[XPU] upgrade to torch 2.13 (#48677)
Signed-off-by: Yan Ma <yan.ma@intel.com> Signed-off-by: Kunshang Ji <kunshang.ji@intel.com> Co-authored-by: Kunshang Ji <kunshang.ji@intel.com> Co-authored-by: Cyrus Leung <tlleungac@connect.ust.hk>
This commit is contained in:
Yan Ma
co-authored by
Kunshang Ji
Cyrus Leung
Kunshang Ji
Cyrus Leung
parent
df2735ea2e
commit
5b29c958c7
@@ -369,7 +369,7 @@ export HF_TOKEN ZE_AFFINITY_MASK
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-e CMDS \
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--name "${container_name}" \
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"${IMAGE}" \
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bash -c 'set -e; source /opt/intel/oneapi/setvars.sh --force; source /opt/intel/oneapi/ccl/2021.15/env/vars.sh --force; echo "ZE_AFFINITY_MASK is ${ZE_AFFINITY_MASK:-}"; eval "$CMDS"' \
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bash -c 'set -e; echo "ZE_AFFINITY_MASK is ${ZE_AFFINITY_MASK:-}"; eval "$CMDS"' \
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>/dev/null
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} 9>/tmp/docker-pull.lock
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+2
-35
@@ -63,21 +63,6 @@ RUN apt-get update -y && \
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python3-pip && \
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rm -rf /var/lib/apt/lists/*
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# Add oneAPI repo, pin oneAPI to 2025.3, then install pinned packages in one layer.
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RUN wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB | gpg --dearmor | tee /usr/share/keyrings/oneapi-archive-keyring.gpg > /dev/null && \
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echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main" | tee /etc/apt/sources.list.d/oneAPI.list && \
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printf '%s\n' \
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'Package: intel-oneapi-* intel-deep-learning-essentials* intel-pti*' \
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'Pin: version 2025.3*' \
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'Pin-Priority: 1001' \
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> /etc/apt/preferences.d/oneapi-2025.3.pref && \
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apt-get update -y && \
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apt-get install -y --no-install-recommends \
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intel-oneapi-compiler-dpcpp-cpp-2025.3 \
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intel-oneapi-mkl-devel-2025.3 \
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intel-oneapi-dnnl-devel-2025.3 && \
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rm -rf /var/lib/apt/lists/*
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# Install UMD
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RUN mkdir neo && \
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cd neo && \
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@@ -100,22 +85,6 @@ RUN curl -LsSf https://astral.sh/uv/install.sh | sh \
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&& uv venv --python ${PYTHON_VERSION} --seed ${VIRTUAL_ENV}
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ENV PATH="$VIRTUAL_ENV/bin:$PATH"
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# This oneccl contains the BMG support which is not the case for default version of oneapi 2025.3.
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ARG ONECCL_INSTALLER="intel-oneccl-2021.15.9.14_offline.sh"
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RUN wget "https://github.com/uxlfoundation/oneCCL/releases/download/2021.15.9/${ONECCL_INSTALLER}" && \
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bash "${ONECCL_INSTALLER}" -a --silent --eula accept && \
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rm "${ONECCL_INSTALLER}" && \
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echo "source /opt/intel/oneapi/setvars.sh --force" >> /root/.bashrc && \
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echo "source /opt/intel/oneapi/ccl/2021.15/env/vars.sh --force" >> /root/.bashrc && \
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rm -f /opt/intel/oneapi/ccl/latest && \
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ln -s /opt/intel/oneapi/ccl/2021.15 /opt/intel/oneapi/ccl/latest && \
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printf '%s\n' \
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'/opt/intel/oneapi/ccl/2021.15/lib' \
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'/opt/intel/oneapi/mpi/2021.15/lib' \
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'/opt/intel/oneapi/compiler/2025.3/lib' \
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> /etc/ld.so.conf.d/oneapi-ccl.conf && \
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ldconfig
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SHELL ["bash", "-c"]
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CMD ["bash", "-c", "source /root/.bashrc && exec bash"]
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@@ -135,8 +104,7 @@ RUN --mount=type=cache,target=/root/.cache/uv \
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uv pip install --upgrade pip
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ENV LD_LIBRARY_PATH=/opt/intel/oneapi/ccl/2021.15/lib:/opt/intel/oneapi/mpi/2021.15/lib:/opt/intel/oneapi/compiler/2025.3/lib:/usr/local/lib
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ENV LD_LIBRARY_PATH=/opt/venv/lib:/usr/local/lib
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CMD ["/bin/bash"]
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######################### UCX + NIXL BUILD STAGE #########################
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@@ -216,8 +184,7 @@ RUN --mount=type=cache,target=/root/.cache/uv \
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uv pip install -r /workspace/vllm/requirements/xpu.txt && \
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uv pip install --no-build-isolation -r /workspace/vllm/requirements/test/xpu.txt && \
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uv pip uninstall triton triton-xpu && \
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uv pip install triton-xpu==3.7.1 && \
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uv pip uninstall oneccl oneccl-devel
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uv pip install triton-xpu==3.7.2
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# Keep source-dependent layers near the end so frequent code-only changes
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# don't invalidate heavy dependency and UCX/NIXL layers.
