Commit 6d2051cc authored by zhuwenwen's avatar zhuwenwen
Browse files

Merge tag 'v0.6.3.post1' into v0.6.3.post1-dev

parents 2c7f740a a2c71c54
......@@ -18,7 +18,13 @@ docker run -itd --entrypoint /bin/bash -v ~/.cache/huggingface:/root/.cache/hugg
# Run basic model test
docker exec cpu-test bash -c "
pip install pytest matplotlib einops transformers_stream_generator
pytest -v -s tests/models -m \"not vlm\" --ignore=tests/models/test_embedding.py --ignore=tests/models/test_oot_registration.py --ignore=tests/models/test_registry.py --ignore=tests/models/test_jamba.py --ignore=tests/models/test_danube3_4b.py" # Mamba and Danube3-4B on CPU is not supported
pytest -v -s tests/models -m \"not vlm\" \
--ignore=tests/models/test_embedding.py \
--ignore=tests/models/test_oot_registration.py \
--ignore=tests/models/test_registry.py \
--ignore=tests/models/test_jamba.py \
--ignore=tests/models/test_mamba.py \
--ignore=tests/models/test_danube3_4b.py" # Mamba kernels and Danube3-4B on CPU is not supported
# online inference
docker exec cpu-test bash -c "
......
......@@ -23,16 +23,24 @@ docker exec cpu-test-avx2 bash -c "python3 examples/offline_inference.py"
# Run basic model test
docker exec cpu-test bash -c "
pip install pytest matplotlib einops transformers_stream_generator datamodel_code_generator
pytest -v -s tests/models/encoder_decoder/language
pytest -v -s tests/models/decoder_only/language \
--ignore=tests/models/test_fp8.py \
--ignore=tests/models/decoder_only/language/test_jamba.py \
--ignore=tests/models/decoder_only/language/test_mamba.py \
--ignore=tests/models/decoder_only/language/test_granitemoe.py \
--ignore=tests/models/decoder_only/language/test_danube3_4b.py" # Mamba and Danube3-4B on CPU is not supported
# Run compressed-tensor test
docker exec cpu-test bash -c "
pytest -s -v \
tests/quantization/test_compressed_tensors.py::test_compressed_tensors_w8a8_static_setup \
tests/quantization/test_compressed_tensors.py::test_compressed_tensors_w8a8_dynanmic_per_token"
tests/quantization/test_compressed_tensors.py::test_compressed_tensors_w8a8_dynamic_per_token"
# Run AWQ test
docker exec cpu-test bash -c "
pytest -s -v \
tests/quantization/test_ipex_quant.py"
# online inference
docker exec cpu-test bash -c "
......
......@@ -11,4 +11,4 @@ trap remove_docker_container EXIT
remove_docker_container
# Run the image and launch offline inference
docker run --network host --name xpu-test --device /dev/dri -v /dev/dri/by-path:/dev/dri/by-path xpu-test python3 examples/offline_inference.py
docker run --network host --name xpu-test --device /dev/dri -v /dev/dri/by-path:/dev/dri/by-path --entrypoint="" xpu-test python3 examples/offline_inference.py
......@@ -9,6 +9,7 @@
# label(str): the name of the test. emoji allowed.
# fast_check(bool): whether to run this on each commit on fastcheck pipeline.
# fast_check_only(bool): run this test on fastcheck pipeline only
# optional(bool): never run this test by default (i.e. need to unblock manually)
# command(str): the single command to run for tests. incompatible with commands.
# commands(list): the list of commands to run for test. incompatbile with command.
# mirror_hardwares(list): the list of hardwares to run the test on as well. currently only supports [amd]
......@@ -39,7 +40,7 @@ steps:
# Check API reference (if it fails, you may have missing mock imports)
- grep \"sig sig-object py\" build/html/dev/sampling_params.html
- label: Async Engine, Inputs, Utils, Worker Test # 15min
- label: Async Engine, Inputs, Utils, Worker Test # 24min
fast_check: true
source_file_dependencies:
- vllm/
......@@ -63,13 +64,21 @@ steps:
fast_check: true
source_file_dependencies:
- vllm/
- tests/basic_correctness
- tests/basic_correctness/test_basic_correctness
- tests/basic_correctness/test_cpu_offload
- tests/basic_correctness/test_preemption
commands:
- pytest -v -s basic_correctness/test_basic_correctness.py
- pytest -v -s basic_correctness/test_cpu_offload.py
- VLLM_TEST_ENABLE_ARTIFICIAL_PREEMPT=1 pytest -v -s basic_correctness/test_preemption.py
- label: Chunked Prefill Test
source_file_dependencies:
- vllm/
- tests/basic_correctness/test_chunked_prefill
commands:
