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DarkLight1337 committed Dec 16, 2024
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16 changes: 16 additions & 0 deletions .buildkite/release-pipeline.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -39,3 +39,19 @@ steps:
- "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=12.1.0 --tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT --target vllm-openai --progress plain ."
- "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT"

- label: "Build and publish TPU release image"
depends_on: ~
if: build.env("NIGHTLY") == "1"
agents:
queue: tpu_queue_postmerge
commands:
- "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --tag vllm/vllm-tpu:nightly --tag vllm/vllm-tpu:$BUILDKITE_COMMIT --progress plain -f Dockerfile.tpu ."
- "docker push vllm/vllm-tpu:nightly"
- "docker push vllm/vllm-tpu:$BUILDKITE_COMMIT"
plugins:
- docker-login#v3.0.0:
username: vllm
password-env: DOCKERHUB_TOKEN
env:
DOCKER_BUILDKIT: "1"
51 changes: 33 additions & 18 deletions .buildkite/test-pipeline.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -181,14 +181,14 @@ steps:
commands:
- VLLM_USE_V1=1 pytest -v -s v1

- label: Examples Test # 15min
- label: Examples Test # 25min
working_dir: "/vllm-workspace/examples"
#mirror_hardwares: [amd]
source_file_dependencies:
- vllm/entrypoints
- examples/
commands:
- pip install awscli tensorizer # for llava example and tensorizer test
- pip install tensorizer # for tensorizer test
- python3 offline_inference.py
- python3 cpu_offload.py
- python3 offline_inference_chat.py
Expand All @@ -198,10 +198,13 @@ steps:
- python3 offline_inference_vision_language_multi_image.py
- python3 tensorize_vllm_model.py --model facebook/opt-125m serialize --serialized-directory /tmp/ --suffix v1 && python3 tensorize_vllm_model.py --model facebook/opt-125m deserialize --path-to-tensors /tmp/vllm/facebook/opt-125m/v1/model.tensors
- python3 offline_inference_encoder_decoder.py
- python3 offline_inference_classification.py
- python3 offline_inference_embedding.py
- python3 offline_inference_scoring.py
- python3 offline_profile.py --model facebook/opt-125m

- label: Prefix Caching Test # 9min
#mirror_hardwares: [amd]
mirror_hardwares: [amd]
source_file_dependencies:
- vllm/
- tests/prefix_caching
Expand Down Expand Up @@ -237,7 +240,7 @@ steps:
source_file_dependencies:
- vllm/lora
- tests/lora
command: pytest -v -s lora --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --ignore lora/test_long_context.py lora/test_chatglm3_tp.py lora/test_llama_tp.py
command: pytest -v -s lora --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --ignore=lora/test_long_context.py --ignore=lora/test_chatglm3_tp.py --ignore=lora/test_llama_tp.py
parallelism: 4

- label: "PyTorch Fullgraph Smoke Test" # 9min
Expand Down Expand Up @@ -321,7 +324,7 @@ steps:

##### models test #####

- label: Basic Models Test # 30min
- label: Basic Models Test # 24min
source_file_dependencies:
- vllm/
- tests/models
Expand All @@ -331,7 +334,7 @@ steps:
- pytest -v -s models/test_registry.py
- pytest -v -s models/test_initialization.py

- label: Language Models Test (Standard) # 42min
- label: Language Models Test (Standard) # 32min
#mirror_hardwares: [amd]
source_file_dependencies:
- vllm/
Expand All @@ -342,7 +345,7 @@ steps:
- pytest -v -s models/decoder_only/language -m 'core_model or quant_model'
- pytest -v -s models/embedding/language -m core_model

- label: Language Models Test (Extended) # 50min
- label: Language Models Test (Extended) # 1h10min
optional: true
source_file_dependencies:
- vllm/
Expand All @@ -353,7 +356,7 @@ steps:
- pytest -v -s models/decoder_only/language -m 'not core_model and not quant_model'
- pytest -v -s models/embedding/language -m 'not core_model'

