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Runtime error
| import torch | |
| CRITICAL_RESERVED_MB = 3500 | |
| def check_vram_usage() -> None: | |
| if not torch.cuda.is_available(): | |
| print("❌ CUDA aktif değil, VRAM ölçülemez.") | |
| return | |
| allocated = torch.cuda.memory_allocated(0) / (1024 ** 2) | |
| reserved = torch.cuda.memory_reserved(0) / (1024 ** 2) | |
| total_capacity = torch.cuda.get_device_properties(0).total_memory / (1024 ** 2) | |
| free_estimate = total_capacity - reserved | |
| print("=" * 40) | |
| print(f"📟 GPU: {torch.cuda.get_device_name(0)}") | |
| print(f"📊 Toplam VRAM: {total_capacity:.2f} MB") | |
| print(f"🔥 Şu An Ayrılan (Allocated): {allocated:.2f} MB") | |
| print(f"🛡️ Rezerve Edilen (Reserved): {reserved:.2f} MB") | |
| print(f"🆓 Boş Alan (Tahmini): {free_estimate:.2f} MB") | |
| if reserved >= CRITICAL_RESERVED_MB: | |
| print(f"⚠️ Kritik Eşik Aşıldı: Reserved >= {CRITICAL_RESERVED_MB} MB") | |
| else: | |
| print(f"✅ Güvenli Bölge: Reserved < {CRITICAL_RESERVED_MB} MB") | |
| print("=" * 40) | |
| if __name__ == "__main__": | |
| check_vram_usage() | |