code: def on_train_batch_end(
      self, trainer, pl_module, outputs, batch, batch_idx
  ):
      context = (
          pytest.raises(TrainingSpikeException)
          if batch_idx == 4 and self.should_raise
          else contextlib.nullcontext()
      )
  
      with context:
          if batch_idx == 4:
              print(outputs)
          super().on_train_batch_end(
              trainer, pl_module, outputs, batch, batch_idx
          )
  
file_path: pytorch-lightning/tests/tests_pytorch/callbacks/test_spike.py
imports: import contextlib
  import sys
  import pytest
  import torch
  from lightning.fabric.utilities.spike import _TORCHMETRICS_GREATER_EQUAL_1_0_0, TrainingSpikeException
  from lightning.pytorch import LightningModule, Trainer
  from lightning.pytorch.callbacks.spike import SpikeDetection
label_desc: Use image node_id 1 for calling the MyTrainerSpikeDetection obj's underlying member method code with example usage: obj.on_train_batch_end(trainer, pl_module, outputs, batch, batch_idx) without return types