#cudnn

Identical PyTorch training runs give different results: seeds, cuDNN and CUBLAS_WORKSPACE_CONFIG

Two training runs with the same seed and data ended with validation accuracy 0.3 points apart, enough to flip a model comparison. Enabling deterministic algorithms then crashed with a CuBLAS error. Seeding every RNG, DataLoader workers, cuDNN flags and CUBLAS_WORKSPACE_CONFIG made runs repeatable.