tests/datasets/SmallConvolutionLayerDataset.h - platform/external/ComputeLibrary - Git at Google

 /*
  * Copyright (c) 2017-2019 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_SMALL_CONVOLUTION_LAYER_DATASET
 #define ARM_COMPUTE_TEST_SMALL_CONVOLUTION_LAYER_DATASET

 #include "tests/datasets/ConvolutionLayerDataset.h"

 #include "utils/TypePrinter.h"

 #include "arm_compute/core/TensorShape.h"
 #include "arm_compute/core/Types.h"

 namespace arm_compute
 {
 namespace test
 {
 namespace datasets
 {
 class SmallWinogradConvolutionLayer3x3Dataset final : public ConvolutionLayerDataset
 {
 public:
     SmallWinogradConvolutionLayer3x3Dataset()
     {
         // Channel size big enough to force multithreaded execution of the input transform
         add_config(TensorShape(8U, 8U, 32U), TensorShape(3U, 3U, 32U, 1U), TensorShape(1U), TensorShape(6U, 6U, 1U), PadStrideInfo(1, 1, 0, 0));
         // Batch size 1
         add_config(TensorShape(8U, 8U, 2U), TensorShape(3U, 3U, 2U, 1U), TensorShape(1U), TensorShape(6U, 6U, 1U), PadStrideInfo(1, 1, 0, 0));
         // Batch size 4
         add_config(TensorShape(23U, 27U, 5U, 4U), TensorShape(3U, 3U, 5U, 21U), TensorShape(21U), TensorShape(21U, 25U, 21U, 4U), PadStrideInfo(1, 1, 0, 0));
         add_config(TensorShape(8U, 8U, 2U), TensorShape(3U, 3U, 2U, 1U), TensorShape(1U), TensorShape(8U, 8U, 1U), PadStrideInfo(1, 1, 1, 1));
         add_config(TensorShape(3U, 9U), TensorShape(3U, 3U), TensorShape(1), TensorShape(3U, 9U), PadStrideInfo(1, 1, 1, 1));
     }
 };

 class SmallWinogradConvolutionLayer3x1Dataset final : public ConvolutionLayerDataset
 {
 public:
     SmallWinogradConvolutionLayer3x1Dataset()
     {
         // Channel size big enough to force multithreaded execution of the input transform
         add_config(TensorShape(8U, 8U, 32U), TensorShape(3U, 1U, 32U, 1U), TensorShape(1U), TensorShape(6U, 8U, 1U), PadStrideInfo(1, 1, 0, 0));
         // Batch size 1
         add_config(TensorShape(8U, 8U, 2U), TensorShape(3U, 1U, 2U, 1U), TensorShape(1U), TensorShape(6U, 8U, 1U), PadStrideInfo(1, 1, 0, 0));
         // Batch size 4
         add_config(TensorShape(23U, 27U, 5U, 4U), TensorShape(3U, 1U, 5U, 21U), TensorShape(21U), TensorShape(21U, 27U, 21U, 4U), PadStrideInfo(1, 1, 0, 0));
         add_config(TensorShape(8U, 8U, 2U), TensorShape(3U, 1U, 2U, 1U), TensorShape(1U), TensorShape(8U, 8U, 1U), PadStrideInfo(1, 1, 1, 0));
     }
 };

 class SmallWinogradConvolutionLayer1x3Dataset final : public ConvolutionLayerDataset
 {
 public:
     SmallWinogradConvolutionLayer1x3Dataset()
     {
         // Channel size big enough to force multithreaded execution of the input transform
         add_config(TensorShape(8U, 8U, 32U), TensorShape(1U, 3U, 32U, 1U), TensorShape(1U), TensorShape(8U, 6U, 1U), PadStrideInfo(1, 1, 0, 0));
         // Batch size 1
         add_config(TensorShape(8U, 8U, 2U), TensorShape(1U, 3U, 2U, 1U), TensorShape(1U), TensorShape(8U, 6U, 1U), PadStrideInfo(1, 1, 0, 0));
         // Batch size 4
         add_config(TensorShape(23U, 27U, 5U, 4U), TensorShape(1U, 3U, 5U, 21U), TensorShape(21U), TensorShape(23U, 25U, 21U, 4U), PadStrideInfo(1, 1, 0, 0));
         add_config(TensorShape(8U, 8U, 2U), TensorShape(1U, 3U, 2U, 1U), TensorShape(1U), TensorShape(8U, 8U, 1U), PadStrideInfo(1, 1, 0, 1));
     }
 };

