code: def inception_crop_with_mask(
      image, mask, resize_size=None, area_min=5, area_max=100
  ):
      """Applies the same inception-style crop to an image and a mask tensor.
  
      Inception-style crop is a random image crop (its size and aspect ratio are
      random) that was used for training Inception models, see
      https://www.cs.unc.edu/~wliu/papers/GoogLeNet.pdf.
  
      Args:
        image: [H, W, C] image tensor.
        mask: [H, W, None] mask tensor. H and W must match the image. Will be
          resized using tf.image.ResizeMethod.NEAREST_NEIGHBOR.
        resize_size: Sequence of 2 ints; Resize image to [height, width] after crop.
        area_min: minimal crop area.
        area_max: maximal crop area.
  
      Returns:
        Cropped image and mask tensors.
      """
      begin, size, _ = tf.image.sample_distorted_bounding_box(
          tf.shape(image),
          tf.zeros([0, 0, 4], tf.float32),
          area_range=(area_min / 100, area_max / 100),
          min_object_covered=0,  # Don't enforce a minimum area.
          use_image_if_no_bounding_boxes=True,
      )
  
      # Process image:
      image_cropped = tf.slice(image, begin, size)
      image_cropped.set_shape([None, None, image.shape[-1]])
      if resize_size:
          image_cropped = tf.image.resize(
              image_cropped, resize_size, tf.image.ResizeMethod.BILINEAR
          )
  
      # Process mask:
      mask_cropped = tf.slice(mask, begin, size)
      mask_cropped.set_shape([None, None, mask.shape[-1]])
      if resize_size:
          mask_cropped = tf.image.resize(
              mask_cropped,
              resize_size,
              tf.image.ResizeMethod.NEAREST_NEIGHBOR,
          )
  
      return image_cropped, mask_cropped
  
imports: import collections
  import dataclasses
  import functools
  import itertools
  from typing import Any, Callable, Dict, Iterator, Optional, Sequence, Union
  from absl import logging
  from flax.training import common_utils
  import jax
  import jax.numpy
  import numpy
  import tensorflow
  import tensorflow_datasets
label_desc: Use image node_id 19 for calling a global function with example usage: inception_crop_with_mask(image, mask, resize_size, area_min, area_max) and returns: image_cropped,  mask_cropped