This is the Linux app named Flax whose latest release can be downloaded as 0.12.0sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named Flax with OnWorks for free.
Follow these instructions in order to run this app:
- 1. Downloaded this application in your PC.
- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 3. Upload this application in such filemanager.
- 4. Start the OnWorks Linux online or Windows online emulator or MACOS online emulator from this website.
- 5. From the OnWorks Linux OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 6. Download the application, install it and run it.
SCREENSHOTS
Ad
Flax
DESCRIPTION
Flax is a flexible neural-network library for JAX that embraces functional programming while offering ergonomic module abstractions. Its design separates pure computation from state by threading parameter collections and RNGs explicitly, enabling reproducibility, transformation, and easy experimentation with JAX transforms like jit, pmap, and vmap. Modules define parameterized computations, but initialization and application remain side-effect free, which pairs naturally with JAX’s staging and compilation model. Flax emphasizes composability: optimizers, training loops, and checkpointing are provided as examples or utilities rather than monolithic frameworks, encouraging research-friendly customization. The library is widely used in vision, language, and reinforcement learning, often serving as a thin layer atop NumPy-like JAX primitives. Tutorials and examples show patterns for multi-host training, mixed precision, and advanced input pipelines that scale from laptops to TPUs.
Features
- Functional, JAX-native module system with explicit state handling
- First-class interoperability with jit, pmap, vmap, and other transforms
- Lightweight training utilities without a heavyweight framework
- Clear RNG and parameter management for reproducibility
- Patterns for mixed precision and multi-host scaling
- Extensive examples spanning vision, NLP, and RL
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/flax.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
