add print and sprint dim and tensor for debug

This commit is contained in:
2024-02-22 10:05:18 +01:00
parent cdc4ddf373
commit ccc3c3257b
5 changed files with 152 additions and 18 deletions
+53 -3
View File
@@ -173,10 +173,60 @@ void printDebug_dimension(dimension *d,char *msg){
printf("(%s)->size = %ld | (%s)->rank = %ld \n",msg,d->size,msg,d->rank); printf("(%s)->size = %ld | (%s)->rank = %ld \n",msg,d->size,msg,d->rank);
for(size_t i=0; i<d->size; ++i) for(size_t i=0; i<d->size; ++i)
printf("[%ld: %ld] |", i,d->perm[i]); printf("[%ld: %ld] |", i,d->perm[i]);
if(endian) /* if(endian)
printf("litle endian (true)\n"); printf("\nendian (true): the bigest index varies first, e.g: [x0,x1,x2,...,xn] xn is the bigest index\n");
else else
printf("litle endian (false) \n"); printf("\nendian (false): the lowest index varies first, e.g: [x0,x1,x2,...,xn] x0 is the lowest index\n");
*/
}
size_t sprint_dimension(char **dimContent, dimension *d){
if(*dimContent != NULL){
free(*dimContent);
*dimContent=NULL;
}
size_t nbch=6*d->size+40;
*dimContent = malloc(nbch);
//printf("nbCh=%ld\n",nbch);
char *val=NULL;
size_t cur=0;
char *dimSzCh="dim->size";
for(size_t i=0; i<strlen(dimSzCh);++i)
(*dimContent)[cur++]=dimSzCh[i];
(*dimContent)[cur++]='=';
val=TYPE_SIZE_T_TO_STR(d->size);
for(size_t c=0;c<strlen(val);++c)
(*dimContent)[cur++]=val[c];
free(val); val = NULL;
(*dimContent)[cur++]=' ';
(*dimContent)[cur++]='/';
(*dimContent)[cur++]=' ';
char *dimRkCh="dim->rank";
for(size_t i=0; i<strlen(dimRkCh);++i)
(*dimContent)[cur++]=dimRkCh[i];
(*dimContent)[cur++]='=';
val=TYPE_SIZE_T_TO_STR(d->rank);
for(size_t c=0;c<strlen(val);++c)
(*dimContent)[cur++]=val[c];
free(val); val = NULL;
(*dimContent)[cur++]=' ';
(*dimContent)[cur++]='\n';
(*dimContent)[cur++]='[';
for(size_t i=0; i<d->size;++i){
(*dimContent)[cur++]=' ';
val=TYPE_SIZE_T_TO_STR(d->perm[i]);
for(size_t c=0;c<strlen(val);++c)
(*dimContent)[cur++]=val[c];
free(val); val = NULL;
(*dimContent)[cur++]=',';
}
(*dimContent)[cur++]=']';
(*dimContent)[cur++]='\n';
(*dimContent)[cur++]='\0';
return cur;
} }
void updateRankDim(dimension *dim){ void updateRankDim(dimension *dim){
@@ -40,6 +40,7 @@ void add_dimension(dimension **d, dimension *d0, dimension *d1);
void min_dimension(dimension **d, dimension *d0, dimension *d1); void min_dimension(dimension **d, dimension *d0, dimension *d1);
void printDebug_dimension(dimension *d, char *msg); void printDebug_dimension(dimension *d, char *msg);
size_t sprint_dimension(char **dimContent, dimension *d);
void updateRankDim(dimension *dim); void updateRankDim(dimension *dim);
size_t LineFromCoord(size_t *coo, dimension *dim); size_t LineFromCoord(size_t *coo, dimension *dim);
+19
View File
@@ -161,6 +161,25 @@ TEST(Coord_linear){
free(coord); free(coord);
} }
TEST(sprint_dim){
dimension *D=create_dim(4);
D->perm[0]=2;
D->perm[1]=3;
D->perm[2]=5;
D->perm[3]=6;
updateRankDim(D);
char *dimSTR =NULL;
size_t nb=sprint_dimension(&dimSTR, D);
