text: /*
   * 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_CLDEPTHWISECONVOLUTION_H__
  #define __ARM_COMPUTE_CLDEPTHWISECONVOLUTION_H__
  
  #include "arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.h"
  #include "arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.h"
  #include "arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsGenericKernel.h"
  #include "arm_compute/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.h"
  #include "arm_compute/core/CL/kernels/CLDepthwiseIm2ColKernel.h"
  #include "arm_compute/core/CL/kernels/CLDepthwiseVectorToTensorKernel.h"
  #include "arm_compute/core/CL/kernels/CLDirectConvolutionLayerOutputStageKernel.h"
  #include "arm_compute/core/CL/kernels/CLFillBorderKernel.h"
  #include "arm_compute/core/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.h"
  #include "arm_compute/core/CL/kernels/ICLDepthwiseConvolutionLayer3x3Kernel.h"
  #include "arm_compute/core/Types.h"
  #include "arm_compute/runtime/CL/CLTensor.h"
  #include "arm_compute/runtime/CL/functions/CLActivationLayer.h"
  #include "arm_compute/runtime/CL/functions/CLPermute.h"
  #include "arm_compute/runtime/IFunction.h"
  #include "arm_compute/runtime/MemoryGroup.h"
  
  namespace arm_compute
  {
  class ICLTensor;
  
  /** Basic function to execute a depthwise convolution for kernel size 3x3xC (when data layout NCHW) or Cx3x3 (when data layout NHWC). This function calls the following OpenCL kernels:
   *
   * -# @ref CLDepthwiseConvolutionLayer3x3NCHWKernel (if data_layout == NCHW)
   * -# @ref CLDepthwiseConvolutionLayer3x3NHWCKernel (if data_layout == NHWC)
   * -# @ref CLDepthwiseConvolutionLayerReshapeWeightsKernel (if data_layout == NHWC)
   * -# @ref CLFillBorderKernel (if pad_x or pad_y > 0)
   *
   */
  class CLDepthwiseConvolutionLayer3x3 : public IFunction
  {
  public:
      /** Default constructor */
      CLDepthwiseConvolutionLayer3x3(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
      /** Prevent instances of this class from being copied (As this class contains pointers) */
      CLDepthwiseConvolutionLayer3x3(const CLDepthwiseConvolutionLayer3x3 &) = delete;
      /** Default move constructor */
      CLDepthwiseConvolutionLayer3x3(CLDepthwiseConvolutionLayer3x3 &&) = default;
      /** Prevent instances of this class from being copied (As this class contains pointers) */
      CLDepthwiseConvolutionLayer3x3 &operator=(const CLDepthwiseConvolutionLayer3x3 &) = delete;
      /** Default move assignment operator */
      CLDepthwiseConvolutionLayer3x3 &operator=(CLDepthwiseConvolutionLayer3x3 &&) = default;
      /** Initialize the function's source, destination, conv and border_size.
       *
       * @param[in, out] input            Source tensor. Data type supported: QASYMM8/F16/F32. (Written to only for border filling).
       * @param[in]      weights          Weights tensor. A 3D tensor with shape [3, 3, IFM]. Data type supported: Same as @p input.
       * @param[in]      biases           Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
       *                                  Data type supported: Same as @p input.
       * @param[out]     output           Destination tensor. Data type supported: same as @p input.
       * @param[in]      conv_info        Padding and stride information to use for the convolution.
       * @param[in]      depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
       * @param[in]      act_info         (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported.
       * @param[in]      dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
       */
      void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1,
                     ActivationLayerInfo act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
  
      /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer3x3
       *
       * @param[in] input            Source tensor info. Data type supported: QASYMM8 for all layouts, F16/F32 for NCHW.
       * @param[in] weights          Weights tensor info. A 3D tensor with shape [3, 3, IFM]. Data type supported: Same as @p input.
       * @param[in] biases           Biases tensor info. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
       *                             Data type supported: Same as @p input, S32 when input is QASYMM8.
       * @param[in] output           Destination tensor. Data type supported: same as @p input.
       * @param[in] conv_info        Padding and stride information to use for the convolution.
       * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
       * @param[in] act_info         (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU for 3x3 QASYMM8 supported.
       * @param[in] gpu_target       (Optional) GPU target to validate the kernel for. Defaults to midgard.
       * @param[in] dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
       *
       * @return a status
       */
      static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier = 1,
                             ActivationLayerInfo act_info = ActivationLayerInfo(), GPUTarget gpu_target = GPUTarget::MIDGARD, const Size2D &dilation = Size2D(1U, 1U));
      // Inherited methods overriden:
      void run() override;
      void prepare() override;
  
  private:
      MemoryGroup                                            _memory_group;
      std::unique_ptr<ICLDepthwiseConvolutionLayer3x3Kernel> _kernel;
      CLFillBorderKernel                                     _border_handler;
      CLPermute                                              _permute_input_to_nchw;
      CLPermute                                              _permute_weights_to_nchw;
      CLPermute                                              _permute_output_to_nhwc;
      CLDepthwiseConvolutionLayerReshapeWeightsKernel        _reshape_weights;
      CLTensor                                               _permuted_input;
      CLTensor                                               _permuted_weights;
      CLTensor                                               _permuted_output;
      const ITensor                                         *_original_weights;
      bool                                                   _needs_permute;
      bool                                                   _needs_weights_reshape;
      bool                                                   _is_prepared;
  };
  
