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-
- import unittest
- from fastNLP import Vocabulary
- from fastNLP.embeddings import ElmoEmbedding
- import torch
- import os
-
- @unittest.skipIf('TRAVIS' in os.environ, "Skip in travis")
- class TestDownload(unittest.TestCase):
- def test_download_small(self):
- # import os
- vocab = Vocabulary().add_word_lst("This is a test .".split())
- elmo_embed = ElmoEmbedding(vocab, model_dir_or_name='en-small')
- words = torch.LongTensor([[0, 1, 2]])
- print(elmo_embed(words).size())
-
-
- # 首先保证所有权重可以加载;上传权重;验证可以下载
-
-
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