Commit e7c1b7f3 authored by zhuwenwen's avatar zhuwenwen
Browse files

Merge branch 'v0.5.4-dtk24.04.1'

parents 7462218e 04c62b93
{% set docker_image = "us-central1-docker.pkg.dev/vllm-405802/vllm-ci-test-repo/vllm-test:$BUILDKITE_COMMIT" %}
{% set default_num_gpu = 1 %}
{% set default_working_dir = "/vllm-workspace/tests" %}
steps:
- label: ":docker: build image"
commands:
- "docker build --build-arg max_jobs=16 --tag {{ docker_image }} --target test --progress plain ."
- "docker push {{ docker_image }}"
env:
DOCKER_BUILDKIT: "1"
retry:
automatic:
- exit_status: -1 # Agent was lost
limit: 5
- exit_status: -10 # Agent was lost
limit: 5
- wait
- group: "AMD Tests"
depends_on: ~
steps:
{% for step in steps %}
{% if step.mirror_hardwares and "amd" in step.mirror_hardwares %}
- label: "AMD: {{ step.label }}"
agents:
queue: amd
command: bash .buildkite/run-amd-test.sh "cd {{ (step.working_dir or default_working_dir) | safe }} ; {{ step.command or (step.commands | join(" ; ")) | safe }}"
env:
DOCKER_BUILDKIT: "1"
soft_fail: true
{% endif %}
{% endfor %}
- label: "Neuron Test"
depends_on: ~
agents:
queue: neuron
command: bash .buildkite/run-neuron-test.sh
soft_fail: false
- label: "Intel Test"
depends_on: ~
agents:
queue: intel
command: bash .buildkite/run-cpu-test.sh
{% for step in steps %}
- label: "{{ step.label }}"
agents:
queue: kubernetes
soft_fail: {{ step.soft_fail or false }}
{% if step.parallelism %}
parallelism: {{ step.parallelism }}
{% endif %}
retry:
automatic:
- exit_status: -1 # Agent was lost
limit: 5
- exit_status: -10 # Agent was lost
limit: 5
plugins:
- kubernetes:
podSpec:
{% if step.num_gpus %}
priorityClassName: gpu-priority-cls-{{ step.num_gpus }}
{% endif %}
volumes:
- name: dshm
emptyDir:
medium: Memory
containers:
- image: "{{ docker_image }}"
command: ["bash"]
args:
- '-c'
- "'cd {{ (step.working_dir or default_working_dir) | safe }} && {{ step.command or (step.commands | join(' && ')) | safe }}'"
{% if not step.no_gpu %}
resources:
requests:
nvidia.com/gpu: "{{ step.num_gpus or default_num_gpu }}"
limits:
nvidia.com/gpu: "{{ step.num_gpus or default_num_gpu }}"
{% endif %}
env:
- name: VLLM_USAGE_SOURCE
value: ci-test
- name: HF_TOKEN
valueFrom:
secretKeyRef:
name: hf-token-secret
key: token
volumeMounts:
- mountPath: /dev/shm
name: dshm
{% endfor %}
github: [vllm-project]
open_collective: [vllm]
name: Add label on auto-merge enabled
on:
pull_request_target:
types:
- auto_merge_enabled
jobs:
add-label-on-auto-merge:
runs-on: ubuntu-latest
steps:
- name: Add label
uses: actions/github-script@v5
with:
script: |
github.rest.issues.addLabels({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: context.issue.number,
labels: ['ready']
})
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
name: Add Ready Label on Ready Comment
on:
issue_comment:
types: [created]
jobs:
add-ready-label:
runs-on: ubuntu-latest
if: github.event.issue.pull_request && contains(github.event.comment.body, '/ready')
steps:
- name: Add label
uses: actions/github-script@v5
with:
script: |
github.rest.issues.addLabels({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: context.issue.number,
labels: ['ready']
})
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
......@@ -30,12 +30,6 @@ jobs:
run: |
EXCLUDES=(
'csrc/moe/topk_softmax_kernels.cu'
'csrc/punica/bgmv/bgmv_bf16_bf16_bf16.cu'
'csrc/punica/bgmv/bgmv_config.h'
'csrc/punica/bgmv/bgmv_impl.cuh'
'csrc/punica/bgmv/vec_dtypes.cuh'
'csrc/punica/punica_ops.cu'
'csrc/punica/type_convert.h'
)
find csrc/ \( -name '*.h' -o -name '*.cpp' -o -name '*.cu' -o -name '*.cuh' \) -print \
| grep -vFf <(printf "%s\n" "${EXCLUDES[@]}") \
......
......@@ -15,7 +15,7 @@ jobs:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ["3.8", "3.9", "3.10", "3.11"]
python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"]
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
......@@ -32,20 +32,17 @@ jobs:
pip install types-setuptools
- name: Mypy
run: |
mypy vllm/attention --config-file pyproject.toml
mypy vllm/core --config-file pyproject.toml
mypy vllm/distributed --config-file pyproject.toml
mypy vllm/entrypoints --config-file pyproject.toml
mypy vllm/executor --config-file pyproject.toml
mypy vllm/multimodal --config-file pyproject.toml
mypy vllm/usage --config-file pyproject.toml
mypy vllm/*.py --config-file pyproject.toml
mypy vllm/transformers_utils --config-file pyproject.toml
mypy vllm/engine --config-file pyproject.toml
mypy vllm/worker --config-file pyproject.toml
mypy vllm/spec_decode --config-file pyproject.toml
mypy vllm/model_executor --config-file pyproject.toml
mypy vllm/lora --config-file pyproject.toml
mypy vllm/logging --config-file pyproject.toml
mypy vllm/model_executor --config-file pyproject.toml
mypy
mypy tests --follow-imports skip
mypy vllm/attention --follow-imports skip
mypy vllm/core --follow-imports skip
mypy vllm/distributed --follow-imports skip
mypy vllm/engine --follow-imports skip
mypy vllm/entrypoints --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
......@@ -48,8 +48,8 @@ jobs:
fail-fast: false
matrix:
os: ['ubuntu-20.04']
python-version: ['3.8', '3.9', '3.10', '3.11']
pytorch-version: ['2.3.0'] # Must be the most recent version that meets requirements-cuda.txt.
