@@ -24,7 +24,7 @@ This document describes how to quickly install MindSpore on a Ubuntu system with
| MindSpore master | Ubuntu 16.04 or later x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5 <br> - For details about other dependency items, see [requirements.txt](https://gitee.com/mindspore/mindspore/blob/master/requirements.txt). | **Compilation dependencies:**<br> - [Python](https://www.python.org/downloads/) 3.7.5 <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> same as the executable file installation dependencies. |
- When Ubuntu version is 18.04, 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.
- 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.
### (Optional) Installing Conda
...
...
@@ -71,7 +71,7 @@ This document describes how to quickly install MindSpore on a Ubuntu system with
bash build.sh -e cpu -z -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.
> - 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`.
3. Run the following command to install MindSpore:
...
...
@@ -99,7 +99,7 @@ If you need to conduct AI model security research or enhance the security of the
| ---- | :--- | :--- | :--- |
| MindArmour master | Ubuntu 16.04 or later x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5 <br> - MindSpore master <br> - For details about other dependency items, see [setup.py](https://gitee.com/mindspore/mindarmour/blob/master/setup.py). | Same as the executable file installation dependencies. |
- When the network is connected, dependency items in the setup.py file are automatically downloaded during .whl package installation. In other cases, you need to manually install dependency items.
- When the network is connected, dependency items in the `setup.py` file are automatically downloaded during .whl package installation. In other cases, you need to manually install dependency items.
@@ -22,7 +22,7 @@ This document describes how to quickly install MindSpore on a Windows system wit
| ---- | :--- | :--- | :--- |
| MindSpore master | Windows 10 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5 <br> - For details about other dependency items, see [requirements.txt](https://gitee.com/mindspore/mindspore/blob/master/requirements.txt). | **Compilation dependencies:**<br> - [Python](https://www.python.org/downloads/) 3.7.5 <br> - [MinGW-W64 GCC-7.3.0](https://sourceforge.net/projects/mingw-w64/files/Toolchains%20targetting%20Win64/Personal%20Builds/mingw-builds/7.3.0/threads-posix/seh/x86_64-7.3.0-release-posix-seh-rt_v5-rev0.7z) x86_64-posix-seh <br> - [ActivePerl](http://downloads.activestate.com/ActivePerl/releases/5.24.3.2404/ActivePerl-5.24.3.2404-MSWin32-x64-404865.exe) 5.24.3.2404 <br> - [CMake](https://cmake.org/download/) 3.14.1 <br> - [wheel](https://pypi.org/project/wheel/) >= 0.32.0 <br>**Installation dependencies:**<br> same as the executable file installation dependencies. |
- 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.
- 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.
### (Optional) Installing Conda
...
...
@@ -70,9 +70,9 @@ This document describes how to quickly install MindSpore on a Windows system wit
```bash
call build.bat
```
> - Before running the preceding command, ensure that the paths of mingw64\bin\ and the executable files cmake have been added to the environment variable PATH.
> - Before running the preceding command, ensure that the paths of `mingw64\bin\` and the executable files `cmake` have been added to the environment variable PATH.
> - If git was not installed in `ProgramFiles`, you will need to set environment variable to where `patch.exe` is allocated. For example, when git was install in `D:\git`, `set MS_PATCH_PATH=D:\git\usr\bin`.
> - In the build.bat 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.bat` 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(Default 6). For example, `call build.bat 12`.
> - Before running the preceding command, ensure that [Visual C ++ Redistributable for Visual Studio 2015](https://www.microsoft.com/zh-CN/download/details.aspx?id=48145) is installed.
- 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。
@@ -36,7 +36,7 @@ This document describes how to quickly install MindSpore on an Ascend AI process
- 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.
- When Ubuntu version is 18.04, 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.
- 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.
### (Optional) Installing Conda
...
...
@@ -89,9 +89,9 @@ The compilation and installation must be performed on the Ascend 910 AI processo
```bash
bash build.sh -e d -z
```
> - 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`.
> - 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`.
3. Run the following command to install MindSpore:
...
...
@@ -161,7 +161,7 @@ If you need to analyze information such as model scalars, graphs, and model trac
| ---- | :--- | :--- | :--- |
| MindInsight master | - Ubuntu 16.04 or later aarch64 <br> - Ubuntu 16.04 or later x86_64 <br> - EulerOS 2.8 aarch64 <br> - EulerOS 2.5 x86_64 <br> | - [Python](https://www.python.org/downloads/) 3.7.5 <br> - MindSpore master <br> - For details about other dependency items, see [requirements.txt](https://gitee.com/mindspore/mindinsight/blob/master/requirements.txt). | **Compilation dependencies:**<br> - [Python](https://www.python.org/downloads/) 3.7.5 <br> - [CMake](https://cmake.org/download/) >= 3.14.1 <br> - [GCC](https://gcc.gnu.org/releases.html) 7.3.0 <br> - [node.js](https://nodejs.org/en/download/) >= 10.19.0 <br> - [wheel](https://pypi.org/project/wheel/) >= 0.32.0 <br> - [pybind11](https://pypi.org/project/pybind11/) >= 2.4.3 <br>**Installation dependencies:**<br> same as the executable file installation dependencies. |
- 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.
- 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.
## Installation Guide
...
...
@@ -201,8 +201,8 @@ If you need to analyze information such as model scalars, graphs, and model trac
(2) Create a .whl package to install MindInsight.
Access the root directory of the source code.
First run the MindInsight compilation script under the build directory of the source code.
Then run the command to install the .whl package generated into the output directory of the source code.
First run the MindInsight compilation script under the `build` directory of the source code.
Then run the command to install the .whl package generated into the `output` directory of the source code.
```bash
cd mindinsight
...
...
@@ -228,7 +228,7 @@ If you need to conduct AI model security research or enhance the security of the
| ---- | :--- | :--- | :--- |
| MindArmour master | - Ubuntu 16.04 or later aarch64 <br> - Ubuntu 16.04 or later x86_64 <br> - EulerOS 2.8 aarch64 <br> - EulerOS 2.5 x86_64 <br> | - [Python](https://www.python.org/downloads/) 3.7.5 <br> - MindSpore master <br> - For details about other dependency items, see [setup.py](https://gitee.com/mindspore/mindarmour/blob/master/setup.py). | Same as the executable file installation dependencies. |
- When the network is connected, dependency items in the setup.py file are automatically downloaded during .whl package installation. In other cases, you need to manually install dependency items.
- When the network is connected, dependency items in the `setup.py` file are automatically downloaded during .whl package installation. In other cases, you need to manually install dependency items.
@@ -31,7 +31,7 @@ This document describes how to quickly install MindSpore on a NVIDIA GPU environ
| MindSpore master | Ubuntu 16.04 or later x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5 <br> - [CUDA 9.2](https://developer.nvidia.com/cuda-92-download-archive) / [CUDA 10.1](https://developer.nvidia.com/cuda-10.1-download-archive-base)<br> - [CuDNN](https://developer.nvidia.com/rdp/cudnn-archive) >= 7.6 <br> - [OpenMPI](https://www.open-mpi.org/faq/?category=building#easy-build) 3.1.5 (optional, required for single-node/multi-GPU and multi-node/multi-GPU training) <br> - [NCCL](https://docs.nvidia.com/deeplearning/sdk/nccl-install-guide/index.html#debian) 2.4.8-1 (optional, required for single-node/multi-GPU and multi-node/multi-GPU training) <br> - For details about other dependency items, see [requirements.txt](https://gitee.com/mindspore/mindspore/blob/master/requirements.txt). | **Compilation dependencies:**<br> - [Python](https://www.python.org/downloads/) 3.7.5 <br> - [wheel](https://pypi.org/project/wheel/) >= 0.32.0 <br> - [CMake](https://cmake.org/download/) >= 3.14.1 <br> - [GCC](https://gcc.gnu.org/releases.html) 7.3.0 <br> - [patch](http://ftp.gnu.org/gnu/patch/) >= 2.5 <br> - [Autoconf](https://www.gnu.org/software/autoconf) >= 2.69 <br> - [Libtool](https://www.gnu.org/software/libtool) >= 2.4.6-29.fc30 <br> - [Automake](https://www.gnu.org/software/automake) >= 1.15.1 <br> - [CUDA 9.2](https://developer.nvidia.com/cuda-92-download-archive) / [CUDA 10.1](https://developer.nvidia.com/cuda-10.1-download-archive-base)<br> - [CuDNN](https://developer.nvidia.com/rdp/cudnn-archive) >= 7.6 <br>**Installation dependencies:**<br> same as the executable file installation dependencies. |
- When Ubuntu version is 18.04, 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.
- 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.
- MindSpore reduces dependency on Autoconf, Libtool, Automake versions for the convenience of users, default versions of these tools built in their systems are now supported.
### (Optional) Installing Conda
...
...
@@ -71,9 +71,9 @@ This document describes how to quickly install MindSpore on a NVIDIA GPU environ
```bash
bash build.sh -e gpu -M on -z
```
> - 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`.
> - 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`.
3. Run the following command to install MindSpore:
...
...
@@ -126,7 +126,7 @@ If you need to analyze information such as model scalars, graphs, and model trac
| ---- | :--- | :--- | :--- |
| MindInsight master | - Ubuntu 16.04 or later x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5 <br> - MindSpore master <br> - For details about other dependency items, see [requirements.txt](https://gitee.com/mindspore/mindinsight/blob/master/requirements.txt). | **Compilation dependencies:**<br> - [Python](https://www.python.org/downloads/) 3.7.5 <br> - [CMake](https://cmake.org/download/) >= 3.14.1 <br> - [GCC](https://gcc.gnu.org/releases.html) 7.3.0 <br> - [node.js](https://nodejs.org/en/download/) >= 10.19.0 <br> - [wheel](https://pypi.org/project/wheel/) >= 0.32.0 <br> - [pybind11](https://pypi.org/project/pybind11/) >= 2.4.3 <br>**Installation dependencies:**<br> same as the executable file installation dependencies. |
- 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.
- 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.
## Installation Guide
...
...
@@ -166,8 +166,8 @@ If you need to analyze information such as model scalars, graphs, and model trac
(2) Create a .whl package to install MindInsight.
Access the root directory of the source code.
First run the MindInsight compilation script under the build directory of the source code.
Then run the command to install the .whl package generated into the output directory of the source code.
First run the MindInsight compilation script under the `build` directory of the source code.
Then run the command to install the .whl package generated into the `output` directory of the source code.
```bash
cd mindinsight
...
...
@@ -193,7 +193,7 @@ If you need to conduct AI model security research or enhance the security of the
| ---- | :--- | :--- | :--- |
| MindArmour master | Ubuntu 16.04 or later x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5 <br> - MindSpore master <br> - For details about other dependency items, see [setup.py](https://gitee.com/mindspore/mindarmour/blob/master/setup.py). | Same as the executable file installation dependencies. |
- When the network is connected, dependency items in the setup.py file are automatically downloaded during .whl package installation. In other cases, you need to manually install dependency items.
- When the network is connected, dependency items in the `setup.py` file are automatically downloaded during .whl package installation. In other cases, you need to manually install dependency items.
