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add sub {head,tail} tensors, update tensor prod with endian option

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fanasina
2024-02-02 21:19:11 +01:00
parent e195aee3b8
commit 2313cd13d9
4 changed files with 182 additions and 3 deletions
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dimension_t/test/is_good.c
+17
View File
@@ -51,6 +51,23 @@ TEST(SubDim){
}
TEST(SubDim){
dimension *D=create_dim(4);
D->perm[0]=2;
D->perm[1]=3;
D->perm[2]=5;
D->perm[3]=6;
dimension *d_head2 = sub_dim_head(D,2);
EXPECT_EQ(d_head2->rank, 2*3);
dimension *d_tail2 = sub_dim_tail(D,2);
EXPECT_EQ(d_tail2->rank, 5*6);
}
TEST(Coord_linear){
dimension *D=create_dim(4);
tensor_t/src/tensor_t/tensor_t.c
+62
View File
@@ -33,6 +33,53 @@ void printArraySzt(size_t *a, size_t sz,char *msg){
return r_tens;\
}\
\
tensor_##type * sub_tensor_head_##type(tensor_##type *rootens, size_t minuSubdim, size_t rankInDim){\
dimension *rdim= rootens->dim;\
dimension *dS_t = sub_dim_tail(rdim,rdim->size - minuSubdim);\
if(rankInDim < dS_t->rank){\
dimension *dS_h = sub_dim_head(rdim,minuSubdim);\
tensor_##type *ret_ens = malloc(sizeof(tensor_##type));\
ret_ens->dim = dS_h;\
/*ret_ens->x = (rootens->x)+rankInDim*dS_t->rank;*/\
if(endian){\
ret_ens->x = malloc(sizeof(type)*dS_h->rank);\
for(size_t i=0; i<dS_h->rank; ++i){\
ret_ens->x[i]=rootens->x[i*dS_t->rank + rankInDim];\
/*printf("%ld: [i:%ld] | %ld : [%ld ]\n",dS_t->rank, i,dS_h->rank,i*dS_h->rank + rankInDim);*/\
\
}\
}else{\
ret_ens->x = (rootens->x)+rankInDim*dS_h->rank;\
\
}\
return ret_ens;\
}\
return NULL;\
}\
\
tensor_##type * sub_tensor_tail_##type(tensor_##type *rootens, size_t minuSubdim, size_t rankInDim){\
dimension *rdim= rootens->dim;\
dimension *dS_h = sub_dim_head(rdim,rdim->size - minuSubdim);\
if(rankInDim < dS_h->rank){\
dimension *dS_t = sub_dim_tail(rdim,minuSubdim);\
tensor_##type *ret_ens = malloc(sizeof(tensor_##type));\
ret_ens->dim = dS_t;\
if(endian==false){\
ret_ens->x = malloc(sizeof(type)*dS_t->rank);\
for(size_t i=0; i<dS_t->rank; ++i){\
ret_ens->x[i]=rootens->x[i*dS_h->rank + rankInDim];\
/*printf("%ld: [i:%ld] | %ld : [%ld ]\n",dS_t->rank, i,dS_h->rank,i*dS_h->rank + rankInDim);*/\
\
}\
}else{\
ret_ens->x = (rootens->x)+rankInDim*dS_t->rank;\
\
}\
return ret_ens;\
}\
return NULL;\
}\
\
void tensorProdNotOpt_##type(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1) { \
dimension *dd; \
add_dimension(&dd, M0->dim, M1->dim); \
@@ -65,7 +112,10 @@ void tensorProd_##type(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1)
size_t m_idx;\
for(size_t i=0; i<M0->dim->rank; ++i){\
for(size_t j=0; j<M1->dim->rank; ++j){\
if(endian)\
m_idx= i*M1->dim->rank + j ;\
else\
m_idx= i+M0->dim->rank * j ;\
M->x[m_idx]=M0->x[i]*M1->x[j];\
/*printf("[%ld|%ld:(%ld,%ld)]",x_idx++,m_idx,i,j);*/\
}\
@@ -133,8 +183,14 @@ void tensorContractnProd_##type(tensor_##type** MM, tensor_##type *M0, tensor_##
\
size_t a0_id, a1_id, n0_id, n1_id;\
for (size_t i = 0; i < M->dim->rank; i++) {\
if(endian){\
a0_id=i/dSub1->rank;\
a1_id=i%dSub1->rank;\
}\
else{\
a0_id=i%dSub0->rank;\
a1_id=i/dSub0->rank;\
}\
/*vCoordFromLin(coord, i, M->dim);\
subArray(coord0, coord, 0, len0, 0);\
subArray(coord1, coord, 0, len1, len0);\
@@ -142,8 +198,14 @@ void tensorContractnProd_##type(tensor_##type** MM, tensor_##type *M0, tensor_##
printf("i:%ld=> c1: %ld vs %ld \n",i,LineFromCoord(coord1,dSub1),a1_id);*/\
