tests/validation/fixtures/DepthwiseConvolutionLayerFixture.h - ml/ComputeLibrary - Gitiles

 /*
  * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
  * Permission is hereby granted, free of charge, to any person obtaining a copy
  * of this software and associated documentation files (the "Software"), to
  * deal in the Software without restriction, including without limitation the
  * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
  * sell copies of the Software, and to permit persons to whom the Software is
  * furnished to do so, subject to the following conditions:
  *
  * The above copyright notice and this permission notice shall be included in all
  * copies or substantial portions of the Software.
  *
  * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
  * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
  * SOFTWARE.
  */
 #ifndef ARM_COMPUTE_TEST_DEPTHWISE_CONVOLUTION_FIXTURE
 #define ARM_COMPUTE_TEST_DEPTHWISE_CONVOLUTION_FIXTURE

 #include "arm_compute/core/TensorShape.h"
 #include "arm_compute/core/Types.h"
 #include "tests/AssetsLibrary.h"
 #include "tests/Globals.h"
 #include "tests/IAccessor.h"
 #include "tests/framework/Asserts.h"
 #include "tests/framework/Fixture.h"
 #include "tests/validation/Helpers.h"
 #include "tests/validation/reference/DepthwiseConvolutionLayer.h"

 #include "utils/Utils.h"

 #include <random>

 namespace arm_compute
 {
 namespace test
 {
 namespace validation
 {
 template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
 class DepthwiseConvolutionLayerValidationGenericFixture : public framework::Fixture
 {
 public:
     using TBias = typename std::conditional<std::is_same<typename std::decay<T>::type, uint8_t>::value, int32_t, T>::type;

 public:
     template <typename...>
     void setup(TensorShape in_shape, TensorShape weights_shape, TensorShape out_shape, PadStrideInfo pad_stride_info, DataType data_type, QuantizationInfo quantization_info, DataLayout data_layout)
     {
         _quantization_info = quantization_info;
         _data_type         = data_type;
         const TensorShape biases_shape(weights_shape[2]);
         const DataType    bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;

         if(data_layout == DataLayout::NHWC)
         {
             permute(in_shape, PermutationVector(2U, 0U, 1U));
             permute(weights_shape, PermutationVector(2U, 0U, 1U));
             permute(out_shape, PermutationVector(2U, 0U, 1U));
         }

         _target    = compute_target(in_shape, weights_shape, biases_shape, out_shape, pad_stride_info, data_type, bias_data_type, quantization_info, data_layout);
         _reference = compute_reference(in_shape, weights_shape, biases_shape, out_shape, pad_stride_info, data_type, bias_data_type, quantization_info, data_layout);
     }

 protected:
     template <typename U>
     void fill(U &&tensor, int i)
     {
         switch(tensor.data_type())
         {
             case DataType::QASYMM8:
             {
                 std::uniform_int_distribution<uint8_t> distribution(0, 10);
                 library->fill(tensor, distribution, i);
                 break;
             }
             case DataType::F32:
             case DataType::F16:
             {
                 std::uniform_real_distribution<> distribution(-1.0f, 1.0f);
                 library->fill(tensor, distribution, i);
                 break;
             }
             case DataType::S32:
             {
                 std::uniform_int_distribution<int32_t> distribution(-100, 100);
                 library->fill(tensor, distribution, i);
                 break;
             }
             default:
                 library->fill_tensor_uniform(tensor, i);
         }
     }

     TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &biases_shape, const TensorShape &output_shape, PadStrideInfo &pad_stride_info,
                               const DataType data_type, const DataType bias_data_type, const QuantizationInfo quantization_info, const DataLayout data_layout)
     {
         // Create tensors
         TensorType src     = create_tensor<TensorType>(input_shape, data_type, 1, 0, quantization_info, data_layout);
         TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, 0, quantization_info, data_layout);
         TensorType biases  = create_tensor<TensorType>(biases_shape, bias_data_type, 1, 0, quantization_info, data_layout);
         TensorType dst     = create_tensor<TensorType>(output_shape, data_type, 1, 0, quantization_info, data_layout);

         // Create Depthwise Convolution configure function
         FunctionType dwc;
         dwc.configure(&src, &weights, &biases, &dst, pad_stride_info);

         ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
         ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
         ARM_COMPUTE_EXPECT(biases.info()->is_resizable(), framework::LogLevel::ERRORS);
         ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);

         // Allocate tensors
         src.allocator()->allocate();
         weights.allocator()->allocate();
         biases.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(!biases.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(biases), 2);

