reland of https://github.com/pytorch/pytorch/pull/133113
I have to create a new PR because the previous reverted PR could not either be rebased, or imported successfully :(
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Moving DTensor to be in the public namespace, to formally add the documentation page that includes all the public APIs. This includes:
* many path renames and path import fixes
* a dedicated doc page without too much content yet (adding in the next PRs)
* To preserve the BC for users still using the torch.distributed._tensor, I added a shim script to redirect old path calls to the new module
The BC preserving is evidented by the fact that all DTensor tests are still working without changing the public imports. So it's safe to land the changes
Pull Request resolved: https://github.com/pytorch/pytorch/pull/134203
Approved by: https://github.com/tianyu-l
Moving DTensor to be in the public namespace, to formally add the
documentation page that includes all the public APIs. This includes:
* many path renames and path import fixes
* a dedicated doc page without too much content yet (adding in the next
PRs)
* To preserve the BC for users still using the `torch.distributed._tensor`,
I added a shim script to redirect old path calls to the new module
The BC preserving is evidented by the fact that all DTensor tests are still
working without changing the public imports. So it's safe to land the
changes
Pull Request resolved: https://github.com/pytorch/pytorch/pull/133113
Approved by: https://github.com/XilunWu
ghstack dependencies: #133305, #133306
Currently, when we have 2D composition, a global variable _extensions controls the 2D deviation we need to take in state_dict calls (See https://github.com/pytorch/pytorch/blob/release/2.1/torch/distributed/fsdp/_fsdp_extensions.py#L66-L68). This is problematic when we have both a 2D model and a plain FSDP model in the same dist environment, as the _extensions will be mistakenly turned on for the plain FSDP model, resulting in state_dict error (RuntimeError: No parent device_mesh is found for FSDP device_mesh.).
This PR binds _fsdp_extension to the FSDP instances to make sure that state_dict calls would not get interfered with each other when mixing both 2D and 1D parallelism.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/113237
Approved by: https://github.com/fduwjj, https://github.com/fegin
This PR adds a all_gather_dtensor() method to fsdp/_fsdp_extensions.py and the actual implementation in tensor/parallel/fsdp.py. This enables FSDP to load 2D DTensor state_dict into model when calling `model.load_state_dict()`.
cc. @fegin
Pull Request resolved: https://github.com/pytorch/pytorch/pull/110925
Approved by: https://github.com/fegin
ghstack dependencies: #110831, #110846
This PR:
1) Add device_mesh kwarg to FSDP. Remove init_device_mesh() from _runtime_utils.py, as device_mesh would be passed in by user as an kwarg.
2) change use_dtensor flag for state_dict_config and optim_state_dict_config to be private. If device_mesh is used with sharded model/optim state dict, _use_dtensor flag would be set to True and model/optim state dict would return dtensor state_dict. Otherwise, _use_dtensor flag would be set to False and model/optim state dict would return sharded_tensor state_dict.
3) Update _optim_utils.py, _shard_utils.py, and _state_dict_utils.py to add support for HSDP to return 2D DTensor state_dict.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/107533
Approved by: https://github.com/fegin, https://github.com/awgu, https://github.com/wanchaol
This PR:
1) Add device_mesh kwarg to FSDP. Remove init_device_mesh() from _runtime_utils.py, as device_mesh would be passed in by user as an kwarg.
2) change use_dtensor flag for state_dict_config and optim_state_dict_config to be private. If device_mesh is used with sharded model/optim state dict, _use_dtensor flag would be set to True and model/optim state dict would return dtensor state_dict. Otherwise, _use_dtensor flag would be set to False and model/optim state dict would return sharded_tensor state_dict.
3) Update _optim_utils.py, _shard_utils.py, and _state_dict_utils.py to add support for HSDP to return 2D DTensor state_dict.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/107533
Approved by: https://github.com/fegin, https://github.com/awgu, https://github.com/wanchaol
This adds `FSDPExtensions` to enable TP + FSDP composability. To be agnostic to both `ShardedTensor` and `DistributedTensor`, the design relies on customizable hooks.
Some notes:
- I preferred the `_ext` prefix (short for "extension") over `_param_extension` simply because it is shorter. It should not matter much because it is purely internal facing.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/85039
Approved by: https://github.com/kumpera, https://github.com/fegin
