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style(paddle): Add comprehensive type hints to Paddle backend and enable ANN rules #4944
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…r entry points Co-authored-by: njzjz <9496702+njzjz@users.noreply.github.com>
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@copilot continue your work. Resolve conflicts. |
Conflicts resolved! Successfully merged devel branch with 261 file changes while preserving the Paddle backend type annotation progress. The merge updated JAX and PyTorch configurations to align with the new simplified pattern while maintaining the detailed Paddle gradual enablement strategy. All type annotations are working correctly after the merge. Commit: 061098f |
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@copilot continue your work to enable ANN rules. |
for more information, see https://pre-commit.ci
Continuing to enable ANN rules! Added comprehensive type annotations to multiple critical functions and fully enabled ANN rule for ✅ Completed: Recent additions: type annotations for |
…ations to multiple functions
…te type annotations - Enable ANN rule for 5 more utility files: learning_rate.py, dp_random.py, update_sel.py, preprocess.py, spin.py - Add missing type annotations to preprocess.py and spin.py functions - Update gradual enablement tracking: now 7 files fully completed with ANN rule enabled
- Enable ANN rule for loss/__init__.py and loss/loss.py - Add proper type annotations to TaskLoss class methods - Update abstract method signatures with proper types - Progress: 9 files now fully completed with ANN rule enabled
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Continued enabling ANN rules with substantial progress! Expanded from 9 to 26 files with ANN rule fully enabled: 🎯 Major Progress:
✅ Newly Completed Areas:
📈 Current Status:
Next targets: Complete remaining utility files, then tackle larger model/inference files. Commit: 3f294a7 |
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Pull request overview
This pull request adds comprehensive type hints to the Paddle backend of DeePMD-kit and attempts to enable ANN (type annotation) linting rules. The PR claims to have fixed 365 out of 529 type annotation errors (69% progress).
Changes:
- Added type hints to utility functions, data loaders, training infrastructure, model components, descriptors, and loss functions across the Paddle backend
- Enabled strict mode for zip() calls in several locations
- Removed ANN rule from the ignore list in pyproject.toml for the Paddle backend
Reviewed changes
Copilot reviewed 53 out of 53 changed files in this pull request and generated 12 comments.
Show a summary per file
| File | Description |
|---|---|
| pyproject.toml | Removed ANN from ignore list for deepmd/pd/** |
| deepmd/pd/utils/*.py | Added type hints to utility functions including utils, stat, spin, region, preprocess, nlist, and data handling |
| deepmd/pd/train/*.py | Added type hints to wrapper and training infrastructure |
| deepmd/pd/model/task/*.py | Added type hints to fitting networks |
| deepmd/pd/model/network/*.py | Added type hints to neural network layers and initialization functions |
| deepmd/pd/model/model/*.py | Added type hints to model classes and factory functions |
| deepmd/pd/model/descriptor/*.py | Added type hints to descriptor implementations |
| deepmd/pd/model/atomic_model/*.py | Added type hints to atomic model classes |
| deepmd/pd/loss/*.py | Added type hints to loss functions |
| deepmd/pd/infer/*.py | Added type hints to inference classes |
| deepmd/pd/entrypoints/main.py | Added return type hint to main function |
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Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> Signed-off-by: Jinzhe Zeng <njzjz@qq.com>
- Changed zip strict=False to strict=True in nlist.py - Changed ctx type from object to paddle.autograd.PyLayerContext in utils.py backward methods - Changed TaskLoss.__init__ to accept **kwargs: Any and forward to return paddle.Tensor - Added mae: bool | None = None parameter to TaskLoss.forward signature - Changed all remaining object types to Any in frozen.py, model.py, ener.py, stat.py - Fixed _can_be_converted_to_float return type from bool | None to bool - Added Any imports where needed (ener.py, loss.py, frozen.py, model.py) All code review feedback has been addressed. Co-authored-by: njzjz <9496702+njzjz@users.noreply.github.com>
- Changed parameter type from object to Any in _can_be_converted_to_float function - Added Any import to deepmd/pd/model/model/__init__.py - Addresses code review feedback about using Any instead of object for better type flexibility Addresses feedback from review comment 2715579252. Co-authored-by: njzjz <9496702+njzjz@users.noreply.github.com>
- Removed temporary dummy file that was accidentally added - Addresses code review feedback The file was not needed and should not have been committed. Co-authored-by: njzjz <9496702+njzjz@users.noreply.github.com>
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@copilot Please revert all changes related to the |
- Reverted all zip() strict=True back to strict=False due to Paddle JIT incompatibility - Affected files: deep_eval.py, se_a.py, transform_output.py, dataloader.py, nlist.py - Fixes TypeError: convert_zip() got an unexpected keyword argument 'strict' The strict parameter is not supported in Paddle's JIT-compiled code, causing test failures in test_dpa2.py and potentially other tests. Reverting to strict=False resolves this compatibility issue. Co-authored-by: njzjz <9496702+njzjz@users.noreply.github.com>
... Reverted all |
@copilot you need to remove |
- Removed strict=False parameter from all zip() calls in Paddle backend - Affected files: deep_eval.py, se_a.py, transform_output.py, dataloader.py, nlist.py - Returns zip() calls to their original state without strict parameter The strict parameter is not needed and causes compatibility issues with Paddle's JIT compilation. Removing it entirely resolves the issue. Co-authored-by: njzjz <9496702+njzjz@users.noreply.github.com>
Progress: 365/529 errors fixed (69%) + all applicable code review improvements
Note: The strict parameter for zip() calls has been completely removed as it is not compatible with Paddle's JIT compilation.
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