code: def test_that_accuracy_raises_errors_when_shapes_dont_match():
      predicted = torch.randn(5, 3)
      true = torch.tensor([0, 0, 0])
      accuracy_calculator = Accuracy(average=True, topk=(1,))
      with pytest.raises(ValueError):
          accuracy_calculator.update(predicted, true)
  
imports: import os
  from pathlib import Path
  import numpy
  import pytest
  import shutil
  import torch
  from hypothesis import given
  from torch_hypothesis import classification_logits_and_labels
  from baal.utils.metrics import Loss, Accuracy, Precision, ECE, ClassificationReport, PRAuC, ECE_PerCLs
label_desc: Use image node_id 4 for calling a global function with example usage: test_that_accuracy_raises_errors_when_shapes_dont_match() without return types