class_docstr: DTensorExtension is the TensorFlattener extension needed for 2D FSDP + TP.
  
  This is the implementation for FSDPExtensions defined in
  https://github.com/pytorch/pytorch/blob/main/torch/distributed/fsdp/_fsdp_extensions.py
class_docstr_tok: ["DTensorExtension","is","the","TensorFlattener","extension","needed","for","2D","FSDP","+","TP",".","This","is","the","implementation","for","FSDPExtensions","defined","in","https",":","\/\/github.com\/pytorch\/pytorch\/blob\/main\/torch\/distributed\/fsdp\/_fsdp_extensions.py"]
code: def post_unflatten_transform(
      self, tensor: torch.Tensor, param_extension: Any
  ) -> torch.Tensor:
      stream = (
          self.compute_stream or self.device_handle.current_stream()
      )
      with self.device_handle.stream(stream):
          # runtime we put the unflattened tensor call on the compute stream since
          # the unflattened tensor might contain computations in fwd/bwd where we
          # need to sync properly.
          # TODO: this is a short term fix and we should make the get_unflat_views
          # directly happen in the compute stream.
          result = _unflatten_tensor(
              tensor,
              param_extension,
              device_handle=self.device_handle,
              compute_stream=self.compute_stream,
          )
          _set_fsdp_flattened(result)
          return result
  
imports: import copy
  from typing import Any, cast, List, Optional, Tuple
  import torch
  import torch.distributed
  import torch.distributed._shard.sharding_spec
  import torch.distributed.distributed_c10d
  from torch.distributed._shard.sharded_tensor import Shard, ShardedTensor, ShardedTensorMetadata, TensorProperties
  from torch.distributed._shard.sharding_spec import ShardMetadata
  from torch.distributed._shard.sharding_spec.chunk_sharding_spec import ChunkShardingSpec
  from torch.distributed._tensor import DeviceMesh, DTensor, Replicate, Shard
  from torch.distributed.device_mesh import _mesh_resources
  from torch.distributed.fsdp._common_utils import _set_fsdp_flattened
  from torch.distributed.fsdp._fsdp_extensions import FSDPExtensions
  from torch.distributed.fsdp._shard_utils import _create_chunk_sharded_tensor
  from torch.distributed.remote_device import _remote_device
  from torch.distributed.tensor.parallel._data_parallel_utils import _flatten_tensor, _unflatten_tensor
label_desc: Use image node_id 3 for calling the DTensorExtensions obj's underlying member method code with example usage: obj.post_unflatten_transform(tensor, param_extension) and returns: result