Profile PyTorch attention to slash transformer GPU costs
The Hugging Face blog walks you through profiling PyTorch's attention layers with the built‑in Profiler, exposing costly matmuls, scaling, masking, and softmax steps. By comparing naive, in‑place, and SDPA implementations, you can pinpoint bottlenecks and choose the fastest kernel for transformer models, shaving GPU time and cost.