code: def make_decoder(
      name: str, config: Dict[str, Any], *, is_1d: bool = False
  ) -> IDecoder:
      base = (Decoder1DMixin if is_1d else DecoderMixin).get(name)  # type: ignore
      return safe_execute(base, config)
  
imports: 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 print_warning
  from cftool.misc import shallow_copy_dict
  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 LABEL_KEY
  from ....constants import PREDICTIONS_KEY
  from ....misc.toolkit import interpolate
  from ....misc.toolkit import auto_num_layers
  from ....modules.blocks import ChannelPadding
label_desc: Use image node_id 1 for calling a global function with example usage: make_decoder(name, config) and returns: safe_execute