code: def _norm_params(mask_size, offset=None):
      tf.assert_equal(
          tf.reduce_any(mask_size % 2 != 0),
          False,
          "mask_size should be divisible by 2",
      )
      if tf.rank(mask_size) == 0:
          mask_size = tf.stack([mask_size, mask_size])
      if offset is not None and tf.rank(offset) == 1:
          offset = tf.expand_dims(offset, 0)
      return mask_size, offset
  
imports: import tensorflow
  from tensorflow_addons.utils.types import TensorLike, Number
label_desc: Use image node_id 1 for calling a global function with example usage: _norm_params(mask_size, offset) and returns: mask_size,  offset