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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
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fix: deeptensor output, add dipole stat UT #3948

Closed anyangml closed 2 months ago

anyangml commented 3 months ago

Summary by CodeRabbit

coderabbitai[bot] commented 3 months ago

Walkthrough

The recent changes involve modifications to the return type of the eval method in deepmd/infer/deep_tensor.py, converting it from a single np.ndarray to Tuple[np.ndarray]. Additionally, the test_permutation.py and test_finetune.py test files have been updated to incorporate a new model_dipole dictionary configuration, modify energy calculation requirements, and add new data requirements for "global_dipole."

Changes

Files Change Summary
deepmd/infer/deep_tensor.py Changed the return type of eval method from np.ndarray to Tuple[np.ndarray], returning values wrapped in tuples.
source/tests/pt/model/test_permutation.py Added model_dipole dictionary with configurations for a dipole model.
source/tests/pt/test_finetune.py Added model_dipole, new data requirements for "global_dipole," and modified energy calculations and class declarations.

Sequence Diagram(s)

sequenceDiagram
    participant Tester as Test Suite
    participant DT as DeepTensor
    participant ModelConfig as Model Configuration

    rect rgb(191, 223, 255)
    note over Tester, DT: Interaction for evaluating models
    Tester ->> DT: Call eval()
    DT -->> Tester: Return tuple of np.ndarray
    end

    rect rgb(245, 224, 177)
    note over Tester, ModelConfig: Interaction for configuring models in tests
    Tester ->> ModelConfig: Load model_dipole configuration
    ModelConfig -->> Tester: Configurations returned
    end

    rect rgb(255, 191, 191)
    note over Tester: Testing with new data requirements
    Tester ->> Tester: Test with global_dipole
    Tester ->> Tester: Adjust energy calculations
    end

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codecov[bot] commented 3 months ago

Codecov Report

Attention: Patch coverage is 0% with 2 lines in your changes missing coverage. Please review.

Project coverage is 34.83%. Comparing base (1c3e099) to head (aa5c20d).

Files Patch % Lines
deepmd/infer/deep_tensor.py 0.00% 2 Missing :warning:

:exclamation: There is a different number of reports uploaded between BASE (1c3e099) and HEAD (aa5c20d). Click for more details.

HEAD has 24 uploads less than BASE | Flag | BASE (1c3e099) | HEAD (aa5c20d) | |------|------|------| ||26|2|
Additional details and impacted files ```diff @@ Coverage Diff @@ ## devel #3948 +/- ## =========================================== - Coverage 82.84% 34.83% -48.02% =========================================== Files 520 520 Lines 50827 50795 -32 Branches 3015 3015 =========================================== - Hits 42108 17692 -24416 - Misses 7785 32495 +24710 + Partials 934 608 -326 ```

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.

anyangml commented 3 months ago

I may close this PR if ndarry is the expected output type.

anyangml commented 3 months ago

Could you please explain the reason of using Tuple[np.ndarray] instead of np.ndarray as returned type of DeepTensor?

It seems the other DeepModels all return a tuple object, I thought they should be consistent. When adding the new UT, DeepDipole eval needs special handling if a ndarray is returned. Although the UT is not as important, since dipole model does not apply bias, just want to check the changes made in #3945.