Secure your code as it's written. Use Snyk Code to scan source code in minutes - no build needed - and fix issues immediately.
optimizer: tf.train.adam(args.learningRate, args.adamBeta1),
loss: ['binaryCrossentropy', 'sparseCategoricalCrossentropy']
});
discriminator.summary();
// Build the generator.
const generator = buildGenerator(args.latentSize);
generator.summary();
const optimizer = tf.train.adam(args.learningRate, args.adamBeta1);
const combined = buildCombinedModel(
args.latentSize, generator, discriminator, optimizer);
await data.loadData();
let {images: xTrain, labels: yTrain} = data.getTrainData();
yTrain = tf.expandDims(yTrain.argMax(-1), -1);
// Save the generator model once before starting the training.
await generator.save(saveURL);
let numTensors;
let logWriter;
if (args.logDir) {
console.log(`Logging to tensorboard at logdir: ${args.logDir}`);
logWriter = tf.node.summaryFileWriter(args.logDir);
}
let step = 0;
for (let epoch = 0; epoch < args.epochs; ++epoch) {
// Write some metadata to disk at the beginning of every epoch.
fs.writeFileSync(
metadataPath,