 class SmallWinogradConvolutionLayer5x5Dataset final : public ConvolutionLayerDataset
 {
 public:
     SmallWinogradConvolutionLayer5x5Dataset()
     {
         add_config(TensorShape(8U, 8U, 2U), TensorShape(5U, 5U, 2U, 1U), TensorShape(1U), TensorShape(4U, 4U, 1U), PadStrideInfo(1, 1, 0, 0));
         add_config(TensorShape(8U, 8U, 2U), TensorShape(5U, 5U, 2U), TensorShape(1U), TensorShape(8U, 8U, 1U), PadStrideInfo(1, 1, 2, 2));
     }
 };

 class SmallWinogradConvolutionLayer5x1Dataset final : public ConvolutionLayerDataset
 {
 public:
     SmallWinogradConvolutionLayer5x1Dataset()
     {
         add_config(TensorShape(8U, 8U, 2U), TensorShape(5U, 1U, 2U, 1U), TensorShape(1U), TensorShape(4U, 8U, 1U), PadStrideInfo(1, 1, 0, 0));
         add_config(TensorShape(8U, 8U, 2U), TensorShape(5U, 1U, 2U), TensorShape(1U), TensorShape(8U, 8U, 1U), PadStrideInfo(1, 1, 2, 0));
     }
 };

 class SmallWinogradConvolutionLayer1x5Dataset final : public ConvolutionLayerDataset
 {
 public:
     SmallWinogradConvolutionLayer1x5Dataset()
     {
         add_config(TensorShape(8U, 8U, 2U), TensorShape(1U, 5U, 2U, 1U), TensorShape(1U), TensorShape(8U, 4U, 1U), PadStrideInfo(1, 1, 0, 0));
         add_config(TensorShape(8U, 8U, 2U), TensorShape(1U, 5U, 2U), TensorShape(1U), TensorShape(8U, 8U, 1U), PadStrideInfo(1, 1, 0, 2));
     }
 };

 class SmallWinogradConvolutionLayer7x1Dataset final : public ConvolutionLayerDataset
 {
 public:
     SmallWinogradConvolutionLayer7x1Dataset()
     {
         add_config(TensorShape(14U, 14U, 2U), TensorShape(7U, 1U, 2U, 1U), TensorShape(1U), TensorShape(8U, 14U, 1U), PadStrideInfo(1, 1, 0, 0));
         add_config(TensorShape(14U, 14U, 2U), TensorShape(7U, 1U, 2U), TensorShape(1U), TensorShape(14U, 14U, 1U), PadStrideInfo(1, 1, 3, 0));
     }
 };

 class SmallWinogradConvolutionLayer1x7Dataset final : public ConvolutionLayerDataset
 {
 public:
     SmallWinogradConvolutionLayer1x7Dataset()
     {
         add_config(TensorShape(14U, 14U, 2U), TensorShape(1U, 7U, 2U, 1U), TensorShape(1U), TensorShape(14U, 8U, 1U), PadStrideInfo(1, 1, 0, 0));
         add_config(TensorShape(14U, 14U, 2U), TensorShape(1U, 7U, 2U), TensorShape(1U), TensorShape(14U, 14U, 1U), PadStrideInfo(1, 1, 0, 3));
     }
 };

 class SmallFFTConvolutionLayerDataset final : public ConvolutionLayerDataset
 {
 public:
     SmallFFTConvolutionLayerDataset()
     {
         add_config(TensorShape(8U, 7U, 3U), TensorShape(3U, 3U, 3U, 2U), TensorShape(2U), TensorShape(8U, 7U, 2U), PadStrideInfo(1, 1, 1, 1));
         add_config(TensorShape(64U, 32U, 5U), TensorShape(5U, 5U, 5U, 10U), TensorShape(10U), TensorShape(64U, 32U, 10U), PadStrideInfo(1, 1, 2, 2));
         add_config(TensorShape(192U, 128U, 8U), TensorShape(9U, 9U, 8U, 3U), TensorShape(3U), TensorShape(192U, 128U, 3U), PadStrideInfo(1, 1, 4, 4));
     }
 };

 class SmallConvolutionLayerDataset final : public ConvolutionLayerDataset
 {
 public:
     SmallConvolutionLayerDataset()
     {
         add_config(TensorShape(224U, 224U, 3U), TensorShape(3U, 3U, 3U, 32U), TensorShape(32U), TensorShape(112U, 112U, 32U),
                    PadStrideInfo(2, 2, /*left*/ 0, /*right*/ 1, /*top*/ 0, /*bottom*/ 1, DimensionRoundingType::FLOOR));

