44 lines
1.4 KiB
Python
44 lines
1.4 KiB
Python
# Copyright (C) 2018-2021 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import numpy as np
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from extensions.back.ForceStrictPrecision import ForceStrictPrecision
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from extensions.ops.prelu import PReLU
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from mo.back.replacement import BackReplacementPattern
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from mo.graph.graph import Graph, rename_node
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from mo.ops.const import Const
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class LeakyReLUMutation(BackReplacementPattern):
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enabled = True
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force_clean_up = True
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def run_before(self):
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return [ForceStrictPrecision]
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@staticmethod
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def pattern():
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return dict(
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nodes=[('leakyrelu', dict(kind='op', op='LeakyReLU'))],
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edges=[],
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)
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@staticmethod
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def replace_pattern(graph: Graph, match: dict):
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relu = match['leakyrelu']
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relu_name = relu.soft_get('name', relu.id)
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if not relu.has_valid('negative_slope'):
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return
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rename_node(relu, relu_name + '/to_delete')
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# Create PReLU op and reconnect input/output from LeakyReLU to PReLU
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prelu = PReLU(graph, dict(name=relu_name)).create_node()
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rename_node(prelu, relu_name)
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const = Const(graph, dict(name=relu_name + "/weights", value=np.array([relu.negative_slope]))).create_node()
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relu.in_port(0).get_connection().set_destination(prelu.in_port(0))
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const.out_port(0).connect(prelu.in_port(1))
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relu.out_port(0).get_connection().set_source(prelu.out_port(0))
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