- VLLM_ATTENTION_BACKEND=XFORMERS pytest -v -s basic_correctness/test_chunked_prefill.py
- VLLM_ATTENTION_BACKEND=FLASH_ATTN pytest -v -s basic_correctness/test_chunked_prefill.py
- VLLM_TEST_ENABLE_ARTIFICIAL_PREEMPT=1 pytest -v -s basic_correctness/test_preemption.py
- label: Core Test # 10min
mirror_hardwares: [amd]
......@@ -81,7 +90,7 @@ steps:
commands:
- pytest -v -s core
- label: Entrypoints Test # 20min
- label: Entrypoints Test # 40min
working_dir: "/vllm-workspace/tests"
fast_check: true
mirror_hardwares: [amd]
......@@ -89,13 +98,13 @@ steps:
- vllm/
commands:
- pip install -e ./plugins/vllm_add_dummy_model
- pip install git+https://github.com/EleutherAI/lm-evaluation-harness.git@a4987bba6e9e9b3f22bd3a6c1ecf0abd04fd5622#egg=lm_eval[api]
- pytest -v -s entrypoints/llm --ignore=entrypoints/llm/test_lazy_outlines.py --ignore=entrypoints/llm/test_generate.py --ignore=entrypoints/llm/test_generate_multiple_loras.py --ignore=entrypoints/llm/test_guided_generate.py
- pytest -v -s entrypoints/llm/test_lazy_outlines.py # it needs a clean process
- pytest -v -s entrypoints/llm/test_generate.py # it needs a clean process
- pytest -v -s entrypoints/llm/test_generate_multiple_loras.py # it needs a clean process
- pytest -v -s entrypoints/llm/test_guided_generate.py # it needs a clean process
- pytest -v -s entrypoints/openai
- pytest -v -s entrypoints/openai --ignore=entrypoints/openai/test_oot_registration.py
- pytest -v -s entrypoints/openai/test_oot_registration.py # it needs a clean process
- pytest -v -s entrypoints/test_chat_utils.py
- pytest -v -s entrypoints/offline_mode # Needs to avoid interference with other tests
......@@ -108,7 +117,9 @@ steps:
- vllm/core/
- tests/distributed
- tests/spec_decode/e2e/test_integration_dist_tp4
- tests/compile
commands:
- pytest -v -s compile/test_basic_correctness.py
- pytest -v -s distributed/test_pynccl.py
- pytest -v -s spec_decode/e2e/test_integration_dist_tp4.py
......@@ -136,7 +147,9 @@ steps:
source_file_dependencies:
- vllm/
- tests/test_regression
command: pytest -v -s test_regression.py
commands:
- pip install modelscope
- pytest -v -s test_regression.py
working_dir: "/vllm-workspace/tests" # optional
- label: Engine Test # 10min
......@@ -150,7 +163,7 @@ steps:
# OOM in the CI unless we run this separately
- pytest -v -s tokenization
- label: Examples Test # 12min
- label: Examples Test # 15min
working_dir: "/vllm-workspace/examples"
#mirror_hardwares: [amd]
source_file_dependencies:
......@@ -167,8 +180,9 @@ 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_profile.py --model facebook/opt-125m
- label: Prefix Caching Test # 7min
- label: Prefix Caching Test # 9min
#mirror_hardwares: [amd]
source_file_dependencies:
- vllm/
......@@ -176,7 +190,7 @@ steps:
commands:
- pytest -v -s prefix_caching
- label: Samplers Test # 18min
- label: Samplers Test # 36min
source_file_dependencies:
- vllm/model_executor/layers
- vllm/sampling_metadata.py
......@@ -192,17 +206,15 @@ steps:
- tests/test_logits_processor
command: pytest -v -s test_logits_processor.py
- label: Speculative decoding tests # 22min
- label: Speculative decoding tests # 30min
source_file_dependencies:
- vllm/spec_decode
- tests/spec_decode
commands:
# See https://github.com/vllm-project/vllm/issues/5152
- export VLLM_ATTENTION_BACKEND=XFORMERS
- pytest -v -s spec_decode/e2e/test_multistep_correctness.py
- pytest -v -s spec_decode --ignore=spec_decode/e2e/test_multistep_correctness.py
- VLLM_ATTENTION_BACKEND=FLASH_ATTN pytest -v -s spec_decode --ignore=spec_decode/e2e/test_multistep_correctness.py
- label: LoRA Test %N # 30min each
- label: LoRA Test %N # 15min each
mirror_hardwares: [amd]
source_file_dependencies:
- vllm/lora
......@@ -210,22 +222,24 @@ steps:
command: pytest -v -s lora --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --ignore=lora/test_long_context.py
parallelism: 4
- label: "PyTorch Fullgraph Smoke Test"
- label: "PyTorch Fullgraph Smoke Test" # 9min
fast_check: true
source_file_dependencies:
- vllm/
- tests/compile
commands:
- pytest -v -s compile/test_full_graph_smoke.py
- pytest -v -s compile/test_basic_correctness.py
- label: "PyTorch Fullgraph Test"
source_file_dependencies:
- vllm/
- tests/compile
commands:
