text: //*****************************************************************************
  // Copyright 2017-2019 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/graph_util.hpp"
  #include "ngraph/op/op.hpp"
  #include "ngraph/op/util/attr_types.hpp"
  
  namespace ngraph
  {
      namespace op
      {
          /// \brief Batched convolution operation, with optional window dilation and stride.
          ///
          class Convolution : public Op
          {
          public:
              NGRAPH_API
              static const std::string type_name;
              const std::string& description() const override { return type_name; }
              /// \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;
  
              virtual std::shared_ptr<Node>
                  copy_with_new_args(const NodeVector& new_args) const override;
              void generate_adjoints(autodiff::Adjoints& adjoints, const NodeVector& 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
              {
                  return ngraph::make_constant_from_string("0", get_element_type(), get_shape());
              }
  
          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 ConvolutionBackpropData : public Op
          {
          public:
              NGRAPH_API
              static const std::string type_name;
              const std::string& description() const override { return type_name; }
              /// \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 output_delta 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>& output_delta,
                                      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;
  
              void generate_adjoints(autodiff::Adjoints& adjoints, const NodeVector& deltas) override;
              virtual std::shared_ptr<Node>
                  copy_with_new_args(const NodeVector& 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;
          };
  
          /// \brief Filters backprop for batched convolution operation.
          class ConvolutionBackpropFilters : public Op
          {
          public:
              NGRAPH_API
              static const std::string type_name;
              const std::string& description() const override { return type_name; }
              /// \brief Constructs a batched-convolution filter-backprop operation.
              ConvolutionBackpropFilters() = default;
              /// \brief Constructs a batched-convolution filter-backprop operation.
              ///
              /// \param data_batch The tensor producing the data batch from forward-prop.
              /// \param filters_shape The shape of the filters from forward-prop.
              /// \param output_delta 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.
              ConvolutionBackpropFilters(const Output<Node>& data_batch,
                                         const Shape& filters_shape,
                                         const Output<Node>& output_delta,
                                         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;
  
              virtual std::shared_ptr<Node>
                  copy_with_new_args(const NodeVector& new_args) const override;
  
              /// \return The filters tensor shape.
              const Shape& get_filters_shape() const { return m_filters_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 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 value to be used if in a convolution
              CoordinateDiff compute_backward_in_pad_above() const;
  
          protected:
              Shape m_filters_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 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.
              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);
          }
      }
  }
  