Skip to content

fix: fix torch compilation #1753

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
wants to merge 1 commit into from
Closed

fix: fix torch compilation #1753

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
11 changes: 4 additions & 7 deletions docarray/typing/tensor/torch_tensor.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -130,7 +130,7 @@ def validate(
field: 'ModelField',
config: 'BaseConfig',
) -> T:
if isinstance(value, TorchTensor):
if isinstance(value, cls):
return cast(T, value)
elif isinstance(value, torch.Tensor):
return cls._docarray_from_native(value)
Expand Down Expand Up @@ -195,10 +195,7 @@ def _docarray_from_native(cls: Type[T], value: torch.Tensor) -> T:
:param value: the native `torch.Tensor`
:return: a `TorchTensor`
"""
if cls.__unparametrizedcls__: # This is not None if the tensor is parametrized
value.__class__ = cls.__unparametrizedcls__ # type: ignore
else:
value.__class__ = cls
value.__class__ = cls
return cast(T, value)

@classmethod
Expand Down Expand Up @@ -254,11 +251,11 @@ def __torch_function__(cls, func, types, args=(), kwargs=None):
# this tells torch to treat all of our custom tensors just like
# torch.Tensor's. Otherwise, torch will complain that it doesn't
# know how to handle our custom tensor type.
docarray_torch_tensors = TorchTensor.__subclasses__()
docarray_torch_tensors = cls.__subclasses__() + [cls]
types_ = tuple(
torch.Tensor if t in docarray_torch_tensors else t for t in types
)
return super().__torch_function__(func, types_, args, kwargs)
return torch.Tensor.__torch_function__(func, types_, args, kwargs)

@classmethod
def _docarray_from_ndarray(cls: Type[T], value: np.ndarray) -> T:
Expand Down