python-version: ['3.8', '3.9', '3.10', '3.11', '3.12']
pytorch-version: ['2.4.0'] # Must be the most recent version that meets requirements-cuda.txt.
cuda-version: ['11.8', '12.1']
steps:
......
name: PR Reminder Comment Bot
on:
pull_request_target:
types: [opened]
jobs:
pr_reminder:
runs-on: ubuntu-latest
steps:
- name: Remind to run full CI on PR
uses: actions/github-script@v6
with:
script: |
github.rest.issues.createComment({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: context.issue.number,
body: '👋 Hi! Thank you for contributing to the vLLM project.\n Just a reminder: PRs would not trigger full CI run by default. Instead, it would only run `fastcheck` CI which consists a small and essential subset of CI tests to quickly catch errors. You can run other CI tests on top of default ones by unblocking the steps in your `fast-check` build on Buildkite UI. \n\nOnce the PR is approved and ready to go, please make sure to run full CI as it is required to merge (or just use auto-merge).\n\n To run full CI, you can do one of these:\n- Comment `/ready` on the PR\n- Add `ready` label to the PR\n- Enable auto-merge.\n\n🚀'
})
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
name: Remove ready Label on notready Comment
on:
issue_comment:
types: [created]
jobs:
add-ready-label:
runs-on: ubuntu-latest
if: github.event.issue.pull_request && contains(github.event.comment.body, '/notready')
steps:
- name: Remove ready label
uses: actions/github-script@v5
with:
script: |
github.rest.issues.removeLabel({
owner: context.repo.owner,
repo: context.repo.repo,
issue_number: context.issue.number,
name: 'ready'
})
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
......@@ -15,7 +15,7 @@ jobs:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ["3.8", "3.9", "3.10", "3.11"]
python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"]
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
......
......@@ -13,8 +13,6 @@ $python_executable -m pip install -r requirements-cuda.txt
# Limit the number of parallel jobs to avoid OOM
export MAX_JOBS=1
# Make sure punica is built for the release (for LoRA)
export VLLM_INSTALL_PUNICA_KERNELS=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"
# Build
......
......@@ -14,7 +14,7 @@ jobs:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ["3.8", "3.9", "3.10", "3.11"]
python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"]
steps:
- uses: actions/checkout@v2
- name: Set up Python ${{ matrix.python-version }}
......
# vllm commit id, generated by setup.py
vllm/commit_id.py
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
......
......@@ -10,6 +10,7 @@ build:
sphinx:
configuration: docs/source/conf.py
fail_on_warning: true
# If using Sphinx, optionally build your docs in additional formats such as PDF
formats:
......
......@@ -2,7 +2,8 @@ cmake_minimum_required(VERSION 3.21)
project(vllm_extensions LANGUAGES CXX)
option(VLLM_TARGET_DEVICE "Target device backend for vLLM" "cuda")
# CUDA by default, can be overridden by using -DVLLM_TARGET_DEVICE=... (used by setup.py)
set(VLLM_TARGET_DEVICE "cuda" CACHE STRING "Target device backend for vLLM")
set(CMAKE_BUILD_TYPE "Release")
......@@ -15,7 +16,7 @@ add_compile_options(-w)
# Supported python versions. These versions will be searched in order, the
# first match will be selected. These should be kept in sync with setup.py.
#
set(PYTHON_SUPPORTED_VERSIONS "3.8" "3.9" "3.10" "3.11")
set(PYTHON_SUPPORTED_VERSIONS "3.8" "3.9" "3.10" "3.11" "3.12")
# Supported NVIDIA architectures.
set(CUDA_SUPPORTED_ARCHS "7.0;7.5;8.0;8.6;8.9;9.0")
......@@ -33,9 +34,8 @@ set(HIP_SUPPORTED_ARCHS "gfx906;gfx908;gfx90a;gfx940;gfx941;gfx942;gfx1030;gfx11
# requirements.txt files and should be kept consistent. The ROCm torch
# versions are derived from Dockerfile.rocm
#
set(TORCH_SUPPORTED_VERSION_CUDA "2.3.0")
set(TORCH_SUPPORTED_VERSION_ROCM_5X "2.0.1")
set(TORCH_SUPPORTED_VERSION_ROCM_6X "2.1.1")
set(TORCH_SUPPORTED_VERSION_CUDA "2.4.0")
set(TORCH_SUPPORTED_VERSION_ROCM "2.5.0")
#
# Try to find python package with an executable that exactly matches
......@@ -68,6 +68,39 @@ endif()
#
find_package(Torch REQUIRED)
#
# Add the `default` target which detects which extensions should be
# built based on platform/architecture. This is the same logic that
# setup.py uses to select which extensions should be built and should
# be kept in sync.
#
# The `default` target makes direct use of cmake easier since knowledge
# of which extensions are supported has been factored in, e.g.
#
# mkdir build && cd build
# cmake -G Ninja -DVLLM_PYTHON_EXECUTABLE=`which python3` -DCMAKE_LIBRARY_OUTPUT_DIRECTORY=../vllm ..
# cmake --build . --target default
#
add_custom_target(default)
message(STATUS "Enabling core extension.")
