{ "info": { "author": "Yuta Koreeda", "author_email": "secret-email@example.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Environment :: Console", "Intended Audience :: Developers", "Intended Audience :: Education", "Intended Audience :: Science/Research", "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3.5", "Topic :: Scientific/Engineering :: Artificial Intelligence", "Topic :: Scientific/Engineering :: Information Analysis" ], "description": ".. -*- coding: utf-8; -*-\n\nAn unofficial visualization tool for `chainer `_, inspired by `tensorboard `_. The toolkit allows visualization of log from ``chainer.extensions.LogReport``.\n\nExample usage:\n\n.. code:: python\n\n model = L.Classifier(MyModel())\n\n optimizer = chainer.optimizers.Adam()\n optimizer.setup(model)\n\n train = create_my_data()\n train_iter = chainer.iterators.SerialIterator(train, batchsize)\n\n updater = training.StandardUpdater(train_iter, optimizer)\n trainer = training.Trainer(updater, (epochs, 'epoch'), out='path/to/output')\n\n trainer.extend(extensions.LogReport(log_name='my_log_data')))\n # optional; allows visualization of parameters\n trainer.extend(extensions.ParameterStatistics(model))\n\n # Run the training\n trainer.run()\n\n\nand point chainerboard at the output log file to start local http server.\n\n.. code:: bash\n\n chainerboard path/to/output/my_log_name\n\n\nnow open http://localhost:6006/ to view the log.\n\n\n.. warning:: The author of this project is not a professional web\n programmer. 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