text: //*****************************************************************************
  // Copyright 2017-2020 Intel Corporation
  //
  // Licensed under the Apache License, Version 2.0 (the "License");
  // you may not use this file except in compliance with the License.
  // You may obtain a copy of the License at
  //
  //     http://www.apache.org/licenses/LICENSE-2.0
  //
  // Unless required by applicable law or agreed to in writing, software
  // distributed under the License is distributed on an "AS IS" BASIS,
  // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  // See the License for the specific language governing permissions and
  // limitations under the License.
  //*****************************************************************************
  
  #pragma once
  
  #include "ngraph/op/convolution.hpp"
  #include "ngraph/op/op.hpp"
  #include "ngraph/op/util/attr_types.hpp"
  #include "ngraph/op/util/fused_op.hpp"
  
  NGRAPH_SUPPRESS_DEPRECATED_START
  
  namespace ngraph
  {
      namespace op
      {
          namespace v1
          {
              /// \brief Batched convolution operation, with optional window dilation and stride.
              class NGRAPH_API GroupConvolution : public Op
              {
              public:
                  NGRAPH_RTTI_DECLARATION;
  
                  /// \brief Constructs a batched convolution operation.
                  GroupConvolution() = default;
                  /// \brief Constructs a batched convolution operation.
                  ///
                  /// \param data_batch The node producing the input data batch tensor.<br>
                  /// `[N, C_IN, D1, ... Df]`
                  /// \param filters The node producing the filters tensor.<br>
                  /// `[GROUPS, FC_OUT, FC_IN, F1, ... Ff]`
                  /// \param strides The strides.<br>
                  /// `[f]`
                  /// \param dilations The dilations.<br>
                  /// `[f]`
                  /// \param pads_begin The beginning of padding shape.<br>
                  /// `[f]`
                  /// \param pads_end The end of padding shape.<br>
                  /// `[f]`
                  /// \param auto_pad The pad type for automatically computing padding sizes.<br>
                  /// `[f]`
                  ///
                  /// Output `[N, FC_OUT * GROUPS, R1, ... Rf]`
                  ///
                  GroupConvolution(const Output<Node>& data_batch,
                                   const Output<Node>& filters,
                                   const Strides& strides,
                                   const CoordinateDiff& pads_begin,
                                   const CoordinateDiff& pads_end,
                                   const Strides& dilations,
                                   const PadType& auto_pad = PadType::EXPLICIT);
  
                  bool visit_attributes(AttributeVisitor& visitor) override;
                  void validate_and_infer_types() override;
  
                  virtual std::shared_ptr<Node>
                      clone_with_new_inputs(const OutputVector& new_args) const override;
                  /// \return The strides.
                  const Strides& get_strides() const { return m_strides; }
                  void set_strides(const Strides& strides) { m_strides = strides; }
                  /// \return The dilations.
                  const Strides& get_dilations() const { return m_dilations; }
                  void set_dilations(const Strides& dilations) { m_dilations = dilations; }
                  /// \return The padding-below sizes (possibly negative).
                  const CoordinateDiff& get_pads_begin() const { return m_pads_begin; }
                  void set_pads_begin(const CoordinateDiff& pads_begin) { m_pads_begin = pads_begin; }
                  /// \return The padding-above sizes (possibly negative).
                  const CoordinateDiff& get_pads_end() const { return m_pads_end; }
                  void set_adding_above(const CoordinateDiff& pads_end) { m_pads_end = pads_end; }
                  /// \return The pad type for convolution.
                  const PadType& get_auto_pad() const { return m_auto_pad; }
                  void set_auto_pad(const PadType& auto_pad) { m_auto_pad = auto_pad; }
                  /// \return The default value for Convolution.
                  virtual std::shared_ptr<Node> get_default_value() const override;
  
              protected:
                  Strides m_strides;
                  Strides m_dilations;
                  CoordinateDiff m_pads_begin;
                  CoordinateDiff m_pads_end;
                  PadType m_auto_pad;
              };
  