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@@ -42,12 +42,12 @@ pip install -v -r requirements/xpu.txt
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```bash
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pip uninstall -y triton triton-xpu
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pip install triton-xpu==3.7.1 --extra-index-url https://download.pytorch.org/whl/xpu
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pip install triton-xpu==3.7.2 --extra-index-url https://download.pytorch.org/whl/xpu
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```
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!!! note
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- `triton` (without suffix) is for NVIDIA GPUs only. On XPU, using it instead of `triton-xpu` can cause correctness or runtime issues.
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- For torch 2.12 (the version used in `requirements/xpu.txt`), the matching package is `triton-xpu==3.7.1`. If you use a different version of torch, check the corresponding `triton-xpu` version in [docker/Dockerfile.xpu](https://github.com/vllm-project/vllm/blob/main/docker/Dockerfile.xpu).
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- For torch 2.13 (the version used in `requirements/xpu.txt`), the matching package is `triton-xpu==3.7.2`. If you use a different version of torch, check the corresponding `triton-xpu` version in [docker/Dockerfile.xpu](https://github.com/vllm-project/vllm/blob/main/docker/Dockerfile.xpu).
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- Finally, build and install vLLM XPU backend:
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+26
-24
@@ -140,7 +140,7 @@ docopt==0.6.2
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# via num2words
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docstring-parser==0.18.0
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# via anthropic
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dpcpp-cpp-rt==2025.3.2
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dpcpp-cpp-rt==2026.0.0
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# via
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# onemkl-sycl-blas
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# onemkl-sycl-dft
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@@ -253,27 +253,27 @@ ijson==3.5.0
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# via -r requirements/test/../common.txt
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imageio==2.37.3
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# via scikit-image
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impi-rt==2021.17.2
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impi-rt==2021.18.0
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# via
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# oneccl
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# torch
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iniconfig==2.3.0
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# via pytest
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intel-cmplr-lib-rt==2025.3.2
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intel-cmplr-lib-rt==2026.0.0
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# via
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# intel-sycl-rt
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# torch
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intel-cmplr-lib-ur==2025.3.2
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intel-cmplr-lib-ur==2026.0.0
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# via
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# intel-openmp
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# intel-sycl-rt
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# torch
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intel-cmplr-lic-rt==2025.3.2
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intel-cmplr-lic-rt==2026.0.0
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# via
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# intel-opencl-rt
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# intel-sycl-rt
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# torch
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intel-opencl-rt==2025.3.2
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intel-opencl-rt==2026.0.0
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# via
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# dpcpp-cpp-rt
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# onemkl-sycl-blas
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@@ -282,14 +282,14 @@ intel-opencl-rt==2025.3.2
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# onemkl-sycl-rng
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# onemkl-sycl-sparse
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# torch
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intel-openmp==2025.3.2
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intel-openmp==2026.0.0
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# via
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# dpcpp-cpp-rt
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# mkl
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# torch
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intel-pti==0.16.0
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intel-pti==0.17.0
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# via torch
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intel-sycl-rt==2025.3.2
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intel-sycl-rt==2026.0.0
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# via
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# dpcpp-cpp-rt
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# oneccl
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@@ -378,7 +378,7 @@ mistral-common==1.11.5
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# -c requirements/common.txt
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# -r requirements/test/../common.txt
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# -r requirements/test/xpu.in
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mkl==2025.3.1
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mkl==2026.0.0
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# via
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# onemkl-sycl-blas
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# onemkl-sycl-dft
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@@ -453,28 +453,28 @@ numpy==2.2.6
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# torchvision
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# transformers
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# xgrammar
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oneccl==2021.17.2
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oneccl==2022.0.0
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# via
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# oneccl-devel
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# torch
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oneccl-devel==2021.17.2
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oneccl-devel==2022.0.0
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# via torch
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onemkl-license==2025.3.1
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onemkl-license==2026.0.0
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# via
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# mkl
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# torch
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onemkl-sycl-blas==2025.3.1
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onemkl-sycl-blas==2026.0.0
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# via
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# onemkl-sycl-lapack
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# onemkl-sycl-sparse
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# torch
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onemkl-sycl-dft==2025.3.1
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onemkl-sycl-dft==2026.0.0
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# via torch
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onemkl-sycl-lapack==2025.3.1
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onemkl-sycl-lapack==2026.0.0
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# via torch
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onemkl-sycl-rng==2025.3.1
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onemkl-sycl-rng==2026.0.0
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# via torch
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onemkl-sycl-sparse==2025.3.1
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onemkl-sycl-sparse==2026.0.0
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# via torch
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openai==2.44.0
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# via
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@@ -719,6 +719,8 @@ pyyaml==6.0.3
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# timm
