torch-shape-validator
Add tensor shape validation and documentation to PyTorch code. This skill should be used when working with PyTorch models to ensure tensor shapes are correct and well-documented with inline comments.
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已收录技能
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Add tensor shape validation and documentation to PyTorch code. This skill should be used when working with PyTorch models to ensure tensor shapes are correct and well-documented with inline comments.
Add comprehensive type hints to Python functions and methods, including PyTorch tensor types. This skill should be used when improving code quality through static type checking or when preparing code for mypy v...
Convert docstrings to NumPy/Sphinx style with proper Parameters, Returns, and Examples sections. This skill should be used when improving documentation quality across Python modules.
Extract classes, functions, or code blocks from large modules into separate files. This skill should be used during refactoring to break up monolithic files while maintaining import compatibility and test cover...
Review code against PRISM target architecture patterns from REFACTORING_DESIGN_DOCUMENT.md. This skill should be used during refactoring to ensure new Runner and Trainer classes follow AbstractRunner/AbstractTr...
Update import statements across the codebase when modules are moved or renamed. This skill should be used after refactoring operations to ensure all imports remain functional and properly organized.
Generate pytest unit tests for Python functions and classes with fixtures, parametrization, and edge cases. This skill should be used when creating test coverage for modules, especially during refactoring to en...
Create well-formatted git commit messages following conventional commits standard. This skill should be used after completing coding tasks to create clear, descriptive commit messages that accurately reflect ch...
Identify and remove unused code, commented blocks, unreachable code, and unused imports. This skill should be used during Phase 1 cleanup tasks to improve codebase maintainability.
Validate optical physics parameters including Fresnel numbers, diffraction regimes, and resolution limits. This skill should be used when configuring Telescope, Microscope, or Camera instruments to ensure physi...
Detect and fix memory leaks in Python and PyTorch code, especially matplotlib figures and unreleased tensors. This skill should be used during Phase 4 performance optimization when memory usage grows over time.
Handle complex-valued tensors in PyTorch for astronomical imaging applications. This skill should be used when working with Fourier transforms, phase/amplitude representations, and complex arithmetic in PRISM.
Format Python code using black, ruff, and isort to ensure consistent style. This skill should be used before committing code to maintain code quality standards and pass CI/CD checks.
Convert Python loops to vectorized PyTorch tensor operations for performance. This skill should be used when optimizing computational bottlenecks in PyTorch code during Phase 4 performance optimization.
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