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Author	SHA1	Message	Date
Starbeamrainbowlabs	9035450213	mono: instantiate right model	2022-11-11 18:28:29 +00:00
Starbeamrainbowlabs	69a2d0cf04	fixup	2022-11-11 18:27:01 +00:00
Starbeamrainbowlabs	65e801cf28	train_mono: fix crash	2022-11-11 18:26:25 +00:00
Starbeamrainbowlabs	8ac5159adc	dataset_mono: simplify param passing, onehot+threshold water depth data	2022-11-11 18:23:50 +00:00
Starbeamrainbowlabs	3a3f7e85da	typo	2022-11-11 18:03:09 +00:00
Starbeamrainbowlabs	3313f77c88	Add (untested) mono rainfall → water depth model ... * sighs * Unfortunately I can't seem to get contrastive learning to work.....	2022-11-10 22:36:11 +00:00
Starbeamrainbowlabs	ce194d9227	slurm: customise log file names	2022-11-10 21:09:34 +00:00
Starbeamrainbowlabs	9384b89165	model_segmentation: spare → normal crossentropy, activation functions at end	2022-11-10 20:53:37 +00:00
Starbeamrainbowlabs	b6676e7361	switch from sparse to normal crossentropy	2022-11-10 20:50:56 +00:00
Starbeamrainbowlabs	d8be26d476	Merge branch 'main' of git.starbeamrainbowlabs.com:sbrl/PhD-Rainfall-Radar	2022-11-10 20:49:01 +00:00
Starbeamrainbowlabs	b03388de60	dataset_segmenter: DEBUG: fix water shape	2022-11-10 20:48:21 +00:00
Starbeamrainbowlabs	daf691bf43	typo	2022-11-10 19:55:00 +00:00
Starbeamrainbowlabs	0aa2ce19f5	read_metadata: support file inputs as well as dirs	2022-11-10 19:53:30 +00:00
Starbeamrainbowlabs	aa7d9b8cf6	fixup	2022-11-10 19:46:09 +00:00
Starbeamrainbowlabs	0894bd09e8	train_predict: add error message for parrams.json not found	2022-11-10 19:45:41 +00:00
Starbeamrainbowlabs	e519b0adb3	GzipChildProcess: spawn-stream is buggy IIRC	2022-11-09 16:43:05 +00:00
Starbeamrainbowlabs	ddbf2cb734	slurm-process: -n28 → --exclusive	2022-11-04 17:42:50 +00:00
Starbeamrainbowlabs	a762664063	slurm-process: -n28 fo uniq call	2022-11-04 17:23:20 +00:00
Starbeamrainbowlabs	0166b4d09e	slurm-process: change log file names	2022-11-04 17:11:10 +00:00
Starbeamrainbowlabs	0353072d15	allow pretrain to run on gpu ... we've slashed the size of the 2nd encoder, so ti should fit naow?	2022-11-04 17:02:07 +00:00
Starbeamrainbowlabs	44ad51f483	CallbackNBatchCsv: bugfix .sort() → sorted()	2022-11-04 16:40:21 +00:00
Starbeamrainbowlabs	4dddcfcb42	pretrain_predict: missing \n	2022-11-04 16:01:28 +00:00
Starbeamrainbowlabs	1375201c5f	CallbackNBatchCsv: open_handle mode	2022-11-03 18:29:00 +00:00
Starbeamrainbowlabs	3206d6b7e7	slurm: rename segmenter job name	2022-11-03 17:12:27 +00:00
Starbeamrainbowlabs	f2ae74ce7b	how could I be so stupid..... round 2	2022-11-02 17:38:26 +00:00
Starbeamrainbowlabs	441ad92b12	slurm: fixup	2022-11-01 19:57:15 +00:00
Starbeamrainbowlabs	bc0e5f05a8	slurm: fixup	2022-11-01 19:55:04 +00:00
Starbeamrainbowlabs	784b8ed35c	recordify: catch NaN --count-file	2022-11-01 19:53:21 +00:00
Starbeamrainbowlabs	c17a4ca05a	slurm: fix sanity logic	2022-11-01 19:38:04 +00:00
Starbeamrainbowlabs	79b231198f	slurm-process: check input files are readable	2022-11-01 19:03:37 +00:00
Starbeamrainbowlabs	a69fa9f0f3	slurm: rename	2022-11-01 18:59:55 +00:00
Starbeamrainbowlabs	f8341e7d89	slurm: add .log	2022-11-01 18:59:15 +00:00
Starbeamrainbowlabs	fecc63b6a2	wrangler: write high-level job file	2022-11-01 18:56:27 +00:00
Starbeamrainbowlabs	91152ebb1c	wrangler:recordify update cli help ... we only output .jsonl.gz to a DIRECTORY, so update cli help to reflect this	2022-11-01 18:29:47 +00:00
Starbeamrainbowlabs	5f8d6dc6ea	Add metrics every 64 batches ... this is important, because with large batches it can be difficult to tell what's happening inside each epoch.	2022-10-31 19:26:10 +00:00
Starbeamrainbowlabs	cf872ef739	how could I be so *stupid*......	2022-10-31 18:40:58 +00:00
Starbeamrainbowlabs	da32d75778	make_callbacks: display steps, not samples	2022-10-31 18:36:28 +00:00
Starbeamrainbowlabs	dfef7db421	moar debugging	2022-10-31 18:26:34 +00:00
Starbeamrainbowlabs	172cf9d8ce	tweak	2022-10-31 18:19:43 +00:00
Starbeamrainbowlabs	dbe35ee943	loss: comment l2 norm	2022-10-31 18:09:03 +00:00
Starbeamrainbowlabs	5e60319024	fixup	2022-10-31 17:56:49 +00:00
Starbeamrainbowlabs	b986b069e2	debug party time	2022-10-31 17:50:29 +00:00
Starbeamrainbowlabs	458faa96d2	loss: fixup	2022-10-31 17:18:21 +00:00
Starbeamrainbowlabs	55dc05e8ce	contrastive: comment weights that aren't needed	2022-10-31 16:26:48 +00:00
Starbeamrainbowlabs	33391eaf16	train_predict/jsonl: don't argmax ... I'm interested inthe raw values	2022-10-26 17:21:19 +01:00
Starbeamrainbowlabs	74f2cdb900	train_predict: .list() → .tolist()	2022-10-26 17:12:36 +01:00
Starbeamrainbowlabs	4f9d543695	train_predict: don't pass model_code ... it's redundant	2022-10-26 17:11:36 +01:00
Starbeamrainbowlabs	1b489518d0	segmenter: add LayerStack2Image to custom_objects	2022-10-26 17:05:50 +01:00
Starbeamrainbowlabs	48ae8a5c20	LossContrastive: normalise features as per the paper	2022-10-26 16:52:56 +01:00
Starbeamrainbowlabs	843cc8dc7b	contrastive: rewrite the loss function. ... The CLIP paper *does* kinda make sense I think	2022-10-26 16:45:45 +01:00