I tried to implement a convolutional auto encoder in pytorch and applied it on MNIST. Unfortunately the train loss makes almost no progress (it does not decrease) during training. Can someone please help? I have posted my code (< 95 lines) at the following Github Gist: code is here.
could you try to remove the normalization from the transformations in your
While this is generally a good idea for classification use cases, since it will standardize your data to have a mean of zero and a stddev of 1, this might cause some troubles for your autoencoder, since you are using a sigmoid at the output layer, which limits the output values to the range
Alternatively, you could try to remove the sigmoid and let your model learn the standardized inputs.
Let me know, if that helps.