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https://github.com/facebookresearch/fairseq.git
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Summary: Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/1357 Reviewed By: alexeib Differential Revision: D24377772 fbshipit-source-id: 51581af041d42d62166b33a35a1a4228b1a76f0c
80 lines
2.9 KiB
Python
80 lines
2.9 KiB
Python
# Copyright (c) Facebook, Inc. and its affiliates.
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#
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# This source code is licensed under the MIT license found in the
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# LICENSE file in the root directory of this source tree.
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import unittest
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import tests.utils as test_utils
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import torch
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from fairseq.data import TokenBlockDataset
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class TestTokenBlockDataset(unittest.TestCase):
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def _build_dataset(self, data, **kwargs):
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sizes = [len(x) for x in data]
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underlying_ds = test_utils.TestDataset(data)
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return TokenBlockDataset(underlying_ds, sizes, **kwargs)
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def test_eos_break_mode(self):
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data = [
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torch.tensor([5, 4, 3, 2, 1], dtype=torch.long),
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torch.tensor([1], dtype=torch.long),
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torch.tensor([8, 7, 6, 1], dtype=torch.long),
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]
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ds = self._build_dataset(data, block_size=None, pad=0, eos=1, break_mode="eos")
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self.assertEqual(ds[0].tolist(), [5, 4, 3, 2, 1])
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self.assertEqual(ds[1].tolist(), [1])
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self.assertEqual(ds[2].tolist(), [8, 7, 6, 1])
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data = [
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torch.tensor([5, 4, 3, 2, 1], dtype=torch.long),
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torch.tensor([8, 7, 6, 1], dtype=torch.long),
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torch.tensor([1], dtype=torch.long),
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]
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ds = self._build_dataset(data, block_size=None, pad=0, eos=1, break_mode="eos")
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self.assertEqual(ds[0].tolist(), [5, 4, 3, 2, 1])
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self.assertEqual(ds[1].tolist(), [8, 7, 6, 1])
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self.assertEqual(ds[2].tolist(), [1])
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def test_block_break_mode(self):
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data = [
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torch.tensor([5, 4, 3, 2, 1], dtype=torch.long),
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torch.tensor([8, 7, 6, 1], dtype=torch.long),
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torch.tensor([9, 1], dtype=torch.long),
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]
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ds = self._build_dataset(data, block_size=3, pad=0, eos=1, break_mode="none")
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self.assertEqual(ds[0].tolist(), [5, 4, 3])
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self.assertEqual(ds[1].tolist(), [2, 1, 8])
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self.assertEqual(ds[2].tolist(), [7, 6, 1])
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self.assertEqual(ds[3].tolist(), [9, 1])
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def test_complete_break_mode(self):
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data = [
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torch.tensor([5, 4, 3, 2, 1], dtype=torch.long),
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torch.tensor([8, 7, 6, 1], dtype=torch.long),
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torch.tensor([9, 1], dtype=torch.long),
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]
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ds = self._build_dataset(
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data, block_size=6, pad=0, eos=1, break_mode="complete"
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)
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self.assertEqual(ds[0].tolist(), [5, 4, 3, 2, 1])
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self.assertEqual(ds[1].tolist(), [8, 7, 6, 1, 9, 1])
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data = [
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torch.tensor([4, 3, 2, 1], dtype=torch.long),
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torch.tensor([5, 1], dtype=torch.long),
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torch.tensor([1], dtype=torch.long),
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torch.tensor([6, 1], dtype=torch.long),
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]
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ds = self._build_dataset(
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data, block_size=3, pad=0, eos=1, break_mode="complete"
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)
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self.assertEqual(ds[0].tolist(), [4, 3, 2, 1])
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self.assertEqual(ds[1].tolist(), [5, 1, 1])
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self.assertEqual(ds[2].tolist(), [6, 1])
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if __name__ == "__main__":
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unittest.main()
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