text: """
   Copyright (C) 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 mo.front.common.partial_infer.utils import int64_array
  from mo.front.common.replacement import FrontReplacementPattern
  from mo.front.tf.graph_utils import create_op_with_const_inputs
  from mo.graph.graph import Graph
  from mo.ops.reshape import Reshape
  
  
  class OneHotDepthNormalizer(FrontReplacementPattern):
      """
      Transformation performs squeezeng one-element tensors on 1st input in OneHot into 0D scalars. This transformation
      allows to avoid problems with some models produced by tf2onnx which have 1D depth in OneHot.
      """
      enabled = True
  
      def pattern(self):
          return dict(
              nodes=[
                  ('onehot', dict(kind='op', type='OneHot'))],
              edges=[]
          )
  
      @staticmethod
      def replace_pattern(graph: Graph, match: dict):
          node = match['onehot']
          node_name = node.soft_get('name', node.id)
          reshape = create_op_with_const_inputs(graph, Reshape, {1: int64_array([])}, {'name': node_name + '/Reshape'})
          node.in_port(1).get_connection().insert_node(reshape)
  