11-lstm-tensorflow-char-pat.py 文件源码

def train_it(sess, step=1):
    _pat_chars_i, _pat_lens = get_batch(__batch_size)
    inputs = {
        pat_chars_i: _pat_chars_i,
        pat_lens: _pat_lens}

    # Run optimization op (backprop)
    #run_options = tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE)
    #run_metadata = tf.RunMetadata()
    #sess.run(optimizer, feed_dict=inputs, options=run_options, run_metadata=run_metadata)
    sess.run(optimizer, feed_dict=inputs)
    #with open('timeline.json', 'w') as f:
    #    f.write(
    #        timeline.Timeline(run_metadata.step_stats)
    #            .generate_chrome_trace_format())

    if step % display_step == 0:
        # Calculate batch loss
        cost_f = sess.run(cost, feed_dict=inputs)
        print ("Iter {}, cost= {:.6f}".format(
            str(step*__batch_size), cost_f))