code: def test_error_on_multidim_tensors(metric_class=RelativeSquaredError):
      """Test that error is raised if a larger than 2D tensor is given as input."""
      metric = metric_class()
      with pytest.raises(
          ValueError,
          match=r"Expected both prediction and target to be 1D or 2D tensors, but received tensors with dimension .",
      ):
          metric(torch.randn(10, 20, 5), torch.randn(10, 20, 5))
  
imports: from functools import partial
  import numpy
  import pytest
  import torch
  from torchmetrics.functional import relative_squared_error
  from torchmetrics.regression import RelativeSquaredError
  from torchmetrics.utilities.imports import _TORCH_GREATER_EQUAL_2_1
  from unittests import BATCH_SIZE, NUM_BATCHES, _Input
  from unittests.helpers import seed_all
  from unittests.helpers.testers import MetricTester
label_desc: Use image node_id 5 for calling a global function with example usage: test_error_on_multidim_tensors(metric_class) without return types