docstr: Test that we can save multiple world_logs from train model on multiple tasks.
docstr_tok: ["Test","that","we","can","save","multiple","world_logs","from","train","model","on","multiple","tasks","."]
code: def test_save_multiple_world_logs(self):
      """
      Test that we can save multiple world_logs from train model on multiple tasks.
      """
      with testing_utils.tempdir() as tmpdir:
          log_report = os.path.join(tmpdir, "world_logs.jsonl")
          multitask = (
              "integration_tests,integration_tests:ReverseTeacher"
          )
          valid, test = testing_utils.train_model(
              {
                  "task": multitask,
                  "validation_max_exs": 10,
                  "model": "repeat_label",
                  "short_final_eval": True,
                  "num_epochs": 1.0,
                  "world_logs": log_report,
              }
          )
  
          for task in multitask.split(","):
              task_log_report = get_task_world_logs(
                  task, log_report, is_multitask=True
              )
              with PathManager.open(task_log_report) as f:
                  json_lines = f.readlines()
              assert len(json_lines) == 5
  
imports: import os
  import unittest
  import json
  import parlai.utils.logging
  import parlai.utils.testing
  from parlai.utils.io import PathManager
  from parlai.core.metrics import AverageMetric
  from parlai.core.worlds import create_task
  from parlai.core.opt import Opt
  from parlai.core.params import ParlaiParser
  from parlai.core.agents import register_agent, Agent
  from parlai.scripts.eval_model import get_task_world_logs
label_desc: Use image node_id 10 for calling the TestTrainModel obj's underlying member method code with example usage: obj.test_save_multiple_world_logs() without return types