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Fixes change in dtype of model.wv.syn0_vocab on updating vocab of a FastText model #1760

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Dec 5, 2017
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Fixes change in dtype of model.wv.syn0_vocab on updating vocab of a FastText model #1760

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7fbc060
extends `test_online` to check dtype
manneshiva Dec 4, 2017
9fac250
casts numpy array returned by `random.uniform` to `float32`
manneshiva Dec 4, 2017
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8 changes: 4 additions & 4 deletions gensim/models/fasttext.py
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Original file line number Diff line number Diff line change
Expand Up @@ -173,12 +173,12 @@ def init_ngrams(self, update=False):
new_vocab_rows = rand_obj.uniform(
-1.0 / self.vector_size, 1.0 / self.vector_size,
(len(self.wv.vocab) - self.old_vocab_len, self.vector_size)
)
).astype(REAL)
new_vocab_lockf_rows = ones((len(self.wv.vocab) - self.old_vocab_len, self.vector_size), dtype=REAL)
new_ngram_rows = rand_obj.uniform(
-1.0 / self.vector_size, 1.0 / self.vector_size,
(len(self.wv.hash2index) - self.old_hash2index_len, self.vector_size)
)
).astype(REAL)
new_ngram_lockf_rows = ones(
(len(self.wv.hash2index) - self.old_hash2index_len, self.vector_size), dtype=REAL
)
Expand All @@ -194,11 +194,11 @@ def reset_ngram_weights(self):
for index in range(len(self.wv.vocab)):
self.wv.syn0_vocab[index] = rand_obj.uniform(
-1.0 / self.vector_size, 1.0 / self.vector_size, self.vector_size
)
).astype(REAL)
for index in range(len(self.wv.hash2index)):
self.wv.syn0_ngrams[index] = rand_obj.uniform(
-1.0 / self.vector_size, 1.0 / self.vector_size, self.vector_size
)
).astype(REAL)

def _do_train_job(self, sentences, alpha, inits):
work, neu1 = inits
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1 change: 1 addition & 0 deletions gensim/test/test_fasttext.py
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Original file line number Diff line number Diff line change
Expand Up @@ -422,6 +422,7 @@ def online_sanity(self, model):
self.assertFalse('terrorism' in model.wv.vocab)
self.assertFalse('orism>' in model.wv.ngrams)
model.build_vocab(terro, update=True) # update vocab
self.assertTrue(model.wv.syn0_ngrams.dtype == 'float32')
self.assertTrue('terrorism' in model.wv.vocab)
self.assertTrue('orism>' in model.wv.ngrams)
orig0_all = np.copy(model.wv.syn0_ngrams)
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