63 lines
1.9 KiB
Python
63 lines
1.9 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.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
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from mo.ops.op import Op
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class PreluOp(Op):
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op = 'PReLU'
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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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'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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'force_precision_in_ports': {1: 'float'},
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'in_ports_count': 2,
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'out_ports_count': 1,
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}, attrs)
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def supported_attrs(self):
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if self.ir_version != 10:
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return ['channel_shared', 'filler_type', 'filler_value', 'min', 'max', 'mean', 'std', 'sparse', 'variance_norm']
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else:
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return []
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@staticmethod
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def infer(node):
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if len(node.in_nodes()) == 2:
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gamma_vector = node.in_node(1)
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if np.all(gamma_vector.shape == [1]):
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node['channel_shared'] = 1
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else:
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node['channel_shared'] = 0
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if not node.graph.graph['cmd_params'].generate_experimental_IR_V10:
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mark_input_bins(node)
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else:
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node.in_node(1)['correct_data_type'] = True
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copy_shape_infer(node)
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