![[P] Zero-code runtime visibility for PyTorch training](https://preview.redd.it/kfjsajv7h7qg1.png?width=140&height=77&auto=webp&s=c3f873d530a7c1c993c600d3c5b0d60985afbead) | I added a zero-code mode to TraceML (oss) : It gives a live terminal view of system + process metrics during PyTorch training, with normal stdout/stderr still visible. Built for the case where a run feels slow and you want a quick first-pass view before adding instrumentation or reaching for a heavier profiler. Current limitation: not for multi-node launches yet. [link] [comments] |
[P] Zero-code runtime visibility for PyTorch training
Reddit r/MachineLearning / 3/20/2026
📰 NewsDeveloper Stack & InfrastructureTools & Practical Usage
Key Points
- TraceML adds a zero-code mode that enables a live runtime view during PyTorch training via the command traceml watch train.py.
- It displays a live terminal view of system and process metrics while stdout/stderr remains visible, enabling quick diagnostics without extra instrumentation.
- The feature is aimed at fast feedback when a training run feels slow, serving as a first-pass check before adding heavier instrumentation or a full profiler.
- A current limitation is that multi-node launches are not yet supported; the project repository is at https://github.com/traceopt-ai/traceml/.
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