A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model
Project description
A unified ensemble framework for pytorch to easily improve the performance and robustness of your deep learning model. Ensemble-PyTorch is part of the pytorch ecosystem, which requires the project to be well maintained.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
torchensemble-0.1.8.tar.gz
(29.1 kB
view details)
Built Distribution
File details
Details for the file torchensemble-0.1.8.tar.gz.
File metadata
- Download URL: torchensemble-0.1.8.tar.gz
- Upload date:
- Size: 29.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 777080b562988fcf3344fdf79a19fd01a344f5b2416d88ad1fe354601ea41c42 |
|
| MD5 | 85f994d098d28b637ab7807142c9dc0a |
|
| BLAKE2b-256 | ffc96976022a8f7131ef7c39bbb339480bc5f654fccc1fe3fa57d431cc01aa50 |
File details
Details for the file torchensemble-0.1.8-py3-none-any.whl.
File metadata
- Download URL: torchensemble-0.1.8-py3-none-any.whl
- Upload date:
- Size: 42.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 6cd6beb22c7e98d72ceb5e64add72091f14d20344135bc8ac7808caa9da3a9e4 |
|
| MD5 | 74c7361c0fead5a36c27d124d8452940 |
|
| BLAKE2b-256 | 368f9d21a7db66dc00acf3ad8c026971daf7f1eca556a43de8ba1c991a43b3aa |
