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Time series Timeseries Deep Learning Machine Learning Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

0.2.24

2 years ago

Release notes

0.2.24

Breaking Changes

  • removed InceptionTSiT, InceptionTSiTPlus, ConvTSiT & ConvTSiTPlus (#276)

New Features

  • add stateful custom sklearn API type tfms: TSShrinkDataFrame, TSOneHotEncoder, TSCategoricalEncoder (#313)

  • Pytorch 1.10 compatibility (#311)

  • ability to pad at the start/ end of sequences and filter results in SlidingWindow (#307)

  • added bias_init to TSiT (#288)

  • plot permutation feature importance after a model's been trained (#286)

  • added separable as an option to MultiConv1d (#285)

  • Modified TSiTPlus to accept a feature extractor and/or categorical variables (#278)

Bugs Squashed

  • learn modules takes too long to load (#312)

  • error in roll2d and roll3d when passing index 2 (#304)

  • TypeError: unhashable type: 'numpy.ndarray' (#302)

  • ValueError: only one element tensors can be converted to Python scalars (#300)

  • unhashable type: 'numpy.ndarray' when using multiclass multistep labels (#298)

  • incorrect data types in NumpyDatasets subset (#297)

  • create_future_mask creates a mask in the past (#293)

  • NameError: name 'X' is not defined in learner.feature_importance (#291)

  • TSiT test fails on cuda (#287)

  • MultiConv1d breaks when ni == nf (#284)

  • WeightedPerSampleLoss reported an error when used with LDS_weights (#281)

  • pos_encoding transfer weight in TSiT fails (#280)

  • MultiEmbedding cat_pos and cont_pos are not in state_dict() (#277)

  • fixed issue with MixedDataLoader (#229), thanks to @Wabinab

0.2.23

2 years ago

Release notes

0.2.23

Breaking Changes

  • removed torch-optimizer dependency (#228)

New Features

  • added option to train MVP on random sequence lengths (#252)

  • added ability to pass an arch name (str) to learner instead of class (#217)

  • created convenience fns create_directory and delete_directory in utils (#213)

  • added option to create random array of given shapes and dtypes (#212)

  • my_setup() print your main system and package versions (#202)

  • added a new tutorial on how to train large datasets using tsai (#199)

  • added a new function to load any file as a module (#196)

  • Created CODE_OF_CONDUCT.md in https://github.com/timeseriesAI/tsai/pull/210

  • Add Optuna tutorial notebook by @dnth in https://github.com/timeseriesAI/tsai/pull/275

Bugs Squashed

  • Loading code just for inference takes too long (#273)

  • Fixed out-of-memory issue with large datasets on disk (#126)

  • AttributeError: module 'torch' has no attribute 'nan_to_num' (#262)

  • Fixed TypeError: unhashable type: 'numpy.ndarray' (#250)

  • Wrong link in paper references (#249)

  • remove default PATH which overwrites custom PATH (#238)

  • Predictions where not properly decoded when using with_decoded. (#237)

  • SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame (#221)

  • InceptionTimePlus wasn't imported by TSLearners (#218)

  • get_subset_dl fn is not properly creating a subset dataloader (#211)

  • Bug in WeightedPersSampleLoss (#203)

  • Bump nokogiri from 1.11.4 to 1.12.5 in /docs by @dependabot in https://github.com/timeseriesAI/tsai/pull/222

New Contributors

Full Changelog: https://github.com/timeseriesAI/tsai/compare/0.2.20...0.2.23

0.2.20

2 years ago

0.2.19

2 years ago