November 2019
Intermediate to advanced
304 pages
8h 40m
English
Content preview from Java Deep Learning Cookbook
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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 ...
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