|
77b8a1a8db
|
dataset_segmenter: squeeze
|
2022-11-29 19:16:15 +00:00 |
|
|
2258b5a229
|
slurm-train: reduce RAM required by 10GB
|
2022-11-29 19:15:34 +00:00 |
|
|
01101ad30b
|
losscrossentropy: return the reduced value * facepalm *
|
2022-11-29 19:07:08 +00:00 |
|
|
ff65393e78
|
log file naming update
|
2022-11-29 18:41:14 +00:00 |
|
|
37f196a785
|
LossCrossentropy: add kwargs
|
2022-11-29 15:40:35 +00:00 |
|
|
838ff56a3b
|
mono: fix loading checkpoint
|
2022-11-29 15:25:11 +00:00 |
|
|
dba6cbffcd
|
WHY. * facepalms *
|
2022-11-28 19:33:42 +00:00 |
|
|
57b8eb93fb
|
fixup
|
2022-11-28 19:09:35 +00:00 |
|
|
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 |
|
|
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 |
|
|
fad1399c2d
|
convnext: whitespace
|
2022-10-26 16:45:20 +01:00 |
|
|
1d872cb962
|
contrastive: fix initial temperature value
It should be 1/0.07, but we had it set to 0.07......
|
2022-10-26 16:45:01 +01:00 |
|
|
f994d449f1
|
Layer2Image: fix
|
2022-10-25 21:32:17 +01:00 |
|
|
6a29105f56
|
model_segmentation: stack not reshape
|
2022-10-25 21:25:15 +01:00 |
|
|
98417a3e06
|
prepare for NCE loss
.....but Tensorflow's implementation looks to be for supervised models :-(
|
2022-10-25 21:15:05 +01:00 |
|
|
bb0679a509
|
model_segmentation: don't softmax twice
|
2022-10-25 21:11:48 +01:00 |
|
|
f2e2ca1484
|
model_contrastive: make water encoder significantly shallower
|
2022-10-24 20:52:31 +01:00 |
|
|
a6b07a49cb
|
count water/nowater pixels in Jupyter Notebook
|
2022-10-24 18:05:34 +01:00 |
|
|
a8b101bdae
|
dataset_predict: add shape_water_desired
|
2022-10-24 18:05:13 +01:00 |
|
|
587c1dfafa
|
train_predict: revamp jsonl handling
|
2022-10-21 16:53:08 +01:00 |
|
|
8195318a42
|
SparseCategoricalAccuracy: losses → metrics
|
2022-10-21 16:51:20 +01:00 |
|
|
612735aaae
|
rename shuffle arg
|
2022-10-21 16:35:45 +01:00 |
|
|
c98d8d05dd
|
segmentation: use the right accuracy
|
2022-10-21 16:17:05 +01:00 |
|
|
bb0258f5cd
|
flip squeeze operator ordering
|
2022-10-21 15:38:57 +01:00 |
|
|
af26964c6a
|
batched_iterator: reset i_item after every time
|
2022-10-21 15:35:43 +01:00 |
|