Nilm_graph_embedding.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "name": "Nilm_graph_embedding.ipynb",
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/LeoVogiatzis/GNN_based_NILM/blob/main/Nilm_graph_embedding.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I53hzURMuMom"
      },
      "source": [
        "!pip install torch-scatter torch-sparse torch-cluster torch-spline-conv torch-geometric -f https://data.pyg.org/whl/torch-1.10.0+cu113.html"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import networkx as nx\n",
        "import pandas as pd\n",
        "import torch\n",
        "import torch_geometric\n",
        "from torch_geometric.data import Dataset, Data\n",
        "import numpy as np\n",
        "import os\n",
        "from tqdm import tqdm\n",
        "\n",
        "print(f\"Torch version: {torch.__version__}\")\n",
        "print(f\"Cuda available: {torch.cuda.is_available()}\")\n",
        "print(f\"Torch geometric version: {torch_geometric.__version__}\")\n",
        "\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from torch_geometric.data import Dataset, Data\n",
        "from torch_geometric.transforms import RandomLinkSplit, RandomNodeSplit \n",
        "import torch\n",
        "from torch.nn import Linear\n",
        "from torch_geometric.nn import GCNConv\n",
        "import torch.nn.functional as F\n",
        "import math  \n",
        "from sklearn.manifold import TSNE\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RgvQcTTTSNvU",
        "outputId": "c46d886e-bddf-451b-8261-b02452f708ce"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Torch version: 1.10.0+cu111\n",
            "Cuda available: True\n",
            "Torch geometric version: 2.0.2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oBqm1sx_8yIm",
        "outputId": "405f2876-823a-450e-f7c4-34bb88454d92"
      },
      "source": [
        "print(f\"Torch version: {torch.__version__}\")\n",
        "print(f\"Cuda available: {torch.cuda.is_available()}\")\n",
        "print(f\"Torch geometric version: {torch_geometric.__version__}\")\n"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Torch version: 1.10.0+cu111\n",
            "Cuda available: True\n",
            "Torch geometric version: 2.0.2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "u_6GF0wDlENS"
      },
      "source": [
        "from torch_geometric.nn import Node2Vec\n",
        "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")"
      ],
      "execution_count": 41,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lfyskJ-t3cnI"
      },
      "source": [
        "class NilmDataset(Dataset):\n",
        "    def __init__(self, root, filename, window, sigma, test=False, transform=None, pre_transform=None):\n",
        "        \"\"\"2\n",
        "        root = Where the dataset should be stored. This folder is split\n",
        "        into raw_dir (downloaded dataset) and processed_dir (processed data).\n",
        "        \"\"\"\n",
        "        self.test = test\n",
        "        self.filename = filename\n",
        "        self.window = window\n",
        "        self.sigma = sigma\n",
        "        super(NilmDataset, self).__init__(root, transform, pre_transform)\n",
        "\n",
        "    @property\n",
        "    def raw_file_names(self):\n",
        "        \"\"\" If this file exists in raw_dir, the download is not triggered.\n",
        "            (The download func. is not implemented here)\n",
        "        \"\"\"\n",
        "        return [self.filename]\n",
        "\n",
        "    @property\n",
        "    def processed_file_names(self):\n",
        "        \"\"\" If these files are found in raw_dir, processing is skipped\"\"\"\n",
        "        data = pd.read_csv(self.raw_paths[0]).reset_index()\n",
        "        if self.test:\n",
        "            return [f'data_test_{i}.pt' for i in list(data.index)]\n",
        "        else:\n",
        "            return [f'data_{i}.pt' for i in list(data.index)]\n",
        "\n",
        "    def download(self):\n",
        "        pass\n",
        "\n",
        "    def process(self):\n",
        "        idx = 0\n",
        "        for raw_path in self.raw_paths:\n",
        "            appliance = pd.read_csv(raw_path).reset_index()\n",
        "            main_val = appliance['dishwaser_20'].values  # get only readings\n",
        "            data_vec = main_val\n",
        "            adjacency, drift = self._get_adjacency_info(data_vec)\n",
        "            edge_indices = self._to_edge_index(adjacency)\n",
        "\n",
        "            # node_feats = np.asarray(drift)\n",
        "            # node_feats = node_feats.reshape((-1, 1))\n",
        "            # node_feats = torch.tensor(node_feats, dtype=torch.float)\n",
        "            labels = np.asarray(drift)\n",
        "            labels = torch.tensor(labels, dtype=torch.int64)\n",
        "\n",
        "            data = Data(edge_index=edge_indices, y=labels,\n",
        "                        #  train_mask=[2000], test_mask=[2000]\n",
        "                        )\n",
        "            # data.num_classes = 2\n",
        "\n",
        "            # splitting the data into train, validation and test\n",
        "            X_train, X_test, y_train, y_test = train_test_split(pd.Series(np.asarray([i for i in range(data.num_nodes)], dtype=np.int64)), pd.Series(np.asarray(labels, dtype=np.float32)), test_size=0.30, random_state=42)\n",
        "            \n",
        "            n_nodes = data.num_nodes\n",
        "            \n",
        "            # create train and test masks for data\n",
        "            train_mask = torch.zeros(n_nodes, dtype=torch.bool)\n",
        "            test_mask = torch.zeros(n_nodes, dtype=torch.bool)\n",
        "            train_mask[X_train.index] = True\n",
        "            test_mask[X_test.index] = True\n",
        "            data['train_mask'] = train_mask\n",
        "            data['test_mask'] = test_mask\n",
        "\n",
        "            # self.data, self.slices = self.collate([data])\n",
        "            if self.pre_filter is not None and not self.pre_filter(data):\n",
        "                continue\n",
        "\n",
        "            if self.pre_transform is not None:\n",
        "                data = self.pre_transform(data)\n",
        "\n",
        "            if self.test:\n",
        "                torch.save(data, os.path.join(self.processed_dir, f'data_test_{idx}.pt'))\n",
        "            else:\n",
        "                torch.save(data, os.path.join(self.processed_dir, f'data_{idx}.pt'))\n",
        "            idx += 1\n",
        "\n",
        "    def _get_node_features(self, graph):\n",
        "        \"\"\"\n",
        "        This will return a matrix / 2d array of the shape\n",
        "        [Number of Nodes, Node Feature size]\n",
        "\n",
        "        We could also use torch_geometric.from_networkx to create a Data object\n",
        "        with both adjacency and features, but instead we do it manually here\n",
        "        \"\"\"\n",
        "        all_node_feats = list(nx.get_node_attributes(graph, 'drift').values())\n",
        "\n",
