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Changelog

Source: NEWS.md

modeltime.gluonts 0.3.0

Support for GluonTS 0.8.0 and Pytorch Backend:

Modeltime GluonTS now support gluonts 0.8.0. Simply run install_gluonts() to upgrade. The upgraded support makes modeltime.gluonts incompatible with earlier versions of GluonTS (e.g. gluonts 0.6.3). The solution is to upgrade to gluonts 0.8.0, which requires:

  • gluonts==0.8.0

  • mxnet~=1.7

Additionally, GluonTS 0.8.0 now supports pytorch as a backend. Use install_gluonts(include_pytorch = TRUE) to simplify installation of the PyTorch backend. Pytorch backend requirements:

  • torch~=1.6.0

  • pytorch-lightning~=1.1

New Algorithms

Pytorch DeepAR

A new engine has been added to deep_ar() that enables the Pytorch backend using set_engine("torch"). This requires the Python packages pytorch and pytorch-lightning. Use install_gluonts(include_pytorch = TRUE) to simplify installation.

GP Forecaster Algorithm

A new function, gp_forecaster(), integrates the Gaussian Process Estimator from GluonTS.

Deep State Algorithm

A new function, deep_state(), integrates the Deep State Estimator from GluonTS.

Tutorials

  • We’ve updated the Installation Guide. This includes revised requirements for installation, upgrading to modeltime.gluonts >= 0.3.0, troubleshooting installation, python environment requirements, and custom python environments.

  • We’ve updated the Getting Started Guide to go through a DeepAR example.

  • We’ve update the GPU Setup Instructions to cover Modeltime >=0.3.0.

Improvements

  • install_gluonts(): Gains two new parameters to help with upgrading:
    1. fresh_install: If TRUE, will remove prior installations of the r-glounts conda environment to setup for a fresh installation. This can be useful if errors appear during upgrades. Default: FALSE.
    2. include_pytorch: If TRUE, will install torch. Needed for Torch implementation of deep_ar(). Default: FALSE.

Breaking Changes

  • GluonTS <= 0.8.0. The modeltime.gluonts package version >= 0.2.2.9000 is not compatible with gluonts < 0.8.0. To fix, simply upgrade to gluonts 0.8.0.

modeltime.gluonts 0.2.2

Dials Params

  • NBEATS Models: Adding Dials helpers #14

modeltime.gluonts 0.2.1

Improvements made to connect with the GluonTS Python Environment on Startup.

modeltime.gluonts 0.2.0

New Vignettes

New Features

  • Internal Scaling by Group: After significant testing it appears that some data sets return better results when the data is scaled by time series “id” (group). To help facilitate this, a new option is available scale by id: scale = TRUE.

  • Custom Python Environments: Provide an option for setting a Custom Python Environment by supplying a GLUONTS_PYTHON environment variable. Before running library(modeltime.gluonts) use Sys.setenv(GLUONTS_PYTHON = 'path/to/python') to set the path of your python executable in a Conda or Virtual Environment that has ‘gluonts’, ‘mxnet’, ‘numpy’, ‘pandas’ and ‘pathlib’ available as dependencies.

Fixes & Improvements

  • GluonTS 0.6.3 Upgrade: install_gluonts() now uses gluonts==0.6.3. This upgrade improves forecast accuracy.
  • CRAN Comment - Add SystemRequirements: GluonTS.
  • CRAN Comment - Fix .onLoad message to provide options for configuring the Python Environment.

modeltime.gluonts 0.1.0

CRAN release: 2020-11-30