[Ez][BE]: Remove accidental classvar #153540
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/153540
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@pytorchbot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
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@pytorchbot revert -m "Broken internal tests, @albanD may you help the author get his PR merged? D74804063" -c ghfirst |
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This reverts commit e0dece5. Reverted #153540 on behalf of https://github.com/jeanschmidt due to Broken internal tests, @albanD may you help the author get his PR merged? D74804063 ([comment](#153540 (comment)))
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@Skylion007 your PR has been successfully reverted. |
| @@ -22,6 +23,8 @@ | |||
| # from run-time to resolve circular dependency. | |||
| from torch.distributed._shard.sharded_tensor import ShardedTensor | |||
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| _ShardingDim: TypeAlias = Union[int, str] | |||
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I'm guess something imported the type Alias from the dataclass internally? I mean 8000 we can keep it as a class based TypeAlias but seems silly
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The error is:
Incompatible parameter type [6]: In call `torch.distributed._shard.sharding_spec.chunk_sharding_spec.ChunkShardingSpec.__init__`, for argument `placements`, expected `List[Union[str, _remote_device]]` but got `List[str]`.
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So I guess we need to fix the wrong type internally and not much we can do here?
Untyped variables become ClassVar in dataclasses, this type alias should just be a type alias; no need for it to eb a classvar.
cc @H-Huang @awgu @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k