v0.2.25

0.2.25

Breaking Changes

• updated forward_gaps removing nan_to_num (#331)

• TSRobustScaler only applied by_var (#329)

• remove add_na arg from TSCategorize (#327)

New Features

• added IntraClassCutMix1d (#384)

• added learn.calibrate_model method (#379)

• added analyze_array function (#378)

• Added TSAddNan transform (#376)

• added dummify function to create dummy data from original data (#366)

• added Locality Self Attention to TSiT (#363)

• added sel_vars argument to MVP callback (#349)

• added sel_vars argument to TSNan2Value (#348)

• added multiclass, weighted FocalLoss (#346)

• added TSRollingMean batch transform (#343)

• added recall_at_specificity metric (#342)

• added train_metrics argument to ts_learner (#341)

• added hist to PredictionDynamics for binary classification (#339)

• add padding_idxs to MultiEmbedding (#330)

Bugs Squashed

• sort_by data may be duplicated in SlidingWindowPanel (#389)

• create_script splits the nb name if multiple underscores are used (#385)

• added torch functional dependency to plot_calibration_curve (#383)

• issue when setting horizon to 0 in SlidingWindow (#382)

• replace learn by self in calibrate_model patch (#381)

• Argument d_head is not used in TSiTPlus (#380)

  • https://github.com/timeseriesAI/tsai/blob/6baf0ba2455895b57b54bf06744633b81cdcb2b3/tsai/models/TSiTPlus.py#L63

• replace default relu activation by gelu in TSiT (#361)

• sel_vars and sel_steps in TSDatasets and TSDalaloaders don't work when used simultaneously (#347)

• ShowGraph fails when recoder.train_metrics=True (#340)

• fixed 'se' always equal to 16 in MLSTM_FCN (#337)

• ShowGraph doesn't work well when train_metrics=True (#336)

• TSPositionGaps doesn't work on cuda (#333)

• XResNet object has no attribute 'backbone' (#332)

• import InceptionTimePlus in tsai.learner (#328)

• df2Xy: Format correctly without the need to specify sort_by (#324)

• bug in MVP code learn.model --> self.learn.model (#323)

• Colab install issues: importing the lib takes forever (#315)

• Calling learner.feature_importance on larger than memory dataset causes OOM (#310)

v0.2.24

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

v0.2.23

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 #210

• Add Optuna tutorial notebook by @dnth in #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 #222

New Contributors

• @geoHeil made their first contribution in #207
• @dnth made their first contribution in #275

Full Changelog: 0.2.20...0.2.23

v0.2.20

conda release

v0.2.19

conda folder