An implementation of the ConvNeXt architecture built on the PyTorch-Lightning API
Project description
ConvNeXt-Lightning
An implementation of the ConvNeXt architecture built on the PyTorch-Lightning API. The base model code (forward passes and architecture) are from the FAIR repo here.
This library allows easy loading of an untrained ConvNeXt model from the PyTorch Lightning API. Additionally, it provides an ImageDataset(nn.Dataset) module for image classification tasks.
Project details
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
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file convnextpl-0.0.1.tar.gz.
File metadata
- Download URL: convnextpl-0.0.1.tar.gz
- Upload date:
- Size: 6.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.7.1 importlib_metadata/4.8.1 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
99b46e0981a428779aac7e4eb435936d4813144a09020fe1506ffe184951137f
|
|
| MD5 |
ecd031c7fd2e55e00f7bd98d9d04b259
|
|
| BLAKE2b-256 |
3759499c5a127c88f2a82d6e848187caa328c29b6d7469dec4708a1e0d2c22ba
|
File details
Details for the file convnextpl-0.0.1-py2.py3-none-any.whl.
File metadata
- Download URL: convnextpl-0.0.1-py2.py3-none-any.whl
- Upload date:
- Size: 6.7 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.7.1 importlib_metadata/4.8.1 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
917e5bce16befa8b318e0cb9d39dccc22c8d9e8f75efd90e77c206b84d5ada49
|
|
| MD5 |
c92a2ab38eea5d855fae9c0e036d46b1
|
|
| BLAKE2b-256 |
be3ab97af3843f998eaddeb54c92414391549b5122a88778c6925f991293477a
|