74 lines
4.1 KiB
Python
74 lines
4.1 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 unittest
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import numpy as np
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from extensions.middle.TensorIteratorCondition import LoopConditionMatcher
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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_with_attrs
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class TensorIteratorConditionTests(unittest.TestCase):
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def test_not_dynamic(self):
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pattern_matcher = LoopConditionMatcher()
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pattern = pattern_matcher.pattern()
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graph = build_graph_with_attrs(nodes_with_attrs=pattern['nodes'], edges_with_attrs=pattern['edges'],
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new_nodes_with_attrs=[('maximum', {'kind': 'op', 'op': 'Maximum'}),
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('maximum_data', {'kind': 'data'}),
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('TensorIteratorInput', {'kind': 'op', 'op': 'TensorIteratorInput'})],
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new_edges_with_attrs=[('maximum', 'maximum_data'),
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('Identity_1_data', 'TensorIteratorInput')],
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update_nodes_attributes=[('init_1_data', {'value': np.array([0])}),
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('init_2_data', {'value': np.array([0])}),
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('add_1_y_data', {'value': np.array(1)}),
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('add_2_y_data', {'value': np.array(1)}),
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('loop_cond_data', {'value': None}),
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('Identity_2_data', {'value': None}, ),
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('Enter_1_less_data', {'value': None},),
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('Enter_2_less_data', {'value': None},),
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])
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pattern_matcher.find_and_replace_pattern(graph)
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graph_ref = build_graph_with_attrs(
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nodes_with_attrs=[('TensorIteratorCondition', {'kind': 'op', 'op': 'TensorIteratorCondition'}),
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('loop_cond_data', {'kind': 'data'}),
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('identity_data', {'kind': 'data'}),
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('StridedSlice', {'kind': 'op', 'op':'StridedSlice'}),
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('StridedSlice_data', {'kind': 'data'}),
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('Maximum', {'kind': 'op', 'op': 'Maximum'}),
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('Maximum_data', {'kind': 'data'}),
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('minimum_data', {'kind': 'data'}),
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('TensorIteratorInput', {'kind': 'op', 'op': 'TensorIteratorInput'})
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],
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edges_with_attrs=[('Maximum', 'Maximum_data'),
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('StridedSlice', 'StridedSlice_data'),
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('StridedSlice_data', 'TensorIteratorCondition', {'in':0}),
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('minimum_data', 'TensorIteratorCondition', {'in':1}),
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('TensorIteratorCondition', 'loop_cond_data'),
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('TensorIteratorCondition', 'identity_data'),
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('identity_data', 'TensorIteratorInput'),
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],
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update_edge_attrs=None,
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new_nodes_with_attrs=[],
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new_edges_with_attrs=[],
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)
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(flag, resp) = compare_graphs(graph, graph_ref, 'loop_cond_data', check_op_attrs=True)
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self.assertTrue(flag, resp)
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