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README.md
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@ -1,14 +1,15 @@
![MindSpore Logo](docs/MindSpore-logo.png "MindSpore logo")
============================================================
[查看中文](./README_CN.md)
<!-- TOC -->
- [What Is MindSpore](#what-is-mindspore)
- [Automatic Differentiation](#automatic-differentiation)
- [Automatic Parallel](#automatic-parallel)
- [Installation](#installation)
- [Binaries](#binaries)
- [From Source](#from-source)
- [Pip mode method installation](#pip-mode-method-installation)
- [Source code compilation installation](#source-code-compilation-installation)
- [Docker Image](#docker-image)
- [Quickstart](#quickstart)
- [Docs](#docs)
@ -16,9 +17,13 @@
- [Governance](#governance)
- [Communication](#communication)
- [Contributing](#contributing)
- [Maintenance phases](#maintenance-phases)
- [Maintenance status](#maintenance-status)
- [Release Notes](#release-notes)
- [License](#license)
<!-- /TOC -->
## What Is MindSpore
MindSpore is a new open source deep learning training/inference framework that
@ -59,7 +64,7 @@ At present, MindSpore uses a fine-grained parallel strategy of splitting operato
## Installation
### Binaries
### Pip mode method installation
MindSpore offers build options across multiple backends:
@ -80,7 +85,7 @@ For installation using `pip`, take `CPU` and `Ubuntu-x86` build version as an ex
1. Download whl from [MindSpore download page](https://www.mindspore.cn/versions/en), and install the package.
```
```bash
pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.0.0/MindSpore/cpu/ubuntu_x86/mindspore-1.0.0-cp37-cp37m-linux_x86_64.whl
```
@ -109,13 +114,24 @@ For installation using `pip`, take `CPU` and `Ubuntu-x86` build version as an ex
mul = Mul()
print(mul(x, y))
```
```
```text
[ 4. 10. 18.]
```
### From Source
Use pip mode method to install MindSpore in different environments. Refer to the following documents.
[Install MindSpore](https://www.mindspore.cn/install/en).
- [Using pip mode method to install MindSpore in Ascend environment](https://gitee.com/mindspore/docs/blob/master/install/mindspore_ascend_install_pip_en.md)
- [Using pip mode method to install MindSpore in GPU environment](https://gitee.com/mindspore/docs/blob/master/install/mindspore_gpu_install_pip_en.md)
- [Using pip mode method to install MindSpore in CPU environment](https://gitee.com/mindspore/docs/blob/master/install/mindspore_cpu_install_pip_en.md)
### Source code compilation installation
Use the source code compilation method to install MindSpore in different environments. Refer to the following documents.
- [Using the source code compilation method to install MindSpore in Ascend environment](https://gitee.com/mindspore/docs/blob/master/install/mindspore_ascend_install_source_en.md)
- [Using the source code compilation method to install MindSpore in GPU environment](https://gitee.com/mindspore/docs/blob/master/install/mindspore_gpu_install_source_en.md)
- [Using the source code compilation method to install MindSpore in CPU environment](https://gitee.com/mindspore/docs/blob/master/install/mindspore_cpu_install_source_en.md)
### Docker Image
@ -125,27 +141,29 @@ currently the containerized build options are supported as follows:
| Hardware Platform | Docker Image Repository | Tag | Description |
| :---------------- | :---------------------- | :-- | :---------- |
| CPU | `mindspore/mindspore-cpu` | `x.y.z` | Production environment with pre-installed MindSpore `x.y.z` CPU release. |
| | | `devel` | Development environment provided to build MindSpore (with `CPU` backend) from the source, refer to https://www.mindspore.cn/install/en for installation details. |
| | | `devel` | Development environment provided to build MindSpore (with `CPU` backend) from the source, refer to <https://www.mindspore.cn/install/en> for installation details. |
| | | `runtime` | Runtime environment provided to install MindSpore binary package with `CPU` backend. |
| GPU | `mindspore/mindspore-gpu` | `x.y.z` | Production environment with pre-installed MindSpore `x.y.z` GPU release. |
| | | `devel` | Development environment provided to build MindSpore (with `GPU CUDA10.1` backend) from the source, refer to https://www.mindspore.cn/install/en for installation details. |
| | | `devel` | Development environment provided to build MindSpore (with `GPU CUDA10.1` backend) from the source, refer to <https://www.mindspore.cn/install/en> for installation details. |
| | | `runtime` | Runtime environment provided to install MindSpore binary package with `GPU CUDA10.1` backend. |
| Ascend | <center>&mdash;</center> | <center>&mdash;</center> | Coming soon. |
> **NOTICE:** For GPU `devel` docker image, it's NOT suggested to directly install the whl package after building from the source, instead we strongly RECOMMEND you transfer and install the whl package inside GPU `runtime` docker image.
