|
df774146d9
|
dataset_segmenter: reshape, not squeeze
|
2022-11-29 19:24:54 +00:00 |
|
|
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 |
|
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f6feb125e3
|
this iss ome serious debugging.
This commit will produce an extremely large volume of output.
|
2022-11-28 18:57:41 +00:00 |
|
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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 |
|
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e7410fb480
|
train_mono_predict: limit label size to 64x64
that's the size the model predicts
|
2022-11-25 17:47:17 +00:00 |
|
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51dd484d13
|
fixup
|
2022-11-25 16:55:45 +00:00 |
|
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884c4eb150
|
rainfall_stats: formatting again
|
2022-11-24 19:08:07 +00:00 |
|
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bfe038086c
|
rainfall_stats: formatting
|
2022-11-24 19:07:44 +00:00 |
|
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7dba03200f
|
fixup
|
2022-11-24 19:06:48 +00:00 |
|
|
e5258b9c66
|
typo
|
2022-11-24 19:06:13 +00:00 |
|
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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 |
|
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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 |
|
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773944f9fa
|
train_mono_predict: initial implementation
|
2022-11-24 16:33:50 +00:00 |
|
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d31326cb30
|
slurm train mono: fix partition name
|
2022-11-22 17:02:02 +00:00 |
|
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ce28ac4013
|
slurm: add job for train_mono
|
2022-11-22 16:58:46 +00:00 |
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3a0356929c
|
mono: drop the sparse
|
2022-11-22 16:20:56 +00:00 |
|
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7e8f63f8ba
|
fixup
|
2022-11-21 19:38:24 +00:00 |
|
|
ace4c8b246
|
dataset_mono: debug
|
2022-11-21 18:46:21 +00:00 |
|
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527b34942d
|
convnext_inverse: kernel_size 4→2
|
2022-11-11 19:29:37 +00:00 |
|
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0662d0854b
|
model_mono: fix bottleneck
|
2022-11-11 19:11:40 +00:00 |
|
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73acda6d9a
|
fix debug logging
|
2022-11-11 19:08:38 +00:00 |
|
|
9da059d738
|
model shape logging
|
2022-11-11 19:03:37 +00:00 |
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00917b2698
|
dataset_mono: log shapes
|
2022-11-11 19:02:43 +00:00 |
|
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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 |
|
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481eeb3759
|
mono: fix dataset preprocessing
rogue dimension
|
2022-11-11 18:31:27 +00:00 |
|
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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 |
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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 |
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d8be26d476
|
Merge branch 'main' of git.starbeamrainbowlabs.com:sbrl/PhD-Rainfall-Radar
|
2022-11-10 20:49:01 +00:00 |
|
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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 |
|
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44ad51f483
|
CallbackNBatchCsv: bugfix .sort() → sorted()
|
2022-11-04 16:40:21 +00:00 |
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4dddcfcb42
|
pretrain_predict: missing \n
|
2022-11-04 16:01:28 +00:00 |
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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 |
|
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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 |
|
|
c5b1501dba
|
train-predict fixup
|
2022-10-21 15:27:39 +01:00 |
|
|
42aea7a0cc
|
plt.close() fixup
|
2022-10-21 15:23:54 +01:00 |
|
|
12dad3bc87
|
vis/segmentation: fix titles
|
2022-10-21 15:22:35 +01:00 |
|
|
0cb2de5d06
|
train-preedict: close matplotlib after we've finished
they act like file handles
|
2022-10-21 15:19:31 +01:00 |
|
|
81e53efd9c
|
PNG: create output dir if doesn't exist
|
2022-10-21 15:17:39 +01:00 |
|
|
3f7db6fa78
|
fix embedding confusion
|
2022-10-21 15:15:59 +01:00 |
|
|
847cd97ec4
|
fixup
|
2022-10-21 14:26:58 +01:00 |
|
|
0e814b7e98
|
Contraster → Segmenter
|
2022-10-21 14:25:43 +01:00 |
|
|
1b658a1b7c
|
train-predict: can't destructure array when iterating generator
....it seems to lead to undefined behaviour or something
|
2022-10-20 19:34:04 +01:00 |
|
|
aed2348a95
|
train_predict: fixup
|
2022-10-20 15:42:33 +01:00 |
|
|
cc6679c609
|
batch data; use generator
|
2022-10-20 15:22:29 +01:00 |
|
|
d306853c42
|
use right daataset
|
2022-10-20 15:16:24 +01:00 |
|
|
59cfa4a89a
|
basename paths
|
2022-10-20 15:11:14 +01:00 |
|
|
4d8ae21a45
|
update cli help text
|
2022-10-19 17:31:42 +01:00 |
|
|
200076596b
|
finish train_predict
|
2022-10-19 17:26:40 +01:00 |
|
|
488f78fca5
|
pretrain_predict: default to parallel_reads=0
|
2022-10-19 16:59:45 +01:00 |
|
|
63e909d9fc
|
datasets: add shuffle=True/False to get_filepaths.
