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c17e53ca75
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deeplabv3+ for rainfall
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2022-12-16 19:52:59 +00:00 |
|
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677e39f820
|
work on slurm for deeplabv3+ rainfall, but it's NOT FINISHED YET
|
2022-12-16 19:52:44 +00:00 |
|
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423e277ed1
|
add comment
|
2022-12-15 19:33:25 +00:00 |
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ef5071b569
|
DeepLabV3+: start working on version for rainfall radar, but it's not finished yet
|
2022-12-15 19:33:14 +00:00 |
|
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15a3150127
|
DeepLabV3+: close each matplotlib figure after writing it
|
2022-12-15 19:14:07 +00:00 |
|
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6ce121f861
|
DeepLabV3+: have argument for number of channels
|
2022-12-14 17:36:30 +00:00 |
|
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1dc2ec3a46
|
DeepLabV3+: pathing.... again
|
2022-12-13 18:51:09 +00:00 |
|
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eb47f8f544
|
dataset_mono: adjust to suit DeepLabV3+ too
|
2022-12-13 18:37:38 +00:00 |
|
|
440e693dfc
|
DeepLabv3+: fix pathing again
|
2022-12-13 18:26:00 +00:00 |
|
|
7e1f271bf4
|
deeplabv3+: fix colourmap
|
2022-12-13 14:02:10 +00:00 |
|
|
4d8ce792c9
|
ddeeplabv3+: fix imports/pathing errors
|
2022-12-13 13:38:27 +00:00 |
|
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fc43f145c2
|
if not
|
2022-12-13 13:28:09 +00:00 |
|
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d907dc48e5
|
DeepLabv3+: add logging
|
2022-12-13 13:20:16 +00:00 |
|
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be4d928319
|
deeplabv3+: chmod +x
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2022-12-13 13:06:42 +00:00 |
|
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91846079b2
|
deeplabv3+ tesst: add shebang
|
2022-12-13 12:56:14 +00:00 |
|
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96e260fe82
|
slurm: add job file for deeplabv3 test
|
2022-12-12 19:31:49 +00:00 |
|
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8866960017
|
TEST SCRIPT: deeplabv3
ref https://keras.io/examples/vision/deeplabv3_plus/
dataset ref https://drive.google.com/uc?id=1B9A9UCJYMwTL4oBEo4RZfbMZMaZhKJaz
(the code is *terrible* spaghetti....!)
|
2022-12-12 19:20:07 +00:00 |
|
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4e4d42a281
|
LossDice: add comment
|
2022-12-12 18:34:20 +00:00 |
|
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449bc425a7
|
LossDice: explicitly cast inputs to float32
|
2022-12-12 17:20:32 +00:00 |
|
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dbf8f5617c
|
drop activation function in last layers
|
2022-12-12 17:20:04 +00:00 |
|
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bcd2f1251e
|
LossDice: Do 1 - thing instead of -thing
|
2022-12-09 19:41:32 +00:00 |
|
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d0dbc50bb7
|
debug
|
2022-12-09 19:33:28 +00:00 |
|
|
2142bb039c
|
again
|
2022-12-09 19:30:01 +00:00 |
|
|
7000b0f193
|
fixup
|
2022-12-09 19:23:35 +00:00 |
|
|
85012d0616
|
fixup
|
2022-12-09 19:18:03 +00:00 |
|
|
719d8e9819
|
strip channels layer at end
|
2022-12-09 19:11:00 +00:00 |
|
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0129c35a35
|
LossDice: remove weird K.* functions
|
2022-12-09 19:06:26 +00:00 |
|
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659fc97fd4
|
fix crash
|
2022-12-09 18:39:27 +00:00 |
|
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e22c0981e6
|
actually use dice loss
|
2022-12-09 18:35:17 +00:00 |
|
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649c262960
|
mono: switch loss from crossentropy to dice
|
2022-12-09 18:13:37 +00:00 |
|
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7fd7c750d6
|
jupyter: identity test
status: FAILED, as usual....!
