code: def testRaggedMapOnStructure_RaggedOutputs(self):
      batman = ragged_factory_ops.constant([[1, 2, 3], [4], [5, 6, 7]])
      # [[10, 20, 30], [40], [50, 60, 70]]
      robin = ragged_functional_ops.map_flat_values(
          mo.multiply, batman, 10
      )
  
      features = {"batman": batman, "robin": robin}
  
      def _increment(f):
          return {
              "batman": f["batman"] + 1,
              "robin": f["robin"] + 1,
          }
  
      output = ragged_map_ops.map_fn(
          fn=_increment,
          elems=features,
          infer_shape=False,
          dtype={
              "batman": ragged_tensor.RaggedTensorType(
                  dtype=dtypes.int32, ragged_rank=1
              ),
              "robin": ragged_tensor.RaggedTensorType(
                  dtype=dtypes.int32, ragged_rank=1
              ),
          },
      )
  
      self.assertAllEqual(output["batman"], [[2, 3, 4], [5], [6, 7, 8]])
      self.assertAllEqual(
          output["robin"], [[11, 21, 31], [41], [51, 61, 71]]
      )
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import map_fn
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import string_ops
  from tensorflow.python.ops.ragged import ragged_factory_ops
  from tensorflow.python.ops.ragged import ragged_functional_ops
  from tensorflow.python.ops.ragged import ragged_map_ops
  from tensorflow.python.ops.ragged import ragged_math_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.platform import googletest
label_desc: Use image node_id 3 for calling the RaggedMapOpTest obj's underlying member method code with example usage: obj.testRaggedMapOnStructure_RaggedOutputs() and returns: dict