code: def test_random_weights_seed():
      # TODO: why do we need min_prediction and max_prediction?
      shared_args = "--random_weights --quiet --min_prediction -50 --max_prediction 50"
  
      a = Workspace(f"--random_seed 1 {shared_args}")
      b = Workspace(f"--random_seed 2 {shared_args}")
  
      dummy_ex_str = " | foo=bar"
      assert a.predict(dummy_ex_str) != b.predict(dummy_ex_str)
  
imports: import os
  from pathlib import Path
  import vowpalwabbit
  from vowpalwabbit import Workspace
  import pytest
  import warnings
  import filecmp
label_desc: Use image node_id 49 for calling a global function with example usage: test_random_weights_seed() without return types