code: def find_class(
      self, module: str, name: str
  ) -> t.Callable[[bytes], t.Any]:
      if module == "torch.storage" and name == "_load_from_bytes":
          return _safe_torch_tensor_loads
      else:
          return super().find_class(module, name)
  
file_path: BentoML/src/bentoml/_internal/utils/pickle.py
imports: from __future__ import annotations
  import io
  import pickle
  import typing
label_desc: Use image node_id 1 for calling the FixTorchUnpickler obj's underlying member method code with example usage: obj.find_class(module, name) and returns: _safe_torch_tensor_loads, super