code: def test_gmm_integration(backend):
      """Test GMM detector on moons dataset.
  
      Test GMM detector on a more complex 2d example. Test that the detector can be fitted
      on reference data and infer a threshold. Test that it differentiates between inliers and outliers.
      """
      gmm_detector = GMM(n_components=8, backend=backend)
      X_ref, _ = make_moons(
          1001, shuffle=True, noise=0.05, random_state=None
      )
      X_ref, x_inlier = X_ref[0:1000], X_ref[1000][None]
      gmm_detector.fit(X_ref)
      gmm_detector.infer_threshold(X_ref, 0.1)
      result = gmm_detector.predict(x_inlier)
      result = result["data"]["is_outlier"][0]
      assert not result
  
      x_outlier = np.array([[-1, 1.5]])
      result = gmm_detector.predict(x_outlier)
      result = result["data"]["is_outlier"][0]
      assert result
  
file_path: alibi-detect/alibi_detect/od/tests/test__gmm/test__gmm.py
imports: import pytest
  import numpy
  import torch
  from alibi_detect.od._gmm import GMM
  from alibi_detect.exceptions import NotFittedError
  from sklearn.datasets import make_moons
label_desc: Use image node_id 4 for calling a global function with example usage: test_gmm_integration(backend) without return types