hypaTorch
Highly Abstract Compound Networks in PyTorch
This python package provides a flexible and comprehensive framework for creating compound PyTorch models in an abstract manner.
Installation
uv add hypatorch
Documentation
How to declare a model, write a submodule, and configure losses, optimizers and
the trainer: hypatorch/agent_docs/. How the
machinery works underneath: docs/.
W&B media logging: rich media.
Acknowledgements
2 maintainers
Metadata
2 maintainers
Release files for hypatorch 1.0.13
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
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Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| hypatorch-1.0.13-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 533.9 kB
Release files / hypatorch-1.0.13.tar.gz
| Download URL | hypatorch-1.0.13.tar.gz |
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| Size | 474.3 kB |
| Tags | Source |
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| Tags | Python 3 |
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