fix(dpmodel): forward spin inputs in DeepEval#5852
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Normalize spin tensors before automatic batching and pass supported extra model inputs through the dpmodel evaluator. Preserve the magnetic mask in non-atomic DeepPot results and add multi-frame regression coverage. Coding-Agent: Codex Codex-Version: codex-cli 0.144.4 Model: gpt-5.6-sol Reasoning-Effort: xhigh
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## master #5852 +/- ##
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- Coverage 78.58% 78.33% -0.26%
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Files 1050 1050
Lines 120637 120648 +11
Branches 4356 4357 +1
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Closes #5661.
Summary
DeepEvaladapter while keeping evaluator-owned inputs canonicalDeepPotresultsWhy existing tests missed this
Existing dpmodel spin tests exercised direct model calls and serialization parity, not the
DeepEvaladapter. Public spin inference coverage targeted the PyTorch and PT2 backends, which already have dedicated spin forwarding paths. Those fixtures were also primarily single-frame, so they would not detect a flat spin tensor being left unsliced when automatic batching splits a multi-frame evaluation.Validation
pytest source/tests/infer/test_dpmodel_deep_eval_spin.py -q(2 passed)source/tests/common/test_auto_batch_size.py::TestAutoBatchSize::test_execute_all(passed)DeepEvalsmoke evaluation (passed)ruff format .(1664 files unchanged)ruff check .(passed)git diff --check(passed)Coding agent: Codex
Codex version: codex-cli 0.144.4
Model: gpt-5.6-sol
Reasoning effort: xhigh