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Updates made for Python3 #102

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Updates made for Python3 #102

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14 changes: 7 additions & 7 deletions lda2vec/__init__.py
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Original file line number Diff line number Diff line change
@@ -1,10 +1,10 @@
import dirichlet_likelihood
import embed_mixture
import tracking
import preprocess
import corpus
import topics
import negative_sampling
import lda2vec.dirichlet_likelihood
import lda2vec.embed_mixture
import lda2vec.tracking
import lda2vec.preprocess
import lda2vec.corpus
import lda2vec.topics
import lda2vec.negative_sampling

dirichlet_likelihood = dirichlet_likelihood.dirichlet_likelihood
EmbedMixture = embed_mixture.EmbedMixture
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2 changes: 1 addition & 1 deletion lda2vec/corpus.py
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Expand Up @@ -576,7 +576,7 @@ def compact_word_vectors(self, vocab, filename=None, array=None,
choice = np.array(keys_raw)[idx][np.argmin(d)]
# choice = difflib.get_close_matches(word, choices)[0]
vector = model[choice]
print compact, word, ' --> ', choice
print(compact, word, ' --> ', choice)
except IndexError:
pass
if vector is None:
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2 changes: 1 addition & 1 deletion lda2vec/preprocess.py
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@@ -1,4 +1,4 @@
from spacy.en import English
from spacy.lang.en import English
from spacy.attrs import LOWER, LIKE_URL, LIKE_EMAIL

import numpy as np
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2 changes: 1 addition & 1 deletion lda2vec/topics.py
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Expand Up @@ -103,7 +103,7 @@ def print_top_words_per_topic(data, top_n=10, do_print=True):
top_words = [data['vocab'][i].strip().replace(' ', '_') for i in top]
msg = ' '.join(top_words)
if do_print:
print prefix + msg
print(prefix + msg)
lists.append(top_words)
return lists

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