Fix: model_output_type unify name

[anyangml]

Summary by CodeRabbit

Release Notes

• Bug Fixes
  • Improved model type detection to recognize additional model configurations, including polarizability-based variants. This expands compatibility with a broader range of supported models during inference operations.

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[Copilot]

Pull request overview

This PR fixes a bug in the PyTorch backend's model type detection by adding support for the "polarizability" output type name. The atomic model returns "polarizability" in its model_output_type(), but the inference code was only checking for "polar", causing polar models to fail type detection.

Key Changes:

• Updated the model type detection logic to recognize both "polar" and "polarizability" as indicators of a polar model

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📝 Walkthrough

Walkthrough

The model type detection logic in the deep evaluation module is modified to expand the conditions for selecting the DeepPolar model. The detection now triggers when the model output type contains either "polar" or "polarizability", whereas previously it only checked for "polar".

Changes

Cohort / File(s)	Summary
Model type detection expansion deepmd/pt/infer/deep_eval.py	Updated DeepPolar model selection condition to recognize both "polar" and "polarizability" in the model output type identifier

Estimated code review effort

🎯 1 (Trivial) | ⏱️ ~3 minutes

• Single file modification with a straightforward condition expansion
• No new logic density or control flow changes
• Localized, self-evident change requiring minimal context

Pre-merge checks and finishing touches

✅ Passed checks (3 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title 'Fix: model_output_type unify name' directly addresses the main change: expanding model type detection to handle both 'polar' and 'polarizability' variants, which is a unification of naming conventions for the model_output_type.
Docstring Coverage	✅ Passed	Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%.

✨ Finishing touches

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📥 Commits

Reviewing files that changed from the base of the PR and between 34f03fc and 44cf67f.

📒 Files selected for processing (1)

• deepmd/pt/infer/deep_eval.py (1 hunks)

🧰 Additional context used

🧠 Learnings (1)

📚 Learning: 2024-09-19T04:25:12.408Z

Learnt from: njzjz
Repo: deepmodeling/deepmd-kit PR: 4144
File: source/api_cc/tests/test_deeppot_dpa_pt.cc:166-246
Timestamp: 2024-09-19T04:25:12.408Z
Learning: Refactoring between test classes `TestInferDeepPotDpaPt` and `TestInferDeepPotDpaPtNopbc` is addressed in PR #3905.

Applied to files:

• deepmd/pt/infer/deep_eval.py

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🔇 Additional comments (1)

deepmd/pt/infer/deep_eval.py (1)

242-260: The concerns raised about redundancy and ordering bugs are not applicable.

The model_output_type() method returns a List[str], not a string. This means the in operator checks for list membership, not substring matching. Therefore:

1. The explicit check for "polarizability" alongside "polar" is necessary and correct—they are distinct strings in the output type list that can both exist.
2. There is no ordering bug with "global_polar" since substring matching does not occur with list membership checks.

The code change is valid: both "polar" and "polarizability" output types should map to DeepPolar.

Likely an incorrect or invalid review comment.

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[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 84.33%. Comparing base (bfa6245) to head (44cf67f).
⚠️ Report is 38 commits behind head on devel.

Additional details and impacted files

@@            Coverage Diff             @@
##            devel    #5069      +/-   ##
==========================================
+ Coverage   84.28%   84.33%   +0.04%     
==========================================
  Files         708      709       +1     
  Lines       69911    70445     +534     
  Branches     3608     3619      +11     
==========================================
+ Hits        58923    59407     +484     
- Misses       9832     9871      +39     
- Partials     1156     1167      +11     

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