code: def testSerializedContainingRaggedFeatureWithMultiplePartitions(self):
      original = [
          # rt shape: [(batch), 2, None, None]
          example(
              features=features(
                  {
                      # rt = [[[[1]], [[2, 3], [4]]], [[], [[5, 6, 7]]]]
                      "rt_values": float_feature([1, 2, 3, 4, 5, 6, 7]),
                      "lengths_axis2": int64_feature([1, 2, 0, 1]),
                      "lengths_axis3": int64_feature([1, 2, 1, 3]),
                      "splits_axis3": int64_feature([0, 1, 3, 4, 7]),
                  }
              )
          ),
          example(
              features=features(
                  {
                      # rt = [[[[1, 2, 3], [4]], [[5], [6], [7, 8]]]]
                      "rt_values": float_feature(
                          [1, 2, 3, 4, 5, 6, 7, 8]
                      ),
                      "lengths_axis2": int64_feature([2, 3]),
                      "lengths_axis3": int64_feature([3, 1, 1, 1, 2]),
                      "splits_axis3": int64_feature([0, 3, 4, 5, 6, 8]),
                  }
              )
          ),
      ]
      serialized = [m.SerializeToString() for m in original]
  
      test_features = {
          "rt1": parsing_ops.RaggedFeature(
              value_key="rt_values",
              partitions=[
                  parsing_ops.RaggedFeature.UniformRowLength(2),
                  parsing_ops.RaggedFeature.RowLengths("lengths_axis2"),
                  parsing_ops.RaggedFeature.RowSplits("splits_axis3"),
              ],
              dtype=dtypes.float32,
              row_splits_dtype=dtypes.int64,
          ),
      }
  
      expected_rt = ragged_factory_ops.constant(
          [
              [[[[1]], [[2, 3], [4]]], [[], [[5, 6, 7]]]],
              [[[[1, 2, 3], [4]], [[5], [6], [7, 8]]]],
          ],
          dtype=dtypes.float32,
          row_splits_dtype=dtypes.int64,
      )
  
      expected_output = {
          "rt1": expected_rt,
      }
  
      self._test(
          ops.convert_to_tensor(serialized),
          test_features,
          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 22 for calling the ParseExampleDatasetTest obj's underlying member method code with example usage: obj.testSerializedContainingRaggedFeatureWithMultiplePartitions() without return types