text: """
   Copyright (C) 2017-2020 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 numpy as np
  
  from mo.graph.graph import Node, Graph
  from mo.ops.op import Op
  
  
  class ConstantFill(Op):
      """ Constant blob generation by broadcasting specified value to a given shape.
  
          It is assumed that there is no equivalent of this op in IE,
          so it is usually relevant to constant folding.
      """
      op = 'ConstantFill'
  
      def __init__(self, graph: Graph, attrs: dict):
          mandatory_props = {
              'type': __class__.op,
              'op': __class__.op,
              'input_as_shape': 1,
              'in_ports_count': 1,
              'out_ports_count': 1,
              'infer': __class__.infer
          }
          super().__init__(graph, mandatory_props, attrs)
  
      def supported_attrs(self):
          return [
              'input_as_shape',
              'fill_value'
          ]
  
      @staticmethod
      def infer(node: Node):
          assert len(node.in_nodes()) == 1
          assert node.fill_value is not None
          assert node.input_as_shape
  
          shape = node.in_node(0).value
          assert shape is not None
  
          node.out_node(0).value = np.full(shape, node.fill_value, np.float32)
          node.out_node(0).shape = np.array(node.out_node(0).value.shape, dtype=np.int64)
  