code: def test_base_output_handler_wrong_setup():
      with pytest.raises(
          TypeError,
          match="metric_names should be either a list or equal 'all'",
      ):
          DummyOutputHandler(
              "tag", metric_names="abc", output_transform=None
          )
  
      with pytest.raises(
          TypeError, match="output_transform should be a function"
      ):
          DummyOutputHandler(
              "tag", metric_names=None, output_transform="abc"
          )
  
      with pytest.raises(
          ValueError,
          match="Either metric_names, output_transform or state_attributes should be defined",
      ):
          DummyOutputHandler("tag", None, None)
  
      with pytest.raises(
          TypeError, match="global_step_transform should be a function"
      ):
          DummyOutputHandler(
              "tag", metric_names=["loss"], global_step_transform="abc"
          )
  
      with pytest.raises(
          TypeError,
          match=r"Argument optimizer should be torch.optim.Optimizer",
      ):
          DummyOptParamsHandler({}, "lr")
  
imports: from typing import Any, Union
  from unittest.mock import call, MagicMock
  import pytest
  import torch
  from ignite.contrib.handlers.base_logger import BaseLogger, BaseOptimizerParamsHandler, BaseOutputHandler, BaseWeightsHandler, BaseWeightsScalarHandler
  from ignite.engine import Engine, Events, EventsList, State
  from tests.ignite.contrib.handlers import MockFP16DeepSpeedZeroOptimizer
label_desc: Use image node_id 1 for calling a global function with example usage: test_base_output_handler_wrong_setup() without return types