COMPMID-1959: Implements 2D FFT on OpenCL
Change-Id: I73cf3984a5463acc854c8a59dc2bd9a5234cd99c
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-on: https://review.mlplatform.org/c/936
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
diff --git a/tests/validation/fixtures/FFTFixture.h b/tests/validation/fixtures/FFTFixture.h
index 8e3c01e..1aaa596 100644
--- a/tests/validation/fixtures/FFTFixture.h
+++ b/tests/validation/fixtures/FFTFixture.h
@@ -31,6 +31,8 @@
#include "tests/IAccessor.h"
#include "tests/framework/Asserts.h"
#include "tests/framework/Fixture.h"
+#include "tests/validation/reference/ActivationLayer.h"
+#include "tests/validation/reference/ConvolutionLayer.h"
#include "tests/validation/reference/DFT.h"
#include <random>
@@ -41,7 +43,7 @@
{
namespace validation
{
-template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+template <typename TensorType, typename AccessorType, typename FunctionType, typename InfoType, typename T>
class FFTValidationFixture : public framework::Fixture
{
public:
@@ -68,8 +70,8 @@
TensorType dst = create_tensor<TensorType>(shape, data_type, 2);
// Create and configure function
- FunctionType fft1d;
- fft1d.configure(&src, &dst, FFT1DInfo());
+ FunctionType fft;
+ fft.configure(&src, &dst, InfoType());
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -85,7 +87,7 @@
fill(AccessorType(src));
// Compute function
- fft1d.run();
+ fft.run();
return dst;
}
@@ -97,13 +99,139 @@
// Fill reference
fill(src);
-
- return reference::dft_1d(src, reference::FFTDirection::Forward);
+ if(std::is_same<InfoType, FFT1DInfo>::value)
+ {
+ return reference::dft_1d(src, reference::FFTDirection::Forward);
+ }
+ else
+ {
+ return reference::dft_2d(src, reference::FFTDirection::Forward);
+ }
}
TensorType _target{};
SimpleTensor<T> _reference{};
};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class FFTConvolutionValidationGenericFixture : public framework::Fixture
+{
+public:
+ template <typename...>
+ void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation,
+ DataType data_type, DataLayout data_layout, ActivationLayerInfo act_info)
+ {
+ _data_type = data_type;
+ _data_layout = data_layout;
+
+ _target = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, dilation, act_info);
+ _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, dilation, act_info);
+ }
+
+protected:
+ template <typename U>
+ void fill(U &&tensor, int i)
+ {
+ switch(tensor.data_type())
+ {
+ case DataType::F32:
+ {
+ std::uniform_real_distribution<> distribution(-1.0f, 1.0f);
+ library->fill(tensor, distribution, i);
+ break;
+ }
+ default:
+ library->fill_tensor_uniform(tensor, i);
+ }
+ }
+
+ TensorType compute_target(TensorShape input_shape, TensorShape weights_shape, const TensorShape &bias_shape, TensorShape output_shape, const PadStrideInfo &info,
+ const Size2D &dilation, const ActivationLayerInfo act_info)
+ {
+ ARM_COMPUTE_UNUSED(dilation);
+ ARM_COMPUTE_ERROR_ON((input_shape[2] % weights_shape[2]) != 0);
+
+ if(_data_layout == DataLayout::NHWC)
+ {
+ permute(input_shape, PermutationVector(2U, 0U, 1U));
+ permute(weights_shape, PermutationVector(2U, 0U, 1U));
+ permute(output_shape, PermutationVector(2U, 0U, 1U));
+ }
+
+ // Create tensors
+ TensorType src = create_tensor<TensorType>(input_shape, _data_type, 1, QuantizationInfo(), _data_layout);
+ TensorType weights = create_tensor<TensorType>(weights_shape, _data_type, 1, QuantizationInfo(), _data_layout);
+ TensorType bias = create_tensor<TensorType>(bias_shape, _data_type, 1, QuantizationInfo(), _data_layout);
+ TensorType dst = create_tensor<TensorType>(output_shape, _data_type, 1, QuantizationInfo(), _data_layout);
+
+ // Create and configure function
+ FunctionType conv;
+ conv.configure(&src, &weights, &bias, &dst, info, act_info);
+
+ ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+ // Allocate tensors
+ src.allocator()->allocate();
+ weights.allocator()->allocate();
+ bias.allocator()->allocate();
+ dst.allocator()->allocate();
+
+ ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(!weights.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(!bias.info()->is_resizable(), framework::LogLevel::ERRORS);
+ ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+ // Fill tensors
+ fill(AccessorType(src), 0);
+ fill(AccessorType(weights), 1);
+ fill(AccessorType(bias), 2);
+
+ // Compute convolution function
+ conv.run();
+
+ return dst;
+ }
+
+ SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info,
+ const Size2D &dilation, const ActivationLayerInfo act_info)
+ {
+ ARM_COMPUTE_ERROR_ON((input_shape[2] % weights_shape[2]) != 0);
+
+ // Create reference
+ SimpleTensor<T> src{ input_shape, _data_type, 1 };
+ SimpleTensor<T> weights{ weights_shape, _data_type, 1 };
+ SimpleTensor<T> bias{ bias_shape, _data_type, 1 };
+
+ // Fill reference
+ fill(src, 0);
+ fill(weights, 1);
+ fill(bias, 2);
+
+ return (act_info.enabled()) ? reference::activation_layer<T>(reference::convolution_layer<T>(src, weights, bias, output_shape, info, dilation), act_info) : reference::convolution_layer<T>(src,
+ weights, bias, output_shape, info, dilation);
+ }
+
+ TensorType _target{};
+ SimpleTensor<T> _reference{};
+ DataType _data_type{};
+ DataLayout _data_layout{};
+};
+
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+class FFTConvolutionValidationFixture : public FFTConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
+{
+public:
+ template <typename...>
+ void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation,
+ DataType data_type, DataLayout data_layout, ActivationLayerInfo act_info)
+ {
+ FFTConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation,
+ data_type, data_layout, act_info);
+ }
+};
} // namespace validation
} // namespace test
} // namespace arm_compute