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/coordinate_diff.hpp"
  #include "ngraph/op/op.hpp"
  #include "ngraph/op/util/attr_types.hpp"
  
  namespace ngraph
  {
      namespace op
      {
          namespace v1
          {
              /// \brief Batched convolution operation, with optional window dilation and stride.
              ///
              class NGRAPH_API Convolution : public Op
              {
              public:
                  static constexpr NodeTypeInfo type_info{"Convolution", 1};
                  const NodeTypeInfo& get_type_info() const override { return type_info; }
                  /// \brief Constructs a batched convolution operation.
                  Convolution() = 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>
                  /// `[C_OUT, C_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, C_OUT, R1, ... Rf]`
                  ///
                  Convolution(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);
  
                  void validate_and_infer_types() override;
                  bool visit_attributes(AttributeVisitor& visitor) override;
  
                  virtual std::shared_ptr<Node>
                      clone_with_new_inputs(const OutputVector& new_args) const override;
                  void generate_adjoints(autodiff::Adjoints& adjoints,
                                         const OutputVector& deltas) 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 ConvolutionBackpropData : public Op
              {
              public:
                  static constexpr NodeTypeInfo type_info{"ConvolutionBackpropData", 1};
                  const NodeTypeInfo& get_type_info() const override { return type_info; }
                  /// \brief Constructs a batched-convolution data batch-backprop operation.
                  ConvolutionBackpropData() = 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, X1, ..., XD].
                  // \param      filters         The node producing the filter from forward-prop. Shape:
                  //                             [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
                  //
                  ConvolutionBackpropData(const Output<Node>& data,
                                          const Output<Node>& filters,
                                          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, X1, ..., XD].
                  // \param      filters         The node producing the filter from forward-prop. Shape:
                  //                             [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
                  //
                  ConvolutionBackpropData(const Output<Node>& data,
                                          const Output<Node>& filters,
                                          const Strides& strides,
                                          const CoordinateDiff& pads_begin,
                                          const CoordinateDiff& pads_end,
                                          const Strides& dilations,
                                          const PadType& auto_pad = PadType::EXPLICIT,
                                          const CoordinateDiff& output_padding = {});
  
                  void validate_and_infer_types() override;
                  bool visit_attributes(AttributeVisitor& visitor) override;
                  virtual bool is_dynamic() const override;
  
                  void generate_adjoints(autodiff::Adjoints& adjoints,
                                         const OutputVector& deltas) override;
                  virtual std::shared_ptr<Node>
                      clone_with_new_inputs(const OutputVector& new_args) const override;
  
                  /// \return The output spatial dimensions shape.
                  const PartialShape get_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 padding-below sizes (possibly negative) from the forward prop.
                  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) from the forward prop.
                  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;
                  }
                  /// \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);
  
              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 v0
          {
              /// \brief Batched convolution operation, with optional window dilation and stride.
              ///
              class NGRAPH_API Convolution : public Op
              {
              public:
                  static constexpr NodeTypeInfo type_info{"Convolution", 0};
                  const NodeTypeInfo& get_type_info() const override { return type_info; }
                  /// \brief Constructs a batched convolution operation.
                  Convolution() = 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>
                  /// `[C_OUT, C_IN, F1, ... Ff]`
                  /// \param window_movement_strides The window movement strides.<br>
                  /// `[f]`
                  /// \param window_dilation_strides The window dilation strides.<br>
                  /// `[f]`
                  /// \param padding_below The padding-below sizes.<br>
                  /// `[f]`
                  /// \param padding_above The padding-above sizes.<br>
                  /// `[f]`
                  /// \param data_dilation_strides The data dilation strides.<br>
                  /// `[f]`
                  /// \param pad_type The pad type for automatically computing padding sizes.<br>
                  /// `[f]`
                  ///
                  /// Output `[N, C_OUT, R1, ... Rf]`
                  ///
                  Convolution(const Output<Node>& data_batch,
                              const Output<Node>& filters,
                              const Strides& window_movement_strides,
                              const Strides& window_dilation_strides,
                              const CoordinateDiff& padding_below,
                              const CoordinateDiff& padding_above,
                              const Strides& data_dilation_strides,
                              const PadType& pad_type = PadType::EXPLICIT);
  
                  /// \brief Constructs a batched convolution operation with no data dilation (i.e.,
                  /// all
                  ///        data dilation strides are 1).
                  ///
                  /// \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>
                  /// `[C_OUT, C_IN, F1, ... Ff]`
                  /// \param window_movement_strides The window movement strides.<br>
                  /// `[f]`
                  /// \param window_dilation_strides The window dilation strides.<br>
                  /// `[f]`
                  /// \param padding_below The padding-below sizes.<br>
                  /// `[f]`
                  /// \param padding_above The padding-above sizes.<br>
                  /// `[f]`
                  ///
                  /// Output `[N, C_OUT, R1, ... Rf]`
                  ///
                  Convolution(const Output<Node>& data_batch,
                              const Output<Node>& filters,
                              const Strides& window_movement_strides,
                              const Strides& window_dilation_strides,
                              const CoordinateDiff& padding_below,
                              const CoordinateDiff& padding_above);
  
