Commit graph

367 commits

Author SHA1 Message Date
6640a41bb7
almost got it....? it's not what I expected....! 2022-11-28 19:08:50 +00:00
f48473b703
fixup 2022-11-28 19:00:11 +00:00
f6feb125e3
this iss ome serious debugging.
This commit will produce an extremely large volume of output.
2022-11-28 18:57:41 +00:00
09f81b0746
train_mono: debug
this commit will generate a large amount of debug output.
2022-11-28 16:46:17 +00:00
f39e4ade70
LayerConvNextGamma: fix config serialisation bug
.....this is unlikely to be the problem as this bug is in an unused code path.
2022-11-25 21:16:31 +00:00
e7410fb480
train_mono_predict: limit label size to 64x64
that's the size the model predicts
2022-11-25 17:47:17 +00:00
51dd484d13
fixup 2022-11-25 16:55:45 +00:00
884c4eb150
rainfall_stats: formatting again 2022-11-24 19:08:07 +00:00
bfe038086c
rainfall_stats: formatting 2022-11-24 19:07:44 +00:00
7dba03200f
fixup 2022-11-24 19:06:48 +00:00
e5258b9c66
typo 2022-11-24 19:06:13 +00:00
64d646bb13
rainfall_stats: formatting 2022-11-24 19:05:35 +00:00
675c7a7448
fixup 2022-11-24 19:03:28 +00:00
afc1cdcf02
fixup 2022-11-24 19:02:58 +00:00
e4bea89c89
typo 2022-11-24 19:01:52 +00:00
a40cbe8705
rainfall_stats: remove unused imports 2022-11-24 19:01:18 +00:00
fe57d6aab2
rainfall_stats: initial implementation
this might reveal why we are having problems. If most/all the rainfall radar
data is v small numbers, normalising
might help.
2022-11-24 18:58:16 +00:00
3131b4f7b3
debug2 2022-11-24 18:25:32 +00:00
d55a13f536
debug 2022-11-24 18:24:03 +00:00
1f60f2a580
do_argmax 2022-11-24 18:11:03 +00:00
6c09d5254d
fixup 2022-11-24 17:57:48 +00:00
54a841efe9
train_mono_predict: convert to correct format 2022-11-24 17:56:07 +00:00
105dc5bc56
missing kwargs 2022-11-24 17:51:29 +00:00
1e1d6dd273
fixup 2022-11-24 17:48:19 +00:00
011e0aef78
update cli docs 2022-11-24 16:38:07 +00:00
773944f9fa
train_mono_predict: initial implementation 2022-11-24 16:33:50 +00:00
d31326cb30
slurm train mono: fix partition name 2022-11-22 17:02:02 +00:00
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
4b2e418ddc
finish comment
...oops
2022-11-11 18:55:35 +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