Commit graph

274 commits

Author SHA1 Message Date
ce28ac4013
slurm: add job for train_mono 2022-11-22 16:58:46 +00:00
3a0356929c
mono: drop the sparse 2022-11-22 16:20:56 +00:00
7e8f63f8ba
fixup 2022-11-21 19:38:24 +00:00
ace4c8b246
dataset_mono: debug 2022-11-21 18:46:21 +00:00
527b34942d
convnext_inverse: kernel_size 4→2 2022-11-11 19:29:37 +00:00
0662d0854b
model_mono: fix bottleneck 2022-11-11 19:11:40 +00:00
73acda6d9a
fix debug logging 2022-11-11 19:08:38 +00:00
9da059d738
model shape logging 2022-11-11 19:03:37 +00:00
00917b2698
dataset_mono: log shapes 2022-11-11 19:02:43 +00:00
54ae88b1b4
in this entire blasted project I have yet to get the rotation of anything correct....! 2022-11-11 18:58:45 +00:00
a7a475dcd1
debug 2 2022-11-11 18:38:07 +00:00
bf2f6e9b64
debug logging
it begins again
2022-11-11 18:31:40 +00:00
481eeb3759
mono: fix dataset preprocessing
rogue dimension
2022-11-11 18:31:27 +00:00
9035450213
mono: instantiate right model 2022-11-11 18:28:29 +00:00
69a2d0cf04
fixup 2022-11-11 18:27:01 +00:00
65e801cf28
train_mono: fix crash 2022-11-11 18:26:25 +00:00
8ac5159adc
dataset_mono: simplify param passing, onehot+threshold water depth data 2022-11-11 18:23:50 +00:00
3a3f7e85da
typo 2022-11-11 18:03:09 +00:00
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
ce194d9227
slurm: customise log file names 2022-11-10 21:09:34 +00:00
9384b89165
model_segmentation: spare → normal crossentropy, activation functions at end 2022-11-10 20:53:37 +00:00
b6676e7361
switch from sparse to normal crossentropy 2022-11-10 20:50:56 +00:00
d8be26d476
Merge branch 'main' of git.starbeamrainbowlabs.com:sbrl/PhD-Rainfall-Radar 2022-11-10 20:49:01 +00:00
b03388de60
dataset_segmenter: DEBUG: fix water shape 2022-11-10 20:48:21 +00:00
daf691bf43
typo 2022-11-10 19:55:00 +00:00
0aa2ce19f5
read_metadata: support file inputs as well as dirs 2022-11-10 19:53:30 +00:00
aa7d9b8cf6
fixup 2022-11-10 19:46:09 +00:00
0894bd09e8
train_predict: add error message for parrams.json not found 2022-11-10 19:45:41 +00:00
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
44ad51f483
CallbackNBatchCsv: bugfix .sort() → sorted() 2022-11-04 16:40:21 +00:00
4dddcfcb42
pretrain_predict: missing \n 2022-11-04 16:01:28 +00:00
1375201c5f
CallbackNBatchCsv: open_handle mode 2022-11-03 18:29:00 +00:00
3206d6b7e7
slurm: rename segmenter job name 2022-11-03 17:12:27 +00:00
f2ae74ce7b
how could I be so stupid..... round 2 2022-11-02 17:38:26 +00:00
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
cf872ef739
how could I be so *stupid*...... 2022-10-31 18:40:58 +00:00
da32d75778
make_callbacks: display steps, not samples 2022-10-31 18:36:28 +00:00
dfef7db421
moar debugging 2022-10-31 18:26:34 +00:00
172cf9d8ce
tweak 2022-10-31 18:19:43 +00:00
dbe35ee943
loss: comment l2 norm 2022-10-31 18:09:03 +00:00
5e60319024
fixup 2022-10-31 17:56:49 +00:00
b986b069e2
debug party time 2022-10-31 17:50:29 +00:00
458faa96d2
loss: fixup 2022-10-31 17:18:21 +00:00
55dc05e8ce
contrastive: comment weights that aren't needed 2022-10-31 16:26:48 +00:00
33391eaf16
train_predict/jsonl: don't argmax
I'm interested inthe raw values
2022-10-26 17:21:19 +01:00
74f2cdb900
train_predict: .list() → .tolist() 2022-10-26 17:12:36 +01:00
4f9d543695
train_predict: don't pass model_code
it's redundant
2022-10-26 17:11:36 +01:00
1b489518d0
segmenter: add LayerStack2Image to custom_objects 2022-10-26 17:05:50 +01:00
48ae8a5c20
LossContrastive: normalise features as per the paper 2022-10-26 16:52:56 +01:00
843cc8dc7b
contrastive: rewrite the loss function.
The CLIP paper *does* kinda make sense I think
2022-10-26 16:45:45 +01:00