Closed richelbilderbeek closed 2 years ago
Hey
I have now added a model M0 on the master branch that is faster to train than the previous models. Running a command to train 1 epoch takes ~10s on my laptop with it, so hopefully it will speed things up a little. The model isn't really a 'smallest possible' and could be scaled down more, but since the majority of the time is spent on loading and preprocessing the data, I don't think a smaller one would matter so much for total runtime at this point.
We are working on speeding up the data loading process, hopefully that feature will be added soon.
I can have a look at making a p0 model soon as well.
Best, K
@kausmees that is great, thanks so much, I will try it out soon!
but since the majority of the time is spent on loading and preprocessing the data
Would that be true for a simulated dataset of 3 individuals with 1 SNP and phenotype as well? Those are what I use for testing :-)
@kausmees that new model is great! It brought a full GitHub Actions test run to 3 minutes!
Happily closing this Issue :+1:
Dear GenoCAE maintainers, hi @cnettel and @kausmees,
Thanks for GenoCAE and the experimental
Pheno
branch!What I would enjoy is a toy
Mx
model (e.g.M0
) and a toypx
model (e.g.p0
) that would be the smallest neural network possible, respecting the dimensions of the input and output (or: 'they just work' (although their predictions will be bad)).I have tried modifying the
/models/M1.json
and/models/p2.json
files (the latter only available on thePheno
branch), but I feel this will take you seconds to create.I would enjoy this as this would speed up my GitHub Actions test suite: now training alone takes 150 seconds, whereas I am (usually) only able in that it creates some files, not the output being useful (for useful output I would use the regular models).
Would it be easy to add toy models
Mx
(e.g.models/M0.json
) and toy modelpx
(e.g.models/p0.json
)?If I underestimate how hard this is, just let me know, and I will try harder :-)
Thanks and cheers, Richel