Therefore, the autoencoder input and output both have 65 values -- 64 pixel grayscale ... set eval() mode because the demo does not use dropout or batch normalization during training, but it's good ...

The learning rate controls how much the weights and biases change on each update during training ... and outputs because an autoencoder predicts its input. The smaller the value of mean squared error, ...

These models, particularly latent diffusion models, operate in the latent encoding space of a pre-trained autoencoder ... training window size, thereby overcoming the limitations of fixed-size output.