On RDNA 4 (gfx1200/gfx1201) and other ROCm GPUs, exhausting VRAM can cause a HIP driver hang that freezes the entire system rather than raising a recoverable Python exception. Two-part fix: - set_per_process_memory_fraction(0.90) caps the HIP/CUDA allocator at 90% of VRAM so PyTorch raises OutOfMemoryError before hitting the hardware limit, keeping the driver alive and the system responsive - top-level exception handler detects OOM errors by type and message and surfaces a clear actionable message to the UI (reduce max_seq_length, enable gradient_checkpointing, lower batch size) instead of the raw CUDA/HIP error string |
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| data_recipe | ||
| export | ||
| inference | ||
| training | ||
| __init__.py | ||
| tool_healing.py | ||