43 lines
1.3 KiB
Python
43 lines
1.3 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.mxnet.extractors.utils import get_mxnet_layer_attrs
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from mo.ops.pad import AttributedPad
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class PadFrontExtractor(FrontExtractorOp):
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op = 'Pad'
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enabled = True
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@classmethod
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def extract(cls, node):
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attrs = get_mxnet_layer_attrs(node.symbol_dict)
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pads = np.array(list(attrs.tuple('pad_width', int, None)))
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pads = pads.reshape([-1, 2])
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value = attrs.float('constant_value', 0.0)
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node_attrs = {
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'pads': pads,
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'mode': attrs.str('mode', None),
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'fill_value': value,
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}
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AttributedPad.update_node_stat(node, node_attrs)
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return cls.enabled
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