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Author SHA1 Message Date
Bugen Zhao cf30ef60cf use newtype for logprobs count (-1 for all)
Signed-off-by: Bugen Zhao <i@bugenzhao.com>
2026-06-22 19:30:10 +08:00
2370 changed files with 52498 additions and 215808 deletions
+3 -3
View File
@@ -2,17 +2,17 @@ name: vllm_intel_ci
job_dirs:
- ".buildkite/intel_jobs"
run_all_patterns:
- ".buildkite/ci_config_intel.yaml"
- ".buildkite/scripts/hardware_ci/run-intel-test.sh"
- "docker/Dockerfile"
- "docker/Dockerfile.xpu"
- "CMakeLists.txt"
- "requirements/common.txt"
- "requirements/xpu.txt"
- "requirements/build/cuda.txt"
- "requirements/test/cuda.txt"
- "setup.py"
- "csrc/"
- "cmake/"
run_all_exclude_patterns:
- "docker/Dockerfile."
- "csrc/cpu/"
- "csrc/rocm/"
- "cmake/hipify.py"
-1
View File
@@ -8,7 +8,6 @@ run_all_patterns:
- "docker/docker-bake-rocm.hcl"
- ".buildkite/hardware_tests/amd.yaml"
- ".buildkite/scripts/ci-bake-rocm.sh"
- ".buildkite/scripts/rocm/"
- ".buildkite/scripts/hardware_ci/run-amd-test.py"
- ".buildkite/scripts/hardware_ci/run-amd-test.sh"
- "CMakeLists.txt"
+29 -40
View File
@@ -1,55 +1,24 @@
group: Hardware - AMD Build
# ROCm image flow:
# 1. Refresh the long-lived ROCm base image only when Dockerfile.rocm_base changes.
# 2. Build ci_base from either the stable base or the freshly refreshed base.
# 3. Build the per-commit ROCm CI image and smoke-test it before GPU jobs run.
steps:
- label: "AMD: :docker: refresh ROCm base"
key: refresh-rocm-base-amd
depends_on: []
device: amd_cpu
no_plugin: true
commands:
- bash .buildkite/scripts/rocm/refresh-base-image.sh
env:
DOCKER_BUILDKIT: "1"
BUILDKIT_PROGRESS: "tty"
TERM: "xterm-256color"
retry:
automatic:
- exit_status: 1 # Transient Docker/BuildKit failure
limit: 1
- exit_status: -1 # Agent was lost
limit: 1
- exit_status: -10 # Agent was lost
limit: 1
# Ensure ci_base is up-to-date before building the test image.
# Compares a content hash of ci_base-affecting files against the remote
# image label. If hashes match the build is skipped (< 30 s); if they
# differ ci_base is rebuilt and pushed automatically.
- label: "AMD: :docker: ensure ci_base"
key: ensure-ci-base-amd
soft_fail: false
depends_on:
- refresh-rocm-base-amd
depends_on: []
device: amd_cpu
no_plugin: true
commands:
- bash .buildkite/scripts/rocm/build-ci-base.sh
- bash .buildkite/scripts/ci-bake-rocm.sh ci-base-rocm-ci-with-deps
env:
DOCKER_BUILDKIT: "1"
BUILDKIT_PROGRESS: "tty"
TERM: "xterm-256color"
VLLM_BAKE_FILE: "docker/docker-bake-rocm.hcl"
PYTORCH_ROCM_ARCH: "gfx90a;gfx942;gfx950"
REMOTE_VLLM: "1"
VLLM_BRANCH: "$BUILDKITE_COMMIT"
retry:
automatic:
- exit_status: 1 # Transient Docker/BuildKit failure
limit: 1
- exit_status: -1 # Agent was lost
limit: 1
- exit_status: -10 # Agent was lost
@@ -57,18 +26,40 @@ steps:
- label: "AMD: :docker: build test image and artifacts"
key: image-build-amd
soft_fail: false
depends_on:
- ensure-ci-base-amd
device: amd_cpu
no_plugin: true
commands:
- bash .buildkite/scripts/rocm/build-test-image.sh
- bash .buildkite/scripts/rocm/smoke-test-image.sh
- |
if [[ "${ROCM_CI_ARTIFACT_ONLY:-0}" == "1" ]]; then
echo "ROCM_CI_ARTIFACT_ONLY=1; building ROCm wheel artifact only"
IMAGE_TAG="" bash .buildkite/scripts/ci-bake-rocm.sh test-rocm-ci-with-artifacts
else
bash .buildkite/scripts/ci-bake-rocm.sh test-rocm-ci-with-wheel
fi
- |
docker run --rm --network=none --entrypoint /bin/bash "rocm/vllm-ci:${BUILDKITE_COMMIT}" -ec '
if [ ! -d /vllm-workspace ]; then echo Missing directory: /vllm-workspace >&2; exit 1; fi
if [ ! -d /vllm-workspace/tests ]; then echo Missing directory: /vllm-workspace/tests >&2; exit 1; fi
if [ ! -d /vllm-workspace/src/vllm ]; then echo Missing directory: /vllm-workspace/src/vllm >&2; exit 1; fi
if [ ! -x /vllm-workspace/src/vllm/vllm-rs ]; then echo Missing executable: /vllm-workspace/src/vllm/vllm-rs >&2; exit 1; fi
command -v python3
command -v uv
command -v pytest
if ! command -v amd-smi >/dev/null 2>&1 && ! command -v rocminfo >/dev/null 2>&1; then
echo No ROCm CLI found in image >&2
exit 1
fi
python3 - <<PY
import torch, vllm
print(torch.__version__)
print(vllm.__version__)
PY
echo AMD image smoke OK
'
env:
DOCKER_BUILDKIT: "1"
BUILDKIT_PROGRESS: "tty"
TERM: "xterm-256color"
VLLM_BAKE_FILE: "docker/docker-bake-rocm.hcl"
PYTORCH_ROCM_ARCH: "gfx90a;gfx942;gfx950"
IMAGE_TAG: "rocm/vllm-ci:$BUILDKITE_COMMIT"
@@ -76,8 +67,6 @@ steps:
VLLM_BRANCH: "$BUILDKITE_COMMIT"
retry:
automatic:
- exit_status: 1 # Transient Docker/BuildKit failure
limit: 1
- exit_status: -1 # Agent was lost
limit: 1
- exit_status: -10 # Agent was lost
+6 -29
View File
@@ -17,22 +17,16 @@ steps:
- tests/kernels/test_awq_int4_to_int8.py
- tests/kernels/quantization/test_cpu_fp8_scaled_mm.py
- tests/kernels/mamba/cpu/test_cpu_gdn_ops.py
- tests/kernels/mamba/test_cpu_short_conv.py
- tests/kernels/mamba/test_causal_conv1d.py
- tests/kernels/mamba/test_mamba_ssm.py
commands:
- |
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 30m "
pytest -x -v -s tests/kernels/attention/test_cpu_attn.py
pytest -x -v -s tests/kernels/moe/test_cpu_fused_moe.py
pytest -x -v -s tests/kernels/moe/test_cpu_quant_fused_moe.py
pytest -x -v -s tests/kernels/mamba/test_cpu_short_conv.py
pytest -x -v -s tests/kernels/test_onednn.py
pytest -x -v -s tests/kernels/test_awq_int4_to_int8.py
pytest -x -v -s tests/kernels/quantization/test_cpu_fp8_scaled_mm.py
pytest -x -v -s tests/kernels/mamba/cpu/test_cpu_gdn_ops.py
pytest -x -v -s tests/kernels/mamba/test_causal_conv1d.py
pytest -x -v -s tests/kernels/mamba/test_mamba_ssm.py"
pytest -x -v -s tests/kernels/mamba/cpu/test_cpu_gdn_ops.py"
# Note: SDE can't be downloaded from CI host because of AWS WAF
# - label: CPU-Compatibility Tests
@@ -59,7 +53,7 @@ steps:
- tests/models/language/pooling/
commands:
- |
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 50m "
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 40m "
pytest -x -v -s tests/models/language/generation -m cpu_model
pytest -x -v -s tests/models/language/pooling -m cpu_model"
@@ -74,15 +68,13 @@ steps:
- vllm/v1/sample/ops/topk_topp_triton.py
- vllm/v1/sample/ops/topk_topp_sampler.py
- tests/v1/sample/test_topk_topp_sampler.py
- tests/v1/e2e/test_cpu_linear_attn_chunked_prefix.py
commands:
- |
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 45m "
uv pip install git+https://github.com/triton-lang/triton-cpu.git@270e696d
VLLM_USE_V2_MODEL_RUNNER=1 pytest -x -v -s tests/models/language/generation/test_granite.py -m cpu_model
# TODO: move to CPU-Kernel Tests once triton-cpu has a pre-built wheel
pytest -x -v -s tests/v1/sample/test_topk_topp_sampler.py::TestTritonTopkTopp
pytest -x -v -s tests/v1/e2e/test_cpu_linear_attn_chunked_prefix.py"
pytest -x -v -s tests/v1/sample/test_topk_topp_sampler.py::TestTritonTopkTopp"
- label: CPU-Quantization Model Tests
depends_on: []
@@ -97,13 +89,11 @@ steps:
- vllm/model_executor/layers/fused_moe/experts/cpu_moe.py
- tests/quantization/test_compressed_tensors.py
- tests/quantization/test_cpu_wna16.py
- tests/quantization/test_cpu_w8a8.py
commands:
- |
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 45m "
pytest -x -v -s tests/quantization/test_compressed_tensors.py::test_compressed_tensors_w8a8_logprobs
pytest -x -v -s tests/quantization/test_cpu_wna16.py
pytest -x -v -s tests/quantization/test_cpu_w8a8.py"
pytest -x -v -s tests/quantization/test_cpu_wna16.py"
- label: CPU-Distributed Tests (PP+TP)
depends_on: []
@@ -145,21 +135,8 @@ steps:
commands:
- |
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 45m "
pytest -x -v -s tests/models/multimodal/generation --ignore=tests/models/multimodal/generation/test_pixtral.py --ignore=tests/models/multimodal/generation/test_qwen2_5_vl.py -m cpu_model --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB"
parallelism: 4
- label: CPU-Qwen2.5-VL Multimodal Tests
depends_on: []
device: intel_cpu
no_plugin: true
source_file_dependencies:
# - vllm/
- vllm/model_executor/layers/rotary_embedding
- tests/models/multimodal/generation/
commands:
- |
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 40m "
VLLM_CI_ENV=0 pytest -x -v -s tests/models/multimodal/generation/test_qwen2_5_vl.py"
pytest -x -v -s tests/models/multimodal/generation --ignore=tests/models/multimodal/generation/test_pixtral.py -m cpu_model --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB"
parallelism: 3
- label: "Arm CPU Test"
depends_on: []
@@ -18,7 +18,7 @@ steps:
- label: "XPU example Test"
depends_on:
- image-build-xpu
timeout_in_minutes: 50
timeout_in_minutes: 30
optional: true
device: intel_gpu
agent_tags:
@@ -39,13 +39,13 @@ steps:
- label: "XPU V1 test"
depends_on:
- image-build-xpu
timeout_in_minutes: 70
timeout_in_minutes: 30
optional: true
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 24+
mem: 16+
no_plugin: true
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
@@ -60,7 +60,7 @@ steps:
- label: "XPU server test"
depends_on:
- image-build-xpu
timeout_in_minutes: 45
timeout_in_minutes: 30
optional: true
device: intel_gpu
agent_tags:
-20
View File
@@ -79,18 +79,12 @@ setup_buildx_builder() {
docker buildx ls | grep -E '^\*|^NAME' || docker buildx ls
}
annotate_image_tags() {
.buildkite/scripts/annotate-image-build.sh \
"${IMAGE_TAG:-}" "${IMAGE_TAG_LATEST:-}"
}
check_and_skip_if_image_exists() {
if [[ -n "${IMAGE_TAG:-}" ]]; then
echo "--- :mag: Checking if image exists"
if docker manifest inspect "${IMAGE_TAG}" >/dev/null 2>&1; then
echo "Image already exists: ${IMAGE_TAG}"
echo "Skipping build"
annotate_image_tags
exit 0
fi
echo "Image not found, proceeding with build"
@@ -177,18 +171,6 @@ BRANCH=$4
IMAGE_TAG=$5
IMAGE_TAG_LATEST=${6:-} # only used for main branch, optional
# When TORCH_NIGHTLY=1, build the base CI image against PyTorch nightly so the
# entire existing pipeline runs on nightly torch (CUDA/GPU lane only). Delegate
# to the dedicated nightly build (PYTORCH_NIGHTLY=1, CUDA 13.0) and tag it at the
# normal IMAGE_TAG that every test step already pulls -- no separate image tag,
# no duplicate "vLLM Against PyTorch Nightly" pipeline section.
if [[ "${TORCH_NIGHTLY:-0}" == "1" ]]; then
echo "--- :warning: TORCH_NIGHTLY=1 -- building base image on PyTorch nightly"
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
exec "${SCRIPT_DIR}/image_build_torch_nightly.sh" \
"${REGISTRY}" "${REPO}" "${BUILDKITE_COMMIT}" "${BRANCH}" "${IMAGE_TAG}"
fi
# build config
TARGET="test-ci"
VLLM_BAKE_FILE_PATH="${VLLM_BAKE_FILE_PATH:-docker/docker-bake.hcl}"
@@ -272,5 +254,3 @@ echo "--- :docker: Building ${TARGET}"
docker --debug buildx bake -f "${VLLM_BAKE_FILE_PATH}" -f "${CI_HCL_PATH}" --progress plain "${TARGET}"
echo "--- :white_check_mark: Build complete"
annotate_image_tags
+18 -20
View File
@@ -9,31 +9,29 @@ fi
REGISTRY=$1
REPO=$2
BUILDKITE_COMMIT=$3
IMAGE="$REGISTRY/$REPO:$BUILDKITE_COMMIT-arm64"
# authenticate with AWS ECR
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY" || true
# skip build if image already exists
if docker manifest inspect "$IMAGE" >/dev/null 2>&1; then
echo "Image found"
else
if [[ -z $(docker manifest inspect "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-arm64) ]]; then
echo "Image not found, proceeding with build..."
# build for arm64 GPU targets: Grace/GH200 (sm_90),
# Blackwell/Thor (sm_100/sm_103/sm_110), and DGX Spark/GB10
# (sm_121, family-covered by 12.0 under CUDA 13)
docker build --file docker/Dockerfile \
--platform linux/arm64 \
--build-arg max_jobs=16 \
--build-arg nvcc_threads=4 \
--build-arg torch_cuda_arch_list="9.0 10.0 11.0 12.0" \
--build-arg USE_SCCACHE=1 \
--build-arg buildkite_commit="$BUILDKITE_COMMIT" \
--tag "$IMAGE" \
--target test \
--progress plain .
# push
docker push "$IMAGE"
else
echo "Image found"
exit 0
fi
.buildkite/scripts/annotate-image-build.sh "$IMAGE"
# build (Grace/GH200 is the arm64 GPU target; sm_90)
docker build --file docker/Dockerfile \
--platform linux/arm64 \
--build-arg max_jobs=16 \
--build-arg nvcc_threads=4 \
--build-arg torch_cuda_arch_list="9.0" \
--build-arg USE_SCCACHE=1 \
--build-arg buildkite_commit="$BUILDKITE_COMMIT" \
--tag "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-arm64 \
--target test \
--progress plain .
# push
docker push "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-arm64
+15 -15
View File
@@ -9,26 +9,26 @@ fi
REGISTRY=$1
REPO=$2
BUILDKITE_COMMIT=$3
IMAGE="$REGISTRY/$REPO:$BUILDKITE_COMMIT-cpu"
# authenticate with AWS ECR
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY" || true
# skip build if image already exists
if docker manifest inspect "$IMAGE" >/dev/null 2>&1; then
echo "Image found"
else
if [[ -z $(docker manifest inspect "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-cpu) ]]; then
echo "Image not found, proceeding with build..."
# build
docker build --file docker/Dockerfile.cpu \
--build-arg max_jobs=16 \
--build-arg buildkite_commit="$BUILDKITE_COMMIT" \
--build-arg VLLM_CPU_X86=true \
--tag "$IMAGE" \
--target vllm-test \
--progress plain .
# push
docker push "$IMAGE"
else
echo "Image found"
exit 0
fi
.buildkite/scripts/annotate-image-build.sh "$IMAGE"
# build
docker build --file docker/Dockerfile.cpu \
--build-arg max_jobs=16 \
--build-arg buildkite_commit="$BUILDKITE_COMMIT" \
--build-arg VLLM_CPU_X86=true \
--tag "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-cpu \
--target vllm-test \
--progress plain .
# push
docker push "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-cpu
+14 -14
View File
@@ -9,25 +9,25 @@ fi
REGISTRY=$1
REPO=$2
BUILDKITE_COMMIT=$3
IMAGE="$REGISTRY/$REPO:$BUILDKITE_COMMIT-arm64-cpu"
# authenticate with AWS ECR
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY" || true
# skip build if image already exists
if docker manifest inspect "$IMAGE" >/dev/null 2>&1; then
echo "Image found"
else
if [[ -z $(docker manifest inspect "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-arm64-cpu) ]]; then
echo "Image not found, proceeding with build..."
# build
docker build --file docker/Dockerfile.cpu \
--build-arg max_jobs=16 \
--build-arg buildkite_commit="$BUILDKITE_COMMIT" \
--tag "$IMAGE" \
--target vllm-test \
--progress plain .
# push
docker push "$IMAGE"
else
echo "Image found"
exit 0
fi
.buildkite/scripts/annotate-image-build.sh "$IMAGE"
# build
docker build --file docker/Dockerfile.cpu \
--build-arg max_jobs=16 \
--build-arg buildkite_commit="$BUILDKITE_COMMIT" \
--tag "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-arm64-cpu \
--target vllm-test \
--progress plain .
# push
docker push "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-arm64-cpu
+15 -15
View File
@@ -9,26 +9,26 @@ fi
REGISTRY=$1
REPO=$2
BUILDKITE_COMMIT=$3
IMAGE="$REGISTRY/$REPO:$BUILDKITE_COMMIT-hpu"
# authenticate with AWS ECR
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY" || true
# skip build if image already exists
if docker manifest inspect "$IMAGE" >/dev/null 2>&1; then
echo "Image found"
else
if [[ -z $(docker manifest inspect "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-hpu) ]]; then
echo "Image not found, proceeding with build..."
# build
docker build \
--file tests/pytorch_ci_hud_benchmark/Dockerfile.hpu \
--build-arg max_jobs=16 \
--build-arg buildkite_commit="$BUILDKITE_COMMIT" \
--tag "$IMAGE" \
--progress plain \
https://github.com/vllm-project/vllm-gaudi.git
# push
docker push "$IMAGE"
else
echo "Image found"
exit 0
fi
.buildkite/scripts/annotate-image-build.sh "$IMAGE"
# build
docker build \
--file tests/pytorch_ci_hud_benchmark/Dockerfile.hpu \
--build-arg max_jobs=16 \
--build-arg buildkite_commit="$BUILDKITE_COMMIT" \
--tag "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-hpu \
--progress plain \
https://github.com/vllm-project/vllm-gaudi.git
# push
docker push "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-hpu
@@ -40,7 +40,6 @@ docker buildx ls
echo "--- :mag: Checking if image already exists"
if docker manifest inspect "$IMAGE_TAG" >/dev/null 2>&1; then
echo "Image found: $IMAGE_TAG — skipping build"
.buildkite/scripts/annotate-image-build.sh "$IMAGE_TAG"
exit 0
fi
echo "Image not found, proceeding with build..."
@@ -67,5 +66,3 @@ docker buildx build --file docker/Dockerfile \
--progress plain .
echo "--- :white_check_mark: Torch nightly image build complete: $IMAGE_TAG"
.buildkite/scripts/annotate-image-build.sh "$IMAGE_TAG"
+14 -14
View File
@@ -9,26 +9,26 @@ fi
REGISTRY=$1
REPO=$2
BUILDKITE_COMMIT=$3
IMAGE="$REGISTRY/$REPO:$BUILDKITE_COMMIT-xpu"
# authenticate with AWS ECR
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY" || true
aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin 936637512419.dkr.ecr.us-east-1.amazonaws.com || true
# skip build if image already exists
if docker manifest inspect "$IMAGE" &> /dev/null; then
echo "Image found"
else
if ! docker manifest inspect "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-xpu &> /dev/null; then
echo "Image not found, proceeding with build..."
# build
docker build \
--file docker/Dockerfile.xpu \
--build-arg max_jobs=16 \
--build-arg buildkite_commit="$BUILDKITE_COMMIT" \
--tag "$IMAGE" \
--progress plain .
# push
docker push "$IMAGE"
else
echo "Image found"
exit 0
fi
.buildkite/scripts/annotate-image-build.sh "$IMAGE"
# build
docker build \
--file docker/Dockerfile.xpu \
--build-arg max_jobs=16 \
--build-arg buildkite_commit="$BUILDKITE_COMMIT" \
--tag "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-xpu \
--progress plain .
# push
docker push "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-xpu
+1 -2
View File
@@ -3,7 +3,7 @@ depends_on:
- image-build-xpu
steps:
- label: XPU Sleep Mode
timeout_in_minutes: 45
timeout_in_minutes: 30
device: intel_gpu
agent_tags:
label: production
@@ -23,5 +23,4 @@ steps:
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
pytest -v -s basic_correctness/test_cpu_offload.py &&
pytest -v -s basic_correctness/test_mem.py::test_end_to_end'
@@ -1,5 +1,5 @@
group: Expert Parallelism
depends_on:
depends_on:
- image-build-xpu
steps:
- label: EPLB Algorithm
+3 -5
View File
@@ -81,12 +81,10 @@ steps:
'cd tests &&
export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
set -o pipefail &&
pytest -v -s lora/test_punica_ops.py::test_kernels &&
pytest -v -s lora/test_punica_ops.py::test_kernels_hidden_size &&
pytest -v -s lora/test_punica_ops.py::test_add_lora_fused_moe_early_exit'
pytest -v -s lora/test_punica_ops.py --deselect="tests/lora/test_punica_ops.py::test_kernels_hidden_size[expand-0-xpu:0-dtype0-3-43264-32-4-4]" --deselect="tests/lora/test_punica_ops.py::test_kernels[shrink-0-xpu:0-dtype1-1-2049-64-128-16]" --deselect="tests/lora/test_punica_ops.py::test_kernels[shrink-0-xpu:0-dtype0-1-2049-128-1-32]" --deselect="tests/lora/test_punica_ops.py::test_kernels[shrink-0-xpu:0-dtype0-1-2049-256-1-4]" --deselect="tests/lora/test_punica_ops.py::test_kernels[shrink-0-xpu:0-dtype0-1-2049-256-8-4]" --deselect="tests/lora/test_punica_ops.py::test_kernels[expand-0-xpu:0-dtype0-3-2049-128-8-16]" --deselect="tests/lora/test_punica_ops.py::test_kernels[shrink-0-xpu:0-dtype0-1-2049-128-8-32]" --deselect="tests/lora/test_punica_ops.py::test_kernels[expand-0-xpu:0-dtype1-1-2049-256-128-32]" --deselect="tests/lora/test_punica_ops.py::test_kernels_hidden_size[shrink-0-xpu:0-dtype0-3-64256-32-4-4]" --deselect="tests/lora/test_punica_ops.py::test_kernels_hidden_size[shrink-0-xpu:0-dtype1-2-29696-32-4-4]" --deselect="tests/lora/test_punica_ops.py::test_kernels_hidden_size[shrink-0-xpu:0-dtype1-3-49408-32-4-4]" --deselect="tests/lora/test_punica_ops.py::test_kernels_hidden_size[shrink-0-xpu:0-dtype0-2-16384-32-4-4]" --deselect="tests/lora/test_punica_ops.py::test_kernels_hidden_size[expand-0-xpu:0-dtype0-2-51328-32-4-4]"'
- label: LoRA Punica FP8/XPU Ops
timeout_in_minutes: 60
timeout_in_minutes: 45
device: intel_gpu
agent_tags:
label: production
@@ -130,10 +128,10 @@ steps:
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
(pytest -v -s lora/test_mixtral.py --deselect="tests/lora/test_mixtral.py::test_mixtral_lora[4]" || true) &&
pytest -v -s lora/test_quant_model.py --deselect="tests/lora/test_quant_model.py::test_quant_model_lora[model0]" --deselect="tests/lora/test_quant_model.py::test_quant_model_lora[model1]" --deselect="tests/lora/test_quant_model.py::test_quant_model_tp_equality[model0]" &&
pytest -v -s lora/test_transformers_model.py &&
pytest -v -s lora/test_chatglm3_tp.py &&
pytest -v -s lora/test_llama_tp.py::test_llama_lora &&
pytest -s -v lora/test_minicpmv_tp.py'
- label: LoRA Multimodal
+10 -57
View File
@@ -3,7 +3,7 @@ depends_on:
- image-build-xpu
steps:
- label: V1 Core + KV + Metrics
timeout_in_minutes: 45
timeout_in_minutes: 30
device: intel_gpu
agent_tags:
label: production
@@ -33,12 +33,12 @@ steps:
pytest -v -s v1/executor'
- label: V1 Sample + Logits
timeout_in_minutes: 90
timeout_in_minutes: 30
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 24+
mem: 16+
no_plugin: true
working_dir: "."
env:
@@ -72,31 +72,9 @@ steps:
pytest -v -s v1/test_oracle.py &&
pytest -v -s v1/test_request.py &&
pytest -v -s v1/test_outputs.py &&
pytest -v -s v1/sample'
- label: Basic Models Tests (Initialization)
timeout_in_minutes: 60
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/
- tests/models/test_initialization.py
- tests/models/registry.py
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'export VLLM_XPU_FUSED_MOE_USE_REF=1 &&
cd tests &&
pytest -v -s models/test_initialization.py::test_can_initialize_large_subset[Eagle3MiniMaxM2ForCausalLM]'
pytest -v -s v1/sample/test_topk_topp_sampler.py &&
pytest -v -s v1/sample/test_logprobs.py &&
pytest -v -s v1/sample/test_logprobs_e2e.py'
- label: XPU CPU Offload
timeout_in_minutes: 60
@@ -125,34 +103,9 @@ steps:
pytest -v -s v1/kv_offload &&
pytest -v -s v1/kv_connector/unit/test_offloading_connector.py'
- label: NixlConnector PD accuracy (2 GPUs)
timeout_in_minutes: 60
num_devices: 2
device: intel_gpu
agent_tags:
label: production
gpu: 2+
mem: 16+
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl/
- vllm/v1/worker/kv_connector_model_runner_mixin.py
- tests/v1/kv_connector/nixl_integration/
- vllm/platforms/xpu.py
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
bash v1/kv_connector/nixl_integration/run_xpu_disagg_accuracy_test.sh'
- label: Regression
key: regression
timeout_in_minutes: 50
timeout_in_minutes: 30
device: intel_gpu
agent_tags:
label: production
@@ -180,13 +133,13 @@ steps:
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'pip install modelscope\<1.38 &&
'pip install modelscope &&
cd tests &&
pytest -v -s test_regression.py'
- label: Metrics, Tracing (2 GPUs)
key: metrics-tracing-2-gpus
timeout_in_minutes: 45
timeout_in_minutes: 30
num_devices: 2
device: intel_gpu
agent_tags:
@@ -222,7 +175,7 @@ steps:
- label: Async Engine, Inputs, Utils, Worker
key: async-engine-inputs-utils-worker
timeout_in_minutes: 55
timeout_in_minutes: 30
device: intel_gpu
agent_tags:
label: production
@@ -1,27 +0,0 @@
group: Models - Distributed
depends_on:
- image-build-xpu
steps:
- label: Distributed Model Tests (2 GPUs)
key: distributed-model-tests-2-gpus
timeout_in_minutes: 65
device: intel_gpu
agent_tags:
label: production
gpu: 2+
mem: 16+
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/model_executor/model_loader/sharded_state_loader.py
- vllm/model_executor/models/
- tests/model_executor/model_loader/test_sharded_state_loader.py
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
pytest -v -s model_executor/model_loader/test_sharded_state_loader.py -m "not slow_test"'
@@ -1,35 +1,10 @@
group: Models - Multimodal
depends_on:
depends_on:
- image-build-xpu
steps:
- label: "Multi-Modal Models (Standard) 1: qwen2"
key: multi-modal-models-standard-1-qwen2
timeout_in_minutes: 70
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 24+
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/
- tests/models/multimodal
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'pip install av &&
cd tests &&
pytest -v -s models/multimodal/generation/test_common.py -m core_model -k "qwen2" &&
pytest -v -s models/multimodal/generation/test_ultravox.py -m core_model'
- label: "Multi-Modal Models (Standard) 2: qwen3 + gemma"
key: multi-modal-models-standard-2-qwen3-gemma
timeout_in_minutes: 70
timeout_in_minutes: 45
device: intel_gpu
agent_tags:
label: production
@@ -47,17 +22,19 @@ steps:
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
pytest -v -s models/multimodal/generation/test_qwen2_5_vl.py -m core_model'
'pip install av git+https://github.com/TIGER-AI-Lab/Mantis.git &&
cd tests &&
pytest -v -s models/multimodal/generation/test_common.py -m core_model -k "qwen2" &&
pytest -v -s models/multimodal/generation/test_ultravox.py -m core_model'
- label: "Multi-Modal Models (Standard) 3: llava + qwen2_vl"
key: multi-modal-models-standard-3-llava-qwen2-vl
timeout_in_minutes: 65
- label: "Multi-Modal Models (Standard) 2: qwen3 + gemma"
key: multi-modal-models-standard-2-qwen3-gemma
timeout_in_minutes: 45
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 24+
mem: 16+
no_plugin: true
working_dir: "."
env:
@@ -70,12 +47,12 @@ steps:
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
pytest -v -s models/multimodal/generation/test_common.py -m core_model -k "not qwen2 and not qwen3 and not gemma" &&
pytest -v -s models/multimodal/generation/test_qwen2_vl.py -m core_model'
'pip install git+https://github.com/TIGER-AI-Lab/Mantis.git &&
cd tests &&
pytest -v -s models/multimodal/generation/test_qwen2_5_vl.py -m core_model'
- label: "Multi-Modal Models (Standard) 4: other + whisper"
key: multi-modal-models-standard-4-other-whisper
- label: "Multi-Modal Models (Standard) 3: llava + qwen2_vl"
key: multi-modal-models-standard-3-llava-qwen2-vl
timeout_in_minutes: 45
device: intel_gpu
agent_tags:
@@ -94,18 +71,43 @@ steps:
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'pip install av &&
'pip install git+https://github.com/TIGER-AI-Lab/Mantis.git &&
cd tests &&
pytest -v -s models/multimodal/generation/test_common.py -m core_model -k "not qwen2 and not qwen3 and not gemma" &&
pytest -v -s models/multimodal/generation/test_qwen2_vl.py -m core_model'
- label: "Multi-Modal Models (Standard) 4: other + whisper"
key: multi-modal-models-standard-4-other-whisper
timeout_in_minutes: 45
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/
- tests/models/multimodal
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'pip install av git+https://github.com/TIGER-AI-Lab/Mantis.git &&
cd tests &&
pytest -v -s models/multimodal -m core_model --ignore models/multimodal/generation/test_common.py --ignore models/multimodal/generation/test_ultravox.py --ignore models/multimodal/generation/test_qwen2_5_vl.py --ignore models/multimodal/generation/test_qwen2_vl.py --ignore models/multimodal/generation/test_whisper.py --ignore models/multimodal/generation/test_memory_leak.py --ignore models/multimodal/processing'
- label: Multi-Modal Processor # 44min
key: multi-modal-processor
timeout_in_minutes: 60
timeout_in_minutes: 45
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 24+
mem: 16+
no_plugin: true
working_dir: "."
env:
@@ -119,9 +121,11 @@ steps:
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'pip install av matplotlib ftfy &&
'pip install av matplotlib ftfy git+https://github.com/TIGER-AI-Lab/Mantis.git &&
pip install open-clip-torch --no-deps &&
cd tests &&
pytest -v -s models/multimodal/processing/test_tensor_schema.py
--deselect "tests/models/multimodal/processing/test_tensor_schema.py::test_model_tensor_schema[mistralai/Mistral-Large-3-675B-Instruct-2512-NVFP4]"
--deselect "tests/models/multimodal/processing/test_tensor_schema.py::test_model_tensor_schema[Qwen/Qwen2.5-Omni-7B-AWQ]"
--num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB'
parallelism: 4
-28
View File
@@ -1,28 +0,0 @@
group: Quantization
depends_on:
- image-build-xpu
steps:
- label: Quantization
key: quantization
timeout_in_minutes: 30
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
no_plugin: true
working_dir: "."
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
source_file_dependencies:
- csrc/
- vllm/model_executor/layers/quantization
- tests/quantization
commands:
# - VLLM_TEST_FORCE_LOAD_FORMAT=auto pytest -v -s quantization/ --ignore quantization/test_blackwell_moe.py
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'VLLM_TEST_FORCE_LOAD_FORMAT=auto pytest -v -s tests/quantization/test_per_token_kv_cache.py --deselect="tests/quantization/test_per_token_kv_cache.py::test_triton_unified_attention_per_token_head_scale[int4-16-128-num_heads0-seq_lens1]"'
+6 -54
View File
@@ -17,7 +17,7 @@ steps:
- label: "XPU example Test"
depends_on:
- image-build-xpu
timeout_in_minutes: 50
timeout_in_minutes: 30
device: intel_gpu
agent_tags:
label: production
@@ -42,46 +42,21 @@ steps:
python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager --kv-cache-dtype fp8 &&
python3 examples/basic/offline_inference/generate.py --model nvidia/Llama-3.1-8B-Instruct-FP8 --block-size 64 --enforce-eager --quantization modelopt --kv-cache-dtype fp8 --attention-backend TRITON_ATTN --max-model-len 4096 &&
python3 examples/basic/offline_inference/generate.py --model superjob/Qwen3-4B-Instruct-2507-GPTQ-Int4 --block-size 64 --enforce-eager --max-model-len 8192 &&
python3 examples/basic/offline_inference/generate.py --model TheBloke/TinyLlama-1.1B-Chat-v0.3-AWQ --block-size 64 --enforce-eager &&
python3 examples/basic/offline_inference/generate.py --model ibm-research/PowerMoE-3b --block-size 64 --enforce-eager -tp 2 &&
python3 examples/basic/offline_inference/generate.py --model ibm-research/PowerMoE-3b --block-size 64 --enforce-eager -tp 2 --enable-expert-parallel &&
python3 examples/basic/offline_inference/generate.py --model superjob/Qwen3-4B-Instruct-2507-GPTQ-Int4 --max-model-len 8192 &&
VLLM_XPU_FUSED_MOE_USE_REF=1 python3 examples/basic/offline_inference/generate.py --model Qwen/Qwen3-30B-A3B-Instruct-2507-FP8 --enforce-eager -tp 2 --max-model-len 8192 &&
python3 examples/basic/offline_inference/generate.py --model INCModel/Qwen3-30B-A3B-Instruct-2507-MXFP4-LLMC --enforce-eager -tp 2 --max-model-len 8192
'
- label: "XPU W8A8 FP8 Linear Examples"
depends_on:
- image-build-xpu
timeout_in_minutes: 60
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 24+
no_plugin: true
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/
- .buildkite/intel_jobs/test-intel.yaml
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'python3 examples/basic/offline_inference/generate.py --linear-backend xpu --model RedHatAI/Meta-Llama-3.1-8B-Instruct-FP8 --enforce-eager --max-model-len 4096 &&
python3 examples/basic/offline_inference/generate.py --linear-backend xpu --model neuralmagic/Llama-3.2-1B-Instruct-FP8-dynamic --enforce-eager --max-model-len 4096 &&
python3 examples/basic/offline_inference/generate.py --linear-backend xpu --model meta-llama/Llama-3.2-1B-Instruct --quantization fp8 --enforce-eager --max-model-len 4096
'
- label: "XPU V1 test"
depends_on:
- image-build-xpu
timeout_in_minutes: 70
timeout_in_minutes: 30
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 24+
mem: 16+
no_plugin: true
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
@@ -93,19 +68,19 @@ steps:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
bash v1/kv_connector/nixl_integration/run_xpu_disagg_accuracy_test.sh &&
pytest -v -s v1/core --ignore=v1/core/test_reset_prefix_cache_e2e.py --ignore=v1/core/test_scheduler_e2e.py &&
pytest -v -s v1/engine --ignore=v1/engine/test_output_processor.py &&
pytest -v -s v1/sample --ignore=v1/sample/test_logprobs.py --ignore=v1/sample/test_logprobs_e2e.py -k "not test_topk_only and not test_topp_only and not test_topk_and_topp" &&
pytest -v -s v1/worker --ignore=v1/worker/test_gpu_model_runner.py --ignore=v1/worker/test_worker_memory_snapshot.py &&
pytest -v -s v1/structured_output &&
pytest -v -s v1/test_serial_utils.py &&
pytest -v -s v1/e2e/general/test_correctness_sliding_window.py --deselect="tests/v1/e2e/general/test_correctness_sliding_window.py::test_sliding_window_retrieval[True-1-5-google/gemma-3-1b-it]" &&
pytest -v -s v1/spec_decode --ignore=v1/spec_decode/test_max_len.py --ignore=v1/spec_decode/test_speculators_eagle3.py --ignore=v1/spec_decode/test_acceptance_length.py --ignore=v1/spec_decode/test_speculators_correctness.py &&
pytest -v -s v1/kv_connector/unit --ignore=v1/kv_connector/unit/test_multi_connector.py --ignore=v1/kv_connector/unit/test_example_connector.py --ignore=v1/kv_connector/unit/test_lmcache_integration.py --ignore=v1/kv_connector/unit/test_hf3fs_client.py --ignore=v1/kv_connector/unit/test_hf3fs_connector.py --ignore=v1/kv_connector/unit/test_hf3fs_metadata_server.py --ignore=v1/kv_connector/unit/test_offloading_connector.py'
- label: "XPU server test"
depends_on:
- image-build-xpu
timeout_in_minutes: 45
timeout_in_minutes: 30
device: intel_gpu
agent_tags:
label: production
@@ -145,27 +120,4 @@ steps:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
pytest -v -s quantization/test_auto_round.py'
- label: "XPU compressed tensors FP8 test"
depends_on:
- image-build-xpu
timeout_in_minutes: 60
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/
- tests/quantization/test_compressed_tensors.py
- .buildkite/intel_jobs/test-intel.yaml
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
pytest -v -s quantization/test_compressed_tensors.py::test_compressed_tensors_fp8'
pytest -v -s quantization/test_auto_round.py'
@@ -1,7 +1,6 @@
# For hf script, without -t option (tensor parallel size).
# bash .buildkite/lm-eval-harness/run-lm-eval-mmlupro-vllm-baseline.sh -m meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8 -l 250 -t 8 -f 5
model_name: "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8"
rocm_safetensors_load_strategy: lazy
required_gpu_arch:
- gfx942
- gfx950
@@ -72,11 +72,6 @@ def launch_lm_eval(eval_config, tp_size):
if moe_backend is not None:
model_args += f"moe_backend={moe_backend},"
if current_platform.is_rocm():
rocm_load_strategy = eval_config.get("rocm_safetensors_load_strategy")
if rocm_load_strategy is not None:
model_args += f"safetensors_load_strategy={rocm_load_strategy},"
env_vars = eval_config.get("env_vars", None)
with scoped_env_vars(env_vars):
results = lm_eval.simple_evaluate(
File diff suppressed because it is too large Load Diff
@@ -3,8 +3,7 @@
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
#
# Append a build artifact line to the Buildkite annotation.
# Usage: annotate-build-artifact.sh <label> <value> <context>
# Usage: annotate-build-artifact.sh <label> <value>
set -e
echo "- **${1}**: \`${2}\`" | \
buildkite-agent annotate --append --style 'info' \
--context "${3:?context is required}"
buildkite-agent annotate --append --style 'info' --context 'release-artifacts'
