text: """
   Copyright (C) 2018-2020 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.
  """
  import logging as log
  
  import numpy as np
  
  from extensions.back.ForceStrictPrecision import ForceStrictPrecision
  from mo.back.replacement import BackReplacementPattern
  from mo.front.common.partial_infer.utils import int64_array
  from mo.front.tf.graph_utils import create_op_node_with_second_input
  from mo.graph.graph import Graph
  from mo.ops.squeeze import Squeeze
  
  
  class Reshape0DToSqueeze(BackReplacementPattern):
      """
      Transformation looks for the Reshape layers which generate 0D tensor and replace them with Reshape_1D->Squeeze to
      overcome issue the IE doesn't 1D constants with value [0] which is generated for the Reshape to OD case.
      """
      enabled = True
      run_not_recursively = True
      force_shape_inference = True
  
      def run_before(self):
          return [ForceStrictPrecision]
  
      def find_and_replace_pattern(self, graph: Graph):
          for reshape_node in graph.get_op_nodes(op='Reshape'):
              output_shape = reshape_node.in_port(1).data.get_value()
              shape_producer_node = reshape_node.in_port(1).get_source().node
              assert output_shape is not None
              if np.array_equal(output_shape, []) and shape_producer_node.op == 'Const':
                  log.debug('Reshape node {} changes shape to 0D tensor.'.format(reshape_node.name))
                  shape_producer_node.value = int64_array([1])
                  shape_producer_node.shape = int64_array([1])
                  shape_producer_node['need_shape_inference'] = True
                  shape_producer_node['override_output_shape'] = True
  
                  reshape_node['need_shape_inference'] = True
                  reshape_node['override_output_shape'] = True
  
                  squeeze_0D = create_op_node_with_second_input(graph, Squeeze, int64_array([0]))
                  squeeze_0D['override_output_shape'] = True
  
                  reshape_node.out_port(0).get_connection().insert_node(squeeze_0D)
  