TL;DR: I was three days into a 72-hour pre-training run on a molecular property prediction task when I checked the loss curves and realized something was deeply wrong — not with my hyperparameters, but with my entire approach. My Transformer was burning A100 time learning that atoms bo

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What's in this article

The Problem: Pre-Training Is Eating Your GPU Budget

What Geometric Deep Learning Actually Gives You (Practically Speaking)

Setting Up PyTorch Geometric Without Breaking Your Environment

Building Your First Graph-Structured Model That Skips the Pre-Training Grind

Replacing the Pre-Training Phase: What the Workflow Looks Like in Practice

The 3 Things That Surprised Me After Switching

When GDL Doesn't Help and You Still Need Pre-Training

Quick Reference: PyG vs.…