Don't worry though, 'cause we has a *planses*..... MUHAHAHAHAHAHAHA
* cue evil laugh *
|
2022-12-09 18:07:56 +00:00 |
|
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cf9e8aa237
|
jupyter: convnext-mono identity test
|
2022-12-09 15:50:27 +00:00 |
|
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2a1772a211
|
confvnext_intrevse: add shallow
|
2022-12-08 19:10:12 +00:00 |
|
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c27869630a
|
I hate VSCode's git commit interface
it doesn't let you ammend
|
2022-12-08 18:58:54 +00:00 |
|
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b3345963f3
|
missing arg pass
|
2022-12-08 18:58:32 +00:00 |
|
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3dde9b69da
|
fixup
|
2022-12-08 18:56:32 +00:00 |
|
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6fce39f696
|
WHY?!?!?!
|
2022-12-08 18:55:53 +00:00 |
|
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26766366fc
|
I hate the python code intelligence
it's bad
|
2022-12-08 18:55:15 +00:00 |
|
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ff56f591c7
|
I hate python
|
2022-12-08 18:53:37 +00:00 |
|
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d37e7224f5
|
train-mono: tidy up arg passing
|
2022-12-08 18:47:03 +00:00 |
|
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b53db648bf
|
fixup
|
2022-12-08 18:31:42 +00:00 |
|
|
18c0210704
|
typo
|
2022-12-08 17:00:25 +00:00 |
|
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a3c9416cf0
|
LossCrossentropy: don't sum
|
2022-12-08 16:57:11 +00:00 |
|
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08046340f4
|
dataset_mono: normalise heightmap
|
2022-12-08 16:10:34 +00:00 |
|
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d997157f55
|
dataset_mono: log when using heightmap
|
2022-12-06 19:30:11 +00:00 |
|
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468c150570
|
slurm-train-mono: add HEIGHTMAP
|
2022-12-06 19:28:06 +00:00 |
|
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d0f2e3d730
|
readfile: do transparent gzip by default
....but there's a glad to turn it off if needed
|
2022-12-06 19:27:39 +00:00 |
|
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eac6472c97
|
Implement support for (optionally) taking a heightmap in
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2022-12-06 18:55:58 +00:00 |
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f92b2b3472
|
according to the equation it looks like it's 2
|
2022-12-02 17:22:46 +00:00 |
|
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cad82cd1bc
|
CBAM: unsure if it's 1 ro 3 dense ayers in the shared mlp
|
2022-12-02 17:21:13 +00:00 |
|
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62f6a993bb
|
implement CBAM, but it's UNTESTED
Convolutional Block Attention Module.
|
2022-12-02 17:17:45 +00:00 |
|
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9d666c3b38
|
train mono: type=int → float
|
2022-12-01 15:39:44 +00:00 |
|
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53dfa32685
|
model_mono: log learning rate
|
2022-12-01 15:10:51 +00:00 |
|
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c384d55dff
|
add arg to adjust learning rate
|
2022-11-29 20:55:00 +00:00 |
|
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8e23e9d341
|
model_segmenter: we're no longer using sparse
|
2022-11-29 19:28:27 +00:00 |
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9a2b4c6838
|
dsseg: fix reshape/onehot ordering
|
2022-11-29 19:28:13 +00:00 |
|
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df774146d9
|
dataset_segmenter: reshape, not squeeze
|
2022-11-29 19:24:54 +00:00 |
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77b8a1a8db
|
dataset_segmenter: squeeze
|
2022-11-29 19:16:15 +00:00 |
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2258b5a229
|
slurm-train: reduce RAM required by 10GB
|
2022-11-29 19:15:34 +00:00 |
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01101ad30b
|
losscrossentropy: return the reduced value * facepalm *
|
2022-11-29 19:07:08 +00:00 |
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ff65393e78
|
log file naming update
|
2022-11-29 18:41:14 +00:00 |
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37f196a785
|
LossCrossentropy: add kwargs
|
2022-11-29 15:40:35 +00:00 |
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838ff56a3b
|
mono: fix loading checkpoint
|
2022-11-29 15:25:11 +00:00 |
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dba6cbffcd
|
WHY. * facepalms *
|
2022-11-28 19:33:42 +00:00 |
|
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57b8eb93fb
|
fixup
|
2022-11-28 19:09:35 +00:00 |
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6640a41bb7
|
almost got it....? it's not what I expected....!