              /// \brief Data batch backprop for batched convolution operation.
              class NGRAPH_API GroupConvolutionBackpropData : public op::util::FusedOp
              {
              public:
                  static constexpr NodeTypeInfo type_info{"GroupConvolutionBackpropData", 1};
                  const NodeTypeInfo& get_type_info() const override { return type_info; }
                  /// \brief Constructs a batched-convolution data batch-backprop operation.
                  GroupConvolutionBackpropData() = default;
                  // clang-format off
                  //
                  // \brief      Constructs a batched-convolution data batch-backprop operation.
                  //
                  // \param      data            The node producing data from forward-prop. Shape: [N,
                  //                             C_INPUT * GROUPS, X1, ..., XD].
                  // \param      filter          The node producing the filter from forward-prop. Shape:
                  //                             [GROUPS, C_INPUT, C_OUTPUT, K_D, ..., K_1]
                  // \param      output_shape    The shape of the data batch from forward-prop. It's size
                  //                             should be equal to number of data spatial dimensions.
                  // \param      strides         The strides from forward-prop.
                  // \param      pads_begin      The padding-below sizes from forward-prop.
                  // \param      pads_end        The padding-above sizes from forward-prop.
                  // \param      dilations       The dilations from forward-prop.
                  // \param      auto_pad        The pad type for automatically computing padding sizes.
                  // \param      output_padding  The output padding adds additional amount of paddings per
                  //                             each spatial axis in the output tensor.
                  //
                  // clang-format on
                  //
                  GroupConvolutionBackpropData(const Output<Node>& data,
                                               const Output<Node>& filter,
                                               const Output<Node>& output_shape,
                                               const Strides& strides,
                                               const CoordinateDiff& pads_begin,
                                               const CoordinateDiff& pads_end,
                                               const Strides& dilations,
                                               const PadType& auto_pad = PadType::EXPLICIT,
                                               const CoordinateDiff& output_padding = {});
  
                  // clang-format off
                  //
                  // \brief      Constructs a batched-convolution data batch-backprop operation.
                  //
                  // \param      data            The node producing data from forward-prop. Shape: [N,
                  //                             C_INPUT * GROUPS, X1, ..., XD].
                  // \param      filter          The node producing the filter from forward-prop. Shape:
                  //                             [GROUPS, C_INPUT, C_OUTPUT, K_D, ..., K_1]
                  // \param      output_shape    The shape of the data batch from forward-prop. It's size
                  //                             should be equal to number of data spatial dimensions.
                  // \param      strides         The strides from forward-prop.
                  // \param      dilations       The dilations from forward-prop.
                  // \param      auto_pad        The pad type for automatically computing padding sizes.
                  // \param      output_padding  The output padding adds additional amount of paddings per
                  //                             each spatial axis in the output tensor.
                  //
                  // clang-format on
                  //
                  GroupConvolutionBackpropData(const Output<Node>& data,
                                               const Output<Node>& filter,
                                               const Output<Node>& output_shape,
                                               const Strides& strides,
                                               const Strides& dilations,
                                               const PadType& auto_pad,
                                               const CoordinateDiff& output_padding = {});
  