                  /// \brief Constructs a batched convolution operation with no padding or data
                  /// dilation
                  ///        (i.e., padding above and below are 0 everywhere, and all data dilation
                  ///        strides are 1).
                  ///
                  /// \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>
                  /// `[C_OUT, C_IN, F1, ... Ff]`
                  /// \param window_movement_strides The window movement strides.<br>
                  /// `[f]`
                  /// \param window_dilation_strides The window dilation strides.<br>
                  /// `[f]`
                  ///
                  /// Output `[N, C_OUT, R1, ... Rf]`
                  ///
                  Convolution(const Output<Node>& data_batch,
                              const Output<Node>& filters,
                              const Strides& window_movement_strides,
                              const Strides& window_dilation_strides);
  
                  /// \brief Constructs a batched convolution operation with no window dilation,
                  /// padding,
                  ///        or data dilation (i.e., padding above and below are 0 everywhere, and all
                  ///        window/data dilation strides are 1).
                  ///
                  /// \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>
                  /// `[C_OUT, C_IN, F1, ... Ff]`
                  /// \param window_movement_strides The window movement strides.<br>
                  /// `[f]`
                  ///
                  /// Output `[N, C_OUT, R1, ... Rf]`
                  ///
                  Convolution(const Output<Node>& data_batch,
                              const Output<Node>& filters,
                              const Strides& window_movement_strides);
  
                  /// \brief Constructs a batched convolution operation with no window dilation or
                  ///        movement stride (i.e., padding above and below are 0 everywhere, and all
                  ///        window/data dilation strides and window movement strides are 1).
                  ///
                  /// \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>
                  /// `[C_OUT, C_IN, F1, ... Ff]`
                  ///
                  /// Output `[N, C_OUT, R1, ... Rf]`
                  ///
                  Convolution(const Output<Node>& data_batch, const Output<Node>& filters);
  
                  void validate_and_infer_types() override;
                  bool visit_attributes(AttributeVisitor& visitor) override;
  
                  virtual std::shared_ptr<Node>
                      clone_with_new_inputs(const OutputVector& new_args) const override;
                  void generate_adjoints(autodiff::Adjoints& adjoints,
                                         const OutputVector& deltas) override;
  
                  /// \return The window movement strides.
                  const Strides& get_window_movement_strides() const
                  {
                      return m_window_movement_strides;
                  }
                  void set_window_movement_strides(const Strides& window_movement_strides)
                  {
                      m_window_movement_strides = window_movement_strides;
                  }
                  /// \return The window dilation strides.
                  const Strides& get_window_dilation_strides() const
                  {
                      return m_window_dilation_strides;
                  }
                  void set_window_dilation_strides(const Strides& window_dilation_strides)
                  {
                      m_window_dilation_strides = window_dilation_strides;
                  }
                  /// \return The padding-below sizes (possibly negative).
                  const CoordinateDiff& get_padding_below() const { return m_padding_below; }
                  void set_padding_below(const CoordinateDiff& padding_below)
                  {
                      m_padding_below = padding_below;
                  }
                  /// \return The padding-above sizes (possibly negative).
                  const CoordinateDiff& get_padding_above() const { return m_padding_above; }
                  void set_adding_above(const CoordinateDiff& padding_above)
                  {
                      m_padding_above = padding_above;
                  }
                  /// \return The input data dilation strides.
                  const Strides& get_data_dilation_strides() const { return m_data_dilation_strides; }
                  void set_data_dilation_strides(const Strides& data_dilation_strides)
                  {
                      m_data_dilation_strides = data_dilation_strides;
                  }
                  /// \return The pad type for convolution.
                  const PadType& get_pad_type() const { return m_pad_type; }
                  void set_pad_type(const PadType& pad_type) { m_pad_type = pad_type; }
                  /// \return The default value for Convolution.
                  virtual std::shared_ptr<Node> get_default_value() const override;
  
              protected:
                  Strides m_window_movement_strides;
                  Strides m_window_dilation_strides;
                  CoordinateDiff m_padding_below;
                  CoordinateDiff m_padding_above;
                  Strides m_data_dilation_strides;
                  PadType m_pad_type;
              };
  
