class_docstr: Base class for any torch model.
  
  :param device: Device the networks should be located on (cpu or cuda)
class_docstr_tok: ["Base","class","for","any","torch","model",".",":","param","device",":","Device","the","networks","should","be","located","on","(","cpu","or","cuda",")"]
docstr: Returns overall number of network parameters.
docstr_tok: ["Returns","overall","number","of","network","parameters","."]
code: def num_params(self) -> int:
      """Returns overall number of network parameters."""
      return sum(t.numel() for t in self.parameters())
  
file_path: maze/maze/core/agent/torch_model.py
imports: from abc import abstractmethod
  from typing import List, Dict
  import torch
label_desc: Use image node_id 2 for calling the TorchModel obj's underlying member method code with example usage: obj.num_params() and returns: sum