code: def test_1d_eval_is_not_stochastic(a_model_with_dropout):
      dummy_input = torch.randn(8, 10)
      test_module = a_model_with_dropout
      test_module.eval()
      # NOTE: This is quite a stochastic test...
      torch.manual_seed(2019)
      with torch.no_grad():
          assert all(
              (
                  test_module(dummy_input) == test_module(dummy_input)
              ).all()
              for _ in range(10)
          )
  
file_path: baal/tests/bayesian/consistent_dropout_test.py
imports: import warnings
  from copy import deepcopy
  import pytest
  import torch
  import baal.bayesian.consistent_dropout
label_desc: Use image node_id 2 for calling a global function with example usage: test_1d_eval_is_not_stochastic(a_model_with_dropout) without return types