fix(pt): fix seed in dpmodel fitting #3916
Conversation
WalkthroughWalkthroughThe recent updates across various files in the Changes
Recent review detailsConfiguration used: CodeRabbit UI Files selected for processing (5)
Additional context usedRuff
Additional comments not posted (6)
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? TipsChatThere are 3 ways to chat with CodeRabbit:
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)
Additionally, you can add CodeRabbit Configration File (
|
![coderabbitai[bot]](https://avatars.githubusercontent.com/in/347564?s=60&v=4){kind=small}
There was a problem hiding this comment.
Actionable comments posted: 2
Outside diff range and nitpick comments (7)
deepmd/dpmodel/fitting/ener_fitting.py (1)
Line range hint
33-33: Refactor mutable default argument.It's recommended not to use mutable default values for function arguments as they can lead to unexpected behaviors. Use
Noneas the default and initialize within the function if necessary.- neuron: List[int] = [120, 120, 120], + neuron: Optional[List[int]] = None, ... + if neuron is None: + neuron = [120, 120, 120]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)
Line range hint
36-36: Refactor mutable default argument.Using mutable default values, especially numpy arrays, can lead to bugs. Initialize
bias_doswithin the function.- bias_dos: Optional[np.ndarray] = None, + bias_dos: Optional[np.ndarray] = None, ... + if bias_dos is None: + bias_dos = np.zeros((ntypes, numb_dos), dtype=DEFAULT_PRECISION)Tools
Ruff
46-46: Do not use mutable data structures for argument defaults
Replace with
None; initialize within function(B006)
deepmd/dpmodel/fitting/dipole_fitting.py (2)
Line range hint
93-93: Refactor mutable default argument.Mutable default values for function arguments should be avoided. Use
Noneas the default and initialize within the function if necessary.- neuron: List[int] = [120, 120, 120], + neuron: Optional[List[int]] = None, ... + if neuron is None: + neuron = [120, 120, 120]
Line range hint
106-106: Refactor mutable default argument.Similar to the previous comment, mutable default values should be avoided. This applies to the
trainableparameter as well.- 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 sizedeepmd/dpmodel/fitting/invar_fitting.py (1)
Line range hint
121-121: Refactor mutable default argument.It's recommended not to use mutable default values for function arguments as they can lead to unexpected behaviors. Use
Noneas the default and initialize within the function if necessary.- neuron: List[int] = [120, 120, 120], + neuron: Optional[List[int]] = None, ... + if neuron is None: + neuron = [120, 120, 120]deepmd/dpmodel/fitting/polarizability_fitting.py (2)
Line range hint
98-98: Refactor mutable default argument.Using mutable default values, especially numpy arrays, can lead to bugs. Initialize
scalewithin the function.- scale: Optional[List[float]] = None, + scale: Optional[List[float]] = None, ... + if scale is None: + scale = [1.0] * ntypes # Assuming ntypes is the intended size
Line range hint
111-111: Refactor mutable default argument.The
trainableparameter should not use a mutable default value. Initialize it within the function.- trainable: Optional[List[bool]] = None, + trainable: Optional[List[bool]] = None, ... + if trainable is None: + trainable = [True] * len(neuron) # Assuming the length of neuron list is the intended size
Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ 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 ☔ View full report in Codecov by Sentry. |
github-merge-queue
bot
removed this pull request from the merge queue due to failed status checks
<!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit - **New Features** - Introduced a new optional `seed` parameter across various fitting modules to enhance customization and reproducibility of model fitting processes. <!-- end of auto-generated comment: release notes by coderabbit.ai -->
Summary by CodeRabbit
seedparameter across various fitting modules to enhance customization and reproducibility of model fitting processes.