[ENH] softs_v2 Model added

[Muhammad-Rebaal]

Referencing #2231

Hi @fkiraly , @phoeenniixx, @PranavBhatP !

I have implemented the SOFTS (Star Aggregate-Dispatch for Time Series Forecasting) model within the PyTorch Forecasting v2 architecture.

Could you please review the PR?

Here is a summary of the changes made:

• Isolated Layer Abstraction (pytorch_forecasting/layers/_blocks/_softs_block.py): Implemented the core neural network components, specifically the novel STADModule (Star Aggregate-Dispatch mechanism) and the SoftsEncoderLayer, completely isolated from the base estimating logic to strictly adhere to the project's v2 architectural standards.
• Model Construction (pytorch_forecasting/models/softs/): Created the main Softs estimator wrapper which inherits from TslibBaseModel. It effectively handles dynamic feature input alignments (history_cont and history_target), optionally applies RevIN scaling, and routes the forward pass through the STAD-based encoders.
• V2 Package Management (_softs_pkg_v2.py): Established the Softs_pkg_v2 class representing model metadata (capability tags, compute requirements) and defined automated testing configurations (get_test_train_params) tightly integrated with the underlying TslibDataModule.
• Registry & Exports: Updated the relevant __init__.py files across the layers and models directories to properly expose Softs, Softs_pkg_v2, and the STAD blocks to the broader PyTorch Forecasting ecosystem.

Thank you!

[codecov]

Codecov Report

❌ Patch coverage is 82.35294% with 24 lines in your changes missing coverage. Please review.
⚠️ Please upload report for BASE (main@44e3ef2). Learn more about missing BASE report.

Files with missing lines	Patch %	Lines
pytorch_forecasting/models/softs/_softs_pkg_v2.py	51.28%	19 Missing ⚠️
pytorch_forecasting/models/softs/_softs_v2.py	91.80%	5 Missing ⚠️

Additional details and impacted files

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