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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

Project details


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chainerboard-0.1.5.tar.gz (850.0 kB view hashes)

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