[BUG] Fix y not being normalized when using EncoderNormalizer

[AmjadAAYD]

Fixes #2360. When using EncoderNormalizer (fit per encoder window, not globally), target_past was normalized at getitem time but the decoder target y was left raw, so the model was trained to predict the raw scale while being fed a normalized encoder input. Fixed by transforming y with the same per-sequence-fitted normalizer used for target_past. For the multi-target case, added a transform_sequence() method on ScalerAdapter mirroring fit_transform_sequence()'s per-column logic (only transform sub-normalizers that are fit_per_sequence, leave the globally-normalized ones untouched) instead of naively calling the top-level transform(), which broke GroupNormalizer sub-adapters that need group columns X. Added a regression test (test_encoder_normalizer_scales_decoder_target) verifying y now matches normalizer.transform() of the raw decoder target. Full test_data_module.py suite passes (43 passed).

[phoeenniixx]

can you please make sure that code quality is passing?

[AmjadAAYD]

Fixed, was just line-length + a formatting nit. Rebased on main too. Code-quality should pass now.

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
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Additional details and impacted files

@@           Coverage Diff           @@
##             main    #2393   +/-   ##
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  Coverage        ?   88.14%           
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  Files           ?      196           
  Lines           ?    11063           
  Branches        ?        0           
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  Hits            ?     9751           
  Misses          ?     1312           
  Partials        ?        0           

Flag	Coverage Δ
cpu	88.14% <100.00%> (?)
pytest	88.14% <100.00%> (?)

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[AmjadAAYD]

Fixed the coverage gap too, turned out to be dead code (a shape guard that could never actually trigger for real multi-target data), removed it .