         // 1D Kernel
         add_config(TensorShape(1U, 5U, 2U), TensorShape(1U, 3U, 2U, 3U), TensorShape(3U), TensorShape(1U, 7U, 3U), PadStrideInfo(1, 1, 0, 0, 2, 2, DimensionRoundingType::FLOOR));

         // Batch size 1
         add_config(TensorShape(23U, 27U, 5U), TensorShape(3U, 3U, 5U, 21U), TensorShape(21U), TensorShape(11U, 25U, 21U), PadStrideInfo(2, 1, 0, 0));
         add_config(TensorShape(33U, 27U, 7U), TensorShape(5U, 5U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U), PadStrideInfo(3, 2, 1, 0));
         add_config(TensorShape(17U, 31U, 2U), TensorShape(5U, 5U, 2U, 19U), TensorShape(19U), TensorShape(15U, 15U, 19U), PadStrideInfo(1, 2, 1, 1));
         add_config(TensorShape(23U, 27U, 5U), TensorShape(3U, 1U, 5U, 21U), TensorShape(21U), TensorShape(11U, 27U, 21U), PadStrideInfo(2, 1, 0, 0));
         add_config(TensorShape(33U, 27U, 7U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 11U, 16U), PadStrideInfo(3, 2, 1, 0));
         add_config(TensorShape(17U, 31U, 2U), TensorShape(5U, 3U, 2U, 19U), TensorShape(19U), TensorShape(15U, 16U, 19U), PadStrideInfo(1, 2, 1, 1));
         add_config(TensorShape(3U, 3U, 1U), TensorShape(2U, 2U, 1U, 11U), TensorShape(11U), TensorShape(2U, 2U, 11U), PadStrideInfo(1, 1, 0, 0));
         // Batch size 4
         add_config(TensorShape(23U, 27U, 5U, 4U), TensorShape(3U, 3U, 5U, 21U), TensorShape(21U), TensorShape(11U, 25U, 21U, 4U), PadStrideInfo(2, 1, 0, 0));
         add_config(TensorShape(33U, 27U, 7U, 4U), TensorShape(5U, 5U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 4U), PadStrideInfo(3, 2, 1, 0));
         add_config(TensorShape(17U, 31U, 2U, 4U), TensorShape(5U, 5U, 2U, 19U), TensorShape(19U), TensorShape(15U, 15U, 19U, 4U), PadStrideInfo(1, 2, 1, 1));
         add_config(TensorShape(23U, 27U, 5U, 4U), TensorShape(3U, 1U, 5U, 21U), TensorShape(21U), TensorShape(11U, 27U, 21U, 4U), PadStrideInfo(2, 1, 0, 0));
         add_config(TensorShape(33U, 27U, 7U, 4U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 11U, 16U, 4U), PadStrideInfo(3, 2, 1, 0));
         add_config(TensorShape(17U, 31U, 2U, 4U), TensorShape(5U, 3U, 2U, 19U), TensorShape(19U), TensorShape(15U, 16U, 19U, 4U), PadStrideInfo(1, 2, 1, 1));
         // Arbitrary batch size
         add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 11U, 16U, 5U), PadStrideInfo(3, 2, 1, 0));
         // FC convolution
         add_config(TensorShape(1U, 1U, 1024U), TensorShape(1U, 1U, 1024U, 1001U), TensorShape(1001U), TensorShape(1U, 1U, 1001U), PadStrideInfo(1, 1, 0, 0));
         // Asymmetric padding
         add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 1, 2, 0, DimensionRoundingType::FLOOR));
         add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 1, 0, 2, DimensionRoundingType::FLOOR));
         add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 2, 1, 2, 0, DimensionRoundingType::FLOOR));
         add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 3, 0, 2, DimensionRoundingType::FLOOR));
         add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(10U, 11U, 16U, 5U), PadStrideInfo(3, 2, 1, 0, 1, 0, DimensionRoundingType::FLOOR));
         add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(10U, 11U, 16U, 5U), PadStrideInfo(3, 2, 0, 1, 0, 1, DimensionRoundingType::FLOOR));

         add_config(TensorShape(5U, 4U, 3U, 2U), TensorShape(4U, 4U, 3U, 1U), TensorShape(1U), TensorShape(2U, 1U, 1U, 2U), PadStrideInfo(1, 1, 0, 0, 0, 0, DimensionRoundingType::FLOOR));
     }
 };