        "        all_node_feats = np.asarray(all_node_feats)\n",
        "        all_node_feats = all_node_feats.reshape((-1, 1))\n",
        "        return torch.tensor(all_node_feats, dtype=torch.float)\n",
        "\n",
        "    def _get_adjacency_info(self, data_vec):\n",
        "        data_aggr = []\n",
        "\n",
        "        for k in range(0, int(np.floor(len(data_vec) / self.window))):\n",
        "            data_aggr.append(np.mean(data_vec[k * self.window:((k + 1) * self.window)]))\n",
        "\n",
        "        if (len(data_vec) % self.window > 0):\n",
        "            data_aggr.append(np.mean(data_vec[int(np.floor(len(data_vec) / self.window)) * self.window:]))\n",
        "        delta_p = [np.round(data_aggr[i + 1] - data_aggr[i], 2) for i in range(0, len(data_aggr) - 1)]\n",
        "        Am = np.zeros((len(delta_p), len(delta_p)))\n",
        "        for i in range(0, Am.shape[0]):\n",
        "            for j in range(0, Am.shape[1]):\n",
        "                Am[i, j] = math.exp(-((delta_p[i] - delta_p[j]) / self.sigma) ** 2)\n",
        "        Am = np.where(Am >= 0.5, 1, 0)\n",
        "        return Am, delta_p\n",
        "\n",
        "    def _to_edge_index(self, adjacency):\n",
        "\n",
        "        edge_indices = []\n",
        "        for i in range(0, adjacency.shape[0]):\n",
        "            for j in range(i, adjacency.shape[0]):\n",
        "                if adjacency[i, j] != 0.0:\n",
        "                    edge_indices += [[i, j], [j, i]]\n",
        "\n",
        "        edge_indices = torch.tensor(edge_indices)\n",
        "        edge_indices = edge_indices.t().to(torch.long).view(2, -1)\n",
        "\n",
        "        return edge_indices\n",
        "\n",
        "    def len(self):\n",
        "        return len(self.processed_file_names)\n",
        "\n",
        "    def get(self, idx):\n",
        "        \"\"\" - Equivalent to __getitem__ in pytorch\n",
        "            - Is not needed for PyG's InMemoryDataset\n",
        "        \"\"\"\n",
        "        if self.test:\n",
        "            data = torch.load(os.path.join(self.processed_dir, f'data_test_{idx}.pt'))\n",
        "        else:\n",
        "            data = torch.load(os.path.join(self.processed_dir, f'data_{idx}.pt'))\n",
        "        return data"
      ],
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QN_-X2CfT87P",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a4235685-929d-4eee-9780-36c589d712f8"
      },
      "source": [
        "dataset = NilmDataset(root='data', filename='dishwasher.csv', window=20, sigma=20)\n",
        "data = dataset[0]\n",
        "# from torch_geometric.datasets import Planetoid\n",
        "# from torch_geometric.transforms import NormalizeFeatures\n",
        "# dataset = Planetoid(root='data/Planetoid', name='Cora', transform=NormalizeFeatures())\n",
        "# data = dataset[0]\n",
        "# print(data.y)\n",
        "data.edge_index"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Processing...\n",
            "/usr/local/lib/python3.7/dist-packages/torch_geometric/data/storage.py:264: UserWarning: Unable to accurately infer 'num_nodes' from the attribute set '{'y', 'edge_index'}'. Please explicitly set 'num_nodes' as an attribute of 'data' to suppress this warning\n",
            "  \" to suppress this warning\")\n",
            "Done!\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[   0,    0,    0,  ..., 3871, 3871, 3871],\n",
              "        [   0,    0,    1,  ..., 3870, 3871, 3871]])"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.train_mask"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XjkJiy9CuH9-",
        "outputId": "0e30ca9d-432b-48dc-d8f6-535398f95e7a"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([False,  True,  True,  ..., False, False, False])"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "7JbTI3jpqvUM"
      },
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xZXe6s9WYdcU"
      },
      "source": [
        "model = Node2Vec(data.edge_index, embedding_dim=128, walk_length=20,\n",
        "                     context_size=10, walks_per_node=10,\n",
        "                     num_negative_samples=1, p=1, q=1, sparse=True).to(device)"
      ],
      "execution_count": 46,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nF5tWnMzhZ1J",
        "outputId": "7d5b8be0-8cd9-4c58-ec25-e32261a0dff9"
      },
      "source": [
        "loader = model.loader(batch_size=128, shuffle=True, num_workers=4)\n",
        "for idx, (pos_rw, neg_rw) in enumerate(loader):\n",
        "    print(idx, pos_rw.shape, neg_rw.shape)\n",
        "idx, (pos_rw, neg_rw) = next(enumerate(loader))"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "1 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "2 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "3 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "4 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "5 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "6 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "7 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "8 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "9 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "10 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "11 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "12 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "13 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "14 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "15 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "16 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "17 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "18 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "19 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "20 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "21 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "22 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "23 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "24 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "25 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "26 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "27 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "28 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "29 torch.Size([14080, 10]) torch.Size([14080, 10])\n",
            "30 torch.Size([3520, 10]) torch.Size([3520, 10])\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LPMlQOD81wN0",
        "outputId": "93e6ac39-d8a6-456f-867a-c1bb9214b63d"
      },
      "source": [
        "(pos_rw.shape, neg_rw.shape)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(torch.Size([14080, 10]), torch.Size([14080, 10]))"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bL9TuUnl16k0",
        "outputId": "2eada3fa-4420-4b2d-b03c-b8f5c9f44ece"
      },
      "source": [
        "pos_rw"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[1285, 1875, 3281,  ..., 2663, 1357,  645],\n",
              "        [2046, 3489, 1894,  ..., 2411, 1832,    3],\n",
              "        [2230,  844,  893,  ..., 1272,  952, 2539],\n",
              "        ...,\n",
              "        [2990, 2543, 2834,  ..., 1927, 1620, 1278],\n",