@@ -1,36 +0,0 @@
#!/bin/bash
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
#
# Append the Docker image tag(s) an image-build step pushed to a Buildkite
# annotation, so the built image tags show up on the build page instead of
# being buried in the job logs.
#
# Usage: annotate-image-build.sh <image_tag> [<image_tag> ...]
set -euo pipefail
# buildkite-agent only exists on Buildkite agents; no-op elsewhere so the
# image build scripts stay runnable locally.
if ! command -v buildkite-agent >/dev/null 2>&1; then
echo "buildkite-agent not found; skipping image tag annotation"
exit 0
fi
label="${BUILDKITE_LABEL:-Image build}"
content=""
for image in "$@"; do
[[ -n "$image" ]] || continue
content+="- **${label}**: \`${image}\`"$'\n'
done
if [[ -z "$content" ]]; then
echo "No image tags provided; nothing to annotate"
exit 0
fi
# Best-effort: a flaky annotation must never fail an otherwise successful
# (and expensive) image build.
if ! printf '%s' "$content" | \
buildkite-agent annotate --append --style 'info' --context 'docker-images'; then
echo "warning: failed to annotate build with image tags"
fi
-32
View File
@@ -1,32 +0,0 @@
#!/usr/bin/env bash
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
#
# Build the macOS arm64 CPU wheel natively on a macOS agent (the `macmini`
# queue) into artifacts/dist/ for upload-nightly-wheels.sh.
set -euo pipefail
# The Rust frontend build needs protoc.
if ! command -v protoc >/dev/null 2>&1; then
brew install protobuf
fi
# upload-nightly-wheels.sh expects exactly one wheel.
rm -rf artifacts/dist
mkdir -p artifacts/dist
export VLLM_TARGET_DEVICE=cpu
export VLLM_REQUIRE_RUST_FRONTEND=1
export MACOSX_DEPLOYMENT_TARGET=11.0
# uv's CPython is universal2; force an arm64-only build and tag so the wheel
# isn't mislabelled universal2 and installed on Intel Macs where import fails.
export ARCHFLAGS="-arch arm64"
export _PYTHON_HOST_PLATFORM="macosx-11.0-arm64"
export CMAKE_BUILD_PARALLEL_LEVEL="${CMAKE_BUILD_PARALLEL_LEVEL:-4}"
uv venv --python 3.12
uv pip install -r requirements/build/cpu.txt --index-strategy unsafe-best-match
uv build --wheel --no-build-isolation -o artifacts/dist
ls -l artifacts/dist/*.whl
@@ -29,11 +29,7 @@ if python3 -c "import torch; assert torch.version.hip" 2>/dev/null; then
TORCH_INDEX_URL=""
fi
else
if [ "${TORCH_NIGHTLY:-0}" = "1" ]; then
TORCH_INDEX_URL="https://download.pytorch.org/whl/nightly/cu130"
else
TORCH_INDEX_URL="https://download.pytorch.org/whl/cu130"
fi
TORCH_INDEX_URL="https://download.pytorch.org/whl/cu130"
fi
echo ">>> Using PyTorch index: ${TORCH_INDEX_URL:-PyPI default}"
+53 -480
View File
@@ -15,10 +15,9 @@ set -euo pipefail
DEFAULT_REPO_SLUG="vllm-project/vllm"
DEFAULT_CI_HCL_SOURCE="docker/ci-rocm.hcl"
DEFAULT_CI_BASE_CONTENT_FILES="requirements/common.txt requirements/rocm.txt requirements/test/rocm.txt docker/Dockerfile.rocm_base docker/ci-rocm.hcl docker/docker-bake-rocm.hcl tools/install_torchcodec_rocm.sh tools/install_protoc.sh rust-toolchain.toml tests/vllm_test_utils .buildkite/scripts/ci-bake-rocm.sh .buildkite/scripts/rocm/build-ci-base.sh"
DEFAULT_CI_BASE_CONTENT_FILES="requirements/common.txt requirements/rocm.txt requirements/test/rocm.txt docker/Dockerfile.rocm_base tools/install_torchcodec_rocm.sh tests/vllm_test_utils"
DEFAULT_CI_BASE_DOCKERFILE="docker/Dockerfile.rocm"
DEFAULT_CI_BASE_DOCKERFILE_STAGES="base rust_toolchain_input_0 rust_toolchain_input_1 rust-toolchain-input rust-toolchain build_rixl build_rocshmem build_deepep mori_base ci_base"
DEFAULT_CI_BASE_METADATA_VERSION="1"
DEFAULT_CI_BASE_DOCKERFILE_STAGES="base build_rixl build_rocshmem build_deepep mori_base ci_base"
IMAGE_EXISTED_BEFORE_BUILD=0
TARGET=""
@@ -285,7 +284,7 @@ get_content_arg_names() {
fi | awk 'NF && !seen[$0]++'
}
compute_ci_base_content_hash_once() {
compute_ci_base_content_hash() {
local -a content_paths=()
local -a content_args=()
local dockerfile="${CI_BASE_DOCKERFILE:-}"
@@ -301,8 +300,7 @@ compute_ci_base_content_hash_once() {
if [[ -n "${dockerfile}" ]]; then
printf 'dockerfile:%s\n' "${dockerfile}"
printf 'resolved-build-args:\n'
hash_dockerfile_arg_values "${dockerfile}" "${content_args[@]}" \
|| return 1
hash_dockerfile_arg_values "${dockerfile}" "${content_args[@]}"
if [[ -n "${stages}" ]]; then
printf 'dockerfile-stages:%s\n' "${stages}"
if [[ -f "${dockerfile}" ]]; then
@@ -315,53 +313,6 @@ compute_ci_base_content_hash_once() {
} | sha256sum | cut -d' ' -f1
}
compute_ci_base_content_hash() {
local attempts="${CI_BASE_HASH_ATTEMPTS:-3}"
local delay_secs="${CI_BASE_HASH_RETRY_DELAY:-5}"
local attempt=0
local hash=""
local failed=0
local -a hashes=()
if [[ ! "${attempts}" =~ ^[1-9][0-9]*$ ]]; then
echo "Invalid CI_BASE_HASH_ATTEMPTS: ${attempts}" >&2
return 1
fi
if [[ ! "${delay_secs}" =~ ^[0-9]+$ ]]; then
echo "Invalid CI_BASE_HASH_RETRY_DELAY: ${delay_secs}" >&2
return 1
fi
for ((attempt = 1; attempt <= attempts; attempt++)); do
if ! hash=$(compute_ci_base_content_hash_once); then
echo "ci_base content hash calculation ${attempt}/${attempts} failed" >&2
failed=1
else
hashes+=("${hash}")
echo "ci_base content hash calculation ${attempt}/${attempts}: ${hash}" >&2
fi
if ((attempt < attempts)); then
sleep "${delay_secs}"
fi
done
if ((failed)) || ((${#hashes[@]} != attempts)); then
echo "Could not calculate a reliable ci_base content hash" >&2
return 1
fi
for hash in "${hashes[@]:1}"; do
if [[ "${hash}" != "${hashes[0]}" ]]; then
echo "ci_base content hash changed between calculations" >&2
printf ' observed: %s\n' "${hashes[@]}" >&2
return 1
fi
done
printf '%s\n' "${hashes[0]}"
}
extract_dockerfile_arg_default() {
local dockerfile="$1"
local arg_name="$2"
@@ -414,11 +365,7 @@ hash_dockerfile_arg_values() {
printf 'arg:%s=%s\n' "${arg_name}" "${arg_value:-<empty>}"
if [[ "${arg_name}" == "BASE_IMAGE" && -n "${arg_value}" ]]; then
digest=$(resolve_image_digest "${arg_value}")
if [[ -z "${digest}" ]]; then
echo "Failed to resolve digest for BASE_IMAGE=${arg_value}" >&2
return 1
fi
printf 'arg:%s.digest=%s\n' "${arg_name}" "${digest}"
printf 'arg:%s.digest=%s\n' "${arg_name}" "${digest:-unknown}"
fi
done
}
@@ -445,16 +392,6 @@ should_upload_wheel_artifacts() {
|| "${TARGET}" == *"artifact"* ]]
}
set_buildkite_metadata() {
local key="$1"
local value="$2"
[[ -n "${value}" ]] || return 0
if command -v buildkite-agent >/dev/null 2>&1; then
buildkite-agent meta-data set "${key}" "${value}" || true
fi
}
get_remote_image_label() {
local image_ref="$1"
local label_key="$2"
@@ -588,22 +525,6 @@ get_remote_image_label_with_retry() {
return 0
}
remote_ci_base_metadata_is_current() {
local image_ref="$1"
local metadata_version=""
metadata_version=$(get_remote_image_label "${image_ref}" "vllm.ci_base.metadata_version")
[[ "${metadata_version}" == "${CI_BASE_METADATA_VERSION:-${DEFAULT_CI_BASE_METADATA_VERSION}}" ]]
}
remote_ci_base_metadata_is_current_with_retry() {
local image_ref="$1"
local metadata_version=""
metadata_version=$(get_remote_image_label_with_retry "${image_ref}" "vllm.ci_base.metadata_version")
[[ "${metadata_version}" == "${CI_BASE_METADATA_VERSION:-${DEFAULT_CI_BASE_METADATA_VERSION}}" ]]
}
remote_image_exists() {
local image_ref="$1"
docker manifest inspect "${image_ref}" >/dev/null 2>&1
@@ -660,7 +581,6 @@ init_config() {
CI_BASE_CONTENT_FILES="${CI_BASE_CONTENT_FILES:-${DEFAULT_CI_BASE_CONTENT_FILES}}"
CI_BASE_DOCKERFILE="${CI_BASE_DOCKERFILE:-${DEFAULT_CI_BASE_DOCKERFILE}}"
CI_BASE_DOCKERFILE_STAGES="${CI_BASE_DOCKERFILE_STAGES:-${DEFAULT_CI_BASE_DOCKERFILE_STAGES}}"
CI_BASE_METADATA_VERSION="${CI_BASE_METADATA_VERSION:-${DEFAULT_CI_BASE_METADATA_VERSION}}"
CI_BASE_IMAGE_TAG="${CI_BASE_IMAGE_TAG:-rocm/vllm-dev:ci_base}"
export PYTORCH_ROCM_ARCH
@@ -715,10 +635,6 @@ load_ci_hcl() {
echo "Copied ${CI_HCL_SOURCE} to ${CI_HCL_PATH}"
}
init_bake_files() {
BAKE_FILES=(-f "${VLLM_BAKE_FILE}" -f "${CI_HCL_PATH}")
}
compute_ci_base_hash_if_needed() {
if [[ -z "${CI_BASE_CONTENT_FILES:-}" ]]; then
return 0
@@ -760,14 +676,12 @@ configure_ci_base_image_refs() {
fi
content_tag=$(ci_base_tag_with_suffix "${stable_tag}" "${CI_BASE_CONTENT_HASH}")
CI_BASE_IMAGE_TAG_CONTENT_REF="${content_tag}"
if [[ -n "${BUILDKITE_COMMIT:-}" ]]; then
commit_tag=$(ci_base_tag_with_suffix "${stable_tag}" "${BUILDKITE_COMMIT}")
CI_BASE_IMAGE_TAG_COMMIT="${commit_tag}"
export CI_BASE_IMAGE_TAG_COMMIT
fi
CI_BASE_IMAGE_TAG_COMMIT_REF="${commit_tag}"
# *_REF is the logical tag recorded in metadata. *_EXTRA is only passed to
# bake when that tag is not already the primary tag, avoiding duplicates.
if should_push_stable_ci_base_tag; then
primary_tag="${content_tag}"
CI_BASE_IMAGE_TAG_STABLE="${stable_tag}"
@@ -777,35 +691,19 @@ configure_ci_base_image_refs() {
fi
CI_BASE_IMAGE_TAG="${primary_tag}"
if [[ "${primary_tag}" == "${content_tag}" ]]; then
CI_BASE_IMAGE_TAG_CONTENT_EXTRA=""
CI_BASE_IMAGE_TAG_CONTENT=""
else
CI_BASE_IMAGE_TAG_CONTENT_EXTRA="${content_tag}"
CI_BASE_IMAGE_TAG_CONTENT="${content_tag}"
fi
if [[ -n "${commit_tag}" && "${commit_tag}" != "${primary_tag}" ]]; then
CI_BASE_IMAGE_TAG_COMMIT_EXTRA="${commit_tag}"
else
CI_BASE_IMAGE_TAG_COMMIT_EXTRA=""
fi
export CI_BASE_IMAGE_TAG
export CI_BASE_IMAGE_TAG_COMMIT_EXTRA
export CI_BASE_IMAGE_TAG_CONTENT_EXTRA
export CI_BASE_IMAGE_TAG_CONTENT_REF
export CI_BASE_IMAGE_TAG_COMMIT_REF
export CI_BASE_IMAGE_TAG_STABLE
export CI_BASE_IMAGE_TAG CI_BASE_IMAGE_TAG_CONTENT CI_BASE_IMAGE_TAG_STABLE
if is_ci_base_target; then
IMAGE_TAG="${primary_tag}"
CI_BASE_IMAGE="${primary_tag}"
export CI_BASE_IMAGE
export IMAGE_TAG
echo "ci_base primary image tag: ${CI_BASE_IMAGE_TAG}"
if [[ -n "${commit_tag}" ]]; then
if [[ "${commit_tag}" == "${primary_tag}" ]]; then
echo "ci_base commit image tag: ${commit_tag} (primary)"
else
echo "ci_base commit image tag: ${commit_tag}"
fi
if [[ -n "${CI_BASE_IMAGE_TAG_COMMIT:-}" ]]; then
echo "ci_base commit image tag: ${CI_BASE_IMAGE_TAG_COMMIT}"
fi
echo "ci_base content image tag: ${content_tag}"
if [[ -n "${CI_BASE_IMAGE_TAG_STABLE}" ]]; then
@@ -814,10 +712,6 @@ configure_ci_base_image_refs() {
echo "ci_base stable alias will not be pushed for this build"
echo "Set NIGHTLY=1 on ${CI_BASE_STABLE_BRANCH:-main} to refresh ${stable_tag}"
fi
set_buildkite_metadata "rocm-ci-base-image" "${CI_BASE_IMAGE_TAG}"
set_buildkite_metadata "rocm-ci-base-image-content" "${content_tag}"
set_buildkite_metadata "rocm-ci-base-image-commit" "${CI_BASE_IMAGE_TAG_COMMIT_REF:-}"
set_buildkite_metadata "rocm-ci-base-image-stable" "${CI_BASE_IMAGE_TAG_STABLE:-}"
return 0
fi
@@ -834,8 +728,8 @@ ci_base_candidate_refs() {
printf '%s\n' \
"${IMAGE_TAG:-}" \
"${CI_BASE_IMAGE_TAG:-}" \
"${CI_BASE_IMAGE_TAG_COMMIT_EXTRA:-}" \
"${CI_BASE_IMAGE_TAG_CONTENT_EXTRA:-}" \
"${CI_BASE_IMAGE_TAG_COMMIT:-}" \
"${CI_BASE_IMAGE_TAG_CONTENT:-}" \
"${CI_BASE_IMAGE_TAG_STABLE:-}" \
| awk 'NF && !seen[$0]++'
}
@@ -849,10 +743,6 @@ find_matching_ci_base_ref() {
remote_image_exists "${candidate}" || continue
candidate_hash=$(get_remote_image_label "${candidate}" "vllm.ci_base.content_hash")
if [[ "${candidate_hash}" == "${CI_BASE_CONTENT_HASH}" ]]; then
if ! remote_ci_base_metadata_is_current "${candidate}"; then
echo "Found matching ci_base content hash but stale metadata: ${candidate}" >&2
continue
fi
printf '%s\n' "${candidate}"
return 0
fi
@@ -927,10 +817,6 @@ maybe_skip_existing_image() {
if [[ -n "${remote_hash}" ]]; then
echo "Remote ci_base content hash: ${remote_hash:0:16}..."
if [[ "${remote_hash}" == "${CI_BASE_CONTENT_HASH}" ]]; then
if ! remote_ci_base_metadata_is_current "${IMAGE_TAG}"; then
echo "Content hashes match but ci_base metadata is stale; rebuilding to refresh metadata"
return 0
fi
if ! refresh_ci_base_tags_from_ref "${IMAGE_TAG}"; then
echo "ci_base tag refresh failed; rebuilding to push expected tags"
return 0
@@ -1112,104 +998,12 @@ prepare_git_cache_metadata() {
fi
}
ci_base_metadata_pairs() {
local dockerfile="${CI_BASE_DOCKERFILE:-${DEFAULT_CI_BASE_DOCKERFILE}}"
local stages="${CI_BASE_DOCKERFILE_STAGES:-${DEFAULT_CI_BASE_DOCKERFILE_STAGES}}"
local content_files="${CI_BASE_CONTENT_FILES:-${DEFAULT_CI_BASE_CONTENT_FILES}}"
local content_files_hash=""
local base_image=""
local base_image_digest=""
local git_branch=""
local -a content_paths=()
local -a content_args=()
read -r -a content_paths <<< "${content_files}"
if [[ ${#content_paths[@]} -gt 0 ]]; then
content_files_hash=$(compute_content_hash "${content_paths[@]}")
fi
mapfile -t content_args < <(
get_content_arg_names "${dockerfile}" "${stages}" "${CI_BASE_CONTENT_ARGS:-}"
)
base_image=$(resolve_dockerfile_arg_value "${dockerfile}" "BASE_IMAGE")
if [[ -n "${base_image}" ]]; then
base_image_digest=$(resolve_image_digest "${base_image}")
fi
git_branch="${BUILDKITE_BRANCH:-${VLLM_BRANCH:-}}"
metadata_pair "vllm.ci_base.metadata_version" "${CI_BASE_METADATA_VERSION:-${DEFAULT_CI_BASE_METADATA_VERSION}}"
metadata_pair "vllm.ci_base.content_hash" "${CI_BASE_CONTENT_HASH:-}"
metadata_pair "vllm.ci_base.content_files_hash" "${content_files_hash}"
metadata_pair "vllm.ci_base.content_files" "${content_files}"
metadata_pair "vllm.ci_base.content_args" "$(join_words "${content_args[@]}")"
metadata_pair "vllm.ci_base.dockerfile" "${dockerfile}"
metadata_pair "vllm.ci_base.dockerfile_stages" "${stages}"
metadata_pair "vllm.ci_base.image.primary" "${CI_BASE_IMAGE_TAG:-}"
metadata_pair "vllm.ci_base.image.content" "${CI_BASE_IMAGE_TAG_CONTENT_REF:-${CI_BASE_IMAGE_TAG_CONTENT_EXTRA:-}}"
metadata_pair "vllm.ci_base.image.commit" "${CI_BASE_IMAGE_TAG_COMMIT_REF:-${CI_BASE_IMAGE_TAG_COMMIT_EXTRA:-}}"
metadata_pair "vllm.ci_base.image.stable" "${CI_BASE_IMAGE_TAG_STABLE:-}"
metadata_pair "vllm.ci_base.git_commit" "${BUILDKITE_COMMIT:-}"
metadata_pair "vllm.ci_base.git_branch" "${git_branch}"
metadata_pair "vllm.ci_base.vllm_branch" "${VLLM_BRANCH:-}"
metadata_pair "vllm.ci_base.stable_branch" "${CI_BASE_STABLE_BRANCH:-main}"
metadata_pair "vllm.rocm.base_image" "${base_image}"
metadata_pair "vllm.rocm.base_image_digest" "${base_image_digest}"
metadata_pair "vllm.rocm.pytorch_rocm_arch" "${PYTORCH_ROCM_ARCH:-}"
metadata_pair "vllm.rocm.nic_backend" "$(resolve_dockerfile_arg_value "${dockerfile}" "NIC_BACKEND")"
metadata_pair "vllm.rocm.ainic_version" "$(resolve_dockerfile_arg_value "${dockerfile}" "AINIC_VERSION")"
metadata_pair "vllm.rocm.ubuntu_codename" "$(resolve_dockerfile_arg_value "${dockerfile}" "UBUNTU_CODENAME")"
metadata_pair "vllm.rocm.rixl_repo" "$(resolve_dockerfile_arg_value "${dockerfile}" "RIXL_REPO")"
metadata_pair "vllm.rocm.rixl_commit" "${RIXL_BRANCH:-$(resolve_dockerfile_arg_value "${dockerfile}" "RIXL_BRANCH")}"
metadata_pair "vllm.rocm.ucx_repo" "$(resolve_dockerfile_arg_value "${dockerfile}" "UCX_REPO")"
metadata_pair "vllm.rocm.ucx_commit" "${UCX_BRANCH:-$(resolve_dockerfile_arg_value "${dockerfile}" "UCX_BRANCH")}"
metadata_pair "vllm.rocm.rocshmem_repo" "$(resolve_dockerfile_arg_value "${dockerfile}" "ROCSHMEM_REPO")"
metadata_pair "vllm.rocm.rocshmem_commit" "${ROCSHMEM_BRANCH:-$(resolve_dockerfile_arg_value "${dockerfile}" "ROCSHMEM_BRANCH")}"
metadata_pair "vllm.rocm.deepep_repo" "$(resolve_dockerfile_arg_value "${dockerfile}" "DEEPEP_REPO")"
metadata_pair "vllm.rocm.deepep_commit" "${DEEPEP_BRANCH:-$(resolve_dockerfile_arg_value "${dockerfile}" "DEEPEP_BRANCH")}"
metadata_pair "vllm.rocm.deepep_nic" "$(resolve_dockerfile_arg_value "${dockerfile}" "DEEPEP_NIC")"
metadata_pair "vllm.rocm.deepep_rocm_arch" "$(resolve_dockerfile_arg_value "${dockerfile}" "DEEPEP_ROCM_ARCH")"
metadata_pair "vllm.rocm.rixl_cache_key" "${RIXL_CACHE_KEY:-}"
metadata_pair "vllm.rocm.rocshmem_cache_key" "${ROCSHMEM_CACHE_KEY:-}"
metadata_pair "vllm.rocm.deepep_cache_key" "${DEEPEP_CACHE_KEY:-}"
metadata_pair "vllm.buildkite.build_number" "${BUILDKITE_BUILD_NUMBER:-}"
metadata_pair "vllm.buildkite.build_id" "${BUILDKITE_BUILD_ID:-}"
}
write_ci_base_metadata_annotations() {
local metadata="$1"
local key=""
local value=""
local annotation=""
[[ -n "${metadata}" ]] || return 0
while IFS=$'\t' read -r key value; do
[[ -n "${key}" && -n "${value}" ]] || continue
annotation="manifest:${key}=${value}"
printf ' "%s",\n' "$(hcl_escape_string "${annotation}")"
done <<< "${metadata}"
}
write_ci_base_metadata_labels() {
local metadata="$1"
local key=""
local value=""
[[ -n "${metadata}" ]] || return 0
while IFS=$'\t' read -r key value; do
[[ -n "${key}" && -n "${value}" ]] || continue
printf ' "%s" = "%s"\n' \
"$(hcl_escape_string "${key}")" \
"$(hcl_escape_string "${value}")"
done <<< "${metadata}"
}
write_ci_base_label_override() {
local target_name=""
local metadata=""
local -a ci_base_targets=()
BAKE_FILES=(-f "${VLLM_BAKE_FILE}" -f "${CI_HCL_PATH}")
if [[ -z "${CI_BASE_CONTENT_HASH:-}" ]]; then
return 0
fi
@@ -1225,23 +1019,16 @@ write_ci_base_label_override() {
return 0
fi
metadata=$(ci_base_metadata_pairs)
: > "${CI_BASE_LABEL_OVERRIDE_PATH}"
for target_name in "${ci_base_targets[@]}"; do
cat >> "${CI_BASE_LABEL_OVERRIDE_PATH}" <<EOF
target "${target_name}" {
annotations = [
"manifest:org.opencontainers.image.revision=",
EOF
write_ci_base_metadata_annotations "${metadata}" >> "${CI_BASE_LABEL_OVERRIDE_PATH}"
cat >> "${CI_BASE_LABEL_OVERRIDE_PATH}" <<EOF
]
labels = {
"org.opencontainers.image.revision" = ""
EOF
write_ci_base_metadata_labels "${metadata}" >> "${CI_BASE_LABEL_OVERRIDE_PATH}"
cat >> "${CI_BASE_LABEL_OVERRIDE_PATH}" <<EOF
"vllm.ci_base.content_hash" = "${CI_BASE_CONTENT_HASH}"
}
}
@@ -1249,7 +1036,7 @@ EOF
done
BAKE_FILES+=(-f "${CI_BASE_LABEL_OVERRIDE_PATH}")
echo "Appended ci_base metadata label override for targets: ${ci_base_targets[*]}"
echo "Appended ci_base content-hash label override for targets: ${ci_base_targets[*]}"
}
uses_rocm_csrc_cache() {
@@ -1263,24 +1050,12 @@ uses_rocm_csrc_cache() {
esac
}
uses_rocm_rust_cache() {
case "${TARGET}" in
rust-rocm-ci|test-rocm-ci|test-rocm-ci-with-wheel|test-rocm-ci-with-artifacts|export-wheel-rocm)
return 0
;;
*)
return 1
;;
esac
}
compute_rocm_csrc_content_hash() {
local bake_dir=""
local dockerfile_rocm=""
local -a content_paths=(
"requirements/common.txt"
"requirements/rocm.txt"
"pyproject.toml"
"setup.py"
"CMakeLists.txt"
"cmake"
@@ -1324,56 +1099,6 @@ compute_rocm_csrc_content_hash_if_needed() {
echo "ROCm csrc content cache ref: ${ROCM_CSRC_CONTENT_CACHE_REF}"
}
compute_rocm_rust_content_hash() {
local bake_dir=""
local dockerfile_rocm=""
local -a content_paths=(
"requirements/build/rust.txt"
"rust/Cargo.lock"
"rust/Cargo.toml"
"rust/proto"
"rust/src"
"rust-toolchain.toml"
"tools/build_rust.py"
"tools/install_protoc.sh"
"build_rust.sh"
)
local -a content_args=()
bake_dir=$(dirname "${VLLM_BAKE_FILE}")
dockerfile_rocm="${bake_dir}/Dockerfile.rocm"
mapfile -t content_args < <(
get_content_arg_names "${dockerfile_rocm}" "base rust_toolchain_input_0 rust_toolchain_input_1 rust-toolchain-input rust_input_0 rust_input_1 rust-input rust-toolchain rust-build" "${ROCM_RUST_CONTENT_ARGS:-}"
)
{
printf 'rust-input-files-hash:%s\n' "$(compute_content_hash "${content_paths[@]}")"
printf 'dockerfile:%s\n' "${dockerfile_rocm}"
printf 'resolved-build-args:\n'
hash_dockerfile_arg_values "${dockerfile_rocm}" "${content_args[@]}"
printf 'dockerfile-stages:base rust_toolchain_input_0 rust_toolchain_input_1 rust-toolchain-input rust_input_0 rust_input_1 rust-input rust-toolchain rust-build\n'
if [[ -f "${dockerfile_rocm}" ]]; then
hash_dockerfile_stages "${dockerfile_rocm}" "base rust_toolchain_input_0 rust_toolchain_input_1 rust-toolchain-input rust_input_0 rust_input_1 rust-input rust-toolchain rust-build"
else
printf 'missing:%s\n' "${dockerfile_rocm}"
fi
} | sha256sum | cut -d' ' -f1
}
compute_rocm_rust_content_hash_if_needed() {
local cache_repo="${DOCKERHUB_CACHE_REPO:-rocm/vllm-ci-cache}"
if [[ "${ROCM_RUST_CONTENT_CACHE:-1}" == "0" ]] || ! uses_rocm_rust_cache; then
return 0
fi
ROCM_RUST_CONTENT_HASH=$(compute_rocm_rust_content_hash)
ROCM_RUST_CONTENT_CACHE_REF="${cache_repo}:rust-rocm-input-${ROCM_RUST_CONTENT_HASH}"
export ROCM_RUST_CONTENT_HASH
export ROCM_RUST_CONTENT_CACHE_REF
echo "ROCm Rust content cache ref: ${ROCM_RUST_CONTENT_CACHE_REF}"
}
write_hcl_string_list_entries() {
local indent="$1"
local value=""
@@ -1394,18 +1119,6 @@ hcl_escape_string() {
printf '%s' "${value}"
}
join_words() {
local IFS=" "
printf '%s' "$*"
}
metadata_pair() {
local key="$1"
local value="${2:-}"
printf '%s\t%s\n' "${key}" "${value}"
}
write_hcl_string_list() {
local indent="$1"
shift
@@ -1431,7 +1144,6 @@ write_rocm_build_arg_override() {
"${CI_BASE_DOCKERFILE_STAGES:-${DEFAULT_CI_BASE_DOCKERFILE_STAGES}}" \
"${CI_BASE_CONTENT_ARGS:-}"
get_content_arg_names "${dockerfile_rocm}" "base csrc-build" "${ROCM_CSRC_CONTENT_ARGS:-}"
get_content_arg_names "${dockerfile_rocm}" "base rust_toolchain_input_0 rust_toolchain_input_1 rust-toolchain-input rust_input_0 rust_input_1 rust-input rust-toolchain rust-build" "${ROCM_RUST_CONTENT_ARGS:-}"
} | awk 'NF && !seen[$0]++'
)
@@ -1480,133 +1192,46 @@ validate_cache_export_mode() {
esac
}
validate_content_cache_export_mode() {
local mode="$1"
local env_name="$2"
case "${mode}" in
missing|always|never)
;;
*)
echo "Error: ${env_name} must be one of: missing, always, never"
exit 1
;;
esac
}
should_export_content_cache_ref() {
local cache_ref="$1"
local cache_name="$2"
local mode="${ROCM_CONTENT_CACHE_EXPORT_MODE:-missing}"
case "${mode}" in
always)
echo "${cache_name} content cache export mode is always; exporting ${cache_ref}"
return 0
;;
never)
echo "${cache_name} content cache export mode is never; not exporting ${cache_ref}"
return 1
;;
missing|"")
if docker buildx imagetools inspect "${cache_ref}" >/dev/null 2>&1; then
echo "${cache_name} content cache exists; not re-exporting ${cache_ref}"
return 1
fi
echo "${cache_name} content cache missing; will export ${cache_ref}"
return 0
;;
*)
echo "Error: ROCM_CONTENT_CACHE_EXPORT_MODE must be one of: missing, always, never"
exit 1
;;
esac
}
write_rocm_cache_override() {
local cache_repo="${DOCKERHUB_CACHE_REPO:-rocm/vllm-ci-cache}"
local content_cache_export_mode="${ROCM_CONTENT_CACHE_EXPORT_MODE:-missing}"
local csrc_cache_to_mode="${ROCM_CSRC_CACHE_TO_MODE:-max}"
local rust_cache_to_mode="${ROCM_RUST_CACHE_TO_MODE:-max}"
local rocm_cache_to_mode="${ROCM_FINAL_CACHE_TO_MODE:-min}"
local -a csrc_content_cache_from=()
local -a rust_content_cache_from=()
local -a combined_content_cache_from=()
local -a content_cache_from=()
local -a csrc_cache_to=()
local -a rust_cache_to=()
local -a rocm_cache_to=()
local -a export_wheel_cache_to=()
local export_csrc_cache=1
local export_rust_cache=1
if ! uses_rocm_csrc_cache && ! uses_rocm_rust_cache; then
if ! uses_rocm_csrc_cache; then
return 0
fi
validate_content_cache_export_mode \
"${content_cache_export_mode}" \
"ROCM_CONTENT_CACHE_EXPORT_MODE"
validate_cache_export_mode "${csrc_cache_to_mode}" "ROCM_CSRC_CACHE_TO_MODE"
validate_cache_export_mode "${rust_cache_to_mode}" "ROCM_RUST_CACHE_TO_MODE"
validate_cache_export_mode "${rocm_cache_to_mode}" "ROCM_FINAL_CACHE_TO_MODE"
echo "ROCm content cache export mode: ${content_cache_export_mode}"
echo "ROCm csrc cache export mode: ${csrc_cache_to_mode}"
echo "ROCm Rust cache export mode: ${rust_cache_to_mode}"
echo "ROCm final image cache export mode: ${rocm_cache_to_mode}"
if [[ -n "${ROCM_CSRC_CONTENT_CACHE_REF:-}" ]]; then
csrc_content_cache_from+=("type=registry,ref=${ROCM_CSRC_CONTENT_CACHE_REF}")
if should_export_content_cache_ref "${ROCM_CSRC_CONTENT_CACHE_REF}" "ROCm csrc"; then
csrc_cache_to+=(
"type=registry,ref=${ROCM_CSRC_CONTENT_CACHE_REF},mode=${csrc_cache_to_mode},ignore-error=true"
)
else
export_csrc_cache=0
fi
content_cache_from+=("type=registry,ref=${ROCM_CSRC_CONTENT_CACHE_REF}")
csrc_cache_to+=(
"type=registry,ref=${ROCM_CSRC_CONTENT_CACHE_REF},mode=${csrc_cache_to_mode},ignore-error=true"
)
fi
if [[ -n "${ROCM_RUST_CONTENT_CACHE_REF:-}" ]]; then
rust_content_cache_from+=("type=registry,ref=${ROCM_RUST_CONTENT_CACHE_REF}")
if should_export_content_cache_ref "${ROCM_RUST_CONTENT_CACHE_REF}" "ROCm Rust"; then
rust_cache_to+=(
"type=registry,ref=${ROCM_RUST_CONTENT_CACHE_REF},mode=${rust_cache_to_mode},ignore-error=true"
)
else
export_rust_cache=0
fi
fi
combined_content_cache_from=("${csrc_content_cache_from[@]}" "${rust_content_cache_from[@]}")
# Docker Hub cache exports are best-effort. A cache-only target failure can
# otherwise cancel the sibling image target before its manifest is pushed.
if [[ -n "${BUILDKITE_COMMIT:-}" ]]; then
if [[ ${export_csrc_cache} -eq 1 ]]; then
csrc_cache_to+=(
"type=registry,ref=${cache_repo}:csrc-rocm-${BUILDKITE_COMMIT},mode=${csrc_cache_to_mode},ignore-error=true"
)
fi
if [[ ${export_rust_cache} -eq 1 ]]; then
rust_cache_to+=(
"type=registry,ref=${cache_repo}:rust-rocm-${BUILDKITE_COMMIT},mode=${rust_cache_to_mode},ignore-error=true"
)
fi
csrc_cache_to+=(
"type=registry,ref=${cache_repo}:csrc-rocm-${BUILDKITE_COMMIT},mode=${csrc_cache_to_mode},ignore-error=true"
)
rocm_cache_to+=(
"type=registry,ref=${cache_repo}:rocm-${BUILDKITE_COMMIT},mode=${rocm_cache_to_mode},ignore-error=true"
)
fi
if [[ -n "${ROCM_CACHE_BRANCH_TAG:-}" ]]; then
if [[ ${export_csrc_cache} -eq 1 ]]; then
csrc_cache_to+=(
"type=registry,ref=${cache_repo}:csrc-rocm-branch-${ROCM_CACHE_BRANCH_TAG},mode=${csrc_cache_to_mode},ignore-error=true"
)
fi
if [[ ${export_rust_cache} -eq 1 ]]; then
rust_cache_to+=(
"type=registry,ref=${cache_repo}:rust-rocm-branch-${ROCM_CACHE_BRANCH_TAG},mode=${rust_cache_to_mode},ignore-error=true"
)
fi
csrc_cache_to+=(
"type=registry,ref=${cache_repo}:csrc-rocm-branch-${ROCM_CACHE_BRANCH_TAG},mode=${csrc_cache_to_mode},ignore-error=true"
)
rocm_cache_to+=(
"type=registry,ref=${cache_repo}:rocm-branch-${ROCM_CACHE_BRANCH_TAG},mode=${rocm_cache_to_mode},ignore-error=true"
)
@@ -1624,7 +1249,7 @@ target "csrc-rocm-ci" {
cache-from = concat(
get_cache_from_rocm_csrc(),
EOF
write_hcl_string_list " " "${csrc_content_cache_from[@]}"
write_hcl_string_list " " "${content_cache_from[@]}"
cat <<EOF
)
EOF
@@ -1632,23 +1257,11 @@ EOF
cat <<EOF
}
target "rust-rocm-ci" {
cache-from = concat(
get_cache_from_rocm_rust(),
EOF
write_hcl_string_list " " "${rust_content_cache_from[@]}"
cat <<EOF
)
EOF
write_hcl_string_list_attr " " "cache-to" "${rust_cache_to[@]}"
cat <<EOF
}
target "test-rocm-ci" {
cache-from = concat(
get_cache_from_rocm(),
EOF
write_hcl_string_list " " "${combined_content_cache_from[@]}"
write_hcl_string_list " " "${content_cache_from[@]}"
cat <<EOF
)
EOF
@@ -1660,7 +1273,7 @@ target "export-wheel-rocm" {
cache-from = concat(
get_cache_from_rocm(),
EOF
write_hcl_string_list " " "${combined_content_cache_from[@]}"
write_hcl_string_list " " "${content_cache_from[@]}"
cat <<EOF
)
EOF
@@ -1928,13 +1541,7 @@ confirm_remote_image_push() {
remote_hash=$(get_remote_image_label_with_retry "${image_ref}" "vllm.ci_base.content_hash")
if [[ -n "${remote_hash}" && "${remote_hash}" == "${CI_BASE_CONTENT_HASH}" ]]; then
if remote_ci_base_metadata_is_current_with_retry "${image_ref}"; then
return 0
fi
echo "Remote image exists with the expected ci_base content hash but stale metadata."
echo " expected metadata version: ${CI_BASE_METADATA_VERSION:-${DEFAULT_CI_BASE_METADATA_VERSION}}"
return 1
return 0
fi
echo "Remote image exists but does not have the expected ci_base content hash."
@@ -1950,8 +1557,8 @@ confirm_remote_image_push() {
fi
if [[ -z "${remote_revision}" \
&& ${IMAGE_EXISTED_BEFORE_BUILD} -eq 0 ]] \
&& image_tag_is_commit_scoped; then
&& ${IMAGE_EXISTED_BEFORE_BUILD} -eq 0 \
&& image_tag_is_commit_scoped ]]; then
echo "Remote image exists under a commit-scoped tag; accepting push despite missing revision label."
return 0
fi
@@ -2009,10 +1616,7 @@ seed_dependency_caches_if_needed() {
echo "--- :docker: Seeding ${target}"
echo "Expected cache ref: ${cache_ref}"
docker buildx bake \
"${BAKE_FILES[@]}" \
--progress "${BUILDKIT_PROGRESS:-plain}" \
"${target}"
docker buildx bake "${BAKE_FILES[@]}" --progress plain "${target}"
verify_dependency_cache_ref "${cache_ref}"
done
}
@@ -2040,10 +1644,7 @@ run_bake() {
local build_rc=0
echo "--- :docker: Building ${TARGET}"
docker buildx bake \
"${BAKE_FILES[@]}" \
--progress "${BUILDKIT_PROGRESS:-plain}" \
"${BAKE_TARGETS[@]}" || build_rc=$?
docker buildx bake "${BAKE_FILES[@]}" --progress plain "${BAKE_TARGETS[@]}" || build_rc=$?
if [[ ${build_rc} -eq 0 ]]; then
echo "--- :white_check_mark: Build complete"
@@ -2081,57 +1682,36 @@ upload_wheel_artifacts_if_present() {
local wheel_dir="./wheel-export"
local artifact_dir="artifacts/vllm-rocm-install"
local archive_name="vllm-rocm-install.tar.gz"
local metadata_dir="${wheel_dir}/.vllm-ci-artifact"
local native_base_image=""
local whl=""
local whl_name=""
local -a wheels=()
if ! should_upload_wheel_artifacts; then
return 0
fi
if [[ -d "${wheel_dir}" ]]; then
mapfile -t wheels < <(find "${wheel_dir}" -maxdepth 1 -type f -name '*.whl' -print)
fi
if [[ ${#wheels[@]} -ne 1 ]]; then
echo "Expected exactly one ROCm wheel in ${wheel_dir}; found ${#wheels[@]}" >&2
return 1
fi
whl="${wheels[0]}"
whl_name=$(basename "${whl}")
native_base_image="${CI_BASE_IMAGE_TAG_COMMIT_REF:-${CI_BASE_IMAGE:-}}"
if [[ -z "${native_base_image}" ]]; then
echo "Native ROCm artifact requires a ci_base image reference" >&2
return 1
if [[ ! -d "${wheel_dir}" ]] || ! ls "${wheel_dir}"/*.whl >/dev/null 2>&1; then
echo "No ROCm wheel artifacts found in ${wheel_dir}"
return 0
fi
echo "--- :package: Uploading ROCm vLLM install artifact"
rm -rf "${artifact_dir}" "${metadata_dir}"
mkdir -p "${artifact_dir}" "${metadata_dir}"
printf '%s\n' "${BUILDKITE_COMMIT:-local}" > "${metadata_dir}/commit.txt"
printf '%s\n' "${native_base_image}" > "${metadata_dir}/native-base-image.txt"
printf '%s\n' "${CI_BASE_IMAGE:-}" > "${metadata_dir}/ci-base-image.txt"
printf '%s\n' "${IMAGE_TAG:-}" > "${metadata_dir}/fallback-image.txt"
printf '%s\n' "${whl_name}" > "${metadata_dir}/wheel-filename.txt"
mkdir -p "${artifact_dir}"
tar -C "${wheel_dir}" -czf "${artifact_dir}/${archive_name}" .
