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- # Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
- #
- # 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 paddle.text.datasets import WMT14, WMT16
-
-
- class TestWMT14Train(unittest.TestCase):
- def test_main(self):
- wmt14 = WMT14(mode='train', dict_size=50)
- self.assertTrue(len(wmt14) == 191155)
-
- # traversal whole dataset may cost a
- # long time, randomly check 1 sample
- idx = np.random.randint(0, 191155)
- data = wmt14[idx]
- self.assertTrue(len(data) == 3)
- self.assertTrue(len(data[0].shape) == 1)
- self.assertTrue(len(data[1].shape) == 1)
- self.assertTrue(len(data[2].shape) == 1)
-
-
- class TestWMT14Test(unittest.TestCase):
- def test_main(self):
- wmt14 = WMT14(mode='test', dict_size=50)
- self.assertTrue(len(wmt14) == 5957)
-
- # traversal whole dataset may cost a
- # long time, randomly check 1 sample
- idx = np.random.randint(0, 5957)
- data = wmt14[idx]
- self.assertTrue(len(data) == 3)
- self.assertTrue(len(data[0].shape) == 1)
- self.assertTrue(len(data[1].shape) == 1)
- self.assertTrue(len(data[2].shape) == 1)
-
-
- class TestWMT14Gen(unittest.TestCase):
- def test_main(self):
- wmt14 = WMT14(mode='gen', dict_size=50)
- self.assertTrue(len(wmt14) == 3001)
-
- # traversal whole dataset may cost a
- # long time, randomly check 1 sample
- idx = np.random.randint(0, 3001)
- data = wmt14[idx]
- self.assertTrue(len(data) == 3)
- self.assertTrue(len(data[0].shape) == 1)
- self.assertTrue(len(data[1].shape) == 1)
- self.assertTrue(len(data[2].shape) == 1)
-
-
- class TestWMT16Train(unittest.TestCase):
- def test_main(self):
- wmt16 = WMT16(
- mode='train', src_dict_size=50, trg_dict_size=50, lang='en'
- )
- self.assertTrue(len(wmt16) == 29000)
-
- # traversal whole dataset may cost a
- # long time, randomly check 1 sample
- idx = np.random.randint(0, 29000)
- data = wmt16[idx]
- self.assertTrue(len(data) == 3)
- self.assertTrue(len(data[0].shape) == 1)
- self.assertTrue(len(data[1].shape) == 1)
- self.assertTrue(len(data[2].shape) == 1)
-
-
- class TestWMT16Test(unittest.TestCase):
- def test_main(self):
- wmt16 = WMT16(
- mode='test', src_dict_size=50, trg_dict_size=50, lang='en'
- )
- self.assertTrue(len(wmt16) == 1000)
-
- # traversal whole dataset may cost a
- # long time, randomly check 1 sample
- idx = np.random.randint(0, 1000)
- data = wmt16[idx]
- self.assertTrue(len(data) == 3)
- self.assertTrue(len(data[0].shape) == 1)
- self.assertTrue(len(data[1].shape) == 1)
- self.assertTrue(len(data[2].shape) == 1)
-
-
- class TestWMT16Val(unittest.TestCase):
- def test_main(self):
- wmt16 = WMT16(mode='val', src_dict_size=50, trg_dict_size=50, lang='en')
- self.assertTrue(len(wmt16) == 1014)
-
- # traversal whole dataset may cost a
- # long time, randomly check 1 sample
- idx = np.random.randint(0, 1014)
- data = wmt16[idx]
- self.assertTrue(len(data) == 3)
- self.assertTrue(len(data[0].shape) == 1)
- self.assertTrue(len(data[1].shape) == 1)
- self.assertTrue(len(data[2].shape) == 1)
-
-
- if __name__ == '__main__':
- unittest.main()
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