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# transformers
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# uvicorn
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pyzes==0.1.1
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# via torch
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pyzmq==27.1.0
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# via
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# -c requirements/common.txt
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@@ -871,14 +873,14 @@ tabledata==1.3.4
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# via pytablewriter
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tabulate==0.10.0
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# via sacrebleu
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tbb==2022.3.1
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tbb==2023.0.0
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# via
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# intel-opencl-rt
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# mkl
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# torch
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tblib==3.1.0
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# via -r requirements/test/xpu.in
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tcmlib==1.4.1
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tcmlib==1.5.0
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# via
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# tbb
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# torch
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@@ -910,7 +912,7 @@ tokenizers==0.22.2
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# -c requirements/common.txt
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# -r requirements/test/../common.txt
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# transformers
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torch==2.12.0+xpu
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torch==2.13.0+xpu
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# via
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# -c requirements/xpu.txt
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# accelerate
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@@ -920,7 +922,7 @@ torch==2.12.0+xpu
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# timm
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# torchvision
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# xgrammar
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torchvision==0.27.0+xpu
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torchvision==0.28.0+xpu
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# via timm
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tqdm==4.67.3
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# via
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@@ -946,7 +948,7 @@ transformers==5.14.1
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# xgrammar
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triton==3.7.1
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# via xgrammar
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triton-xpu==3.7.1
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triton-xpu==3.7.2
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# via torch
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typepy==1.3.4
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# via
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@@ -1001,7 +1003,7 @@ typing-inspection==0.4.2
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# mcp
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# pydantic
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# pydantic-settings
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umf==1.0.3
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umf==1.1.0
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# via
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# intel-cmplr-lib-ur
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# torch
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@@ -12,10 +12,10 @@ jinja2>=3.1.6
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datasets # for benchmark scripts
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numba == 0.65.0 # Required for N-gram speculative decoding
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--extra-index-url=https://download.pytorch.org/whl/xpu
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torch==2.12.0
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torch==2.13.0
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torchaudio
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torchvision
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torchcodec >= 0.14 # Required for the torchcodec video decoding backend
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auto_round_lib==0.14.1
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vllm_xpu_kernels @ https://github.com/vllm-project/vllm-xpu-kernels/releases/download/v0.1.11.1/vllm_xpu_kernels-0.1.11.1-cp38-abi3-manylinux_2_28_x86_64.whl
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auto_round_lib==0.14.2
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vllm_xpu_kernels @ https://github.com/vllm-project/vllm-xpu-kernels/releases/download/v0.1.12/vllm_xpu_kernels-0.1.12-cp38-abi3-manylinux_2_28_x86_64.whl
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@@ -1122,7 +1122,7 @@ if _is_cuda() or _is_hip():
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# copying the relevant .py files from the source repository.
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ext_modules.append(CMakeExtension(name="vllm.triton_kernels", optional=True))
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if sys.version_info >= (3, 11):
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if not _is_xpu() and sys.version_info >= (3, 11):
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ext_modules.append(CMakeExtension(name="vllm.spinloop"))
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ext_modules.append(CMakeExtension(name="vllm.fs_io_C"))
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@@ -2391,17 +2391,6 @@ def topk_softmax(
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e_score_correction_bias: torch.Tensor | None = None,
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is_padding: torch.Tensor | None = None,
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) -> None:
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if current_platform.is_xpu():
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# TODO: Remove after vllm-xpu-kernels supports is_padding.
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torch.ops._moe_C.topk_softmax(
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topk_weights,
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topk_ids,
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token_expert_indices,
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gating_output,
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renormalize,
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e_score_correction_bias,
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)
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return
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torch.ops._moe_C.topk_softmax(
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topk_weights,
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topk_ids,
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@@ -2447,21 +2436,6 @@ def topk_hash_softplus_sqrt(
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hash_indices_table: torch.Tensor | None = None,
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is_padding: torch.Tensor | None = None,
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) -> None:
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if current_platform.is_xpu():
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# TODO: Remove after vllm-xpu-kernels supports is_padding.
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torch.ops._moe_C.topk_softplus_sqrt(
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topk_weights,
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topk_indices,
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token_expert_indices,
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gating_output,
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renormalize,
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routed_scaling_factor,
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e_score_correction_bias,
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input_tokens,
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hash_indices_table,
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)
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return
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torch.ops._moe_C.topk_softplus_sqrt(
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topk_weights,
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topk_indices,
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Reference in New Issue
Block a user