- pytest -v -s compile/test_full_graph.py
# TODO: re-write in comparison tests, and fix symbolic shape
# for quantization ops.
# - label: "PyTorch Fullgraph Test" # 18min
# source_file_dependencies:
# - vllm/
# - tests/compile
# commands:
# - pytest -v -s compile/test_full_graph.py
- label: Kernels Test %N # 30min each
- label: Kernels Test %N # 1h each
mirror_hardwares: [amd]
source_file_dependencies:
- csrc/
......@@ -255,12 +269,12 @@ steps:
- pip install aiohttp
- bash run-benchmarks.sh
- label: Quantization Test # 15min
- label: Quantization Test # 33min
source_file_dependencies:
- csrc/
- vllm/model_executor/layers/quantization
- tests/quantization
command: pytest -v -s quantization
command: VLLM_TEST_FORCE_LOAD_FORMAT=auto pytest -v -s quantization
- label: LM Eval Small Models # 53min
working_dir: "/vllm-workspace/.buildkite/lm-eval-harness"
......@@ -268,7 +282,6 @@ steps:
- csrc/
- vllm/model_executor/layers/quantization
commands:
- pip install lm-eval
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- bash ./run-tests.sh -c configs/models-small.txt -t 1
......@@ -299,7 +312,7 @@ steps:
- pytest -v -s models/test_oot_registration.py # it needs a clean process
- pytest -v -s models/*.py --ignore=models/test_oot_registration.py
- label: Decoder-only Language Models Test # 1h3min
- label: Decoder-only Language Models Test # 1h36min
#mirror_hardwares: [amd]
source_file_dependencies:
- vllm/
......@@ -307,7 +320,7 @@ steps:
commands:
- pytest -v -s models/decoder_only/language
- label: Decoder-only Multi-Modal Models Test # 56min
- label: Decoder-only Multi-Modal Models Test # 1h31min
#mirror_hardwares: [amd]
source_file_dependencies:
- vllm/
......@@ -317,15 +330,28 @@ steps:
- pytest -v -s models/decoder_only/audio_language
- pytest -v -s models/decoder_only/vision_language
- label: Other Models Test # 5min
- label: Other Models Test # 6min
#mirror_hardwares: [amd]
source_file_dependencies:
- vllm/
- tests/models/embedding/language
- tests/models/embedding/vision_language
- tests/models/encoder_decoder/language
- tests/models/encoder_decoder/vision_language
commands:
- pytest -v -s models/embedding/language
- pytest -v -s models/embedding/vision_language
- pytest -v -s models/encoder_decoder/language
- pytest -v -s models/encoder_decoder/vision_language
# 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
commands:
- echo 'Testing custom models...'
# PR authors can temporarily add commands below to test individual models
# e.g. pytest -v -s models/encoder_decoder/vision_language/test_mllama.py
# *To avoid merge conflicts, remember to REMOVE (not just comment out) them before merging the PR*
##### 1 GPU test #####
##### multi gpus test #####
......@@ -358,7 +384,7 @@ steps:
- # 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'
- label: Distributed Tests (2 GPUs) # 28min
- label: Distributed Tests (2 GPUs) # 40min
#mirror_hardwares: [amd]
working_dir: "/vllm-workspace/tests"
num_gpus: 2
......@@ -370,19 +396,21 @@ steps:
- tests/distributed/
- vllm/compilation
commands:
- pytest -v -s ./compile/test_full_graph_multi_gpu.py
- 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
# Avoid importing model tests that cause CUDA reinitialization error
- pytest models/encoder_decoder/language/test_bart.py models/decoder_only/vision_language/test_broadcast.py -v -s -m distributed_2_gpus
- 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_broadcast.py -v -s -m distributed_2_gpus
- 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
- CUDA_VISIBLE_DEVICES=0,1 pytest -v -s test_sharded_state_loader.py
- CUDA_VISIBLE_DEVICES=0,1 pytest -v -s distributed/test_utils.py
- label: Multi-step Tests (4 GPUs) # 21min
- label: Multi-step Tests (4 GPUs) # 36min
working_dir: "/vllm-workspace/tests"
num_gpus: 4
source_file_dependencies:
......@@ -400,7 +428,7 @@ steps:
- pytest -v -s multi_step/test_correctness_async_llm.py
- pytest -v -s multi_step/test_correctness_llm.py
- label: Pipeline Parallelism Test # 23min
- label: Pipeline Parallelism Test # 45min
working_dir: "/vllm-workspace/tests"
num_gpus: 4
