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chore: bump v0.3.6.post3 (#2259)

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This commit is contained in:
Yineng Zhang
2024-11-30 01:41:16 +08:00
committed by GitHub
parent afe1e46586
commit fae4e5e99a
8 changed files with 60 additions and 40 deletions
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28
Makefile
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@@ -1,4 +1,4 @@
.PHONY: check-deps install-deps format
.PHONY: check-deps install-deps format update
check-deps:
@command -v isort >/dev/null 2>&1 || (echo "Installing isort..." && pip install isort)
@@ -10,3 +10,29 @@ install-deps:
format: check-deps
@echo "Formatting modified Python files..."
git diff --name-only --diff-filter=M | grep '\.py$$' | xargs -I {} sh -c 'isort {} && black {}'
FILES_TO_UPDATE = docker/Dockerfile.rocm \
python/pyproject.toml \
python/sglang/version.py \
docs/developer/setup_github_runner.md \
docs/start/install.md
update:
@if [ -z "$(filter-out $@,$(MAKECMDGOALS))" ]; then \
echo "Version required. Usage: make update <new_version>"; \
exit 1; \
fi
@OLD_VERSION=$$(grep "version" python/sglang/version.py | cut -d '"' -f2); \
NEW_VERSION=$(filter-out $@,$(MAKECMDGOALS)); \
echo "Updating version from $$OLD_VERSION to $$NEW_VERSION"; \
for file in $(FILES_TO_UPDATE); do \
if [ "$(shell uname)" = "Darwin" ]; then \
sed -i '' -e "s/$$OLD_VERSION/$$NEW_VERSION/g" $$file; \
else \
sed -i -e "s/$$OLD_VERSION/$$NEW_VERSION/g" $$file; \
fi \
done; \
echo "Version update complete"
%:
@:

37
docker/Dockerfile
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@@ -23,31 +23,32 @@ RUN pip3 install datamodel_code_generator
WORKDIR /sgl-workspace
ARG CUDA_VERSION
RUN python3 -m pip install --upgrade pip setuptools wheel html5lib six \
&& git clone --depth=1 https://github.com/sgl-project/sglang.git \
&& cd sglang \
&& if [ "$BUILD_TYPE" = "srt" ]; then \
python3 -m pip --no-cache-dir install -e "python[srt]"; \
if [ "$CUDA_VERSION" = "12.1.1" ]; then \
python3 -m pip --no-cache-dir install -e "python[srt]" --find-links https://flashinfer.ai/whl/cu121/torch2.4/flashinfer/; \
elif [ "$CUDA_VERSION" = "12.4.1" ]; then \
python3 -m pip --no-cache-dir install -e "python[srt]" --find-links https://flashinfer.ai/whl/cu124/torch2.4/flashinfer/; \
elif [ "$CUDA_VERSION" = "11.8.0" ]; then \
python3 -m pip --no-cache-dir install -e "python[srt]" --find-links https://flashinfer.ai/whl/cu118/torch2.4/flashinfer/; \
else \
echo "Unsupported CUDA version: $CUDA_VERSION" && exit 1; \
fi; \
else \
python3 -m pip --no-cache-dir install -e "python[all]"; \
if [ "$CUDA_VERSION" = "12.1.1" ]; then \
python3 -m pip --no-cache-dir install -e "python[all]" --find-links https://flashinfer.ai/whl/cu121/torch2.4/flashinfer/; \
elif [ "$CUDA_VERSION" = "12.4.1" ]; then \
python3 -m pip --no-cache-dir install -e "python[all]" --find-links https://flashinfer.ai/whl/cu124/torch2.4/flashinfer/; \
elif [ "$CUDA_VERSION" = "11.8.0" ]; then \
python3 -m pip --no-cache-dir install -e "python[all]" --find-links https://flashinfer.ai/whl/cu118/torch2.4/flashinfer/; \
else \
echo "Unsupported CUDA version: $CUDA_VERSION" && exit 1; \
fi; \
fi
ARG CUDA_VERSION
RUN if [ "$CUDA_VERSION" = "12.1.1" ]; then \
export CUDA_IDENTIFIER=cu121 && \
python3 -m pip --no-cache-dir install flashinfer -i https://flashinfer.ai/whl/cu121/torch2.4/; \
elif [ "$CUDA_VERSION" = "12.4.1" ]; then \
export CUDA_IDENTIFIER=cu124 && \
python3 -m pip --no-cache-dir install flashinfer -i https://flashinfer.ai/whl/cu124/torch2.4/; \
elif [ "$CUDA_VERSION" = "11.8.0" ]; then \
export CUDA_IDENTIFIER=cu118 && \
python3 -m pip install torch==2.4.0 --index-url https://download.pytorch.org/whl/cu118 && \
python3 -m pip --no-cache-dir install flashinfer -i https://flashinfer.ai/whl/cu118/torch2.4/; \
else \
echo "Unsupported CUDA version: $CUDA_VERSION" && exit 1; \
fi
RUN python3 -m pip cache purge
ENV DEBIAN_FRONTEND=interactive

