Update DLPack to 0.4 (#55365)
Summary:
Fixes https://github.com/pytorch/pytorch/issues/55090
I included the header directly, but I am not sure if we should add this as a git submodule, what do you guys think?
Also regarding the implementation, in ATen lanes seems not to be supported, but from CuPy complex types are exported with 2 lanes, I am not sure wether this is correct or not. However, in PyTorch this seems to be working properly, so I forgive 2 lanes for complex datatypes.
TODO: add tests for complex and bfloat
Easy test script against cupy
```python
import cupy
import torch
from torch.utils.dlpack import to_dlpack
from torch.utils.dlpack import from_dlpack
# Create a PyTorch tensor.
tx1 = torch.tensor(
[2 + 1j, 3 + 2j, 4 + 3j, 5 + 4j], dtype=torch.complex128
).cuda()
# Convert it into a DLPack tensor.
dx = to_dlpack(tx1)
# Convert it into a CuPy array.
cx = cupy.fromDlpack(dx)
# Convert it back to a PyTorch tensor.
tx2 = from_dlpack(cx.toDlpack())
torch.testing.assert_allclose(tx1, tx2)
```
Thanks to leofang who updated CuPy's dlpack version and his PR served me as the guide for this one.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/55365
Reviewed By: ngimel
Differential Revision: D27724923
Pulled By: mruberry
fbshipit-source-id: 481eadb882ff3dd31e7664e08e8908c60a960f66
