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Merge xgrammar from main
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Signed-off-by: Loc Huynh <[email protected]>
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JC1DA committed Dec 3, 2024
2 parents 4f2cea1 + 9323a31 commit 184b68b
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58 changes: 42 additions & 16 deletions .buildkite/nightly-benchmarks/benchmark-pipeline.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -9,8 +9,11 @@ steps:
- image: badouralix/curl-jq
command:
- sh .buildkite/nightly-benchmarks/scripts/wait-for-image.sh

- wait

- label: "A100"
# skip: "use this flag to conditionally skip the benchmark step, useful for PR testing"
agents:
queue: A100
plugins:
Expand Down Expand Up @@ -41,20 +44,43 @@ steps:
- name: devshm
emptyDir:
medium: Memory
# - label: "H100"
# agents:
# queue: H100
# plugins:
# - docker#v5.11.0:
# image: public.ecr.aws/q9t5s3a7/vllm-ci-test-repo:$BUILDKITE_COMMIT
# command:
# - bash
# - .buildkite/nightly-benchmarks/run-benchmarks-suite.sh
# mount-buildkite-agent: true
# propagate-environment: true
# ipc: host
# gpus: all
# environment:
# - VLLM_USAGE_SOURCE
# - HF_TOKEN

- label: "H200"
# skip: "use this flag to conditionally skip the benchmark step, useful for PR testing"
agents:
queue: H200
plugins:
- docker#v5.12.0:
image: public.ecr.aws/q9t5s3a7/vllm-ci-test-repo:$BUILDKITE_COMMIT
command:
- bash
- .buildkite/nightly-benchmarks/scripts/run-performance-benchmarks.sh
mount-buildkite-agent: true
propagate-environment: true
ipc: host
gpus: 4,5,6,7
volumes:
- /data/benchmark-hf-cache:/root/.cache/huggingface
environment:
- VLLM_USAGE_SOURCE
- HF_TOKEN

- label: "H100"
# skip: "use this flag to conditionally skip the benchmark step, useful for PR testing"
agents:
queue: H100
plugins:
- docker#v5.12.0:
image: public.ecr.aws/q9t5s3a7/vllm-ci-test-repo:$BUILDKITE_COMMIT
command:
- bash
- .buildkite/nightly-benchmarks/scripts/run-performance-benchmarks.sh
mount-buildkite-agent: true
propagate-environment: true
ipc: host
gpus: all # see CUDA_VISIBLE_DEVICES for actual GPUs used
volumes:
- /data/benchmark-hf-cache:/root/.cache/huggingface
environment:
- VLLM_USAGE_SOURCE
- HF_TOKEN
Original file line number Diff line number Diff line change
Expand Up @@ -157,6 +157,18 @@ def results_to_json(latency, throughput, serving):
throughput_results,
serving_results)

for df in [latency_results, serving_results, throughput_results]:
if df.empty:
continue

# Sort all dataframes by their respective "Test name" columns
df.sort_values(by="Test name", inplace=True)

# The GPUs sometimes come in format of "GPUTYPE\nGPUTYPE\n...",
# we want to turn it into "8xGPUTYPE"
df["GPU"] = df["GPU"].apply(
lambda x: f"{len(x.split('\n'))}x{x.split('\n')[0]}")

# get markdown tables
latency_md_table = tabulate(latency_results,
headers='keys',
Expand Down
Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,7 @@

# Do not set -e, as the mixtral 8x22B model tends to crash occasionally
# and we still want to see other benchmarking results even when mixtral crashes.
set -x
set -o pipefail

check_gpus() {
Expand Down Expand Up @@ -85,11 +86,7 @@ kill_gpu_processes() {

ps -aux
lsof -t -i:8000 | xargs -r kill -9
pkill -f pt_main_thread
# this line doesn't work now
# ps aux | grep python | grep openai | awk '{print $2}' | xargs -r kill -9
pkill -f python3
pkill -f /usr/bin/python3
pgrep python3 | xargs -r kill -9


# wait until GPU memory usage smaller than 1GB
Expand Down Expand Up @@ -289,7 +286,7 @@ run_serving_tests() {
# run the server
echo "Running test case $test_name"
echo "Server command: $server_command"
eval "$server_command" &
bash -c "$server_command" &
server_pid=$!

