code: def _get_loss_closure_fallback_internal(
      mll: MarginalLogLikelihood,
      _: object,
      __: object,
      ___: NoneType,
      **ignore: Any,
  ) -> Callable[[], Tensor]:
      r"""Fallback loss closure with internally managed data."""
  
      def closure(**kwargs: Any) -> Tensor:
          model_output = mll.model(*mll.model.train_inputs)
          log_likelihood = mll(
              model_output, mll.model.train_targets, **kwargs
          )
          return -log_likelihood
  
      return closure
  
file_path: botorch/botorch/optim/closures/model_closures.py
imports: from __future__ import annotations
  from itertools import chain, repeat
  from typing import Any, Callable, Dict, Optional, Sequence, Tuple
  from botorch.optim.closures.core import ForwardBackwardClosure
  from botorch.utils.dispatcher import Dispatcher, type_bypassing_encoder
  from botorch.utils.types import NoneType
  from gpytorch.mlls import ExactMarginalLogLikelihood, MarginalLogLikelihood, SumMarginalLogLikelihood
  from torch import Tensor
  from torch.utils.data import DataLoader
label_desc: Use image node_id 5 for calling a global function with example usage: _get_loss_closure_fallback_internal(mll, _, __, ___) and returns: closure, unknown