This is the Windows app named frugally-deep whose latest release can be downloaded as v0.18.2sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named frugally-deep 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
Ad
frugally-deep
DESCRIPTION
Use Keras models in C++ with ease. A lightweight header-only library for using Keras (TensorFlow) models in C++. Works out-of-the-box also when compiled into a 32-bit executable. (Of course, 64 bit is fine too.) Avoids temporarily allocating (potentially large chunks of) additional RAM during convolutions (by not materializing the im2col input matrix). Utterly ignores even the most powerful GPU in your system and uses only one CPU core per prediction. Quite fast on one CPU core, and you can run multiple predictions in parallel, thus utilizing as many CPUs as you like to improve the overall prediction throughput of your application/pipeline.
Features
- Is a small header-only library written in modern and pure C++
- Very easy to integrate and use
- Depends only on FunctionalPlus, Eigen and json - also header-only libraries
- Supports inference (model.predict) not only for sequential models but also for computational graphs with a more complex topology, created with the functional API
- Re-implements a (small) subset of TensorFlow, i.e., the operations needed to support prediction
- Results in a much smaller binary size than linking against TensorFlow
Programming Language
C++
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/frugally-deep.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
