4b6d6d5cf7
Signed-off-by: Joshna Medisetty <joshna.medisetty@intel.com> Co-authored-by: Cursor <cursoragent@cursor.com> Co-authored-by: Chendi.Xue <chendi.xue@intel.com>
96 lines
3.2 KiB
Bash
Executable File
96 lines
3.2 KiB
Bash
Executable File
#!/bin/bash
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# This script build the XPU docker image and run the offline inference inside the container.
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set -ex
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omni_source_dir=$(git rev-parse --show-toplevel)
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base_image_name="xpu/vllm-omni-ci-base:${VLLM_VERSION:?VLLM_VERSION must be set}"
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image_name="xpu/vllm-omni-ci:${BUILDKITE_COMMIT:?BUILDKITE_COMMIT must be set}"
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container_name="xpu_${BUILDKITE_COMMIT}_$(
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tr -dc A-Za-z0-9 </dev/urandom | head -c 10
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echo
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)"
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cd "${omni_source_dir}"
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# The XPU base image is ~37GB; the default gzip layer exporter is single-threaded
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# and takes ~16min to compress it. zstd is multi-threaded (uses all cores) at a
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# similar ratio; set EXPORT_COMPRESSION=uncompressed to skip compression entirely
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# for local-only images. This requires the containerd image store (buildx docker
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# driver), which is the default here.
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EXPORT_COMPRESSION="${EXPORT_COMPRESSION:-zstd}"
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if [ "${EXPORT_COMPRESSION}" = "uncompressed" ]; then
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export_args=(--output "type=image,name={{IMAGE}},compression=uncompressed")
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else
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export_args=(--output "type=image,name={{IMAGE}},compression=${EXPORT_COMPRESSION},compression-level=3,force-compression=true")
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fi
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docker_build() {
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# $1 = image name; remaining args passed through to docker build.
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local image="$1"
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shift
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local out=("${export_args[@]/'{{IMAGE}}'/${image}}")
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docker build "${out[@]}" "$@" -f docker/Dockerfile.xpu .
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}
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build_vllm_base() (
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local vllm_source_dir
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vllm_source_dir=$(mktemp -d)
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trap 'rm -rf "${vllm_source_dir}"' EXIT
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git clone --depth 1 --branch "${VLLM_VERSION}" \
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https://github.com/vllm-project/vllm "${vllm_source_dir}"
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local out=("${export_args[@]/'{{IMAGE}}'/${base_image_name}}")
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docker build "${out[@]}" \
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--target vllm-openai \
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-f "${vllm_source_dir}/docker/Dockerfile.xpu" \
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"${vllm_source_dir}"
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)
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if [ -z "$(docker images -q "${base_image_name}")" ]; then
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build_vllm_base
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fi
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# Try building the docker image
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docker_build "${image_name}" --build-arg "VLLM_BASE=${base_image_name}" --build-arg "VLLM_VERSION=${VLLM_VERSION}"
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# Setup cleanup
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remove_docker_container() {
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docker rm -f "${container_name}" || true
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docker image rm -f "${image_name}" || true
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docker system prune -f || true
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}
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trap remove_docker_container EXIT
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HF_CACHE="${HF_CACHE:-$(realpath ~)/.cache/huggingface}"
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mkdir -p "${HF_CACHE}"
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HF_MOUNT="/root/.cache/huggingface"
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time timeout -k 30 30m docker run \
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--device /dev/dri:/dev/dri \
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--net=host \
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--ipc=host \
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-v /dev/dri/by-path:/dev/dri/by-path \
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-v "${HF_CACHE}:${HF_MOUNT}" \
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--security-opt seccomp=unconfined \
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--entrypoint="" \
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-e VLLM_LOGGING_LEVEL \
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-e VLLM_OMNI_LOGGING_LEVEL \
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-e HF_TOKEN \
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-e ZE_AFFINITY_MASK \
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--name "${container_name}" \
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"${image_name}" \
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bash -c '
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set -e
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echo $ZE_AFFINITY_MASK
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pip install tblib==3.1.0
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cd /workspace/vllm-omni
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XPU_TEST_PATHS="tests/diffusion tests/dfx tests/e2e"
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pytest -v -s $XPU_TEST_PATHS -m "core_model and xpu and B60"
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pytest -v -s tests/diffusion/quantization/test_mxfp8_config.py
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pytest -v -s $XPU_TEST_PATHS -m "advanced_model and xpu and B60"
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pytest -v -s $XPU_TEST_PATHS -m "omni and xpu and B60"
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'
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