dec7df17ed
* Remove unnnecessary ir_version checks in the MO * Cleaned up 'backend_attrs_v2' function * Small clean up from the 'TFCustomSubgraphCall' * Clean up the MO extractor attributes mapping * Renamed PreluOp to PReLU
58 lines
2.0 KiB
Python
58 lines
2.0 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.front.common.partial_infer.elemental import copy_shape_infer
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from mo.front.common.partial_infer.utils import mark_input_bins
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from mo.graph.graph import Graph, Node
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from mo.ops.op import Op
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class NormalizeOp(Op):
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op = 'Normalize'
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enabled = True
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def __init__(self, graph: Graph, attrs: dict):
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super().__init__(graph, {
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'type': self.op,
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'op': self.op,
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'eps': None,
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'in_ports_count': 2,
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'out_ports_count': 1,
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'infer': self.infer
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}, attrs)
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if 'across_spatial' in self.attrs and isinstance(self.attrs['across_spatial'], str):
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self.attrs['across_spatial'] = int(self.attrs['across_spatial'])
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if 'channel_shared' in self.attrs and isinstance(self.attrs['channel_shared'], str):
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self.attrs['channel_shared'] = int(self.attrs['channel_shared'])
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self.attrs['across_spatial'] = bool(self.attrs['across_spatial'])
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self.attrs['channel_shared'] = bool(self.attrs['channel_shared'])
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def supported_attrs(self):
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return ['eps', 'eps_mode',
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('across_spatial',
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lambda node: bool(node.across_spatial) if node.has_valid('across_spatial') else None),
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('channel_shared',
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lambda node: bool(node.channel_shared) if node.has_valid('channel_shared') else None),
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]
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@staticmethod
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def infer(node: Node):
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mark_input_bins(node)
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copy_shape_infer(node)
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