# Define _core_C extension
# built for (almost) every target platform, (excludes TPU and Neuron)
set(VLLM_EXT_SRC
"csrc/core/torch_bindings.cpp")
define_gpu_extension_target(
_core_C
DESTINATION vllm
LANGUAGE CXX
SOURCES ${VLLM_EXT_SRC}
COMPILE_FLAGS ${CXX_COMPILE_FLAGS}
USE_SABI 3
WITH_SOABI)
add_dependencies(default _core_C)
#
# Forward the non-CUDA device extensions to external CMake scripts.
#
......@@ -76,7 +109,7 @@ if (NOT VLLM_TARGET_DEVICE STREQUAL "cuda" AND
if (VLLM_TARGET_DEVICE STREQUAL "cpu")
include(${CMAKE_CURRENT_LIST_DIR}/cmake/cpu_extension.cmake)
else()
message(FATAL_ERROR "Unsupported vLLM target device: ${VLLM_TARGET_DEVICE}")
return()
endif()
return()
endif()
......@@ -100,18 +133,11 @@ elseif(HIP_FOUND)
# .hip extension automatically, HIP must be enabled explicitly.
enable_language(HIP)
# ROCm 5.x
if (ROCM_VERSION_DEV_MAJOR EQUAL 5 AND
NOT Torch_VERSION VERSION_EQUAL ${TORCH_SUPPORTED_VERSION_ROCM_5X})
message(WARNING "Pytorch version ${TORCH_SUPPORTED_VERSION_ROCM_5X} "
"expected for ROCMm 5.x build, saw ${Torch_VERSION} instead.")
endif()
# ROCm 6.x
if (ROCM_VERSION_DEV_MAJOR EQUAL 6 AND
NOT Torch_VERSION VERSION_EQUAL ${TORCH_SUPPORTED_VERSION_ROCM_6X})
message(WARNING "Pytorch version ${TORCH_SUPPORTED_VERSION_ROCM_6X} "
"expected for ROCMm 6.x build, saw ${Torch_VERSION} instead.")
# ROCm 5.X and 6.X
if (ROCM_VERSION_DEV_MAJOR GREATER_EQUAL 5 AND
NOT Torch_VERSION VERSION_EQUAL ${TORCH_SUPPORTED_VERSION_ROCM})
message(WARNING "Pytorch version >= ${TORCH_SUPPORTED_VERSION_ROCM} "
"expected for ROCm build, saw ${Torch_VERSION} instead.")
endif()
else()
message(FATAL_ERROR "Can't find CUDA or HIP installation.")
......@@ -141,7 +167,7 @@ if(NVCC_THREADS AND VLLM_GPU_LANG STREQUAL "CUDA")
endif()
#
# Define extension targets
# Define other extension targets
#
#
......@@ -165,16 +191,18 @@ set(VLLM_EXT_SRC
# "csrc/quantization/fp8/common.cu"
"csrc/cuda_utils_kernels.cu"
"csrc/moe_align_block_size_kernels.cu"
"csrc/prepare_inputs/advance_step.cu"
"csrc/torch_bindings.cpp")
if(VLLM_GPU_LANG STREQUAL "CUDA")
include(FetchContent)
SET(CUTLASS_ENABLE_HEADERS_ONLY=ON)
SET(CUTLASS_ENABLE_HEADERS_ONLY ON CACHE BOOL "Enable only the header library")
FetchContent_Declare(
cutlass
GIT_REPOSITORY https://github.com/nvidia/cutlass.git
# CUTLASS 3.5.0
GIT_TAG 7d49e6c7e2f8896c47f586706e67e1fb215529dc
# CUTLASS 3.5.1
GIT_TAG 06b21349bcf6ddf6a1686a47a137ad1446579db9
GIT_PROGRESS TRUE
)
FetchContent_MakeAvailable(cutlass)
......@@ -183,8 +211,11 @@ if(VLLM_GPU_LANG STREQUAL "CUDA")
"csrc/quantization/awq/gemm_kernels.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/fp8/fp8_marlin.cu"
"csrc/custom_all_reduce.cu"
"csrc/quantization/cutlass_w8a8/scaled_mm_entry.cu"
"csrc/quantization/cutlass_w8a8/scaled_mm_c2x.cu"
......@@ -211,7 +242,7 @@ define_gpu_extension_target(
SOURCES ${VLLM_EXT_SRC}
COMPILE_FLAGS ${VLLM_GPU_FLAGS}
ARCHITECTURES ${VLLM_GPU_ARCHES}
INCLUDE_DIRECTORIES ${CUTLASS_INCLUDE_DIR};${CUTLASS_TOOLS_UTIL_INCLUDE_DIR}
INCLUDE_DIRECTORIES ${CUTLASS_INCLUDE_DIR}
USE_SABI 3
WITH_SOABI)
......@@ -233,76 +264,7 @@ define_gpu_extension_target(
USE_SABI 3
WITH_SOABI)
#
# _punica_C extension
#
set(VLLM_PUNICA_EXT_SRC
"csrc/punica/bgmv/bgmv_bf16_bf16_bf16.cu"
"csrc/punica/bgmv/bgmv_bf16_fp32_bf16.cu"
"csrc/punica/bgmv/bgmv_fp16_fp16_fp16.cu"
"csrc/punica/bgmv/bgmv_fp16_fp32_fp16.cu"
"csrc/punica/bgmv/bgmv_fp32_bf16_bf16.cu"
"csrc/punica/bgmv/bgmv_fp32_fp16_fp16.cu"
"csrc/punica/punica_ops.cu"
"csrc/punica/torch_bindings.cpp")
#
# Copy GPU compilation flags+update for punica
#
set(VLLM_PUNICA_GPU_FLAGS ${VLLM_GPU_FLAGS})
list(REMOVE_ITEM VLLM_PUNICA_GPU_FLAGS
"-D__CUDA_NO_HALF_OPERATORS__"
"-D__CUDA_NO_HALF_CONVERSIONS__"
"-D__CUDA_NO_BFLOAT16_CONVERSIONS__"
"-D__CUDA_NO_HALF2_OPERATORS__")
