code: def test_epoch_metric_wrong_setup_or_input():
      # Wrong compute function
      with pytest.raises(
          TypeError, match=r"Argument compute_fn should be callable."
      ):
          EpochMetric(12345)
  
      def compute_fn(y_preds, y_targets):
          return 0.0
  
      em = EpochMetric(compute_fn)
  
      # Wrong input dims
      with pytest.raises(
          ValueError, match=r"Predictions should be of shape"
      ):
          output = (torch.tensor(0), torch.tensor(0))
          em.update(output)
  
      # Wrong input dims
      with pytest.raises(
          ValueError, match=r"Targets should be of shape"
      ):
          output = (torch.rand(4, 3), torch.rand(4, 3, 1))
          em.update(output)
  
      # Wrong input dims
      with pytest.raises(
          ValueError, match=r"Predictions should be of shape"
      ):
          output = (torch.rand(4, 3, 1), torch.rand(4, 3))
          em.update(output)
  
      em.reset()
      output1 = (
          torch.rand(4, 3),
          torch.randint(0, 2, size=(4, 3), dtype=torch.long),
      )
      em.update(output1)
  
      with pytest.raises(
          ValueError,
          match=r"Incoherent types between input y_pred and stored predictions",
      ):
          output2 = (
              torch.randint(0, 5, size=(4, 3)),
              torch.randint(0, 2, size=(4, 3)),
          )
          em.update(output2)
  
      with pytest.raises(
          ValueError,
          match=r"Incoherent types between input y and stored targets",
      ):
          output2 = (
              torch.rand(4, 3),
              torch.randint(0, 2, size=(4, 3)).to(torch.int32),
          )
          em.update(output2)
  
      with pytest.raises(
          NotComputableError,
          match="EpochMetric must have at least one example before it can be computed",
      ):
          em = EpochMetric(compute_fn)
          em.compute()
  
file_path: ignite/tests/ignite/metrics/test_epoch_metric.py
imports: import pytest
  import torch
  import ignite.distributed
  from ignite.engine import Engine
  from ignite.metrics import EpochMetric
  from ignite.metrics.epoch_metric import EpochMetricWarning, NotComputableError
label_desc: Use image node_id 1 for calling a global function with example usage: test_epoch_metric_wrong_setup_or_input() and returns: int