Eugeny Volosenkov
6f512142b6
* add class ConcatFrontExtractor for onnx * add class ConcatFrontExtractor for onnx * Delete concat from mo/front/onnx/extractor.py * Add identity, reshape extractors classes for onnx * import FrontExtractorOp * Added BatchNormalizationExtractor * Added extra line * Fix import modules * fix caffe bn.py and bn_test.py * Fix BatchNormInference * Modify convert_batch_norm * Modify convert_batch_norm * Modify bn_test.py * Fix old comments BN->batchNormInference
40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
"""
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Copyright (C) 2018-2020 Intel Corporation
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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"""
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from mo.graph.graph import Graph
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from mo.ops.op import Op
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class BatchNormInference(Op):
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"""
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BatchNormInference will be replaced by BNToScaleShift FrontReplacer for Caffe or convert_batch_norm
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function for other frameworks
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"""
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op = 'batchNormInference'
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enabled = False
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def __init__(self, graph: Graph, attrs: dict):
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super().__init__(graph, {
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'type': None,
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'op': self.op,
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'in_ports_count': 5,
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'out_ports_count': 1,
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'infer': self.infer
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}, attrs)
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@staticmethod
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def infer(node):
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node.out_port(0).data.set_shape(node.in_port(0).data.get_shape())
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