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improve code coverage by including "symbreak" for chgnet training #404

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merged 63 commits into from
Oct 22, 2024

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Summary

improve code coverage by including "symbreak" for chgnet training in the united test

Checklist

  • Google format doc strings added. Check with ruff.
  • Type annotations included. Check with mypy.
  • Tests added for new features/fixes.
  • If applicable, new classes/functions/modules have duecredit @due.dcite decorators to reference relevant papers by DOI (example)

Tip: Install pre-commit hooks to auto-check types and linting before every commit:

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kenko911 and others added 30 commits June 22, 2024 09:24
Signed-off-by: Tsz Wai Ko <[email protected]>
kenko911 and others added 27 commits September 4, 2024 11:24
…s and Simulations using the M3GNet Universal Potential.ipynb
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
Signed-off-by: Tsz Wai Ko <[email protected]>
Bumps [boto3](https://github.com/boto/boto3) from 1.35.38 to 1.35.39.
- [Release notes](https://github.com/boto/boto3/releases)
- [Commits](boto/boto3@1.35.38...1.35.39)

---
updated-dependencies:
- dependency-name: boto3
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <[email protected]>
* improve TensorNet model coverage

* Update pyproject.toml

Signed-off-by: Tsz Wai Ko <[email protected]>

* Improve the unit test for SO(3) equivarance in TensorNet class

* improve SO3Net model class coverage and simplify TensorNet implementations

* improve the coverage in MLP_norm class

* Improve the implementation of three-body interactions

* fixed black

* Optimize the speed of _compute_3body class

* type checking is added for scheduler

* update M3GNet Potential training notebook for the demonstration of obtaining and using element offsets

* Downgrade sympy to avoid crash of SO3 operations

* Smooth l1 loss function is added and united tests are improved

* merge the method predict_structure and featurize_structure into a function including both

* remove unnecessary else statement for training magmoms

* modify so3 operation implementation to make united tests pass due to the update of sympy

* skip test_load_all_models for MacOS pytest now

* Reference for CHGNet is added

* Update README.md and index.md for including CHGNet

Signed-off-by: Tsz Wai Ko <[email protected]>

* add more description for using CHGNet pretrained models in Relaxations and Simulations using the M3GNet Universal Potential.ipynb

* A command-line interface for performing ASE MD simulations is added

* added back py.typed

* ExpNormal Smearing for radial basis functions is added

* Changed deprecated torch.scalar_tensor into torch.Tensor

Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
Signed-off-by: Tsz Wai Ko <[email protected]>

* Converted the float number into tensor

Signed-off-by: Tsz Wai Ko <[email protected]>

* fix the united test in test_bond.py

* fix the error from the upgrade of boto3

* Downgrade DGL to 2.2.1

* Downgrade pytorch

* fix mypy by adding self.norm_layers is not None

---------

Signed-off-by: Tsz Wai Ko <[email protected]>
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
Co-authored-by: Shyue Ping Ong <[email protected]>
@kenko911 kenko911 requested a review from shyuep as a code owner October 22, 2024 02:09
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coderabbitai bot commented Oct 22, 2024

Walkthrough

The changes in this pull request focus on enhancing the TestModelTrainer class in the tests/utils/test_training.py file. Key modifications include updates to the CHGNet model's training parameters, the introduction of tests for scenarios involving missing labels and multiple target values, and the addition of a test for CHGNet without magnetic moment labels. These changes aim to improve the robustness and coverage of the testing framework for various models.

Changes

File Change Summary
tests/utils/test_training.py - Updated CHGNet initialization to include magmom_target.
- Added test_chgnet_training_without_m method to test CHGNet without magnetic moments.
- Added test_chgnet_training_with_missing_label method for handling missing labels during training.
- Added test_m3gnet_property_trainin_multiple_values_per_target method for testing M3GNet with multiple target values.

Possibly related PRs

  • Increase more code coverage in _chgnet.py #261: This PR enhances the testing of the CHGNet model, which is directly related to the changes made in the main PR regarding the CHGNet model's training and testing scenarios.
  • Improve the coverage in MLP_norm class #278: This PR improves coverage in the MLP_norm class, which may relate to the overall testing framework improvements in the main PR, although it does not directly modify the same functions or classes.

📜 Recent review details

Configuration used: .coderabbit.yaml
Review profile: CHILL

📥 Commits

Files that changed from the base of the PR and between 9632254 and a2c6b80.

📒 Files selected for processing (1)
  • tests/utils/test_training.py (1 hunks)
🧰 Additional context used
🔇 Additional comments (1)
tests/utils/test_training.py (1)

683-685: Verify that magmom_target is a valid parameter for PotentialLightningModule.

The parameter magmom_target="symbreak" has been added to the PotentialLightningModule initialization. Please ensure that the PotentialLightningModule class's __init__ method accepts this parameter and handles it appropriately.

Run the following script to confirm whether PotentialLightningModule accepts the magmom_target parameter:


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@kenko911 kenko911 merged commit a7729ed into materialsvirtuallab:main Oct 22, 2024
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2 participants