code: def test_gather_all_same_dim1_n(self):
      ts = torch.full(
          (10 + DistributedHelper.rank, 5),
          DistributedHelper.rank,
          dtype=torch.long,
      )
      device = DistributedHelper.make_device()
  
      ts = ts.to(device)
  
      tensor_list = DistributedHelper.gather_all(ts)
      self.assertEqual(DistributedHelper.world_size, len(tensor_list))
  
      for t in tensor_list:
          self.assertEqual(device, t.device)
  
      for rank in range(DistributedHelper.world_size):
          expect = torch.full(
              (10 + rank, 5), rank, dtype=torch.long
          ).to(device)
          self.assertTrue(torch.equal(tensor_list[rank], expect))
  
imports: import os
  import random
  import shutil
  import tempfile
  import time
  import unittest
  import numpy
  import torch
  import torch.distributed
  from torch.nn import Module
  from torch.nn.parallel import DistributedDataParallel
  from avalanche.benchmarks.scenarios.deprecated.generators import dataset_benchmark
  from avalanche.benchmarks.utils.classification_dataset import _make_taskaware_tensor_classification_dataset
  from avalanche.distributed import DistributedHelper
  from avalanche.distributed.distributed_helper import RollingSeedContext, BroadcastSeedContext
  from avalanche.models import SimpleMLP, as_multitask
  from avalanche.models.utils import avalanche_model_adaptation
  from avalanche.training.determinism.rng_manager import RNGManager
  from tests.distributed.distributed_test_utils import check_skip_distributed_slow_test, check_skip_distributed_test, suppress_dst_tests_output, common_dst_tests_setup
label_desc: Use image node_id 11 for calling the DistributedHelperTests obj's underlying member method code with example usage: obj.test_gather_all_same_dim1_n() without return types