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def setUp(self):
embedding_patcher = patch('sister.word_embedders.FasttextEmbedding')
embedding = embedding_patcher.start()(lang='en')
embedding.get_word_vector.return_value = np.random.rand(300)
embedding.get_word_vectors.side_effect = lambda words: np.random.rand(len(words), 300)
self.sentence_embedding = MeanEmbedding(
tokenizer=SimpleTokenizer(),
word_embedder=embedding
)
self.addCleanup(embedding_patcher.stop)
def __init__(
self,
lang: str = 'en',
tokenizer: Tokenizer = None,
word_embedder: WordEmbedding = None) -> None:
tokenizer = tokenizer or {"en": SimpleTokenizer(),
"fr": SimpleTokenizer(),
"ja": JapaneseTokenizer()}[lang]
word_embedder = word_embedder or FasttextEmbedding(lang)
super().__init__(tokenizer, word_embedder)