(
cd "${artifact_dir}"
sha256sum "${archive_name}" > "${archive_name}.sha256"
)
echo "Created ${archive_name}: $(du -sh "${artifact_dir}/${archive_name}" | cut -f1)"
cp "${metadata_dir}"/*.txt "${artifact_dir}/"
cp "${whl}" "${artifact_dir}/${whl_name}"
echo "Copied ${whl_name}: $(du -sh "${artifact_dir}/${whl_name}" | cut -f1)"
printf '%s\n' "${CI_BASE_IMAGE:-}" > "${artifact_dir}/ci-base-image.txt"
printf '%s\n' "${IMAGE_TAG:-}" > "${artifact_dir}/fallback-image.txt"
for whl in "${wheel_dir}"/*.whl; do
[[ -f "${whl}" ]] || continue
whl_name=$(basename "${whl}")
cp "${whl}" "${artifact_dir}/${whl_name}"
echo "Copied ${whl_name}: $(du -sh "${artifact_dir}/${whl_name}" | cut -f1)"
done
if command -v buildkite-agent >/dev/null 2>&1; then
buildkite-agent artifact upload "${artifact_dir}/*" || return 1
buildkite-agent artifact upload "${artifact_dir}/*"
echo "ROCm vLLM install artifacts uploaded to ${artifact_dir}/"
elif [[ "${BUILDKITE:-false}" == "true" ]]; then
echo "buildkite-agent not found; cannot upload required ROCm artifacts" >&2
return 1
else
echo "Not in Buildkite, skipping artifact upload"
fi
@@ -2144,18 +1724,16 @@ main() {
print_header
validate_inputs
load_ci_hcl
init_bake_files
compute_ci_base_hash_if_needed
configure_ci_base_image_refs
maybe_skip_existing_image
setup_builder
prepare_git_cache_metadata
write_ci_base_label_override
extract_dependency_pins
write_rocm_build_arg_override
compute_dependency_cache_keys
write_ci_base_label_override
compute_rocm_csrc_content_hash_if_needed
compute_rocm_rust_content_hash_if_needed
write_rocm_cache_override
resolve_ci_base_dependency_targets
print_bake_config
@@ -2163,11 +1741,6 @@ main() {
echo "BAKE_PRINT_ONLY=1 set; skipping build"
return 0
fi
if should_upload_wheel_artifacts; then
# wheel-export is an output directory, not a BuildKit cache. Starting
# clean prevents a failed/retried export from packaging a stale wheel.
rm -rf ./wheel-export
fi
seed_dependency_caches_if_needed
run_bake
upload_wheel_artifacts_if_present
@@ -45,10 +45,8 @@ $PYTHON .buildkite/scripts/generate-nightly-index.py --version "$SUBPATH" --curr
echo "Uploading indices to $S3_COMMIT_PREFIX"
aws s3 cp --recursive "$INDICES_OUTPUT_DIR/" "$S3_COMMIT_PREFIX"
# copy to /nightly/ only when enabled for a main branch build that is not a PR
if [[ "${UPDATE_NIGHTLY_INDEX:-1}" == "1" && \
"$BUILDKITE_BRANCH" == "main" && \
"$BUILDKITE_PULL_REQUEST" == "false" ]]; then
# copy to /nightly/ only if it is on the main branch and not a PR
if [[ "$BUILDKITE_BRANCH" == "main" && "$BUILDKITE_PULL_REQUEST" == "false" ]]; then
echo "Uploading indices to overwrite /nightly/"
aws s3 cp --recursive "$INDICES_OUTPUT_DIR/" "s3://$BUCKET/nightly/"
fi
@@ -69,7 +67,7 @@ pure_version="${version%%+*}"
echo "Pure version (without variant): $pure_version"
# re-generate and copy to /<pure_version>/ only if it does not have "dev" in the version
if [[ "${UPDATE_VERSION_INDEX:-1}" == "1" && "$version" != *"dev"* ]]; then
if [[ "$version" != *"dev"* ]]; then
echo "Re-generating indices for /$pure_version/"
rm -rf "${INDICES_OUTPUT_DIR:?}"
mkdir -p "$INDICES_OUTPUT_DIR"
+4 -429
View File
@@ -1,7 +1,7 @@
#!/bin/bash
# This script runs ROCm tests either directly in a native CI pod or inside the
# corresponding Docker container. Multi-node tests continue to use Docker.
# This script runs tests inside the corresponding ROCm docker container.
# It handles both single-node and multi-node test configurations.
#
# Multi-node detection: Instead of matching on fragile group names, we detect
# multi-node jobs structurally by looking for the bracket command syntax
@@ -28,34 +28,6 @@
###############################################################################
set -o pipefail
: "${BUILDKIT_PROGRESS:=plain}"
: "${TERM:=xterm-256color}"
: "${FORCE_COLOR:=1}"
: "${CLICOLOR_FORCE:=1}"
: "${PY_COLORS:=1}"
: "${ROCM_DOCKER_TTY:=1}"
: "${PYTHONFAULTHANDLER:=1}"
: "${PYTEST_TIMEOUT:=2100}"
if [[ " ${PYTEST_ADDOPTS:-} " != *" --color"* ]]; then
PYTEST_ADDOPTS="${PYTEST_ADDOPTS:+${PYTEST_ADDOPTS} }--color=yes"
fi
if [[ " ${PYTEST_ADDOPTS:-} " != *" --durations="* ]]; then
PYTEST_ADDOPTS="${PYTEST_ADDOPTS:+${PYTEST_ADDOPTS} }--durations=25"
fi
if [[ " ${PYTEST_ADDOPTS:-} " != *" --durations-min="* ]]; then
PYTEST_ADDOPTS="${PYTEST_ADDOPTS:+${PYTEST_ADDOPTS} }--durations-min=1.0"
fi
# Dump stacks after 15 minutes, then stop an individual test after 35 minutes.
if [[ " ${PYTEST_ADDOPTS:-} " != *" faulthandler_timeout="* ]]; then
PYTEST_ADDOPTS="${PYTEST_ADDOPTS:+${PYTEST_ADDOPTS} }-o faulthandler_timeout=900"
fi
if [[ " ${PYTEST_ADDOPTS:-} " != *" --timeout-method="* &&
" ${PYTEST_ADDOPTS:-} " != *" --timeout-method "* ]]; then
PYTEST_ADDOPTS="${PYTEST_ADDOPTS:+${PYTEST_ADDOPTS} }--timeout-method=thread"
fi
export BUILDKIT_PROGRESS TERM FORCE_COLOR CLICOLOR_FORCE PY_COLORS PYTEST_ADDOPTS PYTEST_TIMEOUT ROCM_DOCKER_TTY
export PYTHONFAULTHANDLER
# Export Python path for commands that run directly on the host. Containerized
# tests set this to /vllm-workspace below so spawned Python processes do not
# depend on their current working directory.
@@ -70,28 +42,6 @@ report_docker_usage() {
docker system df || true
}
clear_ci_orchestration_env() {
unset -v \
VLLM_TEST_GROUP_NAME \
VLLM_CI_REQUIRE_PERSISTENT_HF_CACHE \
VLLM_CI_ARTIFACT_STEP \
VLLM_TEST_CACHE \
VLLM_CI_EXECUTION_MODE \
VLLM_CI_WORKSPACE \
VLLM_CI_REQUIRE_WORKSPACE_MOUNT \
VLLM_TEST_COMMANDS \
VLLM_CI_BRANCH \
VLLM_CI_BASE_IMAGE \
VLLM_CI_FALLBACK_IMAGE \
VLLM_CI_DOCKER_DISABLED \
VLLM_CI_ARTIFACT_GLOB \
VLLM_CI_ARTIFACT_CHECKSUM_GLOB \
VLLM_CI_EXPECTED_GPU_COUNT \
VLLM_CI_USE_ARTIFACTS \
VLLM_CI_RESULTS_ROOT \
VLLM_ALLOW_DEPRECATED_BEAM_SEARCH
}
cleanup_network() {
local max_nodes=${NUM_NODES:-2}
for node in $(seq 0 $((max_nodes - 1))); do
@@ -184,11 +134,7 @@ prepare_artifact_image() {
fi
cp "${wheel_dir}"/*.whl "${context_dir}/wheels/" || return 1
tar -C "${wheel_dir}" \
--exclude='*.whl' \
--exclude='.vllm-ci-artifact' \
--exclude='./.vllm-ci-artifact' \
-cf - . \
tar -C "${wheel_dir}" --exclude='*.whl' -cf - . \
| tar -C "${workspace_dir}" -xf - || return 1
cat > "${context_dir}/Dockerfile" <<'EOF'
ARG BASE_IMAGE
@@ -203,7 +149,6 @@ EOF
echo "--- Building local ROCm test image"
docker build \
--pull=false \
--progress "${BUILDKIT_PROGRESS}" \
--build-arg "BASE_IMAGE=${base_image}" \
-t "${artifact_image}" \
"${context_dir}" || return 1
@@ -211,257 +156,6 @@ EOF
return 0
}
is_native_runtime() {
[[ "${AMD_CI_RUNTIME:-}" == "native" || "${NATIVE_CI:-}" == "true" ]]
}
validate_native_workspace() {
local workspace_dir="${VLLM_CI_WORKSPACE:-/vllm-workspace}"
local workspace_real=""
local checkout_real=""
local workspace_mount=""
mkdir -p "${workspace_dir}" || return 1
workspace_real=$(readlink -m "${workspace_dir}") || return 1
if [[ -n "${BUILDKITE_BUILD_CHECKOUT_PATH:-}" ]]; then
checkout_real=$(readlink -m "${BUILDKITE_BUILD_CHECKOUT_PATH}") || return 1
if [[ "${checkout_real}" == "${workspace_real}" \
|| "${checkout_real}" == "${workspace_real}/"* \
|| "${workspace_real}" == "${checkout_real}/"* ]]; then
echo "Refusing to replace ${workspace_real}; it overlaps the Buildkite checkout ${checkout_real}" >&2
return 1
fi
fi
if [[ "${VLLM_CI_REQUIRE_WORKSPACE_MOUNT:-1}" == "1" ]]; then
if ! command -v findmnt >/dev/null 2>&1; then
echo "findmnt is required to verify the native workspace mount" >&2
return 1
fi
workspace_mount=$(findmnt -n -T "${workspace_real}" -o TARGET 2>/dev/null || true)
if [[ "$(readlink -m "${workspace_mount:-/}")" != "${workspace_real}" ]]; then
echo "Native CI requires a dedicated volume mounted at ${workspace_real}" >&2
return 1
fi
fi
}
prepare_native_workspace() {
if [[ "${VLLM_CI_USE_ARTIFACTS:-0}" != "1" ]]; then
echo "Native CI requires VLLM_CI_USE_ARTIFACTS=1"
return 1
fi
if ! command -v buildkite-agent >/dev/null 2>&1; then
echo "buildkite-agent not found; cannot download ROCm wheel artifact"
return 1
fi
validate_native_workspace || return 1
local artifact_glob="${VLLM_CI_ARTIFACT_GLOB:-artifacts/vllm-rocm-install/vllm-rocm-install.tar.gz}"
local artifact_checksum_glob="${VLLM_CI_ARTIFACT_CHECKSUM_GLOB:-${artifact_glob}.sha256}"
local artifact_step="${VLLM_CI_ARTIFACT_STEP:-image-build-amd}"
local archive=""
local checksum=""
local download_dir=""
local metadata_dir=""
local recorded_base=""
local recorded_commit=""
local recorded_wheel=""
local workspace_dir="${VLLM_CI_WORKSPACE:-/vllm-workspace}"
local wheel_dir=""
local attempt=0
local attempt_dir=""
local -a archives=()
local -a checksums=()
local -a wheels=()
artifact_work_dir=$(mktemp -d -t vllm-rocm-artifact.XXXXXX) || return 1
wheel_dir="${artifact_work_dir}/wheels"
mkdir -p "${wheel_dir}" || return 1
echo "--- Downloading ROCm wheel artifact from ${artifact_step} (native in-pod)"
for attempt in 1 2 3; do
attempt_dir="${artifact_work_dir}/download-${attempt}"
rm -rf "${attempt_dir}" || return 1
mkdir -p "${attempt_dir}" || return 1
if buildkite-agent artifact download \
"${artifact_glob}" "${attempt_dir}" --step "${artifact_step}" \
&& buildkite-agent artifact download \
"${artifact_checksum_glob}" "${attempt_dir}" --step "${artifact_step}"; then
download_dir="${attempt_dir}"
break
fi
echo "Artifact download attempt ${attempt}/3 failed"
if [[ "${attempt}" -lt 3 ]]; then
sleep $((attempt * 2))
fi
done
if [[ -z "${download_dir}" ]]; then
echo "Failed to download ${artifact_glob} and ${artifact_checksum_glob} from ${artifact_step}"
return 1
fi
mapfile -t archives < <(
find "${download_dir}" -name "vllm-rocm-install.tar.gz" -type f -print
)
mapfile -t checksums < <(
find "${download_dir}" -name "vllm-rocm-install.tar.gz.sha256" -type f -print
)
if [[ ${#archives[@]} -ne 1 || ${#checksums[@]} -ne 1 ]]; then
echo "Expected exactly one ROCm archive and checksum; found ${#archives[@]} archive(s) and ${#checksums[@]} checksum(s)" >&2
return 1
fi
archive="${archives[0]}"
checksum="${checksums[0]}"
if [[ "$(dirname "${archive}")" != "$(dirname "${checksum}")" ]]; then
echo "ROCm archive and checksum were downloaded to different directories" >&2
return 1
fi
(
cd "$(dirname "${archive}")"
sha256sum -c "$(basename "${checksum}")"
) || return 1
tar --no-same-owner -xzf "${archive}" -C "${wheel_dir}" || return 1
mapfile -t wheels < <(
find "${wheel_dir}" -maxdepth 1 -type f -name '*.whl' -print
)
if [[ ${#wheels[@]} -ne 1 ]]; then
echo "ROCm artifact must contain exactly one top-level wheel; found ${#wheels[@]}" >&2
return 1
fi
metadata_dir="${wheel_dir}/.vllm-ci-artifact"
for metadata_file in commit.txt native-base-image.txt wheel-filename.txt; do
if [[ ! -s "${metadata_dir}/${metadata_file}" ]]; then
echo "ROCm artifact metadata is missing ${metadata_file}" >&2
return 1
fi
done
for metadata_file in ci-base-image.txt fallback-image.txt; do
if [[ ! -f "${metadata_dir}/${metadata_file}" ]]; then
echo "ROCm artifact metadata is missing ${metadata_file}" >&2
return 1
fi
done
recorded_commit=$(tr -d '\r\n' < "${metadata_dir}/commit.txt")
recorded_base=$(tr -d '\r\n' < "${metadata_dir}/native-base-image.txt")
recorded_wheel=$(tr -d '\r\n' < "${metadata_dir}/wheel-filename.txt")
if [[ -z "${BUILDKITE_COMMIT:-}" || "${recorded_commit}" != "${BUILDKITE_COMMIT}" ]]; then
echo "ROCm artifact commit ${recorded_commit} does not match ${BUILDKITE_COMMIT:-unset}" >&2
return 1
fi
if [[ -z "${VLLM_CI_BASE_IMAGE:-}" || "${recorded_base}" != "${VLLM_CI_BASE_IMAGE}" ]]; then
echo "ROCm artifact base ${recorded_base} does not match ${VLLM_CI_BASE_IMAGE:-unset}" >&2
return 1
fi
if [[ "${recorded_wheel}" != "$(basename "${wheels[0]}")" ]]; then
echo "ROCm artifact wheel manifest ${recorded_wheel} does not match $(basename "${wheels[0]}")" >&2
return 1
fi
for required_dir in tests .buildkite requirements; do
if [[ ! -d "${wheel_dir}/${required_dir}" ]]; then
echo "ROCm wheel artifact did not contain ${required_dir}/" >&2
return 1
fi
done
echo "--- Installing ROCm wheel into pod environment"
python3 -m pip install --no-deps --force-reinstall "${wheels[0]}" || return 1
echo "--- Preparing ${workspace_dir} from artifact"
find "${workspace_dir}" -mindepth 1 -maxdepth 1 -exec rm -rf -- {} + || return 1
tar -C "${wheel_dir}" \
--exclude='*.whl' \
--exclude='.vllm-ci-artifact' \
--exclude='./.vllm-ci-artifact' \
-cf - . | tar --no-same-owner -C "${workspace_dir}" -xf - || return 1
if [[ ! -d "${workspace_dir}/tests" ]]; then
echo "Failed to stage the native test workspace" >&2
return 1
fi
return 0
}
initialize_native_environment() {
local job_id="${BUILDKITE_JOB_ID:-${BUILDKITE_PARALLEL_JOB:-local}}"
local job_id_suffix=""
local native_root=""
local hf_mount=""
if [[ "$(id -u)" -ne 0 ]]; then
echo "Native ROCm CI currently requires the ci_base container to run as root" >&2
return 1
fi
job_id="${job_id//[^A-Za-z0-9_.-]/_}"
job_id_suffix="${job_id##*-}"
job_id_suffix="${job_id_suffix:0:12}"
native_root="/tmp/vllm-native-${job_id}"
TMPDIR="/tmp/vllm-${job_id_suffix}/tmp"
VLLM_RPC_BASE_PATH="/tmp"
: "${TORCHINDUCTOR_CACHE_DIR:=${native_root}/cache/torchinductor}"
: "${TRITON_CACHE_DIR:=${native_root}/cache/triton}"
: "${VLLM_CACHE_ROOT:=${native_root}/cache/vllm}"
: "${XDG_CACHE_HOME:=${native_root}/cache/xdg}"
: "${HF_HOME:=/home/buildkite-agent/huggingface}"
: "${HF_HUB_DOWNLOAD_TIMEOUT:=300}"
: "${HF_HUB_ETAG_TIMEOUT:=60}"
export TMPDIR VLLM_RPC_BASE_PATH
export TORCHINDUCTOR_CACHE_DIR TRITON_CACHE_DIR VLLM_CACHE_ROOT XDG_CACHE_HOME
export HF_HOME HF_HUB_DOWNLOAD_TIMEOUT HF_HUB_ETAG_TIMEOUT
export PYTORCH_ROCM_ARCH=""
mkdir -p "${TMPDIR}" \
"${TORCHINDUCTOR_CACHE_DIR}" \
"${TRITON_CACHE_DIR}" \
"${VLLM_CACHE_ROOT}" \
"${XDG_CACHE_HOME}" \
"${HF_HOME}" || return 1
if [[ "${VLLM_CI_REQUIRE_PERSISTENT_HF_CACHE:-0}" == "1" ]]; then
if ! command -v findmnt >/dev/null 2>&1; then
echo "findmnt is required to verify the native Hugging Face cache mount" >&2
return 1
fi
hf_mount=$(findmnt -n -T "${HF_HOME}" -o TARGET 2>/dev/null || true)
if [[ -z "${hf_mount}" || "${hf_mount}" == "/" ]]; then
echo "Native CI requires a persistent volume mounted at or above ${HF_HOME}" >&2
return 1
fi
fi
}
run_native_preflight() {
local expected_gpus="${VLLM_CI_EXPECTED_GPU_COUNT:-1}"
if [[ ! "${expected_gpus}" =~ ^[0-9]+$ ]]; then
echo "Invalid VLLM_CI_EXPECTED_GPU_COUNT=${expected_gpus}" >&2
return 1
fi
python3 -c "import encodings, importlib.metadata as im, importlib.util as iu; [im.version(d) for d in ('transformers', 'torch', 'ray', 'sympy', 'markupsafe', 'vllm')]; missing=[m for m in ('torch.utils.model_zoo', 'transformers.models.nomic_bert', 'ray.dag', 'sympy.physics', 'markupsafe._speedups') if iu.find_spec(m) is None]; assert not missing, missing" || return 1
if [[ "${expected_gpus}" == "0" ]]; then
echo "Native CPU-only AMD job: skipping ROCm device validation"
return 0
fi
echo "--- ROCm info"
rocminfo || return 1
VLLM_CI_EXPECTED_GPU_COUNT="${expected_gpus}" python3 - <<'PY'
import os
import torch
expected = int(os.environ["VLLM_CI_EXPECTED_GPU_COUNT"])
assert torch.version.hip, "PyTorch is not a ROCm build"
assert torch.cuda.is_available(), "ROCm GPU is not available to PyTorch"
actual = torch.cuda.device_count()
assert actual == expected, f"Expected {expected} ROCm GPU(s), found {actual}"
PY
}
is_multi_node() {
local cmds="$1"
# Primary signal: NUM_NODES environment variable set by the pipeline
@@ -644,58 +338,7 @@ re_quote_pytest_markers() {
# Main
###############################################################################
if is_native_runtime; then
echo "--- Native in-pod ROCm CI (AMD_CI_RUNTIME=${AMD_CI_RUNTIME:-unset}, NATIVE_CI=${NATIVE_CI:-unset})"
artifact_work_dir=""
cleanup_native_workspace() {
if [[ -n "${artifact_work_dir}" ]]; then
rm -rf "${artifact_work_dir}"
fi
}
trap cleanup_native_workspace EXIT
if [[ -n "${VLLM_TEST_COMMANDS:-}" ]]; then
commands="${VLLM_TEST_COMMANDS}"
commands_source="env"
else
commands="$*"
commands_source="argv"
if [[ -z "$commands" ]]; then
echo "Error: No test commands provided for native CI." >&2
exit 1
fi
fi
if [[ "$commands_source" == "argv" ]]; then
commands=$(re_quote_pytest_markers "$commands")
fi
if is_multi_node "$commands"; then
echo "Native CI does not support multi-node jobs yet."
exit 1
fi
if ! initialize_native_environment; then
echo "Failed to initialize the native test environment"
exit 1
fi
if ! prepare_native_workspace; then
echo "Failed to prepare native test workspace"
exit 1
fi
export PYTHONPATH="${VLLM_CI_WORKSPACE:-/vllm-workspace}"
echo "Native test commands: $commands"
run_native_preflight || exit 1
# Keep AMD CI orchestration variables out of vLLM's runtime environment.
clear_ci_orchestration_env
/bin/bash -o pipefail -c "${commands}"
handle_pytest_exit "$?"
fi
# --- GPU initialization for legacy Docker execution ---
# --- GPU initialization ---
echo "--- ROCm info"
rocminfo
@@ -724,20 +367,6 @@ remove_docker_container() {
}
trap remove_docker_container EXIT
# python_only_compile.sh runs `python setup.py develop` and needs the full repo tree
# under /vllm-workspace (Dockerfile.rocm test stage: mkdir src && mv vllm).
# The ROCm wheel artifact tarball only ships a thin tree (tests, etc.), so
# artifact images cannot satisfy that test — use the full rocm/vllm-ci image.
_cmd_probe="${VLLM_TEST_COMMANDS:-}"
if [[ -z "${_cmd_probe}" ]]; then
_cmd_probe="$*"
fi
if [[ "${VLLM_CI_USE_ARTIFACTS:-0}" == "1" && "${_cmd_probe}" == *python_only_compile.sh* ]]; then
echo "INFO: disabling VLLM_CI_USE_ARTIFACTS for python_only_compile (requires full /vllm-workspace tree)"
export VLLM_CI_USE_ARTIFACTS=0
fi
unset -v _cmd_probe
if ! prepare_artifact_image; then
echo "Using full ROCm CI image: ${image_name}"
docker pull "${image_name}" || exit 1
@@ -797,28 +426,6 @@ fi
echo "Final commands: $commands"
standalone_merge_base_env=()
if [[ "$commands" == *python_only_compile.sh* ]]; then
# The ROCm test image often ships /vllm-workspace without .git. Resolve the
# wheels.vllm.ai commit from the agent checkout for this test only.
vllm_standalone_merge_base=""
checkout="${BUILDKITE_BUILD_CHECKOUT_PATH:-}"
if [[ -z "${checkout}" || ! -d "${checkout}" ]]; then
checkout="."
fi
# Pass safe.directory per-command because Buildkite uses mixed user IDs.
if git -c "safe.directory=${checkout}" -C "${checkout}" rev-parse --is-inside-work-tree >/dev/null 2>&1; then
vllm_standalone_merge_base="$(
git -c "safe.directory=${checkout}" -C "${checkout}" merge-base HEAD origin/main 2>/dev/null || true
)"
fi
if [[ -z "${vllm_standalone_merge_base}" ]]; then
vllm_standalone_merge_base="${BUILDKITE_COMMIT:-}"
fi
echo "INFO: passing CI_STANDALONE_MERGE_BASE into container: ${vllm_standalone_merge_base}"
standalone_merge_base_env=(-e "CI_STANDALONE_MERGE_BASE=${vllm_standalone_merge_base}")
fi
MYPYTHONPATH="/vllm-workspace"
container_job_id="${BUILDKITE_JOB_ID:-${BUILDKITE_PARALLEL_JOB:-0}}"
@@ -848,7 +455,6 @@ else
fi
# --- Route: multi-node vs single-node ---
clear_ci_orchestration_env
if is_multi_node "$commands"; then
echo "--- Multi-node job detected"
export DCKR_VER=$(docker --version | sed 's/Docker version \(.*\), build .*/\1/')
@@ -895,37 +501,14 @@ if is_multi_node "$commands"; then
else
echo "--- Single-node job"
echo "Render devices: $BUILDKITE_AGENT_META_DATA_RENDER_DEVICES"
docker_run_terminal_args=(-i)
if [[ "${ROCM_DOCKER_TTY}" == "1" ]]; then
docker_run_terminal_args+=(-t)
echo "Docker interactive stdin: enabled; TTY allocation: enabled"
else
echo "Docker interactive stdin: enabled; TTY allocation: disabled"
fi
ulimit_core_hard=$(ulimit -H -c)
if [[ "$ulimit_core_hard" == "unlimited" ]]; then
# docker run can't pass "unlimited" to --ulimit
ulimit_core_hard="-1"
fi
# Disable core dumps in the ROCm test container unless the ROCm debug agent is enabled
coredump_flags="--ulimit core=0:$ulimit_core_hard"
if [[ "$commands" == *"ROCm debug agent enabled"* ]]; then
# Works around https://github.com/rocm/rocm-systems/issues/6206
coredump_flags='-e HSA_COREDUMP_PATTERN="/tmp/gpucore.%p"'
else
echo "ROCm debug agent not enabled, coredumps are disabled in the test container."
fi
docker run \
"${docker_run_terminal_args[@]}" \
--device /dev/kfd $BUILDKITE_AGENT_META_DATA_RENDER_DEVICES \
$RDMA_FLAGS \
--network=host \
--shm-size=16gb \
--group-add "$render_gid" \
--rm \
$coredump_flags \
-e HF_TOKEN \
-e "HF_HUB_DOWNLOAD_TIMEOUT=${HF_HUB_DOWNLOAD_TIMEOUT}" \
-e "HF_HUB_ETAG_TIMEOUT=${HF_HUB_ETAG_TIMEOUT}" \
@@ -933,13 +516,6 @@ else
-e AWS_SECRET_ACCESS_KEY \
-e BUILDKITE_PARALLEL_JOB \
-e BUILDKITE_PARALLEL_JOB_COUNT \
-e TERM \
-e FORCE_COLOR \
-e CLICOLOR_FORCE \
-e PY_COLORS \
-e PYTHONFAULTHANDLER \
-e PYTEST_ADDOPTS \
-e PYTEST_TIMEOUT \
-v "${HF_CACHE}:${HF_MOUNT}" \
-e "HF_HOME=${HF_MOUNT}" \
-e "PYTHONPATH=${MYPYTHONPATH}" \
@@ -949,7 +525,6 @@ else
-e "VLLM_CACHE_ROOT=${CONTAINER_CACHE_ROOT}/vllm" \
-e "XDG_CACHE_HOME=${CONTAINER_CACHE_ROOT}/xdg" \
-e "PYTORCH_ROCM_ARCH=" \
"${standalone_merge_base_env[@]}" \
--name "${container_name}" \
"${image_name}" \
/bin/bash -c "${CONTAINER_PREFLIGHT} && ${commands}"
@@ -8,7 +8,7 @@ set -ex
CORE_RANGE=${CORE_RANGE:-0-31}
OMP_CORE_RANGE=${OMP_CORE_RANGE:-0-31}
export CMAKE_BUILD_PARALLEL_LEVEL=32
export CMAKE_BUILD_PARALLEL_LEVEL=16
# Setup cleanup
remove_docker_container() {
@@ -37,12 +37,8 @@ function cpu_tests() {
pytest -x -v -s tests/kernels/test_onednn.py
pytest -x -v -s tests/kernels/attention/test_cpu_attn.py
pytest -x -v -s tests/kernels/core/test_cpu_activation.py
pytest -x -v -s tests/kernels/moe/test_cpu_fused_moe.py
pytest -x -v -s tests/kernels/mamba/cpu/test_cpu_gdn_ops.py
pytest -x -v -s tests/kernels/moe/test_cpu_int4_moe.py
pytest -x -v -s tests/kernels/mamba/test_cpu_short_conv.py
pytest -x -v -s tests/kernels/mamba/test_causal_conv1d.py
pytest -x -v -s tests/kernels/mamba/test_mamba_ssm.py"
pytest -x -v -s tests/kernels/moe/test_moe.py -k test_cpu_fused_moe_basic
pytest -x -v -s tests/kernels/mamba/cpu/test_cpu_gdn_ops.py"
# skip tests requiring model downloads if HF_TOKEN is not set
# due to rate-limits
@@ -66,6 +62,7 @@ function cpu_tests() {
set -e
pytest -x -v -s tests/quantization/test_compressed_tensors.py::test_compressed_tensors_w8a8_logprobs"
# basic online serving
docker exec cpu-test bash -c '
set -e
@@ -99,4 +96,3 @@ function cpu_tests() {
# All of CPU tests are expected to be finished less than 40 mins.
export -f cpu_tests
timeout 2h bash -c cpu_tests
+1 -40
View File
@@ -7,49 +7,10 @@ set -euox pipefail
# allow to bind to different cores
CORE_RANGE=${CORE_RANGE:-48-95}
NUMA_NODE=${NUMA_NODE:-1}
AGENT_SLOT=${AGENT_SLOT:-}
IMAGE_NAME="cpu-test-${NUMA_NODE}${AGENT_SLOT:+-${AGENT_SLOT}}"
IMAGE_NAME="cpu-test-$NUMA_NODE"
TIMEOUT_VAL=$1
TEST_COMMAND=$2
# Disk hygiene knobs. Reclaim space only once the Docker root filesystem crosses
# DISK_USAGE_THRESHOLD percent, and cap the shared BuildKit cache at
# BUILDKIT_CACHE_MAX so subsequent builds keep reusing the hottest layers.
DISK_USAGE_THRESHOLD=${DISK_USAGE_THRESHOLD:-70}
BUILDKIT_CACHE_MAX=${BUILDKIT_CACHE_MAX:-80GB}
# Reclaim disk only when the host is under pressure. We trim (not purge) the
# shared BuildKit cache so cross-job/cross-agent reuse stays intact, and only
# touch dangling images; other agents' uniquely tagged images are left alone.
prune_if_disk_pressure() {
local docker_root disk_usage
docker_root=$(docker info -f '{{.DockerRootDir}}' 2>/dev/null || true)
if [ -z "$docker_root" ]; then
return 0
fi
disk_usage=$(df "$docker_root" 2>/dev/null | tail -1 | awk '{print $5}' | tr -d '%')
if [ "${disk_usage:-0}" -gt "$DISK_USAGE_THRESHOLD" ]; then
echo "--- :broom: Disk usage ${disk_usage}% exceeds ${DISK_USAGE_THRESHOLD}%, reclaiming space"
docker image prune -f || true
docker builder prune -f --keep-storage="$BUILDKIT_CACHE_MAX" || true
else
echo "Disk usage ${disk_usage:-unknown}% within ${DISK_USAGE_THRESHOLD}% threshold; skipping prune"
fi
}
# Always drop this agent's image once the job ends (the default builder never
# uses it as a cache source, so removing it costs no rebuild speed), then
# reclaim space if needed. Guard every docker call with `|| true` so the trap
# never overrides the test's exit code.
cleanup() {
docker image rm -f "$IMAGE_NAME" || true
prune_if_disk_pressure
}
trap cleanup EXIT
# Free space up front so a nearly-full host doesn't fail the build.
prune_if_disk_pressure
# building the docker image
echo "--- :docker: Building Docker image"
docker build --progress plain --tag "$IMAGE_NAME" --target vllm-test -f docker/Dockerfile.cpu .
@@ -21,7 +21,6 @@ case "${test_suite}" in
python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager --kv-cache-dtype fp8
python3 examples/basic/offline_inference/generate.py --model nvidia/Llama-3.1-8B-Instruct-FP8 --block-size 64 --enforce-eager --quantization modelopt --kv-cache-dtype fp8 --attention-backend TRITON_ATTN --max-model-len 4096
python3 examples/basic/offline_inference/generate.py --model superjob/Qwen3-4B-Instruct-2507-GPTQ-Int4 --block-size 64 --enforce-eager --max-model-len 8192
python3 examples/basic/offline_inference/generate.py --model TheBloke/TinyLlama-1.1B-Chat-v0.3-AWQ --block-size 64 --enforce-eager
python3 examples/basic/offline_inference/generate.py --model ibm-research/PowerMoE-3b --block-size 64 --enforce-eager -tp 2
python3 examples/basic/offline_inference/generate.py --model ibm-research/PowerMoE-3b --block-size 64 --enforce-eager -tp 2 --enable-expert-parallel
python3 examples/basic/offline_inference/generate.py --model superjob/Qwen3-4B-Instruct-2507-GPTQ-Int4 --max-model-len 8192
@@ -35,8 +34,7 @@ case "${test_suite}" in
pytest -v -s v1/worker --ignore=v1/worker/test_gpu_model_runner.py --ignore=v1/worker/test_worker_memory_snapshot.py
pytest -v -s v1/structured_output
pytest -v -s v1/test_serial_utils.py
pytest -v -s v1/e2e/general/test_correctness_sliding_window.py --deselect="tests/v1/e2e/general/test_correctness_sliding_window.py::test_sliding_window_retrieval[True-1-5-google/gemma-3-1b-it]"
pytest -v -s v1/spec_decode --ignore=v1/spec_decode/test_max_len.py --ignore=v1/spec_decode/test_speculators_eagle3.py --ignore=v1/spec_decode/test_acceptance_length.py --ignore=v1/spec_decode/test_speculators_correctness.py
pytest -v -s v1/spec_decode --ignore=v1/spec_decode/test_max_len.py --ignore=v1/spec_decode/test_speculators_eagle3.py --ignore=v1/spec_decode/test_acceptance_length.py
pytest -v -s v1/kv_connector/unit --ignore=v1/kv_connector/unit/test_multi_connector.py --ignore=v1/kv_connector/unit/test_example_connector.py --ignore=v1/kv_connector/unit/test_lmcache_integration.py --ignore=v1/kv_connector/unit/test_hf3fs_client.py --ignore=v1/kv_connector/unit/test_hf3fs_connector.py --ignore=v1/kv_connector/unit/test_hf3fs_metadata_server.py --ignore=v1/kv_connector/unit/test_offloading_connector.py
;;
server)
@@ -360,7 +360,7 @@ export HF_TOKEN ZE_AFFINITY_MASK
--ipc=host \
--privileged \
-v /dev/dri/by-path:/dev/dri/by-path \
-v "/data/huggingface:/root/.cache/huggingface" \
-v "${HOME}/.cache/huggingface:/root/.cache/huggingface" \
--entrypoint='' \
-e HF_TOKEN \
-e ZE_AFFINITY_MASK \
@@ -369,7 +369,7 @@ export HF_TOKEN ZE_AFFINITY_MASK
-e CMDS \
--name "${container_name}" \
"${IMAGE}" \
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"' \
bash -c 'set -e; echo "ZE_AFFINITY_MASK is ${ZE_AFFINITY_MASK:-}"; eval "$CMDS"' \
>/dev/null
} 9>/tmp/docker-pull.lock
@@ -85,7 +85,7 @@ RUN pip config set global.index-url http://cache-service-vllm.nginx-pypi-cache.s
# Install for pytest to make the docker build cache layer always valid
RUN --mount=type=cache,target=/root/.cache/pip \
pip install pytest>=6.0 'modelscope<1.38'
pip install pytest>=6.0 modelscope
WORKDIR /workspace/vllm
@@ -130,22 +130,6 @@ docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${ROCM_BASE_CACHE_KEY}-rocm
docker push vllm/vllm-openai-rocm:latest-base
docker push vllm/vllm-openai-rocm:v${RELEASE_VERSION}-base
# ---- XPU ----
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-xpu
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-xpu vllm/vllm-openai-xpu:latest-x86_64
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-xpu vllm/vllm-openai-xpu:v${RELEASE_VERSION}-x86_64
docker push vllm/vllm-openai-xpu:latest-x86_64
docker push vllm/vllm-openai-xpu:v${RELEASE_VERSION}-x86_64
docker manifest rm vllm/vllm-openai-xpu:latest || true
docker manifest rm vllm/vllm-openai-xpu:v${RELEASE_VERSION} || true
docker manifest create vllm/vllm-openai-xpu:latest vllm/vllm-openai-xpu:latest-x86_64 --amend
docker manifest create vllm/vllm-openai-xpu:v${RELEASE_VERSION} vllm/vllm-openai-xpu:v${RELEASE_VERSION}-x86_64 --amend
docker manifest push vllm/vllm-openai-xpu:latest
docker manifest push vllm/vllm-openai-xpu:v${RELEASE_VERSION}
# ---- CPU ----
# CPU images are behind separate block steps and may not have been built.
# All-or-nothing: inspect both arches first, then either publish everything
-32
View File
@@ -1,32 +0,0 @@
#!/usr/bin/env bash
# Build the ROCm ci_base image, optionally from a freshly rebuilt ROCm base.
set -euo pipefail
metadata_get() {
local key="$1"
if command -v buildkite-agent >/dev/null 2>&1; then
buildkite-agent meta-data get "${key}" 2>/dev/null || true
fi
}
main() {
local base_refreshed=""
base_refreshed="$(metadata_get rocm-base-refresh)"
if [[ "${base_refreshed}" == "1" ]]; then
export BASE_IMAGE
export CI_BASE_PUSH_STABLE_TAG
BASE_IMAGE="$(metadata_get rocm-base-image)"
CI_BASE_PUSH_STABLE_TAG="$(metadata_get rocm-base-push-stable-tag)"
CI_BASE_PUSH_STABLE_TAG="${CI_BASE_PUSH_STABLE_TAG:-0}"
echo "Using refreshed ROCm base image for ci_base: ${BASE_IMAGE}"
echo "Push stable ci_base tag: ${CI_BASE_PUSH_STABLE_TAG}"
fi
bash .buildkite/scripts/ci-bake-rocm.sh ci-base-rocm-ci-with-deps
}
main "$@"
@@ -1,68 +0,0 @@
#!/usr/bin/env bash
# Build the ROCm CI test image or wheel artifact.
#
# When Dockerfile.rocm_base changes, always build the full image so downstream
# ROCm tests can validate the freshly rebuilt base -> ci_base -> ci image chain.
set -euo pipefail
metadata_get() {
local key="$1"
if command -v buildkite-agent >/dev/null 2>&1; then
buildkite-agent meta-data get "${key}" 2>/dev/null || true
fi
}
use_ci_base_if_present() {
local ci_base_image=""
ci_base_image="$(metadata_get rocm-ci-base-image)"
if [[ -z "${ci_base_image}" ]]; then
return 1
fi
export CI_BASE_IMAGE="${ci_base_image}"
echo "Using ROCm ci_base image selected by the preceding build step: ${CI_BASE_IMAGE}"
}
use_refreshed_base_if_present() {
local base_refreshed=""
base_refreshed="$(metadata_get rocm-base-refresh)"
if [[ "${base_refreshed}" != "1" ]]; then
return 1
fi
export BASE_IMAGE
export IMAGE_TAG_LATEST
BASE_IMAGE="$(metadata_get rocm-base-image)"
IMAGE_TAG_LATEST="$(metadata_get rocm-ci-image-descriptive)"
echo "Using refreshed ROCm base image for test image: ${BASE_IMAGE}"
if [[ -n "${IMAGE_TAG_LATEST}" ]]; then
echo "Also tagging full ROCm CI image as: ${IMAGE_TAG_LATEST}"
fi
return 0
}
main() {
local base_refreshed=0
use_ci_base_if_present || true
if use_refreshed_base_if_present; then
base_refreshed=1
fi
if [[ "${ROCM_CI_ARTIFACT_ONLY:-0}" == "1" && "${base_refreshed}" != "1" ]]; then
echo "ROCM_CI_ARTIFACT_ONLY=1; building ROCm wheel artifact only"
IMAGE_TAG="" bash .buildkite/scripts/ci-bake-rocm.sh test-rocm-ci-with-artifacts
return
fi
bash .buildkite/scripts/ci-bake-rocm.sh test-rocm-ci-with-wheel
}
main "$@"
@@ -1,513 +0,0 @@
#!/usr/bin/env bash
# Build and publish a fresh ROCm base image when Dockerfile.rocm_base changes.
#
# Normal AMD CI builds should not pay for this path. The script no-ops unless
# docker/Dockerfile.rocm_base changed relative to the branch base, the previous
# main commit, or ROCM_BASE_REFRESH_FORCE=1 is set.
set -euo pipefail
DOCKERFILE="${ROCM_BASE_DOCKERFILE:-docker/Dockerfile.rocm_base}"
BASE_REPO="${ROCM_BASE_IMAGE_REPO:-rocm/vllm-dev}"
CI_IMAGE_REPO="${ROCM_CI_IMAGE_REPO:-rocm/vllm-ci}"
BUILDER_NAME="${ROCM_BASE_BUILDER_NAME:-vllm-rocm-base-builder}"
DEFAULT_ROCM_BASE_METADATA_VERSION="1"
DEFAULT_ROCM_BASE_CONTENT_FILES="${DOCKERFILE}"
DEFAULT_ROCM_BASE_CONTENT_ARGS="BASE_IMAGE TRITON_BRANCH TRITON_REPO PYTORCH_BRANCH PYTORCH_REPO PYTORCH_VISION_BRANCH PYTORCH_VISION_REPO PYTORCH_AUDIO_BRANCH PYTORCH_AUDIO_REPO FA_BRANCH FA_REPO AITER_BRANCH AITER_REPO MORI_BRANCH MORI_REPO PYTORCH_ROCM_ARCH PYTHON_VERSION USE_SCCACHE"
metadata_set() {
local key="$1"
local value="$2"
[[ -n "${value}" ]] || return 0
if command -v buildkite-agent >/dev/null 2>&1; then
buildkite-agent meta-data set "${key}" "${value}" || true
fi
}
compute_content_hash() {
local path=""
local file=""
for path in "$@"; do
if [[ -d "${path}" ]]; then
while IFS= read -r -d '' file; do
printf 'file:%s\n' "${file}"
sha256sum "${file}"
done < <(find "${path}" -type f -print0 | sort -z)
elif [[ -f "${path}" ]]; then
printf 'file:%s\n' "${path}"
sha256sum "${path}"
else
printf 'missing:%s\n' "${path}"
fi
done | sha256sum | cut -d' ' -f1
}
clean_docker_tag() {
local input="$1"
echo "${input}" | sed 's/[^a-zA-Z0-9._-]/_/g' | cut -c1-128
}
tag_component() {
local input="$1"
local max_chars="${2:-24}"
clean_docker_tag "${input:-unknown}" | cut -c1-"${max_chars}"
}
extract_arg_default() {
local arg_name="$1"
sed -n -E "s/^[[:space:]]*ARG[[:space:]]+${arg_name}=\"?([^\"[:space:]]+)\"?.*/\\1/p" \
"${DOCKERFILE}" | head -1
}
resolve_image_digest() {
local image_ref="$1"
docker buildx imagetools inspect "${image_ref}" 2>/dev/null \
| sed -n -E 's/^Digest:[[:space:]]+//p' \
| head -1 || true
}
resolve_rocm_base_arg_value() {
local arg_name="$1"
local use_sccache="$2"
case "${arg_name}" in
USE_SCCACHE)
printf '%s\n' "${use_sccache}"
;;
*)
extract_arg_default "${arg_name}"
;;
esac
}
hash_rocm_base_arg_values() {
local use_sccache="$1"
local base_image_digest="$2"
local arg_name=""
local arg_value=""
shift 2 || true
for arg_name in "$@"; do
[[ -n "${arg_name}" ]] || continue
arg_value=$(resolve_rocm_base_arg_value "${arg_name}" "${use_sccache}")
printf 'arg:%s=%s\n' "${arg_name}" "${arg_value:-<empty>}"
if [[ "${arg_name}" == "BASE_IMAGE" && -n "${arg_value}" ]]; then
printf 'arg:%s.digest=%s\n' "${arg_name}" "${base_image_digest:-unknown}"
fi
done
}
rocm_version_from_base_image() {
local base_image="$1"
local version=""
version="$(sed -n -E 's/.*:([0-9]+\.[0-9]+(\.[0-9]+)?)-.*/\1/p' <<<"${base_image}")"
tag_component "${version:-${base_image}}" 16
}
git_diff_changed_base() {
local range="$1"
[[ -n "$(git diff --name-only "${range}" -- "${DOCKERFILE}" 2>/dev/null)" ]]
}
short_git_ref() {
local ref="$1"
git rev-parse --short "${ref}" 2>/dev/null || printf '%s\n' "${ref}"
}
extract_arg_default_from_ref() {
local ref="$1"
local arg_name="$2"
local content=""
content="$(git show "${ref}:${DOCKERFILE}" 2>/dev/null || true)"
sed -n -E "s/^[[:space:]]*ARG[[:space:]]+${arg_name}=\"?([^\"[:space:]]+)\"?.*/\\1/p" \
<<<"${content}" | head -1
}
log_arg_default_changes() {
local old_ref="$1"
local new_ref="$2"
local content_args="${ROCM_BASE_CONTENT_ARGS:-${DEFAULT_ROCM_BASE_CONTENT_ARGS}}"
local arg_name=""
local old_value=""
local new_value=""
local changed=0
echo "Changed ROCm base ARG defaults:"
for arg_name in ${content_args}; do
old_value="$(extract_arg_default_from_ref "${old_ref}" "${arg_name}")"
new_value="$(extract_arg_default_from_ref "${new_ref}" "${arg_name}")"
if [[ "${old_value}" != "${new_value}" ]]; then
echo " - ${arg_name}: ${old_value:-<unset>} -> ${new_value:-<unset>}"
changed=1
fi
done
if [[ "${changed}" == "0" ]]; then
echo " - none detected; Dockerfile instructions changed outside tracked ARG defaults"
fi
}
log_arg_line_diff() {
local range="$1"
local arg_diff=""
arg_diff="$(
git diff --unified=0 "${range}" -- "${DOCKERFILE}" 2>/dev/null \
| awk '/^[+-][[:space:]]*ARG[[:space:]]/ && $0 !~ /^(---|\+\+\+)/ { print " " $0 }' \
|| true
)"
if [[ -n "${arg_diff}" ]]; then
echo "Changed Dockerfile ARG lines:"
printf '%s\n' "${arg_diff}"
fi
}
log_rocm_base_change_check() {
local context="$1"
local range="$2"
local old_ref="$3"
local old_short=""
local head_short=""
old_short="$(short_git_ref "${old_ref}")"
head_short="$(short_git_ref HEAD)"
echo "--- :mag: ROCm base refresh check"
echo "Context: ${context}"
echo "Dockerfile: ${DOCKERFILE}"
echo "Base revision: ${old_short}"
echo "Head revision: ${head_short}"
echo "Git diff range: ${range}"
}
log_rocm_base_rebuild_reason() {
local context="$1"
local range="$2"
local old_ref="$3"
local changed_files=""
log_rocm_base_change_check "${context}" "${range}" "${old_ref}"
changed_files="$(git diff --name-only "${range}" -- "${DOCKERFILE}" 2>/dev/null || true)"
echo "Changed files:"
if [[ -n "${changed_files}" ]]; then
sed 's/^/ - /' <<<"${changed_files}"
else
echo " - ${DOCKERFILE}"
fi
log_arg_default_changes "${old_ref}" HEAD
log_arg_line_diff "${range}"
echo "Decision: rebuilding ROCm base image because ${DOCKERFILE} changed."
