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deepmodeling / deepmd-kit

A deep learning package for many-body potential energy representation and molecular dynamics
https://docs.deepmodeling.com/projects/deepmd/
GNU Lesser General Public License v3.0
1.41k stars 486 forks source link

Feat/add dos finetune UT #3876

Closed anyangml closed 2 weeks ago

anyangml commented 3 weeks ago

Summary by CodeRabbit

coderabbitai[bot] commented 3 weeks ago

Walkthrough

The overall changes involve modifying the training.py file by simplifying the single_model_finetune function and removing unnecessary imports. New test cases have been added to test_finetune.py to support these changes. Additionally, a modification in stat.py introduces an early return for handling empty model_pred dictionaries. These updates seek to improve code clarity, efficiency, and coverage.

Changes

File Path Change Summary
deepmd/pt/train/training.py Removed import of DOSModel; simplified single_model_finetune function.
source/tests/pt/test_finetune.py Added model_dos, new DataRequirementItem, updated test_finetune_change_out_bias, new test class.
deepmd/pt/utils/stat.py Added check for empty model_pred and early return in compute_output_stats_global function.

Sequence Diagram(s)

sequenceDiagram
    participant TestSuite
    participant TrainingModule
    participant StatisticsModule

    TestSuite->>+TrainingModule: call single_model_finetune()
    TrainingModule-->>-TrainingModule: Simplified _model assignment
    TrainingModule-->>TestSuite: Return result

    TestSuite->>+StatisticsModule: call compute_output_stats_global(model_pred)
    StatisticsModule-->>StatisticsModule: Check if model_pred is empty
    alt model_pred is empty
        StatisticsModule-->>TestSuite: Return {}, {}
    else model_pred is not empty
        StatisticsModule->>StatisticsModule: Proceed with computation
        StatisticsModule-->>TestSuite: Return computed stats
    end

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codecov[bot] commented 3 weeks ago

Codecov Report

All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 82.71%. Comparing base (d23f7ae) to head (9547f29).

Additional details and impacted files ```diff @@ Coverage Diff @@ ## devel #3876 +/- ## ======================================= Coverage 82.70% 82.71% ======================================= Files 517 517 Lines 50137 50138 +1 Branches 2984 2987 +3 ======================================= + Hits 41467 41472 +5 + Misses 7760 7756 -4 Partials 910 910 ```

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