              /// \brief Data batch backprop for batched convolution operation.
              class NGRAPH_API ConvolutionBackpropData : public Op
              {
              public:
                  static constexpr NodeTypeInfo type_info{"ConvolutionBackpropData", 0};
                  const NodeTypeInfo& get_type_info() const override { return type_info; }
                  /// \brief Constructs a batched-convolution data batch-backprop operation.
                  ConvolutionBackpropData() = default;
                  ///
                  /// \brief      Constructs a batched-convolution data batch-backprop operation.
                  ///
                  /// \param      data_batch_shape                 The shape of the data batch from
                  ///                                              forward-prop.
                  /// \param      filters                          The node producing the filters from
                  ///                                              forward-prop.
                  /// \param      data                             The node producing output delta.
                  /// \param      window_movement_strides_forward  The window movement strides from
                  ///                                              forward-prop.
                  /// \param      window_dilation_strides_forward  The window dilation strides from
                  ///                                              forward-prop.
                  /// \param      padding_below_forward            The padding-below sizes from
                  ///                                              forward-prop.
                  /// \param      padding_above_forward            The padding-above sizes from
                  ///                                              forward-prop.
                  /// \param      data_dilation_strides_forward    The data dilation strides from
                  ///                                              forward-prop.
                  ///
                  ConvolutionBackpropData(const Shape& data_batch_shape,
                                          const Output<Node>& filters,
                                          const Output<Node>& data,
                                          const Strides& window_movement_strides_forward,
                                          const Strides& window_dilation_strides_forward,
                                          const CoordinateDiff& padding_below_forward,
                                          const CoordinateDiff& padding_above_forward,
                                          const Strides& data_dilation_strides_forward);
  
                  void validate_and_infer_types() override;
                  bool visit_attributes(AttributeVisitor& visitor) override;
  
                  void generate_adjoints(autodiff::Adjoints& adjoints,
                                         const OutputVector& deltas) override;
                  virtual std::shared_ptr<Node>
                      clone_with_new_inputs(const OutputVector& new_args) const override;
  
                  /// \return The data batch shape.
                  const Shape& get_data_batch_shape() const { return m_data_batch_shape; }
                  void set_data_batch_shape(const Shape& data_batch_shape)
                  {
                      m_data_batch_shape = data_batch_shape;
                  }
                  /// \return The window movement strides from the forward prop.
                  const Strides& get_window_movement_strides_forward() const
                  {
                      return m_window_movement_strides_forward;
                  }
                  void set_window_movement_strides_forward(
                      const Strides& window_movement_strides_forward)
                  {
                      m_window_movement_strides_forward = window_movement_strides_forward;
                  }
                  /// \return The window dilation strides from the forward prop.
                  const Strides& get_window_dilation_strides_forward() const
                  {
                      return m_window_dilation_strides_forward;
                  }
                  void set_window_dilation_strides_forward(
                      const Strides& window_dilation_strides_forward)
                  {
                      m_window_dilation_strides_forward = window_dilation_strides_forward;
                  }
                  /// \return The padding-below sizes (possibly negative) from the forward prop.
                  const CoordinateDiff& get_padding_below_forward() const
                  {
                      return m_padding_below_forward;
                  }
                  void set_padding_below_forward(const CoordinateDiff& padding_below_forward)
                  {
                      m_padding_below_forward = padding_below_forward;
                  }
                  /// \return The padding-above sizes (possibly negative) from the forward prop.
                  const CoordinateDiff& get_padding_above_forward() const
                  {
                      return m_padding_above_forward;
                  }
                  void set_padding_above_forward(const CoordinateDiff& padding_above_forward)
                  {
                      m_padding_above_forward = padding_above_forward;
                  }
                  /// \return The input data dilation strides from the forward prop.
                  const Strides& get_data_dilation_strides_forward() const
                  {
                      return m_data_dilation_strides_forward;
                  }
                  void set_data_dilation_strides_forward(const Strides& data_dilation_strides_forward)
                  {
                      m_data_dilation_strides_forward = data_dilation_strides_forward;
                  }
  
                  // Compute the pad_above values to be used if in a convolution
                  CoordinateDiff compute_backward_delta_out_pad_above() const;
                  CoordinateDiff compute_backward_delta_out_pad_below() const;
  
              protected:
                  Shape m_data_batch_shape;
                  Strides m_window_movement_strides_forward;
                  Strides m_window_dilation_strides_forward;
                  CoordinateDiff m_padding_below_forward;
                  CoordinateDiff m_padding_above_forward;
                  Strides m_data_dilation_strides_forward;
              };
          } // namespace v0
  
          namespace util
          {
              // This is a legacy function, retained because the CPU backend uses it for now.
              // TODO: Update CPU backend to use the new stuff in validation_util.hpp, and remove this
              // function.
              NGRAPH_API
              Shape infer_convolution_output_shape(const Node* node,
                                                   const Shape& data_batch_shape,
                                                   const Shape& filters_shape,
                                                   const Strides& window_movement_strides,
                                                   const Strides& window_dilation_strides,
                                                   const CoordinateDiff& padding_below,
                                                   const CoordinateDiff& padding_above,
                                                   const Strides& data_dilation_strides,
                                                   size_t batch_axis_data,
                                                   size_t input_channel_axis_data,
                                                   size_t input_channel_axis_filters,
                                                   size_t output_channel_axis_filters,
                                                   size_t batch_axis_result,
                                                   size_t output_channel_axis_result);
          } // namespace util
  
          using v0::Convolution;
          using v0::ConvolutionBackpropData;
      } // namespace op
  } // namespace ngraph
  