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Implemented the new elementwise functions.

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This commit is contained in:
Elias Kohout
2023-09-15 19:22:43 +02:00
parent 79ed621ba2
commit 5ec1d9e73a
4 changed files with 85 additions and 28 deletions
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3
tensor.c
View File

@@ -4,7 +4,8 @@ tensor tensor_new(void)
{
/* Creates a new tensor struct and returns it.
*
* @return A tensor (pointer to memory for a _tensor struct)
* @return A tensor (pointer to memory for a _tensor struct), if an error
* occurs NULL is returned
*/
return calloc(1, sizeof(struct _tensor));
}

98
tensorfunc.c
View File

@@ -9,7 +9,10 @@ void tensor_fill(tensor t, dtype (*func)(void))
* no sidel effects.
*/
assert(!tensor_is_empty(t));
// TODO
for (uint32_t i = 0; i < t->num_elem; i++) {
t->elements[i] = func();
}
}
void tensor_inspect(const tensor t, void (*func)(dtype))
@@ -20,7 +23,10 @@ void tensor_inspect(const tensor t, void (*func)(dtype))
* @param func The function that is called with the values
*/
assert(!tensor_is_empty(t));
// TODO
for (uint32_t i = 0; i < t->num_elem; i++) {
func(t->elements[i]);
}
}
tensor tensor_map(const tensor t, dtype (*func)(dtype))
@@ -32,10 +38,20 @@ tensor tensor_map(const tensor t, dtype (*func)(dtype))
* @param func The map function that is called, it is expected to have no
* side effects
*
* @return The newly created tensor
* @return The newly created tensor, if it fails NULL is returned
*/
assert(!tensor_is_empty(t));
// TODO
tensor t2 = tensor_new();
if(t2 == NULL || !_tensor_set_size(t2, t->size, t->rank)) {
tensor_destroy(t2);
return NULL;
}
for (uint32_t i = 0; i < t->num_elem; i++) {
t2->elements[i] = func(t->elements[i]);
}
return t2;
}
void tensor_map_inplace(tensor t, dtype (*func)(dtype))
@@ -48,7 +64,10 @@ void tensor_map_inplace(tensor t, dtype (*func)(dtype))
* side effects
*/
assert(!tensor_is_empty(t));
// TODO
for (uint32_t i = 0; i < t->num_elem; i++) {
t->elements[i] = func(t->elements[i]);
}
}
tensor tensor_combine(const tensor t1, const tensor t2, dtype (*func)(dtype, dtype))
@@ -62,14 +81,30 @@ tensor tensor_combine(const tensor t1, const tensor t2, dtype (*func)(dtype, dty
* returns the result that is stored in the created tensor, it is
* expected to have no side effects
*
* @return The tensor with the result of the combination of t1 and t2
* @return The tensor with the result of the combination of t1 and t2, if an
* error occurs NULL is returned
*/
assert(!tensor_is_empty(t1));
assert(!tensor_is_empty(t2));
// TODO
tensor t3;
if (t1->rank != t2->rank) return NULL;
if (!tarray_uint32_equals(t1->size, t2->size, t1->rank)) return NULL;
t3 = tensor_new();
if(t3 == NULL || !_tensor_set_size(t3, t1->size, t1->rank)) {
tensor_destroy(t2);
return NULL;
}
for (uint32_t i = 0; i < t1->num_elem; i++) {
t3->elements[i] = func(t1->elements[i], t2->elements[i]);
}
return t3;
}
void tensor_combine_inplace(tensor t1, const tensor t2, dtype (*func)(dtype, dtype))
bool tensor_combine_inplace(tensor t1, const tensor t2, dtype (*func)(dtype, dtype))
{
/* Combines every value of two tensor and stores the result in the first of
* the tensors. t1 and t2 need to have the same shape.
@@ -79,11 +114,19 @@ void tensor_combine_inplace(tensor t1, const tensor t2, dtype (*func)(dtype, dty
* @param func The function that takes in the values of t1 and t2 and
* returns the result that is stored in t1, it is expected to have
* no side effects
*
* @return true if the operation was successful, false otherwise
*/
assert(!tensor_is_empty(t1));
assert(!tensor_is_empty(t2));
// TODO
if (t1->rank != t2->rank) return false;
if (!tarray_uint32_equals(t1->size, t2->size, t1->rank)) return false;
for (uint32_t i = 0; i < t1->num_elem; i++) {
t1->elements[i] = func(t1->elements[i], t2->elements[i]);
}
return true;
}
dtype _dtype_scalar_helper;
@@ -136,48 +179,61 @@ void tensor_div_scalar(tensor t, dtype scalar)
tensor_map_inplace(t, &_tensor_mul_scalar_helper);
}
void tensor_add_inplace(tensor t1, const tensor t2)
dtype _tensor_add_helper(dtype x, dtype y) { return DTYPE_ADD(x, y); }
dtype _tensor_sub_helper(dtype x, dtype y) { return DTYPE_SUB(x, y); }
dtype _tensor_mul_helper(dtype x, dtype y) { return DTYPE_MUL(x, y); }
dtype _tensor_div_helper(dtype x, dtype y) { return DTYPE_DIV(x, y); }
bool tensor_add_inplace(tensor t1, const tensor t2)
{
/* Adds the values of t2 onto the values of t1. t1 and t2 need to have the
* same shape.
*
* @param t1 The tensor on which the values of t2 are added
* @param t2 The tensor whose values are added
*
* @return true if the operation was successful, false otherwise
*/
// TODO
return tensor_combine_inplace(t1, t2, &_tensor_add_helper);
}
void tensor_sub_inplace(tensor t1, const tensor t2)
bool tensor_sub_inplace(tensor t1, const tensor t2)
{
/* Subtracts the values of t2 from the values of t1. t1 and t2 need to have
* the same shape.
*
* @param t1 The tensor from which the values of t2 are subtracted
* @param t2 The tensor whose values are subtracted
*
* @return true if the operation was successful, false otherwise
*/
// TODO
return tensor_combine_inplace(t1, t2, &_tensor_sub_helper);
}
void tensor_mul_inplace(tensor t1, const tensor t2)
bool tensor_mul_inplace(tensor t1, const tensor t2)
{
/* Multiplies the values of t2 onto t1 element wise. t1 and t2 need to
* have the same shape.
*
* @param t1 The tensor to multiply onto
* @param t2 The tensor to multiply with
*
* @return true if the operation was successful, false otherwise
*/
// TODO
return tensor_combine_inplace(t1, t2, &_tensor_mul_helper);
}
void tensor_div_inplace(tensor t1, const tensor t2)
bool tensor_div_inplace(tensor t1, const tensor t2)
{
/* Divides the values of t2 by the values of t1 element wise. t1 and t2
* need to have the same shape.
*
* @param t1 The tensor to devide
* @param t2 The tensor to devide by
*
* @return true if the operation was successful, false otherwise
*/
// TODO
return tensor_combine_inplace(t1, t2, &_tensor_div_helper);
}
tensor tensor_add(const tensor t1, const tensor t2)
@@ -190,7 +246,7 @@ tensor tensor_add(const tensor t1, const tensor t2)
*
* @return The result of the operation, NULL if an error occurs
*/
// TODO
return tensor_combine(t1, t2, &_tensor_add_helper);
}
tensor tensor_sub(const tensor t1, const tensor t2)
@@ -203,7 +259,7 @@ tensor tensor_sub(const tensor t1, const tensor t2)
*
* @return The result of the operation, NULL if an error occurs
*/
// TODO
return tensor_combine(t1, t2, &_tensor_sub_helper);
}
tensor tensor_mul(const tensor t1, const tensor t2)
@@ -216,7 +272,7 @@ tensor tensor_mul(const tensor t1, const tensor t2)
*
* @return The result of the operation, NULL if an error occurs
*/
// TODO
return tensor_combine(t1, t2, &_tensor_mul_helper);
}
tensor tensor_div(const tensor t1, const tensor t2)
@@ -229,5 +285,5 @@ tensor tensor_div(const tensor t1, const tensor t2)
*
* @return The result of the operation, NULL if an error occurs
*/
// TODO
return tensor_combine(t1, t2, &_tensor_div_helper);
}

