61 lines
2.7 KiB
Python
61 lines
2.7 KiB
Python
"""
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Copyright (C) 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 unittest
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from extensions.front.ThresholdedReluDecomposition import ThresholdedReluDecomposition
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from mo.front.common.partial_infer.utils import float_array
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from mo.utils.ir_engine.compare_graphs import compare_graphs
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from mo.utils.unittest.graph import build_graph, const
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nodes_attributes = {
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'parameter': {'shape': None, 'type': 'Parameter', 'kind': 'op', 'op': 'Parameter'},
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'trelu': {'type': None, 'kind': 'op', 'op': 'ThresholdedRelu', 'alpha': 0.75, 'name': 'my_trelu'},
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'result': {'type': 'Result', 'value': None, 'kind': 'op', 'op': 'Result'},
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'cast': {'type': 'Convert', 'kind': 'op', 'op': 'Cast'},
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'greater': {'type': 'Greater', 'kind': 'op', 'op': 'Greater'},
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'mul': {'type': 'Multiply', 'kind': 'op', 'op': 'Mul', 'name': 'my_trelu'},
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'squeeze2': {'type': 'Squeeze', 'kind': 'op', 'op': 'Squeeze'},
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**const('alpha', float_array([0.75])),
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}
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class ThresholdedReluDecompositionTest(unittest.TestCase):
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def test_trelu(self):
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graph = build_graph(nodes_attributes,
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[('parameter', 'trelu', {'in': 0, 'out': 0}),
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('trelu', 'result', {'in': 0, 'out': 0}),
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], nodes_with_edges_only=True)
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graph_ref = build_graph(nodes_attributes,
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[('parameter', 'greater', {'in': 0, 'out': 0}),
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('alpha', 'greater', {'in': 1, 'out': 0}),
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('greater', 'cast', {'in': 0, 'out': 0}),
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('parameter', 'mul', {'in': 0, 'out': 0}),
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('cast', 'mul', {'in': 1, 'out': 0}),
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('mul', 'result', {'in': 0, 'out': 0}),
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], nodes_with_edges_only=True)
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graph.graph['layout'] = 'NCHW'
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graph.stage = 'front'
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ThresholdedReluDecomposition().find_and_replace_pattern(graph)
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(flag, resp) = compare_graphs(graph, graph_ref, 'result', check_op_attrs=True)
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self.assertTrue(flag, resp)
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self.assertTrue(len(graph.get_op_nodes(name='my_trelu')) == 1 and
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graph.get_op_nodes(name='my_trelu')[0].op == 'Mul')
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