code: def train_flags(self, mu):
      return [
          "--memory-efficient-fp16",
          "--update-freq",
          "1",
          "--seed",
          "1",
          "--log-format",
          "json",
          "--max-update",
          str(mu),
          "--tokens-per-sample",
          "20",
          "--batch-size",
          "2",
          "--share-decoder-input-output-embed",
          "--optimizer",
          "adam",
          "--max-valid-steps",
          "1",
          "--pad-to-fixed-length",
          "--sample-break-mode",
          "none",
      ]
  
imports: import contextlib
  import json
  import logging
  import os
  import tempfile
  import unittest
  from io import StringIO
  import torch
  from fairseq import options
  from fairseq_cli import train
  from tests.utils import create_dummy_data, generate_main, preprocess_lm_data, preprocess_translation_data, train_language_model, train_translation_model
label_desc: Use image node_id 3 for calling the TestMultiGPU obj's underlying member method code with example usage: obj.train_flags(mu) and returns: list