code: def test(self):
      world = dist.get_world_size()
      rank = dist.get_rank()
  
      group = dist.new_group(ranks=list(range(world)))
  
      rows = world * 7
      cols = 3
  
      full = torch.rand(rows, cols).cuda()
      dist.broadcast(full, src=0, group=group)
      part = PartitionedTensor(full, group=group)
  
      my_meta = PartitionedTensor.from_meta(
          part.to_meta(), part.local_data, group
      )
      assert torch.equal(full, my_meta.full())
  
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 unit.common import DistributedTest
label_desc: Use image node_id 1 for calling the TestPartitionedTensorMeta obj's underlying member method code with example usage: obj.test() without return types