fix: type of the preset out bias

[wanghan-iapcm]

Summary by CodeRabbit

• New Features

  • Enhanced error handling for the preset_out_bias parameter, allowing for better validation of input types.
  • Expanded documentation for preset_out_bias, providing clearer guidelines and examples for users.

• Bug Fixes

  • Improved robustness by ensuring unsupported types for energy values raise appropriate errors.

• Tests

  • Added new tests to validate the handling of various input types for the preset_out_bias parameter, ensuring correct processing and error reporting.

[coderabbitai]

Walkthrough

Walkthrough

The changes introduce a new helper function, _can_be_converted_to_float, to improve type validation in the _convert_preset_out_bias_to_array function. This function checks if elements in the preset_out_bias dictionary can be converted to floats. Additionally, the type annotation for preset_out_bias is modified to allow more complex structures. New tests are added to ensure the model correctly handles various input types for preset_out_bias, enhancing error handling and robustness.

Changes

File Path	Change Summary
deepmd/pt/model/model/__init__.py	Added _can_be_converted_to_float function to validate float conversion for preset_out_bias.
deepmd/utils/argcheck.py	Modified documentation and type annotation for preset_out_bias to support more complex structures, allowing lists of floats.
source/tests/pt/model/test_get_model.py	Added three tests for handling preset_out_bias: checking valid float inputs, rejecting unsupported types, and rejecting unsupported string representations.

Possibly related PRs

• chore: support preset bias of atomic model output #4116: The main PR introduces a new helper function _can_be_converted_to_float that enhances the logic of _convert_preset_out_bias_to_array, while PR chore: support preset bias of atomic model output #4116 also modifies the _convert_preset_out_bias_to_array function, indicating a direct connection in handling the preset_out_bias parameter.

Suggested labels

Python

Suggested reviewers

• @
• @njzjz

---

Recent review details

Configuration used: CodeRabbit UI
Review profile: CHILL

Commits

Files that changed from the base of the PR and between 64e6e52 and 4ed8417.

Files selected for processing (3)

• deepmd/pt/model/model/init.py (2 hunks)
• deepmd/utils/argcheck.py (2 hunks)
• source/tests/pt/model/test_get_model.py (1 hunks)

Additional comments not posted (6)

source/tests/pt/model/test_get_model.py (3)

66-83: LGTM!

The test method is well-structured and covers an important case of handling different types of energy values. It verifies that the model correctly processes a list of energy values that includes a string representation of a float, an integer, and a None value, and checks that the model's attributes are set as expected.

---

85-89: LGTM!

The test method is well-structured and covers an important case of handling unsupported types for energy values. It ensures that the model raises a ValueError when the preset_out_bias contains a complex number as one of its energy values, indicating that the model is expected to reject unsupported types for energy values.

---

91-95: LGTM!

The test method is well-structured and covers an important case of handling unsupported formats for energy values. It checks for a ValueError when the energy values include a string representation of a complex number, reinforcing the model's validation logic regarding the types and formats of energy values it can accept.

deepmd/pt/model/model/__init__.py (2)

154-160: LGTM!

The _can_be_converted_to_float function is implemented correctly. It handles the common exceptions that can occur during float conversion and returns the appropriate boolean value.

---

Line range hint 162-182: Excellent improvements to the _convert_preset_out_bias_to_array function!

The changes introduce robust validation and error handling for the elements of preset_out_bias. The use of the _can_be_converted_to_float function ensures that only supported types are processed, and the descriptive error messages help in identifying and debugging issues related to unsupported types or mismatched lengths.

These enhancements improve the overall reliability and maintainability of the code.

deepmd/utils/argcheck.py (1)

Line range hint 1840-1844: Approve the more flexible type for preset_out_bias.

The type change of preset_out_bias from Dict[str, List[Optional[float]]] to Dict[str, List[Optional[Union[float, List[float]]]]] allows specifying a list of floats for each component of a multi-dimensional atomic property in addition to a single float.

This improves flexibility while maintaining backwards compatibility. The updated documentation and example for a dipole model clarify the usage well.

---

Thank you for using CodeRabbit. We offer it for free to the OSS community and would appreciate your support in helping us grow. If you find it useful, would you consider giving us a shout-out on your favorite social media?

Share

• X
• Mastodon
• Reddit
• LinkedIn

Tips

Chat

There are 3 ways to chat with CodeRabbit:

• Review comments: Directly reply to a review comment made by CodeRabbit. Example:
  -- I pushed a fix in commit <commit_id>, please review it.
  -- Generate unit testing code for this file.
  • Open a follow-up GitHub issue for this discussion.
• Files and specific lines of code (under the "Files changed" tab): Tag @coderabbitai in a new review comment at the desired location with your query. Examples:
  -- @coderabbitai generate unit testing code for this file.
  -- @coderabbitai modularize this function.
• PR comments: Tag @coderabbitai in a new PR comment to ask questions about the PR branch. For the best results, please provide a very specific query, as very limited context is provided in this mode. Examples:
  -- @coderabbitai generate interesting stats about this repository and render them as a table.
  -- @coderabbitai read src/utils.ts and generate unit testing code.
  -- @coderabbitai read the files in the src/scheduler package and generate a class diagram using mermaid and a README in the markdown format.
  -- @coderabbitai help me debug CodeRabbit configuration file.

Note: Be mindful of the bot's finite context window. It's strongly recommended to break down tasks such as reading entire modules into smaller chunks. For a focused discussion, use review comments to chat about specific files and their changes, instead of using the PR comments.

CodeRabbit Commands (Invoked using PR comments)

• @coderabbitai pause to pause the reviews on a PR.
• @coderabbitai resume to resume the paused reviews.
• @coderabbitai review to trigger an incremental review. This is useful when automatic reviews are disabled for the repository.
• @coderabbitai full review to do a full review from scratch and review all the files again.
• @coderabbitai summary to regenerate the summary of the PR.
• @coderabbitai resolve resolve all the CodeRabbit review comments.
• @coderabbitai configuration to show the current CodeRabbit configuration for the repository.
• @coderabbitai help to get help.

Other keywords and placeholders

• Add @coderabbitai ignore anywhere in the PR description to prevent this PR from being reviewed.
• Add @coderabbitai summary to generate the high-level summary at a specific location in the PR description.
• Add @coderabbitai anywhere in the PR title to generate the title automatically.

CodeRabbit Configuration File (.coderabbit.yaml)

• You can programmatically configure CodeRabbit by adding a .coderabbit.yaml file to the root of your repository.
• Please see the configuration documentation for more information.
• If your editor has YAML language server enabled, you can add the path at the top of this file to enable auto-completion and validation: # yaml-language-server: $schema=https://coderabbit.ai/integrations/schema.v2.json

Documentation and Community

• Visit our Documentation for detailed information on how to use CodeRabbit.
• Join our Discord Community to get help, request features, and share feedback.
• Follow us on X/Twitter for updates and announcements.

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 83.02%. Comparing base (64e6e52) to head (4ed8417).
Report is 194 commits behind head on devel.

Additional details and impacted files

@@            Coverage Diff             @@
##            devel    #4135      +/-   ##
==========================================
- Coverage   83.03%   83.02%   -0.01%     
==========================================
  Files         532      532              
  Lines       52187    52198      +11     
  Branches     3030     3030              
==========================================
+ Hits        43331    43338       +7     
- Misses       7911     7913       +2     
- Partials      945      947       +2     

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