Instructions to use Ashiedu/fused-split with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Kernels
How to use Ashiedu/fused-split with Kernels:
# !pip install kernels from kernels import get_kernel kernel = get_kernel("Ashiedu/fused-split") - Notebooks
- Google Colab
- Kaggle
File size: 585 Bytes
bc2cb62 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | import platform
import torch
import fused_split
def test_fused_split():
if platform.system() == "Darwin":
device = torch.device("mps")
elif hasattr(torch, "xpu") and torch.xpu.is_available():
device = torch.device("xpu")
elif torch.version.cuda is not None and torch.cuda.is_available():
device = torch.device("cuda")
else:
device = torch.device("cpu")
x = torch.randn(1024, 1024, dtype=torch.float32, device=device)
expected = x + 1.0
result = fused_split.fused_split(x)
torch.testing.assert_close(result, expected) |