96 lines
4.3 KiB
Python
96 lines
4.3 KiB
Python
# Lint as: python3
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# Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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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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# pylint: disable=g-bad-import-order
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"""Test for data_load.py."""
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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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import unittest
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from data_load import DataLoader
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import tensorflow as tf
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class TestLoad(unittest.TestCase):
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def setUp(self): # pylint: disable=g-missing-super-call
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self.loader = DataLoader(
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"./data/train", "./data/valid", "./data/test", seq_length=512)
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def test_get_data(self):
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self.assertIsInstance(self.loader.train_data, list)
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self.assertIsInstance(self.loader.train_label, list)
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self.assertIsInstance(self.loader.valid_data, list)
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self.assertIsInstance(self.loader.valid_label, list)
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self.assertIsInstance(self.loader.test_data, list)
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self.assertIsInstance(self.loader.test_label, list)
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self.assertEqual(self.loader.train_len, len(self.loader.train_data))
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self.assertEqual(self.loader.train_len, len(self.loader.train_label))
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self.assertEqual(self.loader.valid_len, len(self.loader.valid_data))
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self.assertEqual(self.loader.valid_len, len(self.loader.valid_label))
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self.assertEqual(self.loader.test_len, len(self.loader.test_data))
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self.assertEqual(self.loader.test_len, len(self.loader.test_label))
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def test_pad(self):
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original_data1 = [[2, 3], [1, 1]]
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expected_data1_0 = [[2, 3], [2, 3], [2, 3], [2, 3], [1, 1]]
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expected_data1_1 = [[2, 3], [1, 1], [1, 1], [1, 1], [1, 1]]
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original_data2 = [[-2, 3], [-77, -681], [5, 6], [9, -7], [22, 3333],
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[9, 99], [-100, 0]]
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expected_data2 = [[-2, 3], [-77, -681], [5, 6], [9, -7], [22, 3333]]
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padding_data1 = self.loader.pad(original_data1, seq_length=5, dim=2)
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padding_data2 = self.loader.pad(original_data2, seq_length=5, dim=2)
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for i in range(len(padding_data1[0])):
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for j in range(len(padding_data1[0].tolist()[0])):
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self.assertLess(
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abs(padding_data1[0].tolist()[i][j] - expected_data1_0[i][j]),
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10.001)
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for i in range(len(padding_data1[1])):
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for j in range(len(padding_data1[1].tolist()[0])):
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self.assertLess(
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abs(padding_data1[1].tolist()[i][j] - expected_data1_1[i][j]),
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10.001)
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self.assertEqual(padding_data2[0].tolist(), expected_data2)
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self.assertEqual(padding_data2[1].tolist(), expected_data2)
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def test_format(self):
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self.loader.format()
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expected_train_label = int(self.loader.label2id[self.loader.train_label[0]])
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expected_valid_label = int(self.loader.label2id[self.loader.valid_label[0]])
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expected_test_label = int(self.loader.label2id[self.loader.test_label[0]])
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for feature, label in self.loader.train_data: # pylint: disable=unused-variable
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format_train_label = label.numpy()
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break
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for feature, label in self.loader.valid_data:
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format_valid_label = label.numpy()
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break
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for feature, label in self.loader.test_data:
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format_test_label = label.numpy()
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break
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self.assertEqual(expected_train_label, format_train_label)
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self.assertEqual(expected_valid_label, format_valid_label)
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self.assertEqual(expected_test_label, format_test_label)
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self.assertIsInstance(self.loader.train_data, tf.data.Dataset)
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self.assertIsInstance(self.loader.valid_data, tf.data.Dataset)
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self.assertIsInstance(self.loader.test_data, tf.data.Dataset)
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if __name__ == "__main__":
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unittest.main()
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