#
# Filter out CUDA architectures < 8.0 for punica.
#
if (${VLLM_GPU_LANG} STREQUAL "CUDA")
set(VLLM_PUNICA_GPU_ARCHES)
foreach(ARCH ${VLLM_GPU_ARCHES})
string_to_ver(CODE_VER ${ARCH})
if (CODE_VER GREATER_EQUAL 8.0)
list(APPEND VLLM_PUNICA_GPU_ARCHES ${ARCH})
endif()
endforeach()
message(STATUS "Punica target arches: ${VLLM_PUNICA_GPU_ARCHES}")
elseif(${VLLM_GPU_LANG} STREQUAL "HIP")
set(VLLM_PUNICA_GPU_ARCHES ${VLLM_GPU_ARCHES})
message(STATUS "Punica target arches: ${VLLM_PUNICA_GPU_ARCHES}")
endif()
if (VLLM_PUNICA_GPU_ARCHES)
define_gpu_extension_target(
_punica_C
DESTINATION vllm
LANGUAGE ${VLLM_GPU_LANG}
SOURCES ${VLLM_PUNICA_EXT_SRC}
COMPILE_FLAGS ${VLLM_PUNICA_GPU_FLAGS}
ARCHITECTURES ${VLLM_PUNICA_GPU_ARCHES}
USE_SABI 3
WITH_SOABI)
else()
message(WARNING "Unable to create _punica_C target because none of the "
"requested architectures (${VLLM_GPU_ARCHES}) are supported, i.e. >= 8.0")
endif()
#
# Add the `default` target which detects which extensions should be
# built based on platform/architecture. This is the same logic that
# setup.py uses to select which extensions should be built and should
# be kept in sync.
#
# The `default` target makes direct use of cmake easier since knowledge
# of which extensions are supported has been factored in, e.g.
#
# mkdir build && cd build
# cmake -G Ninja -DVLLM_PYTHON_EXECUTABLE=`which python3` -DCMAKE_LIBRARY_OUTPUT_DIRECTORY=../vllm ..
# cmake --build . --target default
#
add_custom_target(default)
if(VLLM_GPU_LANG STREQUAL "CUDA" OR VLLM_GPU_LANG STREQUAL "HIP")
message(STATUS "Enabling C extension.")
......@@ -311,12 +273,4 @@ if(VLLM_GPU_LANG STREQUAL "CUDA" OR VLLM_GPU_LANG STREQUAL "HIP")
message(STATUS "Enabling moe extension.")
add_dependencies(default _moe_C)
# Enable punica if -DVLLM_INSTALL_PUNICA_KERNELS=ON or
# VLLM_INSTALL_PUNICA_KERNELS is set in the environment and
# there are supported target arches.
if (VLLM_PUNICA_GPU_ARCHES AND
(ENV{VLLM_INSTALL_PUNICA_KERNELS} OR VLLM_INSTALL_PUNICA_KERNELS))
message(STATUS "Enabling punica extension.")
add_dependencies(default _punica_C)
endif()
endif()
......@@ -5,33 +5,51 @@
# docs/source/dev/dockerfile/dockerfile.rst and
# docs/source/assets/dev/dockerfile-stages-dependency.png
ARG CUDA_VERSION=12.4.1
#################### BASE BUILD IMAGE ####################
# prepare basic build environment
FROM nvidia/cuda:12.4.1-devel-ubuntu22.04 AS dev
FROM nvidia/cuda:${CUDA_VERSION}-devel-ubuntu20.04 AS base
ARG CUDA_VERSION=12.4.1
ARG PYTHON_VERSION=3.10
ENV DEBIAN_FRONTEND=noninteractive
RUN echo 'tzdata tzdata/Areas select America' | debconf-set-selections \
&& echo 'tzdata tzdata/Zones/America select Los_Angeles' | debconf-set-selections \
&& apt-get update -y \
&& apt-get install -y ccache software-properties-common \
&& add-apt-repository ppa:deadsnakes/ppa \
&& apt-get update -y \
&& apt-get install -y python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-venv \
&& if [ "${PYTHON_VERSION}" != "3" ]; then update-alternatives --install /usr/bin/python3 python3 /usr/bin/python${PYTHON_VERSION} 1; fi \
