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khluuandClaude Opus 4.7 797cdc15f0 [CI] Use uv-installed standalone Python in vllm-base (drop deadsnakes)
The vllm-base stage installs python3.12 via the deadsnakes PPA, which
requires reaching launchpad.net (REST API) or ppa.launchpadcontent.net
(CDN). On the release-v2 build agents, both are unreachable
(Connection timed out to 185.125.190.80), causing the regular Ubuntu
22.04 release images to hang or fail at the apt-get update step.

Switch vllm-base to the same approach the `base` stage already uses:
uv installs a standalone python3.12 (via python-build-standalone,
hosted on astral.sh CDN) into /opt/venv, and we symlink it to
/usr/bin/python3. No Launchpad dependency.

Side benefits:
- Consistent python install path between `base` and `vllm-base`.
- Removes the software-properties-common / add-apt-repository step.
- Drops unused DEADSNAKES_MIRROR_URL / DEADSNAKES_GPGKEY_URL /
  GET_PIP_URL stage args.

Test branch: khluu/release-v0.20.1-uv-python (off releases/v0.20.1).

Signed-off-by: khluu <khluu000@gmail.com>

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 13:42:32 -07:00
khluuandClaude Opus 4.7 438f6548c1 [CI] Use deadsnakes mirror for non-Ubuntu24.04 release images
The 4 Ubuntu 22.04 release image builds (CUDA 12.9 / 13.0 x both archs)
hang for ~30min and intermittently fail because
`add-apt-repository ppa:deadsnakes/ppa` hits the launchpad.net REST API
to resolve PPA metadata, and that call has been timing out in CI:

    TimeoutError: [Errno 110] Connection timed out
    ...
    E: Unable to locate package python3.12

Plumb DEADSNAKES_MIRROR_URL and DEADSNAKES_GPGKEY_URL through to those
steps so the Dockerfile takes the mirror branch and writes the apt
source directly, skipping the flaky API call. The mirror points at the
public Launchpad CDN (same packages add-apt-repository would have
configured) and the GPG key comes from keyserver.ubuntu.com.

Ubuntu 24.04 builds are unaffected — they ship python3.12 in default
apt repos and never enter the deadsnakes branch.

Signed-off-by: khluu <khluu000@gmail.com>

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 13:25:05 -07:00
Yongye Zhuandkhluu 513b5f82dd [DSV4] Add knob to enable pre-attn gemm (#41443)
Signed-off-by: Yongye Zhu <zyy1102000@gmail.com>
(cherry picked from commit bcf5cac9fb)
2026-05-01 12:24:17 -07:00
khluu 135722d58d Revert "."
This reverts commit a5e0ea09ea.
2026-05-01 12:23:33 -07:00
Rohan Potdarandkhluu 7758daca7c [ROCm][Bugfix][GPTOSS]: fix input_ids and expert_map args for quark w4a8 gptoss (#41165)
Signed-off-by: Rohan138 <rohanpotdar138@gmail.com>
(cherry picked from commit 3795d7acf4)
2026-05-01 12:17:45 -07:00
Isotr0pyandkhluu 5f79634b3b [Perf] Intergrate Tile Kernels head_compute_mix_kernel for Deepseek-V4 (#41255)
Signed-off-by: Isotr0py <Isotr0py@outlook.com>
Co-authored-by: Roger Wang <hey@rogerw.io>
(cherry picked from commit a9484dac7b)
2026-05-01 12:17:28 -07:00
Bugen Zhaoandkhluu 05adde9955 [Bugfix] Pass reasoning parser kwargs to structured output (#41199)
Signed-off-by: Bugen Zhao <i@bugenzhao.com>
Co-authored-by: wang.yuqi <yuqi.wang@daocloud.io>
(cherry picked from commit a07642667d)
2026-05-01 12:14:44 -07:00
Jiangyun Zhuandkhluu 9cdcda5fc2 [Bugfix] BailingMoeV2.5: rotate full qk_rope_head_dim in MLA RoPE (#41185)
Signed-off-by: zjy0516 <riverclouds.zhu@qq.com>
(cherry picked from commit 6d7d4da99e)
2026-05-01 12:13:50 -07:00
JiangWeixiangandkhluu a5d4a264dd [Bugfix ] fix bailing_moe_linear (#40859)
Signed-off-by: ghphotoframe <854746559@qq.com>
(cherry picked from commit ed57f77192)
2026-05-01 12:13:41 -07:00
Yongye Zhuandkhluu a5e0ea09ea .
Signed-off-by: Yongye Zhu <zyy1102000@gmail.com>

(cherry picked from commit db0c9d52d4)

Signed-off-by: khluu <khluu000@gmail.com>
2026-04-30 23:16:02 -07:00
Yongye Zhuandkhluu 28a1a85d89 [DSV4] Add BF16 and MXFP8 A2A support for flashinfer a2a one sided (#40960)
Signed-off-by: Yongye Zhu <zyy1102000@gmail.com>
Signed-off-by: Zijing Liu <liuzijing2014@gmail.com>
Co-authored-by: Zijing Liu <liuzijing2014@users.noreply.github.com>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
(cherry picked from commit b4806c8ee1)
2026-04-30 21:39:14 -07:00
Yongye Zhuandkhluu 82ccd9f3b2 [Bugfix] Fix persistent_topk cooperative deadlock at TopK=1024 (#41189)
Signed-off-by: Yongye Zhu <zyy1102000@gmail.com>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
(cherry picked from commit a749a33d8d)
2026-04-30 21:39:14 -07:00
Thien Tranandkhluu d9f3961abb [DSv4] Use cvt PTX for FP32->FP4 conversion (#41015)
Signed-off-by: Thien Tran <gau.nernst@yahoo.com.sg>
(cherry picked from commit 296741d025)
2026-04-30 21:39:14 -07:00
Jee Jee Liandkhluu 4fee1390f4 [Bugfix] Fix repeated DSv4 RoPE cache initialization (#41148)
Signed-off-by: Jee Jee Li <pandaleefree@gmail.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
(cherry picked from commit 9d8ad5b408)
2026-04-30 21:39:14 -07:00
Chaunceyandkhluu bf590b6a24 [Bugfix] DSV32/V4 add missing type conversion for non-streaming tool calls (#41198)
Signed-off-by: chaunceyjiang <chaunceyjiang@gmail.com>
(cherry picked from commit 762022cafb)
2026-04-30 21:39:13 -07:00
Wei Zhaoandkhluu 66df2c03f5 [Bugfix] Fix max_num_batched_token not captured in cuda graph (#40734)
Signed-off-by: wzhao18 <wzhao18.sz@gmail.com>
Signed-off-by: Wei Zhao <51183510+wzhao18@users.noreply.github.com>
Co-authored-by: Wei Zhao (Engrg-Hardware 1) <weizha@login-bia02.bia.clusters.nvidia.com>
(cherry picked from commit 8b49cf3a37)
2026-04-30 21:39:13 -07:00
Jiangyun Zhuandkhluu 17896d817b [Bugfix] fix inductor error for dpsk v4 (#41135)
Signed-off-by: zjy0516 <riverclouds.zhu@qq.com>
(cherry picked from commit 2ae73c758c)
2026-04-30 21:39:13 -07:00
Wei Zhaoandkhluu 1a131a066c [Bugfix] Fix Deepseek V4 import error due to AOT compile cache loading (#41090)
Signed-off-by: wzhao18 <wzhao18.sz@gmail.com>
Signed-off-by: Wei Zhao <51183510+wzhao18@users.noreply.github.com>
(cherry picked from commit 803b9d7881)
2026-04-30 21:39:13 -07:00
qizixiandkhluu 6fffb0b8c8 [DSV4] Align aux stream API with DeepseekV4DecoderLayer (#41171)
Signed-off-by: zixi-qi <zixi@inferact.ai>
(cherry picked from commit 6fb3f7b46b)
2026-04-30 21:39:13 -07:00
Nick Hillandkhluu a076bd1e67 [Core] Account for num_gpu_blocks_override in max_model_len checks (#41069)
Signed-off-by: Nick Hill <nickhill123@gmail.com>
(cherry picked from commit e68fa1b90a)
2026-04-30 21:39:13 -07:00
Yongye Zhuandkhluu c244b6fc83 [DSV4] Enable Multi-stream for Pre-Attn GEMM (#41061)
Signed-off-by: Yongye Zhu <zyy1102000@gmail.com>
(cherry picked from commit 5aa371dc8e)
2026-04-30 21:39:13 -07:00
Jee Jee Liandkhluu 15cc87d2fe [Model][DSV4] Support base model (#41006)
Signed-off-by: Jee Jee Li <pandaleefree@gmail.com>
(cherry picked from commit 2c8b76c5cb)
2026-04-30 21:39:13 -07:00
youkaichaoandkhluu c68fa39ced Auto-disable expandable_segments around cumem memory pool (#40812)
Signed-off-by: youkaichao <youkaichao@gmail.com>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
(cherry picked from commit 2ce95a761b)
2026-04-30 21:39:13 -07:00
Yongye ZhuandGitHub 05ebca5250 Temporary disable persistent topk (#41442)
Signed-off-by: Yongye Zhu <zyy1102000@gmail.com>
2026-04-30 20:37:19 -07:00
Zhewen Liandkhluu 88d34c6409 [Docker] Install numactl CLI in CUDA runtime image (#41032)
Signed-off-by: Zhewen Li <zhewenli@inferact.ai>
Co-authored-by: Zhewen Li <zhewenli@inferact.ai>
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
(cherry picked from commit 6232fb4b66)
2026-04-27 12:04:32 -07:00
Yongye Zhuandkhluu b8160878f0 [DSV4] Add silu clamp limit to shared expert (#40950)
Signed-off-by: Yongye Zhu <zyy1102000@gmail.com>
(cherry picked from commit 706a04d34b)
2026-04-27 00:40:46 -07:00
Dao007foreverandkhluu 84c276d7ea [Bugfix] Cap SWA/chunked-local runtime admission to startup pool-sizing bound (#40946)
Signed-off-by: Dao Le <Dao007forever@gmail.com>
Signed-off-by: Nick Hill <nickhill123@gmail.com>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Nick Hill <nickhill123@gmail.com>
(cherry picked from commit 7b1bc0a3eb)
2026-04-26 21:43:00 -07:00
khluu 5eb3657578 Revert "[Frontend] Remove frontend pooling multi task support. (#37861)"
This reverts commit d2e2e856ad.
2026-04-26 21:42:15 -07:00
3399 changed files with 128930 additions and 509952 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"
+3 -2
View File
@@ -2,16 +2,17 @@ name: vllm_intel_ci
job_dirs:
- ".buildkite/intel_jobs"
run_all_patterns:
- ".buildkite/ci_config_intel.yaml"
- "docker/Dockerfile"
- "docker/Dockerfile.xpu"
- "CMakeLists.txt"
- "requirements/common.txt"
- "requirements/xpu.txt"
- "requirements/build/cuda.txt"
- "requirements/test/cuda.txt"
- "setup.py"
- "csrc/"
- "cmake/"
run_all_exclude_patterns:
- "docker/Dockerfile."
- "csrc/cpu/"
- "csrc/rocm/"
- "cmake/hipify.py"
-23
View File
@@ -1,23 +0,0 @@
name: vllm_rocm_ci
job_dirs:
- ".buildkite/hardware_tests"
run_all_patterns:
- "docker/Dockerfile.rocm"
- "docker/Dockerfile.rocm_base"
- "docker/ci-rocm.hcl"
- "docker/docker-bake-rocm.hcl"
- ".buildkite/hardware_tests/amd.yaml"
- ".buildkite/scripts/ci-bake-rocm.sh"
- ".buildkite/scripts/hardware_ci/run-amd-test.py"
- ".buildkite/scripts/hardware_ci/run-amd-test.sh"
- "CMakeLists.txt"
- "requirements/common.txt"
- "requirements/rocm.txt"
- "requirements/build/rocm.txt"
- "requirements/test/rocm.txt"
- "setup.py"
- "csrc/"
- "cmake/"
run_all_exclude_patterns:
- "csrc/cpu/"
- "cmake/cpu_extension.cmake"
+15 -68
View File
@@ -1,75 +1,22 @@
group: Hardware - AMD Build
group: Hardware - AMD Build
steps:
# Ensure ci_base is up-to-date before building the test image.
# Compares a content hash of ci_base-affecting files against the remote
# image label. If hashes match the build is skipped (< 30 s); if they
# differ ci_base is rebuilt and pushed automatically.
- label: "AMD: :docker: ensure ci_base"
key: ensure-ci-base-amd
soft_fail: false
- label: "AMD: :docker: build image"
key: image-build-amd
depends_on: []
device: amd_cpu
no_plugin: true
commands:
- bash .buildkite/scripts/ci-bake-rocm.sh ci-base-rocm-ci-with-deps
- >
docker build
--build-arg max_jobs=16
--build-arg REMOTE_VLLM=1
--build-arg ARG_PYTORCH_ROCM_ARCH='gfx90a;gfx942;gfx950'
--build-arg VLLM_BRANCH=$BUILDKITE_COMMIT
--tag "rocm/vllm-ci:${BUILDKITE_COMMIT}"
-f docker/Dockerfile.rocm
--target test
--no-cache
--progress plain .
