 let imageWidth = 28
 
 let outputFolder = "./output/"
-let dataset = OldFashionMNIST(batchSize: batchSize, flattening: true)
+let dataset = FashionMNIST(batchSize: batchSize, device: Device.default, 
+    entropy: SystemRandomNumberGenerator(), flattening: true)
 // An autoencoder.
 var autoencoder = Sequential {
     // The encoder.


        optimizer.update(&autoencoder, along: 𝛁model)
    }
}

}
let optimizer = RMSProp(for: autoencoder)


// Training loop
for (epoch, epochBatches) in dataset.training.prefix(epochCount).enumerated() {
    for batch in epochBatches {
        let x = batch.data

        let 𝛁model = TensorFlow.gradient(at: autoencoder) { autoencoder -> Tensor<Float> in
            let image = autoencoder(x)
