code: def _eager_tensor_from_values(values):
      result = {}
      for key, value in values.items():
          if isinstance(value, tf.compat.v1.SparseTensorValue):
              result[key] = tf.sparse.SparseTensor.from_value(value)
          elif isinstance(value, tf.compat.v1.ragged.RaggedTensorValue):
              result[key] = _ragged_tensor_from_value(value)
          else:
              result[key] = tf.constant(value)
      return result
  
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 4 for calling a global function with example usage: _eager_tensor_from_values(values) and returns: result