model-optimizer/extensions/front/mxnet/ssd_pattern_flatten_softmax_activation.py

   1 """
   2  Copyright (c) 2017-2019 Intel Corporation
   3
   4  Licensed under the Apache License, Version 2.0 (the "License");
   5  you may not use this file except in compliance with the License.
   6  You may obtain a copy of the License at
   7
   8       http://www.apache.org/licenses/LICENSE-2.0
   9
  10  Unless required by applicable law or agreed to in writing, software
  11  distributed under the License is distributed on an "AS IS" BASIS,
  12  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  13  See the License for the specific language governing permissions and
  14  limitations under the License.
  15 """
  16
  17 import networkx as nx
  18
  19 from extensions.front.mxnet.ssd_pattern_remove_flatten import SsdPatternRemoveFlatten
  20 from extensions.front.mxnet.ssd_pattern_remove_reshape import SsdPatternRemoveReshape
  21 from mo.front.common.replacement import FrontReplacementSubgraph
  22 from mo.graph.graph import Graph
  23 from mo.ops.reshape import Reshape
  24
  25
  26 class SsdPatternFlattenSoftmaxActivation(FrontReplacementSubgraph):
  27     enabled = True
  28
  29     def run_before(self):
  30         return [SsdPatternRemoveFlatten, SsdPatternRemoveReshape]
  31
  32     def pattern(self):
  33         return dict(
  34             nodes=[
  35                 ('softmax_activation', dict(op='SoftMax')),
  36                 ('multi_box_detection', dict(op='_contrib_MultiBoxDetection'))
  37             ],
  38             edges=[
  39                 ('softmax_activation', 'multi_box_detection', {'in': 1})
  40             ]
  41         )
  42
  43     def replace_sub_graph(self, graph: Graph, match: dict):
  44         """
  45         Need to find the pattern: SoftmaxActivation -> DetectionOutput
  46         DetectionOutput in IE expects flattened input from SoftMax, that is why there is the need to add
  47         Flatten layer
  48
  49         Parameters
  50         ----------
  51         graph : Graph
  52            Graph with loaded model.
  53          match : dict
  54            Patterns which were found in graph structure.
  55         """
  56         softmax_activation = match['softmax_activation']
  57         multi_box_detection = match['multi_box_detection']
  58         softmax_activation['axis'] = -1
  59         edge_data = graph.get_edge_data(softmax_activation.id, multi_box_detection.id)
  60         out_port = edge_data[0]['out']
  61         in_port = edge_data[0]['in']
  62         graph.remove_edge(softmax_activation.id, multi_box_detection.id)
  63         symbol_node = dict(
  64             op='Flatten',
  65             name=multi_box_detection.name + '/Reshape_',
  66             dim=[0, -1],
  67             axis=1,
  68             end_axis=-1
  69         )
  70         new_reshape_op = Reshape(graph, {'symbol_dict': symbol_node})
  71         new_reshape_node = new_reshape_op.create_node([softmax_activation])
  72         new_reshape_node['dim'] = [0, -1]
  73         graph.create_edge(new_reshape_node, multi_box_detection, in_port=in_port, out_port=out_port)