class_docstr: Tests parameter flattening and shard metadata logic.
code: def _test_output(self, module: nn.Module):
      module = module.to(self.rank)
      ref_output = self._get_output(module)
      fsdp_module = FSDP(module)
      fsdp_output = self._get_output(fsdp_module)
      self.assertEqual(ref_output, fsdp_output)
  
imports: import sys
  import torch
  import torch.nn
  from torch import distributed
  from torch.distributed.fsdp import FullyShardedDataParallel
  from torch.distributed.fsdp._flat_param import FlatParamHandle, FlatParamShardMetadata, HandleShardingStrategy
  from torch.testing._internal.common_distributed import skip_if_lt_x_gpu
  from torch.testing._internal.common_fsdp import FSDPTest
  from torch.testing._internal.common_utils import run_tests, TEST_WITH_DEV_DBG_ASAN
label_desc: Use image node_id 20 for calling the TestFlattenParams obj's underlying member method code with example usage: obj._test_output(module) without return types