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Author SHA1 Message Date
khluuandClaude Opus 4.6 f478d42cdb [CI] Reorganize release pipeline: separate nightly vs release sections
Reorder the pipeline into clear sections for readability:

1. Build Python Wheels (always runs)
2. ROCm Wheel Pipeline (always runs)
3. Nightly Docker Images (NIGHTLY=1 only) - CUDA/Ubuntu builds,
   multi-arch manifests, DockerHub publish, ROCm image + publish
4. Release (manual) - version input, PyPI upload, CPU image builds,
   ROCm root index

Key changes:
- Extract CPU image builds (manual/blocked) from nightly-gated group
  into their own "Build release CPU Docker images" group so they remain
  available for actual releases without NIGHTLY=1
- Move ROCm wheel jobs (1-4) up next to CUDA wheel builds
- Remove redundant per-step NIGHTLY gates inside already-gated groups
- Rename groups: "Build release Docker images" -> "Build nightly Docker
  images", "Publish release images" -> "Publish nightly images"

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-15 01:08:39 -07:00
khluuandClaude Opus 4.6 1a811d5747 [CI] Only build release Docker images when NIGHTLY=1
Gate the "Build release Docker images" group, "Publish release images"
group, and ROCm release image build behind NIGHTLY=1 to avoid expensive
image builds on every commit in the release pipeline.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-15 01:01:03 -07:00
2582 changed files with 83748 additions and 343831 deletions
-1
View File
@@ -8,7 +8,6 @@ run_all_patterns:
- "CMakeLists.txt"
- "requirements/common.txt"
- "requirements/cuda.txt"
- "requirements/kv_connectors.txt"
- "requirements/build/cuda.txt"
- "requirements/test/cuda.txt"
- "setup.py"
-20
View File
@@ -17,26 +17,6 @@ steps:
--target test
--no-cache
--progress plain .
- |
docker run --rm --network=none --entrypoint /bin/bash "rocm/vllm-ci:${BUILDKITE_COMMIT}" -ec '
if [ ! -d /vllm-workspace ]; then echo Missing directory: /vllm-workspace >&2; exit 1; fi
if [ ! -d /vllm-workspace/tests ]; then echo Missing directory: /vllm-workspace/tests >&2; exit 1; fi
if [ ! -d /vllm-workspace/src/vllm ]; then echo Missing directory: /vllm-workspace/src/vllm >&2; exit 1; fi
if [ ! -x /vllm-workspace/src/vllm/vllm-rs ]; then echo Missing executable: /vllm-workspace/src/vllm/vllm-rs >&2; exit 1; fi
command -v python3
command -v uv
command -v pytest
if ! command -v amd-smi >/dev/null 2>&1 && ! command -v rocminfo >/dev/null 2>&1; then
echo No ROCm CLI found in image >&2
exit 1
fi
python3 - <<PY
import torch, vllm
print(torch.__version__)
print(vllm.__version__)
PY
echo AMD image smoke OK
'
- docker push "rocm/vllm-ci:${BUILDKITE_COMMIT}"
env:
DOCKER_BUILDKIT: "1"
+12 -48
View File
@@ -12,21 +12,15 @@ steps:
- vllm/_custom_ops.py
- tests/kernels/attention/test_cpu_attn.py
- tests/kernels/moe/test_cpu_fused_moe.py
- tests/kernels/moe/test_cpu_quant_fused_moe.py
- tests/kernels/test_onednn.py
- 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
commands:
- |
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 30m "
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 20m "
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/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/test_awq_int4_to_int8.py"
- label: CPU-Compatibility Tests
depends_on: []
@@ -52,53 +46,34 @@ steps:
- tests/models/language/pooling/
commands:
- |
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 40m "
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 30m "
pytest -x -v -s tests/models/language/generation -m cpu_model
pytest -x -v -s tests/models/language/pooling -m cpu_model"
- label: CPU-ModelRunnerV2 Tests
depends_on: []
device: intel_cpu
no_plugin: true
soft_fail: true
source_file_dependencies:
- vllm/v1/worker/cpu/
- vllm/v1/worker/gpu/
- vllm/v1/sample/ops/topk_topp_triton.py
- vllm/v1/sample/ops/topk_topp_sampler.py
- tests/v1/sample/test_topk_topp_sampler.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"
- label: CPU-Quantization Model Tests
depends_on: []
device: intel_cpu
no_plugin: true
source_file_dependencies:
- csrc/cpu/
- vllm/model_executor/layers/quantization/auto_gptq.py
- vllm/model_executor/layers/quantization/cpu_wna16.py
- vllm/model_executor/layers/quantization/gptq_marlin.py
- vllm/model_executor/layers/quantization/compressed_tensors/schemes/compressed_tensors_w8a8_int8.py
- vllm/model_executor/kernels/linear/mixed_precision/cpu.py
- vllm/model_executor/kernels/linear/scaled_mm/cpu.py
- vllm/model_executor/layers/fused_moe/experts/cpu_moe.py
- vllm/model_executor/layers/quantization/kernels/scaled_mm/cpu.py
- vllm/model_executor/layers/quantization/kernels/mixed_precision/cpu.py
- tests/quantization/test_compressed_tensors.py
- tests/quantization/test_cpu_wna16.py
commands:
- |
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 30m "
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 20m "
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"
- label: CPU-Distributed Tests (PP+TP)
- label: CPU-Distributed Tests
depends_on: []
device: intel_cpu
no_plugin: true
source_file_dependencies: &cpu_distributed_deps
source_file_dependencies:
- csrc/cpu/shm.cpp
- vllm/v1/worker/cpu_worker.py
- vllm/v1/worker/gpu_worker.py
@@ -107,21 +82,10 @@ steps:
- vllm/platforms/cpu.py
- vllm/distributed/parallel_state.py
- vllm/distributed/device_communicators/cpu_communicator.py
- .buildkite/scripts/hardware_ci/run-cpu-distributed-smoke-test.sh
commands:
- |
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 10m "
bash .buildkite/scripts/hardware_ci/run-cpu-distributed-smoke-test.sh tp_pp"
- label: CPU-Distributed Tests (DP+TP)
depends_on: []
device: intel_cpu
no_plugin: true
source_file_dependencies: *cpu_distributed_deps
commands:
- |
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 10m "
bash .buildkite/scripts/hardware_ci/run-cpu-distributed-smoke-test.sh dp_tp"
bash .buildkite/scripts/hardware_ci/run-cpu-distributed-smoke-test.sh"
- label: CPU-Multi-Modal Model Tests %N
depends_on: []
@@ -135,7 +99,7 @@ steps:
- |
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 -m cpu_model --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB"
parallelism: 3
parallelism: 2
- label: "Arm CPU Test"
depends_on: []
+7
View File
@@ -8,3 +8,10 @@ steps:
commands:
- bash .buildkite/scripts/hardware_ci/run-hpu-test.sh
- label: "Intel GPU Test"
depends_on: []
soft_fail: true
device: intel_gpu
no_plugin: true
commands:
- bash .buildkite/scripts/hardware_ci/run-xpu-test.sh
+2 -3
View File
@@ -92,8 +92,8 @@ check_and_skip_if_image_exists() {
}
ecr_login() {
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY" || true
aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin 936637512419.dkr.ecr.us-east-1.amazonaws.com || true
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY"
aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin 936637512419.dkr.ecr.us-east-1.amazonaws.com
}
prepare_cache_tags() {
@@ -192,7 +192,6 @@ export BUILDKITE_COMMIT
export PARENT_COMMIT
export IMAGE_TAG
export IMAGE_TAG_LATEST
export COMMIT="${COMMIT:-${BUILDKITE_COMMIT}}"
export CACHE_FROM
export CACHE_FROM_BASE_BRANCH
export CACHE_FROM_MAIN
-72
View File
@@ -13,60 +13,6 @@ steps:
- exit_status: -10 # Agent was lost
limit: 2
- label: ":docker: :smoking: Non-root smoke tests"
key: image-build-smoke-test
depends_on:
- image-build
commands:
# Smoke 1: the default (root) image must still be importable
# under a non-root UID via `--user 2000:0`. Validates the `vllm` passwd
# entry + group-0-writable /home/vllm + uv path cleanup from #31959.
# Uses `import vllm` rather than `vllm serve --help` because the latter
# instantiates `VllmConfig` which requires a GPU attached to the
# container.
- docker run --rm --user 2000:0 --entrypoint python3 "$IMAGE_TAG" -c "import vllm; print(vllm.__version__)"
# Smoke 2: assert the non-root enabling invariants are baked
# into the image. Runs as UID 2000:0 via a shell so we can verify
# filesystem perms + passwd/group file state + wrapper presence without
# triggering vLLM's GPU-requiring config-init path. The opt-in
# `vllm-openai-nonroot` target adds only `USER vllm`, `WORKDIR
# /home/vllm`, and an `ENTRYPOINT` override on top of these invariants;
# its build correctness is reviewed at the Dockerfile level. Wrapper
# logic is covered separately by the pre-commit hook
# `test-nonroot-entrypoint` (see .pre-commit-config.yaml).
- |
docker run --rm --user 2000:0 --entrypoint /bin/sh "$IMAGE_TAG" -ec '
if ! getent passwd 2000 | grep -q ^vllm:; then
echo FAIL: UID 2000 != vllm
exit 1
fi
if ! id -gn 2>/dev/null | grep -qx root; then
echo FAIL: GID 0 not root group
exit 1
fi
touch /home/vllm/.smoke && rm /home/vllm/.smoke
touch /opt/uv/cache/.smoke && rm /opt/uv/cache/.smoke
if ! test -x /usr/local/bin/vllm-nonroot-entrypoint.sh; then
echo FAIL: wrapper missing
exit 1
fi
if ! test -w /etc/passwd; then
echo FAIL: /etc/passwd not group-writable
exit 1
fi
if ! test -w /etc/group; then
echo FAIL: /etc/group not group-writable
exit 1
fi
echo non-root invariants OK
'
retry:
automatic:
- exit_status: -1 # Agent was lost
limit: 2
- exit_status: -10 # Agent was lost
limit: 2
- label: ":docker: Build CPU image"
key: image-build-cpu
depends_on: []
@@ -110,21 +56,3 @@ steps:
limit: 2
- exit_status: -10 # Agent was lost
limit: 2
- label: ":docker: Build arm64 image"
key: arm64-image-build
depends_on: []
source_file_dependencies:
- ".buildkite/image_build/image_build.yaml"
- ".buildkite/image_build/image_build_arm64.sh"
- "docker/Dockerfile"
commands:
- .buildkite/image_build/image_build_arm64.sh $REGISTRY $REPO $BUILDKITE_COMMIT
env:
DOCKER_BUILDKIT: "1"
retry:
automatic:
- exit_status: -1 # Agent was lost
limit: 2
- exit_status: -10 # Agent was lost
limit: 2
@@ -1,37 +0,0 @@
#!/bin/bash
set -e
if [[ $# -lt 3 ]]; then
echo "Usage: $0 <registry> <repo> <commit>"
exit 1
fi
REGISTRY=$1
REPO=$2
BUILDKITE_COMMIT=$3
# authenticate with AWS ECR
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY" || true
# skip build if image already exists
if [[ -z $(docker manifest inspect "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-arm64) ]]; then
echo "Image not found, proceeding with build..."
else
echo "Image found"
exit 0
fi
# 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
+1 -1
View File
@@ -11,7 +11,7 @@ REPO=$2
BUILDKITE_COMMIT=$3
# authenticate with AWS ECR
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY" || true
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY"
# skip build if image already exists
if [[ -z $(docker manifest inspect "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-cpu) ]]; then
@@ -11,7 +11,7 @@ REPO=$2
BUILDKITE_COMMIT=$3
# authenticate with AWS ECR
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY" || true
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY"
# skip build if image already exists
if [[ -z $(docker manifest inspect "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-arm64-cpu) ]]; then
+1 -1
View File
@@ -11,7 +11,7 @@ REPO=$2
BUILDKITE_COMMIT=$3
# authenticate with AWS ECR
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY" || true
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY"
# skip build if image already exists
if [[ -z $(docker manifest inspect "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-hpu) ]]; then
@@ -46,7 +46,7 @@ echo "Image not found, proceeding with build..."
# --- CUDA 13.0 for nightly builds ---
# Nightly CI uses CUDA 13.0 while regular CI stays on CUDA 12.9
NIGHTLY_CUDA_VERSION="13.0.2"
NIGHTLY_CUDA_VERSION="13.0.0"
NIGHTLY_BUILD_BASE_IMAGE="nvidia/cuda:${NIGHTLY_CUDA_VERSION}-devel-ubuntu22.04"
NIGHTLY_FINAL_BASE_IMAGE="nvidia/cuda:${NIGHTLY_CUDA_VERSION}-base-ubuntu22.04"
+2 -2
View File
@@ -11,8 +11,8 @@ REPO=$2
BUILDKITE_COMMIT=$3
# authenticate with AWS ECR
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$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
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY"
aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin 936637512419.dkr.ecr.us-east-1.amazonaws.com
# skip build if image already exists
if ! docker manifest inspect "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-xpu &> /dev/null; then
-21
View File
@@ -1,21 +0,0 @@
group: Engine Intel
depends_on:
- image-build-xpu
steps:
- label: Engine (1 GPU)
timeout_in_minutes: 30
device: intel_gpu
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/v1/engine/
- tests/v1/engine/
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
pytest -v -s v1/engine --ignore v1/engine/test_preprocess_error_handling.py'
-21
View File
@@ -1,21 +0,0 @@
group: Kernels Intel
depends_on:
- image-build-xpu
steps:
- label: vLLM IR Tests
timeout_in_minutes: 30
device: intel_gpu
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/ir
- vllm/kernels
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
pytest -v -s kernels/ir'
-135
View File
@@ -1,135 +0,0 @@
group: LoRA Intel
depends_on:
- image-build-xpu
steps:
- label: LoRA Runtime + Utils
timeout_in_minutes: 45
device: intel_gpu
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/lora
- tests/lora
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
pytest -v -s lora/test_layers.py &&
pytest -v -s lora/test_lora_checkpoints.py &&
pytest -v -s lora/test_lora_functions.py &&
pytest -v -s lora/test_lora_huggingface.py &&
pytest -v -s lora/test_lora_manager.py &&
pytest -v -s lora/test_lora_utils.py &&
pytest -v -s lora/test_peft_helper.py &&
pytest -v -s lora/test_resolver.py &&
pytest -v -s lora/test_utils.py &&
pytest -v -s lora/test_add_lora.py &&
pytest -v -s lora/test_worker.py'
- label: LoRA Fused/MoE Kernels
timeout_in_minutes: 45
device: intel_gpu
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/lora
- tests/lora
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
pytest -v -s lora/test_fused_moe_lora_kernel.py &&
pytest -v -s lora/test_moe_lora_align_sum.py --deselect="tests/lora/test_moe_lora_align_sum.py::test_moe_lora_align_block_size_mixed_base_and_lora[1]"'
- label: LoRA Punica Kernels
timeout_in_minutes: 45
device: intel_gpu
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/lora
- tests/lora
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
set -o pipefail &&
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: 45
device: intel_gpu
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/lora
- tests/lora
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
pytest -v -s lora/test_punica_ops_fp8.py &&
pytest -v -s lora/test_punica_xpu_ops.py'
- label: LoRA Models
timeout_in_minutes: 45
device: intel_gpu
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/lora
- tests/lora
commands:
- >-
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 -s -v lora/test_minicpmv_tp.py'
- label: LoRA Multimodal
timeout_in_minutes: 45
device: intel_gpu
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/lora
- tests/lora
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
pytest -v -s lora/test_default_mm_loras.py &&
pytest -v -s lora/test_whisper.py'
-55
View File
@@ -1,55 +0,0 @@
group: Miscellaneous Intel
depends_on:
- image-build-xpu
steps:
- label: V1 Core + KV + Metrics
timeout_in_minutes: 30
device: intel_gpu
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/v1/core
- tests/v1/executor
- tests/v1/kv_offload
- tests/v1/worker
- tests/v1/kv_connector/unit
- tests/v1/metrics
- tests/entrypoints/openai/correctness/test_lmeval.py
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'pip install -r requirements/kv_connectors.txt &&
export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
cd tests &&
pytest -v -s v1/executor'
- label: V1 Sample + Logits
timeout_in_minutes: 30
device: intel_gpu
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/v1/sample
- tests/v1/logits_processors
- tests/v1/test_oracle.py
- tests/v1/test_request.py
- tests/v1/test_outputs.py
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
cd tests &&
pytest -v -s v1/logits_processors --ignore=v1/logits_processors/test_custom_online.py --ignore=v1/logits_processors/test_custom_offline.py &&
pytest -v -s v1/test_oracle.py &&
pytest -v -s v1/test_request.py &&
pytest -v -s v1/test_outputs.py'
+3 -25
View File
@@ -36,12 +36,9 @@ steps:
python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager --attention-backend=TRITON_ATTN &&
python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager --quantization fp8 &&
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 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
'
python3 examples/basic/offline_inference/generate.py --model ibm-research/PowerMoE-3b --block-size 64 --enforce-eager -tp 2 --enable-expert-parallel'
- label: "XPU V1 test"
depends_on:
- image-build-xpu
@@ -64,24 +61,5 @@ steps:
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/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'
- label: "XPU server test"
depends_on:
- image-build-xpu
timeout_in_minutes: 30
device: intel_gpu
no_plugin: true
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
source_file_dependencies:
- vllm/
- .buildkite/intel_jobs/test-intel.yaml
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'pip install av &&
cd tests &&
pytest -v -s entrypoints/openai/chat_completion/test_audio_in_video.py &&
pytest -v -s benchmarks/test_serve_cli.py'
pytest -v -s v1/spec_decode --ignore=v1/spec_decode/test_max_len.py --ignore=v1/spec_decode/test_tree_attention.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'
@@ -2,7 +2,7 @@
# We can use this script to compute baseline accuracy on chartqa for vllm.
#
# Make sure you have lm-eval-harness installed:
# pip install "lm-eval[api]>=0.4.12"
# pip install "lm-eval[api]>=0.4.11"
usage() {
echo``
@@ -2,7 +2,7 @@
# We can use this script to compute baseline accuracy on GSM for transformers.
#
# Make sure you have lm-eval-harness installed:
# pip install "lm-eval[api]>=0.4.12"
# pip install "lm-eval[api]>=0.4.11"
usage() {
echo``
@@ -3,7 +3,7 @@
# We use this for fp8, which HF does not support.
#
# Make sure you have lm-eval-harness installed:
# pip install "lm-eval[api]>=0.4.12"
# pip install "lm-eval[api]>=0.4.11"
usage() {
echo``
@@ -3,7 +3,7 @@
# We use this for fp8, which HF does not support.
#
# Make sure you have lm-eval-harness installed:
# pip install "lm-eval[api]>=0.4.12"
# pip install "lm-eval[api]>=0.4.11"
usage() {
echo``
@@ -31,9 +31,30 @@
}
},
"tests": [
{
"test_name": "serving_llama8B_tp1_sharegpt",
"server_parameters": {
"tensor_parallel_size": 1
},
"client_parameters": {
"dataset_name": "sharegpt",
"dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json"
}
},
{
"test_name": "serving_llama8B_tp2_sharegpt",
"server_parameters": {
"tensor_parallel_size": 2
},
"client_parameters": {
"dataset_name": "sharegpt",
"dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json"
}
},
{
"test_name": "serving_llama8B_tp1_random_128_128",
"server_parameters": {
"tensor_parallel_size": 1
},
"client_parameters": {
"dataset_name": "random",
@@ -41,10 +62,158 @@
"random-output-len": 128
}
},
{
"test_name": "serving_llama8B_tp2_random_128_128",
"server_parameters": {
"tensor_parallel_size": 2
},
"client_parameters": {
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 128
}
},
{
"test_name": "serving_llama8B_tp4_random_128_128",
"server_parameters": {
"tensor_parallel_size": 4
},
"client_parameters": {
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 128
}
},
{
"test_name": "serving_llama8B_tp1_random_128_2048",
"server_parameters": {
"tensor_parallel_size": 1
},
"client_parameters": {
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 2048
}
},
{
"test_name": "serving_llama8B_tp2_random_128_2048",
"server_parameters": {
"tensor_parallel_size": 2
},
"client_parameters": {
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 2048
}
},
{
"test_name": "serving_llama8B_tp4_random_128_2048",
"server_parameters": {
"tensor_parallel_size": 4
},
"client_parameters": {
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 2048
}
},
{
"test_name": "serving_llama8B_tp1_random_2048_128",
"server_parameters": {
"tensor_parallel_size": 1
},
"client_parameters": {
"dataset_name": "random",
"random-input-len": 2048,
"random-output-len": 128
}
},
{
"test_name": "serving_llama8B_tp2_random_2048_128",
"server_parameters": {
"tensor_parallel_size": 2
},
"client_parameters": {
"dataset_name": "random",
"random-input-len": 2048,
"random-output-len": 128
}
},
{
"test_name": "serving_llama8B_tp4_random_2048_128",
"server_parameters": {
"tensor_parallel_size": 4
},
"client_parameters": {
"dataset_name": "random",
"random-input-len": 2048,
"random-output-len": 128
}
},
{
"test_name": "serving_llama8B_tp1_random_2048_2048",
"server_parameters": {
"tensor_parallel_size": 1
},
"client_parameters": {
"dataset_name": "random",
"random-input-len": 2048,
"random-output-len": 2048
}
},
{
"test_name": "serving_llama8B_tp2_random_2048_2048",
"server_parameters": {
"tensor_parallel_size": 2
},
"client_parameters": {
"dataset_name": "random",
"random-input-len": 2048,
"random-output-len": 2048
}
},
{
"test_name": "serving_llama8B_tp4_random_2048_2048",
"server_parameters": {
"tensor_parallel_size": 4
},
"client_parameters": {
"dataset_name": "random",
"random-input-len": 2048,
"random-output-len": 2048
}
},
{
"test_name": "serving_llama8B_int4_tp1_random_128_128",
"server_parameters": {
"model": "hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4"
"model": "hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4",
"tensor_parallel_size": 1
},
"client_parameters": {
"model": "hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4",
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 128
}
},
{
"test_name": "serving_llama8B_int4_tp2_random_128_128",
"server_parameters": {
"model": "hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4",
"tensor_parallel_size": 2
},
"client_parameters": {
"model": "hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4",
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 128
}
},
{
"test_name": "serving_llama8B_int4_tp4_random_128_128",
"server_parameters": {
"model": "hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4",
"tensor_parallel_size": 4
},
"client_parameters": {
"model": "hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4",
@@ -56,7 +225,8 @@
{
"test_name": "serving_llama8B_int8_tp1_random_128_128",
"server_parameters": {
"model": "RedHatAI/Meta-Llama-3.1-8B-Instruct-quantized.w8a8"
"model": "RedHatAI/Meta-Llama-3.1-8B-Instruct-quantized.w8a8",
"tensor_parallel_size": 1
},
"client_parameters": {
"model": "RedHatAI/Meta-Llama-3.1-8B-Instruct-quantized.w8a8",
@@ -66,12 +236,26 @@
}
},
{
"test_name": "serving_llama1B_tp1_random_128_128",
"test_name": "serving_llama8B_int8_tp2_random_128_128",
"server_parameters": {
"model": "meta-llama/Llama-3.2-1B"
"model": "RedHatAI/Meta-Llama-3.1-8B-Instruct-quantized.w8a8",
"tensor_parallel_size": 2
},
"client_parameters": {
"model": "meta-llama/Llama-3.2-1B",
"model": "RedHatAI/Meta-Llama-3.1-8B-Instruct-quantized.w8a8",
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 128
}
},
{
"test_name": "serving_llama8B_int8_tp4_random_128_128",
"server_parameters": {
"model": "RedHatAI/Meta-Llama-3.1-8B-Instruct-quantized.w8a8",
"tensor_parallel_size": 4
},
"client_parameters": {
"model": "RedHatAI/Meta-Llama-3.1-8B-Instruct-quantized.w8a8",
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 128
@@ -80,7 +264,8 @@
{
"test_name": "serving_llama3B_tp1_random_128_128",
"server_parameters": {
"model": "meta-llama/Llama-3.2-3B-Instruct"
"model": "meta-llama/Llama-3.2-3B-Instruct",
"tensor_parallel_size": 1
},
"client_parameters": {
"model": "meta-llama/Llama-3.2-3B-Instruct",
@@ -89,22 +274,11 @@
"random-output-len": 128
}
},
{
"test_name": "serving_llama70B_tp1_random_128_128",
"server_parameters": {
"model": "meta-llama/Llama-3.3-70B-Instruct"
},
"client_parameters": {
"model": "meta-llama/Llama-3.3-70B-Instruct",
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 128
}
},
{
"test_name": "serving_granite2B_tp1_random_128_128",
"server_parameters": {
"model": "ibm-granite/granite-3.2-2b-instruct"
"model": "ibm-granite/granite-3.2-2b-instruct",
"tensor_parallel_size": 1
},
"client_parameters": {
"model": "ibm-granite/granite-3.2-2b-instruct",
@@ -116,7 +290,8 @@
{
"test_name": "serving_qwen1.7B_tp1_random_128_128",
"server_parameters": {
"model": "Qwen/Qwen3-1.7B"
"model": "Qwen/Qwen3-1.7B",
"tensor_parallel_size": 1
},
"client_parameters": {
"model": "Qwen/Qwen3-1.7B",
@@ -128,7 +303,8 @@
{
"test_name": "serving_qwen4B_tp1_random_128_128",
"server_parameters": {
"model": "Qwen/Qwen3-4B"
"model": "Qwen/Qwen3-4B",
"tensor_parallel_size": 1
},
"client_parameters": {
"model": "Qwen/Qwen3-4B",
@@ -140,7 +316,8 @@
{
"test_name": "serving_qwen8B_tp1_random_128_128",
"server_parameters": {
"model": "Qwen/Qwen3-8B"
"model": "Qwen/Qwen3-8B",
"tensor_parallel_size": 1
},
"client_parameters": {
"model": "Qwen/Qwen3-8B",
@@ -149,34 +326,11 @@
"random-output-len": 128
}
},
{
"test_name": "serving_qwen14B_tp1_random_128_128",
"server_parameters": {
"model": "Qwen/Qwen3-14B"
},
"client_parameters": {
"model": "Qwen/Qwen3-14B",
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 128
}
},
{
"test_name": "serving_qwen30B_tp1_random_128_128",
"server_parameters": {
"model": "Qwen/Qwen3-30B-A3B"
},
"client_parameters": {
"model": "Qwen/Qwen3-30B-A3B",
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 128
}
},
{
"test_name": "serving_glm9B_tp1_random_128_128",
"server_parameters": {
"model": "zai-org/glm-4-9b-hf"
"model": "zai-org/glm-4-9b-hf",
"tensor_parallel_size": 1
},
"client_parameters": {
"model": "zai-org/glm-4-9b-hf",
@@ -188,7 +342,8 @@
{
"test_name": "serving_gemma7B_tp1_random_128_128",
"server_parameters": {
"model": "google/gemma-7b"
"model": "google/gemma-7b",
"tensor_parallel_size": 1
},
"client_parameters": {
"model": "google/gemma-7b",
@@ -196,94 +351,6 @@
"random-input-len": 128,
"random-output-len": 128
}
},
{
"test_name": "serving_gemma3-4b_tp1_random_128_128",
"server_environment_variables": {
"VLLM_CPU_SGL_KERNEL": 0
},
"server_parameters": {
"model": "google/gemma-3-4b-it"
},
"client_parameters": {
"model": "google/gemma-3-4b-it",
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 128
}
},
{
"test_name": "serving_gemma3-12b_tp1_random_128_128",
"server_environment_variables": {
"VLLM_CPU_SGL_KERNEL": 0
},
"server_parameters": {
"model": "google/gemma-3-12b-it"
},
"client_parameters": {
"model": "google/gemma-3-12b-it",
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 128
}
},
{
"test_name": "serving_gemma4-4b_tp1_random_128_128",
"server_environment_variables": {
"VLLM_CPU_SGL_KERNEL": 0
},
"server_parameters": {
"model": "google/gemma-4-E4B-it"
},
"client_parameters": {
"model": "google/gemma-4-E4B-it",
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 128
}
},
{
"test_name": "serving_gemma4-2b_tp1_random_128_128",
"server_environment_variables": {
"VLLM_CPU_SGL_KERNEL": 0
},
"server_parameters": {
"model": "google/gemma-4-E2B-it"
},
"client_parameters": {
"model": "google/gemma-4-E2B-it",
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 128
}
},
{
"test_name": "serving_gemma4-26b_tp1_random_128_128",
"server_environment_variables": {
"VLLM_CPU_SGL_KERNEL": 0,
"VLLM_CPU_ATTN_SPLIT_KV": 0
},
"server_parameters": {
"model": "google/gemma-4-26B-A4B-it"
},
"client_parameters": {
"model": "google/gemma-4-26B-A4B-it",
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 128
}
},
{
"test_name": "serving_phi4_tp1_random_128_128",
"server_parameters": {
"model": "microsoft/Phi-4-reasoning"
},
"client_parameters": {
"model": "microsoft/Phi-4-reasoning",
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 128
}
}
]
}
@@ -1,112 +1,77 @@
{
"defaults": {
"qps_list": [
"inf"
],
"max_concurrency_list": [12, 16, 24, 32, 64, 128, 200],
"server_parameters": {
"model": "meta-llama/Llama-3.1-8B-Instruct",
"tensor_parallel_size": 1,
"dtype": "bfloat16"
[
{
"test_name": "serving_llama8B_tp1_sharegpt",
"qps_list": [1, 4, 16, "inf"],
"server_parameters": {
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"tensor_parallel_size": 1,
"disable_log_stats": "",
"load_format": "dummy"
},
"client_parameters": {
"model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"backend": "vllm",
"dataset_name": "sharegpt",
"dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json",
"temperature": 0,
"num_prompts": 200
}
},
"client_parameters": {
"model": "meta-llama/Llama-3.1-8B-Instruct",
"backend": "vllm",
"ignore-eos": "",
"temperature": 0,
"num_prompts": 200
{
"test_name": "serving_llama70B_tp4_sharegpt",
"qps_list": [1, 4, 16, "inf"],
"server_parameters": {
"model": "meta-llama/Meta-Llama-3.1-70B-Instruct",
"tensor_parallel_size": 4,
"disable_log_stats": "",
"load_format": "dummy"
},
"client_parameters": {
"model": "meta-llama/Meta-Llama-3.1-70B-Instruct",
"backend": "vllm",
"dataset_name": "sharegpt",
"dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json",
"temperature": 0,
"num_prompts": 200
}
},
{
"test_name": "serving_mixtral8x7B_tp2_sharegpt",
"qps_list": [1, 4, 16, "inf"],
"server_parameters": {
"model": "mistralai/Mixtral-8x7B-Instruct-v0.1",
"tensor_parallel_size": 2,
"disable_log_stats": "",
"load_format": "dummy"
},
"client_parameters": {
"model": "mistralai/Mixtral-8x7B-Instruct-v0.1",
"backend": "vllm",
"dataset_name": "sharegpt",
"dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json",
"temperature": 0,
"num_prompts": 200
}
},
{
"test_name": "serving_llama70B_tp4_sharegpt_specdecode",
"qps_list": [2],
"server_parameters": {
"model": "meta-llama/Meta-Llama-3.1-70B-Instruct",
"tensor_parallel_size": 4,
"speculative_config": {
"model": "turboderp/Qwama-0.5B-Instruct",
"num_speculative_tokens": 4,
"draft_tensor_parallel_size": 1
}
},
"client_parameters": {
"model": "meta-llama/Meta-Llama-3.1-70B-Instruct",
"backend": "vllm",
"dataset_name": "sharegpt",
"dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json",
"temperature": 0,
"num_prompts": 200
}
}
},
"tests": [
{
"test_name": "serving_llama8B_tp1_sharegpt",
"server_parameters": {
"tensor_parallel_size": 1
},
"client_parameters": {
"dataset_name": "sharegpt",
"dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json"
}
},
{
"dataset_name": "sharegpt",
"dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json"
}
},
{
"test_name": "serving_llama8B_tp1_random_128_128",
"server_parameters": {
"tensor_parallel_size": 1
},
"client_parameters": {
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 128
}
},
{
"test_name": "serving_llama8B_tp1_random_128_2048",
"server_parameters": {
"tensor_parallel_size": 1
},
"client_parameters": {
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 2048
}
},
{
"test_name": "serving_llama8B_tp1_random_2048_128",
"server_parameters": {
"tensor_parallel_size": 1
},
"client_parameters": {
"dataset_name": "random",
"random-input-len": 2048,
"random-output-len": 128
}
},
{
"test_name": "serving_llama8B_tp1_random_2048_2048",
"server_parameters": {
"tensor_parallel_size": 1
},
"client_parameters": {
"dataset_name": "random",
"random-input-len": 2048,
"random-output-len": 2048
}
},
{
"test_name": "serving_llama70B_tp4_random_128_128",
"server_parameters": {
"model": "meta-llama/Llama-3.3-70B-Instruct",
"async_scheduling": "",
"no_enable_prefix_caching": "",
"max_num_batched_tokens": 8192
},
"client_parameters": {
"model": "meta-llama/Llama-3.3-70B-Instruct",
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 128
}
},
{
"test_name": "serving_gemma4-e4b_tp1_random_128_128",
"server_parameters": {
"model": "google/gemma-4-E4B-it",
"enable_auto_tool_choice": "",
"tool_call_parser": "gemma4",
"chat_template": "examples/tool_chat_template_gemma4.jinja",
"reasoning_parser": "gemma4"
},
"client_parameters": {
"model": "google/gemma-4-E4B-it",
"dataset_name": "random",
"random-input-len": 128,
"random-output-len": 128
}
}
]
}
]
+299 -481
View File
@@ -1,22 +1,7 @@
# CUDA architecture lists — following PyTorch RELEASE.md
# (https://github.com/pytorch/pytorch/blob/main/RELEASE.md)
# SM86 included for broader Ampere coverage; SM89 for marlin fp8 support
env:
CUDA_ARCH_X86: "7.5 8.0 8.6 8.9 9.0 10.0 12.0+PTX"
# aarch64 only architectures: 8.7 for Orin, 11.0 for Thor (since CUDA 13)
CUDA_ARCH_AARCH64: "8.0 8.7 8.9 9.0 10.0 11.0 12.0+PTX"
CUDA_ARCH_X86_CU129: "7.5 8.0 8.6 8.9 9.0 10.0 12.0"
CUDA_ARCH_AARCH64_CU129: "8.0 8.7 8.9 9.0 10.0 12.0"
MOONCAKE_WHEEL_AARCH64_2_35: "https://vllm-wheels.s3.amazonaws.com/mooncake/mooncake_transfer_engine-0.3.10.post2-0da9dfea3-cp312-cp312-manylinux_2_35_aarch64.whl"
MOONCAKE_WHEEL_AARCH64_2_39: "https://vllm-wheels.s3.amazonaws.com/mooncake/mooncake_transfer_engine-0.3.10.post2-0da9dfea3-cp312-cp312-manylinux_2_39_aarch64.whl"
MOONCAKE_WHEEL_X86_64: "https://vllm-wheels.s3.amazonaws.com/mooncake/mooncake_transfer_engine-0.3.10.post2-0da9dfea3-cp312-cp312-manylinux_2_35_x86_64.whl"
steps:
- input: "Provide Release version here"
id: input-release-version
fields:
- text: "What is the release version?"
key: release-version
# =============================================================================
# Build Python Wheels (runs on every pipeline trigger)
# =============================================================================
- group: "Build Python wheels"
key: "build-wheels"
@@ -27,11 +12,12 @@ steps:
agents:
queue: arm64_cpu_queue_release
commands:
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=12.9.1 --build-arg torch_cuda_arch_list=\"${CUDA_ARCH_AARCH64_CU129}\" --build-arg BUILD_OS=manylinux --build-arg BUILD_BASE_IMAGE=pytorch/manylinuxaarch64-builder:cuda12.9 --tag vllm-ci:build-image --target build --progress plain -f docker/Dockerfile ."
