etna 1.11.0

Highlights:

• ETNA native RNN and base classes for deep learning models
• Lambda transform
• Prophet 1.1 support without c++ compiler dependency
• Prediction intervals for DeepAR and TFTModel
• Add known_future parameter to CLI

Full changelog:

Added

• LSTM based RNN and native deep models base classes (#776)
• Lambda transform (#762)
• assemble pipelines (#774)
• Tests on in-sample, out-sample predictions with gap for all models (#785)

Changed

• Add columns and mode parameters in plot_correlation_matrix (#726)
• Add CatBoostPerSegmentModel and CatBoostMultiSegmentModel classes, deprecate CatBoostModelPerSegment and CatBoostModelMultiSegment (#779)
• Allow Prophet update to 1.1 (#799)
• Make LagTransform, LogTransform, AddConstTransform vectorized (#756)
• Improve the behavior of plot_feature_relevance visualizing p-values (#795)
• Update poetry.core version (#780)
• Make native prediction intervals for DeepAR (#761)
• Make native prediction intervals for TFTModel (#770)
• Test cases for testing inference of models (#794)
• Wandb.log to WandbLogger (#816)

Fixed

• Fix missing prophet in docker images (#767)
• Add known_future parameter to CLI (#758)
• FutureWarning: The frame.append method is deprecated. Use pandas.concat instead (#764)
• Correct ordering if multi-index in backtest (#771)
• Raise errors in models.nn if they can't make in-sample and some cases out-sample predictions (#813)
• Teach BATS/TBATS to work with in-sample, out-sample predictions correctly (#806)
• Github actions cache issue with poetry update (#778)