Remove the beam search generator about chatbot-rnn HOT 2 CLOSED

def chatbot(net, sess, chars, vocab, max_length, beam_width, relevance, temperature, topn, input_text):
    states = initial_state_with_relevance_masking(net, sess, relevance)
    while True:
        #user_input = input('\n> ')
        user_input = input_text
        start_time = time.time()
        user_command_entered, reset, states, relevance, temperature, topn, beam_width = process_user_command(
            user_input, states, relevance, temperature, topn, beam_width)
        if reset: states = initial_state_with_relevance_masking(net, sess, relevance)
        if not user_command_entered:
            beam_width = 1
            states = forward_text(net, sess, states, relevance, vocab, sanitize_text(vocab, "> " + user_input + "\n>"))
            computer_response_generator = beam_search_generator(sess=sess, net=net,
                initial_state=copy.deepcopy(states), initial_sample=vocab[' '],
                early_term_token=vocab['\n'], beam_width=beam_width, forward_model_fn=forward_with_mask,
                forward_args={'relevance':relevance, 'mask_reset_token':vocab['\n'], 'forbidden_token':vocab['>'],
                                'temperature':temperature, 'topn':topn})
            #print(chars)
            out_chars = []
            out = []
            for i, char_token in enumerate(computer_response_generator):
                out_chars.append(chars[char_token])
                out.append(possibly_escaped_char(out_chars))
                #print(possibly_escaped_char(out_chars), end='', flush=True)
                states = forward_text(net, sess, states, relevance, vocab, chars[char_token])
                if i >= max_length: break
            #print("".join(out))
            #print("--- %s seconds ---" % (time.time() - start_time))
            return "".join(out)
            states = forward_text(net, sess, states, relevance, vocab, sanitize_text(vocab, "\n> "))