# #NOTE: torch_cuda_arch_list is derived from upstream PyTorch build files here:
# https://github.com/pytorch/pytorch/blob/main/.ci/aarch64_linux/aarch64_ci_build.sh#L7
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=12.9.1 --build-arg torch_cuda_arch_list='8.7 8.9 9.0 10.0+PTX 12.0' --tag vllm-ci:build-image --target build --progress plain -f docker/Dockerfile ."
- "mkdir artifacts"
- "docker run --rm -v $(pwd)/artifacts:/artifacts_host vllm-ci:build-image bash -c 'cp -r dist /artifacts_host && chmod -R a+rw /artifacts_host'"
- "bash .buildkite/scripts/upload-nightly-wheels.sh"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "s3://vllm-wheels/$$BUILDKITE_COMMIT/$(cd artifacts/dist && echo *.whl)"'
env:
DOCKER_BUILDKIT: "1"
@@ -41,11 +27,12 @@ steps:
agents:
queue: arm64_cpu_queue_release
commands:
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=13.0.2 --build-arg torch_cuda_arch_list=\"${CUDA_ARCH_AARCH64}\" --build-arg BUILD_OS=manylinux --build-arg BUILD_BASE_IMAGE=pytorch/manylinuxaarch64-builder:cuda13.0 --tag vllm-ci:build-image --target build --progress plain -f docker/Dockerfile ."
# #NOTE: torch_cuda_arch_list is derived from upstream PyTorch build files here:
# https://github.com/pytorch/pytorch/blob/main/.ci/aarch64_linux/aarch64_ci_build.sh#L7
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=13.0.1 --build-arg torch_cuda_arch_list='8.7 8.9 9.0 10.0+PTX 12.0' --build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.1-devel-ubuntu22.04 --tag vllm-ci:build-image --target build --progress plain -f docker/Dockerfile ."
- "mkdir artifacts"
- "docker run --rm -v $(pwd)/artifacts:/artifacts_host vllm-ci:build-image bash -c 'cp -r dist /artifacts_host && chmod -R a+rw /artifacts_host'"
- "bash .buildkite/scripts/upload-nightly-wheels.sh"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "s3://vllm-wheels/$$BUILDKITE_COMMIT/$(cd artifacts/dist && echo *.whl)"'
- "bash .buildkite/scripts/upload-nightly-wheels.sh manylinux_2_35"
env:
DOCKER_BUILDKIT: "1"
@@ -58,8 +45,7 @@ steps:
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg GIT_REPO_CHECK=1 --build-arg VLLM_BUILD_ACL=ON --tag vllm-ci:build-image --target vllm-build --progress plain -f docker/Dockerfile.cpu ."
- "mkdir artifacts"
- "docker run --rm -v $(pwd)/artifacts:/artifacts_host vllm-ci:build-image bash -c 'cp -r dist /artifacts_host && chmod -R a+rw /artifacts_host'"
- "bash .buildkite/scripts/upload-nightly-wheels.sh"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "s3://vllm-wheels/$$BUILDKITE_COMMIT/$(cd artifacts/dist && echo *.whl)"'
- "bash .buildkite/scripts/upload-nightly-wheels.sh manylinux_2_35"
env:
DOCKER_BUILDKIT: "1"
@@ -69,11 +55,10 @@ steps:
agents:
queue: cpu_queue_release
commands:
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=12.9.1 --build-arg torch_cuda_arch_list=\"${CUDA_ARCH_X86_CU129}\" --build-arg BUILD_OS=manylinux --build-arg BUILD_BASE_IMAGE=pytorch/manylinux2_28-builder:cuda12.9 --tag vllm-ci:build-image --target build --progress plain -f docker/Dockerfile ."
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=12.9.1 --tag vllm-ci:build-image --target build --progress plain -f docker/Dockerfile ."
- "mkdir artifacts"
- "docker run --rm -v $(pwd)/artifacts:/artifacts_host vllm-ci:build-image bash -c 'cp -r dist /artifacts_host && chmod -R a+rw /artifacts_host'"
- "bash .buildkite/scripts/upload-nightly-wheels.sh"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "s3://vllm-wheels/$$BUILDKITE_COMMIT/$(cd artifacts/dist && echo *.whl)"'
- "bash .buildkite/scripts/upload-nightly-wheels.sh manylinux_2_31"
env:
DOCKER_BUILDKIT: "1"
@@ -83,11 +68,10 @@ steps:
agents:
queue: cpu_queue_release
commands:
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=13.0.2 --build-arg torch_cuda_arch_list=\"${CUDA_ARCH_X86}\" --build-arg BUILD_OS=manylinux --build-arg BUILD_BASE_IMAGE=pytorch/manylinux2_28-builder:cuda13.0 --tag vllm-ci:build-image --target build --progress plain -f docker/Dockerfile ."
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=13.0.1 --build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.1-devel-ubuntu22.04 --tag vllm-ci:build-image --target build --progress plain -f docker/Dockerfile ."
- "mkdir artifacts"
- "docker run --rm -v $(pwd)/artifacts:/artifacts_host vllm-ci:build-image bash -c 'cp -r dist /artifacts_host && chmod -R a+rw /artifacts_host'"
- "bash .buildkite/scripts/upload-nightly-wheels.sh"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "s3://vllm-wheels/$$BUILDKITE_COMMIT/$(cd artifacts/dist && echo *.whl)"'
- "bash .buildkite/scripts/upload-nightly-wheels.sh manylinux_2_35"
env:
DOCKER_BUILDKIT: "1"
@@ -100,8 +84,7 @@ steps:
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg GIT_REPO_CHECK=1 --build-arg VLLM_CPU_X86=true --tag vllm-ci:build-image --target vllm-build --progress plain -f docker/Dockerfile.cpu ."
- "mkdir artifacts"
- "docker run --rm -v $(pwd)/artifacts:/artifacts_host vllm-ci:build-image bash -c 'cp -r dist /artifacts_host && chmod -R a+rw /artifacts_host'"
- "bash .buildkite/scripts/upload-nightly-wheels.sh"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "s3://vllm-wheels/$$BUILDKITE_COMMIT/$(cd artifacts/dist && echo *.whl)"'
- "bash .buildkite/scripts/upload-nightly-wheels.sh manylinux_2_35"
env:
DOCKER_BUILDKIT: "1"
@@ -113,372 +96,8 @@ steps:
commands:
- "bash .buildkite/scripts/generate-and-upload-nightly-index.sh"
- block: "Unblock to build release Docker images"
depends_on: ~
key: block-build-release-images
if: build.env("NIGHTLY") != "1"
- group: "Build release Docker images"
key: "build-release-images"
depends_on: block-build-release-images
allow_dependency_failure: true
steps:
- label: "Build release image - x86_64 - CUDA 13.0"
depends_on: ~
id: build-release-image-x86
agents:
queue: cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- |
DOCKER_BUILDKIT=1 docker build \
$(bash .buildkite/scripts/docker-build-metadata-args.sh) \
--build-arg max_jobs=16 \
--build-arg USE_SCCACHE=1 \
--build-arg GIT_REPO_CHECK=1 \
--build-arg CUDA_VERSION=13.0.2 \
--build-arg torch_cuda_arch_list="${CUDA_ARCH_X86}" \
--build-arg INSTALL_KV_CONNECTORS=true \
--build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_35}" \
--build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
--build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.2-devel-ubuntu22.04 \
--target vllm-openai \
--progress plain \
-f docker/Dockerfile .
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)"
# re-tag to default image tag and push, just in case arm64 build fails
- "docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m) public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT"
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)"'
- label: "Build release image - aarch64 - CUDA 13.0"
depends_on: ~
id: build-release-image-arm64
agents:
queue: arm64_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- |
DOCKER_BUILDKIT=1 docker build \
$(bash .buildkite/scripts/docker-build-metadata-args.sh) \
--build-arg max_jobs=16 \
--build-arg USE_SCCACHE=1 \
--build-arg GIT_REPO_CHECK=1 \
--build-arg CUDA_VERSION=13.0.2 \
--build-arg torch_cuda_arch_list="${CUDA_ARCH_AARCH64}" \
--build-arg INSTALL_KV_CONNECTORS=true \
--build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_35}" \
--build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
--build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.2-devel-ubuntu22.04 \
--target vllm-openai \
--progress plain \
-f docker/Dockerfile .
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)"'
- label: "Build release image - x86_64 - CUDA 12.9"
depends_on: ~
id: build-release-image-x86-cuda-12-9
agents:
queue: cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- |
DOCKER_BUILDKIT=1 docker build \
$(bash .buildkite/scripts/docker-build-metadata-args.sh cu129) \
--build-arg max_jobs=16 \
--build-arg USE_SCCACHE=1 \
--build-arg GIT_REPO_CHECK=1 \
--build-arg CUDA_VERSION=12.9.1 \
--build-arg torch_cuda_arch_list="${CUDA_ARCH_X86_CU129}" \
--build-arg INSTALL_KV_CONNECTORS=true \
--build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_35}" \
--build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
--target vllm-openai \
--progress plain \
-f docker/Dockerfile .
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129"
# re-tag to default image tag and push, just in case arm64 build fails
- "docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129"
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129"'
- label: "Build release image - aarch64 - CUDA 12.9"
depends_on: ~
id: build-release-image-arm64-cuda-12-9
agents:
queue: arm64_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- |
DOCKER_BUILDKIT=1 docker build \
$(bash .buildkite/scripts/docker-build-metadata-args.sh cu129) \
--build-arg max_jobs=16 \
--build-arg USE_SCCACHE=1 \
--build-arg GIT_REPO_CHECK=1 \
--build-arg CUDA_VERSION=12.9.1 \
--build-arg torch_cuda_arch_list="${CUDA_ARCH_AARCH64_CU129}" \
--build-arg INSTALL_KV_CONNECTORS=true \
--build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_35}" \
--build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
--target vllm-openai \
--progress plain \
-f docker/Dockerfile .
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129"'
- label: "Build release image - x86_64 - CUDA 13.0 - Ubuntu 24.04"
depends_on: ~
id: build-release-image-x86-ubuntu2404
agents:
queue: cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- |
DOCKER_BUILDKIT=1 docker build \
$(bash .buildkite/scripts/docker-build-metadata-args.sh ubuntu2404) \
--build-arg max_jobs=16 \
--build-arg USE_SCCACHE=1 \
--build-arg GIT_REPO_CHECK=1 \
--build-arg CUDA_VERSION=13.0.2 \
--build-arg UBUNTU_VERSION=24.04 \
--build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 \
--build-arg torch_cuda_arch_list="${CUDA_ARCH_X86}" \
--build-arg INSTALL_KV_CONNECTORS=true \
--build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_39}" \
--build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
--build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.2-devel-ubuntu24.04 \
--target vllm-openai \
--progress plain \
-f docker/Dockerfile .
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-ubuntu2404"
- "docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-ubuntu2404 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-ubuntu2404"
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-ubuntu2404"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-ubuntu2404"'
- label: "Build release image - aarch64 - CUDA 13.0 - Ubuntu 24.04"
depends_on: ~
id: build-release-image-arm64-ubuntu2404
agents:
queue: arm64_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- |
DOCKER_BUILDKIT=1 docker build \
$(bash .buildkite/scripts/docker-build-metadata-args.sh ubuntu2404) \
--build-arg max_jobs=16 \
--build-arg USE_SCCACHE=1 \
--build-arg GIT_REPO_CHECK=1 \
--build-arg CUDA_VERSION=13.0.2 \
--build-arg UBUNTU_VERSION=24.04 \
--build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 \
--build-arg torch_cuda_arch_list="${CUDA_ARCH_AARCH64}" \
--build-arg INSTALL_KV_CONNECTORS=true \
--build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_39}" \
--build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
--build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.2-devel-ubuntu24.04 \
--target vllm-openai \
--progress plain \
-f docker/Dockerfile .
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-ubuntu2404"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-ubuntu2404"'
- label: "Build release image - x86_64 - CUDA 12.9 - Ubuntu 24.04"
depends_on: ~
id: build-release-image-x86-cuda-12-9-ubuntu2404
agents:
queue: cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- |
DOCKER_BUILDKIT=1 docker build \
$(bash .buildkite/scripts/docker-build-metadata-args.sh cu129-ubuntu2404) \
--build-arg max_jobs=16 \
--build-arg USE_SCCACHE=1 \
--build-arg GIT_REPO_CHECK=1 \
--build-arg CUDA_VERSION=12.9.1 \
--build-arg UBUNTU_VERSION=24.04 \
--build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 \
--build-arg torch_cuda_arch_list="${CUDA_ARCH_X86_CU129}" \
--build-arg INSTALL_KV_CONNECTORS=true \
--build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_39}" \
--build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
--target vllm-openai \
--progress plain \
-f docker/Dockerfile .
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129-ubuntu2404"
- "docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129-ubuntu2404 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129-ubuntu2404"
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129-ubuntu2404"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129-ubuntu2404"'
- label: "Build release image - aarch64 - CUDA 12.9 - Ubuntu 24.04"
depends_on: ~
id: build-release-image-arm64-cuda-12-9-ubuntu2404
agents:
queue: arm64_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- |
DOCKER_BUILDKIT=1 docker build \
$(bash .buildkite/scripts/docker-build-metadata-args.sh cu129-ubuntu2404) \
--build-arg max_jobs=16 \
--build-arg USE_SCCACHE=1 \
--build-arg GIT_REPO_CHECK=1 \
--build-arg CUDA_VERSION=12.9.1 \
--build-arg UBUNTU_VERSION=24.04 \
--build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 \
--build-arg torch_cuda_arch_list="${CUDA_ARCH_AARCH64_CU129}" \
--build-arg INSTALL_KV_CONNECTORS=true \
--build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_39}" \
--build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
--target vllm-openai \
--progress plain \
-f docker/Dockerfile .
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129-ubuntu2404"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129-ubuntu2404"'
- block: "Build release image for x86_64 CPU"
key: block-cpu-release-image-build
depends_on: ~
- label: "Build release image - x86_64 - CPU"
key: build-cpu-release-image-x86
depends_on:
- block-cpu-release-image-build
- input-release-version
agents:
queue: cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg GIT_REPO_CHECK=1 --build-arg VLLM_CPU_X86=true --tag public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:$(buildkite-agent meta-data get release-version) --tag public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:latest --progress plain --target vllm-openai -f docker/Dockerfile.cpu ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:latest"
- "docker push public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:$(buildkite-agent meta-data get release-version)"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:$(buildkite-agent meta-data get release-version)"'
env:
DOCKER_BUILDKIT: "1"
- block: "Build release image for arm64 CPU"
key: block-arm64-cpu-release-image-build
depends_on: ~
- label: "Build release image - arm64 - CPU"
key: build-cpu-release-image-arm64
depends_on:
- block-arm64-cpu-release-image-build
- input-release-version
agents:
queue: arm64_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg GIT_REPO_CHECK=1 --tag public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:$(buildkite-agent meta-data get release-version) --tag public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:latest --progress plain --target vllm-openai -f docker/Dockerfile.cpu ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:latest"
- "docker push public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:$(buildkite-agent meta-data get release-version)"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:$(buildkite-agent meta-data get release-version)"'
env:
DOCKER_BUILDKIT: "1"
- group: "Publish release images"
key: "publish-release-images"
steps:
- label: "Create multi-arch manifest - CUDA 13.0"
depends_on:
- build-release-image-x86
- build-release-image-arm64
id: create-multi-arch-manifest
agents:
queue: small_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "docker manifest create public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-x86_64 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-aarch64 --amend"
- "docker manifest push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "Manifest: CUDA 13.0" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT"'
- label: "Create multi-arch manifest - CUDA 12.9"
depends_on:
- build-release-image-x86-cuda-12-9
- build-release-image-arm64-cuda-12-9
id: create-multi-arch-manifest-cuda-12-9
agents:
queue: small_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "docker manifest create public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-x86_64-cu129 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-aarch64-cu129 --amend"
- "docker manifest push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "Manifest: CUDA 12.9" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129"'
- label: "Create multi-arch manifest - CUDA 13.0 - Ubuntu 24.04"
depends_on:
- build-release-image-x86-ubuntu2404
- build-release-image-arm64-ubuntu2404
id: create-multi-arch-manifest-ubuntu2404
agents:
queue: small_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "docker manifest create public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-ubuntu2404 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-x86_64-ubuntu2404 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-aarch64-ubuntu2404 --amend"
- "docker manifest push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-ubuntu2404"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "Manifest: CUDA 13.0 Ubuntu 24.04" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-ubuntu2404"'
- label: "Create multi-arch manifest - CUDA 12.9 - Ubuntu 24.04"
depends_on:
- build-release-image-x86-cuda-12-9-ubuntu2404
- build-release-image-arm64-cuda-12-9-ubuntu2404
id: create-multi-arch-manifest-cuda-12-9-ubuntu2404
agents:
queue: small_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "docker manifest create public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129-ubuntu2404 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-x86_64-cu129-ubuntu2404 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-aarch64-cu129-ubuntu2404 --amend"
- "docker manifest push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129-ubuntu2404"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "Manifest: CUDA 12.9 Ubuntu 24.04" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129-ubuntu2404"'
- label: "Publish nightly multi-arch image to DockerHub"
depends_on:
- create-multi-arch-manifest
if: build.env("NIGHTLY") == "1"
agents:
queue: small_cpu_queue_release
commands:
- "bash .buildkite/scripts/push-nightly-builds.sh"
# Clean up old nightly builds (keep only last 14)
- "bash .buildkite/scripts/cleanup-nightly-builds.sh"
plugins:
- docker-login#v3.0.0:
username: vllmbot
password-env: DOCKERHUB_TOKEN
env:
DOCKER_BUILDKIT: "1"
DOCKERHUB_USERNAME: "vllmbot"
- label: "Publish nightly multi-arch image to DockerHub - CUDA 12.9"
depends_on:
- create-multi-arch-manifest-cuda-12-9
if: build.env("NIGHTLY") == "1"
agents:
queue: small_cpu_queue_release
commands:
- "bash .buildkite/scripts/push-nightly-builds.sh cu129"
# Clean up old nightly builds (keep only last 14)
- "bash .buildkite/scripts/cleanup-nightly-builds.sh cu129-nightly-"
plugins:
- docker-login#v3.0.0:
username: vllmbot
password-env: DOCKERHUB_TOKEN
env:
DOCKER_BUILDKIT: "1"
DOCKERHUB_USERNAME: "vllmbot"
# =============================================================================
# ROCm Release Pipeline (x86_64 only)
# =============================================================================
#
# vLLM version is determined by the Buildkite checkout (like CUDA pipeline).
# To build a specific version, trigger the build from that branch/tag.
#
# Environment variables for ROCm builds (set via Buildkite UI or schedule):
#
# Note: ROCm version is determined by BASE_IMAGE in docker/Dockerfile.rocm_base
#
# ROCm Wheel Pipeline (runs on every pipeline trigger)
# =============================================================================
# ROCm Job 1: Build ROCm Base Wheels (with S3 caching)
@@ -501,21 +120,21 @@ steps:
echo " CACHE_KEY: $${CACHE_KEY}"
echo " ECR_CACHE_TAG: $${ECR_CACHE_TAG}"
echo "========================================"
# Login to ECR
aws ecr-public get-login-password --region us-east-1 | \
docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7
IMAGE_EXISTS=false
WHEELS_EXIST=false
# Check ECR for Docker image
if docker manifest inspect "$${ECR_CACHE_TAG}" > /dev/null 2>&1; then
IMAGE_EXISTS=true
echo "ECR image cache HIT"
fi
# Check S3 for wheels
WHEEL_CACHE_STATUS=$(.buildkite/scripts/cache-rocm-base-wheels.sh check)
if [ "$${WHEEL_CACHE_STATUS}" = "hit" ]; then
@@ -523,7 +142,7 @@ steps:
echo "S3 wheels cache HIT"
fi
# Scenario 1: Both cached (best case)
if [ "$${IMAGE_EXISTS}" = "true" ] && [ "$${WHEELS_EXIST}" = "true" ]; then
echo ""
@@ -532,16 +151,16 @@ steps:
# Download wheels
.buildkite/scripts/cache-rocm-base-wheels.sh download
# Save ECR tag for downstream jobs
buildkite-agent meta-data set "rocm-base-image-tag" "$${ECR_CACHE_TAG}"
# Scenario 2: Full rebuild needed
else
echo ""
echo " CACHE MISS - Building from scratch..."
echo ""
# Build full base image and push to ECR
DOCKER_BUILDKIT=1 docker buildx build \
--file docker/Dockerfile.rocm_base \
@@ -552,7 +171,7 @@ steps:
--build-arg SCCACHE_S3_NO_CREDENTIALS=0 \
--push \
.
# Build wheel extraction stage
DOCKER_BUILDKIT=1 docker buildx build \
--file docker/Dockerfile.rocm_base \
@@ -564,20 +183,20 @@ steps:
--build-arg SCCACHE_S3_NO_CREDENTIALS=0 \
--load \
.
# Extract and upload wheels
mkdir -p artifacts/rocm-base-wheels
cid=$(docker create rocm-base-debs:$${BUILDKITE_BUILD_NUMBER})
docker cp $${cid}:/app/debs/. artifacts/rocm-base-wheels/
docker rm $${cid}
.buildkite/scripts/cache-rocm-base-wheels.sh upload
# Cache base docker image to ECR
docker push "$${ECR_CACHE_TAG}"
buildkite-agent meta-data set "rocm-base-image-tag" "$${ECR_CACHE_TAG}"
echo ""
echo " Build complete - Image and wheels cached"
fi
@@ -606,7 +225,7 @@ steps:
# This fixes version detection when tags are moved/force-pushed
echo "Fetching latest tags from origin..."
git fetch --tags --force origin
# Log tag information for debugging version detection
echo "========================================"
echo "Git Tag Verification"
@@ -632,18 +251,18 @@ steps:
echo "This should have been set by the build-rocm-base-wheels job"
exit 1
fi
echo "Pulling base Docker image from ECR: $${ECR_IMAGE_TAG}"
# Login to ECR
aws ecr-public get-login-password --region us-east-1 | \
docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7
# Pull base Docker image from ECR
docker pull "$${ECR_IMAGE_TAG}"
echo "Loaded base image: $${ECR_IMAGE_TAG}"
# Prepare base wheels for Docker build context
mkdir -p docker/context/base-wheels
touch docker/context/base-wheels/.keep
@@ -721,30 +340,205 @@ steps:
env:
S3_BUCKET: "vllm-wheels"
# ROCm Job 5: Generate Root Index for ROCm Wheels (for release only)
# This is the job to create https://wheels.vllm.ai/rocm/ index allowing
# users to install with `uv pip install vllm --extra-index-url https://wheels.vllm.ai/rocm/`
- block: "Generate Root Index for ROCm Wheels for Release"
key: block-generate-root-index-rocm-wheels
depends_on: upload-rocm-wheels
# =============================================================================
# Nightly: Build & Publish Docker Images (NIGHTLY=1 only)
# =============================================================================
- label: ":package: Generate Root Index for ROCm Wheels for Release"
depends_on: block-generate-root-index-rocm-wheels
id: generate-root-index-rocm-wheels
agents:
queue: cpu_queue_release
commands:
- "bash tools/vllm-rocm/generate-rocm-wheels-root-index.sh"
env:
S3_BUCKET: "vllm-wheels"
VARIANT: "rocm723"
- group: "Build nightly Docker images"
key: "build-release-images"
if: build.env("NIGHTLY") == "1"
steps:
- label: "Build release image - x86_64 - CUDA 12.9"
depends_on: ~
id: build-release-image-x86
agents:
queue: cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=12.9.1 --build-arg FLASHINFER_AOT_COMPILE=true --build-arg INSTALL_KV_CONNECTORS=true --tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m) --target vllm-openai --progress plain -f docker/Dockerfile ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)"
# re-tag to default image tag and push, just in case arm64 build fails
- "docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m) public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT"
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT"
# ROCm Job 6: Build ROCm Release Docker Image
- label: "Build release image - aarch64 - CUDA 12.9"
depends_on: ~
id: build-release-image-arm64
agents:
queue: arm64_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=12.9.1 --build-arg FLASHINFER_AOT_COMPILE=true --build-arg torch_cuda_arch_list='8.7 8.9 9.0 10.0+PTX 12.0' --build-arg INSTALL_KV_CONNECTORS=true --tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m) --target vllm-openai --progress plain -f docker/Dockerfile ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)"
- label: "Build release image - x86_64 - CUDA 13.0"
depends_on: ~
id: build-release-image-x86-cuda-13-0
agents:
queue: cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=13.0.1 --build-arg INSTALL_KV_CONNECTORS=true --build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.1-devel-ubuntu22.04 --tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu130 --target vllm-openai --progress plain -f docker/Dockerfile ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu130"
# re-tag to default image tag and push, just in case arm64 build fails
- "docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu130 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu130"
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu130"
- label: "Build release image - aarch64 - CUDA 13.0"
depends_on: ~
id: build-release-image-arm64-cuda-13-0
agents:
queue: arm64_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
# compute capability 12.0 for RTX-50 series / RTX PRO 6000 Blackwell, 12.1 for DGX Spark
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=13.0.1 --build-arg torch_cuda_arch_list='8.7 8.9 9.0 10.0+PTX 12.0 12.1' --build-arg INSTALL_KV_CONNECTORS=true --build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.1-devel-ubuntu22.04 --tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu130 --target vllm-openai --progress plain -f docker/Dockerfile ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu130"
- label: "Build release image - x86_64 - CUDA 12.9 - Ubuntu 24.04"
depends_on: ~
id: build-release-image-x86-ubuntu2404
agents:
queue: cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=12.9.1 --build-arg UBUNTU_VERSION=24.04 --build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 --build-arg FLASHINFER_AOT_COMPILE=true --build-arg torch_cuda_arch_list='8.7 8.9 9.0 10.0+PTX 12.0' --build-arg INSTALL_KV_CONNECTORS=true --tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-ubuntu2404 --target vllm-openai --progress plain -f docker/Dockerfile ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-ubuntu2404"
- "docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-ubuntu2404 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-ubuntu2404"
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-ubuntu2404"
- label: "Build release image - aarch64 - CUDA 12.9 - Ubuntu 24.04"
depends_on: ~
id: build-release-image-arm64-ubuntu2404
agents:
queue: arm64_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=12.9.1 --build-arg UBUNTU_VERSION=24.04 --build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 --build-arg FLASHINFER_AOT_COMPILE=true --build-arg torch_cuda_arch_list='8.7 8.9 9.0 10.0+PTX 12.0' --build-arg INSTALL_KV_CONNECTORS=true --tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-ubuntu2404 --target vllm-openai --progress plain -f docker/Dockerfile ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-ubuntu2404"
- label: "Build release image - x86_64 - CUDA 13.0 - Ubuntu 24.04"
depends_on: ~
id: build-release-image-x86-cuda-13-0-ubuntu2404
agents:
queue: cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=13.0.1 --build-arg UBUNTU_VERSION=24.04 --build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 --build-arg FLASHINFER_AOT_COMPILE=true --build-arg torch_cuda_arch_list='8.7 8.9 9.0 10.0+PTX 12.0 12.1' --build-arg INSTALL_KV_CONNECTORS=true --build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.1-devel-ubuntu24.04 --tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu130-ubuntu2404 --target vllm-openai --progress plain -f docker/Dockerfile ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu130-ubuntu2404"
- "docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu130-ubuntu2404 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu130-ubuntu2404"
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu130-ubuntu2404"
- label: "Build release image - aarch64 - CUDA 13.0 - Ubuntu 24.04"
depends_on: ~
id: build-release-image-arm64-cuda-13-0-ubuntu2404
agents:
queue: arm64_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=13.0.1 --build-arg UBUNTU_VERSION=24.04 --build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 --build-arg FLASHINFER_AOT_COMPILE=true --build-arg torch_cuda_arch_list='8.7 8.9 9.0 10.0+PTX 12.0 12.1' --build-arg INSTALL_KV_CONNECTORS=true --build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.1-devel-ubuntu24.04 --tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu130-ubuntu2404 --target vllm-openai --progress plain -f docker/Dockerfile ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu130-ubuntu2404"
- group: "Publish nightly images"
key: "publish-release-images"
if: build.env("NIGHTLY") == "1"
steps:
- label: "Create multi-arch manifest - CUDA 12.9"
depends_on:
- build-release-image-x86
- build-release-image-arm64
id: create-multi-arch-manifest
agents:
queue: small_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "docker manifest create public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-x86_64 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-aarch64 --amend"
- "docker manifest push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT"
- label: "Annotate release workflow - CUDA 12.9"
depends_on:
- create-multi-arch-manifest
id: annotate-release-workflow
agents:
queue: small_cpu_queue_release
commands:
- "bash .buildkite/scripts/annotate-release.sh"
- label: "Create multi-arch manifest - CUDA 13.0"
depends_on:
- build-release-image-x86-cuda-13-0
- build-release-image-arm64-cuda-13-0
id: create-multi-arch-manifest-cuda-13-0
agents:
queue: small_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "docker manifest create public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu130 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-x86_64-cu130 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-aarch64-cu130 --amend"
- "docker manifest push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu130"
- label: "Create multi-arch manifest - CUDA 12.9 - Ubuntu 24.04"
depends_on:
- build-release-image-x86-ubuntu2404
- build-release-image-arm64-ubuntu2404
id: create-multi-arch-manifest-ubuntu2404
agents:
queue: small_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "docker manifest create public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-ubuntu2404 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-x86_64-ubuntu2404 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-aarch64-ubuntu2404 --amend"
- "docker manifest push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-ubuntu2404"
- label: "Create multi-arch manifest - CUDA 13.0 - Ubuntu 24.04"
depends_on:
- build-release-image-x86-cuda-13-0-ubuntu2404
- build-release-image-arm64-cuda-13-0-ubuntu2404
id: create-multi-arch-manifest-cuda-13-0-ubuntu2404
agents:
queue: small_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "docker manifest create public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu130-ubuntu2404 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-x86_64-cu130-ubuntu2404 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-aarch64-cu130-ubuntu2404 --amend"
- "docker manifest push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu130-ubuntu2404"
- label: "Publish nightly multi-arch image to DockerHub"
depends_on:
- create-multi-arch-manifest
agents:
queue: small_cpu_queue_release
commands:
- "bash .buildkite/scripts/push-nightly-builds.sh"
# Clean up old nightly builds (keep only last 14)
- "bash .buildkite/scripts/cleanup-nightly-builds.sh"
plugins:
- docker-login#v3.0.0:
username: vllmbot
password-env: DOCKERHUB_TOKEN
env:
DOCKER_BUILDKIT: "1"
DOCKERHUB_USERNAME: "vllmbot"
- label: "Publish nightly multi-arch image to DockerHub - CUDA 13.0"
depends_on:
- create-multi-arch-manifest-cuda-13-0
agents:
queue: small_cpu_queue_release
commands:
- "bash .buildkite/scripts/push-nightly-builds.sh cu130"
# Clean up old nightly builds (keep only last 14)
- "bash .buildkite/scripts/cleanup-nightly-builds.sh cu130-nightly-"
plugins:
- docker-login#v3.0.0:
username: vllmbot
password-env: DOCKERHUB_TOKEN
env:
DOCKER_BUILDKIT: "1"
DOCKERHUB_USERNAME: "vllmbot"
# ROCm nightly Docker image
- label: ":docker: Build release image - x86_64 - ROCm"
id: build-rocm-release-image
if: build.env("NIGHTLY") == "1"
depends_on:
- step: block-build-release-images
allow_failure: true
- step: build-rocm-base-wheels
allow_failure: false
agents:
@@ -753,11 +547,11 @@ steps:
commands:
- |
set -euo pipefail
# Login to ECR
aws ecr-public get-login-password --region us-east-1 | \
docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7
# Get ECR image tag from metadata (set by build-rocm-base-wheels)
ECR_IMAGE_TAG="$$(buildkite-agent meta-data get rocm-base-image-tag 2>/dev/null || echo '')"
if [ -z "$${ECR_IMAGE_TAG}" ]; then
@@ -765,23 +559,23 @@ steps:
echo "This should have been set by the build-rocm-base-wheels job"
exit 1
fi
echo "Pulling base Docker image from ECR: $${ECR_IMAGE_TAG}"
# Pull base Docker image from ECR
docker pull "$${ECR_IMAGE_TAG}"
echo "Loaded base image: $${ECR_IMAGE_TAG}"
# Pass the base image ECR tag to downstream steps (nightly publish)
buildkite-agent meta-data set "rocm-base-ecr-tag" "$${ECR_IMAGE_TAG}"
echo "========================================"
echo "Building vLLM ROCm release image with:"
echo " BASE_IMAGE: $${ECR_IMAGE_TAG}"
echo " BUILDKITE_COMMIT: $${BUILDKITE_COMMIT}"
echo "========================================"
# Build vLLM ROCm release image using cached base
DOCKER_BUILDKIT=1 docker build \
--build-arg max_jobs=16 \
@@ -794,7 +588,7 @@ steps:
--target vllm-openai \
--progress plain \
-f docker/Dockerfile.rocm .
# Push to ECR
docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$${BUILDKITE_COMMIT}-rocm
@@ -826,45 +620,16 @@ steps:
DOCKERHUB_USERNAME: "vllmbot"
# =============================================================================
# Publish to DockerHub and PyPI (at the end so all builds complete first)
# Release: Publish Wheels & Build CPU Images (manual, requires release version)
# =============================================================================
- block: "Publish release images to DockerHub"
key: block-publish-release-images
depends_on:
- create-multi-arch-manifest
- create-multi-arch-manifest-cuda-12-9
- create-multi-arch-manifest-ubuntu2404
- create-multi-arch-manifest-cuda-12-9-ubuntu2404
- build-rocm-release-image
- input-release-version
# Wait for CPU builds if their block steps were unblocked, so publish
# doesn't race the in-progress CPU build. allow_failure lets publish
# proceed when the operator legitimately leaves the CPU block steps
# unblocked or the CPU build fails.
- step: build-cpu-release-image-x86
allow_failure: true
- step: build-cpu-release-image-arm64
allow_failure: true
if: build.env("NIGHTLY") != "1"
- input: "Provide Release version here"
id: input-release-version
fields:
- text: "What is the release version?"
key: release-version
- label: "Publish release images to DockerHub"
depends_on:
- block-publish-release-images
key: publish-release-images-dockerhub
agents:
queue: small_cpu_queue_release
commands:
- "bash .buildkite/scripts/publish-release-images.sh"
plugins:
- docker-login#v3.0.0:
username: vllmbot
password-env: DOCKERHUB_TOKEN
env:
DOCKER_BUILDKIT: "1"
DOCKERHUB_USERNAME: "vllmbot"
- group: "Publish wheels"
- group: "Publish release wheels"
key: "publish-wheels"
steps:
- block: "Confirm update release wheels to PyPI (experimental, use with caution)?"
