PaddleTS 0.1.0 Release Note EN

API

• Added TSDataset API for representing time series data with one or multiple target variables and optional different kinds of covariates (e.g. known covariates, observed covariates, and static covariates, etc.).
• Added PaddleBaseModel and PaddleBaseModelImpl API, which encapsulate routine procedures (e.g. data loading, callbacks setup, loss computation, training loop control, etc.), allows developers to focus on the implementation of network architectures when developing new models.
• Added 7 time series data transformation API for data preprocessing (e.g. missing values/outliers handling, one-hot encoding, normalization, and automatic date/time-related covariate generation, etc.).
• Added Analysis API for quick data exploration (e.g. basic statistics and summary).
• Added Metrics API for measuring time series model performance.

Models

Introduced 7 state-of-the-art deep learning models.

• LSTNet
• MLP
• NBEATS
• NHiTS
• RNN
• TCN
• Transformer

Environment Setup

• Supports Python 3.7 / 3.8 / 3.9
• Supports PaddlePaddle 2.3.0+
• Pre-built Docker Image: registry.baidubce.com/paddlets/paddlets:0.1.0