Immediately mark DLPack capsule as used after stealing the ownership (#56789)
Summary:
After stealing the ownership of the tensor passed via DLPack capsule, PyTorch should immediately mark it as used (by changing its name to `used_dltensor`). This fix is needed because the following line may raise an exception:
```cpp
py::module::import("torch.cuda").attr("init")();
```
When an exception is raised, Tensor created by `at::fromDLPack` calls the `deleter`. However as the causple is not consumed, the producer (a library that created the capsule) also calls the `deleter`, causing a double free.
Reprodcuer (I'm running this code on A100 GPU + PyTorch wheel which does not include `sm_80` support; in this configuration `torch.cuda.init` will raise a warning):
```py
$ python -Werror
>>> import torch.utils.dlpack
>>> import cupy
>>> tensor = torch.utils.dlpack.from_dlpack(cupy.arange(10).toDlpack())
free(): double free detected in tcache 2
zsh: abort (core dumped) python -Werror
```
Once this fix is merged users can now see the exception correctly:
```
A100-PCIE-40GB with CUDA capability sm_80 is not compatible with the current PyTorch installation.
The current PyTorch install supports CUDA capabilities sm_37 sm_50 sm_60 sm_70.
If you want to use the A100-PCIE-40GB GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/56789
Reviewed By: astaff
Differential Revision: D28118512
Pulled By: mruberry
fbshipit-source-id: 56992f7a3fc78d94c69513e864a473ae9587a9c8