@@ -881,3 +646,56 @@ steps:
queue: small_cpu_queue_release
commands:
- "bash .buildkite/scripts/upload-release-wheels-pypi.sh"
- group: "Build release CPU Docker images"
steps:
- block: "Build release image for x86_64 CPU"
key: block-cpu-release-image-build
depends_on: ~
- label: "Build release image - x86_64 - CPU"
depends_on:
- block-cpu-release-image-build
- input-release-version
agents:
queue: cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg GIT_REPO_CHECK=1 --build-arg VLLM_CPU_X86=true --tag public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:$(buildkite-agent meta-data get release-version) --tag public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:latest --progress plain --target vllm-openai -f docker/Dockerfile.cpu ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:latest"
- "docker push public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:$(buildkite-agent meta-data get release-version)"
env:
DOCKER_BUILDKIT: "1"
- block: "Build release image for arm64 CPU"
key: block-arm64-cpu-release-image-build
depends_on: ~
- label: "Build release image - arm64 - CPU"
depends_on:
- block-arm64-cpu-release-image-build
- input-release-version
agents:
queue: arm64_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg GIT_REPO_CHECK=1 --tag public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:$(buildkite-agent meta-data get release-version) --tag public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:latest --progress plain --target vllm-openai -f docker/Dockerfile.cpu ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:latest"
- "docker push public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:$(buildkite-agent meta-data get release-version)"
env:
DOCKER_BUILDKIT: "1"
- block: "Generate Root Index for ROCm Wheels for Release"
key: block-generate-root-index-rocm-wheels
depends_on: upload-rocm-wheels
- label: ":package: Generate Root Index for ROCm Wheels for Release"
depends_on: block-generate-root-index-rocm-wheels
id: generate-root-index-rocm-wheels
agents:
queue: cpu_queue_release
commands:
- "bash tools/vllm-rocm/generate-rocm-wheels-root-index.sh"
env:
S3_BUCKET: "vllm-wheels"
VARIANT: "rocm721"
@@ -1,9 +0,0 @@
#!/bin/bash
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
#
# Append a build artifact line to the Buildkite annotation.
# Usage: annotate-build-artifact.sh <label> <value>
set -e
echo "- **${1}**: \`${2}\`" | \
buildkite-agent annotate --append --style 'info' --context 'release-artifacts'
+119
View File
@@ -0,0 +1,119 @@
#!/bin/bash
set -ex
# Get release version, default to 1.0.0.dev for nightly/per-commit builds
RELEASE_VERSION=$(buildkite-agent meta-data get release-version 2>/dev/null | sed 's/^v//')
if [ -z "${RELEASE_VERSION}" ]; then
RELEASE_VERSION="1.0.0.dev"
fi
ROCM_BASE_CACHE_KEY=$(.buildkite/scripts/cache-rocm-base-wheels.sh key)
buildkite-agent annotate --style 'info' --context 'release-workflow' << EOF
To download the wheel (by commit):
\`\`\`
aws s3 cp s3://vllm-wheels/${BUILDKITE_COMMIT}/vllm-${RELEASE_VERSION}-cp38-abi3-manylinux_2_31_x86_64.whl .
aws s3 cp s3://vllm-wheels/${BUILDKITE_COMMIT}/vllm-${RELEASE_VERSION}-cp38-abi3-manylinux_2_31_aarch64.whl .
(Optional) For CUDA 13.0:
aws s3 cp s3://vllm-wheels/${BUILDKITE_COMMIT}/vllm-${RELEASE_VERSION}+cu130-cp38-abi3-manylinux_2_35_x86_64.whl .
aws s3 cp s3://vllm-wheels/${BUILDKITE_COMMIT}/vllm-${RELEASE_VERSION}+cu130-cp38-abi3-manylinux_2_35_aarch64.whl .
(Optional) For CPU:
aws s3 cp s3://vllm-wheels/${BUILDKITE_COMMIT}/vllm-${RELEASE_VERSION}+cpu-cp38-abi3-manylinux_2_35_x86_64.whl .
aws s3 cp s3://vllm-wheels/${BUILDKITE_COMMIT}/vllm-${RELEASE_VERSION}+cpu-cp38-abi3-manylinux_2_35_aarch64.whl .
\`\`\`
To download and upload the image:
\`\`\`
# Download images:
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-x86_64
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-aarch64
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-x86_64-cu130
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-aarch64-cu130
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${ROCM_BASE_CACHE_KEY}-rocm-base
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-rocm
docker pull public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:v${RELEASE_VERSION}
docker pull public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:v${RELEASE_VERSION}
# Tag and push images:
## CUDA
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-x86_64 vllm/vllm-openai:x86_64
docker tag vllm/vllm-openai:x86_64 vllm/vllm-openai:latest-x86_64
docker tag vllm/vllm-openai:x86_64 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64
docker push vllm/vllm-openai:latest-x86_64
docker push vllm/vllm-openai:v${RELEASE_VERSION}-x86_64
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-x86_64-cu130 vllm/vllm-openai:x86_64-cu130
docker tag vllm/vllm-openai:x86_64-cu130 vllm/vllm-openai:latest-x86_64-cu130
docker tag vllm/vllm-openai:x86_64-cu130 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu130
docker push vllm/vllm-openai:latest-x86_64-cu130
docker push vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu130
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-aarch64 vllm/vllm-openai:aarch64
docker tag vllm/vllm-openai:aarch64 vllm/vllm-openai:latest-aarch64
docker tag vllm/vllm-openai:aarch64 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64
docker push vllm/vllm-openai:latest-aarch64
docker push vllm/vllm-openai:v${RELEASE_VERSION}-aarch64
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-aarch64-cu130 vllm/vllm-openai:aarch64-cu130
docker tag vllm/vllm-openai:aarch64-cu130 vllm/vllm-openai:latest-aarch64-cu130
docker tag vllm/vllm-openai:aarch64-cu130 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu130
docker push vllm/vllm-openai:latest-aarch64-cu130
docker push vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu130
## ROCm
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-rocm vllm/vllm-openai-rocm:${BUILDKITE_COMMIT}
docker tag vllm/vllm-openai-rocm:${BUILDKITE_COMMIT} vllm/vllm-openai-rocm:latest
docker tag vllm/vllm-openai-rocm:${BUILDKITE_COMMIT} vllm/vllm-openai-rocm:v${RELEASE_VERSION}
docker push vllm/vllm-openai-rocm:latest
docker push vllm/vllm-openai-rocm:v${RELEASE_VERSION}
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${ROCM_BASE_CACHE_KEY}-rocm-base vllm/vllm-openai-rocm:${BUILDKITE_COMMIT}-base
docker tag vllm/vllm-openai-rocm:${BUILDKITE_COMMIT}-base vllm/vllm-openai-rocm:latest-base
docker tag vllm/vllm-openai-rocm:${BUILDKITE_COMMIT}-base vllm/vllm-openai-rocm:v${RELEASE_VERSION}-base
docker push vllm/vllm-openai-rocm:latest-base
docker push vllm/vllm-openai-rocm:v${RELEASE_VERSION}-base
## CPU
docker tag public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:v${RELEASE_VERSION} vllm/vllm-openai-cpu:x86_64
docker tag vllm/vllm-openai-cpu:x86_64 vllm/vllm-openai-cpu:latest-x86_64
docker tag vllm/vllm-openai-cpu:x86_64 vllm/vllm-openai-cpu:v${RELEASE_VERSION}-x86_64
docker push vllm/vllm-openai-cpu:latest-x86_64
docker push vllm/vllm-openai-cpu:v${RELEASE_VERSION}-x86_64
docker tag public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:v${RELEASE_VERSION} vllm/vllm-openai-cpu:arm64
docker tag vllm/vllm-openai-cpu:arm64 vllm/vllm-openai-cpu:latest-arm64
docker tag vllm/vllm-openai-cpu:arm64 vllm/vllm-openai-cpu:v${RELEASE_VERSION}-arm64
docker push vllm/vllm-openai-cpu:latest-arm64
docker push vllm/vllm-openai-cpu:v${RELEASE_VERSION}-arm64
# Create multi-arch manifest:
docker manifest rm vllm/vllm-openai:latest
docker manifest create vllm/vllm-openai:latest vllm/vllm-openai:latest-x86_64 vllm/vllm-openai:latest-aarch64
docker manifest create vllm/vllm-openai:v${RELEASE_VERSION} vllm/vllm-openai:v${RELEASE_VERSION}-x86_64 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64
docker manifest push vllm/vllm-openai:latest
docker manifest push vllm/vllm-openai:v${RELEASE_VERSION}
docker manifest rm vllm/vllm-openai:latest-cu130
docker manifest create vllm/vllm-openai:latest-cu130 vllm/vllm-openai:latest-x86_64-cu130 vllm/vllm-openai:latest-aarch64-cu130
docker manifest create vllm/vllm-openai:v${RELEASE_VERSION}-cu130 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu130 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu130
docker manifest push vllm/vllm-openai:latest-cu130
docker manifest push vllm/vllm-openai:v${RELEASE_VERSION}-cu130
docker manifest rm vllm/vllm-openai-cpu:latest || true
docker manifest create vllm/vllm-openai-cpu:latest vllm/vllm-openai-cpu:latest-x86_64 vllm/vllm-openai-cpu:latest-arm64
docker manifest create vllm/vllm-openai-cpu:v${RELEASE_VERSION} vllm/vllm-openai-cpu:v${RELEASE_VERSION}-x86_64 vllm/vllm-openai-cpu:v${RELEASE_VERSION}-arm64
docker manifest push vllm/vllm-openai-cpu:latest
docker manifest push vllm/vllm-openai-cpu:v${RELEASE_VERSION}
\`\`\`
EOF
@@ -29,7 +29,7 @@ if python3 -c "import torch; assert torch.version.hip" 2>/dev/null; then
TORCH_INDEX_URL=""
fi
else
TORCH_INDEX_URL="https://download.pytorch.org/whl/cu130"
TORCH_INDEX_URL="https://download.pytorch.org/whl/cu129"
fi
echo ">>> Using PyTorch index: ${TORCH_INDEX_URL:-PyPI default}"
-74
View File
@@ -1,74 +0,0 @@
#!/bin/bash
# Usage: ./ci-fetch-log.sh <buildkite_job_url> [output_file]
# ./ci-fetch-log.sh <build_number> <job_uuid> [output_file]
#
# Downloads the raw log for a Buildkite job from the public, unauthenticated
# /organizations/<org>/pipelines/<pipeline>/builds/<n>/jobs/<uuid>/download
# endpoint, then strips ANSI/timestamps via ci-clean-log.sh.
#
# Find <build_number> and <job_uuid> via:
# gh pr checks <PR> --repo vllm-project/vllm
# Each failing row's URL is .../builds/<build_number>#<job_uuid>.
#
# Default output path: ci-<build>-<uuid_first_13_chars>.log (e.g.
# ci-68478-019e6b07-daae.log). Jobs in the same build share the UUID's
# first 8 chars, so the second segment is needed for uniqueness when
# fetching multiple jobs in parallel. The script refuses to overwrite an
# existing output file; pass an explicit path or set CI_FETCH_LOG_FORCE=1
# to override.
set -euo pipefail
ORG="vllm"
PIPELINE="ci"
usage() {
echo "Usage: $0 <buildkite_job_url> [output_file]"
echo " $0 <build_number> <job_uuid> [output_file]"
exit 1
}
if [ $# -lt 1 ]; then usage; fi
if [[ "$1" == https://* ]]; then
BUILD=$(echo "$1" | sed -nE 's#.*/builds/([0-9]+).*#\1#p')
JOB=$(echo "$1" | grep -oE '[0-9a-f]{8}-[0-9a-f-]+' | head -n 1)
OUT="${2:-}"
else
if [ $# -lt 2 ]; then usage; fi
BUILD="$1"
JOB="$2"
OUT="${3:-}"
fi
if [ -z "$BUILD" ] || [ -z "$JOB" ]; then
echo "Could not parse build number or job UUID from: $1" >&2
usage
fi
# Jobs in the same build share the UUID's first segment, so include the
# second segment (chars 9-13, e.g. "019e6b07-daae") to keep default filenames
# unique when fetching multiple jobs from one build in parallel.
if [ -z "$OUT" ]; then
OUT="ci-${BUILD}-${JOB:0:13}.log"
fi
if [ -e "$OUT" ] && [ -z "${CI_FETCH_LOG_FORCE:-}" ]; then
echo "Refusing to overwrite existing $OUT (set CI_FETCH_LOG_FORCE=1 or pass an explicit output path)." >&2
exit 1
fi
COOKIES=$(mktemp)
trap 'rm -f "$COOKIES"' EXIT
# Buildkite issues a session cookie on first hit; subsequent /download needs it.
curl -fsSL -c "$COOKIES" -A "vllm-ci-fetch-log" \
"https://buildkite.com/${ORG}/${PIPELINE}/builds/${BUILD}" -o /dev/null
curl -fsSL -b "$COOKIES" -A "vllm-ci-fetch-log" \
"https://buildkite.com/organizations/${ORG}/pipelines/${PIPELINE}/builds/${BUILD}/jobs/${JOB}/download" \
-o "$OUT"
bash "$(dirname "$0")/ci-clean-log.sh" "$OUT"
echo "$OUT"
-142
View File
@@ -1,142 +0,0 @@
#!/usr/bin/env python3
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""Detect the manylinux platform tag for a wheel and rename it in place.
vLLM's build images produce wheels with the generic ``linux_<arch>`` platform
tag, which installers like ``pip`` won't accept off PyPI/our index. We need to
rewrite the platform tag to the appropriate ``manylinux_<major>_<minor>_<arch>``
before uploading.
Historically the tag was hard-coded per build (``manylinux_2_31`` for the
Ubuntu 20.04-based image, ``manylinux_2_35`` for the Ubuntu 22.04-based
images). That is brittle: bumping the base image silently produces wheels
labelled with the wrong glibc requirement. This script asks ``auditwheel``
to derive the tag from the symbol versions actually referenced by the
binaries inside the wheel, so the label tracks reality.
We can't simply call ``auditwheel repair`` -- it tries to graft external
shared libraries into the wheel and fails on vLLM's CUDA/cuBLAS dependencies.
Instead we use ``auditwheel.wheel_abi.analyze_wheel_abi`` directly, which is
the same call that powers ``auditwheel show``, and read off
``winfo.sym_policy.name``.
Usage:
detect-manylinux-tag.py <wheel_path>
The wheel is renamed in place; the new path is printed on stdout. All
diagnostics go to stderr so callers can capture stdout safely.
"""
from __future__ import annotations
import argparse
import sys
from pathlib import Path
from auditwheel.error import (
AuditwheelError,
NonPlatformWheelError,
WheelToolsError,
)
from auditwheel.wheel_abi import analyze_wheel_abi
from auditwheel.wheeltools import get_wheel_architecture, get_wheel_libc
def detect_platform_tag(wheel_path: Path) -> str:
"""Return the most precise platform tag the wheel is consistent with.
Mirrors ``auditwheel show`` but returns ``sym_policy`` rather than
``overall_policy``: we only care about the glibc symbol versions used,
not about other policy axes (ISA extensions, blacklist, etc.) that
``overall_policy`` folds in.
"""
fn = wheel_path.name
try:
arch = get_wheel_architecture(fn)
except (WheelToolsError, NonPlatformWheelError):
# Architecture isn't deducible from the filename; let auditwheel
# infer it from the ELF binaries inside the wheel.
arch = None
try:
libc = get_wheel_libc(fn)
except WheelToolsError:
# An unrepaired wheel uses ``linux_<arch>``, which doesn't encode
# libc. Let auditwheel infer it from the ELF binaries.
libc = None
winfo = analyze_wheel_abi(
libc,
arch,
wheel_path,
frozenset(),
disable_isa_ext_check=False,
allow_graft=False,
)
return winfo.sym_policy.name
def rename_wheel(wheel_path: Path, new_platform_tag: str) -> Path:
"""Rename the wheel in place, replacing only its platform tag."""
# Wheel filename per PEP 427:
# {distribution}-{version}(-{build})?-{python}-{abi}-{platform}.whl
# The platform tag is always the last ``-``-separated token before
# ``.whl``. Compound tags like ``manylinux_2_31_x86_64`` use ``_`` as the
# internal separator, so ``-``-splitting is unambiguous.
parts = wheel_path.stem.split("-")
if len(parts) < 5:
raise ValueError(f"Unrecognised wheel filename: {wheel_path.name}")
parts[-1] = new_platform_tag
new_path = wheel_path.with_name("-".join(parts) + ".whl")
if new_path != wheel_path:
wheel_path.rename(new_path)
return new_path
def main() -> int:
parser = argparse.ArgumentParser(
description="Detect a wheel's manylinux platform tag with "
"auditwheel and rename the wheel in place."
)
parser.add_argument(
"wheel",
type=Path,
help="Path to the wheel to inspect and rename.",
)
args = parser.parse_args()
wheel_path: Path = args.wheel
if not wheel_path.is_file():
print(f"error: {wheel_path} is not a file", file=sys.stderr)
return 1
# Catch the things that ``analyze_wheel_abi`` and ``rename_wheel`` can
# raise: any subclass of ``AuditwheelError`` (pure-Python wheels,
# invalid libc, malformed wheels), filesystem errors, or our own
# ``ValueError`` for an unrecognised wheel filename. Print a single
# ``ERROR_TYPE: message`` line to stderr instead of a Python
# traceback, which is much friendlier in CI logs.
try:
new_tag = detect_platform_tag(wheel_path)
print(f"detected platform tag: {new_tag}", file=sys.stderr)
new_path = rename_wheel(wheel_path, new_tag)
except (AuditwheelError, ValueError, OSError) as e:
print(
f"error: failed to retag {wheel_path.name}: {type(e).__name__}: {e}",
file=sys.stderr,
)
return 2
if new_path != wheel_path:
print(f"renamed {wheel_path.name} -> {new_path.name}", file=sys.stderr)
else:
print(f"wheel already tagged {new_tag}", file=sys.stderr)
print(new_path)
return 0
if __name__ == "__main__":
sys.exit(main())
@@ -1,54 +0,0 @@
#!/bin/bash
# Emit docker build flags for release image provenance metadata.
# Keep this helper best-effort: missing Buildkite metadata should fall back to
# local/default values instead of blocking the Docker build.
# Variant examples: "", "cu129", "ubuntu2404", "cu129-ubuntu2404".
variant="${1:-}"
variant_suffix="${variant:+-${variant}}"
image_name="${VLLM_DOCKER_IMAGE_NAME:-vllm/vllm-openai}"
staging_repo="${VLLM_STAGING_IMAGE_REPO:-public.ecr.aws/q9t5s3a7/vllm-release-repo}"
build_commit="${VLLM_BUILD_COMMIT:-${BUILDKITE_COMMIT:-unknown}}"
build_pipeline="${VLLM_BUILD_PIPELINE:-${BUILDKITE_PIPELINE_ID:-${BUILDKITE_PIPELINE_SLUG:-local}}}"
build_url="${VLLM_BUILD_URL:-${BUILDKITE_BUILD_URL:-}}"
tag_commit="${BUILDKITE_COMMIT:-${build_commit}}"
if [[ -n "${BUILDKITE:-}" || -n "${BUILDKITE_COMMIT:-}" ]]; then
release_version="${RELEASE_VERSION:-}"
if command -v buildkite-agent >/dev/null 2>&1; then
release_version="${release_version:-$(buildkite-agent meta-data get release-version 2>/dev/null)}"
fi
release_version="${release_version#v}"
release_version="${release_version:-${tag_commit}}"
staging_image_ref="${staging_repo}:${tag_commit}-$(uname -m)${variant_suffix}"
if [[ "${NIGHTLY:-}" == "1" ]]; then
if [[ -z "${variant}" ]]; then
image_tag="${image_name}:nightly-${tag_commit}"
elif [[ "${variant}" == cu* ]]; then
cuda_variant="${variant%%-*}"
remaining_variant="${variant#${cuda_variant}}"
image_tag="${image_name}:${cuda_variant}-nightly-${tag_commit}${remaining_variant}"
else
image_tag="${image_name}:nightly-${tag_commit}${variant_suffix}"
fi
else
image_tag="${image_name}:v${release_version}${variant_suffix}"
fi
else
image_tag="${VLLM_IMAGE_TAG:-local/vllm-openai:dev}"
staging_image_ref="${image_tag}"
fi
emit_arg() {
printf -- "--build-arg %s=%s " "$1" "$2"
}
emit_arg VLLM_BUILD_COMMIT "${build_commit}"
emit_arg VLLM_BUILD_PIPELINE "${build_pipeline}"
emit_arg VLLM_BUILD_URL "${build_url}"
# This is the intended public tag. The final digest is only known after push.
emit_arg VLLM_IMAGE_TAG "${image_tag}"
printf -- "--tag %s " "${staging_image_ref}"
@@ -9,14 +9,21 @@ set -ex
BUCKET="vllm-wheels"
INDICES_OUTPUT_DIR="indices"
DEFAULT_VARIANT_ALIAS="cu130" # align with vLLM_MAIN_CUDA_VERSION in vllm/envs.py
DEFAULT_VARIANT_ALIAS="cu129" # align with vLLM_MAIN_CUDA_VERSION in vllm/envs.py
PYTHON="${PYTHON_PROG:-python3}" # try to read from env var, otherwise use python3
SUBPATH=$BUILDKITE_COMMIT
S3_COMMIT_PREFIX="s3://$BUCKET/$SUBPATH/"
# Select python3 (>= 3.12) -- local if available, else a docker fallback.
# shellcheck source=lib/select-python.sh
source .buildkite/scripts/lib/select-python.sh
select_python
# detect if python3.12+ is available
has_new_python=$($PYTHON -c "print(1 if __import__('sys').version_info >= (3,12) else 0)")
if [[ "$has_new_python" -eq 0 ]]; then
# use new python from docker
docker pull python:3-slim
PYTHON="docker run --rm -u $(id -u):$(id -g) -v $(pwd):/app -w /app python:3-slim python3"
fi
echo "Using python interpreter: $PYTHON"
echo "Python version: $($PYTHON --version)"
# ======== generate and upload indices ========
+125 -27
View File
@@ -35,9 +35,25 @@ export PYTHONPATH=".."
# Helper Functions
###############################################################################
report_docker_usage() {
echo "--- Docker usage"
docker system df || true
cleanup_docker() {
# Get Docker's root directory
docker_root=$(docker info -f '{{.DockerRootDir}}')
if [ -z "$docker_root" ]; then
echo "Failed to determine Docker root directory."
exit 1
fi
echo "Docker root directory: $docker_root"
disk_usage=$(df "$docker_root" | tail -1 | awk '{print $5}' | sed 's/%//')
threshold=70
if [ "$disk_usage" -gt "$threshold" ]; then
echo "Disk usage is above $threshold%. Cleaning up Docker images and volumes..."
docker image prune -f
docker volume prune -f && docker system prune --force --filter "until=72h" --all
echo "Docker images and volumes cleanup completed."
else
echo "Disk usage is below $threshold%. No cleanup needed."
fi
}
cleanup_network() {
@@ -98,7 +114,8 @@ handle_pytest_exit() {
# unquoted since they have no spaces and work fine.
#
# Already-quoted expressions (containing literal single quotes) are passed
# through untouched to avoid double-quoting well-formed shell fragments.
# through untouched to avoid double-quoting values injected by
# apply_rocm_test_overrides.
#
# NOTE: This ONLY fixes -m/-k flags. It cannot recover arbitrary inner
# double-quotes stripped by the calling shell (see header comment).
@@ -230,6 +247,102 @@ re_quote_pytest_markers() {
echo "${output% }"
}
###############################################################################
# ROCm-specific pytest command rewrites
#
# These apply ignore flags and environment overrides for tests that are not
# yet supported or behave differently on ROCm hardware. Kept as a single
# function so new exclusions are easy to add in one place.
###############################################################################
apply_rocm_test_overrides() {
local cmds="$1"
# --- Model registry filter ---
if [[ $cmds == *"pytest -v -s models/test_registry.py"* ]]; then
cmds=${cmds//"pytest -v -s models/test_registry.py"/"pytest -v -s models/test_registry.py -k 'not BambaForCausalLM and not GritLM and not Mamba2ForCausalLM and not Zamba2ForCausalLM'"}
fi
# --- LoRA: disable custom paged attention ---
if [[ $cmds == *"pytest -v -s lora"* ]]; then
cmds=${cmds//"pytest -v -s lora"/"pytest -v -s lora"}
fi
# --- Kernel ignores ---
if [[ $cmds == *" kernels/core"* ]]; then
cmds="${cmds} \
--ignore=kernels/core/test_fused_quant_layernorm.py \
--ignore=kernels/core/test_permute_cols.py"
fi
if [[ $cmds == *" kernels/attention"* ]]; then
cmds="${cmds} \
--ignore=kernels/attention/test_attention_selector.py \
--ignore=kernels/attention/test_encoder_decoder_attn.py \
--ignore=kernels/attention/test_flash_attn.py \
--ignore=kernels/attention/test_flashinfer.py \
--ignore=kernels/attention/test_prefix_prefill.py \
--ignore=kernels/attention/test_cascade_flash_attn.py \
--ignore=kernels/attention/test_mha_attn.py \
--ignore=kernels/attention/test_lightning_attn.py \
--ignore=kernels/attention/test_attention.py"
fi
if [[ $cmds == *" kernels/quantization"* ]]; then
cmds="${cmds} \
--ignore=kernels/quantization/test_int8_quant.py \
--ignore=kernels/quantization/test_machete_mm.py \
--ignore=kernels/quantization/test_block_fp8.py \
--ignore=kernels/quantization/test_block_int8.py \
--ignore=kernels/quantization/test_marlin_gemm.py \
--ignore=kernels/quantization/test_cutlass_scaled_mm.py \
--ignore=kernels/quantization/test_int8_kernel.py"
fi
if [[ $cmds == *" kernels/mamba"* ]]; then
cmds="${cmds} \
--ignore=kernels/mamba/test_mamba_mixer2.py \
--ignore=kernels/mamba/test_causal_conv1d.py \
--ignore=kernels/mamba/test_mamba_ssm_ssd.py"
fi
if [[ $cmds == *" kernels/moe"* ]]; then
cmds="${cmds} \
--ignore=kernels/moe/test_moe.py \
--ignore=kernels/moe/test_cutlass_moe.py"
fi
# --- Entrypoint ignores ---
if [[ $cmds == *" entrypoints/openai "* ]]; then
cmds=${cmds//" entrypoints/openai "/" entrypoints/openai \
--ignore=entrypoints/openai/chat_completion/test_audio.py \
--ignore=entrypoints/openai/completion/test_shutdown.py \
--ignore=entrypoints/openai/test_completion.py \
--ignore=entrypoints/openai/models/test_models.py \
--ignore=entrypoints/openai/test_return_tokens_as_ids.py \
--ignore=entrypoints/openai/chat_completion/test_root_path.py \
--ignore=entrypoints/openai/completion/test_prompt_validation.py "}
fi
if [[ $cmds == *" entrypoints/serve"* ]]; then
cmds="${cmds} \
--ignore=entrypoints/serve/lora/test_lora_adapters.py"
fi
if [[ $cmds == *" entrypoints/llm "* ]]; then
cmds=${cmds//" entrypoints/llm "/" entrypoints/llm \
--ignore=entrypoints/llm/test_chat.py \
--ignore=entrypoints/llm/test_accuracy.py \
--ignore=entrypoints/llm/test_init.py \
--ignore=entrypoints/llm/test_prompt_validation.py "}
fi
# Clean up escaped newlines from --ignore appends
cmds=$(echo "$cmds" | sed 's/ \\ / /g')
echo "$cmds"
}
###############################################################################
# Main
###############################################################################
@@ -238,8 +351,8 @@ re_quote_pytest_markers() {
echo "--- ROCm info"
rocminfo
# --- Docker status ---
report_docker_usage
# --- Docker housekeeping ---
cleanup_docker
# --- Pull test image ---
echo "--- Pulling container"
@@ -248,17 +361,9 @@ container_name="rocm_${BUILDKITE_COMMIT}_$(tr -dc A-Za-z0-9 < /dev/urandom | hea
docker pull "${image_name}"
remove_docker_container() {
# docker run uses --rm, so the container is normally already gone when the
# EXIT trap runs. Cleanup is best-effort and must not affect the test result.
docker rm -f "${container_name}" >/dev/null 2>&1 || true
docker rm -f "${container_name}" || docker image rm -f "${image_name}" || true
}
on_exit() {
local exit_code=$?
remove_docker_container
exit "$exit_code"
}
trap on_exit EXIT
trap remove_docker_container EXIT
# --- Prepare commands ---
echo "--- Running container"
@@ -273,11 +378,9 @@ HF_MOUNT="/root/.cache/huggingface"
# double-quotes will have been stripped by the calling shell.
if [[ -n "${VLLM_TEST_COMMANDS:-}" ]]; then
commands="${VLLM_TEST_COMMANDS}"
commands_source="env"
echo "Commands sourced from VLLM_TEST_COMMANDS (quoting preserved)"
else
commands="$*"
commands_source="argv"
if [[ -z "$commands" ]]; then
echo "Error: No test commands provided." >&2
echo "Usage:" >&2
@@ -294,16 +397,11 @@ fi
echo "Raw commands: $commands"
# Only try to repair stripped pytest -m/-k quoting in legacy argv mode.
# VLLM_TEST_COMMANDS preserves inner quoting already, and re-quoting that path
# can corrupt embedded echo strings or otherwise well-formed shell fragments.
if [[ "$commands_source" == "argv" ]]; then
commands=$(re_quote_pytest_markers "$commands")
echo "After re-quoting: $commands"
else
echo "Skipping re-quoting for VLLM_TEST_COMMANDS input"
fi
# Fix quoting before ROCm overrides (so overrides see correct structure)
commands=$(re_quote_pytest_markers "$commands")
echo "After re-quoting: $commands"
commands=$(apply_rocm_test_overrides "$commands")
echo "Final commands: $commands"
MYPYTHONPATH=".."
@@ -3,37 +3,42 @@ set -euox pipefail
export VLLM_CPU_CI_ENV=0
export VLLM_CPU_KVCACHE_SPACE=1 # avoid OOM
MODE=${1:-all}
echo "--- PP+TP"
vllm serve meta-llama/Llama-3.2-3B-Instruct -tp=2 -pp=2 --max-model-len=4096 &
server_pid=$!
timeout 600 bash -c "until curl localhost:8000/v1/models > /dev/null 2>&1; do sleep 1; done" || exit 1
vllm bench serve \
--backend vllm \
--dataset-name random \
--model meta-llama/Llama-3.2-3B-Instruct \
--num-prompts 20 \
--result-dir ./test_results \
--result-filename tp_pp.json \
--save-result \
--endpoint /v1/completions
kill -s SIGTERM $server_pid; wait $server_pid || true
failed_req=$(jq '.failed' ./test_results/tp_pp.json)
if [ "$failed_req" -ne 0 ]; then
echo "Some requests were failed!"
exit 1
fi
run_scenario() {
local label="$1" result_file="$2"
shift 2
echo "--- $label"
vllm serve meta-llama/Llama-3.2-3B-Instruct "$@" --max-model-len=4096 &
local server_pid=$!
timeout 600 bash -c "until curl localhost:8000/v1/models > /dev/null 2>&1; do sleep 1; done" || exit 1
vllm bench serve \
--backend vllm \
--dataset-name random \
--model meta-llama/Llama-3.2-3B-Instruct \
--num-prompts 20 \
--result-dir ./test_results \
--result-filename "$result_file" \
--save-result \
--endpoint /v1/completions
kill -s SIGTERM "$server_pid"; wait "$server_pid" || true
if [ "$(jq '.failed' "./test_results/$result_file")" -ne 0 ]; then
echo "Some requests were failed in $label!"
exit 1
fi
}
case "$MODE" in
tp_pp) run_scenario "PP+TP" tp_pp.json -tp=2 -pp=2 ;;
dp_tp) run_scenario "DP+TP" dp_tp.json -tp=2 -dp=2 ;;
all)
run_scenario "PP+TP" tp_pp.json -tp=2 -pp=2
run_scenario "DP+TP" dp_tp.json -tp=2 -dp=2
;;
*) echo "ERROR: unknown mode '$MODE' (expected: tp_pp | dp_tp | all)" >&2; exit 1 ;;
esac
#echo "--- DP+TP"
#vllm serve meta-llama/Llama-3.2-3B-Instruct -tp=2 -dp=2 --max-model-len=4096 &
#server_pid=$!
#timeout 600 bash -c "until curl localhost:8000/v1/models > /dev/null 2>&1; do sleep 1; done" || exit 1
#vllm bench serve \
# --backend vllm \
# --dataset-name random \
# --model meta-llama/Llama-3.2-3B-Instruct \
# --num-prompts 20 \
# --result-dir ./test_results \
# --result-filename dp_pp.json \
# --save-result \
# --endpoint /v1/completions
#kill -s SIGTERM $server_pid; wait $server_pid || true
#failed_req=$(jq '.failed' ./test_results/dp_pp.json)
#if [ "$failed_req" -ne 0 ]; then
# echo "Some requests were failed!"
# exit 1
#fi
@@ -31,22 +31,6 @@ function cpu_tests() {
set -e
pip list"
# Run kernel tests
docker exec cpu-test bash -c "
set -e
pytest -x -v -s tests/kernels/test_onednn.py
pytest -x -v -s tests/kernels/attention/test_cpu_attn.py
pytest -x -v -s tests/kernels/core/test_cpu_activation.py
pytest -x -v -s tests/kernels/moe/test_moe.py -k test_cpu_fused_moe_basic
pytest -x -v -s tests/kernels/mamba/cpu/test_cpu_gdn_ops.py"
# skip tests requiring model downloads if HF_TOKEN is not set
# due to rate-limits
if [ -z "$HF_TOKEN" ]; then
echo "Warning: HF_TOKEN is not set. Skipping tests that require model downloads."
return
fi
# offline inference
docker exec cpu-test bash -c "
set -e
@@ -62,6 +46,12 @@ function cpu_tests() {
set -e
pytest -x -v -s tests/quantization/test_compressed_tensors.py::test_compressed_tensors_w8a8_logprobs"
# Run kernel tests
docker exec cpu-test bash -c "
set -e
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/moe/test_moe.py -k test_cpu_fused_moe_basic"
# basic online serving
docker exec cpu-test bash -c '
@@ -76,21 +66,6 @@ function cpu_tests() {
--num-prompts 20 \
--endpoint /v1/completions
kill -s SIGTERM $server_pid &'
# smoke test for Gated DeltaNet
docker exec cpu-test bash -c '
set -e
VLLM_CPU_OMP_THREADS_BIND=$E2E_OMP_THREADS vllm serve Qwen/Qwen3.5-0.8B --max-model-len 2048 &
server_pid=$!
timeout 600 bash -c "until curl localhost:8000/v1/models; do sleep 1; done" || exit 1
vllm bench serve \
--backend vllm \
--dataset-name random \
--model Qwen/Qwen3.5-0.8B \
--num-prompts 20 \
--endpoint /v1/completions
kill -s SIGTERM $server_pid &'
}
# All of CPU tests are expected to be finished less than 40 mins.
@@ -16,5 +16,5 @@ echo "--- :docker: Building Docker image"
docker build --progress plain --tag "$IMAGE_NAME" --target vllm-test -f docker/Dockerfile.cpu .
# Run the image, setting --shm-size=4g for tensor parallel.
docker run --rm --cpuset-cpus="$CORE_RANGE" --cpuset-mems="$NUMA_NODE" -v ~/.cache/huggingface:/root/.cache/huggingface --privileged=true -e HF_TOKEN -e VLLM_CPU_KVCACHE_SPACE=16 -e VLLM_CPU_CI_ENV=1 -e VLLM_CPU_SIM_MULTI_NUMA=1 -e VLLM_CPU_ATTN_SPLIT_KV=0 --shm-size=4g "$IMAGE_NAME" \
docker run --rm --cpuset-cpus="$CORE_RANGE" --cpuset-mems="$NUMA_NODE" -v ~/.cache/huggingface:/root/.cache/huggingface --privileged=true -e HF_TOKEN -e VLLM_CPU_KVCACHE_SPACE=16 -e VLLM_CPU_CI_ENV=1 -e VLLM_CPU_SIM_MULTI_NUMA=1 --shm-size=4g "$IMAGE_NAME" \
timeout "$TIMEOUT_VAL" bash -c "set -euox pipefail; echo \"--- Print packages\"; pip list; echo \"--- Running tests\"; ${TEST_COMMAND}"
+16 -106
View File
@@ -25,100 +25,22 @@ export PYTHONPATH=".."