 // TODO (COMPMID-1749)
 class SmallConvolutionLayerReducedDataset final : public ConvolutionLayerDataset
 {
 public:
     SmallConvolutionLayerReducedDataset()
     {
         // Batch size 1
         add_config(TensorShape(23U, 27U, 5U), TensorShape(3U, 3U, 5U, 21U), TensorShape(21U), TensorShape(11U, 25U, 21U), PadStrideInfo(2, 1, 0, 0));
         add_config(TensorShape(33U, 27U, 7U), TensorShape(5U, 5U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U), PadStrideInfo(3, 2, 1, 0));
         add_config(TensorShape(17U, 31U, 2U), TensorShape(5U, 5U, 2U, 19U), TensorShape(19U), TensorShape(15U, 15U, 19U), PadStrideInfo(1, 2, 1, 1));

         // Asymmetric padding
         add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 1, 2, 0, DimensionRoundingType::FLOOR));
         add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 1, 0, 2, DimensionRoundingType::FLOOR));
         add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 2, 1, 2, 0, DimensionRoundingType::FLOOR));
     }
 };

 class SmallGroupedConvolutionLayerDataset final : public ConvolutionLayerDataset
 {
 public:
     SmallGroupedConvolutionLayerDataset()
     {
         // Batch size 1
         // Number of groups = 2
         add_config(TensorShape(23U, 27U, 8U), TensorShape(1U, 1U, 4U, 24U), TensorShape(24U), TensorShape(12U, 27U, 24U), PadStrideInfo(2, 1, 0, 0));
         add_config(TensorShape(33U, 27U, 12U), TensorShape(5U, 5U, 6U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U), PadStrideInfo(3, 2, 1, 0));
         // Number of groups = 4
         add_config(TensorShape(23U, 27U, 8U), TensorShape(1U, 1U, 2U, 24U), TensorShape(24U), TensorShape(12U, 27U, 24U), PadStrideInfo(2, 1, 0, 0));
         add_config(TensorShape(33U, 27U, 12U), TensorShape(5U, 5U, 4U, 15U), TensorShape(15U), TensorShape(11U, 12U, 15U), PadStrideInfo(3, 2, 1, 0));

         // Batch size 4
         // Number of groups = 2
         add_config(TensorShape(23U, 27U, 8U, 4U), TensorShape(1U, 1U, 4U, 24U), TensorShape(24U), TensorShape(12U, 27U, 24U, 4U), PadStrideInfo(2, 1, 0, 0));
         add_config(TensorShape(33U, 27U, 12U, 4U), TensorShape(5U, 5U, 6U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 4U), PadStrideInfo(3, 2, 1, 0));
         // Number of groups = 4
         add_config(TensorShape(23U, 27U, 8U, 4U), TensorShape(1U, 1U, 2U, 24U), TensorShape(24U), TensorShape(12U, 27U, 24U, 4U), PadStrideInfo(2, 1, 0, 0));
         add_config(TensorShape(33U, 27U, 12U, 4U), TensorShape(5U, 5U, 4U, 15U), TensorShape(15U), TensorShape(11U, 12U, 15U, 4U), PadStrideInfo(3, 2, 1, 0));

         // Arbitrary batch size
         add_config(TensorShape(23U, 27U, 8U, 5U), TensorShape(1U, 1U, 4U, 24U), TensorShape(24U), TensorShape(12U, 27U, 24U, 5U), PadStrideInfo(2, 1, 0, 0));
         add_config(TensorShape(33U, 27U, 12U, 3U), TensorShape(5U, 5U, 6U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 3U), PadStrideInfo(3, 2, 1, 0));
         // Number of groups = 4
         add_config(TensorShape(23U, 27U, 8U, 2U), TensorShape(1U, 1U, 2U, 24U), TensorShape(24U), TensorShape(12U, 27U, 24U, 2U), PadStrideInfo(2, 1, 0, 0));
         add_config(TensorShape(33U, 27U, 12U, 5U), TensorShape(5U, 5U, 4U, 15U), TensorShape(15U), TensorShape(11U, 12U, 15U, 5U), PadStrideInfo(3, 2, 1, 0));

         // Asymmetric padding
         add_config(TensorShape(33U, 27U, 8U, 5U), TensorShape(5U, 7U, 2U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 1, 2, 0, DimensionRoundingType::FLOOR));
         add_config(TensorShape(33U, 27U, 8U, 5U), TensorShape(5U, 7U, 4U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 1, 0, 2, DimensionRoundingType::FLOOR));
         add_config(TensorShape(33U, 27U, 6U, 5U), TensorShape(5U, 7U, 3U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 2, 1, 2, 0, DimensionRoundingType::FLOOR));
     }
 };
 } // namespace datasets
 } // namespace test
 } // namespace arm_compute
 #endif /* ARM_COMPUTE_TEST_SMALL_CONVOLUTION_LAYER_DATASET */
	/*
	* Copyright (c) 2017-2019 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_SMALL_CONVOLUTION_LAYER_DATASET
	#define ARM_COMPUTE_TEST_SMALL_CONVOLUTION_LAYER_DATASET