&& python3 --version
RUN apt-get update -y \
&& apt-get install -y python3-pip git curl sudo
&& apt-get install -y git curl sudo
# Install pip s.t. it will be compatible with our PYTHON_VERSION
RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python${PYTHON_VERSION}
RUN python3 -m pip --version
# Workaround for https://github.com/openai/triton/issues/2507 and
# https://github.com/pytorch/pytorch/issues/107960 -- hopefully
# this won't be needed for future versions of this docker image
# or future versions of triton.
RUN ldconfig /usr/local/cuda-12.4/compat/
RUN ldconfig /usr/local/cuda-$(echo $CUDA_VERSION | cut -d. -f1,2)/compat/
WORKDIR /workspace
# install build and runtime dependencies
COPY requirements-common.txt requirements-common.txt
COPY requirements-adag.txt requirements-adag.txt
COPY requirements-cuda.txt requirements-cuda.txt
RUN --mount=type=cache,target=/root/.cache/pip \
pip install -r requirements-cuda.txt
python3 -m pip install -r requirements-cuda.txt
# install development dependencies
COPY requirements-lint.txt requirements-lint.txt
COPY requirements-test.txt requirements-test.txt
COPY requirements-dev.txt requirements-dev.txt
RUN --mount=type=cache,target=/root/.cache/pip \
pip install -r requirements-dev.txt
COPY requirements-mamba.txt requirements-mamba.txt
RUN python3 -m pip install packaging
RUN python3 -m pip install -r requirements-mamba.txt
# cuda arch list used by torch
# can be useful for both `dev` and `test`
......@@ -41,14 +59,16 @@ ARG torch_cuda_arch_list='7.0 7.5 8.0 8.6 8.9 9.0+PTX'
ENV TORCH_CUDA_ARCH_LIST=${torch_cuda_arch_list}
#################### BASE BUILD IMAGE ####################
#################### WHEEL BUILD IMAGE ####################
FROM dev AS build
FROM base AS build
ARG PYTHON_VERSION=3.10
# install build dependencies
COPY requirements-build.txt requirements-build.txt
RUN --mount=type=cache,target=/root/.cache/pip \
pip install -r requirements-build.txt
python3 -m pip install -r requirements-build.txt
# install compiler cache to speed up compilation leveraging local or remote caching
RUN apt-get update -y && apt-get install -y ccache
......@@ -59,6 +79,7 @@ COPY setup.py setup.py
COPY cmake cmake
COPY CMakeLists.txt CMakeLists.txt
COPY requirements-common.txt requirements-common.txt
COPY requirements-adag.txt requirements-adag.txt
COPY requirements-cuda.txt requirements-cuda.txt
COPY pyproject.toml pyproject.toml
COPY vllm vllm
......@@ -69,8 +90,9 @@ ENV MAX_JOBS=${max_jobs}
# number of threads used by nvcc
ARG nvcc_threads=8
ENV NVCC_THREADS=$nvcc_threads
# make sure punica kernels are built (for LoRA)
ENV VLLM_INSTALL_PUNICA_KERNELS=1
ARG buildkite_commit
ENV BUILDKITE_COMMIT=${buildkite_commit}
ARG USE_SCCACHE
# if USE_SCCACHE is set, use sccache to speed up compilation
......@@ -81,10 +103,15 @@ RUN --mount=type=cache,target=/root/.cache/pip \
&& tar -xzf sccache.tar.gz \
&& sudo mv sccache-v0.8.1-x86_64-unknown-linux-musl/sccache /usr/bin/sccache \
&& rm -rf sccache.tar.gz sccache-v0.8.1-x86_64-unknown-linux-musl \
&& export SCCACHE_BUCKET=vllm-build-sccache \
&& if [ "$CUDA_VERSION" = "11.8.0" ]; then \
export SCCACHE_BUCKET=vllm-build-sccache-2; \
else \
export SCCACHE_BUCKET=vllm-build-sccache; \
fi \
&& export SCCACHE_REGION=us-west-2 \
&& export CMAKE_BUILD_TYPE=Release \
&& sccache --show-stats \
&& python3 setup.py bdist_wheel --dist-dir=dist \
&& python3 setup.py bdist_wheel --dist-dir=dist --py-limited-api=cp38 \
&& sccache --show-stats; \
fi
......@@ -92,7 +119,7 @@ ENV CCACHE_DIR=/root/.cache/ccache
RUN --mount=type=cache,target=/root/.cache/ccache \
--mount=type=cache,target=/root/.cache/pip \
if [ "$USE_SCCACHE" != "1" ]; then \
python3 setup.py bdist_wheel --dist-dir=dist; \
python3 setup.py bdist_wheel --dist-dir=dist --py-limited-api=cp38; \
fi
# check the size of the wheel, we cannot upload wheels larger than 100MB
......@@ -101,24 +128,73 @@ RUN python3 check-wheel-size.py dist
#################### EXTENSION Build IMAGE ####################
#################### DEV IMAGE ####################
FROM base as dev
COPY requirements-lint.txt requirements-lint.txt
COPY requirements-test.txt requirements-test.txt
COPY requirements-dev.txt requirements-dev.txt
RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install -r requirements-dev.txt
#################### DEV IMAGE ####################
#################### MAMBA Build IMAGE ####################
FROM dev as mamba-builder
# max jobs used for build
ARG max_jobs=2
ENV MAX_JOBS=${max_jobs}
WORKDIR /usr/src/mamba
COPY requirements-mamba.txt requirements-mamba.txt
# Download the wheel or build it if a pre-compiled release doesn't exist
RUN pip --verbose wheel -r requirements-mamba.txt \
--no-build-isolation --no-deps --no-cache-dir
#################### MAMBA Build IMAGE ####################
#################### vLLM installation IMAGE ####################
# image with vLLM installed
FROM nvidia/cuda:12.4.1-base-ubuntu22.04 AS vllm-base
FROM nvidia/cuda:${CUDA_VERSION}-base-ubuntu20.04 AS vllm-base
ARG CUDA_VERSION=12.4.1
ARG PYTHON_VERSION=3.10
WORKDIR /vllm-workspace
RUN echo 'tzdata tzdata/Areas select America' | debconf-set-selections \
&& echo 'tzdata tzdata/Zones/America select Los_Angeles' | debconf-set-selections \
&& apt-get update -y \
&& apt-get install -y ccache software-properties-common \
&& add-apt-repository ppa:deadsnakes/ppa \
&& apt-get update -y \
&& apt-get install -y python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-venv \
&& if [ "${PYTHON_VERSION}" != "3" ]; then update-alternatives --install /usr/bin/python3 python3 /usr/bin/python${PYTHON_VERSION} 1; fi \