source_file_dependencies:
......@@ -426,7 +454,7 @@ steps:
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- pytest -v -s -x lora/test_long_context.py
- label: Weight Loading Multiple GPU Test
- label: Weight Loading Multiple GPU Test # 33min
working_dir: "/vllm-workspace/tests"
num_gpus: 2
source_file_dependencies:
......@@ -459,7 +487,7 @@ steps:
# NOTE: don't test llama model here, it seems hf implementation is buggy
# see https://github.com/vllm-project/vllm/pull/5689 for details
- pytest -v -s distributed/test_custom_all_reduce.py
- TARGET_TEST_SUITE=A100 pytest -v -s distributed/test_basic_distributed_correctness.py
- TARGET_TEST_SUITE=A100 pytest basic_correctness/ -v -s -m distributed_2_gpus
- pytest -v -s -x lora/test_mixtral.py
- label: LM Eval Large Models # optional
......@@ -470,6 +498,5 @@ steps:
- csrc/
- vllm/model_executor/layers/quantization
commands:
- pip install lm-eval
- export VLLM_WORKER_MULTIPROC_METHOD=spawn
- bash ./run-tests.sh -c configs/models-large.txt -t 4
vllm/*.so
/.venv
/build
dist
vllm/*.so
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
.mypy_cache
# Distribution / packaging
.Python
/build/
cmake-build-*/
CMakeUserPresets.json
develop-eggs/
/dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
# See https://help.github.com/articles/about-codeowners/
# for more info about CODEOWNERS file
# This lists cover the "core" components of vLLM that require careful review
/vllm/attention/backends/abstract.py @WoosukKwon @zhuohan123 @youkaichao @alexm-neuralmagic @comaniac @njhill
/vllm/core @WoosukKwon @zhuohan123 @youkaichao @alexm-neuralmagic @comaniac @njhill
/vllm/engine/llm_engine.py @WoosukKwon @zhuohan123 @youkaichao @alexm-neuralmagic @comaniac @njhill
/vllm/executor/executor_base.py @WoosukKwon @zhuohan123 @youkaichao @alexm-neuralmagic @comaniac @njhill
/vllm/worker/worker_base.py @WoosukKwon @zhuohan123 @youkaichao @alexm-neuralmagic @comaniac @njhill
/vllm/worker/worker.py @WoosukKwon @zhuohan123 @youkaichao @alexm-neuralmagic @comaniac @njhill
/vllm/model_executor/layers/sampler.py @WoosukKwon @zhuohan123 @youkaichao @alexm-neuralmagic @comaniac @njhill
CMakeLists.txt @tlrmchlsmth @WoosukKwon
# Test ownership
/tests/async_engine @njhill @robertgshaw2-neuralmagic @simon-mo
/tests/test_inputs.py @DarkLight1337 @ywang96
/tests/entrypoints @DarkLight1337 @robertgshaw2-neuralmagic @simon-mo
/tests/models @DarkLight1337 @ywang96
/tests/multimodal @DarkLight1337 @ywang96
/tests/prefix_caching @comaniac @KuntaiDu
/tests/spec_decode @njhill @LiuXiaoxuanPKU
/tests/kernels @tlrmchlsmth @WoosukKwon
/tests/quantization @mgoin @robertgshaw2-neuralmagic
/.buildkite/lm-eval-harness @mgoin @simon-mo
/tests/distributed/test_multi_node_assignment.py @youkaichao
/tests/distributed/test_pipeline_parallel.py @youkaichao
/tests/distributed/test_same_node.py @youkaichao
/tests/multi_step @alexm-neuralmagic @comaniac
/tests/weight_loading @mgoin @youkaichao
/tests/basic_correctness/test_chunked_prefill @rkooo567 @comaniac
version: 2
updates:
# Maintain dependencies for GitHub Actions
- package-ecosystem: "github-actions"
directory: "/"
schedule:
interval: "weekly"
name: Lint GitHub Actions workflows
on:
push:
branches:
- "main"
paths:
- '.github/workflows/*.ya?ml'
- '.github/workflows/actionlint.*'
pull_request:
branches:
- "main"
paths:
- '.github/workflows/*.ya?ml'
- '.github/workflows/actionlint.*'
env:
LC_ALL: en_US.UTF-8
defaults:
run:
shell: bash
permissions:
contents: read
jobs:
actionlint:
runs-on: ubuntu-latest
steps:
- name: "Checkout"
uses: actions/checkout@eef61447b9ff4aafe5dcd4e0bbf5d482be7e7871 # v4.2.1
with:
fetch-depth: 0
- name: "Run actionlint"
run: |
tools/actionlint.sh -color
......@@ -8,7 +8,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Add label
uses: actions/github-script@v5
uses: actions/github-script@v7
with:
script: |
github.rest.issues.addLabels({
......
......@@ -17,9 +17,9 @@ jobs:
matrix:
python-version: ["3.11"]
steps:
- uses: actions/checkout@v2
- uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
- name: Install dependencies
......
