Java Deep Learning Cookbook

How it works...

The intent of the feedForwardWithKey() method in step 1 and 2 is to generate output/predictions for the given input dataset. A map is returned from this method. The input data is represented by the keys in the map and the results (output) are represented by values (INDArray).

feedForwardWithKey() accepts two attributes: input data and the minibatch size for feed-forward operations. The input data (features) is in the format of JavaPairRDD<K, INDArray>.

Note that RDD data is unordered. We need a way to map each input to the respective results (output). Hence, we need to have a key-value pair that maps each input to its respective output. That's the main reason why we use key values here. It has nothing to do with the inference ...