Skip to content

Commit 89bf1a0

Browse files
committed
chore: merge branch 'main' of github.com:ninpnin/probabilistic-word-embeddings
2 parents 1230b62 + 2642f7f commit 89bf1a0

File tree

9 files changed

+503
-449
lines changed

9 files changed

+503
-449
lines changed

README.md

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1,4 +1,4 @@
1-
# probabilistic-word-embeddings v1.13.7
1+
# probabilistic-word-embeddings v1.16.0
22

33
Probabilistic Word Embedding module for Python. Built with TensorFlow 2.x and TensorFlow probability.
44

docs/probabilistic_word_embeddings.html

Lines changed: 3 additions & 3 deletions
Large diffs are not rendered by default.

docs/probabilistic_word_embeddings/embeddings.html

Lines changed: 437 additions & 385 deletions
Large diffs are not rendered by default.

docs/probabilistic_word_embeddings/estimation.html

Lines changed: 3 additions & 3 deletions
Large diffs are not rendered by default.

docs/probabilistic_word_embeddings/evaluation.html

Lines changed: 9 additions & 9 deletions
Large diffs are not rendered by default.

docs/probabilistic_word_embeddings/models.html

Lines changed: 3 additions & 3 deletions
Large diffs are not rendered by default.

docs/probabilistic_word_embeddings/preprocessing.html

Lines changed: 41 additions & 39 deletions
Large diffs are not rendered by default.

docs/probabilistic_word_embeddings/utils.html

Lines changed: 3 additions & 3 deletions
Large diffs are not rendered by default.

probabilistic_word_embeddings/evaluation.py

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -200,9 +200,9 @@ def words_in_e(row):
200200
r = len(df)
201201
target_words = list(df[columns[-1]])
202202

203-
X1 = embedding[df[columns[0]]]
204-
X2 = embedding[df[columns[1]]]
205-
X3 = embedding[df[columns[2]]]
203+
X1 = embedding[list(df[columns[0]])]
204+
X2 = embedding[list(df[columns[1]])]
205+
X3 = embedding[list(df[columns[2]])]
206206
X = X1 - X2 + X3
207207

208208
inv_vocab = {v: k for k, v in e.vocabulary.items()}

0 commit comments

Comments
 (0)