code: def __init__(
      self,
      num_tasks: int,
      method: Optional[str] = None,
  ):
      super().__init__()
      self._n_task, self._method = num_tasks, method
      if method is None or method == "naive":
          pass
      elif method == "softmax":
          self.w = torch.nn.Parameter(torch.ones(num_tasks))
      else:
          raise NotImplementedError(
              f"MTL method '{method}' not implemented"
          )
      self.registered = False
      self._slice: Optional[int] = None
      self._registered: Dict[str, int] = {}
  
imports: import copy
  import torch
  import torch.nn
  from torch import Tensor
  from typing import Any
  from typing import Dict
  from typing import List
  from typing import Tuple
  from typing import Union
  from typing import Callable
  from typing import Iterator
  from typing import Optional
  from functools import wraps
  from torch.nn import Module
  from torch.nn import ModuleList
  from cftool.types import tensor_dict_type
label_desc: Use image node_id 1 to create a new MTL object from inherited base classes: Module with example: obj = MTL(num_tasks, method)