Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Fix KeyedVectors.add matrix type #2761

Merged
merged 6 commits into from
Mar 21, 2020
Merged

Fix KeyedVectors.add matrix type #2761

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
faa4e57
add type test
menshikh-iv Feb 29, 2020
9c1f0f2
cast internal state to passed type
menshikh-iv Feb 29, 2020
38daff5
ekv -> kv
menshikh-iv Mar 1, 2020
e031fc4
parametrize datatype & cast embeddings passed to `add` to KV datatype
menshikh-iv Mar 1, 2020
7c7ce19
set f32 as default type
menshikh-iv Mar 1, 2020
646a051
Merge branch 'develop' into fix-kv-type
mpenkov Mar 21, 2020
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 3 additions & 3 deletions gensim/models/keyedvectors.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -215,7 +215,7 @@ def __str__(self):
class BaseKeyedVectors(utils.SaveLoad):
"""Abstract base class / interface for various types of word vectors."""
def __init__(self, vector_size):
self.vectors = zeros((0, vector_size))
self.vectors = zeros((0, vector_size), dtype=REAL)
mpenkov marked this conversation as resolved.
Show resolved Hide resolved
self.vocab = {}
self.vector_size = vector_size
self.index2entity = []
Expand Down Expand Up @@ -308,7 +308,7 @@ def add(self, entities, weights, replace=False):
self.index2entity.append(entity)

# add vectors for new entities
self.vectors = vstack((self.vectors, weights[~in_vocab_mask]))
self.vectors = vstack((self.vectors, weights[~in_vocab_mask].astype(self.vectors.dtype)))

# change vectors for in_vocab entities if `replace` flag is specified
if replace:
Expand Down Expand Up @@ -2113,7 +2113,7 @@ def word_vec(self, word, use_norm=False):
elif self.bucket == 0:
raise KeyError('cannot calculate vector for OOV word without ngrams')
else:
word_vec = np.zeros(self.vectors_ngrams.shape[1], dtype=np.float32)
word_vec = np.zeros(self.vectors_ngrams.shape[1], dtype=REAL)
ngram_hashes = ft_ngram_hashes(word, self.min_n, self.max_n, self.bucket, self.compatible_hash)
if len(ngram_hashes) == 0:
#
Expand Down
25 changes: 17 additions & 8 deletions gensim/test/test_keyedvectors.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -15,8 +15,8 @@
import numpy as np

from gensim.corpora import Dictionary
from gensim.models.keyedvectors import KeyedVectors as EuclideanKeyedVectors, WordEmbeddingSimilarityIndex, \
FastTextKeyedVectors
from gensim.models.keyedvectors import KeyedVectors, WordEmbeddingSimilarityIndex, \
FastTextKeyedVectors, REAL
from gensim.test.utils import datapath

import gensim.models.keyedvectors
Expand All @@ -27,7 +27,7 @@

class TestWordEmbeddingSimilarityIndex(unittest.TestCase):
def setUp(self):
self.vectors = EuclideanKeyedVectors.load_word2vec_format(
self.vectors = KeyedVectors.load_word2vec_format(
datapath('euclidean_vectors.bin'), binary=True, datatype=np.float64)

def test_most_similar(self):
Expand Down Expand Up @@ -70,9 +70,9 @@ def test_most_similar(self):
self.assertTrue(np.allclose(first_similarities**2.0, second_similarities))


class TestEuclideanKeyedVectors(unittest.TestCase):
class TestKeyedVectors(unittest.TestCase):
def setUp(self):
self.vectors = EuclideanKeyedVectors.load_word2vec_format(
self.vectors = KeyedVectors.load_word2vec_format(
datapath('euclidean_vectors.bin'), binary=True, datatype=np.float64)

def test_similarity_matrix(self):
Expand Down Expand Up @@ -227,7 +227,7 @@ def test_add_single(self):
self.assertTrue(np.allclose(self.vectors[ent], vector))

# Test `add` on empty kv.
kv = EuclideanKeyedVectors(self.vectors.vector_size)
kv = KeyedVectors(self.vectors.vector_size)
for ent, vector in zip(entities, vectors):
kv.add(ent, vector)

Expand All @@ -248,13 +248,22 @@ def test_add_multiple(self):
self.assertTrue(np.allclose(self.vectors[ent], vector))

# Test `add` on empty kv.
kv = EuclideanKeyedVectors(self.vectors.vector_size)
kv = KeyedVectors(self.vectors.vector_size)
kv[entities] = vectors
self.assertEqual(len(kv.vocab), len(entities))

for ent, vector in zip(entities, vectors):
self.assertTrue(np.allclose(kv[ent], vector))

def test_add_type(self):
kv = KeyedVectors(2)
assert kv.vectors.dtype == REAL

words, vectors = ["a"], np.array([1., 1.], dtype=np.float64).reshape(1, -1)
kv.add(words, vectors)

assert kv.vectors.dtype == REAL

def test_set_item(self):
"""Test that __setitem__ works correctly."""
vocab_size = len(self.vectors.vocab)
Expand Down Expand Up @@ -287,7 +296,7 @@ def test_set_item(self):
self.assertTrue(np.allclose(self.vectors[ent], vector))

def test_ft_kv_backward_compat_w_360(self):
kv = EuclideanKeyedVectors.load(datapath("ft_kv_3.6.0.model.gz"))
kv = KeyedVectors.load(datapath("ft_kv_3.6.0.model.gz"))
ft_kv = FastTextKeyedVectors.load(datapath("ft_kv_3.6.0.model.gz"))

expected = ['trees', 'survey', 'system', 'graph', 'interface']
Expand Down