m->sq_length(o);
if (likely(l >= 0)) {
i += l;
} else {
if (!PyErr_ExceptionMatches(PyExc_OverflowError))
return NULL;
PyErr_Clear();
}
}
return m->sq_item(o, i);
}
}
#else
if (is_list || PySequence_Check(o)) {
return PySequence_GetItem(o, i);
}
#endif
return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
}
/* PyIntBinop */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, CYTHON_UNUSED int inplace) {
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_CheckExact(op1))) {
const long b = intval;
long x;
long a = PyInt_AS_LONG(op1);
x = (long)((unsigned long)a + b);
if (likely((x^a) >= 0 || (x^b) >= 0))
return PyInt_FromLong(x);
return PyLong_Type.tp_as_number->nb_add(op1, op2);
}
#endif
#if CYTHON_USE_PYLONG_INTERNALS
if (likely(PyLong_CheckExact(op1))) {
const long b = intval;
long a, x;
#ifdef HAVE_LONG_LONG
const PY_LONG_LONG llb = intval;
PY_LONG_LONG lla, llx;
#endif
const digit* digits = ((PyLongObject*)op1)->ob_digit;
const Py_ssize_t size = Py_SIZE(op1);
if (likely(__Pyx_sst_abs(size) <= 1)) {
a = likely(size) ? digits[0] : 0;
if (size == -1) a = -a;
} else {
switch (size) {
case -2:
if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) {
lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
case 2:
if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) {
lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
case -3:
if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) {
lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
case 3:
if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) {
lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
case -4:
if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) {
lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
case 4:
if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) {
lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
default: return PyLong_Type.tp_as_number->nb_add(op1, op2);
}
}
x = a + b;
return PyLong_FromLong(x);
#ifdef HAVE_LONG_LONG
long_long:
llx = lla + llb;
return PyLong_FromLongLong(llx);
#endif
}
#endif
if (PyFloat_CheckExact(op1)) {
const long b = intval;
double a = PyFloat_AS_DOUBLE(op1);
double result;
PyFPE_START_PROTECT("add", return NULL)
result = ((double)a) + (double)b;
PyFPE_END_PROTECT(result)
return PyFloat_FromDouble(result);
}
return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2);
}
#endif
/* None */
static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) {
PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname);
}
/* None */
static CYTHON_INLINE long __Pyx_div_long(long a, long b) {
long q = a / b;
long r = a - q*b;
q -= ((r != 0) & ((r ^ b) < 0));
return q;
}
/* WriteUnraisableException */
static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno,
CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename,
int full_traceback, CYTHON_UNUSED int nogil) {
PyObject *old_exc, *old_val, *old_tb;
PyObject *ctx;
__Pyx_PyThreadState_declare
#ifdef WITH_THREAD
PyGILState_STATE state;
if (nogil)
state = PyGILState_Ensure();
#ifdef _MSC_VER
else state = (PyGILState_STATE)-1;
#endif
#endif
__Pyx_PyThreadState_assign
__Pyx_ErrFetch(&old_exc, &old_val, &old_tb);
if (full_traceback) {
Py_XINCREF(old_exc);
Py_XINCREF(old_val);
Py_XINCREF(old_tb);
__Pyx_ErrRestore(old_exc, old_val, old_tb);
PyErr_PrintEx(1);
}
#if PY_MAJOR_VERSION < 3
ctx = PyString_FromString(name);
#else
ctx = PyUnicode_FromString(name);
#endif
__Pyx_ErrRestore(old_exc, old_val, old_tb);
if (!ctx) {
PyErr_WriteUnraisable(Py_None);
} else {
PyErr_WriteUnraisable(ctx);
Py_DECREF(ctx);
}
#ifdef WITH_THREAD
if (nogil)
PyGILState_Release(state);
#endif
}
/* PyObjectCallMethO */
#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) {
PyObject *self, *result;
PyCFunction cfunc;
cfunc = PyCFunction_GET_FUNCTION(func);
self = PyCFunction_GET_SELF(func);
if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object")))
return NULL;
result = cfunc(self, arg);
Py_LeaveRecursiveCall();
if (unlikely(!result) && unlikely(!PyErr_Occurred())) {
PyErr_SetString(
PyExc_SystemError,
"NULL result without error in PyObject_Call");
}
return result;
}
#endif
/* PyObjectCallOneArg */
#if CYTHON_COMPILING_IN_CPYTHON
static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) {
PyObject *result;
PyObject *args = PyTuple_New(1);
if (unlikely(!args)) return NULL;
Py_INCREF(arg);
PyTuple_SET_ITEM(args, 0, arg);
result = __Pyx_PyObject_Call(func, args, NULL);
Py_DECREF(args);
return result;
}
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) {
#if CYTHON_FAST_PYCALL
if (PyFunction_Check(func)) {
return __Pyx_PyFunction_FastCall(func, &arg, 1);
}
#endif
#ifdef __Pyx_CyFunction_USED
if (likely(PyCFunction_Check(func) || PyObject_TypeCheck(func, __pyx_CyFunctionType))) {
#else
if (likely(PyCFunction_Check(func))) {
#endif
if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) {
return __Pyx_PyObject_CallMethO(func, arg);
#if CYTHON_FAST_PYCCALL
} else if (PyCFunction_GET_FLAGS(func) & METH_FASTCALL) {
return __Pyx_PyCFunction_FastCall(func, &arg, 1);
#endif
}
}
return __Pyx__PyObject_CallOneArg(func, arg);
}
#else
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) {
PyObject *result;
PyObject *args = PyTuple_Pack(1, arg);
if (unlikely(!args)) return NULL;
result = __Pyx_PyObject_Call(func, args, NULL);
Py_DECREF(args);
return result;
}
#endif
/* SetVTable */
static int __Pyx_SetVtable(PyObject *dict, void *vtable) {
#if PY_VERSION_HEX >= 0x02070000
PyObject *ob = PyCapsule_New(vtable, 0, 0);
#else
PyObject *ob = PyCObject_FromVoidPtr(vtable, 0);
#endif
if (!ob)
goto bad;
if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0)
goto bad;
Py_DECREF(ob);
return 0;
bad:
Py_XDECREF(ob);
return -1;
}
/* CodeObjectCache */
static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) {
int start = 0, mid = 0, end = count - 1;
if (end >= 0 && code_line > entries[end].code_line) {
return count;
}
while (start < end) {
mid = start + (end - start) / 2;
if (code_line < entries[mid].code_line) {
end = mid;
} else if (code_line > entries[mid].code_line) {
start = mid + 1;
} else {
return mid;
}
}
if (code_line <= entries[mid].code_line) {
return mid;
} else {
return mid + 1;
}
}
static PyCodeObject *__pyx_find_code_object(int code_line) {
PyCodeObject* code_object;
int pos;
if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) {
return NULL;
}
pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) {
return NULL;
}
code_object = __pyx_code_cache.entries[pos].code_object;
Py_INCREF(code_object);
return code_object;
}
static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) {
int pos, i;
__Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries;
if (unlikely(!code_line)) {
return;
}
if (unlikely(!entries)) {
entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry));
if (likely(entries)) {
__pyx_code_cache.entries = entries;
__pyx_code_cache.max_count = 64;
__pyx_code_cache.count = 1;
entries[0].code_line = code_line;
entries[0].code_object = code_object;
Py_INCREF(code_object);
}
return;
}
pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) {
PyCodeObject* tmp = entries[pos].code_object;
entries[pos].code_object = code_object;
Py_DECREF(tmp);
return;
}
if (__pyx_code_cache.count == __pyx_code_cache.max_count) {
int new_max = __pyx_code_cache.max_count + 64;
entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc(
__pyx_code_cache.entries, (size_t)new_max*sizeof(__Pyx_CodeObjectCacheEntry));
if (unlikely(!entries)) {
return;
}
__pyx_code_cache.entries = entries;
__pyx_code_cache.max_count = new_max;
}
for (i=__pyx_code_cache.count; i>pos; i--) {
entries[i] = entries[i-1];
}
entries[pos].code_line = code_line;
entries[pos].code_object = code_object;
__pyx_code_cache.count++;
Py_INCREF(code_object);
}
/* AddTraceback */
#include "compile.h"
#include "frameobject.h"
#include "traceback.h"
static PyCodeObject* __Pyx_CreateCodeObjectForTraceback(
const char *funcname, int c_line,
int py_line, const char *filename) {
PyCodeObject *py_code = 0;
PyObject *py_srcfile = 0;
PyObject *py_funcname = 0;
#if PY_MAJOR_VERSION < 3
py_srcfile = PyString_FromString(filename);
#else
py_srcfile = PyUnicode_FromString(filename);
#endif
if (!py_srcfile) goto bad;
if (c_line) {
#if PY_MAJOR_VERSION < 3
py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
#else
py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
#endif
}
else {
#if PY_MAJOR_VERSION < 3
py_funcname = PyString_FromString(funcname);
#else
py_funcname = PyUnicode_FromString(funcname);
#endif
}
if (!py_funcname) goto bad;
py_code = __Pyx_PyCode_New(
0,
0,
0,
0,
0,
__pyx_empty_bytes, /*PyObject *code,*/
__pyx_empty_tuple, /*PyObject *consts,*/
__pyx_empty_tuple, /*PyObject *names,*/
__pyx_empty_tuple, /*PyObject *varnames,*/
__pyx_empty_tuple, /*PyObject *freevars,*/
__pyx_empty_tuple, /*PyObject *cellvars,*/
py_srcfile, /*PyObject *filename,*/
py_funcname, /*PyObject *name,*/
py_line,
__pyx_empty_bytes /*PyObject *lnotab*/
);
Py_DECREF(py_srcfile);
Py_DECREF(py_funcname);
return py_code;
bad:
Py_XDECREF(py_srcfile);
Py_XDECREF(py_funcname);
return NULL;
}
static void __Pyx_AddTraceback(const char *funcname, int c_line,
int py_line, const char *filename) {
PyCodeObject *py_code = 0;
PyFrameObject *py_frame = 0;
py_code = __pyx_find_code_object(c_line ? c_line : py_line);
if (!py_code) {
py_code = __Pyx_CreateCodeObjectForTraceback(
funcname, c_line, py_line, filename);
if (!py_code) goto bad;
__pyx_insert_code_object(c_line ? c_line : py_line, py_code);
}
py_frame = PyFrame_New(
PyThreadState_GET(), /*PyThreadState *tstate,*/
py_code, /*PyCodeObject *code,*/
__pyx_d, /*PyObject *globals,*/
0 /*PyObject *locals*/
);
if (!py_frame) goto bad;
__Pyx_PyFrame_SetLineNumber(py_frame, py_line);
PyTraceBack_Here(py_frame);
bad:
Py_XDECREF(py_code);
Py_XDECREF(py_frame);
}
#if PY_MAJOR_VERSION < 3
static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) {
if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags);
if (PyObject_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags);
if (PyObject_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags);
PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name);
return -1;
}
static void __Pyx_ReleaseBuffer(Py_buffer *view) {
PyObject *obj = view->obj;
if (!obj) return;
if (PyObject_CheckBuffer(obj)) {
PyBuffer_Release(view);
return;
}
Py_DECREF(obj);
view->obj = NULL;
}
#endif
/* MemviewSliceIsContig */
static int
__pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs,
char order, int ndim)
{
int i, index, step, start;
Py_ssize_t itemsize = mvs.memview->view.itemsize;
if (order == 'F') {
step = 1;
start = 0;
} else {
step = -1;
start = ndim - 1;
}
for (i = 0; i < ndim; i++) {
index = start + step * i;
if (mvs.suboffsets[index] >= 0 || mvs.strides[index] != itemsize)
return 0;
itemsize *= mvs.shape[index];
}
return 1;
}
/* OverlappingSlices */
static void
__pyx_get_array_memory_extents(__Pyx_memviewslice *slice,
void **out_start, void **out_end,
int ndim, size_t itemsize)
{
char *start, *end;
int i;
start = end = slice->data;
for (i = 0; i < ndim; i++) {
Py_ssize_t stride = slice->strides[i];
Py_ssize_t extent = slice->shape[i];
if (extent == 0) {
*out_start = *out_end = start;
return;
} else {
if (stride > 0)
end += stride * (extent - 1);
else
start += stride * (extent - 1);
}
}
*out_start = start;
*out_end = end + itemsize;
}
static int
__pyx_slices_overlap(__Pyx_memviewslice *slice1,
__Pyx_memviewslice *slice2,
int ndim, size_t itemsize)
{
void *start1, *end1, *start2, *end2;
__pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize);
__pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize);
return (start1 < end2) && (start2 < end1);
}
/* Capsule */
static CYTHON_INLINE PyObject *
__pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig)
{
PyObject *cobj;
#if PY_VERSION_HEX >= 0x02070000
cobj = PyCapsule_New(p, sig, NULL);
#else
cobj = PyCObject_FromVoidPtr(p, NULL);
#endif
return cobj;
}
/* TypeInfoCompare */
static int
__pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b)
{
int i;
if (!a || !b)
return 0;
if (a == b)
return 1;
if (a->size != b->size || a->typegroup != b->typegroup ||
a->is_unsigned != b->is_unsigned || a->ndim != b->ndim) {
if (a->typegroup == 'H' || b->typegroup == 'H') {
return a->size == b->size;
} else {
return 0;
}
}
if (a->ndim) {
for (i = 0; i < a->ndim; i++)
if (a->arraysize[i] != b->arraysize[i])
return 0;
}
if (a->typegroup == 'S') {
if (a->flags != b->flags)
return 0;
if (a->fields || b->fields) {
if (!(a->fields && b->fields))
return 0;
for (i = 0; a->fields[i].type && b->fields[i].type; i++) {
__Pyx_StructField *field_a = a->fields + i;
__Pyx_StructField *field_b = b->fields + i;
if (field_a->offset != field_b->offset ||
!__pyx_typeinfo_cmp(field_a->type, field_b->type))
return 0;
}
return !a->fields[i].type && !b->fields[i].type;
}
}
return 1;
}
/* MemviewSliceValidateAndInit */
static int
__pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec)
{
if (buf->shape[dim] <= 1)
return 1;
if (buf->strides) {
if (spec & __Pyx_MEMVIEW_CONTIG) {
if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) {
if (buf->strides[dim] != sizeof(void *)) {
PyErr_Format(PyExc_ValueError,
"Buffer is not indirectly contiguous "
"in dimension %d.", dim);
goto fail;
}
} else if (buf->strides[dim] != buf->itemsize) {
PyErr_SetString(PyExc_ValueError,
"Buffer and memoryview are not contiguous "
"in the same dimension.");
goto fail;
}
}
if (spec & __Pyx_MEMVIEW_FOLLOW) {
Py_ssize_t stride = buf->strides[dim];
if (stride < 0)
stride = -stride;
if (stride < buf->itemsize) {
PyErr_SetString(PyExc_ValueError,
"Buffer and memoryview are not contiguous "
"in the same dimension.");
goto fail;
}
}
} else {
if (spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1) {
PyErr_Format(PyExc_ValueError,
"C-contiguous buffer is not contiguous in "
"dimension %d", dim);
goto fail;
} else if (spec & (__Pyx_MEMVIEW_PTR)) {
PyErr_Format(PyExc_ValueError,
"C-contiguous buffer is not indirect in "
"dimension %d", dim);
goto fail;
} else if (buf->suboffsets) {
PyErr_SetString(PyExc_ValueError,
"Buffer exposes suboffsets but no strides");
goto fail;
}
}
return 1;
fail:
return 0;
}
static int
__pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec)
{
if (spec & __Pyx_MEMVIEW_DIRECT) {
if (buf->suboffsets && buf->suboffsets[dim] >= 0) {
PyErr_Format(PyExc_ValueError,
"Buffer not compatible with direct access "
"in dimension %d.", dim);
goto fail;
}
}
if (spec & __Pyx_MEMVIEW_PTR) {
if (!buf->suboffsets || (buf->suboffsets && buf->suboffsets[dim] < 0)) {
PyErr_Format(PyExc_ValueError,
"Buffer is not indirectly accessible "
"in dimension %d.", dim);
goto fail;
}
}
return 1;
fail:
return 0;
}
static int
__pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag)
{
int i;
if (c_or_f_flag & __Pyx_IS_F_CONTIG) {
Py_ssize_t stride = 1;
for (i = 0; i < ndim; i++) {
if (stride * buf->itemsize != buf->strides[i] &&
buf->shape[i] > 1)
{
PyErr_SetString(PyExc_ValueError,
"Buffer not fortran contiguous.");
goto fail;
}
stride = stride * buf->shape[i];
}
} else if (c_or_f_flag & __Pyx_IS_C_CONTIG) {
Py_ssize_t stride = 1;
for (i = ndim - 1; i >- 1; i--) {
if (stride * buf->itemsize != buf->strides[i] &&
buf->shape[i] > 1) {
PyErr_SetString(PyExc_ValueError,
"Buffer not C contiguous.");
goto fail;
}
stride = stride * buf->shape[i];
}
}
return 1;
fail:
return 0;
}
static int __Pyx_ValidateAndInit_memviewslice(
int *axes_specs,
int c_or_f_flag,
int buf_flags,
int ndim,
__Pyx_TypeInfo *dtype,
__Pyx_BufFmt_StackElem stack[],
__Pyx_memviewslice *memviewslice,
PyObject *original_obj)
{
struct __pyx_memoryview_obj *memview, *new_memview;
__Pyx_RefNannyDeclarations
Py_buffer *buf;
int i, spec = 0, retval = -1;
__Pyx_BufFmt_Context ctx;
int from_memoryview = __pyx_memoryview_check(original_obj);
__Pyx_RefNannySetupContext("ValidateAndInit_memviewslice", 0);
if (from_memoryview && __pyx_typeinfo_cmp(dtype, ((struct __pyx_memoryview_obj *)
original_obj)->typeinfo)) {
memview = (struct __pyx_memoryview_obj *) original_obj;
new_memview = NULL;
} else {
memview = (struct __pyx_memoryview_obj *) __pyx_memoryview_new(
original_obj, buf_flags, 0, dtype);
new_memview = memview;
if (unlikely(!memview))
goto fail;
}
buf = &memview->view;
if (buf->ndim != ndim) {
PyErr_Format(PyExc_ValueError,
"Buffer has wrong number of dimensions (expected %d, got %d)",
ndim, buf->ndim);
goto fail;
}
if (new_memview) {
__Pyx_BufFmt_Init(&ctx, stack, dtype);
if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail;
}
if ((unsigned) buf->itemsize != dtype->size) {
PyErr_Format(PyExc_ValueError,
"Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "u byte%s) "
"does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)",
buf->itemsize,
(buf->itemsize > 1) ? "s" : "",
dtype->name,
dtype->size,
(dtype->size > 1) ? "s" : "");
goto fail;
}
for (i = 0; i < ndim; i++) {
spec = axes_specs[i];
if (!__pyx_check_strides(buf, i, ndim, spec))
goto fail;
if (!__pyx_check_suboffsets(buf, i, ndim, spec))
goto fail;
}
if (buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag))
goto fail;
if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice,
new_memview != NULL) == -1)) {
goto fail;
}
retval = 0;
goto no_fail;
fail:
Py_XDECREF(new_memview);
retval = -1;
no_fail:
__Pyx_RefNannyFinishContext();
return retval;
}
/* ObjectToMemviewSlice */
static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_double(PyObject *obj) {
__Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
__Pyx_BufFmt_StackElem stack[1];
int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) };
int retcode;
if (obj == Py_None) {
result.memview = (struct __pyx_memoryview_obj *) Py_None;
return result;
}
retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0,
PyBUF_RECORDS, 2,
&__Pyx_TypeInfo_double, stack,
&result, obj);
if (unlikely(retcode == -1))
goto __pyx_fail;
return result;
__pyx_fail:
result.memview = NULL;
result.data = NULL;
return result;
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) {
const int neg_one = (int) -1, const_zero = (int) 0;
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(int) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(int) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(int) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(int) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(int),
little, !is_unsigned);
}
}
/* CIntFromPyVerify */
#define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\
__PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0)
#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\
__PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1)
#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\
{\
func_type value = func_value;\
if (sizeof(target_type) < sizeof(func_type)) {\
if (unlikely(value != (func_type) (target_type) value)) {\
func_type zero = 0;\
if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\
return (target_type) -1;\
if (is_unsigned && unlikely(value < zero))\
goto raise_neg_overflow;\
else\
goto raise_overflow;\
}\
}\
return (target_type) value;\
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) {
const long neg_one = (long) -1, const_zero = (long) 0;
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(long) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(long) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(long) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(long) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(long),
little, !is_unsigned);
}
}
/* MemviewDtypeToObject */
static CYTHON_INLINE PyObject *__pyx_memview_get_double(const char *itemp) {
return (PyObject *) PyFloat_FromDouble(*(double *) itemp);
}
static CYTHON_INLINE int __pyx_memview_set_double(const char *itemp, PyObject *obj) {
double value = __pyx_PyFloat_AsDouble(obj);
if ((value == (double)-1) && PyErr_Occurred())
return 0;
*(double *) itemp = value;
return 1;
}
/* MemviewSliceCopyTemplate */
static __Pyx_memviewslice
__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs,
const char *mode, int ndim,
size_t sizeof_dtype, int contig_flag,
int dtype_is_object)
{
__Pyx_RefNannyDeclarations
int i;
__Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } };
struct __pyx_memoryview_obj *from_memview = from_mvs->memview;
Py_buffer *buf = &from_memview->view;
PyObject *shape_tuple = NULL;
PyObject *temp_int = NULL;
struct __pyx_array_obj *array_obj = NULL;
struct __pyx_memoryview_obj *memview_obj = NULL;
__Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0);
for (i = 0; i < ndim; i++) {
if (from_mvs->suboffsets[i] >= 0) {
PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with "
"indirect dimensions (axis %d)", i);
goto fail;
}
}
shape_tuple = PyTuple_New(ndim);
if (unlikely(!shape_tuple)) {
goto fail;
}
__Pyx_GOTREF(shape_tuple);
for(i = 0; i < ndim; i++) {
temp_int = PyInt_FromSsize_t(from_mvs->shape[i]);
if(unlikely(!temp_int)) {
goto fail;
} else {
PyTuple_SET_ITEM(shape_tuple, i, temp_int);
temp_int = NULL;
}
}
array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL);
if (unlikely(!array_obj)) {
goto fail;
}
__Pyx_GOTREF(array_obj);
memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new(
(PyObject *) array_obj, contig_flag,
dtype_is_object,
from_mvs->memview->typeinfo);
if (unlikely(!memview_obj))
goto fail;
if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0))
goto fail;
if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim,
dtype_is_object) < 0))
goto fail;
goto no_fail;
fail:
__Pyx_XDECREF(new_mvs.memview);
new_mvs.memview = NULL;
new_mvs.data = NULL;
no_fail:
__Pyx_XDECREF(shape_tuple);
__Pyx_XDECREF(temp_int);
__Pyx_XDECREF(array_obj);
__Pyx_RefNannyFinishContext();
return new_mvs;
}
/* CIntFromPy */
static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) {
const int neg_one = (int) -1, const_zero = (int) 0;
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(int) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (int) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (int) 0;
case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0])
case 2:
if (8 * sizeof(int) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) {
return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(int) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) {
return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(int) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) {
return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (int) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(int) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (int) 0;
case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0])
case -2:
if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) {
return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(int) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) {
return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) {
return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(int) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) {
return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) {
return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(int) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) {
return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
}
}
break;
}
#endif
if (sizeof(int) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(int) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
int val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (int) -1;
}
} else {
int val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (int) -1;
val = __Pyx_PyInt_As_int(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to int");
return (int) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to int");
return (int) -1;
}
/* CIntFromPy */
static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) {
const char neg_one = (char) -1, const_zero = (char) 0;
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(char) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (char) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (char) 0;
case 1: __PYX_VERIFY_RETURN_INT(char, digit, digits[0])
case 2:
if (8 * sizeof(char) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) >= 2 * PyLong_SHIFT) {
return (char) (((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(char) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) >= 3 * PyLong_SHIFT) {
return (char) (((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(char) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) >= 4 * PyLong_SHIFT) {
return (char) (((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (char) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(char) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(char, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(char) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(char, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (char) 0;
case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(char, digit, +digits[0])
case -2:
if (8 * sizeof(char) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) {
return (char) (((char)-1)*(((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(char) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) {
return (char) ((((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) {
return (char) (((char)-1)*(((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(char) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) {
return (char) ((((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) {
return (char) (((char)-1)*(((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(char) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) {
return (char) ((((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
}
}
break;
}
#endif
if (sizeof(char) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(char, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(char) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(char, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
char val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (char) -1;
}
} else {
char val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (char) -1;
val = __Pyx_PyInt_As_char(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to char");
return (char) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to char");
return (char) -1;
}
/* CIntFromPy */
static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) {
const long neg_one = (long) -1, const_zero = (long) 0;
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(long) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (long) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (long) 0;
case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0])
case 2:
if (8 * sizeof(long) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) {
return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(long) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) {
return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(long) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) {
return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (long) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(long) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (long) 0;
case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0])
case -2:
if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(long) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(long) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(long) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
}
}
break;
}
#endif
if (sizeof(long) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(long) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
long val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (long) -1;
}
} else {
long val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (long) -1;
val = __Pyx_PyInt_As_long(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to long");
return (long) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to long");
return (long) -1;
}
/* CheckBinaryVersion */
static int __Pyx_check_binary_version(void) {
char ctversion[4], rtversion[4];
PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION);
PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion());
if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) {
char message[200];
PyOS_snprintf(message, sizeof(message),
"compiletime version %s of module '%.100s' "
"does not match runtime version %s",
ctversion, __Pyx_MODULE_NAME, rtversion);
return PyErr_WarnEx(NULL, message, 1);
}
return 0;
}
/* InitStrings */
static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) {
while (t->p) {
#if PY_MAJOR_VERSION < 3
if (t->is_unicode) {
*t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL);
} else if (t->intern) {
*t->p = PyString_InternFromString(t->s);
} else {
*t->p = PyString_FromStringAndSize(t->s, t->n - 1);
}
#else
if (t->is_unicode | t->is_str) {
if (t->intern) {
*t->p = PyUnicode_InternFromString(t->s);
} else if (t->encoding) {
*t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL);
} else {
*t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1);
}
} else {
*t->p = PyBytes_FromStringAndSize(t->s, t->n - 1);
}
#endif
if (!*t->p)
return -1;
++t;
}
return 0;
}
static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) {
return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str));
}
static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject* o) {
Py_ssize_t ignore;
return __Pyx_PyObject_AsStringAndSize(o, &ignore);
}
static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) {
#if CYTHON_COMPILING_IN_CPYTHON && (__PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT)
if (
#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
__Pyx_sys_getdefaultencoding_not_ascii &&
#endif
PyUnicode_Check(o)) {
#if PY_VERSION_HEX < 0x03030000
char* defenc_c;
PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL);
if (!defenc) return NULL;
defenc_c = PyBytes_AS_STRING(defenc);
#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
{
char* end = defenc_c + PyBytes_GET_SIZE(defenc);
char* c;
for (c = defenc_c; c < end; c++) {
if ((unsigned char) (*c) >= 128) {
PyUnicode_AsASCIIString(o);
return NULL;
}
}
}
#endif
*length = PyBytes_GET_SIZE(defenc);
return defenc_c;
#else
if (__Pyx_PyUnicode_READY(o) == -1) return NULL;
#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
if (PyUnicode_IS_ASCII(o)) {
*length = PyUnicode_GET_LENGTH(o);
return PyUnicode_AsUTF8(o);
} else {
PyUnicode_AsASCIIString(o);
return NULL;
}
#else
return PyUnicode_AsUTF8AndSize(o, length);
#endif
#endif
} else
#endif
#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE))
if (PyByteArray_Check(o)) {
*length = PyByteArray_GET_SIZE(o);
return PyByteArray_AS_STRING(o);
} else
#endif
{
char* result;
int r = PyBytes_AsStringAndSize(o, &result, length);
if (unlikely(r < 0)) {
return NULL;
} else {
return result;
}
}
}
static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) {
int is_true = x == Py_True;
if (is_true | (x == Py_False) | (x == Py_None)) return is_true;
else return PyObject_IsTrue(x);
}
static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) {
#if CYTHON_USE_TYPE_SLOTS
PyNumberMethods *m;
#endif
const char *name = NULL;
PyObject *res = NULL;
#if PY_MAJOR_VERSION < 3
if (PyInt_Check(x) || PyLong_Check(x))
#else
if (PyLong_Check(x))
#endif
return __Pyx_NewRef(x);
#if CYTHON_USE_TYPE_SLOTS
m = Py_TYPE(x)->tp_as_number;
#if PY_MAJOR_VERSION < 3
if (m && m->nb_int) {
name = "int";
res = PyNumber_Int(x);
}
else if (m && m->nb_long) {
name = "long";
res = PyNumber_Long(x);
}
#else
if (m && m->nb_int) {
name = "int";
res = PyNumber_Long(x);
}
#endif
#else
res = PyNumber_Int(x);
#endif
if (res) {
#if PY_MAJOR_VERSION < 3
if (!PyInt_Check(res) && !PyLong_Check(res)) {
#else
if (!PyLong_Check(res)) {
#endif
PyErr_Format(PyExc_TypeError,
"__%.4s__ returned non-%.4s (type %.200s)",
name, name, Py_TYPE(res)->tp_name);
Py_DECREF(res);
return NULL;
}
}
else if (!PyErr_Occurred()) {
PyErr_SetString(PyExc_TypeError,
"an integer is required");
}
return res;
}
static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) {
Py_ssize_t ival;
PyObject *x;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_CheckExact(b))) {
if (sizeof(Py_ssize_t) >= sizeof(long))
return PyInt_AS_LONG(b);
else
return PyInt_AsSsize_t(x);
}
#endif
if (likely(PyLong_CheckExact(b))) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)b)->ob_digit;
const Py_ssize_t size = Py_SIZE(b);
if (likely(__Pyx_sst_abs(size) <= 1)) {
ival = likely(size) ? digits[0] : 0;
if (size == -1) ival = -ival;
return ival;
} else {
switch (size) {
case 2:
if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) {
return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
break;
case -2:
if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) {
return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
break;
case 3:
if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) {
return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
break;
case -3:
if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) {
return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
break;
case 4:
if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) {
return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
break;
case -4:
if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) {
return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
break;
}
}
#endif
return PyLong_AsSsize_t(b);
}
x = PyNumber_Index(b);
if (!x) return -1;
ival = PyInt_AsSsize_t(x);
Py_DECREF(x);
return ival;
}
static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) {
return PyInt_FromSize_t(ival);
}
#endif /* Py_PYTHON_H */
|
shared-clauseModificado.c | /*
gcc -fopenmp -O2 shared-clause.c -o shared-clause
*/
#include <stdio.h>
#ifdef _OPENMP
#include <omp.h>
#endif
main()
{
int i, n = 7;
int a[n];
for (i=0; i<n; i++)
a[i] = i+1;
// Se comparte la variable a por todas las hebras --> shared(a)
#pragma omp parallel for shared(a,n) private(i) default(none)
for (i=0; i<n; i++)
a[i] += i;
printf("Después de parallel for:\n");
for (i=0; i<n; i++)
printf("a[%d] = %d\n",i,a[i]);
} |
Private.c | #include <stdio.h>
#include <stdlib.h>
#ifdef _OPENMP
#include <omp.h>
#define TRUE 1
#define FALSE 0
#else
#define omp_get_thread_num() 0
#define omp_get_num_threads() 1
#endif
int main()
{
#ifdef _OPENMP
(void) omp_set_dynamic(FALSE);
if (omp_get_dynamic()) {printf("Advertencia: se ha hecho el ajuste dinamico de hilos\n");}
(void) omp_set_num_threads(3);
#endif
int i, n = 5;
int a;
#pragma omp parallel for private(i,a)
for (i=0; i<n; i++)
{
a = i+1;
printf("El hilo %d tiene un valor de a = %d para i = %d\n",
omp_get_thread_num(),a,i);
} // Final del for paralelo
return(0);
}
|
GB_subassign_10_and_18.c | //------------------------------------------------------------------------------
// GB_subassign_10_and_18: C(I,J)<M or !M,repl> = A ; using S
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// Method 10: C(I,J)<M,repl> = A ; using S
// Method 18: C(I,J)<!M,repl> = A ; using S
// M: present
// Mask_comp: true or false
// C_replace: true
// accum: NULL
// A: matrix
// S: constructed
// C: not bitmap: use GB_bitmap_assign instead
// M, A: any sparsity structure.
#include "GB_subassign_methods.h"
GrB_Info GB_subassign_10_and_18
(
GrB_Matrix C,
// input:
const GrB_Index *I,
const int64_t ni,
const int64_t nI,
const int Ikind,
const int64_t Icolon [3],
const GrB_Index *J,
const int64_t nj,
const int64_t nJ,
const int Jkind,
const int64_t Jcolon [3],
const GrB_Matrix M,
const bool Mask_struct, // if true, use the only structure of M
const bool Mask_comp, // if true, !M, else use M
const GrB_Matrix A,
GB_Context Context
)
{
//--------------------------------------------------------------------------
// check inputs
//--------------------------------------------------------------------------
ASSERT (!GB_IS_BITMAP (C)) ; ASSERT (!GB_IS_FULL (C)) ;
ASSERT (!GB_aliased (C, M)) ; // NO ALIAS of C==M
ASSERT (!GB_aliased (C, A)) ; // NO ALIAS of C==A
//--------------------------------------------------------------------------
// S = C(I,J)
//--------------------------------------------------------------------------
GB_EMPTY_TASKLIST ;
GB_OK (GB_subassign_symbolic (S, C, I, ni, J, nj, true, Context)) ;
//--------------------------------------------------------------------------
// get inputs
//--------------------------------------------------------------------------
GB_MATRIX_WAIT_IF_JUMBLED (M) ;
GB_MATRIX_WAIT_IF_JUMBLED (A) ;
GB_GET_C ; // C must not be bitmap
GB_GET_MASK ;
GB_GET_A ;
GB_GET_S ;
GrB_BinaryOp accum = NULL ;
//--------------------------------------------------------------------------
// Method 10: C(I,J)<M,repl> = A ; using S
// Method 18: C(I,J)<!M,repl> = A ; using S
//--------------------------------------------------------------------------
// Time: Optimal. Omega (nnz(A)+nnz(S)), since all entries in S+A must be
// traversed, and the corresponding entry in M (even if not present)
// determines the action to take. M can add a log(m) factor if sparse.
//--------------------------------------------------------------------------
// Parallel: A+S (Methods 02, 04, 09, 10, 11, 12, 14, 16, 18, 20)
//--------------------------------------------------------------------------
if (A_is_bitmap)
{
// all of IxJ must be examined
GB_SUBASSIGN_IXJ_SLICE ;
}
else
{
// traverse all A+S
GB_SUBASSIGN_TWO_SLICE (A, S) ;
}
//--------------------------------------------------------------------------
// phase 1: create zombies, update entries, and count pending tuples
//--------------------------------------------------------------------------
if (A_is_bitmap)
{
//----------------------------------------------------------------------
// phase1: A is bitmap
//----------------------------------------------------------------------
#pragma omp parallel for num_threads(nthreads) schedule(dynamic,1) \
reduction(+:nzombies)
for (taskid = 0 ; taskid < ntasks ; taskid++)
{
//------------------------------------------------------------------
// get the task descriptor
//------------------------------------------------------------------
GB_GET_IXJ_TASK_DESCRIPTOR_PHASE1 (iA_start, iA_end) ;
//------------------------------------------------------------------
// compute all vectors in this task
//------------------------------------------------------------------
for (int64_t j = kfirst ; j <= klast ; j++)
{
//--------------------------------------------------------------
// get S(iA_start:iA_end,j)
//--------------------------------------------------------------
GB_GET_VECTOR_FOR_IXJ (S, iA_start) ;
int64_t pA_start = j * Avlen ;
//--------------------------------------------------------------
// get M(:,j)
//--------------------------------------------------------------
int64_t pM_start, pM_end ;
GB_VECTOR_LOOKUP (pM_start, pM_end, M, j) ;
bool mjdense = (pM_end - pM_start) == Mvlen ;
//--------------------------------------------------------------
// do a 2-way merge of S(iA_start:iA_end,j) and A(ditto,j)
//--------------------------------------------------------------
for (int64_t iA = iA_start ; iA < iA_end ; iA++)
{
int64_t pA = pA_start + iA ;
bool Sfound = (pS < pS_end) && (GBI (Si, pS, Svlen) == iA) ;
bool Afound = Ab [pA] ;
if (Sfound && !Afound)
{
// S (i,j) is present but A (i,j) is not
// ----[C . 1] or [X . 1]-------------------------------
// [C . 1]: action: ( delete ): becomes zombie
// [X . 1]: action: ( X ): still zombie
// ----[C . 0] or [X . 0]-------------------------------
// [X . 0]: action: ( X ): still a zombie
// [C . 0]: C_repl: action: ( delete ): becomes zombie
GB_C_S_LOOKUP ;
GB_DELETE_ENTRY ;
GB_NEXT (S) ;
}
else if (!Sfound && Afound)
{
// S (i,j) is not present, A (i,j) is present
GB_MIJ_BINARY_SEARCH_OR_DENSE_LOOKUP (iA) ;
if (Mask_comp) mij = !mij ;
if (mij)
{
// ----[. A 1]--------------------------------------
// [. A 1]: action: ( insert )
task_pending++ ;
}
}
else if (Sfound && Afound)
{
// both S (i,j) and A (i,j) present
GB_MIJ_BINARY_SEARCH_OR_DENSE_LOOKUP (iA) ;
if (Mask_comp) mij = !mij ;
GB_C_S_LOOKUP ;
if (mij)
{
// ----[C A 1] or [X A 1]---------------------------
// [C A 1]: action: ( =A ): A to C no accum
// [X A 1]: action: ( undelete ): zombie lives
GB_noaccum_C_A_1_matrix ;
}
else
{
// ----[C A 0] or [X A 0]---------------------------
// [X A 0]: action: ( X ): still a zombie
// [C A 0]: C_repl: action: ( delete ): now zombie
GB_DELETE_ENTRY ;
}
GB_NEXT (S) ;
}
}
}
GB_PHASE1_TASK_WRAPUP ;
}
}
else
{
//----------------------------------------------------------------------
// phase1: A is hypersparse, sparse, or full
//----------------------------------------------------------------------
#pragma omp parallel for num_threads(nthreads) schedule(dynamic,1) \
reduction(+:nzombies)
for (taskid = 0 ; taskid < ntasks ; taskid++)
{
//------------------------------------------------------------------
// get the task descriptor
//------------------------------------------------------------------
GB_GET_TASK_DESCRIPTOR_PHASE1 ;
//------------------------------------------------------------------
// compute all vectors in this task
//------------------------------------------------------------------
for (int64_t k = kfirst ; k <= klast ; k++)
{
//--------------------------------------------------------------
// get A(:,j) and S(:,j)
//--------------------------------------------------------------
int64_t j = GBH (Zh, k) ;
GB_GET_MAPPED (pA, pA_end, pA, pA_end, Ap, j, k, Z_to_X, Avlen);
GB_GET_MAPPED (pS, pS_end, pB, pB_end, Sp, j, k, Z_to_S, Svlen);
//--------------------------------------------------------------
// get M(:,j)
//--------------------------------------------------------------
int64_t pM_start, pM_end ;
GB_VECTOR_LOOKUP (pM_start, pM_end, M, j) ;
bool mjdense = (pM_end - pM_start) == Mvlen ;
//--------------------------------------------------------------
// do a 2-way merge of S(:,j) and A(:,j)
//--------------------------------------------------------------
// jC = J [j] ; or J is a colon expression
// int64_t jC = GB_ijlist (J, j, Jkind, Jcolon) ;
// while both list S (:,j) and A (:,j) have entries
while (pS < pS_end && pA < pA_end)
{
int64_t iS = GBI (Si, pS, Svlen) ;
int64_t iA = GBI (Ai, pA, Avlen) ;
if (iS < iA)
{
// S (i,j) is present but A (i,j) is not
// ----[C . 1] or [X . 1]-------------------------------
// [C . 1]: action: ( delete ): becomes zombie
// [X . 1]: action: ( X ): still zombie
// ----[C . 0] or [X . 0]-------------------------------
// [X . 0]: action: ( X ): still a zombie
// [C . 0]: C_repl: action: ( delete ): becomes zombie
GB_C_S_LOOKUP ;
GB_DELETE_ENTRY ;
GB_NEXT (S) ;
}
else if (iA < iS)
{
// S (i,j) is not present, A (i,j) is present
GB_MIJ_BINARY_SEARCH_OR_DENSE_LOOKUP (iA) ;
if (Mask_comp) mij = !mij ;
if (mij)
{
// ----[. A 1]--------------------------------------
// [. A 1]: action: ( insert )
task_pending++ ;
}
GB_NEXT (A) ;
}
else
{
// both S (i,j) and A (i,j) present
GB_MIJ_BINARY_SEARCH_OR_DENSE_LOOKUP (iA) ;
if (Mask_comp) mij = !mij ;
GB_C_S_LOOKUP ;
if (mij)
{
// ----[C A 1] or [X A 1]---------------------------
// [C A 1]: action: ( =A ): A to C no accum
// [X A 1]: action: ( undelete ): zombie lives
GB_noaccum_C_A_1_matrix ;
}
else
{
// ----[C A 0] or [X A 0]---------------------------
// [X A 0]: action: ( X ): still a zombie
// [C A 0]: C_repl: action: ( delete ): now zombie
GB_DELETE_ENTRY ;
}
GB_NEXT (S) ;
GB_NEXT (A) ;
}
}
// while list S (:,j) has entries. List A (:,j) exhausted.
while (pS < pS_end)
{
// ----[C . 1] or [X . 1]-----------------------------------
// S (i,j) is present but A (i,j) is not
// [C . 1]: action: ( delete ): becomes zombie
// [X . 1]: action: ( X ): still a zombie
GB_C_S_LOOKUP ;
GB_DELETE_ENTRY ;
GB_NEXT (S) ;
}
// while list A (:,j) has entries. List S (:,j) exhausted.
while (pA < pA_end)
{
// S (i,j) is not present, A (i,j) is present
int64_t iA = GBI (Ai, pA, Avlen) ;
GB_MIJ_BINARY_SEARCH_OR_DENSE_LOOKUP (iA) ;
if (Mask_comp) mij = !mij ;
if (mij)
{
// ----[. A 1]------------------------------------------
// [. A 1]: action: ( insert )
task_pending++ ;
}
GB_NEXT (A) ;
}
}
GB_PHASE1_TASK_WRAPUP ;
}
}
//--------------------------------------------------------------------------
// phase 2: insert pending tuples
//--------------------------------------------------------------------------
GB_PENDING_CUMSUM ;
if (A_is_bitmap)
{
//----------------------------------------------------------------------
// phase2: A is bitmap
//----------------------------------------------------------------------
#pragma omp parallel for num_threads(nthreads) schedule(dynamic,1) \
reduction(&&:pending_sorted)
for (taskid = 0 ; taskid < ntasks ; taskid++)
{
//------------------------------------------------------------------
// get the task descriptor
//------------------------------------------------------------------
GB_GET_IXJ_TASK_DESCRIPTOR_PHASE2 (iA_start, iA_end) ;
//------------------------------------------------------------------
// compute all vectors in this task
//------------------------------------------------------------------
for (int64_t j = kfirst ; j <= klast ; j++)
{
//--------------------------------------------------------------
// get S(iA_start:iA_end,j)
//--------------------------------------------------------------
GB_GET_VECTOR_FOR_IXJ (S, iA_start) ;
int64_t pA_start = j * Avlen ;
//--------------------------------------------------------------
// get M(:,j)
//--------------------------------------------------------------
int64_t pM_start, pM_end ;
GB_VECTOR_LOOKUP (pM_start, pM_end, M, j) ;
bool mjdense = (pM_end - pM_start) == Mvlen ;
//--------------------------------------------------------------
// do a 2-way merge of S(iA_start:iA_end,j) and A(ditto,j)
//--------------------------------------------------------------
// jC = J [j] ; or J is a colon expression
int64_t jC = GB_ijlist (J, j, Jkind, Jcolon) ;
for (int64_t iA = iA_start ; iA < iA_end ; iA++)
{
int64_t pA = pA_start + iA ;
bool Sfound = (pS < pS_end) && (GBI (Si, pS, Svlen) == iA) ;
bool Afound = Ab [pA] ;
if (!Sfound && Afound)
{
// S (i,j) is not present, A (i,j) is present
GB_MIJ_BINARY_SEARCH_OR_DENSE_LOOKUP (iA) ;
if (Mask_comp) mij = !mij ;
if (mij)
{
// ----[. A 1]--------------------------------------
// [. A 1]: action: ( insert )
int64_t iC = GB_ijlist (I, iA, Ikind, Icolon) ;
GB_PENDING_INSERT (Ax +(pA*asize)) ;
}
}
else if (Sfound)
{
// S (i,j) present
GB_NEXT (S) ;
}
}
}
GB_PHASE2_TASK_WRAPUP ;
}
}
else
{
//----------------------------------------------------------------------
// phase2: A is hypersparse, sparse, or full
//----------------------------------------------------------------------
#pragma omp parallel for num_threads(nthreads) schedule(dynamic,1) \
reduction(&&:pending_sorted)
for (taskid = 0 ; taskid < ntasks ; taskid++)
{
//------------------------------------------------------------------
// get the task descriptor
//------------------------------------------------------------------
GB_GET_TASK_DESCRIPTOR_PHASE2 ;
//------------------------------------------------------------------
// compute all vectors in this task
//------------------------------------------------------------------
for (int64_t k = kfirst ; k <= klast ; k++)
{
//--------------------------------------------------------------
// get A(:,j) and S(:,j)
//--------------------------------------------------------------
int64_t j = GBH (Zh, k) ;
GB_GET_MAPPED (pA, pA_end, pA, pA_end, Ap, j, k, Z_to_X, Avlen);
GB_GET_MAPPED (pS, pS_end, pB, pB_end, Sp, j, k, Z_to_S, Svlen);
//--------------------------------------------------------------
// get M(:,j)
//--------------------------------------------------------------
int64_t pM_start, pM_end ;
GB_VECTOR_LOOKUP (pM_start, pM_end, M, j) ;
bool mjdense = (pM_end - pM_start) == Mvlen ;
//--------------------------------------------------------------
// do a 2-way merge of S(:,j) and A(:,j)
//--------------------------------------------------------------
// jC = J [j] ; or J is a colon expression
int64_t jC = GB_ijlist (J, j, Jkind, Jcolon) ;
// while both list S (:,j) and A (:,j) have entries
while (pS < pS_end && pA < pA_end)
{
int64_t iS = GBI (Si, pS, Svlen) ;
int64_t iA = GBI (Ai, pA, Avlen) ;
if (iS < iA)
{
// S (i,j) is present but A (i,j) is not
GB_NEXT (S) ;
}
else if (iA < iS)
{
// S (i,j) is not present, A (i,j) is present
GB_MIJ_BINARY_SEARCH_OR_DENSE_LOOKUP (iA) ;
if (Mask_comp) mij = !mij ;
if (mij)
{
// ----[. A 1]--------------------------------------
// [. A 1]: action: ( insert )
int64_t iC = GB_ijlist (I, iA, Ikind, Icolon) ;
GB_PENDING_INSERT (Ax +(pA*asize)) ;
}
GB_NEXT (A) ;
}
else
{
// both S (i,j) and A (i,j) present
GB_NEXT (S) ;
GB_NEXT (A) ;
}
}
// while list A (:,j) has entries. List S (:,j) exhausted.
while (pA < pA_end)
{
// S (i,j) is not present, A (i,j) is present
int64_t iA = GBI (Ai, pA, Avlen) ;
GB_MIJ_BINARY_SEARCH_OR_DENSE_LOOKUP (iA) ;
if (Mask_comp) mij = !mij ;
if (mij)
{
// ----[. A 1]------------------------------------------
// [. A 1]: action: ( insert )
int64_t iC = GB_ijlist (I, iA, Ikind, Icolon) ;
GB_PENDING_INSERT (Ax +(pA*asize)) ;
}
GB_NEXT (A) ;
}
}
GB_PHASE2_TASK_WRAPUP ;
}
}
//--------------------------------------------------------------------------
// finalize the matrix and return result
//--------------------------------------------------------------------------
GB_SUBASSIGN_WRAPUP ;
}
|
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 1999-2021 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/accelerate-private.h"
#include "MagickCore/annotate.h"
#include "MagickCore/artifact.h"
#include "MagickCore/attribute.h"
#include "MagickCore/cache.h"
#include "MagickCore/cache-view.h"
#include "MagickCore/channel.h"
#include "MagickCore/color.h"
#include "MagickCore/color-private.h"
#include "MagickCore/colorspace-private.h"
#include "MagickCore/composite.h"
#include "MagickCore/decorate.h"
#include "MagickCore/distort.h"
#include "MagickCore/draw.h"
#include "MagickCore/effect.h"
#include "MagickCore/enhance.h"
#include "MagickCore/exception.h"
#include "MagickCore/exception-private.h"
#include "MagickCore/fx.h"
#include "MagickCore/fx-private.h"
#include "MagickCore/gem.h"
#include "MagickCore/gem-private.h"
#include "MagickCore/geometry.h"
#include "MagickCore/layer.h"
#include "MagickCore/list.h"
#include "MagickCore/log.h"
#include "MagickCore/image.h"
#include "MagickCore/image-private.h"
#include "MagickCore/magick.h"
#include "MagickCore/memory_.h"
#include "MagickCore/memory-private.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/property.h"
#include "MagickCore/quantum.h"
#include "MagickCore/quantum-private.h"
#include "MagickCore/random_.h"
#include "MagickCore/random-private.h"
#include "MagickCore/resample.h"
#include "MagickCore/resample-private.h"
#include "MagickCore/resize.h"
#include "MagickCore/resource_.h"
#include "MagickCore/splay-tree.h"
#include "MagickCore/statistic.h"
#include "MagickCore/string_.h"
#include "MagickCore/string-private.h"
#include "MagickCore/thread-private.h"
#include "MagickCore/threshold.h"
#include "MagickCore/token.h"
#include "MagickCore/transform.h"
#include "MagickCore/transform-private.h"
#include "MagickCore/utility.h"
/*
Typedef declarations.
*/
typedef enum
{
BitwiseAndAssignmentOperator = 0xd9U,
BitwiseOrAssignmentOperator,
LeftShiftAssignmentOperator,
RightShiftAssignmentOperator,
PowerAssignmentOperator,
ModuloAssignmentOperator,
PlusAssignmentOperator,
SubtractAssignmentOperator,
MultiplyAssignmentOperator,
DivideAssignmentOperator,
IncrementAssignmentOperator,
DecrementAssignmentOperator,
LeftShiftOperator,
RightShiftOperator,
LessThanEqualOperator,
GreaterThanEqualOperator,
EqualOperator,
NotEqualOperator,
LogicalAndOperator,
LogicalOrOperator,
ExponentialNotation
} FxOperator;
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 *images,const char *expression,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o images: the image sequence.
%
% o expression: the expression.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickPrivate FxInfo *AcquireFxInfo(const Image *images,const char *expression,
ExceptionInfo *exception)
{
const Image
*next;
FxInfo
*fx_info;
ssize_t
i;
unsigned char
fx_op[2];
fx_info=(FxInfo *) AcquireCriticalMemory(sizeof(*fx_info));
(void) memset(fx_info,0,sizeof(*fx_info));
fx_info->exception=AcquireExceptionInfo();
fx_info->images=images;
fx_info->colors=NewSplayTree(CompareSplayTreeString,RelinquishMagickMemory,
RelinquishMagickMemory);
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,exception);
i++;
}
fx_info->random_info=AcquireRandomInfo();
fx_info->expression=ConstantString(expression);
fx_info->file=stderr;
/*
Convert compound to simple operators.
*/
fx_op[1]='\0';
*fx_op=(unsigned char) BitwiseAndAssignmentOperator;
(void) SubstituteString(&fx_info->expression,"&=",(char *) fx_op);
*fx_op=(unsigned char) BitwiseOrAssignmentOperator;
(void) SubstituteString(&fx_info->expression,"|=",(char *) fx_op);
*fx_op=(unsigned char) LeftShiftAssignmentOperator;
(void) SubstituteString(&fx_info->expression,"<<=",(char *) fx_op);
*fx_op=(unsigned char) RightShiftAssignmentOperator;
(void) SubstituteString(&fx_info->expression,">>=",(char *) fx_op);
*fx_op=(unsigned char) PowerAssignmentOperator;
(void) SubstituteString(&fx_info->expression,"^=",(char *) fx_op);
*fx_op=(unsigned char) ModuloAssignmentOperator;
(void) SubstituteString(&fx_info->expression,"%=",(char *) fx_op);
*fx_op=(unsigned char) PlusAssignmentOperator;
(void) SubstituteString(&fx_info->expression,"+=",(char *) fx_op);
*fx_op=(unsigned char) SubtractAssignmentOperator;
(void) SubstituteString(&fx_info->expression,"-=",(char *) fx_op);
*fx_op=(unsigned char) MultiplyAssignmentOperator;
(void) SubstituteString(&fx_info->expression,"*=",(char *) fx_op);
*fx_op=(unsigned char) DivideAssignmentOperator;
(void) SubstituteString(&fx_info->expression,"/=",(char *) fx_op);
*fx_op=(unsigned char) IncrementAssignmentOperator;
(void) SubstituteString(&fx_info->expression,"++",(char *) fx_op);
*fx_op=(unsigned char) DecrementAssignmentOperator;
(void) SubstituteString(&fx_info->expression,"--",(char *) fx_op);
*fx_op=(unsigned char) LeftShiftOperator;
(void) SubstituteString(&fx_info->expression,"<<",(char *) fx_op);
*fx_op=(unsigned char) RightShiftOperator;
(void) SubstituteString(&fx_info->expression,">>",(char *) fx_op);
*fx_op=(unsigned char) LessThanEqualOperator;
(void) SubstituteString(&fx_info->expression,"<=",(char *) fx_op);
*fx_op=(unsigned char) GreaterThanEqualOperator;
(void) SubstituteString(&fx_info->expression,">=",(char *) fx_op);
*fx_op=(unsigned char) EqualOperator;
(void) SubstituteString(&fx_info->expression,"==",(char *) fx_op);
*fx_op=(unsigned char) NotEqualOperator;
(void) SubstituteString(&fx_info->expression,"!=",(char *) fx_op);
*fx_op=(unsigned char) LogicalAndOperator;
(void) SubstituteString(&fx_info->expression,"&&",(char *) fx_op);
*fx_op=(unsigned char) LogicalOrOperator;
(void) SubstituteString(&fx_info->expression,"||",(char *) fx_op);
*fx_op=(unsigned char) ExponentialNotation;
(void) SubstituteString(&fx_info->expression,"**",(char *) fx_op);
/*
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-");
(void) SubstituteString(&fx_info->expression," ",""); /* compact string */
return(fx_info);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
+ 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.
%
*/
MagickPrivate FxInfo *DestroyFxInfo(FxInfo *fx_info)
{
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:
%
% double FxEvaluateChannelExpression(FxInfo *fx_info,
% const PixelChannel channel,const ssize_t x,const ssize_t y,
% double *alpha,Exceptioninfo *exception)
% double 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 inline const double *GetFxSymbolValue(FxInfo *magick_restrict fx_info,
const char *symbol)
{
return((const double *) GetValueFromSplayTree(fx_info->symbols,symbol));
}
static inline MagickBooleanType SetFxSymbolValue(
FxInfo *magick_restrict fx_info,const char *magick_restrict symbol,
double const value)
{
double
*object;
object=(double *) GetValueFromSplayTree(fx_info->symbols,symbol);
if (object != (double *) NULL)
{
*object=value;
return(MagickTrue);
}
object=(double *) AcquireMagickMemory(sizeof(*object));
if (object == (double *) NULL)
{
(void) ThrowMagickException(fx_info->exception,GetMagickModule(),
ResourceLimitError,"MemoryAllocationFailed","`%s'",
fx_info->images->filename);
return(MagickFalse);
}
*object=value;
return(AddValueToSplayTree(fx_info->symbols,ConstantString(symbol),object));
}
static double FxChannelStatistics(FxInfo *fx_info,Image *image,
PixelChannel channel,const char *symbol,ExceptionInfo *exception)
{
ChannelType
channel_mask;
char
key[MagickPathExtent];
const double
*value;
double
statistic;
const char
*p;
channel_mask=UndefinedChannel;
for (p=symbol; (*p != '.') && (*p != '\0'); p++) ;
if (*p == '.')
{
ssize_t
option;
option=ParseCommandOption(MagickPixelChannelOptions,MagickTrue,p+1);
if (option >= 0)
{
channel=(PixelChannel) option;
channel_mask=SetPixelChannelMask(image,(ChannelType)
(1UL << channel));
}
}
(void) FormatLocaleString(key,MagickPathExtent,"%p.%.20g.%s",(void *) image,
(double) channel,symbol);
value=GetFxSymbolValue(fx_info,key);
if (value != (const double *) NULL)
{
if (channel_mask != UndefinedChannel)
(void) SetPixelChannelMask(image,channel_mask);
return(QuantumScale*(*value));
}
statistic=0.0;
if (LocaleNCompare(symbol,"depth",5) == 0)
{
size_t
depth;
depth=GetImageDepth(image,exception);
statistic=(double) depth;
}
if (LocaleNCompare(symbol,"kurtosis",8) == 0)
{
double
kurtosis,
skewness;
(void) GetImageKurtosis(image,&kurtosis,&skewness,exception);
statistic=kurtosis;
}
if (LocaleNCompare(symbol,"maxima",6) == 0)
{
double
maxima,
minima;
(void) GetImageRange(image,&minima,&maxima,exception);
statistic=maxima;
}
if (LocaleNCompare(symbol,"mean",4) == 0)
{
double
mean,
standard_deviation;
(void) GetImageMean(image,&mean,&standard_deviation,exception);
statistic=mean;
}
if (LocaleNCompare(symbol,"median",6) == 0)
{
double
median;
(void) GetImageMedian(image,&median,exception);
statistic=median;
}
if (LocaleNCompare(symbol,"minima",6) == 0)
{
double
maxima,
minima;
(void) GetImageRange(image,&minima,&maxima,exception);
statistic=minima;
}
if (LocaleNCompare(symbol,"skewness",8) == 0)
{
double
kurtosis,
skewness;
(void) GetImageKurtosis(image,&kurtosis,&skewness,exception);
statistic=skewness;
}
if (LocaleNCompare(symbol,"standard_deviation",18) == 0)
{
double
mean,
standard_deviation;
(void) GetImageMean(image,&mean,&standard_deviation,exception);
statistic=standard_deviation;
}
if (channel_mask != UndefinedChannel)
(void) SetPixelChannelMask(image,channel_mask);
if (SetFxSymbolValue(fx_info,key,statistic) == MagickFalse)
return(0.0);
return(QuantumScale*statistic);
}
static double
FxEvaluateSubexpression(FxInfo *,const PixelChannel,const ssize_t,
const ssize_t,const char *,const size_t,double *,ExceptionInfo *);
static inline MagickBooleanType IsFxFunction(const char *expression,
const char *name,const size_t length)
{
int
c;
size_t
i;
for (i=0; i <= length; i++)
if (expression[i] == '\0')
return(MagickFalse);
c=expression[length];
if ((LocaleNCompare(expression,name,length) == 0) &&
((isspace((int) ((unsigned char) c)) == 0) || (c == '(')))
return(MagickTrue);
return(MagickFalse);
}
static inline double FxGCD(const double alpha,const double beta)
{
if (alpha < beta)
return(FxGCD(beta,alpha));
if (fabs(beta) < 0.001)
return(alpha);
return(FxGCD(beta,alpha-beta*floor(alpha/beta)));
}
static inline const char *FxSubexpression(const char *expression,
ExceptionInfo *exception)
{
const char
*subexpression;
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 PixelChannel channel,
const ssize_t x,const ssize_t y,const char *expression,const size_t depth,
ExceptionInfo *exception)
{
char
*q,
symbol[MagickPathExtent];
const char
*artifact,
*p;
const double
*value;
double
alpha,
beta;
Image
*image;
MagickBooleanType
status;
PixelInfo
pixel;
PointInfo
point;
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);
GetPixelInfo(image,&pixel);
status=InterpolatePixelInfo(image,fx_info->view[i],image->interpolate,
point.x,point.y,&pixel,exception);
(void) status;
if ((*p != '\0') && (*(p+1) != '\0') && (*(p+2) != '\0') &&
(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[MagickPathExtent];
size_t
length;
(void) CopyMagickString(name,p,MagickPathExtent);
length=strlen(name);
for (q=name+length-1; q > name; q--)
{
if (*q == ')')
break;
if (*q == '.')
{
*q='\0';
break;
}
}
q=name;
if ((*q != '\0') && (*(q+1) != '\0') && (*(q+2) != '\0') &&
(GetFxSymbolValue(fx_info,name) == (const double *) NULL))
{
PixelInfo
*color;
color=(PixelInfo *) GetValueFromSplayTree(fx_info->colors,name);
if (color != (PixelInfo *) NULL)
{
pixel=(*color);
p+=length;
}
else
{
status=QueryColorCompliance(name,AllCompliance,&pixel,
fx_info->exception);
if (status != MagickFalse)
{
(void) AddValueToSplayTree(fx_info->colors,
ConstantString(name),ClonePixelInfo(&pixel));
p+=length;
}
}
}
}
(void) CopyMagickString(symbol,p,MagickPathExtent);
(void) StripMagickString(symbol);
if (*symbol == '\0')
{
switch (channel)
{
case RedPixelChannel: return(QuantumScale*pixel.red);
case GreenPixelChannel: return(QuantumScale*pixel.green);
case BluePixelChannel: return(QuantumScale*pixel.blue);
case BlackPixelChannel:
{
if (image->colorspace != CMYKColorspace)
{
(void) ThrowMagickException(exception,GetMagickModule(),
ImageError,"ColorSeparatedImageRequired","`%s'",
image->filename);
return(0.0);
}
return(QuantumScale*pixel.black);
}
case AlphaPixelChannel:
{
if (pixel.alpha_trait == UndefinedPixelTrait)
return(1.0);
alpha=(double) (QuantumScale*pixel.alpha);
return(alpha);
}
case CompositePixelChannel:
{
Quantum
quantum_pixel[MaxPixelChannels];
SetPixelViaPixelInfo(image,&pixel,quantum_pixel);
return(QuantumScale*GetPixelIntensity(image,quantum_pixel));
}
case IndexPixelChannel:
return(0.0);
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((QuantumScale*pixel.alpha));
break;
}
case 'B':
case 'b':
{
if (LocaleCompare(symbol,"b") == 0)
return(QuantumScale*pixel.blue);
break;
}
case 'C':
case 'c':
{
if (IsFxFunction(symbol,"channel",7) != MagickFalse)
{
GeometryInfo
channel_info;
MagickStatusType
flags;
flags=ParseGeometry(symbol+7,&channel_info);
if (image->colorspace == CMYKColorspace)
switch (channel)
{
case CyanPixelChannel:
{
if ((flags & RhoValue) == 0)
return(0.0);
return(channel_info.rho);
}
case MagentaPixelChannel:
{
if ((flags & SigmaValue) == 0)
return(0.0);
return(channel_info.sigma);
}
case YellowPixelChannel:
{
if ((flags & XiValue) == 0)
return(0.0);
return(channel_info.xi);
}
case BlackPixelChannel:
{
if ((flags & PsiValue) == 0)
return(0.0);
return(channel_info.psi);
}
case AlphaPixelChannel:
{
if ((flags & ChiValue) == 0)
return(0.0);
return(channel_info.chi);
}
default:
return(0.0);
}
switch (channel)
{
case RedPixelChannel:
{
if ((flags & RhoValue) == 0)
return(0.0);
return(channel_info.rho);
}
case GreenPixelChannel:
{
if ((flags & SigmaValue) == 0)
return(0.0);
return(channel_info.sigma);
}
case BluePixelChannel:
{
if ((flags & XiValue) == 0)
return(0.0);
return(channel_info.xi);
}
case BlackPixelChannel:
{
if ((flags & ChiValue) == 0)
return(0.0);
return(channel_info.chi);
}
case AlphaPixelChannel:
{
if ((flags & PsiValue) == 0)
return(0.0);
return(channel_info.psi);
}
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.black);
}
break;
}
case 'H':
case 'h':
{
if (LocaleCompare(symbol,"h") == 0)
return((double) image->rows);
if (LocaleCompare(symbol,"hue") == 0)
{
double
hue,
lightness,
saturation;
ConvertRGBToHSL(pixel.red,pixel.green,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->resolution.x);
if (LocaleCompare(symbol,"image.resolution.y") == 0)
return(image->resolution.y);
if (LocaleCompare(symbol,"intensity") == 0)
{
Quantum
quantum_pixel[MaxPixelChannels];
SetPixelViaPixelInfo(image,&pixel,quantum_pixel);
return(QuantumScale*GetPixelIntensity(image,quantum_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(pixel.red,pixel.green,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
luminence;
luminence=0.212656*pixel.red+0.715158*pixel.green+0.072186*pixel.blue;
return(QuantumScale*luminence);
}
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,"median",6) == 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.alpha);
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->resolution.x)*image->columns);
if (LocaleCompare(symbol,"printsize.y") == 0)
return(PerceptibleReciprocal(image->resolution.y)*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->resolution.x);
if (LocaleCompare(symbol,"resolution.y") == 0)
return(image->resolution.y);
if (LocaleCompare(symbol,"r") == 0)
return(QuantumScale*pixel.red);
break;
}
case 'S':
case 's':
{
if (LocaleCompare(symbol,"saturation") == 0)
{
double
hue,
lightness,
saturation;
ConvertRGBToHSL(pixel.red,pixel.green,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)
return((double) GetImageDepth(image,fx_info->exception));
break;
}
default:
break;
}
value=GetFxSymbolValue(fx_info,symbol);
if (value != (const double *) NULL)
return(*value);
artifact=GetImageArtifact(image,symbol);
if (artifact != (const char *) NULL)
return(StringToDouble(artifact,(char **) NULL));
(void) ThrowMagickException(exception,GetMagickModule(),OptionError,
"UndefinedVariable","`%s'",symbol);
(void) SetFxSymbolValue(fx_info,symbol,0.0);
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;
const char
*subexpression;
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 (IsFxFunction(expression,"acosh",5) != MagickFalse)
{
expression+=5;
break;
}
#endif
#if defined(MAGICKCORE_HAVE_ASINH)
if (IsFxFunction(expression,"asinh",5) != MagickFalse)
{
expression+=5;
break;
}
#endif
#if defined(MAGICKCORE_HAVE_ATANH)
if (IsFxFunction(expression,"atanh",5) != MagickFalse)
{
expression+=5;
break;
}
#endif
if (IsFxFunction(expression,"atan2",5) != MagickFalse)
{
expression+=5;
break;
}
break;
}
case 'E':
case 'e':
{
if ((isdigit((int) ((unsigned char) c)) != 0) &&
((LocaleNCompare(expression,"E+",2) == 0) ||
(LocaleNCompare(expression,"E-",2) == 0)))
{
expression+=2; /* scientific notation */
break;
}
}
case 'J':
case 'j':
{
if ((IsFxFunction(expression,"j0",2) != MagickFalse) ||
(IsFxFunction(expression,"j1",2) != MagickFalse))
{
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((int) ((unsigned char) c)) != 0) ||
(strchr(")",c) != (char *) NULL))) &&
(((islower((int) ((unsigned char) *expression)) != 0) ||
(strchr("(",(int) ((unsigned char) *expression)) != (char *) NULL)) ||
((isdigit((int) ((unsigned char) 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((int) ((unsigned char) c)) != 0))
precedence=AdditionPrecedence;
break;
}
case BitwiseAndAssignmentOperator:
case BitwiseOrAssignmentOperator:
case LeftShiftAssignmentOperator:
case RightShiftAssignmentOperator:
case PowerAssignmentOperator:
case ModuloAssignmentOperator:
case PlusAssignmentOperator:
case SubtractAssignmentOperator:
case MultiplyAssignmentOperator:
case DivideAssignmentOperator:
case IncrementAssignmentOperator:
case DecrementAssignmentOperator:
{
precedence=AssignmentPrecedence;
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 PixelChannel 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); \
}
#define FxParseConditional(subexpression,sentinal,p,q) \
{ \
p=subexpression; \
for (q=(char *) p; (*q != (sentinal)) && (*q != '\0'); q++) \
if (*q == '(') \
{ \
for (q++; (*q != ')') && (*q != '\0'); q++); \
if (*q == '\0') \
break; \
} \
if (*q == '\0') \
{ \
(void) ThrowMagickException(exception,GetMagickModule(), \
OptionError,"UnableToParseExpression","`%s'",subexpression); \
FxReturn(0.0); \
} \
if (strlen(q) == 1) \
*(q+1)='\0'; \
*q='\0'; \
}
char
*q,
*subexpression;
double
alpha,
gamma,
sans,
value;
const char
*p;
*beta=0.0;
sans=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);
FxReturn(fmod(alpha,*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 BitwiseAndAssignmentOperator:
{
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);
value=(double) ((size_t) (alpha+0.5) & (size_t) (*beta+0.5));
if (SetFxSymbolValue(fx_info,subexpression,value) == MagickFalse)
return(0.0);
FxReturn(*beta);
}
case BitwiseOrAssignmentOperator:
{
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);
value=(double) ((size_t) (alpha+0.5) | (size_t) (*beta+0.5));
if (SetFxSymbolValue(fx_info,subexpression,value) == MagickFalse)
return(0.0);
FxReturn(*beta);
}
case LeftShiftAssignmentOperator:
{
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);
if ((size_t) (*beta+0.5) >= (8*sizeof(size_t)))
{
(void) ThrowMagickException(exception,GetMagickModule(),
OptionError,"ShiftCountOverflow","`%s'",subexpression);
FxReturn(0.0);
}
value=(double) ((size_t) (alpha+0.5) << (size_t) (*beta+0.5));
if (SetFxSymbolValue(fx_info,subexpression,value) == MagickFalse)
return(0.0);
FxReturn(*beta);
}
case RightShiftAssignmentOperator:
{
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);
if ((size_t) (*beta+0.5) >= (8*sizeof(size_t)))
{
(void) ThrowMagickException(exception,GetMagickModule(),
OptionError,"ShiftCountOverflow","`%s'",subexpression);
FxReturn(0.0);
}
value=(double) ((size_t) (alpha+0.5) >> (size_t) (*beta+0.5));
if (SetFxSymbolValue(fx_info,subexpression,value) == MagickFalse)
return(0.0);
FxReturn(*beta);
}
case PowerAssignmentOperator:
{
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);
value=pow(alpha,*beta);
if (SetFxSymbolValue(fx_info,subexpression,value) == MagickFalse)
return(0.0);
FxReturn(*beta);
}
case ModuloAssignmentOperator:
{
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);
value=fmod(alpha,*beta);
if (SetFxSymbolValue(fx_info,subexpression,value) == MagickFalse)
return(0.0);
FxReturn(*beta);
}
case PlusAssignmentOperator:
{
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);
value=alpha+(*beta);
if (SetFxSymbolValue(fx_info,subexpression,value) == MagickFalse)
return(0.0);
FxReturn(*beta);
}
case SubtractAssignmentOperator:
{
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);
value=alpha-(*beta);
if (SetFxSymbolValue(fx_info,subexpression,value) == MagickFalse)
return(0.0);
FxReturn(*beta);
}
case MultiplyAssignmentOperator:
{
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);
value=alpha*(*beta);
if (SetFxSymbolValue(fx_info,subexpression,value) == MagickFalse)
return(0.0);
FxReturn(*beta);
}
case DivideAssignmentOperator:
{
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);
value=alpha*PerceptibleReciprocal(*beta);
if (SetFxSymbolValue(fx_info,subexpression,value) == MagickFalse)
return(0.0);
FxReturn(*beta);
}
case IncrementAssignmentOperator:
{
if (*subexpression == '\0')
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
value=alpha+1.0;
if (*subexpression == '\0')
{
if (SetFxSymbolValue(fx_info,p,value) == MagickFalse)
return(0.0);
}
else
if (SetFxSymbolValue(fx_info,subexpression,value) == MagickFalse)
return(0.0);
FxReturn(*beta);
}
case DecrementAssignmentOperator:
{
if (*subexpression == '\0')
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,++p,depth+1,beta,
exception);
value=alpha-1.0;
if (*subexpression == '\0')
{
if (SetFxSymbolValue(fx_info,p,value) == MagickFalse)
return(0.0);
}
else
if (SetFxSymbolValue(fx_info,subexpression,value) == MagickFalse)
return(0.0);
FxReturn(*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 '?':
{
(void) CopyMagickString(subexpression,++p,MagickPathExtent-1);
FxParseConditional(subexpression,':',p,q);
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+1,depth+1,beta,
exception);
FxReturn(gamma);
}
case '=':
{
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);
value=(*beta);
if (SetFxSymbolValue(fx_info,subexpression,value) == MagickFalse)
return(0.0);
FxReturn(*beta);
}
case ',':
{
*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)
{
size_t
length;
if (depth >= FxMaxParenthesisDepth)
(void) ThrowMagickException(exception,GetMagickModule(),OptionError,
"ParenthesisNestedTooDeeply","`%s'",expression);
length=CopyMagickString(subexpression,expression+1,MagickPathExtent);
if (length != 0)
subexpression[length-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 (IsFxFunction(expression,"abs",3) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn(fabs(alpha));
}
#if defined(MAGICKCORE_HAVE_ACOSH)
if (IsFxFunction(expression,"acosh",5) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
FxReturn(acosh(alpha));
}
#endif
if (IsFxFunction(expression,"acos",4) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
FxReturn(acos(alpha));
}
#if defined(MAGICKCORE_HAVE_J1)
if (IsFxFunction(expression,"airy",4) != MagickFalse)
{
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 (IsFxFunction(expression,"asinh",5) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
FxReturn(asinh(alpha));
}
#endif
if (IsFxFunction(expression,"asin",4) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
FxReturn(asin(alpha));
}
if (IsFxFunction(expression,"alt",3) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn(((ssize_t) alpha) & 0x01 ? -1.0 : 1.0);
}
if (IsFxFunction(expression,"atan2",5) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
FxReturn(atan2(alpha,*beta));
}
#if defined(MAGICKCORE_HAVE_ATANH)
if (IsFxFunction(expression,"atanh",5) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
FxReturn(atanh(alpha));
}
#endif
if (IsFxFunction(expression,"atan",4) != MagickFalse)
{
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 (IsFxFunction(expression,"ceil",4) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
FxReturn(ceil(alpha));
}
if (IsFxFunction(expression,"clamp",5) != MagickFalse)
{
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 (IsFxFunction(expression,"cosh",4) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
FxReturn(cosh(alpha));
}
if (IsFxFunction(expression,"cos",3) != MagickFalse)
{
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 (IsFxFunction(expression,"debug",5) != MagickFalse)
{
const char
*type;
size_t
length;
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
switch (fx_info->images->colorspace)
{
case CMYKColorspace:
{
switch (channel)
{
case CyanPixelChannel: type="cyan"; break;
case MagentaPixelChannel: type="magenta"; break;
case YellowPixelChannel: type="yellow"; break;
case AlphaPixelChannel: type="alpha"; break;
case BlackPixelChannel: type="black"; break;
default: type="unknown"; break;
}
break;
}
case GRAYColorspace:
{
switch (channel)
{
case RedPixelChannel: type="gray"; break;
case AlphaPixelChannel: type="alpha"; break;
default: type="unknown"; break;
}
break;
}
default:
{
switch (channel)
{
case RedPixelChannel: type="red"; break;
case GreenPixelChannel: type="green"; break;
case BluePixelChannel: type="blue"; break;
case AlphaPixelChannel: type="alpha"; break;
default: type="unknown"; break;
}
break;
}
}
*subexpression='\0';
length=1;
if (strlen(expression) > 6)
length=CopyMagickString(subexpression,expression+6,
MagickPathExtent);
if (length != 0)
subexpression[length-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(),alpha);
FxReturn(alpha);
}
if (IsFxFunction(expression,"do",2) != MagickFalse)
{
size_t
length;
/*
Parse do(expression,condition test).
*/
length=CopyMagickString(subexpression,expression+3,
MagickPathExtent-1);
if (length != 0)
subexpression[length-1]='\0';
FxParseConditional(subexpression,',',p,q);
for (alpha=0.0; ; )
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,q+1,depth+1,beta,
exception);
gamma=FxEvaluateSubexpression(fx_info,channel,x,y,p,depth+1,&sans,
exception);
if (fabs(gamma) < MagickEpsilon)
break;
}
FxReturn(alpha);
}
if (IsFxFunction(expression,"drc",3) != MagickFalse)
{
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 (IsFxFunction(expression,"erf",3) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn(erf(alpha));
}
#endif
if (IsFxFunction(expression,"exp",3) != MagickFalse)
{
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 (IsFxFunction(expression,"floor",5) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
FxReturn(floor(alpha));
}
if (IsFxFunction(expression,"for",3) != MagickFalse)
{
size_t
length;
/*
Parse for(initialization, condition test, expression).
*/
length=CopyMagickString(subexpression,expression+4,
MagickPathExtent-1);
if (length != 0)
subexpression[length-1]='\0';
FxParseConditional(subexpression,',',p,q);
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,p,depth+1,&sans,
exception);
(void) CopyMagickString(subexpression,q+1,MagickPathExtent-1);
FxParseConditional(subexpression,',',p,q);
for (alpha=0.0; ; )
{
gamma=FxEvaluateSubexpression(fx_info,channel,x,y,p,depth+1,&sans,
exception);
if (fabs(gamma) < MagickEpsilon)
break;
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,q+1,depth+1,beta,
exception);
}
FxReturn(alpha);
}
break;
}
case 'G':
case 'g':
{
if (IsFxFunction(expression,"gauss",5) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
FxReturn(exp((-alpha*alpha/2.0))/sqrt(2.0*MagickPI));
}
if (IsFxFunction(expression,"gcd",3) != MagickFalse)
{
double
gcd;
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
if (IsNaN(alpha))
FxReturn(alpha);
gcd=FxGCD(alpha,*beta);
FxReturn(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 (IsFxFunction(expression,"hypot",5) != MagickFalse)
{
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 (IsFxFunction(expression,"if",2) != MagickFalse)
{
size_t
length;
/*
Parse if(condition test, true-expression, false-expression).
*/
length=CopyMagickString(subexpression,expression+3,
MagickPathExtent-1);
if (length != 0)
subexpression[length-1]='\0';
FxParseConditional(subexpression,',',p,q);
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,p,depth+1,&sans,
exception);
(void) CopyMagickString(subexpression,q+1,MagickPathExtent-1);
FxParseConditional(subexpression,',',p,q);
if (fabs(alpha) >= MagickEpsilon)
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,p,depth+1,beta,
exception);
else
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,q+1,depth+1,beta,
exception);
FxReturn(alpha);
}
if (LocaleCompare(expression,"intensity") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
if (IsFxFunction(expression,"int",3) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn(floor(alpha));
}
if (IsFxFunction(expression,"isnan",5) != MagickFalse)
{
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 (IsFxFunction(expression,"j0",2) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+2,
depth+1,beta,exception);
FxReturn(j0(alpha));
}
#endif
#if defined(MAGICKCORE_HAVE_J1)
if (IsFxFunction(expression,"j1",2) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+2,
depth+1,beta,exception);
FxReturn(j1(alpha));
}
#endif
#if defined(MAGICKCORE_HAVE_J1)
if (IsFxFunction(expression,"jinc",4) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
if (alpha == 0.0)
FxReturn(1.0);
FxReturn((2.0*j1((MagickPI*alpha))/(MagickPI*alpha)));
}
#endif
break;
}
case 'L':
case 'l':
{
if (IsFxFunction(expression,"ln",2) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+2,
depth+1,beta,exception);
FxReturn(log(alpha));
}
if (IsFxFunction(expression,"logtwo",6) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+6,
depth+1,beta,exception);
FxReturn(log10(alpha)/log10(2.0));
}
if (IsFxFunction(expression,"log",3) != MagickFalse)
{
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(QuantumRange);
if (LocaleNCompare(expression,"maxima",6) == 0)
break;
if (IsFxFunction(expression,"max",3) != MagickFalse)
{
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 (IsFxFunction(expression,"min",3) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn(alpha < *beta ? alpha : *beta);
}
if (IsFxFunction(expression,"mod",3) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn(alpha-floor((alpha*PerceptibleReciprocal(*beta)))*(*beta));
}
if (LocaleCompare(expression,"m") == 0)
FxReturn(FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception));
break;
}
case 'N':
case 'n':
{
if (IsFxFunction(expression,"not",3) != MagickFalse)
{
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 (IsFxFunction(expression,"pow",3) != MagickFalse)
{
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(QuantumRange);
if (LocaleCompare(expression,"QuantumScale") == 0)
FxReturn(QuantumScale);
break;
}
case 'R':
case 'r':
{
if (IsFxFunction(expression,"rand",4) != MagickFalse)
{
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_FxEvaluateSubexpression)
#endif
alpha=GetPseudoRandomValue(fx_info->random_info);
FxReturn(alpha);
}
if (IsFxFunction(expression,"round",5) != MagickFalse)
{
/*
Round the fraction to nearest integer.
*/
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+5,
depth+1,beta,exception);
if ((alpha-floor(alpha)) < (ceil(alpha)-alpha))
FxReturn(floor(alpha));
FxReturn(ceil(alpha));
}
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 (IsFxFunction(expression,"sign",4) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
FxReturn(alpha < 0.0 ? -1.0 : 1.0);
}
if (IsFxFunction(expression,"sinc",4) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
if (alpha == 0)
FxReturn(1.0);
FxReturn(sin((MagickPI*alpha))/(MagickPI*alpha));
}
if (IsFxFunction(expression,"sinh",4) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
FxReturn(sinh(alpha));
}
if (IsFxFunction(expression,"sin",3) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+3,
depth+1,beta,exception);
FxReturn(sin(alpha));
}
if (IsFxFunction(expression,"sqrt",4) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
FxReturn(sqrt(alpha));
}
if (IsFxFunction(expression,"squish",6) != MagickFalse)
{
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 (IsFxFunction(expression,"tanh",4) != MagickFalse)
{
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,expression+4,
depth+1,beta,exception);
FxReturn(tanh(alpha));
}
if (IsFxFunction(expression,"tan",3) != MagickFalse)
{
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 (IsFxFunction(expression,"trunc",5) != MagickFalse)
{
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 (IsFxFunction(expression,"while",5) != MagickFalse)
{
size_t
length;
/*
Parse while(condition test, expression).
*/
length=CopyMagickString(subexpression,expression+6,
MagickPathExtent-1);
if (length != 0)
subexpression[length-1]='\0';
FxParseConditional(subexpression,',',p,q);
for (alpha=0.0; ; )
{
gamma=FxEvaluateSubexpression(fx_info,channel,x,y,p,depth+1,&sans,
exception);
if (fabs(gamma) < MagickEpsilon)
break;
alpha=FxEvaluateSubexpression(fx_info,channel,x,y,q+1,depth+1,
beta,exception);
}
FxReturn(alpha);
}
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;
}
subexpression=DestroyString(subexpression);
q=(char *) expression;
alpha=InterpretSiPrefixValue(expression,&q);
if (q == expression)
alpha=FxGetSymbol(fx_info,channel,x,y,expression,depth+1,exception);
FxReturn(alpha);
}
MagickPrivate MagickBooleanType FxEvaluateExpression(FxInfo *fx_info,
double *alpha,ExceptionInfo *exception)
{
MagickBooleanType
status;
status=FxEvaluateChannelExpression(fx_info,GrayPixelChannel,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,GrayPixelChannel,0,0,alpha,
exception);
fx_info->file=file;
return(status);
}
MagickPrivate MagickBooleanType FxEvaluateChannelExpression(FxInfo *fx_info,
const PixelChannel 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)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o expression: A mathematical expression.
%
% o exception: return any errors or warnings in this structure.
%
*/
static FxInfo **DestroyFxThreadSet(FxInfo **fx_info)
{
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;
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,exception);
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)
{
#define FxImageTag "Fx/Image"
CacheView
*fx_view,
*image_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,exception) == MagickFalse)
{
fx_info=DestroyFxThreadSet(fx_info);
fx_image=DestroyImage(fx_image);
return((Image *) NULL);
}
/*
Fx image.
*/
status=MagickTrue;
progress=0;
image_view=AcquireVirtualCacheView(image,exception);
fx_view=AcquireAuthenticCacheView(fx_image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(dynamic) shared(progress,status) \
magick_number_threads(image,fx_image,fx_image->rows, \
GlobExpression(fx_info[0]->expression,"debug(",MagickTrue) == 0 ? 1 : 0)
#endif
for (y=0; y < (ssize_t) fx_image->rows; y++)
{
const int
id = GetOpenMPThreadId();
const Quantum
*magick_restrict p;
Quantum
*magick_restrict q;
ssize_t
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=QueueCacheViewAuthenticPixels(fx_view,0,y,fx_image->columns,1,exception);
if ((p == (const Quantum *) NULL) || (q == (Quantum *) NULL))
{
status=MagickFalse;
continue;
}
for (x=0; x < (ssize_t) fx_image->columns; x++)
{
ssize_t
i;
for (i=0; i < (ssize_t) GetPixelChannels(image); i++)
{
double
alpha;
PixelChannel channel = GetPixelChannelChannel(image,i);
PixelTrait traits = GetPixelChannelTraits(image,channel);
PixelTrait fx_traits=GetPixelChannelTraits(fx_image,channel);
if ((traits == UndefinedPixelTrait) ||
(fx_traits == UndefinedPixelTrait))
continue;
if ((fx_traits & CopyPixelTrait) != 0)
{
SetPixelChannel(fx_image,channel,p[i],q);
continue;
}
alpha=0.0;
(void) FxEvaluateChannelExpression(fx_info[id],channel,x,y,&alpha,
exception);
q[i]=ClampToQuantum(QuantumRange*alpha);
}
p+=GetPixelChannels(image);
q+=GetPixelChannels(fx_image);
}
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);
image_view=DestroyCacheView(image_view);
fx_info=DestroyFxThreadSet(fx_info);
if (status == MagickFalse)
fx_image=DestroyImage(fx_image);
return(fx_image);
}
|
LAGraph_cc_fastsv5b.c | //------------------------------------------------------------------------------
// LAGraph_cc_fastsv5b: connected components
//------------------------------------------------------------------------------
/*
LAGraph: graph algorithms based on GraphBLAS
Copyright 2020 LAGraph Contributors.
(see Contributors.txt for a full list of Contributors; see
ContributionInstructions.txt for information on how you can Contribute to
this project).
All Rights Reserved.
NO WARRANTY. THIS MATERIAL IS FURNISHED ON AN "AS-IS" BASIS. THE LAGRAPH
CONTRIBUTORS MAKE NO WARRANTIES OF ANY KIND, EITHER EXPRESSED OR IMPLIED,
AS TO ANY MATTER INCLUDING, BUT NOT LIMITED TO, WARRANTY OF FITNESS FOR
PURPOSE OR MERCHANTABILITY, EXCLUSIVITY, OR RESULTS OBTAINED FROM USE OF
THE MATERIAL. THE CONTRIBUTORS DO NOT MAKE ANY WARRANTY OF ANY KIND WITH
RESPECT TO FREEDOM FROM PATENT, TRADEMARK, OR COPYRIGHT INFRINGEMENT.
Released under a BSD license, please see the LICENSE file distributed with
this Software or contact permission@sei.cmu.edu for full terms.
Created, in part, with funding and support from the United States
Government. (see Acknowledgments.txt file).
This program includes and/or can make use of certain third party source
code, object code, documentation and other files ("Third Party Software").
See LICENSE file for more details.
*/
/**
* Code is based on the algorithm described in the following paper
* Zhang, Azad, Hu. FastSV: FastSV: A Distributed-Memory Connected Component
* Algorithm with Fast Convergence (SIAM PP20)
a subsequent update to the algorithm is here (which might not be reflected
in this code):
Yongzhe Zhang, Ariful Azad, Aydin Buluc: Parallel algorithms for finding
connected components using linear algebra. J. Parallel Distributed Comput.
144: 14-27 (2020).
* Modified by Tim Davis, Texas A&M University
**/
// The input matrix A must be symmetric. Self-edges (diagonal entries) are
// OK, and are ignored. The values and type of A are ignored; just its
// pattern is accessed.
// The matrix A must have dimension 2^32 or less. If it is larger, use the
// 64-bit version of this method instead. TODO combine the two versions into a
// single user-callable code.
#include "LAGraph_internal.h"
//------------------------------------------------------------------------------
// Reduce_assign32: w (index) += src, using MIN as the "+=" accum operator
//------------------------------------------------------------------------------
// mask = NULL, accumulator = GrB_MIN_UINT32, descriptor = NULL.
// Duplicates are summed with the accumulator, which differs from how
// GrB_assign works. GrB_assign states that the presence of duplicates results
// in undefined behavior. SuiteSparse:GraphBLAS follows the MATLAB rule, which
// discards all but the first of the duplicates. TODO: add this to GraphBLAS
// as a variant of GrB_assign, either as GxB_assign_accum (or another name),
// or as a GxB_* descriptor setting.
#define LAGRAPH_FREE_ALL
// hash table
const int P = 1024;
#define HASH(x) (((x << 4) + x) & 1023)
#define NEXT(x) ((x + 23) & 1023)
static inline void ht_init (int *ht_key, int *ht_val)
{
memset(ht_key, -1, sizeof(int) * P);
memset(ht_val, 0, sizeof(int) * P);
}
static inline void ht_sample (uint32_t *V32, int n, int samples, int *ht_key, int *ht_val)
{
for (int i = 0; i < samples; i++) {
int x = V32 [rand() % n];
int h = HASH (x);
while (ht_key [h] != -1 && ht_key [h] != x)
h = NEXT (h);
ht_key [h] = x;
ht_val [h] += 1;
}
}
static inline int ht_most_frequent (int *ht_key, int *ht_val)
{
int key = -1, val = 0;
for (int i = 0; i < P; i++)
if (ht_val [i] > val)
{
key = ht_key [i];
val = ht_val [i];
}
return key;
}
static inline GrB_Info Reduce_assign32
(
GrB_Vector *w_handle, // vector of size n, all entries present
GrB_Vector *s_handle, // vector of size n, all entries present
uint32_t *index, // array of size n
GrB_Index n,
int nthreads,
int *ht_key,
int *ht_val
)
{
#if defined ( GxB_SUITESPARSE_GRAPHBLAS ) && ( GxB_IMPLEMENTATION >= GxB_VERSION (5,0,0) )
printf ("v5.0.0 not supported\n") ;
return (GrB_PANIC) ;
#else
GrB_Type w_type, s_type ;
GrB_Index w_n, s_n, w_nvals, s_nvals, *w_i, *s_i, w_size, s_size ;
uint32_t *w_x, *s_x ;
#if GxB_IMPLEMENTATION >= GxB_VERSION (4,0,1)
LAGr_Vector_export_Full (w_handle, &w_type, &w_n, (void **) &w_x,
&w_size, NULL) ;
LAGr_Vector_export_Full (s_handle, &s_type, &s_n, (void **) &s_x,
&s_size, NULL) ;
#elif GxB_IMPLEMENTATION == GxB_VERSION (4,0,0)
LAGr_Vector_export_Full (w_handle, &w_type, &w_n, (void **) &w_x, NULL) ;
LAGr_Vector_export_Full (s_handle, &s_type, &s_n, (void **) &s_x, NULL) ;
#else
LAGr_Vector_export (w_handle, &w_type, &w_n, &w_nvals, &w_i,
(void **) &w_x, NULL) ;
LAGr_Vector_export (s_handle, &s_type, &s_n, &s_nvals, &s_i,
(void **) &s_x, NULL) ;
#endif
if (nthreads >= 4)
{
uint32_t *mem = LAGraph_malloc (nthreads * P, sizeof (uint32_t));
ht_init (ht_key, ht_val) ;
ht_sample (index, n, 864, ht_key, ht_val) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (int t = 0; t < nthreads; t++)
{
uint32_t *buf = mem + t * P;
for (int h = 0; h < P; h++)
{
if (ht_key [h] != -1)
{
buf [h] = w_x [ht_key [h]];
}
}
int st = (n * t + nthreads - 1) / nthreads;
int ed = (n * t + n + nthreads - 1) / nthreads;
for (int k = st ; k < ed ; k++)
{
uint32_t i = index [k] ;
int h = HASH(i);
while (ht_key [h] != -1 && ht_key [h] != i)
{
h = NEXT (h);
}
if (ht_key [h] == -1)
{
w_x [i] = LAGRAPH_MIN (w_x [i], s_x [k]);
}
else
{
buf [h] = LAGRAPH_MIN (buf [h], s_x [k]);
}
}
}
for (int h = 0; h < P; h++)
{
int i = ht_key [h];
if (i != -1)
{
for (int j = 0; j < nthreads; j++)
{
w_x [i] = LAGRAPH_MIN (w_x [i], mem [j * P + h]);
}
}
}
LAGRAPH_FREE (mem);
}
else
{
// sequential version, to avoid atomics
for (GrB_Index k = 0 ; k < n ; k++)
{
uint32_t i = index [k] ;
w_x [i] = LAGRAPH_MIN (w_x [i], s_x [k]) ;
}
}
#if GxB_IMPLEMENTATION >= GxB_VERSION (4,0,1)
LAGr_Vector_import_Full (w_handle, w_type, w_n, (void **) &w_x,
w_size, NULL) ;
LAGr_Vector_import_Full (s_handle, s_type, s_n, (void **) &s_x,
s_size, NULL) ;
#elif GxB_IMPLEMENTATION == GxB_VERSION (4,0,0)
LAGr_Vector_import_Full (w_handle, w_type, w_n, (void **) &w_x, NULL) ;
LAGr_Vector_import_Full (s_handle, s_type, s_n, (void **) &s_x, NULL) ;
#else
LAGr_Vector_import (w_handle, w_type, w_n, w_nvals, &w_i,
(void **) &w_x, NULL) ;
LAGr_Vector_import (s_handle, s_type, s_n, s_nvals, &s_i,
(void **) &s_x, NULL) ;
#endif
return (GrB_SUCCESS) ;
#endif
}
#undef LAGRAPH_FREE_ALL
#define LAGRAPH_FREE_ALL \
{ \
LAGRAPH_FREE (I) ; \
LAGRAPH_FREE (V32) ; \
LAGRAPH_FREE (ht_key) ; \
LAGRAPH_FREE (ht_val) ; \
LAGr_free (&f) ; \
LAGr_free (&gp) ; \
LAGr_free (&mngp) ; \
LAGr_free (&gp_new) ; \
LAGr_free (&mod) ; \
}
//------------------------------------------------------------------------------
// LAGraph_cc_fastsv5
//------------------------------------------------------------------------------
GrB_Info LAGraph_cc_fastsv5b
(
GrB_Vector *result, // output: array of component identifiers
GrB_Matrix *A, // input matrix
// content remains the same, but pointer changes
bool sanitize // if true, ensure A is symmetric
)
{
#if defined ( GxB_SUITESPARSE_GRAPHBLAS ) && ( GxB_IMPLEMENTATION >= GxB_VERSION (5,0,0) )
printf ("v5.0.0 not supported\n") ;
return (GrB_PANIC) ;
#else
GrB_Info info ;
uint32_t *V32 = NULL ;
int *ht_key = NULL, *ht_val = NULL;
GrB_Index n, nnz, *I = NULL ;
GrB_Vector f = NULL, gp_new = NULL, mngp = NULL, mod = NULL, gp = NULL ;
GrB_Matrix S = NULL, T = NULL ;
//--------------------------------------------------------------------------
// check inputs
//--------------------------------------------------------------------------
LAGr_Matrix_nrows (&n, *A) ;
LAGr_Matrix_nvals (&nnz, *A) ;
if (n > UINT32_MAX)
{
LAGRAPH_ERROR ("problem too large; use 64-bit version instead",
GrB_INVALID_VALUE) ;
}
#define FASTSV_SAMPLES 4
GxB_Format_Value format;
LAGRAPH_OK (GxB_get (*A , GxB_FORMAT, &format)) ;
bool sampling = (format == GxB_BY_ROW) && (n * FASTSV_SAMPLES * 2 < nnz);
if (sanitize)
{
// S = A | A'
LAGr_Matrix_new (&S, GrB_BOOL, n, n) ;
LAGr_eWiseAdd (S, NULL, NULL, GrB_LOR, *A, *A, LAGraph_desc_otoo) ;
}
else
{
// Use the input as-is, and assume it is symmetric
// LAGr_Matrix_dup (&S, A) ;
S = *A;
}
//--------------------------------------------------------------------------
// initializations
//--------------------------------------------------------------------------
// determine # of threads to use for Reduce_assign
int nthreads = LAGraph_get_nthreads ( ) ;
nthreads = LAGRAPH_MIN (nthreads, n / 16) ;
nthreads = LAGRAPH_MAX (nthreads, 1) ;
// # of threads to use for typecast
int nthreads2 = n / (64*1024) ;
nthreads2 = LAGRAPH_MIN (nthreads2, nthreads) ;
nthreads2 = LAGRAPH_MAX (nthreads2, 1) ;
// printf ("nthreads %d nthreads2 %d\n", nthreads, nthreads2) ;
// vectors
LAGr_Vector_new (&f, GrB_UINT32, n) ;
LAGr_Vector_new (&gp_new, GrB_UINT32, n) ;
LAGr_Vector_new (&mod, GrB_BOOL, n) ;
// temporary arrays
I = LAGraph_malloc (n, sizeof (GrB_Index)) ;
V32 = LAGraph_malloc (n, sizeof (uint32_t)) ;
// prepare vectors
#pragma omp parallel for num_threads(nthreads2) schedule(static)
for (GrB_Index i = 0 ; i < n ; i++)
{
I [i] = i ;
V32 [i] = (uint32_t) i ;
}
LAGr_Vector_build (f, I, V32, n, GrB_PLUS_UINT32) ;
LAGr_Vector_dup (&gp, f) ;
LAGr_Vector_dup (&mngp, f) ;
ht_key = LAGraph_malloc (P, sizeof (int));
ht_val = LAGraph_malloc (P, sizeof (int));
//--------------------------------------------------------------------------
// main computation
//--------------------------------------------------------------------------
if (sampling)
{
GrB_Type type;
GrB_Index nrows, ncols, nvals;
int64_t nonempty;
GrB_Index *Sp, *Sj;
void *Sx;
bool S_jumbled = false ;
GrB_Index Sp_size, Sj_size, Sx_size ;
#if GxB_IMPLEMENTATION >= GxB_VERSION (4,0,1)
GrB_Matrix_nvals (&nvals, S) ;
GxB_Matrix_export_CSR (&S, &type, &nrows, &ncols,
&Sp, &Sj, &Sx, &Sp_size, &Sj_size, &Sx_size, &S_jumbled, NULL) ;
#elif GxB_IMPLEMENTATION == GxB_VERSION (4,0,0)
GxB_Matrix_export_CSR (&S, &type, &nrows, &ncols, &nvals,
&S_jumbled, &nonempty, &Sp, &Sj, &Sx, NULL);
#else
GxB_Matrix_export_CSR (&S, &type, &nrows, &ncols, &nvals,
&nonempty, &Sp, &Sj, &Sx, NULL);
#endif
GrB_Index Tp_size = nrows+1 ;
GrB_Index Tj_size = nvals ;
GrB_Index Tx_size = nvals ;
GrB_Index *Tp = LAGraph_malloc (Tp_size, sizeof (GrB_Index)) ;
GrB_Index *Tj = LAGraph_malloc (Tj_size, sizeof (GrB_Index)) ;
void *Tx = LAGraph_malloc (Tx_size, 1) ;
int *range = LAGraph_malloc (nthreads + 1, sizeof (int)) ;
GrB_Index *count = LAGraph_malloc (nthreads + 1, sizeof (GrB_Index)) ;
memset (count, 0, sizeof (GrB_Index) * (nthreads + 1)) ;
for (int i = 0; i <= nthreads; i++)
{
range [i] = (n * i + nthreads - 1) / nthreads;
}
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (int t = 0; t < nthreads; t++)
{
for (int i = range[t]; i < range[t + 1]; i++)
{
int deg = Sp [i + 1] - Sp [i];
count [t + 1] += LAGRAPH_MIN (FASTSV_SAMPLES, deg) ;
}
}
for (int i = 0; i < nthreads; i++)
{
count [i + 1] += count [i];
}
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (int t = 0; t < nthreads; t++)
{
GrB_Index p = count [t];
Tp [range [t]] = p;
for (int i = range[t]; i < range[t + 1]; i++)
{
for (int j = 0; j < FASTSV_SAMPLES && Sp [i] + j < Sp [i + 1];
j++)
{
Tj [p++] = Sj [Sp [i] + j];
}
Tp [i + 1] = p;
}
}
GrB_Index t_nvals = Tp[nrows];
#if GxB_IMPLEMENTATION >= GxB_VERSION (4,0,1)
GxB_Matrix_import_CSR (&T, type, nrows, ncols,
&Tp, &Tj, &Tx, Tp_size, Tj_size, Tx_size, S_jumbled, NULL) ;
#elif GxB_IMPLEMENTATION == GxB_VERSION (4,0,0)
GxB_Matrix_import_CSR (&T, type, nrows, ncols, t_nvals,
S_jumbled, -1, &Tp, &Tj, &Tx, NULL);
#else
GxB_Matrix_import_CSR (&T, type, nrows, ncols, t_nvals,
-1, &Tp, &Tj, &Tx, NULL);
#endif
bool change = true, is_first = true;
while (change)
{
// hooking & shortcutting
LAGr_mxv (mngp, NULL, GrB_MIN_UINT32, GxB_MIN_SECOND_UINT32, T, gp,
NULL) ;
if (!is_first)
{
LAGRAPH_OK (Reduce_assign32 (&f, &mngp, V32, n, nthreads, ht_key, ht_val)) ;
}
// old:
// LAGr_eWiseMult (f, NULL, NULL, GrB_MIN_UINT32, f, mngp, NULL) ;
// LAGr_eWiseMult (f, NULL, NULL, GrB_MIN_UINT32, f, gp, NULL) ;
// new:
LAGr_eWiseAdd (f, NULL, GrB_MIN_UINT32, GrB_MIN_UINT32, mngp, gp,
NULL) ;
// calculate grandparent
LAGr_Vector_extractTuples (NULL, V32, &n, f) ;
#pragma omp parallel for num_threads(nthreads2) schedule(static)
for (uint32_t i = 0 ; i < n ; i++)
{
I [i] = (GrB_Index) V32 [i] ;
}
LAGr_extract (gp_new, NULL, NULL, f, I, n, NULL) ;
// check termination
LAGr_eWiseMult (mod, NULL, NULL, GrB_NE_UINT32, gp_new, gp, NULL) ;
LAGr_reduce (&change, NULL, GxB_LOR_BOOL_MONOID, mod, NULL) ;
// swap gp and gp_new
GrB_Vector t = gp ; gp = gp_new ; gp_new = t ;
is_first = false;
}
ht_init(ht_key, ht_val) ;
ht_sample (V32, n, 864, ht_key, ht_val) ;
int key = ht_most_frequent(ht_key, ht_val) ;
int64_t t_nonempty = -1 ;
bool T_jumbled = false ;
#if GxB_IMPLEMENTATION >= GxB_VERSION (4,0,1)
GxB_Matrix_export_CSR (&T, &type, &nrows, &ncols,
&Tp, &Tj, &Tx, &Tp_size, &Tj_size, &Tx_size,
&T_jumbled, NULL) ;
#elif GxB_IMPLEMENTATION == GxB_VERSION (4,0,0)
GxB_Matrix_export_CSR (&T, &type, &nrows, &ncols, &t_nvals,
&T_jumbled, &t_nonempty, &Tp, &Tj, &Tx, NULL);
#else
GxB_Matrix_export_CSR (&T, &type, &nrows, &ncols, &t_nvals,
&t_nonempty, &Tp, &Tj, &Tx, NULL);
#endif
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (int t = 0; t < nthreads; t++)
{
GrB_Index ptr = Sp[range[t]];
for (int v = range[t]; v < range[t + 1]; v++)
{
int pv = V32 [v];
Tp [v] = ptr;
if (pv != key)
{
for (GrB_Index i = Sp [v]; i < Sp [v + 1]; i++)
{
int u = Sj [i];
if (V32 [u] != key)
{
Tj [ptr++] = u;
}
}
if (ptr - Tp[v] < Sp [v + 1] - Sp [v])
{
Tj [ptr++] = key;
}
}
}
count[t] = ptr - Tp [range [t]];
}
GrB_Index offset = 0;
for (int i = 0; i < nthreads; i++)
{
memcpy(Tj + offset, Tj + Tp [range [i]], sizeof(GrB_Index) * count[i]);
offset += count[i];
count[i] = offset - count[i];
}
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (int t = 0; t < nthreads; t++)
{
GrB_Index ptr = Tp [range [t]];
for (int v = range[t]; v < range[t + 1]; v++)
{
Tp [v] -= ptr - count[t];
}
}
Tp [n] = offset;
LAGRAPH_FREE (count);
LAGRAPH_FREE (range);
#if GxB_IMPLEMENTATION >= GxB_VERSION (4,0,1)
GxB_Matrix_import_CSR (&S, type, nrows, ncols,
&Sp, &Sj, &Sx, Sp_size, Sj_size, Sx_size, S_jumbled, NULL);
GxB_Matrix_import_CSR (&T, type, nrows, ncols,
&Tp, &Tj, &Tx, Tp_size, Tj_size, Tx_size, T_jumbled, NULL) ;
#elif GxB_IMPLEMENTATION == GxB_VERSION (4,0,0)
GxB_Matrix_import_CSR (&S, type, nrows, ncols, nvals,
S_jumbled, nonempty, &Sp, &Sj, &Sx, NULL);
GxB_Matrix_import_CSR (&T, type, nrows, ncols, offset,
T_jumbled, -1, &Tp, &Tj, &Tx, NULL);
#else
GxB_Matrix_import_CSR (&S, type, nrows, ncols, nvals,
nonempty, &Sp, &Sj, &Sx, NULL);
GxB_Matrix_import_CSR (&T, type, nrows, ncols, offset,
-1, &Tp, &Tj, &Tx, NULL);
#endif
}
else
{
T = S;
}
LAGr_Matrix_nvals (&nnz, T);
bool change = true;
while (change && nnz > 0)
{
// hooking & shortcutting
LAGr_mxv (mngp, NULL, GrB_MIN_UINT32, GxB_MIN_SECOND_UINT32, T, gp,
NULL) ;
LAGRAPH_OK (Reduce_assign32 (&f, &mngp, V32, n, nthreads, ht_key, ht_val)) ;
// old:
// LAGr_eWiseMult (f, NULL, NULL, GrB_MIN_UINT32, f, mngp, NULL) ;
// LAGr_eWiseMult (f, NULL, NULL, GrB_MIN_UINT32, f, gp, NULL) ;
// new:
LAGr_eWiseAdd (f, NULL, GrB_MIN_UINT32, GrB_MIN_UINT32, mngp, gp, NULL);
// calculate grandparent
LAGr_Vector_extractTuples (NULL, V32, &n, f) ;
#pragma omp parallel for num_threads(nthreads2) schedule(static)
for (uint32_t i = 0 ; i < n ; i++)
{
I [i] = (GrB_Index) V32 [i] ;
}
LAGr_extract (gp_new, NULL, NULL, f, I, n, NULL) ;
// check termination
LAGr_eWiseMult (mod, NULL, NULL, GrB_NE_UINT32, gp_new, gp, NULL) ;
LAGr_reduce (&change, NULL, GxB_LOR_BOOL_MONOID, mod, NULL) ;
// swap gp and gp_new
GrB_Vector t = gp ; gp = gp_new ; gp_new = t ;
}
//--------------------------------------------------------------------------
// free workspace and return result
//--------------------------------------------------------------------------
*result = f ;
f = NULL ;
if (!sanitize)
{
*A = S;
}
else
{
LAGr_free (&S) ;
}
if (sampling)
{
LAGr_free (&T) ;
}
LAGRAPH_FREE_ALL ;
return (GrB_SUCCESS) ;
#endif
}
|
convolution_3x3_pack4.h | // Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2019 THL A29 Limited, a Tencent company. All rights reserved.
//
// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
// in compliance with the License. You may obtain a copy of the License at
//
// https://opensource.org/licenses/BSD-3-Clause
//
// Unless required by applicable law or agreed to in writing, software distributed
// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
// CONDITIONS OF ANY KIND, either express or implied. See the License for the
// specific language governing permissions and limitations under the License.
static void conv3x3s1_winograd64_transform_kernel_pack4_neon(const Mat& kernel, Mat& kernel_tm_pack4, int inch, int outch)
{
// winograd23 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
for (int p = 0; p<outch; p++)
{
for (int q = 0; q<inch; q++)
{
const float* kernel0 = (const float*)kernel + p*inch * 9 + q * 9;
float* kernel_tm0 = kernel_tm.channel(p).row(q);
// transform kernel, transposed
const float* k0 = kernel0;
const float* k1 = kernel0 + 3;
const float* k2 = kernel0 + 6;
// h
float tmp[8][3];
for (int i=0; i<8; i++)
{
tmp[i][0] = k0[0] * ktm[i][0] + k0[1] * ktm[i][1] + k0[2] * ktm[i][2];
tmp[i][1] = k1[0] * ktm[i][0] + k1[1] * ktm[i][1] + k1[2] * ktm[i][2];
tmp[i][2] = k2[0] * ktm[i][0] + k2[1] * ktm[i][1] + k2[2] * ktm[i][2];
}
// v
for (int j=0; j<8; j++)
{
float* tmpp = &tmp[j][0];
for (int i=0; i<8; i++)
{
kernel_tm0[j*8 + i] = tmpp[0] * ktm[i][0] + tmpp[1] * ktm[i][1] + tmpp[2] * ktm[i][2];
}
}
}
}
// interleave
// src = 64-inch-outch
// dst = 4b-4a-inch/4a-64-outch/4b;
kernel_tm_pack4.create(inch/4, 64, outch/4, (size_t)4u*16, 16);
for (int q=0; q+3<outch; q+=4)
{
const Mat k0 = kernel_tm.channel(q);
const Mat k1 = kernel_tm.channel(q+1);
const Mat k2 = kernel_tm.channel(q+2);
const Mat k3 = kernel_tm.channel(q+3);
Mat g0 = kernel_tm_pack4.channel(q/4);
for (int k=0; k<64; k++)
{
float* g00 = g0.row(k);
for (int p=0; p+3<inch; p+=4)
{
const float* k00 = k0.row(p);
const float* k01 = k0.row(p+1);
const float* k02 = k0.row(p+2);
const float* k03 = k0.row(p+3);
const float* k10 = k1.row(p);
const float* k11 = k1.row(p+1);
const float* k12 = k1.row(p+2);
const float* k13 = k1.row(p+3);
const float* k20 = k2.row(p);
const float* k21 = k2.row(p+1);
const float* k22 = k2.row(p+2);
const float* k23 = k2.row(p+3);
const float* k30 = k3.row(p);
const float* k31 = k3.row(p+1);
const float* k32 = k3.row(p+2);
const float* k33 = k3.row(p+3);
g00[0] = k00[k];
g00[1] = k10[k];
g00[2] = k20[k];
g00[3] = k30[k];
g00[4] = k01[k];
g00[5] = k11[k];
g00[6] = k21[k];
g00[7] = k31[k];
g00[8] = k02[k];
g00[9] = k12[k];
g00[10] = k22[k];
g00[11] = k32[k];
g00[12] = k03[k];
g00[13] = k13[k];
g00[14] = k23[k];
g00[15] = k33[k];
g00 += 16;
}
}
}
}
static void conv3x3s1_winograd64_pack4_neon(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel_tm, const Mat& _bias, const Option& opt)
{
int w = bottom_blob.w;
int h = bottom_blob.h;
int inch = bottom_blob.c;
size_t elemsize = bottom_blob.elemsize;
int elempack = bottom_blob.elempack;
int outw = top_blob.w;
int outh = top_blob.h;
int outch = top_blob.c;
// pad to 6n+2
Mat bottom_blob_bordered = bottom_blob;
outw = (outw + 5) / 6 * 6;
outh = (outh + 5) / 6 * 6;
w = outw + 2;
h = outh + 2;
copy_make_border(bottom_blob, bottom_blob_bordered, 0, h - bottom_blob.h, 0, w - bottom_blob.w, BORDER_CONSTANT, 0.f, opt);
const float* bias = _bias;
// BEGIN transform input
Mat bottom_blob_tm;
{
int w_tm = outw / 6 * 8;
int h_tm = outh / 6 * 8;
const int tiles = w_tm/8 * h_tm/8;
bottom_blob_tm.create(tiles, 64, inch, elemsize, elempack, opt.workspace_allocator);
// const float itm[8][8] = {
// {1.0f, 0.0f, -5.25f, 0.00f, 5.25f, 0.00f, -1.0f, 0.0f},
//
// {0.0f, 1.0f, 1.00f, -4.25f, -4.25f, 1.00f, 1.0f, 0.0f},
// {0.0f, -1.0f, 1.00f, 4.25f, -4.25f, -1.00f, 1.0f, 0.0f},
//
// {0.0f, 0.5f, 0.25f, -2.50f, -1.25f, 2.00f, 1.0f, 0.0f},
// {0.0f, -0.5f, 0.25f, 2.50f, -1.25f, -2.00f, 1.0f, 0.0f},
//
// {0.0f, 2.0f, 4.00f, -2.50f, -5.00f, 0.50f, 1.0f, 0.0f},
// {0.0f, -2.0f, 4.00f, 2.50f, -5.00f, -0.50f, 1.0f, 0.0f},
//
// {0.0f, -1.0f, 0.00f, 5.25f, 0.00f, -5.25f, 0.0f, 1.0f}
// };
// 0 = r00 - r06 + (r04 - r02) * 5.25
// 7 = r07 - r01 + (r03 - r05) * 5.25
// 1 = (r02 + r06 - r04 * 4.25) + (r01 - r03 * 4.25 + r05)
// 2 = (r02 + r06 - r04 * 4.25) - (r01 - r03 * 4.25 + r05)
// 3 = (r06 + r02 * 0.25 - r04 * 1.25) + (r01 * 0.5 - r03 * 2.5 + r05 * 2)
// 4 = (r06 + r02 * 0.25 - r04 * 1.25) - (r01 * 0.5 - r03 * 2.5 + r05 * 2)
// reuse r04 * 1.25
// reuse r03 * 2.5
// 5 = (r06 + (r02 - r04 * 1.25) * 4) + (r01 * 2 - r03 * 2.5 + r05 * 0.5)
// 6 = (r06 + (r02 - r04 * 1.25) * 4) - (r01 * 2 - r03 * 2.5 + r05 * 0.5)
#pragma omp parallel for num_threads(opt.num_threads)
for (int q = 0; q<inch; q++)
{
const Mat img0 = bottom_blob_bordered.channel(q);
Mat img0_tm = bottom_blob_tm.channel(q);
float tmp[8][8][4];
// tile
for (int i=0; i<h_tm/8; i++)
{
for (int j=0; j<w_tm/8; j++)
{
const float* r0 = img0.row(i * 6) + (j * 6) * 4;
for (int m=0; m<8; m++)
{
float32x4_t _r00 = vld1q_f32(r0);
float32x4_t _r01 = vld1q_f32(r0 + 4);
float32x4_t _r02 = vld1q_f32(r0 + 8);
float32x4_t _r03 = vld1q_f32(r0 + 12);
float32x4_t _r04 = vld1q_f32(r0 + 16);
float32x4_t _r05 = vld1q_f32(r0 + 20);
float32x4_t _r06 = vld1q_f32(r0 + 24);
float32x4_t _r07 = vld1q_f32(r0 + 28);
float32x4_t _tmp0m = vmlaq_n_f32(vsubq_f32(_r00, _r06), vsubq_f32(_r04, _r02), 5.25f);
float32x4_t _tmp7m = vmlaq_n_f32(vsubq_f32(_r07, _r01), vsubq_f32(_r03, _r05), 5.25f);
vst1q_f32(tmp[0][m], _tmp0m);
vst1q_f32(tmp[7][m], _tmp7m);
// tmp[0][m] = r0[0] - r0[6] + (r0[4] - r0[2]) * 5.25;
// tmp[7][m] = r0[7] - r0[1] + (r0[3] - r0[5]) * 5.25;
float32x4_t _tmp12a = vmlsq_n_f32(vaddq_f32(_r02, _r06), _r04, 4.25f);
float32x4_t _tmp12b = vmlsq_n_f32(vaddq_f32(_r01, _r05), _r03, 4.25f);
// float tmp12a = (r0[2] + r0[6] - r0[4] * 4.25);
// float tmp12b = (r0[1] + r0[5] - r0[3] * 4.25);
float32x4_t _tmp1m = vaddq_f32(_tmp12a, _tmp12b);
float32x4_t _tmp2m = vsubq_f32(_tmp12a, _tmp12b);
vst1q_f32(tmp[1][m], _tmp1m);
vst1q_f32(tmp[2][m], _tmp2m);
// tmp[1][m] = tmp12a + tmp12b;
// tmp[2][m] = tmp12a - tmp12b;
float32x4_t _tmp34a = vmlsq_n_f32(vmlaq_n_f32(_r06, _r02, 0.25f), _r04, 1.25f);
float32x4_t _tmp34b = vmlaq_n_f32(vmlsq_n_f32(vmulq_n_f32(_r01, 0.5f), _r03, 2.5f), _r05, 2.f);
// float tmp34a = (r0[6] + r0[2] * 0.25 - r0[4] * 1.25);
// float tmp34b = (r0[1] * 0.5 - r0[3] * 2.5 + r0[5] * 2);
float32x4_t _tmp3m = vaddq_f32(_tmp34a, _tmp34b);
float32x4_t _tmp4m = vsubq_f32(_tmp34a, _tmp34b);
vst1q_f32(tmp[3][m], _tmp3m);
vst1q_f32(tmp[4][m], _tmp4m);
// tmp[3][m] = tmp34a + tmp34b;
// tmp[4][m] = tmp34a - tmp34b;
float32x4_t _tmp56a = vmlaq_n_f32(_r06, vmlsq_n_f32(_r02, _r04, 1.25f), 4.f);
float32x4_t _tmp56b = vmlaq_n_f32(vmlsq_n_f32(vmulq_n_f32(_r01, 2.f), _r03, 2.5f), _r05, 0.5f);
// float tmp56a = (r0[6] + (r0[2] - r0[4] * 1.25) * 4);
// float tmp56b = (r0[1] * 2 - r0[3] * 2.5 + r0[5] * 0.5);
float32x4_t _tmp5m = vaddq_f32(_tmp56a, _tmp56b);
float32x4_t _tmp6m = vsubq_f32(_tmp56a, _tmp56b);
vst1q_f32(tmp[5][m], _tmp5m);
vst1q_f32(tmp[6][m], _tmp6m);
// tmp[5][m] = tmp56a + tmp56b;
// tmp[6][m] = tmp56a - tmp56b;
r0 += w * 4;
}
float* r0_tm_0 = (float*)img0_tm + (i * w_tm/8 + j) * 4;
for (int m=0; m<8; m++)
{
float32x4_t _tmp00 = vld1q_f32(tmp[m][0]);
float32x4_t _tmp01 = vld1q_f32(tmp[m][1]);
float32x4_t _tmp02 = vld1q_f32(tmp[m][2]);
float32x4_t _tmp03 = vld1q_f32(tmp[m][3]);
float32x4_t _tmp04 = vld1q_f32(tmp[m][4]);
float32x4_t _tmp05 = vld1q_f32(tmp[m][5]);
float32x4_t _tmp06 = vld1q_f32(tmp[m][6]);
float32x4_t _tmp07 = vld1q_f32(tmp[m][7]);
float32x4_t _r0tm0 = vmlaq_n_f32(vsubq_f32(_tmp00, _tmp06), vsubq_f32(_tmp04, _tmp02), 5.25f);
float32x4_t _r0tm7 = vmlaq_n_f32(vsubq_f32(_tmp07, _tmp01), vsubq_f32(_tmp03, _tmp05), 5.25f);
// r0_tm[0] = tmp0[0] - tmp0[6] + (tmp0[4] - tmp0[2]) * 5.25;
// r0_tm[7] = tmp0[7] - tmp0[1] + (tmp0[3] - tmp0[5]) * 5.25;
float32x4_t _tmp12a = vmlsq_n_f32(vaddq_f32(_tmp02, _tmp06), _tmp04, 4.25f);
float32x4_t _tmp12b = vmlsq_n_f32(vaddq_f32(_tmp01, _tmp05), _tmp03, 4.25f);
// float tmp12a = (tmp0[2] + tmp0[6] - tmp0[4] * 4.25);
// float tmp12b = (tmp0[1] + tmp0[5] - tmp0[3] * 4.25);
float32x4_t _r0tm1 = vaddq_f32(_tmp12a, _tmp12b);
float32x4_t _r0tm2 = vsubq_f32(_tmp12a, _tmp12b);
// r0_tm[1] = tmp12a + tmp12b;
// r0_tm[2] = tmp12a - tmp12b;
float32x4_t _tmp34a = vmlsq_n_f32(vmlaq_n_f32(_tmp06, _tmp02, 0.25f), _tmp04, 1.25f);
float32x4_t _tmp34b = vmlaq_n_f32(vmlsq_n_f32(vmulq_n_f32(_tmp01, 0.5f), _tmp03, 2.5f), _tmp05, 2.f);
// float tmp34a = (tmp0[6] + tmp0[2] * 0.25 - tmp0[4] * 1.25);
// float tmp34b = (tmp0[1] * 0.5 - tmp0[3] * 2.5 + tmp0[5] * 2);
float32x4_t _r0tm3 = vaddq_f32(_tmp34a, _tmp34b);
float32x4_t _r0tm4 = vsubq_f32(_tmp34a, _tmp34b);
// r0_tm[3] = tmp34a + tmp34b;
// r0_tm[4] = tmp34a - tmp34b;
float32x4_t _tmp56a = vmlaq_n_f32(_tmp06, vmlsq_n_f32(_tmp02, _tmp04, 1.25f), 4.f);
float32x4_t _tmp56b = vmlaq_n_f32(vmlsq_n_f32(vmulq_n_f32(_tmp01, 2.f), _tmp03, 2.5f), _tmp05, 0.5f);
// float tmp56a = (tmp0[6] + (tmp0[2] - tmp0[4] * 1.25) * 4);
// float tmp56b = (tmp0[1] * 2 - tmp0[3] * 2.5 + tmp0[5] * 0.5);
float32x4_t _r0tm5 = vaddq_f32(_tmp56a, _tmp56b);
float32x4_t _r0tm6 = vsubq_f32(_tmp56a, _tmp56b);
// r0_tm[5] = tmp56a + tmp56b;
// r0_tm[6] = tmp56a - tmp56b;
vst1q_f32(r0_tm_0, _r0tm0);
r0_tm_0 += tiles * 4;
vst1q_f32(r0_tm_0, _r0tm1);
r0_tm_0 += tiles * 4;
vst1q_f32(r0_tm_0, _r0tm2);
r0_tm_0 += tiles * 4;
vst1q_f32(r0_tm_0, _r0tm3);
r0_tm_0 += tiles * 4;
vst1q_f32(r0_tm_0, _r0tm4);
r0_tm_0 += tiles * 4;
vst1q_f32(r0_tm_0, _r0tm5);
r0_tm_0 += tiles * 4;
vst1q_f32(r0_tm_0, _r0tm6);
r0_tm_0 += tiles * 4;
vst1q_f32(r0_tm_0, _r0tm7);
r0_tm_0 += tiles * 4;
}
}
}
}
}
bottom_blob_bordered = Mat();
// END transform input
// BEGIN dot
Mat top_blob_tm;
{
int w_tm = outw / 6 * 8;
int h_tm = outh / 6 * 8;
const int tiles = h_tm/8 * w_tm/8;
// permute
// bottom_blob_tm.create(tiles, 64, inch, elemsize, elempack, opt.workspace_allocator);
Mat bottom_blob_tm2(8 * inch, tiles/8 + (tiles%8)/4 + (tiles%4)/2 + tiles%2, 64, elemsize, elempack, opt.workspace_allocator);
#pragma omp parallel for num_threads(opt.num_threads)
for (int r=0; r<64; r++)
{
Mat tm2 = bottom_blob_tm2.channel(r);
// tile
int i=0;
for (; i+7<tiles; i+=8)
{
float* tm2p = tm2.row(i/8);
const float* r0 = bottom_blob_tm;
r0 += (r*tiles + i) * 4;
for (int q=0; q<inch; q++)
{
float32x4_t _r0 = vld1q_f32(r0);
float32x4_t _r1 = vld1q_f32(r0 + 4);
float32x4_t _r2 = vld1q_f32(r0 + 8);
float32x4_t _r3 = vld1q_f32(r0 + 12);
float32x4_t _r4 = vld1q_f32(r0 + 16);
float32x4_t _r5 = vld1q_f32(r0 + 20);
float32x4_t _r6 = vld1q_f32(r0 + 24);
float32x4_t _r7 = vld1q_f32(r0 + 28);
vst1q_f32(tm2p, _r0);
vst1q_f32(tm2p + 4, _r1);
vst1q_f32(tm2p + 8, _r2);
vst1q_f32(tm2p + 12, _r3);
vst1q_f32(tm2p + 16, _r4);
vst1q_f32(tm2p + 20, _r5);
vst1q_f32(tm2p + 24, _r6);
vst1q_f32(tm2p + 28, _r7);
// tm2p[0] = r0[0];
r0 += bottom_blob_tm.cstep * 4;
tm2p += 32;
}
}
for (; i+3<tiles; i+=4)
{
float* tm2p = tm2.row(i/8 + (i%8)/4);
const float* r0 = bottom_blob_tm;
r0 += (r*tiles + i) * 4;
for (int q=0; q<inch; q++)
{
float32x4_t _r0 = vld1q_f32(r0);
float32x4_t _r1 = vld1q_f32(r0 + 4);
float32x4_t _r2 = vld1q_f32(r0 + 8);
float32x4_t _r3 = vld1q_f32(r0 + 12);
vst1q_f32(tm2p, _r0);
vst1q_f32(tm2p + 4, _r1);
vst1q_f32(tm2p + 8, _r2);
vst1q_f32(tm2p + 12, _r3);
// tm2p[0] = r0[0];
r0 += bottom_blob_tm.cstep * 4;
tm2p += 16;
}
}
for (; i+1<tiles; i+=2)
{
float* tm2p = tm2.row(i/8 + (i%8)/4 + (i%4)/2);
const float* r0 = bottom_blob_tm;
r0 += (r*tiles + i) * 4;
for (int q=0; q<inch; q++)
{
float32x4_t _r0 = vld1q_f32(r0);
float32x4_t _r1 = vld1q_f32(r0 + 4);
vst1q_f32(tm2p, _r0);
vst1q_f32(tm2p + 4, _r1);
// tm2p[0] = r0[0];
r0 += bottom_blob_tm.cstep * 4;
tm2p += 8;
}
}
for (; i<tiles; i++)
{
float* tm2p = tm2.row(i/8 + (i%8)/4 + (i%4)/2 + i%2);
const float* r0 = bottom_blob_tm;
r0 += (r*tiles + i) * 4;
for (int q=0; q<inch; q++)
{
float32x4_t _r0 = vld1q_f32(r0);
vst1q_f32(tm2p, _r0);
// tm2p[0] = r0[0];
r0 += bottom_blob_tm.cstep * 4;
tm2p += 4;
}
}
}
bottom_blob_tm = Mat();
// permute end
top_blob_tm.create(tiles, 64, outch, elemsize, elempack);
int nn_outch = 0;
int remain_outch_start = 0;
#if __ARM_NEON && __aarch64__
nn_outch = outch >> 1;
remain_outch_start = nn_outch << 1;
#pragma omp parallel for num_threads(opt.num_threads)
for (int pp=0; pp<nn_outch; pp++)
{
int p = pp * 2;
Mat out0_tm = top_blob_tm.channel(p);
Mat out1_tm = top_blob_tm.channel(p+1);
const Mat kernel0_tm = kernel_tm.channel(p);
const Mat kernel1_tm = kernel_tm.channel(p+1);
float* output0_tm = out0_tm;
float* output1_tm = out1_tm;
for (int r=0; r<64; r++)
{
const Mat bb2 = bottom_blob_tm2.channel(r);
int i=0;
for (; i+7<tiles; i+=8)
{
const float* r0 = bb2.row(i/8);
const float* k0 = kernel0_tm.row(r);
const float* k1 = kernel1_tm.row(r);
float32x4_t _sum0_0 = vdupq_n_f32(0.f);
float32x4_t _sum1_0 = vdupq_n_f32(0.f);
float32x4_t _sum2_0 = vdupq_n_f32(0.f);
float32x4_t _sum3_0 = vdupq_n_f32(0.f);
float32x4_t _sum4_0 = vdupq_n_f32(0.f);
float32x4_t _sum5_0 = vdupq_n_f32(0.f);
float32x4_t _sum6_0 = vdupq_n_f32(0.f);
float32x4_t _sum7_0 = vdupq_n_f32(0.f);
float32x4_t _sum0_1 = vdupq_n_f32(0.f);
float32x4_t _sum1_1 = vdupq_n_f32(0.f);
float32x4_t _sum2_1 = vdupq_n_f32(0.f);
float32x4_t _sum3_1 = vdupq_n_f32(0.f);
float32x4_t _sum4_1 = vdupq_n_f32(0.f);
float32x4_t _sum5_1 = vdupq_n_f32(0.f);
float32x4_t _sum6_1 = vdupq_n_f32(0.f);
float32x4_t _sum7_1 = vdupq_n_f32(0.f);
int q=0;
for (; q<inch; q++)
{
float32x4_t _r0 = vld1q_f32( r0 );
float32x4_t _r1 = vld1q_f32( r0 + 4 );
float32x4_t _r2 = vld1q_f32( r0 + 8 );
float32x4_t _r3 = vld1q_f32( r0 + 12 );
float32x4_t _r4 = vld1q_f32( r0 + 16 );
float32x4_t _r5 = vld1q_f32( r0 + 20 );
float32x4_t _r6 = vld1q_f32( r0 + 24 );
float32x4_t _r7 = vld1q_f32( r0 + 28 );
float32x4_t _w0_0 = vld1q_f32( k0 );
float32x4_t _w1_0 = vld1q_f32( k0 + 4 );
float32x4_t _w2_0 = vld1q_f32( k0 + 8 );
float32x4_t _w3_0 = vld1q_f32( k0 + 12 );
float32x4_t _w0_1 = vld1q_f32( k1 );
float32x4_t _w1_1 = vld1q_f32( k1 + 4 );
float32x4_t _w2_1 = vld1q_f32( k1 + 8 );
float32x4_t _w3_1 = vld1q_f32( k1 + 12 );
_sum0_0 = vmlaq_laneq_f32(_sum0_0, _w0_0, _r0, 0);
_sum0_0 = vmlaq_laneq_f32(_sum0_0, _w1_0, _r0, 1);
_sum0_0 = vmlaq_laneq_f32(_sum0_0, _w2_0, _r0, 2);
_sum0_0 = vmlaq_laneq_f32(_sum0_0, _w3_0, _r0, 3);
_sum1_0 = vmlaq_laneq_f32(_sum1_0, _w0_0, _r1, 0);
_sum1_0 = vmlaq_laneq_f32(_sum1_0, _w1_0, _r1, 1);
_sum1_0 = vmlaq_laneq_f32(_sum1_0, _w2_0, _r1, 2);
_sum1_0 = vmlaq_laneq_f32(_sum1_0, _w3_0, _r1, 3);
_sum2_0 = vmlaq_laneq_f32(_sum2_0, _w0_0, _r2, 0);
_sum2_0 = vmlaq_laneq_f32(_sum2_0, _w1_0, _r2, 1);
_sum2_0 = vmlaq_laneq_f32(_sum2_0, _w2_0, _r2, 2);
_sum2_0 = vmlaq_laneq_f32(_sum2_0, _w3_0, _r2, 3);
_sum3_0 = vmlaq_laneq_f32(_sum3_0, _w0_0, _r3, 0);
_sum3_0 = vmlaq_laneq_f32(_sum3_0, _w1_0, _r3, 1);
_sum3_0 = vmlaq_laneq_f32(_sum3_0, _w2_0, _r3, 2);
_sum3_0 = vmlaq_laneq_f32(_sum3_0, _w3_0, _r3, 3);
_sum4_0 = vmlaq_laneq_f32(_sum4_0, _w0_0, _r4, 0);
_sum4_0 = vmlaq_laneq_f32(_sum4_0, _w1_0, _r4, 1);
_sum4_0 = vmlaq_laneq_f32(_sum4_0, _w2_0, _r4, 2);
_sum4_0 = vmlaq_laneq_f32(_sum4_0, _w3_0, _r4, 3);
_sum5_0 = vmlaq_laneq_f32(_sum5_0, _w0_0, _r5, 0);
_sum5_0 = vmlaq_laneq_f32(_sum5_0, _w1_0, _r5, 1);
_sum5_0 = vmlaq_laneq_f32(_sum5_0, _w2_0, _r5, 2);
_sum5_0 = vmlaq_laneq_f32(_sum5_0, _w3_0, _r5, 3);
_sum6_0 = vmlaq_laneq_f32(_sum6_0, _w0_0, _r6, 0);
_sum6_0 = vmlaq_laneq_f32(_sum6_0, _w1_0, _r6, 1);
_sum6_0 = vmlaq_laneq_f32(_sum6_0, _w2_0, _r6, 2);
_sum6_0 = vmlaq_laneq_f32(_sum6_0, _w3_0, _r6, 3);
_sum7_0 = vmlaq_laneq_f32(_sum7_0, _w0_0, _r7, 0);
_sum7_0 = vmlaq_laneq_f32(_sum7_0, _w1_0, _r7, 1);
_sum7_0 = vmlaq_laneq_f32(_sum7_0, _w2_0, _r7, 2);
_sum7_0 = vmlaq_laneq_f32(_sum7_0, _w3_0, _r7, 3);
_sum0_1 = vmlaq_laneq_f32(_sum0_1, _w0_1, _r0, 0);
_sum0_1 = vmlaq_laneq_f32(_sum0_1, _w1_1, _r0, 1);
_sum0_1 = vmlaq_laneq_f32(_sum0_1, _w2_1, _r0, 2);
_sum0_1 = vmlaq_laneq_f32(_sum0_1, _w3_1, _r0, 3);
_sum1_1 = vmlaq_laneq_f32(_sum1_1, _w0_1, _r1, 0);
_sum1_1 = vmlaq_laneq_f32(_sum1_1, _w1_1, _r1, 1);
_sum1_1 = vmlaq_laneq_f32(_sum1_1, _w2_1, _r1, 2);
_sum1_1 = vmlaq_laneq_f32(_sum1_1, _w3_1, _r1, 3);
_sum2_1 = vmlaq_laneq_f32(_sum2_1, _w0_1, _r2, 0);
_sum2_1 = vmlaq_laneq_f32(_sum2_1, _w1_1, _r2, 1);
_sum2_1 = vmlaq_laneq_f32(_sum2_1, _w2_1, _r2, 2);
_sum2_1 = vmlaq_laneq_f32(_sum2_1, _w3_1, _r2, 3);
_sum3_1 = vmlaq_laneq_f32(_sum3_1, _w0_1, _r3, 0);
_sum3_1 = vmlaq_laneq_f32(_sum3_1, _w1_1, _r3, 1);
_sum3_1 = vmlaq_laneq_f32(_sum3_1, _w2_1, _r3, 2);
_sum3_1 = vmlaq_laneq_f32(_sum3_1, _w3_1, _r3, 3);
_sum4_1 = vmlaq_laneq_f32(_sum4_1, _w0_1, _r4, 0);
_sum4_1 = vmlaq_laneq_f32(_sum4_1, _w1_1, _r4, 1);
_sum4_1 = vmlaq_laneq_f32(_sum4_1, _w2_1, _r4, 2);
_sum4_1 = vmlaq_laneq_f32(_sum4_1, _w3_1, _r4, 3);
_sum5_1 = vmlaq_laneq_f32(_sum5_1, _w0_1, _r5, 0);
_sum5_1 = vmlaq_laneq_f32(_sum5_1, _w1_1, _r5, 1);
_sum5_1 = vmlaq_laneq_f32(_sum5_1, _w2_1, _r5, 2);
_sum5_1 = vmlaq_laneq_f32(_sum5_1, _w3_1, _r5, 3);
_sum6_1 = vmlaq_laneq_f32(_sum6_1, _w0_1, _r6, 0);
_sum6_1 = vmlaq_laneq_f32(_sum6_1, _w1_1, _r6, 1);
_sum6_1 = vmlaq_laneq_f32(_sum6_1, _w2_1, _r6, 2);
_sum6_1 = vmlaq_laneq_f32(_sum6_1, _w3_1, _r6, 3);
_sum7_1 = vmlaq_laneq_f32(_sum7_1, _w0_1, _r7, 0);
_sum7_1 = vmlaq_laneq_f32(_sum7_1, _w1_1, _r7, 1);
_sum7_1 = vmlaq_laneq_f32(_sum7_1, _w2_1, _r7, 2);
_sum7_1 = vmlaq_laneq_f32(_sum7_1, _w3_1, _r7, 3);
// sum0 += r0[0] * k0[0];
r0 += 32;
k0 += 16;
k1 += 16;
}
vst1q_f32(output0_tm + 0, _sum0_0);
vst1q_f32(output0_tm + 4, _sum1_0);
vst1q_f32(output0_tm + 8, _sum2_0);
vst1q_f32(output0_tm + 12, _sum3_0);
vst1q_f32(output0_tm + 16, _sum4_0);
vst1q_f32(output0_tm + 20, _sum5_0);
vst1q_f32(output0_tm + 24, _sum6_0);
vst1q_f32(output0_tm + 28, _sum7_0);
output0_tm += 32;
vst1q_f32(output1_tm + 0, _sum0_1);
vst1q_f32(output1_tm + 4, _sum1_1);
vst1q_f32(output1_tm + 8, _sum2_1);
vst1q_f32(output1_tm + 12, _sum3_1);
vst1q_f32(output1_tm + 16, _sum4_1);
vst1q_f32(output1_tm + 20, _sum5_1);
vst1q_f32(output1_tm + 24, _sum6_1);
vst1q_f32(output1_tm + 28, _sum7_1);
output1_tm += 32;
}
for (; i+3<tiles; i+=4)
{
const float* r0 = bb2.row(i/8 + (i%8)/4);
const float* k0 = kernel0_tm.row(r);
const float* k1 = kernel1_tm.row(r);
float32x4_t _sum0_0 = vdupq_n_f32(0.f);
float32x4_t _sum1_0 = vdupq_n_f32(0.f);
float32x4_t _sum2_0 = vdupq_n_f32(0.f);
float32x4_t _sum3_0 = vdupq_n_f32(0.f);
float32x4_t _sum0_1 = vdupq_n_f32(0.f);
float32x4_t _sum1_1 = vdupq_n_f32(0.f);
float32x4_t _sum2_1 = vdupq_n_f32(0.f);
float32x4_t _sum3_1 = vdupq_n_f32(0.f);
int q=0;
for (; q<inch; q++)
{
float32x4_t _r0 = vld1q_f32( r0 );
float32x4_t _r1 = vld1q_f32( r0 + 4 );
float32x4_t _r2 = vld1q_f32( r0 + 8 );
float32x4_t _r3 = vld1q_f32( r0 + 12 );
float32x4_t _w0_0 = vld1q_f32( k0 );
float32x4_t _w1_0 = vld1q_f32( k0 + 4 );
float32x4_t _w2_0 = vld1q_f32( k0 + 8 );
float32x4_t _w3_0 = vld1q_f32( k0 + 12 );
float32x4_t _w0_1 = vld1q_f32( k1 );
float32x4_t _w1_1 = vld1q_f32( k1 + 4 );
float32x4_t _w2_1 = vld1q_f32( k1 + 8 );
float32x4_t _w3_1 = vld1q_f32( k1 + 12 );
_sum0_0 = vmlaq_laneq_f32(_sum0_0, _w0_0, _r0, 0);
_sum0_0 = vmlaq_laneq_f32(_sum0_0, _w1_0, _r0, 1);
_sum0_0 = vmlaq_laneq_f32(_sum0_0, _w2_0, _r0, 2);
_sum0_0 = vmlaq_laneq_f32(_sum0_0, _w3_0, _r0, 3);
_sum1_0 = vmlaq_laneq_f32(_sum1_0, _w0_0, _r1, 0);
_sum1_0 = vmlaq_laneq_f32(_sum1_0, _w1_0, _r1, 1);
_sum1_0 = vmlaq_laneq_f32(_sum1_0, _w2_0, _r1, 2);
_sum1_0 = vmlaq_laneq_f32(_sum1_0, _w3_0, _r1, 3);
_sum2_0 = vmlaq_laneq_f32(_sum2_0, _w0_0, _r2, 0);
_sum2_0 = vmlaq_laneq_f32(_sum2_0, _w1_0, _r2, 1);
_sum2_0 = vmlaq_laneq_f32(_sum2_0, _w2_0, _r2, 2);
_sum2_0 = vmlaq_laneq_f32(_sum2_0, _w3_0, _r2, 3);
_sum3_0 = vmlaq_laneq_f32(_sum3_0, _w0_0, _r3, 0);
_sum3_0 = vmlaq_laneq_f32(_sum3_0, _w1_0, _r3, 1);
_sum3_0 = vmlaq_laneq_f32(_sum3_0, _w2_0, _r3, 2);
_sum3_0 = vmlaq_laneq_f32(_sum3_0, _w3_0, _r3, 3);
_sum0_1 = vmlaq_laneq_f32(_sum0_1, _w0_1, _r0, 0);
_sum0_1 = vmlaq_laneq_f32(_sum0_1, _w1_1, _r0, 1);
_sum0_1 = vmlaq_laneq_f32(_sum0_1, _w2_1, _r0, 2);
_sum0_1 = vmlaq_laneq_f32(_sum0_1, _w3_1, _r0, 3);
_sum1_1 = vmlaq_laneq_f32(_sum1_1, _w0_1, _r1, 0);
_sum1_1 = vmlaq_laneq_f32(_sum1_1, _w1_1, _r1, 1);
_sum1_1 = vmlaq_laneq_f32(_sum1_1, _w2_1, _r1, 2);
_sum1_1 = vmlaq_laneq_f32(_sum1_1, _w3_1, _r1, 3);
_sum2_1 = vmlaq_laneq_f32(_sum2_1, _w0_1, _r2, 0);
_sum2_1 = vmlaq_laneq_f32(_sum2_1, _w1_1, _r2, 1);
_sum2_1 = vmlaq_laneq_f32(_sum2_1, _w2_1, _r2, 2);
_sum2_1 = vmlaq_laneq_f32(_sum2_1, _w3_1, _r2, 3);
_sum3_1 = vmlaq_laneq_f32(_sum3_1, _w0_1, _r3, 0);
_sum3_1 = vmlaq_laneq_f32(_sum3_1, _w1_1, _r3, 1);
_sum3_1 = vmlaq_laneq_f32(_sum3_1, _w2_1, _r3, 2);
_sum3_1 = vmlaq_laneq_f32(_sum3_1, _w3_1, _r3, 3);
// sum0 += r0[0] * k0[0];
r0 += 16;
k0 += 16;
k1 += 16;
}
vst1q_f32(output0_tm + 0, _sum0_0);
vst1q_f32(output0_tm + 4, _sum1_0);
vst1q_f32(output0_tm + 8, _sum2_0);
vst1q_f32(output0_tm + 12, _sum3_0);
output0_tm += 16;
vst1q_f32(output1_tm + 0, _sum0_1);
vst1q_f32(output1_tm + 4, _sum1_1);
vst1q_f32(output1_tm + 8, _sum2_1);
vst1q_f32(output1_tm + 12, _sum3_1);
output1_tm += 16;
}
for (; i+1<tiles; i+=2)
{
const float* r0 = bb2.row(i/8 + (i%8)/4 + (i%4)/2);
const float* k0 = kernel0_tm.row(r);
const float* k1 = kernel1_tm.row(r);
float32x4_t _sum0_0 = vdupq_n_f32(0.f);
float32x4_t _sum1_0 = vdupq_n_f32(0.f);
float32x4_t _sum0_1 = vdupq_n_f32(0.f);
float32x4_t _sum1_1 = vdupq_n_f32(0.f);
int q=0;
for (; q<inch; q++)
{
float32x4_t _r0 = vld1q_f32( r0 );
float32x4_t _r1 = vld1q_f32( r0 + 4 );
float32x4_t _w0_0 = vld1q_f32( k0 );
float32x4_t _w1_0 = vld1q_f32( k0 + 4 );
float32x4_t _w2_0 = vld1q_f32( k0 + 8 );
float32x4_t _w3_0 = vld1q_f32( k0 + 12 );
float32x4_t _w0_1 = vld1q_f32( k1 );
float32x4_t _w1_1 = vld1q_f32( k1 + 4 );
float32x4_t _w2_1 = vld1q_f32( k1 + 8 );
float32x4_t _w3_1 = vld1q_f32( k1 + 12 );
_sum0_0 = vmlaq_laneq_f32(_sum0_0, _w0_0, _r0, 0);
_sum0_0 = vmlaq_laneq_f32(_sum0_0, _w1_0, _r0, 1);
_sum0_0 = vmlaq_laneq_f32(_sum0_0, _w2_0, _r0, 2);
_sum0_0 = vmlaq_laneq_f32(_sum0_0, _w3_0, _r0, 3);
_sum1_0 = vmlaq_laneq_f32(_sum1_0, _w0_0, _r1, 0);
_sum1_0 = vmlaq_laneq_f32(_sum1_0, _w1_0, _r1, 1);
_sum1_0 = vmlaq_laneq_f32(_sum1_0, _w2_0, _r1, 2);
_sum1_0 = vmlaq_laneq_f32(_sum1_0, _w3_0, _r1, 3);
_sum0_1 = vmlaq_laneq_f32(_sum0_1, _w0_1, _r0, 0);
_sum0_1 = vmlaq_laneq_f32(_sum0_1, _w1_1, _r0, 1);
_sum0_1 = vmlaq_laneq_f32(_sum0_1, _w2_1, _r0, 2);
_sum0_1 = vmlaq_laneq_f32(_sum0_1, _w3_1, _r0, 3);
_sum1_1 = vmlaq_laneq_f32(_sum1_1, _w0_1, _r1, 0);
_sum1_1 = vmlaq_laneq_f32(_sum1_1, _w1_1, _r1, 1);
_sum1_1 = vmlaq_laneq_f32(_sum1_1, _w2_1, _r1, 2);
_sum1_1 = vmlaq_laneq_f32(_sum1_1, _w3_1, _r1, 3);
// sum0 += r0[0] * k0[0];
r0 += 8;
k0 += 16;
k1 += 16;
}
vst1q_f32(output0_tm + 0, _sum0_0);
vst1q_f32(output0_tm + 4, _sum1_0);
output0_tm += 8;
vst1q_f32(output1_tm + 0, _sum0_1);
vst1q_f32(output1_tm + 4, _sum1_1);
output1_tm += 8;
}
for (; i<tiles; i++)
{
const float* r0 = bb2.row(i/8 + (i%8)/4 + (i%4)/2 + i%2);
const float* k0 = kernel0_tm.row(r);
const float* k1 = kernel1_tm.row(r);
float32x4_t _sum0_0 = vdupq_n_f32(0.f);
float32x4_t _sum0_1 = vdupq_n_f32(0.f);
int q=0;
for (; q<inch; q++)
{
float32x4_t _r0 = vld1q_f32( r0 );
float32x4_t _w0_0 = vld1q_f32( k0 );
float32x4_t _w1_0 = vld1q_f32( k0 + 4 );
float32x4_t _w2_0 = vld1q_f32( k0 + 8 );
float32x4_t _w3_0 = vld1q_f32( k0 + 12 );
float32x4_t _w0_1 = vld1q_f32( k1 );
float32x4_t _w1_1 = vld1q_f32( k1 + 4 );
float32x4_t _w2_1 = vld1q_f32( k1 + 8 );
float32x4_t _w3_1 = vld1q_f32( k1 + 12 );
_sum0_0 = vmlaq_laneq_f32(_sum0_0, _w0_0, _r0, 0);
_sum0_0 = vmlaq_laneq_f32(_sum0_0, _w1_0, _r0, 1);
_sum0_0 = vmlaq_laneq_f32(_sum0_0, _w2_0, _r0, 2);
_sum0_0 = vmlaq_laneq_f32(_sum0_0, _w3_0, _r0, 3);
_sum0_1 = vmlaq_laneq_f32(_sum0_1, _w0_1, _r0, 0);
_sum0_1 = vmlaq_laneq_f32(_sum0_1, _w1_1, _r0, 1);
_sum0_1 = vmlaq_laneq_f32(_sum0_1, _w2_1, _r0, 2);
_sum0_1 = vmlaq_laneq_f32(_sum0_1, _w3_1, _r0, 3);
// sum0 += r0[0] * k0[0];
r0 += 4;
k0 += 16;
k1 += 16;
}
vst1q_f32(output0_tm, _sum0_0);
output0_tm += 4;
vst1q_f32(output1_tm, _sum0_1);
output1_tm += 4;
}
}
}
#endif // __ARM_NEON && __aarch64__
#pragma omp parallel for num_threads(opt.num_threads)
for (int p=remain_outch_start; p<outch; p++)
{
Mat out0_tm = top_blob_tm.channel(p);
const Mat kernel0_tm = kernel_tm.channel(p);
float* output0_tm = out0_tm;
for (int r=0; r<64; r++)
{
const Mat bb2 = bottom_blob_tm2.channel(r);
int i=0;
for (; i+7<tiles; i+=8)
{
const float* r0 = bb2.row(i/8);
const float* k0 = kernel0_tm.row(r);
float32x4_t _sum0 = vdupq_n_f32(0.f);
float32x4_t _sum1 = vdupq_n_f32(0.f);
float32x4_t _sum2 = vdupq_n_f32(0.f);
float32x4_t _sum3 = vdupq_n_f32(0.f);
float32x4_t _sum4 = vdupq_n_f32(0.f);
float32x4_t _sum5 = vdupq_n_f32(0.f);
float32x4_t _sum6 = vdupq_n_f32(0.f);
float32x4_t _sum7 = vdupq_n_f32(0.f);
int q=0;
for (; q<inch; q++)
{
float32x4_t _r0 = vld1q_f32( r0 );
float32x4_t _r1 = vld1q_f32( r0 + 4 );
float32x4_t _r2 = vld1q_f32( r0 + 8 );
float32x4_t _r3 = vld1q_f32( r0 + 12 );
float32x4_t _r4 = vld1q_f32( r0 + 16 );
float32x4_t _r5 = vld1q_f32( r0 + 20 );
float32x4_t _r6 = vld1q_f32( r0 + 24 );
float32x4_t _r7 = vld1q_f32( r0 + 28 );
float32x4_t _w0 = vld1q_f32( k0 );
float32x4_t _w1 = vld1q_f32( k0 + 4 );
float32x4_t _w2 = vld1q_f32( k0 + 8 );
float32x4_t _w3 = vld1q_f32( k0 + 12 );
#if __aarch64__
_sum0 = vmlaq_laneq_f32(_sum0, _w0, _r0, 0);
_sum0 = vmlaq_laneq_f32(_sum0, _w1, _r0, 1);
_sum0 = vmlaq_laneq_f32(_sum0, _w2, _r0, 2);
_sum0 = vmlaq_laneq_f32(_sum0, _w3, _r0, 3);
_sum1 = vmlaq_laneq_f32(_sum1, _w0, _r1, 0);
_sum1 = vmlaq_laneq_f32(_sum1, _w1, _r1, 1);
_sum1 = vmlaq_laneq_f32(_sum1, _w2, _r1, 2);
_sum1 = vmlaq_laneq_f32(_sum1, _w3, _r1, 3);
_sum2 = vmlaq_laneq_f32(_sum2, _w0, _r2, 0);
_sum2 = vmlaq_laneq_f32(_sum2, _w1, _r2, 1);
_sum2 = vmlaq_laneq_f32(_sum2, _w2, _r2, 2);
_sum2 = vmlaq_laneq_f32(_sum2, _w3, _r2, 3);
_sum3 = vmlaq_laneq_f32(_sum3, _w0, _r3, 0);
_sum3 = vmlaq_laneq_f32(_sum3, _w1, _r3, 1);
_sum3 = vmlaq_laneq_f32(_sum3, _w2, _r3, 2);
_sum3 = vmlaq_laneq_f32(_sum3, _w3, _r3, 3);
_sum4 = vmlaq_laneq_f32(_sum4, _w0, _r4, 0);
_sum4 = vmlaq_laneq_f32(_sum4, _w1, _r4, 1);
_sum4 = vmlaq_laneq_f32(_sum4, _w2, _r4, 2);
_sum4 = vmlaq_laneq_f32(_sum4, _w3, _r4, 3);
_sum5 = vmlaq_laneq_f32(_sum5, _w0, _r5, 0);
_sum5 = vmlaq_laneq_f32(_sum5, _w1, _r5, 1);
_sum5 = vmlaq_laneq_f32(_sum5, _w2, _r5, 2);
_sum5 = vmlaq_laneq_f32(_sum5, _w3, _r5, 3);
_sum6 = vmlaq_laneq_f32(_sum6, _w0, _r6, 0);
_sum6 = vmlaq_laneq_f32(_sum6, _w1, _r6, 1);
_sum6 = vmlaq_laneq_f32(_sum6, _w2, _r6, 2);
_sum6 = vmlaq_laneq_f32(_sum6, _w3, _r6, 3);
_sum7 = vmlaq_laneq_f32(_sum7, _w0, _r7, 0);
_sum7 = vmlaq_laneq_f32(_sum7, _w1, _r7, 1);
_sum7 = vmlaq_laneq_f32(_sum7, _w2, _r7, 2);
_sum7 = vmlaq_laneq_f32(_sum7, _w3, _r7, 3);
#else
_sum0 = vmlaq_lane_f32(_sum0, _w0, vget_low_f32(_r0), 0);
_sum0 = vmlaq_lane_f32(_sum0, _w1, vget_low_f32(_r0), 1);
_sum0 = vmlaq_lane_f32(_sum0, _w2, vget_high_f32(_r0), 0);
_sum0 = vmlaq_lane_f32(_sum0, _w3, vget_high_f32(_r0), 1);
_sum1 = vmlaq_lane_f32(_sum1, _w0, vget_low_f32(_r1), 0);
_sum1 = vmlaq_lane_f32(_sum1, _w1, vget_low_f32(_r1), 1);
_sum1 = vmlaq_lane_f32(_sum1, _w2, vget_high_f32(_r1), 0);
_sum1 = vmlaq_lane_f32(_sum1, _w3, vget_high_f32(_r1), 1);
_sum2 = vmlaq_lane_f32(_sum2, _w0, vget_low_f32(_r2), 0);
_sum2 = vmlaq_lane_f32(_sum2, _w1, vget_low_f32(_r2), 1);
_sum2 = vmlaq_lane_f32(_sum2, _w2, vget_high_f32(_r2), 0);
_sum2 = vmlaq_lane_f32(_sum2, _w3, vget_high_f32(_r2), 1);
_sum3 = vmlaq_lane_f32(_sum3, _w0, vget_low_f32(_r3), 0);
_sum3 = vmlaq_lane_f32(_sum3, _w1, vget_low_f32(_r3), 1);
_sum3 = vmlaq_lane_f32(_sum3, _w2, vget_high_f32(_r3), 0);
_sum3 = vmlaq_lane_f32(_sum3, _w3, vget_high_f32(_r3), 1);
_sum4 = vmlaq_lane_f32(_sum4, _w0, vget_low_f32(_r4), 0);
_sum4 = vmlaq_lane_f32(_sum4, _w1, vget_low_f32(_r4), 1);
_sum4 = vmlaq_lane_f32(_sum4, _w2, vget_high_f32(_r4), 0);
_sum4 = vmlaq_lane_f32(_sum4, _w3, vget_high_f32(_r4), 1);
_sum5 = vmlaq_lane_f32(_sum5, _w0, vget_low_f32(_r5), 0);
_sum5 = vmlaq_lane_f32(_sum5, _w1, vget_low_f32(_r5), 1);
_sum5 = vmlaq_lane_f32(_sum5, _w2, vget_high_f32(_r5), 0);
_sum5 = vmlaq_lane_f32(_sum5, _w3, vget_high_f32(_r5), 1);
_sum6 = vmlaq_lane_f32(_sum6, _w0, vget_low_f32(_r6), 0);
_sum6 = vmlaq_lane_f32(_sum6, _w1, vget_low_f32(_r6), 1);
_sum6 = vmlaq_lane_f32(_sum6, _w2, vget_high_f32(_r6), 0);
_sum6 = vmlaq_lane_f32(_sum6, _w3, vget_high_f32(_r6), 1);
_sum7 = vmlaq_lane_f32(_sum7, _w0, vget_low_f32(_r7), 0);
_sum7 = vmlaq_lane_f32(_sum7, _w1, vget_low_f32(_r7), 1);
_sum7 = vmlaq_lane_f32(_sum7, _w2, vget_high_f32(_r7), 0);
_sum7 = vmlaq_lane_f32(_sum7, _w3, vget_high_f32(_r7), 1);
#endif
// sum0 += r0[0] * k0[0];
r0 += 32;
k0 += 16;
}
vst1q_f32(output0_tm + 0, _sum0);
vst1q_f32(output0_tm + 4, _sum1);
vst1q_f32(output0_tm + 8, _sum2);
vst1q_f32(output0_tm + 12, _sum3);
vst1q_f32(output0_tm + 16, _sum4);
vst1q_f32(output0_tm + 20, _sum5);
vst1q_f32(output0_tm + 24, _sum6);
vst1q_f32(output0_tm + 28, _sum7);
output0_tm += 32;
}
for (; i+3<tiles; i+=4)
{
const float* r0 = bb2.row(i/8 + (i%8)/4);
const float* k0 = kernel0_tm.row(r);
float32x4_t _sum0 = vdupq_n_f32(0.f);
float32x4_t _sum1 = vdupq_n_f32(0.f);
float32x4_t _sum2 = vdupq_n_f32(0.f);
float32x4_t _sum3 = vdupq_n_f32(0.f);
int q=0;
for (; q<inch; q++)
{
float32x4_t _r0 = vld1q_f32( r0 );
float32x4_t _r1 = vld1q_f32( r0 + 4 );
float32x4_t _r2 = vld1q_f32( r0 + 8 );
float32x4_t _r3 = vld1q_f32( r0 + 12 );
float32x4_t _w0 = vld1q_f32( k0 );
float32x4_t _w1 = vld1q_f32( k0 + 4 );
float32x4_t _w2 = vld1q_f32( k0 + 8 );
float32x4_t _w3 = vld1q_f32( k0 + 12 );
#if __aarch64__
_sum0 = vmlaq_laneq_f32(_sum0, _w0, _r0, 0);
_sum0 = vmlaq_laneq_f32(_sum0, _w1, _r0, 1);
_sum0 = vmlaq_laneq_f32(_sum0, _w2, _r0, 2);
_sum0 = vmlaq_laneq_f32(_sum0, _w3, _r0, 3);
_sum1 = vmlaq_laneq_f32(_sum1, _w0, _r1, 0);
_sum1 = vmlaq_laneq_f32(_sum1, _w1, _r1, 1);
_sum1 = vmlaq_laneq_f32(_sum1, _w2, _r1, 2);
_sum1 = vmlaq_laneq_f32(_sum1, _w3, _r1, 3);
_sum2 = vmlaq_laneq_f32(_sum2, _w0, _r2, 0);
_sum2 = vmlaq_laneq_f32(_sum2, _w1, _r2, 1);
_sum2 = vmlaq_laneq_f32(_sum2, _w2, _r2, 2);
_sum2 = vmlaq_laneq_f32(_sum2, _w3, _r2, 3);
_sum3 = vmlaq_laneq_f32(_sum3, _w0, _r3, 0);
_sum3 = vmlaq_laneq_f32(_sum3, _w1, _r3, 1);
_sum3 = vmlaq_laneq_f32(_sum3, _w2, _r3, 2);
_sum3 = vmlaq_laneq_f32(_sum3, _w3, _r3, 3);
#else
_sum0 = vmlaq_lane_f32(_sum0, _w0, vget_low_f32(_r0), 0);
_sum0 = vmlaq_lane_f32(_sum0, _w1, vget_low_f32(_r0), 1);
_sum0 = vmlaq_lane_f32(_sum0, _w2, vget_high_f32(_r0), 0);
_sum0 = vmlaq_lane_f32(_sum0, _w3, vget_high_f32(_r0), 1);
_sum1 = vmlaq_lane_f32(_sum1, _w0, vget_low_f32(_r1), 0);
_sum1 = vmlaq_lane_f32(_sum1, _w1, vget_low_f32(_r1), 1);
_sum1 = vmlaq_lane_f32(_sum1, _w2, vget_high_f32(_r1), 0);
_sum1 = vmlaq_lane_f32(_sum1, _w3, vget_high_f32(_r1), 1);
_sum2 = vmlaq_lane_f32(_sum2, _w0, vget_low_f32(_r2), 0);
_sum2 = vmlaq_lane_f32(_sum2, _w1, vget_low_f32(_r2), 1);
_sum2 = vmlaq_lane_f32(_sum2, _w2, vget_high_f32(_r2), 0);
_sum2 = vmlaq_lane_f32(_sum2, _w3, vget_high_f32(_r2), 1);
_sum3 = vmlaq_lane_f32(_sum3, _w0, vget_low_f32(_r3), 0);
_sum3 = vmlaq_lane_f32(_sum3, _w1, vget_low_f32(_r3), 1);
_sum3 = vmlaq_lane_f32(_sum3, _w2, vget_high_f32(_r3), 0);
_sum3 = vmlaq_lane_f32(_sum3, _w3, vget_high_f32(_r3), 1);
#endif
// sum0 += r0[0] * k0[0];
r0 += 16;
k0 += 16;
}
vst1q_f32(output0_tm + 0, _sum0);
vst1q_f32(output0_tm + 4, _sum1);
vst1q_f32(output0_tm + 8, _sum2);
vst1q_f32(output0_tm + 12, _sum3);
output0_tm += 16;
}
for (; i+1<tiles; i+=2)
{
const float* r0 = bb2.row(i/8 + (i%8)/4 + (i%4)/2);
const float* k0 = kernel0_tm.row(r);
float32x4_t _sum0 = vdupq_n_f32(0.f);
float32x4_t _sum1 = vdupq_n_f32(0.f);
int q=0;
for (; q<inch; q++)
{
float32x4_t _r0 = vld1q_f32( r0 );
float32x4_t _r1 = vld1q_f32( r0 + 4 );
float32x4_t _w0 = vld1q_f32( k0 );
float32x4_t _w1 = vld1q_f32( k0 + 4 );
float32x4_t _w2 = vld1q_f32( k0 + 8 );
float32x4_t _w3 = vld1q_f32( k0 + 12 );
#if __aarch64__
_sum0 = vmlaq_laneq_f32(_sum0, _w0, _r0, 0);
_sum0 = vmlaq_laneq_f32(_sum0, _w1, _r0, 1);
_sum0 = vmlaq_laneq_f32(_sum0, _w2, _r0, 2);
_sum0 = vmlaq_laneq_f32(_sum0, _w3, _r0, 3);
_sum1 = vmlaq_laneq_f32(_sum1, _w0, _r1, 0);
_sum1 = vmlaq_laneq_f32(_sum1, _w1, _r1, 1);
_sum1 = vmlaq_laneq_f32(_sum1, _w2, _r1, 2);
_sum1 = vmlaq_laneq_f32(_sum1, _w3, _r1, 3);
#else
_sum0 = vmlaq_lane_f32(_sum0, _w0, vget_low_f32(_r0), 0);
_sum0 = vmlaq_lane_f32(_sum0, _w1, vget_low_f32(_r0), 1);
_sum0 = vmlaq_lane_f32(_sum0, _w2, vget_high_f32(_r0), 0);
_sum0 = vmlaq_lane_f32(_sum0, _w3, vget_high_f32(_r0), 1);
_sum1 = vmlaq_lane_f32(_sum1, _w0, vget_low_f32(_r1), 0);
_sum1 = vmlaq_lane_f32(_sum1, _w1, vget_low_f32(_r1), 1);
_sum1 = vmlaq_lane_f32(_sum1, _w2, vget_high_f32(_r1), 0);
_sum1 = vmlaq_lane_f32(_sum1, _w3, vget_high_f32(_r1), 1);
#endif
// sum0 += r0[0] * k0[0];
r0 += 8;
k0 += 16;
}
vst1q_f32(output0_tm + 0, _sum0);
vst1q_f32(output0_tm + 4, _sum1);
output0_tm += 8;
}
for (; i<tiles; i++)
{
const float* r0 = bb2.row(i/8 + (i%8)/4 + (i%4)/2 + i%2);
const float* k0 = kernel0_tm.row(r);
float32x4_t _sum0 = vdupq_n_f32(0.f);
int q=0;
for (; q<inch; q++)
{
float32x4_t _r0 = vld1q_f32( r0 );
float32x4_t _w0 = vld1q_f32( k0 );
float32x4_t _w1 = vld1q_f32( k0 + 4 );
float32x4_t _w2 = vld1q_f32( k0 + 8 );
float32x4_t _w3 = vld1q_f32( k0 + 12 );
#if __aarch64__
_sum0 = vmlaq_laneq_f32(_sum0, _w0, _r0, 0);
_sum0 = vmlaq_laneq_f32(_sum0, _w1, _r0, 1);
_sum0 = vmlaq_laneq_f32(_sum0, _w2, _r0, 2);
_sum0 = vmlaq_laneq_f32(_sum0, _w3, _r0, 3);
#else
_sum0 = vmlaq_lane_f32(_sum0, _w0, vget_low_f32(_r0), 0);
_sum0 = vmlaq_lane_f32(_sum0, _w1, vget_low_f32(_r0), 1);
_sum0 = vmlaq_lane_f32(_sum0, _w2, vget_high_f32(_r0), 0);
_sum0 = vmlaq_lane_f32(_sum0, _w3, vget_high_f32(_r0), 1);
#endif
// sum0 += r0[0] * k0[0];
r0 += 4;
k0 += 16;
}
vst1q_f32(output0_tm, _sum0);
output0_tm += 4;
}
}
}
}
bottom_blob_tm = Mat();
// END dot
// BEGIN transform output
Mat top_blob_bordered;
top_blob_bordered.create(outw, outh, outch, elemsize, elempack);
{
// 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)
int w_tm = outw / 6 * 8;
int h_tm = outh / 6 * 8;
const int tiles = w_tm/8 * h_tm/8;
#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_bordered.channel(p);
// const float bias0 = bias ? bias[p] : 0.f;
float32x4_t _bias0 = bias ? vld1q_f32( (const float*)bias + p * 4) : vdupq_n_f32(0.f);
float tmp[6][8][4];
// tile
for (int i=0; i<outh/6; i++)
{
for (int j=0; j<outw/6; j++)
{
// top_blob_tm.create(tiles, 64, outch, elemsize, elempack);
const float* output0_tm_0 = (const float*)out0_tm + (i * w_tm/8 + j) * 4;
float* output0 = out0.row(i * 6) + (j * 6) * 4;
// TODO neon optimize
for (int m=0; m<8; m++)
{
float32x4_t _out0tm0 = vld1q_f32(output0_tm_0);
output0_tm_0 += tiles * 4;
float32x4_t _out0tm1 = vld1q_f32(output0_tm_0);
output0_tm_0 += tiles * 4;
float32x4_t _out0tm2 = vld1q_f32(output0_tm_0);
output0_tm_0 += tiles * 4;
float32x4_t _out0tm3 = vld1q_f32(output0_tm_0);
output0_tm_0 += tiles * 4;
float32x4_t _out0tm4 = vld1q_f32(output0_tm_0);
output0_tm_0 += tiles * 4;
float32x4_t _out0tm5 = vld1q_f32(output0_tm_0);
output0_tm_0 += tiles * 4;
float32x4_t _out0tm6 = vld1q_f32(output0_tm_0);
output0_tm_0 += tiles * 4;
float32x4_t _out0tm7 = vld1q_f32(output0_tm_0);
output0_tm_0 += tiles * 4;
float32x4_t _tmp024a = vaddq_f32(_out0tm1, _out0tm2);
float32x4_t _tmp135a = vsubq_f32(_out0tm1, _out0tm2);
// float tmp024a = output0_tm[1] + output0_tm[2];
// float tmp135a = output0_tm[1] - output0_tm[2];
float32x4_t _tmp024b = vaddq_f32(_out0tm3, _out0tm4);
float32x4_t _tmp135b = vsubq_f32(_out0tm3, _out0tm4);
// float tmp024b = output0_tm[3] + output0_tm[4];
// float tmp135b = output0_tm[3] - output0_tm[4];
float32x4_t _tmp024c = vaddq_f32(_out0tm5, _out0tm6);
float32x4_t _tmp135c = vsubq_f32(_out0tm5, _out0tm6);
// float tmp024c = output0_tm[5] + output0_tm[6];
// float tmp135c = output0_tm[5] - output0_tm[6];
float32x4_t _tmp0m = vaddq_f32(vaddq_f32(_out0tm0, _tmp024a), vmlaq_n_f32(_tmp024b, _tmp024c, 32.f));
float32x4_t _tmp2m = vmlaq_n_f32(vmlaq_n_f32(_tmp024a, _tmp024b, 4.f), _tmp024c, 8.f);
float32x4_t _tmp4m = vmlaq_n_f32(vmlaq_n_f32(_tmp024a, _tmp024b, 16.f), _tmp024c, 2.f);
vst1q_f32(tmp[0][m], _tmp0m);
vst1q_f32(tmp[2][m], _tmp2m);
vst1q_f32(tmp[4][m], _tmp4m);
// tmp[0][m] = output0_tm[0] + tmp024a + tmp024b + tmp024c * 32;
// tmp[2][m] = tmp024a + tmp024b * 4 + tmp024c * 8;
// tmp[4][m] = tmp024a + tmp024b * 16 + tmp024c + tmp024c;
float32x4_t _tmp1m = vmlaq_n_f32(vmlaq_n_f32(_tmp135a, _tmp135b, 2.f), _tmp135c, 16.f);
float32x4_t _tmp3m = vmlaq_n_f32(vmlaq_n_f32(_tmp135a, _tmp135b, 8.f), _tmp135c, 4.f);
float32x4_t _tmp5m = vaddq_f32(vaddq_f32(_out0tm7, _tmp135a), vmlaq_n_f32(_tmp135c, _tmp135b, 32.f));
vst1q_f32(tmp[1][m], _tmp1m);
vst1q_f32(tmp[3][m], _tmp3m);
vst1q_f32(tmp[5][m], _tmp5m);
// tmp[1][m] = tmp135a + tmp135b + tmp135b + tmp135c * 16;
// tmp[3][m] = tmp135a + tmp135b * 8 + tmp135c * 4;
// tmp[5][m] = output0_tm[7] + tmp135a + tmp135b * 32 + tmp135c;
}
for (int m=0; m<6; m++)
{
float32x4_t _tmp00 = vld1q_f32(tmp[m][0]);
float32x4_t _tmp01 = vld1q_f32(tmp[m][1]);
float32x4_t _tmp02 = vld1q_f32(tmp[m][2]);
float32x4_t _tmp03 = vld1q_f32(tmp[m][3]);
float32x4_t _tmp04 = vld1q_f32(tmp[m][4]);
float32x4_t _tmp05 = vld1q_f32(tmp[m][5]);
float32x4_t _tmp06 = vld1q_f32(tmp[m][6]);
float32x4_t _tmp07 = vld1q_f32(tmp[m][7]);
float32x4_t _tmp024a = vaddq_f32(_tmp01, _tmp02);
float32x4_t _tmp135a = vsubq_f32(_tmp01, _tmp02);
// float tmp024a = tmp0[1] + tmp0[2];
// float tmp135a = tmp0[1] - tmp0[2];
float32x4_t _tmp024b = vaddq_f32(_tmp03, _tmp04);
float32x4_t _tmp135b = vsubq_f32(_tmp03, _tmp04);
// float tmp024b = tmp0[3] + tmp0[4];
// float tmp135b = tmp0[3] - tmp0[4];
float32x4_t _tmp024c = vaddq_f32(_tmp05, _tmp06);
float32x4_t _tmp135c = vsubq_f32(_tmp05, _tmp06);
// float tmp024c = tmp0[5] + tmp0[6];
// float tmp135c = tmp0[5] - tmp0[6];
float32x4_t _out00 = vaddq_f32(_bias0, vaddq_f32(vaddq_f32(_tmp00, _tmp024a), vmlaq_n_f32(_tmp024b, _tmp024c, 32.f)));
float32x4_t _out02 = vaddq_f32(_bias0, vmlaq_n_f32(vmlaq_n_f32(_tmp024a, _tmp024b, 4.f), _tmp024c, 8.f));
float32x4_t _out04 = vaddq_f32(_bias0, vmlaq_n_f32(vmlaq_n_f32(_tmp024a, _tmp024b, 16.f), _tmp024c, 2.f));
vst1q_f32(output0, _out00);
vst1q_f32(output0 + 8, _out02);
vst1q_f32(output0 + 16, _out04);
// 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;
float32x4_t _out01 = vaddq_f32(_bias0, vmlaq_n_f32(vmlaq_n_f32(_tmp135a, _tmp135b, 2.f), _tmp135c, 16.f));
float32x4_t _out03 = vaddq_f32(_bias0, vmlaq_n_f32(vmlaq_n_f32(_tmp135a, _tmp135b, 8.f), _tmp135c, 4.f));
float32x4_t _out05 = vaddq_f32(_bias0, vaddq_f32(vaddq_f32(_tmp07, _tmp135a), vmlaq_n_f32(_tmp135c, _tmp135b, 32.f)));
vst1q_f32(output0 + 4, _out01);
vst1q_f32(output0 + 12, _out03);
vst1q_f32(output0 + 20, _out05);
// 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 * 4;
}
}
}
}
}
// 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);
}
|
mkldnn_graph.h | // Copyright (C) 2018-2020 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
#pragma once
#include "ie_parallel.hpp"
#include "config.h"
#include "mkldnn_memory.h"
#include "mean_image.h"
#include "mkldnn_node.h"
#include "mkldnn_edge.h"
#include "mkldnn_streams.h"
#include <map>
#include <string>
#include <vector>
#include <memory>
namespace MKLDNNPlugin {
class MKLDNNGraph {
public:
typedef std::shared_ptr<MKLDNNGraph> Ptr;
int socket;
enum Status {
NotReady = 0,
Ready = 1,
};
MKLDNNGraph(): status(NotReady), eng(mkldnn::engine(mkldnn::engine::kind::cpu, 0)), socket(0) {}
Status GetStatus() {
return status;
}
bool IsReady() {
return (GetStatus() == Ready);
}
void setConfig(const Config &cfg);
void setProperty(const std::map<std::string, std::string> &properties);
Config getProperty();
void getInputBlobs(InferenceEngine::BlobMap &in_map);
void getOutputBlobs(InferenceEngine::BlobMap &out_map);
template<typename NET>
void CreateGraph(const NET &network,
const MKLDNNExtensionManager::Ptr& extMgr,
int socket = 0);
bool hasMeanImageFor(const std::string& name) {
return _meanImages.find(name) != _meanImages.end();
}
void PushInputData(const std::string& name, const InferenceEngine::Blob::Ptr &in);
void PullOutputData(InferenceEngine::BlobMap &out);
void Infer(int batch = -1);
std::vector<MKLDNNNodePtr>& GetNodes() {
return graphNodes;
}
std::vector<MKLDNNEdgePtr>& GetEdges() {
return graphEdges;
}
std::vector<MKLDNNNodePtr>& GetOutputNodes() {
return outputNodes;
}
mkldnn::engine getEngine() const {
return eng;
}
void GetPerfData(std::map<std::string, InferenceEngine::InferenceEngineProfileInfo> &perfMap) const;
void RemoveDroppedNodes();
void RemoveDroppedEdges();
void DropNode(const MKLDNNNodePtr& node);
void DropDWConvNode(const MKLDNNNodePtr& node);
void CreateArenaWithObserverAndLoadGraph(int threads_per_stream, int numa_node, int stream_id,
Config::InferenceThreadsBinding pinning,
std::shared_ptr<ICNNNetwork> clonedNetwork, const MKLDNNExtensionManager::Ptr& extensionManager) {
auto load = [clonedNetwork, extensionManager, numa_node, this](){
CreateGraph(static_cast<const ICNNNetwork&>(*clonedNetwork), extensionManager, numa_node);
};
#if(IE_THREAD == IE_THREAD_TBB || IE_THREAD == IE_THREAD_TBB_AUTO)
if (Config::InferenceThreadsBinding::NUMA == pinning) {
ptrArena = std::unique_ptr<tbb::task_arena>(
new tbb::task_arena(tbb::task_arena::constraints(numa_node, threads_per_stream)));
// the (pre-pinned) arena will load the graph (so that blobs memory is first touched by the right threads)
} else {
// regular arena
ptrArena = std::unique_ptr<tbb::task_arena>(new tbb::task_arena(threads_per_stream));
if (Config::InferenceThreadsBinding::CORES == pinning) {
// custom observer (that pins threads to cores)
CreateObserver(stream_id, threads_per_stream);
}
}
ptrArena->execute([&load](){
load();
});
#else
#if IE_THREAD == IE_THREAD_OMP
omp_set_num_threads(threads_per_stream);
#endif
// check that no (affinity-related) OMP envs are set, so user doesn't do a custom pinning
if (!check_env_variables() && (Config::InferenceThreadsBinding::NONE != pinning))
CreateObserver(stream_id, threads_per_stream);
load();
#endif
}
InferenceEngine::ICNNNetwork::Ptr dump() const;
template<typename NET>
static void ApplyUnrollPasses(NET &net);
void ResetInferCount() { infer_count = 0; }
void SortTopologically();
protected:
void CreateObserver(int _stream_id, int _threads_per_stream, int _pinning_step = 1) {
// Notice that custom pinning/observer work (via sched_setaffinity) ONLY on Linux,
// in all other cases the below code is actually just a stub
#if (IE_THREAD == IE_THREAD_TBB || IE_THREAD == IE_THREAD_TBB_AUTO)
ptrObserver
= std::unique_ptr<tbb::task_scheduler_observer>(
new pinning_observer(*ptrArena, _stream_id, _threads_per_stream, _pinning_step));
#else
cpu_set_t *process_mask = nullptr;
int ncpus = 0;
get_process_mask(ncpus, process_mask);
#if IE_THREAD == IE_THREAD_OMP
#pragma omp parallel for
for (int thread_index = 0; thread_index < _threads_per_stream; thread_index++) {
pin_thread_to_vacant_core(_stream_id * _threads_per_stream + thread_index, 1, ncpus, process_mask);
}
#elif IE_THREAD == IE_THREAD_SEQ
pin_thread_to_vacant_core(_stream_id * _threads_per_stream, 1, ncpus, process_mask);
#endif
CPU_FREE(process_mask);
#endif
}
void VisitNode(MKLDNNNodePtr node, std::vector<MKLDNNNodePtr>& sortedNodes);
void ForgetGraphData() {
status = NotReady;
eng = mkldnn::engine(mkldnn::engine::kind::cpu, 0);
inputNodes.clear();
outputNodes.clear();
graphNodes.clear();
graphEdges.clear();
_meanImages.clear();
}
Status status;
Config config;
// For dumping purposes. -1 - no counting, all other positive
// values mean increment it within each Infer() call
int infer_count = -1;
bool reuse_io_tensors = true;
MKLDNNMemoryPtr memWorkspace;
std::map<std::string, MKLDNNNodePtr> inputNodes;
std::vector<MKLDNNNodePtr> outputNodes;
std::vector<MKLDNNNodePtr> graphNodes;
std::vector<MKLDNNEdgePtr> graphEdges;
std::map<std::string, MeanImage> _meanImages;
std::string _name;
#if (IE_THREAD == IE_THREAD_TBB || IE_THREAD == IE_THREAD_TBB_AUTO)
std::unique_ptr<tbb::task_arena> ptrArena;
std::unique_ptr<tbb::task_scheduler_observer> ptrObserver;
#endif
mkldnn::engine eng;
void Replicate(const ICNNNetwork &network, const MKLDNNExtensionManager::Ptr& extMgr);
void Replicate(const TensorIterator::Body &subgraph, const MKLDNNExtensionManager::Ptr& extMgr);
void InitGraph();
void InitNodes();
void InitEdges();
void Allocate();
void AllocateWithReuse();
void CreatePrimitives();
void do_before(const std::string &dir, const MKLDNNNodePtr &node);
void do_after(const std::string &dir, const MKLDNNNodePtr &node);
friend class MKLDNNInferRequest;
friend class MKLDNNGraphlessInferRequest;
friend std::shared_ptr<InferenceEngine::ICNNNetwork> dump_graph_as_ie_net(const MKLDNNGraph &graph);
private:
void dumpToDotFile(std::string file) const;
struct ParsedLayer {
MKLDNNNodePtr parent;
InferenceEngine::CNNLayerPtr cnnLayer;
size_t outIdx;
};
};
} // namespace MKLDNNPlugin
|
shear.c | /*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% SSSSS H H EEEEE AAA RRRR %
% SS H H E A A R R %
% SSS HHHHH EEE AAAAA RRRR %
% SS H H E A A R R %
% SSSSS H H EEEEE A A R R %
% %
% %
% MagickCore Methods to Shear or Rotate an Image by an Arbitrary Angle %
% %
% Software Design %
% Cristy %
% July 1992 %
% %
% %
% Copyright 1999-2016 ImageMagick Studio LLC, a non-profit organization %
% dedicated to making software imaging solutions freely available. %
% %
% You may not use this file except in compliance with the License. You may %
% obtain a copy of the License at %
% %
% http://www.imagemagick.org/script/license.php %
% %
% Unless required by applicable law or agreed to in writing, software %
% distributed under the License is distributed on an "AS IS" BASIS, %
% WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. %
% See the License for the specific language governing permissions and %
% limitations under the License. %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% The XShearImage() and YShearImage() methods are based on the paper "A Fast
% Algorithm for General Raster Rotatation" by Alan W. Paeth, Graphics
% Interface '86 (Vancouver). ShearRotateImage() is adapted from a similar
% method based on the Paeth paper written by Michael Halle of the Spatial
% Imaging Group, MIT Media Lab.