&& python3 --version
RUN apt-get update -y \
&& apt-get install -y python3-pip git vim
&& apt-get install -y python3-pip git vim curl libibverbs-dev
# Install pip s.t. it will be compatible with our PYTHON_VERSION
RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python${PYTHON_VERSION}
RUN python3 -m pip --version
# Workaround for https://github.com/openai/triton/issues/2507 and
# https://github.com/pytorch/pytorch/issues/107960 -- hopefully
# this won't be needed for future versions of this docker image
# or future versions of triton.
RUN ldconfig /usr/local/cuda-12.4/compat/
RUN ldconfig /usr/local/cuda-$(echo $CUDA_VERSION | cut -d. -f1,2)/compat/
# install vllm wheel first, so that torch etc will be installed
RUN --mount=type=bind,from=build,src=/workspace/dist,target=/vllm-workspace/dist \
--mount=type=cache,target=/root/.cache/pip \
pip install dist/*.whl --verbose
python3 -m pip install dist/*.whl --verbose
RUN --mount=type=bind,from=mamba-builder,src=/usr/src/mamba,target=/usr/src/mamba \
--mount=type=cache,target=/root/.cache/pip \
python3 -m pip install /usr/src/mamba/*.whl --no-cache-dir
RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install https://github.com/flashinfer-ai/flashinfer/releases/download/v0.1.2/flashinfer-0.1.2+cu121torch2.4-cp310-cp310-linux_x86_64.whl
#################### vLLM installation IMAGE ####################
......@@ -131,7 +207,7 @@ ADD . /vllm-workspace/
# install development dependencies (for testing)
RUN --mount=type=cache,target=/root/.cache/pip \
pip install -r requirements-dev.txt
python3 -m pip install -r requirements-dev.txt
# doc requires source code
# we hide them inside `test_docs/` , so that this source code
......@@ -148,7 +224,7 @@ FROM vllm-base AS vllm-openai
# install additional dependencies for openai api server
RUN --mount=type=cache,target=/root/.cache/pip \
pip install accelerate hf_transfer modelscope
pip install accelerate hf_transfer 'modelscope!=1.15.0'
ENV VLLM_USAGE_SOURCE production-docker-image
......
......@@ -2,13 +2,20 @@
FROM ubuntu:22.04 AS cpu-test-1
RUN apt-get update -y \
&& apt-get install -y git wget vim numactl gcc-12 g++-12 python3 python3-pip libtcmalloc-minimal4 \
RUN apt-get update -y \
&& apt-get install -y curl git wget vim numactl gcc-12 g++-12 python3 python3-pip libtcmalloc-minimal4 libnuma-dev \
&& update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-12 10 --slave /usr/bin/g++ g++ /usr/bin/g++-12
RUN echo 'export LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libtcmalloc_minimal.so.4:$LD_PRELOAD' >> ~/.bashrc
# https://intel.github.io/intel-extension-for-pytorch/cpu/latest/tutorials/performance_tuning/tuning_guide.html
# intel-openmp provides additional performance improvement vs. openmp
# tcmalloc provides better memory allocation efficiency, e.g, holding memory in caches to speed up access of commonly-used objects.
RUN pip install intel-openmp
RUN pip install https://intel-extension-for-pytorch.s3.amazonaws.com/ipex_dev/cpu/intel_extension_for_pytorch-2.3.100%2Bgit0eb3473-cp310-cp310-linux_x86_64.whl
ENV LD_PRELOAD="/usr/lib/x86_64-linux-gnu/libtcmalloc_minimal.so.4:/usr/local/lib/libiomp5.so:$LD_PRELOAD"
RUN echo 'ulimit -c 0' >> ~/.bashrc
RUN pip install https://intel-extension-for-pytorch.s3.amazonaws.com/ipex_dev/cpu/intel_extension_for_pytorch-2.4.0%2Bgitfbaa4bc-cp310-cp310-linux_x86_64.whl
RUN pip install --upgrade pip \
&& pip install wheel packaging ninja "setuptools>=49.4.0" numpy
......@@ -21,10 +28,14 @@ WORKDIR /workspace/vllm
RUN pip install -v -r requirements-cpu.txt --extra-index-url https://download.pytorch.org/whl/cpu
# Support for building with non-AVX512 vLLM: docker build --build-arg VLLM_CPU_DISABLE_AVX512="true" ...
ARG VLLM_CPU_DISABLE_AVX512
ENV VLLM_CPU_DISABLE_AVX512=${VLLM_CPU_DISABLE_AVX512}
RUN VLLM_TARGET_DEVICE=cpu python3 setup.py install
WORKDIR /workspace/
RUN ln -s /workspace/vllm/tests && ln -s /workspace/vllm/examples && ln -s /workspace/vllm/benchmarks
CMD ["/bin/bash"]
ENTRYPOINT ["python3", "-m", "vllm.entrypoints.openai.api_server"]
# The vLLM Dockerfile is used to construct vLLM image that can be directly used
# to run the OpenAI compatible server.
FROM ubuntu:22.04 AS dev
RUN apt-get update -y && \
apt-get install -y python3-pip git
WORKDIR /workspace
# copy requirements
COPY requirements-build.txt /workspace/vllm/
COPY requirements-common.txt /workspace/vllm/
COPY requirements-openvino.txt /workspace/vllm/
COPY vllm/ /workspace/vllm/vllm
COPY csrc/core /workspace/vllm/csrc/core
COPY cmake/utils.cmake /workspace/vllm/cmake/
COPY CMakeLists.txt /workspace/vllm/
COPY setup.py /workspace/vllm/
# install build requirements
RUN PIP_EXTRA_INDEX_URL="https://download.pytorch.org/whl/cpu" python3 -m pip install -r /workspace/vllm/requirements-build.txt
# build vLLM with OpenVINO backend
RUN PIP_EXTRA_INDEX_URL="https://download.pytorch.org/whl/cpu https://storage.openvinotoolkit.org/simple/wheels/pre-release" VLLM_TARGET_DEVICE="openvino" python3 -m pip install /workspace/vllm/
COPY examples/ /workspace/vllm/examples
COPY benchmarks/ /workspace/vllm/benchmarks
CMD ["/bin/bash"]
FROM mambaorg/micromamba
ARG MAMBA_DOCKERFILE_ACTIVATE=1
USER root
RUN apt-get update -y && apt-get install -y git wget vim numactl gcc-12 g++-12 protobuf-compiler libprotobuf-dev && update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-12 10 --slave /usr/bin/g++ g++ /usr/bin/g++-12
# Some packages in requirements-cpu are installed here
# IBM provides optimized packages for ppc64le processors in the open-ce project for mamba
# Currently these may not be available for venv or pip directly
RUN micromamba install -y -n base -c https://ftp.osuosl.org/pub/open-ce/1.11.0-p10/ -c defaults python=3.10 pytorch-cpu=2.1.2 torchvision-cpu=0.16.2 && micromamba clean --all --yes
COPY ./ /workspace/vllm
WORKDIR /workspace/vllm
# These packages will be in rocketce eventually
RUN pip install -v -r requirements-cpu.txt --prefer-binary --extra-index-url https://repo.fury.io/mgiessing
RUN VLLM_TARGET_DEVICE=cpu python3 setup.py install
WORKDIR /vllm-workspace
ENTRYPOINT ["/opt/conda/bin/python3", "-m", "vllm.entrypoints.openai.api_server"]
# default base image
ARG BASE_IMAGE="rocm/pytorch:rocm6.0_ubuntu20.04_py3.9_pytorch_2.1.1"
FROM $BASE_IMAGE
ARG BASE_IMAGE="rocm/pytorch:rocm6.0_ubuntu20.04_py3.9_pytorch_2.1.1"
RUN echo "Base image is $BASE_IMAGE"
# BASE_IMAGE for ROCm_5.7: "rocm/pytorch:rocm5.7_ubuntu22.04_py3.10_pytorch_2.0.1"
# BASE_IMAGE for ROCm_6.0: "rocm/pytorch:rocm6.0_ubuntu20.04_py3.9_pytorch_2.1.1"
# Default ROCm 6.1 base image
ARG BASE_IMAGE="rocm/pytorch:rocm6.1.2_ubuntu20.04_py3.9_pytorch_staging"
