Commit graph

102 commits

Author SHA1 Message Date
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
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
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
8195318a42
SparseCategoricalAccuracy: losses → metrics 2022-10-21 16:51:20 +01:00
c98d8d05dd
segmentation: use the right accuracy 2022-10-21 16:17:05 +01:00
3f7db6fa78
fix embedding confusion 2022-10-21 15:15:59 +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
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
c45b90764e
segmentation: adds xxtiny, but unsure if it's small enough 2022-10-11 19:22:37 +01:00
11f91a7cf4
train: add --arch; default to convnext_i_xtiny 2022-10-11 19:18:01 +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
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
030d8710b6
fixup 2022-09-28 18:08:31 +01:00
4ee7f2a0d6
add water thresholding 2022-09-28 18:07:26 +01:00
e9e6139c7a
typo 2022-09-28 16:28:18 +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