code: def cast(x, dtype):
      dtype = to_torch_dtype(dtype)
      if isinstance(x, KerasVariable):
          x = x.value
      if is_tensor(x):
          if x.dtype == dtype:
              return x
          else:
              return x.to(dtype)
      return convert_to_tensor(x, dtype)
  
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 9 for calling a global function with example usage: cast(x, dtype) and returns: convert_to_tensor, x, x