	#include "tests/datasets/ConvolutionLayerDataset.h"

	#include "utils/TypePrinter.h"

	#include "arm_compute/core/TensorShape.h"
	#include "arm_compute/core/Types.h"

	namespace arm_compute
	{
	namespace test
	{
	namespace datasets
	{
	class SmallWinogradConvolutionLayer3x3Dataset final : public ConvolutionLayerDataset
	{
	public:
	SmallWinogradConvolutionLayer3x3Dataset()
	{
	// Channel size big enough to force multithreaded execution of the input transform
	add_config(TensorShape(8U, 8U, 32U), TensorShape(3U, 3U, 32U, 1U), TensorShape(1U), TensorShape(6U, 6U, 1U), PadStrideInfo(1, 1, 0, 0));
	// Batch size 1
	add_config(TensorShape(8U, 8U, 2U), TensorShape(3U, 3U, 2U, 1U), TensorShape(1U), TensorShape(6U, 6U, 1U), PadStrideInfo(1, 1, 0, 0));
	// Batch size 4
	add_config(TensorShape(23U, 27U, 5U, 4U), TensorShape(3U, 3U, 5U, 21U), TensorShape(21U), TensorShape(21U, 25U, 21U, 4U), PadStrideInfo(1, 1, 0, 0));
	add_config(TensorShape(8U, 8U, 2U), TensorShape(3U, 3U, 2U, 1U), TensorShape(1U), TensorShape(8U, 8U, 1U), PadStrideInfo(1, 1, 1, 1));
	add_config(TensorShape(3U, 9U), TensorShape(3U, 3U), TensorShape(1), TensorShape(3U, 9U), PadStrideInfo(1, 1, 1, 1));
	}
	};

	class SmallWinogradConvolutionLayer3x1Dataset final : public ConvolutionLayerDataset
	{
	public:
	SmallWinogradConvolutionLayer3x1Dataset()
	{
	// Channel size big enough to force multithreaded execution of the input transform
	add_config(TensorShape(8U, 8U, 32U), TensorShape(3U, 1U, 32U, 1U), TensorShape(1U), TensorShape(6U, 8U, 1U), PadStrideInfo(1, 1, 0, 0));
	// Batch size 1
	add_config(TensorShape(8U, 8U, 2U), TensorShape(3U, 1U, 2U, 1U), TensorShape(1U), TensorShape(6U, 8U, 1U), PadStrideInfo(1, 1, 0, 0));
	// Batch size 4
	add_config(TensorShape(23U, 27U, 5U, 4U), TensorShape(3U, 1U, 5U, 21U), TensorShape(21U), TensorShape(21U, 27U, 21U, 4U), PadStrideInfo(1, 1, 0, 0));
	add_config(TensorShape(8U, 8U, 2U), TensorShape(3U, 1U, 2U, 1U), TensorShape(1U), TensorShape(8U, 8U, 1U), PadStrideInfo(1, 1, 1, 0));
	}
	};

	class SmallWinogradConvolutionLayer1x3Dataset final : public ConvolutionLayerDataset
	{
	public:
	SmallWinogradConvolutionLayer1x3Dataset()
	{
	// Channel size big enough to force multithreaded execution of the input transform
	add_config(TensorShape(8U, 8U, 32U), TensorShape(1U, 3U, 32U, 1U), TensorShape(1U), TensorShape(8U, 6U, 1U), PadStrideInfo(1, 1, 0, 0));
	// Batch size 1
	add_config(TensorShape(8U, 8U, 2U), TensorShape(1U, 3U, 2U, 1U), TensorShape(1U), TensorShape(8U, 6U, 1U), PadStrideInfo(1, 1, 0, 0));
	// Batch size 4
	add_config(TensorShape(23U, 27U, 5U, 4U), TensorShape(1U, 3U, 5U, 21U), TensorShape(21U), TensorShape(23U, 25U, 21U, 4U), PadStrideInfo(1, 1, 0, 0));
	add_config(TensorShape(8U, 8U, 2U), TensorShape(1U, 3U, 2U, 1U), TensorShape(1U), TensorShape(8U, 8U, 1U), PadStrideInfo(1, 1, 0, 1));
	}
	};

