Releases: pytorchbearer/torchbearer
Releases · pytorchbearer/torchbearer
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)