- label: Multi-Modal Models Test (Standard) # 26min
- label: Multi-Modal Models Test (Standard) # 28min
#mirror_hardwares: [amd]
source_file_dependencies:
- vllm/
Expand All @@ -362,13 +365,14 @@ steps:
- tests/models/embedding/vision_language
- tests/models/encoder_decoder/vision_language
commands:
- pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
- pytest -v -s models/decoder_only/audio_language -m 'core_model or quant_model'
- pytest -v -s --ignore models/decoder_only/vision_language/test_phi3v.py models/decoder_only/vision_language -m 'core_model or quant_model'
- pytest -v -s models/embedding/vision_language -m core_model
- pytest -v -s models/encoder_decoder/language -m core_model
- pytest -v -s models/encoder_decoder/vision_language -m core_model

- label: Multi-Modal Models Test (Extended) # 1h15m
- label: Multi-Modal Models Test (Extended) 1 # 1h16m
optional: true
source_file_dependencies:
- vllm/
Expand All @@ -377,15 +381,26 @@ steps:
- tests/models/embedding/vision_language
- tests/models/encoder_decoder/vision_language
commands:
- pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
- pytest -v -s models/decoder_only/audio_language -m 'not core_model and not quant_model'
- pytest -v -s models/decoder_only/vision_language/test_models.py -m 'split(group=0) and not core_model and not quant_model'
# HACK - run phi3v tests separately to sidestep this transformers bug
# https://github.com/huggingface/transformers/issues/34307
- pytest -v -s models/decoder_only/vision_language/test_phi3v.py
- pytest -v -s --ignore models/decoder_only/vision_language/test_phi3v.py models/decoder_only/vision_language -m 'not core_model and not quant_model'
- pytest -v -s --ignore models/decoder_only/vision_language/test_models.py --ignore models/decoder_only/vision_language/test_phi3v.py models/decoder_only/vision_language -m 'not core_model and not quant_model'
- pytest -v -s models/embedding/vision_language -m 'not core_model'
- pytest -v -s models/encoder_decoder/language -m 'not core_model'
- pytest -v -s models/encoder_decoder/vision_language -m 'not core_model'

- label: Multi-Modal Models Test (Extended) 2 # 38m
optional: true
source_file_dependencies:
- vllm/
- tests/models/decoder_only/vision_language
commands:
- pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
- pytest -v -s models/decoder_only/vision_language/test_models.py -m 'split(group=1) and not core_model and not quant_model'

# This test is used only in PR development phase to test individual models and should never run on main
- label: Custom Models Test
optional: true
Expand Down Expand Up @@ -420,11 +435,11 @@ steps:
- tests/distributed/
commands:
- # the following commands are for the first node, with ip 192.168.10.10 (ray environment already set up)
- 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 -q 'Same node test passed'
- 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'
- 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
- # the following commands are for the second node, with ip 192.168.10.11 (ray environment already set up)
- 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 -q 'Same node test passed'
- 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'

- label: Distributed Tests (2 GPUs) # 40min
#mirror_hardwares: [amd]
Expand All @@ -443,12 +458,12 @@ steps:
commands:
- pytest -v -s ./compile/test_basic_correctness.py
- pytest -v -s ./compile/test_wrapper.py
- VLLM_TEST_SAME_HOST=1 torchrun --nproc-per-node=4 distributed/test_same_node.py | grep -q 'Same node test passed'
- TARGET_TEST_SUITE=L4 pytest basic_correctness/ -v -s -m distributed_2_gpus
- VLLM_TEST_SAME_HOST=1 torchrun --nproc-per-node=4 distributed/test_same_node.py | grep 'Same node test passed'
- TARGET_TEST_SUITE=L4 pytest basic_correctness/ -v -s -m 'distributed(num_gpus=2)'
# Avoid importing model tests that cause CUDA reinitialization error
- pytest models/encoder_decoder/language/test_bart.py -v -s -m distributed_2_gpus
- pytest models/encoder_decoder/vision_language/test_broadcast.py -v -s -m distributed_2_gpus
- pytest models/decoder_only/vision_language/test_models.py -v -s -m distributed_2_gpus
- pytest models/encoder_decoder/language/test_bart.py -v -s -m 'distributed(num_gpus=2)'
- pytest models/encoder_decoder/vision_language/test_broadcast.py -v -s -m 'distributed(num_gpus=2)'
- pytest models/decoder_only/vision_language/test_models.py -v -s -m 'distributed(num_gpus=2)'
- pytest -v -s spec_decode/e2e/test_integration_dist_tp2.py
- pip install -e ./plugins/vllm_add_dummy_model
- pytest -v -s distributed/test_distributed_oot.py
Expand Down Expand Up @@ -538,7 +553,7 @@ steps:
# see https://github.com/vllm-project/vllm/pull/5689 for details
- pytest -v -s distributed/test_custom_all_reduce.py
- torchrun --nproc_per_node=2 distributed/test_ca_buffer_sharing.py
- TARGET_TEST_SUITE=A100 pytest basic_correctness/ -v -s -m distributed_2_gpus
- TARGET_TEST_SUITE=A100 pytest basic_correctness/ -v -s -m 'distributed(num_gpus=2)'
- pytest -v -s -x lora/test_mixtral.py