- docker push "rocm/vllm-ci:${BUILDKITE_COMMIT}"
env:
DOCKER_BUILDKIT: "1"
VLLM_BAKE_FILE: "docker/docker-bake-rocm.hcl"
PYTORCH_ROCM_ARCH: "gfx90a;gfx942;gfx950"
REMOTE_VLLM: "1"
VLLM_BRANCH: "$BUILDKITE_COMMIT"
retry:
automatic:
- exit_status: -1 # Agent was lost
limit: 1
- exit_status: -10 # Agent was lost
limit: 1
- label: "AMD: :docker: build test image and artifacts"
key: image-build-amd
soft_fail: false
depends_on:
- ensure-ci-base-amd
device: amd_cpu
no_plugin: true
commands:
- |
if [[ "${ROCM_CI_ARTIFACT_ONLY:-0}" == "1" ]]; then
echo "ROCM_CI_ARTIFACT_ONLY=1; building ROCm wheel artifact only"
IMAGE_TAG="" bash .buildkite/scripts/ci-bake-rocm.sh test-rocm-ci-with-artifacts
else
bash .buildkite/scripts/ci-bake-rocm.sh test-rocm-ci-with-wheel
fi
- |
docker run --rm --network=none --entrypoint /bin/bash "rocm/vllm-ci:${BUILDKITE_COMMIT}" -ec '
if [ ! -d /vllm-workspace ]; then echo Missing directory: /vllm-workspace >&2; exit 1; fi
if [ ! -d /vllm-workspace/tests ]; then echo Missing directory: /vllm-workspace/tests >&2; exit 1; fi
if [ ! -d /vllm-workspace/src/vllm ]; then echo Missing directory: /vllm-workspace/src/vllm >&2; exit 1; fi
if [ ! -x /vllm-workspace/src/vllm/vllm-rs ]; then echo Missing executable: /vllm-workspace/src/vllm/vllm-rs >&2; exit 1; fi
command -v python3
command -v uv
command -v pytest
if ! command -v amd-smi >/dev/null 2>&1 && ! command -v rocminfo >/dev/null 2>&1; then
echo No ROCm CLI found in image >&2
exit 1
fi
python3 - <<PY
import torch, vllm
print(torch.__version__)
print(vllm.__version__)
PY
echo AMD image smoke OK
'
env:
DOCKER_BUILDKIT: "1"
VLLM_BAKE_FILE: "docker/docker-bake-rocm.hcl"
PYTORCH_ROCM_ARCH: "gfx90a;gfx942;gfx950"
IMAGE_TAG: "rocm/vllm-ci:$BUILDKITE_COMMIT"
REMOTE_VLLM: "1"
VLLM_BRANCH: "$BUILDKITE_COMMIT"
retry:
automatic:
- exit_status: -1 # Agent was lost
limit: 1
- exit_status: -10 # Agent was lost
limit: 1
+25 -66
View File
@@ -12,35 +12,28 @@ 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"
# Note: SDE can't be downloaded from CI host because of AWS WAF
# - label: CPU-Compatibility Tests
# depends_on: []
# device: intel_cpu
# no_plugin: true
# source_file_dependencies:
# - cmake/cpu_extension.cmake
# - setup.py
# - vllm/platforms/cpu.py
# commands:
# - |
# bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 20m "
# bash .buildkite/scripts/hardware_ci/run-cpu-compatibility-test.sh"
- label: CPU-Compatibility Tests
depends_on: []
device: intel_cpu
no_plugin: true
source_file_dependencies:
- cmake/cpu_extension.cmake
- setup.py
- vllm/platforms/cpu.py
commands:
- |
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 20m "
bash .buildkite/scripts/hardware_ci/run-cpu-compatibility-test.sh"
- label: CPU-Language Generation and Pooling Model Tests
depends_on: []
@@ -53,57 +46,34 @@ steps:
- tests/models/language/pooling/
commands:
- |
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 50m "
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 40m "
pytest -x -v -s tests/models/language/generation -m cpu_model
pytest -x -v -s tests/models/language/pooling -m cpu_model"
- 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
- tests/v1/e2e/test_cpu_linear_attn_chunked_prefix.py
commands:
- |
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 45m "
uv pip install git+https://github.com/triton-lang/triton-cpu.git@270e696d
VLLM_USE_V2_MODEL_RUNNER=1 pytest -x -v -s tests/models/language/generation/test_granite.py -m cpu_model
# TODO: move to CPU-Kernel Tests once triton-cpu has a pre-built wheel
pytest -x -v -s tests/v1/sample/test_topk_topp_sampler.py::TestTritonTopkTopp
pytest -x -v -s tests/v1/e2e/test_cpu_linear_attn_chunked_prefix.py"
- 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
- tests/quantization/test_cpu_w8a8.py
commands:
- |
bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 45m "
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
pytest -x -v -s tests/quantization/test_cpu_w8a8.py"
pytest -x -v -s tests/quantization/test_cpu_wna16.py"
- label: CPU-Distributed Tests (PP+TP)
- 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
@@ -112,21 +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: []
@@ -140,7 +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: 4
parallelism: 3
- 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
@@ -1,80 +0,0 @@
group: Intel
steps:
- label: ":docker: Build XPU image"
soft_fail: true
optional: true
depends_on: []
key: image-build-xpu
commands:
- bash -lc '.buildkite/image_build/image_build_xpu.sh "public.ecr.aws/q9t5s3a7" "vllm-ci-test-repo" "$BUILDKITE_COMMIT"'
env:
DOCKER_BUILDKIT: "1"
retry:
automatic:
- exit_status: -1 # Agent was lost
limit: 2
- exit_status: -10 # Agent was lost
limit: 2
- label: "XPU example Test"
depends_on:
- image-build-xpu
timeout_in_minutes: 30
optional: true
device: intel_gpu
agent_tags:
label: production
gpu: 2+
mem: 24+
no_plugin: true
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
source_file_dependencies:
- .buildkite/hardware_tests/intel_xpu_ci/test-intel.yaml
- .buildkite/scripts/hardware_ci/run-intel-ci-test.sh
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'bash .buildkite/scripts/hardware_ci/run-intel-ci-test.sh example'
- label: "XPU V1 test"
depends_on:
- image-build-xpu
timeout_in_minutes: 30
optional: true
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
source_file_dependencies:
- .buildkite/hardware_tests/intel_xpu_ci/test-intel.yaml
- .buildkite/scripts/hardware_ci/run-intel-ci-test.sh
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'bash .buildkite/scripts/hardware_ci/run-intel-ci-test.sh v1'
- label: "XPU server test"
depends_on:
- image-build-xpu
timeout_in_minutes: 30
optional: true
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
source_file_dependencies:
- .buildkite/hardware_tests/intel_xpu_ci/test-intel.yaml
- .buildkite/scripts/hardware_ci/run-intel-ci-test.sh
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'bash .buildkite/scripts/hardware_ci/run-intel-ci-test.sh server'
-1
View File
@@ -192,7 +192,6 @@ export BUILDKITE_COMMIT
export PARENT_COMMIT
export IMAGE_TAG
export IMAGE_TAG_LATEST
export COMMIT="${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
@@ -1,38 +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 for arm64 GPU targets: Grace/GH200 (sm_90) and DGX Spark/GB10
# (sm_121, family-covered by 12.0 under CUDA 13)
docker build --file docker/Dockerfile \
--platform linux/arm64 \
--build-arg max_jobs=16 \
--build-arg nvcc_threads=4 \
--build-arg torch_cuda_arch_list="9.0 12.0" \
--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"-hpu) ]]; then
+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
@@ -1,27 +0,0 @@
group: Basic Correctness
depends_on:
- image-build-xpu
steps:
- label: XPU Sleep Mode
timeout_in_minutes: 30
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/
- tests/basic_correctness/test_cumem.py
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
pytest -v -s basic_correctness/test_cpu_offload.py &&
pytest -v -s basic_correctness/test_mem.py::test_end_to_end'
-4
View File
@@ -5,10 +5,6 @@ steps:
- label: Engine (1 GPU)
timeout_in_minutes: 30
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
working_dir: "."
env:
@@ -1,27 +0,0 @@
group: Expert Parallelism
depends_on:
- image-build-xpu
steps:
- label: EPLB Algorithm
key: eplb-algorithm
timeout_in_minutes: 45
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/distributed/eplb
- tests/distributed/test_eplb_algo.py
- tests/distributed/test_eplb_utils.py
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
pytest -v -s distributed/test_eplb_algo.py'
-4
View File
@@ -5,10 +5,6 @@ steps:
- label: vLLM IR Tests
timeout_in_minutes: 30
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
working_dir: "."
env:
+10 -39
View File
@@ -5,10 +5,6 @@ steps:
- label: LoRA Runtime + Utils
timeout_in_minutes: 45
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 24+
no_plugin: true
working_dir: "."
env:
@@ -22,26 +18,21 @@ steps:
- >-
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_functions.py --deselect="tests/lora/test_lora_functions.py::test_lora_functions_sync" --deselect="tests/lora/test_lora_functions.py::test_lora_functions_async" || true) &&
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'
(pytest -v -s lora/test_add_lora.py --deselect="tests/lora/test_add_lora.py::test_add_lora" || true) &&
(pytest -v -s lora/test_worker.py --deselect="tests/lora/test_worker.py::test_worker_apply_lora" || true)'
- label: LoRA Fused/MoE Kernels
timeout_in_minutes: 45
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
working_dir: "."
env:
@@ -55,17 +46,12 @@ steps:
- >-
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]"'
pytest -v -s lora/test_moe_lora_align_sum.py'
- label: LoRA Punica Kernels
timeout_in_minutes: 45
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
working_dir: "."
env:
@@ -79,17 +65,12 @@ steps:
- >-
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]"'
pytest -v -s lora/test_punica_ops.py --deselect="tests/lora/test_punica_ops.py::test_kernels[shrink-0-xpu:0-dtype0-2-2049-64-32-32]" --deselect="tests/lora/test_punica_ops.py::test_kernels_hidden_size[expand-0-xpu:0-dtype1-2-64000-32-4-4]" --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]" --deselect="tests/lora/test_punica_ops.py::test_kernels_hidden_size[expand-0-xpu:0-dtype1-1-102656-32-4-4]"'
- label: LoRA Punica FP8/XPU Ops
timeout_in_minutes: 45
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
working_dir: "."
env:
@@ -103,17 +84,12 @@ steps:
- >-
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
agent_tags:
label: production
gpu: 2+
mem: 24+
no_plugin: true
working_dir: "."
env:
@@ -127,20 +103,14 @@ steps:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
(pytest -v -s lora/test_mixtral.py --deselect="tests/lora/test_mixtral.py::test_mixtral_lora[4]" || true) &&
pytest -v -s lora/test_quant_model.py --deselect="tests/lora/test_quant_model.py::test_quant_model_lora[model0]" --deselect="tests/lora/test_quant_model.py::test_quant_model_lora[model1]" --deselect="tests/lora/test_quant_model.py::test_quant_model_tp_equality[model0]" &&
pytest -v -s lora/test_transformers_model.py &&
pytest -v -s lora/test_chatglm3_tp.py &&
pytest -v -s lora/test_llama_tp.py::test_llama_lora &&
pytest -s -v lora/test_minicpmv_tp.py'
pytest -v -s lora/test_qwen35_densemodel_lora.py &&
pytest -v -s lora/test_transformers_model.py'
- label: LoRA Multimodal
timeout_in_minutes: 45
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
working_dir: "."
env:
@@ -154,6 +124,7 @@ steps:
- >-
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_qwen3_unembed.py || true) &&
(pytest -v -s lora/test_qwenvl.py || true) &&
pytest -v -s lora/test_whisper.py'
+9 -168
View File
@@ -5,10 +5,6 @@ steps:
- label: V1 Core + KV + Metrics
timeout_in_minutes: 30
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
working_dir: "."
env:
@@ -35,54 +31,6 @@ steps:
- label: V1 Sample + Logits
timeout_in_minutes: 30
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/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/
- 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
'pip install lm_eval[api]>=0.4.12 &&
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 &&
pytest -v -s v1/sample/test_topk_topp_sampler.py &&
pytest -v -s v1/sample/test_logprobs.py &&
pytest -v -s v1/sample/test_logprobs_e2e.py'
- label: XPU CPU Offload
timeout_in_minutes: 60
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
working_dir: "."
env:
@@ -91,124 +39,17 @@ steps:
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/
- vllm/v1/kv_offload/
- vllm/v1/kv_connector/
- tests/v1/kv_offload/
- tests/v1/kv_connector/unit/test_offloading_connector.py
- 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/kv_offload &&
pytest -v -s v1/kv_connector/unit/test_offloading_connector.py'
- label: Regression
key: regression
timeout_in_minutes: 30
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/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/
- tests/test_regression
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'pip install modelscope &&
cd tests &&
pytest -v -s test_regression.py'
- label: Metrics, Tracing (2 GPUs)
key: metrics-tracing-2-gpus
timeout_in_minutes: 30
num_devices: 2
device: intel_gpu
agent_tags:
label: production
gpu: 2+
mem: 16+
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/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/
- tests/v1/tracing
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'pip install opentelemetry-sdk\>=1.26.0 opentelemetry-api\>=1.26.0 opentelemetry-exporter-otlp\>=1.26.0 opentelemetry-semantic-conventions-ai\>=0.4.1 &&
cd tests &&
pytest -v -s v1/tracing'
- label: Async Engine, Inputs, Utils, Worker
key: async-engine-inputs-utils-worker
timeout_in_minutes: 30
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 24+
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/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/
- tests/detokenizer
- tests/multimodal
- tests/utils_
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
pip install av &&
pytest -v -s detokenizer &&
pytest -v -s -m "not cpu_test" ./multimodal &&
pytest -v -s utils_ --ignore=utils_/test_mem_utils.py'
pytest -v -s v1/logits_processors &&
pytest -v -s v1/test_oracle.py &&
pytest -v -s v1/test_request.py &&
pytest -v -s v1/test_outputs.py'
@@ -1,62 +0,0 @@
group: Model Runner V2 Intel
depends_on:
- image-build-xpu
steps:
- label: Model Runner V2 Core Tests (Intel)
timeout_in_minutes: 45
device: intel_gpu
agent_tags:
label: production
gpu: 2+
mem: 16+
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/v1/worker/gpu/
- vllm/v1/worker/gpu_worker.py
- vllm/v1/core/sched/
- vllm/v1/attention/
- tests/v1/engine/test_llm_engine.py
- tests/v1/e2e/
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'export VLLM_USE_V2_MODEL_RUNNER=1 &&
cd tests &&
pytest -v -s v1/engine/test_llm_engine.py -k "not test_engine_metrics" &&
ENFORCE_EAGER=1 pytest -v -s v1/e2e/general/test_async_scheduling.py -k "not ngram" &&
pytest -v -s v1/e2e/general/test_min_tokens.py'
- label: Model Runner V2 Examples (Intel)
timeout_in_minutes: 45
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 24+
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/v1/worker/gpu/
- vllm/v1/core/sched/
- vllm/v1/worker/gpu_worker.py
- examples/basic/offline_inference/
- examples/generate/multimodal/
- examples/features/
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'export VLLM_USE_V2_MODEL_RUNNER=1 &&
cd examples &&
python3 basic/offline_inference/chat.py &&
python3 basic/offline_inference/generate.py --model facebook/opt-125m &&
python3 generate/multimodal/vision_language_offline.py --seed 0 &&
python3 features/automatic_prefix_caching/prefix_caching_offline.py'
@@ -1,27 +0,0 @@
group: Models - Distributed
depends_on:
- image-build-xpu
steps:
- label: Distributed Model Tests (2 GPUs)
key: distributed-model-tests-2-gpus
timeout_in_minutes: 50
device: intel_gpu
agent_tags:
label: production
gpu: 2+
mem: 24+
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/model_executor/model_loader/sharded_state_loader.py
- vllm/model_executor/models/
- tests/model_executor/model_loader/test_sharded_state_loader.py
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
pytest -v -s model_executor/model_loader/test_sharded_state_loader.py -m "not slow_test"'
@@ -1,129 +0,0 @@
group: Models - Multimodal
depends_on:
- image-build-xpu
steps:
- label: "Multi-Modal Models (Standard) 1: qwen2"
key: multi-modal-models-standard-1-qwen2
timeout_in_minutes: 45
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/
- tests/models/multimodal
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'pip install av git+https://github.com/TIGER-AI-Lab/Mantis.git &&
cd tests &&
pytest -v -s models/multimodal/generation/test_common.py -m core_model -k "qwen2" &&
pytest -v -s models/multimodal/generation/test_ultravox.py -m core_model'
- label: "Multi-Modal Models (Standard) 2: qwen3 + gemma"
key: multi-modal-models-standard-2-qwen3-gemma
timeout_in_minutes: 45
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/
- tests/models/multimodal
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'pip install git+https://github.com/TIGER-AI-Lab/Mantis.git &&
cd tests &&
pytest -v -s models/multimodal/generation/test_qwen2_5_vl.py -m core_model'
- label: "Multi-Modal Models (Standard) 3: llava + qwen2_vl"
key: multi-modal-models-standard-3-llava-qwen2-vl
timeout_in_minutes: 45
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 24+
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/
- tests/models/multimodal
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'pip install git+https://github.com/TIGER-AI-Lab/Mantis.git &&
cd tests &&
pytest -v -s models/multimodal/generation/test_common.py -m core_model -k "not qwen2 and not qwen3 and not gemma" &&
pytest -v -s models/multimodal/generation/test_qwen2_vl.py -m core_model'
- label: "Multi-Modal Models (Standard) 4: other + whisper"
key: multi-modal-models-standard-4-other-whisper
timeout_in_minutes: 45
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/
- tests/models/multimodal
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'pip install av git+https://github.com/TIGER-AI-Lab/Mantis.git &&
cd tests &&
pytest -v -s models/multimodal -m core_model --ignore models/multimodal/generation/test_common.py --ignore models/multimodal/generation/test_ultravox.py --ignore models/multimodal/generation/test_qwen2_5_vl.py --ignore models/multimodal/generation/test_qwen2_vl.py --ignore models/multimodal/generation/test_whisper.py --ignore models/multimodal/generation/test_memory_leak.py --ignore models/multimodal/processing'
- label: Multi-Modal Processor # 44min
key: multi-modal-processor
timeout_in_minutes: 45
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
working_dir: "."
