ValueError: Default process group has not been initialized in maisi diffusion train

Executing Cell 19--------------------------------------
INFO:notebook:Training the model...


INFO:training:Using cuda:0 of 1
INFO:training:[config] ckpt_folder -> ./temp_work_dir/./models.
INFO:training:[config] data_root -> ./temp_work_dir/./embeddings.
INFO:training:[config] data_list -> ./temp_work_dir/sim_datalist.json.
INFO:training:[config] lr -> 0.0001.
INFO:training:[config] num_epochs -> 2.
INFO:training:[config] num_train_timesteps -> 1000.
INFO:training:num_files_train: 2
Traceback (most recent call last):
  File "/usr/lib/python3.10/runpy.py", line 196, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "/usr/lib/python3.10/runpy.py", line 86, in _run_code
    exec(code, run_globals)
  File "/opt/toolkit/tutorials/monai/generation/maisi/scripts/diff_model_train.py", line 434, in <module>
    diff_model_train(args.env_config, args.model_config, args.model_def)
  File "/opt/toolkit/tutorials/monai/generation/maisi/scripts/diff_model_train.py", line 355, in diff_model_train
    data=train_files, shuffle=True, num_partitions=dist.get_world_size(), even_divisible=True
  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/distributed_c10d.py", line 2002, in get_world_size
    return _get_group_size(group)
  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/distributed_c10d.py", line 987, in _get_group_size
    default_pg = _get_default_group()
  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/distributed_c10d.py", line 1151, in _get_default_group
    raise ValueError(
ValueError: Default process group has not been initialized, please make sure to call init_process_group.
E0930 01:33:38.255000 140127265727104 torch/distributed/elastic/multiprocessing/api.py:863] failed (exitcode: 1) local_rank: 0 (pid: 383) of binary: /usr/bin/python
Traceback (most recent call last):
  File "/usr/local/bin/torchrun", line 33, in <module>
    sys.exit(load_entry_point('torch==2.5.0a0+872d972e41.nv24.8.1', 'console_scripts', 'torchrun')())
  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 355, in wrapper
    return f(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/run.py", line 919, in main
    run(args)
  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/run.py", line 910, in run
    elastic_launch(
  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/launcher/api.py", line 138, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/usr/local/lib/python3.10/dist-packages/torch/distributed/launcher/api.py", line 269, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError: 
============================================================
scripts.diff_model_train FAILED
------------------------------------------------------------
Failures:
  <NO_OTHER_FAILURES>
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2024-09-30_01:33:38
  host      : ipp2-0112.ipp2u1.colossus.nvidia.com
  rank      : 0 (local_rank: 0)
  exitcode  : 1 (pid: 383)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================

Beginne bei scripts/diff_model_train.py in Zeile 355, wo dist.get_world_size() aufgerufen wird, und untersuche, wie der Trainingsprozess aus dem Notebook und über torchrun gestartet wird. Reproduziere Cell 19 mit der gezeigten Konfiguration und verfolge die Einrichtung der Prozessgruppe; abgeschlossen ist die Aufgabe, wenn der Maisi-Diffusion-Trainingslauf ohne den gemeldeten Initialisierungsfehler fortgesetzt wird.