	class SmallWinogradConvolutionLayer5x5Dataset final : public ConvolutionLayerDataset
	{
	public:
	SmallWinogradConvolutionLayer5x5Dataset()
	{
	add_config(TensorShape(8U, 8U, 2U), TensorShape(5U, 5U, 2U, 1U), TensorShape(1U), TensorShape(4U, 4U, 1U), PadStrideInfo(1, 1, 0, 0));
	add_config(TensorShape(8U, 8U, 2U), TensorShape(5U, 5U, 2U), TensorShape(1U), TensorShape(8U, 8U, 1U), PadStrideInfo(1, 1, 2, 2));
	}
	};

	class SmallWinogradConvolutionLayer5x1Dataset final : public ConvolutionLayerDataset
	{
	public:
	SmallWinogradConvolutionLayer5x1Dataset()
	{
	add_config(TensorShape(8U, 8U, 2U), TensorShape(5U, 1U, 2U, 1U), TensorShape(1U), TensorShape(4U, 8U, 1U), PadStrideInfo(1, 1, 0, 0));
	add_config(TensorShape(8U, 8U, 2U), TensorShape(5U, 1U, 2U), TensorShape(1U), TensorShape(8U, 8U, 1U), PadStrideInfo(1, 1, 2, 0));
	}
	};

	class SmallWinogradConvolutionLayer1x5Dataset final : public ConvolutionLayerDataset
	{
	public:
	SmallWinogradConvolutionLayer1x5Dataset()
	{
	add_config(TensorShape(8U, 8U, 2U), TensorShape(1U, 5U, 2U, 1U), TensorShape(1U), TensorShape(8U, 4U, 1U), PadStrideInfo(1, 1, 0, 0));
	add_config(TensorShape(8U, 8U, 2U), TensorShape(1U, 5U, 2U), TensorShape(1U), TensorShape(8U, 8U, 1U), PadStrideInfo(1, 1, 0, 2));
	}
	};

	class SmallWinogradConvolutionLayer7x1Dataset final : public ConvolutionLayerDataset
	{
	public:
	SmallWinogradConvolutionLayer7x1Dataset()
	{
	add_config(TensorShape(14U, 14U, 2U), TensorShape(7U, 1U, 2U, 1U), TensorShape(1U), TensorShape(8U, 14U, 1U), PadStrideInfo(1, 1, 0, 0));
	add_config(TensorShape(14U, 14U, 2U), TensorShape(7U, 1U, 2U), TensorShape(1U), TensorShape(14U, 14U, 1U), PadStrideInfo(1, 1, 3, 0));
	}
	};

	class SmallWinogradConvolutionLayer1x7Dataset final : public ConvolutionLayerDataset
	{
	public:
	SmallWinogradConvolutionLayer1x7Dataset()
	{
	add_config(TensorShape(14U, 14U, 2U), TensorShape(1U, 7U, 2U, 1U), TensorShape(1U), TensorShape(14U, 8U, 1U), PadStrideInfo(1, 1, 0, 0));
	add_config(TensorShape(14U, 14U, 2U), TensorShape(1U, 7U, 2U), TensorShape(1U), TensorShape(14U, 14U, 1U), PadStrideInfo(1, 1, 0, 3));
	}
	};

	class SmallFFTConvolutionLayerDataset final : public ConvolutionLayerDataset
	{
	public:
	SmallFFTConvolutionLayerDataset()
	{
	add_config(TensorShape(8U, 7U, 3U), TensorShape(3U, 3U, 3U, 2U), TensorShape(2U), TensorShape(8U, 7U, 2U), PadStrideInfo(1, 1, 1, 1));
	add_config(TensorShape(64U, 32U, 5U), TensorShape(5U, 5U, 5U, 10U), TensorShape(10U), TensorShape(64U, 32U, 10U), PadStrideInfo(1, 1, 2, 2));
	add_config(TensorShape(192U, 128U, 8U), TensorShape(9U, 9U, 8U, 3U), TensorShape(3U), TensorShape(192U, 128U, 3U), PadStrideInfo(1, 1, 4, 4));
	}
	};

	class SmallConvolutionLayerDataset final : public ConvolutionLayerDataset
	{
	public:
	SmallConvolutionLayerDataset()
	{
	add_config(TensorShape(224U, 224U, 3U), TensorShape(3U, 3U, 3U, 32U), TensorShape(32U), TensorShape(112U, 112U, 32U),
	PadStrideInfo(2, 2, /left/ 0, /right/ 1, /top/ 0, /bottom/ 1, DimensionRoundingType::FLOOR));

	// 1D Kernel
	add_config(TensorShape(1U, 5U, 2U), TensorShape(1U, 3U, 2U, 3U), TensorShape(3U), TensorShape(1U, 7U, 3U), PadStrideInfo(1, 1, 0, 0, 2, 2, DimensionRoundingType::FLOOR));