{
"problemMatcher": [
{
"owner": "actionlint",
"pattern": [
{
"regexp": "^(?:\\x1b\\[\\d+m)?(.+?)(?:\\x1b\\[\\d+m)*:(?:\\x1b\\[\\d+m)*(\\d+)(?:\\x1b\\[\\d+m)*:(?:\\x1b\\[\\d+m)*(\\d+)(?:\\x1b\\[\\d+m)*: (?:\\x1b\\[\\d+m)*(.+?)(?:\\x1b\\[\\d+m)* \\[(.+?)\\]$",
"file": 1,
"line": 2,
"column": 3,
"message": 4,
"code": 5
}
]
}
]
}
......@@ -11,15 +11,15 @@ on:
- main
jobs:
ruff:
mypy:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"]
steps:
- uses: actions/checkout@v2
- uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
- name: Install dependencies
......@@ -32,15 +32,4 @@ jobs:
pip install types-setuptools
- name: Mypy
run: |
mypy
mypy tests --follow-imports skip
mypy vllm/attention --follow-imports skip
mypy vllm/distributed --follow-imports skip
mypy vllm/engine --follow-imports skip
mypy vllm/executor --follow-imports skip
mypy vllm/lora --follow-imports skip
mypy vllm/model_executor --follow-imports skip
mypy vllm/prompt_adapter --follow-imports skip
mypy vllm/spec_decode --follow-imports skip
mypy vllm/worker --follow-imports skip
tools/mypy.sh
......@@ -21,16 +21,16 @@ jobs:
upload_url: ${{ steps.create_release.outputs.upload_url }}
steps:
- name: Checkout
uses: actions/checkout@v3
uses: actions/checkout@v4
- name: Extract branch info
shell: bash
run: |
echo "release_tag=${GITHUB_REF#refs/*/}" >> $GITHUB_ENV
echo "release_tag=${GITHUB_REF#refs/*/}" >> "$GITHUB_ENV"
- name: Create Release
id: create_release
uses: "actions/github-script@v6"
uses: "actions/github-script@v7"
env:
RELEASE_TAG: ${{ env.release_tag }}
with:
......@@ -54,7 +54,7 @@ jobs:
steps:
- name: Checkout
uses: actions/checkout@v3
uses: actions/checkout@v4
- name: Setup ccache
uses: hendrikmuhs/ccache-action@v1.2
......@@ -68,7 +68,7 @@ jobs:
bash -x .github/workflows/scripts/env.sh
- name: Set up Python
uses: actions/setup-python@v4
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
......@@ -86,10 +86,10 @@ jobs:
CMAKE_BUILD_TYPE: Release # do not compile with debug symbol to reduce wheel size
run: |
bash -x .github/workflows/scripts/build.sh ${{ matrix.python-version }} ${{ matrix.cuda-version }}
wheel_name=$(ls dist/*whl | xargs -n 1 basename)
wheel_name=$(find dist -name "*whl" -print0 | xargs -0 -n 1 basename)
asset_name=${wheel_name//"linux"/"manylinux1"}
echo "wheel_name=${wheel_name}" >> $GITHUB_ENV
echo "asset_name=${asset_name}" >> $GITHUB_ENV
echo "wheel_name=${wheel_name}" >> "$GITHUB_ENV"
echo "asset_name=${asset_name}" >> "$GITHUB_ENV"
- name: Upload Release Asset
uses: actions/upload-release-asset@v1
......
......@@ -8,7 +8,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Remind to run full CI on PR
uses: actions/github-script@v6
uses: actions/github-script@v7
with:
script: |
github.rest.issues.createComment({
......
......@@ -17,9 +17,9 @@ jobs:
matrix:
python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"]
steps:
- uses: actions/checkout@v2
- uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
- name: Install dependencies
......
#!/bin/bash
set -eux
python_executable=python$1
cuda_home=/usr/local/cuda-$2
......@@ -8,13 +9,15 @@ PATH=${cuda_home}/bin:$PATH
LD_LIBRARY_PATH=${cuda_home}/lib64:$LD_LIBRARY_PATH
# Install requirements
$python_executable -m pip install wheel packaging
$python_executable -m pip install -r requirements-cuda.txt
$python_executable -m pip install -r requirements-build.txt -r requirements-cuda.txt
# Limit the number of parallel jobs to avoid OOM
export MAX_JOBS=1
# Make sure release wheels are built for the following architectures
export TORCH_CUDA_ARCH_LIST="7.0 7.5 8.0 8.6 8.9 9.0+PTX"
export VLLM_FA_CMAKE_GPU_ARCHES="80-real;90-real"
bash tools/check_repo.sh
# Build
$python_executable setup.py bdist_wheel --dist-dir=dist
......@@ -16,9 +16,9 @@ jobs:
matrix:
python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"]
steps:
- uses: actions/checkout@v2
- uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
- name: Install dependencies
......
......@@ -33,6 +33,7 @@ share/python-wheels/
.installed.cfg
*.egg
MANIFEST
/.deps/
# PyInstaller
# Usually these files are written by a python script from a template
......@@ -198,3 +199,6 @@ hip_compat.h
# Benchmark dataset
benchmarks/*.json
# Linting
actionlint
......@@ -13,10 +13,10 @@ sphinx:
fail_on_warning: true
# If using Sphinx, optionally build your docs in additional formats such as PDF
formats:
- pdf
formats: []
# Optionally declare the Python requirements required to build your docs
python:
install:
- requirements: docs/requirements-docs.txt
......@@ -147,14 +147,32 @@ else()
message(FATAL_ERROR "Can't find CUDA or HIP installation.")