}
rocm_base_changed_in_range() {
local context="$1"
local range="$2"
local old_ref="$3"
if git_diff_changed_base "${range}"; then
log_rocm_base_rebuild_reason "${context}" "${range}" "${old_ref}"
return 0
fi
log_rocm_base_change_check "${context}" "${range}" "${old_ref}"
echo "Decision: ROCm base refresh not required; ${DOCKERFILE} is unchanged."
return 1
}
rocm_base_changed() {
local base_branch="${BUILDKITE_PULL_REQUEST_BASE_BRANCH:-main}"
local base_ref="refs/remotes/origin/${base_branch}"
local merge_base=""
if [[ "${ROCM_BASE_REFRESH_SKIP:-0}" == "1" ]]; then
echo "ROCM_BASE_REFRESH_SKIP=1 set; skipping ROCm base refresh"
return 1
fi
if [[ "${ROCM_BASE_REFRESH_FORCE:-0}" == "1" ]]; then
echo "ROCM_BASE_REFRESH_FORCE=1 set; refreshing ROCm base image"
return 0
fi
if ! git rev-parse --is-inside-work-tree >/dev/null 2>&1; then
echo "Not in a git checkout; skipping ROCm base refresh unless forced"
return 1
fi
if [[ "${BUILDKITE_PULL_REQUEST:-false}" != "false" ]]; then
git fetch --no-tags --depth=200 origin \
"+refs/heads/${base_branch}:${base_ref}" >/dev/null 2>&1 || true
merge_base=$(git merge-base HEAD "${base_ref}" 2>/dev/null || true)
if [[ -z "${merge_base}" ]]; then
echo "Unable to determine merge base with PR base ${base_ref}; skipping ROCm base refresh unless forced"
return 1
fi
if rocm_base_changed_in_range \
"pull request build against ${base_ref}" \
"${merge_base}...HEAD" \
"${merge_base}"; then
return 0
fi
elif [[ "${BUILDKITE_BRANCH:-}" == "${ROCM_BASE_STABLE_BRANCH:-main}" ]] \
&& git rev-parse --verify HEAD~1 >/dev/null 2>&1; then
if rocm_base_changed_in_range \
"stable branch build; comparing against previous ${ROCM_BASE_STABLE_BRANCH:-main} commit" \
"HEAD~1..HEAD" \
"HEAD~1"; then
return 0
fi
else
git fetch --no-tags --depth=200 origin \
"+refs/heads/${base_branch}:${base_ref}" >/dev/null 2>&1 || true
merge_base=$(git merge-base HEAD "${base_ref}" 2>/dev/null || true)
if [[ -z "${merge_base}" ]]; then
echo "Unable to determine merge base with branch base ${base_ref}; skipping ROCm base refresh unless forced"
return 1
fi
if rocm_base_changed_in_range \
"branch build against ${base_ref}" \
"${merge_base}...HEAD" \
"${merge_base}"; then
return 0
fi
fi
return 1
}
should_push_stable_tag() {
if [[ "${BUILDKITE_PULL_REQUEST:-false}" != "false" ]]; then
return 1
fi
if [[ "${ROCM_BASE_PUSH_STABLE_TAG:-}" == "1" ]]; then
return 0
fi
if [[ "${ROCM_BASE_PUSH_STABLE_TAG:-}" == "0" ]]; then
return 1
fi
[[ "${BUILDKITE_PULL_REQUEST:-false}" == "false" \
&& "${BUILDKITE_BRANCH:-}" == "${ROCM_BASE_STABLE_BRANCH:-main}" ]]
}
setup_builder() {
echo "--- :buildkite: Setting up buildx builder for ROCm base"
if docker buildx inspect "${BUILDER_NAME}" >/dev/null 2>&1; then
docker buildx use "${BUILDER_NAME}"
else
docker buildx create --name "${BUILDER_NAME}" --driver docker-container --use
fi
docker buildx inspect --bootstrap
}
compute_base_content_hash() {
local use_sccache="$1"
local base_image_digest="$2"
local content_files="${ROCM_BASE_CONTENT_FILES:-${DEFAULT_ROCM_BASE_CONTENT_FILES}}"
local content_args="${ROCM_BASE_CONTENT_ARGS:-${DEFAULT_ROCM_BASE_CONTENT_ARGS}}"
local -a content_paths=()
local -a content_arg_names=()
read -r -a content_paths <<< "${content_files}"
read -r -a content_arg_names <<< "${content_args}"
{
printf 'content-files-hash:%s\n' "$(compute_content_hash "${content_paths[@]}")"
printf 'dockerfile:%s\n' "${DOCKERFILE}"
printf 'resolved-build-args:\n'
hash_rocm_base_arg_values \
"${use_sccache}" "${base_image_digest}" "${content_arg_names[@]}"
} | sha256sum | cut -d' ' -f1
}
build_base_image() {
local use_sccache="${ROCM_BASE_USE_SCCACHE:-${USE_SCCACHE:-0}}"
local base_hash=""
local build_date=""
local build_suffix=""
local base_image_arg=""
local base_image_digest=""
local rocm_version=""
local triton_arg=""
local pytorch_arg=""
local pytorch_vision_arg=""
local pytorch_audio_arg=""
local fa_arg=""
local aiter_arg=""
local mori_arg=""
local python_version_arg=""
local pytorch_rocm_arch_arg=""
local pytorch_branch=""
local aiter_branch=""
local dependency_summary=""
local descriptor=""
local ci_descriptor=""
local descriptive_tag=""
local stable_tag="${BASE_REPO}:base"
local ci_descriptive_tag=""
local content_files="${ROCM_BASE_CONTENT_FILES:-${DEFAULT_ROCM_BASE_CONTENT_FILES}}"
local content_args="${ROCM_BASE_CONTENT_ARGS:-${DEFAULT_ROCM_BASE_CONTENT_ARGS}}"
local content_files_hash=""
local metadata_version="${ROCM_BASE_METADATA_VERSION:-${DEFAULT_ROCM_BASE_METADATA_VERSION}}"
local -a tags=()
local -a no_cache_args=()
local -a sccache_args=()
local -a content_paths=()
if [[ ! -f "${DOCKERFILE}" ]]; then
echo "Error: ROCm base Dockerfile not found: ${DOCKERFILE}" >&2
exit 1
fi
build_date="${ROCM_BASE_TAG_DATE:-$(date -u +%Y%m%d)}"
if [[ -n "${BUILDKITE_BUILD_NUMBER:-}" ]]; then
build_suffix="_bk_${BUILDKITE_BUILD_NUMBER}"
fi
base_image_arg="$(extract_arg_default BASE_IMAGE)"
base_image_digest="$(resolve_image_digest "${base_image_arg}")"
read -r -a content_paths <<< "${content_files}"
content_files_hash="$(compute_content_hash "${content_paths[@]}")"
base_hash=$(compute_base_content_hash "${use_sccache}" "${base_image_digest}")
rocm_version="$(rocm_version_from_base_image "${base_image_arg}")"
triton_arg="$(extract_arg_default TRITON_BRANCH)"
pytorch_arg="$(extract_arg_default PYTORCH_BRANCH)"
pytorch_vision_arg="$(extract_arg_default PYTORCH_VISION_BRANCH)"
pytorch_audio_arg="$(extract_arg_default PYTORCH_AUDIO_BRANCH)"
fa_arg="$(extract_arg_default FA_BRANCH)"
aiter_arg="$(extract_arg_default AITER_BRANCH)"
mori_arg="$(extract_arg_default MORI_BRANCH)"
python_version_arg="$(extract_arg_default PYTHON_VERSION)"
pytorch_rocm_arch_arg="$(extract_arg_default PYTORCH_ROCM_ARCH)"
pytorch_branch="$(tag_component "${pytorch_arg}" 16)"
aiter_branch="$(tag_component "${aiter_arg}" 24)"
dependency_summary="base=${base_image_arg},rocm=${rocm_version},python=${python_version_arg},pytorch=${pytorch_arg},torchvision=${pytorch_vision_arg},torchaudio=${pytorch_audio_arg},triton=${triton_arg},flash-attn=${fa_arg},aiter=${aiter_arg},mori=${mori_arg},pytorch-rocm-arch=${pytorch_rocm_arch_arg}"
descriptor="$(clean_docker_tag "base_custom_aiter_${aiter_branch}_torch_${pytorch_branch}_${build_date}${build_suffix}")"
ci_descriptor="$(clean_docker_tag "ci_custom_aiter_${aiter_branch}_torch_${pytorch_branch}_${build_date}${build_suffix}")"
descriptive_tag="${BASE_REPO}:${descriptor}"
ci_descriptive_tag="${CI_IMAGE_REPO}:${ci_descriptor}"
tags=(-t "${descriptive_tag}")
if should_push_stable_tag; then
tags+=(-t "${stable_tag}")
metadata_set "rocm-base-push-stable-tag" "1"
else
metadata_set "rocm-base-push-stable-tag" "0"
fi
if [[ "${ROCM_BASE_NO_CACHE:-1}" == "1" ]]; then
no_cache_args=(--no-cache)
fi
for env_name in \
SCCACHE_DOWNLOAD_URL \
SCCACHE_ENDPOINT \
SCCACHE_BUCKET_NAME \
SCCACHE_REGION_NAME \
SCCACHE_S3_NO_CREDENTIALS; do
if [[ -n "${!env_name:-}" ]]; then
sccache_args+=(--build-arg "${env_name}=${!env_name}")
fi
done
echo "--- :docker: Building ROCm base image"
echo "Dockerfile: ${DOCKERFILE}"
echo "Descriptive tag: ${descriptive_tag}"
echo "Stable tag: ${stable_tag} ($(should_push_stable_tag && echo enabled || echo disabled))"
echo "Content hash: ${base_hash}"
echo "Dependency summary: ${dependency_summary}"
echo "USE_SCCACHE: ${use_sccache}"
docker buildx build \
"${no_cache_args[@]}" \
--pull \
--progress "${BUILDKIT_PROGRESS:-plain}" \
--file "${DOCKERFILE}" \
--build-arg "USE_SCCACHE=${use_sccache}" \
"${sccache_args[@]}" \
--label "org.opencontainers.image.source=https://github.com/vllm-project/vllm" \
--label "org.opencontainers.image.vendor=vLLM" \
--label "org.opencontainers.image.title=vLLM ROCm base" \
--label "org.opencontainers.image.revision=${BUILDKITE_COMMIT:-}" \
--label "vllm.rocm_base.metadata_version=${metadata_version}" \
--label "vllm.rocm_base.content_hash=${base_hash}" \
--label "vllm.rocm_base.content_files_hash=${content_files_hash}" \
--label "vllm.rocm_base.dockerfile=${DOCKERFILE}" \
--label "vllm.rocm_base.image.descriptive=${descriptive_tag}" \
--label "vllm.rocm_base.image.stable=${stable_tag}" \
--label "vllm.rocm_base.git_commit=${BUILDKITE_COMMIT:-}" \
--label "vllm.rocm_base.stable_branch=${ROCM_BASE_STABLE_BRANCH:-main}" \
--label "vllm.rocm_base.descriptor=${descriptor}" \
--label "vllm.rocm_base.dependency_summary=${dependency_summary}" \
--label "vllm.rocm_base.base_image=${base_image_arg}" \
--label "vllm.rocm_base.base_image_digest=${base_image_digest}" \
--label "vllm.rocm_base.dependency.rocm=${rocm_version}" \
--label "vllm.rocm_base.dependency.python=${python_version_arg}" \
--label "vllm.rocm_base.dependency.pytorch=${pytorch_arg}" \
--label "vllm.rocm_base.dependency.torchvision=${pytorch_vision_arg}" \
--label "vllm.rocm_base.dependency.torchaudio=${pytorch_audio_arg}" \
--label "vllm.rocm_base.dependency.triton=${triton_arg}" \
--label "vllm.rocm_base.dependency.flash_attention=${fa_arg}" \
--label "vllm.rocm_base.dependency.aiter=${aiter_arg}" \
--label "vllm.rocm_base.dependency.mori=${mori_arg}" \
--label "vllm.rocm_base.pytorch_rocm_arch=${pytorch_rocm_arch_arg}" \
"${tags[@]}" \
--push \
.
docker buildx imagetools inspect "${descriptive_tag}" >/dev/null
metadata_set "rocm-base-refresh" "1"
metadata_set "rocm-base-image" "${descriptive_tag}"
metadata_set "rocm-base-image-descriptive" "${descriptive_tag}"
metadata_set "rocm-base-image-stable" "${stable_tag}"
metadata_set "rocm-base-image-ci-descriptive" "${ci_descriptive_tag}"
metadata_set "rocm-base-metadata-version" "${metadata_version}"
metadata_set "rocm-base-content-hash" "${base_hash}"
metadata_set "rocm-base-content-files-hash" "${content_files_hash}"
metadata_set "rocm-base-content-files" "${content_files}"
metadata_set "rocm-base-content-args" "${content_args}"
metadata_set "rocm-base-base-image-digest" "${base_image_digest}"
metadata_set "rocm-base-dockerfile" "${DOCKERFILE}"
metadata_set "rocm-base-descriptor" "${descriptor}"
metadata_set "rocm-base-dependency-summary" "${dependency_summary}"
metadata_set "rocm-base-dependency-rocm" "${rocm_version}"
metadata_set "rocm-base-dependency-python" "${python_version_arg}"
metadata_set "rocm-base-dependency-pytorch" "${pytorch_arg}"
metadata_set "rocm-base-dependency-torchvision" "${pytorch_vision_arg}"
metadata_set "rocm-base-dependency-torchaudio" "${pytorch_audio_arg}"
metadata_set "rocm-base-dependency-triton" "${triton_arg}"
metadata_set "rocm-base-dependency-flash-attention" "${fa_arg}"
metadata_set "rocm-base-dependency-aiter" "${aiter_arg}"
metadata_set "rocm-base-dependency-mori" "${mori_arg}"
metadata_set "rocm-base-pytorch-rocm-arch" "${pytorch_rocm_arch_arg}"
metadata_set "rocm-ci-image-descriptive" "${ci_descriptive_tag}"
echo "--- :white_check_mark: ROCm base image published"
echo "Use BASE_IMAGE=${descriptive_tag} for downstream ROCm CI builds"
}
main() {
metadata_set "rocm-base-refresh" "0"
if ! rocm_base_changed; then
echo "ROCm base Dockerfile did not change; skipping base image refresh"
return 0
fi
setup_builder
build_base_image
}
main "$@"
@@ -1,32 +0,0 @@
#!/usr/bin/env bash
# Fast structural smoke test for the full ROCm CI image.
set -euo pipefail
image_ref="${VLLM_CI_SMOKE_IMAGE:-rocm/vllm-ci:${BUILDKITE_COMMIT:?BUILDKITE_COMMIT is required}}"
docker run --rm --network=none --entrypoint /bin/bash "${image_ref}" -ec '
if [ ! -d /vllm-workspace ]; then echo Missing directory: /vllm-workspace >&2; exit 1; fi
if [ ! -d /vllm-workspace/tests ]; then echo Missing directory: /vllm-workspace/tests >&2; exit 1; fi
if [ ! -d /vllm-workspace/src/vllm ]; then echo Missing directory: /vllm-workspace/src/vllm >&2; exit 1; fi
if [ ! -x /vllm-workspace/src/vllm/vllm-rs ]; then echo Missing executable: /vllm-workspace/src/vllm/vllm-rs >&2; exit 1; fi
command -v python3
command -v uv
command -v pytest
if ! command -v amd-smi >/dev/null 2>&1 && ! command -v rocminfo >/dev/null 2>&1; then
echo No ROCm CLI found in image >&2
exit 1
fi
python3 - <<PY
import torch
import vllm
print(torch.__version__)
print(vllm.__version__)
PY
echo AMD image smoke OK
'
+1 -3
View File
@@ -109,9 +109,7 @@ run_nodes() {
if [ "$node" -ne 0 ]; then
docker exec -d "node$node" /bin/bash -c "cd $WORKING_DIR ; ${COMMANDS[$node]}"
else
# Allocate a TTY (-t -i) for the foreground head node so its output
# keeps ANSI color in the Buildkite log (see run-amd-test.sh).
docker exec -t -i "node$node" /bin/bash -c "cd $WORKING_DIR ; ${COMMANDS[$node]}"
docker exec "node$node" /bin/bash -c "cd $WORKING_DIR ; ${COMMANDS[$node]}"
fi
done
}
@@ -8,12 +8,7 @@ if [[ "$MODE" != "style-clippy" && "$MODE" != "test" ]]; then
exit 2
fi
if ROOT_DIR="$(git rev-parse --show-toplevel 2>/dev/null)"; then
:
else
SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd -P)"
ROOT_DIR="$(cd -- "${SCRIPT_DIR}/../.." && pwd -P)"
fi
ROOT_DIR="$(git rev-parse --show-toplevel)"
cd "$ROOT_DIR"
export CARGO_TERM_COLOR="${CARGO_TERM_COLOR:-always}"
@@ -21,21 +16,16 @@ export CARGO_HOME="${CARGO_HOME:-$HOME/.cargo}"
export RUSTUP_HOME="${RUSTUP_HOME:-$HOME/.rustup}"
export PATH="$CARGO_HOME/bin:$PATH"
PROTOC_VERSION="${PROTOC_VERSION:-31.1}"
CARGO_BINSTALL_VERSION="${CARGO_BINSTALL_VERSION:-1.20.1}"
UV_VERSION="${UV_VERSION:-0.11.28}"
PYO3_PYTHON_VERSION="${PYO3_PYTHON_VERSION:-3.12}"
CARGO_SORT_VERSION_REQ="${CARGO_SORT_VERSION_REQ:-2}"
CARGO_DENY_VERSION_REQ="${CARGO_DENY_VERSION_REQ:-0.20}"
CARGO_NEXTEST_VERSION_REQ="${CARGO_NEXTEST_VERSION_REQ:-0.9}"
CARGO_LLVM_COV_VERSION="${CARGO_LLVM_COV_VERSION:-0.8.7}"
log_section() {
echo "--- $*"
}
install_protoc() {
if command -v protoc >/dev/null 2>&1; then
return
fi
local version="${PROTOC_VERSION:-31.1}"
local arch
case "$(uname -m)" in
x86_64)
@@ -50,17 +40,16 @@ install_protoc() {
;;
esac
local url="https://github.com/protocolbuffers/protobuf/releases/download/v${PROTOC_VERSION}/protoc-${PROTOC_VERSION}-linux-${arch}.zip"
local url="https://github.com/protocolbuffers/protobuf/releases/download/v${version}/protoc-${version}-linux-${arch}.zip"
local tmp_dir
tmp_dir="$(mktemp -d)"
log_section "Installing protoc ${PROTOC_VERSION}"
log_section "Installing protoc ${version}"
curl -L --proto '=https' --tlsv1.2 -sSf "$url" -o "$tmp_dir/protoc.zip"
mkdir -p "$CARGO_HOME/bin"
unzip -q "$tmp_dir/protoc.zip" bin/protoc 'include/*' -d "$CARGO_HOME"
chmod +x "$CARGO_HOME/bin/protoc"
rm -rf "$tmp_dir"
protoc --version
}
rust_toolchain() {
@@ -81,60 +70,56 @@ install_rust_toolchain() {
}
install_cargo_binstall() {
log_section "Installing cargo-binstall ${CARGO_BINSTALL_VERSION}"
if command -v cargo-binstall >/dev/null 2>&1; then
return
fi
log_section "Installing cargo-binstall"
curl -L --proto '=https' --tlsv1.2 -sSf \
"https://raw.githubusercontent.com/cargo-bins/cargo-binstall/v${CARGO_BINSTALL_VERSION}/install-from-binstall-release.sh" \
| env BINSTALL_VERSION="$CARGO_BINSTALL_VERSION" bash
cargo-binstall -V
https://raw.githubusercontent.com/cargo-bins/cargo-binstall/main/install-from-binstall-release.sh \
| bash
}
install_cargo_sort() {
log_section "Installing cargo-sort ${CARGO_SORT_VERSION_REQ}"
cargo binstall --no-confirm --force "cargo-sort@${CARGO_SORT_VERSION_REQ}"
}
if command -v cargo-sort >/dev/null 2>&1; then
return
fi
install_cargo_deny() {
log_section "Installing cargo-deny ${CARGO_DENY_VERSION_REQ}"
cargo binstall --no-confirm --force "cargo-deny@${CARGO_DENY_VERSION_REQ}"
log_section "Installing cargo-sort"
install_cargo_binstall
cargo binstall --no-confirm cargo-sort
}
install_cargo_nextest() {
log_section "Installing cargo-nextest ${CARGO_NEXTEST_VERSION_REQ}"
cargo binstall \
--no-confirm \
--force \
--secure \
"cargo-nextest@${CARGO_NEXTEST_VERSION_REQ}"
}
if command -v cargo-nextest >/dev/null 2>&1; then
return
fi
install_cargo_llvm_cov() {
log_section "Installing cargo-llvm-cov ${CARGO_LLVM_COV_VERSION}"
local toolchain
toolchain="$(rust_toolchain)"
rustup component add --toolchain "$toolchain" llvm-tools-preview
cargo binstall \
--no-confirm \
--force \
--secure \
"cargo-llvm-cov@${CARGO_LLVM_COV_VERSION}"
log_section "Installing cargo-nextest"
install_cargo_binstall
cargo binstall --no-confirm --secure cargo-nextest
}
install_uv() {
log_section "Installing uv ${UV_VERSION}"
curl -L --proto '=https' --tlsv1.2 -sSf \
"https://github.com/astral-sh/uv/releases/download/${UV_VERSION}/uv-installer.sh" \
if command -v uv >/dev/null 2>&1; then
return
fi
log_section "Installing uv"
curl -LsSf --proto '=https' --tlsv1.2 https://astral.sh/uv/install.sh \
| env UV_INSTALL_DIR="$CARGO_HOME/bin" sh
uv --version
}
setup_pyo3_python() {
log_section "Installing Python ${PYO3_PYTHON_VERSION} for PyO3 tests"
uv python install "$PYO3_PYTHON_VERSION"
local python_version="${PYO3_PYTHON_VERSION:-3.12}"
log_section "Installing Python ${python_version} for PyO3 tests"
uv python install "$python_version"
PYO3_PYTHON="$(uv python find \
--managed-python \
--no-project \
--resolve-links \
"$PYO3_PYTHON_VERSION")"
"$python_version")"
export PYO3_PYTHON
local python_libdir
@@ -156,9 +141,7 @@ PY
}
run_style_clippy() {
install_cargo_binstall
install_cargo_sort
install_cargo_deny
log_section "Checking Rust formatting"
cargo fmt --manifest-path rust/Cargo.toml --all -- --check
@@ -166,13 +149,6 @@ run_style_clippy() {
log_section "Checking Cargo.toml ordering"
cargo sort --workspace --check rust
log_section "Checking Rust dependency bans"
cargo deny \
--manifest-path rust/Cargo.toml \
--config rust/deny.toml \
check \
bans
log_section "Running clippy"
cargo clippy \
--manifest-path rust/Cargo.toml \
@@ -187,43 +163,15 @@ run_style_clippy() {
run_tests() {
install_uv
setup_pyo3_python
install_cargo_binstall
install_cargo_nextest
install_cargo_llvm_cov
log_section "Running cargo nextest with Rust coverage"
mkdir -p artifacts
export LLVM_PROFILE_FILE_NAME="vllm-rust-unit-%4m.profraw"
cargo llvm-cov clean \
--manifest-path rust/Cargo.toml \
--profraw-only
set +e
cargo llvm-cov nextest \
log_section "Running cargo nextest"
cargo nextest run \
--manifest-path rust/Cargo.toml \
--workspace \
--all-features \
--locked \
--no-fail-fast \
--no-clean \
--lcov \
--output-path artifacts/rust-unit.lcov \
--ignore-filename-regex='/\.cargo/(registry|git)/|/rustc/|/target/'
local coverage_rc=$?
local upload_rc=0
if [[ $coverage_rc -eq 0 ]]; then
# shellcheck source=.buildkite/scripts/rust-coverage.sh
source .buildkite/scripts/rust-coverage.sh
rust_coverage_upload artifacts/rust-unit.lcov rust-unit
upload_rc=$?
fi
set -e
if [[ $coverage_rc -ne 0 ]]; then
return "$coverage_rc"
fi
return "$upload_rc"
--no-fail-fast
}
install_protoc
-182
View File
@@ -1,182 +0,0 @@
#!/bin/sh
RUST_CODECOV_VERSION="v11.3.1"
RUST_CODECOV_SHA256="ca1d64196d2d34771084afe76ea657d581bf628e31d993ff8e52ea09cc88a56d"
rust_coverage_repo_root() {
if [ -f /vllm-workspace/.buildkite/scripts/rust-coverage.sh ]; then
printf '%s\n' /vllm-workspace
elif [ -n "${BUILDKITE_BUILD_CHECKOUT_PATH:-}" ] \
&& [ -d "$BUILDKITE_BUILD_CHECKOUT_PATH" ]; then
printf '%s\n' "$BUILDKITE_BUILD_CHECKOUT_PATH"
else
git rev-parse --show-toplevel
fi
}
rust_coverage_start() {
RUST_COVERAGE_FLAG=${1:?coverage flag is required}
RUST_COVERAGE_DIR="/tmp/vllm-rust-coverage/${BUILDKITE_JOB_ID:-local}"
export RUST_COVERAGE_FLAG RUST_COVERAGE_DIR
mkdir -p "$RUST_COVERAGE_DIR"
LLVM_PROFILE_FILE="$RUST_COVERAGE_DIR/rust-%4m.profraw"
export LLVM_PROFILE_FILE
trap rust_coverage_finalize 0
}
rust_coverage_objects() {
rust_cov_objects_manifest="$(dirname "$(command -v llvm-cov)")/../objects"
python3 - "$rust_cov_objects_manifest" <<'PY'
from pathlib import Path
import sys
for relative in Path(sys.argv[1]).read_text().splitlines():
for entry in sys.path:
path = Path(entry or ".").resolve() / relative
if path.is_file():
print(path)
break
else:
raise RuntimeError(f"installed Rust coverage object was not found: {relative}")
PY
}
rust_coverage_collect() {
rust_cov_collect_flag=${1:?coverage flag is required}
rust_cov_collect_lcov="$RUST_COVERAGE_DIR/$rust_cov_collect_flag.lcov"
rust_cov_collect_objects=$(rust_coverage_objects) || return 1
rust_cov_collect_primary=
set --
while IFS= read -r rust_cov_collect_object; do
if [ -z "$rust_cov_collect_primary" ]; then
rust_cov_collect_primary=$rust_cov_collect_object
else
set -- "$@" "--object=$rust_cov_collect_object"
fi
done <<EOF
$rust_cov_collect_objects
EOF
llvm-profdata merge \
-sparse \
"$RUST_COVERAGE_DIR"/*.profraw \
-o "$RUST_COVERAGE_DIR/merged.profdata" || return 1
llvm-cov export \
"$rust_cov_collect_primary" \
"$@" \
--format=lcov \
--instr-profile="$RUST_COVERAGE_DIR/merged.profdata" \
--ignore-filename-regex='/\.cargo/(registry|git)/|/rustc/|/target/' \
> "$rust_cov_collect_lcov" || return 1
RUST_COVERAGE_LCOV=$rust_cov_collect_lcov
export RUST_COVERAGE_LCOV
}
rust_coverage_upload() {
rust_cov_upload_lcov=${1:?LCOV path is required}
rust_cov_upload_flag=${2:?coverage flag is required}
rust_cov_upload_repo_root=$(rust_coverage_repo_root) || return 1
if [ "$(uname -m)" != "x86_64" ]; then
echo "Rust coverage upload currently supports x86_64 CI agents" >&2
return 1
fi
rust_cov_upload_codecov_dir=$(mktemp -d /tmp/codecov-bin.XXXXXX) \
|| return 1
curl -fsSL \
"https://github.com/codecov/codecov-cli/releases/download/${RUST_CODECOV_VERSION}/codecovcli_linux" \
-o "$rust_cov_upload_codecov_dir/codecov" || return 1
echo "$RUST_CODECOV_SHA256 $rust_cov_upload_codecov_dir/codecov" \
| sha256sum -c - || return 1
chmod +x "$rust_cov_upload_codecov_dir/codecov" || return 1
rust_cov_upload_slug="vllm-project/vllm"
if [ -n "${BUILDKITE_PULL_REQUEST:-}" ] \
&& [ "${BUILDKITE_PULL_REQUEST}" != "false" ] \
&& [ -n "${BUILDKITE_PULL_REQUEST_REPO:-}" ]; then
rust_cov_upload_slug=$(echo "$BUILDKITE_PULL_REQUEST_REPO" \
| sed -E 's#(git@|https?://)([^/:]+)[:/]([^/]+/[^/.]+)(\.git)?$#\3#')
case "$rust_cov_upload_slug" in
*/*) ;;
*) rust_cov_upload_slug="vllm-project/vllm" ;;
esac
fi
rust_cov_upload_branch=${BUILDKITE_BRANCH:?BUILDKITE_BRANCH is required}
if [ -z "${CODECOV_TOKEN:-}" ]; then
# Codecov accepts tokenless public uploads on unprotected branch names.
# A colon-separated prefix keeps feature-branch and fork uploads from
# requiring a repository secret.
if [ -n "${BUILDKITE_PULL_REQUEST:-}" ] \
&& [ "${BUILDKITE_PULL_REQUEST}" != "false" ]; then
rust_cov_upload_branch="pr${BUILDKITE_PULL_REQUEST}:$rust_cov_upload_branch"
else
rust_cov_upload_branch="buildkite:$rust_cov_upload_branch"
fi
fi
set --
set -- "$@" upload-process
set -- "$@" --file "$rust_cov_upload_lcov"
# LCOV paths are mapped server-side by codecov.yml. Skip the CLI's local
# source-line fix scanning, which is unrelated to path mapping.
set -- "$@" --disable-search --disable-file-fixes
set -- "$@" --fail-on-error --git-service github
set -- "$@" --build "${BUILDKITE_BUILD_NUMBER:?BUILDKITE_BUILD_NUMBER is required}"
set -- "$@" --branch "$rust_cov_upload_branch"
set -- "$@" --sha "${BUILDKITE_COMMIT:?BUILDKITE_COMMIT is required}"
set -- "$@" --slug "$rust_cov_upload_slug"
set -- "$@" --flag "$rust_cov_upload_flag"
set -- "$@" --name "${rust_cov_upload_flag}-${BUILDKITE_JOB_ID:?BUILDKITE_JOB_ID is required}"
set -- "$@" --dir "$rust_cov_upload_repo_root"
set -- "$@" --network-root-folder "$rust_cov_upload_repo_root"
if [ -n "${BUILDKITE_PULL_REQUEST:-}" ] \
&& [ "${BUILDKITE_PULL_REQUEST}" != "false" ]; then
set -- "$@" --pr "$BUILDKITE_PULL_REQUEST"
fi
rust_cov_upload_log="$rust_cov_upload_codecov_dir/codecov.log"
# E2E steps run from tests/, so execute from the repository root to resolve
# codecov.yml and repository paths consistently.
(
cd "$rust_cov_upload_repo_root" || exit 1
"$rust_cov_upload_codecov_dir/codecov" "$@"
) >"$rust_cov_upload_log" 2>&1
rust_cov_upload_rc=$?
cat "$rust_cov_upload_log"
# v11.3.1 can log API failures while returning zero even with
# --fail-on-error. Preserve the strict CI contract explicitly.
if grep -aEq 'error.* -- ' "$rust_cov_upload_log"; then
echo "Codecov CLI reported an upload error" >&2
rust_cov_upload_rc=1
fi
rm -rf "$rust_cov_upload_codecov_dir"
return "$rust_cov_upload_rc"
}
rust_coverage_finalize() {
rust_cov_finalize_test_rc=$?
trap - 0
set +e
rust_coverage_collect "$RUST_COVERAGE_FLAG"
rust_cov_finalize_collect_rc=$?
rust_cov_finalize_upload_rc=0
if [ "$rust_cov_finalize_collect_rc" -eq 0 ]; then
rust_coverage_upload "$RUST_COVERAGE_LCOV" "$RUST_COVERAGE_FLAG"
rust_cov_finalize_upload_rc=$?
fi
find "$RUST_COVERAGE_DIR" -type f -name '*.profraw' -delete
if [ "$rust_cov_finalize_test_rc" -ne 0 ]; then
exit "$rust_cov_finalize_test_rc"
fi
if [ "$rust_cov_finalize_collect_rc" -ne 0 ]; then
exit "$rust_cov_finalize_collect_rc"
fi
exit "$rust_cov_finalize_upload_rc"
}
@@ -33,14 +33,6 @@ if [[ -n "${ATTENTION_BACKEND:-}" ]]; then
EXTRA_ARGS+=(--attention-backend "${ATTENTION_BACKEND}")
fi
# ROCm: run eager to avoid intermittent HIP-graph decode corruption.
# See https://github.com/ROCm/clr/issues/279
# TODO(aarushjain29): Revert after TheRock 7.14
if command -v rocm-smi &> /dev/null || command -v amd-smi &> /dev/null || [[ -d /opt/rocm ]] || [[ -n "${ROCM_PATH:-}" ]]; then
echo "ROCm platform detected: adding --enforce-eager to avoid HIP-graph decode corruption"
EXTRA_ARGS+=(--enforce-eager)
fi
cleanup() {
if [[ -n "${SERVER_PID:-}" ]] && kill -0 "${SERVER_PID}" 2>/dev/null; then
kill "${SERVER_PID}" 2>/dev/null || true
@@ -18,10 +18,6 @@ wait_for_server() {
MODEL="Qwen/Qwen3-30B-A3B-FP8"
BACK="allgather_reducescatter"
if command -v rocm-smi &> /dev/null || [[ -d /opt/rocm ]] || [[ -n "${ROCM_PATH:-}" ]]; then
# Disable MOE padding for ROCm since it is causing eplb to fail.
export VLLM_ROCM_MOE_PADDING=0
fi
cleanup() {
if [[ -n "${SERVER_PID:-}" ]] && kill -0 "${SERVER_PID}" 2>/dev/null; then
+11 -32
View File
@@ -23,7 +23,6 @@ NC='\033[0m' # No Color
# Default configuration
PIPELINE="ci"
DRY_RUN=true
TORCH_NIGHTLY=false
usage() {
cat <<EOF
@@ -35,14 +34,12 @@ Sets RUN_ALL=1 and NIGHTLY=1 environment variables.
SAFETY: Dry-run by default. Use --execute to actually trigger a build.