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
VLLM_TEST_DEVICE: "xpu"
source_file_dependencies:
- vllm/
- tests/models/multimodal
- tests/models/registry.py
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'pip install av matplotlib ftfy git+https://github.com/TIGER-AI-Lab/Mantis.git &&
pip install open-clip-torch --no-deps &&
cd tests &&
pytest -v -s models/multimodal/processing/test_tensor_schema.py
--num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB'
parallelism: 4
+3 -61
View File
@@ -19,10 +19,6 @@ steps:
- image-build-xpu
timeout_in_minutes: 30
device: intel_gpu
agent_tags:
label: production
gpu: 2+
mem: 24+
no_plugin: true
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
@@ -40,23 +36,14 @@ 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 &&
VLLM_XPU_FUSED_MOE_USE_REF=1 python3 examples/basic/offline_inference/generate.py --model Qwen/Qwen3-30B-A3B-Instruct-2507-FP8 --enforce-eager -tp 2 --max-model-len 8192 &&
python3 examples/basic/offline_inference/generate.py --model INCModel/Qwen3-30B-A3B-Instruct-2507-MXFP4-LLMC --enforce-eager -tp 2 --max-model-len 8192
'
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
timeout_in_minutes: 30
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
@@ -68,56 +55,11 @@ steps:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
bash v1/kv_connector/nixl_integration/run_xpu_disagg_accuracy_test.sh &&
pytest -v -s v1/core --ignore=v1/core/test_reset_prefix_cache_e2e.py --ignore=v1/core/test_scheduler_e2e.py &&
pytest -v -s v1/engine --ignore=v1/engine/test_output_processor.py &&
pytest -v -s v1/sample --ignore=v1/sample/test_logprobs.py --ignore=v1/sample/test_logprobs_e2e.py -k "not test_topk_only and not test_topp_only and not test_topk_and_topp" &&
pytest -v -s v1/worker --ignore=v1/worker/test_gpu_model_runner.py --ignore=v1/worker/test_worker_memory_snapshot.py &&
pytest -v -s v1/structured_output &&
pytest -v -s v1/test_serial_utils.py &&
pytest -v -s v1/spec_decode --ignore=v1/spec_decode/test_max_len.py --ignore=v1/spec_decode/test_speculators_eagle3.py --ignore=v1/spec_decode/test_acceptance_length.py --ignore=v1/spec_decode/test_speculators_correctness.py &&
pytest -v -s v1/kv_connector/unit --ignore=v1/kv_connector/unit/test_multi_connector.py --ignore=v1/kv_connector/unit/test_example_connector.py --ignore=v1/kv_connector/unit/test_lmcache_integration.py --ignore=v1/kv_connector/unit/test_hf3fs_client.py --ignore=v1/kv_connector/unit/test_hf3fs_connector.py --ignore=v1/kv_connector/unit/test_hf3fs_metadata_server.py --ignore=v1/kv_connector/unit/test_offloading_connector.py'
- label: "XPU server test"
depends_on:
- image-build-xpu
timeout_in_minutes: 30
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
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/multimodal/openai/chat_completion/test_audio_in_video.py &&
pytest -v -s benchmarks/test_serve_cli.py'
- label: "XPU quantization test"
depends_on:
- image-build-xpu
timeout_in_minutes: 30
device: intel_gpu
agent_tags:
label: production
gpu: 1+
mem: 16+
no_plugin: true
env:
REGISTRY: "public.ecr.aws/q9t5s3a7"
REPO: "vllm-ci-test-repo"
source_file_dependencies:
- vllm/
- .buildkite/intel_jobs/test-intel.yaml
commands:
- >-
bash .buildkite/scripts/hardware_ci/run-intel-test.sh
'cd tests &&
pytest -v -s quantization/test_auto_round.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'
@@ -6,7 +6,9 @@ tasks:
value: 0.7142
- name: "exact_match,flexible-extract"
value: 0.4579
moe_backend: "flashinfer_cutlass"
env_vars:
VLLM_USE_FLASHINFER_MOE_FP8: "1"
VLLM_FLASHINFER_MOE_BACKEND: "throughput"
limit: 1319
num_fewshot: 5
max_model_len: 262144
@@ -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``
@@ -68,10 +68,6 @@ def launch_lm_eval(eval_config, tp_size):
if current_platform.is_rocm() and "Nemotron-3" in eval_config["model_name"]:
model_args += "attention_backend=TRITON_ATTN"
moe_backend = eval_config.get("moe_backend", None)
if moe_backend is not None:
model_args += f"moe_backend={moe_backend},"
env_vars = eval_config.get("env_vars", None)
with scoped_env_vars(env_vars):
results = lm_eval.simple_evaluate(
@@ -2,6 +2,7 @@
{
"test_name": "latency_llama8B_tp1",
"environment_variables": {
"VLLM_RPC_TIMEOUT": 100000,
"VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
"VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
"VLLM_CPU_KVCACHE_SPACE": 40
@@ -2,6 +2,7 @@
{
"test_name": "latency_llama8B_tp2",
"environment_variables": {
"VLLM_RPC_TIMEOUT": 100000,
"VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
"VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
"VLLM_CPU_SGL_KERNEL": 1,
@@ -13,6 +13,7 @@
200
],
"server_environment_variables": {
"VLLM_RPC_TIMEOUT": 100000,
"VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
"VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
"VLLM_CPU_SGL_KERNEL": 1,
@@ -5,6 +5,7 @@
],
"max_concurrency_list": [12, 16, 24, 32, 64, 128, 200],
"server_environment_variables": {
"VLLM_RPC_TIMEOUT": 100000,
"VLLM_ENGINE_ITERATION_TIMEOUT_S": 120
},
"server_parameters": {
@@ -9,6 +9,7 @@
128
],
"server_environment_variables": {
"VLLM_RPC_TIMEOUT": 100000,
"VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
"VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
"VLLM_CPU_SGL_KERNEL": 1,
@@ -5,6 +5,7 @@
],
"max_concurrency_list": [12, 16, 24, 32, 64, 128, 200],
"server_environment_variables": {
"VLLM_RPC_TIMEOUT": 100000,
"VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
"VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
"VLLM_CPU_SGL_KERNEL": 1,
@@ -30,9 +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",
@@ -40,10 +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",
@@ -55,7 +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",
@@ -65,12 +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
@@ -79,7 +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",
@@ -88,22 +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",
@@ -115,7 +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",
@@ -127,7 +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",
@@ -139,7 +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",
@@ -148,34 +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",
@@ -187,7 +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",
@@ -195,94 +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
}
}
]
}
@@ -5,6 +5,7 @@
],
"max_concurrency_list": [12, 16, 24, 32, 64, 128, 200],
"server_environment_variables": {
"VLLM_RPC_TIMEOUT": 100000,
"VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
"VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
"VLLM_CPU_SGL_KERNEL": 1,
@@ -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
}
}
]
}
]
@@ -2,6 +2,7 @@
{
"test_name": "throughput_llama8B_tp1",
"environment_variables": {
"VLLM_RPC_TIMEOUT": 100000,
"VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
"VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
"VLLM_CPU_KVCACHE_SPACE": 40
@@ -2,6 +2,7 @@
{
"test_name": "throughput_llama8B_tp2",
"environment_variables": {
"VLLM_RPC_TIMEOUT": 100000,
"VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
"VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
"VLLM_CPU_SGL_KERNEL": 1,
+52 -235
View File
@@ -1,28 +1,12 @@
# 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
# These requested arches are filtered by CMake's CUDA_SUPPORTED_ARCHS before
# per-kernel arch selection. Do not add +PTX here: top-level +PTX is stripped
# during that filtering, so kernels that need PTX must request it locally.
env:
# for CUDA >=13, sm_100+ targets have family specifiers (see CMakeLists.txt)
# so targets like 10.3 and 12.1 are automatically supported with this list
CUDA_ARCH_X86: "7.5 8.0 8.6 8.9 9.0 10.0 12.0"
# aarch64-only targets: Orin (8.7), Thor (11.0, CUDA 13+)
CUDA_ARCH_AARCH64: "8.0 8.7 8.9 9.0 10.0 11.0 12.0"
# for CUDA <13, we need to specify all needed targets
# some targets (10.3, 12.1) are skipped to limit the wheel size (< 500MB)
# please use CUDA 13 wheels or compile yourself on these new devices
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"
# pre-built mooncake wheels
# the manylinux_2_35 wheel has compatibility issue on Ubuntu 24.04
# so we use different wheels for the time being
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"
@@ -40,11 +24,10 @@ 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=\"${CUDA_ARCH_AARCH64_CU129}\" --build-arg BUILD_OS=manylinux --build-arg BUILD_BASE_IMAGE=pytorch/manylinuxaarch64-builder:cuda12.9 --tag vllm-ci:build-image --target build --progress plain -f docker/Dockerfile ."
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=12.9.1 --build-arg torch_cuda_arch_list=\"${CUDA_ARCH_AARCH64_CU129}\" --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/$(cd artifacts/dist && echo *.whl)"'
- "bash .buildkite/scripts/upload-nightly-wheels.sh manylinux_2_31"
env:
DOCKER_BUILDKIT: "1"
@@ -54,11 +37,10 @@ steps:
agents:
queue: arm64_cpu_queue_release
commands:
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=13.0.2 --build-arg torch_cuda_arch_list=\"${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 ."
- "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_BASE_IMAGE=nvidia/cuda:13.0.2-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"
@@ -71,8 +53,7 @@ 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/$(cd artifacts/dist && echo *.whl)"'
- "bash .buildkite/scripts/upload-nightly-wheels.sh manylinux_2_35"
env:
DOCKER_BUILDKIT: "1"
@@ -82,11 +63,10 @@ steps:
agents:
queue: cpu_queue_release
commands:
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=12.9.1 --build-arg torch_cuda_arch_list=\"${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 --build-arg torch_cuda_arch_list=\"${CUDA_ARCH_X86_CU129}\" --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/$(cd artifacts/dist && echo *.whl)"'
- "bash .buildkite/scripts/upload-nightly-wheels.sh manylinux_2_31"
env:
DOCKER_BUILDKIT: "1"
@@ -96,11 +76,10 @@ steps:
agents:
queue: cpu_queue_release
commands:
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=13.0.2 --build-arg torch_cuda_arch_list=\"${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=13.0.2 --build-arg torch_cuda_arch_list=\"${CUDA_ARCH_X86}\" --build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.2-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"
@@ -113,8 +92,7 @@ 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"
@@ -143,26 +121,11 @@ steps:
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_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=\"${CUDA_ARCH_X86}\" --build-arg INSTALL_KV_CONNECTORS=true --build-arg DEADSNAKES_MIRROR_URL=https://ppa.launchpadcontent.net/deadsnakes/ppa/ubuntu --build-arg DEADSNAKES_GPGKEY_URL='https://keyserver.ubuntu.com/pks/lookup?op=get&search=0xF23C5A6CF475977595C89F51BA6932366A755776' --build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.2-devel-ubuntu22.04 --tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$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"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)"'
- label: "Build release image - aarch64 - CUDA 13.0"
depends_on: ~
@@ -171,23 +134,8 @@ steps:
queue: arm64_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- |
DOCKER_BUILDKIT=1 docker build \
$(bash .buildkite/scripts/docker-build-metadata-args.sh) \
--build-arg max_jobs=16 \
--build-arg USE_SCCACHE=1 \
--build-arg GIT_REPO_CHECK=1 \
--build-arg CUDA_VERSION=13.0.2 \
--build-arg torch_cuda_arch_list="${CUDA_ARCH_AARCH64}" \
--build-arg INSTALL_KV_CONNECTORS=true \
--build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_35}" \
--build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
--build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.2-devel-ubuntu22.04 \
--target vllm-openai \
--progress plain \
-f docker/Dockerfile .
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=13.0.2 --build-arg torch_cuda_arch_list=\"${CUDA_ARCH_AARCH64}\" --build-arg INSTALL_KV_CONNECTORS=true --build-arg DEADSNAKES_MIRROR_URL=https://ppa.launchpadcontent.net/deadsnakes/ppa/ubuntu --build-arg DEADSNAKES_GPGKEY_URL='https://keyserver.ubuntu.com/pks/lookup?op=get&search=0xF23C5A6CF475977595C89F51BA6932366A755776' --build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.2-devel-ubuntu22.04 --tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m) --target vllm-openai --progress plain -f docker/Dockerfile ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)"'
- label: "Build release image - x86_64 - CUDA 12.9"
depends_on: ~
@@ -196,25 +144,11 @@ steps:
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_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=\"${CUDA_ARCH_X86_CU129}\" --build-arg INSTALL_KV_CONNECTORS=true --build-arg DEADSNAKES_MIRROR_URL=https://ppa.launchpadcontent.net/deadsnakes/ppa/ubuntu --build-arg DEADSNAKES_GPGKEY_URL='https://keyserver.ubuntu.com/pks/lookup?op=get&search=0xF23C5A6CF475977595C89F51BA6932366A755776' --tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129 --target vllm-openai --progress plain -f docker/Dockerfile ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$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 "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129"'
- label: "Build release image - aarch64 - CUDA 12.9"
depends_on: ~
@@ -223,22 +157,8 @@ steps:
queue: arm64_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- |
DOCKER_BUILDKIT=1 docker build \
$(bash .buildkite/scripts/docker-build-metadata-args.sh cu129) \
--build-arg max_jobs=16 \
--build-arg USE_SCCACHE=1 \
--build-arg GIT_REPO_CHECK=1 \
--build-arg CUDA_VERSION=12.9.1 \
--build-arg torch_cuda_arch_list="${CUDA_ARCH_AARCH64_CU129}" \
--build-arg INSTALL_KV_CONNECTORS=true \
--build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_35}" \
--build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
--target vllm-openai \
--progress plain \
-f docker/Dockerfile .
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=12.9.1 --build-arg torch_cuda_arch_list=\"${CUDA_ARCH_AARCH64_CU129}\" --build-arg INSTALL_KV_CONNECTORS=true --build-arg DEADSNAKES_MIRROR_URL=https://ppa.launchpadcontent.net/deadsnakes/ppa/ubuntu --build-arg DEADSNAKES_GPGKEY_URL='https://keyserver.ubuntu.com/pks/lookup?op=get&search=0xF23C5A6CF475977595C89F51BA6932366A755776' --tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129 --target vllm-openai --progress plain -f docker/Dockerfile ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$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: ~
@@ -247,27 +167,10 @@ steps:
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_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 UBUNTU_VERSION=24.04 --build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 --build-arg torch_cuda_arch_list=\"${CUDA_ARCH_X86}\" --build-arg INSTALL_KV_CONNECTORS=true --build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.2-devel-ubuntu24.04 --tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$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"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-ubuntu2404"'
- label: "Build release image - aarch64 - CUDA 13.0 - Ubuntu 24.04"
depends_on: ~
@@ -276,25 +179,8 @@ steps:
queue: arm64_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- |
DOCKER_BUILDKIT=1 docker build \
$(bash .buildkite/scripts/docker-build-metadata-args.sh ubuntu2404) \
--build-arg max_jobs=16 \
--build-arg USE_SCCACHE=1 \
--build-arg GIT_REPO_CHECK=1 \
--build-arg CUDA_VERSION=13.0.2 \
--build-arg UBUNTU_VERSION=24.04 \
--build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 \
--build-arg torch_cuda_arch_list="${CUDA_ARCH_AARCH64}" \
--build-arg INSTALL_KV_CONNECTORS=true \
--build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_39}" \
--build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
--build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.2-devel-ubuntu24.04 \
--target vllm-openai \
--progress plain \
-f docker/Dockerfile .
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=13.0.2 --build-arg UBUNTU_VERSION=24.04 --build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 --build-arg torch_cuda_arch_list=\"${CUDA_ARCH_AARCH64}\" --build-arg INSTALL_KV_CONNECTORS=true --build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.2-devel-ubuntu24.04 --tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-ubuntu2404 --target vllm-openai --progress plain -f docker/Dockerfile ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-ubuntu2404"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$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: ~
@@ -303,26 +189,10 @@ steps:
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_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 torch_cuda_arch_list=\"${CUDA_ARCH_X86_CU129}\" --build-arg INSTALL_KV_CONNECTORS=true --tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129-ubuntu2404 --target vllm-openai --progress plain -f docker/Dockerfile ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$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 "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129-ubuntu2404"'
- label: "Build release image - aarch64 - CUDA 12.9 - Ubuntu 24.04"
depends_on: ~
@@ -331,31 +201,14 @@ steps:
queue: arm64_cpu_queue_release
commands:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- |
DOCKER_BUILDKIT=1 docker build \
$(bash .buildkite/scripts/docker-build-metadata-args.sh cu129-ubuntu2404) \
--build-arg max_jobs=16 \
--build-arg USE_SCCACHE=1 \
--build-arg GIT_REPO_CHECK=1 \
--build-arg CUDA_VERSION=12.9.1 \
--build-arg UBUNTU_VERSION=24.04 \
--build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 \
--build-arg torch_cuda_arch_list="${CUDA_ARCH_AARCH64_CU129}" \
--build-arg INSTALL_KV_CONNECTORS=true \
--build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_39}" \
--build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
--target vllm-openai \
--progress plain \
-f docker/Dockerfile .
