def preprocess_image(image_bytes,
                     is_training=False,
                     use_bfloat16=False,
                     image_size=IMAGE_SIZE,
                     augment_name=None,
                     randaug_num_layers=None,
                     randaug_magnitude=None):
  """Preprocesses the given image.

  Args:
    image_bytes: `Tensor` representing an image binary of arbitrary size.
    is_training: `bool` for whether the preprocessing is for training.
    use_bfloat16: `bool` for whether to use bfloat16.
    image_size: image size.
    augment_name: `string` that is the name of the augmentation method
      to apply to the image. `autoaugment` if AutoAugment is to be used or
      `randaugment` if RandAugment is to be used. If the value is `None` no
      augmentation method will be applied applied. See autoaugment.py for more
      details.
    randaug_num_layers: 'int', if RandAug is used, what should the number of
      layers be. See autoaugment.py for detailed description.
    randaug_magnitude: 'int', if RandAug is used, what should the magnitude
      be. See autoaugment.py for detailed description.

  Returns:
    A preprocessed image `Tensor` with value range of [0, 255].
  """
  if is_training:
    return preprocess_for_train(
        image_bytes, use_bfloat16, image_size, augment_name,
        randaug_num_layers, randaug_magnitude)
  else:
    return preprocess_for_eval(image_bytes, use_bfloat16, image_size)
Preprocesses the given image.

  Args:
    image_bytes: `Tensor` representing an image binary of arbitrary size.
    is_training: `bool` for whether the preprocessing is for training.
    use_bfloat16: `bool` for whether to use bfloat16.
    image_size: image size.
    augment_name: `string` that is the name of the augmentation method
      to apply to the image. `autoaugment` if AutoAugment is to be used or
      `randaugment` if RandAugment is to be used. If the value is `None` no
      augmentation method will be applied applied. See autoaugment.py for more
      details.
    randaug_num_layers: 'int', if RandAug is used, what should the number of
      layers be. See autoaugment.py for detailed description.
    randaug_magnitude: 'int', if RandAug is used, what should the magnitude
      be. See autoaugment.py for detailed description.

  Returns:
    A preprocessed image `Tensor` with value range of [0, 255].
  
tf_to_pytorch/convert_tf_to_pt/original_tf/preprocessing.py