Options:
--execute Actually trigger the build (default: dry-run)
--pipeline Buildkite pipeline slug (default: ${PIPELINE})
--commit Override commit SHA (default: current HEAD)
--branch Override branch name (default: current branch)
--message Custom build message (default: auto-generated)
--torch-nightly Also build and run the full suite against torch nightly
(sets TORCH_NIGHTLY=1)
--help Show this help message
--execute Actually trigger the build (default: dry-run)
--pipeline Buildkite pipeline slug (default: ${PIPELINE})
--commit Override commit SHA (default: current HEAD)
--branch Override branch name (default: current branch)
--message Custom build message (default: auto-generated)
--help Show this help message
Prerequisites:
- bk CLI installed: brew tap buildkite/buildkite && brew install buildkite/buildkite/bk
@@ -52,7 +49,6 @@ Examples:
$(basename "$0") # Dry-run, show what would happen
$(basename "$0") --execute # Actually trigger the build
$(basename "$0") --pipeline ci-shadow # Dry-run with different pipeline
$(basename "$0") --torch-nightly # Dry-run a full torch-nightly run
EOF
exit 1
}
@@ -100,10 +96,6 @@ while [[ $# -gt 0 ]]; do
MESSAGE="$2"
shift 2
;;
--torch-nightly)
TORCH_NIGHTLY=true
shift
;;
--help|-h)
usage
;;
@@ -179,17 +171,11 @@ if [[ $(echo "$REMOTE_BRANCHES" | wc -l) -gt 5 ]]; then
fi
echo ""
# Environment variables passed to the build.
BUILD_ENV=("RUN_ALL=1" "NIGHTLY=1")
if [[ "$TORCH_NIGHTLY" == true ]]; then
BUILD_ENV+=("TORCH_NIGHTLY=1")
fi
log_info "Pipeline: ${PIPELINE}"
log_info "Branch: ${BRANCH}"
log_info "Commit: ${COMMIT}"
log_info "Message: ${MESSAGE}"
log_info "Environment: ${BUILD_ENV[*]}"
log_info "Environment: RUN_ALL=1, NIGHTLY=1"
echo ""
# Build the command
@@ -201,10 +187,9 @@ CMD=(bk build create
--commit "${COMMIT}"
--branch "${BRANCH}"
--message "${MESSAGE}"
--env "RUN_ALL=1"
--env "NIGHTLY=1"
)
for env_var in "${BUILD_ENV[@]}"; do
CMD+=(--env "${env_var}")
done
if [[ "$DRY_RUN" == true ]]; then
echo "=========================================="
@@ -225,14 +210,8 @@ if [[ "$DRY_RUN" == true ]]; then
echo " --commit '$(escape_for_shell "${COMMIT}")' \\"
echo " --branch '$(escape_for_shell "${BRANCH}")' \\"
echo " --message '$(escape_for_shell "${MESSAGE}")' \\"
last_idx=$(( ${#BUILD_ENV[@]} - 1 ))
for i in "${!BUILD_ENV[@]}"; do
if [[ $i -eq $last_idx ]]; then
echo " --env '$(escape_for_shell "${BUILD_ENV[$i]}")'"
else
echo " --env '$(escape_for_shell "${BUILD_ENV[$i]}")' \\"
fi
done
echo " --env 'RUN_ALL=1' \\"
echo " --env 'NIGHTLY=1'"
echo ""
echo "=========================================="
echo -e "${YELLOW}To actually trigger this build, run:${NC}"
+4 -12
View File
@@ -6,14 +6,8 @@ set -ex
# manylinux platform tag with auditwheel.
# Index generation is handled separately by generate-and-upload-nightly-index.sh.
# auditwheel is Linux-only; macOS wheels already carry a valid tag, so skip the
# manylinux retag for them.
WHEEL_PLATFORM="${VLLM_WHEEL_PLATFORM:-linux}"
if [[ "$WHEEL_PLATFORM" == "linux" ]]; then
# shellcheck source=lib/manylinux.sh
source .buildkite/scripts/lib/manylinux.sh
fi
# shellcheck source=lib/manylinux.sh
source .buildkite/scripts/lib/manylinux.sh
BUCKET="vllm-wheels"
SUBPATH=$BUILDKITE_COMMIT
@@ -33,10 +27,8 @@ wheel="${wheel_files[0]}"
# ========= detect manylinux tag and rename ==========
if [[ "$WHEEL_PLATFORM" == "linux" ]]; then
wheel="$(apply_manylinux_tag "$wheel")"
echo "Renamed wheel to: $wheel"
fi
wheel="$(apply_manylinux_tag "$wheel")"
echo "Renamed wheel to: $wheel"
# Extract the version from the wheel
version=$(unzip -p "$wheel" '**/METADATA' | grep '^Version: ' | cut -d' ' -f2)
+3 -3
View File
@@ -113,8 +113,8 @@ $PYTHON .buildkite/scripts/generate-nightly-index.py \
echo "Uploading indices to $S3_COMMIT_PREFIX"
aws s3 cp --recursive "$INDICES_OUTPUT_DIR/" "$S3_COMMIT_PREFIX"
# Only scheduled nightly builds should update the moving nightly index.
if [[ "${NIGHTLY:-0}" == "1" ]]; then
# Update rocm/nightly/ if on main branch and not a PR
if [[ "$BUILDKITE_BRANCH" == "main" && "$BUILDKITE_PULL_REQUEST" == "false" ]] || [[ "$NIGHTLY" == "1" ]]; then
echo "Updating rocm/nightly/ index..."
aws s3 cp --recursive "$INDICES_OUTPUT_DIR/" "s3://$BUCKET/rocm/nightly/"
fi
@@ -147,7 +147,7 @@ echo ""
echo "Install command (by commit):"
echo " pip install vllm --extra-index-url https://${BUCKET}.s3.amazonaws.com/$ROCM_SUBPATH/"
echo ""
if [[ "${NIGHTLY:-0}" == "1" ]]; then
if [[ "$BUILDKITE_BRANCH" == "main" ]] || [[ "$NIGHTLY" == "1" ]]; then
echo "Install command (nightly):"
echo " pip install vllm --extra-index-url https://${BUCKET}.s3.amazonaws.com/rocm/nightly/"
fi
@@ -1,13 +0,0 @@
#!/bin/bash
set -euo pipefail
REGISTRY="public.ecr.aws/q9t5s3a7"
REPO="vllm-release-repo"
ARCH_TAG="${BUILDKITE_COMMIT}-$(uname -m)-xpu"
PLATFORM_TAG="${BUILDKITE_COMMIT}-xpu"
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin ${REGISTRY}
docker manifest rm ${REGISTRY}/${REPO}:${PLATFORM_TAG} || true
docker manifest create ${REGISTRY}/${REPO}:${PLATFORM_TAG} ${REGISTRY}/${REPO}:${ARCH_TAG} --amend
docker manifest push ${REGISTRY}/${REPO}:${PLATFORM_TAG}
@@ -1,21 +0,0 @@
#!/bin/bash
set -ex
ORIG_TAG_NAME="$BUILDKITE_COMMIT"
REPO="vllm/vllm-openai-xpu"
echo "Pushing original XPU tag ${ORIG_TAG_NAME}-xpu to nightly tags in ${REPO}"
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:"$ORIG_TAG_NAME"-x86_64-xpu
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:"$ORIG_TAG_NAME"-x86_64-xpu ${REPO}:nightly-x86_64
docker push ${REPO}:nightly-x86_64
docker manifest rm ${REPO}:nightly || true
docker manifest rm ${REPO}:nightly-"$BUILDKITE_COMMIT" || true
docker manifest create ${REPO}:nightly ${REPO}:nightly-x86_64 --amend
docker manifest create ${REPO}:nightly-"$BUILDKITE_COMMIT" ${REPO}:nightly-x86_64 --amend
docker manifest push ${REPO}:nightly
docker manifest push ${REPO}:nightly-"$BUILDKITE_COMMIT"
+639 -882
View File
File diff suppressed because it is too large Load Diff
+5 -7
View File
@@ -4,7 +4,7 @@ depends_on:
steps:
- label: V1 attention (H100-MI300)
key: v1-attention-h100-mi300
timeout_in_minutes: 85
timeout_in_minutes: 30
device: h100
source_file_dependencies:
- vllm/config/attention.py
@@ -12,12 +12,11 @@ steps:
- vllm/v1/attention
- tests/v1/attention
commands:
- pytest -v -s v1/attention --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
parallelism: 2
- pytest -v -s v1/attention
mirror:
amd:
device: mi325_1
timeout_in_minutes: 95
timeout_in_minutes: 70
depends_on:
- image-build-amd
source_file_dependencies:
@@ -31,7 +30,7 @@ steps:
- label: V1 attention (B200)
key: v1-attention-b200
timeout_in_minutes: 80
timeout_in_minutes: 30
device: b200-k8s
source_file_dependencies:
- vllm/config/attention.py
@@ -39,5 +38,4 @@ steps:
- vllm/v1/attention
- tests/v1/attention
commands:
- pytest -v -s v1/attention --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
parallelism: 2
- pytest -v -s v1/attention
+1 -7
View File
@@ -4,7 +4,7 @@ depends_on:
steps:
- label: Basic Correctness
key: basic-correctness
timeout_in_minutes: 45
timeout_in_minutes: 30
device: h200_18gb
source_file_dependencies:
- vllm/
@@ -16,9 +16,3 @@ steps:
- pytest -v -s basic_correctness/test_mem.py
- pytest -v -s basic_correctness/test_basic_correctness.py
- pytest -v -s basic_correctness/test_cpu_offload.py
mirror:
amd:
device: mi325_1
timeout_in_minutes: 70
depends_on:
- image-build-amd
+2 -8
View File
@@ -4,19 +4,13 @@ depends_on:
steps:
- label: Benchmarks CLI Test
key: benchmarks-cli-test
timeout_in_minutes: 30
timeout_in_minutes: 20
device: h200_18gb
source_file_dependencies:
- vllm/
- tests/benchmarks/
commands:
- pytest -v -s benchmarks/
mirror:
amd:
dind: false
device: mi300_1
depends_on:
- image-build-amd
- label: Attention Benchmarks Smoke Test (B200)
key: attention-benchmarks-smoke-test-b200
@@ -24,7 +18,7 @@ steps:
num_gpus: 2
optional: true
working_dir: "/vllm-workspace/"
timeout_in_minutes: 20
timeout_in_minutes: 10
source_file_dependencies:
- benchmarks/attention_benchmarks/
- vllm/v1/attention/
+11 -11
View File
@@ -4,7 +4,7 @@ depends_on:
steps:
- label: Sequence Parallel Correctness Tests (2 GPUs)
key: sequence-parallel-correctness-tests-2-gpus
timeout_in_minutes: 80
timeout_in_minutes: 50
working_dir: "/vllm-workspace/"
num_devices: 2
source_file_dependencies:
@@ -19,7 +19,7 @@ steps:
- label: Sequence Parallel Correctness Tests (2xH100)
key: sequence-parallel-correctness-tests-2xh100
timeout_in_minutes: 75
timeout_in_minutes: 50
working_dir: "/vllm-workspace/"
device: h100
optional: true
@@ -30,7 +30,7 @@ steps:
- label: AsyncTP Correctness Tests (2xH100)
key: asynctp-correctness-tests-2xh100
timeout_in_minutes: 30
timeout_in_minutes: 50
working_dir: "/vllm-workspace/"
device: h100
optional: true
@@ -41,7 +41,7 @@ steps:
- label: AsyncTP Correctness Tests (B200)
key: asynctp-correctness-tests-b200
timeout_in_minutes: 30
timeout_in_minutes: 50
working_dir: "/vllm-workspace/"
device: b200-k8s
optional: true
@@ -52,7 +52,7 @@ steps:
- label: Distributed Compile Unit Tests (2xH100)
key: distributed-compile-unit-tests-2xh100
timeout_in_minutes: 45
timeout_in_minutes: 20
working_dir: "/vllm-workspace/"
device: h100
num_devices: 2
@@ -66,7 +66,7 @@ steps:
- label: Fusion and Compile Unit Tests (2xB200)
key: fusion-and-compile-unit-tests-2xb200
timeout_in_minutes: 30
timeout_in_minutes: 20
working_dir: "/vllm-workspace/"
device: b200-k8s
source_file_dependencies:
@@ -96,7 +96,7 @@ steps:
- label: Fusion E2E Quick (H100)
key: fusion-e2e-quick-h100
timeout_in_minutes: 25
timeout_in_minutes: 15
working_dir: "/vllm-workspace/"
device: h100
num_devices: 1
@@ -115,7 +115,7 @@ steps:
- label: Fusion E2E Config Sweep (H100)
key: fusion-e2e-config-sweep-h100
timeout_in_minutes: 25
timeout_in_minutes: 30
working_dir: "/vllm-workspace/"
device: h100
num_devices: 1
@@ -149,7 +149,7 @@ steps:
- label: Fusion E2E TP2 Quick (H100)
key: fusion-e2e-tp2-quick-h100
timeout_in_minutes: 35
timeout_in_minutes: 20
working_dir: "/vllm-workspace/"
device: h100
num_devices: 2
@@ -167,7 +167,7 @@ steps:
- label: Fusion E2E TP2 AR-RMS Config Sweep (H100)
key: fusion-e2e-tp2-ar-rms-config-sweep-h100
timeout_in_minutes: 30
timeout_in_minutes: 40
working_dir: "/vllm-workspace/"
device: h100
num_devices: 2
@@ -207,7 +207,7 @@ steps:
- label: Fusion E2E TP2 (B200)
key: fusion-e2e-tp2-b200
timeout_in_minutes: 45
timeout_in_minutes: 20
working_dir: "/vllm-workspace/"
device: b200-k8s
num_devices: 2
+5 -6
View File
@@ -2,9 +2,9 @@ group: CUDA
depends_on:
- image-build
steps:
- label: Platform Tests
key: platform-tests
timeout_in_minutes: 20
- label: Platform Tests (CUDA)
key: platform-tests-cuda
timeout_in_minutes: 15
device: h200_18gb
source_file_dependencies:
- vllm/envs.py
@@ -18,9 +18,8 @@ steps:
- pytest -v -s cuda/test_platform_no_cuda_init.py
- label: Cudagraph
device: h200_35gb
key: cudagraph
timeout_in_minutes: 30
timeout_in_minutes: 20
source_file_dependencies:
- tests/v1/cudagraph
- vllm/v1/cudagraph_dispatcher.py
@@ -29,4 +28,4 @@ steps:
commands:
- pytest -v -s v1/cudagraph/test_cudagraph_dispatch.py
- pytest -v -s v1/cudagraph/test_cudagraph_mode.py
- pytest -v -s v1/cudagraph/test_breakable_cudagraph.py
- pytest -v -s v1/cudagraph/test_breakable_cudagraph.py
+7 -114
View File
@@ -4,7 +4,7 @@ depends_on:
steps:
- label: Distributed NixlConnector PD accuracy (4 GPUs)
key: distributed-nixlconnector-pd-accuracy-4-gpus
timeout_in_minutes: 55
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
@@ -13,24 +13,9 @@ steps:
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
mirror:
amd:
dind: false
device: mi300_4
timeout_in_minutes: 85
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl/
- tests/v1/kv_connector/nixl_integration/
- vllm/platforms/rocm.py
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors_rocm.txt
- ATTENTION_BACKEND=TRITON_ATTN bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
- label: Distributed FlashInfer NixlConnector PD accuracy (4 GPUs)
key: distributed-flashinfer-nixlconnector-pd-accuracy-4-gpus
timeout_in_minutes: 55
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
@@ -40,19 +25,6 @@ steps:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- FLASHINFER=1 bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
- label: Push NixlConnector PP prefill PD accuracy (4 GPUs)
key: push-nixlconnector-pp-prefill-pd-accuracy-4-gpus
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl/
- tests/v1/kv_connector/nixl_integration/
- tests/v1/kv_connector/nixl_push_integration/
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- bash v1/kv_connector/nixl_push_integration/config_sweep_accuracy_test.sh
- label: DP EP Distributed NixlConnector PD accuracy tests (4 GPUs)
key: dp-ep-distributed-nixlconnector-pd-accuracy-tests-4-gpus
timeout_in_minutes: 30
@@ -64,24 +36,10 @@ steps:
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- DP_EP=1 bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
mirror:
amd:
dind: false
device: mi300_4
timeout_in_minutes: 60
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl/
- tests/v1/kv_connector/nixl_integration/
- vllm/platforms/rocm.py
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors_rocm.txt
- DP_EP=1 ATTENTION_BACKEND=TRITON_ATTN bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
- label: CrossLayer KV layout Distributed NixlConnector PD accuracy tests (4 GPUs)
key: crosslayer-kv-layout-distributed-nixlconnector-pd-accuracy-tests-4-gpus
timeout_in_minutes: 55
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
@@ -90,24 +48,10 @@ steps:
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- CROSS_LAYERS_BLOCKS=True bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
mirror:
amd:
dind: false
device: mi300_4
timeout_in_minutes: 85
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl/
- tests/v1/kv_connector/nixl_integration/
- vllm/platforms/rocm.py
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors_rocm.txt
- CROSS_LAYERS_BLOCKS=True ATTENTION_BACKEND=TRITON_ATTN bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
- label: Hybrid SSM NixlConnector PD accuracy tests (4 GPUs)
key: hybrid-ssm-nixlconnector-pd-accuracy-tests-4-gpus
timeout_in_minutes: 60
timeout_in_minutes: 25
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
@@ -116,20 +60,6 @@ steps:
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- HYBRID_SSM=1 bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
mirror:
amd:
dind: false
device: mi300_4
timeout_in_minutes: 80
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl/
- tests/v1/kv_connector/nixl_integration/
- vllm/platforms/rocm.py
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors_rocm.txt
- HYBRID_SSM=1 ATTENTION_BACKEND=TRITON_ATTN bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
- label: Hybrid SSM NixlConnector PD prefix cache test (2 GPUs)
key: hybrid-ssm-nixlconnector-pd-prefix-cache-2-gpus
@@ -147,7 +77,7 @@ steps:
- label: MultiConnector (Nixl+Offloading) PD accuracy (2 GPUs)
key: multiconnector-nixl-offloading-pd-accuracy-2-gpus
timeout_in_minutes: 40
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
@@ -162,7 +92,7 @@ steps:
- label: NixlConnector PD + Spec Decode acceptance (2 GPUs)
key: nixlconnector-pd-spec-decode-acceptance-2-gpus
timeout_in_minutes: 45
timeout_in_minutes: 30
device: a100
working_dir: "/vllm-workspace/tests"
num_devices: 2
@@ -173,25 +103,10 @@ steps:
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- bash v1/kv_connector/nixl_integration/config_sweep_spec_decode_test.sh
mirror:
amd:
dind: false
device: mi300_2
timeout_in_minutes: 70
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl/
- vllm/v1/worker/kv_connector_model_runner_mixin.py
- tests/v1/kv_connector/nixl_integration/
- vllm/platforms/rocm.py
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors_rocm.txt
- KV_CACHE_MEMORY_BYTES=8G ATTENTION_BACKEND=TRITON_ATTN bash v1/kv_connector/nixl_integration/config_sweep_spec_decode_test.sh
- label: MultiConnector (Nixl+Offloading) PD edge cases (2 GPUs)
key: multiconnector-nixl-offloading-pd-edge-cases-2-gpus
timeout_in_minutes: 25
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
@@ -203,25 +118,3 @@ steps:
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- bash v1/kv_connector/nixl_integration/run_multi_connector_edge_case_test.sh
# P TP 4 - D DPEP 4 test case for DSv4-Flash
- label: DSv4-Flash Disaggregated DP EP
key: dsv4-flash-disaggregated
timeout_in_minutes: 60
device: h200
optional: true
working_dir: "/vllm-workspace/tests"
num_devices: 8
env:
ENABLE_HMA_FLAG: "1"
DP_EP: "1"
GPU_MEMORY_UTILIZATION: "0.85"
PREFILLER_TP_SIZE: "4"
DECODER_TP_SIZE: "4"
PREFILL_BLOCK_SIZE: "256"
DECODE_BLOCK_SIZE: "256"
MODEL_NAMES: "deepseek-ai/DeepSeek-V4-Flash"
VLLM_SERVE_EXTRA_ARGS: "--trust-remote-code,--kv-cache-dtype,fp8"
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- bash v1/kv_connector/nixl_integration/run_accuracy_test.sh
+19 -35
View File
@@ -4,7 +4,7 @@ depends_on:
steps:
- label: Distributed Comm Ops
key: distributed-comm-ops
timeout_in_minutes: 25
timeout_in_minutes: 20
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
@@ -18,7 +18,7 @@ steps:
- label: Distributed DP Tests (2 GPUs)
key: distributed-dp-tests-2-gpus
timeout_in_minutes: 35
timeout_in_minutes: 20
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
@@ -37,26 +37,10 @@ steps:
- TP_SIZE=1 DP_SIZE=2 pytest -v -s v1/distributed/test_eagle_dp.py
- TP_SIZE=1 DP_SIZE=2 pytest -v -s v1/distributed/test_external_lb_dp.py
- DP_SIZE=2 pytest -v -s entrypoints/openai/test_multi_api_servers.py
mirror:
amd:
dind: false
device: mi300_2
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/distributed/
- vllm/engine/
- vllm/executor/
- vllm/worker/worker_base.py
- vllm/v1/engine/
- vllm/v1/worker/
- tests/v1/distributed
- tests/entrypoints/openai/test_multi_api_servers.py
- vllm/platforms/rocm.py
- label: Distributed Compile + RPC Tests (2 GPUs)
key: distributed-compile-rpc-tests-2-gpus
timeout_in_minutes: 65
timeout_in_minutes: 20
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
@@ -79,7 +63,7 @@ steps:
- label: Distributed Torchrun + Shutdown Tests (2 GPUs)
key: distributed-torchrun-shutdown-tests-2-gpus
timeout_in_minutes: 30
timeout_in_minutes: 20
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
@@ -134,7 +118,7 @@ steps:
- label: Distributed DP Tests (4 GPUs)
key: distributed-dp-tests-4-gpus
timeout_in_minutes: 45
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
@@ -155,7 +139,7 @@ steps:
- label: Distributed Compile + Comm (4 GPUs)
key: distributed-compile-comm-4-gpus
timeout_in_minutes: 70
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
@@ -175,9 +159,9 @@ steps:
# test multi-node TP with multiproc executor (simulated on single node)
- pytest -v -s distributed/test_multiproc_executor.py::test_multiproc_executor_multi_node
- label: Distributed Tests (8xH100)
key: distributed-tests-8xh100
timeout_in_minutes: 20
- label: Distributed Tests (8 GPUs)(H100)
key: distributed-tests-8-gpus-h100
timeout_in_minutes: 10
device: h100
num_devices: 8
working_dir: "/vllm-workspace/tests"
@@ -196,8 +180,8 @@ steps:
# test with torchrun tp=2 and dp=4 with ep
- torchrun --nproc-per-node=8 ../examples/features/torchrun/torchrun_dp_example_offline.py --tp-size=2 --pp-size=1 --dp-size=4 --enable-ep
- label: Distributed Tests (4xA100)
key: distributed-tests-4xa100
- label: Distributed Tests (4 GPUs)(A100)
key: distributed-tests-4-gpus-a100
device: a100
optional: true
num_devices: 4
@@ -211,9 +195,9 @@ steps:
- TARGET_TEST_SUITE=A100 pytest basic_correctness/ -v -s -m 'distributed(num_gpus=2)'
- pytest -v -s -x lora/test_mixtral.py
- label: Distributed Tests (2xH100-2xMI300)
key: distributed-tests-2xh100-2xmi300
timeout_in_minutes: 30
- label: Distributed Tests (2 GPUs)(H100)
key: distributed-tests-2-gpus-h100
timeout_in_minutes: 15
device: h100
optional: true
working_dir: "/vllm-workspace/"
@@ -226,15 +210,15 @@ steps:
- VLLM_ALLOW_INSECURE_SERIALIZATION=1 pytest -v -s tests/distributed/test_weight_transfer.py
- pytest -v -s tests/distributed/test_packed_tensor.py
- label: Distributed Tests (2xB200)
key: distributed-tests-2xb200
- label: Distributed Tests (2 GPUs)(B200)
key: distributed-tests-2-gpus-b200
device: b200-k8s
optional: true
working_dir: "/vllm-workspace/"
num_devices: 2
commands:
- pytest -v -s tests/distributed/test_context_parallel.py
- pytest -v -s tests/distributed/test_nccl_symm_mem.py
- pytest -v -s tests/distributed/test_nccl_symm_mem_allreduce.py
- pytest -v -s tests/v1/distributed/test_dbo.py
- pytest -v -s tests/distributed/test_mnnvl_alltoall.py
@@ -260,7 +244,7 @@ steps:
- label: Pipeline + Context Parallelism (4 GPUs)
key: pipeline-context-parallelism-4-gpus
timeout_in_minutes: 55
timeout_in_minutes: 60
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
@@ -275,7 +259,7 @@ steps:
- label: RayExecutorV2 (4 GPUs)
key: rayexecutorv2-4-gpus
timeout_in_minutes: 45
timeout_in_minutes: 60
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
+1 -1
View File
@@ -3,7 +3,7 @@ depends_on:
- image-build-cpu
steps:
- label: Docker Build Metadata
timeout_in_minutes: 20
timeout_in_minutes: 10
device: cpu-small
source_file_dependencies:
- .buildkite/release-pipeline.yaml
+11 -11
View File
@@ -2,9 +2,9 @@ group: E2E Integration
depends_on:
- image-build
steps:
- label: DeepSeek V2-Lite Sync EPLB Accuracy (4xH100)
key: deepseek-v2-lite-sync-eplb-accuracy-4xh100
timeout_in_minutes: 25
- label: DeepSeek V2-Lite Sync EPLB Accuracy
key: deepseek-v2-lite-sync-eplb-accuracy
timeout_in_minutes: 60
device: h100
optional: true
num_devices: 4
@@ -12,9 +12,9 @@ steps:
commands:
- bash .buildkite/scripts/scheduled_integration_test/deepseek_v2_lite_ep_eplb.sh 0.25 200 8010
- label: Qwen3-30B-A3B-FP8-block Sync EPLB Accuracy (4xH100)
key: qwen3-30b-a3b-fp8-block-sync-eplb-accuracy-4xh100
timeout_in_minutes: 25
- label: Qwen3-30B-A3B-FP8-block Sync EPLB Accuracy
key: qwen3-30b-a3b-fp8-block-sync-eplb-accuracy
timeout_in_minutes: 60
device: h100
optional: true
num_devices: 4
@@ -22,9 +22,9 @@ steps:
commands:
- bash .buildkite/scripts/scheduled_integration_test/qwen30b_a3b_fp8_block_ep_eplb.sh 0.8 200 8020
- label: Qwen3-30B-A3B-FP8-block Sync EPLB Accuracy (2xB200)
key: qwen3-30b-a3b-fp8-block-sync-eplb-accuracy-2xb200
timeout_in_minutes: 20
- label: Qwen3-30B-A3B-FP8-block Sync EPLB Accuracy (B200)
key: qwen3-30b-a3b-fp8-block-sync-eplb-accuracy-b200
timeout_in_minutes: 60
device: b200-k8s
optional: true
num_devices: 2
@@ -34,7 +34,7 @@ steps:
- label: Qwen3-30B-A3B-FP8 DP4 Async EPLB Accuracy
key: qwen3-30b-a3b-fp8-dp4-async-eplb-accuracy
timeout_in_minutes: 25
timeout_in_minutes: 60
device: h100
optional: true
num_devices: 4
@@ -44,7 +44,7 @@ steps:
- label: DeepSeek V2-Lite Prefetch Offload Accuracy (H100)
key: deepseek-v2-lite-prefetch-offload-accuracy-h100
timeout_in_minutes: 20
timeout_in_minutes: 60
device: h100
optional: true
num_devices: 1
+13 -19
View File
@@ -4,7 +4,7 @@ depends_on:
steps:
- label: Engine
key: engine
timeout_in_minutes: 30
timeout_in_minutes: 15
device: h200_18gb
source_file_dependencies:
- vllm/compilation/
@@ -29,13 +29,13 @@ steps:
mirror:
amd:
device: mi325_1
timeout_in_minutes: 50
timeout_in_minutes: 60
depends_on:
- image-build-amd
- label: Engine (1 GPU)
key: engine-1-gpu
timeout_in_minutes: 45
timeout_in_minutes: 30
source_file_dependencies:
- vllm/v1/engine/
- tests/v1/engine/
@@ -45,13 +45,13 @@ steps:
mirror:
amd:
device: mi325_1
timeout_in_minutes: 55
timeout_in_minutes: 40
depends_on:
- image-build-amd
- label: e2e Scheduling (1 GPU)
key: e2e-scheduling-1-gpu
timeout_in_minutes: 35
timeout_in_minutes: 30
device: h200_18gb
source_file_dependencies:
- vllm/v1/
@@ -60,15 +60,15 @@ steps:
- pytest -v -s v1/e2e/general/test_async_scheduling.py
mirror:
amd:
device: mi325_1
timeout_in_minutes: 70
device: mi250_1
timeout_in_minutes: 60
depends_on:
- image-build-amd
- label: e2e Core (1 GPU)
device: h200_35gb
key: e2e-core-1-gpu
timeout_in_minutes: 40
timeout_in_minutes: 30
source_file_dependencies:
- vllm/v1/
- tests/v1/e2e/general/
@@ -76,8 +76,8 @@ steps:
- pytest -v -s v1/e2e/general --ignore v1/e2e/general/test_async_scheduling.py
mirror:
amd:
device: mi325_1
timeout_in_minutes: 60
device: mi250_1
timeout_in_minutes: 35
depends_on:
- image-build-amd
source_file_dependencies:
@@ -87,7 +87,7 @@ steps:
- label: V1 e2e (2 GPUs)
key: v1-e2e-2-gpus
timeout_in_minutes: 25 # TODO: Fix timeout after we have more confidence in the test stability
timeout_in_minutes: 60 # TODO: Fix timeout after we have more confidence in the test stability
optional: true
num_devices: 2
source_file_dependencies:
@@ -112,16 +112,10 @@ steps:
commands:
# Only run tests that need exactly 2 GPUs
- pytest -v -s v1/e2e/spec_decode/test_spec_decode.py -k "tensor_parallelism"
mirror:
amd:
dind: false
device: mi300_2
depends_on:
- image-build-amd
- label: V1 e2e (4 GPUs)
key: v1-e2e-4-gpus
timeout_in_minutes: 20 # TODO: Fix timeout after we have more confidence in the test stability
timeout_in_minutes: 60 # TODO: Fix timeout after we have more confidence in the test stability
optional: true
num_devices: 4
source_file_dependencies:
@@ -149,7 +143,7 @@ steps:
- label: V1 e2e (4xH100)
key: v1-e2e-4xh100
timeout_in_minutes: 35
timeout_in_minutes: 60
device: h100
num_devices: 4
optional: true
+10 -21
View File
@@ -3,9 +3,8 @@ depends_on:
- image-build
steps:
- label: Entrypoints Unit Tests
device: h200_35gb
key: entrypoints-unit-tests
timeout_in_minutes: 25
timeout_in_minutes: 10
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/entrypoints
@@ -16,9 +15,8 @@ steps:
- pytest -v -s entrypoints/weight_transfer
- label: Entrypoints Integration (LLM)
device: h200_35gb
key: entrypoints-integration-llm
timeout_in_minutes: 60
timeout_in_minutes: 40
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
@@ -31,25 +29,21 @@ steps:
mirror:
amd:
device: mi325_1
# TODO(akaratza): Test after Torch >= 2.12 bump
soft_fail: true
depends_on:
- image-build-amd
- label: Entrypoints Integration (API Server)
key: entrypoints-integration-api-server
device: h200_35gb
timeout_in_minutes: 50
timeout_in_minutes: 130
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
- tests/entrypoints/serve
- tests/entrypoints/scale_out
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s entrypoints/serve --ignore=entrypoints/serve/dev/rpc
- PYTHONPATH=/vllm-workspace pytest -v -s entrypoints/serve/dev/rpc
- pytest -v -s entrypoints/scale_out
mirror:
amd:
device: mi325_1
@@ -57,9 +51,8 @@ steps:
- image-build-amd
- label: Entrypoints Integration (API Server OpenAI - Part 1)
device: h200_35gb
key: entrypoints-integration-api-server-openai-part-1
timeout_in_minutes: 45
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
@@ -71,14 +64,13 @@ steps:
mirror:
amd:
device: mi325_1
timeout_in_minutes: 65
timeout_in_minutes: 80
depends_on:
- image-build-amd
- label: Entrypoints Integration (API Server OpenAI - Part 2)
device: h200_35gb
key: entrypoints-integration-api-server-openai-part-2
timeout_in_minutes: 45
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
@@ -96,7 +88,6 @@ steps:
- image-build-amd
- label: Entrypoints Integration (API Server Generate)
device: h200_35gb
key: entrypoints-integration-api-server-generate
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
@@ -114,12 +105,11 @@ steps:
mirror:
amd:
device: mi325_1
timeout_in_minutes: 65
timeout_in_minutes: 60
depends_on:
- image-build-amd
- label: Entrypoints Integration (Responses API)
device: h200_35gb
key: entrypoints-integration-responses-api
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
@@ -132,7 +122,7 @@ steps:
- label: Entrypoints Integration (Speech to Text)
device: h200_35gb
key: entrypoints-integration-speech_to_text
timeout_in_minutes: 45
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
@@ -144,7 +134,7 @@ steps:
- label: Entrypoints Integration (Multimodal)
device: h200_35gb
key: entrypoints-integration-multimodal
timeout_in_minutes: 45
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
@@ -154,7 +144,6 @@ steps:
- pytest -v -s entrypoints/multimodal
- label: Entrypoints Integration (Pooling)
device: h200_35gb
key: entrypoints-integration-pooling
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
@@ -167,7 +156,7 @@ steps:
- label: OpenAI API Correctness
key: openai-api-correctness
timeout_in_minutes: 20
timeout_in_minutes: 30
device: h200_18gb
source_file_dependencies:
- csrc/
+3 -14
View File
@@ -4,7 +4,7 @@ depends_on:
steps:
- label: EPLB Algorithm
key: eplb-algorithm
timeout_in_minutes: 20
timeout_in_minutes: 15
device: h200_18gb
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
@@ -14,21 +14,10 @@ steps:
commands:
- pytest -v -s distributed/test_eplb_algo.py
- pytest -v -s distributed/test_eplb_utils.py
mirror:
amd:
dind: false
device: mi300_1
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/distributed/eplb
- tests/distributed/test_eplb_algo.py
- tests/distributed/test_eplb_utils.py
- vllm/platforms/rocm.py
- label: EPLB Execution # 17min
key: eplb-execution
timeout_in_minutes: 25
timeout_in_minutes: 27
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
@@ -40,7 +29,7 @@ steps:
- label: Elastic EP Scaling Test
key: elastic-ep-scaling-test
timeout_in_minutes: 30
timeout_in_minutes: 20
device: h100
working_dir: "/vllm-workspace/tests"
num_devices: 4
+28 -46
View File
@@ -4,7 +4,7 @@ depends_on:
steps:
- label: vLLM IR Tests
key: vllm-ir-tests
timeout_in_minutes: 35
timeout_in_minutes: 10
device: h200_18gb
working_dir: "/vllm-workspace/"
source_file_dependencies:
@@ -15,21 +15,19 @@ steps:
- pytest -v -s tests/kernels/ir
- label: Kernels Core Operation Test
device: h200_35gb
key: kernels-core-operation-test
timeout_in_minutes: 120
timeout_in_minutes: 75
source_file_dependencies:
- csrc/
- tests/kernels/core
- tests/kernels/test_concat_mla_q.py
- tests/kernels/test_fused_qk_norm_rope_gate.py
commands:
- pytest -v -s kernels/core --ignore=kernels/core/test_minimax_reduce_rms.py kernels/test_concat_mla_q.py kernels/test_fused_qk_norm_rope_gate.py --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
parallelism: 3
- pytest -v -s kernels/core --ignore=kernels/core/test_minimax_reduce_rms.py kernels/test_concat_mla_q.py kernels/test_fused_qk_norm_rope_gate.py
- label: Kernels MiniMax Reduce RMS Test (2 GPUs)
key: kernels-minimax-reduce-rms-test-2-gpus
timeout_in_minutes: 20
timeout_in_minutes: 15
num_devices: 2
device: h100
source_file_dependencies:
@@ -43,20 +41,18 @@ steps:
- label: Deepseek V4 Kernel Test (H100)
key: deepseek-v4-kernel-test-h100
timeout_in_minutes: 30
timeout_in_minutes: 15
device: h100
source_file_dependencies:
- csrc/fused_deepseek_v4_qnorm_rope_kv_insert_kernel.cu
- vllm/models/deepseek_v4/common/ops/
- tests/kernels/test_fused_deepseek_v4_qnorm_rope_kv_insert.py
- tests/kernels/test_top_k_per_row.py # it runs on Blackwell too - some kernels have arch-specific optimizations
commands:
- pytest -v -s kernels/test_fused_deepseek_v4_*.py
- pytest -v -s kernels/test_top_k_per_row.py
- label: Deepseek V4 Kernel Test (B200)
key: deepseek-v4-kernel-test-b200
timeout_in_minutes: 20
timeout_in_minutes: 15
device: b200-k8s
source_file_dependencies:
- csrc/fused_deepseek_v4_qnorm_rope_kv_insert_kernel.cu
@@ -67,7 +63,7 @@ steps:
- label: Kernels Attention Test %N
key: kernels-attention-test
timeout_in_minutes: 65
timeout_in_minutes: 35
source_file_dependencies:
- csrc/attention/
- vllm/v1/attention
@@ -81,7 +77,7 @@ steps:
mirror:
amd:
device: mi325_1
timeout_in_minutes: 90
timeout_in_minutes: 55
depends_on:
- image-build-amd
source_file_dependencies:
@@ -108,7 +104,7 @@ steps:
- label: Kernels Quantization Test %N
key: kernels-quantization-test
timeout_in_minutes: 60
timeout_in_minutes: 90
source_file_dependencies:
- csrc/quantization/
- vllm/model_executor/layers/quantization
@@ -133,7 +129,7 @@ steps:
- label: Kernels MoE Test %N
key: kernels-moe-test
timeout_in_minutes: 50
timeout_in_minutes: 25
source_file_dependencies:
- csrc/quantization/cutlass_w8a8/moe/
- csrc/moe/
@@ -149,7 +145,7 @@ steps:
mirror:
amd:
device: mi325_1
timeout_in_minutes: 65
timeout_in_minutes: 50
source_file_dependencies:
- csrc/quantization/cutlass_w8a8/moe/
- csrc/moe/
@@ -164,9 +160,8 @@ steps:
- image-build-amd
- label: Kernels Mamba Test
device: h200_35gb
key: kernels-mamba-test
timeout_in_minutes: 40
timeout_in_minutes: 45
source_file_dependencies:
- csrc/mamba/
- tests/kernels/mamba
@@ -175,19 +170,19 @@ steps:
- pytest -v -s kernels/mamba
- label: Kernels KDA Test
timeout_in_minutes: 25
timeout_in_minutes: 20
device: h200_18gb
source_file_dependencies:
- vllm/third_party/flash_linear_attention/ops/kda.py
- vllm/third_party/flash_linear_attention/ops/chunk_delta_h.py
- vllm/third_party/flash_linear_attention/ops/l2norm.py
- vllm/model_executor/layers/fla/ops/kda.py
- vllm/model_executor/layers/fla/ops/chunk_delta_h.py
- vllm/model_executor/layers/fla/ops/l2norm.py
- tests/kernels/test_kda.py
commands:
- pytest -v -s kernels/test_kda.py
- label: Kernels DeepGEMM Test (H100)
key: kernels-deepgemm-test-h100
timeout_in_minutes: 35
timeout_in_minutes: 45
device: h100
num_devices: 1
source_file_dependencies:
@@ -214,7 +209,7 @@ steps:
- label: Kernels (B200)
key: kernels-b200
timeout_in_minutes: 80
timeout_in_minutes: 30
working_dir: "/vllm-workspace/"
device: b200-k8s
# optional: true
@@ -234,15 +229,6 @@ steps:
- vllm/v1/attention/backends/mla/flashinfer_mla.py
- vllm/v1/attention/selector.py
- vllm/platforms/cuda.py
- vllm/model_executor/kernels/linear/cute_dsl/ll_bf16.py
- vllm/model_executor/kernels/linear/cute_dsl/_ll_bf16_dotprod.py
- vllm/model_executor/kernels/linear/cute_dsl/_ll_bf16_splitk.py
- vllm/cute_utils/
- vllm/model_executor/layers/mamba/ops/gdn_chunk_cutedsl/
- vllm/model_executor/layers/fused_moe/router/bf16x3_router_gemm_cutedsl.py
- tests/kernels/mamba/test_gdn_prefill_cutedsl.py
- tests/kernels/test_bf16x3_router_gemm_cutedsl.py
- tests/kernels/test_ll_bf16_gemm.py
- tests/kernels/test_top_k_per_row.py
commands:
- nvidia-smi
@@ -271,28 +257,24 @@ steps:
- pytest -v -s tests/kernels/moe/test_flashinfer_moe.py
- pytest -v -s tests/kernels/moe/test_trtllm_nvfp4_moe.py
- pytest -v -s tests/kernels/moe/test_cutedsl_moe.py
- pytest -v -s tests/kernels/mamba/test_gdn_prefill_cutedsl.py
- pytest -v -s tests/kernels/test_bf16x3_router_gemm_cutedsl.py
- pytest -v -s tests/kernels/test_ll_bf16_gemm.py
# e2e
- pytest -v -s tests/models/quantization/test_nvfp4.py
- label: Kernels Helion Test
key: kernels-helion-test
timeout_in_minutes: 115
timeout_in_minutes: 30
device: h100
source_file_dependencies:
- vllm/utils/import_utils.py
- tests/kernels/helion/
commands:
- pip install helion==1.1.0
- pytest -v -s kernels/helion/ --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
parallelism: 2
- pytest -v -s kernels/helion/
- label: Kernels FP8 MoE Test (1xH100)
key: kernels-fp8-moe-test-1xh100
timeout_in_minutes: 40
- label: Kernels FP8 MoE Test (1 H100)
key: kernels-fp8-moe-test-1-h100
timeout_in_minutes: 90
device: h100
num_devices: 1
optional: true
@@ -307,9 +289,9 @@ steps:
- pytest -v -s kernels/moe/test_triton_moe_no_act_mul.py
- pytest -v -s kernels/moe/test_triton_moe_ptpc_fp8.py
- label: Kernels FP8 MoE Test (2xH100)
key: kernels-fp8-moe-test-2xh100
timeout_in_minutes: 45
- label: Kernels FP8 MoE Test (2 H100s)
key: kernels-fp8-moe-test-2-h100s
timeout_in_minutes: 90
device: h100
num_devices: 2
optional: true
@@ -319,7 +301,7 @@ steps:
- label: Kernels Fp4 MoE Test (B200)
key: kernels-fp4-moe-test-b200
timeout_in_minutes: 25
timeout_in_minutes: 60
device: b200-k8s
num_devices: 1
optional: true
@@ -332,7 +314,7 @@ steps:
- label: Kernels FusedMoE Layer Test (2 H100s)
key: kernels-fusedmoe-layer-test-2-h100s
timeout_in_minutes: 30
timeout_in_minutes: 90
device: h100
num_devices: 2
source_file_dependencies:
+25 -210
View File
@@ -5,7 +5,7 @@ steps:
- label: LM Eval Small Models
device: h200_35gb
key: lm-eval-small-models
timeout_in_minutes: 45
timeout_in_minutes: 75
source_file_dependencies:
- csrc/
- vllm/model_executor/layers/quantization
@@ -28,8 +28,7 @@ steps:
- vllm/_aiter_ops.py
- vllm/platforms/rocm.py
# - label: LM Eval Large Models (4xA100)
# key: lm-eval-large-models-4xa100
# - label: LM Eval Large Models (4 GPUs)(A100)
# device: a100
# optional: true
# num_devices: 4
@@ -41,8 +40,8 @@ steps:
# - export VLLM_WORKER_MULTIPROC_METHOD=spawn
# - pytest -s -v test_lm_eval_correctness.py --config-list-file=configs/models-large.txt --tp-size=4
- label: LM Eval Large Models (4xH100)
key: lm-eval-large-models-4xh100
- label: LM Eval Large Models (4 GPUs)(H100)
key: lm-eval-large-models-4-gpus-h100
device: h100
optional: true
num_devices: 4
@@ -54,9 +53,9 @@ steps:
- export VLLM_USE_DEEP_GEMM=0 # We found Triton is faster than DeepGEMM for H100
- pytest -s -v test_lm_eval_correctness.py --config-list-file=configs/models-large-hopper.txt --tp-size=4
- label: LM Eval Small Models (1xB200)
key: lm-eval-small-models-1xb200
timeout_in_minutes: 50
- label: LM Eval Small Models (B200)
key: lm-eval-small-models-b200
timeout_in_minutes: 120
device: b200-k8s
optional: true
source_file_dependencies:
@@ -65,45 +64,10 @@ steps:
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-blackwell.txt
- label: LM Eval Small Models Distributed (2xB200)
key: lm-eval-small-models-distributed-2xb200
- label: LM Eval Large Models (B200, EP)
key: lm-eval-large-models-b200-ep
timeout_in_minutes: 120
device: b200-k8s
num_devices: 2
optional: true
source_file_dependencies:
- csrc/
- vllm/model_executor/layers/quantization
autorun_on_main: true
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-small-tp.txt
- label: LM Eval PCP (4xB200)
key: lm-eval-pcp-4xb200
timeout_in_minutes: 360
device: b200-k8s
num_devices: 4
optional: true
source_file_dependencies:
- csrc/
- tests/evals/gsm8k/configs/GLM-5.2-NVFP4-TP2-PCP2-EP.yaml
- tests/evals/gsm8k/configs/GLM-5.2-NVFP4-TP1-PCP4-EP.yaml
- tests/evals/gsm8k/configs/models-pcp.txt
- vllm/model_executor/layers/quantization
- vllm/config/parallel.py
- vllm/distributed/parallel_state.py
- vllm/model_executor/layers/attention/mla_attention.py
- vllm/model_executor/layers/attention/pcp.py
- vllm/v1/worker/gpu/model_runner.py
- vllm/v1/worker/gpu/pcp_manager.py
autorun_on_main: true
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-pcp.txt
- label: LM Eval Large Models EP (2xB200)
key: lm-eval-large-models-ep-2xb200
timeout_in_minutes: 60
device: b200-k8s
optional: true
num_devices: 2
source_file_dependencies:
@@ -112,9 +76,9 @@ steps:
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-blackwell-ep.txt
- label: LM Eval Qwen3.5 Models (2xB200)
key: lm-eval-qwen3-5-models-2xb200
timeout_in_minutes: 45
- label: LM Eval Qwen3.5 Models (B200)
key: lm-eval-qwen3-5-models-b200
timeout_in_minutes: 120
device: b200-k8s
optional: true
num_devices: 2
@@ -125,13 +89,13 @@ steps:
- vllm/transformers_utils/configs/qwen3_5_moe.py
- vllm/model_executor/models/qwen3_next.py
- vllm/model_executor/models/qwen3_next_mtp.py
- vllm/third_party/flash_linear_attention/ops/
- vllm/model_executor/layers/fla/ops/
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-qwen35-blackwell.txt
- label: LM Eval Large Models (8xH200)
key: lm-eval-large-models-8xh200
timeout_in_minutes: 50
- label: LM Eval Large Models (H200)
key: lm-eval-large-models-h200
timeout_in_minutes: 60
device: h200
optional: true
num_devices: 8
@@ -139,9 +103,8 @@ steps:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-h200.txt
mirror:
amd:
dind: false
device: mi300_8
timeout_in_minutes: 60
timeout_in_minutes: 180
depends_on:
- image-build-amd
commands:
@@ -173,101 +136,10 @@ steps:
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/moe-refactor-dp-ep/config-b200.txt
- label: LM Eval Humming f16 (A100 - TEMPORARY)
key: lm-eval-humming-f16-a100
timeout_in_minutes: 75
device: a100
optional: true
num_devices: 1
source_file_dependencies:
- vllm/model_executor/layers/quantization/humming.py
- vllm/model_executor/layers/quantization/utils/humming_utils.py
- vllm/model_executor/layers/fused_moe/experts/fused_humming_moe.py
- vllm/model_executor/layers/fused_moe/oracle/
- vllm/model_executor/kernels/linear/
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config.txt
- label: LM Eval Humming Act int8 (A100 - TEMPORARY)
key: lm-eval-humming-act-a100
timeout_in_minutes: 45
device: a100
optional: true
num_devices: 1
source_file_dependencies:
- vllm/model_executor/layers/quantization/humming.py
- vllm/model_executor/layers/quantization/utils/humming_utils.py
- vllm/model_executor/layers/fused_moe/experts/fused_humming_moe.py
- vllm/model_executor/layers/fused_moe/oracle/
- vllm/model_executor/kernels/linear/
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config-act-int8.txt
- label: LM Eval Humming f16 (H100 - TEMPORARY)
key: lm-eval-humming-f16-h100
timeout_in_minutes: 70
device: h100
optional: true
num_devices: 1
source_file_dependencies:
- vllm/model_executor/layers/quantization/humming.py
- vllm/model_executor/layers/quantization/utils/humming_utils.py
- vllm/model_executor/layers/fused_moe/experts/fused_humming_moe.py
- vllm/model_executor/layers/fused_moe/oracle/
- vllm/model_executor/kernels/linear/
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config.txt
- label: LM Eval Humming Act fp8/int8 (H100 - TEMPORARY)
key: lm-eval-humming-act-h100
timeout_in_minutes: 70
device: h100
optional: true
num_devices: 1
source_file_dependencies:
- vllm/model_executor/layers/quantization/humming.py
- vllm/model_executor/layers/quantization/utils/humming_utils.py
- vllm/model_executor/layers/fused_moe/experts/fused_humming_moe.py
- vllm/model_executor/layers/fused_moe/oracle/
- vllm/model_executor/kernels/linear/
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config-act-fp8.txt
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config-act-int8.txt
- label: LM Eval Humming f16 (B200 - TEMPORARY)
key: lm-eval-humming-f16-b200
timeout_in_minutes: 50
device: b200-k8s
optional: true
num_devices: 1
source_file_dependencies:
- vllm/model_executor/layers/quantization/humming.py
- vllm/model_executor/layers/quantization/utils/humming_utils.py
- vllm/model_executor/layers/fused_moe/experts/fused_humming_moe.py
- vllm/model_executor/layers/fused_moe/oracle/
- vllm/model_executor/kernels/linear/
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config.txt
- label: LM Eval Humming Act fp8/int8 (B200 - TEMPORARY)
key: lm-eval-humming-act-b200
timeout_in_minutes: 50
device: b200-k8s
optional: true
num_devices: 1
source_file_dependencies:
- vllm/model_executor/layers/quantization/humming.py
- vllm/model_executor/layers/quantization/utils/humming_utils.py
- vllm/model_executor/layers/fused_moe/experts/fused_humming_moe.py
- vllm/model_executor/layers/fused_moe/oracle/
- vllm/model_executor/kernels/linear/
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config-act-fp8.txt
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config-act-int8.txt
- label: LM Eval TurboQuant KV Cache
key: lm-eval-turboquant-kv-cache
timeout_in_minutes: 55
timeout_in_minutes: 75
device: h200_18gb
source_file_dependencies:
- vllm/model_executor/layers/quantization/turboquant/
@@ -277,9 +149,9 @@ steps:
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/models-turboquant.txt
- label: GPQA Eval (GPT-OSS) (2xH100)
key: gpqa-eval-gpt-oss-2xh100
timeout_in_minutes: 35
- label: GPQA Eval (GPT-OSS) (H100)
key: gpqa-eval-gpt-oss-h100
timeout_in_minutes: 120
device: h100
optional: true
num_devices: 2
@@ -291,9 +163,9 @@ steps:
- uv pip install --system 'gpt-oss[eval]==0.0.5'
- pytest -s -v evals/gpt_oss/test_gpqa_correctness.py --config-list-file=configs/models-h100.txt
- label: GPQA Eval (GPT-OSS) (2xB200)
key: gpqa-eval-gpt-oss-2xb200
timeout_in_minutes: 30
- label: GPQA Eval (GPT-OSS) (B200)
key: gpqa-eval-gpt-oss-b200
timeout_in_minutes: 120
device: b200-k8s
optional: true
num_devices: 2
@@ -305,66 +177,9 @@ steps:
- uv pip install --system 'gpt-oss[eval]==0.0.5'
- pytest -s -v evals/gpt_oss/test_gpqa_correctness.py --config-list-file=configs/models-b200.txt
- label: GPQA Eval (GPT-OSS) (DGX Spark)
key: gpqa-eval-gpt-oss-spark
timeout_in_minutes: 35
device: dgx-spark
optional: true
num_devices: 1
depends_on:
- arm64-image-build
source_file_dependencies:
- csrc/
- vllm/model_executor/layers/quantization
- tests/evals/gpt_oss/
commands:
- uv pip install --system 'gpt-oss[eval]==0.0.5'
- pytest -s -v evals/gpt_oss/test_gpqa_correctness.py --config-list-file=configs/models-spark.txt
- label: LM Eval KV-Offload (1xH200)
key: kv-offload-small
timeout_in_minutes: 30
device: h200_35gb
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/offloading/
- vllm/distributed/kv_transfer/kv_connector/v1/simple_cpu_offload_connector.py
- vllm/v1/kv_offload/
- vllm/v1/simple_kv_offload/
- tests/evals/gsm8k/test_gsm8k_offloading.py
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_offloading.py -k "nemotron-h-8b or gemma-4-e4b-it"
- label: LM Eval KV-Offload (2xH100)
key: kv-offload-medium
timeout_in_minutes: 30
device: h100
num_devices: 2
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/offloading/
- vllm/distributed/kv_transfer/kv_connector/v1/simple_cpu_offload_connector.py
- vllm/v1/kv_offload/
- vllm/v1/simple_kv_offload/
- tests/evals/gsm8k/test_gsm8k_offloading.py
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_offloading.py -k "qwen3.5-35b"
- label: LM Eval KV-Offload (4xH100)
key: kv-offload-large
timeout_in_minutes: 40
device: h100
num_devices: 4
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/offloading/
- vllm/distributed/kv_transfer/kv_connector/v1/simple_cpu_offload_connector.py
- vllm/v1/kv_offload/
- vllm/v1/simple_kv_offload/
- tests/evals/gsm8k/test_gsm8k_offloading.py
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_offloading.py -k "deepseek-v4-flash"
- label: MRCR Eval Small Models
device: h200_35gb
timeout_in_minutes: 25
timeout_in_minutes: 30
source_file_dependencies:
- tests/evals/mrcr/
commands:
+3 -3
View File
@@ -5,7 +5,7 @@ steps:
- label: LoRA %N
device: h200_35gb
key: lora
timeout_in_minutes: 40
timeout_in_minutes: 30
source_file_dependencies:
- vllm/lora
- tests/lora
@@ -16,7 +16,7 @@ steps:
amd:
device: mi325_1
working_dir: "/vllm-workspace/tests"
timeout_in_minutes: 65
timeout_in_minutes: 60
source_file_dependencies:
- vllm/lora
- tests/lora
@@ -27,7 +27,7 @@ steps:
- label: LoRA TP (Distributed)
key: lora-tp-distributed
timeout_in_minutes: 60
timeout_in_minutes: 30
num_devices: 4
source_file_dependencies:
- vllm/lora
+17 -49
View File
@@ -5,7 +5,7 @@ steps:
- label: V1 Spec Decode
device: h200_35gb
key: v1-spec-decode
timeout_in_minutes: 40
timeout_in_minutes: 30
source_file_dependencies:
- vllm/config/
- vllm/distributed/
@@ -23,15 +23,14 @@ steps:
- pytest -v -s -m 'not slow_test' v1/spec_decode
mirror:
amd:
dind: false
device: mi300_1
timeout_in_minutes: 75
timeout_in_minutes: 65
depends_on:
- image-build-amd
- label: V1 Sample + Logits
key: v1-sample-logits
timeout_in_minutes: 45
timeout_in_minutes: 30
device: h200_18gb
source_file_dependencies:
- vllm/config/
@@ -64,9 +63,8 @@ steps:
- image-build-amd
- label: V1 Core + KV + Metrics
device: h200_35gb
key: v1-core-kv-metrics
timeout_in_minutes: 80
timeout_in_minutes: 30
source_file_dependencies:
- vllm/config/
- vllm/distributed/
@@ -91,7 +89,6 @@ steps:
- tests/v1/simple_kv_offload
- tests/v1/worker
- tests/v1/kv_connector/unit
- tests/v1/ec_connector/unit
- tests/v1/metrics
- tests/entrypoints/openai/correctness/test_lmeval.py
commands:
@@ -104,15 +101,14 @@ steps:
- pytest -v -s v1/simple_kv_offload
- pytest -v -s v1/worker
- pytest -v -s -m 'not cpu_test' v1/kv_connector/unit
- pytest -v -s -m 'not cpu_test' v1/ec_connector/unit
- pytest -v -s -m 'not cpu_test' v1/metrics
# Integration test for streaming correctness (requires special branch).
- pip install -U git+https://github.com/vllm-project/lm-evaluation-harness.git@streaming-api
- pip install -U git+https://github.com/robertgshaw2-redhat/lm-evaluation-harness.git@streaming-api
- pytest -v -s entrypoints/openai/correctness/test_lmeval.py::test_lm_eval_accuracy_v1_engine
mirror:
amd:
device: mi325_1
timeout_in_minutes: 75
timeout_in_minutes: 60
depends_on:
- image-build-amd
@@ -176,7 +172,7 @@ steps:
- label: Regression
key: regression
timeout_in_minutes: 30
timeout_in_minutes: 20
device: h200_18gb
source_file_dependencies:
- vllm/config/
@@ -192,14 +188,14 @@ steps:
- vllm/v1/
- tests/test_regression
commands:
- pip install 'modelscope<1.38'
- pip install modelscope
- pytest -v -s test_regression.py
working_dir: "/vllm-workspace/tests" # optional
- label: Examples
device: h200_35gb
key: examples
timeout_in_minutes: 40
timeout_in_minutes: 45
working_dir: "/vllm-workspace/examples"
source_file_dependencies:
- vllm/entrypoints
@@ -228,20 +224,10 @@ steps:
- python3 features/speculative_decoding/spec_decode_offline.py --test --method eagle --num_spec_tokens 3 --dataset-name hf --dataset-path philschmid/mt-bench --num-prompts 80 --temp 0 --top-p 1.0 --top-k -1 --tp 1 --enable-chunked-prefill --max-model-len 2048
# https://github.com/vllm-project/vllm/pull/26682 uses slightly more memory in PyTorch 2.9+ causing this test to OOM in 1xL4 GPU
- python3 features/speculative_decoding/spec_decode_offline.py --test --method eagle3 --num_spec_tokens 3 --dataset-name hf --dataset-path philschmid/mt-bench --num-prompts 80 --temp 0 --top-p 1.0 --top-k -1 --tp 1 --enable-chunked-prefill --max-model-len 1536
mirror:
amd:
device: mi325_1
source_file_dependencies:
- vllm/entrypoints
- vllm/multimodal
- examples/
- vllm/platforms/rocm.py
depends_on:
- image-build-amd
- label: Metrics, Tracing (2 GPUs)
key: metrics-tracing-2-gpus
timeout_in_minutes: 25
timeout_in_minutes: 20
num_devices: 2
source_file_dependencies:
- vllm/config/
@@ -264,12 +250,6 @@ steps:
'opentelemetry-exporter-otlp>=1.26.0' \
'opentelemetry-semantic-conventions-ai>=0.4.1'"
- pytest -v -s v1/tracing
mirror:
amd:
device: mi325_2
depends_on:
- image-build-amd
optional: true
- label: Python-only Installation
key: python-only-installation
@@ -282,21 +262,11 @@ steps:
- setup.py
commands:
- bash standalone_tests/python_only_compile.sh
mirror:
amd:
device: mi325_1
timeout_in_minutes: 45
depends_on:
- image-build-amd
source_file_dependencies:
- tests/standalone_tests/python_only_compile.sh
- setup.py
- vllm/platforms/rocm.py
- label: Async Engine, Inputs, Utils, Worker
device: h200_35gb
key: async-engine-inputs-utils-worker
timeout_in_minutes: 25
timeout_in_minutes: 50
source_file_dependencies:
- vllm/assets/
- vllm/config/
@@ -323,7 +293,7 @@ steps:
key: async-engine-inputs-utils-worker-config-cpu
depends_on:
- image-build-cpu
timeout_in_minutes: 65
timeout_in_minutes: 30
source_file_dependencies:
- vllm/assets/
- vllm/config/
@@ -355,7 +325,6 @@ steps:
- tests/test_outputs.py
- tests/test_pooling_params.py
- tests/test_ray_env.py
- tests/test_sampling_params.py
- tests/multimodal
- tests/renderers
- tests/standalone_tests/lazy_imports.py
@@ -373,10 +342,9 @@ steps:
- pytest -v -s test_outputs.py
- pytest -v -s test_pooling_params.py
- pytest -v -s test_ray_env.py
- pytest -v -s test_sampling_params.py
- pytest -v -s -m 'cpu_test' multimodal
- pytest -v -s renderers
- pytest -v -s reasoning
- pytest -v -s reasoning --ignore=reasoning/test_seedoss_reasoning_parser.py --ignore=reasoning/test_glm4_moe_reasoning_parser.py
- pytest -v -s tool_parsers
- pytest -v -s tokenizers_
- pytest -v -s parser
@@ -385,7 +353,7 @@ steps:
- label: Batch Invariance (A100)
key: batch-invariance-a100
timeout_in_minutes: 40
timeout_in_minutes: 30
device: a100
source_file_dependencies:
- vllm/v1/attention
@@ -399,7 +367,7 @@ steps:
- label: Batch Invariance (H100)
key: batch-invariance-h100
timeout_in_minutes: 40
timeout_in_minutes: 30
device: h100
source_file_dependencies:
- vllm/v1/attention
@@ -415,7 +383,7 @@ steps:
- label: Batch Invariance (B200)
key: batch-invariance-b200
timeout_in_minutes: 35
timeout_in_minutes: 30
device: b200-k8s
source_file_dependencies:
- vllm/v1/attention
@@ -434,7 +402,7 @@ steps:
- label: Acceptance Length Test (Large Models) # optional
device: h200_35gb
key: acceptance-length-test-large-models
timeout_in_minutes: 20
timeout_in_minutes: 25
gpu: h100
optional: true
num_gpus: 1
+1 -20
View File
@@ -3,16 +3,13 @@ depends_on:
- image-build
steps:
- label: Model Executor
device: h200_35gb
key: model-executor
timeout_in_minutes: 45
timeout_in_minutes: 35
source_file_dependencies:
- vllm/engine/arg_utils.py
- vllm/config/model.py
- vllm/model_executor
- vllm/model_executor/warmup
- tests/model_executor
- tests/model_executor/test_jit_warmup.py
- tests/entrypoints/openai/completion/test_tensorizer_entrypoint.py
commands:
- apt-get update && apt-get install -y curl libsodium23
@@ -26,19 +23,3 @@ steps:
# calls that the signal method cannot interrupt.
- pytest -v -s model_executor -m '(not slow_test)' --timeout=900 --timeout-method=thread
- pytest -v -s entrypoints/openai/completion/test_tensorizer_entrypoint.py --timeout=900 --timeout-method=thread
mirror:
amd:
dind: false
device: mi300_1
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/engine/arg_utils.py
- vllm/config/model.py
- vllm/model_executor
- vllm/model_executor/warmup
- tests/model_executor
- tests/model_executor/test_jit_warmup.py
- tests/entrypoints/openai/completion/test_tensorizer_entrypoint.py
- vllm/_aiter_ops.py
- vllm/platforms/rocm.py
+7 -5
View File
@@ -5,7 +5,7 @@ steps:
- label: Model Runner V2 Core Tests
device: h200_35gb
key: model-runner-v2-core-tests
timeout_in_minutes: 35
timeout_in_minutes: 45
source_file_dependencies:
- vllm/v1/worker/gpu/
- vllm/v1/worker/gpu_worker.py
@@ -18,7 +18,9 @@ steps:
- set -x
- export VLLM_USE_V2_MODEL_RUNNER=1
- pytest -v -s v1/engine/test_llm_engine.py -k "not test_engine_metrics"
- pytest -v -s v1/e2e/general/test_async_scheduling.py -k "not ngram"
# This requires eager until we sort out CG correctness issues.
# TODO: remove ENFORCE_EAGER here after https://github.com/vllm-project/vllm/pull/32936 is merged.
- ENFORCE_EAGER=1 pytest -v -s v1/e2e/general/test_async_scheduling.py -k "not ngram"
- pytest -v -s v1/e2e/general/test_context_length.py
- pytest -v -s v1/e2e/general/test_min_tokens.py
# Temporary hack filter to exclude ngram spec decoding based tests.
@@ -27,7 +29,7 @@ steps:
- label: Model Runner V2 Examples
device: h200_35gb
key: model-runner-v2-examples
timeout_in_minutes: 35
timeout_in_minutes: 45
working_dir: "/vllm-workspace/examples"
source_file_dependencies:
- vllm/v1/worker/gpu/
@@ -63,7 +65,7 @@ steps:
- label: Model Runner V2 Distributed (2 GPUs)
key: model-runner-v2-distributed-2-gpus
timeout_in_minutes: 30
timeout_in_minutes: 45
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
@@ -84,7 +86,7 @@ steps:
- label: Model Runner V2 Pipeline Parallelism (4 GPUs)
key: model-runner-v2-pipeline-parallelism-4-gpus
timeout_in_minutes: 50
timeout_in_minutes: 60
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
+13 -14
View File
@@ -4,8 +4,9 @@ depends_on:
steps:
- label: Basic Models Tests (Initialization)
key: basic-models-tests-initialization
timeout_in_minutes: 25
timeout_in_minutes: 45
device: h200_18gb
torch_nightly: true
source_file_dependencies:
- vllm/
- tests/models/test_initialization.py
@@ -13,11 +14,13 @@ steps:
commands:
# Run a subset of model initialization tests
- pytest -v -s models/test_initialization.py::test_can_initialize_small_subset
mirror:
torch_nightly: {}
- label: Basic Models Tests (Extra Initialization) %N
device: h200_35gb
key: basic-models-tests-extra-initialization
timeout_in_minutes: 100
timeout_in_minutes: 45
source_file_dependencies:
- vllm/model_executor/models/
- tests/models/test_initialization.py
@@ -27,35 +30,31 @@ steps:
# subset of supported models (the complement of the small subset in the above
# test.) Also run if model initialization test file is modified
- pytest -v -s models/test_initialization.py -k 'not test_can_initialize_small_subset' --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB
parallelism: 4
parallelism: 2
mirror:
torch_nightly: {}
- label: Basic Models Tests (Other)
device: h200_35gb
key: basic-models-tests-other
timeout_in_minutes: 35
timeout_in_minutes: 45
source_file_dependencies:
- vllm/
- tests/models/test_terratorch.py
- tests/models/transformers/test_backend.py
- tests/models/test_transformers.py
- tests/models/test_registry.py
commands:
- pytest -v -s models/test_terratorch.py models/transformers/test_backend.py models/test_registry.py
mirror:
amd:
device: mi325_1
depends_on:
- image-build-amd
- pytest -v -s models/test_terratorch.py models/test_transformers.py models/test_registry.py
- label: Basic Models Test (Other CPU) # 5min
key: basic-models-test-other-cpu
depends_on:
- image-build-cpu
timeout_in_minutes: 20
timeout_in_minutes: 10
source_file_dependencies:
- vllm/
- tests/models/test_utils.py
- tests/models/test_vision.py
- tests/models/transformers/fusers/
device: cpu-small
commands:
- pytest -v -s models/test_utils.py models/test_vision.py models/transformers/fusers/
- pytest -v -s models/test_utils.py models/test_vision.py
@@ -4,7 +4,7 @@ depends_on:
steps:
- label: Distributed Model Tests (2 GPUs)
key: distributed-model-tests-2-gpus
timeout_in_minutes: 60
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
@@ -17,7 +17,7 @@ steps:
- TARGET_TEST_SUITE=L4 pytest basic_correctness/ -v -s -m 'distributed(num_gpus=2)'
- CUDA_VISIBLE_DEVICES=0,1 pytest -v -s model_executor/model_loader/test_sharded_state_loader.py -m '(not slow_test)'
# Avoid importing model tests that cause CUDA reinitialization error
- pytest models/transformers/test_backend.py -v -s -m 'distributed(num_gpus=2)'
- pytest models/test_transformers.py -v -s -m 'distributed(num_gpus=2)'
- pytest models/language -v -s -m 'distributed(num_gpus=2)'
- pytest models/multimodal/generation/test_phi4siglip.py -v -s -m 'distributed(num_gpus=2)'
- pytest models/multimodal -v -s -m 'distributed(num_gpus=2)' --ignore models/multimodal/generation/test_whisper.py --ignore models/multimodal/generation/test_phi4siglip.py
+16 -49
View File
@@ -4,7 +4,7 @@ depends_on:
steps:
- label: Language Models Tests (Standard)
key: language-models-tests-standard
timeout_in_minutes: 30
timeout_in_minutes: 25
device: h200_18gb
source_file_dependencies:
- vllm/
@@ -14,16 +14,11 @@ steps:
- pip freeze | grep -E 'torch'
- pytest -v -s models/language -m 'core_model and (not slow_test)'
mirror:
amd:
dind: false
device: mi300_1
depends_on:
- image-build-amd
torch_nightly: {}
- label: Language Models Tests (Extra Standard) %N
device: h200_35gb
key: language-models-tests-extra-standard
timeout_in_minutes: 40
timeout_in_minutes: 45
source_file_dependencies:
- vllm/model_executor/models/
- tests/models/language/pooling/test_embedding.py
@@ -36,26 +31,11 @@ steps:
- pytest -v -s models/language -m 'core_model and slow_test' --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB
parallelism: 2
mirror:
amd:
dind: false
device: mi300_1
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/model_executor/models/
- vllm/model_executor/model_loader/
- vllm/model_executor/layers/
- vllm/v1/attention/backends/
- vllm/v1/attention/selector.py
- tests/models/language/pooling/test_embedding.py
- tests/models/language/generation/test_common.py
- tests/models/language/pooling/test_classification.py
- vllm/_aiter_ops.py
- vllm/platforms/rocm.py
torch_nightly: {}
- label: Language Models Tests (Hybrid) %N
device: h200_35gb
key: language-models-tests-hybrid
timeout_in_minutes: 65
timeout_in_minutes: 75
source_file_dependencies:
- vllm/
- tests/models/language/generation
@@ -64,13 +44,14 @@ steps:
# Note: also needed to run plamo2 model in vLLM
- uv pip install --system --no-build-isolation 'git+https://github.com/state-spaces/mamba@v2.3.0'
- uv pip install --system --no-build-isolation 'git+https://github.com/Dao-AILab/causal-conv1d@v1.6.0'
# Shard the hybrid language model tests that are numerically stable on Hopper.
- pytest -v -s models/language/generation -m hybrid_model -k 'not granite-4.0-tiny-preview' --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB
# Shard hybrid language model tests
- pytest -v -s models/language/generation -m hybrid_model --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB
parallelism: 2
mirror:
torch_nightly: {}
amd:
device: mi325_1
timeout_in_minutes: 70
timeout_in_minutes: 90
depends_on:
- image-build-amd
commands:
@@ -78,24 +59,10 @@ steps:
- uv pip install --system --no-build-isolation 'git+https://github.com/Dao-AILab/causal-conv1d@v1.6.0'
- pytest -v -s models/language/generation -m hybrid_model --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB
# Granite 4 hybrid generation is sensitive to hardware-specific Triton SSD
# autotuning (https://github.com/vllm-project/vllm/issues/25194). Keep this one
# correctness test on L4 until its H200 output matches the Transformers reference.
- label: Language Models Tests (Granite L4 Compatibility)
key: language-models-tests-granite-l4-compatibility
timeout_in_minutes: 65
source_file_dependencies:
- vllm/
- tests/models/language/generation
commands:
- uv pip install --system --no-build-isolation 'git+https://github.com/state-spaces/mamba@v2.3.0'
- uv pip install --system --no-build-isolation 'git+https://github.com/Dao-AILab/causal-conv1d@v1.6.0'
- pytest -v -s models/language/generation -m hybrid_model -k 'granite-4.0-tiny-preview'
- label: Language Models Test (Extended Generation) # 80min
device: h200_35gb
key: language-models-test-extended-generation
timeout_in_minutes: 65
timeout_in_minutes: 110
optional: true
source_file_dependencies:
- vllm/
@@ -109,7 +76,7 @@ steps:
- label: Language Models Test (PPL)
key: language-models-test-ppl
timeout_in_minutes: 30
timeout_in_minutes: 110
device: h200_18gb
optional: true
source_file_dependencies:
@@ -118,10 +85,10 @@ steps:
commands:
- pytest -v -s models/language/generation_ppl_test
- label: Language Models Test (Extended Pooling)
- label: Language Models Test (Extended Pooling) # 36min
device: h200_35gb
key: language-models-test-extended-pooling
timeout_in_minutes: 120
timeout_in_minutes: 50
optional: true
source_file_dependencies:
- vllm/
@@ -131,13 +98,13 @@ steps:
mirror:
amd:
device: mi325_1
timeout_in_minutes: 120
timeout_in_minutes: 100
depends_on:
- image-build-amd
- label: Language Models Test (MTEB)
key: language-models-test-mteb
timeout_in_minutes: 45
timeout_in_minutes: 110
device: h200_18gb
optional: true
source_file_dependencies:
+19 -25
View File
@@ -10,6 +10,7 @@ steps:
- vllm/
- tests/models/multimodal
commands:
- pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
- pytest -v -s models/multimodal/generation/test_common.py -m core_model -k "qwen2"
- pytest -v -s models/multimodal/generation/test_ultravox.py -m core_model
mirror:
@@ -20,14 +21,14 @@ steps:
- label: "Multi-Modal Models (Standard) 2: qwen3 + gemma"
key: multi-modal-models-standard-2-qwen3-gemma
timeout_in_minutes: 50
timeout_in_minutes: 45
device: h200_18gb
source_file_dependencies:
- vllm/
- tests/models/multimodal
commands:
- pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
- pytest -v -s models/multimodal/generation/test_common.py -m core_model -k "qwen3 or gemma"
- pytest -v -s models/multimodal/generation/test_mm_prefix_lm.py -m core_model
- pytest -v -s models/multimodal/generation/test_qwen2_5_vl.py -m core_model
mirror:
amd:
@@ -38,11 +39,12 @@ steps:
- label: "Multi-Modal Models (Standard) 3: llava + qwen2_vl"
device: h200_35gb
key: multi-modal-models-standard-3-llava-qwen2-vl
timeout_in_minutes: 40
timeout_in_minutes: 45
source_file_dependencies:
- vllm/
- tests/models/multimodal
commands:
- pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
- pytest -v -s models/multimodal/generation/test_common.py -m core_model -k "not qwen2 and not qwen3 and not gemma"
- pytest -v -s models/multimodal/generation/test_qwen2_vl.py -m core_model
mirror:
@@ -54,12 +56,13 @@ steps:
- label: "Multi-Modal Models (Standard) 4: other + whisper"
device: h200_35gb
key: multi-modal-models-standard-4-other-whisper
timeout_in_minutes: 50
timeout_in_minutes: 45
source_file_dependencies:
- vllm/
- tests/models/multimodal
commands:
- pytest -v -s models/multimodal -m core_model --ignore models/multimodal/generation/test_common.py --ignore models/multimodal/generation/test_ultravox.py --ignore models/multimodal/generation/test_qwen2_5_vl.py --ignore models/multimodal/generation/test_qwen2_vl.py --ignore models/multimodal/generation/test_whisper.py --ignore models/multimodal/generation/test_mm_prefix_lm.py --ignore models/multimodal/generation/test_memory_leak.py --ignore models/multimodal/generation/test_vit_cudagraph.py --ignore models/multimodal/processing
- pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
- pytest -v -s models/multimodal -m core_model --ignore models/multimodal/generation/test_common.py --ignore models/multimodal/generation/test_ultravox.py --ignore models/multimodal/generation/test_qwen2_5_vl.py --ignore models/multimodal/generation/test_qwen2_vl.py --ignore models/multimodal/generation/test_whisper.py --ignore models/multimodal/generation/test_memory_leak.py --ignore models/multimodal/generation/test_vit_cudagraph.py --ignore models/multimodal/processing
- pytest -v -s models/multimodal/generation/test_vit_cudagraph.py -m core_model
- pytest models/multimodal/generation/test_memory_leak.py -m core_model
- cd .. && VLLM_WORKER_MULTIPROC_METHOD=spawn pytest -v -s tests/models/multimodal/generation/test_whisper.py -m core_model # Otherwise, mp_method="spawn" doesn't work
@@ -69,35 +72,36 @@ steps:
depends_on:
- image-build-amd
- label: Multi-Modal Processor (CPU) %N
- label: Multi-Modal Processor (CPU)
key: multi-modal-processor-cpu
depends_on:
- image-build-cpu
timeout_in_minutes: 125
timeout_in_minutes: 60
source_file_dependencies:
- vllm/
- tests/models/multimodal
- tests/models/registry.py
device: cpu-medium
commands:
- pytest -v -s models/multimodal/processing --ignore models/multimodal/processing/test_tensor_schema.py --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB
parallelism: 4
- pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
- pytest -v -s models/multimodal/processing --ignore models/multimodal/processing/test_tensor_schema.py
- label: Multi-Modal Processor # 44min
key: multi-modal-processor
timeout_in_minutes: 65
timeout_in_minutes: 60
device: h200_18gb
source_file_dependencies:
- vllm/
- tests/models/multimodal
- tests/models/registry.py
commands:
- pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
- pytest -v -s models/multimodal/processing/test_tensor_schema.py
- label: Multi-Modal Accuracy Eval (Small Models) # 50min
device: h200_35gb
key: multi-modal-accuracy-eval-small-models
timeout_in_minutes: 30
timeout_in_minutes: 70
working_dir: "/vllm-workspace/.buildkite/lm-eval-harness"
source_file_dependencies:
- vllm/multimodal/
@@ -105,21 +109,8 @@ steps:
- vllm/v1/core/
commands:
- pytest -s -v test_lm_eval_correctness.py --config-list-file=configs/models-mm-small.txt --tp-size=1
mirror:
amd:
dind: false
device: mi300_1
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/multimodal/
- vllm/inputs/
- vllm/v1/core/
- vllm/platforms/rocm.py
- vllm/model_executor/model_loader/
- label: Multi-Modal Models (Extended Generation 1)
device: h200_35gb
key: multi-modal-models-extended-generation-1
optional: true
source_file_dependencies:
@@ -127,6 +118,7 @@ steps:
- tests/models/multimodal/generation
- tests/models/multimodal/test_mapping.py
commands:
- pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
- pytest -v -s models/multimodal/generation -m 'not core_model' --ignore models/multimodal/generation/test_common.py
- pytest -v -s models/multimodal/test_mapping.py
mirror:
@@ -143,6 +135,7 @@ steps:
- vllm/
- tests/models/multimodal/generation
commands:
- pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
- pytest -v -s models/multimodal/generation/test_common.py -m 'split(group=0) and not core_model'
- label: Multi-Modal Models (Extended Generation 3)
@@ -153,6 +146,7 @@ steps:
- vllm/
- tests/models/multimodal/generation
commands:
- pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
- pytest -v -s models/multimodal/generation/test_common.py -m 'split(group=1) and not core_model'
- label: Multi-Modal Models (Extended Pooling)
@@ -167,7 +161,7 @@ steps:
mirror:
amd:
device: mi325_1
timeout_in_minutes: 75
timeout_in_minutes: 60
depends_on:
- image-build-amd
source_file_dependencies:
+1 -6
View File
@@ -4,7 +4,7 @@ depends_on:
steps:
- label: Plugin Tests (2 GPUs)
key: plugin-tests-2-gpus
timeout_in_minutes: 35
timeout_in_minutes: 60
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
@@ -37,11 +37,6 @@ steps:
- pytest -v -s plugins_tests/test_stats_logger_plugins.py
- pip uninstall dummy_stat_logger -y
# end stat_logger plugins test
# begin endpoint plugins test
- pip install -e ./plugins/vllm_add_dummy_endpoint_plugin
- pytest -v -s plugins_tests/test_endpoint_plugins.py
- pip uninstall vllm_add_dummy_endpoint_plugin -y
# end endpoint plugins test
# other tests continue here:
- pytest -v -s plugins_tests/test_scheduler_plugins.py
- pip install -e ./plugins/vllm_add_dummy_model
+6 -52
View File
@@ -5,7 +5,7 @@ steps:
- label: PyTorch Compilation Unit Tests
device: h200_35gb
key: pytorch-compilation-unit-tests
timeout_in_minutes: 90
timeout_in_minutes: 10
source_file_dependencies:
- vllm/__init__.py
- vllm/_aiter_ops.py
@@ -78,7 +78,7 @@ steps:
- label: PyTorch Compilation Passes Unit Tests
key: pytorch-compilation-passes-unit-tests
timeout_in_minutes: 45
timeout_in_minutes: 20
source_file_dependencies:
- vllm/__init__.py
- vllm/_aiter_ops.py
@@ -109,16 +109,14 @@ steps:
- pytest -s -v compile/passes --ignore compile/passes/distributed
mirror:
amd:
dind: false
device: mi300_1
timeout_in_minutes: 65
timeout_in_minutes: 180
depends_on:
- image-build-amd
- label: PyTorch Fullgraph Smoke Test
device: h200_35gb
key: pytorch-fullgraph-smoke-test
timeout_in_minutes: 90
timeout_in_minutes: 35
source_file_dependencies:
- vllm/__init__.py
- vllm/_aiter_ops.py
@@ -150,46 +148,11 @@ steps:
# as it is a heavy test that is covered in other steps.
# Use `find` to launch multiple instances of pytest so that
# they do not suffer from https://github.com/vllm-project/vllm/issues/28965
- "find compile/fullgraph/ -name 'test_*.py' -not -name 'test_full_cudagraph.py' -not -name 'test_full_graph.py' -print0 | xargs -0 -n1 -I{} pytest -s -v '{}'"
# Hopper-only DeepSeek-V2-Lite cases in this file require two 29.3-GiB model
# instances and cannot fit a 35GB MIG slice. L4 retains the original coverage:
# those SM90 cases skip while the architecture-compatible cases still run.
- label: PyTorch Fullgraph CUDAGraph (L4 Compatibility)
key: pytorch-fullgraph-cudagraph-l4-compatibility
timeout_in_minutes: 60
source_file_dependencies:
- vllm/__init__.py
- vllm/_aiter_ops.py
- vllm/_custom_ops.py
- vllm/compilation/
- vllm/config/
- vllm/distributed/
- vllm/engine/
- vllm/env_override.py
- vllm/envs.py
- vllm/forward_context.py
- vllm/inputs/
- vllm/ir/
- vllm/kernels/
- vllm/logger.py
- vllm/model_executor/
- vllm/multimodal/
- vllm/platforms/
- vllm/plugins/
- vllm/sampling_params.py
- vllm/sequence.py
- vllm/transformers_utils/
- vllm/triton_utils/
- vllm/utils/
- vllm/v1/
- tests/compile
commands:
- pytest -s -v compile/fullgraph/test_full_cudagraph.py
- "find compile/fullgraph/ -name 'test_*.py' -not -name 'test_full_graph.py' -print0 | xargs -0 -n1 -I{} pytest -s -v '{}'"
- label: PyTorch Fullgraph
key: pytorch-fullgraph
timeout_in_minutes: 40
timeout_in_minutes: 30
device: h200_18gb
source_file_dependencies:
- vllm/__init__.py
@@ -232,12 +195,3 @@ steps:
- requirements/test/nightly-torch.txt
commands:
- bash standalone_tests/pytorch_nightly_dependency.sh
mirror:
amd:
dind: false
device: mi300_1
depends_on:
- image-build-amd
source_file_dependencies:
- requirements/test/nightly-torch.txt
- vllm/platforms/rocm.py
+6 -17
View File
@@ -3,11 +3,8 @@ depends_on:
- image-build
steps:
- label: Quantization
device: h200_35gb
key: quantization
timeout_in_minutes: 75
env:
VLLM_USE_V2_MODEL_RUNNER: "0"
timeout_in_minutes: 90
source_file_dependencies:
- csrc/
- vllm/model_executor/layers/quantization
@@ -22,15 +19,11 @@ steps:
# TODO(jerryzh168): resolve the above comment
- uv pip install --system torchao==0.17.0 --index-url https://download.pytorch.org/whl/cu130