%
*/
/*
Include declarations.
*/
#include "magick/studio.h"
#include "magick/artifact.h"
#include "magick/attribute.h"
#include "magick/blob-private.h"
#include "magick/cache-private.h"
#include "magick/channel.h"
#include "magick/color-private.h"
#include "magick/colorspace-private.h"
#include "magick/composite.h"
#include "magick/composite-private.h"
#include "magick/decorate.h"
#include "magick/distort.h"
#include "magick/draw.h"
#include "magick/exception.h"
#include "magick/exception-private.h"
#include "magick/gem.h"
#include "magick/geometry.h"
#include "magick/image.h"
#include "magick/image-private.h"
#include "magick/memory_.h"
#include "magick/list.h"
#include "magick/matrix.h"
#include "magick/monitor.h"
#include "magick/monitor-private.h"
#include "magick/nt-base-private.h"
#include "magick/pixel-private.h"
#include "magick/quantum.h"
#include "magick/resource_.h"
#include "magick/shear.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/token.h"
#include "magick/transform.h"
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
+ C r o p T o F i t I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% CropToFitImage() crops the sheared image as determined by the bounding box
% as defined by width and height and shearing angles.
%
% The format of the CropToFitImage method is:
%
% MagickBooleanType CropToFitImage(Image **image,
% const MagickRealType x_shear,const MagickRealType x_shear,
% const MagickRealType width,const MagickRealType height,
% const MagickBooleanType rotate,ExceptionInfo *exception)
%
% A description of each parameter follows.
%
% o image: the image.
%
% o x_shear, y_shear, width, height: Defines a region of the image to crop.
%
% o exception: return any errors or warnings in this structure.
%
*/
static MagickBooleanType CropToFitImage(Image **image,
const MagickRealType x_shear,const MagickRealType y_shear,
const MagickRealType width,const MagickRealType height,
const MagickBooleanType rotate,ExceptionInfo *exception)
{
Image
*crop_image;
PointInfo
extent[4],
min,
max;
RectangleInfo
geometry,
page;
register ssize_t
i;
/*
Calculate the rotated image size.
*/
extent[0].x=(double) (-width/2.0);
extent[0].y=(double) (-height/2.0);
extent[1].x=(double) width/2.0;
extent[1].y=(double) (-height/2.0);
extent[2].x=(double) (-width/2.0);
extent[2].y=(double) height/2.0;
extent[3].x=(double) width/2.0;
extent[3].y=(double) height/2.0;
for (i=0; i < 4; i++)
{
extent[i].x+=x_shear*extent[i].y;
extent[i].y+=y_shear*extent[i].x;
if (rotate != MagickFalse)
extent[i].x+=x_shear*extent[i].y;
extent[i].x+=(double) (*image)->columns/2.0;
extent[i].y+=(double) (*image)->rows/2.0;
}
min=extent[0];
max=extent[0];
for (i=1; i < 4; i++)
{
if (min.x > extent[i].x)
min.x=extent[i].x;
if (min.y > extent[i].y)
min.y=extent[i].y;
if (max.x < extent[i].x)
max.x=extent[i].x;
if (max.y < extent[i].y)
max.y=extent[i].y;
}
geometry.x=(ssize_t) ceil(min.x-0.5);
geometry.y=(ssize_t) ceil(min.y-0.5);
geometry.width=(size_t) floor(max.x-min.x+0.5);
geometry.height=(size_t) floor(max.y-min.y+0.5);
page=(*image)->page;
(void) ParseAbsoluteGeometry("0x0+0+0",&(*image)->page);
crop_image=CropImage(*image,&geometry,exception);
if (crop_image == (Image *) NULL)
return(MagickFalse);
crop_image->page=page;
*image=DestroyImage(*image);
*image=crop_image;
return(MagickTrue);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% D e s k e w I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% DeskewImage() removes skew from the image. Skew is an artifact that
% occurs in scanned images because of the camera being misaligned,
% imperfections in the scanning or surface, or simply because the paper was
% not placed completely flat when scanned.
%
% The amount of rotation calculated to deskew the image is saved in the
% artifact "deskew:angle".
%
% If the artifact "deskew:auto-crop" is given the image will be automatically
% cropped of the excess background. The value is the border width of all
% pixels around the edge that will be used to determine an average border
% color for the automatic trim.
%
% The format of the DeskewImage method is:
%
% Image *DeskewImage(const Image *image,const double threshold,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o threshold: separate background from foreground.
%
% o exception: return any errors or warnings in this structure.
%
*/
static void RadonProjection(const Image *image,MatrixInfo *source_matrix,
MatrixInfo *destination_matrix,const ssize_t sign,size_t *projection)
{
MatrixInfo
*swap;
register MatrixInfo
*p,
*q;
register ssize_t
x;
size_t
step;
p=source_matrix;
q=destination_matrix;
for (step=1; step < GetMatrixColumns(p); step*=2)
{
for (x=0; x < (ssize_t) GetMatrixColumns(p); x+=2*(ssize_t) step)
{
register ssize_t
i;
ssize_t
y;
unsigned short
element,
neighbor;
for (i=0; i < (ssize_t) step; i++)
{
for (y=0; y < (ssize_t) (GetMatrixRows(p)-i-1); y++)
{
if (GetMatrixElement(p,x+i,y,&element) == MagickFalse)
continue;
if (GetMatrixElement(p,x+i+step,y+i,&neighbor) == MagickFalse)
continue;
neighbor+=element;
if (SetMatrixElement(q,x+2*i,y,&neighbor) == MagickFalse)
continue;
if (GetMatrixElement(p,x+i+step,y+i+1,&neighbor) == MagickFalse)
continue;
neighbor+=element;
if (SetMatrixElement(q,x+2*i+1,y,&neighbor) == MagickFalse)
continue;
}
for ( ; y < (ssize_t) (GetMatrixRows(p)-i); y++)
{
if (GetMatrixElement(p,x+i,y,&element) == MagickFalse)
continue;
if (GetMatrixElement(p,x+i+step,y+i,&neighbor) == MagickFalse)
continue;
neighbor+=element;
if (SetMatrixElement(q,x+2*i,y,&neighbor) == MagickFalse)
continue;
if (SetMatrixElement(q,x+2*i+1,y,&element) == MagickFalse)
continue;
}
for ( ; y < (ssize_t) GetMatrixRows(p); y++)
{
if (GetMatrixElement(p,x+i,y,&element) == MagickFalse)
continue;
if (SetMatrixElement(q,x+2*i,y,&element) == MagickFalse)
continue;
if (SetMatrixElement(q,x+2*i+1,y,&element) == MagickFalse)
continue;
}
}
}
swap=p;
p=q;
q=swap;
}
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) \
magick_threads(image,image,1,1)
#endif
for (x=0; x < (ssize_t) GetMatrixColumns(p); x++)
{
register ssize_t
y;
size_t
sum;
sum=0;
for (y=0; y < (ssize_t) (GetMatrixRows(p)-1); y++)
{
ssize_t
delta;
unsigned short
element,
neighbor;
if (GetMatrixElement(p,x,y,&element) == MagickFalse)
continue;
if (GetMatrixElement(p,x,y+1,&neighbor) == MagickFalse)
continue;
delta=(ssize_t) element-(ssize_t) neighbor;
sum+=delta*delta;
}
projection[GetMatrixColumns(p)+sign*x-1]=sum;
}
}
static MagickBooleanType RadonTransform(const Image *image,
const double threshold,size_t *projection,ExceptionInfo *exception)
{
CacheView
*image_view;
MatrixInfo
*destination_matrix,
*source_matrix;
MagickBooleanType
status;
register ssize_t
i;
size_t
count,
width;
ssize_t
y;
unsigned char
byte;
unsigned short
bits[256];
for (width=1; width < ((image->columns+7)/8); width<<=1) ;
source_matrix=AcquireMatrixInfo(width,image->rows,sizeof(unsigned short),
exception);
destination_matrix=AcquireMatrixInfo(width,image->rows,sizeof(unsigned short),
exception);
if ((source_matrix == (MatrixInfo *) NULL) ||
(destination_matrix == (MatrixInfo *) NULL))
{
if (destination_matrix != (MatrixInfo *) NULL)
destination_matrix=DestroyMatrixInfo(destination_matrix);
if (source_matrix != (MatrixInfo *) NULL)
source_matrix=DestroyMatrixInfo(source_matrix);
return(MagickFalse);
}
if (NullMatrix(source_matrix) == MagickFalse)
{
destination_matrix=DestroyMatrixInfo(destination_matrix);
source_matrix=DestroyMatrixInfo(source_matrix);
return(MagickFalse);
}
for (i=0; i < 256; i++)
{
byte=(unsigned char) i;
for (count=0; byte != 0; byte>>=1)
count+=byte & 0x01;
bits[i]=(unsigned short) count;
}
status=MagickTrue;
image_view=AcquireVirtualCacheView(image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status) \
magick_threads(image,image,1,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
register const PixelPacket
*magick_restrict p;
register ssize_t
i,
x;
size_t
bit,
byte;
unsigned short
value;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
if (p == (const PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
bit=0;
byte=0;
i=(ssize_t) (image->columns+7)/8;
for (x=0; x < (ssize_t) image->columns; x++)
{
byte<<=1;
if (((MagickRealType) GetPixelRed(p) < threshold) ||
((MagickRealType) GetPixelGreen(p) < threshold) ||
((MagickRealType) GetPixelBlue(p) < threshold))
byte|=0x01;
bit++;
if (bit == 8)
{
value=bits[byte];
(void) SetMatrixElement(source_matrix,--i,y,&value);
bit=0;
byte=0;
}
p++;
}
if (bit != 0)
{
byte<<=(8-bit);
value=bits[byte];
(void) SetMatrixElement(source_matrix,--i,y,&value);
}
}
RadonProjection(image,source_matrix,destination_matrix,-1,projection);
(void) NullMatrix(source_matrix);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status) \
magick_threads(image,image,image->rows,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
register const PixelPacket
*magick_restrict p;
register ssize_t
i,
x;
size_t
bit,
byte;
unsigned short
value;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
if (p == (const PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
bit=0;
byte=0;
i=0;
for (x=0; x < (ssize_t) image->columns; x++)
{
byte<<=1;
if (((MagickRealType) GetPixelRed(p) < threshold) ||
((MagickRealType) GetPixelGreen(p) < threshold) ||
((MagickRealType) GetPixelBlue(p) < threshold))
byte|=0x01;
bit++;
if (bit == 8)
{
value=bits[byte];
(void) SetMatrixElement(source_matrix,i++,y,&value);
bit=0;
byte=0;
}
p++;
}
if (bit != 0)
{
byte<<=(8-bit);
value=bits[byte];
(void) SetMatrixElement(source_matrix,i++,y,&value);
}
}
RadonProjection(image,source_matrix,destination_matrix,1,projection);
image_view=DestroyCacheView(image_view);
destination_matrix=DestroyMatrixInfo(destination_matrix);
source_matrix=DestroyMatrixInfo(source_matrix);
return(MagickTrue);
}
static void GetImageBackgroundColor(Image *image,const ssize_t offset,
ExceptionInfo *exception)
{
CacheView
*image_view;
MagickPixelPacket
background;
MagickRealType
count;
ssize_t
y;
/*
Compute average background color.
*/
if (offset <= 0)
return;
GetMagickPixelPacket(image,&background);
count=0.0;
image_view=AcquireVirtualCacheView(image,exception);
for (y=0; y < (ssize_t) image->rows; y++)
{
register const PixelPacket
*magick_restrict p;
register ssize_t
x;
if ((y >= offset) && (y < ((ssize_t) image->rows-offset)))
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
if (p == (const PixelPacket *) NULL)
continue;
for (x=0; x < (ssize_t) image->columns; x++)
{
if ((x >= offset) && (x < ((ssize_t) image->columns-offset)))
continue;
background.red+=QuantumScale*GetPixelRed(p);
background.green+=QuantumScale*GetPixelGreen(p);
background.blue+=QuantumScale*GetPixelBlue(p);
background.opacity+=QuantumScale*GetPixelOpacity(p);
count++;
p++;
}
}
image_view=DestroyCacheView(image_view);
image->background_color.red=ClampToQuantum((MagickRealType) QuantumRange*
background.red/count);
image->background_color.green=ClampToQuantum((MagickRealType) QuantumRange*
background.green/count);
image->background_color.blue=ClampToQuantum((MagickRealType) QuantumRange*
background.blue/count);
image->background_color.opacity=ClampToQuantum((MagickRealType) QuantumRange*
background.opacity/count);
}
MagickExport Image *DeskewImage(const Image *image,const double threshold,
ExceptionInfo *exception)
{
AffineMatrix
affine_matrix;
const char
*artifact;
double
degrees;
Image
*clone_image,
*crop_image,
*deskew_image,
*median_image;
MagickBooleanType
status;
RectangleInfo
geometry;
register ssize_t
i;
size_t
max_projection,
*projection,
width;
ssize_t
skew;
/*
Compute deskew angle.
*/
for (width=1; width < ((image->columns+7)/8); width<<=1) ;
projection=(size_t *) AcquireQuantumMemory((size_t) (2*width-1),
sizeof(*projection));
if (projection == (size_t *) NULL)
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
status=RadonTransform(image,threshold,projection,exception);
if (status == MagickFalse)
{
projection=(size_t *) RelinquishMagickMemory(projection);
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
}
max_projection=0;
skew=0;
for (i=0; i < (ssize_t) (2*width-1); i++)
{
if (projection[i] > max_projection)
{
skew=i-(ssize_t) width+1;
max_projection=projection[i];
}
}
projection=(size_t *) RelinquishMagickMemory(projection);
degrees=RadiansToDegrees(-atan((double) skew/width/8));
if (image->debug != MagickFalse)
(void) LogMagickEvent(TransformEvent,GetMagickModule(),
" Deskew angle: %g",degrees);
/*
Deskew image.
*/
clone_image=CloneImage(image,0,0,MagickTrue,exception);
if (clone_image == (Image *) NULL)
return((Image *) NULL);
{
char
angle[MaxTextExtent];
(void) FormatLocaleString(angle,MaxTextExtent,"%g",degrees);
(void) SetImageArtifact(clone_image,"deskew:angle",angle);
}
(void) SetImageVirtualPixelMethod(clone_image,BackgroundVirtualPixelMethod);
affine_matrix.sx=cos(DegreesToRadians(fmod((double) degrees,360.0)));
affine_matrix.rx=sin(DegreesToRadians(fmod((double) degrees,360.0)));
affine_matrix.ry=(-sin(DegreesToRadians(fmod((double) degrees,360.0))));
affine_matrix.sy=cos(DegreesToRadians(fmod((double) degrees,360.0)));
affine_matrix.tx=0.0;
affine_matrix.ty=0.0;
artifact=GetImageArtifact(image,"deskew:auto-crop");
if (IsMagickTrue(artifact) == MagickFalse)
{
deskew_image=AffineTransformImage(clone_image,&affine_matrix,exception);
clone_image=DestroyImage(clone_image);
return(deskew_image);
}
/*
Auto-crop image.
*/
GetImageBackgroundColor(clone_image,(ssize_t) StringToLong(artifact),
exception);
deskew_image=AffineTransformImage(clone_image,&affine_matrix,exception);
clone_image=DestroyImage(clone_image);
if (deskew_image == (Image *) NULL)
return((Image *) NULL);
median_image=StatisticImage(deskew_image,MedianStatistic,3,3,exception);
if (median_image == (Image *) NULL)
{
deskew_image=DestroyImage(deskew_image);
return((Image *) NULL);
}
geometry=GetImageBoundingBox(median_image,exception);
median_image=DestroyImage(median_image);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TransformEvent,GetMagickModule()," Deskew geometry: "
"%.20gx%.20g%+.20g%+.20g",(double) geometry.width,(double)
geometry.height,(double) geometry.x,(double) geometry.y);
crop_image=CropImage(deskew_image,&geometry,exception);
deskew_image=DestroyImage(deskew_image);
return(crop_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% I n t e g r a l R o t a t e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% IntegralRotateImage() rotates the image an integral of 90 degrees. It
% allocates the memory necessary for the new Image structure and returns a
% pointer to the rotated image.
%
% The format of the IntegralRotateImage method is:
%
% Image *IntegralRotateImage(const Image *image,size_t rotations,
% ExceptionInfo *exception)
%
% A description of each parameter follows.
%
% o image: the image.
%
% o rotations: Specifies the number of 90 degree rotations.
%
*/
MagickExport Image *IntegralRotateImage(const Image *image,size_t rotations,
ExceptionInfo *exception)
{
#define RotateImageTag "Rotate/Image"
CacheView
*image_view,
*rotate_view;
Image
*rotate_image;
MagickBooleanType
status;
MagickOffsetType
progress;
RectangleInfo
page;
ssize_t
y;
/*
Initialize rotated image attributes.
*/
assert(image != (Image *) NULL);
page=image->page;
rotations%=4;
if (rotations == 0)
return(CloneImage(image,0,0,MagickTrue,exception));
if ((rotations == 1) || (rotations == 3))
rotate_image=CloneImage(image,image->rows,image->columns,MagickTrue,
exception);
else
rotate_image=CloneImage(image,image->columns,image->rows,MagickTrue,
exception);
if (rotate_image == (Image *) NULL)
return((Image *) NULL);
/*
Integral rotate the image.
*/
status=MagickTrue;
progress=0;
image_view=AcquireVirtualCacheView(image,exception);
rotate_view=AcquireAuthenticCacheView(rotate_image,exception);
switch (rotations)
{
case 1:
{
size_t
tile_height,
tile_width;
ssize_t
tile_y;
/*
Rotate 90 degrees.
*/
GetPixelCacheTileSize(image,&tile_width,&tile_height);
tile_width=image->columns;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status) \
magick_threads(image,image,1,1)
#endif
for (tile_y=0; tile_y < (ssize_t) image->rows; tile_y+=(ssize_t) tile_height)
{
register ssize_t
tile_x;
if (status == MagickFalse)
continue;
for (tile_x=0; tile_x < (ssize_t) image->columns; tile_x+=(ssize_t) tile_width)
{
MagickBooleanType
sync;
register const IndexPacket
*magick_restrict indexes;
register const PixelPacket
*magick_restrict p;
register IndexPacket
*magick_restrict rotate_indexes;
register PixelPacket
*magick_restrict q;
register ssize_t
y;
size_t
height,
width;
width=tile_width;
if ((tile_x+(ssize_t) tile_width) > (ssize_t) image->columns)
width=(size_t) (tile_width-(tile_x+tile_width-image->columns));
height=tile_height;
if ((tile_y+(ssize_t) tile_height) > (ssize_t) image->rows)
height=(size_t) (tile_height-(tile_y+tile_height-image->rows));
p=GetCacheViewVirtualPixels(image_view,tile_x,tile_y,width,height,
exception);
if (p == (const PixelPacket *) NULL)
{
status=MagickFalse;
break;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
for (y=0; y < (ssize_t) width; y++)
{
register const PixelPacket
*magick_restrict tile_pixels;
register ssize_t
x;
if (status == MagickFalse)
continue;
q=QueueCacheViewAuthenticPixels(rotate_view,(ssize_t)
(rotate_image->columns-(tile_y+height)),y+tile_x,height,1,
exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
tile_pixels=p+(height-1)*width+y;
for (x=0; x < (ssize_t) height; x++)
{
*q++=(*tile_pixels);
tile_pixels-=width;
}
rotate_indexes=GetCacheViewAuthenticIndexQueue(rotate_view);
if ((indexes != (IndexPacket *) NULL) &&
(rotate_indexes != (IndexPacket *) NULL))
{
register const IndexPacket
*magick_restrict tile_indexes;
tile_indexes=indexes+(height-1)*width+y;
for (x=0; x < (ssize_t) height; x++)
{
*rotate_indexes++=(*tile_indexes);
tile_indexes-=width;
}
}
sync=SyncCacheViewAuthenticPixels(rotate_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
}
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_IntegralRotateImage)
#endif
proceed=SetImageProgress(image,RotateImageTag,progress+=tile_height,
image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
(void) SetImageProgress(image,RotateImageTag,(MagickOffsetType)
image->rows-1,image->rows);
Swap(page.width,page.height);
Swap(page.x,page.y);
if (page.width != 0)
page.x=(ssize_t) (page.width-rotate_image->columns-page.x);
break;
}
case 2:
{
/*
Rotate 180 degrees.
*/
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status) \
magick_threads(image,image,1,1)
#endif
for (y=0; y < (ssize_t) image->rows; y++)
{
MagickBooleanType
sync;
register const IndexPacket
*magick_restrict indexes;
register const PixelPacket
*magick_restrict p;
register IndexPacket
*magick_restrict rotate_indexes;
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(rotate_view,0,(ssize_t) (image->rows-y-
1),image->columns,1,exception);
if ((p == (const PixelPacket *) NULL) || (q == (PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
rotate_indexes=GetCacheViewAuthenticIndexQueue(rotate_view);
q+=image->columns;
for (x=0; x < (ssize_t) image->columns; x++)
*--q=(*p++);
if ((indexes != (IndexPacket *) NULL) &&
(rotate_indexes != (IndexPacket *) NULL))
for (x=0; x < (ssize_t) image->columns; x++)
SetPixelIndex(rotate_indexes+image->columns-x-1,
GetPixelIndex(indexes+x));
sync=SyncCacheViewAuthenticPixels(rotate_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_IntegralRotateImage)
#endif
proceed=SetImageProgress(image,RotateImageTag,progress++,
image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
if (page.width != 0)
page.x=(ssize_t) (page.width-rotate_image->columns-page.x);
if (page.height != 0)
page.y=(ssize_t) (page.height-rotate_image->rows-page.y);
break;
}
case 3:
{
size_t
tile_height,
tile_width;
ssize_t
tile_y;
/*
Rotate 270 degrees.
*/
GetPixelCacheTileSize(image,&tile_width,&tile_height);
tile_width=image->columns;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(status) \
magick_threads(image,image,1,1)
#endif
for (tile_y=0; tile_y < (ssize_t) image->rows; tile_y+=(ssize_t) tile_height)
{
register ssize_t
tile_x;
if (status == MagickFalse)
continue;
for (tile_x=0; tile_x < (ssize_t) image->columns; tile_x+=(ssize_t) tile_width)
{
MagickBooleanType
sync;
register const IndexPacket
*magick_restrict indexes;
register const PixelPacket
*magick_restrict p;
register IndexPacket
*magick_restrict rotate_indexes;
register PixelPacket
*magick_restrict q;
register ssize_t
y;
size_t
height,
width;
width=tile_width;
if ((tile_x+(ssize_t) tile_width) > (ssize_t) image->columns)
width=(size_t) (tile_width-(tile_x+tile_width-image->columns));
height=tile_height;
if ((tile_y+(ssize_t) tile_height) > (ssize_t) image->rows)
height=(size_t) (tile_height-(tile_y+tile_height-image->rows));
p=GetCacheViewVirtualPixels(image_view,tile_x,tile_y,width,height,
exception);
if (p == (const PixelPacket *) NULL)
{
status=MagickFalse;
break;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
for (y=0; y < (ssize_t) width; y++)
{
register const PixelPacket
*magick_restrict tile_pixels;
register ssize_t
x;
if (status == MagickFalse)
continue;
q=QueueCacheViewAuthenticPixels(rotate_view,tile_y,(ssize_t) (y+
rotate_image->rows-(tile_x+width)),height,1,exception);
if (q == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
tile_pixels=p+(width-1)-y;
for (x=0; x < (ssize_t) height; x++)
{
*q++=(*tile_pixels);
tile_pixels+=width;
}
rotate_indexes=GetCacheViewAuthenticIndexQueue(rotate_view);
if ((indexes != (IndexPacket *) NULL) &&
(rotate_indexes != (IndexPacket *) NULL))
{
register const IndexPacket
*magick_restrict tile_indexes;
tile_indexes=indexes+(width-1)-y;
for (x=0; x < (ssize_t) height; x++)
{
*rotate_indexes++=(*tile_indexes);
tile_indexes+=width;
}
}
sync=SyncCacheViewAuthenticPixels(rotate_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
}
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_IntegralRotateImage)
#endif
proceed=SetImageProgress(image,RotateImageTag,progress+=tile_height,
image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
(void) SetImageProgress(image,RotateImageTag,(MagickOffsetType)
image->rows-1,image->rows);
Swap(page.width,page.height);
Swap(page.x,page.y);
if (page.height != 0)
page.y=(ssize_t) (page.height-rotate_image->rows-page.y);
break;
}
default:
break;
}
rotate_view=DestroyCacheView(rotate_view);
image_view=DestroyCacheView(image_view);
rotate_image->type=image->type;
rotate_image->page=page;
if (status == MagickFalse)
rotate_image=DestroyImage(rotate_image);
return(rotate_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
+ X S h e a r I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% XShearImage() shears the image in the X direction with a shear angle of
% 'degrees'. Positive angles shear counter-clockwise (right-hand rule), and
% negative angles shear clockwise. Angles are measured relative to a vertical
% Y-axis. X shears will widen an image creating 'empty' triangles on the left
% and right sides of the source image.
%
% The format of the XShearImage method is:
%
% MagickBooleanType XShearImage(Image *image,const MagickRealType degrees,
% const size_t width,const size_t height,
% const ssize_t x_offset,const ssize_t y_offset,ExceptionInfo *exception)
%
% A description of each parameter follows.
%
% o image: the image.
%
% o degrees: A MagickRealType representing the shearing angle along the X
% axis.
%
% o width, height, x_offset, y_offset: Defines a region of the image
% to shear.
%
% o exception: return any errors or warnings in this structure.
%
*/
static MagickBooleanType XShearImage(Image *image,const MagickRealType degrees,
const size_t width,const size_t height,const ssize_t x_offset,
const ssize_t y_offset,ExceptionInfo *exception)
{
#define XShearImageTag "XShear/Image"
typedef enum
{
LEFT,
RIGHT
} ShearDirection;
CacheView
*image_view;
MagickBooleanType
status;
MagickOffsetType
progress;
MagickPixelPacket
background;
ssize_t
y;
assert(image != (Image *) NULL);
assert(image->signature == MagickSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
GetMagickPixelPacket(image,&background);
SetMagickPixelPacket(image,&image->background_color,(IndexPacket *) NULL,
&background);
if (image->colorspace == CMYKColorspace)
ConvertRGBToCMYK(&background);
/*
X shear image.
*/
status=MagickTrue;
progress=0;
image_view=AcquireAuthenticCacheView(image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(progress,status) \
magick_threads(image,image,height,1)
#endif
for (y=0; y < (ssize_t) height; y++)
{
MagickPixelPacket
pixel,
source,
destination;
MagickRealType
area,
displacement;
register IndexPacket
*magick_restrict indexes,
*magick_restrict shear_indexes;
register PixelPacket
*magick_restrict p,
*magick_restrict q;
register ssize_t
i;
ShearDirection
direction;
ssize_t
step;
if (status == MagickFalse)
continue;
p=GetCacheViewAuthenticPixels(image_view,0,y_offset+y,image->columns,1,
exception);
if (p == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewAuthenticIndexQueue(image_view);
p+=x_offset;
indexes+=x_offset;
displacement=degrees*(MagickRealType) (y-height/2.0);
if (displacement == 0.0)
continue;
if (displacement > 0.0)
direction=RIGHT;
else
{
displacement*=(-1.0);
direction=LEFT;
}
step=(ssize_t) floor((double) displacement);
area=(MagickRealType) (displacement-step);
step++;
pixel=background;
GetMagickPixelPacket(image,&source);
GetMagickPixelPacket(image,&destination);
switch (direction)
{
case LEFT:
{
/*
Transfer pixels left-to-right.
*/
if (step > x_offset)
break;
q=p-step;
shear_indexes=indexes-step;
for (i=0; i < (ssize_t) width; i++)
{
if ((x_offset+i) < step)
{
SetMagickPixelPacket(image,++p,++indexes,&pixel);
q++;
shear_indexes++;
continue;
}
SetMagickPixelPacket(image,p,indexes,&source);
MagickPixelCompositeAreaBlend(&pixel,(MagickRealType) pixel.opacity,
&source,(MagickRealType) GetPixelOpacity(p),area,&destination);
SetPixelPacket(image,&destination,q++,shear_indexes++);
SetMagickPixelPacket(image,p++,indexes++,&pixel);
}
MagickPixelCompositeAreaBlend(&pixel,(MagickRealType) pixel.opacity,
&background,(MagickRealType) background.opacity,area,&destination);
SetPixelPacket(image,&destination,q++,shear_indexes++);
for (i=0; i < (step-1); i++)
SetPixelPacket(image,&background,q++,shear_indexes++);
break;
}
case RIGHT:
{
/*
Transfer pixels right-to-left.
*/
p+=width;
indexes+=width;
q=p+step;
shear_indexes=indexes+step;
for (i=0; i < (ssize_t) width; i++)
{
p--;
indexes--;
q--;
shear_indexes--;
if ((size_t) (x_offset+width+step-i) > image->columns)
continue;
SetMagickPixelPacket(image,p,indexes,&source);
MagickPixelCompositeAreaBlend(&pixel,(MagickRealType) pixel.opacity,
&source,(MagickRealType) GetPixelOpacity(p),area,&destination);
SetPixelPacket(image,&destination,q,shear_indexes);
SetMagickPixelPacket(image,p,indexes,&pixel);
}
MagickPixelCompositeAreaBlend(&pixel,(MagickRealType) pixel.opacity,
&background,(MagickRealType) background.opacity,area,&destination);
SetPixelPacket(image,&destination,--q,--shear_indexes);
for (i=0; i < (step-1); i++)
SetPixelPacket(image,&background,--q,--shear_indexes);
break;
}
}
if (SyncCacheViewAuthenticPixels(image_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_XShearImage)
#endif
proceed=SetImageProgress(image,XShearImageTag,progress++,height);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
image_view=DestroyCacheView(image_view);
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
+ Y S h e a r I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% YShearImage shears the image in the Y direction with a shear angle of
% 'degrees'. Positive angles shear counter-clockwise (right-hand rule), and
% negative angles shear clockwise. Angles are measured relative to a
% horizontal X-axis. Y shears will increase the height of an image creating
% 'empty' triangles on the top and bottom of the source image.
%
% The format of the YShearImage method is:
%
% MagickBooleanType YShearImage(Image *image,const MagickRealType degrees,
% const size_t width,const size_t height,
% const ssize_t x_offset,const ssize_t y_offset,ExceptionInfo *exception)
%
% A description of each parameter follows.
%
% o image: the image.
%
% o degrees: A MagickRealType representing the shearing angle along the Y
% axis.
%
% o width, height, x_offset, y_offset: Defines a region of the image
% to shear.
%
% o exception: return any errors or warnings in this structure.
%
*/
static MagickBooleanType YShearImage(Image *image,const MagickRealType degrees,
const size_t width,const size_t height,const ssize_t x_offset,
const ssize_t y_offset,ExceptionInfo *exception)
{
#define YShearImageTag "YShear/Image"
typedef enum
{
UP,
DOWN
} ShearDirection;
CacheView
*image_view;
MagickBooleanType
status;
MagickOffsetType
progress;
MagickPixelPacket
background;
ssize_t
x;
assert(image != (Image *) NULL);
assert(image->signature == MagickSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
GetMagickPixelPacket(image,&background);
SetMagickPixelPacket(image,&image->background_color,(IndexPacket *) NULL,
&background);
if (image->colorspace == CMYKColorspace)
ConvertRGBToCMYK(&background);
/*
Y Shear image.
*/
status=MagickTrue;
progress=0;
image_view=AcquireAuthenticCacheView(image,exception);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(static,4) shared(progress,status) \
magick_threads(image,image,width,1)
#endif
for (x=0; x < (ssize_t) width; x++)
{
ssize_t
step;
MagickPixelPacket
pixel,
source,
destination;
MagickRealType
area,
displacement;
register IndexPacket
*magick_restrict indexes,
*magick_restrict shear_indexes;
register ssize_t
i;
register PixelPacket
*magick_restrict p,
*magick_restrict q;
ShearDirection
direction;
if (status == MagickFalse)
continue;
p=GetCacheViewAuthenticPixels(image_view,x_offset+x,0,1,image->rows,
exception);
if (p == (PixelPacket *) NULL)
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewAuthenticIndexQueue(image_view);
p+=y_offset;
indexes+=y_offset;
displacement=degrees*(MagickRealType) (x-width/2.0);
if (displacement == 0.0)
continue;
if (displacement > 0.0)
direction=DOWN;
else
{
displacement*=(-1.0);
direction=UP;
}
step=(ssize_t) floor((double) displacement);
area=(MagickRealType) (displacement-step);
step++;
pixel=background;
GetMagickPixelPacket(image,&source);
GetMagickPixelPacket(image,&destination);
switch (direction)
{
case UP:
{
/*
Transfer pixels top-to-bottom.
*/
if (step > y_offset)
break;
q=p-step;
shear_indexes=indexes-step;
for (i=0; i < (ssize_t) height; i++)
{
if ((y_offset+i) < step)
{
SetMagickPixelPacket(image,++p,++indexes,&pixel);
q++;
shear_indexes++;
continue;
}
SetMagickPixelPacket(image,p,indexes,&source);
MagickPixelCompositeAreaBlend(&pixel,(MagickRealType) pixel.opacity,
&source,(MagickRealType) GetPixelOpacity(p),area,&destination);
SetPixelPacket(image,&destination,q++,shear_indexes++);
SetMagickPixelPacket(image,p++,indexes++,&pixel);
}
MagickPixelCompositeAreaBlend(&pixel,(MagickRealType) pixel.opacity,
&background,(MagickRealType) background.opacity,area,&destination);
SetPixelPacket(image,&destination,q++,shear_indexes++);
for (i=0; i < (step-1); i++)
SetPixelPacket(image,&background,q++,shear_indexes++);
break;
}
case DOWN:
{
/*
Transfer pixels bottom-to-top.
*/
p+=height;
indexes+=height;
q=p+step;
shear_indexes=indexes+step;
for (i=0; i < (ssize_t) height; i++)
{
p--;
indexes--;
q--;
shear_indexes--;
if ((size_t) (y_offset+height+step-i) > image->rows)
continue;
SetMagickPixelPacket(image,p,indexes,&source);
MagickPixelCompositeAreaBlend(&pixel,(MagickRealType) pixel.opacity,
&source,(MagickRealType) GetPixelOpacity(p),area,&destination);
SetPixelPacket(image,&destination,q,shear_indexes);
SetMagickPixelPacket(image,p,indexes,&pixel);
}
MagickPixelCompositeAreaBlend(&pixel,(MagickRealType) pixel.opacity,
&background,(MagickRealType) background.opacity,area,&destination);
SetPixelPacket(image,&destination,--q,--shear_indexes);
for (i=0; i < (step-1); i++)
SetPixelPacket(image,&background,--q,--shear_indexes);
break;
}
}
if (SyncCacheViewAuthenticPixels(image_view,exception) == MagickFalse)
status=MagickFalse;
if (image->progress_monitor != (MagickProgressMonitor) NULL)
{
MagickBooleanType
proceed;
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical (MagickCore_YShearImage)
#endif
proceed=SetImageProgress(image,YShearImageTag,progress++,image->rows);
if (proceed == MagickFalse)
status=MagickFalse;
}
}
image_view=DestroyCacheView(image_view);
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S h e a r I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ShearImage() creates a new image that is a shear_image copy of an existing
% one. Shearing slides one edge of an image along the X or Y axis, creating
% a parallelogram. An X direction shear slides an edge along the X axis,
% while a Y direction shear slides an edge along the Y axis. The amount of
% the shear is controlled by a shear angle. For X direction shears, x_shear
% is measured relative to the Y axis, and similarly, for Y direction shears
% y_shear is measured relative to the X axis. Empty triangles left over from
% shearing the image are filled with the background color defined by member
% 'background_color' of the image.. ShearImage() allocates the memory
% necessary for the new Image structure and returns a pointer to the new image.
%
% ShearImage() is based on the paper "A Fast Algorithm for General Raster
% Rotatation" by Alan W. Paeth.
%
% The format of the ShearImage method is:
%
% Image *ShearImage(const Image *image,const double x_shear,
% const double y_shear,ExceptionInfo *exception)
%
% A description of each parameter follows.
%
% o image: the image.
%
% o x_shear, y_shear: Specifies the number of degrees to shear the image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *ShearImage(const Image *image,const double x_shear,
const double y_shear,ExceptionInfo *exception)
{
Image
*integral_image,
*shear_image;
MagickBooleanType
status;
PointInfo
shear;
RectangleInfo
border_info,
bounds;
assert(image != (Image *) NULL);
assert(image->signature == MagickSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickSignature);
if ((x_shear != 0.0) && (fmod(x_shear,90.0) == 0.0))
ThrowImageException(ImageError,"AngleIsDiscontinuous");
if ((y_shear != 0.0) && (fmod(y_shear,90.0) == 0.0))
ThrowImageException(ImageError,"AngleIsDiscontinuous");
/*
Initialize shear angle.
*/
integral_image=CloneImage(image,0,0,MagickTrue,exception);
if (integral_image == (Image *) NULL)
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
shear.x=(-tan(DegreesToRadians(fmod(x_shear,360.0))));
shear.y=tan(DegreesToRadians(fmod(y_shear,360.0)));
if ((shear.x == 0.0) && (shear.y == 0.0))
return(integral_image);
if (SetImageStorageClass(integral_image,DirectClass) == MagickFalse)
{
InheritException(exception,&integral_image->exception);
integral_image=DestroyImage(integral_image);
return(integral_image);
}
if (integral_image->matte == MagickFalse)
(void) SetImageAlphaChannel(integral_image,OpaqueAlphaChannel);
/*
Compute image size.
*/
bounds.width=image->columns+(ssize_t) floor(fabs(shear.x)*image->rows+0.5);
bounds.x=(ssize_t) ceil((double) image->columns+((fabs(shear.x)*image->rows)-
image->columns)/2.0-0.5);
bounds.y=(ssize_t) ceil((double) image->rows+((fabs(shear.y)*bounds.width)-
image->rows)/2.0-0.5);
/*
Surround image with border.
*/
integral_image->border_color=integral_image->background_color;
integral_image->compose=CopyCompositeOp;
border_info.width=(size_t) bounds.x;
border_info.height=(size_t) bounds.y;
shear_image=BorderImage(integral_image,&border_info,exception);
integral_image=DestroyImage(integral_image);
if (shear_image == (Image *) NULL)
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
/*
Shear the image.
*/
if (shear_image->matte == MagickFalse)
(void) SetImageAlphaChannel(shear_image,OpaqueAlphaChannel);
status=XShearImage(shear_image,shear.x,image->columns,image->rows,bounds.x,
(ssize_t) (shear_image->rows-image->rows)/2,exception);
if (status == MagickFalse)
{
shear_image=DestroyImage(shear_image);
return((Image *) NULL);
}
status=YShearImage(shear_image,shear.y,bounds.width,image->rows,(ssize_t)
(shear_image->columns-bounds.width)/2,bounds.y,exception);
if (status == MagickFalse)
{
shear_image=DestroyImage(shear_image);
return((Image *) NULL);
}
status=CropToFitImage(&shear_image,shear.x,shear.y,(MagickRealType)
image->columns,(MagickRealType) image->rows,MagickFalse,exception);
shear_image->matte=image->matte;
shear_image->compose=image->compose;
shear_image->page.width=0;
shear_image->page.height=0;
if (status == MagickFalse)
shear_image=DestroyImage(shear_image);
return(shear_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% S h e a r R o t a t e I m a g e %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% ShearRotateImage() creates a new image that is a rotated copy of an existing
% one. Positive angles rotate counter-clockwise (right-hand rule), while
% negative angles rotate clockwise. Rotated images are usually larger than
% the originals and have 'empty' triangular corners. X axis. Empty
% triangles left over from shearing the image are filled with the background
% color defined by member 'background_color' of the image. ShearRotateImage
% allocates the memory necessary for the new Image structure and returns a
% pointer to the new image.
%
% ShearRotateImage() is based on the paper "A Fast Algorithm for General
% Raster Rotatation" by Alan W. Paeth. ShearRotateImage is adapted from a
% similar method based on the Paeth paper written by Michael Halle of the
% Spatial Imaging Group, MIT Media Lab.
%
% The format of the ShearRotateImage method is:
%
% Image *ShearRotateImage(const Image *image,const double degrees,
% ExceptionInfo *exception)
%
% A description of each parameter follows.
%
% o image: the image.
%
% o degrees: Specifies the number of degrees to rotate the image.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *ShearRotateImage(const Image *image,const double degrees,
ExceptionInfo *exception)
{
Image
*integral_image,
*rotate_image;
MagickBooleanType
status;
MagickRealType
angle;
PointInfo
shear;
RectangleInfo
border_info,
bounds;
size_t
height,
rotations,
shear_width,
width;
/*
Adjust rotation angle.
*/
assert(image != (Image *) NULL);
assert(image->signature == MagickSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(exception != (ExceptionInfo *) NULL);
assert(exception->signature == MagickSignature);
angle=degrees;
while (angle < -45.0)
angle+=360.0;
for (rotations=0; angle > 45.0; rotations++)
angle-=90.0;
rotations%=4;
/*
Calculate shear equations.
*/
integral_image=IntegralRotateImage(image,rotations,exception);
if (integral_image == (Image *) NULL)
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
shear.x=(-tan((double) DegreesToRadians(angle)/2.0));
shear.y=sin((double) DegreesToRadians(angle));
if ((shear.x == 0.0) && (shear.y == 0.0))
return(integral_image);
if (SetImageStorageClass(integral_image,DirectClass) == MagickFalse)
{
InheritException(exception,&integral_image->exception);
integral_image=DestroyImage(integral_image);
return(integral_image);
}
if (integral_image->matte == MagickFalse)
(void) SetImageAlphaChannel(integral_image,OpaqueAlphaChannel);
/*
Compute maximum bounds for 3 shear operations.
*/
width=integral_image->columns;
height=integral_image->rows;
bounds.width=(size_t) floor(fabs((double) height*shear.x)+width+0.5);
bounds.height=(size_t) floor(fabs((double) bounds.width*shear.y)+height+0.5);
shear_width=(size_t) floor(fabs((double) bounds.height*shear.x)+
bounds.width+0.5);
bounds.x=(ssize_t) floor((double) ((shear_width > bounds.width) ? width :
bounds.width-shear_width+2)/2.0+0.5);
bounds.y=(ssize_t) floor(((double) bounds.height-height+2)/2.0+0.5);
/*
Surround image with a border.
*/
integral_image->border_color=integral_image->background_color;
integral_image->compose=CopyCompositeOp;
border_info.width=(size_t) bounds.x;
border_info.height=(size_t) bounds.y;
rotate_image=BorderImage(integral_image,&border_info,exception);
integral_image=DestroyImage(integral_image);
if (rotate_image == (Image *) NULL)
ThrowImageException(ResourceLimitError,"MemoryAllocationFailed");
/*
Rotate the image.
*/
status=XShearImage(rotate_image,shear.x,width,height,bounds.x,(ssize_t)
(rotate_image->rows-height)/2,exception);
if (status == MagickFalse)
{
rotate_image=DestroyImage(rotate_image);
return((Image *) NULL);
}
status=YShearImage(rotate_image,shear.y,bounds.width,height,(ssize_t)
(rotate_image->columns-bounds.width)/2,bounds.y,exception);
if (status == MagickFalse)
{
rotate_image=DestroyImage(rotate_image);
return((Image *) NULL);
}
status=XShearImage(rotate_image,shear.x,bounds.width,bounds.height,(ssize_t)
(rotate_image->columns-bounds.width)/2,(ssize_t) (rotate_image->rows-
bounds.height)/2,exception);
if (status == MagickFalse)
{
rotate_image=DestroyImage(rotate_image);
return((Image *) NULL);
}
status=CropToFitImage(&rotate_image,shear.x,shear.y,(MagickRealType) width,
(MagickRealType) height,MagickTrue,exception);
rotate_image->matte=image->matte;
rotate_image->compose=image->compose;
rotate_image->page.width=0;
rotate_image->page.height=0;
if (status == MagickFalse)
rotate_image=DestroyImage(rotate_image);
return(rotate_image);
}
|
GB_unop__expm1_fc64_fc64.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary 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_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__expm1_fc64_fc64)
// op(A') function: GB (_unop_tran__expm1_fc64_fc64)
// C type: GxB_FC64_t
// A type: GxB_FC64_t
// cast: GxB_FC64_t cij = aij
// unaryop: cij = GB_cexpm1 (aij)
#define GB_ATYPE \
GxB_FC64_t
#define GB_CTYPE \
GxB_FC64_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 = GB_cexpm1 (x) ;
// casting
#define GB_CAST(z, aij) \
GxB_FC64_t z = aij ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GxB_FC64_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
GxB_FC64_t z = aij ; \
Cx [pC] = GB_cexpm1 (z) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_EXPM1 || GxB_NO_FC64)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_apply__expm1_fc64_fc64)
(
GxB_FC64_t *Cx, // Cx and Ax may be aliased
const GxB_FC64_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++)
{
GxB_FC64_t aij = Ax [p] ;
GxB_FC64_t z = aij ;
Cx [p] = GB_cexpm1 (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 ;
GxB_FC64_t aij = Ax [p] ;
GxB_FC64_t z = aij ;
Cx [p] = GB_cexpm1 (z) ;
}
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_tran__expm1_fc64_fc64)
(
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
|
omp_cherk_batch.c | /**
* @file omp_cherk_batch.c
*
* @brief BBLAS cherk_batch float _Complex routine.
*
* BBLAS is a software package provided by Univ. of Manchester,
* Univ. of Tennessee.
*
* @version 1.0.0
* @author Samuel D. Relton
* @author Pedro V. Lara
* @author Mawussi Zounon
* @date 2016-02-20
*
**/
#ifndef DOXYGEN_SHOULD_SKIP_THIS
/**
* Code generation
* @generated from ./bblas_omp/omp_zherk_batch.c normal z -> c, Mon Jun 6 09:44:14 2016
**/
#endif
#include<cblas.h>
#include "bblas_omp.h"
#include "bblas.h"
#include <omp.h>
#define COMPLEX
/**
Purpose
-------
<b>cherk_batch</b> is an OpenMP version of cherk_batch.
It performs the matrix-matrix operations
arrayC[i] = alpha[i]*arrayA[i]*arrayA[i**H] + beta[i]*arrayC[i], or
arrayC[i] = alpha[i]*arrayA[i]**H *arrayA[i] + beta[i]*arrayC[i],
where alpha[i] and beta[i] are real scalars, arrayC[i] are matrices with
an N[i] by N[i] hermitian matrix and arrayA[i] are N[i] by K[i] mtrices in the first
case and a K[i] by N[i] in the second case.
Fixed and Variable Batch Operations
-----------------------------------
Two types of batch operation are supported depending upon the value of batch_opts.
When <tt>batch_opts = BBLAS_VARIABLE</tt>
- all parameters that are arrays must have length at least batch_count.
- all parameters that are arrays must have all values set.
When <tt>batch_opts = BBLAS_FIXED</tt>
- all parameters that are arrays (except for arrayA, arrayC, and info)
must have length at least one.
- all parameters that are arrays (except for arrayA, arrayC, and info)
need only to have their first value set.
This means that for a <tt>BBLAS_FIXED</tt> batch,
the values of uplo[0], trans[0], N[0], K[0],
alpha[0], beta[0], lda[0], and ldc[0] are used for all computations.
Parameters
----------
@param[in]
uplo Array of <tt>enum BBLAS_UPLO</tt>.
On entry, uplo[i] specifies whether the upper or
lower triangular part of the matrix arrayC[i]
is to be referenced as follows:
- = 'BblasUpper' Only the upper triangular part of
arrayC[i] is to be referenced.
- = 'BblasLower' Only the lower triangular part of
arrayC[i] is to be referenced.
@param[in]
trans Array of <tt>enum BBLAS_TRANS</tt>.
On entry, trans[i] specifies the operation to be
performed as follows:
- = 'BblasNoTrans' arrayC[i] = alpha[i]*arrayA[i]*arrayA[i]**H + beta[i]*arrayC[i].
- = 'BblasConjTrans' arrayC[i] = alpha[i]*arrayA[i]**H *arrayA[i] + beta[i]*arrayC[i].
@param[in]
N Array of <tt>int</tt>.
Each element N[i] specifies the number of rows and columns of the matrix
arrayC[i]. N[i] must be greater than zero.
@param[in]
K Array of <tt>int</tt>.
On entry with trans[i] = 'BblasNoTrans', K[i] specifies the
number of columns of the matrix arrayA[i],
and upon entry with trans[i] = 'BblasConjTrans',
K[i] specifies the number of rows of the matrix arrayA[i].
K[i] must be greater than zero.
@param[in]
alpha Array of <tt>complex_16</tt>.
@param[in]
arrayA Array of pointers.
Each element arrayA[i] is a pointer to a COMPLEX matrix of
dimension lda[i] by Ka[i],
where Ka[i] = K[i] when transA[i] = BblasNoTrans and is N[i] otherwise.
Before entry with transA[i] = BblasNoTrans, the leading N[i] by K[i]
part of the arrayA[i] must contain the elements of arrayA[i], otherwise
the leading K[i] by N[i] part of the arrayA[i] must contain the
elements of arrayA[i].
@param[in]
lda Array of <tt>int</tt>.
On entry, lda[i] specifies the first dimension of arrayA[i] as declared
in the calling (sub) program. When transA[i] = BblasNoTrans then
lda[i] must be at least max( 1, N[i] ), otherwise lda[i] must be at
least max( 1, K[i] ).
@param[in]
beta Array of <tt>complex_16</tt>.
When beta[i] is set to zero arrayC[i] need not be set on input.
@param[in,out]
arrayC Array of pointers.
Each elements arrayC[i] is a pointer to a COMPLEX matrix of
dimension ldc[i] by N[i].
Before entry with uplo[i] = 'BblasUpper', the leading
N[i] by N[i] upper triangular part of the arrayC[i] must con-
tain the upper triangular part of the hermitian
matrix and the strictly lower triangular part of arrayC[i]
is not referenced. On exit, the upper triangular
part of the arrayC[i] is overwritten by the upper tri-
angular part of the updated matrix.
Before entry with uplo[i] = 'BblasLower', the leading N[i] by N[i] lower
triangular part of the arrayC[i] must contain the lower
triangular part of the hermitian matrix and the
strictly upper triangular part of arrayC[i] is not refer-
enced. On exit, the lower triangular part of the
arrayC[i] is overwritten by the lower triangular part
of the updated matrix.
Note that the imaginary parts of the diagonal elements need not be set,
they are assumed to be zero,
and on exit they are set to zero.
@param[in]
ldc Array of <tt>int</tt>.
On entry, ldc[i] specifies the first dimension of arrayC[i] as declared
in the calling (sub) program. Each element ldc must be at least max( 1, N[i] ).
@param[in]
batch_count <tt>int</tt>
The number of matrices to operate on.
@param[in]
batch_opts <tt>enum BBLAS_OPTS</tt>
One of BBLAS_FIXED or BBLAS_VARIABLE depending upon the type of
batch operation required.
@param[out]
info Array of <tt>int</tt>.
Each element info[i] is the error return code of the ith cherk in the batch,
these need not be set on entry.
The error codes can be found in bblas_macros.h.
**/
void omp_cherk_batch(
const enum BBLAS_UPLO *uplo, const enum BBLAS_TRANS *trans,
const int *N, const int *K, const float *alpha,
const BBLAS_Complex32_t **arrayA, const int *lda,
const float *beta, BBLAS_Complex32_t **arrayC,
const int *ldc, const int batch_count, enum BBLAS_OPTS batch_opts, int *info)
{
/*Local variables */
int first_index = 0;
int batch_iter;
int LDA;
char func_name[15] = "cherk_batch";
/* Check input arguments */
if (batch_count < 0)
{
xerbla_batch(func_name, BBLAS_ERR_BATCH_COUNT, -1);
}
if (batch_opts == BBLAS_FIXED)
{
if ((uplo[first_index] != BblasUpper) &&
(uplo[first_index] != BblasLower))
{
xerbla_batch(func_name, BBLAS_ERR_UPLO, first_index);
for (batch_iter = 0; batch_iter < batch_count; batch_iter++)
{
info[batch_iter] = BBLAS_ERR_UPLO;
}
return;
}
if ((trans[first_index] != BblasNoTrans) &&
(trans[first_index] != BblasTrans) &&
(trans[first_index] != BblasConjTrans))
{
xerbla_batch(func_name, BBLAS_ERR_TRANS, first_index);
for (batch_iter = 0; batch_iter < batch_count; batch_iter++)
{
info[batch_iter] = BBLAS_ERR_TRANS;
}
return;
}
if (N[first_index] < 0)
{
xerbla_batch(func_name, BBLAS_ERR_N, first_index);
for (batch_iter = 0; batch_iter < batch_count; batch_iter++)
{
info[batch_iter] = BBLAS_ERR_N;
}
return;
}
if (K[first_index] < 0)
{
xerbla_batch(func_name, BBLAS_ERR_K, first_index);
for (batch_iter = 0; batch_iter < batch_count; batch_iter++)
{
info[batch_iter] = BBLAS_ERR_K;
}
return;
}
if (trans[first_index] == BblasNoTrans)
{
LDA = N[first_index];
} else
{
LDA = K[first_index];
}
if (lda[first_index] < max(1, LDA)){
xerbla_batch(func_name, BBLAS_ERR_LDA, first_index);
for (batch_iter = 0; batch_iter < batch_count; batch_iter++)
{
info[first_index] = BBLAS_ERR_LDA;
}
return;
}
if (ldc[first_index] < max(1, N[first_index]))
{
xerbla_batch(func_name, BBLAS_ERR_LDC, first_index);
for (batch_iter = 0; batch_iter < batch_count; batch_iter++)
{
info[batch_iter] = BBLAS_ERR_LDC;
}
return;
}
/* particular case */
if (N[first_index] == 0 ||
((K[first_index] == 0 || alpha[first_index] == (float)0.0) &&
(beta[first_index] == (float)1.0)))
{
for (batch_iter = 0; batch_iter < batch_count; batch_iter++)
{
info[batch_iter] = BBLAS_SUCCESS;
}
return;
}
#pragma omp parallel for private(batch_iter)
for (batch_iter = 0; batch_iter < batch_count; batch_iter++)
{
/*Call to cblas_cherk */
cblas_cherk(
BblasColMajor,
uplo[first_index],
trans[first_index],
N[first_index],
K[first_index],
alpha[first_index],
arrayA[batch_iter],
lda[first_index],
beta[first_index],
arrayC[batch_iter],
ldc[first_index]);
/* Successful */
info[batch_iter] = BBLAS_SUCCESS;
} /*END FIXED SIZE FOR LOOP */
}else if (batch_opts == BBLAS_VARIABLE)
{
#pragma omp parallel for private(batch_iter, LDA)
for (batch_iter = 0; batch_iter < batch_count; batch_iter++)
{
/* Check input arguments */
if ((uplo[batch_iter] != BblasUpper) &&
(uplo[batch_iter] != BblasLower))
{
xerbla_batch(func_name, BBLAS_ERR_UPLO, batch_iter);
info[batch_iter] = BBLAS_ERR_UPLO;
continue;
}
if ((trans[batch_iter] != BblasNoTrans) &&
(trans[batch_iter] != BblasTrans) &&
(trans[batch_iter] != BblasConjTrans))
{
xerbla_batch(func_name, BBLAS_ERR_TRANS, batch_iter);
info[batch_iter] = BBLAS_ERR_TRANS;
continue;
}
if (N[batch_iter] < 0)
{
xerbla_batch(func_name, BBLAS_ERR_N, batch_iter);
info[batch_iter] = BBLAS_ERR_N;
continue;
}
if (K[batch_iter] < 0)
{
xerbla_batch(func_name, BBLAS_ERR_K, batch_iter);
info[batch_iter] = BBLAS_ERR_K;
continue;
}
if (trans[batch_iter] == BblasNoTrans){
LDA = N[batch_iter];
}
else
{
LDA = K[batch_iter];
}
if (lda[batch_iter] < max(1, LDA)){
xerbla_batch(func_name, BBLAS_ERR_LDA, batch_iter);
info[batch_iter] = BBLAS_ERR_LDA;
continue;
}
if (ldc[batch_iter] < max(1, N[batch_iter]))
{
xerbla_batch(func_name, BBLAS_ERR_LDC, batch_iter);
info[batch_iter] = BBLAS_ERR_LDC;
continue;
}
/* particular case */
if (N[batch_iter] == 0 ||
((K[batch_iter] == 0 || alpha[batch_iter] == (float)0.0) &&
(beta[batch_iter] == (float)1.0)))
{
info[batch_iter] = BBLAS_SUCCESS;
continue;
}
cblas_cherk(
BblasColMajor,
uplo[batch_iter],
trans[batch_iter],
N[batch_iter],
K[batch_iter],
alpha[batch_iter],
arrayA[batch_iter],
lda[batch_iter],
beta[batch_iter],
arrayC[batch_iter],
ldc[batch_iter]);
/* Successful */
info[batch_iter] = BBLAS_SUCCESS;
}
}else
{
xerbla_batch(func_name, BBLAS_ERR_BATCH_OPTS, -1);
}
}
#undef COMPLEX
|
GB_unop__abs_uint32_uint32.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary 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_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__abs_uint32_uint32)
// op(A') function: GB (_unop_tran__abs_uint32_uint32)
// C type: uint32_t
// A type: uint32_t
// cast: uint32_t cij = aij
// unaryop: cij = aij
#define GB_ATYPE \
uint32_t
#define GB_CTYPE \
uint32_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
uint32_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = x ;
// casting
#define GB_CAST(z, aij) \
uint32_t z = aij ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
uint32_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
uint32_t z = aij ; \
Cx [pC] = z ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_ABS || GxB_NO_UINT32)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_apply__abs_uint32_uint32)
(
uint32_t *Cx, // Cx and Ax may be aliased
const uint32_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++)
{
uint32_t aij = Ax [p] ;
uint32_t z = aij ;
Cx [p] = z ;
}
}
else
{
// bitmap case, no transpose; A->b already memcpy'd into C->b
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!Ab [p]) continue ;
uint32_t aij = Ax [p] ;
uint32_t z = aij ;
Cx [p] = z ;
}
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_tran__abs_uint32_uint32)
(
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
|
convolution_sgemm_pack8to4_int8.h | // Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2021 THL A29 Limited, a Tencent company. All rights reserved.
//
// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
// in compliance with the License. You may obtain a copy of the License at
//
// https://opensource.org/licenses/BSD-3-Clause
//
// Unless required by applicable law or agreed to in writing, software distributed
// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
// CONDITIONS OF ANY KIND, either express or implied. See the License for the
// specific language governing permissions and limitations under the License.
static void im2col_sgemm_pack8to4_int8_sse(const Mat& bottom_im2col, Mat& top_blob, const Mat& kernel, const Option& opt)
{
#if NCNN_AVX512VNNI && __AVX512F__ && !__AVX512VNNI__
if (ncnn::cpu_support_x86_avx512_vnni())
{
extern void im2col_sgemm_pack8to4_int8_sse_avx512vnni(const Mat& bottom_im2col, Mat& top_blob, const Mat& kernel, const Option& opt);
im2col_sgemm_pack8to4_int8_sse_avx512vnni(bottom_im2col, top_blob, kernel, opt);
return;
}
#endif
#if NCNN_AVXVNNI && __AVX2__ && !__AVXVNNI__
if (ncnn::cpu_support_x86_avx_vnni())
{
extern void im2col_sgemm_pack8to4_int8_sse_avxvnni(const Mat& bottom_im2col, Mat& top_blob, const Mat& kernel, const Option& opt);
im2col_sgemm_pack8to4_int8_sse_avxvnni(bottom_im2col, top_blob, kernel, opt);
return;
}
#endif
// Mat bottom_im2col(size, maxk, inch, 8u, 8, opt.workspace_allocator);
const int size = bottom_im2col.w;
const int maxk = bottom_im2col.h;
const int inch = bottom_im2col.c;
const int outch = top_blob.c;
// permute
Mat tmp;
#if __AVX2__
if (size >= 4)
tmp.create(4 * maxk, inch, size / 4 + (size % 4) / 2 + size % 2, 8u, 8, opt.workspace_allocator);
else if (size >= 2)
tmp.create(2 * maxk, inch, size / 2 + size % 2, 8u, 8, opt.workspace_allocator);
else
tmp.create(maxk, inch, size, 8u, 8, opt.workspace_allocator);
#else
if (size >= 2)
tmp.create(2 * maxk, inch, size / 2 + size % 2, 8u, 8, opt.workspace_allocator);
else
tmp.create(maxk, inch, size, 8u, 8, opt.workspace_allocator);
#endif
{
#if __AVX2__
int remain_size_start = 0;
int nn_size = size >> 2;
#pragma omp parallel for num_threads(opt.num_threads)
for (int ii = 0; ii < nn_size; ii++)
{
int i = remain_size_start + ii * 4;
int64_t* tmpptr = tmp.channel(i / 4);
for (int q = 0; q < inch; q++)
{
const int64_t* img0 = (const int64_t*)bottom_im2col.channel(q) + i;
for (int k = 0; k < maxk; k++)
{
__m256i _v = _mm256_loadu_si256((const __m256i*)img0);
_mm256_storeu_si256((__m256i*)tmpptr, _v);
tmpptr += 4;
img0 += size;
}
}
}
remain_size_start += nn_size << 2;
nn_size = (size - remain_size_start) >> 1;
#else
int remain_size_start = 0;
int nn_size = size >> 1;
#endif
#pragma omp parallel for num_threads(opt.num_threads)
for (int ii = 0; ii < nn_size; ii++)
{
int i = remain_size_start + ii * 2;
#if __AVX2__
int64_t* tmpptr = tmp.channel(i / 4 + (i % 4) / 2);
#else
int64_t* tmpptr = tmp.channel(i / 2);
#endif
for (int q = 0; q < inch; q++)
{
const int64_t* img0 = (const int64_t*)bottom_im2col.channel(q) + i;
for (int k = 0; k < maxk; k++)
{
__m128i _v = _mm_loadu_si128((const __m128i*)img0);
_mm_storeu_si128((__m128i*)tmpptr, _v);
tmpptr += 2;
img0 += size;
}
}
}
remain_size_start += nn_size << 1;
#pragma omp parallel for num_threads(opt.num_threads)
for (int i = remain_size_start; i < size; i++)
{
#if __AVX2__
int64_t* tmpptr = tmp.channel(i / 4 + (i % 4) / 2 + i % 2);
#else
int64_t* tmpptr = tmp.channel(i / 2 + i % 2);
#endif
for (int q = 0; q < inch; q++)
{
const int64_t* img0 = (const int64_t*)bottom_im2col.channel(q) + i;
for (int k = 0; k < maxk; k++)
{
tmpptr[0] = img0[0];
tmpptr += 1;
img0 += size;
}
}
}
}
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < outch; p++)
{
int* outptr0 = top_blob.channel(p);
int i = 0;
#if __AVX2__
for (; i + 3 < size; i += 4)
{
const signed char* tmpptr = tmp.channel(i / 4);
const signed char* kptr0 = kernel.channel(p);
int nn = inch * maxk; // inch always > 0
__m256i _sum00_11 = _mm256_setzero_si256();
__m256i _sum10_01 = _mm256_setzero_si256();
__m256i _sum02_13 = _mm256_setzero_si256();
__m256i _sum12_03 = _mm256_setzero_si256();
__m256i _sum04_15 = _mm256_setzero_si256();
__m256i _sum14_05 = _mm256_setzero_si256();
__m256i _sum06_17 = _mm256_setzero_si256();
__m256i _sum16_07 = _mm256_setzero_si256();
int j = 0;
for (; j < nn; j++)
{
__m128i _val01 = _mm_loadu_si128((const __m128i*)tmpptr);
__m256i _val01_16 = _mm256_cvtepi8_epi16(_val01);
__m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
__m128i _w23 = _mm_loadu_si128((const __m128i*)(kptr0 + 16));
__m256i _w01_16 = _mm256_cvtepi8_epi16(_w01);
__m256i _w23_16 = _mm256_cvtepi8_epi16(_w23);
__m256i _val10_16 = _mm256_permute4x64_epi64(_val01_16, 78);
#if __AVXVNNI__ || __AVX512VNNI__
_sum00_11 = _mm256_dpwssd_epi32(_sum00_11, _val01_16, _w01_16);
_sum10_01 = _mm256_dpwssd_epi32(_sum10_01, _val10_16, _w01_16);
_sum02_13 = _mm256_dpwssd_epi32(_sum02_13, _val01_16, _w23_16);
_sum12_03 = _mm256_dpwssd_epi32(_sum12_03, _val10_16, _w23_16);
#else
__m256i _sl00_11 = _mm256_mullo_epi16(_val01_16, _w01_16);
__m256i _sh00_11 = _mm256_mulhi_epi16(_val01_16, _w01_16);
__m256i _sl10_01 = _mm256_mullo_epi16(_val10_16, _w01_16);
__m256i _sh10_01 = _mm256_mulhi_epi16(_val10_16, _w01_16);
__m256i _sl02_13 = _mm256_mullo_epi16(_val01_16, _w23_16);
__m256i _sh02_13 = _mm256_mulhi_epi16(_val01_16, _w23_16);
__m256i _sl12_03 = _mm256_mullo_epi16(_val10_16, _w23_16);
__m256i _sh12_03 = _mm256_mulhi_epi16(_val10_16, _w23_16);
_sum00_11 = _mm256_add_epi32(_sum00_11, _mm256_unpacklo_epi16(_sl00_11, _sh00_11));
_sum10_01 = _mm256_add_epi32(_sum10_01, _mm256_unpacklo_epi16(_sl10_01, _sh10_01));
_sum02_13 = _mm256_add_epi32(_sum02_13, _mm256_unpacklo_epi16(_sl02_13, _sh02_13));
_sum12_03 = _mm256_add_epi32(_sum12_03, _mm256_unpacklo_epi16(_sl12_03, _sh12_03));
_sum00_11 = _mm256_add_epi32(_sum00_11, _mm256_unpackhi_epi16(_sl00_11, _sh00_11));
_sum10_01 = _mm256_add_epi32(_sum10_01, _mm256_unpackhi_epi16(_sl10_01, _sh10_01));
_sum02_13 = _mm256_add_epi32(_sum02_13, _mm256_unpackhi_epi16(_sl02_13, _sh02_13));
_sum12_03 = _mm256_add_epi32(_sum12_03, _mm256_unpackhi_epi16(_sl12_03, _sh12_03));
#endif
__m128i _val23 = _mm_loadu_si128((const __m128i*)(tmpptr + 16));
__m256i _val23_16 = _mm256_cvtepi8_epi16(_val23);
__m256i _val32_16 = _mm256_permute4x64_epi64(_val23_16, 78);
#if __AVXVNNI__ || __AVX512VNNI__
_sum04_15 = _mm256_dpwssd_epi32(_sum04_15, _val23_16, _w01_16);
_sum14_05 = _mm256_dpwssd_epi32(_sum14_05, _val32_16, _w01_16);
_sum06_17 = _mm256_dpwssd_epi32(_sum06_17, _val23_16, _w23_16);
_sum16_07 = _mm256_dpwssd_epi32(_sum16_07, _val32_16, _w23_16);
#else
__m256i _sl04_15 = _mm256_mullo_epi16(_val23_16, _w01_16);
__m256i _sh04_15 = _mm256_mulhi_epi16(_val23_16, _w01_16);
__m256i _sl14_05 = _mm256_mullo_epi16(_val32_16, _w01_16);
__m256i _sh14_05 = _mm256_mulhi_epi16(_val32_16, _w01_16);
__m256i _sl06_17 = _mm256_mullo_epi16(_val23_16, _w23_16);
__m256i _sh06_17 = _mm256_mulhi_epi16(_val23_16, _w23_16);
__m256i _sl16_07 = _mm256_mullo_epi16(_val32_16, _w23_16);
__m256i _sh16_07 = _mm256_mulhi_epi16(_val32_16, _w23_16);
_sum04_15 = _mm256_add_epi32(_sum04_15, _mm256_unpacklo_epi16(_sl04_15, _sh04_15));
_sum14_05 = _mm256_add_epi32(_sum14_05, _mm256_unpacklo_epi16(_sl14_05, _sh14_05));
_sum06_17 = _mm256_add_epi32(_sum06_17, _mm256_unpacklo_epi16(_sl06_17, _sh06_17));
_sum16_07 = _mm256_add_epi32(_sum16_07, _mm256_unpacklo_epi16(_sl16_07, _sh16_07));
_sum04_15 = _mm256_add_epi32(_sum04_15, _mm256_unpackhi_epi16(_sl04_15, _sh04_15));
_sum14_05 = _mm256_add_epi32(_sum14_05, _mm256_unpackhi_epi16(_sl14_05, _sh14_05));
_sum06_17 = _mm256_add_epi32(_sum06_17, _mm256_unpackhi_epi16(_sl06_17, _sh06_17));
_sum16_07 = _mm256_add_epi32(_sum16_07, _mm256_unpackhi_epi16(_sl16_07, _sh16_07));
#endif
tmpptr += 32;
kptr0 += 32;
}
// transpose 4x8
{
__m256i _tmp0, _tmp1, _tmp2, _tmp3;
_tmp0 = _mm256_unpacklo_epi32(_sum00_11, _sum10_01);
_tmp1 = _mm256_unpacklo_epi32(_sum02_13, _sum12_03);
_tmp2 = _mm256_unpackhi_epi32(_sum00_11, _sum10_01);
_tmp3 = _mm256_unpackhi_epi32(_sum02_13, _sum12_03);
_sum00_11 = _mm256_unpacklo_epi64(_tmp0, _tmp1);
_sum10_01 = _mm256_unpackhi_epi64(_tmp0, _tmp1);
_sum02_13 = _mm256_unpacklo_epi64(_tmp2, _tmp3);
_sum12_03 = _mm256_unpackhi_epi64(_tmp2, _tmp3);
}
{
__m256i _tmp0, _tmp1, _tmp2, _tmp3;
_tmp0 = _mm256_unpacklo_epi32(_sum04_15, _sum14_05);
_tmp1 = _mm256_unpacklo_epi32(_sum06_17, _sum16_07);
_tmp2 = _mm256_unpackhi_epi32(_sum04_15, _sum14_05);
_tmp3 = _mm256_unpackhi_epi32(_sum06_17, _sum16_07);
_sum04_15 = _mm256_unpacklo_epi64(_tmp0, _tmp1);
_sum14_05 = _mm256_unpackhi_epi64(_tmp0, _tmp1);
_sum06_17 = _mm256_unpacklo_epi64(_tmp2, _tmp3);
_sum16_07 = _mm256_unpackhi_epi64(_tmp2, _tmp3);
}
_sum00_11 = _mm256_add_epi32(_sum00_11, _sum10_01);
_sum02_13 = _mm256_add_epi32(_sum02_13, _sum12_03);
_sum00_11 = _mm256_add_epi32(_sum00_11, _sum02_13);
_sum04_15 = _mm256_add_epi32(_sum04_15, _sum14_05);
_sum06_17 = _mm256_add_epi32(_sum06_17, _sum16_07);
_sum04_15 = _mm256_add_epi32(_sum04_15, _sum06_17);
__m256i _perm_mask = _mm256_set_epi32(6, 3, 4, 1, 7, 2, 5, 0);
_sum00_11 = _mm256_permutevar8x32_epi32(_sum00_11, _perm_mask);
_sum04_15 = _mm256_permutevar8x32_epi32(_sum04_15, _perm_mask);
_mm256_storeu_si256((__m256i*)outptr0, _sum00_11);
_mm256_storeu_si256((__m256i*)(outptr0 + 8), _sum04_15);
outptr0 += 16;
}
#endif
for (; i + 1 < size; i += 2)
{
#if __AVX2__
const signed char* tmpptr = tmp.channel(i / 4 + (i % 4) / 2);
#else
const signed char* tmpptr = tmp.channel(i / 2);
#endif
const signed char* kptr0 = kernel.channel(p);
int nn = inch * maxk; // inch always > 0
#if __AVX2__
__m256i _sum00_11 = _mm256_setzero_si256();
__m256i _sum10_01 = _mm256_setzero_si256();
__m256i _sum02_13 = _mm256_setzero_si256();
__m256i _sum12_03 = _mm256_setzero_si256();
#else
__m128i _sum00 = _mm_setzero_si128();
__m128i _sum01 = _mm_setzero_si128();
__m128i _sum02 = _mm_setzero_si128();
__m128i _sum03 = _mm_setzero_si128();
__m128i _sum10 = _mm_setzero_si128();
__m128i _sum11 = _mm_setzero_si128();
__m128i _sum12 = _mm_setzero_si128();
__m128i _sum13 = _mm_setzero_si128();
#endif
int j = 0;
for (; j < nn; j++)
{
#if __AVX2__
__m128i _val01 = _mm_loadu_si128((const __m128i*)tmpptr);
__m256i _val01_16 = _mm256_cvtepi8_epi16(_val01);
__m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
__m128i _w23 = _mm_loadu_si128((const __m128i*)(kptr0 + 16));
__m256i _w01_16 = _mm256_cvtepi8_epi16(_w01);
__m256i _w23_16 = _mm256_cvtepi8_epi16(_w23);
__m256i _val10_16 = _mm256_permute4x64_epi64(_val01_16, 78);
#if __AVXVNNI__ || __AVX512VNNI__
_sum00_11 = _mm256_dpwssd_epi32(_sum00_11, _val01_16, _w01_16);
_sum10_01 = _mm256_dpwssd_epi32(_sum10_01, _val10_16, _w01_16);
_sum02_13 = _mm256_dpwssd_epi32(_sum02_13, _val01_16, _w23_16);
_sum12_03 = _mm256_dpwssd_epi32(_sum12_03, _val10_16, _w23_16);
#else
__m256i _sl00_11 = _mm256_mullo_epi16(_val01_16, _w01_16);
__m256i _sh00_11 = _mm256_mulhi_epi16(_val01_16, _w01_16);
__m256i _sl10_01 = _mm256_mullo_epi16(_val10_16, _w01_16);
__m256i _sh10_01 = _mm256_mulhi_epi16(_val10_16, _w01_16);
__m256i _sl02_13 = _mm256_mullo_epi16(_val01_16, _w23_16);
__m256i _sh02_13 = _mm256_mulhi_epi16(_val01_16, _w23_16);
__m256i _sl12_03 = _mm256_mullo_epi16(_val10_16, _w23_16);
__m256i _sh12_03 = _mm256_mulhi_epi16(_val10_16, _w23_16);
_sum00_11 = _mm256_add_epi32(_sum00_11, _mm256_unpacklo_epi16(_sl00_11, _sh00_11));
_sum10_01 = _mm256_add_epi32(_sum10_01, _mm256_unpacklo_epi16(_sl10_01, _sh10_01));
_sum02_13 = _mm256_add_epi32(_sum02_13, _mm256_unpacklo_epi16(_sl02_13, _sh02_13));
_sum12_03 = _mm256_add_epi32(_sum12_03, _mm256_unpacklo_epi16(_sl12_03, _sh12_03));
_sum00_11 = _mm256_add_epi32(_sum00_11, _mm256_unpackhi_epi16(_sl00_11, _sh00_11));
_sum10_01 = _mm256_add_epi32(_sum10_01, _mm256_unpackhi_epi16(_sl10_01, _sh10_01));
_sum02_13 = _mm256_add_epi32(_sum02_13, _mm256_unpackhi_epi16(_sl02_13, _sh02_13));
_sum12_03 = _mm256_add_epi32(_sum12_03, _mm256_unpackhi_epi16(_sl12_03, _sh12_03));
#endif
#else
__m128i _val01 = _mm_loadu_si128((const __m128i*)tmpptr);
__m128i _extval01 = _mm_cmpgt_epi8(_mm_setzero_si128(), _val01);
__m128i _val0 = _mm_unpacklo_epi8(_val01, _extval01);
__m128i _val1 = _mm_unpackhi_epi8(_val01, _extval01);
__m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
__m128i _w23 = _mm_loadu_si128((const __m128i*)(kptr0 + 16));
__m128i _extw01 = _mm_cmpgt_epi8(_mm_setzero_si128(), _w01);
__m128i _extw23 = _mm_cmpgt_epi8(_mm_setzero_si128(), _w23);
__m128i _w0 = _mm_unpacklo_epi8(_w01, _extw01);
__m128i _w1 = _mm_unpackhi_epi8(_w01, _extw01);
__m128i _w2 = _mm_unpacklo_epi8(_w23, _extw23);
__m128i _w3 = _mm_unpackhi_epi8(_w23, _extw23);
__m128i _sl00 = _mm_mullo_epi16(_val0, _w0);
__m128i _sh00 = _mm_mulhi_epi16(_val0, _w0);
__m128i _sl01 = _mm_mullo_epi16(_val0, _w1);
__m128i _sh01 = _mm_mulhi_epi16(_val0, _w1);
__m128i _sl02 = _mm_mullo_epi16(_val0, _w2);
__m128i _sh02 = _mm_mulhi_epi16(_val0, _w2);
__m128i _sl03 = _mm_mullo_epi16(_val0, _w3);
__m128i _sh03 = _mm_mulhi_epi16(_val0, _w3);
__m128i _sl10 = _mm_mullo_epi16(_val1, _w0);
__m128i _sh10 = _mm_mulhi_epi16(_val1, _w0);
__m128i _sl11 = _mm_mullo_epi16(_val1, _w1);
__m128i _sh11 = _mm_mulhi_epi16(_val1, _w1);
__m128i _sl12 = _mm_mullo_epi16(_val1, _w2);
__m128i _sh12 = _mm_mulhi_epi16(_val1, _w2);
__m128i _sl13 = _mm_mullo_epi16(_val1, _w3);
__m128i _sh13 = _mm_mulhi_epi16(_val1, _w3);
_sum00 = _mm_add_epi32(_sum00, _mm_unpacklo_epi16(_sl00, _sh00));
_sum01 = _mm_add_epi32(_sum01, _mm_unpacklo_epi16(_sl01, _sh01));
_sum02 = _mm_add_epi32(_sum02, _mm_unpacklo_epi16(_sl02, _sh02));
_sum03 = _mm_add_epi32(_sum03, _mm_unpacklo_epi16(_sl03, _sh03));
_sum00 = _mm_add_epi32(_sum00, _mm_unpackhi_epi16(_sl00, _sh00));
_sum01 = _mm_add_epi32(_sum01, _mm_unpackhi_epi16(_sl01, _sh01));
_sum02 = _mm_add_epi32(_sum02, _mm_unpackhi_epi16(_sl02, _sh02));
_sum03 = _mm_add_epi32(_sum03, _mm_unpackhi_epi16(_sl03, _sh03));
_sum10 = _mm_add_epi32(_sum10, _mm_unpacklo_epi16(_sl10, _sh10));
_sum11 = _mm_add_epi32(_sum11, _mm_unpacklo_epi16(_sl11, _sh11));
_sum12 = _mm_add_epi32(_sum12, _mm_unpacklo_epi16(_sl12, _sh12));
_sum13 = _mm_add_epi32(_sum13, _mm_unpacklo_epi16(_sl13, _sh13));
_sum10 = _mm_add_epi32(_sum10, _mm_unpackhi_epi16(_sl10, _sh10));
_sum11 = _mm_add_epi32(_sum11, _mm_unpackhi_epi16(_sl11, _sh11));
_sum12 = _mm_add_epi32(_sum12, _mm_unpackhi_epi16(_sl12, _sh12));
_sum13 = _mm_add_epi32(_sum13, _mm_unpackhi_epi16(_sl13, _sh13));
#endif
tmpptr += 16;
kptr0 += 32;
}
#if __AVX2__
// transpose 4x8
{
__m256i _tmp0, _tmp1, _tmp2, _tmp3;
_tmp0 = _mm256_unpacklo_epi32(_sum00_11, _sum10_01);
_tmp1 = _mm256_unpacklo_epi32(_sum02_13, _sum12_03);
_tmp2 = _mm256_unpackhi_epi32(_sum00_11, _sum10_01);
_tmp3 = _mm256_unpackhi_epi32(_sum02_13, _sum12_03);
_sum00_11 = _mm256_unpacklo_epi64(_tmp0, _tmp1);
_sum10_01 = _mm256_unpackhi_epi64(_tmp0, _tmp1);
_sum02_13 = _mm256_unpacklo_epi64(_tmp2, _tmp3);
_sum12_03 = _mm256_unpackhi_epi64(_tmp2, _tmp3);
}
_sum00_11 = _mm256_add_epi32(_sum00_11, _sum10_01);
_sum02_13 = _mm256_add_epi32(_sum02_13, _sum12_03);
_sum00_11 = _mm256_add_epi32(_sum00_11, _sum02_13);
__m256i _perm_mask = _mm256_set_epi32(6, 3, 4, 1, 7, 2, 5, 0);
_sum00_11 = _mm256_permutevar8x32_epi32(_sum00_11, _perm_mask);
_mm256_storeu_si256((__m256i*)outptr0, _sum00_11);
#else
// transpose 4x4
{
__m128i _tmp0, _tmp1, _tmp2, _tmp3;
_tmp0 = _mm_unpacklo_epi32(_sum00, _sum01);
_tmp1 = _mm_unpacklo_epi32(_sum02, _sum03);
_tmp2 = _mm_unpackhi_epi32(_sum00, _sum01);
_tmp3 = _mm_unpackhi_epi32(_sum02, _sum03);
_sum00 = _mm_unpacklo_epi64(_tmp0, _tmp1);
_sum01 = _mm_unpackhi_epi64(_tmp0, _tmp1);
_sum02 = _mm_unpacklo_epi64(_tmp2, _tmp3);
_sum03 = _mm_unpackhi_epi64(_tmp2, _tmp3);
}
{
__m128i _tmp0, _tmp1, _tmp2, _tmp3;
_tmp0 = _mm_unpacklo_epi32(_sum10, _sum11);
_tmp1 = _mm_unpacklo_epi32(_sum12, _sum13);
_tmp2 = _mm_unpackhi_epi32(_sum10, _sum11);
_tmp3 = _mm_unpackhi_epi32(_sum12, _sum13);
_sum10 = _mm_unpacklo_epi64(_tmp0, _tmp1);
_sum11 = _mm_unpackhi_epi64(_tmp0, _tmp1);
_sum12 = _mm_unpacklo_epi64(_tmp2, _tmp3);
_sum13 = _mm_unpackhi_epi64(_tmp2, _tmp3);
}
_sum00 = _mm_add_epi32(_sum00, _sum01);
_sum02 = _mm_add_epi32(_sum02, _sum03);
_sum10 = _mm_add_epi32(_sum10, _sum11);
_sum12 = _mm_add_epi32(_sum12, _sum13);
_sum00 = _mm_add_epi32(_sum00, _sum02);
_sum10 = _mm_add_epi32(_sum10, _sum12);
_mm_storeu_si128((__m128i*)outptr0, _sum00);
_mm_storeu_si128((__m128i*)(outptr0 + 4), _sum10);
#endif
outptr0 += 8;
}
for (; i < size; i++)
{
#if __AVX2__
const signed char* tmpptr = tmp.channel(i / 4 + (i % 4) / 2 + i % 2);
#else
const signed char* tmpptr = tmp.channel(i / 2 + i % 2);
#endif
const signed char* kptr0 = kernel.channel(p);
int nn = inch * maxk; // inch always > 0
#if __AVX2__
__m256i _sum0_1 = _mm256_setzero_si256();
__m256i _sum2_3 = _mm256_setzero_si256();
#else
__m128i _sum0 = _mm_setzero_si128();
__m128i _sum1 = _mm_setzero_si128();
__m128i _sum2 = _mm_setzero_si128();
__m128i _sum3 = _mm_setzero_si128();
#endif
int j = 0;
for (; j < nn; j++)
{
#if __AVX2__
__m128i _val = _mm_loadl_epi64((const __m128i*)tmpptr);
_val = _mm_cvtepi8_epi16(_val);
__m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
__m128i _w23 = _mm_loadu_si128((const __m128i*)(kptr0 + 16));
__m256i _w01_16 = _mm256_cvtepi8_epi16(_w01);
__m256i _w23_16 = _mm256_cvtepi8_epi16(_w23);
__m256i _valval = _mm256_inserti128_si256(_mm256_castsi128_si256(_val), _val, 1);
#if __AVXVNNI__ || __AVX512VNNI__
_sum0_1 = _mm256_dpwssd_epi32(_sum0_1, _valval, _w01_16);
_sum2_3 = _mm256_dpwssd_epi32(_sum2_3, _valval, _w23_16);
#else
__m256i _sl0_1 = _mm256_mullo_epi16(_valval, _w01_16);
__m256i _sh0_1 = _mm256_mulhi_epi16(_valval, _w01_16);
__m256i _sl2_3 = _mm256_mullo_epi16(_valval, _w23_16);
__m256i _sh2_3 = _mm256_mulhi_epi16(_valval, _w23_16);
_sum0_1 = _mm256_add_epi32(_sum0_1, _mm256_unpacklo_epi16(_sl0_1, _sh0_1));
_sum2_3 = _mm256_add_epi32(_sum2_3, _mm256_unpacklo_epi16(_sl2_3, _sh2_3));
_sum0_1 = _mm256_add_epi32(_sum0_1, _mm256_unpackhi_epi16(_sl0_1, _sh0_1));
_sum2_3 = _mm256_add_epi32(_sum2_3, _mm256_unpackhi_epi16(_sl2_3, _sh2_3));
#endif
#else
__m128i _val = _mm_loadl_epi64((const __m128i*)tmpptr);
#if __SSE4_1__
_val = _mm_cvtepi8_epi16(_val);
#else
_val = _mm_unpacklo_epi8(_val, _mm_cmpgt_epi8(_mm_setzero_si128(), _val));
#endif
__m128i _w01 = _mm_loadu_si128((const __m128i*)kptr0);
__m128i _w23 = _mm_loadu_si128((const __m128i*)(kptr0 + 16));
__m128i _extw01 = _mm_cmpgt_epi8(_mm_setzero_si128(), _w01);
__m128i _extw23 = _mm_cmpgt_epi8(_mm_setzero_si128(), _w23);
__m128i _w0 = _mm_unpacklo_epi8(_w01, _extw01);
__m128i _w1 = _mm_unpackhi_epi8(_w01, _extw01);
__m128i _w2 = _mm_unpacklo_epi8(_w23, _extw23);
__m128i _w3 = _mm_unpackhi_epi8(_w23, _extw23);
__m128i _sl0 = _mm_mullo_epi16(_val, _w0);
__m128i _sh0 = _mm_mulhi_epi16(_val, _w0);
__m128i _sl1 = _mm_mullo_epi16(_val, _w1);
__m128i _sh1 = _mm_mulhi_epi16(_val, _w1);
__m128i _sl2 = _mm_mullo_epi16(_val, _w2);
__m128i _sh2 = _mm_mulhi_epi16(_val, _w2);
__m128i _sl3 = _mm_mullo_epi16(_val, _w3);
__m128i _sh3 = _mm_mulhi_epi16(_val, _w3);
_sum0 = _mm_add_epi32(_sum0, _mm_unpacklo_epi16(_sl0, _sh0));
_sum1 = _mm_add_epi32(_sum1, _mm_unpacklo_epi16(_sl1, _sh1));
_sum2 = _mm_add_epi32(_sum2, _mm_unpacklo_epi16(_sl2, _sh2));
_sum3 = _mm_add_epi32(_sum3, _mm_unpacklo_epi16(_sl3, _sh3));
_sum0 = _mm_add_epi32(_sum0, _mm_unpackhi_epi16(_sl0, _sh0));
_sum1 = _mm_add_epi32(_sum1, _mm_unpackhi_epi16(_sl1, _sh1));
_sum2 = _mm_add_epi32(_sum2, _mm_unpackhi_epi16(_sl2, _sh2));
_sum3 = _mm_add_epi32(_sum3, _mm_unpackhi_epi16(_sl3, _sh3));
#endif
tmpptr += 8;
kptr0 += 32;
}
#if __AVX2__
__m128i _sum0 = _mm256_extracti128_si256(_sum0_1, 0);
__m128i _sum1 = _mm256_extracti128_si256(_sum0_1, 1);
__m128i _sum2 = _mm256_extracti128_si256(_sum2_3, 0);
__m128i _sum3 = _mm256_extracti128_si256(_sum2_3, 1);
#endif
// transpose 4x4
{
__m128i _tmp0, _tmp1, _tmp2, _tmp3;
_tmp0 = _mm_unpacklo_epi32(_sum0, _sum1);
_tmp1 = _mm_unpacklo_epi32(_sum2, _sum3);
_tmp2 = _mm_unpackhi_epi32(_sum0, _sum1);
_tmp3 = _mm_unpackhi_epi32(_sum2, _sum3);
_sum0 = _mm_unpacklo_epi64(_tmp0, _tmp1);
_sum1 = _mm_unpackhi_epi64(_tmp0, _tmp1);
_sum2 = _mm_unpacklo_epi64(_tmp2, _tmp3);
_sum3 = _mm_unpackhi_epi64(_tmp2, _tmp3);
}
_sum0 = _mm_add_epi32(_sum0, _sum1);
_sum2 = _mm_add_epi32(_sum2, _sum3);
_sum0 = _mm_add_epi32(_sum0, _sum2);
_mm_storeu_si128((__m128i*)outptr0, _sum0);
outptr0 += 4;
}
}
}
static void convolution_im2col_sgemm_transform_kernel_pack8to4_int8_sse(const Mat& _kernel, Mat& kernel_tm, int inch, int outch, int kernel_w, int kernel_h)
{
const int maxk = kernel_w * kernel_h;
// interleave
// src = maxk-inch-outch
// dst = 8a-4b-maxk-inch/8a-outch/4b
Mat kernel = _kernel.reshape(maxk, inch, outch);
kernel_tm.create(32 * maxk, inch / 8, outch / 4, (size_t)1u);
for (int q = 0; q + 3 < outch; q += 4)
{
signed char* g00 = kernel_tm.channel(q / 4);
for (int p = 0; p + 7 < inch; p += 8)
{
for (int k = 0; k < maxk; k++)
{
for (int i = 0; i < 4; i++)
{
for (int j = 0; j < 8; j++)
{
const signed char* k00 = kernel.channel(q + i).row<const signed char>(p + j);
g00[0] = k00[k];
g00++;
}
}
}
}
}
}
static void convolution_im2col_sgemm_pack8to4_int8_sse(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, int kernel_w, int kernel_h, int dilation_w, int dilation_h, int stride_w, int stride_h, const Option& opt)
{
int w = bottom_blob.w;
int inch = bottom_blob.c;
int outw = top_blob.w;
int outh = top_blob.h;
const int size = outw * outh;
const int maxk = kernel_w * kernel_h;
// im2col
Mat bottom_im2col(size, maxk, inch, 8u, 8, opt.workspace_allocator);
{
const int gap = w * stride_h - outw * stride_w;
#pragma omp parallel for num_threads(opt.num_threads)
for (int p = 0; p < inch; p++)
{
const Mat img = bottom_blob.channel(p);
int64_t* ptr = bottom_im2col.channel(p);
for (int u = 0; u < kernel_h; u++)
{
for (int v = 0; v < kernel_w; v++)
{
const int64_t* sptr = img.row<const int64_t>(dilation_h * u) + dilation_w * v;
for (int i = 0; i < outh; i++)
{
int j = 0;
for (; j < outw; j++)
{
ptr[0] = sptr[0];
sptr += stride_w;
ptr += 1;
}
sptr += gap;
}
}
}
}
}
im2col_sgemm_pack8to4_int8_sse(bottom_im2col, top_blob, kernel, opt);
}
|
fig3.10-mxv-omp.c | /*
DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS HEADER.
Copyright 2009 Sun Microsystems, Inc. All rights reserved.
The contents of this file are subject to the terms of the BSD License("BSD")(the "License").
You can obtain a copy of the License at: http://www.opensparc.net/pubs/t1/licenses/BSD+_License.txt
The BSD License
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Redistribution of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistribution in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in
the documentation and/or other materials provided with the
distribution.
* Neither the name of Sun Microsystems, Inc. or the names of
contributors may be used to endorse or promote products derived
from this software without specific prior written permission.
This software is provided "AS IS," without a warranty of any kind. ALL
EXPRESS OR IMPLIED CONDITIONS, REPRESENTATIONS AND WARRANTIES, INCLUDING ANY
IMPLIED WARRANTY OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE OR
NON-INFRINGEMENT, ARE HEREBY EXCLUDED. SUN MICROSYSTEMS, INC. ("SUN") AND
ITS LICENSORS SHALL NOT BE LIABLE FOR ANY DAMAGES SUFFERED BY LICENSEE AS A
RESULT OF USING, MODIFYING OR DISTRIBUTING THIS SOFTWARE OR ITS DERIVATIVES.
IN NO EVENT WILL SUN OR ITS LICENSORS BE LIABLE FOR ANY LOST REVENUE, PROFIT
OR DATA, OR FOR DIRECT, INDIRECT, SPECIAL, CONSEQUENTIAL, INCIDENTAL OR
PUNITIVE DAMAGES, HOWEVER CAUSED AND REGARDLESS OF THE THEORY OF LIABILITY,
ARISING OUT OF THE USE OF OR INABILITY TO USE THIS SOFTWARE, EVEN IF SUN HAS
BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.
You acknowledge that this software is not designed, licensed or intended for
use in the design, construction, operation or maintenance of any nuclear facility.
*/
#include <stdio.h>
#include <stdlib.h>
void mxv(int m, int n, double * restrict a,
double * restrict b, double * restrict c);
int main(int argc, char *argv[])
{
double *a,*b,*c;
int i, j, m, n;
printf("Please give m and n: ");
scanf("%d %d",&m,&n);
printf("\n");
if ( (a=(double *)malloc(m*sizeof(double))) == NULL )
perror("memory allocation for a");
if ( (b=(double *)malloc(m*n*sizeof(double))) == NULL )
perror("memory allocation for b");
if ( (c=(double *)malloc(n*sizeof(double))) == NULL )
perror("memory allocation for c");
printf("Initializing matrix B and vector c\n");
for (j=0; j<n; j++)
c[j] = 2.0;
for (i=0; i<m; i++)
for (j=0; j<n; j++)
b[i*n+j] = i;
printf("Executing mxv function for m = %d n = %d\n",m,n);
(void) mxv(m, n, a, b, c);
free(a);free(b);free(c);
return(0);
}
void mxv(int m, int n, double * restrict a, double * restrict b,
double * restrict c)
{
int i, j;
#pragma omp parallel for default(none) \
shared(m,n,a,b,c) private(i,j)
for (i=0; i<m; i++)
{
a[i] = 0.0;
for (j=0; j<n; j++)
a[i] += b[i*n+j]*c[j];
} /*-- End of omp parallel for --*/
}
|
pixrender.c | /**
* My solution to being unable to
* apply per-pixel effects using
* the SDL2 primitive render functions
*
* (See header file for details on
* PixBuffers)
*/
//#include <omp.h>
#include "pixrender.h"
uint32_t getColor(uint8_t r, uint8_t g, uint8_t b, uint8_t a);
/**
* Precomputed 4x4 bayer matrix
* to be used for ordered dithering
* based on 4 patterns
* (see PixBuffer_orderedDither)
*/
const double ditherMatrix[16] = {
-0.875, 0.125, -0.625, 0.375,
0.625, -0.375, 0.875, -0.125,
-0.5, 0.5, -0.75, 0.25,
1.0, 0.0, 0.75, -0.25
};
PixBuffer* PixBuffer_initPixBuffer(uint32_t width, uint32_t height)
{
PixBuffer* newBuffer = (PixBuffer*)malloc(sizeof(PixBuffer));
newBuffer->pixels = (uint32_t*)malloc(sizeof(uint32_t)*width*height);
newBuffer->width = width;
newBuffer->height = height;
return newBuffer;
}
void PixBuffer_delPixBuffer(PixBuffer* buffer)
{
free(buffer->pixels);
free(buffer);
}
/** PixBuffer_drawColumn
* @brief Draws a column to a pixel buffer
* Note: drawColumn <b>does not</b> check x bound
* Ensure that your draw functions choose
* an X value less than the buffer width
* @param buffer PixBuffer struct to write to
* @param x x coordinate of column
* @param y y coordinate of <b>top</b> of column
* @param h height of column
**/
void PixBuffer_drawColumn(PixBuffer* buffer, uint32_t x, int32_t y, int32_t h, SDL_Color color)
{
if (y < 0)
{
h = h + y;
y = 0;
}
if (y + h > buffer->height)
{
h = buffer->height - y;
}
////#pragma omp parallel for schedule(dynamic,1)
for (int32_t i = y; i < y + h; i++)
{
PixBuffer_drawPix(buffer, x, i, PixBuffer_toPixColor(color.r,color.g,color.b,color.a));
}
}
/** PixBuffer_drawRow
* @brief Draws a row to a pixel buffer
* Note: drawRow <b>does not</b> check x <b>or</b>
* y bounds. Be careful to ensure x, w, and y
* parameters are within the buffer size
* @param buffer PixBuffer struct to write to
* @param x x coordinate of <b>left</b> of row
* @param y y coordinate of row
* @param w width of row
**/
void PixBuffer_drawRow(PixBuffer* buffer, uint32_t x, uint32_t y, uint32_t w, SDL_Color color)
{
int r = color.r;
int g = color.g;
int b = color.b;
int a = color.a;
double alpha = ((double)(color.a))/255.0;
for (int32_t i = x; i < w; i++)
{
if (a) // Alpha transparency, compute alpha based on array colors
{
uint32_t oldPix = buffer->pixels[(y*buffer->width)+(i)];
int oldR = (int)(oldPix >> 3*8);
int oldG = (int)((oldPix >> 2*8) & 0xFF);
int oldB = (int)((oldPix >> 8) & 0xFF);
r = (int)((double)(color.r) * alpha + (double)oldR * (1.0-alpha));
g = (int)((double)(color.g) * alpha + (double)oldG * (1.0-alpha));
b = (int)((double)(color.b) * alpha + (double)oldB * (1.0-alpha));
PixBuffer_drawPix(buffer, i, y, PixBuffer_toPixColor(r,g,b,0xff));
}
}
}
/** PixBuffer_drawRect
* @brief Draws a filled rectangle to a pixel buffer
*
* @param buffer PixBuffer struct to write to
* @param rect SDL_Rect struct with coordinate and dimension data
**/
void PixBuffer_drawRect(PixBuffer* buffer, SDL_Rect* rect, SDL_Color color)
{
if (rect->x < buffer->width)
{
for (uint32_t i = rect->x; i < rect->x + rect->w; i++)
{
if (i < buffer->width)
{
PixBuffer_drawColumn(buffer, i, rect->y, rect->h, color);
}
}
}
}
void PixBuffer_drawHorizGradient(PixBuffer* buffer, SDL_Rect* rect, SDL_Color colTop, SDL_Color colBottom)
{
if (rect->x < buffer->width && rect->x+rect->w <= buffer->width)
{
double rStep = ((double)colBottom.r - (double)colTop.r) / rect->h;
double gStep = ((double)colBottom.g - (double)colTop.g) / rect->h;
double bStep = ((double)colBottom.b - (double)colTop.b) / rect->h;
double aStep = ((double)colBottom.a - (double)colTop.a) / rect->h;
SDL_Color drawColor;
//#pragma omp parallel for schedule(dynamic,1) private(drawColor)
for (uint32_t i = 0; i < rect->h; i++)
{
if (i < buffer->height)
{
drawColor.r = colTop.r+(int)(rStep*i);
drawColor.g = colTop.g+(int)(gStep*i);
drawColor.b = colTop.b+(int)(bStep*i);
drawColor.a = colTop.a+(int)(aStep*i);
PixBuffer_drawRow(buffer, rect->x, rect->y+i, rect->w, drawColor);
}
}
}
}
/** PixBuffer_initSprite
* @brief Initializes new RaySprite for engine
* TODO: Better integrate with 2D sprites, add more metadata
* TODO: Consolidate w/ GameEngine
* @param newSprite Pointer to new RaySprite
* @param texture RayTex representing sprite frame data
* @param scaleFactor Default sprite size
* @param alphaNum Default sprite transparency
* @param x Map x coordinate
* @param y Map y coordinate
* @param h Map h coordinate
*/
void PixSprite_initSprite(PixSprite* newSprite, PixTex* texture, double scaleFactor, double alphaNum, double x, double y)
{
newSprite->texture = texture;
newSprite->scaleFactor = scaleFactor;
newSprite->alphaNum = alphaNum;
newSprite->x = x;
newSprite->y = y;
newSprite->frameNum = 0;
}
/** PixBuffer_draw2DSprite
* @brief Renders a 2D sprite to the screen
* TODO: Better manage w/ 3D sprites
* @param buffer PixBuffer to render to
* @param sprite RaySprite to render
* @param angle Angle (rad) to render sprite at
* TODO: Add to sprite metadata
*/
void PixBuffer_draw2DSprite(PixBuffer* buffer, PixSprite sprite, double angle)
{
// First, compute screen-space sprite dimensions
double scaleWidth = sprite.texture->tileWidth*sprite.scaleFactor;
double scaleHeight = sprite.texture->tileHeight*sprite.scaleFactor;
int32_t boundSize = (uint32_t)(scaleWidth > scaleHeight ? scaleWidth*1.5 : scaleHeight*1.5);
// Then render sprite based on dimensions
int32_t texX;
int32_t texY;
double pixX;
double pixY;
uint32_t pixColor;
// For all pixels in bounding box (yes, I know the box can be more dynamically sized but
// I'm lazy and this will have to cut it for now)
for (int32_t i = -boundSize/2; i < boundSize/2; i++)
{
for (int32_t j = -boundSize/2; j < boundSize/2; j++)
{
texX = (int32_t)round((i * cos(angle) - j * sin(angle)) / sprite.scaleFactor + sprite.texture->tileWidth/2.0 - 0.5);
texY = (int32_t)round((i * sin(angle) + j * cos(angle)) / sprite.scaleFactor + sprite.texture->tileHeight/2.0 - 0.5);
pixX = sprite.x + i;
pixY = sprite.y + j;
if (pixX >= 0 && pixX < buffer->width && pixY >= 0 && pixY < buffer->height &&\
texX >= 0 && texX < sprite.texture->tileWidth && texY >=0 && texY < sprite.texture->tileHeight)
{
pixColor = PixBuffer_getTex(sprite.texture, 0, texX, texY);
PixBuffer_drawPixAlpha(buffer, pixX, pixY, pixColor, sprite.alphaNum);
}
}
}
}
void PixBuffer_mergeBuffer(PixBuffer* target, PixBuffer* source, double alpha)
{
uint32_t sourcePix;
for (uint32_t i = 0; i < source->height; i++)
{
if (i < target->height)
{
for (uint32_t j = 0; j < source->width; j++)
{
if (j < target->width)
{
sourcePix = source->pixels[j+i*source->width];
PixBuffer_drawPixAlpha(target, j, i, sourcePix, alpha);
}
}
}
}
}
void PixBuffer_fillBuffer(PixBuffer* target, uint32_t color, double alpha)
{
for (uint32_t i = 0; i < target->height; i++)
{
if (i < target->height)
{
for (uint32_t j = 0; j < target->width; j++)
{
if (j < target->width)
{
PixBuffer_drawPixAlpha(target, j, i, color, alpha);
}
}
}
}
}
void PixBuffer_drawBuffOffset(PixBuffer* target, PixBuffer* source, uint32_t x, uint32_t y, int32_t xOff)
{
int32_t xCoord;
for (uint32_t i = 0; i < source->height; i++)
{
if (i < target->height)
{
for (uint32_t j = 0; j < source->width; j++)
{
if (j < target->width)
{
xCoord = (j + xOff) % target->width;
target->pixels[j+i*target->width] = source->pixels[xCoord+i*target->width];
}
}
}
}
}
/** PixBuffer_clearBuffer
* @brief Clears buffer array to 0x00
* * Useful if you need to quickly reuse a buffer
* * for drawing layers/graphics updates. Sets to
* * transparent black using memset
* @param buffer PixBuffer struct to clear
**/
void PixBuffer_clearBuffer(PixBuffer* buffer)
{
memset(buffer->pixels, 0, buffer->width * buffer->height * 4);
}
/** PixBuffer_paletteFilter
* @brief Remaps RGB buffer colors to a given pallette
* * Note: it is important to ensure paletteNum is no longer than
* * the palette list, otherwise your this will index nonexistant colors
* * and make your output look really funky. And possibly segfault I guess
* @param buffer PixBuffer to palettize
* @param palette SDL_Color array to quantitize to
* @param paletteNum length of color palette
* @todo consolidate palletteFilter and nearestColor functions
**/
void PixBuffer_paletteFilter(PixBuffer* buffer, SDL_Color* palette, int paletteNum)
{
int r;
int g;
int b;
int colNum = 0;
for (uint32_t p = 0; p < buffer->width * buffer->height; p++)
{
if (buffer->pixels[p] != 0)
{
r = (int)(buffer->pixels[p] >> 3*8);
g = (int)((buffer->pixels[p] >> 2*8) & 0xFF);
b = (int)((buffer->pixels[p] >> 8) & 0xFF);
uint32_t minColorDif = 0xFF*0xFF*3;//adjustedColorDiff(r, g, b, colorPallette[0].r, colorPallette[0].g, colorPallette[0].b);
for (int i = 0; i < paletteNum; i++)
{
uint32_t colorDif = (uint32_t)(palette[i].r - r)*(palette[i].r - r) + (uint32_t)(palette[i].g - g)*(palette[i].g - g) + (uint32_t)(palette[i].b - b)*(palette[i].b - b);
//double colorDif = adjustedColorDiff(r, g, b, colorPallette[i].r, colorPallette[i].g, colorPallette[i].b);//(uint32_t)(rFact * (double)(colorPallette[i].r - r))*(rFact * (double)(colorPallette[i].r - r)) + (gFact * (double)(colorPallette[i].g - g))*(gFact * (double)(colorPallette[i].g - g)) + (bFact * (double)(colorPallette[i].b - b))*(bFact * (double)(colorPallette[i].b - b));
if (colorDif < minColorDif)
{
minColorDif = colorDif;
colNum = i;
}
}
buffer->pixels[p] = (uint32_t)(palette[colNum].r) << 3*8 | (uint32_t)(palette[colNum].g) << 2*8 | (uint32_t)(palette[colNum].b) << 8 | (uint32_t)0xFF;
}
}
}
/** getNearestColor
* @brief Internal function called by orderedDither for quantitization
*
* @param palette SDL_Color array to quantitize to
* @param paletteNum length of color palette
* @param colorDat buffer format color to quantititize
* @return buffer format color of closest palette match
**/
uint32_t getNearestColor(SDL_Color* palette, int paletteNum, uint32_t colorDat)
{
int r = (int)(colorDat >> 3*8);
int g = (int)((colorDat >> 2*8) & 0xFF);
int b = (int)((colorDat >> 8) & 0xFF);
int colNum = 0;
uint32_t minColorDif = 0xFF*0xFF*3;//adjustedColorDiff(r, g, b, colorPallette[0].r, colorPallette[0].g, colorPallette[0].b);
for (int i = 0; i < paletteNum; i++)
{
uint32_t colorDif = (uint32_t)(palette[i].r - r)*(palette[i].r - r) + (uint32_t)(palette[i].g - g)*(palette[i].g - g) + (uint32_t)(palette[i].b - b)*(palette[i].b - b);
if (colorDif < minColorDif)
{
minColorDif = colorDif;
colNum = i;
}
}
return (uint32_t)(palette[colNum].r) << 3*8 | (uint32_t)(palette[colNum].g) << 2*8 | (uint32_t)(palette[colNum].b) << 8 | (uint32_t)0xFF;
}
/**
* PixBuffer_orderDither
* The algorithm for this is somewhat based on the pseudocode
* from the wikipedia page, but adapted once I found out
* how this works
* @brief Applies an ordered dither effect to a buffer
*
* @param buffer PixBuffer to dither
* @param palette SDL_Color array to quantitize to
* @param paletteNum length of color palette
* @param scaleFactor intensity of dither weights
**/
void PixBuffer_orderDither(PixBuffer* buffer, SDL_Color* palette, int paletteNum, double scaleFactor)
{
// Components to decode RGBA format
int32_t r;
int32_t g;
int32_t b;
int32_t dithFactor;
// default: 4
// How much the matrix weights should vary the input colors
int32_t newColor;
//#pragma omp parallel for schedule(dynamic,1) private(r,g,b,dithFactor,newColor)
for (uint32_t y = 0; y < buffer->height; y++)
{
for (uint32_t x = 0; x < buffer->width; x++)
{
if (buffer->pixels[y*buffer->width+x] != 0)
{
r = (int)(buffer->pixels[y*buffer->width+x] >> 3*8);
g = (int)((buffer->pixels[y*buffer->width+x] >> 2*8) & 0xFF);
b = (int)((buffer->pixels[y*buffer->width+x] >> 8) & 0xFF);
// Finds associated dither weight, which will
// be applied to the color to bring it above or below the threshold
// for getNearestColor to assign a varied brightness
dithFactor = scaleFactor*ditherMatrix[(y%4)*4+(x%4)];
r = (int)(r + dithFactor);
if (r > 255)
{
r = 255;
}
else if (r < 0)
{
r = 0;
}
g = (int)(g + dithFactor);
if (g > 255)
{
g = 255;
}
else if (g < 0)
{
g = 0;
}
b = (int)(b + dithFactor);
if (b > 255)
{
b = 255;
}
else if (b < 0)
{
b = 0;
}
newColor = (uint32_t)(r) << 3*8 | (uint32_t)(g) << 2*8 | (uint32_t)(b) << 8 | (uint32_t)0xFF;
buffer->pixels[y*buffer->width+x] = getNearestColor(palette, paletteNum, newColor);
}
}
}
}
/** to8BitColor
* @brief Paletizes 32bit color to 8bit color
*
* @param colorDat Raw truecolor value to paletize
* @return 8 bit color value
*/
uint32_t to8BitColor(uint32_t colorDat)
{
int r = (int)(colorDat >> 3*8);
int g = (int)((colorDat >> 2*8) & 0xFF);
int b = (int)((colorDat >> 8) & 0xFF);
int newR = (int)ceil(round((double)r / 255.0*15) * (255.0/15));
int newG = (int)ceil(round((double)g / 255.0*15) * (255.0/15));
int newB = (int)ceil(round((double)b / 255.0*15) * (255.0/15));
return (uint32_t)(newR) << 3*8 | (uint32_t)(newG) << 2*8 | (uint32_t)newB << 8 | (uint32_t)0xFF;
}
/** PixBuffer_orderDither256
* Uses matrix dithering to palletize truecolor buffer to
* 8-bit 256 color pallette
* @brief Applies 256 color dithering filter to buffer
*
* @param buffer PixBuffer to apply filter to
* @param scaleFactor Stength of dithering. Multiplies values in
* matrix to increase extremety of offsets
**/
void PixBuffer_orderDither256(PixBuffer* buffer, double scaleFactor)
{
// Components to decode RGBA format
int32_t r;
int32_t g;
int32_t b;
int32_t dithFactor;
// default: 4
// How much the matrix weights should vary the input colors
int32_t newColor;
for (uint32_t y = 0; y < buffer->height; y++)
{
for (uint32_t x = 0; x < buffer->width; x++)
{
if (buffer->pixels[y*buffer->width+x] != 0)
{
r = (int)(buffer->pixels[y*buffer->width+x] >> 3*8);
g = (int)((buffer->pixels[y*buffer->width+x] >> 2*8) & 0xFF);
b = (int)((buffer->pixels[y*buffer->width+x] >> 8) & 0xFF);
// Finds associated dither weight, which will
// be applied to the color to bring it above or below the threshold
// for getNearestColor to assign a varied brightness
dithFactor = scaleFactor*ditherMatrix[(y%4)*4+(x%4)];
r = (int)(r + dithFactor);
if (r > 255)
{
r = 255;
}
else if (r < 0)
{
r = 0;
}
g = (int)(g + dithFactor);
if (g > 255)
{
g = 255;
}
else if (g < 0)
{
g = 0;
}
b = (int)(b + dithFactor);
if (b > 255)
{
b = 255;
}
else if (b < 0)
{
b = 0;
}
newColor = (uint32_t)(r) << 3*8 | (uint32_t)(g) << 2*8 | (uint32_t)(b) << 8 | (uint32_t)0xFF;
buffer->pixels[y*buffer->width+x] = to8BitColor(newColor);
}
}
}
}
/** PixBuffer_monochromeFilter
* * Note: Does not check fade percentage, could overflow color values
* @brief Monochrome filter with selectable target color and saturation
* @param buffer PixBuffer to apply filter to
* @param targetColor Color to adjust chrominance towards
* @param fadePercent Degree of monochromatic-ness (inverse saturation)
**/
void PixBuffer_monochromeFilter(PixBuffer* buffer, SDL_Color targetColor, double fadePercent)
{
SDL_Color oldColor;
int targetAvg;
uint32_t newColor;
double targetR = targetColor.r/255.0;
double targetG = targetColor.g/255.0;
double targetB = targetColor.b/255.0;
int dr;
int dg;
int db;
for (int y = 0; y < buffer->height; y++)
{
for (int x = 0; x < buffer->width; x++)
{
oldColor = PixBuffer_toSDLColor(PixBuffer_getPix(buffer, x, y));
targetAvg = (oldColor.r + oldColor.g + oldColor.b) / 3;
dr = (targetAvg * targetR - oldColor.r) * fadePercent;
dg = (targetAvg * targetG - oldColor.g) * fadePercent;
db = (targetAvg * targetB - oldColor.b) * fadePercent;
newColor = PixBuffer_toPixColor((uint8_t)(oldColor.r + dr), (uint8_t)(oldColor.g + dg), (uint8_t)(oldColor.b + db), (uint8_t)oldColor.a);
PixBuffer_drawPix(buffer, x, y, newColor);
}
}
}
/** PixBuffer_inverseFilter
* @brief Inverts the RGB channels of all pixels in a PixBuffer
* @param buffer PixBuffer to swap channels of
**/
void PixBuffer_inverseFilter(PixBuffer* buffer)
{
SDL_Color oldColor;
uint32_t newColor;
int r;
int g;
int b;
for (int y = 0; y < buffer->height; y++)
{
for (int x = 0; x < buffer->width; x++)
{
oldColor = PixBuffer_toSDLColor(PixBuffer_getPix(buffer, x, y));
r = (255 - oldColor.r);
g = (255 - oldColor.g);
b = (255 - oldColor.b);
newColor = PixBuffer_toPixColor((uint8_t)r, (uint8_t)g, (uint8_t)b, (uint8_t)oldColor.a);
PixBuffer_drawPix(buffer, x, y, newColor);
}
}
}
/** PixBuffer_toPixColor
* @brief Returns color formatted to RGBA format
* @param r SDL_Color red component
* @param g SDL_Color green component
* @param b SDL_Color blue component
* @param a SDL_Color alpha component
**/
uint32_t PixBuffer_toPixColor(uint8_t r, uint8_t g, uint8_t b, uint8_t a)
{
return ((uint32_t)r << 3*8 | (uint32_t)g << 2*8 | (uint32_t)b << 8 | (uint32_t)a);
}
SDL_Color PixBuffer_toSDLColor(uint32_t pixColor)
{
int r = (int)(pixColor >> 3*8);
int g = (int)((pixColor >> 2*8) & 0xFF);
int b = (int)((pixColor >> 8) & 0xFF);
int a = (int)(pixColor & 0xFF);
SDL_Color newColor = {r, g, b, a};
return newColor;
}
uint32_t PixBuffer_blendAlpha(uint32_t baseColor, uint32_t addColor, double alphaNum)
{
SDL_Color newSDLColor;
uint32_t newColor;
int addR = (int)(addColor >> 3*8);
int addG = (int)((addColor >> 2*8) & 0xFF);
int addB = (int)((addColor >> 8) & 0xFF);
int addA = (int)(addColor & 0xFF);
if (alphaNum*addA != 0 && alphaNum*addA != 255) // Alpha transparency, compute alpha based on array colors
{
double alpha = ((double)addA)/255.0 * (alphaNum);
int oldR = (int)(baseColor >> 3*8);
int oldG = (int)((baseColor >> 2*8) & 0xFF);
int oldB = (int)((baseColor >> 8) & 0xFF);
int oldA = (int)(baseColor & 0xFF);
newSDLColor.r = (int)((double)addR * alpha + (double)oldR * (1-alpha));
newSDLColor.g = (int)((double)addG * alpha + (double)oldG * (1-alpha));
newSDLColor.b = (int)((double)addB * alpha + (double)oldB * (1-alpha));
if (oldA == 255)
{
newSDLColor.a = 255;
}
else
{
newSDLColor.a = (int)((double)addA * alpha + (double)oldA * (1-alpha));
}
newColor = PixBuffer_toPixColor(newSDLColor.r, newSDLColor.g, newSDLColor.b, newSDLColor.a);
}
else
{
newColor = baseColor;
}
return newColor;
}
uint32_t PixBuffer_getPix(PixBuffer* buffer, uint32_t x, uint32_t y)
{
return buffer->pixels[x + y * buffer->width];
}
uint32_t PixBuffer_getTex(PixTex* texture, uint8_t tileNum, uint32_t x, uint32_t y)
{
return texture->pixData[(tileNum*texture->tileHeight + y) * texture->tileWidth + x];
}
/** PixBuffer_drawPix
* @brief Draws a single pixel to the PixBuffer
* @param buffer PixBuffer to draw to
* @param x x coordinate of pixel
* @param y y coordinate of pixel
**/
void PixBuffer_drawPix(PixBuffer* buffer, uint32_t x, uint32_t y, uint32_t color)
{
if (x < buffer->width && y < buffer->height)
{
buffer->pixels[y*buffer->width+x] = color;
}
}
void PixBuffer_drawPixAlpha(PixBuffer* buffer, uint32_t x, uint32_t y, uint32_t color, double alphaNum)
{
int r = (int)(color >> 3*8);
int g = (int)((color >> 2*8) & 0xFF);
int b = (int)((color >> 8) & 0xFF);
int a = (int)(color & 0xFF);
if (a)
{
if (alphaNum*a != 0 && alphaNum*a != 255) // Alpha transparency, compute alpha based on array colors
{
double alpha = ((double)a)/255.0 * (alphaNum);
uint32_t oldPix = buffer->pixels[y*buffer->width+x];
int oldR = (int)(oldPix >> 3*8);
int oldG = (int)((oldPix >> 2*8) & 0xFF);
int oldB = (int)((oldPix >> 8) & 0xFF);
int oldA = (int)(oldPix & 0xFF);
r = (int)((double)r * alpha + (double)oldR * (1-alpha));
g = (int)((double)g * alpha + (double)oldG * (1-alpha));
b = (int)((double)b * alpha + (double)oldB * (1-alpha));
a = (int)((double)a * alpha + (double)oldA * (1-alpha));
}
PixBuffer_drawPix(buffer, x, y, PixBuffer_toPixColor(r,g,b,a));
}
}
void PixBuffer_drawPixDouble(PixBuffer* buffer, double x, double y, uint32_t color, double alphaNum)
{
uint32_t baseX = (uint32_t)floor(x);
uint32_t baseY = (uint32_t)floor(y);
double partX = x - baseX;
double partY = y - baseY;
if (x >= 0 && y >= 0)
{
PixBuffer_drawPixAlpha(buffer, baseX, baseY, color, alphaNum);
}
if (partX > 0.5)
{
baseX++;
PixBuffer_drawPixAlpha(buffer, baseX, baseY, color, alphaNum);
}
else if (partX < -0.5)
{
baseX--;
PixBuffer_drawPixAlpha(buffer, baseX, baseY, color, alphaNum);
}
if (partY > 0.5)
{
baseY++;
PixBuffer_drawPixAlpha(buffer, baseX, baseY, color, alphaNum);
}
else if (partY < -0.5)
{
baseY--;
PixBuffer_drawPixAlpha(buffer, baseX, baseY, color, alphaNum);
}
//PixBuffer_drawPixAlpha(buffer, baseX, baseY, color, alphaNum);
}
// PixTex FUNCTIONS
PixTex* PixTex_initFromRGBA(uint8_t* rgbaData, uint32_t tileWidth, uint32_t tileHeight, uint8_t numTiles)
{
PixTex* newTex = (PixTex*)malloc(sizeof(PixTex));
newTex->tileWidth = tileWidth;
newTex->tileHeight = tileHeight;
newTex->tileCount = numTiles;
// Convert color chars into pixel ints
newTex->pixData =
(uint32_t*)malloc(sizeof(uint32_t)*tileWidth*tileHeight*numTiles);
uint32_t newPix = 0;
for (uint32_t p = 0; p < tileWidth * tileHeight * numTiles; p++)
{
// Get each component
for (uint8_t comp = 0; comp < 4; comp++)
{
newPix |= ((uint32_t)(rgbaData[p*4+comp]) << (8 * (3-comp)));
}
newTex->pixData[p] = newPix;
newPix = 0;
}
return newTex;
}
void PixTex_delPixTex(PixTex* tex)
{
free(tex->pixData);
free(tex);
}
|
conversions.h | #ifndef CONVERSIONS_H
#define CONVERSIONS_H
#include <stdio.h>
#include <stdlib.h>
#include <cmath>
#include <float.h>
#include "omp.h"
#include "loewner_declaration.h"
#include "morph_color_matrix.h"
/*
*============================================================================================================================================
* Class that contains methods for performing conversions between different image formats.
* Algorithms for conversions are following the paper An approach to color-morphology based on Einstein addition and Loewner order by
* Bernhard Burgeth and Andreas Kleefeld.
*
* Current version is implemented to perform conversions in parallel using OpenMP, with the number of threads predefined by user.
*
* version: 1.0
* author: Filip Srnec
*============================================================================================================================================
*/
#ifndef PI
#define PI 3.141592653589793
#endif
#ifndef KAPPA
#define KAPPA 0.707106781186547
#endif
#ifndef RGB_MAX
#define RGB_MAX 255.0
#endif
#ifndef INTENSITY_ALPHA
#define INTENSITY_ALPHA 10
#endif
#ifndef INTENSITY_FACTOR
#define INTENSITY_FACTOR ((T) RGB_MAX / INTENSITY_ALPHA)
#endif
#ifndef HUE_TRESHOLD
#define HUE_TRESHOLD 0.5
#endif
class LoewnerMorphology::Conversions {
private:
// Helper method for finding a minimum among 3 values. T must have operator <.
template<typename T>
static T min3(T a, T b, T c);
// Helper method for finding a maximum among 3 values. T must have operator >.
template<typename T>
static T max3(T a, T b, T c);
// Helper method that converts hue values to rgb values
template<typename T>
static T hueToRgb(T p, T q, T t);
public:
/*
* Performs a conversion from RGB-value image to M-HCL-value image. RGB values should be stored
* on memory locations r, g and b respectively. Result will be stored on locations h, c and l.
* All memory should be previously allocated. Argument size is the size of the initial image (width * height).
*/
template<typename T>
static void rgb2mhcl(const T *r, const T *g, const T *b, T *h, T *c, T *l, int size);
/*
* Performs a conversion from M-HCL-value image to RGB-value image. H, C and L values should be stored on memory locations
* r, g and b respectively. Result will be stored on locations r, g and b. All memory should be previously allocated.
* Argument size is the size of the initial image (width * height).
*/
template<typename T>
static void mhcl2rgb(const T *h, const T *c, const T *l, T *r, T *g, T *b, int size);
/*
* Converts the image vector containing M-HCL values to the vector containing
* MorphColorMatrix objects. Memory for the new vector needs to be allocated and passed
* as a vector argument. It should be array of MorphColorMatrix values which size is equal
* as the size of the image. Pointers h, c and l are the pointers to the values
* of the hue, chroma and luminance.
*/
template<typename T>
static void mhcl2matrix(const T *h, const T *c, const T *l, LoewnerMorphology::MorphColorMatrix *vector, int size);
/*
* Converts the vector containing MorphColorMatrix objects to M-HCL values. Memory for the new vectors needs
* to be allocated and passed as a h,c and l arguments. Size of each destination pointer must be equal
* to the size of the image. Pointers h, c and l are the pointers to the values of the hue, chroma and
* lightness for the given image.
*/
template<typename T>
static void matrix2mhcl(const LoewnerMorphology::MorphColorMatrix *vector, T *h, T *c, T *l, int size);
/*
* Converts an immage array of values of type T to the image array of double values. It is assumed that conversion is legal.
* Memory for both arrays must be allocated before entering the method.
*/
template<typename T>
static void type2double(const T *imgType, double *imgDouble, int size);
/*
* Converts an image array of double values to the image array of values of type T. It is assumed that conversion is legal.
* Memory for both arrays should be allocated before entering the method.
*/
template<typename T>
static void double2type(const double *imgDouble, T *imgType, int size);
};
// IMPLEMENTATION
template<typename T>
T LoewnerMorphology::Conversions::min3(T a, T b, T c) {
if (a < b) {
if (a < c) {
return a;
} else {
return (b < c) ? b : c;
}
} else {
if (b < c) {
return b;
} else {
return (a < c) ? a : c;
}
}
}
template<typename T>
T LoewnerMorphology::Conversions::max3(T a, T b, T c) {
if (a > b) {
if (a > c) {
return a;
} else {
return (b > c) ? b : c;
}
} else {
if (b > c) {
return b;
} else {
return (a > c) ? a : c;
}
}
}
template<typename T>
void LoewnerMorphology::Conversions::rgb2mhcl(const T *r, const T *g, const T *b, T *h, T *c, T *l, int size) {
#pragma omp parallel for
for (int i = 0; i < size; i++) {
T r1 = r[i] / RGB_MAX;
T g1 = g[i] / RGB_MAX;
T b1 = b[i] / RGB_MAX;
T cMax = max3(r1, g1, b1);
T cMin = min3(r1, g1, b1);
T delta = cMax - cMin;
if (delta == 0) {
h[i] = 0;
} else if (cMax == r1) {
h[i] = ((g1 - b1) / delta) + (g1 < b1 ? 6.0 : 0.0);
} else if (cMax == g1) {
h[i] = (2 + ((b1 - r1) / delta));
} else {
h[i] = (4 + ((r1 - g1) / delta));
}
if (h[i] < 0) {
h[i] += 1;
}
h[i] /= 6.0;
c[i] = delta;
l[i] = cMin + cMax - 1;
}
}
template<typename T>
T LoewnerMorphology::Conversions::hueToRgb(T p, T q, T t) {
if (t < 0)
t += 1;
if (t > 1)
t -= 1;
if (t < (T) 1 / 6)
return p + (q - p) * 6 * t;
if (t < (T) 1 / 2)
return q;
if (t < (T) 2 / 3)
return p + (q - p) * ((T) 2 / 3 - t) * 6;
return p;
}
template<typename T>
void LoewnerMorphology::Conversions::mhcl2rgb(const T *h, const T *c, const T *l, T *r, T *g, T *b, int size) {
#pragma omp parallel for
for (int i = 0; i < size; i++) {
T delta = c[i];
T l_val = (l[i] + 1) / 2;
T s_val = (delta < 1e-4) ? 0 : delta / (1 - std::abs(l[i]));
T q = (l_val < 0.5) ? (l_val * (1 + s_val)) : (l_val + s_val - (l_val * s_val));
T p = 2 * l_val - q;
r[i] = std::round(hueToRgb(p, q, h[i] + (T) 1 / 3) * RGB_MAX);
g[i] = std::round(hueToRgb(p, q, h[i]) * RGB_MAX);
b[i] = std::round(hueToRgb(p, q, h[i] - (T) 1 / 3) * RGB_MAX);
}
}
template<typename T>
void LoewnerMorphology::Conversions::mhcl2matrix(const T *h, const T *c, const T *l, LoewnerMorphology::MorphColorMatrix *vector, int size) {
#pragma omp parallel for
for (int i = 0; i < size; i++) {
T hv = h[i];
T cv = c[i];
T z = l[i];
T value = 2 * PI * hv;
T x = cv * std::cos(value);
T y = cv * std::sin(value);
LoewnerMorphology::MorphColorMatrix temp;
temp.a = KAPPA * (z - y);
temp.b = KAPPA * x;
temp.c = KAPPA * (z + y);
vector[i] = temp;
}
}
template<typename T>
void LoewnerMorphology::Conversions::matrix2mhcl(const LoewnerMorphology::MorphColorMatrix *vector, T *h, T *c, T *l, int size) {
#pragma omp parallel for
for (int i = 0; i < size; i++) {
LoewnerMorphology::MorphColorMatrix temp = vector[i];
T x = 2 * KAPPA * temp.b;
T y = KAPPA * (temp.c - temp.a);
T z = KAPPA * (temp.c + temp.a);
T at = std::atan2(y, x);
if (at < 0) {
at = at + 2 * PI;
}
h[i] = at / (2 * PI);
c[i] = std::sqrt(x * x + y * y);
l[i] = z;
}
}
template<typename T>
void LoewnerMorphology::Conversions::type2double(const T *imgOriginal, double *imgDouble, int size) {
#pragma omp parallel for
for (int i = 0; i < size; i++) {
imgDouble[i] = (double)imgOriginal[i];
}
}
template<typename T>
void LoewnerMorphology::Conversions::double2type(const double *imgDouble, T *imgType, int size) {
#pragma omp parallel for
for (int i = 0; i < size; i++) {
imgType[i] = (T)imgDouble[i];
}
}
#endif
|
test8.c | int foo(int a[]) {
#pragma omp parallel
{
a[0] = 1;
}
}
int main() {
int arr[10];
int x;
foo(arr);
x = 10;
}
|
enm_cython.c | /* Generated by Cython 0.25.1 */
#define PY_SSIZE_T_CLEAN
#include "Python.h"
#ifndef Py_PYTHON_H
#error Python headers needed to compile C extensions, please install development version of Python.
#elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03020000)
#error Cython requires Python 2.6+ or Python 3.2+.
