parameters: ()
return_statement: return tf.estimator.export.ServingInputReceiver(
        images, {'image_bytes': image_bytes_list})
docstring: Serving input fn for raw images.
docstring_summary: Serving input fn for raw images.
docstring_tokens: Serving input fn for raw images .
function: def image_serving_input_fn():
    """Serving input fn for raw images."""
  
    def _preprocess_image(image_bytes):
      """Preprocess a single raw image."""
      image = resnet_preprocessing.preprocess_image(
          image_bytes=image_bytes, is_training=False)
      return image
  
    image_bytes_list = tf.placeholder(
        shape=[None],
        dtype=tf.string,
    )
    images = tf.map_fn(
        _preprocess_image, image_bytes_list, back_prop=False, dtype=tf.float32)
    return tf.estimator.export.ServingInputReceiver(
        images, {'image_bytes': image_bytes_list})
function_tokens: def image_serving_input_fn ( ) : def _preprocess_image ( image_bytes ) : """Preprocess a single raw image.""" image = resnet_preprocessing . preprocess_image ( image_bytes = image_bytes , is_training = False ) return image image_bytes_list = tf . placeholder ( shape = [ None ] , dtype = tf . string , ) images = tf . map_fn ( _preprocess_image , image_bytes_list , back_prop = False , dtype = tf . float32 ) return tf . estimator . export . ServingInputReceiver ( images , { 'image_bytes' : image_bytes_list } )