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Reproducible Training

Same seed, same model, same data — same number, every time.

Key Insight​

Full reproducibility requires more than setting a random seed. You also need to enable deterministic algorithms in PyTorch (via torch.use_deterministic_algorithms(True)), set seeds for Python, NumPy, and CUDA, and control data order with a fixed DataLoader seed.

Why This Matters​

When a training run gives unexpected results, reproducibility lets you bisect the problem: run it twice, compare the outputs, and confirm whether the behavior is deterministic. Without it, debugging is guesswork.