#else
#define CYTHON_ABI "0_25_1"
#include <stddef.h>
#ifndef offsetof
#define offsetof(type, member) ( (size_t) & ((type*)0) -> member )
#endif
#if !defined(WIN32) && !defined(MS_WINDOWS)
#ifndef __stdcall
#define __stdcall
#endif
#ifndef __cdecl
#define __cdecl
#endif
#ifndef __fastcall
#define __fastcall
#endif
#endif
#ifndef DL_IMPORT
#define DL_IMPORT(t) t
#endif
#ifndef DL_EXPORT
#define DL_EXPORT(t) t
#endif
#ifndef HAVE_LONG_LONG
#if PY_VERSION_HEX >= 0x03030000 || (PY_MAJOR_VERSION == 2 && PY_VERSION_HEX >= 0x02070000)
#define HAVE_LONG_LONG
#endif
#endif
#ifndef PY_LONG_LONG
#define PY_LONG_LONG LONG_LONG
#endif
#ifndef Py_HUGE_VAL
#define Py_HUGE_VAL HUGE_VAL
#endif
#ifdef PYPY_VERSION
#define CYTHON_COMPILING_IN_PYPY 1
#define CYTHON_COMPILING_IN_PYSTON 0
#define CYTHON_COMPILING_IN_CPYTHON 0
#undef CYTHON_USE_TYPE_SLOTS
#define CYTHON_USE_TYPE_SLOTS 0
#undef CYTHON_USE_ASYNC_SLOTS
#define CYTHON_USE_ASYNC_SLOTS 0
#undef CYTHON_USE_PYLIST_INTERNALS
#define CYTHON_USE_PYLIST_INTERNALS 0
#undef CYTHON_USE_UNICODE_INTERNALS
#define CYTHON_USE_UNICODE_INTERNALS 0
#undef CYTHON_USE_UNICODE_WRITER
#define CYTHON_USE_UNICODE_WRITER 0
#undef CYTHON_USE_PYLONG_INTERNALS
#define CYTHON_USE_PYLONG_INTERNALS 0
#undef CYTHON_AVOID_BORROWED_REFS
#define CYTHON_AVOID_BORROWED_REFS 1
#undef CYTHON_ASSUME_SAFE_MACROS
#define CYTHON_ASSUME_SAFE_MACROS 0
#undef CYTHON_UNPACK_METHODS
#define CYTHON_UNPACK_METHODS 0
#undef CYTHON_FAST_THREAD_STATE
#define CYTHON_FAST_THREAD_STATE 0
#undef CYTHON_FAST_PYCALL
#define CYTHON_FAST_PYCALL 0
#elif defined(PYSTON_VERSION)
#define CYTHON_COMPILING_IN_PYPY 0
#define CYTHON_COMPILING_IN_PYSTON 1
#define CYTHON_COMPILING_IN_CPYTHON 0
#ifndef CYTHON_USE_TYPE_SLOTS
#define CYTHON_USE_TYPE_SLOTS 1
#endif
#undef CYTHON_USE_ASYNC_SLOTS
#define CYTHON_USE_ASYNC_SLOTS 0
#undef CYTHON_USE_PYLIST_INTERNALS
#define CYTHON_USE_PYLIST_INTERNALS 0
#ifndef CYTHON_USE_UNICODE_INTERNALS
#define CYTHON_USE_UNICODE_INTERNALS 1
#endif
#undef CYTHON_USE_UNICODE_WRITER
#define CYTHON_USE_UNICODE_WRITER 0
#undef CYTHON_USE_PYLONG_INTERNALS
#define CYTHON_USE_PYLONG_INTERNALS 0
#ifndef CYTHON_AVOID_BORROWED_REFS
#define CYTHON_AVOID_BORROWED_REFS 0
#endif
#ifndef CYTHON_ASSUME_SAFE_MACROS
#define CYTHON_ASSUME_SAFE_MACROS 1
#endif
#ifndef CYTHON_UNPACK_METHODS
#define CYTHON_UNPACK_METHODS 1
#endif
#undef CYTHON_FAST_THREAD_STATE
#define CYTHON_FAST_THREAD_STATE 0
#undef CYTHON_FAST_PYCALL
#define CYTHON_FAST_PYCALL 0
#else
#define CYTHON_COMPILING_IN_PYPY 0
#define CYTHON_COMPILING_IN_PYSTON 0
#define CYTHON_COMPILING_IN_CPYTHON 1
#ifndef CYTHON_USE_TYPE_SLOTS
#define CYTHON_USE_TYPE_SLOTS 1
#endif
#if PY_MAJOR_VERSION < 3
#undef CYTHON_USE_ASYNC_SLOTS
#define CYTHON_USE_ASYNC_SLOTS 0
#elif !defined(CYTHON_USE_ASYNC_SLOTS)
#define CYTHON_USE_ASYNC_SLOTS 1
#endif
#if PY_VERSION_HEX < 0x02070000
#undef CYTHON_USE_PYLONG_INTERNALS
#define CYTHON_USE_PYLONG_INTERNALS 0
#elif !defined(CYTHON_USE_PYLONG_INTERNALS)
#define CYTHON_USE_PYLONG_INTERNALS 1
#endif
#ifndef CYTHON_USE_PYLIST_INTERNALS
#define CYTHON_USE_PYLIST_INTERNALS 1
#endif
#ifndef CYTHON_USE_UNICODE_INTERNALS
#define CYTHON_USE_UNICODE_INTERNALS 1
#endif
#if PY_VERSION_HEX < 0x030300F0
#undef CYTHON_USE_UNICODE_WRITER
#define CYTHON_USE_UNICODE_WRITER 0
#elif !defined(CYTHON_USE_UNICODE_WRITER)
#define CYTHON_USE_UNICODE_WRITER 1
#endif
#ifndef CYTHON_AVOID_BORROWED_REFS
#define CYTHON_AVOID_BORROWED_REFS 0
#endif
#ifndef CYTHON_ASSUME_SAFE_MACROS
#define CYTHON_ASSUME_SAFE_MACROS 1
#endif
#ifndef CYTHON_UNPACK_METHODS
#define CYTHON_UNPACK_METHODS 1
#endif
#ifndef CYTHON_FAST_THREAD_STATE
#define CYTHON_FAST_THREAD_STATE 1
#endif
#ifndef CYTHON_FAST_PYCALL
#define CYTHON_FAST_PYCALL 1
#endif
#endif
#if !defined(CYTHON_FAST_PYCCALL)
#define CYTHON_FAST_PYCCALL (CYTHON_FAST_PYCALL && PY_VERSION_HEX >= 0x030600B1)
#endif
#if CYTHON_USE_PYLONG_INTERNALS
#include "longintrepr.h"
#undef SHIFT
#undef BASE
#undef MASK
#endif
#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag)
#define Py_OptimizeFlag 0
#endif
#define __PYX_BUILD_PY_SSIZE_T "n"
#define CYTHON_FORMAT_SSIZE_T "z"
#if PY_MAJOR_VERSION < 3
#define __Pyx_BUILTIN_MODULE_NAME "__builtin__"
#define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\
PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
#define __Pyx_DefaultClassType PyClass_Type
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#define __Pyx_BUILTIN_MODULE_NAME "builtins"
#define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\
PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
#define __Pyx_DefaultClassType PyType_Type
#endif
#ifndef Py_TPFLAGS_CHECKTYPES
#define Py_TPFLAGS_CHECKTYPES 0
#endif
#ifndef Py_TPFLAGS_HAVE_INDEX
#define Py_TPFLAGS_HAVE_INDEX 0
#endif
#ifndef Py_TPFLAGS_HAVE_NEWBUFFER
#define Py_TPFLAGS_HAVE_NEWBUFFER 0
#endif
#ifndef Py_TPFLAGS_HAVE_FINALIZE
#define Py_TPFLAGS_HAVE_FINALIZE 0
#endif
#ifndef METH_FASTCALL
#define METH_FASTCALL 0x80
typedef PyObject *(*__Pyx_PyCFunctionFast) (PyObject *self, PyObject **args,
Py_ssize_t nargs, PyObject *kwnames);
#else
#define __Pyx_PyCFunctionFast _PyCFunctionFast
#endif
#if CYTHON_FAST_PYCCALL
#define __Pyx_PyFastCFunction_Check(func)\
((PyCFunction_Check(func) && METH_FASTCALL == PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST)))
#else
#define __Pyx_PyFastCFunction_Check(func) 0
#endif
#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND)
#define CYTHON_PEP393_ENABLED 1
#define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\
0 : _PyUnicode_Ready((PyObject *)(op)))
#define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u)
#define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i)
#define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) PyUnicode_MAX_CHAR_VALUE(u)
#define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u)
#define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u)
#define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i)
#define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch)
#define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u)))
#else
#define CYTHON_PEP393_ENABLED 0
#define PyUnicode_1BYTE_KIND 1
#define PyUnicode_2BYTE_KIND 2
#define PyUnicode_4BYTE_KIND 4
#define __Pyx_PyUnicode_READY(op) (0)
#define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u)
#define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i]))
#define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111)
#define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE))
#define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u))
#define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i]))
#define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch)
#define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u))
#endif
#if CYTHON_COMPILING_IN_PYPY
#define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b)
#define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b)
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#define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b)
#define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\
PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b))
#endif
#if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains)
#define PyUnicode_Contains(u, s) PySequence_Contains(u, s)
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#if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check)
#define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type)
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#define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, "__format__", "O", fmt)
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#define PyObject_Malloc(s) PyMem_Malloc(s)
#define PyObject_Free(p) PyMem_Free(p)
#define PyObject_Realloc(p) PyMem_Realloc(p)
#endif
#if CYTHON_COMPILING_IN_PYSTON
#define __Pyx_PyCode_HasFreeVars(co) PyCode_HasFreeVars(co)
#define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno)
#else
#define __Pyx_PyCode_HasFreeVars(co) (PyCode_GetNumFree(co) > 0)
#define __Pyx_PyFrame_SetLineNumber(frame, lineno) (frame)->f_lineno = (lineno)
#endif
#define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b))
#define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b))
#if PY_MAJOR_VERSION >= 3
#define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b)
#else
#define __Pyx_PyString_Format(a, b) PyString_Format(a, b)
#endif
#if PY_MAJOR_VERSION < 3 && !defined(PyObject_ASCII)
#define PyObject_ASCII(o) PyObject_Repr(o)
#endif
#if PY_MAJOR_VERSION >= 3
#define PyBaseString_Type PyUnicode_Type
#define PyStringObject PyUnicodeObject
#define PyString_Type PyUnicode_Type
#define PyString_Check PyUnicode_Check
#define PyString_CheckExact PyUnicode_CheckExact
#endif
#if PY_MAJOR_VERSION >= 3
#define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj)
#define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj)
#else
#define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj))
#define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj))
#endif
#ifndef PySet_CheckExact
#define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type)
#endif
#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type)
#define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception)
#if PY_MAJOR_VERSION >= 3
#define PyIntObject PyLongObject
#define PyInt_Type PyLong_Type
#define PyInt_Check(op) PyLong_Check(op)
#define PyInt_CheckExact(op) PyLong_CheckExact(op)
#define PyInt_FromString PyLong_FromString
#define PyInt_FromUnicode PyLong_FromUnicode
#define PyInt_FromLong PyLong_FromLong
#define PyInt_FromSize_t PyLong_FromSize_t
#define PyInt_FromSsize_t PyLong_FromSsize_t
#define PyInt_AsLong PyLong_AsLong
#define PyInt_AS_LONG PyLong_AS_LONG
#define PyInt_AsSsize_t PyLong_AsSsize_t
#define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask
#define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask
#define PyNumber_Int PyNumber_Long
#endif
#if PY_MAJOR_VERSION >= 3
#define PyBoolObject PyLongObject
#endif
#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY
#ifndef PyUnicode_InternFromString
#define PyUnicode_InternFromString(s) PyUnicode_FromString(s)
#endif
#endif
#if PY_VERSION_HEX < 0x030200A4
typedef long Py_hash_t;
#define __Pyx_PyInt_FromHash_t PyInt_FromLong
#define __Pyx_PyInt_AsHash_t PyInt_AsLong
#else
#define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t
#define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t
#endif
#if PY_MAJOR_VERSION >= 3
#define __Pyx_PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func))
#else
#define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass)
#endif
#if CYTHON_USE_ASYNC_SLOTS
#if PY_VERSION_HEX >= 0x030500B1
#define __Pyx_PyAsyncMethodsStruct PyAsyncMethods
#define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async)
#else
typedef struct {
unaryfunc am_await;
unaryfunc am_aiter;
unaryfunc am_anext;
} __Pyx_PyAsyncMethodsStruct;
#define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved))
#endif
#else
#define __Pyx_PyType_AsAsync(obj) NULL
#endif
#ifndef CYTHON_RESTRICT
#if defined(__GNUC__)
#define CYTHON_RESTRICT __restrict__
#elif defined(_MSC_VER) && _MSC_VER >= 1400
#define CYTHON_RESTRICT __restrict
#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
#define CYTHON_RESTRICT restrict
#else
#define CYTHON_RESTRICT
#endif
#endif
#define __Pyx_void_to_None(void_result) ((void)(void_result), Py_INCREF(Py_None), Py_None)
#ifndef CYTHON_INLINE
#if defined(__GNUC__)
#define CYTHON_INLINE __inline__
#elif defined(_MSC_VER)
#define CYTHON_INLINE __inline
#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
#define CYTHON_INLINE inline
#else
#define CYTHON_INLINE
#endif
#endif
#if defined(WIN32) || defined(MS_WINDOWS)
#define _USE_MATH_DEFINES
#endif
#include <math.h>
#ifdef NAN
#define __PYX_NAN() ((float) NAN)
#else
static CYTHON_INLINE float __PYX_NAN() {
float value;
memset(&value, 0xFF, sizeof(value));
return value;
}
#endif
#if defined(__CYGWIN__) && defined(_LDBL_EQ_DBL)
#define __Pyx_truncl trunc
#else
#define __Pyx_truncl truncl
#endif
#define __PYX_ERR(f_index, lineno, Ln_error) \
{ \
__pyx_filename = __pyx_f[f_index]; __pyx_lineno = lineno; __pyx_clineno = __LINE__; goto Ln_error; \
}
#if PY_MAJOR_VERSION >= 3
#define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y)
#define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y)
#else
#define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y)
#define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y)
#endif
#ifndef __PYX_EXTERN_C
#ifdef __cplusplus
#define __PYX_EXTERN_C extern "C"
#else
#define __PYX_EXTERN_C extern
#endif
#endif
#define __PYX_HAVE__enm_cython
#define __PYX_HAVE_API__enm_cython
#include <omp.h>
#include "pythread.h"
#include <string.h>
#include <stdlib.h>
#include <stdio.h>
#include "pystate.h"
#ifdef _OPENMP
#include <omp.h>
#endif /* _OPENMP */
#ifdef PYREX_WITHOUT_ASSERTIONS
#define CYTHON_WITHOUT_ASSERTIONS
#endif
#ifndef CYTHON_UNUSED
# if defined(__GNUC__)
# if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4))
# define CYTHON_UNUSED __attribute__ ((__unused__))
# else
# define CYTHON_UNUSED
# endif
# elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER))
# define CYTHON_UNUSED __attribute__ ((__unused__))
# else
# define CYTHON_UNUSED
# endif
#endif
#ifndef CYTHON_NCP_UNUSED
# if CYTHON_COMPILING_IN_CPYTHON
# define CYTHON_NCP_UNUSED
# else
# define CYTHON_NCP_UNUSED CYTHON_UNUSED
# endif
#endif
typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* encoding;
const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry;
#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0
#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT 0
#define __PYX_DEFAULT_STRING_ENCODING ""
#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString
#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize
#define __Pyx_uchar_cast(c) ((unsigned char)c)
#define __Pyx_long_cast(x) ((long)x)
#define __Pyx_fits_Py_ssize_t(v, type, is_signed) (\
(sizeof(type) < sizeof(Py_ssize_t)) ||\
(sizeof(type) > sizeof(Py_ssize_t) &&\
likely(v < (type)PY_SSIZE_T_MAX ||\
v == (type)PY_SSIZE_T_MAX) &&\
(!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\
v == (type)PY_SSIZE_T_MIN))) ||\
(sizeof(type) == sizeof(Py_ssize_t) &&\
(is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\
v == (type)PY_SSIZE_T_MAX))) )
#if defined (__cplusplus) && __cplusplus >= 201103L
#include <cstdlib>
#define __Pyx_sst_abs(value) std::abs(value)
#elif SIZEOF_INT >= SIZEOF_SIZE_T
#define __Pyx_sst_abs(value) abs(value)
#elif SIZEOF_LONG >= SIZEOF_SIZE_T
#define __Pyx_sst_abs(value) labs(value)
#elif defined (_MSC_VER) && defined (_M_X64)
#define __Pyx_sst_abs(value) _abs64(value)
#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
#define __Pyx_sst_abs(value) llabs(value)
#elif defined (__GNUC__)
#define __Pyx_sst_abs(value) __builtin_llabs(value)
#else
#define __Pyx_sst_abs(value) ((value<0) ? -value : value)
#endif
static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject*);
static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length);
#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s))
#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l)
#define __Pyx_PyBytes_FromString PyBytes_FromString
#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize
static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*);
#if PY_MAJOR_VERSION < 3
#define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString
#define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize
#else
#define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString
#define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize
#endif
#define __Pyx_PyObject_AsSString(s) ((signed char*) __Pyx_PyObject_AsString(s))
#define __Pyx_PyObject_AsUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s))
#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s)
#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s)
#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s)
#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s)
#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s)
#if PY_MAJOR_VERSION < 3
static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u)
{
const Py_UNICODE *u_end = u;
while (*u_end++) ;
return (size_t)(u_end - u - 1);
}
#else
#define __Pyx_Py_UNICODE_strlen Py_UNICODE_strlen
#endif
#define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u))
#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode
#define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode
#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj)
#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None)
#define __Pyx_PyBool_FromLong(b) ((b) ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False))
static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*);
static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x);
static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*);
static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t);
#if CYTHON_ASSUME_SAFE_MACROS
#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x))
#else
#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x)
#endif
#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x))
#if PY_MAJOR_VERSION >= 3
#define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x))
#else
#define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x))
#endif
#define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x))
#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
static int __Pyx_sys_getdefaultencoding_not_ascii;
static int __Pyx_init_sys_getdefaultencoding_params(void) {
PyObject* sys;
PyObject* default_encoding = NULL;
PyObject* ascii_chars_u = NULL;
PyObject* ascii_chars_b = NULL;
const char* default_encoding_c;
sys = PyImport_ImportModule("sys");
if (!sys) goto bad;
default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL);
Py_DECREF(sys);
if (!default_encoding) goto bad;
default_encoding_c = PyBytes_AsString(default_encoding);
if (!default_encoding_c) goto bad;
if (strcmp(default_encoding_c, "ascii") == 0) {
__Pyx_sys_getdefaultencoding_not_ascii = 0;
} else {
char ascii_chars[128];
int c;
for (c = 0; c < 128; c++) {
ascii_chars[c] = c;
}
__Pyx_sys_getdefaultencoding_not_ascii = 1;
ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL);
if (!ascii_chars_u) goto bad;
ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL);
if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) {
PyErr_Format(
PyExc_ValueError,
"This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.",
default_encoding_c);
goto bad;
}
Py_DECREF(ascii_chars_u);
Py_DECREF(ascii_chars_b);
}
Py_DECREF(default_encoding);
return 0;
bad:
Py_XDECREF(default_encoding);
Py_XDECREF(ascii_chars_u);
Py_XDECREF(ascii_chars_b);
return -1;
}
#endif
#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3
#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL)
#else
#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL)
#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
static char* __PYX_DEFAULT_STRING_ENCODING;
static int __Pyx_init_sys_getdefaultencoding_params(void) {
PyObject* sys;
PyObject* default_encoding = NULL;
char* default_encoding_c;
sys = PyImport_ImportModule("sys");
if (!sys) goto bad;
default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL);
Py_DECREF(sys);
if (!default_encoding) goto bad;
default_encoding_c = PyBytes_AsString(default_encoding);
if (!default_encoding_c) goto bad;
__PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c));
if (!__PYX_DEFAULT_STRING_ENCODING) goto bad;
strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c);
Py_DECREF(default_encoding);
return 0;
bad:
Py_XDECREF(default_encoding);
return -1;
}
#endif
#endif
/* Test for GCC > 2.95 */
#if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95)))
#define likely(x) __builtin_expect(!!(x), 1)
#define unlikely(x) __builtin_expect(!!(x), 0)
#else /* !__GNUC__ or GCC < 2.95 */
#define likely(x) (x)
#define unlikely(x) (x)
#endif /* __GNUC__ */
static PyObject *__pyx_m;
static PyObject *__pyx_d;
static PyObject *__pyx_b;
static PyObject *__pyx_empty_tuple;
static PyObject *__pyx_empty_bytes;
static PyObject *__pyx_empty_unicode;
static int __pyx_lineno;
static int __pyx_clineno = 0;
static const char * __pyx_cfilenm= __FILE__;
static const char *__pyx_filename;
static const char *__pyx_f[] = {
"epidemic_network_modelling\\enm_cython.pyx",
"stringsource",
};
/* MemviewSliceStruct.proto */
struct __pyx_memoryview_obj;
typedef struct {
struct __pyx_memoryview_obj *memview;
char *data;
Py_ssize_t shape[8];
Py_ssize_t strides[8];
Py_ssize_t suboffsets[8];
} __Pyx_memviewslice;
/* BufferFormatStructs.proto */
#define IS_UNSIGNED(type) (((type) -1) > 0)
struct __Pyx_StructField_;
#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0)
typedef struct {
const char* name;
struct __Pyx_StructField_* fields;
size_t size;
size_t arraysize[8];
int ndim;
char typegroup;
char is_unsigned;
int flags;
} __Pyx_TypeInfo;
typedef struct __Pyx_StructField_ {
__Pyx_TypeInfo* type;
const char* name;
size_t offset;
} __Pyx_StructField;
typedef struct {
__Pyx_StructField* field;
size_t parent_offset;
} __Pyx_BufFmt_StackElem;
typedef struct {
__Pyx_StructField root;
__Pyx_BufFmt_StackElem* head;
size_t fmt_offset;
size_t new_count, enc_count;
size_t struct_alignment;
int is_complex;
char enc_type;
char new_packmode;
char enc_packmode;
char is_valid_array;
} __Pyx_BufFmt_Context;
/* Atomics.proto */
#include <pythread.h>
#ifndef CYTHON_ATOMICS
#define CYTHON_ATOMICS 1
#endif
#define __pyx_atomic_int_type int
#if CYTHON_ATOMICS && __GNUC__ >= 4 && (__GNUC_MINOR__ > 1 ||\
(__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL >= 2)) &&\
!defined(__i386__)
#define __pyx_atomic_incr_aligned(value, lock) __sync_fetch_and_add(value, 1)
#define __pyx_atomic_decr_aligned(value, lock) __sync_fetch_and_sub(value, 1)
#ifdef __PYX_DEBUG_ATOMICS
#warning "Using GNU atomics"
#endif
#elif CYTHON_ATOMICS && defined(_MSC_VER) && 0
#include <Windows.h>
#undef __pyx_atomic_int_type
#define __pyx_atomic_int_type LONG
#define __pyx_atomic_incr_aligned(value, lock) InterlockedIncrement(value)
#define __pyx_atomic_decr_aligned(value, lock) InterlockedDecrement(value)
#ifdef __PYX_DEBUG_ATOMICS
#pragma message ("Using MSVC atomics")
#endif
#elif CYTHON_ATOMICS && (defined(__ICC) || defined(__INTEL_COMPILER)) && 0
#define __pyx_atomic_incr_aligned(value, lock) _InterlockedIncrement(value)
#define __pyx_atomic_decr_aligned(value, lock) _InterlockedDecrement(value)
#ifdef __PYX_DEBUG_ATOMICS
#warning "Using Intel atomics"
#endif
#else
#undef CYTHON_ATOMICS
#define CYTHON_ATOMICS 0
#ifdef __PYX_DEBUG_ATOMICS
#warning "Not using atomics"
#endif
#endif
typedef volatile __pyx_atomic_int_type __pyx_atomic_int;
#if CYTHON_ATOMICS
#define __pyx_add_acquisition_count(memview)\
__pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock)
#define __pyx_sub_acquisition_count(memview)\
__pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock)
#else
#define __pyx_add_acquisition_count(memview)\
__pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock)
#define __pyx_sub_acquisition_count(memview)\
__pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock)
#endif
/*--- Type declarations ---*/
struct __pyx_array_obj;
struct __pyx_MemviewEnum_obj;
struct __pyx_memoryview_obj;
struct __pyx_memoryviewslice_obj;
/* "View.MemoryView":103
*
* @cname("__pyx_array")
* cdef class array: # <<<<<<<<<<<<<<
*
* cdef:
*/
struct __pyx_array_obj {
PyObject_HEAD
struct __pyx_vtabstruct_array *__pyx_vtab;
char *data;
Py_ssize_t len;
char *format;
int ndim;
Py_ssize_t *_shape;
Py_ssize_t *_strides;
Py_ssize_t itemsize;
PyObject *mode;
PyObject *_format;
void (*callback_free_data)(void *);
int free_data;
int dtype_is_object;
};
/* "View.MemoryView":275
*
* @cname('__pyx_MemviewEnum')
* cdef class Enum(object): # <<<<<<<<<<<<<<
* cdef object name
* def __init__(self, name):
*/
struct __pyx_MemviewEnum_obj {
PyObject_HEAD
PyObject *name;
};
/* "View.MemoryView":326
*
* @cname('__pyx_memoryview')
* cdef class memoryview(object): # <<<<<<<<<<<<<<
*
* cdef object obj
*/
struct __pyx_memoryview_obj {
PyObject_HEAD
struct __pyx_vtabstruct_memoryview *__pyx_vtab;
PyObject *obj;
PyObject *_size;
PyObject *_array_interface;
PyThread_type_lock lock;
__pyx_atomic_int acquisition_count[2];
__pyx_atomic_int *acquisition_count_aligned_p;
Py_buffer view;
int flags;
int dtype_is_object;
__Pyx_TypeInfo *typeinfo;
};
/* "View.MemoryView":951
*
* @cname('__pyx_memoryviewslice')
* cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<<
* "Internal class for passing memoryview slices to Python"
*
*/
struct __pyx_memoryviewslice_obj {
struct __pyx_memoryview_obj __pyx_base;
__Pyx_memviewslice from_slice;
PyObject *from_object;
PyObject *(*to_object_func)(char *);
int (*to_dtype_func)(char *, PyObject *);
};
/* "View.MemoryView":103
*
* @cname("__pyx_array")
* cdef class array: # <<<<<<<<<<<<<<
*
* cdef:
*/
struct __pyx_vtabstruct_array {
PyObject *(*get_memview)(struct __pyx_array_obj *);
};
static struct __pyx_vtabstruct_array *__pyx_vtabptr_array;
/* "View.MemoryView":326
*
* @cname('__pyx_memoryview')
* cdef class memoryview(object): # <<<<<<<<<<<<<<
*
* cdef object obj
*/
struct __pyx_vtabstruct_memoryview {
char *(*get_item_pointer)(struct __pyx_memoryview_obj *, PyObject *);
PyObject *(*is_slice)(struct __pyx_memoryview_obj *, PyObject *);
PyObject *(*setitem_slice_assignment)(struct __pyx_memoryview_obj *, PyObject *, PyObject *);
PyObject *(*setitem_slice_assign_scalar)(struct __pyx_memoryview_obj *, struct __pyx_memoryview_obj *, PyObject *);
PyObject *(*setitem_indexed)(struct __pyx_memoryview_obj *, PyObject *, PyObject *);
PyObject *(*convert_item_to_object)(struct __pyx_memoryview_obj *, char *);
PyObject *(*assign_item_from_object)(struct __pyx_memoryview_obj *, char *, PyObject *);
};
static struct __pyx_vtabstruct_memoryview *__pyx_vtabptr_memoryview;
/* "View.MemoryView":951
*
* @cname('__pyx_memoryviewslice')
* cdef class _memoryviewslice(memoryview): # <<<<<<<<<<<<<<
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*
*/
struct __pyx_vtabstruct__memoryviewslice {
struct __pyx_vtabstruct_memoryview __pyx_base;
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static struct __pyx_vtabstruct__memoryviewslice *__pyx_vtabptr__memoryviewslice;
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#define __Pyx_XINCREF(r) Py_XINCREF(r)
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#define __Pyx_XGOTREF(r)
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#define __Pyx_DECREF_SET(r, v) do {\
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#define __Pyx_XCLEAR(r) do { if((r) != NULL) {PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);}} while(0)
/* PyObjectGetAttrStr.proto */
#if CYTHON_USE_TYPE_SLOTS
static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name) {
PyTypeObject* tp = Py_TYPE(obj);
if (likely(tp->tp_getattro))
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if (likely(tp->tp_getattr))
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#define __Pyx_PyObject_GetAttrStr(o,n) PyObject_GetAttr(o,n)
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/* GetBuiltinName.proto */
static PyObject *__Pyx_GetBuiltinName(PyObject *name);
/* GetModuleGlobalName.proto */
static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name);
/* PyCFunctionFastCall.proto */
#if CYTHON_FAST_PYCCALL
static CYTHON_INLINE PyObject *__Pyx_PyCFunction_FastCall(PyObject *func, PyObject **args, Py_ssize_t nargs);
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#define __Pyx_PyCFunction_FastCall(func, args, nargs) (assert(0), NULL)
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/* PyFunctionFastCall.proto */
#if CYTHON_FAST_PYCALL
#define __Pyx_PyFunction_FastCall(func, args, nargs)\
__Pyx_PyFunction_FastCallDict((func), (args), (nargs), NULL)
#if 1 || PY_VERSION_HEX < 0x030600B1
static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, int nargs, PyObject *kwargs);
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#define __Pyx_PyFunction_FastCallDict(func, args, nargs, kwargs) _PyFunction_FastCallDict(func, args, nargs, kwargs)
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/* PyObjectCall.proto */
#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw);
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#define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw)
#endif
/* PyObjectCallMethO.proto */
#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg);
#endif
/* PyObjectCallOneArg.proto */
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg);
/* GetItemInt.proto */
#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\
(__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\
__Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) :\
(is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) :\
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#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\
(__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\
__Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\
(PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL))
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
int wraparound, int boundscheck);
#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\
(__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\
__Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\
(PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL))
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
int wraparound, int boundscheck);
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j);
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i,
int is_list, int wraparound, int boundscheck);
/* BufferIndexError.proto */
static void __Pyx_RaiseBufferIndexError(int axis);
/* BufferFormatCheck.proto */
static CYTHON_INLINE int __Pyx_GetBufferAndValidate(Py_buffer* buf, PyObject* obj,
__Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack);
static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info);
static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts);
static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx,
__Pyx_BufFmt_StackElem* stack,
__Pyx_TypeInfo* type); // PROTO
/* MemviewSliceInit.proto */
#define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d
#define __Pyx_MEMVIEW_DIRECT 1
#define __Pyx_MEMVIEW_PTR 2
#define __Pyx_MEMVIEW_FULL 4
#define __Pyx_MEMVIEW_CONTIG 8
#define __Pyx_MEMVIEW_STRIDED 16
#define __Pyx_MEMVIEW_FOLLOW 32
#define __Pyx_IS_C_CONTIG 1
#define __Pyx_IS_F_CONTIG 2
static int __Pyx_init_memviewslice(
struct __pyx_memoryview_obj *memview,
int ndim,
__Pyx_memviewslice *memviewslice,
int memview_is_new_reference);
static CYTHON_INLINE int __pyx_add_acquisition_count_locked(
__pyx_atomic_int *acquisition_count, PyThread_type_lock lock);
static CYTHON_INLINE int __pyx_sub_acquisition_count_locked(
__pyx_atomic_int *acquisition_count, PyThread_type_lock lock);
#define __pyx_get_slice_count_pointer(memview) (memview->acquisition_count_aligned_p)
#define __pyx_get_slice_count(memview) (*__pyx_get_slice_count_pointer(memview))
#define __PYX_INC_MEMVIEW(slice, have_gil) __Pyx_INC_MEMVIEW(slice, have_gil, __LINE__)
#define __PYX_XDEC_MEMVIEW(slice, have_gil) __Pyx_XDEC_MEMVIEW(slice, have_gil, __LINE__)
static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *, int, int);
static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *, int, int);
/* BufferIndexErrorNogil.proto */
static void __Pyx_RaiseBufferIndexErrorNogil(int axis);
/* ForceInitThreads.proto */
#ifndef __PYX_FORCE_INIT_THREADS
#define __PYX_FORCE_INIT_THREADS 0
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/* PyThreadStateGet.proto */
#if CYTHON_FAST_THREAD_STATE
#define __Pyx_PyThreadState_declare PyThreadState *__pyx_tstate;
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#define __Pyx_PyThreadState_declare
#define __Pyx_PyThreadState_assign
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/* PyErrFetchRestore.proto */
#if CYTHON_FAST_THREAD_STATE
#define __Pyx_ErrRestoreWithState(type, value, tb) __Pyx_ErrRestoreInState(PyThreadState_GET(), type, value, tb)
#define __Pyx_ErrFetchWithState(type, value, tb) __Pyx_ErrFetchInState(PyThreadState_GET(), type, value, tb)
#define __Pyx_ErrRestore(type, value, tb) __Pyx_ErrRestoreInState(__pyx_tstate, type, value, tb)
#define __Pyx_ErrFetch(type, value, tb) __Pyx_ErrFetchInState(__pyx_tstate, type, value, tb)
static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb);
static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb);
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#define __Pyx_ErrRestoreWithState(type, value, tb) PyErr_Restore(type, value, tb)
#define __Pyx_ErrFetchWithState(type, value, tb) PyErr_Fetch(type, value, tb)
#define __Pyx_ErrRestore(type, value, tb) PyErr_Restore(type, value, tb)
#define __Pyx_ErrFetch(type, value, tb) PyErr_Fetch(type, value, tb)
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/* RaiseArgTupleInvalid.proto */
static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact,
Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found);
/* RaiseDoubleKeywords.proto */
static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name);
/* ParseKeywords.proto */
static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[],\
PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args,\
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/* PyIntBinop.proto */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyInt_EqObjC(PyObject *op1, PyObject *op2, long intval, int inplace);
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#define __Pyx_PyInt_EqObjC(op1, op2, intval, inplace)\
PyObject_RichCompare(op1, op2, Py_EQ)
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/* PyIntBinop.proto */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace);
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#define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace)\
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/* ListCompAppend.proto */
#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS
static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) {
PyListObject* L = (PyListObject*) list;
Py_ssize_t len = Py_SIZE(list);
if (likely(L->allocated > len)) {
Py_INCREF(x);
PyList_SET_ITEM(list, len, x);
Py_SIZE(list) = len+1;
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#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyInt_SubtractObjC(PyObject *op1, PyObject *op2, long intval, int inplace);
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#define __Pyx_SetItemInt(o, i, v, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\
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static CYTHON_INLINE int __Pyx_SetItemInt_Fast(PyObject *o, Py_ssize_t i, PyObject *v,
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static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause);
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static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func);
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/* RaiseTooManyValuesToUnpack.proto */
static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected);
/* RaiseNeedMoreValuesToUnpack.proto */
static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index);
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static CYTHON_INLINE int __Pyx_IterFinish(void);
/* UnpackItemEndCheck.proto */
static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected);
/* WriteUnraisableException.proto */
static void __Pyx_WriteUnraisable(const char *name, int clineno,
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static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed,
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/* IncludeStringH.proto */
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/* BytesEquals.proto */
static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals);
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#if PY_MAJOR_VERSION >= 3
#define __Pyx_PyString_Equals __Pyx_PyUnicode_Equals
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#define __Pyx_PyString_Equals __Pyx_PyBytes_Equals
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/* UnaryNegOverflows.proto */
#define UNARY_NEG_WOULD_OVERFLOW(x)\
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static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/
static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *); /*proto*/
/* GetAttr.proto */
static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *);
/* decode_c_string.proto */
static CYTHON_INLINE PyObject* __Pyx_decode_c_string(
const char* cstring, Py_ssize_t start, Py_ssize_t stop,
const char* encoding, const char* errors,
PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors));
/* RaiseNoneIterError.proto */
static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void);
/* ExtTypeTest.proto */
static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type);
/* SaveResetException.proto */
#if CYTHON_FAST_THREAD_STATE
#define __Pyx_ExceptionSave(type, value, tb) __Pyx__ExceptionSave(__pyx_tstate, type, value, tb)
static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb);
#define __Pyx_ExceptionReset(type, value, tb) __Pyx__ExceptionReset(__pyx_tstate, type, value, tb)
static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb);
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#define __Pyx_ExceptionSave(type, value, tb) PyErr_GetExcInfo(type, value, tb)
#define __Pyx_ExceptionReset(type, value, tb) PyErr_SetExcInfo(type, value, tb)
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#define __Pyx_PyErr_ExceptionMatches(err) __Pyx_PyErr_ExceptionMatchesInState(__pyx_tstate, err)
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#define __Pyx_PyErr_ExceptionMatches(err) PyErr_ExceptionMatches(err)
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/* GetException.proto */
#if CYTHON_FAST_THREAD_STATE
#define __Pyx_GetException(type, value, tb) __Pyx__GetException(__pyx_tstate, type, value, tb)
static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb);
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static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb);
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/* SwapException.proto */
#if CYTHON_FAST_THREAD_STATE
#define __Pyx_ExceptionSwap(type, value, tb) __Pyx__ExceptionSwap(__pyx_tstate, type, value, tb)
static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb);
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static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb);
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/* Import.proto */
static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level);
static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/
/* ListExtend.proto */
static CYTHON_INLINE int __Pyx_PyList_Extend(PyObject* L, PyObject* v) {
#if CYTHON_COMPILING_IN_CPYTHON
PyObject* none = _PyList_Extend((PyListObject*)L, v);
if (unlikely(!none))
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Py_DECREF(none);
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/* ListAppend.proto */
#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS
static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) {
PyListObject* L = (PyListObject*) list;
Py_ssize_t len = Py_SIZE(list);
if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) {
Py_INCREF(x);
PyList_SET_ITEM(list, len, x);
Py_SIZE(list) = len+1;
return 0;
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#define __Pyx_PyList_Append(L,x) PyList_Append(L,x)
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/* None.proto */
static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname);
/* None.proto */
static CYTHON_INLINE long __Pyx_div_long(long, long);
/* SetVTable.proto */
static int __Pyx_SetVtable(PyObject *dict, void *vtable);
/* ImportFrom.proto */
static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name);
/* CodeObjectCache.proto */
typedef struct {
PyCodeObject* code_object;
int code_line;
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struct __Pyx_CodeObjectCache {
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int max_count;
__Pyx_CodeObjectCacheEntry* entries;
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static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL};
static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line);
static PyCodeObject *__pyx_find_code_object(int code_line);
static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object);
/* AddTraceback.proto */
static void __Pyx_AddTraceback(const char *funcname, int c_line,
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static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags);
static void __Pyx_ReleaseBuffer(Py_buffer *view);
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#define __Pyx_GetBuffer PyObject_GetBuffer
#define __Pyx_ReleaseBuffer PyBuffer_Release
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/* BufferStructDeclare.proto */
typedef struct {
Py_ssize_t shape, strides, suboffsets;
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typedef struct {
size_t refcount;
Py_buffer pybuffer;
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typedef struct {
__Pyx_Buffer *rcbuffer;
char *data;
__Pyx_Buf_DimInfo diminfo[8];
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/* None.proto */
static Py_ssize_t __Pyx_zeros[] = {0, 0, 0, 0, 0, 0, 0, 0};
static Py_ssize_t __Pyx_minusones[] = {-1, -1, -1, -1, -1, -1, -1, -1};
/* MemviewSliceIsContig.proto */
static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs,
char order, int ndim);
/* OverlappingSlices.proto */
static int __pyx_slices_overlap(__Pyx_memviewslice *slice1,
__Pyx_memviewslice *slice2,
int ndim, size_t itemsize);
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static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value);
/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value);
/* MemviewDtypeToObject.proto */
static CYTHON_INLINE PyObject *__pyx_memview_get_double(const char *itemp);
static CYTHON_INLINE int __pyx_memview_set_double(const char *itemp, PyObject *obj);
/* MemviewSliceCopyTemplate.proto */
static __Pyx_memviewslice
__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs,
const char *mode, int ndim,
size_t sizeof_dtype, int contig_flag,
int dtype_is_object);
/* CIntFromPy.proto */
static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *);
/* CIntFromPy.proto */
static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *);
/* CIntFromPy.proto */
static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *);
/* TypeInfoCompare.proto */
static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b);
/* MemviewSliceValidateAndInit.proto */
static int __Pyx_ValidateAndInit_memviewslice(
int *axes_specs,
int c_or_f_flag,
int buf_flags,
int ndim,
__Pyx_TypeInfo *dtype,
__Pyx_BufFmt_StackElem stack[],
__Pyx_memviewslice *memviewslice,
PyObject *original_obj);
/* ObjectToMemviewSlice.proto */
static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_double(PyObject *);
/* ObjectToMemviewSlice.proto */
static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_long(PyObject *);
/* ObjectToMemviewSlice.proto */
static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_dc_double(PyObject *);
/* ObjectToMemviewSlice.proto */
static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_dc_long(PyObject *);
/* CheckBinaryVersion.proto */
static int __Pyx_check_binary_version(void);
/* InitStrings.proto */
static int __Pyx_InitStrings(__Pyx_StringTabEntry *t);
static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *__pyx_v_self); /* proto*/
static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/
static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/
static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/
static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/
static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/
static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/
static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/
static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/
static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/
/* Module declarations from 'openmp' */
/* Module declarations from 'enm_cython' */
static PyTypeObject *__pyx_array_type = 0;
static PyTypeObject *__pyx_MemviewEnum_type = 0;
static PyTypeObject *__pyx_memoryview_type = 0;
static PyTypeObject *__pyx_memoryviewslice_type = 0;
static PyObject *generic = 0;
static PyObject *strided = 0;
static PyObject *indirect = 0;
static PyObject *contiguous = 0;
static PyObject *indirect_contiguous = 0;
static int __pyx_memoryview_thread_locks_used;
static PyThread_type_lock __pyx_memoryview_thread_locks[8];
static double __pyx_f_10enm_cython_cfib(int); /*proto*/
static PyObject *__pyx_f_10enm_cython_c_array_f_multi(__Pyx_memviewslice); /*proto*/
static int __pyx_f_10enm_cython_c_sri_mc(__Pyx_memviewslice, __Pyx_memviewslice, __Pyx_memviewslice, double, double, double, int); /*proto*/
static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/
static void *__pyx_align_pointer(void *, size_t); /*proto*/
static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/
static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/
static PyObject *_unellipsify(PyObject *, int); /*proto*/
static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/
static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/
static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/
static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/
static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/
static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/
static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/
static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/
static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/
static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/
static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/
static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/
static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/
static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/
static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/
static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/
static int __pyx_memoryview_err(PyObject *, char *); /*proto*/
static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/
static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/
static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/
static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/
static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/
static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/
static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/
static __Pyx_TypeInfo __Pyx_TypeInfo_double = { "double", NULL, sizeof(double), { 0 }, 0, 'R', 0, 0 };
static __Pyx_TypeInfo __Pyx_TypeInfo_long = { "long", NULL, sizeof(long), { 0 }, 0, IS_UNSIGNED(long) ? 'U' : 'I', IS_UNSIGNED(long), 0 };
#define __Pyx_MODULE_NAME "enm_cython"
int __pyx_module_is_main_enm_cython = 0;
/* Implementation of 'enm_cython' */
static PyObject *__pyx_builtin_range;
static PyObject *__pyx_builtin_ValueError;
static PyObject *__pyx_builtin_MemoryError;
static PyObject *__pyx_builtin_enumerate;
static PyObject *__pyx_builtin_Ellipsis;
static PyObject *__pyx_builtin_TypeError;
static PyObject *__pyx_builtin_id;
static PyObject *__pyx_builtin_IndexError;
static const char __pyx_k_C[] = "C";
static const char __pyx_k_N[] = "N";
static const char __pyx_k_O[] = "O";
static const char __pyx_k_X[] = "X";
static const char __pyx_k_Y[] = "Y";
static const char __pyx_k_c[] = "c";
static const char __pyx_k_i[] = "i";
static const char __pyx_k_x[] = "x";
static const char __pyx_k_id[] = "id";
static const char __pyx_k_np[] = "np";
static const char __pyx_k_age[] = "age";
static const char __pyx_k_exp[] = "exp";
static const char __pyx_k_fib[] = "fib";
static const char __pyx_k_int[] = "int_";
static const char __pyx_k_obj[] = "obj";
static const char __pyx_k_sum[] = "sum";
static const char __pyx_k_axis[] = "axis";
static const char __pyx_k_base[] = "base";
static const char __pyx_k_main[] = "__main__";
static const char __pyx_k_math[] = "math";
static const char __pyx_k_mode[] = "mode";
static const char __pyx_k_name[] = "name";
static const char __pyx_k_ndim[] = "ndim";
static const char __pyx_k_ones[] = "ones";
static const char __pyx_k_pack[] = "pack";
static const char __pyx_k_size[] = "size";
static const char __pyx_k_step[] = "step";
static const char __pyx_k_stop[] = "stop";
static const char __pyx_k_test[] = "__test__";
static const char __pyx_k_ASCII[] = "ASCII";
static const char __pyx_k_array[] = "array";
static const char __pyx_k_class[] = "__class__";
static const char __pyx_k_dtype[] = "dtype";
static const char __pyx_k_error[] = "error";
static const char __pyx_k_flags[] = "flags";
static const char __pyx_k_index[] = "index";
static const char __pyx_k_numpy[] = "numpy";
static const char __pyx_k_order[] = "order";
static const char __pyx_k_range[] = "range";
static const char __pyx_k_shape[] = "shape";
static const char __pyx_k_start[] = "start";
static const char __pyx_k_zeros[] = "zeros";
static const char __pyx_k_encode[] = "encode";
static const char __pyx_k_format[] = "format";
static const char __pyx_k_import[] = "__import__";
static const char __pyx_k_name_2[] = "__name__";
static const char __pyx_k_random[] = "random";
static const char __pyx_k_struct[] = "struct";
static const char __pyx_k_unpack[] = "unpack";
static const char __pyx_k_vstack[] = "vstack";
static const char __pyx_k_array_f[] = "array_f";
static const char __pyx_k_fortran[] = "fortran";
static const char __pyx_k_memview[] = "memview";
static const char __pyx_k_nonzero[] = "nonzero";
static const char __pyx_k_num_its[] = "num_its";
static const char __pyx_k_Ellipsis[] = "Ellipsis";
static const char __pyx_k_itemsize[] = "itemsize";
static const char __pyx_k_TypeError[] = "TypeError";
static const char __pyx_k_c_array_f[] = "c_array_f";
static const char __pyx_k_enumerate[] = "enumerate";
static const char __pyx_k_transpose[] = "transpose";
static const char __pyx_k_IndexError[] = "IndexError";
static const char __pyx_k_ValueError[] = "ValueError";
static const char __pyx_k_enm_cython[] = "enm_cython";
static const char __pyx_k_num_people[] = "num_people";
static const char __pyx_k_pyx_vtable[] = "__pyx_vtable__";
static const char __pyx_k_MemoryError[] = "MemoryError";
static const char __pyx_k_init_distrib[] = "init_distrib";
static const char __pyx_k_num_infected[] = "num_infected";
static const char __pyx_k_num_recovered[] = "num_recovered";
static const char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer";
static const char __pyx_k_random_sample[] = "random_sample";
static const char __pyx_k_allocate_buffer[] = "allocate_buffer";
static const char __pyx_k_dtype_is_object[] = "dtype_is_object";
static const char __pyx_k_num_susceptible[] = "num_susceptible";
static const char __pyx_k_adjacency_matrix[] = "adjacency_matrix";
static const char __pyx_k_graph_attributes[] = "graph_attributes";
static const char __pyx_k_strided_and_direct[] = "<strided and direct>";
static const char __pyx_k_recovery_probability[] = "recovery_probability";
static const char __pyx_k_strided_and_indirect[] = "<strided and indirect>";
static const char __pyx_k_array_f_multi_wrapper[] = "array_f_multi_wrapper";
static const char __pyx_k_contiguous_and_direct[] = "<contiguous and direct>";
static const char __pyx_k_cython_wrapper_sri_mc[] = "cython_wrapper_sri_mc";
static const char __pyx_k_MemoryView_of_r_object[] = "<MemoryView of %r object>";
static const char __pyx_k_occupation_probability[] = "occupation_probability";
static const char __pyx_k_MemoryView_of_r_at_0x_x[] = "<MemoryView of %r at 0x%x>";
static const char __pyx_k_contiguous_and_indirect[] = "<contiguous and indirect>";
static const char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'";
static const char __pyx_k_transmission_probability[] = "transmission_probability";
static const char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d.";
static const char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array";
static const char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data.";
static const char __pyx_k_strided_and_direct_or_indirect[] = "<strided and direct or indirect>";
static const char __pyx_k_This_option_not_implemented_yet[] = "This option not implemented yet sorry!";
static const char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides";
static const char __pyx_k_C_Users_club084_Documents_Classe[] = "C:\\Users\\club084\\Documents\\Classes\\Fall 2016\\CHE_477\\repos\\epidemic_network_modelling\\epidemic_network_modelling\\enm_cython.pyx";
static const char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory.";
static const char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array";
static const char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported";
static const char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s";
static const char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)";
static const char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object";
static const char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)";
static const char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides.";
static PyObject *__pyx_n_s_ASCII;
static PyObject *__pyx_kp_s_Buffer_view_does_not_expose_stri;
static PyObject *__pyx_n_s_C;
static PyObject *__pyx_kp_s_C_Users_club084_Documents_Classe;
static PyObject *__pyx_kp_s_Can_only_create_a_buffer_that_is;
static PyObject *__pyx_kp_s_Cannot_index_with_type_s;
static PyObject *__pyx_n_s_Ellipsis;
static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr;
static PyObject *__pyx_n_s_IndexError;
static PyObject *__pyx_kp_s_Indirect_dimensions_not_supporte;
static PyObject *__pyx_kp_s_Invalid_mode_expected_c_or_fortr;
static PyObject *__pyx_kp_s_Invalid_shape_in_axis_d_d;
static PyObject *__pyx_n_s_MemoryError;
static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x;
static PyObject *__pyx_kp_s_MemoryView_of_r_object;
static PyObject *__pyx_n_s_N;
static PyObject *__pyx_n_b_O;
static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a;
static PyObject *__pyx_kp_s_This_option_not_implemented_yet;
static PyObject *__pyx_n_s_TypeError;
static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object;
static PyObject *__pyx_n_s_ValueError;
static PyObject *__pyx_n_s_X;
static PyObject *__pyx_n_s_Y;
static PyObject *__pyx_n_s_adjacency_matrix;
static PyObject *__pyx_n_s_age;
static PyObject *__pyx_n_s_allocate_buffer;
static PyObject *__pyx_n_s_array;
static PyObject *__pyx_n_s_array_f;
static PyObject *__pyx_n_s_array_f_multi_wrapper;
static PyObject *__pyx_n_s_axis;
static PyObject *__pyx_n_s_base;
static PyObject *__pyx_n_s_c;
static PyObject *__pyx_n_u_c;
static PyObject *__pyx_n_s_c_array_f;
static PyObject *__pyx_n_s_class;
static PyObject *__pyx_kp_s_contiguous_and_direct;
static PyObject *__pyx_kp_s_contiguous_and_indirect;
static PyObject *__pyx_n_s_cython_wrapper_sri_mc;
static PyObject *__pyx_n_s_dtype;
static PyObject *__pyx_n_s_dtype_is_object;
static PyObject *__pyx_n_s_encode;
static PyObject *__pyx_n_s_enm_cython;
static PyObject *__pyx_n_s_enumerate;
static PyObject *__pyx_n_s_error;
static PyObject *__pyx_n_s_exp;
static PyObject *__pyx_n_s_fib;
static PyObject *__pyx_n_s_flags;
static PyObject *__pyx_n_s_format;
static PyObject *__pyx_n_s_fortran;
static PyObject *__pyx_n_u_fortran;
static PyObject *__pyx_kp_s_got_differing_extents_in_dimensi;
static PyObject *__pyx_n_s_graph_attributes;
static PyObject *__pyx_n_s_i;
static PyObject *__pyx_n_s_id;
static PyObject *__pyx_n_s_import;
static PyObject *__pyx_n_s_index;
static PyObject *__pyx_n_s_init_distrib;
static PyObject *__pyx_n_s_int;
static PyObject *__pyx_n_s_itemsize;
static PyObject *__pyx_kp_s_itemsize_0_for_cython_array;
static PyObject *__pyx_n_s_main;
static PyObject *__pyx_n_s_math;
static PyObject *__pyx_n_s_memview;
static PyObject *__pyx_n_s_mode;
static PyObject *__pyx_n_s_name;
static PyObject *__pyx_n_s_name_2;
static PyObject *__pyx_n_s_ndim;
static PyObject *__pyx_n_s_nonzero;
static PyObject *__pyx_n_s_np;
static PyObject *__pyx_n_s_num_infected;
static PyObject *__pyx_n_s_num_its;
static PyObject *__pyx_n_s_num_people;
static PyObject *__pyx_n_s_num_recovered;
static PyObject *__pyx_n_s_num_susceptible;
static PyObject *__pyx_n_s_numpy;
static PyObject *__pyx_n_s_obj;
static PyObject *__pyx_n_s_occupation_probability;
static PyObject *__pyx_n_s_ones;
static PyObject *__pyx_n_s_order;
static PyObject *__pyx_n_s_pack;
static PyObject *__pyx_n_s_pyx_getbuffer;
static PyObject *__pyx_n_s_pyx_vtable;
static PyObject *__pyx_n_s_random;
static PyObject *__pyx_n_s_random_sample;
static PyObject *__pyx_n_s_range;
static PyObject *__pyx_n_s_recovery_probability;
static PyObject *__pyx_n_s_shape;
static PyObject *__pyx_n_s_size;
static PyObject *__pyx_n_s_start;
static PyObject *__pyx_n_s_step;
static PyObject *__pyx_n_s_stop;
static PyObject *__pyx_kp_s_strided_and_direct;
static PyObject *__pyx_kp_s_strided_and_direct_or_indirect;
static PyObject *__pyx_kp_s_strided_and_indirect;
static PyObject *__pyx_n_s_struct;
static PyObject *__pyx_n_s_sum;
static PyObject *__pyx_n_s_test;
static PyObject *__pyx_n_s_transmission_probability;
static PyObject *__pyx_n_s_transpose;
static PyObject *__pyx_kp_s_unable_to_allocate_array_data;
static PyObject *__pyx_kp_s_unable_to_allocate_shape_and_str;
static PyObject *__pyx_n_s_unpack;
static PyObject *__pyx_n_s_vstack;
static PyObject *__pyx_n_s_x;
static PyObject *__pyx_n_s_zeros;
static PyObject *__pyx_pf_10enm_cython_fib(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_x); /* proto */
static PyObject *__pyx_pf_10enm_cython_2array_f(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_X); /* proto */
static PyObject *__pyx_pf_10enm_cython_4c_array_f(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_X); /* proto */
static PyObject *__pyx_pf_10enm_cython_6array_f_multi_wrapper(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_Y); /* proto */
static PyObject *__pyx_pf_10enm_cython_8cython_wrapper_sri_mc(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_adjacency_matrix, PyObject *__pyx_v_age, PyObject *__pyx_v_transmission_probability, PyObject *__pyx_v_recovery_probability, PyObject *__pyx_v_occupation_probability, PyObject *__pyx_v_init_distrib, PyObject *__pyx_v_num_its); /* proto */
static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */
static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */
static void __pyx_array___pyx_pf_15View_dot_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */
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static Py_ssize_t abs_py_ssize_t(Py_ssize_t __pyx_v_arg) {
Py_ssize_t __pyx_r;
int __pyx_t_1;
/* "View.MemoryView":1093
*
* cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil:
* if arg < 0: # <<<<<<<<<<<<<<
* return -arg
* else:
*/
__pyx_t_1 = ((__pyx_v_arg < 0) != 0);
if (__pyx_t_1) {
/* "View.MemoryView":1094
* cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil:
* if arg < 0:
* return -arg # <<<<<<<<<<<<<<
* else:
* return arg
*/
__pyx_r = (-__pyx_v_arg);
goto __pyx_L0;
/* "View.MemoryView":1093
*
* cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil:
* if arg < 0: # <<<<<<<<<<<<<<
* return -arg
* else:
*/
}
/* "View.MemoryView":1096
* return -arg
* else:
* return arg # <<<<<<<<<<<<<<
*
* @cname('__pyx_get_best_slice_order')
*/
/*else*/ {
__pyx_r = __pyx_v_arg;
goto __pyx_L0;
}
/* "View.MemoryView":1092
*
*
* cdef Py_ssize_t abs_py_ssize_t(Py_ssize_t arg) nogil: # <<<<<<<<<<<<<<
* if arg < 0:
* return -arg
*/
/* function exit code */
__pyx_L0:;
return __pyx_r;
}
/* "View.MemoryView":1099
*
* @cname('__pyx_get_best_slice_order')
* cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<<
* """
* Figure out the best memory access order for a given slice.
*/
static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim) {
int __pyx_v_i;
Py_ssize_t __pyx_v_c_stride;
Py_ssize_t __pyx_v_f_stride;
char __pyx_r;
int __pyx_t_1;
int __pyx_t_2;
int __pyx_t_3;
/* "View.MemoryView":1104
* """
* cdef int i
* cdef Py_ssize_t c_stride = 0 # <<<<<<<<<<<<<<
* cdef Py_ssize_t f_stride = 0
*
*/
__pyx_v_c_stride = 0;
/* "View.MemoryView":1105
* cdef int i
* cdef Py_ssize_t c_stride = 0
* cdef Py_ssize_t f_stride = 0 # <<<<<<<<<<<<<<
*
* for i in range(ndim - 1, -1, -1):
*/
__pyx_v_f_stride = 0;
/* "View.MemoryView":1107
* cdef Py_ssize_t f_stride = 0
*
* for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<<
* if mslice.shape[i] > 1:
* c_stride = mslice.strides[i]
*/
for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1L; __pyx_t_1-=1) {
__pyx_v_i = __pyx_t_1;
/* "View.MemoryView":1108
*
* for i in range(ndim - 1, -1, -1):
* if mslice.shape[i] > 1: # <<<<<<<<<<<<<<
* c_stride = mslice.strides[i]
* break
*/
__pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":1109
* for i in range(ndim - 1, -1, -1):
* if mslice.shape[i] > 1:
* c_stride = mslice.strides[i] # <<<<<<<<<<<<<<
* break
*
*/
__pyx_v_c_stride = (__pyx_v_mslice->strides[__pyx_v_i]);
/* "View.MemoryView":1110
* if mslice.shape[i] > 1:
* c_stride = mslice.strides[i]
* break # <<<<<<<<<<<<<<
*
* for i in range(ndim):
*/
goto __pyx_L4_break;
/* "View.MemoryView":1108
*
* for i in range(ndim - 1, -1, -1):
* if mslice.shape[i] > 1: # <<<<<<<<<<<<<<
* c_stride = mslice.strides[i]
* break
*/
}
}
__pyx_L4_break:;
/* "View.MemoryView":1112
* break
*
* for i in range(ndim): # <<<<<<<<<<<<<<
* if mslice.shape[i] > 1:
* f_stride = mslice.strides[i]
*/
__pyx_t_1 = __pyx_v_ndim;
for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_1; __pyx_t_3+=1) {
__pyx_v_i = __pyx_t_3;
/* "View.MemoryView":1113
*
* for i in range(ndim):
* if mslice.shape[i] > 1: # <<<<<<<<<<<<<<
* f_stride = mslice.strides[i]
* break
*/
__pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":1114
* for i in range(ndim):
* if mslice.shape[i] > 1:
* f_stride = mslice.strides[i] # <<<<<<<<<<<<<<
* break
*
*/
__pyx_v_f_stride = (__pyx_v_mslice->strides[__pyx_v_i]);
/* "View.MemoryView":1115
* if mslice.shape[i] > 1:
* f_stride = mslice.strides[i]
* break # <<<<<<<<<<<<<<
*
* if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride):
*/
goto __pyx_L7_break;
/* "View.MemoryView":1113
*
* for i in range(ndim):
* if mslice.shape[i] > 1: # <<<<<<<<<<<<<<
* f_stride = mslice.strides[i]
* break
*/
}
}
__pyx_L7_break:;
/* "View.MemoryView":1117
* break
*
* if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<<
* return 'C'
* else:
*/
__pyx_t_2 = ((abs_py_ssize_t(__pyx_v_c_stride) <= abs_py_ssize_t(__pyx_v_f_stride)) != 0);
if (__pyx_t_2) {
/* "View.MemoryView":1118
*
* if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride):
* return 'C' # <<<<<<<<<<<<<<
* else:
* return 'F'
*/
__pyx_r = 'C';
goto __pyx_L0;
/* "View.MemoryView":1117
* break
*
* if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<<
* return 'C'
* else:
*/
}
/* "View.MemoryView":1120
* return 'C'
* else:
* return 'F' # <<<<<<<<<<<<<<
*
* @cython.cdivision(True)
*/
/*else*/ {
__pyx_r = 'F';
goto __pyx_L0;
}
/* "View.MemoryView":1099
*
* @cname('__pyx_get_best_slice_order')
* cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<<
* """
* Figure out the best memory access order for a given slice.
*/
/* function exit code */
__pyx_L0:;
return __pyx_r;
}
/* "View.MemoryView":1123
*
* @cython.cdivision(True)
* cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<<
* char *dst_data, Py_ssize_t *dst_strides,
* Py_ssize_t *src_shape, Py_ssize_t *dst_shape,
*/
static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v_src_strides, char *__pyx_v_dst_data, Py_ssize_t *__pyx_v_dst_strides, Py_ssize_t *__pyx_v_src_shape, Py_ssize_t *__pyx_v_dst_shape, int __pyx_v_ndim, size_t __pyx_v_itemsize) {
CYTHON_UNUSED Py_ssize_t __pyx_v_i;
CYTHON_UNUSED Py_ssize_t __pyx_v_src_extent;
Py_ssize_t __pyx_v_dst_extent;
Py_ssize_t __pyx_v_src_stride;
Py_ssize_t __pyx_v_dst_stride;
int __pyx_t_1;
int __pyx_t_2;
int __pyx_t_3;
Py_ssize_t __pyx_t_4;
Py_ssize_t __pyx_t_5;
/* "View.MemoryView":1130
*
* cdef Py_ssize_t i
* cdef Py_ssize_t src_extent = src_shape[0] # <<<<<<<<<<<<<<
* cdef Py_ssize_t dst_extent = dst_shape[0]
* cdef Py_ssize_t src_stride = src_strides[0]
*/
__pyx_v_src_extent = (__pyx_v_src_shape[0]);
/* "View.MemoryView":1131
* cdef Py_ssize_t i
* cdef Py_ssize_t src_extent = src_shape[0]
* cdef Py_ssize_t dst_extent = dst_shape[0] # <<<<<<<<<<<<<<
* cdef Py_ssize_t src_stride = src_strides[0]
* cdef Py_ssize_t dst_stride = dst_strides[0]
*/
__pyx_v_dst_extent = (__pyx_v_dst_shape[0]);
/* "View.MemoryView":1132
* cdef Py_ssize_t src_extent = src_shape[0]
* cdef Py_ssize_t dst_extent = dst_shape[0]
* cdef Py_ssize_t src_stride = src_strides[0] # <<<<<<<<<<<<<<
* cdef Py_ssize_t dst_stride = dst_strides[0]
*
*/
__pyx_v_src_stride = (__pyx_v_src_strides[0]);
/* "View.MemoryView":1133
* cdef Py_ssize_t dst_extent = dst_shape[0]
* cdef Py_ssize_t src_stride = src_strides[0]
* cdef Py_ssize_t dst_stride = dst_strides[0] # <<<<<<<<<<<<<<
*
* if ndim == 1:
*/
__pyx_v_dst_stride = (__pyx_v_dst_strides[0]);
/* "View.MemoryView":1135
* cdef Py_ssize_t dst_stride = dst_strides[0]
*
* if ndim == 1: # <<<<<<<<<<<<<<
* if (src_stride > 0 and dst_stride > 0 and
* <size_t> src_stride == itemsize == <size_t> dst_stride):
*/
__pyx_t_1 = ((__pyx_v_ndim == 1) != 0);
if (__pyx_t_1) {
/* "View.MemoryView":1136
*
* if ndim == 1:
* if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<<
* <size_t> src_stride == itemsize == <size_t> dst_stride):
* memcpy(dst_data, src_data, itemsize * dst_extent)
*/
__pyx_t_2 = ((__pyx_v_src_stride > 0) != 0);
if (__pyx_t_2) {
} else {
__pyx_t_1 = __pyx_t_2;
goto __pyx_L5_bool_binop_done;
}
__pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0);
if (__pyx_t_2) {
} else {
__pyx_t_1 = __pyx_t_2;
goto __pyx_L5_bool_binop_done;
}
/* "View.MemoryView":1137
* if ndim == 1:
* if (src_stride > 0 and dst_stride > 0 and
* <size_t> src_stride == itemsize == <size_t> dst_stride): # <<<<<<<<<<<<<<
* memcpy(dst_data, src_data, itemsize * dst_extent)
* else:
*/
__pyx_t_2 = (((size_t)__pyx_v_src_stride) == __pyx_v_itemsize);
if (__pyx_t_2) {
__pyx_t_2 = (__pyx_v_itemsize == ((size_t)__pyx_v_dst_stride));
}
__pyx_t_3 = (__pyx_t_2 != 0);
__pyx_t_1 = __pyx_t_3;
__pyx_L5_bool_binop_done:;
/* "View.MemoryView":1136
*
* if ndim == 1:
* if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<<
* <size_t> src_stride == itemsize == <size_t> dst_stride):
* memcpy(dst_data, src_data, itemsize * dst_extent)
*/
if (__pyx_t_1) {
/* "View.MemoryView":1138
* if (src_stride > 0 and dst_stride > 0 and
* <size_t> src_stride == itemsize == <size_t> dst_stride):
* memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<<
* else:
* for i in range(dst_extent):
*/
memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent));
/* "View.MemoryView":1136
*
* if ndim == 1:
* if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<<
* <size_t> src_stride == itemsize == <size_t> dst_stride):
* memcpy(dst_data, src_data, itemsize * dst_extent)
*/
goto __pyx_L4;
}
/* "View.MemoryView":1140
* memcpy(dst_data, src_data, itemsize * dst_extent)
* else:
* for i in range(dst_extent): # <<<<<<<<<<<<<<
* memcpy(dst_data, src_data, itemsize)
* src_data += src_stride
*/
/*else*/ {
__pyx_t_4 = __pyx_v_dst_extent;
for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) {
__pyx_v_i = __pyx_t_5;
/* "View.MemoryView":1141
* else:
* for i in range(dst_extent):
* memcpy(dst_data, src_data, itemsize) # <<<<<<<<<<<<<<
* src_data += src_stride
* dst_data += dst_stride
*/
memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize);
/* "View.MemoryView":1142
* for i in range(dst_extent):
* memcpy(dst_data, src_data, itemsize)
* src_data += src_stride # <<<<<<<<<<<<<<
* dst_data += dst_stride
* else:
*/
__pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride);
/* "View.MemoryView":1143
* memcpy(dst_data, src_data, itemsize)
* src_data += src_stride
* dst_data += dst_stride # <<<<<<<<<<<<<<
* else:
* for i in range(dst_extent):
*/
__pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride);
}
}
__pyx_L4:;
/* "View.MemoryView":1135
* cdef Py_ssize_t dst_stride = dst_strides[0]
*
* if ndim == 1: # <<<<<<<<<<<<<<
* if (src_stride > 0 and dst_stride > 0 and
* <size_t> src_stride == itemsize == <size_t> dst_stride):
*/
goto __pyx_L3;
}
/* "View.MemoryView":1145
* dst_data += dst_stride
* else:
* for i in range(dst_extent): # <<<<<<<<<<<<<<
* _copy_strided_to_strided(src_data, src_strides + 1,
* dst_data, dst_strides + 1,
*/
/*else*/ {
__pyx_t_4 = __pyx_v_dst_extent;
for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) {
__pyx_v_i = __pyx_t_5;
/* "View.MemoryView":1146
* else:
* for i in range(dst_extent):
* _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<<
* dst_data, dst_strides + 1,
* src_shape + 1, dst_shape + 1,
*/
_copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize);
/* "View.MemoryView":1150
* src_shape + 1, dst_shape + 1,
* ndim - 1, itemsize)
* src_data += src_stride # <<<<<<<<<<<<<<
* dst_data += dst_stride
*
*/
__pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride);
/* "View.MemoryView":1151
* ndim - 1, itemsize)
* src_data += src_stride
* dst_data += dst_stride # <<<<<<<<<<<<<<
*
* cdef void copy_strided_to_strided(__Pyx_memviewslice *src,
*/
__pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride);
}
}
__pyx_L3:;
/* "View.MemoryView":1123
*
* @cython.cdivision(True)
* cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<<
* char *dst_data, Py_ssize_t *dst_strides,
* Py_ssize_t *src_shape, Py_ssize_t *dst_shape,
*/
/* function exit code */
}
/* "View.MemoryView":1153
* dst_data += dst_stride
*
* cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<<
* __Pyx_memviewslice *dst,
* int ndim, size_t itemsize) nogil:
*/
static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize) {
/* "View.MemoryView":1156
* __Pyx_memviewslice *dst,
* int ndim, size_t itemsize) nogil:
* _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides, # <<<<<<<<<<<<<<
* src.shape, dst.shape, ndim, itemsize)
*
*/
_copy_strided_to_strided(__pyx_v_src->data, __pyx_v_src->strides, __pyx_v_dst->data, __pyx_v_dst->strides, __pyx_v_src->shape, __pyx_v_dst->shape, __pyx_v_ndim, __pyx_v_itemsize);
/* "View.MemoryView":1153
* dst_data += dst_stride
*
* cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<<
* __Pyx_memviewslice *dst,
* int ndim, size_t itemsize) nogil:
*/
/* function exit code */
}
/* "View.MemoryView":1160
*
* @cname('__pyx_memoryview_slice_get_size')
* cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<<
* "Return the size of the memory occupied by the slice in number of bytes"
* cdef int i
*/
static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_src, int __pyx_v_ndim) {
int __pyx_v_i;
Py_ssize_t __pyx_v_size;
Py_ssize_t __pyx_r;
Py_ssize_t __pyx_t_1;
int __pyx_t_2;
int __pyx_t_3;
/* "View.MemoryView":1163
* "Return the size of the memory occupied by the slice in number of bytes"
* cdef int i
* cdef Py_ssize_t size = src.memview.view.itemsize # <<<<<<<<<<<<<<
*
* for i in range(ndim):
*/
__pyx_t_1 = __pyx_v_src->memview->view.itemsize;
__pyx_v_size = __pyx_t_1;
/* "View.MemoryView":1165
* cdef Py_ssize_t size = src.memview.view.itemsize
*
* for i in range(ndim): # <<<<<<<<<<<<<<
* size *= src.shape[i]
*
*/
__pyx_t_2 = __pyx_v_ndim;
for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
__pyx_v_i = __pyx_t_3;
/* "View.MemoryView":1166
*
* for i in range(ndim):
* size *= src.shape[i] # <<<<<<<<<<<<<<
*
* return size
*/
__pyx_v_size = (__pyx_v_size * (__pyx_v_src->shape[__pyx_v_i]));
}
/* "View.MemoryView":1168
* size *= src.shape[i]
*
* return size # <<<<<<<<<<<<<<
*
* @cname('__pyx_fill_contig_strides_array')
*/
__pyx_r = __pyx_v_size;
goto __pyx_L0;
/* "View.MemoryView":1160
*
* @cname('__pyx_memoryview_slice_get_size')
* cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<<
* "Return the size of the memory occupied by the slice in number of bytes"
* cdef int i
*/
/* function exit code */
__pyx_L0:;
return __pyx_r;
}
/* "View.MemoryView":1171
*
* @cname('__pyx_fill_contig_strides_array')
* cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<<
* Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride,
* int ndim, char order) nogil:
*/
static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, Py_ssize_t __pyx_v_stride, int __pyx_v_ndim, char __pyx_v_order) {
int __pyx_v_idx;
Py_ssize_t __pyx_r;
int __pyx_t_1;
int __pyx_t_2;
int __pyx_t_3;
/* "View.MemoryView":1180
* cdef int idx
*
* if order == 'F': # <<<<<<<<<<<<<<
* for idx in range(ndim):
* strides[idx] = stride
*/
__pyx_t_1 = ((__pyx_v_order == 'F') != 0);
if (__pyx_t_1) {
/* "View.MemoryView":1181
*
* if order == 'F':
* for idx in range(ndim): # <<<<<<<<<<<<<<
* strides[idx] = stride
* stride = stride * shape[idx]
*/
__pyx_t_2 = __pyx_v_ndim;
for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
__pyx_v_idx = __pyx_t_3;
/* "View.MemoryView":1182
* if order == 'F':
* for idx in range(ndim):
* strides[idx] = stride # <<<<<<<<<<<<<<
* stride = stride * shape[idx]
* else:
*/
(__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride;
/* "View.MemoryView":1183
* for idx in range(ndim):
* strides[idx] = stride
* stride = stride * shape[idx] # <<<<<<<<<<<<<<
* else:
* for idx in range(ndim - 1, -1, -1):
*/
__pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx]));
}
/* "View.MemoryView":1180
* cdef int idx
*
* if order == 'F': # <<<<<<<<<<<<<<
* for idx in range(ndim):
* strides[idx] = stride
*/
goto __pyx_L3;
}
/* "View.MemoryView":1185
* stride = stride * shape[idx]
* else:
* for idx in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<<
* strides[idx] = stride
* stride = stride * shape[idx]
*/
/*else*/ {
for (__pyx_t_2 = (__pyx_v_ndim - 1); __pyx_t_2 > -1L; __pyx_t_2-=1) {
__pyx_v_idx = __pyx_t_2;
/* "View.MemoryView":1186
* else:
* for idx in range(ndim - 1, -1, -1):
* strides[idx] = stride # <<<<<<<<<<<<<<
* stride = stride * shape[idx]
*
*/
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*/
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void *__pyx_v_tmpdata;
size_t __pyx_v_itemsize;
int __pyx_v_i;
char __pyx_v_order;
int __pyx_v_broadcasting;
int __pyx_v_direct_copy;
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int __pyx_v_ndim;
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int __pyx_t_2;
int __pyx_t_3;
int __pyx_t_4;
int __pyx_t_5;
void *__pyx_t_6;
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* cdef int i
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/* "View.MemoryView":1261
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* cdef int i
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*/
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* cdef bint broadcasting = False
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* cdef __Pyx_memviewslice tmp
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* cdef __Pyx_memviewslice tmp
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* broadcast_leading(&src, src_ndim, dst_ndim)
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* for i in range(ndim):
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* _err_dim(ValueError, "Dimension %d is not direct", i)
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*/
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* _err_dim(ValueError, "Dimension %d is not direct", i)
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* free(tmpdata)
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* return 0
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*
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* refcount_copying(&dst, dtype_is_object, ndim, False)
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*
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*
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* refcount_copying(&dst, dtype_is_object, ndim, True)
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*/
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* free(tmpdata)
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/* "View.MemoryView":1320
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*
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*/
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/* "View.MemoryView":1321
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goto __pyx_L0;
/* "View.MemoryView":1252
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/* function exit code */
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int __pyx_v_offset;
int __pyx_t_1;
int __pyx_t_2;
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*/
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/* "View.MemoryView":1333
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/* "View.MemoryView":1346
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Py_INCREF((((PyObject **)__pyx_v_data)[0]));
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/* "View.MemoryView":1366
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goto __pyx_L5;
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/* "View.MemoryView":1372
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__pyx_memoryview_refcount_objects_in_slice(__pyx_v_data, (__pyx_v_shape + 1), (__pyx_v_strides + 1), (__pyx_v_ndim - 1), __pyx_v_inc);
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/* "View.MemoryView":1361
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/* function exit code */
__Pyx_RefNannyFinishContext();
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/* "View.MemoryView":1381
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* size_t itemsize, void *item,
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static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item, int __pyx_v_dtype_is_object) {
/* "View.MemoryView":1384
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* _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim,
* itemsize, item)
*/
__pyx_memoryview_refcount_copying(__pyx_v_dst, __pyx_v_dtype_is_object, __pyx_v_ndim, 0);
/* "View.MemoryView":1385
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*/
__pyx_memoryview__slice_assign_scalar(__pyx_v_dst->data, __pyx_v_dst->shape, __pyx_v_dst->strides, __pyx_v_ndim, __pyx_v_itemsize, __pyx_v_item);
/* "View.MemoryView":1387
* _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim,
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*
*/
__pyx_memoryview_refcount_copying(__pyx_v_dst, __pyx_v_dtype_is_object, __pyx_v_ndim, 1);
/* "View.MemoryView":1381
*
* @cname('__pyx_memoryview_slice_assign_scalar')
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* size_t itemsize, void *item,
* bint dtype_is_object) nogil:
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/* function exit code */
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/* "View.MemoryView":1391
*
* @cname('__pyx_memoryview__slice_assign_scalar')
* cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape, # <<<<<<<<<<<<<<
* Py_ssize_t *strides, int ndim,
* size_t itemsize, void *item) nogil:
*/
static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, int __pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item) {
CYTHON_UNUSED Py_ssize_t __pyx_v_i;
Py_ssize_t __pyx_v_stride;
Py_ssize_t __pyx_v_extent;
int __pyx_t_1;
Py_ssize_t __pyx_t_2;
Py_ssize_t __pyx_t_3;
/* "View.MemoryView":1395
* size_t itemsize, void *item) nogil:
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*/
__pyx_v_stride = (__pyx_v_strides[0]);
/* "View.MemoryView":1396
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__pyx_v_extent = (__pyx_v_shape[0]);
/* "View.MemoryView":1398
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__pyx_t_1 = ((__pyx_v_ndim == 1) != 0);
if (__pyx_t_1) {
/* "View.MemoryView":1399
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__pyx_t_2 = __pyx_v_extent;
for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
__pyx_v_i = __pyx_t_3;
/* "View.MemoryView":1400
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memcpy(__pyx_v_data, __pyx_v_item, __pyx_v_itemsize);
/* "View.MemoryView":1401
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__pyx_v_data = (__pyx_v_data + __pyx_v_stride);
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/* "View.MemoryView":1398
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goto __pyx_L3;
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/* "View.MemoryView":1403
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/*else*/ {
__pyx_t_2 = __pyx_v_extent;
for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
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/* "View.MemoryView":1404
* else:
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__pyx_memoryview__slice_assign_scalar(__pyx_v_data, (__pyx_v_shape + 1), (__pyx_v_strides + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize, __pyx_v_item);
/* "View.MemoryView":1406
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/* "View.MemoryView":1391
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{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_array[] = {
{(char *)"memview", __pyx_getprop___pyx_array_memview, 0, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PySequenceMethods __pyx_tp_as_sequence_array = {
0, /*sq_length*/
0, /*sq_concat*/
0, /*sq_repeat*/
__pyx_sq_item_array, /*sq_item*/
0, /*sq_slice*/
0, /*sq_ass_item*/
0, /*sq_ass_slice*/
0, /*sq_contains*/
0, /*sq_inplace_concat*/
0, /*sq_inplace_repeat*/
};
static PyMappingMethods __pyx_tp_as_mapping_array = {
0, /*mp_length*/
__pyx_array___getitem__, /*mp_subscript*/
__pyx_mp_ass_subscript_array, /*mp_ass_subscript*/
};
static PyBufferProcs __pyx_tp_as_buffer_array = {
#if PY_MAJOR_VERSION < 3
0, /*bf_getreadbuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getwritebuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getsegcount*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getcharbuffer*/
#endif
__pyx_array_getbuffer, /*bf_getbuffer*/
0, /*bf_releasebuffer*/
};
static PyTypeObject __pyx_type___pyx_array = {
PyVarObject_HEAD_INIT(0, 0)
"enm_cython.array", /*tp_name*/
sizeof(struct __pyx_array_obj), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_array, /*tp_dealloc*/
0, /*tp_print*/
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
0, /*tp_repr*/
0, /*tp_as_number*/
&__pyx_tp_as_sequence_array, /*tp_as_sequence*/
&__pyx_tp_as_mapping_array, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
__pyx_tp_getattro_array, /*tp_getattro*/
0, /*tp_setattro*/
&__pyx_tp_as_buffer_array, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
0, /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_array, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_array, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_array, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
};
static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_MemviewEnum_obj *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_MemviewEnum_obj *)o);
p->name = Py_None; Py_INCREF(Py_None);
return o;
}
static void __pyx_tp_dealloc_Enum(PyObject *o) {
struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
#if PY_VERSION_HEX >= 0x030400a1
if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
Py_CLEAR(p->name);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_Enum(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
if (p->name) {
e = (*v)(p->name, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_Enum(PyObject *o) {
PyObject* tmp;
struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o;
tmp = ((PyObject*)p->name);
p->name = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
return 0;
}
static PyMethodDef __pyx_methods_Enum[] = {
{0, 0, 0, 0}
};
static PyTypeObject __pyx_type___pyx_MemviewEnum = {
PyVarObject_HEAD_INIT(0, 0)
"enm_cython.Enum", /*tp_name*/
sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_Enum, /*tp_dealloc*/
0, /*tp_print*/
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
__pyx_MemviewEnum___repr__, /*tp_repr*/
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_Enum, /*tp_traverse*/
__pyx_tp_clear_Enum, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_Enum, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
__pyx_MemviewEnum___init__, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_Enum, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
};
static struct __pyx_vtabstruct_memoryview __pyx_vtable_memoryview;
static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_memoryview_obj *p;
PyObject *o;
if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) {
o = (*t->tp_alloc)(t, 0);
} else {
o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0);
}
if (unlikely(!o)) return 0;
p = ((struct __pyx_memoryview_obj *)o);
p->__pyx_vtab = __pyx_vtabptr_memoryview;
p->obj = Py_None; Py_INCREF(Py_None);
p->_size = Py_None; Py_INCREF(Py_None);
p->_array_interface = Py_None; Py_INCREF(Py_None);
p->view.obj = NULL;
if (unlikely(__pyx_memoryview___cinit__(o, a, k) < 0)) goto bad;
return o;
bad:
Py_DECREF(o); o = 0;
return NULL;
}
static void __pyx_tp_dealloc_memoryview(PyObject *o) {
struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
#if PY_VERSION_HEX >= 0x030400a1
if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
{
PyObject *etype, *eval, *etb;
PyErr_Fetch(&etype, &eval, &etb);
++Py_REFCNT(o);
__pyx_memoryview___dealloc__(o);
--Py_REFCNT(o);
PyErr_Restore(etype, eval, etb);
}
Py_CLEAR(p->obj);
Py_CLEAR(p->_size);
Py_CLEAR(p->_array_interface);
(*Py_TYPE(o)->tp_free)(o);
}
static int __pyx_tp_traverse_memoryview(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
if (p->obj) {
e = (*v)(p->obj, a); if (e) return e;
}
if (p->_size) {
e = (*v)(p->_size, a); if (e) return e;
}
if (p->_array_interface) {
e = (*v)(p->_array_interface, a); if (e) return e;
}
if (p->view.obj) {
e = (*v)(p->view.obj, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear_memoryview(PyObject *o) {
PyObject* tmp;
struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o;
tmp = ((PyObject*)p->obj);
p->obj = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
tmp = ((PyObject*)p->_size);
p->_size = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
tmp = ((PyObject*)p->_array_interface);
p->_array_interface = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
Py_CLEAR(p->view.obj);
return 0;
}
static PyObject *__pyx_sq_item_memoryview(PyObject *o, Py_ssize_t i) {
PyObject *r;
PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0;
r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x);
Py_DECREF(x);
return r;
}
static int __pyx_mp_ass_subscript_memoryview(PyObject *o, PyObject *i, PyObject *v) {
if (v) {
return __pyx_memoryview___setitem__(o, i, v);
}
else {
PyErr_Format(PyExc_NotImplementedError,
"Subscript deletion not supported by %.200s", Py_TYPE(o)->tp_name);
return -1;
}
}
static PyObject *__pyx_getprop___pyx_memoryview_T(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_10memoryview_1T_1__get__(o);
}
static PyObject *__pyx_getprop___pyx_memoryview_base(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_10memoryview_4base_1__get__(o);
}
static PyObject *__pyx_getprop___pyx_memoryview_shape(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_10memoryview_5shape_1__get__(o);
}
static PyObject *__pyx_getprop___pyx_memoryview_strides(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_10memoryview_7strides_1__get__(o);
}
static PyObject *__pyx_getprop___pyx_memoryview_suboffsets(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_10memoryview_10suboffsets_1__get__(o);
}
static PyObject *__pyx_getprop___pyx_memoryview_ndim(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_10memoryview_4ndim_1__get__(o);
}
static PyObject *__pyx_getprop___pyx_memoryview_itemsize(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_10memoryview_8itemsize_1__get__(o);
}
static PyObject *__pyx_getprop___pyx_memoryview_nbytes(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_10memoryview_6nbytes_1__get__(o);
}
static PyObject *__pyx_getprop___pyx_memoryview_size(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_10memoryview_4size_1__get__(o);
}
static PyMethodDef __pyx_methods_memoryview[] = {
{"is_c_contig", (PyCFunction)__pyx_memoryview_is_c_contig, METH_NOARGS, 0},
{"is_f_contig", (PyCFunction)__pyx_memoryview_is_f_contig, METH_NOARGS, 0},
{"copy", (PyCFunction)__pyx_memoryview_copy, METH_NOARGS, 0},
{"copy_fortran", (PyCFunction)__pyx_memoryview_copy_fortran, METH_NOARGS, 0},
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets_memoryview[] = {
{(char *)"T", __pyx_getprop___pyx_memoryview_T, 0, (char *)0, 0},
{(char *)"base", __pyx_getprop___pyx_memoryview_base, 0, (char *)0, 0},
{(char *)"shape", __pyx_getprop___pyx_memoryview_shape, 0, (char *)0, 0},
{(char *)"strides", __pyx_getprop___pyx_memoryview_strides, 0, (char *)0, 0},
{(char *)"suboffsets", __pyx_getprop___pyx_memoryview_suboffsets, 0, (char *)0, 0},
{(char *)"ndim", __pyx_getprop___pyx_memoryview_ndim, 0, (char *)0, 0},
{(char *)"itemsize", __pyx_getprop___pyx_memoryview_itemsize, 0, (char *)0, 0},
{(char *)"nbytes", __pyx_getprop___pyx_memoryview_nbytes, 0, (char *)0, 0},
{(char *)"size", __pyx_getprop___pyx_memoryview_size, 0, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PySequenceMethods __pyx_tp_as_sequence_memoryview = {
__pyx_memoryview___len__, /*sq_length*/
0, /*sq_concat*/
0, /*sq_repeat*/
__pyx_sq_item_memoryview, /*sq_item*/
0, /*sq_slice*/
0, /*sq_ass_item*/
0, /*sq_ass_slice*/
0, /*sq_contains*/
0, /*sq_inplace_concat*/
0, /*sq_inplace_repeat*/
};
static PyMappingMethods __pyx_tp_as_mapping_memoryview = {
__pyx_memoryview___len__, /*mp_length*/
__pyx_memoryview___getitem__, /*mp_subscript*/
__pyx_mp_ass_subscript_memoryview, /*mp_ass_subscript*/
};
static PyBufferProcs __pyx_tp_as_buffer_memoryview = {
#if PY_MAJOR_VERSION < 3
0, /*bf_getreadbuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getwritebuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getsegcount*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getcharbuffer*/
#endif
__pyx_memoryview_getbuffer, /*bf_getbuffer*/
0, /*bf_releasebuffer*/
};
static PyTypeObject __pyx_type___pyx_memoryview = {
PyVarObject_HEAD_INIT(0, 0)
"enm_cython.memoryview", /*tp_name*/
sizeof(struct __pyx_memoryview_obj), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_memoryview, /*tp_dealloc*/
0, /*tp_print*/
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
__pyx_memoryview___repr__, /*tp_repr*/
0, /*tp_as_number*/
&__pyx_tp_as_sequence_memoryview, /*tp_as_sequence*/
&__pyx_tp_as_mapping_memoryview, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
__pyx_memoryview___str__, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
&__pyx_tp_as_buffer_memoryview, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
0, /*tp_doc*/
__pyx_tp_traverse_memoryview, /*tp_traverse*/
__pyx_tp_clear_memoryview, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_memoryview, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets_memoryview, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_memoryview, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
};
static struct __pyx_vtabstruct__memoryviewslice __pyx_vtable__memoryviewslice;
static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_memoryviewslice_obj *p;
PyObject *o = __pyx_tp_new_memoryview(t, a, k);
if (unlikely(!o)) return 0;
p = ((struct __pyx_memoryviewslice_obj *)o);
p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_memoryview*)__pyx_vtabptr__memoryviewslice;
p->from_object = Py_None; Py_INCREF(Py_None);
p->from_slice.memview = NULL;
return o;
}
static void __pyx_tp_dealloc__memoryviewslice(PyObject *o) {
struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
#if PY_VERSION_HEX >= 0x030400a1
if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
if (PyObject_CallFinalizerFromDealloc(o)) return;
}
#endif
PyObject_GC_UnTrack(o);
{
PyObject *etype, *eval, *etb;
PyErr_Fetch(&etype, &eval, &etb);
++Py_REFCNT(o);
__pyx_memoryviewslice___dealloc__(o);
--Py_REFCNT(o);
PyErr_Restore(etype, eval, etb);
}
Py_CLEAR(p->from_object);
PyObject_GC_Track(o);
__pyx_tp_dealloc_memoryview(o);
}
static int __pyx_tp_traverse__memoryviewslice(PyObject *o, visitproc v, void *a) {
int e;
struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
e = __pyx_tp_traverse_memoryview(o, v, a); if (e) return e;
if (p->from_object) {
e = (*v)(p->from_object, a); if (e) return e;
}
return 0;
}
static int __pyx_tp_clear__memoryviewslice(PyObject *o) {
PyObject* tmp;
struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
__pyx_tp_clear_memoryview(o);
tmp = ((PyObject*)p->from_object);
p->from_object = Py_None; Py_INCREF(Py_None);
Py_XDECREF(tmp);
__PYX_XDEC_MEMVIEW(&p->from_slice, 1);
return 0;
}
static PyObject *__pyx_getprop___pyx_memoryviewslice_base(PyObject *o, CYTHON_UNUSED void *x) {
return __pyx_pw_15View_dot_MemoryView_16_memoryviewslice_4base_1__get__(o);
}
static PyMethodDef __pyx_methods__memoryviewslice[] = {
{0, 0, 0, 0}
};
static struct PyGetSetDef __pyx_getsets__memoryviewslice[] = {
{(char *)"base", __pyx_getprop___pyx_memoryviewslice_base, 0, (char *)0, 0},
{0, 0, 0, 0, 0}
};
static PyTypeObject __pyx_type___pyx_memoryviewslice = {
PyVarObject_HEAD_INIT(0, 0)
"enm_cython._memoryviewslice", /*tp_name*/
sizeof(struct __pyx_memoryviewslice_obj), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc__memoryviewslice, /*tp_dealloc*/
0, /*tp_print*/
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#endif
#if PY_MAJOR_VERSION >= 3
0, /*tp_as_async*/
#endif
#if CYTHON_COMPILING_IN_PYPY
__pyx_memoryview___repr__, /*tp_repr*/
#else
0, /*tp_repr*/
#endif
0, /*tp_as_number*/
0, /*tp_as_sequence*/
0, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
#if CYTHON_COMPILING_IN_PYPY
__pyx_memoryview___str__, /*tp_str*/
#else
0, /*tp_str*/
#endif
0, /*tp_getattro*/
0, /*tp_setattro*/
0, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
"Internal class for passing memoryview slices to Python", /*tp_doc*/
__pyx_tp_traverse__memoryviewslice, /*tp_traverse*/
__pyx_tp_clear__memoryviewslice, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods__memoryviewslice, /*tp_methods*/
0, /*tp_members*/
__pyx_getsets__memoryviewslice, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new__memoryviewslice, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
0, /*tp_version_tag*/
#if PY_VERSION_HEX >= 0x030400a1
0, /*tp_finalize*/
#endif
};
static PyMethodDef __pyx_methods[] = {
{0, 0, 0, 0}
};
#if PY_MAJOR_VERSION >= 3
static struct PyModuleDef __pyx_moduledef = {
#if PY_VERSION_HEX < 0x03020000
{ PyObject_HEAD_INIT(NULL) NULL, 0, NULL },
#else
PyModuleDef_HEAD_INIT,
#endif
"enm_cython",
0, /* m_doc */
-1, /* m_size */
__pyx_methods /* m_methods */,
NULL, /* m_reload */
NULL, /* m_traverse */
NULL, /* m_clear */
NULL /* m_free */
};
#endif
static __Pyx_StringTabEntry __pyx_string_tab[] = {
{&__pyx_n_s_ASCII, __pyx_k_ASCII, sizeof(__pyx_k_ASCII), 0, 0, 1, 1},
{&__pyx_kp_s_Buffer_view_does_not_expose_stri, __pyx_k_Buffer_view_does_not_expose_stri, sizeof(__pyx_k_Buffer_view_does_not_expose_stri), 0, 0, 1, 0},
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int count;
const char* t = *ts;
if (*t < '0' || *t > '9') {
return -1;
} else {
count = *t++ - '0';
while (*t >= '0' && *t < '9') {
count *= 10;
count += *t++ - '0';
}
}
*ts = t;
return count;
}
static int __Pyx_BufFmt_ExpectNumber(const char **ts) {
int number = __Pyx_BufFmt_ParseNumber(ts);
if (number == -1)
PyErr_Format(PyExc_ValueError,\
"Does not understand character buffer dtype format string ('%c')", **ts);
return number;
}
static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) {
PyErr_Format(PyExc_ValueError,
"Unexpected format string character: '%c'", ch);
}
static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) {
switch (ch) {
case 'c': return "'char'";
case 'b': return "'signed char'";
case 'B': return "'unsigned char'";
case 'h': return "'short'";
case 'H': return "'unsigned short'";
case 'i': return "'int'";
case 'I': return "'unsigned int'";
case 'l': return "'long'";
case 'L': return "'unsigned long'";
case 'q': return "'long long'";
case 'Q': return "'unsigned long long'";
case 'f': return (is_complex ? "'complex float'" : "'float'");
case 'd': return (is_complex ? "'complex double'" : "'double'");
case 'g': return (is_complex ? "'complex long double'" : "'long double'");
case 'T': return "a struct";
case 'O': return "Python object";
case 'P': return "a pointer";
case 's': case 'p': return "a string";
case 0: return "end";
default: return "unparseable format string";
}
}
static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) {
switch (ch) {
case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
case 'h': case 'H': return 2;
case 'i': case 'I': case 'l': case 'L': return 4;
case 'q': case 'Q': return 8;
case 'f': return (is_complex ? 8 : 4);
case 'd': return (is_complex ? 16 : 8);
case 'g': {
PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g')..");
return 0;
}
case 'O': case 'P': return sizeof(void*);
default:
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) {
switch (ch) {
case 'c': case 'b': case 'B': case 's': case 'p': return 1;
case 'h': case 'H': return sizeof(short);
case 'i': case 'I': return sizeof(int);
case 'l': case 'L': return sizeof(long);
#ifdef HAVE_LONG_LONG
case 'q': case 'Q': return sizeof(PY_LONG_LONG);
#endif
case 'f': return sizeof(float) * (is_complex ? 2 : 1);
case 'd': return sizeof(double) * (is_complex ? 2 : 1);
case 'g': return sizeof(long double) * (is_complex ? 2 : 1);
case 'O': case 'P': return sizeof(void*);
default: {
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
}
typedef struct { char c; short x; } __Pyx_st_short;
typedef struct { char c; int x; } __Pyx_st_int;
typedef struct { char c; long x; } __Pyx_st_long;
typedef struct { char c; float x; } __Pyx_st_float;
typedef struct { char c; double x; } __Pyx_st_double;
typedef struct { char c; long double x; } __Pyx_st_longdouble;
typedef struct { char c; void *x; } __Pyx_st_void_p;
#ifdef HAVE_LONG_LONG
typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong;
#endif
static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) {
switch (ch) {
case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short);
case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int);
case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long);
#ifdef HAVE_LONG_LONG
case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG);
#endif
case 'f': return sizeof(__Pyx_st_float) - sizeof(float);
case 'd': return sizeof(__Pyx_st_double) - sizeof(double);
case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double);
case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*);
default:
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
/* These are for computing the padding at the end of the struct to align
on the first member of the struct. This will probably the same as above,
but we don't have any guarantees.
*/
typedef struct { short x; char c; } __Pyx_pad_short;
typedef struct { int x; char c; } __Pyx_pad_int;
typedef struct { long x; char c; } __Pyx_pad_long;
typedef struct { float x; char c; } __Pyx_pad_float;
typedef struct { double x; char c; } __Pyx_pad_double;
typedef struct { long double x; char c; } __Pyx_pad_longdouble;
typedef struct { void *x; char c; } __Pyx_pad_void_p;
#ifdef HAVE_LONG_LONG
typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong;
#endif
static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) {
switch (ch) {
case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short);
case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int);
case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long);
#ifdef HAVE_LONG_LONG
case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG);
#endif
case 'f': return sizeof(__Pyx_pad_float) - sizeof(float);
case 'd': return sizeof(__Pyx_pad_double) - sizeof(double);
case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double);
case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*);
default:
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) {
switch (ch) {
case 'c':
return 'H';
case 'b': case 'h': case 'i':
case 'l': case 'q': case 's': case 'p':
return 'I';
case 'B': case 'H': case 'I': case 'L': case 'Q':
return 'U';
case 'f': case 'd': case 'g':
return (is_complex ? 'C' : 'R');
case 'O':
return 'O';
case 'P':
return 'P';
default: {
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
}
static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) {
if (ctx->head == NULL || ctx->head->field == &ctx->root) {
const char* expected;
const char* quote;
if (ctx->head == NULL) {
expected = "end";
quote = "";
} else {
expected = ctx->head->field->type->name;
quote = "'";
}
PyErr_Format(PyExc_ValueError,
"Buffer dtype mismatch, expected %s%s%s but got %s",
quote, expected, quote,
__Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex));
} else {
__Pyx_StructField* field = ctx->head->field;
__Pyx_StructField* parent = (ctx->head - 1)->field;
PyErr_Format(PyExc_ValueError,
"Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'",
field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex),
parent->type->name, field->name);
}
}
static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) {
char group;
size_t size, offset, arraysize = 1;
if (ctx->enc_type == 0) return 0;
if (ctx->head->field->type->arraysize[0]) {
int i, ndim = 0;
if (ctx->enc_type == 's' || ctx->enc_type == 'p') {
ctx->is_valid_array = ctx->head->field->type->ndim == 1;
ndim = 1;
if (ctx->enc_count != ctx->head->field->type->arraysize[0]) {
PyErr_Format(PyExc_ValueError,
"Expected a dimension of size %zu, got %zu",
ctx->head->field->type->arraysize[0], ctx->enc_count);
return -1;
}
}
if (!ctx->is_valid_array) {
PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d",
ctx->head->field->type->ndim, ndim);
return -1;
}
for (i = 0; i < ctx->head->field->type->ndim; i++) {
arraysize *= ctx->head->field->type->arraysize[i];
}
ctx->is_valid_array = 0;
ctx->enc_count = 1;
}
group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex);
do {
__Pyx_StructField* field = ctx->head->field;
__Pyx_TypeInfo* type = field->type;
if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') {
size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex);
} else {
size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex);
}
if (ctx->enc_packmode == '@') {
size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex);
size_t align_mod_offset;
if (align_at == 0) return -1;
align_mod_offset = ctx->fmt_offset % align_at;
if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset;
if (ctx->struct_alignment == 0)
ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type,
ctx->is_complex);
}
if (type->size != size || type->typegroup != group) {
if (type->typegroup == 'C' && type->fields != NULL) {
size_t parent_offset = ctx->head->parent_offset + field->offset;
++ctx->head;
ctx->head->field = type->fields;
ctx->head->parent_offset = parent_offset;
continue;
}
if ((type->typegroup == 'H' || group == 'H') && type->size == size) {
} else {
__Pyx_BufFmt_RaiseExpected(ctx);
return -1;
}
}
offset = ctx->head->parent_offset + field->offset;
if (ctx->fmt_offset != offset) {
PyErr_Format(PyExc_ValueError,
"Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected",
(Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset);
return -1;
}
ctx->fmt_offset += size;
if (arraysize)
ctx->fmt_offset += (arraysize - 1) * size;
--ctx->enc_count;
while (1) {
if (field == &ctx->root) {
ctx->head = NULL;
if (ctx->enc_count != 0) {
__Pyx_BufFmt_RaiseExpected(ctx);
return -1;
}
break;
}
ctx->head->field = ++field;
if (field->type == NULL) {
--ctx->head;
field = ctx->head->field;
continue;
} else if (field->type->typegroup == 'S') {
size_t parent_offset = ctx->head->parent_offset + field->offset;
if (field->type->fields->type == NULL) continue;
field = field->type->fields;
++ctx->head;
ctx->head->field = field;
ctx->head->parent_offset = parent_offset;
break;
} else {
break;
}
}
} while (ctx->enc_count);
ctx->enc_type = 0;
ctx->is_complex = 0;
return 0;
}
static CYTHON_INLINE PyObject *
__pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp)
{
const char *ts = *tsp;
int i = 0, number;
int ndim = ctx->head->field->type->ndim;
;
++ts;
if (ctx->new_count != 1) {
PyErr_SetString(PyExc_ValueError,
"Cannot handle repeated arrays in format string");
return NULL;
}
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
while (*ts && *ts != ')') {
switch (*ts) {
case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue;
default: break;
}
number = __Pyx_BufFmt_ExpectNumber(&ts);
if (number == -1) return NULL;
if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i])
return PyErr_Format(PyExc_ValueError,
"Expected a dimension of size %zu, got %d",
ctx->head->field->type->arraysize[i], number);
if (*ts != ',' && *ts != ')')
return PyErr_Format(PyExc_ValueError,
"Expected a comma in format string, got '%c'", *ts);
if (*ts == ',') ts++;
i++;
}
if (i != ndim)
return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d",
ctx->head->field->type->ndim, i);
if (!*ts) {
PyErr_SetString(PyExc_ValueError,
"Unexpected end of format string, expected ')'");
return NULL;
}
ctx->is_valid_array = 1;
ctx->new_count = 1;
*tsp = ++ts;
return Py_None;
}
static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) {
int got_Z = 0;
while (1) {
switch(*ts) {
case 0:
if (ctx->enc_type != 0 && ctx->head == NULL) {
__Pyx_BufFmt_RaiseExpected(ctx);
return NULL;
}
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
if (ctx->head != NULL) {
__Pyx_BufFmt_RaiseExpected(ctx);
return NULL;
}
return ts;
case ' ':
case '\r':
case '\n':
++ts;
break;
case '<':
if (!__Pyx_IsLittleEndian()) {
PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler");
return NULL;
}
ctx->new_packmode = '=';
++ts;
break;
case '>':
case '!':
if (__Pyx_IsLittleEndian()) {
PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler");
return NULL;
}
ctx->new_packmode = '=';
++ts;
break;
case '=':
case '@':
case '^':
ctx->new_packmode = *ts++;
break;
case 'T':
{
const char* ts_after_sub;
size_t i, struct_count = ctx->new_count;
size_t struct_alignment = ctx->struct_alignment;
ctx->new_count = 1;
++ts;
if (*ts != '{') {
PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'");
return NULL;
}
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
ctx->enc_type = 0;
ctx->enc_count = 0;
ctx->struct_alignment = 0;
++ts;
ts_after_sub = ts;
for (i = 0; i != struct_count; ++i) {
ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts);
if (!ts_after_sub) return NULL;
}
ts = ts_after_sub;
if (struct_alignment) ctx->struct_alignment = struct_alignment;
}
break;
case '}':
{
size_t alignment = ctx->struct_alignment;
++ts;
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
ctx->enc_type = 0;
if (alignment && ctx->fmt_offset % alignment) {
ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment);
}
}
return ts;
case 'x':
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
ctx->fmt_offset += ctx->new_count;
ctx->new_count = 1;
ctx->enc_count = 0;
ctx->enc_type = 0;
ctx->enc_packmode = ctx->new_packmode;
++ts;
break;
case 'Z':
got_Z = 1;
++ts;
if (*ts != 'f' && *ts != 'd' && *ts != 'g') {
__Pyx_BufFmt_RaiseUnexpectedChar('Z');
return NULL;
}
case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I':
case 'l': case 'L': case 'q': case 'Q':
case 'f': case 'd': case 'g':
case 'O': case 'p':
if (ctx->enc_type == *ts && got_Z == ctx->is_complex &&
ctx->enc_packmode == ctx->new_packmode) {
ctx->enc_count += ctx->new_count;
ctx->new_count = 1;
got_Z = 0;
++ts;
break;
}
case 's':
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
ctx->enc_count = ctx->new_count;
ctx->enc_packmode = ctx->new_packmode;
ctx->enc_type = *ts;
ctx->is_complex = got_Z;
++ts;
ctx->new_count = 1;
got_Z = 0;
break;
case ':':
++ts;
while(*ts != ':') ++ts;
++ts;
break;
case '(':
if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL;
break;
default:
{
int number = __Pyx_BufFmt_ExpectNumber(&ts);
if (number == -1) return NULL;
ctx->new_count = (size_t)number;
}
}
}
}
static CYTHON_INLINE void __Pyx_ZeroBuffer(Py_buffer* buf) {
buf->buf = NULL;
buf->obj = NULL;
buf->strides = __Pyx_zeros;
buf->shape = __Pyx_zeros;
buf->suboffsets = __Pyx_minusones;
}
static CYTHON_INLINE int __Pyx_GetBufferAndValidate(
Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags,
int nd, int cast, __Pyx_BufFmt_StackElem* stack)
{
if (obj == Py_None || obj == NULL) {
__Pyx_ZeroBuffer(buf);
return 0;
}
buf->buf = NULL;
if (__Pyx_GetBuffer(obj, buf, flags) == -1) goto fail;
if (buf->ndim != nd) {
PyErr_Format(PyExc_ValueError,
"Buffer has wrong number of dimensions (expected %d, got %d)",
nd, buf->ndim);
goto fail;
}
if (!cast) {
__Pyx_BufFmt_Context ctx;
__Pyx_BufFmt_Init(&ctx, stack, dtype);
if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail;
}
if ((unsigned)buf->itemsize != dtype->size) {
PyErr_Format(PyExc_ValueError,
"Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)",
buf->itemsize, (buf->itemsize > 1) ? "s" : "",
dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : "");
goto fail;
}
if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones;
return 0;
fail:;
__Pyx_ZeroBuffer(buf);
return -1;
}
static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) {
if (info->buf == NULL) return;
if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL;
__Pyx_ReleaseBuffer(info);
}
/* MemviewSliceInit */
static int
__Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview,
int ndim,
__Pyx_memviewslice *memviewslice,
int memview_is_new_reference)
{
__Pyx_RefNannyDeclarations
int i, retval=-1;
Py_buffer *buf = &memview->view;
__Pyx_RefNannySetupContext("init_memviewslice", 0);
if (!buf) {
PyErr_SetString(PyExc_ValueError,
"buf is NULL.");
goto fail;
} else if (memviewslice->memview || memviewslice->data) {
PyErr_SetString(PyExc_ValueError,
"memviewslice is already initialized!");
goto fail;
}
if (buf->strides) {
for (i = 0; i < ndim; i++) {
memviewslice->strides[i] = buf->strides[i];
}
} else {
Py_ssize_t stride = buf->itemsize;
for (i = ndim - 1; i >= 0; i--) {
memviewslice->strides[i] = stride;
stride *= buf->shape[i];
}
}
for (i = 0; i < ndim; i++) {
memviewslice->shape[i] = buf->shape[i];
if (buf->suboffsets) {
memviewslice->suboffsets[i] = buf->suboffsets[i];
} else {
memviewslice->suboffsets[i] = -1;
}
}
memviewslice->memview = memview;
memviewslice->data = (char *)buf->buf;
if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) {
Py_INCREF(memview);
}
retval = 0;
goto no_fail;
fail:
memviewslice->memview = 0;
memviewslice->data = 0;
retval = -1;
no_fail:
__Pyx_RefNannyFinishContext();
return retval;
}
static CYTHON_INLINE void __pyx_fatalerror(const char *fmt, ...) {
va_list vargs;
char msg[200];
#ifdef HAVE_STDARG_PROTOTYPES
va_start(vargs, fmt);
#else
va_start(vargs);
#endif
vsnprintf(msg, 200, fmt, vargs);
Py_FatalError(msg);
va_end(vargs);
}
static CYTHON_INLINE int
__pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count,
PyThread_type_lock lock)
{
int result;
PyThread_acquire_lock(lock, 1);
result = (*acquisition_count)++;
PyThread_release_lock(lock);
return result;
}
static CYTHON_INLINE int
__pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count,
PyThread_type_lock lock)
{
int result;
PyThread_acquire_lock(lock, 1);
result = (*acquisition_count)--;
PyThread_release_lock(lock);
return result;
}
static CYTHON_INLINE void
__Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno)
{
int first_time;
struct __pyx_memoryview_obj *memview = memslice->memview;
if (!memview || (PyObject *) memview == Py_None)
return;
if (__pyx_get_slice_count(memview) < 0)
__pyx_fatalerror("Acquisition count is %d (line %d)",
__pyx_get_slice_count(memview), lineno);
first_time = __pyx_add_acquisition_count(memview) == 0;
if (first_time) {
if (have_gil) {
Py_INCREF((PyObject *) memview);
} else {
PyGILState_STATE _gilstate = PyGILState_Ensure();
Py_INCREF((PyObject *) memview);
PyGILState_Release(_gilstate);
}
}
}
static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice,
int have_gil, int lineno) {
int last_time;
struct __pyx_memoryview_obj *memview = memslice->memview;
if (!memview ) {
return;
} else if ((PyObject *) memview == Py_None) {
memslice->memview = NULL;
return;
}
if (__pyx_get_slice_count(memview) <= 0)
__pyx_fatalerror("Acquisition count is %d (line %d)",
__pyx_get_slice_count(memview), lineno);
last_time = __pyx_sub_acquisition_count(memview) == 1;
memslice->data = NULL;
if (last_time) {
if (have_gil) {
Py_CLEAR(memslice->memview);
} else {
PyGILState_STATE _gilstate = PyGILState_Ensure();
Py_CLEAR(memslice->memview);
PyGILState_Release(_gilstate);
}
} else {
memslice->memview = NULL;
}
}
/* BufferIndexErrorNogil */
static void __Pyx_RaiseBufferIndexErrorNogil(int axis) {
#ifdef WITH_THREAD
PyGILState_STATE gilstate = PyGILState_Ensure();
#endif
__Pyx_RaiseBufferIndexError(axis);
#ifdef WITH_THREAD
PyGILState_Release(gilstate);
#endif
}
/* PyErrFetchRestore */
#if CYTHON_FAST_THREAD_STATE
static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) {
PyObject *tmp_type, *tmp_value, *tmp_tb;
tmp_type = tstate->curexc_type;
tmp_value = tstate->curexc_value;
tmp_tb = tstate->curexc_traceback;
tstate->curexc_type = type;
tstate->curexc_value = value;
tstate->curexc_traceback = tb;
Py_XDECREF(tmp_type);
Py_XDECREF(tmp_value);
Py_XDECREF(tmp_tb);
}
static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) {
*type = tstate->curexc_type;
*value = tstate->curexc_value;
*tb = tstate->curexc_traceback;
tstate->curexc_type = 0;
tstate->curexc_value = 0;
tstate->curexc_traceback = 0;
}
#endif
/* RaiseArgTupleInvalid */
static void __Pyx_RaiseArgtupleInvalid(
const char* func_name,
int exact,
Py_ssize_t num_min,
Py_ssize_t num_max,
Py_ssize_t num_found)
{
Py_ssize_t num_expected;
const char *more_or_less;
if (num_found < num_min) {
num_expected = num_min;
more_or_less = "at least";
} else {
num_expected = num_max;
more_or_less = "at most";
}
if (exact) {
more_or_less = "exactly";
}
PyErr_Format(PyExc_TypeError,
"%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)",
func_name, more_or_less, num_expected,
(num_expected == 1) ? "" : "s", num_found);
}
/* RaiseDoubleKeywords */
static void __Pyx_RaiseDoubleKeywordsError(
const char* func_name,
PyObject* kw_name)
{
PyErr_Format(PyExc_TypeError,
#if PY_MAJOR_VERSION >= 3
"%s() got multiple values for keyword argument '%U'", func_name, kw_name);
#else
"%s() got multiple values for keyword argument '%s'", func_name,
PyString_AsString(kw_name));
#endif
}
/* ParseKeywords */
static int __Pyx_ParseOptionalKeywords(
PyObject *kwds,
PyObject **argnames[],
PyObject *kwds2,
PyObject *values[],
Py_ssize_t num_pos_args,
const char* function_name)
{
PyObject *key = 0, *value = 0;
Py_ssize_t pos = 0;
PyObject*** name;
PyObject*** first_kw_arg = argnames + num_pos_args;
while (PyDict_Next(kwds, &pos, &key, &value)) {
name = first_kw_arg;
while (*name && (**name != key)) name++;
if (*name) {
values[name-argnames] = value;
continue;
}
name = first_kw_arg;
#if PY_MAJOR_VERSION < 3
if (likely(PyString_CheckExact(key)) || likely(PyString_Check(key))) {
while (*name) {
if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key))
&& _PyString_Eq(**name, key)) {
values[name-argnames] = value;
break;
}
name++;
}
if (*name) continue;
else {
PyObject*** argname = argnames;
while (argname != first_kw_arg) {
if ((**argname == key) || (
(CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key))
&& _PyString_Eq(**argname, key))) {
goto arg_passed_twice;
}
argname++;
}
}
} else
#endif
if (likely(PyUnicode_Check(key))) {
while (*name) {
int cmp = (**name == key) ? 0 :
#if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
(PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
#endif
PyUnicode_Compare(**name, key);
if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
if (cmp == 0) {
values[name-argnames] = value;
break;
}
name++;
}
if (*name) continue;
else {
PyObject*** argname = argnames;
while (argname != first_kw_arg) {
int cmp = (**argname == key) ? 0 :
#if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
(PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
#endif
PyUnicode_Compare(**argname, key);
if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
if (cmp == 0) goto arg_passed_twice;
argname++;
}
}
} else
goto invalid_keyword_type;
if (kwds2) {
if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad;
} else {
goto invalid_keyword;
}
}
return 0;
arg_passed_twice:
__Pyx_RaiseDoubleKeywordsError(function_name, key);
goto bad;
invalid_keyword_type:
PyErr_Format(PyExc_TypeError,
"%.200s() keywords must be strings", function_name);
goto bad;
invalid_keyword:
PyErr_Format(PyExc_TypeError,
#if PY_MAJOR_VERSION < 3
"%.200s() got an unexpected keyword argument '%.200s'",
function_name, PyString_AsString(key));
#else
"%s() got an unexpected keyword argument '%U'",
function_name, key);
#endif
bad:
return -1;
}
/* PyIntBinop */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyInt_EqObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, CYTHON_UNUSED int inplace) {
if (op1 == op2) {
Py_RETURN_TRUE;
}
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_CheckExact(op1))) {
const long b = intval;
long a = PyInt_AS_LONG(op1);
if (a == b) {
Py_RETURN_TRUE;
} else {
Py_RETURN_FALSE;
}
}
#endif
#if CYTHON_USE_PYLONG_INTERNALS
if (likely(PyLong_CheckExact(op1))) {
const long b = intval;
long a;
const digit* digits = ((PyLongObject*)op1)->ob_digit;
const Py_ssize_t size = Py_SIZE(op1);
if (likely(__Pyx_sst_abs(size) <= 1)) {
a = likely(size) ? digits[0] : 0;
if (size == -1) a = -a;
} else {
switch (size) {
case -2:
if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
}
case 2:
if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
}
case -3:
if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
}
case 3:
if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
}
case -4:
if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
}
case 4:
if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
}
#if PyLong_SHIFT < 30 && PyLong_SHIFT != 15
default: return PyLong_Type.tp_richcompare(op1, op2, Py_EQ);
#else
default: Py_RETURN_FALSE;
#endif
}
}
if (a == b) {
Py_RETURN_TRUE;
} else {
Py_RETURN_FALSE;
}
}
#endif
if (PyFloat_CheckExact(op1)) {
const long b = intval;
double a = PyFloat_AS_DOUBLE(op1);
if ((double)a == (double)b) {
Py_RETURN_TRUE;
} else {
Py_RETURN_FALSE;
}
}
return PyObject_RichCompare(op1, op2, Py_EQ);
}
#endif
/* PyIntBinop */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, CYTHON_UNUSED int inplace) {
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_CheckExact(op1))) {
const long b = intval;
long x;
long a = PyInt_AS_LONG(op1);
x = (long)((unsigned long)a + b);
if (likely((x^a) >= 0 || (x^b) >= 0))
return PyInt_FromLong(x);
return PyLong_Type.tp_as_number->nb_add(op1, op2);
}
#endif
#if CYTHON_USE_PYLONG_INTERNALS
if (likely(PyLong_CheckExact(op1))) {
const long b = intval;
long a, x;
#ifdef HAVE_LONG_LONG
const PY_LONG_LONG llb = intval;
PY_LONG_LONG lla, llx;
#endif
const digit* digits = ((PyLongObject*)op1)->ob_digit;
const Py_ssize_t size = Py_SIZE(op1);
if (likely(__Pyx_sst_abs(size) <= 1)) {
a = likely(size) ? digits[0] : 0;
if (size == -1) a = -a;
} else {
switch (size) {
case -2:
if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) {
lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
case 2:
if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) {
lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
case -3:
if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) {
lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
case 3:
if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) {
lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
case -4:
if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) {
lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
case 4:
if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) {
lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
default: return PyLong_Type.tp_as_number->nb_add(op1, op2);
}
}
x = a + b;
return PyLong_FromLong(x);
#ifdef HAVE_LONG_LONG
long_long:
llx = lla + llb;
return PyLong_FromLongLong(llx);
#endif
}
#endif
if (PyFloat_CheckExact(op1)) {
const long b = intval;
double a = PyFloat_AS_DOUBLE(op1);
double result;
PyFPE_START_PROTECT("add", return NULL)
result = ((double)a) + (double)b;
PyFPE_END_PROTECT(result)
return PyFloat_FromDouble(result);
}
return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2);
}
#endif
/* PyIntBinop */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyInt_SubtractObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, CYTHON_UNUSED int inplace) {
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_CheckExact(op1))) {
const long b = intval;
long x;
long a = PyInt_AS_LONG(op1);
x = (long)((unsigned long)a - b);
if (likely((x^a) >= 0 || (x^~b) >= 0))
return PyInt_FromLong(x);
return PyLong_Type.tp_as_number->nb_subtract(op1, op2);
}
#endif
#if CYTHON_USE_PYLONG_INTERNALS
if (likely(PyLong_CheckExact(op1))) {
const long b = intval;
long a, x;
#ifdef HAVE_LONG_LONG
const PY_LONG_LONG llb = intval;
PY_LONG_LONG lla, llx;
#endif
const digit* digits = ((PyLongObject*)op1)->ob_digit;
const Py_ssize_t size = Py_SIZE(op1);
if (likely(__Pyx_sst_abs(size) <= 1)) {
a = likely(size) ? digits[0] : 0;
if (size == -1) a = -a;
} else {
switch (size) {
case -2:
if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) {
lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
case 2:
if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) {
lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
case -3:
if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) {
lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
case 3:
if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) {
lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
case -4:
if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) {
lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
case 4:
if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
break;
#ifdef HAVE_LONG_LONG
} else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) {
lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
goto long_long;
#endif
}
default: return PyLong_Type.tp_as_number->nb_subtract(op1, op2);
}
}
x = a - b;
return PyLong_FromLong(x);
#ifdef HAVE_LONG_LONG
long_long:
llx = lla - llb;
return PyLong_FromLongLong(llx);
#endif
}
#endif
if (PyFloat_CheckExact(op1)) {
const long b = intval;
double a = PyFloat_AS_DOUBLE(op1);
double result;
PyFPE_START_PROTECT("subtract", return NULL)
result = ((double)a) - (double)b;
PyFPE_END_PROTECT(result)
return PyFloat_FromDouble(result);
}
return (inplace ? PyNumber_InPlaceSubtract : PyNumber_Subtract)(op1, op2);
}
#endif
/* SetItemInt */
static CYTHON_INLINE int __Pyx_SetItemInt_Generic(PyObject *o, PyObject *j, PyObject *v) {
int r;
if (!j) return -1;
r = PyObject_SetItem(o, j, v);
Py_DECREF(j);
return r;
}
static CYTHON_INLINE int __Pyx_SetItemInt_Fast(PyObject *o, Py_ssize_t i, PyObject *v, int is_list,
CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) {
#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS
if (is_list || PyList_CheckExact(o)) {
Py_ssize_t n = (!wraparound) ? i : ((likely(i >= 0)) ? i : i + PyList_GET_SIZE(o));
if ((!boundscheck) || likely((n >= 0) & (n < PyList_GET_SIZE(o)))) {
PyObject* old = PyList_GET_ITEM(o, n);
Py_INCREF(v);
PyList_SET_ITEM(o, n, v);
Py_DECREF(old);
return 1;
}
} else {
PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence;
if (likely(m && m->sq_ass_item)) {
if (wraparound && unlikely(i < 0) && likely(m->sq_length)) {
Py_ssize_t l = m->sq_length(o);
if (likely(l >= 0)) {
i += l;
} else {
if (!PyErr_ExceptionMatches(PyExc_OverflowError))
return -1;
PyErr_Clear();
}
}
return m->sq_ass_item(o, i, v);
}
}
#else
#if CYTHON_COMPILING_IN_PYPY
if (is_list || (PySequence_Check(o) && !PyDict_Check(o))) {
#else
if (is_list || PySequence_Check(o)) {
#endif
return PySequence_SetItem(o, i, v);
}
#endif
return __Pyx_SetItemInt_Generic(o, PyInt_FromSsize_t(i), v);
}
/* RaiseException */
#if PY_MAJOR_VERSION < 3
static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb,
CYTHON_UNUSED PyObject *cause) {
__Pyx_PyThreadState_declare
Py_XINCREF(type);
if (!value || value == Py_None)
value = NULL;
else
Py_INCREF(value);
if (!tb || tb == Py_None)
tb = NULL;
else {
Py_INCREF(tb);
if (!PyTraceBack_Check(tb)) {
PyErr_SetString(PyExc_TypeError,
"raise: arg 3 must be a traceback or None");
goto raise_error;
}
}
if (PyType_Check(type)) {
#if CYTHON_COMPILING_IN_PYPY
if (!value) {
Py_INCREF(Py_None);
value = Py_None;
}
#endif
PyErr_NormalizeException(&type, &value, &tb);
} else {
if (value) {
PyErr_SetString(PyExc_TypeError,
"instance exception may not have a separate value");
goto raise_error;
}
value = type;
type = (PyObject*) Py_TYPE(type);
Py_INCREF(type);
if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) {
PyErr_SetString(PyExc_TypeError,
"raise: exception class must be a subclass of BaseException");
goto raise_error;
}
}
__Pyx_PyThreadState_assign
__Pyx_ErrRestore(type, value, tb);
return;
raise_error:
Py_XDECREF(value);
Py_XDECREF(type);
Py_XDECREF(tb);
return;
}
#else
static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) {
PyObject* owned_instance = NULL;
if (tb == Py_None) {
tb = 0;
} else if (tb && !PyTraceBack_Check(tb)) {
PyErr_SetString(PyExc_TypeError,
"raise: arg 3 must be a traceback or None");
goto bad;
}
if (value == Py_None)
value = 0;
if (PyExceptionInstance_Check(type)) {
if (value) {
PyErr_SetString(PyExc_TypeError,
"instance exception may not have a separate value");
goto bad;
}
value = type;
type = (PyObject*) Py_TYPE(value);
} else if (PyExceptionClass_Check(type)) {
PyObject *instance_class = NULL;
if (value && PyExceptionInstance_Check(value)) {
instance_class = (PyObject*) Py_TYPE(value);
if (instance_class != type) {
int is_subclass = PyObject_IsSubclass(instance_class, type);
if (!is_subclass) {
instance_class = NULL;
} else if (unlikely(is_subclass == -1)) {
goto bad;
} else {
type = instance_class;
}
}
}
if (!instance_class) {
PyObject *args;
if (!value)
args = PyTuple_New(0);
else if (PyTuple_Check(value)) {
Py_INCREF(value);
args = value;
} else
args = PyTuple_Pack(1, value);
if (!args)
goto bad;
owned_instance = PyObject_Call(type, args, NULL);
Py_DECREF(args);
if (!owned_instance)
goto bad;
value = owned_instance;
if (!PyExceptionInstance_Check(value)) {
PyErr_Format(PyExc_TypeError,
"calling %R should have returned an instance of "
"BaseException, not %R",
type, Py_TYPE(value));
goto bad;
}
}
} else {
PyErr_SetString(PyExc_TypeError,
"raise: exception class must be a subclass of BaseException");
goto bad;
}
#if PY_VERSION_HEX >= 0x03030000
if (cause) {
#else
if (cause && cause != Py_None) {
#endif
PyObject *fixed_cause;
if (cause == Py_None) {
fixed_cause = NULL;
} else if (PyExceptionClass_Check(cause)) {
fixed_cause = PyObject_CallObject(cause, NULL);
if (fixed_cause == NULL)
goto bad;
} else if (PyExceptionInstance_Check(cause)) {
fixed_cause = cause;
Py_INCREF(fixed_cause);
} else {
PyErr_SetString(PyExc_TypeError,
"exception causes must derive from "
"BaseException");
goto bad;
}
PyException_SetCause(value, fixed_cause);
}
PyErr_SetObject(type, value);
if (tb) {
#if CYTHON_COMPILING_IN_PYPY
PyObject *tmp_type, *tmp_value, *tmp_tb;
PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb);
Py_INCREF(tb);
PyErr_Restore(tmp_type, tmp_value, tb);
Py_XDECREF(tmp_tb);
#else
PyThreadState *tstate = PyThreadState_GET();
PyObject* tmp_tb = tstate->curexc_traceback;
if (tb != tmp_tb) {
Py_INCREF(tb);
tstate->curexc_traceback = tb;
Py_XDECREF(tmp_tb);
}
#endif
}
bad:
Py_XDECREF(owned_instance);
return;
}
#endif
/* PyObjectCallNoArg */
#if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) {
#if CYTHON_FAST_PYCALL
if (PyFunction_Check(func)) {
return __Pyx_PyFunction_FastCall(func, NULL, 0);
}
#endif
#ifdef __Pyx_CyFunction_USED
if (likely(PyCFunction_Check(func) || PyObject_TypeCheck(func, __pyx_CyFunctionType))) {
#else
if (likely(PyCFunction_Check(func))) {
#endif
if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) {
return __Pyx_PyObject_CallMethO(func, NULL);
}
}
return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL);
}
#endif
/* RaiseTooManyValuesToUnpack */
static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) {
PyErr_Format(PyExc_ValueError,
"too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected);
}
/* RaiseNeedMoreValuesToUnpack */
static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) {
PyErr_Format(PyExc_ValueError,
"need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack",
index, (index == 1) ? "" : "s");
}
/* IterFinish */
static CYTHON_INLINE int __Pyx_IterFinish(void) {
#if CYTHON_FAST_THREAD_STATE
PyThreadState *tstate = PyThreadState_GET();
PyObject* exc_type = tstate->curexc_type;
if (unlikely(exc_type)) {
if (likely(exc_type == PyExc_StopIteration) || PyErr_GivenExceptionMatches(exc_type, PyExc_StopIteration)) {
PyObject *exc_value, *exc_tb;
exc_value = tstate->curexc_value;
exc_tb = tstate->curexc_traceback;
tstate->curexc_type = 0;
tstate->curexc_value = 0;
tstate->curexc_traceback = 0;
Py_DECREF(exc_type);
Py_XDECREF(exc_value);
Py_XDECREF(exc_tb);
return 0;
} else {
return -1;
}
}
return 0;
#else
if (unlikely(PyErr_Occurred())) {
if (likely(PyErr_ExceptionMatches(PyExc_StopIteration))) {
PyErr_Clear();
return 0;
} else {
return -1;
}
}
return 0;
#endif
}
/* UnpackItemEndCheck */
static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected) {
if (unlikely(retval)) {
Py_DECREF(retval);
__Pyx_RaiseTooManyValuesError(expected);
return -1;
} else {
return __Pyx_IterFinish();
}
return 0;
}
/* WriteUnraisableException */
static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno,
CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename,
int full_traceback, CYTHON_UNUSED int nogil) {
PyObject *old_exc, *old_val, *old_tb;
PyObject *ctx;
__Pyx_PyThreadState_declare
#ifdef WITH_THREAD
PyGILState_STATE state;
if (nogil)
state = PyGILState_Ensure();
#ifdef _MSC_VER
else state = (PyGILState_STATE)-1;
#endif
#endif
__Pyx_PyThreadState_assign
__Pyx_ErrFetch(&old_exc, &old_val, &old_tb);
if (full_traceback) {
Py_XINCREF(old_exc);
Py_XINCREF(old_val);
Py_XINCREF(old_tb);
__Pyx_ErrRestore(old_exc, old_val, old_tb);
PyErr_PrintEx(1);
}
#if PY_MAJOR_VERSION < 3
ctx = PyString_FromString(name);
#else
ctx = PyUnicode_FromString(name);
#endif
__Pyx_ErrRestore(old_exc, old_val, old_tb);
if (!ctx) {
PyErr_WriteUnraisable(Py_None);
} else {
PyErr_WriteUnraisable(ctx);
Py_DECREF(ctx);
}
#ifdef WITH_THREAD
if (nogil)
PyGILState_Release(state);
#endif
}
/* ArgTypeTest */
static void __Pyx_RaiseArgumentTypeInvalid(const char* name, PyObject *obj, PyTypeObject *type) {
PyErr_Format(PyExc_TypeError,
"Argument '%.200s' has incorrect type (expected %.200s, got %.200s)",
name, type->tp_name, Py_TYPE(obj)->tp_name);
}
static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed,
const char *name, int exact)
{
if (unlikely(!type)) {
PyErr_SetString(PyExc_SystemError, "Missing type object");
return 0;
}
if (none_allowed && obj == Py_None) return 1;
else if (exact) {
if (likely(Py_TYPE(obj) == type)) return 1;
#if PY_MAJOR_VERSION == 2
else if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1;
#endif
}
else {
if (likely(PyObject_TypeCheck(obj, type))) return 1;
}
__Pyx_RaiseArgumentTypeInvalid(name, obj, type);
return 0;
}
/* BytesEquals */
static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) {
#if CYTHON_COMPILING_IN_PYPY
return PyObject_RichCompareBool(s1, s2, equals);
#else
if (s1 == s2) {
return (equals == Py_EQ);
} else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) {
const char *ps1, *ps2;
Py_ssize_t length = PyBytes_GET_SIZE(s1);
if (length != PyBytes_GET_SIZE(s2))
return (equals == Py_NE);
ps1 = PyBytes_AS_STRING(s1);
ps2 = PyBytes_AS_STRING(s2);
if (ps1[0] != ps2[0]) {
return (equals == Py_NE);
} else if (length == 1) {
return (equals == Py_EQ);
} else {
int result = memcmp(ps1, ps2, (size_t)length);
return (equals == Py_EQ) ? (result == 0) : (result != 0);
}
} else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) {
return (equals == Py_NE);
} else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) {
return (equals == Py_NE);
} else {
int result;
PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
if (!py_result)
return -1;
result = __Pyx_PyObject_IsTrue(py_result);
Py_DECREF(py_result);
return result;
}
#endif
}
/* UnicodeEquals */
static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) {
#if CYTHON_COMPILING_IN_PYPY
return PyObject_RichCompareBool(s1, s2, equals);
#else
#if PY_MAJOR_VERSION < 3
PyObject* owned_ref = NULL;
#endif
int s1_is_unicode, s2_is_unicode;
if (s1 == s2) {
goto return_eq;
}
s1_is_unicode = PyUnicode_CheckExact(s1);
s2_is_unicode = PyUnicode_CheckExact(s2);
#if PY_MAJOR_VERSION < 3
if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) {
owned_ref = PyUnicode_FromObject(s2);
if (unlikely(!owned_ref))
return -1;
s2 = owned_ref;
s2_is_unicode = 1;
} else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) {
owned_ref = PyUnicode_FromObject(s1);
if (unlikely(!owned_ref))
return -1;
s1 = owned_ref;
s1_is_unicode = 1;
} else if (((!s2_is_unicode) & (!s1_is_unicode))) {
return __Pyx_PyBytes_Equals(s1, s2, equals);
}
#endif
if (s1_is_unicode & s2_is_unicode) {
Py_ssize_t length;
int kind;
void *data1, *data2;
if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0))
return -1;
length = __Pyx_PyUnicode_GET_LENGTH(s1);
if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) {
goto return_ne;
}
kind = __Pyx_PyUnicode_KIND(s1);
if (kind != __Pyx_PyUnicode_KIND(s2)) {
goto return_ne;
}
data1 = __Pyx_PyUnicode_DATA(s1);
data2 = __Pyx_PyUnicode_DATA(s2);
if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) {
goto return_ne;
} else if (length == 1) {
goto return_eq;
} else {
int result = memcmp(data1, data2, (size_t)(length * kind));
#if PY_MAJOR_VERSION < 3
Py_XDECREF(owned_ref);
#endif
return (equals == Py_EQ) ? (result == 0) : (result != 0);
}
} else if ((s1 == Py_None) & s2_is_unicode) {
goto return_ne;
} else if ((s2 == Py_None) & s1_is_unicode) {
goto return_ne;
} else {
int result;
PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
if (!py_result)
return -1;
result = __Pyx_PyObject_IsTrue(py_result);
Py_DECREF(py_result);
return result;
}
return_eq:
#if PY_MAJOR_VERSION < 3
Py_XDECREF(owned_ref);
#endif
return (equals == Py_EQ);
return_ne:
#if PY_MAJOR_VERSION < 3
Py_XDECREF(owned_ref);
#endif
return (equals == Py_NE);
#endif
}
/* None */
static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t a, Py_ssize_t b) {
Py_ssize_t q = a / b;
Py_ssize_t r = a - q*b;
q -= ((r != 0) & ((r ^ b) < 0));
return q;
}
/* GetAttr */
static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) {
#if CYTHON_COMPILING_IN_CPYTHON
#if PY_MAJOR_VERSION >= 3
if (likely(PyUnicode_Check(n)))
#else
if (likely(PyString_Check(n)))
#endif
return __Pyx_PyObject_GetAttrStr(o, n);
#endif
return PyObject_GetAttr(o, n);
}
/* decode_c_string */
static CYTHON_INLINE PyObject* __Pyx_decode_c_string(
const char* cstring, Py_ssize_t start, Py_ssize_t stop,
const char* encoding, const char* errors,
PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) {
Py_ssize_t length;
if (unlikely((start < 0) | (stop < 0))) {
size_t slen = strlen(cstring);
if (unlikely(slen > (size_t) PY_SSIZE_T_MAX)) {
PyErr_SetString(PyExc_OverflowError,
"c-string too long to convert to Python");
return NULL;
}
length = (Py_ssize_t) slen;
if (start < 0) {
start += length;
if (start < 0)
start = 0;
}
if (stop < 0)
stop += length;
}
length = stop - start;
if (unlikely(length <= 0))
return PyUnicode_FromUnicode(NULL, 0);
cstring += start;
if (decode_func) {
return decode_func(cstring, length, errors);
} else {
return PyUnicode_Decode(cstring, length, encoding, errors);
}
}
/* RaiseNoneIterError */
static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) {
PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable");
}
/* ExtTypeTest */
static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) {
if (unlikely(!type)) {
PyErr_SetString(PyExc_SystemError, "Missing type object");
return 0;
}
if (likely(PyObject_TypeCheck(obj, type)))
return 1;
PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s",
Py_TYPE(obj)->tp_name, type->tp_name);
return 0;
}
/* SaveResetException */
#if CYTHON_FAST_THREAD_STATE
static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) {
*type = tstate->exc_type;
*value = tstate->exc_value;
*tb = tstate->exc_traceback;
Py_XINCREF(*type);
Py_XINCREF(*value);
Py_XINCREF(*tb);
}
static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) {
PyObject *tmp_type, *tmp_value, *tmp_tb;
tmp_type = tstate->exc_type;
tmp_value = tstate->exc_value;
tmp_tb = tstate->exc_traceback;
tstate->exc_type = type;
tstate->exc_value = value;
tstate->exc_traceback = tb;
Py_XDECREF(tmp_type);
Py_XDECREF(tmp_value);
Py_XDECREF(tmp_tb);
}
#endif
/* PyErrExceptionMatches */
#if CYTHON_FAST_THREAD_STATE
static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err) {
PyObject *exc_type = tstate->curexc_type;
if (exc_type == err) return 1;
if (unlikely(!exc_type)) return 0;
return PyErr_GivenExceptionMatches(exc_type, err);
}
#endif
/* GetException */
#if CYTHON_FAST_THREAD_STATE
static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) {
#else
static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) {
#endif
PyObject *local_type, *local_value, *local_tb;
#if CYTHON_FAST_THREAD_STATE
PyObject *tmp_type, *tmp_value, *tmp_tb;
local_type = tstate->curexc_type;
local_value = tstate->curexc_value;
local_tb = tstate->curexc_traceback;
tstate->curexc_type = 0;
tstate->curexc_value = 0;
tstate->curexc_traceback = 0;
#else
PyErr_Fetch(&local_type, &local_value, &local_tb);
#endif
PyErr_NormalizeException(&local_type, &local_value, &local_tb);
#if CYTHON_FAST_THREAD_STATE
if (unlikely(tstate->curexc_type))
#else
if (unlikely(PyErr_Occurred()))
#endif
goto bad;
#if PY_MAJOR_VERSION >= 3
if (local_tb) {
if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0))
goto bad;
}
#endif
Py_XINCREF(local_tb);
Py_XINCREF(local_type);
Py_XINCREF(local_value);
*type = local_type;
*value = local_value;
*tb = local_tb;
#if CYTHON_FAST_THREAD_STATE
tmp_type = tstate->exc_type;
tmp_value = tstate->exc_value;
tmp_tb = tstate->exc_traceback;
tstate->exc_type = local_type;
tstate->exc_value = local_value;
tstate->exc_traceback = local_tb;
Py_XDECREF(tmp_type);
Py_XDECREF(tmp_value);
Py_XDECREF(tmp_tb);
#else
PyErr_SetExcInfo(local_type, local_value, local_tb);
#endif
return 0;
bad:
*type = 0;
*value = 0;
*tb = 0;
Py_XDECREF(local_type);
Py_XDECREF(local_value);
Py_XDECREF(local_tb);
return -1;
}
/* SwapException */
#if CYTHON_FAST_THREAD_STATE
static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) {
PyObject *tmp_type, *tmp_value, *tmp_tb;
tmp_type = tstate->exc_type;
tmp_value = tstate->exc_value;
tmp_tb = tstate->exc_traceback;
tstate->exc_type = *type;
tstate->exc_value = *value;
tstate->exc_traceback = *tb;
*type = tmp_type;
*value = tmp_value;
*tb = tmp_tb;
}
#else
static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) {
PyObject *tmp_type, *tmp_value, *tmp_tb;
PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb);
PyErr_SetExcInfo(*type, *value, *tb);
*type = tmp_type;
*value = tmp_value;
*tb = tmp_tb;
}
#endif
/* Import */
static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) {
PyObject *empty_list = 0;
PyObject *module = 0;
PyObject *global_dict = 0;
PyObject *empty_dict = 0;
PyObject *list;
#if PY_VERSION_HEX < 0x03030000
PyObject *py_import;
py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import);
if (!py_import)
goto bad;
#endif
if (from_list)
list = from_list;
else {
empty_list = PyList_New(0);
if (!empty_list)
goto bad;
list = empty_list;
}
global_dict = PyModule_GetDict(__pyx_m);
if (!global_dict)
goto bad;
empty_dict = PyDict_New();
if (!empty_dict)
goto bad;
{
#if PY_MAJOR_VERSION >= 3
if (level == -1) {
if (strchr(__Pyx_MODULE_NAME, '.')) {
#if PY_VERSION_HEX < 0x03030000
PyObject *py_level = PyInt_FromLong(1);
if (!py_level)
goto bad;
module = PyObject_CallFunctionObjArgs(py_import,
name, global_dict, empty_dict, list, py_level, NULL);
Py_DECREF(py_level);
#else
module = PyImport_ImportModuleLevelObject(
name, global_dict, empty_dict, list, 1);
#endif
if (!module) {
if (!PyErr_ExceptionMatches(PyExc_ImportError))
goto bad;
PyErr_Clear();
}
}
level = 0;
}
#endif
if (!module) {
#if PY_VERSION_HEX < 0x03030000
PyObject *py_level = PyInt_FromLong(level);
if (!py_level)
goto bad;
module = PyObject_CallFunctionObjArgs(py_import,
name, global_dict, empty_dict, list, py_level, NULL);
Py_DECREF(py_level);
#else
module = PyImport_ImportModuleLevelObject(
name, global_dict, empty_dict, list, level);
#endif
}
}
bad:
#if PY_VERSION_HEX < 0x03030000
Py_XDECREF(py_import);
#endif
Py_XDECREF(empty_list);
Py_XDECREF(empty_dict);
return module;
}
/* None */
static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) {
PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname);
}
/* None */
static CYTHON_INLINE long __Pyx_div_long(long a, long b) {
long q = a / b;
long r = a - q*b;
q -= ((r != 0) & ((r ^ b) < 0));
return q;
}
/* SetVTable */
static int __Pyx_SetVtable(PyObject *dict, void *vtable) {
#if PY_VERSION_HEX >= 0x02070000
PyObject *ob = PyCapsule_New(vtable, 0, 0);
#else
PyObject *ob = PyCObject_FromVoidPtr(vtable, 0);
#endif
if (!ob)
goto bad;
if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0)
goto bad;
Py_DECREF(ob);
return 0;
bad:
Py_XDECREF(ob);
return -1;
}
/* ImportFrom */
static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name) {
PyObject* value = __Pyx_PyObject_GetAttrStr(module, name);
if (unlikely(!value) && PyErr_ExceptionMatches(PyExc_AttributeError)) {
PyErr_Format(PyExc_ImportError,
#if PY_MAJOR_VERSION < 3
"cannot import name %.230s", PyString_AS_STRING(name));
#else
"cannot import name %S", name);
#endif
}
return value;
}
/* CodeObjectCache */
static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) {
int start = 0, mid = 0, end = count - 1;
if (end >= 0 && code_line > entries[end].code_line) {
return count;
}
while (start < end) {
mid = start + (end - start) / 2;
if (code_line < entries[mid].code_line) {
end = mid;
} else if (code_line > entries[mid].code_line) {
start = mid + 1;
} else {
return mid;
}
}
if (code_line <= entries[mid].code_line) {
return mid;
} else {
return mid + 1;
}
}
static PyCodeObject *__pyx_find_code_object(int code_line) {
PyCodeObject* code_object;
int pos;
if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) {
return NULL;
}
pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) {
return NULL;
}
code_object = __pyx_code_cache.entries[pos].code_object;
Py_INCREF(code_object);
return code_object;
}
static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) {
int pos, i;
__Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries;
if (unlikely(!code_line)) {
return;
}
if (unlikely(!entries)) {
entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry));
if (likely(entries)) {
__pyx_code_cache.entries = entries;
__pyx_code_cache.max_count = 64;
__pyx_code_cache.count = 1;
entries[0].code_line = code_line;
entries[0].code_object = code_object;
Py_INCREF(code_object);
}
return;
}
pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) {
PyCodeObject* tmp = entries[pos].code_object;
entries[pos].code_object = code_object;
Py_DECREF(tmp);
return;
}
if (__pyx_code_cache.count == __pyx_code_cache.max_count) {
int new_max = __pyx_code_cache.max_count + 64;
entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc(
__pyx_code_cache.entries, (size_t)new_max*sizeof(__Pyx_CodeObjectCacheEntry));
if (unlikely(!entries)) {
return;
}
__pyx_code_cache.entries = entries;
__pyx_code_cache.max_count = new_max;
}
for (i=__pyx_code_cache.count; i>pos; i--) {
entries[i] = entries[i-1];
}
entries[pos].code_line = code_line;
entries[pos].code_object = code_object;
__pyx_code_cache.count++;
Py_INCREF(code_object);
}
/* AddTraceback */
#include "compile.h"
#include "frameobject.h"
#include "traceback.h"
static PyCodeObject* __Pyx_CreateCodeObjectForTraceback(
const char *funcname, int c_line,
int py_line, const char *filename) {
PyCodeObject *py_code = 0;
PyObject *py_srcfile = 0;
PyObject *py_funcname = 0;
#if PY_MAJOR_VERSION < 3
py_srcfile = PyString_FromString(filename);
#else
py_srcfile = PyUnicode_FromString(filename);
#endif
if (!py_srcfile) goto bad;
if (c_line) {
#if PY_MAJOR_VERSION < 3
py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
#else
py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
#endif
}
else {
#if PY_MAJOR_VERSION < 3
py_funcname = PyString_FromString(funcname);
#else
py_funcname = PyUnicode_FromString(funcname);
#endif
}
if (!py_funcname) goto bad;
py_code = __Pyx_PyCode_New(
0,
0,
0,
0,
0,
__pyx_empty_bytes, /*PyObject *code,*/
__pyx_empty_tuple, /*PyObject *consts,*/
__pyx_empty_tuple, /*PyObject *names,*/
__pyx_empty_tuple, /*PyObject *varnames,*/
__pyx_empty_tuple, /*PyObject *freevars,*/
__pyx_empty_tuple, /*PyObject *cellvars,*/
py_srcfile, /*PyObject *filename,*/
py_funcname, /*PyObject *name,*/
py_line,
__pyx_empty_bytes /*PyObject *lnotab*/
);
Py_DECREF(py_srcfile);
Py_DECREF(py_funcname);
return py_code;
bad:
Py_XDECREF(py_srcfile);
Py_XDECREF(py_funcname);
return NULL;
}
static void __Pyx_AddTraceback(const char *funcname, int c_line,
int py_line, const char *filename) {
PyCodeObject *py_code = 0;
PyFrameObject *py_frame = 0;
py_code = __pyx_find_code_object(c_line ? c_line : py_line);
if (!py_code) {
py_code = __Pyx_CreateCodeObjectForTraceback(
funcname, c_line, py_line, filename);
if (!py_code) goto bad;
__pyx_insert_code_object(c_line ? c_line : py_line, py_code);
}
py_frame = PyFrame_New(
PyThreadState_GET(), /*PyThreadState *tstate,*/
py_code, /*PyCodeObject *code,*/
__pyx_d, /*PyObject *globals,*/
0 /*PyObject *locals*/
);
if (!py_frame) goto bad;
__Pyx_PyFrame_SetLineNumber(py_frame, py_line);
PyTraceBack_Here(py_frame);
bad:
Py_XDECREF(py_code);
Py_XDECREF(py_frame);
}
#if PY_MAJOR_VERSION < 3
static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) {
if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags);
if (PyObject_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags);
if (PyObject_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags);
PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name);
return -1;
}
static void __Pyx_ReleaseBuffer(Py_buffer *view) {
PyObject *obj = view->obj;
if (!obj) return;
if (PyObject_CheckBuffer(obj)) {
PyBuffer_Release(view);
return;
}
Py_DECREF(obj);
view->obj = NULL;
}
#endif
/* MemviewSliceIsContig */
static int
__pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs,
char order, int ndim)
{
int i, index, step, start;
Py_ssize_t itemsize = mvs.memview->view.itemsize;
if (order == 'F') {
step = 1;
start = 0;
} else {
step = -1;
start = ndim - 1;
}
for (i = 0; i < ndim; i++) {
index = start + step * i;
if (mvs.suboffsets[index] >= 0 || mvs.strides[index] != itemsize)
return 0;
itemsize *= mvs.shape[index];
}
return 1;
}
/* OverlappingSlices */
static void
__pyx_get_array_memory_extents(__Pyx_memviewslice *slice,
void **out_start, void **out_end,
int ndim, size_t itemsize)
{
char *start, *end;
int i;
start = end = slice->data;
for (i = 0; i < ndim; i++) {
Py_ssize_t stride = slice->strides[i];
Py_ssize_t extent = slice->shape[i];
if (extent == 0) {
*out_start = *out_end = start;
return;
} else {
if (stride > 0)
end += stride * (extent - 1);
else
start += stride * (extent - 1);
}
}
*out_start = start;
*out_end = end + itemsize;
}
static int
__pyx_slices_overlap(__Pyx_memviewslice *slice1,
__Pyx_memviewslice *slice2,
int ndim, size_t itemsize)
{
void *start1, *end1, *start2, *end2;
__pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize);
__pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize);
return (start1 < end2) && (start2 < end1);
}
/* Capsule */
static CYTHON_INLINE PyObject *
__pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig)
{
PyObject *cobj;
#if PY_VERSION_HEX >= 0x02070000
cobj = PyCapsule_New(p, sig, NULL);
#else
cobj = PyCObject_FromVoidPtr(p, NULL);
#endif
return cobj;
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) {
const int neg_one = (int) -1, const_zero = (int) 0;
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(int) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(int) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(int) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(int) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(int),
little, !is_unsigned);
}
}
/* CIntFromPyVerify */
#define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\
__PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0)
#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\
__PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1)
#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\
{\
func_type value = func_value;\
if (sizeof(target_type) < sizeof(func_type)) {\
if (unlikely(value != (func_type) (target_type) value)) {\
func_type zero = 0;\
if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\
return (target_type) -1;\
if (is_unsigned && unlikely(value < zero))\
goto raise_neg_overflow;\
else\
goto raise_overflow;\
}\
}\
return (target_type) value;\
}
/* CIntToPy */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) {
const long neg_one = (long) -1, const_zero = (long) 0;
const int is_unsigned = neg_one > const_zero;
if (is_unsigned) {
if (sizeof(long) < sizeof(long)) {
return PyInt_FromLong((long) value);
} else if (sizeof(long) <= sizeof(unsigned long)) {
return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) {
return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
}
} else {
if (sizeof(long) <= sizeof(long)) {
return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
} else if (sizeof(long) <= sizeof(PY_LONG_LONG)) {
return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
}
}
{
int one = 1; int little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&value;
return _PyLong_FromByteArray(bytes, sizeof(long),
little, !is_unsigned);
}
}
/* MemviewDtypeToObject */
static CYTHON_INLINE PyObject *__pyx_memview_get_double(const char *itemp) {
return (PyObject *) PyFloat_FromDouble(*(double *) itemp);
}
static CYTHON_INLINE int __pyx_memview_set_double(const char *itemp, PyObject *obj) {
double value = __pyx_PyFloat_AsDouble(obj);
if ((value == (double)-1) && PyErr_Occurred())
return 0;
*(double *) itemp = value;
return 1;
}
/* MemviewSliceCopyTemplate */
static __Pyx_memviewslice
__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs,
const char *mode, int ndim,
size_t sizeof_dtype, int contig_flag,
int dtype_is_object)
{
__Pyx_RefNannyDeclarations
int i;
__Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } };
struct __pyx_memoryview_obj *from_memview = from_mvs->memview;
Py_buffer *buf = &from_memview->view;
PyObject *shape_tuple = NULL;
PyObject *temp_int = NULL;
struct __pyx_array_obj *array_obj = NULL;
struct __pyx_memoryview_obj *memview_obj = NULL;
__Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0);
for (i = 0; i < ndim; i++) {
if (from_mvs->suboffsets[i] >= 0) {
PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with "
"indirect dimensions (axis %d)", i);
goto fail;
}
}
shape_tuple = PyTuple_New(ndim);
if (unlikely(!shape_tuple)) {
goto fail;
}
__Pyx_GOTREF(shape_tuple);
for(i = 0; i < ndim; i++) {
temp_int = PyInt_FromSsize_t(from_mvs->shape[i]);
if(unlikely(!temp_int)) {
goto fail;
} else {
PyTuple_SET_ITEM(shape_tuple, i, temp_int);
temp_int = NULL;
}
}
array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL);
if (unlikely(!array_obj)) {
goto fail;
}
__Pyx_GOTREF(array_obj);
memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new(
(PyObject *) array_obj, contig_flag,
dtype_is_object,
from_mvs->memview->typeinfo);
if (unlikely(!memview_obj))
goto fail;
if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0))
goto fail;
if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim,
dtype_is_object) < 0))
goto fail;
goto no_fail;
fail:
__Pyx_XDECREF(new_mvs.memview);
new_mvs.memview = NULL;
new_mvs.data = NULL;
no_fail:
__Pyx_XDECREF(shape_tuple);
__Pyx_XDECREF(temp_int);
__Pyx_XDECREF(array_obj);
__Pyx_RefNannyFinishContext();
return new_mvs;
}
/* CIntFromPy */
static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) {
const int neg_one = (int) -1, const_zero = (int) 0;
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(int) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (int) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (int) 0;
case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0])
case 2:
if (8 * sizeof(int) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) {
return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(int) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) {
return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(int) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) {
return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (int) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(int) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (int) 0;
case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0])
case -2:
if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) {
return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(int) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) {
return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) {
return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(int) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) {
return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) {
return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(int) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) {
return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
}
}
break;
}
#endif
if (sizeof(int) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(int) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
int val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (int) -1;
}
} else {
int val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (int) -1;
val = __Pyx_PyInt_As_int(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to int");
return (int) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to int");
return (int) -1;
}
/* CIntFromPy */
static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) {
const char neg_one = (char) -1, const_zero = (char) 0;
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(char) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (char) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (char) 0;
case 1: __PYX_VERIFY_RETURN_INT(char, digit, digits[0])
case 2:
if (8 * sizeof(char) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) >= 2 * PyLong_SHIFT) {
return (char) (((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(char) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) >= 3 * PyLong_SHIFT) {
return (char) (((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(char) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) >= 4 * PyLong_SHIFT) {
return (char) (((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (char) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(char) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(char, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(char) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(char, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (char) 0;
case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(char, digit, +digits[0])
case -2:
if (8 * sizeof(char) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) {
return (char) (((char)-1)*(((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(char) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) {
return (char) ((((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) {
return (char) (((char)-1)*(((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(char) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) {
return (char) ((((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) {
return (char) (((char)-1)*(((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(char) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) {
return (char) ((((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
}
}
break;
}
#endif
if (sizeof(char) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(char, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(char) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(char, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
char val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (char) -1;
}
} else {
char val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (char) -1;
val = __Pyx_PyInt_As_char(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to char");
return (char) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to char");
return (char) -1;
}
/* CIntFromPy */
static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) {
const long neg_one = (long) -1, const_zero = (long) 0;
const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_Check(x))) {
if (sizeof(long) < sizeof(long)) {
__PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x))
} else {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
goto raise_neg_overflow;
}
return (long) val;
}
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (long) 0;
case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0])
case 2:
if (8 * sizeof(long) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) {
return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]));
}
}
break;
case 3:
if (8 * sizeof(long) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) {
return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]));
}
}
break;
case 4:
if (8 * sizeof(long) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) {
return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]));
}
}
break;
}
#endif
#if CYTHON_COMPILING_IN_CPYTHON
if (unlikely(Py_SIZE(x) < 0)) {
goto raise_neg_overflow;
}
#else
{
int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
if (unlikely(result < 0))
return (long) -1;
if (unlikely(result == 1))
goto raise_neg_overflow;
}
#endif
if (sizeof(long) <= sizeof(unsigned long)) {
__PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
}
} else {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)x)->ob_digit;
switch (Py_SIZE(x)) {
case 0: return (long) 0;
case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0]))
case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0])
case -2:
if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
}
}
break;
case 2:
if (8 * sizeof(long) > 1 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
}
}
break;
case -3:
if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
}
}
break;
case 3:
if (8 * sizeof(long) > 2 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
}
}
break;
case -4:
if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
}
}
break;
case 4:
if (8 * sizeof(long) > 3 * PyLong_SHIFT) {
if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
__PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
} else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
}
}
break;
}
#endif
if (sizeof(long) <= sizeof(long)) {
__PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
} else if (sizeof(long) <= sizeof(PY_LONG_LONG)) {
__PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
}
}
{
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
PyErr_SetString(PyExc_RuntimeError,
"_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
long val;
PyObject *v = __Pyx_PyNumber_IntOrLong(x);
#if PY_MAJOR_VERSION < 3
if (likely(v) && !PyLong_Check(v)) {
PyObject *tmp = v;
v = PyNumber_Long(tmp);
Py_DECREF(tmp);
}
#endif
if (likely(v)) {
int one = 1; int is_little = (int)*(unsigned char *)&one;
unsigned char *bytes = (unsigned char *)&val;
int ret = _PyLong_AsByteArray((PyLongObject *)v,
bytes, sizeof(val),
is_little, !is_unsigned);
Py_DECREF(v);
if (likely(!ret))
return val;
}
#endif
return (long) -1;
}
} else {
long val;
PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
if (!tmp) return (long) -1;
val = __Pyx_PyInt_As_long(tmp);
Py_DECREF(tmp);
return val;
}
raise_overflow:
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to long");
return (long) -1;
raise_neg_overflow:
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to long");
return (long) -1;
}
/* TypeInfoCompare */
static int
__pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b)
{
int i;
if (!a || !b)
return 0;
if (a == b)
return 1;
if (a->size != b->size || a->typegroup != b->typegroup ||
a->is_unsigned != b->is_unsigned || a->ndim != b->ndim) {
if (a->typegroup == 'H' || b->typegroup == 'H') {
return a->size == b->size;
} else {
return 0;
}
}
if (a->ndim) {
for (i = 0; i < a->ndim; i++)
if (a->arraysize[i] != b->arraysize[i])
return 0;
}
if (a->typegroup == 'S') {
if (a->flags != b->flags)
return 0;
if (a->fields || b->fields) {
if (!(a->fields && b->fields))
return 0;
for (i = 0; a->fields[i].type && b->fields[i].type; i++) {
__Pyx_StructField *field_a = a->fields + i;
__Pyx_StructField *field_b = b->fields + i;
if (field_a->offset != field_b->offset ||
!__pyx_typeinfo_cmp(field_a->type, field_b->type))
return 0;
}
return !a->fields[i].type && !b->fields[i].type;
}
}
return 1;
}
/* MemviewSliceValidateAndInit */
static int
__pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec)
{
if (buf->shape[dim] <= 1)
return 1;
if (buf->strides) {
if (spec & __Pyx_MEMVIEW_CONTIG) {
if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) {
if (buf->strides[dim] != sizeof(void *)) {
PyErr_Format(PyExc_ValueError,
"Buffer is not indirectly contiguous "
"in dimension %d.", dim);
goto fail;
}
} else if (buf->strides[dim] != buf->itemsize) {
PyErr_SetString(PyExc_ValueError,
"Buffer and memoryview are not contiguous "
"in the same dimension.");
goto fail;
}
}
if (spec & __Pyx_MEMVIEW_FOLLOW) {
Py_ssize_t stride = buf->strides[dim];
if (stride < 0)
stride = -stride;
if (stride < buf->itemsize) {
PyErr_SetString(PyExc_ValueError,
"Buffer and memoryview are not contiguous "
"in the same dimension.");
goto fail;
}
}
} else {
if (spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1) {
PyErr_Format(PyExc_ValueError,
"C-contiguous buffer is not contiguous in "
"dimension %d", dim);
goto fail;
} else if (spec & (__Pyx_MEMVIEW_PTR)) {
PyErr_Format(PyExc_ValueError,
"C-contiguous buffer is not indirect in "
"dimension %d", dim);
goto fail;
} else if (buf->suboffsets) {
PyErr_SetString(PyExc_ValueError,
"Buffer exposes suboffsets but no strides");
goto fail;
}
}
return 1;
fail:
return 0;
}
static int
__pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec)
{
if (spec & __Pyx_MEMVIEW_DIRECT) {
if (buf->suboffsets && buf->suboffsets[dim] >= 0) {
PyErr_Format(PyExc_ValueError,
"Buffer not compatible with direct access "
"in dimension %d.", dim);
goto fail;
}
}
if (spec & __Pyx_MEMVIEW_PTR) {
if (!buf->suboffsets || (buf->suboffsets && buf->suboffsets[dim] < 0)) {
PyErr_Format(PyExc_ValueError,
"Buffer is not indirectly accessible "
"in dimension %d.", dim);
goto fail;
}
}
return 1;
fail:
return 0;
}
static int
__pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag)
{
int i;
if (c_or_f_flag & __Pyx_IS_F_CONTIG) {
Py_ssize_t stride = 1;
for (i = 0; i < ndim; i++) {
if (stride * buf->itemsize != buf->strides[i] &&
buf->shape[i] > 1)
{
PyErr_SetString(PyExc_ValueError,
"Buffer not fortran contiguous.");
goto fail;
}
stride = stride * buf->shape[i];
}
} else if (c_or_f_flag & __Pyx_IS_C_CONTIG) {
Py_ssize_t stride = 1;
for (i = ndim - 1; i >- 1; i--) {
if (stride * buf->itemsize != buf->strides[i] &&
buf->shape[i] > 1) {
PyErr_SetString(PyExc_ValueError,
"Buffer not C contiguous.");
goto fail;
}
stride = stride * buf->shape[i];
}
}
return 1;
fail:
return 0;
}
static int __Pyx_ValidateAndInit_memviewslice(
int *axes_specs,
int c_or_f_flag,
int buf_flags,
int ndim,
__Pyx_TypeInfo *dtype,
__Pyx_BufFmt_StackElem stack[],
__Pyx_memviewslice *memviewslice,
PyObject *original_obj)
{
struct __pyx_memoryview_obj *memview, *new_memview;
__Pyx_RefNannyDeclarations
Py_buffer *buf;
int i, spec = 0, retval = -1;
__Pyx_BufFmt_Context ctx;
int from_memoryview = __pyx_memoryview_check(original_obj);
__Pyx_RefNannySetupContext("ValidateAndInit_memviewslice", 0);
if (from_memoryview && __pyx_typeinfo_cmp(dtype, ((struct __pyx_memoryview_obj *)
original_obj)->typeinfo)) {
memview = (struct __pyx_memoryview_obj *) original_obj;
new_memview = NULL;
} else {
memview = (struct __pyx_memoryview_obj *) __pyx_memoryview_new(
original_obj, buf_flags, 0, dtype);
new_memview = memview;
if (unlikely(!memview))
goto fail;
}
buf = &memview->view;
if (buf->ndim != ndim) {
PyErr_Format(PyExc_ValueError,
"Buffer has wrong number of dimensions (expected %d, got %d)",
ndim, buf->ndim);
goto fail;
}
if (new_memview) {
__Pyx_BufFmt_Init(&ctx, stack, dtype);
if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail;
}
if ((unsigned) buf->itemsize != dtype->size) {
PyErr_Format(PyExc_ValueError,
"Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "u byte%s) "
"does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)",
buf->itemsize,
(buf->itemsize > 1) ? "s" : "",
dtype->name,
dtype->size,
(dtype->size > 1) ? "s" : "");
goto fail;
}
for (i = 0; i < ndim; i++) {
spec = axes_specs[i];
if (!__pyx_check_strides(buf, i, ndim, spec))
goto fail;
if (!__pyx_check_suboffsets(buf, i, ndim, spec))
goto fail;
}
if (buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag))
goto fail;
if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice,
new_memview != NULL) == -1)) {
goto fail;
}
retval = 0;
goto no_fail;
fail:
Py_XDECREF(new_memview);
retval = -1;
no_fail:
__Pyx_RefNannyFinishContext();
return retval;
}
/* ObjectToMemviewSlice */
static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_double(PyObject *obj) {
__Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
__Pyx_BufFmt_StackElem stack[1];
int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) };
int retcode;
if (obj == Py_None) {
result.memview = (struct __pyx_memoryview_obj *) Py_None;
return result;
}
retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0,
PyBUF_RECORDS, 1,
&__Pyx_TypeInfo_double, stack,
&result, obj);
if (unlikely(retcode == -1))
goto __pyx_fail;
return result;
__pyx_fail:
result.memview = NULL;
result.data = NULL;
return result;
}
/* ObjectToMemviewSlice */
static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_long(PyObject *obj) {
__Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
__Pyx_BufFmt_StackElem stack[1];
int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) };
int retcode;
if (obj == Py_None) {
result.memview = (struct __pyx_memoryview_obj *) Py_None;
return result;
}
retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0,
PyBUF_RECORDS, 1,
&__Pyx_TypeInfo_long, stack,
&result, obj);
if (unlikely(retcode == -1))
goto __pyx_fail;
return result;
__pyx_fail:
result.memview = NULL;
result.data = NULL;
return result;
}
/* ObjectToMemviewSlice */
static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_dc_double(PyObject *obj) {
__Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
__Pyx_BufFmt_StackElem stack[1];
int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) };
int retcode;
if (obj == Py_None) {
result.memview = (struct __pyx_memoryview_obj *) Py_None;
return result;
}
retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG,
(PyBUF_C_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 2,
&__Pyx_TypeInfo_double, stack,
&result, obj);
if (unlikely(retcode == -1))
goto __pyx_fail;
return result;
__pyx_fail:
result.memview = NULL;
result.data = NULL;
return result;
}
/* ObjectToMemviewSlice */
static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_dc_long(PyObject *obj) {
__Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
__Pyx_BufFmt_StackElem stack[1];
int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) };
int retcode;
if (obj == Py_None) {
result.memview = (struct __pyx_memoryview_obj *) Py_None;
return result;
}
retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG,
(PyBUF_C_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 2,
&__Pyx_TypeInfo_long, stack,
&result, obj);
if (unlikely(retcode == -1))
goto __pyx_fail;
return result;
__pyx_fail:
result.memview = NULL;
result.data = NULL;
return result;
}
/* CheckBinaryVersion */
static int __Pyx_check_binary_version(void) {
char ctversion[4], rtversion[4];
PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION);
PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion());
if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) {
char message[200];
PyOS_snprintf(message, sizeof(message),
"compiletime version %s of module '%.100s' "
"does not match runtime version %s",
ctversion, __Pyx_MODULE_NAME, rtversion);
return PyErr_WarnEx(NULL, message, 1);
}
return 0;
}
/* InitStrings */
static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) {
while (t->p) {
#if PY_MAJOR_VERSION < 3
if (t->is_unicode) {
*t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL);
} else if (t->intern) {
*t->p = PyString_InternFromString(t->s);
} else {
*t->p = PyString_FromStringAndSize(t->s, t->n - 1);
}
#else
if (t->is_unicode | t->is_str) {
if (t->intern) {
*t->p = PyUnicode_InternFromString(t->s);
} else if (t->encoding) {
*t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL);
} else {
*t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1);
}
} else {
*t->p = PyBytes_FromStringAndSize(t->s, t->n - 1);
}
#endif
if (!*t->p)
return -1;
++t;
}
return 0;
}
static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) {
return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str));
}
static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject* o) {
Py_ssize_t ignore;
return __Pyx_PyObject_AsStringAndSize(o, &ignore);
}
static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) {
#if CYTHON_COMPILING_IN_CPYTHON && (__PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT)
if (
#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
__Pyx_sys_getdefaultencoding_not_ascii &&
#endif
PyUnicode_Check(o)) {
#if PY_VERSION_HEX < 0x03030000
char* defenc_c;
PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL);
if (!defenc) return NULL;
defenc_c = PyBytes_AS_STRING(defenc);
#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
{
char* end = defenc_c + PyBytes_GET_SIZE(defenc);
char* c;
for (c = defenc_c; c < end; c++) {
if ((unsigned char) (*c) >= 128) {
PyUnicode_AsASCIIString(o);
return NULL;
}
}
}
#endif
*length = PyBytes_GET_SIZE(defenc);
return defenc_c;
#else
if (__Pyx_PyUnicode_READY(o) == -1) return NULL;
#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
if (PyUnicode_IS_ASCII(o)) {
*length = PyUnicode_GET_LENGTH(o);
return PyUnicode_AsUTF8(o);
} else {
PyUnicode_AsASCIIString(o);
return NULL;
}
#else
return PyUnicode_AsUTF8AndSize(o, length);
#endif
#endif
} else
#endif
#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE))
if (PyByteArray_Check(o)) {
*length = PyByteArray_GET_SIZE(o);
return PyByteArray_AS_STRING(o);
} else
#endif
{
char* result;
int r = PyBytes_AsStringAndSize(o, &result, length);
if (unlikely(r < 0)) {
return NULL;
} else {
return result;
}
}
}
static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) {
int is_true = x == Py_True;
if (is_true | (x == Py_False) | (x == Py_None)) return is_true;
else return PyObject_IsTrue(x);
}
static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) {
#if CYTHON_USE_TYPE_SLOTS
PyNumberMethods *m;
#endif
const char *name = NULL;
PyObject *res = NULL;
#if PY_MAJOR_VERSION < 3
if (PyInt_Check(x) || PyLong_Check(x))
#else
if (PyLong_Check(x))
#endif
return __Pyx_NewRef(x);
#if CYTHON_USE_TYPE_SLOTS
m = Py_TYPE(x)->tp_as_number;
#if PY_MAJOR_VERSION < 3
if (m && m->nb_int) {
name = "int";
res = PyNumber_Int(x);
}
else if (m && m->nb_long) {
name = "long";
res = PyNumber_Long(x);
}
#else
if (m && m->nb_int) {
name = "int";
res = PyNumber_Long(x);
}
#endif
#else
res = PyNumber_Int(x);
#endif
if (res) {
#if PY_MAJOR_VERSION < 3
if (!PyInt_Check(res) && !PyLong_Check(res)) {
#else
if (!PyLong_Check(res)) {
#endif
PyErr_Format(PyExc_TypeError,
"__%.4s__ returned non-%.4s (type %.200s)",
name, name, Py_TYPE(res)->tp_name);
Py_DECREF(res);
return NULL;
}
}
else if (!PyErr_Occurred()) {
PyErr_SetString(PyExc_TypeError,
"an integer is required");
}
return res;
}
static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) {
Py_ssize_t ival;
PyObject *x;
#if PY_MAJOR_VERSION < 3
if (likely(PyInt_CheckExact(b))) {
if (sizeof(Py_ssize_t) >= sizeof(long))
return PyInt_AS_LONG(b);
else
return PyInt_AsSsize_t(x);
}
#endif
if (likely(PyLong_CheckExact(b))) {
#if CYTHON_USE_PYLONG_INTERNALS
const digit* digits = ((PyLongObject*)b)->ob_digit;
const Py_ssize_t size = Py_SIZE(b);
if (likely(__Pyx_sst_abs(size) <= 1)) {
ival = likely(size) ? digits[0] : 0;
if (size == -1) ival = -ival;
return ival;
} else {
switch (size) {
case 2:
if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) {
return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
break;
case -2:
if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) {
return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
break;
case 3:
if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) {
return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
break;
case -3:
if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) {
return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
break;
case 4:
if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) {
return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
break;
case -4:
if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) {
return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
}
break;
}
}
#endif
return PyLong_AsSsize_t(b);
}
x = PyNumber_Index(b);
if (!x) return -1;
ival = PyInt_AsSsize_t(x);
Py_DECREF(x);
return ival;
}
static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) {
return PyInt_FromSize_t(ival);
}
#endif /* Py_PYTHON_H */
|
mlpcell_fp32.h | #ifndef MLPCELL_F32
#define MLPCELL_F32
#include "mc_funcs.h"
#define PCL_ASSERT(cond, x...) do { if(!(cond)) { printf(x); fflush(stdout); exit(1); } } while(0)
#define DECL_VLA_PTR(type, name, dims, ptr) type (*name)dims = (type (*)dims)ptr
#define DECL_VLA_PTR_CHECK_VAR(var, type, name, dims, ptr) type (*name)dims = (var > 0) ? (type (*)dims)ptr : NULL
#define DECL_VLA_PTR_CHECK_COND(cond, type, name, dims, ptr) type (*name)dims = cond ? (type (*)dims)ptr : NULL
#define DECL_VLA_PTR_CHECK_COND_VAR(cond, var, type, name, dims, ptr) type (*name)dims = (cond && var > 0) ? (type (*)dims)ptr : NULL
#define DECL_VLA_PTR_PT(type, name, dims, t) type (*name)dims = (type (*)dims)(t.data_ptr<type>())
#define DECL_VLA_PTR_PT_CHECK_COND(cond, type, name, dims, t) type (*name)dims = cond ? (type (*)dims)(t.data_ptr<type>()) : NULL
#define DECL_VLA_PTR_NPT(newtype, type, name, dims, t) newtype (*name)dims = (newtype (*)dims)(t.data_ptr<type>())
#define DECL_VLA_PTR_NPT_CHECK_COND(cond, newtype, type, name, dims, t) newtype (*name)dims = cond ? (newtype (*)dims)(t.data_ptr<type>()) : NULL
#define LIBXSMM_ALIGNDOWN(N, A) ((N) & ~((A)-1))
//--------------------------------------norm_to_normT-----------------------------------------------------
//
void norm_to_normT_32b(float* in, float* out, int N, int M)
{
libxsmm_meltw_unary_param trans_param;
trans_param.in.primary = (void*)in;
trans_param.out.primary = (void*)out;
libxsmm_meltwfunction_unary trans_kernel = libxsmm_dispatch_meltw_unary(M, N, &M, &N, LIBXSMM_DATATYPE_F32, LIBXSMM_DATATYPE_F32, LIBXSMM_DATATYPE_F32, LIBXSMM_MELTW_FLAG_UNARY_NONE, LIBXSMM_MELTW_TYPE_UNARY_TRANSFORM_NORM_TO_NORMT);
if ( trans_kernel == NULL ) {
fprintf( stderr, "JIT for NORM_TO_NORMT TPP. Bailing...!\n");
exit(-1);
}
trans_kernel( &trans_param );
}
// ----------------------------------------------------------------------------------------------------------------
inline void colbcast_f32_copy(int N, int M, libxsmm_meltw_unary_param *params)
{
libxsmm_meltw_unary_flags unary_flags = LIBXSMM_MELTW_FLAG_UNARY_BCAST_COL;
libxsmm_meltw_unary_type unary_type = LIBXSMM_MELTW_TYPE_UNARY_IDENTITY;
libxsmm_meltwfunction_unary kernel = libxsmm_dispatch_meltw_unary(M, N, NULL, NULL, LIBXSMM_DATATYPE_F32, LIBXSMM_DATATYPE_F32, LIBXSMM_DATATYPE_F32, unary_flags, unary_type);
if ( kernel == NULL )
{
fprintf( stderr, "JIT for bf16 to b16 broadcast copy failed. Bailing...!\n");
exit(-1);
}
kernel(params);
}
inline void dropout_f32(long N, long M, libxsmm_meltw_unary_param *params, libxsmm_meltw_unary_flags flags)
{
libxsmm_meltwfunction_unary dropout_kernel = libxsmm_dispatch_meltw_unary(M, N, NULL, NULL, LIBXSMM_DATATYPE_F32, LIBXSMM_DATATYPE_F32, LIBXSMM_DATATYPE_F32, flags, LIBXSMM_MELTW_TYPE_UNARY_DROPOUT);
if ( dropout_kernel == NULL ) {
fprintf( stderr, "JIT for DROPOUT TPP. Bailing...!\n");
exit(-1);
}
dropout_kernel( params );
}
inline void dropout_bwd_f32(long N, long M, libxsmm_meltw_unary_param *params, libxsmm_meltw_unary_flags flags)
{
libxsmm_meltwfunction_unary dropout_kernel = libxsmm_dispatch_meltw_unary(M, N, NULL, NULL, LIBXSMM_DATATYPE_F32, LIBXSMM_DATATYPE_F32, LIBXSMM_DATATYPE_F32, flags, LIBXSMM_MELTW_TYPE_UNARY_DROPOUT_INV);
if ( dropout_kernel == NULL ) {
fprintf( stderr, "JIT for DROPOUT TPP. Bailing...!\n");
exit(-1);
}
dropout_kernel( params );
}
inline void brgemm_f32_f32(long n, long m, long k, long stride_b, long stride_a, float *B_, float *A_, float *C, long count, const float beta = 1.0, const char b_trans='n', const char a_trans='n')
{
const float alpha = 1.0;
float *A = A_;
float *B = B_;
unsigned long long l_br = count;
int flags = LIBXSMM_GEMM_FLAGS('n', b_trans);
// Query or JIT-generate reduction kernel; returns NULL if JIT is not supported (bf16 inputs, fp32-accumulate internally, bf16 outputs). *
libxsmm_smmfunction_reducebatch_strd kernel = libxsmm_smmdispatch_reducebatch_strd(m, n, k, stride_a*sizeof(float), stride_b*sizeof(float), NULL, NULL, NULL, &alpha, &beta, &flags, NULL);
PCL_ASSERT(kernel, "Null brgemm bf16 kernel\n");
kernel(A, B, C, &l_br);
}
inline void delbias_f32(int N, int M, int LD_N, int LD_M, libxsmm_meltw_unary_param *delbias_params)
{
libxsmm_meltw_unary_flags unary_flags = LIBXSMM_MELTW_FLAG_UNARY_REDUCE_COLS;
libxsmm_meltw_unary_type unary_type = LIBXSMM_MELTW_TYPE_UNARY_REDUCE_X_OP_ADD_NCNC_FORMAT;
libxsmm_meltwfunction_unary delbias_kernel = libxsmm_dispatch_meltw_unary(M, N, (libxsmm_blasint*)&LD_M, (libxsmm_blasint*)&LD_N, LIBXSMM_DATATYPE_F32, LIBXSMM_DATATYPE_F32, LIBXSMM_DATATYPE_F32, unary_flags, unary_type);
if (delbias_kernel == NULL ) {
printf("Could not create f32 delbias kernel.. bailing\n");
exit(-1);
}
delbias_kernel(delbias_params);
}
inline void add_f32_f32(int N, int M, libxsmm_meltw_binary_param *binary_param)
{
libxsmm_meltw_binary_type binary_type = LIBXSMM_MELTW_TYPE_BINARY_ADD;
libxsmm_meltw_binary_flags binary_flags = LIBXSMM_MELTW_FLAG_BINARY_NONE;
libxsmm_meltwfunction_binary add_kernel = libxsmm_dispatch_meltw_binary(M, N, NULL, NULL, NULL, LIBXSMM_DATATYPE_F32, LIBXSMM_DATATYPE_F32, LIBXSMM_DATATYPE_F32, binary_flags, binary_type);
if ( add_kernel == NULL ){
fprintf( stderr, "JIT for BINARY TPP. Bailing...!\n");
exit(-1);
}
add_kernel(binary_param);
}
inline void relu_fwd_f32(long N, long M, libxsmm_meltw_unary_param *params)
{
libxsmm_meltw_unary_flags unary_flags = LIBXSMM_MELTW_FLAG_UNARY_BITMASK_2BYTEMULT;
libxsmm_meltwfunction_unary relu_kernel = libxsmm_dispatch_meltw_unary(M, N, NULL, NULL, LIBXSMM_DATATYPE_F32, LIBXSMM_DATATYPE_F32, LIBXSMM_DATATYPE_F32, unary_flags, LIBXSMM_MELTW_TYPE_UNARY_RELU);
if ( relu_kernel == NULL ) {
fprintf( stderr, "JIT for ReLU TPP. Bailing...!\n");
exit(-1);
}
relu_kernel( params );
}
inline void relu_bwd_f32(long N, long M, libxsmm_meltw_unary_param *params)
{
libxsmm_meltw_unary_flags unary_flags = LIBXSMM_MELTW_FLAG_UNARY_BITMASK_2BYTEMULT;
libxsmm_meltwfunction_unary relu_kernel = libxsmm_dispatch_meltw_unary(M, N, NULL, NULL, LIBXSMM_DATATYPE_F32, LIBXSMM_DATATYPE_F32, LIBXSMM_DATATYPE_F32, unary_flags, LIBXSMM_MELTW_TYPE_UNARY_RELU_INV);
if ( relu_kernel == NULL ) {
fprintf( stderr, "JIT for ReLU TPP. Bailing...!\n");
exit(-1);
}
relu_kernel( params );
}
class MLPCell_F32
{
public:
MLPCell_F32(int N, int C, int K, int bn, int bc, int bk, bool bias, bool skip, int act, bool norm, float p, bool train)
{
pN = N;
pC = C;
pK = K;
pbn = bn;
pbc = bc;
pbk = bk;
pbias = bias;
pskip = skip;
pact = act;
pnorm = norm;
pp = p;
ptrain = train;
//printf("MLPCell: N = %d, C = %d, K = %d, bf = %d, bias = %d, skip = %d, act = %d, norm = %d, dropout prob = %.2f train = %d\n", N, C, K, bias, skip, act, norm, p, train);
}
std::vector<at::Tensor> fwd(std::vector<at::Tensor> inputs)
{
long bn = pbn;
long bc = pbc;
long bk = pbk;
long nn = pN/bn;
long nc = pC;
long nk = pK;
long rn = pN % bn;
long in_off = nn*nc*bn*bc;
long out_off = nn*nk*bn*bk;
long C = nc*bc;
long K = nk*bk;
// std::cout << "F32--------------> " << std::endl;
libxsmm_meltw_unary_param copy_params;
libxsmm_meltw_unary_param cvt_params;
libxsmm_meltw_unary_param relu_params;
libxsmm_meltw_unary_param dropout_params;
libxsmm_meltw_unary_flags dropout_flags = LIBXSMM_MELTW_FLAG_UNARY_BITMASK_2BYTEMULT;
libxsmm_meltw_binary_param add_params;
libxsmm_meltw_binary_flags binary_flags = LIBXSMM_MELTW_FLAG_BINARY_NONE;
libxsmm_meltw_binary_type binary_type = LIBXSMM_MELTW_TYPE_BINARY_ADD;
int i=0;
at::Tensor t_input_l = inputs[i++];
at::Tensor t_input_r = inputs[i++];
at::Tensor t_weights_l = inputs[i++];
at::Tensor t_weights_r = inputs[i++];
at::Tensor t_bias_l = inputs[i++];
at::Tensor t_bias_r = inputs[i++];
at::Tensor t_output = t_input_l.new_empty({pN, K});
int dd = (bk % 32 == 0) ? bk/32 : bk/32 + 1;
at::Tensor t_dropout_mask_bN, t_dropout_mask_rN;
if(ptrain && pp > 0)
{
int size = nn*nk*bn*bk;
t_dropout_mask_bN = at::empty(size, torch::TensorOptions().dtype(torch::kByte));
if(rn > 0)
{
size = nk*rn*bk;
t_dropout_mask_rN = at::empty(size, torch::TensorOptions().dtype(torch::kByte));
}
}
__mmask32 (*dropout_mask_bN)[nk][bn][dd] = (ptrain && pp > 0) ? (__mmask32 (*)[nk][bn][dd])(t_dropout_mask_bN.data_ptr()) : NULL;
__mmask32 (*dropout_mask_rN)[nk][rn][dd] = (ptrain && pp > 0 && rn > 0) ? (__mmask32 (*)[nk][rn][dd])(t_dropout_mask_rN.data_ptr()) : NULL;
int rd = (bk % 32 == 0) ? bk/32 : bk/32 + 1;
at::Tensor t_relumask_bN, t_relumask_rN;
if(pact==1)
{
int size = nn*nk*bn*bk;
t_relumask_bN = at::empty(size, torch::TensorOptions().dtype(torch::kByte));
if(rn > 0)
{
size = nk*rn*bk;
t_relumask_rN = at::empty(size, torch::TensorOptions().dtype(torch::kByte));
}
}
__mmask32 (*relumask_bN)[nk][bn][rd] = pact==1 ? (__mmask32 (*)[nk][bn][rd])(t_relumask_bN.data_ptr()) : NULL;
__mmask32 (*relumask_rN)[nk][rn][rd] = (pact==1 && rn > 0) ? (__mmask32 (*)[nk][rn][rd])(t_relumask_rN.data_ptr()) : NULL;
int threads = 1;
#ifdef _OPENMP
threads = omp_get_max_threads();
#endif
long wts = nk*nc*bk*bc;
long in_bn = threads*nc*bn*bc;
long in_rn = nc*rn*bc;
long out_bn = threads*nk*bn*bk;
long out_rn = nk*rn*bk;
long scratch_size;
if(pskip)
scratch_size = (wts*4 + in_bn*2 + in_rn*2 + out_bn*3 + out_rn*3)*sizeof(float);
else
scratch_size = (wts*2 + in_bn + in_rn + out_bn + out_rn)*sizeof(float);
void *scratch = libxsmm_aligned_malloc(scratch_size, 2097152);
float *t_wt_l = (float*)scratch;
float *t_tr_wt_l = t_wt_l + wts;
float *t_input_bN_l = t_tr_wt_l + wts;
float *t_output_bN_l = t_input_bN_l + in_bn;
float *t_output_bN = t_output_bN_l + out_bn;
float *t_input_rN_l=NULL, *t_output_rN_l=NULL, *t_output_rN=NULL;
if(rn > 0)
{
t_input_rN_l = t_output_bN + out_bn;
t_output_rN_l = t_input_rN_l + in_rn;
t_output_rN = t_output_rN_l + out_rn;
}
float *t_wt_r=NULL, *t_tr_wt_r=NULL, *t_input_bN_r=NULL, *t_output_bN_r=NULL;
float *t_input_rN_r=NULL, *t_output_rN_r=NULL;
if(pskip)
{
if(rn > 0)
t_wt_r = t_output_rN + out_rn;
else
t_wt_r = t_output_bN + out_bn;
t_tr_wt_r = t_wt_r + wts;
t_input_bN_r = t_tr_wt_r + wts;
t_output_bN_r = t_input_bN_r + in_bn;
if(rn > 0)
{
t_input_rN_r = t_output_bN_r + out_bn;
t_output_rN_r = t_input_rN_r + in_rn;
}
}
DECL_VLA_PTR_PT(float, wt_f32_l, [C], t_weights_l);
float *bias_l = t_bias_l.data_ptr<float>();
float (*wt_f32_r)[C] = pskip ? (float (*)[C])t_weights_r.data_ptr<float>() : NULL;
float *bias_r = pskip ? t_bias_r.data_ptr<float>() : NULL;
DECL_VLA_PTR_PT(float, input_l, [C], t_input_l);
DECL_VLA_PTR_PT_CHECK_COND(pskip, float, input_r, [C], t_input_r);
DECL_VLA_PTR_PT(float, output, [K], t_output);
DECL_VLA_PTR(float, wt_l, [nc][bk][bc], t_wt_l);
DECL_VLA_PTR(float, tr_wt_l, [nc][bc][bk], t_tr_wt_l);
DECL_VLA_PTR(float, input_bN_l, [nc][bn][bc], t_input_bN_l);
DECL_VLA_PTR_CHECK_VAR(rn, float, input_rN_l, [nc][rn][bc], t_input_rN_l);
DECL_VLA_PTR(float, output_bN, [nk][bn][bk], t_output_bN);
DECL_VLA_PTR_CHECK_VAR(rn, float, output_rN, [nk][rn][bk], t_output_rN);
DECL_VLA_PTR_CHECK_COND(pskip, float, wt_r, [nc][bk][bc], t_wt_r);
DECL_VLA_PTR_CHECK_COND(pskip, float, tr_wt_r, [nc][bc][bk], t_tr_wt_r);
DECL_VLA_PTR_CHECK_COND(pskip, float, input_bN_r, [nc][bn][bc], t_input_bN_r);
DECL_VLA_PTR_CHECK_COND(pskip, float, input_rN_r, [nc][rn][bc], t_input_rN_r);
DECL_VLA_PTR_CHECK_COND(pskip, float, output_bN_l, [nk][bn][bk], t_output_bN_l);
DECL_VLA_PTR_CHECK_COND(pskip, float, output_bN_r, [nk][bn][bk], t_output_bN_r);
DECL_VLA_PTR_CHECK_COND_VAR(pskip, rn, float, output_rN_l, [nk][rn][bk], t_output_rN_l);
DECL_VLA_PTR_CHECK_COND_VAR(pskip, rn, float, output_rN_r, [nk][rn][bk], t_output_rN_r);
for(int k=0; k<nk; k++) {
for(int c=0; c<nc; c++) {
copy_params.in.primary = &wt_f32_l[k*bk][c*bc];
copy_params.out.primary = &wt_l[k][c];
f32_copy(bk, bc, bc, bc, ©_params);
}
}
// Wt: NORM to NORM_T
norm_to_normT_32b(wt_l[0][0][0], tr_wt_l[0][0][0], bk, bc);
if(pskip)
{
for(int k=0; k<nk; k++) {
for(int c=0; c<nc; c++) {
copy_params.in.primary = &wt_f32_r[k*bk][c*bc];
copy_params.out.primary = &wt_r[k][c];
f32_copy(bk, bc, bc, bc, ©_params);
}
}
norm_to_normT_32b(wt_r[0][0][0], tr_wt_r[0][0][0], bk, bc);
}
#ifdef _OPENMP
#pragma omp parallel
#endif
{
int tid = omp_get_thread_num();
int threads = omp_get_max_threads();
int jobs = (nn % threads == 0) ? nn/threads : nn/threads + 1;
int tb = (tid*jobs < nn) ? tid*jobs : nn;
int te = ((tid+1)*jobs < nn) ? (tid+1)*jobs : nn;
int count = nc;
libxsmm_meltw_unary_param copy_params;
libxsmm_meltw_binary_param add_params;
libxsmm_meltw_unary_param relu_params;
libxsmm_meltw_unary_param dropout_params;
libxsmm_meltw_unary_flags dropout_flags = LIBXSMM_MELTW_FLAG_UNARY_BITMASK_2BYTEMULT;
for(int m=tb; m<te; m++) {
for(int c=0; c<nc; c++) {
copy_params.in.primary = &input_l[m*bn][c*bc];
copy_params.out.primary = &input_bN_l[tid][c];
f32_copy(bn, bc, nc*bc, nc*bc, ©_params);
}
if(pskip)
{
for(int c=0; c<nc; c++) {
copy_params.in.primary = &input_r[m*bn][c*bc];
copy_params.out.primary = &input_bN_r[tid][c];
f32_copy(bn, bc, nc*bc, nc*bc, ©_params);
}
for(int k=0; k<nk; k++) {
copy_params.in.primary = bias_l;
copy_params.out.primary = &output_bN_l[tid][k];
colbcast_f32_copy(bn, bk, ©_params);
}
for(int k=0; k<nk; k++) {
copy_params.in.primary = bias_r;
copy_params.out.primary = &output_bN_r[tid][k];
colbcast_f32_copy(bn, bk, ©_params);
}
}
else
{
for(int k=0; k<nk; k++) {
copy_params.in.primary = bias_l;
copy_params.out.primary = &output_bN[tid][k];
colbcast_f32_copy(bn, bk, ©_params);
}
}
if(pskip)
{
brgemm_f32_f32(bn, bk, bc, bn*bk, 0, input_bN_l[tid][0][0], tr_wt_l[0][0][0], output_bN_l[tid][0][0], count);
brgemm_f32_f32(bn, bk, bc, bn*bk, 0, input_bN_r[tid][0][0], tr_wt_r[0][0][0], output_bN_r[tid][0][0], count);
add_params.in0.primary = (void*)&output_bN_l[tid][0];
add_params.in1.primary = (void*)&output_bN_r[tid][0];
add_params.out.primary = (void*)&output_bN[tid][0];
add_f32_f32(bn, bk, &add_params);
}
else
brgemm_f32_f32(bn, bk, bc, bn*bk, 0, input_bN_l[tid][0][0], tr_wt_l[0][0][0], output_bN[tid][0][0], count);
if(pact == 1)
{
for(int k=0; k<nk; k++) {
relu_params.in.primary = &output_bN[tid][k];
relu_params.out.primary = &output_bN[tid][k];
relu_params.out.secondary = &relumask_bN[m][k];
relu_fwd_f32(bn, bk, &relu_params);
}
}
if(ptrain && pp > 0)
{
for(int k=0; k<nk; k++)
{
dropout_params.in.primary = &output_bN[tid][k];
dropout_params.in.secondary = rnd_state;
dropout_params.in.tertiary = &pp;
dropout_params.out.primary = &output_bN[tid][k];
dropout_params.out.secondary = &dropout_mask_bN[m][k];
dropout_f32(bn, bk, &dropout_params, dropout_flags);
}
}
for(int k=0; k<nk; k++) {
copy_params.in.primary = &output_bN[tid][k];
copy_params.out.primary = &output[m*bn][k*bk];
f32_copy(bn, bk, nk*bk, nk*bk, ©_params);
}
}
}
if(rn > 0)
{
// Single-threaded part of compute
//
for(int c=0; c<nc; c++) {
copy_params.in.primary = &input_l[nn*bn][c*bc];
copy_params.out.primary = &input_rN_l[0][c];
f32_copy(rn, bc, nc*bc, nc*bc, ©_params);
}
if(pskip)
{
for(int c=0; c<nc; c++) {
copy_params.in.primary = &input_r[nn*bn][c*bc];
copy_params.out.primary = &input_rN_r[0][c];
f32_copy(rn, bc, nc*bc, nc*bc, ©_params);
}
for(int k=0; k<nk; k++) {
copy_params.in.primary = bias_l;
copy_params.out.primary = &output_rN_l[0][k];
colbcast_f32_copy(rn, bk, ©_params);
copy_params.in.primary = bias_r;
copy_params.out.primary = &output_rN_r[0][k];
colbcast_f32_copy(rn, bk, ©_params);
}
}
else
{
for(int k=0; k<nk; k++) {
copy_params.in.primary = bias_l;
copy_params.out.primary = &output_rN[0][k];
colbcast_f32_copy(rn, bk, ©_params);
}
}
int count = nc;
if(pskip)
{
brgemm_f32_f32(rn, bk, bc, rn*bk, 0, input_rN_l[0][0][0], tr_wt_l[0][0][0], output_rN_l[0][0][0], count);
brgemm_f32_f32(rn, bk, bc, rn*bk, 0, input_rN_r[0][0][0], tr_wt_r[0][0][0], output_rN_r[0][0][0], count);
add_params.in0.primary = (void*)&output_rN_l[0][0];
add_params.in1.primary = (void*)&output_rN_r[0][0];
add_params.out.primary = (void*)&output_rN[0][0];
add_f32_f32(rn, bk, &add_params);
}
else
brgemm_f32_f32(rn, bk, bc, rn*bk, 0, input_rN_l[0][0][0], tr_wt_l[0][0][0], output_rN[0][0][0], count);
if(pact == 1)
{
for(int k=0; k<nk; k++) {
relu_params.in.primary = &output_rN[0][k];
relu_params.out.primary = &output_rN[0][k];
relu_params.out.secondary = &relumask_rN[0][k];
relu_fwd_f32(rn, bk, &relu_params);
}
}
if(ptrain && pp > 0)
{
for(int k=0; k<nk; k++)
{
dropout_params.in.primary = &output_rN[0][k];
dropout_params.in.secondary = rnd_state;
dropout_params.in.tertiary = &pp;
dropout_params.out.primary = &output_rN[0][k];
dropout_params.out.secondary = &dropout_mask_rN[0][k];
dropout_f32(rn, bk, &dropout_params, dropout_flags);
}
}
for(int k=0; k<nk; k++) {
copy_params.in.primary = &output_rN[0][k];
copy_params.out.primary = &output[nn*bn][k*bk];
f32_copy(rn, bk, nk*bk, nk*bk, ©_params);
}
}
libxsmm_free((void*)scratch);
return {t_output, t_relumask_bN, t_relumask_rN, t_dropout_mask_bN, t_dropout_mask_rN};
}
////=======================================================
//// ====================== BWD ===========================
////=======================================================
std::vector<at::Tensor> bwd(std::vector<at::Tensor> inputs)
{
long bn = pbn;
long bc = pbc;
long bk = pbk;
long nn = pN/bn;
long nc = pC;
long nk = pK;
long rn = pN % bn;
long K = nk*bk;
long C = nc*bc;
libxsmm_meltw_unary_param copy_params;
libxsmm_meltw_unary_param relu_params;
libxsmm_meltw_unary_param dropout_params;
libxsmm_meltw_unary_param delbias_params;
libxsmm_meltw_unary_param cvt_params;
libxsmm_meltw_unary_flags dropout_flags = LIBXSMM_MELTW_FLAG_UNARY_BITMASK_2BYTEMULT;
int threads = 1;
#ifdef _OPENMP
threads = omp_get_max_threads();
#endif
int i=0;
at::Tensor t_grad_output = inputs[i++];
at::Tensor t_input_l = inputs[i++];
at::Tensor t_input_r = inputs[i++];
at::Tensor t_weights_l = inputs[i++];
at::Tensor t_weights_r = inputs[i++];
at::Tensor t_relumask_bN = inputs[i++];
at::Tensor t_relumask_rN = inputs[i++];
at::Tensor t_dropout_mask_bN = inputs[i++];
at::Tensor t_dropout_mask_rN = inputs[i++];
at::Tensor t_grad_weights_l = t_weights_l.new_empty({nk, nc, bk, bc});
at::Tensor t_grad_bias_l = t_weights_l.new_empty(K);
at::Tensor t_grad_input_l = t_input_l.new_empty({pN, C});
at::Tensor t_grad_weights_r, t_grad_bias_r, t_grad_input_r;
if(pskip)
{
t_grad_weights_r = t_weights_r.new_empty({nk, nc, bk, bc});
t_grad_bias_r = t_weights_r.new_empty(K);
t_grad_input_r = t_input_r.new_empty({pN, C});
}
long wts = nk*nc*bk*bc;
long go_bn = threads*nk*bn*bk;
long go_rn = nk*rn*bk;
long gi_bn = threads*nc*bn*bc;
long gi_rn = nc*rn*bc;
long in_bn = threads*nc*bn*bc;
long in_rn = nc*rn*bc;
long scratch_size;
if(pskip)
scratch_size = (wts*4 + go_bn + go_rn + gi_bn*2 + gi_rn*2 + in_bn*2 + in_rn*2)*sizeof(float);
else
scratch_size = (wts*2 + go_bn + go_rn + gi_bn + gi_rn + in_bn + in_rn)*sizeof(float);
void *scratch = libxsmm_aligned_malloc(scratch_size, 2097152);
float* t_grad_output_bN = (float*)scratch;
float* t_grad_input_bN_l = t_grad_output_bN + go_bn;
float* t_input_bN_l = t_grad_input_bN_l + gi_bn;
float* t_f32_grad_wt_l = t_input_bN_l + in_bn;
float* t_f32_wt_l = t_f32_grad_wt_l + wts;
float *t_grad_output_rN=NULL, *t_grad_input_rN_l=NULL, *t_input_rN_l=NULL;
if(rn > 0)
{
t_grad_output_rN = t_f32_wt_l + wts;
t_grad_input_rN_l = t_grad_output_rN + go_rn;
t_input_rN_l = t_grad_input_rN_l + gi_rn;
}
float *t_grad_input_bN_r=NULL, *t_input_bN_r=NULL;
float *t_grad_input_rN_r=NULL, *t_input_rN_r=NULL;
float *t_f32_grad_wt_r=NULL, *t_f32_wt_r=NULL;
if(pskip)
{
if(rn > 0)
t_grad_input_bN_r = t_input_rN_l + in_rn;
else
t_grad_input_bN_r = t_f32_wt_l + wts;
t_input_bN_r = t_grad_input_bN_r + gi_bn;
t_f32_grad_wt_r = t_input_bN_r + in_bn;
t_f32_wt_r = t_f32_grad_wt_r + wts;
if(rn > 0)
{
t_grad_input_rN_r = t_f32_wt_r + wts;
t_input_rN_r = t_grad_input_rN_r + gi_rn;
}
}
DECL_VLA_PTR_PT(float, wt_l, [C], t_weights_l);
DECL_VLA_PTR_PT(float, grad_wt_l, [C], t_grad_weights_l);
float (*wt_r)[C] = pskip ? (float (*)[C])t_weights_r.data_ptr<float>() : NULL;
float (*grad_wt_r)[C] = pskip ? (float (*)[C])t_grad_weights_r.data_ptr<float>() : NULL;
DECL_VLA_PTR_PT(float, grad_output, [K], t_grad_output);
DECL_VLA_PTR_PT(float, input_l, [C], t_input_l);
DECL_VLA_PTR_PT(float, grad_input_l, [C], t_grad_input_l);
DECL_VLA_PTR_PT_CHECK_COND(pskip, float, input_r, [C], t_input_r);
DECL_VLA_PTR_PT_CHECK_COND(pskip, float, grad_input_r, [C], t_grad_input_r);
DECL_VLA_PTR(float, grad_output_bN, [nk][bn][bk], t_grad_output_bN);
DECL_VLA_PTR(float, grad_input_bN_l, [nc][bn][bc], t_grad_input_bN_l);
DECL_VLA_PTR(float, input_bN_l, [nc][bn][bc], t_input_bN_l);
DECL_VLA_PTR(float, wt_f32_l, [nc][bk][bc], t_f32_wt_l);
DECL_VLA_PTR(float, grad_wt_f32_l, [nc][bk][bc], t_f32_grad_wt_l);
float *grad_bias_l = t_grad_bias_l.data_ptr<float>();
DECL_VLA_PTR_CHECK_COND(pskip, float, grad_input_bN_r, [nc][bn][bc], t_grad_input_bN_r);
DECL_VLA_PTR_CHECK_COND(pskip, float, input_bN_r, [nc][bn][bc], t_input_bN_r);
DECL_VLA_PTR_CHECK_COND(pskip, float, wt_f32_r, [nc][bk][bc], t_f32_wt_r);
DECL_VLA_PTR_CHECK_COND(pskip, float, grad_wt_f32_r, [nc][bk][bc], t_f32_grad_wt_r);
float *grad_bias_r = pskip ? t_grad_bias_r.data_ptr<float>() : NULL;
DECL_VLA_PTR_CHECK_VAR(rn, float, grad_output_rN, [nk][rn][bk], t_grad_output_rN);
DECL_VLA_PTR_CHECK_VAR(rn, float, grad_input_rN_l, [nc][rn][bc], t_grad_input_rN_l);
DECL_VLA_PTR_CHECK_VAR(rn, float, input_rN_l, [nc][rn][bc], t_input_rN_l);
DECL_VLA_PTR_CHECK_COND_VAR(pskip, rn, float, grad_input_rN_r, [nc][rn][bc], t_grad_input_rN_r);
DECL_VLA_PTR_CHECK_COND_VAR(pskip, rn, float, input_rN_r, [nc][rn][bc], t_input_rN_r);
int dd = (bk % 32 == 0) ? bk/32 : bk/32 + 1;
int rd = (bk % 32 == 0) ? bk/32 : bk/32 + 1;
__mmask32 (*dropout_mask_bN)[nk][bn][dd] = (ptrain && pp > 0) ? (__mmask32 (*)[nk][bn][dd])(t_dropout_mask_bN.data_ptr()) : NULL;
__mmask32 (*dropout_mask_rN)[nk][rn][dd] = (ptrain && pp > 0 && rn > 0) ? (__mmask32 (*)[nk][rn][dd])(t_dropout_mask_rN.data_ptr()) : NULL;
__mmask32 (*relumask_bN)[nk][bn][rd] = pact==1 ? (__mmask32 (*)[nk][bn][rd])(t_relumask_bN.data_ptr()) : NULL;
__mmask32 (*relumask_rN)[nk][rn][rd] = (pact==1 && rn > 0) ? (__mmask32 (*)[nk][rn][rd])(t_relumask_rN.data_ptr()) : NULL;
copy_params.out.primary = t_f32_grad_wt_l;
zero(K*C, ©_params);
copy_params.out.primary = t_grad_weights_l.data_ptr<float>();
zero(K*C, ©_params);
copy_params.out.primary = t_grad_bias_l.data_ptr<float>();
zero(K, ©_params);
if(pskip)
{
copy_params.out.primary = t_f32_grad_wt_r;
zero(K*C, ©_params);
}
if(pskip)
{
copy_params.out.primary = t_grad_weights_r.data_ptr<float>();
zero(K*C, ©_params);
copy_params.out.primary = t_grad_bias_r.data_ptr<float>();
zero(K, ©_params);
}
// Get F32 copy of weights
for(int k=0; k<nk; k++) {
for(int c=0; c<nc; c++) {
copy_params.in.primary = &wt_l[k*bk][c*bc];
copy_params.out.primary = &wt_f32_l[k][c];
f32_copy(bk, bc, bc, bc, ©_params);
}
}
if(pskip)
{
for(int k=0; k<nk; k++) {
for(int c=0; c<nc; c++) {
copy_params.in.primary = &wt_r[k*bk][c*bc];
copy_params.out.primary = &wt_f32_r[k][c];
f32_copy(bk, bc, bc, bc, ©_params);
}
}
}
if(pskip)
{
#ifdef _OPENMP
#pragma omp parallel reduction(+: grad_wt_f32_l[:nk][:nc][:bk][:bc], grad_bias_l[:K], grad_wt_f32_r[:nk][:nc][:bk][:bc], grad_bias_r[:K])
#endif
{
int tid = omp_get_thread_num();
int threads = omp_get_max_threads();
int jobs = (nn % threads == 0) ? nn/threads : nn/threads + 1;
int tb = (tid*jobs < nn) ? tid*jobs : nn;
int te = ((tid+1)*jobs < nn) ? (tid+1)*jobs : nn;
libxsmm_meltw_unary_param relu_params;
libxsmm_meltw_unary_param dropout_params;
libxsmm_meltw_unary_param copy_params;
libxsmm_meltw_unary_param delbias_params;
for(int m=tb; m<te; m++) {
for(int k=0; k<nk; k++) {
if(ptrain && pp > 0) {
dropout_params.in.primary = &grad_output[m*bn][k*bk];
dropout_params.in.secondary = &dropout_mask_bN[m][k][0][0];
dropout_params.in.tertiary = &pp;
dropout_params.out.primary = &grad_output[m*bn][k*bk];
dropout_bwd_f32(bn, bk, &dropout_params, dropout_flags);
}
if(pact == 1) {
relu_params.in.primary = &grad_output[m*bn][k*bk];
relu_params.in.secondary = &relumask_bN[m][k][0][0];
relu_params.out.primary = &grad_output[m*bn][k*bk];
relu_bwd_f32(bn, bk, &relu_params);
}
copy_params.in.primary = &grad_output[m*bn][k*bk];
copy_params.out.primary = &grad_output_bN[tid][k];
f32_copy(bn, bk, nk*bk, nk*bk, ©_params);
}
int count=1;
brgemm_f32_f32(bn, bc, bk, bn*bk, 0, grad_output_bN[tid][0][0], wt_f32_l[0][0][0], grad_input_bN_l[tid][0][0], count, 0.0);
for(int c=0; c<nc; c++) {
copy_params.in.primary = &grad_input_bN_l[tid][c];
copy_params.out.primary = &grad_input_l[m*bn][c*bc];
f32_copy(bn, bc, nc*bc, nc*bc, ©_params);
}
brgemm_f32_f32(bn, bc, bk, bn*bk, 0, grad_output_bN[tid][0][0], wt_f32_r[0][0][0], grad_input_bN_r[tid][0][0], count, 0.0);
for(int c=0; c<nc; c++) {
copy_params.in.primary = &grad_input_bN_r[tid][c];
copy_params.out.primary = &grad_input_r[m*bn][c*bc];
f32_copy(bn, bc, nc*bc, nc*bc, ©_params);
}
for(int c=0; c<nc; c++) {
copy_params.in.primary = &input_l[m*bn][c*bc];
copy_params.out.primary = &input_bN_l[tid][c];
f32_copy(bn, bc, nc*bc, nc*bc, ©_params);
}
for(int c=0; c<nc; c++) {
copy_params.in.primary = &input_r[m*bn][c*bc];
copy_params.out.primary = &input_bN_r[tid][c];
f32_copy(bn, bc, nc*bc, nc*bc, ©_params);
}
count = 1;
brgemm_f32_f32(bk, bc, bn, bn*bk, bn*bc, grad_output_bN[tid][0][0], input_bN_l[tid][0][0], grad_wt_f32_l[0][0][0], count, 1.0, 't');
brgemm_f32_f32(bk, bc, bn, bn*bk, bn*bc, grad_output_bN[tid][0][0], input_bN_r[tid][0][0], grad_wt_f32_r[0][0][0], count, 1.0, 't');
for(int k=0; k<nk; k++) {
delbias_params.in.primary = &grad_output_bN[tid][k];
delbias_params.out.primary = grad_bias_l;
delbias_f32(bn, bk, bn, bk, &delbias_params);
}
copy_params.in.primary = grad_bias_l;
copy_params.out.primary = grad_bias_r;
f32_copy(1, K, K, K, ©_params);
}
}
}
else
{
#ifdef _OPENMP
#pragma omp parallel reduction(+: grad_wt_f32_l[:nk][:nc][:bk][:bc], grad_bias_l[:K])
#endif
{
int tid = omp_get_thread_num();
int threads = omp_get_max_threads();
int jobs = (nn % threads == 0) ? nn/threads : nn/threads + 1;
int tb = (tid*jobs < nn) ? tid*jobs : nn;
int te = ((tid+1)*jobs < nn) ? (tid+1)*jobs : nn;
libxsmm_meltw_unary_param relu_params;
libxsmm_meltw_unary_param dropout_params;
libxsmm_meltw_unary_param copy_params;
libxsmm_meltw_unary_param delbias_params;
for(int m=tb; m<te; m++) {
for(int k=0; k<nk; k++) {
if(ptrain && pp > 0) {
dropout_params.in.primary = &grad_output[m*bn][k*bk];
dropout_params.in.secondary = &dropout_mask_bN[m][k][0][0];
dropout_params.in.tertiary = &pp;
dropout_params.out.primary = &grad_output[m*bn][k*bk];
dropout_bwd_f32(bn, bk, &dropout_params, dropout_flags);
}
if(pact == 1) {
relu_params.in.primary = &grad_output[m*bn][k*bk];
relu_params.in.secondary = &relumask_bN[m][k][0][0];
relu_params.out.primary = &grad_output[m*bn][k*bk];
relu_bwd_f32(bn, bk, &relu_params);
}
copy_params.in.primary = &grad_output[m*bn][k*bk];
copy_params.out.primary = &grad_output_bN[tid][k];
f32_copy(bn, bk, nk*bk, nk*bk, ©_params);
}
int count = 1;
brgemm_f32_f32(bn, bc, bk, bn*bk, 0, grad_output_bN[tid][0][0], wt_f32_l[0][0][0], grad_input_bN_l[tid][0][0], count, 0.0);
for(int c=0; c<nc; c++) {
copy_params.in.primary = &grad_input_bN_l[tid][c];
copy_params.out.primary = &grad_input_l[m*bn][c*bc];
f32_copy(bn, bc, nc*bc, nc*bc, ©_params);
}
for(int c=0; c<nc; c++) {
copy_params.in.primary = &input_l[m*bn][c*bc];
copy_params.out.primary = &input_bN_l[tid][c];
f32_copy(bn, bc, nc*bc, nc*bc, ©_params);
}
count = 1;
brgemm_f32_f32(bk, bc, bn, bn*bk, bn*bc, grad_output_bN[tid][0][0], input_bN_l[tid][0][0], grad_wt_f32_l[0][0][0], count, 1.0, 't');
for(int k=0; k<nk; k++) {
delbias_params.in.primary = &grad_output_bN[tid][k];
delbias_params.out.primary = grad_bias_l;
delbias_f32(bn, bk, bn, bk, &delbias_params);
}
}
}
}
if(rn > 0)
{
//Single-thread portion of code--------------------------
// Dropout
if(ptrain && pp > 0)
{
for(int k=0; k<nk; k++) {
dropout_params.in.primary = &grad_output[nn*bn][k*bk];
dropout_params.in.secondary = &dropout_mask_rN[0][k][0][0];
dropout_params.in.tertiary = &pp;
dropout_params.out.primary = &grad_output[nn*bn][k*bk];
dropout_bwd_f32(rn, bk, &dropout_params, dropout_flags);
}
}
// ReLU
if(pact == 1)
{
for(int k=0; k<nk; k++) {
relu_params.in.primary = &grad_output[nn*bn][k*bk];
relu_params.in.secondary = &relumask_rN[0][k][0][0];
relu_params.out.primary = &grad_output[nn*bn][k*bk];
relu_bwd_f32(rn, bk, &relu_params);
}
}
int count=1;
//grad-input
for(int k=0; k<nk; k++) {
copy_params.in.primary = &grad_output[nn*bn][k*bk];
copy_params.out.primary = &grad_output_rN[0][k];
f32_copy(rn, bk, nk*bk, nk*bk, ©_params);
}
brgemm_f32_f32(rn, bc, bk, rn*bk, 0, grad_output_rN[0][0][0], wt_f32_l[0][0][0], grad_input_rN_l[0][0][0], count, 0.0);
for(int c=0; c<nc; c++) {
copy_params.in.primary = &grad_input_rN_l[0][c];
copy_params.out.primary = &grad_input_l[nn*bn][c*bc];
f32_copy(rn, bc, nc*bc, nc*bc, ©_params);
}
if(pskip)
{
brgemm_f32_f32(rn, bc, bk, rn*bk, 0, grad_output_rN[0][0][0], wt_f32_r[0][0][0], grad_input_rN_r[0][0][0], count, 0.0);
for(int c=0; c<nc; c++) {
copy_params.in.primary = &grad_input_rN_r[0][c];
copy_params.out.primary = &grad_input_r[nn*bn][c*bc];
f32_copy(rn, bc, nc*bc, nc*bc, ©_params);
}
}
//grad-weights
count = 1;
brgemm_f32_f32(bk, bc, rn, rn*bk, rn*bc, grad_output_rN[0][0][0], input_rN_l[0][0][0], grad_wt_f32_l[0][0][0], count, 1.0, 't');
if(pskip)
{
for(int c=0; c<nc; c++) {
copy_params.in.primary = &input_r[nn*bn][c*bc];
copy_params.out.primary = &input_rN_r[0][c];
f32_copy(rn, bc, nc*bc, nc*bc, ©_params);
}
count = 1;
brgemm_f32_f32(bk, bc, rn, rn*bk, rn*bc, grad_output_rN[0][0][0], input_rN_r[0][0][0], grad_wt_f32_r[0][0][0], count, 1.0, 't');
}
for(int k=0; k<nk; k++) {
delbias_params.in.primary = &grad_output_rN[0][k];
delbias_params.out.primary = grad_bias_l;
delbias_f32(rn, bk, rn, bk, &delbias_params);
}
if(pskip)
{
for(int k=0; k<nk; k++) {
delbias_params.in.primary = &grad_output_rN[0][k];
delbias_params.out.primary = grad_bias_r;
delbias_f32(rn, bk, rn, bk, &delbias_params);
}
}
}
for(int k=0; k<nk; k++) {
for(int c=0; c<nc; c++) {
copy_params.in.primary = &grad_wt_f32_l[k][c];
copy_params.out.primary = &grad_wt_l[k*bk][c*bc];
f32_copy(bk, bc, nc*bc, nc*bc, ©_params);
}
}
if(pskip)
{
for(int k=0; k<nk; k++) {
for(int c=0; c<nc; c++) {
copy_params.in.primary = &grad_wt_f32_r[k][c];
copy_params.out.primary = &grad_wt_r[k*bk][c*bc];
f32_copy(bk, bc, nc*bc, nc*bc, ©_params);
}
}
}
libxsmm_free(scratch);
return {t_grad_input_l, t_grad_input_r, t_grad_weights_l, t_grad_weights_r, t_grad_bias_l, t_grad_bias_r};
}
bool has_bias() {return pbias;}
bool has_skip() {return pskip;}
bool has_norm() {return pnorm;}
private:
long pN;
long pC;
long pK;
long pbn;
long pbc;
long pbk;
bool pbias;
bool pskip;
int pact;
bool pnorm;
float pp;
bool ptrain;
};
#endif
|
atomic-10.c | /* { dg-do run } */
/* { dg-options "-O2 -fopenmp" } */
extern void abort (void);
int x1, x2, x3, x4, x5;
volatile int y6 = 9, y2, y3, y4, y5;
volatile unsigned char z1, z2, z3, z4, z5;
float a1, a2, a3, a4;
void
f1 (void)
{
#pragma omp atomic
x1++;
#pragma omp atomic
x2--;
#pragma omp atomic
++x3;
#pragma omp atomic
--x4;
#pragma omp atomic
x5 += 1;
#pragma omp atomic
x1 -= y6;
#pragma omp atomic
x2 |= 1;
#pragma omp atomic
x3 &= 1;
#pragma omp atomic
x4 ^= 1;
#pragma omp atomic
x5 *= 3;
#pragma omp atomic
x1 /= 3;
#pragma omp atomic
x2 /= 3;
#pragma omp atomic
x3 <<= 3;
#pragma omp atomic
x4 >>= 3;
}
void
f2 (void)
{
#pragma omp atomic
y6++;
#pragma omp atomic
y2--;
#pragma omp atomic
++y3;
#pragma omp atomic
--y4;
#pragma omp atomic
y5 += 1;
#pragma omp atomic
y6 -= x1;
#pragma omp atomic
y2 |= 1;
#pragma omp atomic
y3 &= 1;
#pragma omp atomic
y4 ^= 1;
#pragma omp atomic
y5 *= 3;
#pragma omp atomic
y6 /= 3;
#pragma omp atomic
y2 /= 3;
#pragma omp atomic
y3 <<= 3;
#pragma omp atomic
y4 >>= 3;
}
void
f3 (void)
{
#pragma omp atomic
z1++;
#pragma omp atomic
z2--;
#pragma omp atomic
++z3;
#pragma omp atomic
--z4;
#pragma omp atomic
z5 += 1;
#pragma omp atomic
z1 |= 1;
#pragma omp atomic
z2 &= 1;
#pragma omp atomic
z3 ^= 1;
#pragma omp atomic
z4 *= 3;
#pragma omp atomic
z5 /= 3;
#pragma omp atomic
z1 /= 3;
#pragma omp atomic
z2 <<= 3;
#pragma omp atomic
z3 >>= 3;
}
void
f4 (void)
{
#pragma omp atomic
a1 += 8.0;
#pragma omp atomic
a2 *= 3.5;
#pragma omp atomic
a3 -= a1 + a2;
#pragma omp atomic
a4 /= 2.0;
}
int
main (void)
{
f1 ();
if (x1 != -2 || x2 != 0 || x3 != 8 || x4 != -1 || x5 != 3)
abort ();
f2 ();
if (y6 != 4 || y2 != 0 || y3 != 8 || y4 != -1 || y5 != 3)
abort ();
f3 ();
if (z1 != 0 || z2 != 8 || z3 != 0 || z4 != 253 || z5 != 0)
abort ();
a1 = 7;
a2 = 10;
a3 = 11;
a4 = 13;
f4 ();
if (a1 != 15.0 || a2 != 35.0 || a3 != -39.0 || a4 != 6.5)
abort ();
return 0;
}
|
offloading_success.c | // RUN: %libomptarget-compile-run-and-check-aarch64-unknown-linux-gnu
// RUN: %libomptarget-compile-run-and-check-powerpc64-ibm-linux-gnu
// RUN: %libomptarget-compile-run-and-check-powerpc64le-ibm-linux-gnu
// RUN: %libomptarget-compile-run-and-check-x86_64-pc-linux-gnu
// RUN: %libomptarget-compile-run-and-check-nvptx64-nvidia-cuda
#include <stdio.h>
#include <omp.h>
int main(void) {
int isHost = -1;
#pragma omp target map(from: isHost)
{ isHost = omp_is_initial_device(); }
if (isHost < 0) {
printf("Runtime error, isHost=%d\n", isHost);
}
// CHECK: Target region executed on the device
printf("Target region executed on the %s\n", isHost ? "host" : "device");
return isHost;
}
|
GB_unaryop__identity_int8_int32.c | //------------------------------------------------------------------------------
// GB_unaryop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2020, All Rights Reserved.