              "        [2794, 1575, 1910,  ..., 2292, 1791, 3720],\n",
              "        [3142, 1011, 3072,  ..., 1856,   30, 1575]])"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5K9xoJG71-DW",
        "outputId": "10ec103b-3318-434a-c679-d2c32dce87a0"
      },
      "source": [
        "neg_rw"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([[1285, 1330, 2820,  ..., 1923, 2227, 2818],\n",
              "        [2046,  860,  525,  ...,  324, 1381, 3852],\n",
              "        [2230, 3438, 2212,  ..., 2652, 1256, 3392],\n",
              "        ...,\n",
              "        [1190, 2167, 2100,  ..., 1056, 1442,  573],\n",
              "        [1873, 1502, 2730,  ...,  517, 3140, 2251],\n",
              "        [1131, 3095, 3621,  ..., 1160, 3434, 3415]])"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KcKAv_XCgvUt"
      },
      "source": [
        "edge_tuples = [tuple(x) for x in data.edge_index.numpy().transpose()]\n",
        "G = nx.from_edgelist(edge_tuples)\n",
        "pos = nx.spring_layout(G, center=[0.5, 0.5])\n",
        "nx.set_node_attributes(G, pos, 'pos')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 630
        },
        "id": "WNqOYOujhOW2",
        "outputId": "3f1e0a21-fea8-4e9c-f938-885fd207334c"
      },
      "source": [
        "nodelist = next(enumerate(loader))[1][0][0].tolist()\n",
        "walk = nx.path_graph(len(nodelist))\n",
        "nx.set_node_attributes(walk, {idx: pos[node_id] for idx, node_id in enumerate(nodelist)}, 'pos')\n",
        "\n",
        "fig = plt.figure(figsize=(20, 10))\n",
        "ax = fig.add_subplot(1, 2, 1)\n",
        "nx.draw_networkx_nodes(G, \n",
        "                       ax=ax,\n",
        "                       pos=nx.get_node_attributes(G, 'pos'), \n",
        "                       node_size=5,\n",
        "                       alpha=0.3,\n",
        "                       node_color='b')\n",
        "nx.draw(walk, \n",
        "        node_size=40,\n",
        "        node_color='r',\n",
        "        ax=ax,\n",
        "        pos=nx.get_node_attributes(walk, 'pos'), \n",
        "        width=2,\n",
        "        edge_color='r') \n",
        "ax = fig.add_subplot(1, 2, 2)\n",
        "nx.draw(walk, \n",
        "        node_size=40,\n",
        "        node_color='r',\n",
        "        ax=ax,\n",
        "        pos=nx.get_node_attributes(walk, 'pos'), \n",
        "        width=2,\n",
        "        edge_color='r') "
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x720 with 2 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UveH2ZcY2RLw"
      },
      "source": [
        "optimizer = torch.optim.Adam(model.parameters(), lr=0.01, weight_decay=5e-4)\n",
        "\n",
        "def train():\n",
        "    model.train()\n",
        "    total_loss = 0\n",
        "    for pos_rw, neg_rw in tqdm(loader):\n",
        "        optimizer.zero_grad()\n",
        "        loss = model.loss(pos_rw.to(device), neg_rw.to(device))\n",
        "        loss.backward()\n",
        "        # optimizer.step()\n",
        "        total_loss += loss.item()\n",
        "    return total_loss / len(loader)"
      ],
      "execution_count": 48,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9bWUHGa32UXN",
        "outputId": "36e176fb-318a-4172-d1ff-973294e9aa51"
      },
      "source": [
        "data"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Data(edge_index=[2, 14872632], y=[3872], train_mask=[3872], test_mask=[3872])"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7oWkzXoM2YgM",
        "outputId": "fecf5295-c75d-4825-cb75-b4410d10a0d3"
      },
      "source": [
        "data.y.unique()"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "tensor([-775, -770, -353, -209, -183, -157, -131,  -41,  -33,  -30,   -6,   -3,\n",
              "          -2,   -1,    0,    1,    2,    4,   12,  288,  414,  590,  682,  914])"
            ]
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "geedVIlK2eGZ"
      },
      "source": [
        "@torch.no_grad()\n",
        "def test():\n",
        "    model.eval()\n",
        "    z = model()\n",
        "    acc = model.test(z[data.train_mask], data.y[data.train_mask],\n",
        "                     z[data.test_mask], data.y[data.test_mask],\n",
        "                     max_iter=150)\n",
        "    return acc"
      ],
      "execution_count": 54,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zpbvPXky2f03",
        "outputId": "fdfccd86-8857-4124-e049-c1a9b49a22ba"
      },
      "source": [
        "import torch\n",
        "from torch.nn import Linear\n",
        "from torch_geometric.nn import GCNConv\n",
        "import torch.nn.functional as F\n",
        "\n",
        "\n",
        "for epoch in range(1, 201):\n",
        "    loss = train()\n",
        "    acc = test()\n",
        "    print(f'Epoch: {epoch:02d}, Loss: {loss:.4f}, Acc: {acc:.4f}')\n"
      ],
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.26it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 01, Loss: 10.0206, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.28it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 02, Loss: 10.0172, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.12it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 03, Loss: 10.0217, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.98it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 04, Loss: 10.0332, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.96it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 05, Loss: 10.0225, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.50it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 06, Loss: 10.0247, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.93it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 07, Loss: 10.0158, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.63it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 08, Loss: 10.0134, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.85it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 09, Loss: 10.0287, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.74it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 10, Loss: 10.0217, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.28it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 11, Loss: 10.0298, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.71it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 12, Loss: 10.0222, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.18it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 13, Loss: 10.0102, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.77it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 14, Loss: 10.0255, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.22it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 15, Loss: 10.0285, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.58it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 16, Loss: 10.0258, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.57it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 17, Loss: 10.0314, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.44it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 18, Loss: 