v0.11📈Six algos for forecasting

We make Time-LLM, TEFN, FITS, TimeMixer, GPT4TS, and Transformer work on the forecasting task (still accept POTS as input) for you in this release of v0.11

Additionally, we conduct some refactorings in this version:

1. AMP (Automatic Mixed Precision) is enabled for LLM-based model training. Users can switch it on by specifying the env var ENABLE_AMP #594;
2. pypots tuning is now renamed into pypots hpo #592;
3. pypots environment variables are capitalized #591;
4. all data preprocessing functions are removed from pypots, and users are encouraged to fully use BenchPOTS instead, which includes processing pipelines for 172 public datasets #585;

What's Changed

• Refactor some parts by @WenjieDu in #586
• Update docs by @WenjieDu in #587
• Remove data prerprocessing pipelines and update docs by @WenjieDu in #588
• Capitalize env vars and rename PyPOTS tuning module into hpo by @WenjieDu in #593
• Enable AMP (Automatic Mixed Precision) in PyPOTS by @WenjieDu in #594
• Add pypots.forecasting.Transformer by @WenjieDu in #597
• Add pypots.forecasting.FITS by @WenjieDu in #600
• Add pypots.forecasting.TEFN by @WenjieDu in #602
• Add pypots.forecasting.TimeMixer by @WenjieDu in #603
• Add pypots.forecasting.TimeLLM by @WenjieDu in #604
• Add pypots.forecasting.GPT4TS by @WenjieDu in #605
• Fix x and x_mark shape not consistent bug in forecasting TimeMixer by @WenjieDu in #607
• Release v0.11 by @WenjieDu in #608

Full Changelog: v0.10...v0.11