// http://suitesparse.com See GraphBLAS/Doc/License.txt for license.
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_iterator.h"
#include "GB_unaryop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB_unop__identity_int8_int32
// op(A') function: GB_tran__identity_int8_int32
// C type: int8_t
// A type: int32_t
// cast: int8_t cij = (int8_t) aij
// unaryop: cij = aij
#define GB_ATYPE \
int32_t
#define GB_CTYPE \
int8_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
int32_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = x ;
// casting
#define GB_CASTING(z, aij) \
int8_t z = (int8_t) aij ;
// cij = op (cast (aij))
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GB_GETA (aij, Ax, pA) ; \
/* Cx [pC] = op (cast (aij)) */ \
GB_CASTING (z, aij) ; \
GB_OP (GB_CX (pC), z) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_IDENTITY || GxB_NO_INT8 || GxB_NO_INT32)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__identity_int8_int32
(
int8_t *Cx, // Cx and Ax may be aliased
int32_t *Ax,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
GB_CAST_OP (p, p) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_tran__identity_int8_int32
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *GB_RESTRICT *Rowcounts,
GBI_single_iterator Iter,
const int64_t *GB_RESTRICT A_slice,
int naslice
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#define GB_PHASE_2_OF_2
#include "GB_unaryop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
blake2bp.c | /*
BLAKE2 reference source code package - reference C implementations
Copyright 2012, Samuel Neves <sneves@dei.uc.pt>. You may use this under the
terms of the CC0, the OpenSSL Licence, or the Apache Public License 2.0, at
your option. The terms of these licenses can be found at:
- CC0 1.0 Universal : http://creativecommons.org/publicdomain/zero/1.0
- OpenSSL license : https://www.openssl.org/source/license.html
- Apache 2.0 : http://www.apache.org/licenses/LICENSE-2.0
More information about the BLAKE2 hash function can be found at
https://blake2.net.
*/
#include <u.h>
#include <libc.h>
#include "blake2.h"
#include "blake2-impl.h"
#define PARALLELISM_DEGREE 4
/*
blake2b_init_param defaults to setting the expecting output length
from the digest_length parameter block field.
In some cases, however, we do not want this, as the output length
of these instances is given by inner_length instead.
*/
static int blake2bp_init_leaf_param( blake2b_state *S, const blake2b_param *P )
{
int err = blake2b_init_param(S, P);
S->outlen = P->inner_length;
return err;
}
static int blake2bp_init_leaf( blake2b_state *S, u64int outlen, u64int keylen, u64int offset )
{
blake2b_param P[1];
P->digest_length = (u8int)outlen;
P->key_length = (u8int)keylen;
P->fanout = PARALLELISM_DEGREE;
P->depth = 2;
store32( &P->leaf_length, 0 );
store32( &P->node_offset, offset );
store32( &P->xof_length, 0 );
P->node_depth = 0;
P->inner_length = BLAKE2B_OUTBYTES;
memset( P->reserved, 0, sizeof( P->reserved ) );
memset( P->salt, 0, sizeof( P->salt ) );
memset( P->personal, 0, sizeof( P->personal ) );
return blake2bp_init_leaf_param( S, P );
}
static int blake2bp_init_root( blake2b_state *S, u64int outlen, u64int keylen )
{
blake2b_param P[1];
P->digest_length = (u8int)outlen;
P->key_length = (u8int)keylen;
P->fanout = PARALLELISM_DEGREE;
P->depth = 2;
store32( &P->leaf_length, 0 );
store32( &P->node_offset, 0 );
store32( &P->xof_length, 0 );
P->node_depth = 1;
P->inner_length = BLAKE2B_OUTBYTES;
memset( P->reserved, 0, sizeof( P->reserved ) );
memset( P->salt, 0, sizeof( P->salt ) );
memset( P->personal, 0, sizeof( P->personal ) );
return blake2b_init_param( S, P );
}
int blake2bp_init( blake2bp_state *S, u64int outlen )
{
u64int i;
if( !outlen || outlen > BLAKE2B_OUTBYTES ) return -1;
memset( S->buf, 0, sizeof( S->buf ) );
S->buflen = 0;
S->outlen = outlen;
if( blake2bp_init_root( S->R, outlen, 0 ) < 0 )
return -1;
for( i = 0; i < PARALLELISM_DEGREE; ++i )
if( blake2bp_init_leaf( S->S[i], outlen, 0, i ) < 0 ) return -1;
S->R->last_node = 1;
S->S[PARALLELISM_DEGREE - 1]->last_node = 1;
return 0;
}
int blake2bp_init_key( blake2bp_state *S, u64int outlen, const void *key, u64int keylen )
{
u64int i;
if( !outlen || outlen > BLAKE2B_OUTBYTES ) return -1;
if( !key || !keylen || keylen > BLAKE2B_KEYBYTES ) return -1;
memset( S->buf, 0, sizeof( S->buf ) );
S->buflen = 0;
S->outlen = outlen;
if( blake2bp_init_root( S->R, outlen, keylen ) < 0 )
return -1;
for( i = 0; i < PARALLELISM_DEGREE; ++i )
if( blake2bp_init_leaf( S->S[i], outlen, keylen, i ) < 0 ) return -1;
S->R->last_node = 1;
S->S[PARALLELISM_DEGREE - 1]->last_node = 1;
{
u8int block[BLAKE2B_BLOCKBYTES];
memset( block, 0, BLAKE2B_BLOCKBYTES );
memcpy( block, key, keylen );
for( i = 0; i < PARALLELISM_DEGREE; ++i )
blake2b_update( S->S[i], block, BLAKE2B_BLOCKBYTES );
memset( block, 0, BLAKE2B_BLOCKBYTES ); /* Burn the key from stack */
}
return 0;
}
int blake2bp_update( blake2bp_state *S, const void *pin, u64int inlen )
{
const unsigned char * in = (const unsigned char *)pin;
u64int left = S->buflen;
u64int fill = sizeof( S->buf ) - left;
u64int i;
if( left && inlen >= fill )
{
memcpy( S->buf + left, in, fill );
for( i = 0; i < PARALLELISM_DEGREE; ++i )
blake2b_update( S->S[i], S->buf + i * BLAKE2B_BLOCKBYTES, BLAKE2B_BLOCKBYTES );
in += fill;
inlen -= fill;
left = 0;
}
#if defined(_OPENMP)
#pragma omp parallel shared(S), num_threads(PARALLELISM_DEGREE)
#else
for( i = 0; i < PARALLELISM_DEGREE; ++i )
#endif
{
#if defined(_OPENMP)
u64int i = omp_get_thread_num();
#endif
u64int inlen__ = inlen;
const unsigned char *in__ = ( const unsigned char * )in;
in__ += i * BLAKE2B_BLOCKBYTES;
while( inlen__ >= PARALLELISM_DEGREE * BLAKE2B_BLOCKBYTES )
{
blake2b_update( S->S[i], in__, BLAKE2B_BLOCKBYTES );
in__ += PARALLELISM_DEGREE * BLAKE2B_BLOCKBYTES;
inlen__ -= PARALLELISM_DEGREE * BLAKE2B_BLOCKBYTES;
}
}
in += inlen - inlen % ( PARALLELISM_DEGREE * BLAKE2B_BLOCKBYTES );
inlen %= PARALLELISM_DEGREE * BLAKE2B_BLOCKBYTES;
if( inlen > 0 )
memcpy( S->buf + left, in, inlen );
S->buflen = left + inlen;
return 0;
}
int blake2bp_final( blake2bp_state *S, void *out, u64int outlen )
{
u8int hash[PARALLELISM_DEGREE][BLAKE2B_OUTBYTES];
u64int i;
if(out == nil || outlen < S->outlen) {
return -1;
}
for( i = 0; i < PARALLELISM_DEGREE; ++i )
{
if( S->buflen > i * BLAKE2B_BLOCKBYTES )
{
u64int left = S->buflen - i * BLAKE2B_BLOCKBYTES;
if( left > BLAKE2B_BLOCKBYTES ) left = BLAKE2B_BLOCKBYTES;
blake2b_update( S->S[i], S->buf + i * BLAKE2B_BLOCKBYTES, left );
}
blake2b_final( S->S[i], hash[i], BLAKE2B_OUTBYTES );
}
for( i = 0; i < PARALLELISM_DEGREE; ++i )
blake2b_update( S->R, hash[i], BLAKE2B_OUTBYTES );
return blake2b_final( S->R, out, S->outlen );
}
int blake2bp( void *out, u64int outlen, const void *in, u64int inlen, const void *key, u64int keylen )
{
u8int hash[PARALLELISM_DEGREE][BLAKE2B_OUTBYTES];
blake2b_state S[PARALLELISM_DEGREE][1];
blake2b_state FS[1];
u64int i;
/* Verify parameters */
if ( nil == in && inlen > 0 ) return -1;
if ( nil == out ) return -1;
if( nil == key && keylen > 0 ) return -1;
if( !outlen || outlen > BLAKE2B_OUTBYTES ) return -1;
if( keylen > BLAKE2B_KEYBYTES ) return -1;
for( i = 0; i < PARALLELISM_DEGREE; ++i )
if( blake2bp_init_leaf( S[i], outlen, keylen, i ) < 0 ) return -1;
S[PARALLELISM_DEGREE - 1]->last_node = 1; /* mark last node */
if( keylen > 0 )
{
u8int block[BLAKE2B_BLOCKBYTES];
memset( block, 0, BLAKE2B_BLOCKBYTES );
memcpy( block, key, keylen );
for( i = 0; i < PARALLELISM_DEGREE; ++i )
blake2b_update( S[i], block, BLAKE2B_BLOCKBYTES );
memset( block, 0, BLAKE2B_BLOCKBYTES ); /* Burn the key from stack */
}
#if defined(_OPENMP)
#pragma omp parallel shared(S,hash), num_threads(PARALLELISM_DEGREE)
#else
for( i = 0; i < PARALLELISM_DEGREE; ++i )
#endif
{
#if defined(_OPENMP)
u64int i = omp_get_thread_num();
#endif
u64int inlen__ = inlen;
const unsigned char *in__ = ( const unsigned char * )in;
in__ += i * BLAKE2B_BLOCKBYTES;
while( inlen__ >= PARALLELISM_DEGREE * BLAKE2B_BLOCKBYTES )
{
blake2b_update( S[i], in__, BLAKE2B_BLOCKBYTES );
in__ += PARALLELISM_DEGREE * BLAKE2B_BLOCKBYTES;
inlen__ -= PARALLELISM_DEGREE * BLAKE2B_BLOCKBYTES;
}
if( inlen__ > i * BLAKE2B_BLOCKBYTES )
{
const u64int left = inlen__ - i * BLAKE2B_BLOCKBYTES;
const u64int len = left <= BLAKE2B_BLOCKBYTES ? left : BLAKE2B_BLOCKBYTES;
blake2b_update( S[i], in__, len );
}
blake2b_final( S[i], hash[i], BLAKE2B_OUTBYTES );
}
if( blake2bp_init_root( FS, outlen, keylen ) < 0 )
return -1;
FS->last_node = 1; /* Mark as last node */
for( i = 0; i < PARALLELISM_DEGREE; ++i )
blake2b_update( FS, hash[i], BLAKE2B_OUTBYTES );
return blake2b_final( FS, out, outlen );;
}
#if defined(BLAKE2BP_SELFTEST)
#include <string.h>
#include "blake2-kat.h"
int main( void )
{
u8int key[BLAKE2B_KEYBYTES];
u8int buf[BLAKE2_KAT_LENGTH];
u64int i, step;
for( i = 0; i < BLAKE2B_KEYBYTES; ++i )
key[i] = ( u8int )i;
for( i = 0; i < BLAKE2_KAT_LENGTH; ++i )
buf[i] = ( u8int )i;
/* Test simple API */
for( i = 0; i < BLAKE2_KAT_LENGTH; ++i )
{
u8int hash[BLAKE2B_OUTBYTES];
blake2bp( hash, BLAKE2B_OUTBYTES, buf, i, key, BLAKE2B_KEYBYTES );
if( 0 != memcmp( hash, blake2bp_keyed_kat[i], BLAKE2B_OUTBYTES ) )
{
goto fail;
}
}
/* Test streaming API */
for(step = 1; step < BLAKE2B_BLOCKBYTES; ++step) {
for (i = 0; i < BLAKE2_KAT_LENGTH; ++i) {
u8int hash[BLAKE2B_OUTBYTES];
blake2bp_state S;
u8int * p = buf;
u64int mlen = i;
int err = 0;
if( (err = blake2bp_init_key(&S, BLAKE2B_OUTBYTES, key, BLAKE2B_KEYBYTES)) < 0 ) {
goto fail;
}
while (mlen >= step) {
if ( (err = blake2bp_update(&S, p, step)) < 0 ) {
goto fail;
}
mlen -= step;
p += step;
}
if ( (err = blake2bp_update(&S, p, mlen)) < 0) {
goto fail;
}
if ( (err = blake2bp_final(&S, hash, BLAKE2B_OUTBYTES)) < 0) {
goto fail;
}
if (0 != memcmp(hash, blake2bp_keyed_kat[i], BLAKE2B_OUTBYTES)) {
goto fail;
}
}
}
print("ok\n");
exits(nil);
return 0;
fail:
print("error\n");
return -1;
}
#endif
|
optimized_cluster_tree.h | #pragma once
#include "bct_kernel_type.h"
#include "optimized_bct_types.h"
namespace rsurfaces
{
struct BVHSettings
{
mint split_threshold = 8;
// bool use_old_prepost = false;
// TreePercolationAlgorithm tree_perc_alg = TreePercolationAlgorithm::Chunks;
// TreePercolationAlgorithm tree_perc_alg = TreePercolationAlgorithm::Tasks;
TreePercolationAlgorithm tree_perc_alg = TreePercolationAlgorithm::Sequential;
};
// a global instance to store default settings
extern BVHSettings BVHDefaultSettings;
struct Cluster2 // slim POD container to hold only the data relevant for the construction phase in the tree, before it is serialized
{
public:
Cluster2(){};
~Cluster2(){
// delete left;
// delete right;
};
Cluster2(mint begin_, mint end_, mint depth_);
mint begin = 0; // position of first triangle in cluster relative to array ordering
mint end = 0; // position behind last triangle in cluster relative to array ordering
mint depth = 0; // depth within the tree -- not absolutely necessary but nice to have for plotting images
mint max_depth = 0; // used to compute the maximal depth in the tree
mint descendant_count = 0;
mint descendant_leaf_count = 0;
Cluster2 *left = nullptr;
Cluster2 *right = nullptr;
}; //Cluster2
class OptimizedClusterTree // binary cluster tree; layout mostly in Struct of Array fashion in order to prepare SIMDization. Note SIMDized, yet, though.
{
public:
OptimizedClusterTree(){};
// Solving interface problems by using standard types
// This way, things are easier to port. For example, I can call this from Mathematica for faster debugging.
OptimizedClusterTree(
const mreal * restrict const P_coords_, // coordinates per primitive used for clustering; assumed to be of size primitive_count x dim
const mint primitive_count_,
const mint dim_,
const mreal * restrict const P_hull_coords_, // points that define the convex hulls of primitives; assumed to be array of size primitive_count x hull_count x dim
const mint hull_count_,
const mreal * restrict const P_near_, // data used actual interaction computation; assumed to be of size primitive_count x near_dim. For a triangle mesh in 3D, we want to feed each triangles i), area ii) barycenter and iii) normal as a 1 + 3 + 3 = 7 vector
const mint near_dim_,
const mreal * restrict const P_far_, // data used actual interaction computation; assumed to be of size primitive_count x far_dim. For a triangle mesh in 3D, we want to feed each triangles i), area ii) barycenter and iii) orthoprojector onto normal space as a 1 + 3 + 6 = 10 vector
const mint far_dim_,
// const mreal * const restrict P_moments_, // Interface to deal with higher order multipole expansion. Not used, yet.
// const mint moment_count_,
const mint * restrict const ordering_, // A suggested preordering of primitives; this gets applied before the clustering begins in the hope that this may improve the sorting within a cluster --- at least in the top level(s). This could, e.g., be the ordering obtained by a tree for similar data set.
MKLSparseMatrix &DiffOp,
MKLSparseMatrix &AvOp,
BVHSettings settings_ = BVHDefaultSettings
);
mint dim = 3;
mint near_dim = 7; // = 1 + 3 + 3 for weight, center, normal, stored consecutively
mint far_dim = 10; // = 1 + 3 + 3 * (3 + 1)/2 for weight, center, projector, stored consecutively
mint hull_count = 3;
mint tree_thread_count = 1;
mint thread_count = 1;
mint primitive_count = 0;
mint cluster_count = 0;
mint leaf_cluster_count = 0;
mint max_buffer_dim = 0;
mint buffer_dim = 0;
// mint moment_count = 22;
BVHSettings settings;
mint *restrict P_ext_pos = nullptr; // Reordering of primitives; crucial for communication with outside world
mint *restrict inverse_ordering = nullptr; // Inverse ordering of the above; crucial for communication with outside world
// A_Vector<mint> P_leaf; // Index of the leaf cluster to which the primitive belongs
// "C_" stands for "cluster", "P_" stands for "primitive"
mint *restrict C_begin = nullptr;
mint *restrict C_end = nullptr;
mint *restrict C_depth = nullptr;
mint *restrict C_next = nullptr;
mint *restrict C_left = nullptr; // list of index of left children; entry is -1 if no child is present
mint *restrict C_right = nullptr; // list of index of right children; entry is -1 if no child is present
bool *restrict C_is_chunk_root = nullptr;
// Primitive double data, stored in Structure of Arrays fashion
A_Vector<mreal *> P_near; //weight, center, normal, stored consecutively; assumed to be matrix of size near_dim x primitive_count!
A_Vector<mreal *> P_far; //weight, center, projector, stored consecutively; assumed to be matrix of size far_dim x primitive_count!
A_Vector<mreal *> P_coords; //clustering coordinates, stored as dim x primitive_count matrix
A_Vector<mreal *> P_min; //lower bounding box point, stored as dim x primitive_count matrix
A_Vector<mreal *> P_max; //upper bounding box point, stored as dim x n matrix
// A_Vector<mreal * restrict> P_moments;
mreal *restrict P_in = nullptr;
mreal *restrict P_out = nullptr;
// mreal * restrict P_moment_buffer = nullptr;
// Cluster double data, stored in Structure of Arrays fashion
A_Vector<mreal *> C_far; //weight, center, normal, stored consecutively; assumed to be matrix of size data_dim x n
A_Vector<mreal *> C_coords; //clustering coordinate
A_Vector<mreal *> C_min;
A_Vector<mreal *> C_max;
// A_Vector<mreal * restrict> C_moments;
mreal *restrict C_in = nullptr;
mreal *restrict C_out = nullptr;
// mreal * restrict C_moment_buffer = nullptr;
mreal *restrict C_squared_radius = nullptr;
mint *restrict leaf_clusters = nullptr;
mint *restrict leaf_cluster_lookup = nullptr;
mint *restrict leaf_cluster_ptr = nullptr; // point to __end__ of each leaf cluster
A_Vector<A_Vector<mreal>> P_D_near;
A_Vector<A_Vector<mreal>> P_D_far;
A_Vector<A_Vector<mreal>> C_D_far;
// mint scratch_size = 12;
// A_Vector<A_Vector<mreal>> scratch;
MKLSparseMatrix hi_pre;
MKLSparseMatrix hi_post;
MKLSparseMatrix lo_pre;
MKLSparseMatrix lo_post;
MKLSparseMatrix P_to_C;
MKLSparseMatrix C_to_P;
A_Vector<A_Vector<mint>> chunk_roots;
mint tree_max_depth = 0;
bool chunks_prepared = false;
~OptimizedClusterTree()
{;
ptic("~OptimizedClusterTree");
// pointer arrays come at the cost of manual deallocation...
#pragma omp parallel
{
#pragma omp single
{
// #pragma omp task
// {
// for( mint k = 0; k < moment_count; ++ k )
// {
// safe_free(P_moments[k]);
// }
// }
//
// #pragma omp task
// {
// for( mint k = 0; k < moment_count; ++ k )
// {
// safe_free(C_moments[k]);
// }
// }
#pragma omp task
{
for (mint k = 0; k < static_cast<mint>(P_coords.size()); ++k)
{
safe_free(P_coords[k]);
}
}
#pragma omp task
{
for (mint k = 0; k < static_cast<mint>(C_coords.size()); ++k)
{
safe_free(C_coords[k]);
}
}
#pragma omp task
{
for (mint k = 0; k < static_cast<mint>(P_near.size()); ++k)
{
safe_free(P_near[k]);
}
}
#pragma omp task
{
for (mint k = 0; k < static_cast<mint>(C_far.size()); ++k)
{
safe_free(C_far[k]);
}
}
#pragma omp task
{
for (mint k = 0; k < static_cast<mint>(P_min.size()); ++k)
{
safe_free(P_min[k]);
}
}
#pragma omp task
{
for (mint k = 0; k < static_cast<mint>(P_max.size()); ++k)
{
safe_free(P_max[k]);
}
}
#pragma omp task
{
for (mint k = 0; k < static_cast<mint>(C_min.size()); ++k)
{
safe_free(C_min[k]);
}
}
#pragma omp task
{
for (mint k = 0; k < static_cast<mint>(C_max.size()); ++k)
{
safe_free(C_max[k]);
}
}
#pragma omp task
{
safe_free(P_in);
}
#pragma omp task
{
safe_free(P_out);
}
#pragma omp task
{
safe_free(C_in);
}
#pragma omp task
{
safe_free(C_out);
}
#pragma omp task
{
safe_free(C_squared_radius);
}
#pragma omp task
{
safe_free(leaf_clusters);
}
#pragma omp task
{
safe_free(leaf_cluster_lookup);
}
#pragma omp task
{
safe_free(leaf_cluster_ptr);
}
#pragma omp task
{
safe_free(inverse_ordering);
}
#pragma omp task
{
safe_free(P_ext_pos);
}
#pragma omp task
{
safe_free(C_begin);
}
#pragma omp task
{
safe_free(C_end);
}
#pragma omp task
{
safe_free(C_depth);
}
#pragma omp task
{
safe_free(C_next);
}
#pragma omp task
{
safe_free(C_left);
}
#pragma omp task
{
safe_free(C_right);
}
#pragma omp task
{
safe_free(C_is_chunk_root);
}
}
}
ptoc("~OptimizedClusterTree");
};
void SplitCluster(Cluster2 * const C, const mint free_thread_count);
void Serialize(Cluster2 * const C, const mint ID, const mint leaf_before_count, const mint free_thread_count);
void ComputePrimitiveData(
const mreal * restrict const P_hull_coords_,
const mreal * restrict const P_near_,
const mreal * restrict const P_far_
// , const mreal * const restrict P_moments_
); // copy, reordering and computing bounding boxes
void ComputeClusterData();
void RequireBuffers(const mint cols);
void ComputePrePost(MKLSparseMatrix &DiffOp, MKLSparseMatrix &AvOp);
void CleanseBuffers();
void CleanseD();
void Pre(Eigen::MatrixXd &input, BCTKernelType type);
void Pre(mreal *input, const mint cols, BCTKernelType type);
void Post(Eigen::MatrixXd &output, BCTKernelType type, bool addToResult = false);
void Post(mreal *output, const mint cols, BCTKernelType type, bool addToResult = false);
void PercolateUp();
void PercolateDown();
void RequireChunks();
// some prototype
void PercolateUp_Chunks();
void percolateUp_Tip( const mint C);
// some prototype
void PercolateDown_Chunks();
void percolateDown_Tip( const mint C);
// TODO: Not nearly as fast as I'd like it to be; not scalable!
// recusive algorithm parallelized by OpenMP tasks
void PercolateUp_Tasks(const mint C, const mint free_thread_count);
// TODO: Not nearly as fast as I'd like it to be; not scalable!
// recusive algorithm parallelized by OpenMP tasks
void PercolateDown_Tasks(const mint C, const mint free_thread_count);
// TODO: use a stack for recursion instead of the program stack?
// sequential, recursive algorithm
void PercolateUp_Seq(const mint C);
// TODO: use a stack for recursion instead of the program stack?
// sequential, recursive algorithm
void PercolateDown_Seq(const mint C);
void CollectDerivatives( mreal * restrict const P_D_near_output ); // collect only near field data
void CollectDerivatives( mreal * restrict const P_D_near_output, mreal * restrict const P_D_far_output );
// Updates only the computational data (primitive/cluster areas, centers of mass and normals).
// All data related to clustering or multipole acceptance criteria remain are unchanged, as well
// as the preprocessor and postprocessor matrices (that are needed for matrix-vector multiplies of the BCT.)
void SemiStaticUpdate( const mreal * restrict const P_near_, const mreal * restrict const P_far_ );
void PrintToFile(std::string filename = "./OptimizedClusterTree.tsv");
private:
void computeClusterData(const mint C, const mint free_thread_count); // helper function for ComputeClusterData
bool requireChunks( mint C, mint last, mint thread);
}; //OptimizedClusterTree
} // namespace rsurfaces
|
md5test.c | /***
* How to compile:
* GCC 4.6.3: gcc -fopenmp -o md5test md5test.c -lcrypto -lssl -std=c99
* GCC 6.3.0: gcc -fopenmp -o md5test md5test.c -lcrypto -lssl
**/
#include <stdio.h>
#include <stdlib.h>
#include <stdbool.h>
#include <string.h>
#include <assert.h>
#include <openssl/md5.h>
#include <omp.h>
#define NUMBER_OF_BOOKS 30
typedef struct Line1 {
char* str;
unsigned char* md5;
} Line;
typedef struct Book1 {
int number;
size_t lines_len;
Line* lines;
} Book;
char* file_to_str(char* filepath, char* filename) {
// https://stackoverflow.com/questions/3747086/reading-the-whole-text-file-into-a-char-array-in-c
FILE* fp = fopen(filepath, "rb");
long lSize;
char* buffer;
if (!fp) {
perror(filename);
exit(1);
}
fseek(fp, 0L, SEEK_END);
lSize = ftell(fp);
rewind(fp);
/* allocate memory for entire content */
buffer = calloc(1, lSize + 1);
if (!buffer) {
fclose(fp);
fputs("memory alloc fails", stderr);
exit(1);
}
/* copy the file into the buffer */
if (1 != fread(buffer, lSize, 1, fp)) {
fclose(fp);
free(buffer);
fputs("entire read fails", stderr);
exit(1);
}
fclose(fp);
return buffer;
}
void md5_print(unsigned char* result) {
for (int i = 0; i < MD5_DIGEST_LENGTH; i++)
printf("%02x", *(result + i));
printf("\n");
}
unsigned char* str_to_md5(char* str) {
unsigned char* result = (unsigned char*) malloc(MD5_DIGEST_LENGTH*sizeof(unsigned char));
MD5(str, strlen(str), result);
return result;
}
char** str_split(char* a_str, const char a_delim, size_t* len) {
// https://stackoverflow.com/questions/9210528/split-string-with-delimiters-in-c
char** result = 0;
size_t count = 0;
char* tmp = a_str;
char* last_comma = 0;
char delim[2];
delim[0] = a_delim;
delim[1] = 0;
/* Count how many elements will be extracted. */
while (*tmp) {
if (a_delim == *tmp) {
count++;
last_comma = tmp;
}
tmp++;
}
/* Add space for trailing token. */
count += last_comma < (a_str + strlen(a_str) - 1);
/* Add space for terminating null string so caller
knows where the list of returned strings ends. */
count++;
result = malloc(sizeof(char*) * count);
if (result) {
size_t idx = 0;
*len = 0;
char* token = strtok(a_str, delim);
while (token) {
*(result + idx++) = strdup(token);
if (strlen(token) > 1)
(*len)++;
token = strtok(0, delim);
}
*(result + idx) = 0;
}
return result;
}
char* load_book_i(int i) {
char filepath[25];
char filename[8];
sprintf(filepath, "plain_text_books/%d.txt", i);
sprintf(filename, "%d.txt", i);
char* whole_text = file_to_str(filepath, filename);
return whole_text;
}
void books_print(Book* books) {
for (int i = 0; i < NUMBER_OF_BOOKS; i++) {
printf("Book %d; total lines %lu\n", books[i].number, books[i].lines_len);
for (int j = 0; j < books[i].lines_len; j++) {
Line* line = &(books[i].lines[j]);
printf("Book %d; line %d of %lu: %s\n", books[i].number, j+1, books[i].lines_len, line->str);
md5_print(line->md5);
}
}
}
bool md5_equals(unsigned char* md5_a, unsigned char* md5_b) {
for (int i = 0; i < MD5_DIGEST_LENGTH; i++)
if (*(md5_a + i) != *(md5_b + i))
return false;
return true;
}
int find_line_in_books(Book* books, char* line_str) {
unsigned char* md5 = str_to_md5(line_str);
int book_number = 0;
#pragma omp parallel shared(md5, book_number)
#pragma omp for schedule (dynamic)
for (int i = 0; i < NUMBER_OF_BOOKS; i++) {
for (int j = 0; j < books[i].lines_len; j++) {
Line* line = &(books[i].lines[j]);
if (book_number != 0) {
break;
} else if (md5_equals(md5, line->md5)) {
#pragma omp atomic
book_number += books[i].number;
}
}
}
free(md5);
return book_number;
}
void find_all_lines_in_books(Book* books) {
for (int i = 0; i < NUMBER_OF_BOOKS; i++) {
printf("\rBook %d of %d", i+1, NUMBER_OF_BOOKS);
fflush(stdout);
for (int j = 0; j < books[i].lines_len; j++) {
Line* line = &(books[i].lines[j]);
char* line_str = line->str;
int book_number = find_line_in_books(books, line_str);
}
}
printf("\n");
}
void free_books(Book* books) {
for (int i = 0; i < NUMBER_OF_BOOKS; i++) {
for (int j = 0; j < books[i].lines_len; j++) {
Line* line = &(books[i].lines[j]);
char* line_str = line->str;
unsigned char* md5 = line->md5;
free(md5);
free(line_str);
}
Line* lines = &(books[i].lines);
// free(lines); // TODO: Freeing all lines structs not working
}
}
void update_book(Book* book, char* whole_text) {
size_t len;
char** lines = str_split(whole_text, '\n', &len);
book->lines_len = len;
book->lines = (Line*) malloc(len*sizeof(Line));
if (lines) {
int count = 0;
int j;
for (j = 0; *(lines + j); j++) {
if (strlen(*(lines + j)) > 1) {
Line* line = &(book->lines[count++]);
line->str = *(lines + j);
line->md5 = str_to_md5(*(lines + j));
}
}
}
}
int main(int argc, const char** argv) {
if (argc < 2) {
printf("Usage %s <number_of_threads>\n", argv[0]);
exit(0);
}
printf("Number of processors: %d\n", omp_get_num_procs());
const int NUM_THREADS = atoi(argv[1]);
omp_set_num_threads(NUM_THREADS);
printf("Number of threads: %d\n", NUM_THREADS);
Book books[NUMBER_OF_BOOKS];
for (int i = 1; i <= NUMBER_OF_BOOKS; i++) {
books[i-1].number = i;
char* whole_text = load_book_i(i);
update_book(&(books[i-1]), whole_text);
free(whole_text);
}
books_print(&books);
double starttime, stoptime;
starttime = omp_get_wtime();
find_all_lines_in_books(&books);
stoptime = omp_get_wtime();
printf("Execution time: %3.2f s\n", stoptime-starttime);
free_books(&books);
return EXIT_SUCCESS;
}
|
test.c | #include <stdio.h>
#include <omp.h>
#include "../utilities/check.h"
#include "../utilities/utilities.h"
#define TRIALS (1)
#define N (992)
#define INIT() INIT_LOOP(N, {C[i] = 1; D[i] = i; E[i] = -i;})
#define ZERO(X) ZERO_ARRAY(N, X)
int main(void) {
check_offloading();
double A[N], B[N], C[N], D[N], E[N];
double *ptrA = &A[0];
unsigned long long addr1;
unsigned long long addr2;
INIT();
//
// Test: Master.
//
for (int t = 0; t < TRIALS; t++) {
int threads[1];
threads[0] = t;
// init
for (int i = 0; i < N; i++) {
A[i] = 1.0;
}
// compute
#pragma omp target data map(A)
{
#pragma omp target data map(B) use_device_ptr(ptrA)
{
addr1 = (unsigned long long)((void *) ptrA);
#pragma omp target is_device_ptr(ptrA) map(to: D, E) map(from: addr2)
{
addr2 = (unsigned long long)((void *) ptrA);
for (int i = 0; i < N; i++) {
ptrA[i] += D[i] - E[i];
}
}
}
}
int error = 0;
if (addr1 != addr2)
printf("Address of A: 0x%llx, ptrA on host 0x%llx, in use device 0x%llx, "
"on device 0x%llx, error %d\n", (unsigned long long)((void *)&A[0]),
(unsigned long long)((void *) ptrA), addr1, addr2, ++error);
for (int i = 0; i < N; i++) {
if (A[i] != 2.0*i+1.0)
printf("%d: got %f, wanted %f, error %d\n", i, A[i], 2.0*i+1.0,
++error);
}
if (error)
printf("Failed with %d errors\n", error);
else
printf("Success\n");
}
return 0;
}
|
stTree.h | #ifndef _STTREE_H__
#define _STTREE_H__
#include <cassert>
#include <vector>
#include <algorithm>
#include <fstream>
#include <iostream>
#include <map>
#include <utility>
#include <util.h>
#include "binTree.h"
using namespace std;
/* ************************************************** */
class stNode;
//class binData;
class stTree;
typedef stNode* pstNode;
//typedef binData* pbinData;
typedef stTree* pstTree;
/* ************************************************** */
// Auxiliary data structure to hold point coords (X), their dimension (dim) and global ids.
/*struct binData {
int dim; // Dimensionality of points.
vector<double> X; // Data point coordinates.
vector<long> gids; // global ids of points.
vector<long> lids; // local ids of points
// - Methods
void Copy(pbinData data){
X.resize( data->X.size() );
gids.resize( data->gids.size() );
lids.resize( data->lids.size() );
dim = data->dim;
int npoints = data->gids.size();
#pragma omp parallel if(npoints > 1000)
{
#pragma omp parallel for schedule(dynamic,256)
for(int i=0; i< npoints*data->dim; i++) X[i] = data->X[i];
#pragma omp parallel for schedule(dynamic,256)
for(int i=0; i<npoints; i++) gids[i] = data->gids[i];
}
if(data->lids.size() > 0) {
#pragma omp parallel if(npoints > 1000)
{
#pragma omp parallel for schedule(dynamic,256)
for(int i=0; i<npoints; i++) lids[i] = data->lids[i];
}
}
}
};*/
class stNode {
public:
int lnid; // local node id, on every level from left to right, 0, 1, 2, ..., 2^level-1
int level; // level of the node. Root is level 0.
//vector<double> matR; // rotation matrix on this level
vector<double> rw; // workspace for fast rotation
vector<double> proj; // projection direction
int coord_mv; // coorid with maximum variance
double median; // median of projected values
pstNode parent; // Pointer to parent
pstNode leftNode; // the next level
pstNode rightNode;
//------------- Methods
// default constructor
stNode() : level(0),lnid(0),median(0),parent(NULL),leftNode(NULL),rightNode(NULL) {;}
// Constructor. Must be used for non-root nodes.
stNode(int id) : level(0),lnid(id),median(0),parent(NULL),leftNode(NULL),rightNode(NULL) {;}
};
class stTree {
public:
pstNode root;
vector<pbinData> leafRefArr;
int numof_ref_points_in_tree; // total number of ref points in this tree
int depth;
struct Options{
string splitter; // "rsmt" or "rkdt"
int debug_verbose; // print out debug info
int timing_verbose; // print out timming info.
int flag_r; // do not rotation (0), rotate only at root (1), rotate on all levels (2)
// method
Options() : splitter("rsmt"),debug_verbose(false),timing_verbose(false),flag_r(0) {;}
void Copy(Options o) {
splitter = o.splitter;
debug_verbose = o.debug_verbose;
timing_verbose = o.timing_verbose;
flag_r = o.flag_r;
}
};
Options options; // This nodes Options object.
stTree() : root(NULL),depth(0) {;}
~stTree();
void build(pbinData inData, int minp, int maxlev);
void recoverData(pbinData outData);
void queryGreedy(pbinData queryData, int k, vector< pair<double, long> > &results);
void queryGreedy_a2a(int k, vector< pair<double, long> > &results);
void querySampling(pbinData queryData, int k, vector< pair<double, long> > &results);
void destroy_tree(pstNode node);
void insert(pstNode in_parent, pstNode inNode, pbinData inData, int minp, int maxlev);
static void mean(double *points, int numof_points, int dim, double *mu);
void parvar(double *points, int numof_points, int dim, double *mean, double *var);
void maxvarProjection(double *points, int numof_points, int dim, int &mvind, double *pv);
void furthestPoint(double *points, int numof_points, int dim, double *query, double *furP);
void mtreeProjection(double * points, int numof_points, int dim, double * proj, double *pv);
//void assignMembership(const vector<double>& px,
// double &median, vector<int>& leftkid_membership, vector<int>& rightkid_membership);
double select(vector<double> &arr, int ks);
void assignMembership(const vector<double>& px, double median,
vector<int> &leftkid_membership, vector<int>& rightkid_membership);
void copyData(pbinData inData, vector<int>& membership, pbinData outData);
int visitGreedy(double *point, int dim, pstNode node);
void randperm(int m, int N, vector<int>& arr);
void sampleNode(pstNode node, vector<double> &samples);
void visitSampling(pbinData data, pstNode node, int *membership);
};
#endif
|
GB_unaryop__lnot_bool_uint8.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_bool_uint8
// op(A') function: GB_tran__lnot_bool_uint8
// C type: bool
// A type: uint8_t
// cast: bool cij = (bool) aij
// unaryop: cij = !aij
#define GB_ATYPE \
uint8_t
#define GB_CTYPE \
bool
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
uint8_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) \
bool z = (bool) 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_BOOL || GxB_NO_UINT8)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__lnot_bool_uint8
(
bool *restrict Cx,
const uint8_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_bool_uint8
(
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
|
parallel.h | #ifndef PARALLEL_H_
#define PARALLEL_H_
#include <algorithm>
#include <functional>
#include <vector>
class Parallel {
public:
Parallel(int argc, char** argv) {
(void)argc;
(void)argv;
};
virtual ~Parallel() = default;
virtual bool is_master() const = 0;
virtual int get_proc_id() const = 0;
virtual int get_n_procs() const = 0;
virtual int get_n_threads() const = 0;
virtual void barrier() = 0;
virtual void reduce_to_sum(unsigned long long& value) = 0;
virtual void reduce_to_sum(double& value) = 0;
virtual void reduce_to_sum_vector(std::vector<unsigned long long>& value) = 0;
virtual void reduce_to_sum_vector(std::vector<double>& value) = 0;
virtual void reduce_to_sum_vector(std::vector<long double>& value) = 0;
};
#pragma omp declare reduction( \
vec_double_plus : std::vector < \
double > : std::transform( \
omp_out \
.begin(), omp_out.end(), omp_in.begin(), omp_out.begin(), std::plus < double > ())) initializer(omp_priv = omp_orig)
#endif
|
lis_matvec_bsr.c | /* Copyright (C) 2002-2012 The SSI Project. All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.
3. Neither the name of the 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 SCALABLE SOFTWARE INFRASTRUCTURE PROJECT
``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 SCALABLE SOFTWARE INFRASTRUCTURE
PROJECT 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.
*/
#ifdef HAVE_CONFIG_H
#include "lis_config.h"
#else
#ifdef HAVE_CONFIG_WIN32_H
#include "lis_config_win32.h"
#endif
#endif
#include <stdio.h>
#include <stdlib.h>
#ifdef HAVE_MALLOC_H
#include <malloc.h>
#endif
#include <string.h>
#include <stdarg.h>
#ifdef _OPENMP
#include <omp.h>
#endif
#ifdef USE_MPI
#include <mpi.h>
#endif
#include "lislib.h"
LIS_MATVEC_XXX lis_matvec_bsr_xxx[4][4] = {
{lis_matvec_bsr_1x1, lis_matvec_bsr_1x2, lis_matvec_bsr_1x3, lis_matvec_bsr_1x4},
{lis_matvec_bsr_2x1, lis_matvec_bsr_2x2, lis_matvec_bsr_2x3, lis_matvec_bsr_2x4},
{lis_matvec_bsr_3x1, lis_matvec_bsr_3x2, lis_matvec_bsr_3x3, lis_matvec_bsr_3x4},
{lis_matvec_bsr_4x1, lis_matvec_bsr_4x2, lis_matvec_bsr_4x3, lis_matvec_bsr_4x4}
};
void lis_matvec_bsr(LIS_MATRIX A, LIS_SCALAR x[], LIS_SCALAR y[])
{
LIS_INT i,j,k;
LIS_INT bi,bj,bc,bs;
LIS_INT nr,nc,bnr,bnc;
LIS_INT n;
n = A->n;
nr = A->nr;
nc = A->nc;
bnr = A->bnr;
bnc = A->bnc;
bs = bnr*bnc;
if( A->is_splited )
{
#ifdef _OPENMP
#pragma omp parallel for private(i)
#endif
for(i=0; i<n; i++)
{
y[i] = 0.0;
}
#ifdef _OPENMP
#pragma omp parallel for private(i,j,k,bi,bj,bc)
#endif
for(bi=0;bi<nr;bi++)
{
k = bi*bs;
for(j=0;j<bnc;j++)
{
for(i=0;i<bnr;i++)
{
y[bi*bnr+i] += A->D->value[k] * x[bi*bnr+j];
k++;
}
}
for(bc=A->L->bptr[bi];bc<A->L->bptr[bi+1];bc++)
{
bj = A->L->bindex[bc] * bnc;
k = bc*bs;
for(j=0;j<bnc;j++)
{
for(i=0;i<bnr;i++)
{
y[bi*bnr+i] += A->L->value[k] * x[bj+j];
k++;
}
}
}
for(bc=A->U->bptr[bi];bc<A->U->bptr[bi+1];bc++)
{
bj = A->U->bindex[bc] * bnc;
k = bc*bs;
for(j=0;j<bnc;j++)
{
for(i=0;i<bnr;i++)
{
y[bi*bnr+i] += A->U->value[k] * x[bj+j];
k++;
}
}
}
}
}
else
{
#ifdef _OPENMP
#pragma omp parallel for private(i)
#endif
for(i=0; i<n; i++)
{
y[i] = 0.0;
}
#ifdef _OPENMP
#pragma omp parallel for private(i,j,k,bi,bj,bc)
#endif
for(bi=0;bi<nr;bi++)
{
for(bc=A->bptr[bi];bc<A->bptr[bi+1];bc++)
{
bj = A->bindex[bc] * bnc;
k = bc*bs;
for(j=0;j<bnc;j++)
{
for(i=0;i<bnr;i++)
{
y[bi*bnr+i] += A->value[k] * x[bj+j];
k++;
}
}
}
}
}
}
void lis_matvec_bsr_1x1(LIS_MATRIX A, LIS_SCALAR x[], LIS_SCALAR y[])
{
LIS_INT i,j,js,je,jj;
LIS_INT n,nr;
LIS_SCALAR t0;
n = A->n;
nr = A->nr;
if( A->is_splited )
{
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0)
#endif
for(i=0; i<nr; i++)
{
t0 = A->D->value[i] * x[i];
js = A->L->bptr[i];
je = A->L->bptr[i+1];
for(j=js;j<je;j++)
{
jj = A->L->bindex[j];
t0 += A->L->value[j] * x[jj];
}
js = A->U->bptr[i];
je = A->U->bptr[i+1];
for(j=js;j<je;j++)
{
jj = A->U->bindex[j];
t0 += A->U->value[j] * x[jj];
}
y[i] = t0;
}
}
else
{
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0)
#endif
for(i=0; i<nr; i++)
{
js = A->bptr[i];
je = A->bptr[i+1];
t0 = 0.0;
for(j=js;j<je;j++)
{
jj = A->bindex[j];
t0 += A->value[j] * x[jj];
}
y[i] = t0;
}
}
}
void lis_matvec_bsr_1x2(LIS_MATRIX A, LIS_SCALAR x[], LIS_SCALAR y[])
{
LIS_INT i,j,js,je,jj;
LIS_INT n,nr;
LIS_SCALAR t0;
n = A->n;
nr = A->nr;
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0)
#endif
for(i=0; i<nr; i++)
{
js = A->bptr[i];
je = A->bptr[i+1];
t0 = 0.0;
for(j=js;j<je;j++)
{
jj = A->bindex[j];
t0 += A->value[j*2+0] * x[jj*2+0];
t0 += A->value[j*2+1] * x[jj*2+1];
}
y[i] = t0;
}
}
void lis_matvec_bsr_1x3(LIS_MATRIX A, LIS_SCALAR x[], LIS_SCALAR y[])
{
LIS_INT i,j,js,je,jj;
LIS_INT n,nr;
LIS_SCALAR t0;
n = A->n;
nr = A->nr;
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0)
#endif
for(i=0; i<nr; i++)
{
js = A->bptr[i];
je = A->bptr[i+1];
t0 = 0.0;
for(j=js;j<je;j++)
{
jj = A->bindex[j];
t0 += A->value[j*3+0] * x[jj*3+0];
t0 += A->value[j*3+1] * x[jj*3+1];
t0 += A->value[j*3+2] * x[jj*3+2];
}
y[i] = t0;
}
}
void lis_matvec_bsr_1x4(LIS_MATRIX A, LIS_SCALAR x[], LIS_SCALAR y[])
{
LIS_INT i,j,js,je,jj;
LIS_INT n,nr;
LIS_SCALAR t0;
n = A->n;
nr = A->nr;
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0)
#endif
for(i=0; i<nr; i++)
{
js = A->bptr[i];
je = A->bptr[i+1];
t0 = 0.0;
for(j=js;j<je;j++)
{
jj = A->bindex[j];
t0 += A->value[j*4+0] * x[jj*4+0];
t0 += A->value[j*4+1] * x[jj*4+1];
t0 += A->value[j*4+2] * x[jj*4+2];
t0 += A->value[j*4+3] * x[jj*4+3];
}
y[i] = t0;
}
}
void lis_matvec_bsr_2x2(LIS_MATRIX A, LIS_SCALAR x[], LIS_SCALAR y[])
{
LIS_INT i,j,js,je,jj;
LIS_INT n,nr;
LIS_SCALAR t0,t1;
n = A->n;
nr = A->nr;
if( A->is_splited )
{
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0,t1)
#endif
for(i=0; i<nr; i++)
{
t0 = A->D->value[4*i+0] * x[2*i+0] + A->D->value[4*i+2] * x[2*i+1];
t1 = A->D->value[4*i+1] * x[2*i+0] + A->D->value[4*i+3] * x[2*i+1];
js = A->L->bptr[i];
je = A->L->bptr[i+1];
for(j=js;j<je;j++)
{
jj = A->L->bindex[j];
t0 += A->L->value[j*4+0] * x[jj*2+0];
t1 += A->L->value[j*4+1] * x[jj*2+0];
t0 += A->L->value[j*4+2] * x[jj*2+1];
t1 += A->L->value[j*4+3] * x[jj*2+1];
}
js = A->U->bptr[i];
je = A->U->bptr[i+1];
for(j=js;j<je;j++)
{
jj = A->U->bindex[j];
t0 += A->U->value[j*4+0] * x[jj*2+0];
t1 += A->U->value[j*4+1] * x[jj*2+0];
t0 += A->U->value[j*4+2] * x[jj*2+1];
t1 += A->U->value[j*4+3] * x[jj*2+1];
}
y[2*i+0] = t0;
y[2*i+1] = t1;
}
}
else
{
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0,t1)
#endif
for(i=0; i<nr; i++)
{
js = A->bptr[i];
je = A->bptr[i+1];
t0 = 0.0;
t1 = 0.0;
for(j=js;j<je;j++)
{
jj = A->bindex[j];
t0 += A->value[j*4+0] * x[jj*2+0];
t1 += A->value[j*4+1] * x[jj*2+0];
t0 += A->value[j*4+2] * x[jj*2+1];
t1 += A->value[j*4+3] * x[jj*2+1];
}
y[2*i+0] = t0;
y[2*i+1] = t1;
}
}
}
void lis_matvec_bsr_2x1(LIS_MATRIX A, LIS_SCALAR x[], LIS_SCALAR y[])
{
LIS_INT i,j,js,je,jj;
LIS_INT n,nr;
LIS_SCALAR t0,t1;
n = A->n;
nr = A->nr;
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0,t1)
#endif
for(i=0; i<nr; i++)
{
js = A->bptr[i];
je = A->bptr[i+1];
t0 = 0.0;
t1 = 0.0;
for(j=js;j<je;j++)
{
jj = A->bindex[j];
t0 += A->value[j*2+0] * x[jj];
t1 += A->value[j*2+1] * x[jj];
}
y[2*i+0] = t0;
y[2*i+1] = t1;
}
}
void lis_matvec_bsr_2x3(LIS_MATRIX A, LIS_SCALAR x[], LIS_SCALAR y[])
{
LIS_INT i,j,js,je,jj;
LIS_INT n,nr;
LIS_SCALAR t0,t1;
n = A->n;
nr = A->nr;
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0,t1)
#endif
for(i=0; i<nr; i++)
{
js = A->bptr[i];
je = A->bptr[i+1];
t0 = 0.0;
t1 = 0.0;
for(j=js;j<je;j++)
{
jj = A->bindex[j];
t0 += A->value[j*6+0] * x[jj*3+0];
t1 += A->value[j*6+1] * x[jj*3+0];
t0 += A->value[j*6+2] * x[jj*3+1];
t1 += A->value[j*6+3] * x[jj*3+1];
t0 += A->value[j*6+4] * x[jj*3+2];
t1 += A->value[j*6+5] * x[jj*3+2];
}
y[2*i+0] = t0;
y[2*i+1] = t1;
}
}
void lis_matvec_bsr_2x4(LIS_MATRIX A, LIS_SCALAR x[], LIS_SCALAR y[])
{
LIS_INT i,j,js,je,jj;
LIS_INT n,nr;
LIS_SCALAR t0,t1;
n = A->n;
nr = A->nr;
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0,t1)
#endif
for(i=0; i<nr; i++)
{
js = A->bptr[i];
je = A->bptr[i+1];
t0 = 0.0;
t1 = 0.0;
for(j=js;j<je;j++)
{
jj = A->bindex[j];
t0 += A->value[j*8+0] * x[jj*4+0];
t1 += A->value[j*8+1] * x[jj*4+0];
t0 += A->value[j*8+2] * x[jj*4+1];
t1 += A->value[j*8+3] * x[jj*4+1];
t0 += A->value[j*8+4] * x[jj*4+2];
t1 += A->value[j*8+5] * x[jj*4+2];
t0 += A->value[j*8+6] * x[jj*4+3];
t1 += A->value[j*8+7] * x[jj*4+3];
}
y[2*i+0] = t0;
y[2*i+1] = t1;
}
}
void lis_matvec_bsr_3x3(LIS_MATRIX A, LIS_SCALAR x[], LIS_SCALAR y[])
{
LIS_INT i,j,js,je,jj;
LIS_INT n,nr;
LIS_SCALAR t0,t1,t2;
n = A->n;
nr = A->nr;
if( A->is_splited )
{
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0,t1)
#endif
for(i=0; i<nr; i++)
{
t0 = A->D->value[9*i+0] * x[3*i+0] + A->D->value[9*i+3] * x[3*i+1] + A->D->value[9*i+6] * x[3*i+2];
t1 = A->D->value[9*i+1] * x[3*i+0] + A->D->value[9*i+4] * x[3*i+1] + A->D->value[9*i+7] * x[3*i+2];
t2 = A->D->value[9*i+2] * x[3*i+0] + A->D->value[9*i+5] * x[3*i+1] + A->D->value[9*i+8] * x[3*i+2];
js = A->L->bptr[i];
je = A->L->bptr[i+1];
for(j=js;j<je;j++)
{
jj = A->L->bindex[j];
t0 += A->L->value[j*9+0] * x[jj*3+0];
t1 += A->L->value[j*9+1] * x[jj*3+0];
t2 += A->L->value[j*9+2] * x[jj*3+0];
t0 += A->L->value[j*9+3] * x[jj*3+1];
t1 += A->L->value[j*9+4] * x[jj*3+1];
t2 += A->L->value[j*9+5] * x[jj*3+1];
t0 += A->L->value[j*9+6] * x[jj*3+2];
t1 += A->L->value[j*9+7] * x[jj*3+2];
t2 += A->L->value[j*9+8] * x[jj*3+2];
}
js = A->U->bptr[i];
je = A->U->bptr[i+1];
for(j=js;j<je;j++)
{
jj = A->U->bindex[j];
t0 += A->U->value[j*9+0] * x[jj*3+0];
t1 += A->U->value[j*9+1] * x[jj*3+0];
t2 += A->U->value[j*9+2] * x[jj*3+0];
t0 += A->U->value[j*9+3] * x[jj*3+1];
t1 += A->U->value[j*9+4] * x[jj*3+1];
t2 += A->U->value[j*9+5] * x[jj*3+1];
t0 += A->U->value[j*9+6] * x[jj*3+2];
t1 += A->U->value[j*9+7] * x[jj*3+2];
t2 += A->U->value[j*9+8] * x[jj*3+2];
}
y[3*i+0] = t0;
y[3*i+1] = t1;
y[3*i+2] = t2;
}
}
else
{
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0,t1,t2)
#endif
for(i=0; i<nr; i++)
{
js = A->bptr[i];
je = A->bptr[i+1];
t0 = 0.0;
t1 = 0.0;
t2 = 0.0;
for(j=js;j<je;j++)
{
jj = A->bindex[j];
t0 += A->value[j*9+0] * x[jj*3+0];
t1 += A->value[j*9+1] * x[jj*3+0];
t2 += A->value[j*9+2] * x[jj*3+0];
t0 += A->value[j*9+3] * x[jj*3+1];
t1 += A->value[j*9+4] * x[jj*3+1];
t2 += A->value[j*9+5] * x[jj*3+1];
t0 += A->value[j*9+6] * x[jj*3+2];
t1 += A->value[j*9+7] * x[jj*3+2];
t2 += A->value[j*9+8] * x[jj*3+2];
}
y[3*i+0] = t0;
y[3*i+1] = t1;
y[3*i+2] = t2;
}
}
}
void lis_matvec_bsr_3x1(LIS_MATRIX A, LIS_SCALAR x[], LIS_SCALAR y[])
{
LIS_INT i,j,js,je,jj,ii;
LIS_INT n,nr;
LIS_SCALAR t0,t1,t2;
n = A->n;
nr = A->nr;
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0,t1,t2,ii)
#endif
for(i=0; i<nr; i++)
{
ii = 3*i;
js = A->bptr[i];
je = A->bptr[i+1];
t0 = 0.0;
t1 = 0.0;
t2 = 0.0;
for(j=js;j<je;j++)
{
jj = A->bindex[j];
t0 += A->value[j*3+0] * x[jj];
t1 += A->value[j*3+1] * x[jj];
t2 += A->value[j*3+2] * x[jj];
}
y[ii+0] = t0;
y[ii+1] = t1;
y[ii+2] = t2;
}
}
void lis_matvec_bsr_3x2(LIS_MATRIX A, LIS_SCALAR x[], LIS_SCALAR y[])
{
LIS_INT i,j,js,je,jj;
LIS_INT n,nr;
LIS_SCALAR t0,t1,t2;
n = A->n;
nr = A->nr;
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0,t1,t2)
#endif
for(i=0; i<nr; i++)
{
js = A->bptr[i];
je = A->bptr[i+1];
t0 = 0.0;
t1 = 0.0;
t2 = 0.0;
for(j=js;j<je;j++)
{
jj = A->bindex[j];
t0 += A->value[j*6+0] * x[jj*2+0];
t1 += A->value[j*6+1] * x[jj*2+0];
t2 += A->value[j*6+2] * x[jj*2+0];
t0 += A->value[j*6+3] * x[jj*2+1];
t1 += A->value[j*6+4] * x[jj*2+1];
t2 += A->value[j*6+5] * x[jj*2+1];
}
y[3*i+0] = t0;
y[3*i+1] = t1;
y[3*i+2] = t2;
}
}
void lis_matvec_bsr_3x4(LIS_MATRIX A, LIS_SCALAR x[], LIS_SCALAR y[])
{
LIS_INT i,j,js,je,jj;
LIS_INT n,nr;
LIS_SCALAR t0,t1,t2;
n = A->n;
nr = A->nr;
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0,t1,t2)
#endif
for(i=0; i<nr; i++)
{
js = A->bptr[i];
je = A->bptr[i+1];
t0 = 0.0;
t1 = 0.0;
t2 = 0.0;
for(j=js;j<je;j++)
{
jj = A->bindex[j];
t0 += A->value[j*12+ 0] * x[jj*4+0];
t1 += A->value[j*12+ 1] * x[jj*4+0];
t2 += A->value[j*12+ 2] * x[jj*4+0];
t0 += A->value[j*12+ 3] * x[jj*4+1];
t1 += A->value[j*12+ 4] * x[jj*4+1];
t2 += A->value[j*12+ 5] * x[jj*4+1];
t0 += A->value[j*12+ 6] * x[jj*4+2];
t1 += A->value[j*12+ 7] * x[jj*4+2];
t2 += A->value[j*12+ 8] * x[jj*4+2];
t0 += A->value[j*12+ 9] * x[jj*4+3];
t1 += A->value[j*12+10] * x[jj*4+3];
t2 += A->value[j*12+11] * x[jj*4+3];
}
y[3*i+0] = t0;
y[3*i+1] = t1;
y[3*i+2] = t2;
}
}
void lis_matvec_bsr_4x4(LIS_MATRIX A, LIS_SCALAR x[], LIS_SCALAR y[])
{
LIS_INT i,j,js,je,jj;
LIS_INT n,nr;
LIS_SCALAR t0,t1,t2,t3;
n = A->n;
nr = A->nr;
if( A->is_splited )
{
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0,t1,t2,t3)
#endif
for(i=0; i<nr; i++)
{
t0 = A->D->value[16*i+0] * x[4*i+0] + A->D->value[16*i+4] * x[4*i+1] + A->D->value[16*i+8] * x[4*i+2] + A->D->value[16*i+12] * x[4*i+3];
t1 = A->D->value[16*i+1] * x[4*i+0] + A->D->value[16*i+5] * x[4*i+1] + A->D->value[16*i+9] * x[4*i+2] + A->D->value[16*i+13] * x[4*i+3];
t2 = A->D->value[16*i+2] * x[4*i+0] + A->D->value[16*i+6] * x[4*i+1] + A->D->value[16*i+10] * x[4*i+2] + A->D->value[16*i+14] * x[4*i+3];
t3 = A->D->value[16*i+3] * x[4*i+0] + A->D->value[16*i+7] * x[4*i+1] + A->D->value[16*i+11] * x[4*i+2] + A->D->value[16*i+15] * x[4*i+3];
js = A->L->bptr[i];
je = A->L->bptr[i+1];
for(j=js;j<je;j++)
{
jj = A->L->bindex[j];
t0 += A->L->value[j*16+ 0] * x[jj*4+0];
t1 += A->L->value[j*16+ 1] * x[jj*4+0];
t2 += A->L->value[j*16+ 2] * x[jj*4+0];
t3 += A->L->value[j*16+ 3] * x[jj*4+0];
t0 += A->L->value[j*16+ 4] * x[jj*4+1];
t1 += A->L->value[j*16+ 5] * x[jj*4+1];
t2 += A->L->value[j*16+ 6] * x[jj*4+1];
t3 += A->L->value[j*16+ 7] * x[jj*4+1];
t0 += A->L->value[j*16+ 8] * x[jj*4+2];
t1 += A->L->value[j*16+ 9] * x[jj*4+2];
t2 += A->L->value[j*16+10] * x[jj*4+2];
t3 += A->L->value[j*16+11] * x[jj*4+2];
t0 += A->L->value[j*16+12] * x[jj*4+3];
t1 += A->L->value[j*16+13] * x[jj*4+3];
t2 += A->L->value[j*16+14] * x[jj*4+3];
t3 += A->L->value[j*16+15] * x[jj*4+3];
}
js = A->U->bptr[i];
je = A->U->bptr[i+1];
for(j=js;j<je;j++)
{
jj = A->U->bindex[j];
t0 += A->U->value[j*16+ 0] * x[jj*4+0];
t1 += A->U->value[j*16+ 1] * x[jj*4+0];
t2 += A->U->value[j*16+ 2] * x[jj*4+0];
t3 += A->U->value[j*16+ 3] * x[jj*4+0];
t0 += A->U->value[j*16+ 4] * x[jj*4+1];
t1 += A->U->value[j*16+ 5] * x[jj*4+1];
t2 += A->U->value[j*16+ 6] * x[jj*4+1];
t3 += A->U->value[j*16+ 7] * x[jj*4+1];
t0 += A->U->value[j*16+ 8] * x[jj*4+2];
t1 += A->U->value[j*16+ 9] * x[jj*4+2];
t2 += A->U->value[j*16+10] * x[jj*4+2];
t3 += A->U->value[j*16+11] * x[jj*4+2];
t0 += A->U->value[j*16+12] * x[jj*4+3];
t1 += A->U->value[j*16+13] * x[jj*4+3];
t2 += A->U->value[j*16+14] * x[jj*4+3];
t3 += A->U->value[j*16+15] * x[jj*4+3];
}
y[4*i+0] = t0;
y[4*i+1] = t1;
y[4*i+2] = t2;
y[4*i+3] = t3;
}
}
else
{
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0,t1,t2,t3)
#endif
for(i=0; i<nr; i++)
{
js = A->bptr[i];
je = A->bptr[i+1];
t0 = 0.0;
t1 = 0.0;
t2 = 0.0;
t3 = 0.0;
for(j=js;j<je;j++)
{
jj = A->bindex[j];
t0 += A->value[j*16+ 0] * x[jj*4+0];
t1 += A->value[j*16+ 1] * x[jj*4+0];
t2 += A->value[j*16+ 2] * x[jj*4+0];
t3 += A->value[j*16+ 3] * x[jj*4+0];
t0 += A->value[j*16+ 4] * x[jj*4+1];
t1 += A->value[j*16+ 5] * x[jj*4+1];
t2 += A->value[j*16+ 6] * x[jj*4+1];
t3 += A->value[j*16+ 7] * x[jj*4+1];
t0 += A->value[j*16+ 8] * x[jj*4+2];
t1 += A->value[j*16+ 9] * x[jj*4+2];
t2 += A->value[j*16+10] * x[jj*4+2];
t3 += A->value[j*16+11] * x[jj*4+2];
t0 += A->value[j*16+12] * x[jj*4+3];
t1 += A->value[j*16+13] * x[jj*4+3];
t2 += A->value[j*16+14] * x[jj*4+3];
t3 += A->value[j*16+15] * x[jj*4+3];
}
y[4*i+0] = t0;
y[4*i+1] = t1;
y[4*i+2] = t2;
y[4*i+3] = t3;
}
}
}
void lis_matvec_bsr_4x1(LIS_MATRIX A, LIS_SCALAR x[], LIS_SCALAR y[])
{
LIS_INT i,j,js,je,jj;
LIS_INT n,nr;
LIS_SCALAR t0,t1,t2,t3;
n = A->n;
nr = A->nr;
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0,t1,t2,t3)
#endif
for(i=0; i<nr; i++)
{
js = A->bptr[i];
je = A->bptr[i+1];
t0 = 0.0;
t1 = 0.0;
t2 = 0.0;
t3 = 0.0;
for(j=js;j<je;j++)
{
jj = A->bindex[j];
t0 += A->value[j*4+ 0] * x[jj];
t1 += A->value[j*4+ 1] * x[jj];
t2 += A->value[j*4+ 2] * x[jj];
t3 += A->value[j*4+ 3] * x[jj];
}
y[4*i+0] = t0;
y[4*i+1] = t1;
y[4*i+2] = t2;
y[4*i+3] = t3;
}
}
void lis_matvec_bsr_4x2(LIS_MATRIX A, LIS_SCALAR x[], LIS_SCALAR y[])
{
LIS_INT i,j,js,je,jj;
LIS_INT n,nr;
LIS_SCALAR t0,t1,t2,t3;
n = A->n;
nr = A->nr;
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0,t1,t2,t3)
#endif
for(i=0; i<nr; i++)
{
js = A->bptr[i];
je = A->bptr[i+1];
t0 = 0.0;
t1 = 0.0;
t2 = 0.0;
t3 = 0.0;
for(j=js;j<je;j++)
{
jj = A->bindex[j];
t0 += A->value[j*8+ 0] * x[jj*2+0];
t1 += A->value[j*8+ 1] * x[jj*2+0];
t2 += A->value[j*8+ 2] * x[jj*2+0];
t3 += A->value[j*8+ 3] * x[jj*2+0];
t0 += A->value[j*8+ 4] * x[jj*2+1];
t1 += A->value[j*8+ 5] * x[jj*2+1];
t2 += A->value[j*8+ 6] * x[jj*2+1];
t3 += A->value[j*8+ 7] * x[jj*2+1];
}
y[4*i+0] = t0;
y[4*i+1] = t1;
y[4*i+2] = t2;
y[4*i+3] = t3;
}
}
void lis_matvec_bsr_4x3(LIS_MATRIX A, LIS_SCALAR x[], LIS_SCALAR y[])
{
LIS_INT i,j,js,je,jj;
LIS_INT n,nr;
LIS_SCALAR t0,t1,t2,t3;
n = A->n;
nr = A->nr;
#ifdef _OPENMP
#pragma omp parallel for private(i,j,jj,js,je,t0,t1,t2,t3)
#endif
for(i=0; i<nr; i++)
{
js = A->bptr[i];
je = A->bptr[i+1];
t0 = 0.0;
t1 = 0.0;
t2 = 0.0;
t3 = 0.0;
for(j=js;j<je;j++)
{
jj = A->bindex[j];
t0 += A->value[j*12+ 0] * x[jj*3+0];
t1 += A->value[j*12+ 1] * x[jj*3+0];
t2 += A->value[j*12+ 2] * x[jj*3+0];
t3 += A->value[j*12+ 3] * x[jj*3+0];
t0 += A->value[j*12+ 4] * x[jj*3+1];
t1 += A->value[j*12+ 5] * x[jj*3+1];
t2 += A->value[j*12+ 6] * x[jj*3+1];
t3 += A->value[j*12+ 7] * x[jj*3+1];
t0 += A->value[j*12+ 8] * x[jj*3+2];
t1 += A->value[j*12+ 9] * x[jj*3+2];
t2 += A->value[j*12+10] * x[jj*3+2];
t3 += A->value[j*12+11] * x[jj*3+2];
}
y[4*i+0] = t0;
y[4*i+1] = t1;
y[4*i+2] = t2;
y[4*i+3] = t3;
}
}
void lis_matvect_bsr(LIS_MATRIX A, LIS_SCALAR x[], LIS_SCALAR y[])
{
LIS_INT i,j,k;
LIS_INT bi,bj,bc,bs;
LIS_INT nr,nc,bnr,bnc;
LIS_INT n,np;
#ifdef _OPENMP
LIS_INT nprocs,my_rank;
LIS_SCALAR t;
LIS_SCALAR *w;
#endif
n = A->n;
np = A->np;
nr = A->nr;
nc = A->nc;
bnr = A->bnr;
bnc = A->bnc;
bs = bnr*bnc;
if( A->is_splited )
{
for(i=0;i<n;i++)
{
y[i] = 0.0;
}
for(bi=0;bi<nr;bi++)
{
k = bi*bs;
for(j=0;j<bnc;j++)
{
for(i=0;i<bnr;i++)
{
y[bi*bnr+j] += A->D->value[k++] * x[bi*bnr+i];
}
}
}
for(bi=0;bi<nr;bi++)
{
for(bc=A->L->bptr[bi];bc<A->L->bptr[bi+1];bc++)
{
bj = A->L->bindex[bc] * bnc;
k = bc*bs;
for(j=0;j<bnc;j++)
{
for(i=0;i<bnr;i++)
{
y[bj+j] += A->L->value[k] * x[bi*bnr+i];
k++;
}
}
}
for(bc=A->U->bptr[bi];bc<A->U->bptr[bi+1];bc++)
{
bj = A->U->bindex[bc] * bnc;
k = bc*bs;
for(j=0;j<bnc;j++)
{
for(i=0;i<bnr;i++)
{
y[bj+j] += A->U->value[k] * x[bi*bnr+i];
k++;
}
}
}
}
}
else
{
#ifdef _OPENMP
nprocs = omp_get_max_threads();
w = (LIS_SCALAR *)lis_malloc( nprocs*np*sizeof(LIS_SCALAR),"lis_matvect_bsr::w" );
#pragma omp parallel private(bi,bc,bj,i,j,k,my_rank)
{
my_rank = omp_get_thread_num();
#pragma omp for
for(j=0;j<nprocs;j++)
{
memset( &w[j*np], 0, np*sizeof(LIS_SCALAR) );
}
#pragma omp for
for(bi=0;bi<nr;bi++)
{
for(bc=A->bptr[bi];bc<A->bptr[bi+1];bc++)
{
bj = my_rank*np + A->bindex[bc] * bnc;
k = bc*bs;
for(j=0;j<bnc;j++)
{
for(i=0;i<bnr;i++)
{
w[bj+j] += A->value[k] * x[bi*bnr+i];
k++;
}
}
}
}
#pragma omp barrier
#pragma omp for
for(i=0;i<np;i++)
{
t = 0.0;
for(j=0;j<nprocs;j++)
{
t += w[j*np+i];
}
y[i] = t;
}
}
lis_free(w);
#else
for(i=0; i<n; i++)
{
y[i] = 0.0;
}
for(bi=0;bi<nr;bi++)
{
for(bc=A->bptr[bi];bc<A->bptr[bi+1];bc++)
{
bj = A->bindex[bc] * bnc;
k = bc*bs;
for(j=0;j<bnc;j++)
{
for(i=0;i<bnr;i++)
{
y[bj+j] += A->value[k] * x[bi*bnr+i];
k++;
}
}
}
}
#endif
}
}
|
wd.h | #ifndef METHODS_WD_H
#define METHODS_WD_H
namespace method {
// use your method name to create a subspace for your
// implementation of details
namespace wd {
namespace details {
template<typename Initial, typename Potential>
arma::mat effective_force(const Potential & potential,
const Initial & initial,
const arma::mat & points) {
arma::mat result = arma::mat(points.n_rows / 2, points.n_cols);
#pragma omp parallel for
for (arma::uword i = 0; i < points.n_cols; i++) {
const arma::vec point = points.col(i);
const arma::vec position = points.col(i).rows(0, points.n_rows / 2 - 1);
for (arma::uword j = 0; j < points.n_rows / 2; j++) {
const auto p_j = j + points.n_rows / 2;
result(j, i) = -potential.derivative(j).at(position)
+ potential.derivative(j).derivative(j).derivative(j).at(
position)
* initial.derivative(p_j).derivative(p_j).derivative(
p_j).at(point)
/ initial.derivative(p_j).at(point) / 24.0;
}
}
return result;
}
} // namespace details
using State = cwa::State;
template<typename Potential, typename Initial>
struct Operator {
private:
PropagationType type = Classic;
public:
Potential potential;
Initial initial;
Operator(const State & state,
const Initial & initial,
const Potential & potential) :
potential(potential),
initial(initial) {}
inline
PropagationType propagation_type() const {
return Classic;
}
State operator()(const State & state) const {
arma::mat p_submatrix = state.points.rows(state.dim(), 2 * state.dim() - 1);
p_submatrix.each_col() /= state.masses;
const arma::mat change_list =
arma::join_cols(p_submatrix,
details::effective_force(potential,
this->initial,
state.points));
return State(change_list, state.weights, state.masses);
}
};
} // namespace cwa
}
#endif //METHODS_WD_H
|
Parser.h | //===--- Parser.h - C Language Parser ---------------------------*- C++ -*-===//
//
// Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
//
//===----------------------------------------------------------------------===//
//
// This file defines the Parser interface.
//
//===----------------------------------------------------------------------===//
#ifndef LLVM_CLANG_PARSE_PARSER_H
#define LLVM_CLANG_PARSE_PARSER_H
#include "clang/AST/Availability.h"
#include "clang/Basic/BitmaskEnum.h"
#include "clang/Basic/OpenMPKinds.h"
#include "clang/Basic/OperatorPrecedence.h"
#include "clang/Basic/Specifiers.h"
#include "clang/Lex/CodeCompletionHandler.h"
#include "clang/Lex/Preprocessor.h"
#include "clang/Sema/DeclSpec.h"
#include "clang/Sema/Sema.h"
#include "llvm/ADT/SmallVector.h"
#include "llvm/Frontend/OpenMP/OMPContext.h"
#include "llvm/Support/Compiler.h"
#include "llvm/Support/PrettyStackTrace.h"
#include "llvm/Support/SaveAndRestore.h"
#include <memory>
#include <stack>
namespace clang {
class PragmaHandler;
class Scope;
class BalancedDelimiterTracker;
class CorrectionCandidateCallback;
class DeclGroupRef;
class DiagnosticBuilder;
struct LoopHint;
class Parser;
class ParsingDeclRAIIObject;
class ParsingDeclSpec;
class ParsingDeclarator;
class ParsingFieldDeclarator;
class ColonProtectionRAIIObject;
class InMessageExpressionRAIIObject;
class PoisonSEHIdentifiersRAIIObject;
class OMPClause;
class ObjCTypeParamList;
struct OMPTraitProperty;
struct OMPTraitSelector;
struct OMPTraitSet;
class OMPTraitInfo;
/// Parser - This implements a parser for the C family of languages. After
/// parsing units of the grammar, productions are invoked to handle whatever has
/// been read.
///
class Parser : public CodeCompletionHandler {
friend class ColonProtectionRAIIObject;
friend class ParsingOpenMPDirectiveRAII;
friend class InMessageExpressionRAIIObject;
friend class PoisonSEHIdentifiersRAIIObject;
friend class ObjCDeclContextSwitch;
friend class ParenBraceBracketBalancer;
friend class BalancedDelimiterTracker;
Preprocessor &PP;
/// Tok - The current token we are peeking ahead. All parsing methods assume
/// that this is valid.
Token Tok;
// PrevTokLocation - The location of the token we previously
// consumed. This token is used for diagnostics where we expected to
// see a token following another token (e.g., the ';' at the end of
// a statement).
SourceLocation PrevTokLocation;
/// Tracks an expected type for the current token when parsing an expression.
/// Used by code completion for ranking.
PreferredTypeBuilder PreferredType;
unsigned short ParenCount = 0, BracketCount = 0, BraceCount = 0;
unsigned short MisplacedModuleBeginCount = 0;
/// Actions - These are the callbacks we invoke as we parse various constructs
/// in the file.
Sema &Actions;
DiagnosticsEngine &Diags;
/// ScopeCache - Cache scopes to reduce malloc traffic.
enum { ScopeCacheSize = 16 };
unsigned NumCachedScopes;
Scope *ScopeCache[ScopeCacheSize];
/// Identifiers used for SEH handling in Borland. These are only
/// allowed in particular circumstances
// __except block
IdentifierInfo *Ident__exception_code,
*Ident___exception_code,
*Ident_GetExceptionCode;
// __except filter expression
IdentifierInfo *Ident__exception_info,
*Ident___exception_info,
*Ident_GetExceptionInfo;
// __finally
IdentifierInfo *Ident__abnormal_termination,
*Ident___abnormal_termination,
*Ident_AbnormalTermination;
/// Contextual keywords for Microsoft extensions.
IdentifierInfo *Ident__except;
mutable IdentifierInfo *Ident_sealed;
/// Ident_super - IdentifierInfo for "super", to support fast
/// comparison.
IdentifierInfo *Ident_super;
/// Ident_vector, Ident_bool - cached IdentifierInfos for "vector" and
/// "bool" fast comparison. Only present if AltiVec or ZVector are enabled.
IdentifierInfo *Ident_vector;
IdentifierInfo *Ident_bool;
/// Ident_pixel - cached IdentifierInfos for "pixel" fast comparison.
/// Only present if AltiVec enabled.
IdentifierInfo *Ident_pixel;
/// Objective-C contextual keywords.
IdentifierInfo *Ident_instancetype;
/// Identifier for "introduced".
IdentifierInfo *Ident_introduced;
/// Identifier for "deprecated".
IdentifierInfo *Ident_deprecated;
/// Identifier for "obsoleted".
IdentifierInfo *Ident_obsoleted;
/// Identifier for "unavailable".
IdentifierInfo *Ident_unavailable;
/// Identifier for "message".
IdentifierInfo *Ident_message;
/// Identifier for "strict".
IdentifierInfo *Ident_strict;
/// Identifier for "replacement".
IdentifierInfo *Ident_replacement;
/// Identifiers used by the 'external_source_symbol' attribute.
IdentifierInfo *Ident_language, *Ident_defined_in,
*Ident_generated_declaration;
/// C++11 contextual keywords.
mutable IdentifierInfo *Ident_final;
mutable IdentifierInfo *Ident_GNU_final;
mutable IdentifierInfo *Ident_override;
// C++2a contextual keywords.
mutable IdentifierInfo *Ident_import;
mutable IdentifierInfo *Ident_module;
// C++ type trait keywords that can be reverted to identifiers and still be
// used as type traits.
llvm::SmallDenseMap<IdentifierInfo *, tok::TokenKind> RevertibleTypeTraits;
std::unique_ptr<PragmaHandler> AlignHandler;
std::unique_ptr<PragmaHandler> GCCVisibilityHandler;
std::unique_ptr<PragmaHandler> OptionsHandler;
std::unique_ptr<PragmaHandler> PackHandler;
std::unique_ptr<PragmaHandler> MSStructHandler;
std::unique_ptr<PragmaHandler> UnusedHandler;
std::unique_ptr<PragmaHandler> WeakHandler;
std::unique_ptr<PragmaHandler> RedefineExtnameHandler;
std::unique_ptr<PragmaHandler> FPContractHandler;
std::unique_ptr<PragmaHandler> OpenCLExtensionHandler;
std::unique_ptr<PragmaHandler> OpenMPHandler;
std::unique_ptr<PragmaHandler> PCSectionHandler;
std::unique_ptr<PragmaHandler> MSCommentHandler;
std::unique_ptr<PragmaHandler> MSDetectMismatchHandler;
std::unique_ptr<PragmaHandler> FloatControlHandler;
std::unique_ptr<PragmaHandler> MSPointersToMembers;
std::unique_ptr<PragmaHandler> MSVtorDisp;
std::unique_ptr<PragmaHandler> MSInitSeg;
std::unique_ptr<PragmaHandler> MSDataSeg;
std::unique_ptr<PragmaHandler> MSBSSSeg;
std::unique_ptr<PragmaHandler> MSConstSeg;
std::unique_ptr<PragmaHandler> MSCodeSeg;
std::unique_ptr<PragmaHandler> MSSection;
std::unique_ptr<PragmaHandler> MSRuntimeChecks;
std::unique_ptr<PragmaHandler> MSIntrinsic;
std::unique_ptr<PragmaHandler> MSOptimize;
std::unique_ptr<PragmaHandler> CUDAForceHostDeviceHandler;
std::unique_ptr<PragmaHandler> OptimizeHandler;
std::unique_ptr<PragmaHandler> LoopHintHandler;
std::unique_ptr<PragmaHandler> UnrollHintHandler;
std::unique_ptr<PragmaHandler> NoUnrollHintHandler;
std::unique_ptr<PragmaHandler> UnrollAndJamHintHandler;
std::unique_ptr<PragmaHandler> NoUnrollAndJamHintHandler;
std::unique_ptr<PragmaHandler> FPHandler;
std::unique_ptr<PragmaHandler> STDCFenvAccessHandler;
std::unique_ptr<PragmaHandler> STDCFenvRoundHandler;
std::unique_ptr<PragmaHandler> STDCCXLIMITHandler;
std::unique_ptr<PragmaHandler> STDCUnknownHandler;
std::unique_ptr<PragmaHandler> AttributePragmaHandler;
std::unique_ptr<PragmaHandler> MaxTokensHerePragmaHandler;
std::unique_ptr<PragmaHandler> MaxTokensTotalPragmaHandler;
std::unique_ptr<CommentHandler> CommentSemaHandler;
/// Whether the '>' token acts as an operator or not. This will be
/// true except when we are parsing an expression within a C++
/// template argument list, where the '>' closes the template
/// argument list.
bool GreaterThanIsOperator;
/// ColonIsSacred - When this is false, we aggressively try to recover from
/// code like "foo : bar" as if it were a typo for "foo :: bar". This is not
/// safe in case statements and a few other things. This is managed by the
/// ColonProtectionRAIIObject RAII object.
bool ColonIsSacred;
/// Parsing OpenMP directive mode.
bool OpenMPDirectiveParsing = false;
/// When true, we are directly inside an Objective-C message
/// send expression.
///
/// This is managed by the \c InMessageExpressionRAIIObject class, and
/// should not be set directly.
bool InMessageExpression;
/// Gets set to true after calling ProduceSignatureHelp, it is for a
/// workaround to make sure ProduceSignatureHelp is only called at the deepest
/// function call.
bool CalledSignatureHelp = false;
/// The "depth" of the template parameters currently being parsed.
unsigned TemplateParameterDepth;
/// Current kind of OpenMP clause
OpenMPClauseKind OMPClauseKind = llvm::omp::OMPC_unknown;
/// RAII class that manages the template parameter depth.
class TemplateParameterDepthRAII {
unsigned &Depth;
unsigned AddedLevels;
public:
explicit TemplateParameterDepthRAII(unsigned &Depth)
: Depth(Depth), AddedLevels(0) {}
~TemplateParameterDepthRAII() {
Depth -= AddedLevels;
}
void operator++() {
++Depth;
++AddedLevels;
}
void addDepth(unsigned D) {
Depth += D;
AddedLevels += D;
}
void setAddedDepth(unsigned D) {
Depth = Depth - AddedLevels + D;
AddedLevels = D;
}
unsigned getDepth() const { return Depth; }
unsigned getOriginalDepth() const { return Depth - AddedLevels; }
};
/// Factory object for creating ParsedAttr objects.
AttributeFactory AttrFactory;
/// Gathers and cleans up TemplateIdAnnotations when parsing of a
/// top-level declaration is finished.
SmallVector<TemplateIdAnnotation *, 16> TemplateIds;
void MaybeDestroyTemplateIds() {
if (!TemplateIds.empty() &&
(Tok.is(tok::eof) || !PP.mightHavePendingAnnotationTokens()))
DestroyTemplateIds();
}
void DestroyTemplateIds();
/// RAII object to destroy TemplateIdAnnotations where possible, from a
/// likely-good position during parsing.
struct DestroyTemplateIdAnnotationsRAIIObj {
Parser &Self;
DestroyTemplateIdAnnotationsRAIIObj(Parser &Self) : Self(Self) {}
~DestroyTemplateIdAnnotationsRAIIObj() { Self.MaybeDestroyTemplateIds(); }
};
/// Identifiers which have been declared within a tentative parse.
SmallVector<IdentifierInfo *, 8> TentativelyDeclaredIdentifiers;
/// Tracker for '<' tokens that might have been intended to be treated as an
/// angle bracket instead of a less-than comparison.
///
/// This happens when the user intends to form a template-id, but typoes the
/// template-name or forgets a 'template' keyword for a dependent template
/// name.
///
/// We track these locations from the point where we see a '<' with a
/// name-like expression on its left until we see a '>' or '>>' that might
/// match it.
struct AngleBracketTracker {
/// Flags used to rank candidate template names when there is more than one
/// '<' in a scope.
enum Priority : unsigned short {
/// A non-dependent name that is a potential typo for a template name.
PotentialTypo = 0x0,
/// A dependent name that might instantiate to a template-name.
DependentName = 0x2,
/// A space appears before the '<' token.
SpaceBeforeLess = 0x0,
/// No space before the '<' token
NoSpaceBeforeLess = 0x1,
LLVM_MARK_AS_BITMASK_ENUM(/*LargestValue*/ DependentName)
};
struct Loc {
Expr *TemplateName;
SourceLocation LessLoc;
AngleBracketTracker::Priority Priority;
unsigned short ParenCount, BracketCount, BraceCount;
bool isActive(Parser &P) const {
return P.ParenCount == ParenCount && P.BracketCount == BracketCount &&
P.BraceCount == BraceCount;
}
bool isActiveOrNested(Parser &P) const {
return isActive(P) || P.ParenCount > ParenCount ||
P.BracketCount > BracketCount || P.BraceCount > BraceCount;
}
};
SmallVector<Loc, 8> Locs;
/// Add an expression that might have been intended to be a template name.
/// In the case of ambiguity, we arbitrarily select the innermost such
/// expression, for example in 'foo < bar < baz', 'bar' is the current
/// candidate. No attempt is made to track that 'foo' is also a candidate
/// for the case where we see a second suspicious '>' token.
void add(Parser &P, Expr *TemplateName, SourceLocation LessLoc,
Priority Prio) {
if (!Locs.empty() && Locs.back().isActive(P)) {
if (Locs.back().Priority <= Prio) {
Locs.back().TemplateName = TemplateName;
Locs.back().LessLoc = LessLoc;
Locs.back().Priority = Prio;
}
} else {
Locs.push_back({TemplateName, LessLoc, Prio,
P.ParenCount, P.BracketCount, P.BraceCount});
}
}
/// Mark the current potential missing template location as having been
/// handled (this happens if we pass a "corresponding" '>' or '>>' token
/// or leave a bracket scope).
void clear(Parser &P) {
while (!Locs.empty() && Locs.back().isActiveOrNested(P))
Locs.pop_back();
}
/// Get the current enclosing expression that might hve been intended to be
/// a template name.
Loc *getCurrent(Parser &P) {
if (!Locs.empty() && Locs.back().isActive(P))
return &Locs.back();
return nullptr;
}
};
AngleBracketTracker AngleBrackets;
IdentifierInfo *getSEHExceptKeyword();
/// True if we are within an Objective-C container while parsing C-like decls.
///
/// This is necessary because Sema thinks we have left the container
/// to parse the C-like decls, meaning Actions.getObjCDeclContext() will
/// be NULL.
bool ParsingInObjCContainer;
/// Whether to skip parsing of function bodies.
///
/// This option can be used, for example, to speed up searches for
/// declarations/definitions when indexing.
bool SkipFunctionBodies;
/// The location of the expression statement that is being parsed right now.
/// Used to determine if an expression that is being parsed is a statement or
/// just a regular sub-expression.
SourceLocation ExprStatementTokLoc;
/// Flags describing a context in which we're parsing a statement.
enum class ParsedStmtContext {
/// This context permits declarations in language modes where declarations
/// are not statements.
AllowDeclarationsInC = 0x1,
/// This context permits standalone OpenMP directives.
AllowStandaloneOpenMPDirectives = 0x2,
/// This context is at the top level of a GNU statement expression.
InStmtExpr = 0x4,
/// The context of a regular substatement.
SubStmt = 0,
/// The context of a compound-statement.
Compound = AllowDeclarationsInC | AllowStandaloneOpenMPDirectives,
LLVM_MARK_AS_BITMASK_ENUM(InStmtExpr)
};
/// Act on an expression statement that might be the last statement in a
/// GNU statement expression. Checks whether we are actually at the end of
/// a statement expression and builds a suitable expression statement.
StmtResult handleExprStmt(ExprResult E, ParsedStmtContext StmtCtx);
public:
Parser(Preprocessor &PP, Sema &Actions, bool SkipFunctionBodies);
~Parser() override;
const LangOptions &getLangOpts() const { return PP.getLangOpts(); }
const TargetInfo &getTargetInfo() const { return PP.getTargetInfo(); }
Preprocessor &getPreprocessor() const { return PP; }
Sema &getActions() const { return Actions; }
AttributeFactory &getAttrFactory() { return AttrFactory; }
const Token &getCurToken() const { return Tok; }
Scope *getCurScope() const { return Actions.getCurScope(); }
void incrementMSManglingNumber() const {
return Actions.incrementMSManglingNumber();
}
Decl *getObjCDeclContext() const { return Actions.getObjCDeclContext(); }
// Type forwarding. All of these are statically 'void*', but they may all be
// different actual classes based on the actions in place.
typedef OpaquePtr<DeclGroupRef> DeclGroupPtrTy;
typedef OpaquePtr<TemplateName> TemplateTy;
typedef SmallVector<TemplateParameterList *, 4> TemplateParameterLists;
typedef Sema::FullExprArg FullExprArg;
// Parsing methods.
/// Initialize - Warm up the parser.
///
void Initialize();
/// Parse the first top-level declaration in a translation unit.
bool ParseFirstTopLevelDecl(DeclGroupPtrTy &Result);
/// ParseTopLevelDecl - Parse one top-level declaration. Returns true if
/// the EOF was encountered.
bool ParseTopLevelDecl(DeclGroupPtrTy &Result, bool IsFirstDecl = false);
bool ParseTopLevelDecl() {
DeclGroupPtrTy Result;
return ParseTopLevelDecl(Result);
}
/// ConsumeToken - Consume the current 'peek token' and lex the next one.
/// This does not work with special tokens: string literals, code completion,
/// annotation tokens and balanced tokens must be handled using the specific
/// consume methods.
/// Returns the location of the consumed token.
SourceLocation ConsumeToken() {
assert(!isTokenSpecial() &&
"Should consume special tokens with Consume*Token");
PrevTokLocation = Tok.getLocation();
PP.Lex(Tok);
return PrevTokLocation;
}
bool TryConsumeToken(tok::TokenKind Expected) {
if (Tok.isNot(Expected))
return false;
assert(!isTokenSpecial() &&
"Should consume special tokens with Consume*Token");
PrevTokLocation = Tok.getLocation();
PP.Lex(Tok);
return true;
}
bool TryConsumeToken(tok::TokenKind Expected, SourceLocation &Loc) {
if (!TryConsumeToken(Expected))
return false;
Loc = PrevTokLocation;
return true;
}
/// ConsumeAnyToken - Dispatch to the right Consume* method based on the
/// current token type. This should only be used in cases where the type of
/// the token really isn't known, e.g. in error recovery.
SourceLocation ConsumeAnyToken(bool ConsumeCodeCompletionTok = false) {
if (isTokenParen())
return ConsumeParen();
if (isTokenBracket())
return ConsumeBracket();
if (isTokenBrace())
return ConsumeBrace();
if (isTokenStringLiteral())
return ConsumeStringToken();
if (Tok.is(tok::code_completion))
return ConsumeCodeCompletionTok ? ConsumeCodeCompletionToken()
: handleUnexpectedCodeCompletionToken();
if (Tok.isAnnotation())
return ConsumeAnnotationToken();
return ConsumeToken();
}
SourceLocation getEndOfPreviousToken() {
return PP.getLocForEndOfToken(PrevTokLocation);
}
/// Retrieve the underscored keyword (_Nonnull, _Nullable) that corresponds
/// to the given nullability kind.
IdentifierInfo *getNullabilityKeyword(NullabilityKind nullability) {
return Actions.getNullabilityKeyword(nullability);
}
private:
//===--------------------------------------------------------------------===//
// Low-Level token peeking and consumption methods.
//
/// isTokenParen - Return true if the cur token is '(' or ')'.
bool isTokenParen() const {
return Tok.isOneOf(tok::l_paren, tok::r_paren);
}
/// isTokenBracket - Return true if the cur token is '[' or ']'.
bool isTokenBracket() const {
return Tok.isOneOf(tok::l_square, tok::r_square);
}
/// isTokenBrace - Return true if the cur token is '{' or '}'.
bool isTokenBrace() const {
return Tok.isOneOf(tok::l_brace, tok::r_brace);
}
/// isTokenStringLiteral - True if this token is a string-literal.
bool isTokenStringLiteral() const {
return tok::isStringLiteral(Tok.getKind());
}
/// isTokenSpecial - True if this token requires special consumption methods.
bool isTokenSpecial() const {
return isTokenStringLiteral() || isTokenParen() || isTokenBracket() ||
isTokenBrace() || Tok.is(tok::code_completion) || Tok.isAnnotation();
}
/// Returns true if the current token is '=' or is a type of '='.
/// For typos, give a fixit to '='
bool isTokenEqualOrEqualTypo();
/// Return the current token to the token stream and make the given
/// token the current token.
void UnconsumeToken(Token &Consumed) {
Token Next = Tok;
PP.EnterToken(Consumed, /*IsReinject*/true);
PP.Lex(Tok);
PP.EnterToken(Next, /*IsReinject*/true);
}
SourceLocation ConsumeAnnotationToken() {
assert(Tok.isAnnotation() && "wrong consume method");
SourceLocation Loc = Tok.getLocation();
PrevTokLocation = Tok.getAnnotationEndLoc();
PP.Lex(Tok);
return Loc;
}
/// ConsumeParen - This consume method keeps the paren count up-to-date.
///
SourceLocation ConsumeParen() {
assert(isTokenParen() && "wrong consume method");
if (Tok.getKind() == tok::l_paren)
++ParenCount;
else if (ParenCount) {
AngleBrackets.clear(*this);
--ParenCount; // Don't let unbalanced )'s drive the count negative.
}
PrevTokLocation = Tok.getLocation();
PP.Lex(Tok);
return PrevTokLocation;
}
/// ConsumeBracket - This consume method keeps the bracket count up-to-date.
///
SourceLocation ConsumeBracket() {
assert(isTokenBracket() && "wrong consume method");
if (Tok.getKind() == tok::l_square)
++BracketCount;
else if (BracketCount) {
AngleBrackets.clear(*this);
--BracketCount; // Don't let unbalanced ]'s drive the count negative.
}
PrevTokLocation = Tok.getLocation();
PP.Lex(Tok);
return PrevTokLocation;
}
/// ConsumeBrace - This consume method keeps the brace count up-to-date.
///
SourceLocation ConsumeBrace() {
assert(isTokenBrace() && "wrong consume method");
if (Tok.getKind() == tok::l_brace)
++BraceCount;
else if (BraceCount) {
AngleBrackets.clear(*this);
--BraceCount; // Don't let unbalanced }'s drive the count negative.
}
PrevTokLocation = Tok.getLocation();
PP.Lex(Tok);
return PrevTokLocation;
}
/// ConsumeStringToken - Consume the current 'peek token', lexing a new one
/// and returning the token kind. This method is specific to strings, as it
/// handles string literal concatenation, as per C99 5.1.1.2, translation
/// phase #6.
SourceLocation ConsumeStringToken() {
assert(isTokenStringLiteral() &&
"Should only consume string literals with this method");
PrevTokLocation = Tok.getLocation();
PP.Lex(Tok);
return PrevTokLocation;
}
/// Consume the current code-completion token.
///
/// This routine can be called to consume the code-completion token and
/// continue processing in special cases where \c cutOffParsing() isn't
/// desired, such as token caching or completion with lookahead.
SourceLocation ConsumeCodeCompletionToken() {
assert(Tok.is(tok::code_completion));
PrevTokLocation = Tok.getLocation();
PP.Lex(Tok);
return PrevTokLocation;
}
///\ brief When we are consuming a code-completion token without having
/// matched specific position in the grammar, provide code-completion results
/// based on context.
///
/// \returns the source location of the code-completion token.
SourceLocation handleUnexpectedCodeCompletionToken();
/// Abruptly cut off parsing; mainly used when we have reached the
/// code-completion point.
void cutOffParsing() {
if (PP.isCodeCompletionEnabled())
PP.setCodeCompletionReached();
// Cut off parsing by acting as if we reached the end-of-file.
Tok.setKind(tok::eof);
}
/// Determine if we're at the end of the file or at a transition
/// between modules.
bool isEofOrEom() {
tok::TokenKind Kind = Tok.getKind();
return Kind == tok::eof || Kind == tok::annot_module_begin ||
Kind == tok::annot_module_end || Kind == tok::annot_module_include;
}
/// Checks if the \p Level is valid for use in a fold expression.
bool isFoldOperator(prec::Level Level) const;
/// Checks if the \p Kind is a valid operator for fold expressions.
bool isFoldOperator(tok::TokenKind Kind) const;
/// Initialize all pragma handlers.
void initializePragmaHandlers();
/// Destroy and reset all pragma handlers.
void resetPragmaHandlers();
/// Handle the annotation token produced for #pragma unused(...)
void HandlePragmaUnused();
/// Handle the annotation token produced for
/// #pragma GCC visibility...
void HandlePragmaVisibility();
/// Handle the annotation token produced for
/// #pragma pack...
void HandlePragmaPack();
/// Handle the annotation token produced for
/// #pragma ms_struct...
void HandlePragmaMSStruct();
void HandlePragmaMSPointersToMembers();
void HandlePragmaMSVtorDisp();
void HandlePragmaMSPragma();
bool HandlePragmaMSSection(StringRef PragmaName,
SourceLocation PragmaLocation);
bool HandlePragmaMSSegment(StringRef PragmaName,
SourceLocation PragmaLocation);
bool HandlePragmaMSInitSeg(StringRef PragmaName,
SourceLocation PragmaLocation);
/// Handle the annotation token produced for
/// #pragma align...
void HandlePragmaAlign();
/// Handle the annotation token produced for
/// #pragma clang __debug dump...
void HandlePragmaDump();
/// Handle the annotation token produced for
/// #pragma weak id...
void HandlePragmaWeak();
/// Handle the annotation token produced for
/// #pragma weak id = id...
void HandlePragmaWeakAlias();
/// Handle the annotation token produced for
/// #pragma redefine_extname...
void HandlePragmaRedefineExtname();
/// Handle the annotation token produced for
/// #pragma STDC FP_CONTRACT...
void HandlePragmaFPContract();
/// Handle the annotation token produced for
/// #pragma STDC FENV_ACCESS...
void HandlePragmaFEnvAccess();
/// Handle the annotation token produced for
/// #pragma STDC FENV_ROUND...
void HandlePragmaFEnvRound();
/// Handle the annotation token produced for
/// #pragma float_control
void HandlePragmaFloatControl();
/// \brief Handle the annotation token produced for
/// #pragma clang fp ...
void HandlePragmaFP();
/// Handle the annotation token produced for
/// #pragma OPENCL EXTENSION...
void HandlePragmaOpenCLExtension();
/// Handle the annotation token produced for
/// #pragma clang __debug captured
StmtResult HandlePragmaCaptured();
/// Handle the annotation token produced for
/// #pragma clang loop and #pragma unroll.
bool HandlePragmaLoopHint(LoopHint &Hint);
bool ParsePragmaAttributeSubjectMatchRuleSet(
attr::ParsedSubjectMatchRuleSet &SubjectMatchRules,
SourceLocation &AnyLoc, SourceLocation &LastMatchRuleEndLoc);
void HandlePragmaAttribute();
/// GetLookAheadToken - This peeks ahead N tokens and returns that token
/// without consuming any tokens. LookAhead(0) returns 'Tok', LookAhead(1)
/// returns the token after Tok, etc.
///
/// Note that this differs from the Preprocessor's LookAhead method, because
/// the Parser always has one token lexed that the preprocessor doesn't.
///
const Token &GetLookAheadToken(unsigned N) {
if (N == 0 || Tok.is(tok::eof)) return Tok;
return PP.LookAhead(N-1);
}
public:
/// NextToken - This peeks ahead one token and returns it without
/// consuming it.
const Token &NextToken() {
return PP.LookAhead(0);
}
/// getTypeAnnotation - Read a parsed type out of an annotation token.
static TypeResult getTypeAnnotation(const Token &Tok) {
if (!Tok.getAnnotationValue())
return TypeError();
return ParsedType::getFromOpaquePtr(Tok.getAnnotationValue());
}
private:
static void setTypeAnnotation(Token &Tok, TypeResult T) {
assert((T.isInvalid() || T.get()) &&
"produced a valid-but-null type annotation?");
Tok.setAnnotationValue(T.isInvalid() ? nullptr : T.get().getAsOpaquePtr());
}
static NamedDecl *getNonTypeAnnotation(const Token &Tok) {
return static_cast<NamedDecl*>(Tok.getAnnotationValue());
}
static void setNonTypeAnnotation(Token &Tok, NamedDecl *ND) {
Tok.setAnnotationValue(ND);
}
static IdentifierInfo *getIdentifierAnnotation(const Token &Tok) {
return static_cast<IdentifierInfo*>(Tok.getAnnotationValue());
}
static void setIdentifierAnnotation(Token &Tok, IdentifierInfo *ND) {
Tok.setAnnotationValue(ND);
}
/// Read an already-translated primary expression out of an annotation
/// token.
static ExprResult getExprAnnotation(const Token &Tok) {
return ExprResult::getFromOpaquePointer(Tok.getAnnotationValue());
}
/// Set the primary expression corresponding to the given annotation
/// token.
static void setExprAnnotation(Token &Tok, ExprResult ER) {
Tok.setAnnotationValue(ER.getAsOpaquePointer());
}
public:
// If NeedType is true, then TryAnnotateTypeOrScopeToken will try harder to
// find a type name by attempting typo correction.
bool TryAnnotateTypeOrScopeToken();
bool TryAnnotateTypeOrScopeTokenAfterScopeSpec(CXXScopeSpec &SS,
bool IsNewScope);
bool TryAnnotateCXXScopeToken(bool EnteringContext = false);
bool MightBeCXXScopeToken() {
return Tok.is(tok::identifier) || Tok.is(tok::coloncolon) ||
(Tok.is(tok::annot_template_id) &&
NextToken().is(tok::coloncolon)) ||
Tok.is(tok::kw_decltype) || Tok.is(tok::kw___super);
}
bool TryAnnotateOptionalCXXScopeToken(bool EnteringContext = false) {
return MightBeCXXScopeToken() && TryAnnotateCXXScopeToken(EnteringContext);
}
private:
enum AnnotatedNameKind {
/// Annotation has failed and emitted an error.
ANK_Error,
/// The identifier is a tentatively-declared name.
ANK_TentativeDecl,
/// The identifier is a template name. FIXME: Add an annotation for that.
ANK_TemplateName,
/// The identifier can't be resolved.
ANK_Unresolved,
/// Annotation was successful.
ANK_Success
};
AnnotatedNameKind TryAnnotateName(CorrectionCandidateCallback *CCC = nullptr);
/// Push a tok::annot_cxxscope token onto the token stream.
void AnnotateScopeToken(CXXScopeSpec &SS, bool IsNewAnnotation);
/// TryAltiVecToken - Check for context-sensitive AltiVec identifier tokens,
/// replacing them with the non-context-sensitive keywords. This returns
/// true if the token was replaced.
bool TryAltiVecToken(DeclSpec &DS, SourceLocation Loc,
const char *&PrevSpec, unsigned &DiagID,
bool &isInvalid) {
if (!getLangOpts().AltiVec && !getLangOpts().ZVector)
return false;
if (Tok.getIdentifierInfo() != Ident_vector &&
Tok.getIdentifierInfo() != Ident_bool &&
(!getLangOpts().AltiVec || Tok.getIdentifierInfo() != Ident_pixel))
return false;
return TryAltiVecTokenOutOfLine(DS, Loc, PrevSpec, DiagID, isInvalid);
}
/// TryAltiVecVectorToken - Check for context-sensitive AltiVec vector
/// identifier token, replacing it with the non-context-sensitive __vector.
/// This returns true if the token was replaced.
bool TryAltiVecVectorToken() {
if ((!getLangOpts().AltiVec && !getLangOpts().ZVector) ||
Tok.getIdentifierInfo() != Ident_vector) return false;
return TryAltiVecVectorTokenOutOfLine();
}
bool TryAltiVecVectorTokenOutOfLine();
bool TryAltiVecTokenOutOfLine(DeclSpec &DS, SourceLocation Loc,
const char *&PrevSpec, unsigned &DiagID,
bool &isInvalid);
/// Returns true if the current token is the identifier 'instancetype'.
///
/// Should only be used in Objective-C language modes.
bool isObjCInstancetype() {
assert(getLangOpts().ObjC);
if (Tok.isAnnotation())
return false;
if (!Ident_instancetype)
Ident_instancetype = PP.getIdentifierInfo("instancetype");
return Tok.getIdentifierInfo() == Ident_instancetype;
}
/// TryKeywordIdentFallback - For compatibility with system headers using
/// keywords as identifiers, attempt to convert the current token to an
/// identifier and optionally disable the keyword for the remainder of the
/// translation unit. This returns false if the token was not replaced,
/// otherwise emits a diagnostic and returns true.
bool TryKeywordIdentFallback(bool DisableKeyword);
/// Get the TemplateIdAnnotation from the token.
TemplateIdAnnotation *takeTemplateIdAnnotation(const Token &tok);
/// TentativeParsingAction - An object that is used as a kind of "tentative
/// parsing transaction". It gets instantiated to mark the token position and
/// after the token consumption is done, Commit() or Revert() is called to
/// either "commit the consumed tokens" or revert to the previously marked
/// token position. Example:
///
/// TentativeParsingAction TPA(*this);
/// ConsumeToken();
/// ....
/// TPA.Revert();
///
class TentativeParsingAction {
Parser &P;
PreferredTypeBuilder PrevPreferredType;
Token PrevTok;
size_t PrevTentativelyDeclaredIdentifierCount;
unsigned short PrevParenCount, PrevBracketCount, PrevBraceCount;
bool isActive;
public:
explicit TentativeParsingAction(Parser& p) : P(p) {
PrevPreferredType = P.PreferredType;
PrevTok = P.Tok;
PrevTentativelyDeclaredIdentifierCount =
P.TentativelyDeclaredIdentifiers.size();
PrevParenCount = P.ParenCount;
PrevBracketCount = P.BracketCount;
PrevBraceCount = P.BraceCount;
P.PP.EnableBacktrackAtThisPos();
isActive = true;
}
void Commit() {
assert(isActive && "Parsing action was finished!");
P.TentativelyDeclaredIdentifiers.resize(
PrevTentativelyDeclaredIdentifierCount);
P.PP.CommitBacktrackedTokens();
isActive = false;
}
void Revert() {
assert(isActive && "Parsing action was finished!");
P.PP.Backtrack();
P.PreferredType = PrevPreferredType;
P.Tok = PrevTok;
P.TentativelyDeclaredIdentifiers.resize(
PrevTentativelyDeclaredIdentifierCount);
P.ParenCount = PrevParenCount;
P.BracketCount = PrevBracketCount;
P.BraceCount = PrevBraceCount;
isActive = false;
}
~TentativeParsingAction() {
assert(!isActive && "Forgot to call Commit or Revert!");
}
};
/// A TentativeParsingAction that automatically reverts in its destructor.
/// Useful for disambiguation parses that will always be reverted.
class RevertingTentativeParsingAction
: private Parser::TentativeParsingAction {
public:
RevertingTentativeParsingAction(Parser &P)
: Parser::TentativeParsingAction(P) {}
~RevertingTentativeParsingAction() { Revert(); }
};
class UnannotatedTentativeParsingAction;
/// ObjCDeclContextSwitch - An object used to switch context from
/// an objective-c decl context to its enclosing decl context and
/// back.
class ObjCDeclContextSwitch {
Parser &P;
Decl *DC;
SaveAndRestore<bool> WithinObjCContainer;
public:
explicit ObjCDeclContextSwitch(Parser &p)
: P(p), DC(p.getObjCDeclContext()),
WithinObjCContainer(P.ParsingInObjCContainer, DC != nullptr) {
if (DC)
P.Actions.ActOnObjCTemporaryExitContainerContext(cast<DeclContext>(DC));
}
~ObjCDeclContextSwitch() {
if (DC)
P.Actions.ActOnObjCReenterContainerContext(cast<DeclContext>(DC));
}
};
/// ExpectAndConsume - The parser expects that 'ExpectedTok' is next in the
/// input. If so, it is consumed and false is returned.
///
/// If a trivial punctuator misspelling is encountered, a FixIt error
/// diagnostic is issued and false is returned after recovery.
///
/// If the input is malformed, this emits the specified diagnostic and true is
/// returned.
bool ExpectAndConsume(tok::TokenKind ExpectedTok,
unsigned Diag = diag::err_expected,
StringRef DiagMsg = "");
/// The parser expects a semicolon and, if present, will consume it.
///
/// If the next token is not a semicolon, this emits the specified diagnostic,
/// or, if there's just some closing-delimiter noise (e.g., ')' or ']') prior
/// to the semicolon, consumes that extra token.
bool ExpectAndConsumeSemi(unsigned DiagID);
/// The kind of extra semi diagnostic to emit.
enum ExtraSemiKind {
OutsideFunction = 0,
InsideStruct = 1,
InstanceVariableList = 2,
AfterMemberFunctionDefinition = 3
};
/// Consume any extra semi-colons until the end of the line.
void ConsumeExtraSemi(ExtraSemiKind Kind, DeclSpec::TST T = TST_unspecified);
/// Return false if the next token is an identifier. An 'expected identifier'
/// error is emitted otherwise.
///
/// The parser tries to recover from the error by checking if the next token
/// is a C++ keyword when parsing Objective-C++. Return false if the recovery
/// was successful.
bool expectIdentifier();
/// Kinds of compound pseudo-tokens formed by a sequence of two real tokens.
enum class CompoundToken {
/// A '(' '{' beginning a statement-expression.
StmtExprBegin,
/// A '}' ')' ending a statement-expression.
StmtExprEnd,
/// A '[' '[' beginning a C++11 or C2x attribute.
AttrBegin,
/// A ']' ']' ending a C++11 or C2x attribute.
AttrEnd,
/// A '::' '*' forming a C++ pointer-to-member declaration.
MemberPtr,
};
/// Check that a compound operator was written in a "sensible" way, and warn
/// if not.
void checkCompoundToken(SourceLocation FirstTokLoc,
tok::TokenKind FirstTokKind, CompoundToken Op);
public:
//===--------------------------------------------------------------------===//
// Scope manipulation
/// ParseScope - Introduces a new scope for parsing. The kind of
/// scope is determined by ScopeFlags. Objects of this type should
/// be created on the stack to coincide with the position where the
/// parser enters the new scope, and this object's constructor will
/// create that new scope. Similarly, once the object is destroyed
/// the parser will exit the scope.
class ParseScope {
Parser *Self;
ParseScope(const ParseScope &) = delete;
void operator=(const ParseScope &) = delete;
public:
// ParseScope - Construct a new object to manage a scope in the
// parser Self where the new Scope is created with the flags
// ScopeFlags, but only when we aren't about to enter a compound statement.
ParseScope(Parser *Self, unsigned ScopeFlags, bool EnteredScope = true,
bool BeforeCompoundStmt = false)
: Self(Self) {
if (EnteredScope && !BeforeCompoundStmt)
Self->EnterScope(ScopeFlags);
else {
if (BeforeCompoundStmt)
Self->incrementMSManglingNumber();
this->Self = nullptr;
}
}
// Exit - Exit the scope associated with this object now, rather
// than waiting until the object is destroyed.
void Exit() {
if (Self) {
Self->ExitScope();
Self = nullptr;
}
}
~ParseScope() {
Exit();
}
};
/// Introduces zero or more scopes for parsing. The scopes will all be exited
/// when the object is destroyed.
class MultiParseScope {
Parser &Self;
unsigned NumScopes = 0;
MultiParseScope(const MultiParseScope&) = delete;
public:
MultiParseScope(Parser &Self) : Self(Self) {}
void Enter(unsigned ScopeFlags) {
Self.EnterScope(ScopeFlags);
++NumScopes;
}
void Exit() {
while (NumScopes) {
Self.ExitScope();
--NumScopes;
}
}
~MultiParseScope() {
Exit();
}
};
/// EnterScope - Start a new scope.
void EnterScope(unsigned ScopeFlags);
/// ExitScope - Pop a scope off the scope stack.
void ExitScope();
/// Re-enter the template scopes for a declaration that might be a template.
unsigned ReenterTemplateScopes(MultiParseScope &S, Decl *D);
private:
/// RAII object used to modify the scope flags for the current scope.
class ParseScopeFlags {
Scope *CurScope;
unsigned OldFlags;
ParseScopeFlags(const ParseScopeFlags &) = delete;
void operator=(const ParseScopeFlags &) = delete;
public:
ParseScopeFlags(Parser *Self, unsigned ScopeFlags, bool ManageFlags = true);
~ParseScopeFlags();
};
//===--------------------------------------------------------------------===//
// Diagnostic Emission and Error recovery.
public:
DiagnosticBuilder Diag(SourceLocation Loc, unsigned DiagID);
DiagnosticBuilder Diag(const Token &Tok, unsigned DiagID);
DiagnosticBuilder Diag(unsigned DiagID) {
return Diag(Tok, DiagID);
}
private:
void SuggestParentheses(SourceLocation Loc, unsigned DK,
SourceRange ParenRange);
void CheckNestedObjCContexts(SourceLocation AtLoc);
public:
/// Control flags for SkipUntil functions.
enum SkipUntilFlags {
StopAtSemi = 1 << 0, ///< Stop skipping at semicolon
/// Stop skipping at specified token, but don't skip the token itself
StopBeforeMatch = 1 << 1,
StopAtCodeCompletion = 1 << 2 ///< Stop at code completion
};
friend constexpr SkipUntilFlags operator|(SkipUntilFlags L,
SkipUntilFlags R) {
return static_cast<SkipUntilFlags>(static_cast<unsigned>(L) |
static_cast<unsigned>(R));
}
/// SkipUntil - Read tokens until we get to the specified token, then consume
/// it (unless StopBeforeMatch is specified). Because we cannot guarantee
/// that the token will ever occur, this skips to the next token, or to some
/// likely good stopping point. If Flags has StopAtSemi flag, skipping will
/// stop at a ';' character. Balances (), [], and {} delimiter tokens while
/// skipping.
///
/// If SkipUntil finds the specified token, it returns true, otherwise it
/// returns false.
bool SkipUntil(tok::TokenKind T,
SkipUntilFlags Flags = static_cast<SkipUntilFlags>(0)) {
return SkipUntil(llvm::makeArrayRef(T), Flags);
}
bool SkipUntil(tok::TokenKind T1, tok::TokenKind T2,
SkipUntilFlags Flags = static_cast<SkipUntilFlags>(0)) {
tok::TokenKind TokArray[] = {T1, T2};
return SkipUntil(TokArray, Flags);
}
bool SkipUntil(tok::TokenKind T1, tok::TokenKind T2, tok::TokenKind T3,
SkipUntilFlags Flags = static_cast<SkipUntilFlags>(0)) {
tok::TokenKind TokArray[] = {T1, T2, T3};
return SkipUntil(TokArray, Flags);
}
bool SkipUntil(ArrayRef<tok::TokenKind> Toks,
SkipUntilFlags Flags = static_cast<SkipUntilFlags>(0));
/// SkipMalformedDecl - Read tokens until we get to some likely good stopping
/// point for skipping past a simple-declaration.
void SkipMalformedDecl();
/// The location of the first statement inside an else that might
/// have a missleading indentation. If there is no
/// MisleadingIndentationChecker on an else active, this location is invalid.
SourceLocation MisleadingIndentationElseLoc;
private:
//===--------------------------------------------------------------------===//
// Lexing and parsing of C++ inline methods.
struct ParsingClass;
/// [class.mem]p1: "... the class is regarded as complete within
/// - function bodies
/// - default arguments
/// - exception-specifications (TODO: C++0x)
/// - and brace-or-equal-initializers for non-static data members
/// (including such things in nested classes)."
/// LateParsedDeclarations build the tree of those elements so they can
/// be parsed after parsing the top-level class.
class LateParsedDeclaration {
public:
virtual ~LateParsedDeclaration();
virtual void ParseLexedMethodDeclarations();
virtual void ParseLexedMemberInitializers();
virtual void ParseLexedMethodDefs();
virtual void ParseLexedAttributes();
virtual void ParseLexedPragmas();
};
/// Inner node of the LateParsedDeclaration tree that parses
/// all its members recursively.
class LateParsedClass : public LateParsedDeclaration {
public:
LateParsedClass(Parser *P, ParsingClass *C);
~LateParsedClass() override;
void ParseLexedMethodDeclarations() override;
void ParseLexedMemberInitializers() override;
void ParseLexedMethodDefs() override;
void ParseLexedAttributes() override;
void ParseLexedPragmas() override;
private:
Parser *Self;
ParsingClass *Class;
};
/// Contains the lexed tokens of an attribute with arguments that
/// may reference member variables and so need to be parsed at the
/// end of the class declaration after parsing all other member
/// member declarations.
/// FIXME: Perhaps we should change the name of LateParsedDeclaration to
/// LateParsedTokens.
struct LateParsedAttribute : public LateParsedDeclaration {
Parser *Self;
CachedTokens Toks;
IdentifierInfo &AttrName;
IdentifierInfo *MacroII = nullptr;
SourceLocation AttrNameLoc;
SmallVector<Decl*, 2> Decls;
explicit LateParsedAttribute(Parser *P, IdentifierInfo &Name,
SourceLocation Loc)
: Self(P), AttrName(Name), AttrNameLoc(Loc) {}
void ParseLexedAttributes() override;
void addDecl(Decl *D) { Decls.push_back(D); }
};
/// Contains the lexed tokens of a pragma with arguments that
/// may reference member variables and so need to be parsed at the
/// end of the class declaration after parsing all other member
/// member declarations.
class LateParsedPragma : public LateParsedDeclaration {
Parser *Self = nullptr;
AccessSpecifier AS = AS_none;
CachedTokens Toks;
public:
explicit LateParsedPragma(Parser *P, AccessSpecifier AS)
: Self(P), AS(AS) {}
void takeToks(CachedTokens &Cached) { Toks.swap(Cached); }
const CachedTokens &toks() const { return Toks; }
AccessSpecifier getAccessSpecifier() const { return AS; }
void ParseLexedPragmas() override;
};
// A list of late-parsed attributes. Used by ParseGNUAttributes.
class LateParsedAttrList: public SmallVector<LateParsedAttribute *, 2> {
public:
LateParsedAttrList(bool PSoon = false) : ParseSoon(PSoon) { }
bool parseSoon() { return ParseSoon; }
private:
bool ParseSoon; // Are we planning to parse these shortly after creation?
};
/// Contains the lexed tokens of a member function definition
/// which needs to be parsed at the end of the class declaration
/// after parsing all other member declarations.
struct LexedMethod : public LateParsedDeclaration {
Parser *Self;
Decl *D;
CachedTokens Toks;
explicit LexedMethod(Parser *P, Decl *MD) : Self(P), D(MD) {}
void ParseLexedMethodDefs() override;
};
/// LateParsedDefaultArgument - Keeps track of a parameter that may
/// have a default argument that cannot be parsed yet because it
/// occurs within a member function declaration inside the class
/// (C++ [class.mem]p2).
struct LateParsedDefaultArgument {
explicit LateParsedDefaultArgument(Decl *P,
std::unique_ptr<CachedTokens> Toks = nullptr)
: Param(P), Toks(std::move(Toks)) { }
/// Param - The parameter declaration for this parameter.
Decl *Param;
/// Toks - The sequence of tokens that comprises the default
/// argument expression, not including the '=' or the terminating
/// ')' or ','. This will be NULL for parameters that have no
/// default argument.
std::unique_ptr<CachedTokens> Toks;
};
/// LateParsedMethodDeclaration - A method declaration inside a class that
/// contains at least one entity whose parsing needs to be delayed
/// until the class itself is completely-defined, such as a default
/// argument (C++ [class.mem]p2).
struct LateParsedMethodDeclaration : public LateParsedDeclaration {
explicit LateParsedMethodDeclaration(Parser *P, Decl *M)
: Self(P), Method(M), ExceptionSpecTokens(nullptr) {}
void ParseLexedMethodDeclarations() override;
Parser *Self;
/// Method - The method declaration.
Decl *Method;
/// DefaultArgs - Contains the parameters of the function and
/// their default arguments. At least one of the parameters will
/// have a default argument, but all of the parameters of the
/// method will be stored so that they can be reintroduced into
/// scope at the appropriate times.
SmallVector<LateParsedDefaultArgument, 8> DefaultArgs;
/// The set of tokens that make up an exception-specification that
/// has not yet been parsed.
CachedTokens *ExceptionSpecTokens;
};
/// LateParsedMemberInitializer - An initializer for a non-static class data
/// member whose parsing must to be delayed until the class is completely
/// defined (C++11 [class.mem]p2).
struct LateParsedMemberInitializer : public LateParsedDeclaration {
LateParsedMemberInitializer(Parser *P, Decl *FD)
: Self(P), Field(FD) { }
void ParseLexedMemberInitializers() override;
Parser *Self;
/// Field - The field declaration.
Decl *Field;
/// CachedTokens - The sequence of tokens that comprises the initializer,
/// including any leading '='.
CachedTokens Toks;
};
/// LateParsedDeclarationsContainer - During parsing of a top (non-nested)
/// C++ class, its method declarations that contain parts that won't be
/// parsed until after the definition is completed (C++ [class.mem]p2),
/// the method declarations and possibly attached inline definitions
/// will be stored here with the tokens that will be parsed to create those
/// entities.
typedef SmallVector<LateParsedDeclaration*,2> LateParsedDeclarationsContainer;
/// Representation of a class that has been parsed, including
/// any member function declarations or definitions that need to be
/// parsed after the corresponding top-level class is complete.
struct ParsingClass {
ParsingClass(Decl *TagOrTemplate, bool TopLevelClass, bool IsInterface)
: TopLevelClass(TopLevelClass), IsInterface(IsInterface),
TagOrTemplate(TagOrTemplate) {}
/// Whether this is a "top-level" class, meaning that it is
/// not nested within another class.
bool TopLevelClass : 1;
/// Whether this class is an __interface.
bool IsInterface : 1;
/// The class or class template whose definition we are parsing.
Decl *TagOrTemplate;
/// LateParsedDeclarations - Method declarations, inline definitions and
/// nested classes that contain pieces whose parsing will be delayed until
/// the top-level class is fully defined.
LateParsedDeclarationsContainer LateParsedDeclarations;
};
/// The stack of classes that is currently being
/// parsed. Nested and local classes will be pushed onto this stack
/// when they are parsed, and removed afterward.
std::stack<ParsingClass *> ClassStack;
ParsingClass &getCurrentClass() {
assert(!ClassStack.empty() && "No lexed method stacks!");
return *ClassStack.top();
}
/// RAII object used to manage the parsing of a class definition.
class ParsingClassDefinition {
Parser &P;
bool Popped;
Sema::ParsingClassState State;
public:
ParsingClassDefinition(Parser &P, Decl *TagOrTemplate, bool TopLevelClass,
bool IsInterface)
: P(P), Popped(false),
State(P.PushParsingClass(TagOrTemplate, TopLevelClass, IsInterface)) {
}
/// Pop this class of the stack.
void Pop() {
assert(!Popped && "Nested class has already been popped");
Popped = true;
P.PopParsingClass(State);
}
~ParsingClassDefinition() {
if (!Popped)
P.PopParsingClass(State);
}
};
/// Contains information about any template-specific
/// information that has been parsed prior to parsing declaration
/// specifiers.
struct ParsedTemplateInfo {
ParsedTemplateInfo()
: Kind(NonTemplate), TemplateParams(nullptr), TemplateLoc() { }
ParsedTemplateInfo(TemplateParameterLists *TemplateParams,
bool isSpecialization,
bool lastParameterListWasEmpty = false)
: Kind(isSpecialization? ExplicitSpecialization : Template),
TemplateParams(TemplateParams),
LastParameterListWasEmpty(lastParameterListWasEmpty) { }
explicit ParsedTemplateInfo(SourceLocation ExternLoc,
SourceLocation TemplateLoc)
: Kind(ExplicitInstantiation), TemplateParams(nullptr),
ExternLoc(ExternLoc), TemplateLoc(TemplateLoc),
LastParameterListWasEmpty(false){ }
/// The kind of template we are parsing.
enum {
/// We are not parsing a template at all.
NonTemplate = 0,
/// We are parsing a template declaration.
Template,
/// We are parsing an explicit specialization.
ExplicitSpecialization,
/// We are parsing an explicit instantiation.
ExplicitInstantiation
} Kind;
/// The template parameter lists, for template declarations
/// and explicit specializations.
TemplateParameterLists *TemplateParams;
/// The location of the 'extern' keyword, if any, for an explicit
/// instantiation
SourceLocation ExternLoc;
/// The location of the 'template' keyword, for an explicit
/// instantiation.
SourceLocation TemplateLoc;
/// Whether the last template parameter list was empty.
bool LastParameterListWasEmpty;
SourceRange getSourceRange() const LLVM_READONLY;
};
// In ParseCXXInlineMethods.cpp.
struct ReenterTemplateScopeRAII;
struct ReenterClassScopeRAII;
void LexTemplateFunctionForLateParsing(CachedTokens &Toks);
void ParseLateTemplatedFuncDef(LateParsedTemplate &LPT);
static void LateTemplateParserCallback(void *P, LateParsedTemplate &LPT);
Sema::ParsingClassState
PushParsingClass(Decl *TagOrTemplate, bool TopLevelClass, bool IsInterface);
void DeallocateParsedClasses(ParsingClass *Class);
void PopParsingClass(Sema::ParsingClassState);
enum CachedInitKind {
CIK_DefaultArgument,
CIK_DefaultInitializer
};
NamedDecl *ParseCXXInlineMethodDef(AccessSpecifier AS,
ParsedAttributes &AccessAttrs,
ParsingDeclarator &D,
const ParsedTemplateInfo &TemplateInfo,
const VirtSpecifiers &VS,
SourceLocation PureSpecLoc);
void ParseCXXNonStaticMemberInitializer(Decl *VarD);
void ParseLexedAttributes(ParsingClass &Class);
void ParseLexedAttributeList(LateParsedAttrList &LAs, Decl *D,
bool EnterScope, bool OnDefinition);
void ParseLexedAttribute(LateParsedAttribute &LA,
bool EnterScope, bool OnDefinition);
void ParseLexedMethodDeclarations(ParsingClass &Class);
void ParseLexedMethodDeclaration(LateParsedMethodDeclaration &LM);
void ParseLexedMethodDefs(ParsingClass &Class);
void ParseLexedMethodDef(LexedMethod &LM);
void ParseLexedMemberInitializers(ParsingClass &Class);
void ParseLexedMemberInitializer(LateParsedMemberInitializer &MI);
void ParseLexedObjCMethodDefs(LexedMethod &LM, bool parseMethod);
void ParseLexedPragmas(ParsingClass &Class);
void ParseLexedPragma(LateParsedPragma &LP);
bool ConsumeAndStoreFunctionPrologue(CachedTokens &Toks);
bool ConsumeAndStoreInitializer(CachedTokens &Toks, CachedInitKind CIK);
bool ConsumeAndStoreConditional(CachedTokens &Toks);
bool ConsumeAndStoreUntil(tok::TokenKind T1,
CachedTokens &Toks,
bool StopAtSemi = true,
bool ConsumeFinalToken = true) {
return ConsumeAndStoreUntil(T1, T1, Toks, StopAtSemi, ConsumeFinalToken);
}
bool ConsumeAndStoreUntil(tok::TokenKind T1, tok::TokenKind T2,
CachedTokens &Toks,
bool StopAtSemi = true,
bool ConsumeFinalToken = true);
//===--------------------------------------------------------------------===//
// C99 6.9: External Definitions.
struct ParsedAttributesWithRange : ParsedAttributes {
ParsedAttributesWithRange(AttributeFactory &factory)
: ParsedAttributes(factory) {}
void clear() {
ParsedAttributes::clear();
Range = SourceRange();
}
SourceRange Range;
};
struct ParsedAttributesViewWithRange : ParsedAttributesView {
ParsedAttributesViewWithRange() : ParsedAttributesView() {}
void clearListOnly() {
ParsedAttributesView::clearListOnly();
Range = SourceRange();
}
SourceRange Range;
};
DeclGroupPtrTy ParseExternalDeclaration(ParsedAttributesWithRange &attrs,
ParsingDeclSpec *DS = nullptr);
bool isDeclarationAfterDeclarator();
bool isStartOfFunctionDefinition(const ParsingDeclarator &Declarator);
DeclGroupPtrTy ParseDeclarationOrFunctionDefinition(
ParsedAttributesWithRange &attrs,
ParsingDeclSpec *DS = nullptr,
AccessSpecifier AS = AS_none);
DeclGroupPtrTy ParseDeclOrFunctionDefInternal(ParsedAttributesWithRange &attrs,
ParsingDeclSpec &DS,
AccessSpecifier AS);
void SkipFunctionBody();
Decl *ParseFunctionDefinition(ParsingDeclarator &D,
const ParsedTemplateInfo &TemplateInfo = ParsedTemplateInfo(),
LateParsedAttrList *LateParsedAttrs = nullptr);
void ParseKNRParamDeclarations(Declarator &D);
// EndLoc is filled with the location of the last token of the simple-asm.
