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4f9d543695
|
train_predict: don't pass model_code
it's redundant
|
2022-10-26 17:11:36 +01:00 |
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1b489518d0
|
segmenter: add LayerStack2Image to custom_objects
|
2022-10-26 17:05:50 +01:00 |
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48ae8a5c20
|
LossContrastive: normalise features as per the paper
|
2022-10-26 16:52:56 +01:00 |
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843cc8dc7b
|
contrastive: rewrite the loss function.
The CLIP paper *does* kinda make sense I think
|
2022-10-26 16:45:45 +01:00 |
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fad1399c2d
|
convnext: whitespace
|
2022-10-26 16:45:20 +01:00 |
|
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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 |
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|
f994d449f1
|
Layer2Image: fix
|
2022-10-25 21:32:17 +01:00 |
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|
6a29105f56
|
model_segmentation: stack not reshape
|
2022-10-25 21:25:15 +01:00 |
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98417a3e06
|
prepare for NCE loss
.....but Tensorflow's implementation looks to be for supervised models :-(
|
2022-10-25 21:15:05 +01:00 |
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bb0679a509
|
model_segmentation: don't softmax twice
|
2022-10-25 21:11:48 +01:00 |
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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 |
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a8b101bdae
|
dataset_predict: add shape_water_desired
|
2022-10-24 18:05:13 +01:00 |
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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 |
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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 |
|
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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 |
|
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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 |
|
|
3dee3d8908
|
update cli help
|
2022-09-28 16:23:47 +01:00 |
|
|
b836f7f70c
|
again
|
2022-09-27 19:06:41 +01:00 |
|
|
52dff130dd
|
slurm pretraian predict: moar logging
|
2022-09-27 19:05:54 +01:00 |
|
|
2d24174e0a
|
slurm pretrain predict: add $OUTPUT
|
2022-09-27 18:58:02 +01:00 |
|
|
7d0e3913ae
|
fix logging
|
2022-09-27 18:51:58 +01:00 |
|
|
d765b3b14e
|
fix crash
|
2022-09-27 18:43:43 +01:00 |
|
|
2cd59a01a5
|
slurm-pretrain-plot: add ARGS
|
2022-09-27 18:41:35 +01:00 |
|
|
f4d1d1d77e
|
just wh
|
2022-09-27 18:25:45 +01:00 |
|
|
4c24d69ae6
|
$d → +d
|
2022-09-27 18:17:07 +01:00 |
|
|
cdb19b4d9f
|
fixup
|
2022-09-27 18:13:21 +01:00 |
|
|
c4d3c16873
|
add some logging
|
2022-09-27 18:10:58 +01:00 |
|
|
3772c3227e
|
fixup
|
2022-09-27 17:57:21 +01:00 |
|
|
dbfa45a016
|
write params.json properly
|
2022-09-27 17:49:54 +01:00 |
|
|
a5455dc22a
|
fix import
|
2022-09-27 17:41:24 +01:00 |
|
|
d6ff3fb2ce
|
pretrain_predict fix write mode
|
2022-09-27 17:38:12 +01:00 |
|
|
f95fd8f9e4
|
pretrain-predict: add .tfrecord output function
|
2022-09-27 16:59:31 +01:00 |
|