- uv pip install --system conch-triton-kernels
# The SM90-only checkpoint currently contains a removed weight_chan_scale
# parameter. It was not exercised by the previous L4 job.
- VLLM_TEST_FORCE_LOAD_FORMAT=auto pytest -v -s quantization/ --ignore quantization/test_blackwell_moe.py -k 'not test_compressed_tensors_w4a8_fp8' --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
parallelism: 8
- VLLM_TEST_FORCE_LOAD_FORMAT=auto pytest -v -s quantization/ --ignore quantization/test_blackwell_moe.py
- label: Quantized Fusions
device: h200_35gb
key: quantized-fusions
timeout_in_minutes: 20
timeout_in_minutes: 30
source_file_dependencies:
- tests/fusion
- vllm/model_executor/layers/fusion
@@ -42,7 +35,7 @@ steps:
- label: Quantized MoE Test (B200)
key: quantized-moe-test-b200
timeout_in_minutes: 120
timeout_in_minutes: 60
working_dir: "/vllm-workspace/"
device: b200-k8s
source_file_dependencies:
@@ -59,14 +52,10 @@ steps:
- pytest -s -v tests/quantization/test_blackwell_moe.py
- label: Quantized Models Test
device: h200_35gb
key: quantized-models-test
timeout_in_minutes: 65
env:
VLLM_USE_V2_MODEL_RUNNER: "0"
timeout_in_minutes: 60
source_file_dependencies:
- vllm/model_executor/layers/quantization
- tests/models/quantization
commands:
- pytest -v -s models/quantization --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
parallelism: 3
- pytest -v -s models/quantization
+16 -54
View File
@@ -3,16 +3,11 @@ depends_on:
- image-build
steps:
- label: Rust Frontend OpenAI Coverage
timeout_in_minutes: 30
timeout_in_minutes: 90
device: h200_18gb
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- rust/
- build_rust.sh
- tools/build_rust.py
- rust-toolchain.toml
- .buildkite/scripts/rust-coverage.sh
- codecov.yml
- vllm/benchmarks/
- vllm/entrypoints/openai/
- vllm/entrypoints/serve/
@@ -20,116 +15,84 @@ steps:
- tests/utils.py
- tests/benchmarks/test_serve_cli.py
- tests/entrypoints/openai/chat_completion/test_chat_completion.py
- tests/entrypoints/openai/chat_completion/test_chat_logit_bias_validation.py
# - tests/entrypoints/openai/chat_completion/test_chat_logit_bias_validation.py
# - tests/entrypoints/openai/completion/test_prompt_validation.py
- tests/entrypoints/openai/completion/test_shutdown.py
- tests/entrypoints/openai/test_return_token_ids.py
- tests/entrypoints/openai/test_uds.py
# - tests/entrypoints/openai/test_return_token_ids.py
# - tests/entrypoints/openai/test_uds.py
- tests/v1/sample/test_logprobs_e2e.py
commands:
- . /vllm-workspace/.buildkite/scripts/rust-coverage.sh && rust_coverage_start rust-e2e
- export VLLM_USE_RUST_FRONTEND=1
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s benchmarks/test_serve_cli.py -k "not insecure and not (test_bench_serve and not test_bench_serve_chat)"
- pytest -v -s entrypoints/openai/chat_completion/test_chat_completion.py -k "not test_invalid_json_schema and not test_invalid_regex"
- pytest -v -s entrypoints/openai/chat_completion/test_chat_logit_bias_validation.py -k "not multiple"
- pytest -v -s entrypoints/openai/chat_completion/test_chat_completion.py
# - pytest -v -s entrypoints/openai/chat_completion/test_chat_logit_bias_validation.py -k "not invalid"
# - pytest -v -s entrypoints/openai/completion/test_prompt_validation.py -k "not prompt_embeds"
- pytest -v -s entrypoints/openai/completion/test_shutdown.py -k "not engine_failure and not test_abort_timeout_exits_quickly"
# test_comparison streams differently: Rust emits a separate first (prompt_token_ids) chunk and
# finish chunk without logprobs, while the test reads `logprobs.tokens` on every chunk.
- pytest -v -s entrypoints/openai/test_return_token_ids.py -k "not test_comparison"
- pytest -v -s entrypoints/openai/test_uds.py
# - pytest -v -s entrypoints/openai/test_return_token_ids.py
# - pytest -v -s entrypoints/openai/test_uds.py
- pytest -v -s v1/sample/test_logprobs_e2e.py -k "test_prompt_logprobs_e2e_server"
- label: Rust Frontend Serve/Admin Coverage
timeout_in_minutes: 25
timeout_in_minutes: 60
device: h200_18gb
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- rust/
- build_rust.sh
- tools/build_rust.py
- rust-toolchain.toml
- .buildkite/scripts/rust-coverage.sh
- codecov.yml
- vllm/entrypoints/openai/
- vllm/entrypoints/serve/
- vllm/v1/engine/
- tests/utils.py
- tests/entrypoints/serve/dev/rpc/test_collective_rpc.py
- tests/entrypoints/scale_out/token_in_token_out/test_serving_tokens.py
# - tests/entrypoints/serve/dev/rpc/test_collective_rpc.py
- tests/entrypoints/serve/disagg/test_serving_tokens.py
- tests/entrypoints/serve/instrumentator/test_basic.py
- tests/entrypoints/serve/instrumentator/test_metrics.py
# - tests/entrypoints/serve/dev/test_sleep.py
- tests/entrypoints/serve/tokenize/test_tokenization.py
commands:
- . /vllm-workspace/.buildkite/scripts/rust-coverage.sh && rust_coverage_start rust-e2e
- export VLLM_USE_RUST_FRONTEND=1
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- PYTHONPATH=/vllm-workspace pytest -v -s entrypoints/serve/dev/rpc/test_collective_rpc.py
# server_load can be flaky under the Rust frontend; keep it excluded for now.
# - pytest -v -s entrypoints/serve/dev/rpc/test_collective_rpc.py
- pytest -v -s entrypoints/serve/instrumentator/test_basic.py -k "not show_version and not server_load"
# test_generate_logprobs expects Python-style top_logprobs truncation (dedup sampled + cap at max(k, 1)).
- pytest -v -s entrypoints/scale_out/token_in_token_out/test_serving_tokens.py -k "not stream and not lora and not test_generate_logprobs and not stop_string_workflow"
- pytest -v -s entrypoints/serve/disagg/test_serving_tokens.py -k "not stream and not lora and not test_generate_logprobs and not stop_string_workflow"
- pytest -v -s entrypoints/serve/instrumentator/test_metrics.py -k "text and not show and not run_batch and not test_metrics_counts and not test_metrics_exist"
# - pytest -v -s entrypoints/serve/dev/test_sleep.py
# /tokenizer_info is not implemented in the Rust frontend (the CLI flag is accepted as a no-op).
- pytest -v -s entrypoints/serve/tokenize/test_tokenization.py -k "not tokenizer_info"
- label: Rust Frontend Core Correctness
timeout_in_minutes: 20
timeout_in_minutes: 30
device: h200_18gb
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- rust/
- build_rust.sh
- tools/build_rust.py
- rust-toolchain.toml
- .buildkite/scripts/rust-coverage.sh
- codecov.yml
- vllm/entrypoints/openai/
- tests/utils.py
- tests/entrypoints/openai/correctness/test_lmeval.py
commands:
- . /vllm-workspace/.buildkite/scripts/rust-coverage.sh && rust_coverage_start rust-e2e
- export VLLM_USE_RUST_FRONTEND=1
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -s entrypoints/openai/correctness/test_lmeval.py::test_lm_eval_accuracy_v1_engine
- label: Rust Frontend Tool Use
device: h200_35gb
timeout_in_minutes: 25
timeout_in_minutes: 60
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- rust/
- build_rust.sh
- tools/build_rust.py
- rust-toolchain.toml
- .buildkite/scripts/rust-coverage.sh
- codecov.yml
- vllm/entrypoints/openai/
- vllm/tool_parsers/
- tests/utils.py
- tests/tool_use/
commands:
- . /vllm-workspace/.buildkite/scripts/rust-coverage.sh && rust_coverage_start rust-e2e
- export VLLM_USE_RUST_FRONTEND=1
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s tool_use --ignore=tool_use/mistral --models llama3.2 -k "not test_response_format_with_tool_choice_required and not test_parallel_tool_calls_false and not test_tool_call_and_choice"
- label: Rust Frontend Distributed
timeout_in_minutes: 25
timeout_in_minutes: 30
num_devices: 4
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- rust/
- build_rust.sh
- tools/build_rust.py
- rust-toolchain.toml
- .buildkite/scripts/rust-coverage.sh
- codecov.yml
- vllm/distributed/
- vllm/engine/
- vllm/executor/
@@ -140,7 +103,6 @@ steps:
- tests/v1/distributed/test_hybrid_lb_dp.py
- tests/v1/distributed/test_internal_lb_dp.py
commands:
- . /vllm-workspace/.buildkite/scripts/rust-coverage.sh && rust_coverage_start rust-e2e
- export VLLM_USE_RUST_FRONTEND=1
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- export NCCL_CUMEM_HOST_ENABLE=0
@@ -4,7 +4,7 @@ steps:
- label: Rust Frontend Cargo Style + Clippy
key: rust-frontend-cargo-style-clippy
depends_on: []
timeout_in_minutes: 20
timeout_in_minutes: 30
device: cpu-medium
no_plugin: true
source_file_dependencies:
@@ -18,7 +18,7 @@ steps:
- label: Rust Frontend Cargo Tests
key: rust-frontend-cargo-tests
depends_on: []
timeout_in_minutes: 20
timeout_in_minutes: 30
device: cpu-medium
no_plugin: true
source_file_dependencies:
@@ -26,7 +26,5 @@ steps:
- rust-toolchain.toml
- .buildkite/test_areas/rust_frontend_cargo.yaml
- .buildkite/scripts/run-rust-frontend-cargo-ci.sh
- .buildkite/scripts/rust-coverage.sh
- codecov.yml
commands:
- .buildkite/scripts/run-rust-frontend-cargo-ci.sh test
+2 -2
View File
@@ -5,7 +5,7 @@ steps:
- label: Samplers Test
device: h200_35gb
key: samplers-test
timeout_in_minutes: 40
timeout_in_minutes: 75
source_file_dependencies:
- vllm/model_executor/layers
- vllm/sampling_metadata.py
@@ -19,7 +19,7 @@ steps:
- VLLM_USE_FLASHINFER_SAMPLER=1 pytest -v -s samplers
mirror:
amd:
device: mi325_1
device: mi250_1
depends_on:
- image-build-amd
commands:
+11 -13
View File
@@ -4,7 +4,7 @@ depends_on:
steps:
- label: Spec Decode Eagle
key: spec-decode-eagle
timeout_in_minutes: 25
timeout_in_minutes: 30
device: h200_18gb
source_file_dependencies:
- vllm/v1/spec_decode/
@@ -15,7 +15,7 @@ steps:
mirror:
amd:
device: mi325_1
timeout_in_minutes: 60
timeout_in_minutes: 45
depends_on:
- image-build-amd
source_file_dependencies:
@@ -29,7 +29,7 @@ steps:
- label: Spec Decode Eagle Nightly B200
key: spec-decode-eagle-nightly-b200
timeout_in_minutes: 25
timeout_in_minutes: 30
device: b200-k8s
optional: true
source_file_dependencies:
@@ -41,7 +41,7 @@ steps:
- label: Spec Decode Speculators + MTP
key: spec-decode-speculators-mtp
timeout_in_minutes: 20
timeout_in_minutes: 30
device: h200_18gb
source_file_dependencies:
- vllm/v1/spec_decode/
@@ -82,7 +82,7 @@ steps:
- label: Spec Decode Ngram + Suffix
key: spec-decode-ngram-suffix
timeout_in_minutes: 20
timeout_in_minutes: 30
device: h200_18gb
source_file_dependencies:
- vllm/v1/spec_decode/
@@ -93,9 +93,7 @@ steps:
mirror:
amd:
device: mi325_1
timeout_in_minutes: 55
# TODO(akaratza): Test after Torch >= 2.12 bump
soft_fail: true
timeout_in_minutes: 65
depends_on:
- image-build-amd
source_file_dependencies:
@@ -109,7 +107,7 @@ steps:
- label: Spec Decode Draft Model
key: spec-decode-draft-model
timeout_in_minutes: 45
timeout_in_minutes: 30
device: h200_18gb
source_file_dependencies:
- vllm/v1/spec_decode/
@@ -120,7 +118,7 @@ steps:
mirror:
amd:
device: mi325_1
timeout_in_minutes: 55
timeout_in_minutes: 50
depends_on:
- image-build-amd
source_file_dependencies:
@@ -134,7 +132,7 @@ steps:
- label: Spec Decode Draft Model Nightly B200
key: spec-decode-draft-model-nightly-b200
timeout_in_minutes: 40
timeout_in_minutes: 30
device: b200-k8s
optional: true
source_file_dependencies:
@@ -146,7 +144,7 @@ steps:
- label: Speculators Correctness
key: speculators-correctness
timeout_in_minutes: 30
timeout_in_minutes: 60
device: h100
optional: true
num_devices: 1
@@ -159,7 +157,7 @@ steps:
- pytest -v -s v1/spec_decode/test_speculators_correctness.py -m slow_test
- label: Spec Decode MTP hybrid (B200)
timeout_in_minutes: 20
timeout_in_minutes: 30
device: b200-k8s
optional: true
source_file_dependencies:
+1 -9
View File
@@ -4,7 +4,7 @@ depends_on:
steps:
- label: Weight Loading Multiple GPU # 33min
key: weight-loading-multiple-gpu
timeout_in_minutes: 50
timeout_in_minutes: 45
working_dir: "/vllm-workspace/tests"
num_devices: 2
optional: true
@@ -13,14 +13,6 @@ steps:
- tests/weight_loading
commands:
- bash weight_loading/run_model_weight_loading_test.sh -c weight_loading/models.txt
mirror:
amd:
dind: false
device: mi300_2
depends_on:
- image-build-amd
commands:
- bash weight_loading/run_model_weight_loading_test.sh -c weight_loading/models-amd.txt
# - label: Weight Loading Multiple GPU - Large Models # optional
# working_dir: "/vllm-workspace/tests"
+10 -13
View File
@@ -3,7 +3,7 @@
# This lists cover the "core" components of vLLM that require careful review
/vllm/compilation @zou3519 @youkaichao @ProExpertProg @BoyuanFeng
/vllm/distributed/kv_transfer @NickLucche @ApostaC @orozery @xuechendi @ivanium
/vllm/distributed/kv_transfer @NickLucche @ApostaC @orozery @xuechendi
/vllm/lora @jeejeelee
/vllm/model_executor/layers/attention @LucasWilkinson @MatthewBonanni
/vllm/model_executor/layers/fused_moe @mgoin @pavanimajety @zyongye
@@ -11,7 +11,7 @@
/vllm/model_executor/layers/mamba @tdoublep @tomeras91
/vllm/model_executor/layers/mamba/gdn/qwen_gdn_linear_attn.py @tdoublep @ZJY0516 @vadiklyutiy
/vllm/model_executor/model_loader @22quinn
/vllm/model_executor/layers/batch_invariant.py @yewentao256
/vllm/model_executor/layers/batch_invariant.py @yewentao256
/vllm/ir @ProExpertProg
/vllm/kernels/ @ProExpertProg @tjtanaa
/vllm/kernels/helion @ProExpertProg @zou3519
@@ -23,7 +23,7 @@
# Any change to the VllmConfig changes can have a large user-facing impact,
# so spam a lot of people
/vllm/config @WoosukKwon @youkaichao @robertgshaw2-redhat @mgoin @tlrmchlsmth @houseroad @yewentao256 @ProExpertProg
/vllm/config/cache.py @heheda12345 @ivanium
/vllm/config/cache.py @heheda12345
# Config utils
/vllm/config/utils.py @hmellor
@@ -47,7 +47,6 @@
# Rust Frontend
/rust/ @BugenZhao @njhill
/rust/src/bench @esmeetu
/build_rust.sh @BugenZhao @njhill
/rust-toolchain.toml @BugenZhao @njhill
/.buildkite/test_areas/rust* @BugenZhao @njhill
@@ -68,17 +67,16 @@
/vllm/v1/attention/backends/flashinfer.py @mgoin @pavanimajety @vadiklyutiy
/vllm/v1/attention/backends/triton_attn.py @tdoublep
/vllm/v1/attention/backends/gdn_attn.py @ZJY0516 @vadiklyutiy
/vllm/v1/core @WoosukKwon @robertgshaw2-redhat @njhill @ywang96 @alexm-redhat @heheda12345 @ApostaC @orozery @ivanium
/vllm/v1/core @WoosukKwon @robertgshaw2-redhat @njhill @ywang96 @alexm-redhat @heheda12345 @ApostaC @orozery
/vllm/v1/sample @22quinn @houseroad @njhill
/vllm/v1/spec_decode @benchislett @luccafong @MatthewBonanni
/vllm/v1/structured_output @mgoin @russellb @aarnphm @benchislett
/vllm/v1/kv_cache_interface.py @heheda12345 @ivanium
/vllm/v1/kv_cache_interface.py @heheda12345
/vllm/v1/kv_offload @ApostaC @orozery
/vllm/v1/simple_kv_offload @ivanium
/vllm/v1/engine @njhill
/vllm/v1/executor @njhill
/vllm/v1/worker @njhill
/vllm/v1/worker/kv_connector_model_runner_mixin.py @orozery @NickLucche @ivanium
/vllm/v1/worker/kv_connector_model_runner_mixin.py @orozery @NickLucche
# Model runner V2
/vllm/v1/worker/gpu @WoosukKwon @njhill @yewentao256
@@ -105,14 +103,13 @@
/tests/test_inputs.py @DarkLight1337 @ywang96
/tests/entrypoints/llm/test_struct_output_generate.py @mgoin @russellb @aarnphm
/tests/v1/structured_output @mgoin @russellb @aarnphm
/tests/v1/core @WoosukKwon @robertgshaw2-redhat @njhill @ywang96 @alexm-redhat @heheda12345 @ApostaC @orozery @ivanium
/tests/v1/core @WoosukKwon @robertgshaw2-redhat @njhill @ywang96 @alexm-redhat @heheda12345 @ApostaC @orozery
/tests/weight_loading @mgoin @youkaichao @yewentao256
/tests/lora @jeejeelee
/tests/models/language/generation/test_hybrid.py @tdoublep @tomeras91
/tests/v1/kv_connector/nixl_integration @NickLucche
/tests/v1/kv_connector @ApostaC @orozery @ivanium
/tests/v1/kv_connector @ApostaC @orozery
/tests/v1/kv_offload @ApostaC @orozery
/tests/v1/simple_kv_offload @ivanium
/tests/v1/determinism @yewentao256
/tests/reasoning @aarnphm @chaunceyjiang @sfeng33 @bbrowning
/tests/tool_parsers @aarnphm @chaunceyjiang @sfeng33 @bbrowning
@@ -120,7 +117,7 @@
# Transformers modeling backend
/vllm/model_executor/models/transformers @hmellor
/tests/models/transformers @hmellor
/tests/models/test_transformers.py @hmellor
# Docs
/docs/mkdocs @hmellor
@@ -173,7 +170,7 @@ mkdocs.yaml @hmellor
# Kernels
/vllm/v1/attention/ops/chunked_prefill_paged_decode.py @tdoublep
/vllm/v1/attention/ops/triton_unified_attention.py @tdoublep
/vllm/third_party/flash_linear_attention @ZJY0516 @vadiklyutiy
/vllm/model_executor/layers/fla @ZJY0516 @vadiklyutiy
# ROCm related: specify owner with write access to notify AMD folks for careful code review
/vllm/**/*rocm* @tjtanaa @dllehr-amd
-2
View File
@@ -3,5 +3,3 @@
self-hosted-runner:
labels:
- vllm-runners
# Not yet in actionlint's known-label set.
- macos-26
+2 -2
View File
@@ -323,11 +323,11 @@ jobs:
// {users} will be replaced with @mentions
const ccConfig = {
rocm: {
users: ['hongxiayang', 'tjtanaa', 'vllmellm', 'giuseppegrossi'],
users: ['hongxiayang', 'tjtanaa', 'vllmellm'],
message: 'CC {users} for ROCm-related issue',
},
mistral: {
users: ['patrickvonplaten', 'juliendenize', 'andylolu2', 'NickLucche'],
users: ['patrickvonplaten', 'juliendenize', 'andylolu2'],
message: 'CC {users} for Mistral-related issue',
},
// Add more label -> user mappings here
+10 -19
View File
@@ -11,25 +11,13 @@ permissions:
jobs:
macos-m1-smoke-test:
# macos-26 (the supported target) is still a preview runner, so gate on GA
# macos-15 and keep macos-26 non-blocking.
strategy:
fail-fast: false
matrix:
include:
- os: macos-15
required: true
- os: macos-26
required: false
name: macos-m1-smoke-test (${{ matrix.os }})
runs-on: ${{ matrix.os }}
continue-on-error: ${{ !matrix.required }}
runs-on: macos-latest
timeout-minutes: 30
steps:
- uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0 # v7.0.0
- uses: actions/checkout@v6.0.1
- uses: astral-sh/setup-uv@37802adc94f370d6bfd71619e3f0bf239e1f3b78 # v7.6.0
- uses: astral-sh/setup-uv@v7
with:
enable-cache: true
cache-dependency-glob: |
@@ -84,11 +72,14 @@ jobs:
# Test health endpoint
curl -f http://localhost:8000/health
# Long prompt: hits the split-KV path that short prompts skip (#46769).
PAYLOAD=$(python -c "import json; print(json.dumps({'model': 'Qwen/Qwen3-0.6B', 'prompt': 'The quick brown fox jumps over the lazy dog. ' * 24, 'max_tokens': 16}))")
curl -f --max-time 120 http://localhost:8000/v1/completions \
# Test completion
curl -f http://localhost:8000/v1/completions \
-H "Content-Type: application/json" \
-d "$PAYLOAD"
-d '{
"model": "Qwen/Qwen3-0.6B",
"prompt": "Hello",
"max_tokens": 5
}'
# Cleanup
kill "$SERVER_PID"
+3 -4
View File
@@ -28,8 +28,7 @@ jobs:
pull_number: context.payload.pull_request.number,
});
const readyLabels = ['ready', 'ready-run-all-tests'];
const hasReadyLabel = pr.labels.some(l => readyLabels.includes(l.name));
const hasReadyLabel = pr.labels.some(l => l.name === 'ready');
const hasVerifiedLabel = pr.labels.some(l => l.name === 'verified');
const { data: mergedPRs } = await github.rest.search.issuesAndPullRequests({
@@ -41,7 +40,7 @@ jobs:
if (hasReadyLabel || hasVerifiedLabel || mergedCount >= 4) {
core.info(`Check passed: verified label=${hasVerifiedLabel}, ready label=${hasReadyLabel}, 4+ merged PRs=${mergedCount >= 4}`);
} else {
core.setFailed(`PR must have the 'verified', 'ready', or 'ready-run-all-tests' label (the ready labels also trigger tests) or the author must have at least 4 merged PRs (found ${mergedCount}).`);
core.setFailed(`PR must have the 'verified' or 'ready' (which also triggers tests) label or the author must have at least 4 merged PRs (found ${mergedCount}).`);
}
pre-commit:
@@ -49,7 +48,7 @@ jobs:
if: always() && (needs.pre-run-check.result == 'success' || needs.pre-run-check.result == 'skipped')
runs-on: [self-hosted, linux, x64, vllm-runners]
steps:
- uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0 # v7.0.0
- uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8 # v6.0.1
- uses: actions/setup-python@83679a892e2d95755f2dac6acb0bfd1e9ac5d548 # v6.1.0
with:
python-version: "3.12"
-4
View File
@@ -18,9 +18,6 @@ vllm/third_party/deep_gemm/
# fmha_sm100 vendored package built from source
vllm/third_party/fmha_sm100/
# tml-fa4 vendored package built from source
vllm/third_party/tml_fa4/
# triton jit
.triton
@@ -257,4 +254,3 @@ vllm/grpc/vllm_engine_pb2.pyi
# Ignore generated cpu headers
csrc/cpu/cpu_attn_dispatch_generated.h
rust-coverage-tools/
+2 -15
View File
@@ -30,7 +30,7 @@ repos:
- id: markdownlint-cli2
language_version: lts
args: [--fix]
exclude: (^|/)CLAUDE\.md$
exclude: ^CLAUDE\.md$
- repo: https://github.com/rhysd/actionlint
rev: v1.7.7
hooks:
@@ -131,19 +131,6 @@ repos:
--python-version, "3.12",
]
files: ^requirements/(common|xpu|test/xpu)\.(in|txt)$
- id: pip-compile
alias: pip-compile-cpu
name: pip-compile-cpu
args: [
requirements/test/cuda.in,
-o, requirements/test/cpu.txt,
--index-strategy, unsafe-best-match,
--torch-backend, cpu,
--python-platform, x86_64-manylinux_2_28,
--python-version, "3.12",
]
files: ^requirements/(common|cpu|test/(cuda|cpu))\.(in|txt)$
exclude: ^requirements/test/cuda\.txt$
- id: pip-compile
alias: pip-compile-docs
name: pip-compile-docs
@@ -210,7 +197,7 @@ repos:
name: Check SPDX headers
entry: python tools/pre_commit/check_spdx_header.py
language: python
types_or: [python, rust, proto]
types: [python]
- id: check-root-lazy-imports
name: Check root lazy imports
entry: python tools/pre_commit/check_init_lazy_imports.py
+2
View File
@@ -0,0 +1,2 @@
collect_env.py
vllm/model_executor/layers/fla/ops/*.py
+18 -35
View File
@@ -29,7 +29,6 @@ Do not open one-off PRs for tiny edits (single typo, isolated style change, one
- PR descriptions for AI-assisted work **must** include:
- Why this is not duplicating an existing PR.
- Test commands run and results.
- Model evaluation results when the change affects output, accuracy, or serving.
- Clear statement that AI assistance was used.
### Fail-closed behavior
@@ -67,38 +66,23 @@ VLLM_USE_PRECOMPILED=1 uv pip install -e . --torch-backend=auto
uv pip install -e . --torch-backend=auto
```
### Tests
### Running tests
> Requires [Environment setup](#environment-setup) and [Installing dependencies](#installing-dependencies).
```bash
# Install test dependencies (use cuda.in on non-x86_64):
uv pip install -r requirements/test/cuda.in
# Install test dependencies.
# requirements/test/cuda.txt is pinned to x86_64; on other platforms, use the
# unpinned source file instead:
uv pip install -r requirements/test/cuda.in # resolves for current platform
# Or on x86_64:
uv pip install -r requirements/test/cuda.txt
# Run a specific test file:
# Run a specific test file (use .venv/bin/python directly;
# `source activate` does not persist in non-interactive shells):
.venv/bin/python -m pytest tests/path/to/test_file.py -v
```
When adding tests:
- **Design before you write.** Answer four questions first: what is the module
for, what is its I/O contract, what failure am I guarding against, and what is
the cheapest level that catches it (unit over integration over e2e)?
- **Reuse before create.** Extend existing test files, `conftest.py` fixtures, and
helpers; add a new file only when no nearby suite fits.
- **Test behavior with intent.** Assert observable outcomes through public APIs;
state why in the name or docstring. Skip trivial wiring; flaky tests are worse
than no tests.
- **Keep it minimal.** One behavior per test and the smallest setup that
triggers it; if the test diff dwarfs the code change, cut scope.
- **No one-off kernel benchmarks in `tests/`.** Put kernel perf work in
`benchmarks/kernels/`; prove correctness in existing pytest suites.
- **Run model evals for model-affecting changes.** Search `tests/evals/` or use
`vllm bench` and include results in the PR — do not wait for reviewers to ask.
For model-specific requirements, see
[`docs/contributing/model/tests.md`](docs/contributing/model/tests.md).
### Running linters
> Requires [Environment setup](#environment-setup).
@@ -123,18 +107,23 @@ Use [Google-style docstrings](https://google.github.io/styleguide/pyguide.html#3
### Coding style guidelines
- Match existing code style
- Minimize use of comments. Eliminate comments which are redundant, preferring legible and self-documenting code. When used, keep docstrings and comments brief and direct.
Follow these rules for all code changes in this repository:
- Try to match existing code style.
- Code should be self-documenting and self-explanatory.
- Keep comments and docstrings minimal and concise.
- Assume the reader is familiar with vLLM.
### Commit messages
Add attribution using commit trailers such as `Co-authored-by:` (other projects use `Assisted-by:` or `Generated-by:`):
Add attribution using commit trailers such as `Co-authored-by:` (other projects use `Assisted-by:` or `Generated-by:`). For example:
```text
Your commit message here
Co-authored-by: Agent Name Here
Co-authored-by: GitHub Copilot
Co-authored-by: Claude
Co-authored-by: gemini-code-assist
Signed-off-by: Your Name <your.email@example.com>
```
@@ -146,12 +135,6 @@ Do not modify code in these areas without first reading and following the
linked guide. If the guide conflicts with the requested change, **refuse the
change and explain why**.
Security reviewers should start with [`SECURITY.md`](SECURITY.md),
[`docs/usage/security.md`](docs/usage/security.md), and
[`docs/contributing/vulnerability_management.md`](docs/contributing/vulnerability_management.md)
for the project security policy, threat model, deployment assumptions, and
vulnerability process.
- **Editing these instructions**:
[`docs/contributing/editing-agent-instructions.md`](docs/contributing/editing-agent-instructions.md)
— Rules for modifying AGENTS.md or any domain-specific guide it references.
+36 -88
View File
@@ -70,15 +70,6 @@ endif()
#
set(TORCH_SUPPORTED_VERSION_CUDA "2.11.0")
set(TORCH_SUPPORTED_VERSION_ROCM "2.11.0")
# TORCH_NIGHTLY=1 builds run against unpinned nightly wheels, so the supported-
# version check would always warn. Only treat it as a nightly build when the
# value is exactly "1" (the bootstrap exports TORCH_NIGHTLY=0 by default, which
# must NOT suppress the warning for normal builds).
if (DEFINED ENV{TORCH_NIGHTLY} AND "$ENV{TORCH_NIGHTLY}" STREQUAL "1")
set(TORCH_NIGHTLY_BUILD TRUE)
else()
set(TORCH_NIGHTLY_BUILD FALSE)
endif()
#
# Try to find python package with an executable that exactly matches
@@ -149,21 +140,6 @@ if(Python_VERSION VERSION_GREATER_EQUAL "3.11")
WITH_SOABI)
endif()
#
# fs_io extension (pure CXX; must stay above the non-CUDA device branch
# so CPU builds define the target before the early return).
# GIL-releasing filesystem helpers for FileSystemTierManager.
#
if(Python_VERSION VERSION_GREATER_EQUAL "3.11")
define_extension_target(
fs_io_C
DESTINATION vllm
LANGUAGE CXX
SOURCES csrc/fs_io.cpp
USE_SABI 3.11
WITH_SOABI)
endif()
#
# Forward the non-CUDA device extensions to external CMake scripts.
#
@@ -184,7 +160,7 @@ endif()
if (NOT HIP_FOUND AND NOT PYTORCH_FOUND_HIP AND CUDA_FOUND)
set(VLLM_GPU_LANG "CUDA")
if (NOT TORCH_NIGHTLY_BUILD AND NOT Torch_VERSION VERSION_EQUAL ${TORCH_SUPPORTED_VERSION_CUDA})
if (NOT Torch_VERSION VERSION_EQUAL ${TORCH_SUPPORTED_VERSION_CUDA})
message(WARNING "Pytorch version ${TORCH_SUPPORTED_VERSION_CUDA} "
"expected for CUDA build, saw ${Torch_VERSION} instead.")
endif()
@@ -197,7 +173,7 @@ elseif(HIP_FOUND OR PYTORCH_FOUND_HIP)
enable_language(HIP)
# ROCm 5.X and 6.X
if (NOT TORCH_NIGHTLY_BUILD AND ROCM_VERSION_DEV_MAJOR GREATER_EQUAL 5 AND
if (ROCM_VERSION_DEV_MAJOR GREATER_EQUAL 5 AND
Torch_VERSION VERSION_LESS ${TORCH_SUPPORTED_VERSION_ROCM})
message(WARNING "Pytorch version >= ${TORCH_SUPPORTED_VERSION_ROCM} "
"expected for ROCm build, saw ${Torch_VERSION} instead.")
@@ -294,16 +270,6 @@ if(VLLM_GPU_LANG STREQUAL "HIP")
#
set(CMAKE_${VLLM_GPU_LANG}_FLAGS "${CMAKE_${VLLM_GPU_LANG}_FLAGS} -Wno-unused-result -Wno-unused-value")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wno-unused-result -Wno-unused-value")
# When using LTO then *.cpp files must be compiled with same compiler as used linker
# So if HIP uses clang linker we also must use it
# Otherwise symbols will be missing from .so
if (CMAKE_CXX_FLAGS MATCHES "\-flto")
if(NOT CMAKE_CXX_COMPILER_ID STREQUAL CMAKE_HIP_COMPILER_ID)
message(FATAL_ERROR "LTO is enabled for ROCm build, but the C++ compiler (${CMAKE_CXX_COMPILER_ID}) and HIP compiler (${CMAKE_HIP_COMPILER_ID}) are different which is not supported. "
"Please ensure they are same by setting CXX=${CMAKE_HIP_COMPILER} environment variable. Or alternatively disable LTO.")
endif()
endif()
endif()
#
@@ -359,7 +325,9 @@ endif()
if(VLLM_GPU_LANG STREQUAL "HIP")
set(VLLM_EXT_SRC
"csrc/torch_bindings.cpp"
"csrc/custom_quickreduce.cu")
"csrc/custom_quickreduce.cu"
"csrc/cuda_view.cu"
"csrc/libtorch_stable/cuda_utils_kernels.cu")
message(STATUS "Enabling C extension.")
define_extension_target(
@@ -387,10 +355,7 @@ if(VLLM_GPU_LANG STREQUAL "CUDA" OR VLLM_GPU_LANG STREQUAL "HIP")
#
set(VLLM_STABLE_EXT_SRC
"csrc/libtorch_stable/torch_bindings.cpp"
"csrc/libtorch_stable/cuda_view.cu"
"csrc/libtorch_stable/cuda_utils_kernels.cu"
"csrc/libtorch_stable/activation_kernels.cu"
"csrc/libtorch_stable/ngram_embedding_kernels.cu"
"csrc/libtorch_stable/quantization/activation_kernels.cu"
"csrc/libtorch_stable/quantization/w8a8/int8/scaled_quant.cu"
"csrc/libtorch_stable/quantization/w8a8/fp8/common.cu"
@@ -409,29 +374,14 @@ if(VLLM_GPU_LANG STREQUAL "CUDA" OR VLLM_GPU_LANG STREQUAL "HIP")
"csrc/libtorch_stable/sampler.cu"
"csrc/libtorch_stable/topk.cu"
"csrc/libtorch_stable/mamba/selective_scan_fwd.cu"
"csrc/libtorch_stable/attention/paged_attention_v1.cu"
"csrc/libtorch_stable/attention/paged_attention_v2.cu"
"csrc/libtorch_stable/cache_kernels.cu"
"csrc/libtorch_stable/cache_kernels.cu"
"csrc/libtorch_stable/cache_kernels_fused.cu"
"csrc/libtorch_stable/custom_all_reduce.cu"
"csrc/libtorch_stable/fused_deepseek_v4_qnorm_rope_kv_insert_kernel.cu")
if(VLLM_GPU_LANG STREQUAL "CUDA" AND
DEFINED CMAKE_CUDA_COMPILER_VERSION AND
CMAKE_CUDA_COMPILER_VERSION VERSION_GREATER_EQUAL 12.0)
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 13.0)
cuda_archs_loose_intersection(COOPERATIVE_TOPK_ARCHS
"9.0a;10.0f;10.1f;10.3f;11.0f;12.0f;12.1f" "${CUDA_ARCHS}")
else()
cuda_archs_loose_intersection(COOPERATIVE_TOPK_ARCHS
"9.0a;10.0a;10.1a;10.3a;12.0a;12.1a" "${CUDA_ARCHS}")
endif()
if(COOPERATIVE_TOPK_ARCHS)
list(APPEND VLLM_GPU_FLAGS "-DVLLM_ENABLE_COOPERATIVE_TOPK=1")
endif()
endif()
if(VLLM_GPU_LANG STREQUAL "CUDA")
SET(CUTLASS_ENABLE_HEADERS_ONLY ON CACHE BOOL "Enable only the header library")
@@ -466,6 +416,8 @@ if(VLLM_GPU_LANG STREQUAL "CUDA" OR VLLM_GPU_LANG STREQUAL "HIP")
FetchContent_MakeAvailable(cutlass)
list(APPEND VLLM_STABLE_EXT_SRC
"csrc/libtorch_stable/cuda_view.cu"
"csrc/libtorch_stable/cuda_utils_kernels.cu"
"csrc/libtorch_stable/cutlass_extensions/common.cpp"
"csrc/libtorch_stable/quantization/w8a8/cutlass/scaled_mm_entry.cu"
"csrc/libtorch_stable/quantization/fp4/nvfp4_quant_entry.cu"
@@ -546,14 +498,6 @@ if(VLLM_GPU_LANG STREQUAL "CUDA" OR VLLM_GPU_LANG STREQUAL "HIP")
SRCS "${VLLM_STABLE_EXT_SRC}"
CUDA_ARCHS "${CUDA_ARCHS}")
if(COOPERATIVE_TOPK_ARCHS)
list(APPEND VLLM_STABLE_EXT_SRC
"csrc/libtorch_stable/cooperative_topk.cu")
set_gencode_flags_for_srcs(
SRCS "csrc/libtorch_stable/cooperative_topk.cu"
CUDA_ARCHS "${COOPERATIVE_TOPK_ARCHS}")
endif()
# Only build Marlin kernels if we are building for at least some compatible archs.
# Keep building Marlin for 9.0 as there are some group sizes and shapes that
# are not supported by Machete yet.
@@ -899,9 +843,9 @@ if(VLLM_GPU_LANG STREQUAL "CUDA" OR VLLM_GPU_LANG STREQUAL "HIP")
endif()
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 13.0)
cuda_archs_loose_intersection(SCALED_MM_ARCHS "10.0f;11.0f" "${CUDA_ARCHS}")
cuda_archs_loose_intersection(SCALED_MM_ARCHS "10.0f" "${CUDA_ARCHS}")
else()
cuda_archs_loose_intersection(SCALED_MM_ARCHS "10.0a;10.1a;10.3a" "${CUDA_ARCHS}")
cuda_archs_loose_intersection(SCALED_MM_ARCHS "10.0a;10.3a" "${CUDA_ARCHS}")
endif()
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 12.8 AND SCALED_MM_ARCHS)
set(CUTLASS_MOE_SM100_SRCS "csrc/libtorch_stable/quantization/w8a8/cutlass/moe/grouped_mm_c3x_sm100.cu")
@@ -1096,24 +1040,25 @@ if(VLLM_GPU_LANG STREQUAL "CUDA" OR VLLM_GPU_LANG STREQUAL "HIP")
USE_SABI 3
WITH_SOABI)
# Set TORCH_TARGET_VERSION for stable ABI compatibility.
# This ensures we only use C-shim APIs available in PyTorch 2.11.
# _C_stable_libtorch is abi compatible with PyTorch >= TORCH_TARGET_VERSION
# which is currently set to 2.11.
target_compile_definitions(_C_stable_libtorch PRIVATE
TORCH_TARGET_VERSION=0x020B000000000000ULL)
# Needed to use cuda/hip APIs from C-shim
if(VLLM_GPU_LANG STREQUAL "CUDA")
# Set TORCH_TARGET_VERSION for stable ABI compatibility.
# This ensures we only use C-shim APIs available in PyTorch 2.11.
# _C_stable_libtorch is abi compatible with PyTorch >= TORCH_TARGET_VERSION
# which is currently set to 2.11.
target_compile_definitions(_C_stable_libtorch PRIVATE
TORCH_TARGET_VERSION=0x020B000000000000ULL)
target_compile_definitions(_C_stable_libtorch PRIVATE USE_CUDA)
if(COOPERATIVE_TOPK_ARCHS)
target_compile_definitions(_C_stable_libtorch PRIVATE
VLLM_ENABLE_COOPERATIVE_TOPK=1)
endif()
# Needed by CUTLASS kernels
target_compile_definitions(_C_stable_libtorch PRIVATE
CUTLASS_ENABLE_DIRECT_CUDA_DRIVER_CALL=1)
elseif(VLLM_GPU_LANG STREQUAL "HIP")
# Set TORCH_TARGET_VERSION for stable ABI compatibility.
# This ensures we only use C-shim APIs available in PyTorch 2.10.
# _C_stable_libtorch is abi compatible with PyTorch >= TORCH_TARGET_VERSION
# which is currently set to 2.10.
target_compile_definitions(_C_stable_libtorch PRIVATE
TORCH_TARGET_VERSION=0x020A000000000000ULL)
target_compile_definitions(_C_stable_libtorch PRIVATE USE_ROCM)
endif()
@@ -1321,20 +1266,25 @@ define_extension_target(
USE_SABI 3
WITH_SOABI)
# Set TORCH_TARGET_VERSION for stable ABI compatibility.
# This ensures we only use C-shim APIs available in PyTorch 2.11.
# _moe_C_stable_libtorch is abi compatible with PyTorch >= TORCH_TARGET_VERSION
# which is currently set to 2.11.
target_compile_definitions(_moe_C_stable_libtorch PRIVATE
TORCH_TARGET_VERSION=0x020B000000000000ULL)
# Needed to use cuda/hip APIs from C-shim
if(VLLM_GPU_LANG STREQUAL "CUDA")
# Set TORCH_TARGET_VERSION for stable ABI compatibility.
# This ensures we only use C-shim APIs available in PyTorch 2.11.
# _moe_C_stable_libtorch is abi compatible with PyTorch >= TORCH_TARGET_VERSION
# which is currently set to 2.11.
target_compile_definitions(_moe_C_stable_libtorch PRIVATE
TORCH_TARGET_VERSION=0x020B000000000000ULL)
target_compile_definitions(_moe_C_stable_libtorch PRIVATE USE_CUDA)
# Needed by CUTLASS kernels
target_compile_definitions(_moe_C_stable_libtorch PRIVATE
CUTLASS_ENABLE_DIRECT_CUDA_DRIVER_CALL=1)
elseif(VLLM_GPU_LANG STREQUAL "HIP")
# Set TORCH_TARGET_VERSION for stable ABI compatibility.
# This ensures we only use C-shim APIs available in PyTorch 2.10.
# _moe_C_stable_libtorch is abi compatible with PyTorch >= TORCH_TARGET_VERSION
# which is currently set to 2.10.
target_compile_definitions(_moe_C_stable_libtorch PRIVATE
TORCH_TARGET_VERSION=0x020A000000000000ULL)
target_compile_definitions(_moe_C_stable_libtorch PRIVATE USE_ROCM)
endif()
@@ -1364,7 +1314,6 @@ if(VLLM_GPU_LANG STREQUAL "HIP")
set(VLLM_ROCM_EXT_SRC
"csrc/rocm/torch_bindings.cpp"
"csrc/rocm/skinny_gemms.cu"
"csrc/rocm/skinny_gemms_int4.cu"
"csrc/rocm/attention.cu")
set(VLLM_ROCM_HAS_GFX1100 OFF)
@@ -1408,7 +1357,6 @@ if (VLLM_GPU_LANG STREQUAL "CUDA")
include(cmake/external_projects/fmha_sm100.cmake)
include(cmake/external_projects/flashmla.cmake)
include(cmake/external_projects/qutlass.cmake)
include(cmake/external_projects/tml_fa4.cmake)
# vllm-flash-attn should be last as it overwrites some CMake functions
include(cmake/external_projects/vllm_flash_attn.cmake)
+1 -1
View File
@@ -48,7 +48,7 @@ vLLM is flexible and easy to use with:
- Tool calling and reasoning parsers
- OpenAI-compatible API server, plus Anthropic Messages API and gRPC support
- Efficient multi-LoRA support for dense and MoE layers
- Support for NVIDIA GPUs, AMD GPUs, Intel GPUs, and x86/ARM/PowerPC CPUs. Additionally, diverse hardware plugins such as Google TPUs, Intel Gaudi, IBM Spyre, Huawei Ascend, Rebellions NPU, Apple Silicon, MetaX GPU, and more.
