spectralLayersPyTorch

SpectralLayersPyTorch

Trainable linear spectral layers for PyTorch

Implements trainable spectral layers for PyTorch that can be initialized as 1-D & 2-D DCT and DFT transformations as shown in paper.

Install

The package can be installed as follows:

pip install spectral

pip install git+https://github.com/NarayanSchuetz/SpectralLayersPyTorch.git

Attribution

@misc{alberti2019trainable,
      title={Trainable Spectrally Initializable Matrix Transformations in Convolutional Neural Networks}, 
      author={Michele Alberti and Angela Botros and Narayan Schuez and Rolf Ingold and Marcus Liwicki and Mathias Seuret},
      year={2019},
      eprint={1911.05045},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
   }

Metadata

Release files for spectralLayersPyTorch 0.989

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for spectralLayersPyTorch 0.989
File	Size	Uploaded	Provenance	Actions
spectralLayersPyTorch-0.989.tar.gz	6.1 kB	Oct 23, 2020	Without provenance	Details for spectralLayersPyTorch-0.989.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for spectralLayersPyTorch 0.989
File	Interpreter	ABI	Platform	Actions Reset
spectralLayersPyTorch-0.989-py3-none-any.whl 8.2 kB Oct 23, 2020 Without provenance	Python 3	none	any	Details for spectralLayersPyTorch-0.989-py3-none-any.whl

Total release size: 14.3 kB

Release files / spectralLayersPyTorch-0.989.tar.gz

Download URL	spectralLayersPyTorch-0.989.tar.gz
Size	6.1 kB
Tags	Source
SHA-256 checksum How to use checksums	`68ba544e89711e888f526074dc313444deb6e361de9d8f75e835a20398370828`
BLAKE2b-256 checksum How to use checksums	`db897cf8e1efeb8f6f7a9cc4b0fad0e3f09701ad0e46b8898c7d7ebcae263781`
Upload date	Oct 23, 2020
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/40.2.0 requests-toolbelt/0.9.1 tqdm/4.42.0 CPython/3.7.3`

Release files / spectralLayersPyTorch-0.989-py3-none-any.whl

Download URL	spectralLayersPyTorch-0.989-py3-none-any.whl
Size	8.2 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`454a610e0d4528cba6a3f7b871b624782f15968624cb669cc60449f011132188`
BLAKE2b-256 checksum How to use checksums	`6913f978d422e82a3694785ba619c0ea2192a21823806a5ddcdf095f23eeb227`
Upload date	Oct 23, 2020
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/40.2.0 requests-toolbelt/0.9.1 tqdm/4.42.0 CPython/3.7.3`

Security for spectralLayersPyTorch 0.989

Report project as malware

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

0.989 This release

Oct 23, 2020 2 release files No provenance

spectralLayersPyTorch 0.989