Time series Timeseries Deep Learning Machine Learning Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
added functionality to support inputs with static/ observed (time-dependent) features
added functionality to support inputs with categorical/ continuous features
added functionality to apply patches to time series models
Added MultiRocket/ MultiRocketPlus architectures
added TSSelfDropout (#790)
added get_feat_idxs to calculate multimodal indices (#789)
remaining features assigned to o_cont_idxs by default (#788)
added patch encoder to MultiInputWrapper (#787)
added TSTargetEncoder transform (#769)
added TSRobustScaler to tfm pipelines (#763)
added new tfms - TSDropIfTrueCols and ApplyFunc (#760)
tensor slices in different devices when using TensorSplitter (#799)
mixed augmentations (MixUp1d, CutMix1d,..) are not updating labels (#791)
get_UCR_data function fails due to changed download link (#785)
error when using TSSelectColumns due to pandas df slicing (#762)
short arrays create issues when running get_usable_idxs (#761)
get_X_pred creates different probablities when using numpy array or torch tensor (#754)
partial_n is applied to all datasets by default (#748)
get_best_dls_params function still prints output when the verbose parameter is set to false (#737)
using xresnet for vision classification raises an error (#728)
added optional activation to get_X_preds (#715)
added external vocab option to dls (#705)
allow classification outputs with n dimensions (#704)
added get_sweep_config to wandb module (#687)
added functionality to run pipeline sweeps (#686)
added seed to learners to make training reproducible (#685)
added functionality to filter df for required forecasting dates (#679)
added option to train model on train only (#671)
access all available dataloaders in dls (#724)
make all models ending in Plus work with ndim classification targets (#719)
make all models ending in Plus work with ndim work with ndim regression/ forecasting targets (#718)
added MiniRocket to get_arch (#717)
fixed issue with get_arch missing new models (#709)
valid_metrics causes an error when using TSLearners (#708)
valid_metrics are not shown when an array is passed within splits (#707)
TSDatasets w/o tfms and inplace=False creates new X (#695)
Prediction and True Values Swapped in plot_forecast (utils.py) (#690)
MiniRocket incompatible with latest scikit-learn version (#677)
Df2xy causing incorrect splits (#666)
Feature Importance & Step Importance Not working (#647)
multi-horizon forecasting (#591)
Issues saving models with TSMetaDataset Dataloader (#317)
add option to pass an instantiated model to TSLearners (#650)
Added PatchTST model to tsai (#638)
Added new long-term time series forecasting tutorial notebook
Undefined variable (#662)
Multivariate Regression and Forecasting basic tutorials throw an error (#629)
TypeError: init() got an unexpected keyword argument 'custom_head' (#597)
Issues with TSMultiLabelClassification (#533)
Incompatible errors or missing functions in 'tutorial_nbs' notebooks, please fix. (#447)
Saving models with TSUnwindowedDataset Dataloaders: AttributeError: 'TSUnwindowedDataset' object has no attribute 'new_empty' (#215)
compatibility with Pytorch 1.13 (#619)
added sel_vars to get_robustscale_params (#610)
added sel_steps to TSRandom2Value (#607)
new walk forward cross-validation in tsai (#582)
fixed issue when printing an empty dataset wo transforms NoTfmLists (#622)
fixed minor issue in get_robustscaler params with sel_vars (#615)
fixed issue when using tsai in dev with VSCode (#614)
issue when using lists as sel_vars and sel_steps in TSRandom2Value (#612)
fixed issue with feature_importance and step_importance when using metrics (#609)
renamed data processing tfms feature_idxs as sel_vars for consistency (#608)
fixed issue when importing 'GatedTabTransformer' (#536)
replaced TSOneHot preprocessor by TSOneHotEncode using a different API (#502)
replaced MultiEmbedding n_embeds, embed_dims and padding_idxs by n_cat_embeds, cat_embed_dims and cat_padding_idxs (#497)
added GaussianNoise transform (#514)
added TSSequencer model based on Sequencer: Deep LSTM for Image Classification paper (#508)
added TSPosition to be able to pass any steps list that will be concatenated to the input (#504)
added TSPosition preprocessor to allow the concatenation of a custom position sequence (#503)
added TSOneHot class to encode a variable on the fly (#501)
added token_size and tokenizer arguments to tsai (#496)
SmeLU activation function not found (#495)
added example on how to perform inference, partial fit and fine tuning (#491)
added get_time_per_batch and get_dl_percent_per_epoch (#489)
added TSDropVars used to removed batch variables no longer needed (#488)
added SmeLU activation function (#458)
Feature request: gMLP and GatedTabTransformer. (#354)
Pay Attention to MLPs - gMLP (paper, implementation)
The GatedTabTransformer (paper, implementation);
after_batch tfms set to empty Pipeline when using dl.new() (#516)
00b_How_to_use_numpy_arrays_in_fastai: AttributeError: attribute 'device' of 'torch._C._TensorBase' objects is not writable (#500)
getting regression data returns _check_X() argument error (#430)
I wonder why only 'Nor' is displayed in dls.show_batch(sharvey=True). (#416)
added StratifiedSampler to handle imbalanced datasets (#479)
added seq_embed_size and seq_embed arguments to TSiT (#476)
added get_idxs_to_keep that can be used to filter indices based on different conditions (#469)
added SmeLU activation function (#458)
added split_in_chunks (#454)
upgraded min Python version to 3.7 (#450)
added sampler argument to NumpyDataLoader and TSDataLoader (#436)
added TSMask2Value transform which supports multiple masks (#431)
added TSGaussianStandardize for improved ood generalization (#428)
added get_dir_size function (#421)
Added function that pads sequences to same length (#410)
Added TSRandomStandardize preprocessing technique (#396)
New visualization techniques: model's feature importance and step importance (#393)
Allow from tsai.basics import * to speed up loading (#320)
pip install tsai
from tsai.all import *
updated forward_gaps removing nan_to_num (#331)
TSRobustScaler only applied by_var (#329)
remove add_na arg from TSCategorize (#327)
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)
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)
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)