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0353072d15
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allow pretrain to run on gpu
we've slashed the size of the 2nd encoder, so ti should fit naow?
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2022-11-04 17:02:07 +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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4dddcfcb42
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pretrain_predict: missing \n
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2022-11-04 16:01:28 +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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3206d6b7e7
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slurm: rename segmenter job name
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2022-11-03 17:12:27 +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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441ad92b12
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slurm: fixup
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2022-11-01 19:57:15 +00:00 |
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bc0e5f05a8
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slurm: fixup
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2022-11-01 19:55:04 +00:00 |
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784b8ed35c
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recordify: catch NaN --count-file
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2022-11-01 19:53:21 +00:00 |
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c17a4ca05a
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slurm: fix sanity logic
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2022-11-01 19:38:04 +00:00 |
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79b231198f
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slurm-process: check input files are readable
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2022-11-01 19:03:37 +00:00 |
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a69fa9f0f3
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slurm: rename
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2022-11-01 18:59:55 +00:00 |
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f8341e7d89
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slurm: add .log
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2022-11-01 18:59:15 +00:00 |
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fecc63b6a2
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wrangler: write high-level job file
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2022-11-01 18:56:27 +00:00 |
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91152ebb1c
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wrangler:recordify update cli help
we only output .jsonl.gz to a DIRECTORY, so update cli help to reflect this
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2022-11-01 18:29:47 +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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dfef7db421
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moar debugging
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2022-10-31 18:26:34 +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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33391eaf16
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train_predict/jsonl: don't argmax
I'm interested inthe raw values
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2022-10-26 17:21:19 +01:00 |
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74f2cdb900
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train_predict: .list() → .tolist()
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2022-10-26 17:12:36 +01:00 |
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4f9d543695
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train_predict: don't pass model_code
it's redundant
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2022-10-26 17:11:36 +01:00 |
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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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a6b07a49cb
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count water/nowater pixels in Jupyter Notebook
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2022-10-24 18:05:34 +01:00 |
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a8b101bdae
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dataset_predict: add shape_water_desired
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2022-10-24 18:05:13 +01:00 |
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587c1dfafa
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train_predict: revamp jsonl handling
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2022-10-21 16:53:08 +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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612735aaae
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rename shuffle arg
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2022-10-21 16:35:45 +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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bb0258f5cd
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flip squeeze operator ordering
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2022-10-21 15:38:57 +01:00 |
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af26964c6a
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batched_iterator: reset i_item after every time
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2022-10-21 15:35:43 +01:00 |
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c5b1501dba
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train-predict fixup
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2022-10-21 15:27:39 +01:00 |
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42aea7a0cc
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plt.close() fixup
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2022-10-21 15:23:54 +01:00 |
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12dad3bc87
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vis/segmentation: fix titles
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2022-10-21 15:22:35 +01:00 |
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0cb2de5d06
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train-preedict: close matplotlib after we've finished
they act like file handles
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2022-10-21 15:19:31 +01:00 |
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