This is important because otherwise it SCAMBLES the filenames, which is a disaster for making predictions in the right order....!
|
2022-10-19 16:52:07 +01:00 |
|
|
fe43ddfbf9
|
start implementing driver for train_predict, but not finished yet
|
2022-10-18 19:37:55 +01:00 |
|
|
b3ea189d37
|
segmentation: softmax the output
|
2022-10-13 21:02:57 +01:00 |
|
|
f121bfb981
|
fixup summaryfile
|
2022-10-13 17:54:42 +01:00 |
|
|
5c35c0cee4
|
model_segmentation: document; remove unused args
|
2022-10-13 17:50:16 +01:00 |
|
|
f12e6ab905
|
No need for a CLI arg for feature_dim_in - metadata should contain this
|
2022-10-13 17:37:16 +01:00 |
|
|
e201372252
|
write quick Jupyter notebook to test data
....I'm paranoid
|
2022-10-13 17:27:17 +01:00 |
|
|
ae53130e66
|
layout
|
2022-10-13 14:54:20 +01:00 |
|
|
7933564c66
|
typo
|
2022-10-12 17:33:54 +01:00 |
|
|
dbe4fb0eab
|
train: add slurm job file
|
2022-10-12 17:27:10 +01:00 |
|
|
6423bf6702
|
LayerConvNeXtGamma: avoid adding an EagerTensor to config
Very weird how this is a problem when it wasn't before..
|
2022-10-12 17:12:07 +01:00 |
|
|
32f5200d3b
|
pass model_arch properly
|
2022-10-12 16:50:06 +01:00 |
|
|
5933fb1061
|
fixup
|
2022-10-11 19:23:41 +01:00 |
|
|
c45b90764e
|
segmentation: adds xxtiny, but unsure if it's small enough
|
2022-10-11 19:22:37 +01:00 |
|
|
f4a2c742d9
|
typo
|
2022-10-11 19:19:23 +01:00 |
|
|
11f91a7cf4
|
train: add --arch; default to convnext_i_xtiny
|
2022-10-11 19:18:01 +01:00 |
|
|
5666c5a0d9
|
typo
|
2022-10-10 18:12:51 +01:00 |
|
|
131c0a0a5b
|
pretrain-predict: create dir if not exists
|
2022-10-10 18:00:55 +01:00 |
|
|
deede32241
|
slurm-pretrain: limit memory usage
|
2022-10-10 17:45:29 +01:00 |
|
|
13a8f3f511
|
pretrain-predict: only queue pretrain-plot if I we output jsonl
|
2022-10-10 17:11:10 +01:00 |
|
|
ffcb2e3735
|
pretrain-predict: queue for the actual input
|
2022-10-10 16:53:28 +01:00 |
|
|
f883986eaa
|
Bugfix: modeset to enable TFRecordWriter instead of bare handle
|
2022-10-06 20:07:59 +01:00 |
|
|
e9a8e2eb57
|
fixup
|
2022-10-06 19:23:31 +01:00 |
|
|
9f3ae96894
|
finish wiring for --water-size
|
2022-10-06 19:21:50 +01:00 |
|
|
5dac70aa08
|
typo
|
2022-10-06 19:17:03 +01:00 |
|
|
2960d3b645
|
exception → warning
|
2022-10-06 18:26:40 +01:00 |
|
|
0ee6703c1e
|
Add todo and comment
|
2022-10-03 19:06:56 +01:00 |
|
|
2b182214ea
|
typo
|
2022-10-03 17:53:10 +01:00 |
|
|
92c380bff5
|
fiddle with Conv2DTranspose
you need to set the `stride` argument to actually get it to upscale..... :P
|
2022-10-03 17:51:41 +01:00 |
|
|
d544553800
|
fixup
|
2022-10-03 17:33:06 +01:00 |
|
|
058e3b6248
|
model_segmentation: cast float → int
|
2022-10-03 17:31:36 +01:00 |
|
|
04e5ae0c45
|
model_segmentation: redo reshape
much cheese was applied :P
|
2022-10-03 17:27:52 +01:00 |
|
|
deffe69202
|
typo
|
2022-10-03 16:59:36 +01:00 |
|
|
fc6d2dabc9
|
Upscale first, THEN convnext...
