Memory Efficient Attention - Pytorch

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for lucidrains from gravatar.com lucidrains

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: Phil Wang
  • Tags artificial intelligence, deep learning, attention-mechanism
Classifiers

Project description

The author of this package has not provided a project description

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for lucidrains from gravatar.com lucidrains

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: Phil Wang
  • Tags artificial intelligence, deep learning, attention-mechanism
Classifiers

Release history Release notifications | RSS feed

0.1.6

0.1.5

0.1.4

0.1.2

0.1.1

0.1.0

0.0.27

0.0.26

0.0.25

0.0.24

0.0.23

0.0.22

0.0.21

0.0.20

0.0.19

0.0.18

0.0.17

0.0.16

0.0.15

0.0.14

0.0.12

0.0.11

0.0.10

0.0.9

0.0.8

0.0.7

0.0.6

0.0.5

This version

0.0.4

0.0.2

0.0.1

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

memory-efficient-attention-pytorch-0.0.4.tar.gz (4.5 kB view details)

Uploaded Source

Built Distribution

memory_efficient_attention_pytorch-0.0.4-py3-none-any.whl (4.6 kB view details)

Uploaded Python 3

File details

Details for the file memory-efficient-attention-pytorch-0.0.4.tar.gz.

File metadata

  • Download URL: memory-efficient-attention-pytorch-0.0.4.tar.gz
  • Upload date:
  • Size: 4.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.10

File hashes

Hashes for memory-efficient-attention-pytorch-0.0.4.tar.gz
Algorithm Hash digest
SHA256 0da45c6d65da94d18cd72c5e09898b6dceac478360c89afc6592dbbccaf5e95d
MD5 703d6f337f0a6baacf254d215b7dcc6b
BLAKE2b-256 3a00fcb6cbf5f66a3dc17301923c420f0d9115888be8c7e443adc306a74e9078

See more details on using hashes here.

File details

Details for the file memory_efficient_attention_pytorch-0.0.4-py3-none-any.whl.

File metadata

  • Download URL: memory_efficient_attention_pytorch-0.0.4-py3-none-any.whl
  • Upload date:
  • Size: 4.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/32.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.8 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.10

File hashes

Hashes for memory_efficient_attention_pytorch-0.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 bd4cf4e8081aaddf7b38cfc3d35e6c4aa6f0da2f274c464b21aecb21253028e7
MD5 bdafb870dba21bcf49c5940e3a18f1ba
BLAKE2b-256 113aeb5c4bf0fd9ca3823a56ec38cb89c7052930218ee3733b8b020fd436eda7

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page