|
2022-11-28 19:08:50 +00:00 |
|
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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 |
|
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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 |
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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 |
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675c7a7448
|
fixup
|
2022-11-24 19:03:28 +00:00 |
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afc1cdcf02
|
fixup
|
2022-11-24 19:02:58 +00:00 |
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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 |
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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 |
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3131b4f7b3
|
debug2
|
2022-11-24 18:25:32 +00:00 |
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d55a13f536
|
debug
|
2022-11-24 18:24:03 +00:00 |
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1f60f2a580
|
do_argmax
|
2022-11-24 18:11:03 +00:00 |
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6c09d5254d
|
fixup
|
2022-11-24 17:57:48 +00:00 |
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54a841efe9
|
train_mono_predict: convert to correct format
|
2022-11-24 17:56:07 +00:00 |
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105dc5bc56
|
missing kwargs
|
2022-11-24 17:51:29 +00:00 |
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1e1d6dd273
|
fixup
|
2022-11-24 17:48:19 +00:00 |
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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
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2022-11-22 16:58:46 +00:00 |
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3a0356929c
|
mono: drop the sparse
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2022-11-22 16:20:56 +00:00 |
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7e8f63f8ba
|
fixup
|
2022-11-21 19:38:24 +00:00 |
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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 |
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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 |
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a7a475dcd1
|
debug 2
|
2022-11-11 18:38:07 +00:00 |
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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 |
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69a2d0cf04
|
fixup
|
2022-11-11 18:27:01 +00:00 |
|
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65e801cf28
|
train_mono: fix crash
|
2022-11-11 18:26:25 +00:00 |
|
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8ac5159adc
|
dataset_mono: simplify param passing, onehot+threshold water depth data
|
2022-11-11 18:23:50 +00:00 |
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3a3f7e85da
|
typo
|
2022-11-11 18:03:09 +00:00 |
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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 |
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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 |
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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
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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 |
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daf691bf43
|
typo
|
2022-11-10 19:55:00 +00:00 |
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0aa2ce19f5
|
read_metadata: support file inputs as well as dirs
|
2022-11-10 19:53:30 +00:00 |
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aa7d9b8cf6
|
fixup
|
2022-11-10 19:46:09 +00:00 |
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0894bd09e8
|
train_predict: add error message for parrams.json not found
|
2022-11-10 19:45:41 +00:00 |
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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
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2022-11-03 18:29:00 +00:00 |
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3206d6b7e7
|
slurm: rename segmenter job name
|
2022-11-03 17:12:27 +00:00 |
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f2ae74ce7b
|
how could I be so stupid..... round 2
|
2022-11-02 17:38:26 +00:00 |
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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 |
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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 |
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dfef7db421
|
moar debugging
|
2022-10-31 18:26:34 +00:00 |
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|
172cf9d8ce
|
tweak
|
2022-10-31 18:19:43 +00:00 |
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dbe35ee943
|
loss: comment l2 norm
|
2022-10-31 18:09:03 +00:00 |
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5e60319024
|
fixup
|
2022-10-31 17:56:49 +00:00 |
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|
b986b069e2
|
debug party time
|
2022-10-31 17:50:29 +00:00 |
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458faa96d2
|
loss: fixup
|
2022-10-31 17:18:21 +00:00 |
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55dc05e8ce
|
contrastive: comment weights that aren't needed
|
2022-10-31 16:26:48 +00:00 |
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33391eaf16
|
train_predict/jsonl: don't argmax
I'm interested inthe raw values
|
2022-10-26 17:21:19 +01:00 |
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74f2cdb900
|
train_predict: .list() → .tolist()
|
2022-10-26 17:12:36 +01:00 |
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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 |
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|
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 |
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8195318a42
|
SparseCategoricalAccuracy: losses → metrics
|
2022-10-21 16:51:20 +01:00 |
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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 |
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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 |
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|
c5b1501dba
|
train-predict fixup
|
2022-10-21 15:27:39 +01:00 |
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42aea7a0cc
|
plt.close() fixup
|
2022-10-21 15:23:54 +01:00 |
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12dad3bc87
|
vis/segmentation: fix titles
|
2022-10-21 15:22:35 +01:00 |
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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 |
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3f7db6fa78
|
fix embedding confusion
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2022-10-21 15:15:59 +01:00 |
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847cd97ec4
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fixup
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2022-10-21 14:26:58 +01:00 |
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0e814b7e98
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Contraster → Segmenter
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2022-10-21 14:25:43 +01:00 |
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1b658a1b7c
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train-predict: can't destructure array when iterating generator
....it seems to lead to undefined behaviour or something
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2022-10-20 19:34:04 +01:00 |
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aed2348a95
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train_predict: fixup
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2022-10-20 15:42:33 +01:00 |
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cc6679c609
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batch data; use generator
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2022-10-20 15:22:29 +01:00 |
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d306853c42
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use right daataset
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2022-10-20 15:16:24 +01:00 |
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59cfa4a89a
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basename paths
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2022-10-20 15:11:14 +01:00 |
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4d8ae21a45
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update cli help text
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2022-10-19 17:31:42 +01:00 |
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200076596b
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finish train_predict
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2022-10-19 17:26:40 +01:00 |
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488f78fca5
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pretrain_predict: default to parallel_reads=0
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2022-10-19 16:59:45 +01:00 |
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63e909d9fc
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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....!
