code: def to_torch_dtype(dtype):
      standardized_dtype = TORCH_DTYPES.get(
          standardize_dtype(dtype), None
      )
      if standardized_dtype is None:
          raise ValueError(f"Unsupported dtype for PyTorch: {dtype}")
      return standardized_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 4 for calling a global function with example usage: to_torch_dtype(dtype) and returns: standardized_dtype