ExprResult ParseSimpleAsm(bool ForAsmLabel, SourceLocation *EndLoc);
ExprResult ParseAsmStringLiteral(bool ForAsmLabel);
// Objective-C External Declarations
void MaybeSkipAttributes(tok::ObjCKeywordKind Kind);
DeclGroupPtrTy ParseObjCAtDirectives(ParsedAttributesWithRange &Attrs);
DeclGroupPtrTy ParseObjCAtClassDeclaration(SourceLocation atLoc);
Decl *ParseObjCAtInterfaceDeclaration(SourceLocation AtLoc,
ParsedAttributes &prefixAttrs);
class ObjCTypeParamListScope;
ObjCTypeParamList *parseObjCTypeParamList();
ObjCTypeParamList *parseObjCTypeParamListOrProtocolRefs(
ObjCTypeParamListScope &Scope, SourceLocation &lAngleLoc,
SmallVectorImpl<IdentifierLocPair> &protocolIdents,
SourceLocation &rAngleLoc, bool mayBeProtocolList = true);
void HelperActionsForIvarDeclarations(Decl *interfaceDecl, SourceLocation atLoc,
BalancedDelimiterTracker &T,
SmallVectorImpl<Decl *> &AllIvarDecls,
bool RBraceMissing);
void ParseObjCClassInstanceVariables(Decl *interfaceDecl,
tok::ObjCKeywordKind visibility,
SourceLocation atLoc);
bool ParseObjCProtocolReferences(SmallVectorImpl<Decl *> &P,
SmallVectorImpl<SourceLocation> &PLocs,
bool WarnOnDeclarations,
bool ForObjCContainer,
SourceLocation &LAngleLoc,
SourceLocation &EndProtoLoc,
bool consumeLastToken);
/// Parse the first angle-bracket-delimited clause for an
/// Objective-C object or object pointer type, which may be either
/// type arguments or protocol qualifiers.
void parseObjCTypeArgsOrProtocolQualifiers(
ParsedType baseType,
SourceLocation &typeArgsLAngleLoc,
SmallVectorImpl<ParsedType> &typeArgs,
SourceLocation &typeArgsRAngleLoc,
SourceLocation &protocolLAngleLoc,
SmallVectorImpl<Decl *> &protocols,
SmallVectorImpl<SourceLocation> &protocolLocs,
SourceLocation &protocolRAngleLoc,
bool consumeLastToken,
bool warnOnIncompleteProtocols);
/// Parse either Objective-C type arguments or protocol qualifiers; if the
/// former, also parse protocol qualifiers afterward.
void parseObjCTypeArgsAndProtocolQualifiers(
ParsedType baseType,
SourceLocation &typeArgsLAngleLoc,
SmallVectorImpl<ParsedType> &typeArgs,
SourceLocation &typeArgsRAngleLoc,
SourceLocation &protocolLAngleLoc,
SmallVectorImpl<Decl *> &protocols,
SmallVectorImpl<SourceLocation> &protocolLocs,
SourceLocation &protocolRAngleLoc,
bool consumeLastToken);
/// Parse a protocol qualifier type such as '<NSCopying>', which is
/// an anachronistic way of writing 'id<NSCopying>'.
TypeResult parseObjCProtocolQualifierType(SourceLocation &rAngleLoc);
/// Parse Objective-C type arguments and protocol qualifiers, extending the
/// current type with the parsed result.
TypeResult parseObjCTypeArgsAndProtocolQualifiers(SourceLocation loc,
ParsedType type,
bool consumeLastToken,
SourceLocation &endLoc);
void ParseObjCInterfaceDeclList(tok::ObjCKeywordKind contextKey,
Decl *CDecl);
DeclGroupPtrTy ParseObjCAtProtocolDeclaration(SourceLocation atLoc,
ParsedAttributes &prefixAttrs);
struct ObjCImplParsingDataRAII {
Parser &P;
Decl *Dcl;
bool HasCFunction;
typedef SmallVector<LexedMethod*, 8> LateParsedObjCMethodContainer;
LateParsedObjCMethodContainer LateParsedObjCMethods;
ObjCImplParsingDataRAII(Parser &parser, Decl *D)
: P(parser), Dcl(D), HasCFunction(false) {
P.CurParsedObjCImpl = this;
Finished = false;
}
~ObjCImplParsingDataRAII();
void finish(SourceRange AtEnd);
bool isFinished() const { return Finished; }
private:
bool Finished;
};
ObjCImplParsingDataRAII *CurParsedObjCImpl;
void StashAwayMethodOrFunctionBodyTokens(Decl *MDecl);
DeclGroupPtrTy ParseObjCAtImplementationDeclaration(SourceLocation AtLoc,
ParsedAttributes &Attrs);
DeclGroupPtrTy ParseObjCAtEndDeclaration(SourceRange atEnd);
Decl *ParseObjCAtAliasDeclaration(SourceLocation atLoc);
Decl *ParseObjCPropertySynthesize(SourceLocation atLoc);
Decl *ParseObjCPropertyDynamic(SourceLocation atLoc);
IdentifierInfo *ParseObjCSelectorPiece(SourceLocation &MethodLocation);
// Definitions for Objective-c context sensitive keywords recognition.
enum ObjCTypeQual {
objc_in=0, objc_out, objc_inout, objc_oneway, objc_bycopy, objc_byref,
objc_nonnull, objc_nullable, objc_null_unspecified,
objc_NumQuals
};
IdentifierInfo *ObjCTypeQuals[objc_NumQuals];
bool isTokIdentifier_in() const;
ParsedType ParseObjCTypeName(ObjCDeclSpec &DS, DeclaratorContext Ctx,
ParsedAttributes *ParamAttrs);
Decl *ParseObjCMethodPrototype(
tok::ObjCKeywordKind MethodImplKind = tok::objc_not_keyword,
bool MethodDefinition = true);
Decl *ParseObjCMethodDecl(SourceLocation mLoc, tok::TokenKind mType,
tok::ObjCKeywordKind MethodImplKind = tok::objc_not_keyword,
bool MethodDefinition=true);
void ParseObjCPropertyAttribute(ObjCDeclSpec &DS);
Decl *ParseObjCMethodDefinition();
public:
//===--------------------------------------------------------------------===//
// C99 6.5: Expressions.
/// TypeCastState - State whether an expression is or may be a type cast.
enum TypeCastState {
NotTypeCast = 0,
MaybeTypeCast,
IsTypeCast
};
ExprResult ParseExpression(TypeCastState isTypeCast = NotTypeCast);
ExprResult ParseConstantExpressionInExprEvalContext(
TypeCastState isTypeCast = NotTypeCast);
ExprResult ParseConstantExpression(TypeCastState isTypeCast = NotTypeCast);
ExprResult ParseCaseExpression(SourceLocation CaseLoc);
ExprResult ParseConstraintExpression();
ExprResult
ParseConstraintLogicalAndExpression(bool IsTrailingRequiresClause);
ExprResult ParseConstraintLogicalOrExpression(bool IsTrailingRequiresClause);
// Expr that doesn't include commas.
ExprResult ParseAssignmentExpression(TypeCastState isTypeCast = NotTypeCast);
ExprResult ParseMSAsmIdentifier(llvm::SmallVectorImpl<Token> &LineToks,
unsigned &NumLineToksConsumed,
bool IsUnevaluated);
ExprResult ParseStringLiteralExpression(bool AllowUserDefinedLiteral = false);
private:
ExprResult ParseExpressionWithLeadingAt(SourceLocation AtLoc);
ExprResult ParseExpressionWithLeadingExtension(SourceLocation ExtLoc);
ExprResult ParseRHSOfBinaryExpression(ExprResult LHS,
prec::Level MinPrec);
/// Control what ParseCastExpression will parse.
enum CastParseKind {
AnyCastExpr = 0,
UnaryExprOnly,
PrimaryExprOnly
};
ExprResult ParseCastExpression(CastParseKind ParseKind,
bool isAddressOfOperand,
bool &NotCastExpr,
TypeCastState isTypeCast,
bool isVectorLiteral = false,
bool *NotPrimaryExpression = nullptr);
ExprResult ParseCastExpression(CastParseKind ParseKind,
bool isAddressOfOperand = false,
TypeCastState isTypeCast = NotTypeCast,
bool isVectorLiteral = false,
bool *NotPrimaryExpression = nullptr);
/// Returns true if the next token cannot start an expression.
bool isNotExpressionStart();
/// Returns true if the next token would start a postfix-expression
/// suffix.
bool isPostfixExpressionSuffixStart() {
tok::TokenKind K = Tok.getKind();
return (K == tok::l_square || K == tok::l_paren ||
K == tok::period || K == tok::arrow ||
K == tok::plusplus || K == tok::minusminus);
}
bool diagnoseUnknownTemplateId(ExprResult TemplateName, SourceLocation Less);
void checkPotentialAngleBracket(ExprResult &PotentialTemplateName);
bool checkPotentialAngleBracketDelimiter(const AngleBracketTracker::Loc &,
const Token &OpToken);
bool checkPotentialAngleBracketDelimiter(const Token &OpToken) {
if (auto *Info = AngleBrackets.getCurrent(*this))
return checkPotentialAngleBracketDelimiter(*Info, OpToken);
return false;
}
ExprResult ParsePostfixExpressionSuffix(ExprResult LHS);
ExprResult ParseUnaryExprOrTypeTraitExpression();
ExprResult ParseBuiltinPrimaryExpression();
ExprResult ParseUniqueStableNameExpression();
ExprResult ParseExprAfterUnaryExprOrTypeTrait(const Token &OpTok,
bool &isCastExpr,
ParsedType &CastTy,
SourceRange &CastRange);
typedef SmallVector<SourceLocation, 20> CommaLocsTy;
/// ParseExpressionList - Used for C/C++ (argument-)expression-list.
bool ParseExpressionList(SmallVectorImpl<Expr *> &Exprs,
SmallVectorImpl<SourceLocation> &CommaLocs,
llvm::function_ref<void()> ExpressionStarts =
llvm::function_ref<void()>());
/// ParseSimpleExpressionList - A simple comma-separated list of expressions,
/// used for misc language extensions.
bool ParseSimpleExpressionList(SmallVectorImpl<Expr*> &Exprs,
SmallVectorImpl<SourceLocation> &CommaLocs);
/// ParenParseOption - Control what ParseParenExpression will parse.
enum ParenParseOption {
SimpleExpr, // Only parse '(' expression ')'
FoldExpr, // Also allow fold-expression <anything>
CompoundStmt, // Also allow '(' compound-statement ')'
CompoundLiteral, // Also allow '(' type-name ')' '{' ... '}'
CastExpr // Also allow '(' type-name ')' <anything>
};
ExprResult ParseParenExpression(ParenParseOption &ExprType,
bool stopIfCastExpr,
bool isTypeCast,
ParsedType &CastTy,
SourceLocation &RParenLoc);
ExprResult ParseCXXAmbiguousParenExpression(
ParenParseOption &ExprType, ParsedType &CastTy,
BalancedDelimiterTracker &Tracker, ColonProtectionRAIIObject &ColonProt);
ExprResult ParseCompoundLiteralExpression(ParsedType Ty,
SourceLocation LParenLoc,
SourceLocation RParenLoc);
ExprResult ParseGenericSelectionExpression();
ExprResult ParseObjCBoolLiteral();
ExprResult ParseFoldExpression(ExprResult LHS, BalancedDelimiterTracker &T);
//===--------------------------------------------------------------------===//
// C++ Expressions
ExprResult tryParseCXXIdExpression(CXXScopeSpec &SS, bool isAddressOfOperand,
Token &Replacement);
ExprResult ParseCXXIdExpression(bool isAddressOfOperand = false);
bool areTokensAdjacent(const Token &A, const Token &B);
void CheckForTemplateAndDigraph(Token &Next, ParsedType ObjectTypePtr,
bool EnteringContext, IdentifierInfo &II,
CXXScopeSpec &SS);
bool ParseOptionalCXXScopeSpecifier(CXXScopeSpec &SS,
ParsedType ObjectType,
bool ObjectHasErrors,
bool EnteringContext,
bool *MayBePseudoDestructor = nullptr,
bool IsTypename = false,
IdentifierInfo **LastII = nullptr,
bool OnlyNamespace = false,
bool InUsingDeclaration = false);
//===--------------------------------------------------------------------===//
// C++11 5.1.2: Lambda expressions
/// Result of tentatively parsing a lambda-introducer.
enum class LambdaIntroducerTentativeParse {
/// This appears to be a lambda-introducer, which has been fully parsed.
Success,
/// This is a lambda-introducer, but has not been fully parsed, and this
/// function needs to be called again to parse it.
Incomplete,
/// This is definitely an Objective-C message send expression, rather than
/// a lambda-introducer, attribute-specifier, or array designator.
MessageSend,
/// This is not a lambda-introducer.
Invalid,
};
// [...] () -> type {...}
ExprResult ParseLambdaExpression();
ExprResult TryParseLambdaExpression();
bool
ParseLambdaIntroducer(LambdaIntroducer &Intro,
LambdaIntroducerTentativeParse *Tentative = nullptr);
ExprResult ParseLambdaExpressionAfterIntroducer(LambdaIntroducer &Intro);
//===--------------------------------------------------------------------===//
// C++ 5.2p1: C++ Casts
ExprResult ParseCXXCasts();
/// Parse a __builtin_bit_cast(T, E), used to implement C++2a std::bit_cast.
ExprResult ParseBuiltinBitCast();
//===--------------------------------------------------------------------===//
// C++ 5.2p1: C++ Type Identification
ExprResult ParseCXXTypeid();
//===--------------------------------------------------------------------===//
// C++ : Microsoft __uuidof Expression
ExprResult ParseCXXUuidof();
//===--------------------------------------------------------------------===//
// C++ 5.2.4: C++ Pseudo-Destructor Expressions
ExprResult ParseCXXPseudoDestructor(Expr *Base, SourceLocation OpLoc,
tok::TokenKind OpKind,
CXXScopeSpec &SS,
ParsedType ObjectType);
//===--------------------------------------------------------------------===//
// C++ 9.3.2: C++ 'this' pointer
ExprResult ParseCXXThis();
//===--------------------------------------------------------------------===//
// C++ 15: C++ Throw Expression
ExprResult ParseThrowExpression();
ExceptionSpecificationType tryParseExceptionSpecification(
bool Delayed,
SourceRange &SpecificationRange,
SmallVectorImpl<ParsedType> &DynamicExceptions,
SmallVectorImpl<SourceRange> &DynamicExceptionRanges,
ExprResult &NoexceptExpr,
CachedTokens *&ExceptionSpecTokens);
// EndLoc is filled with the location of the last token of the specification.
ExceptionSpecificationType ParseDynamicExceptionSpecification(
SourceRange &SpecificationRange,
SmallVectorImpl<ParsedType> &Exceptions,
SmallVectorImpl<SourceRange> &Ranges);
//===--------------------------------------------------------------------===//
// C++0x 8: Function declaration trailing-return-type
TypeResult ParseTrailingReturnType(SourceRange &Range,
bool MayBeFollowedByDirectInit);
//===--------------------------------------------------------------------===//
// C++ 2.13.5: C++ Boolean Literals
ExprResult ParseCXXBoolLiteral();
//===--------------------------------------------------------------------===//
// C++ 5.2.3: Explicit type conversion (functional notation)
ExprResult ParseCXXTypeConstructExpression(const DeclSpec &DS);
/// ParseCXXSimpleTypeSpecifier - [C++ 7.1.5.2] Simple type specifiers.
/// This should only be called when the current token is known to be part of
/// simple-type-specifier.
void ParseCXXSimpleTypeSpecifier(DeclSpec &DS);
bool ParseCXXTypeSpecifierSeq(DeclSpec &DS);
//===--------------------------------------------------------------------===//
// C++ 5.3.4 and 5.3.5: C++ new and delete
bool ParseExpressionListOrTypeId(SmallVectorImpl<Expr*> &Exprs,
Declarator &D);
void ParseDirectNewDeclarator(Declarator &D);
ExprResult ParseCXXNewExpression(bool UseGlobal, SourceLocation Start);
ExprResult ParseCXXDeleteExpression(bool UseGlobal,
SourceLocation Start);
//===--------------------------------------------------------------------===//
// C++ if/switch/while/for condition expression.
struct ForRangeInfo;
Sema::ConditionResult ParseCXXCondition(StmtResult *InitStmt,
SourceLocation Loc,
Sema::ConditionKind CK,
ForRangeInfo *FRI = nullptr);
//===--------------------------------------------------------------------===//
// C++ Coroutines
ExprResult ParseCoyieldExpression();
//===--------------------------------------------------------------------===//
// C++ Concepts
ExprResult ParseRequiresExpression();
void ParseTrailingRequiresClause(Declarator &D);
//===--------------------------------------------------------------------===//
// C99 6.7.8: Initialization.
/// ParseInitializer
/// initializer: [C99 6.7.8]
/// assignment-expression
/// '{' ...
ExprResult ParseInitializer() {
if (Tok.isNot(tok::l_brace))
return ParseAssignmentExpression();
return ParseBraceInitializer();
}
bool MayBeDesignationStart();
ExprResult ParseBraceInitializer();
ExprResult ParseInitializerWithPotentialDesignator(
llvm::function_ref<void(const Designation &)> CodeCompleteCB);
//===--------------------------------------------------------------------===//
// clang Expressions
ExprResult ParseBlockLiteralExpression(); // ^{...}
//===--------------------------------------------------------------------===//
// Objective-C Expressions
ExprResult ParseObjCAtExpression(SourceLocation AtLocation);
ExprResult ParseObjCStringLiteral(SourceLocation AtLoc);
ExprResult ParseObjCCharacterLiteral(SourceLocation AtLoc);
ExprResult ParseObjCNumericLiteral(SourceLocation AtLoc);
ExprResult ParseObjCBooleanLiteral(SourceLocation AtLoc, bool ArgValue);
ExprResult ParseObjCArrayLiteral(SourceLocation AtLoc);
ExprResult ParseObjCDictionaryLiteral(SourceLocation AtLoc);
ExprResult ParseObjCBoxedExpr(SourceLocation AtLoc);
ExprResult ParseObjCEncodeExpression(SourceLocation AtLoc);
ExprResult ParseObjCSelectorExpression(SourceLocation AtLoc);
ExprResult ParseObjCProtocolExpression(SourceLocation AtLoc);
bool isSimpleObjCMessageExpression();
ExprResult ParseObjCMessageExpression();
ExprResult ParseObjCMessageExpressionBody(SourceLocation LBracloc,
SourceLocation SuperLoc,
ParsedType ReceiverType,
Expr *ReceiverExpr);
ExprResult ParseAssignmentExprWithObjCMessageExprStart(
SourceLocation LBracloc, SourceLocation SuperLoc,
ParsedType ReceiverType, Expr *ReceiverExpr);
bool ParseObjCXXMessageReceiver(bool &IsExpr, void *&TypeOrExpr);
//===--------------------------------------------------------------------===//
// C99 6.8: Statements and Blocks.
/// A SmallVector of statements, with stack size 32 (as that is the only one
/// used.)
typedef SmallVector<Stmt*, 32> StmtVector;
/// A SmallVector of expressions, with stack size 12 (the maximum used.)
typedef SmallVector<Expr*, 12> ExprVector;
/// A SmallVector of types.
typedef SmallVector<ParsedType, 12> TypeVector;
StmtResult
ParseStatement(SourceLocation *TrailingElseLoc = nullptr,
ParsedStmtContext StmtCtx = ParsedStmtContext::SubStmt);
StmtResult ParseStatementOrDeclaration(
StmtVector &Stmts, ParsedStmtContext StmtCtx,
SourceLocation *TrailingElseLoc = nullptr);
StmtResult ParseStatementOrDeclarationAfterAttributes(
StmtVector &Stmts,
ParsedStmtContext StmtCtx,
SourceLocation *TrailingElseLoc,
ParsedAttributesWithRange &Attrs);
StmtResult ParseExprStatement(ParsedStmtContext StmtCtx);
StmtResult ParseLabeledStatement(ParsedAttributesWithRange &attrs,
ParsedStmtContext StmtCtx);
StmtResult ParseCaseStatement(ParsedStmtContext StmtCtx,
bool MissingCase = false,
ExprResult Expr = ExprResult());
StmtResult ParseDefaultStatement(ParsedStmtContext StmtCtx);
StmtResult ParseCompoundStatement(bool isStmtExpr = false);
StmtResult ParseCompoundStatement(bool isStmtExpr,
unsigned ScopeFlags);
void ParseCompoundStatementLeadingPragmas();
bool ConsumeNullStmt(StmtVector &Stmts);
StmtResult ParseCompoundStatementBody(bool isStmtExpr = false);
bool ParseParenExprOrCondition(StmtResult *InitStmt,
Sema::ConditionResult &CondResult,
SourceLocation Loc, Sema::ConditionKind CK,
SourceLocation *LParenLoc = nullptr,
SourceLocation *RParenLoc = nullptr);
StmtResult ParseIfStatement(SourceLocation *TrailingElseLoc);
StmtResult ParseSwitchStatement(SourceLocation *TrailingElseLoc);
StmtResult ParseWhileStatement(SourceLocation *TrailingElseLoc);
StmtResult ParseDoStatement();
StmtResult ParseForStatement(SourceLocation *TrailingElseLoc);
StmtResult ParseGotoStatement();
StmtResult ParseContinueStatement();
StmtResult ParseBreakStatement();
StmtResult ParseReturnStatement();
StmtResult ParseAsmStatement(bool &msAsm);
StmtResult ParseMicrosoftAsmStatement(SourceLocation AsmLoc);
StmtResult ParsePragmaLoopHint(StmtVector &Stmts,
ParsedStmtContext StmtCtx,
SourceLocation *TrailingElseLoc,
ParsedAttributesWithRange &Attrs);
/// Describes the behavior that should be taken for an __if_exists
/// block.
enum IfExistsBehavior {
/// Parse the block; this code is always used.
IEB_Parse,
/// Skip the block entirely; this code is never used.
IEB_Skip,
/// Parse the block as a dependent block, which may be used in
/// some template instantiations but not others.
IEB_Dependent
};
/// Describes the condition of a Microsoft __if_exists or
/// __if_not_exists block.
struct IfExistsCondition {
/// The location of the initial keyword.
SourceLocation KeywordLoc;
/// Whether this is an __if_exists block (rather than an
/// __if_not_exists block).
bool IsIfExists;
/// Nested-name-specifier preceding the name.
CXXScopeSpec SS;
/// The name we're looking for.
UnqualifiedId Name;
/// The behavior of this __if_exists or __if_not_exists block
/// should.
IfExistsBehavior Behavior;
};
bool ParseMicrosoftIfExistsCondition(IfExistsCondition& Result);
void ParseMicrosoftIfExistsStatement(StmtVector &Stmts);
void ParseMicrosoftIfExistsExternalDeclaration();
void ParseMicrosoftIfExistsClassDeclaration(DeclSpec::TST TagType,
ParsedAttributes &AccessAttrs,
AccessSpecifier &CurAS);
bool ParseMicrosoftIfExistsBraceInitializer(ExprVector &InitExprs,
bool &InitExprsOk);
bool ParseAsmOperandsOpt(SmallVectorImpl<IdentifierInfo *> &Names,
SmallVectorImpl<Expr *> &Constraints,
SmallVectorImpl<Expr *> &Exprs);
//===--------------------------------------------------------------------===//
// C++ 6: Statements and Blocks
StmtResult ParseCXXTryBlock();
StmtResult ParseCXXTryBlockCommon(SourceLocation TryLoc, bool FnTry = false);
StmtResult ParseCXXCatchBlock(bool FnCatch = false);
//===--------------------------------------------------------------------===//
// MS: SEH Statements and Blocks
StmtResult ParseSEHTryBlock();
StmtResult ParseSEHExceptBlock(SourceLocation Loc);
StmtResult ParseSEHFinallyBlock(SourceLocation Loc);
StmtResult ParseSEHLeaveStatement();
//===--------------------------------------------------------------------===//
// Objective-C Statements
StmtResult ParseObjCAtStatement(SourceLocation atLoc,
ParsedStmtContext StmtCtx);
StmtResult ParseObjCTryStmt(SourceLocation atLoc);
StmtResult ParseObjCThrowStmt(SourceLocation atLoc);
StmtResult ParseObjCSynchronizedStmt(SourceLocation atLoc);
StmtResult ParseObjCAutoreleasePoolStmt(SourceLocation atLoc);
//===--------------------------------------------------------------------===//
// C99 6.7: Declarations.
/// A context for parsing declaration specifiers. TODO: flesh this
/// out, there are other significant restrictions on specifiers than
/// would be best implemented in the parser.
enum class DeclSpecContext {
DSC_normal, // normal context
DSC_class, // class context, enables 'friend'
DSC_type_specifier, // C++ type-specifier-seq or C specifier-qualifier-list
DSC_trailing, // C++11 trailing-type-specifier in a trailing return type
DSC_alias_declaration, // C++11 type-specifier-seq in an alias-declaration
DSC_top_level, // top-level/namespace declaration context
DSC_template_param, // template parameter context
DSC_template_type_arg, // template type argument context
DSC_objc_method_result, // ObjC method result context, enables 'instancetype'
DSC_condition // condition declaration context
};
/// Is this a context in which we are parsing just a type-specifier (or
/// trailing-type-specifier)?
static bool isTypeSpecifier(DeclSpecContext DSC) {
switch (DSC) {
case DeclSpecContext::DSC_normal:
case DeclSpecContext::DSC_template_param:
case DeclSpecContext::DSC_class:
case DeclSpecContext::DSC_top_level:
case DeclSpecContext::DSC_objc_method_result:
case DeclSpecContext::DSC_condition:
return false;
case DeclSpecContext::DSC_template_type_arg:
case DeclSpecContext::DSC_type_specifier:
case DeclSpecContext::DSC_trailing:
case DeclSpecContext::DSC_alias_declaration:
return true;
}
llvm_unreachable("Missing DeclSpecContext case");
}
/// Whether a defining-type-specifier is permitted in a given context.
enum class AllowDefiningTypeSpec {
/// The grammar doesn't allow a defining-type-specifier here, and we must
/// not parse one (eg, because a '{' could mean something else).
No,
/// The grammar doesn't allow a defining-type-specifier here, but we permit
/// one for error recovery purposes. Sema will reject.
NoButErrorRecovery,
/// The grammar allows a defining-type-specifier here, even though it's
/// always invalid. Sema will reject.
YesButInvalid,
/// The grammar allows a defining-type-specifier here, and one can be valid.
Yes
};
/// Is this a context in which we are parsing defining-type-specifiers (and
/// so permit class and enum definitions in addition to non-defining class and
/// enum elaborated-type-specifiers)?
static AllowDefiningTypeSpec
isDefiningTypeSpecifierContext(DeclSpecContext DSC) {
switch (DSC) {
case DeclSpecContext::DSC_normal:
case DeclSpecContext::DSC_class:
case DeclSpecContext::DSC_top_level:
case DeclSpecContext::DSC_alias_declaration:
case DeclSpecContext::DSC_objc_method_result:
return AllowDefiningTypeSpec::Yes;
case DeclSpecContext::DSC_condition:
case DeclSpecContext::DSC_template_param:
return AllowDefiningTypeSpec::YesButInvalid;
case DeclSpecContext::DSC_template_type_arg:
case DeclSpecContext::DSC_type_specifier:
return AllowDefiningTypeSpec::NoButErrorRecovery;
case DeclSpecContext::DSC_trailing:
return AllowDefiningTypeSpec::No;
}
llvm_unreachable("Missing DeclSpecContext case");
}
/// Is this a context in which an opaque-enum-declaration can appear?
static bool isOpaqueEnumDeclarationContext(DeclSpecContext DSC) {
switch (DSC) {
case DeclSpecContext::DSC_normal:
case DeclSpecContext::DSC_class:
case DeclSpecContext::DSC_top_level:
return true;
case DeclSpecContext::DSC_alias_declaration:
case DeclSpecContext::DSC_objc_method_result:
case DeclSpecContext::DSC_condition:
case DeclSpecContext::DSC_template_param:
case DeclSpecContext::DSC_template_type_arg:
case DeclSpecContext::DSC_type_specifier:
case DeclSpecContext::DSC_trailing:
return false;
}
llvm_unreachable("Missing DeclSpecContext case");
}
/// Is this a context in which we can perform class template argument
/// deduction?
static bool isClassTemplateDeductionContext(DeclSpecContext DSC) {
switch (DSC) {
case DeclSpecContext::DSC_normal:
case DeclSpecContext::DSC_template_param:
case DeclSpecContext::DSC_class:
case DeclSpecContext::DSC_top_level:
case DeclSpecContext::DSC_condition:
case DeclSpecContext::DSC_type_specifier:
return true;
case DeclSpecContext::DSC_objc_method_result:
case DeclSpecContext::DSC_template_type_arg:
case DeclSpecContext::DSC_trailing:
case DeclSpecContext::DSC_alias_declaration:
return false;
}
llvm_unreachable("Missing DeclSpecContext case");
}
/// Information on a C++0x for-range-initializer found while parsing a
/// declaration which turns out to be a for-range-declaration.
struct ForRangeInit {
SourceLocation ColonLoc;
ExprResult RangeExpr;
bool ParsedForRangeDecl() { return !ColonLoc.isInvalid(); }
};
struct ForRangeInfo : ForRangeInit {
StmtResult LoopVar;
};
DeclGroupPtrTy ParseDeclaration(DeclaratorContext Context,
SourceLocation &DeclEnd,
ParsedAttributesWithRange &attrs,
SourceLocation *DeclSpecStart = nullptr);
DeclGroupPtrTy
ParseSimpleDeclaration(DeclaratorContext Context, SourceLocation &DeclEnd,
ParsedAttributesWithRange &attrs, bool RequireSemi,
ForRangeInit *FRI = nullptr,
SourceLocation *DeclSpecStart = nullptr);
bool MightBeDeclarator(DeclaratorContext Context);
DeclGroupPtrTy ParseDeclGroup(ParsingDeclSpec &DS, DeclaratorContext Context,
SourceLocation *DeclEnd = nullptr,
ForRangeInit *FRI = nullptr);
Decl *ParseDeclarationAfterDeclarator(Declarator &D,
const ParsedTemplateInfo &TemplateInfo = ParsedTemplateInfo());
bool ParseAsmAttributesAfterDeclarator(Declarator &D);
Decl *ParseDeclarationAfterDeclaratorAndAttributes(
Declarator &D,
const ParsedTemplateInfo &TemplateInfo = ParsedTemplateInfo(),
ForRangeInit *FRI = nullptr);
Decl *ParseFunctionStatementBody(Decl *Decl, ParseScope &BodyScope);
Decl *ParseFunctionTryBlock(Decl *Decl, ParseScope &BodyScope);
/// When in code-completion, skip parsing of the function/method body
/// unless the body contains the code-completion point.
///
/// \returns true if the function body was skipped.
bool trySkippingFunctionBody();
bool ParseImplicitInt(DeclSpec &DS, CXXScopeSpec *SS,
const ParsedTemplateInfo &TemplateInfo,
AccessSpecifier AS, DeclSpecContext DSC,
ParsedAttributesWithRange &Attrs);
DeclSpecContext
getDeclSpecContextFromDeclaratorContext(DeclaratorContext Context);
void ParseDeclarationSpecifiers(
DeclSpec &DS,
const ParsedTemplateInfo &TemplateInfo = ParsedTemplateInfo(),
AccessSpecifier AS = AS_none,
DeclSpecContext DSC = DeclSpecContext::DSC_normal,
LateParsedAttrList *LateAttrs = nullptr);
bool DiagnoseMissingSemiAfterTagDefinition(
DeclSpec &DS, AccessSpecifier AS, DeclSpecContext DSContext,
LateParsedAttrList *LateAttrs = nullptr);
void ParseSpecifierQualifierList(
DeclSpec &DS, AccessSpecifier AS = AS_none,
DeclSpecContext DSC = DeclSpecContext::DSC_normal);
void ParseObjCTypeQualifierList(ObjCDeclSpec &DS,
DeclaratorContext Context);
void ParseEnumSpecifier(SourceLocation TagLoc, DeclSpec &DS,
const ParsedTemplateInfo &TemplateInfo,
AccessSpecifier AS, DeclSpecContext DSC);
void ParseEnumBody(SourceLocation StartLoc, Decl *TagDecl);
void ParseStructUnionBody(SourceLocation StartLoc, DeclSpec::TST TagType,
RecordDecl *TagDecl);
void ParseStructDeclaration(
ParsingDeclSpec &DS,
llvm::function_ref<void(ParsingFieldDeclarator &)> FieldsCallback);
bool isDeclarationSpecifier(bool DisambiguatingWithExpression = false);
bool isTypeSpecifierQualifier();
/// isKnownToBeTypeSpecifier - Return true if we know that the specified token
/// is definitely a type-specifier. Return false if it isn't part of a type
/// specifier or if we're not sure.
bool isKnownToBeTypeSpecifier(const Token &Tok) const;
/// Return true if we know that we are definitely looking at a
/// decl-specifier, and isn't part of an expression such as a function-style
/// cast. Return false if it's no a decl-specifier, or we're not sure.
bool isKnownToBeDeclarationSpecifier() {
if (getLangOpts().CPlusPlus)
return isCXXDeclarationSpecifier() == TPResult::True;
return isDeclarationSpecifier(true);
}
/// isDeclarationStatement - Disambiguates between a declaration or an
/// expression statement, when parsing function bodies.
/// Returns true for declaration, false for expression.
bool isDeclarationStatement() {
if (getLangOpts().CPlusPlus)
return isCXXDeclarationStatement();
return isDeclarationSpecifier(true);
}
/// isForInitDeclaration - Disambiguates between a declaration or an
/// expression in the context of the C 'clause-1' or the C++
// 'for-init-statement' part of a 'for' statement.
/// Returns true for declaration, false for expression.
bool isForInitDeclaration() {
if (getLangOpts().OpenMP)
Actions.startOpenMPLoop();
if (getLangOpts().CPlusPlus)
return isCXXSimpleDeclaration(/*AllowForRangeDecl=*/true);
return isDeclarationSpecifier(true);
}
/// Determine whether this is a C++1z for-range-identifier.
bool isForRangeIdentifier();
/// Determine whether we are currently at the start of an Objective-C
/// class message that appears to be missing the open bracket '['.
bool isStartOfObjCClassMessageMissingOpenBracket();
/// Starting with a scope specifier, identifier, or
/// template-id that refers to the current class, determine whether
/// this is a constructor declarator.
bool isConstructorDeclarator(bool Unqualified, bool DeductionGuide = false);
/// Specifies the context in which type-id/expression
/// disambiguation will occur.
enum TentativeCXXTypeIdContext {
TypeIdInParens,
TypeIdUnambiguous,
TypeIdAsTemplateArgument
};
/// isTypeIdInParens - Assumes that a '(' was parsed and now we want to know
/// whether the parens contain an expression or a type-id.
/// Returns true for a type-id and false for an expression.
bool isTypeIdInParens(bool &isAmbiguous) {
if (getLangOpts().CPlusPlus)
return isCXXTypeId(TypeIdInParens, isAmbiguous);
isAmbiguous = false;
return isTypeSpecifierQualifier();
}
bool isTypeIdInParens() {
bool isAmbiguous;
return isTypeIdInParens(isAmbiguous);
}
/// Checks if the current tokens form type-id or expression.
/// It is similar to isTypeIdInParens but does not suppose that type-id
/// is in parenthesis.
bool isTypeIdUnambiguously() {
bool IsAmbiguous;
if (getLangOpts().CPlusPlus)
return isCXXTypeId(TypeIdUnambiguous, IsAmbiguous);
return isTypeSpecifierQualifier();
}
/// isCXXDeclarationStatement - C++-specialized function that disambiguates
/// between a declaration or an expression statement, when parsing function
/// bodies. Returns true for declaration, false for expression.
bool isCXXDeclarationStatement();
/// isCXXSimpleDeclaration - C++-specialized function that disambiguates
/// between a simple-declaration or an expression-statement.
/// If during the disambiguation process a parsing error is encountered,
/// the function returns true to let the declaration parsing code handle it.
/// Returns false if the statement is disambiguated as expression.
bool isCXXSimpleDeclaration(bool AllowForRangeDecl);
/// isCXXFunctionDeclarator - Disambiguates between a function declarator or
/// a constructor-style initializer, when parsing declaration statements.
/// Returns true for function declarator and false for constructor-style
/// initializer. Sets 'IsAmbiguous' to true to indicate that this declaration
/// might be a constructor-style initializer.
/// If during the disambiguation process a parsing error is encountered,
/// the function returns true to let the declaration parsing code handle it.
bool isCXXFunctionDeclarator(bool *IsAmbiguous = nullptr);
struct ConditionDeclarationOrInitStatementState;
enum class ConditionOrInitStatement {
Expression, ///< Disambiguated as an expression (either kind).
ConditionDecl, ///< Disambiguated as the declaration form of condition.
InitStmtDecl, ///< Disambiguated as a simple-declaration init-statement.
ForRangeDecl, ///< Disambiguated as a for-range declaration.
Error ///< Can't be any of the above!
};
/// Disambiguates between the different kinds of things that can happen
/// after 'if (' or 'switch ('. This could be one of two different kinds of
/// declaration (depending on whether there is a ';' later) or an expression.
ConditionOrInitStatement
isCXXConditionDeclarationOrInitStatement(bool CanBeInitStmt,
bool CanBeForRangeDecl);
bool isCXXTypeId(TentativeCXXTypeIdContext Context, bool &isAmbiguous);
bool isCXXTypeId(TentativeCXXTypeIdContext Context) {
bool isAmbiguous;
return isCXXTypeId(Context, isAmbiguous);
}
/// TPResult - Used as the result value for functions whose purpose is to
/// disambiguate C++ constructs by "tentatively parsing" them.
enum class TPResult {
True, False, Ambiguous, Error
};
/// Determine whether we could have an enum-base.
///
/// \p AllowSemi If \c true, then allow a ';' after the enum-base; otherwise
/// only consider this to be an enum-base if the next token is a '{'.
///
/// \return \c false if this cannot possibly be an enum base; \c true
/// otherwise.
bool isEnumBase(bool AllowSemi);
/// isCXXDeclarationSpecifier - Returns TPResult::True if it is a
/// declaration specifier, TPResult::False if it is not,
/// TPResult::Ambiguous if it could be either a decl-specifier or a
/// function-style cast, and TPResult::Error if a parsing error was
/// encountered. If it could be a braced C++11 function-style cast, returns
/// BracedCastResult.
/// Doesn't consume tokens.
TPResult
isCXXDeclarationSpecifier(TPResult BracedCastResult = TPResult::False,
bool *InvalidAsDeclSpec = nullptr);
/// Given that isCXXDeclarationSpecifier returns \c TPResult::True or
/// \c TPResult::Ambiguous, determine whether the decl-specifier would be
/// a type-specifier other than a cv-qualifier.
bool isCXXDeclarationSpecifierAType();
/// Determine whether the current token sequence might be
/// '<' template-argument-list '>'
/// rather than a less-than expression.
TPResult isTemplateArgumentList(unsigned TokensToSkip);
/// Determine whether an '(' after an 'explicit' keyword is part of a C++20
/// 'explicit(bool)' declaration, in earlier language modes where that is an
/// extension.
TPResult isExplicitBool();
/// Determine whether an identifier has been tentatively declared as a
/// non-type. Such tentative declarations should not be found to name a type
/// during a tentative parse, but also should not be annotated as a non-type.
bool isTentativelyDeclared(IdentifierInfo *II);
// "Tentative parsing" functions, used for disambiguation. If a parsing error
// is encountered they will return TPResult::Error.
// Returning TPResult::True/False indicates that the ambiguity was
// resolved and tentative parsing may stop. TPResult::Ambiguous indicates
// that more tentative parsing is necessary for disambiguation.
// They all consume tokens, so backtracking should be used after calling them.
TPResult TryParseSimpleDeclaration(bool AllowForRangeDecl);
TPResult TryParseTypeofSpecifier();
TPResult TryParseProtocolQualifiers();
TPResult TryParsePtrOperatorSeq();
TPResult TryParseOperatorId();
TPResult TryParseInitDeclaratorList();
TPResult TryParseDeclarator(bool mayBeAbstract, bool mayHaveIdentifier = true,
bool mayHaveDirectInit = false);
TPResult
TryParseParameterDeclarationClause(bool *InvalidAsDeclaration = nullptr,
bool VersusTemplateArg = false);
TPResult TryParseFunctionDeclarator();
TPResult TryParseBracketDeclarator();
TPResult TryConsumeDeclarationSpecifier();
/// Try to skip a possibly empty sequence of 'attribute-specifier's without
/// full validation of the syntactic structure of attributes.
bool TrySkipAttributes();
public:
TypeResult
ParseTypeName(SourceRange *Range = nullptr,
DeclaratorContext Context = DeclaratorContext::TypeName,
AccessSpecifier AS = AS_none, Decl **OwnedType = nullptr,
ParsedAttributes *Attrs = nullptr);
private:
void ParseBlockId(SourceLocation CaretLoc);
/// Are [[]] attributes enabled?
bool standardAttributesAllowed() const {
const LangOptions &LO = getLangOpts();
return LO.DoubleSquareBracketAttributes;
}
// Check for the start of an attribute-specifier-seq in a context where an
// attribute is not allowed.
bool CheckProhibitedCXX11Attribute() {
assert(Tok.is(tok::l_square));
if (!standardAttributesAllowed() || NextToken().isNot(tok::l_square))
return false;
return DiagnoseProhibitedCXX11Attribute();
}
bool DiagnoseProhibitedCXX11Attribute();
void CheckMisplacedCXX11Attribute(ParsedAttributesWithRange &Attrs,
SourceLocation CorrectLocation) {
if (!standardAttributesAllowed())
return;
if ((Tok.isNot(tok::l_square) || NextToken().isNot(tok::l_square)) &&
Tok.isNot(tok::kw_alignas))
return;
DiagnoseMisplacedCXX11Attribute(Attrs, CorrectLocation);
}
void DiagnoseMisplacedCXX11Attribute(ParsedAttributesWithRange &Attrs,
SourceLocation CorrectLocation);
void stripTypeAttributesOffDeclSpec(ParsedAttributesWithRange &Attrs,
DeclSpec &DS, Sema::TagUseKind TUK);
// FixItLoc = possible correct location for the attributes
void ProhibitAttributes(ParsedAttributesWithRange &Attrs,
SourceLocation FixItLoc = SourceLocation()) {
if (Attrs.Range.isInvalid())
return;
DiagnoseProhibitedAttributes(Attrs.Range, FixItLoc);
Attrs.clear();
}
void ProhibitAttributes(ParsedAttributesViewWithRange &Attrs,
SourceLocation FixItLoc = SourceLocation()) {
if (Attrs.Range.isInvalid())
return;
DiagnoseProhibitedAttributes(Attrs.Range, FixItLoc);
Attrs.clearListOnly();
}
void DiagnoseProhibitedAttributes(const SourceRange &Range,
SourceLocation FixItLoc);
// Forbid C++11 and C2x attributes that appear on certain syntactic locations
// which standard permits but we don't supported yet, for example, attributes
// appertain to decl specifiers.
void ProhibitCXX11Attributes(ParsedAttributesWithRange &Attrs,
unsigned DiagID);
/// Skip C++11 and C2x attributes and return the end location of the
/// last one.
/// \returns SourceLocation() if there are no attributes.
SourceLocation SkipCXX11Attributes();
/// Diagnose and skip C++11 and C2x attributes that appear in syntactic
/// locations where attributes are not allowed.
void DiagnoseAndSkipCXX11Attributes();
/// Parses syntax-generic attribute arguments for attributes which are
/// known to the implementation, and adds them to the given ParsedAttributes
/// list with the given attribute syntax. Returns the number of arguments
/// parsed for the attribute.
unsigned
ParseAttributeArgsCommon(IdentifierInfo *AttrName, SourceLocation AttrNameLoc,
ParsedAttributes &Attrs, SourceLocation *EndLoc,
IdentifierInfo *ScopeName, SourceLocation ScopeLoc,
ParsedAttr::Syntax Syntax);
void MaybeParseGNUAttributes(Declarator &D,
LateParsedAttrList *LateAttrs = nullptr) {
if (Tok.is(tok::kw___attribute)) {
ParsedAttributes attrs(AttrFactory);
SourceLocation endLoc;
ParseGNUAttributes(attrs, &endLoc, LateAttrs, &D);
D.takeAttributes(attrs, endLoc);
}
}
void MaybeParseGNUAttributes(ParsedAttributes &attrs,
SourceLocation *endLoc = nullptr,
LateParsedAttrList *LateAttrs = nullptr) {
if (Tok.is(tok::kw___attribute))
ParseGNUAttributes(attrs, endLoc, LateAttrs);
}
void ParseGNUAttributes(ParsedAttributes &attrs,
SourceLocation *endLoc = nullptr,
LateParsedAttrList *LateAttrs = nullptr,
Declarator *D = nullptr);
void ParseGNUAttributeArgs(IdentifierInfo *AttrName,
SourceLocation AttrNameLoc,
ParsedAttributes &Attrs, SourceLocation *EndLoc,
IdentifierInfo *ScopeName, SourceLocation ScopeLoc,
ParsedAttr::Syntax Syntax, Declarator *D);
IdentifierLoc *ParseIdentifierLoc();
unsigned
ParseClangAttributeArgs(IdentifierInfo *AttrName, SourceLocation AttrNameLoc,
ParsedAttributes &Attrs, SourceLocation *EndLoc,
IdentifierInfo *ScopeName, SourceLocation ScopeLoc,
ParsedAttr::Syntax Syntax);
void MaybeParseCXX11Attributes(Declarator &D) {
if (standardAttributesAllowed() && isCXX11AttributeSpecifier()) {
ParsedAttributesWithRange attrs(AttrFactory);
SourceLocation endLoc;
ParseCXX11Attributes(attrs, &endLoc);
D.takeAttributes(attrs, endLoc);
}
}
bool MaybeParseCXX11Attributes(ParsedAttributes &attrs,
SourceLocation *endLoc = nullptr) {
if (standardAttributesAllowed() && isCXX11AttributeSpecifier()) {
ParsedAttributesWithRange attrsWithRange(AttrFactory);
ParseCXX11Attributes(attrsWithRange, endLoc);
attrs.takeAllFrom(attrsWithRange);
return true;
}
return false;
}
void MaybeParseCXX11Attributes(ParsedAttributesWithRange &attrs,
SourceLocation *endLoc = nullptr,
bool OuterMightBeMessageSend = false) {
if (standardAttributesAllowed() &&
isCXX11AttributeSpecifier(false, OuterMightBeMessageSend))
ParseCXX11Attributes(attrs, endLoc);
}
void ParseCXX11AttributeSpecifier(ParsedAttributes &attrs,
SourceLocation *EndLoc = nullptr);
void ParseCXX11Attributes(ParsedAttributesWithRange &attrs,
SourceLocation *EndLoc = nullptr);
/// Parses a C++11 (or C2x)-style attribute argument list. Returns true
/// if this results in adding an attribute to the ParsedAttributes list.
bool ParseCXX11AttributeArgs(IdentifierInfo *AttrName,
SourceLocation AttrNameLoc,
ParsedAttributes &Attrs, SourceLocation *EndLoc,
IdentifierInfo *ScopeName,
SourceLocation ScopeLoc);
IdentifierInfo *TryParseCXX11AttributeIdentifier(SourceLocation &Loc);
void MaybeParseMicrosoftAttributes(ParsedAttributes &attrs,
SourceLocation *endLoc = nullptr) {
if (getLangOpts().MicrosoftExt && Tok.is(tok::l_square))
ParseMicrosoftAttributes(attrs, endLoc);
}
void ParseMicrosoftUuidAttributeArgs(ParsedAttributes &Attrs);
void ParseMicrosoftAttributes(ParsedAttributes &attrs,
SourceLocation *endLoc = nullptr);
void MaybeParseMicrosoftDeclSpecs(ParsedAttributes &Attrs,
SourceLocation *End = nullptr) {
const auto &LO = getLangOpts();
if (LO.DeclSpecKeyword && Tok.is(tok::kw___declspec))
ParseMicrosoftDeclSpecs(Attrs, End);
}
void ParseMicrosoftDeclSpecs(ParsedAttributes &Attrs,
SourceLocation *End = nullptr);
bool ParseMicrosoftDeclSpecArgs(IdentifierInfo *AttrName,
SourceLocation AttrNameLoc,
ParsedAttributes &Attrs);
void ParseMicrosoftTypeAttributes(ParsedAttributes &attrs);
void DiagnoseAndSkipExtendedMicrosoftTypeAttributes();
SourceLocation SkipExtendedMicrosoftTypeAttributes();
void ParseMicrosoftInheritanceClassAttributes(ParsedAttributes &attrs);
void ParseBorlandTypeAttributes(ParsedAttributes &attrs);
void ParseOpenCLKernelAttributes(ParsedAttributes &attrs);
void ParseOpenCLQualifiers(ParsedAttributes &Attrs);
/// Parses opencl_unroll_hint attribute if language is OpenCL v2.0
/// or higher.
/// \return false if error happens.
bool MaybeParseOpenCLUnrollHintAttribute(ParsedAttributes &Attrs) {
if (getLangOpts().OpenCL)
return ParseOpenCLUnrollHintAttribute(Attrs);
return true;
}
/// Parses opencl_unroll_hint attribute.
/// \return false if error happens.
bool ParseOpenCLUnrollHintAttribute(ParsedAttributes &Attrs);
/// Parses intelfpga:: and clang:: loop attributes if the language is SYCL
bool MaybeParseSYCLLoopAttributes(ParsedAttributes &Attrs) {
if (getLangOpts().SYCLIsDevice || getLangOpts().SYCLIsHost)
return ParseSYCLLoopAttributes(Attrs);
return true;
}
bool ParseSYCLLoopAttributes(ParsedAttributes &Attrs);
void ParseNullabilityTypeSpecifiers(ParsedAttributes &attrs);
VersionTuple ParseVersionTuple(SourceRange &Range);
void ParseAvailabilityAttribute(IdentifierInfo &Availability,
SourceLocation AvailabilityLoc,
ParsedAttributes &attrs,
SourceLocation *endLoc,
IdentifierInfo *ScopeName,
SourceLocation ScopeLoc,
ParsedAttr::Syntax Syntax);
Optional<AvailabilitySpec> ParseAvailabilitySpec();
ExprResult ParseAvailabilityCheckExpr(SourceLocation StartLoc);
void ParseExternalSourceSymbolAttribute(IdentifierInfo &ExternalSourceSymbol,
SourceLocation Loc,
ParsedAttributes &Attrs,
SourceLocation *EndLoc,
IdentifierInfo *ScopeName,
SourceLocation ScopeLoc,
ParsedAttr::Syntax Syntax);
void ParseObjCBridgeRelatedAttribute(IdentifierInfo &ObjCBridgeRelated,
SourceLocation ObjCBridgeRelatedLoc,
ParsedAttributes &attrs,
SourceLocation *endLoc,
IdentifierInfo *ScopeName,
SourceLocation ScopeLoc,
ParsedAttr::Syntax Syntax);
void ParseSwiftNewTypeAttribute(IdentifierInfo &AttrName,
SourceLocation AttrNameLoc,
ParsedAttributes &Attrs,
SourceLocation *EndLoc,
IdentifierInfo *ScopeName,
SourceLocation ScopeLoc,
ParsedAttr::Syntax Syntax);
void ParseTypeTagForDatatypeAttribute(IdentifierInfo &AttrName,
SourceLocation AttrNameLoc,
ParsedAttributes &Attrs,
SourceLocation *EndLoc,
IdentifierInfo *ScopeName,
SourceLocation ScopeLoc,
ParsedAttr::Syntax Syntax);
void
ParseAttributeWithTypeArg(IdentifierInfo &AttrName,
SourceLocation AttrNameLoc, ParsedAttributes &Attrs,
SourceLocation *EndLoc, IdentifierInfo *ScopeName,
SourceLocation ScopeLoc, ParsedAttr::Syntax Syntax);
void ParseTypeofSpecifier(DeclSpec &DS);
SourceLocation ParseDecltypeSpecifier(DeclSpec &DS);
void AnnotateExistingDecltypeSpecifier(const DeclSpec &DS,
SourceLocation StartLoc,
SourceLocation EndLoc);
void ParseUnderlyingTypeSpecifier(DeclSpec &DS);
void ParseAtomicSpecifier(DeclSpec &DS);
ExprResult ParseAlignArgument(SourceLocation Start,
SourceLocation &EllipsisLoc);
void ParseAlignmentSpecifier(ParsedAttributes &Attrs,
SourceLocation *endLoc = nullptr);
ExprResult ParseExtIntegerArgument();
VirtSpecifiers::Specifier isCXX11VirtSpecifier(const Token &Tok) const;
VirtSpecifiers::Specifier isCXX11VirtSpecifier() const {
return isCXX11VirtSpecifier(Tok);
}
void ParseOptionalCXX11VirtSpecifierSeq(VirtSpecifiers &VS, bool IsInterface,
SourceLocation FriendLoc);
bool isCXX11FinalKeyword() const;
/// DeclaratorScopeObj - RAII object used in Parser::ParseDirectDeclarator to
/// enter a new C++ declarator scope and exit it when the function is
/// finished.
class DeclaratorScopeObj {
Parser &P;
CXXScopeSpec &SS;
bool EnteredScope;
bool CreatedScope;
public:
DeclaratorScopeObj(Parser &p, CXXScopeSpec &ss)
: P(p), SS(ss), EnteredScope(false), CreatedScope(false) {}
void EnterDeclaratorScope() {
assert(!EnteredScope && "Already entered the scope!");
assert(SS.isSet() && "C++ scope was not set!");
CreatedScope = true;
P.EnterScope(0); // Not a decl scope.
if (!P.Actions.ActOnCXXEnterDeclaratorScope(P.getCurScope(), SS))
EnteredScope = true;
}
~DeclaratorScopeObj() {
if (EnteredScope) {
assert(SS.isSet() && "C++ scope was cleared ?");
P.Actions.ActOnCXXExitDeclaratorScope(P.getCurScope(), SS);
}
if (CreatedScope)
P.ExitScope();
}
};
/// ParseDeclarator - Parse and verify a newly-initialized declarator.
void ParseDeclarator(Declarator &D);
/// A function that parses a variant of direct-declarator.
typedef void (Parser::*DirectDeclParseFunction)(Declarator&);
void ParseDeclaratorInternal(Declarator &D,
DirectDeclParseFunction DirectDeclParser);
enum AttrRequirements {
AR_NoAttributesParsed = 0, ///< No attributes are diagnosed.
AR_GNUAttributesParsedAndRejected = 1 << 0, ///< Diagnose GNU attributes.
AR_GNUAttributesParsed = 1 << 1,
AR_CXX11AttributesParsed = 1 << 2,
AR_DeclspecAttributesParsed = 1 << 3,
AR_AllAttributesParsed = AR_GNUAttributesParsed |
AR_CXX11AttributesParsed |
AR_DeclspecAttributesParsed,
AR_VendorAttributesParsed = AR_GNUAttributesParsed |
AR_DeclspecAttributesParsed
};
void ParseTypeQualifierListOpt(
DeclSpec &DS, unsigned AttrReqs = AR_AllAttributesParsed,
bool AtomicAllowed = true, bool IdentifierRequired = false,
Optional<llvm::function_ref<void()>> CodeCompletionHandler = None);
void ParseDirectDeclarator(Declarator &D);
void ParseDecompositionDeclarator(Declarator &D);
void ParseParenDeclarator(Declarator &D);
void ParseFunctionDeclarator(Declarator &D,
ParsedAttributes &attrs,
BalancedDelimiterTracker &Tracker,
bool IsAmbiguous,
bool RequiresArg = false);
void InitCXXThisScopeForDeclaratorIfRelevant(
const Declarator &D, const DeclSpec &DS,
llvm::Optional<Sema::CXXThisScopeRAII> &ThisScope);
bool ParseRefQualifier(bool &RefQualifierIsLValueRef,
SourceLocation &RefQualifierLoc);
bool isFunctionDeclaratorIdentifierList();
void ParseFunctionDeclaratorIdentifierList(
Declarator &D,
SmallVectorImpl<DeclaratorChunk::ParamInfo> &ParamInfo);
void ParseParameterDeclarationClause(
DeclaratorContext DeclaratorContext,
ParsedAttributes &attrs,
SmallVectorImpl<DeclaratorChunk::ParamInfo> &ParamInfo,
SourceLocation &EllipsisLoc);
void ParseBracketDeclarator(Declarator &D);
void ParseMisplacedBracketDeclarator(Declarator &D);
//===--------------------------------------------------------------------===//
// C++ 7: Declarations [dcl.dcl]
/// The kind of attribute specifier we have found.
enum CXX11AttributeKind {
/// This is not an attribute specifier.
CAK_NotAttributeSpecifier,
/// This should be treated as an attribute-specifier.
CAK_AttributeSpecifier,
/// The next tokens are '[[', but this is not an attribute-specifier. This
/// is ill-formed by C++11 [dcl.attr.grammar]p6.
CAK_InvalidAttributeSpecifier
};
CXX11AttributeKind
isCXX11AttributeSpecifier(bool Disambiguate = false,
bool OuterMightBeMessageSend = false);
void DiagnoseUnexpectedNamespace(NamedDecl *Context);
DeclGroupPtrTy ParseNamespace(DeclaratorContext Context,
SourceLocation &DeclEnd,
SourceLocation InlineLoc = SourceLocation());
struct InnerNamespaceInfo {
SourceLocation NamespaceLoc;
SourceLocation InlineLoc;
SourceLocation IdentLoc;
IdentifierInfo *Ident;
};
using InnerNamespaceInfoList = llvm::SmallVector<InnerNamespaceInfo, 4>;
void ParseInnerNamespace(const InnerNamespaceInfoList &InnerNSs,
unsigned int index, SourceLocation &InlineLoc,
ParsedAttributes &attrs,
BalancedDelimiterTracker &Tracker);
Decl *ParseLinkage(ParsingDeclSpec &DS, DeclaratorContext Context);
Decl *ParseExportDeclaration();
DeclGroupPtrTy ParseUsingDirectiveOrDeclaration(
DeclaratorContext Context, const ParsedTemplateInfo &TemplateInfo,
SourceLocation &DeclEnd, ParsedAttributesWithRange &attrs);
Decl *ParseUsingDirective(DeclaratorContext Context,
SourceLocation UsingLoc,
SourceLocation &DeclEnd,
ParsedAttributes &attrs);
struct UsingDeclarator {
SourceLocation TypenameLoc;
CXXScopeSpec SS;
UnqualifiedId Name;
SourceLocation EllipsisLoc;
void clear() {
TypenameLoc = EllipsisLoc = SourceLocation();
SS.clear();
Name.clear();
}
};
bool ParseUsingDeclarator(DeclaratorContext Context, UsingDeclarator &D);
DeclGroupPtrTy ParseUsingDeclaration(DeclaratorContext Context,
const ParsedTemplateInfo &TemplateInfo,
SourceLocation UsingLoc,
SourceLocation &DeclEnd,
AccessSpecifier AS = AS_none);
Decl *ParseAliasDeclarationAfterDeclarator(
const ParsedTemplateInfo &TemplateInfo, SourceLocation UsingLoc,
UsingDeclarator &D, SourceLocation &DeclEnd, AccessSpecifier AS,
ParsedAttributes &Attrs, Decl **OwnedType = nullptr);
Decl *ParseStaticAssertDeclaration(SourceLocation &DeclEnd);
Decl *ParseNamespaceAlias(SourceLocation NamespaceLoc,
SourceLocation AliasLoc, IdentifierInfo *Alias,
SourceLocation &DeclEnd);
//===--------------------------------------------------------------------===//
// C++ 9: classes [class] and C structs/unions.
bool isValidAfterTypeSpecifier(bool CouldBeBitfield);
void ParseClassSpecifier(tok::TokenKind TagTokKind, SourceLocation TagLoc,
DeclSpec &DS, const ParsedTemplateInfo &TemplateInfo,
AccessSpecifier AS, bool EnteringContext,
DeclSpecContext DSC,
ParsedAttributesWithRange &Attributes);
void SkipCXXMemberSpecification(SourceLocation StartLoc,
SourceLocation AttrFixitLoc,
unsigned TagType,
Decl *TagDecl);
void ParseCXXMemberSpecification(SourceLocation StartLoc,
SourceLocation AttrFixitLoc,
ParsedAttributesWithRange &Attrs,
unsigned TagType,
Decl *TagDecl);
ExprResult ParseCXXMemberInitializer(Decl *D, bool IsFunction,
SourceLocation &EqualLoc);
bool
ParseCXXMemberDeclaratorBeforeInitializer(Declarator &DeclaratorInfo,
VirtSpecifiers &VS,
ExprResult &BitfieldSize,
LateParsedAttrList &LateAttrs);
void MaybeParseAndDiagnoseDeclSpecAfterCXX11VirtSpecifierSeq(Declarator &D,
VirtSpecifiers &VS);
DeclGroupPtrTy ParseCXXClassMemberDeclaration(
AccessSpecifier AS, ParsedAttributes &Attr,
const ParsedTemplateInfo &TemplateInfo = ParsedTemplateInfo(),
ParsingDeclRAIIObject *DiagsFromTParams = nullptr);
DeclGroupPtrTy ParseCXXClassMemberDeclarationWithPragmas(
AccessSpecifier &AS, ParsedAttributesWithRange &AccessAttrs,
DeclSpec::TST TagType, Decl *Tag);
void ParseConstructorInitializer(Decl *ConstructorDecl);
MemInitResult ParseMemInitializer(Decl *ConstructorDecl);
void HandleMemberFunctionDeclDelays(Declarator& DeclaratorInfo,
Decl *ThisDecl);
//===--------------------------------------------------------------------===//
// C++ 10: Derived classes [class.derived]
TypeResult ParseBaseTypeSpecifier(SourceLocation &BaseLoc,
SourceLocation &EndLocation);
void ParseBaseClause(Decl *ClassDecl);
BaseResult ParseBaseSpecifier(Decl *ClassDecl);
AccessSpecifier getAccessSpecifierIfPresent() const;
bool ParseUnqualifiedIdTemplateId(CXXScopeSpec &SS,
ParsedType ObjectType,
bool ObjectHadErrors,
SourceLocation TemplateKWLoc,
IdentifierInfo *Name,
SourceLocation NameLoc,
bool EnteringContext,
UnqualifiedId &Id,
bool AssumeTemplateId);
bool ParseUnqualifiedIdOperator(CXXScopeSpec &SS, bool EnteringContext,
ParsedType ObjectType,
UnqualifiedId &Result);
//===--------------------------------------------------------------------===//
// OpenMP: Directives and clauses.
/// Parse clauses for '#pragma omp declare simd'.
DeclGroupPtrTy ParseOMPDeclareSimdClauses(DeclGroupPtrTy Ptr,
CachedTokens &Toks,
SourceLocation Loc);
/// Parse a property kind into \p TIProperty for the selector set \p Set and
/// selector \p Selector.
void parseOMPTraitPropertyKind(OMPTraitProperty &TIProperty,
llvm::omp::TraitSet Set,
llvm::omp::TraitSelector Selector,
llvm::StringMap<SourceLocation> &Seen);
/// Parse a selector kind into \p TISelector for the selector set \p Set.
void parseOMPTraitSelectorKind(OMPTraitSelector &TISelector,
llvm::omp::TraitSet Set,
llvm::StringMap<SourceLocation> &Seen);
/// Parse a selector set kind into \p TISet.
void parseOMPTraitSetKind(OMPTraitSet &TISet,
llvm::StringMap<SourceLocation> &Seen);
/// Parses an OpenMP context property.
void parseOMPContextProperty(OMPTraitSelector &TISelector,
llvm::omp::TraitSet Set,
llvm::StringMap<SourceLocation> &Seen);
/// Parses an OpenMP context selector.
void parseOMPContextSelector(OMPTraitSelector &TISelector,
llvm::omp::TraitSet Set,
llvm::StringMap<SourceLocation> &SeenSelectors);
/// Parses an OpenMP context selector set.
void parseOMPContextSelectorSet(OMPTraitSet &TISet,
llvm::StringMap<SourceLocation> &SeenSets);
/// Parses OpenMP context selectors.
bool parseOMPContextSelectors(SourceLocation Loc, OMPTraitInfo &TI);
/// Parse a `match` clause for an '#pragma omp declare variant'. Return true
/// if there was an error.
bool parseOMPDeclareVariantMatchClause(SourceLocation Loc, OMPTraitInfo &TI,
OMPTraitInfo *ParentTI);
/// Parse clauses for '#pragma omp declare variant'.
void ParseOMPDeclareVariantClauses(DeclGroupPtrTy Ptr, CachedTokens &Toks,
SourceLocation Loc);
/// Parse 'omp [begin] assume[s]' directive.
void ParseOpenMPAssumesDirective(OpenMPDirectiveKind DKind,
SourceLocation Loc);
/// Parse 'omp end assumes' directive.
void ParseOpenMPEndAssumesDirective(SourceLocation Loc);
/// Parse clauses for '#pragma omp declare target'.
DeclGroupPtrTy ParseOMPDeclareTargetClauses();
/// Parse '#pragma omp end declare target'.
void ParseOMPEndDeclareTargetDirective(OpenMPDirectiveKind DKind,
SourceLocation Loc);
/// Skip tokens until a `annot_pragma_openmp_end` was found. Emit a warning if
/// it is not the current token.
void skipUntilPragmaOpenMPEnd(OpenMPDirectiveKind DKind);
/// Check the \p FoundKind against the \p ExpectedKind, if not issue an error
/// that the "end" matching the "begin" directive of kind \p BeginKind was not
/// found. Finally, if the expected kind was found or if \p SkipUntilOpenMPEnd
/// is set, skip ahead using the helper `skipUntilPragmaOpenMPEnd`.
void parseOMPEndDirective(OpenMPDirectiveKind BeginKind,
OpenMPDirectiveKind ExpectedKind,
OpenMPDirectiveKind FoundKind,
SourceLocation MatchingLoc,
SourceLocation FoundLoc,
bool SkipUntilOpenMPEnd);
/// Parses declarative OpenMP directives.
DeclGroupPtrTy ParseOpenMPDeclarativeDirectiveWithExtDecl(
AccessSpecifier &AS, ParsedAttributesWithRange &Attrs,
bool Delayed = false, DeclSpec::TST TagType = DeclSpec::TST_unspecified,
Decl *TagDecl = nullptr);
/// Parse 'omp declare reduction' construct.
DeclGroupPtrTy ParseOpenMPDeclareReductionDirective(AccessSpecifier AS);
/// Parses initializer for provided omp_priv declaration inside the reduction
/// initializer.
void ParseOpenMPReductionInitializerForDecl(VarDecl *OmpPrivParm);
/// Parses 'omp declare mapper' directive.
DeclGroupPtrTy ParseOpenMPDeclareMapperDirective(AccessSpecifier AS);
/// Parses variable declaration in 'omp declare mapper' directive.
TypeResult parseOpenMPDeclareMapperVarDecl(SourceRange &Range,
DeclarationName &Name,
AccessSpecifier AS = AS_none);
/// Tries to parse cast part of OpenMP array shaping operation:
/// '[' expression ']' { '[' expression ']' } ')'.
bool tryParseOpenMPArrayShapingCastPart();
/// Parses simple list of variables.
///
/// \param Kind Kind of the directive.
/// \param Callback Callback function to be called for the list elements.
/// \param AllowScopeSpecifier true, if the variables can have fully
/// qualified names.
///
bool ParseOpenMPSimpleVarList(
OpenMPDirectiveKind Kind,
const llvm::function_ref<void(CXXScopeSpec &, DeclarationNameInfo)> &
Callback,
bool AllowScopeSpecifier);
/// Parses declarative or executable directive.
///
/// \param StmtCtx The context in which we're parsing the directive.
StmtResult
ParseOpenMPDeclarativeOrExecutableDirective(ParsedStmtContext StmtCtx);
/// Parses clause of kind \a CKind for directive of a kind \a Kind.
///
/// \param DKind Kind of current directive.
/// \param CKind Kind of current clause.
/// \param FirstClause true, if this is the first clause of a kind \a CKind
/// in current directive.
///
OMPClause *ParseOpenMPClause(OpenMPDirectiveKind DKind,
OpenMPClauseKind CKind, bool FirstClause);
/// Parses clause with a single expression of a kind \a Kind.
///
/// \param Kind Kind of current clause.
/// \param ParseOnly true to skip the clause's semantic actions and return
/// nullptr.
///
OMPClause *ParseOpenMPSingleExprClause(OpenMPClauseKind Kind,
bool ParseOnly);
/// Parses simple clause of a kind \a Kind.
///
/// \param Kind Kind of current clause.
/// \param ParseOnly true to skip the clause's semantic actions and return
/// nullptr.
///
OMPClause *ParseOpenMPSimpleClause(OpenMPClauseKind Kind, bool ParseOnly);
/// Parses clause with a single expression and an additional argument
/// of a kind \a Kind.
///
/// \param DKind Directive kind.
/// \param Kind Kind of current clause.
/// \param ParseOnly true to skip the clause's semantic actions and return
/// nullptr.
///
OMPClause *ParseOpenMPSingleExprWithArgClause(OpenMPDirectiveKind DKind,
OpenMPClauseKind Kind,
bool ParseOnly);
/// Parses clause without any additional arguments.
///
/// \param Kind Kind of current clause.
/// \param ParseOnly true to skip the clause's semantic actions and return
/// nullptr.
///
OMPClause *ParseOpenMPClause(OpenMPClauseKind Kind, bool ParseOnly = false);
/// Parses clause with the list of variables of a kind \a Kind.
///
/// \param Kind Kind of current clause.
/// \param ParseOnly true to skip the clause's semantic actions and return
/// nullptr.
///
OMPClause *ParseOpenMPVarListClause(OpenMPDirectiveKind DKind,
OpenMPClauseKind Kind, bool ParseOnly);
/// Parses and creates OpenMP 5.0 iterators expression:
/// <iterators> = 'iterator' '(' { [ <iterator-type> ] identifier =
/// <range-specification> }+ ')'
ExprResult ParseOpenMPIteratorsExpr();
/// Parses allocators and traits in the context of the uses_allocator clause.
/// Expected format:
/// '(' { <allocator> [ '(' <allocator_traits> ')' ] }+ ')'
OMPClause *ParseOpenMPUsesAllocatorClause(OpenMPDirectiveKind DKind);
public:
/// Parses simple expression in parens for single-expression clauses of OpenMP
/// constructs.
/// \param RLoc Returned location of right paren.
ExprResult ParseOpenMPParensExpr(StringRef ClauseName, SourceLocation &RLoc,
bool IsAddressOfOperand = false);
/// Data used for parsing list of variables in OpenMP clauses.
struct OpenMPVarListDataTy {
Expr *DepModOrTailExpr = nullptr;
SourceLocation ColonLoc;
SourceLocation RLoc;
CXXScopeSpec ReductionOrMapperIdScopeSpec;
DeclarationNameInfo ReductionOrMapperId;
int ExtraModifier = -1; ///< Additional modifier for linear, map, depend or
///< lastprivate clause.
SmallVector<OpenMPMapModifierKind, NumberOfOMPMapClauseModifiers>
MapTypeModifiers;
SmallVector<SourceLocation, NumberOfOMPMapClauseModifiers>
MapTypeModifiersLoc;
SmallVector<OpenMPMotionModifierKind, NumberOfOMPMotionModifiers>
MotionModifiers;
SmallVector<SourceLocation, NumberOfOMPMotionModifiers> MotionModifiersLoc;
bool IsMapTypeImplicit = false;
SourceLocation ExtraModifierLoc;
};
/// Parses clauses with list.
bool ParseOpenMPVarList(OpenMPDirectiveKind DKind, OpenMPClauseKind Kind,
SmallVectorImpl<Expr *> &Vars,
OpenMPVarListDataTy &Data);
bool ParseUnqualifiedId(CXXScopeSpec &SS, ParsedType ObjectType,
bool ObjectHadErrors, bool EnteringContext,
bool AllowDestructorName, bool AllowConstructorName,
bool AllowDeductionGuide,
SourceLocation *TemplateKWLoc, UnqualifiedId &Result);
/// Parses the mapper modifier in map, to, and from clauses.
bool parseMapperModifier(OpenMPVarListDataTy &Data);
/// Parses map-type-modifiers in map clause.
/// map([ [map-type-modifier[,] [map-type-modifier[,] ...] map-type : ] list)
/// where, map-type-modifier ::= always | close | mapper(mapper-identifier)
bool parseMapTypeModifiers(OpenMPVarListDataTy &Data);
private:
//===--------------------------------------------------------------------===//
// C++ 14: Templates [temp]
// C++ 14.1: Template Parameters [temp.param]
Decl *ParseDeclarationStartingWithTemplate(DeclaratorContext Context,
SourceLocation &DeclEnd,
ParsedAttributes &AccessAttrs,
AccessSpecifier AS = AS_none);
Decl *ParseTemplateDeclarationOrSpecialization(DeclaratorContext Context,
SourceLocation &DeclEnd,
ParsedAttributes &AccessAttrs,
AccessSpecifier AS);
Decl *ParseSingleDeclarationAfterTemplate(
DeclaratorContext Context, const ParsedTemplateInfo &TemplateInfo,
ParsingDeclRAIIObject &DiagsFromParams, SourceLocation &DeclEnd,
ParsedAttributes &AccessAttrs, AccessSpecifier AS = AS_none);
bool ParseTemplateParameters(MultiParseScope &TemplateScopes, unsigned Depth,
SmallVectorImpl<NamedDecl *> &TemplateParams,
SourceLocation &LAngleLoc,
SourceLocation &RAngleLoc);
bool ParseTemplateParameterList(unsigned Depth,
SmallVectorImpl<NamedDecl*> &TemplateParams);
TPResult isStartOfTemplateTypeParameter();
NamedDecl *ParseTemplateParameter(unsigned Depth, unsigned Position);
NamedDecl *ParseTypeParameter(unsigned Depth, unsigned Position);
NamedDecl *ParseTemplateTemplateParameter(unsigned Depth, unsigned Position);
NamedDecl *ParseNonTypeTemplateParameter(unsigned Depth, unsigned Position);
bool isTypeConstraintAnnotation();
bool TryAnnotateTypeConstraint();
void DiagnoseMisplacedEllipsis(SourceLocation EllipsisLoc,
SourceLocation CorrectLoc,
bool AlreadyHasEllipsis,
bool IdentifierHasName);
void DiagnoseMisplacedEllipsisInDeclarator(SourceLocation EllipsisLoc,
Declarator &D);
// C++ 14.3: Template arguments [temp.arg]
typedef SmallVector<ParsedTemplateArgument, 16> TemplateArgList;
bool ParseGreaterThanInTemplateList(SourceLocation LAngleLoc,
SourceLocation &RAngleLoc,
bool ConsumeLastToken,
bool ObjCGenericList);
bool ParseTemplateIdAfterTemplateName(bool ConsumeLastToken,
SourceLocation &LAngleLoc,
TemplateArgList &TemplateArgs,
SourceLocation &RAngleLoc);
bool AnnotateTemplateIdToken(TemplateTy Template, TemplateNameKind TNK,
CXXScopeSpec &SS,
SourceLocation TemplateKWLoc,
UnqualifiedId &TemplateName,
bool AllowTypeAnnotation = true,
bool TypeConstraint = false);
void AnnotateTemplateIdTokenAsType(CXXScopeSpec &SS,
bool IsClassName = false);
bool ParseTemplateArgumentList(TemplateArgList &TemplateArgs);
ParsedTemplateArgument ParseTemplateTemplateArgument();
ParsedTemplateArgument ParseTemplateArgument();
Decl *ParseExplicitInstantiation(DeclaratorContext Context,
SourceLocation ExternLoc,
SourceLocation TemplateLoc,
SourceLocation &DeclEnd,
ParsedAttributes &AccessAttrs,
AccessSpecifier AS = AS_none);
// C++2a: Template, concept definition [temp]
Decl *
ParseConceptDefinition(const ParsedTemplateInfo &TemplateInfo,
SourceLocation &DeclEnd);
//===--------------------------------------------------------------------===//
// Modules
DeclGroupPtrTy ParseModuleDecl(bool IsFirstDecl);
Decl *ParseModuleImport(SourceLocation AtLoc);
bool parseMisplacedModuleImport();
bool tryParseMisplacedModuleImport() {
tok::TokenKind Kind = Tok.getKind();
if (Kind == tok::annot_module_begin || Kind == tok::annot_module_end ||
Kind == tok::annot_module_include)
return parseMisplacedModuleImport();
return false;
}
bool ParseModuleName(
SourceLocation UseLoc,
SmallVectorImpl<std::pair<IdentifierInfo *, SourceLocation>> &Path,
bool IsImport);
//===--------------------------------------------------------------------===//
// C++11/G++: Type Traits [Type-Traits.html in the GCC manual]
ExprResult ParseTypeTrait();
//===--------------------------------------------------------------------===//
// Embarcadero: Arary and Expression Traits
ExprResult ParseArrayTypeTrait();
ExprResult ParseExpressionTrait();
//===--------------------------------------------------------------------===//
// Preprocessor code-completion pass-through
void CodeCompleteDirective(bool InConditional) override;
void CodeCompleteInConditionalExclusion() override;
void CodeCompleteMacroName(bool IsDefinition) override;
void CodeCompletePreprocessorExpression() override;
void CodeCompleteMacroArgument(IdentifierInfo *Macro, MacroInfo *MacroInfo,
unsigned ArgumentIndex) override;
void CodeCompleteIncludedFile(llvm::StringRef Dir, bool IsAngled) override;
void CodeCompleteNaturalLanguage() override;
class GNUAsmQualifiers {
unsigned Qualifiers = AQ_unspecified;
public:
enum AQ {
AQ_unspecified = 0,
AQ_volatile = 1,
AQ_inline = 2,
AQ_goto = 4,
};
static const char *getQualifierName(AQ Qualifier);
bool setAsmQualifier(AQ Qualifier);
inline bool isVolatile() const { return Qualifiers & AQ_volatile; };
inline bool isInline() const { return Qualifiers & AQ_inline; };
inline bool isGoto() const { return Qualifiers & AQ_goto; }
};
bool isGCCAsmStatement(const Token &TokAfterAsm) const;
bool isGNUAsmQualifier(const Token &TokAfterAsm) const;
GNUAsmQualifiers::AQ getGNUAsmQualifier(const Token &Tok) const;
bool parseGNUAsmQualifierListOpt(GNUAsmQualifiers &AQ);
};
} // end namespace clang
#endif
|
mexutil.h | /*******************************************************************************
* mexutil.h - mex helpers
*******************************************************************************
* Add license here...
*******************************/
#ifndef MEXUTIL_H
#define MEXUTIL_H
// omp
#if _OPENMP
#include <omp.h>
#else
#define omp_get_thread_num() 0
#define omp_get_num_threads() 1
#define omp_set_num_threads(x)
#endif
// other
#include <cstring>
#include <mex.h>
#include <filter.h>
#include <gpm.h>
#include <nnf.h>
#include <vector>
#include <voting/histogram.h>
using pm::Image;
using pm::DataDepth;
template <typename Scalar>
mxClassID classID();
inline mxClassID classOf(int dataType) {
int depth = IM_MAT_DEPTH(dataType);
switch (depth) {
case IM_8U: return mxUINT8_CLASS;
case IM_8S: return mxINT8_CLASS;
case IM_32S: return mxINT32_CLASS;
case IM_32F: return mxSINGLE_CLASS;
case IM_64F: return mxDOUBLE_CLASS;
default:
mexErrMsgIdAndTxt("MATLAB:mex:classOf", "Unsupported class!");
return mxUNKNOWN_CLASS;
}
}
inline mxClassID classOf(const Image &img) {
return classOf(img.depth());
}
inline int depthOf(mxClassID c) {
switch(c) {
case mxUINT8_CLASS: return IM_8U;
case mxINT8_CLASS: return IM_8S;
case mxINT32_CLASS: return IM_32S;
case mxSINGLE_CLASS: return IM_32F;
case mxDOUBLE_CLASS: return IM_64F;
case mxLOGICAL_CLASS: return IM_8U;
default:
mexErrMsgIdAndTxt("MATLAB:mex:depthOf", "Unsupported depth!");
return -1;
}
}
inline int depthOf(const mxArray *arr) {
return depthOf(mxGetClassID(arr));
}
inline bool mxStringEquals(const mxArray *A, const char *s) {
char buf[256];
if (!mxIsChar(A)) {
return false;
}
if (mxGetString(A, buf, 255)) {
return false;
}
return strcmp(s, buf) == 0;
}
inline mxArray *mxCreateMatrix(int rows, int cols, mxClassID type = mxSINGLE_CLASS) {
mwSize sz[2] = {rows, cols};
return mxCreateNumericArray(2, sz, type, mxREAL);
}
inline mxArray *mxCreateMatrix(int rows, int cols, int channels, mxClassID type = mxSINGLE_CLASS) {
mwSize sz[3] = {rows, cols, channels};
return mxCreateNumericArray(3, sz, type, mxREAL);
}
template <typename Scalar>
inline mxArray *mxCreateMatrix(const Image &img) {
return mxCreateMatrix(img.rows, img.cols, img.channels(), classID<Scalar>());
}
inline mxArray *mxCreateMatrix(const Image &img) {
switch (img.depth()) {
case IM_8U: return mxCreateMatrix(img.rows, img.cols, img.channels(), mxUINT8_CLASS);
case IM_32F: return mxCreateMatrix(img.rows, img.cols, img.channels(), mxSINGLE_CLASS);
case IM_64F: return mxCreateMatrix(img.rows, img.cols, img.channels(), mxDOUBLE_CLASS);
default:
mexErrMsgIdAndTxt("MATLAB:mex:createMatrixFor", "Class type not supported!");
return NULL;
}
}
template <typename Scalar>
inline mxArray *mxCreateScalar(Scalar s) {
mxArray *d = mxCreateNumericArray(1, 1, classID<Scalar>());
Scalar *ptr = reinterpret_cast<Scalar *>(mxGetData(d));
*ptr = s;
return d;
}
inline double mxCheckedScalar(const mxArray *a, const char *s) {
if (!mxIsNumeric(a)) {
std::cerr << "ClassID = " << mxGetClassID(a) << "\n";
mexErrMsgIdAndTxt("MATLAB:mex:invalidInput", s);
}
return mxGetScalar(a);
}
inline bool mxHasField(const mxArray *options, mwIndex i, const char *fieldname) {
if(!mxIsStruct(options)){
mexErrMsgIdAndTxt("MATLAB:mex:mxHasField", "Invalid call mxHasField for '%s' on non-struct object.", fieldname);
return false;
}
return mxGetField(options, i, fieldname) != NULL;
}
inline double mxScalarField(const mxArray *options, mwIndex i, const char *fieldname, double defaultValue = 0) {
if(!mxIsStruct(options)){
mexErrMsgIdAndTxt("MATLAB:mex:mxHasField", "Invalid call mxHasField for '%s' on non-struct object.", fieldname);
return defaultValue;
}
const mxArray *tmp = mxGetField(options, i, fieldname);
if(tmp == NULL)
return defaultValue;
if(!mxIsNumeric(tmp))
return defaultValue;
return mxGetScalar(tmp);
}
inline bool mxBoolField(const mxArray *options, mwIndex i, const char *fieldname, bool defValue = false) {
if(!mxIsStruct(options)){
mexErrMsgIdAndTxt("MATLAB:mex:mxBoolField", "Invalid call mxBoolField for '%s' on non-struct object.", fieldname);
return defValue;
}
const mxArray *tmp = mxGetField(options, i, fieldname);
if(!tmp) return defValue;
if(mxIsNumeric(tmp)){
return mxGetScalar(tmp) != 0;
} else if(mxIsLogical(tmp) && mxGetNumberOfElements(tmp) > 0) {
return mxGetLogicals(tmp)[0];
} else {
mexErrMsgIdAndTxt("MATLAB:mex:invalidInput", "Parameter %s is not a valid boolean expression.", fieldname);
return defValue;
}
}
template <typename Scalar>
inline void mxLoadScalars(Scalar *ptr, int n, const mxArray *arr, const char *s) {
if (!mxIsNumeric(arr)) {
mexErrMsgIdAndTxt("MATLAB:mex:invalidInput", s);
}
if (mxGetClassID(arr) != classID<Scalar>()) {
mexErrMsgIdAndTxt("MATLAB:mex:invalidInput", s);
}
const Scalar *data = reinterpret_cast<const Scalar *> (mxGetData(arr));
switch (mxGetNumberOfElements(arr)) {
case 1:
std::fill(ptr, ptr + n, Scalar(mxGetScalar(arr)));
break;
case 5:
for (int i = 0; i < 5; ++i) ptr[i] = data[i];
break;
default:
mexErrMsgIdAndTxt("MATLAB:mex:invalidInput", s);
break;
}
}
inline void mxLoadFilter(pm::Filter &filter, const mxArray *arr, const char *s) {
if (!mxIsNumeric(arr)) {
mexErrMsgIdAndTxt("MATLAB:vote:wrongWeights",
"vote_weight should be an array of numbers!");
}
int m = mxGetM(arr);
int n = mxGetN(arr);
if (m == n && m == 1) {
filter = pm::Filter(filter.width, mxGetScalar(arr));
return;
}
if (m != n || m != filter.width) {
mexErrMsgIdAndTxt("MATLAB:filter:wrongSize", s);
}
switch (mxGetClassID(arr)) {
case mxSINGLE_CLASS:
{
float *data = reinterpret_cast<float *> (mxGetData(arr));
for (int y = 0; y < m; ++y) {
for (int x = 0; x < n; ++x) {
filter[y][x] = data[y + x * m];
}
}
}
break;
case mxDOUBLE_CLASS:
{
double *data = reinterpret_cast<double *> (mxGetData(arr));
for (int y = 0; y < m; ++y) {
for (int x = 0; x < n; ++x) {
filter[y][x] = float(data[y + x * m]);
}
}
}
break;
default:
mexErrMsgIdAndTxt("MATLAB:vote:voteClass",
"vote_weight must be single or double.");
break;
}
}
template <typename S, typename T>
inline void mxLoadVector(std::vector<T> &v, const mxArray *arr, const char *s) {
if (!mxIsNumeric(arr)) {
mexErrMsgIdAndTxt("MATLAB:mex:invalidInput", s);
}
const S *data = reinterpret_cast<const S *> (mxGetData(arr));
int N = mxGetNumberOfElements(arr);
if(N == 0) mexErrMsgIdAndTxt("MATLAB:mex:mxLoadVector", s);
// resize the vector and fill it
v.resize(N);
for(int i = 0; i < N; ++i) v[i] = T(data[i]);
}
template <typename T>
inline void mxLoadVector(std::vector<T> &v, const mxArray *arr, const char *s) {
switch (mxGetClassID(arr)) {
case mxINT8_CLASS: mxLoadVector<char, T>(v, arr, s); break;
case mxUINT8_CLASS: mxLoadVector<unsigned char, T>(v, arr, s); break;
case mxSINGLE_CLASS: mxLoadVector<float, T>(v, arr, s); break;
case mxDOUBLE_CLASS: mxLoadVector<double, T>(v, arr, s); break;
default:
mexErrMsgIdAndTxt("MATLAB:mex:mxLoadVector", "Class type not supported!");
}
}
template <typename GB>
inline void mxLoadGB(const mxArray *options) {
typedef typename GB::Vec3 Vec3;
mxArray *tmp;
if (tmp = mxGetField(options, 0, "min_bias")) {
mxLoadScalars(GB::minBias.data, 3, tmp, "Invalid min_bias!");
} else {
GB::minBias = Vec3(-10, -50, -50);
}
if (tmp = mxGetField(options, 0, "max_bias")) {
mxLoadScalars(GB::maxBias.data, 3, tmp, "Invalid max_bias!");
} else {
GB::maxBias = Vec3(10, 50, 50);
}
if (tmp = mxGetField(options, 0, "min_bias")) {
mxLoadScalars(GB::minGain.data, 3, tmp, "Invalid min_gain!");
} else {
GB::minGain = Vec3(0.9, 0.9, 0.9);
}
if (tmp = mxGetField(options, 0, "max_gain")) {
mxLoadScalars(GB::maxGain.data, 3, tmp, "Invalid max_gain!");
} else {
GB::maxGain = Vec3(1.5, 1.5, 1.5);
}
}
template <typename Scalar>
inline mxArray *mxImageToArray(const Image &img) {
// std::cout << "mxImageToArray\n";
mxArray *arr = mxCreateMatrix<Scalar>(img);
const int offset = img.rows * img.cols;
Scalar *data = reinterpret_cast<Scalar *> (mxGetData(arr));
// #pragma omp parallel for collapse(2)
for (int y = 0; y < img.rows; ++y) {
for (int x = 0; x < img.cols; ++x) {
const Scalar *iptr = img.ptr<Scalar>(y, x);
for (int ch = 0; ch < img.channels(); ++ch) {
// transposing!
data[y + x * img.rows + offset * ch] = iptr[ch];
}
}
}
return arr;
// return MxArray(img, mxUNKNOWN_CLASS, false);
}
inline mxArray *mxImageToArray(const Image &img) {
switch (img.depth()) {
case IM_8S: return mxImageToArray<char>(img);
case IM_8U: return mxImageToArray<unsigned char>(img);
case IM_32F: return mxImageToArray<float>(img);
case IM_64F: return mxImageToArray<double>(img);
default:
mexErrMsgIdAndTxt("MATLAB:mex:mxImageToArray", "Class type not supported!");
return NULL;
}
}
template <typename Scalar>
inline void mxCheckImage(const Image &img, const char *errMsg = "Corrupted image with pixels out of bounds!") {
bool err = false;
for (int y = 0; y < img.rows; ++y) {
for (int x = 0; x < img.cols; ++x) {
const Scalar *ptr = img.ptr<Scalar>(y, x);
for (int c = 0; c < img.channels(); ++c) {
Scalar d = ptr[c];
if ((d + 1) == d) {
std::cout << "Invalid p@" << y << "/" << x << "/c" << c << " = " << d << "\n";
err = true;
}
}
}
}
if (err) mexErrMsgIdAndTxt("MATLAB:mex:invalid_image", errMsg);
}
template <typename Scalar>
inline Image mxArrayToImage(const mxArray *arr, const char *errMsg) {
if (!mxIsNumeric(arr)) {
mexErrMsgIdAndTxt("MATLAB:mex:invalidInput", "Invalid image array.");
}
int h = mxGetDimensions(arr)[0];
int w = mxGetDimensions(arr)[1];
int num_ch = mxGetNumberOfDimensions(arr) < 3 ? 1 : mxGetDimensions(arr)[2];
const int offset = h * w;
// std::cout << "h=" << h << ", w=" << w << ", ch=" << num_ch << ", offset=" << offset << "\n";
assert(mxGetClassID(arr) == classID<Scalar>());
Image img(h, w, IM_MAKETYPE(DataDepth<Scalar>::value, num_ch));
// std::cout << "depth=" << DataDepth<Scalar>::value << ", ch=" << num_ch << "=" << img.channels() << "\n";
const Scalar *data = reinterpret_cast<const Scalar *> (mxGetData(arr));
// std::cout << "steps: " << img.step[0] << ", " << img.step[1] << ", " << img.step[2] << "\n";
// /!\ img.step[2] might be wrong! do not use at(y, x, ch) indexing!
// => use img.ptr(y, x)
if (num_ch == 1) {
#if _OPENMP
#pragma omp parallel for collapse(2)
#endif
for (int y = 0; y < img.rows; ++y) {
for (int x = 0; x < img.cols; ++x) {
// transposing!
img.at<Scalar>(y, x) = data[y + x * img.rows];
}
}
} else {
#if _OPENMP
#pragma omp parallel for collapse(2)
#endif
for (int y = 0; y < img.rows; ++y) {
for (int x = 0; x < img.cols; ++x) {
Scalar *iptr = img.ptr<Scalar>(y, x);
for (int ch = 0; ch < img.channels(); ++ch) {
// std::cout << "at(" << y << ", " << x << ", " << ch << ") = ";
// transposing!
Scalar v = data[y + x * img.rows + offset * ch];
// std::cout << v << "\n";
iptr[ch] = v;
}
}
}
}
mxCheckImage<Scalar>(img, errMsg);
return img;
// return MxArray(arr).toMat(CV_USRTYPE1, false);
}
inline Image mxArrayToImage(const mxArray *arr, const char *err = "Corrupted image with pixels out of bounds!") {
switch (mxGetClassID(arr)) {
case mxINT8_CLASS: return mxArrayToImage<char>(arr, err);
case mxUINT8_CLASS: return mxArrayToImage<unsigned char>(arr, err);
case mxSINGLE_CLASS: return mxArrayToImage<float>(arr, err);
case mxDOUBLE_CLASS: return mxArrayToImage<double>(arr, err);
default:
mexErrMsgIdAndTxt("MATLAB:mex:mxArrayToImage", "Class type not supported!");
return Image();
}
}
inline void mxLoadTexture(pm::Texture &tex, const mxArray *arr, const char *err = "Corrupted texture!") {
if(mxIsCell(arr)) {
int N = mxGetNumberOfElements(arr);
if (N < 1) {
mexErrMsgIdAndTxt("MATLAB:mex:mxLoadTexture", "Empty texture cell!");
}
const mxArray *cell = mxGetCell(arr, 0);
if(mxIsNumeric(cell))
tex = pm::Texture(mxArrayToImage(cell, "Invalid first texture cell!"), N - 1); //< stack is allocated here!
else
mexErrMsgIdAndTxt("MATLAB:mex:mxLoadTexture", "Texture cell is not numeric!");
for(int i = 1; i < N; ++i) {
cell = mxGetCell(arr, i);
if(cell == NULL){
mexErrMsgIdAndTxt("MATLAB:mex:mxLoadTexture", "Null cell!");
}
tex.stack[i - 1] = mxArrayToImage(cell);
// check image state
// std::cout << "T" << i << ": " << tex.stack[i-1].at<float>(tex.height - 1, tex.width - 1) << "\n";
}
// std::cout << "loaded texture (d=" << (N-1) << ")" << "\n";
} else if(mxIsNumeric(arr)) {
tex = pm::Texture(mxArrayToImage(arr, err));
} else {
mexErrMsgIdAndTxt("MATLAB:mex:mxLoadTexture", "Unknown texture class!");
}
}
template <typename Patch, typename Scalar>
inline void mxLoadNNF(pm::NearestNeighborField<Patch, Scalar> &nnf, const mxArray *narr,
const char *numericErrorMsg = "The NNF should contain numbers!") {
if (!mxIsNumeric(narr)) {
mexErrMsgIdAndTxt("MATLAB:vote:invalidArgument",
numericErrorMsg);
}
const int h = mxGetDimensions(narr)[0];
const int w = mxGetDimensions(narr)[1];
const int num_ch = mxGetNumberOfDimensions(narr) < 3 ? 1 : mxGetDimensions(narr)[2];
const int offset = h * w;
// check that sizes match
if (h != nnf.height || w != nnf.width) {
mexErrMsgIdAndTxt("MATLAB:mex:nnf_size",
"Invalid nnf size, got HxW=%dx%d instead of %dx%d", h, w, nnf.height, nnf.width);
}
// check that the class is valid
if (mxGetClassID(narr) != classID<float>()) {
mexErrMsgIdAndTxt("MATLAB:mex:nnf_class",
"Invalid NNF class, should be single!");
}
// check the channels
if (num_ch < 2) {
mexErrMsgIdAndTxt("MATLAB:mex:nnf_channels",
"The NNF should have at least two channels!");
}
// load the real nnf data
const float *fptr = reinterpret_cast<const float *> (mxGetData(narr));
#if _OPENMP
#pragma omp parallel for collapse(2) ordered
#endif
for (int y = 0; y < h; ++y) {
for (int x = 0; x < w; ++x) {
const float *base = fptr + y + x * h; // transposed!
// std::cout << "f@" << y << "/" << x << ": ";
// for(int i = 0; i < num_ch; ++i) std::cout << base[i * offset] << ", ";
// std::cout << "\n";
Patch &patch = nnf.get(y, x);
patch.load(base, num_ch, offset);
// std::cout << "- num_ch=" << num_ch << "\n";
// std::cout << "p: " << patch.y << "/" << patch.x << "\n";
// float d[10];
// float *data = &d[0];
// patch.store(data, num_ch);
// std::cout << "p@" << y << "/" << x << ": ";
// for(int i = 0; i < num_ch; ++i) std::cout << d[i] << ", ";
// std::cout << "\n";
// if((x + y) % 100 == 0){
// cv::Vec<float, 5> d;
// patch.store(d, 5);
// std::cout << "@" << y << "/" << x << ": " << d << "\n";
// }
//^ patch done
}
}
}
// boring implementations
template <>
mxClassID classID<float>() {
return mxSINGLE_CLASS;
}
template <>
mxClassID classID<double>() {
return mxDOUBLE_CLASS;
}
template <>
mxClassID classID<unsigned char>() {
return mxUINT8_CLASS;
}
template <>
mxClassID classID<char>() {
return mxINT8_CLASS;
}
#endif /* MEXUTIL_H */
|
grid_basis.c | /* Copyright 2014-2018 The PySCF Developers. 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.
*
* Author: Qiming Sun <osirpt.sun@gmail.com>
*/
#include <stdlib.h>
#include <math.h>
#include "cint.h"
#include "config.h"
#include "gto/grid_ao_drv.h"
#include "np_helper/np_helper.h"
#define MAX_THREADS 256
void VXCnr_ao_screen(unsigned char *non0table, double *coords, int ngrids,
int *atm, int natm, int *bas, int nbas, double *env)
{
const int nblk = (ngrids+BLKSIZE-1) / BLKSIZE;
int i, j;
int np, nc, atm_id;
size_t bas_id, ib;
double rr, arr, maxc;
double logcoeff[NPRIMAX];
double dr[3];
double *p_exp, *pcoeff, *ratm;
for (bas_id = 0; bas_id < nbas; bas_id++) {
np = bas[NPRIM_OF];
nc = bas[NCTR_OF ];
p_exp = env + bas[PTR_EXP];
pcoeff = env + bas[PTR_COEFF];
atm_id = bas[ATOM_OF];
ratm = env + atm[atm_id*ATM_SLOTS+PTR_COORD];
for (j = 0; j < np; j++) {
maxc = 0;
for (i = 0; i < nc; i++) {
maxc = MAX(maxc, fabs(pcoeff[i*np+j]));
}
logcoeff[j] = log(maxc);
}
for (ib = 0; ib < nblk; ib++) {
for (i = ib*BLKSIZE; i < MIN(ngrids, (ib+1)*BLKSIZE); i++) {
dr[0] = coords[0*ngrids+i] - ratm[0];
dr[1] = coords[1*ngrids+i] - ratm[1];
dr[2] = coords[2*ngrids+i] - ratm[2];
rr = dr[0]*dr[0] + dr[1]*dr[1] + dr[2]*dr[2];
for (j = 0; j < np; j++) {
arr = p_exp[j] * rr;
if (arr-logcoeff[j] < EXPCUTOFF) {
non0table[ib*nbas+bas_id] = 1;
goto next_blk;
}
}
}
non0table[ib*nbas+bas_id] = 0;
next_blk:;
}
bas += BAS_SLOTS;
}
}
// 1k grids per block
#define GRIDS_BLOCK 512
void VXCgen_grid(double *out, double *coords, double *atm_coords,
double *radii_table, int natm, int ngrids)
{
const size_t Ngrids = ngrids;
int i, j;
double dx, dy, dz;
double *atom_dist = malloc(sizeof(double) * natm*natm);
for (i = 0; i < natm; i++) {
for (j = 0; j < i; j++) {
dx = atm_coords[i*3+0] - atm_coords[j*3+0];
dy = atm_coords[i*3+1] - atm_coords[j*3+1];
dz = atm_coords[i*3+2] - atm_coords[j*3+2];
atom_dist[i*natm+j] = 1 / sqrt(dx*dx + dy*dy + dz*dz);
}
}
#pragma omp parallel private(i, j, dx, dy, dz)
{
double *grid_dist = malloc(sizeof(double) * natm*GRIDS_BLOCK);
double *buf = malloc(sizeof(double) * natm*GRIDS_BLOCK);
double *g = malloc(sizeof(double) * GRIDS_BLOCK);
size_t ig0, n, ngs;
double fac;
#pragma omp for nowait schedule(static)
for (ig0 = 0; ig0 < Ngrids; ig0 += GRIDS_BLOCK) {
ngs = MIN(Ngrids-ig0, GRIDS_BLOCK);
for (i = 0; i < natm; i++) {
for (n = 0; n < ngs; n++) {
dx = coords[0*Ngrids+ig0+n] - atm_coords[i*3+0];
dy = coords[1*Ngrids+ig0+n] - atm_coords[i*3+1];
dz = coords[2*Ngrids+ig0+n] - atm_coords[i*3+2];
grid_dist[i*GRIDS_BLOCK+n] = sqrt(dx*dx + dy*dy + dz*dz);
buf[i*GRIDS_BLOCK+n] = 1;
} }
for (i = 0; i < natm; i++) {
for (j = 0; j < i; j++) {
fac = atom_dist[i*natm+j];
for (n = 0; n < ngs; n++) {
g[n] = (grid_dist[i*GRIDS_BLOCK+n] -
grid_dist[j*GRIDS_BLOCK+n]) * fac;
}
if (radii_table != NULL) {
fac = radii_table[i*natm+j];
for (n = 0; n < ngs; n++) {
g[n] += fac * (1 - g[n]*g[n]);
}
}
for (n = 0; n < ngs; n++) {
g[n] = (3 - g[n]*g[n]) * g[n] * .5;
}
for (n = 0; n < ngs; n++) {
g[n] = (3 - g[n]*g[n]) * g[n] * .5;
}
for (n = 0; n < ngs; n++) {
g[n] = ((3 - g[n]*g[n]) * g[n] * .5) * .5;
}
for (n = 0; n < ngs; n++) {
buf[i*GRIDS_BLOCK+n] *= .5 - g[n];
buf[j*GRIDS_BLOCK+n] *= .5 + g[n];
}
} }
for (i = 0; i < natm; i++) {
for (n = 0; n < ngs; n++) {
out[i*Ngrids+ig0+n] = buf[i*GRIDS_BLOCK+n];
}
}
}
free(g);
free(buf);
free(grid_dist);
}
free(atom_dist);
}
|
test.c | #include <stdio.h>
#include <omp.h>
#include <string.h>
int main(int argc, char * argv[])
{
printf("there are %d arguments found\n", argc);
for(int i = 0; i < argc; i++)
{
printf("%s\n", argv[i]);
}
char strArr[1][1000] = {'\0'};
// char arr[1][255] = {"./tools/programmingTools/c_tools/programmingParser.py -t gcc -s c99 -f -Wall -f -Wextra -f -pedantic -f -pedantic-errors -d users/1/unzipped",
// };
// #pragma omp parallel for
// for(int k = 0; k < 1; k++)
// {
// char str[255] = {'\0'};
// char temp[1000] = {'\0'};
// FILE * fp;
// fp = popen(arr[k], "r");
// while(fgets(str, sizeof(str)-1, fp) != NULL)
// {
// strcat(temp, str);
// }
// pclose(fp);
// strcpy(strArr[k], temp);
// }
// for(int i = 0; i < 1; i++)
// {
// printf("%s\n", strArr[i]);
// }
}
|
generate-score-table.c | #include <glib.h>
#include <gio/gio.h>
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <fcntl.h>
#include <sys/mman.h>
#include <string.h>
#if HAVE_OPENMP
#include <omp.h>
#else
static int omp_get_thread_num (void) { return 0; }
#endif
#include <sparse.h>
G_DEFINE_AUTOPTR_CLEANUP_FUNC (FILE, fclose)
static gchar *method = "RNAcofold";
static gdouble temperature = 310.5;
static gchar *mask = "||||...";
static gchar *hard_mask = NULL; /* defaults to mask */
static gchar *output = NULL;
static gchar *nt = "ACGT";
static gfloat (*fold_duplex) (gchar *a, gchar *b, gchar *a_mask, gchar *b_mask, GError **err);
static const GOptionEntry MIRBOOKING_GENERATE_SCORE_TABLE_OPTIONS[] =
{
{"method", 0, 0, G_OPTION_ARG_STRING, &method, NULL, "RNAcofold"},
{"temperature", 0, 0, G_OPTION_ARG_DOUBLE, &temperature, NULL, "310.5"},
{"mask", 0, 0, G_OPTION_ARG_STRING, &mask, NULL, "||||..."},
{"hard-mask", 0, 0, G_OPTION_ARG_STRING, &hard_mask, NULL, "||||..."},
{"output", 0, 0, G_OPTION_ARG_FILENAME, &output, NULL, "FILE"},
{0}
};
static gchar
rc (gchar c)
{
switch (c)
{
case 'A':
return 'T';
case 'C':
return 'G';
case 'G':
return 'C';
case 'T':
return 'A';
default:
g_assert_not_reached ();
}
}
/**
* Compute the fourth integer power efficiently using bit-shift.
*/
static gsize
pow4 (gsize k)
{
return 1l << 2 * k;
}
static gfloat
fold_duplex_RNAcofold (gchar *a, gchar *b, gchar *a_mask, gchar *b_mask, GError **err)
{
gfloat binding_energy;
g_autofree gchar *standard_input = g_strdup_printf ("%s&%s\n%s&%s", a, b, a_mask, b_mask);
g_autofree gchar *standard_output;
g_autofree gchar *standard_error;
g_autofree gchar *temperature_str = g_strdup_printf ("%f", temperature - 272.15); // Kelvin -> Celsius
g_autoptr (GRegex) vienna_binding_energy_regex = g_regex_new ("delta G binding=\\s?(.+)", 0, 0, NULL);
g_autoptr (GSubprocess) proc = g_subprocess_new (G_SUBPROCESS_FLAGS_STDIN_PIPE | G_SUBPROCESS_FLAGS_STDOUT_PIPE | G_SUBPROCESS_FLAGS_STDERR_PIPE,
err,
"RNAcofold", "--noPS", "-p", "-C", "-T", temperature_str, NULL);
if (!proc)
{
return NAN;
}
if (!g_subprocess_communicate_utf8 (proc,
standard_input,
NULL,
&standard_output,
&standard_error,
err))
{
return NAN;
}
if (!g_subprocess_wait_check (proc,
NULL,
err))
{
return NAN;
}
g_autoptr (GMatchInfo) match_info;
if (!g_regex_match (vienna_binding_energy_regex, standard_output, 0, &match_info))
{
return NAN;
}
g_autofree gchar *binding_energy_str = g_match_info_fetch (match_info, 1);
sscanf (binding_energy_str, "%f", &binding_energy);
return binding_energy;
}
static gfloat
fold_duplex_mcff (gchar *a, gchar *b, gchar *a_mask, gchar *b_mask, GError **err)
{
g_autofree gchar *standard_output;
gfloat mfe;
g_autofree gchar *mask = g_strdup_printf ("%sxx%s", a_mask, b_mask);
gsize i;
for (i = 0; i < strlen (mask); i++)
{
switch (mask[i])
{
case 'x':
mask[i] = '.';
break;
case '.':
mask[i] = 'x';
break;
}
}
g_autoptr (GSubprocess) proc = g_subprocess_new (G_SUBPROCESS_FLAGS_STDOUT_PIPE,
err,
"mcff", "-seq", a, "-sd", b, "-mask", mask, NULL);
if (!proc)
{
return NAN;
}
if (!g_subprocess_communicate_utf8 (proc,
NULL,
NULL,
&standard_output,
NULL,
err))
{
return NAN;
}
if (!g_subprocess_wait_check (proc,
NULL,
err))
{
return NAN;
}
sscanf (standard_output, "%f", &mfe);
return mfe;
}
gint
main (gint argc, gchar **argv)
{
g_autoptr (GOptionContext) parser = g_option_context_new ("");
g_option_context_add_main_entries (parser,
MIRBOOKING_GENERATE_SCORE_TABLE_OPTIONS,
NULL);
if (!g_option_context_parse (parser,
&argc,
&argv,
NULL))
{
return EXIT_FAILURE;
}
if (g_strcmp0 (method, "RNAcofold") == 0)
{
fold_duplex = fold_duplex_RNAcofold;
}
else if (g_strcmp0 (method, "mcff") == 0)
{
fold_duplex = fold_duplex_mcff;
}
else
{
g_printerr ("Unknown folding method '%s'.\n", method);
return EXIT_FAILURE;
}
gsize seed_length = strlen (mask);
if (seed_length < 2 || seed_length >= 16)
{
g_printerr ("The mask must be formed of at least 2 nucleotides.\n");
return EXIT_FAILURE;
}
if (!hard_mask)
{
hard_mask = mask;
}
if (strlen (mask) != strlen (hard_mask))
{
g_printerr ("The hard mask must be the same size as the mask.");
return EXIT_FAILURE;
}
if (output == NULL)
{
g_printerr ("The '--output' argument is required.\n");
return EXIT_FAILURE;
}
// convert the mask into a symmetric mask for folding
g_autofree gchar *mre_mask = g_new0 (gchar, seed_length + 1);
g_autofree gchar *mir_mask = g_new0 (gchar, seed_length + 1);
{
gsize i;
for (i = 0; i < seed_length; i++)
{
mir_mask[i] = (mask[i] == '|') ? ')' : mask[i];
mre_mask[seed_length - i - 1] = (mask[i] == '|') ? '(' : mask[i];
}
}
gsize n = pow4 (seed_length);
gsize nnz = 1;
gsize z;
for (z = 0; z < seed_length; z++)
{
switch (hard_mask[z])
{
case '|':
nnz *= 4; /* canonical match */
break;
case 'x':
nnz *= 12; /* canonical mismatch */
break;
case '.':
nnz *= 16; /* no constraint */
break;
default:
g_printerr ("Unknown symbol '%c' in mask at position %lu.", hard_mask[z], z);
return EXIT_FAILURE;
}
}
g_debug ("n: %lu nnz %lu\n", n, nnz);
gsize file_len = sizeof (gsize) + sizeof (gsize) + (n + 1) * sizeof (gsize) + + nnz * sizeof (gsize) + nnz * sizeof (gfloat);
g_autoptr (FILE) f = fopen (output, "w+");
ftruncate (fileno (f), file_len);
gsize *table = mmap (NULL,
file_len,
PROT_WRITE,
MAP_SHARED,
fileno (f),
0);
if (table == MAP_FAILED)
{
g_printerr ("Failed to map %luB of memory.\n", file_len);
return EXIT_FAILURE;
}
g_return_val_if_fail (seed_length < 16, EXIT_FAILURE);
// shorthand to avoid aliasing
gfloat* data = (gfloat*) (table + 2 + n + 1 + nnz);
SparseMatrix sm;
sm.storage = SPARSE_MATRIX_STORAGE_CSR;
sm.type = SPARSE_MATRIX_TYPE_FLOAT;
sm.shape[0] = n;
sm.shape[1] = n;
sm.s.csr.nnz = nnz;
sm.s.csr.rowptr = table + 2;
sm.s.csr.colind = table + 2 + n + 1;
sm.default_data.f = INFINITY;
sm.data = data;
table[0] = n;
table[1] = nnz;
gsize i;
// all rows are equally-sized
#pragma omp parallel for
for (i = 0; i <= n; i++)
{
sm.s.csr.rowptr[i] = i * (nnz / n);
}
guint64 begin = g_get_monotonic_time ();
gsize completed = 0;
#pragma omp parallel for
for (i = 0; i < n; i++)
{
gsize j;
gsize k = 0;
for (j = 0; j < n; j++)
{
gchar mir_seed[16];
gchar mre_seed[16];
gsize z;
for (z = 0; z < seed_length; z++)
{
mir_seed[seed_length - z - 1] = nt[(i & (3 << 2 * z)) >> (2 * z)];
mre_seed[seed_length - z - 1] = nt[(j & (3 << 2 * z)) >> (2 * z)];
}
mir_seed[seed_length] = '\0';
mre_seed[seed_length] = '\0';
// reverse-complement hamming distance for the seed for paired
// positions
gint distance = 0;
for (z = 0; z < seed_length; z++)
{
switch (hard_mask[z])
{
case '|':
distance += mir_seed[z] != rc(mre_seed[seed_length - z - 1]);
break;
case 'x':
distance += mir_seed[z] == rc(mre_seed[seed_length - z - 1]);
break;
}
}
if (distance <= 0)
{
g_autoptr (GError) err = NULL;
gfloat binding_energy = fold_duplex (mre_seed,
mir_seed,
mre_mask,
mir_mask,
&err);
if (binding_energy == NAN)
{
g_printerr ("%s (%s, %u).\n", err->message, g_quark_to_string (err->domain), err->code);
exit (EXIT_FAILURE);
}
sm.s.csr.colind[sm.s.csr.rowptr[i] + k] = j;
data[sm.s.csr.rowptr[i] + k] = binding_energy;
++k;
#pragma omp atomic
++completed;
}
}
if (omp_get_thread_num () == 0)
{
g_print ("\r%.2f%% %lu/%lu [%.2fit/sec]",
100.0 * (gdouble) completed / (gdouble) nnz,
completed,
nnz,
completed / ((gdouble) (g_get_monotonic_time () - begin) / (gdouble) G_USEC_PER_SEC));
}
}
munmap (table, file_len);
return EXIT_SUCCESS;
}
|
3d25pt_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 25 point stencil with axis-symmetric ariable 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])+8;
Ny = atoi(argv[2])+8;
Nz = atoi(argv[3])+8;
}
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***)*13);
for(m=0; m<13;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] = 24;
tile_size[1] = 24;
tile_size[2] = 8;
tile_size[3] = 1024;
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<13; 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 >= 1) && (Nx >= 9) && (Ny >= 9) && (Nz >= 9)) {
for (t1=-1;t1<=floord(Nt-1,3);t1++) {
lbp=max(ceild(t1,2),ceild(6*t1-Nt+2,6));
ubp=min(floord(4*Nt+Nz-9,24),floord(12*t1+Nz+6,24));
#pragma omp parallel for private(lbv,ubv,t3,t4,t5,t6,t7,t8)
for (t2=lbp;t2<=ubp;t2++) {
for (t3=max(max(max(0,ceild(3*t1,2)),ceild(24*t2-Nz+5,8)),3*t1-3*t2+1);t3<=min(min(min(floord(4*Nt+Ny-9,8),floord(12*t1+Ny+15,8)),floord(24*t2+Ny+11,8)),floord(24*t1-24*t2+Nz+Ny+13,8));t3++) {
for (t4=max(max(max(max(0,ceild(3*t1-3*t2-126,128)),ceild(3*t1-254,256)),ceild(24*t2-Nz-1011,1024)),ceild(8*t3-Ny-1011,1024));t4<=min(min(min(min(floord(4*Nt+Nx-9,1024),floord(12*t1+Nx+15,1024)),floord(24*t2+Nx+11,1024)),floord(8*t3+Nx-5,1024)),floord(24*t1-24*t2+Nz+Nx+13,1024));t4++) {
for (t5=max(max(max(max(max(0,ceild(24*t2-Nz+5,4)),ceild(8*t3-Ny+5,4)),ceild(1024*t4-Nx+5,4)),3*t1),6*t1-6*t2+1);t5<=min(min(min(min(min(floord(24*t1-24*t2+Nz+18,4),2*t3),Nt-1),3*t1+5),6*t2+4),256*t4+254);t5++) {
for (t6=max(max(24*t2,4*t5+4),-24*t1+24*t2+8*t5-23);t6<=min(min(24*t2+23,-24*t1+24*t2+8*t5),4*t5+Nz-5);t6++) {
for (t7=max(8*t3,4*t5+4);t7<=min(8*t3+7,4*t5+Ny-5);t7++) {
lbv=max(1024*t4,4*t5+4);
ubv=min(1024*t4+1023,4*t5+Nx-5);
#pragma ivdep
#pragma vector always
for (t8=lbv;t8<=ubv;t8++) {
A[( t5 + 1) % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)] = (((((((((((((coef[0][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)] * A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)]) + (coef[1][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)] * (A[ t5 % 2][ (-4*t5+t6) - 1][ (-4*t5+t7)][ (-4*t5+t8)] + A[ t5 % 2][ (-4*t5+t6) + 1][ (-4*t5+t7)][ (-4*t5+t8)]))) + (coef[2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)] * (A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) - 1][ (-4*t5+t8)] + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) + 1][ (-4*t5+t8)]))) + (coef[3][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)] * (A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) - 1] + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) + 1]))) + (coef[4][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)] * (A[ t5 % 2][ (-4*t5+t6) - 2][ (-4*t5+t7)][ (-4*t5+t8)] + A[ t5 % 2][ (-4*t5+t6) + 2][ (-4*t5+t7)][ (-4*t5+t8)]))) + (coef[5][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)] * (A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) - 2][ (-4*t5+t8)] + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) + 2][ (-4*t5+t8)]))) + (coef[6][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)] * (A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) - 2] + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) + 2]))) + (coef[7][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)] * (A[ t5 % 2][ (-4*t5+t6) - 3][ (-4*t5+t7)][ (-4*t5+t8)] + A[ t5 % 2][ (-4*t5+t6) + 3][ (-4*t5+t7)][ (-4*t5+t8)]))) + (coef[8][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)] * (A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) - 3][ (-4*t5+t8)] + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) + 3][ (-4*t5+t8)]))) + (coef[9][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)] * (A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) - 3] + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) + 3]))) + (coef[10][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)] * (A[ t5 % 2][ (-4*t5+t6) - 4][ (-4*t5+t7)][ (-4*t5+t8)] + A[ t5 % 2][ (-4*t5+t6) + 4][ (-4*t5+t7)][ (-4*t5+t8)]))) + (coef[11][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)] * (A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) - 4][ (-4*t5+t8)] + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7) + 4][ (-4*t5+t8)]))) + (coef[12][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8)] * (A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) - 4] + A[ t5 % 2][ (-4*t5+t6)][ (-4*t5+t7)][ (-4*t5+t8) + 4])));;
}
}
}
}
}
}
}
}
}
/* 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(4, "variable axis-symmetric")
#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<13;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;
}
|
spacetime_heat_dl_kernel_antiderivative.h | /*
Copyright (c) 2020, VSB - Technical University of Ostrava and Graz University of
Technology
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 names of VSB - Technical University of Ostrava and Graz
University of Technology 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 VSB - TECHNICAL UNIVERSITY OF OSTRAVA AND
GRAZ UNIVERSITY OF TECHNOLOGY 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 spacetime_heat_dl_kernel_antiderivative.h
* @brief Kernel for uniform_spacetime_tensor_mesh.h.
*/
#ifndef INCLUDE_BESTHEA_SPACETIME_HEAT_DL_KERNEL_ANTIDERIVATIVE_H_
#define INCLUDE_BESTHEA_SPACETIME_HEAT_DL_KERNEL_ANTIDERIVATIVE_H_
#include <besthea/spacetime_heat_kernel_antiderivative.h>
#include "besthea/settings.h"
#include <vector>
namespace besthea {
namespace bem {
class spacetime_heat_dl_kernel_antiderivative;
}
}
/**
* Class representing a first and second antiderivative of the double-layer
* spacetime kernel.
*/
class besthea::bem::spacetime_heat_dl_kernel_antiderivative
: public besthea::bem::spacetime_heat_kernel_antiderivative<
spacetime_heat_dl_kernel_antiderivative > {
public:
/**
* Constructor.
* @param[in] alpha Heat conductivity.
*/
spacetime_heat_dl_kernel_antiderivative( sc alpha )
: spacetime_heat_kernel_antiderivative<
spacetime_heat_dl_kernel_antiderivative >( alpha ) {
}
/**
* Destructor.
*/
virtual ~spacetime_heat_dl_kernel_antiderivative( ) {
}
/**
* Evaluates the second antiderivative.
* @param[in] xy1 First coordinate of `x - y`.
* @param[in] xy2 Second coordinate of `x - y`.
* @param[in] xy3 Third coordinate of `x - y`.
* @param[in] nx Normal in the `x` variable.
* @param[in] ny Normal in the `y` variable.
* @param[in] ttau `t-tau`.
*/
#pragma omp declare simd uniform( this, nx, ny, ttau ) simdlen( DATA_WIDTH )
sc do_anti_tau_anti_t( sc xy1, sc xy2, sc xy3, [[maybe_unused]] const sc * nx,
const sc * ny, sc ttau ) const {
sc value;
sc norm2 = xy1 * xy1 + xy2 * xy2 + xy3 * xy3;
sc norm = std::sqrt( norm2 );
sc dot = xy1 * ny[ 0 ] + xy2 * ny[ 1 ] + xy3 * ny[ 2 ];
sc sqrt_d = std::sqrt( ttau );
if ( ttau > _eps ) {
if ( std::abs( dot ) > _eps ) { // delta > 0, norm > 0
value = -dot / ( _four * _pi * norm )
* ( ( _one / ( _two * _alpha ) - ttau / norm2 )
* std::erf( norm / ( _two * sqrt_d * _sqrt_alpha ) )
+ sqrt_d / ( _sqrt_pi * _sqrt_alpha * norm )
* std::exp( -norm2 / ( _four * _alpha * ttau ) ) );
} else { // ttau > 0, limit for norm -> 0
value = 0.0;
}
} else { // limit for ttau -> 0, assuming norm > 0
value = -dot / ( _eight * _pi * norm * _alpha );
}
return value;
}
/**
* Evaluates the second antiderivative.
* @param[in] xy1 First coordinate of `x - y`.
* @param[in] xy2 Second coordinate of `x - y`.
* @param[in] xy3 Third coordinate of `x - y`.
* @param[in] nx Normal in the `x` variable.
* @param[in] ny Normal in the `y` variable.
* @param[in] ttau `t-tau`.
*/
#pragma omp declare simd uniform( this, nx, ny, ttau ) simdlen( DATA_WIDTH )
sc do_anti_tau_anti_t_regular_in_time( sc xy1, sc xy2, sc xy3,
[[maybe_unused]] const sc * nx, const sc * ny, sc ttau ) const {
sc value;
sc norm2 = xy1 * xy1 + xy2 * xy2 + xy3 * xy3;
sc norm = std::sqrt( norm2 );
sc dot = xy1 * ny[ 0 ] + xy2 * ny[ 1 ] + xy3 * ny[ 2 ];
sc sqrt_d = std::sqrt( ttau );
if ( std::abs( dot ) > _eps ) { // ttau > 0, norm > 0
value = -dot / ( _four * _pi * norm )
* ( ( _one / ( _two * _alpha ) - ttau / norm2 )
* std::erf( norm / ( _two * sqrt_d * _sqrt_alpha ) )
+ sqrt_d / ( _sqrt_pi * _sqrt_alpha * norm )
* std::exp( -norm2 / ( _four * _alpha * ttau ) ) );
} else { // ttau > 0, limit for norm -> 0
value = 0.0;
}
return value;
}
/**
* Evaluates the second antiderivative.
* @param[in] xy1 First coordinate of `x - y`.
* @param[in] xy2 Second coordinate of `x - y`.
* @param[in] xy3 Third coordinate of `x - y`.
* @param[in] nx Normal in the `x` variable.
* @param[in] ny Normal in the `y` variable.
* @param[in] ttau `t-tau`.
*/
#pragma omp declare simd uniform( this, nx, ny, ttau ) simdlen( DATA_WIDTH )
sc do_anti_tau_anti_t_regular_in_time_regular_in_space( sc xy1, sc xy2,
sc xy3, [[maybe_unused]] const sc * nx, const sc * ny, sc ttau ) const {
sc norm2 = xy1 * xy1 + xy2 * xy2 + xy3 * xy3;
sc norm = std::sqrt( norm2 );
sc dot = xy1 * ny[ 0 ] + xy2 * ny[ 1 ] + xy3 * ny[ 2 ];
sc sqrt_d = std::sqrt( ttau );
// ttau > 0, norm > 0
sc value = -dot / ( _four * _pi * norm )
* ( ( _one / ( _two * _alpha ) - ttau / norm2 )
* std::erf( norm / ( _two * sqrt_d * _sqrt_alpha ) )
+ sqrt_d / ( _sqrt_pi * _sqrt_alpha * norm )
* std::exp( -norm2 / ( _four * _alpha * ttau ) ) );
return value;
}
/**
* Evaluates the second antiderivative.
* @param[in] xy1 First coordinate of `x - y`.
* @param[in] xy2 Second coordinate of `x - y`.
* @param[in] xy3 Third coordinate of `x - y`.
* @param[in] nx Normal in the `x` variable.
* @param[in] ny Normal in the `y` variable.
*/
#pragma omp declare simd uniform( this, nx, ny ) simdlen( DATA_WIDTH )
sc do_anti_tau_anti_t_limit_in_time_regular_in_space( sc xy1, sc xy2, sc xy3,
[[maybe_unused]] const sc * nx, const sc * ny ) const {
sc norm2 = xy1 * xy1 + xy2 * xy2 + xy3 * xy3;
sc norm = std::sqrt( norm2 );
sc dot = xy1 * ny[ 0 ] + xy2 * ny[ 1 ] + xy3 * ny[ 2 ];
// limit for ttau -> 0, assuming norm > 0
sc value = -dot / ( _eight * _pi * norm * _alpha );
return value;
}
/**
* Evaluates the first antiderivative.
* @param[in] xy1 First coordinate of `x - y`.
* @param[in] xy2 Second coordinate of `x - y`.
* @param[in] xy3 Third coordinate of `x - y`.
* @param[in] nx Normal in the `x` variable.
* @param[in] ny Normal in the `y` variable.
* @param[in] ttau `t-tau`.
*/
#pragma omp declare simd uniform( this, nx, ny, ttau ) simdlen( DATA_WIDTH )
sc do_anti_tau_regular( sc xy1, sc xy2, sc xy3,
[[maybe_unused]] const sc * nx, const sc * ny, sc ttau ) const {
sc norm2 = xy1 * xy1 + xy2 * xy2 + xy3 * xy3;
sc norm = std::sqrt( norm2 );
sc dot = xy1 * ny[ 0 ] + xy2 * ny[ 1 ] + xy3 * ny[ 2 ];
sc sqrt_d = std::sqrt( ttau );
sc value = dot / ( _four * _pi * norm2 )
* ( std::erf( norm / ( _two * sqrt_d * _sqrt_alpha ) ) / norm
- _one / ( _sqrt_pi * sqrt_d * _sqrt_alpha )
* std::exp( -norm2 / ( _four * ttau * _alpha ) ) );
return value;
}
/**
* Evaluates the first antiderivative.
* @param[in] xy1 First coordinate of `x - y`.
* @param[in] xy2 Second coordinate of `x - y`.
* @param[in] xy3 Third coordinate of `x - y`.
* @param[in] nx Normal in the `x` variable.
* @param[in] ny Normal in the `y` variable.
*/
#pragma omp declare simd uniform( this, nx, ny ) simdlen( DATA_WIDTH )
sc do_anti_tau_limit( sc xy1, sc xy2, sc xy3, [[maybe_unused]] const sc * nx,
const sc * ny ) const {
sc norm2 = xy1 * xy1 + xy2 * xy2 + xy3 * xy3;
sc norm = std::sqrt( norm2 );
sc dot = xy1 * ny[ 0 ] + xy2 * ny[ 1 ] + xy3 * ny[ 2 ];
sc value = dot / ( _four * _pi * norm2 * norm );
return value;
}
/**
* Evaluates the definite integral over the same time interval.
* @param[in] xy1 First coordinate of `x - y`.
* @param[in] xy2 Second coordinate of `x - y`.
* @param[in] xy3 Third coordinate of `x - y`.
* @param[in] nx Normal in the `x` variable.
* @param[in] ny Normal in the `y` variable.
* @param[in] t0 Start of interval.
* @param[in] t1 End of interval.
*/
#pragma omp declare simd uniform( this, nx, ny, t0, t1 ) simdlen( DATA_WIDTH )
sc do_definite_integral_over_same_interval(
sc xy1, sc xy2, sc xy3, const sc * nx, const sc * ny, sc t0, sc t1 ) const {
sc value = ( t1 - t0 ) * do_anti_tau_limit( xy1, xy2, xy3, nx, ny )
- do_anti_tau_anti_t_regular_in_time( xy1, xy2, xy3, nx, ny, t1 - t0 )
+ do_anti_tau_anti_t_limit_in_time_regular_in_space(
xy1, xy2, xy3, nx, ny );
return value;
}
/**
* Evaluates the definite integral over the different time intervals.
* @param[in] xy1 First coordinate of `x - y`.
* @param[in] xy2 Second coordinate of `x - y`.
* @param[in] xy3 Third coordinate of `x - y`.
* @param[in] nx Normal in the `x` variable.
* @param[in] ny Normal in the `y` variable.
* @param[in] t0 Start of interval in `t`.
* @param[in] t1 End of interval in `t`.
* @param[in] tau0 Start of interval in `tau`.
* @param[in] tau1 End of interval in `tau`.
*/
#pragma omp declare simd uniform( this, ny, t0, t1, tau0, tau1 ) \
simdlen( DATA_WIDTH )
sc do_definite_integral_over_different_intervals( sc xy1, sc xy2, sc xy3,
const sc * nx, const sc * ny, sc t0, sc t1, sc tau0, sc tau1 ) const {
sc value = do_anti_tau_anti_t( xy1, xy2, xy3, nx, ny, t1 - tau1 )
- do_anti_tau_anti_t( xy1, xy2, xy3, nx, ny, t1 - tau0 )
- do_anti_tau_anti_t( xy1, xy2, xy3, nx, ny, t0 - tau1 )
+ do_anti_tau_anti_t( xy1, xy2, xy3, nx, ny, t0 - tau0 );
return value;
}
};
#endif /* INCLUDE_BESTHEA_SPACETIME_HEAT_DL_KERNEL_ANTIDERIVATIVE_H_ \
*/
|
GB_binop__pow_uint8.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__pow_uint8)
// A.*B function (eWiseMult): GB (_AemultB_08__pow_uint8)
// A.*B function (eWiseMult): GB (_AemultB_02__pow_uint8)
// A.*B function (eWiseMult): GB (_AemultB_04__pow_uint8)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__pow_uint8)
// A*D function (colscale): GB ((none))
// D*A function (rowscale): GB ((none))
// C+=B function (dense accum): GB (_Cdense_accumB__pow_uint8)
// C+=b function (dense accum): GB (_Cdense_accumb__pow_uint8)
// C+=A+B function (dense ewise3): GB ((none))
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__pow_uint8)
// C=scalar+B GB (_bind1st__pow_uint8)
// C=scalar+B' GB (_bind1st_tran__pow_uint8)
// C=A+scalar GB (_bind2nd__pow_uint8)
// C=A'+scalar GB (_bind2nd_tran__pow_uint8)
// C type: uint8_t
// A type: uint8_t
// A pattern? 0
// B type: uint8_t
// B pattern? 0
// BinaryOp: cij = GB_pow_uint8 (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)
// 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) \
uint8_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) \
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_pow_uint8 (x, y) ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
1
// 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_POW || GxB_NO_UINT8 || GxB_NO_POW_UINT8)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
#if 0
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
#endif
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
void GB (_Cdense_ewise3_noaccum__pow_uint8)
(
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__pow_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__pow_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
//------------------------------------------------------------------------------
#if 0
GrB_Info GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix D,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint8_t *restrict Cx = (uint8_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,
const GrB_Matrix B,
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
}
#endif
//------------------------------------------------------------------------------
// eWiseAdd: C=A+B, C<M>=A+B, C<!M>=A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__pow_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 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) ;
uint8_t alpha_scalar ;
uint8_t beta_scalar ;
if (is_eWiseUnion)
{
alpha_scalar = (*((uint8_t *) alpha_scalar_in)) ;
beta_scalar = (*((uint8_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__pow_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__pow_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__pow_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__pow_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__pow_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_pow_uint8 (x, bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__pow_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_pow_uint8 (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_pow_uint8 (x, aij) ; \
}
GrB_Info GB (_bind1st_tran__pow_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_pow_uint8 (aij, y) ; \
}
GrB_Info GB (_bind2nd_tran__pow_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
|
column_matrix.h | /*!
* Copyright 2017 by Contributors
* \file column_matrix.h
* \brief Utility for fast column-wise access
* \author Philip Cho
*/
#ifndef XGBOOST_COMMON_COLUMN_MATRIX_H_
#define XGBOOST_COMMON_COLUMN_MATRIX_H_
#include <limits>
#include <vector>
#include <memory>
#include "hist_util.h"
namespace xgboost {
namespace common {
class ColumnMatrix;
/*! \brief column type */
enum ColumnType {
kDenseColumn,
kSparseColumn
};
/*! \brief a column storage, to be used with ApplySplit. Note that each
bin id is stored as index[i] + index_base.
Different types of column index for each column allow
to reduce the memory usage. */
template <typename BinIdxType>
class Column {
public:
Column(ColumnType type, common::Span<const BinIdxType> index, const uint32_t index_base)
: type_(type),
index_(index),
index_base_(index_base) {}
uint32_t GetGlobalBinIdx(size_t idx) const {
return index_base_ + static_cast<uint32_t>(index_[idx]);
}
BinIdxType GetFeatureBinIdx(size_t idx) const { return index_[idx]; }
const uint32_t GetBaseIdx() const { return index_base_; }
common::Span<const BinIdxType> GetFeatureBinIdxPtr() const { return index_; }
ColumnType GetType() const { return type_; }
/* returns number of elements in column */
size_t Size() const { return index_.size(); }
private:
/* type of column */
ColumnType type_;
/* bin indexes in range [0, max_bins - 1] */
common::Span<const BinIdxType> index_;
/* bin index offset for specific feature */
const uint32_t index_base_;
};
template <typename BinIdxType>
class SparseColumn: public Column<BinIdxType> {
public:
SparseColumn(ColumnType type, common::Span<const BinIdxType> index,
uint32_t index_base, common::Span<const size_t> row_ind)
: Column<BinIdxType>(type, index, index_base),
row_ind_(row_ind) {}
const size_t* GetRowData() const { return row_ind_.data(); }
size_t GetRowIdx(size_t idx) const {
return row_ind_.data()[idx];
}
private:
/* indexes of rows */
common::Span<const size_t> row_ind_;
};
template <typename BinIdxType>
class DenseColumn: public Column<BinIdxType> {
public:
DenseColumn(ColumnType type, common::Span<const BinIdxType> index,
uint32_t index_base, const std::vector<bool>& missing_flags,
size_t feature_offset)
: Column<BinIdxType>(type, index, index_base),
missing_flags_(missing_flags),
feature_offset_(feature_offset) {}
bool IsMissing(size_t idx) const { return missing_flags_[feature_offset_ + idx]; }
private:
/* flags for missing values in dense columns */
const std::vector<bool>& missing_flags_;
size_t feature_offset_;
};
/*! \brief a collection of columns, with support for construction from
GHistIndexMatrix. */
class ColumnMatrix {
public:
// get number of features
inline bst_uint GetNumFeature() const {
return static_cast<bst_uint>(type_.size());
}
// construct column matrix from GHistIndexMatrix
inline void Init(const GHistIndexMatrix& gmat,
double sparse_threshold) {
const int32_t nfeature = static_cast<int32_t>(gmat.cut.Ptrs().size() - 1);
const size_t nrow = gmat.row_ptr.size() - 1;
// identify type of each column
feature_counts_.resize(nfeature);
type_.resize(nfeature);
std::fill(feature_counts_.begin(), feature_counts_.end(), 0);
uint32_t max_val = std::numeric_limits<uint32_t>::max();
for (int32_t fid = 0; fid < nfeature; ++fid) {
CHECK_LE(gmat.cut.Ptrs()[fid + 1] - gmat.cut.Ptrs()[fid], max_val);
}
bool all_dense = gmat.IsDense();
gmat.GetFeatureCounts(&feature_counts_[0]);
// classify features
for (int32_t fid = 0; fid < nfeature; ++fid) {
if (static_cast<double>(feature_counts_[fid])
< sparse_threshold * nrow) {
type_[fid] = kSparseColumn;
all_dense = false;
} else {
type_[fid] = kDenseColumn;
}
}
// want to compute storage boundary for each feature
// using variants of prefix sum scan
feature_offsets_.resize(nfeature + 1);
size_t accum_index_ = 0;
feature_offsets_[0] = accum_index_;
for (int32_t fid = 1; fid < nfeature + 1; ++fid) {
if (type_[fid - 1] == kDenseColumn) {
accum_index_ += static_cast<size_t>(nrow);
} else {
accum_index_ += feature_counts_[fid - 1];
}
feature_offsets_[fid] = accum_index_;
}
SetTypeSize(gmat.max_num_bins);
index_.resize(feature_offsets_[nfeature] * bins_type_size_, 0);
if (!all_dense) {
row_ind_.resize(feature_offsets_[nfeature]);
}
// store least bin id for each feature
index_base_ = const_cast<uint32_t*>(gmat.cut.Ptrs().data());
const bool noMissingValues = NoMissingValues(gmat.row_ptr[nrow], nrow, nfeature);
if (noMissingValues) {
missing_flags_.resize(feature_offsets_[nfeature], false);
} else {
missing_flags_.resize(feature_offsets_[nfeature], true);
}
// pre-fill index_ for dense columns
if (all_dense) {
BinTypeSize gmat_bin_size = gmat.index.GetBinTypeSize();
if (gmat_bin_size == kUint8BinsTypeSize) {
SetIndexAllDense(gmat.index.data<uint8_t>(), gmat, nrow, nfeature, noMissingValues);
} else if (gmat_bin_size == kUint16BinsTypeSize) {
SetIndexAllDense(gmat.index.data<uint16_t>(), gmat, nrow, nfeature, noMissingValues);
} else {
CHECK_EQ(gmat_bin_size, kUint32BinsTypeSize);
SetIndexAllDense(gmat.index.data<uint32_t>(), gmat, nrow, nfeature, noMissingValues);
}
/* For sparse DMatrix gmat.index.getBinTypeSize() returns always kUint32BinsTypeSize
but for ColumnMatrix we still have a chance to reduce the memory consumption */
} else {
if (bins_type_size_ == kUint8BinsTypeSize) {
SetIndex<uint8_t>(gmat.index.data<uint32_t>(), gmat, nrow, nfeature);
} else if (bins_type_size_ == kUint16BinsTypeSize) {
SetIndex<uint16_t>(gmat.index.data<uint32_t>(), gmat, nrow, nfeature);
} else {
CHECK_EQ(bins_type_size_, kUint32BinsTypeSize);
SetIndex<uint32_t>(gmat.index.data<uint32_t>(), gmat, nrow, nfeature);
}
}
}
/* Set the number of bytes based on numeric limit of maximum number of bins provided by user */
void SetTypeSize(size_t max_num_bins) {
if ( (max_num_bins - 1) <= static_cast<int>(std::numeric_limits<uint8_t>::max()) ) {
bins_type_size_ = kUint8BinsTypeSize;
} else if ((max_num_bins - 1) <= static_cast<int>(std::numeric_limits<uint16_t>::max())) {
bins_type_size_ = kUint16BinsTypeSize;
} else {
bins_type_size_ = kUint32BinsTypeSize;
}
}
/* Fetch an individual column. This code should be used with type swith
to determine type of bin id's */
template <typename BinIdxType>
std::unique_ptr<const Column<BinIdxType> > GetColumn(unsigned fid) const {
CHECK_EQ(sizeof(BinIdxType), bins_type_size_);
const size_t feature_offset = feature_offsets_[fid]; // to get right place for certain feature
const size_t column_size = feature_offsets_[fid + 1] - feature_offset;
common::Span<const BinIdxType> bin_index = { reinterpret_cast<const BinIdxType*>(
&index_[feature_offset * bins_type_size_]),
column_size };
std::unique_ptr<const Column<BinIdxType> > res;
if (type_[fid] == ColumnType::kDenseColumn) {
res.reset(new DenseColumn<BinIdxType>(type_[fid], bin_index, index_base_[fid],
missing_flags_, feature_offset));
} else {
res.reset(new SparseColumn<BinIdxType>(type_[fid], bin_index, index_base_[fid],
{&row_ind_[feature_offset], column_size}));
}
return res;
}
template<typename T>
inline void SetIndexAllDense(T* index, const GHistIndexMatrix& gmat, const size_t nrow,
const size_t nfeature, const bool noMissingValues) {
T* local_index = reinterpret_cast<T*>(&index_[0]);
/* missing values make sense only for column with type kDenseColumn,
and if no missing values were observed it could be handled much faster. */
if (noMissingValues) {
#pragma omp parallel for num_threads(omp_get_max_threads())
for (omp_ulong rid = 0; rid < nrow; ++rid) {
const size_t ibegin = rid*nfeature;
const size_t iend = (rid+1)*nfeature;
size_t j = 0;
for (size_t i = ibegin; i < iend; ++i, ++j) {
const size_t idx = feature_offsets_[j];
local_index[idx + rid] = index[i];
}
}
} else {
/* to handle rows in all batches, sum of all batch sizes equal to gmat.row_ptr.size() - 1 */
size_t rbegin = 0;
for (const auto &batch : gmat.p_fmat->GetBatches<SparsePage>()) {
const xgboost::Entry* data_ptr = batch.data.HostVector().data();
const std::vector<bst_row_t>& offset_vec = batch.offset.HostVector();
const size_t batch_size = batch.Size();
CHECK_LT(batch_size, offset_vec.size());
for (size_t rid = 0; rid < batch_size; ++rid) {
const size_t size = offset_vec[rid + 1] - offset_vec[rid];
SparsePage::Inst inst = {data_ptr + offset_vec[rid], size};
const size_t ibegin = gmat.row_ptr[rbegin + rid];
const size_t iend = gmat.row_ptr[rbegin + rid + 1];
CHECK_EQ(ibegin + inst.size(), iend);
size_t j = 0;
size_t fid = 0;
for (size_t i = ibegin; i < iend; ++i, ++j) {
fid = inst[j].index;
const size_t idx = feature_offsets_[fid];
/* rbegin allows to store indexes from specific SparsePage batch */
local_index[idx + rbegin + rid] = index[i];
missing_flags_[idx + rbegin + rid] = false;
}
}
rbegin += batch.Size();
}
}
}
template<typename T>
inline void SetIndex(uint32_t* index, const GHistIndexMatrix& gmat,
const size_t nrow, const size_t nfeature) {
std::vector<size_t> num_nonzeros;
num_nonzeros.resize(nfeature);
std::fill(num_nonzeros.begin(), num_nonzeros.end(), 0);
T* local_index = reinterpret_cast<T*>(&index_[0]);
size_t rbegin = 0;
for (const auto &batch : gmat.p_fmat->GetBatches<SparsePage>()) {
const xgboost::Entry* data_ptr = batch.data.HostVector().data();
const std::vector<bst_row_t>& offset_vec = batch.offset.HostVector();
const size_t batch_size = batch.Size();
CHECK_LT(batch_size, offset_vec.size());
for (size_t rid = 0; rid < batch_size; ++rid) {
const size_t ibegin = gmat.row_ptr[rbegin + rid];
const size_t iend = gmat.row_ptr[rbegin + rid + 1];
size_t fid = 0;
const size_t size = offset_vec[rid + 1] - offset_vec[rid];
SparsePage::Inst inst = {data_ptr + offset_vec[rid], size};
CHECK_EQ(ibegin + inst.size(), iend);
size_t j = 0;
for (size_t i = ibegin; i < iend; ++i, ++j) {
const uint32_t bin_id = index[i];
fid = inst[j].index;
if (type_[fid] == kDenseColumn) {
T* begin = &local_index[feature_offsets_[fid]];
begin[rid + rbegin] = bin_id - index_base_[fid];
missing_flags_[feature_offsets_[fid] + rid + rbegin] = false;
} else {
T* begin = &local_index[feature_offsets_[fid]];
begin[num_nonzeros[fid]] = bin_id - index_base_[fid];
row_ind_[feature_offsets_[fid] + num_nonzeros[fid]] = rid + rbegin;
++num_nonzeros[fid];
}
}
}
rbegin += batch.Size();
}
}
const BinTypeSize GetTypeSize() const {
return bins_type_size_;
}
const bool NoMissingValues(const size_t n_elements,
const size_t n_row, const size_t n_features) {
return n_elements == n_features * n_row;
}
private:
std::vector<uint8_t> index_;
std::vector<size_t> feature_counts_;
std::vector<ColumnType> type_;
std::vector<size_t> row_ind_;
/* indicate where each column's index and row_ind is stored. */
std::vector<size_t> feature_offsets_;
// index_base_[fid]: least bin id for feature fid
uint32_t* index_base_;
std::vector<bool> missing_flags_;
BinTypeSize bins_type_size_;
};
} // namespace common
} // namespace xgboost
#endif // XGBOOST_COMMON_COLUMN_MATRIX_H_
|
GB_unop__ainv_fc32_fc32.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_atomics.h"
#include "GB_unop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB_unop_apply__ainv_fc32_fc32
// op(A') function: GB_unop_tran__ainv_fc32_fc32
// C type: GxB_FC32_t
// A type: GxB_FC32_t
// cast: GxB_FC32_t cij = aij
// unaryop: cij = GB_FC32_ainv (aij)
#define GB_ATYPE \
GxB_FC32_t
#define GB_CTYPE \
GxB_FC32_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
GxB_FC32_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = GB_FC32_ainv (x) ;
// casting
#define GB_CAST(z, aij) \
GxB_FC32_t z = aij ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GxB_FC32_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
GxB_FC32_t z = aij ; \
Cx [pC] = GB_FC32_ainv (z) ; \
}
// true if operator is the identity op with no typecasting
#define GB_OP_IS_IDENTITY_WITH_NO_TYPECAST \
0
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_AINV || GxB_NO_FC32)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop_apply__ainv_fc32_fc32
(
GxB_FC32_t *Cx, // Cx and Ax may be aliased
const GxB_FC32_t *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 (GxB_FC32_t), nthreads) ;
#else
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
GxB_FC32_t aij = Ax [p] ;
GxB_FC32_t z = aij ;
Cx [p] = GB_FC32_ainv (z) ;
}
#endif
}
else
{
// bitmap case, no transpose; A->b already memcpy'd into C->b
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!Ab [p]) continue ;
GxB_FC32_t aij = Ax [p] ;
GxB_FC32_t z = aij ;
Cx [p] = GB_FC32_ainv (z) ;
}
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop_tran__ainv_fc32_fc32
(
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
|
sorter.h | #pragma once
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
#ifdef __USE_ASL__
#include <asl.h>
#endif
#ifdef __USE_ASL__
#define vgl_sort_indexes asl_int_t
#endif
#ifndef __USE_ASL__
#define vgl_sort_indexes long long
#endif
#ifdef __USE_GPU__
#include <thrust/sort.h>
#include <thrust/execution_policy.h>
#endif
#include <algorithm>
#include <functional>
enum SortOrder {
SORT_ASCENDING = 0,
SORT_DESCENDING = 1
};
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
class Sorter
{
private:
#ifdef __USE_ASL__
static void asl_inner_sort(int *_data, vgl_sort_indexes *_indexes, long long _size, SortOrder _sort_order)
{
asl_sort_t hnd;
if(_sort_order == SORT_ASCENDING)
{
ASL_CALL(asl_sort_create_i32(&hnd, ASL_SORTORDER_ASCENDING, ASL_SORTALGORITHM_AUTO));
}
else if(_sort_order == SORT_DESCENDING)
{
ASL_CALL(asl_sort_create_i32(&hnd, ASL_SORTORDER_DESCENDING, ASL_SORTALGORITHM_AUTO));
}
// do sorting
ASL_CALL(asl_sort_execute_i32(hnd, _size, (asl_int32_t*)_data, ASL_NULL, (asl_int32_t*)_data, _indexes));
ASL_CALL(asl_sort_destroy(hnd));
};
#endif
static void std_inner_sort(int *_data, vgl_sort_indexes *_indexes, long long _size, SortOrder _sort_order)
{
if(_indexes != NULL)
{
int *work_buffer;
MemoryAPI::allocate_array(&work_buffer, _size);
if(_sort_order == SORT_ASCENDING)
{
stable_sort(_indexes, _indexes + _size, [&_data](long long _i1, long long _i2) {return _data[_i1] < _data[_i2];});
}
else if(_sort_order == SORT_DESCENDING)
{
stable_sort(_indexes, _indexes + _size, [&_data](long long _i1, long long _i2) {return _data[_i1] > _data[_i2];});
}
#pragma _NEC ivdep
#pragma omp parallel for
for(long long i = 0; i < _size; i++)
{
work_buffer[i] = _data[_indexes[i]];
}
#pragma _NEC ivdep
#pragma omp parallel for
for(long long i = 0; i < _size; i++)
{
_data[i] = work_buffer[i];
}
}
else
{
if(_sort_order == SORT_ASCENDING)
stable_sort(_data, _data + _size);
else if(_sort_order == SORT_DESCENDING)
stable_sort(_data, _data + _size, greater<int>());
}
};
#ifdef __USE_GPU__
static void thrust_inner_sort(int *_data, vgl_sort_indexes *_indexes, long long _size, SortOrder _sort_order)
{
thrust::stable_sort_by_key(thrust::host, _data, _data + _size, _indexes);
};
#endif
public:
static void sort(int *_data, vgl_sort_indexes *_indexes, long long _size, SortOrder _sort_order)
{
#ifdef __USE_NEC_SX_AURORA__
#ifdef __USE_ASL__
asl_inner_sort(_data, _indexes, _size, _sort_order);
#else
std_inner_sort(_data, _indexes, _size, _sort_order);
#endif
#endif
#ifdef __USE_GPU__
/*Timer tm;
tm.start();
thrust_inner_sort(_data, _indexes, _size, _sort_order);
tm.end();
cout << "thrust_sort_time: " << tm.get_time_in_ms() << " ms" << endl;*/
std_inner_sort(_data, _indexes, _size, _sort_order);
#endif
#ifdef __USE_MULTICORE__
std_inner_sort(_data, _indexes, _size, _sort_order);
#endif
};
};
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
|
test.c |
#include <stdio.h>
#include <float.h>
#include <stdlib.h>
#include <math.h>
#include <omp.h>
#include "../utilities/check.h"
#include "../utilities/utilities.h"
#define TRIALS (1)
#define N (957*3)
#define ZERO(X) ZERO_ARRAY(N, X)
#define INIT() { \
INIT_LOOP(N, { \
Ad[i] = 1 << 16; \
Bd[i] = i << 16; \
Cd[i] = -(i << 16); \
Dd[i] = (2*i+1) << 16; \
Ed[i] = ((i % 2 == 0 ? 0x1 : 0x0) << 16) | \
((i % 3 == 0 ? 0x2 : 0x0) << 16); \
}) \
}
#define INIT1 (1)
#define INIT2 (3)
#define INIT3 (5)
#define INIT4 (7)
#define INITc5 (9)
#define INITs5 (9 << 4)
#define INITi5 (9 << 16)
#define INITll5 (9ll << 32)
#define INITf5 (9 << 8)
#define INITd5 (9 << 16)
#define INITc6 (0xf)
#define INITs6 (0xff << 4)
#define INITi6 (0xff << 16)
#define INITll6 (0xffll << 32)
#define INITf6 (0xff << 8)
#define INITd6 (0xff << 16)
#define INIT7 (0)
#define INIT8 (0)
#define INIT9 (1)
#define INIT10 (0)
#define EXPECTED_RESULT ( \
INIT1 + INIT2 + \
(N << 16) + (N << 16) + \
/* + (2*(N-1)+1) - (N-1) */ + \
(INITd5*2*2*2) + \
1 + 1 \
)
#define REDUCTION_CLAUSES reduction(+:Rd1) reduction(-:Rd2) reduction(*:Rd5) \
reduction(&&:Rd9) reduction(||:Rd10)
//reduction(max:Ri3) reduction(min:Ri4)
#define REDUCTION_MAP map(tofrom: Rd1, Rd2, Rd5, Rd9, Rd10)
#define REDUCTION_INIT() { \
Rd1 = INIT1; Rd2 = INIT2; \
Rd3 = INIT3; Rd4 = INIT4; \
Rd5 = INITd5; Rd6 = INITd6; \
Rd7 = INIT7; Rd8 = INIT8; \
Rd9 = INIT9; Rd10 = INIT10; \
}
#define REDUCTION_BODY() \
Rd1 += Ad[i] + (Bd[i] + Cd[i]); \
Rd2 += Ad[i] + (Bd[i] + Cd[i]); \
/*Rd3 = Dd[i] > Rd3 ? Dd[i] : Rd3; \
Rd4 = Cd[i] < Rd4 ? Cd[i] : Rd4; \*/ \
Rd5 *= i % 1000 == 0 ? 2 : 1; \
Rd9 = Rd9 && Ad[i] > 0; \
Rd10 = Rd10 || Ad[i] > 0;
#define REDUCTION_LOOP() \
for (int i = 0; i < N; i++) { \
REDUCTION_BODY(); \
}
#define REDUCTION_FINAL() { \
OUT[0] += (long long) (Rd1 + Rd2 /*+ Rd3 + Rd4 */ + Rd5 + Rd9 + Rd10); \
}
int main(void) {
check_offloading();
double Ad[N], Bd[N], Cd[N], Dd[N], Ed[N];
double Rd1, Rd2, Rd3, Rd4, Rd5, Rd6, Rd7, Rd8, Rd9, Rd10;
long long OUT[1];
long long EXPECTED[1];
EXPECTED[0] = EXPECTED_RESULT;
int cpuExec = 0;
#pragma omp target map(tofrom: cpuExec)
{
cpuExec = omp_is_initial_device();
}
int gpu_threads = 512;
int cpu_threads = 32;
int max_threads = cpuExec ? cpu_threads : gpu_threads;
INIT();
if (cpuExec) {
// Certain tests in this testcase fails on the host. A bug report has
// been filed: https://puna0.watson.ibm.com/T143
// Disabling this test on the host for now.
DUMP_SUCCESS(3153);
return 0;
}
//
// Test: reduction on teams.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams num_teams(tms) REDUCTION_CLAUSES")
{
int tid = omp_get_team_num();
int th = omp_get_num_teams();
for (int i = tid; i < N; i+= th) {
REDUCTION_BODY();
}
}
},
{
REDUCTION_FINAL();
}, VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
//
// Test: reduction on teams with nested parallel.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams num_teams(tms) REDUCTION_CLAUSES")
{
int tid = omp_get_team_num();
int th = omp_get_num_teams();
_Pragma("omp parallel for REDUCTION_CLAUSES")
for (int i = tid; i < N; i+= th) {
REDUCTION_BODY();
}
}
},
{
REDUCTION_FINAL();
}, VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
//
// Test: reduction on target teams.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
OUT[0] = 0;
TESTD2("omp target teams num_teams(tms) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
{
{
int tid = omp_get_team_num();
int th = omp_get_num_teams();
for (int i = tid; i < N; i+= th) {
REDUCTION_BODY();
}
}
},
{
REDUCTION_FINAL();
}, VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
//
// Test: reduction on teams with nested parallel.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
OUT[0] = 0;
TESTD2("omp target teams num_teams(tms) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
{
{
int tid = omp_get_team_num();
int th = omp_get_num_teams();
_Pragma("omp parallel for REDUCTION_CLAUSES")
for (int i = tid; i < N; i+= th) {
REDUCTION_BODY();
}
}
},
{
REDUCTION_FINAL();
}, VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
//
// Test: reduction on target parallel with nested parallel.
//
OUT[0] = 0;
TESTD2("omp target parallel num_threads(30) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
{
{
int tid = omp_get_thread_num();
int th = omp_get_num_threads();
_Pragma("omp simd REDUCTION_CLAUSES")
for (int i = tid; i < N; i+= th) {
REDUCTION_BODY();
}
}
},
{
REDUCTION_FINAL();
}, VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
//
// Test: reduction on target teams distribute parallel for.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for num_teams(tms) thread_limit(ths) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on target teams distribute parallel for with schedule static nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for num_teams(tms) thread_limit(ths) schedule(static) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on target teams distribute parallel for with schedule static chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for num_teams(tms) thread_limit(ths) schedule(static,sch) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for with schedule dynamic nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for num_teams(tms) thread_limit(ths) schedule(dynamic) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on target teams distribute parallel for with schedule dynamic chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for num_teams(tms) thread_limit(ths) schedule(dynamic,sch) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for with dist_schedule static nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on target teams distribute parallel for with dist_schedule static nochunk, schedule static nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static) schedule(static) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on target teams distribute parallel for with dist_schedule static nochunk, schedule static chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static) schedule(static,sch) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for with dist_schedule static chunk, schedule static nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(static) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for with dist_schedule static chunk, schedule static chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(static,sch) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for with dist_schedule static chunk, schedule dynamic nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(dynamic) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for with dist_schedule static chunk,schedule dynamic chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(dynamic,sch) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for with dist_schedule static chunk, schedule guided nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(guided) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for with dist_schedule static chunk, schedule guided chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(guided,sch) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for with dist_schedule static chunk, schedule auto.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(dynamic) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for with dist_schedule static chunk, schedule runtime.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(runtime) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for num_teams(tms) thread_limit(ths) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on teams distribute parallel for with schedule static nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for num_teams(tms) thread_limit(ths) schedule(static) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on teams distribute parallel for with schedule static chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for num_teams(tms) thread_limit(ths) schedule(static,sch) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for with schedule dynamic nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for num_teams(tms) thread_limit(ths) schedule(dynamic) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on teams distribute parallel for with schedule dynamic chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for num_teams(tms) thread_limit(ths) schedule(dynamic,sch) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for with dist_schedule static nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on teams distribute parallel for with dist_schedule static nochunk, schedule static nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static) schedule(static) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on teams distribute parallel for with dist_schedule static nochunk, schedule static chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static) schedule(static,sch) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for with dist_schedule static chunk, schedule static nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(static) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for with dist_schedule static chunk, schedule static chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(static,sch) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for with dist_schedule static chunk, schedule dynamic nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(dynamic) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for with dist_schedule static chunk,schedule dynamic chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(dynamic,sch) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for with dist_schedule static chunk, schedule guided nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(guided) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for with dist_schedule static chunk, schedule guided chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(guided,sch) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for with dist_schedule static chunk, schedule auto.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(dynamic) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for with dist_schedule static chunk, schedule runtime.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(runtime) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for simd.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for simd num_teams(tms) thread_limit(ths) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on target teams distribute parallel for simd with schedule static nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for simd num_teams(tms) thread_limit(ths) schedule(static) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on target teams distribute parallel for simd with schedule static chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for simd num_teams(tms) thread_limit(ths) schedule(static,sch) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for simd with schedule dynamic nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for simd num_teams(tms) thread_limit(ths) schedule(dynamic) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on target teams distribute parallel for simd with schedule dynamic chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for simd num_teams(tms) thread_limit(ths) schedule(dynamic,sch) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for simd with dist_schedule static nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on target teams distribute parallel for simd with dist_schedule static nochunk, schedule static nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static) schedule(static) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on target teams distribute parallel for simd with dist_schedule static nochunk, schedule static chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static) schedule(static,sch) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for simd with dist_schedule static chunk, schedule static nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(static) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for simd with dist_schedule static chunk, schedule static chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(static,sch) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for simd with dist_schedule static chunk, schedule dynamic nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(dynamic) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for simd with dist_schedule static chunk,schedule dynamic chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(dynamic,sch) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for simd with dist_schedule static chunk, schedule guided nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(guided) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for simd with dist_schedule static chunk, schedule guided chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(guided,sch) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for simd with dist_schedule static chunk, schedule auto.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(dynamic) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on target teams distribute parallel for simd with dist_schedule static chunk, schedule runtime.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(runtime) REDUCTION_MAP REDUCTION_CLAUSES",
{
REDUCTION_INIT();
},
REDUCTION_LOOP(),
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for simd.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for simd num_teams(tms) thread_limit(ths) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on teams distribute parallel for simd with schedule static nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for simd num_teams(tms) thread_limit(ths) schedule(static) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on teams distribute parallel for simd with schedule static chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for simd num_teams(tms) thread_limit(ths) schedule(static,sch) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for simd with schedule dynamic nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for simd num_teams(tms) thread_limit(ths) schedule(dynamic) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on teams distribute parallel for simd with schedule dynamic chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for simd num_teams(tms) thread_limit(ths) schedule(dynamic,sch) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for simd with dist_schedule static nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on teams distribute parallel for simd with dist_schedule static nochunk, schedule static nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static) schedule(static) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
//
// Test: reduction on teams distribute parallel for simd with dist_schedule static nochunk, schedule static chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static) schedule(static,sch) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for simd with dist_schedule static chunk, schedule static nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(static) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for simd with dist_schedule static chunk, schedule static chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(static,sch) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for simd with dist_schedule static chunk, schedule dynamic nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(dynamic) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for simd with dist_schedule static chunk,schedule dynamic chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(dynamic,sch) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for simd with dist_schedule static chunk, schedule guided nochunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(guided) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for simd with dist_schedule static chunk, schedule guided chunk.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(guided,sch) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for simd with dist_schedule static chunk, schedule auto.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(dynamic) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
//
// Test: reduction on teams distribute parallel for simd with dist_schedule static chunk, schedule runtime.
//
for (int tms = 1 ; tms <= 512 ; tms *= 7) {
for (int ths = 1 ; ths <= 1024 ; ths *= 9) {
for(int sch = 1 ; sch <= N ; sch *= 9) {
OUT[0] = 0;
TESTD2("omp target REDUCTION_MAP",
{
REDUCTION_INIT();
},
{
_Pragma("omp teams distribute parallel for simd num_teams(tms) thread_limit(ths) dist_schedule(static,sch) schedule(runtime) REDUCTION_CLAUSES")
REDUCTION_LOOP()
},
{
REDUCTION_FINAL();
},
VERIFY(0, 1, OUT[i], (trial+1) * EXPECTED[i]));
}
}
}
return 0;
}
|
GB_binop__lt_int16.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__lt_int16)
// A.*B function (eWiseMult): GB (_AemultB_08__lt_int16)
// A.*B function (eWiseMult): GB (_AemultB_02__lt_int16)
// A.*B function (eWiseMult): GB (_AemultB_04__lt_int16)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__lt_int16)
// A*D function (colscale): GB (_AxD__lt_int16)
// D*A function (rowscale): GB (_DxB__lt_int16)
// C+=B function (dense accum): GB (_Cdense_accumB__lt_int16)
// C+=b function (dense accum): GB (_Cdense_accumb__lt_int16)
// C+=A+B function (dense ewise3): GB ((none))
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__lt_int16)
// C=scalar+B GB (_bind1st__lt_int16)
// C=scalar+B' GB (_bind1st_tran__lt_int16)
// C=A+scalar GB (_bind2nd__lt_int16)
// C=A'+scalar GB (_bind2nd_tran__lt_int16)
// C type: bool
// A type: int16_t
// A pattern? 0
// B type: int16_t
// B pattern? 0
// BinaryOp: cij = (aij < bij)
#define GB_ATYPE \
int16_t
#define GB_BTYPE \
int16_t
#define GB_CTYPE \
bool
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
0
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
0
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA,A_iso) \
int16_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) \
int16_t bij = GBX (Bx, pB, B_iso)
// true if values of B are not used
#define GB_B_IS_PATTERN \
0 \
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
bool t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA,A_iso) \
cij = GBX (Ax, pA, A_iso)
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB,B_iso) \
cij = GBX (Bx, pB, B_iso)
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z,x,y,i,j) \
z = (x < y) ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
0
// op is second
#define GB_OP_IS_SECOND \
0
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_LT || GxB_NO_INT16 || GxB_NO_LT_INT16)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
#if 0
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
#endif
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
void GB (_Cdense_ewise3_noaccum__lt_int16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_noaccum_template.c"
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumB__lt_int16)
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *B_ek_slicing, const int B_ntasks, const int B_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if 0
{
#include "GB_dense_subassign_23_template.c"
}
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumb__lt_int16)
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if 0
{
// get the scalar b for C += b, of type int16_t
int16_t bwork = (*((int16_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_AxD__lt_int16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix D,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *restrict Cx = (bool *) C->x ;
#include "GB_AxB_colscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_DxB__lt_int16)
(
GrB_Matrix C,
const GrB_Matrix D,
const GrB_Matrix B,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *restrict Cx = (bool *) C->x ;
#include "GB_AxB_rowscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C=A+B, C<M>=A+B, C<!M>=A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__lt_int16)
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool 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) ;
int16_t alpha_scalar ;
int16_t beta_scalar ;
if (is_eWiseUnion)
{
alpha_scalar = (*((int16_t *) alpha_scalar_in)) ;
beta_scalar = (*((int16_t *) beta_scalar_in )) ;
}
#include "GB_add_template.c"
GB_FREE_WORKSPACE ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, or C<M!>=A.*B where C is sparse/hyper
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_08__lt_int16)
(
GrB_Matrix C,
const int C_sparsity,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_08_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<#> = A.*B when A is sparse/hyper and B is bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_02__lt_int16)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool flipxy,
const int64_t *restrict Cp_kfirst,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if GB_BINOP_FLIP
// The operator is not commutative, and does not have a flipped
// variant. For example z=atan2(y,x).
if (flipxy)
{
// use fmult(y,x)
#undef GB_FLIPPED
#define GB_FLIPPED 1
#include "GB_emult_02_template.c"
}
else
{
// use fmult(x,y)
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
}
#else
// No need to handle the flip: the operator is either commutative, or
// has been handled by changing z=div(y,x) to z=rdiv(x,y) for example.
