Installation¶

Prerequisites¶

Python 3.10+
PyTorch 2.0+
CUDA 11.8+
GCC 5.4+

Prepare the Environment¶

Use conda and activate the environment:

conda create -n onedl-mm python=3.10 -y
conda activate onedl-mm

Install PyTorch

Before installing MMEngine, please make sure that PyTorch has been successfully installed in the environment. You can refer to PyTorch official installation documentation. Verify the installation with the following command:
```
python -c 'import torch;print(torch.__version__)'
```

Install MMEngine¶

Install with mim (recommended)¶

mim is a package management tool for OpenMMLab projects, which can be used to install the OpenMMLab project easily.

pip install -U onedl-mim
mim install onedl-mmengine

Install with uv¶

Install uv.

uv pip install onedl-mmengine

Install with pip¶

pip install onedl-mmengine

Use docker images¶

Build the image

docker build -t mmengine https://github.com/vbti-development/onedl-mmengine.git#main:docker/release

More information can be referred from onedl-mmengine/docker.

Run the image

docker run --gpus all --shm-size=8g -it onedl-mmengine

Build from source¶

Build mmengine¶

# if cloning speed is too slow, you can switch the source to https://gitee.com/vbti-development/onedl-mmengine.git
git clone https://github.com/vbti-development/onedl-mmengine.git
cd onedl-mmengine
pip install -e . -v

Verify the Installation¶

To verify if MMEngine and the necessary environment are successfully installed, we can run this command:

python -c 'import mmengine;print(mmengine.__version__)'