         // Compute function
         dwc.run();

         return dst;
     }

     SimpleTensor<T> compute_reference(const TensorShape &in_shape, const TensorShape &weights_shape, const TensorShape &biases_shape, const TensorShape &out_shape, const PadStrideInfo &pad_stride_info,
                                       const DataType data_type, const DataType bias_data_type, const QuantizationInfo quantization_info, const DataLayout data_layout)
     {
         SimpleTensor<T>     src{ in_shape, data_type, 1, 0, quantization_info, data_layout };
         SimpleTensor<T>     weights{ weights_shape, data_type, 1, 0, quantization_info, data_layout };
         SimpleTensor<TBias> biases{ biases_shape, bias_data_type, 1, 0, quantization_info, data_layout };

         fill(src, 0);
         fill(weights, 1);
         fill(biases, 2);

         return reference::depthwise_convolution(src, weights, biases, out_shape, pad_stride_info);
     }

     TensorType       _target{};
     SimpleTensor<T>  _reference{};
     DataType         _data_type{};
     QuantizationInfo _quantization_info{};
 };

 template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
 class DepthwiseConvolutionLayerValidationFixture : public DepthwiseConvolutionLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
 {
 public:
     template <typename...>
     void setup(TensorShape in_shape, TensorShape weights_shape, TensorShape out_shape, PadStrideInfo pad_stride_info, DataType data_type, DataLayout data_layout)
     {
         DepthwiseConvolutionLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(in_shape, weights_shape, out_shape, pad_stride_info,
                                                                                                             data_type, QuantizationInfo(), data_layout);
     }
 };

 template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
 class DepthwiseConvolutionLayerValidationQuantizedFixture : public DepthwiseConvolutionLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
 {
 public:
     template <typename...>
     void setup(TensorShape in_shape, TensorShape weights_shape, TensorShape out_shape, PadStrideInfo pad_stride_info, DataType data_type, QuantizationInfo quantization_info, DataLayout data_layout)
     {
         DepthwiseConvolutionLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(in_shape, weights_shape, out_shape, pad_stride_info,
                                                                                                             data_type, quantization_info, data_layout);
     }
 };
 } // namespace validation
 } // namespace test
 } // namespace arm_compute
 #endif /* ARM_COMPUTE_TEST_DEPTHWISE_CONVOLUTION_FIXTURE */
	/*
	* Copyright (c) 2017-2018 ARM Limited.
	*
	* SPDX-License-Identifier: MIT
	*
	* Permission is hereby granted, free of charge, to any person obtaining a copy
	* of this software and associated documentation files (the "Software"), to
	* deal in the Software without restriction, including without limitation the
	* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
	* sell copies of the Software, and to permit persons to whom the Software is
	* furnished to do so, subject to the following conditions:
	*
	* The above copyright notice and this permission notice shall be included in all
	* copies or substantial portions of the Software.
	*
	* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
	* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
	* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
	* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
	* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
	* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
	* SOFTWARE.
	*/
	#ifndef ARM_COMPUTE_TEST_DEPTHWISE_CONVOLUTION_FIXTURE
	#define ARM_COMPUTE_TEST_DEPTHWISE_CONVOLUTION_FIXTURE

	#include "arm_compute/core/TensorShape.h"
	#include "arm_compute/core/Types.h"
	#include "tests/AssetsLibrary.h"
	#include "tests/Globals.h"
	#include "tests/IAccessor.h"
	#include "tests/framework/Asserts.h"
	#include "tests/framework/Fixture.h"
	#include "tests/validation/Helpers.h"
	#include "tests/validation/reference/DepthwiseConvolutionLayer.h"

	#include "utils/Utils.h"

	#include <random>

	namespace arm_compute
	{
	namespace test
	{
	namespace validation
	{
	template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
	class DepthwiseConvolutionLayerValidationGenericFixture : public framework::Fixture
	{
	public:
	using TBias = typename std::conditional<std::is_same<typename std::decay<T>::type, uint8_t>::value, int32_t, T>::type;

	public:
	template <typename...>
	void setup(TensorShape in_shape, TensorShape weights_shape, TensorShape out_shape, PadStrideInfo pad_stride_info, DataType data_type, QuantizationInfo quantization_info, DataLayout data_layout)
	{
	_quantization_info = quantization_info;
	_data_type = data_type;
	const TensorShape biases_shape(weights_shape[2]);
	const DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;

	if(data_layout == DataLayout::NHWC)
	{
	permute(in_shape, PermutationVector(2U, 0U, 1U));
	permute(weights_shape, PermutationVector(2U, 0U, 1U));
	permute(out_shape, PermutationVector(2U, 0U, 1U));
	}

