message: Update RaggedFeature doctest to be deterministic.
diff: @@ -145,17 +145,22 @@ class RaggedFeature(
  ... tf.io.RaggedFeature.RowSplits("s1")])
  ... }
  - >>> tf.io.parse_single_example(example_batch[0], features)
  - {'f1': <tf.Tensor: ..., numpy=array([3, 1, 4, 1, 5, 9])>,
  - 'f2': <tf.RaggedTensor [[3, 1], [4], [], [1, 5, 9]]>,
  - 'f3': <tf.RaggedTensor [[[3, 1], [4]], [[]], [[1, 5, 9]]]>}
  -
  - >>> tf.io.parse_example(example_batch, features)
  - {'f1': <tf.RaggedTensor [[3, 1, 4, 1, 5, 9], [2, 7, 1, 8, 2, 8, 1]]>,
  - 'f2': <tf.RaggedTensor [[[3, 1], [4], [], [1, 5, 9]],
  - [[2, 7, 1], [8], [2], [8, 1]]]>,
  - 'f3': <tf.RaggedTensor [[[[3, 1], [4]], [[]], [[1, 5, 9]]],
  - [[[2, 7, 1]], [], [[8], [2], [8, 1]]]]>}
  + >>> feature_dict = tf.io.parse_single_example(example_batch[0], features)
  + >>> for (name, val) in sorted(feature_dict.items()):
  + ... print('%s: %s' % (name, val))
  + f1: tf.Tensor([3 1 4 1 5 9], shape=(6,), dtype=int64)
  + f2: <tf.RaggedTensor [[3, 1], [4], [], [1, 5, 9]]>
  + f3: <tf.RaggedTensor [[[3, 1], [4]], [[]], [[1, 5, 9]]]>
  +
  + >>> feature_dict = tf.io.parse_example(example_batch, features)
  + >>> for (name, val) in sorted(feature_dict.items()):
  + ... print('%s: %s' % (name, val))
  + f1: <tf.RaggedTensor [[3, 1, 4, 1, 5, 9],
  + [2, 7, 1, 8, 2, 8, 1]]>
  + f2: <tf.RaggedTensor [[[3, 1], [4], [], [1, 5, 9]],
  + [[2, 7, 1], [8], [2], [8, 1]]]>
  + f3: <tf.RaggedTensor [[[[3, 1], [4]], [[]], [[1, 5, 9]]],
  + [[[2, 7, 1]], [], [[8], [2], [8, 1]]]]>
  Fields:
  dtype: Data type of the `RaggedTensor`. Must be one of:
  