  /** Basic function to execute a generic depthwise convolution. This function calls the following OpenCL kernels:
   *
   * -# @ref CLDepthwiseIm2ColKernel
   * -# @ref CLGEMMMatrixVectorMultiplyKernel
   * -# @ref CLDepthwiseConvolutionLayerReshapeWeightsGenericKernel
   * -# @ref CLFillBorderKernel (if pad_x or pad_y > 0)
   *
   */
  class CLDepthwiseConvolutionLayer : public IFunction
  {
  public:
      /** Default constructor */
      CLDepthwiseConvolutionLayer();
      /** Prevent instances of this class from being copied (As this class contains pointers) */
      CLDepthwiseConvolutionLayer(const CLDepthwiseConvolutionLayer &) = delete;
      /** Default move constructor */
      CLDepthwiseConvolutionLayer(CLDepthwiseConvolutionLayer &&) = default;
      /** Prevent instances of this class from being copied (As this class contains pointers) */
      CLDepthwiseConvolutionLayer &operator=(const CLDepthwiseConvolutionLayer &) = delete;
      /** Default move assignment operator */
      CLDepthwiseConvolutionLayer &operator=(CLDepthwiseConvolutionLayer &&) = default;
      /** Initialize the function's source, destination, weights and convolution information.
       *
       * @param[in, out] input            Source tensor. Data type supported: QASYMM8/F32. (Written to only for border filling).
       * @param[in]      weights          Weights tensor. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input.
       * @param[in]      biases           Biases tensor. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
       *                                  Data type supported: Same as @p input, S32 when input is QASYMM8.
       * @param[out]     output           Destination tensor. Data type supported: same as @p input.
       * @param[in]      conv_info        Padding and stride information to use for the convolution.
       * @param[in]      depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
       * @param[in]      act_info         (Optional) Activation layer information in case of a fused activation.
       * @param[in]      dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
       */
      void configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
                     unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
  
      /** Static function to check if given info will lead to a valid configuration of @ref CLDepthwiseConvolutionLayer
       *
       * @param[in] input            Source tensor info. Data type supported: QASYMM8/F32.
       * @param[in] weights          Weights tensor info. These are 3D tensors with shape [kernel_x, kernel_y, IFM]. Data type supported: Same as @p input.
       * @param[in] biases           Biases tensor info. A 1D tensor with shape [IFM]. Must be nullptr if not needed.
       *                             Data type supported: Same as @p input, S32 when input is QASYMM8.
       * @param[in] output           Destination tensor. Data type supported: same as @p input.
       * @param[in] conv_info        Padding and stride information to use for the convolution.
       * @param[in] depth_multiplier (Optional) Multiplier to apply to the input's depth in order to retrieve the output's depth. Defaults to 1.
       * @param[in] act_info         (Optional) Activation layer information in case of a fused activation.
       * @param[in] dilation         (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
       *
       * @return a status
       */
      static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
                             unsigned int depth_multiplier = 1, const ActivationLayerInfo &act_info = ActivationLayerInfo(), const Size2D &dilation = Size2D(1U, 1U));
  
      // Inherited methods overriden:
      void run() override;
      void prepare() override;
  
  private:
      CLDepthwiseIm2ColKernel                                _im2col_kernel;
      CLDepthwiseConvolutionLayerReshapeWeightsGenericKernel _weights_reshape_kernel;
      CLGEMMMatrixVectorMultiplyKernel                       _v2mm_kernel;
      CLDepthwiseVectorToTensorKernel                        _vector_to_tensor_kernel;
      CLDirectConvolutionLayerOutputStageKernel              _output_stage_kernel;
      CLActivationLayer                                      _activationlayer_function;
      CLFillBorderKernel                                     _v2mm_input_fill_border;
      CLFillBorderKernel                                     _v2mm_weights_fill_border;
      CLTensor                                               _input_reshaped;
      CLTensor                                               _weights_reshaped;
      CLTensor                                               _v2mm_output;
      CLTensor                                               _output_reshaped;
      bool                                                   _is_prepared;
      bool                                                   _is_quantized;
      bool                                                   _is_activationlayer_enabled;
      const ICLTensor                                       *_original_weights;
      std::unique_ptr<IFunction>                             _optimised_function;
  };
  } // namespace arm_compute
  #endif /*__ARM_COMPUTE_CLDEPTHWISECONVOLUTION_H__ */
  