add print and sprint tensor and split dim end tensor

This commit is contained in:
2024-02-20 01:20:15 +01:00
parent ede9ce4d59
commit cdc4ddf373
8 changed files with 588 additions and 52 deletions
+266 -4
View File
@@ -17,7 +17,7 @@
//#include "permutation_t/permutation_t.h"
#include "tensor_t/tensor_t.h"
#define VALGRIND_ 0
#define VALGRIND_ 1
TEST(rank){
endian =true;
@@ -42,9 +42,10 @@ void print_tensor_float(tensor_TYPE_FLOAT *M, char *msg){
LOG("================= %s ===============\n",msg);
#if VALGRIND_
for(size_t i=0; i<M->dim->rank;++i)
/*for(size_t i=0; i<M->dim->rank;++i)
LOG("[%ld]: %f ",i,M->x[i]);
*/
print_tensor_msg_TYPE_FLOAT(M,msg);
#endif
LOG("%s","\n");
}
@@ -53,9 +54,11 @@ void print_tensor_float(tensor_TYPE_FLOAT *M, char *msg){
void print_tensor_double(tensor_TYPE_DOUBLE *M, char *msg){
LOG("================= %s ===============\n",msg);
#if VALGRIND_
/*
for(size_t i=0; i<M->dim->rank;++i)
LOG("[%ld]: %lf ",i,M->x[i]);
*/
print_tensor_msg_TYPE_DOUBLE(M,msg);
#endif
LOG("%s","\n");
}
@@ -260,6 +263,201 @@ TEST(tensorSubtail ){
free_tensor_TYPE_FLOAT(s2t);
}
TEST(randomInit){
dimension *d0=create_dim(3);
d0->perm[0]=4;
d0->perm[1]=3;
d0->perm[2]=5;
updateRankDim(d0);
tensor_TYPE_FLOAT *M0 = CREATE_TENSOR_TYPE_FLOAT(d0);
LOG("M0->dim->rank = %ld\n",M0->dim->rank);
init_random_x_TYPE_FLOAT(M0,2.7,5.4,50001);
print_tensor_float(M0, "M0 random");
free_tensor_TYPE_FLOAT(M0);
}
TEST(printT_init_false){
endian=false;
dimension *d0=create_dim(3);
d0->perm[0]=2;
d0->perm[1]=3;
d0->perm[2]=4;
updateRankDim(d0);
tensor_TYPE_FLOAT *M0 = CREATE_TENSOR_TYPE_FLOAT(d0);
LOG("M0->dim->rank = %ld\n",M0->dim->rank);
//init_random_x_TYPE_FLOAT(M0,2,5,50);
for(size_t i=0; i<M0->dim->rank;++i) M0->x[i]=i*0.1 +1;
// print_tensor_float(M0, "M0 ");
print_tensor_msg_TYPE_FLOAT(M0, "M0 ");
free_tensor_TYPE_FLOAT(M0);
}
TEST(printT_Init_true){
endian=true;
dimension *d0=create_dim(3);
d0->perm[0]=2;
d0->perm[1]=3;
d0->perm[2]=4;
updateRankDim(d0);
tensor_TYPE_FLOAT *M0 = CREATE_TENSOR_TYPE_FLOAT(d0);
LOG("M0->dim->rank = %ld\n",M0->dim->rank);
//init_random_x_TYPE_FLOAT(M0,2,5,50);
for(size_t i=0; i<M0->dim->rank;++i) M0->x[i]=i*0.1 +1;
// print_tensor_float(M0, "M0 ");
print_tensor_msg_TYPE_FLOAT(M0, "M0 ");
free_tensor_TYPE_FLOAT(M0);
}
TEST(sprinttens){
dimension *d0=create_dim(3);
d0->perm[0]=4;
d0->perm[1]=3;
d0->perm[2]=2;
updateRankDim(d0);
tensor_TYPE_DOUBLE *M0 = CREATE_TENSOR_TYPE_DOUBLE(d0);
LOG("M0->dim->rank = %ld\n",M0->dim->rank);
init_random_x_TYPE_DOUBLE(M0,2.7,5.4,50001);
//print_tensor_double(M0, "test print M0");
char *tensCont = NULL;
size_t nbChar = sprint_tensor_TYPE_DOUBLE(&tensCont, M0, false);
LOG(" avec Sprint_tensor sans index, M0 est : \n%s \n, il y a %ld charactères\n",tensCont, nbChar);
nbChar = sprint_tensor_TYPE_DOUBLE(&tensCont, M0, true);
LOG(" avec Sprint_tensor avec index, M0 est : \n%s \n, il y a %ld charactères\n",tensCont, nbChar);
endian=false;
nbChar = sprint_tensor_TYPE_DOUBLE(&tensCont, M0, true);
LOG(" avec Sprint_tensor avec index et endian=false, M0 est : \n%s \n, il y a %ld charactères\n",tensCont, nbChar);
free(tensCont);
free_tensor_TYPE_DOUBLE(M0);
}
#if 1
TEST(Split_randomInit){