* CPU
- CPU
For `CPU` backend, you can directly pull and run the latest stable image using the below command:
```
```bash
docker pull mindspore/mindspore-cpu:1.0.0
docker run -it mindspore/mindspore-cpu:1.0.0 /bin/bash
```
* GPU
- GPU
For `GPU` backend, please make sure the `nvidia-container-toolkit` has been installed in advance, here are some install guidelines for `Ubuntu` users:
```
```bash
DISTRIBUTION=$(. /etc/os-release; echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | apt-key add -
curl -s -L https://nvidia.github.io/nvidia-docker/$DISTRIBUTION/nvidia-docker.list | tee /etc/apt/sources.list.d/nvidia-docker.list
@ -153,8 +171,10 @@ currently the containerized build options are supported as follows:
sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit nvidia-docker2
sudo systemctl restart docker
```
Then edit the file daemon.json:
```
```bash
$ vim /etc/docker/daemon.json
{
"runtimes": {
@ -165,18 +185,23 @@ currently the containerized build options are supported as follows:
}
}
```
Restart docker again:
```
```bash
sudo systemctl daemon-reload
sudo systemctl restart docker
```
Then you can pull and run the latest stable image using the below command:
```
```bash
docker pull mindspore/mindspore-gpu:1.0.0
docker run -it -v /dev/shm:/dev/shm --runtime=nvidia --privileged=true mindspore/mindspore-gpu:1.0.0 /bin/bash
```
To test if the docker image works, please execute the python code below and check the output:
```python
import numpy as np
import mindspore.context as context
@ -189,7 +214,8 @@ currently the containerized build options are supported as follows:
y = Tensor(np.ones([1,3,3,4]).astype(np.float32))
print(F.tensor_add(x, y))
```
```
```text
[[[ 2. 2. 2. 2.],
[ 2. 2. 2. 2.],
[ 2. 2. 2. 2.]],
@ -208,7 +234,7 @@ please check out [docker](docker/README.md) repo for the details.
## Quickstart
See the [Quick Start](https://www.mindspore.cn/tutorial/training/en/master/quick_start/quick_start.html)
See the [Quick Start](https://www.mindspore.cn/tutorial/training/en/master/quick_start/quick_start.html)
to implement the image classification.
## Docs
@ -235,6 +261,7 @@ Welcome contributions. See our [Contributor Wiki](CONTRIBUTING.md) for
more details.
## Maintenance phases
Project stable branches will be in one of the following states:
| **State** | **Time frame** | **Summary** |
|-------------|---------------|--------------------------------------------------|
@ -245,6 +272,7 @@ Project stable branches will be in one of the following states:
| End Of Life (EOL) | N/A | Branch no longer accepting changes. |
## Maintenance status
| **Branch** | **Status** | **Initial Release Date** | **Next Phase** | **EOL Date** |
|--------|--------------|----------------------|-----------------------------------|------------|
| **r1.1** | Development | 2020-12-31 estimated | Maintained <br> 2020-12-31 estimated | |
@ -256,11 +284,6 @@ Project stable branches will be in one of the following states:
| **r0.2** | End Of Life | 2020-04-30 | | 2020-08-31 |
| **r0.1** | End Of Life | 2020-03-28 | | 2020-06-30 |
## Release Notes
The release notes, see our [RELEASE](RELEASE.md).

