train a gan in matlab

main.m
% Load and preprocess your dataset
imds = imageDatastore('path/to/your/images');
augmenter = imageDataAugmenter('RandXReflection', true);
augimds = augmentedImageDatastore([height, width], imds, 'DataAugmentation', augmenter);

% Define the generator and discriminator models
generator = % define your generator model here
discriminator = % define your discriminator model here

% Define the loss functions for the generator and discriminator
gan = ganModel(generator, discriminator);
generatorLoss = 'binarycrossentropy';
discriminatorLoss = 'binarycrossentropy';

% Train the GAN using the generated training data
options = trainingOptions('adam', 'MaxEpochs', numEpochs, 'Verbose', true);
[ganTrained, info] = trainNetwork(augimds, gan, options);
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