code: def test_pad(shape, left, right, dim):
      expected = random_gamma_gaussian(shape, dim)
      padded = expected.event_pad(left=left, right=right)
      assert padded.batch_shape == expected.batch_shape
      assert padded.dim() == left + expected.dim() + right
      mid = slice(left, padded.dim() - right)
      assert_close(padded.info_vec[..., mid], expected.info_vec)
      assert_close(padded.precision[..., mid, mid], expected.precision)
  
imports: import math
  import pytest
  import torch
  from torch.nn.functional import pad
  import pyro.distributions
  from pyro.distributions.util import broadcast_shape
  from pyro.ops.gamma_gaussian import GammaGaussian, gamma_and_mvn_to_gamma_gaussian, gamma_gaussian_tensordot, matrix_and_mvn_to_gamma_gaussian
  from tests.common import assert_close
  from tests.ops.gamma_gaussian import assert_close_gamma_gaussian, random_gamma, random_gamma_gaussian
  from tests.ops.gaussian import random_mvn
label_desc: Use image node_id 4 for calling a global function with example usage: test_pad(shape, left, right, dim) without return types