|
2022-10-03 16:38:43 +01:00 |
|
|
6a0790ff50
|
convnext_inverse: add returns; change ordering
|
2022-10-03 16:32:09 +01:00 |
|
|
fe813cb46d
|
slurm predict: fix plotting subcall
|
2022-10-03 16:03:26 +01:00 |
|
|
e51087d0a9
|
add reshape layer
|
2022-09-28 18:22:48 +01:00 |
|
|
a336cdee90
|
and continues
|
2022-09-28 18:18:10 +01:00 |
|
|
de47a883d9
|
missing units
|
2022-09-28 18:17:22 +01:00 |
|
|
b5e08f92fe
|
the long night continues
|
2022-09-28 18:14:09 +01:00 |
|
|
dc159ecfdb
|
and again
|
2022-09-28 18:11:46 +01:00 |
|
|
4cf0485e32
|
fixup... again
|
2022-09-28 18:10:11 +01:00 |
|
|
030d8710b6
|
fixup
|
2022-09-28 18:08:31 +01:00 |
|
|
4ee7f2a0d6
|
add water thresholding
|
2022-09-28 18:07:26 +01:00 |
|
|
404dc30f08
|
and again
|
2022-09-28 17:39:09 +01:00 |
|
|
4cd8fc6ded
|
segmentation: param name fix
|
2022-09-28 17:37:42 +01:00 |
|
|
41ba980d69
|
segmentationP implement dataset parser
|
2022-09-28 17:19:21 +01:00 |
|
|
d618e6f8d7
|
pretrain-predict: params.json → metadata.jsonl
|
2022-09-28 16:35:22 +01:00 |
|
|
e9e6139c7a
|
typo
|
2022-09-28 16:28:18 +01:00 |
|
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3dee3d8908
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update cli help
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2022-09-28 16:23:47 +01:00 |
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b836f7f70c
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again
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2022-09-27 19:06:41 +01:00 |
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52dff130dd
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slurm pretraian predict: moar logging
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2022-09-27 19:05:54 +01:00 |
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2d24174e0a
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slurm pretrain predict: add $OUTPUT
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2022-09-27 18:58:02 +01:00 |
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7d0e3913ae
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fix logging
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2022-09-27 18:51:58 +01:00 |
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d765b3b14e
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fix crash
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2022-09-27 18:43:43 +01:00 |
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2cd59a01a5
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slurm-pretrain-plot: add ARGS
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2022-09-27 18:41:35 +01:00 |
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f4d1d1d77e
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just wh
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2022-09-27 18:25:45 +01:00 |
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4c24d69ae6
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$d → +d
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2022-09-27 18:17:07 +01:00 |
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cdb19b4d9f
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fixup
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2022-09-27 18:13:21 +01:00 |
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c4d3c16873
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add some logging
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2022-09-27 18:10:58 +01:00 |
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3772c3227e
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fixup
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2022-09-27 17:57:21 +01:00 |
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dbfa45a016
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write params.json properly
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2022-09-27 17:49:54 +01:00 |
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a5455dc22a
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fix import
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2022-09-27 17:41:24 +01:00 |
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d6ff3fb2ce
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pretrain_predict fix write mode
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2022-09-27 17:38:12 +01:00 |
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f95fd8f9e4
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pretrain-predict: add .tfrecord output function
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2022-09-27 16:59:31 +01:00 |
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30b8dd063e
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fixup
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2022-09-27 15:54:37 +01:00 |
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3cf99587e4
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Contraster: add gamma layer to load_model
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2022-09-27 15:53:52 +01:00 |
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9e9852d066
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UMAP: 100k random
no labels.
