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Summary: # Before submitting - [ ] Was this discussed/approved via a Github issue? (no need for typos, doc improvements) - [ ] Did you read the [contributor guideline](https://github.com/pytorch/fairseq/blob/main/CONTRIBUTING.md)? - [ ] Did you make sure to update the docs? - [ ] Did you write any new necessary tests? ## What does this PR do? Fixes # (issue). ## PR review Anyone in the community is free to review the PR once the tests have passed. If we didn't discuss your PR in Github issues there's a high chance it will not be merged. ## Did you have fun? Make sure you had fun coding � Pull Request resolved: https://github.com/fairinternal/fairseq-py/pull/2678 Reviewed By: Mortimerp9 Differential Revision: D32653381 Pulled By: dianaml0 fbshipit-source-id: 2810d14867cd7d64f4d340740e2b590b82de47fe
54 lines
1.8 KiB
Python
54 lines
1.8 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 torch
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from fairseq.data import MonolingualDataset
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from fairseq.tasks.language_modeling import LanguageModelingConfig, LanguageModelingTask
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from tests import utils as test_utils
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class TestLMContextWindow(unittest.TestCase):
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def test_eval_dataloader(self):
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dictionary = test_utils.dummy_dictionary(10)
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assert len(dictionary) == 14 # 4 extra special symbols
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assert dictionary.pad() == 1
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dataset = test_utils.TestDataset(
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[
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torch.tensor([4, 5, 6, 7], dtype=torch.long),
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torch.tensor([8, 9, 10, 11], dtype=torch.long),
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torch.tensor([12, 13], dtype=torch.long),
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]
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)
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dataset = MonolingualDataset(dataset, sizes=[4, 4, 2], src_vocab=dictionary)
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config = LanguageModelingConfig(tokens_per_sample=4)
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task = LanguageModelingTask(config, dictionary)
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eval_dataloader = task.eval_lm_dataloader(
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dataset=dataset,
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batch_size=1,
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context_window=2,
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)
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batch = next(eval_dataloader)
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assert batch["net_input"]["src_tokens"][0].tolist() == [4, 5, 6, 7, 1, 1]
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assert batch["target"][0].tolist() == [4, 5, 6, 7, 1, 1]
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batch = next(eval_dataloader)
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assert batch["net_input"]["src_tokens"][0].tolist() == [6, 7, 8, 9, 10, 11]
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assert batch["target"][0].tolist() == [1, 1, 8, 9, 10, 11]
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batch = next(eval_dataloader)
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assert batch["net_input"]["src_tokens"][0].tolist() == [10, 11, 12, 13]
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assert batch["target"][0].tolist() == [1, 1, 12, 13]
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if __name__ == "__main__":
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unittest.main()
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