COMPMID-908 - Merge Activation layer with Convolution Layer (NEON. CL, GLES)

Change-Id: Iab06d0768ecf805b841e601185608aae88cf9166
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/120874
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

3 files changed, 56 insertions, 40 deletions

diff --git a/tests/validation/fixtures/ConvolutionLayerFixture.h b/tests/validation/fixtures/ConvolutionLayerFixture.h
index 3d073e3f79..1bcffed526 100644
--- a/tests/validation/fixtures/ConvolutionLayerFixture.h
+++ b/tests/validation/fixtures/ConvolutionLayerFixture.h
@@ -33,6 +33,7 @@
 #include "tests/framework/Asserts.h"
 #include "tests/framework/Fixture.h"
 #include "tests/validation/Helpers.h"
+#include "tests/validation/reference/ActivationLayer.h"
 #include "tests/validation/reference/ConvolutionLayer.h"
 #include "tests/validation/reference/Utils.h"
 
@@ -55,7 +56,7 @@ public:
 public:
     template <typename...>
     void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, bool reshape_weights,
-               DataType data_type, int fractional_bits, QuantizationInfo quantization_info)
+               DataType data_type, int fractional_bits, QuantizationInfo quantization_info, ActivationLayerInfo act_info)
     {
         _data_type         = data_type;
         _is_quantized      = is_data_type_quantized_asymmetric(data_type);
@@ -63,8 +64,8 @@ public:
         _fractional_bits   = fractional_bits;
         _quantization_info = quantization_info;
 
-        _target    = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, reshape_weights, dilation);
-        _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, dilation);
+        _target    = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, reshape_weights, dilation, act_info);
+        _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, dilation, act_info);
     }
 
 protected:
@@ -98,7 +99,7 @@ protected:
     }
 
     TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info,
-                              bool reshape_weights, const Size2D &dilation)
+                              bool reshape_weights, const Size2D &dilation, const ActivationLayerInfo act_info)
     {
         const bool is_optimised = std::is_same<FunctionType, NEConvolutionLayer>::value && _data_type == DataType::F32;
 
@@ -140,7 +141,7 @@ protected:
 
         // Create and configure function
         FunctionType conv;
-        conv.configure(&src, &weights, &bias, &dst, info, weights_info, dilation);
+        conv.configure(&src, &weights, &bias, &dst, info, weights_info, dilation, act_info);
 
         ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
         ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -210,7 +211,7 @@ protected:
     }
 
     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 Size2D &dilation, const ActivationLayerInfo act_info)
     {
         // Create reference
         SimpleTensor<T>     src{ input_shape, _data_type, 1, _fractional_bits, _quantization_info };
@@ -222,7 +223,9 @@ protected:
         fill(weights, 1);
         fill(bias, 2);
 
-        return reference::convolution_layer<T>(src, weights, bias, output_shape, info, dilation);
+        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{};
@@ -283,10 +286,12 @@ class ConvolutionValidationFixture : public ConvolutionValidationGenericFixture<
 {
 public:
     template <typename...>
-    void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, bool reshape_weights, DataType data_type)
+    void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, bool reshape_weights, DataType data_type,
+               ActivationLayerInfo act_info)
     {
         ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, reshape_weights, data_type, 0,
-                                                                                              QuantizationInfo());
+                                                                                              QuantizationInfo(),
+                                                                                              act_info);
     }
 };
 
@@ -296,10 +301,11 @@ class ConvolutionValidationFixedPointFixture : public ConvolutionValidationGener
 public:
     template <typename...>
     void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, bool reshape_weights, DataType data_type,
-               int fractional_bits)
+               int                 fractional_bits,
+               ActivationLayerInfo act_info)
     {
         ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, reshape_weights, data_type, fractional_bits,
-                                                                                              QuantizationInfo());
+                                                                                              QuantizationInfo(), act_info);
     }
 };
 
