code: def test_flat_exact_1_1(e, a):
      exists_logits = torch.tensor([e])
      assign_logits = torch.tensor([[a]])
      expected = MarginalAssignment(exists_logits, assign_logits, None)
      actual = MarginalAssignment(exists_logits, assign_logits, 10)
      assert_equal(expected.exists_dist.probs, actual.exists_dist.probs)
      assert_equal(expected.assign_dist.probs, actual.assign_dist.probs)
  
imports: import logging
  import pytest
  import torch
  from torch.autograd import grad
  import pyro
  import pyro.distributions
  from pyro.contrib.tracking.assignment import MarginalAssignment, MarginalAssignmentPersistent, MarginalAssignmentSparse
  from tests.common import assert_equal
label_desc: Use image node_id 9 for calling a global function with example usage: test_flat_exact_1_1(e, a) without return types