###############################################################################
cleanup_docker() {
# Share the same lock with image pull to avoid cleanup/pull races on one node.
local docker_lock="/tmp/docker-pull.lock"
exec 9>"$docker_lock"
flock 9
docker_root=$(docker info -f '{{.DockerRootDir}}')
if [ -z "$docker_root" ]; then
echo "Failed to determine Docker root directory." >&2
flock -u 9
return 1
exit 1
fi
echo "Docker root directory: $docker_root"
disk_usage=$(df "$docker_root" | tail -1 | awk '{print $5}' | sed 's/%//')
threshold=70
if [ "$disk_usage" -gt "$threshold" ]; then
echo "Disk usage is above $threshold%. Running aggressive CI image cleanup..."
cleanup_old_ci_images "${REGISTRY}/${REPO}" "${image_name}" "${DOCKER_IMAGE_CLEANUP_HOURS:-72}" 1
echo "Disk usage is above $threshold%. Cleaning up Docker images and volumes..."
docker image prune -f
docker volume prune -f && docker system prune --force --filter "until=72h" --all
echo "Docker images and volumes cleanup completed."
else
echo "Disk usage is below $threshold%. Checking old CI images anyway."
cleanup_old_ci_images "${REGISTRY}/${REPO}" "${image_name}" "${DOCKER_IMAGE_CLEANUP_HOURS:-72}" 0
fi
echo "Old CI image cleanup completed."
flock -u 9
}
cleanup_old_ci_images() {
local repo_prefix="$1"
local current_image_ref="$2"
local ttl_hours="$3"
local aggressive_cleanup="$4"
if [[ -z "$repo_prefix" || "$repo_prefix" == "/" ]]; then
echo "Skip old-image cleanup: invalid repo prefix '${repo_prefix}'"
return 0
fi
if ! [[ "$ttl_hours" =~ ^[0-9]+$ ]]; then
echo "Invalid DOCKER_IMAGE_CLEANUP_HOURS='${ttl_hours}', fallback to 72"
ttl_hours=72
fi
local now_epoch cutoff_epoch
now_epoch=$(date +%s)
cutoff_epoch=$((now_epoch - ttl_hours * 3600))
local -a used_image_ids
mapfile -t used_image_ids < <(docker ps -aq | xargs -r docker inspect --format '{{.Image}}' | sort -u)
local removed_count=0
local examined_count=0
declare -A seen_ids=()
while read -r image_ref image_id; do
[[ -z "$image_ref" || -z "$image_id" ]] && continue
((examined_count++))
# Keep the image this job is going to use.
if [[ "$image_ref" == "$current_image_ref" ]]; then
continue
fi
# Avoid duplicate deletes when multiple tags point to same image id.
if [[ -n "${seen_ids[$image_id]:-}" ]]; then
continue
fi
seen_ids[$image_id]=1
# Never delete images that are used by any container on this node.
if printf '%s\n' "${used_image_ids[@]}" | grep -qx "$image_id"; then
continue
fi
local created created_epoch
created=$(docker image inspect -f '{{.Created}}' "$image_id" 2>/dev/null || true)
[[ -z "$created" ]] && continue
created_epoch=$(date -d "$created" +%s 2>/dev/null || true)
[[ -z "$created_epoch" ]] && continue
if (( created_epoch < cutoff_epoch )) || [[ "$aggressive_cleanup" == "1" ]]; then
if docker image rm -f "$image_id" >/dev/null 2>&1; then
((removed_count++))
fi
fi
done < <(docker image ls --no-trunc "$repo_prefix" --format '{{.Repository}}:{{.Tag}} {{.ID}}')
# Also trim old dangling layers; this is safe and does not remove referenced images.
docker image prune -f --filter "until=${ttl_hours}h" >/dev/null 2>&1 || true
if [[ "$aggressive_cleanup" == "1" ]]; then
echo "Examined ${examined_count} images under ${repo_prefix}, removed ${removed_count} unused images under disk pressure."
else
echo "Examined ${examined_count} images under ${repo_prefix}, removed ${removed_count} old images (>${ttl_hours}h)."
echo "Disk usage is below $threshold%. No cleanup needed."
fi
}
@@ -318,6 +240,7 @@ fi
cleanup_docker
aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY"
aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin 936637512419.dkr.ecr.us-east-1.amazonaws.com
# --- Build or pull test image ---
IMAGE="${IMAGE_TAG_XPU:-${image_name}}"
@@ -343,6 +266,8 @@ fi
remove_docker_container() {
docker rm -f "${container_name}" || true
docker image rm -f "${image_name}" || true
docker system prune -f || true
}
trap remove_docker_container EXIT
@@ -352,31 +277,16 @@ if [[ -z "${ZE_AFFINITY_MASK:-}" ]]; then
echo "Warning: ZE_AFFINITY_MASK is not set. Proceeding without device affinity." >&2
fi
export CMDS="${commands}"
export HF_TOKEN ZE_AFFINITY_MASK
{
flock 9
if ! docker image inspect "${IMAGE}" >/dev/null 2>&1; then
echo 'Image missing before container creation, pulling again...'
timeout 900 docker pull "${IMAGE}"
fi
docker create \
docker run \
--device /dev/dri:/dev/dri \
--net=host \
--ipc=host \
--privileged \
-v /dev/dri/by-path:/dev/dri/by-path \
-v "${HOME}/.cache/huggingface:/root/.cache/huggingface" \
--entrypoint='' \
-e HF_TOKEN \
-e ZE_AFFINITY_MASK \
-e CMDS \
--entrypoint="" \
-e "HF_TOKEN=${HF_TOKEN:-}" \
-e "ZE_AFFINITY_MASK=${ZE_AFFINITY_MASK:-}" \
-e "CMDS=${commands}" \
--name "${container_name}" \
"${IMAGE}" \
bash -c 'set -e; echo "ZE_AFFINITY_MASK is ${ZE_AFFINITY_MASK:-}"; eval "$CMDS"' \
>/dev/null
} 9>/tmp/docker-pull.lock
docker start -a "${container_name}"
"${image_name}" \
bash -c 'set -e; echo "ZE_AFFINITY_MASK is ${ZE_AFFINITY_MASK:-}"; eval "$CMDS"'
@@ -61,7 +61,7 @@ echo "Results will be stored in: $RESULTS_DIR"
echo "--- Installing Python dependencies ---"
python3 -m pip install --progress-bar off git+https://github.com/thuml/depyf.git \
&& python3 -m pip install --progress-bar off pytest pytest-asyncio tpu-info \
&& python3 -m pip install --progress-bar off "lm-eval[api]>=0.4.12" \
&& python3 -m pip install --progress-bar off "lm-eval[api]>=0.4.11" \
&& python3 -m pip install --progress-bar off hf-transfer tblib==3.1.0
echo "--- Python dependencies installed ---"
@@ -61,7 +61,7 @@ echo "Results will be stored in: $RESULTS_DIR"
echo "--- Installing Python dependencies ---"
python3 -m pip install --progress-bar off git+https://github.com/thuml/depyf.git \
&& python3 -m pip install --progress-bar off pytest pytest-asyncio tpu-info \
&& python3 -m pip install --progress-bar off "lm-eval[api]>=0.4.12" \
&& python3 -m pip install --progress-bar off "lm-eval[api]>=0.4.11" \
&& python3 -m pip install --progress-bar off hf-transfer tblib==3.1.0
echo "--- Python dependencies installed ---"
@@ -136,6 +136,8 @@ run_and_track_test 3 "test_accuracy.py::test_lm_eval_accuracy_v1_engine" \
"python3 -m pytest -s -v /workspace/vllm/tests/entrypoints/llm/test_accuracy.py::test_lm_eval_accuracy_v1_engine"
run_and_track_test 4 "test_quantization_accuracy.py" \
"python3 -m pytest -s -v /workspace/vllm/tests/tpu/test_quantization_accuracy.py"
run_and_track_test 5 "examples/offline_inference/tpu.py" \
"python3 /workspace/vllm/examples/offline_inference/tpu.py"
run_and_track_test 6 "test_tpu_model_runner.py" \
"python3 -m pytest -s -v /workspace/vllm/tests/v1/tpu/worker/test_tpu_model_runner.py"
run_and_track_test 7 "test_sampler.py" \
@@ -0,0 +1,55 @@
#!/bin/bash
# This script build the CPU docker image and run the offline inference inside the container.
# It serves a sanity check for compilation and basic model usage.
set -ex
image_name="xpu/vllm-ci:${BUILDKITE_COMMIT}"
container_name="xpu_${BUILDKITE_COMMIT}_$(tr -dc A-Za-z0-9 < /dev/urandom | head -c 10; echo)"
# Try building the docker image
docker build -t "${image_name}" -f docker/Dockerfile.xpu .
# Setup cleanup
remove_docker_container() {
docker rm -f "${container_name}" || true;
docker image rm -f "${image_name}" || true;
docker system prune -f || true;
}
trap remove_docker_container EXIT
# Run the image and test offline inference/tensor parallel
docker run \
--device /dev/dri:/dev/dri \
--net=host \
--ipc=host \
--privileged \
-v /dev/dri/by-path:/dev/dri/by-path \
--entrypoint="" \
-e "HF_TOKEN=${HF_TOKEN}" \
-e "ZE_AFFINITY_MASK=${ZE_AFFINITY_MASK}" \
--name "${container_name}" \
"${image_name}" \
bash -c '
set -e
echo $ZE_AFFINITY_MASK
python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager
python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 -O3 -cc.cudagraph_mode=NONE
python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager -tp 2 --distributed-executor-backend ray
python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager -tp 2 --distributed-executor-backend mp
python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager --attention-backend=TRITON_ATTN
python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager --quantization fp8
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 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 OPEA/Qwen2.5-0.5B-Instruct-int4-sym-inc --block-size 64 --enforce-eager --max-model-len 8192
cd tests
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
pytest -v -s v1/sample --ignore=v1/sample/test_logprobs.py --ignore=v1/sample/test_logprobs_e2e.py
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/spec_decode --ignore=v1/spec_decode/test_max_len.py --ignore=v1/spec_decode/test_tree_attention.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
pytest -v -s v1/test_serial_utils.py
'
@@ -1,39 +0,0 @@
#!/bin/bash
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
set -euo pipefail
REQUIREMENTS_FILE="${KV_CONNECTORS_REQUIREMENTS:-/vllm-workspace/requirements/kv_connectors.txt}"
uv pip install --system -r "${REQUIREMENTS_FILE}"
NIXL_METADATA=$(python3 - <<'PY'
import importlib.metadata as metadata
import torch
cuda_version = torch.version.cuda
if cuda_version is None:
raise SystemExit("torch.version.cuda is not set")
print(cuda_version.split(".", 1)[0], metadata.version("nixl"))
PY
)
read -r CUDA_MAJOR NIXL_VERSION <<<"${NIXL_METADATA}"
# nixl>=1.1.0 can install multiple CUDA wheel variants. Keep only the variant
# matching this CI image so nixl_ep_cpp links against the available libcudart.
uv pip uninstall --system nixl-cu12 nixl-cu13 2>/dev/null || true
uv pip install --system --no-deps "nixl-cu${CUDA_MAJOR}==${NIXL_VERSION}"
python3 - <<'PY'
import importlib.metadata as metadata
for package_name in ("nixl", "nixl-cu12", "nixl-cu13"):
try:
version = metadata.version(package_name)
except metadata.PackageNotFoundError:
version = "not installed"
print(f"{package_name}: {version}")
PY
-127
View File
@@ -1,127 +0,0 @@
#!/usr/bin/env bash
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
#
# Shared helper for rewriting a wheel's platform tag from the generic
# ``linux_<arch>`` to the correct ``manylinux_<major>_<minor>_<arch>``.
# After sourcing, call ``apply_manylinux_tag <wheel>`` on each wheel
# that still carries the generic tag; the renamed path is printed on
# stdout (logs go to stderr).
#
# Why a pinned Docker container instead of using whatever Python
# happens to be on the agent:
# - vLLM's release agents are heterogeneous -- they don't agree on
# a Python minor version, and we can't rely on a particular
# ``auditwheel`` being installed.
# - ``detect-manylinux-tag.py`` reads ``auditwheel.wheel_abi`` and
# ``Policy.sym_policy``, which are *internal* APIs without a
# stability promise. Pinning both Python and auditwheel makes the
# detected tag a function of the inputs alone, and shifts version
# bumps from "implicit drift" to "deliberate, retested change".
# - Other release scripts (``generate-and-upload-nightly-index.sh``,
# ``upload-rocm-wheels.sh``) already use the python:3-slim image
# when the agent's interpreter is too old; this is the same idea
# made stricter.
#
# To keep the per-wheel cost down (the ROCm upload retags ~10 wheels
# each run), we install auditwheel into a long-lived helper container
# once on source, then ``docker exec`` into it for each call.
#
# Trap behaviour:
# - Sourcing installs an EXIT trap that calls ``manylinux_cleanup`` to
# tear down the helper container. Any EXIT trap that was already in
# place when this file was sourced is captured and run AFTER our
# cleanup, so we don't silently clobber it.
# - If a caller sets a new EXIT trap *after* sourcing, that trap will
# replace ours; in that case the caller should call
# ``manylinux_cleanup`` from their own handler.
if [[ -n "${_MANYLINUX_LIB_SOURCED:-}" ]]; then
return 0
fi
_MANYLINUX_LIB_SOURCED=1
# Pin both sides. Bump these deliberately and re-run a representative
# wheel from each build target through the detection.
_MANYLINUX_PYTHON_IMAGE="python:3.12-slim"
_MANYLINUX_AUDITWHEEL_VERSION="6.6.0"
# Resolve our own directory (and the sibling detect script) using the
# canonical, symlink-resolved path. The container mounts cwd at the
# same absolute path on both sides, so all paths we hand to it -- the
# script, the wheel -- must canonicalise to a location under cwd.
_MANYLINUX_LIB_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd -P)"
_MANYLINUX_DETECT_SCRIPT="$(cd "${_MANYLINUX_LIB_DIR}/.." && pwd -P)/detect-manylinux-tag.py"
_MANYLINUX_CWD="$(pwd -P)"
docker pull --quiet "$_MANYLINUX_PYTHON_IMAGE" >/dev/null
# Spin up a long-lived helper container so we install auditwheel once
# and then ``docker exec`` into it for each wheel.
#
# The container runs as root so ``pip install`` can write into the
# system site-packages; individual ``docker exec`` calls below pin
# themselves to the host UID so any file rename happens with host
# ownership, not root.
_MANYLINUX_CONTAINER="$(docker run -d --rm \
-v "$_MANYLINUX_CWD:$_MANYLINUX_CWD" \
-w "$_MANYLINUX_CWD" \
"$_MANYLINUX_PYTHON_IMAGE" \
sleep infinity)"
docker exec "$_MANYLINUX_CONTAINER" \
pip install --quiet --disable-pip-version-check \
--root-user-action=ignore \
"auditwheel==${_MANYLINUX_AUDITWHEEL_VERSION}"
# Public cleanup -- safe to call multiple times.
manylinux_cleanup() {
if [[ -n "${_MANYLINUX_CONTAINER:-}" ]]; then
docker rm -f "$_MANYLINUX_CONTAINER" >/dev/null 2>&1 || true
_MANYLINUX_CONTAINER=""
fi
}
# Capture any EXIT trap that was already in place so we can chain to
# it rather than overwrite it. ``trap -p EXIT`` prints the handler in
# eval-able form (``trap -- 'CMD' EXIT``) or nothing if unset; we
# strip the wrapper to recover ``CMD``. Handles the common case --
# CMDs without embedded single quotes -- and degrades gracefully (we
# still run our own cleanup) for the pathological case.
_manylinux_prev_exit_trap_cmd=""
_manylinux_existing_exit_trap="$(trap -p EXIT)"
if [[ -n "$_manylinux_existing_exit_trap" ]]; then
_tmp="${_manylinux_existing_exit_trap#trap -- \'}"
_manylinux_prev_exit_trap_cmd="${_tmp%\' EXIT}"
unset _tmp
fi
unset _manylinux_existing_exit_trap
_manylinux_run_exit_chain() {
manylinux_cleanup
if [[ -n "$_manylinux_prev_exit_trap_cmd" ]]; then
eval "$_manylinux_prev_exit_trap_cmd"
fi
}
trap _manylinux_run_exit_chain EXIT
# Detect the manylinux platform tag for a single wheel and rename it
# in place, printing the renamed wheel path on stdout. Returns
# non-zero on failure (which under ``set -e`` propagates to caller).
#
# The wheel must be reachable via a path under the host cwd so it's
# visible inside the helper container; in CI the wheels always live
# under ``artifacts/`` so this is fine.
apply_manylinux_tag() {
local wheel="$1"
local abs_wheel
abs_wheel="$(realpath "$wheel")"
local new_wheel
new_wheel="$(docker exec -u "$(id -u):$(id -g)" \
"$_MANYLINUX_CONTAINER" \
python "$_MANYLINUX_DETECT_SCRIPT" "$abs_wheel")"
if [[ -z "$new_wheel" || ! -f "$new_wheel" ]]; then
echo "apply_manylinux_tag: detect-manylinux-tag.py did not produce a valid wheel path for $wheel" >&2
return 1
fi
printf '%s\n' "$new_wheel"
}
-41
View File
@@ -1,41 +0,0 @@
#!/usr/bin/env bash
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
#
# Pick a Python interpreter for buildkite scripts: prefer a local
# ``python3`` if it is recent enough (>= 3.12), otherwise fall back to
# a one-shot Docker container running ``python:3-slim``. After
# ``select_python`` returns, ``$PYTHON`` is set in the caller's shell
# and is safe to use as a command (e.g. ``$PYTHON some_script.py``).
#
# The 3.12 threshold matches what the existing nightly-index work
# expects -- typing features used by ``generate-nightly-index.py``.
# This helper does not pin the *minor* version; if you need stricter
# reproducibility (e.g. relying on auditwheel internals), invoke
# Docker yourself with a pinned tag rather than calling this.
if [[ -n "${_SELECT_PYTHON_LIB_SOURCED:-}" ]]; then
return 0
fi
_SELECT_PYTHON_LIB_SOURCED=1
# Sets ``PYTHON`` in the caller's shell and exports it. Idempotent --
# calling twice is safe and the second call simply re-runs the probe.
select_python() {
local py="${PYTHON_PROG:-python3}"
local has_new_python
has_new_python=$("$py" -c \
"print(1 if __import__('sys').version_info >= (3,12) else 0)" \
2>/dev/null || echo 0)
if [[ "$has_new_python" -eq 0 ]]; then
# ``-u $(id -u):$(id -g)`` so files created via the container
# end up owned by the host user, not root.
docker pull python:3-slim
PYTHON="docker run --rm -u $(id -u):$(id -g) -v $(pwd):/app -w /app python:3-slim python3"
else
PYTHON="$py"
fi
export PYTHON
echo "Using python interpreter: $PYTHON"
echo "Python version: $($PYTHON --version)"
}
@@ -1,180 +0,0 @@
#!/bin/bash
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
#
# Publish release Docker images from ECR to DockerHub.
# Pulls per-arch images, tags with latest and versioned tags, pushes them,
# then creates and pushes multi-arch manifests.
set -euo pipefail
RELEASE_VERSION=$(buildkite-agent meta-data get release-version --default "" | sed 's/^v//')
if [ -z "${RELEASE_VERSION}" ]; then
echo "ERROR: release-version metadata not set"
exit 1
fi
COMMIT="$BUILDKITE_COMMIT"
ROCM_BASE_CACHE_KEY=$(.buildkite/scripts/cache-rocm-base-wheels.sh key)
echo "========================================"
echo "Publishing release images v${RELEASE_VERSION}"
echo " Commit: ${COMMIT}"
echo " ROCm base cache key: ${ROCM_BASE_CACHE_KEY}"
echo "========================================"
# Login to ECR to pull staging images
aws ecr-public get-login-password --region us-east-1 | \
docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7
# ---- CUDA (default: 13.0) ----
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64 vllm/vllm-openai:latest-x86_64
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64
docker push vllm/vllm-openai:latest-x86_64
docker push vllm/vllm-openai:v${RELEASE_VERSION}-x86_64
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64 vllm/vllm-openai:latest-aarch64
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64
docker push vllm/vllm-openai:latest-aarch64
docker push vllm/vllm-openai:v${RELEASE_VERSION}-aarch64
docker manifest rm vllm/vllm-openai:latest || true
docker manifest rm vllm/vllm-openai:v${RELEASE_VERSION} || true
docker manifest create vllm/vllm-openai:latest vllm/vllm-openai:latest-x86_64 vllm/vllm-openai:latest-aarch64
docker manifest create vllm/vllm-openai:v${RELEASE_VERSION} vllm/vllm-openai:v${RELEASE_VERSION}-x86_64 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64
docker manifest push vllm/vllm-openai:latest
docker manifest push vllm/vllm-openai:v${RELEASE_VERSION}
# ---- CUDA 12.9 ----
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-cu129
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64-cu129
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-cu129 vllm/vllm-openai:latest-x86_64-cu129
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-cu129 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu129
docker push vllm/vllm-openai:latest-x86_64-cu129
docker push vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu129
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64-cu129 vllm/vllm-openai:latest-aarch64-cu129
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64-cu129 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu129
docker push vllm/vllm-openai:latest-aarch64-cu129
docker push vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu129
docker manifest rm vllm/vllm-openai:latest-cu129 || true
docker manifest rm vllm/vllm-openai:v${RELEASE_VERSION}-cu129 || true
docker manifest create vllm/vllm-openai:latest-cu129 vllm/vllm-openai:latest-x86_64-cu129 vllm/vllm-openai:latest-aarch64-cu129
docker manifest create vllm/vllm-openai:v${RELEASE_VERSION}-cu129 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu129 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu129
docker manifest push vllm/vllm-openai:latest-cu129
docker manifest push vllm/vllm-openai:v${RELEASE_VERSION}-cu129
# ---- Ubuntu 24.04 (CUDA 13.0) ----
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-ubuntu2404
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64-ubuntu2404
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-ubuntu2404 vllm/vllm-openai:latest-x86_64-ubuntu2404
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-ubuntu2404 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-ubuntu2404
docker push vllm/vllm-openai:latest-x86_64-ubuntu2404
docker push vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-ubuntu2404
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64-ubuntu2404 vllm/vllm-openai:latest-aarch64-ubuntu2404
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64-ubuntu2404 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-ubuntu2404
docker push vllm/vllm-openai:latest-aarch64-ubuntu2404
docker push vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-ubuntu2404
docker manifest rm vllm/vllm-openai:latest-ubuntu2404 || true
docker manifest rm vllm/vllm-openai:v${RELEASE_VERSION}-ubuntu2404 || true
docker manifest create vllm/vllm-openai:latest-ubuntu2404 vllm/vllm-openai:latest-x86_64-ubuntu2404 vllm/vllm-openai:latest-aarch64-ubuntu2404
docker manifest create vllm/vllm-openai:v${RELEASE_VERSION}-ubuntu2404 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-ubuntu2404 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-ubuntu2404
docker manifest push vllm/vllm-openai:latest-ubuntu2404
docker manifest push vllm/vllm-openai:v${RELEASE_VERSION}-ubuntu2404
# ---- Ubuntu 24.04 (CUDA 12.9) ----
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-cu129-ubuntu2404
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64-cu129-ubuntu2404
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-cu129-ubuntu2404 vllm/vllm-openai:latest-x86_64-cu129-ubuntu2404
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-cu129-ubuntu2404 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu129-ubuntu2404
docker push vllm/vllm-openai:latest-x86_64-cu129-ubuntu2404
docker push vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu129-ubuntu2404
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64-cu129-ubuntu2404 vllm/vllm-openai:latest-aarch64-cu129-ubuntu2404
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64-cu129-ubuntu2404 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu129-ubuntu2404
docker push vllm/vllm-openai:latest-aarch64-cu129-ubuntu2404
docker push vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu129-ubuntu2404
docker manifest rm vllm/vllm-openai:latest-cu129-ubuntu2404 || true
docker manifest rm vllm/vllm-openai:v${RELEASE_VERSION}-cu129-ubuntu2404 || true
docker manifest create vllm/vllm-openai:latest-cu129-ubuntu2404 vllm/vllm-openai:latest-x86_64-cu129-ubuntu2404 vllm/vllm-openai:latest-aarch64-cu129-ubuntu2404
docker manifest create vllm/vllm-openai:v${RELEASE_VERSION}-cu129-ubuntu2404 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu129-ubuntu2404 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu129-ubuntu2404
docker manifest push vllm/vllm-openai:latest-cu129-ubuntu2404
docker manifest push vllm/vllm-openai:v${RELEASE_VERSION}-cu129-ubuntu2404
# ---- ROCm ----
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-rocm
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${ROCM_BASE_CACHE_KEY}-rocm-base
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-rocm vllm/vllm-openai-rocm:latest
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-rocm vllm/vllm-openai-rocm:v${RELEASE_VERSION}
docker push vllm/vllm-openai-rocm:latest
docker push vllm/vllm-openai-rocm:v${RELEASE_VERSION}
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${ROCM_BASE_CACHE_KEY}-rocm-base vllm/vllm-openai-rocm:latest-base
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${ROCM_BASE_CACHE_KEY}-rocm-base vllm/vllm-openai-rocm:v${RELEASE_VERSION}-base
docker push vllm/vllm-openai-rocm:latest-base
docker push vllm/vllm-openai-rocm:v${RELEASE_VERSION}-base
# ---- CPU ----
# CPU images are behind separate block steps and may not have been built.
# All-or-nothing: inspect both arches first, then either publish everything
# (per-arch + multi-arch manifest) or skip everything. Publishing only one
# arch would leave `:latest-x86_64` pointing at the new release while the
# `:latest` multi-arch manifest still resolves to the previous release.
CPU_X86_TAG=public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:v${RELEASE_VERSION}
CPU_ARM_TAG=public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:v${RELEASE_VERSION}
CPU_X86_AVAILABLE=false
CPU_ARM_AVAILABLE=false
docker manifest inspect "${CPU_X86_TAG}" >/dev/null 2>&1 && CPU_X86_AVAILABLE=true
docker manifest inspect "${CPU_ARM_TAG}" >/dev/null 2>&1 && CPU_ARM_AVAILABLE=true
if [ "$CPU_X86_AVAILABLE" = "true" ] && [ "$CPU_ARM_AVAILABLE" = "true" ]; then
docker pull "${CPU_X86_TAG}"
docker tag "${CPU_X86_TAG}" vllm/vllm-openai-cpu:latest-x86_64
docker tag "${CPU_X86_TAG}" vllm/vllm-openai-cpu:v${RELEASE_VERSION}-x86_64
docker push vllm/vllm-openai-cpu:latest-x86_64
docker push vllm/vllm-openai-cpu:v${RELEASE_VERSION}-x86_64
docker pull "${CPU_ARM_TAG}"
docker tag "${CPU_ARM_TAG}" vllm/vllm-openai-cpu:latest-arm64
docker tag "${CPU_ARM_TAG}" vllm/vllm-openai-cpu:v${RELEASE_VERSION}-arm64
docker push vllm/vllm-openai-cpu:latest-arm64
docker push vllm/vllm-openai-cpu:v${RELEASE_VERSION}-arm64
docker manifest rm vllm/vllm-openai-cpu:latest || true
docker manifest rm vllm/vllm-openai-cpu:v${RELEASE_VERSION} || true
docker manifest create vllm/vllm-openai-cpu:latest vllm/vllm-openai-cpu:latest-x86_64 vllm/vllm-openai-cpu:latest-arm64
docker manifest create vllm/vllm-openai-cpu:v${RELEASE_VERSION} vllm/vllm-openai-cpu:v${RELEASE_VERSION}-x86_64 vllm/vllm-openai-cpu:v${RELEASE_VERSION}-arm64
docker manifest push vllm/vllm-openai-cpu:latest
docker manifest push vllm/vllm-openai-cpu:v${RELEASE_VERSION}
elif [ "$CPU_X86_AVAILABLE" = "false" ] && [ "$CPU_ARM_AVAILABLE" = "false" ]; then
echo "WARNING: Neither CPU image found in ECR, skipping CPU publish (ensure block-cpu-release-image-build and block-arm64-cpu-release-image-build were unblocked and the builds finished pushing)"
else
# Partial state: one arch built, the other did not. Fail loudly rather than
# ship a Docker Hub state where `:latest-${arch}` and `:latest` (multi-arch)
# disagree on which release they point at.
echo "ERROR: Partial CPU build detected (x86_64=${CPU_X86_AVAILABLE}, arm64=${CPU_ARM_AVAILABLE})."
echo " Refusing to publish to avoid split-tag drift between per-arch and multi-arch tags."
echo " Re-run the missing CPU build and retry, or manually publish if a single-arch release is intended."
exit 1
fi
echo ""
echo "Successfully published release images for v${RELEASE_VERSION}"
@@ -1,156 +0,0 @@
#!/usr/bin/env bash
set -euo pipefail
MODE="${1:-}"
if [[ "$MODE" != "style-clippy" && "$MODE" != "test" ]]; then
echo "Usage: $0 {style-clippy|test}" >&2
exit 2
fi
ROOT_DIR="$(git rev-parse --show-toplevel)"
cd "$ROOT_DIR"
export CARGO_TERM_COLOR="${CARGO_TERM_COLOR:-always}"
export CARGO_HOME="${CARGO_HOME:-$HOME/.cargo}"
export RUSTUP_HOME="${RUSTUP_HOME:-$HOME/.rustup}"
export PATH="$CARGO_HOME/bin:$PATH"
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)
arch="x86_64"
;;
aarch64|arm64)
arch="aarch_64"
;;
*)
echo "Unsupported protoc architecture: $(uname -m)" >&2
return 1
;;
esac
local url="https://github.com/protocolbuffers/protobuf/releases/download/v${version}/protoc-${version}-linux-${arch}.zip"
local tmp_dir
tmp_dir="$(mktemp -d)"
log_section "Installing protoc ${version}"
curl -L --proto '=https' --tlsv1.2 -sSf "$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"
}
rust_toolchain() {
awk -F '"' '/channel[[:space:]]*=/ { print $2; exit }' rust-toolchain.toml
}
install_rust_toolchain() {
log_section "Installing Rust toolchain"
if ! command -v rustup >/dev/null 2>&1; then
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs \
| sh -s -- -y --profile minimal --default-toolchain none
fi
local toolchain
toolchain="$(rust_toolchain)"
rustup toolchain install "$toolchain" --profile minimal --component rustfmt,clippy
rustup component add --toolchain "$toolchain" rustfmt clippy
}
install_cargo_binstall() {
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/main/install-from-binstall-release.sh \
| bash
}
install_cargo_sort() {
if command -v cargo-sort >/dev/null 2>&1; then
return
fi
log_section "Installing cargo-sort"
install_cargo_binstall
cargo binstall --no-confirm cargo-sort
}
install_cargo_nextest() {
if command -v cargo-nextest >/dev/null 2>&1; then
return
fi
log_section "Installing cargo-nextest"
install_cargo_binstall
cargo binstall --no-confirm --secure cargo-nextest
}
install_uv() {
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="$CARGO_HOME/bin" sh
}
run_style_clippy() {
install_cargo_sort
log_section "Checking Rust formatting"
cargo fmt --manifest-path rust/Cargo.toml --all -- --check
log_section "Checking Cargo.toml ordering"
cargo sort --workspace --check rust
log_section "Running clippy"
cargo clippy \
--manifest-path rust/Cargo.toml \
--workspace \
--all-targets \
--all-features \
--locked \
-- \
-D warnings
}
run_tests() {
install_uv
install_cargo_nextest
log_section "Running cargo nextest"
cargo nextest run \
--manifest-path rust/Cargo.toml \
--workspace \
--all-features \
--locked \
--no-fail-fast
}
install_protoc
install_rust_toolchain
case "$MODE" in
style-clippy)
run_style_clippy
;;
test)
run_tests
;;
esac
@@ -49,7 +49,6 @@ for BACK in "${BACKENDS[@]}"; do
--data-parallel-size 2 \
--enable-expert-parallel \
--enable-eplb \
--eplb-config '{"use_async": false}' \
--trust-remote-code \
--max-model-len 2048 \
--all2all-backend "$BACK" \
@@ -51,7 +51,6 @@ vllm serve "$MODEL" \
--offload-num-in-group 2 \
--offload-prefetch-step 1 \
--offload-params w13_weight w2_weight \
--generation-config vllm \
--port "$PORT" \
${EXTRA_ARGS+"${EXTRA_ARGS[@]}"} &
SERVER_PID=$!
