code: def stack_nested(sequence_elements):
      """Recursively stack the tensors from the same dict field."""
      if isinstance(sequence_elements[0], dict):
          return {
              # Stack along the first dimension
              k: stack_nested(sub_sequence)
              for k, sub_sequence in utils.zip_dict(*sequence_elements)
          }
      # Note: As each field can be a nested ragged list, we don't check here
      # that all elements from the list have matching dtype/shape.
      # Checking is done in `example_serializer` when elements
      # are converted to numpy array and stacked together.
      return list(sequence_elements)
  
imports: from __future__ import annotations
  from typing import List, Optional, Union
  import numpy
  from tensorflow_datasets.core import utils
  from tensorflow_datasets.core.features import feature
  from tensorflow_datasets.core.features import features_dict
  from tensorflow_datasets.core.features import tensor_feature
  from tensorflow_datasets.core.features import top_level_feature
  from tensorflow_datasets.core.proto import feature_pb2
  from tensorflow_datasets.core.utils import py_utils
  from tensorflow_datasets.core.utils import tree_utils
  from tensorflow_datasets.core.utils import type_utils
label_desc: Use image node_id 2 for calling a global function with example usage: stack_nested(sequence_elements) and returns: list, unknown