code: def make_encoder(
      name: str, config: Dict[str, Any], *, is_1d: bool = False
  ) -> IEncoder:
      base = (Encoder1DMixin if is_1d else EncoderMixin).get(name)  # type: ignore
      return safe_execute(base, config)
  
imports: import torch
  import torch.nn
  from torch import Tensor
  from typing import Any
  from typing import Dict
  from typing import Type
  from typing import Optional
  from cftool.misc import safe_execute
  from cftool.misc import check_requires
  from cftool.misc import WithRegister
  from cftool.types import tensor_dict_type
  from ....schema import _forward
  from ....schema import TrainerState
  from ....constants import INPUT_KEY
  from ....constants import LATENT_KEY
  from ....misc.toolkit import eval_context
  from ....misc.toolkit import get_device
  from ....modules.blocks import ImgToPatches
label_desc: Use image node_id 1 for calling a global function with example usage: make_encoder(name, config) and returns: safe_execute