Skorch Notebooks Learning Rate Scheduler Ipynb At Master Github
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There was an error while loading. Please reload this page. There was an error while loading. Please reload this page. Instantly share code, notes, and snippets. A scikit-learn compatible neural network library that wraps PyTorch.
The goal of skorch is to make it possible to use PyTorch with sklearn. This is achieved by providing a wrapper around PyTorch that has an sklearn interface. skorch does not re-invent the wheel, instead getting as much out of your way as possible. If you are familiar with sklearn and PyTorch, you don’t have to learn any new concepts, and the syntax should be well known. (If you’re not familiar with those libraries, it is worth getting familiarized.) Additionally, skorch abstracts away the training loop, making a lot of boilerplate code obsolete.
A simple net.fit(X, y) is enough. Out of the box, skorch works with many types of data, be it PyTorch Tensors, NumPy arrays, Python dicts, and so on. However, if you have other data, extending skorch is easy to allow for that. Overall, skorch aims at being as flexible as PyTorch while having a clean interface as sklearn.
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There was an error while loading. Please reload this page. There was an error while loading. Please reload this page. Instantly share code, notes, and snippets. A scikit-learn compatible neural network library that wraps PyTorch.
The Goal Of Skorch Is To Make It Possible To
The goal of skorch is to make it possible to use PyTorch with sklearn. This is achieved by providing a wrapper around PyTorch that has an sklearn interface. skorch does not re-invent the wheel, instead getting as much out of your way as possible. If you are familiar with sklearn and PyTorch, you don’t have to learn any new concepts, and the syntax should be well known. (If you’re not familiar with...
A Simple Net.fit(X, Y) Is Enough. Out Of The Box,
A simple net.fit(X, y) is enough. Out of the box, skorch works with many types of data, be it PyTorch Tensors, NumPy arrays, Python dicts, and so on. However, if you have other data, extending skorch is easy to allow for that. Overall, skorch aims at being as flexible as PyTorch while having a clean interface as sklearn.
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