10.0157, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.75it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 19, Loss: 10.0224, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.27it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 20, Loss: 10.0350, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.13it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 21, Loss: 10.0240, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.29it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 22, Loss: 10.0377, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.29it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 23, Loss: 10.0248, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.32it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 24, Loss: 10.0113, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.54it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 25, Loss: 10.0198, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.48it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 26, Loss: 10.0253, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.15it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 27, Loss: 10.0209, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.18it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 28, Loss: 10.0198, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.45it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 29, Loss: 10.0180, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.42it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 30, Loss: 10.0219, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.37it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 31, Loss: 10.0146, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.13it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 32, Loss: 10.0245, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.75it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 33, Loss: 10.0279, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.61it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 34, Loss: 10.0177, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.10it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 35, Loss: 10.0226, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.14it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 36, Loss: 10.0288, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.10it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 37, Loss: 10.0107, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.72it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 38, Loss: 10.0170, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.66it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 39, Loss: 10.0192, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.33it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 40, Loss: 10.0214, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.45it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 41, Loss: 10.0144, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.22it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 42, Loss: 10.0212, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.91it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 43, Loss: 10.0281, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.23it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 44, Loss: 10.0371, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.61it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 45, Loss: 10.0238, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.39it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 46, Loss: 10.0154, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.58it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 47, Loss: 10.0276, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.16it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 48, Loss: 10.0163, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.43it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 49, Loss: 10.0201, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.92it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 50, Loss: 10.0236, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.63it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 51, Loss: 10.0233, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.13it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 52, Loss: 10.0206, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.13it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 53, Loss: 10.0176, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.36it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 54, Loss: 10.0174, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.92it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 55, Loss: 10.0132, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.92it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 56, Loss: 10.0317, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.65it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 57, Loss: 10.0227, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.88it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 58, Loss: 10.0207, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.05it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 59, Loss: 10.0191, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.75it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 60, Loss: 10.0205, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.60it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 61, Loss: 10.0220, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.91it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 62, Loss: 10.0226, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.73it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 63, Loss: 10.0095, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.20it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 64, Loss: 10.0260, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.73it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 65, Loss: 10.0226, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.67it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 66, Loss: 10.0167, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.76it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 67, Loss: 10.0244, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.28it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 68, Loss: 10.0178, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.67it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 69, Loss: 10.0212, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.36it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 70, Loss: 10.0203, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.76it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 71, Loss: 10.0200, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.14it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 72, Loss: 10.0211, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.50it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 73, Loss: 10.0087, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.51it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 74, Loss: 10.0328, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.50it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 