# Default ROCm ARCHes to build vLLM for.
ARG PYTORCH_ROCM_ARCH="gfx908;gfx90a;gfx942;gfx1100"
# Whether to install CK-based flash-attention
# If 0, will not install flash-attention
ARG BUILD_FA="1"
# If `TRY_FA_WHEEL=1`, we will try installing flash-attention from `FA_WHEEL_URL`
# If this succeeds, we use the downloaded wheel and skip building flash-attention.
# Otherwise, ROCm flash-attention from `FA_BRANCH` will be built for the
# architectures specified in `FA_GFX_ARCHS`
ARG TRY_FA_WHEEL="1"
ARG FA_WHEEL_URL="https://github.com/ROCm/flash-attention/releases/download/v2.5.9post1-cktile-vllm/flash_attn-2.5.9.post1-cp39-cp39-linux_x86_64.whl"
ARG FA_GFX_ARCHS="gfx90a;gfx942"
RUN echo "FA_GFX_ARCHS is $FA_GFX_ARCHS"
ARG FA_BRANCH="23a2b1c2"
ARG FA_BRANCH="ae7928c"
RUN echo "FA_BRANCH is $FA_BRANCH"
# Whether to build triton on rocm
ARG BUILD_TRITON="1"
ARG TRITON_BRANCH="e0fc12c"
# whether to build flash-attention
# if 0, will not build flash attention
# this is useful for gfx target where flash-attention is not supported
# In that case, we need to use the python reference attention implementation in vllm
ARG BUILD_FA="1"
### Base image build stage
FROM $BASE_IMAGE AS base
# whether to build triton on rocm
ARG BUILD_TRITON="1"
# Import arg(s) defined before this build stage
ARG PYTORCH_ROCM_ARCH
# Install some basic utilities
RUN apt-get update && apt-get install python3 python3-pip -y
# Install some basic utilities
RUN apt-get update && apt-get install -y \
curl \
ca-certificates \
......@@ -40,76 +38,144 @@ RUN apt-get update && apt-get install -y \
build-essential \
wget \
unzip \
nvidia-cuda-toolkit \
tmux \
ccache \
&& rm -rf /var/lib/apt/lists/*
### Mount Point ###
# When launching the container, mount the code directory to /app
# When launching the container, mount the code directory to /vllm-workspace
ARG APP_MOUNT=/vllm-workspace
VOLUME [ ${APP_MOUNT} ]
WORKDIR ${APP_MOUNT}
RUN python3 -m pip install --upgrade pip
RUN python3 -m pip install --no-cache-dir fastapi ninja tokenizers pandas
# Remove sccache so it doesn't interfere with ccache
# TODO: implement sccache support across components
RUN apt-get purge -y sccache; python3 -m pip uninstall -y sccache; rm -f "$(which sccache)"
# Install torch == 2.5.0 on ROCm
RUN case "$(ls /opt | grep -Po 'rocm-[0-9]\.[0-9]')" in \
*"rocm-6.1"*) \
python3 -m pip uninstall -y torch torchvision \
&& python3 -m pip install --no-cache-dir --pre \
torch==2.5.0.dev20240726 \
torchvision==0.20.0.dev20240726 \
--index-url https://download.pytorch.org/whl/nightly/rocm6.1;; \
*) ;; esac
ENV LLVM_SYMBOLIZER_PATH=/opt/rocm/llvm/bin/llvm-symbolizer
ENV PATH=$PATH:/opt/rocm/bin:/libtorch/bin:
ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/rocm/lib/:/libtorch/lib:
ENV CPLUS_INCLUDE_PATH=$CPLUS_INCLUDE_PATH:/libtorch/include:/libtorch/include/torch/csrc/api/include/:/opt/rocm/include/:
# Install ROCm flash-attention
RUN if [ "$BUILD_FA" = "1" ]; then \
mkdir libs \
&& cd libs \
&& git clone https://github.com/ROCm/flash-attention.git \
&& cd flash-attention \
&& git checkout ${FA_BRANCH} \
&& git submodule update --init \
&& export GPU_ARCHS=${FA_GFX_ARCHS} \
&& if [ "$BASE_IMAGE" = "rocm/pytorch:rocm5.7_ubuntu22.04_py3.10_pytorch_2.0.1" ]; then \
patch /opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/utils/hipify/hipify_python.py hipify_patch.patch; fi \
&& python3 setup.py install \
&& cd ..; \
ENV PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH}
ENV CCACHE_DIR=/root/.cache/ccache
### AMD-SMI build stage
FROM base AS build_amdsmi
# Build amdsmi wheel always
RUN cd /opt/rocm/share/amd_smi \
&& python3 -m pip wheel . --wheel-dir=/install
### Flash-Attention wheel build stage
FROM base AS build_fa
ARG BUILD_FA
ARG TRY_FA_WHEEL
ARG FA_WHEEL_URL
ARG FA_GFX_ARCHS
ARG FA_BRANCH
# Build ROCm flash-attention wheel if `BUILD_FA = 1`
RUN --mount=type=cache,target=${CCACHE_DIR} \
if [ "$BUILD_FA" = "1" ]; then \
if [ "${TRY_FA_WHEEL}" = "1" ] && python3 -m pip install "${FA_WHEEL_URL}"; then \
# If a suitable wheel exists, we download it instead of building FA
mkdir -p /install && wget -N "${FA_WHEEL_URL}" -P /install; \
else \
mkdir -p libs \
&& cd libs \
&& git clone https://github.com/ROCm/flash-attention.git \
&& cd flash-attention \
&& git checkout "${FA_BRANCH}" \
&& git submodule update --init \
&& GPU_ARCHS="${FA_GFX_ARCHS}" python3 setup.py bdist_wheel --dist-dir=/install; \
