fanasina/y_project
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity
Files
4bf32c6501c0411d8be0998dde499d39de6ff6c2
y_project/tensor_t/test/is_good.c
T

462 lines
10 KiB
C
Raw Blame History

#include <stdio.h>
#include <stdlib.h>
#include <stdbool.h>
// for sleep !
#ifdef __linux__
#include <unistd.h>
#elif _WIN32
#include <windows.h>
#endif
#include "ftest/ftest.h"
#include "ftest/ftest_array.h"
#include "fmock/fmock.h"
//#include "permutation_t/permutation_t.h"
#include "tensor_t/tensor_t.h"
#include "tensor_t/cl_tensor_t.h"
TEST(rank){
dimension *D=create_dim(4);
D->perm[0]=2;
D->perm[1]=3;
D->perm[2]=5;
D->perm[3]=6;
updateRankDim(D);
tensor_TYPE_FLOAT *tf = CREATE_TENSOR_TYPE_FLOAT(D);
EXPECT_EQ(tf->dim->rank, 180);
}
void print_tensor_float(tensor_TYPE_FLOAT *M, char *msg){
LOG("================= %s ===============\n",msg);
for(size_t i=0; i<M->dim->rank;++i)
LOG("[%ld]: %f ",i,M->x[i]);
LOG("%s","\n");
}
void print_tensor_double(tensor_TYPE_DOUBLE *M, char *msg){
LOG("================= %s ===============\n",msg);
for(size_t i=0; i<M->dim->rank;++i)
LOG("[%ld]: %lf ",i,M->x[i]);
LOG("%s","\n");
}
TEST(tensorProd ){
dimension *d0=create_dim(3);
dimension *d1=create_dim(2);
d0->perm[0]=2;
d0->perm[1]=3;
d0->perm[2]=2;
d1->perm[0]=2;
d1->perm[1]=3;
updateRankDim(d0);
updateRankDim(d1);
tensor_TYPE_FLOAT *M0 = CREATE_TENSOR_TYPE_FLOAT(d0);
tensor_TYPE_FLOAT *M1 = CREATE_TENSOR_TYPE_FLOAT(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_float(M0,"M0");
print_tensor_float(M1,"M1");
tensor_TYPE_FLOAT *M;
tensor_TYPE_FLOAT *Mn;
tensorProd_TYPE_FLOAT(&M,M0,M1);
tensorProdNotOpt_TYPE_FLOAT(&Mn,M0,M1);
LOG("M->dim->rank = %ld\n",M->dim->rank);
print_tensor_float(M,"M");
EXPECT_ARRAY_EQ_TYPE_FLOAT(M->x,M->dim->rank,Mn->x,Mn->dim->rank);
print_tensor_float(Mn,"Mn");
}
TEST(tensorContractnProd_TYPE_FLOAT ){
dimension *d0=create_dim(3);
dimension *d1=create_dim(2);
d0->perm[0]=2;
d0->perm[1]=3;
d0->perm[2]=2;
d1->perm[0]=2;
d1->perm[1]=3;
updateRankDim(d0);
updateRankDim(d1);
tensor_TYPE_FLOAT *M0 = CREATE_TENSOR_TYPE_FLOAT(d0);
tensor_TYPE_FLOAT *M1 = CREATE_TENSOR_TYPE_FLOAT(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_float(M0,"M0");
print_tensor_float(M1,"M1");
tensor_TYPE_FLOAT *M;
tensor_TYPE_FLOAT *MnO;
tensorContractnProd_TYPE_FLOAT(&M, M0,M1,1);
tensorContractnProdNotOpt_TYPE_FLOAT(&MnO, M0,M1,1);
print_tensor_float(M,"M");
print_tensor_float(MnO,"MnO");
// for(size_t i=0;i<M->dim->rank;++i)
// EXPECT_EQ_TYPE_FLOAT(M->x[i],MnO->x[i]);
EXPECT_ARRAY_EQ_TYPE_FLOAT(M->x,M->dim->rank,MnO->x,MnO->dim->rank);
}
TEST(tensorContractnProd_TYPE_FLOAT2 ){
dimension *d0=create_dim(3);
dimension *d1=create_dim(3);
d0->perm[0]=35;
d0->perm[1]=32; //3;
d0->perm[2]=23;
d1->perm[0]=32;
d1->perm[1]=23;//3;
d1->perm[2]=44;
updateRankDim(d0);
updateRankDim(d1);
tensor_TYPE_FLOAT *M0 = CREATE_TENSOR_TYPE_FLOAT(d0);
tensor_TYPE_FLOAT *M1 = CREATE_TENSOR_TYPE_FLOAT(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_float(M0,"M0");
// print_tensor_float(M1,"M1");
tensor_TYPE_FLOAT *M;
tensor_TYPE_FLOAT *MnO;
tensorContractnProd_TYPE_FLOAT(&M, M0,M1,2);
// print_tensor_float(M,"M");
tensorContractnProdNotOpt_TYPE_FLOAT(&MnO, M0,M1,2);
// print_tensor_float(MnO,"MnO");
// for(size_t i=0;i<M->dim->rank;++i)
// EXPECT_EQ_TYPE_FLOAT(M->x[i],MnO->x[i]);
//EXPECT_ARRAY_EQ_TYPE_FLOAT(M->x,M->dim->rank,MnO->x,MnO->dim->rank);
}
TEST(cl_tensorContractnProd_TYPE_FLOAT2 ){
dimension *d0=create_dim(3);
dimension *d1=create_dim(3);
d0->perm[0]=35;
d0->perm[1]=32; //3;
d0->perm[2]=23;
d1->perm[0]=32;
d1->perm[1]=23;//3;
d1->perm[2]=44;
