COMPMID-1084 Rework the way validation is performed for NHWC data layout
Change-Id: I00b95f560548da76718298b642c8166f92421097
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/129520
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele DiGiorgio <michele.digiorgio@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/tests/validation/Validation.h b/tests/validation/Validation.h
index 508fb02..ac3643e 100644
--- a/tests/validation/Validation.h
+++ b/tests/validation/Validation.h
@@ -137,19 +137,45 @@
}
template <typename T>
-bool compare_dimensions(const Dimensions<T> &dimensions1, const Dimensions<T> &dimensions2)
+bool compare_dimensions(const Dimensions<T> &dimensions1, const Dimensions<T> &dimensions2, const DataLayout &data_layout = DataLayout::NCHW)
{
- if(dimensions1.num_dimensions() != dimensions2.num_dimensions())
- {
- return false;
- }
+ ARM_COMPUTE_ERROR_ON(data_layout == DataLayout::UNKNOWN);
- for(unsigned int i = 0; i < dimensions1.num_dimensions(); ++i)
+ if(data_layout == DataLayout::NCHW)
{
- if(dimensions1[i] != dimensions2[i])
+ if(dimensions1.num_dimensions() != dimensions2.num_dimensions())
{
return false;
}
+
+ for(unsigned int i = 0; i < dimensions1.num_dimensions(); ++i)
+ {
+ if(dimensions1[i] != dimensions2[i])
+ {
+ return false;
+ }
+ }
+ }
+ else
+ {
+ // In case a 2D shape becomes 3D after permutation, the permuted tensor will have one dimension more and the first value will be 1
+ if((dimensions1.num_dimensions() != dimensions2.num_dimensions()) && ((dimensions1.num_dimensions() != (dimensions2.num_dimensions() + 1)) || (dimensions1.x() != 1)))
+ {
+ return false;
+ }
+
+ if((dimensions1[0] != dimensions2[2]) || (dimensions1[1] != dimensions2[0]) || (dimensions1[2] != dimensions2[1]))
+ {
+ return false;
+ }
+
+ for(unsigned int i = 3; i < dimensions1.num_dimensions(); ++i)
+ {
+ if(dimensions1[i] != dimensions2[i])
+ {
+ return false;
+ }
+ }
}
return true;
@@ -342,14 +368,14 @@
void validate(const IAccessor &tensor, const SimpleTensor<T> &reference, U tolerance_value, float tolerance_number, float absolute_tolerance_value)
{
// Validate with valid region covering the entire shape
- validate(tensor, reference, shape_to_valid_region(tensor.shape()), tolerance_value, tolerance_number, absolute_tolerance_value);
+ validate(tensor, reference, shape_to_valid_region(reference.shape()), tolerance_value, tolerance_number, absolute_tolerance_value);
}
template <typename T, typename U, typename = typename std::enable_if<std::is_integral<T>::value>::type>
void validate_wrap(const IAccessor &tensor, const SimpleTensor<T> &reference, U tolerance_value, float tolerance_number)
{
// Validate with valid region covering the entire shape
- validate_wrap(tensor, reference, shape_to_valid_region(tensor.shape()), tolerance_value, tolerance_number);
+ validate_wrap(tensor, reference, shape_to_valid_region(reference.shape()), tolerance_value, tolerance_number);
}
template <typename T, typename U>
@@ -367,7 +393,7 @@
}
ARM_COMPUTE_EXPECT_EQUAL(tensor.num_channels(), reference.num_channels(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(compare_dimensions(tensor.shape(), reference.shape()), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(compare_dimensions(tensor.shape(), reference.shape(), tensor.data_layout()), framework::LogLevel::ERRORS);
const int min_elements = std::min(tensor.num_elements(), reference.num_elements());
const int min_channels = std::min(tensor.num_channels(), reference.num_channels());
@@ -377,12 +403,18 @@
{
const Coordinates id = index2coord(reference.shape(), element_idx);
+ Coordinates target_id(id);
+ if(tensor.data_layout() == DataLayout::NHWC)
+ {
+ permute(target_id, PermutationVector(2U, 0U, 1U));
+ }
+
if(is_in_valid_region(valid_region, id))
{
// Iterate over all channels within one element
for(int c = 0; c < min_channels; ++c)
{
- const T &target_value = reinterpret_cast<const T *>(tensor(id))[c];
+ const T &target_value = reinterpret_cast<const T *>(tensor(target_id))[c];
const T &reference_value = reinterpret_cast<const T *>(reference(id))[c];
if(!compare<U>(target_value, reference_value, tolerance_value))
@@ -436,7 +468,7 @@
}
ARM_COMPUTE_EXPECT_EQUAL(tensor.num_channels(), reference.num_channels(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(compare_dimensions(tensor.shape(), reference.shape()), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(compare_dimensions(tensor.shape(), reference.shape(), tensor.data_layout()), framework::LogLevel::ERRORS);
const int min_elements = std::min(tensor.num_elements(), reference.num_elements());
const int min_channels = std::min(tensor.num_channels(), reference.num_channels());
@@ -446,12 +478,18 @@
{
const Coordinates id = index2coord(reference.shape(), element_idx);
+ Coordinates target_id(id);
+ if(tensor.data_layout() == DataLayout::NHWC)
+ {
+ permute(target_id, PermutationVector(2U, 0U, 1U));
+ }
+
if(is_in_valid_region(valid_region, id))
{
// Iterate over all channels within one element
for(int c = 0; c < min_channels; ++c)
{
- const T &target_value = reinterpret_cast<const T *>(tensor(id))[c];
+ const T &target_value = reinterpret_cast<const T *>(tensor(target_id))[c];
const T &reference_value = reinterpret_cast<const T *>(reference(id))[c];
bool equal = compare<U>(target_value, reference_value, tolerance_value);
@@ -518,7 +556,7 @@
}
ARM_COMPUTE_EXPECT_EQUAL(tensor.num_channels(), reference.num_channels(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(compare_dimensions(tensor.shape(), reference.shape()), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(compare_dimensions(tensor.shape(), reference.shape(), tensor.data_layout()), framework::LogLevel::ERRORS);
const int min_elements = std::min(tensor.num_elements(), reference.num_elements());
const int min_channels = std::min(tensor.num_channels(), reference.num_channels());
@@ -528,12 +566,18 @@
{
const Coordinates id = index2coord(reference.shape(), element_idx);
+ Coordinates target_id(id);
+ if(tensor.data_layout() == DataLayout::NHWC)
+ {
+ permute(target_id, PermutationVector(2U, 0U, 1U));
+ }
+
if(valid_mask[element_idx] == 1)
{
// Iterate over all channels within one element
for(int c = 0; c < min_channels; ++c)
{
- const T &target_value = reinterpret_cast<const T *>(tensor(id))[c];
+ const T &target_value = reinterpret_cast<const T *>(tensor(target_id))[c];
const T &reference_value = reinterpret_cast<const T *>(reference(id))[c];
if(!compare<U>(target_value, reference_value, tolerance_value))