How can I fix size mismatch errors when creating layers in a Flux VAE model

Question

With the code in Python programming, can you tell me How I can fix size mismatch errors when creating layers in a Flux VAE model?

Answer 1

To fix size mismatch errors when creating layers in a Flux Variational Autoencoder (VAE) model, ensure that the output dimensions of the encoder match the input dimensions of the decoder and that the latent space size is consistent across the model.

Here is the code snippet you refer to:

In the above code, we are using the following techniques:

• Latent Space Size: Ensure the latent space size (e.g., 2 here) is consistent across both the encoder and decoder.
• Matching Dimensions: The encoder's output size (e.g., Dense(400, 2)) matches the decoder's input size.
• Reparameterization: Use the reparameterization trick to sample from the latent space.

Hence, by referring to the above, you can fix size mismatch errors when creating layers in a Flux VAE model.