套件：python3-skorch（0.9.0-3）
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. In that sense, skorch is the spiritual successor to nolearn, but instead of using Lasagne and Theano, it uses PyTorch.
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.
其他與 python3-skorch 有關的套件
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- dep: python3
- interactive high-level object-oriented language (default python3 version)
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- dep: python3-numpy
- Fast array facility to the Python 3 language
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- dep: python3-scipy
- scientific tools for Python 3
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- dep: python3-sklearn
- Python modules for machine learning and data mining - Python 3
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- dep: python3-tabulate
- pretty-print tabular data in Python3
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- dep: python3-torch (>= 1.3.1)
- Tensors and Dynamic neural networks in Python with strong GPU acceleration
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- dep: python3-tqdm
- fast, extensible progress bar for Python 3 and CLI tool
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- dep: python3.9
- Interactive high-level object-oriented language (version 3.9)