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2022-10-19 16:52:07 +01:00 |
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fe43ddfbf9
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start implementing driver for train_predict, but not finished yet
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2022-10-18 19:37:55 +01:00 |
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b3ea189d37
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segmentation: softmax the output
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2022-10-13 21:02:57 +01:00 |
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f121bfb981
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fixup summaryfile
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2022-10-13 17:54:42 +01:00 |
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5c35c0cee4
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model_segmentation: document; remove unused args
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2022-10-13 17:50:16 +01:00 |
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f12e6ab905
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No need for a CLI arg for feature_dim_in - metadata should contain this
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2022-10-13 17:37:16 +01:00 |
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e201372252
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write quick Jupyter notebook to test data
....I'm paranoid
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2022-10-13 17:27:17 +01:00 |
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ae53130e66
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layout
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2022-10-13 14:54:20 +01:00 |
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7933564c66
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typo
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2022-10-12 17:33:54 +01:00 |
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dbe4fb0eab
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train: add slurm job file
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2022-10-12 17:27:10 +01:00 |
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6423bf6702
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LayerConvNeXtGamma: avoid adding an EagerTensor to config
Very weird how this is a problem when it wasn't before..
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2022-10-12 17:12:07 +01:00 |
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32f5200d3b
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pass model_arch properly
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2022-10-12 16:50:06 +01:00 |
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5933fb1061
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fixup
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2022-10-11 19:23:41 +01:00 |
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c45b90764e
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segmentation: adds xxtiny, but unsure if it's small enough
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2022-10-11 19:22:37 +01:00 |
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f4a2c742d9
|
typo
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2022-10-11 19:19:23 +01:00 |
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11f91a7cf4
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train: add --arch; default to convnext_i_xtiny
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2022-10-11 19:18:01 +01:00 |
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5666c5a0d9
|
typo
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2022-10-10 18:12:51 +01:00 |
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131c0a0a5b
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pretrain-predict: create dir if not exists
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2022-10-10 18:00:55 +01:00 |
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deede32241
|
slurm-pretrain: limit memory usage
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2022-10-10 17:45:29 +01:00 |
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13a8f3f511
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pretrain-predict: only queue pretrain-plot if I we output jsonl
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2022-10-10 17:11:10 +01:00 |
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ffcb2e3735
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pretrain-predict: queue for the actual input
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2022-10-10 16:53:28 +01:00 |
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f883986eaa
|
Bugfix: modeset to enable TFRecordWriter instead of bare handle
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2022-10-06 20:07:59 +01:00 |
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e9a8e2eb57
|
fixup
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2022-10-06 19:23:31 +01:00 |
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9f3ae96894
|
finish wiring for --water-size
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2022-10-06 19:21:50 +01:00 |
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5dac70aa08
|
typo
|
2022-10-06 19:17:03 +01:00 |
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2960d3b645
|
exception → warning
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2022-10-06 18:26:40 +01:00 |
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0ee6703c1e
|
Add todo and comment
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2022-10-03 19:06:56 +01:00 |
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2b182214ea
|
typo
|
2022-10-03 17:53:10 +01:00 |
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92c380bff5
|
fiddle with Conv2DTranspose
you need to set the `stride` argument to actually get it to upscale..... :P
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2022-10-03 17:51:41 +01:00 |
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d544553800
|
fixup
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2022-10-03 17:33:06 +01:00 |
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058e3b6248
|
model_segmentation: cast float → int
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2022-10-03 17:31:36 +01:00 |
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04e5ae0c45
|
model_segmentation: redo reshape
much cheese was applied :P
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2022-10-03 17:27:52 +01:00 |
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deffe69202
|
typo
|
2022-10-03 16:59:36 +01:00 |
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fc6d2dabc9
|
Upscale first, THEN convnext...