	// Batch size 1
	add_config(TensorShape(23U, 27U, 5U), TensorShape(3U, 3U, 5U, 21U), TensorShape(21U), TensorShape(11U, 25U, 21U), PadStrideInfo(2, 1, 0, 0));
	add_config(TensorShape(33U, 27U, 7U), TensorShape(5U, 5U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U), PadStrideInfo(3, 2, 1, 0));
	add_config(TensorShape(17U, 31U, 2U), TensorShape(5U, 5U, 2U, 19U), TensorShape(19U), TensorShape(15U, 15U, 19U), PadStrideInfo(1, 2, 1, 1));
	add_config(TensorShape(23U, 27U, 5U), TensorShape(3U, 1U, 5U, 21U), TensorShape(21U), TensorShape(11U, 27U, 21U), PadStrideInfo(2, 1, 0, 0));
	add_config(TensorShape(33U, 27U, 7U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 11U, 16U), PadStrideInfo(3, 2, 1, 0));
	add_config(TensorShape(17U, 31U, 2U), TensorShape(5U, 3U, 2U, 19U), TensorShape(19U), TensorShape(15U, 16U, 19U), PadStrideInfo(1, 2, 1, 1));
	add_config(TensorShape(3U, 3U, 1U), TensorShape(2U, 2U, 1U, 11U), TensorShape(11U), TensorShape(2U, 2U, 11U), PadStrideInfo(1, 1, 0, 0));
	// Batch size 4
	add_config(TensorShape(23U, 27U, 5U, 4U), TensorShape(3U, 3U, 5U, 21U), TensorShape(21U), TensorShape(11U, 25U, 21U, 4U), PadStrideInfo(2, 1, 0, 0));
	add_config(TensorShape(33U, 27U, 7U, 4U), TensorShape(5U, 5U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 4U), PadStrideInfo(3, 2, 1, 0));
	add_config(TensorShape(17U, 31U, 2U, 4U), TensorShape(5U, 5U, 2U, 19U), TensorShape(19U), TensorShape(15U, 15U, 19U, 4U), PadStrideInfo(1, 2, 1, 1));
	add_config(TensorShape(23U, 27U, 5U, 4U), TensorShape(3U, 1U, 5U, 21U), TensorShape(21U), TensorShape(11U, 27U, 21U, 4U), PadStrideInfo(2, 1, 0, 0));
	add_config(TensorShape(33U, 27U, 7U, 4U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 11U, 16U, 4U), PadStrideInfo(3, 2, 1, 0));
	add_config(TensorShape(17U, 31U, 2U, 4U), TensorShape(5U, 3U, 2U, 19U), TensorShape(19U), TensorShape(15U, 16U, 19U, 4U), PadStrideInfo(1, 2, 1, 1));
	// Arbitrary batch size
	add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 11U, 16U, 5U), PadStrideInfo(3, 2, 1, 0));
	// FC convolution
	add_config(TensorShape(1U, 1U, 1024U), TensorShape(1U, 1U, 1024U, 1001U), TensorShape(1001U), TensorShape(1U, 1U, 1001U), PadStrideInfo(1, 1, 0, 0));
	// Asymmetric padding
	add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 1, 2, 0, DimensionRoundingType::FLOOR));
	add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 1, 0, 2, DimensionRoundingType::FLOOR));
	add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 2, 1, 2, 0, DimensionRoundingType::FLOOR));
	add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 3, 0, 2, DimensionRoundingType::FLOOR));
	add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(10U, 11U, 16U, 5U), PadStrideInfo(3, 2, 1, 0, 1, 0, DimensionRoundingType::FLOOR));
	add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(10U, 11U, 16U, 5U), PadStrideInfo(3, 2, 0, 1, 0, 1, DimensionRoundingType::FLOOR));

	add_config(TensorShape(5U, 4U, 3U, 2U), TensorShape(4U, 4U, 3U, 1U), TensorShape(1U), TensorShape(2U, 1U, 1U, 2U), PadStrideInfo(1, 1, 0, 0, 0, 0, DimensionRoundingType::FLOOR));
	}
	};

	// TODO (COMPMID-1749)
	class SmallConvolutionLayerReducedDataset final : public ConvolutionLayerDataset
	{
	public:
	SmallConvolutionLayerReducedDataset()
	{
	// Batch size 1
	add_config(TensorShape(23U, 27U, 5U), TensorShape(3U, 3U, 5U, 21U), TensorShape(21U), TensorShape(11U, 25U, 21U), PadStrideInfo(2, 1, 0, 0));
	add_config(TensorShape(33U, 27U, 7U), TensorShape(5U, 5U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U), PadStrideInfo(3, 2, 1, 0));
	add_config(TensorShape(17U, 31U, 2U), TensorShape(5U, 5U, 2U, 19U), TensorShape(19U), TensorShape(15U, 15U, 19U), PadStrideInfo(1, 2, 1, 1));

