class_docstr: A training loop that uses the stochastic local closed world assumption training approach.
  
  [ruffinelli2020]_ call the sLCWA ``NegSamp`` in their work.
class_docstr_tok: ["A","training","loop","that","uses","the","stochastic","local","closed","world","assumption","training","approach",".","[","ruffinelli2020","]","_","call","the","sLCWA","``","NegSamp","``","in","their","work","."]
code: def _get_batch_size(batch: SLCWABatch) -> int:  # noqa: D102
      return batch[0].shape[0]
  
imports: import logging
  from typing import Optional
  import torch.utils.data
  from class_resolver import HintOrType, OptionalKwargs
  from torch.utils.data import DataLoader
  from .training_loop import TrainingLoop
  from ..losses import Loss
  from ..models.base import Model
  from ..sampling import NegativeSampler
  from ..triples import CoreTriplesFactory
  from ..triples.instances import SLCWABatch, SLCWASampleType
  from ..typing import InductiveMode
label_desc: Use image node_id 3 for calling the SLCWATrainingLoop obj's underlying member method code with example usage: obj._get_batch_size(batch) and returns: batch