[WIP] On-the-fly data loading of global models

[SimonWittner]

🔬 Background

• Currently very high data consumption when loading global models with many IDs. Would fix Drastically increased memory load #1469

🔮 Key changes

• On the fly sampling of the dataloader

📋 Review Checklist

• I have performed a self-review of my own code.
• I have commented my code, added docstrings and data types to function definitions.
• I have added pytests to check whether my feature / fix works.

Please make sure to follow our best practices in the Contributing guidelines.

[github-actions]

Model Benchmark

Benchmark	Metric	main	current	diff
AirPassengers	MAE_val	31.6338	31.6338	0.0%	✅
AirPassengers	RMSE_val	32.6669	32.6669	0.0%	✅
AirPassengers	Loss_val	0.01372	0.01372	0.0%	✅
AirPassengers	MAE	6.24137	6.24137	0.0%	✅
AirPassengers	RMSE	7.82929	7.82929	0.0%	✅
AirPassengers	Loss	0.00063	0.00063	0.0%	✅
AirPassengers	time	10.2346	11.09	8.36%	❌
YosemiteTemps	MAE_val	0.64178	0.64178	0.0%	✅
YosemiteTemps	RMSE_val	0.92787	0.92787	0.0%	✅
YosemiteTemps	Loss_val	0.0005	0.0005	0.0%	✅
YosemiteTemps	MAE	1.092	1.092	0.0%	✅
YosemiteTemps	RMSE	1.89124	1.89124	0.0%	✅
YosemiteTemps	Loss	0.00155	0.00155	0.0%	✅
YosemiteTemps	time	62.2979	58.57	-5.98%	🎉
EnergyPriceDaily	MAE_val	5.55889	5.55889	0.0%	✅
EnergyPriceDaily	RMSE_val	7.12233	7.12233	0.0%	✅
EnergyPriceDaily	Loss_val	0.02829	0.02829	0.0%	✅
EnergyPriceDaily	MAE	6.37172	6.37172	0.0%	✅
EnergyPriceDaily	RMSE	8.53016	8.53016	0.0%	✅
EnergyPriceDaily	Loss	0.02907	0.02907	0.0%	✅
EnergyPriceDaily	time	15.2201	15.48	1.71%	✅
PeytonManning	MAE_val	0.3466	0.3466	0.0%	✅
PeytonManning	RMSE_val	0.49808	0.49808	0.0%	✅
PeytonManning	Loss_val	0.01752	0.01752	0.0%	✅
PeytonManning	MAE	0.34735	0.34735	0.0%	✅
PeytonManning	RMSE	0.48788	0.48788	0.0%	✅
PeytonManning	Loss	0.01457	0.01457	0.0%	✅
PeytonManning	time	21.7667	20.71	-4.85%	✅

Model training plots

Model Training

PeytonManning

YosemiteTemps

AirPassengers

EnergyPriceDaily

[codecov]

Codecov Report

Attention: 7 lines in your changes are missing coverage. Please review.

Comparison is base (5c45f46) 88.33% compared to head (660934c) 88.26%.
Report is 1 commits behind head on main.

Files	Patch %	Lines
neuralprophet/time_dataset.py	83.33%	7 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1495      +/-   ##
==========================================
- Coverage   88.33%   88.26%   -0.08%     
==========================================
  Files          38       38              
  Lines        5099     5128      +29     
==========================================
+ Hits         4504     4526      +22     
- Misses        595      602       +7     

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[SimonWittner]

Changes merged with PR #1510