code: def test_hawkesll_output_multivariate_ok():
      T, N, K = 9, 2, 3
  
      mu = nd.array([1.5, 2.0, 3.0])
      alpha = nd.array([0.2, 0.3, 0.4])
      beta = nd.array([2.0, 2.0, 2.0])
  
      lags = nd.array(
          [[6, 7, 8, 9, 3, 2, 5, 1, 7], [1, 2, 3, 4, 2, 1, 2, 1, 4]]
      )
      marks = nd.array(
          [[0, 1, 2, 1, 0, 2, 1, 0, 2], [1, 2, 0, 0, 0, 2, 2, 1, 0]]
      ).astype(np.int32)
  
      states = nd.zeros((N, K))
  
      valid_length = nd.array([7, 9])
      max_time = nd.ones((N,)) * 100.0
  
      A = nd.contrib.hawkesll(
          mu.tile((N, 1)),
          alpha,
          beta,
          states,
          lags,
          marks,
          valid_length,
          max_time,
      )
  
      assert np.allclose(
          np.array([-647.01240372, -646.28617272]), A[0].asnumpy()
      )
  
imports: import mxnet
  import numpy
  from mxnet import nd
label_desc: Use image node_id 2 for calling a global function with example usage: test_hawkesll_output_multivariate_ok() without return types