I have created an autoencoder using a separate encoder and decoder as described in this link. Split autoencoder on encoder and decoder keras I am checkpointing my autoencoder as followed. How do I save the encoder and decoder separately corresponding to the autoencoder? Alternatively, can I extract deep encoder and decoder from my save autoencoder? Answer You could try to
Tag: autoencoder
InvalidArgumentError training multivariate LSTM autoencoder
I tried to do experiments in different datasets using this model, it works fine for univariate time series. However, I get an issue when trying to do it for multivariate time series and I think it’s due to Time Distributed layer but I am not sure. I tried to read different posts about the same question with no luck. trainx
During creating VAE model throws exception “you should implement a `call` method.”
I want to create VAE(variational autoencoder). During model creating it throws exception. When subclassing the Model class, you should implement a call method. I am using Tensorflow 2.0 Models with names I want to get model. Answer The problem is here: You are passing three arguments to the construction, where only two are needed (inputs and outputs). Models do not
Split autoencoder on encoder and decoder keras
I am trying to create an autoencoder for: Train the model Split encoder and decoder Visualise compressed data (encoder) Use arbitrary compressed data to get the output (decoder) How to split train it and split with the trained weights? Answer Make encoder: Make decoder: Make autoencoder: Now you can use any of them any way you want to. train the