mirror of https://github.com/Jittor/Jittor
polish install
This commit is contained in:
parent
2476a471d4
commit
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56
README.cn.md
56
README.cn.md
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@ -76,18 +76,6 @@ for i,(x,y) in enumerate(get_data(n)):
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## 安装
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我们提供了Docker安装方式,免去您配置环境,Docker安装方法如下:
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```
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# CPU only
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docker run -it --network host jittor/jittor
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# CPU and CUDA
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docker run -it --network host jittor/jittor-cuda
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```
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关于Docker安装的详细教程,可以参考[Windows/Mac/Linux通过Docker安装计图](https://cg.cs.tsinghua.edu.cn/jittor/tutorial/2020-5-15-00-00-docker/)
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Jittor使用Python和C++编写。 它需要用于即时编译的编译器。当前,我们支持三种编译器:
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@ -96,6 +84,7 @@ Jittor使用Python和C++编写。 它需要用于即时编译的编译器。当
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- clang (>=8.0)
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* GPU 编译器(可选)
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- nvcc (>=10.0 for g++ 或者 >=10.2 for clang)
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* cudnn-dev (cudnn开发版)
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Jittor的环境要求如下:
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@ -109,12 +98,27 @@ Jittor的环境要求如下:
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Jittor 一共提供三种方式安装: pip安装, 一键脚本安装 和 手动安装.
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Jittor 一共提供三种方式安装: docker安装,pip安装, 和 手动安装.
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## Docker 安装
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我们提供了Docker安装方式,免去您配置环境,Docker安装方法如下:
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```
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# CPU only
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docker run -it --network host jittor/jittor
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# CPU and CUDA
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docker run -it --network host jittor/jittor-cuda
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```
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关于Docker安装的详细教程,可以参考[Windows/Mac/Linux通过Docker安装计图](https://cg.cs.tsinghua.edu.cn/jittor/tutorial/2020-5-15-00-00-docker/)
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## Pip 安装
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如果您没有准备好环境,欢迎使用我们提供的一键安装脚本, 如果您已经装好编译器和对应版本的Python,我们强烈推荐您使用这种方法
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如果您没有准备好环境,或者使用的不是Ubuntu操作系统, 推荐使用docker安装, 如果您已经装好编译器和对应版本的Python,我们强烈推荐您使用这种方法
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(如果无法访问github, 可以通过jittor主页下载):
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```bash
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@ -128,30 +132,6 @@ python3.7 -m jittor.test.test_example
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如果测试运行通过,恭喜你已经安装完成.
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jittor会自动在路径中寻找合适的编译器, 如果您希望手动指定编译器, 请使用环境变量 `cc_path` 和 `nvcc_path`(可选).
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## 一键脚本安装
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一键脚本安装会帮您安装好所需的编译器以及对应的Python版本.
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我们提供能快速安装最新版本Jittor的单行命令(Ubuntu> = 16.04):
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```bash
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# install with clang and cuda
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wget -O - https://raw.githubusercontent.com/Jittor/jittor/master/script/install.sh | with_clang=1 with_cuda=1 bash
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# install with clang
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wget -O - https://raw.githubusercontent.com/Jittor/jittor/master/script/install.sh | with_clang=1 bash
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# install with g++ and cuda
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wget -O - https://raw.githubusercontent.com/Jittor/jittor/master/script/install.sh | with_gcc=1 with_cuda=1 bash
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# install with g++
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wget -O - https://raw.githubusercontent.com/Jittor/jittor/master/script/install.sh | with_gcc=1 bash
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```
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执行后,脚本将显示一些需要导出的环境变量。
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如果将Jittor用于CPU计算,则强烈建议使用clang(> = 8.0)作为Jittor的后端编译器。 因为Jittor会用到其中一些定制的优化。
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## 手动安装
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51
README.md
51
README.md
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@ -76,17 +76,6 @@ We provide some jupyter notebooks to help you quick start with Jittor.
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## Install
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We provide a Docker installation method to save you from configuring the environment. The Docker installation method is as follows:
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```
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# CPU only
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docker run -it --network host jittor/jittor
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# CPU and CUDA
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docker run -it --network host jittor/jittor-cuda
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```
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Jittor is written in Python and C++. It requires a compiler for JIT compilation, Currently, we support four compilers:
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@ -95,6 +84,7 @@ Jittor is written in Python and C++. It requires a compiler for JIT compilation,
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* clang (>=8.0)
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* GPU compiler (optional)
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* nvcc (>=10.0 for g++ or >=10.2 for clang)
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* cudnn-dev
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@ -107,7 +97,21 @@ Jittor environment requirements:
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Note: Currently Jittor runs on the Windows operating system through WSL. For the installation method of WSL, please refer to [Microsoft official website](https://docs.microsoft.com/en-us/windows/wsl/install-win10). WSL does not yet support CUDA.
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Jittor offers three ways to install: pip, script or manual.
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Jittor offers three ways to install: docker, pip, or manual.
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## Docker Install
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We provide a Docker installation method to save you from configuring the environment. The Docker installation method is as follows:
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```
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# CPU only
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docker run -it --network host jittor/jittor
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# CPU and CUDA
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docker run -it --network host jittor/jittor-cuda
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```
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@ -123,29 +127,6 @@ python3.7 -m jittor.test.test_example
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```
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## single line script install
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We provide single line command for quick installation the latest version of Jittor(Ubuntu>=16.04):
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```bash
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# install with clang and cuda
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wget -O - https://raw.githubusercontent.com/Jittor/jittor/master/script/install.sh | with_clang=1 with_cuda=1 bash
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# install with clang
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wget -O - https://raw.githubusercontent.com/Jittor/jittor/master/script/install.sh | with_clang=1 bash
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# install with g++ and cuda
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wget -O - https://raw.githubusercontent.com/Jittor/jittor/master/script/install.sh | with_gcc=1 with_cuda=1 bash
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# install with g++
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wget -O - https://raw.githubusercontent.com/Jittor/jittor/master/script/install.sh | with_gcc=1 bash
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```
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After execution, the script will show some environment variables you need to export.
