awslabs/gluonts

Introduce model input API

Open

#2,650 opened on Feb 14, 2023

View on GitHub
 (0 comments) (0 reactions) (0 assignees)Python (753 forks)batch import
enhancementhelp wanted

Repository metrics

Stars
 (3,888 stars)
PR merge metrics
 (Avg merge 26d 17h) (4 merged PRs in 30d)

Description

Model networks expect a set of parameters.

For example, DeepAR (mxnet) takes the following values:

https://github.com/awslabs/gluonts/blob/9260639dd28791e48db694d409fe5ef1eeb6806d/src/gluonts/mx/model/deepar/_network.py#L874-L886

It would be useful to make these parameters available on Estimator and Predictor to expose what input values (incl. type, etc) are expected.

We already do this to some extend in torch, where we expose input_shapes and input_types on some models.

Ideally we have single way of retrieving this information from all trainable models, both mxnet and torch.

Contributor guide

Research direction
Investigate the existing `input shapes` and `input types` in torch models, then design a unified API that works for both mxnet and torch models, ensuring backward compatibility.
Tech stack
python
Domain
machine learning
Issue type
Feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
3-5 days
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Fresh
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Mostly clear
Prerequisites
PythonGluonTS
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
30