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
36 lines
1.1 KiB
Python
36 lines
1.1 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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import numpy as np
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from mo.front.extractor import FrontExtractorOp
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from mo.front.onnx.extractors.utils import onnx_attr
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from mo.ops.reshape import Reshape
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class ReshapeFrontExtractor(FrontExtractorOp):
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op = 'Reshape'
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enabled = True
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@classmethod
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def extract(cls, node):
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dim = onnx_attr(node, 'shape', 'ints', None)
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if dim is not None:
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dim = np.array(dim, dtype=np.int64)
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Reshape.update_node_stat(node, {'dim': dim})
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else:
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Reshape.update_node_stat(node)
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return cls.enabled
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