1 files changed, 133 insertions, 5 deletions

diff --git a/tests/validation/fixtures/FFTFixture.h b/tests/validation/fixtures/FFTFixture.h
index 8e3c01eaff..1aaa5965b2 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 test
 {
 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 @@ protected:
         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 @@ protected:
         fill(AccessorType(src));
 
         // Compute function
-        fft1d.run();
+        fft.run();
 
         return dst;
     }
@@ -97,12 +99,138 @@ protected:
 
         // Fill reference
         fill(src);
+        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;
+    }
 
-        return reference::dft_1d(src, reference::FFTDirection::Forward);
+    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