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=12.9.1 --build-arg UBUNTU_VERSION=24.04 --build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 --build-arg torch_cuda_arch_list=\"${CUDA_ARCH_AARCH64_CU129}\" --build-arg INSTALL_KV_CONNECTORS=true --tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129-ubuntu2404 --target vllm-openai --progress plain -f docker/Dockerfile ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129-ubuntu2404"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$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
@@ -366,7 +219,6 @@ steps:
- "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 "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:$(buildkite-agent meta-data get release-version)"'
env:
DOCKER_BUILDKIT: "1"
@@ -375,8 +227,7 @@ steps:
depends_on: ~
- label: "Build release image - arm64 - CPU"
key: build-cpu-release-image-arm64
depends_on:
depends_on:
- block-arm64-cpu-release-image-build
- input-release-version
agents:
@@ -386,7 +237,6 @@ steps:
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg GIT_REPO_CHECK=1 --tag public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:$(buildkite-agent meta-data get release-version) --tag public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:latest --progress plain --target vllm-openai -f docker/Dockerfile.cpu ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:latest"
- "docker push public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:$(buildkite-agent meta-data get release-version)"
- 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:$(buildkite-agent meta-data get release-version)"'
env:
DOCKER_BUILDKIT: "1"
@@ -404,7 +254,15 @@ steps:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "docker manifest create public.ecr.aws/q9t5s3a7/vllm-release-repo:$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: "Annotate release workflow - CUDA 13.0"
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 12.9"
depends_on:
@@ -417,7 +275,6 @@ steps:
- "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:$BUILDKITE_COMMIT-cu129"'
- label: "Create multi-arch manifest - CUDA 13.0 - Ubuntu 24.04"
depends_on:
@@ -430,7 +287,6 @@ steps:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "docker manifest create public.ecr.aws/q9t5s3a7/vllm-release-repo:$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:
@@ -443,7 +299,6 @@ steps:
- "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:
@@ -481,6 +336,24 @@ steps:
DOCKER_BUILDKIT: "1"
DOCKERHUB_USERNAME: "vllmbot"
- group: "Publish wheels"
key: "publish-wheels"
steps:
- block: "Confirm update release wheels to PyPI (experimental, use with caution)?"
key: block-upload-release-wheels
depends_on:
- input-release-version
- build-wheels
- label: "Upload release wheels to PyPI"
depends_on:
- block-upload-release-wheels
id: upload-release-wheels
agents:
queue: small_cpu_queue_release
commands:
- "bash .buildkite/scripts/upload-release-wheels-pypi.sh"
# =============================================================================
# ROCm Release Pipeline (x86_64 only)
# =============================================================================
@@ -594,7 +467,7 @@ steps:
echo ""
echo " Build complete - Image and wheels cached"
fi
artifact_paths:
- "artifacts/rocm-base-wheels/*.whl"
env:
@@ -750,7 +623,7 @@ steps:
- "bash tools/vllm-rocm/generate-rocm-wheels-root-index.sh"
env:
S3_BUCKET: "vllm-wheels"
VARIANT: "rocm723"
VARIANT: "rocm721"
# ROCm Job 6: Build ROCm Release Docker Image
- label: ":docker: Build release image - x86_64 - ROCm"
@@ -810,7 +683,7 @@ steps:
# Push to ECR
docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$${BUILDKITE_COMMIT}-rocm
echo ""
echo " Successfully built and pushed ROCm release image"
echo " Image: public.ecr.aws/q9t5s3a7/vllm-release-repo:$${BUILDKITE_COMMIT}-rocm"
@@ -837,59 +710,3 @@ steps:
env:
DOCKER_BUILDKIT: "1"
DOCKERHUB_USERNAME: "vllmbot"
# =============================================================================
# Publish to DockerHub and PyPI (at the end so all builds complete first)
# =============================================================================
- 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
- 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"
key: "publish-wheels"
steps:
- block: "Confirm update release wheels to PyPI (experimental, use with caution)?"
key: block-upload-release-wheels
depends_on:
- input-release-version
- build-wheels
- label: "Upload release wheels to PyPI"
depends_on:
- block-upload-release-wheels
id: upload-release-wheels
agents:
queue: small_cpu_queue_release
commands:
- "bash .buildkite/scripts/upload-release-wheels-pypi.sh"
@@ -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-${RELEASE_VERSION}-cp38-abi3-manylinux_2_35_x86_64.whl .
aws s3 cp s3://vllm-wheels/${BUILDKITE_COMMIT}/vllm-${RELEASE_VERSION}-cp38-abi3-manylinux_2_35_aarch64.whl .
(Optional) For CUDA 12.9:
aws s3 cp s3://vllm-wheels/${BUILDKITE_COMMIT}/vllm-${RELEASE_VERSION}+cu129-cp38-abi3-manylinux_2_31_x86_64.whl .
aws s3 cp s3://vllm-wheels/${BUILDKITE_COMMIT}/vllm-${RELEASE_VERSION}+cu129-cp38-abi3-manylinux_2_31_aarch64.whl .
(Optional) For CPU:
aws s3 cp s3://vllm-wheels/${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-cu129
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-aarch64-cu129
docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${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:${BUILDKITE_COMMIT}-x86_64-cu129 vllm/vllm-openai:x86_64-cu129
docker tag vllm/vllm-openai:x86_64-cu129 vllm/vllm-openai:latest-x86_64-cu129
docker tag vllm/vllm-openai:x86_64-cu129 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu129
docker push vllm/vllm-openai:latest-x86_64-cu129
docker push vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu129
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${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:${BUILDKITE_COMMIT}-aarch64-cu129 vllm/vllm-openai:aarch64-cu129
docker tag vllm/vllm-openai:aarch64-cu129 vllm/vllm-openai:latest-aarch64-cu129
docker tag vllm/vllm-openai:aarch64-cu129 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu129
docker push vllm/vllm-openai:latest-aarch64-cu129
docker push vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu129
## ROCm
docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${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${RELEASE_VERSION}
docker manifest rm vllm/vllm-openai:latest-cu129
docker manifest create vllm/vllm-openai:latest-cu129 vllm/vllm-openai:latest-x86_64-cu129 vllm/vllm-openai:latest-aarch64-cu129
docker manifest create vllm/vllm-openai:v${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${RELEASE_VERSION}-cu129
docker manifest rm vllm/vllm-openai-cpu:latest || true
docker manifest create vllm/vllm-openai-cpu:latest vllm/vllm-openai-cpu:latest-x86_64 vllm/vllm-openai-cpu:latest-arm64
docker manifest create vllm/vllm-openai-cpu:v${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
File diff suppressed because it is too large Load Diff
-3
View File
@@ -13,8 +13,5 @@ INPUT_FILE="$1"
# Strip timestamps
sed -i 's/^\[[0-9]\{4\}-[0-9]\{2\}-[0-9]\{2\}T[0-9]\{2\}:[0-9]\{2\}:[0-9]\{2\}Z\] //' "$INPUT_FILE"
# Strip Buildkite inline timestamp markers (ESC _bk;t=<ms> BEL)
sed -i 's/\x1B_bk;t=[0-9]*\x07//g' "$INPUT_FILE"
# Strip colorization
sed -i -r 's/\x1B\[[0-9;]*[mK]//g' "$INPUT_FILE"
-178
View File
@@ -1,178 +0,0 @@
#!/bin/bash
# Fetch vLLM Buildkite CI logs (public; no login required).
#
# Usage:
# ci-fetch-log.sh [--soft|--all] --pr [<PR>] failed jobs in the PR's latest
# build (current branch if omitted)
# ci-fetch-log.sh [--soft|--all] <build_url> failed jobs in that build
# ci-fetch-log.sh <job_url> [output] one job; both #<job_uuid> and
# ?sid=<id> URL forms work
# ci-fetch-log.sh <build> <job_uuid> [output]
#
# --soft also fetches soft-failed jobs; --all fetches every finished job.
# Saves each log as ci-<build>-<job-name>.log (ANSI/timestamps stripped) and
# prints "<file>\t<job name>" per job. [output] is single-job only; "-"
# streams to stdout. Existing files are kept; CI_FETCH_LOG_FORCE=1 refetches.
set -euo pipefail
ORG="vllm"
PIPELINE="ci"
UA="vllm-ci-fetch-log"
UUID_RE='[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}'
usage() {
sed -n '2,15p' "$0" | sed 's/^# \{0,1\}//'
exit 1
}
die() {
echo "$1" >&2
exit 1
}
BUILD="" JOB="" SID="" OUT=""
SCOPE="failed"
while :; do
case "${1:-}" in
--soft) SCOPE="soft" ;;
--all) SCOPE="all" ;;
*) break ;;
esac
shift
done
case "${1:-}" in
--pr)
PR="${2:-}"
# gh pr checks exits non-zero when checks are failing; that is the
# expected case here.
URL=$(gh pr checks ${PR:+"$PR"} --repo vllm-project/vllm 2>/dev/null |
grep -oE "https://buildkite.com/${ORG}/${PIPELINE}/builds/[0-9]+" |
sort -t/ -k7 -n | tail -1 || true)
[ -n "$URL" ] || die "No Buildkite build found via: gh pr checks ${PR:-<current branch>}"
BUILD="${URL##*/}"
;;
https://*)
BUILD=$(echo "$1" | sed -nE 's#.*/builds/([0-9]+).*#\1#p')
JOB=$(echo "$1" | grep -oE "#${UUID_RE}" | head -n 1 | cut -c2- || true)
SID=$(echo "$1" | grep -oE "[?&]sid=${UUID_RE}" | head -n 1 | sed 's/.*sid=//' || true)
OUT="${2:-}"
[ -n "$BUILD" ] || die "Could not parse build number from: $1"
;;
[0-9]*)
[ $# -ge 2 ] || usage
BUILD="$1"
JOB="$2"
OUT="${3:-}"
;;
*)
usage
;;
esac
COOKIES=$(mktemp)
JOBS_TSV=$(mktemp)
trap 'rm -f "$COOKIES" "$JOBS_TSV"' EXIT
# Buildkite issues a session cookie on first hit; later requests need it.
curl -fsSL -c "$COOKIES" -A "$UA" \
"https://buildkite.com/${ORG}/${PIPELINE}/builds/${BUILD}" -o /dev/null
# The build's job list (id, step uuid, state, name) is served as JSON from
# the user-facing /data/jobs endpoint. Flatten it to TSV for easy filtering:
# job_id step_uuid failed soft_failed finished slug name
curl -fsSL -b "$COOKIES" -A "$UA" \
"https://buildkite.com/${ORG}/${PIPELINE}/builds/${BUILD}/data/jobs" |
python3 -c '
import json, re, sys
data = json.load(sys.stdin)
if data.get("has_next_page"):
print("warning: job list is paginated; some jobs not shown", file=sys.stderr)
for r in data["records"]:
if r.get("type") != "script":
continue
name = (r.get("name") or "").replace("\t", " ").replace("\n", " ")
slug = re.sub(r"[^a-z0-9]+", "-", name.lower()).strip("-")[:60]
print("\t".join([
r["id"],
r.get("step_uuid") or "",
str(r.get("passed") is False),
str(bool(r.get("soft_failed"))),
str(bool(r.get("finished_at"))),
slug,
name,
]))
' >"$JOBS_TSV" || die "Could not list jobs for build ${BUILD}"
if [ -n "$SID" ] && [ -z "$JOB" ]; then
# The ?sid= in builds/<N>/list URLs is the *step* uuid, not the job uuid.
JOB=$(awk -F'\t' -v s="$SID" '$1 == s || $2 == s {print $1; exit}' "$JOBS_TSV")
[ -n "$JOB" ] || die "No job matching sid=${SID} in build ${BUILD}"
fi
fetch_job() { # <job_uuid> <output_file>
curl -fsSL -b "$COOKIES" -A "$UA" \
"https://buildkite.com/organizations/${ORG}/pipelines/${PIPELINE}/builds/${BUILD}/jobs/$1/download" \
-o "$2"
bash "$(dirname "$0")/ci-clean-log.sh" "$2"
}
if [ -n "$JOB" ]; then
# Single-job mode.
NAME=$(awk -F'\t' -v j="$JOB" '$1 == j {print $7; exit}' "$JOBS_TSV")
SLUG=$(awk -F'\t' -v j="$JOB" '$1 == j {print $6; exit}' "$JOBS_TSV")
[ -n "$OUT" ] || OUT="ci-${BUILD}-${SLUG:-${JOB:0:13}}.log"
if [ "$OUT" = "-" ]; then
TMP=$(mktemp)
fetch_job "$JOB" "$TMP"
cat "$TMP"
rm -f "$TMP"
exit 0
fi
if [ -e "$OUT" ] && [ -z "${CI_FETCH_LOG_FORCE:-}" ]; then
die "Refusing to overwrite existing ${OUT} (set CI_FETCH_LOG_FORCE=1 or pass an output path)."
fi
fetch_job "$JOB" "$OUT"
printf '%s\t%s\n' "$OUT" "${NAME:-$JOB}"
exit 0
fi
# Build-wide mode: fetch finished jobs matching $SCOPE.
[ -z "$OUT" ] || die "[output_file] is only valid when fetching a single job."
case "$SCOPE" in
failed) FILTER='$3 == "True" && $4 == "False" && $5 == "True"' ;;
soft) FILTER='$3 == "True" && $5 == "True"' ;;
all) FILTER='$5 == "True"' ;;
esac
if [ "$SCOPE" = "failed" ]; then
SOFT=$(awk -F'\t' '$3 == "True" && $4 == "True"' "$JOBS_TSV" | wc -l)
[ "$SOFT" -eq 0 ] || echo "Skipping ${SOFT} soft-failed job(s); use --soft to include them." >&2
fi
FOUND=0
EMITTED=" "
while IFS=$'\t' read -r job_id _ _ _ _ slug name; do
FOUND=$((FOUND + 1))
out="ci-${BUILD}-${slug:-${job_id:0:13}}.log"
# Retries share a name with the original job; disambiguate by uuid.
case "$EMITTED" in
*" $out "*) out="ci-${BUILD}-${slug:-job}-${job_id:0:13}.log" ;;
esac
EMITTED="${EMITTED}${out} "
if [ -e "$out" ] && [ -z "${CI_FETCH_LOG_FORCE:-}" ]; then
echo "Keeping existing ${out} (set CI_FETCH_LOG_FORCE=1 to refetch)." >&2
elif ! fetch_job "$job_id" "$out"; then
echo "Failed to download log for job ${job_id} (${name})." >&2
continue
fi
printf '%s\t%s\n' "$out" "$name"
done < <(awk -F'\t' "$FILTER" "$JOBS_TSV")
if [ "$FOUND" -eq 0 ]; then
echo "No matching jobs in build ${BUILD} (scope: ${SCOPE})." >&2
fi
-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}"
@@ -10,13 +10,20 @@ set -ex
BUCKET="vllm-wheels"
INDICES_OUTPUT_DIR="indices"
DEFAULT_VARIANT_ALIAS="cu130" # 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 ========
+130 -199
View File
@@ -28,18 +28,32 @@
###############################################################################
set -o pipefail
# Export Python path for commands that run directly on the host. Containerized
# tests set this to /vllm-workspace below so spawned Python processes do not
# depend on their current working directory.
export PYTHONPATH="${PYTHONPATH:-..}"
# Export Python path
export PYTHONPATH=".."
###############################################################################
# Helper Functions
###############################################################################
report_docker_usage() {
echo "--- Docker usage"
docker system df || true
cleanup_docker() {
# Get Docker's root directory
docker_root=$(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 $threshold%. No cleanup needed."
fi
}
cleanup_network() {
@@ -54,108 +68,6 @@ cleanup_network() {
fi
}
prepare_artifact_image() {
if [[ "${VLLM_CI_USE_ARTIFACTS:-0}" != "1" ]]; then
return 1
fi
if ! command -v buildkite-agent >/dev/null 2>&1; then
echo "buildkite-agent not found; cannot download ROCm wheel artifact"
return 1
fi
local artifact_glob="${VLLM_CI_ARTIFACT_GLOB:-artifacts/vllm-rocm-install/vllm-rocm-install.tar.gz}"
local archive=""
local metadata_file=""
local base_image="${VLLM_CI_BASE_IMAGE:-rocm/vllm-dev:ci_base}"
local artifact_image=""
local artifact_key=""
local base_digest=""
local wheel_dir=""
local context_dir=""
local workspace_dir=""
artifact_work_dir=$(mktemp -d -t vllm-rocm-artifact.XXXXXX)
wheel_dir="${artifact_work_dir}/wheels"
context_dir="${artifact_work_dir}/context"
workspace_dir="${context_dir}/workspace"
mkdir -p "${wheel_dir}" "${context_dir}/wheels" "${workspace_dir}"
echo "--- Downloading ROCm wheel artifact"
if ! buildkite-agent artifact download "${artifact_glob}" "${artifact_work_dir}"; then
echo "Failed to download ${artifact_glob}"
return 1
fi
buildkite-agent artifact download \
"artifacts/vllm-rocm-install/ci-base-image.txt" \
"${artifact_work_dir}" >/dev/null 2>&1 || true
archive=$(find "${artifact_work_dir}" -name "vllm-rocm-install.tar.gz" -type f | head -1)
if [[ -z "${archive}" || ! -f "${archive}" ]]; then
echo "ROCm wheel artifact archive was not found"
return 1
fi
metadata_file=$(find "${artifact_work_dir}" -name "ci-base-image.txt" -type f | head -1)
if [[ -n "${metadata_file}" && -s "${metadata_file}" ]]; then
base_image=$(tr -d '[:space:]' < "${metadata_file}")
fi
echo "--- Preparing local ROCm test image"
echo "Base image: ${base_image}"
docker pull "${base_image}" || return 1
base_digest=$(
docker image inspect \
--format='{{if .RepoDigests}}{{index .RepoDigests 0}}{{else}}{{.Id}}{{end}}' \
"${base_image}" 2>/dev/null || printf '%s' "${base_image}"
)
artifact_key=$(
{
printf 'base-image:%s\n' "${base_digest}"
sha256sum "${archive}"
} | sha256sum | cut -c1-24
)
artifact_image="rocm/vllm-ci-artifact:${artifact_key}"
if docker image inspect "${artifact_image}" >/dev/null 2>&1; then
echo "Using existing local ROCm artifact image: ${artifact_image}"
image_name="${artifact_image}"
return 0
fi
tar -xzf "${archive}" -C "${wheel_dir}" || return 1
if ! ls "${wheel_dir}"/*.whl >/dev/null 2>&1; then
echo "ROCm wheel artifact did not contain a wheel"
return 1
fi
if [[ ! -d "${wheel_dir}/tests" ]]; then
echo "ROCm wheel artifact did not contain the test workspace"
return 1
fi
cp "${wheel_dir}"/*.whl "${context_dir}/wheels/" || return 1
tar -C "${wheel_dir}" --exclude='*.whl' -cf - . \
| tar -C "${workspace_dir}" -xf - || return 1
cat > "${context_dir}/Dockerfile" <<'EOF'
ARG BASE_IMAGE
FROM ${BASE_IMAGE}
COPY wheels/ /tmp/vllm-wheels/
COPY workspace/ /vllm-workspace/
RUN python3 -m pip install --no-deps --force-reinstall /tmp/vllm-wheels/*.whl \
&& rm -rf /tmp/vllm-wheels
WORKDIR /vllm-workspace
EOF
echo "--- Building local ROCm test image"
docker build \
--pull=false \
--build-arg "BASE_IMAGE=${base_image}" \
-t "${artifact_image}" \
"${context_dir}" || return 1
image_name="${artifact_image}"
return 0
}
is_multi_node() {
local cmds="$1"