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If you use Jittor for CPU computing, we strongly recommend clang(>=8.0) as the back-end compiler of Jittor. Because some customized optimizations will be enabled.
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## manual install
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We will show how to install Jittor in Ubuntu 16.04 step by step, Other Linux distributions may have similar commands.
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@ -94,19 +94,6 @@ We provide some jupyter notebooks to help you quick start with Jittor.
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## 安装
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我们提供了Docker安装方式,免去您配置环境,Docker安装方法如下:
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We provide a Docker installation method to save you from configuring the environment. The Docker installation method is as follows:
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```
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# CPU only
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docker run -it --network host jittor/jittor
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# CPU and CUDA
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docker run -it --network host jittor/jittor-cuda
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```
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关于Docker安装的详细教程,可以参考[Windows/Mac/Linux通过Docker安装计图](https://cg.cs.tsinghua.edu.cn/jittor/tutorial/2020-5-15-00-00-docker/)
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Jittor is written in Python and C++. It requires a compiler for JIT compilation, Currently, we support four compilers:
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Jittor使用Python和C++编写。 它需要用于即时编译的编译器。当前,我们支持三种编译器:
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@ -119,8 +106,10 @@ Jittor使用Python和C++编写。 它需要用于即时编译的编译器。当
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- clang (>=8.0)
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* GPU compiler (optional)
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* nvcc (>=10.0 for g++ or >=10.2 for clang)
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* cudnn-dev
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* GPU 编译器(可选)
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- nvcc (>=10.0 for g++ 或者 >=10.2 for clang)
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* cudnn-dev (cudnn开发版)
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Jittor的环境要求如下:
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@ -138,15 +127,32 @@ Jittor environment requirements:
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Note: Currently Jittor runs on the Windows operating system through WSL. For the installation method of WSL, please refer to [Microsoft official website](https://docs.microsoft.com/en-us/windows/wsl/install-win10). WSL does not yet support CUDA.
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Jittor offers three ways to install: pip, script or manual.
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Jittor offers three ways to install: docker, pip, or manual.
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Jittor 一共提供三种方式安装: pip安装, 一键脚本安装 和 手动安装.
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Jittor 一共提供三种方式安装: docker安装,pip安装, 和 手动安装.
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## Docker Install
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## Docker 安装
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我们提供了Docker安装方式,免去您配置环境,Docker安装方法如下:
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We provide a Docker installation method to save you from configuring the environment. The Docker installation method is as follows:
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```
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# CPU only
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docker run -it --network host jittor/jittor
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# CPU and CUDA
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docker run -it --network host jittor/jittor-cuda
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```
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关于Docker安装的详细教程,可以参考[Windows/Mac/Linux通过Docker安装计图](https://cg.cs.tsinghua.edu.cn/jittor/tutorial/2020-5-15-00-00-docker/)
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## Pip 安装
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## Pip install
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如果您没有准备好环境,欢迎使用我们提供的一键安装脚本, 如果您已经装好编译器和对应版本的Python,我们强烈推荐您使用这种方法
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||||
如果您没有准备好环境,或者使用的不是Ubuntu操作系统, 推荐使用**docker安装**, 如果您已经装好编译器和对应版本的Python,我们强烈推荐您使用这种方法
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||||
(如果无法访问github, 可以通过jittor主页下载):
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||||
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||||
```bash
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||||
|
@ -160,34 +166,6 @@ python3.7 -m jittor.test.test_example
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|||
如果测试运行通过,恭喜你已经安装完成.
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||||
jittor会自动在路径中寻找合适的编译器, 如果您希望手动指定编译器, 请使用环境变量 `cc_path` 和 `nvcc_path`(可选).
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## 一键脚本安装
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## single line script install
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一键脚本安装会帮您安装好所需的编译器以及对应的Python版本.
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We provide single line command for quick installation the latest version of Jittor(Ubuntu>=16.04):
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||||
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我们提供能快速安装最新版本Jittor的单行命令(Ubuntu> = 16.04):
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||||
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```bash
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# install with clang and cuda
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wget -O - https://raw.githubusercontent.com/Jittor/jittor/master/script/install.sh | with_clang=1 with_cuda=1 bash
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# install with clang
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wget -O - https://raw.githubusercontent.com/Jittor/jittor/master/script/install.sh | with_clang=1 bash
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# install with g++ and cuda
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wget -O - https://raw.githubusercontent.com/Jittor/jittor/master/script/install.sh | with_gcc=1 with_cuda=1 bash
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# install with g++
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wget -O - https://raw.githubusercontent.com/Jittor/jittor/master/script/install.sh | with_gcc=1 bash
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```
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After execution, the script will show some environment variables you need to export.
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||||
|
||||
执行后,脚本将显示一些需要导出的环境变量。
|
||||
|
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If you use Jittor for CPU computing, we strongly recommend clang(>=8.0) as the back-end compiler of Jittor. Because some customized optimizations will be enabled.
|
||||
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||||
如果将Jittor用于CPU计算,则强烈建议使用clang(> = 8.0)作为Jittor的后端编译器。 因为Jittor会用到其中一些定制的优化。
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## 手动安装
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## manual install
|
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|
|
Loading…
Reference in New Issue