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openvino/model-optimizer/extensions/middle/CutInputHavingZeroDimFromConcat_test.py

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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
import numpy as np
from extensions.middle.CutInputHavingZeroDimFromConcat import CutInputHavingZeroDimFromConcat
from mo.front.common.partial_infer.utils import int64_array
from mo.utils.ir_engine.compare_graphs import compare_graphs
from mo.utils.unittest.graph import build_graph
node_attrs_for_the_case_when_there_are_no_zero_shape_constants = {
'const0': {
'kind': 'op',
'type': 'Const',
'op': 'Const',
'shape': int64_array([1, 2, 5]),
'value': np.zeros((1, 2, 5))
},
'const0_data': {'kind': 'data', 'shape': int64_array([1, 2, 5]), 'value': None},
'const1': {
'kind': 'op',
'type': 'Const',
'op': 'Const',
'shape': int64_array([1, 2, 7]),
'value': np.zeros((1, 2, 7))
},
'const1_data': {'kind': 'data', 'shape': int64_array([1, 2, 7]), 'value': None},
'placeholder': {'kind': 'op', 'type': 'Parameter', 'op': 'Parameter'},
'placeholder_data': {
'kind': 'data',
'value': None,
'shape': int64_array([1, 2, 8]),
'data_type': None
},
'concat': {'kind': 'op', 'type': 'Concat', 'op': 'Concat', 'axis': 2},
'concat_data': {'kind': 'data', 'shape': int64_array([1, 2, 20]), 'value': None},
'output': {'kind': 'op', 'op': 'Result', 'type': 'Result'},
}
edges_for_the_case_when_there_are_no_zero_shape_constants = [
('const0', 'const0_data'),
('const1', 'const1_data'),
('placeholder', 'placeholder_data'),
('const0_data', 'concat', {'in': 0}),
('const1_data', 'concat', {'in': 1}),
('placeholder_data', 'concat', {'in': 2}),
('concat', 'concat_data'),
('concat_data', 'output')
]
class CutInputHavingZeroDimFromConcatTest(unittest.TestCase):
"""
This class tests deleting of inputs of Concat having zeros in their shapes, if not all inputs have such shapes.
"""
def test_when_need_to_do_nothing(self):
graph = build_graph(
nodes_attrs=node_attrs_for_the_case_when_there_are_no_zero_shape_constants,
edges=edges_for_the_case_when_there_are_no_zero_shape_constants
)
ref_graph = build_graph(
nodes_attrs=node_attrs_for_the_case_when_there_are_no_zero_shape_constants,
edges=edges_for_the_case_when_there_are_no_zero_shape_constants
)
CutInputHavingZeroDimFromConcat().find_and_replace_pattern(graph)
(flag, resp) = compare_graphs(graph, ref_graph, 'output')
self.assertTrue(flag, resp)
def test_when_there_are_three_inputs_and_middle_constant_has_zero_in_shape(self):
graph = build_graph(
nodes_attrs={
'const0': {
'kind': 'op',
'type': 'Const',
'op': 'Const',
'shape': int64_array([1, 2, 5]),
'value': np.zeros((1, 2, 5))
},
'const0_data': {'kind': 'data', 'shape': int64_array([1, 2, 5]), 'value': None},
'const1': {
'kind': 'op',
'type': 'Const',
'op': 'Const',
'shape': int64_array([1, 2, 0]),
'value': np.zeros((1, 2, 0))
},
'const1_data': {'kind': 'data', 'shape': int64_array([1, 2, 0]), 'value': None},
'placeholder': {'kind': 'op', 'type': 'Parameter', 'op': 'Parameter'},
'placeholder_data': {
'kind': 'data',
'value': None,
'shape': int64_array([1, 2, 17]),
'data_type': None
},
'concat': {'kind': 'op', 'type': 'Concat', 'op': 'Concat', 'axis': 2},
'concat_data': {'kind': 'data', 'shape': int64_array([1, 2, 22]), 'value': None},
'output': {'kind': 'op', 'op': 'Result', 'type': 'Result'},
},
edges=[
('const0', 'const0_data'),
('const1', 'const1_data'),
('placeholder', 'placeholder_data'),
('const0_data', 'concat', {'in': 0}),
('const1_data', 'concat', {'in': 1}),
