code: def test(self):
      world = dist.get_world_size()
  
      group = dist.new_group(ranks=list(range(world)))
  
      rows = world * 4 - 1
      cols = world + 1
  
      full = torch.rand(rows, cols).to(get_accelerator().device_name())
      dist.broadcast(full, src=0, group=group)
      part = PartitionedTensor(full, group=group)
  
      assert len(part.local_size()) == 1
  
      reconstructed = part.full()
      assert torch.equal(full, reconstructed)
  
imports: import pytest
  import torch
  import deepspeed.comm
  from deepspeed.runtime.utils import partition_uniform
  from deepspeed.runtime.utils import partition_balanced
  from deepspeed.runtime.utils import prefix_sum_inc
  from deepspeed.runtime.utils import PartitionedTensor
  from deepspeed.accelerator import get_accelerator
  from unit.common import DistributedTest
label_desc: Use image node_id 1 for calling the TestPartitionedTensorUnEven obj's underlying member method code with example usage: obj.test() without return types