chore: support preset bias of atomic model output

[wanghan-iapcm]

Summary by CodeRabbit

• New Features

  • Introduced a new preset_out_bias parameter for enhanced model configuration, allowing users to define biases.
  • Added documentation for the preset_out_bias parameter in the model arguments for improved clarity.

• Bug Fixes

  • Implemented validation to ensure the preset_out_bias length matches the model's type map, preventing runtime errors.

• Tests

  • Added unit tests for the get_model function to validate model attributes and ensure proper error handling for the new bias parameter.

[coderabbitai]

Walkthrough

Walkthrough

The pull request introduces modifications to the get_standard_model function in the deepmd/pt/model/model/__init__.py file by adding a new parameter, preset_out_bias, which allows for user-defined biases in model configurations. It includes validation to ensure the length of preset_out_bias matches type_map. Additionally, the BaseAtomicModel class in deepmd/pt/model/atomic_model/base_atomic_model.py is updated to change the type of preset_out_bias from PyTorch tensors to NumPy arrays. The model_args function in deepmd/utils/argcheck.py is updated to document this new parameter. A new test file, test_get_model.py, is added to validate the behavior of the get_model function, including tests for attribute settings and error handling.

Changes

File	Change Summary
deepmd/pt/model/model/init.py	Added preset_out_bias parameter to get_standard_model function with validation for length consistency with type_map. Introduced helper functions _convert_preset_out_bias_to_torch_tensor and _convert_preset_out_bias_to_array.
deepmd/pt/model/atomic_model/base_atomic_model.py	Changed type of preset_out_bias from Dict[str, List[Optional[torch.Tensor]]] to Dict[str, List[Optional[np.ndarray]]] in BaseAtomicModel. Updated constructor to reflect this change and added import for NumPy.
deepmd/utils/argcheck.py	Updated model_args function to include documentation for the new preset_out_bias parameter, defined as an optional dictionary with a default value of None.
deepmd/pt/utils/stat.py	Modified type annotations for preset_bias in compute_output_stats and compute_output_stats_global functions from Optional[Dict[str, List[Optional[torch.Tensor]]]] to Optional[Dict[str, List[Optional[np.ndarray]]]]. Updated _make_preset_out_bias function to standardize ibias parameter type to Optional[np.ndarray].
source/tests/pt/model/test_get_model.py	Introduced unit tests for the get_model function, including tests for attribute validation, default behavior when parameters are omitted, and error handling for incorrect preset_out_bias lengths. Added the TestGetModel class with three test methods: test_model_attr, test_notset_model_attr, and test_preset_wrong_len.

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Recent review details

Configuration used: CodeRabbit UI
Review profile: CHILL

Commits

Files that changed from the base of the PR and between 836e6c2 and 1afca1c.

Files selected for processing (2)

• deepmd/pt/model/atomic_model/base_atomic_model.py (3 hunks)
• deepmd/pt/utils/stat.py (4 hunks)

Files skipped from review as they are similar to previous changes (1)

• deepmd/pt/model/atomic_model/base_atomic_model.py

Additional comments not posted (2)

deepmd/pt/utils/stat.py (2)

190-191: LGTM!

The change in the type annotation of ibias parameter from Optional[np.array] to Optional[np.ndarray] is approved.

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Line range hint 245-267: Verify the impact of using NumPy arrays instead of PyTorch tensors for preset_bias.

The type annotation of preset_bias parameter has been updated to use NumPy arrays (np.ndarray) instead of PyTorch tensors (torch.Tensor).

Please ensure that this change is thoroughly tested to confirm that it behaves as expected and does not introduce any unintended side effects or performance issues.

Run the following script to verify the usage of preset_bias:

Tools

Ruff

242-242: Do not use mutable data structures for argument defaults

Replace with None; initialize within function

(B006)

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[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 83.02%. Comparing base (d2b6243) to head (1afca1c).
Report is 202 commits behind head on devel.

Additional details and impacted files

@@            Coverage Diff             @@
##            devel    #4116      +/-   ##
==========================================
- Coverage   83.02%   83.02%   -0.01%     
==========================================
  Files         532      532              
  Lines       52174    52187      +13     
  Branches     3030     3031       +1     
==========================================
+ Hits        43319    43328       +9     
- Misses       7911     7913       +2     
- Partials      944      946       +2     

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

[coderabbitai]

Actionable comments posted: 0

Outside diff range, codebase verification and nitpick comments (1)

deepmd/pt/model/model/__init__.py (1)

Line range hint 171-224: LGTM, but remove the unused variable.

The changes to get_standard_model look good. The new preset_out_bias parameter is correctly processed through the new helper function _convert_preset_out_bias_to_torch_tensor, allowing for user-defined biases in model configurations.

However, the static analysis tools have correctly identified that the variable default_preset_out_bias at line 197 is unused.

Please remove the unused variable:

-default_preset_out_bias = [None] * len(model_params["type_map"])
 preset_out_bias = model_params.get("preset_out_bias")

Tools

Ruff

197-197: Local variable default_preset_out_bias is assigned to but never used

Remove assignment to unused variable default_preset_out_bias

(F841)

GitHub Check: CodeQL

[notice] 197-197: Unused local variable
Variable default_preset_out_bias is not used.

[coderabbitai]

Actionable comments posted: 1

[njzjz]

2024-09-10T20:18:26.6301739Z =========================== short test summary info ============================
2024-09-10T20:18:26.6302282Z FAILED source/tests/pt/model/test_property_fitting.py::TestInvariance::test_trans - AssertionError: 
2024-09-10T20:18:26.6302507Z Not equal to tolerance rtol=1e-07, atol=0
2024-09-10T20:18:26.6302517Z 
2024-09-10T20:18:26.6302717Z Mismatched elements: 55 / 55 (100%)
2024-09-10T20:18:26.6302927Z Max absolute difference: 0.00115797
2024-09-10T20:18:26.6303063Z Max relative difference: 0.02320881
2024-09-10T20:18:26.6303396Z  x: array([[[ 1.013011, -0.031964,  0.467955, -1.055318,  0.08362 ,
2024-09-10T20:18:26.6303659Z           0.343627,  0.329521, -1.231861, -0.326444, -1.820717,
2024-09-10T20:18:26.6303812Z           1.033206],...
2024-09-10T20:18:26.6304088Z  y: array([[[ 1.01299 , -0.03189 ,  0.467994, -1.055362,  0.08366 ,
2024-09-10T20:18:26.6304419Z           0.343748,  0.329551, -1.231867, -0.326422, -1.82073 ,
2024-09-10T20:18:26.6304542Z           1.033258],...
2024-09-10T20:18:26.6304892Z = 1 failed, 8331 passed, 3631 skipped, 59809 deselected, 145 warnings in 1976.94s (0:32:56) =