@@ -309,10 +315,10 @@ class ConvolutionValidationQuantizedFixture : public ConvolutionValidationGeneri
 public:
     template <typename...>
     void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, bool reshape_weights, DataType data_type,
-               QuantizationInfo quantization_info)
+               QuantizationInfo quantization_info, ActivationLayerInfo act_info)
     {
         ConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, reshape_weights, data_type, 0,
-                                                                                              quantization_info);
+                                                                                              quantization_info, act_info);
     }
 };
 } // namespace validation
diff --git a/tests/validation/fixtures/DirectConvolutionLayerFixture.h b/tests/validation/fixtures/DirectConvolutionLayerFixture.h
index fef9d2dc6e..ef7721dd5e 100644
--- a/tests/validation/fixtures/DirectConvolutionLayerFixture.h
+++ b/tests/validation/fixtures/DirectConvolutionLayerFixture.h
@@ -49,7 +49,7 @@ public:
 public:
     template <typename...>
     void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels,
-               DataType data_type, int fractional_bits, QuantizationInfo quantization_info)
+               DataType data_type, int fractional_bits, QuantizationInfo quantization_info, ActivationLayerInfo act_info)
     {
         _fractional_bits   = fractional_bits;
         _quantization_info = quantization_info;
@@ -61,13 +61,13 @@ public:
         const TensorShape   output_shape   = get_output_shape(input_shape, weights_shape, info);
         const DataType      bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
 
-        _target    = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info);
-        _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info);
+        _target    = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info);
+        _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info);
     }
 
     template <typename...>
     void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation,
-               DataType data_type, int fractional_bits, QuantizationInfo quantization_info)
+               DataType data_type, int fractional_bits, QuantizationInfo quantization_info, ActivationLayerInfo act_info)
     {
         ARM_COMPUTE_UNUSED(dilation);
 
@@ -77,8 +77,8 @@ public:
 
         const DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
 
-        _target    = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info);
-        _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info);
+        _target    = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info);
+        _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, bias_data_type, fractional_bits, quantization_info, act_info);
     }
 
 protected:
@@ -112,7 +112,7 @@ protected:
     }
 
     TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info,
-                              DataType data_type, DataType bias_data_type, int fixed_point_position, QuantizationInfo quantization_info)
+                              DataType data_type, DataType bias_data_type, int fixed_point_position, QuantizationInfo quantization_info, ActivationLayerInfo act_info)
     {
         // Create tensors
         TensorType src     = create_tensor<TensorType>(input_shape, data_type, 1, fixed_point_position, quantization_info);
@@ -122,7 +122,7 @@ protected:
 
         // Create and configure function
         FunctionType conv;
-        conv.configure(&src, &weights, &bias, &dst, info);
+        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);
@@ -152,7 +152,7 @@ protected:
     }
 
     SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info,
-                                      DataType data_type, DataType bias_data_type, int fixed_point_position, QuantizationInfo quantization_info)
+                                      DataType data_type, DataType bias_data_type, int fixed_point_position, QuantizationInfo quantization_info, ActivationLayerInfo act_info)
     {
         // Create reference
         SimpleTensor<T>     src{ input_shape, data_type, 1, fixed_point_position, quantization_info };
@@ -164,7 +164,9 @@ protected:
         fill(weights, 1);
         fill(bias, 2);
 
-        return reference::convolution_layer<T>(src, weights, bias, output_shape, info);
+        return (act_info.enabled()) ? reference::activation_layer<T>(reference::convolution_layer<T>(src, weights, bias, output_shape, info),
+                                                                     act_info) :
+               reference::convolution_layer<T>(src, weights, bias, output_shape, info);
     }
 
     TensorType       _target{};
@@ -194,9 +196,10 @@ class DirectConvolutionValidationFixture : public DirectConvolutionValidationGen
 {
 public:
     template <typename...>
-    void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type)
+    void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, ActivationLayerInfo act_info)
     {
-        DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, 0, QuantizationInfo());
+        DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, 0, QuantizationInfo(),
+                                                                                                    act_info);
     }
 };
 
@@ -205,10 +208,11 @@ class DirectConvolutionValidationFixedPointFixture : public DirectConvolutionVal
 {
 public:
     template <typename...>
-    void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, int fractional_bits)
+    void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, int fractional_bits,
+               ActivationLayerInfo act_info)
     {
         DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, fractional_bits,
-                                                                                                    QuantizationInfo());
+                                                                                                    QuantizationInfo(), act_info);
     }
 };
 