LOG(" nb char : %ld\n, dim print:\n%s\n",nb, dimSTR);
free_dimension(D);
free(dimSTR);
}
int main(int argc, char **argv){ int main(int argc, char **argv){
+14 -2
View File
@@ -343,9 +343,11 @@ void print_tensor_msg_##type(tensor_##type *T,char *msg) {\
if (endian ) {\ if (endian ) {\
begin = (T->dim->size) - 1; end = 0;\ begin = (T->dim->size) - 1; end = 0;\
iter = decr; cond = isGreatEqThan; \ iter = decr; cond = isGreatEqThan; \
printf("endian(=true): the bigest index varies first, e.g: [x0,x1,x2,...,xn] xn is the bigest index \n");\
}else{\ }else{\
begin = 0 ; end = (T->dim->size) - 1; \ begin = 0 ; end = (T->dim->size) - 1; \
iter = incr; cond = isLessEqThan; \ iter = incr; cond = isLessEqThan; \
printf("endian(=false): the lowest index varies first, e.g: [x0,x1,x2,...,xn] x0 is the lowest index \n");\
}\ }\
for(long int i=0;i<(T->dim)->rank;++i){\ for(long int i=0;i<(T->dim)->rank;++i){\
vCoordFromLin(coord,i,T->dim);\ vCoordFromLin(coord,i,T->dim);\
@@ -378,8 +380,8 @@ size_t sprint_tensor_##type(char **tensorContent,tensor_##type *T, bool withInde
free(*tensorContent);\ free(*tensorContent);\
*tensorContent = NULL; \ *tensorContent = NULL; \
}\ }\
size_t sz = ((T->dim)->rank)*(32+ withIndex * 5*(T->dim)->size + 9 );\ size_t sz = ((T->dim)->rank)*(32+ withIndex * 5*(T->dim)->size + 129 );\
printf("malloc %ld char\n",sz);\ /*printf("malloc %ld char\n",sz);*/\
*tensorContent = malloc(sz ) ;\ *tensorContent = malloc(sz ) ;\
size_t cur=0;\ size_t cur=0;\
long int *coord = malloc(sizeof(long int)*(T->dim)->size); \ long int *coord = malloc(sizeof(long int)*(T->dim)->size); \
@@ -390,9 +392,19 @@ size_t sprint_tensor_##type(char **tensorContent,tensor_##type *T, bool withInde
if (endian ) {\ if (endian ) {\
begin = (T->dim->size) - 1; end = 0;\ begin = (T->dim->size) - 1; end = 0;\
iter = decr; cond = isGreatEqThan; \ iter = decr; cond = isGreatEqThan; \
val=malloc(128);\
sprintf(val,"endian(=true): the bigest index varies first, e.g: [x0,x1,x2,...,xn] xn is the bigest index \n");\
for(size_t c=0;c<strlen(val);++c)\
(*tensorContent)[cur++]=val[c];\
free(val); val = NULL;\
}else{\ }else{\
begin = 0 ; end = (T->dim->size) - 1; \ begin = 0 ; end = (T->dim->size) - 1; \
iter = incr; cond = isLessEqThan; \ iter = incr; cond = isLessEqThan; \
val=malloc(128);\
sprintf(val,"endian(=false): the lowest index varies first, e.g: [x0,x1,x2,...,xn] x0 is the lowest index \n");\
for(size_t c=0;c<strlen(val);++c)\
(*tensorContent)[cur++]=val[c];\
free(val); val = NULL;\
}\ }\
for(long int i=0;i<(T->dim)->rank;++i){\ for(long int i=0;i<(T->dim)->rank;++i){\
vCoordFromLin(coord,i,T->dim);\ vCoordFromLin(coord,i,T->dim);\
+65 -13
View File
@@ -380,9 +380,9 @@ TEST(sprinttens){
TEST(Split_randomInit){ TEST(Split_randomInit){
dimension *d0=create_dim(3); dimension *d0=create_dim(3);
d0->perm[0]=4; d0->perm[0]=2;
d0->perm[1]=3; d0->perm[1]=3;
d0->perm[2]=5; d0->perm[2]=4;
updateRankDim(d0); updateRankDim(d0);