endif()
#
# Override the GPU architectures detected by cmake/torch and filter them by
# the supported versions for the current language.
# The final set of arches is stored in `VLLM_GPU_ARCHES`.
#
override_gpu_arches(VLLM_GPU_ARCHES
if(VLLM_GPU_LANG STREQUAL "CUDA")
#
# For cuda we want to be able to control which architectures we compile for on
# a per-file basis in order to cut down on compile time. So here we extract
# the set of architectures we want to compile for and remove the from the
# CMAKE_CUDA_FLAGS so that they are not applied globally.
#
clear_cuda_arches(CUDA_ARCH_FLAGS)
extract_unique_cuda_archs_ascending(CUDA_ARCHS "${CUDA_ARCH_FLAGS}")
message(STATUS "CUDA target architectures: ${CUDA_ARCHS}")
# Filter the target architectures by the supported supported archs
# since for some files we will build for all CUDA_ARCHS.
cuda_archs_loose_intersection(CUDA_ARCHS
"${CUDA_SUPPORTED_ARCHS}" "${CUDA_ARCHS}")
message(STATUS "CUDA supported target architectures: ${CUDA_ARCHS}")
else()
#
# For other GPU targets override the GPU architectures detected by cmake/torch
# and filter them by the supported versions for the current language.
# The final set of arches is stored in `VLLM_GPU_ARCHES`.
#
override_gpu_arches(VLLM_GPU_ARCHES
${VLLM_GPU_LANG}
"${${VLLM_GPU_LANG}_SUPPORTED_ARCHS}")
endif()
#
# Query torch for additional GPU compilation flags for the given
......@@ -170,7 +188,16 @@ if(NVCC_THREADS AND VLLM_GPU_LANG STREQUAL "CUDA")
list(APPEND VLLM_GPU_FLAGS "--threads=${NVCC_THREADS}")
endif()
#
# Use FetchContent for C++ dependencies that are compiled as part of vLLM's build process.
# Configure it to place files in vllm/.deps, in order to play nicely with sccache.
#
include(FetchContent)
get_filename_component(PROJECT_ROOT_DIR "${CMAKE_CURRENT_SOURCE_DIR}" ABSOLUTE)
file(MAKE_DIRECTORY "${FETCHCONTENT_BASE_DIR}")
set(FETCHCONTENT_BASE_DIR "${PROJECT_ROOT_DIR}/.deps")
message(STATUS "FetchContent base directory: ${FETCHCONTENT_BASE_DIR}")
#
# Define other extension targets
......@@ -224,30 +251,89 @@ if(VLLM_GPU_LANG STREQUAL "CUDA")
"csrc/mamba/causal_conv1d/causal_conv1d.cu"
"csrc/quantization/aqlm/gemm_kernels.cu"
"csrc/quantization/awq/gemm_kernels.cu"
"csrc/quantization/gguf/gguf_kernel.cu"
"csrc/custom_all_reduce.cu"
"csrc/permute_cols.cu"
"csrc/quantization/cutlass_w8a8/scaled_mm_entry.cu")
set_gencode_flags_for_srcs(
SRCS "${VLLM_EXT_SRC}"
CUDA_ARCHS "${CUDA_ARCHS}")
# Only build Marlin kernels if we are building for at least some compatible archs.
# Keep building Marlin for 9.0 as there are some group sizes and shapes that
# are not supported by Machete yet.
cuda_archs_loose_intersection(MARLIN_ARCHS "8.0;8.6;8.9;9.0" ${CUDA_ARCHS})
if (MARLIN_ARCHS)
set(MARLIN_SRCS
"csrc/quantization/fp8/fp8_marlin.cu"
"csrc/quantization/marlin/dense/marlin_cuda_kernel.cu"
"csrc/quantization/marlin/sparse/marlin_24_cuda_kernel.cu"
"csrc/quantization/marlin/qqq/marlin_qqq_gemm_kernel.cu"
"csrc/quantization/gptq_marlin/gptq_marlin.cu"
"csrc/quantization/gptq_marlin/gptq_marlin_repack.cu"
"csrc/quantization/gptq_marlin/awq_marlin_repack.cu"
"csrc/quantization/gguf/gguf_kernel.cu"
"csrc/quantization/fp8/fp8_marlin.cu"
"csrc/custom_all_reduce.cu"
"csrc/permute_cols.cu"
"csrc/quantization/cutlass_w8a8/scaled_mm_entry.cu"
"csrc/quantization/cutlass_w8a8/scaled_mm_c2x.cu"
"csrc/quantization/cutlass_w8a8/scaled_mm_c3x.cu")
"csrc/quantization/gptq_marlin/awq_marlin_repack.cu")
set_gencode_flags_for_srcs(
SRCS "${MARLIN_SRCS}"
CUDA_ARCHS "${MARLIN_ARCHS}")
list(APPEND VLLM_EXT_SRC "${MARLIN_SRCS}")
message(STATUS "Building Marlin kernels for archs: ${MARLIN_ARCHS}")
else()
message(STATUS "Not building Marlin kernels as no compatible archs found"
"in CUDA target architectures")
endif()