# Primary signal: NUM_NODES environment variable set by the pipeline
@@ -202,7 +114,8 @@ handle_pytest_exit() {
# unquoted since they have no spaces and work fine.
#
# Already-quoted expressions (containing literal single quotes) are passed
# through untouched to avoid double-quoting well-formed shell fragments.
# through untouched to avoid double-quoting values injected by
# apply_rocm_test_overrides.
#
# NOTE: This ONLY fixes -m/-k flags. It cannot recover arbitrary inner
# double-quotes stripped by the calling shell (see header comment).
@@ -334,6 +247,102 @@ re_quote_pytest_markers() {
echo "${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 "$cmds"
}
###############################################################################
# Main
###############################################################################
@@ -342,50 +351,20 @@ re_quote_pytest_markers() {
echo "--- ROCm info"
rocminfo
# --- Docker status ---
report_docker_usage
# --- Docker housekeeping ---
cleanup_docker
# --- Pull test image ---
echo "--- Pulling container"
image_name="${VLLM_CI_FALLBACK_IMAGE:-rocm/vllm-ci:${BUILDKITE_COMMIT:-local}}"
artifact_work_dir=""
image_name="rocm/vllm-ci:${BUILDKITE_COMMIT}"
container_name="rocm_${BUILDKITE_COMMIT}_$(tr -dc A-Za-z0-9 < /dev/urandom | head -c 10; echo)"
docker pull "${image_name}"
remove_docker_container() {
if docker container inspect "${container_name}" >/dev/null 2>&1; then
docker rm -f "${container_name}" || true
fi
if [[ "${VLLM_CI_REMOVE_TEST_IMAGE:-0}" == "1" ]]; then
docker image rm -f "${image_name}" || true
else
# Keep images by default so later jobs on the same AMD node can reuse layers.
echo "Keeping ROCm test image locally: ${image_name}"
fi
if [[ -n "${artifact_work_dir}" ]]; then
rm -rf "${artifact_work_dir}"
fi
docker rm -f "${container_name}" || docker image rm -f "${image_name}" || true
}
trap remove_docker_container EXIT
# python_only_compile.sh runs `python setup.py develop` and needs the full repo tree
# under /vllm-workspace (Dockerfile.rocm test stage: mkdir src && mv vllm).
# The ROCm wheel artifact tarball only ships a thin tree (tests, etc.), so
# artifact images cannot satisfy that test — use the full rocm/vllm-ci image.
_cmd_probe="${VLLM_TEST_COMMANDS:-}"
if [[ -z "${_cmd_probe}" ]]; then
_cmd_probe="$*"
fi
if [[ "${VLLM_CI_USE_ARTIFACTS:-0}" == "1" && "${_cmd_probe}" == *python_only_compile.sh* ]]; then
echo "INFO: disabling VLLM_CI_USE_ARTIFACTS for python_only_compile (requires full /vllm-workspace tree)"
export VLLM_CI_USE_ARTIFACTS=0
fi
unset -v _cmd_probe
if ! prepare_artifact_image; then
echo "Using full ROCm CI image: ${image_name}"
docker pull "${image_name}" || exit 1
fi
# --- Prepare commands ---
echo "--- Running container"
@@ -393,25 +372,15 @@ HF_CACHE="$(realpath ~)/huggingface"
mkdir -p "${HF_CACHE}"
HF_MOUNT="/root/.cache/huggingface"
# Hugging Face Hub defaults to 10s request/download timeouts, while the ROCm
# CI image currently raises downloads to 60s. AMD model-test jobs routinely
# start from a cold or partially-populated shared cache, and the 60s read cap
# has still timed out before pytest reached the vLLM behavior under test.
# Keep the CI default explicit and overridable from the Buildkite environment.
: "${HF_HUB_DOWNLOAD_TIMEOUT:=300}"
: "${HF_HUB_ETAG_TIMEOUT:=60}"
# ---- Command source selection ----
# Prefer VLLM_TEST_COMMANDS (preserves all inner quoting intact).
# Fall back to $* for backward compatibility, but warn that inner
# double-quotes will have been stripped by the calling shell.
if [[ -n "${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
@@ -428,44 +397,14 @@ 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: $commands"
# The ROCm test image often ships /vllm-workspace without .git (artifact tarball unpack).
# tests/standalone_tests/python_only_compile.sh uses merge-base(HEAD, origin/main) for
# wheels.vllm.ai; compute on the agent (full git checkout) and pass into the container.
vllm_standalone_merge_base=""
checkout="${BUILDKITE_BUILD_CHECKOUT_PATH:-}"
if [[ -z "${checkout}" || ! -d "${checkout}" ]]; then
checkout="."
fi
if git -C "${checkout}" rev-parse --is-inside-work-tree >/dev/null 2>&1; then
vllm_standalone_merge_base="$(
git -C "${checkout}" merge-base HEAD origin/main 2>/dev/null || true
)"
fi
if [[ -z "${vllm_standalone_merge_base}" ]]; then
vllm_standalone_merge_base="${BUILDKITE_COMMIT:-}"
fi
echo "INFO: passing VLLM_STANDALONE_MERGE_BASE into container: ${vllm_standalone_merge_base}"
MYPYTHONPATH="/vllm-workspace"
container_job_id="${BUILDKITE_JOB_ID:-${BUILDKITE_PARALLEL_JOB:-0}}"
container_job_id="${container_job_id//[^A-Za-z0-9_.-]/_}"
container_job_id_short="${container_job_id:0:8}"
CONTAINER_TMPDIR="/tmp/vllm-${container_job_id_short}"
CONTAINER_CACHE_ROOT="/tmp/vllm-buildkite-${container_job_id}/cache"
CONTAINER_PREFLIGHT="mkdir -p \"\$TMPDIR\" \"\$TORCHINDUCTOR_CACHE_DIR\" \"\$TRITON_CACHE_DIR\" \"\$VLLM_CACHE_ROOT\" \"\$XDG_CACHE_HOME\" && python -c \"import encodings, importlib.metadata as im, importlib.util as iu; [im.version(d) for d in ('transformers', 'torch', 'ray', 'sympy', 'markupsafe', 'vllm')]; missing=[m for m in ('torch.utils.model_zoo', 'transformers.models.nomic_bert', 'ray.dag', 'sympy.physics', 'markupsafe._speedups') if iu.find_spec(m) is None]; assert not missing, missing\""
MYPYTHONPATH=".."
# Verify GPU access
render_gid=$(getent group render | cut -d: -f3)
@@ -542,8 +481,6 @@ else
--group-add "$render_gid" \
--rm \
-e HF_TOKEN \
-e "HF_HUB_DOWNLOAD_TIMEOUT=${HF_HUB_DOWNLOAD_TIMEOUT}" \
-e "HF_HUB_ETAG_TIMEOUT=${HF_HUB_ETAG_TIMEOUT}" \
-e AWS_ACCESS_KEY_ID \
-e AWS_SECRET_ACCESS_KEY \
-e BUILDKITE_PARALLEL_JOB \
@@ -551,16 +488,10 @@ else
-v "${HF_CACHE}:${HF_MOUNT}" \
-e "HF_HOME=${HF_MOUNT}" \
-e "PYTHONPATH=${MYPYTHONPATH}" \
-e "TMPDIR=${CONTAINER_TMPDIR}/tmp" \
-e "TORCHINDUCTOR_CACHE_DIR=${CONTAINER_CACHE_ROOT}/torchinductor" \
-e "TRITON_CACHE_DIR=${CONTAINER_CACHE_ROOT}/triton" \
-e "VLLM_CACHE_ROOT=${CONTAINER_CACHE_ROOT}/vllm" \
-e "XDG_CACHE_HOME=${CONTAINER_CACHE_ROOT}/xdg" \
-e "PYTORCH_ROCM_ARCH=" \
-e "VLLM_STANDALONE_MERGE_BASE=${vllm_standalone_merge_base}" \
--name "${container_name}" \
"${image_name}" \
/bin/bash -c "${CONTAINER_PREFLIGHT} && ${commands}"
/bin/bash -c "${commands}"
exit_code=$?
handle_pytest_exit "$exit_code"
@@ -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 [ "$failed_req" -ne 0 ]; then
echo "Some requests were failed!"
exit 1
fi
@@ -8,7 +8,7 @@ set -ex
CORE_RANGE=${CORE_RANGE:-0-31}
OMP_CORE_RANGE=${OMP_CORE_RANGE:-0-31}
export CMAKE_BUILD_PARALLEL_LEVEL=32
export CMAKE_BUILD_PARALLEL_LEVEL=16
# Setup cleanup
remove_docker_container() {
@@ -31,22 +31,6 @@ function cpu_tests() {
set -e
pip list"
# Run kernel tests
docker exec cpu-test bash -c "
set -e
pytest -x -v -s tests/kernels/test_onednn.py
pytest -x -v -s tests/kernels/attention/test_cpu_attn.py
pytest -x -v -s tests/kernels/core/test_cpu_activation.py
pytest -x -v -s tests/kernels/moe/test_cpu_fused_moe.py
pytest -x -v -s tests/kernels/mamba/cpu/test_cpu_gdn_ops.py"
# skip tests requiring model downloads if HF_TOKEN is not set
# due to rate-limits
if [ -z "$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 +46,13 @@ 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/core/test_cpu_activation.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 +67,6 @@ 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 $server_pid &'
}
# All of CPU tests are expected to be finished less than 40 mins.
+1 -40
View File
@@ -7,49 +7,10 @@ set -euox pipefail
# allow to bind to different cores
CORE_RANGE=${CORE_RANGE:-48-95}
NUMA_NODE=${NUMA_NODE:-1}
AGENT_SLOT=${AGENT_SLOT:-}
IMAGE_NAME="cpu-test-${NUMA_NODE}${AGENT_SLOT:+-${AGENT_SLOT}}"
IMAGE_NAME="cpu-test-$NUMA_NODE"
TIMEOUT_VAL=$1
TEST_COMMAND=$2
# Disk hygiene knobs. Reclaim space only once the Docker root filesystem crosses
# DISK_USAGE_THRESHOLD percent, and cap the shared BuildKit cache at
# BUILDKIT_CACHE_MAX so subsequent builds keep reusing the hottest layers.
DISK_USAGE_THRESHOLD=${DISK_USAGE_THRESHOLD:-70}
BUILDKIT_CACHE_MAX=${BUILDKIT_CACHE_MAX:-80GB}
# Reclaim disk only when the host is under pressure. We trim (not purge) the
# shared BuildKit cache so cross-job/cross-agent reuse stays intact, and only
# touch dangling images; other agents' uniquely tagged images are left alone.
prune_if_disk_pressure() {
local docker_root disk_usage
docker_root=$(docker info -f '{{.DockerRootDir}}' 2>/dev/null || true)
if [ -z "$docker_root" ]; then
return 0
fi
disk_usage=$(df "$docker_root" 2>/dev/null | tail -1 | awk '{print $5}' | tr -d '%')
if [ "${disk_usage:-0}" -gt "$DISK_USAGE_THRESHOLD" ]; then
echo "--- :broom: Disk usage ${disk_usage}% exceeds ${DISK_USAGE_THRESHOLD}%, reclaiming space"
docker image prune -f || true
docker builder prune -f --keep-storage="$BUILDKIT_CACHE_MAX" || true
else
echo "Disk usage ${disk_usage:-unknown}% within ${DISK_USAGE_THRESHOLD}% threshold; skipping prune"
fi
}
# Always drop this agent's image once the job ends (the default builder never
# uses it as a cache source, so removing it costs no rebuild speed), then
# reclaim space if needed. Guard every docker call with `|| true` so the trap
# never overrides the test's exit code.
cleanup() {
docker image rm -f "$IMAGE_NAME" || true
prune_if_disk_pressure
}
trap cleanup EXIT
# Free space up front so a nearly-full host doesn't fail the build.
prune_if_disk_pressure
# building the docker image
echo "--- :docker: Building Docker image"
docker build --progress plain --tag "$IMAGE_NAME" --target vllm-test -f docker/Dockerfile.cpu .
@@ -243,10 +243,8 @@ container_name="xpu_${BUILDKITE_COMMIT}_$(tr -dc A-Za-z0-9 < /dev/urandom | head
# ---- Command source selection ----
commands=""
commands_source=""
if [[ -n "${VLLM_TEST_COMMANDS:-}" ]]; then
commands="${VLLM_TEST_COMMANDS}"
commands_source="env"
echo "Commands sourced from VLLM_TEST_COMMANDS (quoting preserved)"
elif [[ $# -gt 0 ]]; then
all_yaml=true
@@ -305,12 +303,8 @@ if [[ -z "$commands" ]]; then
fi
echo "Raw commands: $commands"
if [[ "$commands_source" != "env" ]]; then
commands=$(re_quote_pytest_markers "$commands")
echo "After re-quoting: $commands"
else
echo "Skipping re-quoting for VLLM_TEST_COMMANDS input"
fi
commands=$(re_quote_pytest_markers "$commands")
echo "After re-quoting: $commands"
commands=$(apply_intel_test_overrides "$commands")
echo "Final commands: $commands"
@@ -330,6 +324,23 @@ IMAGE="${IMAGE_TAG_XPU:-${image_name}}"
echo "Using image: ${IMAGE}"
if docker image inspect "${IMAGE}" >/dev/null 2>&1; then
echo "Image already exists locally, skipping pull"
else
echo "Image not found locally, waiting for lock..."
flock /tmp/docker-pull.lock bash -c "
if docker image inspect '${IMAGE}' >/dev/null 2>&1; then
echo 'Image already pulled by another runner'
else
echo 'Pulling image...'
timeout 900 docker pull '${IMAGE}'
fi
"
echo "Pull step completed"
fi
remove_docker_container() {
docker rm -f "${container_name}" || true
}
@@ -341,36 +352,17 @@ if [[ -z "${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 already exists locally, skipping pull"
else
echo "Image not found locally, pulling image..."
timeout 900 docker pull "${IMAGE}"
echo "Pull step completed"
fi
docker create \
docker run \
--device /dev/dri:/dev/dri \
--net=host \
--ipc=host \
--privileged \
-v /dev/dri/by-path:/dev/dri/by-path \
-v "${HOME}/.cache/huggingface:/root/.cache/huggingface" \
--entrypoint='' \
-e HF_TOKEN \
-e ZE_AFFINITY_MASK \
-e BUILDKITE_PARALLEL_JOB \
-e BUILDKITE_PARALLEL_JOB_COUNT \
-e CMDS \
-v ${HOME}/.cache/huggingface:/root/.cache/huggingface \
--entrypoint="" \
-e "HF_TOKEN=${HF_TOKEN:-}" \
-e "ZE_AFFINITY_MASK=${ZE_AFFINITY_MASK:-}" \
-e "CMDS=${commands}" \
--name "${container_name}" \
"${IMAGE}" \
bash -c 'set -e; source /opt/intel/oneapi/setvars.sh --force; source /opt/intel/oneapi/ccl/2021.15/env/vars.sh --force; echo "ZE_AFFINITY_MASK is ${ZE_AFFINITY_MASK:-}"; eval "$CMDS"' \
>/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: $RESULTS_DIR"
echo "--- Installing Python dependencies ---"
python3 -m pip install --progress-bar off git+https://github.com/thuml/depyf.git \
&& python3 -m pip install --progress-bar off pytest pytest-asyncio tpu-info \
&& python3 -m pip install --progress-bar off "lm-eval[api]>=0.4.12" \
&& python3 -m pip install --progress-bar off "lm-eval[api]>=0.4.11" \
&& python3 -m pip install --progress-bar off hf-transfer tblib==3.1.0
echo "--- Python dependencies installed ---"
@@ -136,6 +136,8 @@ run_and_track_test 3 "test_accuracy.py::test_lm_eval_accuracy_v1_engine" \
"python3 -m pytest -s -v /workspace/vllm/tests/entrypoints/llm/test_accuracy.py::test_lm_eval_accuracy_v1_engine"
run_and_track_test 4 "test_quantization_accuracy.py" \
"python3 -m pytest -s -v /workspace/vllm/tests/tpu/test_quantization_accuracy.py"
run_and_track_test 5 "examples/offline_inference/tpu.py" \
"python3 /workspace/vllm/examples/offline_inference/tpu.py"
run_and_track_test 6 "test_tpu_model_runner.py" \
"python3 -m pytest -s -v /workspace/vllm/tests/v1/tpu/worker/test_tpu_model_runner.py"
run_and_track_test 7 "test_sampler.py" \
@@ -1,51 +1,53 @@
#!/bin/bash
set -euo pipefail
# This script build the CPU docker image and run the offline inference inside the container.
# It serves a sanity check for compilation and basic model usage.
set -ex
test_suite="${1:-}"
image_name="xpu/vllm-ci:${BUILDKITE_COMMIT}"
container_name="xpu_${BUILDKITE_COMMIT}_$(tr -dc A-Za-z0-9 < /dev/urandom | head -c 10; echo)"
if [[ -z "${test_suite}" ]]; then
echo "Usage: $0 <example|v1|server>" >&2
exit 1
fi
# Try building the docker image
docker build -t "${image_name}" -f docker/Dockerfile.xpu .