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2022-09-27 15:52:45 +01:00 |
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58c65bdc86
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slurm: allow predictions on gpu
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2022-09-23 19:21:57 +01:00 |
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d59de41ebb
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embeddings: change title rendering; make even moar widererer
We need to see that parallel coordinates plot in detail
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2022-09-23 18:56:39 +01:00 |
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b4ddb24589
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slurm plot: compute → highmem
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2022-09-22 18:27:58 +01:00 |
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df12470e78
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flip conda and time
hopefully we can capture the exit code this way
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2022-09-21 14:40:28 +01:00 |
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5252a81238
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vis: don't call add_subplot
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2022-09-20 19:06:21 +01:00 |
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32bb55652b
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slurm predict: autoqueue UMAP plot
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2022-09-16 19:36:57 +01:00 |
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24c5263bf0
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slurm predict-plot: fixup
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2022-09-16 19:27:26 +01:00 |
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7e9c119b04
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slurm: fix job name
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2022-09-16 19:20:59 +01:00 |
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1574529704
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slurm pretrain-predict: move to compute; make exclusive just in case
also shortent o 3 days
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2022-09-16 19:17:42 +01:00 |
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d7f5958af0
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slurm: write new job files
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2022-09-16 19:00:43 +01:00 |
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a552cc4dad
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ai vis: make parallel coordinates wider
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2022-09-16 18:51:49 +01:00 |
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a70794e661
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umap: no min_dist
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2022-09-16 17:09:09 +01:00 |
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5778fc51f7
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embeddings: fix title; remove colourmap
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2022-09-16 17:08:04 +01:00 |
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4fd852d782
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fixup
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2022-09-16 16:44:35 +01:00 |
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fcab227f6a
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cheese: set label for everything to 1
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2022-09-16 16:42:05 +01:00 |
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b31645bd5d
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pretrain-plot: fix crash; remove water code
the model doesn't save the water encoder at this time
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2022-09-16 16:24:07 +01:00 |
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a5f03390ef
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pretrain-plot: handle open w -> r
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2022-09-16 16:14:30 +01:00 |
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1103ae5561
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ai: tweak progress bar
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2022-09-16 16:07:16 +01:00 |
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1e35802d2b
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ai: fix embed i/o
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2022-09-16 16:02:27 +01:00 |
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ed94da7492
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fixup
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2022-09-16 15:51:26 +01:00 |
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366db658a8
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ds predict: fix filenames in
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2022-09-16 15:45:22 +01:00 |
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e333dcba9c
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tweak projection head
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2022-09-16 15:36:01 +01:00 |
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6defd24000
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bugfix: too many values to unpack
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2022-09-15 19:56:17 +01:00 |
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e3c8277255
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ai: tweak the segmentation model structure
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2022-09-15 19:54:50 +01:00 |
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1bc8a5bf13
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ai: fix crash
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2022-09-15 19:37:06 +01:00 |
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bd64986332
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ai: implement batched_iterator to replace .batch()
...apparently .batch() means you get a BatchedDataset or whatever when you iterate it like a tf.function instead of the actual tensor :-/
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2022-09-15 19:16:38 +01:00 |
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ccd256c00a
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embed rainfall radar, not both
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2022-09-15 17:37:04 +01:00 |
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2c74676902
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predict → predict_on_batch
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2022-09-15 17:31:50 +01:00 |
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f036e79098
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fixup
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2022-09-15 17:09:26 +01:00 |
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d5f1a26ba3
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disable prefetching when predicting a thing
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2022-09-15 17:09:09 +01:00 |
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8770638022
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ai: call .predict(), not the model itself
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2022-09-14 17:41:01 +01:00 |
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a96cefde62
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ai: predict oops
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2022-09-14 17:37:48 +01:00 |
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fa3165a5b2
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dataset: simplify dataset_predict
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2022-09-14 17:33:17 +01:00 |
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279e27c898
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fixup
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2022-09-14 17:16:49 +01:00 |
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fad3313ede
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fixup
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2022-09-14 17:14:04 +01:00 |
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1e682661db
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ai: kwargs in from_checkpoint
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2022-09-14 17:11:06 +01:00 |
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6bda24d4da
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ai: how did I miss that?!
