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train_evaluate_cv fails due to out_of_memory #14

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jakubczakon opened this issue Jul 29, 2018 · 0 comments
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train_evaluate_cv fails due to out_of_memory #14

jakubczakon opened this issue Jul 29, 2018 · 0 comments
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@jakubczakon jakubczakon added the bug Something isn't working label Jul 29, 2018
@jakubczakon jakubczakon moved this from misc to done in kaggle-competition Aug 29, 2018
jakubczakon added a commit that referenced this issue Oct 13, 2018
* Hypercolumn (#16)

* fixed lovash loss, added helpers for loss weighing (#14)

* updated results exploration, added unet with hypercolumn

* updated with lighter hypercolumn setup

* Model average (#17)

* added prediction average notebook

* added simple average notebook

* added replication pad instead of zero pad (#18)

* changed to heng-like arch, added channel and spatial squeeze and excite, extended hypercolumn (#19)

* Update unet_models.py

typo in resnet unet fixed

* added resnet 18 an50 pretrained options, unified hyper and vanilla in one class (#20)

* Update models.py

Changed old class import and namings

* Loss design (#21)

* local

* initial

* formated results

* added focal, added border weighing, added size weighing added focus, added loss desing notebook

* fixed wrong focal definition, updated loss api

* exp with dropped borders

* set best params, not using weighing for now

* Dev depth experiments (#23)

* add depth layer in input

* reduce lr on plateau scheduler

* depth channels transformer

* fix reduce lr

* bugfix

* change default config

* added adaptive threshold in callbacks (#24)

* added adaptive threshold in callbacks

* fix

* added initial lr selector (#25)

* Initial lb selector (#26)

* added initial lr selector

* small refactor

* Auxiliary data small masks (#27)

* exping

* auxiliary data for border masks generated
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