d2694eacb1fdd698a7629271d43f99acf5e75b34,models/official/amoeba_net/amoeba_net.py,,main,#Any#,319

Before Change

          time_hook.compute_speed(len(results) * eval_batch_size)))
  elif mode == "export_savedmodel":
    tf.logging.info("Starting exporting saved model ...")
    image_classifier.export_saved_model(
        export_dir_base=model_dir + "/export_savedmodel/",
        serving_input_receiver_fn=build_tensor_serving_input_receiver_fn(
            [hparams.image_size, hparams.image_size, 3],
            batch_size=hparams.eval_batch_size),
        as_text=True)
  else:  // default to train mode.
    current_step = _load_global_step_from_checkpoint_dir(model_dir)
    total_step = int(hparams.num_epochs * train_steps_per_epoch)
    if current_step < total_step:

After Change

        serving_input_receiver_fn=build_image_serving_input_receiver_fn(
            serving_shape),
        as_text=True)
    if FLAGS.add_warmup_requests:
      write_warmup_requests(
          export_path,
          FLAGS.model_name,
          hparams.image_size,
          batch_sizes=FLAGS.inference_batch_sizes)


if __name__ == "__main__":
  tf.logging.set_verbosity(tf.logging.INFO)
  app.run(main)

Instances