First, thank you for your time
I am trying to use TraceTailAdaptive_ELBO within the SVI of an VAE and I have some questions:
I can see it does not support subsampling…so no batch training? Will it be implemented at some point?
I am not sure if this is expected but if I am running for example data with these settings:
Training size : 300 sequences
Validation size: 100 sequences
Hidden dimensions of NN in model: 50
Number of particles : 10
The first iteration it runs properly and gives a shape of [300, 50] and the next iteration would add a dimension as such [10, 300, 50], so it raises an error and cannot continue.
I have used the “number of particles” flag in other ELBO implementations and I did not have to reshape my data or anything, it was ‘automatically’ sorted out. So, I am guessing it is associated to the compulsory vectorize_particles= True and the attempt to parallelize the computations. So I am wondering if this an expected behavior?, otherwise, it means I have to change data shapes depending on the iteration…I am using a DataLoader (only 1 batch though) and I am not sure how to combine both case scenarios,
I am confused, is there any examples? (I cannot find them on the github)
Thank you very much for your time and attention,