A hackable blueprint for training neural networks using PyTorch and Lightning.
Project description
Venturi
A hackable blueprint for training neural networks using PyTorch and Lightning.
Desigin principles
The configuration is purposely designed to not have pydantic validation. You create your classes and/or custom functions and add their parameters to a yaml file, and that is it. You can add your own pydantic validation before passing the configuration to the experiment object.
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 venturi-0.9.0.tar.gz.
File metadata
- Download URL: venturi-0.9.0.tar.gz
- Upload date:
- Size: 66.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.11
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
1ca0b9d90b93b6a5685605106ee14a5929beb484c65453fb03becb1704d981f4
|
|
| MD5 |
5454a881255cf44f5c947b00799bf904
|
|
| BLAKE2b-256 |
1730b346e06b1777ee846da7d2f51debea7e466d6d9540433036406a9ecffeac
|
File details
Details for the file venturi-0.9.0-py3-none-any.whl.
File metadata
- Download URL: venturi-0.9.0-py3-none-any.whl
- Upload date:
- Size: 24.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.11
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f69455027c1fb3c6fd39a4a65da6b3042869f7292bf40df4cc88c0957ff6b651
|
|
| MD5 |
cd0b1272f2e95ff965b764514f99d46f
|
|
| BLAKE2b-256 |
5e3fb89bde44e2314a86df9425c10583cbe7512a6b17b24074892b8dbe3f6d27
|