10
tensorfunc.h
View File

@@ -10,17 +10,17 @@ tensor tensor_map(const tensor t, dtype (*func)(dtype));
void tensor_map_inplace(tensor t, dtype (*func)(dtype));
tensor tensor_combine(const tensor t1, const tensor t2, dtype (*func)(dtype, dtype));
void tensor_combine_inplace(tensor t1, const tensor t2, dtype (*func)(dtype, dtype));
bool tensor_combine_inplace(tensor t1, const tensor t2, dtype (*func)(dtype, dtype));
void tensor_add_scalar(tensor t, dtype scalar);
void tensor_sub_scalar(tensor t, dtype scalar);
void tensor_mul_scalar(tensor t, dtype scalar);
void tensor_div_scalar(tensor t, dtype scalar);
void tensor_add_inplace(tensor t1, const tensor t2);
void tensor_sub_inplace(tensor t1, const tensor t2);
void tensor_mul_inplace(tensor t1, const tensor t2);
void tensor_div_inplace(tensor t1, const tensor t2);
bool tensor_add_inplace(tensor t1, const tensor t2);
bool tensor_sub_inplace(tensor t1, const tensor t2);
bool tensor_mul_inplace(tensor t1, const tensor t2);
bool tensor_div_inplace(tensor t1, const tensor t2);
tensor tensor_add(const tensor t1, const tensor t2);
tensor tensor_sub(const tensor t1, const tensor t2);

2
tests/tensorfunc_test.c
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@@ -105,7 +105,7 @@ void tensor_test_sub_scalar(void)
tensor_add_inplace(t1, t2);
tensor_add_inplace(t1, t2);
tensor_sub_scalar(t3, 3.0);
tensor_sub_scalar(t1, 3.0);
tensor_assert_eq(t1, t3);