Skip to main content

docs License codecov pypi

You saw the lightning. Now it's time to hear the thunder 🌩️

Thunder 🌩️

The Deep Learning framework based on Lightning.

Install

pip install thunder

Start experimenting

It's as simple as 1, 2, 3:

  1. Create a config (e.g. base.config):

    from myproject import MyDataset, MyModule
    from lightning import Trainer
    from torch.utils.data import DataLoader
    
    # these 3 fields are required
    train_data = DataLoader(MyDataset())
    module = MyModule()
    trainer = Trainer()
    
  2. Build the experiment:

    thunder build base.config /path/to/some/folder
    
  3. Run it

    thunder run /path/to/some/folder
    

Also, 2 and 3 can be combined into a single command:

thunder build-run base.config /path/to/some/folder

More advanced stuff

See our docs for a full list of neat things thunder🌩️ can do for you

Download files

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

Source Distribution

thunder-0.1.1.tar.gz (27.9 kB view details)

Uploaded Source

File details

Details for the file thunder-0.1.1.tar.gz.

File metadata

  • Download URL: thunder-0.1.1.tar.gz
  • Upload date:
  • Size: 27.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for thunder-0.1.1.tar.gz
Algorithm Hash digest
SHA256 de633ee242f2f272ff664b3a711e1095aa6ed1901d1ad32b7fd0b2b35e444e54
MD5 5c57bacd7473e4a4c93840b855c7ce8f
BLAKE2b-256 8eea1d83420293a45b0b1b43c012b1093a560a063ef2872233d3874a004aaa06

See more details on using hashes here.

Release history Release notifications | RSS feed

This release

0.1.1 This release

1 file

0.0.1

1 file

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page