Evgeny Lazarev
f3d1aa6490
* Removed test-generator from all MO requirement files except the dev one * Moved all MO unit tests files to a separate directory * Added __init__.py files to the tests directory. Fixed importing paths for some unit tests * Fixed imports in all unit tests. Moved all unit test related files from the MO code to the dedicated directory * Renamed directory with unit test utils * Updated imports in unit tests
153 lines
9.4 KiB
Python
153 lines
9.4 KiB
Python
# Copyright (C) 2018-2021 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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import unittest
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import numpy as np
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from extensions.middle.TensorIteratorInput import SmartInputMatcher, SimpleInputMatcher, BackEdgeSimpleInputMatcher
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from mo.utils.ir_engine.compare_graphs import compare_graphs
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from unit_tests.utils.graph import build_graph_with_attrs
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class SmartInputMatcherTests(unittest.TestCase):
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def test(self):
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pattern_matcher = SmartInputMatcher()
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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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update_edge_attrs={('range_data', 'TensorArrayScatter', 0): {'in': 1},
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('TensorArray_handle', 'TensorArrayScatter', 0): {'in': 0},
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('TensorArray_flow', 'TensorArrayScatter', 0): {'in': 3}},
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new_nodes_with_attrs=[('ta_size', {'kind': 'data'}),
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('ta_size_op', {'kind': 'op'}),
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('value', {'kind': 'data'}),
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],
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new_edges_with_attrs=[
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('ta_size_op', 'ta_size'),
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('ta_size', 'TensorArray'),
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('value', 'TensorArrayScatter', {'in':2}),
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],
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update_nodes_attributes=[('Enter_data', {'value': np.array([1])}),
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('stack_data', {'value': np.array([0])}),
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('stack_1_data', {'value': np.array([1])}),
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('stack_2_data', {'value': np.array([1])}),
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('start_data', {'value': np.array([0])}),
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('delta_data', {'value': np.array([1])})
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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=[('condition_data', {'kind': 'data'}),
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('TensorIteratorInput', {'kind': 'op', 'op': 'TensorIteratorInput'}),
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('TensorArrayRead_data', {'kind': 'data'}),
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('condition_data', {'kind': 'data'}),
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('value', {'kind': 'data'}),
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('ta_size', {'kind': 'data'}),
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('ta_size_op', {'kind': 'op'})],
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edges_with_attrs=[('ta_size', 'TensorIteratorInput', {'in': 0}),
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('condition_data', 'TensorIteratorInput', {'in': 2}),
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('value', 'TensorIteratorInput', {'in': 1}),
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('TensorIteratorInput', 'TensorArrayRead_data'),
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('ta_size_op', 'ta_size')],
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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, 'TensorArrayRead_data', check_op_attrs=True)
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self.assertTrue(flag, resp)
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class SimpleInputMatcherTest(unittest.TestCase):
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def test(self):
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pattern_matcher = SimpleInputMatcher()
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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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update_edge_attrs=None,
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new_nodes_with_attrs=[('in_node', {'kind': 'data'}),
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('Enter_data', {'kind': 'data'})],
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new_edges_with_attrs=[('in_node', 'Enter'), ('Enter', 'Enter_data')],
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update_nodes_attributes=[])
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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=[('TensorIteratorInput', {'kind': 'op', 'op': 'TensorIteratorInput'}),
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('in_node', {'kind': 'data'}),
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('Enter_data', {'kind': 'data'})
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],
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edges_with_attrs=[('in_node', 'TensorIteratorInput'), ('TensorIteratorInput', 'Enter_data')],
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)
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(flag, resp) = compare_graphs(graph, graph_ref, 'Enter_data', check_op_attrs=True)
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self.assertTrue(flag, resp)
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class BackEdgeInputMatcherTest(unittest.TestCase):
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def test1(self):
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"""
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Case with constant input to init
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"""
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pattern_matcher = BackEdgeSimpleInputMatcher()
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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=[('cycle_data', {'kind': 'data'}),
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('condition', {'kind': 'data'}),
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('init', {'kind': 'data', 'shape': np.array([1,3])}),
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],
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new_edges_with_attrs=[('condition', 'BackEdge', {'in': 2}),
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('init', 'BackEdge', {'in': 0}),
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('cycle_data', 'BackEdge', {'in': 1})],)
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pattern_matcher.find_and_replace_pattern(graph)
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graph_ref = build_graph_with_attrs(nodes_with_attrs=pattern['nodes'], edges_with_attrs=pattern['edges'],
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new_nodes_with_attrs=[('cycle_data', {'kind': 'data'}),
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('condition', {'kind': 'data'}),
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('init', {'kind': 'data', 'shape': np.array([1,3])}),
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('TensorIteratorInput', {'kind': 'op', 'op': 'TensorIteratorInput'}),
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('TensorIteratorInput_data', {'kind': 'data', 'shape': np.array([1,3])}),
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],
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new_edges_with_attrs=[('TensorIteratorInput_data', 'TensorIteratorInput'),
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('TensorIteratorInput', 'init'),
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('condition', 'BackEdge', {'in': 2}),
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('init', 'BackEdge', {'in': 0}),
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('cycle_data', 'BackEdge', {'in': 1})],)
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(flag, resp) = compare_graphs(graph, graph_ref, 'BackEdge', check_op_attrs=True)
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self.assertTrue(flag, resp)
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def test2(self):
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"""
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Case with non-constant input to init.
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Nothing should happen with graph.
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"""
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pattern_matcher = BackEdgeSimpleInputMatcher()
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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=[('cycle_data', {'kind': 'data'}),
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('condition', {'kind': 'data'}),
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('init', {'kind': 'data', 'shape': np.array([1, 3])}),
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('Enter', {'kind': 'op', 'op': 'Enter'}),
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],
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new_edges_with_attrs=[('Enter', 'init'),
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('condition', 'BackEdge', {'in': 2}),
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('init', 'BackEdge', {'in': 0}),
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('cycle_data', 'BackEdge', {'in': 1})])
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pattern_matcher.find_and_replace_pattern(graph)
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graph_ref = build_graph_with_attrs(nodes_with_attrs=pattern['nodes'], edges_with_attrs=pattern['edges'],
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new_nodes_with_attrs=[('cycle_data', {'kind': 'data'}),
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('condition', {'kind': 'data'}),
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('init', {'kind': 'data', 'shape': np.array([1, 3])}),
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('Enter', {'kind': 'op', 'op': 'Enter'}),
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],
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new_edges_with_attrs=[('Enter', 'init'),
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('condition', 'BackEdge', {'in': 2}),
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('init', 'BackEdge', {'in': 0}),
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('cycle_data', 'BackEdge', {'in': 1})], )
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(flag, resp) = compare_graphs(graph, graph_ref, 'BackEdge', check_op_attrs=True)
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self.assertTrue(flag, resp)
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