75, Loss: 10.0231, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.18it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 76, Loss: 10.0307, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.79it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 77, Loss: 10.0162, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.91it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 78, Loss: 10.0129, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.39it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 79, Loss: 10.0313, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.70it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 80, Loss: 10.0216, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.97it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 81, Loss: 10.0194, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.01it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 82, Loss: 10.0252, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.39it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 83, Loss: 10.0243, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.48it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 84, Loss: 10.0227, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.65it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 85, Loss: 10.0253, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.85it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 86, Loss: 10.0277, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.14it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 87, Loss: 10.0245, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.66it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 88, Loss: 10.0243, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.73it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 89, Loss: 10.0271, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.02it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 90, Loss: 10.0222, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.25it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 91, Loss: 10.0212, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.20it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 92, Loss: 10.0319, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.80it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 93, Loss: 10.0273, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.13it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 94, Loss: 10.0138, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.17it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 95, Loss: 10.0168, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.50it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 96, Loss: 10.0279, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.37it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 97, Loss: 10.0182, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.05it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 98, Loss: 10.0268, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.59it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 99, Loss: 10.0221, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.95it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 100, Loss: 10.0153, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.31it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 101, Loss: 10.0167, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.25it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 102, Loss: 10.0222, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.93it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 103, Loss: 10.0258, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.08it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 104, Loss: 10.0335, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.62it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 105, Loss: 10.0254, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.70it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 106, Loss: 10.0289, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.19it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 107, Loss: 10.0286, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.74it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 108, Loss: 10.0224, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.96it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 109, Loss: 10.0252, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.56it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 110, Loss: 10.0269, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.49it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 111, Loss: 10.0226, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.79it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 112, Loss: 10.0268, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.57it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 113, Loss: 10.0229, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.91it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 114, Loss: 10.0123, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 115, Loss: 10.0244, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.91it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 116, Loss: 10.0183, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.19it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 117, Loss: 10.0180, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.38it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 118, Loss: 10.0114, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.17it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 119, Loss: 10.0214, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.62it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 120, Loss: 10.0202, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.08it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 121, Loss: 10.0155, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.18it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 122, Loss: 10.0273, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.84it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 123, Loss: 10.0146, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.02it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 124, Loss: 10.0142, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.54it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 125, Loss: 10.0151, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.49it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 126, Loss: 10.0210, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.15it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 127, Loss: 10.0162, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.71it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 128, Loss: 10.0162, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.86it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 129, Loss: 10.0168, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.57it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 130, Loss: 10.0299, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.01it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 131, Loss: 