f80bc276189c2e35894faa73871b1b4ee6202ef9,bin/basenji_train_queues.py,,run,#Any#Any#Any#Any#Any#Any#,44

Before Change

      // print update
      print("Epoch: %3d,  Steps: %7d,  Train loss: %7.5f," % (epoch+1, steps, train_loss), end="")
      print(" Valid loss: %7.5f,  Valid R2: %7.5f," % (valid_loss, valid_r2), end="")
      print(" Time: %s%s" % (time_str, best_str))
      sys.stdout.flush()

      // update epoch

After Change

                            FLAGS.ensemble_rc, ensemble_shifts)

  // launch accuracy compute thread
  acc_queue = Queue()
  acc_thread = AccuracyWorker(acc_queue)
  acc_thread.start()

  // checkpoints
  saver = tf.train.Saver()

  with tf.Session() as sess:
    train_writer = tf.summary.FileWriter(FLAGS.logdir + "/train",
                                         sess.graph) if FLAGS.logdir else None

    coord = tf.train.Coordinator()
    tf.train.start_queue_runners(coord=coord)

    if FLAGS.restart:
      // load variables into session
      saver.restore(sess, FLAGS.restart)
    else:
      // initialize variables
      t0 = time.time()
      print("Initializing...")
      sess.run(tf.local_variables_initializer())
      sess.run(tf.global_variables_initializer())
      print("Initialization time %f" % (time.time() - t0))

    train_loss = None
    best_loss = None
    early_stop_i = 0

    epoch = 0
    while (train_epochs is not None and epoch < train_epochs) or \
          (train_epochs is None and early_stop_i < FLAGS.early_stop):
      t0 = time.time()

      // save previous
      train_loss_last = train_loss

      // train epoch
      sess.run(training_init_op)
      train_loss, steps = model.train_epoch_tfr(sess, train_writer, train_epoch_batches)

      // block for previous accuracy compute
      acc_queue.join()

      // test validation
      sess.run(test_init_op)
      valid_acc = model.test_tfr(sess, test_epoch_batches)

Instances