	_target = compute_target(in_shape, weights_shape, biases_shape, out_shape, pad_stride_info, data_type, bias_data_type, quantization_info, data_layout);
	_reference = compute_reference(in_shape, weights_shape, biases_shape, out_shape, pad_stride_info, data_type, bias_data_type, quantization_info, data_layout);
	}

	protected:
	template <typename U>
	void fill(U &&tensor, int i)
	{
	switch(tensor.data_type())
	{
	case DataType::QASYMM8:
	{
	std::uniform_int_distribution<uint8_t> distribution(0, 10);
	library->fill(tensor, distribution, i);
	break;
	}
	case DataType::F32:
	case DataType::F16:
	{
	std::uniform_real_distribution<> distribution(-1.0f, 1.0f);
	library->fill(tensor, distribution, i);
	break;
	}
	case DataType::S32:
	{
	std::uniform_int_distribution<int32_t> distribution(-100, 100);
	library->fill(tensor, distribution, i);
	break;
	}
	default:
	library->fill_tensor_uniform(tensor, i);
	}
	}

	TensorType compute_target(const TensorShape &input_shape, const TensorShape &weights_shape, const TensorShape &biases_shape, const TensorShape &output_shape, PadStrideInfo &pad_stride_info,
	const DataType data_type, const DataType bias_data_type, const QuantizationInfo quantization_info, const DataLayout data_layout)
	{
	// Create tensors
	TensorType src = create_tensor<TensorType>(input_shape, data_type, 1, 0, quantization_info, data_layout);
	TensorType weights = create_tensor<TensorType>(weights_shape, data_type, 1, 0, quantization_info, data_layout);
	TensorType biases = create_tensor<TensorType>(biases_shape, bias_data_type, 1, 0, quantization_info, data_layout);
	TensorType dst = create_tensor<TensorType>(output_shape, data_type, 1, 0, quantization_info, data_layout);

	// Create Depthwise Convolution configure function
	FunctionType dwc;
	dwc.configure(&src, &weights, &biases, &dst, pad_stride_info);

	ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
	ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
	ARM_COMPUTE_EXPECT(biases.info()->is_resizable(), framework::LogLevel::ERRORS);
	ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);

	// Allocate tensors
	src.allocator()->allocate();
	weights.allocator()->allocate();
	biases.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(!biases.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(biases), 2);

	// Compute function
	dwc.run();

	return dst;
	}

	SimpleTensor<T> compute_reference(const TensorShape &in_shape, const TensorShape &weights_shape, const TensorShape &biases_shape, const TensorShape &out_shape, const PadStrideInfo &pad_stride_info,
	const DataType data_type, const DataType bias_data_type, const QuantizationInfo quantization_info, const DataLayout data_layout)
	{
	SimpleTensor<T> src{ in_shape, data_type, 1, 0, quantization_info, data_layout };
	SimpleTensor<T> weights{ weights_shape, data_type, 1, 0, quantization_info, data_layout };
	SimpleTensor<TBias> biases{ biases_shape, bias_data_type, 1, 0, quantization_info, data_layout };

	fill(src, 0);
	fill(weights, 1);
	fill(biases, 2);

	return reference::depthwise_convolution(src, weights, biases, out_shape, pad_stride_info);
	}

	TensorType _target{};
	SimpleTensor<T> _reference{};
	DataType _data_type{};
	QuantizationInfo _quantization_info{};
	};

	template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
	class DepthwiseConvolutionLayerValidationFixture : public DepthwiseConvolutionLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
	{
	public:
	template <typename...>
	void setup(TensorShape in_shape, TensorShape weights_shape, TensorShape out_shape, PadStrideInfo pad_stride_info, DataType data_type, DataLayout data_layout)
	{
	DepthwiseConvolutionLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(in_shape, weights_shape, out_shape, pad_stride_info,
	data_type, QuantizationInfo(), data_layout);
	}
	};

	template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
	class DepthwiseConvolutionLayerValidationQuantizedFixture : public DepthwiseConvolutionLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
	{
	public:
	template <typename...>
	void setup(TensorShape in_shape, TensorShape weights_shape, TensorShape out_shape, PadStrideInfo pad_stride_info, DataType data_type, QuantizationInfo quantization_info, DataLayout data_layout)
	{
	DepthwiseConvolutionLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(in_shape, weights_shape, out_shape, pad_stride_info,
	data_type, quantization_info, data_layout);
	}
	};
	} // namespace validation
	} // namespace test
	} // namespace arm_compute
	#endif /* ARM_COMPUTE_TEST_DEPTHWISE_CONVOLUTION_FIXTURE */