case "${test_suite}" in
example)
pip install tblib==3.1.0
# Setup cleanup
remove_docker_container() {
docker rm -f "${container_name}" || 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 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
;;
v1)
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 --ignore=v1/engine/test_output_processor.py
pytest -v -s v1/sample --ignore=v1/sample/test_logprobs.py --ignore=v1/sample/test_logprobs_e2e.py -k "not test_topk_only and not test_topp_only and not test_topk_and_topp"
pytest -v -s v1/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
pytest -v -s v1/spec_decode --ignore=v1/spec_decode/test_max_len.py --ignore=v1/spec_decode/test_speculators_eagle3.py --ignore=v1/spec_decode/test_acceptance_length.py --ignore=v1/spec_decode/test_speculators_correctness.py
pytest -v -s v1/kv_connector/unit --ignore=v1/kv_connector/unit/test_multi_connector.py --ignore=v1/kv_connector/unit/test_example_connector.py --ignore=v1/kv_connector/unit/test_lmcache_integration.py --ignore=v1/kv_connector/unit/test_hf3fs_client.py --ignore=v1/kv_connector/unit/test_hf3fs_connector.py --ignore=v1/kv_connector/unit/test_hf3fs_metadata_server.py --ignore=v1/kv_connector/unit/test_offloading_connector.py
;;
server)
pip install av
cd tests
pytest -v -s entrypoints/multimodal/openai/chat_completion/test_audio_in_video.py
pytest -v -s benchmarks/test_serve_cli.py
;;
*)
echo "Unknown Intel test suite: ${test_suite}" >&2
exit 1
;;
esac
'
@@ -1,44 +0,0 @@
#!/bin/bash
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
set -euo pipefail
if python3 -c "import torch; raise SystemExit(0 if torch.version.hip is not None else 1)"; then
uv pip install --system -r /vllm-workspace/requirements/kv_connectors_rocm.txt
exit 0
fi
REQUIREMENTS_FILE="${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}"
@@ -1,205 +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_deny() {
if command -v cargo-deny >/dev/null 2>&1; then
return
fi
log_section "Installing cargo-deny"
install_cargo_binstall
cargo binstall --no-confirm cargo-deny
}
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="$CARGO_HOME/bin" sh
}
setup_pyo3_python() {
local python_version="${PYO3_PYTHON_VERSION:-3.12}"
log_section "Installing Python ${python_version} for PyO3 tests"
uv python install "$python_version"
PYO3_PYTHON="$(uv python find \
--managed-python \
--no-project \
--resolve-links \
"$python_version")"
export PYO3_PYTHON
local python_libdir
python_libdir="$("$PYO3_PYTHON" - <<'PY'
import pathlib
import sysconfig
libdir = pathlib.Path(sysconfig.get_config_var("LIBDIR"))
ldlibrary = sysconfig.get_config_var("LDLIBRARY")
assert sysconfig.get_config_var("Py_ENABLE_SHARED") == 1
assert ldlibrary
assert (libdir / ldlibrary).exists(), libdir / ldlibrary
print(libdir)
PY
)"
export LD_LIBRARY_PATH="${python_libdir}:${LD_LIBRARY_PATH:-}"
export LIBRARY_PATH="${python_libdir}:${LIBRARY_PATH:-}"
}
run_style_clippy() {
install_cargo_sort
install_cargo_deny
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 "Checking Rust dependency bans"
cargo deny \
--manifest-path rust/Cargo.toml \
check \
--config rust/deny.toml \
bans
log_section "Running clippy"
cargo clippy \
--manifest-path rust/Cargo.toml \
--workspace \
--all-targets \
--all-features \
--locked \
-- \
-D warnings
}
run_tests() {
install_uv
setup_pyo3_python
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 "$BACK" \
@@ -33,14 +33,6 @@ if [[ -n "${ATTENTION_BACKEND:-}" ]]; then
EXTRA_ARGS+=(--attention-backend "${ATTENTION_BACKEND}")
fi
# ROCm: run eager to avoid intermittent HIP-graph decode corruption.
# See https://github.com/ROCm/clr/issues/279
# TODO(aarushjain29): Revert after TheRock 7.14
if command -v rocm-smi &> /dev/null || command -v amd-smi &> /dev/null || [[ -d /opt/rocm ]] || [[ -n "${ROCM_PATH:-}" ]]; then
echo "ROCm platform detected: adding --enforce-eager to avoid HIP-graph decode corruption"
EXTRA_ARGS+=(--enforce-eager)
fi
cleanup() {
if [[ -n "${SERVER_PID:-}" ]] && kill -0 "${SERVER_PID}" 2>/dev/null; then
kill "${SERVER_PID}" 2>/dev/null || true
@@ -59,7 +51,6 @@ vllm serve "$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 "${DATA_PARALLEL_SIZE}" \
--enable-expert-parallel \
@@ -28,7 +28,6 @@
# BFCL_MAX_MODEL_LEN - Max model length (default: 4096)
# BFCL_PORT - Server port (default: 8000)
# BFCL_REASONING_PARSER - Reasoning parser name (default: disabled)
# BFCL_TEMPERATURE - Temperature (default: 0.0)
# BFCL_EXTRA_ARGS - Additional vLLM server args
set -euo pipefail
@@ -44,7 +43,6 @@ TP_SIZE="${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
+874 -693
View File
File diff suppressed because it is too large Load Diff
+2 -18
View File
@@ -2,8 +2,7 @@ group: Attention
depends_on:
- image-build
steps:
- label: V1 attention (H100-MI300)
key: v1-attention-h100-mi300
- label: V1 attention (H100)
timeout_in_minutes: 30
device: h100
source_file_dependencies:
@@ -13,25 +12,10 @@ steps:
- tests/v1/attention
commands:
- pytest -v -s v1/attention
mirror:
amd:
device: mi325_1
timeout_in_minutes: 70
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/config/attention.py
- vllm/model_executor/layers/attention
- vllm/v1/attention
- tests/v1/attention
- vllm/_aiter_ops.py
- vllm/envs.py
- vllm/platforms/rocm.py
- 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
+2 -9
View File
@@ -3,22 +3,15 @@ depends_on:
- image-build
steps:
- label: Basic Correctness
key: basic-correctness
timeout_in_minutes: 30
device: h200_18gb
source_file_dependencies:
- vllm/
- tests/basic_correctness/test_basic_correctness
- tests/basic_correctness/test_cpu_offload
- tests/basic_correctness/test_mem.py
- tests/basic_correctness/test_cumem.py
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s basic_correctness/test_mem.py
- pytest -v -s basic_correctness/test_cumem.py
- pytest -v -s basic_correctness/test_basic_correctness.py
- pytest -v -s basic_correctness/test_cpu_offload.py
mirror:
amd:
device: mi325_1
timeout_in_minutes: 50
depends_on:
- image-build-amd
+2 -9
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:
@@ -11,15 +10,9 @@ steps:
- tests/benchmarks/
commands:
- pytest -v -s benchmarks/
mirror:
amd:
device: mi300_1
depends_on:
- image-build-amd
- 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/"
@@ -28,4 +21,4 @@ steps:
- benchmarks/attention_benchmarks/
- vllm/v1/attention/
commands:
- python3 benchmarks/attention_benchmarks/benchmark.py --backends flash flashinfer --batch-specs "8q1s1k"
- python3 benchmarks/attention_benchmarks/benchmark.py --backends flash flashinfer --batch-specs "8q1s1k" --repeats 1 --warmup-iters 1
+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/
+3 -10
View File
@@ -2,23 +2,17 @@ group: CUDA
depends_on:
- image-build
steps:
- label: Platform Tests
key: platform-tests
- label: 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
+19 -108
View File
@@ -3,185 +3,96 @@ 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/
- vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
- tests/v1/kv_connector/nixl_integration/
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
- bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
mirror:
amd:
device: mi300_4
timeout_in_minutes: 110
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl/
- tests/v1/kv_connector/nixl_integration/
- vllm/platforms/rocm.py
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors_rocm.txt
- ATTENTION_BACKEND=TRITON_ATTN bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
- label: Distributed FlashInfer NixlConnector PD accuracy (4 GPUs)
key: distributed-flashinfer-nixlconnector-pd-accuracy-4-gpus
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl/
- vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
- tests/v1/kv_connector/nixl_integration/
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
- 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/
- vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
- tests/v1/kv_connector/nixl_integration/
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- 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
mirror:
amd:
device: mi300_4
timeout_in_minutes: 50
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl/
- tests/v1/kv_connector/nixl_integration/
- vllm/platforms/rocm.py
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors_rocm.txt
- DP_EP=1 ATTENTION_BACKEND=TRITON_ATTN bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
- label: CrossLayer KV layout Distributed NixlConnector PD accuracy tests (4 GPUs)
key: crosslayer-kv-layout-distributed-nixlconnector-pd-accuracy-tests-4-gpus
timeout_in_minutes: 30
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl/
- vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
- tests/v1/kv_connector/nixl_integration/
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- 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
mirror:
amd:
device: mi300_4
timeout_in_minutes: 110
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl/
- tests/v1/kv_connector/nixl_integration/
- vllm/platforms/rocm.py
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors_rocm.txt
- CROSS_LAYERS_BLOCKS=True ATTENTION_BACKEND=TRITON_ATTN bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
- label: Hybrid SSM NixlConnector PD accuracy tests (4 GPUs)
key: hybrid-ssm-nixlconnector-pd-accuracy-tests-4-gpus
timeout_in_minutes: 25
timeout_in_minutes: 20
working_dir: "/vllm-workspace/tests"
num_devices: 4
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl/
- vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
- tests/v1/kv_connector/nixl_integration/
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- 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
mirror:
amd:
device: mi300_4
timeout_in_minutes: 60
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl/
- tests/v1/kv_connector/nixl_integration/
- vllm/platforms/rocm.py
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors_rocm.txt
- HYBRID_SSM=1 ATTENTION_BACKEND=TRITON_ATTN bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
- label: Hybrid SSM NixlConnector PD prefix cache test (2 GPUs)
key: hybrid-ssm-nixlconnector-pd-prefix-cache-2-gpus
timeout_in_minutes: 25
working_dir: "/vllm-workspace/tests"
num_devices: 2
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl/
- vllm/v1/core/sched/
- vllm/v1/core/kv_cache_coordinator.py
- tests/v1/kv_connector/nixl_integration/
commands:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- bash v1/kv_connector/nixl_integration/run_mamba_prefix_cache_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/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:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- 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)
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/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:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- bash v1/kv_connector/nixl_integration/config_sweep_spec_decode_test.sh
mirror:
amd:
device: mi300_2
timeout_in_minutes: 60
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/distributed/kv_transfer/kv_connector/v1/nixl/
- vllm/v1/worker/kv_connector_model_runner_mixin.py
- tests/v1/kv_connector/nixl_integration/
- vllm/platforms/rocm.py
commands:
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors_rocm.txt
- ATTENTION_BACKEND=TRITON_ATTN bash v1/kv_connector/nixl_integration/config_sweep_spec_decode_test.sh
- 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)
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/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:
- bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
- bash v1/kv_connector/nixl_integration/run_multi_connector_edge_case_test.sh
- uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
- bash v1/kv_connector/nixl_integration/run_multi_connector_edge_case_test.sh
+13 -46
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
@@ -37,24 +35,8 @@ steps:
- TP_SIZE=1 DP_SIZE=2 pytest -v -s v1/distributed/test_eagle_dp.py
- TP_SIZE=1 DP_SIZE=2 pytest -v -s v1/distributed/test_external_lb_dp.py
- DP_SIZE=2 pytest -v -s entrypoints/openai/test_multi_api_servers.py
mirror:
amd:
device: mi300_2
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/distributed/
- vllm/engine/
- vllm/executor/
- vllm/worker/worker_base.py
- vllm/v1/engine/
- vllm/v1/worker/
- tests/v1/distributed
- tests/entrypoints/openai/test_multi_api_servers.py
- vllm/platforms/rocm.py
- label: Distributed Compile + RPC Tests (2 GPUs)
key: distributed-compile-rpc-tests-2-gpus
timeout_in_minutes: 20
working_dir: "/vllm-workspace/tests"
num_devices: 2
@@ -77,7 +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
@@ -100,7 +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
@@ -108,8 +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
@@ -126,13 +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
@@ -153,7 +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
@@ -174,29 +153,25 @@ steps:
# test multi-node TP with multiproc executor (simulated on single node)
- pytest -v -s distributed/test_multiproc_executor.py::test_multiproc_executor_multi_node
- label: Distributed Tests (8xH100)
key: distributed-tests-8xh100
- label: 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 (4xA100)
key: distributed-tests-4xa100
- label: Distributed Tests (4 GPUs)(A100)
device: a100
optional: true
num_devices: 4
@@ -210,8 +185,7 @@ steps:
- TARGET_TEST_SUITE=A100 pytest basic_correctness/ -v -s -m 'distributed(num_gpus=2)'
- pytest -v -s -x lora/test_mixtral.py
- label: Distributed Tests (2xH100-2xMI300)
key: distributed-tests-2xh100-2xmi300
- label: Distributed Tests (2 GPUs)(H100)
timeout_in_minutes: 15
device: h100
optional: true
@@ -220,14 +194,13 @@ 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
- label: Distributed Tests (2xB200)
key: distributed-tests-2xb200
device: b200-k8s
- label: Distributed Tests (2 GPUs)(B200)
device: b200
optional: true
working_dir: "/vllm-workspace/"
num_devices: 2
@@ -235,12 +208,8 @@ 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
@@ -253,12 +222,11 @@ 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: Pipeline + Context Parallelism (4 GPUs)
key: pipeline-context-parallelism-4-gpus
timeout_in_minutes: 60
working_dir: "/vllm-workspace/tests"
num_devices: 4
@@ -273,7 +241,6 @@ 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 -9
View File
@@ -2,8 +2,7 @@ group: E2E Integration
depends_on:
- image-build
steps:
- label: DeepSeek V2-Lite Sync EPLB Accuracy (4xH100)
key: deepseek-v2-lite-sync-eplb-accuracy-4xh100
- 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 (4xH100)
key: qwen3-30b-a3b-fp8-block-sync-eplb-accuracy-4xh100
- label: Qwen3-30B-A3B-FP8-block Accuracy
timeout_in_minutes: 60
device: h100
optional: true
@@ -22,10 +20,9 @@ steps:
commands:
- bash .buildkite/scripts/scheduled_integration_test/qwen30b_a3b_fp8_block_ep_eplb.sh 0.8 200 8020
- label: Qwen3-30B-A3B-FP8-block Sync EPLB Accuracy (2xB200)
key: qwen3-30b-a3b-fp8-block-sync-eplb-accuracy-2xb200
- 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"
@@ -33,7 +30,6 @@ steps:
- 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
@@ -43,7 +39,6 @@ steps:
- 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
+12 -86
View File
@@ -3,38 +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
mirror:
amd:
device: mi325_1
timeout_in_minutes: 60
depends_on:
- image-build-amd
- 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/
@@ -42,15 +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:
@@ -58,96 +32,48 @@ 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/
- tests/v1/e2e/general/
commands:
- pytest -v -s v1/e2e/general --ignore v1/e2e/general/test_async_scheduling.py
mirror:
amd:
device: mi250_1
timeout_in_minutes: 35
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/v1/
- tests/v1/e2e/general/
- vllm/platforms/rocm.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: mi300_2
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
+65 -136
View File
@@ -2,153 +2,90 @@ 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:
- vllm/entrypoints
- tests/entrypoints/unit_tests
- tests/entrypoints/weight_transfer
- tests/entrypoints/
commands:
- pytest -v -s entrypoints/unit_tests
- pytest -v -s entrypoints/weight_transfer
- pytest -v -s entrypoints/openai/tool_parsers
- 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:
- vllm/
- tests/entrypoints/llm
- tests/entrypoints/offline_mode
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s entrypoints/llm --ignore=entrypoints/llm/test_generate.py --ignore=entrypoints/llm/test_collective_rpc.py --ignore=entrypoints/llm/offline_mode