81
README_CN.md
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@ -1,14 +1,15 @@
![MindSpore标志](docs/MindSpore-logo.png "MindSpore logo")
============================================================
[View English](./README.md)
<!-- TOC -->
- [MindSpore介绍](#mindspore介绍)
- [自动微分](#自动微分)
- [自动并行](#自动并行)
- [安装](#安装)
- [二进制文件](#二进制文件)
- [来源](#来源)
- [pip方式安装](#pip方式安装)
- [源码编译方式安装](#源码编译方式安装)
- [Docker镜像](#docker镜像)
- [快速入门](#快速入门)
- [文档](#文档)
@ -16,9 +17,13 @@
- [治理](#治理)
- [交流](#交流)
- [贡献](#贡献)
- [分支维护策略](#分支维护策略)
- [现有分支维护状态](#现有分支维护状态)
- [版本说明](#版本说明)
- [许可证](#许可证)
<!-- /TOC -->
## MindSpore介绍
MindSpore是一种适用于端边云场景的新型开源深度学习训练/推理框架。
@ -56,7 +61,7 @@ MindSpore自动并行的目的是构建数据并行、模型并行和混合并
## 安装
### 二进制文件
### pip方式安装
MindSpore提供跨多个后端的构建选项：
@ -77,7 +82,7 @@ MindSpore提供跨多个后端的构建选项：
1. 请从[MindSpore下载页面](https://www.mindspore.cn/versions)下载并安装whl包。
```
```bash
pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/1.0.0/MindSpore/cpu/ubuntu_x86/mindspore-1.0.0-cp37-cp37m-linux_x86_64.whl
```
@ -89,29 +94,41 @@ MindSpore提供跨多个后端的构建选项：
import mindspore.nn as nn
from mindspore import Tensor
from mindspore.ops import operations as P
context.set_context(mode=context.GRAPH_MODE, device_target="CPU")
class Mul(nn.Cell):
def __init__(self):
super(Mul, self).__init__()
self.mul = P.Mul()
def construct(self, x, y):
return self.mul(x, y)
x = Tensor(np.array([1.0, 2.0, 3.0]).astype(np.float32))
y = Tensor(np.array([4.0, 5.0, 6.0]).astype(np.float32))
mul = Mul()
print(mul(x, y))
```
```
```text
[ 4. 10. 18.]
```
### 来源
[MindSpore安装](https://www.mindspore.cn/install)。
使用pip方式，在不同的环境安装MindSpore，可参考以下文档。
- [Ascend环境使用pip方式安装MindSpore](https://gitee.com/mindspore/docs/blob/master/install/mindspore_ascend_install_pip.md)
- [GPU环境使用pip方式安装MindSpore](https://gitee.com/mindspore/docs/blob/master/install/mindspore_gpu_install_pip.md)
- [CPU环境使用pip方式安装MindSpore](https://gitee.com/mindspore/docs/blob/master/install/mindspore_cpu_install_pip.md)
### 源码编译方式安装
使用源码编译方式，在不同的环境安装MindSpore，可参考以下文档。
- [Ascend环境使用源码编译方式安装MindSpore](https://gitee.com/mindspore/docs/blob/master/install/mindspore_ascend_install_source.md)
- [GPU环境使用源码编译方式安装MindSpore](https://gitee.com/mindspore/docs/blob/master/install/mindspore_gpu_install_source.md)
- [CPU环境使用源码编译方式安装MindSpore](https://gitee.com/mindspore/docs/blob/master/install/mindspore_cpu_install_source.md)
### Docker镜像
@ -121,27 +138,29 @@ MindSpore的Docker镜像托管在[Docker Hub](https://hub.docker.com/r/mindspore
| 硬件平台 | Docker镜像仓库 | 标签 | 说明 |
| :----- | :------------------------ | :----------------------- | :--------------------------------------- |
| CPU | `mindspore/mindspore-cpu` | `x.y.z` | 已经预安装MindSpore `x.y.z` CPU版本的生产环境。 |
| | | `devel` | 提供开发环境从源头构建MindSpore（`CPU`后端）。安装详情请参考https://www.mindspore.cn/install 。 |
| | | `devel` | 提供开发环境从源头构建MindSpore（`CPU`后端）。安装详情请参考<https://www.mindspore.cn/install> 。 |
| | | `runtime` | 提供运行时环境安装MindSpore二进制包（`CPU`后端）。 |
| GPU | `mindspore/mindspore-gpu` | `x.y.z` | 已经预安装MindSpore `x.y.z` GPU版本的生产环境。 |