- label: LM Eval Large Models # optional
Expand Down
81 changes: 81 additions & 0 deletions .github/workflows/lint-and-deploy.yaml
Original file line number Diff line number Diff line change
@@ -0,0 +1,81 @@
name: Lint and Deploy Charts

on: pull_request

jobs:
lint-and-deploy:
runs-on: ubuntu-latest
steps:
- name: Checkout
uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
with:
fetch-depth: 0

- name: Set up Helm
uses: azure/setup-helm@fe7b79cd5ee1e45176fcad797de68ecaf3ca4814 # v4.2.0
with:
version: v3.14.4

#Python is required because ct lint runs Yamale and yamllint which require Python.
- uses: actions/setup-python@0b93645e9fea7318ecaed2b359559ac225c90a2b # v5.3.0
with:
python-version: '3.13'

- name: Set up chart-testing
uses: helm/chart-testing-action@e6669bcd63d7cb57cb4380c33043eebe5d111992 # v2.6.1
with:
version: v3.10.1

- name: Run chart-testing (lint)
run: ct lint --target-branch ${{ github.event.repository.default_branch }} --chart-dirs examples/chart-helm --charts examples/chart-helm

- name: Setup minio
run: |
docker network create vllm-net
docker run -d -p 9000:9000 --name minio --net vllm-net \
-e "MINIO_ACCESS_KEY=minioadmin" \
-e "MINIO_SECRET_KEY=minioadmin" \
-v /tmp/data:/data \
-v /tmp/config:/root/.minio \
minio/minio server /data
export AWS_ACCESS_KEY_ID=minioadmin
export AWS_SECRET_ACCESS_KEY=minioadmin
export AWS_EC2_METADATA_DISABLED=true
mkdir opt-125m
cd opt-125m && curl -O -Ls "https://huggingface.co/facebook/opt-125m/resolve/main/{pytorch_model.bin,config.json,generation_config.json,merges.txt,special_tokens_map.json,tokenizer_config.json,vocab.json}" && cd ..
aws --endpoint-url http://127.0.0.1:9000/ s3 mb s3://testbucket
aws --endpoint-url http://127.0.0.1:9000/ s3 cp opt-125m/ s3://testbucket/opt-125m --recursive
- name: Create kind cluster
uses: helm/kind-action@0025e74a8c7512023d06dc019c617aa3cf561fde # v1.10.0

- name: Build the Docker image vllm cpu
run: docker buildx build -f Dockerfile.cpu -t vllm-cpu-env .