- 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/llm/offline_mode # Needs to avoid interference with other tests
- pytest -v -s entrypoints/offline_mode # Needs to avoid interference with other tests
- label: Entrypoints Integration (API Server openai - Part 1)
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
- tests/entrypoints/openai
- 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_chat_with_tool_reasoning.py --ignore=entrypoints/openai/chat_completion/test_oot_registration.py
mirror:
amd:
device: mi325_1
# TODO(akaratza): Test after Torch >= 2.12 bump
soft_fail: true
depends_on:
- image-build-amd
- label: Entrypoints Integration (API Server)
key: entrypoints-integration-api-server
device: h200_35gb
- label: 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
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
mirror:
amd:
device: mi325_1
depends_on:
- image-build-amd
- label: Entrypoints Integration (API Server openai - Part 3)
timeout_in_minutes: 50
device: h200_18gb
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
- tests/entrypoints/openai
- 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/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)
timeout_in_minutes: 130
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
- tests/entrypoints/serve
- tests/entrypoints/scale_out
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s entrypoints/serve --ignore=entrypoints/serve/dev/rpc
- PYTHONPATH=/vllm-workspace pytest -v -s entrypoints/serve/dev/rpc
- pytest -v -s entrypoints/scale_out
mirror:
amd:
device: mi325_1
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:
- vllm/
- tests/entrypoints/openai
- tests/entrypoints/test_chat_utils
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s entrypoints/openai --ignore=entrypoints/openai/completion --ignore=entrypoints/openai/chat_completion --ignore=entrypoints/openai/responses --ignore=entrypoints/openai/correctness
mirror:
amd:
device: mi325_1
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
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s entrypoints/openai/chat_completion
- pytest -v -s entrypoints/openai/completion --ignore=entrypoints/openai/completion/test_tensorizer_entrypoint.py
mirror:
amd:
device: mi325_1
timeout_in_minutes: 80
depends_on:
- image-build-amd
- label: Entrypoints Integration (API Server Generate)
key: entrypoints-integration-api-server-generate
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
- tests/entrypoints/rpc
- tests/entrypoints/serve/instrumentator
- tests/tool_use
- tests/entrypoints/tool_parsers
- tests/entrypoints/anthropic
- tests/entrypoints/generate
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s entrypoints/serve/instrumentator
- PYTHONPATH=/vllm-workspace pytest -v -s entrypoints/rpc
- pytest -v -s tool_use
- pytest -v -s entrypoints/tool_parsers
- pytest -v -s entrypoints/generate
- pytest -v -s entrypoints/anthropic
mirror:
amd:
device: mi325_1
timeout_in_minutes: 60
depends_on:
- image-build-amd
- label: Entrypoints Integration (Responses API)
key: entrypoints-integration-responses-api
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
- tests/entrypoints/openai/responses
commands:
- pytest -v -s entrypoints/openai/responses
- 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
- label: Entrypoints Integration (Multimodal)
device: h200_35gb
key: entrypoints-integration-multimodal
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
- tests/entrypoints/multimodal
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s entrypoints/multimodal
- label: Entrypoints Integration (Pooling)
key: entrypoints-integration-pooling
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
@@ -158,29 +95,21 @@ steps:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s entrypoints/pooling
- label: Entrypoints Integration (Responses API)
timeout_in_minutes: 50
working_dir: "/vllm-workspace/tests"
source_file_dependencies:
- vllm/
- tests/entrypoints/openai/responses
commands:
- 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/
mirror:
amd:
device: mi325_1
depends_on:
- image-build-amd
source_file_dependencies:
- csrc/
- vllm/entrypoints/openai/
- vllm/model_executor/layers/
- vllm/v1/attention/backends/
- vllm/v1/attention/selector.py
- vllm/_aiter_ops.py
- vllm/platforms/rocm.py
- vllm/model_executor/model_loader/
commands:
- bash ../tools/install_torchcodec_rocm.sh || exit 1
- 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"
@@ -14,19 +13,8 @@ steps:
commands:
- pytest -v -s distributed/test_eplb_algo.py
- pytest -v -s distributed/test_eplb_utils.py
mirror:
amd:
device: mi300_1
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/distributed/eplb
- tests/distributed/test_eplb_algo.py
- tests/distributed/test_eplb_utils.py
- vllm/platforms/rocm.py
- label: EPLB Execution # 17min
key: eplb-execution
timeout_in_minutes: 27
working_dir: "/vllm-workspace/tests"
num_devices: 4
@@ -38,7 +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"
+10 -130
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/"
@@ -15,18 +14,15 @@ 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/
- tests/kernels/core
- tests/kernels/test_concat_mla_q.py
- tests/kernels/test_fused_qk_norm_rope_gate.py
commands:
- pytest -v -s kernels/core --ignore=kernels/core/test_minimax_reduce_rms.py kernels/test_concat_mla_q.py kernels/test_fused_qk_norm_rope_gate.py
- 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
@@ -39,32 +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
- tests/kernels/test_top_k_per_row.py # it runs on Blackwell too - some kernels have arch-specific optimizations
commands:
- pytest -v -s kernels/test_fused_deepseek_v4_*.py
- pytest -v -s kernels/test_top_k_per_row.py
- label: Deepseek V4 Kernel Test (B200)
key: deepseek-v4-kernel-test-b200
timeout_in_minutes: 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/
@@ -76,36 +47,8 @@ steps:
commands:
- pytest -v -s kernels/attention --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
parallelism: 2
mirror:
amd:
device: mi325_1
timeout_in_minutes: 55
depends_on:
- image-build-amd
source_file_dependencies:
- csrc/attention/
- vllm/v1/attention
- vllm/model_executor/layers/attention
- tests/kernels/attention
- vllm/_aiter_ops.py
- vllm/envs.py
- vllm/platforms/rocm.py
- label: Kernels Attention DiffKV Test (H100)
key: kernels-attention-diffkv-test-h100
timeout_in_minutes: 20
device: h100
num_devices: 1
source_file_dependencies:
- vllm/v1/attention/ops/triton_unified_attention_diffkv.py
- vllm/v1/attention/backends/triton_attn_diffkv.py
- vllm/v1/attention/backends/flash_attn_diffkv.py
- tests/kernels/attention/test_triton_unified_attention_diffkv.py
commands:
- pytest -v -s kernels/attention/test_triton_unified_attention_diffkv.py
- label: Kernels Quantization Test %N
key: kernels-quantization-test
timeout_in_minutes: 90
source_file_dependencies:
- csrc/quantization/
@@ -114,23 +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
- vllm/config/
- 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/
@@ -144,25 +72,8 @@ steps:
- pytest -v -s kernels/moe --ignore=kernels/moe/test_modular_oai_triton_moe.py --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
- pytest -v -s kernels/moe/test_modular_oai_triton_moe.py --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
parallelism: 5
mirror:
amd:
device: mi325_1
timeout_in_minutes: 50
source_file_dependencies:
- csrc/quantization/cutlass_w8a8/moe/
- csrc/moe/
- tests/kernels/moe
- vllm/model_executor/layers/fused_moe/
- vllm/distributed/device_communicators/
- vllm/envs.py
- vllm/config
- vllm/_aiter_ops.py
- vllm/platforms/rocm.py
depends_on:
- image-build-amd
- label: Kernels Mamba Test
key: kernels-mamba-test
timeout_in_minutes: 45
source_file_dependencies:
- csrc/mamba/
@@ -171,28 +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
@@ -200,31 +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
@@ -257,25 +145,22 @@ steps:
- 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==1.1.0
- pip install helion==1.0.0
- pytest -v -s kernels/helion/
- label: Kernels FP8 MoE Test (1xH100)
key: kernels-fp8-moe-test-1xh100
- label: Kernels FP8 MoE Test (1 H100)
timeout_in_minutes: 90
device: h100
num_devices: 1
@@ -291,8 +176,7 @@ steps:
- pytest -v -s kernels/moe/test_triton_moe_no_act_mul.py
- pytest -v -s kernels/moe/test_triton_moe_ptpc_fp8.py
- label: Kernels FP8 MoE Test (2xH100)
key: kernels-fp8-moe-test-2xh100
- label: Kernels FP8 MoE Test (2 H100s)
timeout_in_minutes: 90
device: h100
num_devices: 2
@@ -302,9 +186,8 @@ 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:
@@ -315,7 +198,6 @@ steps:
- label: Kernels FusedMoE Layer Test (2 H100s)
key: kernels-fusedmoe-layer-test-2-h100s
timeout_in_minutes: 90
device: h100
num_devices: 2
@@ -332,9 +214,8 @@ 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/
@@ -346,4 +227,3 @@ steps:
- vllm/config
commands:
- pytest -v -s kernels/moe/test_moe_layer.py
- pytest -v -s kernels/moe/test_deepep_v2_moe.py
+12 -142
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/
@@ -12,24 +10,8 @@ steps:
autorun_on_main: true
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-small.txt
mirror:
amd:
device: mi325_1
timeout_in_minutes: 55
depends_on:
- image-build-amd
source_file_dependencies:
- csrc/
- vllm/model_executor/layers/quantization
- vllm/model_executor/models/
- vllm/model_executor/model_loader/
- vllm/v1/attention/backends/
- vllm/v1/attention/selector.py
- vllm/_aiter_ops.py
- vllm/platforms/rocm.py
# - label: LM Eval Large Models (4xA100)
# key: lm-eval-large-models-4xa100
# - label: LM Eval Large Models (4 GPUs)(A100)
# device: a100
# optional: true
# num_devices: 4
@@ -41,8 +23,7 @@ steps:
# - export VLLM_WORKER_MULTIPROC_METHOD=spawn
# - pytest -s -v test_lm_eval_correctness.py --config-list-file=configs/models-large.txt --tp-size=4
- label: LM Eval Large Models (4xH100)
key: lm-eval-large-models-4xh100
- label: LM Eval Large Models (4 GPUs)(H100)
device: h100
optional: true
num_devices: 4
@@ -54,10 +35,9 @@ steps:
- export VLLM_USE_DEEP_GEMM=0 # We found Triton is faster than DeepGEMM for H100
- pytest -s -v test_lm_eval_correctness.py --config-list-file=configs/models-large-hopper.txt --tp-size=4
- label: LM Eval Small Models (2xB200)
key: lm-eval-small-models-2xb200
- label: LM Eval Small Models (B200)
timeout_in_minutes: 120
device: b200-k8s
device: b200
optional: true
source_file_dependencies:
- csrc/
@@ -65,34 +45,9 @@ steps:
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-blackwell.txt
- label: LM Eval Small Models (2xL4)
key: lm-eval-small-models-tp
timeout_in_minutes: 10
num_devices: 2
optional: true
source_file_dependencies:
- csrc/
- vllm/model_executor/layers/quantization
autorun_on_main: true
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-small-tp.txt
- label: LM Eval Large Models EP (2xB200)
key: lm-eval-large-models-ep-2xb200
- label: LM Eval Qwen3.5 Models (B200)
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 (2xB200)
key: lm-eval-qwen3-5-models-2xb200
timeout_in_minutes: 120
device: b200-k8s
device: b200
optional: true
num_devices: 2
source_file_dependencies:
@@ -106,27 +61,15 @@ steps:
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-qwen35-blackwell.txt
- label: LM Eval Large Models (8xH200)
key: lm-eval-large-models-8xh200
- label: LM Eval Large Models (H200)
timeout_in_minutes: 60
device: h200
optional: true
num_devices: 8
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-h200.txt
mirror:
amd:
device: mi300_8
timeout_in_minutes: 180
depends_on:
- image-build-amd
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- export PYTORCH_ROCM_ARCH=gfx942 # Limit Quark compilation to save time
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-mi3xx.txt
- label: MoE Refactor Integration Test (H100 - TEMPORARY)
key: moe-refactor-integration-test-h100-temporary
device: h100
optional: true
num_devices: 2
@@ -134,69 +77,22 @@ 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:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/moe-refactor-dp-ep/config-b200.txt
- label: LM Eval Humming (A100 - TEMPORARY)
key: lm-eval-humming-a100
timeout_in_minutes: 30
device: a100
optional: true
num_devices: 1
source_file_dependencies:
- vllm/model_executor/layers/quantization/humming.py
- vllm/model_executor/layers/quantization/utils/humming_utils.py
- vllm/model_executor/layers/fused_moe/experts/fused_humming_moe.py
- vllm/model_executor/layers/fused_moe/oracle/mxfp4.py
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config.txt
- label: LM Eval Humming (H100 - TEMPORARY)
key: lm-eval-humming-h100
timeout_in_minutes: 30
device: h100
optional: true
num_devices: 1
source_file_dependencies:
- vllm/model_executor/layers/quantization/humming.py
- vllm/model_executor/layers/quantization/utils/humming_utils.py
- vllm/model_executor/layers/fused_moe/experts/fused_humming_moe.py
- vllm/model_executor/layers/fused_moe/oracle/mxfp4.py
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config.txt
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config-act-fp8.txt
- label: LM Eval Humming (B200 - TEMPORARY)
key: lm-eval-humming-b200
timeout_in_minutes: 30
device: b200-k8s
optional: true
num_devices: 1
source_file_dependencies:
- vllm/model_executor/layers/quantization/humming.py
- vllm/model_executor/layers/quantization/utils/humming_utils.py
- vllm/model_executor/layers/fused_moe/experts/fused_humming_moe.py
- vllm/model_executor/layers/fused_moe/oracle/mxfp4.py
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config.txt
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config-act-fp8.txt
- 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
@@ -205,8 +101,7 @@ steps:
commands:
- pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/models-turboquant.txt
- label: GPQA Eval (GPT-OSS) (2xH100)
key: gpqa-eval-gpt-oss-2xh100
- label: GPQA Eval (GPT-OSS) (H100)
timeout_in_minutes: 120
device: h100
optional: true
@@ -219,10 +114,9 @@ steps:
- uv pip install --system 'gpt-oss[eval]==0.0.5'
- pytest -s -v evals/gpt_oss/test_gpqa_correctness.py --config-list-file=configs/models-h100.txt
- label: GPQA Eval (GPT-OSS) (2xB200)
key: gpqa-eval-gpt-oss-2xb200
- label: GPQA Eval (GPT-OSS) (B200)
timeout_in_minutes: 120
device: b200-k8s
device: b200
optional: true
num_devices: 2
source_file_dependencies:
@@ -232,27 +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: GPQA Eval (GPT-OSS) (DGX Spark)
key: gpqa-eval-gpt-oss-spark
timeout_in_minutes: 120
device: dgx-spark
optional: true
num_devices: 1
depends_on:
- arm64-image-build
source_file_dependencies:
- csrc/
- vllm/model_executor/layers/quantization
- tests/evals/gpt_oss/
commands:
- uv pip install --system 'gpt-oss[eval]==0.0.5'
- pytest -s -v evals/gpt_oss/test_gpqa_correctness.py --config-list-file=configs/models-spark.txt
- label: 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 -17
View File
@@ -3,35 +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
mirror:
amd:
device: mi325_1
working_dir: "/vllm-workspace/tests"
timeout_in_minutes: 60
source_file_dependencies:
- vllm/lora
- tests/lora
- vllm/platforms/rocm.py
depends_on:
- image-build-amd
- 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
@@ -43,7 +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
+24 -225
View File
@@ -3,19 +3,9 @@ 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
@@ -23,27 +13,15 @@ steps:
- pytest -v -s -m 'not slow_test' v1/spec_decode
mirror:
amd:
device: mi300_1
timeout_in_minutes: 65
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
@@ -63,42 +41,23 @@ 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
@@ -108,30 +67,14 @@ steps:
mirror:
amd:
device: mi325_1
timeout_in_minutes: 60
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:
@@ -142,50 +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
- vllm/distributed/kv_transfer/kv_connector/v1/example_hidden_states_connector.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: Extract Hidden States Integration (2 GPUs)
key: extract-hidden-states-integration-2-gpus
timeout_in_minutes: 20
num_devices: 2
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
- vllm/distributed/kv_transfer/kv_connector/v1/example_hidden_states_connector.py
- tests/v1/kv_connector/extract_hidden_states_integration
commands:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s -m 'distributed' 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
@@ -193,8 +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:
@@ -211,47 +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