@@ -217,9 +221,11 @@ class DirectConvolutionValidationQuantizedFixture : public DirectConvolutionVali
 {
 public:
     template <typename...>
-    void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, QuantizationInfo quantization_info)
+    void setup(TensorShape input_shape, int stride_x, int stride_y, int pad_x, int pad_y, unsigned int kernel_size, unsigned int num_kernels, DataType data_type, QuantizationInfo quantization_info,
+               ActivationLayerInfo act_info)
     {
-        DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, 0, quantization_info);
+        DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, stride_x, stride_y, pad_x, pad_y, kernel_size, num_kernels, data_type, 0, quantization_info,
+                                                                                                    act_info);
     }
 };
 
@@ -229,9 +235,10 @@ class DirectConvolutionValidationWithTensorShapesQuantizedFixture : public Direc
 public:
     template <typename...>
     void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation,
-               DataType data_type, QuantizationInfo quantization_info)
+               DataType data_type, QuantizationInfo quantization_info, ActivationLayerInfo act_info)
     {
-        DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, 0, quantization_info);
+        DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, 0, quantization_info,
+                                                                                                    act_info);
     }
 };
 
@@ -241,9 +248,10 @@ class DirectConvolutionValidationWithTensorShapesFixture : public DirectConvolut
 public:
     template <typename...>
     void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation,
-               DataType data_type)
+               DataType data_type, ActivationLayerInfo act_info)
     {
-        DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, 0, QuantizationInfo());
+        DirectConvolutionValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, weights_shape, bias_shape, output_shape, info, dilation, data_type, 0, QuantizationInfo(),
+                                                                                                    act_info);
     }
 };
 
diff --git a/tests/validation/fixtures/WinogradLayerFixture.h b/tests/validation/fixtures/WinogradLayerFixture.h
index a86f24f35e..5210cbf720 100644
--- a/tests/validation/fixtures/WinogradLayerFixture.h
+++ b/tests/validation/fixtures/WinogradLayerFixture.h
@@ -33,6 +33,7 @@
 #include "tests/framework/Asserts.h"
 #include "tests/framework/Fixture.h"
 #include "tests/validation/Helpers.h"
+#include "tests/validation/reference/ActivationLayer.h"
 #include "tests/validation/reference/ConvolutionLayer.h"
 #include "tests/validation/reference/Utils.h"
 #include "tests/validation/reference/Winograd.h"
@@ -52,12 +53,12 @@ class WinogradConvolutionLayerValidationFixture : 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)
+    void setup(TensorShape input_shape, TensorShape weights_shape, TensorShape bias_shape, TensorShape output_shape, PadStrideInfo info, Size2D dilation, DataType data_type, ActivationLayerInfo act_info)
     {
         ARM_COMPUTE_UNUSED(dilation);
 
-        _target    = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type);
-        _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type);
+        _target    = compute_target(input_shape, weights_shape, bias_shape, output_shape, info, data_type, act_info);
+        _reference = compute_reference(input_shape, weights_shape, bias_shape, output_shape, info, data_type, act_info);
     }
 
 protected:
@@ -82,7 +83,7 @@ protected:
     }
 
     TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info,
-                              DataType data_type)
+                              DataType data_type, ActivationLayerInfo act_info)
     {
         // Create tensors
         TensorType src     = create_tensor<TensorType>(input_shape, data_type, 1);
@@ -92,7 +93,7 @@ protected:
 
         // Create and configure function
         FunctionType conv;
-        conv.configure(&src, &weights, &bias, &dst, info);
+        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);
@@ -122,7 +123,7 @@ protected:
     }
 
     SimpleTensor<T> compute_reference(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &bias_shape, const TensorShape &output_shape, const PadStrideInfo &info,
-                                      DataType data_type)
+                                      DataType data_type, ActivationLayerInfo act_info)
     {
         // Create reference
         SimpleTensor<T> src{ input_shape, data_type, 1 };
@@ -134,7 +135,8 @@ protected:
         fill(weights, 1, -1.f, 1.f);
         fill(bias, 2, -1.f, 1.f);
 
-        return reference::convolution_layer<T>(src, weights, bias, output_shape, info);
+        return (act_info.enabled()) ? reference::activation_layer<T>(reference::convolution_layer<T>(src, weights, bias, output_shape, info), act_info) : reference::convolution_layer<T>(src, weights, bias,
+                output_shape, info);
     }
 
     TensorType      _target{};