code: def test__xla_dist_model_run_parallel_n_threads_without_sync():
      # tests issue : https://github.com/pytorch/ignite/issues/1096
      import torch_xla.core.xla_model as xm
      from joblib import delayed, Parallel
  
      devices = xm.get_xla_supported_devices()
      folds = 1
      d = 0
      if len(devices) > 5:
          folds = 5
          d = 1
      Parallel(n_jobs=folds, backend="threading")(
          delayed(main_fold)(i + d) for i in range(folds)
      )
  
file_path: ignite/tests/ignite/distributed/comp_models/test_xla.py
imports: import os
  import pytest
  import torch
  from ignite.distributed.comp_models import has_xla_support
label_desc: Use image node_id 11 for calling a global function with example usage: test__xla_dist_model_run_parallel_n_threads_without_sync() without return types