code: def test_mmd(mmd_params):
      n_features, n_instances = mmd_params
      xshape, yshape = (n_instances[0], n_features), (
          n_instances[1],
          n_features,
      )
      np.random.seed(0)
      x = torch.from_numpy(np.random.random(xshape).astype("float32"))
      y = torch.from_numpy(np.random.random(yshape).astype("float32"))
      mmd_xx = mmd2(x, x, kernel=GaussianRBF(sigma=torch.ones(1)))
      mmd_xy = mmd2(x, y, kernel=GaussianRBF(sigma=torch.ones(1)))
      assert mmd_xy > mmd_xx
  
file_path: alibi-detect/alibi_detect/utils/pytorch/tests/test_distance_pt.py
imports: import numpy
  from itertools import product
  import pytest
  import torch
  from alibi_detect.utils.pytorch import GaussianRBF, mmd2, mmd2_from_kernel_matrix, permed_lsdds
  from alibi_detect.utils.pytorch import squared_pairwise_distance, batch_compute_kernel_matrix
label_desc: Use image node_id 4 for calling a global function with example usage: test_mmd(mmd_params) without return types