class_docstr: The serializer that utilizes :func:`torch.save` and :func:`torch.load` to save and load data.
  
  This serializer should work in most scenarios, including cases when strategies have some tensors in their states (e.g., DRL).
  The downside is that it relies on torch to be installed.
  
  Parameters
  ----------
  map_location
      The ``map_location`` argument to be passed to :func:`torch.load`.
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code: def save(self, checkpoint: Any, path: Path):
      import torch
  
      torch.save(checkpoint, str(path) + self.suffix)
  
file_path: nni/nni/nas/utils/serializer.py
imports: from __future__ import annotations
  import logging
  from pathlib import Path
  from typing import Any, ClassVar, Type, cast
label_desc: Use image node_id 2 for calling the TorchSerializer obj's underlying member method code with example usage: obj.save(checkpoint, path) without return types