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|
| import unittest |
|
|
| import torch |
| from fairseq.data import LanguagePairDataset, TokenBlockDataset |
| from fairseq.data.concat_dataset import ConcatDataset |
| from tests.test_train import mock_dict |
|
|
|
|
| class TestConcatDataset(unittest.TestCase): |
| def setUp(self): |
| d = mock_dict() |
| tokens_1 = torch.LongTensor([1]).view(1, -1) |
| tokens_ds1 = TokenBlockDataset( |
| tokens_1, |
| sizes=[tokens_1.size(-1)], |
| block_size=1, |
| pad=0, |
| eos=1, |
| include_targets=False, |
| ) |
| self.dataset_1 = LanguagePairDataset( |
| tokens_ds1, tokens_ds1.sizes, d, shuffle=False |
| ) |
| tokens_2 = torch.LongTensor([2]).view(1, -1) |
| tokens_ds2 = TokenBlockDataset( |
| tokens_2, |
| sizes=[tokens_2.size(-1)], |
| block_size=1, |
| pad=0, |
| eos=1, |
| include_targets=False, |
| ) |
| self.dataset_2 = LanguagePairDataset( |
| tokens_ds2, tokens_ds2.sizes, d, shuffle=False |
| ) |
|
|
| def test_concat_dataset_basics(self): |
| d = ConcatDataset([self.dataset_1, self.dataset_2]) |
| assert len(d) == 2 |
| assert d[0]["source"][0] == 1 |
| assert d[1]["source"][0] == 2 |
|
|
| d = ConcatDataset([self.dataset_1, self.dataset_2], sample_ratios=[1, 2]) |
| assert len(d) == 3 |
| assert d[0]["source"][0] == 1 |
| assert d[1]["source"][0] == 2 |
| assert d[2]["source"][0] == 2 |
|
|
| d = ConcatDataset([self.dataset_1, self.dataset_2], sample_ratios=[2, 1]) |
| assert len(d) == 3 |
| assert d[0]["source"][0] == 1 |
| assert d[1]["source"][0] == 1 |
| assert d[2]["source"][0] == 2 |
|
|
