def test_visualize_word_emeddings():
with open('./resources/visual/snippet.txt') as f:
sentences = [x for x in f.read().split('\n') if x]
sentences = [Sentence(x) for x in sentences]
charlm_embedding_forward = CharLMEmbeddings('news-forward')
visualizer = Visualizer()
visualizer.visualize_char_emeddings(
charlm_embedding_forward, sentences,
'./resources/visual/sentence_embeddings.html')
# clean up directory
os.remove('./resources/visual/sentence_embeddings.html')
def test_visualize_word_emeddings(resources_path):
with open(resources_path / 'visual/snippet.txt') as f:
sentences = [x for x in f.read().split('\n') if x]
sentences = [Sentence(x) for x in sentences]
charlm_embedding_forward = CharLMEmbeddings('news-forward')
visualizer = Visualizer()
visualizer.visualize_char_emeddings(
charlm_embedding_forward, sentences,
str(resources_path / 'visual/sentence_embeddings.html'))
# clean up directory
(resources_path / 'visual/sentence_embeddings.html').unlink()
def test_visualize():
with open('./resources/visual/snippet.txt') as f:
sentences = [x for x in f.read().split('\n') if x]
sentences = [Sentence(x) for x in sentences]
embeddings = CharLMEmbeddings('news-forward')
visualizer = Visualizer()
X_forward = visualizer.prepare_char_embeddings(embeddings, sentences)
embeddings = CharLMEmbeddings('news-backward')
X_backward = visualizer.prepare_char_embeddings(embeddings, sentences)
X = numpy.concatenate([X_forward, X_backward], axis=1)
contexts = visualizer.char_contexts(sentences)
trans_ = tSNE()
reduced = trans_.fit(X)
visualizer.visualize(reduced, contexts,
'./resources/visual/char_embeddings.html')
# clean up directory
os.remove('./resources/visual/char_embeddings.html')
def test_visualize_word_emeddings(resources_path):
with open(resources_path / 'visual/snippet.txt') as f:
sentences = [x for x in f.read().split('\n') if x]
sentences = [Sentence(x) for x in sentences]
charlm_embedding_forward = CharLMEmbeddings('news-forward')
charlm_embedding_backward = CharLMEmbeddings('news-backward')
embeddings = StackedEmbeddings(
[charlm_embedding_backward, charlm_embedding_forward])
visualizer = Visualizer()
visualizer.visualize_word_emeddings(
embeddings, sentences,
str(resources_path / 'visual/sentence_embeddings.html'))
# clean up directory
os.remove(resources_path / 'visual/sentence_embeddings.html')