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fix(tf): fix modifier_type in DeepEval #3855

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merged 1 commit into from
Jun 6, 2024

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@njzjz njzjz commented Jun 4, 2024

A downgrade in #3213.

Summary by CodeRabbit

  • New Features
    • Added support for modifier_type in the evaluation process to enhance model flexibility.
  • Tests
    • Introduced unit tests for deep potential model evaluation using TensorFlow.

@njzjz njzjz requested review from iProzd and wanghan-iapcm June 4, 2024 21:25
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coderabbitai bot commented Jun 4, 2024

Walkthrough

Walkthrough

The changes primarily focus on enhancing the DeepEval class in the deepmd/tf/infer/deep_eval.py file by incorporating a new attribute, modifier_type, and initializing it correctly. Additionally, a new test file, test_dplr.py, has been added to validate the deep potential model's evaluation functionality using TensorFlow for molecular dynamics simulations.

Changes

Files Change Summary
deepmd/tf/infer/deep_eval.py Initialized modifier_type in the constructor, added it to _init_tensors, and set it in _init_attr.
source/tests/tf/test_dplr.py Added a new test class TestDPLR to test the evaluation functionality of a deep potential model.

Sequence Diagram(s) (Beta)

sequenceDiagram
    participant User
    participant DeepEval
    participant TensorFlow
    participant TestDPLR

    User->>DeepEval: Initialize instance
    DeepEval->>DeepEval: _init_tensors
    DeepEval->>TensorFlow: Fetch tensor values
    TensorFlow-->>DeepEval: Return tensor values
    DeepEval->>DeepEval: Set modifier_type in _init_attr

    TestDPLR->>DeepEval: Call evaluation functionality
    DeepEval->>TensorFlow: Perform evaluation
    TensorFlow-->>DeepEval: Return evaluation results
    DeepEval-->>TestDPLR: Return results
    TestDPLR-->>User: Display test results
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Recent review details

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Review profile: CHILL

Commits

Files that changed from the base of the PR and between eb474d4 and f9e0a5a.

Files selected for processing (2)
  • deepmd/tf/infer/deep_eval.py (3 hunks)
  • source/tests/tf/test_dplr.py (1 hunks)
Files skipped from review due to trivial changes (1)
  • source/tests/tf/test_dplr.py
Additional comments not posted (2)
deepmd/tf/infer/deep_eval.py (2)

204-204: Initialization of modifier_type in _init_tensors method.

This change aligns with the PR's objective to handle modifier_type more effectively by initializing it in the _init_tensors method instead of the constructor.


265-267: Handling of modifier_type in _init_attr method.

The update to conditionally set modifier_type based on its presence in tensors is a robust enhancement. This ensures that modifier_type is only set if it is indeed available, preventing potential errors.


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@github-actions github-actions bot added the Python label Jun 4, 2024
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codecov bot commented Jun 4, 2024

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 82.67%. Comparing base (eb474d4) to head (f9e0a5a).
Report is 120 commits behind head on devel.

Additional details and impacted files
@@            Coverage Diff             @@
##            devel    #3855      +/-   ##
==========================================
- Coverage   82.67%   82.67%   -0.01%     
==========================================
  Files         515      515              
  Lines       49549    49551       +2     
  Branches     2989     2985       -4     
==========================================
+ Hits        40965    40966       +1     
- Misses       7673     7674       +1     
  Partials      911      911              

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@iProzd iProzd added this pull request to the merge queue Jun 6, 2024
Merged via the queue into deepmodeling:devel with commit b780108 Jun 6, 2024
60 checks passed
mtaillefumier pushed a commit to mtaillefumier/deepmd-kit that referenced this pull request Sep 18, 2024
A downgrade in deepmodeling#3213.

<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->

## Summary by CodeRabbit

- **New Features**
- Added support for `modifier_type` in the evaluation process to enhance
model flexibility.
- **Tests**
- Introduced unit tests for deep potential model evaluation using
TensorFlow.

<!-- end of auto-generated comment: release notes by coderabbit.ai -->

Signed-off-by: Jinzhe Zeng <[email protected]>
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3 participants