@@ -48,7 +48,7 @@ for BACK in "${BACKENDS[@]}"; do
--enforce-eager \
--enable-eplb \
--all2all-backend "$BACK" \
--eplb-config '{"window_size":10, "step_interval":100, "num_redundant_experts":0, "log_balancedness":true, "use_async":false}' \
--eplb-config '{"window_size":10, "step_interval":100, "num_redundant_experts":0, "log_balancedness":true}' \
--tensor-parallel-size "${TENSOR_PARALLEL_SIZE}" \
--data-parallel-size "${DATA_PARALLEL_SIZE}" \
--enable-expert-parallel \
@@ -1,55 +0,0 @@
#!/usr/bin/env bash
set -euxo pipefail
# args: [THRESHOLD] [NUM_QUESTIONS] [START_PORT]
THRESHOLD=${1:-0.8}
NUM_Q=${2:-1319}
PORT=${3:-8050}
OUT_DIR=${OUT_DIR:-/tmp/vllm-scheduled}
mkdir -p "${OUT_DIR}"
wait_for_server() {
local port=$1
timeout 600 bash -c '
until curl -sf "http://127.0.0.1:'"$port"'/health" > /dev/null; do
sleep 1
done'
}
MODEL="Qwen/Qwen3-30B-A3B-FP8"
BACK="allgather_reducescatter"
cleanup() {
if [[ -n "${SERVER_PID:-}" ]] && kill -0 "${SERVER_PID}" 2>/dev/null; then
kill "${SERVER_PID}" 2>/dev/null || true
for _ in {1..20}; do
kill -0 "${SERVER_PID}" 2>/dev/null || break
sleep 0.5
done
kill -9 "${SERVER_PID}" 2>/dev/null || true
fi
}
trap cleanup EXIT
VLLM_DEEP_GEMM_WARMUP=skip \
vllm serve "$MODEL" \
--enforce-eager \
--data-parallel-size 4 \
--enable-expert-parallel \
--enable-eplb \
--all2all-backend "$BACK" \
--eplb-config '{"window_size":20, "step_interval":100, "use_async":true}' \
--trust-remote-code \
--max-model-len 2048 \
--port "$PORT" &
SERVER_PID=$!
wait_for_server "$PORT"
TAG=$(echo "$MODEL" | tr '/: \\n' '_____')
OUT="${OUT_DIR}/${TAG}_${BACK}.json"
python3 tests/evals/gsm8k/gsm8k_eval.py --host http://127.0.0.1 --port "$PORT" --num-questions "${NUM_Q}" --save-results "${OUT}"
python3 - <<PY
import json; acc=json.load(open('${OUT}'))['accuracy']
print(f"${MODEL} ${BACK}: accuracy {acc:.3f}")
assert acc >= ${THRESHOLD}, f"${MODEL} ${BACK} accuracy {acc}"
PY
@@ -28,7 +28,6 @@
# BFCL_MAX_MODEL_LEN - Max model length (default: 4096)
# BFCL_PORT - Server port (default: 8000)
# BFCL_REASONING_PARSER - Reasoning parser name (default: disabled)
# BFCL_TEMPERATURE - Temperature (default: 0.0)
# BFCL_EXTRA_ARGS - Additional vLLM server args
set -euo pipefail
@@ -44,7 +43,6 @@ TP_SIZE="${BFCL_TP_SIZE:-1}"
MAX_MODEL_LEN="${BFCL_MAX_MODEL_LEN:-4096}"
PORT="${BFCL_PORT:-8000}"
REASONING_PARSER="${BFCL_REASONING_PARSER:-}"
TEMPERATURE="${BFCL_TEMPERATURE:-0.0}"
EXTRA_ARGS="${BFCL_EXTRA_ARGS:-}"
# Set up output directory
@@ -70,7 +68,7 @@ echo "============================================"
# ---- Install bfcl-eval if missing ----
if ! python3 -c "import bfcl_eval" 2>/dev/null; then
echo "Installing bfcl-eval..."
uv pip install "bfcl-eval>=2025.10.20.1,<2026"
pip install "bfcl-eval>=2025.10.20.1,<2026"
fi
# ---- Cleanup handler ----
@@ -100,7 +98,7 @@ SERVE_ARGS=(
--tensor-parallel-size "$TP_SIZE"
--max-model-len "$MAX_MODEL_LEN"
--enforce-eager
--enable-prefix-caching
--no-enable-prefix-caching
)
# Append reasoning parser if specified
@@ -141,7 +139,7 @@ echo "vLLM server is ready. (started in ${SECONDS_WAITED}s)"
# be patched in-process so BFCL knows to use the OpenAI-compatible handler
# against our local vLLM server.
bfcl_exit_code=0
python3 - "$MODEL" "$TEST_CATEGORY" "$NUM_THREADS" "$PORT" "$API_TYPE" "$TEMPERATURE" "$OUTPUT_DIR" << 'PYEOF' || bfcl_exit_code=$?
python3 - "$MODEL" "$TEST_CATEGORY" "$NUM_THREADS" "$PORT" "$API_TYPE" "$OUTPUT_DIR" << 'PYEOF' || bfcl_exit_code=$?
import os
import sys
@@ -150,8 +148,7 @@ test_category = sys.argv[2]
num_threads = int(sys.argv[3])
port = sys.argv[4]
api_type = sys.argv[5]
temperature = float(sys.argv[6])
output_dir = sys.argv[7] if len(sys.argv) > 7 and sys.argv[7] else os.getcwd()
output_dir = sys.argv[6] if len(sys.argv) > 6 and sys.argv[6] else os.getcwd()
os.environ["OPENAI_BASE_URL"] = f"http://localhost:{port}/v1"
os.environ["OPENAI_API_KEY"] = "dummy"
@@ -207,7 +204,6 @@ gen_kwargs["model"] = [model]
gen_kwargs["test_category"] = [c.strip() for c in test_category.split(",")]
gen_kwargs["skip_server_setup"] = True
gen_kwargs["num_threads"] = num_threads
gen_kwargs["temperature"] = temperature
generate(**gen_kwargs)
# ---- evaluate ----
+14 -8
View File
@@ -2,18 +2,14 @@
set -ex
# Upload a single wheel to S3, after detecting and applying the appropriate
# manylinux platform tag with auditwheel.
# Upload a single wheel to S3 (rename linux -> manylinux).
# Index generation is handled separately by generate-and-upload-nightly-index.sh.
# shellcheck source=lib/manylinux.sh
source .buildkite/scripts/lib/manylinux.sh
BUCKET="vllm-wheels"
SUBPATH=$BUILDKITE_COMMIT
S3_COMMIT_PREFIX="s3://$BUCKET/$SUBPATH/"
# ========= locate the wheel ==========
# ========= collect, rename & upload the wheel ==========
# Assume wheels are in artifacts/dist/*.whl
wheel_files=(artifacts/dist/*.whl)
@@ -25,9 +21,19 @@ if [[ ${#wheel_files[@]} -ne 1 ]]; then
fi
wheel="${wheel_files[0]}"
# ========= detect manylinux tag and rename ==========
# default build image uses ubuntu 20.04, which corresponds to manylinux_2_31
# we also accept params as manylinux tag
# refer to https://github.com/mayeut/pep600_compliance?tab=readme-ov-file#acceptable-distros-to-build-wheels
manylinux_version="${1:-manylinux_2_31}"
wheel="$(apply_manylinux_tag "$wheel")"
# Rename 'linux' to the appropriate manylinux version in the wheel filename
if [[ "$wheel" != *"linux"* ]]; then
echo "Error: Wheel filename does not contain 'linux': $wheel"
exit 1
fi
new_wheel="${wheel/linux/$manylinux_version}"
mv -- "$wheel" "$new_wheel"
wheel="$new_wheel"
echo "Renamed wheel to: $wheel"
# Extract the version from the wheel
@@ -39,17 +39,10 @@ fi
set -x # avoid printing secrets above
# install uv if not already available
if ! command -v uv &> /dev/null; then
curl -LsSf https://astral.sh/uv/install.sh | UV_VERSION=0.11.14 sh
export PATH="$HOME/.local/bin:$PATH"
fi
# install twine and sdist build prerequisites using uv with Python 3.12
uv venv --python 3.12 /tmp/vllm-release-env
# install twine from pypi
python3 -m venv /tmp/vllm-release-env
source /tmp/vllm-release-env/bin/activate
uv pip install twine
uv pip install -r requirements/build/cuda.txt
pip install twine
python3 -m twine --version
# copy release wheels to local directory
+18 -23
View File
@@ -20,6 +20,10 @@ BUCKET="${S3_BUCKET:-vllm-wheels}"
ROCM_SUBPATH="rocm/${BUILDKITE_COMMIT}"
S3_COMMIT_PREFIX="s3://$BUCKET/$ROCM_SUBPATH/"
INDICES_OUTPUT_DIR="rocm-indices"
PYTHON="${PYTHON_PROG:-python3}"
# ROCm uses manylinux_2_35 (Ubuntu 22.04 based)
MANYLINUX_VERSION="manylinux_2_35"
echo "========================================"
echo "ROCm Wheel Upload Configuration"
@@ -30,21 +34,19 @@ echo "Commit: $BUILDKITE_COMMIT"
echo "Branch: $BUILDKITE_BRANCH"
echo "========================================"
# ======== Part 0: Setup Python and helpers ========
# ======== Part 0: Setup Python ========
# Pick a Python interpreter for index generation -- local if recent
# enough, else a one-shot docker fallback.
# shellcheck source=lib/select-python.sh
source .buildkite/scripts/lib/select-python.sh
select_python
# Detect if python3.12+ is available
has_new_python=$($PYTHON -c "print(1 if __import__('sys').version_info >= (3,12) else 0)" 2>/dev/null || echo 0)
if [[ "$has_new_python" -eq 0 ]]; then
# Use new python from docker
# Use --user to ensure files are created with correct ownership (not root)
docker pull python:3-slim
PYTHON="docker run --rm --user $(id -u):$(id -g) -v $(pwd):/app -w /app python:3-slim python3"
fi
# Set up auditwheel-in-a-container for the manylinux retagging step.
# Distinct from select_python: ``manylinux.sh`` deliberately pins both
# the Python and auditwheel versions (the script reads auditwheel
# internals) and so always runs in a known-good container regardless
# of what's on the agent.
# shellcheck source=lib/manylinux.sh
source .buildkite/scripts/lib/manylinux.sh
echo "Using python interpreter: $PYTHON"
echo "Python version: $($PYTHON --version)"
# ======== Part 1: Collect and prepare wheels ========
@@ -61,18 +63,11 @@ if [ "$WHEEL_COUNT" -eq 0 ]; then
exit 1
fi
# Detect the appropriate manylinux platform tag for any wheel that still
# carries the generic ``linux_<arch>`` tag, and rename it in place. We use
# auditwheel via ``apply_manylinux_tag`` (see lib/manylinux.sh) rather than
# a hard-coded ``manylinux_2_35`` string so that the label tracks the actual
# glibc symbol versions used by the binaries (and stays correct if the
# rocm_base image is rebased).
#
# The ``linux``/``manylinux`` filter below skips both pre-tagged wheels
# (e.g. upstream torch) and pure-Python ``-any.whl`` wheels.
# Rename linux to manylinux in wheel filenames
for wheel in all-rocm-wheels/*.whl; do
if [[ "$wheel" == *"linux"* ]] && [[ "$wheel" != *"manylinux"* ]]; then
new_wheel="$(apply_manylinux_tag "$wheel")"
new_wheel="${wheel/linux/$MANYLINUX_VERSION}"
mv -- "$wheel" "$new_wheel"
echo "Renamed: $(basename "$wheel") -> $(basename "$new_wheel")"
fi
done
+3105 -2788
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+1 -3
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@@ -3,7 +3,6 @@ depends_on:
- image-build
steps:
- label: V1 attention (H100)
key: v1-attention-h100
timeout_in_minutes: 30
device: h100
source_file_dependencies:
@@ -15,9 +14,8 @@ steps:
- pytest -v -s v1/attention
- label: V1 attention (B200)
key: v1-attention-b200
timeout_in_minutes: 30
device: b200-k8s
device: b200
source_file_dependencies:
- vllm/config/attention.py
- vllm/model_executor/layers/attention
@@ -3,7 +3,6 @@ depends_on:
- image-build
steps:
- label: Basic Correctness
key: basic-correctness
timeout_in_minutes: 30
device: h200_18gb
source_file_dependencies:
+1 -3
View File
@@ -3,7 +3,6 @@ depends_on:
- image-build
steps:
- label: Benchmarks CLI Test
key: benchmarks-cli-test
timeout_in_minutes: 20
device: h200_18gb
source_file_dependencies:
@@ -13,8 +12,7 @@ steps:
- pytest -v -s benchmarks/
- label: Attention Benchmarks Smoke Test (B200)
key: attention-benchmarks-smoke-test-b200
device: b200-k8s
device: b200
num_gpus: 2
optional: true
working_dir: "/vllm-workspace/"
+4 -17
View File
@@ -3,7 +3,6 @@ depends_on:
- image-build
steps:
- label: Sequence Parallel Correctness Tests (2 GPUs)
key: sequence-parallel-correctness-tests-2-gpus
timeout_in_minutes: 50
working_dir: "/vllm-workspace/"
num_devices: 2
@@ -18,7 +17,6 @@ steps:
- pytest -v -s tests/compile/correctness_e2e/test_sequence_parallel.py
- label: Sequence Parallel Correctness Tests (2xH100)
key: sequence-parallel-correctness-tests-2xh100
timeout_in_minutes: 50
working_dir: "/vllm-workspace/"
device: h100
@@ -29,7 +27,6 @@ steps:
- pytest -v -s tests/compile/correctness_e2e/test_sequence_parallel.py
- label: AsyncTP Correctness Tests (2xH100)
key: asynctp-correctness-tests-2xh100
timeout_in_minutes: 50
working_dir: "/vllm-workspace/"
device: h100
@@ -40,10 +37,9 @@ steps:
- pytest -v -s tests/compile/correctness_e2e/test_async_tp.py
- label: AsyncTP Correctness Tests (B200)
key: asynctp-correctness-tests-b200
timeout_in_minutes: 50
working_dir: "/vllm-workspace/"
device: b200-k8s
device: b200
optional: true
num_devices: 2
commands:
@@ -51,7 +47,6 @@ steps:
- pytest -v -s tests/compile/correctness_e2e/test_async_tp.py
- label: Distributed Compile Unit Tests (2xH100)
key: distributed-compile-unit-tests-2xh100
timeout_in_minutes: 20
working_dir: "/vllm-workspace/"
device: h100
@@ -65,10 +60,9 @@ steps:
- pytest -s -v tests/compile/passes/distributed
- label: Fusion and Compile Unit Tests (2xB200)
key: fusion-and-compile-unit-tests-2xb200
timeout_in_minutes: 20
working_dir: "/vllm-workspace/"
device: b200-k8s
device: b200
source_file_dependencies:
- csrc/quantization/fp4/
- vllm/model_executor/layers/quantization/
@@ -95,7 +89,6 @@ steps:
- pytest -v -s tests/compile/fullgraph/test_full_graph.py::test_fp8_kv_scale_compile
- label: Fusion E2E Quick (H100)
key: fusion-e2e-quick-h100
timeout_in_minutes: 15
working_dir: "/vllm-workspace/"
device: h100
@@ -114,7 +107,6 @@ steps:
- pytest -v -s tests/compile/fusions_e2e/test_tp1_quant.py -k "inductor_partition and not +rms_norm and +quant_fp8 and (qwen3 or deepseek)"
- label: Fusion E2E Config Sweep (H100)
key: fusion-e2e-config-sweep-h100
timeout_in_minutes: 30
working_dir: "/vllm-workspace/"
device: h100
@@ -134,10 +126,9 @@ steps:
- pytest -v -s tests/compile/fusions_e2e/test_tp1_quant.py -k "llama-3"
- label: Fusion E2E Config Sweep (B200)
key: fusion-e2e-config-sweep-b200
timeout_in_minutes: 30
working_dir: "/vllm-workspace/"
device: b200-k8s
device: b200
num_devices: 1
optional: true
commands:
@@ -148,7 +139,6 @@ steps:
- pytest -v -s tests/compile/fusions_e2e/test_tp1_quant.py -k "inductor_partition and (FLASHINFER and not +rms_norm and (not +quant_fp8 or +quant_fp8 and (qwen3 or deepseek)) or llama-3)"
- label: Fusion E2E TP2 Quick (H100)
key: fusion-e2e-tp2-quick-h100
timeout_in_minutes: 20
working_dir: "/vllm-workspace/"
device: h100
@@ -166,7 +156,6 @@ steps:
- pytest -v -s tests/compile/fusions_e2e/test_tp2_async_tp.py -k "inductor_partition and not +rms_norm and (not +quant_fp8 or +quant_fp8 and (qwen3 or deepseek))"
- label: Fusion E2E TP2 AR-RMS Config Sweep (H100)
key: fusion-e2e-tp2-ar-rms-config-sweep-h100
timeout_in_minutes: 40
working_dir: "/vllm-workspace/"
device: h100
@@ -186,7 +175,6 @@ steps:
- pytest -v -s tests/compile/fusions_e2e/test_tp2_ar_rms.py -k "llama-3"
- label: Fusion E2E TP2 AsyncTP Config Sweep (H100)
key: fusion-e2e-tp2-asynctp-config-sweep-h100
timeout_in_minutes: 40
working_dir: "/vllm-workspace/"
device: h100
@@ -206,10 +194,9 @@ steps:
- pytest -v -s tests/compile/fusions_e2e/test_tp2_async_tp.py -k "llama-3"
- label: Fusion E2E TP2 (B200)
key: fusion-e2e-tp2-b200
timeout_in_minutes: 20
working_dir: "/vllm-workspace/"
device: b200-k8s
device: b200
num_devices: 2
source_file_dependencies:
- csrc/quantization/
+2 -9
View File
@@ -3,22 +3,16 @@ depends_on:
- image-build
steps:
- label: Platform Tests (CUDA)
key: platform-tests-cuda
timeout_in_minutes: 15
device: h200_18gb
source_file_dependencies:
- vllm/envs.py
- vllm/logger.py
- vllm/platforms/
- vllm/plugins/
- vllm/utils/
- vllm/
- tests/cuda
commands:
- pytest -v -s cuda/test_cuda_context.py
- pytest -v -s cuda/test_platform_no_cuda_init.py
- label: Cudagraph
key: cudagraph
timeout_in_minutes: 20
source_file_dependencies:
- tests/v1/cudagraph
@@ -27,5 +21,4 @@ steps:
- vllm/compilation
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_cudagraph_mode.py
-106
View File
@@ -1,106 +0,0 @@
group: Disaggregated
depends_on:
- image-build
steps:
- label: Distributed NixlConnector PD accuracy (4 GPUs)
key: distributed-nixlconnector-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/
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- 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: 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/
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- FLASHINFER=1 bash v1/kv_connector/nixl_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
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/
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- DP_EP=1 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: 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/
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
- label: Hybrid SSM NixlConnector PD accuracy tests (4 GPUs)
key: hybrid-ssm-nixlconnector-pd-accuracy-tests-4-gpus
timeout_in_minutes: 25
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/
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- HYBRID_SSM=1 bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
- label: MultiConnector (Nixl+Offloading) PD accuracy (2 GPUs)
key: multiconnector-nixl-offloading-pd-accuracy-2-gpus
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl/
- vllm/distributed/kv_transfer/kv_connector/v1/multi_connector.py
- vllm/distributed/kv_transfer/kv_connector/v1/offloading_connector.py
- vllm/distributed/kv_transfer/kv_connector/v1/offloading/
- tests/v1/kv_connector/nixl_integration/
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- bash v1/kv_connector/nixl_integration/run_multi_connector_accuracy_test.sh
- label: NixlConnector PD + Spec Decode acceptance (2 GPUs)
key: nixlconnector-pd-spec-decode-acceptance-2-gpus
timeout_in_minutes: 30
device: a100
working_dir: "/vllm-workspace/tests"
num_devices: 2
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/
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- 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: 30
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl/
- vllm/distributed/kv_transfer/kv_connector/v1/multi_connector.py
- vllm/distributed/kv_transfer/kv_connector/v1/offloading_connector.py
- vllm/distributed/kv_transfer/kv_connector/v1/offloading/
- tests/v1/kv_connector/nixl_integration/
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- bash v1/kv_connector/nixl_integration/run_multi_connector_edge_case_test.sh
+95 -29
View File
@@ -3,7 +3,6 @@ depends_on:
- image-build
steps:
- label: Distributed Comm Ops
key: distributed-comm-ops
timeout_in_minutes: 20
working_dir: "/vllm-workspace/tests"
num_devices: 2
@@ -17,7 +16,6 @@ steps:
- pytest -v -s distributed/test_shm_storage.py
- label: Distributed DP Tests (2 GPUs)
key: distributed-dp-tests-2-gpus
timeout_in_minutes: 20
working_dir: "/vllm-workspace/tests"
num_devices: 2
@@ -39,7 +37,6 @@ steps:
- DP_SIZE=2 pytest -v -s entrypoints/openai/test_multi_api_servers.py
- label: Distributed Compile + RPC Tests (2 GPUs)
key: distributed-compile-rpc-tests-2-gpus
timeout_in_minutes: 20
working_dir: "/vllm-workspace/tests"
num_devices: 2
@@ -62,7 +59,6 @@ steps:
- pytest -v -s ./compile/test_wrapper.py
- label: Distributed Torchrun + Shutdown Tests (2 GPUs)
key: distributed-torchrun-shutdown-tests-2-gpus
timeout_in_minutes: 20
working_dir: "/vllm-workspace/tests"
num_devices: 2
@@ -85,7 +81,6 @@ steps:
- pytest -v -s v1/worker/test_worker_memory_snapshot.py
- label: Distributed Torchrun + Examples (4 GPUs)
key: distributed-torchrun-examples-4-gpus
timeout_in_minutes: 30
working_dir: "/vllm-workspace"
num_devices: 4
@@ -93,8 +88,9 @@ steps:
- vllm/distributed/
- tests/distributed/test_torchrun_example.py
- tests/distributed/test_torchrun_example_moe.py
- examples/offline_inference/rlhf_colocate.py
- examples/rl/
- tests/examples/features/data_parallel/data_parallel_offline.py
- tests/examples/offline_inference/data_parallel.py
commands:
# https://github.com/NVIDIA/nccl/issues/1838
- export NCCL_CUMEM_HOST_ENABLE=0
@@ -111,13 +107,12 @@ steps:
# test with torchrun tp=2 and dp=2 with ep
- TP_SIZE=2 DP_SIZE=2 ENABLE_EP=1 torchrun --nproc-per-node=4 tests/distributed/test_torchrun_example_moe.py
# test with internal dp
- python3 examples/features/data_parallel/data_parallel_offline.py --enforce-eager
- python3 examples/offline_inference/data_parallel.py --enforce-eager
# rlhf examples
- VLLM_ALLOW_INSECURE_SERIALIZATION=1 python3 examples/rl/rlhf_nccl.py
- VLLM_ALLOW_INSECURE_SERIALIZATION=1 python3 examples/rl/rlhf_ipc.py
- label: Distributed DP Tests (4 GPUs)
key: distributed-dp-tests-4-gpus
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 4
@@ -138,7 +133,6 @@ steps:
- pytest -v -s distributed/test_utils.py
- label: Distributed Compile + Comm (4 GPUs)
key: distributed-compile-comm-4-gpus
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 4
@@ -160,28 +154,24 @@ steps:
- pytest -v -s distributed/test_multiproc_executor.py::test_multiproc_executor_multi_node
- 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"
source_file_dependencies:
- examples/features/torchrun/torchrun_dp_example_offline.py
- examples/offline_inference/torchrun_dp_example.py
- vllm/config/parallel.py
- vllm/distributed/
- vllm/v1/engine/llm_engine.py
- vllm/v1/executor/uniproc_executor.py
- vllm/v1/worker/gpu_worker.py
- tests/distributed/test_mnnvl_alltoall.py
commands:
# https://github.com/NVIDIA/nccl/issues/1838
- export NCCL_CUMEM_HOST_ENABLE=0
# 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
- torchrun --nproc-per-node=8 ../examples/offline_inference/torchrun_dp_example.py --tp-size=2 --pp-size=1 --dp-size=4 --enable-ep
- label: Distributed Tests (4 GPUs)(A100)
key: distributed-tests-4-gpus-a100
device: a100
optional: true
num_devices: 4
@@ -196,7 +186,6 @@ steps:
- pytest -v -s -x lora/test_mixtral.py
- label: Distributed Tests (2 GPUs)(H100)
key: distributed-tests-2-gpus-h100
timeout_in_minutes: 15
device: h100
optional: true
@@ -205,14 +194,12 @@ steps:
commands:
- pytest -v -s tests/distributed/test_context_parallel.py
- VLLM_ALLOW_INSECURE_SERIALIZATION=1 python3 examples/rl/rlhf_async_new_apis.py
- VLLM_USE_DEEP_GEMM=1 VLLM_LOGGING_LEVEL=DEBUG python3 examples/features/data_parallel/data_parallel_offline.py --model=Qwen/Qwen1.5-MoE-A2.7B -tp=1 -dp=2 --max-model-len=2048 --all2all-backend=deepep_high_throughput
- VLLM_USE_DEEP_GEMM=1 VLLM_LOGGING_LEVEL=DEBUG python3 examples/offline_inference/data_parallel.py --model=Qwen/Qwen1.5-MoE-A2.7B -tp=1 -dp=2 --max-model-len=2048 --all2all-backend=deepep_high_throughput
- pytest -v -s tests/v1/distributed/test_dbo.py
- VLLM_ALLOW_INSECURE_SERIALIZATION=1 pytest -v -s tests/distributed/test_weight_transfer.py
- pytest -v -s tests/distributed/test_packed_tensor.py
- TP_SIZE=1 DP_SIZE=2 pytest -v -s tests/v1/distributed/test_eagle_dp.py
- label: Distributed Tests (2 GPUs)(B200)
key: distributed-tests-2-gpus-b200
device: b200-k8s
device: b200
optional: true
working_dir: "/vllm-workspace/"
num_devices: 2
@@ -220,12 +207,8 @@ steps:
- pytest -v -s tests/distributed/test_context_parallel.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
- label: 2 Node Test (4 GPUs)
key: 2-node-test-4-gpus
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 2
@@ -238,12 +221,96 @@ steps:
- vllm/executor/
- vllm/model_executor/models/
- tests/distributed/
- tests/examples/features/data_parallel/data_parallel_offline.py
- tests/examples/offline_inference/data_parallel.py
commands:
- ./.buildkite/scripts/run-multi-node-test.sh /vllm-workspace/tests 2 2 $IMAGE_TAG "VLLM_TEST_SAME_HOST=0 torchrun --nnodes 2 --nproc-per-node=2 --rdzv_backend=c10d --rdzv_endpoint=192.168.10.10 distributed/test_same_node.py | grep 'Same node test passed' && NUM_NODES=2 torchrun --nnodes 2 --nproc-per-node=2 --rdzv_backend=c10d --rdzv_endpoint=192.168.10.10 distributed/test_node_count.py | grep 'Node count test passed' && python3 ../examples/features/data_parallel/data_parallel_offline.py -dp=2 -tp=1 --dp-num-nodes=2 --dp-node-rank=0 --dp-master-addr=192.168.10.10 --dp-master-port=12345 --enforce-eager --trust-remote-code && VLLM_MULTI_NODE=1 pytest -v -s distributed/test_multi_node_assignment.py && VLLM_MULTI_NODE=1 pytest -v -s distributed/test_pipeline_parallel.py" "VLLM_TEST_SAME_HOST=0 torchrun --nnodes 2 --nproc-per-node=2 --rdzv_backend=c10d --rdzv_endpoint=192.168.10.10 distributed/test_same_node.py | grep 'Same node test passed' && NUM_NODES=2 torchrun --nnodes 2 --nproc-per-node=2 --rdzv_backend=c10d --rdzv_endpoint=192.168.10.10 distributed/test_node_count.py | grep 'Node count test passed' && python3 ../examples/features/data_parallel/data_parallel_offline.py -dp=2 -tp=1 --dp-num-nodes=2 --dp-node-rank=1 --dp-master-addr=192.168.10.10 --dp-master-port=12345 --enforce-eager --trust-remote-code"
- ./.buildkite/scripts/run-multi-node-test.sh /vllm-workspace/tests 2 2 $IMAGE_TAG "VLLM_TEST_SAME_HOST=0 torchrun --nnodes 2 --nproc-per-node=2 --rdzv_backend=c10d --rdzv_endpoint=192.168.10.10 distributed/test_same_node.py | grep 'Same node test passed' && NUM_NODES=2 torchrun --nnodes 2 --nproc-per-node=2 --rdzv_backend=c10d --rdzv_endpoint=192.168.10.10 distributed/test_node_count.py | grep 'Node count test passed' && python3 ../examples/offline_inference/data_parallel.py -dp=2 -tp=1 --dp-num-nodes=2 --dp-node-rank=0 --dp-master-addr=192.168.10.10 --dp-master-port=12345 --enforce-eager --trust-remote-code && VLLM_MULTI_NODE=1 pytest -v -s distributed/test_multi_node_assignment.py && VLLM_MULTI_NODE=1 pytest -v -s distributed/test_pipeline_parallel.py" "VLLM_TEST_SAME_HOST=0 torchrun --nnodes 2 --nproc-per-node=2 --rdzv_backend=c10d --rdzv_endpoint=192.168.10.10 distributed/test_same_node.py | grep 'Same node test passed' && NUM_NODES=2 torchrun --nnodes 2 --nproc-per-node=2 --rdzv_backend=c10d --rdzv_endpoint=192.168.10.10 distributed/test_node_count.py | grep 'Node count test passed' && python3 ../examples/offline_inference/data_parallel.py -dp=2 -tp=1 --dp-num-nodes=2 --dp-node-rank=1 --dp-master-addr=192.168.10.10 --dp-master-port=12345 --enforce-eager --trust-remote-code"
- label: Distributed NixlConnector 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_connector.py
- tests/v1/kv_connector/nixl_integration/
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
- bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
- label: DP EP Distributed NixlConnector PD accuracy tests (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_connector.py
- tests/v1/kv_connector/nixl_integration/
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
- DP_EP=1 bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
- label: CrossLayer KV layout Distributed NixlConnector PD accuracy tests (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_connector.py
- tests/v1/kv_connector/nixl_integration/
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
- CROSS_LAYERS_BLOCKS=True bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
- label: Hyrbid SSM NixlConnector PD accuracy tests (4 GPUs)
timeout_in_minutes: 20
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
- tests/v1/kv_connector/nixl_integration/
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
- HYBRID_SSM=1 bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
- label: MultiConnector (Nixl+Offloading) PD accuracy (2 GPUs)
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
- vllm/distributed/kv_transfer/kv_connector/v1/multi_connector.py
- vllm/distributed/kv_transfer/kv_connector/v1/offloading_connector.py
- vllm/distributed/kv_transfer/kv_connector/v1/offloading/
- tests/v1/kv_connector/nixl_integration/
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
- bash v1/kv_connector/nixl_integration/run_multi_connector_accuracy_test.sh
- label: NixlConnector PD + Spec Decode acceptance (2 GPUs)
timeout_in_minutes: 30
device: a100
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
- vllm/v1/worker/kv_connector_model_runner_mixin.py
- tests/v1/kv_connector/nixl_integration/
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
- bash v1/kv_connector/nixl_integration/spec_decode_acceptance_test.sh
- label: MultiConnector (Nixl+Offloading) PD edge cases (2 GPUs)
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
- vllm/distributed/kv_transfer/kv_connector/v1/multi_connector.py
- vllm/distributed/kv_transfer/kv_connector/v1/offloading_connector.py
- vllm/distributed/kv_transfer/kv_connector/v1/offloading/
- tests/v1/kv_connector/nixl_integration/
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
- bash v1/kv_connector/nixl_integration/run_multi_connector_edge_case_test.sh
- label: Pipeline + Context Parallelism (4 GPUs)
key: pipeline-context-parallelism-4-gpus
timeout_in_minutes: 60
working_dir: "/vllm-workspace/tests"
num_devices: 4
@@ -258,7 +325,6 @@ steps:
- pytest -v -s distributed/test_pipeline_parallel.py
- label: RayExecutorV2 (4 GPUs)
key: rayexecutorv2-4-gpus
timeout_in_minutes: 60
working_dir: "/vllm-workspace/tests"
num_devices: 4
-16
View File
@@ -1,16 +0,0 @@
group: Docker
depends_on:
- image-build-cpu
steps:
- label: Docker Build Metadata
timeout_in_minutes: 10
device: cpu-small
source_file_dependencies:
- .buildkite/release-pipeline.yaml
- .buildkite/scripts/docker-build-metadata-args.sh
- docker/Dockerfile
- docker/Dockerfile.cpu
- docker/docker-bake.hcl
- tests/tools/test_docker_build_metadata_args.py
commands:
- pytest -v -s tools/test_docker_build_metadata_args.py
+4 -18
View File
@@ -2,8 +2,7 @@ group: E2E Integration
depends_on:
- image-build
steps:
- label: DeepSeek V2-Lite Sync EPLB Accuracy
key: deepseek-v2-lite-sync-eplb-accuracy
- label: DeepSeek V2-Lite Accuracy
timeout_in_minutes: 60
device: h100
optional: true
@@ -12,8 +11,7 @@ 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
key: qwen3-30b-a3b-fp8-block-sync-eplb-accuracy
- label: Qwen3-30B-A3B-FP8-block Accuracy
timeout_in_minutes: 60
device: h100
optional: true
@@ -22,28 +20,16 @@ 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 (B200)
key: qwen3-30b-a3b-fp8-block-sync-eplb-accuracy-b200
- label: Qwen3-30B-A3B-FP8-block Accuracy (B200)
timeout_in_minutes: 60
device: b200-k8s
device: b200
optional: true
num_devices: 2
working_dir: "/vllm-workspace"
commands:
- bash .buildkite/scripts/scheduled_integration_test/qwen30b_a3b_fp8_block_ep_eplb.sh 0.8 200 8020 2 1
- label: Qwen3-30B-A3B-FP8 DP4 Async EPLB Accuracy
key: qwen3-30b-a3b-fp8-dp4-async-eplb-accuracy
timeout_in_minutes: 60
device: h100
optional: true
num_devices: 4
working_dir: "/vllm-workspace"
commands:
- bash .buildkite/scripts/scheduled_integration_test/qwen30b_a3b_fp8_dp4_async_eplb.sh 0.8 200 8050
- label: DeepSeek V2-Lite Prefetch Offload Accuracy (H100)
key: deepseek-v2-lite-prefetch-offload-accuracy-h100
timeout_in_minutes: 60
device: h100
optional: true
+16 -69
View File
@@ -3,32 +3,19 @@ depends_on:
- image-build
steps:
- label: Engine
key: engine
timeout_in_minutes: 15
device: h200_18gb
source_file_dependencies:
- vllm/compilation/
- vllm/config/
- vllm/engine/
- vllm/entrypoints/logger.py
- vllm/envs.py
- vllm/logger.py
- vllm/logging_utils/
- vllm/platforms/
- vllm/sequence.py
- vllm/triton_utils/
- vllm/utils/
- vllm/
- tests/engine
- tests/test_sequence
- tests/test_config
- tests/test_logger
- tests/test_vllm_port
- tests/test_jit_monitor.py
commands:
