chore: improve type anotations in deepmd.infer

[njzjz]

Fix several incorrect type anotations.

Summary by CodeRabbit

• New Features

  • Enhanced flexibility in function and method parameters, allowing for more versatile use cases.

• Improvements

  • Streamlined type annotations for improved code maintainability and readability.
  • Updated import statements for better module organization and efficiency.

• Bug Fixes

  • Corrected parameter types to ensure proper handling of optional and varied input types.

These changes aim to improve the overall usability and robustness of the application, making it more adaptable to different scenarios.

[coderabbitai]

Walkthrough

Walkthrough

The updates primarily focus on enhancing flexibility and type safety across various modules in the deepmd package. Key changes include altering function signatures to use more generic type annotations, adding optional parameters, and introducing overloaded methods to support different input scenarios. These modifications aim to make the codebase more adaptable and maintainable, ensuring it can handle a wider range of input types and configurations.

Changes

File(s)	Change Summary
deepmd/dpmodel/infer/deep_eval.py, deepmd/infer/deep_eval.py, deepmd/pt/infer/deep_eval.py, deepmd/tf/infer/deep_eval.py	Updated function signatures to use more generic type annotations (Any), made certain parameters optional, and adjusted method return types.
deepmd/entrypoints/test.py	Replaced specific imports with a more general import statement for DeepTensor.
deepmd/infer/deep_dos.py, deepmd/infer/deep_polar.py	Changed kwargs parameter type to Any.
deepmd/infer/deep_pot.py	Added overloaded eval methods to support different input scenarios based on the atomic parameter.
deepmd/infer/model_devi.py	Modified the calc_model_devi_f function's signature to include overloads for the atomic parameter.
deepmd/tf/infer/deep_tensor.py	Updated eval and eval_full methods to accept an optional cells parameter.

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Review profile: CHILL

Commits

Files that changed from the base of the PR and between d62a41f and 81ec3b6.

Files selected for processing (10)

• deepmd/dpmodel/infer/deep_eval.py (2 hunks)
• deepmd/entrypoints/test.py (1 hunks)
• deepmd/infer/deep_dos.py (2 hunks)
• deepmd/infer/deep_eval.py (7 hunks)
• deepmd/infer/deep_polar.py (1 hunks)
• deepmd/infer/deep_pot.py (3 hunks)
• deepmd/infer/model_devi.py (2 hunks)
• deepmd/pt/infer/deep_eval.py (4 hunks)
• deepmd/tf/infer/deep_eval.py (5 hunks)
• deepmd/tf/infer/deep_tensor.py (2 hunks)

Files skipped from review due to trivial changes (2)

• deepmd/infer/deep_dos.py
• deepmd/infer/deep_polar.py

Additional Context Used

GitHub Check Runs (1)

CodeQL neutral (1)

deepmd/infer/model_devi.py: [notice] 50-50: Statement has no effect
This statement has no effect.

Additional comments not posted (26)

deepmd/infer/deep_pot.py (4)

93-105: The overloaded method eval for atomic: Literal[True] is well-defined with appropriate type annotations and optional parameters.

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107-119: The overloaded method eval for atomic: Literal[False] is correctly updated to enhance flexibility and maintainability.

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121-133: The addition of a generic overloaded eval method with a boolean atomic parameter increases the method's flexibility in handling different scenarios.

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Line range hint 134-144: The main eval method implementation is comprehensive, handling various scenarios effectively with the new flexible type annotations.

deepmd/dpmodel/infer/deep_eval.py (2)

79-82: The constructor __init__ now uses more generic type annotations for *args and **kwargs, enhancing flexibility and maintainability.

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164-169: The eval method is updated to allow cells to be optional and to accept more generic keyword arguments, improving the method's usability in different contexts.

deepmd/tf/infer/deep_tensor.py (2)

149-149: The eval method now correctly allows the cells parameter to be optional, aligning with the changes aimed at increasing method flexibility.

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279-279: The eval_full method has been updated to allow optional cells, maintaining consistency with the eval method and enhancing flexibility.

deepmd/infer/model_devi.py (3)

31-31: The overloaded method calc_model_devi_f for atomic: Literal[False] is correctly updated to use a more flexible type annotation.

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40-40: The overloaded method calc_model_devi_f for atomic: Literal[True] is appropriately updated to enhance flexibility.

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44-50: The addition of a generic overloaded calc_model_devi_f method with a boolean atomic parameter increases the method's flexibility in handling different scenarios.

deepmd/infer/deep_eval.py (7)

86-89: Updated type annotations for *args and **kwargs to Any enhance flexibility.

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103-108: The cells parameter is now optional, aligning with the flexibility described in the PR summary.

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170-176: The cells parameter in eval_descriptor method is now optional, which is consistent with the changes in eval.

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250-250: The method _check_mixed_types now returns a boolean directly using .item(), which is a more explicit conversion from a numpy array to a native Python type.

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254-254: The return type of model_type has been updated to Type["DeepEval"], improving type hinting and readability.

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320-323: The constructor of DeepEval class now uses Any for *args and **kwargs, aligning with the changes in DeepEvalBackend.

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391-391: The **kwargs parameter in eval_descriptor of DeepEval class is now more generic, which is consistent with other changes in the file.

deepmd/pt/infer/deep_eval.py (3)

91-95: Updated type annotations for *args and **kwargs to Any enhance flexibility in the PyTorch implementation of DeepEval.

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169-169: The return type of model_type has been updated to Type["DeepEvalWrapper"], improving type hinting and readability in the PyTorch context.

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215-220: The cells parameter is now optional in the eval method, aligning with changes in the TensorFlow implementation and enhancing flexibility.

deepmd/entrypoints/test.py (1)

49-49: Import of DeepTensor aligns with the PR's objective to adjust imports for improved type annotations.

deepmd/tf/infer/deep_eval.py (4)

13-13: Updated import of Type from typing module aligns with the new type annotations used in the class.

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266-266: Updated return type for model_type method to Type["DeepEvalWrapper"] enhances type hinting and readability.

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697-703: The method signature for eval has been updated to use Optional[np.ndarray] for cells and Any for **kwargs. This change increases the flexibility of the method by allowing cells to be optional and supporting a wider range of keyword arguments.

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Line range hint 1027-1084: The method signature for eval_descriptor and its inner method _eval_descriptor_inner have been updated similarly to eval, using Optional[np.ndarray] for cells and allowing more flexible keyword arguments with Any. This consistency in method signatures across the class is beneficial for maintainability.

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[codecov]

Codecov Report

Attention: Patch coverage is 75.00000% with 4 lines in your changes are missing coverage. Please review.

Project coverage is 82.58%. Comparing base (d62a41f) to head (81ec3b6).

Files	Patch %	Lines
deepmd/infer/deep_pot.py	66.66%	3 Missing ⚠️
deepmd/entrypoints/test.py	0.00%	1 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##            devel    #3792      +/-   ##
==========================================
- Coverage   82.58%   82.58%   -0.01%     
==========================================
  Files         515      515              
  Lines       48796    48806      +10     
  Branches     2982     2982              
==========================================
+ Hits        40300    40308       +8     
- Misses       7585     7587       +2     
  Partials      911      911              

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[wanghan-iapcm]

ref: https://stackoverflow.com/questions/37031928/type-annotations-for-args-and-kwargs