fanasina/y_project
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

add test, I notice that if we increase parallel tests (-p 4 form me) it was less precision in gpu (cl) calculation: some tests failed

Browse Source
This commit is contained in:
fanasina
2024-02-02 23:30:11 +01:00
parent 7dd749f85e
commit 5fc1681e19
1 changed files with 88 additions and 1 deletions
Download Patch File Download Diff File Expand all files Collapse all files
tensor_t/test_cl/is_good.c
+88 -1
View File
@@ -19,7 +19,6 @@
#include "tensor_t/cl_tensor_t.h" #include "tensor_t/cl_tensor_t.h"
TEST(rank){ TEST(rank){
endian=false;
dimension *D=create_dim(4); dimension *D=create_dim(4);
D->perm[0]=2; D->perm[0]=2;
D->perm[1]=3; D->perm[1]=3;
@@ -537,6 +536,94 @@ TEST(tensorProd_vs2d ){
//print_tensor_float(Mn,"Mn"); //print_tensor_float(Mn,"Mn");
} }
TEST(tensorProd_vs2d_Endian ){
endian=false;
dimension *d0=create_dim(3);
dimension *d1=create_dim(2);
d0->perm[0]=24;
d0->perm[1]=32;
d0->perm[2]=2;
d1->perm[0]=64;
d1->perm[1]=16;
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;
cl_tensorProd_TYPE_FLOAT(&M,M0,M1);
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(tensorProd_vs2d_Endian ){
dimension *d0=create_dim(3);
dimension *d1=create_dim(2);
d0->perm[0]=24;
d0->perm[1]=32;
d0->perm[2]=2;
d1->perm[0]=64;
d1->perm[1]=24;
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);
//cl2d_tensorProd_TYPE_FLOAT(&Mn,M0,M1,24,24);
//cl2d_tensorProd_TYPE_FLOAT(&Mn,M0,M1,32,32);
cl2d_tensorProd_TYPE_FLOAT(&Mn,M0,M1,64,16);
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");
}
int main(int argc, char **argv){ int main(int argc, char **argv){