model-equivariance-auditor
CommunityVerify your model's symmetry guarantees.
Authorlyndonkl
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill ensures that your implemented neural network models correctly adhere to their intended symmetries, preventing subtle bugs that can lead to poor training and inconsistent results.
Core Features & Use Cases
- Equivariance Verification: Run end-to-end tests to confirm if your model respects specified symmetries (e.g., rotation, translation).
- Layer-wise Debugging: Isolate and identify specific layers that violate equivariance properties.
- Gradient Symmetry Check: Verify that the model's gradients also respect the intended symmetries, crucial for stable training.
- Use Case: After implementing a new 3D convolutional neural network for molecular property prediction, use this Skill to rigorously test if its predictions change predictably when the input molecule is rotated.
Quick Start
Use the model-equivariance-auditor skill to run end-to-end equivariance tests on your PyTorch model.
Dependency Matrix
Required Modules
torchnumpyscipy
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: model-equivariance-auditor Download link: https://github.com/lyndonkl/claude/archive/main.zip#model-equivariance-auditor Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
Agent Skills Search Helper
Install a tiny helper to your Agent, search and equip skill from 223,000+ vetted skills library on demand.