Use web API

Send training logs via web API.

Start ChainerUI server

$ chainerui server

Open http://localhost:5000/ . To stop, press Ctrl+C on the console. When use original host or port, see command option.

Or, use ChainerUI’s docker container to run ChainerUI server, see docker start.

Customize training loop

Setup example from a brief MNIST example:

import chainerui

def main():
    args = parser.parse_args()

    # [ChainerUI] To use ChainerUI web client, must initialize
    # args will be shown as parameter of this experiment.

    # Set up a neural network to train
    # Classifier reports softmax cross entropy loss and accuracy at every
    # iteration, which will be used by the PrintReport extension below.
    # [ChainerUI] plot loss and accuracy reported by this link
    model = L.Classifier(MLP(args.unit, 10))

    trainer = training.Trainer(updater, (args.epoch, 'epoch'), out=args.out)

    # [ChainerUI] set log reporter on the extention


User doesn’t have to execute $ chainerui project create command. chainerui.init() add a project using current directory on the first running. Project name can be customized using project_name option. Training results wil be created every running. Result name is set timestamp automatically and can be customized via web UI.