# How get matrix of word embeddings in FastText of gensim?

I try get the matrix embedding of my model but I can't because although this code gives no error it never ends running. The code is:

def fast_text(norm_corpus):
wpt = nltk.WordPunctTokenizer()
tokenized_corpus = [wpt.tokenize(document) for document in norm_corpus]
# Set values for various parameters
feature_size = 300
# Word vector dimensionality
window_context = 5
# Context window size
min_word_count = 1
# Minimum word count
sample = 1e-3
ft_model = FastText(tokenized_corpus, size=feature_size, window=window_context,min_count=min_word_count,sample=sample, sg=i, iter=50)

words = list(ft_model.wv.vocab)
vectors = []
for w in words:
vectors.append(ft_model[w].tolist())
embedding_matrix = np.array(vectors)
embedding_matrix = embedding_matrix.T
print(embedding_matrix.shape)

return embedding_matrix


I don't know how fix it.