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2022-10-03 16:38:43 +01:00 |
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6a0790ff50
|
convnext_inverse: add returns; change ordering
|
2022-10-03 16:32:09 +01:00 |
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fe813cb46d
|
slurm predict: fix plotting subcall
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2022-10-03 16:03:26 +01:00 |
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e51087d0a9
|
add reshape layer
|
2022-09-28 18:22:48 +01:00 |
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a336cdee90
|
and continues
|
2022-09-28 18:18:10 +01:00 |
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de47a883d9
|
missing units
|
2022-09-28 18:17:22 +01:00 |
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b5e08f92fe
|
the long night continues
|
2022-09-28 18:14:09 +01:00 |
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dc159ecfdb
|
and again
|
2022-09-28 18:11:46 +01:00 |
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4cf0485e32
|
fixup... again
|
2022-09-28 18:10:11 +01:00 |
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030d8710b6
|
fixup
|
2022-09-28 18:08:31 +01:00 |
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4ee7f2a0d6
|
add water thresholding
|
2022-09-28 18:07:26 +01:00 |
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404dc30f08
|
and again
|
2022-09-28 17:39:09 +01:00 |
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4cd8fc6ded
|
segmentation: param name fix
|
2022-09-28 17:37:42 +01:00 |
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41ba980d69
|
segmentationP implement dataset parser
|
2022-09-28 17:19:21 +01:00 |
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d618e6f8d7
|
pretrain-predict: params.json → metadata.jsonl
|
2022-09-28 16:35:22 +01:00 |
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e9e6139c7a
|
typo
|
2022-09-28 16:28:18 +01:00 |
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|
3dee3d8908
|
update cli help
|
2022-09-28 16:23:47 +01:00 |
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b836f7f70c
|
again
|
2022-09-27 19:06:41 +01:00 |
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52dff130dd
|
slurm pretraian predict: moar logging
|
2022-09-27 19:05:54 +01:00 |
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2d24174e0a
|
slurm pretrain predict: add $OUTPUT
|
2022-09-27 18:58:02 +01:00 |
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7d0e3913ae
|
fix logging
|
2022-09-27 18:51:58 +01:00 |
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d765b3b14e
|
fix crash
|
2022-09-27 18:43:43 +01:00 |
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2cd59a01a5
|
slurm-pretrain-plot: add ARGS
|
2022-09-27 18:41:35 +01:00 |
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f4d1d1d77e
|
just wh
|
2022-09-27 18:25:45 +01:00 |
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4c24d69ae6
|
$d → +d
|
2022-09-27 18:17:07 +01:00 |
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|
cdb19b4d9f
|
fixup
|
2022-09-27 18:13:21 +01:00 |
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|
c4d3c16873
|
add some logging
|
2022-09-27 18:10:58 +01:00 |
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|
3772c3227e
|
fixup
|
2022-09-27 17:57:21 +01:00 |
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|
dbfa45a016
|
write params.json properly
|
2022-09-27 17:49:54 +01:00 |
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a5455dc22a
|
fix import
|
2022-09-27 17:41:24 +01:00 |
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d6ff3fb2ce
|
pretrain_predict fix write mode
|
2022-09-27 17:38:12 +01:00 |
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f95fd8f9e4
|
pretrain-predict: add .tfrecord output function
|
2022-09-27 16:59:31 +01:00 |
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30b8dd063e
|
fixup
|
2022-09-27 15:54:37 +01:00 |
|
|
3cf99587e4
|
Contraster: add gamma layer to load_model
|
2022-09-27 15:53:52 +01:00 |
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9e9852d066
|
UMAP: 100k random
no labels.
|
2022-09-27 15:52:45 +01:00 |
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58c65bdc86
|
slurm: allow predictions on gpu
|
2022-09-23 19:21:57 +01:00 |
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d59de41ebb
|
embeddings: change title rendering; make even moar widererer
We need to see that parallel coordinates plot in detail
|
2022-09-23 18:56:39 +01:00 |
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b4ddb24589
|
slurm plot: compute → highmem
|
2022-09-22 18:27:58 +01:00 |
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|
df12470e78
|
flip conda and time
hopefully we can capture the exit code this way
|
2022-09-21 14:40:28 +01:00 |
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5252a81238
|
vis: don't call add_subplot
|
2022-09-20 19:06:21 +01:00 |
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|
32bb55652b
|
slurm predict: autoqueue UMAP plot
|
2022-09-16 19:36:57 +01:00 |
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|
24c5263bf0
|
slurm predict-plot: fixup
|
2022-09-16 19:27:26 +01:00 |
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7e9c119b04
|
slurm: fix job name
|
2022-09-16 19:20:59 +01:00 |
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1574529704
|
slurm pretrain-predict: move to compute; make exclusive just in case
also shortent o 3 days
|
2022-09-16 19:17:42 +01:00 |
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