forked from mindspore-Ecosystem/mindspore
Update docker image section in README.md
Signed-off-by: leonwanghui <leon.wanghui@huawei.com>
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README.md
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README.md
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@ -1,7 +1,7 @@
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============================================================
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- [What is MindSpore?](#what-is-MindSpore)
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- [What is MindSpore?](#what-is-mindspore)
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- [Automatic Differentiation](#automatic-differentiation)
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- [Automatic Parallel](#automatic-parallel)
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- [Installation](#installation)
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@ -53,7 +53,7 @@ The goal of MindSpore automatic parallel is to build a training method that comb
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<img src="docs/Automatic-parallel.png" alt="Automatic Parallel" width="600"/>
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At present, MindSpore uses a fine-grained parallel strategy of splitting operators, that is, each operator in the figure is splited into a cluster to complete parallel operations. The splitting strategy during this period may be very complicated, but as a developer advocating Pythonic, you don't need to care about the underlying implementation, as long as the top-level API compute is efficient.
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At present, MindSpore uses a fine-grained parallel strategy of splitting operators, that is, each operator in the figure is splitted into a cluster to complete parallel operations. The splitting strategy during this period may be very complicated, but as a developer advocating Pythonic, you don't need to care about the underlying implementation, as long as the top-level API compute is efficient.
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## Installation
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@ -70,9 +70,9 @@ MindSpore offers build options across multiple backends:
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| GPU CUDA 10.1 | Ubuntu-x86 | ✔️ |
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| CPU | Ubuntu-x86 | ✔️ |
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For installation using pip, take `Ubuntu-x86` and `CPU` build version as an example:
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For installation using `pip`, take `Ubuntu-x86` and `CPU` build version as an example:
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1. Download whl from [MindSpore website](https://www.mindspore.cn/), and install the package.
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1. Download whl from [MindSpore download page](https://www.mindspore.cn/versions/en), and install the package.
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```
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pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/0.1.0-alpha/MindSpore/cpu/ubuntu-x86/mindspore-0.1.0-cp37-cp37m-linux_x86_64.whl
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@ -96,13 +96,59 @@ currently the containerized build options are supported as follows:
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| Hardware Platform | Docker Image URL |
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| :---------------- | :--------------- |
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| CPU | `mindspore/mindspore-cpu:0.1.0-alpha` |
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| GPU CUDA 9.2 | `mindspore/mindspore-cuda9.2:0.1.0-alpha` |
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| GPU CUDA 10.1 | `mindspore/mindspore-cuda10.1:0.1.0-alpha` |
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| GPU | `mindspore/mindspore-gpu:0.1.0-alpha` |
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| Ascend | <center>—</center> |
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Take `CPU` for example, you can directly pull the image using the below command:
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* CPU
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For `CPU` backend, you can directly pull and run the image using the below command:
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```
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docker pull mindspore/mindspore-cpu:0.1.0-alpha
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docker run -it mindspore/mindspore-cpu:0.1.0-alpha python -c 'import mindspore'
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```
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* GPU
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For `GPU` backend, please make sure the `nvidia-container-toolkit` has been installed in advance, here are some install guidelines for Ubuntu users:
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```
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DISTRIBUTION=$(. /etc/os-release; echo $ID$VERSION_ID)
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curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | apt-key add -
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curl -s -L https://nvidia.github.io/nvidia-docker/$DISTRIBUTION/nvidia-docker.list | tee /etc/apt/sources.list.d/nvidia-docker.list
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sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit nvidia-docker2
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sudo systemctl restart docker
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```
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Then you can pull and run the image using the below command:
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```
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docker pull mindspore/mindspore-gpu:0.1.0-alpha
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docker run -it --runtime=nvidia --privileged=true mindspore/mindspore-gpu:0.1.0-alpha /bin/bash
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```
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To test if the docker image works, please execute the python code below and check the output:
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```python
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import numpy as np
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from mindspore import Tensor
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from mindspore.ops import functional as F
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import mindspore.context as context
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context.set_context(device_target="GPU")
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x = Tensor(np.ones([1,3,3,4]).astype(np.float32))
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y = Tensor(np.ones([1,3,3,4]).astype(np.float32))
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print(F.tensor_add(x, y))
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```
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```
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[[[ 2. 2. 2. 2.],
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[ 2. 2. 2. 2.],
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[ 2. 2. 2. 2.]],
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[[ 2. 2. 2. 2.],
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[ 2. 2. 2. 2.],
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[ 2. 2. 2. 2.]],
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[[ 2. 2. 2. 2.],
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[ 2. 2. 2. 2.],
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[ 2. 2. 2. 2.]]]
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```
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If anyone wants to learn more about the build process of MindSpore docker images,
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