docstr: Checks we can train a small MLP model.
docstr_tok: ["Checks","we","can","train","a","small","MLP","model","."]
code: def test_training(self):
      """Checks we can train a small MLP model."""
  
      num_processes = 2
  
      for config_key, expected_success in [
          ("invalid_config", False),
          ("config", True),
      ]:
          cmd = get_distributed_launch_cmd(
              num_processes=num_processes,
              trainer_path=f"{self.path}/../classy_train.py",
              config_path=self.config_files[config_key],
          )
          result = subprocess.run(cmd, shell=True)
          success = result.returncode == 0
          self.assertEqual(success, expected_success)
  
file_path: ClassyVision/test/trainer_distributed_trainer_test.py
imports: import copy
  import json
  import os
  import subprocess
  import tempfile
  import unittest
  from pathlib import Path
  import torch
  from test.generic.config_utils import get_distributed_launch_cmd, get_test_mlp_task_config
label_desc: Use image node_id 3 for calling the TestDistributedTrainer obj's underlying member method code with example usage: obj.test_training() without return types