code: def _ragged_tensor_from_value(value):
      if isinstance(value, tf.compat.v1.ragged.RaggedTensorValue):
          return tf.RaggedTensor.from_row_splits(
              values=_ragged_tensor_from_value(value.values),
              row_splits=value.row_splits,
          )
      else:
          # Recursion base case, value here is a numpy array.
          return tf.constant(value)
  
imports: import copy
  import os
  import numpy
  from packaging import version
  import pyarrow
  import tensorflow
  from tensorflow_transform import analyzers
  from tensorflow_transform import impl_helper
  from tensorflow_transform import schema_inference
  from tensorflow_transform import test_case
  from tensorflow_transform.output_wrapper import TFTransformOutput
  from tensorflow_transform.tf_metadata import schema_utils
label_desc: Use image node_id 3 for calling a global function with example usage: _ragged_tensor_from_value(value) and returns: tf, tf