| | | `devel` | 提供开发环境从源头构建MindSpore（`GPU CUDA10.1`后端）。安装详情请参考https://www.mindspore.cn/install 。 |
| | | `devel` | 提供开发环境从源头构建MindSpore（`GPU CUDA10.1`后端）。安装详情请参考<https://www.mindspore.cn/install> 。 |
| | | `runtime` | 提供运行时环境安装MindSpore二进制包（`GPU CUDA10.1`后端）。 |
| Ascend | <center>&mdash;</center> | <center>&mdash;</center> | 即将推出，敬请期待。 |
> **注意：** 不建议从源头构建GPU `devel` Docker镜像后直接安装whl包。我们强烈建议您在GPU `runtime` Docker镜像中传输并安装whl包。
* CPU
- CPU
对于`CPU`后端，可以直接使用以下命令获取并运行最新的稳定镜像：
```
```bash
docker pull mindspore/mindspore-cpu:1.0.0
docker run -it mindspore/mindspore-cpu:1.0.0 /bin/bash
```
* GPU
- GPU
对于`GPU`后端，请确保`nvidia-container-toolkit`已经提前安装，以下是`Ubuntu`用户安装指南：
```
```bash
DISTRIBUTION=$(. /etc/os-release; echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | apt-key add -
curl -s -L https://nvidia.github.io/nvidia-docker/$DISTRIBUTION/nvidia-docker.list | tee /etc/apt/sources.list.d/nvidia-docker.list
@ -149,8 +168,10 @@ MindSpore的Docker镜像托管在[Docker Hub](https://hub.docker.com/r/mindspore
sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit nvidia-docker2
sudo systemctl restart docker
```
编辑文件 daemon.json:
```
```bash
$ vim /etc/docker/daemon.json
{
"runtimes": {
@ -161,18 +182,23 @@ MindSpore的Docker镜像托管在[Docker Hub](https://hub.docker.com/r/mindspore
}
}
```
再次重启docker:
```
```bash
sudo systemctl daemon-reload
sudo systemctl restart docker
```
使用以下命令获取并运行最新的稳定镜像：
```
```bash
docker pull mindspore/mindspore-gpu:1.0.0
docker run -it -v /dev/shm:/dev/shm --runtime=nvidia --privileged=true mindspore/mindspore-gpu:1.0.0 /bin/bash
```
要测试Docker是否正常工作，请运行下面的Python代码并检查输出：
```python
import numpy as np
import mindspore.context as context
@ -185,7 +211,8 @@ MindSpore的Docker镜像托管在[Docker Hub](https://hub.docker.com/r/mindspore
y = Tensor(np.ones([1,3,3,4]).astype(np.float32))
print(F.tensor_add(x, y))
```
```
```text
[[[ 2. 2. 2. 2.],
[ 2. 2. 2. 2.],
[ 2. 2. 2. 2.]],
@ -205,7 +232,6 @@ MindSpore的Docker镜像托管在[Docker Hub](https://hub.docker.com/r/mindspore
参考[快速入门](https://www.mindspore.cn/tutorial/training/zh-CN/master/quick_start/quick_start.html)实现图片分类。
## 文档
有关安装指南、教程和API的更多详细信息，请参阅[用户文档](https://gitee.com/mindspore/docs)。
@ -228,6 +254,7 @@ MindSpore的Docker镜像托管在[Docker Hub](https://hub.docker.com/r/mindspore
欢迎参与贡献。更多详情，请参阅我们的[贡献者Wiki](CONTRIBUTING.md)。
## 分支维护策略
MindSpore的版本分支有以下几种维护阶段：
| **状态** | **持续时间** | **说明** |
|-------------|---------------|--------------------------------------------------|
@ -238,6 +265,7 @@ MindSpore的版本分支有以下几种维护阶段：
| End Of Life (EOL) | N/A | 不再接受修改合入该分支。 |
## 现有分支维护状态
| **分支名** | **当前状态** | **上线时间** | **后续状态** | **EOL 日期** |
|--------|--------------|----------------------|-----------------------------------|------------|
| **r1.1** | Development | 2020-12-31 estimated | Maintained <br> 2020-12-31 estimated | |
@ -249,11 +277,6 @@ MindSpore的版本分支有以下几种维护阶段：
| **r0.2** | End Of Life | 2020-04-30 | | 2020-08-31 |
| **r0.1** | End Of Life | 2020-03-28 | | 2020-06-30 |
## 版本说明
版本说明请参阅[RELEASE](RELEASE.md)。