                  // clang-format off
                  //
                  // \brief      Constructs a batched-convolution data batch-backprop operation.
                  //
                  // \param      data            The node producing data from forward-prop. Shape:
                  //                             [N, C_INPUT * GROUPS, X1, ..., XD].
                  // \param      filter          The node producing the filter from forward-prop. Shape:
                  //                             [GROUPS, C_INPUT, C_OUTPUT, K_D, ..., K_1]
                  // \param      strides         The strides from forward-prop.
                  // \param      pads_begin      The padding-below sizes from forward-prop.
                  // \param      pads_end        The padding-above sizes from forward-prop.
                  // \param      dilations       The dilations from forward-prop.
                  // \param      auto_pad        The pad type for automatically computing padding sizes.
                  // \param      output_padding  The output padding adds additional amount of paddings per
                  //                             each spatial axis in the output tensor.
                  //
                  // clang-format on
                  GroupConvolutionBackpropData(const Output<Node>& data,
                                               const Output<Node>& filter,
                                               const Strides& strides,
                                               const CoordinateDiff& pads_begin,
                                               const CoordinateDiff& pads_end,
                                               const Strides& dilations,
                                               const PadType& auto_pad = PadType::EXPLICIT,
                                               const CoordinateDiff& output_padding = {});
                  ///
                  /// \brief      Calculates output spatial features size.
                  ///
                  /// \param[in]  input_data_shape      The input data partial shape
                  /// \param[in]  filters_shape         The filters partial shape
                  /// \param[in]  strides               The strides values.
                  /// \param[in]  dilations             The dilations values.
                  /// \param[in]  pads_begin            The paddings at the beginning of axis.
                  /// \param[in]  pads_end              The paddings at the end of axis.
                  /// \param[in]  output_padding    The output padding values.
                  /// \param      output_spatial_shape  The placeholder for computed output spatial
                  /// partial
                  /// shape.
                  ///
                  void infer_conv_backprop_output_spatial_shape(
                      const std::vector<Dimension>& input_data_shape,
                      const std::vector<Dimension>& filters_shape,
                      const Strides& strides,
                      const Strides& dilations,
                      const CoordinateDiff& pads_begin,
                      const CoordinateDiff& pads_end,
                      const CoordinateDiff& output_padding,
                      std::vector<Dimension>& output_spatial_shape);
  
                  bool visit_attributes(AttributeVisitor& visitor) override;
                  virtual bool is_dynamic() const override;
                  virtual OutputVector decompose_op() const override;
                  virtual void pre_validate_and_infer_types() override;
  
                  virtual std::shared_ptr<Node>
                      clone_with_new_inputs(const OutputVector& new_args) const override;
  
                  /// \return The spatial shape of the output.
                  const PartialShape get_convolution_output_shape() const;
                  void set_output_shape(const Shape& output_shape);
                  /// \return The strides from the forward prop.
                  const Strides& get_strides() const { return m_strides; }
                  void set_strides(const Strides& strides) { m_strides = strides; }
                  /// \return The dilations from the forward prop.
                  const Strides& get_dilations() const { return m_dilations; }
                  void set_dilations(const Strides& dilations) { m_dilations = dilations; }
                  /// \return The number of pixels to add to the beginning along each axis.
                  const CoordinateDiff& get_pads_begin() const { return m_pads_begin; }
                  void set_pads_begin(const CoordinateDiff& pads_begin) { m_pads_begin = pads_begin; }
                  /// \return The number of pixels to add to the ending along each axis.
                  const CoordinateDiff& get_pads_end() const { return m_pads_end; }
                  void set_pads_end(const CoordinateDiff& pads_end) { m_pads_end = pads_end; }
                  /// \return The auto pad.
                  const PadType& get_auto_pad() const { return m_auto_pad; }
                  void set_auto_pad(const PadType& auto_pad) { m_auto_pad = auto_pad; }
                  /// \return The output padding.
                  const CoordinateDiff& get_output_padding() const { return m_output_padding; }
                  void set_output_padding(const CoordinateDiff& output_padding)
                  {
                      m_output_padding = output_padding;
                  }
  
              protected:
                  Strides m_strides;
                  Strides m_dilations;
                  CoordinateDiff m_pads_begin;
                  CoordinateDiff m_pads_end;
                  PadType m_auto_pad;
                  CoordinateDiff m_output_padding;
              };
          } // namespace v1
      }     // namespace op
  } // namespace ngraph
  
  NGRAPH_SUPPRESS_DEPRECATED_END
  