| CPU | `mindspore/mindspore-cpu` | `0.1.0-alpha` | Production environment with pre-installed MindSpore `0.1.0-alpha` CPU release. |
| 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. |
| | | `runtime` | Runtime environment provided to install MindSpore binary package with `CPU` backend. |
| GPU | `mindspore/mindspore-gpu` | `0.1.0-alpha` | Production environment with pre-installed MindSpore `0.1.0-alpha` GPU release. |
| 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. |
| | | `runtime` | Runtime environment provided to install MindSpore binary package with `GPU` backend. |
| | | `runtime` | Runtime environment provided to install MindSpore binary package with `GPU CUDA10.1` backend. |
> **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
For `CPU` backend, you can directly pull and run the image using the below command:
For `CPU` backend, you can directly pull and run the latest stable image using the below command:
```
docker pull mindspore/mindspore-cpu:0.1.0-alpha
docker run -it mindspore/mindspore-cpu:0.1.0-alpha python -c 'import mindspore'
docker pull mindspore/mindspore-cpu:0.2.0-alpha
docker run -it mindspore/mindspore-cpu:0.2.0-alpha python -c 'import mindspore'
```
* GPU
...
...
@@ -124,20 +126,21 @@ currently the containerized build options are supported as follows:
sudo systemctl restart docker
```
Then you can pull and run the image using the below command:
Then you can pull and run the latest stable image using the below command:
```
docker pull mindspore/mindspore-gpu:0.1.0-alpha
docker run -it --runtime=nvidia --privileged=true mindspore/mindspore-gpu:0.1.0-alpha /bin/bash
docker pull mindspore/mindspore-gpu:0.2.0-alpha
docker run -it --runtime=nvidia --privileged=true mindspore/mindspore-gpu:0.2.0-alpha /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
from mindspore import Tensor
from mindspore.ops import functional as F
import mindspore.context as context
context.set_context(device_target="GPU")
x = Tensor(np.ones([1,3,3,4]).astype(np.float32))
y = Tensor(np.ones([1,3,3,4]).astype(np.float32))
print(F.tensor_add(x, y))
...
...
@@ -161,7 +164,7 @@ please check out `docker` folder for the details.
## Quickstart
See the [Quick Start](https://www.mindspore.cn/tutorial/en/0.1.0-alpha/quick_start/quick_start.html)
See the [Quick Start](https://www.mindspore.cn/tutorial/en/0.2.0-alpha/quick_start/quick_start.html)
RUN pip install--no-cache-dir https://ms-release.obs.cn-north-4.myhuaweicloud.com/0.2.0-alpha/MindSpore/cpu/ubuntu-x86/mindspore-0.2.0-cp37-cp37m-linux_x86_64.whl
RUN pip install--no-cache-dir https://ms-release.obs.cn-north-4.myhuaweicloud.com/0.2.0-alpha/MindSpore/gpu/cuda-10.1/mindspore-0.2.0-cp37-cp37m-linux_x86_64.whl