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ELEKTRONN / elektronn3

A PyTorch-based library for working with 3D and 2D convolutional neural networks, with focus on semantic segmentation of volumetric biomedical image data
MIT License
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Docstrings and type information #15

Closed mdraw closed 5 years ago

mdraw commented 6 years ago

We need docstrings, especially for the two core classes PatchCreator and StoppableTrainer.

While we used NumPy-style docstrings in ELEKTRONN2, I decided to write new docstrings in [Google style] because they are less cumbersome to write, require significantly less lines and are more commonly used (most importantly: PyTorch uses Google style). IMO they are also more suitable for type-hint-free docstrings. Type hints should not be included in docstrings anymore; they instead belong in the function signatures in a PEP-484-compliant way, so we can eventually use mypy for static type checking. One example of a class that follows the docstring- and type information style that I am proposing here is the UNet class at https://github.com/ELEKTRONN/elektronn3/blob/a18301d19e7dd88a0e32926be850bf35da886138/elektronn3/models/unet.py#L225

mdraw commented 6 years ago

Update: I've added basic documentation to PatchCreator and StoppableTrainer. We will still need to convert existing docstrings of other code to the new format.