for key, values in w2v.items(): f.write('%s %s\n' % (key, ' '.join(format(x, '.5f') for x in values))) f.close() # Initialisation if FLAGS.method == 'articles': document = Articles(params=FLAGS) document.build_dictionary() vocabulary_size = document.get_vocab_size() word2id = document.get_word2id() id2word = document.get_id2word() articles = document.get_articles() next_word_idx = 0 input_word, context_word = build_training_data() next_batch_articles(FLAGS.batch_size, FLAGS.skip_window) else: tw = TextWords() tw.build_dictionary() word2id = tw.get_word2id() id2word = tw.get_id2word() data = tw.get_data() vocabulary_size = tw.get_vocab_size() # Generate training batch for the skip-gram model data_index = 0