code: def training_loss_closure(
      model: BayesianModel, data: Data, **closure_kwargs: Any
  ) -> Callable[[], tf.Tensor]:
      if isinstance(model, ExternalDataTrainingLossMixin):
          return model.training_loss_closure(data, **closure_kwargs)  # type: ignore[no-any-return]
      else:
          _assert_equal_data(model.data, data)
          return model.training_loss_closure(**closure_kwargs)
  
file_path: GPflow/gpflow/models/util.py
imports: from typing import Any, Callable, Sequence, Union
  import numpy
  import tensorflow
  from check_shapes import check_shapes
  from ..base import AnyNDArray
  from ..config import default_float
  from ..inducing_variables import InducingPoints, InducingVariables
  from .model import BayesianModel
  from .training_mixins import Data, ExternalDataTrainingLossMixin
label_desc: Use image node_id 3 for calling a global function with example usage: training_loss_closure(model, data) and returns: model, model