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提交 ddd4ebed 编写于 作者: M mindspore-ci-bot 提交者： Gitee
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!330 update ubuntu env and build cmd - sync 

Merge pull request !330 from guozhijian/sync_update_ubuntu_env_build_cmd
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install/mindspore_cpu_install.md
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2. 在源码根目录下执行如下命令编译MindSpore。
```bash
bash build.sh -e cpu -z -j4
bash build.sh -e cpu -j4
```
> - 在执行上述命令前，需保证可执行文件cmake和patch所在路径已加入环境变量PATH中。
> - `build.sh`中会执行`git clone`获取第三方依赖库的代码，请提前确保git的网络设置正确可用。
> - 如果编译机性能较好，可在执行中增加-j{线程数}来增加线程数量。如`bash build.sh -e cpu -z -j12`。
> - 如果编译机性能较好，可在执行中增加-j{线程数}来增加线程数量。如`bash build.sh -e cpu -j12`。
3. 执行如下命令安装MindSpore。
......
install/mindspore_cpu_install_en.md
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......@@ -68,11 +68,11 @@ This document describes how to quickly install MindSpore on a Ubuntu system with
2. Run the following command in the root directory of the source code to compile MindSpore:
```bash
bash build.sh -e cpu -z -j4
bash build.sh -e cpu -j4
```
> - Before running the preceding command, ensure that the paths where the executable files cmake and patch store have been added to the environment variable PATH.
> - In the `build.sh` script, the `git clone` command will be executed to obtain the code in the third-party dependency database. Ensure that the network settings of Git are correct.
> - If the compiler performance is strong, you can add -j{Number of threads} in to script to increase the number of threads. For example, `bash build.sh -e cpu -z -j12`.
> - If the compiler performance is strong, you can add -j{Number of threads} in to script to increase the number of threads. For example, `bash build.sh -e cpu -j12`.
3. Run the following command to install MindSpore:
......
install/mindspore_d_install.md
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| 版本号 | 操作系统 | 可执行文件安装依赖 | 源码编译安装依赖 |
| ---- | :--- | :--- | :--- |
| MindSpore 0.5.0-beta | - Ubuntu 18.04 aarch64 <br> - Ubuntu 18.04 x86_64 <br> - EulerOS 2.8 aarch64 <br> - EulerOS 2.5 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5 <br> - Ascend 910 AI处理器配套软件包（对应版本Atlas Data Center Solution V100R020C00T100） <br> - [gmp](https://gmplib.org/download/gmp/) 6.1.2 <br> - 其他依赖项参见[requirements.txt](https://gitee.com/mindspore/mindspore/blob/r0.5/requirements.txt) | **编译依赖：**<br> - [Python](https://www.python.org/downloads/) 3.7.5 <br> - Ascend 910 AI处理器配套软件包（对应版本Atlas Data Center Solution V100R020C00T100） <br> - [wheel](https://pypi.org/project/wheel/) >= 0.32.0 <br> - [GCC](https://gcc.gnu.org/releases.html) 7.3.0 <br> - [CMake](https://cmake.org/download/) >= 3.14.1 <br> - [patch](http://ftp.gnu.org/gnu/patch/) >= 2.5 <br> - [gmp](https://gmplib.org/download/gmp/) 6.1.2 <br> **安装依赖：**<br> 与可执行文件安装依赖相同 |
| MindSpore 0.5.0-beta | - Ubuntu 18.04 aarch64 <br> - Ubuntu 18.04 x86_64 <br> - EulerOS 2.8 aarch64 <br> - EulerOS 2.5 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5 <br> - Ascend 910 AI处理器配套软件包（对应版本Atlas Data Center Solution V100R020C00） <br> - [gmp](https://gmplib.org/download/gmp/) 6.1.2 <br> - 其他依赖项参见[requirements.txt](https://gitee.com/mindspore/mindspore/blob/r0.5/requirements.txt) | **编译依赖：**<br> - [Python](https://www.python.org/downloads/) 3.7.5 <br> - Ascend 910 AI处理器配套软件包（对应版本Atlas Data Center Solution V100R020C00） <br> - [wheel](https://pypi.org/project/wheel/) >= 0.32.0 <br> - [GCC](https://gcc.gnu.org/releases.html) 7.3.0 <br> - [CMake](https://cmake.org/download/) >= 3.14.1 <br> - [patch](http://ftp.gnu.org/gnu/patch/) >= 2.5 <br> - [gmp](https://gmplib.org/download/gmp/) 6.1.2 <br> **安装依赖：**<br> 与可执行文件安装依赖相同 |
- 确认当前用户有权限访问Ascend 910 AI处理器配套软件包（对应版本Atlas Data Center Solution V100R020C00T100）的安装路径`/usr/local/Ascend`，若无权限，需要root用户将当前用户添加到`/usr/local/Ascend`所在的用户组，具体配置请详见配套软件包的说明文档。
- 确认当前用户有权限访问Ascend 910 AI处理器配套软件包（对应版本Atlas Data Center Solution V100R020C00）的安装路径`/usr/local/Ascend`，若无权限，需要root用户将当前用户添加到`/usr/local/Ascend`所在的用户组，具体配置请详见配套软件包的说明文档。
- GCC 7.3.0可以直接通过apt命令安装。
- 在联网状态下，安装whl包时会自动下载`requirements.txt`中的依赖项，其余情况需自行安装。
......@@ -57,7 +57,7 @@
### 配套软件包依赖配置
- 安装Ascend 910 AI处理器配套软件包（对应版本Atlas Data Center Solution V100R020C00T100）提供的whl包，whl包随配套软件包发布，升级配套软件包之后需要重新安装。
- 安装Ascend 910 AI处理器配套软件包（对应版本Atlas Data Center Solution V100R020C00）提供的whl包，whl包随配套软件包发布，升级配套软件包之后需要重新安装。
```bash
pip install /usr/local/Ascend/fwkacllib/lib64/topi-{version}-py3-none-any.whl
......@@ -88,11 +88,11 @@
2. 在源码根目录下，执行如下命令编译MindSpore。
```bash
bash build.sh -e d -z
bash build.sh -e ascend
```
> - 在执行上述命令前，需保证可执行文件`cmake`和`patch`所在路径已加入环境变量PATH中。
> - `build.sh`中会执行`git clone`获取第三方依赖库的代码，请提前确保git的网络设置正确可用。
> - `build.sh`中默认的编译线程数为8，如果编译机性能较差可能会出现编译错误，可在执行中增加-j{线程数}来减少线程数量。如`bash build.sh -e d -z -j4`。
> - `build.sh`中默认的编译线程数为8，如果编译机性能较差可能会出现编译错误，可在执行中增加-j{线程数}来减少线程数量。如`bash build.sh -e ascend -j4`。
3. 执行如下命令安装MindSpore。
......@@ -103,19 +103,40 @@
## 配置环境变量
- 安装好MindSpore之后，需要导出Runtime相关环境变量。
- EulerOS操作系统，安装好MindSpore之后，需要导出Runtime相关环境变量。
```bash
# control log level. 0-DEBUG, 1-INFO, 2-WARNING, 3-ERROR, default level is WARNING.
export GLOG_v=2
# Conda environmental options
LOCAL_ASCEND=/usr/local/Ascend # the root directory of run package
# lib libraries that the run package depends on
export LD_LIBRARY_PATH=${LOCAL_ASCEND}/add-ons/:${LOCAL_ASCEND}/fwkacllib/lib64:${LD_LIBRARY_PATH}
# Environment variables that must be configured
export TBE_IMPL_PATH=${LOCAL_ASCEND}/opp/op_impl/built-in/ai_core/tbe # TBE operator implementation tool path
export PATH=${LOCAL_ASCEND}/fwkacllib/ccec_compiler/bin/:${PATH} # TBE operator compilation tool path
export PYTHONPATH=${TBE_IMPL_PATH}:${PYTHONPATH} # Python library that TBE implementation depends on
```
- Ubuntu操作系统，安装好MindSpore之后，需要导出Runtime相关环境变量，注意：需要将如下配置中{version}替换为环境上真实的版本号。
```bash
# control log level. 0-DEBUG, 1-INFO, 2-WARNING, 3-ERROR, default level is WARNING.
export GLOG_v=2
# Conda environmental options
LOCAL_ASCEND=/usr/local/Ascend # the root directory of run package
# lib libraries that the run package depends on
export LD_LIBRARY_PATH=${LOCAL_ASCEND}/add-ons/:${LOCAL_ASCEND}/ascend-toolkit/{version}/fwkacllib/lib64:${LOCAL_ASCEND}/driver/lib64:${LD_LIBRARY_PATH}
# Environment variables that must be configured
export TBE_IMPL_PATH=${LOCAL_ASCEND}/opp/op_impl/built-in/ai_core/tbe # TBE operator implementation tool path
export PATH=${LOCAL_ASCEND}/fwkacllib/ccec_compiler/bin/:${PATH} # TBE operator compilation tool path
export PYTHONPATH=${TBE_IMPL_PATH}:${PYTHONPATH} # Python library that TBE implementation depends on
export TBE_IMPL_PATH=${LOCAL_ASCEND}/ascend-toolkit/{version}/opp/op_impl/built-in/ai_core/tbe # TBE operator implementation tool path
export PATH=${LOCAL_ASCEND}/ascend-toolkit/{version}/fwkacllib/ccec_compiler/bin/:${PATH} # TBE operator compilation tool path
export PYTHONPATH=${TBE_IMPL_PATH}:${PYTHONPATH} # Python library that TBE implementation depends on
```
## 安装验证
......
install/mindspore_d_install_en.md
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......@@ -32,9 +32,9 @@ This document describes how to quickly install MindSpore on an Ascend AI process
| Version | Operating System | Executable File Installation Dependencies | Source Code Compilation and Installation Dependencies |
| ---- | :--- | :--- | :--- |
| MindSpore 0.5.0-beta | - Ubuntu 18.04 aarch64 <br> - Ubuntu 18.04 x86_64 <br> - EulerOS 2.8 aarch64 <br> - EulerOS 2.5 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5 <br> - Ascend 910 AI processor software package(Version:Atlas Data Center Solution V100R020C00T100) <br> - [gmp](https://gmplib.org/download/gmp/) 6.1.2 <br> - For details about other dependency items, see [requirements.txt](https://gitee.com/mindspore/mindspore/blob/r0.5/requirements.txt). | **Compilation dependencies:**<br> - [Python](https://www.python.org/downloads/) 3.7.5 <br> - Ascend 910 AI processor software package(Version:Atlas Data Center Solution V100R020C00T100) <br> - [wheel](https://pypi.org/project/wheel/) >= 0.32.0 <br> - [GCC](https://gcc.gnu.org/releases.html) 7.3.0 <br> - [CMake](https://cmake.org/download/) >= 3.14.1 <br> - [patch](http://ftp.gnu.org/gnu/patch/) >= 2.5 <br> - [gmp](https://gmplib.org/download/gmp/) 6.1.2 <br> **Installation dependencies:**<br> same as the executable file installation dependencies. |
| MindSpore 0.5.0-beta | - Ubuntu 18.04 aarch64 <br> - Ubuntu 18.04 x86_64 <br> - EulerOS 2.8 aarch64 <br> - EulerOS 2.5 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5 <br> - Ascend 910 AI processor software package(Version:Atlas Data Center Solution V100R020C00) <br> - [gmp](https://gmplib.org/download/gmp/) 6.1.2 <br> - For details about other dependency items, see [requirements.txt](https://gitee.com/mindspore/mindspore/blob/r0.5/requirements.txt). | **Compilation dependencies:**<br> - [Python](https://www.python.org/downloads/) 3.7.5 <br> - Ascend 910 AI processor software package(Version:Atlas Data Center Solution V100R020C00) <br> - [wheel](https://pypi.org/project/wheel/) >= 0.32.0 <br> - [GCC](https://gcc.gnu.org/releases.html) 7.3.0 <br> - [CMake](https://cmake.org/download/) >= 3.14.1 <br> - [patch](http://ftp.gnu.org/gnu/patch/) >= 2.5 <br> - [gmp](https://gmplib.org/download/gmp/) 6.1.2 <br> **Installation dependencies:**<br> same as the executable file installation dependencies. |
- Confirm that the current user has the right to access the installation path `/usr/local/Ascend `of Ascend 910 AI processor software package(Version:Atlas Data Center Solution V100R020C00T100). If not, the root user needs to add the current user to the user group where `/usr/local/Ascend` is located. For the specific configuration, please refer to the software package instruction document.
- Confirm that the current user has the right to access the installation path `/usr/local/Ascend `of Ascend 910 AI processor software package(Version:Atlas Data Center Solution V100R020C00). If not, the root user needs to add the current user to the user group where `/usr/local/Ascend` is located. For the specific configuration, please refer to the software package instruction document.
- GCC 7.3.0 can be installed by using apt command.
- When the network is connected, dependency items in the `requirements.txt` file are automatically downloaded during .whl package installation. In other cases, you need to manually install dependency items.
......@@ -56,7 +56,7 @@ This document describes how to quickly install MindSpore on an Ascend AI process
### Configuring software package Dependencies
- Install the .whl package provided in Ascend 910 AI processor software package(Version:Atlas Data Center Solution V100R020C00T100). The .whl package is released with the software package. After software package is upgraded, reinstall the .whl package.
- Install the .whl package provided in Ascend 910 AI processor software package(Version:Atlas Data Center Solution V100R020C00). The .whl package is released with the software package. After software package is upgraded, reinstall the .whl package.
```bash
pip install /usr/local/Ascend/fwkacllib/lib64/topi-{version}-py3-none-any.whl
......@@ -87,11 +87,11 @@ The compilation and installation must be performed on the Ascend 910 AI processo
2. Run the following command in the root directory of the source code to compile MindSpore:
```bash
bash build.sh -e d -z
bash build.sh -e ascend
```
> - Before running the preceding command, ensure that the paths where the executable files `cmake` and `patch` store have been added to the environment variable PATH.
> - In the `build.sh` script, the `git clone` command will be executed to obtain the code in the third-party dependency database. Ensure that the network settings of Git are correct.
> - In the `build.sh` script, the default number of compilation threads is 8. If the compiler performance is poor, compilation errors may occur. You can add -j{Number of threads} in to script to reduce the number of threads. For example, `bash build.sh -e d -z -j4`.
> - In the `build.sh` script, the default number of compilation threads is 8. If the compiler performance is poor, compilation errors may occur. You can add -j{Number of threads} in to script to reduce the number of threads. For example, `bash build.sh -e ascend -j4`.
3. Run the following command to install MindSpore:
......@@ -102,19 +102,40 @@ The compilation and installation must be performed on the Ascend 910 AI processo
## Configuring Environment Variables
- After MindSpore is installed, export runtime-related environment variables.
- In EulerOS, after MindSpore is installed, export runtime-related environment variables.
```bash
# control log level. 0-DEBUG, 1-INFO, 2-WARNING, 3-ERROR, default level is WARNING.
export GLOG_v=2
# Conda environmental options
LOCAL_ASCEND=/usr/local/Ascend # the root directory of run package
# lib libraries that the run package depends on
export LD_LIBRARY_PATH=${LOCAL_ASCEND}/add-ons/:${LOCAL_ASCEND}/fwkacllib/lib64:${LD_LIBRARY_PATH}
# Environment variables that must be configured
export TBE_IMPL_PATH=${LOCAL_ASCEND}/opp/op_impl/built-in/ai_core/tbe # TBE operator implementation tool path
export PATH=${LOCAL_ASCEND}/fwkacllib/ccec_compiler/bin/:${PATH} # TBE operator compilation tool path
export PYTHONPATH=${TBE_IMPL_PATH}:${PYTHONPATH} # Python library that TBE implementation depends on
```
- In Ubuntu, after MindSpore is installed, export runtime-related environment variables. Note: you need to replace {version} in the following configuration with the actual version number on the environment.
```bash
# control log level. 0-DEBUG, 1-INFO, 2-WARNING, 3-ERROR, default level is WARNING.
export GLOG_v=2
# Conda environmental options
LOCAL_ASCEND=/usr/local/Ascend # the root directory of run package
# lib libraries that the run package depends on
export LD_LIBRARY_PATH=${LOCAL_ASCEND}/add-ons/:${LOCAL_ASCEND}/ascend-toolkit/{version}/fwkacllib/lib64:${LOCAL_ASCEND}/driver/lib64:${LD_LIBRARY_PATH}
# Environment variables that must be configured
export TBE_IMPL_PATH=${LOCAL_ASCEND}/opp/op_impl/built-in/ai_core/tbe # TBE operator implementation tool path
export PATH=${LOCAL_ASCEND}/fwkacllib/ccec_compiler/bin/:${PATH} # TBE operator compilation tool path
export PYTHONPATH=${TBE_IMPL_PATH}:${PYTHONPATH} # Python library that TBE implementation depends on
export TBE_IMPL_PATH=${LOCAL_ASCEND}/ascend-toolkit/{version}/opp/op_impl/built-in/ai_core/tbe # TBE operator implementation tool path
export PATH=${LOCAL_ASCEND}/ascend-toolkit/{version}/fwkacllib/ccec_compiler/bin/:${PATH} # TBE operator compilation tool path
export PYTHONPATH=${TBE_IMPL_PATH}:${PYTHONPATH} # Python library that TBE implementation depends on
```
## Installation Verification
......
install/mindspore_gpu_install.md
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......@@ -68,11 +68,11 @@
2. 在源码根目录下执行如下命令编译MindSpore。
```bash
bash build.sh -e gpu -M on -z
bash build.sh -e gpu
```
> - 在执行上述命令前，需保证可执行文件`cmake`和`patch`所在路径已加入环境变量PATH中。
> - `build.sh`中会执行`git clone`获取第三方依赖库的代码，请提前确保git的网络设置正确可用。
> - `build.sh`中默认的编译线程数为8，如果编译机性能较差可能会出现编译错误，可在执行中增加-j{线程数}来减少线程数量。如`bash build.sh -e gpu -M on -z -j4`。
> - `build.sh`中默认的编译线程数为8，如果编译机性能较差可能会出现编译错误，可在执行中增加-j{线程数}来减少线程数量。如`bash build.sh -e gpu -j4`。
3. 执行如下命令安装MindSpore。
......
install/mindspore_gpu_install_en.md
浏览文件 @ ddd4ebed
......@@ -68,11 +68,11 @@ This document describes how to quickly install MindSpore on a NVIDIA GPU environ
2. Run the following command in the root directory of the source code to compile MindSpore:
```bash
bash build.sh -e gpu -M on -z
bash build.sh -e gpu
```
> - Before running the preceding command, ensure that the paths where the executable files `cmake` and `patch` store have been added to the environment variable PATH.
> - In the `build.sh` script, the `git clone` command will be executed to obtain the code in the third-party dependency database. Ensure that the network settings of Git are correct.
> - In the `build.sh` script, the default number of compilation threads is 8. If the compiler performance is poor, compilation errors may occur. You can add -j{Number of threads} in to script to reduce the number of threads. For example, `bash build.sh -e gpu -M on -z -j4`.
> - In the `build.sh` script, the default number of compilation threads is 8. If the compiler performance is poor, compilation errors may occur. You can add -j{Number of threads} in to script to reduce the number of threads. For example, `bash build.sh -e gpu -j4`.
3. Run the following command to install MindSpore:
......
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