text: """
   Copyright (C) 2018-2021 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 mo.front.extractor import attr_getter
  from mo.graph.graph import Node, Graph
  from mo.ops.op import Op
  
  
  class SimplerNMSOp(Op):
      op = 'SimplerNMS'
  
      def __init__(self, graph: Graph, attrs: dict):
          mandatory_props = {
              'type': __class__.op,
              'op': __class__.op,
              'version': 'experimental',
              'in_ports_count': 3,
              'out_ports_count': 1,
              'infer': SimplerNMSOp.simplernms_infer
          }
          super().__init__(graph, mandatory_props, attrs)
  
      def supported_attrs(self):
          return [
              'cls_threshold',
              'max_num_proposals',
              'iou_threshold',
              'min_bbox_size',
              'feat_stride',
              'pre_nms_topn',
              'post_nms_topn',
              'scale'
          ]
  
      def backend_attrs(self):
          return [
              'cls_threshold',
              'max_num_proposals',
              'iou_threshold',
              'min_bbox_size',
              'feat_stride',
              'pre_nms_topn',
              'post_nms_topn',
              ('scale', lambda node: attr_getter(node, 'scale'))
          ]
  
      @staticmethod
      def simplernms_infer(node: Node):
          """
             Sets shape of output node according to specified param of post_nms_topn
             and number of the following params: [is_obj, x, y, w, h]
             Parameters
             ----------
             node
  
             """
          if node.feat_stride != 16:
              log.error("SimplerNMS layer doesn't support other feat_stride value that 16")
              return
  
          scale_list = []
          for i in range(0, len(node.scale)):
              scale_list.append(str(node.scale[i]))
  
          node.scale = scale_list
  
          node.out_node().shape = np.array([node.post_nms_topn, 5])
  