10.0203, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.06it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 132, Loss: 10.0291, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.26it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 133, Loss: 10.0194, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.43it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 134, Loss: 10.0313, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.86it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 135, Loss: 10.0142, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.62it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 136, Loss: 10.0194, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.81it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 137, Loss: 10.0301, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.45it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 138, Loss: 10.0199, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.94it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 139, Loss: 10.0143, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.70it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 140, Loss: 10.0250, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.38it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 141, Loss: 10.0199, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.28it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 142, Loss: 10.0220, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.94it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 143, Loss: 10.0156, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.45it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 144, Loss: 10.0299, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.67it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 145, Loss: 10.0171, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.00it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 146, Loss: 10.0169, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.01it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 147, Loss: 10.0131, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.54it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 148, Loss: 10.0246, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.13it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 149, Loss: 10.0139, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.27it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 150, Loss: 10.0309, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.44it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 151, Loss: 10.0192, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.99it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 152, Loss: 10.0216, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.22it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 153, Loss: 10.0325, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.44it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 154, Loss: 10.0226, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.50it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 155, Loss: 10.0231, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.69it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 156, Loss: 10.0238, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.42it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 157, Loss: 10.0222, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.64it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 158, Loss: 10.0218, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.08it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 159, Loss: 10.0211, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.07it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 160, Loss: 10.0336, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.81it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 161, Loss: 10.0146, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.53it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 162, Loss: 10.0218, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.44it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 163, Loss: 10.0168, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.14it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 164, Loss: 10.0255, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.81it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 165, Loss: 10.0320, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.43it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 166, Loss: 10.0090, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.29it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 167, Loss: 10.0235, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.53it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 168, Loss: 10.0147, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.10it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 169, Loss: 10.0208, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.69it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 170, Loss: 10.0297, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.71it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 171, Loss: 10.0257, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.87it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 172, Loss: 10.0074, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.28it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 173, Loss: 10.0263, Acc: 0.9923\n"
          ]
        },
        {
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.28it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 174, Loss: 10.0260, Acc: 0.9923\n"
          ]
        },
        {
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.42it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 175, Loss: 10.0045, Acc: 0.9923\n"
          ]
        },
        {
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.07it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 176, Loss: 10.0196, Acc: 0.9923\n"
          ]
        },
        {
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.18it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 177, Loss: 10.0262, Acc: 0.9923\n"
          ]
        },
        {
