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Pepijn
1842100402
The dashboard expects per-phase timings (forward_s, backward_s, optimizer_s) in step_timing_summary.json, but only total_update_s and dataloading_s were collected — leaving every chart except dataloading empty. Add a lightweight TrainingProfiler.section(name) context manager that times a region with torch.cuda.synchronize before and after (so GPU work is captured, not just the kernel-launch latency) and accumulates per-section samples into step_timing_summary.json. Wrap forward, backward (incl. grad clip), and optimizer (incl. zero_grad and scheduler.step) in update_policy with these sections. When profiling is off (profiler=None) the wrappers become no-ops, so training performance is unchanged outside CI. Made-with: Cursor