code: def test_compute():
      a = np.random.randn(4)
      b = np.random.randn(4)
      c = np.random.randn(4)
      d = np.random.randn(4)
      ground_truth = np.random.randn(4)
  
      m = CanberraMetric()
  
      canberra = DistanceMetric.get_metric("canberra")
  
      m.update((torch.from_numpy(a), torch.from_numpy(ground_truth)))
      np_sum = (
          np.abs(ground_truth - a) / (np.abs(a) + np.abs(ground_truth))
      ).sum()
      assert m.compute() == pytest.approx(np_sum)
      assert canberra.pairwise([a, ground_truth])[0][
          1
      ] == pytest.approx(np_sum)
  
      m.update((torch.from_numpy(b), torch.from_numpy(ground_truth)))
      np_sum += (
          (np.abs(ground_truth - b))
          / (np.abs(b) + np.abs(ground_truth))
      ).sum()
      assert m.compute() == pytest.approx(np_sum)
      v1 = np.hstack([a, b])
      v2 = np.hstack([ground_truth, ground_truth])
      assert canberra.pairwise([v1, v2])[0][1] == pytest.approx(np_sum)
  
      m.update((torch.from_numpy(c), torch.from_numpy(ground_truth)))
      np_sum += (
          (np.abs(ground_truth - c))
          / (np.abs(c) + np.abs(ground_truth))
      ).sum()
      assert m.compute() == pytest.approx(np_sum)
      v1 = np.hstack([v1, c])
      v2 = np.hstack([v2, ground_truth])
      assert canberra.pairwise([v1, v2])[0][1] == pytest.approx(np_sum)
  
      m.update((torch.from_numpy(d), torch.from_numpy(ground_truth)))
      np_sum += (
          np.abs(ground_truth - d) / (np.abs(d) + np.abs(ground_truth))
      ).sum()
      assert m.compute() == pytest.approx(np_sum)
      v1 = np.hstack([v1, d])
      v2 = np.hstack([v2, ground_truth])
      assert canberra.pairwise([v1, v2])[0][1] == pytest.approx(np_sum)
  
imports: import os
  import numpy
  import pytest
  import torch
  from sklearn.metrics import DistanceMetric
  import ignite.distributed
  from ignite.contrib.metrics.regression import CanberraMetric
  from ignite.engine import Engine
label_desc: Use image node_id 2 for calling a global function with example usage: test_compute() without return types