2
docker/Dockerfile.rocm
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@@ -1,5 +1,5 @@
# Usage (to build SGLang ROCm docker image):
# docker build --build-arg SGL_BRANCH=v0.3.6.post2 -t v0.3.6.post2-rocm620 -f Dockerfile.rocm .
# docker build --build-arg SGL_BRANCH=v0.3.6.post3 -t v0.3.6.post3-rocm620 -f Dockerfile.rocm .
# default base image
ARG BASE_IMAGE="rocm/vllm-dev:20241022"

4
docs/developer/setup_github_runner.md
View File

@@ -11,9 +11,9 @@ docker pull nvidia/cuda:12.1.1-devel-ubuntu22.04
# Nvidia
docker run --shm-size 128g -it -v /tmp/huggingface:/hf_home --gpus all nvidia/cuda:12.1.1-devel-ubuntu22.04 /bin/bash
# AMD
docker run --rm --device=/dev/kfd --device=/dev/dri --group-add video --shm-size 128g -it -v /tmp/huggingface:/hf_home lmsysorg/sglang:v0.3.6.post2-rocm620 /bin/bash
docker run --rm --device=/dev/kfd --device=/dev/dri --group-add video --shm-size 128g -it -v /tmp/huggingface:/hf_home lmsysorg/sglang:v0.3.6.post3-rocm620 /bin/bash
# AMD just the last 2 GPUs
docker run --rm --device=/dev/kfd --device=/dev/dri/renderD176 --device=/dev/dri/renderD184 --group-add video --shm-size 128g -it -v /tmp/huggingface:/hf_home lmsysorg/sglang:v0.3.6.post2-rocm620 /bin/bash
docker run --rm --device=/dev/kfd --device=/dev/dri/renderD176 --device=/dev/dri/renderD184 --group-add video --shm-size 128g -it -v /tmp/huggingface:/hf_home lmsysorg/sglang:v0.3.6.post3-rocm620 /bin/bash
```
### Step 2: Configure the runner by `config.sh`

20
docs/start/install.md
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@@ -5,10 +5,7 @@ You can install SGLang using any of the methods below.
## Method 1: With pip
```
pip install --upgrade pip
pip install "sglang[all]"
# Install FlashInfer accelerated kernels (CUDA only for now)
pip install flashinfer -i https://flashinfer.ai/whl/cu121/torch2.4/
pip install "sglang[all]" --find-links https://flashinfer.ai/whl/cu121/torch2.4/flashinfer/
```
Note: Please check the [FlashInfer installation doc](https://docs.flashinfer.ai/installation.html) to install the proper version according to your PyTorch and CUDA versions.
@@ -16,14 +13,11 @@ Note: Please check the [FlashInfer installation doc](https://docs.flashinfer.ai/
## Method 2: From source
```
# Use the last release branch
git clone -b v0.3.6.post2 https://github.com/sgl-project/sglang.git
git clone -b v0.3.6.post3 https://github.com/sgl-project/sglang.git
cd sglang
pip install --upgrade pip
pip install -e "python[all]"
# Install FlashInfer accelerated kernels (CUDA only for now)
pip install flashinfer -i https://flashinfer.ai/whl/cu121/torch2.4/
pip install -e "python[all]" --find-links https://flashinfer.ai/whl/cu121/torch2.4/flashinfer/
```
Note: Please check the [FlashInfer installation doc](https://docs.flashinfer.ai/installation.html) to install the proper version according to your PyTorch and CUDA versions.
@@ -32,7 +26,7 @@ Note: To AMD ROCm system with Instinct/MI GPUs, do following instead:
```
# Use the last release branch
git clone -b v0.3.6.post2 https://github.com/sgl-project/sglang.git
git clone -b v0.3.6.post3 https://github.com/sgl-project/sglang.git
cd sglang
pip install --upgrade pip
@@ -57,7 +51,7 @@ docker run --gpus all \
Note: To AMD ROCm system with Instinct/MI GPUs, it is recommended to use `docker/Dockerfile.rocm` to build images, example and usage as below:
```bash
docker build --build-arg SGL_BRANCH=v0.3.6.post2 -t v0.3.6.post2-rocm620 -f Dockerfile.rocm .
docker build --build-arg SGL_BRANCH=v0.3.6.post3 -t v0.3.6.post3-rocm620 -f Dockerfile.rocm .
alias drun='docker run -it --rm --network=host --device=/dev/kfd --device=/dev/dri --ipc=host \
--shm-size 16G --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined \
@@ -66,11 +60,11 @@ alias drun='docker run -it --rm --network=host --device=/dev/kfd --device=/dev/d
drun -p 30000:30000 \
-v ~/.cache/huggingface:/root/.cache/huggingface \
--env "HF_TOKEN=<secret>" \
v0.3.6.post2-rocm620 \
v0.3.6.post3-rocm620 \
python3 -m sglang.launch_server --model-path meta-llama/Llama-3.1-8B-Instruct --host 0.0.0.0 --port 30000
# Till flashinfer backend available, --attention-backend triton --sampling-backend pytorch are set by default
drun v0.3.6.post2-rocm620 python3 -m sglang.bench_one_batch --batch-size 32 --input 1024 --output 128 --model amd/Meta-Llama-3.1-8B-Instruct-FP8-KV --tp 8 --quantization fp8
drun v0.3.6.post3-rocm620 python3 -m sglang.bench_one_batch --batch-size 32 --input 1024 --output 128 --model amd/Meta-Llama-3.1-8B-Instruct-FP8-KV --tp 8 --quantization fp8
```
## Method 4: Using docker compose

