66 lines
2.6 KiB
Python
66 lines
2.6 KiB
Python
"""
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Copyright (c) 2018-2019 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.ops.data_augmentation import DataAugmentationOp
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from mo.graph.graph import Node
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from mo.utils.unittest.graph import build_graph
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nodes_attributes = {
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'node_1': {'type': 'Identity', 'kind': 'op'},
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'da': {'type': 'DataAugmentation', 'kind': 'op'},
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'node_3': {'type': 'Identity', 'kind': 'op'},
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'op_output': { 'kind': 'op', 'op': 'Result'}
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}
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class TestConcatPartialInfer(unittest.TestCase):
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def test_tf_concat_infer(self):
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graph = build_graph(nodes_attributes,
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[
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('node_1', 'da'),
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('da', 'node_3'),
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('node_3', 'op_output')
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],
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{
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'node_3': {'shape': None},
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'node_1': {'shape': np.array([1, 3, 227, 227])},
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'da': {'crop_width': 225,
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'crop_height': 225,
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'write_augmented': "",
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'max_multiplier': 255.0,
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'augment_during_test': True,
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'recompute_mean': 0,
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'write_mean': "",
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'mean_per_pixel': False,
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'mean': 0,
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'mode': "add",
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'bottomwidth': 0,
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'bottomheight': 0,
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'num': 0,
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'chromatic_eigvec': [0.0]}
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})
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da_node = Node(graph, 'da')
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DataAugmentationOp.data_augmentation_infer(da_node)
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exp_shape = np.array([1, 3, 225, 225])
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res_shape = graph.node['node_3']['shape']
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for i in range(0, len(exp_shape)):
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self.assertEqual(exp_shape[i], res_shape[i])
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