Lightning-AI / Lightning-AI/lightning-thunder
In-place ops on cloned tensor propagates to the original tensor
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- Dominant language
- Python
- Stars
- 1.5k
- Forks
- 121
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Description
## 🐛 Bug
On `main` 006a2435a74acce2f86056f3d6b8a8d28154a5a2
```py
import torch, thunder
@thunder.jit
def fn(x):
y = x.clone()
y.sin_()
return x + y
x = torch.randn(4, device="cuda")
x_ref = x.clone()
out = fn(x)
torch.testing.assert_close(x, x_ref) # AssertionError: Tensor-likes are not close!
torch.testing.assert_close(out, x_ref + x_ref.sin()) # AssertionError: Tensor-likes are not close!
```
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by running the supplied Python reproducer on the referenced main revision, focusing on the interaction between x.clone(), y.sin_(), and the returned values. Trace the compiler path exercised by @thunder.jit and identify where the clone's in-place operation affects x. Done means both torch.testing.assert_close checks pass without modifying the original tensor.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- compilers, machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100