mirror of
https://github.com/saymrwulf/pytorch.git
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8286ce1e3a
Summary: Closes https://github.com/caffe2/caffe2/pull/1260 Differential Revision: D5906739 Pulled By: Yangqing fbshipit-source-id: e482ba9ba60b5337d9165f28f7ec68d4518a0902
78 lines
2.7 KiB
Python
78 lines
2.7 KiB
Python
# Copyright (c) 2016-present, Facebook, Inc.
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#
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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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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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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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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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from caffe2.python import core, workspace
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from caffe2.python.test_util import TestCase
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import numpy as np
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lengths = [[0], [1, 2], [1, 0, 2, 0]]
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features1 = [[],
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[1, 2, 2],
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[[1, 1], [2, 2], [2, 2]]
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]
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features2 = [[],
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[2, 4, 4],
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[[2, 2], [4, 4], [4, 4]]
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]
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lengths_exp = [[1], [1, 2], [1, 1, 2, 1]]
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features1_exp = [[0],
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[1, 2, 2],
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[[1, 1], [0, 0], [2, 2], [2, 2], [0, 0]]]
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features2_exp = [[0],
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[2, 4, 4],
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[[2, 2], [0, 0], [4, 4], [4, 4], [0, 0]]]
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class TestEmptySampleOps(TestCase):
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def test_emptysample(self):
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for i in range(0, 3):
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PadEmptyTest = core.CreateOperator(
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'PadEmptySamples',
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['lengths', 'features1', 'features2'],
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['out_lengths', 'out_features1', 'out_features2'],
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)
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workspace.FeedBlob(
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'lengths',
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np.array(lengths[i], dtype=np.int32))
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workspace.FeedBlob(
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'features1',
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np.array(features1[i], dtype=np.int64))
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workspace.FeedBlob(
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'features2',
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np.array(features2[i], dtype=np.int64))
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workspace.RunOperatorOnce(PadEmptyTest)
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np.testing.assert_allclose(
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lengths_exp[i],
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workspace.FetchBlob('out_lengths'),
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atol=1e-4, rtol=1e-4, err_msg='Mismatch in lengths')
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np.testing.assert_allclose(
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features1_exp[i],
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workspace.FetchBlob('out_features1'),
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atol=1e-4, rtol=1e-4, err_msg='Mismatch in features1')
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np.testing.assert_allclose(
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features2_exp[i],
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workspace.FetchBlob('out_features2'),
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atol=1e-4, rtol=1e-4, err_msg='Mismatch in features2')
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if __name__ == "__main__":
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import unittest
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unittest.main()
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