sudoku_train.ipynb

{
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   "id": "1b6b69c5-aa11-48e3-a194-a611d8d64f46",
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   "source": [
    "import logging\r\n",
    "import torch\r\n",
    "import pandas as pd\r\n",
    "from torch.utils.tensorboard import SummaryWriter\r\n",
    "from unet_module import UNET\r\n",
    "from SudokuDataset import SudokuDataset\r\n",
    "import sys\r\n",
    "from unet_master import train_net\r\n",
    "\r\n",
    "\r\n",
    "class objectview(object):\r\n",
    "    def __init__(self, d):\r\n",
    "        self.__dict__ = d\r\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dd0d89c0-ded0-468e-9754-87fc82294745",
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     "source_hidden": false
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   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO: Using device cuda\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "Epoch 1/10:   0%|          | 0/2673000 [00:00<?, ?img/s]"
     ]
    }
   ],
   "source": [
    "    logging.basicConfig(level=logging.INFO, format='%(levelname)s: %(message)s')\r\n",
    "    device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\r\n",
    "    logging.info(f'Using device {device}')\r\n",
    "    writer = SummaryWriter('runs/unet_testing_1')\r\n",
    "\r\n",
    "    args = objectview({\r\n",
    "        'epochs': 10,\r\n",
    "        'batch_size': 256,\r\n",
    "        'lr': 1e-5,\r\n",
    "        'val': 1,\r\n",
    "        'amp': True,\r\n",
    "    })\r\n",
    "\r\n",
    "    model = UNET(in_channels=10, out_channels=9)\r\n",
    "    data = pd.read_csv('sudoku-3m.csv', sep=',')\r\n",
    "\r\n",
    "\r\n",
    "\r\n",
    "    dataset = SudokuDataset(data)\r\n",
    "\r\n",
    "\r\n",
    "    model.to(device=device)\r\n",
    "    try:\r\n",
    "        train_net(net=model,\r\n",
    "                  dataset=dataset,\r\n",
    "                  epochs=args.epochs,\r\n",
    "                  batch_size=args.batch_size,\r\n",
    "                  learning_rate=args.lr,\r\n",
    "                  device=device,\r\n",
    "                  writer=writer,\r\n",
    "                  val_percent=args.val / 100,\r\n",
    "                  amp=args.amp)\r\n",
    "    except KeyboardInterrupt:\r\n",
    "        torch.save(model.state_dict(), 'INTERRUPTED.pth')\r\n",
    "        logging.info('Saved interrupt')\r\n",
    "        sys.exit(0)\r\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3e2356da-5b5a-4f62-ae9d-60122356a2db",
   "metadata": {
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     "source_hidden": false
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   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting kaggle\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Downloading kaggle-1.5.12.tar.gz (58 kB)\r\n",
      "\u001b[?25l\r",
      "\u001b[K     |█████▋                          | 10 kB 30.4 MB/s eta 0:00:01\r",
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      "\u001b[K     |████████████████▊               | 30 kB 33.7 MB/s eta 0:00:01\r",
      "\u001b[K     |██████████████████████▎         | 40 kB 20.7 MB/s eta 0:00:01\r",
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      "\u001b[K     |████████████████████████████████| 58 kB 22.1 MB/s \r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[?25hRequirement already satisfied: six>=1.10 in /opt/conda/lib/python3.8/site-packages (from kaggle) (1.16.0)\r\n",
      "Requirement already satisfied: certifi in /opt/conda/lib/python3.8/site-packages (from kaggle) (2021.10.8)\r\n",
      "Requirement already satisfied: python-dateutil in /opt/conda/lib/python3.8/site-packages (from kaggle) (2.8.2)\r\n",
      "Requirement already satisfied: requests in /opt/conda/lib/python3.8/site-packages (from kaggle) (2.26.0)\r\n",
      "Requirement already satisfied: tqdm in /opt/conda/lib/python3.8/site-packages (from kaggle) (4.62.3)\r\n",
      "Requirement already satisfied: python-slugify in /opt/conda/lib/python3.8/site-packages (from kaggle) (5.0.2)\r\n",
      "Requirement already satisfied: urllib3 in /opt/conda/lib/python3.8/site-packages (from kaggle) (1.26.7)\r\n",
      "Requirement already satisfied: text-unidecode>=1.3 in /opt/conda/lib/python3.8/site-packages (from python-slugify->kaggle) (1.3)\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: charset-normalizer~=2.0.0 in /opt/conda/lib/python3.8/site-packages (from requests->kaggle) (2.0.9)\r\n",
