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62 Commits

Author SHA1 Message Date
Jensun Ravichandran
5ffbd43a7c Refactor into shared_step 2021-05-19 16:57:51 +02:00
Jensun Ravichandran
fdf9443a2c Add validation and test logic 2021-05-19 16:30:19 +02:00
Jensun Ravichandran
eefec19c9b Custom non-gradient training 2021-05-18 19:49:16 +02:00
Jensun Ravichandran
4957e821f6 Close matplotlib figure on train end 2021-05-18 10:13:22 +02:00
Jensun Ravichandran
81346785bd Cleanup models 
Siamese architectures no longer accept a `backbone_module`. They have to be
initialized with an pre-initialized backbone object instead. This is so that the
visualization callbacks could use the very same object for visualization
purposes. Also, there's no longer a dependent copy of the backbone. It is
managed simply with `requires_grad` instead.
 2021-05-17 17:00:23 +02:00
Jensun Ravichandran
7a87636ad7 Update KNN 2021-05-17 16:59:35 +02:00
Jensun Ravichandran
77b7b59bad Clean visualization callbacks 2021-05-17 16:59:22 +02:00
Jensun Ravichandran
6e7d80be88 [BUGFIX] Fix siamese visualization callback 2021-05-15 12:52:44 +02:00
Jensun Ravichandran
b7684ae512 predict_latent no longer returns numpy 2021-05-15 12:52:16 +02:00
Alexander Engelsberger
0eac2ce326 Examples use GPUs if available. 2021-05-13 15:22:01 +02:00
Jensun Ravichandran
8f9c29bd2b [BUGFIX] Remove incorrect import statement 2021-05-12 16:45:01 +02:00
Jensun Ravichandran
ca39aa00d5 Stop passing component initializers as hparams 
Pass the component initializer as an hparam slows down the script very much. The
API has now been changed to pass it as a kwarg to the models instead.

The example scripts have also been updated to reflect the new changes.

Also, ImageGMLVQ and an example script `gmlvq_mnist.py` that uses it have also
been added.
 2021-05-12 16:36:22 +02:00
Alexander Engelsberger
1498c4bde5 Bump version: 0.1.6 → 0.1.7 2021-05-11 17:18:29 +02:00
Jensun Ravichandran
59b8ab6643 Add knn 2021-05-11 17:22:02 +02:00
Jensun Ravichandran
eab1ec72c2 Change optimizer using kwargs 2021-05-11 16:13:00 +02:00
Jensun Ravichandran
b38acd58a8 [BUGFIX] Fix visualization callbacks bug 2021-05-11 16:09:27 +02:00
Alexander Engelsberger
e87563e10d Bump version: 0.1.5 → 0.1.6 2021-05-11 13:41:26 +02:00
Alexander Engelsberger
3fa6378c4d Add LVQ1 and LVQ2.1 Models. 2021-05-11 13:26:13 +02:00
Alexander Engelsberger
30ee287ecc Bump version: 0.1.4 → 0.1.5 2021-05-10 17:13:00 +02:00
Alexander Engelsberger
f49db0bf2c Bump version: 0.1.3 → 0.1.4 2021-05-10 17:06:28 +02:00
Alexander Engelsberger
54a8494d86 Bump version: 0.1.2 → 0.1.3 2021-05-10 17:04:20 +02:00
Alexander Engelsberger
bf310be97c Bump version: 0.1.1 → 0.1.2 2021-05-10 16:47:33 +02:00
Alexander Engelsberger
1ae2b41edd Bump version: 0.1.0 → 0.1.1 2021-05-10 16:26:21 +02:00
Alexander Engelsberger
f6e3a37e2b Bump version: 0.0.0 → 0.1.0 2021-05-10 16:01:46 +02:00
Alexander Engelsberger
6873927349 Setup bumpversion 2021-05-10 15:34:43 +02:00
Jensun Ravichandran
49100f43f5 Example to save and reload a model 2021-05-10 14:30:02 +02:00
Jensun Ravichandran
ed03ab168e [BUGFIX] Fix lambda_matrix property in GMLVQ 2021-05-10 14:09:25 +02:00
Jensun Ravichandran
c6e06ceaa4 Properly initialize prototypes in LVQMLN 2021-05-09 20:55:28 +02:00
Jensun Ravichandran
ca4c9da10a Add the namespace hook for GMLVQ in the model class 2021-05-09 20:53:31 +02:00
Jensun Ravichandran
ff7a1e93d2 Refactor visualization callbacks 2021-05-09 20:53:03 +02:00
Jensun Ravichandran
11b3e53ecb Return prototypes as torch tensor 2021-05-07 15:45:37 +02:00
Jensun Ravichandran
d7972a69e8 Update GMLVQ model 2021-05-07 15:24:47 +02:00
Jensun Ravichandran
17315ff242 Add models to the prototorch.models namespace 2021-05-07 15:23:52 +02:00
Jensun Ravichandran
5f937066bf Move and improve visualization callbacks 2021-05-07 15:22:54 +02:00
Alexander Engelsberger
4bbe73e3a9 Add GRLVQ with examples. 2021-05-06 18:42:06 +02:00
Alexander Engelsberger
3df282a0af Increase visualization pause. 2021-05-06 18:41:33 +02:00
Alexander Engelsberger
5a2f4f6170 Revert deletion of training accuracy. 2021-05-06 18:02:01 +02:00
Alexander Engelsberger
1c3613019b Update Examples to new initializer architecture. 
Visualization still borken for some examples.
 2021-05-06 14:10:09 +02:00
Jensun Ravichandran
d644114090 Add loss transfer function to glvq 2021-05-04 20:56:16 +02:00
Jensun Ravichandran
f402eea884 Add GMLVQ examples 2021-05-04 15:11:16 +02:00
Jensun Ravichandran
a1ac5a70c7 Use squared euclidean distance in GMLVQ 2021-05-04 14:34:00 +02:00
Jensun Ravichandran
d8e017ae74 Update SiameseGLVQ 2021-05-03 16:09:22 +02:00
Jensun Ravichandran
96aeaa3448 Add support for multiple optimizers 2021-05-03 13:20:49 +02:00
Jensun Ravichandran
042b3fcaa2 Add tensorboard argument to visualization callbacks 2021-05-03 13:19:23 +02:00
Jensun Ravichandran
6dd9b1492c Add more models 2021-04-29 23:37:22 +02:00
Jensun Ravichandran
db7bb7619f Add border argument in visualization callback 2021-04-29 22:36:10 +02:00
Jensun Ravichandran
ccaa52c408 Add missing abstract.py file 2021-04-29 19:14:33 +02:00
Jensun Ravichandran
fef73e2fbf [BUG] NaN when training with selection initializer 
How to reproduce:
Run the `glvq_spiral.py` file under `examples/`.

The error seems to occur when using a lot of prototypes in combination with the
`StratifiedSelectionInitializer`. Using only a prototype per class, or using
another initializer like the `StratifiedMeanInitializer` seems to make the
problem go away.
 2021-04-29 19:09:10 +02:00
Jensun Ravichandran
a16bebd0c4 Use Components instead of Prototypes and refactor old examples 2021-04-29 17:05:41 +02:00
Alexander Engelsberger
eeb684b3b6 GLVQ with configurable distance. 2021-04-27 15:41:44 +02:00