search

deepmodeling / deepmd-kit

A deep learning package for many-body potential energy representation and molecular dynamics
https://docs.deepmodeling.com/projects/deepmd/
GNU Lesser General Public License v3.0
1.41k stars 486 forks source link

fix(pt): fix seed in dpmodel fitting #3916

Closed iProzd closed 1 week ago

iProzd commented 1 week ago

Summary by CodeRabbit

coderabbitai[bot] commented 1 week ago
Walkthrough ## Walkthrough The recent updates across various files in the `deepmd/dpmodel/fitting` module mainly involve the inclusion and activation of a `seed` parameter in the `__init__` methods of several classes. These changes help in controlling random number generation within the module, enhancing reproducibility. Additionally, some redundant comments were removed, and initialization logic was refined for clarity and explicitness, particularly setting flags such as `old_impl`. ## Changes | File | Change Summary | |----------------------------------------------------|-----------------------------------| | `deepmd/dpmodel/fitting/dipole_fitting.py` | Removed `seed` from initial declaration, added during object initialization, set `old_impl` to `False`. | | `deepmd/dpmodel/fitting/dos_fitting.py` | Activated and reordered `seed` parameter in `__init__` method. | | `deepmd/dpmodel/fitting/ener_fitting.py` | Utilized `seed` parameter in `__init__` method, was previously commented out. | | `deepmd/dpmodel/fitting/invar_fitting.py` | Added `seed` parameter to `__init__` method of `FittingInvar` class. | | `deepmd/dpmodel/fitting/polarizability_fitting.py` | Included `seed` in `__init__`, cleaned up comments, and passed `seed` to another function within the method. |
Recent review details **Configuration used: CodeRabbit UI** **Review profile: CHILL**
Commits Files that changed from the base of the PR and between 17cdcb0d59460b1baf487804259706fc6bd28cae and 6d303ee01d8395ee56c3d3be2d56759a043703c3.
Files selected for processing (5) * deepmd/dpmodel/fitting/dipole_fitting.py (2 hunks) * deepmd/dpmodel/fitting/dos_fitting.py (2 hunks) * deepmd/dpmodel/fitting/ener_fitting.py (2 hunks) * deepmd/dpmodel/fitting/invar_fitting.py (3 hunks) * deepmd/dpmodel/fitting/polarizability_fitting.py (2 hunks)
Additional context used
Ruff
deepmd/dpmodel/fitting/ener_fitting.py
33-33: Do not use mutable data structures for argument defaults Replace with `None`; initialize within function (B006) --- 47-47: Do not use mutable data structures for argument defaults Replace with `None`; initialize within function (B006)
deepmd/dpmodel/fitting/dos_fitting.py
36-36: Do not use mutable data structures for argument defaults Replace with `None`; initialize within function (B006) --- 46-46: Do not use mutable data structures for argument defaults Replace with `None`; initialize within function (B006)
deepmd/dpmodel/fitting/dipole_fitting.py
93-93: Do not use mutable data structures for argument defaults Replace with `None`; initialize within function (B006) --- 106-106: Do not use mutable data structures for argument defaults Replace with `None`; initialize within function (B006)
deepmd/dpmodel/fitting/invar_fitting.py
121-121: Do not use mutable data structures for argument defaults Replace with `None`; initialize within function (B006) --- 136-136: Do not use mutable data structures for argument defaults Replace with `None`; initialize within function (B006)
deepmd/dpmodel/fitting/polarizability_fitting.py
98-98: Do not use mutable data structures for argument defaults Replace with `None`; initialize within function (B006) --- 111-111: Do not use mutable data structures for argument defaults Replace with `None`; initialize within function (B006)
Additional comments not posted (6)
deepmd/dpmodel/fitting/ener_fitting.py (2)
`72-72`: **Proper integration of `seed` parameter.** The `seed` parameter has been correctly added to the `__init__` method and passed to the superclass constructor, aligning with the PR objectives. --- `47-47`: **Refactor mutable default argument.** Similar to the previous comment, mutable default values should be avoided. This applies to the `trainable` parameter as well. ```diff - trainable: Optional[List[bool]] = None, + trainable: Optional[List[bool]] = None, ... + if trainable is None: + trainable = [True] * len(neuron) # Assuming that the length of neuron list is the intended size ``` > Likely invalid or redundant comment.
