Version 0.1.5

[0.1.5] - 2018-07-30

Added

• Added a on_validation_criterion callback hook
• Added a DatasetValidationSplitter which can be used to create a validation split if required for datasets like Cifar10 or MNIST
• Added simple timer callback

Changed

Deprecated

Removed

Fixed

• Fixed a bug where checkpointers would not save the model in some cases
• Fixed a bug with the ROC metric causing it to not work

Version 0.1.4

[0.1.4] - 2018-07-23

Added

• Added a decorator API for metrics which allows decorators to be used for metric construction
• Added a default_for_key decorator which can be used to associate a string with a given metric in metric lists
• Added a decorator API for callbacks which allows decorators to be used for simple callback construction
• Added a add_to_loss callback decorator which allows quicker constructions of callbacks that add values to the loss

Changed

• Changed the API for running metrics and aggregators to no longer wrap a metric but instead receive input

Deprecated

Removed

Fixed

Version 0.1.3

[0.1.3] - 2018-07-17

Added

• Added a flag (step_on_batch) to the LR Scheduler callbacks which allows for step() to be called on each iteration instead of each epoch
• Added on_sample_validation and on_forward_validation calls for validation callbacks
• Added GradientClipping callback which simply clips the absolute gradient of the model parameters

Changed

• Changed the order of the arguments to the lambda function in the EpochLambda metric for consistency with pytorch and other metrics
• Checkpointers now create directory to savepath if it doesn't exist
• Changed the 'on_forward_criterion' callback method to 'on_criterion'
• Changed epoch number in printer callbacks to be consistent with the rest of torchbearer

Deprecated

Removed

Fixed

• Fixed tests which were failing as of version 0.1.2
• Fixed validation_steps not being added to state
• Fixed checkpointer bug when path contained only filename and no directory path
• Fixed console printer bug not printing validation statistics
• Fixed console printer bug calling final_metrics before they existed in state

Version 0.1.2

[0.1.2] - 2018-06-08

Added

• Added support for tuple outputs from generators, bink expects output to be length 2. Specifically, x, y = next() is possible, where x and y can be tuples of arbitrary size or depth
• Added support for torch dtypes in bink Model.to(...)
• Added pickle_module and pickle_protocol to checkpointers for consistency with torch.save

Changed

• Changed the learning rate scheduler callbacks to no longer require an optimizer and to have the proper arguments

Deprecated

Removed

Fixed

• Fixed an issue in GradientNormClipping which raised a warning in PyTorch >= 0.4

Version 0.1.1

• Add support for tuples in data loader

Version 0.1.0

v0.1.0

Add setup.py (#125)