code: def __init__(
      self,
      m: nn.Module,
      device: torch.device,
      *,
      use_amp: bool = False,
      use_half: bool = False,
  ):
      if use_amp and use_half:
          raise ValueError(
              "`use_amp` & `use_half` should not be True simultaneously"
          )
      self.m = m.eval().requires_grad_(False)
      self.device = device
      self.use_amp = use_amp
      self.use_half = use_half
  
imports: import torch
  import torch.nn
  from typing import Any
  from typing import Type
  from typing import TypeVar
  from typing import Optional
  from cftool.data_structures import ILoadableItem
  from cftool.data_structures import ILoadablePool
  from cftool.types import tensor_dict_type
  from torch.cuda.amp.autocast_mode import autocast
  from .zoo import TPipeline
  from ..misc.toolkit import is_cpu
  from ..misc.toolkit import get_device
  from ..misc.toolkit import empty_cuda_cache
label_desc: Use image node_id 1 to create a new APIMixin object  with example: obj = APIMixin(m, device)