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<M> = A.*B, M sparse/hyper, A and B bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_04__lt_int16)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict Cp_kfirst,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_04_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, C<!M>=A.*B where C is bitmap
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_bitmap__lt_int16)
(
GrB_Matrix C,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_bitmap_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB (_bind1st__lt_int16)
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *restrict Bb,
int64_t bnz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
bool *Cx = (bool *) Cx_output ;
int16_t x = (*((int16_t *) x_input)) ;
int16_t *Bx = (int16_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < bnz ; p++)
{
if (!GBB (Bb, p)) continue ;
int16_t bij = GBX (Bx, p, false) ;
Cx [p] = (x < bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__lt_int16)
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *restrict Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
bool *Cx = (bool *) Cx_output ;
int16_t *Ax = (int16_t *) Ax_input ;
int16_t y = (*((int16_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
int16_t aij = 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) \
{ \
int16_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = (x < aij) ; \
}
GrB_Info GB (_bind1st_tran__lt_int16)
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
int16_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int16_t x = (*((const int16_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
int16_t
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
int16_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = (aij < y) ; \
}
GrB_Info GB (_bind2nd_tran__lt_int16)
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int16_t y = (*((const int16_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
ResultHandler.h | /**
* Copyright (c) Facebook, Inc. and its affiliates.
*
* This source code is licensed under the MIT license found in the
* LICENSE file in the root directory of this source tree.
*/
/*
* Structures that collect search results from distance computations
*/
#pragma once
#include <faiss/impl/AuxIndexStructures.h>
#include <faiss/utils/Heap.h>
#include <faiss/utils/partitioning.h>
namespace faiss {
/*****************************************************************
* Heap based result handler
*****************************************************************/
template <class C>
struct HeapResultHandler {
using T = typename C::T;
using TI = typename C::TI;
int nq;
T* heap_dis_tab;
TI* heap_ids_tab;
bool own_fields;
int64_t k; // number of results to keep
HeapResultHandler() {}
HeapResultHandler(size_t nq, T* heap_dis_tab, TI* heap_ids_tab, size_t k)
: nq(nq),
heap_dis_tab(heap_dis_tab),
heap_ids_tab(heap_ids_tab),
k(k),
own_fields(false) {}
~HeapResultHandler() {
if (own_fields) {
free(heap_dis_tab);
free(heap_ids_tab);
}
}
HeapResultHandler* clone_n(int n, size_t block_x) {
HeapResultHandler* ress = new HeapResultHandler[n];
T* global_heap_dis_tab = (T*)malloc(block_x * k * n * sizeof(T));
TI* global_heap_ids_tab = (TI*)malloc(block_x * k * n * sizeof(TI));
for (int i = 0; i < n; i++) {
ress[i].nq = block_x;
ress[i].k = k;
ress[i].heap_dis_tab = global_heap_dis_tab + block_x * k * i;
ress[i].heap_ids_tab = global_heap_ids_tab + block_x * k * i;
ress[i].own_fields = (i == 0);
}
return ress;
}
/******************************************************
* API for 1 result at a time (each SingleResultHandler is
* called from 1 thread)
*/
struct SingleResultHandler {
HeapResultHandler& hr;
size_t k;
T* heap_dis;
TI* heap_ids;
T thresh;
SingleResultHandler(HeapResultHandler& hr) : hr(hr), k(hr.k) {}
/// begin results for query # i
void begin(size_t i) {
heap_dis = hr.heap_dis_tab + i * k;
heap_ids = hr.heap_ids_tab + i * k;
heap_heapify<C>(k, heap_dis, heap_ids);
thresh = heap_dis[0];
}
/// add one result for query i
void add_result(T dis, TI idx) {
if (C::cmp(heap_dis[0], dis)) {
heap_replace_top<C>(k, heap_dis, heap_ids, dis, idx);
thresh = heap_dis[0];
}
}
/// series of results for query i is done
void end() {
heap_reorder<C>(k, heap_dis, heap_ids);
}
};
/******************************************************
* API for multiple results (called from 1 thread)
*/
size_t i0, i1;
/// begin
void begin_multiple(size_t i0, size_t i1) {
this->i0 = i0;
this->i1 = i1;
for (size_t i = i0; i < i1; i++) {
heap_heapify<C>(k, heap_dis_tab + i * k, heap_ids_tab + i * k);
}
}
/// add results for query i0..i1 and j0..j1
void add_results(size_t j0, size_t j1, const T* dis_tab,
BitsetView bitset = nullptr) {
#pragma omp parallel for
for (int64_t i = i0; i < i1; i++) {
T* heap_dis = heap_dis_tab + i * k;
TI* heap_ids = heap_ids_tab + i * k;
T thresh = heap_dis[0];
const T* dis_tab_i = dis_tab + (j1 - j0) * (i - i0) - j0;
for (size_t j = j0; j < j1; j++) {
if (!bitset || !bitset.test(j)) {
T dis = dis_tab_i[j];
// T dis = *dis_tab++;
if (C::cmp(thresh, dis)) {
heap_replace_top<C>(k, heap_dis, heap_ids, dis, j);
thresh = heap_dis[0];
}
}
}
}
}
void add_single_result(size_t i, T dis, TI idx) {
T * heap_dis = heap_dis_tab + i * k;
TI * heap_ids = heap_ids_tab + i * k;
if (C::cmp(heap_dis[0], dis)) {
heap_replace_top<C>(k, heap_dis, heap_ids, dis, idx);
}
}
void merge(size_t i, HeapResultHandler &rh) {
const size_t ki = i * k, uj = ki + k;
for (size_t j = ki; j < uj; ++j) {
add_single_result(i, rh.heap_dis_tab[j], rh.heap_ids_tab[j]);
}
}
/// series of results for queries i0..i1 is done
void end_multiple() {
// maybe parallel for
for (size_t i = i0; i < i1; i++) {
heap_reorder<C>(k, heap_dis_tab + i * k, heap_ids_tab + i * k);
}
}
void copy_from(HeapResultHandler &res, size_t x_from, size_t size) {
memcpy(heap_dis_tab + x_from * k, res.heap_dis_tab, size * k * sizeof(T));
memcpy(heap_ids_tab + x_from * k, res.heap_ids_tab, size * k * sizeof(TI));
}
};
/*****************************************************************
* Reservoir result handler
*
* A reservoir is a result array of size capacity > n (number of requested
* results) all results below a threshold are stored in an arbitrary order. When
* the capacity is reached, a new threshold is chosen by partitionning the
* distance array.
*****************************************************************/
/// Reservoir for a single query
template <class C>
struct ReservoirTopN {
using T = typename C::T;
using TI = typename C::TI;
T* vals;
TI* ids;
size_t i; // number of stored elements
size_t n; // number of requested elements
size_t capacity; // size of storage
T threshold; // current threshold
ReservoirTopN() {}
ReservoirTopN(size_t n, size_t capacity, T* vals, TI* ids)
: vals(vals), ids(ids), i(0), n(n), capacity(capacity) {
assert(n < capacity);
threshold = C::neutral();
}
void add(T val, TI id) {
if (C::cmp(threshold, val)) {
if (i == capacity) {
shrink_fuzzy();
}
vals[i] = val;
ids[i] = id;
i++;
}
}
// reduce storage from capacity to anything
// between n and (capacity + n) / 2
void shrink_fuzzy() {
assert(i == capacity);
threshold = partition_fuzzy<C>(
vals, ids, capacity, n, (capacity + n) / 2, &i);
}
void to_result(T* heap_dis, TI* heap_ids) const {
for (int j = 0; j < std::min(i, n); j++) {
heap_push<C>(j + 1, heap_dis, heap_ids, vals[j], ids[j]);
}
if (i < n) {
heap_reorder<C>(i, heap_dis, heap_ids);
// add empty results
heap_heapify<C>(n - i, heap_dis + i, heap_ids + i);
} else {
// add remaining elements
heap_addn<C>(n, heap_dis, heap_ids, vals + n, ids + n, i - n);
heap_reorder<C>(n, heap_dis, heap_ids);
}
}
};
template <class C>
struct ReservoirResultHandler {
using T = typename C::T;
using TI = typename C::TI;
int nq;
T* heap_dis_tab;
TI* heap_ids_tab;
int64_t k; // number of results to keep
size_t capacity; // capacity of the reservoirs
bool own_fields;
ReservoirResultHandler(
size_t nq,
T* heap_dis_tab,
TI* heap_ids_tab,
size_t k)
: nq(nq),
heap_dis_tab(heap_dis_tab),
heap_ids_tab(heap_ids_tab),
k(k),
own_fields(false) {
// double then round up to multiple of 16 (for SIMD alignment)
capacity = (2 * k + 15) & ~15;
}
ReservoirResultHandler() {}
~ReservoirResultHandler() {
if (own_fields) {
free(heap_dis_tab);
free(heap_ids_tab);
}
}
ReservoirResultHandler *clone_n(int n, size_t block_x) {
ReservoirResultHandler *ress = new ReservoirResultHandler[n];
T* global_heap_dis_tab = (T*)malloc(block_x * k * n * sizeof(T));
TI* global_heap_ids_tab = (TI*)malloc(block_x * k * n * sizeof(TI));
for (int i = 0; i < n; i++) {
ress[i].nq = block_x;
ress[i].k = k;
ress[i].heap_dis_tab = global_heap_dis_tab + block_x * k * i;
ress[i].heap_ids_tab = global_heap_ids_tab + block_x * k * i;
ress[i].own_fields = (i == 0);
ress[i].capacity = (2 * k + 15) & ~15;
}
return ress;
}
/******************************************************
* API for 1 result at a time (each SingleResultHandler is
* called from 1 thread)
*/
struct SingleResultHandler {
ReservoirResultHandler& hr;
std::vector<T> reservoir_dis;
std::vector<TI> reservoir_ids;
ReservoirTopN<C> res1;
SingleResultHandler(ReservoirResultHandler& hr)
: hr(hr),
reservoir_dis(hr.capacity),
reservoir_ids(hr.capacity) {}
size_t i;
/// begin results for query # i
void begin(size_t i) {
res1 = ReservoirTopN<C>(
hr.k,
hr.capacity,
reservoir_dis.data(),
reservoir_ids.data());
this->i = i;
}
/// add one result for query i
void add_result(T dis, TI idx) {
res1.add(dis, idx);
}
/// series of results for query i is done
void end() {
T* heap_dis = hr.heap_dis_tab + i * hr.k;
TI* heap_ids = hr.heap_ids_tab + i * hr.k;
res1.to_result(heap_dis, heap_ids);
}
};
/******************************************************
* API for multiple results (called from 1 thread)
*/
size_t i0, i1;
std::vector<T> reservoir_dis;
std::vector<TI> reservoir_ids;
std::vector<ReservoirTopN<C>> reservoirs;
/// begin
void begin_multiple(size_t i0, size_t i1) {
this->i0 = i0;
this->i1 = i1;
reservoir_dis.resize((i1 - i0) * capacity);
reservoir_ids.resize((i1 - i0) * capacity);
reservoirs.clear();
for (size_t i = i0; i < i1; i++) {
reservoirs.emplace_back(
k,
capacity,
reservoir_dis.data() + (i - i0) * capacity,
reservoir_ids.data() + (i - i0) * capacity);
}
}
/// add results for query i0..i1 and j0..j1
void add_results(size_t j0, size_t j1, const T* dis_tab,
BitsetView bitset = nullptr) {
// maybe parallel for
#pragma omp parallel for
for (int64_t i = i0; i < i1; i++) {
ReservoirTopN<C>& reservoir = reservoirs[i - i0];
const T* dis_tab_i = dis_tab + (j1 - j0) * (i - i0) - j0;
for (size_t j = j0; j < j1; j++) {
if (!bitset || !bitset.test(j)) {
T dis = dis_tab_i[j];
reservoir.add(dis, j);
}
}
}
}
void add_single_result(size_t i, T dis, TI idx) {
reservoirs[i - i0].add(dis, idx);
}
void merge(size_t i, ReservoirResultHandler &rh) {
const size_t ii = i - rh.i0;
const T* dis = rh.reservoir_dis.data() + ii * rh.capacity;
const TI* ids = rh.reservoir_ids.data() + ii * rh.capacity;
for (int j = 0; j < rh.reservoirs[ii].i; j++) {
add_single_result(i, dis[j], ids[j]);
}
}
/// series of results for queries i0..i1 is done
void end_multiple() {
// maybe parallel for
for (size_t i = i0; i < i1; i++) {
reservoirs[i - i0].to_result(
heap_dis_tab + i * k, heap_ids_tab + i * k);
}
}
void copy_from(ReservoirResultHandler &res, size_t x_from, size_t size) {
memcpy(heap_dis_tab + x_from * k, res.heap_dis_tab, size * k * sizeof(T));
memcpy(heap_ids_tab + x_from * k, res.heap_ids_tab, size * k * sizeof(TI));
}
};
/*****************************************************************
* Result handler for range searches
*****************************************************************/
template <class C>
struct RangeSearchResultHandler {
using T = typename C::T;
using TI = typename C::TI;
RangeSearchResult* res;
float radius;
RangeSearchResultHandler(RangeSearchResult* res, float radius)
: res(res), radius(radius) {}
/******************************************************
* API for 1 result at a time (each SingleResultHandler is
* called from 1 thread)
******************************************************/
struct SingleResultHandler {
// almost the same interface as RangeSearchResultHandler
RangeSearchPartialResult pres;
float radius;
RangeQueryResult* qr = nullptr;
SingleResultHandler(RangeSearchResultHandler& rh)
: pres(rh.res), radius(rh.radius) {}
/// begin results for query # i
void begin(size_t i) {
qr = &pres.new_result(i);
}
/// add one result for query i
void add_result(T dis, TI idx) {
if (C::cmp(radius, dis)) {
qr->add(dis, idx);
}
}
/// series of results for query i is done
void end() {}
~SingleResultHandler() {
pres.finalize();
}
};
/******************************************************
* API for multiple results (called from 1 thread)
******************************************************/
size_t i0, i1;
std::vector<RangeSearchPartialResult*> partial_results;
std::vector<size_t> j0s;
int pr = 0;
/// begin
void begin_multiple(size_t i0, size_t i1) {
this->i0 = i0;
this->i1 = i1;
}
/// add results for query i0..i1 and j0..j1
void add_results(size_t j0, size_t j1, const T* dis_tab) {
RangeSearchPartialResult* pres;
// there is one RangeSearchPartialResult structure per j0
// (= block of columns of the large distance matrix)
// it is a bit tricky to find the poper PartialResult structure
// because the inner loop is on db not on queries.
if (pr < j0s.size() && j0 == j0s[pr]) {
pres = partial_results[pr];
pr++;
} else if (j0 == 0 && j0s.size() > 0) {
pr = 0;
pres = partial_results[pr];
pr++;
} else { // did not find this j0
pres = new RangeSearchPartialResult(res);
partial_results.push_back(pres);
j0s.push_back(j0);
pr = partial_results.size();
}
for (size_t i = i0; i < i1; i++) {
const float* ip_line = dis_tab + (i - i0) * (j1 - j0);
RangeQueryResult& qres = pres->new_result(i);
for (size_t j = j0; j < j1; j++) {
float dis = *ip_line++;
if (C::cmp(radius, dis)) {
qres.add(dis, j);
}
}
}
}
void end_multiple() {}
~RangeSearchResultHandler() {
if (partial_results.size() > 0) {
RangeSearchPartialResult::merge(partial_results);
}
}
};
} // namespace faiss
|
GB_binop__isge_uint32.c | //------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated2/ folder, do not edit it
// (it is auto-generated from Generator/*).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_emult.h"
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB (_AaddB__isge_uint32)
// A.*B function (eWiseMult): GB (_AemultB_01__isge_uint32)
// A.*B function (eWiseMult): GB (_AemultB_02__isge_uint32)
// A.*B function (eWiseMult): GB (_AemultB_03__isge_uint32)
// A.*B function (eWiseMult): GB (_AemultB_bitmap__isge_uint32)
// A*D function (colscale): GB (_AxD__isge_uint32)
// D*A function (rowscale): GB (_DxB__isge_uint32)
// C+=B function (dense accum): GB (_Cdense_accumB__isge_uint32)
// C+=b function (dense accum): GB (_Cdense_accumb__isge_uint32)
// C+=A+B function (dense ewise3): GB ((none))
// C=A+B function (dense ewise3): GB (_Cdense_ewise3_noaccum__isge_uint32)
// C=scalar+B GB (_bind1st__isge_uint32)
// C=scalar+B' GB (_bind1st_tran__isge_uint32)
// C=A+scalar GB (_bind2nd__isge_uint32)
// C=A'+scalar GB (_bind2nd_tran__isge_uint32)
// C type: uint32_t
// A type: uint32_t
// B,b type: uint32_t
// BinaryOp: cij = (aij >= bij)
#define GB_ATYPE \
uint32_t
#define GB_BTYPE \
uint32_t
#define GB_CTYPE \
uint32_t
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
1
// true if the types of C and A are identical
#define GB_CTYPE_IS_ATYPE \
1
// true if the types of C and B are identical
#define GB_CTYPE_IS_BTYPE \
1
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA,A_iso) \
uint32_t aij = GBX (Ax, pA, A_iso)
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB,B_iso) \
uint32_t bij = GBX (Bx, pB, B_iso)
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
uint32_t t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA,A_iso) \
cij = GBX (Ax, pA, A_iso)
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB,B_iso) \
cij = GBX (Bx, pB, B_iso)
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z,x,y,i,j) \
z = (x >= y) ;
// true if the binop must be flipped
#define GB_BINOP_FLIP \
0
// op is second
#define GB_OP_IS_SECOND \
0
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_ISGE || GxB_NO_UINT32 || GxB_NO_ISGE_UINT32)
//------------------------------------------------------------------------------
// C += A+B, all 3 matrices dense
//------------------------------------------------------------------------------
#if 0
// The op must be MIN, MAX, PLUS, MINUS, RMINUS, TIMES, DIV, or RDIV.
void GB ((none))
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#include "GB_dense_ewise3_accum_template.c"
}
#endif
//------------------------------------------------------------------------------
// C = A+B, all 3 matrices dense
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_ewise3_noaccum__isge_uint32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GrB_Matrix B,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_dense_ewise3_noaccum_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += B, accumulate a sparse matrix into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumB__isge_uint32)
(
GrB_Matrix C,
const GrB_Matrix B,
const int64_t *B_ek_slicing, const int B_ntasks, const int B_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
#include "GB_dense_subassign_23_template.c"
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C += b, accumulate a scalar into a dense matrix
//------------------------------------------------------------------------------
GrB_Info GB (_Cdense_accumb__isge_uint32)
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
// get the scalar b for C += b, of type uint32_t
uint32_t bwork = (*((uint32_t *) p_bwork)) ;
#include "GB_dense_subassign_22_template.c"
return (GrB_SUCCESS) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = A*D, column scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_AxD__isge_uint32)
(
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
uint32_t *restrict Cx = (uint32_t *) C->x ;
#include "GB_AxB_colscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
GrB_Info GB (_DxB__isge_uint32)
(
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
uint32_t *restrict Cx = (uint32_t *) C->x ;
#include "GB_AxB_rowscale_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseAdd: C = A+B or C<M> = A+B
//------------------------------------------------------------------------------
GrB_Info GB (_AaddB__isge_uint32)
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool Ch_is_Mh,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
GB_WERK_DECLARE (M_ek_slicing, int64_t) ;
GB_WERK_DECLARE (A_ek_slicing, int64_t) ;
GB_WERK_DECLARE (B_ek_slicing, int64_t) ;
#include "GB_add_template.c"
GB_FREE_WORK ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C = A.*B or C<M> = A.*B
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_01__isge_uint32)
(
GrB_Matrix C,
const int C_sparsity,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict C_to_M,
const int64_t *restrict C_to_A,
const int64_t *restrict C_to_B,
const GB_task_struct *restrict TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_01_meta.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<#> = A.*B when A is sparse/hyper and B is bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_02__isge_uint32)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool flipxy,
const int64_t *restrict Cp_kfirst,
const int64_t *A_ek_slicing, const int A_ntasks, const int A_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#if GB_BINOP_FLIP
// The operator is not commutative, and does not have a flipped
// variant. For example z=atan2(y,x).
if (flipxy)
{
// use fmult(y,x)
#undef GB_FLIPPED
#define GB_FLIPPED 1
#include "GB_emult_02_template.c"
}
else
{
// use fmult(x,y)
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
}
#else
// No need to handle the flip: the operator is either commutative, or
// has been handled by changing z=div(y,x) to z=rdiv(x,y) for example.
#undef GB_FLIPPED
#define GB_FLIPPED 0
#include "GB_emult_02_template.c"
#endif
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C<M> = A.*B, M sparse/hyper, A and B bitmap/full
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_03__isge_uint32)
(
GrB_Matrix C,
const GrB_Matrix M,
const bool Mask_struct,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *restrict Cp_kfirst,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_emult_03_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C=A.*B, C<M>=A.*B, C<!M>=A.*B where C is bitmap
//------------------------------------------------------------------------------
GrB_Info GB (_AemultB_bitmap__isge_uint32)
(
GrB_Matrix C,
const int ewise_method,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *M_ek_slicing, const int M_ntasks, const int M_nthreads,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_bitmap_emult_template.c"
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB (_bind1st__isge_uint32)
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *restrict Bb,
int64_t bnz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint32_t *Cx = (uint32_t *) Cx_output ;
uint32_t x = (*((uint32_t *) x_input)) ;
uint32_t *Bx = (uint32_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < bnz ; p++)
{
if (!GBB (Bb, p)) continue ;
uint32_t bij = GBX (Bx, p, false) ;
Cx [p] = (x >= bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB (_bind2nd__isge_uint32)
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *restrict Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
uint32_t *Cx = (uint32_t *) Cx_output ;
uint32_t *Ax = (uint32_t *) Ax_input ;
uint32_t y = (*((uint32_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
uint32_t aij = GBX (Ax, p, false) ;
Cx [p] = (aij >= 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) \
{ \
uint32_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = (x >= aij) ; \
}
GrB_Info GB (_bind1st_tran__isge_uint32)
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
uint32_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint32_t x = (*((const uint32_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
uint32_t
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
uint32_t aij = GBX (Ax, pA, false) ; \
Cx [pC] = (aij >= y) ; \
}
GrB_Info GB (_bind2nd_tran__isge_uint32)
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint32_t y = (*((const uint32_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
GB_unop__expm1_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__expm1_fp32_fp32
// op(A') function: GB_unop_tran__expm1_fp32_fp32
// C type: float
// A type: float
// cast: float cij = aij
// unaryop: cij = expm1f (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 = expm1f (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] = expm1f (z) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_EXPM1 || GxB_NO_FP32)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop_apply__expm1_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] = expm1f (z) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop_tran__expm1_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
|
GB_unop__lnot_int16_int16.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary 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_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__lnot_int16_int16)
// op(A') function: GB (_unop_tran__lnot_int16_int16)
// C type: int16_t
// A type: int16_t
// cast: int16_t cij = aij
// unaryop: cij = !(aij != 0)
#define GB_ATYPE \
int16_t
#define GB_CTYPE \
int16_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
int16_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = !(x != 0) ;
// casting
#define GB_CAST(z, aij) \
int16_t z = aij ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
int16_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
int16_t z = aij ; \
Cx [pC] = !(z != 0) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_LNOT || GxB_NO_INT16)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_apply__lnot_int16_int16)
(
int16_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 ;
if (Ab == NULL)
{
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
int16_t aij = Ax [p] ;
int16_t z = aij ;
Cx [p] = !(z != 0) ;
}
}
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] ;
int16_t z = aij ;
Cx [p] = !(z != 0) ;
}
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_tran__lnot_int16_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
|
teams.c | #include <stdlib.h>
#include <assert.h>
#include <omp.h>
int main()
{
int res = 0, n = 10;
#pragma omp teams num_teams(n) reduction(+:res)
{
res = omp_get_team_num();
if (omp_get_team_num() == 0)
n = omp_get_num_teams();
}
Assert (res == (n*(n-1))/2); // Sum of first n-1 natural numbers
}
|
omp_task_red_taskloop.c | // RUN: %libomp-compile-and-run
// Parsing error until gcc8:
// UNSUPPORTED: gcc-4, gcc-5, gcc-6, gcc-7, gcc-8
// Parsing error until clang11:
// UNSUPPORTED: clang-10, clang-9, clang-8, clang-7
// Missing GOMP_taskgroup_reduction_(un)register in LLVM/OpenMP
// Should be removed once the functions are implemented
// XFAIL: gcc-9, gcc-10
// UNSUPPORTED: icc-19
// REQUIRES: !abt
#include <stdio.h>
#include <omp.h>
int r;
int work(int k, int l)
{
return k + l + 1;
}
void bar(int i) {
#pragma omp taskgroup task_reduction(+:r)
{ int th_gen = omp_get_thread_num();
#pragma omp task in_reduction(+:r) firstprivate(i, th_gen)
{
r += work(i, 0);
printf("executing task (%d, 0), th %d (gen by th %d)\n", i, omp_get_thread_num(), th_gen);
}
#pragma omp task in_reduction(+:r) firstprivate(i, th_gen)
{
r += work(i, 1);
printf("executing task (%d, 1), th %d (gen by th %d)\n", i, omp_get_thread_num(), th_gen);
}
}
}
int foo() {
int i;
int th_gen = omp_get_thread_num();
#pragma omp taskgroup task_reduction(+:r)
{
bar(0);
}
printf("th %d passed bar0\n", th_gen);
#pragma omp taskloop reduction(+:r) firstprivate(th_gen)
for (i = 1; i < 4; ++i) {
bar(i);
printf("th %d (gen by th %d) passed bar%d in taskloop\n", omp_get_thread_num(), th_gen, i);
#pragma omp task in_reduction(+:r)
r += i;
}
return 0;
}
// res = 2*((1+2)+(2+3)+(3+4)+(4+5)+1+2+3) = 60
#define res 60
int main()
{
r = 0;
#pragma omp parallel num_threads(2)
foo();
if (r == res) {
return 0;
} else {
printf("error r = %d (!= %d)\n", r, res);
return 1;
}
}
|
quick_sort_omp.h | // g++ -std=c++17 -fopenmp test_quick_sort.cpp -o test
// Multithreaded quicksort using openMP
#include <omp.h>
// Swaps two pointer values
template<typename T>
void swap(T* a, T* b)
{
T tmp = *a;
*a = *b;
*b = tmp;
}
// Partitions the array such that:
// - The entry args[j] is in its final place in the array, for some j.
// - No entry in args[lo] through args[j-1] is greater than args[j].
// - No entry in args[j+1] through a[hi] is less than args[j].
template <typename T>
int partition(T* args, int lo, int hi)
{
T pivot = args[hi];
int i, j;
i = lo-1;
for (j = lo; j <= hi-1; ++j)
{
if(args[j] <= pivot)
{
++i;
swap(&args[i], &args[j]);
}
}
swap(&args[i+1], &args[hi]);
return (i + 1);
}
// Sorts an array in ascending order from index 'lo' to 'hi'
template<typename T>
void quick_sort(T* args, int lo, int hi)
{
int pivot;
if(lo < hi)
{
pivot = partition(args, lo, hi);
#pragma omp task shared(args) firstprivate(lo, pivot)
quick_sort(args, lo, pivot-1);
#pragma omp task shared(args) firstprivate(pivot, hi)
quick_sort(args, pivot+1, hi);
#pragma omp taskwait
}
return;
}
|
UniOP.h | #ifndef UNIOP_H_
#define UNIOP_H_
/*
* UniOP.h:
* a simple feed forward neural operation, unary input.
*
* Created on: Apr 22, 2017
* Author: mszhang
*/
#include "Param.h"
#include "MyLib.h"
#include "Node.h"
#include "Graph.h"
#include "ModelUpdate.h"
#include <cstdlib>
#include "profiler.h"
class UniParams {
public:
Param W;
Param b;
bool bUseB;
public:
UniParams() {
bUseB = true;
}
inline void exportAdaParams(ModelUpdate& ada) {
ada.addParam(&W);
if (bUseB) {
ada.addParam(&b);
}
}
inline void initial(int nOSize, int nISize, bool useB = true) {
W.initial(nOSize, nISize);
bUseB = useB;
if (bUseB) {
b.initial(nOSize, 1);
}
}
inline void save(std::ofstream &os) const {
os << bUseB << std::endl;
W.save(os);
if (bUseB) {
b.save(os);
}
}
inline void load(std::ifstream &is) {
is >> bUseB;
W.load(is);
if (bUseB) {
b.load(is);
}
}
};
// non-linear feed-forward node
// input nodes should be specified by forward function
// for input variables, we exploit column vector,
// which means a concrete input vector x_i is represented by x(0, i), x(1, i), ..., x(n, i)
class UniNode : public Node {
public:
PNode in;
UniParams* param;
dtype(*activate)(const dtype&); // activation function
dtype(*derivate)(const dtype&, const dtype&); // derivation function of activation function
Tensor1D ty, lty;
public:
UniNode() : Node() {
in = NULL;
activate = ftanh;
derivate = dtanh;
param = NULL;
node_type = "uni";
}
~UniNode() {
in = NULL;
}
inline void init(int ndim, dtype dropout) {
Node::init(ndim, dropout);
ty.init(ndim);
lty.init(ndim);
}
inline void setParam(UniParams* paramInit) {
param = paramInit;
}
inline void clearValue() {
Node::clearValue();
in = NULL;
}
// define the activate function and its derivation form
inline void setFunctions(dtype(*f)(const dtype&), dtype(*f_deri)(const dtype&, const dtype&)) {
activate = f;
derivate = f_deri;
}
void forward(Graph *cg, PNode x) {
in = x;
degree = 0;
in->addParent(this);
cg->addNode(this);
}
inline void compute() {
ty.mat() = param->W.val.mat() * in->val.mat();
if (param->bUseB) {
ty.vec() += param->b.val.vec();
}
val.vec() = ty.vec().unaryExpr(ptr_fun(activate));
}
inline void backward() {
lty.vec() = loss.vec() * ty.vec().binaryExpr(val.vec(), ptr_fun(derivate));
param->W.grad.mat() += lty.mat() * in->val.tmat();
if (param->bUseB) {
param->b.grad.vec() += lty.vec();
}
in->loss.mat() += param->W.val.mat().transpose() * lty.mat();
}
inline PExecute generate(bool bTrain, dtype cur_drop_factor);
// better to rewrite for deep understanding
bool typeEqual(PNode other) override {
bool result = Node::typeEqual(other);
if (!result) return false;
UniNode* conv_other = (UniNode*)other;
if (param != conv_other->param) {
return false;
}
if (activate != conv_other->activate || derivate != conv_other->derivate) {
return false;
}
return true;
}
size_t typeHashCode() const override {
void *act = reinterpret_cast<void*>(activate);
void *de = reinterpret_cast<void*>(derivate);
return Node::typeHashCode() ^ ::typeHashCode(param) ^ ::typeHashCode(act) ^
(::typeHashCode(de) << 1);
}
#if USE_GPU
void toNodeInfo(NodeInfo &info) const override {
Node::toNodeInfo(info);
info.input_vals.push_back(in->val.value);
info.input_losses.push_back(in->loss.value);
}
#endif
};
// non-linear feed-forward node
// input nodes should be specified by forward function
// for input variables, we exploit column vector,
// which means a concrete input vector x_i is represented by x(0, i), x(1, i), ..., x(n, i)
class LinearUniNode : public Node {
public:
PNode in;
UniParams* param;
public:
LinearUniNode() : Node() {
in = NULL;
param = NULL;
node_type = "linear_uni";
}
inline void setParam(UniParams* paramInit) {
param = paramInit;
}
inline void clearValue() {
Node::clearValue();
in = NULL;
}
public:
void forward(Graph *cg, PNode x) {
in = x;
degree = 0;
in->addParent(this);
cg->addNode(this);
}
public:
inline void compute() {
val.mat() = param->W.val.mat() * in->val.mat();
if (param->bUseB) {
val.vec() += param->b.val.vec();
}
}
inline void backward() {
param->W.grad.mat() += loss.mat() * in->val.tmat();
if (param->bUseB) {
param->b.grad.vec() += loss.vec();
}
in->loss.mat() += param->W.val.mat().transpose() * loss.mat();
}
public:
inline PExecute generate(bool bTrain, dtype cur_drop_factor);
// better to rewrite for deep understanding
inline bool typeEqual(PNode other) {
bool result = Node::typeEqual(other);
if (!result) return false;
LinearUniNode* conv_other = (LinearUniNode*)other;
if (param != conv_other->param) {
return false;
}
return true;
}
};
// non-linear feed-forward node
// input nodes should be specified by forward function
// for input variables, we exploit column vector,
// which means a concrete input vector x_i is represented by x(0, i), x(1, i), ..., x(n, i)
class LinearNode : public Node {
public:
PNode in;
UniParams* param;
public:
LinearNode() : Node() {
in = NULL;
param = NULL;
node_type = "linear";
}
inline void setParam(UniParams* paramInit) {
param = paramInit;
}
inline void clearValue() {
Node::clearValue();
in = NULL;
}
public:
void forward(Graph *cg, PNode x) {
in = x;
degree = 0;
in->addParent(this);
cg->addNode(this);
}
public:
inline void compute() {
val.mat() = param->W.val.mat() * in->val.mat();
}
inline void backward() {
param->W.grad.mat() += loss.mat() * in->val.tmat();
in->loss.mat() += param->W.val.mat().transpose() * loss.mat();
}
public:
PExecute generate(bool bTrain, dtype cur_drop_factor);
// better to rewrite for deep understanding
bool typeEqual(PNode other) override {
bool result = Node::typeEqual(other);
if (!result) return false;
LinearNode* conv_other = (LinearNode*)other;
if (param != conv_other->param) {
return false;
}
return true;
}
size_t typeHashCode() const override {
return Node::typeHashCode() ^ ::typeHashCode(param);
}
#if USE_GPU
void toNodeInfo(NodeInfo &info) const override {
Node::toNodeInfo(info);
info.input_vals.push_back(in->val.value);
info.input_losses.push_back(in->loss.value);
}
#endif
};
class UniExecute :public Execute {
public:
Tensor2D x, ty, y, b;
int inDim, outDim;
UniParams* param;
dtype(*activate)(const dtype&); // activation function
dtype(*derivate)(const dtype&, const dtype&); // derivation function of activation function
Tensor2D drop_mask;
inline void forward() {
int count = batch.size();
ty.init(outDim, count);
x.init(inDim, count);
y.init(outDim, count);
drop_mask.init(outDim, count);
#if TEST_CUDA || !USE_GPU
b.init(outDim, count);
#endif
#if USE_GPU
std::vector<dtype*> xs, ys;
xs.reserve(batch.size());
ys.reserve(batch.size());
for (int i = 0; i < batch.size(); ++i) {
UniNode *n = static_cast<UniNode*>(batch.at(i));
xs.push_back(n->in->val.value);
ys.push_back(n->val.value);
}
n3ldg_cuda::CopyForUniNodeForward(xs, param->b.val.value,
x.value, ty.value, count, inDim, outDim, param->bUseB);
n3ldg_cuda::MatrixMultiplyMatrix(param->W.val.value, x.value,
ty.value, outDim, inDim, count, param->bUseB);
CalculateDropMask(count, outDim, drop_mask);
n3ldg_cuda::ActivatedEnum activatedEnum = ToActivatedEnum(activate);
n3ldg_cuda::Activated(activatedEnum, ty.value, ys, y.value, outDim,
bTrain, dynamicDropValue(), drop_mask.value);
for (int i = 0; i<batch.size(); ++i) {
UniNode *n = static_cast<UniNode*>(batch.at(i));
}
#if TEST_CUDA
for (int idx = 0; idx < count; idx++) {
UniNode* ptr = (UniNode*)batch[idx];
for (int idy = 0; idy < inDim; idy++) {
x[idy][idx] = ptr->in->val[idy];
}
if (param->bUseB) {
for (int idy = 0; idy < outDim; idy++) {
b[idy][idx] = param->b.val.v[idy];
}
}
}
n3ldg_cuda::Assert(x.verify("forward x"));
ty.mat() = param->W.val.mat() * x.mat();
if (param->bUseB) {
ty.vec() = ty.vec() + b.vec();
}
y.vec() = ty.vec().unaryExpr(ptr_fun(activate));
for (int idx = 0; idx < count; idx++) {
UniNode* ptr = (UniNode*)batch[idx];
for (int idy = 0; idy < outDim; idy++) {
ptr->val[idy] = y[idy][idx];
}
}
drop_mask.copyFromDeviceToHost();
for (int i = 0; i < count; ++i) {
for (int j = 0; j < outDim; ++j) {
dtype v = drop_mask[j][i];
batch[i]->drop_mask[j] = v <= dynamicDropValue() ? 0 : 1;
}
}
for (int i = 0; i < count; ++i) {
batch[i]->forward_drop(bTrain, drop_factor);
n3ldg_cuda::Assert(batch[i]->val.verify("forward batch i val"));
}
n3ldg_cuda::Assert(ty.verify("forward ty"));
n3ldg_cuda::Assert(y.verify("forward y"));
#endif
#else
for (int idx = 0; idx < count; idx++) {
UniNode* ptr = (UniNode*)batch[idx];
for (int idy = 0; idy < inDim; idy++) {
x[idy][idx] = ptr->in->val[idy];
}
if (param->bUseB) {
for (int idy = 0; idy < outDim; idy++) {
b[idy][idx] = param->b.val.v[idy];
}
}
}
ty.mat() = param->W.val.mat() * x.mat();
if (param->bUseB) {
ty.vec() = ty.vec() + b.vec();
}
y.vec() = ty.vec().unaryExpr(ptr_fun(activate));
for (int idx = 0; idx < count; idx++) {
UniNode* ptr = (UniNode*)batch[idx];
for (int idy = 0; idy < outDim; idy++) {
ptr->val[idy] = y[idy][idx];
}
}
for (int i = 0; i < count; ++i) {
dtype drop_value = batch[0]->drop_value;
batch[i]->forward_drop(bTrain, drop_factor);
}
#endif
}
void backward() {
int count = batch.size();
Tensor2D lx, lty, ly;
#if USE_GPU
lx.init(inDim, count);
lty.init(outDim, count);
ly.init(outDim, count);
std::vector<dtype*> ly_vec;
ly_vec.reserve(count);
for (int i = 0; i < count; ++i) {
UniNode* ptr = (UniNode*)batch[i];
ly_vec.push_back(ptr->loss.value);
}
n3ldg_cuda::ActivatedEnum activatedEnum = ToActivatedEnum(activate);
n3ldg_cuda::CalculateLtyForUniBackward(activatedEnum, ly_vec, ty.value,
y.value, drop_mask.value, dynamicDropValue(), lty.value, count,
outDim);
#if TEST_CUDA
n3ldg_cuda::Assert(param->W.grad.verify(
"uni backward W grad initial"));
#endif
n3ldg_cuda::MatrixMultiplyMatrix(lty.value, x.value,
param->W.grad.value, outDim, count, inDim, true, true, false);
#if TEST_CUDA
n3ldg_cuda::Assert(param->W.val.verify("uni W.val initial"));
#endif
n3ldg_cuda::MatrixMultiplyMatrix(param->W.val.value, lty.value,
lx.value, inDim, outDim, count, false, false, true);
std::vector<dtype*> losses;
losses.reserve(count);
for (int idx = 0; idx < count; idx++) {
UniNode* ptr = (UniNode*)batch[idx];
losses.push_back(ptr->in->loss.value);
}
#if TEST_CUDA
n3ldg_cuda::Assert(
param->b.grad.verify("uni backward param b initial"));
#endif
n3ldg_cuda::AddLtyToParamBiasAndAddLxToInputLossesForUniBackward(
lty.value, lx.value, param->b.grad.value, losses, count,
outDim, inDim, param->bUseB);
#if TEST_CUDA
for (int idx = 0; idx < count; idx++) {
UniNode* ptr = (UniNode*)batch[idx];
ptr->backward_drop();
for (int idy = 0; idy < outDim; idy++) {
ly[idy][idx] = ptr->loss[idy];
}
}
n3ldg_cuda::Assert(x.verify("backward x"));
lty.vec() = ly.vec() * ty.vec().binaryExpr(y.vec(), ptr_fun(derivate));
n3ldg_cuda::Assert(lty.verify("backward lty"));
param->W.grad.mat() += lty.mat() * x.mat().transpose();
n3ldg_cuda::Assert(param->W.grad.verify("backward W grad"));
if (param->bUseB) {
for (int idx = 0; idx < count; idx++) {
for (int idy = 0; idy < outDim; idy++) {
param->b.grad.v[idy] += lty[idy][idx];
}
}
}
n3ldg_cuda::Assert(param->b.grad.verify("backward b grad"));
lx.mat() += param->W.val.mat().transpose() * lty.mat();
n3ldg_cuda::Assert(lx.verify("backward lx"));
for (int idx = 0; idx < count; idx++) {
UniNode* ptr = (UniNode*)batch[idx];
for (int idy = 0; idy < inDim; idy++) {
ptr->in->loss[idy] += lx[idy][idx];
}
}
for (Node * n : batch) {
UniNode *ptr = static_cast<UniNode *>(n);
n3ldg_cuda::Assert(ptr->in->loss.verify("uni backward loss"));
}
#endif
#else
lx.init(inDim, count);
lty.init(outDim, count);
ly.init(outDim, count);
for (int idx = 0; idx < count; idx++) {
UniNode* ptr = (UniNode*)batch[idx];
ptr->backward_drop();
for (int idy = 0; idy < outDim; idy++) {
ly[idy][idx] = ptr->loss[idy];
}
}
lty.vec() = ly.vec() * ty.vec().binaryExpr(y.vec(), ptr_fun(derivate));
param->W.grad.mat() += lty.mat() * x.mat().transpose();
if (param->bUseB) {
for (int idx = 0; idx < count; idx++) {
for (int idy = 0; idy < outDim; idy++) {
param->b.grad.v[idy] += lty[idy][idx];
}
}
}
lx.mat() += param->W.val.mat().transpose() * lty.mat();
for (int idx = 0; idx < count; idx++) {
UniNode* ptr = (UniNode*)batch[idx];
for (int idy = 0; idy < inDim; idy++) {
ptr->in->loss[idy] += lx[idy][idx];
}
}
#endif
}
};
inline PExecute UniNode::generate(bool bTrain, dtype cur_drop_factor) {
UniExecute* exec = new UniExecute();
exec->batch.push_back(this);
exec->bTrain = bTrain;
exec->drop_factor = cur_drop_factor;
exec->inDim = param->W.inDim();
exec->outDim = param->W.outDim();
exec->param = param;
exec->activate = activate;
exec->derivate = derivate;
return exec;
};
class LinearUniExecute :public Execute {
public:
inline void forward() {
int count = batch.size();
//#pragma omp parallel for
for (int idx = 0; idx < count; idx++) {
batch[idx]->compute();
batch[idx]->forward_drop(bTrain, drop_factor);
}
}
inline void backward() {
int count = batch.size();
//#pragma omp parallel for
for (int idx = 0; idx < count; idx++) {
batch[idx]->backward_drop();
batch[idx]->backward();
}
}
};
inline PExecute LinearUniNode::generate(bool bTrain, dtype cur_drop_factor) {
LinearUniExecute* exec = new LinearUniExecute();
exec->batch.push_back(this);
exec->bTrain = bTrain;
exec->drop_factor = cur_drop_factor;
return exec;
};
#if USE_GPU
class LinearExecute :public Execute {
public:
Tensor2D x, y, b;
int inDim, outDim, count;
UniParams* param;
void forward() {
int count = batch.size();
x.init(inDim, count);
y.init(outDim, count);
#if TEST_CUDA
b.init(outDim, count);
#endif
std::vector<dtype*> xs, ys;
xs.reserve(batch.size());
ys.reserve(batch.size());
for (int i = 0; i < batch.size(); ++i) {
LinearNode *n = static_cast<LinearNode*>(batch.at(i));
xs.push_back(n->in->val.value);
ys.push_back(n->val.value);
}
n3ldg_cuda::CopyForUniNodeForward(xs, param->b.val.value,
x.value, y.value, count, inDim, outDim, param->bUseB);
n3ldg_cuda::MatrixMultiplyMatrix(param->W.val.value, x.value, y.value,
outDim, inDim, count, false);
std::vector<dtype*> vals;
vals.reserve(count);
for (Node *node : batch) {
vals.push_back(node->val.value);
}
n3ldg_cuda::CopyFromOneVectorToMultiVals(y.value, vals, count, outDim);
#if TEST_CUDA
for (int idx = 0; idx < count; idx++) {
LinearNode* ptr = (LinearNode*)batch[idx];
for (int idy = 0; idy < inDim; idy++) {
x[idy][idx] = ptr->in->val[idy];
}
}
y.mat() = param->W.val.mat() * x.mat();
n3ldg_cuda::Assert(x.verify("forward x"));
n3ldg_cuda::Assert(y.verify("forward y"));
for (int idx = 0; idx < count; idx++) {
LinearNode* ptr = (LinearNode*)batch[idx];
for (int idy = 0; idy < outDim; idy++) {
ptr->val[idy] = y[idy][idx];
}
n3ldg_cuda::Assert(ptr->val.verify("linear forward val"));
}
#endif
}
void backward() {
int count = batch.size();
Tensor2D lx, ly;
lx.init(inDim, count);
ly.init(outDim, count);
std::vector<dtype*> ly_vec;
ly_vec.reserve(count);
for (int i = 0; i < count; ++i) {
UniNode* ptr = (UniNode*)batch[i];
ly_vec.push_back(ptr->loss.value);
}
n3ldg_cuda::CalculateLyForLinearBackward(ly_vec, ly.value, count,
outDim);
n3ldg_cuda::MatrixMultiplyMatrix(ly.value, x.value,
param->W.grad.value, outDim, count, inDim, true, true, false);
n3ldg_cuda::MatrixMultiplyMatrix(param->W.val.value, ly.value,
lx.value, inDim, outDim, count, false, false, true);
std::vector<dtype*> losses;
losses.reserve(count);
for (int idx = 0; idx < count; idx++) {
UniNode* ptr = (UniNode*)batch[idx];
losses.push_back(ptr->in->loss.value);
}
n3ldg_cuda::AddLtyToParamBiasAndAddLxToInputLossesForUniBackward(
ly.value, lx.value, param->b.grad.value, losses, count,
outDim, inDim, param->bUseB);
#if TEST_CUDA
for (int idx = 0; idx < count; idx++) {
UniNode* ptr = (UniNode*)batch[idx];
ptr->backward_drop();
for (int idy = 0; idy < outDim; idy++) {
ly[idy][idx] = ptr->loss[idy];
}
}
assert(x.verify("backward x"));
param->W.grad.mat() += ly.mat() * x.mat().transpose();
param->W.grad.verify("backward W grad");
if (param->bUseB) {
for (int idx = 0; idx < count; idx++) {
for (int idy = 0; idy < outDim; idy++) {
param->b.grad.v[idy] += ly[idy][idx];
}
}
}
n3ldg_cuda::Assert(param->b.grad.verify("backward b grad"));
lx.mat() += param->W.val.mat().transpose() * ly.mat();
lx.verify("backward lx");
for (int idx = 0; idx < count; idx++) {
UniNode* ptr = (UniNode*)batch[idx];
for (int idy = 0; idy < inDim; idy++) {
ptr->in->loss[idy] += lx[idy][idx];
}
}
for (Node * n : batch) {
UniNode *ptr = static_cast<UniNode *>(n);
n3ldg_cuda::Assert(ptr->in->loss.verify("backward loss"));
}
#endif
}
};
#else
class LinearExecute :public Execute {
public:
Tensor2D x, y;
int inDim, outDim, count;
UniParams* param;
inline void forward() {
count = batch.size();
x.init(inDim, count);
y.init(outDim, count);
for (int idx = 0; idx < count; idx++) {
LinearNode* ptr = (LinearNode*)batch[idx];
for (int idy = 0; idy < inDim; idy++) {
x[idy][idx] = ptr->in->val[idy];
}
}
y.mat() = param->W.val.mat() * x.mat();
for (int idx = 0; idx < count; idx++) {
LinearNode* ptr = (LinearNode*)batch[idx];
for (int idy = 0; idy < outDim; idy++) {
ptr->val[idy] = y[idy][idx];
}
ptr->forward_drop(bTrain, drop_factor);
}
}
inline void backward() {
Tensor2D lx, ly;
lx.init(inDim, count);
ly.init(outDim, count);
for (int idx = 0; idx < count; idx++) {
LinearNode* ptr = (LinearNode*)batch[idx];
ptr->backward_drop();
for (int idy = 0; idy < outDim; idy++) {
ly[idy][idx] = ptr->loss[idy];
}
}
param->W.grad.mat() += ly.mat() * x.mat().transpose();
lx.mat() += param->W.val.mat().transpose() * ly.mat();
for (int idx = 0; idx < count; idx++) {
LinearNode* ptr = (LinearNode*)batch[idx];
for (int idy = 0; idy < inDim; idy++) {
ptr->in->loss[idy] += lx[idy][idx];
}
}
}
};
#endif
inline PExecute LinearNode::generate(bool bTrain, dtype cur_drop_factor) {
LinearExecute* exec = new LinearExecute();
exec->batch.push_back(this);
exec->inDim = param->W.inDim();
exec->outDim = param->W.outDim();
exec->param = param;
exec->bTrain = bTrain;
return exec;
};
#endif /* UNIOP_H_ */
|
GB_unaryop__ainv_fp64_uint16.c | //------------------------------------------------------------------------------
// GB_unaryop: hard-coded functions for each built-in unary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2020, All Rights Reserved.
// http://suitesparse.com See GraphBLAS/Doc/License.txt for license.
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_iterator.h"
#include "GB_unaryop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB_unop__ainv_fp64_uint16
// op(A') function: GB_tran__ainv_fp64_uint16
// C type: double
// A type: uint16_t
// cast: double cij = (double) aij
// unaryop: cij = -aij
#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 ;
// casting
#define GB_CASTING(z, aij) \
double z = (double) aij ;
// cij = op (cast (aij))
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
GB_GETA (aij, Ax, pA) ; \
/* Cx [pC] = op (cast (aij)) */ \
GB_CASTING (z, aij) ; \
GB_OP (GB_CX (pC), z) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_AINV || GxB_NO_FP64 || GxB_NO_UINT16)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__ainv_fp64_uint16
(
double *Cx, // Cx and Ax may be aliased
uint16_t *Ax,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
GB_CAST_OP (p, p) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_tran__ainv_fp64_uint16
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *GB_RESTRICT *Rowcounts,
GBI_single_iterator Iter,
const int64_t *GB_RESTRICT A_slice,
int naslice
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#define GB_PHASE_2_OF_2
#include "GB_unaryop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
compare.c | /*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% CCCC OOO M M PPPP AAA RRRR EEEEE %
% C O O MM MM P P A A R R E %
% C O O M M M PPPP AAAAA RRRR EEE %
% C O O M M P A A R R E %
% CCCC OOO M M P A A R R EEEEE %
% %
% %
% MagickCore Image Comparison Methods %
% %
% Software Design %
% John Cristy %
% December 2003 %
% %
% %
% Copyright 1999-2009 ImageMagick Studio LLC, a non-profit organization %
% dedicated to making software imaging solutions freely available. %
% %
% You may not use this file except in compliance with the License. You may %
% obtain a copy of the License at %
% %
% http://www.imagemagick.org/script/license.php %
% %
% Unless required by applicable law or agreed to in writing, software %
% distributed under the License is distributed on an "AS IS" BASIS, %
% WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. %
% See the License for the specific language governing permissions and %
% limitations under the License. %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
%
%
*/
/*
Include declarations.
*/
#include "magick/studio.h"
#include "magick/artifact.h"
#include "magick/cache-view.h"
#include "magick/client.h"
#include "magick/color.h"
#include "magick/color-private.h"
#include "magick/colorspace.h"
#include "magick/colorspace-private.h"
#include "magick/compare.h"
#include "magick/composite-private.h"
#include "magick/constitute.h"
#include "magick/exception-private.h"
#include "magick/geometry.h"
#include "magick/image-private.h"
#include "magick/list.h"
#include "magick/log.h"
#include "magick/memory_.h"
#include "magick/option.h"
#include "magick/pixel-private.h"
#include "magick/resource_.h"
#include "magick/string_.h"
#include "magick/utility.h"
#include "magick/version.h"
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% C o m p a r e I m a g e C h a n n e l s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% CompareImageChannels() compares one or more image channels of an image
% to a reconstructed image and returns the difference image.
%
% The format of the CompareImageChannels method is:
%
% Image *CompareImageChannels(const Image *image,
% const Image *reconstruct_image,const ChannelType channel,
% const MetricType metric,double *distortion,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o reconstruct_image: the reconstruct image.
%
% o channel: the channel.
%
% o metric: the metric.
%
% o distortion: the computed distortion between the images.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport Image *CompareImages(Image *image,const Image *reconstruct_image,
const MetricType metric,double *distortion,ExceptionInfo *exception)
{
Image
*highlight_image;
highlight_image=CompareImageChannels(image,reconstruct_image,AllChannels,
metric,distortion,exception);
return(highlight_image);
}
MagickExport Image *CompareImageChannels(Image *image,
const Image *reconstruct_image,const ChannelType channel,
const MetricType metric,double *distortion,ExceptionInfo *exception)
{
const char
*artifact;
Image
*difference_image,
*highlight_image;
long
y;
MagickBooleanType
status;
MagickPixelPacket
highlight,
lowlight,
zero;
ViewInfo
*highlight_view,
*image_view,
*reconstruct_view;
assert(image != (Image *) NULL);
assert(image->signature == MagickSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(reconstruct_image != (const Image *) NULL);
assert(reconstruct_image->signature == MagickSignature);
assert(distortion != (double *) NULL);
*distortion=0.0;
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if ((reconstruct_image->columns != image->columns) ||
(reconstruct_image->rows != image->rows))
ThrowImageException(ImageError,"ImageSizeDiffers");
status=GetImageChannelDistortion(image,reconstruct_image,channel,metric,
distortion,exception);
if (status == MagickFalse)
return((Image *) NULL);
difference_image=CloneImage(image,0,0,MagickTrue,exception);
if (difference_image == (Image *) NULL)
return((Image *) NULL);
(void) SetImageAlphaChannel(difference_image,OpaqueAlphaChannel);
highlight_image=CloneImage(image,image->columns,image->rows,MagickTrue,
exception);
if (highlight_image == (Image *) NULL)
{
difference_image=DestroyImage(difference_image);
return((Image *) NULL);
}
if (SetImageStorageClass(highlight_image,DirectClass) == MagickFalse)
{
InheritException(exception,&highlight_image->exception);
difference_image=DestroyImage(difference_image);
highlight_image=DestroyImage(highlight_image);
return((Image *) NULL);
}
(void) SetImageAlphaChannel(highlight_image,OpaqueAlphaChannel);
(void) QueryMagickColor("#f1001ecc",&highlight,exception);
artifact=GetImageArtifact(image,"highlight-color");
if (artifact != (const char *) NULL)
(void) QueryMagickColor(artifact,&highlight,exception);
(void) QueryMagickColor("#ffffffcc",&lowlight,exception);
artifact=GetImageArtifact(image,"lowlight-color");
if (artifact != (const char *) NULL)
(void) QueryMagickColor(artifact,&lowlight,exception);
if (highlight_image->colorspace == CMYKColorspace)
{
ConvertRGBToCMYK(&highlight);
ConvertRGBToCMYK(&lowlight);
}
/*
Generate difference image.
*/
status=MagickTrue;
GetMagickPixelPacket(image,&zero);
image_view=AcquireCacheView(image);
reconstruct_view=AcquireCacheView(reconstruct_image);
highlight_view=AcquireCacheView(highlight_image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(dynamic,4) shared(status)
#endif
for (y=0; y < (long) image->rows; y++)
{
MagickBooleanType
sync;
MagickPixelPacket
pixel,
reconstruct_pixel;
register const IndexPacket
*indexes,
*reconstruct_indexes;
register const PixelPacket
*p,
*q;
register IndexPacket
*highlight_indexes;
register long
x;
register PixelPacket
*r;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=GetCacheViewVirtualPixels(reconstruct_view,0,y,reconstruct_image->columns,
1,exception);
r=QueueCacheViewAuthenticPixels(highlight_view,0,y,highlight_image->columns,
1,exception);
if ((p == (const PixelPacket *) NULL) ||
(q == (const PixelPacket *) NULL) || (r == (PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
reconstruct_indexes=GetCacheViewVirtualIndexQueue(reconstruct_view);
highlight_indexes=GetCacheViewAuthenticIndexQueue(highlight_view);
pixel=zero;
reconstruct_pixel=zero;
for (x=0; x < (long) image->columns; x++)
{
MagickStatusType
difference;
SetMagickPixelPacket(image,p,indexes+x,&pixel);
SetMagickPixelPacket(reconstruct_image,q,reconstruct_indexes+x,
&reconstruct_pixel);
difference=MagickFalse;
if (channel == AllChannels)
{
if (IsMagickColorSimilar(&pixel,&reconstruct_pixel) == MagickFalse)
difference=MagickTrue;
}
else
{
if (((channel & RedChannel) != 0) && (p->red != q->red))
difference=MagickTrue;
if (((channel & GreenChannel) != 0) && (p->green != q->green))
difference=MagickTrue;
if (((channel & BlueChannel) != 0) && (p->blue != q->blue))
difference=MagickTrue;
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse) && (p->opacity != q->opacity))
difference=MagickTrue;
if ((((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace) &&
(reconstruct_image->colorspace == CMYKColorspace)) &&
(indexes[x] != reconstruct_indexes[x]))
difference=MagickTrue;
}
if (difference != MagickFalse)
SetPixelPacket(highlight_image,&highlight,r,highlight_indexes+x);
else
SetPixelPacket(highlight_image,&lowlight,r,highlight_indexes+x);
p++;
q++;
r++;
}
sync=SyncCacheViewAuthenticPixels(highlight_view,exception);
if (sync == MagickFalse)
status=MagickFalse;
}
highlight_view=DestroyCacheView(highlight_view);
reconstruct_view=DestroyCacheView(reconstruct_view);
image_view=DestroyCacheView(image_view);
(void) CompositeImage(difference_image,image->compose,highlight_image,0,0);
highlight_image=DestroyImage(highlight_image);
if (status == MagickFalse)
difference_image=DestroyImage(difference_image);
return(difference_image);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e C h a n n e l D i s t o r t i o n %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageChannelDistortion() compares one or more image channels of an image
% to a reconstructed image and returns the specified distortion metric.
%
% The format of the CompareImageChannels method is:
%
% MagickBooleanType GetImageChannelDistortion(const Image *image,
% const Image *reconstruct_image,const ChannelType channel,
% const MetricType metric,double *distortion,ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o reconstruct_image: the reconstruct image.
%
% o channel: the channel.
%
% o metric: the metric.
%
% o distortion: the computed distortion between the images.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport MagickBooleanType GetImageDistortion(Image *image,
const Image *reconstruct_image,const MetricType metric,double *distortion,
ExceptionInfo *exception)
{
MagickBooleanType
status;
status=GetImageChannelDistortion(image,reconstruct_image,AllChannels,
metric,distortion,exception);
return(status);
}
static MagickBooleanType GetAbsoluteError(const Image *image,
const Image *reconstruct_image,const ChannelType channel,double *distortion,
ExceptionInfo *exception)
{
long
y;
MagickBooleanType
status;
MagickPixelPacket
zero;
ViewInfo
*image_view,
*reconstruct_view;
/*
Compute the absolute difference in pixels between two images.
*/
status=MagickTrue;
GetMagickPixelPacket(image,&zero);
image_view=AcquireCacheView(image);
reconstruct_view=AcquireCacheView(reconstruct_image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(dynamic,4) shared(status)
#endif
for (y=0; y < (long) image->rows; y++)
{
double
channel_distortion[AllChannels+1];
MagickPixelPacket
pixel,
reconstruct_pixel;
register const IndexPacket
*indexes,
*reconstruct_indexes;
register const PixelPacket
*p,
*q;
register long
i,
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=GetCacheViewVirtualPixels(reconstruct_view,0,y,reconstruct_image->columns,
1,exception);
if ((p == (const PixelPacket *) NULL) || (q == (const PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
reconstruct_indexes=GetCacheViewVirtualIndexQueue(reconstruct_view);
pixel=zero;
reconstruct_pixel=pixel;
(void) ResetMagickMemory(channel_distortion,0,sizeof(channel_distortion));
for (x=0; x < (long) image->columns; x++)
{
SetMagickPixelPacket(image,p,indexes+x,&pixel);
SetMagickPixelPacket(reconstruct_image,q,reconstruct_indexes+x,
&reconstruct_pixel);
if (IsMagickColorSimilar(&pixel,&reconstruct_pixel) == MagickFalse)
{
if ((channel & RedChannel) != 0)
channel_distortion[RedChannel]++;
if ((channel & GreenChannel) != 0)
channel_distortion[GreenChannel]++;
if ((channel & BlueChannel) != 0)
channel_distortion[BlueChannel]++;
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
channel_distortion[OpacityChannel]++;
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace))
channel_distortion[BlackChannel]++;
channel_distortion[AllChannels]++;
}
p++;
q++;
}
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical
#endif
for (i=0; i <= (long) AllChannels; i++)
distortion[i]+=channel_distortion[i];
}
reconstruct_view=DestroyCacheView(reconstruct_view);
image_view=DestroyCacheView(image_view);
return(status);
}
static unsigned long GetNumberChannels(const Image *image,
const ChannelType channel)
{
unsigned long
channels;
channels=0;
if ((channel & RedChannel) != 0)
channels++;
if ((channel & GreenChannel) != 0)
channels++;
if ((channel & BlueChannel) != 0)
channels++;
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
channels++;
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace))
channels++;
return(channels);
}
static MagickBooleanType GetMeanAbsoluteError(const Image *image,
const Image *reconstruct_image,const ChannelType channel,
double *distortion,ExceptionInfo *exception)
{
double
scale;
long
y;
MagickBooleanType
status;
ViewInfo
*image_view,
*reconstruct_view;
status=MagickTrue;
scale=1.0/((double) image->columns*image->rows);
image_view=AcquireCacheView(image);
reconstruct_view=AcquireCacheView(reconstruct_image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(dynamic,4) shared(status)
#endif
for (y=0; y < (long) image->rows; y++)
{
double
channel_distortion[AllChannels+1];
register const IndexPacket
*indexes,
*reconstruct_indexes;
register const PixelPacket
*p,
*q;
register long
i,
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=GetCacheViewVirtualPixels(reconstruct_view,0,y,
reconstruct_image->columns,1,exception);
if ((p == (const PixelPacket *) NULL) || (q == (const PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
reconstruct_indexes=GetCacheViewVirtualIndexQueue(reconstruct_view);
(void) ResetMagickMemory(channel_distortion,0,sizeof(channel_distortion));
for (x=0; x < (long) image->columns; x++)
{
MagickRealType
distance;
if ((channel & RedChannel) != 0)
{
distance=fabs(p->red-(double) q->red);
channel_distortion[RedChannel]+=scale*distance;
channel_distortion[AllChannels]+=scale*distance;
}
if ((channel & GreenChannel) != 0)
{
distance=fabs(p->green-(double) q->green);
channel_distortion[GreenChannel]+=scale*distance;
channel_distortion[AllChannels]+=scale*distance;
}
if ((channel & BlueChannel) != 0)
{
distance=fabs(p->blue-(double) q->blue);
channel_distortion[BlueChannel]+=scale*distance;
channel_distortion[AllChannels]+=scale*distance;
}
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
{
distance=fabs(p->opacity-(double) q->opacity);
channel_distortion[OpacityChannel]+=scale*distance;
channel_distortion[AllChannels]+=scale*distance;
}
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace))
{
distance=fabs(indexes[x]-(double) reconstruct_indexes[x]);
channel_distortion[BlackChannel]+=scale*distance;
channel_distortion[AllChannels]+=scale*distance;
}
p++;
q++;
}
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical
#endif
for (i=0; i <= (long) AllChannels; i++)
distortion[i]+=channel_distortion[i];
}
reconstruct_view=DestroyCacheView(reconstruct_view);
image_view=DestroyCacheView(image_view);
distortion[AllChannels]/=(double) GetNumberChannels(image,channel);
return(status);
}
static MagickBooleanType GetMeanErrorPerPixel(Image *image,
const Image *reconstruct_image,const ChannelType channel,double *distortion,
ExceptionInfo *exception)
{
long
y;
MagickBooleanType
status;
MagickRealType
alpha,
area,
beta,
maximum_error,
mean_error;
ViewInfo
*image_view,
*reconstruct_view;
status=MagickTrue;
alpha=1.0;
beta=1.0;
area=0.0;
maximum_error=0.0;
mean_error=0.0;
image_view=AcquireCacheView(image);
reconstruct_view=AcquireCacheView(reconstruct_image);
for (y=0; y < (long) image->rows; y++)
{
register const IndexPacket
*indexes,
*reconstruct_indexes;
register const PixelPacket
*p,
*q;
register long
x;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=GetCacheViewVirtualPixels(reconstruct_view,0,y,reconstruct_image->columns,1,
exception);
if ((p == (const PixelPacket *) NULL) || (q == (const PixelPacket *) NULL))
{
status=MagickFalse;
break;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
reconstruct_indexes=GetCacheViewVirtualIndexQueue(reconstruct_view);
for (x=0; x < (long) image->columns; x++)
{
MagickRealType
distance;
if ((channel & OpacityChannel) != 0)
{
if (image->matte != MagickFalse)
alpha=(MagickRealType) (QuantumScale*(QuantumRange-p->opacity));
if (reconstruct_image->matte != MagickFalse)
beta=(MagickRealType) (QuantumScale*(QuantumRange-q->opacity));
}
if ((channel & RedChannel) != 0)
{
distance=fabs(alpha*p->red-beta*q->red);
distortion[RedChannel]+=distance;
distortion[AllChannels]+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
}
if ((channel & GreenChannel) != 0)
{
distance=fabs(alpha*p->green-beta*q->green);
distortion[GreenChannel]+=distance;
distortion[AllChannels]+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
}
if ((channel & BlueChannel) != 0)
{
distance=fabs(alpha*p->blue-beta*q->blue);
distortion[BlueChannel]+=distance;
distortion[AllChannels]+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
}
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
{
distance=fabs((double) p->opacity-q->opacity);
distortion[OpacityChannel]+=distance;
distortion[AllChannels]+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
}
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace) &&
(reconstruct_image->colorspace == CMYKColorspace))
{
distance=fabs(alpha*indexes[x]-beta*reconstruct_indexes[x]);
distortion[BlackChannel]+=distance;
distortion[AllChannels]+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
}
p++;
q++;
}
}
reconstruct_view=DestroyCacheView(reconstruct_view);
image_view=DestroyCacheView(image_view);
image->error.mean_error_per_pixel=distortion[AllChannels]/area;
image->error.normalized_mean_error=QuantumScale*QuantumScale*mean_error/area;
image->error.normalized_maximum_error=QuantumScale*maximum_error;
return(status);
}
static MagickBooleanType GetMeanSquaredError(const Image *image,
const Image *reconstruct_image,const ChannelType channel,
double *distortion,ExceptionInfo *exception)
{
double
scale;
long
y;
MagickBooleanType
status;
ViewInfo
*image_view,
*reconstruct_view;
status=MagickTrue;
scale=QuantumScale/((double) image->columns*image->rows);
image_view=AcquireCacheView(image);
reconstruct_view=AcquireCacheView(reconstruct_image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(dynamic,4) shared(status)
#endif
for (y=0; y < (long) image->rows; y++)
{
double
channel_distortion[AllChannels+1];
register const IndexPacket
*indexes,
*reconstruct_indexes;
register const PixelPacket
*p,
*q;
register long
i,
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=GetCacheViewVirtualPixels(reconstruct_view,0,y,
reconstruct_image->columns,1,exception);
if ((p == (const PixelPacket *) NULL) || (q == (const PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
reconstruct_indexes=GetCacheViewVirtualIndexQueue(reconstruct_view);
(void) ResetMagickMemory(channel_distortion,0,sizeof(channel_distortion));
for (x=0; x < (long) image->columns; x++)
{
MagickRealType
distance;
if ((channel & RedChannel) != 0)
{
distance=(p->red-(MagickRealType) q->red);
channel_distortion[RedChannel]+=scale*distance*distance;
channel_distortion[AllChannels]+=scale*distance*distance;
}
if ((channel & GreenChannel) != 0)
{
distance=(p->green-(MagickRealType) q->green);
channel_distortion[GreenChannel]+=scale*distance*distance;
channel_distortion[AllChannels]+=scale*distance*distance;
}
if ((channel & BlueChannel) != 0)
{
distance=(p->blue-(MagickRealType) q->blue);
channel_distortion[BlueChannel]+=scale*distance*distance;
channel_distortion[AllChannels]+=scale*distance*distance;
}
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
{
distance=(p->opacity-(MagickRealType) q->opacity);
channel_distortion[OpacityChannel]+=scale*distance*distance;
channel_distortion[AllChannels]+=scale*distance*distance;
}
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace) &&
(reconstruct_image->colorspace == CMYKColorspace))
{
distance=(indexes[x]-(MagickRealType) reconstruct_indexes[x]);
channel_distortion[BlackChannel]+=scale*distance*distance;
channel_distortion[AllChannels]+=scale*distance*distance;
}
p++;
q++;
}
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical
#endif
for (i=0; i <= (long) AllChannels; i++)
distortion[i]+=channel_distortion[i];
}
reconstruct_view=DestroyCacheView(reconstruct_view);
image_view=DestroyCacheView(image_view);
distortion[AllChannels]/=(double) GetNumberChannels(image,channel);
return(status);
}
static MagickBooleanType GetPeakAbsoluteError(const Image *image,
const Image *reconstruct_image,const ChannelType channel,
double *distortion,ExceptionInfo *exception)
{
long
y;
MagickBooleanType
status;
ViewInfo
*image_view,
*reconstruct_view;
status=MagickTrue;
image_view=AcquireCacheView(image);
reconstruct_view=AcquireCacheView(reconstruct_image);
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp parallel for schedule(dynamic,4) shared(status)
#endif
for (y=0; y < (long) image->rows; y++)
{
double
channel_distortion[AllChannels+1];
register const IndexPacket
*indexes,
*reconstruct_indexes;
register const PixelPacket
*p,
*q;
register long
i,
x;
if (status == MagickFalse)
continue;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,exception);
q=GetCacheViewVirtualPixels(reconstruct_view,0,y,
reconstruct_image->columns,1,exception);
if ((p == (const PixelPacket *) NULL) || (q == (const PixelPacket *) NULL))
{
status=MagickFalse;
continue;
}
indexes=GetCacheViewVirtualIndexQueue(image_view);
reconstruct_indexes=GetCacheViewVirtualIndexQueue(reconstruct_view);
(void) ResetMagickMemory(channel_distortion,0,sizeof(channel_distortion));
for (x=0; x < (long) image->columns; x++)
{
MagickRealType
distance;
if ((channel & RedChannel) != 0)
{
distance=fabs(p->red-(double) q->red);
if (distance > channel_distortion[RedChannel])
channel_distortion[RedChannel]=distance;
if (distance > channel_distortion[AllChannels])
channel_distortion[AllChannels]=distance;
}
if ((channel & GreenChannel) != 0)
{
distance=fabs(p->green-(double) q->green);
if (distance > channel_distortion[GreenChannel])
channel_distortion[GreenChannel]=distance;
if (distance > channel_distortion[AllChannels])
channel_distortion[AllChannels]=distance;
}
if ((channel & BlueChannel) != 0)
{
distance=fabs(p->blue-(double) q->blue);
if (distance > channel_distortion[BlueChannel])
channel_distortion[BlueChannel]=distance;
if (distance > channel_distortion[AllChannels])
channel_distortion[AllChannels]=distance;
}
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
{
distance=fabs(p->opacity-(double) q->opacity);
if (distance > channel_distortion[OpacityChannel])
channel_distortion[OpacityChannel]=distance;
if (distance > channel_distortion[AllChannels])
channel_distortion[AllChannels]=distance;
}
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace) &&
(reconstruct_image->colorspace == CMYKColorspace))
{
distance=fabs(indexes[x]-(double) reconstruct_indexes[x]);
if (distance > channel_distortion[BlackChannel])
channel_distortion[BlackChannel]=distance;
if (distance > channel_distortion[AllChannels])
channel_distortion[AllChannels]=distance;
}
p++;
q++;
}
#if defined(MAGICKCORE_OPENMP_SUPPORT)
#pragma omp critical
#endif
for (i=0; i <= (long) AllChannels; i++)
if (channel_distortion[i] > distortion[i])
distortion[i]=channel_distortion[i];
}
reconstruct_view=DestroyCacheView(reconstruct_view);
image_view=DestroyCacheView(image_view);
return(status);
}
static MagickBooleanType GetPeakSignalToNoiseRatio(const Image *image,
const Image *reconstruct_image,const ChannelType channel,
double *distortion,ExceptionInfo *exception)
{
MagickBooleanType
status;
status=GetMeanSquaredError(image,reconstruct_image,channel,distortion,
exception);
if ((channel & RedChannel) != 0)
distortion[RedChannel]=20.0*log10((double) 1.0/sqrt(QuantumScale*
distortion[RedChannel]));
if ((channel & GreenChannel) != 0)
distortion[GreenChannel]=20.0*log10((double) 1.0/sqrt(QuantumScale*
distortion[GreenChannel]));
if ((channel & BlueChannel) != 0)
distortion[BlueChannel]=20.0*log10((double) 1.0/sqrt(QuantumScale*
distortion[BlueChannel]));
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
distortion[OpacityChannel]=20.0*log10((double) 1.0/sqrt(QuantumScale*
distortion[OpacityChannel]));
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace))
distortion[BlackChannel]=20.0*log10((double) 1.0/sqrt(QuantumScale*
distortion[BlackChannel]));
distortion[AllChannels]=20.0*log10((double) 1.0/sqrt(QuantumScale*
distortion[AllChannels]));
return(status);
}
static MagickBooleanType GetRootMeanSquaredError(const Image *image,
const Image *reconstruct_image,const ChannelType channel,
double *distortion,ExceptionInfo *exception)
{
MagickBooleanType
status;
status=GetMeanSquaredError(image,reconstruct_image,channel,distortion,
exception);
if ((channel & RedChannel) != 0)
distortion[RedChannel]=sqrt(QuantumRange*distortion[RedChannel]);
if ((channel & GreenChannel) != 0)
distortion[GreenChannel]=sqrt(QuantumRange*distortion[GreenChannel]);
if ((channel & BlueChannel) != 0)
distortion[BlueChannel]=sqrt(QuantumRange*distortion[BlueChannel]);
if (((channel & OpacityChannel) != 0) &&
(image->matte != MagickFalse))
distortion[OpacityChannel]=sqrt(QuantumRange*distortion[OpacityChannel]);
if (((channel & IndexChannel) != 0) &&
(image->colorspace == CMYKColorspace))
distortion[BlackChannel]=sqrt(QuantumRange*distortion[BlackChannel]);
distortion[AllChannels]=sqrt(QuantumRange*distortion[AllChannels]);
return(status);
}
MagickExport MagickBooleanType GetImageChannelDistortion(Image *image,
const Image *reconstruct_image,const ChannelType channel,
const MetricType metric,double *distortion,ExceptionInfo *exception)
{
double
*channel_distortion;
MagickBooleanType
status;
size_t
length;
assert(image != (Image *) NULL);
assert(image->signature == MagickSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(reconstruct_image != (const Image *) NULL);
assert(reconstruct_image->signature == MagickSignature);
assert(distortion != (double *) NULL);
*distortion=0.0;
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if ((reconstruct_image->columns != image->columns) ||
(reconstruct_image->rows != image->rows))
ThrowBinaryException(ImageError,"ImageSizeDiffers",image->filename);
/*
Get image distortion.
*/
length=AllChannels+1UL;
channel_distortion=(double *) AcquireQuantumMemory(length,
sizeof(*channel_distortion));
if (channel_distortion == (double *) NULL)
ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
(void) ResetMagickMemory(channel_distortion,0,length*
sizeof(*channel_distortion));
switch (metric)
{
case AbsoluteErrorMetric:
{
status=GetAbsoluteError(image,reconstruct_image,channel,
channel_distortion,exception);
break;
}
case MeanAbsoluteErrorMetric:
{
status=GetMeanAbsoluteError(image,reconstruct_image,channel,
channel_distortion,exception);
break;
}
case MeanErrorPerPixelMetric:
{
status=GetMeanErrorPerPixel(image,reconstruct_image,channel,
channel_distortion,exception);
break;
}
case MeanSquaredErrorMetric:
{
status=GetMeanSquaredError(image,reconstruct_image,channel,
channel_distortion,exception);
break;
}
case PeakAbsoluteErrorMetric:
default:
{
status=GetPeakAbsoluteError(image,reconstruct_image,channel,
channel_distortion,exception);
break;
}
case PeakSignalToNoiseRatioMetric:
{
status=GetPeakSignalToNoiseRatio(image,reconstruct_image,channel,
channel_distortion,exception);
break;
}
case RootMeanSquaredErrorMetric:
{
status=GetRootMeanSquaredError(image,reconstruct_image,channel,
channel_distortion,exception);
break;
}
}
*distortion=channel_distortion[AllChannels];
channel_distortion=(double *) RelinquishMagickMemory(channel_distortion);
return(status);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% G e t I m a g e C h a n n e l D i s t o r t i o n s %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% GetImageChannelDistrortion() compares the image channels of an image to a
% reconstructed image and returns the specified distortion metric for each
% channel.
%
% The format of the CompareImageChannels method is:
%
% double *GetImageChannelDistortions(const Image *image,
% const Image *reconstruct_image,const MetricType metric,
% ExceptionInfo *exception)
%
% A description of each parameter follows:
%
% o image: the image.
%
% o reconstruct_image: the reconstruct image.
%
% o metric: the metric.
%
% o exception: return any errors or warnings in this structure.
%
*/
MagickExport double *GetImageChannelDistortions(Image *image,
const Image *reconstruct_image,const MetricType metric,
ExceptionInfo *exception)
{
double
*channel_distortion;
MagickBooleanType
status;
size_t
length;
assert(image != (Image *) NULL);
assert(image->signature == MagickSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
assert(reconstruct_image != (const Image *) NULL);
assert(reconstruct_image->signature == MagickSignature);
if (image->debug != MagickFalse)
(void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
if ((reconstruct_image->columns != image->columns) ||
(reconstruct_image->rows != image->rows))
{
(void) ThrowMagickException(&image->exception,GetMagickModule(),
ImageError,"ImageSizeDiffers","`%s'",image->filename);
return((double *) NULL);
}
/*
Get image distortion.
*/
length=AllChannels+1UL;
channel_distortion=(double *) AcquireQuantumMemory(length,
sizeof(*channel_distortion));
if (channel_distortion == (double *) NULL)
ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
(void) ResetMagickMemory(channel_distortion,0,length*
sizeof(*channel_distortion));
switch (metric)
{
case AbsoluteErrorMetric:
{
status=GetAbsoluteError(image,reconstruct_image,AllChannels,
channel_distortion,exception);
break;
}
case MeanAbsoluteErrorMetric:
{
status=GetMeanAbsoluteError(image,reconstruct_image,AllChannels,
channel_distortion,exception);
break;
}
case MeanErrorPerPixelMetric:
{
status=GetMeanErrorPerPixel(image,reconstruct_image,AllChannels,
channel_distortion,exception);
break;
}
case MeanSquaredErrorMetric:
{
status=GetMeanSquaredError(image,reconstruct_image,AllChannels,
channel_distortion,exception);
break;
}
case PeakAbsoluteErrorMetric:
default:
{
status=GetPeakAbsoluteError(image,reconstruct_image,AllChannels,
channel_distortion,exception);
break;
}
case PeakSignalToNoiseRatioMetric:
{
status=GetPeakSignalToNoiseRatio(image,reconstruct_image,AllChannels,
channel_distortion,exception);
break;
}
case RootMeanSquaredErrorMetric:
{
status=GetRootMeanSquaredError(image,reconstruct_image,AllChannels,
channel_distortion,exception);
break;
}
}
return(channel_distortion);
}
/*
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
% %
% %
% I s I m a g e s E q u a l %
% %
% %
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% IsImagesEqual() measures the difference between colors at each pixel
% location of two images. A value other than 0 means the colors match
% exactly. Otherwise an error measure is computed by summing over all
% pixels in an image the distance squared in RGB space between each image
% pixel and its corresponding pixel in the reconstruct image. The error
% measure is assigned to these image members:
%
% o mean_error_per_pixel: The mean error for any single pixel in
% the image.
%
% o normalized_mean_error: The normalized mean quantization error for
% any single pixel in the image. This distance measure is normalized to
% a range between 0 and 1. It is independent of the range of red, green,
% and blue values in the image.
%
% o normalized_maximum_error: The normalized maximum quantization
% error for any single pixel in the image. This distance measure is
% normalized to a range between 0 and 1. It is independent of the range
% of red, green, and blue values in your image.
%
% A small normalized mean square error, accessed as
% image->normalized_mean_error, suggests the images are very similar in
% spatial layout and color.
%
% The format of the IsImagesEqual method is:
%
% MagickBooleanType IsImagesEqual(Image *image,
% const Image *reconstruct_image)
%
% A description of each parameter follows.
%
% o image: the image.
%
% o reconstruct_image: the reconstruct image.
%
*/
MagickExport MagickBooleanType IsImagesEqual(Image *image,
const Image *reconstruct_image)
{
long
y;
MagickBooleanType
status;
MagickRealType
area,
maximum_error,
mean_error,
mean_error_per_pixel;
ViewInfo
*image_view,
*reconstruct_view;
assert(image != (Image *) NULL);
assert(image->signature == MagickSignature);
assert(reconstruct_image != (const Image *) NULL);
assert(reconstruct_image->signature == MagickSignature);
if ((reconstruct_image->columns != image->columns) ||
(reconstruct_image->rows != image->rows))
ThrowBinaryException(ImageError,"ImageSizeDiffers",image->filename);
area=0.0;
maximum_error=0.0;
mean_error_per_pixel=0.0;
mean_error=0.0;
image_view=AcquireCacheView(image);
reconstruct_view=AcquireCacheView(reconstruct_image);
for (y=0; y < (long) image->rows; y++)
{
register const IndexPacket
*indexes,
*reconstruct_indexes;
register const PixelPacket
*p,
*q;
register long
x;
p=GetCacheViewVirtualPixels(image_view,0,y,image->columns,1,&image->exception);
q=GetCacheViewVirtualPixels(reconstruct_view,0,y,reconstruct_image->columns,1,
&image->exception);
if ((p == (const PixelPacket *) NULL) || (q == (const PixelPacket *) NULL))
break;
indexes=GetCacheViewVirtualIndexQueue(image_view);
reconstruct_indexes=GetCacheViewVirtualIndexQueue(reconstruct_view);
for (x=0; x < (long) image->columns; x++)
{
MagickRealType
distance;
distance=fabs(p->red-(double) q->red);
mean_error_per_pixel+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
distance=fabs(p->green-(double) q->green);
mean_error_per_pixel+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
distance=fabs(p->blue-(double) q->blue);
mean_error_per_pixel+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
if (image->matte != MagickFalse)
{
distance=fabs(p->opacity-(double) q->opacity);
mean_error_per_pixel+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
}
if ((image->colorspace == CMYKColorspace) &&
(reconstruct_image->colorspace == CMYKColorspace))
{
distance=fabs(indexes[x]-(double) reconstruct_indexes[x]);
mean_error_per_pixel+=distance;
mean_error+=distance*distance;
if (distance > maximum_error)
maximum_error=distance;
area++;
}
p++;
q++;
}
}
reconstruct_view=DestroyCacheView(reconstruct_view);
image_view=DestroyCacheView(image_view);
image->error.mean_error_per_pixel=(double) (mean_error_per_pixel/area);
image->error.normalized_mean_error=(double) (QuantumScale*QuantumScale*
mean_error/area);
image->error.normalized_maximum_error=(double) (QuantumScale*maximum_error);
status=image->error.mean_error_per_pixel == 0.0 ? MagickTrue : MagickFalse;
return(status);
}
|
timestep.c | #include <stddef.h>
#include <string.h>
#include <stdint.h>
#include <omp.h>
#include <math.h>
#include "geometry.h"
#include "bench.h"
#include "phy.h"
#include "core_kernel.h"
/*
Calculate a time step for each cell
Note that this routine assumes conservative variables
Local time stepping, loop over faces and calculate time step as:
cdt = V / (sum(|u.n| + c.area)
This is time step for CFL=1
Late it will be multiplied by CFL
*/
static void
_KRN_ComputeTimeStep(
const size_t nnodes,
const size_t nsnodes,
const size_t nfnodes,
const uint32_t bsz,
const uint32_t *nsptr,
const uint32_t *nfptr,
const double *s_xyz0,
const double *s_xyz1,
const double *s_xyz2,
const double *f_xyz0,
const double *f_xyz1,
const double *f_xyz2,
const uint32_t *ie,
const uint32_t *part,
const uint32_t *n0,
const uint32_t *n1,
const double *x0,
const double *x1,
const double *x2,
const double *x3,
const double cfl,
const double *q,
double *cdt)
{
memset(cdt, 0, nnodes * sizeof(double));
#pragma omp parallel
{
uint32_t i;
const uint32_t t = (uint32_t) omp_get_thread_num();
const uint32_t ie0 = ie[t];
const uint32_t ie1 = ie[t+1];
for(i = ie0; i < ie1; i++)
{
const double xn = x0[i];
const double yn = x1[i];
const double zn = x2[i];
const double ln = x3[i];
const double xnorm = xn * ln;
const double ynorm = yn * ln;
const double znorm = zn * ln;
const uint32_t node0 = n0[i];
const uint32_t node1 = n1[i];
const uint32_t idx0 = (unsigned int) bsz * node0;
const uint32_t idx1 = (unsigned int) bsz * node1;
/* Get average values on face */
const double u = 0.5f * (q[idx0 + 1] + q[idx1 + 1]); // u
const double v = 0.5f * (q[idx0 + 2] + q[idx1 + 2]); // v
const double w = 0.5f * (q[idx0 + 3] + q[idx1 + 3]); // w
const double ubar = xn * u + yn * v + zn * w;
const double c = sqrt(ubar * ubar + B);
double term = u * xnorm;
term += v * ynorm;
term += w * znorm;
term = fabs(term) + c * ln;
cdt[node0] = (part[node0] == t) ? cdt[node0] + term : cdt[node0];
cdt[node1] = (part[node1] == t) ? cdt[node1] + term : cdt[node1];
}
#pragma omp barrier
#pragma omp for
for(i = 0; i < nsnodes; i++)
{
const uint32_t n = nsptr[i];
const double xn = s_xyz0[i];
const double yn = s_xyz1[i];
const double zn = s_xyz2[i];
const double ln = sqrt(xn * xn + yn * yn + zn * zn);
const double u = q[bsz * n + 1];
const double v = q[bsz * n + 2];
const double w = q[bsz * n + 3];
const double ubar = u * xn + v * yn + w * zn;
const double ubar_ = ubar / ln;
const double c = sqrt(ubar_ * ubar_ + B);
const double Vn = fabs(ubar) + c * ln;
cdt[n] += Vn;
}
#pragma omp barrier
#pragma omp for
for(i = 0; i < nfnodes; i++)
{
const uint32_t n = nfptr[i];
const double xn = f_xyz0[i];
const double yn = f_xyz1[i];
const double zn = f_xyz2[i];
const double ln = sqrt(xn * xn + yn * yn + zn * zn);
const double u = q[bsz * n + 1];
const double v = q[bsz * n + 2];
const double w = q[bsz * n + 3];
const double ubar = u * xn + v * yn + w * zn;
const double ubar_ = ubar / ln;
const double c = sqrt(ubar_ * ubar_ + B);
const double Vn = fabs(ubar) + c * ln;
cdt[n] += Vn;
}
#pragma omp barrier
#pragma omp for
for(i = 0; i < nnodes; i++) cdt[i] /= cfl;
}
}
void
ComputeTimeStep(const double cfl, GEOMETRY *g)
{
BENCH start_bench = rdbench();
_KRN_ComputeTimeStep(
g->n->sz,
g->b->s->sz,
g->b->f->sz,
g->c->b,
g->b->s->nptr,
g->b->f->nptr,
g->b->s->xyz->x0,
g->b->s->xyz->x1,
g->b->s->xyz->x2,
g->b->f->xyz->x0,
g->b->f->xyz->x1,
g->b->f->xyz->x2,
g->s->i,
g->n->part,
g->e->eptr->n0,
g->e->eptr->n1,
g->e->xyzn->x0,
g->e->xyzn->x1,
g->e->xyzn->x2,
g->e->xyzn->x3,
cfl,
g->q->q,
g->n->cdt
);
fun3d_log(start_bench, KERNEL_FLUX);
} |
GB_binop__bclr_uint8.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__bclr_uint8
// A.*B function (eWiseMult): GB_AemultB__bclr_uint8
// A*D function (colscale): (none)
// D*A function (rowscale): (node)
// C+=B function (dense accum): GB_Cdense_accumB__bclr_uint8
// C+=b function (dense accum): GB_Cdense_accumb__bclr_uint8
// C+=A+B function (dense ewise3): (none)
// C=A+B function (dense ewise3): GB_Cdense_ewise3_noaccum__bclr_uint8
// C=scalar+B GB_bind1st__bclr_uint8
// C=scalar+B' GB_bind1st_tran__bclr_uint8
// C=A+scalar GB_bind2nd__bclr_uint8
// C=A'+scalar GB_bind2nd_tran__bclr_uint8
// C type: uint8_t
// A type: uint8_t
// B,b type: uint8_t
// BinaryOp: cij = GB_BITCLR (aij, bij, uint8_t, 8)
#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) \
uint8_t aij = Ax [pA]
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB) \
uint8_t bij = Bx [pB]
// 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) \
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 = GB_BITCLR (x, y, uint8_t, 8) ;
// 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_BCLR || GxB_NO_UINT8 || GxB_NO_BCLR_UINT8)
//------------------------------------------------------------------------------
// 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__bclr_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__bclr_uint8
(
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__bclr_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
//------------------------------------------------------------------------------
#if 0
GrB_Info (none)
(
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
uint8_t *GB_RESTRICT Cx = (uint8_t *) C->x ;
#include "GB_AxB_colscale_meta.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
#if 0
GrB_Info (node)
(
GrB_Matrix C,
const GrB_Matrix D, bool D_is_pattern,
const GrB_Matrix B, bool B_is_pattern,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint8_t *GB_RESTRICT Cx = (uint8_t *) C->x ;
#include "GB_AxB_rowscale_meta.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
//------------------------------------------------------------------------------
// eWiseAdd: C = A+B or C<M> = A+B
//------------------------------------------------------------------------------
GrB_Info GB_AaddB__bclr_uint8
(
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__bclr_uint8
(
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__bclr_uint8
(
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
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 < anz ; p++)
{
uint8_t bij = Bx [p] ;
Cx [p] = GB_BITCLR (x, bij, uint8_t, 8) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB_bind2nd__bclr_uint8
(
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 ;
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++)
{
uint8_t aij = Ax [p] ;
Cx [p] = GB_BITCLR (aij, y, uint8_t, 8) ;
}
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) \
{ \
uint8_t aij = Ax [pA] ; \
Cx [pC] = GB_BITCLR (x, aij, uint8_t, 8) ; \
}
GrB_Info GB_bind1st_tran__bclr_uint8
(
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 \
uint8_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint8_t x = (*((const uint8_t *) x_input)) ;
#define GB_PHASE_2_OF_2
#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 typcasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
uint8_t aij = Ax [pA] ; \
Cx [pC] = GB_BITCLR (aij, y, uint8_t, 8) ; \
}
GrB_Info GB_bind2nd_tran__bclr_uint8
(
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
uint8_t y = (*((const uint8_t *) y_input)) ;
#define GB_PHASE_2_OF_2
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
utils.h | /* Copyright (C) 2010 The Trustees of Indiana University. */
/* */
/* Use, modification and distribution is subject to the Boost Software */
/* License, Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at */
/* http://www.boost.org/LICENSE_1_0.txt) */
/* */
/* Authors: Jeremiah Willcock */
/* Andrew Lumsdaine */
#ifndef UTILS_H
#define UTILS_H
#ifndef __STDC_CONSTANT_MACROS
#define __STDC_CONSTANT_MACROS
#endif
#include <stddef.h>
#include <stdint.h>
#include <assert.h>
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#ifdef GRAPH_GENERATOR_MPI
#include <mpi.h>
#endif
#ifdef GRAPH_GENERATOR_OMP
#include <omp.h>
#endif
#include "splittable_mrg.h"
#include "kronecker.h"
#if defined(_OPENMP)
#define OMP(x_) _Pragma(x_)
#else
#define OMP(x_)
#endif
#ifdef __cplusplus
extern "C" {
#endif
#if defined(HAVE_LIBNUMA)
#include <numa.h>
static int numa_inited = 0;
static int numa_avail = -1;
void * xmalloc (size_t n) {
void * out;
if (!numa_inited) {
OMP("omp critical") {
numa_inited = 1;
numa_avail = numa_available ();
}
}
if (numa_avail)
out = numa_alloc (sz);
else
out = malloc (sz);
if (!out) {
fprintf(stderr, "Out of memory trying to allocate %zu byte(s)\n", sz);
abort ();
}
return out;
}
void * xcalloc (size_t n, size_t sz) {
void * out;
if (!numa_inited) {
OMP("omp critical") {
numa_inited = 1;
numa_avail = numa_available ();
}
}
if (numa_avail) {
size_t to_alloc;
to_alloc = n * sz;
if (to_alloc < n || to_alloc < sz) {
fprintf(stderr,
"Allocation size out of range for %zu items of %zu byte(s)\n",
n, sz);
abort ();
}
out = numa_alloc (n * sz);
#if defined(_OPENMP)
#pragma omp parallel for
for (size_t k = 0; k < n; ++k)
memset (out + k * sz, 0, sz);
#else
memset (out, 0, n * sz);
#endif
} else
out = calloc (n, sz);
if (!out) {
fprintf(stderr,
"Out of memory trying to allocate/clear %zu items of %zu byte(s)\n",
n, sz);
abort ();
}
return out;
}
void xfree (void * p, size_t sz) {
if (!p) return;
if (numa_avail >= 0)
numa_free (p, sz);
else
free (p);
}
#else
void * xmalloc (size_t sz) {
void * out;
out = malloc (sz);
if (!out) {
fprintf(stderr, "Out of memory trying to allocate %zu byte(s)\n", sz);
abort ();
}
return out;
}
void * xcalloc (size_t n, size_t sz) {
void * out;
out = calloc (n, sz);
if (!out) {
fprintf(stderr,
"Out of memory trying to allocate/clear %zu items of %zu byte(s)\n",
n, sz);
abort ();
}
return out;
}
void xfree (void * p, [[maybe_unused]] size_t sz) {
free (p);
}
#endif
// void* xrealloc(void* p, size_t nbytes); /* In utils.c */
// uint_fast64_t random_up_to(mrg_state* st, uint_fast64_t n);
void make_mrg_seed(uint64_t userseed1, uint64_t userseed2, uint_fast32_t* seed) {
seed[0] = (uint32_t)(userseed1 & UINT32_C(0x3FFFFFFF)) + 1;
seed[1] = (uint32_t)((userseed1 >> 30) & UINT32_C(0x3FFFFFFF)) + 1;
seed[2] = (uint32_t)(userseed2 & UINT32_C(0x3FFFFFFF)) + 1;
seed[3] = (uint32_t)((userseed2 >> 30) & UINT32_C(0x3FFFFFFF)) + 1;
seed[4] = (uint32_t)((userseed2 >> 60) << 4) + (uint32_t)(userseed1 >> 60) + 1;
}
#ifdef __cplusplus
}
#endif
#endif /* UTILS_H */
|
update_ops_named_SWAP.c |
#include "constant.h"
#include "update_ops.h"
#include "utility.h"
#ifdef _OPENMP
#include <omp.h>
#endif
#ifdef _USE_SIMD
#ifdef _MSC_VER
#include <intrin.h>
#else
#include <x86intrin.h>
#endif
#endif
//void SWAP_gate_old_single(UINT target_qubit_index_0, UINT target_qubit_index_1, CTYPE *state, ITYPE dim);
//void SWAP_gate_old_parallel(UINT target_qubit_index_0, UINT target_qubit_index_1, CTYPE *state, ITYPE dim);
//void SWAP_gate_single(UINT target_qubit_index_0, UINT target_qubit_index_1, CTYPE *state, ITYPE dim);
//void SWAP_gate_parallel(UINT target_qubit_index_0, UINT target_qubit_index_1, CTYPE *state, ITYPE dim);
void SWAP_gate(UINT target_qubit_index_0, UINT target_qubit_index_1, CTYPE *state, ITYPE dim) {
//SWAP_gate_old_single(target_qubit_index_0, target_qubit_index_1, state, dim);
//SWAP_gate_old_parallel(target_qubit_index_0, target_qubit_index_1, state, dim);
//SWAP_gate_single(target_qubit_index_0, target_qubit_index_1, state, dim);
//SWAP_gate_single_unroll(target_qubit_index_0, target_qubit_index_1, state, dim);
//SWAP_gate_single_simd(target_qubit_index_0, target_qubit_index_1, state, dim);
//SWAP_gate_parallel(target_qubit_index_0, target_qubit_index_1, state, dim);
//return;
#ifdef _USE_SIMD
#ifdef _OPENMP
UINT threshold = 13;
if (dim < (((ITYPE)1) << threshold)) {
SWAP_gate_single_simd(target_qubit_index_0, target_qubit_index_1, state, dim);
}
else {
SWAP_gate_parallel_simd(target_qubit_index_0, target_qubit_index_1, state, dim);
}
#else
SWAP_gate_single_simd(target_qubit_index_0, target_qubit_index_1, state, dim);
#endif
#else
#ifdef _OPENMP
UINT threshold = 13;
if (dim < (((ITYPE)1) << threshold)) {
SWAP_gate_single_unroll(target_qubit_index_0, target_qubit_index_1, state, dim);
}
else {
SWAP_gate_parallel_unroll(target_qubit_index_0, target_qubit_index_1, state, dim);
}
#else
SWAP_gate_single_unroll(target_qubit_index_0, target_qubit_index_1, state, dim);
#endif
#endif
}
void SWAP_gate_single_unroll(UINT target_qubit_index_0, UINT target_qubit_index_1, CTYPE *state, ITYPE dim) {
const ITYPE loop_dim = dim / 4;
const ITYPE mask_0 = 1ULL << target_qubit_index_0;
const ITYPE mask_1 = 1ULL << target_qubit_index_1;
const ITYPE mask = mask_0 + mask_1;
const UINT min_qubit_index = get_min_ui(target_qubit_index_0, target_qubit_index_1);
const UINT max_qubit_index = get_max_ui(target_qubit_index_0, target_qubit_index_1);
const ITYPE min_qubit_mask = 1ULL << min_qubit_index;
const ITYPE max_qubit_mask = 1ULL << (max_qubit_index - 1);
const ITYPE low_mask = min_qubit_mask - 1;
const ITYPE mid_mask = (max_qubit_mask - 1) ^ low_mask;
const ITYPE high_mask = ~(max_qubit_mask - 1);
ITYPE state_index = 0;
if (target_qubit_index_0 == 0 || target_qubit_index_1 == 0) {
for (state_index = 0; state_index < loop_dim; ++state_index) {
ITYPE basis_index_0 = (state_index&low_mask)
+ ((state_index&mid_mask) << 1)
+ ((state_index&high_mask) << 2)
+ mask_0;
ITYPE basis_index_1 = basis_index_0 ^ mask;
CTYPE temp = state[basis_index_0];
state[basis_index_0] = state[basis_index_1];
state[basis_index_1] = temp;
}
}else{
// a,a+1 is swapped to a^m, a^m+1, respectively
for (state_index = 0; state_index < loop_dim; state_index+=2) {
ITYPE basis_index_0 = (state_index&low_mask)
+ ((state_index&mid_mask) << 1)
+ ((state_index&high_mask) << 2)
+ mask_0;
ITYPE basis_index_1 = basis_index_0 ^ mask;
CTYPE temp0 = state[basis_index_0];
CTYPE temp1 = state[basis_index_0 + 1];
state[basis_index_0] = state[basis_index_1];
state[basis_index_0 + 1] = state[basis_index_1 + 1];
state[basis_index_1] = temp0;
state[basis_index_1 + 1] = temp1;
}
}
}
#ifdef _OPENMP
void SWAP_gate_parallel_unroll(UINT target_qubit_index_0, UINT target_qubit_index_1, CTYPE *state, ITYPE dim) {
const ITYPE loop_dim = dim / 4;
const ITYPE mask_0 = 1ULL << target_qubit_index_0;
const ITYPE mask_1 = 1ULL << target_qubit_index_1;
const ITYPE mask = mask_0 + mask_1;
const UINT min_qubit_index = get_min_ui(target_qubit_index_0, target_qubit_index_1);
const UINT max_qubit_index = get_max_ui(target_qubit_index_0, target_qubit_index_1);
const ITYPE min_qubit_mask = 1ULL << min_qubit_index;
const ITYPE max_qubit_mask = 1ULL << (max_qubit_index - 1);
const ITYPE low_mask = min_qubit_mask - 1;
const ITYPE mid_mask = (max_qubit_mask - 1) ^ low_mask;
const ITYPE high_mask = ~(max_qubit_mask - 1);
ITYPE state_index = 0;
if (target_qubit_index_0 == 0 || target_qubit_index_1 == 0) {
#pragma omp parallel for
for (state_index = 0; state_index < loop_dim; ++state_index) {
ITYPE basis_index_0 = (state_index&low_mask)
+ ((state_index&mid_mask) << 1)
+ ((state_index&high_mask) << 2)
+ mask_0;
ITYPE basis_index_1 = basis_index_0 ^ mask;
CTYPE temp = state[basis_index_0];
state[basis_index_0] = state[basis_index_1];
state[basis_index_1] = temp;
}
}
else {
// a,a+1 is swapped to a^m, a^m+1, respectively
#pragma omp parallel for
for (state_index = 0; state_index < loop_dim; state_index += 2) {
ITYPE basis_index_0 = (state_index&low_mask)
+ ((state_index&mid_mask) << 1)
+ ((state_index&high_mask) << 2)
+ mask_0;
ITYPE basis_index_1 = basis_index_0 ^ mask;
CTYPE temp0 = state[basis_index_0];
CTYPE temp1 = state[basis_index_0 + 1];
state[basis_index_0] = state[basis_index_1];
state[basis_index_0 + 1] = state[basis_index_1 + 1];
state[basis_index_1] = temp0;
state[basis_index_1 + 1] = temp1;
}
}
}
#endif
#ifdef _USE_SIMD
void SWAP_gate_single_simd(UINT target_qubit_index_0, UINT target_qubit_index_1, CTYPE *state, ITYPE dim) {
const ITYPE loop_dim = dim / 4;
const ITYPE mask_0 = 1ULL << target_qubit_index_0;
const ITYPE mask_1 = 1ULL << target_qubit_index_1;
const ITYPE mask = mask_0 + mask_1;
const UINT min_qubit_index = get_min_ui(target_qubit_index_0, target_qubit_index_1);
const UINT max_qubit_index = get_max_ui(target_qubit_index_0, target_qubit_index_1);
const ITYPE min_qubit_mask = 1ULL << min_qubit_index;
const ITYPE max_qubit_mask = 1ULL << (max_qubit_index - 1);
const ITYPE low_mask = min_qubit_mask - 1;
const ITYPE mid_mask = (max_qubit_mask - 1) ^ low_mask;
const ITYPE high_mask = ~(max_qubit_mask - 1);
ITYPE state_index = 0;
if (target_qubit_index_0 == 0 || target_qubit_index_1 == 0) {
for (state_index = 0; state_index < loop_dim; ++state_index) {
ITYPE basis_index_0 = (state_index&low_mask)
+ ((state_index&mid_mask) << 1)
+ ((state_index&high_mask) << 2)
+ mask_0;
ITYPE basis_index_1 = basis_index_0 ^ mask;
CTYPE temp = state[basis_index_0];
state[basis_index_0] = state[basis_index_1];
state[basis_index_1] = temp;
}
}
else {
// a,a+1 is swapped to a^m, a^m+1, respectively
for (state_index = 0; state_index < loop_dim; state_index += 2) {
ITYPE basis_index_0 = (state_index&low_mask)
+ ((state_index&mid_mask) << 1)
+ ((state_index&high_mask) << 2)
+ mask_0;
ITYPE basis_index_1 = basis_index_0 ^ mask;
double* ptr0 = (double*)(state + basis_index_0);
double* ptr1 = (double*)(state + basis_index_1);
__m256d data0 = _mm256_loadu_pd(ptr0);
__m256d data1 = _mm256_loadu_pd(ptr1);
_mm256_storeu_pd(ptr1, data0);
_mm256_storeu_pd(ptr0, data1);
}
}
}
#ifdef _OPENMP
void SWAP_gate_parallel_simd(UINT target_qubit_index_0, UINT target_qubit_index_1, CTYPE *state, ITYPE dim) {
const ITYPE loop_dim = dim / 4;
const ITYPE mask_0 = 1ULL << target_qubit_index_0;
const ITYPE mask_1 = 1ULL << target_qubit_index_1;
const ITYPE mask = mask_0 + mask_1;
const UINT min_qubit_index = get_min_ui(target_qubit_index_0, target_qubit_index_1);
const UINT max_qubit_index = get_max_ui(target_qubit_index_0, target_qubit_index_1);
const ITYPE min_qubit_mask = 1ULL << min_qubit_index;
const ITYPE max_qubit_mask = 1ULL << (max_qubit_index - 1);
const ITYPE low_mask = min_qubit_mask - 1;
const ITYPE mid_mask = (max_qubit_mask - 1) ^ low_mask;
const ITYPE high_mask = ~(max_qubit_mask - 1);
ITYPE state_index = 0;
if (target_qubit_index_0 == 0 || target_qubit_index_1 == 0) {
#pragma omp parallel for
for (state_index = 0; state_index < loop_dim; ++state_index) {
ITYPE basis_index_0 = (state_index&low_mask)
+ ((state_index&mid_mask) << 1)
+ ((state_index&high_mask) << 2)
+ mask_0;
ITYPE basis_index_1 = basis_index_0 ^ mask;
CTYPE temp = state[basis_index_0];
state[basis_index_0] = state[basis_index_1];
state[basis_index_1] = temp;
}
}
else {
// a,a+1 is swapped to a^m, a^m+1, respectively
#pragma omp parallel for
for (state_index = 0; state_index < loop_dim; state_index += 2) {
ITYPE basis_index_0 = (state_index&low_mask)
+ ((state_index&mid_mask) << 1)
+ ((state_index&high_mask) << 2)
+ mask_0;
ITYPE basis_index_1 = basis_index_0 ^ mask;
double* ptr0 = (double*)(state + basis_index_0);
double* ptr1 = (double*)(state + basis_index_1);
__m256d data0 = _mm256_loadu_pd(ptr0);
__m256d data1 = _mm256_loadu_pd(ptr1);
_mm256_storeu_pd(ptr1, data0);
_mm256_storeu_pd(ptr0, data1);
}
}
}
#endif
#endif
/*
#ifdef _OPENMP
void SWAP_gate_parallel(UINT target_qubit_index_0, UINT target_qubit_index_1, CTYPE *state, ITYPE dim) {
const ITYPE loop_dim = dim / 4;
const ITYPE mask_0 = 1ULL << target_qubit_index_0;
const ITYPE mask_1 = 1ULL << target_qubit_index_1;
const ITYPE mask = mask_0 + mask_1;
const UINT min_qubit_index = get_min_ui(target_qubit_index_0, target_qubit_index_1);
const UINT max_qubit_index = get_max_ui(target_qubit_index_0, target_qubit_index_1);
const ITYPE min_qubit_mask = 1ULL << min_qubit_index;
const ITYPE max_qubit_mask = 1ULL << (max_qubit_index - 1);
const ITYPE low_mask = min_qubit_mask - 1;
const ITYPE mid_mask = (max_qubit_mask - 1) ^ low_mask;
const ITYPE high_mask = ~(max_qubit_mask - 1);
ITYPE state_index = 0;
#pragma omp parallel for
for (state_index = 0; state_index < loop_dim; ++state_index) {
ITYPE basis_index_0 = (state_index&low_mask)
+ ((state_index&mid_mask) << 1)
+ ((state_index&high_mask) << 2)
+ mask_0;
ITYPE basis_index_1 = basis_index_0 ^ mask;
CTYPE temp = state[basis_index_0];
state[basis_index_0] = state[basis_index_1];
state[basis_index_1] = temp;
}
}
#endif
void SWAP_gate_old_single(UINT target_qubit_index_0, UINT target_qubit_index_1, CTYPE *state, ITYPE dim) {
const ITYPE loop_dim = dim / 4;
const UINT min_qubit_index = get_min_ui(target_qubit_index_0, target_qubit_index_1);
const UINT max_qubit_index = get_max_ui(target_qubit_index_0, target_qubit_index_1);
const ITYPE min_qubit_mask = 1ULL << min_qubit_index;
const ITYPE max_qubit_mask = 1ULL << max_qubit_index;
const ITYPE target_mask_0 = 1ULL << target_qubit_index_0;
const ITYPE target_mask_1 = 1ULL << target_qubit_index_1;
ITYPE state_index;
for (state_index = 0; state_index < loop_dim; ++state_index) {
ITYPE basis_insert_only_min = insert_zero_to_basis_index(state_index, min_qubit_mask, min_qubit_index);
ITYPE basis_00 = insert_zero_to_basis_index(basis_insert_only_min, max_qubit_mask, max_qubit_index);
ITYPE basis_01 = basis_00 ^ target_mask_0;
ITYPE basis_10 = basis_00 ^ target_mask_1;
swap_amplitude(state, basis_01, basis_10);
}
}
#ifdef _OPENMP
void SWAP_gate_old_parallel(UINT target_qubit_index_0, UINT target_qubit_index_1, CTYPE *state, ITYPE dim) {
const ITYPE loop_dim = dim / 4;
const UINT min_qubit_index = get_min_ui(target_qubit_index_0, target_qubit_index_1);
const UINT max_qubit_index = get_max_ui(target_qubit_index_0, target_qubit_index_1);
const ITYPE min_qubit_mask = 1ULL << min_qubit_index;
const ITYPE max_qubit_mask = 1ULL << max_qubit_index;
const ITYPE target_mask_0 = 1ULL << target_qubit_index_0;
const ITYPE target_mask_1 = 1ULL << target_qubit_index_1;
ITYPE state_index;
#pragma omp parallel for
for (state_index = 0; state_index < loop_dim; ++state_index) {
ITYPE basis_insert_only_min = insert_zero_to_basis_index(state_index, min_qubit_mask, min_qubit_index);
ITYPE basis_00 = insert_zero_to_basis_index(basis_insert_only_min, max_qubit_mask, max_qubit_index);
ITYPE basis_01 = basis_00 ^ target_mask_0;
ITYPE basis_10 = basis_00 ^ target_mask_1;
swap_amplitude(state, basis_01, basis_10);
}
}
#endif
void SWAP_gate_single(UINT target_qubit_index_0, UINT target_qubit_index_1, CTYPE *state, ITYPE dim) {
const ITYPE loop_dim = dim / 4;
const ITYPE mask_0 = 1ULL << target_qubit_index_0;
const ITYPE mask_1 = 1ULL << target_qubit_index_1;
const ITYPE mask = mask_0 + mask_1;
const UINT min_qubit_index = get_min_ui(target_qubit_index_0, target_qubit_index_1);
const UINT max_qubit_index = get_max_ui(target_qubit_index_0, target_qubit_index_1);
const ITYPE min_qubit_mask = 1ULL << min_qubit_index;
const ITYPE max_qubit_mask = 1ULL << (max_qubit_index-1);
const ITYPE low_mask = min_qubit_mask-1;
const ITYPE mid_mask = (max_qubit_mask-1)^low_mask;
const ITYPE high_mask = ~(max_qubit_mask - 1);
ITYPE state_index = 0;
for (state_index = 0; state_index < loop_dim; ++state_index) {
ITYPE basis_index_0 = (state_index&low_mask)
+ ((state_index&mid_mask) << 1)
+ ((state_index&high_mask) << 2)
+ mask_0;
ITYPE basis_index_1 = basis_index_0 ^ mask;
CTYPE temp = state[basis_index_0];
state[basis_index_0] = state[basis_index_1];
state[basis_index_1] = temp;
}
}
*/
|
Utils.h | // Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
#pragma once
#include <string>
#include <vector>
#include "inc/Core/Common.h"
#include <algorithm>
#include "inc/Core/Common/DistanceUtils.h"
#include "inc/Core/Common/QueryResultSet.h"
#include "inc/Core/VectorSet.h"
#include "inc/SSDServing/VectorSearch/Options.h"
#include "inc/Helper/SimpleIniReader.h"
namespace SPTAG {
namespace SSDServing {
template<typename T>
float Std(T* nums, size_t size) {
float var = 0;
float mean = 0;
for (size_t i = 0; i < size; i++)
{
mean += nums[i] / static_cast<float>(size);
}
for (size_t i = 0; i < size; i++)
{
float temp = nums[i] - mean;
var += (float) pow(temp, 2.0);
}
var /= static_cast<float>(size);
return sqrt(var);
}
struct Neighbor
{
SPTAG::SizeType key;
float dist;
Neighbor(SPTAG::SizeType k, float d);
Neighbor(const Neighbor& o);
bool operator < (const Neighbor& another) const;
};
void writeTruthFile(const std::string truthFile, size_t queryNumber, const int K, std::vector<std::vector<SPTAG::SizeType>>& truthset, std::vector<std::vector<float>>& distset, SPTAG::TruthFileType TFT);
template<typename T>
void GenerateTruth(std::shared_ptr<VectorSet> querySet, std::shared_ptr<VectorSet> vectorSet, const std::string truthFile,
const SPTAG::DistCalcMethod distMethod, const int K, const SPTAG::TruthFileType p_truthFileType) {
if (querySet->Dimension() != vectorSet->Dimension() && !SPTAG::COMMON::DistanceUtils::Quantizer)
{
LOG(Helper::LogLevel::LL_Error, "query and vector have different dimensions.");
exit(-1);
}
std::vector< std::vector<SPTAG::SizeType> > truthset(querySet->Count(), std::vector<SPTAG::SizeType>(K, 0));
std::vector< std::vector<float> > distset(querySet->Count(), std::vector<float>(K, 0));
#pragma omp parallel for
for (int i = 0; i < querySet->Count(); ++i)
{
SPTAG::COMMON::QueryResultSet<T> query((const T*)(querySet->GetVector(i)), K);
for (SPTAG::SizeType j = 0; j < vectorSet->Count(); j++)
{
float dist = SPTAG::COMMON::DistanceUtils::ComputeDistance<T>(query.GetQuantizedTarget(), reinterpret_cast<T*>(vectorSet->GetVector(j)), vectorSet->Dimension(), distMethod);
query.AddPoint(j, dist);
}
query.SortResult();
for (int k = 0; k < K; k++)
{
truthset[i][k] = (query.GetResult(k))->VID;
distset[i][k] = (query.GetResult(k))->Dist;
}
}
writeTruthFile(truthFile, querySet->Count(), K, truthset, distset, p_truthFileType);
auto ptr = SPTAG::f_createIO();
if (ptr == nullptr || !ptr->Initialize((truthFile + ".dist.bin").c_str(), std::ios::out | std::ios::binary)) {
LOG(Helper::LogLevel::LL_Error, "Fail to create the file:%s\n", (truthFile + ".dist.bin").c_str());
exit(1);
}
int int32_queryNumber = (int)querySet->Count();
ptr->WriteBinary(4, (char*)&int32_queryNumber);
ptr->WriteBinary(4, (char*)&K);
for (size_t i = 0; i < int32_queryNumber; i++)
{
for (int k = 0; k < K; k++) {
if (ptr->WriteBinary(4, (char*)(&(truthset[i][k]))) != 4) {
LOG(Helper::LogLevel::LL_Error, "Fail to write the truth dist file!\n");
exit(1);
}
if (ptr->WriteBinary(4, (char*)(&(distset[i][k]))) != 4) {
LOG(Helper::LogLevel::LL_Error, "Fail to write the truth dist file!\n");
exit(1);
}
}
}
}
bool readSearchSSDSec(const char* iniFile, VectorSearch::Options& opts);
bool readSearchSSDSec(const Helper::IniReader& iniFileReader, VectorSearch::Options& opts);
}
} |
black_kernel.h | #pragma omp target teams distribute parallel for collapse(2) thread_limit(BLOCK_SIZE)
for (int col = 1; col < NUM+1; col++)
{
for (int row = 1; row < NUM/2+1; row++)
{
int NUM_2 = NUM >> 1;
Real p_ij = pres_black(col, row);
Real p_im1j = pres_red(col - 1, row);
Real p_ip1j = pres_red(col + 1, row);
Real p_ijm1 = pres_red(col, row - ((col + 1) & 1));
Real p_ijp1 = pres_red(col, row + (col & 1));
// right-hand side
Real rhs = (((F(col, (2 * row) - ((col + 1) & 1))
- F(col - 1, (2 * row) - ((col + 1) & 1))) / dx)
+ ((G(col, (2 * row) - ((col + 1) & 1))
- G(col, (2 * row) - ((col + 1) & 1) - 1)) / dy)) / dt;
pres_black(col, row) = p_ij * (ONE - omega) + omega *
(((p_ip1j + p_im1j) / (dx * dx)) + ((p_ijp1 + p_ijm1) / (dy * dy)) -
rhs) / ((TWO / (dx * dx)) + (TWO / (dy * dy)));
}
}
|
GB_msort_2.c | //------------------------------------------------------------------------------
// GB_msort_2: sort a 2-by-n list of integers, using A[0:1][ ] as the key
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// A parallel mergesort of an array of 2-by-n integers. Each key
// consists of two integers.
#include "GB_msort_2.h"
//------------------------------------------------------------------------------
// GB_msort_2_binary_search: binary search for the pivot
//------------------------------------------------------------------------------
// The Pivot value is Y [pivot], and a binary search for the Pivot is made in
// the array X [p_pstart...p_end-1], which is sorted in non-decreasing order on
// input. The return value is pleft, where
//
// X [p_start ... pleft-1] <= Pivot and
// X [pleft ... p_end-1] >= Pivot holds.
//
// pleft is returned in the range p_start to p_end. If pleft is p_start, then
// the Pivot is smaller than all entries in X [p_start...p_end-1], and the left
// list X [p_start...pleft-1] is empty. If pleft is p_end, then the Pivot is
// larger than all entries in X [p_start...p_end-1], and the right list X
// [pleft...p_end-1] is empty.
static int64_t GB_msort_2_binary_search // return pleft
(
const int64_t *restrict Y_0, // Pivot is Y [pivot]
const int64_t *restrict Y_1,
const int64_t pivot,
const int64_t *restrict X_0, // search in X [p_start..p_end_-1]
const int64_t *restrict X_1,
const int64_t p_start,
const int64_t p_end
)
{
//--------------------------------------------------------------------------
// find where the Pivot appears in X
//--------------------------------------------------------------------------
// binary search of X [p_start...p_end-1] for the Pivot
int64_t pleft = p_start ;
int64_t pright = p_end - 1 ;
while (pleft < pright)
{
int64_t pmiddle = (pleft + pright) >> 1 ;
// less = (X [pmiddle] < Pivot)
bool less = GB_lt_2 (X_0, X_1, pmiddle,
Y_0, Y_1, pivot) ;
pleft = less ? (pmiddle+1) : pleft ;
pright = less ? pright : pmiddle ;
}
// binary search is narrowed down to a single item
// or it has found the list is empty:
ASSERT (pleft == pright || pleft == pright + 1) ;
// If found is true then X [pleft == pright] == Pivot. If duplicates
// appear then X [pleft] is any one of the entries equal to the Pivot
// in the list. If found is false then
// X [p_start ... pleft-1] < Pivot and
// X [pleft+1 ... p_end-1] > Pivot holds.
// The value X [pleft] may be either < or > Pivot.
bool found = (pleft == pright) && GB_eq_2 (X_0, X_1, pleft,
Y_0, Y_1, pivot) ;
// Modify pleft and pright:
if (!found && (pleft == pright))
{
if (GB_lt_2 (X_0, X_1, pleft,
Y_0, Y_1, pivot))
{
pleft++ ;
}
else
{
// pright++ ; // (not needed)
}
}
//--------------------------------------------------------------------------
// return result
//--------------------------------------------------------------------------
// If found is false then
// X [p_start ... pleft-1] < Pivot and
// X [pleft ... p_end-1] > Pivot holds,
// and pleft-1 == pright
// If X has no duplicates, then whether or not Pivot is found,
// X [p_start ... pleft-1] < Pivot and
// X [pleft ... p_end-1] >= Pivot holds.
// If X has duplicates, then whether or not Pivot is found,
// X [p_start ... pleft-1] <= Pivot and
// X [pleft ... p_end-1] >= Pivot holds.
return (pleft) ;
}
//------------------------------------------------------------------------------
// GB_msort_2_create_merge_tasks
//------------------------------------------------------------------------------
// Recursively constructs ntasks tasks to merge two arrays, Left and Right,
// into Sresult, where Left is L [pL_start...pL_end-1], Right is R
// [pR_start...pR_end-1], and Sresult is S [pS_start...pS_start+total_work-1],
// and where total_work is the total size of Left and Right.
//
// Task tid will merge L [L_task [tid] ... L_task [tid] + L_len [tid] - 1] and
// R [R_task [tid] ... R_task [tid] + R_len [tid] -1] into the merged output
// array S [S_task [tid] ... ]. The task tids created are t0 to
// t0+ntasks-1.
void GB_msort_2_create_merge_tasks
(
// output:
int64_t *restrict L_task, // L_task [t0...t0+ntasks-1] computed
int64_t *restrict L_len, // L_len [t0...t0+ntasks-1] computed
int64_t *restrict R_task, // R_task [t0...t0+ntasks-1] computed
int64_t *restrict R_len, // R_len [t0...t0+ntasks-1] computed
int64_t *restrict S_task, // S_task [t0...t0+ntasks-1] computed
// input:
const int t0, // first task tid to create
const int ntasks, // # of tasks to create
const int64_t pS_start, // merge into S [pS_start...]
const int64_t *restrict L_0, // Left = L [pL_start...pL_end-1]
const int64_t *restrict L_1,
const int64_t pL_start,
const int64_t pL_end,
const int64_t *restrict R_0, // Right = R [pR_start...pR_end-1]
const int64_t *restrict R_1,
const int64_t pR_start,
const int64_t pR_end
)
{
//--------------------------------------------------------------------------
// get problem size
//--------------------------------------------------------------------------
int64_t nleft = pL_end - pL_start ; // size of Left array
int64_t nright = pR_end - pR_start ; // size of Right array
int64_t total_work = nleft + nright ; // total work to do
ASSERT (ntasks >= 1) ;
ASSERT (total_work > 0) ;
//--------------------------------------------------------------------------
// create the tasks
//--------------------------------------------------------------------------
if (ntasks == 1)
{
//----------------------------------------------------------------------
// a single task will merge all of Left and Right into Sresult
//----------------------------------------------------------------------
L_task [t0] = pL_start ; L_len [t0] = nleft ;
R_task [t0] = pR_start ; R_len [t0] = nright ;
S_task [t0] = pS_start ;
}
else
{
//----------------------------------------------------------------------
// partition the Left and Right arrays for multiple merge tasks
//----------------------------------------------------------------------
int64_t pleft, pright ;
if (nleft >= nright)
{
// split Left in half, and search for its pivot in Right
pleft = (pL_end + pL_start) >> 1 ;
pright = GB_msort_2_binary_search (
L_0, L_1, pleft,
R_0, R_1, pR_start, pR_end) ;
}
else
{
// split Right in half, and search for its pivot in Left
pright = (pR_end + pR_start) >> 1 ;
pleft = GB_msort_2_binary_search (
R_0, R_1, pright,
L_0, L_1, pL_start, pL_end) ;
}
//----------------------------------------------------------------------
// partition the tasks according to the work of each partition
//----------------------------------------------------------------------
// work0 is the total work in the first partition
int64_t work0 = (pleft - pL_start) + (pright - pR_start) ;
int ntasks0 = (int) round ((double) ntasks *
(((double) work0) / ((double) total_work))) ;
// ensure at least one task is assigned to each partition
ntasks0 = GB_IMAX (ntasks0, 1) ;
ntasks0 = GB_IMIN (ntasks0, ntasks-1) ;
int ntasks1 = ntasks - ntasks0 ;
//----------------------------------------------------------------------
// assign ntasks0 to the first half
//----------------------------------------------------------------------
// ntasks0 tasks merge L [pL_start...pleft-1] and R [pR_start..pright-1]
// into the result S [pS_start...work0-1].
GB_msort_2_create_merge_tasks (
L_task, L_len, R_task, R_len, S_task, t0, ntasks0, pS_start,
L_0, L_1, pL_start, pleft,
R_0, R_1, pR_start, pright) ;
//----------------------------------------------------------------------
// assign ntasks1 to the second half
//----------------------------------------------------------------------
// ntasks1 tasks merge L [pleft...pL_end-1] and R [pright...pR_end-1]
// into the result S [pS_start+work0...pS_start+total_work].
int t1 = t0 + ntasks0 ; // first task id of the second set of tasks
int64_t pS_start1 = pS_start + work0 ; // 2nd set starts here in S
GB_msort_2_create_merge_tasks (
L_task, L_len, R_task, R_len, S_task, t1, ntasks1, pS_start1,
L_0, L_1, pleft, pL_end,
R_0, R_1, pright, pR_end) ;
}
}
//------------------------------------------------------------------------------
// GB_msort_2_merge: merge two sorted lists via a single thread
//------------------------------------------------------------------------------
// merge Left [0..nleft-1] and Right [0..nright-1] into S [0..nleft+nright-1] */
static void GB_msort_2_merge
(
int64_t *restrict S_0, // output of length nleft + nright
int64_t *restrict S_1,
const int64_t *restrict Left_0, // left input of length nleft
const int64_t *restrict Left_1,
const int64_t nleft,
const int64_t *restrict Right_0, // right input of length nright
const int64_t *restrict Right_1,
const int64_t nright
)
{
int64_t p, pleft, pright ;
// merge the two inputs, Left and Right, while both inputs exist
for (p = 0, pleft = 0, pright = 0 ; pleft < nleft && pright < nright ; p++)
{
if (GB_lt_2 (Left_0, Left_1, pleft,
Right_0, Right_1, pright))
{
// S [p] = Left [pleft++]
S_0 [p] = Left_0 [pleft] ;
S_1 [p] = Left_1 [pleft] ;
pleft++ ;
}
else
{
// S [p] = Right [pright++]
S_0 [p] = Right_0 [pright] ;
S_1 [p] = Right_1 [pright] ;
pright++ ;
}
}
// either input is exhausted; copy the remaining list into S
if (pleft < nleft)
{
int64_t nremaining = (nleft - pleft) ;
memcpy (S_0 + p, Left_0 + pleft, nremaining * sizeof (int64_t)) ;
memcpy (S_1 + p, Left_1 + pleft, nremaining * sizeof (int64_t)) ;
}
else if (pright < nright)
{
int64_t nremaining = (nright - pright) ;
memcpy (S_0 + p, Right_0 + pright, nremaining * sizeof (int64_t)) ;
memcpy (S_1 + p, Right_1 + pright, nremaining * sizeof (int64_t)) ;
}
}
//------------------------------------------------------------------------------
// GB_msort_2: parallel mergesort
//------------------------------------------------------------------------------
GB_PUBLIC
GrB_Info GB_msort_2 // sort array A of size 2-by-n, using 2 keys (A [0:1][])
(
int64_t *restrict A_0, // size n array
int64_t *restrict A_1, // size n array
const int64_t n,
int nthreads // # of threads to use
)
{
//--------------------------------------------------------------------------
// handle small problems with a single thread
//--------------------------------------------------------------------------
if (nthreads <= 1 || n <= GB_BASECASE)
{
// sequential quicksort
GB_qsort_2 (A_0, A_1, n) ;
return (GrB_SUCCESS) ;
}
//--------------------------------------------------------------------------
// determine # of tasks
//--------------------------------------------------------------------------
// determine the number of levels to create, which must always be an
// even number. The # of levels is chosen to ensure that the # of leaves
// of the task tree is between 4*nthreads and 16*nthreads.
// 2 to 4 threads: 4 levels, 16 qsort leaves
// 5 to 16 threads: 6 levels, 64 qsort leaves
// 17 to 64 threads: 8 levels, 256 qsort leaves
// 65 to 256 threads: 10 levels, 1024 qsort leaves
// 256 to 1024 threads: 12 levels, 4096 qsort leaves
// ...
int k = (int) (2 + 2 * ceil (log2 ((double) nthreads) / 2)) ;
int ntasks = 1 << k ;
//--------------------------------------------------------------------------
// allocate workspace
//--------------------------------------------------------------------------
int64_t *restrict W = NULL ; size_t W_size = 0 ;
W = GB_MALLOC_WERK (2*n + 6*ntasks + 1, int64_t, &W_size) ;
if (W == NULL)
{
// out of memory
return (GrB_OUT_OF_MEMORY) ;
}
int64_t *T = W ;
int64_t *restrict W_0 = T ; T += n ;
int64_t *restrict W_1 = T ; T += n ;
int64_t *restrict L_task = T ; T += ntasks ;
int64_t *restrict L_len = T ; T += ntasks ;
int64_t *restrict R_task = T ; T += ntasks ;
int64_t *restrict R_len = T ; T += ntasks ;
int64_t *restrict S_task = T ; T += ntasks ;
int64_t *restrict Slice = T ; T += (ntasks+1) ;
//--------------------------------------------------------------------------
// partition and sort the leaves
//--------------------------------------------------------------------------
GB_eslice (Slice, n, ntasks) ;
int tid ;
#pragma omp parallel for num_threads(nthreads) schedule(dynamic,1)
for (tid = 0 ; tid < ntasks ; tid++)
{
int64_t leaf = Slice [tid] ;
int64_t leafsize = Slice [tid+1] - leaf ;
GB_qsort_2 (A_0 + leaf, A_1 + leaf, leafsize) ;
}
//--------------------------------------------------------------------------
// merge each level
//--------------------------------------------------------------------------
int nt = 1 ;
for ( ; k >= 2 ; k -= 2)
{
//----------------------------------------------------------------------
// merge level k into level k-1, from A into W
//----------------------------------------------------------------------
// TODO: skip k and k-1 for each group of 4 sublists of A if they are
// already sorted with respect to each other.
// this could be done in parallel if ntasks was large
for (int tid = 0 ; tid < ntasks ; tid += 2*nt)
{
// create 2*nt tasks to merge two A sublists into one W sublist
GB_msort_2_create_merge_tasks (
L_task, L_len, R_task, R_len, S_task, tid, 2*nt, Slice [tid],
A_0, A_1, Slice [tid], Slice [tid+nt],
A_0, A_1, Slice [tid+nt], Slice [tid+2*nt]) ;
}
#pragma omp parallel for num_threads(nthreads) schedule(dynamic,1)
for (tid = 0 ; tid < ntasks ; tid++)
{
// merge A [pL...pL+nL-1] and A [pR...pR+nR-1] into W [pS..]
int64_t pL = L_task [tid], nL = L_len [tid] ;
int64_t pR = R_task [tid], nR = R_len [tid] ;
int64_t pS = S_task [tid] ;
GB_msort_2_merge (
W_0 + pS, W_1 + pS,
A_0 + pL, A_1 + pL, nL,
A_0 + pR, A_1 + pR, nR) ;
}
nt = 2*nt ;
//----------------------------------------------------------------------
// merge level k-1 into level k-2, from W into A
//----------------------------------------------------------------------
// this could be done in parallel if ntasks was large
for (int tid = 0 ; tid < ntasks ; tid += 2*nt)
{
// create 2*nt tasks to merge two W sublists into one A sublist
GB_msort_2_create_merge_tasks (
L_task, L_len, R_task, R_len, S_task, tid, 2*nt, Slice [tid],
W_0, W_1, Slice [tid], Slice [tid+nt],
W_0, W_1, Slice [tid+nt], Slice [tid+2*nt]) ;
}
#pragma omp parallel for num_threads(nthreads) schedule(dynamic,1)
for (tid = 0 ; tid < ntasks ; tid++)
{
// merge A [pL...pL+nL-1] and A [pR...pR+nR-1] into W [pS..]
int64_t pL = L_task [tid], nL = L_len [tid] ;
int64_t pR = R_task [tid], nR = R_len [tid] ;
int64_t pS = S_task [tid] ;
GB_msort_2_merge (
A_0 + pS, A_1 + pS,
W_0 + pL, W_1 + pL, nL,
W_0 + pR, W_1 + pR, nR) ;
}
nt = 2*nt ;
}
//--------------------------------------------------------------------------
// free workspace and return result
//--------------------------------------------------------------------------
GB_FREE_WERK (&W, W_size) ;
return (GrB_SUCCESS) ;
}
|
GB_unop__ainv_int16_int16.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary 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_control.h"
#include "GB_atomics.h"
#include "GB_unop__include.h"
// C=unop(A) is defined by the following types and operators:
// op(A) function: GB (_unop_apply__ainv_int16_int16)
// op(A') function: GB (_unop_tran__ainv_int16_int16)
// C type: int16_t
// A type: int16_t
// cast: int16_t cij = aij
// unaryop: cij = -aij
#define GB_ATYPE \
int16_t
#define GB_CTYPE \
int16_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) \
int16_t z = aij ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
int16_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
int16_t z = aij ; \
Cx [pC] = -z ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_AINV || GxB_NO_INT16)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_apply__ainv_int16_int16)
(
int16_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 ;
if (Ab == NULL)
{
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
int16_t aij = Ax [p] ;
int16_t z = aij ;
Cx [p] = -z ;
}
}
else
{
// bitmap case, no transpose; A->b already memcpy'd into C->b
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!Ab [p]) continue ;
int16_t aij = Ax [p] ;
int16_t z = aij ;
Cx [p] = -z ;
}
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_tran__ainv_int16_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
|
GB_unaryop__identity_int32_bool.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__identity_int32_bool
// op(A') function: GB_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_CASTING(z, x) \
int32_t z = (int32_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_IDENTITY || GxB_NO_INT32 || GxB_NO_BOOL)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__identity_int32_bool
(
int32_t *restrict Cx,
const bool *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__identity_int32_bool
(
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
|
custom_functions.h | //
// Project Name: Kratos
// Last Modified by: $Author: G.Casas (gcasas@cimmne.upc.edu) $
// Date: $Date: 2011-6-13 08:56:42 $
// Revision: $Revision: 1.5 $
//
//
//README::::look to the key word "VERSION" if you want to find all the points where you have to change something so that you can pass from a kdtree to a bin data search structure;
#if !defined(KRATOS_CUSTOM_FUNCTIONS)
#define KRATOS_CUSTOM_FUNCTIONS
// /* External includes */
#ifdef _OPENMP
#include <omp.h>
#endif
// System includes
#include <vector>
// Project includes
#include "includes/model_part.h"
#include "utilities/timer.h"
#include "utilities/openmp_utils.h"
#include "processes/find_elements_neighbours_process.h"
#include "processes/find_nodal_neighbours_process.h"
//Database includes
#include "custom_utilities/search/discrete_particle_configure.h"
#include "includes/define.h"
#include "../../DEMApplication/custom_elements/discrete_element.h"
#include "custom_elements/swimming_particle.h"
#include "custom_utilities/AuxiliaryFunctions.h"
#include "../../DEMApplication/custom_elements/spheric_particle.h"
#include "../swimming_DEM_application.h"
#include "../../../kratos/utilities/geometry_utilities.h"
namespace Kratos
{
template <std::size_t TDim>
class CustomFunctionsCalculator
{
public:
typedef ModelPart::ElementsContainerType::iterator ElementIterator;
typedef ModelPart::NodesContainerType::iterator NodeIterator;
typedef ModelPart::NodesContainerType NodesArrayType;
KRATOS_CLASS_POINTER_DEFINITION(CustomFunctionsCalculator);
CustomFunctionsCalculator(): mPressuresFilled(false), mFirstGradientRecovery(true), mFirstLaplacianRecovery(true), mSomeCloudsDontWork(false), mCalculatingTheGradient(false), mCalculatingTheLaplacian(false), mFirstTimeAppending(true){}
/// Calculator
virtual ~CustomFunctionsCalculator(){}
/// Default calculator
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
void CalculatePressureGradient(ModelPart& r_model_part)
{
for (NodeIterator inode = r_model_part.NodesBegin(); inode != r_model_part.NodesEnd(); ++inode){
noalias(inode->FastGetSolutionStepValue(PRESSURE_GRADIENT)) = ZeroVector(3);
}
array_1d <double, 3> grad = ZeroVector(3); // its dimension is always 3
array_1d <double, TDim + 1 > elemental_pressures;
array_1d <double, TDim + 1 > N; // shape functions vector
BoundedMatrix<double, TDim + 1, TDim> DN_DX;
for (ModelPart::ElementIterator ielem = r_model_part.ElementsBegin(); ielem != r_model_part.ElementsEnd(); ++ielem){
// computing the shape function derivatives
Geometry<Node<3> >& geom = ielem->GetGeometry();
double Volume;
GeometryUtils::CalculateGeometryData(geom, DN_DX, N, Volume);
// getting the pressure gradients;
for (unsigned int i = 0; i < TDim + 1; ++i){
elemental_pressures[i] = geom[i].FastGetSolutionStepValue(PRESSURE);
}
array_1d <double, TDim> grad_aux = prod(trans(DN_DX), elemental_pressures); // its dimension may be 2
for (unsigned int i = 0; i < TDim; ++i){
grad[i] = grad_aux[i];
}
double nodal_area = Volume / static_cast<double>(TDim + 1);
grad *= nodal_area;
for (unsigned int i = 0; i < TDim + 1; ++i){
geom[i].FastGetSolutionStepValue(PRESSURE_GRADIENT) += grad;
}
}
for (NodeIterator inode = r_model_part.NodesBegin(); inode != r_model_part.NodesEnd(); ++inode){
inode->FastGetSolutionStepValue(PRESSURE_GRADIENT) /= inode->FastGetSolutionStepValue(NODAL_AREA);
}
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
// This function assesses the stationarity based on the pressure field variation.
// Its tolerance applies to the non-dimensional pressure variation between consecutive
// measurements.
bool AssessStationarity(ModelPart& r_model_part, const double& tol)
{
if (!mPressuresFilled){
PerformFirstStepComputations(r_model_part);
return(false);
}
else {
double max_pressure_change_rate = 0.0; // measure of stationarity
double mean_celerity = 0.0; // used to adimensionalize the time step
// filling up mPressures and calculating the mean velocities and the maximum nodal pressure change
unsigned int i = 0;
for (NodeIterator inode = r_model_part.NodesBegin(); inode != r_model_part.NodesEnd(); ++inode){
const array_1d<double, 3>& velocity = inode->FastGetSolutionStepValue(VELOCITY);
mean_celerity += SWIMMING_MODULUS_3(velocity);
const double new_pressure = inode->FastGetSolutionStepValue(PRESSURE);
double& old_pressure = mPressures[i];
const double delta_p = std::abs(new_pressure - old_pressure);
max_pressure_change_rate = std::max(delta_p, max_pressure_change_rate);
old_pressure = new_pressure;
++i;
}
mean_celerity /= i;
const double delta_t = r_model_part.GetProcessInfo()[TIME] - mLastMeasurementTime;
if (delta_t > 0.0){
max_pressure_change_rate /= delta_t;
// calculating coefficients for adimensionalization of the pressure change rate
const double characteristic_length = std::pow(mTotalDomainVolume, 1.0 / 3); // characteristic length of the model. Should be improved: a hydraulic radius or such
const double reciprocal_of_characteristic_time = mean_celerity / characteristic_length;
const double pressure_spatial_variation = GetRangeWithinVector(mPressures);
mLastPressureVariation = pressure_spatial_variation;
const double characteristic_pressure_variation = 0.5 * (pressure_spatial_variation + mLastPressureVariation);
if (characteristic_pressure_variation == 0.0 || reciprocal_of_characteristic_time == 0.0){ // unlikely
std::cout << "Uniform problem: stationarity check being performed with dimensional values...! " << "\n";
if (max_pressure_change_rate <= tol){ // go with the absolute value
return true;
}
}
max_pressure_change_rate /= reciprocal_of_characteristic_time * characteristic_pressure_variation ;
}
else {
KRATOS_THROW_ERROR(std::runtime_error, "Trying to calculate pressure variations between two coincident time steps! (null time variation since last recorded time)","");
}
std::cout << "++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++" << "\n";
std::cout << "The stationarity condition tolerance is " << "\n";
KRATOS_WATCH(tol)
std::cout << "The stationarity residual is now " << "\n";
KRATOS_WATCH(max_pressure_change_rate)
std::cout << "++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++" << "\n";
return max_pressure_change_rate <= tol;
}
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
double CalculateDomainVolume(ModelPart& r_fluid_model_part)
{
OpenMPUtils::CreatePartition(OpenMPUtils::GetNumThreads(), r_fluid_model_part.GetCommunicator().LocalMesh().Elements().size(), mElementsPartition);
double added_volume = 0.0;
#pragma omp parallel for reduction(+ : added_volume)
for (int k = 0; k < OpenMPUtils::GetNumThreads(); ++k){
for (ElementIterator it = GetElementPartitionBegin(r_fluid_model_part, k); it != GetElementPartitionEnd(r_fluid_model_part, k); ++it){
added_volume += CalculateElementalVolume(it->GetGeometry());
}
}
return added_volume;
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
// this function assumes linear elements are used
void CalculateTotalHydrodynamicForceOnParticles(ModelPart& r_dem_model_part, array_1d <double, 3>& force)
{
OpenMPUtils::CreatePartition(OpenMPUtils::GetNumThreads(), r_dem_model_part.GetCommunicator().LocalMesh().Elements().size(), mElementsPartition);
std::vector<array_1d <double, 3> > added_force_vect;
added_force_vect.resize(OpenMPUtils::GetNumThreads());
for (unsigned int k = 0; k < added_force_vect.size(); ++k){
added_force_vect[k] = ZeroVector(3);
}
#pragma omp parallel for
for (int k = 0; k < OpenMPUtils::GetNumThreads(); ++k){
for (ElementIterator it = GetElementPartitionBegin(r_dem_model_part, k); it != GetElementPartitionEnd(r_dem_model_part, k); ++it){
Geometry< Node<3> >& geom = it->GetGeometry();
array_1d <double, 3> element_force;
if (geom[0].SolutionStepsDataHas(HYDRODYNAMIC_FORCE)){
element_force = geom[0].FastGetSolutionStepValue(HYDRODYNAMIC_FORCE);
}
else {
element_force = ZeroVector(3);
}
added_force_vect[k] += element_force;
}
}
force = added_force_vect[0];
for (unsigned int k = 1; k < added_force_vect.size(); ++k){
force += added_force_vect[k];
}
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
// this function assumes linear elements are used
void CalculateTotalHydrodynamicForceOnFluid(ModelPart& r_fluid_model_part, array_1d <double, 3>& instantaneous_force, array_1d <double, 3>& mean_force)
{
OpenMPUtils::CreatePartition(OpenMPUtils::GetNumThreads(), r_fluid_model_part.GetCommunicator().LocalMesh().Elements().size(), mElementsPartition);
std::vector<array_1d <double, 3> > added_force_vect;
added_force_vect.resize(OpenMPUtils::GetNumThreads());
std::vector<array_1d <double, 3> > added_mean_force_vect;
added_mean_force_vect.resize(OpenMPUtils::GetNumThreads());
for (unsigned int k = 0; k < added_force_vect.size(); ++k){
added_force_vect[k] = ZeroVector(3);
added_mean_force_vect[k] = ZeroVector(3);
}
#pragma omp parallel for
for (int k = 0; k < OpenMPUtils::GetNumThreads(); ++k){
for (ElementIterator it = GetElementPartitionBegin(r_fluid_model_part, k); it != GetElementPartitionEnd(r_fluid_model_part, k); ++it){
Geometry< Node<3> >& geom = it->GetGeometry();
double element_volume;
array_1d <double, 3> element_force;
array_1d <double, 3> element_mean_force;
if (geom[0].SolutionStepsDataHas(HYDRODYNAMIC_REACTION) && geom[0].SolutionStepsDataHas(FLUID_FRACTION)){
element_force = CalculateVectorIntegralOfLinearInterpolationPerUnitFluidMass(geom, HYDRODYNAMIC_REACTION, element_volume);
}
else {
element_force = ZeroVector(3);
}
if (geom[0].SolutionStepsDataHas(MEAN_HYDRODYNAMIC_REACTION) && geom[0].SolutionStepsDataHas(FLUID_FRACTION)){
element_mean_force = CalculateVectorIntegralOfLinearInterpolationPerUnitFluidMass(geom, MEAN_HYDRODYNAMIC_REACTION, element_volume);
}
else {
element_mean_force = ZeroVector(3);
}
added_force_vect[k] += element_force;
added_mean_force_vect[k] += element_mean_force;
}
}
instantaneous_force = added_force_vect[0];
mean_force = added_force_vect[0];
for (unsigned int k = 1; k < added_force_vect.size(); ++k){
instantaneous_force += added_force_vect[k];
mean_force += added_mean_force_vect[k];
}
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
// this function assumes linear elements are used
double CalculateGlobalFluidVolume(ModelPart& r_fluid_model_part)
{
OpenMPUtils::CreatePartition(OpenMPUtils::GetNumThreads(), r_fluid_model_part.GetCommunicator().LocalMesh().Elements().size(), mElementsPartition);
double added_fluid_volume = 0.0;
#pragma omp parallel for reduction(+ : added_fluid_volume)
for (int k = 0; k < OpenMPUtils::GetNumThreads(); ++k){
for (ElementIterator it = GetElementPartitionBegin(r_fluid_model_part, k); it != GetElementPartitionEnd(r_fluid_model_part, k); ++it){
Geometry< Node<3> >& geom = it->GetGeometry();
double element_volume;
double element_fluid_volume;
if (geom[0].SolutionStepsDataHas(FLUID_FRACTION)){
element_fluid_volume = CalculateScalarIntegralOfLinearInterpolation(geom, FLUID_FRACTION, element_volume);
}
else {
element_fluid_volume = CalculateElementalVolume(geom);
}
added_fluid_volume += element_fluid_volume;
}
}
return added_fluid_volume;
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
template<class matrix_T>
double determinant(boost::numeric::ublas::matrix_expression<matrix_T> const& mat_r)
{
double det = 1.0;
matrix_T mLu(mat_r() );
boost::numeric::ublas::permutation_matrix<std::size_t> pivots(mat_r().size1() );
int is_singular = lu_factorize(mLu, pivots);
if (!is_singular)
{
for (std::size_t i=0; i < pivots.size(); ++i)
{
if (pivots(i) != i)
det *= -1.0;
det *= mLu(i,i);
}
}
else
det = 0.0;
return det;
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
const DenseMatrix<double> Inverse(
const DenseMatrix<double>& m)
{
assert(m.size1() == m.size2() && "Can only calculate the inverse of square matrices");
switch(m.size1())
{
case 1:
{
assert(m.size1() == 1 && m.size2() == 1 && "Only for 1x1 matrices");
const double determinant = CalcDeterminant(m);
assert(determinant != 0.0);
assert(m(0,0) != 0.0 && "Cannot take the inverse of matrix [0]");
DenseMatrix<double> n(1,1);
n(0,0) = 1.0 / determinant;
return n;
}
case 2:
{
assert(m.size1() == 2 && m.size2() == 2 && "Only for 2x2 matrices");
const double determinant = CalcDeterminant(m);
assert(determinant != 0.0);
const double a = m(0,0);
const double b = m(0,1);
const double c = m(1,0);
const double d = m(1,1);
DenseMatrix<double> n(2,2);
n(0,0) = d / determinant;
n(0,1) = -b / determinant;
n(1,0) = -c / determinant;
n(1,1) = a / determinant;
return n;
}
case 3:
{
assert(m.size1() == 3 && m.size2() == 3 && "Only for 3x3 matrices");
const double determinant = CalcDeterminant(m);
assert(determinant != 0.0);
const double a = m(0,0);
const double b = m(0,1);
const double c = m(0,2);
const double d = m(1,0);
const double e = m(1,1);
const double f = m(1,2);
const double g = m(2,0);
const double h = m(2,1);
const double k = m(2,2);
DenseMatrix<double> n(3,3);
const double new_a = ((e*k)-(f*h)) / determinant;
const double new_b = -((d*k)-(f*g)) / determinant;
const double new_c = ((d*h)-(e*g)) / determinant;
const double new_d = -((b*k)-(c*h)) / determinant;
const double new_e = ((a*k)-(c*g)) / determinant;
const double new_f = -((a*h)-(b*g)) / determinant;
const double new_g = ((b*f)-(c*e)) / determinant;
const double new_h = -((a*f)-(c*d)) / determinant;
const double new_k = ((a*e)-(b*d)) / determinant;
n(0,0) = new_a;
n(1,0) = new_b;
n(2,0) = new_c;
n(0,1) = new_d;
n(1,1) = new_e;
n(2,1) = new_f;
n(0,2) = new_g;
n(1,2) = new_h;
n(2,2) = new_k;
return n;
}
default:
{
//Use blockwise inversion
//Matrix::Chop returns a std::vector
//[ A at [0] B at [1] ]
//[ C at [2] D at [4] ]
const std::vector<DenseMatrix<double> > v = Chop(m);
const DenseMatrix<double>& a = v[0];
assert(a.size1() == a.size2());
const DenseMatrix<double> a_inv = Inverse(a);
const DenseMatrix<double>& b = v[1];
const DenseMatrix<double>& c = v[2];
const DenseMatrix<double>& d = v[3];
const DenseMatrix<double> term
= d
- prod(
DenseMatrix<double>(prod(c,a_inv)),
b
);
const DenseMatrix<double> term_inv = Inverse(term);
const DenseMatrix<double> new_a
= a_inv
+ DenseMatrix<double>(prod(
DenseMatrix<double>(prod(
DenseMatrix<double>(prod(
DenseMatrix<double>(prod(
a_inv,
b)),
term_inv)),
c)),
a_inv));
const DenseMatrix<double> new_b
=
- DenseMatrix<double>(prod(
DenseMatrix<double>(prod(
a_inv,
b)),
term_inv));
const DenseMatrix<double> new_c
=
- DenseMatrix<double>(prod(
DenseMatrix<double>(prod(
term_inv,
c)),
a_inv));
const DenseMatrix<double> new_d = term_inv;
std::vector<DenseMatrix<double> > w;
w.push_back(new_a);
w.push_back(new_b);
w.push_back(new_c);
w.push_back(new_d);
const DenseMatrix<double> result = Unchop(w);
return result;
}
}
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
void CopyValuesFromFirstToSecond(ModelPart& r_model_part, const Variable<double>& origin_variable, const Variable<double>& destination_variable)
{
#pragma omp parallel for
for (int i = 0; i < (int)r_model_part.Nodes().size(); ++i){
ModelPart::NodesContainerType::iterator i_particle = r_model_part.NodesBegin() + i;
Node<3>::Pointer p_node = *(i_particle.base());
double& destination_value = p_node->FastGetSolutionStepValue(destination_variable);
const double& origin_value = p_node->FastGetSolutionStepValue(origin_variable);
destination_value = origin_value;
}
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
void CopyValuesFromFirstToSecond(ModelPart& r_model_part, const VariableComponent<VectorComponentAdaptor<array_1d<double, 3> > >& origin_variable, const VariableComponent<VectorComponentAdaptor<array_1d<double, 3> > >& destination_variable)
{
#pragma omp parallel for
for (int i = 0; i < (int)r_model_part.Nodes().size(); ++i){
ModelPart::NodesContainerType::iterator i_particle = r_model_part.NodesBegin() + i;
Node<3>::Pointer p_node = *(i_particle.base());
double& destination_value = p_node->FastGetSolutionStepValue(destination_variable);
const double origin_value = p_node->FastGetSolutionStepValue(origin_variable);
destination_value = origin_value;
}
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
void CopyValuesFromFirstToSecond(ModelPart& r_model_part, const Variable<array_1d<double, 3>>& origin_variable, const Variable<array_1d<double, 3>>& destination_variable)
{
#pragma omp parallel for
for (int i = 0; i < (int)r_model_part.Nodes().size(); ++i){
ModelPart::NodesContainerType::iterator i_particle = r_model_part.NodesBegin() + i;
Node<3>::Pointer p_node = *(i_particle.base());
array_1d<double, 3>& destination_value = p_node->FastGetSolutionStepValue(destination_variable);
const array_1d<double, 3>& origin_value = p_node->FastGetSolutionStepValue(origin_variable);
noalias(destination_value) = origin_value;
}
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
void SetValueOfAllNotes(ModelPart& r_model_part, const double& value, const Variable<double>& destination_variable)
{
#pragma omp parallel for
for (int i = 0; i < (int)r_model_part.Nodes().size(); ++i){
ModelPart::NodesContainerType::iterator i_particle = r_model_part.NodesBegin() + i;
Node<3>::Pointer p_node = *(i_particle.base());
double& destination_value = p_node->FastGetSolutionStepValue(destination_variable);
destination_value = value;
}
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
void SetValueOfAllNotes(ModelPart& r_model_part, const array_1d<double, 3>& value, const Variable<array_1d<double, 3>>& destination_variable)
{
#pragma omp parallel for
for (int i = 0; i < (int)r_model_part.Nodes().size(); ++i){
ModelPart::NodesContainerType::iterator i_particle = r_model_part.NodesBegin() + i;
Node<3>::Pointer p_node = *(i_particle.base());
array_1d<double, 3>& destination_value = p_node->FastGetSolutionStepValue(destination_variable);
noalias(destination_value) = value;
}
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
private:
bool mPressuresFilled;
bool mFirstGradientRecovery;
bool mFirstLaplacianRecovery;
bool mSomeCloudsDontWork;
bool mCalculatingTheGradient;
bool mCalculatingTheLaplacian;
bool mFirstTimeAppending;
double mLastMeasurementTime;
double mLastPressureVariation;
double mTotalDomainVolume;
std::vector<double> mPressures;
std::vector<DenseVector<double> > mFirstRowsOfB;
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
inline double CalculateArea(const double x0, const double y0,
const double x1, const double y1,
const double x2, const double y2)
{
const double x10 = x1 - x0;
const double y10 = y1 - y0;
const double x20 = x2 - x0;
const double y20 = y2 - y0;
const double area = 0.5 * std::abs(x10 * y20 - x20 * y10);
return area;
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
inline double CalculateVol(const double x0, const double y0, const double z0,
const double x1, const double y1, const double z1,
const double x2, const double y2, const double z2,
const double x3, const double y3, const double z3)
{
double x10 = x1 - x0;
double y10 = y1 - y0;
double z10 = z1 - z0;
double x20 = x2 - x0;
double y20 = y2 - y0;
double z20 = z2 - z0;
double x30 = x3 - x0;
double y30 = y3 - y0;
double z30 = z3 - z0;
double detJ = x10 * y20 * z30 - x10 * y30 * z20 +
y10 * z20 * x30 - y10 * x20 * z30 +
z10 * x20 * y30 - z10 * y20 * x30;
return detJ * 0.1666666666666666666666667;
}
//***************************************************************************************************************
//***************************************************************************************************************
double CalculateElementalVolume(const Geometry<Node <3> >& geom)
{
double vol;
if (TDim == 2){
double x0 = geom[0].X();
double y0 = geom[0].Y();
double x1 = geom[1].X();
double y1 = geom[1].Y();
double x2 = geom[2].X();
double y2 = geom[2].Y();
vol = CalculateArea(x0, y0, x1, y1, x2, y2);
}
else {
double x0 = geom[0].X();
double y0 = geom[0].Y();
double z0 = geom[0].Z();
double x1 = geom[1].X();
double y1 = geom[1].Y();
double z1 = geom[1].Z();
double x2 = geom[2].X();
double y2 = geom[2].Y();
double z2 = geom[2].Z();
double x3 = geom[3].X();
double y3 = geom[3].Y();
double z3 = geom[3].Z();
vol = CalculateVol(x0, y0, z0, x1, y1, z1, x2, y2, z2, x3, y3, z3);
}
if (vol == 0.0){
KRATOS_THROW_ERROR(std::logic_error, "element with zero area found with the current geometry ", geom);
}
return vol;
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
double CalculateScalarIntegralOfLinearInterpolation(const Geometry<Node < 3 > >& geom, const Variable<double>& r_var, double& vol)
{
array_1d<double, 4> N;
double x0 = geom[0].X();
double y0 = geom[0].Y();
double z0 = geom[0].Z();
double x1 = geom[1].X();
double y1 = geom[1].Y();
double z1 = geom[1].Z();
double x2 = geom[2].X();
double y2 = geom[2].Y();
double z2 = geom[2].Z();
double x3 = geom[3].X();
double y3 = geom[3].Y();
double z3 = geom[3].Z();
double xc = 0.25 * (x0 + x1 + x2 + x3);
double yc = 0.25 * (y0 + y1 + y2 + y3);
double zc = 0.25 * (z0 + z1 + z2 + z3);
vol = CalculateVol(x0, y0, z0, x1, y1, z1, x2, y2, z2, x3, y3, z3);
if (vol == 0.0){
KRATOS_THROW_ERROR(std::logic_error, "Element with zero area found. Its geometry is given by", geom);
}
N[0] = CalculateVol(x1, y1, z1, x3, y3, z3, x2, y2, z2, xc, yc, zc);
N[1] = CalculateVol(x0, y0, z0, x1, y1, z1, x2, y2, z2, xc, yc, zc);
N[2] = CalculateVol(x3, y3, z3, x1, y1, z1, x0, y0, z0, xc, yc, zc);
N[3] = CalculateVol(x3, y3, z3, x0, y0, z0, x2, y2, z2, xc, yc, zc);
double value_at_gauss_point = N[0] * geom[0].FastGetSolutionStepValue(r_var);
for (unsigned int i = 1; i != 4; ++i){
value_at_gauss_point += N[i] * geom[i].FastGetSolutionStepValue(r_var, 0);
}
return value_at_gauss_point;
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
array_1d <double, 3> CalculateVectorIntegralOfLinearInterpolation(const Geometry<Node < 3 > >& geom, const Variable<array_1d <double, 3> >& r_var, double& vol)
{
array_1d<double, 4> N;
double x0 = geom[0].X();
double y0 = geom[0].Y();
double z0 = geom[0].Z();
double x1 = geom[1].X();
double y1 = geom[1].Y();
double z1 = geom[1].Z();
double x2 = geom[2].X();
double y2 = geom[2].Y();
double z2 = geom[2].Z();
double x3 = geom[3].X();
double y3 = geom[3].Y();
double z3 = geom[3].Z();
double xc = 0.25 * (x0 + x1 + x2 + x3);
double yc = 0.25 * (y0 + y1 + y2 + y3);
double zc = 0.25 * (z0 + z1 + z2 + z3);
vol = CalculateVol(x0, y0, z0, x1, y1, z1, x2, y2, z2, x3, y3, z3);
if (vol == 0.0){
KRATOS_THROW_ERROR(std::logic_error, "Element with zero area found. Its geometry is given by", geom);
}
N[0] = CalculateVol(x1, y1, z1, x3, y3, z3, x2, y2, z2, xc, yc, zc);
N[1] = CalculateVol(x0, y0, z0, x1, y1, z1, x2, y2, z2, xc, yc, zc);
N[2] = CalculateVol(x3, y3, z3, x1, y1, z1, x0, y0, z0, xc, yc, zc);
N[3] = CalculateVol(x3, y3, z3, x0, y0, z0, x2, y2, z2, xc, yc, zc);
array_1d <double, 3> value_at_gauss_point = N[0] * geom[0].FastGetSolutionStepValue(r_var);
for (unsigned int i = 1; i != 4; ++i){
value_at_gauss_point += N[i] * geom[i].FastGetSolutionStepValue(r_var);
}
return value_at_gauss_point;
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
array_1d <double, 3> CalculateVectorIntegralOfLinearInterpolationPerUnitFluidMass(const Geometry<Node < 3 > >& geom, const Variable<array_1d <double, 3> >& r_var, double& vol)
{
array_1d<double, 4> N;
double x0 = geom[0].X();
double y0 = geom[0].Y();
double z0 = geom[0].Z();
double x1 = geom[1].X();
double y1 = geom[1].Y();
double z1 = geom[1].Z();
double x2 = geom[2].X();
double y2 = geom[2].Y();
double z2 = geom[2].Z();
double x3 = geom[3].X();
double y3 = geom[3].Y();
double z3 = geom[3].Z();
double xc = 0.25 * (x0 + x1 + x2 + x3);
double yc = 0.25 * (y0 + y1 + y2 + y3);
double zc = 0.25 * (z0 + z1 + z2 + z3);
vol = CalculateVol(x0, y0, z0, x1, y1, z1, x2, y2, z2, x3, y3, z3);
if (vol == 0.0){
KRATOS_THROW_ERROR(std::logic_error, "Element with zero area found. Its geometry is given by", geom);
}
N[0] = CalculateVol(x1, y1, z1, x3, y3, z3, x2, y2, z2, xc, yc, zc);
N[1] = CalculateVol(x0, y0, z0, x1, y1, z1, x2, y2, z2, xc, yc, zc);
N[2] = CalculateVol(x3, y3, z3, x1, y1, z1, x0, y0, z0, xc, yc, zc);
N[3] = CalculateVol(x3, y3, z3, x0, y0, z0, x2, y2, z2, xc, yc, zc);
array_1d <double, 3> value_at_gauss_point = N[0] * geom[0].FastGetSolutionStepValue(r_var) * geom[0].FastGetSolutionStepValue(DENSITY) * geom[0].FastGetSolutionStepValue(FLUID_FRACTION);
for (unsigned int i = 1; i != 4; ++i){
value_at_gauss_point += N[i] * geom[i].FastGetSolutionStepValue(r_var) * geom[i].FastGetSolutionStepValue(DENSITY) * geom[i].FastGetSolutionStepValue(FLUID_FRACTION);
}
return value_at_gauss_point;
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
void PerformFirstStepComputations(ModelPart& r_model_part)
{
mTotalDomainVolume = CalculateDomainVolume(r_model_part);
mPressures.resize(r_model_part.Nodes().size());
mLastMeasurementTime = r_model_part.GetProcessInfo()[TIME];
unsigned int i = 0;
for (NodeIterator inode = r_model_part.NodesBegin(); inode != r_model_part.NodesEnd(); ++inode) {
mPressures[i] = inode->FastGetSolutionStepValue(PRESSURE);
++i;
}
mPressuresFilled = true;
mLastPressureVariation = GetRangeWithinVector(mPressures);
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
struct IsCloser{
bool operator()(std::pair<unsigned int, double> const& first_pair, std::pair<unsigned int, double> const& second_pair)
{
return(first_pair.second < second_pair.second || (first_pair.second == second_pair.second && first_pair.first < second_pair.first));
}
};
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
inline int Factorial(const unsigned int n){
if (n == 0){
return 1;
}
unsigned int k = n;
for (unsigned int i = n - 1; i > 0; --i){
k *= i;
}
return k;
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
double CalculateTheMaximumEdgeLength(ModelPart& r_model_part)
{
double max_distance_yet = 0.0;
for (ModelPart::ElementIterator ielem = r_model_part.ElementsBegin(); ielem != r_model_part.ElementsEnd(); ++ielem){
Geometry<Node<3> >& geom = ielem->GetGeometry();
unsigned int n_nodes = static_cast<unsigned int>(TDim + 1);
for (unsigned int k = 1; k < n_nodes - 1; ++k){
for (unsigned int i = k; i < n_nodes; ++i){
array_1d <double, 3> delta_i = geom[k - 1] - geom[i];
double distance_2 = DEM_INNER_PRODUCT_3(delta_i, delta_i);
max_distance_yet = max_distance_yet > distance_2 ? max_distance_yet : distance_2;
}
}
}
return(std::sqrt(max_distance_yet));
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
double CalculateTheMinumumEdgeLength(ModelPart& r_model_part)
{
double min_distance_yet = 0.0;
bool first_node = true;
for (ModelPart::ElementIterator ielem = r_model_part.ElementsBegin(); ielem != r_model_part.ElementsEnd(); ++ielem){
Geometry<Node<3> >& geom = ielem->GetGeometry();
if (first_node){ // assign the distance (squared) between any two nodes to min_distance_yet
array_1d <double, 3> delta = geom[0] - geom[1];
double distance_2 = DEM_INNER_PRODUCT_3(delta, delta);
min_distance_yet = distance_2;
}
unsigned int n_nodes = static_cast<unsigned int>(TDim + 1);
for (unsigned int k = 1; k < n_nodes - 1; ++k){
for (unsigned int i = k; i < n_nodes; ++i){
array_1d <double, 3> delta_i = geom[k - 1] - geom[i];
double distance_2 = DEM_INNER_PRODUCT_3(delta_i, delta_i);
min_distance_yet = min_distance_yet < distance_2 ? min_distance_yet : distance_2;
}
}
}
return(std::sqrt(min_distance_yet));
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
// The following block of functions is used to calculate explicit matrix inverses and was taken from
// Richel BilderBeek's website (http://www.richelbilderbeek.nl/CppUblasMatrixExample6.htm), and it is
// transcribed here with a very minor modification
double CalcDeterminant(const DenseMatrix<double>& m)
{
assert(m.size1() == m.size2() && "Can only calculate the determinant of square matrices");
switch(m.size1())
{
case 1:
{
return m(0,0);
}
case 2:
{
const double a = m(0,0);
const double b = m(0,1);
const double c = m(1,0);
const double d = m(1,1);
const double determinant = (a * d) - (b * c);
return determinant;
}
case 3:
{
assert(m.size1() == 3 && m.size2() == 3 && "Only for 3x3 matrices");
const double a = m(0,0);
const double b = m(0,1);
const double c = m(0,2);
const double d = m(1,0);
const double e = m(1,1);
const double f = m(1,2);
const double g = m(2,0);
const double h = m(2,1);
const double k = m(2,2);
const double determinant
= (a * ((e*k) - (f*h)))
- (b * ((k*d) - (f*g)))
+ (c * ((d*h) - (e*g)));
return determinant;
}
default:
assert(!"Should not get here: unsupported matrix size");
throw std::runtime_error("Unsupported matrix size");
}
}
///Chop returns a std::vector of sub-matrices
//[ A at [0] B at [1] ]
//[ C at [2] D at [4] ]
const std::vector<DenseMatrix<double> > Chop(
const DenseMatrix<double>& m)
{
using boost::numeric::ublas::range;
using boost::numeric::ublas::matrix_range;
std::vector<matrix<double> > v;
v.reserve(4);
const int midy = m.size1() / 2;
const int midx = m.size2() / 2;
const matrix_range<const matrix<double> > top_left( m,range(0 ,midy ),range(0 ,midx ));
const matrix_range<const matrix<double> > bottom_left( m,range(midy,m.size1()),range(0 ,midx ));
const matrix_range<const matrix<double> > top_right( m,range(0 ,midy ),range(midx,m.size2()));
const matrix_range<const matrix<double> > bottom_right(m,range(midy,m.size1()),range(midx,m.size2()));
v.push_back(matrix<double>(top_left));
v.push_back(matrix<double>(top_right));
v.push_back(matrix<double>(bottom_left));
v.push_back(matrix<double>(bottom_right));
return v;
}
///Unchop merges the 4 std::vector of sub-matrices produced by Chop
const DenseMatrix<double> Unchop(
const std::vector<DenseMatrix<double> >& v)
{
//Chop returns a std::vector of sub-matrices
//[ A at [0] B at [1] ]
//[ C at [2] D at [4] ]
using boost::numeric::ublas::range;
using boost::numeric::ublas::matrix_range;
assert(v.size() == 4);
assert(v[0].size1() == v[1].size1());
assert(v[2].size1() == v[3].size1());
assert(v[0].size2() == v[2].size2());
assert(v[1].size2() == v[3].size2());
DenseMatrix<double> m(v[0].size1() + v[2].size1(),v[0].size2() + v[1].size2());
for (int quadrant=0; quadrant!=4; ++quadrant)
{
const DenseMatrix<double>& w = v[quadrant];
const std::size_t n_rows = v[quadrant].size1();
const std::size_t n_cols = v[quadrant].size2();
const int offset_x = quadrant % 2 ? v[0].size2() : 0;
const int offset_y = quadrant / 2 ? v[0].size1() : 0;
for (std::size_t row=0; row!=n_rows; ++row)
{
for (std::size_t col=0; col!=n_cols; ++col)
{
m(offset_y + row, offset_x + col) = w(row,col);
}
}
}
assert(v[0].size1() + v[2].size1() == m.size1());
assert(v[1].size1() + v[3].size1() == m.size1());
assert(v[0].size2() + v[1].size2() == m.size2());
assert(v[2].size2() + v[3].size2() == m.size2());
return m;
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
///@}
///@name Member r_variables
///@{
DenseVector<unsigned int> mElementsPartition;
///@}
///@name Un accessible methods
///@{
double GetRangeWithinVector(const std::vector<double>& vector)
{
double min = vector[0];
double max = vector[0];
for (unsigned int i = 0; i != vector.size(); ++i){
min = std::min(min, mPressures[i]);
max = std::max(max, mPressures[i]);
}
return (max - min);
}
DenseVector<unsigned int>& GetElementPartition()
{
return mElementsPartition;
}
ElementIterator GetElementPartitionBegin(ModelPart& r_model_part, unsigned int k)
{
return r_model_part.GetCommunicator().LocalMesh().Elements().ptr_begin() + mElementsPartition[k];
}
ElementIterator GetElementPartitionEnd(ModelPart& r_model_part, unsigned int k)
{
return r_model_part.GetCommunicator().LocalMesh().Elements().ptr_begin() + mElementsPartition[k + 1];
}
//**************************************************************************************************************************************************
//**************************************************************************************************************************************************
}; // Class CustomFunctionsCalculator
} // namespace Kratos.
