Скачать или смотреть Mastering PyTorch Hooks: From Basics to Big Model Inference

Want X-ray vision into any PyTorch model, without touching its source code? In this beginner-friendly deep-dive you’ll master the four hook types (pre-forward, forward, backward, tensor) and use them to:
• Introduction to PyTorch Hooks (00:00)
• Inspect activations & gradients on the fly (01:25)
• Catch shape mismatches before they crash training (04:17)
• Build a mini-Accelerate for big-model inference (21:10)
• Cut GPU memory by 30 % with smart caching hooks (27:25)
Follow the step-by-step notebook to add hooks in sub-10 lines of code, then apply them to real debugging tasks, model interpretability, and multi-GPU training. Perfect for ML engineers who need to profile, patch, or scale PyTorch code quickly.

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