mirror:
amd:
device: mi325_1
source_file_dependencies:
- vllm/entrypoints
- vllm/multimodal
- examples/
- vllm/platforms/rocm.py
depends_on:
- image-build-amd
- 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 \
@@ -260,53 +140,20 @@ steps:
'opentelemetry-exporter-otlp>=1.26.0' \
'opentelemetry-semantic-conventions-ai>=0.4.1'"
- pytest -v -s v1/tracing
mirror:
amd:
device: mi325_2
depends_on:
- image-build-amd
optional: true
- label: Python-only Installation
key: python-only-installation
depends_on: ~
optional: true
timeout_in_minutes: 20
device: h200_18gb
source_file_dependencies:
- tests/standalone_tests/python_only_compile.sh
- setup.py
commands:
- bash standalone_tests/python_only_compile.sh
mirror:
amd:
device: mi325_1
timeout_in_minutes: 20
depends_on:
- image-build-amd
source_file_dependencies:
- tests/standalone_tests/python_only_compile.sh
- setup.py
- vllm/platforms/rocm.py
- label: Async Engine, Inputs, Utils, Worker
device: h200_35gb
key: async-engine-inputs-utils-worker
timeout_in_minutes: 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_
@@ -316,37 +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/parser/
- 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/
- tests/test_envs.py
- vllm/
- tests/test_inputs.py
- tests/test_outputs.py
- tests/test_pooling_params.py
@@ -354,45 +175,27 @@ steps:
- tests/multimodal
- tests/renderers
- tests/standalone_tests/lazy_imports.py
- tests/tokenizers_
- tests/reasoning
- tests/tool_parsers
- tests/tokenizers_
- tests/parser
- tests/transformers_utils
- tests/config
device: cpu-small
commands:
- python3 standalone_tests/lazy_imports.py
- pytest -v -s test_envs.py
- pytest -v -s test_inputs.py
- pytest -v -s test_outputs.py
- pytest -v -s test_pooling_params.py
- pytest -v -s test_ray_env.py
- pytest -v -s -m 'cpu_test' multimodal
- pytest -v -s renderers
- pytest -v -s reasoning
- pytest -v -s tool_parsers
- pytest -v -s tokenizers_
- pytest -v -s parser
- 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 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:
@@ -408,9 +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
@@ -423,11 +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 -23
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
@@ -14,25 +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
mirror:
amd:
device: mi300_1
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/engine/arg_utils.py
- vllm/config/model.py
- vllm/model_executor
- tests/model_executor
- tests/entrypoints/openai/completion/test_tensorizer_entrypoint.py
- vllm/_aiter_ops.py
- vllm/platforms/rocm.py
- pytest -v -s model_executor -m '(not slow_test)'
- pytest -v -s entrypoints/openai/completion/test_tensorizer_entrypoint.py
+14 -24
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
@@ -94,29 +87,26 @@ steps:
- vllm/v1/worker/gpu_worker.py
- tests/distributed/test_pipeline_parallel.py
- tests/distributed/test_pp_cudagraph.py
- tests/v1/distributed/test_pp_dp_v2.py
commands:
- set -x
- export VLLM_USE_V2_MODEL_RUNNER=1
- pytest -v -s distributed/test_pipeline_parallel.py -k "not ray and not Jamba"
- pytest -v -s distributed/test_pp_cudagraph.py -k "not ray"
- pytest -v -s v1/distributed/test_pp_dp_v2.py
- 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"
+31 -7
View File
@@ -3,9 +3,7 @@ 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
source_file_dependencies:
- vllm/
@@ -18,8 +16,6 @@ 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 +31,6 @@ steps:
torch_nightly: {}
- label: Basic Models Tests (Other)
device: h200_35gb
key: basic-models-tests-other
timeout_in_minutes: 45
source_file_dependencies:
- vllm/
@@ -51,8 +45,8 @@ steps:
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
@@ -63,3 +57,33 @@ 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
- label: Transformers Backward Compatibility Models Test
working_dir: "/vllm-workspace/"
optional: true
soft_fail: true
commands:
- pip install transformers==4.57.5
- 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/offline_inference/basic/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 -39
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
@@ -15,13 +13,8 @@ steps:
- pytest -v -s models/language -m 'core_model and (not slow_test)'
mirror:
torch_nightly: {}
amd:
device: mi300_1
depends_on:
- image-build-amd
- label: Language Models Tests (Extra Standard) %N
key: language-models-tests-extra-standard
timeout_in_minutes: 45
source_file_dependencies:
- vllm/model_executor/models/
@@ -36,24 +29,8 @@ steps:
parallelism: 2
mirror:
torch_nightly: {}
amd:
device: mi300_1
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/model_executor/models/
- vllm/model_executor/model_loader/
- vllm/model_executor/layers/
- vllm/v1/attention/backends/
- vllm/v1/attention/selector.py
- tests/models/language/pooling/test_embedding.py
- tests/models/language/generation/test_common.py
- tests/models/language/pooling/test_classification.py
- vllm/_aiter_ops.py
- vllm/platforms/rocm.py
- label: Language Models Tests (Hybrid) %N
key: language-models-tests-hybrid
timeout_in_minutes: 75
source_file_dependencies:
- vllm/
@@ -68,19 +45,8 @@ steps:
parallelism: 2
mirror:
torch_nightly: {}
amd:
device: mi325_1
timeout_in_minutes: 90
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:
@@ -92,9 +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
@@ -105,8 +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:
@@ -117,12 +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
+3 -39
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:
@@ -30,6 +28,7 @@ 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
@@ -37,8 +36,6 @@ 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/
@@ -54,16 +51,13 @@ 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/
- tests/models/multimodal
commands:
- pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
- pytest -v -s models/multimodal -m core_model --ignore models/multimodal/generation/test_common.py --ignore models/multimodal/generation/test_ultravox.py --ignore models/multimodal/generation/test_qwen2_5_vl.py --ignore models/multimodal/generation/test_qwen2_vl.py --ignore models/multimodal/generation/test_whisper.py --ignore models/multimodal/generation/test_memory_leak.py --ignore models/multimodal/generation/test_vit_cudagraph.py --ignore models/multimodal/processing
- pytest -v -s models/multimodal/generation/test_vit_cudagraph.py -m core_model
- pytest -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:
@@ -73,8 +67,7 @@ steps:
- 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:
@@ -87,7 +80,6 @@ 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:
@@ -99,8 +91,6 @@ 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:
@@ -109,20 +99,8 @@ steps:
- vllm/v1/core/
commands:
- pytest -s -v test_lm_eval_correctness.py --config-list-file=configs/models-mm-small.txt --tp-size=1
mirror:
amd:
device: mi300_1
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/multimodal/
- vllm/inputs/
- vllm/v1/core/
- vllm/platforms/rocm.py
- vllm/model_executor/model_loader/
- label: Multi-Modal Models (Extended Generation 1)
key: multi-modal-models-extended-generation-1
optional: true
source_file_dependencies:
- vllm/
@@ -139,8 +117,6 @@ 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/
@@ -150,8 +126,6 @@ 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/
@@ -161,7 +135,6 @@ 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:
@@ -169,12 +142,3 @@ steps:
- tests/models/multimodal/pooling
commands:
- pytest -v -s models/multimodal/pooling -m 'not core_model'
mirror:
amd:
device: mi325_1
timeout_in_minutes: 60
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/
- tests/models/multimodal/pooling
+3 -22
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
@@ -27,10 +26,6 @@ steps:
- pip install -e ./plugins/bge_m3_sparse_plugin
- pytest -v -s plugins_tests/test_bge_m3_sparse_io_processor_plugins.py
- pip uninstall bge_m3_sparse_plugin -y
# test colbert_query io_processor plugin
- pip install -e ./plugins/colbert_query_plugin
- pytest -v -s plugins_tests/test_colbert_query_io_processor_plugins.py
- pip uninstall colbert_query_plugin -y
# end io_processor plugins test
# begin stat_logger plugins test
- pip install -e ./plugins/vllm_add_dummy_stat_logger
@@ -41,20 +36,6 @@ steps:
- pytest -v -s plugins_tests/test_scheduler_plugins.py
- pip install -e ./plugins/vllm_add_dummy_model
- pytest -v -s distributed/test_distributed_oot.py
- pytest -v -s plugins_tests/test_oot_registration_online.py # it needs a clean process
- pytest -v -s plugins_tests/test_oot_registration_offline.py # it needs a clean process
- pytest -v -s plugins_tests/lora_resolvers # unit tests for in-tree lora resolver plugins
- label: GGUF Plugin
key: gguf-plugin
device: h200_18gb
timeout_in_minutes: 30
soft_fail: true
optional: true
source_file_dependencies:
- vllm/model_executor/layers/quantization
- tests/plugins_tests/test_gguf_plugin.py
commands:
- pip install "vllm-gguf-plugin >= 0.0.2"
- pytest -v -s plugins_tests/gguf
- pytest -v -s entrypoints/openai/chat_completion/test_oot_registration.py # it needs a clean process
- pytest -v -s models/test_oot_registration.py # it needs a clean process
- pytest -v -s plugins/lora_resolvers # unit tests for in-tree lora resolver plugins
+5 -141
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/,
@@ -43,105 +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
mirror:
amd:
device: mi300_1
timeout_in_minutes: 180
depends_on:
- image-build-amd
- 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
@@ -151,41 +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
@@ -195,11 +67,3 @@ steps:
- requirements/test/nightly-torch.txt
commands:
- bash standalone_tests/pytorch_nightly_dependency.sh
mirror:
amd:
device: mi300_1
depends_on:
- image-build-amd
source_file_dependencies:
- requirements/test/nightly-torch.txt
- vllm/platforms/rocm.py
+1 -16
View File
@@ -3,7 +3,6 @@ depends_on:
- image-build
steps:
- label: Quantization
key: quantization
timeout_in_minutes: 90
source_file_dependencies:
- csrc/
@@ -21,23 +20,10 @@ steps:
- uv pip install --system conch-triton-kernels
- VLLM_TEST_FORCE_LOAD_FORMAT=auto pytest -v -s quantization/ --ignore quantization/test_blackwell_moe.py
- label: Quantized Fusions
key: quantized-fusions
timeout_in_minutes: 30
source_file_dependencies:
- tests/fusion
- vllm/model_executor/layers/fusion
- vllm/model_executor/kernels/linear
- vllm/model_executor/layers/quantization/compressed_tensors
- vllm/model_executor/layers/quantization/modelopt.py
commands:
- pytest -v -s fusion/
- 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
@@ -52,7 +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.
-111
View File
@@ -1,111 +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 -k "not test_invalid_json_schema and not test_invalid_regex"
# - pytest -v -s entrypoints/openai/chat_completion/test_chat_logit_bias_validation.py -k "not 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/scale_out/token_in_token_out/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/scale_out/token_in_token_out/test_serving_tokens.py -k "not stream and not lora and not test_generate_logprobs and not stop_string_workflow"
- pytest -v -s entrypoints/serve/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_external_lb_dp.py
- tests/v1/distributed/test_hybrid_lb_dp.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"
- TP_SIZE=1 DP_SIZE=2 pytest -v -s v1/distributed/test_external_lb_dp.py -k "not 4 and not server_info"
- TP_SIZE=1 DP_SIZE=4 pytest -v -s v1/distributed/test_hybrid_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:
+7 -88
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:
@@ -12,25 +11,10 @@ steps:
- tests/v1/e2e/spec_decode/
commands:
- pytest -v -s v1/e2e/spec_decode -k "eagle_correctness"
mirror:
amd:
device: mi325_1
timeout_in_minutes: 45
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/v1/spec_decode/
- vllm/v1/worker/gpu/spec_decode/
- vllm/model_executor/model_loader/
- vllm/v1/sample/
- vllm/model_executor/layers/
- tests/v1/e2e/spec_decode/
- vllm/platforms/rocm.py
- label: Spec Decode Eagle Nightly B200
key: spec-decode-eagle-nightly-b200
timeout_in_minutes: 30
device: b200-k8s
device: b200
optional: true
source_file_dependencies:
- vllm/v1/spec_decode/
@@ -40,37 +24,19 @@ steps:
- 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"
mirror:
amd:
device: mi325_1
timeout_in_minutes: 65
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/v1/spec_decode/
- vllm/v1/worker/gpu/spec_decode/
- vllm/model_executor/model_loader/
- vllm/v1/sample/
- vllm/model_executor/layers/
- vllm/transformers_utils/configs/speculators/
- tests/v1/e2e/spec_decode/
- vllm/platforms/rocm.py
- label: Spec Decode Speculators + MTP Nightly B200
key: spec-decode-speculators-mtp-nightly-b200
timeout_in_minutes: 30
device: b200-k8s
device: b200
optional: true
source_file_dependencies:
- vllm/v1/spec_decode/
@@ -81,7 +47,6 @@ steps:
- 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:
@@ -90,25 +55,8 @@ steps:
- tests/v1/e2e/spec_decode/
commands:
- pytest -v -s v1/e2e/spec_decode -k "ngram or suffix"
mirror:
amd:
device: mi325_1
timeout_in_minutes: 65
# TODO(akaratza): Test after Torch >= 2.12 bump
soft_fail: true
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/v1/spec_decode/
- vllm/v1/worker/gpu/spec_decode/
- vllm/model_executor/model_loader/
- vllm/v1/sample/
- vllm/model_executor/layers/
- tests/v1/e2e/spec_decode/
- vllm/platforms/rocm.py
- label: Spec Decode Draft Model
key: spec-decode-draft-model
timeout_in_minutes: 30
device: h200_18gb
source_file_dependencies:
@@ -117,25 +65,10 @@ steps:
- tests/v1/e2e/spec_decode/
commands:
- pytest -v -s v1/e2e/spec_decode -k "draft_model or no_sync or batch_inference"
mirror:
amd:
device: mi325_1
timeout_in_minutes: 50
depends_on:
- image-build-amd
source_file_dependencies:
- vllm/v1/spec_decode/
- vllm/v1/worker/gpu/spec_decode/
- vllm/model_executor/model_loader/
- vllm/v1/sample/
- vllm/model_executor/layers/
- tests/v1/e2e/spec_decode/
- vllm/platforms/rocm.py
- label: Spec Decode Draft Model Nightly B200
key: spec-decode-draft-model-nightly-b200
timeout_in_minutes: 30
device: b200-k8s
device: b200
optional: true
source_file_dependencies:
- vllm/v1/spec_decode/
@@ -144,29 +77,15 @@ steps:
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
- label: DFlash Speculators Correctness
timeout_in_minutes: 30
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
- tests/v1/spec_decode/test_speculators_dflash.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"
- pytest -v -s v1/spec_decode/test_speculators_dflash.py -m slow_test
@@ -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
@@ -13,13 +12,6 @@ steps:
- tests/weight_loading
commands:
- bash weight_loading/run_model_weight_loading_test.sh -c weight_loading/models.txt
mirror:
amd:
device: mi300_2
depends_on:
- image-build-amd
commands:
- bash weight_loading/run_model_weight_loading_test.sh -c weight_loading/models-amd.txt
# - label: Weight Loading Multiple GPU - Large Models # optional
# working_dir: "/vllm-workspace/tests"
@@ -1,35 +0,0 @@
---
name: ci-fails-buildkite
description: Fetch and diagnose vLLM Buildkite CI failure logs. Use when investigating failing CI jobs on a PR or build, when the user pastes a buildkite.com URL, or asks to fetch/diagnose CI logs.
---
# Diagnosing vLLM Buildkite CI Failures
Buildkite logs are public; no login needed.
`.buildkite/scripts/ci-fetch-log.sh` saves each log as `ci-<build>-<job-name>.log`, stripped of timestamps and ANSI codes. Existing files are kept; set `CI_FETCH_LOG_FORCE=1` to refetch.
## Fetching logs
```bash
# All failed jobs in a PR's latest build (current branch's PR if omitted):
.buildkite/scripts/ci-fetch-log.sh --pr <PR>
# All failed jobs in a build (--soft also includes soft-failed jobs;
# --all fetches every finished job):
.buildkite/scripts/ci-fetch-log.sh "https://buildkite.com/vllm/ci/builds/<N>"
# One job — `gh pr checks` URLs (#<job_uuid>) and web UI URLs (?sid=) both
# work; pass "-" as a second argument to stream to stdout:
.buildkite/scripts/ci-fetch-log.sh "https://buildkite.com/vllm/ci/builds/<N>#<job_uuid>"
```
To clean an already-downloaded log with `.buildkite/scripts/ci-clean-log.sh`:
```bash
./ci-clean-log.sh ci.log
```
## Reference
See [docs/contributing/ci/failures.md](../../../docs/contributing/ci/failures.md) for the full guide: filing CI failure issues, investigating/bisecting, reproducing flaky tests, and daily triage.

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