Combolutional Neural Networks
Training, evaluation, and implementations of Combolutional Layers in PyTorch
Table of contents
Installation
You can install from PyPI:
pip install combnet
or from a local clone:
pip install -e .
For full training and evaluation compatibility, you will also need to install FFMPEG version >=4, <7 (version 6 is recommended).
Training
Download
python -m combnet.data.download
Download and uncompress datasets used for training
Augmentation
python -m combnet.data.augment --datasets giantsteps_mtg
Augment data (pitch shift to other keys)
Preprocess
python -m combnet.data.preprocess --datasets giantsteps_mtg giantsteps
Preprocess datasets
Partition
python -m combnet.partition
Partition datasets. Partitions are saved in combnet/assets/partitions.
Train
python -m combnet.train --config <config> --gpus <gpus>
Trains a model according to a given configuration.
Monitor
Run tensorboard --logdir runs/. If you are running training remotely, you
must create a SSH connection with port forwarding to view Tensorboard.
This can be done with ssh -L 6006:localhost:6006 <user>@<server-ip-address>.
Then, open localhost:6006 in your browser.
Evaluate
python -m combnet.evaluate \
--config <config> \
--checkpoint <checkpoint> \
--gpu <gpu>
Evaluate a model. <checkpoint> is the checkpoint file to evaluate and <gpu>
is the GPU index.
Metadata
Release files for combnet 1.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| combnet-1.0.1.tar.gz | 232.4 kB | Details |
Release files / combnet-1.0.1.tar.gz
| Download URL | combnet-1.0.1.tar.gz |
|---|---|
| Size | 232.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
3b6690840b42aa82884f3fe13e2f56cecd343bcbb719197e04b2cc64b151c5ff
|
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BLAKE2b-256 checksum How to use checksums |
71ada7b99c461f743b1b688bc3f41edbae6e152604f7c37f8a89eb2991f3fde1
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.1.0 CPython/3.13.5
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