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62f6a993bb
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implement CBAM, but it's UNTESTED
Convolutional Block Attention Module.
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2022-12-02 17:17:45 +00:00 |
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53dfa32685
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model_mono: log learning rate
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2022-12-01 15:10:51 +00:00 |
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c384d55dff
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add arg to adjust learning rate
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2022-11-29 20:55:00 +00:00 |
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8e23e9d341
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model_segmenter: we're no longer using sparse
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2022-11-29 19:28:27 +00:00 |
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01101ad30b
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losscrossentropy: return the reduced value * facepalm *
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2022-11-29 19:07:08 +00:00 |
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37f196a785
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LossCrossentropy: add kwargs
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2022-11-29 15:40:35 +00:00 |
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838ff56a3b
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mono: fix loading checkpoint
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2022-11-29 15:25:11 +00:00 |
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dba6cbffcd
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WHY. * facepalms *
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2022-11-28 19:33:42 +00:00 |
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57b8eb93fb
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fixup
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2022-11-28 19:09:35 +00:00 |
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6640a41bb7
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almost got it....? it's not what I expected....!
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2022-11-28 19:08:50 +00:00 |
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f48473b703
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fixup
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2022-11-28 19:00:11 +00:00 |
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f6feb125e3
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this iss ome serious debugging.
This commit will produce an extremely large volume of output.
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2022-11-28 18:57:41 +00:00 |
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09f81b0746
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train_mono: debug
this commit will generate a large amount of debug output.
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2022-11-28 16:46:17 +00:00 |
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f39e4ade70
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LayerConvNextGamma: fix config serialisation bug
.....this is unlikely to be the problem as this bug is in an unused code path.
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2022-11-25 21:16:31 +00:00 |
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3a0356929c
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mono: drop the sparse
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2022-11-22 16:20:56 +00:00 |
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527b34942d
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convnext_inverse: kernel_size 4→2
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2022-11-11 19:29:37 +00:00 |
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0662d0854b
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model_mono: fix bottleneck
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2022-11-11 19:11:40 +00:00 |
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73acda6d9a
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fix debug logging
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2022-11-11 19:08:38 +00:00 |
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9da059d738
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model shape logging
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2022-11-11 19:03:37 +00:00 |
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54ae88b1b4
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in this entire blasted project I have yet to get the rotation of anything correct....!
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2022-11-11 18:58:45 +00:00 |
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a7a475dcd1
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debug 2
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2022-11-11 18:38:07 +00:00 |
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bf2f6e9b64
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debug logging
it begins again
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2022-11-11 18:31:40 +00:00 |
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9035450213
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mono: instantiate right model
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2022-11-11 18:28:29 +00:00 |
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3313f77c88
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Add (untested) mono rainfall → water depth model
* sighs *
Unfortunately I can't seem to get contrastive learning to work.....
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2022-11-10 22:36:11 +00:00 |
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9384b89165
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model_segmentation: spare → normal crossentropy, activation functions at end
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2022-11-10 20:53:37 +00:00 |
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b6676e7361
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switch from sparse to normal crossentropy
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2022-11-10 20:50:56 +00:00 |
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44ad51f483
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CallbackNBatchCsv: bugfix .sort() → sorted()
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2022-11-04 16:40:21 +00:00 |
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1375201c5f
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CallbackNBatchCsv: open_handle mode
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2022-11-03 18:29:00 +00:00 |
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f2ae74ce7b
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how could I be so stupid..... round 2
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2022-11-02 17:38:26 +00:00 |
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5f8d6dc6ea
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Add metrics every 64 batches
this is important, because with large batches it can be difficult to tell what's happening inside each epoch.
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2022-10-31 19:26:10 +00:00 |
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cf872ef739
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how could I be so *stupid*......
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2022-10-31 18:40:58 +00:00 |
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da32d75778
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make_callbacks: display steps, not samples
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2022-10-31 18:36:28 +00:00 |
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172cf9d8ce
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tweak
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2022-10-31 18:19:43 +00:00 |
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dbe35ee943
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loss: comment l2 norm
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2022-10-31 18:09:03 +00:00 |
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5e60319024
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fixup
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2022-10-31 17:56:49 +00:00 |
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b986b069e2
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debug party time
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2022-10-31 17:50:29 +00:00 |
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458faa96d2
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loss: fixup
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2022-10-31 17:18:21 +00:00 |
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55dc05e8ce
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contrastive: comment weights that aren't needed
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2022-10-31 16:26:48 +00:00 |
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1b489518d0
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segmenter: add LayerStack2Image to custom_objects
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2022-10-26 17:05:50 +01:00 |
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48ae8a5c20
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LossContrastive: normalise features as per the paper
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2022-10-26 16:52:56 +01:00 |
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843cc8dc7b
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contrastive: rewrite the loss function.
The CLIP paper *does* kinda make sense I think
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2022-10-26 16:45:45 +01:00 |
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fad1399c2d
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convnext: whitespace
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2022-10-26 16:45:20 +01:00 |
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1d872cb962
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contrastive: fix initial temperature value
It should be 1/0.07, but we had it set to 0.07......
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2022-10-26 16:45:01 +01:00 |
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f994d449f1
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Layer2Image: fix
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2022-10-25 21:32:17 +01:00 |
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6a29105f56
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model_segmentation: stack not reshape
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2022-10-25 21:25:15 +01:00 |
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98417a3e06
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prepare for NCE loss
.....but Tensorflow's implementation looks to be for supervised models :-(
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2022-10-25 21:15:05 +01:00 |
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bb0679a509
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model_segmentation: don't softmax twice
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2022-10-25 21:11:48 +01:00 |
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f2e2ca1484
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model_contrastive: make water encoder significantly shallower
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2022-10-24 20:52:31 +01:00 |
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8195318a42
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SparseCategoricalAccuracy: losses → metrics
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2022-10-21 16:51:20 +01:00 |
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c98d8d05dd
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segmentation: use the right accuracy
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2022-10-21 16:17:05 +01:00 |
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