# wait until the server is alive
Expand Down Expand Up @@ -322,7 +319,7 @@ run_serving_tests() {
echo "Running test case $test_name with qps $qps"
echo "Client command: $client_command"

eval "$client_command"
bash -c "$client_command"

# record the benchmarking commands
jq_output=$(jq -n \
Expand Down
21 changes: 8 additions & 13 deletions .buildkite/release-pipeline.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -6,28 +6,23 @@ steps:
- "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 vllm-ci:build-image --target build --progress plain ."
- "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'"
# rename the files to change linux -> manylinux1
- "for f in artifacts/dist/*.whl; do mv -- \"$$f\" \"$${f/linux/manylinux1}\"; done"
- "mv artifacts/dist/$(ls artifacts/dist) artifacts/dist/vllm-1.0.0.dev-cp38-abi3-manylinux1_x86_64.whl"
- "aws s3 cp artifacts/dist/vllm-1.0.0.dev-cp38-abi3-manylinux1_x86_64.whl s3://vllm-wheels/$BUILDKITE_COMMIT/vllm-1.0.0.dev-cp38-abi3-manylinux1_x86_64.whl"
- "aws s3 cp artifacts/dist/vllm-1.0.0.dev-cp38-abi3-manylinux1_x86_64.whl s3://vllm-wheels/nightly/vllm-1.0.0.dev-cp38-abi3-manylinux1_x86_64.whl"
- "bash .buildkite/upload-wheels.sh"
env:
DOCKER_BUILDKIT: "1"

- block: "Build CUDA 11.8 wheel"
key: block-build-cu118-wheel

# Note(simon): We can always build CUDA 11.8 wheel to ensure the build is working.
# However, this block can be uncommented to save some compute hours.
# - block: "Build CUDA 11.8 wheel"
# key: block-build-cu118-wheel

- label: "Build wheel - CUDA 11.8"
depends_on: block-build-cu118-wheel
# depends_on: block-build-cu118-wheel
agents:
queue: cpu_queue
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=11.8.0 --tag vllm-ci:build-image --target build --progress plain ."
- "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'"
# rename the files to change linux -> manylinux1
- "for f in artifacts/dist/*.whl; do mv -- \"$$f\" \"$${f/linux/manylinux1}\"; done"
- "aws s3 cp --recursive artifacts/dist s3://vllm-wheels/$BUILDKITE_COMMIT/"
- "aws s3 cp --recursive artifacts/dist s3://vllm-wheels/nightly/"
- "bash .buildkite/upload-wheels.sh"
env:
DOCKER_BUILDKIT: "1"
1 change: 0 additions & 1 deletion .buildkite/run-amd-test.sh
Original file line number Diff line number Diff line change
Expand Up @@ -85,7 +85,6 @@ if [[ $commands == *" kernels "* ]]; then
--ignore=kernels/test_encoder_decoder_attn.py \
--ignore=kernels/test_flash_attn.py \
--ignore=kernels/test_flashinfer.py \
--ignore=kernels/test_gguf.py \
--ignore=kernels/test_int8_quant.py \
--ignore=kernels/test_machete_gemm.py \
--ignore=kernels/test_mamba_ssm.py \
Expand Down
43 changes: 3 additions & 40 deletions .buildkite/run-cpu-test-ppc64le.sh
Original file line number Diff line number Diff line change
Expand Up @@ -4,48 +4,11 @@
# It serves a sanity check for compilation and basic model usage.
set -ex

# Try building the docker image
docker build -t cpu-test -f Dockerfile.ppc64le .

# Setup cleanup
remove_docker_container() { docker rm -f cpu-test || true; }
remove_docker_container() { docker rm -f cpu-test || true; docker system prune -f; }
trap remove_docker_container EXIT
remove_docker_container

