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[dtensor] handle the case where output of op is Optional[Tensor] #90241

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[dtensor] handle the case where output of op is Optional[Tensor] #90241

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[dtensor] handle the case where output of op is Optional[Tensor]
wanchaol Dec 6, 2022
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Update on "[dtensor] handle the case where output of op is Optional[T…
wanchaol Dec 6, 2022
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Update on "[dtensor] handle the case where output of op is Optional[T…
wanchaol Dec 6, 2022
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7 changes: 6 additions & 1 deletion torch/distributed/_tensor/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@
ArgKwargsType = Union[Tuple[object, ...], Dict[str, object]]
# ATen op schemas could have Tensor, Tuple[Tensor] and List[Tensor], so output type sould
# be the same set of possiblities.
OutputSpecType = Optional[Union[DTensorSpec, Sequence[DTensorSpec]]]
OutputSpecType = Optional[Union[DTensorSpec, Sequence[Optional[DTensorSpec]]]]


def unwrap_local_tensor(e: "dtensor.DTensor") -> torch.Tensor:
Expand Down Expand Up @@ -45,8 +45,13 @@ def wrap(res: object, spec: OutputSpecType) -> object:
assert spec is not None and isinstance(
spec, tuple
), f"output spec does not match with output! Expected tuple, got {spec}"

# NOTE: local results might return Optional Tensor from ATen op, so we need to
# handle that case and make sure we don't wrap None with DTensor.
# (i.e. native_layer_norm.backward)
return tuple(
dtensor.DTensor(e, s.mesh, s.placements, size=s.shape)
if e is not None and s is not None else None
for e, s in zip(res, spec)
)
else:
Expand Down