- pytest -v -s engine test_sequence.py test_config.py test_logger.py test_vllm_port.py test_jit_monitor.py
- pytest -v -s engine test_sequence.py test_config.py test_logger.py test_vllm_port.py
- label: Engine (1 GPU)
key: engine-1-gpu
timeout_in_minutes: 30
source_file_dependencies:
- vllm/v1/engine/
@@ -36,15 +23,8 @@ steps:
commands:
- pytest -v -s v1/engine/test_preprocess_error_handling.py
- pytest -v -s v1/engine --ignore v1/engine/test_preprocess_error_handling.py
mirror:
amd:
device: mi325_1
timeout_in_minutes: 40
depends_on:
- image-build-amd
- label: e2e Scheduling (1 GPU)
key: e2e-scheduling-1-gpu
timeout_in_minutes: 30
device: h200_18gb
source_file_dependencies:
@@ -52,16 +32,8 @@ steps:
- tests/v1/e2e/general/
commands:
- pytest -v -s v1/e2e/general/test_async_scheduling.py
mirror:
amd:
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: 30
source_file_dependencies:
- vllm/v1/
@@ -70,63 +42,38 @@ steps:
- pytest -v -s v1/e2e/general --ignore v1/e2e/general/test_async_scheduling.py
- label: V1 e2e (2 GPUs)
key: v1-e2e-2-gpus
timeout_in_minutes: 60 # TODO: Fix timeout after we have more confidence in the test stability
optional: true
num_devices: 2
source_file_dependencies:
- vllm/compilation/
- vllm/config/
- vllm/distributed/
- vllm/engine/
- vllm/envs.py
- vllm/forward_context.py
- vllm/inputs/
- vllm/logger.py
- vllm/logging_utils/
- vllm/model_executor/
- vllm/multimodal/
- vllm/platforms/
- vllm/sampling_params.py
- vllm/transformers_utils/
- vllm/triton_utils/
- vllm/utils/
- vllm/v1/
- tests/v1/e2e/spec_decode
- vllm/
- tests/v1/e2e
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:
device: mi325_2
depends_on:
- image-build-amd
- label: V1 e2e (4 GPUs)
key: v1-e2e-4-gpus
timeout_in_minutes: 60 # TODO: Fix timeout after we have more confidence in the test stability
optional: true
num_devices: 4
source_file_dependencies:
- vllm/compilation/
- vllm/config/
- vllm/distributed/
- vllm/engine/
- vllm/envs.py
- vllm/forward_context.py
- vllm/inputs/
- vllm/logger.py
- vllm/logging_utils/
- vllm/model_executor/
- vllm/multimodal/
- vllm/platforms/
- vllm/sampling_params.py
- vllm/transformers_utils/
- vllm/triton_utils/
- vllm/utils/
- vllm/v1/
- tests/v1/e2e/spec_decode
- vllm/
- tests/v1/e2e
commands:
# Only run tests that need 4 GPUs
- pytest -v -s v1/e2e/spec_decode/test_spec_decode.py -k "eagle_correctness_heavy"
mirror:
amd:
device: mi325_4
depends_on:
- image-build-amd
- label: V1 e2e (4xH100)
key: v1-e2e-4xh100
timeout_in_minutes: 60
device: h100
num_devices: 4
+14 -57
View File
@@ -2,8 +2,7 @@ group: Entrypoints
depends_on:
- image-build
steps:
- label: Entrypoints Unit Tests
key: entrypoints-unit-tests
- label: Entrypoints Unit Tests
timeout_in_minutes: 10
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
@@ -11,10 +10,9 @@ steps:
- tests/entrypoints/
commands:
- pytest -v -s entrypoints/openai/tool_parsers
- pytest -v -s entrypoints/ --ignore=entrypoints/llm --ignore=entrypoints/offline_mode --ignore=entrypoints/openai --ignore=entrypoints/serve --ignore=entrypoints/test_chat_utils.py --ignore=entrypoints/pooling --ignore=entrypoints/speech_to_text --ignore=tests/entrypoints/generate
- pytest -v -s entrypoints/ --ignore=entrypoints/llm --ignore=entrypoints/rpc --ignore=entrypoints/sleep --ignore=entrypoints/serve/instrumentator --ignore=entrypoints/openai --ignore=entrypoints/offline_mode --ignore=entrypoints/test_chat_utils.py --ignore=entrypoints/pooling
- label: Entrypoints Integration (LLM)
key: entrypoints-integration-llm
timeout_in_minutes: 40
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
@@ -26,15 +24,8 @@ steps:
- pytest -v -s entrypoints/llm --ignore=entrypoints/llm/test_generate.py --ignore=entrypoints/llm/test_collective_rpc.py
- pytest -v -s entrypoints/llm/test_generate.py # it needs a clean process
- pytest -v -s entrypoints/offline_mode # Needs to avoid interference with other tests
mirror:
amd:
device: mi325_1
soft_fail: true
depends_on:
- image-build-amd
- label: Entrypoints Integration (API Server openai - Part 1)
key: entrypoints-integration-api-server-openai-part-1
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
@@ -43,40 +34,32 @@ steps:
- tests/entrypoints/test_chat_utils
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s entrypoints/openai/chat_completion --ignore=entrypoints/openai/chat_completion/test_oot_registration.py
- pytest -v -s entrypoints/openai/chat_completion --ignore=entrypoints/openai/chat_completion/test_chat_with_tool_reasoning.py --ignore=entrypoints/openai/chat_completion/test_oot_registration.py
mirror:
amd:
device: mi325_1
soft_fail: true
timeout_in_minutes: 80
depends_on:
- image-build-amd
- label: Entrypoints Integration (API Server openai - Part 2)
key: entrypoints-integration-api-server-openai-part-2
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
- tests/entrypoints/openai
- tests/entrypoints/test_chat_utils
- tests/entrypoints/generate
- tests/tool_use
commands:
- pytest -v -s entrypoints/openai/completion --ignore=entrypoints/openai/completion/test_tensorizer_entrypoint.py
- pytest -v -s entrypoints/openai/speech_to_text/
- pytest -v -s entrypoints/test_chat_utils.py
- pytest -v -s entrypoints/generate
- pytest -v -s tool_use
mirror:
amd:
device: mi325_1
soft_fail: true
timeout_in_minutes: 60
depends_on:
- image-build-amd
- label: Entrypoints Integration (API Server openai - Part 3)
key: entrypoints-integration-api-server-openai-part-3
timeout_in_minutes: 50
device: h200_18gb
working_dir: "/vllm-workspace/tests"
@@ -86,48 +69,23 @@ steps:
- tests/entrypoints/test_chat_utils
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s entrypoints/openai --ignore=entrypoints/openai/chat_completion --ignore=entrypoints/openai/completion --ignore=entrypoints/openai/correctness/ --ignore=entrypoints/openai/tool_parsers/ --ignore=entrypoints/openai/responses --ignore=entrypoints/openai/test_multi_api_servers.py
mirror:
amd:
device: mi325_1
soft_fail: true
timeout_in_minutes: 60
depends_on:
- image-build-amd
- pytest -v -s entrypoints/openai --ignore=entrypoints/openai/chat_completion --ignore=entrypoints/openai/completion --ignore=entrypoints/openai/speech_to_text/ --ignore=entrypoints/openai/correctness/ --ignore=entrypoints/openai/tool_parsers/ --ignore=entrypoints/openai/responses --ignore=entrypoints/openai/test_multi_api_servers.py
- label: Entrypoints Integration (API Server 2)
device: h200_35gb
key: entrypoints-integration-api-server-2
timeout_in_minutes: 130
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
- tests/entrypoints/serve
- tests/entrypoints/rpc
- tests/entrypoints/serve/instrumentator
- tests/tool_use
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
mirror:
amd:
device: mi325_1
soft_fail: true
depends_on:
- image-build-amd
- label: Entrypoints Integration (Speech to Text)
device: h200_35gb
key: entrypoints-integration-speech_to_text
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
- tests/entrypoints/speech_to_text
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s entrypoints/speech_to_text
- pytest -v -s entrypoints/serve/instrumentator
- PYTHONPATH=/vllm-workspace pytest -v -s entrypoints/rpc
- pytest -v -s tool_use
- label: Entrypoints Integration (Pooling)
key: entrypoints-integration-pooling
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
@@ -138,7 +96,6 @@ steps:
- pytest -v -s entrypoints/pooling
- label: Entrypoints Integration (Responses API)
key: entrypoints-integration-responses-api
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
@@ -148,11 +105,11 @@ steps:
- pytest -v -s entrypoints/openai/responses
- label: OpenAI API Correctness
key: openai-api-correctness
timeout_in_minutes: 30
device: h200_18gb
source_file_dependencies:
- csrc/
- vllm/entrypoints/openai/
commands: # LMEval
- vllm/model_executor/models/whisper.py
commands: # LMEval+Transcription WER check
- pytest -s entrypoints/openai/correctness/
@@ -3,7 +3,6 @@ depends_on:
- image-build
steps:
- label: EPLB Algorithm
key: eplb-algorithm
timeout_in_minutes: 15
device: h200_18gb
working_dir: "/vllm-workspace/tests"
@@ -16,7 +15,6 @@ steps:
- pytest -v -s distributed/test_eplb_utils.py
- label: EPLB Execution # 17min
key: eplb-execution
timeout_in_minutes: 27
working_dir: "/vllm-workspace/tests"
num_devices: 4
@@ -28,7 +26,6 @@ steps:
- pytest -v -s distributed/test_eplb_spec_decode.py
- label: Elastic EP Scaling Test
key: elastic-ep-scaling-test
timeout_in_minutes: 20
device: h100
working_dir: "/vllm-workspace/tests"
+7 -80
View File
@@ -3,7 +3,6 @@ depends_on:
- image-build
steps:
- label: vLLM IR Tests
key: vllm-ir-tests
timeout_in_minutes: 10
device: h200_18gb
working_dir: "/vllm-workspace/"
@@ -15,7 +14,6 @@ steps:
- pytest -v -s tests/kernels/ir
- label: Kernels Core Operation Test
key: kernels-core-operation-test
timeout_in_minutes: 75
source_file_dependencies:
- csrc/
@@ -25,7 +23,6 @@ steps:
- pytest -v -s kernels/core --ignore=kernels/core/test_minimax_reduce_rms.py kernels/test_concat_mla_q.py
- label: Kernels MiniMax Reduce RMS Test (2 GPUs)
key: kernels-minimax-reduce-rms-test-2-gpus
timeout_in_minutes: 15
num_devices: 2
device: h100
@@ -38,30 +35,7 @@ steps:
commands:
- pytest -v -s kernels/core/test_minimax_reduce_rms.py
- label: Deepseek V4 Kernel Test (H100)
key: deepseek-v4-kernel-test-h100
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
commands:
- pytest -v -s kernels/test_fused_deepseek_v4_*.py
- label: Deepseek V4 Kernel Test (B200)
key: deepseek-v4-kernel-test-b200
timeout_in_minutes: 15
device: b200-k8s
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
commands:
- pytest -v -s kernels/test_fused_deepseek_v4_*.py
- label: Kernels Attention Test %N
key: kernels-attention-test
timeout_in_minutes: 35
source_file_dependencies:
- csrc/attention/
@@ -75,7 +49,6 @@ steps:
parallelism: 2
- label: Kernels Quantization Test %N
key: kernels-quantization-test
timeout_in_minutes: 90
source_file_dependencies:
- csrc/quantization/
@@ -84,22 +57,8 @@ steps:
commands:
- pytest -v -s kernels/quantization --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
parallelism: 2
mirror:
amd:
device: mi325_1
source_file_dependencies:
- csrc/quantization/
- vllm/model_executor/layers/quantization
- tests/kernels/quantization
- tests/kernels/quantization/test_rocm_skinny_gemms.py
- vllm/_aiter_ops.py
- vllm/platforms/rocm.py
- vllm/model_executor/kernels/
depends_on:
- image-build-amd
- label: Kernels MoE Test %N
key: kernels-moe-test
timeout_in_minutes: 25
source_file_dependencies:
- csrc/quantization/cutlass_w8a8/moe/
@@ -115,7 +74,6 @@ steps:
parallelism: 5
- label: Kernels Mamba Test
key: kernels-mamba-test
timeout_in_minutes: 45
source_file_dependencies:
- csrc/mamba/
@@ -124,28 +82,12 @@ steps:
commands:
- pytest -v -s kernels/mamba
- label: Kernels KDA Test
timeout_in_minutes: 20
device: h200_18gb
source_file_dependencies:
- 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: 45
device: h100
num_devices: 1
source_file_dependencies:
- cmake/external_projects/deepgemm.cmake
- tools/install_deepgemm.sh
- tools/build_deepgemm_C.py
- tools/setup_deepgemm_pythons.sh
- tools/check_wheel_deepgemm.py
- vllm/utils/deep_gemm.py
- vllm/model_executor/layers/fused_moe
- vllm/model_executor/layers/quantization
@@ -153,31 +95,24 @@ steps:
- tests/kernels/moe/test_deepgemm.py
- tests/kernels/moe/test_batched_deepgemm.py
- tests/kernels/attention/test_deepgemm_attention.py
- tests/quantization/test_cutlass_w4a16.py
commands:
- python3 ../tools/check_wheel_deepgemm.py
- pytest -v -s kernels/quantization/test_block_fp8.py
- pytest -v -s kernels/moe/test_deepgemm.py
- pytest -v -s kernels/moe/test_batched_deepgemm.py
- pytest -v -s kernels/attention/test_deepgemm_attention.py
- pytest -v -s quantization/test_cutlass_w4a16.py
- label: Kernels (B200)
key: kernels-b200
timeout_in_minutes: 30
working_dir: "/vllm-workspace/"
device: b200-k8s
device: b200
# optional: true
source_file_dependencies:
- csrc/quantization/fp4/
- csrc/attention/mla/
- csrc/quantization/cutlass_w8a8/moe/
- vllm/model_executor/layers/fused_moe/experts/cutlass_moe.py
- vllm/model_executor/layers/fused_moe/experts/flashinfer_cutlass_moe.py
- vllm/model_executor/layers/fused_moe/experts/trtllm_nvfp4_moe.py
- vllm/model_executor/layers/fused_moe/oracle/nvfp4.py
- vllm/model_executor/layers/fused_moe/prepare_finalize/flashinfer_nvlink_one_sided.py
- vllm/model_executor/layers/fused_moe/prepare_finalize/flashinfer_nvlink_two_sided.py
- vllm/model_executor/layers/fused_moe/cutlass_moe.py
- vllm/model_executor/layers/fused_moe/flashinfer_cutlass_moe.py
- vllm/model_executor/layers/fused_moe/flashinfer_a2a_prepare_finalize.py
- vllm/model_executor/layers/quantization/utils/flashinfer_utils.py
- vllm/v1/attention/backends/flashinfer.py
- vllm/v1/attention/backends/mla/cutlass_mla.py
@@ -206,29 +141,25 @@ steps:
- pytest -v -s tests/kernels/quantization/test_nvfp4_qutlass.py
- pytest -v -s tests/kernels/quantization/test_mxfp4_qutlass.py
- pytest -v -s tests/kernels/moe/test_nvfp4_moe.py
- pytest -v -s tests/kernels/moe/test_mxfp4_moe.py
- pytest -v -s tests/kernels/moe/test_ocp_mx_moe.py
- pytest -v -s tests/kernels/moe/test_flashinfer.py
- 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
# e2e
- pytest -v -s tests/models/quantization/test_nvfp4.py
- label: Kernels Helion Test
key: kernels-helion-test
timeout_in_minutes: 30
device: h100
source_file_dependencies:
- vllm/utils/import_utils.py
- tests/kernels/helion/
commands:
- pip install helion==1.0.0
- pip install helion==0.3.3
- pytest -v -s kernels/helion/
- label: Kernels FP8 MoE Test (1 H100)
key: kernels-fp8-moe-test-1-h100
timeout_in_minutes: 90
device: h100
num_devices: 1
@@ -245,7 +176,6 @@ steps:
- pytest -v -s kernels/moe/test_triton_moe_ptpc_fp8.py
- label: Kernels FP8 MoE Test (2 H100s)
key: kernels-fp8-moe-test-2-h100s
timeout_in_minutes: 90
device: h100
num_devices: 2
@@ -255,9 +185,8 @@ steps:
- pytest -v -s kernels/moe/test_deepep_moe.py
- label: Kernels Fp4 MoE Test (B200)
key: kernels-fp4-moe-test-b200
timeout_in_minutes: 60
device: b200-k8s
device: b200
num_devices: 1
optional: true
commands:
@@ -268,7 +197,6 @@ steps:
- label: Kernels FusedMoE Layer Test (2 H100s)
key: kernels-fusedmoe-layer-test-2-h100s
timeout_in_minutes: 90
device: h100
num_devices: 2
@@ -285,9 +213,8 @@ steps:
- label: Kernels FusedMoE Layer Test (2 B200s)
key: kernels-fusedmoe-layer-test-2-b200s
timeout_in_minutes: 90
device: b200-k8s
device: b200
num_devices: 2
source_file_dependencies:
- csrc/quantization/cutlass_w8a8/moe/
+5 -38
View File
@@ -3,8 +3,6 @@ depends_on:
- image-build
steps:
- label: LM Eval Small Models
device: h200_35gb
key: lm-eval-small-models
timeout_in_minutes: 75
source_file_dependencies:
- csrc/
@@ -26,7 +24,6 @@ steps:
# - pytest -s -v test_lm_eval_correctness.py --config-list-file=configs/models-large.txt --tp-size=4
- label: LM Eval Large Models (4 GPUs)(H100)
key: lm-eval-large-models-4-gpus-h100
device: h100
optional: true
num_devices: 4
@@ -39,9 +36,8 @@ steps:
- pytest -s -v test_lm_eval_correctness.py --config-list-file=configs/models-large-hopper.txt --tp-size=4
- label: LM Eval Small Models (B200)
key: lm-eval-small-models-b200
timeout_in_minutes: 120
device: b200-k8s
device: b200
optional: true
source_file_dependencies:
- csrc/
@@ -49,22 +45,9 @@ steps:
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-blackwell.txt
- label: LM Eval Large Models (B200, EP)
key: lm-eval-large-models-b200-ep
timeout_in_minutes: 120
device: b200-k8s
optional: true
num_devices: 2
source_file_dependencies:
- csrc/
- vllm/model_executor/layers/quantization
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-blackwell-ep.txt
- label: LM Eval Qwen3.5 Models (B200)
key: lm-eval-qwen3-5-models-b200
timeout_in_minutes: 120
device: b200-k8s
device: b200
optional: true
num_devices: 2
source_file_dependencies:
@@ -79,7 +62,6 @@ steps:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-qwen35-blackwell.txt
- label: LM Eval Large Models (H200)
key: lm-eval-large-models-h200
timeout_in_minutes: 60
device: h200
optional: true
@@ -88,7 +70,6 @@ steps:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-h200.txt
- label: MoE Refactor Integration Test (H100 - TEMPORARY)
key: moe-refactor-integration-test-h100-temporary
device: h100
optional: true
num_devices: 2
@@ -96,16 +77,14 @@ steps:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/moe-refactor/config-h100.txt
- label: MoE Refactor Integration Test (B200 - TEMPORARY)
key: moe-refactor-integration-test-b200-temporary
device: b200-k8s
device: b200
optional: true
num_devices: 2
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/moe-refactor/config-b200.txt
- label: MoE Refactor Integration Test (B200 DP - TEMPORARY)
key: moe-refactor-integration-test-b200-dp-temporary
device: b200-k8s
device: b200
optional: true
num_devices: 2
commands:
@@ -113,9 +92,7 @@ steps:
- label: LM Eval TurboQuant KV Cache
key: lm-eval-turboquant-kv-cache
timeout_in_minutes: 75
device: h200_18gb
source_file_dependencies:
- vllm/model_executor/layers/quantization/turboquant/
- vllm/v1/attention/backends/turboquant_attn.py
@@ -125,7 +102,6 @@ steps:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/models-turboquant.txt
- label: GPQA Eval (GPT-OSS) (H100)
key: gpqa-eval-gpt-oss-h100
timeout_in_minutes: 120
device: h100
optional: true
@@ -139,9 +115,8 @@ steps:
- pytest -s -v evals/gpt_oss/test_gpqa_correctness.py --config-list-file=configs/models-h100.txt
- label: GPQA Eval (GPT-OSS) (B200)
key: gpqa-eval-gpt-oss-b200
timeout_in_minutes: 120
device: b200-k8s
device: b200
optional: true
num_devices: 2
source_file_dependencies:
@@ -151,11 +126,3 @@ steps:
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-b200.txt
- label: MRCR Eval Small Models
device: h200_35gb
timeout_in_minutes: 30
source_file_dependencies:
- tests/evals/mrcr/
commands:
- pytest -s -v evals/mrcr/test_mrcr_correctness.py --config-list-file=evals/mrcr/configs/models-small.txt
+2 -6
View File
@@ -3,24 +3,20 @@ depends_on:
- image-build
steps:
- label: LoRA %N
device: h200_35gb
key: lora
timeout_in_minutes: 30
source_file_dependencies:
- vllm/lora
- tests/lora
commands:
- pytest -v -s lora --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --ignore=lora/test_chatglm3_tp.py --ignore=lora/test_llama_tp.py --ignore=lora/test_qwen3_with_multi_loras.py --ignore=lora/test_olmoe_tp.py --ignore=lora/test_deepseekv2_tp.py --ignore=lora/test_gptoss_tp.py --ignore=lora/test_qwen3moe_tp.py --ignore=lora/test_qwen35_densemodel_lora.py
- pytest -v -s lora --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --ignore=lora/test_chatglm3_tp.py --ignore=lora/test_llama_tp.py --ignore=lora/test_llm_with_multi_loras.py --ignore=lora/test_olmoe_tp.py --ignore=lora/test_deepseekv2_tp.py --ignore=lora/test_gptoss_tp.py --ignore=lora/test_qwen3moe_tp.py --ignore=lora/test_qwen35_densemodel_lora.py
parallelism: 4
- label: LoRA TP (Distributed)
key: lora-tp-distributed
timeout_in_minutes: 30
num_devices: 4
source_file_dependencies:
- vllm/lora
- vllm/model_executor/layers/fused_moe/
- tests/lora
commands:
# FIXIT: find out which code initialize cuda before running the test
@@ -32,7 +28,7 @@ steps:
# requires multi-GPU testing for validation.
- pytest -v -s -x lora/test_chatglm3_tp.py
- pytest -v -s -x lora/test_llama_tp.py
- pytest -v -s -x lora/test_qwen3_with_multi_loras.py
- pytest -v -s -x lora/test_llm_with_multi_loras.py
- pytest -v -s -x lora/test_olmoe_tp.py
- pytest -v -s -x lora/test_gptoss_tp.py
- pytest -v -s -x lora/test_qwen35_densemodel_lora.py
+31 -176
View File
@@ -3,41 +3,25 @@ depends_on:
- image-build
steps:
- label: V1 Spec Decode
device: h200_35gb
key: v1-spec-decode
timeout_in_minutes: 30
source_file_dependencies:
- vllm/config/
- vllm/distributed/
- vllm/inputs/
- vllm/model_executor/
- vllm/platforms/
- vllm/sampling_params.py
- vllm/transformers_utils/
- vllm/utils/
- vllm/v1/
- vllm/
- tests/v1/spec_decode
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
# TODO: create another `optional` test group for slow tests
- pytest -v -s -m 'not slow_test' v1/spec_decode
mirror:
amd:
device: mi325_1
depends_on:
- image-build-amd
- label: V1 Sample + Logits
key: v1-sample-logits
timeout_in_minutes: 30
device: h200_18gb
source_file_dependencies:
- vllm/config/
- vllm/distributed/
- vllm/engine/
- vllm/inputs/
- vllm/logger.py
- vllm/model_executor/
- vllm/platforms/
- vllm/sampling_params.py
- vllm/transformers_utils/
- vllm/utils/
- vllm/v1/
- vllm/
- tests/v1/sample
- tests/v1/logits_processors
- tests/v1/test_oracle.py
@@ -57,69 +41,40 @@ steps:
- image-build-amd
- label: V1 Core + KV + Metrics
key: v1-core-kv-metrics
timeout_in_minutes: 30
source_file_dependencies:
- vllm/config/
- vllm/distributed/
- vllm/engine/
- vllm/entrypoints/pooling/
- vllm/inputs/
- vllm/lora/
- vllm/model_executor/
- vllm/multimodal/
- vllm/outputs.py
- vllm/platforms/
- vllm/pooling_params.py
- vllm/profiler/
- vllm/sampling_params.py
- vllm/tokenizers/
- vllm/transformers_utils/
- vllm/utils/
- vllm/v1/
- vllm/
- tests/v1/core
- tests/v1/executor
- tests/v1/kv_offload
- tests/v1/simple_kv_offload
- tests/v1/worker
- tests/v1/kv_connector/unit
- tests/v1/metrics
- tests/entrypoints/openai/correctness/test_lmeval.py
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
# split the test to avoid interference
- pytest -v -s -m 'not cpu_test' v1/core
- pytest -v -s v1/executor
- pytest -v -s v1/kv_offload
- 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/metrics
# Integration test for streaming correctness (requires special branch).
- 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
depends_on:
- image-build-amd
- label: V1 Others (CPU)
key: v1-others-cpu
depends_on:
- image-build-cpu
source_file_dependencies:
- vllm/config/
- vllm/distributed/
- vllm/engine/
- vllm/inputs/
- vllm/lora/
- vllm/multimodal/
- vllm/outputs.py
- vllm/platforms/
- vllm/pooling_params.py
- vllm/profiler/
- vllm/sampling_params.py
- vllm/tokenizers/
- vllm/transformers_utils/
- vllm/utils/
- vllm/v1/
- vllm/
- tests/v1
device: cpu-small
commands:
@@ -130,35 +85,11 @@ steps:
- pytest -v -s -m 'cpu_test' v1/kv_connector/unit
- pytest -v -s -m 'cpu_test' v1/metrics
- label: Extract Hidden States Integration
key: extract-hidden-states-integration
timeout_in_minutes: 20
device: h200_18gb
source_file_dependencies:
- vllm/v1/spec_decode/extract_hidden_states.py
- vllm/model_executor/models/extract_hidden_states.py
- vllm/transformers_utils/configs/extract_hidden_states.py
- tests/v1/kv_connector/extract_hidden_states_integration
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s v1/kv_connector/extract_hidden_states_integration
- label: Regression
key: regression
timeout_in_minutes: 20
device: h200_18gb
source_file_dependencies:
- vllm/config/
- vllm/distributed/
- vllm/engine/
- vllm/inputs/
- vllm/model_executor/
- vllm/multimodal/
- vllm/platforms/
- vllm/sampling_params.py
- vllm/transformers_utils/
- vllm/utils/
- vllm/v1/
- vllm/
- tests/test_regression
commands:
- pip install modelscope
@@ -166,8 +97,6 @@ steps:
working_dir: "/vllm-workspace/tests" # optional
- label: Examples
device: h200_35gb
key: examples
timeout_in_minutes: 45
working_dir: "/vllm-workspace/examples"
source_file_dependencies:
@@ -184,37 +113,25 @@ steps:
- python3 basic/offline_inference/embed.py
- python3 basic/offline_inference/score.py
# for multi-modal models
- python3 generate/multimodal/audio_language_offline.py --seed 0
- python3 generate/multimodal/vision_language_offline.py --seed 0
- python3 generate/multimodal/vision_language_multi_image_offline.py --seed 0
- python3 generate/multimodal/encoder_decoder_multimodal_offline.py --model-type whisper --seed 0
- python3 offline_inference/audio_language.py --seed 0
- python3 offline_inference/vision_language.py --seed 0
- python3 offline_inference/vision_language_multi_image.py --seed 0
- python3 offline_inference/encoder_decoder_multimodal.py --model-type whisper --seed 0
# for pooling models
- python3 pooling/embed/vision_embedding_offline.py --seed 0
# for features demo
- python3 features/automatic_prefix_caching/prefix_caching_offline.py
- python3 deployment/llm_engine_example.py
- python3 features/tensorize_vllm_model.py --model facebook/opt-125m serialize --serialized-directory /tmp/ --suffix v1 && python3 features/tensorize_vllm_model.py --model facebook/opt-125m deserialize --path-to-tensors /tmp/vllm/facebook/opt-125m/v1/model.tensors
- 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
- python3 offline_inference/prefix_caching.py
- python3 offline_inference/llm_engine_example.py
- python3 others/tensorize_vllm_model.py --model facebook/opt-125m serialize --serialized-directory /tmp/ --suffix v1 && python3 others/tensorize_vllm_model.py --model facebook/opt-125m deserialize --path-to-tensors /tmp/vllm/facebook/opt-125m/v1/model.tensors
- python3 offline_inference/spec_decode.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
- python3 offline_inference/spec_decode.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
- label: Metrics, Tracing (2 GPUs)
key: metrics-tracing-2-gpus
timeout_in_minutes: 20
num_devices: 2
source_file_dependencies:
- vllm/config/
- vllm/distributed/
- vllm/engine/
- vllm/inputs/
- vllm/model_executor/
- vllm/multimodal/
- vllm/platforms/
- vllm/sampling_params.py
- vllm/tracing/
- vllm/transformers_utils/
- vllm/utils/
- vllm/v1/
- vllm/
- tests/v1/tracing
commands:
- "pip install \
@@ -225,11 +142,8 @@ steps:
- pytest -v -s v1/tracing
- label: Python-only Installation
key: python-only-installation
depends_on: ~
optional: true
timeout_in_minutes: 20
device: h200_18gb
source_file_dependencies:
- tests/standalone_tests/python_only_compile.sh
- setup.py
@@ -237,23 +151,9 @@ steps:
- bash standalone_tests/python_only_compile.sh
- label: Async Engine, Inputs, Utils, Worker
device: h200_35gb
key: async-engine-inputs-utils-worker
timeout_in_minutes: 50
source_file_dependencies:
- vllm/assets/
- vllm/config/
- vllm/distributed/
- vllm/engine/
- vllm/inputs/
- vllm/model_executor/
- vllm/multimodal/
- vllm/platforms/
- vllm/sampling_params.py
- vllm/tokenizers/
- vllm/transformers_utils/
- vllm/utils/
- vllm/v1/
- vllm/
- tests/detokenizer
- tests/multimodal
- tests/utils_
@@ -263,35 +163,11 @@ steps:
- pytest -v -s utils_
- label: Async Engine, Inputs, Utils, Worker, Config (CPU)
key: async-engine-inputs-utils-worker-config-cpu
depends_on:
depends_on:
- image-build-cpu
timeout_in_minutes: 30
source_file_dependencies:
- vllm/assets/
- vllm/config/
- vllm/engine/arg_utils.py
- vllm/entrypoints/chat_utils.py
- vllm/entrypoints/mcp/
- vllm/entrypoints/openai/chat_completion/protocol.py
- vllm/entrypoints/openai/engine/protocol.py
- vllm/envs.py
- vllm/exceptions.py
- vllm/inputs/
- vllm/model_executor/layers/quantization/quark/
- vllm/multimodal/
- vllm/outputs.py
- vllm/platforms/
- vllm/pooling_params.py
- vllm/ray/
- vllm/reasoning/
- vllm/renderers/
- vllm/sampling_params.py
- vllm/tokenizers/
- vllm/tool_parsers/
- vllm/transformers_utils/
- vllm/utils/
- vllm/v1/
- vllm/
- tests/test_inputs.py
- tests/test_outputs.py
- tests/test_pooling_params.py
@@ -302,7 +178,6 @@ steps:
- tests/tokenizers_
- tests/reasoning
- tests/tool_parsers
- tests/parser
- tests/transformers_utils
- tests/config
device: cpu-small
@@ -315,28 +190,12 @@ steps:
- pytest -v -s -m 'cpu_test' multimodal
- pytest -v -s renderers
- pytest -v -s tokenizers_
- pytest -v -s reasoning --ignore=reasoning/test_seedoss_reasoning_parser.py --ignore=reasoning/test_glm4_moe_reasoning_parser.py
- pytest -v -s reasoning --ignore=reasoning/test_seedoss_reasoning_parser.py --ignore=reasoning/test_glm4_moe_reasoning_parser.py --ignore=reasoning/test_gemma4_reasoning_parser.py
- pytest -v -s tool_parsers
- pytest -v -s parser
- pytest -v -s transformers_utils
- pytest -v -s config
- label: Batch Invariance (A100)
key: batch-invariance-a100
timeout_in_minutes: 30
device: a100
source_file_dependencies:
- vllm/v1/attention
- vllm/model_executor/layers
- tests/v1/determinism/
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pip install pytest-timeout pytest-forked
- pytest -v -s v1/determinism/test_batch_invariance.py
- VLLM_TEST_MODEL=deepseek-ai/DeepSeek-V2-Lite-Chat pytest -v -s v1/determinism/test_batch_invariance.py::test_v1_generation_is_deterministic_across_batch_sizes_with_needle[TRITON_MLA]
- label: Batch Invariance (H100)
key: batch-invariance-h100
timeout_in_minutes: 30
device: h100
source_file_dependencies:
@@ -352,9 +211,8 @@ steps:
- VLLM_TEST_MODEL=Qwen/Qwen3-30B-A3B-Thinking-2507-FP8 pytest -v -s v1/determinism/test_batch_invariance.py::test_v1_generation_is_deterministic_across_batch_sizes_with_needle[FLASH_ATTN]
- label: Batch Invariance (B200)
key: batch-invariance-b200
timeout_in_minutes: 30
device: b200-k8s
device: b200
source_file_dependencies:
- vllm/v1/attention
- vllm/model_executor/layers
@@ -367,11 +225,8 @@ steps:
- VLLM_TEST_MODEL=deepseek-ai/DeepSeek-V2-Lite-Chat pytest -v -s v1/determinism/test_batch_invariance.py::test_v1_generation_is_deterministic_across_batch_sizes_with_needle[TRITON_MLA]
- VLLM_TEST_MODEL=Qwen/Qwen3-30B-A3B-Thinking-2507-FP8 pytest -v -s v1/determinism/test_batch_invariance.py::test_v1_generation_is_deterministic_across_batch_sizes_with_needle[FLASH_ATTN]
- pytest -v -s v1/determinism/test_nvfp4_batch_invariant.py
- pytest -v -s v1/determinism/test_nvfp4_batch_invariant_scaled_mm.py
- label: Acceptance Length Test (Large Models) # optional
device: h200_35gb
key: acceptance-length-test-large-models
timeout_in_minutes: 25
gpu: h100
optional: true
+2 -10
View File
@@ -3,7 +3,6 @@ depends_on:
- image-build
steps:
- label: Model Executor
key: model-executor
timeout_in_minutes: 35
source_file_dependencies:
- vllm/engine/arg_utils.py
@@ -14,12 +13,5 @@ steps:
commands:
