code: def test_train_tiny():
      command = "textattack train --model distilbert-base-uncased --attack textfooler --dataset rotten_tomatoes --model-max-length 64  --num-epochs 1 --num-clean-epochs 0 --num-train-adv-examples 2"
  
      # Run command and validate outputs.
      result = run_command_and_get_result(command)
  
      assert result.stdout is not None
      assert result.stderr is not None
      assert result.returncode == 0
  
      stdout = result.stdout.decode().strip()
      print("stdout =>", stdout)
      stderr = result.stderr.decode().strip()
      print("stderr =>", stderr)
  
      train_args_json_path = re.findall(
          r"Wrote original training args to (\S+)\.", stderr
      )
      assert len(train_args_json_path) and os.path.exists(
          train_args_json_path[0]
      )
  
      train_acc = re.findall(r"Train accuracy: (\S+)", stderr)
      assert train_acc
      train_acc = float(train_acc[0][:-1])  # [:-1] removes percent sign
      assert train_acc > 60
  
      eval_acc = re.findall(r"Eval accuracy: (\S+)", stderr)
      assert eval_acc
      eval_acc = float(eval_acc[0][:-1])  # [:-1] removes percent sign
      assert train_acc > 60
  
imports: import os
  import re
  from helpers import run_command_and_get_result
label_desc: Use image node_id 1 for calling a global function with example usage: test_train_tiny() without return types