M->x[i] = 0;\
for (size_t k = 0; k < dM->rank; k++) {\
if(endian){\
n0_id= a0_id*dM->rank + k;\
n1_id= a1_id + dSub1->rank * k;\
}\
else{\
n0_id= a0_id + dSub0->rank * k;\
n1_id= a1_id*dM->rank + k;\
}\
M->x[i] += M0->x[n0_id] * M1->x[n1_id];\
/*vCoordFromLin(Koord, k, dM);\
concatArray(coordM0, coord0, Koord, 0, 0, len0, 0, contractionNumber);\
tensor_t/src/tensor_t/tensor_t.h
+2
View File
@@ -12,6 +12,8 @@ struct tensor_##type{\
};\
typedef struct tensor_##type tensor_##type;\
tensor_##type * CREATE_TENSOR_##type(dimension *dim); \
tensor_##type * sub_tensor_head_##type(tensor_##type *rootens, size_t minuSubdim, size_t rankInDim); \
tensor_##type * sub_tensor_tail_##type(tensor_##type *rootens, size_t minuSubdim, size_t rankInDim); \
void tensorProdNotOpt_##type(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1); \
void tensorProd_##type(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1); \
void tensorContractnProd_##type(tensor_##type **MM, tensor_##type *M0, tensor_##type *M1, size_t contractionNumber); \
tensor_t/test/is_good.c
+98
View File
@@ -31,6 +31,10 @@ TEST(rank){
}
void print_tensor_float(tensor_TYPE_FLOAT *M, char *msg){
if(M==NULL) {
LOG("empty tensor | %s ===============\n",msg);
return;
}
LOG("================= %s ===============\n",msg);
for(size_t i=0; i<M->dim->rank;++i)
LOG("[%ld]: %f ",i,M->x[i]);
@@ -47,6 +51,100 @@ void print_tensor_double(tensor_TYPE_DOUBLE *M, char *msg){
LOG("%s","\n");
}
TEST(tensorSubhead_ ){
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);
for(size_t i=0; i<M0->dim->rank;++i) M0->x[i]=i*0.1 +1;
endian=false;
size_t rnkId = 1;
tensor_TYPE_FLOAT *s2h = sub_tensor_head_TYPE_FLOAT(M0,1,rnkId);
print_tensor_float(M0, "M0 for sub");
print_tensor_float(s2h, "sub s2h of M0");
printDebug_dimension(M0->dim," M0 dimension ");
printDebug_dimension(s2h->dim," s2h dimension ");
//EXPECT_ARRAY_EQ_TYPE_FLOAT(M0->x,s2h->dim->rank,s2h->x,s2h->dim->rank);
for(size_t i1=0; i1<d0->perm[1];++i1){
for(size_t i0=0; i0<d0->perm[0];++i0){
printf("EXPECT_EQ_TYPE_FLOAT c0[%ld](%ld,%ld,%ld) : s[%ld](%ld,%ld) \n",LineFromCoord((size_t[]){i0,i1,rnkId},M0->dim),rnkId,i0,i1,LineFromCoord((size_t[]){i0,i1},s2h->dim),i0,i1);
EXPECT_EQ_TYPE_FLOAT(M0->x[LineFromCoord((size_t[]){i0,i1,rnkId},M0->dim)],s2h->x[LineFromCoord((size_t[]){i0,i1},s2h->dim)]);
}
}
}
TEST(tensorSubtail ){
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);
for(size_t i=0; i<M0->dim->rank;++i) M0->x[i]=i*0.1 +1;
tensor_TYPE_FLOAT *s1t = sub_tensor_tail_TYPE_FLOAT(M0,1,5);
print_tensor_float(M0, "M0 for sub");
print_tensor_float(s1t, "sub s2t of M0 from 5");
}
TEST(tensorSubtail ){
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);
for(size_t i=0; i<M0->dim->rank;++i) M0->x[i]=i*0.1 +1;
//endian=false;
size_t rnkId=3;
tensor_TYPE_FLOAT *s2t = sub_tensor_tail_TYPE_FLOAT(M0,1,rnkId);
print_tensor_float(M0, "M0 for sub");
print_tensor_float(s2t, "sub s2t of M0 from 3");
for(size_t i1=0; i1<d0->perm[1];++i1){
for(size_t i2=0; i2<d0->perm[2];++i2){
printf("EXPECT_EQ_TYPE_FLOAT c0[%ld](%ld,%ld,%ld) : s[%ld](%ld,%ld) \n",LineFromCoord((size_t[]){rnkId,i1,i2},M0->dim),rnkId,i1,i2,LineFromCoord((size_t[]){i1,i2},s2t->dim),i1,i2);
EXPECT_EQ_TYPE_FLOAT(M0->x[LineFromCoord((size_t[]){rnkId,i1,i2},M0->dim)],s2t->x[LineFromCoord((size_t[]){i1,i2},s2t->dim)]);
}
}
}
TEST(tensorProd ){
dimension *d0=create_dim(3);