Tools
Ruff
47-47: Do not use mutable data structures for argument defaults Replace with `None`; initialize within function (B006)
deepmd/dpmodel/fitting/dos_fitting.py (1)
`71-71`: **Proper integration of `seed` parameter.** The `seed` parameter has been correctly added to the `__init__` method and passed to the superclass constructor, aligning with the PR objectives.
deepmd/dpmodel/fitting/dipole_fitting.py (1)
`144-144`: **Proper integration of `seed` parameter and handling of `old_impl`.** The `seed` parameter has been correctly added and the `old_impl` flag has been set to `False` as part of the initialization. This aligns with the PR objectives and the changes are properly integrated.
deepmd/dpmodel/fitting/invar_fitting.py (1)
`138-138`: **Proper integration of `seed` parameter.** The `seed` parameter has been correctly added to the `__init__` method and passed to the superclass constructor, aligning with the PR objectives.
deepmd/dpmodel/fitting/polarizability_fitting.py (1)
`168-168`: **Proper integration of `seed` parameter.** The `seed` parameter has been correctly added to the `__init__` method and passed to the superclass constructor, aligning with the PR objectives.
--- 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](https://twitter.com/intent/tweet?text=I%20just%20used%20%40coderabbitai%20for%20my%20code%20review%2C%20and%20it%27s%20fantastic%21%20It%27s%20free%20for%20OSS%20and%20offers%20a%20free%20trial%20for%20the%20proprietary%20code.%20Check%20it%20out%3A&url=https%3A//coderabbit.ai) - [Mastodon](https://mastodon.social/share?text=I%20just%20used%20%40coderabbitai%20for%20my%20code%20review%2C%20and%20it%27s%20fantastic%21%20It%27s%20free%20for%20OSS%20and%20offers%20a%20free%20trial%20for%20the%20proprietary%20code.%20Check%20it%20out%3A%20https%3A%2F%2Fcoderabbit.ai) - [Reddit](https://www.reddit.com/submit?title=Great%20tool%20for%20code%20review%20-%20CodeRabbit&text=I%20just%20used%20CodeRabbit%20for%20my%20code%20review%2C%20and%20it%27s%20fantastic%21%20It%27s%20free%20for%20OSS%20and%20offers%20a%20free%20trial%20for%20proprietary%20code.%20Check%20it%20out%3A%20https%3A//coderabbit.ai) - [LinkedIn](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fcoderabbit.ai&mini=true&title=Great%20tool%20for%20code%20review%20-%20CodeRabbit&summary=I%20just%20used%20CodeRabbit%20for%20my%20code%20review%2C%20and%20it%27s%20fantastic%21%20It%27s%20free%20for%20OSS%20and%20offers%20a%20free%20trial%20for%20proprietary%20code)
Tips ### Chat There are 3 ways to chat with [CodeRabbit](https://coderabbit.ai): - Review comments: Directly reply to a review comment made by CodeRabbit. Example: - `I pushed a fix in commit .` - `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 show all the console.log statements in this repository.` - `@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 as 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. Additionally, you can add `@coderabbitai ignore` anywhere in the PR description to prevent this PR from being reviewed. ### CodeRabbit Configration 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](https://docs.coderabbit.ai/guides/configure-coderabbit) 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](https://coderabbit.ai/docs) for detailed information on how to use CodeRabbit. - Join our [Discord Community](https://discord.com/invite/GsXnASn26c) to get help, request features, and share feedback. - Follow us on [X/Twitter](https://twitter.com/coderabbitai) for updates and announcements.
codecov[bot] commented 1 week ago

Codecov Report

All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 82.72%. Comparing base (17cdcb0) to head (6d303ee).

Additional details and impacted files ```diff @@ Coverage Diff @@ ## devel #3916 +/- ## ========================================== - Coverage 82.72% 82.72% -0.01% ========================================== Files 519 519 Lines 50515 50516 +1 Branches 3015 3016 +1 ========================================== - Hits 41791 41789 -2 - Misses 7788 7791 +3 Partials 936 936 ```

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.