code: def testSerializedContainingRaggedFeatureWithNoPartitions(self):
      original = [
          example(
              features=features(
                  {
                      "rt_c": float_feature([3, 4, 5, 6, 7, 8]),
                      "rt_f_values": float_feature([0, 1, 2, 3, 4]),
                  }
              )
          ),
          example(
              features=features(
                  {
                      "rt_c": float_feature([]),  # empty float list
                  }
              )
          ),
          example(
              features=features(
                  {
                      "rt_d": feature(),  # feature with nothing in it
                  }
              )
          ),
          example(
              features=features(
                  {
                      "rt_c": float_feature([1, 2, -1]),
                      "rt_d": bytes_feature([b"hi"]),
                      "rt_f_values": float_feature([0, 1, 2]),
                  }
              )
          ),
      ]
  
      serialized = [m.SerializeToString() for m in original]
  
      expected_rt_c = ragged_factory_ops.constant_value(
          [[3.0, 4.0, 5.0, 6.0, 7.0, 8.0], [], [], [1.0, 2.0, -1.0]],
          row_splits_dtype=dtypes.int32,
      )
      expected_rt_d = ragged_factory_ops.constant_value(
          [[], [], [], [b"hi"]], row_splits_dtype=dtypes.int64
      )
      expected_rt_f = ragged_factory_ops.constant_value(
          [[0.0, 1.0, 2.0, 3.0, 4.0], [], [], [0.0, 1.0, 2.0]],
          row_splits_dtype=dtypes.int32,
      )
  
      expected_output = {
          "rt_c": expected_rt_c,
          "rt_d": expected_rt_d,
          "rt_f": expected_rt_f,
      }
  
      self._test(
          ops.convert_to_tensor(serialized),
          {
              "rt_c": parsing_ops.RaggedFeature(dtypes.float32),
              "rt_d": parsing_ops.RaggedFeature(
                  dtypes.string, row_splits_dtype=dtypes.int64
              ),
              "rt_f": parsing_ops.RaggedFeature(
                  dtypes.float32, value_key="rt_f_values"
              ),
          },
          expected_values=expected_output,
          create_iterator_twice=True,
      )
  
imports: import copy
  from absl.testing import parameterized
  import numpy
  from tensorflow.core.example import example_pb2
  from tensorflow.core.example import feature_pb2
  from tensorflow.python.data.experimental.ops import parsing_ops
  from tensorflow.python.data.kernel_tests import checkpoint_test_base
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.kernel_tests import tf_record_test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import options
  from tensorflow.python.eager import context
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops import parsing_ops
  from tensorflow.python.ops.ragged import ragged_factory_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 20 for calling the ParseExampleDatasetTest obj's underlying member method code with example usage: obj.testSerializedContainingRaggedFeatureWithNoPartitions() without return types