import org.apache.commons.cli.*;

public class CommandLineOptions {

public static void main(String[] args) {

// Define the options

Options options = new Options();

// Add options

options.addOption("input", true, "Path to the input data file"); // Required input file

options.addOption("output", true, "Path to the output file"); // Required output file

options.addOption("learningRate", true, "Learning rate for the algorithm"); // Required learning rate

options.addOption("epochs", false, "Number of training epochs"); // Optional epochs

options.addOption("batchSize", false, "Batch size for mini-batch gradient descent"); // Optional batch size

options.addOption("modelType", false, "Type of model to use (e.g., linear, neural)"); // Optional model type

options.addOption("verbose", true, "Enable verbose output"); // Required verbose flag

// Parse the command-line arguments

CommandLineParser parser = new DefaultParser();

CommandLine cmd = parser.parse(args);

// Access the option values

String inputPath = cmd.getOptionValue("input");

String outputPath = cmd.getOptionValue("output");

double learningRate = Double.parseDouble(cmd.getOptionValue("learningRate"));

int epochs = (cmd.getOptionValue("epochs") != null) ? Integer.parseInt(cmd.getOptionValue("epochs")) : 10; //default to 10 if not specified

int batchSize = (cmd.getOptionValue("batchSize") != null) ? Integer.parseInt(cmd.getOptionValue("batchSize")) : 32; //default to 32 if not specified

String modelType = cmd.getOptionValue("modelType");

boolean verbose = cmd.getOptionValue("verbose").equals("true");

// Print the values (for demonstration)

System.out.println("Input Path: " + inputPath);

System.out.println("Output Path: " + outputPath);

System.out.println("Learning Rate: " + learningRate);

System.out.println("Epochs: " + epochs);

System.out.println("Batch Size: " + batchSize);

System.out.println("Model Type: " + modelType);

System.out.println("Verbose: " + verbose);

//Further processing based on the options goes here.

}

}