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.
  """
  
  from extensions.middle.ONNXRNNSequenceNormalize import ONNXRNNSequenceNormalize
  from extensions.middle.TF_lstm_cell_to_generic import TensorFlowLSTMtoGeneric
  from extensions.middle.TensorIteratorMerge import TensorIteratorMerge
  from mo.graph.graph import Graph
  from mo.middle.pattern_match import find_isomorphisms
  from mo.middle.replacement import MiddleReplacementPattern
  from mo.utils.error import Error
  
  
  class TensorIteratorLSTM(MiddleReplacementPattern):
      """ Detects TensorIterator with LSTMCell of supported form.
  
          Collect original operation names of supported LSTMCells in
          the list LSTMCell.instances_supported_by_IE. It will be used at the second
          round of the network translation. Mark all supported LSTMCell with flag
          supported_by_IE to have a chance to detect all not-supported instances
          in a separate pass.
      """
  
      enabled = False
  
      def run_after(self):
          return [TensorIteratorMerge, ONNXRNNSequenceNormalize, TensorFlowLSTMtoGeneric]
  
      def pattern(self):
          return dict(
              nodes=[
                  ('ti', dict(kind='op', op='TensorIterator')),
              ],
              edges=[
              ]
          )
  
      @staticmethod
      def replace_pattern(graph: Graph, match: dict):
          nodes = [
              ('input_unsqueezed'),
              ('squeeze', dict(op='Reshape')),
              ('input_squeezed'),
              ('input_hidden'),
              ('input_cell'),
              ('weights'),
              ('biases'),
  
              ('lstm', dict(op='LSTMCell')),
  
              ('output_hidden'),
              ('output_cell'),
              ('unsqueeze', dict(op='Reshape')),
              ('output_unsqueezed'),
          ]
          edges = [
              ('input_unsqueezed', 'squeeze'),
              ('squeeze', 'input_squeezed'),
  
              ('input_squeezed', 'lstm', {'in': 0}),
              ('input_hidden', 'lstm', {'in': 1}),
              ('input_cell', 'lstm', {'in': 2}),
              ('weights', 'lstm', {'in': 3}),
              ('biases', 'lstm', {'in': 4}),
  
              ('lstm', 'output_hidden', {'out': 0}),
              ('lstm', 'output_cell', {'out': 1}),
  
              ('output_hidden', 'unsqueeze'),
              ('unsqueeze', 'output_unsqueezed'),
          ]
          ti = match['ti']
          isomorphisms = find_isomorphisms(ti.body, nodes, edges)
          if len(list(isomorphisms)) != 1:
              raise Error('Unsupported TensorIterator layer {} was found: either its body, ports or '
                          'edges are not supported by Inference Engine. '
                          'Only TensorIterator with LSTMCell in a body of strict form is supported. '
                          'Please modify the original network '
                          'to meet the requirements.'.format(ti.soft_get('name')))
          body_match = isomorphisms[0]
          if body_match['input_hidden'].has_valid('value') or body_match['input_cell'].has_valid('value'):
              raise Error('Unsupported TensorIterator layer {} was found: initial hidden and/or cell states '
                          'for LSTMCell are constants. This is not supported. '
                          'Only TensorIterator with LSTMCell in a body of strict form is supported. '
                          'Please modify the original network '
                          'to meet the requirements.'.format(ti.soft_get('name')))
          # TODO Additional checks for port indices
  