code: def _wrap_unconditional_loss(loss_fn, index):
      """Wraps callable/unconditional loss, returning a serializable function."""
      # Extract original loss function from partial function
      fn = (
          loss_fn.args[0]
          if isinstance(loss_fn, functools.partial)
          else loss_fn
      )
      if isinstance(fn, def_function.Function):
          return fn
      else:
          return def_function.Function(
              fn, "loss_fn_{}".format(index), input_signature=[]
          )
  
imports: import functools
  import threading
  import weakref
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.keras import backend
  from tensorflow.python.keras.engine import base_layer_utils
  from tensorflow.python.keras.engine import input_spec
  from tensorflow.python.keras.mixed_precision import autocast_variable
  from tensorflow.python.keras.saving import saving_utils
  from tensorflow.python.keras.saving.saved_model import constants
  from tensorflow.python.keras.saving.saved_model import load
  from tensorflow.python.keras.saving.saved_model import serialized_attributes
  from tensorflow.python.keras.saving.saved_model import utils
  from tensorflow.python.keras.utils import tf_contextlib
  from tensorflow.python.keras.utils import tf_inspect
  from tensorflow.python.keras.utils import tf_utils
  from tensorflow.python.keras.utils import version_utils
  from tensorflow.python.keras.utils.generic_utils import LazyLoader
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.trackable import data_structures
  from tensorflow.python.util import nest
  from tensorflow.python.util import tf_decorator
label_desc: Use image node_id 18 for calling a global function with example usage: _wrap_unconditional_loss(loss_fn, index) and returns: fn, def_function