def main():
config = load_config()
with open(os.path.join(config.cooccurrence_dir, "vocab.pkl"), "rb") as f:
vocab = pickle.load(f)
model = GloVe(
vocab_size=config.vocab_size,
embedding_size=config.embedding_size,
x_max=config.x_max,
alpha=config.alpha
)
model.load_state_dict(torch.load(config.output_filepath))
keyed_vectors = KeyedVectors(vector_size=config.embedding_size)
keyed_vectors.add_vectors(
keys=[vocab.get_token(index) for index in range(config.vocab_size)],
weights=(model.weight.weight.detach()
+ model.weight_tilde.weight.detach()).numpy()
)
print("How similar is man and woman:")
print(keyed_vectors.similarity("woman", "man"))
print("How similar is man and apple:")
print(keyed_vectors.similarity("apple", "man"))
print("How similar is woman and apple:")
print(keyed_vectors.similarity("apple", "woman"))
for word in ["computer", "united", "early"]:
print(f"Most similar words of {word}:")
most_similar_words = [word for word, _ in keyed_vectors.similar_by_word(word)]
print(most_similar_words)
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_vectors(words, vectors)
assert kv.vectors.dtype == REAL
def test_no_header(self):
randkv = KeyedVectors(vector_size=100)
count = 20
keys = [str(i) for i in range(count)]
weights = [pseudorandom_weak_vector(randkv.vector_size) for _ in range(count)]
randkv.add_vectors(keys, weights)
tmpfiletxt = gensim.test.utils.get_tmpfile("tmp_kv.txt")
randkv.save_word2vec_format(tmpfiletxt, binary=False, write_header=False)
reloadtxtkv = KeyedVectors.load_word2vec_format(tmpfiletxt, binary=False, no_header=True)
self.assertEqual(randkv.index_to_key, reloadtxtkv.index_to_key)
self.assertTrue((randkv.vectors == reloadtxtkv.vectors).all())
def test_add_single(self):
"""Test that adding entity in a manual way works correctly."""
entities = [f'___some_entity{i}_not_present_in_keyed_vectors___' for i in range(5)]
vectors = [np.random.randn(self.vectors.vector_size) for _ in range(5)]
# Test `add` on already filled kv.
for ent, vector in zip(entities, vectors):
self.vectors.add_vectors(ent, vector)
for ent, vector in zip(entities, vectors):
self.assertTrue(np.allclose(self.vectors[ent], vector))
# Test `add` on empty kv.
kv = KeyedVectors(self.vectors.vector_size)
for ent, vector in zip(entities, vectors):
kv.add_vectors(ent, vector)
for ent, vector in zip(entities, vectors):
self.assertTrue(np.allclose(kv[ent], vector))