# Run the image, setting --shm-size=4g for tensor parallel.
source /etc/environment
#docker run -itd --entrypoint /bin/bash -v ~/.cache/huggingface:/root/.cache/huggingface --privileged=true --network host -e HF_TOKEN --env VLLM_CPU_KVCACHE_SPACE=4 --shm-size=4g --name cpu-test cpu-test
docker run -itd --entrypoint /bin/bash -v ~/.cache/huggingface:/root/.cache/huggingface --privileged=true --network host -e HF_TOKEN="$HF_TOKEN" --name cpu-test cpu-test

function cpu_tests() {
# Run basic model test
docker exec cpu-test bash -c "
set -e
pip install pytest pytest-asyncio \
decord einops librosa peft Pillow sentence-transformers soundfile \
transformers_stream_generator matplotlib datamodel_code_generator
pip install torchvision --index-url https://download.pytorch.org/whl/cpu
# Embedding models are not supported for CPU yet
# pytest -v -s tests/models/embedding/language
pytest -v -s tests/models/encoder_decoder/language
pytest -v -s tests/models/decoder_only/language/test_models.py
pytest -v -s tests/models/decoder_only/audio_language -m cpu_model
pytest -v -s tests/models/decoder_only/vision_language -m cpu_model"

# online inference
docker exec cpu-test bash -c "
set -e
python3 -m vllm.entrypoints.openai.api_server --model facebook/opt-125m &
timeout 600 bash -c 'until curl localhost:8000/v1/models; do sleep 1; done' || exit 1
python3 benchmarks/benchmark_serving.py \
--backend vllm \
--dataset-name random \
--model facebook/opt-125m \
--num-prompts 20 \
--endpoint /v1/completions \
--tokenizer facebook/opt-125m"
}
# Try building the docker image
docker build -t cpu-test -f Dockerfile.ppc64le .

# All of CPU tests are expected to be finished less than 25 mins.
export -f cpu_tests
timeout 25m bash -c "cpu_tests"
48 changes: 30 additions & 18 deletions .buildkite/run-cpu-test.sh
Original file line number Diff line number Diff line change
Expand Up @@ -4,59 +4,71 @@
# It serves a sanity check for compilation and basic model usage.
set -ex

# allow to bind to different cores
CORE_RANGE=${CORE_RANGE:-48-95}
NUMA_NODE=${NUMA_NODE:-1}

# Try building the docker image
numactl -C 48-95 -N 1 docker build -t cpu-test -f Dockerfile.cpu .
numactl -C 48-95 -N 1 docker build --build-arg VLLM_CPU_DISABLE_AVX512="true" -t cpu-test-avx2 -f Dockerfile.cpu .
numactl -C "$CORE_RANGE" -N "$NUMA_NODE" docker build -t cpu-test -f Dockerfile.cpu .
numactl -C "$CORE_RANGE" -N "$NUMA_NODE" docker build --build-arg VLLM_CPU_DISABLE_AVX512="true" -t cpu-test-avx2 -f Dockerfile.cpu .

# Setup cleanup
remove_docker_container() { docker rm -f cpu-test cpu-test-avx2 || true; }
remove_docker_container() { docker rm -f cpu-test-"$NUMA_NODE" cpu-test-avx2-"$NUMA_NODE" || true; }
trap remove_docker_container EXIT
remove_docker_container

# Run the image, setting --shm-size=4g for tensor parallel.
docker run -itd --entrypoint /bin/bash -v ~/.cache/huggingface:/root/.cache/huggingface --cpuset-cpus=48-95 \
--cpuset-mems=1 --privileged=true --network host -e HF_TOKEN --env VLLM_CPU_KVCACHE_SPACE=4 --shm-size=4g --name cpu-test cpu-test
docker run -itd --entrypoint /bin/bash -v ~/.cache/huggingface:/root/.cache/huggingface --cpuset-cpus=48-95 \
--cpuset-mems=1 --privileged=true --network host -e HF_TOKEN --env VLLM_CPU_KVCACHE_SPACE=4 --shm-size=4g --name cpu-test-avx2 cpu-test-avx2
docker run -itd --entrypoint /bin/bash -v ~/.cache/huggingface:/root/.cache/huggingface --cpuset-cpus="$CORE_RANGE" \
--cpuset-mems="$NUMA_NODE" --privileged=true --network host -e HF_TOKEN --env VLLM_CPU_KVCACHE_SPACE=4 --shm-size=4g --name cpu-test-"$NUMA_NODE" cpu-test
docker run -itd --entrypoint /bin/bash -v ~/.cache/huggingface:/root/.cache/huggingface --cpuset-cpus="$CORE_RANGE" \
--cpuset-mems="$NUMA_NODE" --privileged=true --network host -e HF_TOKEN --env VLLM_CPU_KVCACHE_SPACE=4 --shm-size=4g --name cpu-test-avx2-"$NUMA_NODE" cpu-test-avx2

function cpu_tests() {
set -e
export NUMA_NODE=$2

# offline inference
docker exec cpu-test-avx2 bash -c "
docker exec cpu-test-avx2-"$NUMA_NODE" bash -c "
set -e
python3 examples/offline_inference.py"