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.12it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 178, Loss: 10.0154, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.23it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 179, Loss: 10.0234, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.09it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 180, Loss: 10.0153, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.98it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 181, Loss: 10.0153, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.94it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 182, Loss: 10.0222, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.45it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 183, Loss: 10.0182, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.52it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 184, Loss: 10.0212, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.91it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 185, Loss: 10.0287, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.04it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 186, Loss: 10.0289, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.43it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 187, Loss: 10.0117, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.61it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 188, Loss: 10.0105, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.48it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 189, Loss: 10.0145, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.80it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 190, Loss: 10.0257, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.06it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 191, Loss: 10.0095, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.32it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 192, Loss: 10.0115, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.15it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 193, Loss: 10.0248, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.90it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 194, Loss: 10.0163, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.39it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 195, Loss: 10.0295, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.75it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 196, Loss: 10.0198, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 26.03it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 197, Loss: 10.0186, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.96it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 198, Loss: 10.0298, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 24.74it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 199, Loss: 10.0290, Acc: 0.9923\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\r  0%|          | 0/31 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/torch/utils/data/dataloader.py:481: UserWarning: This DataLoader will create 4 worker processes in total. Our suggested max number of worker in current system is 2, 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",
            "  cpuset_checked))\n",
            "100%|██████████| 31/31 [00:01<00:00, 25.07it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch: 200, Loss: 10.0269, Acc: 0.9923\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.manifold import TSNE\n",
        "import matplotlib.pyplot as plt\n"
      ],
      "metadata": {
        "id": "of_ao-C7S2E6"
      },
      "execution_count": 62,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "np.unique(data.y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6riGba0UahL0",
        "outputId": "850f04a0-1255-4985-e1ba-6d304962fdec"
      },
      "execution_count": 67,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([-775, -770, -353, -209, -183, -157, -131,  -41,  -33,  -30,   -6,\n",
              "         -3,   -2,   -1,    0,    1,    2,    4,   12,  288,  414,  590,\n",
              "        682,  914])"
            ]
          },
          "metadata": {},
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "@torch.no_grad()\n",
        "def plot_points(colors):\n",
        "    model.eval()\n",
        "    z = model(torch.arange(data.num_nodes, device=device))\n",
        "    z = TSNE(n_components=2).fit_transform(z.cpu().numpy())\n",
        "    y = data.y.cpu().numpy()\n",
        "\n",
        "    plt.figure(figsize=(8, 8))\n",
        "    for i in range(len(np.unique(data.y))):\n",
        "        plt.scatter(z[y == i, 0], z[y == i, 1], s=20, color=colors[i])\n",
        "    plt.axis('off')\n",
        "    plt.show()\n",
        "\n",
        "colors = [\n",
        "    '#ffc0cb', '#bada55', '#008080', '#420420', '#7fe5f0', '#065535',\n",
        "    '#ffd700'\n",
        "]\n",
        "plot_points(colors)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 937
        },
        "id": "2-mKWgGMSjz6",
        "outputId": "4e10c32a-93f2-4200-e311-d5c3c451056f"
      },
      "execution_count": 68,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/torch_geometric/data/storage.py:264: UserWarning: Unable to accurately infer 'num_nodes' from the attribute set '{'train_mask', 'y', 'test_mask', 'edge_index'}'. Please explicitly set 'num_nodes' as an attribute of 'data' to suppress this warning\n",
            "  \" to suppress this warning\")\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/manifold/_t_sne.py:783: FutureWarning: The default initialization in TSNE will change from 'random' to 'pca' in 1.2.\n",
            "  FutureWarning,\n",
            "/usr/local/lib/python3.7/dist-packages/sklearn/manifold/_t_sne.py:793: FutureWarning: The default learning rate in TSNE will change from 200.0 to 'auto' in 1.2.\n",
            "  FutureWarning,\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "IndexError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-68-e58e00aee9e8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     16\u001b[0m     \u001b[0;34m'#ffd700'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     17\u001b[0m ]\n\u001b[0;32m---> 18\u001b[0;31m \u001b[0mplot_points\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcolors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/torch/autograd/grad_mode.py\u001b[0m in \u001b[0;36mdecorate_context\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     26\u001b[0m         \u001b[0;32mdef\u001b[0m \u001b[0mdecorate_context\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     27\u001b[0m             \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__class__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 28\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     29\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mcast\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mF\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdecorate_context\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     30\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m<ipython-input-68-e58e00aee9e8>\u001b[0m in \u001b[0;36mplot_points\u001b[0;34m(colors)\u001b[0m\n\u001b[1;32m      8\u001b[0m     \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfigsize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m8\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m8\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m         \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscatter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mz\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0my\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mz\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0my\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0ms\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m20\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcolors\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     11\u001b[0m     \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'off'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     12\u001b[0m     \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mIndexError\u001b[0m: list index out of range"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "BSlVM-dUSzyW"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}