code: def preprocess_for_eval(
      image_bytes, use_bfloat16, image_size=IMAGE_SIZE
  ):
      """Preprocesses the given image for evaluation.
  
      Args:
        image_bytes: `Tensor` representing an image binary of arbitrary size.
        use_bfloat16: `bool` for whether to use bfloat16.
        image_size: image size.
  
      Returns:
        A preprocessed image `Tensor`.
      """
      image = _decode_and_center_crop(image_bytes, image_size)
      image = tf.reshape(image, [image_size, image_size, 3])
      image = tf.image.convert_image_dtype(
          image, dtype=tf.bfloat16 if use_bfloat16 else tf.float32
      )
      return image
  
file_path: EfficientNet-PyTorch/tf_to_pytorch/convert_tf_to_pt/original_tf/preprocessing.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl import logging
  import tensorflow.compat.v1
label_desc: Use image node_id 7 for calling a global function with example usage: preprocess_for_eval(image_bytes, use_bfloat16, image_size) and returns: image