class_docstr: A PyTorch Lightning module for training a model with sLCWA training loop.
class_docstr_tok: ["A","PyTorch","Lightning","module","for","training","a","model","with","sLCWA","training","loop","."]
code: def _step(self, batch, prefix: str):  # noqa: D102
      loss = SLCWATrainingLoop._process_batch_static(
          model=self.model,
          loss=self.loss,
          mode=self.mode,
          batch=batch,
          label_smoothing=self.label_smoothing,
          # TODO: sub-batching / slicing
          slice_size=None,
          start=None,
          stop=None,
      )
      self.log(f"{prefix}_loss", loss)
      return loss
  
imports: from abc import abstractmethod
  from typing import Optional
  import click
  import pytorch_lightning
  import torch
  import torch.utils.data
  from class_resolver import ClassResolver, HintOrType, OptionalKwargs
  from pykeen.datasets import dataset_resolver, get_dataset
  from pykeen.datasets.base import Dataset
  from pykeen.losses import Loss, loss_resolver
  from pykeen.models import Model, model_resolver
  from pykeen.models.cli import options
  from pykeen.optimizers import optimizer_resolver
  from pykeen.sampling import NegativeSampler
  from pykeen.training import LCWATrainingLoop, SLCWATrainingLoop
  from pykeen.triples.triples_factory import CoreTriplesFactory
  from pykeen.typing import InductiveMode, OneOrSequence
label_desc: Use image node_id 2 for calling the SLCWALitModule obj's underlying member method code with example usage: obj._step(batch, prefix) and returns: loss