- apt-get update && apt-get install -y curl libsodium23
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
# Dump tracebacks of all threads if a test hangs, so a wedged GPU/CUDA
# init surfaces a stack instead of silently stalling.
- export PYTHONFAULTHANDLER=1
# Per-test watchdog: a single hung test (e.g. stuck during engine/CUDA
# init) fails fast with a traceback instead of running until the global
# build timeout. The `thread` method also handles hangs inside C/CUDA
# 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
- pytest -v -s model_executor -m '(not slow_test)'
- pytest -v -s entrypoints/openai/completion/test_tensorizer_entrypoint.py
+14 -22
View File
@@ -3,8 +3,6 @@ depends_on:
- image-build
steps:
- label: Model Runner V2 Core Tests
device: h200_35gb
key: model-runner-v2-core-tests
timeout_in_minutes: 45
source_file_dependencies:
- vllm/v1/worker/gpu/
@@ -27,19 +25,16 @@ steps:
- pytest -v -s entrypoints/llm/test_struct_output_generate.py -k "xgrammar and not speculative_config6 and not speculative_config7 and not speculative_config8 and not speculative_config0"
- label: Model Runner V2 Examples
device: h200_35gb
key: model-runner-v2-examples
timeout_in_minutes: 45
working_dir: "/vllm-workspace/examples"
source_file_dependencies:
- vllm/v1/worker/gpu/
- vllm/v1/core/sched/
- vllm/v1/worker/gpu_worker.py
- examples/offline_inference/
- examples/basic/offline_inference/
- examples/generate/multimodal/
- examples/features/
- examples/pooling/embed/vision_embedding_offline.py
- examples/features/tensorize_vllm_model.py
- examples/others/tensorize_vllm_model.py
commands:
- set -x
- export VLLM_USE_V2_MODEL_RUNNER=1
@@ -49,22 +44,21 @@ steps:
#- python3 basic/offline_inference/generate.py --model meta-llama/Llama-2-13b-chat-hf --cpu-offload-gb 10 # TODO
#- python3 basic/offline_inference/embed.py # TODO
# for multi-modal models
- python3 generate/multimodal/audio_language_offline.py --seed 0
- python3 generate/multimodal/vision_language_offline.py --seed 0
- python3 generate/multimodal/vision_language_multi_image_offline.py --seed 0
- python3 generate/multimodal/encoder_decoder_multimodal_offline.py --model-type whisper --seed 0
- python3 offline_inference/audio_language.py --seed 0
- python3 offline_inference/vision_language.py --seed 0
- python3 offline_inference/vision_language_multi_image.py --seed 0
- python3 offline_inference/encoder_decoder_multimodal.py --model-type whisper --seed 0
# for pooling models
- python3 pooling/embed/vision_embedding_offline.py --seed 0
# for features demo
- python3 features/automatic_prefix_caching/prefix_caching_offline.py
- python3 deployment/llm_engine_example.py
- python3 features/tensorize_vllm_model.py --model facebook/opt-125m serialize --serialized-directory /tmp/ --suffix v1 && python3 features/tensorize_vllm_model.py --model facebook/opt-125m deserialize --path-to-tensors /tmp/vllm/facebook/opt-125m/v1/model.tensors
- 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
- python3 offline_inference/prefix_caching.py
- python3 offline_inference/llm_engine_example.py
- python3 others/tensorize_vllm_model.py --model facebook/opt-125m serialize --serialized-directory /tmp/ --suffix v1 && python3 others/tensorize_vllm_model.py --model facebook/opt-125m deserialize --path-to-tensors /tmp/vllm/facebook/opt-125m/v1/model.tensors
- python3 offline_inference/spec_decode.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
- python3 offline_inference/spec_decode.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
- label: Model Runner V2 Distributed (2 GPUs)
key: model-runner-v2-distributed-2-gpus
timeout_in_minutes: 45
working_dir: "/vllm-workspace/tests"
num_devices: 2
@@ -85,7 +79,6 @@ steps:
- TP_SIZE=1 DP_SIZE=2 pytest -v -s v1/distributed/test_eagle_dp.py
- label: Model Runner V2 Pipeline Parallelism (4 GPUs)
key: model-runner-v2-pipeline-parallelism-4-gpus
timeout_in_minutes: 60
working_dir: "/vllm-workspace/tests"
num_devices: 4
@@ -101,20 +94,19 @@ steps:
- pytest -v -s distributed/test_pp_cudagraph.py -k "not ray"
- label: Model Runner V2 Spec Decode
device: h200_35gb
key: model-runner-v2-spec-decode
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/v1/worker/gpu/
- vllm/v1/worker/gpu_worker.py
- tests/v1/spec_decode/test_max_len.py
- tests/v1/spec_decode/test_rejection_sampler_utils.py
- tests/v1/spec_decode/test_probabilistic_rejection_sampler_utils.py
- tests/v1/spec_decode/test_synthetic_rejection_sampler_utils.py
- tests/v1/e2e/spec_decode/test_spec_decode.py
commands:
- set -x
- export VLLM_USE_V2_MODEL_RUNNER=1
- pytest -v -s v1/spec_decode/test_max_len.py -k "eagle or mtp"
- pytest -v -s v1/spec_decode/test_rejection_sampler_utils.py
- pytest -v -s v1/spec_decode/test_probabilistic_rejection_sampler_utils.py
- pytest -v -s v1/spec_decode/test_synthetic_rejection_sampler_utils.py
- pytest -v -s v1/e2e/spec_decode/test_spec_decode.py -k "eagle or mtp"
+21 -6
View File
@@ -3,7 +3,6 @@ depends_on:
- image-build
steps:
- label: Basic Models Tests (Initialization)
key: basic-models-tests-initialization
timeout_in_minutes: 45
device: h200_18gb
torch_nightly: true
@@ -18,8 +17,6 @@ steps:
torch_nightly: {}
- label: Basic Models Tests (Extra Initialization) %N
device: h200_35gb
key: basic-models-tests-extra-initialization
timeout_in_minutes: 45
source_file_dependencies:
- vllm/model_executor/models/
@@ -35,8 +32,6 @@ steps:
torch_nightly: {}
- label: Basic Models Tests (Other)
device: h200_35gb
key: basic-models-tests-other
timeout_in_minutes: 45
source_file_dependencies:
- vllm/
@@ -45,9 +40,14 @@ steps:
- tests/models/test_registry.py
commands:
- pytest -v -s models/test_terratorch.py models/test_transformers.py models/test_registry.py
mirror:
amd:
device: mi325_1
depends_on:
- image-build-amd
- label: Basic Models Test (Other CPU) # 5min
key: basic-models-test-other-cpu
depends_on:
- image-build-cpu
timeout_in_minutes: 10
@@ -58,3 +58,18 @@ steps:
device: cpu-small
commands:
- pytest -v -s models/test_utils.py models/test_vision.py
- label: Transformers Nightly Models
working_dir: "/vllm-workspace/"
optional: true
soft_fail: true
commands:
- pip install --upgrade git+https://github.com/huggingface/transformers
- pytest -v -s tests/models/test_initialization.py
- pytest -v -s tests/models/test_transformers.py
- pytest -v -s tests/models/multimodal/processing/
- pytest -v -s tests/models/multimodal/test_mapping.py
- python3 examples/basic/offline_inference/chat.py
- python3 examples/offline_inference/vision_language.py --model-type qwen2_5_vl
# Whisper needs spawn method to avoid deadlock
- VLLM_WORKER_MULTIPROC_METHOD=spawn python3 examples/offline_inference/audio_language.py --model-type whisper
@@ -3,7 +3,6 @@ depends_on:
- image-build
steps:
- label: Distributed Model Tests (2 GPUs)
key: distributed-model-tests-2-gpus
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
num_devices: 2
+9 -19
View File
@@ -3,9 +3,7 @@ depends_on:
- image-build
steps:
- label: Language Models Tests (Standard)
key: language-models-tests-standard
timeout_in_minutes: 25
device: h200_18gb
source_file_dependencies:
- vllm/
- tests/models/language
@@ -17,7 +15,6 @@ steps:
torch_nightly: {}
- label: Language Models Tests (Extra Standard) %N
key: language-models-tests-extra-standard
timeout_in_minutes: 45
source_file_dependencies:
- vllm/model_executor/models/
@@ -34,7 +31,6 @@ steps:
torch_nightly: {}
- label: Language Models Tests (Hybrid) %N
key: language-models-tests-hybrid
timeout_in_minutes: 75
source_file_dependencies:
- vllm/
@@ -49,18 +45,8 @@ steps:
parallelism: 2
mirror:
torch_nightly: {}
amd:
device: mi325_1
depends_on:
- image-build-amd
commands:
- uv pip install --system --no-build-isolation 'git+https://github.com/AndreasKaratzas/mamba@fix-rocm-7.0-warp-size-constexpr'
- 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
- label: Language Models Test (Extended Generation) # 80min
device: h200_35gb
key: language-models-test-extended-generation
timeout_in_minutes: 110
optional: true
source_file_dependencies:
@@ -72,9 +58,17 @@ steps:
- 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 '(not core_model) and (not hybrid_model)'
mirror:
amd:
device: mi325_1
depends_on:
- image-build-amd
commands:
- uv pip install --system --no-build-isolation 'git+https://github.com/AndreasKaratzas/mamba@fix-rocm-7.0-warp-size-constexpr'
- 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 '(not core_model) and (not hybrid_model)'
- label: Language Models Test (PPL)
key: language-models-test-ppl
timeout_in_minutes: 110
device: h200_18gb
optional: true
@@ -85,8 +79,6 @@ steps:
- pytest -v -s models/language/generation_ppl_test
- label: Language Models Test (Extended Pooling) # 36min
device: h200_35gb
key: language-models-test-extended-pooling
timeout_in_minutes: 50
optional: true
source_file_dependencies:
@@ -97,12 +89,10 @@ steps:
mirror:
amd:
device: mi325_1
timeout_in_minutes: 100
depends_on:
- image-build-amd
- label: Language Models Test (MTEB)
key: language-models-test-mteb
timeout_in_minutes: 110
device: h200_18gb
optional: true
+6 -18
View File
@@ -3,7 +3,6 @@ depends_on:
- image-build
steps:
- label: "Multi-Modal Models (Standard) 1: qwen2"
key: multi-modal-models-standard-1-qwen2
timeout_in_minutes: 45
device: h200_18gb
source_file_dependencies:
@@ -20,7 +19,6 @@ steps:
- image-build-amd
- label: "Multi-Modal Models (Standard) 2: qwen3 + gemma"
key: multi-modal-models-standard-2-qwen3-gemma
timeout_in_minutes: 45
device: h200_18gb
source_file_dependencies:
@@ -30,7 +28,6 @@ steps:
- 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_qwen2_5_vl.py -m core_model
- pytest -v -s models/multimodal/generation/test_vit_cudagraph.py -m core_model
mirror:
amd:
device: mi325_1
@@ -38,8 +35,6 @@ steps:
- image-build-amd
- label: "Multi-Modal Models (Standard) 3: llava + qwen2_vl"
device: h200_35gb
key: multi-modal-models-standard-3-llava-qwen2-vl
timeout_in_minutes: 45
source_file_dependencies:
- vllm/
@@ -55,8 +50,6 @@ steps:
- image-build-amd
- label: "Multi-Modal Models (Standard) 4: other + whisper"
device: h200_35gb
key: multi-modal-models-standard-4-other-whisper
timeout_in_minutes: 45
source_file_dependencies:
- vllm/
@@ -66,10 +59,14 @@ steps:
- 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
- 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
mirror:
amd:
device: mi325_1
depends_on:
- image-build-amd
- label: Multi-Modal Processor (CPU)
key: multi-modal-processor-cpu
depends_on:
depends_on:
- image-build-cpu
timeout_in_minutes: 60
source_file_dependencies:
@@ -82,7 +79,6 @@ steps:
- 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: 60
device: h200_18gb
source_file_dependencies:
@@ -94,8 +90,6 @@ steps:
- 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: 70
working_dir: "/vllm-workspace/.buildkite/lm-eval-harness"
source_file_dependencies:
@@ -106,7 +100,6 @@ steps:
- pytest -s -v test_lm_eval_correctness.py --config-list-file=configs/models-mm-small.txt --tp-size=1
- label: Multi-Modal Models (Extended Generation 1)
key: multi-modal-models-extended-generation-1
optional: true
source_file_dependencies:
- vllm/
@@ -123,8 +116,6 @@ steps:
- image-build-amd
- label: Multi-Modal Models (Extended Generation 2)
device: h200_35gb
key: multi-modal-models-extended-generation-2
optional: true
source_file_dependencies:
- vllm/
@@ -134,8 +125,6 @@ steps:
- pytest -v -s models/multimodal/generation/test_common.py -m 'split(group=0) and not core_model'
- label: Multi-Modal Models (Extended Generation 3)
device: h200_35gb
key: multi-modal-models-extended-generation-3
optional: true
source_file_dependencies:
- vllm/
@@ -145,7 +134,6 @@ steps:
- pytest -v -s models/multimodal/generation/test_common.py -m 'split(group=1) and not core_model'
- label: Multi-Modal Models (Extended Pooling)
key: multi-modal-models-extended-pooling
optional: true
device: h200_18gb
source_file_dependencies:
-1
View File
@@ -3,7 +3,6 @@ depends_on:
- image-build
steps:
- label: Plugin Tests (2 GPUs)
key: plugin-tests-2-gpus
timeout_in_minutes: 60
working_dir: "/vllm-workspace/tests"
num_devices: 2
+5 -127
View File
@@ -3,34 +3,9 @@ depends_on:
- image-build
steps:
- label: PyTorch Compilation Unit Tests
device: h200_35gb
key: pytorch-compilation-unit-tests
timeout_in_minutes: 10
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/
- vllm/
- tests/compile
commands:
# Run unit tests defined directly under compile/,
@@ -43,99 +18,27 @@ steps:
- "find compile/ -maxdepth 1 -name 'test_*.py' -print0 | xargs -0 -n1 -I{} pytest -s -v '{}'"
- label: PyTorch Compilation Unit Tests (H100)
key: pytorch-compilation-unit-tests-h100
timeout_in_minutes: 30
device: h100
num_devices: 1
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/
- vllm/
- tests/compile/h100/
commands:
- "find compile/h100/ -name 'test_*.py' -print0 | xargs -0 -n1 -I{} pytest -s -v '{}'"
- label: PyTorch Compilation Passes Unit Tests
key: pytorch-compilation-passes-unit-tests
timeout_in_minutes: 20
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/
- vllm/
- tests/compile/passes
commands:
- pytest -s -v compile/passes --ignore compile/passes/distributed
- label: PyTorch Fullgraph Smoke Test
key: pytorch-fullgraph-smoke-test
timeout_in_minutes: 35
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/
- vllm/
- tests/compile
commands:
# Run smoke tests under fullgraph directory, except test_full_graph.py
@@ -145,41 +48,16 @@ steps:
- "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: 30
device: h200_18gb
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/
- vllm/
- tests/compile
commands:
# fp8 kv scales not supported on sm89, tested on Blackwell instead
- pytest -v -s compile/fullgraph/test_full_graph.py -k 'not test_fp8_kv_scale_compile'
- label: Pytorch Nightly Dependency Override Check # 2min
key: pytorch-nightly-dependency-override-check
# if this test fails, it means the nightly torch version is not compatible with some
# of the dependencies. Please check the error message and add the package to whitelist
# in /vllm/tools/pre_commit/generate_nightly_torch_test.py
+1 -4
View File
@@ -3,7 +3,6 @@ depends_on:
- image-build
steps:
- label: Quantization
key: quantization
timeout_in_minutes: 90
source_file_dependencies:
- csrc/
@@ -22,10 +21,9 @@ steps:
- VLLM_TEST_FORCE_LOAD_FORMAT=auto pytest -v -s quantization/ --ignore quantization/test_blackwell_moe.py
- label: Quantized MoE Test (B200)
key: quantized-moe-test-b200
timeout_in_minutes: 60
working_dir: "/vllm-workspace/"
device: b200-k8s
device: b200
source_file_dependencies:
- tests/quantization/test_blackwell_moe.py
- vllm/model_executor/models/deepseek_v2.py
@@ -40,7 +38,6 @@ steps:
- pytest -s -v tests/quantization/test_blackwell_moe.py
- label: Quantized Models Test
key: quantized-models-test
timeout_in_minutes: 60
source_file_dependencies:
- vllm/model_executor/layers/quantization
-1
View File
@@ -3,7 +3,6 @@ depends_on:
- image-build
steps:
- label: Ray Dependency Compatibility Check
key: ray-dependency-compatibility-check
# Informational only — does not block the pipeline.
# If this fails, it means the PR introduces a dependency that
# conflicts with Ray's dependency constraints.
-107
View File
@@ -1,107 +0,0 @@
group: Rust Frontend E2E
depends_on:
- image-build
steps:
- label: Rust Frontend OpenAI Coverage
timeout_in_minutes: 90
device: h200_18gb
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- rust/
- vllm/benchmarks/
- vllm/entrypoints/openai/
- vllm/entrypoints/serve/
- vllm/v1/sample/
- 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/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/v1/sample/test_logprobs_e2e.py
commands:
- 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
# - 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"
# - 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: 60
device: h200_18gb
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- rust/
- vllm/entrypoints/openai/
- vllm/entrypoints/serve/
- vllm/v1/engine/
- tests/utils.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
commands:
- export VLLM_USE_RUST_FRONTEND=1
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
# - 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"
- 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
- label: Rust Frontend Core Correctness
timeout_in_minutes: 30
device: h200_18gb
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- rust/
- vllm/entrypoints/openai/
- tests/utils.py
- tests/entrypoints/openai/correctness/test_lmeval.py
commands:
- 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
timeout_in_minutes: 60
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- rust/
- vllm/entrypoints/openai/
- vllm/tool_parsers/
- tests/utils.py
- tests/tool_use/
commands:
- 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: 30
num_devices: 4
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- rust/
- vllm/distributed/
- vllm/engine/
- vllm/executor/
- vllm/v1/engine/
- vllm/v1/worker/
- tests/utils.py
- tests/v1/distributed/test_internal_lb_dp.py
commands:
- export VLLM_USE_RUST_FRONTEND=1
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- export NCCL_CUMEM_HOST_ENABLE=0
- TP_SIZE=1 DP_SIZE=4 pytest -v -s v1/distributed/test_internal_lb_dp.py -k "not 4 and not server_info"
@@ -1,30 +0,0 @@
group: Rust Frontend Cargo
depends_on: []
steps:
- label: Rust Frontend Cargo Style + Clippy
key: rust-frontend-cargo-style-clippy
depends_on: []
timeout_in_minutes: 30
device: cpu-medium
no_plugin: true
source_file_dependencies:
- rust/
- rust-toolchain.toml
- .buildkite/test_areas/rust_frontend_cargo.yaml
- .buildkite/scripts/run-rust-frontend-cargo-ci.sh
commands:
- .buildkite/scripts/run-rust-frontend-cargo-ci.sh style-clippy
- label: Rust Frontend Cargo Tests
key: rust-frontend-cargo-tests
depends_on: []
timeout_in_minutes: 30
device: cpu-medium
no_plugin: true
source_file_dependencies:
- rust/
- rust-toolchain.toml
- .buildkite/test_areas/rust_frontend_cargo.yaml
- .buildkite/scripts/run-rust-frontend-cargo-ci.sh
commands:
- .buildkite/scripts/run-rust-frontend-cargo-ci.sh test
+2 -7
View File
@@ -3,23 +3,18 @@ depends_on:
- image-build
steps:
- label: Samplers Test
device: h200_35gb
key: samplers-test
timeout_in_minutes: 75
source_file_dependencies:
- vllm/model_executor/layers
- vllm/sampling_metadata.py
- tests/samplers
- tests/conftest.py
- vllm/entrypoints/generate/beam_search
commands:
# VLLM_USE_FLASHINFER_SAMPLER defaults to 1 now, so we need to pin both
# values explicitly to still cover the PyTorch-native (Triton) path.
- VLLM_USE_FLASHINFER_SAMPLER=0 pytest -v -s samplers
- pytest -v -s samplers
- VLLM_USE_FLASHINFER_SAMPLER=1 pytest -v -s samplers
mirror:
amd:
device: mi250_1
device: mi325_1
depends_on:
- image-build-amd
commands:
-69
View File
@@ -3,7 +3,6 @@ depends_on:
- image-build
steps:
- label: Spec Decode Eagle
key: spec-decode-eagle
timeout_in_minutes: 30
device: h200_18gb
source_file_dependencies:
@@ -13,46 +12,18 @@ steps:
commands:
- pytest -v -s v1/e2e/spec_decode -k "eagle_correctness"
- label: Spec Decode Eagle Nightly B200
key: spec-decode-eagle-nightly-b200
timeout_in_minutes: 30
device: b200-k8s
optional: true
source_file_dependencies:
- vllm/v1/spec_decode/
- vllm/v1/worker/gpu/spec_decode/
- tests/v1/e2e/spec_decode/
commands:
- pytest -v -s v1/e2e/spec_decode -k "eagle_correctness"
- label: Spec Decode Speculators + MTP
key: spec-decode-speculators-mtp
timeout_in_minutes: 30
device: h200_18gb
source_file_dependencies:
- vllm/v1/spec_decode/
- vllm/v1/worker/gpu/spec_decode/
- vllm/v1/attention/backends/
- vllm/transformers_utils/configs/speculators/
- tests/v1/e2e/spec_decode/
commands:
- pytest -v -s v1/e2e/spec_decode -k "speculators or mtp_correctness"
- label: Spec Decode Speculators + MTP Nightly B200
key: spec-decode-speculators-mtp-nightly-b200
timeout_in_minutes: 30
device: b200-k8s
optional: true
source_file_dependencies:
- vllm/v1/spec_decode/
- vllm/v1/worker/gpu/spec_decode/
- vllm/transformers_utils/configs/speculators/
- tests/v1/e2e/spec_decode/
commands:
- pytest -v -s v1/e2e/spec_decode -k "speculators or mtp_correctness"
- label: Spec Decode Ngram + Suffix
key: spec-decode-ngram-suffix
timeout_in_minutes: 30
device: h200_18gb
source_file_dependencies:
@@ -63,7 +34,6 @@ steps:
- pytest -v -s v1/e2e/spec_decode -k "ngram or suffix"
- label: Spec Decode Draft Model
key: spec-decode-draft-model
timeout_in_minutes: 30
device: h200_18gb
source_file_dependencies:
@@ -72,42 +42,3 @@ steps:
- tests/v1/e2e/spec_decode/
commands:
- pytest -v -s v1/e2e/spec_decode -k "draft_model or no_sync or batch_inference"
- label: Spec Decode Draft Model Nightly B200
key: spec-decode-draft-model-nightly-b200
timeout_in_minutes: 30
device: b200-k8s
optional: true
source_file_dependencies:
- vllm/v1/spec_decode/
- vllm/v1/worker/gpu/spec_decode/
- tests/v1/e2e/spec_decode/
commands:
- pytest -v -s v1/e2e/spec_decode -k "draft_model or no_sync or batch_inference"
- label: Speculators Correctness
key: speculators-correctness
timeout_in_minutes: 60
device: h100
optional: true
num_devices: 1
source_file_dependencies:
- vllm/v1/spec_decode/
- vllm/model_executor/models/qwen3_dflash.py
- tests/v1/spec_decode/test_speculators_correctness.py
commands:
- export VLLM_ALLOW_INSECURE_SERIALIZATION=1
- pytest -v -s v1/spec_decode/test_speculators_correctness.py -m slow_test
- label: Spec Decode MTP hybrid (B200)
timeout_in_minutes: 30
device: b200-k8s
optional: true
source_file_dependencies:
- vllm/v1/spec_decode/
- vllm/v1/worker/gpu/spec_decode/
- vllm/model_executor/models/qwen3_5.py
- vllm/model_executor/models/qwen3_5_mtp.py
- tests/v1/e2e/spec_decode/
commands:
- pytest -v -s v1/e2e/spec_decode -k "qwen3_5-hybrid"
@@ -3,7 +3,6 @@ depends_on:
- image-build
steps:
- label: Weight Loading Multiple GPU # 33min
key: weight-loading-multiple-gpu
timeout_in_minutes: 45
working_dir: "/vllm-workspace/tests"
num_devices: 2
-2
View File
@@ -2,7 +2,6 @@
/build
dist
vllm/*.so
vllm/vllm-rs
# Byte-compiled / optimized / DLL files
__pycache__/
@@ -32,4 +31,3 @@ share/python-wheels/
.installed.cfg
*.egg
MANIFEST
rust/target/
+26 -47
View File
@@ -6,8 +6,8 @@
/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
/vllm/model_executor/layers/quantization @mgoin @robertgshaw2-redhat @tlrmchlsmth @yewentao256 @pavanimajety @zyongye
/vllm/model_executor/layers/fused_moe @mgoin @pavanimajety
/vllm/model_executor/layers/quantization @mgoin @robertgshaw2-redhat @tlrmchlsmth @yewentao256 @pavanimajety
/vllm/model_executor/layers/mamba @tdoublep @tomeras91
/vllm/model_executor/layers/mamba/gdn_linear_attn.py @tdoublep @ZJY0516 @vadiklyutiy
/vllm/model_executor/layers/rotary_embedding.py @vadiklyutiy
@@ -18,8 +18,7 @@
/vllm/kernels/helion @ProExpertProg @zou3519
/vllm/multimodal @DarkLight1337 @ywang96 @NickLucche @tjtanaa
/vllm/vllm_flash_attn @LucasWilkinson @MatthewBonanni
/CMakeLists.txt @tlrmchlsmth @LucasWilkinson @Harry-Chen
/cmake @tlrmchlsmth @LucasWilkinson @Harry-Chen
CMakeLists.txt @tlrmchlsmth @LucasWilkinson
# Any change to the VllmConfig changes can have a large user-facing impact,
# so spam a lot of people
@@ -31,8 +30,8 @@
/vllm/entrypoints/cli @hmellor @mgoin @DarkLight1337 @russellb
/vllm/entrypoints/mcp @heheda12345
/vllm/entrypoints/openai @aarnphm @chaunceyjiang @DarkLight1337 @russellb
/vllm/entrypoints/speech_to_text/realtime @njhill
/vllm/entrypoints/speech_to_text @NickLucche
/vllm/entrypoints/openai/realtime @njhill
/vllm/entrypoints/openai/speech_to_text @NickLucche
/vllm/entrypoints/pooling @noooop
/vllm/entrypoints/sagemaker @DarkLight1337
/vllm/entrypoints/serve @njhill
@@ -40,20 +39,13 @@
/vllm/entrypoints/chat_utils.py @DarkLight1337
/vllm/entrypoints/llm.py @DarkLight1337
# Rust Frontend
/rust/ @BugenZhao @njhill
/build_rust.sh @BugenZhao @njhill
/rust-toolchain.toml @BugenZhao @njhill
/.buildkite/test_areas/rust* @BugenZhao @njhill
# Input/Output Processing
/vllm/sampling_params.py @njhill @NickLucche
/vllm/pooling_params.py @noooop @DarkLight1337
/vllm/tokenizers @DarkLight1337 @njhill
/vllm/renderers @DarkLight1337 @njhill
/vllm/reasoning @aarnphm @chaunceyjiang @sfeng33 @bbrowning
/vllm/tool_parsers @aarnphm @chaunceyjiang @sfeng33 @bbrowning
/vllm/parser @aarnphm @chaunceyjiang @sfeng33 @bbrowning
/vllm/reasoning @aarnphm @chaunceyjiang
/vllm/tool_parsers @aarnphm @chaunceyjiang
# vLLM V1
/vllm/v1/attention @LucasWilkinson @MatthewBonanni
@@ -77,24 +69,18 @@
/vllm/v1/worker/gpu @WoosukKwon @njhill
/vllm/v1/worker/gpu/kv_connector.py @orozery
# CI & building
/.buildkite @Harry-Chen @khluu
/docker/Dockerfile @Harry-Chen @khluu
/pyproject.toml @khluu
/setup.py @khluu
# Test ownership
/.buildkite/lm-eval-harness @mgoin
/.buildkite/lm-eval-harness @mgoin
/tests/distributed/test_multi_node_assignment.py @youkaichao
/tests/distributed/test_pipeline_parallel.py @youkaichao
/tests/distributed/test_same_node.py @youkaichao
/tests/entrypoints @DarkLight1337 @robertgshaw2-redhat @aarnphm @NickLucche @AndreasKaratzas
/tests/evals @mgoin @vadiklyutiy @AndreasKaratzas
/tests/kernels @mgoin @tlrmchlsmth @WoosukKwon @yewentao256 @zyongye @AndreasKaratzas
/tests/entrypoints @DarkLight1337 @robertgshaw2-redhat @aarnphm @NickLucche
/tests/evals @mgoin @vadiklyutiy
/tests/kernels @mgoin @tlrmchlsmth @WoosukKwon @yewentao256
/tests/kernels/ir @ProExpertProg @tjtanaa
/tests/models @DarkLight1337 @ywang96 @AndreasKaratzas
/tests/models @DarkLight1337 @ywang96
/tests/multimodal @DarkLight1337 @ywang96 @NickLucche
/tests/quantization @mgoin @robertgshaw2-redhat @yewentao256 @pavanimajety @zyongye @AndreasKaratzas
/tests/quantization @mgoin @robertgshaw2-redhat @yewentao256 @pavanimajety
/tests/test_inputs.py @DarkLight1337 @ywang96
/tests/entrypoints/llm/test_struct_output_generate.py @mgoin @russellb @aarnphm
/tests/v1/structured_output @mgoin @russellb @aarnphm
@@ -105,10 +91,7 @@
/tests/v1/kv_connector/nixl_integration @NickLucche
/tests/v1/kv_connector @ApostaC @orozery
/tests/v1/kv_offload @ApostaC @orozery
/tests/v1/determinism @yewentao256
/tests/reasoning @aarnphm @chaunceyjiang @sfeng33 @bbrowning
/tests/tool_parsers @aarnphm @chaunceyjiang @sfeng33 @bbrowning
/tests/tool_use @aarnphm @chaunceyjiang @sfeng33 @bbrowning
/tests/v1/determinism @yewentao256
# Transformers modeling backend
/vllm/model_executor/models/transformers @hmellor
@@ -160,10 +143,6 @@ mkdocs.yaml @hmellor
# MTP-specific files
/vllm/model_executor/models/deepseek_mtp.py @luccafong
# DeepseekV4-specific files
/vllm/models/deepseek_v4 @zyongye
/vllm/model_executor/layers/sparse_attn_indexer.py @zyongye
# Mistral-specific files
/vllm/model_executor/models/mistral*.py @patrickvonplaten
/vllm/model_executor/models/mixtral*.py @patrickvonplaten
@@ -178,21 +157,21 @@ mkdocs.yaml @hmellor
/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
/docker/Dockerfile.rocm* @tjtanaa @dllehr-amd @AndreasKaratzas
/vllm/v1/attention/backends/rocm*.py @tjtanaa @dllehr-amd
/vllm/v1/attention/backends/mla/rocm*.py @tjtanaa @dllehr-amd
/vllm/v1/attention/ops/rocm*.py @tjtanaa @dllehr-amd
/vllm/model_executor/layers/fused_moe/rocm*.py @tjtanaa @dllehr-amd
/csrc/rocm @tjtanaa @dllehr-amd
/requirements/*rocm* @tjtanaa @AndreasKaratzas
/tests/**/*rocm* @tjtanaa @AndreasKaratzas
/vllm/**/*rocm* @tjtanaa
/docker/Dockerfile.rocm* @gshtras @tjtanaa
/vllm/v1/attention/backends/rocm*.py @gshtras @tjtanaa
/vllm/v1/attention/backends/mla/rocm*.py @gshtras @tjtanaa
/vllm/v1/attention/ops/rocm*.py @gshtras @tjtanaa
/vllm/model_executor/layers/fused_moe/rocm*.py @gshtras @tjtanaa
/csrc/rocm @gshtras @tjtanaa
/requirements/*rocm* @tjtanaa
/tests/**/*rocm* @tjtanaa
/docs/**/*rocm* @tjtanaa
/vllm/**/*quark* @tjtanaa
/tests/**/*quark* @tjtanaa @AndreasKaratzas
/tests/**/*quark* @tjtanaa
/docs/**/*quark* @tjtanaa
/vllm/**/*aiter* @tjtanaa @AndreasKaratzas
/tests/**/*aiter* @tjtanaa @AndreasKaratzas
/vllm/**/*aiter* @tjtanaa
/tests/**/*aiter* @tjtanaa
# TPU
/vllm/v1/worker/tpu* @NickLucche
+1
View File
@@ -15,6 +15,7 @@ PLEASE FILL IN THE PR DESCRIPTION HERE ENSURING ALL CHECKLIST ITEMS (AT THE BOTT
- [ ] The test plan, such as providing test command.
- [ ] The test results, such as pasting the results comparison before and after, or e2e results
- [ ] (Optional) The necessary documentation update, such as updating `supported_models.md` and `examples` for a new model.
- [ ] (Optional) Release notes update. If your change is user facing, please update the release notes draft in the [Google Doc](https://docs.google.com/document/d/1YyVqrgX4gHTtrstbq8oWUImOyPCKSGnJ7xtTpmXzlRs/edit?tab=t.0).
</details>
**BEFORE SUBMITTING, PLEASE READ <https://docs.vllm.ai/en/latest/contributing>** (anything written below this line will be removed by GitHub Actions)
+12 -18
View File
@@ -103,19 +103,6 @@ pull_request_rules:
add:
- frontend
- name: label-rust
description: Automatically apply rust label
conditions:
- label != stale
- or:
- files~=(?i)rust
- title~=(?i)rust
- title~=(?i)vllm-rs
actions:
label:
add:
- rust
- name: label-llama
description: Automatically apply llama label
conditions:
@@ -275,7 +262,7 @@ pull_request_rules:
- files~=^docker/Dockerfile.xpu
- files~=^\\.buildkite/intel_jobs/
- files=\.buildkite/ci_config_intel.yaml
- files=vllm/model_executor/layers/fused_moe/experts/xpu_moe.py
- files=vllm/model_executor/layers/fused_moe/xpu_fused_moe.py
- files=vllm/model_executor/kernels/linear/mixed_precision/xpu.py
- files=vllm/model_executor/kernels/linear/mxfp8/xpu.py
- files=vllm/model_executor/kernels/linear/scaled_mm/xpu.py
@@ -321,7 +308,8 @@ pull_request_rules:
- files=benchmarks/benchmark_serving_structured_output.py
- files=benchmarks/run_structured_output_benchmark.sh
- files=docs/features/structured_outputs.md
- files=^examples/features/structured_outputs/
- files=examples/offline_inference/structured_outputs.py
- files=examples/online_serving/structured_outputs/structured_outputs.py
- files~=^tests/v1/structured_output/
- files=tests/entrypoints/llm/test_struct_output_generate.py
- files~=^vllm/v1/structured_output/
@@ -337,7 +325,7 @@ pull_request_rules:
- or:
- files~=^vllm/v1/spec_decode/
- files~=^tests/v1/spec_decode/
- files=^examples/features/speculative_decoding/
- files~=^examples/.*(spec_decode|mlpspeculator|eagle|speculation).*\.py
- files~=^vllm/model_executor/models/.*eagle.*\.py
- files=vllm/model_executor/models/mlp_speculator.py
- files~=^vllm/transformers_utils/configs/(eagle|medusa|mlp_speculator)\.py
@@ -401,7 +389,11 @@ pull_request_rules:
- files~=^tests/entrypoints/anthropic/.*tool.*
- files~=^vllm/tool_parsers/
- files=docs/features/tool_calling.md
- files~=^examples/tool_calling/
- files~=^examples/tool_chat_*
- files=examples/offline_inference/chat_with_tools.py
- files=examples/online_serving/openai_chat_completion_client_with_tools_required.py
- files=examples/online_serving/openai_chat_completion_tool_calls_with_reasoning.py
- files=examples/online_serving/openai_chat_completion_client_with_tools.py
actions:
label:
add:
@@ -490,7 +482,9 @@ pull_request_rules:
conditions:
- label != stale
- or:
- files~=^examples/disaggregated/
- files~=^examples/online_serving/disaggregated[^/]*/.*
- files~=^examples/offline_inference/disaggregated[^/]*/.*
- files~=^examples/others/lmcache/
- files~=^tests/v1/kv_connector/
- files~=^vllm/distributed/kv_transfer/
- title~=(?i)\bP/?D\b
+1 -1
View File
@@ -10,7 +10,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Add label
uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8.0.0
with:
script: |
github.rest.issues.addLabels({
+3 -3
View File
@@ -14,7 +14,7 @@ jobs:
steps:
- name: Label issues based on keywords
id: label-step
uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8.0.0
with:
script: |
// Configuration: Add new labels and keywords here
@@ -315,7 +315,7 @@ jobs:
- name: CC users for labeled issues
if: steps.label-step.outputs.labels_added != '[]'
uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8.0.0
with:
script: |
// Configuration: Map labels to GitHub users to CC
@@ -392,7 +392,7 @@ jobs:
- name: Request missing ROCm info from issue author
if: contains(steps.label-step.outputs.labels_added, 'rocm') && contains(toJSON(github.event.issue.labels.*.name), 'bug')
uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8.0.0
with:
script: |
const body = (context.payload.issue.body || '').toLowerCase();
-1
View File
@@ -45,7 +45,6 @@ jobs:
- name: Smoke test vllm serve
run: |
# Start server in background
VLLM_CPU_KVCACHE_SPACE=1 \
vllm serve Qwen/Qwen3-0.6B \
--max-model-len=2K \
--load-format=dummy \
+7 -7
View File
@@ -12,7 +12,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Update PR description
uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8.0.0
with:
script: |
const { owner, repo } = context.repo;
@@ -55,21 +55,21 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Post welcome comment for first-time contributors
uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8.0.0
with:
script: |
const { owner, repo } = context.repo;
const prAuthor = context.payload.pull_request.user.login;
const { data: searchResults } = await github.rest.search.issuesAndPullRequests({
q: `repo:${owner}/${repo} type:pr is:merged author:${prAuthor}`,
q: `repo:${owner}/${repo} type:pr author:${prAuthor}`,
per_page: 1,
});
const mergedPRCount = searchResults.total_count;
console.log(`Found ${mergedPRCount} merged PRs by ${prAuthor}`);
const authorPRCount = searchResults.total_count;
console.log(`Found ${authorPRCount} PRs by ${prAuthor}`);
if (mergedPRCount === 0) {
if (authorPRCount === 1) {
console.log(`Posting welcome comment for first-time contributor: ${prAuthor}`);
await github.rest.issues.createComment({
owner,
@@ -98,5 +98,5 @@ jobs:
].join('\n'),
});
} else {
console.log(`Skipping comment for ${prAuthor} - not a first-time contributor (${mergedPRCount} merged PRs)`);
console.log(`Skipping comment for ${prAuthor} - not their first PR (${authorPRCount} PRs found)`);
}
+13 -4
View File
@@ -16,11 +16,15 @@ permissions:
jobs:
pre-run-check:
if: github.event_name == 'pull_request'
if: >-
github.event_name == 'pull_request' &&
(github.event.action != 'labeled' ||
github.event.label.name == 'ready' ||
github.event.label.name == 'verified')
runs-on: ubuntu-latest
steps:
- name: Check PR label and author merge count
uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8.0.0
with:
script: |
const { data: pr } = await github.rest.pulls.get({
@@ -45,11 +49,16 @@ jobs:
pre-commit:
needs: pre-run-check
if: always() && (needs.pre-run-check.result == 'success' || needs.pre-run-check.result == 'skipped')
if: >-
always() &&
(github.event.action != 'labeled' ||
github.event.label.name == 'ready' ||
github.event.label.name == 'verified') &&
(needs.pre-run-check.result == 'success' || needs.pre-run-check.result == 'skipped')
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8 # v6.0.1
- uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
- uses: actions/setup-python@83679a892e2d95755f2dac6acb0bfd1e9ac5d548 # v6.1.0
with:
python-version: "3.12"
- run: echo "::add-matcher::.github/workflows/matchers/actionlint.json"
+1 -4
View File
@@ -9,15 +9,12 @@ PATH=${cuda_home}/bin:$PATH
LD_LIBRARY_PATH=${cuda_home}/lib64:$LD_LIBRARY_PATH
# Install requirements
if [ "$(echo $2 | cut -d. -f1)" = "12" ]; then
sed -i 's/^nvidia-cutlass-dsl\[cu13\]>=/nvidia-cutlass-dsl>=/' requirements/cuda.txt
fi
$python_executable -m pip install -r requirements/build/cuda.txt -r requirements/cuda.txt
# Limit the number of parallel jobs to avoid OOM
export MAX_JOBS=1
# Make sure release wheels are built for the following architectures
export TORCH_CUDA_ARCH_LIST="7.5 8.0 8.6 8.9 9.0 10.0 12.0+PTX"
export TORCH_CUDA_ARCH_LIST="7.0 7.5 8.0 8.6 8.9 9.0+PTX"
bash tools/check_repo.sh
-4
View File
@@ -26,9 +26,6 @@ __pycache__/
# C extensions
*.so
# Rust binaries
vllm/vllm-rs
# Distribution / packaging
.Python
build/
@@ -240,7 +237,6 @@ ep_kernels_workspace/
# Allow tracked library source folders under submodules (e.g., benchmarks/lib)
!vllm/benchmarks/lib/
!.buildkite/scripts/lib/
# Generated gRPC protobuf files (compiled at build time from vllm_engine.proto)
vllm/grpc/vllm_engine_pb2.py
+1 -43
View File
@@ -21,7 +21,7 @@ repos:
rev: v21.1.2
hooks:
- id: clang-format
exclude: 'csrc/(moe/topk_softmax_kernels.cu|libtorch_stable/quantization/gguf/(ggml-common.h|dequantize.cuh|vecdotq.cuh|mmq.cuh|mmvq.cuh))|vllm/third_party/.*'
exclude: 'csrc/(moe/topk_softmax_kernels.cu|quantization/gguf/(ggml-common.h|dequantize.cuh|vecdotq.cuh|mmq.cuh|mmvq.cuh))|vllm/third_party/.*'
types_or: [c++, cuda]
args: [--style=file, --verbose]
- repo: https://github.com/DavidAnson/markdownlint-cli2
@@ -131,16 +131,6 @@ repos:
--python-version, "3.12",
]
files: ^requirements/(common|xpu|test/xpu)\.(in|txt)$
- id: pip-compile
alias: pip-compile-docs
name: pip-compile-docs
args: [
requirements/docs.in,
-o, requirements/docs.txt,
--python-platform, x86_64-manylinux_2_28,
--python-version, "3.12",
]
files: ^requirements/docs\.(in|txt)$
- repo: local
hooks:
- id: format-torch-nightly-test
@@ -222,12 +212,6 @@ repos:
name: Update Dockerfile dependency graph
entry: tools/pre_commit/update-dockerfile-graph.sh
language: script
- id: test-nonroot-entrypoint
name: Test non-root entrypoint wrapper
entry: bash docker/entrypoints/test_vllm_nonroot_entrypoint.sh
language: system
pass_filenames: false
files: ^docker/entrypoints/(vllm-nonroot-entrypoint|test_vllm_nonroot_entrypoint)\.sh$
- id: check-forbidden-imports
name: Check for forbidden imports
entry: python tools/pre_commit/check_forbidden_imports.py
@@ -262,32 +246,6 @@ repos:
entry: python tools/pre_commit/check_boolean_context_manager.py
language: python
types: [python]
# Rust hooks. These shell out to `cargo`; tools/pre_commit/rust-check.sh
# skips with a warning when cargo is not installed.
- id: rust-cargo-autoinherit
name: Rust - Normalize Cargo manifests with autoinherit
entry: tools/pre_commit/rust-check.sh autoinherit --prefer-simple-dotted
language: script
pass_filenames: false
require_serial: true
stages: [pre-commit] # Only run locally as Buildkite will cover this
files: ^rust/(Cargo\.toml|src/.*/Cargo\.toml)$
- id: rust-cargo-sort
name: Rust - Sort Cargo manifest sections
entry: tools/pre_commit/rust-check.sh sort --workspace
language: script
pass_filenames: false
require_serial: true
stages: [pre-commit] # Only run locally as Buildkite will cover this
files: ^rust/(Cargo\.toml|src/.*/Cargo\.toml)$
- id: rust-cargo-fmt
name: Rust - Format code
entry: tools/pre_commit/rust-check.sh fmt
language: script
pass_filenames: false
require_serial: true
stages: [pre-commit] # Only run locally as Buildkite will cover this
files: ^rust/.*(\.rs|Cargo\.toml|rustfmt\.toml)$
# Keep `suggestion` last
- id: suggestion
name: Suggestion
+1 -1
View File
@@ -9,8 +9,8 @@ build:
python: "3.12"
jobs:
post_checkout:
# - bash docs/maybe_skip_pr_build.sh
- git fetch origin main --unshallow --no-tags --filter=blob:none || true
- bash docs/pre_run_check.sh
pre_create_environment:
- pip install uv
create_environment:
View File
-2
View File
@@ -101,8 +101,6 @@ pre-commit run ruff-check --all-files
pre-commit run mypy-3.10 --all-files --hook-stage manual
```
The line length limit for Python code is 88 characters. If you are not sure, use pre-commit to check.
