Quick reference

• The official Caffe docker image.

• Maintained by: openEuler CloudNative SIG.

• Where to get help: openEuler CloudNative SIG, openEuler.

Caffe | openEuler

Current Caffe docker images are built on the openEuler. This repository is free to use and exempted from per-user rate limits.

Caffe is a deep learning framework made with expression, speed, and modularity in mind.

Learn more about on Caffe Website.

Supported tags and respective Dockerfile links

The tag of each caffe docker image is consist of the complete software stack version. The details are as follows

Tag	Currently	Architectures
1.0-oe2403sp1	Caffe 1.0 on openEuler 24.03-LTS-SP1	amd64, arm64

Usage

In this usage, users can select the corresponding {Tag} and container startup options based on their requirements.

• Pull the openeuler/caffe image from docker

  docker pull openeuler/caffe:{Tag}
  

• Run with an interactive shell

  You can also start the container with an interactive shell to use caffe.

  docker run -it --rm openeuler/caffe:{Tag} bash
  

• How to train LeNet on MNIST with BVLC Caffe (CPU/GPU)

  • Download the MNIST dataset manually(mirror)

    In your container, go to mnist directory:

    cd /opt/caffe/data/mnist
    

    Download the files from a reliable public mirror:

    wget https://ossci-datasets.s3.amazonaws.com/mnist/train-images-idx3-ubyte.gz
    wget https://ossci-datasets.s3.amazonaws.com/mnist/train-labels-idx1-ubyte.gz
    wget https://ossci-datasets.s3.amazonaws.com/mnist/t10k-images-idx3-ubyte.gz
    wget https://ossci-datasets.s3.amazonaws.com/mnist/t10k-labels-idx1-ubyte.gz
    

    Uncompress the files:

    gzip -d *.gz
    

  • Convert the dataset to LMDB

    Switch to the Caffe root directory and run:

    cd /opt/caffe
    ./examples/mnist/create_mnist.sh
    

    This script converts the raw MNIST files to LMDB format which Caffe uses for training.

  • Check the solver configuration

    Open the solver prototxt file:

    vi ./examples/mnist/lenet_solver.prototxt
    

    Make sure the last line matches your build:

    solver_mode: CPU   # For CPU-only Caffe builds
    

    or

    solver_mode: GPU   # For Caffe built with CUDA/cuDNN
    

  • Train the model

    Finally, run the training command:

    ./build/tools/caffe train --solver=examples/mnist/lenet_solver.prototxt
    

    Caffe will start training the LeNet model on the MNIST dataset.

Question and answering

If you have any questions or want to use some special features, please submit an issue or a pull request on openeuler-docker-images.