4 commits

Author	SHA1	Message	Date
Starbeamrainbowlabs	654eefd9ca	properly handle water dimensions; add log files to .gitignore ... TODO: add heightmap	2022-08-31 18:03:39 +01:00
Starbeamrainbowlabs	28a3f578d5	update .gitignore	2022-08-04 16:49:53 +01:00
Starbeamrainbowlabs	1297f41105	.tfrecord files are too much hassle ... let's go with a standard of .jsonl.gz instead	2022-07-01 18:28:39 +01:00
Starbeamrainbowlabs	8a9cd6c1c0	Lay out some basic scaffolding ... I *really* hope this works. This is the 3rd major revision of this model. I've learnt a ton of stuff between now and my last attempt, so here's hoping that all goes well :D The basic idea behind this attempt is *Contrastive Learning*. If we don't get anything useful with this approach, then we can assume that it's not really possible / feasible. Something we need to watch out for is the variance (or rather lack thereof) in the dataset. We have 1.5M timesteps, but not a whole lot will be happening in most of those.... We may need to analyse the variance of the water depth data and extract a subsample that's more balanced.	2022-05-13 19:06:15 +01:00