text: """
   Copyright (c) 2018-2019 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 numpy as np
  
  from extensions.ops.elementwise import Maximum, Mul
  from mo.graph.graph import Graph
  from mo.middle.replacement import MiddleReplacementPattern
  from mo.ops.const import Const
  
  
  class MinimumMiddleReplacer(MiddleReplacementPattern):
      enabled = True
  
      def run_after(self):
          from extensions.middle.pass_separator import MiddleStart
          return [MiddleStart]
  
      def run_before(self):
          from extensions.middle.pass_separator import MiddleFinish
          return [MiddleFinish]
  
      def pattern(self):
          return dict(
              nodes=[
                  ('minimum', dict(kind='op', op='Minimum'))
              ],
              edges=[]
          )
  
      def replace_pattern(self, graph: Graph, match: dict):
          node = match['minimum']
          # Constant propagation case
          if node.in_node(0).value is not None and node.in_node(1).value is not None:
              return
  
          neg_1_const = Const(graph, dict(value=np.array(-1), name=node.name + '/negate1_const'))
          neg_2_const = Const(graph, dict(value=np.array(-1), name=node.name + '/negate2_const'))
          negate_1 = Mul(graph, dict(name=node.name + '/negate1_'))
          negate_2 = Mul(graph, dict(name=node.name + '/negate2_'))
          maximum = Maximum(graph, dict(name=node.name + '/Max_'))
          negate_output_const = Const(graph, dict(value=np.array(-1), name=node.name + '/negate_out_const_'))
          negate_output = Mul(graph, dict(scale=-1, name=node.name + '/negate_out_'))
  
          negate_output.create_node_with_data(
              inputs=[
                  maximum.create_node_with_data(
                      [negate_1.create_node_with_data([node.in_node(0), neg_1_const.create_node_with_data()]),
                       negate_2.create_node_with_data([node.in_node(1), neg_2_const.create_node_with_data()])]),
                  negate_output_const.create_node_with_data()
              ],
              data_nodes=node.out_node())
          # Delete minimum vertex
          node.graph.remove_node(node.id)
  