- Support for NVIDIA GPUs, AMD GPUs, and x86/ARM/PowerPC CPUs. Additionally, diverse hardware plugins such as Google TPUs, Intel Gaudi, IBM Spyre, Huawei Ascend, Rebellions NPU, Apple Silicon, MetaX GPU, and more.
vLLM seamlessly supports 200+ model architectures on Hugging Face, including:
+3 -175
View File
@@ -75,11 +75,7 @@ def run_mla_benchmark(config: BenchmarkConfig, **kwargs) -> BenchmarkResult:
from mla_runner import run_mla_benchmark as run_mla
return run_mla(
config.backend,
config,
prefill_backend=config.prefill_backend,
sparse_mla_force_mqa=config.sparse_mla_force_mqa,
**kwargs,
config.backend, config, prefill_backend=config.prefill_backend, **kwargs
)
@@ -596,30 +592,6 @@ def main():
default="profile",
help="Output file name for ncu profile (default: 'profile').",
)
parser.add_argument(
"--torch-profile",
action="store_true",
default=False,
help="Collect a PyTorch profiler Chrome trace for each benchmark run.",
)
parser.add_argument(
"--torch-profile-dir",
default=None,
help="Directory for PyTorch profiler traces.",
)
parser.add_argument(
"--torch-profile-iters",
type=int,
default=3,
help="Number of forward passes to record per PyTorch profiler trace.",
)
parser.add_argument(
"--sparse-mla-mha-variants",
nargs="+",
default=None,
choices=["dense_mha", "mqa"],
help="Sparse MLA variants to run in mha_vs_mqa mode. Defaults to both.",
)
# Parameter sweep (use YAML config for advanced sweeps)
parser.add_argument(
@@ -669,7 +641,6 @@ def main():
# Prefill backends (e.g., ["fa3", "fa4"])
args.prefill_backends = yaml_config.get("prefill_backends", None)
args.prefill_backend = yaml_config.get("prefill_backend", None)
# FP8 output benchmark knobs; CLI wins.
if args.fp8_output_scale is None:
@@ -712,9 +683,6 @@ def main():
args.num_q_heads = model.get("num_q_heads", args.num_q_heads)
args.num_kv_heads = model.get("num_kv_heads", args.num_kv_heads)
args.block_size = model.get("block_size", args.block_size)
args.max_model_len = model.get(
"max_model_len", getattr(args, "max_model_len", None)
)
# MLA-specific dimensions
args.kv_lora_rank = model.get("kv_lora_rank", args.kv_lora_rank)
args.qk_nope_head_dim = model.get("qk_nope_head_dim", args.qk_nope_head_dim)
@@ -733,21 +701,6 @@ def main():
args.cuda_graphs = yaml_config["cuda_graphs"]
if "ncu_profile" in yaml_config:
args.ncu_profile = yaml_config["ncu_profile"]
if "torch_profile" in yaml_config:
args.torch_profile = yaml_config["torch_profile"]
if "torch_profile_dir" in yaml_config:
args.torch_profile_dir = yaml_config["torch_profile_dir"]
if "torch_profile_iters" in yaml_config:
args.torch_profile_iters = yaml_config["torch_profile_iters"]
args.sparse_mla_topk_pattern = yaml_config.get(
"sparse_mla_topk_pattern", "random"
)
args.sparse_mla_dense_mha_max_seq_len = yaml_config.get(
"sparse_mla_dense_mha_max_seq_len", None
)
args.sparse_mla_mha_variants = yaml_config.get(
"sparse_mla_mha_variants", args.sparse_mla_mha_variants
)
# Parameter sweep configuration
if "parameter_sweep" in yaml_config:
@@ -889,6 +842,8 @@ def main():
num_kv_heads=args.num_kv_heads,
block_size=args.block_size,
device=args.device,
repeats=args.repeats,
warmup_iters=args.warmup_iters,
profile_memory=args.profile_memory,
kv_cache_dtype=args.kv_cache_dtype,
use_cuda_graphs=args.cuda_graphs,
@@ -1108,133 +1063,6 @@ def main():
f"\n [yellow]Prefill always faster for batch_size={bs}[/]"
)
# Handle MHA vs MQA comparison mode for sparse MLA
elif hasattr(args, "mode") and args.mode == "mha_vs_mqa":
console.print("[yellow]Mode: MHA vs MQA comparison for sparse MLA[/]")
sparse_mla_topk_pattern = getattr(args, "sparse_mla_topk_pattern", "random")
dense_mha_max_seq_len = getattr(args, "sparse_mla_dense_mha_max_seq_len", None)
prefill_backend = getattr(args, "prefill_backend", None)
if prefill_backend:
console.print(f"Prefill backend: {prefill_backend}")
available_variants = [
("dense_mha", False, "dense"),
("mqa", True, "auto"),
]
requested_variants = getattr(args, "sparse_mla_mha_variants", None)
if requested_variants is not None:
valid_variants = {label for label, _, _ in available_variants}
invalid_variants = sorted(set(requested_variants) - valid_variants)
if invalid_variants:
raise ValueError(
"Invalid sparse_mla_mha_variants entries: "
f"{invalid_variants}. Valid variants are: "
f"{sorted(valid_variants)}"
)
requested_variant_set = set(requested_variants)
variants = [
variant
for variant in available_variants
if variant[0] in requested_variant_set
]
else:
variants = available_variants
formatter = ResultsFormatter(console)
total = 0
for spec in args.batch_specs:
q_len = max(request.q_len for request in parse_batch_spec(spec))
for variant_label, _, _ in variants:
if (
variant_label == "dense_mha"
and dense_mha_max_seq_len is not None
and q_len > dense_mha_max_seq_len
):
continue
total += len(backends)
with tqdm(total=total, desc="Benchmarking") as pbar:
for spec in args.batch_specs:
q_len = max(request.q_len for request in parse_batch_spec(spec))
for backend in backends:
for variant_label, force_mqa, mha_mode in variants:
if (
variant_label == "dense_mha"
and dense_mha_max_seq_len is not None
and q_len > dense_mha_max_seq_len
):
continue
config = BenchmarkConfig(
backend=f"{backend}_{variant_label}",
batch_spec=spec,
num_layers=args.num_layers,
head_dim=args.head_dim,
num_q_heads=args.num_q_heads,
num_kv_heads=args.num_kv_heads,
block_size=args.block_size,
device=args.device,
max_model_len=getattr(args, "max_model_len", None),
kv_cache_dtype=args.kv_cache_dtype,
profile_memory=args.profile_memory,
use_cuda_graphs=args.cuda_graphs,
ncu_profile=args.ncu_profile,
torch_profile=args.torch_profile,
torch_profile_dir=args.torch_profile_dir,
torch_profile_iters=args.torch_profile_iters,
warmup_ms=args.warmup_ms,
kv_lora_rank=getattr(args, "kv_lora_rank", None),
qk_nope_head_dim=getattr(args, "qk_nope_head_dim", None),
qk_rope_head_dim=getattr(args, "qk_rope_head_dim", None),
v_head_dim=getattr(args, "v_head_dim", None),
sparse_mla_force_mqa=force_mqa,
sparse_mla_mha_mode=mha_mode,
sparse_mla_dense_mha_max_seq_len=dense_mha_max_seq_len,
sparse_mla_topk_pattern=sparse_mla_topk_pattern,
prefill_backend=prefill_backend,
)
# run_mla_benchmark needs the real backend name
from mla_runner import run_mla_benchmark as run_mla
run_label = f"{backend}_{variant_label} {spec}"
pbar.set_postfix_str(run_label)
try:
result = run_mla(
backend,
config,
prefill_backend=prefill_backend,
sparse_mla_force_mqa=force_mqa,
)
except Exception as e:
result = BenchmarkResult(
config=config,
mean_time=float("inf"),
median_time=float("inf"),
std_time=0,
min_time=float("inf"),
max_time=float("inf"),
error=str(e),
)
all_results.append(result)
if args.output_csv:
formatter.save_csv(all_results, args.output_csv)
if args.output_json:
formatter.save_json(all_results, args.output_json)
if not result.success:
console.print(
f"[red]Error {backend}_{variant_label} "
f"{spec}: {result.error}[/]"
)
pbar.update(1)
# Display results with variant labels as separate "backends"
console.print("\n[bold green]MHA vs MQA Results:[/]")
variant_backends = [f"{b}_{v}" for b in backends for v, _, _ in variants]
formatter.print_table(all_results, variant_backends)
# Handle model parameter sweep mode
elif hasattr(args, "model_parameter_sweep") and args.model_parameter_sweep:
# Model parameter sweep
+37 -68
View File
@@ -4,10 +4,8 @@
"""Common utilities for attention benchmarking."""
import csv
import gc
import json
import math
from collections.abc import Sequence
from dataclasses import asdict, dataclass
from pathlib import Path
from typing import Any
@@ -46,13 +44,10 @@ def run_do_bench(
kwargs: dict[str, Any] = {"return_mode": "all"}
if use_cuda_graphs:
result = triton.testing.do_bench_cudagraph(benchmark_fn, **kwargs)
gc.collect()
torch.accelerator.empty_cache()
else:
if warmup_ms is not None:
kwargs["warmup"] = warmup_ms
result = triton.testing.do_bench(benchmark_fn, **kwargs)
torch.accelerator.synchronize()
return result
@@ -96,6 +91,42 @@ except ImportError:
AttentionLayerBase = object # Fallback
class MockKVBProj:
"""Mock KV projection layer for MLA prefill mode.
Mimics ColumnParallelLinear behavior for kv_b_proj in MLA backends.
Projects kv_c_normed to [qk_nope_head_dim + v_head_dim] per head.
"""
def __init__(self, num_heads: int, qk_nope_head_dim: int, v_head_dim: int):
self.num_heads = num_heads
self.qk_nope_head_dim = qk_nope_head_dim
self.v_head_dim = v_head_dim
self.out_dim = qk_nope_head_dim + v_head_dim
self.weight = torch.empty(0, dtype=torch.bfloat16)
def __call__(self, x: torch.Tensor) -> tuple[torch.Tensor]:
"""
Project kv_c_normed to output space.
Args:
x: Input tensor [num_tokens, kv_lora_rank]
Returns:
Tuple containing output tensor
[num_tokens, num_heads, qk_nope_head_dim + v_head_dim]
"""
num_tokens = x.shape[0]
result = torch.randn(
num_tokens,
self.num_heads,
self.out_dim,
device=x.device,
dtype=x.dtype,
)
return (result,) # Return as tuple to match ColumnParallelLinear API
class MockIndexer:
"""Mock Indexer for sparse MLA backends.
@@ -127,60 +158,6 @@ class MockIndexer:
)
self.topk_indices_buffer[:num_tokens] = indices
def fill_indices(
self,
num_tokens: int,
max_kv_len: int,
pattern: str = "random",
requests: Sequence[Any] | None = None,
):
if pattern == "random":
self.fill_random_indices(num_tokens, max_kv_len)
return
if pattern == "prefix":
indices = torch.arange(
self.topk_tokens,
dtype=torch.int32,
device=self.topk_indices_buffer.device,
)
indices = (indices % max_kv_len).expand(num_tokens, -1)
self.topk_indices_buffer[:num_tokens] = indices
return
if pattern == "sliding_window":
if requests is None:
start = max(max_kv_len - self.topk_tokens, 0)
indices = torch.arange(
start,
start + self.topk_tokens,
dtype=torch.int32,
device=self.topk_indices_buffer.device,
)
indices = indices.clamp(max=max_kv_len - 1).expand(num_tokens, -1)
self.topk_indices_buffer[:num_tokens] = indices
return
rows = []
offsets = torch.arange(
self.topk_tokens,
dtype=torch.int32,
device=self.topk_indices_buffer.device,
) - (self.topk_tokens - 1)
for request in requests:
q_len = request.q_len
kv_len = request.kv_len
context_len = kv_len - q_len
positions = torch.arange(
context_len,
kv_len,
dtype=torch.int32,
device=self.topk_indices_buffer.device,
)
row_indices = positions[:, None] + offsets[None, :]
rows.append(row_indices.clamp(min=0, max=kv_len - 1))
self.topk_indices_buffer[:num_tokens] = torch.cat(rows, dim=0)
return
raise ValueError(f"Unknown sparse MLA topk pattern: {pattern}")
class MockLayer(AttentionLayerBase):
"""Mock attention layer with scale parameters and impl.
@@ -275,14 +252,10 @@ class BenchmarkConfig:
num_kv_heads: int
block_size: int
device: str
max_model_len: int | None = None
dtype: torch.dtype = torch.float16
profile_memory: bool = False
use_cuda_graphs: bool = True
use_cuda_graphs: bool = False
ncu_profile: bool = False
torch_profile: bool = False
torch_profile_dir: str | None = None
torch_profile_iters: int = 3
warmup_ms: int | None = None
# "auto" or "fp8"
@@ -298,10 +271,6 @@ class BenchmarkConfig:
# Backend-specific tuning
num_kv_splits: int | None = None # CUTLASS MLA
reorder_batch_threshold: int | None = None # FlashAttn MLA, FlashMLA
sparse_mla_force_mqa: bool = False # Force MQA path for sparse MLA
sparse_mla_mha_mode: str = "auto" # "auto" or "dense"
sparse_mla_dense_mha_max_seq_len: int | None = None
sparse_mla_topk_pattern: str = "random" # "random", "prefix", "sliding_window"
num_splits: int | None = None # FlashAttention split-K (0=auto, 1=disabled)
@@ -1,474 +0,0 @@
# Sparse MLA benchmark: forward_mha vs forward_mqa
#
# Usage:
# python benchmark.py --config configs/mla_sparse_mha_vs_mqa.yaml
#
# Heatmap grid:
# - batch_size: 1, 2, 4, 8, 16, 32
# - seq_len: 32, 64, 128, 256, 512, 1024, 2048
# - q_len: powers of two through seq_len
#
# Specs with q_len < seq_len include context; the q_len == seq_len diagonal
# covers pure prefill.
# The model shape below is the DP case. For the TP8 run, manually change
# model.num_q_heads from 128 to 16 before rerunning this benchmark.
mode: mha_vs_mqa
model:
name: "deepseek-v3"
num_layers: 60
num_q_heads: 128
num_kv_heads: 1
head_dim: 576
kv_lora_rank: 512
qk_nope_head_dim: 128
qk_rope_head_dim: 64
v_head_dim: 128
block_size: 128
max_model_len: 2048
batch_specs:
# Batch size 1
# seq_len = 32
- "1q1s32"
- "1q2s32"
- "1q4s32"
- "1q8s32"
- "1q16s32"
- "1q32"
# seq_len = 64
- "1q1s64"
- "1q2s64"
- "1q4s64"
- "1q8s64"
- "1q16s64"
- "1q32s64"
- "1q64"
# seq_len = 128
- "1q1s128"
- "1q2s128"
- "1q4s128"
- "1q8s128"
- "1q16s128"
- "1q32s128"
- "1q64s128"
- "1q128"
# seq_len = 256
- "1q1s256"
- "1q2s256"
- "1q4s256"
- "1q8s256"
- "1q16s256"
- "1q32s256"
- "1q64s256"
- "1q128s256"
- "1q256"
# seq_len = 512
- "1q1s512"
- "1q2s512"
- "1q4s512"
- "1q8s512"
- "1q16s512"
- "1q32s512"
- "1q64s512"
- "1q128s512"
- "1q256s512"
- "1q512"
# seq_len = 1024
- "1q1s1024"
- "1q2s1024"
- "1q4s1024"
- "1q8s1024"
- "1q16s1024"
- "1q32s1024"
- "1q64s1024"
- "1q128s1024"
- "1q256s1024"
- "1q512s1024"
- "1q1024"
# seq_len = 2048
- "1q1s2048"
- "1q2s2048"
- "1q4s2048"
- "1q8s2048"
- "1q16s2048"
- "1q32s2048"
- "1q64s2048"
- "1q128s2048"
- "1q256s2048"
- "1q512s2048"
- "1q1024s2048"
- "1q2048"
# Batch size 2
# seq_len = 32
- "2q1s32"
- "2q2s32"
- "2q4s32"
- "2q8s32"
- "2q16s32"
- "2q32"
# seq_len = 64
- "2q1s64"
- "2q2s64"
- "2q4s64"
- "2q8s64"
- "2q16s64"
- "2q32s64"
- "2q64"
# seq_len = 128
- "2q1s128"
- "2q2s128"
- "2q4s128"
- "2q8s128"
- "2q16s128"
- "2q32s128"
- "2q64s128"
- "2q128"
# seq_len = 256
- "2q1s256"
- "2q2s256"
- "2q4s256"
- "2q8s256"
- "2q16s256"
- "2q32s256"
- "2q64s256"
- "2q128s256"
- "2q256"
# seq_len = 512
- "2q1s512"
- "2q2s512"
- "2q4s512"
- "2q8s512"
- "2q16s512"
- "2q32s512"
- "2q64s512"
- "2q128s512"
- "2q256s512"
- "2q512"
# seq_len = 1024
- "2q1s1024"
- "2q2s1024"
- "2q4s1024"
- "2q8s1024"
- "2q16s1024"
- "2q32s1024"
- "2q64s1024"
- "2q128s1024"
- "2q256s1024"
- "2q512s1024"
- "2q1024"
# seq_len = 2048
- "2q1s2048"
- "2q2s2048"
- "2q4s2048"
- "2q8s2048"
- "2q16s2048"
- "2q32s2048"
- "2q64s2048"
- "2q128s2048"
- "2q256s2048"
- "2q512s2048"
- "2q1024s2048"
- "2q2048"
# Batch size 4
# seq_len = 32
- "4q1s32"
- "4q2s32"
- "4q4s32"
- "4q8s32"
- "4q16s32"
- "4q32"
# seq_len = 64
- "4q1s64"
- "4q2s64"
- "4q4s64"
- "4q8s64"
- "4q16s64"
- "4q32s64"
- "4q64"
# seq_len = 128
- "4q1s128"
- "4q2s128"
- "4q4s128"
- "4q8s128"
- "4q16s128"
- "4q32s128"
- "4q64s128"
- "4q128"
# seq_len = 256
- "4q1s256"
- "4q2s256"
- "4q4s256"
- "4q8s256"
- "4q16s256"
- "4q32s256"
- "4q64s256"
- "4q128s256"
- "4q256"
# seq_len = 512
- "4q1s512"
- "4q2s512"
- "4q4s512"
- "4q8s512"
- "4q16s512"
- "4q32s512"
- "4q64s512"
- "4q128s512"
- "4q256s512"
- "4q512"
# seq_len = 1024
- "4q1s1024"
- "4q2s1024"
- "4q4s1024"
- "4q8s1024"
- "4q16s1024"
- "4q32s1024"
- "4q64s1024"
- "4q128s1024"
- "4q256s1024"
- "4q512s1024"
- "4q1024"
# seq_len = 2048
- "4q1s2048"
- "4q2s2048"
- "4q4s2048"
- "4q8s2048"
- "4q16s2048"
- "4q32s2048"
- "4q64s2048"
- "4q128s2048"
- "4q256s2048"
- "4q512s2048"
- "4q1024s2048"
- "4q2048"
# Batch size 8
# seq_len = 32
- "8q1s32"
- "8q2s32"
- "8q4s32"
- "8q8s32"
- "8q16s32"
- "8q32"
# seq_len = 64
- "8q1s64"
- "8q2s64"
- "8q4s64"
- "8q8s64"
- "8q16s64"
- "8q32s64"
- "8q64"
# seq_len = 128
- "8q1s128"
- "8q2s128"
- "8q4s128"
- "8q8s128"
- "8q16s128"
- "8q32s128"
- "8q64s128"
- "8q128"
# seq_len = 256
- "8q1s256"
- "8q2s256"
- "8q4s256"
- "8q8s256"
- "8q16s256"
- "8q32s256"
- "8q64s256"
- "8q128s256"
- "8q256"
# seq_len = 512
- "8q1s512"
- "8q2s512"
- "8q4s512"
- "8q8s512"
- "8q16s512"
- "8q32s512"
- "8q64s512"
- "8q128s512"
- "8q256s512"
- "8q512"
# seq_len = 1024
- "8q1s1024"
- "8q2s1024"
- "8q4s1024"
- "8q8s1024"
- "8q16s1024"
- "8q32s1024"
- "8q64s1024"
- "8q128s1024"
- "8q256s1024"
- "8q512s1024"
- "8q1024"
# seq_len = 2048
- "8q1s2048"
- "8q2s2048"
- "8q4s2048"
- "8q8s2048"
- "8q16s2048"
- "8q32s2048"
- "8q64s2048"
- "8q128s2048"
- "8q256s2048"
- "8q512s2048"
- "8q1024s2048"
- "8q2048"
# Batch size 16
# seq_len = 32
- "16q1s32"
- "16q2s32"
- "16q4s32"
- "16q8s32"
- "16q16s32"
- "16q32"
# seq_len = 64
- "16q1s64"
- "16q2s64"
- "16q4s64"
- "16q8s64"
- "16q16s64"
- "16q32s64"
- "16q64"
# seq_len = 128
- "16q1s128"
- "16q2s128"
- "16q4s128"
- "16q8s128"
- "16q16s128"
- "16q32s128"
- "16q64s128"
- "16q128"
# seq_len = 256
- "16q1s256"
- "16q2s256"
- "16q4s256"
- "16q8s256"
- "16q16s256"
- "16q32s256"
- "16q64s256"
- "16q128s256"
- "16q256"
# seq_len = 512
- "16q1s512"
- "16q2s512"
- "16q4s512"
- "16q8s512"
- "16q16s512"
- "16q32s512"
- "16q64s512"
- "16q128s512"
- "16q256s512"
- "16q512"
# seq_len = 1024
- "16q1s1024"
- "16q2s1024"
- "16q4s1024"
- "16q8s1024"
- "16q16s1024"
- "16q32s1024"
- "16q64s1024"
- "16q128s1024"
- "16q256s1024"
- "16q512s1024"
- "16q1024"
# seq_len = 2048
- "16q1s2048"
- "16q2s2048"
- "16q4s2048"
- "16q8s2048"
- "16q16s2048"
- "16q32s2048"
- "16q64s2048"
- "16q128s2048"
- "16q256s2048"
- "16q512s2048"
- "16q1024s2048"
- "16q2048"
# Batch size 32
# seq_len = 32
- "32q1s32"
- "32q2s32"
- "32q4s32"
- "32q8s32"
- "32q16s32"
- "32q32"
# seq_len = 64
- "32q1s64"
- "32q2s64"
- "32q4s64"
- "32q8s64"
- "32q16s64"
- "32q32s64"
- "32q64"
# seq_len = 128
- "32q1s128"
- "32q2s128"
- "32q4s128"
- "32q8s128"
- "32q16s128"
- "32q32s128"
- "32q64s128"
- "32q128"
# seq_len = 256
- "32q1s256"
- "32q2s256"
- "32q4s256"
- "32q8s256"
- "32q16s256"
- "32q32s256"
- "32q64s256"
- "32q128s256"
- "32q256"
# seq_len = 512
- "32q1s512"
- "32q2s512"
- "32q4s512"
- "32q8s512"
- "32q16s512"
- "32q32s512"
- "32q64s512"
- "32q128s512"
- "32q256s512"
- "32q512"
# seq_len = 1024
- "32q1s1024"
- "32q2s1024"
- "32q4s1024"
- "32q8s1024"
- "32q16s1024"
- "32q32s1024"
- "32q64s1024"
- "32q128s1024"
- "32q256s1024"
- "32q512s1024"
- "32q1024"
# seq_len = 2048
- "32q1s2048"
- "32q2s2048"
- "32q4s2048"
- "32q8s2048"
- "32q16s2048"
- "32q32s2048"
- "32q64s2048"
- "32q128s2048"
- "32q256s2048"
- "32q512s2048"
- "32q1024s2048"
- "32q2048"
backends:
- FLASHMLA_SPARSE
device: "cuda:0"
profile_memory: false
sparse_mla_dense_mha_max_seq_len: 2048
sparse_mla_topk_pattern: "random"
output:
csv: "benchmark_output/mla_sparse_mha_vs_mqa.csv"
json: "benchmark_output/mla_sparse_mha_vs_mqa.json"
+17 -171
View File
@@ -9,8 +9,6 @@ needing full VllmConfig integration.
"""
import statistics
import tempfile
from pathlib import Path
import numpy as np
import torch
@@ -19,6 +17,7 @@ from common import (
BenchmarkResult,
MockHfConfig,
MockIndexer,
MockKVBProj,
MockLayer,
run_do_bench,
run_ncu_profile,
@@ -34,59 +33,8 @@ from vllm.config import (
VllmConfig,
set_current_vllm_config,
)
from vllm.model_executor.layers.linear import ColumnParallelLinear
from vllm.v1.attention.backends.mla.prefill.registry import MLAPrefillBackendEnum
def _safe_profile_name(value: str) -> str:
return "".join(c if c.isalnum() or c in "._-" else "_" for c in value)
def _create_kv_b_proj(
mla_dims: dict,
device: torch.device,
):
kv_b_proj = ColumnParallelLinear(
mla_dims["kv_lora_rank"],
mla_dims["num_q_heads"]
* (mla_dims["qk_nope_head_dim"] + mla_dims["v_head_dim"]),
bias=False,
params_dtype=torch.bfloat16,
quant_config=None,
prefix="benchmark.kv_b_proj",
).to(device)
with torch.no_grad():
kv_b_proj.weight.copy_(torch.randn_like(kv_b_proj.weight))
return kv_b_proj
def _ensure_single_rank_model_parallel() -> None:
import torch.distributed as dist
from vllm.distributed import (
ensure_model_parallel_initialized,
init_distributed_environment,
model_parallel_is_initialized,
)
if not dist.is_available():
return
if not dist.is_initialized():
with tempfile.NamedTemporaryFile(
prefix="vllm_bench_dist_", delete=False
) as init_file:
distributed_init_method = f"file://{init_file.name}"
init_distributed_environment(
world_size=1,
rank=0,
distributed_init_method=distributed_init_method,
local_rank=0,
backend="nccl",
)
if not model_parallel_is_initialized():
ensure_model_parallel_initialized(1, 1)
# ============================================================================
# VllmConfig Creation
# ============================================================================
@@ -118,12 +66,10 @@ def create_minimal_vllm_config(
block_size: int = 128,
max_num_seqs: int = 256,
max_num_batched_tokens: int = 8192,
max_model_len: int = 32768,
mla_dims: dict | None = None,
index_topk: int | None = None,
prefill_backend: str | None = None,
kv_cache_dtype: str = "auto",
sparse_mla_force_mqa: bool = False,
) -> VllmConfig:
"""
Create minimal VllmConfig for MLA benchmarks.
@@ -140,8 +86,6 @@ def create_minimal_vllm_config(
prefill_backend: Prefill backend name (e.g., "fa3", "fa4", "flashinfer",
"trtllm"). Configures the attention config to force
the specified prefill backend.
sparse_mla_force_mqa: If True, forces all sparse MLA tokens through
forward_mqa (even prefill tokens).
Returns:
VllmConfig for benchmarking
@@ -187,7 +131,7 @@ def create_minimal_vllm_config(
trust_remote_code=True,
dtype="bfloat16",
seed=0,
max_model_len=max_model_len,
max_model_len=32768,
quantization=None,
enforce_eager=False,
max_logprobs=20,
@@ -219,7 +163,7 @@ def create_minimal_vllm_config(
scheduler_config = SchedulerConfig(
max_num_seqs=max_num_seqs,
max_num_batched_tokens=max(max_num_batched_tokens, max_num_seqs),
max_model_len=max_model_len,
max_model_len=32768,
is_encoder_decoder=False,
enable_chunked_prefill=True,
)
@@ -248,9 +192,6 @@ def create_minimal_vllm_config(
"flash_attn_version"
]
if sparse_mla_force_mqa:
vllm_config.attention_config.sparse_mla_force_mqa = True
return vllm_config
@@ -607,7 +548,12 @@ def _create_backend_impl(
# Calculate scale
scale = 1.0 / np.sqrt(mla_dims["qk_nope_head_dim"] + mla_dims["qk_rope_head_dim"])
kv_b_proj = _create_kv_b_proj(mla_dims, device)
# Create mock kv_b_proj layer for prefill mode
mock_kv_b_proj = MockKVBProj(
num_heads=mla_dims["num_q_heads"],
qk_nope_head_dim=mla_dims["qk_nope_head_dim"],
v_head_dim=mla_dims["v_head_dim"],
)
# Create indexer for sparse backends
indexer = None
@@ -638,7 +584,7 @@ def _create_backend_impl(
"qk_rope_head_dim": mla_dims["qk_rope_head_dim"],
"qk_head_dim": mla_dims["qk_nope_head_dim"] + mla_dims["qk_rope_head_dim"],
"v_head_dim": mla_dims["v_head_dim"],
"kv_b_proj": kv_b_proj,
"kv_b_proj": mock_kv_b_proj,
}
# Add indexer for sparse backends
@@ -839,35 +785,14 @@ def _run_single_benchmark(
# Fill indexer with random indices for sparse backends
is_sparse = backend_cfg.get("is_sparse", False)
if is_sparse and indexer is not None:
indexer.fill_indices(
total_q,
max_kv_len,
getattr(config, "sparse_mla_topk_pattern", "random"),
)
indexer.fill_random_indices(total_q, max_kv_len)
# Determine which forward methods to use based on metadata.
# Non-sparse backends use .decode/.prefill sub-objects.
# Sparse backends use num_decode_tokens/num_prefills directly.
#
# sparse_mla_force_mqa overrides: even for prefill metadata, use MQA.
force_mqa = getattr(config, "sparse_mla_force_mqa", False)
force_dense_mha = getattr(config, "sparse_mla_mha_mode", "auto") == "dense"
if force_mqa:
has_decode = True
has_prefill = False
elif is_sparse:
has_decode = metadata.num_decode_tokens > 0
has_prefill = metadata.num_prefills > 0
else:
has_decode = metadata.decode is not None
has_prefill = metadata.prefill is not None
# Sparse MLA backends always use forward_mqa
has_decode = is_sparse or getattr(metadata, "decode", None) is not None
has_prefill = not is_sparse and getattr(metadata, "prefill", None) is not None
if not has_decode and not has_prefill:
raise RuntimeError("Metadata has neither decode nor prefill metadata")
if is_sparse and force_dense_mha and not has_prefill:
raise RuntimeError(
"Sparse MLA dense_mha benchmark did not produce prefill metadata. "
"Check reorder_batch_threshold/path forcing."
)
num_decode = (
metadata.num_decode_tokens
@@ -946,6 +871,7 @@ def _run_single_benchmark(
metadata,
prefill_inputs["k_scale"],
prefill_fp8_output if fused_output else prefill_inputs["output"],
prefill_output_scale if fused_output else None,
)
if fused_output:
out = prefill_fp8_output
@@ -972,48 +898,6 @@ def _run_single_benchmark(
throughput_tokens_per_sec=0.0,
)
if config.torch_profile:
profile_dir = Path(
config.torch_profile_dir or "benchmark_outputs/torch_profiles"
)
profile_dir.mkdir(parents=True, exist_ok=True)
trace_name = _safe_profile_name(f"{config.backend}_{config.batch_spec}")
trace_path = profile_dir / f"{trace_name}.json"
iters = max(config.torch_profile_iters, 1)
forward_fn()
torch.accelerator.synchronize()
with torch.profiler.profile(
activities=[
torch.profiler.ProfilerActivity.CPU,
torch.profiler.ProfilerActivity.CUDA,
],
record_shapes=True,
profile_memory=True,
with_stack=False,
) as prof:
for _ in range(iters):
forward_fn()
torch.accelerator.synchronize()
prof.step()
prof.export_chrome_trace(str(trace_path))
print(f"Saved PyTorch profiler trace to {trace_path}")
print(
prof.key_averages().table(
sort_by="cuda_time_total",
row_limit=25,
)
)
return BenchmarkResult(
config=config,
mean_time=0.0,
median_time=0.0,
std_time=0.0,
min_time=0.0,
max_time=0.0,
throughput_tokens_per_sec=0.0,
)
all_ms = run_do_bench(benchmark_fn, config.use_cuda_graphs, config.warmup_ms)
# Convert ms to seconds per layer
@@ -1036,7 +920,6 @@ def _run_mla_benchmark_batched(
configs_with_params: list[tuple], # [(config, threshold, num_splits), ...]
index_topk: int = 2048,
prefill_backend: str | None = None,
sparse_mla_force_mqa: bool = False,
output_scale: float | None = None,
fuse_quant_op: bool = False,
) -> list[BenchmarkResult]:
@@ -1057,8 +940,6 @@ def _run_mla_benchmark_batched(
index_topk: Topk value for sparse MLA backends (default 2048)
prefill_backend: Prefill backend name (e.g., "fa3", "fa4").
When set, forces the specified FlashAttention version for prefill.
sparse_mla_force_mqa: If True, forces all sparse MLA tokens through
forward_mqa (even prefill tokens).
Returns:
List of BenchmarkResult objects
@@ -1099,41 +980,21 @@ def _run_mla_benchmark_batched(
sum(r.q_len for r in parse_batch_spec(cfg.batch_spec))
for cfg, *_ in configs_with_params
)
max_model_len = max(
max_total_q,
max(
getattr(cfg, "max_model_len", None) or 32768
for cfg, *_ in configs_with_params
),
)
# Create and set vLLM config for MLA (reused across all benchmarks)
vllm_config = create_minimal_vllm_config(
model_name="deepseek-v3", # Used only for model path
block_size=block_size,
max_num_batched_tokens=max_total_q,
max_model_len=max_model_len,
mla_dims=mla_dims, # Use custom dims from config or default
index_topk=index_topk if is_sparse else None,
prefill_backend=prefill_backend,
kv_cache_dtype=kv_cache_dtype,
sparse_mla_force_mqa=sparse_mla_force_mqa,
)
results = []
# Initialize workspace manager (needed by metadata builders)
from vllm.v1.worker.workspace import (
init_workspace_manager,
is_workspace_manager_initialized,
)
if not is_workspace_manager_initialized():
init_workspace_manager(device)
with set_current_vllm_config(vllm_config):
_ensure_single_rank_model_parallel()
# Create backend impl, layer, builder, and indexer (reused across benchmarks)
impl, layer, builder_instance, indexer = _create_backend_impl(
backend_cfg,
@@ -1179,20 +1040,9 @@ def _run_mla_benchmark_batched(
for config, threshold, num_splits in configs_with_params:
# Set threshold for this benchmark (FlashAttn/FlashMLA only)
original_threshold = None
effective_threshold = threshold
force_dense_mha = (
is_sparse
and getattr(config, "sparse_mla_mha_mode", "auto") == "dense"
and not getattr(config, "sparse_mla_force_mqa", False)
)
if force_dense_mha:
# Sparse MLA normally treats q_len <= 1 as decode. Use an
# impossible threshold so dense_mha benchmarks actually run
# the prefill/MHA path, including q_len=1 short extends.
effective_threshold = -1
if effective_threshold is not None and builder_instance:
if threshold is not None and builder_instance:
original_threshold = builder_instance.reorder_batch_threshold
builder_instance.reorder_batch_threshold = effective_threshold
builder_instance.reorder_batch_threshold = threshold
# Set num_splits for CUTLASS
original_num_splits = None
@@ -1240,7 +1090,6 @@ def run_mla_benchmark(
num_kv_splits: int | None = None,
index_topk: int = 2048,
prefill_backend: str | None = None,
sparse_mla_force_mqa: bool = False,
output_scale: float | None = None,
fuse_quant_op: bool = False,
) -> BenchmarkResult | list[BenchmarkResult]:
@@ -1262,8 +1111,6 @@ def run_mla_benchmark(
index_topk: Topk value for sparse MLA backends (default 2048)
prefill_backend: Prefill backend name (e.g., "fa3", "fa4").
When set, forces the specified FlashAttention version for prefill.
sparse_mla_force_mqa: If True, forces all sparse MLA tokens through
forward_mqa (even prefill tokens).
output_scale: Static per-tensor FP8 scale for prefill output (None = bf16).
fuse_quant_op: With output_scale set, fuse the FP8 write into the prefill
kernel vs a standalone post-quant kernel. See _run_single_benchmark.
@@ -1295,7 +1142,6 @@ def run_mla_benchmark(
configs_with_params,
index_topk,
prefill_backend=prefill_backend,
sparse_mla_force_mqa=sparse_mla_force_mqa,
output_scale=output_scale,
fuse_quant_op=fuse_quant_op,
)
+2 -2
View File
@@ -12,7 +12,7 @@ from dataclasses import dataclass, field
import aiohttp
import huggingface_hub.constants
from tqdm.asyncio import tqdm
from transformers import AutoTokenizer, PythonBackend, TokenizersBackend
from transformers import AutoTokenizer, PreTrainedTokenizer, PreTrainedTokenizerFast
# NOTE(simon): do not import vLLM here so the benchmark script
# can run without vLLM installed.
@@ -609,7 +609,7 @@ def get_tokenizer(
tokenizer_mode: str = "auto",
trust_remote_code: bool = False,
**kwargs,
) -> PythonBackend | TokenizersBackend:
) -> PreTrainedTokenizer | PreTrainedTokenizerFast:
if pretrained_model_name_or_path is not None and not os.path.exists(
pretrained_model_name_or_path
):
+4 -3
View File
@@ -69,11 +69,12 @@ def make_inputs(total_tokens, num_reqs, block_size):
# Output workspace
dst = torch.zeros(total_tokens, HEAD_DIM, dtype=torch.bfloat16, device="cuda")
seq_lens_t = torch.tensor(seq_lens, dtype=torch.int32, device="cuda")
workspace_starts_t = torch.tensor(
workspace_starts, dtype=torch.int32, device="cuda"
)
return cache, dst, block_table, workspace_starts_t
return cache, dst, block_table, seq_lens_t, workspace_starts_t
def bench_scenario(label, num_reqs, total_tokens_list, save_path):
@@ -93,7 +94,7 @@ def bench_scenario(label, num_reqs, total_tokens_list, save_path):
)
)
def bench_fn(total_tokens, provider, num_reqs):
cache, dst, block_table, ws_starts = make_inputs(
cache, dst, block_table, seq_lens_t, ws_starts = make_inputs(
total_tokens, num_reqs, BLOCK_SIZE
)
@@ -101,7 +102,7 @@ def bench_scenario(label, num_reqs, total_tokens_list, save_path):
ms, min_ms, max_ms = triton.testing.do_bench_cudagraph(
lambda: ops.cp_gather_and_upconvert_fp8_kv_cache(
cache, dst, block_table, ws_starts, num_reqs
cache, dst, block_table, seq_lens_t, ws_starts, num_reqs
),
quantiles=quantiles,
rep=500,
@@ -17,7 +17,7 @@ from vllm.model_executor.layers.fused_moe.fused_flydsl_moe import fused_flydsl_m
from vllm.model_executor.layers.quantization.compressed_tensors.compressed_tensors_moe import ( # noqa: E501
compressed_tensors_moe_w4a16_flydsl,
)
from vllm.utils.platform_utils import get_device_name_as_file_name
from vllm.platforms import current_platform
RoutingBuffers = tuple[
torch.Tensor, # sorted_token_ids
@@ -259,7 +259,7 @@ def tune_flydsl_moe_w4a16(
)
us_best = us
tuned_config[str(num_tokens)] = tile_config
device_name = get_device_name_as_file_name()
device_name = current_platform.get_device_name().replace(" ", "_")
tuned_config_file_name = (
f"E={num_experts},N={inter_dim},device_name={device_name},"
f"dtype=int4_w4a16,backend=flydsl.json"
@@ -80,17 +80,13 @@ _FI_MAX_SIZES = {
2: 64 * MiB, # 64MB
4: 64 * MiB, # 64MB
8: 64 * MiB, # 64MB
16: 64 * MiB, # 64MB (multi-node)
}
# Global workspace tensors for FlashInfer (keyed by backend name)
_FI_WORKSPACES: dict = {}
# Backends to benchmark. trtllm is single-node only and can hang cross-node, so
# multi-node sweeps can restrict to mnnvl via FI_BACKENDS=mnnvl.
FLASHINFER_BACKENDS = [
b for b in os.environ.get("FI_BACKENDS", "trtllm,mnnvl").split(",") if b
]
# Backends to benchmark
FLASHINFER_BACKENDS = ["trtllm", "mnnvl"]
def setup_flashinfer_workspace(
@@ -999,10 +995,7 @@ def main():
rank = int(os.environ["RANK"])
world_size = int(os.environ["WORLD_SIZE"])
# Use LOCAL_RANK for the device so multi-node runs (global rank >= GPUs per
# node) map to a valid local GPU; falls back to global rank single-node.
local_rank = int(os.environ.get("LOCAL_RANK", rank))
device = torch.device(f"cuda:{local_rank}")
device = torch.device(f"cuda:{rank}")
torch.accelerator.set_device_index(device)
torch.set_default_device(device)

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