@@ -399,20 +399,22 @@ TEST(Split_randomInit){
tensor_TYPE_FLOAT *Tpart1=NULL, *Tpart2=NULL; tensor_TYPE_FLOAT *Tpart1=NULL, *Tpart2=NULL;
split_tensor_TYPE_FLOAT(M0,&Tpart1,&Tpart2, 1, 2); //split_tensor_TYPE_FLOAT(M0,&Tpart1,&Tpart2, 1, 2);
//split_tensor_TYPE_FLOAT(M0,&Tpart1,&Tpart2, 2, 3);
split_tensor_TYPE_FLOAT(M0,&Tpart1,&Tpart2, 1, 1);
print_tensor_float(Tpart1, " Tpart1 1"); print_tensor_float(Tpart1, " Tpart1 1");
print_tensor_msg_TYPE_FLOAT(Tpart1, " Tpart1 1"); //print_tensor_msg_TYPE_FLOAT(Tpart1, " Tpart1 1");
print_tensor_float(Tpart2, "Tpart2 .."); print_tensor_float(Tpart2, "Tpart2 ..");
print_tensor_msg_TYPE_FLOAT(Tpart2, "Tpart2 .."); //print_tensor_msg_TYPE_FLOAT(Tpart2, "Tpart2 ..");
printDebug_dimension(Tpart1->dim,"dim part1 "); // printDebug_dimension(Tpart1->dim,"dim part1 ");
printDebug_dimension(Tpart2->dim,"dim part2 "); // printDebug_dimension(Tpart2->dim,"dim part2 ");
printDebug_dimension(M0->dim,"dim root "); // printDebug_dimension(M0->dim,"dim root ");
free_tensor_TYPE_FLOAT(M0); free_tensor_TYPE_FLOAT(M0);
free(Tpart1->dim); free_dimension(Tpart1->dim);
free(Tpart2->dim); free_dimension(Tpart2->dim);
free(Tpart1); free(Tpart1);
free(Tpart2); free(Tpart2);
} }
@@ -421,6 +423,7 @@ TEST(Split_randomInit){
#if 1 #if 1
TEST(Split_randomInit){ TEST(Split_randomInit){
endian=false;
dimension *d0=create_dim(3); dimension *d0=create_dim(3);
d0->perm[0]=4; d0->perm[0]=4;
@@ -441,7 +444,9 @@ TEST(Split_randomInit){
tensor_TYPE_FLOAT *Tpart1=NULL, *Tpart2=NULL; tensor_TYPE_FLOAT *Tpart1=NULL, *Tpart2=NULL;
split_tensor_TYPE_FLOAT(M0,&Tpart1,&Tpart2, 2, 1); split_tensor_TYPE_FLOAT(M0,&Tpart1,&Tpart2, 2, 4);
//split_tensor_TYPE_FLOAT(M0,&Tpart1,&Tpart2, 0, 1);
//split_tensor_TYPE_FLOAT(M0,&Tpart1,&Tpart2, 2, 1);
print_tensor_float(Tpart1, " Tpart1 1"); print_tensor_float(Tpart1, " Tpart1 1");
print_tensor_float(Tpart2, "Tpart2 .."); print_tensor_float(Tpart2, "Tpart2 ..");
@@ -451,8 +456,55 @@ TEST(Split_randomInit){
printDebug_dimension(M0->dim,"dim root "); printDebug_dimension(M0->dim,"dim root ");
free_tensor_TYPE_FLOAT(M0); free_tensor_TYPE_FLOAT(M0);
free(Tpart1->dim); free_dimension(Tpart1->dim);
free(Tpart2->dim); free_dimension(Tpart2->dim);
free(Tpart1);
free(Tpart2);
}
#endif
#if 1
TEST(SplitOne_randomInit){
dimension *d0=create_dim(1);
d0->perm[0]=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(M0,2.7,5.4,50001);
print_tensor_float(M0, "M0 random");
tensor_TYPE_FLOAT *Tpart1=NULL, *Tpart2=NULL;
if(endian){
split_tensor_TYPE_FLOAT(M0,&Tpart1,&Tpart2, 0, 1);
}else{
split_tensor_TYPE_FLOAT(M0,&Tpart1,&Tpart2, 0, 3);
}
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 ");
for(size_t i=0;i<(Tpart1->dim)->rank;++i) Tpart1->x[i]=0;
print_tensor_float(Tpart1, "Tpart1 0");
print_tensor_float(M0, "M0 Tpart1 0");
free_tensor_TYPE_FLOAT(M0);
free_dimension(Tpart1->dim);
free_dimension(Tpart2->dim);
free(Tpart1); free(Tpart1);
free(Tpart2); free(Tpart2);
} }