code: def _build_ragged_tensors(
      serialized_shape,
      ragged_values,
      ragged_row_splits,
      ragged_inner_splits=None,
  ):
      """Builds RaggedTensors from the outputs of a parse op."""
      if ragged_inner_splits is not None:
          ragged_values = [
              ragged_tensor.RaggedTensor.from_row_splits(
                  val, split, validate=False
              )
              for (val, split) in zip(
                  ragged_values, ragged_inner_splits
              )
          ]
      if serialized_shape.ndims == 0:
          return ragged_values
      else:
          return [
              ragged_tensor.RaggedTensor.from_row_splits(
                  val, split, validate=False
              )
              for (val, split) in zip(ragged_values, ragged_row_splits)
          ]
  
imports: import collections
  import re
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import check_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import sparse_ops
  from tensorflow.python.ops.ragged import ragged_math_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 4 for calling a global function with example usage: _build_ragged_tensors(serialized_shape, ragged_values, ragged_row_splits, ragged_inner_splits) and returns: ragged_values, unknown