Files
openvino/model-optimizer/extensions/back/FuseTransposesSequence_test.py
T
Yegor Kruglov 465707eba7 [MO MXNET] Fixed spatial reshape on GluonCV models (#587)
* added value propagation for slice_like op

* Mark slice_lice as undead node

* fixes in mark_undead_nodes and unittests update
2020-06-30 22:32:13 +03:00

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7.0 KiB
Python

"""
Copyright (C) 2018-2020 Intel Corporation
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
import unittest
from argparse import Namespace
import numpy as np
from extensions.back.FuseTransposesSequence import FuseTransposesSequence
from mo.middle.passes.eliminate_test import build_graph
from mo.utils.ir_engine.compare_graphs import compare_graphs
# The dictionary with nodes attributes used to build various graphs. A key is the name of the node and the value is the
# dictionary with node attributes.
nodes_attributes = {
'placeholder_1': {'name': 'placeholder_1', 'value': None, 'shape': None, 'type': 'Parameter', 'kind': 'op',
'op': 'Parameter'},
'placeholder_1_data': {'name': 'placeholder_1_data', 'value': None, 'shape': None, 'kind': 'data',
'data_type': None},
# Transpose layers
'const_1': {'value': None, 'kind': 'op', 'type': 'Const', 'op': 'Const'},
'const_1_data': {'value': None, 'shape': None, 'kind': 'data'},
'permute_1': {'type': 'Transpose', 'value': None, 'kind': 'op', 'op': 'Transpose'},
'permute_1_data': {'value': None, 'shape': None, 'kind': 'data'},
'const_2': {'value': None, 'kind': 'op', 'type': 'Const', 'op': 'Const'},
'const_2_data': {'value': None, 'shape': None, 'kind': 'data'},
'permute_2': {'type': 'Transpose', 'value': None, 'kind': 'op', 'op': 'Transpose'},
'permute_2_data': {'value': None, 'shape': None, 'kind': 'data'},
'const_3': {'value': None, 'kind': 'op', 'type': 'Const', 'op': 'Const'},
'const_3_data': {'value': None, 'shape': None, 'kind': 'data'},
'permute_3': {'type': 'Transpose', 'value': None, 'kind': 'op', 'op': 'Transpose'},
'permute_3_data': {'value': None, 'shape': None, 'kind': 'data'},
'op_output': {'op': 'Result', 'kind': 'op'}
}
class FuseTransposesSequenceTest(unittest.TestCase):
def test_1(self):
#
# NHWC NCHW NHWC
# Input->DATA->Transpose->DATA->Transpose->DATA => Input->DATA
#
graph = build_graph(nodes_attributes,
[('placeholder_1', 'placeholder_1_data'),
('placeholder_1_data', 'permute_1'),
('permute_1', 'permute_1_data'),
('permute_1_data', 'permute_2'),
('permute_2', 'permute_2_data'),
('permute_2_data', 'op_output'),
('const_1', 'const_1_data'),
('const_1_data', 'permute_1', {'in': 1}),
('const_2', 'const_2_data'),
('const_2_data', 'permute_2', {'in': 1}),
],
{'placeholder_1_data': {'shape': np.array([1, 227, 227, 3])},
'const_1_data': {'value': np.array([0, 3, 1, 2])},
'permute_1_data': {'shape': np.array([1, 3, 227, 227])},
'const_2_data': {'value': np.array([0, 2, 3, 1])},
'permute_2_data': {'shape': np.array([1, 227, 227, 3])},
}, nodes_with_edges_only=True)
graph.graph['layout'] = 'NHWC'
graph.graph['cmd_params'] = Namespace(keep_shape_ops=False)
graph_ref = build_graph(nodes_attributes,
[('placeholder_1', 'placeholder_1_data'),
('placeholder_1_data', 'op_output')
],
{'placeholder_1_data': {'shape': np.array([1, 227, 227, 3])}},
nodes_with_edges_only=True)
pattern = FuseTransposesSequence()
pattern.find_and_replace_pattern(graph)
(flag, resp) = compare_graphs(graph, graph_ref, 'placeholder_1_data', check_op_attrs=True)
self.assertTrue(flag, resp)
def test_2(self):
#
# Input->DATA->Transpose->DATA->Transpose->DATA => Input->DATA->Transpose->DATA
#
graph = build_graph(nodes_attributes,
[('placeholder_1', 'placeholder_1_data'),
('placeholder_1_data', 'permute_1'),
('permute_1', 'permute_1_data'),
('permute_1_data', 'permute_2'),
('permute_2', 'permute_2_data'),
('permute_2_data', 'op_output'),
('const_1', 'const_1_data'),
('const_1_data', 'permute_1', {'in': 1}),
('const_2', 'const_2_data'),
('const_2_data', 'permute_2', {'in': 1}),
],
{'placeholder_1_data': {'shape': np.array([1, 227, 227, 3])},
'const_1': {'shape': np.array([4])},
'const_1_data': {'value': np.array([0, 3, 1, 2])},
'permute_1_data': {'shape': np.array([1, 3, 227, 227])},
'const_2': {'shape': np.array([4])},
'const_2_data': {'value': np.array([0, 1, 2, 3])},
'permute_2_data': {'shape': np.array([1, 3, 227, 227])},
}, nodes_with_edges_only=True)
graph.graph['layout'] = 'NHWC'
graph.graph['cmd_params'] = Namespace(keep_shape_ops=False)
graph_ref = build_graph(nodes_attributes,
[('placeholder_1', 'placeholder_1_data'),
('placeholder_1_data', 'permute_1'),
('permute_1', 'permute_1_data'),
('permute_1_data', 'op_output'),
('const_1', 'const_1_data'),
('const_1_data', 'permute_1', {'in': 1}),
],
{'placeholder_1_data': {'shape': np.array([1, 227, 227, 3])},
'const_1_data': {'value': np.array([0, 3, 1, 2])},
'permute_1_data': {'shape': np.array([1, 3, 227, 227])},
}, nodes_with_edges_only=True)
pattern = FuseTransposesSequence()
pattern.find_and_replace_pattern(graph)
(flag, resp) = compare_graphs(graph, graph_ref, 'placeholder_1_data', check_op_attrs=True)
self.assertTrue(flag, resp)
if __name__ == '__main__':
unittest.main()