GPU is identified and available to WekaDeeplearning4j. install-cuda-libs.sh ~/Downloads/wekaDeeplearning4j-cuda-10.2-1.6.0-linux-x86_64.zipĮnsuring your GPU is setup correctly may be difficult so to help out we've provided IsGPUAvailable, a simple diagnostic tool to test whether your If you want to download the library zip yourself, choose the appropriate combination of your platform and CUDA version from the latest release and point the installation script to the file, e.g.
#WEKA JAR FILES INSTALL#
The install script automatically downloads the libraries and copies them into your wekaDeeplearning4j package installation. Make sure CUDA is installed on your system as explained here. To add GPU support, download and run the latest install-cuda-libs.sh for Linux/Macosx or install-cuda-libs.ps1 for Windows. Which results in Installed Repository Loaded Packageġ.5.6 - Yes : Weka wrappers for Deeplearning4j You can check whether the installation was successful with $ java -cp \ Where must be replaced by the path pointing to the Weka jar file, and is the wekaDeeplearning4j package zip file. Weka packages can be easily installed either via the user interface as described here, or simply via the commandline: $ java -cp \ Nvidia provides some good installation instructions for all platforms: The GPU additions needs the CUDA Toolkit 10.0, 10.1, or 10.2 backend with the appropriate cuDNN library to be installed on your system.
CPUįor the package no further requisites are necessary.
#WEKA JAR FILES ZIP FILE#
You need to unzip the Weka zip file to a directory of your choice. WekaDeeplearning4j package latest version ( here).
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