torch-attentions

This repository contains PyTorch implementations of various attention mechanisms. The attention mechanisms are implemented as PyTorch modules and can be easily integrated into existing models.

Metadata

Release files for torch-attentions 0.1.4

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

Source distribution (sdist)

Source distribution for torch-attentions 0.1.4
File	Size	Uploaded
torch_attentions-0.1.4.tar.gz	1.4 kB	Sep 2, 2024	Details

Built distribution (wheel)

Table of built distributions (wheels) for torch-attentions 0.1.4
File	Interpreter	ABI	Platform	Reset
torch_attentions-0.1.4-py3-none-any.whl 2.2 kB Sep 2, 2024	Python 3	none	any	Details

Total release size: 3.6 kB

Release files / torch_attentions-0.1.4.tar.gz

Download URL	torch_attentions-0.1.4.tar.gz
Size	1.4 kB
Tags	Source
SHA-256 checksum How to use checksums	`d8abd3a3c125bd91088add38229df67aa255e246e2c749e53f2b4ff60f6568f2`
BLAKE2b-256 checksum How to use checksums	`06ed489c49c5c41011f6a4c0c323d2583cc68f447ffa9c9e7fcdca3b78c29293`
Upload date	Sep 2, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`poetry/1.7.1 CPython/3.10.9 Windows/10`

Release files / torch_attentions-0.1.4-py3-none-any.whl

Download URL	torch_attentions-0.1.4-py3-none-any.whl
Size	2.2 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`e48cd1eb36d517e143258c750fc604485bf2ef0198e486006e024a0fe3524f0b`
BLAKE2b-256 checksum How to use checksums	`3f6b1c2034752f8afcfe13559e5106c7b9561beebc914840cdb89b7276039431`
Upload date	Sep 2, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`poetry/1.7.1 CPython/3.10.9 Windows/10`