      "Requirement already satisfied: idna<4,>=2.5 in /opt/conda/lib/python3.8/site-packages (from requests->kaggle) (3.1)\r\n",
      "Building wheels for collected packages: kaggle\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Building wheel for kaggle (setup.py) ... \u001b[?25l-"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\b \b\\\b \bdone\r\n",
      "\u001b[?25h  Created wheel for kaggle: filename=kaggle-1.5.12-py3-none-any.whl size=73052 sha256=10effdbf85b09cc3b493bb91fec7ba2eff3edd257c87378937e3fe1fe730e14d\r\n",
      "  Stored in directory: /tmp/pip-ephem-wheel-cache-et1suu3_/wheels/29/da/11/144cc25aebdaeb4931b231e25fd34b394e6a5725cbb2f50106\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Successfully built kaggle\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Installing collected packages: kaggle\r\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Successfully installed kaggle-1.5.12\r\n",
      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\r\n"
     ]
    }
   ],
   "source": [
    "!pip install kaggle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2aba8790-2509-473c-906e-782d409ea9ab",
   "metadata": {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading 3-million-sudoku-puzzles-with-ratings.zip to /notebooks\r\n",
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     ]
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      " 81%|████████████████████████████████▎       | 167M/207M [00:07<00:01, 23.8MB/s]"
     ]
    },
    {
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      "\r",
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      "\r",
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     ]
    },
    {
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      "\r",
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    },
    {
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      "\r",
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     ]
    },
    {
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      "\r",
      " 92%|████████████████████████████████████▉   | 191M/207M [00:09<00:00, 23.8MB/s]"
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      " 94%|█████████████████████████████████████▍  | 194M/207M [00:09<00:00, 23.8MB/s]"
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    {
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     "text": [
      "\r",
      " 95%|██████████████████████████████████████  | 197M/207M [00:09<00:00, 23.7MB/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 97%|██████████████████████████████████████▋ | 200M/207M [00:09<00:00, 23.9MB/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      " 98%|███████████████████████████████████████▏| 203M/207M [00:09<00:00, 23.9MB/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r",
      "100%|███████████████████████████████████████▊| 206M/207M [00:09<00:00, 23.9MB/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\r\n",
      "\r",
      "100%|████████████████████████████████████████| 207M/207M [00:09<00:00, 22.2MB/s]\r\n"
     ]
    }
   ],
   "source": [
    "!KAGGLE_USERNAME=k5rovski KAGGLE_KEY=89b46e4c1db01fa6d45d5d15fb4a47e9 kaggle datasets download -d radcliffe/3-million-sudoku-puzzles-with-ratings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "37ee7c6d-d4bb-4e06-89f1-983eaafd4038",
   "metadata": {
    "collapsed": false,
    "gradient": {
     "editing": false,
     "execution_count": 18,
     "id": "37ee7c6d-d4bb-4e06-89f1-983eaafd4038",
     "kernelId": "d331b851-182b-40aa-9975-c9dd2cc4fde4",
     "source_hidden": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Archive:  3-million-sudoku-puzzles-with-ratings.zip\r\n",
      "replace sudoku-3m.csv? [y]es, [n]o, [A]ll, [N]one, [r]ename: "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "^C\r\n"
     ]
    }
   ],
   "source": [
    "!unzip 3-million-sudoku-puzzles-with-ratings.zip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "018f7484-e7e1-43a9-b5fe-af821c8953f2",
   "metadata": {
    "collapsed": false,
    "gradient": {
     "editing": false,
     "id": "018f7484-e7e1-43a9-b5fe-af821c8953f2",
     "kernelId": "d331b851-182b-40aa-9975-c9dd2cc4fde4",
     "source_hidden": false
    }
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {},
 "nbformat": 4,
 "nbformat_minor": 5
}