text: //*****************************************************************************
  // Copyright 2017-2021 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/op.hpp"
  #include "ngraph/op/util/attr_types.hpp"
  
  namespace ngraph
  {
      namespace op
      {
          namespace util
          {
              // clang-format off
              /// \brief Abstract base class for elementwise binary comparison operations, i.e.,
              ///        operations where the same scalar binary comparison operation is applied to
              ///        each corresponding pair of elements in two input tensors. Implicit
              ///        broadcast of input tensors is supported through one of the AutoBroadcast
              ///        modes.
              ///
              /// For example, if the underlying comparison operation (determined by the subclass) is
              /// \f$\mathit{op}(x,y)\f$, the input tensors \f$[[x_0,y_0],[z_0,w_0]]\f$ and
              /// \f$[[x_1,y_1],[z_1,w_1]]\f$ will be mapped to
              /// \f$[[\mathit{op}(x_0,x_1),\mathit{op}(y_0,y_1)],[\mathit{op}(z_0,z_1),\mathit{op}(w_0,w_1)]]\f$.
              ///
              /// ## Inputs
              ///
              /// |        | Type                              | Description                                            |
              /// | ------ | --------------------------------- | ------------------------------------------------------ |
              /// | `arg0` | \f$E[d_1,\dots,d_n]~(n \geq 0)\f$ | A tensor of any shape and element type.                |
              /// | `arg1` | \f$E[d_1,\dots,d_n]~(n \geq 0)\f$ | A tensor of the same shape and element type as `arg0`. |
              /// | `autob`| AutoBroadcastSpec                 | Auto broadcast specification.                          |
              ///
              /// ## Output
              ///
              /// | Type                               | Description                                                                                                                                                                                                        |
              /// | ---------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
              /// | \f$\texttt{bool}[d_1,\dots,d_n]\f$ | The tensor \f$T\f$, where \f$T[i_1,\dots,i_n] = \mathit{op}(\texttt{arg0}[i_1,\dots,i_n],\texttt{arg1}[i_1,\dots,i_n])\f$. This will always have the same shape as the input tensors, and the element type `bool`. |
              // clang-format on
              class NGRAPH_API BinaryElementwiseComparison : public Op
              {
              protected:
                  /// \brief Constructs a binary elementwise comparison operation.
                  BinaryElementwiseComparison(const AutoBroadcastSpec& autob);
  
                  /// \brief Constructs a binary elementwise comparison operation.
                  ///
                  /// \param arg0 Output that produces the first input tensor.
                  /// \param arg1 Output that produces the second input tensor.
                  /// \param autob AutoBroadcast mode.
                  BinaryElementwiseComparison(const Output<Node>& arg0,
                                              const Output<Node>& arg1,
                                              const AutoBroadcastSpec& autob = AutoBroadcastSpec());
  
              public:
                  void validate_and_infer_types() override;
  
                  const AutoBroadcastSpec& get_autob() const override { return m_autob; }
                  void set_autob(const AutoBroadcastSpec& autob) { m_autob = autob; }
                  bool visit_attributes(AttributeVisitor& visitor) override;
  
              private:
                  AutoBroadcastSpec m_autob;
              };
          }
      }
  }
  