class_docstr: Tests parameter flattening and shard metadata logic.
code: def _get_shared_params_transformer(self, seed=0):
      module = self._get_transformer(seed=seed)
      # share the FFNs
      for enc_layer, dec_layer in zip(
          module.encoder.layers, module.decoder.layers
      ):
          dec_layer.linear1.weight = enc_layer.linear1.weight
          dec_layer.linear2.weight = enc_layer.linear2.weight
      return module
  
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 4 for calling the TestFlattenParams obj's underlying member method code with example usage: obj._get_shared_params_transformer(seed) and returns: module