#
# The CUTLASS kernels for Hopper require sm90a to be enabled.
# This is done via the below gencode option, BUT that creates kernels for both sm90 and sm90a.
# That adds an extra 17MB to compiled binary, so instead we selectively enable it.
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0)
set_source_files_properties(
"csrc/quantization/cutlass_w8a8/scaled_mm_c3x.cu"
PROPERTIES
COMPILE_FLAGS
"-gencode arch=compute_90a,code=sm_90a")
# The cutlass_scaled_mm kernels for Hopper (c3x, i.e. CUTLASS 3.x) require
# CUDA 12.0 or later (and only work on Hopper, 9.0/9.0a for now).
cuda_archs_loose_intersection(SCALED_MM_3X_ARCHS "9.0;9.0a" "${CUDA_ARCHS}")
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0 AND SCALED_MM_3X_ARCHS)
set(SRCS "csrc/quantization/cutlass_w8a8/scaled_mm_c3x.cu")
set_gencode_flags_for_srcs(
SRCS "${SRCS}"
CUDA_ARCHS "${SCALED_MM_3X_ARCHS}")
list(APPEND VLLM_EXT_SRC "${SRCS}")
list(APPEND VLLM_GPU_FLAGS "-DENABLE_SCALED_MM_C3X=1")
message(STATUS "Building scaled_mm_c3x for archs: ${SCALED_MM_3X_ARCHS}")
else()
if (NOT ${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0 AND SCALED_MM_3X_ARCHS)
message(STATUS "Not building scaled_mm_c3x as CUDA Compiler version is "
"not >= 12.0, we recommend upgrading to CUDA 12.0 or "
"later if you intend on running FP8 quantized models on "
"Hopper.")
else()
message(STATUS "Not building scaled_mm_c3x as no compatible archs found "
"in CUDA target architectures")
endif()
# clear SCALED_MM_3X_ARCHS so the scaled_mm_c2x kernels know we didn't
# build any 3x kernels
set(SCALED_MM_3X_ARCHS)
endif()
#
# For the cutlass_scaled_mm kernels we want to build the c2x (CUTLASS 2.x)
# kernels for the remaining archs that are not already built for 3x.
cuda_archs_loose_intersection(SCALED_MM_2X_ARCHS
"7.5;8.0;8.6;8.9;9.0" "${CUDA_ARCHS}")
# subtract out the archs that are already built for 3x
list(REMOVE_ITEM SCALED_MM_2X_ARCHS ${SCALED_MM_3X_ARCHS})
if (SCALED_MM_2X_ARCHS)
set(SRCS "csrc/quantization/cutlass_w8a8/scaled_mm_c2x.cu")
set_gencode_flags_for_srcs(
SRCS "${SRCS}"
CUDA_ARCHS "${SCALED_MM_2X_ARCHS}")
list(APPEND VLLM_EXT_SRC "${SRCS}")
list(APPEND VLLM_GPU_FLAGS "-DENABLE_SCALED_MM_C2X=1")
message(STATUS "Building scaled_mm_c2x for archs: ${SCALED_MM_2X_ARCHS}")
else()
if (SCALED_MM_3X_ARCHS)
message(STATUS "Not building scaled_mm_c2x as all archs are already built"
" for and covered by scaled_mm_c3x")
else()
message(STATUS "Not building scaled_mm_c2x as no compatible archs found "
"in CUDA target architectures")
endif()
endif()
......@@ -255,15 +341,26 @@ if(VLLM_GPU_LANG STREQUAL "CUDA")
# Machete kernels
# The machete kernels only work on hopper and require CUDA 12.0 or later.
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0)
# Only build Machete kernels if we are building for something compatible with sm90a
cuda_archs_loose_intersection(MACHETE_ARCHS "9.0a" "${CUDA_ARCHS}")
if(${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0 AND MACHETE_ARCHS)
#
# For the Machete kernels we automatically generate sources for various
# preselected input type pairs and schedules.
# Generate sources:
set(MACHETE_GEN_SCRIPT
${CMAKE_CURRENT_SOURCE_DIR}/csrc/quantization/machete/generate.py)
file(MD5 ${MACHETE_GEN_SCRIPT} MACHETE_GEN_SCRIPT_HASH)
message(STATUS "Machete generation script hash: ${MACHETE_GEN_SCRIPT_HASH}")
message(STATUS "Last run machete generate script hash: $CACHE{MACHETE_GEN_SCRIPT_HASH}")
if (NOT DEFINED CACHE{MACHETE_GEN_SCRIPT_HASH}
OR NOT $CACHE{MACHETE_GEN_SCRIPT_HASH} STREQUAL ${MACHETE_GEN_SCRIPT_HASH})
execute_process(
COMMAND ${CMAKE_COMMAND} -E env
PYTHONPATH=${CMAKE_CURRENT_SOURCE_DIR}/csrc/cutlass_extensions/:${CUTLASS_DIR}/python/:${VLLM_PYTHON_PATH}:$PYTHONPATH
${Python_EXECUTABLE} ${CMAKE_CURRENT_SOURCE_DIR}/csrc/quantization/machete/generate.py
${Python_EXECUTABLE} ${MACHETE_GEN_SCRIPT}
RESULT_VARIABLE machete_generation_result
OUTPUT_VARIABLE machete_generation_output
OUTPUT_FILE ${CMAKE_CURRENT_BINARY_DIR}/machete_generation.log
......@@ -276,26 +373,40 @@ if(VLLM_GPU_LANG STREQUAL "CUDA")
"\nCheck the log for details: "
"${CMAKE_CURRENT_BINARY_DIR}/machete_generation.log")
else()
set(MACHETE_GEN_SCRIPT_HASH ${MACHETE_GEN_SCRIPT_HASH}
CACHE STRING "Last run machete generate script hash" FORCE)
message(STATUS "Machete generation completed successfully.")