('placeholder_data', 'concat', {'in': 2}),
('concat', 'concat_data'),
('concat_data', 'output')
]
)
ref_graph = build_graph(
nodes_attrs={
'const0': {
'kind': 'op',
'type': 'Const',
'op': 'Const',
'shape': int64_array([1, 2, 5]),
'value': np.zeros((1, 2, 5))
},
'const0_data': {'kind': 'data', 'shape': int64_array([1, 2, 5]), 'value': None},
'placeholder': {'kind': 'op', 'type': 'Parameter', 'op': 'Parameter'},
'placeholder_data': {
'kind': 'data',
'value': None,
'shape': int64_array([1, 2, 17]),
'data_type': None
},
'concat': {'kind': 'op', 'type': 'Concat', 'op': 'Concat', 'axis': 2},
'concat_data': {'kind': 'data', 'shape': int64_array([1, 2, 22]), 'value': None},
'output': {'kind': 'op', 'op': 'Result', 'type': 'Result'},
},
edges=[
('const0', 'const0_data'),
('placeholder', 'placeholder_data'),
('const0_data', 'concat', {'in': 0}),
('placeholder_data', 'concat', {'in': 1}),
('concat', 'concat_data'),
('concat_data', 'output')
]
)
CutInputHavingZeroDimFromConcat().find_and_replace_pattern(graph)
(flag, resp) = compare_graphs(graph, ref_graph, 'output')
self.assertTrue(flag, resp)
def test_there_are_four_inputs_and_first_and_third_input_have_zero_in_their_shapes(self):
graph = build_graph(
nodes_attrs={
'const0': {
'kind': 'op',
'type': 'Const',
'op': 'Const',
'shape': int64_array([5, 0]),
'value': np.zeros((5, 0))
},
'const0_data': {'kind': 'data', 'shape': int64_array([5, 0]), 'value': None},
'placeholder': {'kind': 'op', 'type': 'Parameter', 'op': 'Parameter'},
'placeholder_data': {
'kind': 'data',
'value': None,
'shape': int64_array([5, 17]),
'data_type': None
},
'const2': {
'kind': 'op',
'type': 'Const',
'op': 'Const',
'shape': int64_array([5, 0]),
'value': np.zeros((5, 0))
},
'const2_data': {'kind': 'data', 'shape': int64_array([5, 0]), 'value': None},
'const3': {
'kind': 'op',
'type': 'Const',
'op': 'Const',
'shape': int64_array([5, 23]),
'value': np.zeros((5, 23))
},
'const3_data': {'kind': 'data', 'shape': int64_array([5, 23]), 'value': None},
'concat': {'kind': 'op', 'type': 'Concat', 'op': 'Concat', 'axis': 1},
'concat_data': {'kind': 'data', 'shape': int64_array([5, 40]), 'value': None},
'output': {'kind': 'op', 'op': 'Result', 'type': 'Result'},
},
edges=[
('const0', 'const0_data'),
('placeholder', 'placeholder_data'),
('const2', 'const2_data'),
('const3', 'const3_data'),
('const0_data', 'concat', {'in': 0}),
('placeholder_data', 'concat', {'in': 1}),
('const2_data', 'concat', {'in': 2}),
('const3_data', 'concat', {'in': 3}),
('concat', 'concat_data'),
('concat_data', 'output')
]
)
ref_graph = build_graph(
nodes_attrs={
'placeholder': {'kind': 'op', 'type': 'Parameter', 'op': 'Parameter'},
'placeholder_data': {
'kind': 'data',
'value': None,
'shape': int64_array([5, 17]),
'data_type': None
},
'const3': {
'kind': 'op',
'type': 'Const',
'op': 'Const',
'shape': int64_array([5, 23]),
'value': np.zeros((5, 23))
},
'const3_data': {'kind': 'data', 'shape': int64_array([5, 23]), 'value': None},
'concat': {'kind': 'op', 'type': 'Concat', 'op': 'Concat', 'axis': 1},
'concat_data': {'kind': 'data', 'shape': int64_array([5, 40]), 'value': None},
'output': {'kind': 'op', 'op': 'Result', 'type': 'Result'},
},
edges=[
('placeholder', 'placeholder_data'),
('const3', 'const3_data'),
('placeholder_data', 'concat', {'in': 0}),
('const3_data', 'concat', {'in': 1}),
('concat', 'concat_data'),
('concat_data', 'output')
]
)
CutInputHavingZeroDimFromConcat().find_and_replace_pattern(graph)
(flag, resp) = compare_graphs(graph, ref_graph, 'output')
self.assertTrue(flag, resp)