fix(model): resolve cross-day batching issue in DailyBatchSampler

[Akshay Kumar Hudedmani (akshaykumarhudedmani)]

Description

Fixes #2319. DailyBatchSampler previously assumed that the dataset rows belonging to the same trading day were contiguous. However, since the dataset is instrument-major, it was silently yielding cross-day batches (one instrument across many consecutive days).
This PR rewrites DailyBatchSampler to explicitly group by the datetime index level, yielding batches that are true cross-sectional single days. Additionally, it properly re-aligns the prediction output in the GATs.predict method to match the new iteration order of the sampler.

Motivation and Context

Fixes #2319. Training with cross-day batches completely invalidates cross-sectional models like GATs, as the graph/attention operates over a single stock's history rather than a single day's cross-section.

How Has This Been Tested?

• Pass the test by running: pytest qlib/tests/test_all_pipeline.py under upper directory of qlib.
• If you are adding a new feature, test on your own test scripts.

Screenshots of Test Results (if appropriate):

Pipeline test passed successfully. Validated locally via isolated sampler iteration test.

Types of changes

• Fix bugs
• Add new feature
• Update documentation

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