updateRankDim(d0);
updateRankDim(d1);
tensor_TYPE_FLOAT *M0 = CREATE_TENSOR_TYPE_FLOAT(d0);
tensor_TYPE_FLOAT *M1 = CREATE_TENSOR_TYPE_FLOAT(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_float(M0,"M0");
// print_tensor_float(M1,"M1");
tensor_TYPE_FLOAT *M;
tensor_TYPE_FLOAT *MnO;
tensorContractnProdNotOpt_TYPE_FLOAT(&M, M0,M1,2);
// print_tensor_float(M,"M");
cl_tensorContractnProd_TYPE_FLOAT(&MnO, M0,M1,2);
// print_tensor_float(MnO,"MnO");
// for(size_t i=0;i<M->dim->rank;++i)
// EXPECT_EQ_TYPE_FLOAT(M->x[i],MnO->x[i]);
//EXPECT_ARRAY_EQ_TYPE_FLOAT(M->x,M->dim->rank,MnO->x,MnO->dim->rank);
}
TEST(cl_tensorContractnProd_TYPE_DOUBLE2 ){
dimension *d0=create_dim(3);
dimension *d1=create_dim(3);
d0->perm[0]=125;
d0->perm[1]=52; //3;
d0->perm[2]=63;
d1->perm[0]=52;
d1->perm[1]=63;//3;
d1->perm[2]=54;
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;
tensorContractnProdNotOpt_TYPE_DOUBLE(&M, M0,M1,2);
//tensorContractnProd_TYPE_DOUBLE(&M, M0,M1,2);
//print_tensor_double(M,"M");
cl_tensorContractnProd_TYPE_DOUBLE(&MnO, M0,M1,2);
//print_tensor_double(MnO,"MnO");
// 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);
}
TEST(tensorContractnProd_TYPE_DOUBLE2 ){
dimension *d0=create_dim(3);
dimension *d1=create_dim(3);
d0->perm[0]=125;
d0->perm[1]=52; //3;
d0->perm[2]=63;
d1->perm[0]=52;
d1->perm[1]=63;//3;
d1->perm[2]=54;
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;
tensorContractnProd_TYPE_DOUBLE(&M, M0,M1,2);
//print_tensor_double(M,"M");
//cl_tensorContractnProd_TYPE_DOUBLE(&MnO, M0,M1,2);
tensorContractnProdNotOpt_TYPE_DOUBLE(&MnO, M0,M1,2);
//print_tensor_double(MnO,"MnO");
// 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);
}
TEST(TensorProdCL){
dimension *d0=create_dim(3);
dimension *d1=create_dim(2);
d0->perm[0]=2;
d0->perm[1]=3;
d0->perm[2]=2;
d1->perm[0]=2;
d1->perm[1]=3;
updateRankDim(d0);
updateRankDim(d1);
tensor_TYPE_FLOAT *M0 = CREATE_TENSOR_TYPE_FLOAT(d0);
tensor_TYPE_FLOAT *M1 = CREATE_TENSOR_TYPE_FLOAT(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_float(M0,"M0");
print_tensor_float(M1,"M1");
tensor_TYPE_FLOAT *M;
tensor_TYPE_FLOAT *Mn;
tensorProd_TYPE_FLOAT(&M,M0,M1);
cl_tensorProd_TYPE_FLOAT(&Mn,M0,M1);
LOG("M->dim->rank = %ld\n",M->dim->rank);
print_tensor_float(M,"M");
EXPECT_ARRAY_EQ_TYPE_FLOAT(M->x,M->dim->rank,Mn->x,Mn->dim->rank);
print_tensor_float(Mn,"Mn");
}
TEST(VS_cl_tensorContractnProd_TYPE_DOUBLE2 ){
dimension *d0=create_dim(3);
dimension *d1=create_dim(3);
d0->perm[0]=125;
d0->perm[1]=52; //3;
d0->perm[2]=63;
d1->perm[0]=52;
d1->perm[1]=63;//3;
d1->perm[2]=154;
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;
//tensorContractnProdNotOpt_TYPE_DOUBLE(&M, M0,M1,2);
//tensorContractnProd_TYPE_DOUBLE(&M, M0,M1,2);
//print_tensor_double(M,"M");
cl_tensorContractnProd_TYPE_DOUBLE(&MnO, M0,M1,2);
//print_tensor_double(MnO,"MnO");
// 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);
}
TEST(VStensorContractnProd_TYPE_DOUBLE2 ){
dimension *d0=create_dim(3);
dimension *d1=create_dim(3);
d0->perm[0]=125;
d0->perm[1]=52; //3;
d0->perm[2]=63;
d1->perm[0]=52;
d1->perm[1]=63;//3;
d1->perm[2]=154;
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;
tensorContractnProd_TYPE_DOUBLE(&M, M0,M1,2);
//print_tensor_double(M,"M");
//cl_tensorContractnProd_TYPE_DOUBLE(&MnO, M0,M1,2);
//tensorContractnProdNotOpt_TYPE_DOUBLE(&MnO, M0,M1,2);
//print_tensor_double(MnO,"MnO");
// 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);
}
int main(int argc, char **argv){
run_all_tests_args(argc, argv);
return 0;
}
Reference in New Issue View Git Blame Copy Permalink