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Commit 0384a5af authored by gaoqiong's avatar gaoqiong
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update v0.0.6

parent 54638dc2
# <div align="center"><strong>AutoAWQ_kernel</strong></div> # AutoAWQ Kernels
## 简介
AutoAWQ_kernel是一个从AutoAWQ分离出来的一个组件,以减少编译时间
## 安装
### 使用源码编译方式安装
#### 编译环境准备
下载光源的镜像,起dcoker
```
docker pull image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.1.0-centos7.6-dtk24.04-py310
# <Image ID>用上面拉取docker镜像的ID替换
# <Host Path>主机端路径
# <Container Path>容器映射路径
docker run -it --name baichuan --shm-size=1024G -v /opt/hyhal:/opt/hyhal:ro --device=/dev/kfd --device=/dev/dri/ --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --ulimit memlock=-1:-1 --ipc=host --network host --group-add video -v <Host Path>:<Container Path> <Image ID> /bin/bash
```
注:
1、docker启动 -v /opt/hyhal:/opt/hyhal 这个变量不能少
#### 源码编译安装
- 代码下载
根据不同的需求下载不同的分支
- 提供2种源码编译方式(进入AutoAWQ目录):
```
1. 源码编译安装
pip3 install e.
2. 编译成whl包安装
# 安装wheel
python3 setup.py bdist_wheel
cd dist && pip3 install autoawq*
```
AutoAWQ Kernels is a new package that is split up from the [main repository](https://github.com/casper-hansen/AutoAWQ) in order to avoid compilation times.
## Requirements
- Windows: Must use WSL2.
- NVIDIA:
- GPU: Must be compute capability 7.5 or higher.
- CUDA Toolkit: Must be 11.8 or higher.
- AMD:
- ROCm: Must be 5.6 or higher.
## Install
### Install from PyPi
The package is available on PyPi with CUDA 12.1.1 wheels:
```
pip install autoawq-kernels
```
### Install release wheels
For ROCm and other CUDA versions, you can use the wheels published at each [release](https://github.com/casper-hansen/AutoAWQ_kernels/releases/):
```
pip install https://github.com/casper-hansen/AutoAWQ_kernels/releases/download/v0.0.2/autoawq_kernels-0.0.2+rocm561-cp310-cp310-linux_x86_64.whl
```
### Build from source
You can also build from source:
```
git clone https://github.com/casper-hansen/AutoAWQ_kernels
cd AutoAWQ_kernels
pip install -e .
```
To build for ROCm, you need to first install the following packages `rocsparse-dev hipsparse-dev rocthrust-dev rocblas-dev hipblas-dev`.
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# <div align="center"><strong>AutoAWQ_kernel</strong></div>
## 简介
AutoAWQ_kernel是一个从AutoAWQ分离出来的一个组件,以减少编译时间
## 安装
### 使用源码编译方式安装
#### 编译环境准备
下载光源的镜像,起dcoker
```
docker pull image.sourcefind.cn:5000/dcu/admin/base/pytorch:2.1.0-centos7.6-dtk24.04-py310
# <Image ID>用上面拉取docker镜像的ID替换
# <Host Path>主机端路径
# <Container Path>容器映射路径
docker run -it --name baichuan --shm-size=1024G -v /opt/hyhal:/opt/hyhal:ro --device=/dev/kfd --device=/dev/dri/ --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --ulimit memlock=-1:-1 --ipc=host --network host --group-add video -v <Host Path>:<Container Path> <Image ID> /bin/bash
```
注:
1、docker启动 -v /opt/hyhal:/opt/hyhal 这个变量不能少
#### 源码编译安装
- 代码下载
根据不同的需求下载不同的分支
- 提供2种源码编译方式(进入AutoAWQ目录):
```
1. 源码编译安装
pip3 install e.
2. 编译成whl包安装
# 安装wheel
python3 setup.py bdist_wheel
cd dist && pip3 install autoawq*
```
# AutoAWQ Kernels
AutoAWQ Kernels is a new package that is split up from the [main repository](https://github.com/casper-hansen/AutoAWQ) in order to avoid compilation times.
## Requirements
- Windows: Must use WSL2.
- NVIDIA:
- GPU: Must be compute capability 7.5 or higher.
- CUDA Toolkit: Must be 11.8 or higher.
- AMD:
- ROCm: Must be 5.6 or higher.
## Install
### Install from PyPi
The package is available on PyPi with CUDA 12.1.1 wheels:
```
pip install autoawq-kernels
```
### Install release wheels
For ROCm and other CUDA versions, you can use the wheels published at each [release](https://github.com/casper-hansen/AutoAWQ_kernels/releases/):
```
pip install https://github.com/casper-hansen/AutoAWQ_kernels/releases/download/v0.0.2/autoawq_kernels-0.0.2+rocm561-cp310-cp310-linux_x86_64.whl
```
### Build from source
You can also build from source:
```
git clone https://github.com/casper-hansen/AutoAWQ_kernels
cd AutoAWQ_kernels
pip install -e .
```
To build for ROCm, you need to first install the following packages `rocsparse-dev hipsparse-dev rocthrust-dev rocblas-dev hipblas-dev`.
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