code: def test_backward_count_with_grad_accumulation(torch_backward):
      """Test that backward is called the correct number of times when accumulating gradients."""
      model = BoringModel()
      trainer = Trainer(
          max_epochs=1, limit_train_batches=6, accumulate_grad_batches=2
      )
      trainer.fit(model)
      assert torch_backward.call_count == 6
  
      torch_backward.reset_mock()
  
      trainer = Trainer(max_steps=6, accumulate_grad_batches=2)
      trainer.fit(model)
      assert torch_backward.call_count == 12
  
file_path: pytorch-lightning/tests/tests_pytorch/trainer/optimization/test_backward_calls.py
imports: from unittest.mock import patch
  import pytest
  import torch
  from lightning.pytorch import Trainer
  from lightning.pytorch.demos.boring_classes import BoringModel
label_desc: Use image node_id 2 for calling a global function with example usage: test_backward_count_with_grad_accumulation(torch_backward) without return types