95 lines
3.0 KiB
Python
95 lines
3.0 KiB
Python
"""
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Copyright (c) 2017-2019 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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from unittest.mock import patch
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import numpy as np
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from extensions.front.caffe.data_augmentation_ext import DataAugmentationFrontExtractor
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from extensions.ops.data_augmentation import DataAugmentationOp
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from mo.utils.unittest.extractors import FakeMultiParam
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from mo.utils.unittest.graph import FakeNode
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from mo.ops.op import Op
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class FakeDAProtoLayer:
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def __init__(self, val):
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self.augmentation_param = val
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class TestDA(unittest.TestCase):
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@classmethod
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def setUpClass(cls):
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Op.registered_ops['DataAugmentation'] = DataAugmentationOp
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def test_da_no_pb_no_ml(self):
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self.assertRaises(AttributeError, DataAugmentationFrontExtractor.extract, None)
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@patch('extensions.front.caffe.data_augmentation_ext.merge_attrs')
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def test_da_ext_ideal_numbers(self, merge_attrs_mock):
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params = {
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'crop_width': 0,
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'crop_height': 0,
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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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merge_attrs_mock.return_value = {
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**params,
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'test': 54,
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'test2': 'test3'
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}
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fake_pl = FakeDAProtoLayer(FakeMultiParam(params))
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fake_node = FakeNode(fake_pl, None)
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DataAugmentationFrontExtractor.extract(fake_node)
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exp_res = {
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'type': 'DataAugmentation',
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'op': 'DataAugmentation',
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'crop_width': 0,
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'crop_height': 0,
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'write_augmented': "",
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'max_multiplier': 255.0,
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'augment_during_test': 1,
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'recompute_mean': 0,
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'write_mean': "",
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'mean_per_pixel': 0,
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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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'infer': DataAugmentationOp.data_augmentation_infer
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}
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for key in exp_res.keys():
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if key in ('chromatic_eigvec',):
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np.testing.assert_equal(exp_res[key], fake_node[key])
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else:
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self.assertEqual(exp_res[key], fake_node[key])
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