- name: Configuration of docker images, network and namespace for the kind cluster
run: |
docker pull amazon/aws-cli:2.6.4
kind load docker-image amazon/aws-cli:2.6.4 --name chart-testing
kind load docker-image vllm-cpu-env:latest --name chart-testing
docker network connect vllm-net "$(docker ps -aqf "name=chart-testing-control-plane")"
kubectl create ns ns-vllm
- name: Run chart-testing (install)
run: |
export AWS_ACCESS_KEY_ID=minioadmin
export AWS_SECRET_ACCESS_KEY=minioadmin
helm install --wait --wait-for-jobs --timeout 5m0s --debug --create-namespace --namespace=ns-vllm test-vllm examples/chart-helm -f examples/chart-helm/values.yaml --set secrets.s3endpoint=http://minio:9000 --set secrets.s3bucketname=testbucket --set secrets.s3accesskeyid=$AWS_ACCESS_KEY_ID --set secrets.s3accesskey=$AWS_SECRET_ACCESS_KEY --set resources.requests.cpu=1 --set resources.requests.memory=4Gi --set resources.limits.cpu=2 --set resources.limits.memory=5Gi --set image.env[0].name=VLLM_CPU_KVCACHE_SPACE --set image.env[1].name=VLLM_LOGGING_LEVEL --set-string image.env[0].value="1" --set-string image.env[1].value="DEBUG" --set-string extraInit.s3modelpath="opt-125m/" --set-string 'resources.limits.nvidia\.com/gpu=0' --set-string 'resources.requests.nvidia\.com/gpu=0' --set-string image.repository="vllm-cpu-env"
- name: curl test
run: |
kubectl -n ns-vllm port-forward service/test-vllm-service 8001:80 &
sleep 10
CODE="$(curl -v -f --location http://localhost:8001/v1/completions \
--header "Content-Type: application/json" \
--data '{
"model": "opt-125m",
"prompt": "San Francisco is a",
"max_tokens": 7,
"temperature": 0
}'):$CODE"
echo "$CODE"
3 changes: 2 additions & 1 deletion CMakeLists.txt
Original file line number Diff line number Diff line change
Expand Up @@ -196,6 +196,7 @@ set(VLLM_EXT_SRC
"csrc/quantization/gptq/q_gemm.cu"
"csrc/quantization/compressed_tensors/int8_quant_kernels.cu"
"csrc/quantization/fp8/common.cu"
"csrc/quantization/fused_kernels/fused_layernorm_dynamic_per_token_quant.cu"
"csrc/quantization/gguf/gguf_kernel.cu"
"csrc/cuda_utils_kernels.cu"
"csrc/prepare_inputs/advance_step.cu"
Expand Down Expand Up @@ -300,7 +301,7 @@ if(VLLM_GPU_LANG STREQUAL "CUDA")
#
# For the cutlass_scaled_mm kernels we want to build the c2x (CUTLASS 2.x)
# kernels for the remaining archs that are not already built for 3x.
cuda_archs_loose_intersection(SCALED_MM_2X_ARCHS
cuda_archs_loose_intersection(SCALED_MM_2X_ARCHS
"7.5;8.0;8.6;8.7;8.9;9.0" "${CUDA_ARCHS}")
# subtract out the archs that are already built for 3x
list(REMOVE_ITEM SCALED_MM_2X_ARCHS ${SCALED_MM_3X_ARCHS})
Expand Down
40 changes: 32 additions & 8 deletions Dockerfile
Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,7 @@ ARG CUDA_VERSION=12.4.1
FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu20.04 AS base
ARG CUDA_VERSION=12.4.1
ARG PYTHON_VERSION=3.12
ARG TARGETPLATFORM
ENV DEBIAN_FRONTEND=noninteractive

# Install Python and other dependencies
Expand Down Expand Up @@ -46,9 +47,14 @@ WORKDIR /workspace
# install build and runtime dependencies
COPY requirements-common.txt requirements-common.txt
COPY requirements-cuda.txt requirements-cuda.txt
COPY requirements-cuda-arm64.txt requirements-cuda-arm64.txt
RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install -r requirements-cuda.txt

RUN --mount=type=cache,target=/root/.cache/pip \
if [ "$TARGETPLATFORM" = "linux/arm64" ]; then \
python3 -m pip install -r requirements-cuda-arm64.txt; \
fi

# cuda arch list used by torch
# can be useful for both `dev` and `test`
Expand All @@ -63,13 +69,19 @@ ENV VLLM_FA_CMAKE_GPU_ARCHES=${vllm_fa_cmake_gpu_arches}

#################### WHEEL BUILD IMAGE ####################
FROM base AS build
ARG TARGETPLATFORM

# install build dependencies
COPY requirements-build.txt requirements-build.txt

RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install -r requirements-build.txt

RUN --mount=type=cache,target=/root/.cache/pip \
if [ "$TARGETPLATFORM" = "linux/arm64" ]; then \
python3 -m pip install -r requirements-cuda-arm64.txt; \
fi

