class_docstr: Crop a random sized region from the image.
code: def __call__(self, features):
      h, w = get_hw(features, dtype=tf.int32)
      wcrop = tf.random.uniform(
          [],
          self.min_size,
          tf.minimum(w, self.max_size),
          dtype=tf.int32,
      )
      hcrop = tf.random.uniform(
          [],
          self.min_size,
          tf.minimum(h, self.max_size),
          dtype=tf.int32,
      )
  
      i = tf.random.uniform([], 0, h - hcrop + 1, dtype=tf.int32)
      j = tf.random.uniform([], 0, w - wcrop + 1, dtype=tf.int32)
      region = (i, j, hcrop, wcrop)
  
      return crop(features, region)
  
imports: from typing import Any, Dict
  import tensorflow
label_desc: Use image node_id 2 for calling the RandomSizeCrop obj's underlying member method code with example usage: obj.__call__(features) and returns: crop