p4_2_2__workers_8.ipynb

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      "Tue Dec 12 01:17:39 2023       \n",
      "+---------------------------------------------------------------------------------------+\n",
      "| NVIDIA-SMI 535.104.05             Driver Version: 535.104.05   CUDA Version: 12.2     |\n",
      "|-----------------------------------------+----------------------+----------------------+\n",
      "| GPU  Name                 Persistence-M | Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
      "| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |\n",
      "|                                         |                      |               MIG M. |\n",
      "|=========================================+======================+======================|\n",
      "|   0  Tesla T4                       Off | 00000000:3B:00.0 Off |                    0 |\n",
      "| N/A   47C    P0              28W /  70W |      2MiB / 15360MiB |      6%      Default |\n",
      "|                                         |                      |                  N/A |\n",
      "+-----------------------------------------+----------------------+----------------------+\n",
      "                                                                                         \n",
      "+---------------------------------------------------------------------------------------+\n",
      "| Processes:                                                                            |\n",
      "|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |\n",
      "|        ID   ID                                                             Usage      |\n",
      "|=======================================================================================|\n",
      "|  No running processes found                                                           |\n",
      "+---------------------------------------------------------------------------------------+\n"
     ]
    }
   ],
   "source": [
    "!nvidia-smi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c944415a-0e66-4846-976f-483402a815fd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU:\n",
      "  CPU: Intel(R) Xeon(R) Gold 6240 CPU @ 2.60GHz\n",
      "  Architecture: X86_64\n",
      "CUDA available\n",
      "/home/zhou.he1/.local/lib/python3.9/site-packages/torch/utils/data/dataloader.py:557: UserWarning: This DataLoader will create 8 worker processes in total. Our suggested max number of worker in current system is 4, which is smaller than what this DataLoader is going to create. Please be aware that excessive worker creation might get DataLoader running slow or even freeze, lower the worker number to avoid potential slowness/freeze if necessary.\n",
      "  warnings.warn(_create_warning_msg(\n",
      "Running on 1 GPU with 8 processes----------------------------\n",
      "Epoch [1/5]------------------------------------------------------------------------\n",
      "| Train Loss: 2.6422 | Train Acc: 0.3406 | Val Loss: 2.2021, Val Acc: 0.4074\n",
      "| Elapsed Time: 224.6506 s | Max GPU Memory Alloc: 1960.8457 MB\n",
      "Epoch [2/5]------------------------------------------------------------------------\n",
      "| Train Loss: 2.0209 | Train Acc: 0.4719 | Val Loss: 1.7971, Val Acc: 0.5216\n",
      "| Elapsed Time: 222.2073 s | Max GPU Memory Alloc: 1960.8472 MB\n",
      "Epoch [3/5]------------------------------------------------------------------------\n",
      "| Train Loss: 1.8274 | Train Acc: 0.5141 | Val Loss: 1.6481, Val Acc: 0.5436\n",
      "| Elapsed Time: 222.1483 s | Max GPU Memory Alloc: 1960.8481 MB\n",
      "Epoch [4/5]------------------------------------------------------------------------\n",
      "| Train Loss: 1.2209 | Train Acc: 0.6451 | Val Loss: 1.2316, Val Acc: 0.6412\n",
      "| Elapsed Time: 222.4511 s | Max GPU Memory Alloc: 1960.8491 MB\n",
      "Epoch [5/5]------------------------------------------------------------------------\n",
      "| Train Loss: 1.2085 | Train Acc: 0.6483 | Val Loss: 1.2196, Val Acc: 0.6451\n",
      "| Elapsed Time: 221.2881 s | Max GPU Memory Alloc: 1960.8501 MB\n",
      "\n",
      "total_time: 1113.5023527145386\n",
      "best_valid_acc: 0.6450603232415206\n",
      "train_loss: [2.642194299386622, 2.0208991153471203, 1.8274293835346813, 1.2208642493566932, 1.2085188906161841]\n",
      "train_acc: [tensor(0.3406, device='cuda:0', dtype=torch.float64), tensor(0.4719, device='cuda:0', dtype=torch.float64), tensor(0.5141, device='cuda:0', dtype=torch.float64), tensor(0.6451, device='cuda:0', dtype=torch.float64), tensor(0.6483, device='cuda:0', dtype=torch.float64)]\n",
      "valid_loss: [2.2020997007099936, 1.797089404257126, 1.64809937371145, 1.231584107797129, 1.2195817719972841]\n",
      "valid_acc: [tensor(0.4074, device='cuda:0', dtype=torch.float64), tensor(0.5216, device='cuda:0', dtype=torch.float64), tensor(0.5436, device='cuda:0', dtype=torch.float64), tensor(0.6412, device='cuda:0', dtype=torch.float64), tensor(0.6451, device='cuda:0', dtype=torch.float64)]\n",
      "epo_elapsed_time: [224.65064334869385, 222.20726990699768, 222.14829015731812, 222.45111727714539, 221.28811836242676]\n",
      "max_alloc: [1960.845703125, 1960.84716796875, 1960.84814453125, 1960.84912109375, 1960.85009765625]\n",
      "Figure(1200x500)\n",
      "Figure(7200x3000)\n"
     ]
    }
   ],
   "source": [
    "!python p4_2_2__process_main.py --num_workers 8 --num_epochs 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "657657d4-e576-4885-bf2d-e73d3e177174",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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