code: def test_marginalize(batch_shape, left, right):
      dim = left + right
      g = random_gaussian(batch_shape, dim)
      assert_close(
          g.marginalize(left=left).event_logsumexp(),
          g.event_logsumexp(),
      )
      assert_close(
          g.marginalize(right=right).event_logsumexp(),
          g.event_logsumexp(),
      )
  
imports: import math
  from collections import OrderedDict
  import pytest
  import torch
  from torch.distributions import constraints, transform_to
  from torch.nn.functional import pad
  import pyro.distributions
  from pyro.distributions.util import broadcast_shape
  from pyro.ops.gaussian import AffineNormal, Gaussian, gaussian_tensordot, matrix_and_gaussian_to_gaussian, matrix_and_mvn_to_gaussian, mvn_to_gaussian, sequential_gaussian_filter_sample, sequential_gaussian_tensordot
  from tests.common import assert_close
  from tests.ops.gaussian import assert_close_gaussian, random_gaussian, random_mvn
label_desc: Use image node_id 9 for calling a global function with example usage: test_marginalize(batch_shape, left, right) without return types