message: Extending documentation for tf.data.Dataset.map()
  Added an example for running a custom Python function (as discussed in https://github.com/tensorflow/tensorflow/issues/30653)
diff: @@ -1165,7 +1165,20 @@ class DatasetV2(tracking_base.Trackable, composite_tensor.CompositeTensor):
  some but not all Python code.
  2) Use `tf.py_function`, which allows you to write arbitrary Python code but
  - will generally result in worse performance than 1).
  + will generally result in worse performance than 1). For example:
  +
  + ```python
  + d = tf.data.Dataset.from_tensor_slices(['hello', 'world'])
  +
  + # transform a string tensor to upper case string using a Python function
  + def upper_case_fn(t: tf.Tensor) -> str:
  + return t.numpy().decode('utf-8').upper()
  +
  + result = d.map(lambda x: tf.py_function(func=upper_case_fn,
  + inp=[x], Tout=tf.string))
  + # list(result) == [<tf.Tensor: id=.., shape=(), dtype=string, numpy=b'HELLO'>,
  + # <tf.Tensor: id=.., shape=(), dtype=string, numpy=b'WORLD'>]
  + ```
  Args:
  map_func: A function mapping a nested structure of tensors (having shapes
  