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Visualization toolkit for Chainer

Project description

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_name

now open http://localhost:6006/ to view the log.

Development

To setup development environment:

pip install -r requirements.txt

For testing,

tox

Build document

python setup.py build_sphinx

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page