text: import numpy as np
  from cogdl import pipeline
  
  
  def test_dataset_stats():
      stats = pipeline("dataset-stats")
      outputs = stats("cora")
      outputs = outputs[0]
  
      assert len(outputs) == 6
      assert tuple(outputs) == ("cora", 2708, 10556, 1433, 7, 140)
  
  
  def test_dataset_visual():
      visual = pipeline("dataset-visual")
      outputs = visual("cora", seed=0, depth=3)
  
      assert len(outputs) == 72
  
  
  def test_oagbert():
      oagbert = pipeline("oagbert", model="oagbert-test", load_weights=False)
      outputs = oagbert("CogDL is developed by KEG, Tsinghua.")
  
      assert len(outputs) == 2
      assert tuple(outputs[0].shape) == (1, 14, 32)
      assert tuple(outputs[1].shape) == (1, 32)
  
  
  def test_gen_emb():
      generator = pipeline("generate-emb", model="prone")
  
      edge_index = np.array([[0, 1], [0, 2], [0, 3], [1, 2], [2, 3], [3, 4], [4, 5], [5, 6], [6, 7]])
      outputs = generator(edge_index)
      assert tuple(outputs.shape) == (8, 8)
  
      generator = pipeline(
          "generate-emb",
          model="mvgrl",
          no_test=True,
          num_features=8,
          hidden_size=10,
          sample_size=2,
          max_epoch=2,
          cpu=True,
      )
      outputs = generator(edge_index, x=np.random.randn(8, 8))
      assert tuple(outputs.shape) == (8, 10)
  
  
  # def test_recommendation():
  #     data = np.array([[0, 0], [0, 1], [0, 2], [1, 1], [1, 3], [1, 4], [2, 4], [2, 5], [2, 6]])
  #     rec = pipeline("recommendation", model="lightgcn", data=data, max_epoch=2, evaluate_interval=1000, cpu=True)
  #     ret = rec([0], topk=3)
  #     assert len(ret[0]) == 3
  
  
  if __name__ == "__main__":
      test_dataset_stats()
      test_dataset_visual()
      test_oagbert()
      test_gen_emb()
      # test_recommendation()
  