bugfix ah/c
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2022-09-14 16:53:43 +01:00 |
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decdd434d8
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ai from_checkpoint: bugfix
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2022-09-14 16:49:01 +01:00 |
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c9e00ea485
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pretrain_predict: fix import
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2022-09-14 16:02:36 +01:00 |
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f568d8d19f
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io.open → handle_open
this was we get transparent .gz support
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2022-09-14 16:01:22 +01:00 |
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9b25186541
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fix --only-gpu
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2022-09-14 15:55:21 +01:00 |
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a9c9c70d13
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typo
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2022-09-14 15:17:59 +01:00 |
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fb8f884487
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add umap dependencies
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2022-09-14 15:16:45 +01:00 |
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1876a8883c
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ai pretrain-predict: fix - → _ in cli parsing
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2022-09-14 15:12:07 +01:00 |
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f97b771922
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make --help display help
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2022-09-14 15:03:07 +01:00 |
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3c1aef5913
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update help
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2022-09-13 19:36:56 +01:00 |
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206257f9f5
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ai pretrain_predict: no need to plot here anymore
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2022-09-13 19:35:44 +01:00 |
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7685ec3e8b
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implement ability to embed & plot pretrained embeddings
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2022-09-13 19:18:59 +01:00 |
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7130c4fdf8
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start implementing core image segmentation model
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2022-09-07 17:45:38 +01:00 |
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22620a1854
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ai: implement saving only the rainfall encoder
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2022-09-06 19:48:46 +01:00 |
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4c4358c3e5
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whitespace
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2022-09-06 16:24:11 +01:00 |
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4202821d98
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typo
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2022-09-06 15:37:36 +01:00 |
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3e13ad12c8
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ai Bugfix LayerContrastiveEncoder: channels → input_channels
for consistency
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2022-09-05 23:53:16 +01:00 |
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ead8009425
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pretrain: add CLI arg for size of watch prediction width/height
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2022-09-05 15:36:40 +01:00 |
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9d39215dd5
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dataset: drop incomplete batches
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2022-09-05 15:36:10 +01:00 |
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c94f5d042e
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ai: slurm fixup again
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2022-09-02 19:13:56 +01:00 |
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7917820e59
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ai: slurm fixup
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2022-09-02 19:11:54 +01:00 |
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cd104190e8
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slurm: no need to be exclusive anymore
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2022-09-02 19:09:45 +01:00 |
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a9dede7bfe
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ai: n=10 slurm
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2022-09-02 19:09:07 +01:00 |
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42de502f99
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slurm-pretrain: set name
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2022-09-02 19:08:16 +01:00 |
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457c2eef0d
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ai: fixup
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2022-09-02 19:06:54 +01:00 |
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a3f03b6d8d
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slurm-pretrain: prepare
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2022-09-02 19:05:18 +01:00 |
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1d1533d160
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ai: how did things get this confusing
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2022-09-02 18:51:46 +01:00 |
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1c5defdcd6
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ai: cats
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2022-09-02 18:45:23 +01:00 |
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6135bcd0cd
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fixup
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2022-09-02 18:41:31 +01:00 |
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