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JAX - Download

Free download JAX Windows app to run online win Wine in Ubuntu online, Fedora online or Debian online

This is the Windows app named JAX whose latest release can be downloaded as Jaxlibreleasev0.1.74.zip. It can be run online in the free hosting provider OnWorks for workstations.

Download and run online this app named JAX 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 any OS OnWorks online emulator from this website, but better Windows online emulator.

- 5. From the OnWorks Windows 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 and install it.

- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.

Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.

SCREENSHOTS:

JAX


DESCRIPTION:

With its updated version of Autograd, JAX can automatically differentiate native Python and NumPy functions. It can differentiate through loops, branches, recursion, and closures, and it can take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation) via grad as well as forward-mode differentiation, and the two can be composed arbitrarily to any order. What’s new is that JAX uses XLA to compile and run your NumPy programs on GPUs and TPUs. Compilation happens under the hood by default, with library calls getting just-in-time compiled and executed. But JAX also lets you just-in-time compile your own Python functions into XLA-optimized kernels using a one-function API, jit. Compilation and automatic differentiation can be composed arbitrarily, so you can express sophisticated algorithms and get maximal performance without leaving Python.



Features

  • JAX is Autograd and XLA, brought together for high-performance machine learning research
  • You can even program multiple GPUs or TPU cores at once using pmap, and differentiate through the whole thing
  • JAX is really an extensible system for composable function transformations
  • Jump right in using a notebook in your browser, connected to a Google Cloud GPU
  • At its core, JAX is an extensible system for transforming numerical functions
  • You can use XLA to compile your functions end-to-end


Programming Language

Python



This is an application that can also be fetched from https://sourceforge.net/projects/jax.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.


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