Java Deep Learning Cookbook

How it works...

In step 4, we set up a strategy by which the network configurations will be picked up from the search space. We use CandidateGenerator for this purpose. We created a parameter mapping to store all data mappings for use with the data source and passed it to CandidateGenerator.

In step 5, we implemented the configure() method along with three other methods from the DataSource interface. The configure() method accepts a Properties attribute, which has all parameters to be used with the data source. If we want to pass miniBatchSize as a property, then we can create a Properties instance as shown here:

Properties dataSourceProperties = new Properties(); dataSourceProperties.setProperty("minibatchSize", "64");

Note that the minibatch ...