text: /*
   * Copyright (c) 2017-2020 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_ICLDEPTHWISECONVOLUTIONKERNEL3x3_H
  #define ARM_COMPUTE_ICLDEPTHWISECONVOLUTIONKERNEL3x3_H
  
  #include "arm_compute/core/CL/ICLKernel.h"
  
  namespace arm_compute
  {
  class ICLTensor;
  
  /** Interface for the kernel to run a 3x3 depthwise convolution on a tensor.
   */
  class ICLDepthwiseConvolutionLayer3x3Kernel : public ICLKernel
  {
  public:
      /** Default constructor */
      ICLDepthwiseConvolutionLayer3x3Kernel()
          : _border_size(0), _input(), _output(), _weights(), _biases(), _conv_stride_y(1), _output_multipliers(), _output_shifts(), _is_quantized(false)
      {
      }
      /** Prevent instances of this class from being copied (As this class contains pointers) */
      ICLDepthwiseConvolutionLayer3x3Kernel(const ICLDepthwiseConvolutionLayer3x3Kernel &) = delete;
      /** Prevent instances of this class from being copied (As this class contains pointers) */
      ICLDepthwiseConvolutionLayer3x3Kernel &operator=(const ICLDepthwiseConvolutionLayer3x3Kernel &) = delete;
      /** Default Move Constructor. */
      ICLDepthwiseConvolutionLayer3x3Kernel(ICLDepthwiseConvolutionLayer3x3Kernel &&) = default;
      /** Default move assignment operator */
      ICLDepthwiseConvolutionLayer3x3Kernel &operator=(ICLDepthwiseConvolutionLayer3x3Kernel &&) = default;
      /** Initialize the function's source, destination, conv and border_size.
       *
       * @param[in]  input              Source tensor. DataType supported: QASYMM8/F16/F32.
       * @param[in]  weights            Weights tensor. A 3D tensor with dimensions [3, 3, IFM].
       *                                Data type supported: Same as @p input, QASYMM8/QSYMM8_PER_CHANNEL when input is QASYMM8.
       * @param[in]  biases             Biases tensor. A 1D tensor with dimensions [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. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU are supported for QASYMM8.
       * @param[in]  dilation           (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
       * @param[in]  output_multipliers (Optional) Output multipliers tensor for quantized computations. In case of per-channel quantization,
       *                                the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32
       * @param[in]  output_shifts      (Optional) Output shifts tensor for quantized computations. In case of per-channel quantization,
       *                                the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32
       */
      virtual void configure(const 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),
                             const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr) = 0;
      /** Initialize the function's source, destination, conv and border_size.
       *
       * @param[in]  compile_context    The compile context to be used.
       * @param[in]  input              Source tensor. DataType supported: QASYMM8/F16/F32.
       * @param[in]  weights            Weights tensor. A 3D tensor with dimensions [3, 3, IFM].
       *                                Data type supported: Same as @p input, QASYMM8/QSYMM8_PER_CHANNEL when input is QASYMM8.
       * @param[in]  biases             Biases tensor. A 1D tensor with dimensions [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. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU are supported for QASYMM8.
       * @param[in]  dilation           (Optional) Dilation, in elements, across x and y. Defaults to (1, 1).
       * @param[in]  output_multipliers (Optional) Output multipliers tensor for quantized computations. In case of per-channel quantization,
       *                                the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32
       * @param[in]  output_shifts      (Optional) Output shifts tensor for quantized computations. In case of per-channel quantization,
       *                                the number of multipliers must be equal to the number of filters (IFM). Supported data types: S32
       */
      virtual void configure(const CLCompileContext &compile_context, const 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),
                             const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr) = 0;
  
  protected:
      BorderSize       _border_size;
      const ICLTensor *_input;
      ICLTensor       *_output;
      const ICLTensor *_weights;
      const ICLTensor *_biases;
      unsigned int     _conv_stride_y;
      const ICLTensor *_output_multipliers;
      const ICLTensor *_output_shifts;
      bool             _is_quantized;
  };
  } // namespace arm_compute
  #endif /*ARM_COMPUTE_ICLDEPTHWISECONVOLUTIONKERNEL3x3_H */
  