fi; \
# Create an empty directory otherwise as later build stages expect one
else mkdir -p /install; \
fi
# Error related to odd state for numpy 1.20.3 where there is no METADATA etc, but an extra LICENSES_bundled.txt.
# Manually removed it so that later steps of numpy upgrade can continue
RUN if [ "$BASE_IMAGE" = "rocm/pytorch:rocm6.0_ubuntu20.04_py3.9_pytorch_2.1.1" ]; then \
rm -rf /opt/conda/envs/py_3.9/lib/python3.9/site-packages/numpy-1.20.3.dist-info/; fi
# build triton
RUN if [ "$BUILD_TRITON" = "1" ]; then \
### Triton wheel build stage
FROM base AS build_triton
ARG BUILD_TRITON
ARG TRITON_BRANCH
# Build triton wheel if `BUILD_TRITON = 1`
RUN --mount=type=cache,target=${CCACHE_DIR} \
if [ "$BUILD_TRITON" = "1" ]; then \
mkdir -p libs \
&& cd libs \
&& pip uninstall -y triton \
&& git clone https://github.com/ROCm/triton.git \
&& cd triton/python \
&& pip3 install . \
&& cd ../..; \
&& git clone https://github.com/OpenAI/triton.git \
&& cd triton \
&& git checkout "${TRITON_BRANCH}" \
&& cd python \
&& python3 setup.py bdist_wheel --dist-dir=/install; \
# Create an empty directory otherwise as later build stages expect one
else mkdir -p /install; \
fi
WORKDIR /vllm-workspace
### Final vLLM build stage
FROM base AS final
# Import the vLLM development directory from the build context
COPY . .
#RUN python3 -m pip install pynvml # to be removed eventually
RUN python3 -m pip install --upgrade pip numba
# Package upgrades for useful functionality or to avoid dependency issues
RUN --mount=type=cache,target=/root/.cache/pip \
python3 -m pip install --upgrade numba scipy huggingface-hub[cli]
# make sure punica kernels are built (for LoRA)
ENV VLLM_INSTALL_PUNICA_KERNELS=1
# Workaround for ray >= 2.10.0
ENV RAY_EXPERIMENTAL_NOSET_ROCR_VISIBLE_DEVICES=1
# Silences the HF Tokenizers warning
ENV TOKENIZERS_PARALLELISM=false
RUN --mount=type=cache,target=${CCACHE_DIR} \
--mount=type=cache,target=/root/.cache/pip \
python3 -m pip install -Ur requirements-rocm.txt \
&& case "$(ls /opt | grep -Po 'rocm-[0-9]\.[0-9]')" in \
*"rocm-6.1"*) \
# Bring in upgrades to HIP graph earlier than ROCm 6.2 for vLLM
wget -N https://github.com/ROCm/vllm/raw/fa78403/rocm_patch/libamdhip64.so.6 -P /opt/rocm/lib \
# Prevent interference if torch bundles its own HIP runtime
&& rm -f "$(python3 -c 'import torch; print(torch.__path__[0])')"/lib/libamdhip64.so* || true;; \
*) ;; esac \
&& python3 setup.py clean --all \
&& python3 setup.py develop
# Copy amdsmi wheel into final image
RUN --mount=type=bind,from=build_amdsmi,src=/install,target=/install \
mkdir -p libs \
&& cp /install/*.whl libs \
# Preemptively uninstall to avoid same-version no-installs
&& python3 -m pip uninstall -y amdsmi;
ENV VLLM_NCCL_SO_PATH=/opt/rocm/lib/librccl.so
# Copy triton wheel(s) into final image if they were built
RUN --mount=type=bind,from=build_triton,src=/install,target=/install \
mkdir -p libs \
&& if ls /install/*.whl; then \
cp /install/*.whl libs \
# Preemptively uninstall to avoid same-version no-installs
&& python3 -m pip uninstall -y triton; fi
RUN --mount=type=cache,target=/root/.cache/pip \
pip install -U -r requirements-rocm.txt \
&& patch /opt/rocm/include/hip/amd_detail/amd_hip_bf16.h ./rocm_patch/rocm_bf16.patch \
&& python3 setup.py install \
&& cp build/lib.linux-x86_64-cpython-39/vllm/_C.abi3.so vllm/ \
&& cp build/lib.linux-x86_64-cpython-39/vllm/_punica_C.abi3.so vllm/ \
&& cp build/lib.linux-x86_64-cpython-39/vllm/_moe_C.abi3.so vllm/ \
&& cd ..
# Copy flash-attn wheel(s) into final image if they were built
RUN --mount=type=bind,from=build_fa,src=/install,target=/install \
mkdir -p libs \
&& if ls /install/*.whl; then \
cp /install/*.whl libs \
# Preemptively uninstall to avoid same-version no-installs
&& python3 -m pip uninstall -y flash-attn; fi
# Install wheels that were built to the final image
RUN --mount=type=cache,target=/root/.cache/pip \
if ls libs/*.whl; then \
python3 -m pip install libs/*.whl; fi
CMD ["/bin/bash"]
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