pydrobert-pytorch
PyTorch utilities for Machine Learning. This is an eclectic mix of utilities
that I've used in my various projects. There is a definite leaning towards
speech, specifically end-to-end ASR. The primary benefit pydrobert-pytorch
has over other packages is modularity: you can pick and choose the
functionality you desire without subscribing to an entire ecosystem. You can
find out more about what the package offers in the documentation links below.
This is student-driven code, so don't expect a stable API. I'll try to use semantic versioning, but the best way to keep functionality stable is by pinning the version in the requirements or by forking.
Documentation
Installation
pydrobert-pytorch is available through both Conda and PyPI.
conda install -c sdrobert pydrobert-pytorch
pip install pydrobert-pytorch
Licensing and How to Cite
Please see the pydrobert page for more details.
Implementations of pydrobert.torch.util.polyharmonic_spline and
pydrobert.torch.util.sparse_image_warp are based off Tensorflow's codebase,
which is Apache 2.0 licensed.
1 maintainer
Metadata
1 maintainer
Release files for pydrobert-pytorch 0.3.0
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| File | Size | Uploaded | Provenance | Actions |
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| pydrobert-pytorch-0.3.0.tar.gz | 10.4 MB | Without provenance | Details for pydrobert-pytorch-0.3.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
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| pydrobert_pytorch-0.3.0-py3-none-any.whl | Python 3 | none | any | Details for pydrobert_pytorch-0.3.0-py3-none-any.whl |
Total release size: 10.5 MB
Release files / pydrobert-pytorch-0.3.0.tar.gz
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Release files / pydrobert_pytorch-0.3.0-py3-none-any.whl
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| Tags | Python 3 |
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