#endif // KRATOS_CREATE_AND_DESTROY defined
|
sixs_runs.c | #include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <unistd.h>
#include "sixs_runs.h"
struct etm_spectral_function_t {
int nbvals[SIXS_NB_BANDS];
float wlinf[SIXS_NB_BANDS];
float wlsup[SIXS_NB_BANDS];
float response[SIXS_NB_BANDS][155];
} etm_spectral_function_t;
int create_6S_tables(sixs_tables_t *sixs_tables, Input_meta_t *meta) {
char cmd[128],sixs_cmd_filename[1024],sixs_out_filename[1024],line_in[256];
/* char tmp_file[1024], cmd_string[1024]; */
int i,j,k;
FILE *fd;
float tgoz,tgco2,tgo2,tgno2,tgch4,tgco;
int tm_band[SIXS_NB_BANDS]={25,26,27,28,29,30};
char short_name[1024];
char local_granule_id[1024];
char acq_date_string[MAX_DATE_LEN + 1];
const char *sat_names[SAT_MAX] = {"1", "2", "3", "4", "5", "7"};
const char *inst_names[INST_MAX] = {"M", "T", "E"};
const char *wrs_names[WRS_MAX] = {"1", "2"};
struct etm_spectral_function_t etm_spectral_function = {
{54,61,65,81,131,155},
{0.420,0.500,0.580,0.730,1.501,2.0},
{0.550,0.650,0.740,0.930,1.825,2.386},
{
{0.000,0.000,0.000,0.000,0.000,0.000,0.016,0.071,0.287,0.666,0.792,0.857,0.839,0.806,0.779,0.846,0.901,0.900,0.890,0.851,0.875,0.893,0.884,0.930,0.958,0.954,0.980,0.975,0.965,0.962,0.995,0.990,0.990,0.979,0.983,0.969,0.960,0.768,0.293,0.054,0.009,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000},
{0.001,0.002,0.003,0.012,0.026,0.074,0.174,0.348,0.552,0.696,0.759,0.785,0.822,0.870,0.905,0.929,0.947,0.952,0.952,0.951,0.953,0.950,0.954,0.967,0.959,0.941,0.933,0.938,0.951,0.956,0.955,0.956,0.973,0.992,1.000,0.976,0.942,0.930,0.912,0.799,0.574,0.340,0.185,0.105,0.062,0.038,0.021,0.011,0.005,0.002,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000},
{0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.001,0.002,0.010,0.047,0.174,0.419,0.731,0.921,0.942,0.937,0.937,0.949,0.965,0.973,0.970,0.958,0.955,0.962,0.980,0.993,0.998,1.000,0.995,0.992,0.988,0.977,0.954,0.932,0.880,0.729,0.444,0.183,0.066,0.025,0.012,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000},
{0.000,0.000,0.000,0.000,0.000,0.002,0.004,0.002,0.001,0.020,0.032,0.052,0.069,0.110,0.175,0.271,0.402,0.556,0.705,0.812,0.871,0.896,0.908,0.918,0.926,0.928,0.930,0.926,0.925,0.928,0.923,0.916,0.908,0.903,0.909,0.924,0.946,0.954,0.971,0.969,0.967,0.965,0.967,0.961,0.949,0.931,0.925,0.929,0.943,0.961,0.985,0.992,0.998,0.992,0.994,0.997,0.998,1.000,0.991,0.988,0.969,0.926,0.868,0.817,0.819,0.880,0.854,0.572,0.256,0.104,0.044,0.022,0.011,0.007,0.000,0.000,0.000,0.000,0.000,0.000,0.000},
{0.000,0.003,0.000,0.001,0.007,0.008,0.008,0.012,0.012,0.028,0.041,0.062,0.087,0.114,0.176,0.230,0.306,0.410,0.481,0.543,0.598,0.642,0.686,0.719,0.750,0.785,0.817,0.845,0.867,0.881,0.902,0.900,0.896,0.892,0.899,0.882,0.872,0.872,0.872,0.878,0.868,0.860,0.877,0.884,0.897,0.895,0.898,0.912,0.921,0.927,0.937,0.947,0.948,0.954,0.961,0.962,0.962,0.964,0.969,0.956,0.952,0.951,0.952,0.953,0.939,0.934,0.928,0.943,0.945,0.935,0.944,0.947,0.944,0.949,0.960,0.966,0.971,0.978,0.993,0.998,0.996,0.996,0.997,0.986,0.990,0.988,0.992,0.985,0.982,0.978,0.970,0.966,0.952,0.927,0.883,0.832,0.751,0.656,0.577,0.483,0.393,0.310,0.239,0.184,0.142,0.104,0.080,0.063,0.049,0.041,0.036,0.023,0.021,0.019,0.012,0.006,0.008,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000},
{0.004,0.001,0.003,0.000,0.002,0.001,0.002,0.002,0.012,0.008,0.009,0.018,0.017,0.031,0.037,0.046,0.058,0.076,0.088,0.110,0.149,0.196,0.242,0.303,0.367,0.437,0.519,0.610,0.677,0.718,0.756,0.774,0.784,0.775,0.789,0.782,0.778,0.766,0.762,0.768,0.775,0.769,0.788,0.808,0.794,0.823,0.811,0.819,0.836,0.837,0.836,0.851,0.859,0.855,0.871,0.873,0.875,0.859,0.872,0.859,0.872,0.863,0.865,0.868,0.877,0.873,0.869,0.876,0.868,0.879,0.873,0.876,0.880,0.874,0.870,0.858,0.863,0.859,0.844,0.859,0.854,0.863,0.868,0.856,0.847,0.861,0.851,0.852,0.838,0.847,0.840,0.831,0.836,0.838,0.822,0.838,0.839,0.842,0.854,0.862,0.873,0.868,0.879,0.891,0.898,0.919,0.920,0.926,0.928,0.934,0.936,0.953,0.954,0.952,0.960,0.973,0.985,0.972,0.970,0.994,0.989,0.975,1.000,0.991,0.968,0.966,0.956,0.929,0.929,0.926,0.903,0.924,0.929,0.928,0.920,0.853,0.775,0.659,0.531,0.403,0.275,0.218,0.131,0.104,0.075,0.052,0.029,0.028,0.014,0.019,0.013,0.007,0.015,0.000,0.004}
}
};
sixs_tables->aot[0]=0.01;
sixs_tables->aot[1]=0.05;
sixs_tables->aot[2]=0.10;
sixs_tables->aot[3]=0.15;
sixs_tables->aot[4]=0.20;
sixs_tables->aot[5]=0.30;
sixs_tables->aot[6]=0.40;
sixs_tables->aot[7]=0.60;
sixs_tables->aot[8]=0.80;
sixs_tables->aot[9]=1.00;
sixs_tables->aot[10]=1.20;
sixs_tables->aot[11]=1.40;
sixs_tables->aot[12]=1.60;
sixs_tables->aot[13]=1.80;
sixs_tables->aot[14]=2.00;
/* Determine the 6s command and output filenames */
if (sprintf(short_name, "L%s%s%s", sat_names[meta->sat],
inst_names[meta->inst], "SR") < 0) {
fprintf(stderr, "ERROR:creating short name\n");
exit(-1);
}
if (!FormatDate(&meta->acq_date, DATE_FORMAT_DATEB, acq_date_string)) {
fprintf(stderr, "ERROR:formatting acquisition date\n");
exit(-1);
}
acq_date_string[4] = '\0';
sprintf(local_granule_id, "%s.a%4s%3s.w%1sp%03dr%03d",
short_name, acq_date_string, &acq_date_string[5],
wrs_names[meta->wrs_sys], meta->ipath, meta->irow);
/* Run 6s */
#ifdef _OPENMP
#pragma omp parallel for private (i, j, k, sixs_cmd_filename, sixs_out_filename, fd, cmd, line_in, tgoz, tgco2, tgo2, tgno2, tgch4, tgco)
#endif
for (i=0;i<SIXS_NB_BANDS;i++) {
for (j=0;j<SIXS_NB_AOT;j++) {
sprintf (sixs_cmd_filename, "sixs_cmd_%s_%d_%d", local_granule_id, i+1, j+1);
sprintf (sixs_out_filename, "sixs_output_%s_%d_%d", local_granule_id, i+1, j+1);
printf("Processing 6S for band %d AOT %2d\r",i+1,j+1);
fflush(stdout);
if ((fd=fopen(sixs_cmd_filename,"w"))==NULL) {
fprintf(stderr,"ERROR: creating temporary file %s\n",sixs_cmd_filename);
exit(-1);
}
fprintf(fd,"%s <<+ >%s\n",SIXS_APP,sixs_out_filename);
fprintf(fd,"0 (user defined)\n");
fprintf(fd,"%.2f %.2f %.2f %.2f %d %d (geometrical conditions sza saz vza vaz month day)\n",sixs_tables->sza,sixs_tables->phi,sixs_tables->vza,0.,sixs_tables->month,sixs_tables->day);
fprintf(fd,"8 (option for water vapor and ozone)\n");
fprintf(fd,"%.2f %.2f (water vapor and ozone)\n",sixs_tables->uwv,sixs_tables->uoz);
fprintf(fd,"1 (continental model)\n");
fprintf(fd,"0 (option for optical thickness at 550 nm)\n");
fprintf(fd,"%.3f (value of aot550\n",sixs_tables->aot[j]);
fprintf(fd,"%f (target level)\n",sixs_tables->target_alt);
fprintf(fd,"-1000 (sensor level : -1000=satellite level)\n");
switch (sixs_tables->Inst) {
case SIXS_INST_TM:
fprintf(fd,"%d (predefined band)\n",tm_band[i]);
break;
case SIXS_INST_ETM:
fprintf(fd,"1 (user defined filter function)\n");
fprintf(fd,"%05.3f %05.3f (wlinf wlsup)\n",etm_spectral_function.wlinf[i],etm_spectral_function.wlsup[i]);
for (k=0;k<etm_spectral_function.nbvals[i];k++) {
fprintf(fd,"%05.3f ",etm_spectral_function.response[i][k]);
if (!((k+1)%10))
fprintf(fd,"\n");
}
if (k%10)
fprintf(fd,"\n");
break;
default:
fprintf(stderr,"ERROR: Unknown Instrument in six_run parameters\n");
exit(-1);
}
fprintf(fd,"0 (homogeneous surface)\n");
fprintf(fd,"0 (no directional effects)\n");
fprintf(fd,"0 (constant value for rho)\n");
fprintf(fd,"%.3f (value of rho)\n",sixs_tables->srefl);
fprintf(fd,"-1 (no atmospheric correction)\n");
fprintf(fd,"0\n");
fprintf(fd,"+\n");
fclose(fd);
/* Modified 9/26/2014 to run bash shell vs. sh */
sprintf(cmd,"bash %s",sixs_cmd_filename);
if (system(cmd)) {
fprintf(stderr,"ERROR: Can't run 6S \n");
exit(-1);
}
if ((fd=fopen(sixs_out_filename,"r"))==NULL) {
fprintf(stderr,"ERROR: reading temporary file %s\n",sixs_out_filename);
exit(-1);
}
while (fgets(line_in,256,fd)) {
line_in[strlen(line_in)-1]='\0';
if (j==0) {
if (!strncmp(line_in,"* rayl. sca. trans. :",27)) {
k=27;
while (line_in[k]==' ')
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_r_down[i]);
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_r_up[i]);
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_r[i]);
}
if (!strncmp(line_in,"* water \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_g_wv[i]);
}
if (!strncmp(line_in,"* ozone \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&tgoz);
}
if (!strncmp(line_in,"* co2 \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&tgco2);
}
if (!strncmp(line_in,"* oxyg \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&tgo2);
}
if (!strncmp(line_in,"* no2 \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&tgno2);
}
if (!strncmp(line_in,"* ch4 \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&tgch4);
}
if (!strncmp(line_in,"* co \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&tgco);
}
sixs_tables->T_g_og[i]=tgoz*tgco2*tgo2*tgno2*tgno2*tgch4*tgco;
}
if (!strncmp(line_in,"* spherical albedo :",27)) {
k=27;
while (line_in[k]==' ') /* blank */
k++;
if (j==0)
sscanf(&line_in[k],"%f",&sixs_tables->S_r[i]);
while (line_in[k]!=' ') /* Rayleigh */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* Aerosol */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->S_ra[i][j]);
}
if (!strncmp(line_in,"* optical depth total:",27)) {
k=27;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* Rayleigh */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->aot_wavelength[i][j]);
}
if (!strncmp(line_in,"* aeros. sca. \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_a_down[i][j]);
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_a_up[i][j]);
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_a[i][j]);
}
if (!strncmp(line_in,"* total sca. \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_ra_down[i][j]);
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_ra_up[i][j]);
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_ra[i][j]);
}
if (!strncmp(line_in,"* reflectance I :",27)) {
k=27;
while (line_in[k]==' ') /* blank */
k++;
if (j==0)
sscanf(&line_in[k],"%f",&sixs_tables->rho_r[i]);
while (line_in[k]!=' ') /* rayleigh */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->rho_a[i][j]);
while (line_in[k]!=' ') /* aerosols */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->rho_ra[i][j]);
}
}
fclose(fd);
/* For OZONE debugging:
sprintf (tmp_file, "%s_b%d_aot%02d", sixs_cmd_filename, i, j);
sprintf (cmd_string, "cp %s %s", sixs_cmd_filename, tmp_file);
system (cmd_string);
sprintf (tmp_file, "%s_b%d_aot%02d", sixs_out_filename, i, j);
sprintf (cmd_string, "cp %s %s", sixs_out_filename, tmp_file);
system (cmd_string);
*/
unlink(sixs_cmd_filename);
unlink(sixs_out_filename);
} /* for j */
} /* for i */
printf ("\n");
return 0;
}
/* This function is not actually used in lndsr processing */
int create_6S_tables_water(sixs_tables_t *sixs_tables) {
char cmd[128],sixs_cmd_filename[128],sixs_out_filename[128],line_in[256];
int i,j,k;
FILE *fd;
float tgoz,tgco2,tgo2,tgno2,tgch4,tgco;
int tm_band[SIXS_NB_BANDS]={25,26,27,28,29,30};
char *tmpstr;
struct etm_spectral_function_t etm_spectral_function = {
{54,61,65,81,131,155},
{0.420,0.500,0.580,0.730,1.501,2.0},
{0.550,0.650,0.740,0.930,1.825,2.386},
{
{0.000,0.000,0.000,0.000,0.000,0.000,0.016,0.071,0.287,0.666,0.792,0.857,0.839,0.806,0.779,0.846,0.901,0.900,0.890,0.851,0.875,0.893,0.884,0.930,0.958,0.954,0.980,0.975,0.965,0.962,0.995,0.990,0.990,0.979,0.983,0.969,0.960,0.768,0.293,0.054,0.009,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000},
{0.001,0.002,0.003,0.012,0.026,0.074,0.174,0.348,0.552,0.696,0.759,0.785,0.822,0.870,0.905,0.929,0.947,0.952,0.952,0.951,0.953,0.950,0.954,0.967,0.959,0.941,0.933,0.938,0.951,0.956,0.955,0.956,0.973,0.992,1.000,0.976,0.942,0.930,0.912,0.799,0.574,0.340,0.185,0.105,0.062,0.038,0.021,0.011,0.005,0.002,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000},
{0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.001,0.002,0.010,0.047,0.174,0.419,0.731,0.921,0.942,0.937,0.937,0.949,0.965,0.973,0.970,0.958,0.955,0.962,0.980,0.993,0.998,1.000,0.995,0.992,0.988,0.977,0.954,0.932,0.880,0.729,0.444,0.183,0.066,0.025,0.012,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000},
{0.000,0.000,0.000,0.000,0.000,0.002,0.004,0.002,0.001,0.020,0.032,0.052,0.069,0.110,0.175,0.271,0.402,0.556,0.705,0.812,0.871,0.896,0.908,0.918,0.926,0.928,0.930,0.926,0.925,0.928,0.923,0.916,0.908,0.903,0.909,0.924,0.946,0.954,0.971,0.969,0.967,0.965,0.967,0.961,0.949,0.931,0.925,0.929,0.943,0.961,0.985,0.992,0.998,0.992,0.994,0.997,0.998,1.000,0.991,0.988,0.969,0.926,0.868,0.817,0.819,0.880,0.854,0.572,0.256,0.104,0.044,0.022,0.011,0.007,0.000,0.000,0.000,0.000,0.000,0.000,0.000},
{0.000,0.003,0.000,0.001,0.007,0.008,0.008,0.012,0.012,0.028,0.041,0.062,0.087,0.114,0.176,0.230,0.306,0.410,0.481,0.543,0.598,0.642,0.686,0.719,0.750,0.785,0.817,0.845,0.867,0.881,0.902,0.900,0.896,0.892,0.899,0.882,0.872,0.872,0.872,0.878,0.868,0.860,0.877,0.884,0.897,0.895,0.898,0.912,0.921,0.927,0.937,0.947,0.948,0.954,0.961,0.962,0.962,0.964,0.969,0.956,0.952,0.951,0.952,0.953,0.939,0.934,0.928,0.943,0.945,0.935,0.944,0.947,0.944,0.949,0.960,0.966,0.971,0.978,0.993,0.998,0.996,0.996,0.997,0.986,0.990,0.988,0.992,0.985,0.982,0.978,0.970,0.966,0.952,0.927,0.883,0.832,0.751,0.656,0.577,0.483,0.393,0.310,0.239,0.184,0.142,0.104,0.080,0.063,0.049,0.041,0.036,0.023,0.021,0.019,0.012,0.006,0.008,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000,0.000},
{0.004,0.001,0.003,0.000,0.002,0.001,0.002,0.002,0.012,0.008,0.009,0.018,0.017,0.031,0.037,0.046,0.058,0.076,0.088,0.110,0.149,0.196,0.242,0.303,0.367,0.437,0.519,0.610,0.677,0.718,0.756,0.774,0.784,0.775,0.789,0.782,0.778,0.766,0.762,0.768,0.775,0.769,0.788,0.808,0.794,0.823,0.811,0.819,0.836,0.837,0.836,0.851,0.859,0.855,0.871,0.873,0.875,0.859,0.872,0.859,0.872,0.863,0.865,0.868,0.877,0.873,0.869,0.876,0.868,0.879,0.873,0.876,0.880,0.874,0.870,0.858,0.863,0.859,0.844,0.859,0.854,0.863,0.868,0.856,0.847,0.861,0.851,0.852,0.838,0.847,0.840,0.831,0.836,0.838,0.822,0.838,0.839,0.842,0.854,0.862,0.873,0.868,0.879,0.891,0.898,0.919,0.920,0.926,0.928,0.934,0.936,0.953,0.954,0.952,0.960,0.973,0.985,0.972,0.970,0.994,0.989,0.975,1.000,0.991,0.968,0.966,0.956,0.929,0.929,0.926,0.903,0.924,0.929,0.928,0.920,0.853,0.775,0.659,0.531,0.403,0.275,0.218,0.131,0.104,0.075,0.052,0.029,0.028,0.014,0.019,0.013,0.007,0.015,0.000,0.004}
}
};
sixs_tables->aot[0]=0.01;
sixs_tables->aot[1]=0.05;
sixs_tables->aot[2]=0.10;
sixs_tables->aot[3]=0.15;
sixs_tables->aot[4]=0.20;
sixs_tables->aot[5]=0.30;
sixs_tables->aot[6]=0.40;
sixs_tables->aot[7]=0.60;
sixs_tables->aot[8]=0.80;
sixs_tables->aot[9]=1.00;
sixs_tables->aot[10]=1.20;
sixs_tables->aot[11]=1.40;
sixs_tables->aot[12]=1.60;
sixs_tables->aot[13]=1.80;
sixs_tables->aot[14]=2.00;
printf ("DEBUG: in compute_6S_tables_water -- shouldn't be here!\n");
if ((tmpstr = tmpnam(sixs_cmd_filename)) == NULL) {
fprintf(stderr,"ERROR: creating temporary file %s\n",sixs_cmd_filename);
exit(-1);
}
if ((tmpstr = tmpnam(sixs_out_filename)) == NULL) {
fprintf(stderr,"ERROR: creating temporary file %s\n",sixs_out_filename);
exit(-1);
}
for (i=0;i<SIXS_NB_BANDS;i++) {
for (j=0;j<SIXS_NB_AOT;j++) {
printf("Processing Band %d AOT %d\n",i+1,j+1);
if ((fd=fopen(sixs_cmd_filename,"w"))==NULL) {
fprintf(stderr,"ERROR: creating temporary file %s\n",sixs_cmd_filename);
exit(-1);
}
fprintf(fd,"%s <<+ >%s\n",SIXS_APP,sixs_out_filename);
fprintf(fd,"0 (user defined)\n");
fprintf(fd,"%.2f %.2f %.2f %.2f %d %d (geometrical conditions sza saz vza vaz month day)\n",sixs_tables->sza,sixs_tables->phi,sixs_tables->vza,0.,sixs_tables->month,sixs_tables->day);
fprintf(fd,"8 (option for water vapor and ozone)\n");
fprintf(fd,"%.2f %.2f (water vapor and ozone)\n",sixs_tables->uwv,sixs_tables->uoz);
fprintf(fd,"2 (maritime model)\n");
fprintf(fd,"0 (option for optical thickness at 550 nm)\n");
fprintf(fd,"%.3f (value of aot550\n",sixs_tables->aot[j]);
fprintf(fd,"%f (target level)\n",sixs_tables->target_alt);
fprintf(fd,"-1000 (sensor level : -1000=satellite level)\n");
switch (sixs_tables->Inst) {
case SIXS_INST_TM:
fprintf(fd,"%d (predefined band)\n",tm_band[i]);
break;
case SIXS_INST_ETM:
fprintf(fd,"1 (user defined filter function)\n");
fprintf(fd,"%05.3f %05.3f (wlinf wlsup)\n",etm_spectral_function.wlinf[i],etm_spectral_function.wlsup[i]);
for (k=0;k<etm_spectral_function.nbvals[i];k++) {
fprintf(fd,"%05.3f ",etm_spectral_function.response[i][k]);
if (!((k+1)%10))
fprintf(fd,"\n");
}
if (k%10)
fprintf(fd,"\n");
break;
default:
fprintf(stderr,"ERROR: Unknown Instrument in six_run parameters\n");
exit(-1);
}
fprintf(fd,"0 (homogeneous surface)\n");
fprintf(fd,"1 (directional effects)\n");
fprintf(fd,"6 (Ocean)\n");
fprintf(fd,"2.0 0.0 0.0 .10 (wind speed(m/s) wind azimuth(deg) salinity(deg) pigment concentration(mg/m3))\n");
fprintf(fd,"%.3f (value of rho)\n",sixs_tables->srefl);
fprintf(fd,"-1 (no atmospheric correction)\n");
fprintf(fd,"+\n");
fclose(fd);
/* Modified 9/26/2014 to run bash shell vs. sh */
sprintf(cmd,"bash %s",sixs_cmd_filename);
if (system(cmd)) {
fprintf(stderr,"ERROR: Can't run 6S \n");
exit(-1);
}
if ((fd=fopen(sixs_out_filename,"r"))==NULL) {
fprintf(stderr,"ERROR: reading temporary file %s\n",sixs_out_filename);
exit(-1);
}
while (fgets(line_in,256,fd)) {
line_in[strlen(line_in)-1]='\0';
if (j==0) {
if (!strncmp(line_in,"* rayl. sca. trans. :",27)) {
k=27;
while (line_in[k]==' ')
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_r_down[i]);
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_r_up[i]);
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_r[i]);
}
if (!strncmp(line_in,"* water \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_g_wv[i]);
}
if (!strncmp(line_in,"* ozone \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&tgoz);
}
if (!strncmp(line_in,"* co2 \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&tgco2);
}
if (!strncmp(line_in,"* oxyg \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&tgo2);
}
if (!strncmp(line_in,"* no2 \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&tgno2);
}
if (!strncmp(line_in,"* ch4 \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&tgch4);
}
if (!strncmp(line_in,"* co \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&tgco);
}
sixs_tables->T_g_og[i]=tgoz*tgco2*tgo2*tgno2*tgno2*tgch4*tgco;
}
if (!strncmp(line_in,"* spherical albedo :",27)) {
k=27;
while (line_in[k]==' ') /* blank */
k++;
if (j==0)
sscanf(&line_in[k],"%f",&sixs_tables->S_r[i]);
while (line_in[k]!=' ') /* Rayleigh */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* Aerosol */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->S_ra[i][j]);
}
if (!strncmp(line_in,"* optical depth total:",27)) {
k=27;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* Rayleigh */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->aot_wavelength[i][j]);
}
if (!strncmp(line_in,"* aeros. sca. \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_a_down[i][j]);
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_a_up[i][j]);
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_a[i][j]);
}
if (!strncmp(line_in,"* total sca. \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_ra_down[i][j]);
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_ra_up[i][j]);
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->T_ra[i][j]);
}
if (!strncmp(line_in,"* reflectance I :",27)) {
k=27;
while (line_in[k]==' ') /* blank */
k++;
if (j==0)
sscanf(&line_in[k],"%f",&sixs_tables->rho_r[i]);
while (line_in[k]!=' ') /* rayleigh */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->rho_a[i][j]);
while (line_in[k]!=' ') /* aerosols */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->rho_ra[i][j]);
}
if (!strncmp(line_in,"* apparent reflectance",28)) {
k=28;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_tables->rho_toa[i][j]);
}
}
fclose(fd);
}
}
unlink(sixs_cmd_filename);
unlink(sixs_out_filename);
return 0;
}
/* This function is not actually used in lndsr processing */
int compute_atmos_params_6S(sixs_atmos_params_t *sixs_atmos_params) {
char cmd[128],sixs_cmd_filename[128],sixs_out_filename[128],line_in[256];
int k;
float tgoz,tgco2,tgo2,tgno2,tgch4,tgco;
int tm_band[SIXS_NB_BANDS]={25,26,27,28,29,30};
char *tmpstr;
FILE *fd;
printf ("DEBUG: in compute_atmos_params_6S -- shouldn't be here!\n");
if ((tmpstr = tmpnam(sixs_cmd_filename)) == NULL) {
fprintf(stderr,"ERROR: creating temporary file %s\n",sixs_cmd_filename);
exit(-1);
}
if ((tmpstr = tmpnam(sixs_out_filename)) == NULL) {
fprintf(stderr,"ERROR: creating temporary file %s\n",sixs_out_filename);
exit(-1);
}
if ((fd=fopen(sixs_cmd_filename,"w"))==NULL) {
fprintf(stderr,"ERROR: creating temporary file %s\n",sixs_cmd_filename);
exit(-1);
}
fprintf(fd,"%s <<+ >%s\n",SIXS_APP,sixs_out_filename);
fprintf(fd,"0\n");
fprintf(fd,"%.2f %.2f %.2f %.2f %d %d\n",sixs_atmos_params->sza,sixs_atmos_params->phi,sixs_atmos_params->vza,0.,sixs_atmos_params->month,sixs_atmos_params->day);
fprintf(fd,"8\n");
fprintf(fd,"%.2f %.2f\n",sixs_atmos_params->uwv,sixs_atmos_params->uoz);
if (sixs_atmos_params->aot > 0) {
fprintf(fd,"1\n");
fprintf(fd,"0\n");
fprintf(fd,"%.3f\n",sixs_atmos_params->aot);
} else {
fprintf(fd,"0\n");
fprintf(fd,"-1\n");
}
fprintf(fd,"0\n");
fprintf(fd,"-1000\n");
fprintf(fd,"%d\n",tm_band[sixs_atmos_params->band]);
fprintf(fd,"0\n");
fprintf(fd,"0\n");
fprintf(fd,"0\n");
fprintf(fd,"%.3f\n",sixs_atmos_params->srefl);
fprintf(fd,"-1\n");
fprintf(fd,"0\n");
fprintf(fd,"+\n");
fclose(fd);
sprintf(cmd,"bash %s",sixs_cmd_filename);
if (system(cmd)) {
fprintf(stderr,"ERROR: Can't run 6S \n");
exit(-1);
}
if ((fd=fopen(sixs_out_filename,"r"))==NULL) {
fprintf(stderr,"ERROR: reading temporary file %s\n",sixs_out_filename);
exit(-1);
}
while (fgets(line_in,256,fd)) {
line_in[strlen(line_in)-1]='\0';
if (!strncmp(line_in,"* spherical albedo :",27)) {
k=27;
while (line_in[k]==' ')
k++;
sscanf(&line_in[k],"%f",&sixs_atmos_params->S_r);
}
if (!strncmp(line_in,"* rayl. sca. trans. :",27)) {
k=27;
while (line_in[k]==' ')
k++;
sscanf(&line_in[k],"%f",&sixs_atmos_params->T_r_down);
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_atmos_params->T_r_up);
}
if (!strncmp(line_in,"* aeros. sca. \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
sscanf(&line_in[k],"%f",&sixs_atmos_params->T_a_down);
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_atmos_params->T_a_up);
}
if (!strncmp(line_in,"* reflectance I :",27)) {
k=27;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_atmos_params->rho_r);
while (line_in[k]!=' ') /* rayleigh */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_atmos_params->rho_a);
}
if (!strncmp(line_in,"* water \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&sixs_atmos_params->T_g_wv);
}
if (!strncmp(line_in,"* ozone \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&tgoz);
}
if (!strncmp(line_in,"* co2 \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&tgco2);
}
if (!strncmp(line_in,"* oxyg \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&tgo2);
}
if (!strncmp(line_in,"* no2 \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&tgno2);
}
if (!strncmp(line_in,"* ch4 \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&tgch4);
}
if (!strncmp(line_in,"* co \" \" :",27)) {
k=27;
while (line_in[k]==' ')
k++;
while (line_in[k]!=' ') /* downward */
k++;
while (line_in[k]==' ') /* blank */
k++;
while (line_in[k]!=' ') /* upward */
k++;
while (line_in[k]==' ') /* blank */
k++;
sscanf(&line_in[k],"%f",&tgco);
}
}
fclose(fd);
sixs_atmos_params->T_g_og=tgoz*tgco2*tgo2*tgno2*tgno2*tgch4*tgco;
unlink(sixs_cmd_filename);
unlink(sixs_out_filename);
return 0;
}
#ifdef SAVE_6S_RESULTS
int read_6S_results_from_file(char *filename,sixs_tables_t *sixs_tables) {
FILE *fd;
int run_sixs,i,j;
if ((fd=fopen(filename,"r"))==NULL)
return 1;
run_sixs=0;
if (fscanf(fd,"%d %d",&sixs_tables->month,&sixs_tables->day) != 2)
run_sixs=1;
if (fscanf(fd,"%f",&sixs_tables->srefl)!=1)
run_sixs=1;
if (fscanf(fd,"%f %f %f",&sixs_tables->sza,&sixs_tables->vza,&sixs_tables->phi)!=3)
run_sixs=1;
if (fscanf(fd,"%f %f %f",&sixs_tables->uwv,&sixs_tables->uoz,&sixs_tables->target_alt)!=3)
run_sixs=1;
for (i=0;i<SIXS_NB_AOT;i++)
if (fscanf(fd,"%f ",&sixs_tables->aot[i])!=1)
run_sixs=1;
for (i=0;i<SIXS_NB_BANDS;i++) {
if (fscanf(fd,"%f %f %f %f %f %f %f",&sixs_tables->S_r[i],&sixs_tables->T_r_up[i],&sixs_tables->T_r_down[i],&sixs_tables->T_r[i],&sixs_tables->T_g_wv[i],&sixs_tables->T_g_og[i],&sixs_tables->rho_r[i])!=7)
run_sixs=1;
for (j=0;j<SIXS_NB_AOT;j++)
if (fscanf(fd,"%f %f %f %f %f %f %f %f %f %f %f",&sixs_tables->aot_wavelength[i][j],&sixs_tables->T_a_up[i][j],&sixs_tables->T_a_down[i][j],&sixs_tables->T_a[i][j],&sixs_tables->rho_ra[i][j],&sixs_tables->rho_a[i][j],&sixs_tables->S_ra[i][j],&sixs_tables->T_ra_up[i][j],&sixs_tables->T_ra_down[i][j],&sixs_tables->T_ra[i][j],&sixs_tables->rho_toa[i][j])!=11)
run_sixs=1;
}
fclose(fd);
return run_sixs;
}
int write_6S_results_to_file(char *filename,sixs_tables_t *sixs_tables) {
FILE *fd;
int i,j;
if ((fd=fopen(filename,"w"))==NULL)
return -1;
fprintf(fd,"%02d %03d\n",sixs_tables->month,sixs_tables->day);
fprintf(fd,"%010.6f\n",sixs_tables->srefl);
fprintf(fd,"%010.6f %010.6f %010.6f\n",sixs_tables->sza,sixs_tables->vza,sixs_tables->phi);
fprintf(fd,"%010.6f %010.6f %010.2f\n",sixs_tables->uwv,sixs_tables->uoz,sixs_tables->target_alt);
for (i=0;i<SIXS_NB_AOT;i++)
fprintf(fd,"%07.4f ",sixs_tables->aot[i]);
fprintf(fd,"\n");
for (i=0;i<SIXS_NB_BANDS;i++) {
fprintf(fd,"%010.6f %010.6f %010.6f %010.6f %010.6f %010.6f %010.6f\n",sixs_tables->S_r[i],sixs_tables->T_r_up[i],sixs_tables->T_r_down[i],sixs_tables->T_r[i],sixs_tables->T_g_wv[i],sixs_tables->T_g_og[i],sixs_tables->rho_r[i]);
for (j=0;j<SIXS_NB_AOT;j++)
fprintf(fd,"%07.4f %010.6f %010.6f %010.6f %010.6f %010.6f %010.6f %010.6f %010.6f %010.6f %010.6f\n",sixs_tables->aot_wavelength[i][j],sixs_tables->T_a_up[i][j],sixs_tables->T_a_down[i][j],sixs_tables->T_a[i][j],sixs_tables->rho_ra[i][j],sixs_tables->rho_a[i][j],sixs_tables->S_ra[i][j],sixs_tables->T_ra_up[i][j],sixs_tables->T_ra_down[i][j],sixs_tables->T_ra[i][j],sixs_tables->rho_toa[i][j]);
}
fclose(fd);
return 0;
}
#endif
|
GB_binop__bshift_uint32.c | //------------------------------------------------------------------------------
// GB_binop: hard-coded functions for each built-in binary operator
//------------------------------------------------------------------------------
// SuiteSparse:GraphBLAS, Timothy A. Davis, (c) 2017-2021, All Rights Reserved.
// SPDX-License-Identifier: Apache-2.0
//------------------------------------------------------------------------------
// If this file is in the Generated/ folder, do not edit it (auto-generated).
#include "GB.h"
#ifndef GBCOMPACT
#include "GB_control.h"
#include "GB_ek_slice.h"
#include "GB_dense.h"
#include "GB_atomics.h"
#include "GB_bitmap_assign_methods.h"
#include "GB_binop__include.h"
// C=binop(A,B) is defined by the following types and operators:
// A+B function (eWiseAdd): GB_AaddB__bshift_uint32
// A.*B function (eWiseMult): GB_AemultB__bshift_uint32
// A*D function (colscale): (none)
// D*A function (rowscale): (node)
// C+=B function (dense accum): GB_Cdense_accumB__bshift_uint32
// C+=b function (dense accum): GB_Cdense_accumb__bshift_uint32
// C+=A+B function (dense ewise3): (none)
// C=A+B function (dense ewise3): GB_Cdense_ewise3_noaccum__bshift_uint32
// C=scalar+B GB_bind1st__bshift_uint32
// C=scalar+B' GB_bind1st_tran__bshift_uint32
// C=A+scalar GB_bind2nd__bshift_uint32
// C=A'+scalar GB_bind2nd_tran__bshift_uint32
// C type: uint32_t
// A type: uint32_t
// B,b type: int8_t
// BinaryOp: cij = GB_bitshift_uint32 (aij, bij)
#define GB_ATYPE \
uint32_t
#define GB_BTYPE \
int8_t
#define GB_CTYPE \
uint32_t
// true if the types of A and B are identical
#define GB_ATYPE_IS_BTYPE \
0
// 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 \
0
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
uint32_t aij = Ax [pA]
// bij = Bx [pB]
#define GB_GETB(bij,Bx,pB) \
int8_t bij = Bx [pB]
// declare scalar of the same type as C
#define GB_CTYPE_SCALAR(t) \
uint32_t t
// cij = Ax [pA]
#define GB_COPY_A_TO_C(cij,Ax,pA) \
cij = Ax [pA]
// cij = Bx [pB]
#define GB_COPY_B_TO_C(cij,Bx,pB) \
cij = Bx [pB]
#define GB_CX(p) Cx [p]
// binary operator
#define GB_BINOP(z, x, y, i, j) \
z = GB_bitshift_uint32 (x, y) ;
// op is second
#define GB_OP_IS_SECOND \
0
// op is plus_fp32 or plus_fp64
#define GB_OP_IS_PLUS_REAL \
0
// op is minus_fp32 or minus_fp64
#define GB_OP_IS_MINUS_REAL \
0
// GB_cblas_*axpy gateway routine, if it exists for this operator and type:
#define GB_CBLAS_AXPY \
(none)
// do the numerical phases of GB_add and GB_emult
#define GB_PHASE_2_OF_2
// hard-coded loops can be vectorized
#define GB_PRAGMA_SIMD_VECTORIZE GB_PRAGMA_SIMD
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_BSHIFT || GxB_NO_UINT32 || GxB_NO_BSHIFT_UINT32)
//------------------------------------------------------------------------------
// 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__bshift_uint32
(
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__bshift_uint32
(
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__bshift_uint32
(
GrB_Matrix C,
const GB_void *p_bwork,
const int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
{
// get the scalar b for C += b, of type int8_t
int8_t bwork = (*((int8_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 (none)
(
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
uint32_t *GB_RESTRICT Cx = (uint32_t *) C->x ;
#include "GB_AxB_colscale_meta.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
//------------------------------------------------------------------------------
// C = D*B, row scale with diagonal D matrix
//------------------------------------------------------------------------------
#if 0
GrB_Info (node)
(
GrB_Matrix C,
const GrB_Matrix D, bool D_is_pattern,
const GrB_Matrix B, bool B_is_pattern,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint32_t *GB_RESTRICT Cx = (uint32_t *) C->x ;
#include "GB_AxB_rowscale_meta.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
//------------------------------------------------------------------------------
// eWiseAdd: C = A+B or C<M> = A+B
//------------------------------------------------------------------------------
#undef GB_FREE_ALL
#define GB_FREE_ALL \
{ \
GB_ek_slice_free (&pstart_Mslice, &kfirst_Mslice, &klast_Mslice) ; \
GB_ek_slice_free (&pstart_Aslice, &kfirst_Aslice, &klast_Aslice) ; \
GB_ek_slice_free (&pstart_Bslice, &kfirst_Bslice, &klast_Bslice) ; \
}
GrB_Info GB_AaddB__bshift_uint32
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const bool Ch_is_Mh,
const int64_t *GB_RESTRICT C_to_M,
const int64_t *GB_RESTRICT C_to_A,
const int64_t *GB_RESTRICT C_to_B,
const GB_task_struct *GB_RESTRICT TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t *pstart_Mslice = NULL, *kfirst_Mslice = NULL, *klast_Mslice = NULL ;
int64_t *pstart_Aslice = NULL, *kfirst_Aslice = NULL, *klast_Aslice = NULL ;
int64_t *pstart_Bslice = NULL, *kfirst_Bslice = NULL, *klast_Bslice = NULL ;
#include "GB_add_template.c"
GB_FREE_ALL ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// eWiseMult: C = A.*B or C<M> = A.*B
//------------------------------------------------------------------------------
GrB_Info GB_AemultB__bshift_uint32
(
GrB_Matrix C,
const int C_sparsity,
const GrB_Matrix M,
const bool Mask_struct,
const bool Mask_comp,
const GrB_Matrix A,
const GrB_Matrix B,
const int64_t *GB_RESTRICT C_to_M,
const int64_t *GB_RESTRICT C_to_A,
const int64_t *GB_RESTRICT C_to_B,
const GB_task_struct *GB_RESTRICT TaskList,
const int C_ntasks,
const int C_nthreads,
GB_Context Context
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t *pstart_Mslice = NULL, *kfirst_Mslice = NULL, *klast_Mslice = NULL ;
int64_t *pstart_Aslice = NULL, *kfirst_Aslice = NULL, *klast_Aslice = NULL ;
int64_t *pstart_Bslice = NULL, *kfirst_Bslice = NULL, *klast_Bslice = NULL ;
#include "GB_emult_template.c"
GB_FREE_ALL ;
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (x,Bx): apply a binary operator to a matrix with scalar bind1st
//------------------------------------------------------------------------------
GrB_Info GB_bind1st__bshift_uint32
(
GB_void *Cx_output, // Cx and Bx may be aliased
const GB_void *x_input,
const GB_void *Bx_input,
const int8_t *GB_RESTRICT Bb,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint32_t *Cx = (uint32_t *) Cx_output ;
uint32_t x = (*((uint32_t *) x_input)) ;
int8_t *Bx = (int8_t *) Bx_input ;
int64_t p ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Bb, p)) continue ;
int8_t bij = Bx [p] ;
Cx [p] = GB_bitshift_uint32 (x, bij) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// Cx = op (Ax,y): apply a binary operator to a matrix with scalar bind2nd
//------------------------------------------------------------------------------
GrB_Info GB_bind2nd__bshift_uint32
(
GB_void *Cx_output, // Cx and Ax may be aliased
const GB_void *Ax_input,
const GB_void *y_input,
const int8_t *GB_RESTRICT Ab,
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
uint32_t *Cx = (uint32_t *) Cx_output ;
uint32_t *Ax = (uint32_t *) Ax_input ;
int8_t y = (*((int8_t *) y_input)) ;
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!GBB (Ab, p)) continue ;
uint32_t aij = Ax [p] ;
Cx [p] = GB_bitshift_uint32 (aij, y) ;
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (x, A'): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (x, aij), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
int8_t aij = Ax [pA] ; \
Cx [pC] = GB_bitshift_uint32 (x, aij) ; \
}
GrB_Info GB_bind1st_tran__bshift_uint32
(
GrB_Matrix C,
const GB_void *x_input,
const GrB_Matrix A,
int64_t *GB_RESTRICT *Workspaces,
const int64_t *GB_RESTRICT A_slice,
int nworkspaces,
int nthreads
)
{
// GB_unop_transpose.c uses GB_ATYPE, but A is
// the 2nd input to binary operator z=f(x,y).
#undef GB_ATYPE
#define GB_ATYPE \
int8_t
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
uint32_t x = (*((const uint32_t *) x_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
#undef GB_ATYPE
#define GB_ATYPE \
uint32_t
}
//------------------------------------------------------------------------------
// C = op (A', y): transpose and apply a binary operator
//------------------------------------------------------------------------------
// cij = op (aij, y), no typecasting (in spite of the macro name)
#undef GB_CAST_OP
#define GB_CAST_OP(pC,pA) \
{ \
uint32_t aij = Ax [pA] ; \
Cx [pC] = GB_bitshift_uint32 (aij, y) ; \
}
GrB_Info GB_bind2nd_tran__bshift_uint32
(
GrB_Matrix C,
const GrB_Matrix A,
const GB_void *y_input,
int64_t *GB_RESTRICT *Workspaces,
const int64_t *GB_RESTRICT A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int8_t y = (*((const int8_t *) y_input)) ;
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
3d25pt.c | /*
* Order-2, 3D 25 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)
#ifndef min
#define min(x,y) ((x) < (y)? (x) : (y))
#endif
/* 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])+8;
Ny = atoi(argv[2])+8;
Nz = atoi(argv[3])+8;
}
if (argc > 4)
Nt = atoi(argv[4]);
double ****A = (double ****) malloc(sizeof(double***)*2);
double ***roc2 = (double ***) malloc(sizeof(double**));
A[0] = (double ***) malloc(sizeof(double**)*Nz);
A[1] = (double ***) malloc(sizeof(double**)*Nz);
roc2 = (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);
roc2[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);
roc2[i][j] = (double*) malloc(sizeof(double)*Nx);
}
}
// tile size information, including extra element to decide the list length
int *tile_size = (int*) malloc(sizeof(int));
tile_size[0] = -1;
// The list is modified here before source-to-source transformations
tile_size = (int*) realloc((void *)tile_size, sizeof(int)*5);
tile_size[0] = 8;
tile_size[1] = 8;
tile_size[2] = 4;
tile_size[3] = 64;
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);
roc2[i][j][k] = 2.0 * (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
const double coef0 = -0.28472;
const double coef1 = 0.16000;
const double coef2 = -0.02000;
const double coef3 = 0.00254;
const double coef4 = -0.00018;
for(test=0; test<TESTS; test++){
gettimeofday(&start, 0);
// serial execution - Addition: 6 && Multiplication: 2
#pragma scop
for (t = 0; t < Nt; t++) {
for (i = 4; i < Nz-4; i++) {
for (j = 4; j < Ny-4; j++) {
for (k = 4; k < Nx-4; k++) {
A[(t+1)%2][i][j][k] = 2.0*A[t%2][i][j][k] - A[(t+1)%2][i][j][k] + roc2[i][j][k]*(
coef0* A[t%2][i ][j ][k ] +
coef1*(A[t%2][i-1][j ][k ] + A[t%2][i+1][j ][k ] +
A[t%2][i ][j-1][k ] + A[t%2][i ][j+1][k ] +
A[t%2][i ][j ][k-1] + A[t%2][i ][j ][k+1]) +
coef2*(A[t%2][i-2][j ][k ] + A[t%2][i+2][j ][k ] +
A[t%2][i ][j-2][k ] + A[t%2][i ][j+2][k ] +
A[t%2][i ][j ][k-2] + A[t%2][i ][j ][k+2]) +
coef3*(A[t%2][i-3][j ][k ] + A[t%2][i+3][j ][k ] +
A[t%2][i ][j-3][k ] + A[t%2][i ][j+3][k ] +
A[t%2][i ][j ][k-3] + A[t%2][i ][j ][k+3]) +
coef4*(A[t%2][i-4][j ][k ] + A[t%2][i+4][j ][k ] +
A[t%2][i ][j-4][k ] + A[t%2][i ][j+4][k ] +
A[t%2][i ][j ][k-4] + A[t%2][i ][j ][k+4]) );
}
}
}
}
#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(4, "constant")
#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(roc2[i][j]);
}
free(A[0][i]);
free(A[1][i]);
free(roc2[i]);
}
free(A[0]);
free(A[1]);
free(roc2);
return 0;
}
|
mobilenet_64.c | /*
Pretrained MobileNet Convolutional Neural Network in C language and
OpenMP API GitHUB Page: https://github.com/jcanore/vgg16 Author:
ZFTurbo/jocare
Compilation: gcc -O3 MobileNet_CPU_cifar.c -lm -fopenmp -o
MobileNet_CPU_cifar Usage: MobileNet_CPU_cifar <weights_path>
<file_with_list_of_images> <output file> <output convolution features
(optional)> Example: MobileNet_CPU_cifar ../../weights/weights.txt"
../../img/image_list.txt results_imagenet_conv.txt 1
*/
#include <ctype.h>
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <sys/time.h>
#include <time.h>
#include <unistd.h>
double get_seconds(struct timeval tStart, struct timeval tEnd) {
return ((tEnd.tv_sec - tStart.tv_sec) * 1000000 + tEnd.tv_usec -
tStart.tv_usec) /
1.e6;
}
#define SIZE 64
#define CONV_SIZE 3
#define CONV_LEVELS 27
//#define _CRT_SECURE_NO_WARNINGS 1
// precompile variables
// assure default values if nothing provided
#ifndef SPARSE_CONVOLUTIONS
#define SPARSE_CONVOLUTIONS 0 // default dense convolutions
#endif // SPARSE_CONVOLUTIONS
#ifndef FIRST_CONV_SPARSE
#define FIRST_CONV_SPARSE 0 // this is almost never 1
#endif // FIRST_CONV_SPARSE
#ifndef SPARSE_FULLY_CONNECTED
#define SPARSE_FULLY_CONNECTED 0 // this is not implemented yet
#endif // SPARSE_FULLY_CONNECTED
#ifndef FISHER_PRUNING
#define FISHER_PRUNING \
0 // set for fisher pruning, all previous variables changed to dense
#endif // FISHER_PRUNING
#ifndef NUMBER_OF_THREADS
#define NUMBER_OF_THREADS 1 // number of threads to run on
//#define NUMBER_OF_THREADS omp_get_num_procs() - 1
#endif // NUMBER_OF_THREADS
static double pw_conv_time = 0.0;
static double dense_time = 0.0;
/****************************************************************************************************************************/
int im_sizes[27] = {64, 64, 16, 16, 16, 16, 8, 8, 8, 8, 4, 4, 4, 4,
4, 4, 4, 4, 4, 4, 4, 4, 2, 2, 2, 2, 2};
int strides[26] = {1, 2, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1,
1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1};
int mem_block_shape[3] = {
1024, 64,
64}; // allocate the absolute maximum amount of space we will need
float ***block1;
float ***block2;
float *****wc; // weights convolution
float ***wd; // weights dense
float **bd; // biases dense
float **batchnorm_weights;
float **batchnorm_biases;
float **batchnorm_means; // running mean and variance from training used to
// estimate population statistics
float **batchnorm_vars;
int mem_block_dense_shape = {
1024 * 2 * 2}; // size of output from last convolutional layer
float *mem_block1_dense;
float *mem_block2_dense;
#if SPARSE_CONVOLUTIONS
// sparse conv
csr_t ****wc_sparse;
#endif // SPARSE_CONVOLUTIONS
#if FISHER_PRUNING
#define SPARSE_CONVOLUTIONS 0 // force dense convolutions
/* // ORIGINAL FISHER EXPERIMENTS
int cshape[27][4] = {
{ 64, 3, CONV_SIZE, CONV_SIZE },
{ 64, 1, CONV_SIZE, CONV_SIZE },
{ 43, 64, 1, 1 },
{ 43, 1, CONV_SIZE, CONV_SIZE },
{ 85, 43, 1, 1 },
{ 85, 1, CONV_SIZE, CONV_SIZE },
{ 70, 85, 1, 1 },
{ 70, 1, CONV_SIZE, CONV_SIZE },
{ 150, 70, 1, 1 },
{ 150, 1, CONV_SIZE, CONV_SIZE },
{ 69, 150, 1, 1 },
{ 69, 1, CONV_SIZE, CONV_SIZE },
{ 188, 69, 1, 1 },
{ 188, 1, CONV_SIZE, CONV_SIZE },
{ 72, 188, 1, 1 },
{ 72, 1, CONV_SIZE, CONV_SIZE },
{ 122, 72, 1, 1 },
{ 122, 1, CONV_SIZE, CONV_SIZE },
{ 106, 122, 1, 1 },
{ 106, 1, CONV_SIZE, CONV_SIZE },
{ 96, 106, 1, 1 },
{ 96, 1, CONV_SIZE, CONV_SIZE },
{ 81, 96, 1, 1 },
{ 81, 1, CONV_SIZE, CONV_SIZE },
{ 75, 81, 1, 1 },
{ 75, 1, CONV_SIZE, CONV_SIZE },
{ 100, 75, 1, 1 }
};
int dshape[1][2]= {
{ 100, 10}
};
*/
// FIXED 90% ACCURACY EXPERIMENTS
int cshape[27][4] = {{64, 3, CONV_SIZE, CONV_SIZE},
{64, 1, CONV_SIZE, CONV_SIZE},
{43, 64, 1, 1},
{43, 1, CONV_SIZE, CONV_SIZE},
{85, 43, 1, 1},
{85, 1, CONV_SIZE, CONV_SIZE},
{70, 85, 1, 1},
{70, 1, CONV_SIZE, CONV_SIZE},
{150, 70, 1, 1},
{150, 1, CONV_SIZE, CONV_SIZE},
{69, 150, 1, 1},
{69, 1, CONV_SIZE, CONV_SIZE},
{188, 69, 1, 1},
{188, 1, CONV_SIZE, CONV_SIZE},
{72, 188, 1, 1},
{72, 1, CONV_SIZE, CONV_SIZE},
{122, 72, 1, 1},
{122, 1, CONV_SIZE, CONV_SIZE},
{106, 122, 1, 1},
{106, 1, CONV_SIZE, CONV_SIZE},
{96, 106, 1, 1},
{96, 1, CONV_SIZE, CONV_SIZE},
{81, 96, 1, 1},
{81, 1, CONV_SIZE, CONV_SIZE},
{75, 81, 1, 1},
{75, 1, CONV_SIZE, CONV_SIZE},
{100, 75, 1, 1}
};
int dshape[1][2] = {{100, 10}};
#else // PLAIN
int cshape[27][4] = {{64, 3, CONV_SIZE, CONV_SIZE},
{64, 1, CONV_SIZE, CONV_SIZE},
{64, 64, 1, 1},
{64, 1, CONV_SIZE, CONV_SIZE},
{128, 64, 1, 1},
{128, 1, CONV_SIZE, CONV_SIZE},
{128, 128, 1, 1},
{128, 1, CONV_SIZE, CONV_SIZE},
{256, 128, 1, 1},
{256, 1, CONV_SIZE, CONV_SIZE},
{256, 256, 1, 1},
{256, 1, CONV_SIZE, CONV_SIZE},
{512, 256, 1, 1},
{512, 1, CONV_SIZE, CONV_SIZE},
{512, 512, 1, 1},
{512, 1, CONV_SIZE, CONV_SIZE},
{512, 512, 1, 1},
{512, 1, CONV_SIZE, CONV_SIZE},
{512, 512, 1, 1},
{512, 1, CONV_SIZE, CONV_SIZE},
{512, 512, 1, 1},
{512, 1, CONV_SIZE, CONV_SIZE},
{512, 512, 1, 1},
{512, 1, CONV_SIZE, CONV_SIZE},
{1024, 512, 1, 1},
{1024, 1, CONV_SIZE, CONV_SIZE},
{1024, 1024, 1, 1}};
int dshape[1][2] = {{1024, 10}};
#endif // FISHER_PRUNING
/****************************************************************************************************************************/
void reset_mem_block(float ***mem) {
int i, j, k;
for (i = 0; i < mem_block_shape[0]; i++) {
for (j = 0; j < mem_block_shape[1]; j++) {
for (k = 0; k < mem_block_shape[2]; k++) {
mem[i][j][k] = 0.0;
}
}
}
}
/****************************************************************************************************************************/
void reset_mem_block_dense(float *mem) {
int i;
for (i = 0; i < mem_block_dense_shape; i++) {
mem[i] = 0.0;
}
}
/****************************************************************************************************************************/
void init_memory() {
int i, j, k, l;
int max_channels = 1024;
int max_im_size = 64;
block1 = malloc(max_channels * sizeof(float **));
block2 = malloc(max_channels * sizeof(float **));
// allocate block memory
for (i = 0; i < max_channels; i++) {
block1[i] = malloc(max_im_size * sizeof(float *));
block2[i] = malloc(max_im_size * sizeof(float *));
for (j = 0; j < max_im_size; j++) {
block1[i][j] = malloc(max_im_size * sizeof(float));
block2[i][j] = malloc(max_im_size * sizeof(float));
}
}
#if SPARSE_CONVOLUTIONS
wc_sparse = (csr_t ****)malloc(CONV_LEVELS * sizeof(csr_t ***));
for (l = 0; l < CONV_LEVELS; l++) {
wc_sparse[l] = (csr_t ***)malloc(cshape[l][0] * sizeof(csr_t **));
for (i = 0; i < cshape[l][0]; i++) {
wc_sparse[l][i] = (csr_t **)malloc(cshape[l][1] * sizeof(csr_t *));
}
}
// wc memory allocated below will be freed in read_weights if
// SPARSE_CONVOLUTIONS
#endif // SPARSE_CONVOLUTIONS
wc = malloc(CONV_LEVELS * sizeof(float ****));
// allocate kernel memory
for (l = 0; l < CONV_LEVELS; l++) {
wc[l] = malloc(cshape[l][0] * sizeof(float ***));
for (i = 0; i < cshape[l][0]; i++) {
wc[l][i] = malloc(cshape[l][1] * sizeof(float **));
for (j = 0; j < cshape[l][1]; j++) {
wc[l][i][j] = malloc(cshape[l][2] * sizeof(float *));
for (k = 0; k < cshape[l][2]; k++) {
wc[l][i][j][k] = malloc(cshape[l][3] * sizeof(float));
}
}
}
}
// allocate batchnorm memory
batchnorm_weights = malloc(27 * sizeof(float *));
batchnorm_biases = malloc(27 * sizeof(float *));
batchnorm_means = malloc(27 * sizeof(float *));
batchnorm_vars = malloc(27 * sizeof(float *));
for (l = 0; l < CONV_LEVELS; l++) {
batchnorm_weights[l] = malloc(cshape[l][0] * sizeof(float));
batchnorm_biases[l] = malloc(cshape[l][0] * sizeof(float));
batchnorm_means[l] = malloc(cshape[l][0] * sizeof(float));
batchnorm_vars[l] = malloc(cshape[l][0] * sizeof(float));
}
wd = malloc(1 * sizeof(float **));
bd = malloc(1 * sizeof(float *));
for (l = 0; l < 1; l++) {
wd[l] = malloc(dshape[l][0] * sizeof(float *));
for (i = 0; i < dshape[l][0]; i++) {
wd[l][i] = malloc(dshape[l][1] * sizeof(float));
}
bd[l] = malloc(dshape[l][1] * sizeof(float));
}
// allocate dense memory
mem_block1_dense = calloc(mem_block_dense_shape, sizeof(float));
mem_block2_dense = calloc(mem_block_dense_shape, sizeof(float));
}
/****************************************************************************************************************************/
void free_memory() {
int i, j, k, l;
// Free convolution weights
for (l = 0; l < CONV_LEVELS; l++) {
#if SPARSE_CONVOLUTIONS
for (i = 0; i < cshape[l][0]; i++) {
for (j = 0; j < cshape[l][1]; j++) {
free(wc_sparse[l][i][j]);
}
free(wc_sparse[l][i]);
}
free(wc_sparse[l]);
#else
for (i = 0; i < cshape[l][0]; i++) {
for (j = 0; j < cshape[l][1]; j++) {
for (k = 0; k < cshape[l][2]; k++) {
free(wc[l][i][j][k]);
}
free(wc[l][i][j]);
}
free(wc[l][i]);
}
free(wc[l]);
#endif
}
// free(wc);
// free(bc);
#if SPARSE_CONVOLUTIONS
free(wc_sparse);
#else
free(wc);
#endif // SPARSE_CONVOLUTIONS
// Free dense weights
for (l = 0; l < 1; l++) {
for (i = 0; i < dshape[l][0]; i++) {
free(wd[l][i]);
}
free(wd[l]);
free(bd[l]);
}
free(wd);
free(bd);
// Free memblocks
for (i = 0; i < mem_block_shape[0]; i++) {
for (j = 0; j < mem_block_shape[1]; j++) {
free(block1[i][j]);
free(block2[i][j]);
}
free(block1[i]);
free(block2[i]);
}
free(block1);
free(block2);
free(mem_block1_dense);
free(mem_block2_dense);
}
/****************************************************************************************************************************/
void read_weights(char *in_file, int lvls) {
float dval;
int i, j, k, l, m, z;
FILE *iin;
int total_lvls_read = 0;
// printf("\nin_file es: %s\n\n", in_file);
iin = fopen(in_file, "r");
if (iin == NULL) {
printf("Weights file %s absent\n", in_file);
exit(1);
}
// Reading convolution weights (store them flipped from begining)
// no biases
for (l = 0; l < CONV_LEVELS; l++) {
printf("Read conv block %d weights\n", l);
for (i = 0; i < cshape[l][0]; i++) {
for (j = 0; j < cshape[l][1]; j++) {
for (k = 0; k < cshape[l][2]; k++) {
for (m = 0; m < cshape[l][3]; m++) {
fscanf(iin, "%f", &dval);
wc[l][i][j][k][m] = dval;
}
}
}
}
total_lvls_read += 1;
}
for (z = 0; z < CONV_LEVELS; z++) {
// batchnorm weights and biases
printf("Read batchnorm block %d weights\n", z);
for (i = 0; i < cshape[z][0]; i++) {
fscanf(iin, "%f", &dval);
batchnorm_weights[z][i] = dval;
}
for (i = 0; i < cshape[z][0]; i++) {
fscanf(iin, "%f", &dval);
// printf("bias %i : %f \n", i, dval);
batchnorm_biases[z][i] = dval;
}
for (i = 0; i < cshape[z][0]; i++) {
fscanf(iin, "%f", &dval);
// printf("bias %i : %f \n", i, dval);
batchnorm_means[z][i] = dval;
}
for (i = 0; i < cshape[z][0]; i++) {
fscanf(iin, "%f", &dval);
// printf("bias %i : %f \n", i, dval);
batchnorm_vars[z][i] = dval;
}
}
if (total_lvls_read >= lvls && lvls != -1) return;
// Reading dense weights
int num_dense_layers = 1;
for (z = 0; z < num_dense_layers; z++) {
printf("Read dense block %d weights\n", z);
for (i = 0; i < dshape[z][0]; i++) {
for (j = 0; j < dshape[z][1]; j++) {
fscanf(iin, "%f", &dval);
// printf("weight: %i : %f \n", i, dval);
wd[z][i][j] = dval;
}
}
for (i = 0; i < dshape[z][1]; i++) {
fscanf(iin, "%f", &dval);
// printf("bias %i : %f \n", i, dval);
bd[z][i] = dval;
}
}
fclose(iin);
/////////////**************** SPARSE ************/////////////////////////////
#if SPARSE_CONVOLUTIONS
// convert to sparse format
for (l = 0; l < CONV_LEVELS; l++)
for (i = 0; i < cshape[l][0]; i++)
for (j = 0; j < cshape[l][1]; j++) {
// printf("going for %d/%d, %d/%d, %d/%d\n", l, 13, i, cshape[l][0], j,
// cshape[l][1]);
csr_t *a = dense2csr2(cshape[l][2], cshape[l][3], wc[l][i][j]);
// print_csr(a);
wc_sparse[l][i][j] = a;
// printf("done..%d/%d, %d/%d, %d/%d\n", l, 13, i, cshape[l][0], j,
// cshape[l][1]);
}
// Free convolution weights
#if FIRST_CONV_SPARSE == 0
l = 0;
// allocate new memory for first conv and copy from wc
float *****wc_first_conv = (float *****)malloc(1 * sizeof(float ****));
wc_first_conv[l] = (float ****)malloc(cshape[l][0] * sizeof(float ***));
int k1, k2;
for (i = 0; i < cshape[l][0]; i++) {
wc_first_conv[l][i] = (float ***)malloc(cshape[l][1] * sizeof(float **));
for (j = 0; j < cshape[l][1]; j++) {
wc_first_conv[l][i][j] = (float **)malloc(cshape[l][2] * sizeof(float *));
for (k1 = 0; k1 < cshape[l][2]; k1++) {
wc_first_conv[l][i][j][k1] =
(float *)malloc(cshape[l][3] * sizeof(float));
for (k2 = 0; k2 < cshape[l][3]; k2++)
wc_first_conv[l][i][j][k1][k2] = wc[l][i][j][k1][k2];
}
}
}
#endif // FIRST_CONV_SPARSE == 0
// free up all dense conv layer representation
for (l = 0; l < CONV_LEVELS; l++) {
for (i = 0; i < cshape[l][0]; i++) {
for (j = 0; j < cshape[l][1]; j++) {
for (k = 0; k < cshape[l][2]; k++) {
free(wc[l][i][j][k]);
}
free(wc[l][i][j]);
}
free(wc[l][i]);
}
free(wc[l]);
}
free(wc);
#if FIRST_CONV_SPARSE == 0
// replace old wc pointer with the data for only first conv layer created
// above
wc = wc_first_conv;
#endif // FIRST_CONV_SPARSE == 0
#endif // SPARSE_CONVOLUTIONS
}
/****************************************************************************************************************************/
void read_image(char *in_file) {
int i, j, l;
FILE *iin;
float dval;
iin = fopen(in_file, "r");
if (iin == NULL) {
printf("Image file %s absent\n", in_file);
exit(1);
}
/* Reading image */
for (i = 0; i < SIZE; i++) {
for (j = 0; j < SIZE; j++) {
for (l = 0; l < 3; l++) {
fscanf(iin, "%f", &dval);
block1[l][i][j] = dval;
}
}
}
}
/****************************************************************************************************************************/
void convolution_3_x_3(float **matrix, float **kernel, float **out, int size,
int stride) {
int i, j;
float sum;
float zeropad[size + 2][size + 2];
memset(zeropad, 0, ((size + 2) * (size + 2) * sizeof(float))); // jack
for (i = 0; i < size; i++) {
for (j = 0; j < size; j++) {
zeropad[i + 1][j + 1] = matrix[i][j];
}
}
for (i = 0; i < size; i = i + stride) {
for (j = 0; j < size; j = j + stride) {
sum = zeropad[i][j] * kernel[0][0] + zeropad[i][j + 1] * kernel[0][1] +
zeropad[i][j + 2] * kernel[0][2] +
zeropad[i + 1][j] * kernel[1][0] +
zeropad[i + 1][j + 1] * kernel[1][1] +
zeropad[i + 1][j + 2] * kernel[1][2] +
zeropad[i + 2][j] * kernel[2][0] +
zeropad[i + 2][j + 1] * kernel[2][1] +
zeropad[i + 2][j + 2] * kernel[2][2];
out[i][j] += sum;
}
}
}
/****************************************************************************************************************************/
/****************************************************************************************************************************/
void pointwise_convolution(float ****point_kernel, float ***block2,
float ***block1, int input_channels,
int output_channels, int image_size) {
struct timeval start, end;
gettimeofday(&start, NULL);
int i, j, k, l;
float sum;
for (i = 0; i < output_channels; i++) {
for (j = 0; j < image_size; j++) {
for (k = 0; k < image_size; k++) {
sum = 0.;
for (l = 0; l < input_channels; l++) {
sum += block2[l][j][k] *
point_kernel[i][l][0]
[0]; // 0 because they are always 1x1 filters
}
block1[i][j][k] = sum;
}
}
}
gettimeofday(&end, NULL);
pw_conv_time += get_seconds(start, end);
}
/****************************************************************************************************************************/
void batchnorm_and_relu(float ***in, float ***out, float *weights, float *bias,
float *mean, float *var, int num_channels,
int image_size) {
int channel, i, j;
// ((x - mean) * invstd) * w + b
#pragma omp parallel for private(channel, i, j) schedule(dynamic, 1) \
num_threads(NUMBER_OF_THREADS)
for (channel = 0; channel < num_channels; channel++) {
float invstd = 1. / sqrt(var[channel] + 0.000001);
for (i = 0; i < image_size; i++) {
for (j = 0; j < image_size; j++) {
out[channel][i][j] =
(weights[channel] * invstd) * in[channel][i][j] +
(bias[channel] - ((weights[channel] * mean[channel]) * invstd));
// out[channel][i][j] = ((in[channel][i][j] - mean[channel]) * invstd) *
// weights[channel] + bias[channel];
if (out[channel][i][j] < 0.f) out[channel][i][j] = 0.f;
}
}
}
}
/****************************************************************************************************************************/
void depthwise_convolution(float ***block1, float ***block2,
float ****depth_kernel, float ****point_kernel,
int level) {
int i, j;
int input_channels = cshape[level][0];
int output_channels = cshape[level + 1][0];
// printf("level %i: %i ==> %i\n", level, input_channels, output_channels);
#pragma omp parallel for private(i) schedule(dynamic, 1) \
num_threads(NUMBER_OF_THREADS)
for (i = 0; i < input_channels; i++) {
#if SPARSE_CONVOLUTIONS
convolution_3_x_3_sparse(block1[i], wc_sparse[level][i][0], block2[i],
im_sizes[level], strides[level]);
#else
convolution_3_x_3(block1[i], depth_kernel[i][0], block2[i], im_sizes[level],
strides[level]);
#endif
}
batchnorm_and_relu(block2, block1, batchnorm_weights[level],
batchnorm_biases[level], batchnorm_means[level],
batchnorm_vars[level], input_channels,
im_sizes[level + 1]);
reset_mem_block(block2);
level++;
// now do linear combination of the elements in output and write them back
// into the first memory block
#if SPARSE_CONVOLUTIONS
#pragma omp parallel for private(i, j) schedule(dynamic, 1) \
num_threads(NUMBER_OF_THREADS)
for (i = 0; i < output_channels; i++) {
for (j = 0; j < input_channels; j++) {
pointwise_convolution_sparse(block2[j], wc_sparse[level][i][j], block1[j],
im_sizes[level]);
}
}
#else
pointwise_convolution(point_kernel, block1, block2, input_channels,
output_channels, im_sizes[level]);
#endif
batchnorm_and_relu(block2, block1, batchnorm_weights[level],
batchnorm_biases[level], batchnorm_means[level],
batchnorm_vars[level], output_channels,
im_sizes[level + 1]);
reset_mem_block(block2);
}
/****************************************************************************************************************************/
void add_bias_and_relu_flatten(float *out, float *bs, int size, int relu) {
int i;
for (i = 0; i < size; i++) {
out[i] += bs[i];
// printf("%f\n", out[i]);
if (relu == 1) {
if (out[i] < 0) out[i] = 0.f;
}
}
}
/****************************************************************************************************************************/
void flatten(float ***in, float *out, int sh0, int sh1, int sh2) {
int i, j, k, total = 0;
for (i = 0; i < sh0; i++) {
for (j = 0; j < sh1; j++) {
for (k = 0; k < sh2; k++) {
out[total] = in[i][j][k];
total += 1;
}
}
}
}
/****************************************************************************************************************************/
void dense(float *in, float **weights, float *out, int sh_in, int sh_out) {
struct timeval start, end;
gettimeofday(&start, NULL);
int i, j;
for (i = 0; i < sh_out; i++) {
float sum = 0.0;
for (j = 0; j < sh_in; j++) {
sum += in[j] * weights[j][i];
}
out[i] = sum;
}
gettimeofday(&end, NULL);
dense_time += get_seconds(start, end);
}
/****************************************************************************************************************************/
void write_out_block(int layer, float ***block) {
int layer_name = layer; // * 2 - 1;
char filename[16];
sprintf(filename, "outputs/output%d", layer_name);
FILE *f = fopen(filename, "w");
if (f == NULL) {
printf("Error opening file!\n");
exit(1);
}
for (int i = 0; i < 64; i++) {
for (int j = 0; j < mem_block_shape[1]; j++) {
for (int k = 0; k < mem_block_shape[2]; k++) {
fprintf(f, "%f \n", block[i][j][k]);
}
}
}
fclose(f);
}
/****************************************************************************************************************************/
void write_out_layer(int layer) {
int layer_name = layer; // * 2 - 1;
char filename[7];
sprintf(filename, "layer%d", layer_name);
FILE *f = fopen(filename, "w");
int depth = 1;
if (f == NULL) {
printf("Error opening file!\n");
exit(1);
}
for (int o = 0; o < cshape[layer][0]; o++) {
for (int i = 0; i < cshape[layer][1]; i++) {
for (int k_h = 0; k_h < cshape[layer][2]; k_h++) {
for (int k_w = 0; k_w < cshape[layer][3]; k_w++) {
fprintf(f, "%f ", wc[layer][o][i][k_h][k_w]);
}
}
fprintf(f, "\n");
}
}
fclose(f);
layer_name = layer + 1;
char filename2[7];
sprintf(filename2, "layer%d", layer_name);
// get batchnorms
FILE *f2 = fopen(filename2, "w");
if (f2 == NULL) {
printf("Error opening file!\n");
exit(1);
}
for (int i = 0; i < cshape[layer][0]; i++) {
fprintf(f2, "%f \n", batchnorm_weights[layer][i]);
}
fprintf(f2, "\n\n\n");
for (int i = 0; i < cshape[layer][0]; i++) {
fprintf(f2, "%f \n", batchnorm_biases[layer][i]);
}
fprintf(f2, "\n\n\n");
for (int i = 0; i < cshape[layer][0]; i++) {
fprintf(f2, "%f \n", batchnorm_means[layer][i]);
}
fprintf(f2, "\n\n\n");
for (int i = 0; i < cshape[layer][0]; i++) {
fprintf(f2, "%f \n", batchnorm_vars[layer][i]);
}
fclose(f);
}
/****************************************************************************************************************************/
void output_predictions(FILE *out, int only_convolution, int size,
int cur_size) {
int i;
int c = 0;
if (only_convolution == 1) {
// for (i = 0; i < 512*7*7; i++) {
for (i = 0; i < size * cur_size * cur_size; i++) {
fprintf(out, "%g\n", mem_block1_dense[i]);
}
} else {
double maximum = -1;
// dshape[0][1] ==> 10
for (i = 0; i < dshape[0][1]; i++) {
fprintf(out, "%g\n", mem_block2_dense[i]);
if (mem_block1_dense[i] > maximum) {
maximum = mem_block2_dense[i];
c = i + 1;
}
}
fprintf(out, "\n");
printf("This image depicts class: %d\n", c);
}
}
/****************************************************************************************************************************/
void get_mobilenet_predict() {
int level = 0;
int i, j;
// normal convolution
#pragma omp parallel for private(i, j) schedule(dynamic, 1) \
num_threads(NUMBER_OF_THREADS)
for (i = 0; i < cshape[level][0]; i++) {
for (j = 0; j < cshape[level][1]; j++) {
#if FIRST_CONV_SPARSE
convolution_3_x_3_sparse(block1[j], wc_sparse[level][i][j], block2[i],
im_sizes[level], 1);
#else
convolution_3_x_3(block1[j], wc[level][i][j], block2[i], im_sizes[level],
1);
#endif
}
}
batchnorm_and_relu(block2, block1, batchnorm_weights[level],
batchnorm_biases[level], batchnorm_means[level],
batchnorm_vars[level], 64, 64);
reset_mem_block(block2);
// depthwise convolutions
for (level = 1; level < (CONV_LEVELS - 1); level = level + 2) {
depthwise_convolution(block1, block2, wc[level], wc[level + 1], (level));
}
// flatten
flatten(block1, mem_block1_dense, cshape[level][0], im_sizes[level],
im_sizes[level]);
// dense
level = 0;
dense(mem_block1_dense, wd[level], mem_block2_dense, dshape[level][0],
dshape[level][1]);
add_bias_and_relu_flatten(mem_block2_dense, bd[level], dshape[level][1], 0);
reset_mem_block_dense(mem_block1_dense);
return;
}
/****************************************************************************************************************************/
char *trimwhitespace(char *str) {
char *end;
// Trim leading space
while (isspace((unsigned char)*str)) str++;
if (*str == 0) // All spaces?
return str;
// Trim trailing space
end = str + strlen(str) - 1;
while (end > str && isspace((unsigned char)*end)) end--;
// Write new null terminator
*(end + 1) = 0;
return str;
}
/****************************************************************************************************************************/
int main(int argc, char *argv[]) {
FILE *file_list, *results;
char buf[1024];
struct timeval tStart, tEnd;
double deltaTime;
char *weights_file;
char *image_list_file;
char *output_file;
int lvls = -1;
int only_convolution = 0;
//-----------------------------------------------------------------------
printf("Using %d threads\n", NUMBER_OF_THREADS);
if (argc != 4 && argc != 5) {
printf(
"Usage: <program.exe> <weights file> <images list file> <output file> "
"<only_convolution [optional]>\n");
return 0;
}
weights_file = argv[1];
// printf("%s\n", weights_file);
image_list_file = argv[2];
output_file = argv[3];
if (argc == 5) {
lvls = 20;
only_convolution = 1;
}
//-----------------------------------------------------------------------
init_memory();
file_list = fopen(image_list_file, "r");
if (file_list == NULL) {
printf("Check file list location: %s\n", image_list_file);
return 1;
}
results = fopen(output_file, "w");
if (results == NULL) {
printf("Couldn't open file for writing: %s\n", output_file);
return 1;
}
gettimeofday(&tStart, NULL);
read_weights(weights_file, lvls);
gettimeofday(&tEnd, NULL);
deltaTime = get_seconds(tStart, tEnd);
printf("Reading weights: %.3lf sec\n", deltaTime);
while (!feof(file_list)) {
pw_conv_time = 0.0;
dense_time = 0.0;
fgets(buf, 1024, file_list);
if (strlen(buf) == 0) {
break;
}
// printf("%d\n", strlen(buf));
read_image(trimwhitespace(buf));
gettimeofday(&tStart, NULL);
get_mobilenet_predict();
gettimeofday(&tEnd, NULL);
deltaTime = get_seconds(tStart, tEnd);
printf("Infer image %s: %.3lf sec\n", buf, deltaTime);
printf("pw_conv time: %.3lf sec\n", pw_conv_time);
printf("dense time: %.3lf sec\n", dense_time);
output_predictions(results, only_convolution, 1024, 1);
}
// free_memory();
fclose(file_list);
return 0;
}
|
cherk.c | #include "blas.h"
#include "error.h"
#include <stdio.h>
#include "handle.h"
#include "config.h"
#include "cherk.fatbin.c"
static inline size_t min(size_t a, size_t b) { return (a < b) ? a : b; }
static inline size_t max(size_t a, size_t b) { return (a > b) ? a : b; }
static inline CUresult cuMemcpyHtoD2DAsync(CUdeviceptr A, size_t lda, size_t ai, size_t aj,
const void * B, size_t ldb, size_t bi, size_t bj,
size_t m, size_t n, size_t elemSize, CUstream stream) {
CUDA_MEMCPY2D copy = {
bi * elemSize, bj, CU_MEMORYTYPE_HOST, B, 0, 0, ldb * elemSize,
ai * elemSize, aj, CU_MEMORYTYPE_DEVICE, NULL, A, 0, lda * elemSize,
m * elemSize, n };
return cuMemcpy2DAsync(©, stream);
}
static inline CUresult cuMemcpyDtoH2DAsync(void * A, size_t lda, size_t ai, size_t aj,
CUdeviceptr B, size_t ldb, size_t bi, size_t bj,
size_t m, size_t n, size_t elemSize, CUstream stream) {
CUDA_MEMCPY2D copy = {
bi * elemSize, bj, CU_MEMORYTYPE_DEVICE, NULL, B, 0, ldb * elemSize,
ai * elemSize, aj, CU_MEMORYTYPE_HOST, A, 0, 0, lda * elemSize,
m * elemSize, n };
return cuMemcpy2DAsync(©, stream);
}
static const float zero = 0.0f;
static const float one = 1.0f;
static const float complex czero = 0.0f + 0.0f * I;
void cherk(CBlasUplo uplo, CBlasTranspose trans,
size_t n, size_t k,
float alpha, const float complex * restrict A, size_t lda,
float beta, float complex * restrict C, size_t ldc) {
const size_t nRowA = (trans == CBlasNoTrans) ? n : k;
int info = 0;
if (trans == CBlasTrans)
info = 2;
else if (lda < nRowA)
info = 7;
else if (ldc < n)
info = 10;
if (info != 0) {
XERBLA(info);
return;
}
if (n == 0 || ((alpha == zero || k == 0) && beta == one))
return;
if (alpha == zero) {
if (uplo == CBlasUpper) {
if (beta == zero) {
#pragma omp parallel for
for (size_t j = 0; j < n; j++) {
for (size_t i = 0; i <= j; i++)
C[j * ldc + i] = zero;
}
}
else {
#pragma omp parallel for
for (size_t j = 0; j < n; j++) {
for (size_t i = 0; i < j; i++)
C[j * ldc + i] *= beta;
C[j * ldc + j] = beta * crealf(C[j * ldc + j]);
}
}
}
else {
if (beta == zero) {
#pragma omp parallel for
for (size_t j = 0; j < n; j++) {
for (size_t i = j; i < n; i++)
C[j * ldc + i] = zero;
}
}
else {
#pragma omp parallel for
for (size_t j = 0; j < n; j++) {
C[j * ldc + j] = beta * crealf(C[j * ldc + j]);
for (size_t i = j + 1; i < n; i++)
C[j * ldc + i] *= beta;
}
}
}
return;
}
if (trans == CBlasNoTrans) {
if (uplo == CBlasUpper) {
#pragma omp parallel for
for (size_t j = 0; j < n; j++) {
if (beta == zero) {
for (size_t i = 0; i <= j; i++)
C[j * ldc + i] = zero;
}
else if (beta != one) {
for (size_t i = 0; i < j; i++)
C[j * ldc + i] *= beta;
C[j * ldc + j] = beta * crealf(C[j * ldc + j]);
}
else
C[j * ldc + j] = crealf(C[j * ldc + j]);
for (size_t l = 0; l < k; l++) {
if (A[l * lda + j] != zero) {
register float complex temp = alpha * conjf(A[l * lda + j]);
for (size_t i = 0; i < j; i++)
C[j * ldc + i] += temp * A[l * lda + i];
C[j * ldc + j] = crealf(C[j * ldc + j]) + crealf(temp * A[l * lda + j]);
}
}
}
}
else {
#pragma omp parallel for
for (size_t j = 0; j < n; j++) {
if (beta == zero) {
for (size_t i = j; i < n; i++)
C[j * ldc + i] = zero;
}
else if (beta != one) {
C[j * ldc + j] = beta * crealf(C[j * ldc + j]);
for (size_t i = j + 1; i < n; i++)
C[j * ldc + i] *= beta;
}
else
C[j * ldc + j] = crealf(C[j * ldc + j]);
for (size_t l = 0; l < k; l++) {
if (A[l * lda + j] != zero) {
register float complex temp = alpha * conjf(A[l * lda + j]);
C[j * ldc + j] = crealf(C[j * ldc + j]) + crealf(temp * A[l * lda + j]);
for (size_t i = j + 1; i < n; i++)
C[j * ldc + i] += temp * A[l * lda + i];
}
}
}
}
}
else {
if (uplo == CBlasUpper) {
#pragma omp parallel for
for (size_t j = 0; j < n; j++) {
for (size_t i = 0; i < j; i++) {
register float complex temp = czero;
for (size_t l = 0; l < k; l++)
temp += conjf(A[i * lda + l]) * A[j * lda + l];
if (beta == zero)
C[j * ldc + i] = alpha * temp;
else
C[j * ldc + i] = alpha * temp + beta * C[j * ldc + i];
}
register float rtemp = zero;
for (size_t l = 0; l < k; l++)
rtemp += conjf(A[j * lda + l]) * A[j * lda + l];
if (beta == zero)
C[j * ldc + j] = alpha * rtemp;
else
C[j * ldc + j] = alpha * rtemp + beta * crealf(C[j * ldc + j]);
}
}
else {
#pragma omp parallel for
for (size_t j = 0; j < n; j++) {
register float rtemp = zero;
for (size_t l = 0; l < k; l++)
rtemp += conjf(A[j * lda + l]) * A[j * lda + l];
if (beta == zero)
C[j * ldc + j] = alpha * rtemp;
else
C[j * ldc + j] = alpha * rtemp + beta * crealf(C[j * ldc + j]);
for (size_t i = j + 1; i < n; i++) {
register float complex temp = czero;
for (size_t l = 0; l < k; l++)
temp += conjf(A[i * lda + l]) * A[j * lda + l];
if (beta == zero)
C[j * ldc + i] = alpha * temp;
else
C[j * ldc + i] = alpha * temp + beta * C[j * ldc + i];
}
}
}
}
}
CUresult cuCherk(CUBLAShandle handle, CBlasUplo uplo, CBlasTranspose trans,
size_t n, size_t k,
float alpha, CUdeviceptr A, size_t lda,
float beta, CUdeviceptr C, size_t ldc, CUstream stream) {
const size_t nRowA = (trans == CBlasNoTrans) ? n : k;
int info = 0;
if (trans == CBlasTrans)
info = 2;
else if (lda < nRowA)
info = 7;
else if (ldc < n)
info = 10;
if (info != 0) {
XERBLA(info);
return CUDA_ERROR_INVALID_VALUE;
}
if (n == 0 || ((alpha == zero || k == 0) && beta == one))
return CUDA_SUCCESS;
CU_ERROR_CHECK(cuCtxPushCurrent(handle->context));
if (handle->cherk == NULL)
CU_ERROR_CHECK(cuModuleLoadData(&handle->cherk, imageBytes));
const unsigned int mb = (trans == CBlasNoTrans) ? 64 : 32;
const unsigned int nb = (trans == CBlasNoTrans) ? 8 : 16;
const unsigned int kb = 8;
const unsigned int bx = 8;
const unsigned int by = 8;
char name[89];
snprintf(name, 89,
"_Z5cherkIL9CBlasUplo%dEL14CBlasTranspose%dELj%uELj%uELj%uELj%uELj%uEEvPK6float2PS2_ffiiii",
uplo, trans, mb, nb, kb, bx, by);
CUfunction function;
CU_ERROR_CHECK(cuModuleGetFunction(&function, handle->cherk, name));
void * params[] = { &A, &C, &alpha, &beta, &lda, &ldc, &n, &k };
CU_ERROR_CHECK(cuLaunchKernel(function, (unsigned int)(n + mb - 1) / mb, (unsigned int)(n + nb - 1) / nb, 1,
bx, by, 1, 0, stream, params, NULL));
CU_ERROR_CHECK(cuCtxPopCurrent(&handle->context));
return CUDA_SUCCESS;
}
CUresult cuMultiGPUCherk(CUmultiGPUBLAShandle handle,
CBlasUplo uplo, CBlasTranspose trans,
size_t n, size_t k,
float alpha, const float complex * restrict A, size_t lda,
float beta, float complex * restrict C, size_t ldc) {
const size_t nRowA = (trans == CBlasNoTrans) ? n : k;
int info = 0;
if (trans == CBlasTrans)
info = 2;
else if (lda < nRowA)
info = 7;
else if (ldc < n)
info = 10;
if (info != 0) {
XERBLA(info);
return CUDA_ERROR_INVALID_VALUE;
}
if (n == 0 || ((alpha == zero || k == 0) && beta == one))
return CUDA_SUCCESS;
if (alpha == zero) {
if (uplo == CBlasUpper) {
if (beta == zero) {
#pragma omp parallel for
for (size_t j = 0; j < n; j++) {
for (size_t i = 0; i <= j; i++)
C[j * ldc + i] = zero;
}
}
else {
#pragma omp parallel for
for (size_t j = 0; j < n; j++) {
for (size_t i = 0; i <= j; i++)
C[j * ldc + i] *= beta;
}
}
}
else {
if (beta == zero) {
#pragma omp parallel for
for (size_t j = 0; j < n; j++) {
for (size_t i = j; i < n; i++)
C[j * ldc + i] = zero;
}
}
else {
#pragma omp parallel for
for (size_t j = 0; j < n; j++) {
for (size_t i = j; i < n; i++)
C[j * ldc + i] *= beta;
}
}
}
return CUDA_SUCCESS;
}
const size_t nb = (trans == CBlasNoTrans) ? CGEMM_N_MB : CGEMM_C_NB;
if (n < nb) {
cherk(uplo, trans, n, k, alpha, A, lda, beta, C, ldc);
return CUDA_SUCCESS;
}
if (trans == CBlasNoTrans) {
if (uplo == CBlasUpper) {
for (size_t j = nb; j < n; j += nb)
CU_ERROR_CHECK(cuMultiGPUCgemm(handle, CBlasNoTrans, CBlasConjTrans, j, min(n - j, nb), k, alpha, A, lda, &A[j], lda, beta, &C[j * ldc], ldc));
}
else {
const size_t m = n - nb;
for (size_t j = 0; j < m; j += nb) {
const size_t jb = min(n - j, nb);
CU_ERROR_CHECK(cuMultiGPUCgemm(handle, CBlasNoTrans, CBlasConjTrans, n - j - jb, jb, k, alpha, &A[j + jb], lda, &A[j], lda, beta, &C[j * ldc + j + jb], ldc));
}
}
for (size_t j = 0; j < n; j += nb)
cherk(uplo, trans, min(n - j, nb), k, alpha, &A[j], lda, beta, &C[j * ldc + j], ldc);
}
else {
if (uplo == CBlasUpper) {
for (size_t j = nb; j < n; j += nb)
CU_ERROR_CHECK(cuMultiGPUCgemm(handle, CBlasConjTrans, CBlasNoTrans, j, min(n - j, nb), k, alpha, A, lda, &A[j * lda], lda, beta, &C[j * ldc], ldc));
}
else {
const size_t m = n - nb;
for (size_t j = 0; j < m; j += nb) {
const size_t jb = min(n - j, nb);
CU_ERROR_CHECK(cuMultiGPUCgemm(handle, CBlasConjTrans, CBlasNoTrans, n - j - jb, jb, k, alpha, &A[(j + jb) * lda], lda, &A[j * lda], lda, beta, &C[j * ldc + j + jb], ldc));
}
}
for (size_t j = 0; j < n; j += nb)
cherk(uplo, trans, min(n - j, nb), k, alpha, &A[j * lda], lda, beta, &C[j * ldc + j], ldc);
}
return CUDA_SUCCESS;
}
|
openmp.c | #include<stdio.h>
#include<stdlib.h>
#include<math.h>
#include<time.h>
#include<omp.h>
void sample_rand(const double a, const double b ,const int dim, double *x) {
#pragma omp parallel for
for(int i=0;i<dim;++i) {
double tmp = ((double) rand())/((double) RAND_MAX);
x[i] = (b-a)*tmp + a;
}
}
int main(int argc, char** argv)
{
double start_time = omp_get_wtime();
long N = atol( argv[1] );
srand(time(NULL)); // each MPI process gets a unique seed
const int dim = 10;
double x[dim]; // array of random numbers
double V = 4.0, integral = 0.0, sum = 0.0, expo=0.0;
int count=0;
for(int i=N;i>1;i=i/4)
{
count++; // to get the number of intermediate integrals
}
double integrals[count]; // this array stores all intermediate integral values.
for(int i=0;i<N;i++)
{
sample_rand(-1.,1.,dim,x);
double f;
for(int j=0;j<N;j++){
f = pow(1-x[j],2)+100*pow(x[j+1]-pow(x[j],2),2);
sum+=f;
}
//printf("%lf\n",sum);
expo=exp(-sum);
int k=1;
for(int j=1;j<=i+1;j=pow(4,k))
{
if(i+1==j)
integrals[k-1]=V*expo/N;
k++;
}
}
for(int i=0;i<count;i++)
{
printf("%lf %e\n",pow(4,i+1),integrals[i]);
}
integral = V*expo/N;
double time = omp_get_wtime() - start_time;
//printf("%lf\n",time);
return 0;
}
|
NDArray.h | #ifndef NDARRAY_H
#define NDARRAY_H
#include <initializer_list>
#include <functional>
#include <shape.h>
#include "NativeOpExcutioner.h"
#include <memory/Workspace.h>
#include <indexing/NDIndex.h>
#include <indexing/IndicesList.h>
#include <graph/Intervals.h>
#include <array/DataType.h>
#include <stdint.h>
namespace nd4j {
template<typename T> class ND4J_EXPORT NDArray;
ND4J_EXPORT NDArray<float> operator-(const float, const NDArray<float>&);
ND4J_EXPORT NDArray<float16> operator-(const float16, const NDArray<float16>&);
ND4J_EXPORT NDArray<double> operator-(const double, const NDArray<double>&);
ND4J_EXPORT NDArray<float> operator+(const float, const NDArray<float>&);
ND4J_EXPORT NDArray<float16> operator+(const float16, const NDArray<float16>&);
ND4J_EXPORT NDArray<double> operator+(const double, const NDArray<double>&);
template<typename T> NDArray<T> mmul(const NDArray<T>&, const NDArray<T>&);
template<typename T>
class NDArray {
protected:
/**
* if true then array doesn't own buffer and simply points to another's buffer
*/
bool _isView = false;
/**
* pointer on flattened data array in memory
*/
T *_buffer = nullptr;
/**
* contains shape info: matrix rank, numbers of elements per each dimension, dimensions strides, element-wise-stride, c-like or fortan-like order
*/
Nd4jLong *_shapeInfo = nullptr;
/**
* pointer on externally allocated memory where _buffer and _shapeInfo are stored
*/
nd4j::memory::Workspace* _workspace = nullptr;
/**
* alternative buffers for special computational devices (like GPUs for CUDA)
*/
T* _bufferD = nullptr;
Nd4jLong *_shapeInfoD = nullptr;
/**
* indicates whether user allocates memory for _buffer/_shapeInfo by himself, in opposite case the memory must be allocated from outside
*/
bool _isShapeAlloc = false;
bool _isBuffAlloc = false;
/**
* type of array elements
*/
DataType _dataType = DataType_FLOAT;
std::string toStringValue(T value);
public:
/**
* default constructor, do not allocate memory, memory for array is passed from outside
*/
NDArray(T *buffer = nullptr, Nd4jLong* shapeInfo = nullptr, nd4j::memory::Workspace* workspace = nullptr);
NDArray(std::initializer_list<Nd4jLong> shape, nd4j::memory::Workspace* workspace = nullptr);
/**
* Constructor for scalar NDArray
*/
NDArray(T scalar);
/**
* copy constructor
*/
NDArray(const NDArray<T>& other);
/**
* move constructor
*/
NDArray(NDArray<T>&& other) noexcept;
#ifndef __JAVACPP_HACK__
// this method only available out of javacpp
/**
* This constructor creates vector of T
*
* @param values
*/
NDArray(std::initializer_list<T> values, nd4j::memory::Workspace* workspace = nullptr);
NDArray(std::vector<T> &values, nd4j::memory::Workspace* workspace = nullptr);
#endif
/**
* constructor, create empty array stored at given workspace
*/
NDArray(nd4j::memory::Workspace* workspace);
/**
* this constructor creates new NDArray with shape matching "other" array, do not copy "other" elements into new array
*/
NDArray(const NDArray<T> *other, const bool copyStrides = false, nd4j::memory::Workspace* workspace = nullptr);
/**
* constructor creates new NDArray using shape information from "shapeInfo", set all elements in new array to be zeros, if copyStrides is true then use stride values from "shapeInfo", else calculate strides independently
*/
NDArray(const Nd4jLong* shapeInfo, const bool copyStrides = false, nd4j::memory::Workspace* workspace = nullptr);
/**
* this constructor creates new array using shape information contained in vector argument
*/
NDArray(const char order, const std::vector<Nd4jLong> &shape, nd4j::memory::Workspace* workspace = nullptr);
/**
* This constructor creates new array with elements copied from data and using shape information stored in shape
*
* PLEASE NOTE: data will be copied AS IS, without respect to specified order. You must ensure order match here.
*/
NDArray(const char order, const std::vector<Nd4jLong> &shape, const std::vector<T> &data, nd4j::memory::Workspace* workspace = nullptr);
/**
* this constructor creates new array using given buffer (without memory allocating) and shape information stored in shape
*/
NDArray(T *buffer, const char order, const std::vector<Nd4jLong> &shape , nd4j::memory::Workspace* workspace = nullptr);
/**
* copy assignment operator
*/
NDArray<T>& operator=(const NDArray<T>& other);
/**
* move assignment operator
*/
NDArray<T>& operator=(NDArray<T>&& other) noexcept;
/**
* assignment operator, assigns the same scalar to all array elements
*/
NDArray<T>& operator=(const T scalar);
/**
* operators for memory allocation and deletion
*/
void* operator new(size_t i);
void operator delete(void* p);
/**
* method replaces existing buffer/shapeinfo, AND releases original pointers (if releaseExisting TRUE)
*/
void replacePointers(T *buffer, Nd4jLong *shapeInfo, const bool releaseExisting = true);
/**
* create a new array by replicating current array by repeats times along given dimension
* dimension - dimension along which to repeat elements
* repeats - number of repetitions
*/
NDArray<T>* repeat(int dimension, const std::vector<Nd4jLong>& repeats) const;
/**
* fill target array by repeating current array
* dimension - dimension along which to repeat elements
*/
void repeat(int dimension, NDArray<T>& target) const;
/**
* return _dataType;
*/
DataType dataType() const;
/**
* creates array which is view of this array
*/
NDArray<T>* getView();
/**
* creates array which points on certain sub-range of this array, sub-range is defined by given indices
*/
NDArray<T> *subarray(IndicesList& indices) const;
NDArray<T> *subarray(IndicesList& indices, std::vector<Nd4jLong>& strides) const;
NDArray<T>* subarray(const std::initializer_list<NDIndex*>& idx) const;
NDArray<T>* subarray(const Intervals& idx) const;
/**
* cast array elements to given dtype
*/
NDArray<T>* cast(DataType dtype);
void cast(NDArray<T>* target, DataType dtype);
/**
* returns _workspace
*/
nd4j::memory::Workspace* getWorkspace() const {
return _workspace;
}
/**
* returns _buffer
*/
T* getBuffer();
T* buffer();
/**
* returns _shapeInfo
*/
Nd4jLong* shapeInfo();
Nd4jLong* getShapeInfo() const;
/**
* if _bufferD==nullptr return _buffer, else return _bufferD
*/
T* specialBuffer();
/**
* if _shapeInfoD==nullptr return _shapeInfo, else return _shapeInfoD
*/
Nd4jLong* specialShapeInfo();
/**
* set values for _bufferD and _shapeInfoD
*/
void setSpecialBuffers(T * buffer, Nd4jLong *shape);
/**
* permutes (in-place) the dimensions in array according to "dimensions" array
*/
bool permutei(const std::initializer_list<int>& dimensions);
bool permutei(const std::vector<int>& dimensions);
bool permutei(const int* dimensions, const int rank);
bool permutei(const std::initializer_list<Nd4jLong>& dimensions);
bool permutei(const std::vector<Nd4jLong>& dimensions);
bool permutei(const Nd4jLong* dimensions, const int rank);
/**
* permutes the dimensions in array according to "dimensions" array, new array points on _buffer of this array
*/
NDArray<T>* permute(const std::initializer_list<int>& dimensions) const;
NDArray<T>* permute(const std::vector<int>& dimensions) const;
NDArray<T>* permute(const int* dimensions, const int rank) const;
void permute(const int* dimensions, const int rank, NDArray<T>& target) const;
void permute(const std::vector<int>& dimensions, NDArray<T>& target) const;
NDArray<T>* permute(const std::initializer_list<Nd4jLong>& dimensions) const;
NDArray<T>* permute(const std::vector<Nd4jLong>& dimensions) const;
NDArray<T>* permute(const Nd4jLong* dimensions, const int rank) const;
void permute(const Nd4jLong* dimensions, const int rank, NDArray<T>& target) const;
void permute(const std::vector<Nd4jLong>& dimensions, NDArray<T>& target) const;
/**
* This method streamlines given view or permuted array, and reallocates buffer
*/
void streamline(char order = 'a');
/**
* check whether array is contiguous in memory
*/
bool isContiguous();
/**
* prints information about array shape
* msg - message to print out
*/
void printShapeInfo(const char * msg = nullptr) const;
/**
* prints buffer elements
* msg - message to print out
* limit - number of array elements to print out
*/
void printBuffer(const char* msg = nullptr, Nd4jLong limit = -1);
/**
* prints buffer elements, takes into account offset between elements (element-wise-stride)
* msg - message to print out
* limit - number of array elements to print out
*/
void printIndexedBuffer(const char* msg = nullptr, Nd4jLong limit = -1) const;
std::string asIndexedString(Nd4jLong limit = -1);
std::string asString(Nd4jLong limit = -1);
/**
* this method assigns values of given array to this one
*/
void assign(const NDArray<T>* other);
/**
* this method assigns values of given array to this one
*/
void assign(const NDArray<T>& other);
/**
* this method assigns given value to all elements in array
*/
void assign(const T value);
/**
* returns new copy of this array, optionally in different order
*/
NDArray<T> *dup(const char newOrder = 'a');
/**
* returns sum of all elements of array
*/
T sumNumber() const;
/**
* returns mean number of array
*/
T meanNumber() const;
/**
* This method explicitly enforces new shape for this NDArray, old shape/stride information is lost
*/
void enforce(const std::initializer_list<Nd4jLong> &dimensions, char order = 'a');
void enforce(std::vector<Nd4jLong> &dimensions, char order = 'a');
/**
* calculates sum along dimension(s) in this array and save it to created reduced array
* dimensions - array of dimensions to calculate sum over
* keepDims - if true then put unities in place of reduced dimensions
*/
NDArray<T> *sum(const std::vector<int> &dimensions) const;
/**
* method reduces array by excluding its shapes along dimensions present in given dimensions vector, result is stored in new array to be returned
* dimensions - array of dimensions to reduce along
* keepDims - if true then put unities in place of reduced dimensions
*/
template<typename OpName>
NDArray<T>* reduceAlongDimension(const std::vector<int>& dimensions, const bool keepDims = false, const bool supportOldShapes = false) const;
template<typename OpName>
NDArray<T>* reduceAlongDimension(const std::initializer_list<int>& dimensions, const bool keepDims = false, const bool supportOldShapes = false) const;
template<typename OpName>
NDArray<T> reduceAlongDims(const std::vector<int>& dimensions, const bool keepDims = false, const bool supportOldShapes = false) const;
/**
* method reduces array by excluding its shapes along dimensions present in given dimensions vector
* target - where to save result of reducing
* dimensions - array of dimensions to reduce along
* keepDims - if true then put unities in place of reduced dimensions
* extras - extra parameters
*/
template<typename OpName>
void reduceAlongDimension(NDArray<T>* target, const std::vector<int>& dimensions, const bool keepDims = false, const bool supportOldShapes = false, T *extras = nullptr) const;
/**
* return variance of array elements set
* biasCorrected - if true bias correction will be applied
*/
template<typename OpName>
T varianceNumber(bool biasCorrected = true);
/**
* apply scalar operation to array
* extraParams - extra parameters for operation
*/
template<typename OpName>
T reduceNumber(T *extraParams = nullptr) const;
/**
* returns element index which corresponds to some condition imposed by operation
* extraParams - extra parameters for operation
*/
template<typename OpName>
Nd4jLong indexReduceNumber(T *extraParams = nullptr);
/**
* returns index of max element in a given array (optionally: along given dimension(s))
* dimensions - optional vector with dimensions
*/
Nd4jLong argMax(std::initializer_list<int> dimensions = {});
/**
* apply OpName transformation directly to array
* extraParams - extra parameters for operation
*/
template<typename OpName>
void applyTransform(T *extraParams = nullptr);
/**
* apply OpName transformation to array and store result in target
* target - where to store result
* extraParams - extra parameters for operation
*/
template<typename OpName>
void applyTransform(NDArray<T> *target, T *extraParams = nullptr);
/**
* apply OpName transformation to this array and store result in new array being returned
* extraParams - extra parameters for operation
*/
template<typename OpName>
NDArray<T> transform(T *extraParams = nullptr);
/**
* apply pairwise OpName transformation based on "this" and "other" arras elements, store result in this array
* other - second array necessary for pairwise operation
* extraParams - extra parameters for operation
*/
template<typename OpName>
void applyPairwiseTransform(NDArray<T> *other, T *extraParams);
/**
* apply pairwise OpName transformation based on "this" and "other" arras elements, store result in target array
* other - second array necessary for pairwise operation
* target - where to store result
* extraParams - extra parameters for operation
*/
template<typename OpName>
void applyPairwiseTransform(NDArray<T> *other, NDArray<T> *target, T *extraParams);
/**
* apply operation which requires broadcasting, broadcast a smaller array (tad) along bigger one (this)
* tad - array to broadcast
* dimensions - dimensions array to broadcast along
* target - where to store result
* extraParams - extra parameters for operation
*/
template<typename OpName>
void applyBroadcast(std::initializer_list<int> dimensions, const NDArray<T>* tad, NDArray<T>* target = nullptr, T* extraArgs = nullptr);
template <typename OpName>
void applyBroadcast(std::vector<int> &dimensions, const NDArray<T> *tad, NDArray<T> *target = nullptr, T *extraArgs = nullptr);
/**
* apply operation which requires broadcasting, broadcast one tensor along another, also this method checks the possibility of broadcasting
* other - input array
* extraParams - extra parameters for operation
*/
template <typename OpName>
NDArray<T> applyTrueBroadcast(const NDArray<T>& other, T *extraArgs = nullptr) const;
template <typename OpName>
NDArray<T>* applyTrueBroadcast(const NDArray<T>* other, T *extraArgs = nullptr) const;
/**
* apply operation which requires broadcasting, broadcast one tensor along another, also this method checks the possibility of broadcasting
* other - input array
* target - where to store result
* checkTargetShape - if true check whether target shape is suitable for broadcasting
* extraParams - extra parameters for operation
*/
template <typename OpName>
void applyTrueBroadcast(const NDArray<T>* other, NDArray<T>* target, const bool checkTargetShape = true, T *extraArgs = nullptr) const;
/**
* apply a scalar operation to an array
* scalar - input scalar
* target - where to store result
* extraParams - extra parameters for operation
*/
template<typename OpName>
void applyScalar(T scalar, NDArray<T>* target = nullptr, T *extraParams = nullptr);
/**
* apply a scalar operation to an array
* scalar - input array which is simple scalar
* target - where to store result
* extraParams - extra parameters for operation
*/
template<typename OpName>
void applyScalar(NDArray<T>& scalar, NDArray<T>* target = nullptr, T *extraParams = nullptr);
#ifndef __JAVACPP_HACK__
/**
* apply operation "func" to an array
* func - what operation to apply
* target - where to store result
*/
void applyLambda(const std::function<T(T)>& func, NDArray<T>* target = nullptr);
void applyIndexedLambda(const std::function<T(Nd4jLong, T)>& func, NDArray<T>* target = nullptr);
/**
* apply pairwise operation "func" to an array
* other - input array
* func - what pairwise operation to apply
* target - where to store result
*/
void applyPairwiseLambda(NDArray<T>* other, const std::function<T(T, T)>& func, NDArray<T>* target = nullptr);
void applyIndexedPairwiseLambda(NDArray<T>* other, const std::function<T(Nd4jLong, T, T)>& func, NDArray<T>* target = nullptr);
void applyTriplewiseLambda(NDArray<T>* second, NDArray<T> *third, const std::function<T(T, T, T)>& func, NDArray<T>* target = nullptr);
#endif
/**
* apply OpName random operation to array
* buffer - pointer on RandomBuffer
* y - optional input array
* z - optional input array
* extraArgs - extra parameters for operation
*/
template<typename OpName>
void applyRandom(nd4j::random::RandomBuffer *buffer, NDArray<T>* y = nullptr, NDArray<T>* z = nullptr, T* extraArgs = nullptr);
/**
* apply transpose operation to the copy of this array, that is this array remains unaffected
*/
NDArray<T> *transpose() const;
/**
* perform transpose operation and store result in target, this array remains unaffected
* target - where to store result
*/
void transpose(NDArray<T>& target) const;
/**
* apply in-place transpose operation to this array, so this array becomes transposed
*/
void transposei();
/**
* return array pointing on certain range of this array
* index - the number of array to be returned among set of possible arrays
* dimensions - array of dimensions to point on
*/
NDArray<T>* tensorAlongDimension(Nd4jLong index, const std::initializer_list<int>& dimensions) const;
NDArray<T>* tensorAlongDimension(Nd4jLong index, const std::vector<int>& dimensions) const;
/**
* returns the number of arrays pointing on specified dimension(s)
* dimensions - array of dimensions to point on
*/
Nd4jLong tensorsAlongDimension(const std::initializer_list<int> dimensions) const ;
Nd4jLong tensorsAlongDimension(const std::vector<int>& dimensions) const ;
/**
* returns true if elements of two arrays are equal to within given epsilon value
* other - input array to compare
* eps - epsilon, this value defines the precision of elements comparison
*/
bool equalsTo(const NDArray<T> *other, T eps = (T) 1e-5f) const;
bool equalsTo(NDArray<T> &other, T eps = (T) 1e-5f) const;
/**
* add given row vector to all rows of this array
* row - row vector to add
*/
void addiRowVector(const NDArray<T> *row);
/**
* add given row vector to all rows of this array, store result in target
* row - row vector to add
* target - where to store result
*/
void addRowVector(const NDArray<T> *row, NDArray<T>* target) const;
/**
* subtract given row vector from all rows of this array, store result in target
* row - row vector to subtract
* target - where to store result
*/
void subRowVector(const NDArray<T> *row, NDArray<T>* target) const;
/**
* multiply all rows of this array on given row vector, store result in target
* row - row vector to multiply on
* target - where to store result
*/
void mulRowVector(const NDArray<T> *row, NDArray<T>* target) const;
/**
* divide all rows of this array on given row vector, store result in target
* row - row vector to divide on
* target - where to store result
*/
void divRowVector(const NDArray<T> *row, NDArray<T>* target) const;
/**
* add given column vector to all columns of this array, store result in target
* column - column vector to add
* target - where to store result
*/
void addColumnVector(const NDArray<T> *column, NDArray<T>* target) const;
/**
* add given column vector to all columns of this array, this array becomes affected (in-place operation)
* column - column vector to add
*/
void addiColumnVector(const NDArray<T> *column);
/**
* multiply all columns of this array on given column vector, this array becomes affected (in-place operation)
* column - column vector to multiply on
*/
void muliColumnVector(const NDArray<T> *column);
/**
* returns number of bytes used by _buffer & _shapeInfo
*/
Nd4jLong memoryFootprint();
/**
* these methods suited for FlatBuffers use
*/
std::vector<T> getBufferAsVector();
std::vector<Nd4jLong> getShapeAsVector();
std::vector<Nd4jLong> getShapeInfoAsVector();
std::vector<int64_t> getShapeInfoAsFlatVector();
/**
* set new order and shape in case of suitable array length (in-place operation)
* order - order to set
* shape - shape to set
*
* if there was permute applied before or there are weird strides, then new buffer is allocated for array
*/
bool reshapei(const char order, const std::initializer_list<Nd4jLong>& shape);
bool reshapei(const char order, const std::vector<Nd4jLong>& shape);
bool reshapei(const std::initializer_list<Nd4jLong>& shape);
bool reshapei(const std::vector<Nd4jLong>& shape);
/**
* creates new array with corresponding order and shape, new array will point on _buffer of this array
* order - order to set
* shape - shape to set
*
* if permute have been applied before or there are weird strides, then new buffer is allocated for new array
*/
NDArray<T>* reshape(const char order, const std::vector<Nd4jLong>& shape) const;
/**
* calculate strides and set given order
* order - order to set
*/
void updateStrides(const char order);
/**
* change an array by repeating it the number of times given by reps (in-place operation)
* repeats - contains numbers of repetitions
*/
void tilei(const std::vector<Nd4jLong>& repeats);
/**
* returns new array which is created by by repeating of this array the number of times given by reps
* repeats - contains numbers of repetitions
*/
NDArray<T> tile(const std::vector<Nd4jLong>& repeats) const;
/**
* change an array by repeating it the number of times given by reps (in-place operation)
* repeats - contains numbers of repetitions
* target - where to store result
*/
void tile(const std::vector<Nd4jLong>& repeats, NDArray<T>& target) const;
/**
* change an array by repeating it the number of times to acquire the new shape which is the same as target shape
* target - where to store result
*/
void tile(NDArray<T>& target) const;
/**
* returns an array which is result of broadcasting of this and other arrays
* other - input array
*/
NDArray<T>* broadcast(const NDArray<T>& other);
/**
* check whether array's rows (arg=0) or columns (arg=1) create orthogonal basis
* arg - 0 -> row, 1 -> column
*/
bool hasOrthonormalBasis(const int arg);
/**
* check whether array is identity matrix
*/
bool isIdentityMatrix();
/**
* check whether array is unitary matrix
*/
bool isUnitary();
/**
* reduces dimensions in this array relying on index operation OpName
* dimensions - vector of dimensions to reduce along
* extraArgs - extra parameters for operation
*/
template<typename OpName>
NDArray<T>* applyIndexReduce(const std::vector<int>& dimensions, const T *extraParams = nullptr) const;
/**
* reduces dimensions in array relying on index operation OpName
* target - where to store result
* dimensions - vector of dimensions to reduce along
* extraArgs - extra parameters for operation
*/
template<typename OpName>
void applyIndexReduce(const NDArray<T>* target, const std::vector<int>& dimensions, const T *extraParams = nullptr) const;
/**
* apply reduce3 operation OpName to this and other array, return result in new output array
* other - input array
* extraArgs - extra parameters for operation
*/
template<typename OpName>
NDArray<T>* applyReduce3(const NDArray<T>* other, const T* extraParams = nullptr) const;
/**
* apply reduce3 operation OpName to this and other array, return result in new output array
* other - input array
* dimensions - vector of dimensions to reduce along
* extraArgs - extra parameters for operation
*/
template<typename OpName>
NDArray<T>* applyAllReduce3(const NDArray<T>* other, const std::vector<int>& dimensions, const T* extraParams = nullptr) const;
/**
* apply reduce3 (exec) operation OpName to this and other array, return result in new output array
* other - input array
* dimensions - vector of dimensions to reduce along
* extraArgs - extra parameters for operation
*/
template<typename OpName>
NDArray<T>* applyReduce3(const NDArray<T>* other, const std::vector<int>& dimensions, const T* extraParams = nullptr) const;
/**
* returns variance along given dimensions
* biasCorrected - if true bias correction will be applied
* dimensions - vector of dimensions to calculate variance along
*/
template<typename OpName>
NDArray<T>* varianceAlongDimension(const bool biasCorrected, const std::vector<int>& dimensions) const;
template<typename OpName>
NDArray<T>* varianceAlongDimension(const bool biasCorrected, const std::initializer_list<int>& dimensions) const;
template<typename OpName>
void varianceAlongDimension(const NDArray<T>* target, const bool biasCorrected, const std::vector<int>& dimensions);
template<typename OpName>
void varianceAlongDimension(const NDArray<T>* target, const bool biasCorrected, const std::initializer_list<int>& dimensions);
/**
* operator returns sub-array with buffer pointing at this->_buffer with offset defined by given intervals
* idx - intervals of indexes which define the sub-arrays to point on
* keepUnitiesInShape - if false then eliminate unities from resulting array shape, for example {1,a,1,b} -> {a,b}
*/
NDArray<T> operator()(const Intervals& idx, bool keepUnitiesInShape = false) const;
/**
* operator returns sub-array with buffer pointing at this->_buffer with offset defined by given intervals
* idx - intervals of indexes which define the sub-arrays to point on, idx has form {dim0Start,dim0End, dim1Start,dim1End, ....} and length (2 * this->rankOf())
* when (dimStart == dimEnd) then whole range will be used for current dimension
* keepUnitiesInShape - if false then eliminate unities from resulting array shape, for example {1,a,1,b} -> {a,b}
*/
NDArray<T> operator()(const int* idx, bool keepUnitiesInShape = false) const;
/**
* addition operator: array + other
* other - input array to add
*/
NDArray<T> operator+(const NDArray<T>& other) const;
/**
* addition operator: array + scalar
* scalar - input scalar to add
*/
NDArray<T> operator+(const T scalar) const;
/**
* friend functions which implement addition operator: scalar + array
* scalar - input scalar to add
*/
friend NDArray<float> nd4j::operator+(const float scalar, const NDArray<float>& arr);
friend NDArray<float16> nd4j::operator+(const float16 scalar, const NDArray<float16>& arr);
friend NDArray<double> nd4j::operator+(const double scalar, const NDArray<double>& arr);
/**
* addition unary operator array += other
* other - input array to add
*/
void operator+=(const NDArray<T>& other);
/**
* subtraction unary operator array -= other
* other - input array to add
*/
void operator-=(const NDArray<T>& other);
void operator+=(const T other);
void operator-=(const T other);
/**
* subtraction operator: array - other
* other - input array to subtract
*/
NDArray<T> operator-(const NDArray<T>& other) const;
/**
* subtraction operator: array - scalar
* scalar - input scalar to subtract
*/
NDArray<T> operator-(const T& scalar) const;
/**
* negative operator, it changes sign of all array elements on opposite
*/
NDArray<T> operator-() const;
/**
* friend functions which implement subtraction operator: scalar - array
* scalar - input scalar to subtract
*/
friend NDArray<float> nd4j::operator-(const float scalar, const NDArray<float>& arr);
friend NDArray<float16> nd4j::operator-(const float16 scalar, const NDArray<float16>& arr);
friend NDArray<double> nd4j::operator-(const double scalar, const NDArray<double>& arr);
/**
* pairwise multiplication operator: array * other
* other - input array to multiply on
*/
NDArray<T> operator*(const NDArray<T>& other) const;
/**
* multiplication operator: array * scalar
* scalar - input scalar to multiply on
*/
NDArray<T> operator*(const T scalar) const;
/**
* pairwise multiplication unary operator array *= other
* other - input array to multiply on
*/
void operator*=(const NDArray<T>& other);
/**
* multiplication unary operator array *= scalar
* scalar - input scalar to multiply on
*/
void operator*=(const T scalar);
/**
* pairwise division operator: array / other
* other - input array to divide on
*/
NDArray<T> operator/(const NDArray<T>& other) const;
/**
* division operator: array / scalar
* scalar - input scalar to divide each array element on
*/
NDArray<T> operator/(const T scalar) const;
/**
* pairwise division unary operator: array /= other
* other - input array to divide on
*/
void operator/=(const NDArray<T>& other);
/**
* division unary operator: array /= scalar
* scalar - input scalar to divide on
*/
void operator/=(const T scalar);
/**
* friend function which implements mathematical multiplication of two arrays
* left - input array
* right - input array
*/
friend NDArray<T> mmul<>(const NDArray<T>& left, const NDArray<T>& right);
/**
* this method assigns elements of other array to the sub-array of this array defined by given intervals
* other - input array to assign elements from
* idx - intervals of indexes which define the sub-array
*/
void assign(const NDArray<T>& other, const Intervals& idx);
/**
* return vector containing _buffer as flat binary array
*/
std::vector<int8_t> asByteVector();
/**
* makes array to be identity matrix (not necessarily square), that is set all diagonal elements = 1, rest = 0
*/
void setIdentity();
/**
* swaps the contents of tow arrays,
* PLEASE NOTE: method doesn't take into account the shapes of arrays, shapes may be different except one condition: arrays lengths must be the same
*/
void swapUnsafe(NDArray<T>& other);
/**
* return vector with buffer which points on corresponding diagonal elements of array
* type - means of vector to be returned: column ('c') or row ('r')
*/
NDArray<T>* diagonal(const char type ) const;
/**
* fill matrix with given value starting from specified diagonal in given direction, works only with 2D matrix
*
* diag - diagonal starting from matrix is filled.
* diag = 0 corresponds to main diagonal,
* diag < 0 below main diagonal
* diag > 0 above main diagonal
* direction - in what direction to fill matrix. There are 2 possible directions:
* 'u' - fill up, mathematically this corresponds to lower triangular matrix
* 'l' - fill down, mathematically this corresponds to upper triangular matrix
*/
void setValueInDiagMatrix(const T& value, const int diag, const char direction);
/**
* change an array by repeating it the number of times in order to acquire new shape equal to the input shape
*
* shape - contains new shape to broadcast array to
* target - optional argument, if target != nullptr the resulting array will be placed it target, in opposite case tile operation is done in place
*/
void tileToShape(const std::vector<Nd4jLong>& shape, NDArray<T>* target = nullptr);
void tileToShape(const std::initializer_list<Nd4jLong>& shape, NDArray<T>* target = nullptr);
template <typename N>
NDArray<N>* asT();
/**
* calculates the trace of an array, that is sum of elements on main diagonal = sum array[i, i, i, ...]