dimension *d0=create_dim(3);
d0->perm[0]=4;
d0->perm[1]=3;
d0->perm[2]=5;
updateRankDim(d0);
tensor_TYPE_FLOAT *M0 = CREATE_TENSOR_TYPE_FLOAT(d0);
LOG("M0->dim->rank = %ld\n",M0->dim->rank);
init_random_x_TYPE_FLOAT(M0,2.7,5.4,50001);
print_tensor_float(M0, "M0 random");
print_tensor_msg_TYPE_FLOAT(M0, "M0 random");
tensor_TYPE_FLOAT *Tpart1=NULL, *Tpart2=NULL;
split_tensor_TYPE_FLOAT(M0,&Tpart1,&Tpart2, 1, 2);
print_tensor_float(Tpart1, " Tpart1 1");
print_tensor_msg_TYPE_FLOAT(Tpart1, " Tpart1 1");
print_tensor_float(Tpart2, "Tpart2 ..");
print_tensor_msg_TYPE_FLOAT(Tpart2, "Tpart2 ..");
printDebug_dimension(Tpart1->dim,"dim part1 ");
printDebug_dimension(Tpart2->dim,"dim part2 ");
printDebug_dimension(M0->dim,"dim root ");
free_tensor_TYPE_FLOAT(M0);
free(Tpart1->dim);
free(Tpart2->dim);
free(Tpart1);
free(Tpart2);
}
#endif
#if 1
TEST(Split_randomInit){
dimension *d0=create_dim(3);
d0->perm[0]=4;
d0->perm[1]=3;
d0->perm[2]=5;
updateRankDim(d0);
tensor_TYPE_FLOAT *M0 = CREATE_TENSOR_TYPE_FLOAT(d0);
LOG("M0->dim->rank = %ld\n",M0->dim->rank);
init_random_x_TYPE_FLOAT(M0,2.7,5.4,50001);
print_tensor_float(M0, "M0 random");
tensor_TYPE_FLOAT *Tpart1=NULL, *Tpart2=NULL;
split_tensor_TYPE_FLOAT(M0,&Tpart1,&Tpart2, 2, 1);
print_tensor_float(Tpart1, " Tpart1 1");
print_tensor_float(Tpart2, "Tpart2 ..");
printDebug_dimension(Tpart1->dim,"dim part1 ");
printDebug_dimension(Tpart2->dim,"dim part2 ");
printDebug_dimension(M0->dim,"dim root ");
free_tensor_TYPE_FLOAT(M0);
free(Tpart1->dim);
free(Tpart2->dim);
free(Tpart1);
free(Tpart2);
}
#endif
TEST(tensorProd ){
dimension *d0=create_dim(3);
dimension *d1=create_dim(2);
@@ -620,6 +818,70 @@ TEST(Pthread_tensorContractnPro2d_TYPE_DOUBLE2 ){
free_tensor_TYPE_DOUBLE(M1);
}
TEST(contract_dim1){
dimension *d0=create_dim(3);
dimension *d1=create_dim(1);
#if VALGRIND_
d0->perm[0]=5;
d0->perm[1]=2; //3;
d0->perm[2]=3;
d1->perm[0]=3;
#else
d0->perm[0]=125;
d0->perm[1]=52; //3;
d0->perm[2]=63;
d1->perm[0]=63;
#endif
updateRankDim(d0);
updateRankDim(d1);
tensor_TYPE_DOUBLE *M0 = CREATE_TENSOR_TYPE_DOUBLE(d0);
tensor_TYPE_DOUBLE *M1 = CREATE_TENSOR_TYPE_DOUBLE(d1);
LOG("M0->dim->rank = %ld\n",M0->dim->rank);
LOG("M1->dim->rank = %ld\n",M1->dim->rank);
for(size_t i=0; i<M0->dim->rank;++i) M0->x[i]=i*0.1 +1;
for(size_t i=0; i<M1->dim->rank;++i) M1->x[i]=i*0.003 + 2;
print_tensor_double(M0,"M0");
print_tensor_double(M1,"M1");
tensor_TYPE_DOUBLE *M;
tensor_TYPE_DOUBLE *MnO;
size_t nbthread = 5;
tensorContractnProd_TYPE_DOUBLE(&M, M0,M1,1);
//print_tensor_double(M,"M");
//cl_tensorContractnProd_TYPE_DOUBLE(&MnO, M0,M1,1);
tensorContractnProdThread_TYPE_DOUBLE(&MnO, M0,M1,1,nbthread);
print_tensor_double(MnO,"MnO");
printDebug_dimension(M0->dim," M0 dimension ");
printDebug_dimension(M1->dim," M1 dimension ");
printDebug_dimension(M->dim," M dimension ");
// for(size_t i=0;i<M->dim->rank;++i)
// EXPECT_EQ_TYPE_DOUBLE(M->x[i],MnO->x[i]);
EXPECT_ARRAY_EQ_TYPE_DOUBLE(M->x,M->dim->rank,MnO->x,MnO->dim->rank);
free_tensor_TYPE_DOUBLE(M);
free_tensor_TYPE_DOUBLE(MnO);
free_tensor_TYPE_DOUBLE(M0);
free_tensor_TYPE_DOUBLE(M1);
}
TEST(Pthread_tensorContractnProd_TYPE_DOUBLE2 ){
dimension *d0=create_dim(3);
dimension *d1=create_dim(3);