### Commit messages
Add attribution using commit trailers such as `Co-authored-by:` (other projects use `Assisted-by:` or `Generated-by:`). For example:
+133 -243
View File
@@ -13,12 +13,8 @@ cmake_minimum_required(VERSION 3.26)
# cmake --install . --component _C
project(vllm_extensions LANGUAGES CXX)
set(CMAKE_CXX_STANDARD 20)
set(CMAKE_CXX_STANDARD 17)
set(CMAKE_CXX_STANDARD_REQUIRED ON)
set(CMAKE_CUDA_STANDARD 20)
set(CMAKE_CUDA_STANDARD_REQUIRED ON)
set(CMAKE_HIP_STANDARD 20)
set(CMAKE_HIP_STANDARD_REQUIRED ON)
# CUDA by default, can be overridden by using -DVLLM_TARGET_DEVICE=... (used by setup.py)
@@ -38,10 +34,10 @@ install(CODE "set(CMAKE_INSTALL_LOCAL_ONLY TRUE)" ALL_COMPONENTS)
# Supported python versions. These versions will be searched in order, the
# first match will be selected. These should be kept in sync with setup.py.
#
set(PYTHON_SUPPORTED_VERSIONS "3.10" "3.11" "3.12" "3.13" "3.14")
set(PYTHON_SUPPORTED_VERSIONS "3.10" "3.11" "3.12" "3.13")
# Supported AMD GPU architectures.
set(HIP_SUPPORTED_ARCHS "gfx906;gfx908;gfx90a;gfx942;gfx950;gfx1030;gfx1100;gfx1101;gfx1102;gfx1103;gfx1150;gfx1151;gfx1152;gfx1153;gfx1200;gfx1201")
set(HIP_SUPPORTED_ARCHS "gfx906;gfx908;gfx90a;gfx942;gfx950;gfx1030;gfx1100;gfx1101;gfx1150;gfx1151;gfx1152;gfx1153;gfx1200;gfx1201")
# ROCm installation prefix. Default to /opt/rocm but allow override via
# -DROCM_PATH=/your/rocm/path when invoking cmake.
@@ -98,35 +94,14 @@ find_package(Torch REQUIRED)
# This check must happen after find_package(Torch) because that's when CMAKE_CUDA_COMPILER_VERSION gets defined
if(DEFINED CMAKE_CUDA_COMPILER_VERSION AND
CMAKE_CUDA_COMPILER_VERSION VERSION_GREATER_EQUAL 13.0)
# starting from CUDA 12.9 and Blackwell (10.0), we use family-specific targets (10.0f, 12.0f, etc)
# to support the whole generation without specifying all sub-architectures
# see: https://developer.nvidia.com/blog/nvidia-blackwell-and-nvidia-cuda-12-9-introduce-family-specific-architecture-features/
set(CUDA_SUPPORTED_ARCHS "7.5;8.0;8.6;8.7;8.9;9.0;10.0;11.0;12.0")
set(CUDA_SUPPORTED_ARCHS "7.5;8.0;8.6;8.7;8.9;9.0;10.0;11.0;12.0;12.1")
elseif(DEFINED CMAKE_CUDA_COMPILER_VERSION AND
CMAKE_CUDA_COMPILER_VERSION VERSION_GREATER_EQUAL 12.8)
set(CUDA_SUPPORTED_ARCHS "7.5;8.0;8.6;8.7;8.9;9.0;10.0;10.1;10.3;12.0;12.1")
set(CUDA_SUPPORTED_ARCHS "7.0;7.2;7.5;8.0;8.6;8.7;8.9;9.0;10.0;10.1;12.0;12.1")
else()
set(CUDA_SUPPORTED_ARCHS "7.0;7.5;8.0;8.6;8.7;8.9;9.0")
set(CUDA_SUPPORTED_ARCHS "7.0;7.2;7.5;8.0;8.6;8.7;8.9;9.0")
endif()
#
# spinloop extension (pure CXX; must stay above the non-CUDA device branch so
# CPU builds define the target before the early return)
#
set(VLLM_SPINLOOP_EXT_SRC "csrc/spinloop.cpp")
set(SPINLOOP_COMPILE_FLAGS "")
if(CMAKE_SYSTEM_PROCESSOR MATCHES "x86_64|amd64")
list(APPEND SPINLOOP_COMPILE_FLAGS "-mmwaitx")
endif()
define_extension_target(
spinloop
DESTINATION vllm
LANGUAGE CXX
SOURCES ${VLLM_SPINLOOP_EXT_SRC}
COMPILE_FLAGS ${SPINLOOP_COMPILE_FLAGS}
USE_SABI 3.11
WITH_SOABI)
#
# Forward the non-CUDA device extensions to external CMake scripts.
#
@@ -144,14 +119,14 @@ endif()
# Set up GPU language and check the torch version and warn if it isn't
# what is expected.
#
if (NOT HIP_FOUND AND NOT PYTORCH_FOUND_HIP AND CUDA_FOUND)
if (NOT HIP_FOUND AND CUDA_FOUND)
set(VLLM_GPU_LANG "CUDA")
if (NOT Torch_VERSION VERSION_EQUAL ${TORCH_SUPPORTED_VERSION_CUDA})
message(WARNING "Pytorch version ${TORCH_SUPPORTED_VERSION_CUDA} "
"expected for CUDA build, saw ${Torch_VERSION} instead.")
endif()
elseif(HIP_FOUND OR PYTORCH_FOUND_HIP)
elseif(HIP_FOUND)
set(VLLM_GPU_LANG "HIP")
# Importing torch recognizes and sets up some HIP/ROCm configuration but does
@@ -305,17 +280,34 @@ endif()
#
set(VLLM_EXT_SRC
"csrc/mamba/mamba_ssm/selective_scan_fwd.cu"
"csrc/cache_kernels.cu"
"csrc/cache_kernels_fused.cu"
"csrc/attention/paged_attention_v1.cu"
"csrc/attention/paged_attention_v2.cu"
"csrc/attention/merge_attn_states.cu"
"csrc/attention/vertical_slash_index.cu"
"csrc/pos_encoding_kernels.cu"
"csrc/activation_kernels.cu"
"csrc/layernorm_kernels.cu"
"csrc/fused_qknorm_rope_kernel.cu"
"csrc/layernorm_quant_kernels.cu"
"csrc/sampler.cu"
"csrc/topk.cu"
"csrc/cuda_view.cu"
"csrc/quantization/gptq/q_gemm.cu"
"csrc/quantization/w8a8/int8/scaled_quant.cu"
"csrc/quantization/w8a8/fp8/common.cu"
"csrc/quantization/fused_kernels/fused_layernorm_dynamic_per_token_quant.cu"
"csrc/quantization/fused_kernels/fused_silu_mul_block_quant.cu"
"csrc/quantization/gguf/gguf_kernel.cu"
"csrc/quantization/activation_kernels.cu"
"csrc/cuda_utils_kernels.cu"
"csrc/custom_all_reduce.cu"
"csrc/torch_bindings.cpp"
"csrc/fused_deepseek_v4_qnorm_rope_kv_insert_kernel.cu")
"csrc/torch_bindings.cpp")
if(VLLM_GPU_LANG STREQUAL "CUDA")
list(APPEND VLLM_EXT_SRC
"csrc/minimax_reduce_rms_kernel.cu")
list(APPEND VLLM_EXT_SRC "csrc/minimax_reduce_rms_kernel.cu")
SET(CUTLASS_ENABLE_HEADERS_ONLY ON CACHE BOOL "Enable only the header library")
@@ -350,6 +342,7 @@ if(VLLM_GPU_LANG STREQUAL "CUDA")
FetchContent_MakeAvailable(cutlass)
list(APPEND VLLM_EXT_SRC
"csrc/quantization/awq/gemm_kernels.cu"
"csrc/cutlass_extensions/common.cpp")
set_gencode_flags_for_srcs(
@@ -361,30 +354,16 @@ if(VLLM_GPU_LANG STREQUAL "CUDA")
# are not supported by Machete yet.
# marlin arches for fp16 output
# Family-conditional 12.0f (one cubin for SM12x family) requires CUDA >= 13.0;
# fall back to architecture-specific 12.0a;12.1a on CUDA < 13.0 (e.g. 12.8).
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 13.0)
cuda_archs_loose_intersection(MARLIN_ARCHS "8.0+PTX;12.0f" "${CUDA_ARCHS}")
else()
cuda_archs_loose_intersection(MARLIN_ARCHS "8.0+PTX;12.0a;12.1a" "${CUDA_ARCHS}")
endif()
cuda_archs_loose_intersection(MARLIN_ARCHS "8.0+PTX" "${CUDA_ARCHS}")
# marlin has limited support for turing
cuda_archs_loose_intersection(MARLIN_SM75_ARCHS "7.5" "${CUDA_ARCHS}")
# marlin arches for bf16 output (we need 9.0 for bf16 atomicAdd PTX)
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 13.0)
cuda_archs_loose_intersection(MARLIN_BF16_ARCHS "8.0+PTX;9.0+PTX;12.0f" "${CUDA_ARCHS}")
else()
cuda_archs_loose_intersection(MARLIN_BF16_ARCHS "8.0+PTX;9.0+PTX;12.0a;12.1a" "${CUDA_ARCHS}")
endif()
cuda_archs_loose_intersection(MARLIN_BF16_ARCHS "8.0+PTX;9.0+PTX" "${CUDA_ARCHS}")
# marlin arches for fp8 input
# - sm80 doesn't support fp8 computation
# - sm90 and sm100 don't support QMMA.16832.F32.E4M3.E4M3 SAAS instruction
# so we only enable fp8 computation for SM89 (e.g. RTX 40x0) and 12.0 (e.g. RTX 50x0)
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 13.0)
cuda_archs_loose_intersection(MARLIN_FP8_ARCHS "8.9;12.0f" "${CUDA_ARCHS}")
else()
cuda_archs_loose_intersection(MARLIN_FP8_ARCHS "8.9;12.0a;12.1a" "${CUDA_ARCHS}")
endif()
cuda_archs_loose_intersection(MARLIN_FP8_ARCHS "8.9;12.0;12.1" "${CUDA_ARCHS}")
# marlin arches for other files
cuda_archs_loose_intersection(MARLIN_OTHER_ARCHS "7.5;8.0+PTX" "${CUDA_ARCHS}")
@@ -495,6 +474,46 @@ if(VLLM_GPU_LANG STREQUAL "CUDA")
" in CUDA target architectures")
endif()
# Only build AllSpark kernels if we are building for at least some compatible archs.
cuda_archs_loose_intersection(ALLSPARK_ARCHS "8.0;8.6;8.7;8.9" "${CUDA_ARCHS}")
if (ALLSPARK_ARCHS)
set(ALLSPARK_SRCS
"csrc/quantization/gptq_allspark/allspark_repack.cu"
"csrc/quantization/gptq_allspark/allspark_qgemm_w8a16.cu")
set_gencode_flags_for_srcs(
SRCS "${ALLSPARK_SRCS}"
CUDA_ARCHS "${ALLSPARK_ARCHS}")
list(APPEND VLLM_EXT_SRC "${ALLSPARK_SRCS}")
message(STATUS "Building AllSpark kernels for archs: ${ALLSPARK_ARCHS}")
else()
message(STATUS "Not building AllSpark kernels as no compatible archs found"
" in CUDA target architectures")
endif()
# CUTLASS MLA Archs and flags
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 13.0)
cuda_archs_loose_intersection(MLA_ARCHS "10.0f;11.0f;12.0f" "${CUDA_ARCHS}")
else()
cuda_archs_loose_intersection(MLA_ARCHS "10.0a;10.1a;10.3a;12.0a;12.1a" "${CUDA_ARCHS}")
endif()
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 12.8 AND MLA_ARCHS)
set(SRCS
"csrc/attention/mla/sm100_cutlass_mla_kernel.cu")
set_gencode_flags_for_srcs(
SRCS "${SRCS}"
CUDA_ARCHS "${MLA_ARCHS}")
list(APPEND VLLM_EXT_SRC "${SRCS}")
list(APPEND VLLM_GPU_FLAGS "-DENABLE_CUTLASS_MLA=1")
# Add MLA-specific include directories only to MLA source files
set_source_files_properties(${SRCS}
PROPERTIES INCLUDE_DIRECTORIES "${CUTLASS_DIR}/examples/77_blackwell_fmha;${CUTLASS_DIR}/examples/common")
message(STATUS "Building CUTLASS MLA for archs: ${MLA_ARCHS}")
else()
message(STATUS "Not building CUTLASS MLA as no compatible archs were found.")
# clear MLA_ARCHS
set(MLA_ARCHS)
endif()
# Expert-specialization MXFP8 blockscaled grouped kernels (SM100+).
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 13.0)
cuda_archs_loose_intersection(ES_MXFP8_GROUPED_MM_ARCHS "10.0f;11.0f" "${CUDA_ARCHS}")
@@ -522,6 +541,24 @@ if(VLLM_GPU_LANG STREQUAL "CUDA")
endif()
endif()
# DeepSeek V3 fused A GEMM kernel (requires SM 9.0+, Hopper and later)
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 13.0)
cuda_archs_loose_intersection(DSV3_FUSED_A_GEMM_ARCHS "9.0a;10.0f;11.0f" "${CUDA_ARCHS}")
else()
cuda_archs_loose_intersection(DSV3_FUSED_A_GEMM_ARCHS "9.0a;10.0a;10.1a;10.3a" "${CUDA_ARCHS}")
endif()
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 12.0 AND DSV3_FUSED_A_GEMM_ARCHS)
set(DSV3_FUSED_A_GEMM_SRC "csrc/dsv3_fused_a_gemm.cu")
set_gencode_flags_for_srcs(
SRCS "${DSV3_FUSED_A_GEMM_SRC}"
CUDA_ARCHS "${DSV3_FUSED_A_GEMM_ARCHS}")
list(APPEND VLLM_EXT_SRC ${DSV3_FUSED_A_GEMM_SRC})
message(STATUS "Building dsv3_fused_a_gemm for archs: ${DSV3_FUSED_A_GEMM_ARCHS}")
else()
message(STATUS "Not building dsv3_fused_a_gemm as no compatible archs found "
"in CUDA target architectures.")
endif()
#
# Machete kernels
@@ -593,6 +630,16 @@ if(VLLM_GPU_LANG STREQUAL "CUDA")
endif()
# Hadacore kernels
cuda_archs_loose_intersection(HADACORE_ARCHS "8.0+PTX;9.0+PTX" "${CUDA_ARCHS}")
if(HADACORE_ARCHS)
set(SRCS "csrc/quantization/hadamard/hadacore/hadamard_transform_cuda.cu")
set_gencode_flags_for_srcs(
SRCS "${SRCS}"
CUDA_ARCHS "${HADACORE_ARCHS}")
list(APPEND VLLM_EXT_SRC "${SRCS}")
message(STATUS "Building hadacore")
endif()
# if CUDA endif
endif()
@@ -624,95 +671,31 @@ define_extension_target(
# Setting this variable sidesteps the issue by calling the driver directly.
target_compile_definitions(_C PRIVATE CUTLASS_ENABLE_DIRECT_CUDA_DRIVER_CALL=1)
if(VLLM_GPU_LANG STREQUAL "CUDA" OR VLLM_GPU_LANG STREQUAL "HIP")
# add OR VLLM_GPU_LANG STREQUAL "HIP" here once
# https://github.com/vllm-project/vllm/issues/35163 is resolved
if(VLLM_GPU_LANG STREQUAL "CUDA")
#
# _C_stable_libtorch extension (ops registered via STABLE_TORCH_LIBRARY)
#
set(VLLM_STABLE_EXT_SRC
"csrc/libtorch_stable/torch_bindings.cpp"
"csrc/libtorch_stable/activation_kernels.cu"
"csrc/libtorch_stable/quantization/w8a8/int8/scaled_quant.cu"
"csrc/libtorch_stable/quantization/w8a8/fp8/common.cu"
"csrc/libtorch_stable/quantization/gptq/q_gemm.cu"
"csrc/libtorch_stable/quantization/gguf/gguf_kernel.cu"
"csrc/libtorch_stable/pos_encoding_kernels.cu"
"csrc/libtorch_stable/fused_qknorm_rope_kernel.cu"
"csrc/libtorch_stable/layernorm_kernels.cu"
"csrc/libtorch_stable/layernorm_quant_kernels.cu"
"csrc/libtorch_stable/quantization/fused_kernels/fused_layernorm_dynamic_per_token_quant.cu"
"csrc/libtorch_stable/attention/merge_attn_states.cu"
"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_fused.cu")
"csrc/cutlass_extensions/common.cpp"
"csrc/cuda_utils_kernels.cu"
"csrc/libtorch_stable/quantization/w8a8/cutlass/scaled_mm_entry.cu"
"csrc/libtorch_stable/quantization/fp4/nvfp4_quant_entry.cu"
"csrc/libtorch_stable/quantization/fp4/nvfp4_scaled_mm_entry.cu")
if(VLLM_GPU_LANG STREQUAL "CUDA")
list(APPEND VLLM_STABLE_EXT_SRC
"csrc/cuda_utils_kernels.cu"
"csrc/cutlass_extensions/common.cpp"
"csrc/libtorch_stable/quantization/w8a8/cutlass/scaled_mm_entry.cu"
"csrc/libtorch_stable/quantization/fp4/nvfp4_quant_entry.cu"
"csrc/libtorch_stable/quantization/fp4/nvfp4_scaled_mm_entry.cu"
"csrc/libtorch_stable/permute_cols.cu"
"csrc/libtorch_stable/quantization/w8a8/fp8/per_token_group_quant.cu"
"csrc/libtorch_stable/quantization/w8a8/int8/per_token_group_quant.cu"
"csrc/libtorch_stable/quantization/awq/gemm_kernels.cu")
"csrc/libtorch_stable/quantization/w8a8/int8/per_token_group_quant.cu")
endif()
if(VLLM_GPU_LANG STREQUAL "CUDA")
set_gencode_flags_for_srcs(
SRCS "${VLLM_STABLE_EXT_SRC}"
CUDA_ARCHS "${CUDA_ARCHS}")
# DeepSeek V3 fused A GEMM kernel (requires SM 9.0+, Hopper and later)
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 13.0)
cuda_archs_loose_intersection(DSV3_FUSED_A_GEMM_ARCHS "9.0a;10.0f;11.0f" "${CUDA_ARCHS}")
else()
cuda_archs_loose_intersection(DSV3_FUSED_A_GEMM_ARCHS "9.0a;10.0a;10.1a;10.3a" "${CUDA_ARCHS}")
endif()
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 12.0 AND DSV3_FUSED_A_GEMM_ARCHS)
set(SRCS "csrc/libtorch_stable/dsv3_fused_a_gemm.cu")
set_gencode_flags_for_srcs(
SRCS "${SRCS}"
CUDA_ARCHS "${DSV3_FUSED_A_GEMM_ARCHS}")
list(APPEND VLLM_STABLE_EXT_SRC "${SRCS}")
message(STATUS "Building dsv3_fused_a_gemm for archs: ${DSV3_FUSED_A_GEMM_ARCHS}")
else()
message(STATUS "Not building dsv3_fused_a_gemm as no compatible archs found "
"in CUDA target architectures.")
endif()
# FP32 router GEMM (H=3072, E=256, M<=32). Requires SM90+ and CUDA >= 12.0.
cuda_archs_sm90plus(FP32_ROUTER_GEMM_ARCHS "${CUDA_ARCHS}")
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 12.0 AND FP32_ROUTER_GEMM_ARCHS)
set(SRCS
"csrc/libtorch_stable/fp32_router_gemm_entry.cu"
"csrc/libtorch_stable/fp32_router_gemm.cu")
set_gencode_flags_for_srcs(
SRCS "${SRCS}"
CUDA_ARCHS "${FP32_ROUTER_GEMM_ARCHS}")
list(APPEND VLLM_STABLE_EXT_SRC "${SRCS}")
message(STATUS "Building fp32_router_gemm for archs: ${FP32_ROUTER_GEMM_ARCHS}")
else()
message(STATUS "Not building fp32_router_gemm as no compatible archs found "
"(requires SM90+ and CUDA >= 12.0).")
endif()
# Only build AllSpark kernels if we are building for at least some compatible archs.
cuda_archs_loose_intersection(ALLSPARK_ARCHS "8.0;8.6;8.7;8.9" "${CUDA_ARCHS}")
if (ALLSPARK_ARCHS)
set(SRCS
"csrc/libtorch_stable/quantization/gptq_allspark/allspark_repack.cu"
"csrc/libtorch_stable/quantization/gptq_allspark/allspark_qgemm_w8a16.cu")
set_gencode_flags_for_srcs(
SRCS "${SRCS}"
CUDA_ARCHS "${ALLSPARK_ARCHS}")
list(APPEND VLLM_STABLE_EXT_SRC "${SRCS}")
message(STATUS "Building AllSpark kernels for archs: ${ALLSPARK_ARCHS}")
else()
message(STATUS "Not building AllSpark kernels as no compatible archs found"
" in CUDA target architectures")
endif()
#
@@ -940,12 +923,6 @@ if(VLLM_GPU_LANG STREQUAL "CUDA" OR VLLM_GPU_LANG STREQUAL "HIP")
SRCS "${SRCS}"
CUDA_ARCHS "${FP4_ARCHS}")
list(APPEND VLLM_STABLE_EXT_SRC "${SRCS}")
set(NVFP4_KV_SRC "csrc/libtorch_stable/nvfp4_kv_cache_kernels.cu")
set_gencode_flags_for_srcs(
SRCS "${NVFP4_KV_SRC}"
CUDA_ARCHS "${FP4_ARCHS}")
list(APPEND VLLM_STABLE_EXT_SRC "${NVFP4_KV_SRC}")
target_compile_definitions(_C PRIVATE ENABLE_NVFP4_SM120=1)
list(APPEND VLLM_GPU_FLAGS "-DENABLE_NVFP4_SM120=1")
list(APPEND VLLM_GPU_FLAGS "-DENABLE_CUTLASS_MOE_SM120=1")
message(STATUS "Building NVFP4 for archs: ${FP4_ARCHS}")
@@ -967,19 +944,11 @@ if(VLLM_GPU_LANG STREQUAL "CUDA" OR VLLM_GPU_LANG STREQUAL "HIP")
"csrc/libtorch_stable/quantization/fp4/activation_nvfp4_quant_fusion_kernels.cu"
"csrc/libtorch_stable/quantization/fp4/nvfp4_experts_quant.cu"
"csrc/libtorch_stable/quantization/fp4/nvfp4_scaled_mm_kernels.cu"
"csrc/libtorch_stable/quantization/fp4/nvfp4_blockwise_moe_kernel.cu"
"csrc/libtorch_stable/quantization/fp4/mxfp4_experts_quant.cu"
"csrc/libtorch_stable/quantization/fp4/mxfp4_blockwise_moe_kernel.cu")
"csrc/libtorch_stable/quantization/fp4/nvfp4_blockwise_moe_kernel.cu")
set_gencode_flags_for_srcs(
SRCS "${SRCS}"
CUDA_ARCHS "${FP4_ARCHS}")
list(APPEND VLLM_STABLE_EXT_SRC "${SRCS}")
set(NVFP4_KV_SRC "csrc/libtorch_stable/nvfp4_kv_cache_kernels.cu")
set_gencode_flags_for_srcs(
SRCS "${NVFP4_KV_SRC}"
CUDA_ARCHS "${FP4_ARCHS}")
list(APPEND VLLM_STABLE_EXT_SRC "${NVFP4_KV_SRC}")
target_compile_definitions(_C PRIVATE ENABLE_NVFP4_SM100=1)
list(APPEND VLLM_GPU_FLAGS "-DENABLE_NVFP4_SM100=1")
list(APPEND VLLM_GPU_FLAGS "-DENABLE_CUTLASS_MOE_SM100=1")
message(STATUS "Building NVFP4 for archs: ${FP4_ARCHS}")
@@ -1022,44 +991,6 @@ if(VLLM_GPU_LANG STREQUAL "CUDA" OR VLLM_GPU_LANG STREQUAL "HIP")
endif()
endif()
# CUTLASS MLA Archs and flags
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 13.0)
cuda_archs_loose_intersection(MLA_ARCHS "10.0f;11.0f;12.0f" "${CUDA_ARCHS}")
else()
cuda_archs_loose_intersection(MLA_ARCHS "10.0a;10.1a;10.3a;12.0a;12.1a" "${CUDA_ARCHS}")
endif()
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 12.8 AND MLA_ARCHS)
set(SRCS
"csrc/libtorch_stable/attention/mla/sm100_cutlass_mla_kernel.cu")
set_gencode_flags_for_srcs(
SRCS "${SRCS}"
CUDA_ARCHS "${MLA_ARCHS}")
list(APPEND VLLM_STABLE_EXT_SRC "${SRCS}")
list(APPEND VLLM_GPU_FLAGS "-DENABLE_CUTLASS_MLA=1")
# Add MLA-specific include directories only to MLA source files
set_source_files_properties(${SRCS}
PROPERTIES INCLUDE_DIRECTORIES "${CUTLASS_DIR}/examples/77_blackwell_fmha;${CUTLASS_DIR}/examples/common")
message(STATUS "Building CUTLASS MLA for archs: ${MLA_ARCHS}")
else()
message(STATUS "Not building CUTLASS MLA as no compatible archs were found.")
# clear MLA_ARCHS
set(MLA_ARCHS)
endif()
# Hadacore kernels
cuda_archs_loose_intersection(HADACORE_ARCHS "8.0+PTX;9.0+PTX" "${CUDA_ARCHS}")
if(HADACORE_ARCHS)
set(SRCS "csrc/libtorch_stable/quantization/hadamard/hadacore/hadamard_transform_cuda.cu")
set_gencode_flags_for_srcs(
SRCS "${SRCS}"
CUDA_ARCHS "${HADACORE_ARCHS}")
list(APPEND VLLM_STABLE_EXT_SRC "${SRCS}")
message(STATUS "Building hadacore")
endif()
# if CUDA endif
endif()
message(STATUS "Enabling C_stable extension.")
define_extension_target(
_C_stable_libtorch
@@ -1079,34 +1010,13 @@ if(VLLM_GPU_LANG STREQUAL "CUDA" OR VLLM_GPU_LANG STREQUAL "HIP")
target_compile_definitions(_C_stable_libtorch PRIVATE
TORCH_TARGET_VERSION=0x020A000000000000ULL)
# Needed to use cuda/hip APIs from C-shim
if(VLLM_GPU_LANG STREQUAL "CUDA")
target_compile_definitions(_C_stable_libtorch PRIVATE USE_CUDA)
# Needed by CUTLASS kernels
target_compile_definitions(_C_stable_libtorch PRIVATE
CUTLASS_ENABLE_DIRECT_CUDA_DRIVER_CALL=1)
elseif(VLLM_GPU_LANG STREQUAL "HIP")
target_compile_definitions(_C_stable_libtorch PRIVATE USE_ROCM)
endif()
# Needed to use cuda APIs from C-shim
target_compile_definitions(_C_stable_libtorch PRIVATE
USE_CUDA)
# On ROCm, _C_stable_libtorch calls raw HIP APIs (e.g. hipGetDevice in
# get_device_prop()) which must resolve to the same libamdhip64.so that
# PyTorch uses. When PyTorch bundles its own copy (pip/conda wheels),
# the raw HIP calls would otherwise resolve to the system ROCm copy,
# initializing a second HIP runtime that corrupts device state (wrong
# device on DeviceGuard, core dumps on multi-GPU tests).
#
# If PyTorch doesn't bundle libamdhip64 (built from source against system
# ROCm), there is only one copy in the process and no action is needed —
# the HIP compiler already links the system libamdhip64 automatically.
if(VLLM_GPU_LANG STREQUAL "HIP")
find_library(_STABLE_TORCH_AMDHIP64 amdhip64
PATHS "${TORCH_INSTALL_PREFIX}/lib" NO_DEFAULT_PATH)
if(_STABLE_TORCH_AMDHIP64)
message(STATUS "Found PyTorch-bundled libamdhip64 at ${_STABLE_TORCH_AMDHIP64}")
target_link_libraries(_C_stable_libtorch PRIVATE ${_STABLE_TORCH_AMDHIP64})
endif()
endif()
# Needed by CUTLASS kernels
target_compile_definitions(_C_stable_libtorch PRIVATE
CUTLASS_ENABLE_DIRECT_CUDA_DRIVER_CALL=1)
endif()
#
@@ -1116,13 +1026,13 @@ endif()
set(VLLM_MOE_EXT_SRC
"csrc/moe/torch_bindings.cpp"
"csrc/moe/moe_align_sum_kernels.cu"
"csrc/moe/topk_softmax_kernels.cu"
"csrc/moe/topk_softplus_sqrt_kernels.cu")
"csrc/moe/topk_softmax_kernels.cu")
if(VLLM_GPU_LANG STREQUAL "CUDA")
list(APPEND VLLM_MOE_EXT_SRC
"csrc/moe/moe_wna16.cu"
"csrc/moe/grouped_topk_kernels.cu")
"csrc/moe/grouped_topk_kernels.cu"
"csrc/moe/router_gemm.cu")
endif()
if(VLLM_GPU_LANG STREQUAL "CUDA")
@@ -1149,11 +1059,7 @@ if(VLLM_GPU_LANG STREQUAL "CUDA")
# moe marlin arches
# note that we always set `use_atomic_add=False` for moe marlin now,
# so we don't need 9.0 for bf16 atomicAdd PTX
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 13.0)
cuda_archs_loose_intersection(MARLIN_MOE_ARCHS "8.0+PTX;12.0f" "${CUDA_ARCHS}")
else()
cuda_archs_loose_intersection(MARLIN_MOE_ARCHS "8.0+PTX;12.0a;12.1a" "${CUDA_ARCHS}")
endif()
cuda_archs_loose_intersection(MARLIN_MOE_ARCHS "8.0+PTX" "${CUDA_ARCHS}")
# moe marlin has limited support for turing
cuda_archs_loose_intersection(MARLIN_MOE_SM75_ARCHS "7.5" "${CUDA_ARCHS}")
# moe marlin arches for fp8 input
@@ -1256,22 +1162,24 @@ if(VLLM_GPU_LANG STREQUAL "CUDA")
" in CUDA target architectures")
endif()
# DeepSeek V3 router GEMM kernel requires SM90+ and CUDA >= 12.0.
# (fp32_router_gemm has been migrated to _C_stable_libtorch above.)
cuda_archs_sm90plus(SM90PLUS_ROUTER_GEMM_ARCHS "${CUDA_ARCHS}")
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 12.0 AND SM90PLUS_ROUTER_GEMM_ARCHS)
# DeepSeek V3 router GEMM kernel - requires SM90+
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 13.0)
cuda_archs_loose_intersection(DSV3_ROUTER_GEMM_ARCHS "9.0a;10.0f;11.0f" "${CUDA_ARCHS}")
else()
cuda_archs_loose_intersection(DSV3_ROUTER_GEMM_ARCHS "9.0a;10.0a;10.1a;10.3a" "${CUDA_ARCHS}")
endif()
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER_EQUAL 12.0 AND DSV3_ROUTER_GEMM_ARCHS)
set(DSV3_ROUTER_GEMM_SRC
"csrc/moe/dsv3_router_gemm_entry.cu"
"csrc/moe/dsv3_router_gemm_float_out.cu"
"csrc/moe/dsv3_router_gemm_bf16_out.cu")
set_gencode_flags_for_srcs(
SRCS "${DSV3_ROUTER_GEMM_SRC}"
CUDA_ARCHS "${SM90PLUS_ROUTER_GEMM_ARCHS}")
CUDA_ARCHS "${DSV3_ROUTER_GEMM_ARCHS}")
list(APPEND VLLM_MOE_EXT_SRC "${DSV3_ROUTER_GEMM_SRC}")
message(STATUS "Building DSV3 router GEMM kernels for archs: ${SM90PLUS_ROUTER_GEMM_ARCHS}")
message(STATUS "Building DSV3 router GEMM kernel for archs: ${DSV3_ROUTER_GEMM_ARCHS}")
else()
message(STATUS "Not building DSV3 router GEMM kernels as no compatible archs found"
message(STATUS "Not building DSV3 router GEMM kernel as no compatible archs found"
" (requires SM90+ and CUDA >= 12.0)")
endif()
endif()
@@ -1298,14 +1206,6 @@ if(VLLM_GPU_LANG STREQUAL "HIP")
"csrc/rocm/skinny_gemms.cu"
"csrc/rocm/attention.cu")
set(VLLM_ROCM_HAS_GFX1100 OFF)
if(VLLM_GPU_ARCHES MATCHES "gfx1100")
set(VLLM_ROCM_HAS_GFX1100 ON)
list(APPEND VLLM_ROCM_EXT_SRC
"csrc/rocm/q_gemm_rdna3.cu"
"csrc/rocm/q_gemm_rdna3_wmma.cu")
endif()
define_extension_target(
_rocm_C
DESTINATION vllm
@@ -1315,16 +1215,6 @@ if(VLLM_GPU_LANG STREQUAL "HIP")
ARCHITECTURES ${VLLM_GPU_ARCHES}
USE_SABI 3
WITH_SOABI)
if(VLLM_ROCM_HAS_GFX1100)
target_compile_definitions(_rocm_C PRIVATE VLLM_ROCM_GFX1100)
endif()
endif()
# Must run after the last HIP `define_extension_target` so every extension
# has registered its sources.
if (VLLM_GPU_LANG STREQUAL "HIP")
vllm_finalize_hipify_target()
endif()
# For CUDA and HIP builds also build the triton_kernels external package.

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