code: def __torch_function__(cls, func, types, args=(), kwargs=None):
      args = [
          arg.value if isinstance(arg, KerasVariable) else arg
          for arg in args
      ]
      if kwargs is None:
          kwargs = {}
      kwargs = {
          key: value.value
          if isinstance(value, KerasVariable)
          else value
          for key, value in kwargs.items()
      }
      return func(*args, **kwargs)
  
imports: import contextlib
  import os
  import numpy
  import torch
  import tree
  from keras.backend.common import KerasVariable
  from keras.backend.common import global_state
  from keras.backend.common import standardize_dtype
  from keras.backend.common.dtypes import result_type
  from keras.backend.common.keras_tensor import KerasTensor
  from keras.backend.common.stateless_scope import StatelessScope
  from keras.backend.config import floatx
  from keras.utils.nest import pack_sequence_as
label_desc: Use image node_id 4 for calling the Variable obj's underlying member method code with example usage: obj.__torch_function__(cls, func, types, args, kwargs) and returns: func