COPY . .
ARG GIT_REPO_CHECK=0
RUN --mount=type=bind,source=.git,target=.git \
Expand Down Expand Up @@ -134,15 +146,18 @@ COPY requirements-test.txt requirements-test.txt
COPY requirements-dev.txt requirements-dev.txt
RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install -r requirements-dev.txt

#################### DEV IMAGE ####################

#################### vLLM installation IMAGE ####################
# image with vLLM installed
FROM nvidia/cuda:${CUDA_VERSION}-base-ubuntu22.04 AS vllm-base
ARG CUDA_VERSION=12.4.1
ARG PYTHON_VERSION=3.12
WORKDIR /vllm-workspace
ENV DEBIAN_FRONTEND=noninteractive
ARG TARGETPLATFORM

COPY requirements-cuda-arm64.txt requirements-cuda-arm64.txt

RUN PYTHON_VERSION_STR=$(echo ${PYTHON_VERSION} | sed 's/\.//g') && \
echo "export PYTHON_VERSION_STR=${PYTHON_VERSION_STR}" >> /etc/environment
Expand All @@ -168,18 +183,25 @@ RUN echo 'tzdata tzdata/Areas select America' | debconf-set-selections \
# or future versions of triton.
RUN ldconfig /usr/local/cuda-$(echo $CUDA_VERSION | cut -d. -f1,2)/compat/

# install vllm wheel first, so that torch etc will be installed
# Install vllm wheel first, so that torch etc will be installed.
RUN --mount=type=bind,from=build,src=/workspace/dist,target=/vllm-workspace/dist \
--mount=type=cache,target=/root/.cache/pip \
python3 -m pip install dist/*.whl --verbose

RUN --mount=type=cache,target=/root/.cache/pip \
. /etc/environment && \
python3 -m pip install https://github.com/flashinfer-ai/flashinfer/releases/download/v0.1.6/flashinfer-0.1.6+cu121torch2.4-cp${PYTHON_VERSION_STR}-cp${PYTHON_VERSION_STR}-linux_x86_64.whl
if [ "$TARGETPLATFORM" = "linux/arm64" ]; then \
pip uninstall -y torch && \
python3 -m pip install -r requirements-cuda-arm64.txt; \
fi

RUN --mount=type=cache,target=/root/.cache/pip \
. /etc/environment && \
if [ "$TARGETPLATFORM" != "linux/arm64" ]; then \
python3 -m pip install https://github.com/flashinfer-ai/flashinfer/releases/download/v0.1.6/flashinfer-0.1.6+cu121torch2.4-cp${PYTHON_VERSION_STR}-cp${PYTHON_VERSION_STR}-linux_x86_64.whl; \
fi
COPY examples examples
#################### vLLM installation IMAGE ####################


#################### TEST IMAGE ####################
# image to run unit testing suite
# note that this uses vllm installed by `pip`
Expand Down Expand Up @@ -209,7 +231,6 @@ COPY vllm/v1 /usr/local/lib/python3.12/dist-packages/vllm/v1
RUN mkdir test_docs
RUN mv docs test_docs/
RUN mv vllm test_docs/

#################### TEST IMAGE ####################

#################### OPENAI API SERVER ####################
Expand All @@ -218,8 +239,11 @@ FROM vllm-base AS vllm-openai

# install additional dependencies for openai api server
RUN --mount=type=cache,target=/root/.cache/pip \
pip install accelerate hf_transfer 'modelscope!=1.15.0' 'bitsandbytes>=0.44.0' timm==0.9.10

if [ "$TARGETPLATFORM" = "linux/arm64" ]; then \
pip install accelerate hf_transfer 'modelscope!=1.15.0' 'bitsandbytes>=0.42.0' 'timm==0.9.10'; \
else \
pip install accelerate hf_transfer 'modelscope!=1.15.0' 'bitsandbytes>=0.45.0' 'timm==0.9.10'; \
fi
ENV VLLM_USAGE_SOURCE production-docker-image

ENTRYPOINT ["python3", "-m", "vllm.entrypoints.openai.api_server"]
Expand Down
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