v2.5.3

New Features

• add at_end feature to SaveModelCallback (#3296), thanks to @tmabraham

Bugs Squashed

• fix fp16 test (#3284), thanks to @tmabraham

v2.5.1

• Import download_url from fastdownload

v2.5.0

Breaking changes

• config.yml has been renamed to config.ini, and is now in ConfigParser format instead of YAML
• THe _path suffixes in config.ini have been removed

Bugs Squashed

• Training with learn.to_fp16() fails with PyTorch 1.9 / Cuda 11.4 (#3438)
• pandas 1.3.0 breaks add_elapsed_times (#3431)

v2.4.1

New Features

• add DiceLoss (#3386), thanks to @tcapelle
• TabularPandas data transform reproducibility (#2826)

Bugs Squashed

• Latest Pillow v8.3.0 breaks conversion Image to Tensor (#3416)

v2.4

Breaking changes

• QRNN module removed, due to incompatibility with PyTorch 1.9, and lack of utilization of QRNN in the deep learning community. QRNN was our only module that wasn't pure Python, so with this change fastai is now a pure Python package.

New Features

• Support for PyTorch 1.9
• Improved LR Suggestions (#3377), thanks to @muellerzr
• SaveModelCallback every nth epoch (#3375), thanks to @KeremTurgutlu
• Send self.loss_func to device if it is an instance of nn.Module (#3395), thanks to @arampacha
• Batch support for more than one image (#3339)
• Changable tfmdlists for TransformBlock, Datasets, DataBlock (#3327)

Bugs Squashed

• convert TensorBBox to TensorBase during compare (#3388), thanks to @kevinbird15
• Check if normalize exists on _add_norm (#3371), thanks to @renato145

v2.3.2

New Features

• send self.loss_func to device if it is an instance of nn.Module (#3395), thanks to @arampacha
• Improved LR Suggestions (#3377), thanks to @muellerzr
• SaveModelCallback every nth epoch (#3375), thanks to @KeremTurgutlu
• Batch support for more than one image (#3339)
• Changable tfmdlists for TransformBlock, Datasets, DataBlock (#3327)

Bugs Squashed

• convert TensorBBox to TensorBase during compare (#3388), thanks to @kevinbird15
• Check if normalize exists on _add_norm (#3371), thanks to @renato145

v2.3.1

New Features

• Add support for pytorch 1.8 (#3349)
• Add support for spacy3 (#3348)
• Add support for Windows. Big thanks to Microsoft for many contributions to get this working
• Timedistributed layer and Image Sequence Tutorial (#3124), thanks to @tcapelle
• Add interactive run logging to AzureMLCallback (#3341), thanks to @yijinlee
• Batch support for more than one image (#3339)
• Have interp use ds_idx, add tests (#3332), thanks to @muellerzr
• Automatically have fastai determine the right device, even with torch DataLoaders (#3330), thanks to @muellerzr
• Add at_end feature to SaveModelCallback (#3296), thanks to @tmabraham
• Improve inplace params in Tabular's new and allow for new and test_dl to be in place (#3292), thanks to @muellerzr
• Update VSCode & Codespaces dev container (#3280), thanks to @bamurtaugh
• Add max_scale param to RandomResizedCrop(GPU) (#3252), thanks to @kai-tub
• Increase testing granularity for speedup (#3242), thanks to @ddobrinskiy

Bugs Squashed

• Make TTA turn shuffle and drop_last off when using ds_idx (#3347), thanks to @muellerzr
• Add order to TrackerCallback derived classes (#3346), thanks to @muellerzr
• Prevent schedule from crashing close to the end of training (#3335), thanks to @Lewington-pitsos
• Fix ability to use raw pytorch DataLoaders (#3328), thanks to @hamelsmu
• Fix PixelShuffle_icnr weight (#3322), thanks to @pratX
• Creation of new DataLoader in Learner.get_preds has wrong keyword (#3316), thanks to @tcapelle
• Correct layers order in tabular learner (#3314), thanks to @gradientsky
• Fix vmin parameter default (#3305), thanks to @tcapelle
• Ensure call to one_batch places data on the right device (#3298), thanks to @tcapelle
• Fix Cutmix Augmentation (#3259), thanks to @MrRobot2211
• Fix custom tokenizers for DataLoaders (#3256), thanks to @iskode
• fix error setting 'tok_tfm' parameter in TextDataloaders.from_folder
• Fix lighting augmentation (#3255), thanks to @kai-tub
• Fix CUDA variable serialization (#3253), thanks to @mszhanyi
• change batch tfms to have the correct dimensionality (#3251), thanks to @trdvangraft
• Ensure add_datepart adds elapsed as numeric column (#3230), thanks to @aberres

v2.3.0

Breaking Changes

• fix optimwrapper to work with param_groups (#3241), thanks to @tmabraham
  • OptimWrapper now has a different constructor signature, which makes it easier to wrap PyTorch optimizers

New Features

• Support discriminative learning with OptimWrapper (#2829)

Bugs Squashed

• Updated to support adding transforms to multiple dataloaders (#3268), thanks to @marii-moe
  • This fixes an issue in 2.2.7 which resulted in incorrect validation metrics when using Normalization

v2.2.7

Bugs Squashed

• Regression fix: Ensure add_datepart adds elapsed as numeric column (#3230), thanks to @aberres

v2.2.6

Bugs Squashed

• 2.2.5 was not released correctly - it was actually 2.2.3