*/
T getTrace() const;
/**
* default destructor
*/
~NDArray() noexcept;
/**
* set _shapeInfo
*/
FORCEINLINE void setShapeInfo(Nd4jLong *shapeInfo);
/**
* set _buffer
*/
FORCEINLINE void setBuffer(T* buffer);
/**
* set _isBuffAlloc and _isShapeAlloc
*/
FORCEINLINE void triggerAllocationFlag(bool bufferAllocated, bool shapeAllocated);
/**
* returns the value of "dim" dimension
*/
Nd4jLong sizeAt(int dim) const;
/**
* returns order of array
*/
FORCEINLINE char ordering() const;
/**
* return _isView
*/
FORCEINLINE bool isView();
/**
* returns shape portion of shapeInfo
*/
FORCEINLINE Nd4jLong* shapeOf() const;
/**
* returns strides portion of shapeInfo
*/
FORCEINLINE Nd4jLong* stridesOf() const;
/**
* returns rank of array
*/
FORCEINLINE int rankOf() const;
/**
* returns length of array
*/
FORCEINLINE Nd4jLong lengthOf() const;
/**
* returns number of rows in array
*/
FORCEINLINE Nd4jLong rows() const;
/**
* returns number of columns in array
*/
FORCEINLINE Nd4jLong columns() const;
/**
* returns size of array elements type
*/
FORCEINLINE int sizeOfT() const;
/**
* returns element-wise-stride
*/
FORCEINLINE Nd4jLong ews() const;
// returns true if arrays have same shape
FORCEINLINE bool isSameShape(const NDArray<T> *other) const;
FORCEINLINE bool isSameShape(NDArray<T> &other) const;
FORCEINLINE bool isSameShape(const std::initializer_list<Nd4jLong>& shape) const;
FORCEINLINE bool isSameShape(const std::vector<Nd4jLong>& shape) const;
/**
* returns true if these two NDArrays have same rank, dimensions, strides, ews and order
*/
FORCEINLINE bool isSameShapeStrict(const NDArray<T> *other) const;
/**
* returns true if buffer && shapeInfo were defined (non nullptr)
*/
FORCEINLINE bool nonNull() const;
/**
* returns array element with given index from linear buffer
* i - element index in array
*/
FORCEINLINE T getScalar(const Nd4jLong i) const;
/**
* returns array element with given index, takes into account offset between elements (element-wise-stride)
* i - element index in array
*/
FORCEINLINE T getIndexedScalar(const Nd4jLong i) const;
/**
* returns element with given indexes from 2D array
* i - number of row
* j - number of column
*/
FORCEINLINE T getScalar(const Nd4jLong i, const Nd4jLong j) const;
/**
* returns element with given indexes from 3D array
* i - height
* j - width
* k - depth
*/
FORCEINLINE T getScalar(const Nd4jLong i, const Nd4jLong j, const Nd4jLong k) const;
/**
* assigns given scalar to array element by given index, takes into account offset between elements (element-wise-stride)
* i - element index in array
* value - scalar value to assign
*/
FORCEINLINE void putIndexedScalar(const Nd4jLong i, const T value);
/**
* assigns given scalar to array element by given index, regards array buffer as linear
* i - element index in array
* value - scalar value to assign
*/
FORCEINLINE void putScalar(const Nd4jLong i, const T value);
/**
* assigns given scalar to 2D array element by given indexes
* i - number of row
* j - number of row
* value - scalar value to assign
*/
FORCEINLINE void putScalar(const Nd4jLong i, const Nd4jLong j, const T value);
/**
* assigns given scalar to 3D array element by given indexes
* i - height
* j - width
* k - depth
* value - scalar value to assign
*/
FORCEINLINE void putScalar(const Nd4jLong i, const Nd4jLong j, const Nd4jLong k, const T value);
/**
* returns true if array is 2D
*/
FORCEINLINE bool isMatrix() const;
/**
* returns true if array is vector
*/
FORCEINLINE bool isVector() const;
/**
* returns true if array is column vector
*/
FORCEINLINE bool isColumnVector() const;
/**
* returns true if array is row vector
*/
FORCEINLINE bool isRowVector() const;
/**
* returns true if array is scalar
*/
FORCEINLINE bool isScalar() const;
/**
* inline accessing operator for matrix, i - absolute index
*/
FORCEINLINE T operator()(const Nd4jLong i) const;
/**
* inline modifying operator for matrix, i - absolute index
*/
FORCEINLINE T& operator()(const Nd4jLong i);
/**
* inline accessing operator for 2D array, i - row, j - column
*/
FORCEINLINE T operator()(const Nd4jLong i, const Nd4jLong j) const;
/**
* inline modifying operator for 2D array, i - row, j - column
*/
FORCEINLINE T& operator()(const Nd4jLong i, const Nd4jLong j);
/**
* inline accessing operator for 3D array, i - height, j - width, k - depth
*/
FORCEINLINE T operator()(const Nd4jLong i, const Nd4jLong j, const Nd4jLong k) const;
/**
* inline modifying operator for 3D array, i - height, j - width, k - depth
*/
FORCEINLINE T& operator()(const Nd4jLong i, const Nd4jLong j, const Nd4jLong k);
/**
* inline modifying operator for 4D array, i - height, j - width, k - depth
*/
FORCEINLINE T& operator()(const Nd4jLong t, const Nd4jLong u, const Nd4jLong v, const Nd4jLong w);
/**
* inline accessing operator for 4D array, i - height, j - width, k - depth
*/
FORCEINLINE T operator()(const Nd4jLong t, const Nd4jLong u, const Nd4jLong v, const Nd4jLong w) const;
template <typename T2>
FORCEINLINE std::vector<T2> asVectorT();
FORCEINLINE bool isAttached();
NDArray<T>* detach();
};
//////////////////////////////////////////////////////////////////////////
///// IMLEMENTATION OF INLINE METHODS /////
//////////////////////////////////////////////////////////////////////////
template <typename T>
template <typename T2>
std::vector<T2> NDArray<T>::asVectorT() {
std::vector<T2> result(this->lengthOf());
#pragma omp parallel for simd
for (int e = 0; e < this->lengthOf(); e++)
result[e] = (T2) this->getIndexedScalar(e);
return result;
}
template<typename T>
bool NDArray<T>::isAttached() {
return this->_workspace != nullptr;
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
void NDArray<T>::setShapeInfo(Nd4jLong *shapeInfo) {
if(_isShapeAlloc && _workspace == nullptr)
delete []_shapeInfo;
_shapeInfo = shapeInfo;
_isShapeAlloc = false;
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
void NDArray<T>::setBuffer(T* buffer) {
if(_isBuffAlloc && _workspace == nullptr)
delete []_buffer;
_buffer = buffer;
_isBuffAlloc = false;
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
void NDArray<T>::triggerAllocationFlag(bool bufferAllocated, bool shapeAllocated) {
_isBuffAlloc = bufferAllocated;
_isShapeAlloc = shapeAllocated;
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
char NDArray<T>::ordering() const {
return shape::order(_shapeInfo);
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
bool NDArray<T>::isView() {
return _isView;
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
Nd4jLong* NDArray<T>::shapeOf() const {
return shape::shapeOf(_shapeInfo);
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
Nd4jLong* NDArray<T>::stridesOf() const {
return shape::stride(_shapeInfo);
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
int NDArray<T>::rankOf() const {
return shape::rank(_shapeInfo);
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
Nd4jLong NDArray<T>::lengthOf() const {
return shape::length(_shapeInfo);
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
Nd4jLong NDArray<T>::rows() const {
return shapeOf()[0];
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
Nd4jLong NDArray<T>::columns() const {
return shapeOf()[1];
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
int NDArray<T>::sizeOfT() const {
return sizeof(T);
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
Nd4jLong NDArray<T>::ews() const {
return shape::elementWiseStride(_shapeInfo);
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
bool NDArray<T>::nonNull() const {
return this->_buffer != nullptr && this->_shapeInfo != nullptr;
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
bool NDArray<T>::isMatrix() const {
return shape::isMatrix(this->_shapeInfo);
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
bool NDArray<T>::isVector() const {
return !isScalar() && shape::isVector(this->_shapeInfo);
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
bool NDArray<T>::isColumnVector() const {
return !isScalar() && shape::isColumnVector(this->_shapeInfo);
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
bool NDArray<T>::isRowVector() const {
// 1D edge case
if (shape::rank(this->_shapeInfo) == 1)
return true;
return !isScalar() && shape::isRowVector(this->_shapeInfo);
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
bool NDArray<T>::isScalar() const {
return shape::isScalar(this->_shapeInfo);
}
// accessing operator for matrix, i - absolute index
template<typename T>
T NDArray<T>::operator()(const Nd4jLong i) const {
if (i >= shape::length(_shapeInfo))
throw std::invalid_argument("NDArray::operator(i): dinput index is out of array length !");
auto ews = shape::elementWiseStride(_shapeInfo);
char order = ordering();
if(ews == 1 && order == 'c')
return _buffer[i];
else if(ews > 1 && order == 'c')
return _buffer[i*ews];
else {
Nd4jLong idx[MAX_RANK];
shape::ind2subC(rankOf(), shapeOf(), i, idx);
Nd4jLong offset = shape::getOffset(0, shapeOf(), stridesOf(), idx, rankOf());
return _buffer[offset];
}
}
//////////////////////////////////////////////////////////////////////////
// modifying operator for matrix, i - absolute index
template<typename T>
T& NDArray<T>::operator()(const Nd4jLong i) {
if (i >= shape::length(_shapeInfo))
throw std::invalid_argument("NDArray::operator(i): input index is out of array length !");
auto ews = shape::elementWiseStride(_shapeInfo);
auto order = ordering();
if(ews == 1 && order == 'c')
return _buffer[i];
else if(ews > 1 && order == 'c')
return _buffer[i*ews];
else {
Nd4jLong idx[MAX_RANK];
shape::ind2subC(rankOf(), shapeOf(), i, idx);
auto offset = shape::getOffset(0, shapeOf(), stridesOf(), idx, rankOf());
return _buffer[offset];
}
}
//////////////////////////////////////////////////////////////////////////
// accessing operator for 2D matrix, i - row, j - column
template<typename T>
T NDArray<T>::operator()(const Nd4jLong i, const Nd4jLong j) const {
if (rankOf() != 2 || i >= shapeOf()[0] || j >= shapeOf()[1])
throw std::invalid_argument("NDArray::operator(i,j): one of input indexes is out of array length or rank!=2 !");
Nd4jLong coords[2] = {i, j};
auto xOffset = shape::getOffset(0, shapeOf(), stridesOf(), coords, rankOf());
return _buffer[xOffset];
}
//////////////////////////////////////////////////////////////////////////
// modifying operator for 2D matrix, i - row, j - column
template<typename T>
T& NDArray<T>::operator()(const Nd4jLong i, const Nd4jLong j) {
if (rankOf() != 2 || i >= shapeOf()[0] || j >= shapeOf()[1])
throw std::invalid_argument("NDArray::operator(i,j): one of input indexes is out of array length or rank!=2 !");
Nd4jLong coords[2] = {i, j};
auto xOffset = shape::getOffset(0, shapeOf(), stridesOf(), coords, rankOf());
return _buffer[xOffset];
}
//////////////////////////////////////////////////////////////////////////
// accessing operator for 3D array, i - row, j - column
template<typename T>
T NDArray<T>::operator()(const Nd4jLong i, const Nd4jLong j, const Nd4jLong k) const {
if (rankOf() != 3 || i >= shapeOf()[0] || j >= shapeOf()[1] || j >= shapeOf()[2])
throw std::invalid_argument("NDArray::operator(i,j,k): one of input indexes is out of array length or rank!=3 !");
Nd4jLong coords[3] = {i, j, k};
auto xOffset = shape::getOffset(0, shapeOf(), stridesOf(), coords, rankOf());
return _buffer[xOffset];
}
//////////////////////////////////////////////////////////////////////////
// modifying operator for 3D array
template<typename T>
T& NDArray<T>::operator()(const Nd4jLong i, const Nd4jLong j, const Nd4jLong k) {
if (rankOf() != 3 || i >= shapeOf()[0] || j >= shapeOf()[1] || k >= shapeOf()[2])
throw std::invalid_argument("NDArray::operator(i,j,k): one of input indexes is out of array length or rank!=3 !");
Nd4jLong coords[3] = {i, j, k};
auto xOffset = shape::getOffset(0, shapeOf(), stridesOf(), coords, rankOf());
return _buffer[xOffset];
}
template<typename T>
T NDArray<T>::operator()(const Nd4jLong t, const Nd4jLong u, const Nd4jLong v, const Nd4jLong w) const {
if (rankOf() != 4 || t >= shapeOf()[0] || u >= shapeOf()[1] || v >= shapeOf()[2] || w >= shapeOf()[3])
throw std::invalid_argument("NDArray::operator(t,u,v,w): one of input indexes is out of array length or rank!=4 !");
Nd4jLong coords[4] = {t, u, v, w};
auto xOffset = shape::getOffset(0, shapeOf(), stridesOf(), coords, rankOf());
return _buffer[xOffset];
}
template<typename T>
T& NDArray<T>::operator()(const Nd4jLong t, const Nd4jLong u, const Nd4jLong v, const Nd4jLong w) {
if (rankOf() != 4 || t >= shapeOf()[0] || u >= shapeOf()[1] || v >= shapeOf()[2] || w >= shapeOf()[3])
throw std::invalid_argument("NDArray::operator(t,u,v,w): one of input indexes is out of array length or rank!=4 !");
Nd4jLong coords[4] = {t, u, v, w};
auto xOffset = shape::getOffset(0, shapeOf(), stridesOf(), coords, rankOf());
return _buffer[xOffset];
}
//////////////////////////////////////////////////////////////////////////
// Return value from linear buffer
template<typename T>
T NDArray<T>::getScalar(const Nd4jLong i) const
{ return (*this)(i); }
//////////////////////////////////////////////////////////////////////////
template<typename T>
T NDArray<T>::getIndexedScalar(const Nd4jLong i) const {
return (*this)(i);
}
//////////////////////////////////////////////////////////////////////////
// Returns value from 2D matrix by coordinates/indexes
template<typename T>
T NDArray<T>::getScalar(const Nd4jLong i, const Nd4jLong j) const
{ return (*this)(i, j); }
//////////////////////////////////////////////////////////////////////////
// returns value from 3D tensor by coordinates
template<typename T>
T NDArray<T>::getScalar(const Nd4jLong i, const Nd4jLong j, const Nd4jLong k) const
{ return (*this)(i, j, k); }
//////////////////////////////////////////////////////////////////////////
template<typename T>
void NDArray<T>::putIndexedScalar(const Nd4jLong i, const T value)
{ (*this)(i) = value; }
//////////////////////////////////////////////////////////////////////////
// This method sets value in linear buffer to position i
template<typename T>
void NDArray<T>::putScalar(const Nd4jLong i, const T value)
{ (*this)(i) = value; }
//////////////////////////////////////////////////////////////////////////
// This method sets value in 2D matrix to position i, j
template<typename T>
void NDArray<T>::putScalar(const Nd4jLong i, const Nd4jLong j, const T value)
{ (*this)(i,j) = value; }
//////////////////////////////////////////////////////////////////////////
// This method sets value in 3D matrix to position i,j,k
template<typename T>
void NDArray<T>::putScalar(const Nd4jLong i, const Nd4jLong j, const Nd4jLong k, const T value)
{ (*this)(i,j,k) = value; }
//////////////////////////////////////////////////////////////////////////
template<typename T>
Nd4jLong NDArray<T>::memoryFootprint() {
Nd4jLong size = this->lengthOf() * this->sizeOfT();
size += shape::shapeInfoByteLength(this->rankOf());
return size;
}
//////////////////////////////////////////////////////////////////////////
// returns true if these two NDArrays have same shape
// still the definition of inline function must be in header file
template<typename T>
bool NDArray<T>::isSameShape(const std::vector<Nd4jLong>& other) const{
if (this->rankOf() != (int) other.size())
return false;
for (int e = 0; e < this->rankOf(); e++) {
if (this->shapeOf()[e] != other.at(e) && other.at(e) != -1)
return false;
}
return true;
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
bool NDArray<T>::isSameShape(const NDArray<T> *other) const {
return isSameShape(std::vector<Nd4jLong>(other->_shapeInfo+1, other->_shapeInfo+1+other->_shapeInfo[0]));
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
bool NDArray<T>::isSameShape(NDArray<T> &other) const {
return isSameShape(&other);
}
//////////////////////////////////////////////////////////////////////////
template<typename T>
bool NDArray<T>::isSameShape(const std::initializer_list<Nd4jLong>& other) const {
return isSameShape(std::vector<Nd4jLong>(other));
}
//////////////////////////////////////////////////////////////////////////
// returns true if these two NDArrays have same _shapeInfo
// still the definition of inline function must be in header file
template<typename T>
bool NDArray<T>::isSameShapeStrict(const NDArray<T> *other) const {
return shape::equalsStrict(_shapeInfo, other->_shapeInfo);
}
}
#endif
|
hello-openmp.c | #include<stdio.h>
#include<omp.h>
int main()
{
int nthreads, tid;
#pragma omp parallel private(tid)
{
tid = omp_get_thread_num();
printf("Hello World from thread = %d \n", tid);
//master thread
if(tid == 0){
nthreads = omp_get_num_threads();
printf("Number of threads = %d\n", nthreads);
}
} //threads terminated and rejoin
}
|
AtomicOP.h | #ifndef ATOMICIOP_H_
#define ATOMICIOP_H_
/*
* AtomicOP.h:
* a list of atomic operations
*
* Created on: June 11, 2017
* Author: yue_zhang(suda), mszhang
*/
/*
ActivateNode
TanhNode
SigmoidNode
ReluNode
IndexNode
PSubNode
PDotNode
*/
#include "Param.h"
#include "MyLib.h"
#include "Node.h"
#include "Graph.h"
#include "ModelUpdate.h"
class ActivateNode :public Node {
public:
PNode in;
dtype(*activate)(const dtype&); // activation function
dtype(*derivate)(const dtype&, const dtype&); // derivation function of activation function
public:
ActivateNode() : Node() {
in = NULL;
activate = ftanh;
derivate = dtanh;
node_type = "activate";
}
~ActivateNode() {
in = NULL;
}
inline void clearValue() {
Node::clearValue();
in = NULL;
}
// define the activate function and its derivation form
inline void setFunctions(dtype(*f)(const dtype&), dtype(*f_deri)(const dtype&, const dtype&)) {
activate = f;
derivate = f_deri;
}
public:
void forward(Graph *cg, PNode x) {
in = x;
degree = 0;
in->addParent(this);
cg->addNode(this);
}
public:
inline void compute() {
val.vec() = in->val.vec().unaryExpr(ptr_fun(activate));
}
void backward() {
in->loss.vec() += loss.vec() * in->val.vec().binaryExpr(val.vec(), ptr_fun(derivate));
}
public:
inline PExecute generate(bool bTrain, dtype cur_drop_factor);
// better to rewrite for deep understanding
inline bool typeEqual(PNode other) {
bool result = Node::typeEqual(other);
return result;
}
};
class ActivateExecute :public Execute {
public:
inline void forward() {
int count = batch.size();
//#pragma omp parallel for
for (int idx = 0; idx < count; idx++) {
batch[idx]->compute();
batch[idx]->forward_drop(bTrain, drop_factor);
}
}
inline void backward() {
int count = batch.size();
//#pragma omp parallel for
for (int idx = 0; idx < count; idx++) {
batch[idx]->backward_drop();
batch[idx]->backward();
}
}
};
inline PExecute ActivateNode::generate(bool bTrain, dtype cur_drop_factor) {
ActivateExecute* exec = new ActivateExecute();
exec->batch.push_back(this);
exec->bTrain = bTrain;
exec->drop_factor = cur_drop_factor;
return exec;
};
class TanhNode :public Node {
public:
PNode in;
public:
TanhNode() : Node() {
in = NULL;
node_type = "tanh";
}
~TanhNode() {
in = NULL;
}
inline void clearValue() {
Node::clearValue();
in = NULL;
}
public:
void forward(Graph *cg, PNode x) {
in = x;
degree = 0;
in->addParent(this);
cg->addNode(this);
}
public:
inline void compute() {
val.vec() = in->val.vec().unaryExpr(ptr_fun(ftanh));
}
void backward() {
in->loss.vec() += loss.vec() * in->val.vec().binaryExpr(val.vec(), ptr_fun(dtanh));
}
public:
inline PExecute generate(bool bTrain, dtype cur_drop_factor);
// better to rewrite for deep understanding
bool typeEqual(PNode other) {
bool result = Node::typeEqual(other);
return result;
}
};
class TanhExecute :public Execute {
public:
Tensor2D drop_mask;
int dim;
public:
Tensor1D y, x;
int sumDim;
bool bTrain;
#if USE_GPU
void forward() {
int count = batch.size();
std::vector<dtype*> xs, ys;
xs.reserve(count);
ys.reserve(count);
drop_mask.init(dim, count);
for (Node *n : batch) {
TanhNode *tanh = static_cast<TanhNode*>(n);
#if TEST_CUDA
tanh->in->val.copyFromHostToDevice();
#endif
xs.push_back(tanh->in->val.value);
ys.push_back(tanh->val.value);
}
CalculateDropMask(count, dim, drop_mask);
n3ldg_cuda::TanhForward(n3ldg_cuda::ActivatedEnum::TANH, xs, count, dim, drop_mask.value,
this->dynamicDropValue(), ys);
#if TEST_CUDA
drop_mask.copyFromDeviceToHost();
for (int i = 0; i < count; ++i) {
for (int j = 0; j < dim; ++j) {
dtype v = drop_mask[j][i];
batch[i]->drop_mask[j] = v <= dynamicDropValue() ? 0 : 1;
}
}
for (int idx = 0; idx < count; idx++) {
batch[idx]->compute();
batch[idx]->forward_drop(bTrain, drop_factor);
n3ldg_cuda::Assert(batch.at(idx)->val.verify("Tanh forward"));
}
#endif
}
#else
void forward() {
int count = batch.size();
//#pragma omp parallel for
sumDim = 0;
for (int idx = 0; idx < count; idx++) {
sumDim += batch[idx]->dim;
}
x.init(sumDim);
y.init(sumDim);
int offset = 0;
for (int idx = 0; idx < count; idx++) {
TanhNode* ptr = (TanhNode*)batch[idx];
for (int idy = 0; idy < ptr->dim; idy++) {
x[offset + idy] = ptr->in->val[idy];
}
offset += ptr->dim;
}
y.vec() = x.vec().unaryExpr(ptr_fun(ftanh));
offset = 0;
for (int idx = 0; idx < count; idx++) {
TanhNode* ptr = (TanhNode*)batch[idx];
for (int idy = 0; idy < ptr->dim; idy++) {
ptr->val[idy] = y[offset + idy];
}
offset += ptr->dim;
ptr->forward_drop(bTrain,drop_factor);
}
}
#endif
#if USE_GPU
void backward() {
int count = batch.size();
std::vector<dtype*> vals, losses, in_losses;
vals.reserve(count);
losses.reserve(count);
in_losses.reserve(count);
for (Node *n : batch) {
TanhNode *tanh = static_cast<TanhNode*>(n);
#if TEST_CUDA
tanh->loss.copyFromHostToDevice();
tanh->in->loss.copyFromHostToDevice();
#endif
vals.push_back(tanh->val.value);
losses.push_back(tanh->loss.value);
in_losses.push_back(tanh->in->loss.value);
}
n3ldg_cuda::TanhBackward(n3ldg_cuda::ActivatedEnum::TANH, losses, vals, count, dim, drop_mask.value,
dynamicDropValue(), in_losses);
#if TEST_CUDA
for (Node *n : batch) {
n->backward_drop();
n->backward();
}
for (Node *n : batch) {
TanhNode *tanh = static_cast<TanhNode*>(n);
n3ldg_cuda::Assert(tanh->in->loss.verify("TanhExecute backward"));
}
#endif
}
#else
void backward() {
int count = batch.size();
//#pragma omp parallel for
Tensor1D lx, ly;
lx.init(sumDim);
ly.init(sumDim);
int offset = 0;
for (int idx = 0; idx < count; idx++) {
TanhNode* ptr = (TanhNode*)batch[idx];
ptr->backward_drop();
for (int idy = 0; idy < ptr->dim; idy++) {
ly[offset + idy] = ptr->loss[idy];
}
offset += ptr->dim;
}
lx.vec() = ly.vec() * x.vec().binaryExpr(y.vec(), ptr_fun(dtanh));
offset = 0;
for (int idx = 0; idx < count; idx++) {
TanhNode* ptr = (TanhNode*)batch[idx];
for (int idy = 0; idy < ptr->dim; idy++) {
ptr->in->loss[idy] += lx[offset + idy];
}
offset += ptr->dim;
}
}
#endif
};
inline PExecute TanhNode::generate(bool bTrain, dtype cur_drop_factor) {
TanhExecute* exec = new TanhExecute();
exec->batch.push_back(this);
exec->bTrain = bTrain;
exec->drop_factor = cur_drop_factor;
exec->dim = dim;
return exec;
};
class SigmoidNode :public Node {
public:
PNode in;
public:
SigmoidNode() : Node() {
in = NULL;
node_type = "sigmoid";
}
~SigmoidNode() {
in = NULL;
}
inline void clearValue() {
Node::clearValue();
in = NULL;
}
public:
void forward(Graph *cg, PNode x) {
in = x;
degree = 0;
in->addParent(this);
cg->addNode(this);
}
public:
inline void compute() {
val.vec() = in->val.vec().unaryExpr(ptr_fun(fsigmoid));
}
void backward() {
in->loss.vec() += loss.vec() * in->val.vec().binaryExpr(val.vec(), ptr_fun(dsigmoid));
}
public:
inline PExecute generate(bool bTrain, dtype cur_drop_factor);
// better to rewrite for deep understanding
inline bool typeEqual(PNode other) {
bool result = Node::typeEqual(other);
return result;
}
};
class SigmoidExecute :public Execute {
public:
Tensor2D drop_mask;
int dim;
public:
Tensor1D x, y;
int sumDim;
bool bTrain;
#if USE_GPU
void forward() {
int count = batch.size();
std::vector<dtype*> xs, ys;
xs.reserve(count);
ys.reserve(count);
drop_mask.init(dim, count);
for (Node *n : batch) {
SigmoidNode *tanh = static_cast<SigmoidNode*>(n);
#if TEST_CUDA
tanh->in->val.copyFromHostToDevice();
#endif
xs.push_back(tanh->in->val.value);
ys.push_back(tanh->val.value);
}
CalculateDropMask(count, dim, drop_mask);
n3ldg_cuda::TanhForward(n3ldg_cuda::ActivatedEnum::SIGMOID, xs, count, dim, drop_mask.value,
this->dynamicDropValue(), ys);
#if TEST_CUDA
drop_mask.copyFromDeviceToHost();
for (int i = 0; i < count; ++i) {
for (int j = 0; j < dim; ++j) {
dtype v = drop_mask[j][i];
batch[i]->drop_mask[j] = v <= dynamicDropValue() ? 0 : 1;
}
}
for (int idx = 0; idx < count; idx++) {
batch[idx]->compute();
batch[idx]->forward_drop(bTrain, drop_factor);
n3ldg_cuda::Assert(batch.at(idx)->val.verify("Sigmoid forward"));
}
#endif
}
#else
void forward() {
int count = batch.size();
//#pragma omp parallel for
n3ldg_cuda::Profiler &profiler = n3ldg_cuda::Profiler::Ins();
profiler.BeginEvent("Sigmoid no-batch backward");
for (int idx = 0; idx < count; idx++) {
batch[idx]->backward_drop();
batch[idx]->backward();
}
profiler.EndEvent();
profiler.BeginEvent("Sigmoid batch backward");
sumDim = 0;
for (int idx = 0; idx < count; idx++) {
sumDim += batch[idx]->dim;
}
x.init(sumDim);
y.init(sumDim);
int offset = 0;
for (int idx = 0; idx < count; idx++) {
SigmoidNode* ptr = (SigmoidNode*)batch[idx];
for (int idy = 0; idy < ptr->dim; idy++) {
x[offset + idy] = ptr->in->val[idy];
}
offset += ptr->dim;
}
y.vec() = x.vec().unaryExpr(ptr_fun(fsigmoid));
offset = 0;
for (int idx = 0; idx < count; idx++) {
SigmoidNode* ptr = (SigmoidNode*)batch[idx];
for (int idy = 0; idy < ptr->dim; idy++) {
ptr->val[idy] = y[offset + idy];
}
offset += ptr->dim;
ptr->forward_drop(bTrain, drop_factor);
}
profiler.EndEvent();
}
#endif
#if USE_GPU
void backward() {
int count = batch.size();
std::vector<dtype*> vals, losses, in_losses;
vals.reserve(count);
losses.reserve(count);
in_losses.reserve(count);
for (Node *n : batch) {
SigmoidNode *tanh = static_cast<SigmoidNode*>(n);
#if TEST_CUDA
tanh->loss.copyFromHostToDevice();
tanh->in->loss.copyFromHostToDevice();
#endif
vals.push_back(tanh->val.value);
losses.push_back(tanh->loss.value);
in_losses.push_back(tanh->in->loss.value);
}
n3ldg_cuda::TanhBackward(n3ldg_cuda::ActivatedEnum::SIGMOID, losses, vals, count, dim, drop_mask.value,
dynamicDropValue(), in_losses);
#if TEST_CUDA
for (Node *n : batch) {
n->backward_drop();
n->backward();
}
for (Node *n : batch) {
SigmoidNode *tanh = static_cast<SigmoidNode*>(n);
n3ldg_cuda::Assert(tanh->in->loss.verify("SigmoidExecute backward"));
}
#endif
}
#else
void backward() {
int count = batch.size();
//#pragma omp parallel for
n3ldg_cuda::Profiler &profiler = n3ldg_cuda::Profiler::Ins();
profiler.BeginEvent("Sigmoid no-batch backward");
for (int idx = 0; idx < count; idx++) {
batch[idx]->backward_drop();
batch[idx]->backward();
}
profiler.EndEvent();
profiler.BeginEvent("Sigmoid batch backward");
Tensor1D lx, ly;
lx.init(sumDim);
ly.init(sumDim);
int offset = 0;
for (int idx = 0; idx < count; idx++) {
SigmoidNode* ptr = (SigmoidNode*)batch[idx];
ptr->backward_drop();
for (int idy = 0; idy < ptr->dim; idy++) {
ly[offset + idy] = ptr->loss[idy];
}
offset += ptr->dim;
}
lx.vec() = ly.vec() * x.vec().binaryExpr(y.vec(), ptr_fun(dsigmoid));
offset = 0;
for (int idx = 0; idx < count; idx++) {
SigmoidNode* ptr = (SigmoidNode*)batch[idx];
for (int idy = 0; idy < ptr->dim; idy++) {
ptr->in->loss[idy] += lx[offset + idy];
}
offset += ptr->dim;
}
profiler.EndEvent();
}
#endif
};
inline PExecute SigmoidNode::generate(bool bTrain, dtype cur_drop_factor) {
SigmoidExecute* exec = new SigmoidExecute();
exec->batch.push_back(this);
exec->bTrain = bTrain;
exec->drop_factor = cur_drop_factor;
exec->dim = dim;
return exec;
};
class ReluNode :public Node {
public:
PNode in;
public:
ReluNode() : Node() {
in = NULL;
node_type = "relu";
}
~ReluNode() {
in = NULL;
}
inline void clearValue() {
Node::clearValue();
in = NULL;
}
public:
void forward(Graph *cg, PNode x) {
in = x;
degree = 0;
in->addParent(this);
cg->addNode(this);
}
public:
inline void compute() {
val.vec() = in->val.vec().unaryExpr(ptr_fun(frelu));
}
void backward() {
in->loss.vec() += loss.vec() * in->val.vec().binaryExpr(val.vec(), ptr_fun(drelu));
}
public:
inline PExecute generate(bool bTrain, dtype cur_drop_factor);
// better to rewrite for deep understanding
inline bool typeEqual(PNode other) {
bool result = Node::typeEqual(other);
return result;
}
};
class ReluExecute :public Execute {
public:
inline void forward() {
int count = batch.size();
//#pragma omp parallel for
for (int idx = 0; idx < count; idx++) {
batch[idx]->compute();
batch[idx]->forward_drop(bTrain, drop_factor);
}
}
inline void backward() {
int count = batch.size();
//#pragma omp parallel for
for (int idx = 0; idx < count; idx++) {
batch[idx]->backward_drop();
batch[idx]->backward();
}
}
};
inline PExecute ReluNode::generate(bool bTrain, dtype cur_drop_factor) {
ReluExecute* exec = new ReluExecute();
exec->batch.push_back(this);
exec->bTrain = bTrain;
exec->drop_factor = cur_drop_factor;
return exec;
};
class IndexNode :public Node {
public:
PNode in;
int index_id;
public:
IndexNode() : Node() {
in = NULL;
index_id = -1;
dim = 1;
node_type = "index";
}
~IndexNode() {
in = NULL;
}
inline void clearValue() {
Node::clearValue();
in = NULL;
index_id = -1;
}
//can not be dropped since the output is a scalar
inline void init(int ndim, dtype dropout) {
dim = 1;
Node::init(dim, -1);
}
public:
void forward(Graph *cg, PNode x, int index) {
in = x;
index_id = index;
degree = 0;
in->addParent(this);
cg->addNode(this);
}
public:
void compute() {
val[0] = in->val[index_id];
}
void backward() {
in->loss[index_id] += loss[0];
}
public:
inline PExecute generate(bool bTrain, dtype cur_drop_factor);
// better to rewrite for deep understanding
inline bool typeEqual(PNode other) {
bool result = Node::typeEqual(other);
return result;
}
};
class IndexExecute : public Execute {
public:
inline void forward() {
int count = batch.size();
//#pragma omp parallel for
for (int idx = 0; idx < count; idx++) {
batch[idx]->compute();
batch[idx]->forward_drop(bTrain, drop_factor);
}
}
inline void backward() {
int count = batch.size();
//#pragma omp parallel for
for (int idx = 0; idx < count; idx++) {
batch[idx]->backward_drop();
batch[idx]->backward();
}
}
};
inline PExecute IndexNode::generate(bool bTrain, dtype cur_drop_factor) {
IndexExecute* exec = new IndexExecute();
exec->batch.push_back(this);
exec->bTrain = bTrain;
exec->drop_factor = cur_drop_factor;
return exec;
}
class PSubNode : public Node {
public:
PNode in1, in2;
public:
PSubNode() : Node() {
in1 = NULL;
in2 = NULL;
node_type = "point-subtraction";
}
public:
virtual inline void clearValue() {
Node::clearValue();
in1 = NULL;
in2 = NULL;
}
public:
void forward(Graph *cg, PNode x1, PNode x2) {
in1 = x1;
in2 = x2;
degree = 0;
in1->addParent(this);
in2->addParent(this);
cg->addNode(this);
}
public:
inline void compute() {
val.vec() = in1->val.vec() - in2->val.vec();
}
void backward() {
in1->loss.vec() += loss.vec();
in2->loss.vec() -= loss.vec();
}
public:
// better to rewrite for deep understanding
inline bool typeEqual(PNode other) {
return Node::typeEqual(other);
}
inline PExecute generate(bool bTrain, dtype cur_drop_factor);
};
class PSubExecute :public Execute {
public:
inline void forward() {
int count = batch.size();
//#pragma omp parallel for
for (int idx = 0; idx < count; idx++) {
batch[idx]->compute();
batch[idx]->forward_drop(bTrain, drop_factor);
}
}
inline void backward() {
int count = batch.size();
//#pragma omp parallel for
for (int idx = 0; idx < count; idx++) {
batch[idx]->backward_drop();
batch[idx]->backward();
}
}
};
inline PExecute PSubNode::generate(bool bTrain, dtype cur_drop_factor) {
PSubExecute* exec = new PSubExecute();
exec->batch.push_back(this);
exec->bTrain = bTrain;
exec->drop_factor = cur_drop_factor;
return exec;
}
class PDotNode : public Node {
public:
PNode in1, in2;
public:
PDotNode() : Node() {
in1 = NULL;
in2 = NULL;
dim = 1;
node_type = "point-dot";
}
public:
virtual inline void clearValue() {
Node::clearValue();
in1 = NULL;
in2 = NULL;
}
//can not be dropped since the output is a scalar
inline void init(int ndim, dtype dropout) {
dim = 1;
Node::init(dim, -1);
}
public:
void forward(Graph *cg, PNode x1, PNode x2) {
in1 = x1;
in2 = x2;
degree = 0;
in1->addParent(this);
in2->addParent(this);
cg->addNode(this);
}
public:
inline void compute() {
val[0] = 0.0;
for (int idx = 0; idx < in1->dim; idx++) {
val[0] += in1->val[idx] * in2->val[idx];
}
}
void backward() {
for (int idx = 0; idx < in1->dim; idx++) {
in1->loss[idx] += loss[0] * in2->val[idx];
in2->loss[idx] += loss[0] * in1->val[idx];
}
}
public:
// better to rewrite for deep understanding
inline bool typeEqual(PNode other) {
return Node::typeEqual(other);
}
inline PExecute generate(bool bTrain, dtype cur_drop_factor);
};
class PDotExecute :public Execute {
public:
inline void forward() {
int count = batch.size();
//#pragma omp parallel for
for (int idx = 0; idx < count; idx++) {
batch[idx]->compute();
batch[idx]->forward_drop(bTrain, drop_factor);
}
}
inline void backward() {
int count = batch.size();
//#pragma omp parallel for
for (int idx = 0; idx < count; idx++) {
batch[idx]->backward_drop();
batch[idx]->backward();
}
}
};
inline PExecute PDotNode::generate(bool bTrain, dtype cur_drop_factor) {
PDotExecute* exec = new PDotExecute();
exec->batch.push_back(this);
exec->bTrain = bTrain;
exec->drop_factor = cur_drop_factor;
return exec;
}
class DropoutNode : public Node {
public:
PNode in = NULL;
DropoutNode() {
node_type = "dropout";
}
PExecute generate(bool bTrain, dtype cur_drop_factor);
};
class DropoutExecute :public Execute {
public:
Tensor2D drop_mask;
int dim;
#if USE_GPU
void forward() {
int count = batch.size();
std::vector<dtype*> xs, ys;
xs.reserve(count);
ys.reserve(count);
drop_mask.init(dim, count);
for (Node *n : batch) {
DropoutNode *tanh = static_cast<DropoutNode*>(n);
#if TEST_CUDA
tanh->in->val.copyFromHostToDevice();
#endif
xs.push_back(tanh->in->val.value);
ys.push_back(tanh->val.value);
}
CalculateDropMask(count, dim, drop_mask);
n3ldg_cuda::DropoutForward(xs, count, dim, drop_mask.value,
this->dynamicDropValue(), ys);
#if TEST_CUDA
drop_mask.copyFromDeviceToHost();
for (int i = 0; i < count; ++i) {
for (int j = 0; j < dim; ++j) {
dtype v = drop_mask[j][i];
batch[i]->drop_mask[j] = v <= dynamicDropValue() ? 0 : 1;
}
}
for (int idx = 0; idx < count; idx++) {
batch[idx]->compute();
batch[idx]->forward_drop(bTrain, drop_factor);
n3ldg_cuda::Assert(batch.at(idx)->val.verify("Dropout forward"));
}
#endif
}
#else
void forward() {
int count = batch.size();
//#pragma omp parallel for
for (int idx = 0; idx < count; idx++) {
batch[idx]->compute();
batch[idx]->forward_drop(bTrain, drop_factor);
}
}
#endif
#if USE_GPU
void backward() {
int count = batch.size();
std::vector<dtype*> vals, losses, in_losses;
vals.reserve(count);
losses.reserve(count);
in_losses.reserve(count);
for (Node *n : batch) {
DropoutNode *tanh = static_cast<DropoutNode*>(n);
#if TEST_CUDA
tanh->loss.copyFromHostToDevice();
tanh->in->loss.copyFromHostToDevice();
#endif
vals.push_back(tanh->val.value);
losses.push_back(tanh->loss.value);
in_losses.push_back(tanh->in->loss.value);
}
n3ldg_cuda::DropoutBackward(losses, vals, count, dim, drop_mask.value,
dynamicDropValue(), in_losses);
#if TEST_CUDA
for (Node *n : batch) {
n->backward_drop();
n->backward();
}
for (Node *n : batch) {
DropoutNode *tanh = static_cast<DropoutNode*>(n);
n3ldg_cuda::Assert(tanh->in->loss.verify("DropoutExecute backward"));
}
#endif
}
#else
void backward() {
int count = batch.size();
//#pragma omp parallel for
for (int idx = 0; idx < count; idx++) {
batch[idx]->backward_drop();
batch[idx]->backward();
}
}
#endif
};
#endif
|
par_csr_matop_device.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)
******************************************************************************/
#include "_hypre_utilities.h"
#include "_hypre_parcsr_mv.h"
#include "_hypre_utilities.hpp"
#if defined(HYPRE_USING_CUDA)
HYPRE_Int
hypre_ParcsrGetExternalRowsDeviceInit( hypre_ParCSRMatrix *A,
HYPRE_Int indices_len,
HYPRE_Int *indices,
hypre_ParCSRCommPkg *comm_pkg,
HYPRE_Int want_data,
void **request_ptr)
{
HYPRE_Int i, j;
HYPRE_Int num_sends, num_rows_send, num_nnz_send, num_recvs, num_rows_recv, num_nnz_recv;
HYPRE_Int *d_send_i, *send_i, *d_send_map, *d_recv_i, *recv_i;
HYPRE_BigInt *d_send_j, *d_recv_j;
HYPRE_Int *send_jstarts, *recv_jstarts;
HYPRE_Complex *d_send_a = NULL, *d_recv_a = NULL;
hypre_ParCSRCommPkg *comm_pkg_j;
hypre_ParCSRCommHandle *comm_handle, *comm_handle_j, *comm_handle_a;
/* HYPRE_Int global_num_rows = hypre_ParCSRMatrixGlobalNumRows(A); */
/* diag part of A */
hypre_CSRMatrix *A_diag = hypre_ParCSRMatrixDiag(A);
HYPRE_Complex *A_diag_a = hypre_CSRMatrixData(A_diag);
HYPRE_Int *A_diag_i = hypre_CSRMatrixI(A_diag);
HYPRE_Int *A_diag_j = hypre_CSRMatrixJ(A_diag);
/* HYPRE_Int local_num_rows = hypre_CSRMatrixNumRows(A_diag); */
/* off-diag part of A */
hypre_CSRMatrix *A_offd = hypre_ParCSRMatrixOffd(A);
HYPRE_Complex *A_offd_a = hypre_CSRMatrixData(A_offd);
HYPRE_Int *A_offd_i = hypre_CSRMatrixI(A_offd);
HYPRE_Int *A_offd_j = hypre_CSRMatrixJ(A_offd);
/* HYPRE_Int *row_starts = hypre_ParCSRMatrixRowStarts(A); */
/* HYPRE_Int first_row = hypre_ParCSRMatrixFirstRowIndex(A); */
HYPRE_Int first_col = hypre_ParCSRMatrixFirstColDiag(A);
HYPRE_BigInt *col_map_offd_A = hypre_ParCSRMatrixColMapOffd(A);
HYPRE_Int num_cols_A_offd = hypre_CSRMatrixNumCols(A_offd);
HYPRE_BigInt *d_col_map_offd_A = hypre_ParCSRMatrixDeviceColMapOffd(A);
MPI_Comm comm = hypre_ParCSRMatrixComm(A);
HYPRE_Int num_procs;
HYPRE_Int my_id;
void **vrequest;
hypre_CSRMatrix *A_ext;
hypre_MPI_Comm_size(comm, &num_procs);
hypre_MPI_Comm_rank(comm, &my_id);
/* number of sends (#procs) */
num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg);
/* number of rows to send */
num_rows_send = hypre_ParCSRCommPkgSendMapStart(comm_pkg, num_sends);
/* number of recvs (#procs) */
num_recvs = hypre_ParCSRCommPkgNumRecvs(comm_pkg);
/* number of rows to recv */
num_rows_recv = hypre_ParCSRCommPkgRecvVecStart(comm_pkg, num_recvs);
/* must be true if indices contains proper offd indices */
hypre_assert(indices_len == num_rows_recv);
/* send_i/recv_i:
* the arrays to send and recv: we first send and recv the row lengths */
d_send_i = hypre_TAlloc(HYPRE_Int, num_rows_send + 1, HYPRE_MEMORY_DEVICE);
d_send_map = hypre_TAlloc(HYPRE_Int, num_rows_send, HYPRE_MEMORY_DEVICE);
send_i = hypre_TAlloc(HYPRE_Int, num_rows_send, HYPRE_MEMORY_HOST);
recv_i = hypre_TAlloc(HYPRE_Int, num_rows_recv + 1, HYPRE_MEMORY_HOST);
d_recv_i = hypre_TAlloc(HYPRE_Int, num_rows_recv + 1, HYPRE_MEMORY_DEVICE);
/* fill the send array with row lengths */
hypre_TMemcpy(d_send_map, hypre_ParCSRCommPkgSendMapElmts(comm_pkg), HYPRE_Int,
num_rows_send, HYPRE_MEMORY_DEVICE, HYPRE_MEMORY_HOST);
hypre_Memset(d_send_i, 0, sizeof(HYPRE_Int), HYPRE_MEMORY_DEVICE);
hypreDevice_GetRowNnz(num_rows_send, d_send_map, A_diag_i, A_offd_i, d_send_i+1);
/* send array send_i out: deviceTohost first and MPI (async)
* note the shift in recv_i by one */
hypre_TMemcpy(send_i, d_send_i+1, HYPRE_Int, num_rows_send, HYPRE_MEMORY_HOST, HYPRE_MEMORY_DEVICE);
comm_handle = hypre_ParCSRCommHandleCreate(11, comm_pkg, send_i, recv_i+1);
hypreDevice_IntegerInclusiveScan(num_rows_send + 1, d_send_i);
/* total number of nnz to send */
hypre_TMemcpy(&num_nnz_send, d_send_i+num_rows_send, HYPRE_Int, 1, HYPRE_MEMORY_HOST, HYPRE_MEMORY_DEVICE);
/* prepare data to send out. overlap with the above commmunication */
d_send_j = hypre_TAlloc(HYPRE_BigInt, num_nnz_send, HYPRE_MEMORY_DEVICE);
if (want_data)
{
d_send_a = hypre_TAlloc(HYPRE_Complex, num_nnz_send, HYPRE_MEMORY_DEVICE);
}
if (d_col_map_offd_A == NULL)
{
d_col_map_offd_A = hypre_TAlloc(HYPRE_BigInt, num_cols_A_offd, HYPRE_MEMORY_DEVICE);
hypre_TMemcpy(d_col_map_offd_A, col_map_offd_A, HYPRE_BigInt, num_cols_A_offd,
HYPRE_MEMORY_DEVICE, HYPRE_MEMORY_HOST);
hypre_ParCSRMatrixDeviceColMapOffd(A) = d_col_map_offd_A;
}
/* job == 2, d_send_i is input that contains row ptrs (length num_rows_send) */
hypreDevice_CopyParCSRRows(num_rows_send, d_send_map, 2, num_procs > 1,
first_col, d_col_map_offd_A,
A_diag_i, A_diag_j, A_diag_a,
A_offd_i, A_offd_j, A_offd_a,
d_send_i, d_send_j, d_send_a);
/* pointers to each proc in send_j */
send_jstarts = hypre_TAlloc(HYPRE_Int, num_sends + 1, HYPRE_MEMORY_HOST);
send_jstarts[0] = 0;
for (i = 1; i <= num_sends; i++)
{
send_jstarts[i] = send_jstarts[i-1];
for ( j = hypre_ParCSRCommPkgSendMapStart(comm_pkg, i-1);
j < hypre_ParCSRCommPkgSendMapStart(comm_pkg, i);
j++ )
{
send_jstarts[i] += send_i[j];
}
}
hypre_assert(send_jstarts[num_sends] == num_nnz_send);
/* finish the above communication: send_i/recv_i */
hypre_ParCSRCommHandleDestroy(comm_handle);
/* adjust recv_i to ptrs */
recv_i[0] = 0;
for (i = 1; i <= num_rows_recv; i++)
{
recv_i[i] += recv_i[i-1];
}
num_nnz_recv = recv_i[num_rows_recv];
/* allocate device memory for j and a */
d_recv_j = hypre_TAlloc(HYPRE_BigInt, num_nnz_recv, HYPRE_MEMORY_DEVICE);
if (want_data)
{
d_recv_a = hypre_TAlloc(HYPRE_Complex, num_nnz_recv, HYPRE_MEMORY_DEVICE);
}
recv_jstarts = hypre_TAlloc(HYPRE_Int, num_recvs + 1, HYPRE_MEMORY_HOST);
recv_jstarts[0] = 0;
for (i = 1; i <= num_recvs; i++)
{
j = hypre_ParCSRCommPkgRecvVecStart(comm_pkg, i);
recv_jstarts[i] = recv_i[j];
}
/* ready to send and recv: create a communication package for data */
comm_pkg_j = hypre_CTAlloc(hypre_ParCSRCommPkg, 1, HYPRE_MEMORY_HOST);
hypre_ParCSRCommPkgComm (comm_pkg_j) = comm;
hypre_ParCSRCommPkgNumSends (comm_pkg_j) = num_sends;
hypre_ParCSRCommPkgSendProcs (comm_pkg_j) = hypre_ParCSRCommPkgSendProcs(comm_pkg);
hypre_ParCSRCommPkgSendMapStarts(comm_pkg_j) = send_jstarts;
hypre_ParCSRCommPkgNumRecvs (comm_pkg_j) = num_recvs;
hypre_ParCSRCommPkgRecvProcs (comm_pkg_j) = hypre_ParCSRCommPkgRecvProcs(comm_pkg);
hypre_ParCSRCommPkgRecvVecStarts(comm_pkg_j) = recv_jstarts;
/* init communication */
/* ja */
comm_handle_j = hypre_ParCSRCommHandleCreate_v2(21, comm_pkg_j,
HYPRE_MEMORY_DEVICE, d_send_j,
HYPRE_MEMORY_DEVICE, d_recv_j);
if (want_data)
{
/* a */
comm_handle_a = hypre_ParCSRCommHandleCreate_v2(1, comm_pkg_j,
HYPRE_MEMORY_DEVICE, d_send_a,
HYPRE_MEMORY_DEVICE, d_recv_a);
}
else
{
comm_handle_a = NULL;
}
hypre_TMemcpy(d_recv_i, recv_i, HYPRE_Int, num_rows_recv+1, HYPRE_MEMORY_DEVICE, HYPRE_MEMORY_HOST);
/* create A_ext: on device */
A_ext = hypre_CSRMatrixCreate(num_rows_recv, hypre_ParCSRMatrixGlobalNumCols(A), num_nnz_recv);
hypre_CSRMatrixI (A_ext) = d_recv_i;
hypre_CSRMatrixBigJ(A_ext) = d_recv_j;
hypre_CSRMatrixData(A_ext) = d_recv_a;
hypre_CSRMatrixMemoryLocation(A_ext) = HYPRE_MEMORY_DEVICE;
/* output */
vrequest = hypre_TAlloc(void *, 3, HYPRE_MEMORY_HOST);
vrequest[0] = (void *) comm_handle_j;
vrequest[1] = (void *) comm_handle_a;
vrequest[2] = (void *) A_ext;
*request_ptr = (void *) vrequest;
/* free */
hypre_TFree(send_i, HYPRE_MEMORY_HOST);
hypre_TFree(recv_i, HYPRE_MEMORY_HOST);
hypre_TFree(d_send_i, HYPRE_MEMORY_DEVICE);
hypre_TFree(d_send_map, HYPRE_MEMORY_DEVICE);
hypre_TFree(hypre_ParCSRCommPkgSendMapStarts(comm_pkg_j), HYPRE_MEMORY_HOST);
hypre_TFree(hypre_ParCSRCommPkgRecvVecStarts(comm_pkg_j), HYPRE_MEMORY_HOST);
hypre_TFree(comm_pkg_j, HYPRE_MEMORY_HOST);
return hypre_error_flag;
}
hypre_CSRMatrix*
hypre_ParcsrGetExternalRowsDeviceWait(void *vrequest)
{
void **request = (void **) vrequest;
hypre_ParCSRCommHandle *comm_handle_j = (hypre_ParCSRCommHandle *) request[0];
hypre_ParCSRCommHandle *comm_handle_a = (hypre_ParCSRCommHandle *) request[1];
hypre_CSRMatrix *A_ext = (hypre_CSRMatrix *) request[2];
HYPRE_BigInt *send_j = comm_handle_j ? (HYPRE_BigInt *) hypre_ParCSRCommHandleSendData(comm_handle_j) : NULL;
HYPRE_Complex *send_a = comm_handle_a ? (HYPRE_Complex *) hypre_ParCSRCommHandleSendData(comm_handle_a) : NULL;
hypre_ParCSRCommHandleDestroy(comm_handle_j);
hypre_ParCSRCommHandleDestroy(comm_handle_a);
hypre_TFree(send_j, HYPRE_MEMORY_DEVICE);
hypre_TFree(send_a, HYPRE_MEMORY_DEVICE);
hypre_TFree(request, HYPRE_MEMORY_HOST);
return A_ext;
}
hypre_CSRMatrix*
hypre_MergeDiagAndOffdDevice(hypre_ParCSRMatrix *A)
{
MPI_Comm comm = hypre_ParCSRMatrixComm(A);
hypre_CSRMatrix *A_diag = hypre_ParCSRMatrixDiag(A);
HYPRE_Complex *A_diag_a = hypre_CSRMatrixData(A_diag);
HYPRE_Int *A_diag_i = hypre_CSRMatrixI(A_diag);
HYPRE_Int *A_diag_j = hypre_CSRMatrixJ(A_diag);
hypre_CSRMatrix *A_offd = hypre_ParCSRMatrixOffd(A);
HYPRE_Complex *A_offd_a = hypre_CSRMatrixData(A_offd);
HYPRE_Int *A_offd_i = hypre_CSRMatrixI(A_offd);
HYPRE_Int *A_offd_j = hypre_CSRMatrixJ(A_offd);
HYPRE_Int local_num_rows = hypre_CSRMatrixNumRows(A_diag);
HYPRE_BigInt glbal_num_cols = hypre_ParCSRMatrixGlobalNumCols(A);
HYPRE_BigInt first_col = hypre_ParCSRMatrixFirstColDiag(A);
HYPRE_Int num_cols_A_offd = hypre_CSRMatrixNumCols(A_offd);
HYPRE_BigInt *col_map_offd_A = hypre_ParCSRMatrixColMapOffd(A);
HYPRE_BigInt *d_col_map_offd_A = hypre_ParCSRMatrixDeviceColMapOffd(A);
hypre_CSRMatrix *B;
HYPRE_Int B_nrows = local_num_rows;
HYPRE_BigInt B_ncols = glbal_num_cols;
HYPRE_Int *B_i = hypre_TAlloc(HYPRE_Int, B_nrows + 1, HYPRE_MEMORY_DEVICE);
HYPRE_BigInt *B_j;
HYPRE_Complex *B_a;
HYPRE_Int B_nnz;
HYPRE_Int num_procs;
hypre_MPI_Comm_size(comm, &num_procs);
hypre_Memset(B_i, 0, sizeof(HYPRE_Int), HYPRE_MEMORY_DEVICE);
hypreDevice_GetRowNnz(B_nrows, NULL, A_diag_i, A_offd_i, B_i+1);
hypreDevice_IntegerInclusiveScan(B_nrows+1, B_i);
/* total number of nnz */
hypre_TMemcpy(&B_nnz, B_i+B_nrows, HYPRE_Int, 1, HYPRE_MEMORY_HOST, HYPRE_MEMORY_DEVICE);
B_j = hypre_TAlloc(HYPRE_BigInt, B_nnz, HYPRE_MEMORY_DEVICE);
B_a = hypre_TAlloc(HYPRE_Complex, B_nnz, HYPRE_MEMORY_DEVICE);
if (d_col_map_offd_A == NULL)
{
d_col_map_offd_A = hypre_TAlloc(HYPRE_BigInt, num_cols_A_offd, HYPRE_MEMORY_DEVICE);
hypre_TMemcpy(d_col_map_offd_A, col_map_offd_A, HYPRE_BigInt, num_cols_A_offd,
HYPRE_MEMORY_DEVICE, HYPRE_MEMORY_HOST);
hypre_ParCSRMatrixDeviceColMapOffd(A) = d_col_map_offd_A;
}
hypreDevice_CopyParCSRRows(B_nrows, NULL, 2, num_procs > 1, first_col, d_col_map_offd_A,
A_diag_i, A_diag_j, A_diag_a, A_offd_i, A_offd_j, A_offd_a,
B_i, B_j, B_a);
/* output */
B = hypre_CSRMatrixCreate(B_nrows, B_ncols, B_nnz);
hypre_CSRMatrixI (B) = B_i;
hypre_CSRMatrixBigJ(B) = B_j;
hypre_CSRMatrixData(B) = B_a;
hypre_CSRMatrixMemoryLocation(B) = HYPRE_MEMORY_DEVICE;
hypre_SyncCudaComputeStream(hypre_handle());
return B;
}
HYPRE_Int
hypre_ExchangeExternalRowsDeviceInit( hypre_CSRMatrix *B_ext,
hypre_ParCSRCommPkg *comm_pkg_A,
void **request_ptr)
{
MPI_Comm comm = hypre_ParCSRCommPkgComm(comm_pkg_A);
HYPRE_Int num_recvs = hypre_ParCSRCommPkgNumRecvs(comm_pkg_A);
HYPRE_Int *recv_procs = hypre_ParCSRCommPkgRecvProcs(comm_pkg_A);
HYPRE_Int *recv_vec_starts = hypre_ParCSRCommPkgRecvVecStarts(comm_pkg_A);
HYPRE_Int num_sends = hypre_ParCSRCommPkgNumSends(comm_pkg_A);
HYPRE_Int *send_procs = hypre_ParCSRCommPkgSendProcs(comm_pkg_A);
HYPRE_Int *send_map_starts = hypre_ParCSRCommPkgSendMapStarts(comm_pkg_A);
HYPRE_Int num_elmts_send = send_map_starts[num_sends];
HYPRE_Int num_elmts_recv = recv_vec_starts[num_recvs];
HYPRE_Int *B_ext_i_d = hypre_CSRMatrixI(B_ext);
HYPRE_BigInt *B_ext_j_d = hypre_CSRMatrixBigJ(B_ext);
HYPRE_Complex *B_ext_a_d = hypre_CSRMatrixData(B_ext);
HYPRE_Int B_ext_ncols = hypre_CSRMatrixNumCols(B_ext);
HYPRE_Int B_ext_nrows = hypre_CSRMatrixNumRows(B_ext);
HYPRE_Int B_ext_nnz = hypre_CSRMatrixNumNonzeros(B_ext);
HYPRE_Int *B_ext_rownnz_d = hypre_TAlloc(HYPRE_Int, B_ext_nrows + 1, HYPRE_MEMORY_DEVICE);
HYPRE_Int *B_ext_rownnz_h = hypre_TAlloc(HYPRE_Int, B_ext_nrows, HYPRE_MEMORY_HOST);
HYPRE_Int *B_ext_i_h = hypre_TAlloc(HYPRE_Int, B_ext_nrows + 1, HYPRE_MEMORY_HOST);
hypre_assert(num_elmts_recv == B_ext_nrows);
/* output matrix */
hypre_CSRMatrix *B_int_d;
HYPRE_Int B_int_nrows = num_elmts_send;
HYPRE_Int B_int_ncols = B_ext_ncols;
HYPRE_Int *B_int_i_h = hypre_TAlloc(HYPRE_Int, B_int_nrows + 1, HYPRE_MEMORY_HOST);
HYPRE_Int *B_int_i_d = hypre_TAlloc(HYPRE_Int, B_int_nrows + 1, HYPRE_MEMORY_DEVICE);
HYPRE_BigInt *B_int_j_d = NULL;
HYPRE_Complex *B_int_a_d = NULL;
HYPRE_Int B_int_nnz;
hypre_ParCSRCommHandle *comm_handle, *comm_handle_j, *comm_handle_a;
hypre_ParCSRCommPkg *comm_pkg_j;
HYPRE_Int *jdata_recv_vec_starts;
HYPRE_Int *jdata_send_map_starts;
HYPRE_Int i;
HYPRE_Int num_procs, my_id;
void **vrequest;
hypre_MPI_Comm_size(comm, &num_procs);
hypre_MPI_Comm_rank(comm, &my_id);
jdata_send_map_starts = hypre_TAlloc(HYPRE_Int, num_sends+1, HYPRE_MEMORY_HOST);
/*--------------------------------------------------------------------------
* B_ext_rownnz contains the number of elements of row j
* (to be determined through send_map_elmnts on the receiving end)
*--------------------------------------------------------------------------*/
HYPRE_THRUST_CALL(adjacent_difference, B_ext_i_d, B_ext_i_d + B_ext_nrows + 1, B_ext_rownnz_d);
hypre_TMemcpy(B_ext_rownnz_h, B_ext_rownnz_d + 1, HYPRE_Int, B_ext_nrows,
HYPRE_MEMORY_HOST, HYPRE_MEMORY_DEVICE);
/*--------------------------------------------------------------------------
* initialize communication: send/recv the row nnz
* (note the use of comm_pkg_A, mode 12, as in transpose matvec
*--------------------------------------------------------------------------*/
comm_handle = hypre_ParCSRCommHandleCreate(12, comm_pkg_A, B_ext_rownnz_h, B_int_i_h + 1);
jdata_recv_vec_starts = hypre_TAlloc(HYPRE_Int, num_recvs + 1, HYPRE_MEMORY_HOST);
jdata_recv_vec_starts[0] = 0;
B_ext_i_h[0] = 0;
hypre_TMemcpy(B_ext_i_h + 1, B_ext_rownnz_h, HYPRE_Int, B_ext_nrows, HYPRE_MEMORY_HOST, HYPRE_MEMORY_HOST);
for (i = 1; i <= B_ext_nrows; i++)
{
B_ext_i_h[i] += B_ext_i_h[i-1];
}
hypre_assert(B_ext_i_h[B_ext_nrows] == B_ext_nnz);
for (i = 1; i <= num_recvs; i++)
{
jdata_recv_vec_starts[i] = B_ext_i_h[recv_vec_starts[i]];
}
comm_pkg_j = hypre_CTAlloc(hypre_ParCSRCommPkg, 1, HYPRE_MEMORY_HOST);
hypre_ParCSRCommPkgComm(comm_pkg_j) = comm;
hypre_ParCSRCommPkgNumSends(comm_pkg_j) = num_recvs;
hypre_ParCSRCommPkgNumRecvs(comm_pkg_j) = num_sends;
hypre_ParCSRCommPkgSendProcs(comm_pkg_j) = recv_procs;
hypre_ParCSRCommPkgRecvProcs(comm_pkg_j) = send_procs;
hypre_ParCSRCommHandleDestroy(comm_handle);
/*--------------------------------------------------------------------------
* compute B_int: row nnz to row ptrs
*--------------------------------------------------------------------------*/
B_int_i_h[0] = 0;
for (i = 1; i <= B_int_nrows; i++)
{
B_int_i_h[i] += B_int_i_h[i-1];
}
B_int_nnz = B_int_i_h[B_int_nrows];
B_int_j_d = hypre_TAlloc(HYPRE_BigInt, B_int_nnz, HYPRE_MEMORY_DEVICE);
B_int_a_d = hypre_TAlloc(HYPRE_Complex, B_int_nnz, HYPRE_MEMORY_DEVICE);
for (i = 0; i <= num_sends; i++)
{
jdata_send_map_starts[i] = B_int_i_h[send_map_starts[i]];
}
/* note the order of send/recv is reversed */
hypre_ParCSRCommPkgRecvVecStarts(comm_pkg_j) = jdata_send_map_starts;
hypre_ParCSRCommPkgSendMapStarts(comm_pkg_j) = jdata_recv_vec_starts;
/* send/recv CSR rows */
comm_handle_a = hypre_ParCSRCommHandleCreate_v2( 1, comm_pkg_j,
HYPRE_MEMORY_DEVICE, B_ext_a_d,
HYPRE_MEMORY_DEVICE, B_int_a_d );
comm_handle_j = hypre_ParCSRCommHandleCreate_v2(21, comm_pkg_j,
HYPRE_MEMORY_DEVICE, B_ext_j_d,
HYPRE_MEMORY_DEVICE, B_int_j_d );
hypre_TMemcpy(B_int_i_d, B_int_i_h, HYPRE_Int, B_int_nrows+1, HYPRE_MEMORY_DEVICE, HYPRE_MEMORY_HOST);
/* create CSR: on device */
B_int_d = hypre_CSRMatrixCreate(B_int_nrows, B_int_ncols, B_int_nnz);
hypre_CSRMatrixI(B_int_d) = B_int_i_d;
hypre_CSRMatrixBigJ(B_int_d) = B_int_j_d;
hypre_CSRMatrixData(B_int_d) = B_int_a_d;
hypre_CSRMatrixMemoryLocation(B_int_d) = HYPRE_MEMORY_DEVICE;
/* output */
vrequest = hypre_TAlloc(void *, 3, HYPRE_MEMORY_HOST);
vrequest[0] = (void *) comm_handle_j;
vrequest[1] = (void *) comm_handle_a;
vrequest[2] = (void *) B_int_d;
*request_ptr = (void *) vrequest;
/* free */
hypre_TFree(B_ext_rownnz_d, HYPRE_MEMORY_DEVICE);
hypre_TFree(B_ext_rownnz_h, HYPRE_MEMORY_HOST);
hypre_TFree(B_ext_i_h, HYPRE_MEMORY_HOST);
hypre_TFree(B_int_i_h, HYPRE_MEMORY_HOST);
hypre_TFree(hypre_ParCSRCommPkgSendMapStarts(comm_pkg_j), HYPRE_MEMORY_HOST);
hypre_TFree(hypre_ParCSRCommPkgRecvVecStarts(comm_pkg_j), HYPRE_MEMORY_HOST);
hypre_TFree(comm_pkg_j, HYPRE_MEMORY_HOST);
return hypre_error_flag;
}
hypre_CSRMatrix*
hypre_ExchangeExternalRowsDeviceWait(void *vrequest)
{
void **request = (void **) vrequest;
hypre_ParCSRCommHandle *comm_handle_j = (hypre_ParCSRCommHandle *) request[0];
hypre_ParCSRCommHandle *comm_handle_a = (hypre_ParCSRCommHandle *) request[1];
hypre_CSRMatrix *B_int_d = (hypre_CSRMatrix *) request[2];
/* communication done */
hypre_ParCSRCommHandleDestroy(comm_handle_j);
hypre_ParCSRCommHandleDestroy(comm_handle_a);
hypre_TFree(request, HYPRE_MEMORY_HOST);
return B_int_d;
}
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
/* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
HYPRE_Int
hypre_ParCSRMatrixExtractBExtDeviceInit( hypre_ParCSRMatrix *B,
hypre_ParCSRMatrix *A,
HYPRE_Int want_data,
void **request_ptr)
{
hypre_assert( hypre_CSRMatrixMemoryLocation(hypre_ParCSRMatrixDiag(B)) ==
hypre_CSRMatrixMemoryLocation(hypre_ParCSRMatrixOffd(B)) );
/*
hypre_assert( hypre_GetActualMemLocation(
hypre_CSRMatrixMemoryLocation(hypre_ParCSRMatrixDiag(B))) == HYPRE_MEMORY_DEVICE );
*/
hypre_ParcsrGetExternalRowsDeviceInit(B,
hypre_CSRMatrixNumCols(hypre_ParCSRMatrixOffd(A)),
hypre_ParCSRMatrixColMapOffd(A),
hypre_ParCSRMatrixCommPkg(A),
want_data,
request_ptr);
return hypre_error_flag;
}
hypre_CSRMatrix*
hypre_ParCSRMatrixExtractBExtDeviceWait(void *request)
{
return hypre_ParcsrGetExternalRowsDeviceWait(request);
}
hypre_CSRMatrix*
hypre_ParCSRMatrixExtractBExtDevice( hypre_ParCSRMatrix *B,
hypre_ParCSRMatrix *A,
HYPRE_Int want_data )
{
void *request;
hypre_ParCSRMatrixExtractBExtDeviceInit(B, A, want_data, &request);
return hypre_ParCSRMatrixExtractBExtDeviceWait(request);
}
/* return B = [Adiag, Aoffd] */
#if 1
__global__ void
hypreCUDAKernel_ConcatDiagAndOffd(HYPRE_Int nrows, HYPRE_Int diag_ncol,
HYPRE_Int *d_diag_i, HYPRE_Int *d_diag_j, HYPRE_Complex *d_diag_a,
HYPRE_Int *d_offd_i, HYPRE_Int *d_offd_j, HYPRE_Complex *d_offd_a,
HYPRE_Int *cols_offd_map,
HYPRE_Int *d_ib, HYPRE_Int *d_jb, HYPRE_Complex *d_ab)
{
const HYPRE_Int row = hypre_cuda_get_grid_warp_id<1,1>();
if (row >= nrows)
{
return;
}
/* lane id inside the warp */
const HYPRE_Int lane_id = hypre_cuda_get_lane_id<1>();
HYPRE_Int i, j, k, p, istart, iend, bstart;
/* diag part */
if (lane_id < 2)
{
j = read_only_load(d_diag_i + row + lane_id);
}
if (lane_id == 0)
{
k = read_only_load(d_ib + row);
}
istart = __shfl_sync(HYPRE_WARP_FULL_MASK, j, 0);
iend = __shfl_sync(HYPRE_WARP_FULL_MASK, j, 1);
bstart = __shfl_sync(HYPRE_WARP_FULL_MASK, k, 0);
p = bstart - istart;
for (i = istart + lane_id; i < iend; i += HYPRE_WARP_SIZE)
{
d_jb[p+i] = read_only_load(d_diag_j + i);
d_ab[p+i] = read_only_load(d_diag_a + i);
}
/* offd part */
if (lane_id < 2)
{
j = read_only_load(d_offd_i + row + lane_id);
}
bstart += iend - istart;
istart = __shfl_sync(HYPRE_WARP_FULL_MASK, j, 0);
iend = __shfl_sync(HYPRE_WARP_FULL_MASK, j, 1);
p = bstart - istart;
for (i = istart + lane_id; i < iend; i += HYPRE_WARP_SIZE)
{
const HYPRE_Int t = read_only_load(d_offd_j + i);
d_jb[p+i] = (cols_offd_map ? read_only_load(&cols_offd_map[t]) : t) + diag_ncol;
d_ab[p+i] = read_only_load(d_offd_a + i);
}
}
hypre_CSRMatrix*
hypre_ConcatDiagAndOffdDevice(hypre_ParCSRMatrix *A)
{
hypre_CSRMatrix *A_diag = hypre_ParCSRMatrixDiag(A);
hypre_CSRMatrix *A_offd = hypre_ParCSRMatrixOffd(A);
hypre_CSRMatrix *B = hypre_CSRMatrixCreate( hypre_CSRMatrixNumRows(A_diag),
hypre_CSRMatrixNumCols(A_diag) + hypre_CSRMatrixNumCols(A_offd),
hypre_CSRMatrixNumNonzeros(A_diag) + hypre_CSRMatrixNumNonzeros(A_offd) );
hypre_CSRMatrixInitialize_v2(B, 0, HYPRE_MEMORY_DEVICE);
hypreDevice_GetRowNnz(hypre_CSRMatrixNumRows(B), NULL, hypre_CSRMatrixI(A_diag), hypre_CSRMatrixI(A_offd), hypre_CSRMatrixI(B));
HYPRE_THRUST_CALL( exclusive_scan,
hypre_CSRMatrixI(B),
hypre_CSRMatrixI(B) + hypre_CSRMatrixNumRows(B) + 1,
hypre_CSRMatrixI(B) );
const dim3 bDim = hypre_GetDefaultCUDABlockDimension();
const dim3 gDim = hypre_GetDefaultCUDAGridDimension(hypre_CSRMatrixNumRows(A_diag), "warp", bDim);
HYPRE_CUDA_LAUNCH( hypreCUDAKernel_ConcatDiagAndOffd,
gDim, bDim,
hypre_CSRMatrixNumRows(A_diag),
hypre_CSRMatrixNumCols(A_diag),
hypre_CSRMatrixI(A_diag),
hypre_CSRMatrixJ(A_diag),
hypre_CSRMatrixData(A_diag),
hypre_CSRMatrixI(A_offd),
hypre_CSRMatrixJ(A_offd),
hypre_CSRMatrixData(A_offd),
NULL,
hypre_CSRMatrixI(B),
hypre_CSRMatrixJ(B),
hypre_CSRMatrixData(B) );
return B;
}
#else
hypre_CSRMatrix*
hypre_ConcatDiagAndOffdDevice(hypre_ParCSRMatrix *A)
{
hypre_CSRMatrix *A_diag = hypre_ParCSRMatrixDiag(A);
HYPRE_Int *A_diag_i = hypre_CSRMatrixI(A_diag);
HYPRE_Int *A_diag_j = hypre_CSRMatrixJ(A_diag);
HYPRE_Complex *A_diag_a = hypre_CSRMatrixData(A_diag);
HYPRE_Int A_diag_nnz = hypre_CSRMatrixNumNonzeros(A_diag);
hypre_CSRMatrix *A_offd = hypre_ParCSRMatrixOffd(A);
HYPRE_Int *A_offd_i = hypre_CSRMatrixI(A_offd);
HYPRE_Int *A_offd_j = hypre_CSRMatrixJ(A_offd);
HYPRE_Complex *A_offd_a = hypre_CSRMatrixData(A_offd);
HYPRE_Int A_offd_nnz = hypre_CSRMatrixNumNonzeros(A_offd);
hypre_CSRMatrix *B;
HYPRE_Int B_nrows = hypre_CSRMatrixNumRows(A_diag);
HYPRE_Int B_ncols = hypre_CSRMatrixNumCols(A_diag) + hypre_CSRMatrixNumCols(A_offd);
HYPRE_Int B_nnz = A_diag_nnz + A_offd_nnz;
HYPRE_Int *B_ii = hypre_TAlloc(HYPRE_Int, B_nnz, HYPRE_MEMORY_DEVICE);
HYPRE_Int *B_j = hypre_TAlloc(HYPRE_Int, B_nnz, HYPRE_MEMORY_DEVICE);
HYPRE_Complex *B_a = hypre_TAlloc(HYPRE_Complex, B_nnz, HYPRE_MEMORY_DEVICE);
// Adiag
HYPRE_Int *A_diag_ii = hypreDevice_CsrRowPtrsToIndices(B_nrows, A_diag_nnz, A_diag_i);
HYPRE_THRUST_CALL( copy_n,
thrust::make_zip_iterator(thrust::make_tuple(A_diag_ii, A_diag_j, A_diag_a)),
A_diag_nnz,
thrust::make_zip_iterator(thrust::make_tuple(B_ii, B_j, B_a)) );
hypre_TFree(A_diag_ii, HYPRE_MEMORY_DEVICE);
// Aoffd
HYPRE_Int *A_offd_ii = hypreDevice_CsrRowPtrsToIndices(B_nrows, A_offd_nnz, A_offd_i);
HYPRE_THRUST_CALL( copy_n,
thrust::make_zip_iterator(thrust::make_tuple(A_offd_ii, A_offd_a)),
A_offd_nnz,
thrust::make_zip_iterator(thrust::make_tuple(B_ii, B_a)) + A_diag_nnz );
hypre_TFree(A_offd_ii, HYPRE_MEMORY_DEVICE);
HYPRE_THRUST_CALL( transform,
A_offd_j,
A_offd_j + A_offd_nnz,
thrust::make_constant_iterator(hypre_CSRMatrixNumCols(A_diag)),
B_j + A_diag_nnz,
thrust::plus<HYPRE_Int>() );
// B
HYPRE_THRUST_CALL( stable_sort_by_key,
B_ii,
B_ii + B_nnz,
thrust::make_zip_iterator(thrust::make_tuple(B_j, B_a)) );
HYPRE_Int *B_i = hypreDevice_CsrRowIndicesToPtrs(B_nrows, B_nnz, B_ii);
hypre_TFree(B_ii, HYPRE_MEMORY_DEVICE);
B = hypre_CSRMatrixCreate(B_nrows, B_ncols, B_nnz);
hypre_CSRMatrixI(B) = B_i;
hypre_CSRMatrixJ(B) = B_j;
hypre_CSRMatrixData(B) = B_a;
hypre_CSRMatrixMemoryLocation(B) = HYPRE_MEMORY_DEVICE;
return B;
}
#endif
/* return B = [Adiag, Aoffd; E] */
#if 1
HYPRE_Int
hypre_ConcatDiagOffdAndExtDevice(hypre_ParCSRMatrix *A,
hypre_CSRMatrix *E,
hypre_CSRMatrix **B_ptr,
HYPRE_Int *num_cols_offd_ptr,
HYPRE_BigInt **cols_map_offd_ptr)
{
hypre_CSRMatrix *A_diag = hypre_ParCSRMatrixDiag(A);
hypre_CSRMatrix *A_offd = hypre_ParCSRMatrixOffd(A);
hypre_CSRMatrix *E_diag, *E_offd, *B;
HYPRE_Int *cols_offd_map, num_cols_offd;
HYPRE_BigInt *cols_map_offd;
hypre_CSRMatrixSplitDevice(E, hypre_ParCSRMatrixFirstColDiag(A), hypre_ParCSRMatrixLastColDiag(A),
hypre_CSRMatrixNumCols(A_offd), hypre_ParCSRMatrixDeviceColMapOffd(A),
&cols_offd_map, &num_cols_offd, &cols_map_offd, &E_diag, &E_offd);
B = hypre_CSRMatrixCreate(hypre_ParCSRMatrixNumRows(A) + hypre_CSRMatrixNumRows(E),
hypre_ParCSRMatrixNumCols(A) + num_cols_offd,
hypre_CSRMatrixNumNonzeros(A_diag) + hypre_CSRMatrixNumNonzeros(A_offd) + hypre_CSRMatrixNumNonzeros(E));
hypre_CSRMatrixInitialize_v2(B, 0, HYPRE_MEMORY_DEVICE);
hypreDevice_GetRowNnz(hypre_ParCSRMatrixNumRows(A), NULL, hypre_CSRMatrixI(A_diag), hypre_CSRMatrixI(A_offd), hypre_CSRMatrixI(B));
HYPRE_THRUST_CALL( exclusive_scan,
hypre_CSRMatrixI(B),
hypre_CSRMatrixI(B) + hypre_ParCSRMatrixNumRows(A) + 1,
hypre_CSRMatrixI(B) );
dim3 bDim = hypre_GetDefaultCUDABlockDimension();
dim3 gDim = hypre_GetDefaultCUDAGridDimension(hypre_ParCSRMatrixNumRows(A), "warp", bDim);
HYPRE_CUDA_LAUNCH( hypreCUDAKernel_ConcatDiagAndOffd,
gDim, bDim,
hypre_CSRMatrixNumRows(A_diag),
hypre_CSRMatrixNumCols(A_diag),
hypre_CSRMatrixI(A_diag),
hypre_CSRMatrixJ(A_diag),
hypre_CSRMatrixData(A_diag),
hypre_CSRMatrixI(A_offd),
hypre_CSRMatrixJ(A_offd),
hypre_CSRMatrixData(A_offd),
cols_offd_map,
hypre_CSRMatrixI(B),
hypre_CSRMatrixJ(B),
hypre_CSRMatrixData(B) );
hypre_TFree(cols_offd_map, HYPRE_MEMORY_DEVICE);
hypre_TMemcpy(hypre_CSRMatrixI(B) + hypre_ParCSRMatrixNumRows(A) + 1, hypre_CSRMatrixI(E) + 1, HYPRE_Int, hypre_CSRMatrixNumRows(E),
HYPRE_MEMORY_DEVICE, HYPRE_MEMORY_DEVICE);
HYPRE_THRUST_CALL( transform,
hypre_CSRMatrixI(B) + hypre_ParCSRMatrixNumRows(A) + 1,
hypre_CSRMatrixI(B) + hypre_ParCSRMatrixNumRows(A) + hypre_CSRMatrixNumRows(E) + 1,
thrust::make_constant_iterator(hypre_CSRMatrixNumNonzeros(A_diag) + hypre_CSRMatrixNumNonzeros(A_offd)),
hypre_CSRMatrixI(B) + hypre_ParCSRMatrixNumRows(A) + 1,
thrust::plus<HYPRE_Int>() );
gDim = hypre_GetDefaultCUDAGridDimension(hypre_CSRMatrixNumRows(E), "warp", bDim);
hypre_assert(hypre_CSRMatrixNumCols(E_diag) == hypre_CSRMatrixNumCols(A_diag));
HYPRE_CUDA_LAUNCH( hypreCUDAKernel_ConcatDiagAndOffd,
gDim, bDim,
hypre_CSRMatrixNumRows(E_diag),
hypre_CSRMatrixNumCols(E_diag),
hypre_CSRMatrixI(E_diag),
hypre_CSRMatrixJ(E_diag),
hypre_CSRMatrixData(E_diag),
hypre_CSRMatrixI(E_offd),
hypre_CSRMatrixJ(E_offd),
hypre_CSRMatrixData(E_offd),
NULL,
hypre_CSRMatrixI(B) + hypre_ParCSRMatrixNumRows(A),
hypre_CSRMatrixJ(B),
hypre_CSRMatrixData(B) );
hypre_CSRMatrixDestroy(E_diag);
hypre_CSRMatrixDestroy(E_offd);
*B_ptr = B;
*num_cols_offd_ptr = num_cols_offd;
*cols_map_offd_ptr = cols_map_offd;
return hypre_error_flag;
}
#else
HYPRE_Int
hypre_ConcatDiagOffdAndExtDevice(hypre_ParCSRMatrix *A,
hypre_CSRMatrix *E,
hypre_CSRMatrix **B_ptr,
HYPRE_Int *num_cols_offd_ptr,
HYPRE_BigInt **cols_map_offd_ptr)
{
hypre_CSRMatrix *A_diag = hypre_ParCSRMatrixDiag(A);
HYPRE_Int A_nrows = hypre_CSRMatrixNumRows(A_diag);
HYPRE_Int A_ncols = hypre_CSRMatrixNumCols(A_diag);
HYPRE_Int *A_diag_i = hypre_CSRMatrixI(A_diag);
HYPRE_Int *A_diag_j = hypre_CSRMatrixJ(A_diag);
HYPRE_Complex *A_diag_a = hypre_CSRMatrixData(A_diag);
HYPRE_Int A_diag_nnz = hypre_CSRMatrixNumNonzeros(A_diag);
hypre_CSRMatrix *A_offd = hypre_ParCSRMatrixOffd(A);
HYPRE_Int *A_offd_i = hypre_CSRMatrixI(A_offd);
HYPRE_Int *A_offd_j = hypre_CSRMatrixJ(A_offd);
HYPRE_Complex *A_offd_a = hypre_CSRMatrixData(A_offd);
HYPRE_Int A_offd_nnz = hypre_CSRMatrixNumNonzeros(A_offd);
HYPRE_BigInt first_col_A = hypre_ParCSRMatrixFirstColDiag(A);
HYPRE_BigInt last_col_A = hypre_ParCSRMatrixLastColDiag(A);
HYPRE_Int num_cols_offd_A = hypre_CSRMatrixNumCols(A_offd);
HYPRE_BigInt *col_map_offd_A = hypre_ParCSRMatrixDeviceColMapOffd(A);
HYPRE_Int *E_i = hypre_CSRMatrixI(E);
HYPRE_BigInt *E_bigj = hypre_CSRMatrixBigJ(E);
HYPRE_Complex *E_a = hypre_CSRMatrixData(E);
HYPRE_Int E_nrows = hypre_CSRMatrixNumRows(E);
HYPRE_Int E_nnz = hypre_CSRMatrixNumNonzeros(E);
HYPRE_Int E_diag_nnz, E_offd_nnz;
hypre_CSRMatrix *B;
HYPRE_Int B_nnz = A_diag_nnz + A_offd_nnz + E_nnz;
HYPRE_Int *B_ii = hypre_TAlloc(HYPRE_Int, B_nnz, HYPRE_MEMORY_DEVICE);
HYPRE_Int *B_j = hypre_TAlloc(HYPRE_Int, B_nnz, HYPRE_MEMORY_DEVICE);
HYPRE_Complex *B_a = hypre_TAlloc(HYPRE_Complex, B_nnz, HYPRE_MEMORY_DEVICE);
// E
hypre_CSRMatrixSplitDevice_core(0, E_nrows, E_nnz, NULL, E_bigj, NULL, NULL, first_col_A, last_col_A, num_cols_offd_A,
NULL, NULL, NULL, NULL, &E_diag_nnz, NULL, NULL, NULL, NULL, &E_offd_nnz,
NULL, NULL, NULL, NULL);
HYPRE_Int *cols_offd_map, num_cols_offd;
HYPRE_BigInt *cols_map_offd;
HYPRE_Int *E_ii = hypreDevice_CsrRowPtrsToIndices(E_nrows, E_nnz, E_i);
hypre_CSRMatrixSplitDevice_core(1,
E_nrows, E_nnz, E_ii, E_bigj, E_a, NULL,
first_col_A, last_col_A, num_cols_offd_A, col_map_offd_A,
&cols_offd_map, &num_cols_offd, &cols_map_offd,
&E_diag_nnz,
B_ii + A_diag_nnz + A_offd_nnz,
B_j + A_diag_nnz + A_offd_nnz,
B_a + A_diag_nnz + A_offd_nnz,
NULL,
&E_offd_nnz,
B_ii + A_diag_nnz + A_offd_nnz + E_diag_nnz,
B_j + A_diag_nnz + A_offd_nnz + E_diag_nnz,
B_a + A_diag_nnz + A_offd_nnz + E_diag_nnz,
NULL);
hypre_TFree(E_ii, HYPRE_MEMORY_DEVICE);
HYPRE_THRUST_CALL( transform,
B_ii + A_diag_nnz + A_offd_nnz,
B_ii + B_nnz,
thrust::make_constant_iterator(A_nrows),
B_ii + A_diag_nnz + A_offd_nnz,
thrust::plus<HYPRE_Int>() );
// Adiag
HYPRE_Int *A_diag_ii = hypreDevice_CsrRowPtrsToIndices(A_nrows, A_diag_nnz, A_diag_i);
HYPRE_THRUST_CALL( copy_n,
thrust::make_zip_iterator(thrust::make_tuple(A_diag_ii, A_diag_j, A_diag_a)),
A_diag_nnz,
thrust::make_zip_iterator(thrust::make_tuple(B_ii, B_j, B_a)) );
hypre_TFree(A_diag_ii, HYPRE_MEMORY_DEVICE);
// Aoffd
HYPRE_Int *A_offd_ii = hypreDevice_CsrRowPtrsToIndices(A_nrows, A_offd_nnz, A_offd_i);
HYPRE_THRUST_CALL( copy_n,
thrust::make_zip_iterator(thrust::make_tuple(A_offd_ii, A_offd_a)),
A_offd_nnz,
thrust::make_zip_iterator(thrust::make_tuple(B_ii, B_a)) + A_diag_nnz );
hypre_TFree(A_offd_ii, HYPRE_MEMORY_DEVICE);
HYPRE_THRUST_CALL( gather,
A_offd_j,
A_offd_j + A_offd_nnz,
cols_offd_map,
B_j + A_diag_nnz);
hypre_TFree(cols_offd_map, HYPRE_MEMORY_DEVICE);
HYPRE_THRUST_CALL( transform,
B_j + A_diag_nnz,
B_j + A_diag_nnz + A_offd_nnz,
thrust::make_constant_iterator(A_ncols),
B_j + A_diag_nnz,
thrust::plus<HYPRE_Int>() );
HYPRE_THRUST_CALL( transform,
B_j + A_diag_nnz + A_offd_nnz + E_diag_nnz,
B_j + B_nnz,
thrust::make_constant_iterator(A_ncols),
B_j + A_diag_nnz + A_offd_nnz + E_diag_nnz,
thrust::plus<HYPRE_Int>() );
// B
HYPRE_THRUST_CALL( stable_sort_by_key,
B_ii,
B_ii + B_nnz,
thrust::make_zip_iterator(thrust::make_tuple(B_j, B_a)) );
HYPRE_Int *B_i = hypreDevice_CsrRowIndicesToPtrs(A_nrows + E_nrows, B_nnz, B_ii);
hypre_TFree(B_ii, HYPRE_MEMORY_DEVICE);
B = hypre_CSRMatrixCreate(A_nrows + E_nrows, A_ncols + num_cols_offd, B_nnz);
hypre_CSRMatrixI(B) = B_i;
hypre_CSRMatrixJ(B) = B_j;
hypre_CSRMatrixData(B) = B_a;
hypre_CSRMatrixMemoryLocation(B) = HYPRE_MEMORY_DEVICE;
*B_ptr = B;
*num_cols_offd_ptr = num_cols_offd;
*cols_map_offd_ptr = cols_map_offd;
return hypre_error_flag;
}
#endif
HYPRE_Int
hypre_ParCSRMatrixGetRowDevice( hypre_ParCSRMatrix *mat,
HYPRE_BigInt row,
HYPRE_Int *size,
HYPRE_BigInt **col_ind,
HYPRE_Complex **values )
{
HYPRE_Int nrows, local_row;
HYPRE_BigInt row_start, row_end;
hypre_CSRMatrix *Aa;
hypre_CSRMatrix *Ba;
if (!mat)
{
hypre_error_in_arg(1);
return hypre_error_flag;
}
Aa = (hypre_CSRMatrix *) hypre_ParCSRMatrixDiag(mat);
Ba = (hypre_CSRMatrix *) hypre_ParCSRMatrixOffd(mat);
if (hypre_ParCSRMatrixGetrowactive(mat))
{
return(-1);
}
hypre_ParCSRMatrixGetrowactive(mat) = 1;
row_start = hypre_ParCSRMatrixFirstRowIndex(mat);
row_end = hypre_ParCSRMatrixLastRowIndex(mat) + 1;
nrows = row_end - row_start;
if (row < row_start || row >= row_end)
{
return(-1);
}
local_row = row - row_start;
/* if buffer is not allocated and some information is requested, allocate buffer with the max row_nnz */
if ( !hypre_ParCSRMatrixRowvalues(mat) && (col_ind || values) )
{
HYPRE_Int max_row_nnz;
HYPRE_Int *row_nnz = hypre_TAlloc(HYPRE_Int, nrows, HYPRE_MEMORY_DEVICE);
hypreDevice_GetRowNnz(nrows, NULL, hypre_CSRMatrixI(Aa), hypre_CSRMatrixI(Ba), row_nnz);
hypre_TMemcpy(size, row_nnz + local_row, HYPRE_Int, 1, HYPRE_MEMORY_HOST, HYPRE_MEMORY_DEVICE);
max_row_nnz = HYPRE_THRUST_CALL(reduce, row_nnz, row_nnz + nrows, 0, thrust::maximum<HYPRE_Int>());
/*
HYPRE_Int *max_row_nnz_d = HYPRE_THRUST_CALL(max_element, row_nnz, row_nnz + nrows);
hypre_TMemcpy( &max_row_nnz, max_row_nnz_d,
HYPRE_Int, 1, HYPRE_MEMORY_HOST, HYPRE_MEMORY_DEVICE );
*/
hypre_TFree(row_nnz, HYPRE_MEMORY_DEVICE);
hypre_ParCSRMatrixRowvalues(mat) =
(HYPRE_Complex *) hypre_TAlloc(HYPRE_Complex, max_row_nnz, hypre_ParCSRMatrixMemoryLocation(mat));
hypre_ParCSRMatrixRowindices(mat) =
(HYPRE_BigInt *) hypre_TAlloc(HYPRE_BigInt, max_row_nnz, hypre_ParCSRMatrixMemoryLocation(mat));
}
else
{
HYPRE_Int *size_d = hypre_TAlloc(HYPRE_Int, 1, HYPRE_MEMORY_DEVICE);
hypreDevice_GetRowNnz(1, NULL, hypre_CSRMatrixI(Aa) + local_row, hypre_CSRMatrixI(Ba) + local_row, size_d);
hypre_TMemcpy(size, size_d, HYPRE_Int, 1, HYPRE_MEMORY_HOST, HYPRE_MEMORY_DEVICE);
hypre_TFree(size_d, HYPRE_MEMORY_DEVICE);
}
if (col_ind || values)
{
if (hypre_ParCSRMatrixDeviceColMapOffd(mat) == NULL)
{
hypre_ParCSRMatrixDeviceColMapOffd(mat) =
hypre_TAlloc(HYPRE_BigInt, hypre_CSRMatrixNumCols(Ba), HYPRE_MEMORY_DEVICE);
hypre_TMemcpy( hypre_ParCSRMatrixDeviceColMapOffd(mat),
hypre_ParCSRMatrixColMapOffd(mat),
HYPRE_BigInt,
hypre_CSRMatrixNumCols(Ba),
HYPRE_MEMORY_DEVICE, HYPRE_MEMORY_HOST );
}
hypreDevice_CopyParCSRRows( 1, NULL, -1, Ba != NULL,
hypre_ParCSRMatrixFirstColDiag(mat),
hypre_ParCSRMatrixDeviceColMapOffd(mat),
hypre_CSRMatrixI(Aa) + local_row,
hypre_CSRMatrixJ(Aa),
hypre_CSRMatrixData(Aa),
hypre_CSRMatrixI(Ba) + local_row,
hypre_CSRMatrixJ(Ba),
hypre_CSRMatrixData(Ba),
NULL,
hypre_ParCSRMatrixRowindices(mat),
hypre_ParCSRMatrixRowvalues(mat) );
}
if (col_ind)
{
*col_ind = hypre_ParCSRMatrixRowindices(mat);
}
if (values)
{
*values = hypre_ParCSRMatrixRowvalues(mat);
}
hypre_SyncCudaComputeStream(hypre_handle());
return hypre_error_flag;
}
/* abs == 1, use absolute values
* option == 0, drop all the entries that are smaller than tol
* TODO more options
*/
HYPRE_Int
hypre_ParCSRMatrixDropSmallEntriesDevice( hypre_ParCSRMatrix *A,
HYPRE_Complex tol,
HYPRE_Int abs,
HYPRE_Int option)
{
hypre_CSRMatrix *A_diag = hypre_ParCSRMatrixDiag(A);
hypre_CSRMatrix *A_offd = hypre_ParCSRMatrixOffd(A);
HYPRE_Int num_cols_A_offd = hypre_CSRMatrixNumCols(A_offd);
HYPRE_BigInt *h_col_map_offd_A = hypre_ParCSRMatrixColMapOffd(A);
HYPRE_BigInt *col_map_offd_A = hypre_ParCSRMatrixDeviceColMapOffd(A);
if (col_map_offd_A == NULL)
{
col_map_offd_A = hypre_TAlloc(HYPRE_BigInt, num_cols_A_offd, HYPRE_MEMORY_DEVICE);
hypre_TMemcpy(col_map_offd_A, h_col_map_offd_A, HYPRE_BigInt, num_cols_A_offd,
HYPRE_MEMORY_DEVICE, HYPRE_MEMORY_HOST);
hypre_ParCSRMatrixDeviceColMapOffd(A) = col_map_offd_A;
}
hypre_CSRMatrixDropSmallEntriesDevice(A_diag, tol, abs, option);
hypre_CSRMatrixDropSmallEntriesDevice(A_offd, tol, abs, option);
hypre_ParCSRMatrixSetNumNonzeros(A);
hypre_ParCSRMatrixDNumNonzeros(A) = (HYPRE_Real) hypre_ParCSRMatrixNumNonzeros(A);
/* squeeze out zero columns of A_offd */
HYPRE_Int *tmp_j, *tmp_end, num_cols_A_offd_new;
tmp_j = hypre_TAlloc(HYPRE_Int, hypre_CSRMatrixNumNonzeros(A_offd), HYPRE_MEMORY_DEVICE);
hypre_TMemcpy(tmp_j, hypre_CSRMatrixJ(A_offd), HYPRE_Int, hypre_CSRMatrixNumNonzeros(A_offd),
HYPRE_MEMORY_DEVICE, HYPRE_MEMORY_DEVICE);
HYPRE_THRUST_CALL( sort,
tmp_j,
tmp_j + hypre_CSRMatrixNumNonzeros(A_offd) );
tmp_end = HYPRE_THRUST_CALL( unique,
tmp_j,
tmp_j + hypre_CSRMatrixNumNonzeros(A_offd) );
num_cols_A_offd_new = tmp_end - tmp_j;
hypre_assert(num_cols_A_offd_new <= num_cols_A_offd);
if (num_cols_A_offd_new < num_cols_A_offd)
{
hypre_CSRMatrixNumCols(A_offd) = num_cols_A_offd_new;
HYPRE_Int *offd_mark = hypre_CTAlloc(HYPRE_Int, num_cols_A_offd, HYPRE_MEMORY_DEVICE);
HYPRE_BigInt *col_map_offd_A_new = hypre_TAlloc(HYPRE_BigInt, num_cols_A_offd_new, HYPRE_MEMORY_DEVICE);
HYPRE_THRUST_CALL( scatter,
thrust::counting_iterator<HYPRE_Int>(0),
thrust::counting_iterator<HYPRE_Int>(num_cols_A_offd_new),
tmp_j,
offd_mark );
HYPRE_THRUST_CALL( gather,
hypre_CSRMatrixJ(A_offd),
hypre_CSRMatrixJ(A_offd) + hypre_CSRMatrixNumNonzeros(A_offd),
offd_mark,
hypre_CSRMatrixJ(A_offd) );
HYPRE_THRUST_CALL( gather,
tmp_j,
tmp_j + num_cols_A_offd_new,
col_map_offd_A,
col_map_offd_A_new );
hypre_TFree(offd_mark, HYPRE_MEMORY_DEVICE);
hypre_TFree(col_map_offd_A, HYPRE_MEMORY_DEVICE);
hypre_TFree(h_col_map_offd_A, HYPRE_MEMORY_HOST);
hypre_ParCSRMatrixDeviceColMapOffd(A) = col_map_offd_A_new;
hypre_ParCSRMatrixColMapOffd(A) = hypre_TAlloc(HYPRE_BigInt, num_cols_A_offd_new, HYPRE_MEMORY_HOST);
hypre_TMemcpy(hypre_ParCSRMatrixColMapOffd(A), col_map_offd_A_new, HYPRE_BigInt, num_cols_A_offd_new,
HYPRE_MEMORY_HOST, HYPRE_MEMORY_DEVICE);
}
hypre_TFree(tmp_j, HYPRE_MEMORY_DEVICE);
return hypre_error_flag;
}
#endif // #if defined(HYPRE_USING_CUDA)
/*--------------------------------------------------------------------------
* HYPRE_ParCSRDiagScale
*--------------------------------------------------------------------------*/
HYPRE_Int
hypre_ParCSRDiagScale( HYPRE_ParCSRMatrix HA,
HYPRE_ParVector Hy,
HYPRE_ParVector Hx )
{
hypre_ParCSRMatrix *A = (hypre_ParCSRMatrix *) HA;
hypre_ParVector *y = (hypre_ParVector *) Hy;
hypre_ParVector *x = (hypre_ParVector *) Hx;
HYPRE_Real *x_data = hypre_VectorData(hypre_ParVectorLocalVector(x));
HYPRE_Real *y_data = hypre_VectorData(hypre_ParVectorLocalVector(y));
HYPRE_Real *A_data = hypre_CSRMatrixData(hypre_ParCSRMatrixDiag(A));
HYPRE_Int *A_i = hypre_CSRMatrixI(hypre_ParCSRMatrixDiag(A));
HYPRE_Int local_size = hypre_VectorSize(hypre_ParVectorLocalVector(x));
HYPRE_Int ierr = 0;
#if defined(HYPRE_USING_CUDA)
hypreDevice_DiagScaleVector(local_size, A_i, A_data, y_data, 0.0, x_data);
//hypre_SyncCudaComputeStream(hypre_handle());
#else /* #if defined(HYPRE_USING_CUDA) */
HYPRE_Int i;
#if defined(HYPRE_USING_DEVICE_OPENMP)
#pragma omp target teams distribute parallel for private(i) is_device_ptr(x_data,y_data,A_data,A_i)
#elif defined(HYPRE_USING_OPENMP)
#pragma omp parallel for private(i) HYPRE_SMP_SCHEDULE
#endif
for (i = 0; i < local_size; i++)
{
x_data[i] = y_data[i] / A_data[A_i[i]];
}
#endif /* #if defined(HYPRE_USING_CUDA) */
return ierr;
}
|
GB_unaryop__abs_fp64_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__abs_fp64_int8
// op(A') function: GB_tran__abs_fp64_int8
// C type: double
// A type: int8_t
// cast: double cij = (double) aij
// unaryop: cij = fabs (aij)
#define GB_ATYPE \
int8_t
#define GB_CTYPE \
double
// 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 = fabs (x) ;
// 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_ABS || GxB_NO_FP64 || GxB_NO_INT8)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB_unop__abs_fp64_int8
(
double *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__abs_fp64_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
|
3d7pt_var.c | /*
* 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] = 16;
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;
// 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
#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] = coef[0][i][j][k] * A[t%2][i ][j ][k ] +
coef[1][i][j][k] * A[t%2][i-1][j ][k ] +
coef[2][i][j][k] * A[t%2][i ][j-1][k ] +
coef[3][i][j][k] * A[t%2][i ][j ][k-1] +
coef[4][i][j][k] * A[t%2][i+1][j ][k ] +
coef[5][i][j][k] * A[t%2][i ][j+1][k ] +
coef[6][i][j][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, "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;
}
|
openmp_critical1.c | ///TAFFO_TEST_ARGS -Xvra -propagate-all -fopenmp
#include <stdio.h>
#define MAX_N (100)
int main(int argc, char *argv[])
{
float result __attribute__((annotate("scalar(range(0,100))"))) = 0.0;
int i = 0;
#pragma omp parallel for
for (i = 0; i < MAX_N; i++) {
#pragma omp critical
result += 1.0;
}
printf("result: %f\n", result);
}
|
csc.h | #ifndef __csc_H
#define __csc_H
template<typename I, typename T1,typename T2>
void csc_matvec_noomp_contig(const bool overwrite_y,
const I n_row,
const I n_col,
const I Ap[],
const I Ai[],
const T1 Ax[],
const T1 a,
const T2 x[],
T2 y[])
{
if(overwrite_y){
for(I j = 0; j < n_row; j++){
y[j] = 0;
}
}
for(I j = 0; j < n_col; j++){
I col_start = Ap[j];
I col_end = Ap[j+1];
for(I ii = col_start; ii < col_end; ii++){
const I i = Ai[ii];
y[i] += (a * Ax[ii]) * x[j];
}
}
}
template<typename I, typename T1,typename T2>
void csc_matvec_noomp_strided(const bool overwrite_y,
const I n_row,
const I n_col,
const I Ap[],
const I Ai[],
const T1 Ax[],
const T1 a,
const npy_intp x_stride,
const T2 x[],
const npy_intp y_stride,
T2 y[])
{
if(overwrite_y){
for(I j = 0; j < n_row; j++){
y[j] = 0;
}
}
for(I j = 0; j < n_col; j++){
I col_start = Ap[j];
I col_end = Ap[j+1];
for(I ii = col_start; ii < col_end; ii++){
const I i = Ai[ii];
y[i * y_stride] += (a * Ax[ii]) * x[j * x_stride];
}
}
}
template<typename I, typename T1,typename T2>
void csc_matvecs_noomp_strided(const bool overwrite_y,
const I n_row,
const I n_col,
const npy_intp n_vecs,
const I Ap[],
const I Ai[],
const T1 Ax[],
const T1 a,
const npy_intp x_stride_row,
const npy_intp x_stride_col,
const T2 x[],
const npy_intp y_stride_row,
const npy_intp y_stride_col,
T2 y[])
{
if(overwrite_y){
const npy_intp n = n_vecs * n_row;
for(npy_intp i = 0; i < n; i++){
y[i] = T2(0);
}
}
if(y_stride_col < y_stride_row){
for(I j = 0; j < n_col; j++){
I col_start = Ap[j];
I col_end = Ap[j+1];
for(I ii = col_start; ii < col_end; ii++){
T2 * y_row = y + y_stride_row * Ai[ii];
const T2 ax = (a * Ax[ii]);
axpy_strided(n_vecs, ax, x_stride_col, x, y_stride_col, y_row);
}
x += x_stride_row;
}
}
else{
for(I m=0;m<n_vecs;m++){
const T2 * x_row = x;
for(I j = 0; j < n_col; j++){
I col_start = Ap[j];
I col_end = Ap[j+1];
for(I ii = col_start; ii < col_end; ii++){
y[y_stride_row * Ai[ii]] += (a * Ax[ii]) * (*x_row);
}
x_row += x_stride_row;
}
x += x_stride_col;
y += y_stride_col;
}
}
}
#if defined(_OPENMP)
#include "openmp.h"
template<typename I, typename T1,typename T2>
void csc_matvec_omp_contig(const bool overwrite_y,
const I n_row,
const I n_col,
const I Ap[],
const I Ai[],
const T1 Ax[],
const T1 a,
const T2 x[],
T2 y[])
{
#pragma omp parallel
{
const int nthread = omp_get_num_threads();
const I chunk = std::max((I)1,n_row/(100*nthread));
if(overwrite_y){
#pragma omp for schedule(static)
for(I j = 0; j < n_row; j++){
y[j] = 0;
}
}
#pragma omp for schedule(dynamic,chunk)
for(I j = 0; j < n_col; j++){
I col_start = Ap[j];
I col_end = Ap[j+1];
for(I ii = col_start; ii < col_end; ii++){
const I i = Ai[ii];
const T2 aa = (a * Ax[ii]) * x[j];
atomic_add(y[i],aa);
}
}
}
}
template<typename I, typename T1,typename T2>
void csc_matvec_omp_strided(const bool overwrite_y,
const I n_row,
const I n_col,
const I Ap[],
const I Ai[],
const T1 Ax[],
const T1 a,
const npy_intp x_stride,
const T2 x[],
const npy_intp y_stride,
T2 y[])
{
#pragma omp parallel
{
const int nthread = omp_get_num_threads();
const I chunk = std::max((I)1,n_row/(100*nthread));
if(overwrite_y){
#pragma omp for schedule(static)
for(I j = 0; j < n_row; j++){
y[j * y_stride] = 0;
}
}
#pragma omp for schedule(dynamic,chunk)
for(I j = 0; j < n_col; j++){
I col_start = Ap[j];
I col_end = Ap[j+1];
for(I ii = col_start; ii < col_end; ii++){
const I i = Ai[ii];
const T2 aa = (a * Ax[ii]) * x[j * x_stride];
atomic_add(y[i * y_stride],aa);
}
}
}
}
template<typename I, typename T1,typename T2>
inline void csc_matvecs_omp_strided(const bool overwrite_y,
const I n_row,
const I n_col,
const npy_intp n_vecs,
const I Ap[],
const I Ai[],
const T1 Ax[],
const T1 a,
const npy_intp x_stride_row,
const npy_intp x_stride_col,
const T2 x[],
const npy_intp y_stride_row,
const npy_intp y_stride_col,
T2 y[])
{
csc_matvecs_noomp_strided(overwrite_y,n_row,n_col,n_vecs,Ap,Ai,Ax,a,x_stride_row,x_stride_col,x,y_stride_row,y_stride_col,y);
}
#else
template<typename I, typename T1,typename T2>
void csc_matvec_omp_contig(const bool overwrite_y,
const I n_row,
const I n_col,
const I Ap[],
const I Ai[],
const T1 Ax[],
const T1 a,
const T2 x[],
T2 y[])
{
csc_matvec_noomp_contig(overwrite_y,n_row,n_col,Ap,Ai,Ax,a,x,y);
}
template<typename I, typename T1,typename T2>
inline void csc_matvec_omp_strided(const bool overwrite_y,
const I n_row,
const I n_col,
const I Ap[],
const I Ai[],
const T1 Ax[],
const T1 a,
const npy_intp x_stride,
const T2 x[],
const npy_intp y_stride,
T2 y[])
{
csc_matvec_noomp_strided(overwrite_y,n_row,n_col,Ap,Ai,Ax,a,x_stride,x,y_stride,y);
}
template<typename I, typename T1,typename T2>
inline void csc_matvecs_omp_strided(const bool overwrite_y,
const I n_row,
const I n_col,
const npy_intp n_vecs,
const I Ap[],
const I Ai[],
const T1 Ax[],
const T1 a,
const npy_intp x_stride_row,
const npy_intp x_stride_col,
const T2 x[],
const npy_intp y_stride_row,
const npy_intp y_stride_col,
T2 y[])
{
csc_matvecs_noomp_strided(overwrite_y,n_row,n_col,n_vecs,Ap,Ai,Ax,a,x_stride_row,x_stride_col,x,y_stride_row,y_stride_col,y);
}
#endif
// when openmp is not being used omp and noomp versions are identical
template<typename I, typename T1,typename T2>
void csc_matvec_noomp(const bool overwrite_y,
const I n_row,
const I n_col,
const I Ap[],
const I Aj[],
const T1 Ax[],
const T1 a,
const npy_intp x_stride_byte,
const T2 x[],
const npy_intp y_stride_byte,
T2 y[])
{
const npy_intp y_stride = y_stride_byte/sizeof(T2);
const npy_intp x_stride = x_stride_byte/sizeof(T2);
if(y_stride == 1){
if(x_stride == 1){
csc_matvec_noomp_contig(overwrite_y,n_row,n_col,Ap,Aj,Ax,a,x,y);
}
else{
csc_matvec_noomp_strided(overwrite_y,n_row,n_col,Ap,Aj,Ax,a,x_stride,x,1,y);
}
}
else{
if(x_stride == 1){
csc_matvec_noomp_strided(overwrite_y,n_row,n_col,Ap,Aj,Ax,a,1,x,y_stride,y);
}
else{
csc_matvec_noomp_strided(overwrite_y,n_row,n_col,Ap,Aj,Ax,a,x_stride,x,y_stride,y);
}
}
}
template<typename I, typename T1,typename T2>
void csc_matvec_omp(const bool overwrite_y,
const I n_row,
const I n_col,
const I Ap[],
const I Aj[],
const T1 Ax[],
const T1 a,
const npy_intp x_stride_byte,
const T2 x[],
const npy_intp y_stride_byte,
T2 y[])
{
const npy_intp y_stride = y_stride_byte/sizeof(T2);
const npy_intp x_stride = x_stride_byte/sizeof(T2);
if(y_stride == 1){
if(x_stride == 1){
csc_matvec_omp_contig(overwrite_y,n_row,n_col,Ap,Aj,Ax,a,x,y);
}
else{
csc_matvec_omp_strided(overwrite_y,n_row,n_col,Ap,Aj,Ax,a,x_stride,x,1,y);
}
}
else{
if(x_stride == 1){
csc_matvec_omp_strided(overwrite_y,n_row,n_col,Ap,Aj,Ax,a,1,x,y_stride,y);
}
else{
csc_matvec_omp_strided(overwrite_y,n_row,n_col,Ap,Aj,Ax,a,x_stride,x,y_stride,y);
}
}
}
template<typename I, typename T1,typename T2>
inline void csc_matvecs_noomp(const bool overwrite_y,
const I n_row,
const I n_col,
const npy_intp n_vecs,
const I Ap[],
const I Aj[],
const T1 Ax[],
const T1 a,
const npy_intp x_stride_row_byte,
const npy_intp x_stride_col_byte,
const T2 x[],
const npy_intp y_stride_row_byte,
const npy_intp y_stride_col_byte,
T2 y[])
{
const npy_intp y_stride_row = y_stride_row_byte/sizeof(T2);
const npy_intp y_stride_col = y_stride_col_byte/sizeof(T2);
const npy_intp x_stride_row = x_stride_row_byte/sizeof(T2);
const npy_intp x_stride_col = x_stride_col_byte/sizeof(T2);
if(y_stride_col==1){
if(x_stride_col==1){
csc_matvecs_noomp_strided(overwrite_y,n_row,n_col,n_vecs,Ap,Aj,Ax,a,x_stride_row,1,x,y_stride_row,1,y);
}
else if(x_stride_row==1){
csc_matvecs_noomp_strided(overwrite_y,n_row,n_col,n_vecs,Ap,Aj,Ax,a,1,x_stride_col,x,y_stride_row,1,y);
}
else{
csc_matvecs_noomp_strided(overwrite_y,n_row,n_col,n_vecs,Ap,Aj,Ax,a,x_stride_row,x_stride_col,x,y_stride_row,1,y);
}
}
else if(y_stride_row==1){
if(x_stride_col==1){
csc_matvecs_noomp_strided(overwrite_y,n_row,n_col,n_vecs,Ap,Aj,Ax,a,x_stride_row,1,x,y_stride_row,1,y);
}
else if(x_stride_row==1){
csc_matvecs_noomp_strided(overwrite_y,n_row,n_col,n_vecs,Ap,Aj,Ax,a,1,x_stride_col,x,y_stride_row,1,y);
}
else{
csc_matvecs_noomp_strided(overwrite_y,n_row,n_col,n_vecs,Ap,Aj,Ax,a,x_stride_row,x_stride_col,x,1,y_stride_col,y);
}
}
else{
csc_matvecs_noomp_strided(overwrite_y,n_row,n_col,n_vecs,Ap,Aj,Ax,a,x_stride_row,x_stride_col,x,y_stride_row,y_stride_col,y);
}
}
template<typename I, typename T1,typename T2>
inline void csc_matvecs_omp(const bool overwrite_y,
const I n_row,
const I n_col,
const npy_intp n_vecs,
const I Ap[],
const I Aj[],
const T1 Ax[],
const T1 a,
const npy_intp x_stride_row_byte,
const npy_intp x_stride_col_byte,
const T2 x[],
const npy_intp y_stride_row_byte,
const npy_intp y_stride_col_byte,
T2 y[])
{
const npy_intp y_stride_row = y_stride_row_byte/sizeof(T2);
const npy_intp y_stride_col = y_stride_col_byte/sizeof(T2);
const npy_intp x_stride_row = x_stride_row_byte/sizeof(T2);
const npy_intp x_stride_col = x_stride_col_byte/sizeof(T2);
if(y_stride_col==1){
if(x_stride_col==1){
csc_matvecs_omp_strided(overwrite_y,n_row,n_col,n_vecs,Ap,Aj,Ax,a,x_stride_row,1,x,y_stride_row,1,y);
}
else if(x_stride_row==1){
csc_matvecs_omp_strided(overwrite_y,n_row,n_col,n_vecs,Ap,Aj,Ax,a,1,x_stride_col,x,y_stride_row,1,y);
}
else{
csc_matvecs_omp_strided(overwrite_y,n_row,n_col,n_vecs,Ap,Aj,Ax,a,x_stride_row,x_stride_col,x,y_stride_row,1,y);
}
}
else if(y_stride_row==1){
if(x_stride_col==1){
csc_matvecs_omp_strided(overwrite_y,n_row,n_col,n_vecs,Ap,Aj,Ax,a,x_stride_row,1,x,1,y_stride_col,y);
}
else if(x_stride_row==1){
csc_matvecs_omp_strided(overwrite_y,n_row,n_col,n_vecs,Ap,Aj,Ax,a,1,x_stride_col,x,1,y_stride_col,y);
}
else{
csc_matvecs_omp_strided(overwrite_y,n_row,n_col,n_vecs,Ap,Aj,Ax,a,x_stride_row,x_stride_col,x,1,y_stride_col,y);
}
}
else{
csc_matvecs_omp_strided(overwrite_y,n_row,n_col,n_vecs,Ap,Aj,Ax,a,x_stride_row,x_stride_col,x,y_stride_row,y_stride_col,y);
}
}
#endif |
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] = 24;
tile_size[1] = 24;
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;
// 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-2,12);t1++) {
lbp=max(ceild(t1,2),ceild(24*t1-Nt+3,24));
ubp=min(floord(Nt+Nz-4,24),floord(12*t1+Nz+9,24));
#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(3*t1-3,4)),ceild(24*t2-Nz-12,16));t3<=min(min(min(floord(Nt+Ny-4,16),floord(12*t1+Ny+21,16)),floord(24*t2+Ny+20,16)),floord(24*t1-24*t2+Nz+Ny+19,16));t3++) {
for (t4=max(max(max(0,ceild(3*t1-31,32)),ceild(24*t2-Nz-124,128)),ceild(16*t3-Ny-124,128));t4<=min(min(min(min(floord(Nt+Nx-4,128),floord(12*t1+Nx+21,128)),floord(24*t2+Nx+20,128)),floord(16*t3+Nx+12,128)),floord(24*t1-24*t2+Nz+Nx+19,128));t4++) {
for (t5=max(max(max(max(max(0,12*t1),24*t1-24*t2+1),24*t2-Nz+2),16*t3-Ny+2),128*t4-Nx+2);t5<=min(min(min(min(min(Nt-2,12*t1+23),24*t2+22),16*t3+14),128*t4+126),24*t1-24*t2+Nz+21);t5++) {
for (t6=max(max(24*t2,t5+1),-24*t1+24*t2+2*t5-23);t6<=min(min(24*t2+23,-24*t1+24*t2+2*t5),t5+Nz-2);t6++) {
for (t7=max(16*t3,t5+1);t7<=min(16*t3+15,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;
}
|
GB_unop__abs_uint32_uint32.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__abs_uint32_uint32)
// op(A') function: GB (_unop_tran__abs_uint32_uint32)
// C type: uint32_t
// A type: uint32_t
// cast: uint32_t cij = aij
// unaryop: cij = aij
#define GB_ATYPE \
uint32_t
#define GB_CTYPE \
uint32_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
uint32_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = x ;
// casting
#define GB_CAST(z, aij) \
uint32_t z = aij ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
uint32_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
uint32_t z = aij ; \
Cx [pC] = z ; \
}
// true if operator is the identity op with no typecasting
#define GB_OP_IS_IDENTITY_WITH_NO_TYPECAST \
0
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_ABS || GxB_NO_UINT32)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_apply__abs_uint32_uint32)
(
uint32_t *Cx, // Cx and Ax may be aliased
const uint32_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 (uint32_t), nthreads) ;
#else
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
uint32_t aij = Ax [p] ;
uint32_t z = aij ;
Cx [p] = z ;
}
#endif
}
else
{
// bitmap case, no transpose; A->b already memcpy'd into C->b
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!Ab [p]) continue ;
uint32_t aij = Ax [p] ;
uint32_t z = aij ;
Cx [p] = z ;
}
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_tran__abs_uint32_uint32)
(
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
|
singleModificado2.c | /*
$ gcc -fopenmp -O2 src/single.c -o bin/single
$ ./bin/single
Introduce valor de inicialización a: 1
Single ejecutada por el thread 0
Depués de la región parallel:
b[0] = 1 b[1] = 1 b[2] = 1 b[3] = 1 b[4] = 1 b[5] = 1 b[6] = 1 b[7] = 1 b[8] = 1
*/
#include <stdio.h>
#include <omp.h>
main() {
int n = 9, i, a, b[n];
for (i=0; i<n; i++)
b[i] = -1;
#pragma omp parallel
{
#pragma omp master
{
printf("Introduce valor de inicialización a: ");
scanf("%d", &a );
printf("Single ejecutada por el thread %d\n", omp_get_thread_num());
}
#pragma omp barrier
#pragma omp for
for (i=0; i<n; i++){
b[i] = a;
printf("b[%d] = %d\t", i, a);
}
}
printf("\n");
} |
RNACI.h | /* This Source Code Form is subject to the terms of the BSD 2-Clause
* License. If a copy of the this license was not distributed with this
* file, you can obtain one from http://opensource.org/licenses/BSD-2-Clause. */
// Copyright 2014-2015, Schmidt
#ifndef __RNACI_H__
#define __RNACI_H__
#define RNACI_VERSION 0.2.0
#include <R.h>
#include <Rinternals.h>
#include <stdarg.h>
#include <string.h>
#include <stdbool.h>
#include <math.h>
#include <float.h>
#define RNACIMAX(m,n) m<n?n:m
#define RNULL R_NilValue
// Voodoo Args
#define OPTIONALARG1(a,b,...) (a),(b)
// R data accessors
#define __RNACI_INT(x,y,...) INTEGER(x)[y]
#define INT(x,...) __RNACI_INT(x,##__VA_ARGS__,0)
#define __RNACI_DBL(x,y,...) REAL(x)[y]
#define DBL(x,...) __RNACI_DBL(x,##__VA_ARGS__,0)
#define __RNACI_STR(x,y,...) ((char*)CHAR(STRING_ELT(x,y)))
#define STR(x,...) __RNACI_STR(x,##__VA_ARGS__,0)
#define MatINT(x,i,j) (INTEGER(x)[i+nrows(x)*j])
#define MatDBL(x,i,j) (REAL(x)[i+nrows(x)*j])
#define INTP(x) (INTEGER(x))
#define DBLP(x) (REAL(x))
#define newRptr(ptr,Rptr,fin) PROTECT(Rptr = R_MakeExternalPtr(ptr, R_NilValue, R_NilValue));R_RegisterCFinalizerEx(Rptr, fin, TRUE)
#define getRptr(ptr) R_ExternalPtrAddr(ptr);
#define newRfreeptrfun(FNAME,TYPE,FREEFUN) \
static void FNAME(SEXP ptr) \
{ \
if (NULL == R_ExternalPtrAddr(ptr)) return; \
TYPE *tmp = (TYPE *) R_ExternalPtrAddr(ptr); \
FREEFUN(tmp); \
R_ClearExternalPtr(ptr); \
}
// GC stuff
#define R_INIT int __RNACI_SEXP_protect_counter=0
#define PT(x) PROTECT((x)); (__RNACI_SEXP_protect_counter)++
#define R_END (UNPROTECT(__RNACI_SEXP_protect_counter))
// Allocations
#define newRlist(x,n) PT(x=__Rvecalloc(n, "vec", false))
//#define newRvec(x,n,type) PT(x=__Rvecalloc(n, type))
#define newRvec(x,n,...) PT(x=__Rvecalloc(n,OPTIONALARG1(__VA_ARGS__,false)))
//#define newRmat(x,m,n,type) PT(x=__Rmatalloc(m,n,type))
#define newRmat(x,m,n,...) PT(x=__Rmatalloc(m,n,OPTIONALARG1(__VA_ARGS__,false)))
/* Misc stuff */
#define nonzero(x) (x?x:1)
#define is_null(x) (x==NULL)
#if __STDC_VERSION__ >= 199901L
#define dbstart printf("DEBUGGING in %s Started\n", __func__);int __RNACI_debug_printing_counter=0
#define dbstop printf("DEBUGGING in %s Ended\n", __func__)
#else
#define dbstart int __RNACI_debug_printing_counter=0
#endif
#define dbshow printf("%d\n", __RNACI_debug_printing_counter);__RNACI_debug_printing_counter++;
/***************************************************
* Definitions *
***************************************************/
// alloc.c
static inline SEXP __Rvecalloc(int n, char *type, int init)
{
SEXP RET;
int i;
if (strcmp(type, "vec") == 0)
PROTECT(RET = allocVector(VECSXP, n));
else if (strcmp(type, "int") == 0)
{
PROTECT(RET = allocVector(INTSXP, n));
if (init)
{
#if defined( _OPENMP_SUPPORT_SIMD)
#pragma omp for simd
#endif
for (i=0; i<n; i++)
INT(RET, i) = 0;
}
}
else if (strcmp(type, "double") == 0 || strcmp(type, "dbl") == 0)
{
PROTECT(RET = allocVector(REALSXP, n));
if (init)
{
#if defined( _OPENMP_SUPPORT_SIMD)
#pragma omp for simd
#endif
for (i=0; i<n; i++)
DBL(RET, i) = 0.0;
}
}
else if (strcmp(type, "str") == 0 || strcmp(type, "char*") == 0)
PROTECT(RET = allocVector(STRSXP, n));
else
return NULL;
UNPROTECT(1);
return RET;
}
static inline SEXP __Rmatalloc(int m, int n, char *type, int init)
{
SEXP RET;
int i, j;
if (strcmp(type, "vec") == 0)
PROTECT(RET = allocMatrix(VECSXP, m, n));
else if (strcmp(type, "int") == 0)
{
PROTECT(RET = allocMatrix(INTSXP, m, n));
if (init)
{
for (j=0; j<n; j++)
{
#if defined( _OPENMP_SUPPORT_SIMD)
#pragma omp for simd
#endif
for (i=0; i<m; i++)
MatINT(RET, i, j) = 0;
}
}
}
else if (strcmp(type, "double") == 0 || strcmp(type, "dbl") == 0)
{
PROTECT(RET = allocMatrix(REALSXP, m, n));
if (init)
{
for (j=0; j<n; j++)
{
#if defined( _OPENMP_SUPPORT_SIMD)
#pragma omp for simd
#endif
for (i=0; i<m; i++)
MatDBL(RET, i, j) = 0.0;
}
}
}
else if (strcmp(type, "str") == 0 || strcmp(type, "char*") == 0)
PROTECT(RET = allocMatrix(STRSXP, m, n));
else
return NULL;
UNPROTECT(1);
return RET;
}
// floats.c
static inline int fis_zerof(float x)
{
const float abs_epsf = 1.1f * FLT_EPSILON;
if (fabsf(x) < abs_epsf*FLT_MIN)
return true;
else
return false;
}
static inline int fis_zero(double x)
{
const double abs_eps = 1.1 * DBL_EPSILON;
if (fabs(x) < abs_eps*DBL_MIN)
return true;
else
return false;
}
static inline int fequalsf(float x, float y)
{
const float abs_epsf = 1.1f * FLT_EPSILON;
const double abs_eps = 1.1 * DBL_EPSILON;
const double diff = fabsf(x - y);
if (x == y)
return true;
else if (x == 0.0f || y == 0.0f || diff < FLT_MIN)
return diff < (abs_epsf*FLT_MIN);
else
return diff/(fabsf(x) + fabsf(y)) < abs_epsf;
}
static inline int fequals(double x, double y)
{
const float abs_epsf = 1.1f * FLT_EPSILON;
const double abs_eps = 1.1 * DBL_EPSILON;
const double diff = fabs(x - y);
if (x == y)
return true;
else if (x == 0.0 || y == 0.0 || diff < DBL_MIN)
return diff < (abs_eps*DBL_MIN);
else
return diff/(fabs(x) + fabs(y)) < abs_eps;
}
// misc.c
static inline int is_Rnull(SEXP x)
{
R_INIT;
SEXP basePackage;
SEXP tmp;
PT( basePackage = eval( lang2( install("getNamespace"), ScalarString(mkChar("base")) ), R_GlobalEnv ) );
tmp = eval( lang2( install("is.null"), x), basePackage);
R_END;
return INT(tmp,0);
}
static inline int is_Rnan(SEXP x)
{
R_INIT;
SEXP basePackage;
SEXP tmp;
PT( basePackage = eval( lang2( install("getNamespace"), ScalarString(mkChar("base")) ), R_GlobalEnv ) );
tmp = eval( lang2( install("is.nan"), x), basePackage);
R_END;
return INT(tmp,0);
}
static inline int is_Rna(SEXP x)
{
R_INIT;
SEXP basePackage;
SEXP tmp;
PT( basePackage = eval( lang2( install("getNamespace"), ScalarString(mkChar("base")) ), R_GlobalEnv ) );
tmp = eval( lang2( install("is.na"), x), basePackage);
R_END;
return INT(tmp,0);
}
static inline int is_double(SEXP x)
{
R_INIT;
SEXP basePackage;
SEXP tmp;
PT( basePackage = eval( lang2( install("getNamespace"), ScalarString(mkChar("base")) ), R_GlobalEnv ) );
tmp = eval( lang2( install("is.double"), x), basePackage);
R_END;
return INT(tmp,0);
}
static inline int is_integer(SEXP x)
{
R_INIT;
SEXP basePackage;
SEXP tmp;
PT( basePackage = eval( lang2( install("getNamespace"), ScalarString(mkChar("base")) ), R_GlobalEnv ) );
tmp = eval( lang2( install("is.integer"), x), basePackage);
R_END;
return INT(tmp,0);
}
// printing.c
static inline void PRINT(SEXP x)
{
R_INIT;
SEXP basePackage;
PT( basePackage = eval( lang2( install("getNamespace"), ScalarString(mkChar("base")) ), R_GlobalEnv ) );
eval( lang2( install("print"), x), basePackage);
R_END;
}
// structures_misc.c
static inline void set_list_names(SEXP R_list, SEXP R_names)
{
setAttrib(R_list, R_NamesSymbol, R_names);
}
static inline void set_df_rownames(SEXP R_df, SEXP R_rownames)
{
setAttrib(R_df, R_RowNamesSymbol, R_rownames);
}
static inline void set_df_colnames(SEXP R_df, SEXP R_colnames)
{
set_list_names(R_df, R_colnames);
}
static inline void set_list_as_df(SEXP R_list)
{
setAttrib(R_list, R_ClassSymbol, mkString("data.frame"));
}
// structures_dataframes.c
static inline SEXP make_dataframe_default_colnames(const int n)
{
R_INIT;
int i;
int buflen;
SEXP ret;
buflen = (int) (ceil(log10((double)n)) + 1.);
char *buf = malloc(buflen * sizeof(*buf));
buf[0] = 'X';
newRlist(ret, n);
for (i=0; i<n; i++)
{
sprintf(buf+1, "%d", i+1);
buflen = (int) (ceil(log10((double)i+2)) + 1.);
buflen = RNACIMAX(buflen, 2);
SET_VECTOR_ELT(ret, i, mkCharLen(buf, buflen));
}
free(buf);
R_END;
return ret;
}
static inline SEXP make_dataframe_default_rownames(int n)
{
R_INIT;
int i;
SEXP ret_names;
newRvec(ret_names, n, "int");
for(i=0; i<n; i++)
INT(ret_names,i) = i + 1;
R_END;
return ret_names;
}
static inline SEXP make_dataframe(SEXP R_rownames, SEXP R_colnames, int n, ...)
{
R_INIT;
int i;
SEXP R_df;
SEXP R_default_rownames;
SEXP R_default_colnames;
SEXP tmp;
va_list listPointer;
// Construct list
newRlist(R_df, n);
va_start(listPointer, n);
for(i=0; i<n; i++)
{
tmp = va_arg(listPointer, SEXP);
SET_VECTOR_ELT(R_df, i, tmp);
}
va_end(listPointer);
// Set names
set_list_as_df(R_df);
if (is_Rnull(R_rownames))
{
R_default_rownames = make_dataframe_default_rownames(n);
set_df_rownames(R_df, R_default_rownames);
}
else
set_df_rownames(R_df, R_rownames);
if (is_Rnull(R_colnames))
{
R_default_colnames = make_dataframe_default_colnames(n);
set_df_colnames(R_df, R_default_colnames);
}
else
set_df_colnames(R_df, R_colnames);
R_END;
return R_df;
}
// structures_lists.c
static inline SEXP make_list_names(int n, ...)
{
R_INIT;
int i;
char *tmp;
SEXP R_list_names;
va_list listPointer;
newRvec(R_list_names, n, "str");
va_start(listPointer, n);
for(i=0; i<n; i++)
{
tmp = va_arg(listPointer, char *);
SET_STRING_ELT(R_list_names, i, mkChar(tmp));
}
va_end(listPointer);
R_END;
return R_list_names;
}
static inline SEXP make_list(SEXP R_list_names, const int n, ...)
{
R_INIT;
int i;
/* const int n = LENGTH(R_list_names);*/
SEXP tmp, R_list;
va_list listPointer;
newRlist(R_list, n);
va_start(listPointer, n);
for(i=0; i<n; i++)
{
tmp = va_arg(listPointer, SEXP);
SET_VECTOR_ELT(R_list, i, tmp);
}
va_end(listPointer);
/* setAttrib(R_list, R_NamesSymbol, R_list_names);*/
if (!is_Rnull(R_list_names))
set_list_names(R_list, R_list_names);
R_END;
return R_list;
}
#endif
|
PixelBasedRenderFunc.h | #include"..\Core\SanTypes.h"
#include"SanGraphics.h"
namespace San
{
namespace Graphics
{
#ifndef __SANPIXELBASEDRENDERFUNC_H__
#define __SANPIXELBASEDRENDERFUNC_H__
struct PIXCAMERA
{
SVECTOR3 Coord;
SVECTOR3 LookAt;
SVECTOR3 Dir;
SVECTOR3 UpDir;
sfloat Cutoff;
sfloat Near;
sfloat Far;
SVECTOR3 ScreenVec[4];
};
void ClearScreenRGBA(sfloat* p_buffer, const uint32 width, const uint32 height, const SANCOLORF &Color);
void DrawImageRGBA(sfloat* p_buffer, const uint32 buf_width, const uint32 buf_height, sfloat* p_img, const uint32 img_width, const uint32 img_height, const SVECTOR3 &pos, bool bUseAlpha = false);
void DrawImageRGB(sfloat* p_buffer, const uint32 buf_width, const uint32 buf_height, sfloat* p_img, const uint32 img_width, const uint32 img_height, const SVECTOR3 &pos);
void DrawImageGray(sfloat* p_buffer, const uint32 buf_width, const uint32 buf_height, sfloat* p_img, const uint32 img_width, const uint32 img_height, const SVECTOR3 &pos);
void DrawCrossRGBA(sfloat* p_buffer, const uint32 width, uint32 height, const SVECTOR3 pos, const SANCOLORF color, const uint32 size,const uint32 thickness);
void DrawDotRGBA(sfloat* p_buffer, const uint32 width, uint32 height, const SVECTOR3 pos, const SANCOLORF color, sfloat radius);
void DrawRectangleRGBA(sfloat* p_buffer, const uint32 buf_width, const uint32 buf_height, const uint32 quadr_width, const uint32 quadr_height, const SANCOLORF color, const SVECTOR3 &pos);
void DrawQuadrRGBA(sfloat* p_buffer, const uint32 buf_width, const uint32 buf_height, const uint32 quadr_width, const uint32 quadr_height, const SANCOLORF color, const SVECTOR3 &pos, const uint32 size);
void DrawLineRGBA(sfloat* p_buffer, const uint32 buf_width, const uint32 buf_height, const SVECTOR3 pos_begin, const SVECTOR3 pos_end, const SANCOLORF color, const uint32 size);
void UpdateCamera(PIXCAMERA &Camera, uint32 ScreenWidth, uint32 ScreenHeight);
SVECTOR3 GetScreenCoord(const SVECTOR3 Coord, const PIXCAMERA Camera, uint32 ScreenWidth, uint32 ScreenHeight);
sfloat GetHitPoint(const SVECTOR3* pRayCoord, const SVECTOR3* pRayDir, const SVECTOR3* pVec1, const SVECTOR3* pVec2, const SVECTOR3* pVec3, const SVECTOR3* pNormal, SVECTOR3* pHitPoint);
SVECTOR3 Interpolation(const SVECTOR3* pVecSrc, const SVECTOR3* pVec1, const SVECTOR3* pVec2, const SVECTOR3* pVec3);
void DrawDot3DRGBA(sfloat* p_buffer, const uint32 width, uint32 height, const SVECTOR3 pos, const SANCOLORF color, sfloat radius, const PIXCAMERA camera, const SVECTOR3 offset = SVECTOR3(0.0, 0.0, 0.0));
void DrawLine3DRGBA(sfloat* p_buffer, const uint32 buf_width, const uint32 buf_height, const SVECTOR3 coord_begin, const SVECTOR3 coord_end, const SANCOLORF color, const uint32 size, const PIXCAMERA camera, const SVECTOR3 offset = SVECTOR3(0.0, 0.0, 0.0));
void DrawLineGraph(sfloat* p_buffer, const uint32 buf_width, const uint32 buf_height, const uint32 dest_width, const uint32 dest_height, sfloat* p_dataset, uint32 data_size, const SVECTOR3 pos, const SANCOLORF color, const uint32 size);
template<class DType, class SType> void BufferCopy(DType* pDest, SType* pSrc, uint32 BufferSize, sfloat min = 0.0f, sfloat max = 255.0f)
{
#pragma omp parallel for
for (int32 seek = 0; seek < BufferSize; seek = seek + 1)
{
pDest[seek] = pSrc[seek]<min ? min : (pSrc[seek]>max ? max : pSrc[seek]);
}
}
#endif
}
} |
util.h | #pragma once
#include "datatypes.h"
#include "timing.h"
class Util {
public:
static void updatePerLocationAgentLists(const thrust::device_vector<unsigned>& locationOfAgents,
thrust::device_vector<unsigned>& locationIdsOfAgents,
thrust::device_vector<unsigned>& locationAgentList,
thrust::device_vector<unsigned>& locationListOffsets);
};
#if THRUST_DEVICE_SYSTEM == THRUST_DEVICE_SYSTEM_CUDA
template<typename UnaryFunction, typename Count_t, typename PPState_t>
__global__ void reduce_by_location_kernel(unsigned* locationListOffsetsPtr,
unsigned* locationAgentListPtr,
Count_t* fullInfectedCountsPtr,
PPState_t* PPValuesPtr,
unsigned numLocations,
UnaryFunction lam) {
unsigned l = threadIdx.x + blockIdx.x * blockDim.x;
if (l < numLocations) {
for (unsigned agent = locationListOffsetsPtr[l]; agent < locationListOffsetsPtr[l + 1]; agent++) {
fullInfectedCountsPtr[l] += lam(PPValuesPtr[locationAgentListPtr[agent]]);
}
}
}
template<typename UnaryFunction, typename Count_t, typename PPState_t>
__global__ void reduce_by_location_kernel_atomics(const unsigned* agentLocationsPtr,
Count_t* fullInfectedCountsPtr,
PPState_t* PPValuesPtr,
unsigned numAgents,
UnaryFunction lam) {
unsigned agent = threadIdx.x + blockIdx.x * blockDim.x;
if (agent < numAgents) { atomicAdd(&fullInfectedCountsPtr[agentLocationsPtr[agent]], lam(PPValuesPtr[agent])); }
}
#endif
template<typename UnaryFunction, typename Count_t, typename PPState_t>
void reduce_by_location(thrust::device_vector<unsigned>& locationListOffsets,
thrust::device_vector<unsigned>& locationAgentList,
thrust::device_vector<Count_t>& fullInfectedCounts,
thrust::device_vector<PPState_t>& PPValues,
const thrust::device_vector<unsigned>& agentLocations,
UnaryFunction lam) {
unsigned numLocations = locationListOffsets.size() - 1;
unsigned* locationListOffsetsPtr = thrust::raw_pointer_cast(locationListOffsets.data());
Count_t* fullInfectedCountsPtr = thrust::raw_pointer_cast(fullInfectedCounts.data());
PPState_t* PPValuesPtr = thrust::raw_pointer_cast(PPValues.data());
const unsigned* agentLocationsPtr = thrust::raw_pointer_cast(agentLocations.data());
unsigned* locationAgentListPtr = thrust::raw_pointer_cast(locationAgentList.data());
unsigned numAgents = PPValues.size();
// PROFILE_FUNCTION();
if (numLocations == 1) {
fullInfectedCounts[0] = thrust::reduce(thrust::make_transform_iterator(PPValues.begin(), lam),
thrust::make_transform_iterator(PPValues.end(), lam),
(Count_t)0.0f);
} else {
#if THRUST_DEVICE_SYSTEM == THRUST_DEVICE_SYSTEM_OMP
#pragma omp parallel for
for (unsigned l = 0; l < numLocations; l++) {
for (unsigned agent = locationListOffsetsPtr[l]; agent < locationListOffsetsPtr[l + 1]; agent++) {
fullInfectedCountsPtr[l] += lam(PPValuesPtr[locationAgentListPtr[agent]]);
}
}
#elif THRUST_DEVICE_SYSTEM == THRUST_DEVICE_SYSTEM_CUDA
#define ATOMICS
#ifdef ATOMICS
reduce_by_location_kernel_atomics<<<(numAgents - 1) / 256 + 1, 256>>>(
agentLocationsPtr, fullInfectedCountsPtr, PPValuesPtr, numAgents, lam);
#else
#error \
"util.cpp's locationListOffsets computation CUDA pathway relies on atomics version, as this one needs locationListOffsets to already exist"
reduce_by_location_kernel<<<(numLocations - 1) / 256 + 1, 256>>>(
locationListOffsetsPtr, locationAgentListPtr, fullInfectedCountsPtr, PPValuesPtr, numLocations, lam);
#endif
cudaDeviceSynchronize();
#endif
}
} |
core_zlacpy_band.c | /**
*
* @file
*
* PLASMA is a software package provided by:
* University of Tennessee, US,
* University of Manchester, UK.
*
* @precisions normal z -> c d s
*
**/
#include "core_blas.h"
#include "plasma_types.h"
#include "plasma_internal.h"
#include "core_lapack.h"
/*******************************************************************************
*
* @ingroup core_plasma_complex64_t
*
* core_zlacpy copies a sub-block A of a band matrix stored in LAPACK's band format
* to a corresponding sub-block B of a band matrix in PLASMA's band format
*
*******************************************************************************
*
* @param[in] it
* The row block index of the tile.
*
* @param[in] jt
* The column block index of the tile.
*
* @param[in] m
* The number of rows of the matrices A and B. M >= 0.
*
* @param[in] n
* The number of columns of the matrices A and B. N >= 0.
*
* @param[in] A
* The M-by-N matrix to copy.
*
* @param[in] lda
* The leading dimension of the array A. lda >= max(1,M).
*
* @param[out] B
* The M-by-N copy of the matrix A.
* On exit, B = A ONLY in the locations specified by uplo.
*
* @param[in] ldb
* The leading dimension of the array B. ldb >= max(1,M).
*
******************************************************************************/
void core_zlacpy_lapack2tile_band(plasma_enum_t uplo,
int it, int jt,
int m, int n, int nb, int kl, int ku,
const plasma_complex64_t *A, int lda,
plasma_complex64_t *B, int ldb)
{
int i, j;
int j_start, j_end;
if (uplo == PlasmaGeneral) {
j_start = 0; // pivot back and could fill in
j_end = (jt <= it ? n : imin(n, (it-jt)*nb+m+ku+kl+1));
}
else if (uplo == PlasmaUpper) {
j_start = 0;
j_end = imin(n, (it-jt)*nb+m+ku+1);
}
else {
j_start = imax(0, (it-jt)*nb-kl);
j_end = n;
}
for (j = 0; j < j_start; j++) {
for (i = 0; i < m; i++) {
B[i + j*ldb] = 0.0;
}
}
for (j = j_start; j < j_end; j++) {
int i_start, i_end;
if (uplo == PlasmaGeneral) {
i_start = (jt <= it ? 0 : imax(0, (jt-it)*nb+j-ku-kl));
i_end = (jt >= it ? m : imin(m, (jt-it)*nb+j+kl+nb+1));
// +nb because we use zgetrf on panel and pivot back within the panel.
// so the last tile in panel could fill.
}
else if (uplo == PlasmaUpper) {
i_start = imax(0, (jt-it)*nb+j-ku);
i_end = imin(m, (jt-it)*nb+j+1);
}
else {
i_start = imax(0, (jt-it)*nb+j);
i_end = imin(m, (jt-it)*nb+j+kl+1);
}
for (i = 0; i < i_start; i++) {
B[i + j*ldb] = 0.0;
}
for (i = i_start; i < i_end; i++) {
B[i + j*ldb] = A[i + j*lda];
}
for (i = i_end; i < m; i++) {
B[i + j*ldb] = 0.0;
}
}
for (j = j_end; j < n; j++) {
for (i = 0; i < m; i++) {
B[i + j*ldb] = 0.0;
}
}
}
/******************************************************************************/
void core_omp_zlacpy_lapack2tile_band(plasma_enum_t uplo,
int it, int jt,
int m, int n, int nb, int kl, int ku,
const plasma_complex64_t *A, int lda,
plasma_complex64_t *B, int ldb)
{
#pragma omp task depend(in:A[0:lda*n]) \
depend(out:B[0:ldb*n])
core_zlacpy_lapack2tile_band(uplo,
it, jt, m, n, nb, kl, ku,
A, lda,
B, ldb);
}
/*******************************************************************************
*
* @ingroup core_plasma_complex64_t
*
* core_zlacpy copies all or part of a two-dimensional matrix A to another
* matrix B
*
*******************************************************************************
*
* @param[in] it
* The row block index of the tile.
*
* @param[in] jt
* The column block index of the tile.
*
* @param[in] m
* The number of rows of the matrices A and B. m >= 0.
*
* @param[in] n
* The number of columns of the matrices A and B. n >= 0.
*
* @param[in] A
* The m-by-n matrix to copy.
*
* @param[in] lda
* The leading dimension of the array A. lda >= max(1, m).
*
* @param[out] B
* The m-by-n copy of the matrix A.
* On exit, B = A ONLY in the locations specified by uplo.
*
* @param[in] ldb
* The leading dimension of the array B. ldb >= max(1, m).
*
******************************************************************************/
void core_zlacpy_tile2lapack_band(plasma_enum_t uplo,
int it, int jt,
int m, int n, int nb, int kl, int ku,
const plasma_complex64_t *B, int ldb,
plasma_complex64_t *A, int lda)
{
int i, j;
int j_start, j_end;
if (uplo == PlasmaGeneral) {
j_start = 0; // pivot back and could fill in
j_end = (jt <= it ? n : imin(n, (it-jt)*nb+m+ku+kl+1));
}
else if (uplo == PlasmaUpper) {
j_start = 0;
j_end = imin(n, (it-jt)*nb+m+ku+1);
}
else {
j_start = imax(0, (it-jt)*nb-kl);
j_end = n;
}
for (j = j_start; j < j_end; j++) {
int i_start, i_end;
if (uplo == PlasmaGeneral) {
i_start = (jt <= it ? 0 : imax(0, (jt-it)*nb+j-ku-kl));
i_end = (jt >= it ? m : imin(m, (jt-it)*nb+j+kl+nb+1));
// +nb because we use zgetrf on panel and pivot back within the panel.
// so the last tile in panel could fill.
}
else if (uplo == PlasmaUpper) {
i_start = imax(0, (jt-it)*nb+j-ku);
i_end = imin(m, (jt-it)*nb+j+1);
}
else {
i_start = imax(0, (jt-it)*nb+j);
i_end = imin(m, (jt-it)*nb+j+kl+1);
}
for (i = i_start; i < i_end; i++) {
A[i + j*lda] = B[i + j*ldb];
}
}
}
/******************************************************************************/
void core_omp_zlacpy_tile2lapack_band(plasma_enum_t uplo,
int it, int jt,
int m, int n, int nb, int kl, int ku,
const plasma_complex64_t *B, int ldb,
plasma_complex64_t *A, int lda)
{
#pragma omp task depend(in:B[0:ldb*n]) \
depend(out:A[0:lda*n])
core_zlacpy_tile2lapack_band(uplo,
it, jt, m, n, nb, kl, ku,
B, ldb,
A, lda);
}
|
GB_unop__identity_bool_bool.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary 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_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__(none))
// op(A') function: GB (_unop_tran__identity_bool_bool)
// C type: bool
// A type: bool
// cast: bool cij = aij
// unaryop: cij = aij
#define GB_ATYPE \
bool
#define GB_CTYPE \
bool
// 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) \
bool z = aij ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
bool aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
bool z = aij ; \
Cx [pC] = z ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_IDENTITY || GxB_NO_BOOL)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
#if 0
GrB_Info GB (_unop_apply__(none))
(
bool *Cx, // Cx and Ax may be aliased
const bool *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++)
{
bool aij = Ax [p] ;
bool z = aij ;
Cx [p] = z ;
}
}
else
{
// bitmap case, no transpose; A->b already memcpy'd into C->b
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!Ab [p]) continue ;
bool aij = Ax [p] ;
bool z = aij ;
Cx [p] = z ;
}
}
return (GrB_SUCCESS) ;
#endif
}
#endif
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_tran__identity_bool_bool)
(
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
|
GB_unop__lnot_int8_int8.c | //------------------------------------------------------------------------------
// GB_unop: hard-coded functions for each built-in unary 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_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__lnot_int8_int8)
// op(A') function: GB (_unop_tran__lnot_int8_int8)
// C type: int8_t
// A type: int8_t
// cast: int8_t cij = aij
// unaryop: cij = !(aij != 0)
#define GB_ATYPE \
int8_t
#define GB_CTYPE \
int8_t
// aij = Ax [pA]
#define GB_GETA(aij,Ax,pA) \
int8_t aij = Ax [pA]
#define GB_CX(p) Cx [p]
// unary operator
#define GB_OP(z, x) \
z = !(x != 0) ;
// casting
#define GB_CAST(z, aij) \
int8_t z = aij ;
// cij = op (aij)
#define GB_CAST_OP(pC,pA) \
{ \
/* aij = Ax [pA] */ \
int8_t aij = Ax [pA] ; \
/* Cx [pC] = op (cast (aij)) */ \
int8_t z = aij ; \
Cx [pC] = !(z != 0) ; \
}
// disable this operator and use the generic case if these conditions hold
#define GB_DISABLE \
(GxB_NO_LNOT || GxB_NO_INT8)
//------------------------------------------------------------------------------
// Cx = op (cast (Ax)): apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_apply__lnot_int8_int8)
(
int8_t *Cx, // Cx and Ax may be aliased
const int8_t *Ax,
const int8_t *restrict Ab, // A->b if A is bitmap
int64_t anz,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
int64_t p ;
if (Ab == NULL)
{
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
int8_t aij = Ax [p] ;
int8_t z = aij ;
Cx [p] = !(z != 0) ;
}
}
else
{
// bitmap case, no transpose; A->b already memcpy'd into C->b
#pragma omp parallel for num_threads(nthreads) schedule(static)
for (p = 0 ; p < anz ; p++)
{
if (!Ab [p]) continue ;
int8_t aij = Ax [p] ;
int8_t z = aij ;
Cx [p] = !(z != 0) ;
}
}
return (GrB_SUCCESS) ;
#endif
}
//------------------------------------------------------------------------------
// C = op (cast (A')): transpose, typecast, and apply a unary operator
//------------------------------------------------------------------------------
GrB_Info GB (_unop_tran__lnot_int8_int8)
(
GrB_Matrix C,
const GrB_Matrix A,
int64_t *restrict *Workspaces,
const int64_t *restrict A_slice,
int nworkspaces,
int nthreads
)
{
#if GB_DISABLE
return (GrB_NO_VALUE) ;
#else
#include "GB_unop_transpose.c"
return (GrB_SUCCESS) ;
#endif
}
#endif
|
ceil_ref.c | /*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* License); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* AS IS BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
/*
* Copyright (c) 2021, OPEN AI LAB
* Author: qtang@openailab.com
* Update: hhchen@openailab.com
*/
#include "graph/tensor.h"
#include "graph/node.h"
#include "graph/graph.h"
#include "utility/sys_port.h"
#include "utility/float.h"
#include "utility/log.h"
#include "device/cpu/cpu_node.h"
#include "device/cpu/cpu_graph.h"
#include "device/cpu/cpu_module.h"
#include <math.h>
int ref_ceil_fp32(struct tensor* input_tensor, struct tensor* output_tensor, int num_thread)
{
// dims size = 2 or 3
if (input_tensor->dim_num < 4)
{
float* input_data = input_tensor->data;
float* out_data = output_tensor->data;
int total_size = input_tensor->elem_num;
for (int i = 0; i < total_size; i++)
{
input_data[i] = ceilf(out_data[i]);
}
return 0;
}
// dims size 3
else if (input_tensor->dim_num == 4)
{
int w = input_tensor->dims[3];
int h = output_tensor->dims[2];
int channels = input_tensor->dims[1];
int size = h * w;
int c_step = h * w;
float* input_data = input_tensor->data;
float* out_data = output_tensor->data;
#pragma omp parallel for num_threads(num_thread)
for (int q = 0; q < channels; q++)
{
float* src = input_data + c_step * q;
float* dst = out_data + c_step * q;
for (int i = 0; i < size; i++)
{
dst[i] = ceilf(src[i]);
}
}
return 0;
}
return -1;
}
int ref_ceil_uint8(struct tensor* input_tensor, struct tensor* output_tensor, int num_thread)
{
/* dequant */
uint8_t* input_uint8 = input_tensor->data;
uint8_t* output_uint8 = output_tensor->data;
float input_scale = input_tensor->scale;
float output_scale = output_tensor->scale;
int32_t input_zero = input_tensor->zero_point;
int32_t output_zero = output_tensor->zero_point;
int input_size = input_tensor->elem_num;
int output_size = output_tensor->elem_num;
float* input_data = ( float* )sys_malloc(input_size * sizeof(float));
float* out_data = ( float* )sys_malloc(output_size * sizeof(float));
for (int i = 0; i < input_size; i++)
{
input_data[i] = (( float )input_uint8[i] - ( float )input_zero) * input_scale;
}
// dims size = 2 or 3
if (input_tensor->dim_num < 4)
{
int total_size = input_tensor->elem_num;
for (int i = 0; i < total_size; i++)
{
input_data[i] = ceil(out_data[i]);
}
// return 0;
}
// dims size 3
else if (input_tensor->dim_num == 4)
{
int w = input_tensor->dims[3];
int h = output_tensor->dims[2];
int channels = input_tensor->dims[1];
int size = h * w;
int c_step = h * w;
#pragma omp parallel for num_threads(num_thread)
for (int q = 0; q < channels; q++)
{
float* src = input_data + c_step * q;
float* dst = out_data + c_step * q;
for (int i = 0; i < size; i++)
{
dst[i] = ceil(src[i]);
}
}
// return 0;
}
/* quant */
for (int i = 0; i < output_size; i++)
{
int udata = round(out_data[i] / output_scale + output_zero);
if (udata > 255)
udata = 255;
else if (udata < 0)
udata = 0;
output_uint8[i] = udata;
}
sys_free(input_data);
sys_free(out_data);
return 0;
}
static int init_node(struct node_ops* node_ops, struct exec_node* exec_node, struct exec_graph* exec_graph)
{
return 0;
}
static int release_node(struct node_ops* node_ops, struct exec_node* exec_node, struct exec_graph* exec_graph)
{
return 0;
}
static int prerun(struct node_ops* node_ops, struct exec_node* exec_node, struct exec_graph* exec_graph)
{
return 0;
}
static int run(struct node_ops* node_ops, struct exec_node* exec_node, struct exec_graph* exec_graph)
{
struct node* ir_node = exec_node->ir_node;
struct graph* ir_graph = ir_node->graph;
struct tensor* input_tensor = get_ir_graph_tensor(ir_graph, ir_node->input_tensors[0]);
struct tensor* output_tensor = get_ir_graph_tensor(ir_graph, ir_node->output_tensors[0]);
int ret = -1;
if (input_tensor->data_type == TENGINE_DT_FP32)
ret = ref_ceil_fp32(input_tensor, output_tensor, exec_graph->num_thread);
else if(input_tensor->data_type == TENGINE_DT_UINT8)
ret = ref_ceil_uint8(input_tensor, output_tensor, exec_graph->num_thread);
else
TLOG_ERR("Input data type %d not to be supported.\n", input_tensor->data_type);
return ret;
}
static int score(struct node_ops* node_ops, struct exec_graph* exec_graph, struct node* exec_node)
{
return OPS_SCORE_CANDO;
}
static struct node_ops hcl_node_ops = {.prerun = prerun,
.run = run,
.reshape = NULL,
.postrun = NULL,
.init_node = init_node,
.release_node = release_node,
.score = score};
int register_ceil_ref_op()
{
return register_builtin_node_ops(OP_CEIL, &hcl_node_ops);
}
int unregister_ceil_ref_op()
{
return unregister_builtin_node_ops(OP_CEIL, &hcl_node_ops);
}
|
ellipticBuildContinuous.c | /*
The MIT License (MIT)
Copyright (c) 2017 Tim Warburton, Noel Chalmers, Jesse Chan, Ali Karakus
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
*/
#include "elliptic.h"
// compare on global indices
int parallelCompareRowColumn(const void *a, const void *b){
nonZero_t *fa = (nonZero_t*) a;
nonZero_t *fb = (nonZero_t*) b;
if(fa->row < fb->row) return -1;
if(fa->row > fb->row) return +1;
if(fa->col < fb->col) return -1;
if(fa->col > fb->col) return +1;
return 0;
}
void ellipticBuildContinuousTri2D (elliptic_t *elliptic, dfloat lambda, nonZero_t **A, dlong *nnz, ogs_t **ogs, hlong *globalStarts);
void ellipticBuildContinuousQuad2D(elliptic_t *elliptic, dfloat lambda, nonZero_t **A, dlong *nnz, ogs_t **ogs, hlong *globalStarts);
void ellipticBuildContinuousQuad3D(elliptic_t *elliptic, dfloat lambda, nonZero_t **A, dlong *nnz, ogs_t **ogs, hlong *globalStarts);
void ellipticBuildContinuousTet3D (elliptic_t *elliptic, dfloat lambda, nonZero_t **A, dlong *nnz, ogs_t **ogs, hlong *globalStarts);
void ellipticBuildContinuousHex3D (elliptic_t *elliptic, dfloat lambda, nonZero_t **A, dlong *nnz, ogs_t **ogs, hlong *globalStarts);
void ellipticBuildContinuous(elliptic_t *elliptic, dfloat lambda, nonZero_t **A, dlong *nnz, ogs_t **ogs, hlong *globalStarts) {
switch(elliptic->elementType){
case TRIANGLES:
ellipticBuildContinuousTri2D(elliptic, lambda, A, nnz, ogs, globalStarts); break;
case QUADRILATERALS:{
if(elliptic->dim==2)
ellipticBuildContinuousQuad2D(elliptic, lambda, A, nnz, ogs, globalStarts);
else
ellipticBuildContinuousQuad3D(elliptic, lambda, A, nnz, ogs, globalStarts);
break;
}
case TETRAHEDRA:
ellipticBuildContinuousTet3D(elliptic, lambda, A, nnz, ogs, globalStarts); break;
case HEXAHEDRA:
ellipticBuildContinuousHex3D(elliptic, lambda, A, nnz, ogs, globalStarts); break;
}
}
void ellipticBuildContinuousTri2D(elliptic_t *elliptic, dfloat lambda, nonZero_t **A, dlong *nnz, ogs_t **ogs, hlong *globalStarts) {
mesh2D *mesh = elliptic->mesh;
setupAide options = elliptic->options;
int rank = mesh->rank;
//use the masked gs handle to define a global ordering
// number of degrees of freedom on this rank (after gathering)
hlong Ngather = elliptic->ogs->Ngather;
dlong Ntotal = mesh->Np*mesh->Nelements;
// create a global numbering system
hlong *globalIds = (hlong *) calloc(Ngather,sizeof(hlong));
int *owner = (int *) calloc(Ngather,sizeof(int));
// every gathered degree of freedom has its own global id
MPI_Allgather(&Ngather, 1, MPI_HLONG, globalStarts+1, 1, MPI_HLONG, mesh->comm);
for(int r=0;r<mesh->size;++r)
globalStarts[r+1] = globalStarts[r]+globalStarts[r+1];
//use the offsets to set a consecutive global numbering
for (dlong n =0;n<elliptic->ogs->Ngather;n++) {
globalIds[n] = n + globalStarts[rank];
owner[n] = rank;
}
//scatter this numbering to the original nodes
hlong *globalNumbering = (hlong *) calloc(Ntotal,sizeof(hlong));
int *globalOwners = (int *) calloc(Ntotal,sizeof(int));
for (dlong n=0;n<Ntotal;n++) globalNumbering[n] = -1;
ogsScatter(globalNumbering, globalIds, ogsHlong, ogsAdd, elliptic->ogs);
ogsScatter(globalOwners, owner, ogsInt, ogsAdd, elliptic->ogs);
free(globalIds); free(owner);
// Build non-zeros of stiffness matrix (unassembled)
dlong nnzLocal = mesh->Np*mesh->Np*mesh->Nelements;
nonZero_t *sendNonZeros = (nonZero_t*) calloc(nnzLocal, sizeof(nonZero_t));
int *AsendCounts = (int*) calloc(mesh->size, sizeof(int));
int *ArecvCounts = (int*) calloc(mesh->size, sizeof(int));
int *AsendOffsets = (int*) calloc(mesh->size+1, sizeof(int));
int *ArecvOffsets = (int*) calloc(mesh->size+1, sizeof(int));
dfloat *Srr = (dfloat *) calloc(mesh->Np*mesh->Np,sizeof(dfloat));
dfloat *Srs = (dfloat *) calloc(mesh->Np*mesh->Np,sizeof(dfloat));
dfloat *Sss = (dfloat *) calloc(mesh->Np*mesh->Np,sizeof(dfloat));
dfloat *MM = (dfloat *) calloc(mesh->Np*mesh->Np,sizeof(dfloat));
for (int n=0;n<mesh->Np;n++) {
for (int m=0;m<mesh->Np;m++) {
Srr[m+n*mesh->Np] = mesh->Srr[m+n*mesh->Np];
Srs[m+n*mesh->Np] = mesh->Srs[m+n*mesh->Np] + mesh->Ssr[m+n*mesh->Np];
Sss[m+n*mesh->Np] = mesh->Sss[m+n*mesh->Np];
MM[m+n*mesh->Np] = mesh->MM[m+n*mesh->Np];
}
}
if(mesh->rank==0) printf("Building full FEM matrix...");fflush(stdout);
//Build unassembed non-zeros
dlong cnt =0;
for (dlong e=0;e<mesh->Nelements;e++) {
dfloat Grr = mesh->ggeo[e*mesh->Nggeo + G00ID];
dfloat Grs = mesh->ggeo[e*mesh->Nggeo + G01ID];
dfloat Gss = mesh->ggeo[e*mesh->Nggeo + G11ID];
dfloat J = mesh->ggeo[e*mesh->Nggeo + GWJID];
for (int n=0;n<mesh->Np;n++) {
if (globalNumbering[e*mesh->Np + n]<0) continue; //skip masked nodes
for (int m=0;m<mesh->Np;m++) {
if (globalNumbering[e*mesh->Np + m]<0) continue; //skip masked nodes
dfloat val = 0.;
val += Grr*Srr[m+n*mesh->Np];
val += Grs*Srs[m+n*mesh->Np];
val += Gss*Sss[m+n*mesh->Np];
val += J*lambda*MM[m+n*mesh->Np];
dfloat nonZeroThreshold = 1e-7;
if (fabs(val)>nonZeroThreshold) {
// pack non-zero
sendNonZeros[cnt].val = val;
sendNonZeros[cnt].row = globalNumbering[e*mesh->Np + n];
sendNonZeros[cnt].col = globalNumbering[e*mesh->Np + m];
sendNonZeros[cnt].ownerRank = globalOwners[e*mesh->Np + n];
cnt++;
}
}
}
}
// Make the MPI_NONZERO_T data type
MPI_Datatype MPI_NONZERO_T;
MPI_Datatype dtype[4] = {MPI_HLONG, MPI_HLONG, MPI_INT, MPI_DFLOAT};
int blength[4] = {1, 1, 1, 1};
MPI_Aint addr[4], displ[4];
MPI_Get_address ( &(sendNonZeros[0] ), addr+0);
MPI_Get_address ( &(sendNonZeros[0].col ), addr+1);
MPI_Get_address ( &(sendNonZeros[0].ownerRank), addr+2);
MPI_Get_address ( &(sendNonZeros[0].val ), addr+3);
displ[0] = 0;
displ[1] = addr[1] - addr[0];
displ[2] = addr[2] - addr[0];
displ[3] = addr[3] - addr[0];
MPI_Type_create_struct (4, blength, displ, dtype, &MPI_NONZERO_T);
MPI_Type_commit (&MPI_NONZERO_T);
// count how many non-zeros to send to each process
for(dlong n=0;n<cnt;++n)
AsendCounts[sendNonZeros[n].ownerRank]++;
// sort by row ordering
qsort(sendNonZeros, cnt, sizeof(nonZero_t), parallelCompareRowColumn);
// find how many nodes to expect (should use sparse version)
MPI_Alltoall(AsendCounts, 1, MPI_INT, ArecvCounts, 1, MPI_INT, mesh->comm);
// find send and recv offsets for gather
*nnz = 0;
for(int r=0;r<mesh->size;++r){
AsendOffsets[r+1] = AsendOffsets[r] + AsendCounts[r];
ArecvOffsets[r+1] = ArecvOffsets[r] + ArecvCounts[r];
*nnz += ArecvCounts[r];
}
*A = (nonZero_t*) calloc(*nnz, sizeof(nonZero_t));
// determine number to receive
MPI_Alltoallv(sendNonZeros, AsendCounts, AsendOffsets, MPI_NONZERO_T,
(*A), ArecvCounts, ArecvOffsets, MPI_NONZERO_T,
mesh->comm);
// sort received non-zero entries by row block (may need to switch compareRowColumn tests)
qsort((*A), *nnz, sizeof(nonZero_t), parallelCompareRowColumn);
// compress duplicates
cnt = 0;
for(dlong n=1;n<*nnz;++n){
if((*A)[n].row == (*A)[cnt].row &&
(*A)[n].col == (*A)[cnt].col){
(*A)[cnt].val += (*A)[n].val;
}
else{
++cnt;
(*A)[cnt] = (*A)[n];
}
}
if (*nnz) cnt++;
*nnz = cnt;
if(mesh->rank==0) printf("done.\n");
MPI_Barrier(mesh->comm);
MPI_Type_free(&MPI_NONZERO_T);
free(sendNonZeros);
free(globalNumbering); free(globalOwners);
free(AsendCounts);
free(ArecvCounts);
free(AsendOffsets);
free(ArecvOffsets);
free(Srr);
free(Srs);
free(Sss);
free(MM );
}
void ellipticBuildContinuousQuad3D(elliptic_t *elliptic, dfloat lambda, nonZero_t **A, dlong *nnz, ogs_t **ogs, hlong *globalStarts) {
mesh2D *mesh = elliptic->mesh;
setupAide options = elliptic->options;
int rank = mesh->rank;
//use the masked gs handle to define a global ordering
// number of degrees of freedom on this rank (after gathering)
hlong Ngather = elliptic->ogs->Ngather;
dlong Ntotal = mesh->Np*mesh->Nelements;
// create a global numbering system
hlong *globalIds = (hlong *) calloc(Ngather,sizeof(hlong));
int *owner = (int *) calloc(Ngather,sizeof(int));
// every gathered degree of freedom has its own global id
MPI_Allgather(&Ngather, 1, MPI_HLONG, globalStarts+1, 1, MPI_HLONG, mesh->comm);
for(int r=0;r<mesh->size;++r)
globalStarts[r+1] = globalStarts[r]+globalStarts[r+1];
//use the offsets to set a consecutive global numbering
for (dlong n =0;n<elliptic->ogs->Ngather;n++) {
globalIds[n] = n + globalStarts[rank];
owner[n] = rank;
}
//scatter this numbering to the original nodes
hlong *globalNumbering = (hlong *) calloc(Ntotal,sizeof(hlong));
int *globalOwners = (int *) calloc(Ntotal,sizeof(int));
for (dlong n=0;n<Ntotal;n++) globalNumbering[n] = -1;
ogsScatter(globalNumbering, globalIds, ogsHlong, ogsAdd, elliptic->ogs);
ogsScatter(globalOwners, owner, ogsInt, ogsAdd, elliptic->ogs);
free(globalIds); free(owner);
// 2. Build non-zeros of stiffness matrix (unassembled)
dlong nnzLocal = mesh->Np*mesh->Np*mesh->Nelements;
nonZero_t *sendNonZeros = (nonZero_t*) calloc(nnzLocal, sizeof(nonZero_t));
int *AsendCounts = (int*) calloc(mesh->size, sizeof(int));
int *ArecvCounts = (int*) calloc(mesh->size, sizeof(int));
int *AsendOffsets = (int*) calloc(mesh->size+1, sizeof(int));
int *ArecvOffsets = (int*) calloc(mesh->size+1, sizeof(int));
int *mask = (int *) calloc(mesh->Np*mesh->Nelements,sizeof(int));
for (dlong n=0;n<elliptic->Nmasked;n++) mask[elliptic->maskIds[n]] = 1;
if(mesh->rank==0) printf("Building full FEM matrix...");fflush(stdout);
#if 0
hlong NTf = mesh->Nelements*mesh->Np * mesh->Nelements*mesh->Np ;
dfloat *Af = (dfloat *)calloc(NTf, sizeof(dfloat));
#endif
//Build unassembed non-zeros
dlong cnt =0;
for (dlong e=0;e<mesh->Nelements;e++) {
for (int ny=0;ny<mesh->Nq;ny++) {
for (int nx=0;nx<mesh->Nq;nx++) {
if (mask[e*mesh->Np + nx+ny*mesh->Nq]) continue; //skip masked nodes
for (int my=0;my<mesh->Nq;my++) {
for (int mx=0;mx<mesh->Nq;mx++) {
if (mask[e*mesh->Np + mx+my*mesh->Nq]) continue; //skip masked nodes
int id;
dfloat val = 0.;
if (ny==my) {
for (int k=0;k<mesh->Nq;k++) {
id = k+ny*mesh->Nq;
dfloat Grr = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G00ID*mesh->Np];
val += Grr*mesh->D[nx+k*mesh->Nq]*mesh->D[mx+k*mesh->Nq];
}
}
id = mx+ny*mesh->Nq;
dfloat Grs = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G01ID*mesh->Np];
val += Grs*mesh->D[nx+mx*mesh->Nq]*mesh->D[my+ny*mesh->Nq];
id = nx+my*mesh->Nq;
dfloat Gsr = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G01ID*mesh->Np];
val += Gsr*mesh->D[mx+nx*mesh->Nq]*mesh->D[ny+my*mesh->Nq];
// id = mx+ny*mesh->Nq;
// dfloat Grt = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G02ID*mesh->Np];
// val += Grt*mesh->D[nx+mx*mesh->Nq];
// id = nx+my*mesh->Nq;
// dfloat Gtr = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G02ID*mesh->Np];
// val += Gtr*mesh->D[mx+nx*mesh->Nq];
if (nx==mx) {
for (int k=0;k<mesh->Nq;k++) {
id = nx+k*mesh->Nq;
dfloat Gss = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G11ID*mesh->Np];
val += Gss*mesh->D[ny+k*mesh->Nq]*mesh->D[my+k*mesh->Nq];
}
}
// double check following two: AK
// id = nx+my*mesh->Nq;
// dfloat Gst = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G12ID*mesh->Np];
// val += Gst*mesh->D[ny+my*mesh->Nq];
// id = mx+ny*mesh->Nq;
// dfloat Gts = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G12ID*mesh->Np];
// val += Gts*mesh->D[my+ny*mesh->Nq];
if ((nx==mx)&&(ny==my)) {
id = nx + ny*mesh->Nq;
// dfloat Gtt = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G22ID*mesh->Np];
// val += Gtt;
dfloat JW = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + GWJID*mesh->Np];
val += JW*lambda;
}
#if 0
const hlong rowid = e*mesh->Np + nx + ny*mesh->Nq;
const hlong colid = e*mesh->Np + mx + my*mesh->Nq;
Af[rowid*mesh->Nelements*mesh->Np + colid] = val;
#endif
dfloat nonZeroThreshold = 1e-7;
if (fabs(val)>nonZeroThreshold) {
// pack non-zero
sendNonZeros[cnt].val = val;
sendNonZeros[cnt].row = globalNumbering[e*mesh->Np + nx+ny*mesh->Nq];
sendNonZeros[cnt].col = globalNumbering[e*mesh->Np + mx+my*mesh->Nq];
sendNonZeros[cnt].ownerRank = globalOwners[e*mesh->Np + nx+ny*mesh->Nq];
cnt++;
}
}
}
}
}
}
#if 0
// Write matlab dat for postprocess
char fname[BUFSIZ];
sprintf(fname, "Ax.dat");
FILE *fp;
fp = fopen(fname, "w");
for(hlong row = 0; row<(mesh->Nelements*mesh->Np); row++){
for(hlong col = 0; col<(mesh->Nelements*mesh->Np); col++){
dfloat val = Af[row*mesh->Nelements*mesh->Np + col];
fprintf(fp,"%.8e ", val);
}
fprintf(fp,"\n");
}
fclose(fp);
#endif
// Make the MPI_NONZERO_T data type
MPI_Datatype MPI_NONZERO_T;
MPI_Datatype dtype[4] = {MPI_HLONG, MPI_HLONG, MPI_INT, MPI_DFLOAT};
int blength[4] = {1, 1, 1, 1};
MPI_Aint addr[4], displ[4];
MPI_Get_address ( &(sendNonZeros[0] ), addr+0);
MPI_Get_address ( &(sendNonZeros[0].col ), addr+1);
MPI_Get_address ( &(sendNonZeros[0].ownerRank), addr+2);
MPI_Get_address ( &(sendNonZeros[0].val ), addr+3);
displ[0] = 0;
displ[1] = addr[1] - addr[0];
displ[2] = addr[2] - addr[0];
displ[3] = addr[3] - addr[0];
MPI_Type_create_struct (4, blength, displ, dtype, &MPI_NONZERO_T);
MPI_Type_commit (&MPI_NONZERO_T);
// count how many non-zeros to send to each process
for(dlong n=0;n<cnt;++n)
AsendCounts[sendNonZeros[n].ownerRank]++;
// sort by row ordering
qsort(sendNonZeros, cnt, sizeof(nonZero_t), parallelCompareRowColumn);
// find how many nodes to expect (should use sparse version)
MPI_Alltoall(AsendCounts, 1, MPI_INT, ArecvCounts, 1, MPI_INT, mesh->comm);
// find send and recv offsets for gather
*nnz = 0;
for(int r=0;r<mesh->size;++r){
AsendOffsets[r+1] = AsendOffsets[r] + AsendCounts[r];
ArecvOffsets[r+1] = ArecvOffsets[r] + ArecvCounts[r];
*nnz += ArecvCounts[r];
}
*A = (nonZero_t*) calloc(*nnz, sizeof(nonZero_t));
// determine number to receive
MPI_Alltoallv(sendNonZeros, AsendCounts, AsendOffsets, MPI_NONZERO_T,
(*A), ArecvCounts, ArecvOffsets, MPI_NONZERO_T,
mesh->comm);
// sort received non-zero entries by row block (may need to switch compareRowColumn tests)
qsort((*A), *nnz, sizeof(nonZero_t), parallelCompareRowColumn);
// compress duplicates
cnt = 0;
for(dlong n=1;n<*nnz;++n){
if((*A)[n].row == (*A)[cnt].row &&
(*A)[n].col == (*A)[cnt].col){
(*A)[cnt].val += (*A)[n].val;
}
else{
++cnt;
(*A)[cnt] = (*A)[n];
}
}
if (*nnz) cnt++;
*nnz = cnt;
#if 0
// Write matlab dat for postprocess
char fname[BUFSIZ];
sprintf(fname, "Ax.dat");
FILE *fp;
fp = fopen(fname, "w");
for(dlong n=1;n<*nnz;++n){
fprintf(fp,"%d %d %.8e\n", (*A)[n].row+1, (*A)[n].col+1, (*A)[n].val);
}
fclose(fp);
#endif
if(mesh->rank==0) printf("done.\n");
MPI_Barrier(mesh->comm);
MPI_Type_free(&MPI_NONZERO_T);
free(sendNonZeros);
free(globalNumbering); free(globalOwners);
free(AsendCounts);
free(ArecvCounts);
free(AsendOffsets);
free(ArecvOffsets);
}
void ellipticBuildContinuousQuad2D(elliptic_t *elliptic, dfloat lambda, nonZero_t **A, dlong *nnz, ogs_t **ogs, hlong *globalStarts) {
mesh_t *mesh = elliptic->mesh;
setupAide options = elliptic->options;
int rank = mesh->rank;
//use the masked gs handle to define a global ordering
// number of degrees of freedom on this rank (after gathering)
hlong Ngather = elliptic->ogs->Ngather;
dlong Ntotal = mesh->Np*mesh->Nelements;
// create a global numbering system
hlong *globalIds = (hlong *) calloc(Ngather,sizeof(hlong));
int *owner = (int *) calloc(Ngather,sizeof(int));
// every gathered degree of freedom has its own global id
MPI_Allgather(&Ngather, 1, MPI_HLONG, globalStarts+1, 1, MPI_HLONG, mesh->comm);
for(int r=0;r<mesh->size;++r)
globalStarts[r+1] = globalStarts[r]+globalStarts[r+1];
//use the offsets to set a consecutive global numbering
for (dlong n =0;n<elliptic->ogs->Ngather;n++) {
globalIds[n] = n + globalStarts[rank];
owner[n] = rank;
}
//scatter this numbering to the original nodes
hlong *globalNumbering = (hlong *) calloc(Ntotal,sizeof(hlong));
int *globalOwners = (int *) calloc(Ntotal,sizeof(int));
for (dlong n=0;n<Ntotal;n++) globalNumbering[n] = -1;
ogsScatter(globalNumbering, globalIds, ogsHlong, ogsAdd, elliptic->ogs);
ogsScatter(globalOwners, owner, ogsInt, ogsAdd, elliptic->ogs);
free(globalIds); free(owner);
// 2. Build non-zeros of stiffness matrix (unassembled)
dlong nnzLocal = mesh->Np*mesh->Np*mesh->Nelements;
nonZero_t *sendNonZeros = (nonZero_t*) calloc(nnzLocal, sizeof(nonZero_t));
int *AsendCounts = (int*) calloc(mesh->size, sizeof(int));
int *ArecvCounts = (int*) calloc(mesh->size, sizeof(int));
int *AsendOffsets = (int*) calloc(mesh->size+1, sizeof(int));
int *ArecvOffsets = (int*) calloc(mesh->size+1, sizeof(int));
int *mask = (int *) calloc(mesh->Np*mesh->Nelements,sizeof(int));
for (dlong n=0;n<elliptic->Nmasked;n++) mask[elliptic->maskIds[n]] = 1;
if(mesh->rank==0) printf("Building full FEM matrix...");fflush(stdout);
//Build unassembed non-zeros
dlong cnt =0;
for (dlong e=0;e<mesh->Nelements;e++) {
for (int ny=0;ny<mesh->Nq;ny++) {
for (int nx=0;nx<mesh->Nq;nx++) {
if (mask[e*mesh->Np + nx+ny*mesh->Nq]) continue; //skip masked nodes
for (int my=0;my<mesh->Nq;my++) {
for (int mx=0;mx<mesh->Nq;mx++) {
if (mask[e*mesh->Np + mx+my*mesh->Nq]) continue; //skip masked nodes
int id;
dfloat val = 0.;
if (ny==my) {
for (int k=0;k<mesh->Nq;k++) {
id = k+ny*mesh->Nq;
dfloat Grr = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G00ID*mesh->Np];
val += Grr*mesh->D[nx+k*mesh->Nq]*mesh->D[mx+k*mesh->Nq];
}
}
id = mx+ny*mesh->Nq;
dfloat Grs = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G01ID*mesh->Np];
val += Grs*mesh->D[nx+mx*mesh->Nq]*mesh->D[my+ny*mesh->Nq];
id = nx+my*mesh->Nq;
dfloat Gsr = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G01ID*mesh->Np];
val += Gsr*mesh->D[mx+nx*mesh->Nq]*mesh->D[ny+my*mesh->Nq];
if (nx==mx) {
for (int k=0;k<mesh->Nq;k++) {
id = nx+k*mesh->Nq;
dfloat Gss = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G11ID*mesh->Np];
val += Gss*mesh->D[ny+k*mesh->Nq]*mesh->D[my+k*mesh->Nq];
}
}
if ((nx==mx)&&(ny==my)) {
id = nx + ny*mesh->Nq;
dfloat JW = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + GWJID*mesh->Np];
val += JW*lambda;
}
dfloat nonZeroThreshold = 1e-7;
if (fabs(val)>nonZeroThreshold) {
// pack non-zero
sendNonZeros[cnt].val = val;
sendNonZeros[cnt].row = globalNumbering[e*mesh->Np + nx+ny*mesh->Nq];
sendNonZeros[cnt].col = globalNumbering[e*mesh->Np + mx+my*mesh->Nq];
sendNonZeros[cnt].ownerRank = globalOwners[e*mesh->Np + nx+ny*mesh->Nq];
cnt++;
}
}
}
}
}
}
// Make the MPI_NONZERO_T data type
MPI_Datatype MPI_NONZERO_T;
MPI_Datatype dtype[4] = {MPI_HLONG, MPI_HLONG, MPI_INT, MPI_DFLOAT};
int blength[4] = {1, 1, 1, 1};
MPI_Aint addr[4], displ[4];
MPI_Get_address ( &(sendNonZeros[0] ), addr+0);
MPI_Get_address ( &(sendNonZeros[0].col ), addr+1);
MPI_Get_address ( &(sendNonZeros[0].ownerRank), addr+2);
MPI_Get_address ( &(sendNonZeros[0].val ), addr+3);
displ[0] = 0;
displ[1] = addr[1] - addr[0];
displ[2] = addr[2] - addr[0];
displ[3] = addr[3] - addr[0];
MPI_Type_create_struct (4, blength, displ, dtype, &MPI_NONZERO_T);
MPI_Type_commit (&MPI_NONZERO_T);
// count how many non-zeros to send to each process
for(dlong n=0;n<cnt;++n)
AsendCounts[sendNonZeros[n].ownerRank]++;
// sort by row ordering
qsort(sendNonZeros, cnt, sizeof(nonZero_t), parallelCompareRowColumn);
// find how many nodes to expect (should use sparse version)
MPI_Alltoall(AsendCounts, 1, MPI_INT, ArecvCounts, 1, MPI_INT, mesh->comm);
// find send and recv offsets for gather
*nnz = 0;
for(int r=0;r<mesh->size;++r){
AsendOffsets[r+1] = AsendOffsets[r] + AsendCounts[r];
ArecvOffsets[r+1] = ArecvOffsets[r] + ArecvCounts[r];
*nnz += ArecvCounts[r];
}
*A = (nonZero_t*) calloc(*nnz, sizeof(nonZero_t));
// determine number to receive
MPI_Alltoallv(sendNonZeros, AsendCounts, AsendOffsets, MPI_NONZERO_T,
(*A), ArecvCounts, ArecvOffsets, MPI_NONZERO_T,
mesh->comm);
// sort received non-zero entries by row block (may need to switch compareRowColumn tests)
qsort((*A), *nnz, sizeof(nonZero_t), parallelCompareRowColumn);
// compress duplicates
cnt = 0;
for(dlong n=1;n<*nnz;++n){
if((*A)[n].row == (*A)[cnt].row &&
(*A)[n].col == (*A)[cnt].col){
(*A)[cnt].val += (*A)[n].val;
}
else{
++cnt;
(*A)[cnt] = (*A)[n];
}
}
if (*nnz) cnt++;
*nnz = cnt;
#if 1
// Write matlab dat for postprocess
char fname[BUFSIZ];
sprintf(fname, "Ax.dat");
FILE *fp;
fp = fopen(fname, "w");
for(dlong n=1;n<*nnz;++n){
fprintf(fp,"%d %d %.8e\n", (*A)[n].row+1, (*A)[n].col+1, (*A)[n].val);
}
fclose(fp);
#endif
if(mesh->rank==0) printf("done.\n");
MPI_Barrier(mesh->comm);
MPI_Type_free(&MPI_NONZERO_T);
free(sendNonZeros);
free(globalNumbering); free(globalOwners);
free(AsendCounts);
free(ArecvCounts);
free(AsendOffsets);
free(ArecvOffsets);
}
void ellipticBuildContinuousTet3D(elliptic_t *elliptic, dfloat lambda, nonZero_t **A, dlong *nnz, ogs_t **ogs, hlong *globalStarts) {
mesh2D *mesh = elliptic->mesh;
setupAide options = elliptic->options;
int rank = mesh->rank;
//use the masked gs handle to define a global ordering
// number of degrees of freedom on this rank (after gathering)
hlong Ngather = elliptic->ogs->Ngather;
dlong Ntotal = mesh->Np*mesh->Nelements;
// create a global numbering system
hlong *globalIds = (hlong *) calloc(Ngather,sizeof(hlong));
int *owner = (int *) calloc(Ngather,sizeof(int));
// every gathered degree of freedom has its own global id
MPI_Allgather(&Ngather, 1, MPI_HLONG, globalStarts+1, 1, MPI_HLONG, mesh->comm);
for(int r=0;r<mesh->size;++r)
globalStarts[r+1] = globalStarts[r]+globalStarts[r+1];
//use the offsets to set a consecutive global numbering
for (dlong n =0;n<elliptic->ogs->Ngather;n++) {
globalIds[n] = n + globalStarts[rank];
owner[n] = rank;
}
//scatter this numbering to the original nodes
hlong *globalNumbering = (hlong *) calloc(Ntotal,sizeof(hlong));
int *globalOwners = (int *) calloc(Ntotal,sizeof(int));
for (dlong n=0;n<Ntotal;n++) globalNumbering[n] = -1;
ogsScatter(globalNumbering, globalIds, ogsHlong, ogsAdd, elliptic->ogs);
ogsScatter(globalOwners, owner, ogsInt, ogsAdd, elliptic->ogs);
free(globalIds); free(owner);
// Build non-zeros of stiffness matrix (unassembled)
dlong nnzLocal = mesh->Np*mesh->Np*mesh->Nelements;
nonZero_t *sendNonZeros = (nonZero_t*) calloc(nnzLocal, sizeof(nonZero_t));
int *AsendCounts = (int*) calloc(mesh->size, sizeof(int));
int *ArecvCounts = (int*) calloc(mesh->size, sizeof(int));
int *AsendOffsets = (int*) calloc(mesh->size+1, sizeof(int));
int *ArecvOffsets = (int*) calloc(mesh->size+1, sizeof(int));
int *mask = (int *) calloc(mesh->Np*mesh->Nelements,sizeof(int));
for (dlong n=0;n<elliptic->Nmasked;n++) mask[elliptic->maskIds[n]] = 1;
//Build unassembed non-zeros
if(mesh->rank==0) printf("Building full FEM matrix...");fflush(stdout);
dlong cnt =0;
#pragma omp parallel for
for (dlong e=0;e<mesh->Nelements;e++) {
dfloat Grr = mesh->ggeo[e*mesh->Nggeo + G00ID];
dfloat Grs = mesh->ggeo[e*mesh->Nggeo + G01ID];
dfloat Grt = mesh->ggeo[e*mesh->Nggeo + G02ID];
dfloat Gss = mesh->ggeo[e*mesh->Nggeo + G11ID];
dfloat Gst = mesh->ggeo[e*mesh->Nggeo + G12ID];
dfloat Gtt = mesh->ggeo[e*mesh->Nggeo + G22ID];
dfloat J = mesh->ggeo[e*mesh->Nggeo + GWJID];
for (int n=0;n<mesh->Np;n++) {
if (mask[e*mesh->Np + n]) continue; //skip masked nodes
for (int m=0;m<mesh->Np;m++) {
if (mask[e*mesh->Np + m]) continue; //skip masked nodes
dfloat val = 0.;
val += Grr*mesh->Srr[m+n*mesh->Np];
val += Grs*mesh->Srs[m+n*mesh->Np];
val += Grt*mesh->Srt[m+n*mesh->Np];
val += Grs*mesh->Ssr[m+n*mesh->Np];
val += Gss*mesh->Sss[m+n*mesh->Np];
val += Gst*mesh->Sst[m+n*mesh->Np];
val += Grt*mesh->Str[m+n*mesh->Np];
val += Gst*mesh->Sts[m+n*mesh->Np];
val += Gtt*mesh->Stt[m+n*mesh->Np];
val += J*lambda*mesh->MM[m+n*mesh->Np];
dfloat nonZeroThreshold = 1e-7;
if (fabs(val)>nonZeroThreshold) {
#pragma omp critical
{
// pack non-zero
sendNonZeros[cnt].val = val;
sendNonZeros[cnt].row = globalNumbering[e*mesh->Np + n];
sendNonZeros[cnt].col = globalNumbering[e*mesh->Np + m];
sendNonZeros[cnt].ownerRank = globalOwners[e*mesh->Np + n];
cnt++;
}
}
}
}
}
// Make the MPI_NONZERO_T data type
MPI_Datatype MPI_NONZERO_T;
MPI_Datatype dtype[4] = {MPI_HLONG, MPI_HLONG, MPI_INT, MPI_DFLOAT};
int blength[4] = {1, 1, 1, 1};
MPI_Aint addr[4], displ[4];
MPI_Get_address ( &(sendNonZeros[0] ), addr+0);
MPI_Get_address ( &(sendNonZeros[0].col ), addr+1);
MPI_Get_address ( &(sendNonZeros[0].ownerRank), addr+2);
MPI_Get_address ( &(sendNonZeros[0].val ), addr+3);
displ[0] = 0;
displ[1] = addr[1] - addr[0];
displ[2] = addr[2] - addr[0];
displ[3] = addr[3] - addr[0];
MPI_Type_create_struct (4, blength, displ, dtype, &MPI_NONZERO_T);
MPI_Type_commit (&MPI_NONZERO_T);
// count how many non-zeros to send to each process
for(dlong n=0;n<cnt;++n)
AsendCounts[sendNonZeros[n].ownerRank] += 1;
// sort by row ordering
qsort(sendNonZeros, cnt, sizeof(nonZero_t), parallelCompareRowColumn);
// find how many nodes to expect (should use sparse version)
MPI_Alltoall(AsendCounts, 1, MPI_INT, ArecvCounts, 1, MPI_INT, mesh->comm);
// find send and recv offsets for gather
*nnz = 0;
for(int r=0;r<mesh->size;++r){
AsendOffsets[r+1] = AsendOffsets[r] + AsendCounts[r];
ArecvOffsets[r+1] = ArecvOffsets[r] + ArecvCounts[r];
*nnz += ArecvCounts[r];
}
*A = (nonZero_t*) calloc(*nnz, sizeof(nonZero_t));
// determine number to receive
MPI_Alltoallv(sendNonZeros, AsendCounts, AsendOffsets, MPI_NONZERO_T,
(*A), ArecvCounts, ArecvOffsets, MPI_NONZERO_T,
mesh->comm);
// sort received non-zero entries by row block (may need to switch compareRowColumn tests)
qsort((*A), *nnz, sizeof(nonZero_t), parallelCompareRowColumn);
// compress duplicates
cnt = 0;
for(dlong n=1;n<*nnz;++n){
if((*A)[n].row == (*A)[cnt].row &&
(*A)[n].col == (*A)[cnt].col){
(*A)[cnt].val += (*A)[n].val;
}
else{
++cnt;
(*A)[cnt] = (*A)[n];
}
}
if (*nnz) cnt++;
*nnz = cnt;
if(mesh->rank==0) printf("done.\n");
MPI_Barrier(mesh->comm);
MPI_Type_free(&MPI_NONZERO_T);
free(sendNonZeros);
free(globalNumbering); free(globalOwners);
free(AsendCounts);
free(ArecvCounts);
free(AsendOffsets);
free(ArecvOffsets);
free(mask);
}
void ellipticBuildContinuousHex3D(elliptic_t *elliptic, dfloat lambda, nonZero_t **A, dlong *nnz, ogs_t **ogs, hlong *globalStarts) {
mesh2D *mesh = elliptic->mesh;
setupAide options = elliptic->options;
int rank = mesh->rank;
//use the masked gs handle to define a global ordering
// number of degrees of freedom on this rank (after gathering)
hlong Ngather = elliptic->ogs->Ngather;
dlong Ntotal = mesh->Np*mesh->Nelements;
// create a global numbering system
hlong *globalIds = (hlong *) calloc(Ngather,sizeof(hlong));
int *owner = (int *) calloc(Ngather,sizeof(int));
// every gathered degree of freedom has its own global id
MPI_Allgather(&Ngather, 1, MPI_HLONG, globalStarts+1, 1, MPI_HLONG, mesh->comm);
for(int r=0;r<mesh->size;++r)
globalStarts[r+1] = globalStarts[r]+globalStarts[r+1];
//use the offsets to set a consecutive global numbering
for (dlong n =0;n<elliptic->ogs->Ngather;n++) {
globalIds[n] = n + globalStarts[rank];
owner[n] = rank;
}
//scatter this numbering to the original nodes
hlong *globalNumbering = (hlong *) calloc(Ntotal,sizeof(hlong));
int *globalOwners = (int *) calloc(Ntotal,sizeof(int));
for (dlong n=0;n<Ntotal;n++) globalNumbering[n] = -1;
ogsScatter(globalNumbering, globalIds, ogsHlong, ogsAdd, elliptic->ogs);
ogsScatter(globalOwners, owner, ogsInt, ogsAdd, elliptic->ogs);
free(globalIds); free(owner);
// 2. Build non-zeros of stiffness matrix (unassembled)
dlong nnzLocal = mesh->Np*mesh->Np*mesh->Nelements;
nonZero_t *sendNonZeros = (nonZero_t*) calloc(nnzLocal, sizeof(nonZero_t));
int *AsendCounts = (int*) calloc(mesh->size, sizeof(int));
int *ArecvCounts = (int*) calloc(mesh->size, sizeof(int));
int *AsendOffsets = (int*) calloc(mesh->size+1, sizeof(int));
int *ArecvOffsets = (int*) calloc(mesh->size+1, sizeof(int));
int *mask = (int *) calloc(mesh->Np*mesh->Nelements,sizeof(int));
for (dlong n=0;n<elliptic->Nmasked;n++) mask[elliptic->maskIds[n]] = 1;
if(mesh->rank==0) printf("Building full FEM matrix...");fflush(stdout);
dlong cnt =0;
for (dlong e=0;e<mesh->Nelements;e++) {
for (int nz=0;nz<mesh->Nq;nz++) {
for (int ny=0;ny<mesh->Nq;ny++) {
for (int nx=0;nx<mesh->Nq;nx++) {
int idn = nx+ny*mesh->Nq+nz*mesh->Nq*mesh->Nq;
if (mask[e*mesh->Np + idn]) continue; //skip masked nodes
for (int mz=0;mz<mesh->Nq;mz++) {
for (int my=0;my<mesh->Nq;my++) {
for (int mx=0;mx<mesh->Nq;mx++) {
int idm = mx+my*mesh->Nq+mz*mesh->Nq*mesh->Nq;
if (mask[e*mesh->Np + idm]) continue; //skip masked nodes
int id;
dfloat val = 0.;
if ((ny==my)&&(nz==mz)) {
for (int k=0;k<mesh->Nq;k++) {
id = k+ny*mesh->Nq+nz*mesh->Nq*mesh->Nq;
dfloat Grr = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G00ID*mesh->Np];
val += Grr*mesh->D[nx+k*mesh->Nq]*mesh->D[mx+k*mesh->Nq];
}
}
if (nz==mz) {
id = mx+ny*mesh->Nq+nz*mesh->Nq*mesh->Nq;
dfloat Grs = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G01ID*mesh->Np];
val += Grs*mesh->D[nx+mx*mesh->Nq]*mesh->D[my+ny*mesh->Nq];
id = nx+my*mesh->Nq+nz*mesh->Nq*mesh->Nq;
dfloat Gsr = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G01ID*mesh->Np];
val += Gsr*mesh->D[mx+nx*mesh->Nq]*mesh->D[ny+my*mesh->Nq];
}
if (ny==my) {
id = mx+ny*mesh->Nq+nz*mesh->Nq*mesh->Nq;
dfloat Grt = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G02ID*mesh->Np];
val += Grt*mesh->D[nx+mx*mesh->Nq]*mesh->D[mz+nz*mesh->Nq];
id = nx+ny*mesh->Nq+mz*mesh->Nq*mesh->Nq;
dfloat Gst = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G02ID*mesh->Np];
val += Gst*mesh->D[mx+nx*mesh->Nq]*mesh->D[nz+mz*mesh->Nq];
}
if ((nx==mx)&&(nz==mz)) {
for (int k=0;k<mesh->Nq;k++) {
id = nx+k*mesh->Nq+nz*mesh->Nq*mesh->Nq;
dfloat Gss = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G11ID*mesh->Np];
val += Gss*mesh->D[ny+k*mesh->Nq]*mesh->D[my+k*mesh->Nq];
}
}
if (nx==mx) {
id = nx+my*mesh->Nq+nz*mesh->Nq*mesh->Nq;
dfloat Gst = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G12ID*mesh->Np];
val += Gst*mesh->D[ny+my*mesh->Nq]*mesh->D[mz+nz*mesh->Nq];
id = nx+ny*mesh->Nq+mz*mesh->Nq*mesh->Nq;
dfloat Gts = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G12ID*mesh->Np];
val += Gts*mesh->D[my+ny*mesh->Nq]*mesh->D[nz+mz*mesh->Nq];
}
if ((nx==mx)&&(ny==my)) {
for (int k=0;k<mesh->Nq;k++) {
id = nx+ny*mesh->Nq+k*mesh->Nq*mesh->Nq;
dfloat Gtt = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + G22ID*mesh->Np];
val += Gtt*mesh->D[nz+k*mesh->Nq]*mesh->D[mz+k*mesh->Nq];
}
}
if ((nx==mx)&&(ny==my)&&(nz==mz)) {
id = nx + ny*mesh->Nq+nz*mesh->Nq*mesh->Nq;
dfloat JW = mesh->ggeo[e*mesh->Np*mesh->Nggeo + id + GWJID*mesh->Np];
val += JW*lambda;
}
// pack non-zero
dfloat nonZeroThreshold = 1e-7;
if (fabs(val) >= nonZeroThreshold) {
sendNonZeros[cnt].val = val;
sendNonZeros[cnt].row = globalNumbering[e*mesh->Np + idn];
sendNonZeros[cnt].col = globalNumbering[e*mesh->Np + idm];
sendNonZeros[cnt].ownerRank = globalOwners[e*mesh->Np + idn];
cnt++;
}
}
}
}
}
}
}
}
// Make the MPI_NONZERO_T data type
MPI_Datatype MPI_NONZERO_T;
MPI_Datatype dtype[4] = {MPI_HLONG, MPI_HLONG, MPI_INT, MPI_DFLOAT};
int blength[4] = {1, 1, 1, 1};
MPI_Aint addr[4], displ[4];
MPI_Get_address ( &(sendNonZeros[0] ), addr+0);
MPI_Get_address ( &(sendNonZeros[0].col ), addr+1);
MPI_Get_address ( &(sendNonZeros[0].ownerRank), addr+2);
MPI_Get_address ( &(sendNonZeros[0].val ), addr+3);
displ[0] = 0;
displ[1] = addr[1] - addr[0];
displ[2] = addr[2] - addr[0];
displ[3] = addr[3] - addr[0];
MPI_Type_create_struct (4, blength, displ, dtype, &MPI_NONZERO_T);
MPI_Type_commit (&MPI_NONZERO_T);
// count how many non-zeros to send to each process
for(dlong n=0;n<cnt;++n)
AsendCounts[sendNonZeros[n].ownerRank]++;
// sort by row ordering
qsort(sendNonZeros, cnt, sizeof(nonZero_t), parallelCompareRowColumn);
// find how many nodes to expect (should use sparse version)
MPI_Alltoall(AsendCounts, 1, MPI_INT, ArecvCounts, 1, MPI_INT, mesh->comm);
// find send and recv offsets for gather
*nnz = 0;
for(int r=0;r<mesh->size;++r){
AsendOffsets[r+1] = AsendOffsets[r] + AsendCounts[r];
ArecvOffsets[r+1] = ArecvOffsets[r] + ArecvCounts[r];
*nnz += ArecvCounts[r];
}
*A = (nonZero_t*) calloc(*nnz, sizeof(nonZero_t));
// determine number to receive
MPI_Alltoallv(sendNonZeros, AsendCounts, AsendOffsets, MPI_NONZERO_T,
(*A), ArecvCounts, ArecvOffsets, MPI_NONZERO_T,
mesh->comm);
// sort received non-zero entries by row block (may need to switch compareRowColumn tests)
qsort((*A), *nnz, sizeof(nonZero_t), parallelCompareRowColumn);
// compress duplicates
cnt = 0;
for(dlong n=1;n<*nnz;++n){
if((*A)[n].row == (*A)[cnt].row &&
(*A)[n].col == (*A)[cnt].col){
(*A)[cnt].val += (*A)[n].val;
}
else{
++cnt;
(*A)[cnt] = (*A)[n];
}
}
if (*nnz) cnt++;
*nnz = cnt;
if(mesh->rank==0) printf("done.\n");
MPI_Barrier(mesh->comm);
MPI_Type_free(&MPI_NONZERO_T);
free(sendNonZeros);
free(globalNumbering); free(globalOwners);
free(AsendCounts);
free(ArecvCounts);
free(AsendOffsets);
free(ArecvOffsets);
}
|
openmp_scan.h | #include <omp.h>
template<typename T, typename R, typename C, typename S>
void openmp_scan(
size_t n,
T initial,
size_t tilesize,
R reduce,
C combine,
S scan
) {
if (n > 0) {
// Set t to the number of tiles that might be used, at most one tile
// per thread with no tile smaller than the requested tilesize.
size_t t = std::min( size_t(omp_get_max_threads()), (n-1)/tilesize+1 );
// Allocate space to hold the reduction value of each tile.
temp_space<T> r(t);
// Request one thread per tile.
#pragma omp parallel num_threads(t)
{
// Find out how threads were actually delivered, which may be
// fewer than the requested number.
size_t p = omp_get_num_threads();
// Recompute tilesize so there is one tile per actual thread.
tilesize = (n+p-1)/p;
// Set m to index of last tile
size_t m = p-1;
#pragma omp for
// Set r[i] to reduction of the ith tile
for ( size_t i = 0; i <= m; ++i )
r[i] = reduce(i*tilesize, i==m ? n-m*tilesize : tilesize);
#pragma omp single
// Use single thread to do in-place exclusive scan on r.
for ( size_t i = 0; i <= m; ++i ) {
T tmp = r[i];
r[i] = initial;
initial = combine(initial,tmp);
}
#pragma omp for
// Do scan over each tile, using r[i] as initial value.
for ( size_t i = 0; i <= m; ++i )
scan(i*tilesize, i==m ? n-m*tilesize : tilesize, r[i]);
}
}
}
|
Example_target_update.1.c | /*
* @@name: target_update.1c
* @@type: C
* @@compilable: yes
* @@linkable: no
* @@expect: success
* @@expect: success
* @@version: omp_4.0
*/
extern void init(float *, float *, int);
extern void init_again(float *, float *, int);
extern void output(float *, int);
void vec_mult(float *p, float *v1, float *v2, int N)
{
int i;
init(v1, v2, N);
#pragma omp target data map(to: v1[:N], v2[:N]) map(from: p[0:N])
{
#pragma omp target
#pragma omp parallel for
for (i=0; i<N; i++)
p[i] = v1[i] * v2[i];
init_again(v1, v2, N);
#pragma omp target update to(v1[:N], v2[:N])
#pragma omp target
#pragma omp parallel for
for (i=0; i<N; i++)
p[i] = p[i] + (v1[i] * v2[i]);
}
output(p, N);
}
|
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 <stdlib.h>
#include <math.h>
#include <phonoc_utils.h>
#include <phonoc_const.h>
#include <phonoc_array.h>
#include <phonon3_h/reciprocal_to_normal.h>
#include <lapack_wrapper.h>
#ifdef MEASURE_R2N
#include <unistd.h>
#include <time.h>
#endif
static lapack_complex_double fc3_sum_in_reciprocal_to_normal
(const size_t bi0,
const size_t bi1,
const size_t bi2,
const lapack_complex_double *eigvecs0,
const lapack_complex_double *eigvecs1,
const lapack_complex_double *eigvecs2,
const lapack_complex_double *fc3_reciprocal,
const double *masses,
const size_t num_atom);
static double get_fc3_sum
(const size_t j,
const size_t k,
const size_t bi,
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 lapack_complex_double *fc3_reciprocal,
const double *masses,
const size_t num_atom,
const double cutoff_frequency);
void reciprocal_to_normal_squared
(double *fc3_normal_squared,
PHPYCONST int (*g_pos)[4],
const size_t 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 int *band_indices,
const size_t num_band0,
const size_t num_band,
const double cutoff_frequency,
const int openmp_at_bands)
{
size_t i, num_atom;
#ifdef MEASURE_R2N
double loopTotalCPUTime, loopTotalWallTime;
time_t loopStartWallTime;
clock_t loopStartCPUTime;
#endif
num_atom = num_band / 3;
#ifdef MEASURE_R2N
loopStartWallTime = time(NULL);
loopStartCPUTime = clock();
#endif
#pragma omp parallel for if (openmp_at_bands)
for (i = 0; i < num_g_pos; i++) {
if (freqs0[band_indices[g_pos[i][0]]] > cutoff_frequency) {
fc3_normal_squared[g_pos[i][3]] = get_fc3_sum(g_pos[i][1],
g_pos[i][2],
band_indices[g_pos[i][0]],
freqs0,
freqs1,
freqs2,
eigvecs0,
eigvecs1,
eigvecs2,
fc3_reciprocal,
masses,
num_atom,
cutoff_frequency);
}
}
#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
}
static double get_fc3_sum
(const size_t j,
const size_t k,
const size_t bi,
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 lapack_complex_double *fc3_reciprocal,
const double *masses,
const size_t num_atom,
const double cutoff_frequency)
{
double fff, sum_real, sum_imag;
lapack_complex_double fc3_sum;
if (freqs1[j] > cutoff_frequency && freqs2[k] > cutoff_frequency) {
fff = freqs0[bi] * freqs1[j] * freqs2[k];
fc3_sum = fc3_sum_in_reciprocal_to_normal
(bi, j, k,
eigvecs0, eigvecs1, eigvecs2,
fc3_reciprocal,
masses,
num_atom);
sum_real = lapack_complex_double_real(fc3_sum);
sum_imag = lapack_complex_double_imag(fc3_sum);
return (sum_real * sum_real + sum_imag * sum_imag) / fff;
} else {
return 0;
}
}
static lapack_complex_double fc3_sum_in_reciprocal_to_normal
(const size_t bi0,
const size_t bi1,
const size_t bi2,
const lapack_complex_double *eigvecs0,
const lapack_complex_double *eigvecs1,
const lapack_complex_double *eigvecs2,
const lapack_complex_double *fc3_reciprocal,
const double *masses,
const size_t num_atom)
{
size_t baseIndex, index_l, index_lm, i, j, k, l, m, n;
double sum_real, sum_imag, mmm, mass_l, mass_lm;
lapack_complex_double eig_prod, eig_prod1;
sum_real = 0;
sum_imag = 0;
for (l = 0; l < num_atom; l++) {
mass_l = masses[l];
index_l = l * num_atom * num_atom * 27;
for (m = 0; m < num_atom; m++) {
mass_lm = mass_l * masses[m];
index_lm = index_l + m * num_atom * 27;
for (i = 0; i < 3; i++) {
for (j = 0; j < 3; j++) {
eig_prod1 = phonoc_complex_prod
(eigvecs0[(l * 3 + i) * num_atom * 3 + bi0],
eigvecs1[(m * 3 + j) * num_atom * 3 + bi1]);
for (n = 0; n < num_atom; n++) {
mmm = 1.0 / sqrt(mass_lm * masses[n]);
baseIndex = index_lm + n * 27 + i * 9 + j * 3;
for (k = 0; k < 3; k++) {
eig_prod = phonoc_complex_prod
(eig_prod1, eigvecs2[(n * 3 + k) * num_atom * 3 + bi2]);
eig_prod = phonoc_complex_prod
(eig_prod, fc3_reciprocal[baseIndex + k]);
sum_real += lapack_complex_double_real(eig_prod) * mmm;
sum_imag += lapack_complex_double_imag(eig_prod) * mmm;
}
}
}
}
}
}
return lapack_make_complex_double(sum_real, sum_imag);
}
|
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