4
python/pyproject.toml
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@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
[project]
name = "sglang"
version = "0.3.6.post2"
version = "0.3.6.post3"
description = "SGLang is yet another fast serving framework for large language models and vision language models."
readme = "README.md"
requires-python = ">=3.8"
@@ -23,7 +23,7 @@ runtime_common = ["aiohttp", "decord", "fastapi",
"psutil", "pydantic", "python-multipart",
"pyzmq>=25.1.2", "torchao", "uvicorn", "uvloop",
"xgrammar>=0.1.4"]
srt = ["sglang[runtime_common]", "torch", "vllm>=0.6.3.post1", "cuda-python"]
srt = ["sglang[runtime_common]", "torch", "vllm>=0.6.3.post1", "cuda-python", "flashinfer>=0.1.6"]
# HIP (Heterogeneous-computing Interface for Portability) for AMD
# => base docker rocm/vllm-dev:20241022, not from public vllm whl

2
python/sglang/version.py
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@@ -1 +1 @@
__version__ = "0.3.6.post2"
__version__ = "0.3.6.post3"

3
scripts/ci_install_dependency.sh
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@@ -3,9 +3,8 @@ Install the dependency in CI.
"""
pip install --upgrade pip
pip install -e "python[all]"
pip install -e "python[all]" --find-links https://flashinfer.ai/whl/cu121/torch2.4/flashinfer/
pip install transformers==4.45.2 sentence_transformers accelerate peft
pip install flashinfer -i https://flashinfer.ai/whl/cu121/torch2.4/ --force-reinstall
# for compling eagle kernels
pip install cutex
# for compling xgrammar kernels