	// Asymmetric padding
	add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 1, 2, 0, DimensionRoundingType::FLOOR));
	add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 1, 0, 2, DimensionRoundingType::FLOOR));
	add_config(TensorShape(33U, 27U, 7U, 5U), TensorShape(5U, 7U, 7U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 2, 1, 2, 0, DimensionRoundingType::FLOOR));
	}
	};

	class SmallGroupedConvolutionLayerDataset final : public ConvolutionLayerDataset
	{
	public:
	SmallGroupedConvolutionLayerDataset()
	{
	// Batch size 1
	// Number of groups = 2
	add_config(TensorShape(23U, 27U, 8U), TensorShape(1U, 1U, 4U, 24U), TensorShape(24U), TensorShape(12U, 27U, 24U), PadStrideInfo(2, 1, 0, 0));
	add_config(TensorShape(33U, 27U, 12U), TensorShape(5U, 5U, 6U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U), PadStrideInfo(3, 2, 1, 0));
	// Number of groups = 4
	add_config(TensorShape(23U, 27U, 8U), TensorShape(1U, 1U, 2U, 24U), TensorShape(24U), TensorShape(12U, 27U, 24U), PadStrideInfo(2, 1, 0, 0));
	add_config(TensorShape(33U, 27U, 12U), TensorShape(5U, 5U, 4U, 15U), TensorShape(15U), TensorShape(11U, 12U, 15U), PadStrideInfo(3, 2, 1, 0));

	// Batch size 4
	// Number of groups = 2
	add_config(TensorShape(23U, 27U, 8U, 4U), TensorShape(1U, 1U, 4U, 24U), TensorShape(24U), TensorShape(12U, 27U, 24U, 4U), PadStrideInfo(2, 1, 0, 0));
	add_config(TensorShape(33U, 27U, 12U, 4U), TensorShape(5U, 5U, 6U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 4U), PadStrideInfo(3, 2, 1, 0));
	// Number of groups = 4
	add_config(TensorShape(23U, 27U, 8U, 4U), TensorShape(1U, 1U, 2U, 24U), TensorShape(24U), TensorShape(12U, 27U, 24U, 4U), PadStrideInfo(2, 1, 0, 0));
	add_config(TensorShape(33U, 27U, 12U, 4U), TensorShape(5U, 5U, 4U, 15U), TensorShape(15U), TensorShape(11U, 12U, 15U, 4U), PadStrideInfo(3, 2, 1, 0));

	// Arbitrary batch size
	add_config(TensorShape(23U, 27U, 8U, 5U), TensorShape(1U, 1U, 4U, 24U), TensorShape(24U), TensorShape(12U, 27U, 24U, 5U), PadStrideInfo(2, 1, 0, 0));
	add_config(TensorShape(33U, 27U, 12U, 3U), TensorShape(5U, 5U, 6U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 3U), PadStrideInfo(3, 2, 1, 0));
	// Number of groups = 4
	add_config(TensorShape(23U, 27U, 8U, 2U), TensorShape(1U, 1U, 2U, 24U), TensorShape(24U), TensorShape(12U, 27U, 24U, 2U), PadStrideInfo(2, 1, 0, 0));
	add_config(TensorShape(33U, 27U, 12U, 5U), TensorShape(5U, 5U, 4U, 15U), TensorShape(15U), TensorShape(11U, 12U, 15U, 5U), PadStrideInfo(3, 2, 1, 0));

	// Asymmetric padding
	add_config(TensorShape(33U, 27U, 8U, 5U), TensorShape(5U, 7U, 2U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 1, 2, 0, DimensionRoundingType::FLOOR));
	add_config(TensorShape(33U, 27U, 8U, 5U), TensorShape(5U, 7U, 4U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 1, 1, 0, 2, DimensionRoundingType::FLOOR));
	add_config(TensorShape(33U, 27U, 6U, 5U), TensorShape(5U, 7U, 3U, 16U), TensorShape(16U), TensorShape(11U, 12U, 16U, 5U), PadStrideInfo(3, 2, 2, 1, 2, 0, DimensionRoundingType::FLOOR));
	}
	};
	} // namespace datasets
	} // namespace test
	} // namespace arm_compute
	#endif /* ARM_COMPUTE_TEST_SMALL_CONVOLUTION_LAYER_DATASET */