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This repository was archived by the owner on Sep 9, 2026. It is now read-only.
TorchTensor deepcopy raises error when dtype is not float32 #1831
Description
Initial Checks
- I have read and followed the docs and still think this is a bug
Description
when calling copy.deepcopy() over TorchTensor, it fails when tensor.dtype != torch.float32.
The problem is that TorchTensor.new_empty() will create a float32 tensor no matter what, regardless of self.dtype
Example Code
import torch
from docarray.typing.tensor.torch_tensor import TorchTensor
import copy
x = TorchTensor(torch.randn(2,3))
y = copy.deepcopy(x) # this works
xx = TorchTensor(torch.randint(0,100,(2,3)))
yy = copy.deepcopy(xx) # RuntimeError: Expected a Storage of type float or an UntypedStorage, but got type Long for argument 1 'storage'Python, DocArray & OS Version
0.39.1
Activity
JoanFM commentedon Nov 14, 2023
Hey @igamenovoer,
Thanms for reporting the issue. Since you spotted the problem, would you like to contribute the fix?
ai-naymul commentedon Nov 30, 2023
I think we need to add a custom implementation of
deepcopyfor TorchTensor to avoid storage-sharing issues.@JoanFM could you please help me to contribute in this?
Here is my approach:
JoanFM commentedon Nov 30, 2023
what do u mean by a deepcopy class for that?
ai-naymul commentedon Nov 30, 2023
Oh, I am sorry I was mentioning the method, It's was a typing mistake.
JoanFM commentedon Nov 30, 2023
the approach seems to make sense indeed
ai-naymul commentedon Nov 30, 2023
So should I try the approach?
JoanFM commentedon Nov 30, 2023
yws
ai-naymul commentedon Dec 2, 2023
@JoanFM would you mind having a look at the PR, please?