'in_matr': in_matr,
'out_matr': out_matr
}
import time
print("Reading data", time.asctime(time.localtime(time.time())))
# Estimate vocabulary from training data
# voc = pickle.load(open("voc.pkl", "rb"))
voc = Vocabulary()
with open(data_path, "r") as data:
line = data.readline()
while line:
tokens = line.strip().split()
voc.add_words(tokens)
line = data.readline()
voc.prune(top_words)
voc.export_vocabulary(top_words, "voc.tsv")
voc.save("voc.pkl")
print("Starting training", time.asctime(time.localtime(time.time())))
reader = Reader(data_path, voc, n_contexts, window_size, k)
terminals = assemble_graph(top_words, n_dims)
first_batch = None
in_words_ = terminals['in_words']
out_words_ = terminals['out_words']
