35 lines
1.0 KiB
Python
35 lines
1.0 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 mo.graph.graph import Node, Graph
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from mo.ops.op import Op
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class HardSigmoid(Op):
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op = 'HardSigmoid'
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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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'op': self.op,
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'type': self.op,
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'version': 'opset1',
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'infer': self.infer,
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'in_ports_count': 3,
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'out_ports_count': 1,
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}, attrs)
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@staticmethod
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def infer(node: Node):
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input_node = node.in_node(0)
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data_value = node.in_port(0).data.get_value()
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alpha_value = node.in_port(1).data.get_value()
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beta_value = node.in_port(2).data.get_value()
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if data_value is not None and alpha_value is not None and beta_value is not None:
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node.out_port(0).data.set_value(np.clip(data_value * alpha_value + beta_value, 0, 1))
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return
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node.out_port(0).data.set_shape(input_node.shape.copy())
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