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| # Copyright (c) Facebook, Inc. and its affiliates. | |
| # | |
| # This source code is licensed under the MIT license found in the | |
| # LICENSE file in the root directory of this source tree. | |
| import unittest | |
| import torch | |
| from fairseq.data import Dictionary | |
| from fairseq.modules import CharacterTokenEmbedder | |
| class TestCharacterTokenEmbedder(unittest.TestCase): | |
| def test_character_token_embedder(self): | |
| vocab = Dictionary() | |
| vocab.add_symbol("hello") | |
| vocab.add_symbol("there") | |
| embedder = CharacterTokenEmbedder( | |
| vocab, [(2, 16), (4, 32), (8, 64), (16, 2)], 64, 5, 2 | |
| ) | |
| test_sents = [["hello", "unk", "there"], ["there"], ["hello", "there"]] | |
| max_len = max(len(s) for s in test_sents) | |
| input = torch.LongTensor(len(test_sents), max_len + 2).fill_(vocab.pad()) | |
| for i in range(len(test_sents)): | |
| input[i][0] = vocab.eos() | |
| for j in range(len(test_sents[i])): | |
| input[i][j + 1] = vocab.index(test_sents[i][j]) | |
| input[i][j + 2] = vocab.eos() | |
| embs = embedder(input) | |
| assert embs.size() == (len(test_sents), max_len + 2, 5) | |
| self.assertAlmostEqual(embs[0][0], embs[1][0]) | |
| self.assertAlmostEqual(embs[0][0], embs[0][-1]) | |
| self.assertAlmostEqual(embs[0][1], embs[2][1]) | |
| self.assertAlmostEqual(embs[0][3], embs[1][1]) | |
| embs.sum().backward() | |
| assert embedder.char_embeddings.weight.grad is not None | |
| def assertAlmostEqual(self, t1, t2): | |
| self.assertEqual(t1.size(), t2.size(), "size mismatch") | |
| self.assertLess((t1 - t2).abs().max(), 1e-6) | |
| if __name__ == "__main__": | |
| unittest.main() | |