text: #!/usr/bin/env python
  # -*- coding: utf-8 -*-
  #
  # Copyright (c) 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.
  
  from tensorflow.python.framework import tensor_util
  import tensorflow as tf
  from neural_compressor.utils import logger
  import numpy as np
  from ..graph.graph import Graph
  from ..ops.op import OPERATORS
  from ..tf_utils import graph_node_names_details
  from ..graph_utils import names_from_input
  
  
  class TensorflowExtractor(object):
      """
      Decorate the node in model.graph_def, and the new node has the attributes like input_tensors
      and output_tensors, these tensors record the source/dest op name. All of these nodes
      (in a list) will compose a graph, which is Graph class, as the return object.
      Args:
          model: neural_compressor TensorflowBaseModel
      Return:
          Graph: Graph class, the new graph object
  
      """
      @classmethod
      def __call__(self, model):
  
          nodes = model.graph_def.node
          graph_nodes_dict = graph_node_names_details(nodes)
          logger.info('Start to extarct tensorflow model ops...')
          new_graph = Graph()
          new_graph.framework = 'tensorflow'
          for node in nodes:
              # ignore the Const nodes, they have no source inputs
              if node.op == 'Const':
                  continue
              else:
                  op_type = node.op
                  if op_type in OPERATORS.keys():
                      new_node = OPERATORS[op_type]()
                      new_node.extract('tensorflow', node, model, graph_nodes_dict)
                      new_graph.insert_nodes(len(new_graph.nodes), [new_node])
                  else:
                      raise ValueError('the {} operation does not support now...'.format(op_type))
  
          return new_graph
  