minke.yu/sglang
1
0
Fork 0
Code Issues Pull Requests Actions 12 Packages Projects Releases Wiki Activity

[XPU] upgrade sglang xpu backend to PyTorch 2.13 (#31751)

Browse Source 
Co-authored-by: MingxuZh <109504044+MingxuZh@users.noreply.github.com>
Co-authored-by: Ma Mingfei <mingfei.ma@intel.com>
This commit is contained in:
yuchengliu1
2026-08-17 18:29:15 +08:00
committed by GitHub
co-authored by MingxuZh Ma Mingfei
parent c82e928fe5
commit 744740dbea
5 changed files with 56 additions and 25 deletions
Download Patch File Download Diff File Expand all files Collapse all files
docs/docs/hardware-platforms/xpu.mdx
+1 -1
View File
@@ -53,7 +53,7 @@ conda create -n sgl-xpu python=3.12 -y
conda activate sgl-xpu
# Set PyTorch XPU as primary pip install channel to avoid installing the larger CUDA-enabled version and prevent potential runtime issues.
pip3 install torch==2.12.0+xpu torchvision==0.27.0+xpu torchaudio==2.11.0+xpu --index-url https://download.pytorch.org/whl/xpu
pip3 install torch==2.13.0+xpu torchvision==0.28.0+xpu torchaudio==2.11.0+xpu --index-url https://download.pytorch.org/whl/xpu
pip3 install xgrammar --no-deps # xgrammar will introduce CUDA-enabled triton which might conflict with XPU
pip3 install apache-tvm-ffi # xgrammar requires apache-tvm-ffi
docs/docs/sglang-diffusion/installation.mdx
+1 -5
View File
@@ -87,11 +87,7 @@ pip install -e "python[all_musa]"
## Platform-Specific: Intel XPU
For Intel Data Center GPU Max or Arc GPUs, follow the [XPU installation guide](../hardware-platforms/xpu) to set up the base environment, then install diffusion dependencies:
```bash Command
pip install -e "python[diffusion]"
```
For Intel Data Center GPU Max or Arc GPUs, follow the installation with docker in [XPU installation guide](../hardware-platforms/xpu). The dockerfile already include diffusion dependencies:
## Platform-Specific: Ascend NPU