In a Java11 project (actually Java Play-Framework) I depend directly on org.deeplearning4j:deeplearning4j-nlp:1.0.0-M2 in my build.sbt running SBT 1.5.5. That dependency transitively depends on several other libraries (like e.g. org.bytedeco:ffmpeg:5.0-1.5.7) that exists as platform dependent libraries and seem to use the SBT “classifier” to indicate the platform .. linux-x86, linux-x86_64, android-x86_64, windows… and so on. Now with my SBT commands like
Tag: deeplearning4j
Deeplearning4j – how to iterate multiple DataSets for large data?
I’m studying Deeplearning4j (ver. 1.0.0-M1.1) for building neural networks. I use IrisClassifier from Deeplearning4j as an example, it works fine: For my project, I have inputs ~30000 records (in iris example – 150). Each record is a vector size ~7000 (in iris example – 4). Obviously, I can’t process the whole data in one DataSet – in will produce OOM
DeepLearning4J Problems with INDArray
I use INDArray input = Nd4j.create(f); to create the INDArray but this m1.output(input) throws following exception: I do not understand why the created INDArray is two-dimensional and where the 63 is coming from.. Edit: The MultiLayerNetwork Configuration: Answer Your 63 is coming from the neural network itself. You have a shape mismatch on the number of inputs and outputs. If