Changelog
New Features:
Model averaging (823)
add SampleForecast and Predictor objects for TPPs (819)
Add temperature scaling to categorical distrubution (792)
Representation module (755)
New methods for missing value imputation (843)
Add shuffling function (873)
make distributions pickleable (889)
Aggregate lag transformation (886)
SimpleFeedForward to produce DistributionForecast (870)
Added support for gzipped files. (914)
MQCNN: Support for past dynamic features and scaling (916)
Implemented model iteration averaging to reduce model variance (901)
add nan support to simple feedforward model (933)
Added timeout option for batch requests. (931)
Implemented moving average (926)
NanMixture: Distribution to model missing values (913)
Added Rotbaum (653)
DeepTPP: RNN-based temporal point processes model (976)
Added logging of scored instances for batch-transform. (1010)
Enable distribution output in seq2seq (1008)
Implemented activation regularization (955)
Adding mean absolute quantile loss to avoid the case of dividing by 0 as a possible HPO metric (1012)
Inflated Beta Distributions (1018)
Implement different dropout strategies (963)
Adding support for `num_forking` as MQ-CNN hp (1022)
Generalised Pareto distribution (1031)
Added use of supported quantiles in shell when QuantileForecastGenerator is used. (1048)
PyTorch Predictor (1051)
Add TFT model (962)
ConvTrans Implementation (961)
Add evaluation metrics for anomaly detection (1065)
Add piecewise linear quantile function output with fixed knots (1074)
include callback in trainer and example for warm starting (1087)
initial pytorch distribution output class (1082)
Glide (995)
specialize plot method for QuantileForecast (1114)
Bug fixess
Fixed disabling of tqdm. (839)
Fix comparison of ParameterDict when non prefixed variables are in dict. (859)
Fixing edge case of prediction length 1. (867)
Frequency String for Pandas Timestamp (884)
fix imports (885)
Fixed invalid num_worker possibility. (892)
Corrected the formula for the stddev of the MixtureDistribution. (900)
Fix pathes in R for Windows. (903)
Scale the negative binomial's gamma (909)
Shape squeeze edge case bug fix (911)
Use of \n to split lines in batch transform. (920)
Fixing cardinality array when use_feat_static_cat = False but feat_static_cat present in dataset (918)
Fix batch-transform case, where request is empty. (927)
fix DeterministicOutput, add tests (982)
Fixing the FileDataset case with caching off for num_workers calculation (986)
Overriding early stopping for iteration-based averaging strategies (993)
Bug Fixes, Warnings, and One-Hot Encodings for Rotbaum (980)
Fixing case with only time features and yearly freq (1002)
Fixed import of Trainer. (1005)
Fixed DeepAR typing error (1017)
Fix sampling for MixtureDistribution class (1042)
MQ-CNN: Bound context_length by the max_ts_len - prediction_length (1037)
Fix gamma nans (1061)
Fix scaling for MQ-(C|R)NN when distribution outputs are used (1070)
added value in support to mixture output (1077)
fix Gamma distribution's NaN gradients for zero inputs (1078)
Fix dataset.splitter max_history argument (1085)
Fix max window (1097)
Ignore NaN values during training and throw a warning (training got stuck before) (1104)
Fix a few bugs about tensor shapes in default values for TFT implementation (1093)
Fixes awslabs/gluon-ts1106 (1125)
Breaking changes
Mqcnn rts (668)
Changed dataset.splitter to use DataEntry instead of TimeSeriesItem (890)
Refactoring data loading utilities (898)
Removed TimeSeriesItem. (904)
refactor imputation transformation (907)
making backtest_metrics simpler (924)
Moved get_seasonality from evaluation to time_feature. (971)
Removed mxContext from core. (977)
Other changes and improvements
Update bug_report.md (835)
Dockerfile for R container added (841)
Added mx module. (876)
Adapted use of mx module. Applied isort. (878)
Simplified AsNumpyArray. (879)
Removed unused `Transformation.estimate`. (880)
Added README to shell. (882)
Docs requirements (883)
add documentation related to shuffle_buffer_length/ (910)
Default QuantileForecast.mean to p50. (930)
Addded trimming to encoded sagemaker parameters in shell package. (917)
Shell: Fix writing of `output/failure` file in case of error in provided hyper-parameters. (942)
Pass listify_dataset as a hyperparameter through the shell (934)
Evaluation metrics now stored in output folder (938)
Make TrainEnv `path` argument explicit. (943)
Removing mp worker del method. (944)
Fixed logical error in data_loder tests. (951)
Pass multiprocessing parameters through the shell (952)
Fix pandas requirement. (967)
Fix `shell.train`.
Moved Dockerfiles to examples/dockerfiles (946)
Cleaned up unused imports. (1007)
Fix docstrings for SimpleFeedForward (1009)
Fix docstrings, enable distr_output in MQRNN (1021)
Update README.md (1024)
Update holidays version (1033)
improved and simplified aggregate lag transformation (1028)
Refactoring forecast generators and predictors for framework independence (1052)
Improved logging for batch-transform. (1059)
Reverting 1042 and adding shape assertions to the MixtureDistribution (1058)
Using pad_to_size function to remove duplicate code in pad_arrays (1047)
re-organized modules and imports (1068)
speed labels_to_ranges using numba (1071)
Fix numba warning; mask np.nan labels (1072)
added PyTorch predictor example notebook (1053)
refactor multiprocessing batcher to work with spawn method (1080)
Using zero floating point tolerance in denominator rather than checkign for exact zero equality (1079)
Fix FieldNames of Train/test splitter (1083)
Added Stateful to serde. (1088)
Added ty.checked decorator. (1091)
update links in readme (1090)
Adding test_quantiles hyperparameter to the shell to specify the quantiles for evaluation (1096)
Refactored serde into a package. (1100)
Refactored shell. (1101)
Updated pytest to v5. (1102)
cap pydantic version (1115)
add item_id to forecast from seasonal naive (1113)
reduce number of batches used in test (1131)
fix pandas usage and remove version cap (1132)