code: def test_experiment():
      torch.manual_seed(1234)
      d = torchdrift.detectors.KernelMMDDriftDetector()
      dm_ref = TensorDataModule(torch.randn(500, 5))
      dm_x = TensorDataModule(torch.randn(500, 5))
      dm_y = TensorDataModule(torch.randn(500, 5) + 1)
      experiment = torchdrift.utils.DriftDetectionExperiment(
          d,
          torch.nn.Linear(5, 5),
      )
      experiment.post_training(
          torch.utils.data.DataLoader(dm_ref.ds, batch_size=100)
      )
      experiment.evaluate(dm_x, dm_y)
      experiment = torchdrift.utils.DriftDetectionExperiment(
          d, torch.nn.Linear(5, 5), ood_ratio=0.9, sample_size=10
      )
      experiment.post_training(
          torch.utils.data.DataLoader(dm_ref.ds, batch_size=100)
      )
      experiment.evaluate(dm_x, dm_y)
  
file_path: TorchDrift/test/test_utils.py
imports: import pytest
  import torchdrift
  import torch
  import torch.utils.data
label_desc: Use image node_id 2 for calling a global function with example usage: test_experiment() without return types