# Run basic model test
docker exec cpu-test bash -c "
docker exec cpu-test-"$NUMA_NODE" bash -c "
set -e
pip install pytest pytest-asyncio \
decord einops librosa peft Pillow sentence-transformers soundfile \
transformers_stream_generator matplotlib datamodel_code_generator
pip install torchvision --index-url https://download.pytorch.org/whl/cpu
# Embedding models are not supported for CPU yet
# pytest -v -s tests/models/embedding/language
pytest -v -s tests/models/encoder_decoder/language
pytest -v -s tests/models/decoder_only/language/test_models.py
pytest -v -s tests/models/decoder_only/language -m cpu_model
pytest -v -s tests/models/embedding/language -m cpu_model
pytest -v -s tests/models/encoder_decoder/language -m cpu_model
pytest -v -s tests/models/decoder_only/audio_language -m cpu_model
pytest -v -s tests/models/decoder_only/vision_language -m cpu_model"

# Run compressed-tensor test
docker exec cpu-test bash -c "
docker exec cpu-test-"$NUMA_NODE" bash -c "
set -e
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_dynamic_per_token"

# Run AWQ test
docker exec cpu-test bash -c "
docker exec cpu-test-"$NUMA_NODE" bash -c "
set -e
pytest -s -v \
tests/quantization/test_ipex_quant.py"

# Run chunked-prefill and prefix-cache test
docker exec cpu-test-"$NUMA_NODE" bash -c "
set -e
pytest -s -v -k cpu_model \
tests/basic_correctness/test_chunked_prefill.py"

# online inference
docker exec cpu-test bash -c "
docker exec cpu-test-"$NUMA_NODE" bash -c "
set -e
export VLLM_CPU_KVCACHE_SPACE=10
export VLLM_CPU_OMP_THREADS_BIND=48-92
export VLLM_CPU_OMP_THREADS_BIND=$1
python3 -m vllm.entrypoints.openai.api_server --model facebook/opt-125m --dtype half &
timeout 600 bash -c 'until curl localhost:8000/v1/models; do sleep 1; done' || exit 1
python3 benchmarks/benchmark_serving.py \
Expand All @@ -70,4 +82,4 @@ function cpu_tests() {

# All of CPU tests are expected to be finished less than 25 mins.
export -f cpu_tests
timeout 25m bash -c "cpu_tests"
timeout 30m bash -c "cpu_tests $CORE_RANGE $NUMA_NODE"
2 changes: 1 addition & 1 deletion .buildkite/run-hpu-test.sh
Original file line number Diff line number Diff line change
Expand Up @@ -13,4 +13,4 @@ trap remove_docker_container EXIT
remove_docker_container

# Run the image and launch offline inference
docker run --runtime=habana --name=hpu-test --network=host -e VLLM_SKIP_WARMUP=true --entrypoint="" hpu-test-env python3 examples/offline_inference.py
docker run --runtime=habana --name=hpu-test --network=host -e HABANA_VISIBLE_DEVICES=all -e VLLM_SKIP_WARMUP=true --entrypoint="" hpu-test-env python3 examples/offline_inference.py
6 changes: 4 additions & 2 deletions .buildkite/run-xpu-test.sh
Original file line number Diff line number Diff line change
Expand Up @@ -12,5 +12,7 @@ remove_docker_container() { docker rm -f xpu-test || true; }
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 --entrypoint="" xpu-test python3 examples/offline_inference.py
# Run the image and test offline inference/tensor parallel
docker run -it -d --name xpu-test --device /dev/dri -v /dev/dri/by-path:/dev/dri/by-path xpu-test /bin/bash
docker exec xpu-test bash -c "python3 examples/offline_inference.py"
docker exec xpu-test bash -c "python3 examples/offline_inference_cli.py -tp 2"
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