An unofficial visualization tool for chainer, inspired by tensorboard. The toolkit allows visualization of log from chainer.extensions.LogReport.
Example usage:
model = L.Classifier(MyModel())
optimizer = chainer.optimizers.Adam()
optimizer.setup(model)
train = create_my_data()
train_iter = chainer.iterators.SerialIterator(train, batchsize)
updater = training.StandardUpdater(train_iter, optimizer)
trainer = training.Trainer(updater, (epochs, 'epoch'), out='path/to/output')
trainer.extend(extensions.LogReport(log_name='my_log_data')))
# optional; allows visualization of parameters
trainer.extend(extensions.ParameterStatistics(model))
# Run the training
trainer.run()and point chainerboard at the output log file to start local http server.
chainerboard path/to/output/my_log_namenow open http://localhost:6006/ to view the log.
Development
To setup development environment:
pip install -r requirements.txtFor testing,
toxBuild document
python setup.py build_sphinx1 maintainer
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