pytorch-patterns
PyTorch Development Patterns
Idiomatic PyTorch patterns and best practices for building robust, efficient, and reproducible deep learning applications.
When to Activate
- Writing new PyTorch models or training scripts
- Reviewing deep learning code
- Debugging training loops or data pipelines
- Optimizing GPU memory usage or training speed
- Setting up reproducible experiments
Core Principles
1. Device-Agnostic Code
Always write code that works on both CPU and GPU without hardcoding devices.
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