CHANGES
=======

0.5.2
-----

* Update version to 0.5.2
* Add regression test and reasonable default for stop\_factor
* Close yaml files when done reading them
* bugfix: give monitor\_data to rate\_controllers

0.5.1
-----

* Update version to 0.5.1
* Add test of multilayer perceptron and batch\_multiplier
* Make confusion matrix calculation robust to poor classifiers
* Inline \_do\_training\_step and incorporate test steps
* Fix bug with calculating num\_steps with batch\_multiplier
* Update version to 0.5.0
* Add ability to specify a 'batch\_multiplier' when training
* Clarifying comment
* Monitor api 'step' to 'write' and steps start at 1 now
* Add multilayer perceptron and factor out layers
* pytorch can now be installed via pypi
* Remove setting manual seeds

0.4.0
-----

* Update version to 0.4.0
* Bump up max-complexity a little bit
* Make DataframeMonitor plot prettier and more flexible
* Add triangle and step rate controllers

0.3.2
-----

* Update version to 0.3.2
* Pass kwargs to plot instead of figure
* Basic Classifier test changed, update README too

0.3.1
-----

* Update version to 0.3.1
* Clean up BasicClassifier
* flake 8 fix
* Add losswise monitor

0.3.0
-----

* Update version to 0.3.0
* Add plot\_confusion\_matrix method to ClassifierTrainer
* Fix default download folder name for pytorch datasets
* Fix logic for cycle\_length in multi\_train
* Add gridlines to default dataframe plot

0.2.0
-----

* Update version to 0.2.0
* Added script to release to pypi
* Add \_\_version\_\_ to sconce package
* Remove MNISTTest base test class
* DataGenerator classmethod to load pytorch datasets
* Rewording
* Add author and author\_email (pypi requires it)
* Add 'installation' and 'getting started' sections to README

0.1.0
-----

* bump version
* RingbufferMonitor has 'movement\_index' property
* Add constant rate controller with patience
* Remove torch and torchvision from requirments.txt
* Add 'calculate\_metrics' support
* Allow setting of test\_to\_train\_ratio per training session
* Display training loss during learning rate survey
* Make ExponentialRateController able to stop early
* Make it so that rate\_controllers can end training
* Journals and StatusMonitors are now just Monitors
* Fix wrong dataset class used in tests
* Make autoencoder and classifier trainers into mixins
* Set env variable to choose matplotlib backend in tests
* Add a server setup guide
* dummy commit
* Be more careful about checking for cuda in tests
* Add ClassifierTrainer and test model
* Make autoencoder test run much faster
* Move flake8 to be before tests so we can fail faster
* Add Trainer and basic model to test with
* Better default blacklist for DataframeJournal
* Model.calculate\_loss returns 'loss' not 'total\_loss'
* DataGenerators now generate Variables
* Allow MNISTTests to use subset of MNIST data for speedup
* Add DataframeJournal
* Added RateControllers
* Pull in Progbar from keras
* Extract reset method
* Add vim swap files to gitignore
* Add Project files and DataGenerator
* Initial commit