endif()
else()
message(STATUS "Machete generation script has not changed, skipping generation.")
endif()
# Add machete generated sources
file(GLOB MACHETE_GEN_SOURCES "csrc/quantization/machete/generated/*.cu")
list(APPEND VLLM_EXT_SRC ${MACHETE_GEN_SOURCES})
message(STATUS "Machete generated sources: ${MACHETE_GEN_SOURCES}")
set_source_files_properties(
${MACHETE_GEN_SOURCES}
PROPERTIES
COMPILE_FLAGS
"-gencode arch=compute_90a,code=sm_90a")
endif()
# forward compatible
set_gencode_flags_for_srcs(
SRCS "${MACHETE_GEN_SOURCES}"
CUDA_ARCHS "${MACHETE_ARCHS}")
# Add pytorch binding for machete (add on even CUDA < 12.0 so that we can
# raise an error if the user that this was built with an incompatible
# CUDA version)
list(APPEND VLLM_EXT_SRC
csrc/quantization/machete/machete_pytorch.cu)
message(STATUS "Building Machete kernels for archs: ${MACHETE_ARCHS}")
else()
if (NOT ${CMAKE_CUDA_COMPILER_VERSION} VERSION_GREATER 12.0
AND MACHETE_ARCHS)
message(STATUS "Not building Machete kernels as CUDA Compiler version is "
"not >= 12.0, we recommend upgrading to CUDA 12.0 or "
"later if you intend on running w4a16 quantized models on "
"Hopper.")
else()
message(STATUS "Not building Machete kernels as no compatible archs "
"found in CUDA target architectures")
endif()
endif()
# if CUDA endif
endif()
message(STATUS "Enabling C extension.")
......@@ -324,14 +435,33 @@ set(VLLM_MOE_EXT_SRC
"csrc/moe/torch_bindings.cpp"
"csrc/moe/topk_softmax_kernels.cu")
set_gencode_flags_for_srcs(
SRCS "${VLLM_MOE_EXT_SRC}"
CUDA_ARCHS "${CUDA_ARCHS}")
if(VLLM_GPU_LANG STREQUAL "CUDA")
list(APPEND VLLM_MOE_EXT_SRC
cuda_archs_loose_intersection(MARLIN_MOE_ARCHS "8.0;8.6;8.9;9.0" "${CUDA_ARCHS}")
if (MARLIN_MOE_ARCHS)
set(MARLIN_MOE_SRC
"csrc/moe/marlin_kernels/marlin_moe_kernel.h"
"csrc/moe/marlin_kernels/marlin_moe_kernel_ku4b8.h"
"csrc/moe/marlin_kernels/marlin_moe_kernel_ku4b8.cu"
"csrc/moe/marlin_kernels/marlin_moe_kernel_ku8b128.h"
"csrc/moe/marlin_kernels/marlin_moe_kernel_ku8b128.cu"
"csrc/moe/marlin_kernels/marlin_moe_kernel_ku4.h"
"csrc/moe/marlin_kernels/marlin_moe_kernel_ku4.cu"
"csrc/moe/marlin_moe_ops.cu")
set_gencode_flags_for_srcs(
SRCS "${MARLIN_MOE_SRC}"
CUDA_ARCHS "${MARLIN_MOE_ARCHS}")
list(APPEND VLLM_MOE_EXT_SRC "${MARLIN_MOE_SRC}")
message(STATUS "Building Marlin MOE kernels for archs: ${MARLIN_MOE_ARCHS}")
else()
message(STATUS "Not building Marlin MOE kernels as no compatible archs found"
"in CUDA target architectures")
endif()
endif()
message(STATUS "Enabling moe extension.")
......@@ -371,6 +501,17 @@ if (NOT VLLM_TARGET_DEVICE STREQUAL "cuda")
return()
endif ()
# vLLM flash attention requires VLLM_GPU_ARCHES to contain the set of target
# arches in the CMake syntax (75-real, 89-virtual, etc), since we clear the
# arches in the CUDA case (and instead set the gencodes on a per file basis)
# we need to manually set VLLM_GPU_ARCHES here.
if(VLLM_GPU_LANG STREQUAL "CUDA")
foreach(_ARCH ${CUDA_ARCHS})
string(REPLACE "." "" _ARCH "${_ARCH}")
list(APPEND VLLM_GPU_ARCHES "${_ARCH}-real")
endforeach()
endif()
#
# Build vLLM flash attention from source
#
......
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