tensor2tensor/models/image_transformer_2d.py [337:366]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      ]):
        new_result = tf.identity(new_result)

      return new_result, new_length

    result = tf.zeros((1, 0, 1, 1), dtype=tf.int64)
    length = tf.squeeze(tf.zeros(1, dtype=tf.int32))

    result, length = tf.while_loop(
        while_exit_cond,
        infer_step,
        [result, length],
        shape_invariants=[
            tf.TensorShape([1, None, 1, 1]),
            tf.TensorShape([]),
        ],
        back_prop=False,
        parallel_iterations=1)

    result = result[:, :length, :, :]

    features["inputs"] = inputs_old

    return {
        "outputs": result,
        "scores": None,
    }


@registry.register_hparams
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



tensor2tensor/models/research/transformer_parallel.py [202:231]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
      ]):
        new_result = tf.identity(new_result)

      return new_result, new_length

    result = tf.zeros((1, 0, 1, 1), dtype=tf.int64)
    length = tf.squeeze(tf.zeros(1, dtype=tf.int32))

    result, length = tf.while_loop(
        while_exit_cond,
        infer_step,
        [result, length],
        shape_invariants=[
            tf.TensorShape([1, None, 1, 1]),
            tf.TensorShape([]),
        ],
        back_prop=False,
        parallel_iterations=1)

    result = result[:, :length, :, :]

    features["inputs"] = inputs_old

    return {
        "outputs": result,
        "scores": None,
    }


@registry.register_hparams
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -