From a14430966b3887d199f28e4712e18dd0ed46332d Mon Sep 17 00:00:00 2001 From: SebastianHan Date: Mon, 29 Jun 2020 14:39:18 +0800 Subject: [PATCH] update master to 0.5 --- docs/source_en/architecture.md | 2 +- docs/source_en/benchmark.md | 2 +- .../source_en/constraints_on_network_construction.md | 2 +- docs/source_en/glossary.md | 2 +- docs/source_en/operator_list.md | 2 +- docs/source_en/roadmap.md | 2 +- docs/source_zh_cn/architecture.md | 2 +- docs/source_zh_cn/benchmark.md | 2 +- .../constraints_on_network_construction.md | 2 +- docs/source_zh_cn/glossary.md | 2 +- docs/source_zh_cn/operator_list.md | 2 +- docs/source_zh_cn/roadmap.md | 2 +- install/mindspore_cpu_install.md | 8 ++++---- install/mindspore_cpu_install_en.md | 8 ++++---- install/mindspore_cpu_win_install.md | 4 ++-- install/mindspore_cpu_win_install_en.md | 4 ++-- install/mindspore_d_install.md | 12 ++++++------ install/mindspore_d_install_en.md | 12 ++++++------ install/mindspore_gpu_install.md | 12 ++++++------ install/mindspore_gpu_install_en.md | 12 ++++++------ resource/faq/FAQ_en.md | 4 ++-- resource/faq/FAQ_zh_cn.md | 4 ++-- tutorials/notebook/quick_start.ipynb | 2 +- .../advanced_use/computer_vision_application.md | 4 ++-- .../advanced_use/customized_debugging_information.md | 2 +- .../source_en/advanced_use/dashboard_and_lineage.md | 2 +- .../advanced_use/debugging_in_pynative_mode.md | 2 +- .../source_en/advanced_use/differential_privacy.md | 2 +- .../source_en/advanced_use/distributed_training.md | 6 +++--- tutorials/source_en/advanced_use/mixed_precision.md | 2 +- tutorials/source_en/advanced_use/model_security.md | 2 +- .../source_en/advanced_use/network_migration.md | 4 ++-- tutorials/source_en/advanced_use/nlp_application.md | 2 +- .../source_en/advanced_use/on_device_inference.md | 4 ++-- .../source_en/advanced_use/performance_profiling.md | 2 +- tutorials/source_en/quick_start/quick_start.md | 4 ++-- tutorials/source_en/use/custom_operator.md | 2 +- .../use/data_preparation/converting_datasets.md | 2 +- .../data_processing_and_augmentation.md | 2 +- .../use/data_preparation/loading_the_datasets.md | 2 +- tutorials/source_en/use/multi_platform_inference.md | 4 ++-- .../use/saving_and_loading_model_parameters.md | 2 +- .../source_zh_cn/advanced_use/aware_quantization.md | 2 +- .../advanced_use/checkpoint_for_hybrid_parallel.md | 2 +- .../advanced_use/computer_vision_application.md | 4 ++-- .../advanced_use/customized_debugging_information.md | 2 +- .../advanced_use/dashboard_and_lineage.md | 2 +- .../advanced_use/debugging_in_pynative_mode.md | 2 +- .../advanced_use/differential_privacy.md | 2 +- .../advanced_use/distributed_training.md | 6 +++--- .../source_zh_cn/advanced_use/graph_kernel_fusion.md | 2 +- .../source_zh_cn/advanced_use/mixed_precision.md | 2 +- .../source_zh_cn/advanced_use/model_security.md | 2 +- .../source_zh_cn/advanced_use/network_migration.md | 6 +++--- .../source_zh_cn/advanced_use/nlp_application.md | 2 +- .../source_zh_cn/advanced_use/on_device_inference.md | 4 ++-- .../advanced_use/performance_profiling.md | 2 +- .../source_zh_cn/advanced_use/use_on_the_cloud.md | 2 +- tutorials/source_zh_cn/quick_start/quick_start.md | 6 +++--- tutorials/source_zh_cn/quick_start/quick_video.md | 2 +- tutorials/source_zh_cn/use/custom_operator.md | 2 +- .../use/data_preparation/converting_datasets.md | 2 +- .../data_processing_and_augmentation.md | 2 +- .../use/data_preparation/loading_the_datasets.md | 2 +- .../source_zh_cn/use/multi_platform_inference.md | 4 ++-- .../use/saving_and_loading_model_parameters.md | 2 +- 66 files changed, 112 insertions(+), 112 deletions(-) diff --git a/docs/source_en/architecture.md b/docs/source_en/architecture.md index cd30baf77b..0f95ac4117 100644 --- a/docs/source_en/architecture.md +++ b/docs/source_en/architecture.md @@ -8,7 +8,7 @@ This document describes the overall architecture of MindSpore. - + The MindSpore framework consists of the Frontend Expression layer, Graph Engine layer, and Backend Runtime layer. diff --git a/docs/source_en/benchmark.md b/docs/source_en/benchmark.md index 6c541a6755..719943f87f 100644 --- a/docs/source_en/benchmark.md +++ b/docs/source_en/benchmark.md @@ -1,6 +1,6 @@ # Benchmarks - + This document describes the MindSpore benchmarks. For details about the MindSpore pre-trained model, see [Model Zoo](https://gitee.com/mindspore/mindspore/tree/master/model_zoo). diff --git a/docs/source_en/constraints_on_network_construction.md b/docs/source_en/constraints_on_network_construction.md index 69345b9878..47bc6dc5c1 100644 --- a/docs/source_en/constraints_on_network_construction.md +++ b/docs/source_en/constraints_on_network_construction.md @@ -23,7 +23,7 @@ - + ## Overview MindSpore can compile user source code based on the Python syntax into computational graphs, and can convert common functions or instances inherited from nn.Cell into computational graphs. Currently, MindSpore does not support conversion of any Python source code into computational graphs. Therefore, there are constraints on source code compilation, including syntax constraints and network definition constraints. As MindSpore evolves, the constraints may change. diff --git a/docs/source_en/glossary.md b/docs/source_en/glossary.md index 073a76f32a..3f0f4b1471 100644 --- a/docs/source_en/glossary.md +++ b/docs/source_en/glossary.md @@ -6,7 +6,7 @@ - + | Acronym and Abbreviation | Description | | ----- | ----- | diff --git a/docs/source_en/operator_list.md b/docs/source_en/operator_list.md index 33328e0a85..7f912b97db 100644 --- a/docs/source_en/operator_list.md +++ b/docs/source_en/operator_list.md @@ -8,7 +8,7 @@ - + ## mindspore.nn diff --git a/docs/source_en/roadmap.md b/docs/source_en/roadmap.md index 5c89ddfb0d..aeec98616e 100644 --- a/docs/source_en/roadmap.md +++ b/docs/source_en/roadmap.md @@ -14,7 +14,7 @@ MindSpore's top priority plans in the year are displayed as follows. We will con - + In general, we will make continuous improvements in the following aspects: 1. Support more preset models. diff --git a/docs/source_zh_cn/architecture.md b/docs/source_zh_cn/architecture.md index 27205cde10..7f05d732c2 100644 --- a/docs/source_zh_cn/architecture.md +++ b/docs/source_zh_cn/architecture.md @@ -8,7 +8,7 @@ - + MindSpore框架架构总体分为MindSpore前端表示层、MindSpore计算图引擎和MindSpore后端运行时三层。 diff --git a/docs/source_zh_cn/benchmark.md b/docs/source_zh_cn/benchmark.md index 4d3f4efcbe..fdbc9c1b48 100644 --- a/docs/source_zh_cn/benchmark.md +++ b/docs/source_zh_cn/benchmark.md @@ -1,6 +1,6 @@ # 基准性能 - + 本文介绍MindSpore的基准性能。MindSpore预训练模型可参考[Model Zoo](https://gitee.com/mindspore/mindspore/tree/master/model_zoo)。 diff --git a/docs/source_zh_cn/constraints_on_network_construction.md b/docs/source_zh_cn/constraints_on_network_construction.md index ff628c7982..4538ab05fd 100644 --- a/docs/source_zh_cn/constraints_on_network_construction.md +++ b/docs/source_zh_cn/constraints_on_network_construction.md @@ -23,7 +23,7 @@ - + ## 概述 MindSpore完成从用户源码到计算图的编译，用户源码基于Python语法编写，当前MindSpore支持将普通函数或者继承自nn.Cell的实例转换生成计算图，暂不支持将任意Python源码转换成计算图，所以对于用户源码支持的写法有所限制，主要包括语法约束和网络定义约束两方面。随着MindSpore的演进，这些约束可能会发生变化。 diff --git a/docs/source_zh_cn/glossary.md b/docs/source_zh_cn/glossary.md index eb1c2cdd6a..20aee2b801 100644 --- a/docs/source_zh_cn/glossary.md +++ b/docs/source_zh_cn/glossary.md @@ -6,7 +6,7 @@ - + | 术语/缩略语 | 说明 | | ----- | ----- | diff --git a/docs/source_zh_cn/operator_list.md b/docs/source_zh_cn/operator_list.md index 128e5bc31d..de68a7d2d1 100644 --- a/docs/source_zh_cn/operator_list.md +++ b/docs/source_zh_cn/operator_list.md @@ -8,7 +8,7 @@ - + ## mindspore.nn diff --git a/docs/source_zh_cn/roadmap.md b/docs/source_zh_cn/roadmap.md index 528182d2e3..772a7092a1 100644 --- a/docs/source_zh_cn/roadmap.md +++ b/docs/source_zh_cn/roadmap.md @@ -23,7 +23,7 @@ - + ## 预置模型 * CV：目标检测、GAN、图像分割、姿态识别等场景经典模型。 diff --git a/install/mindspore_cpu_install.md b/install/mindspore_cpu_install.md index 45a1beee50..431fc4dfcb 100644 --- a/install/mindspore_cpu_install.md +++ b/install/mindspore_cpu_install.md @@ -21,7 +21,7 @@ | 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 master | Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- 其他依赖项参见[requirements.txt](https://gitee.com/mindspore/mindspore/blob/master/requirements.txt) | **编译依赖：**
- [Python](https://www.python.org/downloads/) 3.7.5
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [CMake](https://cmake.org/download/) >= 3.14.1
- [patch](http://ftp.gnu.org/gnu/patch/) >= 2.5
**安装依赖：**
与可执行文件安装依赖相同 | +| MindSpore master | Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- 其他依赖项参见[requirements.txt](https://gitee.com/mindspore/mindspore/blob/r0.5/requirements.txt) | **编译依赖：**
- [Python](https://www.python.org/downloads/) 3.7.5
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [CMake](https://cmake.org/download/) >= 3.14.1
- [patch](http://ftp.gnu.org/gnu/patch/) >= 2.5
**安装依赖：**
与可执行文件安装依赖相同 | - 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。 @@ -62,7 +62,7 @@ 1. 从代码仓下载源码。 ```bash - git clone https://gitee.com/mindspore/mindspore.git + git clone https://gitee.com/mindspore/mindspore.git -b r0.5 ``` 2. 在源码根目录下执行如下命令编译MindSpore。 @@ -97,7 +97,7 @@ | 版本号 | 操作系统 | 可执行文件安装依赖 | 源码编译安装依赖 | | ---------------------- | :------------------ | :----------------------------------------------------------- | :----------------------- | -| MindArmour master | Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- 其他依赖项参见[setup.py](https://gitee.com/mindspore/mindarmour/blob/master/setup.py) | 与可执行文件安装依赖相同 | +| MindArmour master | Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- 其他依赖项参见[setup.py](https://gitee.com/mindspore/mindarmour/blob/r0.5/setup.py) | 与可执行文件安装依赖相同 | - 在联网状态下，安装whl包时会自动下载`setup.py`中的依赖项，其余情况需自行安装。 @@ -122,7 +122,7 @@ 1. 从代码仓下载源码。 ```bash - git clone https://gitee.com/mindspore/mindarmour.git + git clone https://gitee.com/mindspore/mindarmour.git -b r0.5 ``` 2. 在源码根目录下，执行如下命令编译并安装MindArmour。 diff --git a/install/mindspore_cpu_install_en.md b/install/mindspore_cpu_install_en.md index 5d2eaa2120..1bc2b62cd2 100644 --- a/install/mindspore_cpu_install_en.md +++ b/install/mindspore_cpu_install_en.md @@ -21,7 +21,7 @@ This document describes how to quickly install MindSpore on a Ubuntu system with | Version | Operating System | Executable File Installation Dependencies | Source Code Compilation and Installation Dependencies | | ---- | :--- | :--- | :--- | -| MindSpore master | Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- For details about other dependency items, see [requirements.txt](https://gitee.com/mindspore/mindspore/blob/master/requirements.txt). | **Compilation dependencies:**
- [Python](https://www.python.org/downloads/) 3.7.5
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [CMake](https://cmake.org/download/) >= 3.14.1
- [patch](http://ftp.gnu.org/gnu/patch/) >= 2.5
same as the executable file installation dependencies. | +| MindSpore master | Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- For details about other dependency items, see [requirements.txt](https://gitee.com/mindspore/mindspore/blob/r0.5/requirements.txt). | **Compilation dependencies:**
- [Python](https://www.python.org/downloads/) 3.7.5
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [CMake](https://cmake.org/download/) >= 3.14.1
- [patch](http://ftp.gnu.org/gnu/patch/) >= 2.5
same as the executable file installation dependencies. | - 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. @@ -62,7 +62,7 @@ This document describes how to quickly install MindSpore on a Ubuntu system with 1. Download the source code from the code repository. ```bash - git clone https://gitee.com/mindspore/mindspore.git + git clone https://gitee.com/mindspore/mindspore.git -b r0.5 ``` 2. Run the following command in the root directory of the source code to compile MindSpore: @@ -97,7 +97,7 @@ If you need to conduct AI model security research or enhance the security of the | Version | Operating System | Executable File Installation Dependencies | Source Code Compilation and Installation Dependencies | | ---- | :--- | :--- | :--- | -| MindArmour master | Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- 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. | +| MindArmour master | Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- For details about other dependency items, see [setup.py](https://gitee.com/mindspore/mindarmour/blob/r0.5/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. @@ -122,7 +122,7 @@ If you need to conduct AI model security research or enhance the security of the 1. Download the source code from the code repository. ```bash - git clone https://gitee.com/mindspore/mindarmour.git + git clone https://gitee.com/mindspore/mindarmour.git -b r0.5 ``` 2. Run the following command in the root directory of the source code to compile and install MindArmour: diff --git a/install/mindspore_cpu_win_install.md b/install/mindspore_cpu_win_install.md index 5b33ddb3c8..359280013b 100644 --- a/install/mindspore_cpu_win_install.md +++ b/install/mindspore_cpu_win_install.md @@ -20,7 +20,7 @@ | 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 master | Windows 10 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- 其他依赖项参见[requirements.txt](https://gitee.com/mindspore/mindspore/blob/master/requirements.txt) | **编译依赖：**
- [Python](https://www.python.org/downloads/) 3.7.5
- [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
- [ActivePerl](http://downloads.activestate.com/ActivePerl/releases/5.24.3.2404/ActivePerl-5.24.3.2404-MSWin32-x64-404865.exe) 5.24.3.2404
- [CMake](https://cmake.org/download/) 3.14.1
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
**安装依赖：**
与可执行文件安装依赖相同 | +| MindSpore master | Windows 10 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- 其他依赖项参见[requirements.txt](https://gitee.com/mindspore/mindspore/blob/r0.5/requirements.txt) | **编译依赖：**
- [Python](https://www.python.org/downloads/) 3.7.5
- [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
- [ActivePerl](http://downloads.activestate.com/ActivePerl/releases/5.24.3.2404/ActivePerl-5.24.3.2404-MSWin32-x64-404865.exe) 5.24.3.2404
- [CMake](https://cmake.org/download/) 3.14.1
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
**安装依赖：**
与可执行文件安装依赖相同 | - 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。 @@ -62,7 +62,7 @@ 1. 从代码仓下载源码。 ```bash - git clone https://gitee.com/mindspore/mindspore.git + git clone https://gitee.com/mindspore/mindspore.git -b r0.5 ``` 2. 在源码根目录下执行如下命令编译MindSpore。 diff --git a/install/mindspore_cpu_win_install_en.md b/install/mindspore_cpu_win_install_en.md index 2f1fe17739..9de7edbcfd 100644 --- a/install/mindspore_cpu_win_install_en.md +++ b/install/mindspore_cpu_win_install_en.md @@ -20,7 +20,7 @@ This document describes how to quickly install MindSpore on a Windows system wit | Version | Operating System | Executable File Installation Dependencies | Source Code Compilation and Installation Dependencies | | ---- | :--- | :--- | :--- | -| MindSpore master | Windows 10 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- For details about other dependency items, see [requirements.txt](https://gitee.com/mindspore/mindspore/blob/master/requirements.txt). | **Compilation dependencies:**
- [Python](https://www.python.org/downloads/) 3.7.5
- [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
- [ActivePerl](http://downloads.activestate.com/ActivePerl/releases/5.24.3.2404/ActivePerl-5.24.3.2404-MSWin32-x64-404865.exe) 5.24.3.2404
- [CMake](https://cmake.org/download/) 3.14.1
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
**Installation dependencies:**
same as the executable file installation dependencies. | +| MindSpore master | Windows 10 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- For details about other dependency items, see [requirements.txt](https://gitee.com/mindspore/mindspore/blob/r0.5/requirements.txt). | **Compilation dependencies:**
- [Python](https://www.python.org/downloads/) 3.7.5
- [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
- [ActivePerl](http://downloads.activestate.com/ActivePerl/releases/5.24.3.2404/ActivePerl-5.24.3.2404-MSWin32-x64-404865.exe) 5.24.3.2404
- [CMake](https://cmake.org/download/) 3.14.1
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
**Installation dependencies:**
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. @@ -62,7 +62,7 @@ This document describes how to quickly install MindSpore on a Windows system wit 1. Download the source code from the code repository. ```bash - git clone https://gitee.com/mindspore/mindspore.git + git clone https://gitee.com/mindspore/mindspore.git -b r0.5 ``` 2. Run the following command in the root directory of the source code to compile MindSpore: diff --git a/install/mindspore_d_install.md b/install/mindspore_d_install.md index c2e1da96b8..cd2f1d41a2 100644 --- a/install/mindspore_d_install.md +++ b/install/mindspore_d_install.md @@ -33,7 +33,7 @@ | 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 master | - Ubuntu 18.04 aarch64
- Ubuntu 18.04 x86_64
- EulerOS 2.8 aarch64
- EulerOS 2.5 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- Ascend 910 AI处理器配套软件包（对应版本Atlas Data Center Solution V100R020C00T100）
- [gmp](https://gmplib.org/download/gmp/) 6.1.2
- 其他依赖项参见[requirements.txt](https://gitee.com/mindspore/mindspore/blob/master/requirements.txt) | **编译依赖：**
- [Python](https://www.python.org/downloads/) 3.7.5
- Ascend 910 AI处理器配套软件包（对应版本Atlas Data Center Solution V100R020C00T100）
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [CMake](https://cmake.org/download/) >= 3.14.1
- [patch](http://ftp.gnu.org/gnu/patch/) >= 2.5
- [gmp](https://gmplib.org/download/gmp/) 6.1.2
**安装依赖：**
与可执行文件安装依赖相同 | +| MindSpore master | - Ubuntu 18.04 aarch64
- Ubuntu 18.04 x86_64
- EulerOS 2.8 aarch64
- EulerOS 2.5 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- Ascend 910 AI处理器配套软件包（对应版本Atlas Data Center Solution V100R020C00T100）
- [gmp](https://gmplib.org/download/gmp/) 6.1.2
- 其他依赖项参见[requirements.txt](https://gitee.com/mindspore/mindspore/blob/r0.5/requirements.txt) | **编译依赖：**
- [Python](https://www.python.org/downloads/) 3.7.5
- Ascend 910 AI处理器配套软件包（对应版本Atlas Data Center Solution V100R020C00T100）
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [CMake](https://cmake.org/download/) >= 3.14.1
- [patch](http://ftp.gnu.org/gnu/patch/) >= 2.5
- [gmp](https://gmplib.org/download/gmp/) 6.1.2
**安装依赖：**
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。 - GCC 7.3.0可以直接通过apt命令安装。 @@ -82,7 +82,7 @@ 1. 从代码仓下载源码。 ```bash - git clone https://gitee.com/mindspore/mindspore.git + git clone https://gitee.com/mindspore/mindspore.git -b r0.5 ``` 2. 在源码根目录下，执行如下命令编译MindSpore。 @@ -160,7 +160,7 @@ | 版本号 | 操作系统 | 可执行文件安装依赖 | 源码编译安装依赖 | | ---- | :--- | :--- | :--- | -| MindInsight master | - Ubuntu 18.04 aarch64
- Ubuntu 18.04 x86_64
- EulerOS 2.8 aarch64
- EulerOS 2.5 x86_64
| - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- 其他依赖项参见[requirements.txt](https://gitee.com/mindspore/mindinsight/blob/master/requirements.txt) | **编译依赖：**
- [Python](https://www.python.org/downloads/) 3.7.5
- [CMake](https://cmake.org/download/) >= 3.14.1
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [node.js](https://nodejs.org/en/download/) >= 10.19.0
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [pybind11](https://pypi.org/project/pybind11/) >= 2.4.3
**安装依赖：**
与可执行文件安装依赖相同 | +| MindInsight master | - Ubuntu 18.04 aarch64
- Ubuntu 18.04 x86_64
- EulerOS 2.8 aarch64
- EulerOS 2.5 x86_64
| - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- 其他依赖项参见[requirements.txt](https://gitee.com/mindspore/mindinsight/blob/r0.5/requirements.txt) | **编译依赖：**
- [Python](https://www.python.org/downloads/) 3.7.5
- [CMake](https://cmake.org/download/) >= 3.14.1
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [node.js](https://nodejs.org/en/download/) >= 10.19.0
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [pybind11](https://pypi.org/project/pybind11/) >= 2.4.3
**安装依赖：**
与可执行文件安装依赖相同 | - 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。 @@ -185,7 +185,7 @@ 1. 从代码仓下载源码。 ```bash - git clone https://gitee.com/mindspore/mindinsight.git + git clone https://gitee.com/mindspore/mindinsight.git -b r0.5 ``` > **不能**直接在仓库主页下载zip包获取源码。 @@ -225,7 +225,7 @@ | 版本号 | 操作系统 | 可执行文件安装依赖 | 源码编译安装依赖 | | ---- | :--- | :--- | :--- | -| MindArmour master | - Ubuntu 18.04 aarch64
- Ubuntu 18.04 x86_64
- EulerOS 2.8 aarch64
- EulerOS 2.5 x86_64
| - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- 其他依赖项参见[setup.py](https://gitee.com/mindspore/mindarmour/blob/master/setup.py) | 与可执行文件安装依赖相同 | +| MindArmour master | - Ubuntu 18.04 aarch64
- Ubuntu 18.04 x86_64
- EulerOS 2.8 aarch64
- EulerOS 2.5 x86_64
| - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- 其他依赖项参见[setup.py](https://gitee.com/mindspore/mindarmour/blob/r0.5/setup.py) | 与可执行文件安装依赖相同 | - 在联网状态下，安装whl包时会自动下载`setup.py`中的依赖项，其余情况需自行安装。 @@ -250,7 +250,7 @@ 1. 从代码仓下载源码。 ```bash - git clone https://gitee.com/mindspore/mindarmour.git + git clone https://gitee.com/mindspore/mindarmour.git -b r0.5 ``` 2. 在源码根目录下，执行如下命令编译并安装MindArmour。 diff --git a/install/mindspore_d_install_en.md b/install/mindspore_d_install_en.md index 1b93cae8a6..6b215d072c 100644 --- a/install/mindspore_d_install_en.md +++ b/install/mindspore_d_install_en.md @@ -32,7 +32,7 @@ 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 master | - Ubuntu 18.04 aarch64
- Ubuntu 18.04 x86_64
- EulerOS 2.8 aarch64
- EulerOS 2.5 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- Ascend 910 AI processor software package(Version:Atlas Data Center Solution V100R020C00T100)
- [gmp](https://gmplib.org/download/gmp/) 6.1.2
- For details about other dependency items, see [requirements.txt](https://gitee.com/mindspore/mindspore/blob/master/requirements.txt). | **Compilation dependencies:**
- [Python](https://www.python.org/downloads/) 3.7.5
- Ascend 910 AI processor software package(Version:Atlas Data Center Solution V100R020C00T100)
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [CMake](https://cmake.org/download/) >= 3.14.1
- [patch](http://ftp.gnu.org/gnu/patch/) >= 2.5
- [gmp](https://gmplib.org/download/gmp/) 6.1.2
**Installation dependencies:**
same as the executable file installation dependencies. | +| MindSpore master | - Ubuntu 18.04 aarch64
- Ubuntu 18.04 x86_64
- EulerOS 2.8 aarch64
- EulerOS 2.5 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- Ascend 910 AI processor software package(Version:Atlas Data Center Solution V100R020C00T100)
- [gmp](https://gmplib.org/download/gmp/) 6.1.2
- For details about other dependency items, see [requirements.txt](https://gitee.com/mindspore/mindspore/blob/r0.5/requirements.txt). | **Compilation dependencies:**
- [Python](https://www.python.org/downloads/) 3.7.5
- Ascend 910 AI processor software package(Version:Atlas Data Center Solution V100R020C00T100)
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [CMake](https://cmake.org/download/) >= 3.14.1
- [patch](http://ftp.gnu.org/gnu/patch/) >= 2.5
- [gmp](https://gmplib.org/download/gmp/) 6.1.2
**Installation dependencies:**
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. - GCC 7.3.0 can be installed by using apt command. @@ -81,7 +81,7 @@ The compilation and installation must be performed on the Ascend 910 AI processo 1. Download the source code from the code repository. ```bash - git clone https://gitee.com/mindspore/mindspore.git + git clone https://gitee.com/mindspore/mindspore.git -b r0.5 ``` 2. Run the following command in the root directory of the source code to compile MindSpore: @@ -159,7 +159,7 @@ If you need to analyze information such as model scalars, graphs, and model trac | Version | Operating System | Executable File Installation Dependencies | Source Code Compilation and Installation Dependencies | | ---- | :--- | :--- | :--- | -| MindInsight master | - Ubuntu 18.04 aarch64
- Ubuntu 18.04 x86_64
- EulerOS 2.8 aarch64
- EulerOS 2.5 x86_64
| - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- For details about other dependency items, see [requirements.txt](https://gitee.com/mindspore/mindinsight/blob/master/requirements.txt). | **Compilation dependencies:**
- [Python](https://www.python.org/downloads/) 3.7.5
- [CMake](https://cmake.org/download/) >= 3.14.1
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [node.js](https://nodejs.org/en/download/) >= 10.19.0
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [pybind11](https://pypi.org/project/pybind11/) >= 2.4.3
**Installation dependencies:**
same as the executable file installation dependencies. | +| MindInsight master | - Ubuntu 18.04 aarch64
- Ubuntu 18.04 x86_64
- EulerOS 2.8 aarch64
- EulerOS 2.5 x86_64
| - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- For details about other dependency items, see [requirements.txt](https://gitee.com/mindspore/mindinsight/blob/r0.5/requirements.txt). | **Compilation dependencies:**
- [Python](https://www.python.org/downloads/) 3.7.5
- [CMake](https://cmake.org/download/) >= 3.14.1
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [node.js](https://nodejs.org/en/download/) >= 10.19.0
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [pybind11](https://pypi.org/project/pybind11/) >= 2.4.3
**Installation dependencies:**
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. @@ -184,7 +184,7 @@ If you need to analyze information such as model scalars, graphs, and model trac 1. Download the source code from the code repository. ```bash - git clone https://gitee.com/mindspore/mindinsight.git + git clone https://gitee.com/mindspore/mindinsight.git -b r0.5 ``` > You are **not** supposed to obtain the source code from the zip package downloaded from the repository homepage. @@ -226,7 +226,7 @@ If you need to conduct AI model security research or enhance the security of the | Version | Operating System | Executable File Installation Dependencies | Source Code Compilation and Installation Dependencies | | ---- | :--- | :--- | :--- | -| MindArmour master | - Ubuntu 18.04 aarch64
- Ubuntu 18.04 x86_64
- EulerOS 2.8 aarch64
- EulerOS 2.5 x86_64
| - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- 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. | +| MindArmour master | - Ubuntu 18.04 aarch64
- Ubuntu 18.04 x86_64
- EulerOS 2.8 aarch64
- EulerOS 2.5 x86_64
| - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- For details about other dependency items, see [setup.py](https://gitee.com/mindspore/mindarmour/blob/r0.5/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. @@ -251,7 +251,7 @@ If you need to conduct AI model security research or enhance the security of the 1. Download the source code from the code repository. ```bash - git clone https://gitee.com/mindspore/mindarmour.git + git clone https://gitee.com/mindspore/mindarmour.git -b r0.5 ``` 2. Run the following command in the root directory of the source code to compile and install MindArmour: diff --git a/install/mindspore_gpu_install.md b/install/mindspore_gpu_install.md index 7aa1e902ac..12f3da5107 100644 --- a/install/mindspore_gpu_install.md +++ b/install/mindspore_gpu_install.md @@ -28,7 +28,7 @@ | 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 master | Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- [CUDA 10.1](https://developer.nvidia.com/cuda-10.1-download-archive-base)
- [CuDNN](https://developer.nvidia.com/rdp/cudnn-archive) >= 7.6
- [OpenMPI](https://www.open-mpi.org/faq/?category=building#easy-build) 3.1.5 （可选，单机多卡/多机多卡训练需要）
- [NCCL](https://docs.nvidia.com/deeplearning/sdk/nccl-install-guide/index.html#debian) 2.4.8-1 （可选，单机多卡/多机多卡训练需要）
- 其他依赖项参见[requirements.txt](https://gitee.com/mindspore/mindspore/blob/master/requirements.txt) | **编译依赖：**
- [Python](https://www.python.org/downloads/) 3.7.5
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [CMake](https://cmake.org/download/) >= 3.14.1
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [patch](http://ftp.gnu.org/gnu/patch/) >= 2.5
- [Autoconf](https://www.gnu.org/software/autoconf) >= 2.69
- [Libtool](https://www.gnu.org/software/libtool) >= 2.4.6-29.fc30
- [Automake](https://www.gnu.org/software/automake) >= 1.15.1
- [CUDA 9.2](https://developer.nvidia.com/cuda-92-download-archive) / [CUDA 10.1](https://developer.nvidia.com/cuda-10.1-download-archive-base)
- [CuDNN](https://developer.nvidia.com/rdp/cudnn-archive) >= 7.6
**安装依赖：**
与可执行文件安装依赖相同 | +| MindSpore master | Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- [CUDA 10.1](https://developer.nvidia.com/cuda-10.1-download-archive-base)
- [CuDNN](https://developer.nvidia.com/rdp/cudnn-archive) >= 7.6
- [OpenMPI](https://www.open-mpi.org/faq/?category=building#easy-build) 3.1.5 （可选，单机多卡/多机多卡训练需要）
- [NCCL](https://docs.nvidia.com/deeplearning/sdk/nccl-install-guide/index.html#debian) 2.4.8-1 （可选，单机多卡/多机多卡训练需要）
- 其他依赖项参见[requirements.txt](https://gitee.com/mindspore/mindspore/blob/r0.5/requirements.txt) | **编译依赖：**
- [Python](https://www.python.org/downloads/) 3.7.5
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [CMake](https://cmake.org/download/) >= 3.14.1
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [patch](http://ftp.gnu.org/gnu/patch/) >= 2.5
- [Autoconf](https://www.gnu.org/software/autoconf) >= 2.69
- [Libtool](https://www.gnu.org/software/libtool) >= 2.4.6-29.fc30
- [Automake](https://www.gnu.org/software/automake) >= 1.15.1
- [CUDA 9.2](https://developer.nvidia.com/cuda-92-download-archive) / [CUDA 10.1](https://developer.nvidia.com/cuda-10.1-download-archive-base)
- [CuDNN](https://developer.nvidia.com/rdp/cudnn-archive) >= 7.6
**安装依赖：**
与可执行文件安装依赖相同 | - 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。 - 为了方便用户使用，MindSpore降低了对Autoconf、Libtool、Automake版本的依赖，可以使用系统自带版本。 @@ -63,7 +63,7 @@ 1. 从代码仓下载源码。 ```bash - git clone https://gitee.com/mindspore/mindspore.git + git clone https://gitee.com/mindspore/mindspore.git -b r0.5 ``` 2. 在源码根目录下执行如下命令编译MindSpore。 @@ -123,7 +123,7 @@ | 版本号 | 操作系统 | 可执行文件安装依赖 | 源码编译安装依赖 | | ---- | :--- | :--- | :--- | -| MindInsight master | - Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- 其他依赖项参见[requirements.txt](https://gitee.com/mindspore/mindinsight/blob/master/requirements.txt) | **编译依赖：**
- [Python](https://www.python.org/downloads/) 3.7.5
- [CMake](https://cmake.org/download/) >= 3.14.1
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [node.js](https://nodejs.org/en/download/) >= 10.19.0
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [pybind11](https://pypi.org/project/pybind11/) >= 2.4.3
**安装依赖：**
与可执行文件安装依赖相同 | +| MindInsight master | - Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- 其他依赖项参见[requirements.txt](https://gitee.com/mindspore/mindinsight/blob/r0.5/requirements.txt) | **编译依赖：**
- [Python](https://www.python.org/downloads/) 3.7.5
- [CMake](https://cmake.org/download/) >= 3.14.1
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [node.js](https://nodejs.org/en/download/) >= 10.19.0
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [pybind11](https://pypi.org/project/pybind11/) >= 2.4.3
**安装依赖：**
与可执行文件安装依赖相同 | - 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。 @@ -148,7 +148,7 @@ 1. 从代码仓下载源码。 ```bash - git clone https://gitee.com/mindspore/mindinsight.git + git clone https://gitee.com/mindspore/mindinsight.git -b r0.5 ``` > **不能**直接在仓库主页下载zip包获取源码。 @@ -188,7 +188,7 @@ | 版本号 | 操作系统 | 可执行文件安装依赖 | 源码编译安装依赖 | | ---------------------- | :------------------ | :----------------------------------------------------------- | :----------------------- | -| MindArmour master | Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- 其他依赖项参见[setup.py](https://gitee.com/mindspore/mindarmour/blob/master/setup.py) | 与可执行文件安装依赖相同 | +| MindArmour master | Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- 其他依赖项参见[setup.py](https://gitee.com/mindspore/mindarmour/blob/r0.5/setup.py) | 与可执行文件安装依赖相同 | - 在联网状态下，安装whl包时会自动下载`setup.py`中的依赖项，其余情况需自行安装。 @@ -213,7 +213,7 @@ 1. 从代码仓下载源码。 ```bash - git clone https://gitee.com/mindspore/mindarmour.git + git clone https://gitee.com/mindspore/mindarmour.git -b r0.5 ``` 2. 在源码根目录下，执行如下命令编译并安装MindArmour。 diff --git a/install/mindspore_gpu_install_en.md b/install/mindspore_gpu_install_en.md index 7507771b6e..ba51bbc117 100644 --- a/install/mindspore_gpu_install_en.md +++ b/install/mindspore_gpu_install_en.md @@ -28,7 +28,7 @@ This document describes how to quickly install MindSpore on a NVIDIA GPU environ | Version | Operating System | Executable File Installation Dependencies | Source Code Compilation and Installation Dependencies | | ---- | :--- | :--- | :--- | -| MindSpore master | Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- [CUDA 10.1](https://developer.nvidia.com/cuda-10.1-download-archive-base)
- [CuDNN](https://developer.nvidia.com/rdp/cudnn-archive) >= 7.6
- [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)
- [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)
- For details about other dependency items, see [requirements.txt](https://gitee.com/mindspore/mindspore/blob/master/requirements.txt). | **Compilation dependencies:**
- [Python](https://www.python.org/downloads/) 3.7.5
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [CMake](https://cmake.org/download/) >= 3.14.1
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [patch](http://ftp.gnu.org/gnu/patch/) >= 2.5
- [Autoconf](https://www.gnu.org/software/autoconf) >= 2.69
- [Libtool](https://www.gnu.org/software/libtool) >= 2.4.6-29.fc30
- [Automake](https://www.gnu.org/software/automake) >= 1.15.1
- [CUDA 9.2](https://developer.nvidia.com/cuda-92-download-archive) / [CUDA 10.1](https://developer.nvidia.com/cuda-10.1-download-archive-base)
- [CuDNN](https://developer.nvidia.com/rdp/cudnn-archive) >= 7.6
**Installation dependencies:**
same as the executable file installation dependencies. | +| MindSpore master | Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- [CUDA 10.1](https://developer.nvidia.com/cuda-10.1-download-archive-base)
- [CuDNN](https://developer.nvidia.com/rdp/cudnn-archive) >= 7.6
- [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)
- [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)
- For details about other dependency items, see [requirements.txt](https://gitee.com/mindspore/mindspore/blob/r0.5/requirements.txt). | **Compilation dependencies:**
- [Python](https://www.python.org/downloads/) 3.7.5
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [CMake](https://cmake.org/download/) >= 3.14.1
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [patch](http://ftp.gnu.org/gnu/patch/) >= 2.5
- [Autoconf](https://www.gnu.org/software/autoconf) >= 2.69
- [Libtool](https://www.gnu.org/software/libtool) >= 2.4.6-29.fc30
- [Automake](https://www.gnu.org/software/automake) >= 1.15.1
- [CUDA 9.2](https://developer.nvidia.com/cuda-92-download-archive) / [CUDA 10.1](https://developer.nvidia.com/cuda-10.1-download-archive-base)
- [CuDNN](https://developer.nvidia.com/rdp/cudnn-archive) >= 7.6
**Installation dependencies:**
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. - 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. @@ -63,7 +63,7 @@ This document describes how to quickly install MindSpore on a NVIDIA GPU environ 1. Download the source code from the code repository. ```bash - git clone https://gitee.com/mindspore/mindspore.git + git clone https://gitee.com/mindspore/mindspore.git -b r0.5 ``` 2. Run the following command in the root directory of the source code to compile MindSpore: @@ -123,7 +123,7 @@ If you need to analyze information such as model scalars, graphs, and model trac | Version | Operating System | Executable File Installation Dependencies | Source Code Compilation and Installation Dependencies | | ---- | :--- | :--- | :--- | -| MindInsight master | - Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- For details about other dependency items, see [requirements.txt](https://gitee.com/mindspore/mindinsight/blob/master/requirements.txt). | **Compilation dependencies:**
- [Python](https://www.python.org/downloads/) 3.7.5
- [CMake](https://cmake.org/download/) >= 3.14.1
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [node.js](https://nodejs.org/en/download/) >= 10.19.0
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [pybind11](https://pypi.org/project/pybind11/) >= 2.4.3
**Installation dependencies:**
same as the executable file installation dependencies. | +| MindInsight master | - Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- For details about other dependency items, see [requirements.txt](https://gitee.com/mindspore/mindinsight/blob/r0.5/requirements.txt). | **Compilation dependencies:**
- [Python](https://www.python.org/downloads/) 3.7.5
- [CMake](https://cmake.org/download/) >= 3.14.1
- [GCC](https://gcc.gnu.org/releases.html) 7.3.0
- [node.js](https://nodejs.org/en/download/) >= 10.19.0
- [wheel](https://pypi.org/project/wheel/) >= 0.32.0
- [pybind11](https://pypi.org/project/pybind11/) >= 2.4.3
**Installation dependencies:**
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. @@ -148,7 +148,7 @@ If you need to analyze information such as model scalars, graphs, and model trac 1. Download the source code from the code repository. ```bash - git clone https://gitee.com/mindspore/mindinsight.git + git clone https://gitee.com/mindspore/mindinsight.git -b r0.5 ``` > You are **not** supposed to obtain the source code from the zip package downloaded from the repository homepage. @@ -190,7 +190,7 @@ If you need to conduct AI model security research or enhance the security of the | Version | Operating System | Executable File Installation Dependencies | Source Code Compilation and Installation Dependencies | | ---- | :--- | :--- | :--- | -| MindArmour master | Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- 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. | +| MindArmour master | Ubuntu 18.04 x86_64 | - [Python](https://www.python.org/downloads/) 3.7.5
- MindSpore master
- For details about other dependency items, see [setup.py](https://gitee.com/mindspore/mindarmour/blob/r0.5/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. @@ -215,7 +215,7 @@ If you need to conduct AI model security research or enhance the security of the 1. Download the source code from the code repository. ```bash - git clone https://gitee.com/mindspore/mindarmour.git + git clone https://gitee.com/mindspore/mindarmour.git -b r0.5 ``` 2. Run the following command in the root directory of the source code to compile and install MindArmour: diff --git a/resource/faq/FAQ_en.md b/resource/faq/FAQ_en.md index 5815ab26b8..3630c1c979 100644 --- a/resource/faq/FAQ_en.md +++ b/resource/faq/FAQ_en.md @@ -68,7 +68,7 @@ A: Please install the software manually if there is any suggestion of certain `s Q: What types of model is currently supported by MindSpore for training ? -A: MindSpore has basic support for common training scenarios, please refer to [Release note](https://gitee.com/mindspore/mindspore/blob/master/RELEASE.md) for detailed information. +A: MindSpore has basic support for common training scenarios, please refer to [Release note](https://gitee.com/mindspore/mindspore/blob/r0.5/RELEASE.md) for detailed information.
@@ -92,7 +92,7 @@ A: MindSpore provides pluggable device management interface so that developer co Q: What hardware does MindSpore require? -A: Currently, you can try out MindSpore through Docker images on laptops or in environments with GPUs. Some models in MindSpore Model Zoo support GPU-based training and inference, and other models are being improved. For distributed parallel training, MindSpore supports multi-GPU training. You can obtain the latest information from [RoadMap](https://www.mindspore.cn/docs/en/master/roadmap.html) and project [Release Notes](https://gitee.com/mindspore/mindspore/blob/master/RELEASE.md). +A: Currently, you can try out MindSpore through Docker images on laptops or in environments with GPUs. Some models in MindSpore Model Zoo support GPU-based training and inference, and other models are being improved. For distributed parallel training, MindSpore supports multi-GPU training. You can obtain the latest information from [RoadMap](https://www.mindspore.cn/docs/en/master/roadmap.html) and project [Release Notes](https://gitee.com/mindspore/mindspore/blob/r0.5/RELEASE.md). ### System Support diff --git a/resource/faq/FAQ_zh_cn.md b/resource/faq/FAQ_zh_cn.md index 3ee10f6b70..68929bd7d2 100644 --- a/resource/faq/FAQ_zh_cn.md +++ b/resource/faq/FAQ_zh_cn.md @@ -67,7 +67,7 @@ A：当有此提示时说明要用户安装`tclsh`；如果仍提示缺少其他 Q：MindSpore支持哪些模型的训练？ -A：MindSpore针对典型场景均有模型训练支持，支持情况详见[Release note](https://gitee.com/mindspore/mindspore/blob/master/RELEASE.md)。 +A：MindSpore针对典型场景均有模型训练支持，支持情况详见[Release note](https://gitee.com/mindspore/mindspore/blob/r0.5/RELEASE.md)。
@@ -91,7 +91,7 @@ A：MindSpore提供了可插拔式的设备管理接口，其他计算单元（ Q：MindSpore需要什么硬件支持？ -A：目前笔记本电脑或者有GPU的环境，都可以通过Docker镜像来试用。当前MindSpore Model Zoo中有部分模型已经支持GPU的训练和推理，其他模型也在不断地进行完善。在分布式并行训练方面，MindSpore当前支持GPU多卡训练。你可以通过[RoadMap](https://www.mindspore.cn/docs/zh-CN/master/roadmap.html)和项目[Release note](https://gitee.com/mindspore/mindspore/blob/master/RELEASE.md)获取最新信息。 +A：目前笔记本电脑或者有GPU的环境，都可以通过Docker镜像来试用。当前MindSpore Model Zoo中有部分模型已经支持GPU的训练和推理，其他模型也在不断地进行完善。在分布式并行训练方面，MindSpore当前支持GPU多卡训练。你可以通过[RoadMap](https://www.mindspore.cn/docs/zh-CN/master/roadmap.html)和项目[Release note](https://gitee.com/mindspore/mindspore/blob/r0.5/RELEASE.md)获取最新信息。 ### 系统支持 diff --git a/tutorials/notebook/quick_start.ipynb b/tutorials/notebook/quick_start.ipynb index da57dbd4aa..31fec669e4 100644 --- a/tutorials/notebook/quick_start.ipynb +++ b/tutorials/notebook/quick_start.ipynb @@ -34,7 +34,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "说明：
你可以在这里找到完整可运行的样例代码：https://gitee.com/mindspore/docs/blob/master/tutorials/tutorial_code/lenet.py" + "说明：
你可以在这里找到完整可运行的样例代码：https://gitee.com/mindspore/docs/blob/r0.5/tutorials/tutorial_code/lenet.py" ] }, { diff --git a/tutorials/source_en/advanced_use/computer_vision_application.md b/tutorials/source_en/advanced_use/computer_vision_application.md index be0522cd85..70fbc929a5 100644 --- a/tutorials/source_en/advanced_use/computer_vision_application.md +++ b/tutorials/source_en/advanced_use/computer_vision_application.md @@ -16,7 +16,7 @@ - + ## Overview @@ -64,7 +64,7 @@ Next, let's use MindSpore to solve the image classification task. The overall pr 5. Call the high-level `Model` API to train and save the model file. 6. Load the saved model for inference. -> This example is for the hardware platform of the Ascend 910 AI processor. You can find the complete executable sample code at： . +> This example is for the hardware platform of the Ascend 910 AI processor. You can find the complete executable sample code at： . The key parts of the task process code are explained below. diff --git a/tutorials/source_en/advanced_use/customized_debugging_information.md b/tutorials/source_en/advanced_use/customized_debugging_information.md index d7721e19b3..3e18520988 100644 --- a/tutorials/source_en/advanced_use/customized_debugging_information.md +++ b/tutorials/source_en/advanced_use/customized_debugging_information.md @@ -14,7 +14,7 @@ - + ## Overview diff --git a/tutorials/source_en/advanced_use/dashboard_and_lineage.md b/tutorials/source_en/advanced_use/dashboard_and_lineage.md index 551be944c7..8fc357c4b4 100644 --- a/tutorials/source_en/advanced_use/dashboard_and_lineage.md +++ b/tutorials/source_en/advanced_use/dashboard_and_lineage.md @@ -21,7 +21,7 @@ - + ## Overview Scalars, images, computational graphs, and model hyperparameters during training are recorded in files and can be viewed on the web page. diff --git a/tutorials/source_en/advanced_use/debugging_in_pynative_mode.md b/tutorials/source_en/advanced_use/debugging_in_pynative_mode.md index 1142684a4e..569b3a8efd 100644 --- a/tutorials/source_en/advanced_use/debugging_in_pynative_mode.md +++ b/tutorials/source_en/advanced_use/debugging_in_pynative_mode.md @@ -11,7 +11,7 @@ - + ## Overview diff --git a/tutorials/source_en/advanced_use/differential_privacy.md b/tutorials/source_en/advanced_use/differential_privacy.md index 50717af4aa..b38b5c1034 100644 --- a/tutorials/source_en/advanced_use/differential_privacy.md +++ b/tutorials/source_en/advanced_use/differential_privacy.md @@ -14,7 +14,7 @@ - + ## Overview diff --git a/tutorials/source_en/advanced_use/distributed_training.md b/tutorials/source_en/advanced_use/distributed_training.md index 20cd61d625..eb249ee93c 100644 --- a/tutorials/source_en/advanced_use/distributed_training.md +++ b/tutorials/source_en/advanced_use/distributed_training.md @@ -18,7 +18,7 @@ - + ## Overview In deep learning, the increasing number of datasets and parameters prolongs the training time and requires more hardware resources, becoming a training bottleneck. Parallel distributed training is an important optimization method for training, which can reduce requirements on hardware, such as memory and computing performance. Based on different parallel principles and modes, parallelism is generally classified into the following types: @@ -34,7 +34,7 @@ MindSpore also provides the parallel distributed training function. It supports This tutorial describes how to train the ResNet-50 network in data parallel and automatic parallel modes on MindSpore. > The example in this tutorial applies to hardware platforms based on the Ascend 910 AI processor, whereas does not support CPU and GPU scenarios. -> Download address of the complete sample code: +> Download address of the complete sample code: ## Preparations @@ -177,7 +177,7 @@ Different from the single-node system, the multi-node system needs to transfer t ## Defining the Network -In data parallel and automatic parallel modes, the network definition method is the same as that in a single-node system. The reference code is as follows: +In data parallel and automatic parallel modes, the network definition method is the same as that in a single-node system. The reference code is as follows: ## Defining the Loss Function and Optimizer diff --git a/tutorials/source_en/advanced_use/mixed_precision.md b/tutorials/source_en/advanced_use/mixed_precision.md index b88cbd8ec2..1f09f5bca7 100644 --- a/tutorials/source_en/advanced_use/mixed_precision.md +++ b/tutorials/source_en/advanced_use/mixed_precision.md @@ -10,7 +10,7 @@ - + ## Overview diff --git a/tutorials/source_en/advanced_use/model_security.md b/tutorials/source_en/advanced_use/model_security.md index 0b4990aace..7774c16c1a 100644 --- a/tutorials/source_en/advanced_use/model_security.md +++ b/tutorials/source_en/advanced_use/model_security.md @@ -15,7 +15,7 @@ - + ## Overview diff --git a/tutorials/source_en/advanced_use/network_migration.md b/tutorials/source_en/advanced_use/network_migration.md index 9f396fe548..656ba30e10 100644 --- a/tutorials/source_en/advanced_use/network_migration.md +++ b/tutorials/source_en/advanced_use/network_migration.md @@ -79,7 +79,7 @@ The ResNet-50 network migration and training on the Ascend 910 is used as an exa num_shards=device_num, shard_id=rank_id) ``` - Then, perform data augmentation, data cleaning, and batch processing. For details about the code, see . + Then, perform data augmentation, data cleaning, and batch processing. For details about the code, see . 3. Build a network. @@ -214,7 +214,7 @@ The ResNet-50 network migration and training on the Ascend 910 is used as an exa 6. Build the entire network. - The [ResNet-50](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/resnet/src/resnet.py) network structure is formed by connecting multiple defined subnets. Follow the rule of defining subnets before using them and define all the subnets used in the `__init__` and connect subnets in the `construct`. + The [ResNet-50](https://gitee.com/mindspore/mindspore/blob/r0.5/model_zoo/resnet/src/resnet.py) network structure is formed by connecting multiple defined subnets. Follow the rule of defining subnets before using them and define all the subnets used in the `__init__` and connect subnets in the `construct`. 7. Define a loss function and an optimizer. diff --git a/tutorials/source_en/advanced_use/nlp_application.md b/tutorials/source_en/advanced_use/nlp_application.md index 1d2b11258b..cd7becd13c 100644 --- a/tutorials/source_en/advanced_use/nlp_application.md +++ b/tutorials/source_en/advanced_use/nlp_application.md @@ -20,7 +20,7 @@ - + ## Overview diff --git a/tutorials/source_en/advanced_use/on_device_inference.md b/tutorials/source_en/advanced_use/on_device_inference.md index f3ddc120b3..f8c1309518 100644 --- a/tutorials/source_en/advanced_use/on_device_inference.md +++ b/tutorials/source_en/advanced_use/on_device_inference.md @@ -11,7 +11,7 @@ - + ## Overview @@ -60,7 +60,7 @@ The compilation procedure is as follows: 2. Download source code from the code repository. ```bash - git clone https://gitee.com/mindspore/mindspore.git + git clone https://gitee.com/mindspore/mindspore.git -b r0.5 ``` 3. Run the following command in the root directory of the source code to compile MindSpore Predict: -I indicates options for compiling MindSpore Predict and the parameter is the target platform architecture. Currently, only the Android arm64 platform is supported. diff --git a/tutorials/source_en/advanced_use/performance_profiling.md b/tutorials/source_en/advanced_use/performance_profiling.md index 2162cbcb5a..f251dd4c31 100644 --- a/tutorials/source_en/advanced_use/performance_profiling.md +++ b/tutorials/source_en/advanced_use/performance_profiling.md @@ -16,7 +16,7 @@ - + ## Overview Performance data like operators' execution time are recorded in files and can be viewed on the web page, this can help the user optimize the performance of neural networks. MindInsight Profiler can only support the Ascend chip now. diff --git a/tutorials/source_en/quick_start/quick_start.md b/tutorials/source_en/quick_start/quick_start.md index 500c9614e3..9fdc7698c3 100644 --- a/tutorials/source_en/quick_start/quick_start.md +++ b/tutorials/source_en/quick_start/quick_start.md @@ -24,7 +24,7 @@ - + ## Overview @@ -38,7 +38,7 @@ During the practice, a simple image classification function is implemented. The 5. Load the saved model for inference. 6. Validate the model, load the test dataset and trained model, and validate the result accuracy. -> You can find the complete executable sample code at . +> You can find the complete executable sample code at . This is a simple and basic application process. For other advanced and complex applications, extend this basic process as needed. diff --git a/tutorials/source_en/use/custom_operator.md b/tutorials/source_en/use/custom_operator.md index c6f4296a3d..db1224ffff 100644 --- a/tutorials/source_en/use/custom_operator.md +++ b/tutorials/source_en/use/custom_operator.md @@ -14,7 +14,7 @@ - + ## Overview diff --git a/tutorials/source_en/use/data_preparation/converting_datasets.md b/tutorials/source_en/use/data_preparation/converting_datasets.md index 11ea33c866..966794ca30 100644 --- a/tutorials/source_en/use/data_preparation/converting_datasets.md +++ b/tutorials/source_en/use/data_preparation/converting_datasets.md @@ -14,7 +14,7 @@ - + ## Overview diff --git a/tutorials/source_en/use/data_preparation/data_processing_and_augmentation.md b/tutorials/source_en/use/data_preparation/data_processing_and_augmentation.md index ee669c4d34..6fa0aec89d 100644 --- a/tutorials/source_en/use/data_preparation/data_processing_and_augmentation.md +++ b/tutorials/source_en/use/data_preparation/data_processing_and_augmentation.md @@ -16,7 +16,7 @@ - + ## Overview diff --git a/tutorials/source_en/use/data_preparation/loading_the_datasets.md b/tutorials/source_en/use/data_preparation/loading_the_datasets.md index 4ffaf9de19..2041da36da 100644 --- a/tutorials/source_en/use/data_preparation/loading_the_datasets.md +++ b/tutorials/source_en/use/data_preparation/loading_the_datasets.md @@ -13,7 +13,7 @@ - + ## Overview diff --git a/tutorials/source_en/use/multi_platform_inference.md b/tutorials/source_en/use/multi_platform_inference.md index 373dc9b634..e8731b46b9 100644 --- a/tutorials/source_en/use/multi_platform_inference.md +++ b/tutorials/source_en/use/multi_platform_inference.md @@ -8,7 +8,7 @@ - + ## Overview @@ -16,7 +16,7 @@ Models based on MindSpore training can be used for inference on different hardwa 1. Inference on the Ascend 910 AI processor - MindSpore provides the `model.eval` API for model validation. You only need to import the validation dataset. The processing method of the validation dataset is the same as that of the training dataset. For details about the complete code, see . + MindSpore provides the `model.eval` API for model validation. You only need to import the validation dataset. The processing method of the validation dataset is the same as that of the training dataset. For details about the complete code, see . ```python res = model.eval(dataset) diff --git a/tutorials/source_en/use/saving_and_loading_model_parameters.md b/tutorials/source_en/use/saving_and_loading_model_parameters.md index 78fc04726f..2bd4bb7806 100644 --- a/tutorials/source_en/use/saving_and_loading_model_parameters.md +++ b/tutorials/source_en/use/saving_and_loading_model_parameters.md @@ -13,7 +13,7 @@ - + ## Overview diff --git a/tutorials/source_zh_cn/advanced_use/aware_quantization.md b/tutorials/source_zh_cn/advanced_use/aware_quantization.md index fcb5a520ae..9f831fe06f 100644 --- a/tutorials/source_zh_cn/advanced_use/aware_quantization.md +++ b/tutorials/source_zh_cn/advanced_use/aware_quantization.md @@ -12,7 +12,7 @@ - + ## 概述 diff --git a/tutorials/source_zh_cn/advanced_use/checkpoint_for_hybrid_parallel.md b/tutorials/source_zh_cn/advanced_use/checkpoint_for_hybrid_parallel.md index 6aaf7eb9e7..63bf4733a8 100644 --- a/tutorials/source_zh_cn/advanced_use/checkpoint_for_hybrid_parallel.md +++ b/tutorials/source_zh_cn/advanced_use/checkpoint_for_hybrid_parallel.md @@ -26,7 +26,7 @@ - + ## 概述 diff --git a/tutorials/source_zh_cn/advanced_use/computer_vision_application.md b/tutorials/source_zh_cn/advanced_use/computer_vision_application.md index d8839c1b94..6497d34f07 100644 --- a/tutorials/source_zh_cn/advanced_use/computer_vision_application.md +++ b/tutorials/source_zh_cn/advanced_use/computer_vision_application.md @@ -16,7 +16,7 @@ - + ## 概述 @@ -65,7 +65,7 @@ MindSpore当前支持的图像分类网络包括：典型网络LeNet、AlexNet 6. 加载保存的模型进行推理 -> 本例面向Ascend 910 AI处理器硬件平台，你可以在这里下载完整的样例代码： +> 本例面向Ascend 910 AI处理器硬件平台，你可以在这里下载完整的样例代码： 下面对任务流程中各个环节及代码关键片段进行解释说明。 diff --git a/tutorials/source_zh_cn/advanced_use/customized_debugging_information.md b/tutorials/source_zh_cn/advanced_use/customized_debugging_information.md index 9febbe7c2e..2e25b94c22 100644 --- a/tutorials/source_zh_cn/advanced_use/customized_debugging_information.md +++ b/tutorials/source_zh_cn/advanced_use/customized_debugging_information.md @@ -13,7 +13,7 @@ - + ## 概述 diff --git a/tutorials/source_zh_cn/advanced_use/dashboard_and_lineage.md b/tutorials/source_zh_cn/advanced_use/dashboard_and_lineage.md index 97512495b4..d962ca944b 100644 --- a/tutorials/source_zh_cn/advanced_use/dashboard_and_lineage.md +++ b/tutorials/source_zh_cn/advanced_use/dashboard_and_lineage.md @@ -21,7 +21,7 @@ - + ## 概述 训练过程中的标量、图像、计算图以及模型超参等信息记录到文件中，通过可视化界面供用户查看。 diff --git a/tutorials/source_zh_cn/advanced_use/debugging_in_pynative_mode.md b/tutorials/source_zh_cn/advanced_use/debugging_in_pynative_mode.md index 08ac3f3f4d..c5a3e29d10 100644 --- a/tutorials/source_zh_cn/advanced_use/debugging_in_pynative_mode.md +++ b/tutorials/source_zh_cn/advanced_use/debugging_in_pynative_mode.md @@ -11,7 +11,7 @@ - + ## 概述 diff --git a/tutorials/source_zh_cn/advanced_use/differential_privacy.md b/tutorials/source_zh_cn/advanced_use/differential_privacy.md index 84c381f7cf..7dbaf65499 100644 --- a/tutorials/source_zh_cn/advanced_use/differential_privacy.md +++ b/tutorials/source_zh_cn/advanced_use/differential_privacy.md @@ -1,6 +1,6 @@ # 机器学习中的差分隐私 - + ## 概述 diff --git a/tutorials/source_zh_cn/advanced_use/distributed_training.md b/tutorials/source_zh_cn/advanced_use/distributed_training.md index 52627db1c5..4044307d69 100644 --- a/tutorials/source_zh_cn/advanced_use/distributed_training.md +++ b/tutorials/source_zh_cn/advanced_use/distributed_training.md @@ -18,7 +18,7 @@ - + ## 概述 在深度学习中，当数据集和参数量的规模越来越大，训练所需的时间和硬件资源会随之增加，最后会变成制约训练的瓶颈。分布式并行训练，可以降低对内存、计算性能等硬件的需求，是进行训练的重要优化手段。根据并行的原理及模式不同，业界主流的并行类型有以下几种： @@ -34,7 +34,7 @@ 本篇教程我们主要讲解如何在MindSpore上通过数据并行及自动并行模式训练ResNet-50网络。 > 本例面向Ascend 910 AI处理器硬件平台，暂不支持CPU和GPU场景。 -> 你可以在这里下载完整的样例代码： +> 你可以在这里下载完整的样例代码： ## 准备环节 @@ -175,7 +175,7 @@ def create_dataset(data_path, repeat_num=1, batch_size=32, rank_id=0, rank_size= ## 定义网络 -数据并行及自动并行模式下，网络定义方式与单机一致。代码请参考： +数据并行及自动并行模式下，网络定义方式与单机一致。代码请参考： ## 定义损失函数及优化器 diff --git a/tutorials/source_zh_cn/advanced_use/graph_kernel_fusion.md b/tutorials/source_zh_cn/advanced_use/graph_kernel_fusion.md index 3f53b6c3fc..294d91046e 100644 --- a/tutorials/source_zh_cn/advanced_use/graph_kernel_fusion.md +++ b/tutorials/source_zh_cn/advanced_use/graph_kernel_fusion.md @@ -12,7 +12,7 @@ - + ## 概述 diff --git a/tutorials/source_zh_cn/advanced_use/mixed_precision.md b/tutorials/source_zh_cn/advanced_use/mixed_precision.md index 4cacb8c7a4..4df6ab97df 100644 --- a/tutorials/source_zh_cn/advanced_use/mixed_precision.md +++ b/tutorials/source_zh_cn/advanced_use/mixed_precision.md @@ -10,7 +10,7 @@ - + ## 概述 diff --git a/tutorials/source_zh_cn/advanced_use/model_security.md b/tutorials/source_zh_cn/advanced_use/model_security.md index 9daf517e31..198b20eb4b 100644 --- a/tutorials/source_zh_cn/advanced_use/model_security.md +++ b/tutorials/source_zh_cn/advanced_use/model_security.md @@ -15,7 +15,7 @@ - + ## 概述 diff --git a/tutorials/source_zh_cn/advanced_use/network_migration.md b/tutorials/source_zh_cn/advanced_use/network_migration.md index 8d3f574dbe..6d0aa8f27f 100644 --- a/tutorials/source_zh_cn/advanced_use/network_migration.md +++ b/tutorials/source_zh_cn/advanced_use/network_migration.md @@ -17,7 +17,7 @@ - + ## 概述 @@ -77,7 +77,7 @@ MindSpore与TensorFlow、PyTorch在网络结构组织方式上，存在一定差 num_shards=device_num, shard_id=rank_id) ``` - 然后对数据进行了数据增强、数据清洗和批处理等操作。代码详见。 + 然后对数据进行了数据增强、数据清洗和批处理等操作。代码详见。 3. 构建网络。 @@ -210,7 +210,7 @@ MindSpore与TensorFlow、PyTorch在网络结构组织方式上，存在一定差 6. 构造整网。 - 将定义好的多个子网连接起来就是整个[ResNet-50](https://gitee.com/mindspore/mindspore/blob/master/model_zoo/resnet/src/resnet.py)网络的结构了。同样遵循先定义后使用的原则，在`__init__`中定义所有用到的子网，在`construct`中连接子网。 + 将定义好的多个子网连接起来就是整个[ResNet-50](https://gitee.com/mindspore/mindspore/blob/r0.5/model_zoo/resnet/src/resnet.py)网络的结构了。同样遵循先定义后使用的原则，在`__init__`中定义所有用到的子网，在`construct`中连接子网。 7. 定义损失函数和优化器。 diff --git a/tutorials/source_zh_cn/advanced_use/nlp_application.md b/tutorials/source_zh_cn/advanced_use/nlp_application.md index ace94f759d..f42511a1a9 100644 --- a/tutorials/source_zh_cn/advanced_use/nlp_application.md +++ b/tutorials/source_zh_cn/advanced_use/nlp_application.md @@ -20,7 +20,7 @@ - + ## 概述 diff --git a/tutorials/source_zh_cn/advanced_use/on_device_inference.md b/tutorials/source_zh_cn/advanced_use/on_device_inference.md index eb224de000..7de3f8f563 100644 --- a/tutorials/source_zh_cn/advanced_use/on_device_inference.md +++ b/tutorials/source_zh_cn/advanced_use/on_device_inference.md @@ -11,7 +11,7 @@ - + ## 概述 @@ -59,7 +59,7 @@ MindSpore Predict是一个轻量级的深度神经网络推理引擎，提供了 2. 从代码仓下载源码。 ```bash - git clone https://gitee.com/mindspore/mindspore.git + git clone https://gitee.com/mindspore/mindspore.git -b r0.5 ``` 3. 在源码根目录下，执行如下命令编译MindSpore Predict。-I为编译MindSpore Predict的编译参数，-I的参数为目标端侧平台，目前仅支持安卓arm64平台。 diff --git a/tutorials/source_zh_cn/advanced_use/performance_profiling.md b/tutorials/source_zh_cn/advanced_use/performance_profiling.md index ee36edfad6..8cb5ad4b5b 100644 --- a/tutorials/source_zh_cn/advanced_use/performance_profiling.md +++ b/tutorials/source_zh_cn/advanced_use/performance_profiling.md @@ -17,7 +17,7 @@ - + ## 概述 将训练过程中的算子耗时等信息记录到文件中，通过可视化界面供用户查看分析，帮助用户更高效地调试神经网络性能。目前仅支持在Ascend芯片上的性能调试。 diff --git a/tutorials/source_zh_cn/advanced_use/use_on_the_cloud.md b/tutorials/source_zh_cn/advanced_use/use_on_the_cloud.md index 8b6a147e31..3f74f6b321 100644 --- a/tutorials/source_zh_cn/advanced_use/use_on_the_cloud.md +++ b/tutorials/source_zh_cn/advanced_use/use_on_the_cloud.md @@ -24,7 +24,7 @@ - + ## 概述 diff --git a/tutorials/source_zh_cn/quick_start/quick_start.md b/tutorials/source_zh_cn/quick_start/quick_start.md index 19a7c8e7a4..a06cb6ea4b 100644 --- a/tutorials/source_zh_cn/quick_start/quick_start.md +++ b/tutorials/source_zh_cn/quick_start/quick_start.md @@ -24,9 +24,9 @@ - +    - + ## 概述 @@ -40,7 +40,7 @@ 5. 加载保存的模型，进行推理。 6. 验证模型，加载测试数据集和训练后的模型，验证结果精度。 -> 你可以在这里找到完整可运行的样例代码： 。 +> 你可以在这里找到完整可运行的样例代码： 。 这是简单、基础的应用流程，其他高级、复杂的应用可以基于这个基本流程进行扩展。 diff --git a/tutorials/source_zh_cn/quick_start/quick_video.md b/tutorials/source_zh_cn/quick_start/quick_video.md index ccc368390d..5f0e8be9f6 100644 --- a/tutorials/source_zh_cn/quick_start/quick_video.md +++ b/tutorials/source_zh_cn/quick_start/quick_video.md @@ -43,7 +43,7 @@ -**查看代码**： +**查看代码**： ### 模型参数保存与加载 diff --git a/tutorials/source_zh_cn/use/custom_operator.md b/tutorials/source_zh_cn/use/custom_operator.md index 064b271fd8..891c6502a8 100644 --- a/tutorials/source_zh_cn/use/custom_operator.md +++ b/tutorials/source_zh_cn/use/custom_operator.md @@ -14,7 +14,7 @@ - + ## 概述 diff --git a/tutorials/source_zh_cn/use/data_preparation/converting_datasets.md b/tutorials/source_zh_cn/use/data_preparation/converting_datasets.md index ba744652da..84f9184055 100644 --- a/tutorials/source_zh_cn/use/data_preparation/converting_datasets.md +++ b/tutorials/source_zh_cn/use/data_preparation/converting_datasets.md @@ -14,7 +14,7 @@ - + ## 概述 diff --git a/tutorials/source_zh_cn/use/data_preparation/data_processing_and_augmentation.md b/tutorials/source_zh_cn/use/data_preparation/data_processing_and_augmentation.md index 190440fb1e..a5537f1e96 100644 --- a/tutorials/source_zh_cn/use/data_preparation/data_processing_and_augmentation.md +++ b/tutorials/source_zh_cn/use/data_preparation/data_processing_and_augmentation.md @@ -16,7 +16,7 @@ - + ## 概述 diff --git a/tutorials/source_zh_cn/use/data_preparation/loading_the_datasets.md b/tutorials/source_zh_cn/use/data_preparation/loading_the_datasets.md index 26ddc142db..974d59331b 100644 --- a/tutorials/source_zh_cn/use/data_preparation/loading_the_datasets.md +++ b/tutorials/source_zh_cn/use/data_preparation/loading_the_datasets.md @@ -13,7 +13,7 @@ - + ## 概述 diff --git a/tutorials/source_zh_cn/use/multi_platform_inference.md b/tutorials/source_zh_cn/use/multi_platform_inference.md index 3d2bb3fb10..6df770d36d 100644 --- a/tutorials/source_zh_cn/use/multi_platform_inference.md +++ b/tutorials/source_zh_cn/use/multi_platform_inference.md @@ -19,7 +19,7 @@ - + ## 概述 @@ -60,7 +60,7 @@ CPU | ONNX格式 | 支持ONNX推理的runtime/SDK，如TensorRT。 ``` 其中， `model.eval`为模型验证接口，对应接口说明：。 - > 推理样例代码：。 + > 推理样例代码：。 2. 使用`model.predict`接口来进行推理操作。 ```python diff --git a/tutorials/source_zh_cn/use/saving_and_loading_model_parameters.md b/tutorials/source_zh_cn/use/saving_and_loading_model_parameters.md index dc4848e187..111c493105 100644 --- a/tutorials/source_zh_cn/use/saving_and_loading_model_parameters.md +++ b/tutorials/source_zh_cn/use/saving_and_loading_model_parameters.md @@ -13,7 +13,7 @@ - + ## 概述 -- Gitee