code: def test_evaluation_loop_when_batch_idx_argument_is_not_given(tmpdir):
      class TestModel(BoringModel):
          def __init__(self) -> None:
              super().__init__()
              self.validation_step_called = False
              self.test_step_called = False
  
          def validation_step(self, batch):
              self.validation_step_called = True
              return {"x": self.step(batch)}
  
          def test_step(self, batch):
              self.test_step_called = True
              return {"y": self.step(batch)}
  
      trainer = Trainer(
          default_root_dir=tmpdir,
          fast_dev_run=1,
          logger=False,
          enable_checkpointing=False,
          enable_progress_bar=False,
      )
      model = TestModel()
  
      trainer.validate(model)
      assert model.validation_step_called
  
      trainer.test(model)
      assert model.test_step_called
  
imports: from unittest import mock
  from unittest.mock import Mock, call
  import pytest
  import torch
  from lightning.fabric.accelerators.cuda import _clear_cuda_memory
  from lightning.pytorch import LightningModule, Trainer
  from lightning.pytorch.demos.boring_classes import BoringModel, RandomDataset
  from lightning.pytorch.utilities import CombinedLoader
  from torch.utils.data.dataloader import DataLoader
  from torch.utils.data.sampler import BatchSampler, RandomSampler
  from tests_pytorch.helpers.runif import RunIf
label_desc: Use image node_id 10 for calling a global function with example usage: test_evaluation_loop_when_batch_idx_argument_is_not_given(tmpdir) and returns: dict, dict