code: def test_logaddexp():
      X = np.array([[0.0, 0.0], [0.0, 0.0]])
      out = np.zeros(X.shape[0])
      logsumexp_kernel.forall(out.size)(X, out)
      assert np.allclose(out, np.logaddexp.reduce(X, axis=1))
  
      X = np.array([[3.0, 1.0], [0.2, 0.7]])
      logsumexp_kernel.forall(out.size)(X, out)
      assert np.allclose(out, np.logaddexp.reduce(X, axis=1))
  
file_path: cuml/python/cuml/tests/test_kernel_density.py
imports: from cuml.testing.utils import as_type
  from sklearn.model_selection import GridSearchCV
  import pytest
  from hypothesis.extra.numpy import arrays
  from hypothesis import given, settings, assume, strategies
  from cuml.neighbors import KernelDensity, VALID_KERNELS, logsumexp_kernel
  from cuml.common.exceptions import NotFittedError
  from sklearn.metrics import pairwise_distances
  from sklearn.neighbors._ball_tree import kernel_norm
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 4 for calling a global function with example usage: test_logaddexp() without return types