1 /* 2 * Copyright (c) 2018-2020 Arm Limited. 3 * 4 * SPDX-License-Identifier: MIT 5 * 6 * Permission is hereby granted, free of charge, to any person obtaining a copy 7 * of this software and associated documentation files (the "Software"), to 8 * deal in the Software without restriction, including without limitation the 9 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or 10 * sell copies of the Software, and to permit persons to whom the Software is 11 * furnished to do so, subject to the following conditions: 12 * 13 * The above copyright notice and this permission notice shall be included in all 14 * copies or substantial portions of the Software. 15 * 16 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 17 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 18 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 19 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 20 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 21 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 22 * SOFTWARE. 23 */ 24 #ifndef ARM_COMPUTE_CLWINOGRADOUTPUTTRANSFORMKERNEL_H 25 #define ARM_COMPUTE_CLWINOGRADOUTPUTTRANSFORMKERNEL_H 26 27 #include "src/core/CL/ICLKernel.h" 28 29 namespace arm_compute 30 { 31 class ICLTensor; 32 33 /** Interface for the Winograd output transform kernel. */ 34 class CLWinogradOutputTransformKernel : public ICLKernel 35 { 36 public: 37 /** Default constructor */ 38 CLWinogradOutputTransformKernel(); 39 /** Prevent instances of this class from being copied (As this class contains pointers) */ 40 CLWinogradOutputTransformKernel(const CLWinogradOutputTransformKernel &) = delete; 41 /** Prevent instances of this class from being copied (As this class contains pointers) */ 42 CLWinogradOutputTransformKernel &operator=(const CLWinogradOutputTransformKernel &) = delete; 43 /** Allow instances of this class to be moved */ 44 CLWinogradOutputTransformKernel(CLWinogradOutputTransformKernel &&) = default; 45 /** Allow instances of this class to be moved */ 46 CLWinogradOutputTransformKernel &operator=(CLWinogradOutputTransformKernel &&) = default; 47 /** Default destructor */ 48 ~CLWinogradOutputTransformKernel() = default; 49 /** Set the input and output tensor. 50 * 51 * @note Winograd output transform supports the following configurations for NCWH data layout 52 * F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3), 53 * F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), 54 * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) 55 * 56 * @note Winograd output transform supports the following configurations for NHWC data layout 57 * F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), 58 * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) 59 * 60 * Strides: only unit strides 61 * 62 * @param[in] input Source tensor with shape [C, N, K, batches]. Data types supported: F16/F32. 63 * @param[in] bias Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. It can be a nullptr. Data type supported: as @p input 64 * @param[out] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_output_transform_shape. Data types supported: Same as @p input 65 * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo 66 * @param[in] act_info (Optional) Activation layer information in case of a fused activation. 67 */ 68 void configure(const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const WinogradInfo &winograd_info, const ActivationLayerInfo &act_info = ActivationLayerInfo()); 69 /** Set the input and output tensor. 70 * 71 * @note Winograd output transform supports the following configurations for NCWH data layout 72 * F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3), 73 * F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), 74 * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) 75 * 76 * @note Winograd output transform supports the following configurations for NHWC data layout 77 * F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), 78 * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) 79 * 80 * Strides: only unit strides 81 * 82 * @param[in] compile_context The compile context to be used. 83 * @param[in] input Source tensor with shape [C, N, K, batches]. Data types supported: F16/F32. 84 * @param[in] bias Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. It can be a nullptr. Data type supported: as @p input 85 * @param[out] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_output_transform_shape. Data types supported: Same as @p input 86 * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo 87 * @param[in] act_info (Optional) Activation layer information in case of a fused activation. 88 */ 89 void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *bias, ICLTensor *output, const WinogradInfo &winograd_info, 90 const ActivationLayerInfo &act_info = ActivationLayerInfo()); 91 92 /** Static function to check if given info will lead to a valid configuration of @ref CLWinogradOutputTransformKernel 93 * 94 * @note Winograd output transform supports the following configurations for NCWH data layout 95 * F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3), 96 * F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), 97 * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) 98 * 99 * @note Winograd output transform supports the following configurations for NHWC data layout 100 * F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3), 101 * F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5) 102 * 103 * Strides: only unit strides 104 * 105 * @param[in] input Source tensor with shape [C, N, K, batches]. Data types supported: F16/F32. 106 * @param[in] bias Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. It can be a nullptr. Data type supported: as @p input 107 * @param[out] output The output tensor. The shape for this tensor can be calculated using the utility function @p compute_winograd_output_transform_shape. Data types supported: Same as @p input 108 * @param[in] winograd_info Contains Winograd's information described in @ref WinogradInfo 109 * @param[in] act_info (Optional) Activation layer information in case of a fused activation @ref ActivationLayerInfo. Only RELU, BOUNDED_RELU, LU_BOUNDED_RELU, LEAKY_RELU and SOFT_RELU supported. 110 * 111 * @return a status 112 */ 113 static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const WinogradInfo &winograd_info, const ActivationLayerInfo &act_info = ActivationLayerInfo()); 114 115 // Inherited methods overridden: 116 void run(const Window &window, cl::CommandQueue &queue) override; 117 118 private: 119 using WinogradKey = std::pair<std::pair<int, int>, std::pair<int, int>>; 120 121 const ICLTensor *_input; 122 const ICLTensor *_bias; 123 ICLTensor *_output; 124 bool _is_nhwc; 125 }; 126 } // namespace arm_compute 127 #endif /*ARM_COMPUTE_CLWINOGRADOUTPUTTRANSFORMKERNEL_H */ 128